Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long-Term Care Hospital Prospective Payment System and Proposed Policy Changes and Fiscal Year 2020 Rates; Proposed Quality Reporting Requirements for Specific Providers; Medicare and Medicaid Promoting Interoperability Programs Proposed Requirements for Eligible Hospitals and Critical Access Hospitals
| Published date | 03 May 2019 |
| Record Number | 2019-08330 |
| Section | Proposed rules |
| Court | Centers For Medicare & Medicaid Services |
Federal Register, Volume 84 Issue 86 (Friday, May 3, 2019)
[Federal Register Volume 84, Number 86 (Friday, May 3, 2019)]
[Proposed Rules]
[Pages 19158-19677]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2019-08330]
[[Page 19157]]
Vol. 84
Friday,
No. 86
May 3, 2019
Part II
Book 2 of 2 Books
Pages 19157-19682
Department of Health and Human Services
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Centers for Medicare & Medicaid Services
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42 CFR Parts 412, 413, and 495
Medicare Program; Hospital Inpatient Prospective Payment Systems for
Acute Care Hospitals and the Long-Term Care Hospital Prospective
Payment System and Proposed Policy Changes and Fiscal Year 2020 Rates;
Proposed Quality Reporting Requirements for Specific Providers;
Medicare and Medicaid Promoting Interoperability Programs Proposed
Requirements for Eligible Hospitals and Critical Access Hospitals;
Proposed Rule
Federal Register / Vol. 84 , No. 86 / Friday, May 3, 2019 / Proposed
Rules
[[Page 19158]]
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Medicare & Medicaid Services
42 CFR Parts 412, 413, and 495
[CMS-1716-P]
RIN 0938-AT73
Medicare Program; Hospital Inpatient Prospective Payment Systems
for Acute Care Hospitals and the Long-Term Care Hospital Prospective
Payment System and Proposed Policy Changes and Fiscal Year 2020 Rates;
Proposed Quality Reporting Requirements for Specific Providers;
Medicare and Medicaid Promoting Interoperability Programs Proposed
Requirements for Eligible Hospitals and Critical Access Hospitals
AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.
ACTION: Proposed rule.
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SUMMARY: We are proposing to revise the Medicare hospital inpatient
prospective payment systems (IPPS) for operating and capital-related
costs of acute care hospitals to implement changes arising from our
continuing experience with these systems for FY 2020 and to implement
certain recent legislation. We also are proposing to make changes
relating to Medicare graduate medical education (GME) for teaching
hospitals and payments to critical access hospital (CAHs). In addition,
we are proposing to provide the market basket update that would apply
to the rate-of-increase limits for certain hospitals excluded from the
IPPS that are paid on a reasonable cost basis, subject to these limits
for FY 2020. We are proposing to update the payment policies and the
annual payment rates for the Medicare prospective payment system (PPS)
for inpatient hospital services provided by long-term care hospitals
(LTCHs) for FY 2020. In this proposed rule, we are including proposals
to address wage index disparities between high and low wage index
hospitals; to provide for an alternative IPPS new technology add-on
payment pathway for certain transformative new devices; and to revise
the calculation of the IPPS new technology add-on payment. In addition,
we are requesting public comments on the substantial clinical
improvement criterion used for evaluating applications for both the
IPPS new technology add-on payment and the OPPS transitional pass-
through payment for devices, and we discuss potential revisions that we
are considering adopting as final policies related to the substantial
clinical improvement criterion for applications received beginning in
FY 2020 for IPPS (that is, for FY 2021 and later new technology add-on
payments) and beginning in CY 2020 for the OPPS.
We are proposing to establish new requirements or revise existing
requirements for quality reporting by specific Medicare providers
(acute care hospitals, PPS-exempt cancer hospitals, and LTCHs). We also
are proposing to establish new requirements and revise existing
requirements for eligible hospitals and critical access hospitals
(CAHs) participating in the Medicare and Medicaid Promoting
Interoperability Programs. We are proposing to update policies for the
Hospital Value-Based Purchasing (VBP) Program, the Hospital
Readmissions Reduction Program, and the Hospital-Acquired Condition
(HAC) Reduction Program.
DATES: To be assured consideration, comments must be received at one of
the addresses provided in the ADDRESSES section, no later than 5 p.m.
EDT on June 24, 2019.
ADDRESSES: In commenting, please refer to file code CMS-1716-P. Because
of staff and resource limitations, we cannot accept comments by
facsimile (FAX) transmission.
Comments, including mass comment submissions, must be submitted in
one of the following three ways (please choose only one of the ways
listed):
1. Electronically. You may (and we encourage you to) submit
electronic comments on this regulation to http://www.regulations.gov.
Follow the instructions under the ``submit a comment'' tab.
2. By regular mail. You may mail written comments to the following
address ONLY: Centers for Medicare & Medicaid Services, Department of
Health and Human Services, Attention: CMS-1716-P, P.O. Box 8013,
Baltimore, MD 21244-1850.
Please allow sufficient time for mailed comments to be received
before the close of the comment period.
3. By express or overnight mail. You may send written comments via
express or overnight mail to the following address ONLY: Centers for
Medicare & Medicaid Services, Department of Health and Human Services,
Attention: CMS-1716-P, Mail Stop C4-26-05, 7500 Security Boulevard,
Baltimore, MD 21244-1850.
For information on viewing public comments, we refer readers to the
beginning of the SUPPLEMENTARY INFORMATION section.
FOR FURTHER INFORMATION CONTACT: Donald Thompson, (410) 786-4487, and
Michele Hudson, (410) 786-4487, Operating Prospective Payment, MS-DRGs,
Wage Index, New Medical Service and Technology Add-On Payments,
Hospital Geographic Reclassifications, Graduate Medical Education,
Capital Prospective Payment, Excluded Hospitals, Medicare
Disproportionate Share Hospital (DSH) Payment Adjustment, Medicare-
Dependent Small Rural Hospital (MDH) Program, Low-Volume Hospital
Payment Adjustment, and Critical Access Hospital (CAH) Issues.
Michele Hudson, (410) 786-4487, Mark Luxton, (410) 786-4530, and
Emily Lipkin, (410) 786-3633, Long-Term Care Hospital Prospective
Payment System and MS-LTC-DRG Relative Weights Issues.
Siddhartha Mazumdar, (410) 786-6673, Rural Community Hospital
Demonstration Program Issues.
Jeris Smith, (410) 786-0110, Frontier Community Health Integration
Project Demonstration Issues.
Erin Patton, (410) 786-2437, Hospital Readmissions Reduction
Program Administration Issues.
Lein Han, 410-786-0205, Hospital Readmissions Reduction Program--
Readmissions--Measures Issues.
Michael Brea, (410) 786-4961, Hospital-Acquired Condition Reduction
Program Issues.
Annese Abdullah-Mclaughlin, (410) 786-2995, Hospital-Acquired
Condition Reduction Program--Measures Issues.
Grace Snyder, (410) 786-0700 and James Poyer, (410) 786-2261,
Hospital Inpatient Quality Reporting and Hospital Value-Based
Purchasing--Program Administration, Validation, and Reconsideration
Issues.
Cindy Tourison, (410) 786-1093, Hospital Inpatient Quality
Reporting and Hospital Value-Based Purchasing--Measures Issues Except
Hospital Consumer Assessment of Healthcare Providers and Systems
Issues.
Elizabeth Goldstein, (410) 786-6665, Hospital Inpatient Quality
Reporting and Hospital Value-Based Purchasing--Hospital Consumer
Assessment of Healthcare Providers and Systems Measures Issues.
Nekeshia McInnis, (410) 786-4486 and Ronique Evans, (410) 786-1000,
PPS-Exempt Cancer Hospital Quality Reporting Issues.
Mary Pratt, (410) 786-6867, Long-Term Care Hospital Quality Data
Reporting Issues.
Elizabeth Holland, (410) 786-1309, Dylan Podson (410) 786-5031, and
Bryan Rossi (410) 786-065l, Promoting Interoperability Programs.
[[Page 19159]]
Benjamin Moll, (410) 786-4390, Provider Reimbursement Review Board
Appeals Issues.
SUPPLEMENTARY INFORMATION: Inspection of Public Comments: All comments
received before the close of the comment period are available for
viewing by the public, including any personally identifiable or
confidential business information that is included in a comment. We
post all comments received before the close of the comment period on
the following website as soon as possible after they have been
received: http://www.regulations.gov/. Follow the search instructions
on that website to view public comments.
Electronic Access
This Federal Register document is available from the Federal
Register online database through Federal Digital System (FDsys), a
service of the U.S. Government Printing Office. This database can be
accessed via the internet at: http://www.gpo.gov/fdsys.
Tables Available Through the Internet on the CMS Website
In the past, a majority of the tables referred to throughout this
preamble and in the Addendum to the proposed rule and the final rule
were published in the Federal Register as part of the annual proposed
and final rules. However, beginning in FY 2012, the majority of the
IPPS tables and LTCH PPS tables are no longer published in the Federal
Register. Instead, these tables, generally, will be available only
through the internet. The IPPS tables for this FY 2020 proposed rule
are available through the internet on the CMS website at: http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. Click on the link on the left side of the
screen titled, ``FY 2020 IPPS Proposed Rule Home Page'' or ``Acute
Inpatient--Files for Download.'' The LTCH PPS tables for this FY 2020
proposed rule are available through the internet on the CMS website at:
http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/LongTermCareHospitalPPS/index.html under the list item for Regulation
Number CMS-1716-P. For further details on the contents of the tables
referenced in this proposed rule, we refer readers to section VI. of
the Addendum to this proposed rule.
Readers who experience any problems accessing any of the tables
that are posted on the CMS websites identified above should contact
Michael Treitel at (410) 786-4552.
Table of Contents
I. Executive Summary and Background
A. Executive Summary
B. Background Summary
C. Summary of Provisions of Recent Legislation Implemented in
This Proposed Rule
D. Summary of the Provisions of This Proposed Rule
E. Advancing Health Information Exchange
II. Proposed Changes to Medicare Severity Diagnosis-Related Group
(MS-DRG) Classifications and Relative Weights
A. Background
B. MS-DRG Reclassifications
C. Adoption of the MS-DRGs in FY 2008
D. Proposed FY 2020 MS-DRG Documentation and Coding Adjustment
E. Refinement of the MS-DRG Relative Weight Calculation
F. Proposed Changes to Specific MS-DRG Classifications
G. Recalibration of the Proposed FY 2020 MS-DRG Relative Weights
H. Proposed Add-On Payments for New Services and Technologies
for FY 2020
III. Proposed Changes to the Hospital Wage Index for Acute Care
Hospitals
A. Background
B. Worksheet S-3 Wage Data for the Proposed FY 2020 Wage Index
C. Verification of Worksheet S-3 Wage Data
D. Method for Computing the Proposed FY 2020 Unadjusted Wage
Index
E. Proposed Occupational Mix Adjustment to the Proposed FY 2020
Wage Index
F. Analysis and Implementation of the Proposed Occupational Mix
Adjustment and the Proposed FY 2020 Occupational Mix Adjusted Wage
Index
G. Proposed Application of the Rural Floor, Expired Imputed
Floor Policy, and Proposed Application of the State Frontier Floor
H. Proposed FY 2020 Wage Index Tables
I. Proposed Revisions to the Wage Index Based on Hospital
Redesignations and Reclassifications
J. Proposed Out-Migration Adjustment Based on Commuting Patterns
of Hospital Employees
K. Reclassification from Urban to Rural Under Section
1886(d)(8)(E) of the Act Implemented at 42 CFR 412.103
L. Process for Requests for Wage Index Data Corrections
M. Proposed Labor-Related Share for the FY 2020 Wage Index
N. Proposals to Address Wage Index Disparities Between High and
Low Wage Index Hospitals
IV. Other Decisions and Proposed Changes to the IPPS for Operating
Costs
A. Proposed Changes to MS-DRGs Subject to Postacute Care
Transfer and MS-DRG Special Payment Policies
B. Proposed Changes in the Inpatient Hospital Updates for FY
2020 (Sec. 412.64(d))
C. Proposed Rural Referral Centers (RRCs) Annual Updates to
Case-Mix Index and Discharge Criteria (Sec. 412.96)
D. Proposed Payment Adjustment for Low-Volume Hospitals (Sec.
412.101)
E. Proposed Indirect Medical Education (IME) Payment Adjustment
(Sec. 412.105)
F. Proposed Payment Adjustment for Medicare Disproportionate
Share Hospitals (DSHs) for FY 2020 (Sec. 412.106)
G. Hospital Readmissions Reduction Program: Proposed Updates and
Changes (Sec. Sec. 412.150 through 412.154)
H. Hospital Value-Based Purchasing (VBP) Program: Proposed
Policy Changes
I. Hospital-Acquired Condition (HAC) Reduction Program
J. Payments for Indirect and Direct Graduate Medical Education
Costs (Sec. Sec. 412.105 and 413.75 through 413.83)
K. Rural Community Hospital Demonstration Program
V. Proposed Changes to the IPPS for Capital-Related Costs
A. Overview
B. Additional Provisions
C. Proposed Annual Update for FY 2020
VI. Proposed Changes for Hospitals Excluded From the IPPS
A. Proposed Rate-of-Increase in Payments to Excluded Hospitals
for FY 2020
B. Request for Public Comments on Methodologies and Requirements
for Adjustments to Rate-of-Increase Ceiling
C. Critical Access Hospitals (CAHs)
VII. Proposed Changes to the Long-Term Care Hospital Prospective
Payment System (LTCH PPS) for FY 2019
A. Background of the LTCH PPS
B. Proposed Medicare Severity Long-Term Care Diagnosis-Related
Group (MS-LTC-DRG) Classifications and Relative Weights for FY 2020
C. Proposed Payment Adjustment for LTCH Discharges That Do Not
Meet the Applicable Discharge Payment Percentage
D. Proposed Changes to the LTCH PPS Payment Rates and Other
Proposed Changes to the LTCH PPS for FY 2020
VIII. Proposed Quality Data Reporting Requirements for Specific
Providers and Suppliers
A. Hospital Inpatient Quality Reporting (IQR) Program
B. PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) Program
C. Long-Term Care Hospital Quality Reporting Program (LTCH QRP)
D. Proposed Changes to the Medicare and Medicaid Promoting
Interoperability Programs
IX. MedPAC Recommendations
X. Other Required Information
A. Publicly Available Data
B. Collection of Information Requirements
C. Response to Public Comments
XI. Provider Reimbursement Review Board (PRRB) Appeals
Regulation Text
Addendum--Proposed Schedule of Standardized Amounts, Update Factors,
and Rate-of-Increase Percentages Effective With Cost Reporting Periods
Beginning on or After October 1, 2019 and Proposed Payment Rates for
LTCHs Effective With Discharges Occurring on or After October 1, 2019
I. Summary and Background
II. Proposed Changes to the Prospective Payment Rates for Hospital
Inpatient
[[Page 19160]]
Operating Costs for Acute Care Hospitals for FY 2020
A. Calculation of the Proposed Adjusted Standardized Amount
B. Proposed Adjustments for Area Wage Levels and Cost-of-Living
C. Calculation of the Proposed Prospective Payment Rates
III. Proposed Changes to Payment Rates for Acute Care Hospital
Inpatient Capital-Related Costs for FY 2020
A. Determination of Proposed Federal Hospital Inpatient Capital-
Related Prospective Payment Rate Update
B. Calculation of the Proposed Inpatient Capital-Related
Prospective Payments for FY 2020
C. Capital Input Price Index
IV. Proposed Changes to Payment Rates for Excluded Hospitals: Rate-
of-Increase Percentages for FY 2020
V. Proposed Updates to the Payment Rates for the LTCH PPS for FY
2020
A. Proposed LTCH PPS Standard Federal Payment Rate for FY 2020
B. Proposed Adjustment for Area Wage Levels Under the LTCH PPS
for FY 2020
C. Proposed LTCH PPS Cost-of-Living Adjustment (COLA) for LTCHs
Located in Alaska and Hawaii
D. Proposed Adjustment for LTCH PPS High-Cost Outlier (HCO)
Cases
E. Proposed Update to the IPPS Comparable/Equivalent Amounts to
Reflect the Statutory Changes to the IPPS DSH Payment Adjustment
Methodology
F. Computing the Proposed Adjusted LTCH PPS Federal Prospective
Payments for FY 2020
VI. Tables Referenced in This Proposed Rule and Available Through
the Internet on the CMS Website
Appendix A--Economic Analyses
I. Regulatory Impact Analysis
A. Statement of Need
B. Overall Impact
C. Objectives of the IPPS and the LTCH PPS
D. Limitations of Our Analysis
E. Hospitals Included in and Excluded From the IPPS
F. Effects on Hospitals and Hospital Units Excluded From the
IPPS
G. Quantitative Effects of the Proposed Policy Changes Under the
IPPS for Operating Costs
H. Effects of Other Proposed Policy Changes
I. Effects of Proposed Changes in the Capital IPPS
J. Effects of Proposed Payment Rate Changes and Policy Changes
Under the LTCH PPS
K. Effects of Proposed Requirements for Hospital Inpatient
Quality Reporting (IQR) Program
L. Effects of Proposed Requirements for the PPS-Exempt Cancer
Hospital Quality Reporting (PCHQR) Program
M. Effects of Proposed Requirements for the Long-Term Care
Hospital Quality Reporting Program (LTCH QRP)
N. Effects of Proposed Requirements Regarding the Medicare
Promoting Interoperability Program
O. Alternatives Considered
P. Reducing Regulation and Controlling Regulatory Costs
Q. Overall Conclusion
R. Regulatory Review Costs
II. Accounting Statements and Tables
A. Acute Care Hospitals
B. LTCHs
III. Regulatory Flexibility Act (RFA) Analysis
IV. Impact on Small Rural Hospitals
V. Unfunded Mandate Reform Act (UMRA) Analysis
VI. Executive Order 13175
VII. Executive Order 12866
Appendix B: Recommendation of Update Factors for Operating Cost Rates
of Payment for Inpatient Hospital Services
I. Background
II. Proposed Inpatient Hospital Update for FY 2020
A. Proposed FY 2020 Inpatient Hospital Update
B. Proposed Update for SCHs and MDHs for FY 2020
C. Proposed FY 2020 Puerto Rico Hospital Update
D. Proposed Update for Hospitals Excluded From the IPPS
E. Proposed Update for LTCHs for FY 2020
III. Secretary's Recommendation
IV. MedPAC Recommendation for Assessing Payment Adequacy and
Updating Payments in Traditional Medicare
I. Executive Summary and Background
A. Executive Summary
1. Purpose and Legal Authority
This proposed rule would make payment and policy changes under the
Medicare inpatient prospective payment systems (IPPS) for operating and
capital-related costs of acute care hospitals as well as for certain
hospitals and hospital units excluded from the IPPS. In addition, it
would make payment and policy changes for inpatient hospital services
provided by long-term care hospitals (LTCHs) under the long-term care
hospital prospective payment system (LTCH PPS). This proposed rule also
would make policy changes to programs associated with Medicare IPPS
hospitals, IPPS-excluded hospitals, and LTCHs. In this proposed rule,
we are including proposals to address wage index disparities between
high and low wage index hospitals; to provide for an alternative IPPS
new technology add-on payment pathway for certain transformative new
devices; and to revise the calculation of the IPPS new technology add-
on payment. In addition, we are requesting public comments on the
substantial clinical improvement criterion for evaluating applications
for both the IPPS new technology add-on payment and the OPPS
transitional pass-through payment for devices, and we discuss potential
revisions that we are considering adopting as final policies related to
the substantial clinical improvement criterion for FY 2020 for IPPS and
CY 2020 for the OPPS.
We are proposing to establish new requirements and revise existing
requirements for quality reporting by specific providers (acute care
hospitals, PPS-exempt cancer hospitals, and LTCHs) that are
participating in Medicare. We also are proposing to establish new
requirements and revise existing requirements for eligible hospitals
and CAHs participating in the Medicare and Medicaid Promoting
Interoperability Programs. We are proposing to update policies for the
Hospital Value-Based Purchasing (VBP) Program, the Hospital
Readmissions Reduction Program, and the Hospital-Acquired Condition
(HAC) Reduction Program.
Under various statutory authorities, we are proposing to make
changes to the Medicare IPPS, to the LTCH PPS, and to other related
payment methodologies and programs for FY 2020 and subsequent fiscal
years. These statutory authorities include, but are not limited to, the
following:
Section 1886(d) of the Social Security Act (the Act),
which sets forth a system of payment for the operating costs of acute
care hospital inpatient stays under Medicare Part A (Hospital
Insurance) based on prospectively set rates. Section 1886(g) of the Act
requires that, instead of paying for capital-related costs of inpatient
hospital services on a reasonable cost basis, the Secretary use a
prospective payment system (PPS).
Section 1886(d)(1)(B) of the Act, which specifies that
certain hospitals and hospital units are excluded from the IPPS. These
hospitals and units are: Rehabilitation hospitals and units; LTCHs;
psychiatric hospitals and units; children's hospitals; cancer
hospitals; extended neoplastic disease care hospitals, and hospitals
located outside the 50 States, the District of Columbia, and Puerto
Rico (that is, hospitals located in the U.S. Virgin Islands, Guam, the
Northern Mariana Islands, and American Samoa). Religious nonmedical
health care institutions (RNHCIs) are also excluded from the IPPS.
Sections 123(a) and (c) of the BBRA (Pub. L. 106-113) and
section 307(b)(1) of the BIPA (Pub. L. 106-554) (as codified under
section 1886(m)(1) of the Act), which provide for the development and
implementation of a prospective payment system for payment for
inpatient hospital services of LTCHs described in section
1886(d)(1)(B)(iv) of the Act.
[[Page 19161]]
Sections 1814(l), 1820, and 1834(g) of the Act, which
specify that payments are made to critical access hospitals (CAHs)
(that is, rural hospitals or facilities that meet certain statutory
requirements) for inpatient and outpatient services and that these
payments are generally based on 101 percent of reasonable cost.
Section 1866(k) of the Act, which establishes a quality
reporting program for hospitals described in section 1886(d)(1)(B)(v)
of the Act, referred to as ``PPS-exempt cancer hospitals.''
Section 1886(a)(4) of the Act, which specifies that costs
of approved educational activities are excluded from the operating
costs of inpatient hospital services. Hospitals with approved graduate
medical education (GME) programs are paid for the direct costs of GME
in accordance with section 1886(h) of the Act.
Section 1886(b)(3)(B)(viii) of the Act, which requires the
Secretary to reduce the applicable percentage increase that would
otherwise apply to the standardized amount applicable to a subsection
(d) hospital for discharges occurring in a fiscal year if the hospital
does not submit data on measures in a form and manner, and at a time,
specified by the Secretary.
Section 1886(o) of the Act, which requires the Secretary
to establish a Hospital Value-Based Purchasing (VBP) Program, under
which value-based incentive payments are made in a fiscal year to
hospitals meeting performance standards established for a performance
period for such fiscal year.
Section 1886(p) of the Act, which establishes a Hospital-
Acquired Condition (HAC) Reduction Program, under which payments to
applicable hospitals are adjusted to provide an incentive to reduce
hospital-acquired conditions.
Section 1886(q) of the Act, as amended by section 15002 of
the 21st Century Cures Act, which establishes the Hospital Readmissions
Reduction Program. Under the program, payments for discharges from an
applicable hospital as defined under section 1886(d) of the Act will be
reduced to account for certain excess readmissions. Section 15002 of
the 21st Century Cures Act requires the Secretary to compare hospitals
with respect to the number of their Medicare-Medicaid dual-eligible
beneficiaries (dual-eligibles) in determining the extent of excess
readmissions.
Section 1886(r) of the Act, as added by section 3133 of
the Affordable Care Act, which provides for a reduction to
disproportionate share hospital (DSH) payments under section
1886(d)(5)(F) of the Act and for a new uncompensated care payment to
eligible hospitals. Specifically, section 1886(r) of the Act requires
that, for fiscal year 2014 and each subsequent fiscal year, subsection
(d) hospitals that would otherwise receive a DSH payment made under
section 1886(d)(5)(F) of the Act will receive two separate payments:
(1) 25 percent of the amount they previously would have received under
section 1886(d)(5)(F) of the Act for DSH (``the empirically justified
amount''), and (2) an additional payment for the DSH hospital's
proportion of uncompensated care, determined as the product of three
factors. These three factors are: (1) 75 percent of the payments that
would otherwise be made under section 1886(d)(5)(F) of the Act; (2) 1
minus the percent change in the percent of individuals who are
uninsured; and (3) a hospital's uncompensated care amount relative to
the uncompensated care amount of all DSH hospitals expressed as a
percentage.
Section 1886(m)(6) of the Act, as added by section
1206(a)(1) of the Pathway for Sustainable Growth Rate (SGR) Reform Act
of 2013 (Pub. L. 113-67) and amended by section 51005(a) of the
Bipartisan Budget Act of 2018 (Pub. L. 115-123), which provided for the
establishment of site neutral payment rate criteria under the LTCH PPS,
with implementation beginning in FY 2016, and provides for a 4-year
transitional blended payment rate for discharges occurring in LTCH cost
reporting periods beginning in FYs 2016 through 2019. Section 51005(b)
of the Bipartisan Budget Act of 2018 amended section 1886(m)(6)(B) by
adding new clause (iv), which specifies that the IPPS comparable amount
defined in clause (ii)(I) shall be reduced by 4.6 percent for FYs 2018
through 2026.
Section 1886(m)(5)(D)(iv) of the Act, as added by section
1206(c) of the Pathway for Sustainable Growth Rate (SGR) Reform Act of
2013 (Pub. L. 113-67), which provides for the establishment of a
functional status quality measure in the LTCH QRP for change in
mobility among inpatients requiring ventilator support.
Section 1899B of the Act, as added by section 2(a) of the
Improving Medicare Post-Acute Care Transformation Act of 2014 (IMPACT
Act) (Pub. L. 113-185), which provides for the establishment of
standardized data reporting for certain post-acute care providers,
including LTCHs.
2. Summary of the Major Provisions
Below we provide a summary of the major provisions in this proposed
rule. In general, these major provisions are being proposed as part of
the annual update to the payment policies and payment rates, consistent
with the applicable statutory provisions. A general summary of the
proposed changes in this proposed rule is presented in section I.D. of
the preamble of this proposed rule.
a. Proposed MS-DRG Documentation and Coding Adjustment
Section 631 of the American Taxpayer Relief Act of 2012 (ATRA, Pub.
L. 112-240) amended section 7(b)(1)(B) of Public Law 110-90 to require
the Secretary to make a recoupment adjustment to the standardized
amount of Medicare payments to acute care hospitals to account for
changes in MS-DRG documentation and coding that do not reflect real
changes in case-mix, totaling $11 billion over a 4-year period of FYs
2014, 2015, 2016, and 2017. The FY 2014 through FY 2017 adjustments
represented the amount of the increase in aggregate payments as a
result of not completing the prospective adjustment authorized under
section 7(b)(1)(A) of Public Law 110-90 until FY 2013. Prior to the
ATRA, this amount could not have been recovered under Public Law 110
90. Section 414 of the Medicare Access and CHIP Reauthorization Act of
2015 (MACRA) (Pub. L. 114-10) replaced the single positive adjustment
we intended to make in FY 2018 with a 0.5 percent positive adjustment
to the standardized amount of Medicare payments to acute care hospitals
for FYs 2018 through 2023. (The FY 2018 adjustment was subsequently
adjusted to 0.4588 percent by section 15005 of the 21st Century Cures
Act.) Therefore, for FY 2020, we are proposing to make an adjustment of
+ 0.5 percent to the standardized amount.
b. Request for Information on the New Technology Add-On Payment and
Transitional Device Pass-Through Payment Substantial Clinical
Improvement Criterion and Discussion of Potential Revisions to the New
Technology Add-On Payment and Transitional Device Pass-Through Payment
Substantial Clinical Improvement Criterion
The substantial clinical improvement criterion that is used to
evaluate a technology that is the subject of an application for the new
technology add-on payment under the IPPS or an application for the
transitional pass-through payment for additional costs of innovative
devices under the OPPS is the subject of the request for information
and the discussion of potential revisions included in this proposed
rule.
[[Page 19162]]
We understand that greater clarity regarding what would
substantiate the requirements of this criterion would help the public,
including innovators, better understand how CMS evaluates new
technology applications for add-on payments and provide greater
predictability about which applications will meet the criterion for
substantial clinical improvement. We are considering potential
revisions to the substantial clinical improvement criterion under the
IPPS new technology add-on payment policy and the OPPS transitional
pass-through payment policy for devices policy, and are seeking public
comments on the type of additional detail and guidance that the public
and applicants for new technology add-on payments would find useful.
The comments we receive in response to those general questions will
inform future rulemaking after the FY 2020 IPPS/LTCH PPS final rule.
This request for public comments is intended to be broad in scope and
provide a foundation for potential rulemaking in future years.
In addition to this broad request for public comments for potential
rulemaking in future years, in order to respond to stakeholder feedback
requesting greater understanding of CMS' approach to evaluating
substantial clinical improvement, we are soliciting public comments on
specific changes or clarifications to the IPPS and OPPS substantial
clinical improvement criterion that CMS might consider making in the FY
2020 IPPS/LTCH PPS final rule for applications received beginning in FY
2020 for the IPPS and CY 2020 for the OPPS to provide greater clarity
and predictability.
c. Proposed Alternative Inpatient New Technology Add-On Payment Pathway
for Transformative New Devices
After consideration of the issues discussed in section III.H.8. of
the preamble of this proposed rule relating to the Food and Drug
Administration's (FDA's) expedited programs, and consistent with the
Administration's commitment to addressing barriers to health care
innovation and ensuring that Medicare beneficiaries have access to
critical and life-saving new cures and technologies that improve
beneficiary health outcomes, we concluded that it would be appropriate
to develop an alternative pathway for the inpatient new technology add-
on payment for transformative medical devices. In situations where a
new medical device is part of the FDA's Breakthrough Devices Program
and has received FDA marketing authorization (that is, the device has
received pre-market approval (PMA); 510(k) clearance; or the granting
of a De Novo classification request), we are proposing an alternative
inpatient new technology add-on payment pathway to facilitate access to
this technology for Medicare beneficiaries.
Specifically, we are proposing that, for applications received for
IPPS new technology add-on payments for FY 2021 and subsequent fiscal
years, if a medical device is part of the FDA's Breakthrough Devices
Program and received FDA marketing authorization, such a device would
be considered new and not substantially similar to an existing
technology for purposes of new technology add-on payment under the
IPPS. In light of the criteria applied under the FDA's Breakthrough
Devices Program, and because the technology may not have a sufficient
evidence base to demonstrate substantial clinical improvement at the
time of FDA marketing authorization, we also are proposing that the
medical device would not need to meet the requirement under 42 CFR
412.87(b)(1) that it represent an advance that substantially improves,
relative to technologies previously available, the diagnosis or
treatment of Medicare beneficiaries.
d. Proposed Revision of the Calculation of the Inpatient Hospital New
Technology Add-On Payment
The current calculation of the new technology add-on payment is
based on the cost to hospitals for the new medical service or
technology. Under Sec. 412.88, if the costs of the discharge
(determined by applying cost-to-charge ratios (CCRs) as described in
Sec. 412.84(h)) exceed the full DRG payment (including payments for
IME and DSH, but excluding outlier payments), Medicare will make an
add-on payment equal to the lesser of: (1) 50 percent of the costs of
the new medical service or technology; or (2) 50 percent of the amount
by which the costs of the case exceed the standard DRG payment. Unless
the discharge qualifies for an outlier payment, the additional Medicare
payment is limited to the full MS-DRG payment plus 50 percent of the
estimated costs of the new technology or medical service.
After consideration of the concerns raised by commenters and other
stakeholders, we agree that there may be merit to the recommendations
to increase the maximum add-on amount, and that capping the add-on
payment amount at 50 percent could, in some cases, no longer provide a
sufficient incentive for the use of new technology. To address this
issue, we believe it would be appropriate to modify the current payment
mechanism to increase the amount of the maximum add-on payment amount
to 65 percent. Therefore, we are proposing that, beginning with
discharges occurring on or after October 1, 2019, if the costs of a
discharge involving a new medical service or technology exceed the full
DRG payment (including payments for IME and DSH, but excluding outlier
payments), Medicare would make an add-on payment equal to the lesser
of: (1) 65 percent of the costs of the new medical service or
technology; or (2) 65 percent of the amount by which the costs of the
case exceed the standard DRG payment.
e. Proposals To Address Wage Index Disparities Between High and Low
Wage Index Hospitals
In the FY 2019 IPPS/LTCH PPS proposed rule (83 FR 20372), we
invited the public to submit further comments, suggestions, and
recommendations for regulatory and policy changes to the Medicare wage
index. Many of the responses received from this request for information
(RFI) reflect a common concern that the current wage index system
perpetuates and exacerbates the disparities between high and low wage
index hospitals. Many respondents also expressed concern that the
calculation of the rural floor has allowed a limited number of States
to manipulate the wage index system to achieve higher wages for many
urban hospitals in those States at the expense of hospitals in other
States, which also contributes to wage index disparities.
To help mitigate these wage index disparities, including those
resulting from the inclusion of hospitals with rural reclassifications
under 42 CFR 412.103 in the rural floor, we are proposing to reduce the
disparity between high and low wage index hospitals by increasing the
wage index values for certain hospitals with low wage index values and
decreasing the wage index values for certain hospitals with high wage
index values for budget neutrality purposes, as well as changing the
calculation of the rural floor. We also are proposing a transition for
hospitals experiencing significant decreases in their wage index values
as a result of these proposed changes. We are proposing to make these
changes in a budget neutral manner.
In this proposed rule, we are proposing to increase the wage index
for hospitals with a wage index value below the 25th percentile wage
index value for a fiscal year by half the difference between the
otherwise applicable final wage index value for a year for that
hospital and the 25th percentile wage index value for that year across
all hospitals. Furthermore, we are
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proposing that this policy would be effective for at least 4 years,
beginning in FY 2020, in order to allow employee compensation increases
implemented by these hospitals sufficient time to be reflected in the
wage index calculation. Under our proposal, in order to offset the
estimated increase in IPPS payments to hospitals with wage index values
below the 25th percentile wage index value, we are proposing to
decrease the wage index values for certain hospitals with high wage
index values (that is, hospitals with wage index values above the 75th
percentile wage index value), but preserve the rank order among those
values.
In addition, we are proposing to remove urban to rural
reclassifications from the calculation of the rural floor, such that,
beginning in FY 2020, the rural floor would be calculated without
including the wage data of hospitals that have reclassified as rural
under section 1886(d)(8)(E) of the Act (as implemented in the
regulations at Sec. 412.103). Also, for the purposes of applying the
provisions of section 1886(d)(8)(C)(iii) of the Act, we are proposing
to remove urban to rural reclassifications from the calculation of
``the wage index for rural areas in the State in which the county is
located'' as referred to in the statute.
Lastly, for FY 2020, we are proposing to place a 5-percent cap on
any decrease in a hospital's wage index from the hospital's final wage
index in FY 2019. We are proposing to apply a budget neutrality
adjustment to the standardized amount so that our proposed transition
for hospitals that could be negatively impacted is implemented in a
budget neutral manner.
f. Proposed DSH Payment Adjustment and Additional Payment for
Uncompensated Care
Section 3133 of the Affordable Care Act modified the Medicare
disproportionate share hospital (DSH) payment methodology beginning in
FY 2014. Under section 1886(r) of the Act, which was added by section
3133 of the Affordable Care Act, starting in FY 2014, DSHs receive 25
percent of the amount they previously would have received under the
statutory formula for Medicare DSH payments in section 1886(d)(5)(F) of
the Act. The remaining amount, equal to 75 percent of the amount that
otherwise would have been paid as Medicare DSH payments, is paid as
additional payments after the amount is reduced for changes in the
percentage of individuals that are uninsured. Each Medicare DSH will
receive an additional payment based on its share of the total amount of
uncompensated care for all Medicare DSHs for a given time period.
In this FY 2020 IPPS/LTCH PPS proposed rule, we are proposing to
update our estimates of the three factors used to determine
uncompensated care payments for FY 2020. We are proposing to continue
to use uninsured estimates produced by CMS' Office of the Actuary
(OACT) as part of the development of the National Health Expenditure
Accounts (NHEA) in the calculation of Factor 2. We also are proposing
to use a single year of data on uncompensated care costs from Worksheet
S-10 for FY 2015 to determine Factor 3 for FY 2020. We also are seeking
public comments on whether we should, due to changes in the reporting
instructions that became effective for FY 2017, alternatively use a
single year of Worksheet S-10 data from the FY 2017 cost reports,
instead of the FY 2015 Worksheet S-10 data, to calculate Factor 3 for
FY 2020. In addition, we are proposing to continue to use only data
regarding low-income insured days for FY 2013 to determine the amount
of uncompensated care payments for Puerto Rico hospitals, and Indian
Health Service and Tribal hospitals. We are not proposing specific
Factor 3 polices for all-inclusive rate providers for FY 2020. In this
proposed rule, we also are proposing to continue to use the following
established policies: (1) For providers with multiple cost reports,
beginning in the same fiscal year, to use the longest cost report and
annualize Medicaid data and uncompensated care data if a hospital's
cost report does not equal 12 months of data; (2) in the rare case
where a provider has multiple cost reports beginning in the same fiscal
year, but one report also spans the entirety of the following fiscal
year, such that the hospital has no cost report for that fiscal year,
to use the cost report that spans both fiscal years for the latter
fiscal year; and (3) to apply statistical trim methodologies to
potentially aberrant cost-to-charge ratios (CCRs) and potentially
aberrant uncompensated care costs reported on the Worksheet S-10.
g. Proposed Changes to the LTCH PPS
In this proposed rule, we set forth proposed changes to the LTCH
PPS Federal payment rates, factors, and other payment rate policies
under the LTCH PPS for FY 2020. We also are proposing the payment
adjustment for LTCH discharges when the LTCH does not meet the
applicable discharge payment percentage and a proposed reinstatement
process, as required by section 1886(m)(6)(C) of the Act. An LTCH would
be subject to this payment adjustment if, for cost reporting periods
beginning in FY 2020 and subsequent fiscal years, the LTCH's percentage
of Medicare discharges that meet the criteria for exclusion from the
site neutral payment rate (that is, discharges paid the LTCH PPS
standard Federal payment rate) of its total number of Medicare FFS
discharges paid under the LTCH PPS during the cost reporting period is
not at least 50 percent.
h. Reduction of Hospital Payments for Excess Readmissions
We are proposing to make changes to policies for the Hospital
Readmissions Reduction Program, which was established under section
1886(q) of the Act, as amended by section 15002 of the 21st Century
Cures Act. The Hospital Readmissions Reduction Program requires a
reduction to a hospital's base operating DRG payment to account for
excess readmissions of selected applicable conditions. For FY 2017 and
subsequent years, the reduction is based on a hospital's risk-adjusted
readmission rate during a 3-year period for acute myocardial infarction
(AMI), heart failure (HF), pneumonia, chronic obstructive pulmonary
disease (COPD), elective primary total hip arthroplasty/total knee
arthroplasty (THA/TKA), and coronary artery bypass graft (CABG)
surgery. In this proposed rule, we are proposing the following
policies: (1) A measure removal policy that aligns with the removal
factor policies previously adopted in other quality reporting and
quality payment programs; (2) an update to the Program's definition of
``dual-eligible'' beginning with the FY 2021 program year to allow for
a 1-month lookback period in data sourced from the State Medicare
Modernization Act (MMA) files to determine dual-eligible status for
beneficiaries who die in the month of discharge; (3) a subregulatory
process to address any potential future nonsubstantive changes to the
payment adjustment factor components; and (4) an update to the
Program's regulations at 42 CFR 412.152 and 412.154 to reflect proposed
policies and to codify additional previously finalized policies.
i. Hospital Value-Based Purchasing (VBP) Program
Section 1886(o) of the Act requires the Secretary to establish a
Hospital VBP Program under which value-based incentive payments are
made in a fiscal year to hospitals based on their performance on
measures established for a performance period for such fiscal year. In
this proposed rule, we are proposing that the Hospital VBP
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Program will use the same data used by the HAC Reduction Program for
purposes of calculating the Centers for Disease Control and Prevention
(CDC) National Health Safety Network (NHSN) Healthcare-Associated
Infection (HAI) measures beginning with CY 2020 data collection, when
the Hospital IQR Program will no longer collect data on those measures,
and will rely on HAC Reduction Program validation to ensure the
accuracy of CDC NHSN HAI measure data used in the Hospital VBP Program.
We also are newly establishing certain performance standards.
j. Hospital-Acquired Condition (HAC) Reduction Program
Section 1886(p) of the Act establishes an incentive to hospitals to
reduce the incidence of hospital-acquired conditions by requiring the
Secretary to make an adjustment to payments to applicable hospitals
effective for discharges beginning on October 1, 2014. This 1-percent
payment reduction applies to hospitals that rank in the worst-
performing quartile (25 percent) of all applicable hospitals, relative
to the national average, of conditions acquired during the applicable
period and on all of the hospital's discharges for the specified fiscal
year. As part of our agency-wide Patients over Paperwork and Meaningful
Measures Initiatives, discussed in section I.A.2. of the FY 2019 IPPS/
LTCH PPS final rule (83 FR 41147 and 41148), we are proposing to: (1)
Adopt a measure removal policy that aligns with the removal factor
policies previously adopted in other quality reporting and quality
payment programs; (2) clarify administrative policies for validation of
the CDC NHSN HAI measures; (3) adopt the data collection periods for
the FY 2022 program year; and (4) update 42 CFR 412.172(f) to reflect
policies finalized in the FY 2019 IPPS/LTCH PPS final rule.
k. Hospital Inpatient Quality Reporting (IQR) Program
Under section 1886(b)(3)(B)(viii) of the Act, subsection (d)
hospitals are required to report data on measures selected by the
Secretary for a fiscal year in order to receive the full annual
percentage increase that would otherwise apply to the standardized
amount applicable to discharges occurring in that fiscal year.
In this proposed rule, we are proposing to make several changes. We
are proposing to: (1) Adopt two opioid-related eCQMs (Safe Use of
Opioids--Concurrent Prescribing eCQM (NQF #3316e) and Hospital Harm--
Opioid-Related Adverse Events eCQM) beginning with the CY 2021
reporting period/FY 2023 payment determination; (2) adopt the Hybrid
Hospital-Wide All-Cause Readmission (Hybrid HWR) measure (NQF #2879) in
a stepwise fashion, beginning with two voluntary reporting periods
which would run from July 1, 2021 through June 30, 2022, and from July
1, 2022 through June 30, 2023, before requiring reporting of the
measure for the reporting period that would run from July 1, 2023
through June 30, 2024, impacting the FY 2026 payment determination and
for subsequent years; and (3) remove the Claims-Based Hospital-Wide
All-Cause Unplanned Readmission Measure (NQF #1789) (HWR claims-only
measure) beginning with the FY 2026 payment determination. We also are
proposing reporting and submission requirements for eCQMs, including
proposals to: (1) Extend current eCQM reporting and submission
requirements for both the CY 2020 reporting period/FY 2022 payment
determination and CY 2021 reporting period/FY 2023 payment
determination; (2) change eCQM reporting and submission requirements
for the CY 2022 reporting period/FY 2024 payment determination, such
that hospitals would be required to report one, self-selected calendar
quarter of data for three self-selected eCQMs and the proposed Safe Use
of Opioids--Concurrent Prescribing eCQM (NQF #3316e), for a total of
four eCQMs; and (3) continue requiring that EHRs be certified to all
available eCQMs used in the Hospital IQR Program for the CY 2020
reporting period/FY 2022 payment determination and subsequent years.
These proposals are in alignment with proposals under the Promoting
Interoperability Program. We also are proposing reporting and
submission requirements for the Hybrid HWR measure. In addition, we are
seeking public comments on three measures for potential future
inclusion in the Hospital IQR Program.
l. Long-Term Care Hospital Quality Reporting Program (LTCH QRP)
The LTCH QRP is authorized by section 1886(m)(5) of the Act and
applies to all hospitals certified by Medicare as long-term care
hospitals (LTCHs). Under the LTCH QRP, the Secretary must reduce by 2
percentage points the annual update to the LTCH PPS standard Federal
rate for discharges for an LTCH during a fiscal year if the LTCH fails
to submit data in accordance with the LTCH QRP requirements specified
for that fiscal year. As discussed in section VIII.C. of the preamble
of this proposed rule, we are proposing to adopt two measures that meet
the requirements of section 1899B(c)(1)(E) of the Act, modify an
existing measure, and adopt new standardized patient assessment data
elements that satisfy section 1899B(b) of the Act. We also are
proposing to move the implementation date of the LTCH Continuity
Assessment Record and Evaluation Data Set (LTCH CARE Data Set or LCDS)
from April to October to align with other post-acute care programs
beginning October 1, 2020. Lastly, we are proposing updates related to
the system used for the submission of data and related regulations.
m. Medicare and Medicaid Promoting Interoperability Programs
For purposes of an increased level of stability, reducing the
burden on eligible hospitals and CAHs, and clarifying certain existing
policies, we are proposing several changes to the Medicare Promoting
Interoperability Program. Specifically, we are proposing to: (1)
Eliminate requirement that, for the FY 2020 payment adjustment year,
for an eligible hospital that has not successfully demonstrated it is a
meaningful EHR user in a prior year, the EHR reporting period in CY
2019 must end before and the eligible hospital must successfully
register for and attest to meaningful use no later than the October 1,
2019 deadline; (2) establish an EHR reporting period of a minimum of
any continuous 90-day period in CY 2021 for new and returning
participants (eligible hospitals and CAHs) in the Medicare Promoting
Interoperability Program attesting to CMS; (3) require that the
Medicare Promoting Interoperability Program measure actions must occur
within the EHR reporting period beginning with the EHR reporting period
in CY 2020; (4) revise the Query of PDMP measure to make it an optional
measure worth 5 bonus points in CY 2020, remove the exclusions
associated with this measure in CY 2020, require a yes/no response
instead of a numerator and denominator for CY 2019 and CY 2020, and
clearly state our intended policy that the measure is worth a full 5
bonus points in CY 2019 and CY 2020; (5) change the maximum points
available for the e-Prescribing measure to 10 points beginning in CY
2020, in the event we finalize the proposed changes to the Query of
PDMP measure; (6) remove the Verify Opioid Treatment Agreement measure
beginning in CY 2020 and clearly state our intended policy that this
measure is worth a full 5 bonus points in CY 2019; and (7) revise the
Support Electronic Referral Loops by Receiving and Incorporating Health
Information measure to more clearly
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capture the previously established policy regarding CEHRT use. We are
also proposing to amend our regulations to incorporate several of these
proposals.
For CQM reporting under the Medicare and Medicaid Promoting
Interoperability Programs, we are generally proposing to align our
requirements with requirements under the Hospital IQR Program.
Specifically, we are proposing to: (1) Adopt two opioid-related eCQMs
(Safe Use of Opioids--Concurrent Prescribing eCQM (NQF #3316e) and
Hospital Harm--Opioid-Related Adverse Events eCQM) beginning with the
reporting period in CY 2021; (2) extend current CQM reporting and
submission requirements for the reporting periods in CY 2020 and CY
2021; and (3) establish CQM reporting and submission requirements for
the reporting period in CY 2022, which would require all eligible
hospitals and CAHs to report on the proposed Safe Use of Opioids--
Concurrent Prescribing eCQM (NQF #3316e) beginning with the reporting
period in CY 2022.
We are seeking public comments on whether we should consider
proposing to adopt in future rulemaking the Hybrid Hospital-Wide All-
Cause Readmission (Hybrid HWR) measure beginning with the reporting
period in CY 2023, a measure which we are proposing to adopt under the
Hospital IQR Program, and we are seeking information on a variety of
issues regarding the future direction of the Medicare and Medicaid
Promoting Interoperability Programs.
3. Summary of Costs and Benefits
Proposed Adjustment for MS-DRG Documentation and Coding
Changes. Section 414 of the MACRA replaced the single positive
adjustment we intended to make in FY 2018 once the recoupment required
by section 631 of the ATRA was complete with a 0.5 percentage point
positive adjustment to the standardized amount of Medicare payments to
acute care hospitals for FYs 2018 through 2023. (The FY 2018 adjustment
was subsequently adjusted to 0.4588 percentage point by section 15005
of the 21st Century Cures Act.) For FY 2020, we are proposing to make
an adjustment of +0.5 percentage point to the standardized amount
consistent with the MACRA.
Proposed Alternative Inpatient New Technology Add-On
Payment Pathway for Transformative New Devices: In this proposed rule,
we are proposing an alternative inpatient new technology add-on payment
pathway for a new medical device that is part of the FDA Breakthrough
Devices Program and has received FDA marketing authorization, that is,
received PMA approval, 510(k) clearance, or the granting of De Novo
classification request.
Given the relatively recent introduction of FDA's Breakthrough
Devices Program, there have not been any medical devices that were part
of the Breakthrough Devices Program and received FDA marketing
authorization and for which the applicant applied for a new technology
add-on payment under the IPPS and was not approved. Therefore, it is
not possible to quantify the impact of this proposal.
Proposed Changes to the Calculation of the
Inpatient Hospital New Technology Add-On Payment: The current
calculation of the new technology add-on payment is based on the cost
to hospitals for the new medical service or technology. Under existing
Sec. 412.88, if the costs of the discharge exceed the full DRG payment
(including payments for IME and DSH, but excluding outlier payments),
Medicare makes an add-on payment equal to the lesser of: (1) 50 percent
of the estimated costs of the new technology or medical service; or (2)
50 percent of the amount by which the costs of the case exceed the
standard DRG payment. In this proposed rule, we are proposing to modify
the current payment mechanism to increase the amount of the maximum
add-on payment amount to 65 percent. Therefore, we are proposing that
if the costs of a discharge involving a new technology exceed the full
DRG payment (including payments for IME and DSH, but excluding outlier
payments), Medicare would make an add-on payment equal to the lesser
of: (1) 65 percent of the costs of the new medical service or
technology; or (2) 65 percent of the amount by which the costs of the
case exceed the standard DRG payment.
We estimate that if we finalize our proposals for the 9
technologies for which we are proposing to continue to make new
technology add-on payments in FY 2020 and if we determine that all 17
of the FY 2020 new technology add-on payment applications meet the
specified criteria for new technology add-on payments for FY 2020, this
proposal, if finalized, would increase IPPS spending by approximately
$110 million in FY 2020.
Proposed Changes to Address Wage Index Disparities Between
High and Low Wage Index Hospitals. As discussed in section III.N. of
the preamble of this proposed rule, to help mitigate wage index
disparities, including those resulting from the inclusion of hospitals
with rural reclassifications under 42 CFR 412.103 in the rural floor,
we are proposing to reduce the disparity between high and low wage
index hospitals by increasing the wage index values for certain
hospitals with low wage index values and decreasing the wage index
values of certain hospitals with high wage index values for budget
neutrality purposes, as well as changing the calculation of the rural
floor. We also are proposing a transition for hospitals experiencing
significant decreases in their wage index values as a result of these
proposed changes. We are proposing to make these changes in a budget
neutral manner.
We are proposing to apply a budget neutrality adjustment to the
standardized amount so that our proposed transition for hospitals that
could be negatively impacted is implemented in a budget neutral manner.
Proposed Medicare DSH Payment Adjustment and Additional
Payment for Uncompensated Care. For FY 2020, we are proposing to update
our estimates of the three factors used to determine uncompensated care
payments. We are proposing to continue to use uninsured estimates
produced by OACT as part of the development of the NHEA in the
calculation of Factor 2. We also are proposing to use a single year of
data on uncompensated care costs from Worksheet S-10 for FY 2015 to
determine Factor 3 for FY 2020. In addition, we are seeking public
comments on whether we should, due to changes in the reporting
instructions that became effective for FY 2017, alternatively use a
single year of Worksheet S-10 data from the FY 2017 cost reports,
instead of the FY 2015 Worksheet S-10 data, to calculate Factor 3 for
FY 2020. To determine the amount of uncompensated care for purposes of
calculating Factor 3 for Puerto Rico hospitals and Indian Health
Service and Tribal hospitals, we are proposing to continue to use only
data regarding low-income insured days for FY 2013.
We project that the amount available to distribute as payments for
uncompensated care for FY 2020 would increase by approximately $216
million, as compared to our estimate of the uncompensated care payments
that will be distributed in FY 2019. The payments have redistributive
effects, based on a hospital's uncompensated care amount relative to
the uncompensated care amount for all hospitals that are projected to
be eligible to receive Medicare DSH payments, and the calculated
payment amount is not directly tied to a hospital's number of
discharges.
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Proposed Update to the LTCH PPS Payment Rates
and Other Payment Policies. Based on the best available data for the
384 LTCHs in our database, we estimate that the proposed changes to the
payment rates and factors that we present in the preamble of and
Addendum to this proposed rule, which reflect the end of the transition
of the statutory application of the site neutral payment rate and the
proposed update to the LTCH PPS standard Federal payment rate for FY
2020, would result in an estimated increase in payments in FY 2020 of
approximately $37 million.
Proposed Changes to the Hospital Readmissions Reduction
Program. For FY 2020 and subsequent years, the reduction is based on a
hospital's risk-adjusted readmission rate during a 3-year period for
acute myocardial infarction (AMI), heart failure (HF), pneumonia,
chronic obstructive pulmonary disease (COPD), elective primary total
hip arthroplasty/total knee arthroplasty (THA/TKA), and coronary artery
bypass graft (CABG) surgery. Overall, in this proposed rule, we
estimate that 2,599 hospitals would have their base operating DRG
payments reduced by their determined proxy FY 2020 hospital-specific
readmission adjustment. As a result, we estimate that the Hospital
Readmissions Reduction Program would save approximately $550 million in
FY 2020.
Value-Based Incentive Payments Under the Hospital VBP
Program. We estimate that there would be no net financial impact to the
Hospital VBP Program for the FY 2020 program year in the aggregate
because, by law, the amount available for value-based incentive
payments under the program in a given year must be equal to the total
amount of base operating MS-DRG payment amount reductions for that
year, as estimated by the Secretary. The estimated amount of base
operating MS-DRG payment amount reductions for the FY 2020 program year
and, therefore, the estimated amount available for value-based
incentive payments for FY 2020 discharges is approximately $1.9
billion.
Proposed Changes to the HAC Reduction Program. A
hospital's Total HAC score and its ranking in comparison to other
hospitals in any given year depend on several different factors. The FY
2020 program year is the first year in which we will implement our
equal measure weights scoring methodology. Any significant impact due
to the HAC Reduction Program proposed changes for FY 2020, including
which hospitals will receive the adjustment, would depend on the actual
experience of hospitals in the Program. We also are proposing to update
the hourly wage rate associated with burden for CDC NHSN HAI validation
under the HAC Reduction Program.
Proposed Changes to the Hospital Inpatient Quality
Reporting (IQR) Program. Across 3,300 IPPS hospitals, we estimate that
our proposed changes for the Hospital IQR Program in this proposed rule
would result in changes to the information collection burden compared
to previously adopted requirements. The only proposal that would affect
the information collection burden for the Hospital IQR Program is the
proposal to adopt the Hybrid Hospital-Wide All-Cause Readmission
(Hybrid HWR) measure (NQF #2879) in a stepwise fashion, beginning with
two voluntary reporting periods which would run from July 1, 2021
through June 30, 2022, and from July 1, 2022 through June 30, 2023,
before requiring reporting of the measure for the reporting period that
would run from July 1, 2023 through June 30, 2024, impacting the FY
2026 payment determination and for subsequent years. We estimate that
the impact of this proposed change is a total collection of information
burden increase of 2,211 hours and a total cost increase of
approximately $83,266 for all participating IPPS hospitals annually.
Proposed Changes to the Medicare and Medicaid Promoting
Interoperability Programs. We believe that, overall, the proposals in
this proposed rule would reduce burden, as described in detail in
section X.B.9. of the preamble and Appendix A, section I.N. of this
proposed rule.
B. Background Summary
1. Acute Care Hospital Inpatient Prospective Payment System (IPPS)
Section 1886(d) of the Social Security Act (the Act) sets forth a
system of payment for the operating costs of acute care hospital
inpatient stays under Medicare Part A (Hospital Insurance) based on
prospectively set rates. Section 1886(g) of the Act requires the
Secretary to use a prospective payment system (PPS) to pay for the
capital-related costs of inpatient hospital services for these
``subsection (d) hospitals.'' Under these PPSs, Medicare payment for
hospital inpatient operating and capital-related costs is made at
predetermined, specific rates for each hospital discharge. Discharges
are classified according to a list of diagnosis-related groups (DRGs).
The base payment rate is comprised of a standardized amount that is
divided into a labor-related share and a nonlabor-related share. The
labor-related share is adjusted by the wage index applicable to the
area where the hospital is located. If the hospital is located in
Alaska or Hawaii, the nonlabor-related share is adjusted by a cost-of-
living adjustment factor. This base payment rate is multiplied by the
DRG relative weight.
If the hospital treats a high percentage of certain low-income
patients, it receives a percentage add-on payment applied to the DRG-
adjusted base payment rate. This add-on payment, known as the
disproportionate share hospital (DSH) adjustment, provides for a
percentage increase in Medicare payments to hospitals that qualify
under either of two statutory formulas designed to identify hospitals
that serve a disproportionate share of low-income patients. For
qualifying hospitals, the amount of this adjustment varies based on the
outcome of the statutory calculations. The Affordable Care Act revised
the Medicare DSH payment methodology and provides for a new additional
Medicare payment beginning on October 1, 2013, that considers the
amount of uncompensated care furnished by the hospital relative to all
other qualifying hospitals.
If the hospital is training residents in an approved residency
program(s), it receives a percentage add-on payment for each case paid
under the IPPS, known as the indirect medical education (IME)
adjustment. This percentage varies, depending on the ratio of residents
to beds.
Additional payments may be made for cases that involve new
technologies or medical services that have been approved for special
add-on payments. To qualify, a new technology or medical service must
demonstrate that it is a substantial clinical improvement over
technologies or services otherwise available, and that, absent an add-
on payment, it would be inadequately paid under the regular DRG
payment.
The costs incurred by the hospital for a case are evaluated to
determine whether the hospital is eligible for an additional payment as
an outlier case. This additional payment is designed to protect the
hospital from large financial losses due to unusually expensive cases.
Any eligible outlier payment is added to the DRG-adjusted base payment
rate, plus any DSH, IME, and new technology or medical service add-on
adjustments.
Although payments to most hospitals under the IPPS are made on the
basis of the standardized amounts, some categories of hospitals are
paid in whole or in part based on their hospital-specific rate, which
is determined from their costs in a base year. For example, sole
community hospitals (SCHs)
[[Page 19167]]
receive the higher of a hospital-specific rate based on their costs in
a base year (the highest of FY 1982, FY 1987, FY 1996, or FY 2006) or
the IPPS Federal rate based on the standardized amount. SCHs are the
sole source of care in their areas. Specifically, section
1886(d)(5)(D)(iii) of the Act defines an SCH as a hospital that is
located more than 35 road miles from another hospital or that, by
reason of factors such as an isolated location, weather conditions,
travel conditions, or absence of other like hospitals (as determined by
the Secretary), is the sole source of hospital inpatient services
reasonably available to Medicare beneficiaries. In addition, certain
rural hospitals previously designated by the Secretary as essential
access community hospitals are considered SCHs.
Under current law, the Medicare-dependent, small rural hospital
(MDH) program is effective through FY 2022. Through and including FY
2006, an MDH received the higher of the Federal rate or the Federal
rate plus 50 percent of the amount by which the Federal rate was
exceeded by the higher of its FY 1982 or FY 1987 hospital-specific
rate. For discharges occurring on or after October 1, 2007, but before
October 1, 2022, an MDH receives the higher of the Federal rate or the
Federal rate plus 75 percent of the amount by which the Federal rate is
exceeded by the highest of its FY 1982, FY 1987, or FY 2002 hospital-
specific rate. MDHs are a major source of care for Medicare
beneficiaries in their areas. Section 1886(d)(5)(G)(iv) of the Act
defines an MDH as a hospital that is located in a rural area (or, as
amended by the Bipartisan Budget Act of 2018, a hospital located in a
State with no rural area that meets certain statutory criteria), has
not more than 100 beds, is not an SCH, and has a high percentage of
Medicare discharges (not less than 60 percent of its inpatient days or
discharges in its cost reporting year beginning in FY 1987 or in two of
its three most recently settled Medicare cost reporting years).
Section 1886(g) of the Act requires the Secretary to pay for the
capital-related costs of inpatient hospital services in accordance with
a prospective payment system established by the Secretary. The basic
methodology for determining capital prospective payments is set forth
in our regulations at 42 CFR 412.308 and 412.312. Under the capital
IPPS, payments are adjusted by the same DRG for the case as they are
under the operating IPPS. Capital IPPS payments are also adjusted for
IME and DSH, similar to the adjustments made under the operating IPPS.
In addition, hospitals may receive outlier payments for those cases
that have unusually high costs.
The existing regulations governing payments to hospitals under the
IPPS are located in 42 CFR part 412, subparts A through M.
2. Hospitals and Hospital Units Excluded From the IPPS
Under section 1886(d)(1)(B) of the Act, as amended, certain
hospitals and hospital units are excluded from the IPPS. These
hospitals and units are: Inpatient rehabilitation facility (IRF)
hospitals and units; long-term care hospitals (LTCHs); psychiatric
hospitals and units; children's hospitals; cancer hospitals; extended
neoplastic disease care hospitals, and hospitals located outside the 50
States, the District of Columbia, and Puerto Rico (that is, hospitals
located in the U.S. Virgin Islands, Guam, the Northern Mariana Islands,
and American Samoa). Religious nonmedical health care institutions
(RNHCIs) are also excluded from the IPPS. Various sections of the
Balanced Budget Act of 1997 (BBA, Pub. L. 105-33), the Medicare,
Medicaid and SCHIP [State Children's Health Insurance Program] Balanced
Budget Refinement Act of 1999 (BBRA, Pub. L. 106-113), and the
Medicare, Medicaid, and SCHIP Benefits Improvement and Protection Act
of 2000 (BIPA, Pub. L. 106-554) provide for the implementation of PPSs
for IRF hospitals and units, LTCHs, and psychiatric hospitals and units
(referred to as inpatient psychiatric facilities (IPFs)). (We note that
the annual updates to the LTCH PPS are included along with the IPPS
annual update in this document. Updates to the IRF PPS and IPF PPS are
issued as separate documents.) Children's hospitals, cancer hospitals,
hospitals located outside the 50 States, the District of Columbia, and
Puerto Rico (that is, hospitals located in the U.S. Virgin Islands,
Guam, the Northern Mariana Islands, and American Samoa), and RNHCIs
continue to be paid solely under a reasonable cost-based system,
subject to a rate-of-increase ceiling on inpatient operating costs.
Similarly, extended neoplastic disease care hospitals are paid on a
reasonable cost basis, subject to a rate-of-increase ceiling on
inpatient operating costs.
The existing regulations governing payments to excluded hospitals
and hospital units are located in 42 CFR parts 412 and 413.
3. Long-Term Care Hospital Prospective Payment System (LTCH PPS)
The Medicare prospective payment system (PPS) for LTCHs applies to
hospitals described in section 1886(d)(1)(B)(iv) of the Act, effective
for cost reporting periods beginning on or after October 1, 2002. The
LTCH PPS was established under the authority of sections 123 of the
BBRA and section 307(b) of the BIPA (as codified under section
1886(m)(1) of the Act). During the 5-year (optional) transition period,
a LTCH's payment under the PPS was based on an increasing proportion of
the LTCH Federal rate with a corresponding decreasing proportion based
on reasonable cost principles. Effective for cost reporting periods
beginning on or after October 1, 2006 through September 30, 2015 all
LTCHs were paid 100 percent of the Federal rate. Section 1206(a) of the
Pathway for SGR Reform Act of 2013 (Pub. L. 113-67) established the
site neutral payment rate under the LTCH PPS, which made the LTCH PPS a
dual rate payment system beginning in FY 2016. Under this statute,
based on a rolling effective date that is linked to the date on which a
given LTCH's Federal FY 2016 cost reporting period begins, LTCHs are
generally paid for discharges at the site neutral payment rate unless
the discharge meets the patient criteria for payment at the LTCH PPS
standard Federal payment rate. The existing regulations governing
payment under the LTCH PPS are located in 42 CFR part 412, subpart O.
Beginning October 1, 2009, we issue the annual updates to the LTCH PPS
in the same documents that update the IPPS (73 FR 26797 through 26798).
4. Critical Access Hospitals (CAHs)
Under sections 1814(l), 1820, and 1834(g) of the Act, payments made
to critical access hospitals (CAHs) (that is, rural hospitals or
facilities that meet certain statutory requirements) for inpatient and
outpatient services are generally based on 101 percent of reasonable
cost. Reasonable cost is determined under the provisions of section
1861(v) of the Act and existing regulations under 42 CFR part 413.
5. Payments for Graduate Medical Education (GME)
Under section 1886(a)(4) of the Act, costs of approved educational
activities are excluded from the operating costs of inpatient hospital
services. Hospitals with approved graduate medical education (GME)
programs are paid for the direct costs of GME in accordance with
section 1886(h) of the Act. The amount of payment for direct GME costs
for a cost reporting period is based on the hospital's number of
residents in that period and the hospital's costs per resident in a
base year. The existing regulations governing payments to the
[[Page 19168]]
various types of hospitals are located in 42 CFR part 413.
C. Summary of Provisions of Recent Legislation That Would Be
Implemented in This Proposed Rule
1. Pathway for SGR Reform Act of 2013 (Pub. L. 113-67)
The Pathway for SGR Reform Act of 2013 (Pub. L. 113-67) introduced
new payment rules in the LTCH PPS. Under section 1206 of this law,
discharges in cost reporting periods beginning on or after October 1,
2015, under the LTCH PPS, receive payment under a site neutral rate
unless the discharge meets certain patient-specific criteria. In this
proposed rule, we are proposing to continue to update certain policies
that implemented provisions under section 1206 of the Pathway for SGR
Reform Act.
2. Improving Medicare Post-Acute Care Transformation Act of 2014
(IMPACT Act) (Pub. L. 113-185)
The Improving Medicare Post-Acute Care Transformation Act of 2014
(IMPACT Act) (Pub. L. 113-185), enacted on October 6, 2014, made a
number of changes that affect the Long-Term Care Hospital Quality
Reporting Program (LTCH QRP). In this proposed rule, we are proposing
to continue to implement portions of section 1899B of the Act, as added
by section 2(a) of the IMPACT Act, which, in part, requires LTCHs,
among other post-acute care providers, to report standardized patient
assessment data, data on quality measures, and data on resource use and
other measures.
3. The Medicare Access and CHIP Reauthorization Act of 2015 (Pub. L.
114-10)
Section 414 of the Medicare Access and CHIP Reauthorization Act of
2015 (MACRA, Pub. L. 114-10) specifies a 0.5 percent positive
adjustment to the standardized amount of Medicare payments to acute
care hospitals for FYs 2018 through 2023. These adjustments follow the
recoupment adjustment to the standardized amounts under section 1886(d)
of the Act based upon the Secretary's estimates for discharges
occurring from FYs 2014 through 2017 to fully offset $11 billion, in
accordance with section 631 of the ATRA. The FY 2018 adjustment was
subsequently adjusted to 0.4588 percent by section 15005 of the 21st
Century Cures Act.
4. The 21st Century Cures Act (Pub. L. 114-255)
The 21st Century Cures Act (Pub. L. 114-255), enacted on December
13, 2016, contained the following provision affecting payments under
the Hospital Readmissions Reduction Program, which we are proposing to
continue to implement in this proposed rule:
Section 15002, which amended section 1886(q)(3) of the Act
by adding subparagraphs (D) and (E), which requires the Secretary to
develop a methodology for calculating the excess readmissions
adjustment factor for the Hospital Readmissions Reduction Program based
on cohorts defined by the percentage of dual-eligible patients (that
is, patients who are eligible for both Medicare and full-benefit
Medicaid coverage) cared for by a hospital. In this proposed rule, we
are proposing to continue to implement changes to the payment
adjustment factor to assess penalties based on a hospital's
performance, relative to other hospitals treating a similar proportion
of dual-eligible patients.
D. Summary of the Provisions of This Proposed Rule
In this proposed rule, we set forth proposed payment and policy
changes to the Medicare IPPS for FY 2020 operating costs and capital-
related costs of acute care hospitals and certain hospitals and
hospital units that are excluded from IPPS. In addition, we set forth
proposed changes to the payment rates, factors, and other payment and
policy-related changes to programs associated with payment rate
policies under the LTCH PPS for FY 2020.
Below is a general summary of the changes that we are proposing to
make in this proposed rule.
1. Proposed Changes to MS-DRG Classifications and Recalibrations of
Relative Weights
In section II. of the preamble of this proposed rule, we include--
Proposed changes to MS-DRG classifications based on our
yearly review for FY 2020.
Proposed adjustment to the standardized amounts under
section 1886(d) of the Act for FY 2020 in accordance with the
amendments made to section 7(b)(1)(B) of Public Law 110-90 by section
414 of the MACRA.
Proposed recalibration of the MS-DRG relative weights.
A discussion of the proposed FY 2020 status of new
technologies approved for add-on payments for FY 2019 and a
presentation of our evaluation and analysis of the FY 2020 applicants
for add-on payments for high-cost new medical services and technologies
(including public input, as directed by Pub. L. 108-173, obtained in a
town hall meeting).
A request for public comments on the substantial clinical
improvement criterion used to evaluate applications for both the IPPS
new technology add-on payments and the OPPS transitional pass-through
payment for devices, and a discussion of potential revisions that we
are considering adopting as final policies related to the substantial
clinical improvement criterion for applications received beginning in
FY 2020 for the IPPS (that is, for FY 2021 and later new technology
add-on payments) and beginning in CY 2020 for the OPPS.
A proposed alternative IPPS new technology add-on payment
pathway for certain transformative new devices.
Proposed changes to the calculation of the IPPS new
technology add-on payment.
2. Proposed Changes to the Hospital Wage Index for Acute Care Hospitals
In section III. of the preamble to this proposed rule, we are
proposing to make revisions to the wage index for acute care hospitals
and the annual update of the wage data. Specific issues addressed
include, but are not limited to, the following:
The proposed FY 2020 wage index update using wage data
from cost reporting periods beginning in FY 2016.
Proposals to address wage index disparities between high
and low wage index hospitals.
Calculation, analysis, and implementation of the proposed
occupational mix adjustment to the wage index for acute care hospitals
for FY 2020 based on the 2016 Occupational Mix Survey.
Proposed application of the rural floor and the frontier
State floor.
Proposed revisions to the wage index for acute care
hospitals, based on hospital redesignations and reclassifications under
sections 1886(d)(8)(B), (d)(8)(E), and (d)(10) of the Act.
Proposed change to Lugar county assignments.
Proposed adjustment to the wage index for acute care
hospitals for FY 2020 based on commuting patterns of hospital employees
who reside in a county and work in a different area with a higher wage
index.
Proposed labor-related share for the proposed FY 2020 wage
index.
3. Other Decisions and Proposed Changes to the IPPS for Operating Costs
In section IV. of the preamble of this proposed rule, we discuss
proposed changes or clarifications of a number of the provisions of the
regulations in 42
[[Page 19169]]
CFR parts 412 and 413, including the following:
Proposed changes to MS-DRGs subject to the postacute care
transfer policy and special payment policy.
Proposed changes to the inpatient hospital update for FY
2020.
Proposed conforming changes to the regulations for the
low-volume hospital payment adjustment policy.
Proposed updated national and regional case-mix values and
discharges for purposes of determining RRC status.
The statutorily required IME adjustment factor for FY
2020.
Proposed changes to the methodologies for determining
Medicare DSH payments and the additional payments for uncompensated
care.
A request for public comments on PRRB appeals related to a
hospital's Medicaid fraction in the DSH payment adjustment calculation.
Proposed changes to the policies for payment adjustments
under the Hospital Readmissions Reduction Program based on hospital
readmission measures and the process for hospital review and correction
of those rates for FY 2020.
Proposed changes to the requirements and provision of
value-based incentive payments under the Hospital Value-Based
Purchasing Program.
Proposed requirements for payment adjustments to hospitals
under the HAC Reduction Program for FY 2020.
Proposed changes related to CAHs as nonproviders for
direct GME and IME payment purposes.
Discussion of and proposals relating to the implementation
of the Rural Community Hospital Demonstration Program in FY 2020.
4. Proposed FY 2020 Policy Governing the IPPS for Capital-Related Costs
In section V. of the preamble to this proposed rule, we discuss the
proposed payment policy requirements for capital-related costs and
capital payments to hospitals for FY 2020.
5. Proposed Changes to the Payment Rates for Certain Excluded
Hospitals: Rate-of-Increase Percentages
In section VI. of the preamble of this proposed rule, we discuss--
Proposed changes to payments to certain excluded hospitals
for FY 2020.
Proposed change related to CAH payment for ambulance
services.
Proposed continued implementation of the Frontier
Community Health Integration Project (FCHIP) Demonstration.
6. Proposed Changes to the LTCH PPS
In section VII. of the preamble of this proposed rule, we set
forth--
Proposed changes to the LTCH PPS Federal payment rates,
factors, and other payment rate policies under the LTCH PPS for FY
2020.
Proposed payment adjustment for discharges of LTCHs that
do not meet the applicable discharge payment percentage.
7. Proposed Changes Relating to Quality Data Reporting for Specific
Providers and Suppliers
In section VIII. of the preamble of this proposed rule, we
address--
Proposed requirements for the Hospital Inpatient Quality
Reporting (IQR) Program.
Proposed changes to the requirements for the quality
reporting program for PPS-exempt cancer hospitals (PCHQR Program).
Proposed changes to the requirements under the LTCH
Quality Reporting Program (LTCH QRP).
Proposed changes to requirements pertaining to eligible
hospitals and CAHs participating in the Medicare and Medicaid Promoting
Interoperability Programs.
8. Provider Reimbursement Review Board Appeals
In section XI. of the preamble of this proposed rule, we discuss
the growing number of Provider Reimbursement Review Board appeals made
by providers and the action initiatives that are being implemented with
the goal to: decrease the number of appeals submitted; decrease the
number of appeals in inventory; reduce the time to resolution; and
increase customer satisfaction.
9. Determining Prospective Payment Operating and Capital Rates and
Rate-of-Increase Limits for Acute Care Hospitals
In sections II. and III. of the Addendum to this proposed rule, we
set forth the proposed changes to the amounts and factors for
determining the proposed FY 2020 prospective payment rates for
operating costs and capital-related costs for acute care hospitals. We
are proposing to establish the threshold amounts for outlier cases,
including a proposed change to the methodology for calculating those
threshold amounts for FY 2020 to incorporate a projection of outlier
payment reconciliations. In addition, in section IV. of the Addendum to
this proposed rule, we address the update factors for determining the
rate-of-increase limits for cost reporting periods beginning in FY 2020
for certain hospitals excluded from the IPPS.
10. Determining Prospective Payment Rates for LTCHs
In section V. of the Addendum to this proposed rule, we set forth
proposed changes to the amounts and factors for determining the
proposed FY 2020 LTCH PPS standard Federal payment rate and other
factors used to determine LTCH PPS payments under both the LTCH PPS
standard Federal payment rate and the site neutral payment rate in FY
2020. We are proposing to establish the adjustments for wage levels,
the labor-related share, the cost-of-living adjustment, and high-cost
outliers, including the applicable fixed-loss amounts and the LTCH
cost-to-charge ratios (CCRs) for both payment rates.
11. Impact Analysis
In Appendix A of this proposed rule, we set forth an analysis of
the impact the proposed changes would have on affected acute care
hospitals, CAHs, LTCHs, and PCHs.
12. Recommendation of Update Factors for Operating Cost Rates of
Payment for Hospital Inpatient Services
In Appendix B of this proposed rule, as required by sections
1886(e)(4) and (e)(5) of the Act, we provide our recommendations of the
appropriate percentage changes for FY 2020 for the following:
A single average standardized amount for all areas for
hospital inpatient services paid under the IPPS for operating costs of
acute care hospitals (and hospital-specific rates applicable to SCHs
and MDHs).
Target rate-of-increase limits to the allowable operating
costs of hospital inpatient services furnished by certain hospitals
excluded from the IPPS.
The LTCH PPS standard Federal payment rate and the site
neutral payment rate for hospital inpatient services provided for LTCH
PPS discharges.
13. Discussion of Medicare Payment Advisory Commission Recommendations
Under section 1805(b) of the Act, MedPAC is required to submit a
report to Congress, no later than March 15 of each year, in which
MedPAC reviews and makes recommendations on Medicare payment policies.
MedPAC's March 2019 recommendations concerning hospital inpatient
payment policies addressed the update factor for hospital inpatient
operating costs and capital-related costs for hospitals under the IPPS.
We address these
[[Page 19170]]
recommendations in Appendix B of this proposed rule. For further
information relating specifically to the MedPAC March 2019 report or to
obtain a copy of the report, contact MedPAC at (202) 220-3700 or visit
MedPAC's website at: http://www.medpac.gov.
E. Advancing Health Information Exchange
The Department of Health and Human Services (HHS) has a number of
initiatives designed to encourage and support the adoption of
interoperable health information technology and to promote nationwide
health information exchange to improve health care. The Office of the
National Coordinator for Health Information Technology (ONC) and CMS
work collaboratively to advance interoperability across settings of
care, including post-acute care.
To further interoperability in post-acute care, we developed a Data
Element Library (DEL) to serve as a publicly available centralized,
authoritative resource for standardized data elements and their
associated mappings to health IT standards. The DEL furthers CMS' goal
of data standardization and interoperability, which is also a goal of
the IMPACT Act. These interoperable data elements can reduce provider
burden by allowing the use and exchange of health care data, support
provider exchange of electronic health information for care
coordination, person-centered care, and support real-time, data driven,
clinical decision making. Standards in the Data Element Library
(https://del.cms.gov/) can be referenced on the CMS website and in the
ONC Interoperability Standards Advisory (ISA). The 2019 ISA is
available at: https://www.healthit.gov/isa.
The 21st Century Cures Act (the Cures Act) (Pub. L. 114-255,
enacted December 13, 2016) requires HHS to take new steps to enable the
electronic sharing of health information ensuring interoperability for
providers and settings across the care continuum. In an important
provision, Congress defined ``information blocking'' as practices
likely to interfere with, prevent, or materially discourage access,
exchange, or use of electronic health information, and established new
authority for HHS to discourage these practices. In March 2019, ONC and
CMS published the proposed rules, ``21st Century Cures Act:
Interoperability, Information Blocking, and the ONC Health IT
Certification Program'' (84 FR 7424 through 7610) and
``Interoperability and Patient Access'' (84 FR 7610 through 7680), to
promote secure and more immediate access to health information for
patients and health care providers through the implementation of
information blocking provisions of the Cures Act and the use of
standardized application programming interfaces (APIs) that enable
easier access to electronic health information. These two proposed
rules are open for public comments at: www.regulations.gov.
We invite providers to learn more about these important
developments and how they are likely to affect hospitals paid under the
IPPS and the LTCH PPS.
II. Proposed Changes to Medicare Severity Diagnosis-Related Group (MS-
DRG) Classifications and Relative Weights
A. Background
Section 1886(d) of the Act specifies that the Secretary shall
establish a classification system (referred to as diagnosis-related
groups (DRGs)) for inpatient discharges and adjust payments under the
IPPS based on appropriate weighting factors assigned to each DRG.
Therefore, under the IPPS, Medicare pays for inpatient hospital
services on a rate per discharge basis that varies according to the DRG
to which a beneficiary's stay is assigned. The formula used to
calculate payment for a specific case multiplies an individual
hospital's payment rate per case by the weight of the DRG to which the
case is assigned. Each DRG weight represents the average resources
required to care for cases in that particular DRG, relative to the
average resources used to treat cases in all DRGs.
Section 1886(d)(4)(C) of the Act requires that the Secretary adjust
the DRG classifications and relative weights at least annually to
account for changes in resource consumption. These adjustments are made
to reflect changes in treatment patterns, technology, and any other
factors that may change the relative use of hospital resources.
B. MS-DRG Reclassifications
For general information about the MS-DRG system, including yearly
reviews and changes to the MS-DRGs, we refer readers to the previous
discussions in the FY 2010 IPPS/RY 2010 LTCH PPS final rule (74 FR
43764 through 43766) and the FYs 2011 through 2019 IPPS/LTCH PPS final
rules (75 FR 50053 through 50055; 76 FR 51485 through 51487; 77 FR
53273; 78 FR 50512; 79 FR 49871; 80 FR 49342; 81 FR 56787 through
56872; 82 FR 38010 through 38085, and 83 FR 41158 through 41258,
respectively).
C. Adoption of the MS-DRGs in FY 2008
For information on the adoption of the MS-DRGs in FY 2008, we refer
readers to the FY 2008 IPPS final rule with comment period (72 FR 47140
through 47189).
D. Proposed FY 2020 MS-DRG Documentation and Coding Adjustment
1. Background on the Prospective MS-DRG Documentation and Coding
Adjustments for FY 2008 and FY 2009 Authorized by Public Law 110-90 and
the Recoupment or Repayment Adjustment Authorized by Section 631 of the
American Taxpayer Relief Act of 2012 (ATRA)
In the FY 2008 IPPS final rule with comment period (72 FR 47140
through 47189), we adopted the MS-DRG patient classification system for
the IPPS, effective October 1, 2007, to better recognize severity of
illness in Medicare payment rates for acute care hospitals. The
adoption of the MS-DRG system resulted in the expansion of the number
of DRGs from 538 in FY 2007 to 745 in FY 2008. By increasing the number
of MS-DRGs and more fully taking into account patient severity of
illness in Medicare payment rates for acute care hospitals, MS-DRGs
encourage hospitals to improve their documentation and coding of
patient diagnoses.
In the FY 2008 IPPS final rule with comment period (72 FR 47175
through 47186), we indicated that the adoption of the MS-DRGs had the
potential to lead to increases in aggregate payments without a
corresponding increase in actual patient severity of illness due to the
incentives for additional documentation and coding. In that final rule
with comment period, we exercised our authority under section
1886(d)(3)(A)(vi) of the Act, which authorizes us to maintain budget
neutrality by adjusting the national standardized amount, to eliminate
the estimated effect of changes in coding or classification that do not
reflect real changes in case-mix. Our actuaries estimated that
maintaining budget neutrality required an adjustment of -4.8 percentage
points to the national standardized amount. We provided for phasing in
this -4.8 percentage point adjustment over 3 years. Specifically, we
established prospective documentation and coding adjustments of -1.2
percentage points for FY 2008, -1.8 percentage points for FY 2009, and
-1.8 percentage points for FY 2010.
On September 29, 2007, Congress enacted the TMA [Transitional
Medical Assistance], Abstinence Education, and
[[Page 19171]]
QI [Qualifying Individuals] Programs Extension Act of 2007 (Pub. L.
110-90). Section 7(a) of Public Law 110-90 reduced the documentation
and coding adjustment made as a result of the MS-DRG system that we
adopted in the FY 2008 IPPS final rule with comment period to -0.6
percentage point for FY 2008 and -0.9 percentage point for FY 2009.
As discussed in prior year rulemakings, and most recently in the FY
2017 IPPS/LTCH PPS final rule (81 FR 56780 through 56782), we
implemented a series of adjustments required under sections 7(b)(1)(A)
and 7(b)(1)(B) of Public Law 110-90, based on a retrospective review of
FY 2008 and FY 2009 claims data. We completed these adjustments in FY
2013 but indicated in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53274
through 53275) that delaying full implementation of the adjustment
required under section 7(b)(1)(A) of Public Law 110-90 until FY 2013
resulted in payments in FY 2010 through FY 2012 being overstated, and
that these overpayments could not be recovered under Public Law 110-90.
In addition, as discussed in prior rulemakings and most recently in
the FY 2018 IPPS/LTCH PPS final rule (82 FR 38008 through 38009),
section 631 of the ATRA amended section 7(b)(1)(B) of Public Law 110-90
to require the Secretary to make a recoupment adjustment or adjustments
totaling $11 billion by FY 2017. This adjustment represented the amount
of the increase in aggregate payments as a result of not completing the
prospective adjustment authorized under section 7(b)(1)(A) of Public
Law 110-90 until FY 2013.
2. Adjustments Made for FY 2018 and FY 2019 as Required Under Section
414 of Public Law 114-10 (MACRA) and Section 15005 of Public Law 114-
255
As stated in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56785),
once the recoupment required under section 631 of the ATRA was
complete, we had anticipated making a single positive adjustment in FY
2018 to offset the reductions required to recoup the $11 billion under
section 631 of the ATRA. However, section 414 of the MACRA (which was
enacted on April 16, 2015) replaced the single positive adjustment we
intended to make in FY 2018 with a 0.5 percentage point positive
adjustment for each of FYs 2018 through 2023. In the FY 2017
rulemaking, we indicated that we would address the adjustments for FY
2018 and later fiscal years in future rulemaking. Section 15005 of the
21st Century Cures Act (Pub. L. 114-255), which was enacted on December
13, 2016, amended section 7(b)(1)(B) of the TMA, as amended by section
631 of the ATRA and section 414 of the MACRA, to reduce the adjustment
for FY 2018 from a 0.5 percentage point positive adjustment to a 0.4588
percentage point positive adjustment. As we discussed in the FY 2018
rulemaking, we believe the directive under section 15005 of Public Law
114-255 is clear. Therefore, in the FY 2018 IPPS/LTCH PPS final rule
(82 FR 38009) for FY 2018, we implemented the required +0.4588
percentage point adjustment to the standardized amount. In the FY 2019
IPPS/LTCH PPS final rule (83 FR 41157), consistent with the
requirements of section 414 of the MACRA, we implemented a 0.5
percentage point positive adjustment to the standardized amount for FY
2019. We indicated that both the FY 2018 and FY 2019 adjustments were
permanent adjustments to payment rates. We also stated that we plan to
propose future adjustments required under section 414 of the MACRA for
FYs 2020 through 2023 in future rulemaking.
3. Proposed Adjustment for FY 2020
Consistent with the requirements of section 414 of the MACRA, we
are proposing to implement a 0.5 percentage point positive adjustment
to the standardized amount for FY 2020. This would constitute a
permanent adjustment to payment rates. We plan to propose future
adjustments required under section 414 of the MACRA for FYs 2021
through 2023 in future rulemaking.
E. Refinement of the MS-DRG Relative Weight Calculation
1. Background
Beginning in FY 2007, we implemented relative weights for DRGs
based on cost report data instead of charge information. We refer
readers to the FY 2007 IPPS final rule (71 FR 47882) for a detailed
discussion of our final policy for calculating the cost-based DRG
relative weights and to the FY 2008 IPPS final rule with comment period
(72 FR 47199) for information on how we blended relative weights based
on the CMS DRGs and MS-DRGs. We also refer readers to the FY 2017 IPPS/
LTCH PPS final rule (81 FR 56785 through 56787) for a detailed
discussion of the history of changes to the number of cost centers used
in calculating the DRG relative weights. Since FY 2014, we have
calculated the IPPS MS-DRG relative weights using 19 CCRs, which now
include distinct CCRs for implantable devices, MRIs, CT scans, and
cardiac catheterization.
2. Discussion of Policy for FY 2020
Consistent with our established policy, we are calculating the
proposed MS-DRG relative weights for FY 2020 using two data sources:
The MedPAR file as the claims data source and the HCRIS as the cost
report data source. We adjust the charges from the claims to costs by
applying the 19 national average CCRs developed from the cost reports.
The description of the calculation of the proposed 19 CCRs and the
proposed MS-DRG relative weights for FY 2020 is included in section
II.G. of the preamble to this FY 2020 IPPS/LTCH PPS proposed rule. As
we did with the FY 2019 IPPS/LTCH PPS final rule, for this FY 2020
proposed rule, we are providing the version of the HCRIS from which we
calculated these proposed 19 CCRs on the CMS website at: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. Click on the link on the left side of the
screen titled ``FY 2020 IPPS Proposed Rule Home Page'' or ``Acute
Inpatient Files for Download.''
F. Proposed Changes to Specific MS-DRG Classifications
1. Discussion of Changes to Coding System and Basis for Proposed FY
2020 MS-DRG Updates
a. Conversion of MS-DRGs to the International Classification of
Diseases, 10th Revision (ICD-10)
As of October 1, 2015, providers use the International
Classification of Diseases, 10th Revision (ICD-10) coding system to
report diagnoses and procedures for Medicare hospital inpatient
services under the MS-DRG system instead of the ICD-9-CM coding system,
which was used through September 30, 2015. The ICD-10 coding system
includes the International Classification of Diseases, 10th Revision,
Clinical Modification (ICD-10-CM) for diagnosis coding and the
International Classification of Diseases, 10th Revision, Procedure
Coding System (ICD-10-PCS) for inpatient hospital procedure coding, as
well as the ICD-10-CM and ICD-10-PCS Official Guidelines for Coding and
Reporting. For a detailed discussion of the conversion of the MS-DRGs
to ICD-10, we refer readers to the FY 2017 IPPS/LTCH PPS final rule (81
FR 56787 through 56789).
b. Basis for Proposed FY 2020 MS-DRG Updates
CMS has previously encouraged input from our stakeholders
concerning the annual IPPS updates when that input was made available
to us by December
[[Page 19172]]
7 of the year prior to the next annual proposed rule update. As
discussed in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38010), as we
work with the public to examine the ICD-10 claims data used for updates
to the ICD-10 MS DRGs, we would like to examine areas where the MS-DRGs
can be improved, which will require additional time for us to review
requests from the public to make specific updates, analyze claims data,
and consider any proposed updates. Given the need for more time to
carefully evaluate requests and propose updates, we changed the
deadline to request updates to the MS-DRGs to November 1 of each year.
This will provide an additional 5 weeks for the data analysis and
review process. Interested parties had to submit any comments and
suggestions for FY 2020 by November 1, 2018, and should submit any
comments and suggestions for FY 2021 by November 1, 2019 via the CMS
MS-DRG Classification Change Request Mailbox located at:
[email protected]. The comments that were submitted
in a timely manner for FY 2020 are discussed in this section of the
preamble of this proposed rule. As we discuss in the sections that
follow, we may not be able to fully consider all of the requests that
we receive for the upcoming fiscal year. We have found that, with the
implementation of ICD-10, some types of requested changes to the MS-DRG
classifications require more extensive research to identify and analyze
all of the data that are relevant to evaluating the potential change.
We note in the discussion that follows those topics for which further
research and analysis are required, and which we will continue to
consider in connection with future rulemaking.
Following are the changes that we are proposing to the MS-DRGs for
FY 2020. We are inviting public comments on each of the MS-DRG
classification proposed changes, as well as our proposals to maintain
certain existing MS-DRG classifications discussed in this proposed
rule. In some cases, we are proposing changes to the MS-DRG
classifications based on our analysis of claims data and consultation
with our clinical advisors. In other cases, we are proposing to
maintain the existing MS-DRG classifications based on our analysis of
claims data and consultation with our clinical advisors. For this FY
2020 IPPS/LTCH PPS proposed rule, our MS-DRG analysis was based on ICD-
10 claims data from the September 2018 update of the FY 2018 MedPAR
file, which contains hospital bills received through September 30,
2018, for discharges occurring through September 30, 2018. In our
discussion of the proposed MS-DRG reclassification changes, we refer to
these claims data as the ``September 2018 update of the FY 2018 MedPAR
file.''
As explained in previous rulemaking (76 FR 51487), in deciding
whether to propose to make further modifications to the MS-DRGs for
particular circumstances brought to our attention, we consider whether
the resource consumption and clinical characteristics of the patients
with a given set of conditions are significantly different than the
remaining patients represented in the MS-DRG. We evaluate patient care
costs using average costs and lengths of stay and rely on the judgment
of our clinical advisors to determine whether patients are clinically
distinct or similar to other patients represented in the MS-DRG. In
evaluating resource costs, we consider both the absolute and percentage
differences in average costs between the cases we select for review and
the remainder of cases in the MS-DRG. We also consider variation in
costs within these groups; that is, whether observed average
differences are consistent across patients or attributable to cases
that are extreme in terms of costs or length of stay, or both. Further,
we consider the number of patients who will have a given set of
characteristics and generally prefer not to create a new MS-DRG unless
it would include a substantial number of cases.
In our examination of the claims data, we apply the following
criteria established in FY 2008 (72 FR 47169) to determine if the
creation of a new complication or comorbidity (CC) or major
complication or comorbidity (MCC) subgroup within a base MS-DRG is
warranted:
A reduction in variance of costs of at least 3 percent;
At least 5 percent of the patients in the MS-DRG fall
within the CC or MCC subgroup;
At least 500 cases are in the CC or MCC subgroup;
There is at least a 20-percent difference in average costs
between subgroups; and
There is a $2,000 difference in average costs between
subgroups.
In order to warrant creation of a CC or MCC subgroup within a base
MS-DRG, the subgroup must meet all five of the criteria.
2. Pre-MDC
a. Peripheral ECMO
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41166 through
41169), we discussed a request we received to review cases reporting
the use of extracorporeal membrane oxygenation (ECMO) in combination
with the insertion of a percutaneous short-term external heart assist
device. We also noted that a separate request to create a new ICD-10-
PCS procedure code specifically for percutaneous ECMO was discussed at
the March 6-7, 2018 ICD-10 Coordination and Maintenance Committee
Meeting for which we finalized the creation of three new procedure
codes to identify and describe different types of ECMO treatments
currently being utilized. These three new procedure codes were included
in the FY 2019 ICD-10-PCS procedure codes files (which are available
via the internet on the CMS website at: https://www.cms.gov/Medicare/Coding/ICD10/2019-ICD-10-PCS.html) and were made publicly available in
May 2018. We received recommendations from commenters on suggested MS-
DRG assignments for the two new procedure codes that uniquely identify
percutaneous (peripheral) ECMO, including assignment to MS-DRG 215
(Other Heart Assist System Implant), or to Pre-MDC MS-DRG 004
(Tracheostomy with Mechanical Ventilation >96 Hours or Principal
Diagnosis Except Face, Mouth and Neck without Major O.R. Procedure)
specifically for the new procedure code describing percutaneous veno-
venous (VV) ECMO or an alternate MS-DRG within MDC 4 (Diseases and
Disorders of the Respiratory System). In our response, we noted that
because these codes were not finalized at the time of the proposed
rule, there were no proposed MDC or MS-DRG assignments or O.R. and non-
O.R. designations for these new procedure codes and they were not
reflected in Table 6B.--New Procedure Codes (which is available via the
internet on the CMS website at: http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html)
associated with the FY 2019 IPPS/LTCH PPS proposed rule.
We further noted that, consistent with our annual process of
assigning new procedure codes to MDCs and MS-DRGs, and designating a
procedure as an O.R. or non-O.R. procedure, we reviewed the predecessor
procedure code assignment. For the reasons discussed in the FY 2019
IPPS/LTCH PPS final rule, our clinical advisors did not support
assigning the new procedure codes for the percutaneous (peripheral)
ECMO procedures to the same MS-DRG as the predecessor code for open
(central) ECMO in pre-MDC MS-DRG 003.
[[Page 19173]]
Effective with discharges occurring on and after October 1, 2018,
the three ECMO procedure codes and their corresponding MS-DRG
assignments are as shown in the following table.
----------------------------------------------------------------------------------------------------------------
ICD-10-PCS code Code description MS-DRG MS-DRG description
----------------------------------------------------------------------------------------------------------------
5A1522F...................... Extracorporeal Pre-MDC...................... ECMO or Tracheostomy with
Oxygenation, MS-DRG 003................... Mechanical Ventilation
Membrane, Central. >96 Hours or Principal
Diagnosis Except Face,
Mouth and Neck with Major
O.R. Procedure.
5A1522G...................... Extracorporeal MS-DRG 207................... Respiratory System
Oxygenation, Diagnosis with Ventilator
Membrane, Peripheral Support >96 Hours or
Veno-arterial. Peripheral Extracorporeal
Membrane Oxygenation
(ECMO).
MS-DRG 291................... Heart Failure and Shock
with MCC or Peripheral
Extracorporeal Membrane
Oxygenation (ECMO).
MS-DRG 296................... Cardiac Arrest,
Unexplained with MCC or
Peripheral Extracorporeal
Membrane Oxygenation
(ECMO).
MS-DRG 870................... Septicemia Or Severe
Sepsis with Mechanical
Ventilation >96 Hours Or
Peripheral Extracorporeal
Membrane Oxygenation
(ECMO).
5A1522H...................... Extracorporeal MS-DRG 207................... Respiratory System
Oxygenation, Diagnosis with Ventilator
Membrane, Peripheral Support >96 Hours or
Veno-venous. Peripheral Extracorporeal
Membrane Oxygenation
(ECMO).
MS-DRG 291................... Heart Failure and Shock
with MCC or Peripheral
Extracorporeal Membrane
Oxygenation (ECMO).
MS-DRG 296................... Cardiac Arrest,
Unexplained with MCC or
Peripheral Extracorporeal
Membrane Oxygenation
(ECMO).
MS-DRG 870................... Septicemia Or Severe
Sepsis with Mechanical
Ventilation >96 Hours Or
Peripheral Extracorporeal
Membrane Oxygenation
(ECMO).
----------------------------------------------------------------------------------------------------------------
After publication of the FY 2019 IPPS/LTCH PPS final rule, we
received comments and feedback from stakeholders expressing concern
with the MS-DRG assignments for the two new procedure codes describing
peripheral ECMO. Specifically, these stakeholders stated that: (1) The
MS-DRG assignments for ECMO should not be based on how the patient is
cannulated (open versus peripheral) because most of the costs for both
central and peripheral ECMO can be attributed to the severity of
illness of the patient; (2) there was a lack of opportunity for public
comment on the finalized MS-DRG assignments; (3) patient access to ECMO
treatment and programs is now at risk because of inadequate payment;
and (4) CMS did not appear to have access to enough patient data to
evaluate for appropriate MS-DRG assignment consideration. They also
stated that the new procedure codes do not account for an open cut-down
approach that may be performed on a peripheral vessel during a
peripheral ECMO procedure. These stakeholders recommended that,
consistent with the usual process of assigning new procedure codes to
the same MS-DRG as the predecessor code, the MS-DRG assignment for
peripheral ECMO procedures should be revised to allow assignment of
peripheral ECMO procedures to Pre-MDC MS-DRG 003 (ECMO or Tracheostomy
with Mechanical Ventilation >96 Hours or Principal Diagnosis Except
Face, Mouth and Neck with Major O.R. Procedure). They stated that this
revision would also allow for the collection of further claims data for
patients treated with ECMO and assist in determining the
appropriateness of any future modifications in MS-DRG assignment.
We also received feedback from a few stakeholders that, for some
cases involving peripheral ECMO, the current designation provides
compensation that these stakeholders believe is ``reasonable'' (for
example, for peripheral ECMO in certain patients admitted with acute
respiratory failure and sepsis). Some of these stakeholders agreed with
CMS that once claims data become available, the volume, length of stay
and cost data of claims with these new codes can be examined to
determine if modifications to MS-DRG assignment or O.R. and non-O.R.
designation are warranted. However, some of these stakeholders also
expressed concerns that the current assignments and designation do not
appropriately compensate for the resources used when peripheral ECMO is
used to treat certain patients (for example, patients who are admitted
with cardiac arrest and cardiogenic shock of known cause or patients
admitted with a different principal diagnosis or patients who develop a
diagnosis after admission that requires ECMO). These stakeholders
stated that the current MS-DRG assignments for such cases involving
peripheral ECMO do not provide sufficient payment and do not fully
consider the severity of illness of the patient and the level of
resources involved in treating such patients, such as surgical team,
general anesthesia, and other ECMO support such as specialized
monitoring.
With regard to stakeholders' concerns that we did not allow the
opportunity for public comment on the MS-DRG assignment for the three
new procedure codes that describe central and peripheral ECMO, as noted
above and as explained in the FY 2019 IPPS/LTCH PPS final rule (83 FR
41168), these new procedure codes were not finalized at the time of the
proposed rule. We note that although there were no proposed MDC or MS-
DRG assignment or O.R. and non-O.R. designations for these three new
procedure codes, we did, in fact, review and respond to comments on the
recommended MDC and MS-DRG assignments and O.R./non-O.R. designations
in the final rule (83 FR 41168 through 41169). For FY 2019, consistent
with our annual process of assigning new procedure codes to MDCs and
MS-DRGs and designating a procedure as an O.R. or non-O.R. procedure,
we reviewed the predecessor procedure code assignments. Upon completing
the review, our clinical advisors did not support assigning the two new
ICD-10-PCS procedure codes for peripheral ECMO procedures to the same
MS-DRG as the predecessor code for open (central) ECMO procedures.
Further, our clinical advisors also did not agree with designating
peripheral
[[Page 19174]]
ECMO procedures as O.R. procedures because they stated that these
procedures are less resource intensive compared to open ECMO
procedures.
As noted, our annual process for assigning new procedure codes
involves review of the predecessor procedure code's MS-DRG assignment.
However, this process does not automatically result in the new
procedure code being assigned (or proposed for assignment) to the same
MS-DRG as the predecessor code. There are several factors to consider
during this process that our clinical advisors take into account. For
example, in the absence of volume, length of stay, and cost data, they
may consider the specific service, procedure, or treatment being
described by the new procedure code, the indications, treatment
difficulty, and the resources utilized. We have continued to consider
how these and other factors may apply in the context of classifying
procedures under the ICD-10 MS-DRGs, including with regard to the
specific concerns raised by stakeholders.
In the absence of claims data for the new ICD-10-PCS procedure
codes describing peripheral ECMO, we analyzed claims data from the
September 2018 update of the FY 2018 MedPAR file for cases reporting
the predecessor ICD-10-PCS procedure code 5A15223 (Extracorporeal
membrane oxygenation, continuous) in Pre-MDC MS-DRG 003, including
those cases reporting secondary diagnosis MCC and CC conditions, that
were grouped under the ICD-10 MS-DRG Version 35 GROUPER. Our findings
are shown in the table below.
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 003--All cases........................................... 14,456 29.6 $122,168
MS-DRG 003--Cases reporting procedure code 5A15223 2,086 20.2 128,168
(Extracorporeal membrane oxygenation, continuous)..............
MS-DRG 003--Cases reporting procedure code 5A15223 2,000 20.7 131,305
(Extracorporeal membrane oxygenation, continuous) with MCC.....
MS-DRG 003--Cases reporting procedure code 5A15223 79 7.6 58,231
(Extracorporeal membrane oxygenation, continuous) with CC......
----------------------------------------------------------------------------------------------------------------
The total number of cases reported in MS-DRG 003 was 14,456, with
an average length of stay of 29.6 days and average costs of $122,168.
For the cases reporting procedure code 5A15223 (Extracorporeal membrane
oxygenation, continuous), there was a total of 2,086 cases, with an
average length of stay of 20.2 days and average costs of $128,168. For
the cases reporting procedure code 5A15223 with an MCC, there was a
total of 2,000 cases, with an average length of stay of 20.7 days and
average costs of $131,305. For the cases reporting procedure code
5A15223 with a CC, there was a total of 79 cases, with an average
length of stay of 7.6 days and average costs of $58,231.
Our clinical advisors reviewed these data and noted that the
average length of stay for the cases reporting ECMO with procedure code
5A15223 of 20.2 days may not necessarily be a reliable indicator of
resources that can be attributed to ECMO treatment. Our clinical
advisors believed that a more appropriate measure of resource
consumption for ECMO would be the number of hours or days that a
patient was specifically receiving ECMO treatment, rather than the
length of hospital stay. However, they noted that this information is
not currently available in the claims data. Our clinical advisors also
stated that the average costs of $128,168 for the cases reporting ECMO
with procedure code 5A15223 are not necessarily reflective of the
resources utilized for ECMO treatment alone, as the average costs
represent a combination of factors, including the principal diagnosis,
any secondary diagnosis CC and/or MCC conditions necessitating
initiation of ECMO, and potentially any other procedures that may be
performed during the hospital stay. Our clinical advisors recognized
that patients who require ECMO treatment are severely ill and
recommended we review the claims data to identify the number
(frequency) and types of principal and secondary diagnosis CC and/or
MCC conditions that were reported among the 2,086 cases reporting
procedure code 5A15223. Our findings are shown in the following tables
for the top 10 principal diagnosis codes, followed by the top 10
secondary diagnosis MCC and secondary diagnosis CC conditions that were
reported within the claims data with procedure code 5A15223.
Top 10 Principal Diagnosis Codes Reported With Procedure Code 5A1223
[Extracorporeal membrane oxygenation, continuous]
------------------------------------------------------------------------
Number of
ICD-10-CM code Description times reported
------------------------------------------------------------------------
A41.9....................... Sepsis, unspecified 145
organism.
I21.4....................... Non-ST elevation (NSTEMI) 137
myocardial infarction.
I35.0....................... Nonrheumatic aortic 81
(valve) stenosis.
J84.112..................... Idiopathic pulmonary 68
fibrosis.
I25.110..................... Atherosclerotic heart 55
disease of native
coronary artery with
unstable angina pectoris.
J96.01...................... Acute respiratory failure 52
with hypoxia.
I21.09...................... STEMI involving other 49
coronary artery of
anterior wall.
I25.10...................... Atherosclerotic heart 48
disease of native
coronary artery w/o
angina pectoris.
I13.0....................... Hypertensive heart & 46
chronic kidney disease w
heart failure and stage 1
through stage 4 chronic
kidney disease, or
unspecified chronic
kidney disease.
I21.19...................... ST elevation (STEMI) 43
myocardial infarction
involving other coronary
artery of inferior wall.
------------------------------------------------------------------------
[[Page 19175]]
Top 10 Secondary Diagnosis MCC Conditions Reported With Procedure Code 5A1223
[Extracorporeal membrane oxygenation, continuous]
----------------------------------------------------------------------------------------------------------------
Number of Average length
ICD-10-CM code Description times reported of stay Average costs
----------------------------------------------------------------------------------------------------------------
A41.9........................... Sepsis, unspecified organism.. 322 29.7 $186,055
E43............................. Unspecified severe protein- 220 41.5 213,742
calorie malnutrition.
G93.40.......................... Encephalopathy, unspecified... 217 27.2 165,193
J18.9........................... Pneumonia, unspecified 220 23.5 150,242
organism.
J96.01.......................... Acute respiratory failure with 944 17.9 122,614
hypoxia.
J96.02.......................... Acute respiratory failure with 220 20.9 139,511
hypercapnia.
K72.00.......................... Acute and subacute hepatic 524 19 140,878
failure without coma.
N17.0........................... Acute kidney failure with 741 26.2 162,583
tubular necrosis.
R57.0........................... Cardiogenic shock............. 448 27.7 153,878
R65.21.......................... Severe sepsis with septic 504 29.7 177,992
shock.
----------------------------------------------------------------------------------------------------------------
Top 10 Secondary Diagnosis CC Conditions Reported With Procedure Code 5A1223
[Extracorporeal membrane oxygenation, continuous]
----------------------------------------------------------------------------------------------------------------
Number of Average length
ICD-10-CM code Description times reported of stay Average costs
----------------------------------------------------------------------------------------------------------------
D62............................. Acute posthemorrhagic anemia.. 1,139 21.8 $144,033
D68.9........................... Coagulation defect, 402 20.5 138,417
unspecified.
E87.0........................... Hyperosmolality and 585 26.6 162,028
hypernatremia.
E87.1........................... Hypo-osmolality and 316 26.1 151,824
hyponatremia.
E87.2........................... Acidosis...................... 937 17.3 120,881
E87.4........................... Mixed disorder of acid-base 268 26 150,257
balance.
I13.0........................... Hypertensive heart and chronic 314 18.4 121,962
kidney disease with heart
failure and stage 1 through
stage 4 chronic kidney
disease, or unspecified
chronic kidney disease.
I47.2........................... Ventricular tachycardia....... 384 17.5 123,383
J98.11.......................... Atelectasis................... 273 26.9 158,812
N17.9........................... Acute kidney failure, 757 18.5 122,180
unspecified.
----------------------------------------------------------------------------------------------------------------
These data show that the conditions reported for these patients
requiring treatment with ECMO and reported with predecessor ICD-10-PCS
procedure code 5A1223 represent a greater severity of illness, present
greater treatment difficulty, have poorer prognoses, and have a greater
need for intervention. While the data analysis was based on the
conditions reported with the predecessor ICD-10-PCS procedure code
5A1223 (Extracorporeal membrane oxygenation, continuous), our clinical
advisors believe the data may provide an indication of how cases
reporting the new procedure codes describing peripheral (percutaneous)
ECMO may be represented in future claims data with regard to
indications for treatment, a patient's severity of illness, resource
utilization, and treatment difficulty.
Based on the results of our data analysis and further review of the
cases reporting ECMO, including consideration of the stakeholders'
concerns that the MS-DRG assignments for ECMO procedures should not be
based on the method of cannulation, our clinical advisors agree that
resource consumption for both central and peripheral ECMO cases can be
primarily attributed to the severity of illness of the patient, and
that the method of cannulation is less relevant when considering the
overall resources required to treat patients on ECMO. Specifically, our
clinical advisors noted that consideration of resource consumption for
cases reporting the use of ECMO may extend well beyond the duration of
time that a patient was actively receiving ECMO treatment, which may
range anywhere from less than 24 hours to 10 days or more. As noted
above, in the absence of unique procedure codes that specify the
duration of time that a patient was receiving ECMO treatment, we cannot
ascertain from the claims data the resource use specifically
attributable to treatment with ECMO during a hospital stay. However,
when reviewing consumption of hospital resources for the cases in which
ECMO was reported during a hospital stay, the claims data clearly show
that the patients placed on ECMO typically have multiple MCC and CC
conditions. These data provide additional information on the expanding
indications for ECMO treatment as well as an indication of the
complexities and the treatment difficulty associated with these
patients. While our clinical advisors continue to believe that central
(open) ECMO may be more resource intensive and carries significant
risks for complications, including bleeding, infection, and vessel
injury because it requires an incision along the sternum (sternotomy)
and is performed for open heart surgery, they believe that the subset
of patients who require treatment with ECMO, regardless of the
cannulation method, would be similar in terms of overall hospital
resource consumption. We also note that while we do not yet have
Medicare claims data to evaluate the new peripheral ECMO procedure
codes, review of limited registry data provided by stakeholders for
patients treated with a reported peripheral ECMO procedure did not
contradict that costs for peripheral ECMO appear to be similar to the
costs of overall resources required to treat patients on ECMO
(regardless of method of cannulation) and appear to be attributable to
the severity of illness of the patient.
With regard to stakeholders who stated that the two new procedure
codes do not account for an open cut-down approach that may be
performed on a peripheral vessel during a peripheral ECMO procedure, we
note that a request and proposal to create ICD-10-PCS codes to
differentiate between peripheral vessel percutaneous and peripheral
vessel open cutdown
[[Page 19176]]
according to the indication (VA or VV) for ECMO was discussed at the
March 5-6, 2019 ICD-10 Coordination and Maintenance Committee meeting.
We refer readers to the website at: https://www.cms.gov/Medicare/Coding/ICD9ProviderDiagnosticCodes/ICD-9-CM-C-and-M-Meeting-Materials.html for the committee meeting materials and discussion
regarding this proposal. We also note that, in this same proposal,
another coding option to add duration values to allow the reporting of
the number of hours or the number of days a patient received ECMO
during the stay was also made available for public comment.
Upon further review and consideration of peripheral ECMO
procedures, including the indications, treatment difficulty, and the
resources utilized, for the reasons discussed above, our clinical
advisors support the assignment of the new ICD-10-PCS procedure codes
for peripheral ECMO procedures to the same MS-DRG as the predecessor
code for open (central) ECMO procedures for FY 2020. Therefore, based
on our review, including consideration of the comments and input from
our clinical advisors, we are proposing to reassign the following
procedure codes describing peripheral ECMO procedures from their
current MS-DRG assignments to Pre-MDC MS-DRG 003 (ECMO or Tracheostomy
with Mechanical Ventilation >96 Hours or Principal Diagnosis Except
Face, Mouth and Neck with Major O.R. Procedure) as shown in the table
below. If this proposal is finalized, we also would make conforming
changes to the titles for MS-DRGs 207, 291, 296, and 870 to no longer
reflect the ``or Peripheral Extracorporeal Membrane Oxygenation
(ECMO)'' terminology in the title. We note that this proposal includes
maintaining the designation of these peripheral ECMO procedures as non-
O.R. Therefore, if finalized, the procedures would be defined as non-
O.R. affecting the MS-DRG assignment for Pre-MDC MS-DRG 003.
----------------------------------------------------------------------------------------------------------------
ICD-10-PCS code Code description Current MS-DRG Proposed MS-DRG
----------------------------------------------------------------------------------------------------------------
5A1522G..................... Extracorporeal MS-DRG 207 (Respiratory Pre-MDC MS-DRG 003 (ECMO or
Oxygenation, Membrane, System Diagnosis with Tracheostomy with
Peripheral Veno- Ventilator Support >96 Mechanical Ventilation >96
arterial. Hours or Peripheral Hours or Principal
Extracorporeal Membrane Diagnosis Except Face,
Oxygenation (ECMO)). Mouth and Neck with Major
O.R. Procedure).
MS-DRG 291 (Heart Failure Pre-MDC MS-DRG 003 (ECMO or
and Shock with MCC or Tracheostomy with
Peripheral Extracorporeal Mechanical Ventilation >96
Membrane Oxygenation Hours or Principal
(ECMO)). Diagnosis Except Face,
Mouth and Neck with Major
O.R. Procedure).
MS-DRG 296 (Cardiac Arrest, Pre-MDC MS-DRG 003 (ECMO or
Unexplained with MCC or Tracheostomy with
Peripheral Extracorporeal Mechanical Ventilation >96
Membrane Oxygenation Hours or Principal
(ECMO)). Diagnosis Except Face,
Mouth and Neck with Major
O.R. Procedure).
MS-DRG 870 (Septicemia or Pre-MDC MS-DRG 003 (ECMO or
Severe Sepsis with Tracheostomy with
Mechanical Ventilation >96 Mechanical Ventilation >96
Hours or Peripheral Hours or Principal
Extracorporeal Membrane Diagnosis Except Face,
Oxygenation (ECMO)). Mouth and Neck with Major
O.R. Procedure).
5A1522H..................... Extracorporeal MS-DRG 207 (Respiratory Pre-MDC MS-DRG 003 (ECMO or
Oxygenation, Membrane, System Diagnosis with Tracheostomy with
Peripheral Veno-venous. Ventilator Support >96 Mechanical Ventilation >96
Hours or Peripheral Hours or Principal
Extracorporeal Membrane Diagnosis Except Face,
Oxygenation (ECMO)). Mouth and Neck with Major
O.R. Procedure).
MS-DRG 291 (Heart Failure Pre-MDC MS-DRG 003 (ECMO or
and Shock with MCC or Tracheostomy with
Peripheral Extracorporeal Mechanical Ventilation >96
Membrane Oxygenation Hours or Principal
(ECMO)). Diagnosis Except Face,
Mouth and Neck with Major
O.R. Procedure).
MS-DRG 296 (Cardiac Arrest, Pre-MDC MS-DRG 003 (ECMO or
Unexplained with MCC or Tracheostomy with
Peripheral Extracorporeal Mechanical Ventilation >96
Membrane Oxygenation Hours or Principal
(ECMO)). Diagnosis Except Face,
Mouth and Neck with Major
O.R. Procedure).
MS-DRG 870 (Septicemia or Pre-MDC MS-DRG 003 (ECMO or
Severe Sepsis with Tracheostomy with
Mechanical Ventilation >96 Mechanical Ventilation >96
Hours or Peripheral Hours or Principal
Extracorporeal Membrane Diagnosis Except Face,
Oxygenation (ECMO)). Mouth and Neck with Major
O.R. Procedure).
----------------------------------------------------------------------------------------------------------------
b. Allogeneic Bone Marrow Transplant
We received a request to create new MS-DRGs for cases that would
identify patients who undergo an allogeneic hematopoietic cell
transplant (HCT) procedure. The requestor asked us to split MS-DRG 014
(Allogeneic Bone Marrow Transplant) into two new MS-DRGs and assign
cases to the recommended new MS-DRGs according to the donor source,
with cases for allogeneic related matched donor source assigned to one
MS-DRG and cases for allogeneic unrelated matched donor source assigned
to the other MS-DRG. The requestor stated that by creating two new MS-
DRGs for allogeneic related and allogeneic unrelated donor source,
respectively, the MS-DRGs would more appropriately recognize the
clinical characteristics and cost differences in allogeneic HCT cases.
The requestor stated that allogeneic related and allogeneic
unrelated HCT cases are clinically different and have significantly
different donor search and cell acquisition charges. According to the
requestor, 70 percent of patients do not have a matched sibling donor
(that is, an allogeneic related matched donor) in their family. The
requestor also stated that this rate is higher for Medicare
beneficiaries. According to the requestor, the current payment for
allogeneic HCT cases is inadequate and affects patient's access to
care.
The requestor performed its own analysis and stated that it found
the average costs for HCT cases reporting revenue code 0815 (Stem cell
acquisition) alone or revenue code 0819 (Other organ acquisition) in
combination with revenue code 0815 with one of the ICD-10-PCS procedure
[[Page 19177]]
codes for allogeneic unrelated donor source were significantly higher
than the average costs for HCT cases reporting revenue code 0815 alone
or both revenue codes 0815 and 0819 in combination with one of the ICD-
10-PCS procedure codes for allogeneic related donor source. Further,
the requestor reported that, according to its analysis, the average
costs for HCT cases reporting revenue code 0815 alone or both revenue
codes 0815 and 0819 in combination with one of the ICD-10-PCS procedure
codes for unspecified allogeneic donor source were also significantly
higher than the average costs for HCT cases reporting the ICD-10-PCS
procedure codes for allogeneic related donor source. The requestor
suggested that cases reporting the unspecified donor source procedure
code are highly likely to represent unrelated donors, and recommended
that, if the two new MS-DRGs are created as suggested, the cases
reporting the procedure codes for unspecified donor source be included
in the suggested new ``unrelated donor'' MS-DRG. The requestor also
suggested that CMS apply a code edit through the inpatient Medicare
Code Editor (MCE), similar to the edit in the Integrated Outpatient
Code Editor (I/OCE) which requires reporting of revenue code 0815 on
the claim with the appropriate procedure code or the claim may be
subject to being returned to the provider.
The ICD-10-PCS procedure codes assigned to MS-DRG 014 that identify
related, unrelated and unspecified donor source for an allogeneic HCT
are shown in the following table.
------------------------------------------------------------------------
ICD-10-PCS code Code description
------------------------------------------------------------------------
30230G2............................. Transfusion of allogeneic related
bone marrow into peripheral vein,
open approach.
30230G3............................. Transfusion of allogeneic
unrelated bone marrow into
peripheral vein, open approach.
30230G4............................. Transfusion of allogeneic
unspecified bone marrow into
peripheral vein, open approach.
30230X2............................. Transfusion of allogeneic related
cord blood stem cells into
peripheral vein, open approach.
30230X3............................. Transfusion of allogeneic
unrelated cord blood stem cells
into peripheral vein, open
approach.
30230X4............................. Transfusion of allogeneic
unspecified cord blood stem cells
into peripheral vein, open
approach.
30230Y2............................. Transfusion of allogeneic related
hematopoietic stem cells into
peripheral vein, open approach.
30230Y3............................. Transfusion of allogeneic
unrelated hematopoietic stem
cells into peripheral vein, open
approach.
30230Y4............................. Transfusion of allogeneic
unspecified hematopoietic stem
cells into peripheral vein, open
approach.
30233G2............................. Transfusion of allogeneic related
bone marrow into peripheral vein,
percutaneous approach.
30233G3............................. Transfusion of allogeneic
unrelated bone marrow into
peripheral vein, percutaneous
approach.
30233G4............................. Transfusion of allogeneic
unspecified bone marrow into
peripheral vein, percutaneous
approach.
30233X2............................. Transfusion of allogeneic related
cord blood stem cells into
peripheral vein, percutaneous
approach.
30233X3............................. Transfusion of allogeneic
unrelated cord blood stem cells
into peripheral vein,
percutaneous approach.
30233X4............................. Transfusion of allogeneic
unspecified cord blood stem cells
into peripheral vein,
percutaneous approach.
30233Y2............................. Transfusion of allogeneic related
hematopoietic stem cells into
peripheral vein, percutaneous
approach.
30233Y3............................. Transfusion of allogeneic
unrelated hematopoietic stem
cells into peripheral vein,
percutaneous approach.
30233Y4............................. Transfusion of allogeneic
unspecified hematopoietic stem
cells into peripheral vein,
percutaneous approach.
30240G2............................. Transfusion of allogeneic related
bone marrow into central vein,
open approach.
30240G3............................. Transfusion of allogeneic
unrelated bone marrow into
central vein, open approach.
30240G4............................. Transfusion of allogeneic
unspecified bone marrow into
central vein, open approach.
30240X2............................. Transfusion of allogeneic related
cord blood stem cells into
central vein, open approach.
30240X3............................. Transfusion of allogeneic
unrelated cord blood stem cells
into central vein, open approach.
30240X4............................. Transfusion of allogeneic
unspecified cord blood stem cells
into central vein, open approach.
30240Y2............................. Transfusion of allogeneic related
hematopoietic stem cells into
central vein, open approach.
30240Y3............................. Transfusion of allogeneic
unrelated hematopoietic stem
cells into central vein, open
approach.
30240Y4............................. Transfusion of allogeneic
unspecified hematopoietic stem
cells into central vein, open
approach.
30243G2............................. Transfusion of allogeneic related
bone marrow into central vein,
percutaneous approach.
30243G3............................. Transfusion of allogeneic
unrelated bone marrow into
central vein, percutaneous
approach.
30243G4............................. Transfusion of allogeneic
unspecified bone marrow into
central vein, percutaneous
approach.
30243X2............................. Transfusion of allogeneic related
cord blood stem cells into
central vein, percutaneous
approach.
30243X3............................. Transfusion of allogeneic
unrelated cord blood stem cells
into central vein, percutaneous
approach.
30243X4............................. Transfusion of allogeneic
unspecified cord blood stem cells
into central vein, percutaneous
approach.
30243Y2............................. Transfusion of allogeneic related
hematopoietic stem cells into
central vein, percutaneous
approach.
30243Y3............................. Transfusion of allogeneic
unrelated hematopoietic stem
cells into central vein,
percutaneous approach.
30243Y4............................. Transfusion of allogeneic
unspecified hematopoietic stem
cells into central vein,
percutaneous approach.
30250G1............................. Transfusion of nonautologous bone
marrow into peripheral artery,
open approach.
30250X1............................. Transfusion of nonautologous cord
blood stem cells into peripheral
artery, open approach.
30250Y1............................. Transfusion of nonautologous
hematopoietic stem cells into
peripheral artery, open approach.
30253G1............................. Transfusion of nonautologous bone
marrow into peripheral artery,
percutaneous approach.
30253X1............................. Transfusion of nonautologous cord
blood stem cells into peripheral
artery, percutaneous approach.
30253Y1............................. Transfusion of nonautologous
hematopoietic stem cells into
peripheral artery, percutaneous
approach.
30260G1............................. Transfusion of nonautologous bone
marrow into central artery, open
approach.
30260X1............................. Transfusion of nonautologous cord
blood stem cells into central
artery, open approach.
30260Y1............................. Transfusion of nonautologous
hematopoietic stem cells into
central artery, open approach.
30263G1............................. Transfusion of nonautologous bone
marrow into central artery,
percutaneous approach.
30263X1............................. Transfusion of nonautologous cord
blood stem cells into central
artery, percutaneous approach.
30263Y1............................. Transfusion of nonautologous
hematopoietic stem cells into
central artery, percutaneous
approach.
------------------------------------------------------------------------
We examined claims data from the September 2018 update of the FY
2018 MedPAR file for MS-DRG 014 and identified the subset of cases
within MS-DRG 014 reporting procedure codes for allogeneic HCT related
donor source, allogeneic HCT unrelated donor source, and allogeneic HCT
unspecified donor source, respectively. Our findings are shown in the
following table.
[[Page 19178]]
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 014--All cases........................................... 854 28.2 $91,446
MS-DRG 014--Cases reporting allogeneic HCT related donor source. 292 29.5 87,444
MS-DRG 014--Cases reporting allogeneic HCT unrelated donor 466 27.9 95,146
source.........................................................
MS-DRG 014--Cases reporting allogeneic HCT unspecified donor 90 26.2 90,945
source.........................................................
----------------------------------------------------------------------------------------------------------------
The total number of cases reported in MS-DRG 014 was 854, with an
average length of stay of 28.2 days and average costs of $91,446. For
the subset of cases reporting procedure codes for allogeneic HCT
related donor source, there were a total of 292 cases with an average
length of stay of 29.5 days and average costs of $87,444. For the
subset of cases reporting procedure codes for allogeneic HCT unrelated
donor source, there was a total of 466 cases with an average length of
stay of 27.9 days and average costs of $95,146. For the subset of cases
reporting procedure codes for allogeneic HCT unspecified donor source,
there was a total of 90 cases with an average length of stay of 26.2
days and average costs of $90,945.
Based on the analysis described above, the current MS-DRG
assignment for the cases in MS-DRG 014 that identify patients who
undergo an allogeneic HCT procedure, regardless of donor source,
appears appropriate. The data analysis reflects that each subset of
cases reporting a procedure code for an allogeneic HCT procedure (that
is, related, unrelated, or unspecified donor source) has an average
length of stay and average costs that are comparable to the average
length of stay and average costs of all cases in MS-DRG 014. We also
take this opportunity to note that, in deciding whether to propose to
make further modifications to the MS-DRGs for particular circumstances
brought to our attention, we do not consider the reported revenue
codes. Rather, as stated previously, we consider whether the resource
consumption and clinical characteristics of the patients with a given
set of conditions are significantly different than the remaining
patients represented in the MS-DRG. We do this by evaluating the ICD-
10-CM diagnosis and/or ICD-10-PCS procedure codes that identify the
patient conditions, procedures, and the relevant MS-DRG(s) that are the
subject of a request. Specifically, for this request, as noted above,
we analyzed the cases reporting the ICD-10-PCS procedure codes that
identify an allogeneic HCT procedure according to the donor source. We
then evaluated patient care costs using average costs and average
lengths of stay (based on the MedPAR data) and rely on the judgment of
our clinical advisors to determine whether the patients are clinically
distinct or similar to other patients represented in the MS-DRG.
Because MS-DRG 014 is defined by patients who undergo an allogeneic HCT
transplant procedure, our clinical advisors state they are all
clinically similar in that regard. We also note that the ICD-10-PCS
procedure codes that describe an allogeneic HCT procedure were revised
effective October 1, 2016 to uniquely identify the donor source in
response to a request and proposal that was discussed at the March 9-
10, 2016 ICD-10 Coordination and Maintenance Committee meeting. We
refer readers to the website at: https://www.cms.gov/Medicare/Coding/ICD9Provider DiagnosticCodes/ICD-9-CM-C-and-M-Meeting-Materials.html
for the committee meeting materials and discussion regarding this
proposal.
In response to the requestor's statement that allogeneic related
and allogeneic unrelated HCT cases are clinically different and have
significantly different donor search and cell acquisition charges, our
clinical advisors support maintaining the current structure for MS-DRG
014 because they believe that MS-DRG 014 appropriately classifies all
patients who undergo an allogeneic HCT procedures and, therefore, it is
clinically coherent. While the requestor stated that there are clinical
differences in the related and unrelated HCT cases, they did not
provide any specific examples of these clinical differences. With
regard to the donor search and cell acquisition charges, the requestor
noted that the unrelated donor cases are more expensive than the
related donor cases because of the donor search process, which includes
a registry search to identify the best donor source, extensive donor
screenings, evaluation, and cell acquisition and transportation
services for the patient. The requestor appeared to base that belief
according to the donor source and average charges reported with revenue
code 0815. As noted above, we use MedPAR data and do not consider the
reported revenue codes in deciding whether to propose to make further
modifications to the MS-DRGs. Based on our analysis of claims data for
MS-DRG 014, our clinical advisors stated that the resources are similar
for patients who undergo an allogeneic HCT procedure regardless of the
donor source.
In reviewing this request, we also reviewed the instructions on
billing for stem cell transplantation in Chapter 3 of the Medicare
Claims Processing Manual and found that there appears to be inadvertent
duplication under Section 90.3.1 and Section 90.3.3 of Chapter 3, as
both sections provide instructions on Billing for Stem Cell
Transplantation. Therefore, we are further reviewing the Medicare
Claims Processing Manual to identify potential revisions to address
this duplication. However, we also note that section 90.3.1 and section
90.3.3 provide different instruction regarding which revenue code
should be reported. Section 90.3.1 instructs providers to report
revenue code 0815 and Section 90.3.3 instructs providers to report
revenue code 0819. We note that we issued instructions as a One-Time
Notification, Pub. No. 100-04, Transmittal 3571, Change Request 9674,
effective January 1, 2017, which instructs that the appropriate revenue
code to report on claims for allogeneic stem cell acquisition/donor
services is revenue code 0815. Accordingly, we also are considering
additional revisions as needed to conform the instructions for
reporting these codes in the Medicare Claims Processing Manual.
With regard to the requestor's recommendation that we create a new
code edit through the inpatient MCE similar to the edit in the I/OCE
which requires reporting of revenue code 0815 on the claim, we note
that the MCE is not designed to include revenue codes for claims
editing purposes. Rather, as stated in section II.F.16. of the preamble
of this proposed rule, it is a software program that detects and
reports errors in the coding of Medicare claims data. The coding of
Medicare claims data refers to diagnosis and procedure coding, as well
as demographic information.
For the reasons described above, we are not proposing to change the
current structure of MS-DRG 014. We are not proposing to split MS-DRG
014 into two new MS-DRGs that assign cases according to whether the
allogeneic donor source is related or unrelated, as the requestor
suggested.
In addition, while conducting our analysis of cases reporting ICD-
10-PCS
[[Page 19179]]
procedure codes for allogeneic HCT procedures that are assigned to MS-
DRG 014, we noted that 8 procedure codes for autologous HCT procedures
are currently included in MS-DRG 014, as shown in the following table.
These codes are not properly assigned because MS-DRG 014 is defined by
cases reporting allogenic HCT procedures.
------------------------------------------------------------------------
ICD-10-PCS code Code description
------------------------------------------------------------------------
30230X0............................. Transfusion of autologous cord
blood stem cells into peripheral
vein, open approach.
30233X0............................. Transfusion of autologous cord
blood stem cells into peripheral
vein, percutaneous approach.
30240X0............................. Transfusion of autologous cord
blood stem cells into central
vein, open approach.
30243X0............................. Transfusion of autologous cord
blood stem cells into central
vein, percutaneous approach.
30250X0............................. Transfusion of autologous cord
blood stem cells into peripheral
artery, open approach.
30253X0............................. Transfusion of autologous cord
blood stem cells into peripheral
artery, percutaneous approach.
30260X0............................. Transfusion of autologous cord
blood stem cells into central
artery, open approach.
30263X0............................. Transfusion of autologous cord
blood stem cells into central
artery, percutaneous approach.
------------------------------------------------------------------------
The 8 ICD-10-PCS procedure codes for autologous HCT procedures were
inadvertently included in MS-DRG 014 as a result of efforts to
replicate the ICD-9-CM MS-DRGs. Under the ICD-9-CM MS-DRGs, procedure
code 41.06 (Cord blood stem cell transplant) was used to identify these
procedures and was also assigned to MS-DRG 014. As shown in the ICD-9-
CM code description, the reference to ``autologous'' is not included.
However, because the ICD-10-PCS autologous HCT procedure codes were
considered as plausible translations of the ICD-9-CM procedure code
(41.06), they were inadvertently included in MS-DRG 014. We also note
that, of these 8 procedure codes, there are 4 procedure codes that
describe a transfusion via arterial access. As described in more detail
below, because a transfusion procedure always uses venous access rather
than arterial access, these codes are considered clinically invalid and
were the subject of a proposal discussed at the March 5-6, 2019 ICD-10
Coordination and Maintenance Committee meeting to delete these codes
effective October 1, 2019 (FY 2020).
The majority of ICD-10-PCS procedure codes specifying autologous
HCT procedures are currently assigned to MS-DRGs 016 and 017
(Autologous Bone Marrow Transplant with CC/MCC or T-cell Immunotherapy
and Autologous Bone Marrow Transplant without CC/MCC, respectively).
These codes are listed in the following table.
------------------------------------------------------------------------
ICD-10-PCS code Code description
------------------------------------------------------------------------
30230AZ............................. Transfusion of embryonic stem
cells into peripheral vein, open
approach.
30230G0............................. Transfusion of autologous bone
marrow into peripheral vein, open
approach.
30230Y0............................. Transfusion of autologous
hematopoietic stem cells into
peripheral vein, open approach.
30233AZ............................. Transfusion of embryonic stem
cells into peripheral vein,
percutaneous approach.
30233G0............................. Transfusion of autologous bone
marrow into peripheral vein,
percutaneous approach.
30233Y0............................. Transfusion of autologous
hematopoietic stem cells into
peripheral vein, percutaneous
approach.
30240AZ............................. Transfusion of embryonic stem
cells into central vein, open
approach.
30240G0............................. Transfusion of autologous bone
marrow into central vein, open
approach.
30240Y0............................. Transfusion of autologous
hematopoietic stem cells into
central vein, open approach.
30243AZ............................. Transfusion of embryonic stem
cells into central vein,
percutaneous approach.
30243G0............................. Transfusion of autologous bone
marrow into central vein,
percutaneous approach.
30243Y0............................. Transfusion of autologous
hematopoietic stem cells into
central vein, percutaneous
approach.
30250G0............................. Transfusion of autologous bone
marrow into peripheral artery,
open approach.
30250Y0............................. Transfusion of autologous
hematopoietic stem cells into
peripheral artery, open approach.
30253G0............................. Transfusion of autologous bone
marrow into peripheral artery,
percutaneous approach.
30253Y0............................. Transfusion of autologous
hematopoietic stem cells into
peripheral artery, percutaneous
approach.
30260G0............................. Transfusion of autologous bone
marrow into central artery, open
approach.
30260Y0............................. Transfusion of autologous
hematopoietic stem cells into
central artery, open approach.
30263G0............................. Transfusion of autologous bone
marrow into central artery,
percutaneous approach.
30263Y0............................. Transfusion of autologous
hematopoietic stem cells into
central artery, percutaneous
approach.
------------------------------------------------------------------------
While we believe, as indicated, that the cases reporting ICD-10-PCS
procedure codes for autologous HCT procedures may be improperly
assigned to MS-DRG 014, we also examined claims data for this subset of
cases to determine the frequency with which they were reported and the
relative resource use as compared with all cases assigned to MS-DRGs
016 and 017. Our findings are shown in the following table.
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 014--Cases reporting autologous cord blood stem cell 6 23.5 $38,319
donor source...................................................
MS-DRG 016--All cases........................................... 2,150 18 47,546
MS-DRG 017--All cases........................................... 104 11 33,540
----------------------------------------------------------------------------------------------------------------
For the subset of cases in MS-DRG 014 reporting ICD-10-PCS codes
for autologous HCT procedures, there was a total of 6 cases with an
average length of stay of 23.5 days and average costs of $38,319. The
total number of cases reported in MS-DRG 016 was 2,150, with an average
length of stay of 18 days and average costs of $47,546. The total
number of cases reported in MS-DRG 017 was 104, with an average length
of
[[Page 19180]]
stay of 11 days and average costs of $33,540.
The results of our analysis indicate that the frequency with which
these autologous HCT procedure codes was reported in MS-DRG 014 is low
and that average costs of cases reporting autologous HCT procedures
assigned to MS-DRG 014 are more aligned with the average costs of cases
assigned to MS-DRGs 016 and 017, with the average costs being lower
than the average costs for all cases assigned to MS-DRG 016 and higher
than the average costs for all cases assigned to MS-DRG 017. Our
clinical advisors also indicated that the procedure codes for
autologous HCT procedures are more clinically aligned with cases that
are assigned to MS-DRGs 016 and 017 that are comprised of autologous
HCT procedures. Therefore, we are proposing to reassign the following 4
procedure codes for HCT procedures specifying autologous cord blood
stem cell as the donor source via venous access to MS-DRGs 016 and 017
for FY 2020.
------------------------------------------------------------------------
ICD-10-PCS code Code description
------------------------------------------------------------------------
30230X0............................. Transfusion of autologous cord
blood stem cells into peripheral
vein, open approach.
30233X0............................. Transfusion of autologous cord
blood stem cells into peripheral
vein, percutaneous approach.
30240X0............................. Transfusion of autologous cord
blood stem cells into central
vein, open approach.
30243X0............................. Transfusion of autologous cord
blood stem cells into central
vein, percutaneous approach.
------------------------------------------------------------------------
As discussed earlier in this section, the 4 procedure codes for HCT
procedures that describe an autologous cord blood stem cell transfusion
via arterial access currently assigned to MS-DRG 014, as listed
previously, are considered clinically invalid. These procedure codes
were discussed at the March 5-6, 2019 ICD-10 Coordination and
Maintenance Committee meeting, along with additional procedure codes
that are also considered clinically invalid, as described in the
section below.
During our analysis of procedure codes that describe a HCT
procedure, we identified 128 clinically invalid codes from the
transfusion table (table 302) in the ICD-10-PCS classification
identifying a transfusion using arterial access, as listed in Table
6P.1a. associated with this proposed rule (which is available via the
internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html). As shown in
Table 6P.1a., these 128 procedure codes describe transfusion procedures
with body system/region values ``5'' Peripheral Artery and ``6''
Central Artery. Because a transfusion procedure always uses venous
access rather than arterial access, these codes are considered
clinically invalid and were proposed for deletion at the March 5-6,
2019 ICD-10 Coordination and Maintenance Committee meeting. We refer
the reader to the website at: https://www.cms.gov/Medicare/Coding/ICD10/C-and-M-Meeting-Materials.html for the Committee meeting
materials regarding this proposal.
We examined claims data from the September 2018 update of the FY
2018 MedPAR file for MS-DRGs 014, 016, and 017 to determine if there
were any cases that reported one of the 128 clinically invalid codes
from the transfusion table in the ICD-10-PCS classification identifying
a transfusion using arterial access, and as listed in Table 6P.1a.
associated with this proposed rule. Our clinical advisors agree that
because a transfusion procedure always uses venous access rather than
arterial access, these codes are considered invalid. Because these
procedure codes describe clinically invalid procedures, we would not
expect these codes to be reported in any claims data. Our findings are
shown in the following table.
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRGs 014, 016, and 017--All cases............................ 3,108 20.4 $59,140
MS-DRGs 014, 016, and 017--Cases with invalid transfusion codes. 31 19.6 52,912
----------------------------------------------------------------------------------------------------------------
As shown in this table, we found a total of 3,108 cases across MS-
DRGs 014, 016, and 017 with an average length of stay of 20.4 days and
average costs of $59,140. We found a total of 31 cases (0.9 percent)
reporting a procedure code for an invalid transfusion procedure,
identifying the body system/region value ``5'' Peripheral Artery or
``6'' Central Artery, with an average length of stay of 19.6 days and
average costs of $52,912. The results of the data analysis demonstrate
that these invalid transfusion procedures represent approximately 1
percent of all discharges across MS-DRGs 014, 016, and 017. To
summarize, we are proposing to: (1) Reassign the four ICD-10-PCS codes
for HCT procedures specifying autologous cord blood stem cell as the
donor source from MS-DRG 014 to MS-DRGs 016 and 017 (procedure codes
30230X0, 30233X0, 30240X0, 30243X0); and (2) delete the 128 clinically
invalid codes from the transfusion table in the ICD-10-PCS
Classification describing a transfusion using arterial access that were
discussed at the March 5-6, 2019 ICD-10 Coordination and Maintenance
Committee meeting and are listed in Table 6P.1a associated with this
proposed rule. As discussed previously, we are not proposing to split
MS-DRG 014 into the two requested new MS DRGs that would assign cases
according to whether the allogeneic donor source is related or
unrelated.
c. Chimeric Antigen Receptor (CAR) T-Cell Therapies
We received a request to create a new MS-DRG for procedures
involving CAR T-cell therapies. The requestor stated that creation of a
new MS-DRG would improve payment for CAR T-cell therapies in the
inpatient setting. According to the requestor, while cases involving
CAR T-cell therapy may now be eligible for new technology add-on
payments and outlier payments, there continue to be significant
financial losses by providers. The requestor also suggested that CMS
modify its existing payment mechanisms to use a CCR of 1.0 for charges
associated with CAR T-cell therapy.
In addition, the requestor included technical and operational
suggestions related to CAR T-cell therapy, such as
[[Page 19181]]
the development of unique CAR T-cell therapy revenue and cost centers
for billing and cost reporting purposes. We will consider these
technical and operational suggestions in the development of future
billing and cost reporting guidelines and instructions.
Currently, procedures involving CAR T-cell therapies are identified
with ICD-10-PCS procedure codes XW033C3 (Introduction of engineered
autologous chimeric antigen receptor t-cell immunotherapy into
peripheral vein, percutaneous approach, new technology group 3) and
XW043C3 (Introduction of engineered autologous chimeric antigen
receptor t-cell immunotherapy into central vein, percutaneous approach,
new technology group 3), which became effective October 1, 2017. In the
FY 2019 IPPS/LTCH PPS final rule, we finalized our proposal to assign
cases reporting these ICD-10-PCS procedure codes to Pre-MDC MS-DRG 016
for FY 2019 and to revise the title of this MS-DRG to ``Autologous Bone
Marrow Transplant with CC/MCC or T-cell Immunotherapy''. We refer
readers to section II.F.2.d. of the preamble of the FY 2019 IPPS/LTCH
PPS final rule for a complete discussion of these final policies (83 FR
41172 through 41174).
As stated earlier, the current procedure codes for CAR T-cell
therapies both became effective October 1, 2017. In the FY 2019 IPPS/
LTCH PPS final rule (83 FR 41172 through 41174), we indicated we should
collect more comprehensive clinical and cost data before considering
assignment of a new MS-DRG to these therapies. While the September 2018
update of the FY 2018 MedPAR data file does contain some claims that
include those procedure codes that identify CAR T-cell therapies, the
number of cases is limited, and the submitted costs vary widely due to
differences in provider billing and charging practices for this
therapy. Therefore, while these claims could potentially be used to
create relative weights for a new MS-DRG, we do not have the
comprehensive clinical and cost data that we generally believe are
needed to do so. Furthermore, given the relative newness of CAR T-cell
therapy and our proposal to continue new technology add-on payments for
FY 2020 for the two CAR T-cell therapies that currently have FDA
approval (KYMRIAHTM and YESCARTATM), as discussed
in section II.G.4.d. of the preamble of this proposed rule, at this
time we believe it may be premature to consider creation of a new MS-
DRG specifically for cases involving CAR T-cell therapy for FY 2020.
Therefore, we are proposing not to modify the current MS-DRG
assignment for cases reporting CAR T-cell therapies for FY 2020. As
noted earlier, cases reporting ICD-10-PCS codes XW033C3 and XW043C3
would continue to be eligible to receive new technology add-on payments
for discharges occurring in FY 2020 if our proposal to continue such
payments is finalized. Currently, we expect that, in future years, we
would have additional data that exhibit more stability and greater
consistency in charging and billing practices that could be used to
evaluate the potential creation of a new MS-DRG specifically for cases
involving CAR T-cell therapies.
Alternatively, notwithstanding our concerns regarding the claims
data, and the concerns discussed in the FY 2019 IPPS/LTCH PPS final
rule (83 FR 41172 to 41174), we are seeking public comments on payment
alternatives for CAR T-cell therapies, including payment under any
potential new MS-DRG. We also are inviting public comments on how these
payment alternatives would affect access to care, as well as how they
affect incentives to encourage lower drug prices, which is a high
priority for this Administration. As discussed in the FY 2019 IPPS/LTCH
PPS final rule (83 FR 41172 through 41174), we are considering
approaches and authorities to encourage value-based care and lower drug
prices. We are soliciting public comments on how the effective dates of
any potential payment methodology alternatives, if any were to be
adopted, may intersect and affect future participation in any such
alternative approaches.
As part of our solicitation of public comment on the potential
creation of a new MS-DRG for CAR T-cell therapy procedures, we are also
seeking comment on the most appropriate way to develop the relative
weight if we were to finalize the creation of a new MS-DRG. While the
data are limited, it may be operationally possible to create a relative
weight by dividing the average costs of cases that include the CAR T-
cell procedures by the average costs of all cases, consistent with our
current methodology for setting the relative weights for FY 2020 and
using the same applicable data sources used for other MS-DRGs (for FY
2020, the FY 2018 MedPAR data and FY 2016 HCRIS data). We are seeking
public comments on whether this is the most accurate method for
determining the relative weight, given the current variation in the
claims data for these procedures, and also on how to address the
significant number of cases involving clinical trials. While we do not
typically exclude cases in clinical trials when developing the relative
weights, in this case, the absence of the drug costs on claims for
cases involving clinical trial claims could have a significant impact
on the relative weight. It is unclear whether a relative weight
calculated using cases for which hospitals do and do not incur drug
costs would accurately reflect the resource costs of caring for
patients who are not involved in clinical trials. A different approach
might be to develop a relative weight using an appropriate portion of
the average sales price (ASP) for these drugs as an alternative way to
reflect the costs involved in treating patients receiving CAR T-cell
therapies. We are requesting public comments on these approaches or
other approaches for setting the relative weight if we were to finalize
a new MS-DRG. We note that any such new MS-DRG would be established in
a budget neutral manner, consistent with section 1886(d)(4)(C)(iii) of
the Act, which specifies that the annual DRG reclassification and
recalibration of the relative weights must be made in a manner that
ensures that aggregate payments to hospitals are not affected.
Another potential consideration if we were to create a new MS-DRG
is the extent to which it would be appropriate to geographically adjust
the payment under any such new MS-DRG. Under the methodology for
determining the Federal payment rate for operating costs under the
IPPS, the labor-related proportion of the national standardized amounts
is adjusted by the wage index to reflect the relative differences in
labor costs among geographic areas. The IPPS Federal payment rate for
operating costs is calculated as the MS-DRG relative weight x [(labor-
related applicable standardized amount x applicable wage index) +
(nonlabor-related applicable standardized amount x cost-of-living
adjustment)]. Given our understanding that the costs for CAR T-cell
therapy drugs do not vary among geographic areas, and given that costs
for CAR T-cell therapy would likely be an extremely high portion of the
costs for the MS-DRG, we are seeking public comments on whether we
should not geographically adjust the payment for cases assigned to any
potential new MS-DRG for CAR T-cell therapy procedures. We also are
seeking public comments on whether to instead apply the geographic
adjustment to a lower proportion of payments under any potential new
MS-DRG and, if so, how that lower proportion should be determined. We
note that while the prices of other drugs may also not vary
significantly among geographic areas, generally speaking, those other
drugs would not have estimated costs as high
[[Page 19182]]
as those of CAR T-cell therapies, nor would they represent as
significant a percentage of the average costs for the case. We are
seeking public comments on the use of our exceptions and adjustments
authority under section 1886(d)(5)(I) of the Act (or other relevant
authorities) to implement any such potential changes.
Section 1886(d)(5)(B) of the Act provides that prospective payment
hospitals that have residents in an approved graduate medical education
(GME) program receive an additional payment for a Medicare discharge to
reflect the higher patient care costs of teaching hospitals relative to
nonteaching hospitals. The regulations regarding the calculation of
this additional payment, known as the indirect medical education (IME)
adjustment, are located at 42 CFR 412.105. The formula is traditionally
described in terms of a certain percentage increase in payment for
every 10-percent increase in the resident-to-bed ratio. For some
hospitals, this percentage increase can exceed an additional 25 percent
or more of the otherwise applicable payment. Some hospitals, sometimes
the same hospitals, can also receive a large percentage increase in
payments due to the Medicare disproportionate hospital (DSH) adjustment
provision under section 1886(d)(5)(F) of the Act. The regulations
regarding the calculation of the additional DSH payment are located at
42 CFR 412.106.
Given that the payment for cases assigned to a new MS-DRG for CAR
T-cell therapy could significantly exceed the historical payment for
any existing MS-DRG, these percentage add-on payments could arguably
result in unreasonably high additional payments for CAR T-cell therapy
cases unrelated in any significant empirical way to the costs of the
hospital in providing care. For example, consider a teaching hospital
that has an IME adjustment factor of 0.25, and a DSH adjustment factor
of 0.10. If we were to create a new MS-DRG for CAR T-cell therapy
procedures that resulted in an average IPPS Federal payment rate for
operating costs of $400,000, under the current payment mechanism, the
hospital would receive an IME payment of $100,000 ($400,000 x 0.25) and
a DSH payment of $40,000 ($400,000 x 0.10), such that the total IPPS
Federal payment rate for operating costs including IME and DSH payments
would be $540,000 ($400,000 + $100,000 + $40,000). We are seeking
public comments on whether the IME and DSH payments should not be made
for cases assigned to any new MS-DRG for CAR T-cell therapy. We also
are seeking public comments on whether we should instead reduce the
applicable percentages used to determine these add-ons and, if so, how
those lower percentages should be determined. We are seeking public
comments on the use of our exceptions and adjustments authority under
section 1886(d)(5)(I) of the Act (or other relevant authorities) to
implement any potential changes.
As further discussed section II.G.7. of the preamble to this
proposed rule, we are also requesting public comment on other payment
alternatives for these cases, including eliminating the use of the CCR
in calculating the new technology add-on payment for KYMRIAH[supreg]
and YESCARTA[supreg] by making a uniform add-on payment that equals the
proposed maximum add-on payment, that is, 65 percent of the cost of the
technology (in accordance with the proposed increase in the calculation
of the maximum new technology add-on payment amount), which in this
instance would be $242,450; and/or using a higher percentage than the
proposed 65 percent to calculate the maximum new technology add-on
payment amount.
We are also requesting public comments on whether, in light of the
additional experience with billing and payment for cases involving CAR
T-cell therapies to Medicare patients, we should consider utilizing a
specific CCR for ICD-10-PCS procedure codes used to report the
performance of procedures involving the use of CAR T-cell therapies;
for example, a CCR of 1.0, when determining outlier payments, when
determining the new technology add-on payments, and when determining
payments to IPPS-excluded cancer hospitals for CAR T-cell therapies.
We note that we also considered this payment alternative for FY
2019, as discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41172
through 41174). We indicated in that rulemaking that such a payment
alternative might use a CCR of 1.0 for charges associated with ICD-10-
PCS procedure codes XW033C3 and XW043C3, given that many public
inquirers believed that hospitals would be unlikely to set charges
different from the costs for KYMRIAH[supreg] and YESCARTA[supreg] CAR
T-cell therapies. We also indicated such a change would result in a
higher outlier payment, higher new technology add-on payment, or the
determination of higher costs for IPPS-excluded cancer hospital cases.
For example, and as described in the FY 2019 IPPS LTCH PPS final rule
(83 FR 41773), if a hospital charged $400,000 for the procedure
described by ICD-10-PCS procedure code XW033C3, the application of a
hypothetical CCR of 0.25 results in a cost of $100,000 (= $400,000 *
0.25) while the application of a hypothetical CCR of 1.00 results in a
cost of $400,000 (= $400,000 * 1.0).
3. MDC 1 (Diseases and Disorders of the Nervous System): Carotid Artery
Stent Procedures
The logic for case assignment to MS-DRGs 034, 035, and 036 (Carotid
Artery Stent Procedures with MCC, with CC, and without CC/MCC,
respectively) as displayed in the ICD-10 MS-DRG Version 36 Definitions
Manual (which is available via the internet on the CMS website at:
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.html) is
comprised of two lists of logic that include procedure codes for
operating room (O.R.) procedures involving dilation of a carotid artery
(common, internal or external) with intraluminal device(s). The first
list of logic is entitled ``Operating Room Procedures'' and the second
list of logic is entitled ``Operating Room Procedures with Operating
Room Procedures''. We identified 46 ICD-10-PCS procedure codes in the
second logic list that do not describe dilation of a carotid artery
with an intraluminal device. Of these 46 procedure codes, we identified
24 codes describing dilation of a carotid artery without an
intraluminal device; 8 codes describing dilation of the vertebral
artery; and 14 codes describing dilation of a vein (jugular, vertebral
and face), as shown in the following table.
ICD-10 PCS Codes That Involve Dilation of a Neck Artery or Vein With and
Without an Intraluminal Device
------------------------------------------------------------------------
ICD-10-PCS code Code description
------------------------------------------------------------------------
037H3Z6............................. Dilation of right common carotid
artery, bifurcation, percutaneous
approach.
037H3ZZ............................. Dilation of right common carotid
artery, percutaneous approach.
[[Page 19183]]
037H4Z6............................. Dilation of right common carotid
artery, bifurcation, percutaneous
endoscopic approach.
037H4ZZ............................. Dilation of right common carotid
artery, percutaneous endoscopic
approach.
037J3Z6............................. Dilation of left common carotid
artery, bifurcation, percutaneous
approach.
037J3ZZ............................. Dilation of left common carotid
artery, percutaneous approach.
037J4Z6............................. Dilation of left common carotid
artery, bifurcation, percutaneous
endoscopic approach.
037J4ZZ............................. Dilation of left common carotid
artery, percutaneous endoscopic
approach.
037K3Z6............................. Dilation of right internal carotid
artery, bifurcation, percutaneous
approach.
037K3ZZ............................. Dilation of right internal carotid
artery, percutaneous approach.
037K4Z6............................. Dilation of right internal carotid
artery, bifurcation, percutaneous
endoscopic approach.
037K4ZZ............................. Dilation of right internal carotid
artery, percutaneous endoscopic
approach.
037L3Z6............................. Dilation of left internal carotid
artery, bifurcation, percutaneous
approach.
037L3ZZ............................. Dilation of left internal carotid
artery, percutaneous approach.
037L4Z6............................. Dilation of left internal carotid
artery, bifurcation, percutaneous
endoscopic approach.
037L4ZZ............................. Dilation of left internal carotid
artery, percutaneous endoscopic
approach.
037M3Z6............................. Dilation of right external carotid
artery, bifurcation, percutaneous
approach.
037M3ZZ............................. Dilation of right external carotid
artery, percutaneous approach.
037M4Z6............................. Dilation of right external carotid
artery, bifurcation, percutaneous
endoscopic approach.
037M4ZZ............................. Dilation of right external carotid
artery, percutaneous endoscopic
approach.
037N3Z6............................. Dilation of left external carotid
artery, bifurcation, percutaneous
approach.
037N3ZZ............................. Dilation of left external carotid
artery, percutaneous approach.
037N4Z6............................. Dilation of left external carotid
artery, bifurcation, percutaneous
endoscopic approach.
037N4ZZ............................. Dilation of left external carotid
artery, percutaneous endoscopic
approach.
037P3Z6............................. Dilation of right vertebral
artery, bifurcation, percutaneous
approach.
037P3ZZ............................. Dilation of right vertebral
artery, percutaneous approach.
037P4Z6............................. Dilation of right vertebral
artery, bifurcation, percutaneous
endoscopic approach.
037P4ZZ............................. Dilation of right vertebral
artery, percutaneous endoscopic
approach.
037Q3Z6............................. Dilation of left vertebral artery,
bifurcation, percutaneous
approach.
037Q3ZZ............................. Dilation of left vertebral artery,
percutaneous approach.
037Q4Z6............................. Dilation of left vertebral artery,
bifurcation, percutaneous
endoscopic approach.
037Q4ZZ............................. Dilation of left vertebral artery,
percutaneous endoscopic approach.
057M3DZ............................. Dilation of right internal jugular
vein with intraluminal device,
percutaneous approach.
057M4DZ............................. Dilation of right internal jugular
vein with intraluminal device,
percutaneous endoscopic approach.
057N3DZ............................. Dilation of left internal jugular
vein with intraluminal device,
percutaneous approach.
057N4DZ............................. Dilation of left internal jugular
vein with intraluminal device,
percutaneous endoscopic approach.
057P3DZ............................. Dilation of right external jugular
vein with intraluminal device,
percutaneous approach.
057P4DZ............................. Dilation of right external jugular
vein with intraluminal device,
percutaneous endoscopic approach.
057Q3DZ............................. Dilation of left external jugular
vein with intraluminal device,
percutaneous approach.
057Q4DZ............................. Dilation of left external jugular
vein with intraluminal device,
percutaneous endoscopic approach.
057R3DZ............................. Dilation of left vertebral vein
with intraluminal device,
percutaneous approach.
057R4DZ............................. Dilation of right vertebral vein
with intraluminal device,
percutaneous endoscopic approach.
057S3DZ............................. Dilation of left vertebral vein
with intraluminal device,
percutaneous approach.
057S4DZ............................. Dilation of left vertebral vein
with intraluminal device,
percutaneous endoscopic approach.
057T3DZ............................. Dilation of right face vein with
intraluminal device, percutaneous
approach.
057T4DZ............................. Dilation of right face vein with
intraluminal device, percutaneous
endoscopic approach.
------------------------------------------------------------------------
We examined claims data from the September 2018 update of the FY
2018 MedPAR file for MS-DRGs 034, 035, and 036 and identified cases
reporting any one of the 46 ICD-10-PCS procedure codes listed in the
tables above. Our findings are shown in the following table.
MS-DRGs for Carotid Artery Stent Procedures
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 034--All cases........................................... 863 6.8 $27,600
MS-DRG 034--Cases with procedure code other than dilation of a 15 8.8 36,596
carotid artery with an intraluminal device.....................
MS-DRG 035--All cases........................................... 2,369 3 16,731
MS-DRG 035--Cases with procedure code other than dilation of a 52 3.5 17,815
carotid artery with an intraluminal device.....................
MS-DRG 036--All cases........................................... 3,481 1.4 12,637
MS-DRG 036--Cases with procedure code other than dilation of a 67 1.4 12,621
carotid artery with an intraluminal device.....................
----------------------------------------------------------------------------------------------------------------
As shown in the table above, we found a total of 863 cases with an
average length of stay of 6.8 days and average costs of $27,600 in MS-
DRG 034. There were 15 cases reporting at least one of the 46 procedure
codes that
[[Page 19184]]
do not describe dilation of the carotid artery with an intraluminal
device in MS-DRG 034 with an average length of stay of 8.8 days and
average costs of $36,596. For MS-DRG 035, we found a total of 2,369
cases with an average length of stay of 3 days and average costs of
$16,731. There were 52 cases reporting at least one of the 46 procedure
codes that do not describe dilation of the carotid artery with an
intraluminal device in MS-DRG 035 with an average length of stay of 3.5
days and average costs of $17,815. For MS-DRG 036, we found a total of
3,481 cases with an average length of stay of 1.4 days and average
costs of $12,637. There were 67 cases reporting at least one of the 46
procedure codes that do not describe dilation of the carotid artery
with an intraluminal device in MS-DRG 036 with an average length of
stay of 1.4 days and average costs of $12,621.
Our clinical advisors stated that MS-DRGs 034, 035, and 036 are
defined to include only those procedure codes that describe procedures
that involve dilation of a carotid artery with an intraluminal device.
Therefore, we are proposing to remove the procedure codes listed in the
table above from MS-DRGs 034, 035, and 036 that describe procedures
which (1) do not include an intraluminal device; (2) describe
procedures performed on arteries other than a carotid; and (3) describe
procedures performed on a vein.
The 46 ICD-10-PCS procedure codes listed in the table above are
also assigned to MS-DRGs 037, 038, and 039 (Extracranial Procedures
with MCC, with CC, and without CC/MCC, respectively). Therefore, we
also examined claims data from the September 2018 update of the FY 2018
MedPAR file for MS-DRGs 037, 038, and 039. Our findings are shown in
the following table.
MS-DRGs for Extracranial Procedures
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 037--All cases........................................... 3,612 7.1 $23,703
MS-DRG 038--All cases........................................... 11,406 3.1 12,480
MS-DRG 039--All cases........................................... 22,938 1.5 8,400
----------------------------------------------------------------------------------------------------------------
We found a total of 3,612 cases in MS-DRG 037 with an average
length of stay of 7.1 days and average costs of $23,703. We found a
total of 11,406 cases in MS-DRG 038 with an average length of stay of
3.1 days and average costs of $12,480. We found a total of 22,938 cases
in MS-DRG 039 with an average length of stay of 1.5 days and average
costs of $8,400.
During our review of claims data for MS-DRGs 037, 038, and 039, we
also discovered 96 ICD-10-PCS procedure codes describing dilation of a
carotid artery with an intraluminal device that were inadvertently
included as a result of efforts to replicate the ICD-9 based MS-DRGs.
These procedure codes are also included in the logic for MS-DRGs 034,
035, and 036. Under ICD-9-CM, procedure codes 00.61 (Percutaneous
angioplasty of extracranial vessel(s)) and 00.63 (Percutaneous
insertion of carotid artery stent(s)) are both required to be reported
on a claim to identify that a carotid artery stent procedure was
performed and for assignment of the case to MS-DRGs 034, 035, and 036.
Procedure code 00.61 is designated as an O.R. procedure, while
procedure code 00.63 is designated as a non-O.R. procedure. Under ICD-
10-PCS, a carotid artery stent procedure is described by one unique
code that includes both clinical concepts of the angioplasty (dilation)
and the insertion of the stent (intraluminal device). This
``combination code'' under ICD-10-PCS is designated as an O.R.
procedure. Under ICD-9-CM, procedure code 00.61 reported in the absence
of procedure code 00.63 results in assignment to MS-DRGs 037, 038, and
039 according to the MS-DRG logic because procedure code 00.61 has an
inclusion term for vertebral vessels, as well as for the carotid
vessels. Therefore, when all of the comparable translations of
procedure code 00.61 as an O.R. procedure were replicated from the ICD-
9 based MS-DRGs to the ICD-10 based MS-DRGs, this replication
inadvertently results in the assignment of ICD-10-PCS procedure codes
that identify and describe a carotid artery stent procedure to MS-DRGs
037, 038, and 039. Therefore, we are proposing to remove the 96 ICD-10-
PCS procedure codes describing dilation of a carotid artery with an
intraluminal device from MS-DRGs 037, 038, and 039.
We also found 6 procedure codes describing dilation of a carotid
artery with an intraluminal device in MS-DRGs 037, 038, and 039 that
are not currently assigned to MS-DRGs 034, 035, and 036. Our clinical
advisors recommended that these 6 procedure codes be reassigned from
MS-DRGs 037, 038, and 039 to MS-DRGs 034, 035, and 036 because the 6
procedure codes are consistent with the other procedures describing
dilation of a carotid artery with an intraluminal device that are
currently assigned to MS-DRGs 034, 035, and 036. We refer readers to
Table 6P.1b. associated with this proposed rule (which is available via
the internet on the CMS website at: http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html) for the
complete list of procedure codes that we are proposing to remove from
MS-DRGs 037, 038, and 039.
We also note that, as discussed in section II.F.14.f. of the
preamble of this proposed rule, we are deleting a number of codes that
include the ICD-10-PCS qualifier term ``bifurcation'' as the result of
the finalized proposal discussed at the September 11-12, 2018 ICD-10
Coordination and Maintenance Committee meeting. We refer readers to the
website at: https://www.cms.gov/Medicare/Coding/ICD9ProviderDiagnosticCodes/ICD-9-CM-C-and-M-Meeting-Materials.html for
the committee meeting materials and discussion regarding this proposal.
We note that, of the 96 procedure codes that we are proposing to remove
from the logic for MS-DRGs 037, 038, and 039, there are 48 procedure
codes that include the qualifier term ``bifurcation''. Therefore, these
48 procedure codes will be deleted effective October 1, 2019. The 48
remaining valid procedure codes that do not include the term
``bifurcation'' that we are proposing to remove from MS-DRGs 037, 038,
and 039 will continue to be assigned to MS-DRGs 034, 035, and 036.
Lastly, if the applicable proposed MS-DRG changes are finalized, we
would make a conforming change to the ICD-10 MS-DRG Version 37
Definitions Manual for FY 2020 by combining all the procedure codes
identifying a carotid artery stent procedure within MS-DRGs 034, 035,
and 036 into one list entitled ``Operating Room Procedures'' to better
reflect the
[[Page 19185]]
definition of these MS-DRGs based on the discussion and proposals
described above.
4. MDC 4 (Diseases and Disorders of the Respiratory System): Pulmonary
Embolism
We received a request to reassign three ICD-10-CM diagnosis codes
for pulmonary embolism with acute cor pulmonale from MS-DRG 176
(Pulmonary Embolism without MCC) to the higher severity level MS-DRG
175 (Pulmonary Embolism with MCC). The three diagnosis codes are
identified in the following table.
------------------------------------------------------------------------
ICD-10-CM code Code description
------------------------------------------------------------------------
I26.01.............................. Septic pulmonary embolism with
acute cor pulmonale.
I26.02.............................. Saddle embolus of pulmonary artery
with acute cor pulmonale.
I26.09.............................. Other pulmonary embolism with
acute cor pulmonale.
------------------------------------------------------------------------
The requestor noted that, in the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41231 through 41234), we finalized the proposal to remove the
special logic in the GROUPER for processing claims containing a code on
the Principal Diagnosis Is Its Own CC or MCC Lists and deleted the
relevant tables from the ICD-10 MS-DRG Definitions Manual Version 36,
effective October 1, 2018. As a result of this change, cases reporting
any one of the three ICD-10-CM diagnosis codes describing a pulmonary
embolism with acute cor pulmonale were reassigned from MS-DRG 175 to
MS-DRG 176, absent a secondary diagnosis code to trigger assignment to
MS-DRG 175. The requestor stated that this change in the MS-DRG
assignment for these cases resulted in a reduction in payment for cases
involving pulmonary embolism with acute cor pulmonale and that the FY
2019 payment rate for MS-DRG 176 does not appropriately account for the
costs and resource utilization associated with these cases because the
subset of patients with pulmonary embolism with acute cor pulmonale
often represents a more severe set of patients with pulmonary embolism.
The logic for case assignment to MS-DRGs 175 and 176 is displayed
in the ICD-10 MS-DRG Version 36 Definitions Manual, which is available
via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.html.
We analyzed claims data from the September 2018 update of the FY
2018 MedPAR file for MS-DRGs 175 and 176 to identify cases reporting
diagnosis codes describing pulmonary embolism with acute cor pulmonale
as listed above (ICD-10-CM diagnosis codes I26.01, I26.02 or I26.09) as
the principal diagnosis or as a secondary diagnosis. Our findings are
shown in the following table.
MS-DRGs for Pulmonary Embolism
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 175--All cases........................................... 24,389 5.2 $10,294
MS-DRG 175--Cases with pulmonary embolism with acute cor 2,326 5.7 13,034
pulmonale......................................................
MS-DRG 176--All cases........................................... 30,215 3.3 6,356
MS-DRG 176--Cases with pulmonary embolism with acute cor 1,821 3.9 9,630
pulmonale......................................................
----------------------------------------------------------------------------------------------------------------
As shown in the table, for MS-DRG 175, there was a total of 24,389
cases with an average length of stay of 5.2 days and average costs of
$10,294. Of these 24,389 cases, there were 2,326 cases reporting
pulmonary embolism with acute cor pulmonale, with an average length of
stay 5.7 days and average costs of $13,034. For MS-DRG 176, there was a
total of 30,215 cases with an average length of stay of 3.3 days and
average costs of $6,356. Of these 30,215 cases, there were 1,821 cases
reporting pulmonary embolism with acute cor pulmonale with an average
length of stay of 3.9 days and average costs of $9,630.
As stated in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41231
through 41234), available ICD-10 data can now be used to evaluate other
indicators of resource utilization and, as shown by our claims
analysis, the data indicate that the average costs of cases reporting
pulmonary embolism or saddle embolus with acute cor pulmonale ($9,630)
in MS-DRG 176 are closer to the average costs for all pulmonary
embolism cases in MS-DRG 175 ($10,294) as compared to the average costs
for all cases in MS-DRG 176 ($6,356). Our clinical advisors also agree
that this subset of patients with acute cor pulmonale often represents
a more severe set of patients and that these cases are more
appropriately assigned to the higher severity level ``with MCC'' MS-
DRG. Therefore, we are proposing to reassign cases reporting diagnosis
code I26.01, I26.02, or I26.09 to the higher severity level MS-DRG 175
and to revise the title for MS-DRG 175 to ``Pulmonary Embolism with MCC
or Acute Cor Pulmonale'' to more accurately reflect the diagnoses
assigned there.
5. MDC 5 (Diseases and Disorders of the Circulatory System)
a. Transcatheter Mitral Valve Repair With Implant
As we did for the FY 2015 IPPS/LTCH PPS proposed rule (79 FR 28008
through 28010) and for the FY 2017 IPPS/LTCH PPS proposed rule (81 FR
24985 through 24989), for FY 2020, we received a request to modify the
MS-DRG assignment for transcatheter mitral valve repair (TMVR) with
implant procedures. ICD-10-PCS procedure code 02UG3JZ (Supplement
mitral valve with synthetic substitute, percutaneous approach)
identifies and describes this procedure. This request also included the
suggestion that CMS give consideration to reclassifying other
endovascular cardiac valve repair procedures. Specifically, the
requestor recommended that cases reporting procedure codes describing
an endovascular cardiac valve repair with implant be reassigned to MS-
DRGs 266 and 267 (Endovascular Cardiac Valve Replacement with and
without MCC, respectively) and that the MS-DRG titles be revised to
Endovascular Cardiac Valve Interventions with Implant with and without
MCC, respectively. We refer readers to detailed discussions of
[[Page 19186]]
the MitraClip[supreg] System (hereafter referred to as
MitraClip[supreg]) for transcatheter mitral valve repair in previous
rulemakings, including the FY 2012 IPPS/LTCH PPS proposed rule (76 FR
25822) and final rule (76 FR 51528 through 51529), the FY 2013 IPPS/
LTCH PPS proposed rule (77 FR 27902 through 27903) and final rule (77
FR 53308 through 53310), the FY 2015 IPPS/LTCH PPS proposed rule (79 FR
28008 through 28010) and final rule (79 FR 49889 through 49892), the FY
2016 IPPS/LTCH PPS proposed rule (80 FR 24356 through 24359) and final
rule (80 FR 49363 through 49367), and the FY 2017 IPPS/LTCH PPS
proposed rule (81 FR 24985 through 24989) and final rule (81 FR 56809
through 56813), in response to requests for MS-DRG reclassification, as
well as the FY 2014 IPPS/LTCH PPS proposed rule (78 FR 27547 through
27552), under the new technology add-on payment policy. In the FY 2014
IPPS/LTCH PPS final rule (78 FR 50575), we were unable to consider
further the application for a new technology add-on payment for
MitraClip[supreg] because the technology had not received FDA approval
by the July 1, 2013 deadline.
In the FY 2015 IPPS/LTCH PPS final rule, we finalized our proposal
to not create a new MS-DRG or to reassign cases reporting ICD-9-CM
procedure code 35.97 that described procedures involving the
MitraClip[supreg] to another MS-DRG (79 FR 49889 through 49892). Under
a new application, the request for new technology add-on payments for
the MitraClip[supreg] System was approved for FY 2015 (79 FR 49941
through 49946). The new technology add-on payment for MitraClip[supreg]
was subsequently discontinued effective FY 2017.
In the FY 2016 IPPS/LTCH PPS final rule (80 FR 49371), we finalized
a modification to the MS-DRGs to which procedures involving the
MitraClip[supreg] were assigned. For the ICD-10 based MS-DRGs to fully
replicate the ICD-9-CM based MS-DRGs, ICD-10-PCS code 02UG3JZ
(Supplement mitral valve with synthetic substitute, percutaneous
approach), which identifies the MitraClip[supreg] technology and is the
ICD-10-PCS code translation for ICD-9-CM procedure code 35.97
(Percutaneous mitral valve repair with implant), was assigned to new
MS-DRGs 273 and 274 (Percutaneous Intracardiac Procedures with MCC and
without MCC, respectively) and continued to be assigned to MS-DRGs 231
and 232 (Coronary Bypass with PTCA with MCC and without MCC,
respectively).
In the FY 2017 IPPS/LTCH PPS proposed and final rules, we also
discussed our analysis of MS-DRGs 228, 229, and 230 (Other
Cardiothoracic Procedures with MCC, with CC, and without CC/MCC,
respectively) with regard to the possible reassignment of cases
reporting ICD-10-PCS procedure code 02UG3JZ (Supplement mitral valve
with synthetic substitute, percutaneous approach). We finalized our
proposal to collapse these MS-DRGs (228, 229, and 230) from three
severity levels to two severity levels by deleting MS-DRG 230 and
revising the structure of MS-DRG 229. We also finalized our proposal to
reassign ICD-10-PCS procedure code 02UG3JZ (Supplement mitral valve
with synthetic substitute, percutaneous approach) from MS-DRGs 273 and
274 to MS-DRG 228 and revised MS-DRG 229 (81 FR 56813).
According to the requestor, there are substantial clinical and
resource differences between the transcatheter mitral valve repair
(TMVR) procedure and other procedures currently grouping to MS-DRGs 228
and 229. The requestor noted that, currently, ICD-10-PCS procedure code
02UG3JZ is the only endovascular valve intervention with implant
procedure that maps to MS-DRGs 228 and 229. The requestor also noted
that other ICD-10-PCS procedure codes describing procedures for
endovascular (transcatheter) cardiac valve repair with implant map to
MS-DRGs 273 and 274 or to MS-DRGs 216, 217, 218, 219, 220, and 221
(Cardiac Valve and Other Major Cardiothoracic Procedures with and
without Cardiac Catheterization with MCC, with CC and without CC/MCC,
respectively). The requestor further noted that all ICD-10-PCS
procedure codes for endovascular cardiac valve replacement procedures
map to MS-DRGs 266 (Endovascular Cardiac Valve Replacement with MCC)
and 267 (Endovascular Cardiac Valve Replacement without MCC).
The ICD-10-PCS procedure codes describing a transcatheter cardiac
valve repair procedure with an implant are listed in the following
table.
------------------------------------------------------------------------
ICD-10-PCS code Description
------------------------------------------------------------------------
02UF37J............................. Supplement aortic valve created
from truncal valve with
autologous tissue substitute,
percutaneous approach.
02UF37Z............................. Supplement aortic valve with
autologous tissue substitute,
percutaneous approach.
02UF38J............................. Supplement aortic valve created
from truncal valve with
zooplastic tissue, percutaneous
approach.
02UF38Z............................. Supplement aortic valve with
zooplastic tissue, percutaneous
approach.
02UF3JJ............................. Supplement aortic valve created
from truncal valve with synthetic
substitute, percutaneous
approach.
02UF3JZ............................. Supplement aortic valve with
synthetic substitute,
percutaneous approach.
02UF3KJ............................. Supplement aortic valve created
from truncal valve with
nonautologous tissue substitute,
percutaneous approach.
02UF3KZ............................. Supplement aortic valve with
nonautologous tissue substitute,
percutaneous approach.
02UG37E............................. Supplement mitral valve created
from left atrioventricular valve
with autologous tissue
substitute, percutaneous
approach.
02UG37Z............................. Supplement mitral valve with
autologous tissue substitute,
percutaneous approach.
02UG38E............................. Supplement mitral valve created
from left atrioventricular valve
with zooplastic tissue,
percutaneous approach.
02UG38Z............................. Supplement mitral valve with
zooplastic tissue, percutaneous
approach.
02UG3KE............................. Supplement mitral valve created
from left atrioventricular valve
with nonautologous tissue
substitute, percutaneous
approach.
02UG3KZ............................. Supplement mitral valve with
nonautologous tissue substitute,
percutaneous approach.
02UG3JE............................. Supplement mitral valve created
from left atrioventricular valve
with synthetic substitute,
percutaneous approach.
02UG3JZ............................. Supplement mitral valve with
synthetic substitute,
percutaneous approach.
02UH37Z............................. Supplement pulmonary valve with
autologous tissue substitute,
percutaneous approach.
02UH38Z............................. Supplement pulmonary valve with
zooplastic tissue, percutaneous
approach.
02UH3JZ............................. Supplement pulmonary valve with
synthetic substitute,
percutaneous approach.
02UH3KZ............................. Supplement pulmonary valve with
nonautologous tissue substitute,
percutaneous approach.
02UJ37G............................. Supplement tricuspid valve created
from right atrioventricular valve
with autologous tissue
substitute, percutaneous
approach.
02UJ37Z............................. Supplement tricuspid valve with
autologous tissue substitute,
percutaneous approach.
02UJ38G............................. Supplement tricuspid valve created
from right atrioventricular valve
with zooplastic tissue,
percutaneous approach.
02UJ38Z............................. Supplement tricuspid valve with
zooplastic tissue, percutaneous
approach.
02UJ3JG............................. Supplement tricuspid valve created
from right atrioventricular valve
with synthetic substitute,
percutaneous approach.
02UJ3JZ............................. Supplement tricuspid valve with
synthetic substitute,
percutaneous approach.
[[Page 19187]]
02UJ3KG............................. Supplement tricuspid valve created
from right atrioventricular valve
with nonautologous tissue
substitute, percutaneous
approach.
02UJ3KZ............................. Supplement tricuspid valve with
nonautologous tissue substitute,
percutaneous approach.
------------------------------------------------------------------------
The ICD-10-PCS procedure codes describing a transcatheter cardiac
valve replacement procedure are listed in the following table.
------------------------------------------------------------------------
ICD-10-PCS code Description
------------------------------------------------------------------------
02RF37H............................. Replacement of aortic valve with
autologous tissue substitute,
transapical, percutaneous
approach.
02RF37Z............................. Replacement of aortic valve with
autologous tissue substitute,
percutaneous approach.
02RF38H............................. Replacement of aortic valve with
zooplastic tissue, transapical,
percutaneous approach.
02RF38Z............................. Replacement of aortic valve with
zooplastic tissue, percutaneous
approach.
02RF3JH............................. Replacement of aortic valve with
synthetic substitute,
transapical, percutaneous
approach.
02RF3JZ............................. Replacement of aortic valve with
synthetic substitute,
percutaneous approach.
02RF3KH............................. Replacement of aortic valve with
nonautologous tissue substitute,
transapical, percutaneous
approach.
02RF3KZ............................. Replacement of aortic valve with
nonautologous tissue substitute,
percutaneous approach.
02RG37H............................. Replacement of mitral valve with
autologous tissue substitute,
transapical, percutaneous
approach.
02RG37Z............................. Replacement of mitral valve with
autologous tissue substitute,
percutaneous approach.
02RG38H............................. Replacement of mitral valve with
zooplastic tissue, transapical,
percutaneous approach.
02RG38Z............................. Replacement of mitral valve with
zooplastic tissue, percutaneous
approach.
02RG3JH............................. Replacement of mitral valve with
synthetic substitute,
transapical, percutaneous
approach.
02RG3JZ............................. Replacement of mitral valve with
synthetic substitute,
percutaneous approach.
02RG3KH............................. Replacement of mitral valve with
nonautologous tissue substitute,
transapical, percutaneous
approach.
02RG3KZ............................. Replacement of mitral valve with
nonautologous tissue substitute,
percutaneous approach.
02RH37H............................. Replacement of pulmonary valve
with autologous tissue
substitute, transapical,
percutaneous approach.
02RH37Z............................. Replacement of pulmonary valve
with autologous tissue
substitute, percutaneous
approach.
02RH38H............................. Replacement of pulmonary valve
with zooplastic tissue,
transapical, percutaneous
approach.
02RH38Z............................. Replacement of pulmonary valve
with zooplastic tissue,
percutaneous approach.
02RH3JH............................. Replacement of pulmonary valve
with synthetic substitute,
transapical, percutaneous
approach.
02RH3JZ............................. Replacement of pulmonary valve
with synthetic substitute,
percutaneous approach.
02RH3KH............................. Replacement of pulmonary valve
with nonautologous tissue
substitute, transapical,
percutaneous approach.
02RH3KZ............................. Replacement of pulmonary valve
with nonautologous tissue
substitute, percutaneous
approach.
02RJ37H............................. Replacement of tricuspid valve
with autologous tissue
substitute, transapical,
percutaneous approach.
02RJ37Z............................. Replacement of tricuspid valve
with autologous tissue
substitute, percutaneous
approach.
02RJ38H............................. Replacement of tricuspid valve
with zooplastic tissue,
transapical, percutaneous
approach.
02RJ38Z............................. Replacement of tricuspid valve
with zooplastic tissue,
percutaneous approach.
02RJ3JH............................. Replacement of tricuspid valve
with synthetic substitute,
transapical, percutaneous
approach.
02RJ3JZ............................. Replacement of tricuspid valve
with synthetic substitute,
percutaneous approach.
02RJ3KH............................. Replacement of tricuspid valve
with nonautologous tissue
substitute, transapical,
percutaneous approach.
02RJ3KZ............................. Replacement of tricuspid valve
with nonautologous tissue
substitute, percutaneous
approach.
X2RF332............................. Replacement of aortic valve using
zooplastic tissue, rapid
deployment technique,
percutaneous approach, new
technology group 2.
------------------------------------------------------------------------
The requestor performed its own analyses, first comparing TMVR
procedures (ICD-10-PCS procedure code 02UG3JZ) to other procedures
currently assigned to MS-DRGs 228 and 229, as well as to the
transcatheter cardiac valve replacement procedures in MS-DRGs 266 and
267. We refer the reader to the ICD-10 MS-DRG Version 36 Definitions
Manual for complete documentation of the logic for case assignment to
MS-DRGs 228 and 229 (which is available via the internet on the CMS
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.html).
According to the requestor, its findings indicate that TMVR is more
closely aligned with MS-DRGs 266 and 267 than MS-DRGs 228 and 229 with
regard to average length of stay and average [standardized] costs. The
requestor also examined the impact of removing cases reporting a TMVR
procedure (ICD-10-PCS procedure code 02UG3JZ) from MS-DRGs 228 and 229
and adding those cases to MS-DRGs 266 and 267. The requestor noted this
movement would have minimal impact to MS-DRGs 266 and 267 based on its
analysis. In addition, the requestor stated that its request is in
alignment with CMS' policy goal of creating and maintaining clinically
coherent MS-DRGs.
The requestor acknowledged that CMS has indicated in prior
rulemaking that TMVR procedures are not clinically similar to
endovascular cardiac valve replacement procedures, and the requestor
agreed that they are distinct procedures. However, the requestor also
believed that TMVR is more similar to the replacement procedures in MS-
DRGs 266 and 267 compared to the other procedures currently assigned to
MS-DRGs 228 and 229. The requestor provided the following table of
procedures in volume order (highest to lowest) to illustrate the
clinical differences between TMVR procedures and other procedures
currently assigned to MS-DRGs 228 and 229.
----------------------------------------------------------------------------------------------------------------
ICD-10-PCS root
Procedure Approach Anatomy treated operation Implanted device
----------------------------------------------------------------------------------------------------------------
TMVR............................ Percutaneous...... Valves............ Supplement........ Substitute.
Destruction..................... Open.............. Atria............. Destruction....... None.
[[Page 19188]]
Coronary Atherectomy............ Open.............. Coronary Artery... Extirpation....... None.
Insertion....................... Percutaneous...... Atria or Insertion......... Pacemaker or
Ventricles. Intraluminal
Device.
Destruction..................... Percutaneous...... Atria............. Destructions...... None.
Structural Heart Repair......... Open.............. Septum, Heart, Repair............ None.
Chordae Tendinae,
or Papillary
Muscle.
Structural Heart Excision....... Open.............. Septum, Atria, Excision.......... None.
Ventricles,
Chordae Tendinae,
or Papillary
Muscle.
----------------------------------------------------------------------------------------------------------------
The requestor noted that, among the procedures listed in the table,
TMVR is the only procedure that involves treatment of a cardiac valve
and is the only procedure that involves implanting a synthetic
substitute.
To illustrate the similarities between TMVR procedures and
endovascular cardiac valve replacements in MS-DRGs 266 and 267, the
requestor provided the following table.
----------------------------------------------------------------------------------------------------------------
ICD-10-PCS root
Procedure Approach Anatomy treated operation Implanted device
----------------------------------------------------------------------------------------------------------------
TMVR............................ Percutaneous...... Valves............ Supplement........ Substitute.
Endovascular Cardiac Valve Percutaneous...... Valves............ Replacement....... Substitute.
Replacement.
----------------------------------------------------------------------------------------------------------------
The requestor noted that both TMVR procedures and endovascular
cardiac valve replacements use a percutaneous approach, treat cardiac
valves, and use an implanted device for purposes of improving the
function of the specified valve. The requestor believed that the
analyses support the request to group TMVR procedures with endovascular
cardiac valve replacements from a resource perspective and an
improvement to clinical coherence could be achieved because TMVR
procedures are more similar to the endovascular cardiac valve
replacements compared to the other procedures in MS-DRGs 228 and 229,
where TMVR is currently assigned.
As noted earlier in this section, the request also included the
suggestion that CMS give consideration to reclassifying other
endovascular cardiac valve repair with implant procedures to MS-DRGs
266 and 267; specifically, endovascular cardiac valve repair with
implant procedures involving the aortic, pulmonary, tricuspid and other
non-TMVR mitral valve procedures that currently group to MS-DRGs 273
and 274 or MS-DRGs 216, 217, 218, 219, 220 and 221. The requestor
acknowledged that endovascular cardiac valve repair with implant
procedures involving these other cardiac valves have lower volumes in
comparison to the TMVR procedure (ICD-10-PCS procedure code 02UG3JZ),
which makes analysis of these procedures a little more difficult.
However, the requestor suggested that movement of these procedures to
MS-DRGs 266 and 267 would enable the ability to maintain clinical
coherence for all endovascular cardiac valve interventions. The
requestor also stated that there is an anticipated increase in the
volume of not only the TMVR procedure described by ICD-10-PCS procedure
code 02UG3JZ (which has grown annually since the MitraClip[supreg] was
approved for new technology add-on payment in FY 2015), but also for
the other endovascular cardiac valve repair with implant procedures,
such as those involving the tricuspid valve, which are currently under
study in the United States and Europe. Based on this anticipated
increase in volume for endovascular cardiac valve repair with implant
procedures, the requestor believed that it would be advantageous to
take this opportunity to restructure the MS-DRGs by moving all the
endovascular cardiac valve repair with implant procedures to MS-DRGs
266 and 267 with revised titles as noted previously, to improve
clinical consistency beginning in FY 2020. The requestor further noted
that while the requestor believes its request reflects the best
approach for appropriate MS-DRG assignment for TMVR and other
endovascular cardiac valve repair with implant procedures, the
requestor understands that CMS may consider other alternatives.
We analyzed claims data from the September 2018 update of the FY
2018 MedPAR file for cases reporting ICD-10-PCS procedure code 02UG3JZ
in MS-DRGs 228 and 229 as well as cases reporting one of the procedure
codes listed above describing a transcatheter cardiac valve repair with
implant procedure in MS-DRGs 216, 217, 218, 219, 220, 221, 273, and
274. Our findings are shown in the tables below.
MS-DRGs for Transcatheter Cardiac Valve Repair With Implant Procedures
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 216--All cases........................................... 5,909 16 $70,435
MS-DRG 216--Cases with procedure codes for transcatheter cardiac 48 12.6 72,556
valve repair...................................................
MS-DRG 217--All cases........................................... 2,166 9.4 47,299
MS-DRG 217--Cases with procedure codes for transcatheter cardiac 25 3.4 40,707
valve repair...................................................
MS-DRG 218--All cases........................................... 268 6.8 39,501
MS-DRG 218--Cases with procedure codes for transcatheter cardiac 4 1.3 45,903
valve repair...................................................
MS-DRG 219--All cases........................................... 15,105 10.9 55,423
MS-DRG 219--Cases with procedure codes for transcatheter cardiac 55 7.1 65,880
valve repair...................................................
[[Page 19189]]
MS-DRG 220--All cases........................................... 15,889 6.6 38,313
MS-DRG 220--Cases with procedure codes for transcatheter cardiac 40 3 38,906
valve repair...................................................
MS-DRG 221--All cases........................................... 2,652 4.7 33,577
MS-DRG 221--Cases with procedure codes for transcatheter cardiac 13 2.2 29,646
valve repair...................................................
MS-DRG 228--All cases........................................... 5,583 9.2 46,613
MS-DRG 228--Cases with procedure code 02UG3JZ (Supplement mitral 1,688 5.6 49,569
valve with synthetic substitute, percutaneous approach)........
MS-DRG 229--All cases........................................... 6,593 4.3 32,322
MS-DRG 229--Cases with procedure code 02UG3JZ (Supplement mitral 2,018 1.7 38,321
valve with synthetic substitute, percutaneous approach)........
MS-DRG 273--All cases........................................... 7,785 6.9 27,200
MS-DRG 273--Cases with procedure codes for transcatheter cardiac 6 7.5 52,370
valve repair...................................................
MS-DRG 274--All cases........................................... 20,434 2.3 22,771
MS-DRG 274--Cases with procedure codes for transcatheter cardiac 7 1.4 28,152
valve repair...................................................
----------------------------------------------------------------------------------------------------------------
As shown in the table, we found a total of 5,909 cases for MS-DRG
216 with an average length of stay of 16 days and average costs of
$70,435. Of those 5,909 cases, there were 48 cases reporting a
procedure code for a transcatheter cardiac valve repair with an average
length of stay of 12.6 days and average costs of $72,556. We found a
total of 2,166 cases for MS-DRG 217 with an average length of stay of
9.4 days and average costs of $47,299. Of those 2,166 cases, there was
a total of 25 cases reporting a procedure for a transcatheter cardiac
valve repair with an average length of stay of 3.4 days and average
costs of $40,707. We found a total of 268 cases for MS-DRG 218 with an
average length of stay of 6.8 days and average costs of $39,501. Of
those 268 cases, there were 4 cases reporting a procedure code for a
transcatheter cardiac valve repair with an average length of stay of
1.3 days and average costs of $45,903. We found a total of 15,105 cases
for MS-DRG 219 with an average length of stay of 10.9 days and average
costs of $55,423. Of those 15,105 cases, there were 55 cases reporting
a procedure code for a transcatheter cardiac valve repair with an
average length of stay of 7.1 days and average costs of $65,880. We
found a total of 15,889 cases for MS-DRG 220 with an average length of
stay of 6.6 days and average costs of $38,313. Of those 15,889 cases,
there were 40 cases reporting a procedure code for a transcatheter
cardiac valve repair with an average length of stay of 3 days and
average costs of $38,906. We found a total of 2,652 cases for MS-DRG
221 with an average length of stay of 4.7 days and average costs of
$33,577. Of those 2,652 cases, there were 13 cases reporting a
procedure code for a transcatheter cardiac valve repair with an average
length of stay of 2.2 days and average costs of $29,646.
For MS-DRG 228, we found a total of 5,583 cases with an average
length of stay of 9.2 days and average costs of $46,613. Of those 5,583
cases, there were 1,688 cases reporting ICD-10-PCS procedure code
02UG3JZ (Supplement mitral valve with synthetic substitute,
percutaneous approach) with an average length of stay of 5.6 days and
average costs of $49,569. As noted previously, ICD-10-PCS procedure
code 02UG3JZ is the only endovascular cardiac valve repair with implant
procedure assigned to MS-DRGs 228 and 229. We found a total of 6,593
cases for MS-DRG 229 with an average length of stay of 4.3 days and
average costs of $32,322. Of those 6,593 cases, there were 2,018 cases
reporting ICD-10-PCS procedure code 02UG3JZ with an average length of
stay of 1.7 days and average costs of $38,321.
For MS-DRG 273, we found a total of 7,785 cases with an average
length of stay of 6.9 days and average costs of $27,200. Of those 7,785
cases, there were 6 cases reporting a procedure code for a
transcatheter cardiac valve repair with an average length of stay of
7.5 days and average costs of $52,370. We found a total of 20,434 cases
in MS-DRG 274 with an average length of stay of 2.3 days and average
costs of $22,771. Of those 20,434 cases, there were 7 cases reporting a
procedure code for a transcatheter cardiac valve repair with an average
length of stay of 1.4 days and average costs of $28,152.
We also analyzed cases reporting any one of the procedure codes
listed above describing a transcatheter cardiac valve replacement
procedure in MS-DRGs 266 and 267. Our findings are shown in the table
below.
MS-DRGs for Transcatheter Cardiac Valve Replacement Procedures
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 266--All cases........................................... 15,079 5.6 $51,402
MS-DRG 267--All cases........................................... 20,845 2.4 41,891
----------------------------------------------------------------------------------------------------------------
As shown in the table, there was a total of 15,079 cases with an
average length of stay of 5.6 days and average costs of $51,402 in MS-
DRG 266. For MS-DRG 267, there was a total of 20,845 cases with an
average length of stay of 2.4 days and average costs of $41,891.
As stated previously, the requestor noted that ICD-10-PCS procedure
code 02UG3JZ describing a transcatheter mitral valve repair with
implant procedure is the only endovascular cardiac valve intervention
with implant procedure assigned to MS-DRGs 228 and 229. The data
analysis shows that for the cases reporting procedure code 02UG3JZ in
MS-DRGs 228 and 229, the average length of stay and average costs are
aligned with the average length of stay and average costs of cases in
MS-DRGs 266 and 267, respectively.
The data also show that, for MS-DRGs 216, 217, 218, 219, 220, and
221 and for
[[Page 19190]]
MS-DRG 274, the average length of stay for cases reporting a
transcatheter cardiac valve with implant procedure is shorter than the
average length of stay for all the cases in their assigned MS-DRG. For
MS-DRG 273, the average length of stay for cases reporting a
transcatheter cardiac valve with implant procedure is slightly longer
(7.5 days versus 6.9 days). In addition, the average costs for the
cases reporting a transcatheter cardiac valve with implant procedure
are higher when compared to all the cases in their assigned MS-DRG with
the exception of MS-DRG 217 ($40,707 versus $47,299) and MS-DRG 221
($29,646 versus $33,577).
Our clinical advisors continue to believe that transcatheter
cardiac valve repair procedures are not the same as a transcatheter
(endovascular) cardiac valve replacement. However, they agree with the
requestor and, based on our data analysis, that these procedures are
more clinically coherent in that they also describe endovascular
cardiac valve interventions with implants and are similar in terms of
average length of stay and average costs to cases in MS-DRGs 266 and
267 when compared to other procedures in their current MS-DRG
assignment. For these reasons, our clinical advisors agree that we
should propose to reassign the endovascular cardiac valve repair
procedures (supplement procedures) listed previously to the
endovascular cardiac valve replacement MS-DRGs.
We analyzed the impact of grouping the endovascular cardiac valve
repair with implant (supplement) procedures with the endovascular
cardiac valve replacement procedures. The following table reflects our
findings for the proposed revised endovascular cardiac valve
(supplement) procedures with the endovascular cardiac valve replacement
MS-DRGs with a 2-way severity level split.
Proposed Revised MS-DRGs for Endovascular Cardiac Valve Replacement and Supplement Procedures
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 266 (Endovascular Cardiac Valve Replacement and 16,922 5.7 $51,564
Supplement Procedures with MCC)................................
MS-DRG 267 (Endovascular Cardiac Valve Replacement and 22,958 2.4 41,563.
Supplement Procedures without MCC).............................
----------------------------------------------------------------------------------------------------------------
As shown in the table, there was a total of 16,922 cases for the
endovascular cardiac valve replacement and supplement procedures with
MCC group, with an average length of stay of 5.7 days and average costs
of $51,564. There was a total of 22,958 cases for the endovascular
cardiac valve replacement and supplement procedures without MCC group,
with an average length of stay of 2.4 days and average costs of
$41,563. We applied the criteria to create subgroups for the two-way
severity level split for the proposed revised MS-DRGs and found that
all five criteria were met. For the proposed revised MS-DRGs, there is
at least (1) 500 or more cases in the MCC group or in the without MCC
subgroup; (2) 5 percent or more of the cases in the MCC group or in the
without MCC subgroup; (3) a 20 percent difference in average costs
between the MCC group and the without MCC group; (4) a $2,000
difference in average costs between the MCC group and the without MCC
group; and (5) a 3-percent reduction in cost variance, indicating that
the proposed severity level splits increase the explanatory power of
the base MS-DRG in capturing differences in expected cost between the
proposed MS-DRG severity level splits by at least 3 percent and thus
improve the overall accuracy of the IPPS payment system.
During our review of the transcatheter cardiac valve repair
(supplement) procedures in MS-DRGs 216, 217, 218, 219, 220, and 221,
MS-DRGs 228 and 229, and MS-DRGs 273 and 274, our clinical advisors
recommended that we also analyze the claims data to identify other
(non-supplement) transcatheter (endovascular) procedures that involve
the cardiac valves and are assigned to those same MS-DRGs to determine
if additional modifications may be warranted, consistent with our
ongoing efforts to refine the ICD-10 MS-DRGs.
We analyzed the following ICD-10-PCS procedure codes that are
currently assigned to MS-DRGs 216, 217, 218, 219, 220, and 221.
------------------------------------------------------------------------
ICD-10-PCS code Description
------------------------------------------------------------------------
02QF3ZJ............................. Repair aortic valve created from
truncal valve, percutaneous
approach.
02QF3ZZ............................. Repair aortic valve, percutaneous
approach.
02QG3ZE............................. Repair mitral valve created from
left atrioventricular valve,
percutaneous approach.
02QG3ZZ............................. Repair mitral valve, percutaneous
approach.
02QH3ZZ............................. Repair pulmonary valve,
percutaneous approach.
02QJ3ZG............................. Repair tricuspid valve created
from right atrioventricular
valve, percutaneous approach.
02QJ3ZZ............................. Repair tricuspid valve,
percutaneous approach.
02TH3ZZ............................. Resection of pulmonary valve,
percutaneous approach.
02VG3ZZ............................. Restriction of mitral valve,
percutaneous approach.
02WF38Z............................. Revision of zooplastic tissue in
aortic valve, percutaneous
approach.
02WF3JZ............................. Revision of synthetic substitute
in aortic valve, percutaneous
approach.
02WF3KZ............................. Revision of nonautologous tissue
substitute in aortic valve,
percutaneous approach.
02WG37Z............................. Revision of autologous tissue
substitute in mitral valve,
percutaneous approach.
02WG38Z............................. Revision of zooplastic tissue in
mitral valve, percutaneous
approach.
02WG3JZ............................. Revision of synthetic substitute
in mitral valve, percutaneous
approach.
02WG3KZ............................. Revision of nonautologous tissue
substitute in mitral valve,
percutaneous approach.
02WH37Z............................. Revision of autologous tissue
substitute in pulmonary valve,
percutaneous approach.
02WH38Z............................. Revision of zooplastic tissue in
pulmonary valve, percutaneous
approach.
02WH3JZ............................. Revision of synthetic substitute
in pulmonary valve, percutaneous
approach.
02WH3KZ............................. Revision of nonautologous tissue
substitute in pulmonary valve,
percutaneous approach.
02WJ37Z............................. Revision of autologous tissue
substitute in tricuspid valve,
percutaneous approach.
[[Page 19191]]
02WJ38Z............................. Revision of zooplastic tissue in
tricuspid valve, percutaneous
approach.
02WJ3JZ............................. Revision of synthetic substitute
in tricuspid valve, percutaneous
approach.
02WJ3KZ............................. Revision of nonautologous tissue
substitute in tricuspid valve,
percutaneous approach.
------------------------------------------------------------------------
We also analyzed ICD-10-PCS procedure code 02TH3ZZ (Resection of
pulmonary valve, percutaneous approach) that is currently assigned to
MS-DRGs 228 and 229. Lastly, we analyzed the following ICD-10-PCS
procedure codes that are currently assigned to MS-DRGs 273 and 274.
------------------------------------------------------------------------
ICD-10-PCS code Description
------------------------------------------------------------------------
025F3ZZ............................. Destruction of aortic valve,
percutaneous approach.
025G3ZZ............................. Destruction of mitral valve,
percutaneous approach.
025H3ZZ............................. Destruction of pulmonary valve,
percutaneous approach.
025J3ZZ............................. Destruction of tricuspid valve,
percutaneous approach.
027F34Z............................. Dilation of aortic valve with drug-
eluting intraluminal device,
percutaneous approach.
027F3DZ............................. Dilation of aortic valve with
intraluminal device, percutaneous
approach.
027F3ZZ............................. Dilation of aortic valve,
percutaneous approach.
027G34Z............................. Dilation of mitral valve with drug-
eluting intraluminal device,
percutaneous approach.
027G3DZ............................. Dilation of mitral valve with
intraluminal device, percutaneous
approach.
027G3ZZ............................. Dilation of mitral valve,
percutaneous approach.
027H34Z............................. Dilation of pulmonary valve with
drug-eluting intraluminal device,
percutaneous approach.
027H3DZ............................. Dilation of pulmonary valve with
intraluminal device, percutaneous
approach.
027H3ZZ............................. Dilation of pulmonary valve,
percutaneous approach.
027J34Z............................. Dilation of tricuspid valve with
drug-eluting intraluminal device,
percutaneous approach.
027J3DZ............................. Dilation of tricuspid valve with
intraluminal device, percutaneous
approach.
027J3ZZ............................. Dilation of tricuspid valve,
percutaneous approach.
02BF3ZZ............................. Excision of aortic valve,
percutaneous approach.
02BG3ZZ............................. Excision of mitral valve,
percutaneous approach.
02BH3ZZ............................. Excision of pulmonary valve,
percutaneous approach.
02BJ3ZZ............................. Excision of tricuspid valve,
percutaneous approach.
------------------------------------------------------------------------
We analyzed claims data from the September 2018 update of the FY
2018 MedPAR file for cases reporting any of the above listed procedure
codes in MS-DRGs 216, 217, 218, 219, 220, and 221, MS-DRGs 228 and 229,
and MS-DRGs 273 and 274. Our findings are shown in the following
tables. We note that there were no cases found in MS-DRGs 228 and 229
reporting ICD-10-PCS procedure code 02TH3ZZ (Resection of pulmonary
valve, percutaneous approach).
Other Cardiac Valve Procedures in MS-DRGs 216 Through 221
----------------------------------------------------------------------------------------------------------------
Number of Average length
ICD-10-PCS code Description times reported of stay Average costs
----------------------------------------------------------------------------------------------------------------
02QF3ZZ........................ Repair aortic valve, 58 9.7 $33,588
percutaneous approach.
02QG3ZE........................ Repair mitral valve created 4 1.3 38,680
from left atrioventricular
valve, percutaneous approach.
02QG3ZZ........................ Repair mitral valve, 40 3.4 30,160
percutaneous approach.
02QH3ZZ........................ Repair pulmonary valve, 1 1 33,014
percutaneous approach.
02QJ3ZG........................ Repair tricuspid valve created 1 9 51,294
from right atrioventricular
valve, percutaneous approach.
02QJ3ZZ........................ Repair tricuspid valve, 15 5 25,208
percutaneous approach.
02VG3ZZ........................ Restriction of mitral valve, 11 8.1 53,798
percutaneous approach.
02WF38Z........................ Revision of zooplastic tissue 26 8.9 61,124
in aortic valve, percutaneous
approach.
02WF3JZ........................ Revision of synthetic 37 7.1 26,605
substitute in aortic valve,
percutaneous approach.
02WF3KZ........................ Revision of nonautologous 2 1 69,030
tissue substitute in aortic
valve, percutaneous approach.
02WG38Z........................ Revision of zooplastic tissue 2 7.5 16,982
in mitral valve, percutaneous
approach.
02WG3JZ........................ Revision of synthetic 31 7.3 28,682
substitute in mitral valve,
percutaneous approach.
02WH3JZ........................ Revision of synthetic 1 6 30,340
substitute in pulmonary valve,
percutaneous approach.
02WJ3JZ........................ Revision of synthetic 1 3 14,145
substitute in tricuspid valve,
percutaneous approach.
-----------------------------------------------
Total...................... ............................... 230 7.1 34,968
----------------------------------------------------------------------------------------------------------------
Other Cardiac Valve Procedures in MS-DRGs 273 and 274
----------------------------------------------------------------------------------------------------------------
Number of Average length
ICD-10-PCS code Description times reported of stay Average costs
----------------------------------------------------------------------------------------------------------------
025F3ZZ........................ Destruction of aortic valve, 6 4.7 $11,130
percutaneous approach.
[[Page 19192]]
025J3ZZ........................ Destruction of tricuspid valve, 21 3.9 18,320
percutaneous approach.
027F34Z........................ Dilation of aortic valve with 1 16 53,786
drug-eluting intraluminal
device, percutaneous approach.
027F3DZ........................ Dilation of aortic valve with 5 8.4 20,951
intraluminal device,
percutaneous approach.
027F3ZZ........................ Dilation of aortic valve, 1,720 8.6 25,265
percutaneous approach.
027G3ZZ........................ Dilation of mitral valve, 86 6.4 19,791
percutaneous approach.
027H3ZZ........................ Dilation of pulmonary valve, 5 3.8 10,506
percutaneous approach.
02BJ3ZZ........................ Excision of tricuspid valve, 1 4 30,843
percutaneous approach.
-----------------------------------------------
Total...................... ............................... 1,845 8.4 24,851
----------------------------------------------------------------------------------------------------------------
We found that the overall frequency with which cases reporting at
least one of the above ICD-10-PCS procedure codes were reflected in the
claims data was 2,075 times with an average length of stay of 8.5 days
and average costs of $27,838. ICD-10-PCS procedure code 027F3ZZ
(Dilation of aortic valve, percutaneous approach) had the highest
frequency of 1,720 times with an average length of stay of 8.6 days and
average costs of $25,265. We also found that cases reporting ICD-10-PCS
procedure code 02WF3KZ (Revision of nonautologous tissue substitute in
aortic valve, percutaneous approach) had the highest average costs of
$69,030 with an average length of stay of 1 day. While not displayed
above, we also note that, of the 7,785 cases found in MS-DRG 273, from
the remaining procedure codes describing procedures other than those
performed on a cardiac valve, there were 4,920 cases reporting ICD-10-
PCS procedure code 02583ZZ (Destruction of conduction mechanism,
percutaneous approach) with an average length of stay of 6.6 days and
average costs of $26,800, representing approximately 63 percent of all
the cases in that MS-DRG. In addition, of the 20,434 cases in MS-DRG
274, from the remaining procedure codes describing procedures other
than those performed on a cardiac valve, there were 9,268 cases
reporting ICD-10-PCS procedure code 02583ZZ (Destruction of conduction
mechanism, percutaneous approach) with an average length of stay of 3.2
days and average costs of $21,689, and 8,775 cases reporting ICD-10-PCS
procedure code 02L73DK (Occlusion of left atrial appendage with
intraluminal device, percutaneous approach) with an average length of
stay of 1.2 days and average costs of $25,476, representing
approximately 88 percent of all the cases in that MS-DRG.
After analyzing the claims data to identify the overall frequency
with which the other (non-supplement) ICD-10-PCS procedure codes
describing a transcatheter (endovascular) cardiac valve procedure were
reported and assigned to MS-DRGs 216, 217, 218, 219, 220, and 221, MS-
DRGs 228 and 229, and MS-DRGs 273 and 274, our clinical advisors
suggested that these other cardiac valve procedures should be grouped
together because the procedure codes are describing procedures
performed on a cardiac valve with a percutaneous (transcatheter/
endovascular) approach, they can be performed in a cardiac
catheterization laboratory, they require that the interventional
cardiologist have special additional training and skills, and often
require additional ancillary procedures and equipment, such as trans-
esophageal echocardiography, be available at the time of the procedure.
Our clinical advisors noted that these procedures are generally
considered more complicated and resource-intensive, and form a
clinically coherent group. They also noted that the majority of
procedures currently being reported in MS-DRGs 273 and 274 are
procedures other than those involving a cardiac valve and, therefore,
believed that reassignment of the other (non-supplement) ICD-10-PCS
procedure codes describing a transcatheter (endovascular) cardiac valve
procedure would have minimal impact to those MS-DRGs.
We then analyzed the impact of grouping the other transcatheter
cardiac valve procedures. The following table reflects our findings for
the suggested other endovascular cardiac valve procedures MS-DRGs with
a 2-way severity level split.
Suggested MS-DRGs for Other Endovascular Cardiac Valve Procedures
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG XXX (Other Endovascular Cardiac Valve Procedures with 1,527 9.7 $27,801
MCC)...........................................................
MS-DRG XXX (Other Endovascular Cardiac Valve Procedures without 560 3.9 17,027
MCC)...........................................................
----------------------------------------------------------------------------------------------------------------
As shown in the table, there were 1,527 cases for the other
endovascular cardiac valve procedures with MCC group, with an average
length of stay of 9.7 days and average costs of $27,801. There was a
total of 560 cases for the other endovascular cardiac valve procedures
without MCC group, with an average length of stay of 3.9 days and
average costs of $17,027. We applied the criteria to create subgroups
for the two-way severity level split for the suggested MS-DRGs and
found that all five criteria were met. For the suggested MS-DRGs, there
is at least (1) 500 or more cases in the MCC group or in the without
MCC subgroup; (2) 5 percent or more of the cases in the MCC group or in
the without MCC subgroup; (3) a 20 percent difference in average costs
between the MCC group and the without MCC group; (4) at least a $2,000
difference in average costs between the MCC group and the without MCC
group; and (5) a 3-percent reduction in cost variance, indicating that
the proposed severity level splits increase the explanatory power of
the base MS-DRG in capturing differences in expected cost between the
proposed MS-DRG severity level splits by at least 3 percent and thus
improve the overall accuracy of the IPPS payment system.
[[Page 19193]]
For FY 2020, we are proposing to modify the structure of MS-DRGs
266 and 267 by reassigning the procedure codes describing a
transcatheter cardiac valve repair (supplement) procedure from the list
above and to revise the title of these MS-DRGs. We are proposing to
revise the title of MS-DRGs 266 from ``Endovascular Cardiac Valve
Replacement with MCC'' to ``Endovascular Cardiac Valve Replacement and
Supplement Procedures with MCC'' and the title of MS-DRG 267 from
``Endovascular Cardiac Valve Replacement without MCC'' to
``Endovascular Cardiac Valve Replacement and Supplement Procedures
without MCC'', to reflect the proposed restructuring. We also are
proposing to create two new MS-DRGs with a two-way severity level split
for the remaining (non-supplement) transcatheter cardiac valve
procedures listed above. These proposed new MS-DRGs are proposed new
MS-DRG 319 (Other Endovascular Cardiac Valve Procedures with MCC) and
proposed new MS-DRG 320 (Other Endovascular Cardiac Valve Procedures
without MCC), which would also conform with the severity level split of
MS-DRGs 266 and 267. We are proposing to reassign the procedure codes
from their current MS-DRGs to the proposed new MS-DRGs.
b. Revision of Pacemaker Lead
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41189 through
41190), we finalized our proposal to maintain the Version 35 ICD-10 MS-
DRG GROUPER logic for the Version 36 ICD-10 MS-DRG GROUPER logic within
MS-DRGs 260, 261, and 262 (Cardiac Pacemaker Revision Except Device
Replacement with MCC, with CC and without CC/MCC, respectively) so that
cases reporting any of the ICD-10-PCS procedure codes describing
procedures involving pacemakers and related procedures and associated
devices would continue to be assigned to those MS-DRGs under MDC 5
because they are reported when a pacemaker device requires revision and
they have a corresponding circulatory system diagnosis. We also
discussed and finalized the addition of ICD-10-PCS procedure codes
02H63MZ (Insertion of cardiac lead into right atrium, percutaneous
approach) and 02H73MZ (Insertion of cardiac lead into left atrium,
percutaneous approach) to the GROUPER logic as non-O.R. procedures that
impact the MS-DRG assignment when reported as stand-alone codes for the
insertion of a pacemaker lead within MS-DRGs 260, 261, and 262 in
response to a commenter's suggestion.
After publication of the FY 2019 IPPS/LTCH PPS final rule, it was
brought to our attention that ICD-10-PCS procedure code 02H60JZ
(Insertion of pacemaker lead into right atrium, open approach) was
inadvertently omitted from the GROUPER logic for MS-DRGs 260, 261, and
262. This procedure code is designated as a non-O.R. procedure.
However, we note that, within MDC 5, in MS-DRGs 242, 243, and 244, this
procedure code is part of a code pair that requires another procedure
code (cluster). We are proposing to add procedure code 02H60JZ to the
list of non-O.R. procedures that would impact MS-DRGs 260, 261, and 262
when reported as a stand-alone procedure code, consistent with ICD-10-
PCS procedure codes 02H63JZ (Insertion of pacemaker lead into right
atrium, percutaneous approach) and 02H64JZ (Insertion of pacemaker lead
into right atrium, percutaneous endoscopic approach), which also
describe the insertion of a pacemaker lead into the right atrium. If
the proposal is finalized, we would make conforming changes to the ICD-
10 MS-DRG Definitions Manual Version 37.
6. MDC 8 (Diseases and Disorders of the Musculoskeletal System and
Connective Tissue)
a. Knee Procedures With Principal Diagnosis of Infection
We received a request to add ICD-10-CM diagnosis codes M00.9
(Pyogenic arthritis, unspecified) and A54.42 (Gonococcal arthritis) to
the list of principal diagnoses for MS-DRGs 485, 486, and 487 (Knee
Procedure with Principal Diagnosis of Infection with MCC, with CC, and
without CC/MCC, respectively) in MDC 8. The requestor believed that
adding diagnosis code M00.9 is necessary to accurately recognize knee
procedures that are performed with a principal diagnosis of infectious
arthritis, including those procedures performed when the specific
infectious agent is unknown. The requestor stated that, currently, only
diagnosis codes describing infections caused by a specific bacterium
are included in MS-DRGs 485, 486, and 487. The requestor stated that
additional diagnosis codes such as M00.9 are indicated for knee
procedures performed as a result of infection because pyogenic
arthritis can reasonably be diagnosed based on the patient's history
and clinical symptoms, even if a bacterial infection is not confirmed
by culture. For example, the requestor noted that a culture may present
negative for infection if a patient has been treated with antibiotics
prior to knee surgery, but other clinical signs may indicate a
principal diagnosis of joint infection. In the absence of a culture
identifying an infection by a specific bacterium, the requestor stated
that ICD-10-CM diagnosis code M00.09 should also be included as a
principal diagnosis in MS-DRGs 485, 486, and 487.
The requestor also asserted that ICD-10-CM diagnosis code A54.42
should be added to the list of principal diagnoses for MS-DRGs 485,
486, and 487 because gonococcal arthritis is also an infectious type of
arthritis that can be an indication for a knee procedure.
Currently, cases reporting ICD-10-CM diagnosis codes M00.9 or
A54.42 as a principal diagnosis group to MS-DRGs 488 and 489 (Knee
Procedures without Principal Diagnosis of Infection with and without
CC/MCC, respectively) when a knee procedure is also reported on the
claim.
We analyzed claims data from the September 2018 update of the FY
2018 MedPAR file for ICD-10-CM diagnosis codes M00.9 and A54.42, which
are currently assigned to medical MS-DRGs 548, 549, and 550 (Septic
Arthritis with MCC, with CC, and without CC/MCC, respectively) in the
absence of a surgical procedure. Our findings are shown in the
following table.
MS-DRGs for Septic Arthritis With Pyogenic Arthritis or Gonococcal Arthritis
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 548--All cases........................................... 601 8.1 $13,974
MS-DRG 548--Cases with pyogenic arthritis as principal diagnosis 312 7.6 13,177
MS-DRG 549--All cases........................................... 1,169 5.0 8,547
MS-DRG 549--Cases with pyogenic arthritis as principal diagnosis 686 4.7 7,976
MS-DRG 549--Cases with gonococcal arthritis as principal 2 8.0 7,070
diagnosis......................................................
MS-DRG 550--All cases........................................... 402 3.5 6,317
[[Page 19194]]
MS-DRG 550--Cases with pyogenic arthritis as principal diagnosis 260 3.2 6,209
MS-DRG 550--Cases with gonococcal arthritis as principal 3 2.3 3,929
diagnosis......................................................
----------------------------------------------------------------------------------------------------------------
As shown in the table, we found a total of 2,172 cases in MS-DRGs
548, 549, and 550. A total of 601 cases were reported in MS-DRG 548,
with an average length of stay of 8.1 days and average costs of
$13,974. Cases in MS-DRG 548 with a principal diagnosis of pyogenic
arthritis (ICD-10-CM diagnosis code M00.9) accounted for 312 of these
601 cases, and reported an average length of stay of 7.6 days and
average costs of $13,177. None of the cases in MS-DRG 548 had a
principal diagnosis of gonococcal arthritis (ICD-10-CM diagnosis code
A54.42).
The total number of cases reported in MS-DRG 549 was 1,169, with an
average length of stay of 5 days and average costs of $8,547. Within
this MS-DRG, 686 cases had a principal diagnosis described by ICD-10-CM
diagnosis code M00.9, with an average length of stay of 4.7 days and
average costs of $7,976. Two of the cases reported in MS-DRG 549 had a
principal diagnosis described by ICD-10-CM diagnosis code A54.42. These
2 cases had an average length of stay of 8 days and average costs of
$7,070.
The total number of cases reported in MS-DRG 550 was 402, with an
average length of stay of 3.5 days and average costs of $6,317. Within
this MS-DRG, 260 cases had a principal diagnosis described by ICD-10-CM
diagnosis code M00.9 with an average length of stay of 3.2 days and
average costs of $6,209. Three of the cases reported in MS-DRG 550 had
a principal diagnosis described by ICD-10-CM diagnosis code A54.42.
These 3 cases had an average length of stay of 2.3 days and average
costs of $3,929.
In summary, for MS-DRGs 548, 549, and 550, there were 1,258 cases
that reported ICD-10-CM diagnosis code M00.9 as the principal diagnosis
and 5 cases that reported ICD-10-CM diagnosis code A54.42 as the
principal diagnosis. We note that, overall, our data analysis suggests
that the MS-DRG assignment for cases reporting ICD-10-CM diagnosis
codes M00.9 and A54.42 is appropriate based on the average costs and
average length of stay. However, it is unclear how many of these cases
involved infected knee joints because neither ICD-10-CM diagnosis code
M00.9 nor A54.42 is specific to the knee. We then analyzed claims data
for MS-DRGs 485, 486, and 487 (Knee Procedures with Principal Diagnosis
of Infection with MCC, with CC, and without CC/MCC, respectively) and
for MS-DRGs 488 and 489 (Knee Procedures without Principal Diagnosis of
Infection with and without CC/MCC, respectively). For MS-DRGs 488 and
489, we also analyzed claims data for cases reporting a knee procedure
with ICD-10-CM diagnosis code M00.9 or A54.42 as a principal diagnosis,
as these are the MS-DRGs to which such cases would currently group. Our
findings are shown in the following table.
MS-DRGs for Knee Procedures With and Without Infection
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 485--All cases........................................... 1,021 9.7 $23,980
MS-DRG 486--All cases........................................... 2,260 6 16,060
MS-DRG 487--All cases........................................... 614 4.2 12,396
MS-DRG 488--All cases........................................... 2,857 4.8 14,197
MS-DRG 488--Cases with pyogenic arthritis as principal diagnosis 524 7.1 16,894
MS-DRG 489--All cases........................................... 2,416 2.4 9,217
MS-DRG 489--Cases with pyogenic arthritis as principal diagnosis 195 4.1 9,526
MS-DRG 489--Cases with gonococcal arthritis as principal 1 8 10,810
diagnosis......................................................
----------------------------------------------------------------------------------------------------------------
As shown in the table, we found a total of 1,021 cases reported in
MS-DRG 485, with an average length of stay of 9.7 days and average
costs of $23,980. We found a total of 2,260 cases reported in MS-DRG
486, with an average length of stay of 6.0 days and average costs of
$16,060. The total number of cases reported in MS-DRG 487 was 614, with
an average length of stay of 4.2 days and average costs of $12,396. For
MS-DRG 488, we found a total of 2,857 cases with an average length of
stay of 4.8 days and average costs of $14,197. Of these 2,857 cases, we
found 524 cases that reported a principal diagnosis of pyogenic
arthritis (ICD-10-CM diagnosis code M00.9), with an average length of
stay of 7.1 days and average costs of $16,894. There were no cases
found that reported a principal diagnosis of gonococcal arthritis (ICD-
10-CM diagnosis code A54.42). For MS-DRG 489, we found a total of 2,416
cases with an average length of stay of 2.4 days and average costs of
$9,217. Of these 2,416 cases, we found 195 cases that reported a
principal diagnosis of pyogenic arthritis (ICD-10-CM diagnosis code
M00.9), with an average length of stay of 4.1 days and average costs of
$9,526. We found 1 case that reported a principal diagnosis of
gonococcal arthritis (ICD-10-CM diagnosis code A54.42) in MS-DRG 489,
with an average length of stay of 8 days and average costs of $10,810.
Upon review of the data, we noted that the average costs and
average length of stay for cases reporting a principal diagnosis of
pyogenic arthritis (ICD-10-CM diagnosis code M00.9) in MS-DRG 488 are
higher than the average costs and average length of stay for all cases
in MS-DRG 488. We found similar results for MS-DRG 489 for the cases
reporting diagnosis code M00.9 or A54.42 as the principal diagnosis.
As stated earlier, the requestor recommended that ICD-10-CM
diagnosis codes M00.9 and A54.42 be added to the list of principal
diagnoses in MS-DRGs 485, 486, and 487 to recognize knee procedures
that are performed with a principal diagnosis of an infectious type of
arthritis. Because these diagnosis codes are not specific to the knee
in the code description, we
[[Page 19195]]
examined the ICD-10-CM Alphabetic Index to review the entries that
refer and correspond to these diagnosis codes. Specifically, we
searched the Index for codes M00.9 and A54.42 and found the following
entries.
[GRAPHIC] [TIFF OMITTED] TP03MY19.000
Our clinical advisors agreed that the results of our ICD-10-CM
Alphabetic Index review combined with the data analysis results support
the addition of ICD-10-CM diagnosis code M00.9 to the list of principal
diagnoses of infection for MS-DRGs 485, 486, and 487. The entries for
diagnosis code M00.9 include infection of the knee, and as discussed
above, in our data analysis, we found cases reporting ICD-10-CM
diagnosis code M00.9 as a principal diagnosis in MS-DRGs 488 and 489,
indicating that knee procedures are, in fact, being performed for an
infectious arthritis of the knee. In addition, the average costs for
cases reporting a principal diagnosis code of pyogenic arthritis (ICD-
10-CM diagnosis code M00.9) in MS-DRG 488 are similar to the average
costs of cases in MS-DRG 486 ($16,894 and $16,060, respectively).
Because MS-DRG 488 includes cases with a CC or an MCC, we reviewed how
many of the 524 cases reporting a principal diagnosis code of pyogenic
arthritis (ICD-10-CM diagnosis code M00.9) were reported with a CC or
an MCC. We found that there were 361 cases reporting a CC with an
average length of stay of 6 days and average costs of $14,092 and 163
cases reporting an MCC with an average length of stay of 9.5 days and
average costs of $23,100. Therefore, the cases in MS-DRG 488 reporting
a principal diagnosis code of pyogenic arthritis (ICD-10-CM diagnosis
code M00.9) with an MCC have average costs that are consistent with the
average costs of cases in MS-DRG 485 ($23,100 and $23,980,
respectively), and the cases with a CC have average costs that are
consistent with the average costs of cases in MS-DRG 486 ($14,092 and
$16,060, respectively), as noted above.
[[Page 19196]]
We also note that the average length of stay for cases reporting a
principal diagnosis code of pyogenic arthritis (ICD-10-CM diagnosis
code M00.9) with an MCC in MS-DRG 488 is similar to the average length
of stay for cases in MS-DRG 485 (9.5 days and 9.7 days, respectively),
and the cases with a CC have an average length of stay that is
equivalent to the average length of stay for cases in MS-DRG 486 (6
days and 6 days, respectively). We further note that the average length
of stay for cases reporting a principal diagnosis code of pyogenic
arthritis (ICD-10-CM diagnosis code M00.9) in MS-DRG 489 is similar to
the average length of stay for cases in MS DRG 487 (4.1 days and 4.2
days, respectively). Lastly, the average costs for cases reporting a
principal diagnosis code of pyogenic arthritis (ICD-10-CM diagnosis
code M00.9) in MS-DRG 489 are consistent with the average costs for
cases in MS-DRG 487 ($9,526 and $12,396, respectively), with a
difference of $2,870. For these reasons, we are proposing to add ICD-
10-CM diagnosis code M00.9 to the list of principal diagnosis codes for
MS-DRGs 485, 486, and 487.
Our clinical advisors did not support the addition of ICD-10-CM
diagnosis code A54.42 to the list of principal diagnosis codes for MS-
DRGs 485, 486, and 487 because ICD-10-CM diagnosis code A54.42 is not
specifically indexed to include the knee or any infection in the knee.
Therefore, we are not proposing to add ICD-10-CM diagnosis code A54.42
to the list of principal diagnosis codes for these MS-DRGs.
Upon review of the existing list of principal diagnosis codes for
MS-DRGs 485, 486, and 487, our clinical advisors recommended that we
review the following ICD-10-CM diagnosis codes currently included on
the list of principal diagnosis codes because the codes are not
specific to the knee.
------------------------------------------------------------------------
ICD-10-CM code Code description
------------------------------------------------------------------------
M86.9..................... Osteomyelitis, unspecified.
T84.50XA.................. Infection and inflammatory reaction due to
unspecified internal joint prosthesis,
initial encounter.
T84.51XA.................. Infection and inflammatory reaction due to
internal right hip prosthesis, initial
encounter.
T84.52XA.................. Infection and inflammatory reaction due to
internal left hip prosthesis, initial
encounter.
T84.59XA.................. Infection and inflammatory reaction due to
other internal joint prosthesis, initial
encounter.
T84.60XA.................. Infection and inflammatory reaction due to
internal fixation device of unspecified
site, initial encounter.
T84.63XA.................. Infection and inflammatory reaction due to
internal fixation device of spine, initial
encounter.
T84.69XA.................. Infection and inflammatory reaction due to
internal fixation device of other site,
initial encounter.
------------------------------------------------------------------------
These ICD-10-CM diagnosis codes are currently assigned to medical
MS-DRGs 559, 560, and 561 (Aftercare, Musculoskeletal System and
Connective Tissue with MCC, with CC, and without CC/MCC, respectively)
within MDC 8 in the absence of a surgical procedure. Similar to the
process described above, we examined the ICD-10-CM Alphabetic Index to
review the entries that refer and correspond to the diagnosis codes
shown in the table above. We found the following entries.
------------------------------------------------------------------------
-------------------------------------------------------------------------
Index entries referring to M86.9: Osteomyelitis (general) (infective)
(localized) (neonatal) (purulent) (septic) (staphylococcal)
(streptococcal) (suppurative) (with periostitis).
Index entries referring to T84.50XA:Complication(s) (from) (of) > joint
prosthesis, internal > infection or inflammation Infection, infected,
infective (opportunistic) > joint NEC > due to internal joint
prosthesis.
Index entries referring to T84.51XA: Infection, infected, infective
(opportunistic) > hip (joint) NEC > due to internal joint prosthesis >
right.
Index entries referring to T84.52XA: Infection, infected, infective
(opportunistic) > hip (joint) NEC > due to internal joint prosthesis >
left.
Index entries referring to T84.59XA: Complication(s) (from) (of) > joint
prosthesis, internal > infection or inflammation > specified joint NEC
Infection, infected, infective (opportunistic) > shoulder (joint) NEC >
due to internal joint prosthesis.
Index entries referring to T84.60XA: Complication(s) (from) (of) >
fixation device, internal (orthopedic) > infection and inflammation.
Index entries referring to T84.63XA: Complication(s) (from) (of) >
fixation device, internal (orthopedic) > infection and inflammation >
spine.
Index entries referring to T84.69XA: Complication(s) (from) (of) >
fixation device, internal (orthopedic) > infection and inflammation >
specified site NEC.
------------------------------------------------------------------------
The Index entries for the ICD-10-CM diagnosis codes listed above
reflect terms relating to an infection. However, none of the entries is
specific to the knee. In addition, we note that there are other
diagnosis codes in the subcategory T84.5- series (Infection and
inflammatory reaction due to internal joint prosthesis) that are
specific to the knee. For example, ICD-10-CM diagnosis code T84.53X-
(Infection and inflammatory reaction due to internal right knee
prosthesis) or ICD-10-CM diagnosis code T84.54X- (Infection and
inflammatory reaction due to internal left knee prosthesis) with the
appropriate 7th digit character to identify initial encounter,
subsequent encounter or sequela, would be reported to identify a
documented infection of the right or left knee due to an internal
prosthesis. We further note that these ICD-10-CM diagnosis codes
(T84.53X- and T84.54X-) with the 7th character ``A'' for initial
encounter are currently already in the list of principal diagnosis
codes for MS-DRGs 485, 486, and 487.
Our clinical advisors support the removal of the above ICD-10-CM
diagnosis codes from the list of principal diagnosis codes for MS-DRGs
485, 486, and 487 because they are not specifically indexed to include
an infection of the knee and there are other diagnosis codes in the
subcategory T84.5- series that uniquely identify an infection and
inflammatory reaction of the right or left knee due to an internal
prosthesis as noted above.
We also analyzed claims data for MS-DRGs 485, 486 and 487 to
identify cases reporting one of the above listed ICD-10-CM diagnosis
codes not specific to the knee as a principal diagnosis. Our findings
are shown in the following table.
[[Page 19197]]
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 485--Cases reporting principal diagnosis code not 13 11.2 $30,765
specific to the knee...........................................
MS-DRG 486--Cases reporting principal diagnosis code not 43 6.5 15,837
specific to the knee...........................................
MS-DRG 487--Cases reporting principal diagnosis code not 7 2.6 11,362
specific to the knee...........................................
----------------------------------------------------------------------------------------------------------------
For MS-DRG 485, we found 13 cases reporting one of the diagnosis
codes not specific to the knee as a principal diagnosis with an average
length of stay of 11.2 days and average costs of $30,765. For MS-DRG
486, we found 43 cases reporting one of the diagnosis codes not
specific to the knee as a principal diagnosis with an average length of
stay of 6.5 days and average costs of $15,837. For MS-DRG 487, we found
7 cases reporting one of the diagnosis codes not specific to the knee
as a principal diagnosis with an average length of stay of 2.6 days and
average costs of $11,362.
Overall, for MS-DRGs 485, 486, and 487, there were a total of 63
cases reporting one of the ICD-10-CM diagnosis codes not specific to
the knee as a principal diagnosis with an average length of stay of 7
days and average costs of $18,421. Of those 63 cases, there were 32
cases reporting a principal diagnosis code from the ICD-10-CM
subcategory T84.5-series (Infection and inflammatory reaction due to
internal joint prosthesis); 23 cases reporting a principal diagnosis
code from the ICD-10-CM subcategory T84.6-series (Infection and
inflammatory reaction due to internal fixation device), with 22 of the
23 cases reporting ICD-10-CM diagnosis code T84.69XA (Infection and
inflammatory reaction due to internal fixation device of other site,
initial encounter) and 1 case reporting ICD-10-CM diagnosis code
T84.63XA (Infection and inflammatory reaction due to internal fixation
device of spine, initial encounter); and 8 cases reporting ICD-10-CM
diagnosis code M86.9 (Osteomyelitis, unspecified) as a principal
diagnosis.
Our clinical advisors believe that there may have been coding
errors among the 63 cases reporting a principal diagnosis of infection
not specific to the knee. For example, 32 cases reported a principal
diagnosis code from the ICD-10-CM subcategory T84.5-series (Infection
and inflammatory reaction due to internal joint prosthesis) that was
not specific to the knee and, as stated previously, there are other
codes in this subcategory that uniquely identify an infection and
inflammatory reaction of the right or left knee due to an internal
prosthesis.
Based on the results of our claims analysis and input from our
clinical advisors, we are proposing to remove the following ICD-10-CM
diagnosis codes that do not describe an infection of the knee from the
list of principal diagnosis codes for MS-DRGs 485, 486, and 487: M86.9;
T84.50XA; T84.51XA; T84.52XA; T84.59XA; T84.60XA; T84.63XA; and
T84.69XA. We are not proposing to change the current assignment of
these diagnosis codes in MS-DRGs 559, 560, and 561.
In addition, our clinical advisors recommended that we add the
following ICD-10-CM diagnosis codes as principal diagnosis codes for
MS-DRGs 485, 486, and 487 because they are specific to the knee and
describe an infection.
------------------------------------------------------------------------
ICD-10-CM code Code description
------------------------------------------------------------------------
A18.02.................... Tuberculous arthritis of other joints.
M01.X61................... Direct infection of right knee in infectious
and parasitic diseases classified
elsewhere.
M01.X62................... Direct infection of left knee in infectious
and parasitic diseases classified
elsewhere.
M01.X69................... Direct infection of unspecified knee in
infectious and parasitic diseases
classified elsewhere.
M71.061................... Abscess of bursa, right knee.
M71.062................... Abscess of bursa, left knee.
M71.069................... Abscess of bursa, unspecified knee.
M71.161................... Other infective bursitis, right knee.
M71.162................... Other infective bursitis, left knee.
M71.169................... Other infective bursitis, unspecified knee.
------------------------------------------------------------------------
ICD-10-CM diagnosis code A18.02 (Tuberculous arthritis of other
joints) is currently assigned to medical MS-DRGs 548, 549, and 550
(Septic Arthritis with MCC, with CC, and without CC/MCC, respectively)
within MDC 8 and MS-DRGs 974, 975, and 976 (HIV with Major Related
Condition with MCC, with CC, and without CC/MCC, respectively) within
MDC 25 (Human Immunodeficiency Virus Infections) in the absence of a
surgical procedure. ICD-10-CM diagnosis codes M01.X61 (Direct infection
of right knee in infectious and parasitic diseases classified
elsewhere), M01.X62 (Direct infection of left knee in infectious and
parasitic diseases classified elsewhere), and M01.X69 (Direct infection
of unspecified knee in infectious and parasitic diseases classified
elsewhere) are currently assigned to medical MS-DRGs 548, 549, and 550
(Septic Arthritis with MCC, with CC, and without CC/MCC, respectively)
within MDC 8 in the absence of a surgical procedure. ICD-10-CM
diagnosis codes M71.061 (Abscess of bursa, right knee), M71.062
(Abscess of bursa, left knee), M71.069 (Abscess of bursa, unspecified
knee), M71.161 (Other infective bursitis, right knee), M71.162 (Other
infective bursitis, left knee), and M71.169 (Other infective bursitis,
unspecified knee) are currently assigned to medical MS-DRGs 557 and 558
(Tendonitis, Myositis and Bursitis with and without MCC, respectively)
within MDC 8 in the absence of a surgical procedure.
Similar to the process described above, we examined the ICD-10-CM
Alphabetic Index to review the entries that refer and correspond to the
diagnosis codes shown in the table above. We found the following
entries.
BILLING CODE 4120-01-P
[[Page 19198]]
[GRAPHIC] [TIFF OMITTED] TP03MY19.001
[[Page 19199]]
[GRAPHIC] [TIFF OMITTED] TP03MY19.002
[[Page 19200]]
[GRAPHIC] [TIFF OMITTED] TP03MY19.003
BILLING CODE 4120-01-C
We note that there were no Index entries specifically for ICD-10-CM
diagnosis codes M71.061, M71.062, M71.069, M71.161, M71.162, and
M71.169. Rather, there were Index entries at the subcategory levels of
M71.06- and M71.16-. We found the following entries.
[[Page 19201]]
------------------------------------------------------------------------
-------------------------------------------------------------------------
Index entry referring to M71.06-: (connective tissue) (embolic)
(fistulous) (infective) (metastatic) (multiple) (pernicious) (pyogenic)
(septic) > bursa > knee.
Index entry referring to M71.16-: Infective NEC > knee.
------------------------------------------------------------------------
Our clinical advisors agreed that the results of our review of the
ICD-10-CM Alphabetic Index support the addition of these ICD-10-CM
diagnosis codes to MS-DRGs 485, 486, and 487 because the Index entries
and/or the code descriptions clearly describe or include an infection
that is specific to the knee.
Therefore, we are proposing to add the following ICD-10-CM
diagnosis codes to the list of principal diagnosis codes for MS-DRGs
485, 486, and 487: A18.02; M01.X61; M01.X62; M01.X69; M71.061; M71.062;
M71.069; M71.161; M71.162; and M71.169.
b. Neuromuscular Scoliosis
We received a request to add ICD-10-CM diagnosis codes describing
neuromuscular scoliosis to the list of principal diagnosis codes for
MS-DRGs 456, 457, and 458 (Spinal Fusion except Cervical with Spinal
Curvature or Malignancy or Infection or Extensive Fusions with MCC,
with CC, and without CC/MCC, respectively). Excluding the ICD-10-CM
diagnosis codes that address the cervical spine, the following ICD-10-
CM diagnosis codes are used to describe neuromuscular scoliosis.
------------------------------------------------------------------------
ICD-10-CM code Code description
------------------------------------------------------------------------
M41.40.................... Neuromuscular scoliosis, site unspecified.
M41.44.................... Neuromuscular scoliosis, thoracic region.
M41.45.................... Neuromuscular scoliosis, thoracolumbar
region.
M41.46.................... Neuromuscular scoliosis, lumbar region.
M41.47.................... Neuromuscular scoliosis, lumbosacral region.
------------------------------------------------------------------------
The requestor asserted that all levels of neuromuscular scoliosis,
except cervical, should group to the non-cervical spinal fusion MS-DRGs
for spinal curvature (MS-DRGs 456, 457, and 458). The requestor also
noted that the current MS-DRG logic only groups cases reporting
neuromuscular scoliosis to MS-DRGs 456, 457, and 458 when neuromuscular
scoliosis is reported as a secondary diagnosis. The requestor contended
that it would be rare for a diagnosis of neuromuscular scoliosis to be
reported as a secondary diagnosis because there is not a ``code first''
note in the ICD-10-CM Tabular List of Diseases and Injuries indicating
to ``code first'' the underlying cause. According to the requestor,
when a diagnosis of neuromuscular scoliosis is the reason for an
admission for non-cervical spinal fusion, neuromuscular scoliosis must
be sequenced as the principal diagnosis because it is the chief
condition responsible for the admission. However, this sequencing,
which adheres to the ICD-10-CM Official Guidelines for Coding and
Reporting, prevents the admission from grouping to the non-cervical
spinal fusion MS-DRGs for spinal curvature caused by neuromuscular
scoliosis.
We analyzed claims data from the September 2018 update of the FY
2018 MedPAR file for cases reporting any of the ICD-10-CM diagnosis
codes describing neuromuscular scoliosis (as listed previously) as a
principal diagnosis with a non-cervical spinal fusion, which are
currently assigned to MS-DRGs 459 and 460 (Spinal Fusion except
Cervical with MCC and without MCC, respectively). Our findings are
shown in the following table.
MS-DRGs for Cases Involving Non-Cervical Spinal Fusion With Principal Diagnosis of Neuromuscular Scoliosis
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 459--All cases........................................... 3,903 8.6 $46,416
MS-DRG 459--Cases with principal diagnosis of neuromuscular 3 15.3 95,745
scoliosis......................................................
MS-DRG 460--All cases........................................... 52,597 3.3 28,754
MS-DRG 460--Cases with principal diagnosis of neuromuscular 8 4.3 71,406
scoliosis......................................................
----------------------------------------------------------------------------------------------------------------
The data reveal that there was a total of 56,500 cases in MS-DRGs
459 and 460. We found 3,903 cases reported in MS-DRG 459, with an
average length of stay of 8.6 days and average costs of $46,416. Of
these 3,903 cases, 3 reported a principal diagnosis code of
neuromuscular scoliosis, with an average length of stay of 15.3 days
and average costs of $95,745. We found a total of 52,597 cases in MS-
DRG 460, with an average length of stay of 3.3 days and average costs
of $28,754. Of these 52,597 cases, 8 cases reported a principal
diagnosis code describing neuromuscular scoliosis, with an average
length of stay of 4.3 days and average costs of $71,406. The data
clearly demonstrate that the average costs and average length of stay
for the small number of cases reporting a principal diagnosis of
neuromuscular scoliosis are higher in comparison to all the cases in
their assigned MS-DRG.
We also analyzed claims data for MS-DRGs 456, 457, and 458 (Spinal
Fusion except Cervical with Spinal Curvature or Malignancy or Infection
or Extensive Fusions with MCC, with CC, and without CC/MCC,
respectively) to identify the spinal fusion cases reporting any of the
ICD-10-CM codes describing neuromuscular scoliosis (as listed
previously) as a secondary diagnosis. Our findings are shown in the
following table.
[[Page 19202]]
MS-DRGs for Cases Involving Non-Cervical Spinal Fusion With Spinal Curvature or Malignancy or Infection or
Extensive Fusions With Secondary Diagnosis of Neuromuscular Scoliosis
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 456--All cases........................................... 1,344 12.0 $66,012
MS-DRG 456--Cases with secondary diagnosis of neuromuscular 6 18.2 79,809
scoliosis......................................................
MS-DRG 457--All cases........................................... 3,654 6.2 47,577
MS-DRG 457--Cases with secondary diagnosis of neuromuscular 12 4.5 31,646
scoliosis......................................................
MS-DRG 458--All cases........................................... 1,245 3.4 34,179
MS-DRG 458--Cases with secondary diagnosis of neuromuscular 6 3.3 31,117
scoliosis......................................................
----------------------------------------------------------------------------------------------------------------
The data indicate that there were 1,344 cases reported in MS-DRG
456, with an average length of stay of 12 days and average costs of
$66,012. Of these 1,344 cases, 6 cases reported a secondary diagnosis
code describing neuromuscular scoliosis, with an average length of stay
of 18.2 days and average costs of $79,809. We found a total of 3,654
cases in MS-DRG 457, with an average length of stay of 6.2 days and
average costs of $47,577. Twelve of these 3,654 cases reported a
secondary diagnosis code describing neuromuscular scoliosis, with an
average length of stay of 4.5 days and average costs of $31,646.
Finally, the 1,245 cases reported in MS-DRG 458 had an average length
of stay of 3.4 days and average costs of $34,179. Of these 1,245 cases,
6 cases reported neuromuscular scoliosis as a secondary diagnosis, with
an average length of stay of 3.3 days and average costs of $31,117.
We reviewed the ICD-10-CM Tabular List of Diseases for subcategory
M41.4 and confirmed there is a ``Code also underlying condition'' note.
We also reviewed the ICD-10-CM Official Guidelines for Coding and
Reporting for the ``code also'' note at Section 1.A.12.b., which
states: ``A `code also' note instructs that two codes may be required
to fully describe a condition, but this note does not provide
sequencing direction.'' Our clinical advisors agree that the sequencing
of the ICD-10-CM diagnosis codes is determined by which condition leads
to the encounter and is responsible for the admission. They also note
that there may be instances in which the underlying cause of the
diagnosis of neuromuscular scoliosis is not treated or responsible for
the admission.
As discussed earlier, our review of the claims data shows that a
small number of cases reported neuromuscular scoliosis either as a
principal diagnosis in MS-DRGs 459 and 460 or as a secondary diagnosis
in MS-DRGs 456, 457, and 458. Our clinical advisors agree that while
the volume of cases is small, the average costs and average length of
stay for the cases reporting neuromuscular scoliosis as a principal
diagnosis with a non-cervical spinal fusion currently grouping to MS-
DRGs 459 and 460 are more aligned with the average costs and average
length of stay for the cases reporting neuromuscular scoliosis as a
secondary diagnosis with a non-cervical spinal fusion currently
grouping to MS-DRGs 456, 457, and 458. Therefore, for the reasons
described above, we are proposing to add the following ICD-10-CM codes
describing neuromuscular scoliosis to the list of principal diagnosis
codes for MS-DRGs 456, 457, and 458: M41.40; M41.44; M41.45; M41.46;
and M41.47.
c. Secondary Scoliosis and Secondary Kyphosis
We received a request to add ICD-10-CM diagnosis codes describing
secondary scoliosis and secondary kyphosis to the list of principal
diagnoses for MS-DRGs 456, 457, and 458 (Spinal Fusion except Cervical
with Spinal Curvature or Malignancy or Infection or Extensive Fusions
with MCC, with CC, and without CC/MCC, respectively). Excluding the
ICD-10-CM diagnosis codes that address the cervical spine, the
following ICD-10-CM diagnosis codes are used to describe secondary
scoliosis.
------------------------------------------------------------------------
ICD-10-CM code Code description
------------------------------------------------------------------------
M41.50.................... Other secondary scoliosis, site unspecified.
M41.54.................... Other secondary scoliosis, thoracic region.
M41.55.................... Other secondary scoliosis, thoracolumbar
region.
M41.56.................... Other secondary scoliosis, lumbar region.
M41.57.................... Other secondary scoliosis, lumbosacral
region.
------------------------------------------------------------------------
Excluding the ICD-10-CM diagnosis codes that address the cervical
spine, the following ICD-10-CM diagnosis codes are used to describe
secondary kyphosis.
------------------------------------------------------------------------
ICD-10-CM code Code description
------------------------------------------------------------------------
M40.10.................... Other secondary kyphosis, site unspecified.
M40.14.................... Other secondary kyphosis, thoracic region.
M40.15.................... Other secondary kyphosis, thoracolumbar
region.
------------------------------------------------------------------------
The requestor stated that generally in cases of diagnoses of
secondary scoliosis or kyphosis, the underlying cause of the condition
is not treated or is not responsible for the admission. If a patient is
admitted for surgery to correct non-cervical spinal curvature, it is
appropriate to sequence the diagnosis of secondary scoliosis or
secondary kyphosis as principal diagnosis. However, reporting a
diagnosis of secondary scoliosis or secondary
[[Page 19203]]
kyphosis as the principal diagnosis with a non-cervical spinal fusion
procedure results in the case grouping to MS-DRG 459 or 460 (Spinal
Fusion except Cervical with MCC and without MCC, respectively), instead
of the spinal fusion with spinal curvature MS-DRGs 456, 457, and 458.
We analyzed claims data from the September 2018 update of the FY
2018 MedPAR file for MS-DRGs 459 and 460 to determine the number of
cases reporting an ICD-10-CM diagnosis code describing secondary
scoliosis or secondary kyphosis as the principal diagnosis. Our
findings are shown in the following table.
MS-DRGs for Cases Involving Non-Cervical Spinal Fusion With a Principal Diagnosis of Secondary Scoliosis or
Secondary Kyphosis
----------------------------------------------------------------------------------------------------------------
Number of Average
MS-DRG cases length of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 459--All cases........................................... 3,903 8.6 $46,416
MS-DRG 459--Cases with a principal diagnosis of secondary 4 7.3 56,024
scoliosis......................................................
MS-DRG 459--Cases with a principal diagnosis of secondary 4 5.8 41,883
kyphosis.......................................................
MS-DRG 460--All cases........................................... 52,597 3.3 28,754
MS-DRG 460--Cases with a principal diagnosis of secondary 34 3.6 34,424
scoliosis......................................................
MS-DRG 460--Cases with a principal diagnosis of secondary 31 4.6 42,315
kyphosis.......................................................
----------------------------------------------------------------------------------------------------------------
As shown in the table, we found a total of 3,903 cases in MS-DRG
459, with an average length of stay of 8.6 days and average costs of
$46,416. Of these 3,903 cases, we found 4 cases that reported a
principal diagnosis of secondary scoliosis, with an average length of
stay of 7.3 days and average costs of $56,024. We also found 4 cases
that reported a principal diagnosis of secondary kyphosis, with an
average length of stay of 5.8 days and average costs of $41,883. For
MS-DRG 460, we found a total of 52,597 cases with an average length of
stay of 3.3 days and average costs of $28,754. Of these 52,597 cases,
we found 34 cases that reported a principal diagnosis of secondary
scoliosis, with an average length of stay of 3.6 days and average costs
of $34,424. We found 31 cases that reported a principal diagnosis of
secondary kyphosis in MS-DRG 460, with an average length of stay of 4.6
days and average costs of $42,315.
We also analyzed claims data for MS-DRGs 456, 457, and 458 to
determine the number of cases reporting an ICD-10-CM diagnosis code
describing secondary scoliosis or secondary kyphosis as a secondary
diagnosis. Our findings are shown in the following table.
MS-DRGs for Cases Involving Non-Cervical Spinal Fusion With Spinal Curvature or Malignancy or Infection or
Extensive Fusions With Secondary Diagnosis of Secondary Scoliosis or Secondary Kyphosis
----------------------------------------------------------------------------------------------------------------
Number of Average
MS-DRG cases length of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 456--All cases........................................... 1,344 12 $66,012
MS-DRG 456--Cases with a secondary diagnosis of secondary 37 7.7 58,009
scoliosis......................................................
MS-DRG 456--Cases with a secondary diagnosis of secondary 52 12 78,865
kyphosis.......................................................
MS-DRG 457--All cases........................................... 3,654 6.2 47,577
MS-DRG 457--Cases with a secondary diagnosis of secondary 187 4.9 37,655
scoliosis......................................................
MS-DRG 457--Cases with a secondary diagnosis of secondary 114 5.2 37,357
kyphosis.......................................................
MS-DRG 458--All cases........................................... 1,245 3.4 34,179
MS-DRG 458--Cases with a secondary diagnosis of secondary 190 3.0 29,052
scoliosis......................................................
MS-DRG 458--Cases with a secondary diagnosis of secondary 39 3.7 31,015
kyphosis.......................................................
----------------------------------------------------------------------------------------------------------------
The data indicate that there were 1,344 cases in MS-DRG 456, with
an average length of stay of 12 days and average costs of $66,012. Of
these 1,344 cases, there were 37 cases that reported a secondary
diagnosis of secondary scoliosis, with an average length of stay of 7.7
days and average costs of $58,009. There were also 52 cases in MS-DRG
456 reporting a secondary diagnosis of secondary kyphosis, with an
average length of stay of 12 days and average costs of $78,865. In MS-
DRG 457, there was a total of 3,654 cases, with an average length of
stay of 6.2 days and average costs of $47,577. Of these 3,654 cases,
there were 187 cases that reported secondary scoliosis as a secondary
diagnosis, with an average length of stay of 4.9 days and average costs
of $37,655. In MS-DRG 457, there were also 114 cases that reported a
secondary diagnosis of secondary kyphosis, with an average length of
stay of 5.2 days and average costs of $37,357. Finally, there was a
total of 1,245 cases in MS-DRG 458, with an average length of stay of
3.4 days and average costs of $34,179. Of these 1,245 cases, there were
190 cases that reported a secondary diagnosis of secondary scoliosis,
with an average length of stay of 3 days and average costs of $29,052.
There were 39 cases in MS-DRG 458 that reported a secondary diagnosis
of secondary kyphosis, with an average length of stay of 3.7 days and
average costs of $31,015.
Our clinical advisors agree that the average length of stay and
average costs for the small number of cases reporting secondary
scoliosis or secondary kyphosis as a principal diagnosis with a non-
cervical spinal fusion currently grouping to MS-DRGs 459 and 460 are
generally more aligned with the average length of stay and average
costs for the cases reporting secondary scoliosis or secondary kyphosis
as a secondary diagnosis with a non-cervical spinal fusion currently
grouping to MS-DRGs 456, 457, and 458. They also note that there may be
instances in which the underlying cause of the diagnosis of secondary
scoliosis or secondary kyphosis is not treated or responsible for the
admission.
Therefore, for the reasons described above, we are proposing to add
the following ICD-10-CM diagnosis codes describing secondary scoliosis
and
[[Page 19204]]
secondary kyphosis to the list of principal diagnosis codes for MS-DRGs
456, 457, and 458: M40.10; M40.14; M40.15; M41.50; M41.54; M41.55;
M41.56; and M41.57. During our review of MS-DRGs 456, 457, and 458, we
found the following diagnosis codes that describe conditions involving
the cervical region.
------------------------------------------------------------------------
ICD-10-CM code Code description
------------------------------------------------------------------------
M40.03.................... Postural kyphosis, cervicothoracic region.
M40.202................... Unspecified kyphosis, cervical region.
M40.203................... Unspecified kyphosis, cervicothoracic
region.
M40.292................... Other kyphosis, cervical region.
M40.293................... Other kyphosis, cervicothoracic region.
M41.02.................... Infantile idiopathic scoliosis, cervical
region.
M41.03.................... Infantile idiopathic scoliosis,
cervicothoracic region.
M41.112................... Juvenile idiopathic scoliosis, cervical
region.
M41.113................... Juvenile idiopathic scoliosis,
cervicothoracic region.
M41.122................... Adolescent idiopathic scoliosis, cervical
region.
M41.123................... Adolescent idiopathic scoliosis,
cervicothoracic region.
M41.22.................... Other idiopathic scoliosis, cervical region.
M41.23.................... Other idiopathic scoliosis, cervicothoracic
region.
M41.82.................... Other forms of scoliosis, cervical region.
M41.83.................... Other forms of scoliosis, cervicothoracic
region.
M42.01.................... Juvenile osteochondrosis of spine, occipito-
atlanto-axial region.
M42.02.................... Juvenile osteochondrosis of spine, cervical
region.
M42.03.................... Juvenile osteochondrosis of spine,
cervicothoracic region.
M43.8X1................... Other specified deforming dorsopathies,
occipito-atlanto-axial region.
M43.8X2................... Other specified deforming dorsopathies,
cervical region.
M43.8X3................... Other specified deforming dorsopathies,
cervicothoracic region.
M46.21.................... Osteomyelitis of vertebra, occipito-atlanto-
axial region.
M46.22.................... Osteomyelitis of vertebra, cervical region.
M46.23.................... Osteomyelitis of vertebra, cervicothoracic
region.
M48.51XA.................. Collapsed vertebra, not elsewhere
classified, occipito-atlanto-axial region,
initial encounter for fracture.
M48.52XA.................. Collapsed vertebra, not elsewhere
classified, cervical region, initial
encounter for fracture.
M48.53XA.................. Collapsed vertebra, not elsewhere
classified, cervicothoracic region, initial
encounter for fracture.
M40.12.................... Other secondary kyphosis, cervical region.
M40.13.................... Other secondary kyphosis, cervicothoracic
region.
M41.41.................... Neuromuscular scoliosis, occipito-atlanto-
axial region.
M4.142.................... Neuromuscular scoliosis, cervical region.
M4143..................... Neuromuscular scoliosis, cervicothoracic
region.
M41.52.................... Other secondary scoliosis, cervical region.
M41.53.................... Other secondary scoliosis, cervicothoracic
region.
------------------------------------------------------------------------
Our clinical advisors noted that because the diagnosis codes shown
in the table above describe conditions involving the cervical region,
they are not clinically appropriate for assignment to MS-DRGs 456, 457,
and 458, which are defined by non-cervical spinal fusion procedures
(with spinal curvature or malignancy or infection or extensive
fusions). Therefore, our clinical advisors recommended that these codes
be removed from the MS-DRG logic for these MS-DRGs. As such, we are
proposing to remove the diagnosis codes that describe conditions
involving the cervical region as shown in the table above from MS-DRGs
456, 457, and 458.
7. MDC 11 (Diseases and Disorders of the Kidney and Urinary Tract):
Extracorporeal Shock Wave Lithotripsy (ESWL)
We received two separate, but related requests to add ICD-10-CM
diagnosis code N13.6 (Pyonephrosis) and ICD-10-CM diagnosis code
T83.192A (Other mechanical complication of indwelling ureteral stent,
initial encounter) to the list of principal diagnosis codes for MS-DRGs
691 and 692 (Urinary Stones with ESW Lithotripsy with CC/MCC and
without CC/MCC, respectively) in MDC 11 so that cases are assigned more
appropriately when an Extracorporeal Shock Wave Lithotripsy (ESWL)
procedure is performed.
ICD-10-CM diagnosis code N13.6 currently groups to MS-DRGs 689 and
690 (Kidney and Urinary Tract Infections with MCC and without MCC,
respectively) and ICD-10-CM diagnosis code T83.192A currently groups to
MS-DRGs 698, 699, and 700 (Other Kidney and Urinary Tract Diagnoses
with MCC, with CC, and without CC/MCC, respectively).
The ICD-10-PCS procedure codes for identifying procedures involving
ESWL are designated as non-O.R. procedures and are shown in the
following table.
------------------------------------------------------------------------
ICD-10-PCS code Code description
------------------------------------------------------------------------
0TF3XZZ................... Fragmentation in right kidney pelvis,
external approach.
0TF4XZZ................... Fragmentation in left kidney pelvis,
external approach.
OTF6XZZ................... Fragmentation in right ureter, external
approach.
OTF7XZZ................... Fragmentation in left ureter, external
approach.
OTFBXZZ................... Fragmentation in bladder, external approach.
OTFCXZZ................... Fragmentation in bladder neck, external
approach.
OTFDXZZ................... Fragmentation in urethra, external approach.
------------------------------------------------------------------------
[[Page 19205]]
Pyonephrosis can be described as an infection of the kidney with
pus in the upper collecting system which can progress to obstruction.
Patients with an obstruction in the upper urinary tract due to urinary
stones (calculi), tumors, fungus balls or ureteropelvic obstruction
(UPJ) may also have a higher risk of developing pyonephrosis. If
pyonephrosis is not recognized and treated promptly, it can result in
serious complications, including fistulas, septic shock, irreversible
damage to the kidneys, and death.
As noted above, the requestor recommended that ICD-10-CM diagnosis
codes N13.6 and T83.192A be added to the list of principal diagnosis
codes for MS-DRGs 691 and 692. There are currently four MS-DRGs that
group cases for diagnoses involving urinary stones, which are
subdivided to identify cases with and without an ESWL procedure: MS-
DRGs 691 and 692 (Urinary Stones with ESW Lithotripsy with and without
CC/MCC, respectively) and MS-DRGs 693 and 694 (Urinary Stones without
ESW Lithotripsy with and without MCC, respectively).
The requestor stated that when patients who have been diagnosed
with hydronephrosis secondary to renal and ureteral calculus
obstruction undergo an ESWL procedure, ICD-10-CM diagnosis code N13.2
(Hydronephrosis with renal and ureteral calculous obstruction) is
reported and groups to MS-DRGs 691 and 692. However, if a patient with
a diagnosis of hydronephrosis has a urinary tract infection (UTI) in
addition to a renal calculus obstruction and undergoes an ESWL
procedure, ICD-10-CM diagnosis code N13.6 must be coded and reported as
the principal diagnosis, which groups to MS-DRGs 689 and 690. The
requestor stated that ICD-10-CM diagnosis code N13.6 should be grouped
to MS-DRGs 691 and 692 when reported as a principal diagnosis because
this grouping will more appropriately reflect resource consumption for
patients who undergo an ESWL procedure for obstructive urinary calculi,
while also receiving treatment for urinary tract infections.
With regard to ICD-10-CM diagnosis code T83.192A, the requestor
believed that when an ESWL procedure is performed for the treatment of
calcifications within and around an indwelling ureteral stent, it is
comparable to an ESWL procedure performed for the treatment of urinary
calculi. Therefore, the requestor recommended adding ICD-10-CM
diagnosis code T83.192A to MS-DRGs 691 and 692 when reported as a
principal diagnosis and an ESWL procedure is also reported on the
claim.
To analyze these separate, but related requests, we first reviewed
the reporting of ICD-10-CM diagnosis code N13.6 within the ICD-10-CM
classification. ICD-10-CM diagnosis code N13.6 is to be assigned for
conditions identified in the code range N13.0-N13.5 with infection.
(Codes in this range describe hydronephrosis with obstruction.)
Infection may be documented by the patient's provider as urinary tract
infection (UTI) or as specific as acute pyelonephritis. We agree with
the requestor that if a patient with a diagnosis of hydronephrosis has
a urinary tract infection (UTI) in addition to a renal calculus
obstruction and undergoes an ESWL procedure, ICD-10-CM diagnosis code
N13.6 must be coded and reported as the principal diagnosis, which
groups to MS-DRGs 689 and 690. In this case scenario, the ESWL
procedure is designated as a non-O.R. procedure and does not impact the
MS-DRG assignment when reported with ICD-10-CM diagnosis code N13.6.
The ICD-10-CM classification instructs that when both a urinary
obstruction and a genitourinary infection co-exist, the correct code
assignment for reporting is ICD-10-CM diagnosis code N13.6, which is
appropriately grouped to MS-DRGs 689 and 690 (Kidney and Urinary Tract
Infections with MCC and without MCC, respectively) because it describes
a type of urinary tract infection. Therefore, in response to the
requestor's suggestion that ICD-10-CM diagnosis code N13.6 be grouped
to MS-DRGs 691 and 692 when reported as a principal diagnosis to more
appropriately reflect resource consumption for patients who undergo an
ESWL procedure for obstructive urinary calculi while also receiving
treatment for urinary tract infections, we note that the ICD-10-CM
classification provides instruction to identify the conditions reported
with ICD-10-CM diagnosis code N13.6 as an infection, and not as urinary
stones. Our clinical advisors agree with this classification and the
corresponding MS-DRG assignment for diagnosis code N13.6. In addition,
our clinical advisors noted that an ESWL procedure is a non-O.R.
procedure and they do not believe that this procedure is a valid
indicator of resource consumption for cases that involve an infection
and obstruction. Our clinical advisors believe that the resources used
for a case that involves an infection and an obstruction are clinically
distinct from the cases that involve an obstruction only in the course
of treatment. Therefore, our clinical advisors do not agree with the
request to add ICD-10-CM diagnosis code N13.6 to the list of principal
diagnoses for MS-DRGs 691 and 692.
We also performed various analyses of claims data to evaluate this
request. We analyzed claims data from the September 2018 update of the
FY 2018 MedPAR file for MS-DRGs 689 and 690 to identify cases reporting
ICD-10-CM diagnosis code N13.6 as the principal diagnosis with and
without an ESWL procedure. Our findings are reflected in the table
below.
Kidney and Urinary Tract Infections With Principal Diagnosis of Pyonephrosis With and Without ESWL
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 689--All cases........................................... 68,020 4.8 $7,873
MS-DRG 689--Cases with principal diagnosis of pyonephrosis...... 1,024 6.1 13,809
MS-DRG 689--Cases with principal diagnosis of pyonephrosis with 6 14.2 45,489
ESWL...........................................................
MS-DRG 690--All cases........................................... 131,999 3.5 5,692
MS-DRG 690--Cases with principal diagnosis of pyonephrosis...... 4,625 3.6 5,483
MS-DRG 690--Cases with principal diagnosis of pyonephrosis with 24 4.8 14,837
ESWL...........................................................
----------------------------------------------------------------------------------------------------------------
For MS-DRG 689, we found a total of 68,020 cases with an average
length of stay of 4.8 days and average costs of $7,873. Of those 68,020
cases, we found 1,024 cases reporting pyonephrosis (ICD-10-CM diagnosis
code N13.6) as a principal diagnosis with an average length of stay of
6.1 days and average costs of $13,809. Of those 1,024 cases reporting
pyonephrosis (ICD-10-CM diagnosis code N13.6) as a principal diagnosis,
there were 6 cases that also reported an ESWL procedure with an average
length of stay of 14.2 days and average costs of $45,489. For MS-DRG
[[Page 19206]]
690, we found a total of 131,999 cases with an average length of stay
of 3.5 days and average costs of $5,692. Of those 131,999 cases, we
found 4,625 cases reporting pyonephrosis (ICD-10-CM diagnosis code
N13.6) as a principal diagnosis with an average length of stay of 3.6
days and average costs of $5,483. Of those 4,625 cases reporting
pyonephrosis (ICD-10-CM diagnosis code N13.6) as a principal diagnosis,
there were 24 cases that also reported an ESWL procedure with an
average length of stay of 4.8 days and average costs of $14,837.
The data indicate that the 1,024 cases reporting pyonephrosis (ICD-
10-CM diagnosis code N13.6) as a principal diagnosis in MS-DRG 689 have
a longer average length of stay (6.1 days versus 4.8 days) and higher
average costs ($13,809 versus $7,873) compared to all the cases in MS-
DRG 689. The data also indicate that the 6 cases reporting pyonephrosis
(ICD-10-CM diagnosis code N13.6) as a principal diagnosis that also
reported an ESWL procedure have a longer average length of stay (14.2
days versus 4.8 days) and higher average costs ($45,489 versus $7,873)
in comparison to all the cases in MS-DRG 689. We found similar results
for cases reporting pyonephrosis (ICD-10-CM diagnosis code N13.6) as a
principal diagnosis with an ESWL procedure in MS-DRG 690, where the
average length of stay was slightly longer (4.8 days versus 3.5 days)
and the average costs were higher ($14,837 versus $5,692).
We then conducted further analysis for the six cases in MS-DRG 689
that reported a principal diagnosis of pyonephrosis with ESWL to
determine what factors may be contributing to the longer lengths of
stay and higher average costs. Specifically, we analyzed the MCC
conditions that were reported across the six cases. Our findings are
shown in the table below.
Secondary Diagnosis MCC Conditions Reported in MS-DRG 689 With Principal Diagnosis of Pyonephrosis with ESWL
----------------------------------------------------------------------------------------------------------------
Number of Average
ICD-10-CM code Description times reported length of stay Average costs
----------------------------------------------------------------------------------------------------------------
A41.9........................... Sepsis, unspecified organism.. 2 26.5 96,525
G82.50.......................... Quadriplegia, unspecified..... 1 7 13,782
I50.23.......................... Acute on chronic systolic 1 7 13,304
(congestive) heart failure.
J96. 01......................... Acute respiratory failure with 1 7 13,304
hypoxia.
K66.1........................... Hemoperitoneum................ 1 10 26,314
L89.153......................... Pressure ulcer of sacral 1 8 26,487
region, stage 3.
R57.1........................... Hypovolemic shock............. 1 10 26,314
-----------------------------------------------
Total....................... .............................. 8 12.8 39,069
----------------------------------------------------------------------------------------------------------------
We found seven secondary diagnosis MCC conditions reported among
the six cases in MS-DRG 689 that had a principal diagnosis of
pyonephrosis with ESWL. These MCC conditions appear to have contributed
to the longer lengths of stay and higher average costs for those six
cases. As shown in the table above, the overall average length of stay
for the cases reporting these conditions is 12.8 days with average
costs of $39,069, which is consistent with the average length of stay
of 14.2 days and average costs of $45,489 for the cases in MS-DRG 689
that had a principal diagnosis of pyonephrosis with ESWL.
We then analyzed the 24 cases in MS-DRG 690 that reported a
principal diagnosis of pyonephrosis with ESWL to determine what factors
may be contributing to the longer lengths of stay and higher average
costs. Specifically, we analyzed the CC conditions that were reported
across the 24 cases. Our findings are shown in the table below.
Secondary Diagnosis CC Conditions Reported in MS-DRG 690 With Principal Diagnosis of Pyonephrosis With ESWL
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number of Average
ICD-10-CM code Description times reported length of stay Average costs
--------------------------------------------------------------------------------------------------------------------------------------------------------
B37.0........................................ Candidal stomatitis...................................... 2 9.5 $18,895
B37.49....................................... Other urogenital candidiasis............................. 2 7.5 30,458
C79.89....................................... Secondary malignant neoplasm of other specified sites.... 1 3 5,882
E22.2........................................ Syndrome of inappropriate secretion of antidiuretic 1 2 5,979
hormone.
E44.0........................................ Moderate protein-calorie malnutrition.................... 1 6 9,027
E46.......................................... Unspecified protein-calorie malnutrition................. 2 5.5 8,704
E87.0........................................ Hyperosmolality and hypernatremia........................ 1 6 9,027
E87.1........................................ Hypo-osmolality and hyponatremia......................... 1 5 12,339
F11.20....................................... Opioid dependence, uncomplicated......................... 1 1 8,209
F33.1........................................ Major depressive disorder, recurrent, moderate........... 1 12 55,034
G81.94....................................... Hemiplegia, unspecified affecting left nondominant side.. 3 9.3 25,390
G82.20....................................... Paraplegia, unspecified.................................. 1 10 15,142
G93.40....................................... Encephalopathy, unspecified.............................. 2 7 10,277
I13.0........................................ Hypertensive heart and chronic kidney disease with heart 1 4 12,348
failure and stage 1 through stage 4 chronic kidney
disease, or unspecified chronic kidney dis.
I48.1........................................ Persistent atrial fibrillation........................... 1 12 55,034
I50.22....................................... Chronic systolic (congestive) heart failure.............. 1 12 55,034
I50.32....................................... Chronic diastolic (congestive) heart failure............. 2 3.5 9,115
I69.351...................................... Hemiplegia and hemiparesis following cerebral infarction 1 3 4,845
affecting right dominant side.
[[Page 19207]]
I69.859...................................... Hemiplegia and hemiparesis following other 1 4 18,160
cerebrovascular disease affecting unspecified side.
I97.791...................................... Other intraoperative cardiac functional disturbances 1 8 8,114
during other surgery.
J44.0........................................ Chronic obstructive pulmonary disease with acute lower 1 11 25,641
respiratory infection.
J44.1........................................ Chronic obstructive pulmonary disease with (acute) 2 5 11,283
exacerbation.
J96.10....................................... Chronic respiratory failure, unspecified whether with 1 12 55,034
hypoxia or hypercapnia.
J96.11....................................... Chronic respiratory failure with hypoxia................. 2 7 15,243
K57.92....................................... Diverticulitis of intestine, part unspecified, without 1 8 12,150
perforation or abscess without bleeding.
N12.......................................... Tubulo-interstitial nephritis, not specified as acute or 1 11 25,641
chronic.
N13.8........................................ Other obstructive and reflux uropathy.................... 1 5 32,854
N17.9........................................ Acute kidney failure, unspecified........................ 1 2 21,329
N20.1........................................ Calculus of ureter....................................... 1 10 15,142
N20.2........................................ Calculus of kidney with calculus of ureter............... 1 6 9,027
R44.3........................................ Hallucinations, unspecified.............................. 1 2 21,329
R47.01....................................... Aphasia.................................................. 1 4 10,161
R78.81....................................... Bacteremia............................................... 1 11 4,849
S37.012A..................................... Minor contusion of left kidney, initial encounter........ 1 2 21,329
T83.511A..................................... Infection and inflammatory reaction due to indwelling 1 10 15,142
urethral catheter, initial encounter.
Z68.1........................................ Body mass index (BMI) 19.9 or less, adult................ 2 4.5 10,040
Z68.43....................................... Body mass index (BMI) 50-59.9, adult..................... 1 3 6,145
-----------------------------------------------
Total.................................... ......................................................... 47 6.6 18,173
--------------------------------------------------------------------------------------------------------------------------------------------------------
We found 37 secondary diagnosis CC conditions reported among the 24
cases in MS-DRG 690 that had a principal diagnosis of pyonephrosis with
ESWL. These CC conditions appear to have contributed to the longer
length of stay and higher average costs for those 24 cases. As shown in
the table above, the overall average length of stay for the cases
reporting these conditions is 6.6 days with average costs of $18,173,
which is higher, although comparable, to the average length of stay of
4.8 days and average costs of $14,837 for the cases in MS-DRG 690 that
had a principal diagnosis of pyonephrosis with ESWL. We note that it
appears that 1 of the 24 cases had at least 4 secondary diagnosis CC
conditions (F33.1, I48.1, I50.22, and J96.10) with an average length of
stay of 12 days and average costs of $55,034, which we believe
contributed greatly overall to the longer length of stay and higher
average costs for those secondary diagnosis CC conditions reported
among the 24 cases.
Our clinical advisors agree that the resource consumption for the 6
cases in MS-DRG 689 and the 24 cases in MS-DRG 690 that reported a
principal diagnosis of pyonephrosis with ESWL cannot be directly
attributed to ESWL and believe that it is the secondary diagnosis MCC
and CC conditions that are the major contributing factors to the longer
average length of stay and higher average costs for these cases.
We also analyzed claims data for MS-DRGs 691 and 692 (Urinary
Stones with ESW Lithotripsy with CC/MCC and without CC/MCC,
respectively) and MS-DRGs 693 and 694 (Urinary Stones without ESW
Lithotripsy with MCC and without MCC, respectively) to identify claims
reporting pyonephrosis (ICD-10-CM diagnosis code N13.6) as a secondary
diagnosis. Our findings are shown in the following table.
MS-DRGs for Urinary Stones With Secondary Diagnosis of Pyonephrosis With and Without ESWL
----------------------------------------------------------------------------------------------------------------
Number of Average
MS-DRG times reported length of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 691--All cases........................................... 140 3.9 $11,997
MS-DRG 691--Cases with secondary diagnosis of pyonephrosis and 3 8 24,280
ESWL...........................................................
MS-DRG 692--All cases........................................... 124 2.1 8,326
MS-DRG 693--All cases........................................... 1,315 5.1 9,668
MS-DRG 693--Cases with secondary diagnosis of pyonephrosis...... 16 5.5 9,962
MS-DRG 694--All cases........................................... 7,240 2.7 5,263
MS-DRG 694--Cases with secondary diagnosis of pyonephrosis...... 89 3.5 6,678
----------------------------------------------------------------------------------------------------------------
As shown in the table above, in MS-DRG 691, there was a total of
140 cases with an average length of stay of 3.9 days and average costs
of $11,997. Of those 140 cases, there were 3 cases that reported
pyonephrosis as a secondary diagnosis and an ESWL procedure with an
average length of stay of 8.0 days and average costs of $24,280. There
was a total of 124 cases found in MS-DRG 692 with an average length of
stay of 2.1 days and average costs of $8,326. There were no cases in
MS-DRG 692 that reported pyonephrosis as a secondary diagnosis with an
ESWL procedure. For MS-DRG 693, there was a total of 1,315 cases with
an average length of stay of 5.1 days and average costs of $9,668. Of
[[Page 19208]]
those 1,315 cases, there were 16 cases reporting pyonephrosis as a
secondary diagnosis with an average length of stay of 5.5 days and
average costs of $9,962. For MS-DRG 694, there was a total of 7,240
cases with an average length of stay of 2.7 days and average costs of
$5,263. Of those 7,240 cases, there were 89 cases reporting
pyonephrosis as a secondary diagnosis with an average length of stay of
3.5 days and average costs of $6,678.
Similar to the process described above, we then conducted further
analysis for the three cases in MS-DRG 691 that reported a secondary
diagnosis of pyonephrosis with ESWL to determine what factors may be
contributing to the longer lengths of stay and higher average costs.
Specifically, we analyzed what other MCC and CC conditions were
reported across the three cases. We found no other MCC conditions
reported for those three cases. Our findings for the CC conditions
reported for those three cases are shown in the table below.
Secondary Diagnosis CC Conditions Reported in MS-DRG 691
----------------------------------------------------------------------------------------------------------------
Number of Average length
ICD-10-CM code Description times reported of stay Average costs
----------------------------------------------------------------------------------------------------------------
E44.0........................... Moderate protein-calorie 1 15 $52,384
malnutrition.
J96.10.......................... Chronic respiratory failure, 1 7 15,110
unspecified whether with
hypoxia or hypercapnia.
N13.6........................... Pyonephrosis.................. 2 8.5 28,865
N17.9........................... Acute kidney failure, 1 2 5,346
unspecified.
N39.0........................... Urinary tract infection, site 1 2 5,346
not specified.
Q79.6........................... Ehlers-Danlos syndrome........ 1 2 5,346
-----------------------------------------------
Total....................... .............................. 7 6.4 20,181
----------------------------------------------------------------------------------------------------------------
We found six secondary diagnosis CC conditions reported among the
three cases in MS-DRG 691 that had a secondary diagnosis of
pyonephrosis with ESWL. These CC conditions appear to have contributed
to the longer lengths of stay and higher average costs for those three
cases. As shown in the table above, the overall average length of stay
for the cases reporting these conditions is 6.4 days with average costs
of $20,181, which is more consistent with the average length of stay of
8.0 days and average costs of $24,280 for the cases in MS-DRG 691 that
had a secondary diagnosis of pyonephrosis with ESWL.
Our clinical advisors believe that the resource consumption for
those three cases cannot be directly attributed to ESWL and that it is
the secondary diagnosis CC conditions reported in addition to
pyonephrosis, which is also designated as a CC condition, that are the
major contributing factors for the longer average lengths of stay and
higher average costs for these cases in MS-DRG 691.
We did not conduct further analysis for the 16 cases in MS-DRG 693
or the 89 cases in MS-DRG 694 that reported a secondary diagnosis of
pyonephrosis because MS-DRGs 693 and 694 do not include ESWL procedures
and the average length of stay and average costs for those cases were
consistent with the data findings for all of the cases in their
assigned MS-DRG.
As discussed earlier in this section, the requestor suggested that
ICD-10-CM diagnosis code N13.6 should be grouped to MS-DRGs 691 and 692
when reported as a principal diagnosis because this grouping will more
appropriately reflect resource consumption for patients who undergo an
ESWL procedure for obstructive urinary calculi, while also receiving
treatment for urinary tract infections. However, based on the results
of the data analysis and input from our clinical advisors, we believe
that cases for which ICD-10-CM diagnosis code N13.6 was reported as a
principal diagnosis or as a secondary diagnosis with an ESWL procedure
should not be utilized as an indicator for increased utilization of
resources based on the performance of an ESWL procedure. Rather, we
believe that the resource consumption is more likely the result of
secondary diagnosis CC and/or MCC diagnosis codes.
With respect to the requestor's concern that cases reporting ICD-
10-CM diagnosis code T83.192A (Other mechanical complication of
indwelling ureteral stent, initial encounter) and an ESWL procedure are
not appropriately assigned and should be added to the list of principal
diagnoses for MS-DRGs 691 and 692 (Urinary Stones with ESW Lithotripsy
with CC/MCC and without CC/MCC, respectively), our clinical advisors
note that ICD-10-CM diagnosis code T83.192A is not necessarily
indicative of a patient having urinary stones. As such, they do not
support adding ICD-10-CM diagnosis code T83.192A to the list of
principal diagnosis codes for MS-DRGs 691 and 692.
We analyzed claims data to identify cases reporting ICD-10-CM
diagnosis code T83.192A as a principal diagnosis with ESWL in MS-DRGs
698, 699, and 700 (Other Kidney and Urinary Tract Diagnoses with MCC,
with CC, and without CC/MCC, respectively). Our findings are shown in
the following table.
MS-DRGs for Other Kidney and Urinary Tract Diagnoses With Principal Diagnosis of Other Mechanical Complications
of Indwelling Ureteral Stent With ESWL
----------------------------------------------------------------------------------------------------------------
Number of Average
MS-DRG cases length of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 698--All cases........................................... 56,803 6.1 $11,220
MS-DRG 698--Cases with diagnosis code T83.192A reported as 35 7.1 14,574
principal diagnosis............................................
MS-DRG 699--All cases........................................... 33,693 4.2 7,348
MS-DRG 699--Cases with diagnosis code T83.192A reported as 63 4.1 7,652
principal diagnosis............................................
MS-DRG 699--Cases with diagnosis code T83.192A reported as 1 3 7,986
principal diagnosis with ESWL..................................
[[Page 19209]]
MS-DRG 700--All cases........................................... 3,719 3 5,356
----------------------------------------------------------------------------------------------------------------
For MS-DRG 698, there was a total of 56,803 cases reported, with an
average length of stay of 6.1 days and average costs of $11,220. Of
these 56,803 cases, 35 cases reported ICD-10-CM diagnosis code T83.192A
as the principal diagnosis, with an average length of stay of 7.1 days
and average costs of $14,574. There were no cases that reported an ESWL
procedure with ICD-10-CM diagnosis code T83.192A as the principal
diagnosis in MS-DRG 698. For MS-DRG 699, there was a total of 33,693
cases reported, with an average length of stay of 4.2 days and average
costs of $7,348. Of the 33,693 cases in MS-DRG 699, there were 63 cases
that reported ICD-10-CM diagnosis code T83.192A as the principal
diagnosis, with an average length of stay of 4.1 days and average costs
of $7,652. There was only 1 case in MS-DRG 699 that reported ICD-10-CM
diagnosis code T83.192A as the principal diagnosis with an ESWL
procedure, with an average length of stay of 3 days and average costs
of $7,986. For MS-DRG 700, there was a total of 3,719 cases reported,
with an average length of stay of 3 days and average costs of $5,356.
There were no cases that reported ICD-10-CM diagnosis code T83.192A as
the principal diagnosis in MS-DRG 700. Of the 98 cases in MS-DRGs 698
and 699 that reported a principal diagnosis of other mechanical
complication of indwelling ureteral stent (diagnosis code T83.192A),
only 1 case also reported an ESWL procedure. Based on the results of
our data analysis and input from our clinical advisors, we are not
proposing to add ICD-10-CM diagnosis code T83.192A to the list of
principal diagnosis codes for MS-DRGs 691 and 692.
In connection with these requests, our clinical advisors
recommended that we evaluate the frequency with which ESWL is reported
in the inpatient setting across all the MS-DRGs. Therefore, we also
analyzed claims data from the September 2018 update of the FY 2018
MedPAR file to identify the other MS-DRGs to which claims reporting an
ESWL procedure were reported. Our findings are shown in the following
table.
------------------------------------------------------------------------
MS-DRGs MS-DRG description
------------------------------------------------------------------------
654....................... Major Bladder Procedures with CC.
657....................... Kidney and Ureter Procedures for Neoplasm
with CC.
659, 660, 661............. Kidney and Ureter Procedures for Non-
Neoplasm with MCC, with CC, without CC/MCC,
respectively.
662, 663.................. Minor Bladder Procedures with MCC and with
CC, respectively.
665, 666.................. Prostatectomy with MCC and with CC,
respectively.
668, 669, 670............. Transurethral Procedures with MCC, with CC,
and without CC/MCC, respectively.
671....................... Urethral Procedures with CC/MCC.
682, 683.................. Renal Failure with MCC and with CC,
respectively.
689, 690.................. Kidney and Urinary Tract Infections with MCC
and without MCC, respectively.
691, 692.................. Urinary Stones with ESW Lithotripsy with CC/
MCC and without CC/MCC, respectively.
696....................... Kidney and Urinary Tract Signs and Symptoms
without MCC.
698, 699, 700............. Other Kidney and Urinary Tract Diagnoses
with MCC, with CC, and without CC/MCC,
respectively.
982....................... Extensive O.R. Procedure Unrelated to
Principal Diagnosis with CC.
------------------------------------------------------------------------
Our findings with respect to the cases reporting an ESWL procedure
in each of these MS-DRGs, as compared to all cases in the applicable
MS-DRG, are shown in the table below.
----------------------------------------------------------------------------------------------------------------
Number of Average
MS-DRG times reported length of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 654--All cases........................................... 3,838 6.7 $19,805
MS-DRG 654--Cases reporting ESWL................................ 1 5 9,102
MS-DRG 657--All cases........................................... 7,242 4.1 14,047
MS-DRG 657--Cases reporting ESWL................................ 2 2 19,021
MS-DRG 659--All cases........................................... 7,761 8.1 18,717
MS-DRG 659--Cases reporting ESWL................................ 71 11.1 26,366
MS-DRG 660--All cases........................................... 17,617 4.1 10,292
MS-DRG 660--Cases reporting ESWL................................ 193 4 13,627
MS-DRG 661--All cases........................................... 12,434 2.3 7,997
MS-DRG 661--Cases reporting ESWL................................ 154 2.7 12,639
MS-DRG 662--All cases........................................... 614 10.2 23,110
MS-DRG 662--Cases reporting ESWL................................ 1 22 57,520
MS-DRG 663--All cases........................................... 1,349 5 11,213
MS-DRG 663--Cases reporting ESWL................................ 2 3.5 15,870
MS-DRG 665--All cases........................................... 589 9.4 21,328
MS-DRG 665--Cases reporting ESWL................................ 2 16.5 17,710
MS-DRG 666--All cases........................................... 1,517 5.6 13,060
MS-DRG 666--Cases reporting ESWL................................ 2 9.5 16,521
MS-DRG 668--All cases........................................... 2,065 9 20,229
[[Page 19210]]
MS-DRG 668--Cases reporting ESWL................................ 1 4 19,383
MS-DRG 669--All cases........................................... 5,259 4.9 11,217
MS-DRG 669--Cases reporting ESWL................................ 5 2.4 13,006
MS-DRG 670--All cases........................................... 1,707 2.6 7,177
MS-DRG 670--Cases reporting ESWL................................ 5 3 18,416
MS-DRG 671--All cases........................................... 367 6.4 13,519
MS-DRG 671--Cases reporting ESWL................................ 1 3 29,731
MS-DRG 682--All cases........................................... 97,347 5.7 10,384
MS-DRG 682--Cases reporting ESWL................................ 5 10 26,773
MS-DRG 683--All cases........................................... 132,206 3.9 6,450
MS-DRG 683--Cases reporting ESWL................................ 4 13.3 19,706
MS-DRG 689--All cases........................................... 68,020 4.8 7,873
MS-DRG 689--Cases reporting ESWL................................ 11 13.3 35,510
MS-DRG 690--All cases........................................... 131,999 3.5 5,692
MS-DRG 690--Cases reporting ESWL................................ 39 4.9 13,567
MS-DRG 691--All cases........................................... 140 3.9 11,997
MS-DRG 691--Cases reporting ESWL................................ 140 3.9 11,997
MS-DRG 692--All cases........................................... 124 2.1 8,326
MS-DRG 692--Cases reporting ESWL................................ 124 2.1 8,326
MS-DRG 696--All cases........................................... 5,933 2.9 4,938
MS-DRG 696--Cases reporting ESWL................................ 2 2.5 6,238
MS-DRG 698--All cases........................................... 56,803 6.1 11,220
MS-DRG 698--Cases reporting ESWL................................ 18 9.2 27,818
MS-DRG 699--All cases........................................... 33,693 4.2 7,348
MS-DRG 699--Cases reporting ESWL................................ 9 4.4 10,986
MS-DRG 700--All cases........................................... 3,719 3 5,356
MS-DRG 700--Cases reporting ESWL................................ 1 1 7,580
MS-DRG 982--All cases........................................... 16,834 6.3 16,939
MS-DRG 982--Cases reporting ESWL................................ 2 11 74,751
----------------------------------------------------------------------------------------------------------------
Our data analysis indicates that, generally, the subset of cases
reporting an ESWL procedure appear to have a longer average length of
stay and higher average costs when compared to all the cases in their
assigned MS-DRG. However, we note that this same subset of cases also
reported at least one O.R. procedure and/or diagnosis designated as a
CC or an MCC, which our clinical advisors believe are contributing
factors to the longer average lengths of stay and higher average costs,
with the exception of the case assigned to MS-DRG 700, which is a
medical MS-DRG and has no CC or MCC conditions in the logic. Therefore,
our clinical advisors do not believe that cases reporting an ESWL
procedure should be considered as an indication of increased resource
consumption for inpatient hospitalizations.
Our clinical advisors also suggested that we evaluate the reporting
of ESWL procedures in the inpatient setting over the past few years. We
analyzed claims data for MS-DRGs 691 and 692 from the FY 2012 through
the FY 2016 MedPAR files, which were used in our analysis of claims
data for MS-DRG reclassification requests effective for FY 2014 through
FY 2018. We note that the analysis findings shown in the following
table reflect ICD-9-CM, ICD-10-CM and ICD-10-PCS coded claims data.
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
FY 2014 (version 31) FY 2015 (version 32) FY 2016 (version 33) FY 2017 (version 34) FY 2018 (version 35)
-----------------------------------------------------------------------------------------------------------------------------------------------------
MS-DRG Average Average Average Average Average
Number length Average Number length Average Number length Average Number length Average Number length Average
of cases of stay costs of cases of stay costs of cases of stay costs of cases of stay costs of cases of stay costs
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
MS-DRG 691--Urinary Stones with ESW 898 3.77 $10,274 832 3.81 $11,141 812 3.72 $11,534 750 4.06 $11,907 448 3.4 $11,502
Lithotripsy w CC/MCC.....................
MS-DRG 692--Urinary Stones with ESW 231 2.02 7,292 197 2.14 8,041 133 2.32 9,273 103 2.39 9,398 61 2.3 8,702
Lithotripsy without CC/MCC...............
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
The data show a steady decline in the number of cases reporting
urinary stones with an ESWL procedure for the past 5 years. As
previously noted, the total number of cases reporting urinary stones
with an ESWL procedure for MS-DRGs 691 and 692 based on our analysis of
the September 2018 update of the FY 2018 MedPAR file was 264, which
again is a decline from the prior year's figures. As discussed
throughout this section, an ESWL procedure is a non-O.R. procedure
which currently groups to medical MS-DRGs 691 and 692. Therefore,
because an ESWL procedure is a non-O.R. procedure and due to decreased
usage of this procedure in the inpatient setting for the treatment of
urinary stones, our clinical advisors believe that there is no longer a
clinical reason to subdivide the MS-DRGs for urinary stones (MS-DRGs
691, 692, 693, and 694) based on ESWL procedures.
Therefore, we are proposing to delete MS-DRGs 691 and 692 and to
revise the titles for MS-DRGs 693 and 694 from ``Urinary Stones without
ESW Lithotripsy with MCC'' and ``Urinary Stones without ESW Lithotripsy
without MCC'', respectively to ``Urinary Stones with MCC'' and
``Urinary Stones without MCC'', respectively.
8. MDC 12 (Diseases and Disorders of the Male Reproductive System):
Diagnostic Imaging of Male Anatomy
We received a request to review four ICD-10-CM diagnosis codes
describing
[[Page 19211]]
body parts associated with male anatomy that are currently assigned to
MDC 5 (Diseases and Disorders of the Circulatory System) in MS-DRGs 302
and 303 (Atherosclerosis with MCC and Atherosclerosis without MCC,
respectively). The four codes are listed in the following table.
------------------------------------------------------------------------
ICD-10-CM code Code description
------------------------------------------------------------------------
R93.811................... Abnormal radiologic findings on diagnostic
imaging of right testicle.
R93.812................... Abnormal radiologic findings on diagnostic
imaging of left testicle.
R93.813................... Abnormal radiologic findings on diagnostic
imaging of testicles, bilateral.
R93.819................... Abnormal radiologic findings on diagnostic
imaging of unspecified testicle.
------------------------------------------------------------------------
The requestor recommended that the four diagnosis codes shown in
the table above be considered for assignment to MDC 12 (Diseases and
Disorders of the Male Reproductive System), consistent with other
diagnosis codes that include the male anatomy. However, the requestor
did not suggest a specific MS-DRG assignment within MDC 12.
We examined claims data from the September 2018 update of the FY
2018 MedPAR file for MS-DRGs 302 and 303 to identify any cases
reporting a diagnosis code for abnormal radiologic findings on
diagnostic imaging of the testicles. We did not find any such cases.
Our clinical advisors reviewed this request and determined that the
assignment of diagnosis codes R93.811, R93.812, R93.813, and R93.819 to
MDC 5 in MS-DRGs 302 and 303 was a result of replication from ICD-9-CM
diagnosis code 793.2 (Nonspecific (abnormal) findings on radiological
and other examination of other intrathoracic organs) which was assigned
to those MS-DRGs. Therefore, our clinical advisors support reassignment
of these codes to MDC 12. Our clinical advisors agree that this
reassignment is clinically appropriate because these diagnosis codes
are specific to the male anatomy, consistent with other diagnosis codes
in MDC 12 that include the male anatomy. Specifically, our clinical
advisors suggest reassignment of the four diagnosis codes to MS-DRGs
729 and 730 (Other Male Reproductive System Diagnoses with CC/MCC and
without CC/MCC, respectively). Therefore, we are proposing to reassign
ICD-10-CM diagnosis codes R93.811, R93.812, R93.813, and R93.819 from
MDC 5 in MS-DRGs 302 and 303 to MDC 12 in MS-DRGs 729 and 730.
9. MDC 14 (Pregnancy, Childbirth and the Puerperium): Proposed
Reassignment of Diagnosis Code O99.89
We received a request to review the MS-DRG assignment for cases
reporting ICD-10-CM diagnosis code O99.89 (Other specified diseases and
conditions complicating pregnancy, childbirth and the puerperium). The
requestor stated that it is experiencing MS-DRG shifts to MS-DRG 769
(Postpartum and Post Abortion Diagnoses with O.R. Procedure) as a
result of the new obstetric MS-DRG logic when ICD-10-CM diagnosis code
O99.89 is reported as a principal diagnosis in the absence of a
delivery code on the claim (to indicate the patient delivered during
that hospitalization), or when there is no other secondary diagnosis
code on the claim indicating that the patient is in the postpartum
period. According to the requestor, claims reporting ICD-10-CM
diagnosis code O99.89 as a principal diagnosis for conditions described
as occurring during the antepartum period that are reported with an
O.R. procedure are grouping to MS-DRG 769. In the example provided by
the requestor, ICD-10-CM diagnosis code O99.89 was reported as the
principal diagnosis, with ICD-10-CM diagnosis codes N13.2
(Hydronephrosis with renal and ureteral calculous obstruction) and
Z3A.25 (25 weeks of gestation of pregnancy) reported as secondary
diagnoses with ICD-10-PCS procedure code 0T68DZ (Dilation of right
ureter with intraluminal device, endoscopic approach), resulting in
assignment to MS-DRG 769. The requestor noted that, in the FY 2019
IPPS/LTCH PPS final rule (83 FR 41212), we stated ``If there was not a
principal diagnosis of abortion reported on the claim, the logic asks
if there was a principal diagnosis of an antepartum condition reported
on the claim. If yes, the logic then asks if there was an O.R.
procedure reported on the claim. If yes, the logic assigns the case to
one of the proposed new MS-DRGs 817, 818, or 819.'' In the requestor's
example, there were not any codes reported to indicate that the patient
was in the postpartum period, nor was there a delivery code reported on
the claim. Therefore, the requestor suggested that a more appropriate
assignment for ICD-10-CM diagnosis code O99.89 may be MS-DRGs 817, 818,
and 819 (Other Antepartum Diagnoses with O.R. Procedure with MCC, with
CC and without CC/MCC, respectively).
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41202 through
41216), we finalized our proposal to restructure the MS-DRGs within MDC
14 (Pregnancy, Childbirth and the Puerperium) which established new
concepts for the GROUPER logic. As a result of the modifications made,
ICD-10-CM diagnosis code O99.89 was classified as a postpartum
condition and is currently assigned to MS-DRG 769 (Postpartum and Post
Abortion Diagnoses with O.R. Procedure) and MS-DRG 776 (Postpartum and
Post Abortion Diagnoses without O.R. Procedure) under the Version 36
ICD-10 MS-DRGs. As also discussed and displayed in Diagram 2 in the FY
2019 IPPS/LTCH PPS final rule (83 FR 41212 through 41213), the logic
asks if there was a principal diagnosis of a postpartum condition
reported on the claim. If yes, the logic then asks if there was an O.R.
procedure reported on the claim. If yes, the logic assigns the case to
MS-DRG 769. If no, the logic assigns the case to MS-DRG 776. Therefore,
the MS-DRG assignment for the example provided by the requestor is
grouping accurately according to the current GROUPER logic.
We analyzed claims data from the September 2018 update of the FY
2018 MedPAR file for cases reporting diagnosis code O99.89 in MS-DRGs
769 and 776 as a principal diagnosis or as a secondary diagnosis. Our
findings are shown in the following table.
[[Page 19212]]
Postpartum MS-DRGs With Principal or Secondary Diagnosis of Other Specified Diseases and Conditions Complicating
Pregnancy, Childbirth and the Puerperium
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 769--All cases........................................... 91 4.3 $11,015
MS-DRG 769--Cases reporting diagnosis code O99.89 as principal 7 5.6 19,059
diagnosis......................................................
MS-DRG 769--Cases reporting diagnosis code O99.89 as secondary 61 12.1 41,717
diagnosis......................................................
MS-DRG 776--All cases........................................... 560 3.1 5,332
MS-DRG 776--Cases reporting diagnosis code O99.89 as principal 57 3.5 6,439
diagnosis......................................................
----------------------------------------------------------------------------------------------------------------
As shown in the table above, we found a total of 91 cases in MS-DRG
769 with an average length of stay of 4.3 days and average costs of
$11,015. Of these 91 cases, 7 cases reported ICD-10-CM diagnosis code
O99.89 as a principal diagnosis with an average length of stay of 5.6
days and average costs of $19,059, and 61 cases reported ICD-10-CM
diagnosis code O99.89 as a secondary diagnosis with an average length
of stay of 12.1 days and average costs of $41,717. For MS-DRG 776, we
found a total of 560 cases with an average length of stay of 3.1 days
and average costs of $5,332. Of these 560 cases, 57 cases reported ICD-
10-CM diagnosis code O99.89 as a principal diagnosis with an average
length of stay of 3.5 days and average costs of $6,439. There were no
cases reporting ICD-10-CM diagnosis code O99.89 as a secondary
diagnosis in MS-DRG 776.
For MS-DRG 769, the data show that the 68 cases reporting ICD-10-CM
diagnosis code O99.89 as a principal or secondary diagnosis have a
longer average length of stay and higher average costs compared to all
the cases in MS-DRG 769. For MS-DRG 776, the data show that the 57
cases reporting a principal diagnosis of ICD-10-CM diagnosis code
O99.89 have a similar average length of stay compared to all the cases
in MS-DRG 776 (3.5 days versus 3.1 days) and average costs that are
consistent with the average costs of all cases in MS-DRG 776 ($6,439
versus $5,332).
We note that the description for ICD-10-CM diagnosis code O99.89
``Other specified diseases and conditions complicating pregnancy,
childbirth and the puerperium'', describes conditions that may occur
during the antepartum period (pregnancy), during childbirth, or during
the postpartum period (puerperium). In addition, in the ICD-10-CM
Tabular List of Diseases, there is an inclusion term at subcategory
O99.8- instructing users that the reporting of any diagnosis codes in
that subcategory is intended for conditions that are reported in
certain ranges of the classification. Specifically, the inclusion term
states ``Conditions in D00-D48, H00-H95, M00-N99, and Q00-Q99.'' There
is also an instructional note to ``Use additional code to identify
condition.'' As a result, ICD-10-CM diagnosis code O99.89 may be
reported to identify conditions that occur during the antepartum period
(pregnancy), during childbirth, or during the postpartum period
(puerperium). However, it is not restricted to the reporting of
obstetric specific conditions only. In the example provided by the
requestor, ICD-10-CM diagnosis code O99.89 was reported as the
principal diagnosis with ICD-10-CM diagnosis code N13.2 (Hydronephrosis
with renal and ureteral calculous obstruction) as a secondary
diagnosis. ICD-10-CM diagnosis code N13.2 is within the code range
referenced earlier in this section (M00-N99) and qualifies as an
appropriate condition for reporting according to the instruction.
As noted earlier, ICD-10-CM diagnosis code O99.89 is intended to
report conditions that occur during the antepartum period (pregnancy),
during childbirth, or during the postpartum period (puerperium) and is
not restricted to the reporting of obstetric specific conditions only.
However, because the diagnosis code description includes three distinct
obstetric related stages, it is not clear what stage the patient is in
by this single code. For example, upon review of subcategory O99.8-, we
recognized that the other ICD-10-CM diagnosis code sub-subcategories
are expanded to include unique codes that identify the condition as
occurring or complicating pregnancy, childbirth or the puerperium.
Specifically, sub-subcategory O99.81- (Abnormal glucose complicating
pregnancy, childbirth, and the puerperium) is expanded to include the
following ICD-10-CM diagnosis codes.
------------------------------------------------------------------------
ICD-10-CM code Code description
------------------------------------------------------------------------
O99.810................... Abnormal glucose complicating pregnancy.
O99.814................... Abnormal glucose complicating childbirth.
O99.815................... Abnormal glucose complicating the
puerperium.
------------------------------------------------------------------------
The codes listed above specifically identify at what stage the
abnormal glucose was a complicating condition. Because each code
uniquely identifies a stage, the code can be easily classified under
MDC 14 as an antepartum condition (ICD-10-CM diagnosis code O99.810),
occurring during a delivery episode (ICD-10-CM diagnosis code O99.814),
or as a postpartum condition (ICD-10-CM diagnosis code O99.815). The
same is not true for ICD-10-CM diagnosis code O99.89 because it
includes all three stages in the single code.
Therefore, we examined the number and type of secondary diagnoses
reported with ICD-10-CM diagnosis code O99.89 as a principal diagnosis
for MS-DRGs 769 and 776 to identify how many secondary diagnoses were
related to other obstetric conditions and how many were related to non-
obstetric conditions.
[[Page 19213]]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number of
secondary Number of Number of Number of Number of Number of
diagnoses secondary OB secondary OB secondary OB secondary OB secondary non-
MS-DRG reported with related related related related OB related
O99.89 as diagnoses antepartum postpartum delivery diagnoses
principal diagnoses diagnoses diagnoses
--------------------------------------------------------------------------------------------------------------------------------------------------------
MS-DRG 769.............................................. 59 13 11 1 1 46
MS-DRG 776.............................................. 376 113 88 19 6 263
--------------------------------------------------------------------------------------------------------------------------------------------------------
As shown in the table above, there was a total of 59 secondary
diagnoses reported with diagnosis code O99.89 as the principal
diagnosis for MS-DRG 769. Of those 59 secondary diagnoses, 13 were
obstetric (OB) related diagnosis codes (11 antepartum, 1 postpartum and
1 delivery) and 46 were non-obstetric (Non-OB) related diagnosis codes.
For MS-DRG 776, there was a total of 376 secondary diagnoses reported
with diagnosis code O99.89 as the principal diagnosis. Of those 376
secondary diagnoses, 113 were obstetric (OB) related diagnosis codes
(88 antepartum, 19 postpartum and 6 delivery) and 263 were non-
obstetric (Non-OB) related diagnosis codes.
The data reflect that, for MS-DRGs 769 and 776, the number of
secondary diagnoses identified as OB-related antepartum diagnoses is
greater than the number of secondary diagnoses identified as OB-related
postpartum diagnoses (99 antepartum diagnoses versus 20 postpartum
diagnoses). The data also indicate that, of the 435 secondary diagnoses
reported with ICD-10-CM diagnosis code O99.89 as the principal
diagnosis, 309 (71 percent) of those secondary diagnoses were non-OB-
related diagnosis codes. Because there was a greater number of
secondary diagnoses identified as OB-related antepartum diagnoses
compared to the OB-related postpartum diagnoses within the postpartum
MS-DRGs when ICD-10-CM diagnosis code O99.89 was reported as the
principal diagnosis, we performed further analysis of diagnosis code
O99.89 within the antepartum MS-DRGs.
Under the Version 35 ICD-10 MS-DRGs, diagnosis code O99.89 was
classified as an antepartum condition and was assigned to MS-DRG 781
(Other Antepartum Diagnoses with Medical Complications). Therefore, we
also analyzed claims data for MS-DRGs 817, 818 and 819 (Other
Antepartum Diagnoses with O.R. Procedure with MCC, with CC and without
CC/MCC, respectively) and MS-DRGs 831, 832, and 833 (Other Antepartum
Diagnoses without O.R. Procedure with MCC, with CC and without CC/MCC,
respectively) for cases reporting ICD-10-CM diagnosis code O99.89 as a
secondary diagnosis. We note that the analysis for the proposed FY 2020
ICD-10 MS-DRGs is based upon the September 2018 update of the FY 2018
MedPAR claims data that were grouped through the ICD-10 MS-DRG GROUPER
Version 36. Our findings are shown in the table below.
Antepartum MS-DRGs With Secondary Diagnosis of Other Specified Diseases and Conditions Complicating Pregnancy,
Childbirth and the Puerperium
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 817--All cases........................................... 63 5.7 $14,948
MS-DRG 817--Cases reporting diagnosis code O99.89 as secondary 8 10.8 24,359
diagnosis......................................................
MS-DRG 818--All cases........................................... 78 4.1 9,343
MS-DRG 818--Cases reporting diagnosis code O99.89 as secondary 7 3.4 14,182
diagnosis......................................................
MS-DRG 819--All cases........................................... 25 2.2 5,893
MS-DRG 819--Cases reporting diagnosis code O99.89 as secondary 1 1 4,990
diagnosis......................................................
MS-DRG 831--All cases........................................... 747 4.8 7,714
MS-DRG 831--Cases reporting diagnosis code O99.89 as secondary 127 5.4 7,050
diagnosis......................................................
MS-DRG 832--All cases........................................... 1,142 3.6 5,159
MS-DRG 832--Cases reporting diagnosis code O99.89 as secondary 145 4.2 5,656
diagnosis......................................................
MS-DRG 833--All cases........................................... 537 2.6 3,807
MS-DRG 833--Cases reporting diagnosis code O99.89 as secondary 47 2.6 3,307
diagnosis......................................................
----------------------------------------------------------------------------------------------------------------
As shown in the table above, we found a total of 63 cases in MS-DRG
817 with an average length of stay of 5.7 days and average costs of
$14,948. Of these 63 cases, there were 8 cases reporting ICD-10-CM
diagnosis code O99.89 as a secondary diagnosis with an average length
of stay of 10.8 days and average costs of $24,359. For MS-DRG 818, we
found a total of 78 cases with an average length of stay of 4.1 days
and average costs of $9,343. Of these 78 cases, there were 7 cases
reporting ICD-10-CM diagnosis code O99.89 as a secondary diagnosis with
an average length of stay of 3.4 days and average costs of $14,182. For
MS-DRG 819, we found a total of 25 cases with an average length of stay
of 2.2 days and average costs of $5,893. Of these 25 cases, there was 1
case reporting ICD-10-CM diagnosis code O99.89 as a secondary diagnosis
with an average length of stay of 1 day and average costs of $4,990.
For MS-DRG 831, we found a total of 747 cases with an average
length of stay of 4.8 days and average costs of $7,714. Of these 747
cases, there were 127 cases reporting ICD-10-CM diagnosis code O99.89
as a secondary diagnosis with an average length of stay of 5.4 days and
average costs of $7,050. For MS-DRG 832, we found a total of 1,142
cases with an average length of stay of 3.6 days and average costs of
$5,159. Of these 1,142 cases, there were 145 cases reporting ICD-10-CM
diagnosis code O99.89 as a secondary diagnosis with an average length
of stay of 4.2 days and average costs of $5,656. For MS-DRG 833, we
found a total of 537 cases with an average length of stay of 2.6 days
and average costs of $3,807. Of these 537 cases, there were 47 cases
reporting ICD-10-CM diagnosis code O99.89 as a secondary diagnosis with
an average length of stay of 2.6 days and average costs of $3,307.
[[Page 19214]]
Overall, there was a total of 335 cases reporting ICD-10-CM
diagnosis code O99.89 as a secondary diagnosis within the antepartum
MS-DRGs. Of those 335 cases, 16 cases involved an O.R. procedure and
319 cases did not involve an O.R. procedure. The data indicate that
ICD-10-CM diagnosis code O99.89 is reported more often as a secondary
diagnosis within the antepartum MS-DRGs (335 cases) than it is reported
as a principal or secondary diagnosis within the postpartum MS-DRGs
(125 cases).
Our clinical advisors believe that, because ICD-10-CM diagnosis
code O99.89 can be reported during the antepartum period (pregnancy),
during childbirth, or during the postpartum period (puerperium), there
is not a clear clinical indication as to which set of MS-DRGs
(antepartum, delivery, or postpartum) would be the most appropriate
assignment for this diagnosis code. They recommended that we
collaborate with the National Center for Health Statistics (NCHS) at
the Centers for Disease Control and Prevention (CDC), in consideration
of a proposal to possibly expand ICD-10-CM diagnosis code O99.89 to
become a sub-subcategory that would result in the creation of unique
codes with a sixth digit character to specify which obstetric related
stage the patient is in. For example, under subcategory O99.8-, a
proposed new sub-subcategory for ICD-10-CM diagnosis code O99.89- could
include the following proposed new diagnosis codes:
O99.890 (Other specified diseases and conditions
complicating pregnancy);
O99.894 (Other specified diseases and conditions
complicating childbirth); and
O99.85 (Other specified diseases and conditions
complicating the puerperium).
If such a proposal to create this new sub-subcategory and new
diagnosis codes were approved and finalized, it would enable improved
data collection and more appropriate MS-DRG assignment, consistent with
the current MS-DRG assignments of the existing obstetric related
diagnosis codes. For instance, a new diagnosis code described as
``complicating pregnancy'' would be clinically aligned with the
antepartum MS-DRGs, a new diagnosis code described as ``complicating
childbirth'' would be clinically aligned with the delivery MS-DRGs, and
a new diagnosis code described as ``complicating the puerperium'' would
be clinically aligned with the postpartum MS-DRGs. (We note that all
requests for new diagnosis codes require that a proposal be approved
for discussion at a future ICD-10 Coordination and Maintenance
Committee meeting.)
While our clinical advisors could not provide a strong clinical
justification for classifying ICD-10-CM diagnosis code O99.89 as an
antepartum condition versus as a postpartum condition for the reasons
described above, they did consider the claims data to be informative as
to how the diagnosis code is being reported for obstetric patients. In
analyzing both the postpartum MS-DRGs and the antepartum MS-DRGs
discussed earlier in this section, they agreed that the data clearly
show that ICD-10-CM diagnosis code O99.89 is reported more frequently
as a secondary diagnosis within the antepartum MS-DRGs than it is
reported as a principal or secondary diagnosis within the postpartum
MS-DRGs.
Based on our analysis of claims data and input from our clinical
advisors, we are proposing to reclassify ICD-10-CM diagnosis code
O99.89 from a postpartum condition to an antepartum condition under MDC
14. If finalized, ICD-10-CM diagnosis code O99.89 would follow the
logic as described in the FY 2019 IPPS/LTCH PPS final rule (83 FR
41212) which asks if there was a principal diagnosis of an antepartum
condition reported on the claim. If yes, the logic then asks if there
was an O.R. procedure reported on the claim. If yes, the logic assigns
the case to MS-DRG 817, 818, or 819. If no (there was not an O.R.
procedure reported on the claim), the logic assigns the case to MS-DRG
831, 832, or 833.
10. MDC 22 (Burns): Skin Graft to Perineum for Burn
We received a request to add seven ICD-10-PCS procedure codes that
describe a skin graft to the perineum to MS-DRG 927 (Extensive Burns Or
Full Thickness Burns with MV >96 Hours with Skin Graft) and MS-DRGs 928
and 929 (Full Thickness Burn with Skin Graft Or Inhalation Injury with
CC/MCC and without CC/MCC, respectively) in MDC 22. The seven procedure
codes are listed in the following table.
------------------------------------------------------------------------
ICD-10-PCS code Code description
------------------------------------------------------------------------
0HR9X73................... Replacement of perineum skin with autologous
tissue substitute, full thickness, external
approach.
0HR9X74................... Replacement of perineum skin with autologous
tissue substitute, partial thickness,
external approach.
0HR9XJ3................... Replacement of perineum skin with synthetic
substitute, full thickness, external
approach.
0HR9XJ4................... Replacement of perineum skin with synthetic
substitute, partial thickness, external
approach.
0HR9XJZ................... Replacement of perineum skin with synthetic
substitute, external approach.
0HR9XK3................... Replacement of perineum skin with non-
autologous tissue substitute, full
thickness, external approach.
0HR9XK4................... Replacement of perineum skin with non-
autologous tissue substitute, partial
thickness, external approach.
------------------------------------------------------------------------
These seven procedure codes are currently assigned to MS-DRGs 746
and 747 (Vagina, Cervix and Vulva Procedures with CC/MCC and without
CC/MCC, respectively). In addition, when reported in conjunction with a
principal diagnosis in MDC 21 (Injuries, Poisonings and Toxic Effects
of Drugs), these codes group to MS-DRGs 907, 908, and 909 (Other O.R.
Procedures For Injuries with MCC, with CC and without CC/MCC,
respectively), and when reported in conjunction with a principal
diagnosis in MDC 24 (Multiple Significant Trauma), these codes group to
MS-DRGs 957, 958, and 959 (Other O.R. Procedures For Multiple
Significant Trauma with MCC, with CC and without CC/MCC, respectively).
In addition, these procedures are designated as non-extensive O.R.
procedures and are assigned to MS-DRGs 987, 988 and 989 (Non-Extensive
O.R. Procedure Unrelated to Principal Diagnosis with MCC, with CC, and
without CC/MCC, respectively) when a principal diagnosis that is
unrelated to the procedure is reported on the claim.
The requestor provided an example in which it identified one case
where a patient underwent debridement and split thickness skin graft
(STSG) to the perineum area (only), and expressed concern that the case
did not route to MS-DRGs 928 and 929 to recognize operating room
resources. (We note that the requestor did not specify the diagnosis
associated with this case nor the MS-DRG to which this one case was
grouped.) The requestor stated that providers may document various
terminologies for this anatomic site,
[[Page 19215]]
including perineum, groin, and buttocks crease; therefore, when a
provider deems a burn to affect the perineum as opposed to the groin or
buttock crease, cases should route to MS-DRGs which compensate
hospitals for skin grafting operating room resources. Therefore, the
requestor recommended that the cited seven ICD-10-PCS codes be added to
the list of procedure codes for a skin graft within MS-DRGs 927, 928,
and 929.
We reviewed this request by analyzing claims data from the
September 2018 update of the FY 2018 MedPAR file for cases reporting
any of the above seven procedure codes in MS-DRGs 746, 747, 907, 908,
909, 957, 958, 959, 987, 988, and 989. Our findings are shown in the
following table.
Cases Involving Skin Graft to the Perineum
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 746--All cases........................................... 1,344 5 $11,847
MS-DRG 746--Cases with skin graft to the perineum procedure..... 1 2 10,830
MS-DRG 907--All cases........................................... 7,843 10 28,919
MS-DRG 907--Cases with skin graft to the perineum procedure..... 1 8 21,909
MS-DRG 908--All cases........................................... 9,286 5.3 14,601
MS-DRG 908--Cases with skin graft to the perineum procedure..... 1 6 8,410
MS-DRG 988--All cases........................................... 8,391 5.7 12,294
MS-DRG 988--Cases with skin graft to the perineum procedure..... 2 3 6,906
MS-DRG 989--All cases........................................... 1,551 3.1 8,171
MS-DRG 989--Cases with skin graft to the perineum procedure..... 1 7 14,080
----------------------------------------------------------------------------------------------------------------
As shown in the table above, the overall volume of cases reporting
a skin graft to the perineum procedure is low, with a total of 6 cases
found. In MS-DRG 746, we found a total of 1,344 cases with an average
length of stay of 5 days and average costs of $11,847. The single case
reporting a skin graft to the perineum procedure in MS-DRG 746 had a
length of stay of 2 days and a cost of $10,830. In MS-DRG 907, we found
a total of 7,843 cases with an average length of stay of 10 days and
average costs of $28,919. The single case reporting a skin graft to the
perineum procedure in MS-DRG 907 had a length of stay of 8 days and a
cost of $21,909. In MS-DRG 908, we found a total of 9,286 cases with an
average length of stay of 5.3 days and average costs of $14,601. The
single case reporting a skin graft to the perineum procedure in MS-DRG
908 had a length of stay of 6 days and a cost of $8,410. In MS-DRG 988,
we found a total of 8,391 cases with an average length of stay of 5.7
days and average costs of $12,294. The 2 cases reporting a skin graft
to the perineum procedure in MS-DRG 988 had an average length of stay
of 3 days and average costs of $6,906. In MS-DRG 989, we found a total
of 1,551 cases with an average length of stay of 3.1 days and average
costs of $8,171. The single case reporting a skin graft to the perineum
procedure in MS-DRG 989 had a length of stay of 7 day and a cost of
$14,080. We found no cases reporting a skin graft to the perineum
procedure in MS-DRG 747, 909, 957, 958, 959, or 987. Cases reporting a
skin graft to the perineum procedure generally had shorter length of
stays and lower average costs than those of their assigned MS-DRGs
overall.
We then analyzed claims data for MS-DRGs 927, 928, and 929 (the MS-
DRGs to which the requestor suggested that these cases group) for all
cases reporting a procedure describing a skin graft to the perineum
listed in the table above to consider how the resources involved in the
cases reporting a procedure describing a skin graft to the perineum
compared to those of all cases in MS-DRGs 927, 928, and 929. Our
findings are shown in the following table.
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 927--All cases........................................... 146 30.9 $147,903
MS-DRG 928--All cases........................................... 1,149 15.7 45,523
MS-DRG 928--Cases with skin graft to the perineum procedure..... 5 39 64,041
MS-DRG 929--All cases........................................... 296 7.9 21,474
----------------------------------------------------------------------------------------------------------------
As shown in the table above, for MS-DRG 927, we found a total of
146 cases with an average length of stay of 30.9 days and average costs
of $147,903; no cases reporting a skin graft to the perineum procedure
were found. For MS-DRG 928, we found a total of 1,149 cases with an
average length of stay of 15.7 days and average costs of $45,523. We
found 5 cases reporting a skin graft to the perineum procedure with an
average length of stay of 39 days and average costs of $64,041. For MS-
DRG 929, we found a total of 296 cases with an average length of stay
of 7.9 days and average costs of $21,474; and no cases reporting a skin
graft to the perineum procedure were found. We note that none of the 5
cases reporting a skin graft to the perineum in MS-DRGs 927, 928, and
929 reported a skin graft to the perineum procedure as the only
operating room procedure. Therefore, it is not possible to determine
how much of the operating room resources for these 5 cases were
attributable to the skin graft to the perineum procedure.
Our clinical advisors reviewed the claims data described above and
noted that none of the cases reporting the seven identified procedure
codes that grouped to MS-DRGs 746, 907, 908, 988, and 989 (listed in
the table above) had a principal or secondary diagnosis of a burn,
which suggests that these skin grafts were not performed to treat a
burn. Therefore, our clinical advisors believe that it would not be
appropriate for these cases that report a skin graft to the perineum
procedure to group to MS-DRGs 927, 928, and 929, which describe burns.
Our clinical advisors state that the seven ICD-10-PCS procedure codes
that describe a skin graft to the perineum are more clinically aligned
with the other procedures in MS-DRGs 746 and 747, to which they are
currently assigned. Therefore, we are
[[Page 19216]]
not proposing to add the seven identified procedure codes to MS-DRGs
927, 928, and 929.
11. MDC 23 (Factors Influencing Health Status and Other Contacts With
Health Services): Proposed Assignment of Diagnosis Code R93.89
We received a request to consider reassignment of ICD-10-CM
diagnosis code R93.89 (Abnormal finding on diagnostic imaging of other
specified body structures) from MDC 5 (Diseases and Disorders of the
Circulatory System) in MS-DRGs 302 and 303 (Atherosclerosis with and
without MCC and Atherosclerosis without MCC, respectively) to MDC 23
(Factors Influencing Health Status and Other Contact with Health
Services), consistent with other diagnosis codes that include abnormal
findings. However, the requestor did not suggest a specific MS-DRG
assignment within MDC 23.
We examined claims data from the September 2018 update of the FY
2018 MedPAR file for MS-DRGs 302 and 303 and identified cases reporting
diagnosis code R93.89. Our findings are shown in the following table.
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 302--All cases........................................... 3,750 3.8 $7,956
MS-DRG 302--Cases reporting diagnosis code R93.89............... 3 7.7 10,818
MS-DRG 303--All cases........................................... 12,986 2.3 4,920
MS-DRG 303--Cases reporting diagnosis code R93.89............... 10 2 3,416
----------------------------------------------------------------------------------------------------------------
As shown in the table, for MS-DRG 302, there was a total of 3,750
cases with an average length of stay of 3.8 days and average costs of
$7,956. Of these 3,750 cases, there were 3 cases reporting abnormal
finding on diagnostic imaging of other specified body structures, with
an average length of stay 7.7 days and average costs of $10,818. For
MS-DRG 303, there was a total of 12,986 cases with an average length of
stay of 2.3 days and average costs of $4,920. Of these 12,986 cases,
there were 10 cases reporting abnormal finding on diagnostic imaging of
other specified body structures, with an average length of stay 2 days
and average costs of $3,416.
Our clinical advisors reviewed this request and determined that the
assignment of diagnosis code R93.89 to MDC 5 in MS-DRGs 302 and 303 was
a result of replication from ICD-9-CM diagnosis code 793.2 (Nonspecific
(abnormal) findings on radiological and other examination of other
intrathoracic organs), which was assigned to those MS-DRGs. Therefore,
they support reassignment of diagnosis code R93.89 to MDC 23. Our
clinical advisors agree this reassignment is clinically appropriate as
it is consistent with other diagnosis codes in MDC 23 that include
abnormal findings from other nonspecified sites. Specifically, our
clinical advisors suggest reassignment of diagnosis code R89.93 to MS-
DRGs 947 and 948 (Signs and Symptoms with and without MCC,
respectively). Therefore, we are proposing to reassign ICD-10-CM
diagnosis code R93.89 from MDC 5 in MS-DRGs 302 and 303 to MDC 23 in
MS-DRGs 947 and 948.
12. Review of Procedure Codes in MS-DRGs 981 Through 983 and 987
Through 989
a. Adding Procedure Codes and Diagnosis Codes Currently Grouping to MS-
DRGs 981 Through 983 or MS-DRGs 987 Through 989 into MDCs
We annually conduct a review of procedures producing assignment to
MS-DRGs 981 through 983 (Extensive O.R. Procedure Unrelated to
Principal Diagnosis with MCC, with CC, and without CC/MCC,
respectively) or MS-DRGs 987 through 989 (Nonextensive O.R. Procedure
Unrelated to Principal Diagnosis with MCC, with CC, and without CC/MCC,
respectively) on the basis of volume, by procedure, to see if it would
be appropriate to move cases reporting these procedure codes out of
these MS-DRGs into one of the surgical MS-DRGs for the MDC into which
the principal diagnosis falls. The data are arrayed in two ways for
comparison purposes. We look at a frequency count of each major
operative procedure code. We also compare procedures across MDCs by
volume of procedure codes within each MDC. We use this information to
determine which procedure codes and diagnosis codes to examine.
We identify those procedures occurring in conjunction with certain
principal diagnoses with sufficient frequency to justify adding them to
one of the surgical MS-DRGs for the MDC in which the diagnosis falls.
We also consider whether it would be more appropriate to move the
principal diagnosis codes into the MDC to which the procedure is
currently assigned. Based on the results of our review of the claims
data from the September 2018 update of the FY 2018 MedPAR file, we are
proposing to move the cases reporting the procedures and/or principal
diagnosis codes described below from MS-DRGs 981 through 983 or MS-DRGs
987 through 989 into one of the surgical MS-DRGs for the MDC into which
the principal diagnosis or procedure is assigned.
(1) Gastrointestinal Stromal Tumors With Excision of Stomach and Small
Intestine
Gastrointestinal stromal tumors (GIST) are tumors of connective
tissue, and are currently assigned to MDC 8 (Diseases and Disorders of
the Musculoskeletal System and Connective Tissue). The ICD-10-CM
diagnosis codes describing GIST are listed in the table below.
------------------------------------------------------------------------
ICD-10-CM diagnosis code Code description
------------------------------------------------------------------------
C49.A0.................... Gastrointestinal stromal tumor, unspecified
site.
C49.A1.................... Gastrointestinal stromal tumor of esophagus.
C49.A2.................... Gastrointestinal stromal tumor of stomach.
C49.A3.................... Gastrointestinal stromal tumor of small
intestine.
C49.A4.................... Gastrointestinal stromal tumor of large
intestine.
C49.A5.................... Gastrointestinal stromal tumor of rectum.
C49.A9.................... Gastrointestinal stromal tumor of other
sites.
------------------------------------------------------------------------
[[Page 19217]]
During our review of cases that group to MS-DRGs 981 through 983,
we noted that when procedures describing open excision of the stomach
or small intestine (ICD-10-PCS procedure codes 0DB60ZZ (Excision of
stomach, open approach) and 0DB80ZZ (Excision of small intestine, open
approach)) were reported with a principal diagnosis of GIST, the cases
group to MS-DRGs 981 through 983. These two excision codes are assigned
to several MDCs, as listed in the table below. Whenever there is a
surgical procedure reported on the claim, which is unrelated to the MDC
to which the case was assigned based on the principal diagnosis, it
results in an MS-DRG assignment to a surgical class referred to as
``unrelated operating room procedures''.
DRG Assignments for ICD-10-PCS Procedure Codes 0DB60ZZ and 0DB80ZZ
----------------------------------------------------------------------------------------------------------------
MDC DRG DRG Description
----------------------------------------------------------------------------------------------------------------
5............................ 264......................... Other Circulatory O.R. Procedures.
6............................ 326-328..................... Stomach, Esophageal and Duodenal Procedures.
10........................... 619-621..................... Procedures for Obesity.
17........................... 820-822..................... Lymphoma and Leukemia with Major Procedure.
17........................... 826-828..................... Myeloproliferative Disorders or Poorly
Differentiated Neoplasms with Major Procedure.
21........................... 907-909..................... Other O.R. Procedures for Injuries.
24........................... 957-959..................... Other Procedures for Multiple Significant Trauma.
----------------------------------------------------------------------------------------------------------------
We first examined cases that reported a principal diagnosis of GIST
and ICD-10-PCS procedure code 0DB60ZZ or 0DB80ZZ that currently group
to MS-DRGs 981 through 983, as well as all cases in MS-DRGs 981 through
983. Our findings are shown in the table below.
MS-DRGs 981-983: All Cases and Cases With Principal Diagnosis of GIST and Procedure Code 0DB60ZZ or 0DB80ZZ
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 981--All cases........................................... 29,192 11.3 $29,862
MS-DRG 981--Cases with procedure code 0DB60ZZ................... 46 12.4 35,723
MS-DRG 981--Cases with procedure code 0DB80ZZ................... 12 10.8 28,059
MS-DRG 982--All cases........................................... 16,834 6.3 16,939
MS-DRG 982--Cases with procedure code 0DB60ZZ................... 104 6.8 17,442
MS-DRG 982--Cases with procedure code 0DB80ZZ................... 41 8 18,961
MS-DRG 983--All cases........................................... 3,166 3.3 11,872
MS-DRG 983--Cases with procedure code 0DB60ZZ................... 97 4.5 11,901
MS-DRG 983--Cases with procedure code 0DB80ZZ................... 19 4.5 9,971
----------------------------------------------------------------------------------------------------------------
Of the MDCs to which these gastrointestinal excision procedures are
currently assigned, our clinical advisors indicated that cases with a
principal diagnosis of GIST that also report an open gastrointestinal
excision procedure code would logically be assigned to MDC 6 (Diseases
and Disorders of the Digestive System). Within MDC 6, ICD-10-PCS
procedures codes 0DB60ZZ and 0DB80ZZ are currently assigned to MS-DRGs
326, 327, and 328 (Stomach, Esophageal and Duodenal Procedures with
MCC, CC, and without CC/MCC, respectively). To understand how the
resources associated with the subset of cases reporting a principal
diagnosis of GIST and procedure code 0DB60ZZ or 0DB80ZZ compare to
those of cases in MS-DRGs 326, 327, and 328 as a whole, we examined the
average costs and average length of stay for all cases in MS-DRGs 326,
327, and 328. Our findings are shown in the table below.
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 326--All cases........................................... 9,898 13 $36,129
MS-DRG 327--All cases........................................... 9,602 6.6 18,736
MS-DRG 328--All cases........................................... 7,634 2.9 11,555
----------------------------------------------------------------------------------------------------------------
Our clinical advisors reviewed these data and noted that the
average length of stay and average costs of this subset of cases were
similar to those of cases in MS-DRGs 326, 327, and 328 in MDC 6. To
consider whether it was appropriate to move the GIST diagnosis codes
from MDC 8, we examined the other procedure codes reported for cases
that report a principal diagnosis of GIST and noted that almost all of
the O.R. procedures most frequently reported were assigned to MDC 6
rather than MDC 8. Our clinical advisors believe that, given the
similarity in resource use between this subset of cases and cases in
MS-DRGs 326, 327, and 328, and that the GIST diagnosis codes are
gastrointestinal in nature, they would be more appropriately assigned
to MS-DRGs 326, 327, and 328 in MDC 6 than their current assignment in
MDC 8. Therefore, we are proposing to move the GIST diagnosis codes
listed above from MDC 8 to MDC 6 within MS-DRGs 326, 327, and 328.
Under our proposal, cases reporting a principal diagnosis of GIST would
group to MS-DRGs 326, 327, and 328.
(2) Peritoneal Dialysis Catheter Complications
During our review of the cases currently grouping to MS-DRGs 981-
[[Page 19218]]
983, we noted that cases reporting a principal diagnosis of
complications of peritoneal dialysis catheters with procedure codes
describing removal, revision, and/or insertion of new peritoneal
dialysis catheters group to MS-DRGs 981 through 983. The ICD-10-CM
diagnosis codes that describe complications of peritoneal dialysis
catheters, listed in the table below, are assigned to MDC 21 (Injuries,
Poisonings and Toxic Effects of Drugs). These principal diagnoses are
frequently reported with the procedure codes describing removal,
revision, and/or insertion of new peritoneal dialysis catheters.
------------------------------------------------------------------------
ICD-10-CM code Code description
------------------------------------------------------------------------
T85.611A.................. Breakdown (mechanical) of intraperitoneal
dialysis catheter, initial encounter.
T85.621A.................. Displacement of intraperitoneal dialysis
catheter, initial encounter.
T85.631A.................. Leakage of intraperitoneal dialysis
catheter, initial encounter.
T85.691A.................. Other mechanical complication of
intraperitoneal dialysis catheter, initial
encounter.
T85.71XA.................. Infection and inflammatory reaction due to
peritoneal dialysis catheter, initial
encounter.
T85.898A.................. Other specified complication of other
internal prosthetic devices, implants and
graft, initial encounter.
------------------------------------------------------------------------
The procedure codes in the table below describe removal, revision,
and/or insertion of new peritoneal dialysis catheters or revision of
synthetic substitutes and are currently assigned to MDC 6 (Diseases and
Disorders of the Digestive System) in MS-DRGs 356, 357, and 358 (Other
Digestive System O.R. Procedures with MCC, with CC, and without CC/MCC,
respectively).
------------------------------------------------------------------------
ICD-10-PCS procedure code Code description
------------------------------------------------------------------------
0WHG03Z................... Insertion of infusion device into peritoneal
cavity, open approach.
0WHG43Z................... Insertion of infusion device into peritoneal
cavity, percutaneous endoscopic approach.
0WPG03Z................... Removal of infusion device from peritoneal
cavity, open approach.
0WPG43Z................... Removal of infusion device from peritoneal
cavity, percutaneous endoscopic approach.
0WWG03Z................... Revision of infusion device in peritoneal
cavity, open approach.
0WWG0JZ................... Revision of synthetic substitute in
peritoneal cavity, open approach.
0WWG43Z................... Revision of infusion device in peritoneal
cavity, percutaneous endoscopic approach.
0WWG4JZ................... Revision of synthetic substitute in
peritoneal cavity, percutaneous endoscopic
approach.
------------------------------------------------------------------------
We examined the claims data from the September 2018 update of the
FY 2018 MedPAR file for the average costs and length of stay for cases
that report a principal diagnosis of complications of peritoneal
dialysis catheters with a procedure describing removal, revision, and/
or insertion of new peritoneal dialysis catheters or revision of
synthetic substitutes. Our findings are shown in the table below. We
note that we did not find any such cases in MS-DRG 983.
MS-DRG 981 Through 982: Peritoneal Dialysis Catheter Procedures With Principal Diagnosis of Complications of
Peritoneal Dialysis Catheters
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 981--Cases reporting peritoneal dialysis catheter 1,603 8.5 $20,676
procedures with a principal diagnosis of complications of
peritoneal dialysis catheters..................................
MS-DRG 982--Cases reporting peritoneal dialysis catheter 5 8.6 11,694
procedures with a principal diagnosis of complications of
peritoneal dialysis catheters..................................
----------------------------------------------------------------------------------------------------------------
Our clinical advisors indicated that, within MDC 21, the procedures
describing removal, revision, and/or insertion of new peritoneal
dialysis catheters or revision of synthetic substitutes most suitably
group to MS-DRGs 907, 908, and 909, which contain all procedures for
injuries that are not specific to the hand, skin, and wound
debridement. To determine how the resources for this subset of cases
compared to cases in MS-DRGs 907, 908, and 909 as a whole, we examined
the average costs and length of stay for cases in MS-DRGs 907, 908, and
909. Our findings are shown in the table below.
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 907--All cases........................................... 9,482 9.7 $27,492
MS-DRG 908--All cases........................................... 9,305 5.3 14,597
MS-DRG 909--All cases........................................... 3,011 3 9,587
----------------------------------------------------------------------------------------------------------------
Our clinical advisors considered these data and noted that the
average costs and length of stay for this subset of cases, most of
which group to MS-DRG 981, are lower than the average costs and length
of stay for cases of the same
[[Page 19219]]
severity level in MS-DRGs 907. However, our clinical advisors believe
that the procedures describing removal, revision, and/or insertion of
new peritoneal dialysis catheters or revision of synthetic substitutes
are clearly related to the principal diagnosis codes describing
complications of peritoneal dialysis catheters and, therefore, it is
clinically appropriate for the procedures to group to the same MS-DRGs
as the principal diagnoses. Therefore, we are proposing to add the
eight procedure codes listed in the table above that describe removal,
revision, and/or insertion of new peritoneal dialysis catheters or
revision of synthetic substitutes to MDC 21 (Injuries, Poisonings &
Toxic Effects of Drugs) in MS-DRGs 907, 908, and 909. Under this
proposal, cases reporting a principal diagnosis of complications of
peritoneal dialysis catheters with a procedure describing removal,
revision, and/or insertion of new peritoneal dialysis catheters or
revision of synthetic substitutes would group to MS-DRGs 907, 908, and
909.
(3) Bone Excision With Pressure Ulcers
During our review of the cases that group to MS-DRGs 981 through
983, we noted that when procedures describing excision of the sacrum,
pelvic bones, and coccyx (ICD-10-PCS procedure codes 0QB10ZZ (Excision
of sacrum, open approach), 0QB20ZZ (Excision of right pelvic bone, open
approach), 0QB30ZZ (Excision of left pelvic bone, open approach), and
0QBS0ZZ (Excision of coccyx, open approach)) are reported with a
principal diagnosis of pressure ulcers in MDC 9 (Diseases and Disorders
of the Skin, Subcutaneous Tissue and Breast), the cases group to MS-
DRGs 981 through 983. The procedures describing excision of the sacrum,
pelvic bones, and coccyx group to several MDCs, which are listed in the
table below.
MS-DRG Assignments for ICD-10-PCS Codes 0QB10ZZ, 0QB20ZZ, 0QB30ZZ, and 0QBS0ZZ
----------------------------------------------------------------------------------------------------------------
MDC MS-DRG MS-DRG description
----------------------------------------------------------------------------------------------------------------
3............................ 133-134..................... Other Ear, Nose, Mouth and Throat O.R. Procedures
with CC/MCC and without CC/MCC, respectively.
8............................ 515-517..................... Other Musculoskeletal System and Connective Tissue
O.R. Procedures with MCC, with CC, and without CC/
MCC, respectively.
10........................... 628-630..................... Other Endocrine, Nutritional and Metabolic O.R.
Procedures with MCC, with CC, and without CC/MCC,
respectively.
21........................... 907-909..................... Other O.R. Procedures for Injuries.
24........................... 957-959..................... Other Procedures for Multiple Significant Trauma.
----------------------------------------------------------------------------------------------------------------
When cases reporting procedure codes describing excision of the
sacrum, pelvic bones, and coccyx report a principal diagnosis from MDC
9, the ICD-10-CM diagnosis codes that are most frequently reported as
principal diagnoses are listed below.
------------------------------------------------------------------------
ICD-10-CM diagnosis code Code description
------------------------------------------------------------------------
L89.150................... Pressure ulcer of sacral region,
unstageable.
L89.153................... Pressure ulcer of sacral region, stage 3.
L89.154................... Pressure ulcer of sacral region, stage 4.
L89.214................... Pressure ulcer of right hip, stage 4.
L89.224................... Pressure ulcer of left hip, stage 4.
L89.314................... Pressure ulcer of right buttock, stage 4.
L89.324................... Pressure ulcer of left buttock, stage 4.
L89.894................... Pressure ulcer of other site, stage 4.
------------------------------------------------------------------------
We examined the claims data from the September 2018 update of the
FY 2018 MedPAR file for the average costs and length of stay for cases
that report procedures describing excision of the sacrum, pelvic bones,
and coccyx in conjunction with a principal diagnosis of pressure
ulcers.
MS-DRGs 981 Through 983: Cases Reporting Excision of the Sacrum, Pelvic Bones, and Coccyx Reported With a
Principal Diagnosis of Pressure Ulcers
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 981--Cases reporting excision of the sacrum, pelvic 394 11.9 $24,398
bones, and coccyx and a principal diagnosis of pressure ulcers.
MS-DRG 982--Cases Reporting excision of the sacrum, pelvic 477 9.4 16,464
bones, and coccyx and a principal diagnosis of pressure ulcers.
MS-DRG 983--Cases Reporting excision of the sacrum, pelvic 38 4.8 8,519
bones, and coccyx and a principal diagnosis of pressure ulcers.
----------------------------------------------------------------------------------------------------------------
Our clinical advisors indicated that, given the nature of these
procedures, they could not be appropriately assigned to the specific
surgical MS-DRGs within MDC 9, which are: Skin graft; skin debridement;
mastectomy for malignancy; and breast biopsy, local excision, and other
breast procedures. Therefore, our clinical advisors believe that these
procedures would most suitably group to MS-DRGs 579, 580, and 581
(Other Skin, Subcutaneous Tissue and Breast Procedures with MCC, with
CC, and without CC/MCC, respectively), which contain procedures
[[Page 19220]]
assigned to MDC 9 that do not fit within the specific surgical MS-DRGs
in MDC 9. Therefore, we examined the claims data for the average length
of stay and average costs for MS-DRGs 579, 580, and 581 in MDC 9. Our
findings are shown in the table below.
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 579...................................................... 4,091 9.2 $19,873
MS-DRG 580...................................................... 10,048 5.2 11,229
MS-DRG 581...................................................... 4,364 3 8,987
----------------------------------------------------------------------------------------------------------------
Our clinical advisors reviewed these data and noted that, in this
subset of cases, most cases group to MS-DRGs 981 and 982 and have
greater average length of stay and average costs than those cases of
the same severity level in MS-DRGs 579 and 580. The smaller number of
cases that group to MS-DRG 983 have lower average costs than cases in
MS-DRG 581. However, our clinical advisors believe that the procedure
codes describing excision of the sacrum, pelvic bones, and coccyx are
clearly related to the principal diagnosis codes describing pressure
ulcers, as these procedures would be performed to treat pressure ulcers
in the sacrum, hip, and buttocks regions. Therefore, our clinical
advisors believe that it is clinically appropriate for the procedures
to group to the same MS-DRGs as the principal diagnoses. Therefore, we
are proposing to add the ICD-10-PCS procedure codes describing excision
of the sacrum, pelvic bones, and coccyx to MDC 9 in MS-DRGs 579, 580,
and 581. Under this proposal, cases reporting a principal diagnosis in
MDC 9 (such as pressure ulcers) with a procedure describing excision of
the sacrum, pelvic bones, and coccyx would group to MS-DRGs 579, 580,
and 581.
(4) Lower Extremity Muscle and Tendon Excision
During the review of the cases that group to MS-DRGs 981 through
983, we noted that when several ICD-10-PCS procedure codes describing
excision of lower extremity muscles and tendons are reported in
conjunction with ICD-10-CM diagnosis codes in MDC 10 (Endocrine,
Nutritional and Metabolic Diseases and Disorders), the cases group to
MS-DRGs 981 through 983. These ICD-10-PCS procedure codes are listed in
the table below, and are assigned to several MS-DRGs, which are also
listed below.
----------------------------------------------------------------------------------------------------------------
ICD-10-PCS procedure code Code description
-----------------------------------------------------------------------------------
0KBN0ZZ......................... Excision of right hip muscle, open approach.
0KBP0ZZ......................... Excision of left hip muscle, open approach.
0KBS0ZZ......................... Excision of right lower leg muscle, open
approach.
0KBT0ZZ......................... Excision of left lower leg muscle, open approach.
0KBV0ZZ......................... Excision of right foot muscle, open approach.
0KBW0ZZ......................... Excision of left foot muscle, open approach.
0LBV0ZZ......................... Excision of right foot tendon, open approach.
0LBW0ZZ......................... Excision of left foot tendon, open approach.
----------------------------------------------------------------------------------------------------------------
----------------------------------------------------------------------------------------------------------------
MDC MS-DRG MS-DRG description
----------------------------------------------------------------------------------------------------------------
01........................... 040-042..................... Peripheral, Cranial Nerve and Other Nervous System
Procedures with MCC, with CC or Peripheral
Neurostimulator, and without CC/MCC, respectively.
08........................... 500-502..................... Soft Tissue Procedures with MCC, with CC, and
without CC/MCC, respectively.
09........................... 579-581..................... Other Skin, Subcutaneous Tissue and Breast
Procedures with MCC, with CC, and without CC/MCC,
respectively.
21........................... 907-909..................... Other O.R. Procedures for Injuries.
24........................... 957-959..................... Other Procedures for Multiple Significant Trauma.
----------------------------------------------------------------------------------------------------------------
The ICD-10-CM diagnosis codes in MDC 10 that are most frequently
reported as the principal diagnosis with a procedure describing
excision of lower extremity muscles and tendons are listed in the table
below. The combination indicates debridement procedures for more
complex diabetic ulcers.
------------------------------------------------------------------------
ICD-10-CM procedure code Code description
------------------------------------------------------------------------
E11.621................... Type 2 diabetes mellitus with foot ulcer.
E11.69.................... Type 2 diabetes mellitus with other
specified complication.
E11.628................... Type 2 diabetes mellitus with other skin
complications.
E11.622................... Type 2 diabetes mellitus with other skin
ulcer.
E10.621................... Type 1 diabetes mellitus with foot ulcer.
------------------------------------------------------------------------
To understand the resource use for the subset of cases reporting
procedure codes describing excision of lower extremity muscles and
tendons that are currently grouping to MS-DRGs 981 through 983, we
examined claims data
[[Page 19221]]
for the average length of stay and average costs for these cases. Our
findings are shown in the table below.
MS-DRGs 981-983: Cases Reporting Procedures Describing Excision of Lower Extremity Muscles and Tendons With a
Principal Diagnosis in MDC 10
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 981--Cases reporting excision of lower extremity muscles 125 9.1 $19,031
and tendons and a principal diagnosis in MDC 10................
MS-DRG 982--Cases reporting excision of lower extremity muscles 561 6.2 12,000
and tendons and a principal diagnosis in MDC 10................
MS-DRG 983--Cases reporting excision of lower extremity muscles 16 4.8 9,003
and tendons and a principal diagnosis in MDC 10................
----------------------------------------------------------------------------------------------------------------
Our clinical advisors examined cases reporting procedures
describing excision of lower extremity muscles and tendons with a
principal diagnosis in the MS-DRGs within MDC 10 and determined that
these cases would most suitably group to MS-DRGs 622, 623, and 624
(Skin Grafts and Wound Debridement for Endocrine, Nutritional and
Metabolic Disorders with MCC, with CC, and without CC/MCC,
respectively). Therefore, we examined the average length of stay and
average costs for cases assigned to MS-DRGs 622, 623, and 624. Our
findings are shown in the table below.
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 622...................................................... 1,540 11.7 $25,114
MS-DRG 623...................................................... 4,849 6.6 13,490
MS-DRG 624...................................................... 232 3.7 7,442
----------------------------------------------------------------------------------------------------------------
Our clinical advisors reviewed these data and noted that most of
the cases reporting procedures describing excision of lower extremity
muscles and tendons group to MS-DRGs 981 and 982. For these cases, the
average length of stay and average costs are lower than those of cases
that currently group to MS-DRGs 622 and 623. However, our clinical
advisors believe that these procedures are clearly related to the
principal diagnoses in MDC 10, as they would be performed to treat
skin-related complications of diabetes and, therefore, it is clinically
appropriate for the procedures to group to the same MS-DRGs as the
principal diagnoses. Therefore, we are proposing to add the procedure
codes listed previously describing excision of lower extremity muscles
and tendons to MDC 10. Under our proposal, cases reporting these
procedure codes with a principal diagnosis in MDC 10 would group to MS-
DRGs 622, 623, and 624.
(5) Kidney Transplantation Procedures
During our review of the cases that group to MS-DRGs 981 through
983, we noted that when procedures describing transplantation of
kidneys (ICD-10-PCS procedure codes 0TY00Z0 (Transplantation of right
kidney, allogeneic, open approach) and 0TY10Z0 (Transplantation of left
kidney, allogeneic, open approach)) are reported in conjunction with
ICD-10-CM diagnosis codes in MDC 5 (Diseases and Disorders of the
Circulatory System), the cases group to MS-DRGs 981 through 983. The
ICD-10-CM diagnosis codes in MDC 5 that are reported with the kidney
transplantation codes are I13.0 (Hypertensive heart and chronic kidney
disease with heart failure and with stage 1 through stage 4 chronic
kidney disease) and I13.2 (Hypertensive heart and chronic kidney
disease with heart failure and with stage 5 chronic kidney disease),
which group to MDC 5. Procedure codes describing transplantation of
kidneys are assigned to MS-DRG 652 (Kidney Transplant) in MDC 11. We
examined claims data to identify the average length of stay and average
costs for cases reporting procedure codes describing transplantation of
kidneys with a principal diagnosis in MDC 5, which are currently
grouping to MS-DRGs 981 through 983. Our findings are shown in the
table below. We did not find any such cases in MS-DRG 983.
MS-DRGs 981 Through 983: Cases Reporting Procedures Describing Transplantation of Kidney With a Principal
Diagnosis in MDC 5
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 981--Cases reporting transplantation of kidney and a 285 6.8 $25,340
principal diagnosis in MDC 5...................................
MS-DRG 982--Cases reporting transplantation of kidney and a 2 3.5 21,678
principal diagnosis in MDC 5...................................
----------------------------------------------------------------------------------------------------------------
Our clinical advisors examined the MS-DRGs within MDC 5 and
indicated that, given the nature of the procedures compared to the
specific surgical procedures contained in the other surgical MS-DRGs in
MDC 5, they could not be appropriately assigned to any of the specific
surgical MS-DRGs. Therefore, they determined that these cases would
most suitably group to MS-DRG 264 (Other Circulatory System O.R.
Procedures), which contains a broader range of procedures related to
MDC 5 diagnoses. We examined claims data to determine the average
length of stay and
[[Page 19222]]
average costs for cases assigned to MS-DRG 264. We found a total of
10,073 cases, with an average length of stay of 9.3 days and average
costs of $22,643.
Our clinical advisors reviewed these data and noted that the
average costs for cases reporting transplantation of kidney with a
diagnosis from MDC 5 are similar to the average costs of cases in MS-
DRG 264 ($22,643 in MS-DRG 264 compared to $25,340 in MS-DRG 981),
while the average length of stay is shorter than that of cases in MS-
DRG 264 (9.3 days in MS-DRG 264 compared to 6.8 days in MS-DRG 981).
Our clinical advisors noted that ICD-10-CM diagnosis codes describing
hypertensive heart and chronic kidney disease without heart failure
(I13.10 (Hypertensive heart and chronic kidney disease without heart
failure, with stage 1 through stage 4 chronic kidney disease, or
unspecified chronic kidney disease) and I13.11 (Hypertensive heart and
chronic kidney disease without heart failure, with stage 5 chronic
kidney disease, or end stage renal disease group) group to MS-DRG 652
(Kidney Transplant) in MDC 11 (Diseases and Disorders of the Kidney and
Urinary Tract). Our clinical advisors also noted that the counterpart
codes describing hypertensive heart and chronic kidney disease with
heart failure are as related to the kidney transplantation codes as the
codes without heart failure, but because the codes with heart failure
group to MDC 5, cases reporting a kidney transplant procedure with a
diagnosis code of hypertensive heart and chronic kidney disease with
heart failure currently group to MS-DRGs 981 through 983. Therefore, we
are proposing to add ICD-10-PCS procedure codes 0TY00Z0 and 0TY10Z0 to
MS-DRG 264 in MDC 5. Under this proposal, cases reporting a principal
diagnosis in MDC 5 with a procedure describing kidney transplantation
would group to MS-DRG 264 in MDC 5. We note that because MDC 5 covers
the circulatory system, and kidney transplants generally group to MDC
11, we are seeking public comments on whether the procedure codes
should instead continue to group to MS-DRGs 981 through 983.
(6) Insertion of Feeding Device
During our review of the cases that group to MS-DRGs 981 through
983, we noted that when ICD-10-PCS procedure code 0DH60UZ (Insertion of
feeding device into stomach, open approach) is reported with ICD-10-CM
diagnosis codes assigned to MDC 1 (Diseases and Disorders of the
Nervous System) or MDC 10 (Endocrine, Nutritional and Metabolic
Diseases and Disorders), the cases group to MS-DRGs 981 through 983.
ICD-10-PCS procedure code 0DH60UZ is currently assigned to MDC 6
(Diseases and Disorders of the Digestive System) in MS-DRGs 326, 327,
and 328 (Stomach, Esophageal and Duodenal Procedures) and MDC 21
(Injuries, Poisonings and Toxic Effects of Drugs) in MS-DRGs 907, 908,
and 909 (Other O.R. Procedures for Injuries). We also noticed that: (1)
When ICD-10-PCS procedure code 0DH60UZ is reported with a principal
diagnosis in MDC 1, the ICD-10-CM diagnosis codes reported with this
procedure code describe cerebral infarctions of various etiology and
anatomic locations and resulting complications; and (2) when ICD-10-PCS
procedure code 0DH60UZ is reported with a principal diagnosis in MDC
10, the ICD-10-CM diagnosis codes reported with this procedure code
pertain to dehydration, failure to thrive, and various forms of
malnutrition.
We examined claims data to identify the average length of stay and
average costs for cases in MS-DRGs 981 through 983 reporting ICD-10-PCS
procedure code 0DH60UZ in conjunction with a principal diagnosis from
MDC 1 or MDC 10. Our findings are shown in the table below.
MS-DRGs 981 Through 983: Cases Reporting Procedure Code 0DH60UZ With a Principal Diagnosis in MDC 1 or MDC 10
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 981--Cases reporting procedure code 0DH60UZ and a 115 19.3 $40,598
principal diagnosis in MDC 1...................................
MS-DRG 982--Cases reporting procedure code 0DH60UZ and a 43 13.2 25,042
principal diagnosis in MDC 1...................................
MS-DRG 983--Cases reporting procedure code 0DH60UZ and a 4 14.3 26,954
principal diagnosis in MDC 1...................................
MS-DRG 981--Cases reporting procedure code 0DH60UZ and a 47 13.4 24,690
principal diagnosis in MDC 10..................................
MS-DRG 982--Cases reporting procedure code 0DH60UZ and a 20 7.2 12,792
principal diagnosis in MDC 10..................................
MS-DRG 983--Cases reporting procedure code 0DH60UZ and a 5 5.0 8,608
principal diagnosis in MDC 10..................................
----------------------------------------------------------------------------------------------------------------
Our clinical advisors determined that the feeding tube procedure
was related to specific diagnoses within MDC 1 and MDC 10 and,
therefore, could be assigned to both MDCs. Therefore, they reviewed the
MS-DRGs within MDC 1 and MDC 10. They determined that the most suitable
MS-DRG assignment within MDC 1 would be MS-DRGs 040, 041, and 042
(Peripheral, Cranial Nerve and Other Nervous System Procedures with
MCC, with CC or Peripheral Neurostimulator, and without CC/MCC,
respectively), which contain procedures assigned to MDC 1 that describe
insertion of devices into anatomical areas that are not part of the
nervous system. Our clinical advisors determined that the most suitable
MS-DRG assignment within MDC 10 would be MS-DRGs 628, 629, and 630
(Other Endocrine, Nutritional and Metabolic O.R. Procedures with MCC,
with CC, and without CC/MCC, respectively), which contain the most
clinically similar procedures assigned to MDC 10, such as those
describing insertion of infusion pump into subcutaneous tissue and
fascia. Therefore, we examined claims data to identify the average
length of stay and average costs for cases assigned to MDC 1 in MS-DRGs
040, 041, and 042 and MDC 10 in MS-DRGs 628, 629, and 630. Our findings
are shown in the tables below.
[[Page 19223]]
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRGs in MDC 1 cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 040...................................................... 4,211 10.2 $27,096
MS-DRG 041...................................................... 6,153 5.1 16,917
MS-DRG 042...................................................... 2,249 3.0 13,365
----------------------------------------------------------------------------------------------------------------
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRGs in MDC 10 cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 628...................................................... 3,004 9.9 $25,472
MS-DRG 629...................................................... 5,435 7.2 16,391
MS-DRG 630...................................................... 237 3.2 10,659
----------------------------------------------------------------------------------------------------------------
Our clinical advisors reviewed these data and noted that the
average length of stay and average costs for the subset of cases
reporting ICD-10-PCS procedure code 0DH60UZ with a principal diagnosis
assigned to MDC 1 are higher than those cases in MS-DRGs 040, 041, and
042. For example, the cases reporting ICD-10-PCS procedure code 0DH60UZ
and a principal diagnosis in MDC 1 that currently group to MS-DRG 981
have an average length of stay of 19.3 days and average costs of
$40,598, while the cases in MS-DRG 040 have an average length of stay
of 10.2 days and average costs of $27,096. Our clinical advisors noted
that the average length of stay and average costs for the subset of
cases reporting ICD-10-PCS procedure code 0DH60UZ with a principal
diagnosis assigned to MDC 10 are more closely aligned with those cases
in MS-DRGs 628, 629, and 630. In both cases, our clinical advisors
believe that the insertion of feeding device is clearly related to the
principal diagnoses in MDC 1 and MDC 10 and, therefore, it is
clinically appropriate for the procedures to group to the same MS-DRGs
as the principal diagnoses. Therefore, we are proposing to add ICD-10-
PCS procedure code 0DH60UZ to MDC 1 and MDC 10. Under this proposal,
cases reporting procedure code 0DH60UZ with a principal diagnosis in
MDC 1 would group to MS-DRGs 040, 041, and 042, while cases reporting
ICD-10-PCS procedure code 0DH60UZ with a principal diagnosis in MDC 10
would group to MS-DRGs 628, 629, and 630.
(7) Basilic Vein Reposition in Chronic Kidney Disease
During our review of the cases that group to MS-DRGs 981 through
983, we noted that when procedures codes describing reposition of
basilic vein (ICD-10-PCS procedure codes 05SB0ZZ (Reposition right
basilic vein, open approach), 05SB3ZZ (Reposition right basilic vein,
percutaneous approach), 05SC0ZZ (Reposition left basilic vein, open
approach), and 05SC3ZZ (Reposition left basilic vein, percutaneous
approach)) are reported with a principal diagnosis in MDC 11 (Diseases
and Disorders of the Kidney and Urinary Tract) (typically describing
chronic kidney disease), the cases group to MS-DRGs 981 through 983.
This code combination suggests a revision of an arterio-venous fistula
in a patient on chronic hemodialysis. We examined claims data to
identify the average length of stay and average costs for cases
reporting procedures describing reposition of basilic vein with a
principal diagnosis in MDC 11, which are currently grouping to MS-DRGs
981 through 983. Our findings are shown in the table below.
MS-DRGs 981-983: Cases Reporting Procedures Describing Reposition of Basilic Vein With Principal Diagnosis in
MDC 11
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 981--Cases reporting procedures describing reposition of 48 4.6 $12,232
basilic vein and a principal diagnosis in MDC 11...............
MS-DRG 982--Cases reporting procedures describing reposition of 10 6.9 18,481
basilic vein and a principal diagnosis in MDC 11...............
MS-DRG 983--Cases reporting procedures describing reposition of 1 3.0 3,552
basilic vein and a principal diagnosis in MDC 11...............
----------------------------------------------------------------------------------------------------------------
Our clinical advisors examined claims data for cases in the MS-DRGs
within MDC 11 and determined that cases reporting procedures describing
reposition of basilic vein with a principal diagnosis in MDC 11 would
most suitably group to MS-DRGs 673, 674, and 675 (Other Kidney and
Urinary Tract Procedures with MCC, with CC, and without CC/MCC,
respectively), to which MDC 11 procedures describing reposition of
veins (other than renal veins) are assigned. Therefore, we examined
claims data to identify the average length of stay and average costs
for cases assigned to MS-DRGs 673, 674, and 675. Our findings are shown
in the table below.
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 673...................................................... 10,542 10.8 $25,842
MS-DRG 674...................................................... 6,167 7.4 17,685
MS-DRG 675...................................................... 437 3.9 11,858
----------------------------------------------------------------------------------------------------------------
[[Page 19224]]
Our clinical advisors reviewed these data and noted that the
average length of stay and average costs for cases reporting procedures
describing reposition of basilic vein with a principal diagnosis in MDC
11 with an MCC are significantly lower than for those cases in MS-DRG
673. The average length of stay and average costs are similar for those
cases with a CC, while the single case without a CC or MCC had
significantly lower costs than the average costs of cases in MS-DRG
675. However, our clinical advisors believe that when the procedures
describing reposition of basilic vein are reported with a principal
diagnosis describing chronic kidney disease, the procedure is likely
related to arteriovenous fistulas for dialysis associated with the
chronic kidney disease. Therefore, our clinical advisors believe that
it is clinically appropriate for the procedures to group to the same
MS-DRGs as the principal diagnoses. Therefore, we are proposing to add
ICD-10-PCS procedures codes 05SB0ZZ, 05SB3ZZ, 05SC0ZZ, and 05SC3ZZ to
MDC 11. Under our proposal, cases reporting procedure codes describing
reposition of basilic vein with a principal diagnosis in MDC 11 would
group to MS-DRGs 673, 674, and 675.
(8) Colon Resection With Fistula
During our review of the cases that group to MS-DRGs 981 through
983, we noted that when ICD-10-PCS procedure code 0DTN0ZZ (Resection of
sigmoid colon, open approach) is reported with a principal diagnosis in
MDC 11 (Diseases and Disorders of the Kidney and Urinary Tract), the
cases group to MS-DRGs 981 through 983. The principal diagnosis most
frequently reported with ICD-10-PCS procedure code 0DTN0ZZ in MDC 11 is
ICD-10-CM code N321 (Vesicointestinal fistula). ICD-10-PCS procedure
code 0DTN0ZZ currently groups to several MDCs, which are listed in the
table below.
MS-DRG Assignments for ICD-10-PCS Procedure Code 0DTN0ZZ
------------------------------------------------------------------------
MDC MS-DRG MS-DRG description
------------------------------------------------------------------------
6..................... 329-331............... Major Small and Large
Bowel Procedures.
17.................... 820-822............... Lymphoma and Leukemia
with Major Procedure.
17.................... 826-828............... Myeloproliferative
Disorders or Poorly
Differentiated
Neoplasms with Major
Procedure.
21.................... 907-909............... Other O.R. Procedures
for Injuries.
24.................... 957-959............... Other Procedures for
Multiple Significant
Trauma.
------------------------------------------------------------------------
We examined claims data to identify the average length of stay and
average costs for cases reporting procedure code 0DTN0ZZ with a
principal diagnosis in MDC 11, which are currently grouping to MS-DRGs
981 through 983. Our findings are shown in the table below.
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 981--Cases reporting procedure code 0DTN0ZZ and a 27 15.81 $44,743
principal diagnosis in MDC 11..................................
MS-DRG 982--Cases reporting procedure code 0DTN0ZZ and a 33 8.48 20,105
principal diagnosis in MDC 11..................................
MS-DRG 983--Cases reporting procedure code 0DTN0ZZ and a 5 3.60 12,351
principal diagnosis in MDC 11..................................
----------------------------------------------------------------------------------------------------------------
Our clinical advisors examined the MS-DRGs within MDC 11 and
determined that the cases reporting procedure code 0DTN0ZZ with a
principal diagnosis in MDC 11 would most suitably group to MS-DRGs 673,
674, and 675, which contain procedures performed on structures other
than kidney and urinary tract anatomy. We note that the claims data
describing the average length of stay and average costs for cases in
these MS-DRGs are included in a table earlier in this section. Because
vesicointestinal fistulas involve both the bladder and the bowel, some
procedures in both MDC 6 (Diseases and Disorders of the Digestive
System) and MDC 11 (Diseases and Disorders of the Kidney and Urinary
Tract) would be expected to be related to a principal diagnosis of
vesicointestinal fistula (ICD-10-CM code N321). Our clinical advisors
observed that procedure code 0DTN0ZZ is the second most common
procedure reported in conjunction with a principal diagnosis of code
N321, after ICD-10-PCS procedure code 0TQB0ZZ (Repair bladder, open
approach), which is assigned to both MDC 6 and MDC 11. Our clinical
advisors reviewed the data and noted that the average length of stay
and average costs for this subset of cases are generally higher for
this subset of cases than for cases in MS-DRGs 673, 674, and 675.
However, our clinical advisors believe that when ICD-10-PCS procedure
code 0DTN0ZZ is reported with a principal diagnosis in MDC 11
(typically vesicointestinal fistula), the procedure is related to the
principal diagnosis. Therefore, we are proposing to add ICD-10-PCS
procedure code 0DTN0ZZ to MDC 11. Under our proposal, cases reporting
procedure code 0DTN0ZZ with a principal diagnosis of vesicointestinal
fistula (diagnosis code N321) in MDC 11 would group to MS-DRGs 673,
674, and 675.
b. Reassignment of Procedures Among MS-DRGs 981 Through 983 and 987
Through 989
We also review the list of ICD-10-PCS procedures that, when in
combination with their principal diagnosis code, result in assignment
to MS-DRGs 981 through 983, or 987 through 989, to ascertain whether
any of those procedures should be reassigned from one of those two
groups of MS-DRGs to the other group of MS-DRGs based on average costs
and the length of stay. We look at the data for trends such as shifts
in treatment practice or reporting practice that would make the
resulting MS-DRG assignment illogical. If we find these shifts, we
would propose to move cases to keep the MS-DRGs clinically similar or
to provide payment for the cases in a similar manner. Generally, we
move only those procedures for which we have an adequate number of
discharges to analyze the data.
[[Page 19225]]
Based on the results of our review of claims data in the September
2018 update of the FY 2018 MedPAR file, we are not proposing to change
the current structure of MS-DRGs 981 through 983 and MS-DRGs 987
through 989.
c. Proposed Additions for Diagnosis and Procedure Codes to MDCs
Below we summarize the requests we received to examine cases found
to group to MS-DRGs 981 through 983 or MS-DRGs 987 through 989 to
determine if it would be appropriate to add procedure codes to one of
the surgical MS DRGs for the MDC into which the principal diagnosis
falls or to move the principal diagnosis to the surgical MS-DRGs to
which the procedure codes are assigned.
(1) Stage 3 Pressure Ulcers of the Hip
We received a request to reassign cases for a stage 3 pressure
ulcer of the left hip when reported with procedures involving excision
of pelvic bone or transfer of hip muscle from MS-DRGs 981, 982, and 983
(Extensive O.R. Procedure Unrelated to Principal Diagnosis with MCC,
with CC, and without CC/MCC, respectively) to MS-DRG 579 (Other Skin,
Subcutaneous Tissue and Breast Procedures with MCC) in MDC 9. ICD-10-CM
diagnosis code L89.223 (Pressure ulcer left hip, stage 3) is used to
report this condition and is currently assigned to MDC 9 (Diseases and
Disorders of the Skin, Subcutaneous Tissue and Breast). We refer
readers to section II.12.a. of the preamble of this proposed rule,
where we address ICD-10-PCS procedure code 0QB30ZZ (Excision of left
pelvic bone, open approach), which was reviewed as part of our ongoing
analysis of the unrelated MS-DRGs and which we are proposing to add to
MS-DRGs 579, 580, and 581 in MDC 5. (While the requestor only referred
to base MS-DRG 579, we believe it is appropriate to assign the cases to
MS-DRGs 579, 580, and 581 by severity level.) ICD-10-PCS procedure
codes 0KXP0ZZ (Transfer left hip muscle, open approach) and 0KXN0ZZ
(Transfer right hip muscle, open approach) may be reported to describe
transfer of hip muscle procedures and are currently assigned to MDC 1
(Diseases and Disorders of the Nervous System) and MDC 8 (Diseases and
Disorders of the Musculoskeletal System and Connective Tissue). We
included ICD-10-PCS procedure code 0KXN0ZZ in our analysis because it
describes the identical procedure on the right side.
Our analysis of this grouping issue confirmed that, when a stage 3
pressure ulcer of the left hip (ICD-10-CM diagnosis code L89.223) is
reported as a principal diagnosis with ICD-10-PCS procedure code
0KXP0ZZ or 0KXN0ZZ, these cases group to MS-DRGs 981, 982, and 983. The
reason for this grouping is because whenever there is a surgical
procedure reported on a claim that is unrelated to the MDC to which the
case was assigned based on the principal diagnosis, it results in an
MS-DRG assignment to a surgical class referred to as ``unrelated
operating room procedures.'' In the example provided, because ICD-10-CM
diagnosis code L89.223 describing a stage 3 pressure ulcer of left hip
is classified to MDC 9 and because ICD-10-PCS procedure codes 0KXP0ZZ
and 0KXN0ZZ are classified to MDC 1 (Diseases and Disorders of the
Nervous System) in MS-DRGs 040, 041, and 042 (Peripheral, Cranial Nerve
and Other Nervous System Procedures with MCC, with CC or Peripheral
Neurostimulator, and without CC/MCC, respectively) and MDC 8 (Diseases
and Disorders of the Musculoskeletal System and Connective Tissue) in
MS-DRGs 500, 501, and 502 (Soft Tissue Procedures with MCC, with CC,
and without CC/MCC, respectively), the GROUPER logic assigns this case
to the ``unrelated operating room procedures'' set of MS-DRGs.
For our review of this grouping issue and the request to have
procedure code 0KXP0ZZ added to MDC 9, we examined claims data for
cases reporting procedure code 0KXP0ZZ or 0KXN0ZZ in conjunction with a
diagnosis code that typically groups to MDC 9. Our findings are shown
in the table below.
MS-DRGs 981 Through 983: Cases With Hip Muscle Transfer and Principal Diagnosis in MDC 9
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 981--Cases with procedure code 0KXP0ZZ or 0KXN0ZZ and 72 12.6 $25,023
principal diagnosis in MDC 9...................................
MS-DRG 982--Cases with procedure code 0KXP0ZZ or 0KXN0ZZ and 130 10.5 17,955
principal diagnosis in MDC 9...................................
MS-DRG 983--Cases with procedure code 0KXP0ZZ or 0KXN0ZZ and 16 6.5 13,196
principal diagnosis in MDC 9...................................
----------------------------------------------------------------------------------------------------------------
As indicated earlier, the requestor suggested that we move ICD-10-
PCS procedure code 0KXP0ZZ to MS-DRG 579. However, our clinical
advisors believe that, within MDC 9, these procedure codes are more
clinically aligned with the procedure codes assigned to MS-DRGs 573,
574, and 575 (Skin Graft for Skin Ulcer or Cellulitis with MCC, with CC
and without CC/MCC, respectively), which are more specific to the care
of stage 3, 4 and unstageable pressure ulcers than MS-DRGs 579, 580,
and 581. Therefore, we examined claims data to identify the average
length of stay and average costs for cases assigned to MS-DRGs 573,
574, and 575. Our findings are shown in the table below.
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 573...................................................... 548 15.4 $34,549
MS-DRG 574...................................................... 1,254 9.8 21,251
MS-DRG 575...................................................... 238 5.4 12,006
----------------------------------------------------------------------------------------------------------------
We note that the average costs for cases in MS-DRGs 573 and 574 are
higher than the average costs of the subset of cases with the same
severity reporting a hip muscle transfer and a principal diagnosis in
MDC 9, while the average costs of those cases in MS-DRG 575 are similar
to the average costs of those cases that are currently grouping
[[Page 19226]]
to MS-DRG 983. However, our clinical advisors believe that the cases of
hip muscle transfer represent a distinct, recognizable clinical group
similar to those cases in MS-DRGs 573, 574, and 575, and that the
procedures are clearly related to the principal diagnosis codes.
Therefore, they believe that it is clinically appropriate for the
procedures to group to the same MS-DRGs as the principal diagnoses.
Therefore, we are proposing to add ICD-10-PCS procedure codes 0KXP0ZZ
and 0KXN0ZZ to MDC 9. Under our proposal, cases reporting ICD-10-PCS
procedure code 0KXP0ZZ or 0KXN0ZZ with a principal diagnosis in MDC 9
would group to MS-DRGs 573, 574, and 575.
(2) Gastrointestinal Stromal Tumor
We received a request to reassign cases for gastrointestinal
stromal tumor of the stomach when reported with a procedure describing
laparoscopic bypass of the stomach to jejunum from MS-DRGs 981, 982,
and 983 to MS-DRGs 326, 327, and 328 (Stomach, Esophageal and Duodenal
Procedures with MCC, with CC, and without CC/MCC, respectively) by
adding ICD-10-PCS procedure code 0D164ZA (Bypass stomach to jejunum,
percutaneous endoscopic approach) to MDC 6. ICD-10-CM diagnosis code
C49.A2 (Gastrointestinal stromal tumor of stomach) is used to report
this condition and is currently assigned to MDC 8. ICD-10-PCS procedure
code 0D164ZA is used to report the stomach bypass procedure and is
currently assigned to MDC 5 (Diseases and Disorders of the Circulatory
System), MDC 6 (Diseases and Disorders of the Digestive System), MDC 7
(Diseases and Disorders of the Hepatobiliary System and Pancreas), MDC
10 (Endocrine, Nutritional and Metabolic Diseases and Disorders), and
MDC 17 (Myeloproliferative Diseases and Disorders, Poorly
Differentiated Neoplasms). We refer readers to section II.12.a. of the
preamble of this proposed rule where we discuss our proposal to move
the listed diagnosis codes describing gastrointestinal stromal tumors,
including ICD-10-CM diagnosis code C49.A2, into MDC 6. Therefore, this
proposal, if finalized, would address the cases grouping to MS-DRGs 981
through 983 by instead moving the diagnosis codes to MDC 6, which would
result in the diagnosis code and the procedure code referenced by the
requestor grouping to the same MDC.
(3) Finger Cellulitis
We received a request to reassign cases for cellulitis of the right
finger when reported with a procedure describing open excision of the
right finger phalanx from MS-DRGs 981, 982, and 983 to MS-DRGs 579,
580, and 581 (Other Skin, Subcutaneous Tissue and Breast Procedures
with MCC, with CC, and without CC/MCC, respectively). Currently, ICD-
10-CM diagnosis code L03.011 (Cellulitis of right finger) is used to
report this condition and is currently assigned to MDC 09 in MS-DRGs
573, 574, and 575 (Skin Graft for Skin Ulcer or Cellulitis with MCC,
CC, and without CC/MCC, respectively), 576, 577, and 578 (Skin Graft
except for Skin Ulcer or Cellulitis with MCC, CC, and without CC/MCC,
respectively), and 602 and 603 (Cellulitis with MCC and without MCC,
respectively). ICD-10-PCS procedure code 0PBT0ZZ (Excision of right
finger phalanx, open approach) is used to identify the excision
procedure, and is currently assigned to MDC 03 (Diseases and Disorders
of the Ear, Nose, Mouth and Throat) in MS-DRGs 133 and 134 (Other Ear,
Nose, Mouth and Throat O.R. Procedures with CC/MCC, and without CC/MCC,
respectively); MDC 08 (Diseases and Disorders of the Musculoskeletal
System and Connective Tissue) in MS-DRGs 515, 516, and 517 (Other
Musculoskeletal System and Connective Tissue O.R. Procedures with MCC,
with CC, and without CC/MCC, respectively); MDC 10 (Endocrine,
Nutritional and Metabolic Diseases and Disorders) in MS-DRGs 628, 629,
and 630 (Other Endocrine, Nutritional and Metabolic O.R. Procedures
with MCC, with CC, and without CC/MCC, respectively); MDC 21 (Injuries,
Poisonings and Toxic Effects of Drugs) in MS-DRGs 907, 908, and 909
(Other O.R. Procedures for Injuries with MCC, with CC, and without CC/
MCC, respectively); and MDC 24 (Multiple Significant Trauma) in MS-DRGs
957, 958, and 959 (Other O.R. Procedures for Multiple Significant
Trauma with MCC, with CC, and without CC/MCC, respectively).
Our analysis of this grouping issue confirmed that when a procedure
such as open excision of right finger phalanx (ICD-10-PCS procedure
code 0PBT0ZZ) is reported with a principal diagnosis from MDC 9, such
as cellulitis of the right finger (ICD-10-CM diagnosis code L03.011),
these cases group to MS-DRGs 981, 982, and 983. During our review of
this issue, we also examined claims data for similar procedures
describing excision of phalanges (which are listed in the table below)
and noted the same pattern. We further noted that the ICD-10-PCS
procedure codes describing excision of phalanx procedures with the
diagnostic qualifier ``X'', which are used to report these procedures
when performed for diagnostic purposes, are already assigned to MS-DRGs
579, 580, and 581 (to which the requestor suggested these cases group).
Our clinical advisors also believe that procedures describing resection
of phalanges should be assigned to the same MS-DRG as the excisions,
because the resection procedures would also group to MS-DRGs 981, 982,
and 983 when reported with a principal diagnosis from MDC 9.
------------------------------------------------------------------------
ICD-10-PCS procedure code Code description
------------------------------------------------------------------------
0PBR0ZZ...................... Excision of right thumb phalanx, open
approach.
0PBR3ZZ...................... Excision of right thumb phalanx,
percutaneous approach.
0PBR4ZZ...................... Excision of right thumb phalanx,
percutaneous endoscopic approach.
0PBS0ZZ...................... Excision of left thumb phalanx, open
approach.
0PBS3ZZ...................... Excision of left thumb phalanx,
percutaneous approach.
0PBS4ZZ...................... Excision of left thumb phalanx,
percutaneous endoscopic approach.
0PBT0ZZ...................... Excision of right finger phalanx, open
approach.
0PBT3ZZ...................... Excision of right finger phalanx,
percutaneous approach.
0PBT4ZZ...................... Excision of right finger phalanx,
percutaneous endoscopic approach.
0PBV0ZZ...................... Excision of left finger phalanx, open
approach.
0PBV3ZZ...................... Excision of left finger phalanx,
percutaneous approach.
0PBV4ZZ...................... Excision of left finger phalanx,
percutaneous endoscopic approach.
0PTR0ZZ...................... Resection of right thumb phalanx, open
approach.
0PTS0ZZ...................... Resection of left thumb phalanx, open
approach.
0PTT0ZZ...................... Resection of right finger phalanx, open
approach.
0PTV0ZZ...................... Resection of left finger phalanx, open
approach.
0RTW0ZZ...................... Resection of right finger phalangeal
joint, open approach.
[[Page 19227]]
0RTX0ZZ...................... Resection of left finger phalangeal
joint, open approach.
------------------------------------------------------------------------
As noted in the previous discussion, whenever there is a surgical
procedure reported on the claim that is unrelated to the MDC to which
the case was assigned based on the principal diagnosis, it results in
an MS-DRG assignment to a surgical class referred to as ``unrelated
operating room procedures''.
We examined the claims data for the three codes describing
cellulitis of the finger (ICD-10-CM diagnosis codes L03.011 (Cellulitis
of the right finger), L03.012 (Cellulitis of left finger), and L03.019
(Cellulitis of unspecified finger)) to identify the average length of
stay and average costs for cases reporting a principal diagnosis of
cellulitis of the finger in conjunction with the excision of phalanx
procedures listed in the table above. We note that there were no cases
reporting a principal diagnosis of cellulitis of the finger in
conjunction with the resection of phalanx procedures listed in the
table above.
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 981--Cases with principal diagnosis of cellulitis of the 2 3.5 $7,934
finger and excision of phalanx procedure.......................
MS-DRG 982--Cases with principal diagnosis of cellulitis of the 11 4.2 7,244
finger and excision of phalanx procedure.......................
MS-DRG 983--Cases with principal diagnosis of cellulitis of the 4 4.8 8,058
finger and excision of phalanx procedure.......................
----------------------------------------------------------------------------------------------------------------
We also examined the claims data to identify the average length of
stay and average costs for all cases in MS-DRGs 579, 580, and 581. Our
findings are shown in the table in section II.12.A.3.of the preamble of
this proposed rule.
While our clinical advisors noted that the average length of stay
and average costs for cases in MS-DRGs 579, 580, and 581 are generally
higher than the average length of stay and average costs for the subset
of cases reporting a principal diagnosis of cellulitis of the finger
and a procedure describing excision of phalanx, they believe that the
procedures are clearly related to the principal diagnosis codes and,
therefore, it is clinically appropriate for the procedures to group to
the same MS-DRGs as the principal diagnoses, particularly given that
procedures describing excision of phalanx with the diagnostic qualifier
``X'' are already assigned to these MS-DRGs. In addition, our clinical
advisors believe it is clinically appropriate for the procedures
describing resection of phalanx to be assigned to MS-DRGs 579, 580, and
581 as well. Therefore, we are proposing to add the procedure codes
describing excision and resection of phalanx listed above to MS-DRGs
579, 580, and 581. Under this proposal, cases reporting one of the
excision or resection procedures listed in the table above in
conjunction with a principal diagnosis from MDC 9 would group to MS-
DRGs 579, 580, and 581.
(4) Multiple Trauma With Internal Fixation of Joints
We received a request to reassign cases involving multiple
significant trauma with internal fixation of joints from MS-DRGs 981,
982, and 983 to MS-DRGs 957, 958, and 959 (Other O.R. Procedures for
Multiple Significant Trauma with MCC, with CC, and without CC/MCC,
respectively). The requestor provided an example of several ICD-10-CM
diagnosis codes that together described multiple significant trauma in
conjunction with ICD-10-PCS procedure codes beginning with the prefix
``0SH'' and ``0RH'' that describe internal fixation of joints. The
requestor provided several suggestions to address this assignment,
including: Adding all ICD-10-PCS procedure codes in MDC 8 (Diseases and
Disorders of the Musculoskeletal System and Connective Tissue) with the
exception of codes that group to MS-DRG 956 (Limb Reattachment, Hip and
Femur Procedures for Multiple Significant Trauma) to MS-DRGs 957, 958,
and 959; adding codes within the ``0SH'' and ``0RH'' code ranges to MDC
24; and adding ICD-10-PCS procedure codes from all MDCs except those
that currently group to MS-DRG 955 (Craniotomy for Multiple Significant
Trauma) or MS-DRG 956 (Limb Reattachment, Hip and Femur Procedures for
Multiple Significant Trauma) to MS-DRGs 957, 958, and 959.
While we understand the requestor's concern about these multiple
significant trauma cases, we believe any potential reassignment of
these cases requires significant analysis. Similar to our analysis of
MDC 14 (initially discussed at 81 FR 56854), there are multiple logic
lists in MDC 24 that would need to be reviewed. For example, to satisfy
the logic for multiple significant trauma, the logic requires a
diagnosis code from the significant trauma principal diagnosis list and
two or more significant trauma diagnoses from different body sites. The
significant trauma logic lists for the other body sites (which include
head, chest, abdominal, kidney, urinary system, pelvis or spine, upper
limb, and lower limb) allow the extensive list of diagnosis codes
included in the logic to be reported as a principal or secondary
diagnosis. The analysis of the reporting of all the codes as a
principal and/or secondary diagnosis within MDC 24, combined with the
analysis of all of the ICD-10-PCS procedure codes within MDC 8, is
anticipated to be a multi-year effort. Therefore, we plan to consider
this issue for future rulemaking as part of our ongoing analysis of the
unrelated procedure MS-DRGs.
(5) Totally Implantable Vascular Access Devices
We received a request to reassign cases for insertion of totally
implantable vascular access devices (TIVADs) listed in the table below
when reported with principal diagnoses in MDCs other than MDC 9
(Diseases and Disorders of the Skin, Subcutaneous Tissue and Breast)
and MDC 11 (Diseases and Disorders of the Kidney and Urinary Tract)
from MS-DRGs 981 through 983 to a surgical MS-DRG within the
appropriate MDC based on the principal diagnosis. The requestor noted
that the insertion of
[[Page 19228]]
TIVAD procedures are newly designated as O.R. procedures, effective
October 1, 2018, and are assigned to MDCs 9 and 11. The requestor
stated that TIVADs can be placed for a variety of purposes and are used
to treat a wide range of malignancies at various sites and, therefore,
would likely have a relationship to the principal diagnosis within any
MDC. The requestor suggested that procedures describing the insertion
of TIVADs group to surgical MS-DRGs within every MDC (other than MDCs
2, 20, and 22, which do not contain surgical MS-DRGs). The requestor
further stated that the surgical hierarchy should assign more
significant O.R. procedures within each MDC to a higher position than
procedures describing the insertion of TIVADs because these procedures
consume less O.R. resources than more invasive procedures.
------------------------------------------------------------------------
ICD-PCS code Code description
------------------------------------------------------------------------
0JH60WZ................... Insertion of totally implantable vascular
access device into chest subcutaneous
tissue and fascia, open approach.
0JH80WZ................... Insertion of totally implantable vascular
access device into abdomen subcutaneous
tissue and fascia, open approach.
0JHD0WZ................... Insertion of totally implantable vascular
access device into right upper arm
subcutaneous tissue and fascia, open
approach.
0JHF0WZ................... Insertion of totally implantable vascular
access device into left upper arm
subcutaneous tissue and fascia, open
approach.
0JHG0WZ................... Insertion of totally implantable vascular
access device into right lower arm
subcutaneous tissue and fascia, open
approach.
0JHH0WZ................... Insertion of totally implantable vascular
access device into left lower arm
subcutaneous tissue and fascia, open
approach.
0JHL0WZ................... Insertion of totally implantable vascular
access device into right upper leg
subcutaneous tissue and fascia, open
approach.
0JHM0WZ................... Insertion of totally implantable vascular
access device into left upper leg
subcutaneous tissue and fascia, open
approach.
0JHN0WZ................... Insertion of totally implantable vascular
access device into right lower leg
subcutaneous tissue and fascia, open
approach.
0JHP0WZ................... Insertion of totally implantable vascular
access device into left lower leg
subcutaneous tissue and fascia, open
approach.
------------------------------------------------------------------------
While we agree that TIVAD procedures may be performed in connection
with a variety of principal diagnoses, we note that because these
procedures are newly designated as O.R. procedures effective October 1,
2018, we do not yet have sufficient data to analyze this request. We
plan to consider this issue in future rulemaking as part of our ongoing
analysis of the unrelated procedure MS-DRGs.
(6) Gastric Band Procedure Complications or Infections
We received a request to reassign cases for infection or
complications due to gastric band procedures when reported with a
procedure describing revision of or removal of extraluminal device in/
from the stomach from MS-DRGs 987, 988, and 989 (Non-Extensive O.R.
Procedure Unrelated to Principal Diagnosis with MCC, with CC and
without MCC/CC, respectively) to MS-DRGs 326, 327, and 328 (Stomach,
Esophageal, and Duodenal Procedures with MCC, with CC, and without CC/
MCC, respectively). ICD-10-CM diagnosis codes K95.01 (Infection due to
gastric band procedure) and K95.09 (Other complications of gastric band
procedure) are used to report these conditions and are currently
assigned to MDC 6 (Diseases and Disorders of the Digestive System).
ICD-10-PCS procedure codes 0DW64CZ (Revision of extraluminal device in
stomach, percutaneous endoscopic approach) and 0DP64CZ (Removal of
extraluminal device from stomach, percutaneous endoscopic approach) are
used to report the revision of, or removal of, an extraluminal device
in/from the stomach and are currently assigned to MDC 10 (Endocrine,
Nutritional and Metabolic Diseases and Disorders) in MS-DRGs 619, 620,
and 621 (O.R. Procedures for Obesity with MCC with CC, and without CC/
MCC, respectively).
Our analysis of this grouping issue confirmed that when procedures
describing the revision of or removal of an extraluminal device in/from
the stomach are reported with principal diagnoses in MDC 6 (such as
ICD-10-CM diagnosis codes K95.01 and K95.09), in the absence of a
procedure assigned to MDC 6, these cases group to MS-DRGs 987, 988, and
989. As noted in the previous discussion, whenever there is a surgical
procedure reported on the claim that is unrelated to the MDC to which
the case was assigned based on the principal diagnosis, it results in
an MS-DRG assignment to a surgical class referred to as ``unrelated
operating room procedures''.
We examined the claims data to identify cases involving ICD-10-PCS
procedure codes 0DW64CZ and 0DP64CZ reported with a principal diagnosis
of K95.01 or K95.09 that are currently grouping to MS-DRGs 987, 988,
and 989. Our findings are shown in the table below.
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 987--All cases........................................... 8,674 11 $23,885
MS-DRG 987--Cases reporting procedure code 0DW64CZ or 0DP64CZ 20 6.6 17,873
and principal diagnosis code K95.01 or K95.09..................
MS-DRG 988--All cases........................................... 8,391 5.7 12,294
MS-DRG 988--Cases reporting procedure code 0DW64CZ or 0DP64CZ 105 2.2 7,253
and principal diagnosis code K95.01 or K95.09..................
MS-DRG 989--All cases........................................... 1,551 3.1 8,171
MS-DRG 989--Cases reporting procedure code 0DW64CZ or 0DP64CZ 120 1.6 6,010
and principal diagnosis code K95.01 or K95.09..................
----------------------------------------------------------------------------------------------------------------
We also examined the data for cases in MS-DRGs 326, 327, and 328,
and our findings are provided in a table presented in section II.12.a.
of the preamble of this proposed rule. While our clinical advisors
noted that the average length of stay and average costs of cases in MS-
DRGs 326, 327, and 328 are significantly higher than the average length
of stay and average costs for the subset of cases reporting procedure
code 0DW64CZ or 0DP64CZ and a principal diagnosis code of K95.01 or
K95.09, they believe that the procedures are clearly related to the
principal diagnosis and, therefore, it is clinically appropriate for
the procedures to group to the same MS-DRGs as the principal
[[Page 19229]]
diagnoses. In addition, our clinical advisors believe that because
these procedures are intended to treat a complication of a procedure
related to obesity, rather than the obesity itself, they are more
appropriately assigned to stomach, esophageal, and duodenal procedures
(MS-DRGs 326, 327, and 328) in MDC 6 than to procedures for obesity
(MS-DRGs 619, 620, and 621) in MDC 10.
Therefore, we are proposing to add ICD-10-PCS procedure codes
0DW64CZ and 0DP64CZ to MDC 6 in MS-DRGs 326, 327, and 328. Under this
proposal, cases reporting procedure code 0DW64CZ or 0DP64CZ in
conjunction with a principal diagnosis code of K95.01 or K95.09 would
group to MS-DRGs 326, 327, and 328.
(7) Peritoneal Dialysis Catheters
We received a request to reassign cases for complications of
peritoneal dialysis catheters when reported with procedure codes
describing removal, revision, and/or insertion of new peritoneal
dialysis catheters from MS-DRGs 981 through 983 to MS-DRGs 356, 357,
and 358 (Other Digestive System O.R. Procedures with MCC, with CC, and
without CC/MCC, respectively) in MDC 6 by adding the diagnosis codes
describing complications of peritoneal dialysis catheters to MDC 6. We
refer readers to section II.12.a. of the preamble of this proposed rule
in which we describe our analysis of this issue as part of our broader
review of the unrelated MS-DRGs. Our clinical advisors believe it is
more appropriate to add the procedure codes describing removal,
revision, and/or insertion of new peritoneal dialysis catheters to MS-
DRGs 907, 908, and 909 than to move the diagnosis codes describing
complications of peritoneal dialysis catheters to MDC 6 because the
diagnosis codes describe complications, rather than initial placement,
of peritoneal dialysis catheters, and therefore, are most clinically
aligned with the diagnosis codes assigned to MDC 21 (where they are
currently assigned). In section II.12.a. of the preamble of this
proposed rule, we are proposing to add procedures describing removal,
revision, and/or insertion of peritoneal dialysis catheters to MS-DRGs
907, 908, and 909 in MDC 21.
(8) Occlusion of Left Renal Vein
We received a request to reassign cases for varicose veins in the
pelvic region when reported with an embolization procedure from MS-DRGs
981, 982 and 983 (Non-Extensive O.R. Procedure Unrelated to Principal
Diagnosis with MCC, with CC, and without CC/MCC, respectively) to MS-
DRGs 715 and 716 (Other Male Reproductive System O.R. Procedures for
Malignancy with CC/MCC and without CC/MCC, respectively) and MS-DRGs
717 and 718 (Other Male Reproductive System O.R. Procedures Except
Malignancy with CC/MCC and without CC/MCC, respectively) in MDC 12
(Diseases and Disorders of the Male Reproductive System) and to MS-DRGs
749 and 750 (Other Female Reproductive System O.R. Procedures with CC/
MCC and without CC/MCC, respectively) in MDC 13 (Diseases and Disorders
of the Female Reproductive System). ICD-10-CM diagnosis code I86.2
(Pelvic varices) is reported to identify the condition of varicose
veins in the pelvic region and is currently assigned to MDC 12 and to
MDC 13. ICD-10-PCS procedure code 06LB3DZ (Occlusion of left renal vein
with intraluminal device, percutaneous approach) may be reported to
describe an embolization procedure performed for the treatment of
pelvic varices and is currently assigned to MDC 5 (Diseases and
Disorders of the Circulatory System) in MS-DRGs 270, 271, and 272
(Other Major Cardiovascular Procedures with MCC, with CC, and without
CC/MCC, respectively), MDC 6 (Diseases and Disorders of the Digestive
System) in MS-DRGs 356, 357, and 358 (Other Digestive System O.R.
Procedures with MCC, with CC, and without CC/MCC, respectively), MDC 21
(Injuries, Poisonings and Toxic Effects of Drugs) in MS-DRGs 907, 908,
and 909 (Other O.R. Procedures for Injuries with MCC, CC, without CC/
MCC, respectively), and MDC 24 (Multiple Significant Trauma) in MS-DRGs
957, 958, 959 (Other O.R. Procedures for Multiple Significant Trauma
with MCC, with CC, and without CC/MCC, respectively). The requestor
also noted that when this procedure is performed on the right renal
vein (which is reported with ICD-10-PCS code 06L03DZ (Occlusion of
inferior vena cava with intraluminal device, percutaneous approach) for
varicose veins in the pelvic region, the case groups to MS-DRGs 715 and
716 and MS-DRGs 717 and 718 in MDC 12 (for male patients) or MS-DRGs
749 and 750 in MDC 13 (for female patients).
Our analysis of this grouping issue confirmed that when ICD-10-CM
diagnosis code I86.2 (Pelvic varices) is reported with ICD-10-PCS
procedure code 06LB3DZ, the case groups to MS-DRGs 981, 982, and 983.
As noted above in previous discussions, whenever there is a surgical
procedure reported on the claim that is unrelated to the MDC to which
the case was assigned based on the principal diagnosis, it results in
an MS-DRG assignment to a surgical class referred to as ``unrelated
operating room procedures.''
We examined the claims data to identify cases involving procedure
code 06LB3DZ in MS-DRGs 981, 982, and 983 reported with a principal
diagnosis code of I86.2. We found no cases in the claims data.
In the absence of data to examine, our clinical advisors reviewed
this request and agree with the requestor that when the embolization
procedure is performed on the left renal vein (reported with ICD-10-PCS
procedure code 06LB3DZ), it should group to the same MS-DRGs as when it
is performed on the right renal vein. Therefore, we are proposing to
add ICD-10-PCS procedure code 06LB3DZ to MDC 12 in MS-DRGs 715, 716,
717, and 718 and to MDC 13 in MS-DRGs 749 and 750. Under this proposal,
cases reporting ICD-10-CM diagnosis code I86.2 with ICD-10-PCS
procedure code 06LB3DZ would group to MDC 12 (for male patients) or MDC
13 (for female patients).
13. Operating Room (O.R.) and Non-O.R. Issues
a. Background
Under the IPPS MS-DRGs (and former CMS MS-DRGs), we have a list of
procedure codes that are considered operating room (O.R.) procedures.
Historically, we developed this list using physician panels that
classified each procedure code based on the procedure and its effect on
consumption of hospital resources. For example, generally the presence
of a surgical procedure which required the use of the operating room
would be expected to have a significant effect on the type of hospital
resources (for example, operating room, recovery room, and anesthesia)
used by a patient, and therefore, these patients were considered
surgical. Because the claims data generally available do not precisely
indicate whether a patient was taken to the operating room, surgical
patients were identified based on the procedures that were performed.
Generally, if the procedure was not expected to require the use of the
operating room, the patient would be considered medical (non-O.R.).
Currently, each ICD-10-PCS procedure code has designations that
determine whether and in what way the presence of that procedure on a
claim impacts the MS-DRG assignment. First, each ICD-10-PCS procedure
code is either designated as an O.R. procedure for purposes of MS-DRG
assignment
[[Page 19230]]
(``O.R. procedures'') or is not designated as an O.R. procedure for
purposes of MS-DRG assignment (``non-O.R. procedures''). Second, for
each procedure that is designated as an O.R. procedure, that O.R.
procedure is further classified as either extensive or non-extensive.
Third, for each procedure that is designated as a non-O.R. procedure,
that non-O.R. procedure is further classified as either affecting the
MS-DRG assignment or not affecting the MS-DRG assignment. We refer to
these designations that do affect MS-DRG assignment as ``non-O.R.
affecting the MS-DRG.'' For new procedure codes that have been
finalized through the ICD-10 Coordination and Maintenance Committee
meeting process and are proposed to be classified as O.R. procedures or
non-O.R. procedures affecting the MS-DRG, our clinical advisors
recommend the MS-DRG assignment which is then made available in
association with the proposed rule (Table 6B.--New Procedure Codes) and
subject to public comment. These proposed assignments are generally
based on the assignment of predecessor codes or the assignment of
similar codes. For example, we generally examine the MS-DRG assignment
for similar procedures, such as the other approaches for that
procedure, to determine the most appropriate MS-DRG assignment for
procedures proposed to be newly designated as O.R. procedures. As
discussed in section II.F.15. of the preamble of this proposed rule, we
are making Table 6B.--New Procedure Codes--FY 2020 available on the CMS
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. We also refer readers to the ICD-
10 MS-DRG Version 36 Definitions Manual at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.html for detailed information regarding
the designation of procedures as O.R. or non-O.R. (affecting the MS-
DRG) in Appendix E--Operating Room Procedures and Procedure Code/MS-DRG
Index.
Given the long period of time that has elapsed since the original
O.R. (extensive and non-extensive) and non-O.R. designations were
established, the incremental changes that have occurred to these O.R.
and non-O.R. procedure code lists, and changes in the way inpatient
care is delivered, we plan to conduct a comprehensive, systematic
review of the ICD-10-PCS procedure codes. This will be a multi-year
project during which we will also review the process for determining
when a procedure is considered an operating room procedure. For
example, we may restructure the current O.R. and non-O.R. designations
for procedures by leveraging the detail that is now available in the
ICD-10 claims data. We refer readers to the discussion regarding the
designation of procedure codes in the FY 2018 IPPS/LTCH PPS final rule
(82 FR 38066) where we stated that the determination of when a
procedure code should be designated as an O.R. procedure has become a
much more complex task. This is, in part, due to the number of various
approaches available in the ICD-10-PCS classification, as well as
changes in medical practice. While we have typically evaluated
procedures on the basis of whether or not they would be performed in an
operating room, we believe that there may be other factors to consider
with regard to resource utilization, particularly with the
implementation of ICD-10. Therefore, we are again soliciting public
comments on what factors or criteria to consider in determining whether
a procedure is designated as an O.R. procedure in the ICD-10-PCS
classification system for future consideration. Commenters should
submit their recommendations to the following email address:
[email protected] by November 1, 2019.
As a result of this planned review and potential restructuring,
procedures that are currently designated as O.R. procedures may no
longer warrant that designation, and conversely, procedures that are
currently designated as non-O.R. procedures may warrant an O.R. type of
designation. We intend to consider the resources used and how a
procedure should affect the MS-DRG assignment. We may also consider the
effect of specific surgical approaches to evaluate whether to subdivide
specific MS-DRGs based on a specific surgical approach. We plan to
utilize our available MedPAR claims data as a basis for this review and
the input of our clinical advisors. As part of this comprehensive
review of the procedure codes, we also intend to evaluate the MS-DRG
assignment of the procedures and the current surgical hierarchy because
both of these factor into the process of refining the ICD-10 MS-DRGs to
better recognize complexity of service and resource utilization.
We will provide more detail on this analysis and the methodology
for conducting this review in future rulemaking. As we continue to
develop our process and methodology, as noted above, we are soliciting
public comments on other factors to consider in our refinement efforts
to recognize and differentiate consumption of resources for the ICD-10
MS-DRGs.
In this proposed rule, we are addressing requests that we received
regarding changing the designation of specific ICD-10-PCS procedure
codes from non-O.R. to O.R. procedures, or changing the designation
from O.R. procedure to non-O.R. procedure. Below we discuss the process
that was utilized for evaluating the requests that were received for FY
2020 consideration. For each procedure, our clinical advisors
considered:
Whether the procedure would typically require the
resources of an operating room;
Whether it is an extensive or a nonextensive procedure;
and
To which MS-DRGs the procedure should be assigned.
We note that many MS-DRGs require the presence of any O.R.
procedure. As a result, cases with a principal diagnosis associated
with a particular MS-DRG would, by default, be grouped to that MS-DRG.
Therefore, we do not list these MS-DRGs in our discussion below.
Instead, we only discuss MS-DRGs that require explicitly adding the
relevant procedures codes to the GROUPER logic in order for those
procedure codes to affect the MS-DRG assignment as intended. In cases
where we are proposing to change the designation of procedure codes
from non-O.R. procedures to O.R. procedures, we also are proposing one
or more MS-DRGs with which these procedures are clinically aligned and
to which the procedure code would be assigned.
In addition, cases that contain O.R. procedures will map to MS-DRG
981, 982, or 983 (Extensive O.R. Procedure Unrelated to Principal
Diagnosis with MCC, with CC, and without CC/MCC, respectively) or MS-
DRG 987, 988, or 989 (Non-Extensive O.R. Procedure Unrelated to
Principal Diagnosis with MCC, with CC, and without CC/MCC,
respectively) when they do not contain a principal diagnosis that
corresponds to one of the MDCs to which that procedure is assigned.
These procedures need not be assigned to MS-DRGs 981 through 989 in
order for this to occur. Therefore, if requestors included some or all
of MS-DRGs 981 through 989 in their request or included MS-DRGs that
require the presence of any O.R. procedure, we did not specifically
address that aspect in summarizing their request or our response to the
request in the section below.
For procedures that would not typically require the resources of an
operating room, our clinical advisors
[[Page 19231]]
determined if the procedure should affect the MS-DRG assignment.
We received several requests to change the designation of specific
ICD-10-PCS procedure codes from non-O.R. procedures to O.R. procedures,
or to change the designation from O.R. procedures to non-O.R.
procedures. Below we detail and respond to some of those requests. With
regard to the remaining requests, our clinical advisors believe it is
appropriate to consider these requests as part of our comprehensive
review of the procedure codes discussed above.
b. O.R. Procedures to Non-O.R. Procedures
(1) Bronchoalveolar Lavage
Bronchoalveolar lavage (BAL) is a diagnostic procedure in which a
bronchoscope is passed through the patient's mouth or nose into the
lungs. A small amount of fluid is squirted into an area of the lung and
then collected for examination. Two requestors identified 13 ICD-10-PCS
procedure codes describing BAL procedures that generally can be
performed at bedside and would not require the resources of an
operating room. In the ICD-10 MS-DRG Version 36 Definitions Manual,
these 13 ICD-10-PCS procedure codes are currently recognized as O.R.
procedures for purposes of MS-DRG assignment.
We agree with the requestors that these procedures do not typically
require the resources of an operating room. Therefore, we are proposing
to remove the following 13 procedure codes from the FY 2020 ICD-10 MS-
DRGs Version 37 Definitions Manual in Appendix E--Operating Room
Procedures and Procedure Code/MS-DRG Index as O.R. procedures. Under
this proposal, these procedures would no longer impact MS-DRG
assignment.
------------------------------------------------------------------------
ICD-10-PCS code Code description
------------------------------------------------------------------------
0B9H8ZX................... Drainage of lung lingula, via natural or
artificial opening endoscopic, diagnostic.
0B9K8ZX................... Drainage of right lung, via natural or
artificial opening endoscopic, diagnostic.
0B9L8ZX................... Drainage of left lung, via natural or
artificial opening endoscopic, diagnostic.
0B9M8ZX................... Drainage of bilateral lungs, via natural or
artificial opening endoscopic, diagnostic.
0B9C8ZZ................... Drainage of right upper lung lobe, via
natural or artificial opening endoscopic.
0B9D8ZZ................... Drainage of right middle lung lobe, via
natural or artificial opening endoscopic.
0B9F8ZZ................... Drainage of right lower lung lobe, via
natural or artificial opening endoscopic.
0B9G8ZZ................... Drainage of left upper lung lobe, via
natural or artificial opening endoscopic.
0B9H8ZZ................... Drainage of Lung Lingula, via natural or
artificial opening endoscopic.
0B9J8ZZ................... Drainage of left lower lung lobe, via
natural or artificial opening endoscopic.
0B9K8ZZ................... Drainage of right lung, via natural or
artificial opening endoscopic.
0B9L8ZZ................... Drainage of left lung, via natural or
artificial opening endoscopic.
0B9M8ZZ................... Drainage of bilateral lungs, via natural or
artificial opening endoscopic.
------------------------------------------------------------------------
(2) Percutaneous Drainage of Pelvic Cavity
One requestor identified two ICD-10-PCS procedure codes that
describe procedures involving percutaneous drainage of the pelvic
cavity. The two ICD-10-PCS procedure codes are: 0W9J3ZX (Drainage of
pelvic cavity, percutaneous approach, diagnostic) and 0W9J3ZZ (Drainage
of pelvic cavity, percutaneous approach).
ICD-10-PCS procedure code 0W9J3ZX is currently recognized as an
O.R. procedure for purposes of MS-DRG assignment, while the
nondiagnostic ICD-10-PCS procedure code 0W9J3ZZ is not recognized as an
O.R. procedure for purposes of MS-DRG assignment. The requestor stated
that percutaneous drainage procedures of the pelvic cavity for both
diagnostic and nondiagnostic purposes are not complex procedures and
both types of procedures are usually performed in a radiology suite.
The requestor stated that both procedures should be classified as non-
O.R. procedures.
We agree with the requestor that these procedures do not typically
require the resources of an operating room. Therefore, we are proposing
to remove procedure code 0W9J3ZX from the FY 2020 ICD-10 MS-DRG Version
37 Definitions Manual in Appendix E--Operating Room Procedures and
Procedure Code/MS-DRG Index as an O.R. procedure. Under this proposal,
this procedure would no longer impact MS-DRG assignment.
(3) Percutaneous Removal of Drainage Device
One requestor identified two ICD-10-PCS procedure codes that
describe procedures involving the percutaneous placement and removal of
drainage devices from the pancreas. These two ICD-10-PCS procedure
codes are: 0FPG30Z (Removal of drainage device from pancreas,
percutaneous approach) and 0F9G30Z (Drainage of pancreas with drainage
device, percutaneous approach). ICD-10-PCS procedure code 0FPG30Z is
currently recognized as an O.R. procedure for purposes of MS-DRG
assignment, while ICD-10-PCS procedure code 0F9G30Z is not recognized
as an O.R. procedure for purposes of MS-DRG assignment. The requestor
stated that percutaneous placement of drains is typically performed in
a radiology suite under image guidance and removal of a drain would not
be more resource intensive than its placement.
We agree with the requestor that these procedures do not typically
require the resources of an operating room. Therefore, we are proposing
to remove ICD-10-PCS procedure code 0FPG30Z from the FY 2020 ICD-10 MS-
DRG Version 37 Definitions Manual in Appendix E--Operating Room
Procedures and Procedure Code/MS-DRG Index as an O.R. procedure. Under
this proposal, this procedure would no longer impact MS-DRG assignment.
c. Non-O.R. Procedures to O.R. Procedures
(1) Percutaneous Occlusion of Gastric Artery
One requestor identified two ICD-10-PCS procedure codes that
describe percutaneous occlusion and restriction of the gastric artery
with intraluminal device, ICD-10-PCS procedure codes 04L23DZ (Occlusion
of gastric artery with intraluminal device, percutaneous approach) and
04V23DZ (Restriction of gastric artery with intraluminal device,
percutaneous approach), that the requestor stated are currently not
recognized as O.R. procedures for purposes of MS-DRG assignment. The
requestor noted that transcatheter endovascular embolization of the
gastric artery with intraluminal devices uses comparable resources to
transcatheter endovascular embolization of the gastroduodenal artery.
The requestor stated that ICD-10-PCS procedure codes 04L33DZ (Occlusion
of hepatic
[[Page 19232]]
artery with intraluminal device, percutaneous approach) and 04V33DZ
(Restriction of hepatic artery with intraluminal device, percutaneous
approach) are recognized as O.R. procedures for purposes of MS-DRG
assignment, and ICD-10-PCS procedure codes 04L23DZ and 04V23DZ should
therefore also be recognized as O.R. procedures for purposes of MS-DRG
assignment. We note that, contrary to the requestor's statement, ICD-
10-PCS procedure code 04V23DZ is already recognized as an O.R.
procedure for purposes of MS-DRG assignment.
We agree with the requestor that ICD-10-PCS procedure code 04L23DZ
typically requires the resources of an operating room. Therefore, we
are proposing to add this code to the FY 2020 ICD-10 MS-DRG Version 37
Definitions Manual in Appendix E--Operating Room Procedures and
Procedure Code/MS-DRG Index as an O.R. procedure assigned to MS-DRGs
270, 271, and 272 (Other Major Cardiovascular Procedures with MCC, CC,
without CC/MCC, respectively) in MDC 05 (Diseases and Disorders of the
Circulatory System); MS-DRGs 356, 357, and 358 (Other Digestive System
O.R. Procedures, with MCC, CC, without CC/MCC, respectively) in MDC 06
(Diseases and Disorders of the Digestive System); MS-DRGs 907, 908, and
909 (Other O.R. Procedures for Injuries with MCC, CC, without CC/MCC,
respectively) in MDC 21 (Injuries, Poisonings and Toxic Effects of
Drugs); and MS-DRGs 957, 958, and 959 (Other O.R. Procedures for
Multiple Significant Trauma with MCC, CC, without CC/MCC, respectively)
in MDC 24 (Multiple Significant Trauma).
(2) Endoscopic Insertion of Endobronchial Valves
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41257), we discussed
a comment we received in response to the FY 2019 IPPS/LTCH PPS proposed
rule regarding eight ICD-10-PCS procedure codes that describe
endobronchial valve procedures that the commenter believed should be
designated as O.R. procedures. The codes are identified in the
following table.
------------------------------------------------------------------------
ICD-10-PCS code Code description
------------------------------------------------------------------------
0BH38GZ................... Insertion of endobronchial valve into right
main bronchus, via natural or artificial
opening endoscopic.
0BH48GZ................... Insertion of endobronchial valve into right
upper lobe bronchus, via natural or
artificial opening endoscopic.
0BH58GZ................... Insertion of endobronchial valve into right
middle lobe bronchus, via natural or
artificial opening endoscopic.
0BH68GZ................... Insertion of endobronchial valve into right
lower lobe bronchus, via natural or
artificial opening endoscopic.
0BH78GZ................... Insertion of endobronchial valve into left
main bronchus, via natural or artificial
opening endoscopic.
0BH88GZ................... Insertion of endobronchial valve into left
upper lobe bronchus, via natural or
artificial opening endoscopic.
0BH98GZ................... Insertion of endobronchial valve into
lingula bronchus, via natural or artificial
opening endoscopic.
0BHB8GZ................... Insertion of endobronchial valve into left
lower lobe bronchus, via natural or
artificial opening endoscopic.
------------------------------------------------------------------------
The commenter stated that these procedures are most commonly
performed in the O.R., given the need for better monitoring and support
through the process of identifying and occluding a prolonged air leak
using endobronchial valve technology. The commenter also noted that
other endobronchial valve procedures have an O.R. designation. We noted
that, in the ICD-10 MS-DRGs Version 35, these eight ICD-10-PCS
procedure codes are not recognized as O.R. procedures for purposes of
MS-DRG assignment. The commenter requested that these eight procedure
codes be assigned to MS-DRG 163 (Major Chest Procedures with MCC) due
to similar cost and resource use. As discussed in the FY 2019 IPPS/LTCH
PPS final rule, our clinical advisors disagreed with the commenter that
the eight identified procedures typically require the use of an
operating room, and believed that these procedures would typically be
performed in an endoscopy suite. Therefore, we did not finalize a
change to the eight procedure codes describing endoscopic insertion of
an endobronchial valve listed in the table above for FY 2019 under the
ICD-10 MS-DRGs Version 36.
After publication of the FY 2019 IPPS/LTCH PPS final rule, we
received feedback from several stakeholders expressing continued
concern with the designation of the eight ICD-10-PCS procedure codes
describing the endoscopic insertion of an endobronchial valve listed in
the table above, including requests to reconsider the designation of
these codes for FY 2020. Some requestors stated that while they
appreciated CMS' attention to the issue, they believed that important
clinical and financial factors had been overlooked. The requestors
noted that while the site of care is an important consideration for MS-
DRG assignment, there are other clinical factors such as case
complexity, patient health risk and the need for anesthesia that also
affect hospital resource consumption and should influence MS-DRG
assignment. With regard to complexity, the requestors stated that many
of these patients are high-risk, often recovering from major lung
surgery and have significantly compromised respiratory function.
According to one requestor, these patients may have major
comorbidities, such as cancer or emphysema contributing to longer
lengths of stay in the hospital. This requestor acknowledged that
procedures performed for the endoscopic insertion of an endobronchial
valve are often, but not always, performed in the O.R., however, the
requestor also noted this should not preclude the designation of these
procedures as O.R. procedures since there have been other examples of
reclassification requests where the combination of factors, such as
treatment difficulty, resource utilization, patient health status, and
anesthesia administration were considered in the decision to change the
designation for a procedure from non-O.R. to O.R. Another requestor
stated that CMS' current designation of a procedure involving the
endoscopic insertion of an endobronchial valve as a non-O.R. procedure
is not reflective of actual practice and this designation has payment
consequences that may affect access to the treatment for a vulnerable
patient population, with limited treatment options. The requestor
recommended that procedures involving the endoscopic insertion of an
endobronchial valve should be designated as O.R. procedures and
assigned to MS-DRGs 163, 164, and 165 (Major Chest Procedures with MCC,
with CC and without CC/MCC, respectively). In addition, a few of the
requestors also conducted their own analyses and indicated that if
procedures involving the endoscopic insertion of an endobronchial valve
were to be assigned to MS-DRGs 163, 164, and 165, the average costs of
the cases reporting a procedure code describing the endoscopic
insertion of an endobronchial valve would still be higher compared to
all the cases in the assigned MS-DRG.
We examined claims data from the September 2018 update of the FY
2018 MedPAR file for MS-DRGs 163, 164 and
[[Page 19233]]
165 to identify cases reporting any one of the eight procedure codes
listed in the above table describing the endoscopic insertion of an
endobronchial valve. Cases reporting one of these procedure codes would
be assigned to MS-DRG 163, 164, or 165 if at least one other procedure
that is designated as an O.R. procedure and assigned to these MS-DRGs
was also reported on the claim. In addition, cases reporting a
procedure code describing the endoscopic insertion of an endobronchial
valve with a different surgical approach are assigned to MS-DRGs 163,
164, and 165. Our findings are shown in the following table.
MS-DRGs for Major Chest Procedures With Endoscopic Insertion of Endobronchial Valve Procedures
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 163--All cases........................................... 10,812 11.6 $33,433
MS-DRG 163--Cases reporting a procedure for the endoscopic 49 21.1 53,641
insertion of an endobronchial valve............................
MS-DRG 164--All cases........................................... 14,800 5.6 18,202
MS-DRG 164--Cases reporting a procedure for the endoscopic 23 14 37,287
insertion of an endobronchial valve............................
MS-DRG 165--All cases........................................... 7,907 3.3 13,408
MS-DRG 165--Cases reporting a procedure for the endoscopic 3 18.3 39,249
insertion of an endobronchial valve............................
----------------------------------------------------------------------------------------------------------------
We found a total of 10,812 cases in MS-DRG 163 with an average
length of stay of 11.6 days and average costs of $33,433. Of those
10,812 cases, we found 49 cases reporting a procedure for the
endoscopic insertion of an endobronchial valve with an average length
of stay of 21.1 days and average costs of $53,641. For MS-DRG 164, we
found a total of 14,800 cases with an average length of stay of 5.6
days and average costs of $18,202. Of those 14,800 cases, we found 23
cases reporting a procedure for the endoscopic insertion of an
endobronchial valve with an average length of stay of 14 days and
average costs of $37,287. For MS-DRG 165, we found a total of 7,907
cases with an average length of stay of 3.3 days and average costs of
$13,408. Of those 7,907 cases, we found 3 cases reporting a procedure
for the endoscopic insertion of an endobronchial valve with an average
length of stay of 18.3 days and average costs of $39,249.
We also examined claims data to identify any cases reporting any
one of the eight procedure codes listed in the table above describing
the endoscopic insertion of an endobronchial valve within MS-DRGs 166,
167, and 168 (Other Respiratory System O.R. Procedures with MCC, with
CC, and without CC/MCC, respectively). Cases reporting one of these
procedure codes would be assigned to MS-DRG 166, 167, or 168 if at
least one other procedure that is designated as an O.R. procedure and
assigned to these MS-DRGs was also reported on the claim. In addition,
MS-DRGs 166, 167, and 168 are the other surgical MS-DRGs where cases
reporting a respiratory diagnosis within MDC 4 would be assigned. Our
findings are shown in the following table.
MS-DRGs for Other Respiratory System O.R. Procedures With Endoscopic Insertion of Endobronchial Valve
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 166--All cases........................................... 16,050 10.6 $26,645
MS-DRG 166--Cases reporting a procedure for the endoscopic 11 25.7 71,700
insertion of an endobronchial valve............................
MS-DRG 167--All cases........................................... 8,165 5.3 13,687
MS-DRG 167--Cases reporting a procedure for the endoscopic 4 10 28,847
insertion of an endobronchial valve............................
MS-DRG 168--All cases........................................... 2,430 2.8 9,645
----------------------------------------------------------------------------------------------------------------
We found a total of 16,050 cases in MS-DRG 166 with an average
length of stay of 10.6 days and average costs of $26,645. Of those
16,050 cases, we found 11 cases reporting a procedure for the
endoscopic insertion of an endobronchial valve with an average length
of stay of 25.7 days and average costs of $71,700. For MS-DRG 167, we
found a total of 8,165 cases with an average length of stay of 5.3 days
and average costs of $13,687. Of those 8,165 cases, we found 4 cases
reporting a procedure for the endoscopic insertion of an endobronchial
valve with an average length of stay of 10 days and average costs of
$28,847. For MS-DRG 168, we found a total of 2,430 cases with an
average length of stay of 2.8 days and average costs of $9,645. Of
those 2,430 cases, we did not find any cases reporting a procedure for
the endoscopic insertion of an endobronchial valve.
The results of our data analysis indicate that cases reporting a
procedure for the endoscopic insertion of an endobronchial valve in MS-
DRGs 163, 164, 165, 166, and 167 have a longer length of stay and
higher average costs when compared to all the cases in their assigned
MS-DRG. Because the data are based on surgical MS-DRGs 163, 164, 165,
166 and 167, and the procedure codes for endoscopic insertion of an
endobronchial valve are currently designated as non-O.R. procedures,
there was at least one other O.R. procedure reported on the claim
resulting in case assignment to one of those MS-DRGs. Our clinical
advisors indicated that because there was another O.R. procedure
reported, the insertion of the endobronchial valve procedure may or may
not have been
[[Page 19234]]
the main determinant of resource use for those cases. Therefore, we
conducted further analysis to evaluate cases for which no other O.R.
procedure was performed with the endoscopic insertion of an
endobronchial valve and case assignment resulted in a medical MS-DRG.
Our findings are shown in the following table.
Medical MS-DRGs With Insertion of Endobronchial Valve Procedures
----------------------------------------------------------------------------------------------------------------
Number of Average length
MS-DRG cases of stay Average costs
----------------------------------------------------------------------------------------------------------------
MS-DRG 069 (Transient Ischemia without Thrombolytic)............ 1 9 $26,002
MS-DRG 177 (Respiratory Infections and Inflammations with MCC).. 11 19.5 33,877
MS-DRG 178 (Respiratory Infections and Inflammations with CC)... 4 10.8 20,109
MS-DRG 180 (Respiratory Neoplasms with MCC)..................... 2 11.5 19,273
MS-DRG 181 (Respiratory Neoplasms with MCC)..................... 1 3 12,641
MS-DRG 186 (Pleural Effusion with MCC).......................... 1 8 23,609
MS-DRG 187 (Pleural Effusion with CC)........................... 1 18 49,214
MS-DRG 189 (Pulmonary Edema and Respiratory Failure)............ 2 13.5 65,431
MS-DRG 190 (Chronic Obstructive Pulmonary Disease with MCC)..... 2 9 39,925
MS-DRG 191 (Chronic Obstructive Pulmonary Disease with CC)...... 1 15 55,958
MS-DRG 192 (Chronic Obstructive Pulmonary Disease without CC/ 1 5 10,394
MCC)...........................................................
MS-DRG 193 (Simple Pneumonia and Pleurisy with MCC)............. 1 18 27,182
MS-DRG 197 (Interstitial Lung Disease with CC).................. 1 12 11,458
MS-DRG 199 (Pneumothorax with MCC).............................. 28 16.4 38,384
MS-DRG 200 (Pneumothorax with CC)............................... 11 8.3 20,764
MS-DRG 201 (Pneumothorax without CC/MCC)........................ 2 10 20,243
MS-DRG 205 (Other Respiratory System Diagnoses with MCC)........ 2 4.5 10,851
MS-DRG 207 (Respiratory System Diagnosis with Ventilation 4 20 67,299
Support >96 Hours or Peripheral Extracorporeal Membrane
Oxygenation (ECMO))............................................
MS-DRG 208 (Respiratory System Diagnosis with Ventilation 8 13.6 32,533
Support [lE]96 Hours or Peripheral Extracorporeal Membrane
Oxygenation (ECMO))............................................
MS-DRG 815 (Reticuloendothelial and Immunity Disorders with CC). 1 5 17,379
MS-DRG 871 (Septicemia or Severe Sepsis without Mechanical 3 15 39,706
Ventilation >96 Hours with MCC)................................
MS-DRG 919 (Complications of Treatment with MCC)................ 2 5 36,143
MS-DRG 920 (Complications of Treatment with CC)................. 1 5 14,923
-----------------------------------------------
Total....................................................... 91 13.7 33,377
----------------------------------------------------------------------------------------------------------------
The data indicate that there is a wide variation in the average
length of stay and average costs for cases reporting a procedure for
the endoscopic insertion of an endobronchial valve, with volume
generally low across MS-DRGs. As shown in the table, for several of the
medical MS-DRGs, there was only one case reporting a procedure for the
endoscopic insertion of an endobronchial valve. The highest volume of
cases reporting a procedure for the endoscopic insertion of an
endobronchial valve was found in MS-DRG 199 (Pneumothorax with MCC)
with a total of 28 cases with an average length of stay of 16.4 days
and average costs of $38,384. The highest average costs and longest
average length of stay for cases reporting a procedure for the
endoscopic insertion of an endobronchial valve was $67,299 in MS-DRG
207 (Respiratory System Diagnosis with Ventilator Support >96 Hours or
Peripheral Extracorporeal Membrane Oxygenation (ECMO)) where 4 cases
were found with an average length of stay of 20 days. Overall, there
was a total of 91 cases reporting the insertion of an endobronchial
valve procedure with an average length of stay of 13.7 days and average
costs of $33,377 across the medical MS-DRGs.
Our clinical advisors agree that the subset of patients who undergo
endoscopic insertion of an endobronchial procedure are complex and may
have multiple comorbidities such as severe underlying lung disease that
impact the hospital length of stay. They also believe that, as we begin
the process of refining how procedure codes may be classified under
ICD-10-PCS, including designation of a procedure as O.R. or non-O.R.,
we should take into consideration whether the procedure is driving
resource use for the admission. (We refer the reader to section
II.F.13.a. of the preamble of this proposed rule for the discussion of
our plans to conduct a comprehensive review of the ICD-10-PCS procedure
codes). Based on the claims data analysis, which show a wide variation
in average costs for cases reporting endoscopic insertion of an
endobronchial valve without an O.R. procedure, our clinical advisors
are not convinced that endoscopic insertion of an endobronchial valve
is a key contributing factor to the consumption of resources as
reflected in the data. They also believe, in review of the procedures
that are currently assigned to MS-DRGs 163, 164, 165, 166, 167, and
168, that further refinement of these MS-DRGs may be warranted. For
these reasons, at this time, our clinical advisors do not support
designating endoscopic insertion of an endobronchial valve as an O.R.
procedure, nor do they support assignment of these procedures to MS-
DRGs 163, 164, and 165 until additional analyses can be performed for
this subset of patients as part of the comprehensive procedure code
review.
For the reasons described above, we are not proposing to change the
current non-O.R. designation of the eight ICD-10-PCS procedure codes
that describe endoscopic insertion of an endobronchial valve. However,
because we agree that endoscopic insertion of an endobronchial valve
procedures are performed on clinically complex patients, we believe it
may be appropriate to consider designating these procedures as non-O.R.
affecting specific MS-DRGs for FY 2020. Therefore, we are requesting
public comment on designating these procedure codes as non-O.R.
procedures affecting the MS-DRG assignment, including the specific MS-
DRGs that cases reporting the endoscopic insertion
[[Page 19235]]
of an endobronchial valve should affect for FY 2020. As noted, it is
not clear based on the claims data to what degree the endoscopic
insertion of an endobronchial valve is a contributing factor for the
consumption of resources for these clinically complex patients and
given the potential refinement that may be needed for MS-DRGs 163, 164,
165, 166, 167, and 168, we are soliciting comment on whether cases
reporting the endoscopic insertion of an endobronchial valve should
affect any of these MS-DRGs or other MS-DRGs.
14. Proposed Changes to the MS-DRG Diagnosis Codes for FY 2020
a. Background of the CC List and the CC Exclusions List
Under the IPPS MS-DRG classification system, we have developed a
standard list of diagnoses that are considered CCs. Historically, we
developed this list using physician panels that classified each
diagnosis code based on whether the diagnosis, when present as a
secondary condition, would be considered a substantial complication or
comorbidity. A substantial complication or comorbidity was defined as a
condition that, because of its presence with a specific principal
diagnosis, would cause an increase in the length-of-stay by at least 1
day in at least 75 percent of the patients. However, depending on the
principal diagnosis of the patient, some diagnoses on the basic list of
complications and comorbidities may be excluded if they are closely
related to the principal diagnosis. In FY 2008, we evaluated each
diagnosis code to determine its impact on resource use and to determine
the most appropriate CC subclassification (non-CC, CC, or MCC)
assignment. We refer readers to sections II.D.2. and 3. of the preamble
of the FY 2008 IPPS final rule with comment period for a discussion of
the refinement of CCs in relation to the MS-DRGs we adopted for FY 2008
(72 FR 47152 through 47171).
b. Overview of Comprehensive CC/MCC Analysis
In the FY 2008 IPPS/LTCH PPS final rule (72 FR 47159), we described
our process for establishing three different levels of CC severity into
which we would subdivide the diagnosis codes. The categorization of
diagnoses as an MCC, a CC, or a non-CC was accomplished using an
iterative approach in which each diagnosis was evaluated to determine
the extent to which its presence as a secondary diagnosis resulted in
increased hospital resource use. We refer readers to the FY 2008 IPPS/
LTCH PPS final rule (72 FR 47159) for a complete discussion of our
approach. Since this comprehensive analysis was completed for FY 2008,
we have evaluated diagnosis codes individually when receiving requests
to change the severity level of specific diagnosis codes. However,
given the transition to ICD-10-CM and the significant changes that have
occurred to diagnosis codes since this review, we believe it is
necessary to conduct a comprehensive analysis once again. We have
completed this analysis and we are discussing our findings in this
proposed rule. We used the same methodology utilized in FY 2008 to
conduct this analysis, as described below.
For each secondary diagnosis, we measured the impact in resource
use for the following three subsets of patients:
(1) Patients with no other secondary diagnosis or with all other
secondary diagnoses that are non-CCs.
(2) Patients with at least one other secondary diagnosis that is a
CC but none that is an MCC.
(3) Patients with at least one other secondary diagnosis that is an
MCC.
Numerical resource impact values were assigned for each diagnosis
as follows:
------------------------------------------------------------------------
Value Meaning
------------------------------------------------------------------------
0................................ Significantly below expected value
for the non-CC subgroup.
1................................ Approximately equal to expected value
for the non-CC subgroup.
2................................ Approximately equal to expected value
for the CC subgroup.
3................................ Approximately equal to expected value
for the MCC subgroup.
4................................ Significantly above the expected
value for the MCC subgroup.
------------------------------------------------------------------------
Each diagnosis for which Medicare data were available was evaluated
to determine its impact on resource use and to determine the most
appropriate CC subclass (non-CC, CC, or MCC) assignment. In order to
make this determination, the average cost for each subset of cases was
compared to the expected cost for cases in that subset. The following
format was used to evaluate each diagnosis:
--------------------------------------------------------------------------------------------------------------------------------------------------------
--------------------------------------------------------------------------------------------------------------------------------------------------------
Code Diagnosis Cnt1 C1 Cnt2 C2 Cnt3 C3
--------------------------------------------------------------------------------------------------------------------------------------------------------
Count (Cnt) is the number of patients in each subset and C1, C2,
and C3 are a measure of the impact on resource use of patients in each
of the subsets. The C1, C2, and C3 values are a measure of the ratio of
average costs for patients with these conditions to the expected
average cost across all cases. The C1 value reflects a patient with no
other secondary diagnosis or with all other secondary diagnoses that
are non-CCs. The C2 value reflects a patient with at least one other
secondary diagnosis that is a CC but none that is a major CC. The C3
value reflects a patient with at least one other secondary diagnosis
that is a major CC. A value close to 1.0 in the C1 field would suggest
that the code produces the same expected value as a non-CC diagnosis.
That is, average costs for the case are similar to the expected average
costs for that subset and the diagnosis is not expected to increase
resource usage. A higher value in the C1 (or C2 and C3) field suggests
more resource usage is associated with the diagnosis and an increased
likelihood that it is more like a CC or major CC than a non-CC. Thus, a
value close to 2.0 suggests the condition is more like a CC than a non-
CC but not as significant in resource usage as an MCC. A value close to
3.0 suggests the condition is expected to consume resources more
similar to an MCC than a CC or non-CC. For example, a C1 value of 1.8
for a secondary diagnosis means that for the subset of patients who
have the secondary diagnosis and have either no other secondary
diagnosis present, or all the other secondary diagnoses present are
non-CCs, the impact on resource use of the secondary diagnoses is
greater than the expected value for a non-CC by an amount equal to 80
percent of the difference between the expected value of a CC and a non-
CC (that is, the impact on resource use of the secondary diagnosis is
closer to a CC than a non-CC).
These mathematical constructs are used as guides in conjunction
with the judgment of our clinical advisors to classify each secondary
diagnosis reviewed as an MCC, a CC, or a non-CC. Our clinical advisors
reviewed the resource use impact reports and suggested modifications to
the initial CC subclass assignments when clinically appropriate.
c. Proposed Changes to Severity Levels
(1) Summary of Proposed Changes
The diagnosis codes for which we are proposing a change in severity
level designation as a result of the analysis
[[Page 19236]]
described in this proposed rule are shown in Table 6P.1c. (which is
available via the internet on the CMS website at: http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html). Using the method described above to
perform our comprehensive CC/MCC analysis, our clinical advisors
recommended a change in the severity level designation for 1,492 ICD-
10-CM diagnosis codes. As shown in Table 6P.1c. associated with this
proposed rule, the proposed changes to severity level resulting from
our comprehensive analysis would move some diagnosis codes to a higher
severity level designation and other diagnosis codes to a lower
severity level designation, as indicated in the two columns which
display CMS' FY 2019 classification in column C and the proposed
changes for FY 2020 in column D.
The table below shows the Version 36 ICD-10 MS-DRG categorization
of diagnosis codes by severity level.
Current Categorization of CC Codes
[Version 36]
------------------------------------------------------------------------
Number of
codes
------------------------------------------------------------------------
MCC..................................................... 3,244
CC...................................................... 14,528
Non-CC.................................................. 54,160
---------------
Total............................................... 71,932
------------------------------------------------------------------------
The following table compares the Version 36 ICD-10 MS-DRG CC list
and the proposed Version 37 ICD-10 MS-DRG CC list. There are 17,772
diagnosis codes on the Version 36 MCC/CC lists. The proposed MCC/CC
severity level changes would reduce the number of diagnosis codes on
the MCC/CC lists to 16,790 (3,099 + 13,691). Based on the Version 36
MCC/CC lists, 81.5 percent of cases have at least one MCC/CC present,
using claims data from the September 2018 update of the FY 2018 MedPAR
file. Based on the proposed Version 37 MCC/CC lists, the percent of
cases having at least one MCC/CC present would be reduced to 76.6
percent.
Comparison of Current CC List and Proposed CC List
------------------------------------------------------------------------
Current CC Proposed CC
List List
------------------------------------------------------------------------
Codes designated as an MCC.............. 3,244 3,099
Percent of cases with one or more MCCs.. 41.0% 36.3%
Average charge of cases with one or more $16,439 $16,490
MCCs...................................
Codes designated as a CC................ 14,528 13,691
Percent of cases with one or more CCs... 40.5% 40.3%
Average charge of cases with one or more $10,332 $10,518
CCs....................................
Codes designated as non-CC.............. 54,160 55,142
Percent of cases with no CC............. 18.5% 23.4%
Average charge of cases with no CCs..... $9,885 $10,166
------------------------------------------------------------------------
Using the method described above to perform our comprehensive
analysis, we are proposing to modify the Version 36 CC subclass
assignments for 2.1 percent of the ICD-10-CM diagnosis codes, as
summarized in the table below.
Proposed MCC/CC Subclass Modifications
--------------------------------------------------------------------------------------------------------------------------------------------------------
Proposed Proposed Proposed
Version 36 Proposed version 37 version 37 Version 37
severity level version 37 change to MCC change to CC change to non-
Severity level--CC subclass number of severity level Percent change subclass, subclass, CC subclass,
codes number of number of number of number of
codes codes codes codes
--------------------------------------------------------------------------------------------------------------------------------------------------------
MCC..................................................... 3,244 3,099 -4.5 N/A 136 17
CC...................................................... 14,528 13,691 -5.8 8 N/A 1,148
Non-CC.................................................. 54,160 55,142 1.8 0 183 N/A
-----------------------------------------------------------------------------------------------
Total............................................... 71,932 71,932 N/A 8 319 1,166
--------------------------------------------------------------------------------------------------------------------------------------------------------
As a result of these proposed changes, of the 71,932 diagnosis
codes included in the analysis, the net result would be a decrease of
145 (3,244-3,099) codes designated as an MCC, a decrease of 837
(14,528-13,691) codes designated as a CC, and an increase of 982
(55,142-54,160) codes designated as a non-CC.
(2) Illustrations of Proposed Severity Level Changes
As noted above, based on our comprehensive CC/MCC analysis as
described previously in this section, we are proposing changes in the
severity level designations for 1,492 ICD-10-CM diagnosis codes, and
the specific proposed changes to severity level designations for those
diagnosis codes are shown in Table 6P.1.c. associated with this
proposed rule (which is available via the internet on the CMS website
at: http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html). Below we provide illustrative examples
of certain categories of codes for which we are proposing changes to
the severity level designations as a result of our comprehensive
analysis. As described above, these proposals are based on review of
the data as well as consideration of the clinical nature of each of the
secondary diagnoses and the severity level of clinically similar
diagnoses. The first set of codes, from the Neoplasms chapter,
encompasses more than half of all proposed severity level changes. The
additional examples are from a variety of body systems and conditions,
and they are illustrative of both proposed increases and proposed
decreases in severity level designation. We note that we are making
available a
[[Page 19237]]
supplementary file containing the data describing the impact on
resource use when reported as a secondary diagnosis for all 1,492 ICD-
10-CM diagnosis codes for which we are proposing a change in
designation via the internet on the CMS website at: http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.
(a) Neoplasms Chapter Codes
Of the total number of ICD-10-CM diagnosis codes for which we are
proposing a change of severity level designation, 767 are from the
Neoplasms chapter of the ICD-10-CM classification (C00-D49) and are
currently designated as a CC. We note that the Neoplasms chapter
contains a total of 1,661 ICD-10-CM diagnosis codes. In Version 36 of
the MS-DRGs, none of the 1,661 neoplasm codes are designated as an MCC,
767 are designated as a CC, and 894 are designated as a non-CC. For all
767 codes currently designated as a CC, our clinical advisors
recommended changing the severity level designation from CC to non-CC.
The following table presents examples of some of the neoplasm codes for
which we are proposing a severity level change to non-CC, and their
impact on resource use when reported as a secondary diagnosis. As noted
previously, the data analysis for the remainder of these neoplasm codes
is included in the supplementary file that we are making available on
the CMS website.
Proposed Severity Level Changes for Neoplasm Codes as Secondary Diagnosis
--------------------------------------------------------------------------------------------------------------------------------------------------------
ICD-10-CM diagnosis code Cnt1 C1 Cnt2 C2 Cnt3 C3 Current CC subclass Proposed CC subclass
--------------------------------------------------------------------------------------------------------------------------------------------------------
C20 (Malignant neoplasm of rectum) 2,960 1.0485 7,561 2.2169 6,492 3.0790 CC...................... Non-CC.
C22.0 (Liver cell carcinoma)...... 1,672 1.2289 9,444 2.0638 12,503 3.0914 CC...................... Non-CC.
C25.0 (Malignant neoplasm of head 1,205 1.1357 3,834 2.1788 6,191 3.0229 CC...................... Non-CC.
of pancreas).
C64.1 (Malignant neoplasm of right 1,512 1.2276 4,463 2.1600 4,593 3.1158 CC...................... Non-CC.
kidney, except renal pelvis).
C64.2 (Malignant neoplasm of left 1,368 1.3407 4,517 2.1947 4,593 3.0947 CC...................... Non-CC.
kidney, except renal pelvis).
C78.01 (Secondary malignant 4,149 1.0417 14,946 2.0888 20,324 3.0043 CC...................... Non-CC.
neoplasm of right lung).
C78.02 (Secondary malignant 3,599 1.0078 13,456 2.0853 18,384 3.0024 CC...................... Non-CC.
neoplasm of left lung).
C79.31 (Secondary malignant 7,164 1.1895 22,989 2.1330 41,387 2.9116 CC...................... Non-CC.
neoplasm of brain).
C79.51 (Secondary malignant 26,095 1.3048 88,022 2.2020 99,670 3.0449 CC...................... Non-CC.
neoplasm of bone).
C90.00 (Multiple myeloma not 9,947 1.1588 34,155 2.2144 33,830 3.1281 CC...................... Non-CC.
having achieved remission).
--------------------------------------------------------------------------------------------------------------------------------------------------------
As described in section II.F.15.b. of the preamble of this proposed
rule, we examined the impact in resource use for three subsets of
patients in order to evaluate the severity level designations for each
secondary diagnosis. In the table above, the C1 values are generally
close to 1, C2 values are generally close to 2, and C3 values are
generally close to 3. As explained in section II.F.15.b. of the
preamble of this proposed rule, these values suggest that when a
neoplasm is reported as a secondary diagnosis, the resources involved
in caring for a patient with this condition are more aligned with a
non-CC severity level than a CC severity level. Our clinical advisors
reviewed these data and believe the resources involved in caring for a
patient with this condition are more aligned with a non-CC severity
level. Our clinical advisors noted that when a neoplasm is reported as
a secondary diagnosis, because it is not the condition that occasioned
the patient's admission to the hospital, it does not significantly
impact resource use. Our clinical advisors noted that if these patients
are admitted for treatment of the neoplasm, the neoplasm is the
principal diagnosis, and other complicating or comorbid conditions
reported as secondary diagnoses would determine the appropriate
severity level designation for each particular case. For example, if a
patient is admitted for resection of malignant neoplasm of the right
kidney, ICD-10-CM diagnosis code C64.1 (Malignant neoplasm of right
kidney, except renal pelvis) is reported as the principal diagnosis,
and any complicating conditions reported as secondary diagnoses during
the hospital stay would determine the appropriate severity level
designation for the case.
(b) Diseases of the Circulatory System Chapter Codes
In the Diseases of the Circulatory System chapter of the ICD-10-CM
diagnosis classification (I00-I99), based on the results of our
comprehensive review, we are proposing to change the severity level
designation for 13 ICD-10-CM diagnosis codes from categories I21 (Acute
myocardial infarction) and I22 (Subsequent ST elevation (STEMI) and
non-ST elevation (NSTEMI) myocardial infarction) from an MCC to a CC.
The following table contains the ICD-10-CM diagnosis codes for
which we are proposing a severity level change, and their impact on
resource use when reported as a secondary diagnosis.
[[Page 19238]]
Proposed Severity Level Changes for Myocardial Infarction Codes as Secondary Diagnosis
--------------------------------------------------------------------------------------------------------------------------------------------------------
ICD-10-CM diagnosis code Cnt1 C1 Cnt2 C2 Cnt3 C3 Current CC subclass Proposed CC subclass
--------------------------------------------------------------------------------------------------------------------------------------------------------
I21.01 (ST elevation (STEMI) 2 1.2010 17 2.9902 38 3.0195 MCC..................... CC.
myocardial infarction involving
left main coronary artery).
I21.02 (ST elevation (STEMI) 149 0.9326 322 1.6565 754 3.3157 MCC..................... CC.
myocardial infarction involving
left anterior descending coronary
artery).
I21.09 (ST elevation (STEMI) 583 1.2201 1,288 2.2225 3,744 3.1094 MCC..................... CC.
myocardial infarction involving
other coronary artery of anterior
wall).
I21.11 (ST elevation (STEMI) 175 1.8486 326 2.0867 581 3.1141 MCC..................... CC.
myocardial infarction involving
right coronary artery).
I21.19 (ST elevation (STEMI) 913 1.5054 1,940 2.2641 4,081 3.1996 MCC..................... CC.
myocardial infarction involving
other coronary artery of inferior
wall).
I21.21 (ST elevation (STEMI) 30 0.9445 56 2.4160 117 2.9965 MCC..................... CC.
myocardial infarction involving
left circumflex coronary artery).
I21.29 (ST elevation (STEMI) 162 1.0143 417 2.2401 1,048 3.3341 MCC..................... CC.
myocardial infarction involving
other sites).
I21.3 (ST elevation (STEMI) 1,271 1.6587 3,876 2.2420 10,168 3.2432 MCC..................... CC.
myocardial infarction of
unspecified site).
I22.0 (Subsequent ST elevation 10 0.9199 74 1.2558 165 2.6794 MCC..................... CC.
(STEMI) myocardial infarction of
anterior wall).
I22.1 (Subsequent ST elevation 4 0.0000 81 1.6022 143 3.3056 MCC..................... CC.
(STEMI) myocardial infarction of
inferior wall).
I22.2 (Subsequent non-ST elevation 94 2.1034 352 2.1291 1,916 3.0157 MCC..................... CC.
(NSTEMI) myocardial infarction).
I22.8 (Subsequent ST elevation 5 2.2963 18 2.0589 53 3.1306 MCC..................... CC.
(STEMI) myocardial infarction of
other sites).
I22.9 (Subsequent ST elevation 27 1.7140 87 1.8737 293 2.9627 MCC..................... CC.
(STEMI) myocardial infarction of
unspecified site).
--------------------------------------------------------------------------------------------------------------------------------------------------------
As shown in the table above, all of these myocardial infarction
codes are currently assigned as MCCs. As explained earlier, values
close to 2.0 in column C1 suggest that the condition is more like a CC
than a non-CC but not as significant in resource usage as an MCC. The
C1 values for the secondary diagnoses with the largest number of cases
in this subset in the table above, ICD-10-CM codes I21.3 and I21.19,
are closer to 2.0 than to 1.0, indicating that these secondary
diagnoses are more aligned with a CC than either a non-CC or an MCC.
Therefore, the data suggest that for patients for whom any of the
myocardial infarction codes listed in the table above is reported as a
secondary diagnosis, the resources involved in their care are not
aligned with those of an MCC. Our clinical advisors reviewed these data
and believe that the resources involved in caring for a patient with
this condition are aligned with a CC. Patients with a secondary
diagnosis of myocardial infarction may require additional diagnostic
imaging, monitoring, medications, and additional interventions, thereby
consuming resources that are consistent with CC status. Our clinical
advisors noted that while, for certain codes, the number of cases shown
in the data may not be sufficient to reliably indicate impact on
resource use as a secondary diagnosis, these codes are clinically
similar to other codes for which the data are sufficient to indicate
impact on resource use. Because our clinical advisors believe that it
is appropriate to ensure consistency across codes describing similar
diagnoses, we are proposing to reassign the severity level for all of
the codes in the table above from an MCC to a CC.
(c) Diseases of the Skin and Subcutaneous Tissue Chapter Codes
In the Diseases of the Skin and Subcutaneous Tissue chapter of the
ICD-10-CM diagnosis classification (L00-L99), based on the results of
our comprehensive review, we are proposing a change to the severity
level for 150 ICD-10-CM diagnosis codes describing pressure ulcers.
Pressure ulcers, which are also known as pressure injuries, involve
damage to the skin and soft tissue. They may result from prolonged
pressure over a bony prominence or result from a medical device. The
ICD-10-CM classification includes 150 diagnosis codes that describe
pressure ulcers across various anatomical regions and across the
various possible stages (stages 1 through 4, unspecified stage, and
unstageable). These codes are listed in Table 6P.1.d. associated with
this proposed rule (which is available via the internet on the CMS
website at: http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html). In the course of our
comprehensive review of the CC/MCC lists, our clinical advisors
reviewed the current categorization of pressure ulcers, which designate
all stage 3 and 4 pressure ulcers as MCCs, while stage 1, stage 2,
unspecified stage,
[[Page 19239]]
and unstageable pressure ulcers are currently designated as non-CCs.
Our clinical advisors reviewed data on the relative contribution to
the overall cost of hospital care for all stages of pressure ulcers
coded as secondary diagnoses, and found (1) that there was little
difference in the cost contribution regardless of stage, and (2) the
cost contributions (cost weights) of all stages supported a designation
of CC rather than MCC (for stage 3 and 4 ulcers), and CC rather than
non-CC (for stages 1, 2, unspecified, and unstageable). Our clinical
advisors noted that the apparent similar contribution of all pressure
ulcer stages can be explained by the fact that pressure ulcers occur in
patients with serious underlying illness, such as stroke, cancer,
dementia, and end-stage cardiac or pulmonary disease that can result in
multiple factors (frailty, immobility, paralysis, malnutrition, and
general debility) that predispose them to pressure ulcers. It is the
serious underlying illness and debilitated state that causes the
pressure ulcer that is the primary driver of resource use. Although a
pressure ulcer at any stage requires care and preventive measures that
make additional contributions to the overall cost of care, our clinical
advisors believe that the fact that the ulcer developed in the first
place is more important than the stage of the ulcer itself in
determining the impact on the costs of hospitalization. The presence of
a pressure ulcer may indicate an increase in resource use, but that
increase is similar regardless of the stage of the ulcer.
The following table contains illustrations of pressure ulcer codes
and their impact on resource use when reported as a secondary
diagnosis. We selected secondary diagnosis codes describing pressure
ulcer of the sacrum as examples because they account for almost half of
all instances of pressure ulcers reported as secondary diagnoses, but
note that the data for the codes describing pressure ulcer of other
body parts generally show a similar pattern. As noted previously, the
data analysis for the remainder of the pressure ulcer codes for which
we are proposing a change in severity level designation is included in
the supplementary file that we are making available on the CMS website.
Proposed Severity Level Changes for Pressure Ulcer Codes as Secondary Diagnosis
--------------------------------------------------------------------------------------------------------------------------------------------------------
ICD-10-CM diagnosis code Cnt1 C1 Cnt2 C2 Cnt3 C3 Current CC subclass Proposed CC subclass
--------------------------------------------------------------------------------------------------------------------------------------------------------
L89.150 (Pressure ulcer of sacral 605 2.003 6,247 2.560 24,047 3.254 Non-CC.................. CC.
region, unstageable).
L89.151 (Pressure ulcer of sacral 2,374 1.691 16,688 2.404 36,428 3.182 Non-CC.................. CC.
region, stage 1).
L89.152 (Pressure ulcer of sacral 4,238 1.737 35,608 2.497 95,832 3.274 Non-CC.................. CC.
region, stage 2).
L89.153 (Pressure ulcer of sacral 1,722 1.832 15,266 2.522 48,414 3.289 MCC..................... CC.
region, stage 3).
L89.154 (Pressure ulcer of sacral 1,237 1.755 14,306 2.438 56,619 3.196 MCC..................... CC.
region, stage 4).
L89.159 (Pressure ulcer of sacral 1,453 1.387 12,466 2.311 35,020 3.176 Non-CC.................. CC.
region, unspecified stage).
--------------------------------------------------------------------------------------------------------------------------------------------------------
As explained previously, a value in column C1 that is close to 2.0
suggests the condition is more like a CC than a non-CC but not as
significant in resource usage as an MCC. Given that the values in
column C1 in the table above are closer to 2.0 than to 1.0, the data
suggest that when pressure ulcers of the sacral region are reported as
a secondary diagnosis, the resources involved in caring for these
patients are more consistent with a CC than either a non-CC or an MCC.
Our clinical advisors reviewed these data and believe that it is
appropriate to ensure consistency across codes involving similar
diagnoses. Therefore, we are proposing to designate as CCs both the 50
ICD-10-CM diagnosis codes that are currently designated as MCCs and the
100 ICD-10-CM diagnosis codes currently designated as non-CCs.
We note that, under the Hospital-Acquired Condition (HAC) payment
provision established by section 5001(c) of the Deficit Reduction Act
(DRA) of 2005, hospitals no longer receive additional payment for cases
in which one of the selected conditions occurred but was not present on
admission (POA). That is, the case is paid as though the condition were
not present. The HAC-POA payment provision is applicable for secondary
diagnosis code reporting only, as the selected conditions are
designated as a CC or an MCC when reported as a secondary diagnosis.
For the DRA HAC-POA payment provision, a payment adjustment is only
applicable if there are no other CC/MCC conditions reported on the
claim. Currently, there are 14 HAC categories subject to the HAC-POA
payment provision, one of which is pressure ulcers. The pressure ulcer
HAC category (HAC 04) specifically includes diagnosis codes describing
a stage 3 or stage 4 pressure ulcer because they are designated as an
MCC, as noted earlier in this section. If the proposed severity level
designations for the pressure ulcer diagnosis codes are finalized, the
100 ICD-10-CM diagnosis codes describing pressure ulcers currently
designated as non-CCs would be subject to the HAC-POA payment provision
as CCs when reported as a secondary diagnosis and not POA, effective
beginning in FY 2020. The diagnosis codes describing a stage 3 or stage
4 pressure ulcer would continue to be subject to the HAC-POA payment
provision as CCs.
In addition, consistent with the proposed changes to the severity
level designation of the pressure ulcer codes, we are proposing to
revise the title of the HAC 04 category from ``Pressure Ulcer--Stages
III & IV'' to ``Pressure Ulcers''. We refer readers to the website at:
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HospitalAcqCond/index.html for additional information regarding the
HAC-POA payment provision under the DRA.
(d) Diseases of the Genitourinary System Chapter Codes
In the Diseases of the Genitourinary System chapter of the ICD-10-
CM diagnosis classification (N00-N99), based on the results of our
comprehensive analysis, we are proposing to change the severity level
designation for eight ICD-10-CM diagnosis codes. For these eight
[[Page 19240]]
diagnosis codes, based on their clinical judgment and for the reasons
described below, our clinical advisors recommended that we increase the
severity level designation from a CC to an MCC for one code, and from a
non-CC to a CC for seven codes. The following table contains the
Diseases of the Genitourinary System chapter codes that describe
conditions for which we are proposing a severity level designation
change, and their impact on resource use when reported as a secondary
diagnosis.
Proposed Severity Level Changes for Genitourinary Codes as Secondary Diagnosis
--------------------------------------------------------------------------------------------------------------------------------------------------------
ICD-10-CM diagnosis code Cnt1 C1 Cnt2 C2 Cnt3 C3 Current CC subclass Proposed CC subclass
--------------------------------------------------------------------------------------------------------------------------------------------------------
N10 (Acute pyelonephritis)........ 5,385 0.9639 20,476 1.9444 26,929 3.0413 Non-CC.................. CC.
N18.4 (Chronic kidney disease, 36,940 1.0919 219,482 2.0679 319,849 3.0840 Non-CC.................. CC.
stage 4 (severe)).
N18.5 (Chronic kidney disease, 1,158 1.0303 30,851 2.0841 34,733 3.1508 Non-CC.................. CC.
stage 5).
N18.6 (End stage renal disease)... 26,276 1.5755 578,587 2.3010 492,710 3.2761 CC...................... MCC.
N30.00 (Acute cystitis without 18,597 1.0576 53,820 1.9409 73,996 2.8976 Non-CC.................. CC.
hematuria).
N30.01 (Acute cystitis with 4,872 0.9503 16,949 1.8514 24,422 2.8070 Non-CC.................. CC.
hematuria).
N41.0 (Acute prostatitis)......... 845 0.9519 3,031 1.8163 2,135 3.0450 Non-CC.................. CC.
N76.4 (Abscess of vulva).......... 368 0.8284 1,276 2.0906 1,049 3.1341 Non-CC.................. CC.
--------------------------------------------------------------------------------------------------------------------------------------------------------
The C1, C2, and C3 values in the table above are generally close to
1.0, 2.0, and 3.0, respectively, which would indicate that these
conditions are more aligned with a non-CC than with either a CC or an
MCC. However, our clinical advisors believe that patients with a
secondary diagnosis of one of the genitourinary conditions in the table
above may consume additional resources, including but not limited to
monitoring for hypertension, diagnostic tests, and balancing
electrolytes. Patients with end-stage renal disease (ICD-10-CM code
N18.6) would typically require dialysis in addition to these resources,
which our clinical advisors believe is more aligned with an MCC.
Therefore, we are proposing to change the severity level designations
for the eight codes as shown in the table above.
e. Injury, Poisoning and Certain Other Consequences of External Causes
Chapter Codes
In subcategory S32.5 (Fracture of pubis) of the ICD-10-CM diagnosis
classification, based on our comprehensive analysis, we are proposing
to change the severity level designation from CC to non-CC for 19 ICD-
10-CM diagnosis codes that specify fractures of the pubic bone. The
following table contains the diagnosis codes for which we are proposing
a severity level designation change, and their impact on resource use
when reported as a secondary diagnosis.
Proposed Severity Level Changes, Pubis Fracture Codes as Secondary Diagnosis
--------------------------------------------------------------------------------------------------------------------------------------------------------
ICD-10-CM diagnosis code Cnt1 C1 Cnt2 C2 Cnt3 C3 Current CC subclass Proposed CC subclass
--------------------------------------------------------------------------------------------------------------------------------------------------------
S32.501A (Unspecified fracture of 393 1.0234 1,171 2.1215 847 3.0423 CC...................... Non-CC.
right pubis, initial encounter
for closed fracture).
S32.501K (Unspecified fracture of 1 1.5125 12 2.1144 2 1.8454 CC...................... Non-CC.
right pubis, subsequent encounter
for fracture with nonunion).
S32.502A (Unspecified fracture of 398 1.3072 1,152 2.0593 914 3.0028 CC...................... Non-CC.
left pubis, initial encounter for
closed fracture).
S32.502K (Unspecified fracture of 3 0.0000 7 2.8723 1 0.7401 CC...................... Non-CC.
left pubis, subsequent encounter
for fracture with nonunion).
S32.509A (Unspecified fracture of 49 1.1075 156 2.1066 154 3.1704 CC...................... Non-CC.
unspecified pubis, initial
encounter for closed fracture).
S32.509K (Unspecified fracture of 0 0.0000 1 3.4022 1 2.1306 CC...................... Non-CC.
unspecified pubis, subsequent
encounter for fracture with
nonunion).
S32.511A (Fracture of superior rim 743 1.1812 2,132 2.1519 1,504 2.8763 CC...................... Non-CC.
of right pubis, initial encounter
for closed fracture).
S32.511K (Fracture of superior rim 2 2.0354 5 0.0000 4 2.3425 CC...................... Non-CC.
of right pubis, subsequent
encounter for fracture with
nonunion).
[[Page 19241]]
S32.512A (Fracture of superior rim 760 1.5738 2,098 2.0828 1,590 2.9020 CC...................... Non-CC.
of left pubis, initial encounter
for closed fracture).
S32.512K (Fracture of superior rim 3 2.1915 3 2.4812 8 4.0000 CC...................... Non-CC.
of left pubis, subsequent
encounter for fracture with
nonunion).
S32.519A (Fracture of superior rim 15 2.6829 53 1.5795 35 2.9052 CC...................... Non-CC.
of unspecified pubis, initial
encounter for closed fracture).
S32.519K (Fracture of superior rim 0 0.000 0 0.000 0 0.000 CC...................... Non-CC.
of unspecified pubis, subsequent
encounter for fracture with
nonunion).
S32.591A (Other specified fracture 2,427 1.2524 6,513 2.0970 4,397 2.9930 CC...................... Non-CC.
of right pubis, initial encounter
for closed fracture).
S32.591K (Other specified fracture 7 2.7706 15 1.9772 5 0.8969 CC...................... Non-CC.
of right pubis, subsequent
encounter for fracture with
nonunion).
S32.592A (Other specified fracture 2,424 1.3691 6,604 2.0921 4,922 2.9428 CC...................... Non-CC.
of left pubis, initial encounter
for closed fracture).
S32.592K (Other specified fracture 4 0.6970 24 2.5574 10 3.0015 CC...................... Non-CC.
of left pubis, subsequent
encounter for fracture with
nonunion).
S32.599A (Other specified fracture 151 1.6748 457 2.0518 394 3.1844 CC...................... Non-CC.
of unspecified pubis, initial
encounter for closed fracture).
S32.599K (Other specified fracture 1 0.0000 0 0.0000 3 1.4709 CC...................... Non-CC.
of unspecified pubis, subsequent
encounter for fracture with
nonunion).
--------------------------------------------------------------------------------------------------------------------------------------------------------
The C1, C2, and C3 values in the table above are generally close to
1.0, 2.0, and 3.0, respectively, particularly for those codes for which
the highest number of cases were reported. This indicates that these
conditions are more aligned with a non-CC than with either a CC or an
MCC. Our clinical advisors reviewed these data, particularly with
respect to ICD-10-CM diagnosis codes S32.591A and S32.592A which
account for the majority of cases in this group, and believe the
resources involved in caring for a patient with these conditions are
more aligned with a non-CC. Our clinical advisors noted that, similar
to the proposed severity level designation changes in the Neoplasms
chapter of the ICD-10-CM diagnosis classification discussed above, if
patients are admitted for treatment of an acute or nonunion fracture of
the pubic bone, the fracture is the principal diagnosis, and other
complicating or comorbid conditions reported as secondary diagnoses
would determine the appropriate severity level for each particular
case. For example, if a patient is admitted for surgical treatment of
the nonunion of a right pubic fracture at the superior rim, ICD-10-CM
diagnosis code S32.511K (Fracture of superior rim of right pubis,
subsequent encounter for fracture with nonunion) is reported as the
principal diagnosis. Because our clinical advisors believe that it is
appropriate to ensure consistency across codes involving similar
diagnoses, we are proposing to reassign the severity level for all of
the codes in the table above from a CC to a non-CC.
In category S72 (Fracture of femur) of the ICD-10-CM
classification, based on our comprehensive analysis, we are proposing
to change the severity level designation from MCC to CC for 35 ICD-10-
CM diagnosis codes specifying fractures of the hip. The following table
contains the Injury, Poisoning and Certain Other Consequences of
External Causes chapter codes for which we are proposing a severity
level change, and their impact on resource use when reported as a
secondary diagnosis.
Proposed Severity Level Changes, Hip Fracture Codes as Secondary Diagnosis
--------------------------------------------------------------------------------------------------------------------------------------------------------
ICD-10-CM diagnosis code Cnt1 C1 Cnt2 C2 Cnt3 C3 Current CC subclass Proposed CC subclass
--------------------------------------------------------------------------------------------------------------------------------------------------------
S72.011A (Unspecified 145 2.1400 464 2.3419 700 2.9623 MCC..................... CC.
intracapsular fracture of right
femur, initial encounter for
closed fracture).
S72.012A (Unspecified 155 2.0099 455 2.2738 754 3.0423 MCC..................... CC.
intracapsular fracture of left
femur, initial encounter for
closed fracture).
[[Page 19242]]
S72.019A (Unspecified 1 0.9364 4 1.0008 10 2.7267 MCC..................... CC.
intracapsular fracture of
unspecified femur, initial
encounter for closed fracture).
S72.111A (Displaced fracture of 266 1.5110 605 2.2983 442 3.1874 MCC..................... CC.
greater trochanter of right
femur, initial encounter for
closed fracture).
S72.112A (Displaced fracture of 249 1.7779 573 2.4626 418 3.0108 MCC..................... CC.
greater trochanter of left femur,
initial encounter for closed
fracture).
S72.113A (Displaced fracture of 11 1.7739 21 2.9650 23 3.5762 MCC..................... CC.
greater trochanter of unspecified
femur, initial encounter for
closed fracture).
S72.114A (Nondisplaced fracture of 112 0.8826 339 2.1640 178 3.1028 MCC..................... CC.
greater trochanter of right
femur, initial encounter for
closed fracture).
S72.115A (Nondisplaced fracture of 118 1.3960 288 2.0607 202 2.8640 MCC..................... CC.
greater trochanter of left femur,
initial encounter for closed
fracture).
S72.116A (Nondisplaced fracture of 3 0.9472 8 1.3030 3 3.4270 MCC..................... CC.
greater trochanter of unspecified
femur, initial encounter for
closed fracture).
S72.121A (Displaced fracture of 22 2.0288 74 3.1110 49 3.1174 MCC..................... CC.
lesser trochanter of right femur,
initial encounter for closed
fracture).
S72.122A (Displaced fracture of 23 1.1648 75 2.9379 40 2.4430 MCC..................... CC.
lesser trochanter of left femur,
initial encounter for closed
fracture).
S72.123A (Displaced fracture of 0 0.0000 2 0.0000 6 2.2881 MCC..................... CC.
lesser trochanter of unspecified
femur, initial encounter for
closed fracture).
S72.124A (Nondisplaced fracture of 4 0.9792 19 2.4244 8 2.7792 MCC..................... CC.
lesser trochanter of right femur,
initial encounter for closed
fracture).
S72.125A (Nondisplaced fracture of 5 0.6759 13 1.2700 7 3.1292 MCC..................... CC.
lesser trochanter of left femur,
initial encounter for closed
fracture).
S72.126A (Nondisplaced fracture of 0 0.0000 0 0.0000 1 1.1159 MCC..................... CC.
lesser trochanter of unspecified
femur, initial encounter for
closed fracture).
S72.131A (Displaced apophyseal 1 3.4327 0 0.0000 2 4.0000 MCC..................... CC.
fracture of right femur, initial
encounter for closed fracture).
S72.132A (Displaced apophyseal 0 0.0000 1 2.6423 0 0.0000 MCC..................... CC.
fracture of left femur, initial
encounter for closed fracture).
S72.134A (Nondisplaced apophyseal 0 0.000 1 3.501 0 0.000 MCC..................... CC.
fracture of right femur, initial
encounter for closed fracture).
S72.135A (Nondisplaced apophyseal 0 0.000 0 0.000 0 0.000 MCC..................... CC.
fracture of left femur, initial
encounter for closed fracture).
S72.136A (Nondisplaced apophyseal 0 0.000 0 0.000 0 0.000 MCC..................... CC.
fracture of unspecified femur,
initial encounter for closed
fracture).
[[Page 19243]]
S72.141A (Displaced 289 2.2607 894 2.6329 1,293 3.1692 MCC..................... CC.
intertrochanteric fracture of
right femur, initial encounter
for closed fracture).
S72.142A (Displaced 347 2.2587 972 2.5641 1,405 3.1003 MCC..................... CC.
intertrochanteric fracture of
left femur, initial encounter for
closed fracture).
S72.143A (Displaced 10 2.3446 21 1.0169 35 3.3080 MCC..................... CC.
intertrochanteric fracture of
unspecified femur, initial
encounter for closed fracture).
S72.144A (Nondisplaced 44 1.7331 149 2.4637 168 3.1302 MCC..................... CC.
intertrochanteric fracture of
right femur, initial encounter
for closed fracture).
S72.145A (Nondisplaced 39 1.9170 112 2.8435 170 3.2612 MCC..................... CC.
intertrochanteric fracture of
left femur, initial encounter for
closed fracture).
S72.146A (Nondisplaced 0 0.0000 9 1.2250 2 0.0000 MCC..................... CC.
intertrochanteric fracture of
unspecified femur, initial
encounter for closed fracture).
S72.21XA (Displaced 57 1.7697 159 2.2460 205 3.1614 MCC..................... CC.
subtrochanteric fracture of right
femur, initial encounter for
closed fracture).
S72.22XA (Displaced 70 2.3685 160 2.6079 184 3.2178 MCC..................... CC.
subtrochanteric fracture of left
femur, initial encounter for
closed fracture).
S72.23XA (Displaced 0 0.0000 9 3.4708 6 3.3401 MCC..................... CC.
subtrochanteric fracture of
unspecified femur, initial
encounter for closed fracture).
S72.24XA (Nondisplaced 12 0.5442 22 2.7275 11 3.6028 MCC..................... CC.
subtrochanteric fracture of right
femur, initial encounter for
closed fracture).
S72.25XA (Nondisplaced 13 1.7115 25 2.1005 17 3.1686 MCC..................... CC.
subtrochanteric fracture of left
femur, initial encounter for
closed fracture).
S72.26XA (Nondisplaced 0 0.0000 1 2.0474 0 0.0000 MCC..................... CC.
subtrochanteric fracture of
unspecified femur, initial
encounter for closed fracture).
S72.301A (Unspecified fracture of 61 2.3462 156 3.0491 159 3.5567 MCC..................... CC.
shaft of right femur, initial
encounter for closed fracture).
S72.302A (Unspecified fracture of 71 2.6314 186 2.4838 157 3.4436 MCC..................... CC.
shaft of left femur, initial
encounter for closed fracture).
--------------------------------------------------------------------------------------------------------------------------------------------------------
As shown in the table above, all of these secondary diagnoses are
currently designated as MCCs. The C2 values of the codes most
frequently reported, ICD-10-CM codes S72.142A and S72.141A, are closer
to 3.0 than 2.0, which indicates that they are more clinically aligned
with a CC than an MCC. Therefore, the data suggest that when fracture
of the hip codes are reported as a secondary diagnosis, the resources
involved in caring for patients with these conditions are more aligned
with a CC than an MCC. Our clinical advisors reviewed these data and
believe the resources involved in caring for patients with these
conditions are more aligned with a CC. While we note that there is
little to no data for some of these ICD-10-CM codes as secondary
diagnoses, there is sufficient data for clinically similar secondary
diagnoses. Therefore, because our clinical advisors believe that it is
appropriate to ensure consistency across codes involving similar
diagnoses, we are proposing to reassign the severity level for all of
the codes in the table above from an MCC to a CC.
(f) Factors Influencing Health Status and Contact With Health Services
The last chapter of the ICD-10-CM classification specifies other
factors that influence a patient's health status or necessitate contact
with health care
[[Page 19244]]
providers (Z00-Z99). Of these ICD-10-CM codes, based on our
comprehensive review, we are proposing to change the severity level
designation from non-CC to CC for four codes specifying anti-microbial
drug resistance and one code specifying homelessness. Based on this
same review, we also are proposing to change the severity level
designation from CC to non-CC for 3 ICD-10-CM codes specifying adult
body mass index (BMI) ranges and 13 ICD-10-CM codes indicating that the
patient has previously undergone an organ transplant or cardiac device
implantation with no current complications (the code indicates status
only).
The following table contains the five codes for which we are
proposing a severity level change from non-CC to CC and their impact on
resource use when reported as a secondary diagnosis.
Proposed Severity Level Changes for Z Chapter Codes as Secondary Diagnosis
--------------------------------------------------------------------------------------------------------------------------------------------------------
ICD-10-CM diagnosis code Cnt1 C1 Cnt2 C2 Cnt3 C3 Current CC subclass Proposed CC subclass
--------------------------------------------------------------------------------------------------------------------------------------------------------
Z16.12 (Extended spectrum beta 3,082 2.1134 19,692 2.5995 25,544 3.1752 Non-CC.................. CC.
lactamase (ESBL) resistance).
Z16.21 (Resistance to vancomycin). 692 2.1507 6,733 2.8659 11,672 3.3365 Non-CC.................. CC.
Z16.24 (Resistance to multiple 2,970 1.5821 16,097 2.4086 20,738 3.1174 Non-CC.................. CC.
antibiotics).
Z16.39 (Resistance to other 448 1.2003 2,326 2.2555 2,494 3.1127 Non-CC.................. CC.
specified antimicrobial drug).
Z59.0 (Homelessness).............. 14,927 1.5964 41,328 2.3012 22,101 3.1256 Non-CC.................. CC.
--------------------------------------------------------------------------------------------------------------------------------------------------------
As indicated above, a value close to 2.0 in column C1 suggests that
the secondary diagnosis is more aligned with a CC than a non-CC.
Because the C1 values in the table above are generally close to 2, the
data suggest that when these five Z chapter diagnosis codes are
reported as a secondary diagnosis, the resources involved in caring for
a patient with other factors such as homelessness support increasing
the severity level from a non-CC to a CC. Our clinical advisors
reviewed these data and believe the resources involved in caring for
patients with these other reported factors are more aligned with a CC.
While we note that ICD-10-CM diagnosis code Z16.39 does not follow
this pattern, our clinical advisors believe that this code is
clinically similar to the other diagnoses in the table above describing
anti-microbial drug resistance. Therefore, because our clinical
advisors believe that it is appropriate to ensure consistency across
codes involving similar diagnoses, we are proposing to reassign the
severity level for all four of the codes specifying anti-microbial drug
resistance in the table above from a non-CC to a CC.
The following table contains the 14 BMI and transplant/cardiac
device status codes for which we are proposing a severity level
designation change from CC to non-CC, and their impact on resource use
when reported as a secondary diagnosis.
Proposed Severity Level Changes for Z Chapter BMI and Transplant/Cardiac Device Status Codes as Secondary Diagnosis
--------------------------------------------------------------------------------------------------------------------------------------------------------
ICD-10-CM diagnosis code Cnt1 C1 Cnt2 C2 Cnt3 C3 Current CC subclass Proposed CC subclass
--------------------------------------------------------------------------------------------------------------------------------------------------------
Z68.1 (Body mass index (BMI) 19.9 18,983 1.1170 244,156 2.2082 350,731 3.0733 CC...................... Non-CC.
or less, adult).
Z68.41 (Body mass index (BMI) 40.0- 139,420 1.1139 209,300 2.0752 213,929 3.0814 CC...................... Non-CC.
44.9, adult).
Z68.42 (Body mass index (BMI) 45.0- 60,408 1.1643 102,897 2.0783 109,928 3.0867 CC...................... Non-CC.
49.9, adult).
Z94.0 (Kidney transplant status).. 18,649 1.0277 70,484 2.0573 45,382 3.1032 CC...................... Non-CC.
Z94.1 (Heart transplant status)... 2,311 1.0649 8,138 2.2471 5,037 3.2653 CC...................... Non-CC.
Z94.2 (Lung transplant status).... 1,461 1.0886 5,032 2.1898 3,466 3.1285 CC...................... Non-CC.
Z94.3 (Heart and lungs transplant 20 0.8287 88 3.0647 59 3.1675 CC...................... Non-CC.
status).
Z94.4 (Liver transplant status)... 6,050 0.9811 17,556 2.0323 12,970 3.1688 CC...................... Non-CC.
Z94.81 (Bone marrow transplant 1,655 0.9778 5,447 2.0919 5,150 3.1918 CC...................... Non-CC.
status).
Z94.82 (Intestine transplant 119 1.5661 351 2.1844 230 3.2081 CC...................... Non-CC.
status).
Z94.83 (Pancreas transplant 1,789 1.2032 7,788 2.0739 4,536 3.1381 CC...................... Non-CC.
status).
Z94.84 (Stem cells transplant 3,083 1.1451 10,412 2.3041 8,835 3.2932 CC...................... Non-CC.
status).
Z95.811 (Presence of heart assist 1,053 1.6453 7,373 2.3089 5,974 3.1198 CC...................... Non-CC.
device).
Z95.812 (Presence of fully 45 2.0467 132 2.5603 142 2.4139 CC...................... Non-CC.
implantable artificial heart).
--------------------------------------------------------------------------------------------------------------------------------------------------------
[[Page 19245]]
The C1, C2, and C3 values in the table above are generally close to
1.0, 2.0, and 3.0, respectively. This indicates that these conditions
are more aligned with a non-CC than with either a CC or an MCC.
Therefore, the data suggest that when these BMI and transplant/cardiac
device status codes are reported as a secondary diagnosis, the
resources involved in caring for patients with these conditions
indicating health status are not aligned with those of a CC. Our
clinical advisors reviewed these data and believe the resources
involved in caring for patients with these conditions indicating health
status are more aligned with a non-CC. Our clinical advisors noted
that, in the absence of a diagnosis that represents a complication of
the patient's current status, the presence of a BMI within a stated
range or the fact that a patient has previously undergone a transplant
or cardiac device implant is not by itself a clinical indication of
increased severity of illness. Therefore, we are proposing to reassign
the severity level for all of the codes in the table above from a CC to
a non-CC.
(3) Results of Impact Analysis
Using claims data from the September 2018 update of the FY 2018
MedPAR file, we employed the following method to determine the impact
of changing severity level designation for the 1,492 ICD-10-CM
diagnosis codes. Edits and cost estimations used for relative weight
calculations were applied, resulting in 8,908,404 IPPS claims analyzed
for this impact evaluation of our proposed changes to severity levels.
We refer readers to section II.G. of the preamble of this proposed rule
for further information regarding the methodology for calculation of
the proposed relative weights.
First, we analyzed the 8,908,404 IPPS claims using the Version 36
ICD-10 MS-DRG GROUPER to determine the current distribution of severity
level designation. We identified 3,648,331 cases (41.0 percent)
reporting one or more secondary diagnosis codes assigned to the MCC
severity level, 3,612,600 cases (40.5 percent) reporting one or more
secondary diagnosis codes assigned to the CC severity level, and
1,647,473 cases (18.5 percent) not reporting a secondary diagnosis code
assigned to the MCC or CC severity level.
Next, we reprocessed the 8,908,404 claims using the proposed change
in severity level designation for the 1,492 ICD-10-CM diagnosis codes
to determine the impact on the distribution of severity level
designation. We identified 3,236,493 cases (36.3 percent) reporting one
or more secondary diagnosis codes that would be assigned to the MCC
severity level, 3,589,677 cases (40.3 percent) reporting one or more
secondary diagnosis codes that would be assigned to the CC severity
level, and 2,082,234 cases (23.4 percent) not reporting a secondary
diagnosis code that would be assigned to the MCC or CC severity level.
Below we provide a summary of the steps followed for the analysis
performed.
Step 1.--Analyzed 8,908,404 claims to determine the current
distribution of severity level designation.
Severity Level Distribution Before Proposed Changes--8,908,404 Claims
Analyzed
------------------------------------------------------------------------
------------------------------------------------------------------------
Number of cases reporting one or more 3,648,331 (41.0%)
secondary diagnosis codes assigned to the
MCC severity level.......................
Number of cases reporting one or more 3,612,600 (40.5%)
secondary diagnosis codes assigned to the
CC severity level........................
Number of cases reporting no secondary 1,647,473 (18.5%)
diagnosis codes assigned to the MCC or CC
severity level...........................
------------------------------------------------------------------------
Step 2.--Made proposed severity level changes to 1,492 ICD-10-CM
codes.
Step 2--Made proposed severity level changes to 1,492 ICD-10-CM codes.
------------------------------------------------------------------------
Proposed version 37 Number of
Current version 36 severity level severity level codes
------------------------------------------------------------------------
Non-CC............................ CC.................. 183
CC................................ Non-CC.............. 1,148
CC................................ MCC................. 8
MCC............................... Non-CC.............. 17
MCC............................... CC.................. 136
---------------
Total......................... .................... 1,492
------------------------------------------------------------------------
Step 3.--Reprocessed 8,908,404 claims to determine severity level
distribution after changes.
Severity Level Distribution after Proposed Changes--8,908,404 Claims
Analyzed
------------------------------------------------------------------------
------------------------------------------------------------------------
Number of cases reporting one or more 3,236,493 (36.3%)
secondary diagnosis codes assigned to the
MCC severity level.......................
Number of cases reporting one or more 3,589,677 (40.3%)
secondary diagnosis codes assigned to the
CC severity level........................
Number of cases reporting no secondary 2,082,234 (23.4%)
diagnosis codes assigned to the MCC or CC
severity level...........................
------------------------------------------------------------------------
The overall statistics by CC subgroup for the proposed Version 37
MS-DRGs are contained in the table below. Cases in the MCC subgroup
have average costs that are 62 percent higher than the average costs
for cases in the CC subgroup. The CC subgroup with the largest number
of cases is the CC subgroup with 40.3 percent of the cases.
[[Page 19246]]
Overall Statistics for Proposed MS-DRGs
----------------------------------------------------------------------------------------------------------------
Number of
CC subgroup cases Percent Average costs
----------------------------------------------------------------------------------------------------------------
Major........................................................... 3,236,493 36.3 $16,890
CC.............................................................. 3,589,677 40.3 10,518
Non-CC.......................................................... 2,082,234 23.4 10,166
----------------------------------------------------------------------------------------------------------------
The distribution of cases across the different types of CC
subgroups in the proposed Version 37 MS-DRGs is contained in the table
below. The table shows that 91 percent of the cases would be assigned
to base MS-DRGs with three CC subgroups, and only 9 percent of the
cases would be assigned to base MS-DRGs with no CC subgroups.
Distribution of Patient by Type of CC Subgroup in Proposed Version 37 MS-
DRGs
------------------------------------------------------------------------
CC subgroup Number Percent
------------------------------------------------------------------------
None.................................... 68 9
(MCC and CC), Non-CC.................... 84 11
MCC, (CC and Non-CC).................... 132 17
MCC, CC, and Non-CC..................... 477 63
-------------------------------
Total............................... 761 ..............
------------------------------------------------------------------------
We performed regression analysis to compare the variance in the MS-
DRGs with and without the proposed severity level designation changes
and thereby the impact of payment to cost ratios. The results of the
regression analysis showed a slight decrease in variance with the
proposed severity level designation changes, showing an R-squared of
35.9 percent after making the severity level changes, compared with an
R-squared of 35.6 percent in the current Version 36 ICD-10 MS-DRG
GROUPER. This indicates that the proposed severity level changes
increase the explanatory power of the GROUPER in capturing differences
in expected cost between the MS-DRGs and thus would improve the overall
accuracy of the IPPS payment system.
After considering the results of our data analysis, the clinical
judgment of our clinical advisors, and the overall aggregate impact of
these changes, we are proposing a change to the severity level
designations for 1,492 ICD-10-CM diagnosis codes as shown in Table
6P.1c. associated with this proposed rule (which is available via the
internet on the CMS website at: http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.)
d. Requested Changes to Severity Levels
(1) Acute Right Heart Failure
We received a request to change the severity level for ICD-10-CM
diagnosis codes I50.811 (Acute right heart failure) and I50.813 (Acute
on chronic right heart failure) from a non-CC to an MCC. The requestor
stated that similar diagnosis codes in the classification are
designated as an MCC. We used the approach outlined earlier in this
section to evaluate this request. The following table shows the claims
data that were used to evaluate this request:
--------------------------------------------------------------------------------------------------------------------------------------------------------
ICD-10-CM diagnosis code Cnt1 C1 Cnt2 C2 Cnt3 C3 Current CC subclass Requested CC subclass
--------------------------------------------------------------------------------------------------------------------------------------------------------
I50.811 Acute right heart failure. 92 1.3290 470 2.5375 1,632 3.1907 non-CC.................. MCC.
I50.813 Acute on chronic right 183 1.4412 1,189 2.6036 3,099 3.2870 non-CC.................. MCC.
heart failure.
--------------------------------------------------------------------------------------------------------------------------------------------------------
For ICD-10-CM diagnosis code I50.811, the data suggest that the
resources involved in caring for a patient with this condition are 33
percent greater than expected when the patient has either no other
secondary diagnosis present, or all the other secondary diagnoses
present are non-CCs. The resources are 54 percent greater than expected
when reported in conjunction with another secondary diagnosis that is a
CC, and 19 percent greater than expected when reported in conjunction
with another secondary diagnosis code that is an MCC. Our clinical
advisors reviewed this request and agree that the resources involved in
caring for a patient with this condition are not aligned with those of
an MCC.
For ICD-10-CM diagnosis code I50.813, the data suggest that the
resources involved in caring for a patient with this condition are 44
percent greater than expected when the patient has either no other
secondary diagnosis present or all the other secondary diagnoses
present are non-CCs. The resources are 60 percent greater than expected
when reported in conjunction with another secondary diagnosis that is a
CC, and 28 percent greater than expected when reported in conjunction
with another secondary diagnosis code that is an MCC. Our clinical
advisors reviewed this request and agree that the resources involved in
caring for a patient with this condition are not aligned with those of
an MCC.
However, we note that although the data suggest that the resources
involved in caring for a patient with this condition are not aligned
with those of an MCC, the data suggest and our clinical advisors
believe that the resources appear to be aligned with
[[Page 19247]]
those of a CC. Therefore, we are soliciting public comment on whether a
CC severity level designation for ICD-10-CM diagnosis codes I50.811 and
I50.813 for FY 2020 is appropriate.
(2) Chronic Right Heart Failure
We received a request to change the severity level for ICD-10-CM
diagnosis code I50.812 (Chronic right heart failure) from a non-CC to a
CC. The requestor stated that this code warrants CC classification
because it indicates the presence and treatment of chronic heart
failure. We used the approach outlined earlier to evaluate this
request. The following table contains the data that we used to evaluate
this request:
--------------------------------------------------------------------------------------------------------------------------------------------------------
ICD-10-CM diagnosis code Cnt1 C1 Cnt2 C2 Cnt3 C3 Current CC subclass Requested CC subclass
--------------------------------------------------------------------------------------------------------------------------------------------------------
I50.812 Chronic right heart 179 1.5114 1,533 2.1146 1,758 3.0549 non-CC.................. CC.
failure.
--------------------------------------------------------------------------------------------------------------------------------------------------------
For ICD-10-CM diagnosis code I50.812, the data suggest that the
resources involved in caring for a patient with this condition are 51
percent greater than expected when the patient has either no other
secondary diagnosis present or all the other secondary diagnoses
present are non-CCs. The resources are 11 percent greater than expected
when reported in conjunction with another secondary diagnosis that is a
CC, and 5 percent greater than expected when reported in conjunction
with another secondary diagnosis code that is an MCC. Our clinical
advisors reviewed this request and agree that the resources involved in
caring for a patient with this condition are not aligned with those of
a CC. Therefore, we are not proposing a change to the severity level
for ICD-10-CM diagnosis code I50.812.
(3) Ascites in Alcoholic Liver Disease and Toxic Liver Disease
We received a request to change the severity level for ICD-10-CM
diagnosis codes K70.11 (Alcoholic hepatitis with ascites), K70.31
(Alcoholic cirrhosis with ascites), and K71.51 (Toxic liver disease
with chronic active hepatitis with ascites) from a non-CC to a CC. The
requestor stated that these codes warrant CC classification because
providers are not currently compensated for the ascites treatment. We
used the approach outlined earlier to evaluate this request. The
following table contains the data that we used to evaluate this
request.
--------------------------------------------------------------------------------------------------------------------------------------------------------
ICD-10-CM diagnosis code Cnt1 C1 Cnt2 C2 Cnt3 C3 Current CC subclass Requested CC subclass
--------------------------------------------------------------------------------------------------------------------------------------------------------
K70.11 Alcoholic hepatitis with 134 1.2952 1,940 2.3444 3,331 3.3635 non-CC.................. CC.
ascites.
K70.31 Alcoholic cirrhosis with 1,634 1.1129 18,675 2.2301 26,822 3.2479 non-CC.................. CC.
ascites.
K71.51 Toxic liver disease with 16 0.8913 218 2.1743 274 3.1418 non-CC.................. CC.
chronic active hepatitis with
ascites.
--------------------------------------------------------------------------------------------------------------------------------------------------------
For ICD-10-CM diagnosis code K70.11, the data suggest that the
resources involved in caring for a patient with this condition are 29
percent greater than expected when the patient has either no other
secondary diagnosis present or all the other secondary diagnoses
present are non-CCs. The resources are 34 percent greater than expected
when reported in conjunction with another secondary diagnosis that is a
CC, and 36 percent greater than expected when reported in conjunction
with another secondary diagnosis code that is an MCC. Our clinical
advisors reviewed this request and agree that the resources involved in
caring for a patient with this condition are not aligned with those of
a CC. Therefore, we are not proposing a change to the severity level
for ICD-10-CM diagnosis code K70.11.
For ICD-10-CM diagnosis code K70.31, the data suggest that the
resources involved in caring for a patient with this condition are 11
percent greater than expected when the patient has either no other
secondary diagnosis present or all the other secondary diagnoses
present are non-CCs. The resources are 23 percent greater than expected
when reported in conjunction with another secondary diagnosis that is a
CC, and 25 percent greater than expected when reported in conjunction
with another secondary diagnosis code that is an MCC. Our clinical
advisors reviewed this request and agree that the resources involved in
caring for a patient with this condition are not aligned with those of
a CC. Therefore, we are not proposing a change to the severity level
for ICD-10-CM diagnosis code K70.31.
For ICD-10-CM diagnosis code K71.51, the data suggest that the
resources involved in caring for a patient with this condition are 11
percent lower than expected when the patient has either no other
secondary diagnosis present, or all the other secondary diagnoses
present are non-CCs. The resources are 17 percent greater than expected
when reported in conjunction with another secondary diagnosis that is a
CC, and 14 percent greater than expected when reported in conjunction
with another secondary diagnosis code that is an MCC. Our clinical
advisors reviewed this request and agree that the resources involved in
caring for a patient with this condition are not aligned with those of
a CC. Therefore, we are not proposing a change to the severity level
for ICD-10-CM diagnosis code K71.51.
(4) Factitious Disorder Imposed on Self
We received a request to change the severity level for ICD-10-CM
diagnosis codes F68.11 (Factitious disorder imposed on self, with
predominantly psychological signs and symptoms) and F68.13 (Factitious
disorder imposed on self, with combined psychological and physical
signs and symptoms) from a
[[Page 19248]]
non-CC to a CC. The requestor stated that similar codes in the
classification are designated as a CC. We used the approach outlined
earlier to evaluate this request. The following table contains the data
that we used to evaluate this request.
--------------------------------------------------------------------------------------------------------------------------------------------------------
ICD-10-CM diagnosis code Cnt1 C1 Cnt2 C2 Cnt3 C3 Current CC subclass Requested CC subclass
--------------------------------------------------------------------------------------------------------------------------------------------------------
F68.11 Factitious disorder imposed 16 1.2040 59 0.9979 15 3.2395 non-CC.................. CC.
on self, with predominantly
psychological signs and symptoms.
F68.13 Factitious disorder imposed 4 1.6226 32 1.9840 11 4.0000 non-CC.................. CC.
on self, with combined
psychological and physical signs
and symptoms.
--------------------------------------------------------------------------------------------------------------------------------------------------------
For ICD-10-CM diagnosis code F68.11, the number of patients found
in the September 2018 update of the FY 2018 MedPAR data in each of the
subsets is 16, 59, and 15, and for ICD-10-CM diagnosis code F68.13, the
number of patients in each of the subsets is 4, 32, and 11. Our
clinical advisors reviewed this request and believe that due to the
small number of cases in the data, it is not possible to use
statistical methods to evaluate the impact on resource use of patients.
Our clinical advisors also do not believe there is a clinical basis to
change the severity level in the absence of data. Our clinical advisors
noted that if a patient was diagnosed with either one of these ICD-10-
CM diagnoses (ICM-10-CM diagnosis code F68.11 or F68.13), there would
more than likely be another diagnosis code reported that identifies the
psychological and/or physical symptoms the patient is experiencing that
may be a better indicator of resources utilized because these patients
often fabricate their illness and inflict injuries on themselves to
receive attention. For example, a patient may cut his or her finger,
resulting in a wound which requires repair. It is the cut and need for
repair that contribute to the resources consumed in caring for a
patient with this diagnosis. Therefore, we are not proposing a change
to the severity level for ICD-10-CM diagnosis codes F68.11 and F68.13
at this time.
(5) Nonunion and Malunion of Physeal Metatarsal Fractures
We received a request to change the severity level designations for
the following six ICD-10-CM diagnosis codes from a non-CC to a CC:
S99.101B (Unspecified physeal fracture of right metatarsal, initial
encounter for open fracture); S99.101K (Unspecified physeal fracture of
right metatarsal, subsequent encounter for fracture); S99.101P
(Unspecified physeal fracture of right metatarsal, subsequent encounter
for fracture with malunion); S99.132B (Salter-Harris Type III physeal
fracture of left metatarsal, initial encounter for open fracture),
S99.132K (Salter-Harris Type III physeal fracture of left metatarsal,
subsequent encounter for fracture with nonunion); and S99.132P (Salter-
Harris Type III physeal fracture of left metatarsal, subsequent
encounter for fracture with malunion with nonunion). The requestor
stated that similar codes for open fractures, nonunions, and malunions
of other sites currently are designated as CCs. However the requestor
did not provide the specific ICD-10-CM diagnosis codes that are
currently designated as CCs that the requestor believes are an
appropriate comparator. There are a considerable number of fractures,
nonunions, and malunions of other sites, some of which are designated
as CCs and others that are not. In particular, in evaluating this
request, we would want to review the appropriateness of designating
unspecified codes (that is, ICD-10-CM diagnosis codes S99.101B,
S99.101K, and S99.101P) as a CC, to avoid potentially discouraging more
detailed coding. In addition, none of the other ICD-10-CM diagnosis
codes describing Salter-Harris fractures (for example, ICD-10-CM
diagnosis codes in sub-subcategory S99.11- (Salter-Harris Type I
physeal fracture of metatarsal), S99.12- (Salter-Harris Type II physeal
fracture of metatarsal), S99.13- (Salter-Harris Type III physeal
fracture of metatarsal), and S99.14- (Salter-Harris Type IV physeal
fracture of metatarsal)) currently have a CC designation.
Given the lack of supporting information for this request and
because we believe this request may require further research and
analysis to evaluate the relevant category of fracture codes and fully
assess the claims data, we are unable to fully evaluate this request
for FY 2020. Therefore, at this time, we are not proposing changes to
the severity level designations for ICD-10-CM diagnosis codes S99.101B,
S99.101K, S99.101P, S99.132B, S99.132K, and S99.132P as the requestor
recommended.
(6) Other Encephalopathy
In the FY 2019 IPPS/LTCH PPS proposed rule (83 FR 20241), we
discussed a request that we had received to change the severity level
designation for ICD-10-CM diagnosis code G93.40 (Encephalopathy,
unspecified) from an MCC to a non-CC. We did not propose a change based
on the review of the claims data and input from our clinical advisors.
However, after a review of public comments in response to that
proposal, we finalized a change in the severity level designation for
ICD-10-CM diagnosis code G93.40 from an MCC to a CC (83 FR 41239).
We received a request to reconsider the change in the severity
level designation for ICD-10-CM diagnosis code G93.49 (Other
encephalopathy) from an MCC to a CC, as reflected in Table 6I.2--
Deletions to the MCC List and Table 6J.--Complete CC List that were
associated with the FY 2019 IPPS/LTCH PPS final rule, because the
requestor noted this diagnosis code was not discussed in the FY 2019
IPPS/LTCH PPS proposed or final rules along with the discussion of
related ICD-10-CM diagnosis code G93.40. The requestor stated that
diagnosis code G93.49 warrants an MCC classification to accurately
reflect severity of illness and resources contributing to an extended
length of stay for patients who have this condition.
Our clinical advisors reviewed the data for ICD-10-CM diagnosis
code G93.49 (Other encephalopathy) as set forth in the table below, and
noted that the C1 value is close to 2.0, which indicates that the
resource use is aligned with that of a CC, while the C2 value is about
halfway between 2.0 and 3.0, which is also consistent with the resource
use of a CC. They also compared the C1, C2, and C3 values of diagnosis
code G93.49 to those of diagnosis code G93.40, as also set forth in the
table below, and noted that the values were similar for both codes. Our
clinical advisors noted that similar to diagnosis code G93.40,
diagnosis code
[[Page 19249]]
G93.49 (Other encephalopathy) is poorly defined, not all
encephalopathies are MCCs, and the MCC status may create an incentive
for coding personnel to not pursue specificity of encephalopathy.
Therefore, they believe that these conditions are clinically similar
and should be assigned the same CC severity level status. Therefore, we
are not proposing any change to the severity level for ICD 10 CM
diagnosis code G93.49 (Other encephalopathy) for FY 2020.
----------------------------------------------------------------------------------------------------------------
ICD-10-CM diagnosis code Cnt1 C1 Cnt2 C2 Cnt3 C3
----------------------------------------------------------------------------------------------------------------
G93.40 (Encephalopathy, unspecified).......... 32,023 1.812 161,991 2.494 294,088 3.289
G93.49 (Other encephalopathy)................. 4,258 1.758 23,203 2.536 40,836 3.349
----------------------------------------------------------------------------------------------------------------
(7) Obstetrics Chapter Codes
We received a request to change the severity level for 94 ICD-10-CM
diagnosis codes in the Obstetrics chapter of the ICD-10-CM diagnosis
classification that describe a variety of complications of pregnancy,
childbirth and the puerperium. The requestor stated that the
reclassification of the 94 obstetric diagnosis codes would more
appropriately reflect severity of illness and accurate MS-DRG grouping
after CMS' FY 2019 creation of new obstetric MS-DRGs subdivided by
severity level (with MCC, with CC, and without CC/MCC).
The 94 obstetrics codes associated with this request and their
current and requested severity level designation are shown in Table
6P.1e. associated with this proposed rule (which is available via the
internet on the CMS website at: http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html). We are
proposing to move some of these diagnosis codes to a higher severity
level and some diagnosis codes to a lower severity level. Our proposals
are shown in the table below.
Our clinical advisors indicated that the approach outlined
elsewhere in this section to evaluate requested changes to severity
levels, in which each diagnosis is evaluated using Medicare cost data
to determine the extent to which its presence as a secondary diagnosis
resulted in increased hospital resource use, could not be used to
evaluate this request because the number of obstetric patients in the
Medicare data was insufficient to perform evaluation using statistical
methods. Instead, our clinical advisors used their clinical judgment to
evaluate the requested changes to the severity levels for the 94
obstetrics diagnosis codes. Our clinical advisors concur with the
requestor that changes to the severity level for some of the obstetrics
diagnosis codes would more appropriately reflect severity of illness
and accurate MS-DRG grouping. Specifically, our clinical advisors
agreed with the requested change to severity from a non-CC to a CC for
10 of the diagnosis codes identified by the requestor because they
believe these conditions clinically warrant a CC designation. They
noted that 6 of the 10 diagnosis codes describe gestational diabetes
mellitus in pregnancy, gestational diabetes mellitus in childbirth, or
gestational diabetes mellitus in the puerperium requiring control,
either by insulin or oral hypoglycemic drugs and the condition would
require additional monitoring and resources in the inpatient setting.
They also noted that 2 of the 10 diagnosis codes describe maternal care
for other isoimmunization in the first trimester for single or multiple
gestations where the fetus is unspecified or fetus number 1 is
specified. They indicated that although there are additional diagnosis
codes describing maternal care for other isoimmunization in the first
trimester that uniquely identify fetus number 2 through fetus number 5,
as well as an ``other'' fetus beyond number 5, they do not believe
these other diagnosis codes have any additional impact on resource use
because treatment would be directed at the entire uterine cavity. They
further noted that 1 of the 10 diagnosis codes describes a conjoined
twin pregnancy in the third trimester and, while conjoined twins occur
rarely and carry a high risk of complications and mortality, they
believe the complexities are greatest in the third trimester. Lastly, 1
of the 10 diagnosis codes describes unspecified diabetes mellitus in
childbirth, and because the diagnosis codes describing unspecified
diabetes mellitus in pregnancy and unspecified diabetes mellitus in the
puerperium are designated as a CC, our clinical advisors agreed that
clinically, the condition occurring in childbirth warrants a CC
designation as well. Our clinical advisors also agreed with the
requested change to severity level from an MCC to a CC for 4 other
diagnosis codes identified by the requestor because, clinically, the CC
designation is consistent with the other diagnosis codes within those
diagnosis code families. For example, the diagnosis codes describing
preexisting type 1 diabetes mellitus in pregnancy, preexisting type 2
diabetes mellitus in pregnancy and unspecified preexisting diabetes
mellitus in pregnancy, regardless of trimester (first, second, third,
and unspecified) are all designated as CCs. Our clinical advisors
agreed that the diagnosis codes describing these same conditions ``in
childbirth'' also warrant a CC designation because the conditions do
not require additional resources or reflect a greater severity of
illness compared to the conditions when they occur ``in pregnancy''.
Therefore, we are proposing a change to the severity level for 14 ICD-
10-CM diagnosis codes as shown in the following table.
----------------------------------------------------------------------------------------------------------------
ICD-10-CM diagnosis code Current CC subclass Proposed CC subclass
----------------------------------------------------------------------------------------------------------------
O24.02 (Pre-existing type 1 diabetes mellitus, in MCC.......................... CC.
childbirth).
O24.12 (Pre-existing type 2 diabetes mellitus, in MCC.......................... CC.
childbirth).
O24.32 (Unspecified pre-existing diabetes mellitus MCC.......................... CC.
in childbirth).
O24.414 (Gestational diabetes mellitus in Non-CC....................... CC.
pregnancy, insulin controlled).
O24.415 (Gestational diabetes mellitus in Non-CC....................... CC.
pregnancy, controlled by oral hypoglycemic drugs).
O24.424 (Gestational diabetes mellitus in Non-CC....................... CC.
childbirth, insulin controlled).
O24.425 (Gestational diabetes mellitus in Non-CC....................... CC.
childbirth, controlled by oral hypoglycemic drugs).
O24.434 (Gestational diabetes mellitus in the Non-CC....................... CC.
puerperium, insulin controlled).
O24.435 (Gestational diabetes mellitus in Non-CC....................... CC.
puerperium, controlled by oral hypoglycemic drugs).
O24.82 (Other pre-existing diabetes mellitus in MCC.......................... CC.
childbirth).
O24.92 (Unspecified diabetes mellitus in Non-CC....................... CC.
childbirth).
[[Page 19250]]
O30.023 (Conjoined twin pregnancy, third trimester) Non-CC....................... CC.
O36.1910 (Maternal care for other isoimmunization, Non-CC....................... CC.
first trimester, not applicable or unspecified).
O36.1911 (Maternal care for other isoimmunization, Non-CC....................... CC.
first trimester, fetus 1).
----------------------------------------------------------------------------------------------------------------
Given the limited number of cases reporting ICD-10-CM obstetrical
codes in the Medicare claims data, we note that use of datasets other
than MedPAR cost data for future evaluation of severity level
designation for the ICD-10-CM diagnosis codes from the Obstetrics
chapter of the ICD-10-CM classification is under consideration.
e. Proposed Additions and Deletions to the Diagnosis Code Severity
Levels for FY 2020
The following tables identify the proposed additions and deletions
to the diagnosis code MCC severity levels list and the proposed
additions and deletions to the diagnosis code CC severity levels list
for FY 2020 and are available via the internet on the CMS website at:
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.
Table 6I.1--Proposed Additions to the MCC List--FY 2020;
Table 6I.2--Proposed Deletions to the MCC List--FY 2020;
Table 6J.1--Proposed Additions to the CC List--FY 2020; and
Table 6J.2--Proposed Deletions to the CC List--FY 2020.
f. Proposed CC Exclusions List for FY 2020
In the September 1, 1987 final notice (52 FR 33143) concerning
changes to the DRG classification system, we modified the GROUPER logic
so that certain diagnoses included on the standard list of CCs would
not be considered valid CCs in combination with a particular principal
diagnosis. We created the CC Exclusions List for the following reasons:
(1) To preclude coding of CCs for closely related conditions; (2) to
preclude duplicative or inconsistent coding from being treated as CCs;
and (3) to ensure that cases are appropriately classified between the
complicated and uncomplicated DRGs in a pair.
In the May 19, 1987 proposed notice (52 FR 18877) and the September
1, 1987 final notice (52 FR 33154), we explained that the excluded
secondary diagnoses were established using the following five
principles:
Chronic and acute manifestations of the same condition
should not be considered CCs for one another;
Specific and nonspecific (that is, not otherwise specified
(NOS)) diagnosis codes for the same condition should not be considered
CCs for one another;
Codes for the same condition that cannot coexist, such as
partial/total, unilateral/bilateral, obstructed/unobstructed, and
benign/malignant, should not be considered CCs for one another;
Codes for the same condition in anatomically proximal
sites should not be considered CCs for one another; and
Closely related conditions should not be considered CCs
for one another.
The creation of the CC Exclusions List was a major project
involving hundreds of codes. We have continued to review the remaining
CCs to identify additional exclusions and to remove diagnoses from the
master list that have been shown not to meet the definition of a CC. We
refer readers to the FY 2014 IPPS/LTCH PPS final rule (78 FR 50541
through 50544) for detailed information regarding revisions that were
made to the CC and CC Exclusion Lists under the ICD-9-CM MS-DRGs.
In this FY 2020 IPPS/LTCH PPS proposed rule, for FY 2020, we are
proposing changes to the ICD-10 MS-DRGs Version 37 CC Exclusion List.
Therefore, we have developed Table 6G.1.--Proposed Secondary Diagnosis
Order Additions to the CC Exclusions List--FY 2020; Table 6G.2.--
Proposed Principal Diagnosis Order Additions to the CC Exclusions
List--FY 2020; Table 6H.1.--Proposed Secondary Diagnosis Order
Deletions to the CC Exclusions List--FY 2020; and Table 6H.2.--Proposed
Principal Diagnosis Order Deletions to the CC Exclusions List--FY 2020.
For Table 6G.1, each secondary diagnosis code proposed for addition to
the CC Exclusion List is shown with an asterisk and the principal
diagnoses proposed to exclude the secondary diagnosis code are provided
in the indented column immediately following it. For Table 6G.2, each
of the principal diagnosis codes for which there is a CC exclusion is
shown with an asterisk and the conditions proposed for addition to the
CC Exclusion List that will not count as a CC are provided in an
indented column immediately following the affected principal diagnosis.
For Table 6H.1, each secondary diagnosis code proposed for deletion
from the CC Exclusion List is shown with an asterisk followed by the
principal diagnosis codes that currently exclude it. For Table 6H.2,
each of the principal diagnosis codes is shown with an asterisk and the
proposed deletions to the CC Exclusions List are provided in an
indented column immediately following the affected principal diagnosis.
Tables 6G.1., 6G.2., 6H.1., and 6H.2. associated with this proposed
rule are available via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.
15. Proposed Changes to the ICD-10-CM and ICD-10-PCS Coding Systems
To identify new, revised and deleted diagnosis and procedure codes,
for FY 2020, we have developed Table 6A.--New Diagnosis Codes, Table
6B.--New Procedure Codes, Table 6C.--Invalid Diagnosis Codes, Table
6D.--Invalid Procedure Codes, Table 6E.--Revised Diagnosis Code Titles,
and Table 6F.--Revised Procedure Code Titles for this proposed rule.
These tables are not published in the Addendum to this proposed
rule but are available via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html as described in section VI. of the
Addendum to this proposed rule. As discussed in section II.F.18. of the
preamble of this proposed rule, the code titles are adopted as part of
the ICD-10 (previously ICD-9-CM) Coordination and Maintenance Committee
process. Therefore, although we publish the code titles in the IPPS
proposed and final rules, they are not subject to comment in the
proposed or final rules.
We are proposing the MDC and MS-DRG assignments for the new
diagnosis and procedure codes as set forth in Table 6A.--New Diagnosis
Codes and Table 6B.--New Procedure Codes. In addition, the proposed
severity level designations for the new diagnosis codes are set forth
in Table 6A. and the proposed O.R. status for the new procedure codes
are set forth in Table 6B.
We are making available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html
[[Page 19251]]
the following tables associated with this proposed rule:
Table 6A.--New Diagnosis Codes--FY 2020;
Table 6B.--New Procedure Codes--FY 2020;
Table 6C.--Invalid Diagnosis Codes--FY 2020;
Table 6D.--Invalid Procedure Codes--FY 2020;
Table 6E.--Revised Diagnosis Code Titles--FY 2020;
Table 6F.--Revised Procedure Code Titles--FY 2020;
Table 6G.1.--Proposed Secondary Diagnosis Order Additions
to the CC Exclusions List--FY 2020;
Table 6G.2.--Proposed Principal Diagnosis Order Additions
to the CC Exclusions List--FY 2020;
Table 6H.1.--Proposed Secondary Diagnosis Order Deletions
to the CC Exclusions List--FY 2020;
Table 6H.2.--Proposed Principal Diagnosis Order Deletions
to the CC Exclusions List--FY 2020;
Table 6I.1.--Proposed Additions to the MCC List--FY 2020;
Table 6I.2.-Proposed Deletions to the MCC List--FY 2020;
Table 6J.1.--Proposed Additions to the CC List--FY 2020;
and
Table 6J.2.--Proposed Deletions to the CC List--FY 2020.
16. Proposed Changes to the Medicare Code Editor (MCE)
The Medicare Code Editor (MCE) is a software program that detects
and reports errors in the coding of Medicare claims data. Patient
diagnoses, procedure(s), and demographic information are entered into
the Medicare claims processing systems and are subjected to a series of
automated screens. The MCE screens are designed to identify cases that
require further review before classification into an MS-DRG.
As discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41220),
we made available the FY 2019 ICD-10 MCE Version 36 manual file. The
link to this MCE manual file, along with the link to the mainframe and
computer software for the MCE Version 36 (and ICD-10 MS-DRGs) are
posted on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.html.
For this FY 2020 IPPS/LTCH PPS proposed rule, below we address the
MCE requests we received by the November 1, 2018 deadline. We also
discuss the proposals we are making based on our internal review and
analysis.
a. Age Conflict Edit: Maternity Diagnoses
In the MCE, the Age conflict edit exists to detect inconsistencies
between a patient's age and any diagnosis on the patient's record; for
example, a 5-year-old patient with benign prostatic hypertrophy or a
78-year-old patient coded with a delivery. In these cases, the
diagnosis is clinically and virtually impossible for a patient of the
stated age. Therefore, either the diagnosis or the age is presumed to
be incorrect. Currently, in the MCE, the following four age diagnosis
categories appear under the Age conflict edit and are listed in the
manual and written in the software program:
Perinatal/Newborn--Age of 0 years only; a subset of
diagnoses which will only occur during the perinatal or newborn period
of age 0 (for example, tetanus neonatorum, health examination for
newborn under 8 days old).
Pediatric--Age is 0-17 years inclusive (for example,
Reye's syndrome, routine child health exam).
Maternity--Age range is 12-55 years inclusive (for
example, diabetes in pregnancy, antepartum pulmonary complication).
Adult--Age range is 15-124 years inclusive (for example,
senile delirium, mature cataract).
Under the ICD-10 MCE, the maternity diagnoses category for the Age
conflict edit considers the age range of 12 to 55 years inclusive. For
that reason, the diagnosis codes on this Age conflict edit list would
be expected to apply to conditions or disorders specific to that age
group only.
We received a request to reconsider the age range associated with
the maternity diagnoses category for the Age conflict edit. According
to the requestor, pregnancies can and do occur prior to age 12 and
after age 55. The requestor suggested that a more appropriate age range
would be from age 9 to age 64 for the maternity diagnoses category.
We agree with the requestor that pregnancies can and do occur prior
to the age of 12 and after the age of 55. We also agree that the
suggested range, age 9 to age 64, is an appropriate age range.
Therefore, we are proposing to revise the maternity diagnoses category
for the Age conflict edit to consider the new age range of 9 to 64
years inclusive.
b. Sex Conflict Edit: Diagnoses for Females Only Edit
In the MCE, the Sex conflict edit detects inconsistencies between a
patient's sex and any diagnosis or procedure on the patient's record;
for example, a male patient with cervical cancer (diagnosis) or a
female patient with a prostatectomy (procedure). In both instances, the
indicated diagnosis or the procedure conflicts with the stated sex of
the patient. Therefore, the patient's diagnosis, procedure, or sex is
presumed to be incorrect.
As discussed in section II.F.15. of the preamble of this proposed
rule, Table 6A.--New Diagnosis Codes which is associated with this
proposed rule (and is available via the internet on the CMS website at:
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html) lists the new diagnosis codes that have
been approved to date which will be effective with discharges on and
after October 1, 2019. ICD-10-CM diagnosis code N99.85 (Post
endometrial ablation syndrome) is a new code that describes a condition
consistent with the female sex. We are proposing to add this diagnosis
code to the Diagnoses for Females Only edit code list under the Sex
conflict edit.
c. Unacceptable Principal Diagnosis Edit
In the MCE, there are select codes that describe a circumstance
that influences an individual's health status but does not actually
describe a current illness or injury. There also are codes that are not
specific manifestations but may be due to an underlying cause. These
codes are considered unacceptable as a principal diagnosis. In limited
situations, there are a few codes on the MCE Unacceptable Principal
Diagnosis edit code list that are considered ``acceptable'' when a
specified secondary diagnosis is also coded and reported on the claim.
ICD-10-CM diagnosis codes I46.2 (Cardiac arrest due to underlying
cardiac condition) and I46.8 (Cardiac arrest due to other underlying
condition) are codes that clearly specify cardiac arrest as being due
to an underlying condition. Also, in the ICD-10-CM Tabular List, there
are instructional notes to ``Code first underlying cardiac condition''
at ICD-10-CM diagnosis code I46.2 and to ``Code first underlying
condition'' at ICD-10-CM diagnosis code I46.8. Therefore, we are
proposing to add ICD-10-CM diagnosis codes I46.2 and I46.8 to the
Unacceptable Principal Diagnosis Category edit code list.
As discussed in section II.F.15. of the preamble of this proposed
rule, Table 6A.--New Diagnosis Codes associated with this proposed rule
(which is available via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html) lists the new diagnosis
[[Page 19252]]
codes that have been approved to date that will be effective with
discharges occurring on and after October 1, 2019.
We are proposing to add the new ICD-10-CM diagnosis codes listed in
the following table to the Unacceptable Principal Diagnosis Category
edit code list, as these codes are consistent with other ICD-10-CM
diagnosis codes currently included on the Unacceptable Principal
Diagnosis Category edit code list.
------------------------------------------------------------------------
ICD-10-CM code Code description
------------------------------------------------------------------------
T50.915A.................. Adverse effect of multiple unspecified
drugs, medicaments and biological
substances, initial encounter.
T50.915D.................. Adverse effect of multiple unspecified
drugs, medicaments and biological
substances, subsequent encounter.
T50.915S.................. Adverse effect of multiple unspecified
drugs, medicaments and biological
substances, sequela.
T50.916A.................. Underdosing of multiple unspecified drugs,
medicaments and biological substances,
initial encounter.
T50.916D.................. Underdosing of multiple unspecified drugs,
medicaments and biological substances,
subsequent encounter.
T50.916S.................. Underdosing of multiple unspecified drugs,
medicaments and biological substances,
sequela.
Z11.7..................... Encounter for testing for latent
tuberculosis infection.
Z22.7..................... Latent tuberculosis.
Z71.84.................... Encounter for health counseling related to
travel.
Z86.002................... Personal history of in-situ neoplasm of
other and unspecified genital organs.
Z86.003................... Personal history of in-situ neoplasm of oral
cavity, esophagus and stomach.
Z86.004................... Personal history of in-situ neoplasm of
other and unspecified digestive organs.
Z86.005................... Personal history of in-situ neoplasm of
middle ear and respiratory system.
Z86.006................... Personal history of melanoma in-situ.
------------------------------------------------------------------------
d. Non-Covered Procedure Edit
In the MCE, the Non-Covered Procedure edit identifies procedures
for which Medicare does not provide payment. Payment is not provided
due to specific criteria that are established in the National Coverage
Determination (NCD) process. We refer readers to the website at:
https://www.cms.gov/Medicare/Coverage/Determination Process/
howtorequestanNCD.html for additional information on this process. In
addition, there are procedures that would normally not be paid by
Medicare but, due to the presence of certain diagnoses, are paid.
As discussed in section II.F.15. of the preamble of this proposed
rule, Table 6D.--Invalid Procedure Codes associated with this proposed
rule (which is available via the internet on the CMS website at:
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatient PPS/index.html) lists the procedure codes that are no
longer effective as of October 1, 2019. Included in this table are the
following ICD-10-PCS procedure codes listed on the Non-Covered
Procedure edit code list.
------------------------------------------------------------------------
ICD-10-PCS code Code description
------------------------------------------------------------------------
037G3Z6................... Dilation of intracranial artery,
bifurcation, percutaneous approach.
037G4Z6................... Dilation of intracranial artery,
bifurcation, percutaneous endoscopic
approach.
------------------------------------------------------------------------
We are proposing to remove these codes from the Non-Covered
Procedure edit code list. In addition, as discussed in section
II.F.2.b. of the preamble of this proposed rule, a number of ICD-10-PCS
procedure codes describing bone marrow transplant procedures were the
subject of a proposal discussed at the March 5-6, 2019 ICD-10
Coordination and Maintenance Committee meeting, to be deleted effective
October 1, 2019. We are proposing that if the applicable proposal is
finalized, we would delete the subset of those ICD-10-PCS procedure
codes that are currently listed on the Non-Covered Procedure edit code
list as shown in the following table.
------------------------------------------------------------------------
ICD-10-PCS code Code description
------------------------------------------------------------------------
30250G0................... Transfusion of autologous bone marrow into
peripheral artery, open approach.
30250Y0................... Transfusion of autologous hematopoietic stem
cells into peripheral artery, open
approach.
30253G0................... Transfusion of autologous bone marrow into
peripheral artery, percutaneous approach.
30253Y0................... Transfusion of autologous hematopoietic stem
cells into peripheral artery, percutaneous
approach.
30260G0................... Transfusion of autologous bone marrow into
central artery, open approach.
30260Y0................... Transfusion of autologous hematopoietic stem
cells into central artery, open approach.
30263G0................... Transfusion of autologous bone marrow into
central artery, percutaneous approach.
30263Y0................... Transfusion of autologous hematopoietic stem
cells into central artery, percutaneous
approach.
------------------------------------------------------------------------
e. Future Enhancement
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38053 through
38054), we noted the importance of ensuring accuracy of the coded data
from the reporting, collection, processing, coverage, payment, and
analysis aspects. We have engaged a contractor to assist in the review
of the limited coverage and noncovered procedure edits in the MCE that
may also be present in other claims processing systems that are
utilized by our MACs. The MACs must adhere to criteria specified within
the National Coverage Determinations (NCDs) and may implement their own
edits in addition to what are already incorporated into the MCE,
resulting in duplicate edits. The objective of this review is to
identify where duplicate edits may exist and to determine what the
impact might be if these edits were to be removed from the MCE.
We have noted that the purpose of the MCE is to ensure that errors
and inconsistencies in the coded data are recognized during Medicare
claims processing. As we indicated in the FY 2019 IPPS/LTCH PPS final
rule (83 FR
[[Page 19253]]
41228), we are considering whether the inclusion of coverage edits in
the MCE necessarily aligns with that specific goal because the focus of
coverage edits is on whether or not a particular service is covered for
payment purposes and not whether it was coded correctly.
As we continue to evaluate the purpose and function of the MCE with
respect to ICD-10, we encourage public input for future discussion. As
we have discussed in prior rulemaking, we recognize a need to further
examine the current list of edits and the definitions of those edits.
We continue to encourage public comments on whether there are
additional concerns with the current edits, including specific edits or
language that should be removed or revised, edits that should be
combined, or new edits that should be added to assist in detecting
errors or inaccuracies in the coded data. Comments should be directed
to the MS-DRG Classification Change Mailbox located at:
[email protected] by November 1, 2019 for the FY
2021 rulemaking.
17. Proposed Changes to Surgical Hierarchies
Some inpatient stays entail multiple surgical procedures, each one
of which, occurring by itself, could result in assignment of the case
to a different MS-DRG within the MDC to which the principal diagnosis
is assigned. Therefore, it is necessary to have a decision rule within
the GROUPER by which these cases are assigned to a single MS-DRG. The
surgical hierarchy, an ordering of surgical classes from most resource-
intensive to least resource-intensive, performs that function.
Application of this hierarchy ensures that cases involving multiple
surgical procedures are assigned to the MS-DRG associated with the most
resource-intensive surgical class.
A surgical class can be composed of one or more MS-DRGs. For
example, in MDC 11, the surgical class ``kidney transplant'' consists
of a single MS-DRG (MS-DRG 652) and the class ``major bladder
procedures'' consists of three MS-DRGs (MS-DRGs 653, 654, and 655).
Consequently, in many cases, the surgical hierarchy has an impact on
more than one MS-DRG. The methodology for determining the most
resource-intensive surgical class involves weighting the average
resources for each MS-DRG by frequency to determine the weighted
average resources for each surgical class. For example, assume surgical
class A includes MS-DRGs 001 and 002 and surgical class B includes MS-
DRGs 003, 004, and 005. Assume also that the average costs of MS-DRG
001 are higher than that of MS-DRG 003, but the average costs of MS-
DRGs 004 and 005 are higher than the average costs of MS-DRG 002. To
determine whether surgical class A should be higher or lower than
surgical class B in the surgical hierarchy, we would weigh the average
costs of each MS-DRG in the class by frequency (that is, by the number
of cases in the MS-DRG) to determine average resource consumption for
the surgical class. The surgical classes would then be ordered from the
class with the highest average resource utilization to that with the
lowest, with the exception of ``other O.R. procedures'' as discussed in
this proposed rule.
This methodology may occasionally result in assignment of a case
involving multiple procedures to the lower-weighted MS-DRG (in the
highest, most resource-intensive surgical class) of the available
alternatives. However, given that the logic underlying the surgical
hierarchy provides that the GROUPER search for the procedure in the
most resource-intensive surgical class, in cases involving multiple
procedures, this result is sometimes unavoidable.
We note that, notwithstanding the foregoing discussion, there are a
few instances when a surgical class with a lower average cost is
ordered above a surgical class with a higher average cost. For example,
the ``other O.R. procedures'' surgical class is uniformly ordered last
in the surgical hierarchy of each MDC in which it occurs, regardless of
the fact that the average costs for the MS-DRG or MS-DRGs in that
surgical class may be higher than those for other surgical classes in
the MDC. The ``other O.R. procedures'' class is a group of procedures
that are only infrequently related to the diagnoses in the MDC, but are
still occasionally performed on patients with cases assigned to the MDC
with these diagnoses. Therefore, assignment to these surgical classes
should only occur if no other surgical class more closely related to
the diagnoses in the MDC is appropriate.
A second example occurs when the difference between the average
costs for two surgical classes is very small. We have found that small
differences generally do not warrant reordering of the hierarchy
because, as a result of reassigning cases on the basis of the hierarchy
change, the average costs are likely to shift such that the higher-
ordered surgical class has lower average costs than the class ordered
below it.
Based on the changes that we are proposing to make in this FY 2020
IPPS/LTCH PPS proposed rule, as discussed in section II.F.5. of this
preamble of this proposed rule, we are proposing to revise the surgical
hierarchy for MDC 5 (Diseases and Disorders of the Circulatory System)
as follows: In MDC 5, we are proposing to sequence proposed new MS-DRGs
319 and 320 (Other Endovascular Cardiac Valve Procedures with and
without MCC, respectively) above MS-DRGs 222, 223, 224, 225, 226, and
227 (Cardiac Defibrillator Implant with and without Cardiac
Catheterization with and without AMI/HF/Shock with and without MCC,
respectively) and below MS-DRGs 266 and 267 (Endovascular Cardiac Valve
Replacement with and without MCC, respectively). We also note that, as
discussed in section II.F.5.a. of this preamble of this proposed rule,
we are proposing to revise the titles for MS-DRGs 266 and 267 to
``Endovascular Cardiac Valve Replacement and Supplement Procedures with
MCC'' and ``Endovascular Cardiac Valve Replacement and Supplement
Procedures without MCC'', respectively.
Our proposal for Appendix D--MS-DRG Surgical Hierarchy by MDC and
MS-DRG of the ICD-10 MS-DRG Definitions Manual Version 37 is
illustrated in the following table.
Proposed Surgical Hierarchy: MDC 5
------------------------------------------------------------------------
------------------------------------------------------------------------
MS-DRG 215............................. Other Heart Assist System
Implant.
MS-DRGs 216-221........................ Cardiac Valve and Other Major
Cardiothoracic Procedures.
MS-DRGs 266 and 267.................... Endovascular Cardiac Valve
Procedures.
Proposed New MS-DRGs 319 and 320....... Other Endovascular Cardiac
Valve Procedures.
MS-DRGs 222-227........................ Cardiac Defibrillator Implant.
------------------------------------------------------------------------
[[Page 19254]]
As with other MS-DRG related issues, we encourage commenters to
submit requests to examine ICD-10 claims pertaining to the surgical
hierarchy via the CMS MS-DRG Classification Change Request Mailbox
located at: [email protected] by November 1, 2019
for consideration for FY 2021.
18. Maintenance of the ICD-10-CM and ICD-10-PCS Coding Systems
In September 1985, the ICD-9-CM Coordination and Maintenance
Committee was formed. This is a Federal interdepartmental committee,
co-chaired by the National Center for Health Statistics (NCHS), the
Centers for Disease Control and Prevention (CDC), and CMS, charged with
maintaining and updating the ICD-9-CM system. The final update to ICD-
9-CM codes was made on October 1, 2013. Thereafter, the name of the
Committee was changed to the ICD-10 Coordination and Maintenance
Committee, effective with the March 19-20, 2014 meeting. The ICD-10
Coordination and Maintenance Committee addresses updates to the ICD-10-
CM and ICD-10-PCS coding systems. The Committee is jointly responsible
for approving coding changes, and developing errata, addenda, and other
modifications to the coding systems to reflect newly developed
procedures and technologies and newly identified diseases. The
Committee is also responsible for promoting the use of Federal and non-
Federal educational programs and other communication techniques with a
view toward standardizing coding applications and upgrading the quality
of the classification system.
The official list of ICD-9-CM diagnosis and procedure codes by
fiscal year can be found on the CMS website at: http://cms.hhs.gov/Medicare/Coding/ICD9ProviderDiagnosticCodes/codes.html. The official
list of ICD-10-CM and ICD-10-PCS codes can be found on the CMS website
at: http://www.cms.gov/Medicare/Coding/ICD10/index.html.
The NCHS has lead responsibility for the ICD-10-CM and ICD-9-CM
diagnosis codes included in the Tabular List and Alphabetic Index for
Diseases, while CMS has lead responsibility for the ICD-10-PCS and ICD-
9-CM procedure codes included in the Tabular List and Alphabetic Index
for Procedures.
The Committee encourages participation in the previously mentioned
process by health-related organizations. In this regard, the Committee
holds public meetings for discussion of educational issues and proposed
coding changes. These meetings provide an opportunity for
representatives of recognized organizations in the coding field, such
as the American Health Information Management Association (AHIMA), the
American Hospital Association (AHA), and various physician specialty
groups, as well as individual physicians, health information management
professionals, and other members of the public, to contribute ideas on
coding matters. After considering the opinions expressed at the public
meetings and in writing, the Committee formulates recommendations,
which then must be approved by the agencies.
The Committee presented proposals for coding changes for
implementation in FY 2020 at a public meeting held on September 11-12,
2018, and finalized the coding changes after consideration of comments
received at the meetings and in writing by November 13, 2018.
The Committee held its 2019 meeting on March 5-6, 2019. The
deadline for submitting comments on these code proposals is scheduled
for April 5, 2019. It was announced at this meeting that any new
diagnosis and procedure codes for which there was consensus of public
support and for which complete tabular and indexing changes would be
made by May 2019 would be included in the October 1, 2019 update to the
ICD-10-CM diagnosis and ICD-10-PCS procedure code sets. As discussed in
earlier sections of the preamble of this proposed rule, there are new,
revised, and deleted ICD-10-CM diagnosis codes and ICD-10-PCS procedure
codes that are captured in Table 6A.--New Diagnosis Codes, Table 6B.--
New Procedure Codes, Table 6C.--Invalid Diagnosis Codes, Table 6D.--
Invalid Procedure Codes, Table 6E.--Revised Diagnosis Code Titles, and
Table 6F.--Revised Procedure Code Titles for this proposed rule, which
are available via the internet on the CMS website at: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. The code titles are adopted as part of
the ICD-10 (previously ICD-9-CM) Coordination and Maintenance Committee
process. Therefore, although we make the code titles available for the
IPPS proposed rule, they are not subject to comment in the proposed
rule. Because of the length of these tables, they are not published in
the Addendum to the proposed rule. Rather, they are available via the
internet as discussed in section VI. of the Addendum to this proposed
rule.
Live Webcast recordings of the discussions of the diagnosis and
procedure codes at the Committee's September 11-12, 2018 meeting can be
obtained from the CMS website at: http://cms.hhs.gov/Medicare/Coding/ICD9ProviderDiagnosticCodes/index.html?redirect=/icd9ProviderDiagnosticCodes/03_meetings.asp. The live webcast
recordings of the discussions of the diagnosis and procedure codes at
the Committee's March 5-6, 2019 meeting can be obtained from the CMS
website at: https://www.cms.gov/Medicare/Coding/ICD10/C-and-M-Meeting-Materials.html.
The materials for the discussions relating to diagnosis codes at
the September 11-12 2018 meeting and March 5-6, 2019 meeting can be
found at: http://www.cdc.gov/nchs/icd/icd10cm_maintenance.html. These
websites also provide detailed information about the Committee,
including information on requesting a new code, attending a Committee
meeting, and timeline requirements and meeting dates.
We encourage commenters to address suggestions on coding issues
involving diagnosis codes to: Donna Pickett, Co-Chairperson, ICD-10
Coordination and Maintenance Committee, NCHS, Room 2402, 3311 Toledo
Road, Hyattsville, MD 20782. Comments may be sent by Email to:
[email protected].
Questions and comments concerning the procedure codes should be
submitted via Email to: ICDProcedure [email protected].
In the September 7, 2001 final rule implementing the IPPS new
technology add-on payments (66 FR 46906), we indicated we would attempt
to include proposals for procedure codes that would describe new
technology discussed and approved at the Spring meeting as part of the
code revisions effective the following October.
Section 503(a) of Public Law 108-173 included a requirement for
updating diagnosis and procedure codes twice a year instead of a single
update on October 1 of each year. This requirement was included as part
of the amendments to the Act relating to recognition of new technology
under the IPPS. Section 503(a) amended section 1886(d)(5)(K) of the Act
by adding a clause (vii) which states that the Secretary shall provide
for the addition of new diagnosis and procedure codes on April 1 of
each year, but the addition of such codes shall not require the
Secretary to adjust the payment (or diagnosis-related group
classification) until the fiscal year that begins after such date. This
requirement improves the recognition of new technologies under the IPPS
by providing information on these new technologies
[[Page 19255]]
at an earlier date. Data will be available 6 months earlier than would
be possible with updates occurring only once a year on October 1.
While section 1886(d)(5)(K)(vii) of the Act states that the
addition of new diagnosis and procedure codes on April 1 of each year
shall not require the Secretary to adjust the payment, or DRG
classification, under section 1886(d) of the Act until the fiscal year
that begins after such date, we have to update the DRG software and
other systems in order to recognize and accept the new codes. We also
publicize the code changes and the need for a mid-year systems update
by providers to identify the new codes. Hospitals also have to obtain
the new code books and encoder updates, and make other system changes
in order to identify and report the new codes.
The ICD-10 (previously the ICD-9-CM) Coordination and Maintenance
Committee holds its meetings in the spring and fall in order to update
the codes and the applicable payment and reporting systems by October 1
of each year. Items are placed on the agenda for the Committee meeting
if the request is received at least 3 months prior to the meeting. This
requirement allows time for staff to review and research the coding
issues and prepare material for discussion at the meeting. It also
allows time for the topic to be publicized in meeting announcements in
the Federal Register as well as on the CMS website. A complete addendum
describing details of all diagnosis and procedure coding changes, both
tabular and index, is published on the CMS and NCHS websites in June of
each year. Publishers of coding books and software use this information
to modify their products that are used by health care providers. This
5-month time period has proved to be necessary for hospitals and other
providers to update their systems.
A discussion of this timeline and the need for changes are included
in the December 4-5, 2005 ICD-9-CM Coordination and Maintenance
Committee Meeting minutes. The public agreed that there was a need to
hold the fall meetings earlier, in September or October, in order to
meet the new implementation dates. The public provided comment that
additional time would be needed to update hospital systems and obtain
new code books and coding software. There was considerable concern
expressed about the impact this April update would have on providers.
In the FY 2005 IPPS final rule, we implemented section
1886(d)(5)(K)(vii) of the Act, as added by section 503(a) of Public Law
108-173, by developing a mechanism for approving, in time for the April
update, diagnosis and procedure code revisions needed to describe new
technologies and medical services for purposes of the new technology
add-on payment process. We also established the following process for
making these determinations. Topics considered during the Fall ICD-10
(previously ICD-9-CM) Coordination and Maintenance Committee meeting
are considered for an April 1 update if a strong and convincing case is
made by the requestor at the Committee's public meeting. The request
must identify the reason why a new code is needed in April for purposes
of the new technology process. The participants at the meeting and
those reviewing the Committee meeting materials and live webcast are
provided the opportunity to comment on this expedited request. All
other topics are considered for the October 1 update. Participants at
the Committee meeting are encouraged to comment on all such requests.
There were not any requests approved for an expedited April l, 2019
implementation of a code at the September 11-12, 2018 Committee
meeting. Therefore, there were not any new codes for implementation on
April 1, 2019.
ICD-9-CM addendum and code title information is published on the
CMS website at: http://www.cms.hhs.gov/Medicare/Coding/ICD9ProviderDiagnosticCodes/index.html?redirect=/icd9ProviderDiagnosticCodes/01overview.asp#TopofPage. ICD-10-CM and
ICD-10-PCS addendum and code title information is published on the CMS
website at: http://www.cms.gov/Medicare/Coding/ICD10/index.html. CMS
also sends copies of all ICD-10-CM and ICD-10-PCS coding changes to its
Medicare contractors for use in updating their systems and providing
education to providers.
Information on ICD-10-CM diagnosis codes, along with the Official
ICD-10-CM Coding Guidelines, can also be found on the CDC website at:
http://www.cdc.gov/nchs/icd/icd10.htm. Additionally, information on
new, revised, and deleted ICD-10-CM diagnosis and ICD-10-PCS procedure
codes is provided to the AHA for publication in the Coding Clinic for
ICD-10. AHA also distributes coding update information to publishers
and software vendors.
The following chart shows the number of ICD-10-CM and ICD-10-PCS
codes and code changes since FY 2016 when ICD-10 was implemented.
Total Number of Codes and Changes in Total Number of Codes per Fiscal
Year ICD-10-CM and ICD-10-PCS Codes
------------------------------------------------------------------------
Fiscal year Number Change
------------------------------------------------------------------------
FY 2016:
ICD-10-CM......................................... 69,823 ........
ICD-10-PCS........................................ 71,974 ........
FY 2017:
ICD-10-CM......................................... 71,486 +1,663
ICD-10-PCS........................................ 75,789 +3,815
FY 2018:
ICD-10-CM......................................... 71,704 +218
ICD-10-PCS........................................ 78,705 +2,916
FY 2019:
ICD-10-CM......................................... 71,932 +228
ICD-10-PCS........................................ 78,881 +176
FY 2020 (Proposed):
ICD-10-CM......................................... 72,184 +252
ICD-10-PCS........................................ 77,221 -1,660
------------------------------------------------------------------------
As mentioned previously, the public is provided the opportunity to
comment on any requests for new diagnosis or procedure codes discussed
at the ICD-10 Coordination and Maintenance Committee meeting.
19. Replaced Devices Offered Without Cost or With a Credit
a. Background
In the FY 2008 IPPS final rule with comment period (72 FR 47246
through 47251), we discussed the topic of Medicare payment for devices
that are replaced without cost or where credit for a replaced device is
furnished to the hospital. We implemented a policy to reduce a
hospital's IPPS payment for certain MS-DRGs where the implantation of a
device that subsequently failed or was recalled determined the base MS-
DRG assignment. At that time, we specified that we will reduce a
hospital's IPPS payment for those MS-DRGs where the hospital received a
credit for a replaced device equal to 50 percent or more of the cost of
the device.
In the FY 2012 IPPS/LTCH PPS final rule (76 FR 51556 through
51557), we clarified this policy to state that the policy applies if
the hospital received a credit equal to 50 percent or more of the cost
of the replacement device and issued instructions to hospitals
accordingly.
b. Proposed Changes for FY 2020
As discussed in section II.F.5.a. of the preamble of this proposed
rule, for FY 2020, we are proposing to create new MS-DRGs 319 and 320
(Other Endovascular Cardiac Valve Procedures with and without MCC,
respectively) and to revise the title for MS-DRG 266 from
``Endovascular Cardiac Valve Replacement with MCC'' to
[[Page 19256]]
``Endovascular Cardiac Valve Replacement and Supplement Procedures with
MCC'' and the title for MS-DRG 267 from ``Endovascular Cardiac Valve
Replacement without MCC'' to ``Endovascular Cardiac Valve Replacement
and Supplement Procedures without MCC''.
As stated in the FY 2016 IPPS/LTCH PPS proposed rule (80 FR 24409),
we generally map new MS-DRGs onto the list when they are formed from
procedures previously assigned to MS-DRGs that are already on the list.
Currently, MS-DRGs 216 through 221 are on the list of MS-DRGs subject
to the policy for payment under the IPPS for replaced devices offered
without cost or with a credit as shown in the table below. A subset of
the procedures currently assigned to MS-DRGs 216 through 221 is being
proposed for assignment to proposed new MS-DRGs 319 and 320. Therefore,
we are proposing that if the applicable proposed MS-DRG changes are
finalized, we also would add proposed new MS-DRGs 319 and 320 to the
list of MS-DRGs subject to the policy for payment under the IPPS for
replaced devices offered without cost or with a credit and make
conforming changes to the titles of MS-DRGs 266 and 267 as reflected in
the table below. We also are proposing to continue to include the
existing MS-DRGs currently subject to the policy as also displayed in
the table below.
------------------------------------------------------------------------
MDC MS-DRG MS-DRG title
------------------------------------------------------------------------
Pre-MDC................... 001 Heart Transplant or Implant
of Heart Assist System with
MCC.
Pre-MDC................... 002 Heart Transplant or Implant
of Heart Assist System
without MCC.
1......................... 023 Craniotomy with Major Device
Implant or Acute Complex
CNS Principal Diagnosis
with MCC or Chemotherapy
Implant or Epilepsy with
Neurostimulator.
1......................... 024 Craniotomy with Major Device
Implant or Acute Complex
CNS Principal Diagnosis
without MCC.
1......................... 025 Craniotomy & Endovascular
Intracranial Procedures
with MCC.
1......................... 026 Craniotomy & Endovascular
Intracranial Procedures
with CC.
1......................... 027 Craniotomy & Endovascular
Intracranial Procedures
without CC/MCC.
1......................... 040 Peripheral, Cranial Nerve &
Other Nervous System
Procedures with MCC.
1......................... 041 Peripheral, Cranial Nerve &
Other Nervous System
Procedures with CC or
Peripheral Neurostimulator.
1......................... 042 Peripheral, Cranial Nerve &
Other Nervous System
Procedures without CC/MCC.
3......................... 129 Major Head & Neck Procedures
with CC/MCC or Major
Device.
3......................... 130 Major Head & Neck Procedures
without CC/MCC.
5......................... 215 Other Heart Assist System
Implant.
5......................... 216 Cardiac Valve & Other Major
Cardiothoracic Procedure
with Cardiac
Catheterization with MCC.
5......................... 217 Cardiac Valve & Other Major
Cardiothoracic Procedure
with Cardiac
Catheterization with CC.
5......................... 218 Cardiac Valve & Other Major
Cardiothoracic Procedure
with Cardiac
Catheterization without CC/
MCC.
5......................... 219 Cardiac Valve & Other Major
Cardiothoracic Procedure
without Cardiac
Catheterization with MCC.
5......................... 220 Cardiac Valve & Other Major
Cardiothoracic Procedure
without Cardiac
Catheterization with CC.
5......................... 221 Cardiac Valve & Other Major
Cardiothoracic Procedure
without Cardiac
Catheterization without CC/
MCC.
5......................... 222 Cardiac Defibrillator
Implant with Cardiac
Catheterization with AMI/
Heart Failure/Shock with
MCC.
5......................... 223 Cardiac Defibrillator
Implant with Cardiac
Catheterization with AMI/
Heart Failure/Shock without
MCC.
5......................... 224 Cardiac Defibrillator
Implant with Cardiac
Catheterization without AMI/
Heart Failure/Shock with
MCC.
5......................... 225 Cardiac Defibrillator
Implant with Cardiac
Catheterization without AMI/
Heart Failure/Shock without
MCC.
5......................... 226 Cardiac Defibrillator
Implant without Cardiac
Catheterization with MCC.
5......................... 227 Cardiac Defibrillator
Implant without Cardiac
Catheterization without
MCC.
5......................... 242 Permanent Cardiac Pacemaker
Implant with MCC.
5......................... 243 Permanent Cardiac Pacemaker
Implant with CC.
5......................... 244 Permanent Cardiac Pacemaker
Implant without CC/MCC.
5......................... 245 AICD Generator Procedures.
5......................... 258 Cardiac Pacemaker Device
Replacement with MCC.
5......................... 259 Cardiac Pacemaker Device
Replacement without MCC.
5......................... 260 Cardiac Pacemaker Revision
Except Device Replacement
with MCC.
5......................... 261 Cardiac Pacemaker Revision
Except Device Replacement
with CC.
5......................... 262 Cardiac Pacemaker Revision
Except Device Replacement
without CC/MCC.
5......................... 265 AICD Lead Procedures.
5......................... 266 Endovascular Cardiac Valve
Replacement and Supplement
Procedures with MCC.
5......................... 267 Endovascular Cardiac Valve
Replacement and Supplement
Procedures without MCC.
5......................... 268 Aortic and Heart Assist
Procedures Except Pulsation
Balloon with MCC.
5......................... 269 Aortic and Heart Assist
Procedures Except Pulsation
Balloon without MCC.
5......................... 270 Other Major Cardiovascular
Procedures with MCC.
5......................... 271 Other Major Cardiovascular
Procedures with CC.
5......................... 272 Other Major Cardiovascular
Procedures without CC/MCC.
5......................... 319 Other Endovascular Cardiac
Valve Procedures with MCC.
5......................... 320 Other Endovascular Cardiac
Valve Procedures without
MCC.
8......................... 461 Bilateral or Multiple Major
Joint Procedures of Lower
Extremity with MCC.
8......................... 462 Bilateral or Multiple Major
Joint Procedures of Lower
Extremity without MCC.
8......................... 466 Revision of Hip or Knee
Replacement with MCC.
8......................... 467 Revision of Hip or Knee
Replacement with CC.
8......................... 468 Revision of Hip or Knee
Replacement without CC/MCC.
8......................... 469 Major Hip and Knee Joint
Replacement or Reattachment
of Lower Extremity with MCC
or Total Ankle Replacement.
8......................... 470 Major Hip and Knee Joint
Replacement or Reattachment
of Lower Extremity without
MCC.
------------------------------------------------------------------------
The final list of MS-DRGs subject to the IPPS policy for replaced
devices offered without cost or with a credit will be included in the
FY 2020 IPPS/LTCH PPS final rule and also will be issued to
[[Page 19257]]
providers in the form of a Change Request (CR).
G. Recalibration of the Proposed FY 2020 MS-DRG Relative Weights
1. Data Sources for Developing the Proposed Relative Weights
In developing the proposed FY 2020 system of weights, we are
proposing to use two data sources: Claims data and cost report data. As
in previous years, the claims data source is the MedPAR file. This file
is based on fully coded diagnostic and procedure data for all Medicare
inpatient hospital bills. The FY 2018 MedPAR data used in this proposed
rule include discharges occurring on October 1, 2017, through September
30, 2018, based on bills received by CMS through December 31, 2018,
from all hospitals subject to the IPPS and short-term, acute care
hospitals in Maryland (which at that time were under a waiver from the
IPPS). The FY 2018 MedPAR file used in calculating the proposed
relative weights includes data for approximately 9,480,820 Medicare
discharges from IPPS providers. Discharges for Medicare beneficiaries
enrolled in a Medicare Advantage managed care plan are excluded from
this analysis. These discharges are excluded when the MedPAR ``GHO
Paid'' indicator field on the claim record is equal to ``1'' or when
the MedPAR DRG payment field, which represents the total payment for
the claim, is equal to the MedPAR ``Indirect Medical Education (IME)''
payment field, indicating that the claim was an ``IME only'' claim
submitted by a teaching hospital on behalf of a beneficiary enrolled in
a Medicare Advantage managed care plan. In addition, the December 31,
2018 update of the FY 2018 MedPAR file complies with version 5010 of
the X12 HIPAA Transaction and Code Set Standards, and includes a
variable called ``claim type.'' Claim type ``60'' indicates that the
claim was an inpatient claim paid as fee-for-service. Claim types
``61,'' ``62,'' ``63,'' and ``64'' relate to encounter claims, Medicare
Advantage IME claims, and HMO no-pay claims. Therefore, the calculation
of the proposed relative weights for FY 2020 also excludes claims with
claim type values not equal to ``60.'' The data exclude CAHs, including
hospitals that subsequently became CAHs after the period from which the
data were taken. We note that the proposed FY 2020 relative weights are
based on the ICD-10-CM diagnosis codes and ICD-10-PCS procedure codes
from the FY 2018 MedPAR claims data, grouped through the ICD-10 version
of the proposed FY 2020 GROUPER (Version 37).
The second data source used in the cost-based relative weighting
methodology is the Medicare cost report data files from the HCRIS.
Normally, we use the HCRIS dataset that is 3 years prior to the IPPS
fiscal year. Specifically, we used cost report data from the December
31, 2018 update of the FY 2017 HCRIS for calculating the proposed FY
2020 cost-based relative weights.
2. Methodology for Calculation of the Proposed Relative Weights
As we explain in section II.E.2. of the preamble of this proposed
rule, we calculated the proposed FY 2020 relative weights based on 19
CCRs, as we did for FY 2019. The methodology we are proposing to use to
calculate the FY 2020 MS-DRG cost-based relative weights based on
claims data in the FY 2018 MedPAR file and data from the FY 2017
Medicare cost reports is as follows:
To the extent possible, all the claims were regrouped
using the proposed FY 2020 MS-DRG classifications discussed in sections
II.B. and II.F. of the preamble of this proposed rule.
The transplant cases that were used to establish the
proposed relative weights for heart and heart-lung, liver and/or
intestinal, and lung transplants (MS-DRGs 001, 002, 005, 006, and 007,
respectively) were limited to those Medicare-approved transplant
centers that have cases in the FY 2018 MedPAR file. (Medicare coverage
for heart, heart-lung, liver and/or intestinal, and lung transplants is
limited to those facilities that have received approval from CMS as
transplant centers.)
Organ acquisition costs for kidney, heart, heart-lung,
liver, lung, pancreas, and intestinal (or multivisceral organs)
transplants continue to be paid on a reasonable cost basis. Because
these acquisition costs are paid separately from the prospective
payment rate, it is necessary to subtract the acquisition charges from
the total charges on each transplant bill that showed acquisition
charges before computing the average cost for each MS-DRG and before
eliminating statistical outliers.
Claims with total charges or total lengths of stay less
than or equal to zero were deleted. Claims that had an amount in the
total charge field that differed by more than $30.00 from the sum of
the routine day charges, intensive care charges, pharmacy charges,
implantable devices charges, supplies and equipment charges, therapy
services charges, operating room charges, cardiology charges,
laboratory charges, radiology charges, other service charges, labor and
delivery charges, inhalation therapy charges, emergency room charges,
blood and blood products charges, anesthesia charges, cardiac
catheterization charges, CT scan charges, and MRI charges were also
deleted.
At least 92.3 percent of the providers in the MedPAR file
had charges for 14 of the 19 cost centers. All claims of providers that
did not have charges greater than zero for at least 14 of the 19 cost
centers were deleted. In other words, a provider must have no more than
five blank cost centers. If a provider did not have charges greater
than zero in more than five cost centers, the claims for the provider
were deleted.
Statistical outliers were eliminated by removing all cases
that were beyond 3.0 standard deviations from the geometric mean of the
log distribution of both the total charges per case and the total
charges per day for each MS-DRG.
Effective October 1, 2008, because hospital inpatient
claims include a POA indicator field for each diagnosis present on the
claim, only for purposes of relative weight-setting, the POA indicator
field was reset to ``Y'' for ``Yes'' for all claims that otherwise have
an ``N'' (No) or a ``U'' (documentation insufficient to determine if
the condition was present at the time of inpatient admission) in the
POA field.
Under current payment policy, the presence of specific HAC codes,
as indicated by the POA field values, can generate a lower payment for
the claim. Specifically, if the particular condition is present on
admission (that is, a ``Y'' indicator is associated with the diagnosis
on the claim), it is not a HAC, and the hospital is paid for the higher
severity (and, therefore, the higher weighted MS-DRG). If the
particular condition is not present on admission (that is, an ``N''
indicator is associated with the diagnosis on the claim) and there are
no other complicating conditions, the DRG GROUPER assigns the claim to
a lower severity (and, therefore, the lower weighted MS-DRG) as a
penalty for allowing a Medicare inpatient to contract a HAC. While the
POA reporting meets policy goals of encouraging quality care and
generates program savings, it presents an issue for the relative
weight-setting process. Because cases identified as HACs are likely to
be more complex than similar cases that are not identified as HACs, the
charges associated with HAC cases are likely to be higher as well.
Therefore, if the higher charges of these HAC claims are grouped into
lower severity MS-DRGs prior to the relative
[[Page 19258]]
weight-setting process, the relative weights of these particular MS-
DRGs would become artificially inflated, potentially skewing the
relative weights. In addition, we want to protect the integrity of the
budget neutrality process by ensuring that, in estimating payments, no
increase to the standardized amount occurs as a result of lower overall
payments in a previous year that stem from using weights and case-mix
that are based on lower severity MS-DRG assignments. If this would
occur, the anticipated cost savings from the HAC policy would be lost.
To avoid these problems, we reset the POA indicator field to ``Y''
only for relative weight-setting purposes for all claims that otherwise
have an ``N'' or a ``U'' in the POA field. This resetting ``forced''
the more costly HAC claims into the higher severity MS-DRGs as
appropriate, and the relative weights calculated for each MS-DRG more
closely reflect the true costs of those cases.
In addition, in the FY 2013 IPPS/LTCH PPS final rule, for FY 2013
and subsequent fiscal years, we finalized a policy to treat hospitals
that participate in the Bundled Payments for Care Improvement (BPCI)
initiative the same as prior fiscal years for the IPPS payment modeling
and ratesetting process without regard to hospitals' participation
within these bundled payment models (77 FR 53341 through 53343).
Specifically, because acute care hospitals participating in the BPCI
Initiative still receive IPPS payments under section 1886(d) of the
Act, we include all applicable data from these subsection (d) hospitals
in our IPPS payment modeling and ratesetting calculations as if the
hospitals were not participating in those models under the BPCI
initiative. We refer readers to the FY 2013 IPPS/LTCH PPS final rule
for a complete discussion on our final policy for the treatment of
hospitals participating in the BPCI initiative in our ratesetting
process. For additional information on the BPCI initiative, we refer
readers to the CMS' Center for Medicare and Medicaid Innovation's
website at: http://innovation.cms.gov/initiatives/Bundled-Payments/index.html and to section IV.H.4. of the preamble of the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53341 through 53343).
The participation of hospitals in the BPCI initiative concluded on
September 30, 2018. The participation of hospitals in the Bundled
Payments for Care Improvement (BPCI) Advanced model started on October
1, 2018. The BPCI Advanced model, tested under the authority of section
3021 of the Affordable Care Act (codified at section 1115A of the Act),
is comprised of a single payment and risk track, which bundles payments
for multiple services beneficiaries receive during a Clinical Episode.
Acute care hospitals may participate in BPCI Advanced in one of two
capacities: As a model Participant or as a downstream Episode
Initiator. Regardless of the capacity in which they participate in the
BPCI Advanced model, participating acute care hospitals will continue
to receive IPPS payments under section 1886(d) of the Act. Acute care
hospitals that are Participants also assume financial and quality
performance accountability for Clinical Episodes in the form of a
reconciliation payment. For additional information on the BPCI Advanced
model, we refer readers to the BPCI Advanced web page on the CMS Center
for Medicare and Medicaid Innovation's website at: https://innovation.cms.gov/initiatives/bpci-advanced/. Consistent with our
policy for FY 2019, and consistent with how we have treated hospitals
that participated in the BPCI Initiative, for FY 2020, we continue to
believe it is appropriate to include all applicable data from the
subsection (d) hospitals participating in the BPCI Advanced model in
our IPPS payment modeling and ratesetting calculations because, as
noted above, these hospitals are still receiving IPPS payments under
section 1886(d) of the Act.
The charges for each of the proposed 19 cost groups for each claim
were standardized to remove the effects of differences in proposed area
wage levels, IME and DSH payments, and for hospitals located in Alaska
and Hawaii, the applicable proposed cost-of-living adjustment. Because
hospital charges include charges for both operating and capital costs,
we standardized total charges to remove the effects of differences in
proposed geographic adjustment factors, cost-of-living adjustments, and
DSH payments under the capital IPPS as well. Charges were then summed
by MS-DRG for each of the proposed 19 cost groups so that each MS-DRG
had 19 standardized charge totals. Statistical outliers were then
removed. These charges were then adjusted to cost by applying the
proposed national average CCRs developed from the FY 2017 cost report
data.
The proposed 19 cost centers that we used in the proposed relative
weight calculation are shown in the following table. The table shows
the lines on the cost report and the corresponding revenue codes that
we used to create the proposed 19 national cost center CCRs. If
stakeholders have comments about the groupings in this table, we may
consider those comments as we finalize our policy.
We are inviting public comments on our proposals related to
recalibration of the proposed FY 2020 relative weights and the changes
in relative weights from FY 2019.
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3. Development of Proposed National Average CCRs
We developed the proposed national average CCRs as follows:
Using the FY 2017 cost report data, we removed CAHs, Indian Health
Service hospitals, all-inclusive rate hospitals, and cost reports that
represented time periods of less than 1 year (365 days). We included
hospitals located in Maryland because we include their charges in our
claims database. We then created CCRs for each provider for each cost
center (see prior table for line items used in the calculations) and
removed any CCRs that were greater
[[Page 19272]]
than 10 or less than 0.01. We normalized the departmental CCRs by
dividing the CCR for each department by the total CCR for the hospital
for the purpose of trimming the data. We then took the logs of the
normalized cost center CCRs and removed any cost center CCRs where the
log of the cost center CCR was greater or less than the mean log plus/
minus 3 times the standard deviation for the log of that cost center
CCR. Once the cost report data were trimmed, we calculated a Medicare-
specific CCR. The Medicare-specific CCR was determined by taking the
Medicare charges for each line item from Worksheet D-3 and deriving the
Medicare-specific costs by applying the hospital-specific departmental
CCRs to the Medicare-specific charges for each line item from Worksheet
D-3. Once each hospital's Medicare-specific costs were established, we
summed the total Medicare-specific costs and divided by the sum of the
total Medicare-specific charges to produce national average, charge-
weighted CCRs.
After we multiplied the total charges for each MS-DRG in each of
the proposed 19 cost centers by the corresponding national average CCR,
we summed the 19 ``costs'' across each proposed MS-DRG to produce a
total standardized cost for the proposed MS-DRG. The average
standardized cost for each proposed MS-DRG was then computed as the
total standardized cost for the proposed MS-DRG divided by the
transfer-adjusted case count for the proposed MS-DRG. The average cost
for each proposed MS-DRG was then divided by the national average
standardized cost per case to determine the proposed relative weight.
The proposed FY 2020 cost-based relative weights were then
normalized by a proposed adjustment factor of 1.788337 so that the
average case weight after recalibration was equal to the average case
weight before recalibration. The proposed normalization adjustment is
intended to ensure that recalibration by itself neither increases nor
decreases total payments under the IPPS, as required by section
1886(d)(4)(C)(iii) of the Act.
The proposed 19 national average CCRs for FY 2020 are as follows:
------------------------------------------------------------------------
Group CCR
------------------------------------------------------------------------
Routine Days............................................ 0.433
Intensive Days.......................................... 0.362
Drugs................................................... 0.191
Supplies & Equipment.................................... 0.301
Implantable Devices..................................... 0.308
Therapy Services........................................ 0.297
Laboratory.............................................. 0.109
Operating Room.......................................... 0.175
Cardiology.............................................. 0.099
Cardiac Catheterization................................. 0.106
Radiology............................................... 0.140
MRIs.................................................... 0.073
CT Scans................................................ 0.035
Emergency Room.......................................... 0.154
Blood and Blood Products................................ 0.282
Other Services.......................................... 0.344
Labor & Delivery........................................ 0.369
Inhalation Therapy...................................... 0.151
Anesthesia.............................................. 0.077
------------------------------------------------------------------------
Since FY 2009, the relative weights have been based on 100 percent
cost weights based on our MS-DRG grouping system.
When we recalibrated the DRG weights for previous years, we set a
threshold of 10 cases as the minimum number of cases required to
compute a reasonable weight. We are proposing to use that same case
threshold in recalibrating the proposed MS-DRG relative weights for FY
2020. Using data from the FY 2018 MedPAR file, there were 8 MS-DRGs
that contain fewer than 10 cases. For FY 2020, because we do not have
sufficient MedPAR data to set accurate and stable cost relative weights
for these low-volume MS-DRGs, we are proposing to compute relative
weights for the proposed low-volume MS-DRGs by adjusting their final FY
2019 relative weights by the percentage change in the average weight of
the cases in other MS-DRGs from FY 2019 to FY 2020. The crosswalk table
is shown below.
------------------------------------------------------------------------
Low-volume MS-DRG MS-DRG title Crosswalk to MS-DRG
------------------------------------------------------------------------
338...................... Appendectomy with Final FY 2019 relative
Complicated weight (adjusted by
Principal percent change in
Diagnosis with MCC. average weight of the
cases in other MS-
DRGs).
789...................... Neonates, Died or Final FY 2019 relative
Transferred to weight (adjusted by
Another Acute Care percent change in
Facility. average weight of the
cases in other MS-
DRGs).
790...................... Extreme Immaturity Final FY 2019 relative
or Respiratory weight (adjusted by
Distress Syndrome, percent change in
Neonate. average weight of the
cases in other MS-
DRGs).
791...................... Prematurity with Final FY 2019 relative
Major Problems. weight (adjusted by
percent change in
average weight of the
cases in other MS-
DRGs).
792...................... Prematurity without Final FY 2019 relative
Major Problems. weight (adjusted by
percent change in
average weight of the
cases in other MS-
DRGs).
793...................... Full-Term Neonate Final FY 2019 relative
with Major weight (adjusted by
Problems. percent change in
average weight of the
cases in other MS-
DRGs).
794...................... Neonate with Other Final FY 2019 relative
Significant weight (adjusted by
Problems. percent change in
average weight of the
cases in other MS-
DRGs).
795...................... Normal Newborn..... Final FY 2019 relative
weight (adjusted by
percent change in
average weight of the
cases in other MS-
DRGs).
------------------------------------------------------------------------
H. Proposed Add-On Payments for New Services and Technologies for FY
2020
1. Background
Sections 1886(d)(5)(K) and (L) of the Act establish a process of
identifying and ensuring adequate payment for new medical services and
technologies (sometimes collectively referred to in this section as
``new technologies'') under the IPPS. Section 1886(d)(5)(K)(vi) of the
Act specifies that a medical service or technology will be considered
new if it meets criteria established by the Secretary after notice and
opportunity for public comment. Section 1886(d)(5)(K)(ii)(I) of the Act
specifies that a new medical service or technology may be considered
for new technology add-on payment if, based on the estimated costs
incurred with respect to discharges involving such service or
technology, the DRG prospective payment rate otherwise applicable to
such discharges under this subsection is inadequate. We note that,
beginning with discharges occurring in FY 2008, CMS transitioned from
CMS-DRGs to MS-DRGs. The regulations at 42 CFR 412.87 implement these
provisions and specify three criteria for a new medical service or
technology to receive the additional payment: (1) The medical service
or technology must be new; (2) the medical service or technology must
be costly such that the
[[Page 19273]]
DRG rate otherwise applicable to discharges involving the medical
service or technology is determined to be inadequate; and (3) the
service or technology must demonstrate a substantial clinical
improvement over existing services or technologies. Below we highlight
some of the major statutory and regulatory provisions relevant to the
new technology add-on payment criteria, as well as other information.
For a complete discussion on the new technology add-on payment
criteria, we refer readers to the FY 2012 IPPS/LTCH PPS final rule (76
FR 51572 through 51574).
Under the first criterion, as reflected in Sec. 412.87(b)(2), a
specific medical service or technology will be considered ``new'' for
purposes of new medical service or technology add-on payments until
such time as Medicare data are available to fully reflect the cost of
the technology in the MS-DRG weights through recalibration. We note
that we do not consider a service or technology to be new if it is
substantially similar to one or more existing technologies. That is,
even if a medical product receives a new FDA approval or clearance, it
may not necessarily be considered ``new'' for purposes of new
technology add-on payments if it is ``substantially similar'' to
another medical product that was approved or cleared by FDA and has
been on the market for more than 2 to 3 years. In the FY 2010 IPPS/RY
2010 LTCH PPS final rule (74 FR 43813 through 43814), we established
criteria for evaluating whether a new technology is substantially
similar to an existing technology, specifically: (1) Whether a product
uses the same or a similar mechanism of action to achieve a therapeutic
outcome; (2) whether a product is assigned to the same or a different
MS-DRG; and (3) whether the new use of the technology involves the
treatment of the same or similar type of disease and the same or
similar patient population. If a technology meets all three of these
criteria, it would be considered substantially similar to an existing
technology and would not be considered ``new'' for purposes of new
technology add-on payments. For a detailed discussion of the criteria
for substantial similarity, we refer readers to the FY 2006 IPPS final
rule (70 FR 47351 through 47352), and the FY 2010 IPPS/LTCH PPS final
rule (74 FR 43813 through 43814).
Under the second criterion, Sec. 412.87(b)(3) further provides
that, to be eligible for the add-on payment for new medical services or
technologies, the MS-DRG prospective payment rate otherwise applicable
to discharges involving the new medical service or technology must be
assessed for adequacy. Under the cost criterion, consistent with the
formula specified in section 1886(d)(5)(K)(ii)(I) of the Act, to assess
the adequacy of payment for a new technology paid under the applicable
MS-DRG prospective payment rate, we evaluate whether the charges for
cases involving the new technology exceed certain threshold amounts.
The MS-DRG threshold amounts used in evaluating new technology add-on
payment applications for FY 2020 are presented in a data file that is
available, along with the other data files associated with the FY 2019
IPPS/LTCH PPS final rule and correction notice, on the CMS website at:
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/FY2019-IPPS-Final-Rule-Home-Page-Items/FY2019-IPPS-Final-Rule-Data-Files.html?DLPage=1&DLEntries=10&DLSort=0&DLSortDir=ascending. As
finalized in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41275),
beginning with FY 2020, we include the thresholds applicable to the
next fiscal year (previously included in Table 10 of the annual IPPS/
LTCH PPS proposed and final rules) in the data files associated with
the prior fiscal year. Accordingly, the proposed thresholds for
applications for new technology add-on payments for FY 2021 are
presented in a data file that is available on the CMS website, along
with the other data files associated with this FY 2020 proposed rule,
by clicking on the FY 2020 IPPS Proposed Rule Home Page at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.
In the September 7, 2001 final rule that established the new
technology add-on payment regulations (66 FR 46917), we discussed the
issue of whether the Health Insurance Portability and Accountability
Act (HIPAA) Privacy Rule at 45 CFR parts 160 and 164 applies to claims
information that providers submit with applications for new medical
service or technology add-on payments. We refer readers to the FY 2012
IPPS/LTCH PPS final rule (76 FR 51573) for complete information on this
issue.
Under the third criterion, Sec. 412.87(b)(1) of our existing
regulations provides that a new technology is an appropriate candidate
for an additional payment when it represents an advance that
substantially improves, relative to technologies previously available,
the diagnosis or treatment of Medicare beneficiaries. For example, a
new technology represents a substantial clinical improvement when it
reduces mortality, decreases the number of hospitalizations or
physician visits, or reduces recovery time compared to the technologies
previously available. (We refer readers to the September 7, 2001 final
rule for a more detailed discussion of this criterion (66 FR 46902). We
also refer readers to section II.H.8. of the preamble of this proposed
rule for a discussion of our proposed alternative inpatient new
technology add-on payment pathway for transformative new devices.)
The new medical service or technology add-on payment policy under
the IPPS provides additional payments for cases with relatively high
costs involving eligible new medical services or technologies, while
preserving some of the incentives inherent under an average-based
prospective payment system. The payment mechanism is based on the cost
to hospitals for the new medical service or technology. Under Sec.
412.88, if the costs of the discharge (determined by applying cost-to-
charge ratios (CCRs) as described in Sec. 412.84(h)) exceed the full
DRG payment (including payments for IME and DSH, but excluding outlier
payments), Medicare will make an add-on payment equal to the lesser of:
(1) 50 percent of the estimated costs of the new technology or medical
service (if the estimated costs for the case including the new
technology or medical service exceed Medicare's payment); or (2) 50
percent of the difference between the full DRG payment and the
hospital's estimated cost for the case. Unless the discharge qualifies
for an outlier payment, the additional Medicare payment is limited to
the full MS-DRG payment plus 50 percent of the estimated costs of the
new technology or medical service. We refer readers to section II.H.9.
of the preamble of this proposed rule for a discussion of our proposed
change to the calculation of the new technology add-on payment
beginning in FY 2020, including our proposed amendments to Sec. 412.88
of the regulations.
Section 503(d)(2) of Public Law 108-173 provides that there shall
be no reduction or adjustment in aggregate payments under the IPPS due
to add-on payments for new medical services and technologies.
Therefore, in accordance with section 503(d)(2) of Public Law 108-173,
add-on payments for new medical services or technologies for FY 2005
and later years have not been subjected to budget neutrality.
In the FY 2009 IPPS final rule (73 FR 48561 through 48563), we
modified our regulations at Sec. 412.87 to codify our longstanding
practice of how CMS evaluates the eligibility criteria for new
[[Page 19274]]
medical service or technology add-on payment applications. That is, we
first determine whether a medical service or technology meets the
newness criterion, and only if so, do we then make a determination as
to whether the technology meets the cost threshold and represents a
substantial clinical improvement over existing medical services or
technologies. We amended Sec. 412.87(c) to specify that all applicants
for new technology add-on payments must have FDA approval or clearance
by July 1 of the year prior to the beginning of the fiscal year for
which the application is being considered.
The Council on Technology and Innovation (CTI) at CMS oversees the
agency's cross-cutting priority on coordinating coverage, coding and
payment processes for Medicare with respect to new technologies and
procedures, including new drug therapies, as well as promoting the
exchange of information on new technologies and medical services
between CMS and other entities. The CTI, composed of senior CMS staff
and clinicians, was established under section 942(a) of Public Law 108-
173. The Council is co-chaired by the Director of the Center for
Clinical Standards and Quality (CCSQ) and the Director of the Center
for Medicare (CM), who is also designated as the CTI's Executive
Coordinator.
The specific processes for coverage, coding, and payment are
implemented by CM, CCSQ, and the local Medicare Administrative
Contractors (MACs) (in the case of local coverage and payment
decisions). The CTI supplements, rather than replaces, these processes
by working to assure that all of these activities reflect the agency-
wide priority to promote high-quality, innovative care. At the same
time, the CTI also works to streamline, accelerate, and improve
coordination of these processes to ensure that they remain up to date
as new issues arise. To achieve its goals, the CTI works to streamline
and create a more transparent coding and payment process, improve the
quality of medical decisions, and speed patient access to effective new
treatments. It is also dedicated to supporting better decisions by
patients and doctors in using Medicare-covered services through the
promotion of better evidence development, which is critical for
improving the quality of care for Medicare beneficiaries.
To improve the understanding of CMS' processes for coverage,
coding, and payment and how to access them, the CTI has developed an
``Innovator's Guide'' to these processes. The intent is to consolidate
this information, much of which is already available in a variety of
CMS documents and in various places on the CMS website, in a user
friendly format. This guide was published in 2010 and is available on
the CMS website at: https://www.cms.gov/Medicare/Coverage/CouncilonTechInnov/Downloads/Innovators-Guide-Master-7-23-15.pdf.
As we indicated in the FY 2009 IPPS final rule (73 FR 48554), we
invite any product developers or manufacturers of new medical services
or technologies to contact the agency early in the process of product
development if they have questions or concerns about the evidence that
would be needed later in the development process for the agency's
coverage decisions for Medicare.
The CTI aims to provide useful information on its activities and
initiatives to stakeholders, including Medicare beneficiaries,
advocates, medical product manufacturers, providers, and health policy
experts. Stakeholders with further questions about Medicare's coverage,
coding, and payment processes, or who want further guidance about how
they can navigate these processes, can contact the CTI at
[email protected].
We note that applicants for add-on payments for new medical
services or technologies for FY 2021 must submit a formal request,
including a full description of the clinical applications of the
medical service or technology and the results of any clinical
evaluations demonstrating that the new medical service or technology
represents a substantial clinical improvement, along with a significant
sample of data to demonstrate that the medical service or technology
meets the high-cost threshold. Complete application information, along
with final deadlines for submitting a full application, will be posted
as it becomes available on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/newtech.html. To allow interested parties to identify the new medical
services or technologies under review before the publication of the
proposed rule for FY 2021, the CMS website also will post the tracking
forms completed by each applicant. We note that the burden associated
with this information collection requirement is the time and effort
required to collect and submit the data in the formal request for add-
on payments for new medical services and technologies to CMS. The
aforementioned burden is subject to the PRA; it is currently approved
under OMB control number 0938-1347, which expires on December 31, 2020.
2. Public Input Before Publication of a Notice of Proposed Rulemaking
on Add-On Payments
Section 1886(d)(5)(K)(viii) of the Act, as amended by section
503(b)(2) of Public Law 108-173, provides for a mechanism for public
input before publication of a notice of proposed rulemaking regarding
whether a medical service or technology represents a substantial
clinical improvement or advancement. The process for evaluating new
medical service and technology applications requires the Secretary to--
Provide, before publication of a proposed rule, for public
input regarding whether a new service or technology represents an
advance in medical technology that substantially improves the diagnosis
or treatment of Medicare beneficiaries;
Make public and periodically update a list of the services
and technologies for which applications for add-on payments are
pending;
Accept comments, recommendations, and data from the public
regarding whether a service or technology represents a substantial
clinical improvement; and
Provide, before publication of a proposed rule, for a
meeting at which organizations representing hospitals, physicians,
manufacturers, and any other interested party may present comments,
recommendations, and data regarding whether a new medical service or
technology represents a substantial clinical improvement to the
clinical staff of CMS.
In order to provide an opportunity for public input regarding add-
on payments for new medical services and technologies for FY 2020 prior
to publication of this FY 2020 IPPS/LTCH PPS proposed rule, we
published a notice in the Federal Register on October 5, 2018 (83 FR
50379), and held a town hall meeting at the CMS Headquarters Office in
Baltimore, MD, on December 4, 2018. In the announcement notice for the
meeting, we stated that the opinions and presentations provided during
the meeting would assist us in our evaluations of applications by
allowing public discussion of the substantial clinical improvement
criterion for each of the FY 2020 new medical service and technology
add-on payment applications before the publication of the FY 2020 IPPS/
LTCH PPS proposed rule.
Approximately 100 individuals registered to attend the town hall
meeting in person, while additional individuals listened over an open
[[Page 19275]]
telephone line. We also live-streamed the town hall meeting and posted
the morning and afternoon sessions of the town hall on the CMS YouTube
web page at: https://www.youtube.com/watch?v=4z1AhEuGHqQ and https://www.youtube.com/watch?v=m26Xj1EzbIY, respectively. We considered each
applicant's presentation made at the town hall meeting, as well as
written comments submitted on the applications that were received by
the due date of December 14, 2018, in our evaluation of the new
technology add-on payment applications for FY 2020 in this FY 2020
IPPS/LTCH PPS proposed rule.
In response to the published notice and the December 4, 2018 New
Technology Town Hall meeting, we received written comments regarding
the applications for FY 2020 new technology add-on payments. We note
that we do not summarize comments that are unrelated to the
``substantial clinical improvement'' criterion. As explained earlier
and in the Federal Register notice announcing the New Technology Town
Hall meeting (83 FR 50379 through 50381), the purpose of the meeting
was specifically to discuss the substantial clinical improvement
criterion in regard to pending new technology add-on payment
applications for FY 2020. Therefore, we are not summarizing those
written comments in this proposed rule that are unrelated to the
substantial clinical improvement criterion. In section II.H.5. of the
preamble of this FY 2020 IPPS/LTCH PPS proposed rule, we are
summarizing comments regarding individual applications, or, if
applicable, indicating that there were no comments received in response
to the New Technology Town Hall meeting notice, at the end of each
discussion of the individual applications.
Comment: One commenter expressed appreciation for CMS' statements
in the FY 2019 IPPS/LTCH PPS proposed rule (83 FR 20278 through 20279)
relating to the similarity between data that satisfy the FDA's
designations and data that satisfy the substantial clinical improvement
criterion under the new technology add-on payment policy. The commenter
stated that clarity was provided that will help future applicants
understand which types of data can serve as the foundation for
satisfying the substantial clinical improvement criterion. The
commenter also expressed its appreciation that CMS further clarified
that it accepts a wide range of data that would support the conclusion
that the technology represents a substantial clinical improvement. The
commenter explained that it interpreted CMS' statements to mean that
CMS appreciates and considers the patient's experience and point-of-
view in its determination of a technology's substantial clinical
improvement with respect to existing technologies, and stated that it
hopes the agency will confirm this rationale in upcoming rulemaking.
Response: We appreciate the commenter's support of our clarifying
statements in the FY 2019 IPPS/LTCH PPS proposed rule. Additionally, we
refer the commenter to the September 7, 2001 final rule for a more
detailed discussion of the substantial clinical improvement criterion
(66 FR 46902). We also refer readers to section II.H.8. of the preamble
of this proposed rule for a discussion of our proposed alternative
inpatient new technology add-on payment pathway for transformative new
devices, and sections II.H.6. and II.H.7. of the preamble of this
proposed rule for a discussion of and request for comment on potential
revisions to the new technology add-on payment substantial clinical
improvement criterion.
Comment: Another commenter stated that the criteria for priority
FDA review are very similar to the criteria to substantiate a
technology's substantial clinical improvement under the new technology
add-on payment policy and, therefore, devices used in the inpatient
setting that are determined to be eligible for expedited review and
approved by the FDA should automatically be considered as representing
a substantial clinical improvement with respect to existing
technologies, without further consideration by CMS.
Response: We refer readers to our response to this and similar
comments in the FY 2019 IPPS/LTCH PPS proposed rule (83 FR 20278
through 20279).
Comment: One commenter stated that an entity submitting an
application for new technology add-on payments should be entitled to
administrative review of an adverse determination by an official of the
Department of Health and Human Services other than an official of the
CMS. The commenter believed that this will provide a safeguard both for
the manufacturer submitting an application, as well as for
beneficiaries who would benefit from access to the innovative
technology that is the subject of the new technology add-on payment
application. The commenter further recommended that administrative
review of an adverse determination should not preclude resubmission of
a modified application at a later point in the future.
Response: As discussed previously, the public has an opportunity at
the New Technology Town Hall meeting to provide input regarding the
substantial clinical improvement criterion for each new technology add-
on payment application under review for the upcoming fiscal year. We
summarize each application in the IPPS/LTCH PPS proposed rule, and
consider the public comments received in response to the proposed rule
in determining whether to approve an application for new technology
add-on payments. Furthermore, we also accept additional supplemental
information on all new technology add-on payment applications
summarized in the proposed rule through the end of the comment period
for the annual IPPS/LTCH PPS proposed rule. We conduct a thorough
review of all applications and, as described above, allow a wide range
of data that would support the conclusion of a representation of
substantial clinical improvement. We also note that an applicant may
always resubmit an application for new technology add-on payments for a
subsequent year following a denial of an application submitted for a
prior fiscal year.
3. ICD-10-PCS Section ``X'' Codes for Certain New Medical Services and
Technologies
As discussed in the FY 2016 IPPS/LTCH PPS final rule (80 FR 49434),
the ICD-10-PCS includes a new section containing the new Section ``X''
codes, which began being used with discharges occurring on or after
October 1, 2015. Decisions regarding changes to ICD-10-PCS Section
``X'' codes will be handled in the same manner as the decisions for all
of the other ICD-10-PCS code changes. That is, proposals to create,
delete, or revise Section ``X'' codes under the ICD-10-PCS structure
will be referred to the ICD-10 Coordination and Maintenance Committee.
In addition, several of the new medical services and technologies that
have been, or may be, approved for new technology add-on payments may
now, and in the future, be assigned a Section ``X'' code within the
structure of the ICD-10-PCS. We posted ICD-10-PCS Guidelines on the CMS
website at: http://www.cms.gov/Medicare/Coding/ICD10/2016-ICD-10-PCS-and-GEMs.html, including guidelines for ICD-10-PCS Section ``X'' codes.
We encourage providers to view the material provided on ICD-10-PCS
Section ``X'' codes.
[[Page 19276]]
4. Proposed FY 2020 Status of Technologies Approved for FY 2019 New
Technology Add-On Payments
a. Defitelio[supreg] (Defibrotide)
Jazz Pharmaceuticals submitted an application for new technology
add-on payments for FY 2017 for defibrotide (Defitelio[supreg]), a
treatment for patients who have been diagnosed with hepatic veno-
occlusive disease (VOD) with evidence of multi-organ dysfunction. VOD,
also known as sinusoidal obstruction syndrome (SOS), is a potentially
life-threatening complication of hematopoietic stem cell
transplantation (HSCT), with an incidence rate of 8 percent to 15
percent. Diagnoses of VOD range in severity from what has been
classically defined as a disease limited to the liver (mild) and
reversible, to a severe syndrome associated with multi-organ
dysfunction or failure and death. Patients who have received treatment
involving HSCT who develop VOD with multi-organ failure face an
immediate risk of death, with a mortality rate of more than 80 percent
when only supportive care is used. The applicant asserted that
Defitelio[supreg] improves the survival rate of patients who have been
diagnosed with VOD with multi-organ failure by 23 percent.
Defitelio[supreg] received Orphan Drug Designation for the
treatment of VOD in 2003 and for the prevention of VOD in 2007. It has
been available to patients as an investigational drug through an
Expanded Access Program since 2006. The applicant's New Drug
Application (NDA) for Defitelio[supreg] received FDA approval on March
30, 2016. The applicant confirmed that Defitelio[supreg] was not
available on the U.S. market as of the FDA NDA approval date of March
30, 2016. According to the applicant, commercial packaging could not be
completed until the label for Defitelio[supreg] was finalized with FDA
approval, and that commercial shipments of Defitelio[supreg] to
hospitals and treatment centers began on April 4, 2016. Therefore, we
agreed that, based on this information, the newness period for
Defitelio[supreg] begins on April 4, 2016, the date of its first
commercial availability.
The applicant received approval to use unique ICD-10-PCS procedure
codes to describe the use of Defitelio[supreg], with an effective date
of October 1, 2016. The approved ICD-10-PCS procedure codes are:
XW03392 (Introduction of defibrotide sodium anticoagulant into
peripheral vein, percutaneous approach); and XW04392 (Introduction of
defibrotide sodium anticoagulant into central vein, percutaneous
approach). After evaluation of the newness, costs, and substantial
clinical improvement criteria for new technology add-on payments for
Defitelio[supreg] and consideration of the public comments we received
in response to the FY 2017 IPPS/LTCH PPS proposed rule, we approved
Defitelio[supreg] for new technology add-on payments for FY 2017 (81 FR
56906). With the new technology add-on payment application, the
applicant estimated that the average Medicare beneficiary would require
a dosage of 25 mg/kg/day for a minimum of 21 days of treatment. The
recommended dose is 6.25 mg/kg given as a 2-hour intravenous infusion
every 6 hours. Dosing should be based on a patient's baseline body
weight, which is assumed to be 70 kg for an average adult patient. All
vials contain 200 mg at a cost of $825 per vial. Therefore, we
determined that cases involving the use of the Defitelio[supreg]
technology would incur an average cost per case of $151,800 (70 kg
adult x 25 mg/kg/day x 21 days = 36,750 mg per patient/200 mg vial =
184 vials per patient x $825 per vial = $151,800). Under existing Sec.
412.88(a)(2), we limit new technology add-on payments to the lesser of
50 percent of the average cost of the technology or 50 percent of the
costs in excess of the MS-DRG payment for the case. As a result, the
maximum new technology add-on payment amount for a case involving the
use of Defitelio[supreg] is $75,900 for FY 2019.
Our policy is that a medical service or technology may continue to
be considered ``new'' for purposes of new technology add-on payments
within 2 or 3 years after the point at which data begin to become
available reflecting the inpatient hospital code assigned to the new
service or technology. Our practice has been to begin and end new
technology add-on payments on the basis of a fiscal year, and we have
generally followed a guideline that uses a 6-month window before and
after the start of the fiscal year to determine whether to extend the
new technology add-on payment for an additional fiscal year. In
general, we extend new technology add-on payments for an additional
year only if the 3-year anniversary date of the product's entry onto
the U.S. market occurs in the latter half of the fiscal year (70 FR
47362).
With regard to the newness criterion for Defitelio[supreg], we
considered the beginning of the newness period to commence on the first
day Defitelio[supreg] was commercially available (April 4, 2016).
Because the 3-year anniversary date of the entry of the
Defitelio[supreg] onto the U.S. market (April 4, 2019) will occur
during FY 2019, we are proposing to discontinue new technology add-on
payments for this technology for FY 2020. We are inviting public
comments on our proposal to discontinue new technology add-on payments
for Defitelio[supreg] for FY 2020.
b. Ustekinumab (Stelara[supreg])
Janssen Biotech submitted an application for new technology add-on
payments for the Stelara[supreg] induction therapy for FY 2018.
Stelara[supreg] received FDA approval on September 23, 2016 as an
intravenous (IV) infusion treatment for adult patients who have been
diagnosed with moderately to severely active Crohn's disease (CD) who
have failed or were intolerant to treatment using immunomodulators or
corticosteroids, but never failed a tumor necrosis factor (TNF)
blocker, or failed or were intolerant to treatment using one or more
TNF blockers. Stelara[supreg] IV is intended for induction--
subcutaneous prefilled syringes are intended for maintenance dosing.
Stelara[supreg] must be administered intravenously by a health care
professional in either an inpatient hospital setting or an outpatient
hospital setting.
Stelara[supreg] for IV infusion is packaged in single 130 mg vials.
Induction therapy consists of a single IV infusion dose using the
following weight-based dosing regimen: Patients weighing 55 kg or less
than () 55 kg, but 85 kg or less than () 85 kg are administered 520 mg of Stelara[supreg]
(4 vials). An average dose of Stelara[supreg] administered through IV
infusion is 390 mg (3 vials). Maintenance doses of Stelara[supreg] are
administered at 90 mg, subcutaneously, at 8-week intervals and may
occur in the outpatient hospital setting.
CD is an inflammatory bowel disease of unknown etiology,
characterized by transmural inflammation of the gastrointestinal (GI)
tract. Symptoms of CD may include fatigue, prolonged diarrhea with or
without bleeding, abdominal pain, weight loss and fever. CD can affect
any part of the GI tract including the mouth, esophagus, stomach, small
intestine, and large intestine. Most commonly used pharmacologic
treatments for CD include antibiotics, mesalamines, corticosteroids,
immunomodulators, tumor necrosis alpha (TNF[alpha]) inhibitors, and
anti-integrin agents. Surgery may be necessary for some patients who
have been diagnosed with CD in which conventional therapies have
failed. After evaluation of the newness, costs,
[[Page 19277]]
and substantial clinical improvement criteria for new technology add-on
payments for Stelara[supreg] and consideration of the public comments
we received in response to the FY 2018 IPPS/LTCH PPS proposed rule, we
approved Stelara[supreg] for new technology add-on payments for FY 2018
(82 FR 38129). Cases involving Stelara[supreg] that are eligible for
new technology add-on payments are identified by ICD-10-PCS procedure
code XW033F3 (Introduction of other New Technology therapeutic
substance into peripheral vein, percutaneous approach, new technology
group 3). With the new technology add-on payment application, the
applicant estimated that the average Medicare beneficiary would require
a dosage of 390 mg (3 vials) at a hospital acquisition cost of $1,600
per vial (for a total of $4,800). Under existing Sec. 412.88(a)(2), we
limit new technology add-on payments to the lesser of 50 percent of the
average cost of the technology or 50 percent of the costs in excess of
the MS-DRG payment for the case. As a result, the maximum new
technology add-on payment amount for a case involving the use of
Stelara[supreg] is $2,400 for FY 2019.
With regard to the newness criterion for Stelara[supreg], we
considered the beginning of the newness period to commence when
Stelara[supreg] received FDA approval as an IV infusion treatment for
Crohn's disease (CD) on September 23, 2016. Because the 3-year
anniversary date of the entry of Stelara[supreg] onto the U.S. market
(September 23, 2019) will occur during FY 2019, we are proposing to
discontinue new technology add-on payments for this technology for FY
2020. We are inviting public comments on our proposal to discontinue
new technology add-on payments for Stelara[supreg] for FY 2020.
c. Bezlotoxumab (ZINPLAVATM)
Merck & Co., Inc. submitted an application for new technology add-
on payments for ZINPLAVATM for FY 2018.
ZINPLAVATM is indicated as a treatment to reduce recurrence
of Clostridium difficile infection (CDI) in adult patients who are
receiving antibacterial drug treatment for a diagnosis of CDI and who
are at high risk for CDI recurrence. ZINPLAVATM is not
indicated for the treatment of the presenting episode of CDI and is not
an antibacterial drug. ZINPLAVATM should only be used in
conjunction with an antibacterial drug treatment for CDI.
Clostridium difficile (C-diff) is a disease-causing anaerobic,
spore forming bacterium that affects the gastrointestinal (GI) tract.
Some people carry the C-diff bacterium in their intestines, but never
develop symptoms of an infection. The difference between asymptomatic
colonization and disease is caused primarily by the production of an
enterotoxin (Toxin A) and/or a cytotoxin (Toxin B). The presence of
either or both toxins can lead to symptomatic CDI, which is defined as
the acute onset of diarrhea with a documented infection with toxigenic
C-diff. The GI tract contains millions of bacteria, commonly referred
to as ``normal flora'' or ``good bacteria,'' which play a role in
protecting the body from infection. Antibiotics can kill these good
bacteria and allow C-diff to multiply and release toxins that damage
the cells lining the intestinal wall, resulting in a CDI. CDI is a
leading cause of hospital-associated gastrointestinal illnesses.
Persons at increased risk for CDI include people who are currently on
or who have recently been treated with antibiotics, people who have
encountered current or recent hospitalization, people who are older
than 65 years, immunocompromised patients, and people who have recently
had a diagnosis of CDI. CDI symptoms include, but are not limited to,
diarrhea, abdominal pain, and fever. CDI symptoms range in severity
from mild (abdominal discomfort, loose stools) to severe (profuse,
watery diarrhea, severe abdominal pain, and high fevers). Severe CDI
can be life-threatening and, in rare cases, can cause bowel rupture,
sepsis and organ failure. CDI is responsible for 14,000 deaths per year
in the United States.
C-diff produces two virulent, pro-inflammatory toxins, Toxin A and
Toxin B, which target host colonic endothelial cells by binding to
endothelial cell surface receptors via combined repetitive oligopeptide
(CROP) domains. These toxins cause the release of inflammatory
cytokines leading to intestinal fluid secretion and intestinal
inflammation. The applicant asserted that ZINPLAVATM targets
Toxin B sites within the CROP domain rather than the C-diff organism
itself. According to the applicant, by targeting C-diff Toxin B,
ZINPLAVATM neutralizes Toxin B, prevents large intestine
endothelial cell inflammation, symptoms associated with CDI, and
reduces the recurrence of CDI. ZINPLAVATM received FDA
approval on October 21, 2016, as a treatment to reduce the recurrence
of CDI in adult patients receiving antibacterial drug treatment for CDI
and who are at high risk of CDI recurrence. As previously stated,
ZINPLAVATM is not indicated for the treatment of CDI.
ZINPLAVATM is not an antibacterial drug, and should only be
used in conjunction with an antibacterial drug treatment for CDI.
ZINPLAVATM became commercially available on February 10,
2017. Therefore, the newness period for ZINPLAVATM began on
February 10, 2017. The applicant submitted a request for a unique ICD-
10-PCS procedure code and was granted approval for the following
procedure codes: XW033A3 (Introduction of bezlotoxumab monoclonal
antibody, into peripheral vein, percutaneous approach, new technology
group 3) and XW043A3 (Introduction of bezlotoxumab monoclonal antibody,
into central vein, percutaneous approach, new technology group 3).
After evaluation of the newness, costs, and substantial clinical
improvement criteria for new technology add-on payments for
ZINPLAVATM and consideration of the public comments we
received in response to the FY 2018 IPPS/LTCH PPS proposed rule, we
approved ZINPLAVATM for new technology add-on payments for
FY 2018 (82 FR 38119). With the new technology add-on payment
application, the applicant estimated that the average Medicare
beneficiary would require a dosage of 10 mg/kg of ZINPLAVATM
administered as an IV infusion over 60 minutes as a single dose.
According to the applicant, the WAC for one dose is $3,800. Under
existing Sec. 412.88(a)(2), we limit new technology add-on payments to
the lesser of 50 percent of the average cost of the technology or 50
percent of the costs in excess of the MS-DRG payment for the case. As a
result, the maximum new technology add-on payment amount for a case
involving the use of ZINPLAVATM is $1,900 for FY 2019.
With regard to the newness criterion for ZINPLAVATM, we
considered the beginning of the newness period to commence on February
10, 2017. As discussed previously in this section, in general, we
extend new technology add-on payments for an additional year only if
the 3-year anniversary date of the product's entry onto the U.S. market
occurs in the latter half of the upcoming fiscal year. Because the 3-
year anniversary date of the entry of ZINPLAVATM onto the
U.S. market (February 10, 2020) will occur in the first half of FY
2020, we are proposing to discontinue new technology add-on payments
for this technology for FY 2020. We are inviting public comments on our
proposal to discontinue new technology add-on payments for
ZINPLAVATM for FY 2020.
[[Page 19278]]
d. KYMRIAH[supreg] (Tisagenlecleucel) and YESCARTA[supreg]
(Axicabtagene Ciloleucel)
Two manufacturers, Novartis Pharmaceuticals Corporation and Kite
Pharma, Inc., submitted separate applications for new technology add-on
payments for FY 2019 for KYMRIAH[supreg] (tisagenlecleucel) and
YESCARTA[supreg] (axicabtagene ciloleucel), respectively. Both of these
technologies are CD-19-directed T-cell immunotherapies used for the
purposes of treating patients with aggressive variants of non-Hodgkin
lymphoma (NHL).
On May 1, 2018, Novartis Pharmaceuticals Corporation received FDA
approval for KYMRIAH[supreg]'s second indication, the treatment of
adult patients with relapsed or refractory (r/r) large B-cell lymphoma
after two or more lines of systemic therapy including diffuse large B-
cell lymphoma (DLBCL) not otherwise specified, high grade B-cell
lymphoma and DLBCL arising from follicular lymphoma. On October 18,
2017, Kite Pharma, Inc. received FDA approval for the use of
YESCARTA[supreg] indicated for the treatment of adult patients with r/r
large B-cell lymphoma after two or more lines of systemic therapy,
including DLBCL not otherwise specified, primary mediastinal large B-
cell lymphoma, high grade B-cell lymphoma, and DLBCL arising from
follicular lymphoma.
Procedures involving the KYMRIAH[supreg] and YESCARTA[supreg]
therapies are both reported using the following ICD-10-PCS procedure
codes: XW033C3 (Introduction of engineered autologous chimeric antigen
receptor t-cell immunotherapy into peripheral vein, percutaneous
approach, new technology group 3); and XW043C3 (Introduction of
engineered autologous chimeric antigen receptor t-cell immunotherapy
into central vein, percutaneous approach, new technology group 3). In
the FY 2019 IPPS/LTCH PPS final rule, we finalized our proposal to
assign cases reporting these ICD-10-PCS procedure codes to Pre-MDC MS-
DRG 016 for FY 2019 and to revise the title of this MS-DRG to
Autologous Bone Marrow Transplant with CC/MCC or T-cell Immunotherapy.
We refer readers to section II.F.2.d. of the preamble of the FY 2019
IPPS/LTCH PPS final rule for a complete discussion of these final
policies (83 FR 41172 through 41174).
With respect to the newness criterion, according to both
applicants, KYMRIAH[supreg] and YESCARTA[supreg] are the first CAR T-
cell immunotherapies of their kind. As discussed in the FY 2019 IPPS/
LTCH PPS proposed and final rules, because potential cases representing
patients who may be eligible for treatment using KYMRIAH[supreg] and
YESCARTA[supreg] would group to the same MS-DRGs (because the same ICD-
10-CM diagnosis codes and ICD-10-PCS procedures codes are used to
report treatment using either KYMRIAH[supreg] or YESCARTA[supreg]), and
we believed that these technologies are intended to treat the same or
similar disease in the same or similar patient population, and are
purposed to achieve the same therapeutic outcome using the same or
similar mechanism of action, we believed these two technologies are
substantially similar to each other and that it was appropriate to
evaluate both technologies as one application for new technology add-on
payments under the IPPS. For these reasons, we stated that we intended
to make one determination regarding approval for new technology add-on
payments that would apply to both applications, and in accordance with
our policy, would use the earliest market availability date submitted
as the beginning of the newness period for both KYMRIAH[supreg] and
YESCARTA[supreg].
As summarized in the FY 2019 IPPS/LTCH PPS final rule, we received
comments from the applicants for KYMRIAH[supreg] and YESCARTA[supreg]
regarding whether KYMRIAH[supreg] and YESCARTA[supreg] were
substantially similar to each other. The applicant for YESCARTA[supreg]
stated that it believed each technology consists of notable differences
in the construction, as well as manufacturing processes and successes
that may lead to differences in activity. The applicant encouraged CMS
to evaluate YESCARTA[supreg] as a separate new technology add-on
payment application and approve separate new technology add-on payments
for YESCARTA[supreg], effective October 1, 2018, and to not move
forward with a single new technology add-on payment evaluation
determination that covers both CAR T-cell therapies, YESCARTA[supreg]
and KYMRIAH[supreg]. The applicant for KYMRIAH[supreg] indicated that,
based on FDA's approval, it agreed with CMS that KYMRIAH[supreg] is
substantially similar to YESCARTA[supreg], as defined by the new
technology add-on payment application evaluation criteria. We refer
readers to the FY 2019 IPPS/LTCH PPS final rule for a more detailed
summary of these and other public comments we received regarding
substantial similarity for KYMRIAH[supreg] and YESCARTA[supreg].
After consideration of the public comments we received and for the
reasons discussed in the FY 2019 IPPS/LTCH PPS final rule, we stated
that we believed that KYMRIAH[supreg] and YESCARTA[supreg] are
substantially similar to one another. We also noted that for FY 2019,
there was no payment impact regarding this determination of substantial
similarity because the cost of the technologies is the same. However,
we stated that we welcomed additional comments in future rulemaking
regarding whether KYMRIAH[supreg] and YESCARTA[supreg] are
substantially similar and intended to revisit this issue in the FY 2020
IPPS/LTCH PPS proposed rule. For the reasons discussed in the FY 2019
IPPS/LTCH PPS final rule, we continue to believe that KYMRIAH[supreg]
and YESCARTA[supreg] are substantially similar to each other. We note
that for FY 2020, the pricing for KYMRIAH[supreg] and YESCARTA[supreg]
remains the same and, therefore, for FY 2020, there would continue to
be no payment impact regarding the determination that the two
technologies are substantially similar to each other. Similar to last
year, we welcome public comments regarding whether KYMRIAH[supreg] and
YESCARTA[supreg] are substantially similar to each other. We refer
readers to the FY 2019 IPPS/LTCH PPS final rule for a complete
discussion on newness and substantial similarity regarding
KYMRIAH[supreg] and YESCARTA[supreg].
After evaluation of the newness, costs, and substantial clinical
improvement criteria for new technology add-on payments for
KYMRIAH[supreg] and YESCARTA[supreg] and consideration of the public
comments we received in response to the FY 2019 IPPS/LTCH PPS proposed
rule, we approved new technology add-on payments for KYMRIAH[supreg]
and YESCARTA[supreg] for FY 2019 (83 FR 41299). Cases involving
KYMRIAH[supreg] or YESCARTA[supreg] that are eligible for new
technology add-on payments are identified by ICD-10-PCS procedure codes
XW033C3 or XW043C3. The applicants for both KYMRIAH[supreg] and
YESCARTA[supreg] estimated that the average cost for an administered
dose of KYMRIAH[supreg] or YESCARTA[supreg] is $373,000. Under existing
Sec. 412.88(a)(2), we limit new technology add-on payments to the
lesser of 50 percent of the average cost of the technology or 50
percent of the costs in excess of the MS-DRG payment for the case. As a
result, for FY 2019, the maximum new technology add-on payment for a
case involving the use of KYMRIAH[supreg] or YESCARTA[supreg] is
$186,500.
As stated above, our policy is that a medical service or technology
may continue to be considered ``new'' for purposes of new technology
add-on payments within 2 or 3 years after the point at which data begin
to become available reflecting the inpatient hospital code assigned to
the new service or technology. With regard to the newness criterion for
KYMRIAH[supreg] and YESCARTA[supreg], as discussed in the FY
[[Page 19279]]
2019 IPPS/LTCH PPS final rule, according to the applicant for
YESCARTA[supreg], the first commercial shipment of YESCARTA[supreg] was
received by a certified treatment center on November 22, 2017. As
stated above, we use the earliest market availability date submitted as
the beginning of the newness period for both KYMRIAH[supreg] and
YESCARTA[supreg]. Therefore, we consider the beginning of the newness
period for both KYMRIAH[supreg] and YESCARTA[supreg] to commence
November 22, 2017. Because the 3-year anniversary date of the entry of
the technology onto the U.S. market (November 22, 2020) will occur
after FY 2020, we are proposing to continue new technology add-on
payments for KYMRIAH[supreg] and YESCARTA[supreg] for FY 2020. Under
the proposed change to the calculation of the new technology add-on
payment amount discussed in section II.H.9. of the preamble of this
proposed rule, we are proposing that the maximum new technology add-on
payment amount for a case involving the use of KYMRIAH[supreg] and
YESCARTA[supreg] would be increased to $242,450 for FY 2020; that is,
65 percent of the average cost of the technology. However, if we do not
finalize the proposed change to the calculation of the new technology
add-on payment amount, we are proposing that the maximum new technology
add-on payment for a case involving KYMRIAH[supreg] or YESCARTA[supreg]
would remain at $186,500 for FY 2020. We are inviting public comments
on our proposals to continue new technology add-on payments for
KYMRIAH[supreg] and YESCARTA[supreg] for FY 2020.
For the reasons discussed in section II.F.2.c. of this proposed
rule, we are proposing not to modify the current MS-DRG assignment for
cases reporting CAR T-cell therapies for FY 2020. Alternatively, we are
seeking public comments on payment alternatives for CAR T-cell
therapies. We also are inviting public comments on how these payment
alternatives would affect access to care, as well as how they affect
incentives to encourage lower drug prices, which is a high priority for
this Administration. As discussed in the FY 2019 IPPS/LTCH PPS final
rule (83 FR 41172 through 41174), we are considering approaches and
authorities to encourage value-based care and lower drug prices. We are
soliciting public comments on how the effective dates of any potential
payment methodology alternatives, if any were to be adopted, may
intersect and affect future participation in any such alternative
approaches. Such payment alternatives could include adjusting the CCRs
used to calculate new technology add-on payments for cases involving
the use of KYMRIAH[supreg] and YESCARTA[supreg]. We note that we also
considered this payment alternative for FY 2019, as discussed in the FY
2019 IPPS/LTCH PPS final rule (83 FR 41172 through 41174), and are
revisiting this approach given the additional experience with CAR T-
cell therapy being provided in hospitals paid under the IPPS and in
IPPS-excluded cancer hospitals. We also are requesting public comments
on other payment alternatives for these cases, including eliminating
the use of CCRs in calculating the new technology add-on payments for
cases involving the use of KYMRIAH[supreg] and YESCARTA[supreg] by
making a uniform add-on payment that equals the proposed maximum add-on
payment, that is, 65 percent of the cost of the technology (in
accordance with the proposed increase in the calculation of the maximum
new technology add-on payment amount), which in this instance would be
$242,450; and/or using a higher percentage than the proposed 65 percent
to calculate the maximum new technology add-on payment amount. If we
were to finalize any such changes to the new technology add-on payment
for cases involving the use of KYMRIAH[supreg] and YESCARTA[supreg], we
would also revise our proposed amendments to Sec. 412.88 accordingly.
e. VYXEOSTM (Cytarabine and Daunorubicin Liposome for
Injection)
Jazz Pharmaceuticals, Inc. submitted an application for new
technology add-on payments for the VYXEOSTM technology for
FY 2019. VYXEOSTM was approved by FDA on August 3, 2017, for
the treatment of adults with newly diagnosed therapy-related acute
myeloid leukemia (t-AML) or AML with myelodysplasia-related changes
(AML-MRC).
Treatment of AML diagnoses usually consists of two phases;
remission induction and post-remission therapy. Phase one, remission
induction, is aimed at eliminating as many myeloblasts as possible. The
most common used remission induction regimens for AML diagnoses are the
``7+3'' regimens using an antineoplastic and an anthracycline.
Cytarabine and daunorubicin are two commonly used drugs for ``7+3''
remission induction therapy. Cytarabine is continuously administered
intravenously over the course of 7 days, while daunorubicin is
intermittently administered intravenously for the first 3 days. The
``7+3'' regimen typically achieves a 70 to 80 percent complete
remission (CR) rate in most patients under 60 years of age.
VYXEOSTM is a nano-scale liposomal formulation
containing a fixed combination of cytarabine and daunorubicin in a 5:1
molar ratio. This formulation was developed by the applicant using a
proprietary system known as CombiPlex. According to the applicant,
CombiPlex addresses several fundamental shortcomings of conventional
combination regimens, specifically the conventional ``7+3'' free drug
dosing, as well as the challenges inherent in combination drug
development, by identifying the most effective synergistic molar ratio
of the drugs being combined in vitro, and fixing this ratio in a nano-
scale drug delivery complex to maintain the optimized combination after
administration and ensuring exposure of this ratio to the tumor.
After evaluation of the newness, costs, and substantial clinical
improvement criteria for new technology add-on payments for
VYXEOSTM and consideration of the public comments we
received in response to the FY 2019 IPPS/LTCH PPS proposed rule, we
approved VYXEOSTM for new technology add-on payments for FY
2019 (83 FR 41304). Cases involving VYXEOSTM that are
eligible for new technology add-on payments are identified by ICD-10-
PCS procedure codes XW033B3 (Introduction of cytarabine and
caunorubicin liposome antineoplastic into peripheral vein, percutaneous
approach, new technology group 3) or XW043B3 (Introduction of
cytarabine and daunorubicin liposome antineoplastic into central vein,
percutaneous approach, new technology group 3). In its application, the
applicant estimated that the average cost of a single vial for
VYXEOSTM is $7,750 (daunorubicin 44 mg/m\2\ and cytarabine
100 mg/m\2\). As discussed in the FY 2019 IPPS/LTCH PPS final rule (83
FR 41305), we computed a maximum average of 9.4 vials used in the
inpatient hospital setting with the maximum average cost for
VYXEOSTM used in the inpatient hospital setting equaling
$72,850 ($7,750 cost per vial * 9.4 vials). Under existing Sec.
412.88(a)(2), we limit new technology add-on payments to the lesser of
50 percent of the average cost of the technology or 50 percent of the
costs in excess of the MS-DRG payment for the case. As a result, the
maximum new technology add-on payment for a case involving the use of
VYXEOSTM is $36,425 for FY 2019.
With regard to the newness criterion for VYXEOSTM, we
consider the beginning of the newness period to commence when
VYXEOSTM was approved by the FDA (August 3, 2017). As
discussed previously in this section,
[[Page 19280]]
in general, we extend new technology add-on payments for an additional
year only if the 3-year anniversary date of the product's entry onto
the U.S. market occurs in the latter half of the upcoming fiscal year.
Because the 3-year anniversary date of the entry of the
VYXEOSTM onto the U.S. market (August 3, 2020) will occur in
the second half of FY 2020, we are proposing to continue new technology
add-on payments for this technology for FY 2020. Under the proposed
change to the calculation of the new technology add-on payment amount
discussed in section II.H.9. of the preamble of this proposed rule, we
are proposing that the maximum new technology add-on payment amount for
a case involving the use of VYXEOSTM would be $47,353.50 for
FY 2020; that is, 65 percent of the average cost of the technology.
However, if we do not finalize the proposed change to the calculation
of the new technology add-on payment amount, we are proposing that the
maximum new technology add-on payment for a case involving
VYXEOSTM would remain at $36,425 for FY 2020. We are
inviting public comments on our proposals to continue new technology
add-on payments for VYXEOSTM for FY 2020.
f. VABOMERETM (Meropenem-Vaborbactam)
Melinta Therapeutics, Inc., submitted an application for new
technology add-on payments for VABOMERETM for FY 2019.
VABOMERETM is indicated for use in the treatment of adult
patients who have been diagnosed with complicated urinary tract
infections (cUTIs), including pyelonephritis, caused by designated
susceptible bacteria. VABOMERETM received FDA approval on
August 29, 2017.
After evaluation of the newness, costs, and substantial clinical
improvement criteria for new technology add-on payments for
VABOMERETM and consideration of the public comments we
received in response to the FY 2019 IPPS/LTCH PPS proposed rule, we
approved VABOMERETM for new technology add-on payments for
FY 2019 (83 FR 41311). We noted in the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41311) that the applicant did not request approval for the use
of a unique ICD-10-PCS procedure code for VABOMERETM for FY
2019 and that as a result, hospitals would be unable to uniquely
identify the use of VABOMERETM on an inpatient claim using
the typical coding of an ICD-10-PCS procedure code. We noted that in
the FY 2013 IPPS/LTCH PPS final rule (77 FR 53352), with regard to the
oral drug DIFICIDTM, we revised our policy to allow for the
use of an alternative code set to identify oral medications where no
inpatient procedure is associated for the purposes of new technology
add-on payments. We established the use of a NDC as the alternative
code set for this purpose and described our rationale for this
particular code set. This change was effective for payments for
discharges occurring on or after October 1, 2012. In the FY 2019 IPPS/
LTCH PPS final rule, we acknowledged that VABOMERETM is not
an oral drug and is administered by IV infusion, but it was the first
approved new technology aside from an oral drug with no uniquely
assigned inpatient procedure code. Therefore, we believed that the
circumstances with respect to the identification of eligible cases
using VABOMERETM are similar to those addressed in the FY
2013 IPPS/LTCH PPS final rule with regard to DIFICIDTM
because we did not have current ICD-10-PCS code(s) to uniquely identify
the use of VABOMERETM to make the new technology add-on
payment. We stated that because we have determined that
VABOMERETM has met all of the new technology add-on payment
criteria and cases involving the use of VABOMERETM would be
eligible for such payments for FY 2019, we needed to use an alternative
coding method to identify these cases and make the new technology add-
on payment for use of VABOMERETM in FY 2019. Therefore, for
the reasons discussed in the FY 2019 IPPS/LTCH PPS final rule and
similar to the policy in the FY 2013 IPPS/LTCH PPS final rule, cases
involving VABOMERETM that are eligible for new technology
add-on payments for FY 2019 are identified by National Drug Codes (NDC)
65293-0009-01 or 70842-0120-01 (VABOMERETM Meropenem-
Vaborbactam Vial).
According to the applicant, the cost of VABOMERETM is
$165 per vial. A patient receives two vials per dose and three doses
per day. Therefore, the per-day cost of VABOMERETM is $990
per patient. The duration of therapy, consistent with the Prescribing
Information, is up to 14 days. Therefore, the estimated cost of
VABOMERETM to the hospital, per patient, is $13,860. We
stated in the FY 2019 IPPS/LTCH PPS final rule that based on the
limited data from the product's launch, approximately 80 percent of
VABOMERETM's usage would be in the inpatient hospital
setting, and approximately 20 percent of VABOMERETM's usage
may take place outside of the inpatient hospital setting. Therefore,
the average number of days of VABOMERETM administration in
the inpatient hospital setting is estimated at 80 percent of 14 days,
or approximately 11.2 days. As a result, the total inpatient cost for
VABOMERETM is $11,088 ($990 * 11.2 days). Under existing
Sec. 412.88(a)(2), we limit new technology add-on payments to the
lesser of 50 percent of the average cost of the technology or 50
percent of the costs in excess of the MS-DRG payment for the case. As a
result, the maximum new technology add-on payment for a case involving
the use of VABOMERETM is $5,544 for FY 2019.
With regard to the newness criterion for VABOMERETM, we
consider the beginning of the newness period to commence when
VABOMERETM received FDA approval (August 29, 2017). As
discussed previously in this section, in general, we extend new
technology add-on payments for an additional year only if the 3-year
anniversary date of the product's entry onto the U.S. market occurs in
the latter half of the upcoming fiscal year. Because the 3-year
anniversary date of the entry of VABOMERETM onto the U.S.
market (August 29, 2020) will occur during the second half of FY 2020,
we are proposing to continue new technology add-on payments for this
technology for FY 2020. Under the proposed change to the calculation of
the new technology add-on payment amount discussed in section II.H.9.
of the preamble of this proposed rule, we are proposing that the
maximum new technology add-on payment amount for a case involving the
use of VABOMERETM would be $7,207.20 for FY 2020; that is,
65 percent of the average cost of the technology. However, if we do not
finalize the proposed change to the calculation of the new technology
add-on payment amount, we are proposing that the maximum new technology
add-on payment for a case involving VABOMERETM would remain
at $5,544 for FY 2020.
As noted above, because there was no ICD-10-PCS code(s) to uniquely
identify the use of VABOMERETM, we indicated in the FY 2019
IPPS/LTCH PPS final rule that FY 2019 cases involving the use of
VABOMERETM that are eligible for the FY 2019 new technology
add-on payments would be identified using an NDC code. Subsequent to
the issuance of that final rule, new ICD-10-PCS codes XW033N5
(Introduction of Meropenem-vaborbactam Anti-infective into Peripheral
Vein, Percutaneous Approach, New Technology Group 5) and XW043N5
(Introduction of Meropenem-vaborbactam Anti-infective
[[Page 19281]]
into Central Vein, Percutaneous Approach, New Technology Group 5) were
finalized to identify cases involving the use of VABOMERETM,
effective October 1, 2019, as shown in Table 6B--New Procedure Codes,
associated with this proposed rule and available via the internet on
the CMS website at: http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. Therefore, for FY 2020,
we will use these two ICD-10-PCS codes (XW033N5 and XW043N5) to
identify cases involving the use of VABOMERETM that are
eligible for the new technology add-on payments.
While these newly approved ICD-10-PCS procedure codes can be used
to uniquely identify cases involving the use of VABOMERETM
for FY 2020, we are concerned that limiting new technology add-on
payments only to cases reporting these new ICD-10-PCS codes for FY 2020
could cause confusion because it is possible that some providers may
inadvertently continue to bill some claims with the NDC codes rather
than the new ICD-10-PCS codes. Therefore, for FY 2020, we are proposing
that in addition to using the new ICD-10-PCS codes to identify cases
involving the use of VABOMERETM, we would also continue to
use the NDC codes to identify cases and make the new technology add-on
payments. As a result, we are proposing that cases involving the use of
VABOMERETM that are eligible for new technology add-on
payments for FY 2020 would be identified by ICD-10-PCS codes XW033N5 or
XW043N5 or NDCs 65293-0009-01 or 70842-0120-01.
We are inviting public comments on our proposal to continue new
technology add-on payments for VABOMERETM for FY 2020 and
our proposals for identifying and making new technology add-on payments
for cases involving the use of VABOMERETM.
g. remed[emacr][supreg] System
Respicardia, Inc. submitted an application for new technology add-
on payments for the remed[emacr][supreg] System for FY 2019. According
to the applicant, the remed[emacr][supreg] System is indicated for use
as a transvenous phrenic nerve stimulator in the treatment of adult
patients who have been diagnosed with moderate to severe central sleep
apnea. The remed[emacr][supreg] System consists of an implantable pulse
generator, and a stimulation and sensing lead. The pulse generator is
placed under the skin, in either the right or left side of the chest,
and it functions to monitor the patient's respiratory signals. A
transvenous lead for unilateral stimulation of the phrenic nerve is
placed either in the left pericardiophrenic vein or the right
brachiocephalic vein, and a second lead to sense respiration is placed
in the azygos vein. Both leads, in combination with the pulse
generator, function to sense respiration and, when appropriate,
generate an electrical stimulation to the left or right phrenic nerve
to restore regular breathing patterns. On October 6, 2017, the
remed[emacr][supreg] System was approved by the FDA as an implantable
phrenic nerve stimulator indicated for the use in the treatment of
adult patients who have been diagnosed with moderate to severe CSA. The
device was available commercially upon FDA approval. Therefore, the
newness period for the remed[emacr][supreg] System is considered to
begin on October 6, 2017.
After evaluation of the newness, costs, and substantial clinical
improvement criteria for new technology add-on payments for the
remed[emacr][supreg] System and consideration of the public comments we
received in response to the FY 2019 IPPS/LTCH PPS proposed rule, we
approved the remed[emacr][supreg] System for new technology add-on
payments for FY 2019. Cases involving the use of the
remed[emacr][supreg] System that are eligible for new technology add-on
payments are identified by ICD-10-PCS procedures codes 0JH60DZ and
05H33MZ in combination with procedure code 05H03MZ (Insertion of
neurostimulator lead into right innominate vein, percutaneous approach)
or 05H43MZ (Insertion of neurostimulator lead into left innominate
vein, percutaneous approach). According to the application, the cost of
the remed[emacr][supreg] System is $34,500 per patient. Under existing
Sec. 412.88(a)(2), we limit new technology add-on payments to the
lesser of 50 percent of the average cost of the technology or 50
percent of the costs in excess of the MS-DRG payment for the case. As a
result, the maximum new technology add-on payment for a case involving
the use of the remed[emacr][supreg] System is $17,250 for FY 2019 (83
FR 41320).
With regard to the newness criterion for the remed[emacr][supreg]
System, we consider the beginning of the newness period to commence
when the remed[emacr][supreg] System was approved by the FDA on October
6, 2017. Because the 3-year anniversary date of the entry of the
remed[emacr][supreg] System onto the U.S. market (October 6, 2020) will
occur after FY 2020, we are proposing to continue new technology add-on
payments for this technology for FY 2020. Under the proposed change to
the calculation of the new technology add-on payment amount discussed
in section II.H.9. of the preamble of this proposed rule, we are
proposing that the maximum new technology add-on payment amount for a
case involving the use of the remed[emacr][supreg] System would be
$22,425 for FY 2020; that is, 65 percent of the average cost of the
technology. However, if we do not finalize the proposed change to the
calculation of the new technology add-on payment amount, we are
proposing that the maximum new technology add-on payment for a case
involving the remed[emacr][supreg] System would remain at $17,250 for
FY 2020. We are inviting public comments on our proposals to continue
new technology add-on payments for the remed[emacr][supreg] System for
FY 2020.
h. ZEMDRITM (Plazomicin)
Achaogen, Inc. submitted an application for new technology add-on
payments for ZEMDRITM (Plazomicin) for FY 2019. According to
the applicant, ZEMDRITM (Plazomicin) is a next-generation
aminoglycoside antibiotic, which has been found in vitro to have
enhanced activity against many multi-drug resistant (MDR) gram-negative
bacteria. The applicant received approval from the FDA on June 25,
2018, for use in the treatment of adults who have been diagnosed with
cUTIs, including pyelonephritis. After evaluation of the newness,
costs, and substantial clinical improvement criteria for new technology
add-on payments for ZEMDRITM and consideration of the public
comments we received in response to the FY 2019 IPPS/LTCH PPS proposed
rule, we approved ZEMDRITM for new technology add-on
payments for FY 2019 (83 FR 41334). Cases involving ZEMDRITM
that are eligible for new technology add-on payments are identified by
ICD-10-PCS procedure codes XW033G4 (Introduction of Plazomicin anti-
infective into peripheral vein, percutaneous approach, new technology
group 4) or XW043G4 (Introduction of Plazomicin anti-infective into
central vein, percutaneous approach, new technology group 4). In its
application, the applicant estimated that the average Medicare
beneficiary would require a dosage of 15 mg/kg administered as an IV
infusion as a single dose. According to the applicant, the WAC for one
dose is $330, and patients will typically require 3 vials for the
course of treatment with ZEMDRITM per day for an average
duration of 5.5 days. Therefore, the total cost of ZEMDRITM
per patient is $5,445. Under existing Sec. 412.88(a)(2), we limit new
technology add-on payments to the
[[Page 19282]]
lesser of 50 percent of the average cost of the technology or 50
percent of the costs in excess of the MS-DRG payment for the case. As a
result, the maximum new technology add-on payment for a case involving
the use of ZEMDRITM is $2,722.50 for FY 2019. With regard to
the newness criterion for ZEMDRITM, we consider the
beginning of the newness period to commence when ZEMDRITM
was approved by the FDA on June 25, 2018. Because the 3-year
anniversary date of the entry of ZEMDRITM onto the U.S.
market (June 25, 2021) will occur after FY 2020, we are proposing to
continue new technology add-on payments for this technology for FY
2020. Under the proposed change to the calculation of the new
technology add-on payment amount discussed in section II.H.9. of the
preamble of this proposed rule, we are proposing that the maximum new
technology add-on payment amount for a case involving the use of
ZEMDRITM would be $3,539.25 for FY 2020; that is, 65 percent
of the average cost of the technology. However, if we do not finalize
the proposed change to the calculation of the new technology add-on
payment amount, we are proposing that the maximum new technology add-on
payment for a case involving ZEMDRITM would remain at
$2,722.50 for FY 2020. We are inviting public comments on our proposals
to continue new technology add-on payments for ZEMDRITM for
FY 2020.
i. GIAPREZATM
The La Jolla Pharmaceutical Company submitted an application for
new technology add-on payments for GIAPREZATM for FY 2019.
GIAPREZATM, a synthetic human angiotensin II, is
administered through intravenous infusion to raise blood pressure in
adult patients who have been diagnosed with septic or other
distributive shock.
GIAPREZATM was granted a Priority Review designation
under FDA's expedited program and received FDA approval on December 21,
2017, for the use in the treatment of adults who have been diagnosed
with septic or other distributive shock as an intravenous infusion to
increase blood pressure. After evaluation of the newness, costs, and
substantial clinical improvement criteria for new technology add-on
payments for GIAPREZATM and consideration of the public
comments we received in response to the FY 2019 IPPS/LTCH PPS proposed
rule, we approved GIAPREZATM for new technology add-on
payments for FY 2019 (83 FR 41342). Cases involving
GIAPREZATM that are eligible for new technology add-on
payments are identified by ICD-10-PCS procedure codes XW033H4
(Introduction of synthetic human angiotensin II into peripheral vein,
percutaneous approach, new technology, group 4) or XW043H4
(Introduction of synthetic human angiotensin II into central vein,
percutaneous approach, new technology group 4). In its application, the
applicant estimated that the average Medicare beneficiary would require
a dosage of 20 ng/kg/min administered as an IV infusion over 48 hours,
which would require 2 vials. The applicant explained that the WAC for
one vial is $1,500, with each episode-of-care costing $3,000 per
patient. Under existing Sec. 412.88(a)(2), we limit new technology
add-on payments to the lesser of 50 percent of the average cost of the
technology or 50 percent of the costs in excess of the MS-DRG payment
for the case. As a result, the maximum new technology add-on payment
for a case involving the use of GIAPREZATM is $1,500 for FY
2019.
With regard to the newness criterion for GIAPREZATM, we
consider the beginning of the newness period to commence when
GIAPREZATM was approved by the FDA (December 21, 2017).
Because the 3-year anniversary date of the entry of
GIAPREZATM onto the U.S. market (December 21, 2020) would
occur after FY 2020, we are proposing to continue new technology add-on
payments for this technology for FY 2020. Under the proposed change to
the calculation of the new technology add-on payment discussed in
section II.H.9. of the preamble of this proposed rule, we are proposing
that the maximum new technology add-on payment amount for a case
involving the use of GIAPREZATM would be $1,950 for FY 2020;
that is, 65 percent of the average cost of the technology. However, if
we do not finalize the proposed change to the calculation of the new
technology add-on payment amount, we are proposing that the maximum new
technology add-on payment for a case involving GIAPREZATM
would remain at $1,500 for FY 2020. We are inviting public comments on
our proposals to continue new technology add-on payments for
GIAPREZATM for FY 2020.
j. Cerebral Protection System (Sentinel[supreg] Cerebral Protection
System)
Claret Medical, Inc. submitted an application for new technology
add-on payments for the Cerebral Protection System (Sentinel[supreg]
Cerebral Protection System) for FY 2019. According to the applicant,
the Sentinel Cerebral Protection System is indicated for the use as an
embolic protection (EP) device to capture and remove thrombus and
debris while performing transcatheter aortic valve replacement (TAVR)
procedures. The device is percutaneously delivered via the right radial
artery and is removed upon completion of the TAVR procedure. The De
Novo request for the Sentinel[supreg] Cerebral Protection System was
granted by FDA on June 1, 2017 (DEN160043).
After evaluation of the newness, costs, and substantial clinical
improvement criteria for new technology add-on payments for the
Sentinel[supreg] Cerebral Protection System and consideration of the
public comments we received in response to the FY 2019 IPPS/LTCH PPS
proposed rule, we approved the Sentinel[supreg] Cerebral Protection
System for new technology add-on payments for FY 2019 (83 FR 41348).
Cases involving the Sentinel[supreg] Cerebral Protection System that
are eligible for new technology add-on payments are identified by ICD-
10-PCS code X2A5312 (Cerebral embolic filtration, dual filter in
innominate artery and left common carotid artery, percutaneous
approach). In its application, the applicant estimated that the cost of
the Sentinel[supreg] Cerebral Protection System is $2,800. Under
existing Sec. 412.88(a)(2), we limit new technology add-on payments to
the lesser of 50 percent of the average cost of the technology or 50
percent of the costs in excess of the MS-DRG payment for the case. As a
result, the maximum new technology add-on payment for a case involving
the use of the Sentinel[supreg] Cerebral Protection System is $1,400
for FY 2019.
With regard to the newness criterion for the Sentinel[supreg]
Cerebral Protection System, we consider the beginning of the newness
period to commence when the FDA granted the De Novo request for the
Sentinel[supreg] Cerebral Protection System (June 1, 2017). As
discussed previously in this section, in general, we extend new
technology add-on payments for an additional year only if the 3-year
anniversary date of the product's entry onto the U.S. market occurs in
the latter half of the upcoming fiscal year. Because the 3-year
anniversary date of the entry of the Sentinel[supreg] Cerebral
Protection System onto the U.S. market (June 1, 2020) will occur in the
second half of FY 2020, we are proposing to continue new technology
add-on payments for this technology for FY 2020. Under the proposed
change to the calculation of the new technology add-on payment amount
discussed in section II.H.9. of the preamble of this proposed rule, we
are proposing that the maximum new technology add-on payment amount for
[[Page 19283]]
a case involving the use of the Sentinel[supreg] Cerebral Protection
System would be $1,820 for FY 2020; that is, 65 percent of the average
cost of the technology. However, if we do not finalize the proposed
change to the calculation of the new technology add-on payment amount,
we are proposing that the maximum new technology add-on payment for a
case involving the Sentinel[supreg] Cerebral Protection System would
remain at $1,400 for FY 2020. We are inviting public comments on our
proposals to continue new technology add-on payments for the
Sentinel[supreg] Cerebral Protection System for FY 2020.
k. The AQUABEAM System (Aquablation)
PROCEPT BioRobotics Corporation submitted an application for new
technology add-on payments for the AQUABEAM System (Aquablation) for FY
2019. According to the applicant, the AQUABEAM System is indicated for
the use in the treatment of patients experiencing lower urinary tract
symptoms caused by a diagnosis of benign prostatic hyperplasia (BPH).
The AQUABEAM System consists of three main components: A console with
two high-pressure pumps, a conformal surgical planning unit with trans-
rectal ultrasound imaging, and a single-use robotic hand-piece. The
applicant reported that the AQUABEAM System provides the operating
surgeon a multi-dimensional view, using both ultrasound image guidance
and endoscopic visualization, to clearly identify the prostatic adenoma
and plan the surgical resection area. Based on the planning inputs from
the surgeon, the system's robot delivers Aquablation, an autonomous
waterjet ablation therapy that enables targeted, controlled, heat-free
and immediate removal of prostate tissue used for the purpose of
treating lower urinary tract symptoms caused by a diagnosis of BPH. The
combination of surgical mapping and robotically-controlled resection of
the prostate is designed to offer predictable and reproducible
outcomes, independent of prostate size, prostate shape or surgeon
experience.
The FDA granted the AQUABEAM System's De Novo request on December
21, 2017, for use in the resection and removal of prostate tissue in
males suffering from lower urinary tract symptoms (LUTS) due to benign
prostatic hyperplasia. The applicant stated that the AQUABEAM System
was made available on the U.S. market immediately after the FDA granted
the De Novo request.
After evaluation of the newness, costs, and substantial clinical
improvement criteria for new technology add-on payments for the
AQUABEAM System and consideration of the public comments we received in
response to the FY 2019 IPPS/LTCH PPS proposed rule, we approved the
AQUABEAM System for new technology add-on payments for FY 2019 (83 FR
41355). Cases involving the AQUABEAM System that are eligible for new
technology add-on payments are identified by ICD-10-PCS code XV508A4
(Destruction of prostate using robotic waterjet ablation, via natural
or artificial opening endoscopic, new technology group 4). The
applicant estimated that the average Medicare beneficiary would require
the transurethral procedure of one AQUABEAM System per patient.
According to the application, the cost of the AQUABEAM System is $2,500
per procedure. Under existing Sec. 412.88(a)(2), we limit new
technology add-on payments to the lesser of 50 percent of the average
cost of the technology or 50 percent of the costs in excess of the MS-
DRG payment for the case. As a result, the maximum new technology add-
on payment for a case involving the use of the AQUABEAM System's
Aquablation System is $1,250 for FY 2019.
With regard to the newness criterion for the AQUABEAM System, we
consider the beginning of the newness period to commence on the date
the FDA granted the De Novo request (December 21, 2017). As noted above
and in the FY 2019 rulemaking, the applicant stated that the AQUABEAM
System was made available on the U.S. market immediately after the FDA
granted the De Novo request.
We note that in the FY 2019 IPPS/LTCH PPS final rule, we
inadvertently misstated the newness period beginning date as April 19,
2018 (83 FR 41351). As discussed in the FY 2019 IPPS/LTCH PPS final
rule (83 FR 41350), in its public comment in response to the FY 2019
IPPS/LTCH PPS proposed rule, the applicant explained that, while the
AQUABEAM System received approval from the FDA for its De Novo request
on December 21, 2017, local non-coverage determinations in the Medicare
population resulted in the first case being delayed until April 19,
2018. Therefore, the applicant believed that the newness period should
begin on April 19, 2018, instead of the date FDA granted the De Novo
request. In the final rule, we responded that with regard to the
beginning of the technology's newness period, as discussed in the FY
2005 IPPS final rule (69 FR 49003), the timeframe that a new technology
can be eligible to receive new technology add-on payments begins when
data begin to become available. While local non-coverage determinations
may limit the use of a technology in different regions in the country,
a technology may be available in regions where no local non-coverage
decision existed (with data beginning to become available). We also
explained that under our historical policy we do not consider how
frequently the medical service or technology has been used in the
Medicare population in our determination of newness (as discussed in
the FY 2006 IPPS final rule (70 FR 47349)). Consistent with this
response, and as indicated in the proposed rule and elsewhere in the
final rule, we believe the beginning of the newness period to commence
on the first day the AQUABEAM System was commercially available
(December 21, 2017). As noted, the later statement that the newness
period beginning date for the AQUABEAM System is April 19, 2018 was an
inadvertent error. As we indicated in the FY 2019 IPPS/LTCH PPS final
rule, we welcome further information from the applicant for
consideration regarding the beginning of the newness period.
Because the 3-year anniversary date of the entry of the AQUABEAM
System onto the U.S. market (December 21, 2020) will occur after FY
2020, we are proposing to continue new technology add-on payments for
this technology for FY 2020. Under the proposed change to the
calculation of the new technology add on payment amount discussed in
section II.H.9. of the preamble of this proposed rule, we are proposing
that the maximum new technology add-on payment amount for a case
involving the use of the AQUABEAM System would be $1,625 for FY 2020;
that is, 65 percent of the average cost of the technology. However, if
we do not finalize the proposed change to the calculation of the new
technology add-on payment amount, we are proposing that the maximum new
technology add-on payment for a case involving the AQUABEAM System
would remain at $1,250 for FY 2020. We are inviting public comments on
our proposals to continue new technology add-on payments for the
AQUABEAM System for FY 2020.
l. AndexXaTM (Andexanet alfa)
Portola Pharmaceuticals, Inc. (Portola) submitted an application
for new technology add-on payments for FY 2019 for the use of
AndexXaTM (Andexanet alfa).
AndexXaTM received FDA approval on May 3, 2018, and is
indicated for use in the treatment of patients who are
[[Page 19284]]
receiving treatment with rivaroxaban and apixaban, when reversal of
anticoagulation is needed due to life-threatening or uncontrolled
bleeding.
After evaluation of the newness, costs, and substantial clinical
improvement criteria for new technology add-on payments for
AndexXaTM and consideration of the public comments we
received in response to the FY 2019 IPPS/LTCH PPS proposed rule, we
approved AndexXaTM for new technology add-on payments for FY
2019 (83 FR 41362). Cases involving the use of AndexXaTM
that are eligible for new technology add-on payments are identified by
ICD-10-PCS procedure codes XW03372 (Introduction of Andexanet alfa,
Factor Xa inhibitor reversal agent into peripheral vein, percutaneous
approach, new technology group 2) or XW04372 (Introduction of Andexanet
alfa, Factor Xa inhibitor reversal agent into central vein,
percutaneous approach, new technology group 2). The applicant explained
that the WAC for 1 vial is $2,750, with the use of an average of 10
vials for the low dose and 18 vials for the high dose. The applicant
noted that per the clinical trial data, 90 percent of cases were
administered a low dose and 10 percent of cases were administered the
high dose. The weighted average between the low and high dose is an
average of 10.22727 vials. Therefore, the cost of a standard dosage of
AndexXaTM is $28,125 ($2,750 x 10.22727). Under existing
Sec. 412.88(a)(2), we limit new technology add-on payments to the
lesser of 50 percent of the average cost of the technology or 50
percent of the costs in excess of the MS-DRG payment for the case. As a
result, the maximum new technology add-on payment for a case involving
the use of AndexXaTM is $14,062.50 for FY 2019.
With regard to the newness criterion for AndexXaTM, we
consider the beginning of the newness period to commence when
AndexXaTM received FDA approval (May 3, 2018). Because the
3-year anniversary date of the entry of AndexXaTM onto the
U.S. market (May 3, 2021) will occur after FY 2020, we are proposing to
continue new technology add-on payments for this technology for FY
2020. Under the proposed change to the calculation of the new
technology add-on payment amount discussed in section II.H.9. of the
preamble of this proposed rule, we are proposing that the maximum new
technology add-on payment amount for a case involving the use of
AndexXaTM would be $18,281.25 for FY 2020; that is, 65
percent of the average cost of the technology. However, if we do not
finalize the proposed change to the calculation of the new technology
add-on payment amount, we are proposing that the maximum new technology
add-on payment for a case involving AndexXaTM would remain
at $14,062.50 for FY 2020. We are inviting public comments on our
proposals to continue new technology add-on payments for
AndexXaTM for FY 2020.
5. Proposed FY 2020 Applications for New Technology Add-On Payments
We received 18 applications for new technology add-on payments for
FY 2020. In accordance with the regulations under Sec. 412.87(c),
applicants for new technology add-on payments must have FDA approval or
clearance by July 1 of the year prior to the beginning of the fiscal
year for which the application is being considered. One applicant
withdrew its application prior to the issuance of this proposed rule. A
discussion of the 17 remaining applications is presented below.
a. AZEDRA[supreg] (Ultratrace[supreg] iobenguane Iodine-131) Solution
Progenics Pharmaceuticals, Inc. submitted an application for new
technology add-on payments for AZEDRA[supreg] (Ultratrace[supreg]
iobenguane Iodine-131) for FY 2020. (We note that Progenics
Pharmaceuticals, Inc. previously submitted an application for new
technology add-on payments for AZEDRA[supreg] for FY 2019, which was
withdrawn prior to the issuance of the FY 2019 IPPS/LTCH PPS final
rule.) AZEDRA[supreg] is a drug solution formulated for intravenous
(IV) use in the treatment of patients who have been diagnosed with
obenguane avid malignant and/or recurrent and/or unresectable
pheochromocytoma and paraganglioma. AZEDRA[supreg] contains a small
molecule ligand consisting of meta-iodobenzylguanidine (MIBG) and
\131\Iodine (\131\I) (hereafter referred to as ``\131\I-MIBG''). The
applicant noted that iobenguane Iodine-131 is also known as \131\I-
MIBG.
The applicant reported that pheochromocytomas and paragangliomas
are rare tumors with an incidence of approximately 2 to 8 people per
million per year.1 2 Both tumors are catecholamine-secreting
neuroendocrine tumors, with pheochromocytomas being the more common of
the two and comprising 80 to 85 percent of cases. While 10 percent of
pheochromocytomas are malignant, whereby ``malignant'' is defined by
the World Health Organization (WHO) as ``the presence of distant
metastases,'' paragangliomas have a malignancy frequency of 25
percent.3 4 Approximately one-half of malignant tumors are
pronounced at diagnosis, while other malignant tumors develop slowly
within 5 years.\5\ Pheochromocytomas and paragangliomas tend to be
indistinguishable at the cellular level and frequently at the clinical
level. For example catecholamine-secreting paragangliomas often present
clinically like pheochromocytomas with hypertension, episodic headache,
sweating, tremor, and forceful palpitations.\6\ Although
pheochromocytomas and paragangliomas can share overlapping
histopathology, epidemiology, and molecular pathobiology
characteristics, there are differences between these two neuroendocrine
tumors in clinical behavior, aggressiveness and metastatic potential,
biochemical findings and association with inherited genetic syndrome
differences, highlighting the importance of distinguishing between the
presence of malignant pheochromocytoma and the presence of malignant
paraganglioma. At this time, there is no curative treatment for
malignant pheochromocytomas and paragangliomas. Successful management
of these malignancies requires a multidisciplinary approach of
decreasing tumor burden, controlling endocrine activity, and treating
debilitating symptoms. According to the applicant, decreasing
metastatic tumor burden would address the leading cause of mortality in
this patient population, where the 5-year survival rate is 50 percent
for patients with untreated malignant pheochromocytomas and
paragangliomas.\7\ The applicant stated that controlling catecholamine
[[Page 19285]]
hypersecretion (for example, severe paroxysmal or sustained
hypertension, palpitations and arrhythmias) would also mean decreasing
morbidity associated with hypertension (for example, risk of stroke,
myocardial infarction and renal failure), and begin to address the 30-
percent cardiovascular mortality rate associated with malignant
pheochromocytomas and paragangliomas.
---------------------------------------------------------------------------
\1\ Beard, C.M., Sheps, S.G., Kurland, L.T., Carney, J.A., Lie,
J.T., ``Occurrence of pheochromocytoma in Rochester, Minnesota'',
pp. 1950-1979.
\2\ Stenstr[ouml]m, G., Sv[auml]rdsudd, K., ``Pheochromocytoma
in Sweden 1958-1981. An analysis of the National Cancer Registry
Data,'' Acta Medica Scandinavica, 1986, vol. 220(3), pp. 225-232.
\3\ Fishbein, Lauren, ``Pheochromocytoma and Paraganglioma,''
Hematology/Oncology Clinics 30, no. 1, 2016, pp. 135-150.
\4\ Lloyd, R.V., Osamura, R.Y., Kl[ouml]ppel, G., & Rosai, J.
(2017). World Health Organization (WHO) Classification of Tumours of
Endocrine Organs. Lyon, France: International Agency for Research on
Center (IARC).
\5\ Kantorovich, Vitaly, and Karel Pacak. ``Pheochromocytoma and
paraganglioma.'' Progress in Brain Research., 2010, vol. 182, pp.
343-373.
\6\ Carty, SE, Young, W.F., Elfky, A., ``Paraganglioma and
pheochromocytoma: Management of malignant disease,'' UpToDate.
Available at: https://www.uptodate.com/contents/paraganglioma-and-pheochromocytoma-management-of-malignant-disease.
\7\ Kantorovich, Vitaly, and Karel Pacak. ``Pheochromocytoma and
paraganglioma.'' Progress in Brain Research., 2010, vol. 182, pp.
343-373.
---------------------------------------------------------------------------
The applicant reported that, prior to the introduction of
AZEDRA[supreg], controlling catecholamine activity in pheochromocytomas
and paragangliomas was medically achieved with administration of
combined alpha and beta-adrenergic blockade, and surgically with tumor
tissue reduction. Because there is no curative treatment for malignant
pheochromocytomas and paragangliomas, resecting both primary and
metastatic lesions whenever possible to decrease tumor burden \8\
provides a methodology for controlling catecholamine activity and
lowering cardiovascular mortality risk. Besides surgical removal of
tumor tissue for lowering tumor burden, there are other treatment
options that depend upon tumor type (that is, pheochromocytoma tumors
versus paraganglioma tumors), anatomic location, and the number and
size of the metastatic tumors. These treatment options include: (1)
Radiation therapy; (2) nonsurgical local ablative therapy with
radiofrequency ablation, cryoablation, and percutaneous ethanol
injection; (3) transarterial chemoembolization for liver metastases;
and (4) radionuclide therapy using metaiodobenzylguanidine (MIBG) or
somatostatin. Regardless of the method to reduce local tumor burden,
periprocedural medical care is needed to prevent massive catecholamine
secretion and hypertensive crisis.\9\
---------------------------------------------------------------------------
\8\ Noda, T., Nagano, H., Miyamoto, A., et al., ``Successful
outcome after resection of liver metastasis arising from an
extraadrenal retroperitoneal paraganglioma that appeared 9 years
after surgical excision of the primary lesion,'' Int J Clin Oncol,
2009, vol. 14, pp. 473.
\9\ Carty, SE, Young, W.F., Elfky, A., ``Paraganglioma and
pheochromocytoma: Management of malignant disease,'' UpToDate.
Available at: https://www.uptodate.com/contents/paraganglioma-and-pheochromocytoma-management-of-malignant-disease.
---------------------------------------------------------------------------
The applicant stated that AZEDRA[supreg] specifically targets
neuroendocrine tumors arising from chromaffin cells of the adrenal
medulla (in the case of pheochromocytomas) and from neuroendocrine
cells of the extra-adrenal autonomic paraganglia (in the case of
paragangliomas).\10\ According to the applicant, AZEDRA[supreg] is a
more consistent form of 131I-MIBG compared to compounded
formulations of 131I-MIBG that are not approved by the FDA.
AZEDRA[supreg] (iobenguane I 131) (AZEDRA) was approved by the FDA on
July 30, 2018, and according to the applicant, is the first and only
drug indicated for the treatment of adult and pediatric patients 12
years and older who have been diagnosed with iobenguane scan positive,
unresectable, locally advanced or metastatic pheochromocytoma or
paraganglioma who require systemic anticancer therapy. Among local
tumor tissue reduction options, use of external beam radiation therapy
(EBRT) at doses greater than 40 Gy can provide local pheochromocytoma
and paraganglioma tumor control and relief of symptoms for tumors at a
variety of sites, including the soft tissues of the skull base and
neck, abdomen, and thorax, as well as painful bone metastases.\11\
However, the applicant stated that EBRT irradiated tissues are
unresponsive to subsequent treatment with 131I-MIBG
radionuclide.\12\ MIBG was initially used for the imaging of
paragangliomas and pheochromocytomas because of its similarity to
noradrenaline, which is taken up by chromaffin cells. Conventional MIBG
used in imaging expanded to off-label use in patients who had been
diagnosed with malignant pheochromocytomas and paragangliomas. Because
131I-MIBG is sequestered within pheochromocytoma and
paraganglioma tumors, subsequent malignant cell death occurs from
radioactivity. Approximately 50 percent of tumors are eligible for
treatment involving 131I-MIBG therapy based on having MIBG
uptake with diagnostic imaging. According to the applicant, despite
uptake by tumors, studies have also found that 131I-MIBG
therapy has been limited by total radiation dose, hematologic side
effects, and hypertension. While the pathophysiology of total radiation
dose and hematologic side effects are more readily understandable,
hypertension is believed to be precipitated by large quantities of non-
iodinated MIBG or ``cold'' MIBG being introduced along with radioactive
\131\I-MIBG therapy.\13\ The ``cold'' MIBG blocks synaptic reuptake of
norepinephrine, which can lead to tachycardia and paroxysmal
hypertension within the first 24 hours, the majority of which occur
within 30 minutes of administration and can be dose-limiting.\14\
---------------------------------------------------------------------------
\10\ Ibid.
\11\ Ibid.
\12\ Fitzgerald, P.A., Goldsby, R.E., Huberty, J.P., et al.,
``Malignant pheochromocytomas and paragangliomas: a phase II study
of therapy with high-dose 131I-metaiodobenzylguanidine (131I-
MIBG),'' Ann N Y Acad Sci, 2006, vol. 1073, pp. 465.
\13\ Loh, K.C., Fitzgerald, P.A., Matthay, K.K., Yeo, P.P.,
Price, DC, ``The treatment of malignant pheochromocytoma with
iodine-131 metaiodobenzylguanidine (\131\I-MIBG): a comprehensive
review of 116 reported patients,'' J Endocrinol Invest, 1997, vol.
20(11), pp. 648-658.
\14\ Gonias, S, et al., ``Phase II Study of High-Dose [\131\I
]Metaiodobenzylguanidine Therapy for Patients With Metastatic
Pheochromocytoma and Paraganglioma,'' J of Clin Onc, July 27, 2009.
---------------------------------------------------------------------------
The applicant asserted that its new proprietary manufacturing
process called Ultratrace[supreg] allows AZEDRA[supreg] to be
manufactured without the inclusion of unlabeled or ``cold'' MIBG in the
final formulation. The applicant also noted that targeted radionuclide
MIBG therapy to reduce tumor burden is one of two treatments that have
been studied the most. The other treatment is cytotoxic chemotherapy
and, specifically, Carboplatin, Vincristine, and Dacarbazine (CVD). The
applicant stated that cytotoxic chemotherapy is an option for patients
who experience symptoms with rapidly progressive, non-resectable, high
tumor burden, and that cytotoxic chemotherapy is another option for a
large number of metastatic bone lesions.\15\ According to the
applicant, CVD was believed to have an effect on malignant
pheochromocytomas and paragangliomas due to the embryonic origin being
similar to neuroblastomas. The response rates to CVD have been variable
between 25 percent and 50 percent.16 17 These patients
experience side effects consistent with chemotherapeutic treatment with
CVD, with the added concern of the precipitation of hormonal
complications such as hypertensive crisis, thereby requiring close
monitoring during cytotoxic chemotherapy.\18\ According to the
applicant, use of CVD relative to other tumor burden reduction options
is not
[[Page 19286]]
an ideal treatment because of nearly 100 percent recurrence rates, and
the need for chemotherapy cycles to be continually readministered at
the risk of increased systemic toxicities and eventual development of
resistance. Finally, there is a subgroup of patients that are
asymptomatic and have slower progressing tumors where frequent follow-
up is an option for care.\19\ Therefore, the applicant believed that
AZEDRA[supreg] offers cytotoxic radioactive therapy for the indicated
population that avoids harmful side effects that typically result from
use of low-specific activity products.
---------------------------------------------------------------------------
\15\ Carty, SE, Young, W.F., Elfky, A., ``Paraganglioma and
pheochromocytoma: Management of malignant disease,'' UpToDate.
Available at: https://www.uptodate.com/contents/paraganglioma-and-pheochromocytoma-management-of-malignant-disease.
\16\ Niemeijer, N.D., Alblas, G., Hulsteijn, L.T., Dekkers, O.M.
and Corssmit, E.P. M., ``Chemotherapy with cyclophosphamide,
vincristine and dacarbazine for malignant paraganglioma and
pheochromocytoma: systematic review and meta[hyphen]analysis,''
Clinical endocrinology, 2014, vol 81(5), pp. 642-651.
\17\ Ayala-Ramirez, Montserrat, et al., ``Clinical Benefits of
Systemic Chemotherapy for Patients with Metastatic Pheochromocytomas
or Sympathetic Extra-Adrenal Paragangliomas: Insights from the
Largest Single Institutional Experience,'' Cancer, 2012, vol.
118(11), pp. 2804-2812.
\18\ Wu, L.T., Dicpinigaitis, P., Bruckner, H., et al.,
``Hypertensive crises induced by treatment of malignant
pheochromocytoma with a combination of cyclophosphamide,
vincristine, and dacarbazine,'' Med Pediatr Oncol, 1994, vol. 22(6),
pp. 389-392.
\19\ Carty, SE, Young, W.F., Elfky, A., ``Paraganglioma and
pheochromocytoma: Management of malignant disease,'' UpToDate.
Available at: https://www.uptodate.com/contents/paraganglioma-and-pheochromocytoma-management-of-malignant-disease.
---------------------------------------------------------------------------
The applicant reported that the recommended AZEDRA[supreg] dosage
and frequency for patients receiving treatment involving \131\I-MIBG
therapy for a diagnosis of avid malignant and/or recurrent and/or
unresectable pheochromocytoma and paraganglioma tumors is:
Dosimetric Dosing--5 to 6 micro curies (mCi) (185 to 222
MBq) for a patient weighing more than or equal to 50 kg, and 0.1 mCi/kg
(3.7 MBq/kg) for patients weighing less than 50 kg. Each recommended
dosimetric dose is administered as an IV injection.
Therapeutic Dosing--500 mCi (18.5 GBq) for patients
weighing more than 62.5 kg, and 8 mCi/kg (296 MBq/kg) for patients
weighing less than or equal to 62.5 kg. Therapeutic doses are
administered by IV infusion, in ~50 mL over a period of ~30 minutes
(100 mL/hour), administered approximately 90 days apart.
With respect to the newness criterion, the applicant indicated that
FDA granted Orphan Drug designation for AZEDRA[supreg] on January 18,
2006, followed by Fast Track designation on March 8, 2006, and
Breakthrough Therapy designation on July 26, 2015. The applicant's New
Drug Application (NDA) proceeded on a rolling basis, and was completed
on November 2, 2017. AZEDRA[supreg] was approved by the FDA on July 30,
2018, for the treatment of adult and pediatric patients 12 years and
older who have been diagnosed with iobenguane scan positive,
unresectable, locally advanced or metastatic pheochromocytoma or
paraganglioma who require systemic anticancer therapy through a New
Drug Approval (NDA) filed under Section 505(b)(1) of the Federal Food,
Drug and Cosmetic Act and 21 CFR 314.50. Currently, there are no
approved ICD-10-PCS procedure codes to uniquely identify procedures
involving the administration of AZEDRA[supreg]. We note that the
applicant submitted a request for approval for a unique ICD-10-PCS code
for the administration of AZEDRA[supreg] beginning in FY 2020.
As discussed earlier, if a technology meets all three of the
substantial similarity criteria, it would be considered substantially
similar to an existing technology and would not be considered ``new''
for purposes of new technology add-on payments.
With regard to the first criterion, whether a product uses the same
or similar mechanism of action, the applicant stated that while
AZEDRA[supreg] and low-specific activity conventional I-131 MIBG both
target the same transporter sites on the tumor cell surface, the
therapies' safety and efficacy outcomes are different. These
differences in outcomes are because AZEDRA[supreg] is manufactured
using the proprietary Ultratrace[supreg] technology, which maximizes
the molecules that carry the tumoricidal component (I-131 MIBG) and
minimizes the extraneous unlabeled component (MIBG, free ligands),
which could cause cardiovascular side effects. Therefore, according to
the applicant, AZEDRA[supreg] is designed to increase efficacy and
decrease safety risks, whereas conventional I-131 MIBG uses existing
technologies and results in a product that overwhelms the normal
reuptake system with excess free ligands, which leads to safety issues
as well as decreasing the probability of the \131\I-MIBG binding to the
tumor cells.
With regard to the second criterion, whether a product is assigned
to the same or a different MS-DRG, the applicant noted that there are
no specific MS-DRGs for the assignment of cases involving the treatment
of patients who have been diagnosed with pheochromocytoma and
paraganglioma. We believe that potential cases representing patients
who may be eligible for treatment involving the administration of
AZEDRA[supreg] would be assigned to the same MS-DRGs as cases
representing patients who receive treatment for a diagnosis of
iobenguane avid malignant and/or recurrent and/or unresectable
pheochromocytoma and paraganglioma. We also refer readers to the cost
criterion discussion below, which includes the applicant's list of the
MS-DRGs to which potential cases involving treatment with the
administration of AZEDRA[supreg] most likely would map.
With regard to the third criterion, whether the new use of the
technology involves the treatment of the same or similar type of
disease and the same or similar patient population, according to the
applicant, AZEDRA[supreg] is the only FDA-approved drug indicated for
use in the treatment of patients who have been diagnosed with malignant
pheochromocytoma and paraganglioma tumors that avidly take up \131\I-
MIBG and are recurrent and/or unresectable. The applicant stated that
these patients face serious mortality and morbidity risks if left
untreated, as well as potentially suffer from side effects if treated
by available off-label therapies.
The applicant also contended that AZEDRA[supreg] can be
distinguished from other currently available treatments because it
potentially provides the following advantages:
AZEDRA[supreg] will have a very limited impact on normal
norepinephrine reuptake due to the negligible amount of unlabeled MIBG
present in the dose. Therefore, AZEDRA[supreg] is expected to pose a
much lower risk of acute drug-induced hypertension.
There is minimal unlabeled MIBG to compete for the
norepinephrine transporter binding sites in the tumor, resulting in
more effective delivery of radioactivity.
Current off-label therapeutic use of \131\I is compounded
by individual pharmacies with varied quality and conformance standards.
Because of its higher specific activity (the activity of a
given radioisotope per unit mass), AZEDRA[supreg] infusion times are
significantly shorter than conventional \131\I administrations.
Therefore, with these potential advantages, the applicant
maintained that AZEDRA[supreg] represents an option for the treatment
of patients who have been diagnosed with malignant and/or recurrent
and/or unresectable pheochromocytoma and paraganglioma tumors, where
there is a clear, unmet medical need.
For the reasons cited earlier, the applicant believed that
AZEDRA[supreg] is not substantially similar to other currently
available therapies and/or technologies and meets the ``newness''
criterion. We are inviting public comments on whether AZEDRA[supreg] is
substantially similar to other currently available therapies and/or
technologies and meets the ``newness'' criterion.
With regard to the cost criterion, the applicant conducted an
analysis using FY 2015 MedPAR data to demonstrate that AZEDRA[supreg]
meets the cost criterion.
The applicant searched for potential cases representing patients
who may be eligible for treatment involving AZEDRA[supreg] that had one
of the following ICD-9-CM diagnosis codes (which the applicant believed
is indicative of
[[Page 19287]]
diagnosis appropriate for treatment involving AZEDRA[supreg]): 194.0
(Malignant neoplasm of adrenal gland), 194.6 (Malignant neoplasm of
aortic body and other paraganglia), 209.29 (Malignant carcinoid tumor
of other sites), 209.30 (Malignant poorly differentiated neuroendocrine
carcinoma, any site), 227.0 (Benign neoplasm of adrenal gland), 237.3
(Neoplasm of uncertain behavior of paraganglia)--in combination with
one of the following ICD-9-CM procedure codes describing the
administration of a radiopharmaceutical: 00.15 (High-dose infusion
interleukin-2); 92.20 (Infusion of liquid brachytherapy radioisotope);
92.23 (Radioisotopic teleradiotherapy); 92.27 (Implantation or
insertion of radioactive elements); 92.28 (Injection or instillation of
radioisotopes). The applicant reported that the potential cases used
for this analysis mapped to MS-DRGs 054 and 055 (Nervous System
Neoplasms with and without MCC, respectively), MS-DRG 271 (Other Major
Cardiovascular Procedures with CC), MS-DRG 436 (Malignancy of
Hepatobiliary System or Pancreas with CC), MS-DRG 827
(Myeloproliferative Disorders or Poorly Differentiated Neoplasms with
Major O.R. Procedure with CC), and MS-DRG 843 (Other Myeloproliferative
Disorders or Poorly Differentiated Neoplastic Diagnosis with MCC). Due
to patient privacy concerns, because the number of cases under each MS-
DRG was less than 11 in total, the applicant assumed an equal
distribution between these 6 MS-DRGs. Based on the FY 2019 IPPS/LTCH
PPS final rule correction notice data file thresholds, the average
case-weighted threshold amount was $60,136. Using the identified cases,
the applicant determined that the average unstandardized charge per
case ranged from $21,958 to $152,238 for the 6 evaluated MS-DRGs. After
removing charges estimated to be associated with precursor agents, the
applicant used a 3-year inflation factor of 1.1436 (a yearly inflation
factor of 1.04574 applied over 3 years), based on the FY 2018 IPPS/LTCH
PPS final rule (82 FR 38527), to inflate the charges from FY 2015 to FY
2018. The applicant provided an estimated average of $151,000 per
therapeutic dose per patient, based on the wholesale acquisition cost
of the drug and the average dosage amount for most patients, with a
total cost per patient estimated to be approximately $980,000. After
including the cost of the technology, the applicant determined an
inflated average case-weighted standardized charge per case of
$1,078,631.
We are concerned with the limited number of cases the applicant
analyzed. However, we acknowledge the difficulty in obtaining cost data
for such a rare condition. We are inviting public comments on whether
the AZEDRA[supreg] technology meets the cost criterion.
With regard to substantial clinical improvement, the applicant
maintained that the use of AZEDRA[supreg] has been shown to reduce the
incidence of hypertensive episodes and use of antihypertensive
medications, reduce tumor size, improve blood pressure control, and
reduce secretion of tumor biomarkers. In addition, the applicant
asserted that AZEDRA[supreg] provides a treatment option for those
outlined in its indication patient population. The applicant asserted
that AZEDRA[supreg] meets the substantial clinical improvement
criterion based on the results from two clinical studies: (1) MIP-IB12
(IB12): A Phase I Study of Iobenguane (MIBG) I-131 in Patients With
Malignant Pheochromocytoma/Paraganglioma; \20\ and (2) MIP-IB12B
(IB12B): A Study Evaluating Ultratrace[supreg] Iobenguane I-131 in
Patients With Malignant Relapsed/Refractory Pheochromocytoma/
Paraganglioma. The applicant explained that the IB12B study is similar
to the IB12 study in that both studies evaluated two open-label,
single-arm studies. The applicant reported that both studies included
patients who had been diagnosed with malignant and/or recurrent and/or
unresectable pheochromocytoma and paraganglioma tumors, and both
studies assessed objective tumor response, biochemical tumor response,
overall survival rates, occurrence of hypertensive crisis, and the
long-term benefit of AZEDRA[supreg] treatment relative to the need for
antihypertensives. However, according to the applicant, the study
designs differed in dose regimens (1 dose administered to patients in
the IB12 study, and 2 doses administered to patients in the IB12B
study) and primary study endpoints. Differences in the designs of the
studies prevented direct comparison of study endpoints and pooling of
the data. In addition, the applicant stated that results from safety
data from the IB12 study and the IB12B study were pooled and used to
support substantial clinical improvement assertions. We note that
neither the IB12 study nor the IB12B study compared the effects of the
use of AZEDRA[supreg] to any of the other treatment options to decrease
tumor burden (for example, cytotoxic chemotherapy, radiation therapy,
and surgical debulking).
---------------------------------------------------------------------------
\20\ Noto, Richard B., et. al., ``Phase 1 Study of High-
Specific-Activity I-131 MIBG for Metastatic and/or Recurrent
Pheochromocytoma or Paraganglioma (IB12 Phase 1 Study),'' J Clin
Endocrinol Metab, vol. 103(1), pp. 213-220.
---------------------------------------------------------------------------
Regarding the data results from the IB12 study, the applicant
asserted that, based on the reported safety and tolerability, and
primary endpoint of radiological response at 12 months, high-specific-
activity I-131 MIBG may be an effective alternative therapeutic option
for patients who have been diagnosed with iobenguane-avid, metastatic
and/or recurrent pheochromocytoma and paraganglioma tumors for whom
there are no other approved therapies and for those patients who have
failed available treatment options. In addition, the applicant used the
exploratory finding of decreased or discontinuation of anti-
hypertensive medications relative to baseline medications as evidence
that AZEDRA[supreg] has clinical benefit and positive impact on the
long-term effects of hypertension induced norepinephrine producing
malignant pheochromocytoma and paraganglioma tumors. We understand that
the applicant used antihypertensive medications as a proxy to assess
the long-term effects of hypertension such as renal, myocardial, and
cerebral end organ damage. The applicant reported that it studied 15 of
the original IB12 study's 21-patient cohort, and found 33 percent (n=5)
had decreased or discontinuation of antihypertensive medications during
the 12 months of follow-up. However, the applicant did not provide
additional data on the incidence of renal insufficiency/failure,
myocardial ischemic/infarction events, or transient ischemic attacks or
strokes. Therefore, it is unclear to us if these five patients also had
decreased urine metanephrines, changed their diet, lost significant
weight, or if other underlying comorbidities that influence
hypertension were resolved, making it difficult to understand the
significance of this exploratory finding.
Regarding the applicant's assertion that the use of AZEDRA[supreg]
is safer and more effective than alternative therapies, we note that
the IB12 study was a dose-escalating study and did not compare current
therapies with the use of AZEDRA[supreg]. We also note the following:
(1) The average age of the 21 enrolled patients in the IB12 study was
50.4 years old (a range of 30 to 72 years old); (2) the gender
distribution was 61.9 percent (n=13) male and 38.1 percent (n=8)
female; and (3) 76.2 percent (n=16) were white, 14.3 percent (n=3) were
black or African American, and 9.5 percent (n=2) were Asian. We
[[Page 19288]]
agree with the study's conductor \21\ that the size of the study is a
limitation, and with a younger, predominately white, male patient
population, generalization of study results to a more diverse
population may be difficult. The applicant reported that one other
aspect of the patient population indicated that all 21 patients
received prior anti-cancer therapy for treatment of malignant
pheochromocytoma and paraganglioma tumors, which included the
following: 57.1 percent (n=12) received radiation therapy including
external beam radiation and conventional MIBG; 28.6 percent (n=6)
received cytotoxic chemotherapy (for example, CVD and other
chemotherapeutic agents); and 14.3 percent (n=3) received
Octreotide.\22\ Although this study's patient population illustrates a
population that has failed some of the currently available therapy
options, which may potentially support a finding of substantial
clinical improvement for those with no other treatment options, we are
unclear which patients benefited from treatment involving
AZEDRA[supreg], especially in view of the finding of a Fitzgerald, et
al. study cited earlier \23\ that concluded tissues previously
irradiated by EBRT were found to be unresponsive to subsequent
treatment with \131\I-MIBG radionuclide. It was not clear in the
application how previously EBRT-treated patients who failed EBRT fared
with the Response Evaluation Criteria in Solid Tumors (RECIST) scores,
biotumor marker results, and reduction in antihypertensive medications.
We also lacked information to draw the same correlation between
previously CVD-treated patients and their RECIST scores, biotumor
marker results, and reduction in antihypertensive medications.
---------------------------------------------------------------------------
\21\ Noto, Richard B., et al., ``Phase 1 Study of High-Specific-
Activity I-131 MIBG for Metastatic and/or Recurrent Pheochromocytoma
or Paraganglioma (IB12 Phase 1 Study),'' J Clin Endocrinol Metab,
vol. 103(1), pp. 213-220.
\22\ Ibid.
\23\ Fitzgerald, P.A., Goldsby, R.E., Huberty, J.P., et al.,
``Malignant pheochromocytomas and paragangliomas: a phase II study
of therapy with high-dose 131I-metaiodobenzylguanidine (131I-
MIBG).'' Ann N Y Acad Sci, 2006, vol. 1073, pp. 465.
---------------------------------------------------------------------------
The applicant asserted that the use of AZEDRA[supreg] reduces tumor
size and reduces the secretion of tumor biomarkers, thereby providing
important clinical benefits to patients. The IB12 study assessed the
overall best tumor response based on RECIST.\24\ Tumor biomarker
response was assessed as complete or partial response for serum
chromogranin A and total metanephrines in 80 percent and 64 percent of
patients, respectively. The applicant noted that both the overall best
tumor response based on RECIST and tumor biomarker response favorable
results are at doses higher than 500 mCi. We noticed that tumor burden
improvement, as measured by RECIST criteria, showed that none of the 21
patients achieved a complete response. In addition, although 4 patients
showed partial response, these 4 patients also experienced dose-
limiting toxicity with hematological events, and all 4 patients
received administered doses greater than 18.5 GBq (500 mCi). We also
note that, regardless of total administered activity (for example,
greater than or less than 18.5 GBq (500 mCi)), 61.9 percent (n=13) of
the 21 patients enrolled in the study had stable disease and 14.3
percent (n=2) of the 14 patients who received greater than administered
doses of 18.5 GBq (500 mCi) had progressive disease. Finally, we also
noticed that, for most tumor biomarkers, there were no dose
relationship trends. While we appreciate the applicant's contention
that there is no other FDA-approved drug therapy for patients who have
been diagnosed with \131\I-MIBG avid malignant and/or recurrent and/or
unresectable pheochromocytoma and paraganglioma tumors, we have
questions as to whether the overall tumor best response and overall
best tumor biomarker data results from the IB12 study support a finding
that the use of the AZEDRA[supreg] technology represents a substantial
clinical improvement.
---------------------------------------------------------------------------
\24\ Therasse, P., Arbuck, S.G., Eisenhauer, J.W., Kaplan, R.S.,
Rubinsten, L., Verweij, J., Van Blabbeke, M., Van Oosterom, A.T.,
Christian, M.D., and Gwyther, S.G., ``New guidelines to evaluate the
response to treatment in solid tumors,'' J Natl Cancer Inst, 2000,
vol. 92(3), pp. 205-16. Available at: http://www.eortc.be/Services/Doc/RECIST.pdf.
---------------------------------------------------------------------------
Finally, regarding the applicant's assertion that, based on the
IB12 study data, AZEDRA[supreg] provides a safe alternative therapy for
those patients who have failed other currently available treatment
therapies, we note that none of the patients experienced hypertensive
crisis, and that 76 percent (n=16) of the 21 patients enrolled in the
study experienced Grade III or IV adverse events. Although the
applicant indicated the adverse events were related to the study drug,
the applicant also noted that there was no statistically significant
difference between the greater than or less than 18.5 GBq administered
doses; both groups had adverse events rates greater than 75 percent.
Specifically, 5 of 7 patients (76 percent) who received less than or
equal to 18.5 GBq administered doses, and 11 of 14 patients (79
percent) who received greater than 18.5 GBq administered doses
experienced Grade III or IV adverse advents. The most common (greater
than or equal to 10 percent) Grade III and IV adverse events were
neutropenia, leukopenia, thrombocytopenia, nausea, and vomiting. We
also note that: (1) There were 5 deaths during the study that occurred
from approximately 2.5 months up to 22 months after treatment and there
was no detailed data regarding the 5 deaths, especially related to the
total activity received during the study; (2) there was no information
about which patients received prior radiation therapy with EBRT and/or
conventional MIBG relative to those who experienced Grade III or IV
adverse events; and (3) the total lifetime radiation dose was not
provided by the applicant. We are inviting public comments on whether
the safety data profile from the IB12 study supports a finding that the
use of AZEDRA[supreg] represents a substantial clinical improvement for
patients who received treatment with \131\I-MIBG for a diagnosis of
avid malignant and/or recurrent and/or unresectable pheochromocytoma
and paraganglioma tumors, given the risks for Grade III or IV adverse
events.
The applicant provided study data results from the IB12B study
(MIP-IB12B), an open-label, prospective 5-year follow-up, single-arm,
multi-center, Phase II pivotal study to evaluate the safety and
efficacy of the use of AZEDRA[supreg] for the treatment of patients who
have been diagnosed with malignant and/or recurrent pheochromocytoma
and paraganglioma tumors to support the assertion of substantial
clinical improvement. The applicant reported that the IB12B's primary
endpoint is the proportion of patients with a reduction (including
discontinuation) of all anti-hypertensive medication by at least 50
percent for at least 6 months. Seventy-four patients who received at
least 1 dosimetric dose of AZEDRA[supreg] were evaluated for safety and
68 patients who received at least 1 therapeutic dose of AZEDRA[supreg],
each at 500 mCi (or 8 mCi/kg for patients weighing less than or equal
to 62.5 kg), were assessed for specific clinical outcomes. The
applicant asserted that results from this prospective study met the
primary endpoint (reduction or discontinuation of anti-hypertensive
medications), as well as demonstrated strong supportive evidence from
key secondary endpoints (overall tumor response, tumor biomarker
response, and overall survival rates) that confers important clinical
relevance to patients
[[Page 19289]]
who have been diagnosed with malignant pheochromocytoma and
paraganglioma tumors. The applicant also indicated that the use of
AZEDRA[supreg] was shown to be generally well tolerated at doses
administered at 8 mCi/kg. We note that the data results from the IB12B
study did not have a comparator arm, making it difficult to interpret
the clinical outcome data relative to other currently available
therapies.
As discussed for the IB12 study, the applicant reported that
antihypertension treatment was a proxy for effectiveness of the use of
AZEDRA[supreg] on norepinephrine induced hypertension producing tumors.
In the IB12B study, 25 percent (17/68) of patients met the primary
endpoint of having a greater than 50 percent reduction in anti-
hypertensive agents for at least 6 months. The applicant further
indicated that an additional 16 patients showed a greater than 50
percent reduction in anti-hypertensive agents for less than 6 months,
and by pooling data results from these 33 patients the applicant
concluded that 49 percent (33/68) of patients achieved a greater than
50 percent reduction at any time during the study's 12-month follow-up
period. The study's primary endpoint data also revealed that 11 percent
of the 88 patients who received a therapeutic dose of AZEDRA[supreg]
experienced a worsening of preexisting hypertension defined as an
increase in systolic blood pressure to >=160 mmHg with an increase of
20 mmHg or an increase in diastolic blood pressure >= 00 mmHg with an
increase of 10 mmHg. All changes in blood pressure occurred within the
first 24 hours post infusion. The applicant further compared its data
results from the IB12B study regarding antihypertension medication and
the frequency of post-infusion hypertension with published studies on
MIBG and CVD therapy. The applicant noted a retrospective analysis of
CVD therapy of 52 patients who had been diagnosed with metastatic
pheochromocytoma and paraganglioma tumors that found only 15 percent of
CVD-treated patients achieved a 50-percent reduction in anti-
hypertensive agents. The applicant also compared its data results for
post-infusion hypertension with literature reporting on MIBG and found
14 and 19 percent (depending on the study) of patients receiving MIBG
experience hypertension within 24 hours of infusion. Comparatively, the
applicant stated that the use of AZEDRA[supreg] had no acute events of
hypertension following infusion. We are inviting public comments on
whether these data results regarding hypertension support a finding
that the use of the AZEDRA[supreg] technology represents a substantial
clinical improvement, and if anti-hypertensive medication reduction is
an adequate proxy for improvement in renal, cerebral, and myocardial
end organ damage.
Regarding reduction in tumor burden (as defined by RECIST scores),
the applicant indicated that at the conclusion of the IB12B study's 12-
month follow-up period, 23.4 percent (n=15) of the 68 patients showed a
partial response, 68.8 percent (n=44) of the 68 patients achieved
stable disease, and 4.7 percent (n=3) of the 68 patients showed
progressive disease. None of the patients showed completed response.
The applicant maintained that achieving stable disease is important for
patients who have been treated for malignant pheochromocytoma and
paraganglioma tumors because this is a progressive disease without a
cure at this time. The applicant also indicated that literature shows
that stable disease is maintained in approximately 47 percent of
treatment na[iuml]ve patients who have been diagnosed with metastatic
pheochromocytoma and paraganglioma tumors at 1 year due to the indolent
nature of the disease.\25\ In the IB12B study, the data results equated
to 23 percent of patients achieving partial response and 69 percent of
patients achieving stable disease. According to the applicant, this
compares favorably to treatment with both conventional radiolabeled
MIBG and CVD chemotherapy.
---------------------------------------------------------------------------
\25\ Hescot, S., Leboulleux, S., Amar, L., Vezzosi, D., Borget,
I., Bournaud-Salinas, C., de la Fouchardiere, C., Lib[eacute], R.,
Do Cao, C., Niccoli, P., Tabarin, A., ``One-year progression-free
survival of therapy-naive patients with malignant pheochromocytoma
and paraganglioma,'' The J Clin Endocrinol Metab, 2013, vol. 98(10),
pp. 4006-4012.
---------------------------------------------------------------------------
The applicant stated that the data results demonstrated effective
tumor response rates. The applicant reported that the IB12 and IB12B
study data showed overall tumor response rates of 80 percent and 92
percent, respectively. In addition, the applicant contended that the
study data across both trials show that patients demonstrated improved
blood pressure control, reductions in tumor biomarker secretion, and
strong evidence in overall survival rates. The overall median time to
death from the first dose was 36.7 months in all treated patients.
Patients who received 2 therapeutic doses had an overall median
survival rate of 48.7 months, compared to 17.5 months for patients who
only received a single dose. We note that the IB12B study reported 12-
month Kaplan-Meier estimate of survival of 91 percent, while the drug
dosing study IB12 reported overall subject survival of 86 percent at 12
months, 62 percent at 24 months, 38 percent at 36 months, and 4.8
percent at 48 months. We also note that only 45 of 68 patients who
received at least 1 therapeutic dose completed the 12-month efficacy
phase.
The applicant indicated that comparison of the IB12B study data
regarding overall survival rate with historical data is difficult due
to the differences in the retrospective nature of the published
clinical studies and heterogeneous patient characteristics, especially
when overall survival is calculated from the time of initial diagnosis.
We agree with the applicant regarding the difficulties in comparing the
results of the published clinical studies, and also believe that the
differences in these studies may make it more difficult to evaluate
whether the use of the AZEDRA[supreg] technology improves overall
survival rates relative to other therapies.
We acknowledge the challenges with constructing robust clinical
studies due to the extremely rare occurrence of patients who have been
diagnosed with pheochromocytoma and paraganglioma tumors. However, we
are concerned that because the data for both of these studies is mainly
based upon retrospective studies and small, heterogeneous patient
cohorts, it is difficult to draw precise conclusions regarding
efficacy. Only very limited nonpublished data from two, single-arm,
noncomparative studies are available to evaluate the safety and
effectiveness of AZEDRA[supreg], leading to a comparison of outcomes
with historical controls.
We are inviting public comments on whether the use of the
AZEDRA[supreg] technology meets the substantial clinical improvement
criterion, including with respect to the specific concerns we have
raised. We did not receive any written comments in response to the New
Technology Town Hall meeting notice published in the Federal Register
regarding the substantial clinical improvement criterion for
AZEDRA[supreg] or at the New Technology Town Hall meeting.
b. CABLIVI[supreg] (caplacizumab-yhdp)
The Sanofi Company submitted an application for new technology add-
on payments for CABLIVI[supreg] (caplacizumab-yhdp) for FY 2020. The
applicant described CABLIVI[supreg] as a humanized bivalent nanobody
consisting of two identical building blocks joined by a tri alanine
linker, which is administered through intravenous and subcutaneous
[[Page 19290]]
injection to inhibit microclot formation in adult patients who have
been diagnosed with acquired thrombotic thrombocytopenic purpura
(aTTP). The applicant stated that aTTP is a life-threatening, immune-
mediated thrombotic microangiopathy characterized by severe
thrombocytopenia, hemolytic anemia, and organ ischemia with an
estimated 3 to 11 cases per million per year in the U.K. and
U.S.26 27 28 Further, the applicant stated that aTTP is an
ultra-orphan disease caused by inhibitory autoantibodies to von
Willebrand Factor-cleaving protease (vWFCP) also known as ``a
disintegrin and metalloprotease with thrombospondin type 1 motif,
member 13 (ADAMTS13),'' resulting in a severe deficiency in WFCP. The
applicant further explained that von Willebrand Factor (vWF) is a key
protein in hemostasis and is an adhesive, multimeric plasma
glycoprotein with a pivotal role in the recruitment of platelets to
sites of vascular injury. According to the applicant, more than 90
percent of circulating vWF is expressed by endothelial cells and
secreted into the systemic circulation as ultra-large von Willebrand
Factor (ULvWF) multimers. The applicant stated that decreased ADAMTS13
activity leads to an accumulation of ULvWF multimers, which bind to
platelets and induce platelet aggregation. According to the applicant,
the consumption of platelets in these microthrombi causes severe
thrombocytopenia, tissue ischemia and organ dysfunction (commonly
involving the brain, heart, and kidneys) and may result in acute
thromboembolic events such as stroke, myocardial infarction, venous
thrombosis, and early death. The applicant indicated that the
aforementioned tissue and organ damage resulting from the ischemia
leads to increased levels of lactate dehydrogenase (LDH), troponins,
and creatinine (organ damage markers) and that faster normalization of
these organ damage markers and platelet counts is believed to be linked
with faster resolution of the ongoing microthrombotic process and the
associated tissue ischemia. According to the applicant, in diagnoses of
aTTP there is no consensual, validated surrogate marker that defines
the subpopulation at greatest risk of death or significant morbidity.
Therefore, the applicant stated that all patients who have been
diagnosed with aTTP should be considered severe cases and treated in
order to prevent death and significant morbidity.
---------------------------------------------------------------------------
\26\ Scully, M., et al., ``Regional UK TTP registry: correlation
with laboratory ADAMTS 13 analysis and clinical Features,'' Br. J.
Haematol., 2008, vol. 142(5), pp. 819-26.
\27\ Reese, J.A., et al., ``Children and adults with thrombotic
thrombocytopenic purpura associated with severe, acquired Adamts13
deficiency: comparison of incidence, demographic and clinical
features,'' Pediatr. Blood Cancer, 2013, vol. 60(10), pp. 1676-82.
\28\ Terrell, D.R., et al., ``The incidence of thrombotic
thrombocytopenic purpura-hemolytic uremic syndrome: all patients,
idiopathic patients, and patients with severe ADAMTS-13
deficiency,'' J. Thromb. Haemost., 2005, vol. 3(7), pp. 1432-6.
---------------------------------------------------------------------------
The applicant explained that the two standard-of-care (SOC)
treatment options for a diagnosis of aTTP are plasma exchange (PE), in
which a patient's blood plasma is removed through apheresis and is
replaced with donor plasma, and immunosuppression (for example,
corticosteroids and increasingly also rituximab), which is often
administered as adjunct to plasma exchange in the treatment for a
diagnosis of aTTP.29 30 According to the applicant, despite
the current SOC treatment options, acute aTTP episodes are still
associated with a mortality rate of up to 20 percent, which generally
occurs within the first weeks of diagnosis. The applicant asserted
that, although the 20-percent mortality rate reflects substantial
improvement because of PE treatment, in spite of greater understanding
of disease pathogenesis and the use of newer immunosuppressants, the
mortality rate has not been further
improved.31 32 33 34 35 36 The applicant also noted that
another important limitation of the currently available therapies (PE
and immunosuppression) is the delayed onset of effect of days to weeks
of these therapies because such therapies do not directly address the
pathophysiological platelet aggregation that leads to the formation of
microthrombi, which is ultimately associated with death or with the
severe outcomes reported with diagnoses of aTTP. The applicant
explained that despite current treatment, exacerbation and relapse
occur and frequently lead to hospitalization and the need to restart
daily PE treatment and optimize immunosuppression. In addition, the
applicant noted that patients may experience exacerbations after
discontinuing plasma exchange treatment due to continuing formation of
microthrombi as a result of unresolved underlying autoimmune disease,
and patients remain at risk of thrombotic complications or early death
until the episode is completely resolved.\37\
---------------------------------------------------------------------------
\29\ Scully, M., et al., ``Guidelines on the diagnosis and
management of thrombotic thrombocytopenic purpura and other
thrombotic microangiopathies,'' Br. J. Haematol., 2012, vol. 158(3),
pp. 323-35.
\30\ George, J.N., ``Corticosteroids and rituximab as adjunctive
treatments for thrombotic thrombocytopenic Purpura,'' Am. J.
Hematol., 2012, vol. 87 Suppl 1, pp. S88-91.
\31\ Form for Notification of a Compassionate Use Programme to
the Paul-Ehrlich-Institut.
\32\ Benhamou, Y., et al., ``Cardiac troponin-I on diagnosis
predicts early death and refractoriness in acquired thrombotic
thrombocytopenic purpura. Experience of the French Thrombotic
Microangiopathies Reference Center,'' J. Thromb. Haemost., 2015,
vol. 13(2), pp. 293-302.
\33\ Han, B., et al., ``Depression and cognitive impairment
following recovery from thrombotic thrombocytopenic purpura,'' Am.
J. of Hematol., 2015, vol. 90(8), pp. 709-14.
\34\ Rajan, S.K., ``BMJ Best Practice; Thrombotic
thrombocyopenic purpura,'' May 27, 2016.
\35\ Goel, R., et al., ``Prognostic risk-stratified score for
predicting mortality in hospitalized patients with thrombotic
thrombocytopenic purpura: nationally representative data from 2007
to 2012,'' Transfusion, 2016, vol. 56(6), pp. 1451-8.
\36\ Rock, G.A., Shumak, K.H., Buskard, N.A., et al.,
``Comparison of plasma exchange with plasma infusion in the
treatment of thrombotic thrombocytopenic purpura. Canadian Apheresis
Study Group,'' N Engl J Med, 1991, vol. 325, pp. 393-397.
\37\ Goel, R., et al., ``Prognostic risk-stratified score for
predicting mortality in hospitalized patients with thrombotic
thrombocytopenic purpura: nationally representative data from 2007
to 2012,'' Transfusion, 2016, vol. 56(6), pp. 1451-8.
---------------------------------------------------------------------------
According to the information provided by the applicant,
CABLIVI[supreg] is administered as an adjunct to PE treatment and
immunosuppressive therapy immediately upon diagnosis of aTTP through a
bolus intraveneous injection for the first dose and subcutaneous
injection for all subsequent doses. The recommended treatment regimen
and dosage of CABLIVI[supreg] consists of administering 10 mg on the
first day of treatment via intravenous injection prior to the standard
plasma exchange treatment. After completion of PE treatment on the
first day, a 10 mg subcutaneous injection is administered. After the
first day, and for the rest of the plasma exchange treatment period, a
daily 10 mg subcutaneous injection is administered following each day's
PE treatment. After the PE treatment period is completed, a daily 10 mg
subcutaneous injection is administered for 30 days. If the underlying
immunological disease (aTTP) is not resolved, the treatment period
should be extended beyond 30 days and be accompanied by optimization of
immunosuppression (another SOC treatment option, in addition to PE
treatment). According to the applicant and as discussed later, the use
of CABLIVI[supreg] produces faster normalization of platelet count
response compared to that of SOC treatment options alone. The applicant
indicated that this contributes to a decrease in the
[[Page 19291]]
length of the SOC treatment period with respect to the number of days
of PE treatment, the mean length of intensive care unit stays, and the
mean length of hospitalizations.
With respect to the newness criterion, CABLIVI[supreg] received FDA
approval on February 6, 2019, for the treatment of adult patients who
have been diagnosed with aTTP, in combination with plasma exchange and
immunosuppressive therapy. According to information provided by the
applicant, CABLIVI[supreg] was previously granted Fast Track and Orphan
Drug designations in the United States for the treatment of aTTP by the
FDA and Orphan Drug designation in Europe for the treatment of aTTP.
Currently, there are no ICD-10-PCS procedure codes to uniquely identify
procedures involving CABLIVI[supreg]. We note that the applicant
submitted a request for approval for a unique ICD-10-PCS procedure code
for the administration of CABLIVI[supreg] beginning in FY 2020.
As discussed above, if a technology meets all three of the
substantial similarity criteria, it would be considered substantially
similar to an existing technology and would not be considered ``new''
for purposes of new technology add-on payments.
With regard to the first criterion, whether a product uses the same
or a similar mechanism of action to achieve a therapeutic outcome,
according to the applicant, CABLIVI[supreg] is a first-in-class therapy
with an innovative mechanism of action. The applicant explained that
CABLIVI[supreg] binds to the A1 domain of vWF and specifically inhibits
the interaction between vWF and platelets. Furthermore, the applicant
indicated that in patients who have been diagnosed with aTTP,
proteolysis of ULvWF multimers by ADAMTS13 is impaired due to the
presence of inhibiting or clearing anti-ADAMTS13 auto-antibodies,
resulting in the persistence of the constitutively active A1 domain
and, as a consequence, platelets spontaneously bind to ULvWF and
generate microvascular blood clots in high shear blood vessels. The
applicant noted that CABLIVI[supreg] is able to interact with vWF in
both its active (that is, ULvWF multimers or normal multimers activated
through immobilization or shear stress) and inactive forms (that is,
multimers prior to conformational change of the A1 domain), thereby
immediately blocking the interaction of vWF with the platelet receptor
(GPIb-IX-V) and further preventing spontaneous interaction of ULvWF
with platelets that would lead to platelet microthrombi formation in
the microvasculature, local schemia and platelet consumption. The
applicant highlighted that this immediate platelet-protective effect
differentiates CABLIVI[supreg] from slower-acting therapies, such as PE
and immunosuppressants, which need days to exert their effect. The
applicant explained that PE acts by removing ULvWF and the circulating
auto-antibodies against ADAMTS13, thereby replenishing blood levels of
ADAMTS13, while immunosuppressants aim to stop or reduce the formation
of auto-antibodies against ADAMTS13.
With respect to the second criterion, whether a product is assigned
to the same or a different MS-DRG, the applicant believed that
potential cases representing patients who may be eligible for treatment
involving CABLIVI[supreg] would be assigned to the same MS- DRGs as
cases representing patients who receive SOC treatment for a diagnosis
of aTTP. As explained below in the discussion of the cost criterion,
the applicant believed that potential cases representing patients who
may be eligible for treatment involving CABLIVI[supreg] would be
assigned to MS-DRGs that contain cases representing patients who were
diagnosed with aTTP and received therapeutic PE procedures during
hospitalization.
With respect to the third criterion, whether the new use of the
technology involves the treatment of the same or similar type of
disease and the same or similar patient population, according to the
applicant, there are no other specific therapies approved for the
treatment of patients diagnosed with aTTP. As stated earlier, according
to the applicant, patients who have been diagnosed with aTTP have two
currently available SOC treatment options: PE, in which a patient's
blood plasma is removed through apheresis and is replaced with donor
plasma, and immunosuppression (for example, corticosteroids and
increasingly rituximab), which is administered as an adjunct to PE in
the treatment of aTTP. The applicant further explained that
immunosuppression consisting of glucocorticoids is often administered
as adjunct to PE in the initial treatment of a diagnosis of
aTTP,38 39 but their use is based on historical evidence
that some patients with limited symptoms might respond to
corticosteroids alone.40 41 The applicant noted that there
have been no studies specifically comparing treatment involving the
combination of PE with corticosteroids, versus PE alone; that they are
not specifically approved for the treatment of a diagnosis of aTTP, and
that other immunosuppressive agents used to treat a diagnosis of aTTP,
such as rituximab, have not been studied in properly controlled,
double-blind studies. The applicant also noted that rituximab, aside
from not being licensed for the treatment of a diagnosis of aTTP, is
not fully effective during the first 2 weeks of treatment, with a
reported delay of onset of its effect that may extend up to 27 days,
with at least 3 to 7 days needed to achieve adequate B-cell depletion
(given the B-cells may also contain ADAMTS13 antibodies), and even
longer to restore ADAMTS13 activity levels.42 43
---------------------------------------------------------------------------
\38\ Scully, M., et al., ``Guidelines on the diagnosis and
management of thrombotic thrombocytopenic purpura and other
thrombotic microangiopathies,'' Br. J. Haematol., 2012, vol. 158(3),
pp. 323-35.
\39\ George, J.N., ``Corticosteroids and rituximab as adjunctive
treatments for thrombotic thrombocytopenic Purpura,'' Am. J.
Hematol., 2012, vol. 87 Suppl 1, pp. S88-91.
\40\ Bell, W.R., et al., ``Improved survival in thrombotic
thrombocytopenic purpura-hemolytic uremic Syndrome. Clinical
experience in 108 patients,'' N. Engl. J. Med., 1991, vol. 325(6),
pp. 398-403.
\41\ Phillips, E.H., et al., ``The role of ADAMTS-13 activity
and complement mutational analysis in differentiating acute
thrombotic microangiopathies,'' J. Thromb. Haemost., 2016, vol.
14(1), pp. 175-85.
\42\ Coppo, P., ``Management of thrombotic thrombocytopenic
purpura,'' Transfus Clin Biol., Sep 2017, vol. 24(3), pp. 148-153.
\43\ Froissart, A., et al., ``Rituximab in autoimmune thrombotic
thrombocytopenic purpura: A success story,'' Eur. J. Intern. Med.,
2015, vol. 26(9), pp. 659-65.
---------------------------------------------------------------------------
Based on the applicant's statements as summarized above, the
applicant believes that CABLIVI[supreg] provides a new treatment option
for patients who have been diagnosed with aTTP. However, it is not
clear that CABLIVI[supreg] would involve the treatment of a different
type of disease or a different patient population. As stated earlier,
according to the applicant, patients who have been diagnosed with aTTP
have two SOC treatment options for a diagnosis of aTTP: PE, in which a
patient's blood plasma is removed through apheresis and is replaced
with donor plasma, and immunosuppression (for example, corticosteroids
and increasingly also rituximab), which is administered as an adjunct
to PE in the initial treatment for a diagnosis of aTTP. Therefore, it
appears that CABLIVI[supreg] is used to treat the same or similar type
of disease (a diagnosis of aTTP) and a similar patient population as
currently available treatment options.
We are inviting public comments on whether CABLIVI[supreg] is
substantially similar to other technologies and whether CABLIVI[supreg]
meets the newness criterion.
[[Page 19292]]
With regard to the cost criterion, the applicant conducted the
following analysis to demonstrate that the technology meets the cost
criterion. In order to identify the range of MS-DRGs that cases
representing potential patients who may be eligible for treatment using
CABLIVI[supreg] may map to, the applicant identified all MS-DRGs for
patients who had been hospitalized for a diagnosis of aTTP.
Specifically, the applicant searched the FY 2017 MedPAR file for
Medicare fee-for-service inpatient hospital claims submitted between
October 1, 2016 and September 30, 2017, and identified potential cases
by ICD-10-CM diagnosis code M31.1 (Thrombotic microangiopathy) and ICD-
10-PCS procedure codes 6A550Z3 (Pheresis of plasma, single) and 6A551Z3
(Pheresis of plasma, multiple). The applicant noted that it excluded
cases with an ICD-10-CM diagnosis code of D59.3 (Hemolytic-uremic
syndrome).
This resulted in 360 cases spanning 61 MS-DRGs, with approximately
67.2 percent of all potential cases mapping to the following 5 MS-DRGs:
------------------------------------------------------------------------
MS-DRG MS-DRG title
------------------------------------------------------------------------
MS-DRG 545.......................... Connective Tissue Disorders with
MCC.
MS-DRG 546.......................... Connective Tissue Disorders
without CC.
MS-DRG 547.......................... Connective Tissue Disorders
without CC/MCC.
MS-DRG 682.......................... Renal Failure with MCC.
MS-DRG 698.......................... Other Kidney and Urinary Tract
Diagnoses with MCC.
------------------------------------------------------------------------
Using the 242 identified cases that mapped to the top 5 MS-DRGs
above, the average case-weighted unstandardized charge per case was
$188,765. The applicant then standardized the charges and then removed
historic charges for items that are expected to be avoided for patients
who receive treatment involving CABLIVI[supreg]. The applicant
determined that 31 percent of historical routine bed charges, 65
percent of historical ICU charges, and 38 percent of historical blood
administration charges (which includes charges for therapeutic PE)
would be reduced because of the use of CABLIVI[supreg], based on the
findings from the Phase III clinical study HERCULES. The applicant
indicated it used the FY 2017 MedPAR file to determine the appropriate
amount of charges to remove. The applicant then inflated the adjusted
standardized charges by 8.864 percent utilizing the 2-year inflation
factor published by CMS in the FY 2019 IPPS/LTCH PPS final rule to
adjust the outlier threshold (83 FR 41722). (We note that this figure
was revised in the FY 2019 IPPS/LTCH PPS final rule correction notice.
The corrected final 2-year inflation factor is 1.08986 (83 FR 49844).
We further note that even when using the corrected final rule values to
inflate the charges, the average case-weighted standardized charge per
case exceeded the average case-weighted threshold amount.) The
applicant explained that the anticipated price for CABLIVI[supreg]'s
indication for the treatment of patients who have been diagnosed with
aTTP, in combination with plasma exchange and immunosuppressive
therapy, has yet to be determined and, therefore, no charges for
CABLIVI[supreg] were added in the analysis. Based on the FY 2019 IPPS/
LTCH PPS final rule correction notice data file thresholds for FY 2020,
the applicant determined the average case-weighted threshold amount was
$49,904. The final inflated average case-weighted standardized charge
per case was $145,543. Because the final inflated average case-weighted
standardized charge per case exceeds the average case-weighted
threshold amount, the applicant maintained that the technology meets
the cost criterion. We are inviting public comments on whether
CABLIVI[supreg] meets the cost criterion.
With respect to the substantial clinical improvement criterion, the
applicant asserted that it believes that CABLIVI[supreg] represents a
substantial clinical improvement compared to the use of currently
available treatments (PE and immunosuppressants) because it: (1)
Significantly reduces time to platelet count response, which is
consistent with the halting of platelet consumption in microthrombi;
(2) significantly reduces the number of patients with aTTP-related
death, recurrence of aTTP-related episodes, or a major thromboembolic
event; (3) reduces mortality; (4) reduces the proportion of patients
with recurrence of aTTP diagnoses; (5) reduces the proportion of
patients who develop refractory disease; (6) reduces the number of days
of PE; (7) reduces the mean length of intensive care unit stay and the
mean length of hospitalization; and (8) shows a trend of more rapid
normalization of organ damage markers. The applicant provided further
detail regarding these assertions, referencing the results of Phase II
and Phase III studies and an integrated efficacy analysis of both
studies.
The applicant reported that the Phase II study was a randomized,
single-blind, placebo controlled study entitled ALX-0681-2.1/10 (TITAN)
that examined the efficacy and safety of the use of CABLIVI[supreg]
compared to a placebo, with the primary endpoint being achievement of a
statistically significant reduction in time to platelet count response.
Seventy-five patients, 66 of which were white, (19 to 72 years old,
with a mean of 41.6 years old; 44 women and 31 men) with an episode of
aTTP were randomized 1:1 to receive either CABLIVI[supreg] (n=36) or
placebo (n=39), in addition to daily PE.\44\ Patients received their
first dose of CABLIVI[supreg] administered through intravenous
injection prior to the first PE, followed by daily doses administered
subcutaneously after each PE. After discontinuing PE, daily doses of
CABLIVI[supreg] administered through subcutaneous injection were
continued for 30 days. The median treatment duration with
CABLIVI[supreg] was 36 days.
---------------------------------------------------------------------------
\44\ Peyvandi, F., Scully, M., Kremer Hovinga, J.A., Cataland,
S., Kn[ouml]bl, P., Wu, H., Artoni, A., Westwood, J.P., Mansouri
Taleghani, M., Jilma, B., Callewaert, F., Ulrichts, H., Duby, C.,
Tersago, D., TITAN Investigators, ``Caplacizumab for Acquired
Thrombotic Thrombocytopenic Purpura,'' N Engl J Med., February 11,
2016, vol. 374(6), pp. 511-22. PMID: 26863353.
---------------------------------------------------------------------------
According to the applicant, significantly more patients in the
treatment arm met the primary endpoint [95 percent Confidence Interval
(CI) (3.78, 1.28)]. The applicant indicated that the time to platelet
count response improvement constitutes a significant substantial
clinical improvement because it demonstrated that patients treated with
CABLIVI[supreg] were 2.2 times more likely to achieve an acceptable
time to platelet count response than patients receiving treatment with
the placebo. Additionally, the applicant noted that exacerbation of
aTTP occurred in fewer patients who were treated with CABLIVI[supreg]
(8.3 percent) than placebo (28.2 percent). During the 1-month follow-up
period, 8 relapses (defined as a recurrence more than 30 days after
discontinuing PE) occurred in the CABLIVI[supreg] group with 7 of the
relapses occurring within 10 days of
[[Page 19293]]
discontinuing the study drug. In all seven of the relapses, ADAMTS13
activity was still severely suppressed at the end of the treatment
period, evidence of ongoing underlying immunological disease and
indicating an imminent risk of another relapse. The applicant explained
that according to post-hoc analyses, the group of patients who were
treated with CABLIVI[supreg] compared to placebo showed a decrease in
the percentage of patients with refractory disease (0 percent versus
10.8 percent), a reduction in the number of days of PE (7.7 days versus
11.7 days) and a trend to more rapid normalization of organ damage
markers (lactate dehydrogenase, cardiac troponin I and serum
creatinine). Finally, the applicant noted that there were no deaths in
the group of patients who were treated with CABLIVI[supreg]. However, 2
of the 39 placebo-treated patients (5.1 percent) died.
The applicant explained that the Phase III study was a randomized,
double-blind, placebo controlled study entitled ALX0681-C301 (HERCULES)
that examined the efficacy and safety of the use of CABLIVI[supreg]
compared to a placebo, with the primary endpoint being achievement of a
statistically significant reduction in time to platelet count response.
One hundred forty-five patients (18 to 79 years old, with a mean of 46
years old, 100 women and 45 men), with an episode of aTTP were
randomized 1:1 to receive either CABLIVI[supreg] (n=72) or placebo
(n=73) in addition to daily PE and immunosuppression.\45\ The applicant
explained that patients received a single 10 mg CABLIVI[supreg]
intravenous injection or placebo prior to the first PE, followed by a
daily CABLIVI[supreg] 10 mg subcutaneous injection or placebo after
completion of PE, for the duration of the daily PE treatment period and
for 30 days thereafter. According to the applicant, if at the end of
this treatment period (daily PE treatment period and 30 days after)
there was evidence of persistent underlying immunological disease
activity (indicative of an imminent risk for recurrence), treatment
could be extended weekly for a maximum of 4 weeks, together with
optimization of immunosuppression. The applicant indicated that
patients who experienced a recurrence while undergoing study drug
treatment were switched to open-label CABLIVI[supreg] and they were
again treated for the duration of daily PE treatment and for 30 days
thereafter. If at the end of this treatment period (daily PE treatment
period and 30 days after) there was evidence of ongoing underlying
immunological disease, open-label treatment with CABLIVI[supreg] could
be extended weekly for a maximum of 4 weeks, together with optimization
of immunosuppression. Patients were followed for 28 days after
discontinuation of treatment. Upon recurrence during the follow-up
period (that is, after all study drug treatment had been discontinued),
there was no re-initiation of the study drug because recurrence at this
point was treated according to the SOC. The median treatment duration
with CABLIVI[supreg] in the double-blind period was 35 days.
---------------------------------------------------------------------------
\45\ Scully, M., et al., ``Treatment of Acquired Thrombotic
Thrombocytopenic Purpura with Caplacizumab,'' N. Engl. J. Med., (In
Press).
---------------------------------------------------------------------------
According to the applicant, patients in the treatment arm were more
likely to achieve platelet count response at any given time point,
compared to the placebo [95 percent CI (1.1, 2.2)]. The applicant
believed that this constitutes a significant substantial clinical
improvement because patients who were treated with CABLIVI[supreg] were
1.55 times more likely to achieve platelet count response at any given
time point, compared to placebo. The applicant also indicated that,
compared to placebo, treatment with CABLIVI[supreg] resulted in a 74
percent reduction in the number of patients with aTTP-related death,
recurrence of aTTP diagnosis, or a major thromboembolic event, during
the study drug treatment period (p60 61 62 (3)
gastric signet ring adenocarcinoma; (4) pancreatic cancer; and (5)
other abdominal malignancies. There were 13 patients associated with
these 4 case series.
---------------------------------------------------------------------------
\59\ Seneviratne, D., McLaughlin, C., Todor, D., Kaplan, B.,
Fields, E., ``The CivaSheet: The new frontier of intraoperative
radiation therapy or a pricier alternative to LDR brachytherapy?,''
Advances in Radiation Oncology, 2018, vol. 3, pp. 87-91.
\60\ Zhen, H., Turian, J.V., Sen, N., et al.,''Initial clinical
experience using a novel Pd-103 surface applicator for the treatment
of retroperitoneal and abdominal wall malignancies,'' Advances in
Radiation Oncology, 2018, vol. 3, pp. 216-220.
\61\ Howell, K.J., Meyer, J.E., Rivard, M.J., et al., ``Initial
Clinical Experience with Directional LDR Brachytherapy for
Retroperitoneal Sarcoma,'' submitted Int J of Rad Onc Biol Phys,
2018.
\62\ Turian, J.V., ``Emerging Technologies for IORT:
Unidirectional Planar Brachytherapy Sources,'' Presented at AAPM
2017 Annual Meeting.
---------------------------------------------------------------------------
Seneviratne, et al.'s case series report documented experience with
the use of the CivaSheet[supreg] device in a 78 year old male patient
who had been diagnosed with axillary squamous cell carcinoma. According
to the case series report, prior to surgery a dose of 58 Gy, prescribed
to the 95 percent isodose line (5 percent), was delivered
in 2 Gy fractions with 3-dimensional conformal EBRT with concurrent
weekly administration of cisplatin 40 mg/m2 at an outside facility.
Magnetic resonance imaging scans obtained 3 months post-treatment
revealed that the mass had decreased in size to 3.8 cm x 2.5 cm x 3.9
cm, but maintained encasement of the axillary artery, axillary vein,
and several inferior branches of the brachial plexus. Concerns with
regard to increased toxicity to the axillary structures discouraged
further EBRT, and the CivaSheet[supreg] device was implanted
immediately post tumor resection. Given that microscopic disease within
formerly irradiated tissue was being treated, a prescription dose of 20
Gy at 5 mm from the surface of the mesh was considered adequate because
of its delivery of a biologically effective dose (BED)-10 of 39.8 Gy
and equivalent dose (EQD)-2 of 33.2 Gy to the tumor bed, while limiting
the D2cc for the brachial plexus to a BED3 of 27.9 Gy and EQD2 of 16.7
Gy, based on post implant analysis. According to the Seneviratne, et
al. analysis, this approach allowed for a significantly limited dose to
be delivered to the brachial plexus. A composite dose constraint of
D2cc of 75 Gy was selected on the basis of recent data showing elevated
clinical brachial plexopathy rates beyond this threshold. This
constraint was met with an estimated composite EQD2 of 74.7 Gy, which,
according to the applicant, would not have been obtainable with EBRT to
a tumor bed EQD2 of greater than or equal to 30 Gy. The patient was
discharged on the same day with instructions on wound care and
radiation safety. According to the applicant, the incision healed well,
with no signs of infection, seroma, or lymphadenopathy during monthly
follow-up visits. At the 8-month follow-up visit, the patient was
documented to only have minor shoulder pain. Seneviratne, et al., also
discussed their views on the advantages of the use of
[[Page 19298]]
the CivaSheet[supreg] device, which include its bio-absorbability, ease
of visualization with imaging, potential for intra-operative
customization, ability to complement various treatment approaches
including EBRT and surgical resection, and ease of implantation with
minimal training.
To further substantiate its assertions of a reduced rate of device-
related complications regarding the CivaSheet[supreg] device, the
applicant stated that its malleability is likely to be particularly
useful in treating irregularly shaped surgical cavities, such as those
created after breast lumpectomies or pelvic side wall resections.
According to the applicant, the CivaSheet[supreg] device also overcomes
several shortcomings observed even among those LDR mesh devices that
use the same isotope. According to the applicant, as the vicryl sutures
of traditional LDR mesh devices bend and curve around irregular
surfaces during placement, the spacing and orientation of the
radioactive seeds may be altered, leading to unpredictable variations
in isodose geometry. The applicant stated that, in contrast, the
polymer encapsulation of the Pd-103 Civa seeds before embedding within
the membrane allows the sources to maintain their orientation in space
and deliver radiation in accordance with the predetermined geometry.
According to the applicant, additionally, unlike older LDR mesh devices
that run the risk of source dispersion after mesh degradation, the
polymer encapsulation allows the seeds to maintain their placement even
as the membrane is absorbed over time. In this same case study,
Seneviratne, et al., stated that a 3-month post implantation imaging of
the CivaSheet[supreg] device demonstrated that the radioactive source
geometry had remained stable since the initial implantation.
The applicant also provided Howell, et al.'s case series results of
six patients diagnosed with recurrent retroperitoneal sarcoma who had
been treated with the use of the CivaSheet[supreg] device to support
its claims of reduced rate of toxicity and improved local control.
Similar to the Seneviratne, et al. case series report, Howell, et al.'s
case series' report also noted concerns regarding prior EBRT, costs
associated with intra-operative radiation therapy both for the patient
and the hospital, and concerns of at-risk surrounding anatomic
structures. Given these concerns, Howell, et al.'s case series report
also investigated LDR brachytherapy using CivaSheet[supreg]. Amongst
the six patients observed, five patients had diagnoses of recurrent
disease in the retroperitoneum or pelvic side wall; one patient had a
diagnosis of locally-advanced leiomyosarcoma with no previous
treatment. Regarding prior treatment, two patients had prior EBRT at
first diagnosis. Four patients received neoadjuvant EBRT prior to
surgery in addition to treatment involving CivaSheet[supreg]
brachytherapy. The LDR brachytherapy dose was determined using
radiobiological calculations of biological effective dose (BED) based
on the linear-quadratic model and EQD2 values. An LDR brachytherapy
dose of 20 to 60 Gy (36 Gy mean) was administered, corresponding to BED
values of 15 to 53 Gy (29 Gy mean) and EQD2 values of 12 to 43 Gy (23
Gy mean). Because the goal was to provide a conformal radiation boost
for an additional 15 to 20 Gy EQD2, the prescribed absorbed doses were
considered appropriate. All patients were followed by CT scan to assess
implant migration, observed radiation-related toxicities, and evidence
for local recurrence between 2.5 weeks and 3 months. No evidence of
implant migration or radiation-related toxicities was found. Based on
these results, the study concluded that LDR directional brachytherapy
delivered a targeted dose distribution that was successfully used to
treat retroperitoneal sarcoma, and that the utilized device is an
important option for the treatment of patients who have been diagnosed
with retroperitoneal sarcoma having close/positive surgical margins
and/or in combination with EBRT to optimize local control.
Two other case series, by Zhen, H. et al.,\63\ and Turian, et
al.,\64\ were submitted by the applicant to support the assertion of
reduced rate of device-related complications. Both case series assessed
the use of LDR brachytherapy using the CivaSheet[supreg] device in the
tumor bed given the same clinical challenges outlined in case series
observed and investigated in the Seneviratne, et al., and Howell, et
al. analyses in patients previously treated with chemoradiation
protocols and in patients who had been diagnosed with recurrent tumors
close to important functional tissues. Both case series assessed LDR
brachytherapy using the CivaSheet[supreg] device in the treatment of
different cancers like retroperitoneal sarcomas, pancreatic cancers,
and gastric singnet ring adenocarcinoma or other abdominal carcinomas.
Both case series followed the patients with CT imaging sometime between
2.5 weeks and 86 weeks. Both case series' study concluded that LDR
brachytherapy with the use of the CivaSheet[supreg] device was a
feasible alternative treatment modality for the cancers treated in each
case series. According to Zhen, et al., an advantage of using the
CivaSheet[supreg] device is that the CivaDot sheets can be easily cut
to any size and shape at the time of implant. The author further stated
that the CivaDot sheet is malleable and can conform to curved surfaces.
This device characteristic, according to the author, gives the
physician more flexibility to treat tumor beds with irregular shapes
and surface curvatures compared with electron beam cylindrical
applicators, thereby reducing the rate of device-related complications.
However, the analysis by Zhen, et al. also indicated that a limitation
in dosimetric evaluation using CT imaging is related to the inability
to identify the orientation of the individual CivaDot mainly because of
limited resolution and metal artifact caused by the gold plating.
CivaDot orientation is inferred from the fact that all dots are
embedded in a membrane that is sutured to the tumor bed and because the
post-implant CT scan shows the shape of the CivaSheet[supreg] seeds
being maintained. Also, Zhen, et al. noted that surgical clips could be
mistakenly identified as CivaDots. The analysis by Zhen, et al.
recommended that the use of surgical clips should be minimized.
---------------------------------------------------------------------------
\63\ Zhen, H., Turian, J.V., Sen, N., et al.,''Initial clinical
experience using a novel Pd-103 surface applicator for the treatment
of retroperitoneal and abdominal wall malignancies'', Advances in
Radiation Oncology, 2018, vol. 3, pp. 216-220.
\64\ Turian, J.V., ``Emerging Technologies for IORT:
Unidirectional Planar Brachytherapy Sources,'' Presented at AAPM
2017 Annual Meeting.
---------------------------------------------------------------------------
With regard to the reduced rate of toxicity, the applicant provided
a clinical case series by Howell, et al.\65\ to show that shielding
healthy tissues while irradiating the tumor bed after surgical
resection was achieved by providing a conformal radiotherapy, a novel
Pd-103 low-dose rate (LDR) brachytherapy device. Methods and materials
of the case include the following: The LDR brachytherapy device was
considered for patients who had been diagnosed with recurrent
retroperitoneal sarcoma, had received prior radiotherapy to the area,
and/or had anatomy concerning for high-risk margins predicted for
recurrence after resection. The case series included the clinical
conclusions for five patients who had been diagnosed with recurrent
disease in the retroperitoneum or pelvic side wall, one patient who had
been diagnosed with locally-advanced leiomyosarcoma with no previous
treatment, two patients who had prior
[[Page 19299]]
EBRT at first diagnosis, and four patients who received neoadjuvant
EBRT prior to surgery in combination with brachytherapy. The LDR
brachytherapy dose was determined using radiobiological calculations of
biological effective dose (BED) based on the linear-quadratic model and
EQD2 values. An LDR brachytherapy dose of 20 to 60 Gy (36 Gy mean) was
administered, corresponding to BED values of 15 to 53 Gy (29 Gy mean)
and EQD2 values of 12 to 43 Gy (23 Gy mean). Because the goal was to
provide a conformal radiation boost for an additional 15 to 20 Gy EQD2,
the prescribed absorbed doses were considered appropriate. According to
the applicant, results showed that radiation was delivered to the at-
risk tissues with minimal irradiation of adjacent healthy structures or
structures occupying the surgical cavity after tumor resection.
According to the applicant, clinical outcomes indicated feasibility for
surgical implantation and promising results in comparison to current
standards-of-care. The device did not migrate over the course of
follow-up and there were no observed radiation-related toxicities.
---------------------------------------------------------------------------
\65\ Howell, K.J., Meyer, J.E.,Rivard, M.J. et al., ``Initial
Clinical Experiences with Directional LDR Brachytherapy for
Retroperitoneal Sarcomo, submitted to Int J of Rad Onc Biol Phys,
2018.
---------------------------------------------------------------------------
The Howell, et al. clinical case series concluded that LDR
directional brachytherapy delivered a targeted dose distribution that
was successfully used to treat retroperitoneal sarcoma and that the
utilized device is an important option for the treatment of patients
who have been diagnosed with retroperitoneal sarcoma having close/
positive surgical margins and/or in combination with EBRT to optimize
local control.
The applicant also cited three additional case series to support
their assertions of reduced rate of device-related complications and
reduced rate of radiation toxicity. The first is on file at CivaTech in
which they indicated that more than 60 patients, since 2015, had
CivaSheet[supreg] implanted with no reported device-related toxicity in
patients previously treated with maximal EBRT. No other details were
provided by the applicant. The second case series by Taunk, et al.\66\
assessed the use of CivaSheet[supreg] in three patients who had been
diagnosed with colorectal adenocarcinoma who had undergone prior
induction chemotherapy and neoadjuvant chemoradiation.
CivaSheet[supreg] was placed in the tumor bed and patients were
followed with CT imaging to assess implant migration, 30- and 90-day
radiation toxicity and local recurrence. One patient was deemed not a
feasible candidate because the CivaSheet[supreg] could not be uniformly
opposed to the sacrum due to the degree of concavity. The other two
patients underwent successful CivaSheet[supreg] implantation, and at 30
days showed stability of the device and no apparent toxicity. In the
final additional case series from Rivard, et al.,\67\ a single patient
who had been diagnosed with pelvic side wall cancer (type not
indicated) was implanted with CivaSheet[supreg] and the
CivaSheet[supreg] dose distributions were compared to those of
conventional low-dose rate, low-energy photon-emitting brachytherapy
seeds (that is, palladium 103, Iodine-125, and Cesium-131). According
to the applicant, results suggest gold-shielding CivaDots attenuate
radiation for directional brachytherapy and CivaSheet[supreg] provides
a therapeutic target dose, while substantially minimizing critical
structure doses. In this specific case study, the applicant stated that
the use of CivaSheet[supreg] showed decreased radiation to adjacent
organs, such as the bowel and the bladder.
---------------------------------------------------------------------------
\66\ Taunk, N.K., Cohen, G., Taggar, A.S., et al., ``Preliminary
Clinical Experience from a Phase I Feasibility Study of a Novel
Permanent Unidirectional Intraoperative Brachytherapy Device,'' ABS
2017 Annual Meeting.
\67\ Rivard, M.J., ``Low-energy brachytherapy sources for pelvic
sidewall treatment,'' Presented at ABS 2016 Annual Meeting.
---------------------------------------------------------------------------
With regard to decreasing the number of future hospital visits, the
applicant provided a poster presentation presented at the American
Brachytherapy Society 2017 Annual Meeting. The purpose of this study
was to investigate the feasibility of using intra-operative directional
brachytherapy for the treatment of squamous cell carcinoma of the
oropharynx. The study included a single patient who had received a
prior course of external beam radiation therapy of 70 Gy in 2015. Due
to positive margins near the carotid after the resection, and the
increased risk of additional external radiation, brachytherapy was
considered as a treatment option. CivaSheet[supreg] was used for the
implant. The Pd-103 sources were spaced 8 mm apart on a rectangular
grid. Unidirectional dose was achieved by a 0.05 mm thick gold disk-
shaped foil on the reverse side of each source. A dose of 120 Gy at 5
mm depth was prescribed. After the resection, the entire polymer sheet
was placed on the treatment area to determine the needed dimensions.
The CivaSheet[supreg] device was then removed and cut to size with
scissors leaving 26 Pd-103 sources remaining. The surgeon used 3.0
vicryl sutures for attachment in a concave shape over the carotid
artery, where there was a positive margin. The gold foil was positioned
to protect the neck flap and closure. The surgical team completed the
procedure and the patient recovered without any complications.
Results of the study showed that the sources remained in position
in a concave array pattern. Due to the dose fall-off of Pd-103, the
calculated dose to critical structures was minimized. Because the
surgical implant of the CivaDot sheet proceeded as expected with no
complications and the post-implant plan indicated that the
CivaSheet[supreg] remained in position with the radioactive side
contacting the treatment area, the applicant asserts that future
hospital visits will be decreased because the patient will not return
for EBRT.
With regard to decreases in the rate of subsequent therapeutic
interventions, the applicant stated that the standard-of-care for most
patients undergoing surgery is typically preceded or followed by a form
of external beam radiation therapy. A typical course of intensity
modulated radiation therapy (IMRT) is 25 to 30 fractions (separate
treatments) delivered over the course of 3 to 6 weeks. The applicant
stated that, for some patients, CivaSheet[supreg] will be the only form
of radiation therapy they will receive. CivaSheet[supreg] is implanted
in one procedure and radiation is locally delivered over the course of
several weeks, while the sources provide a continuous dose and later
decay. The device is not removed and no additional follow-up visits are
required for the patient to receive therapeutic intervention. According
to the applicant, use of CivaSheet[supreg] can avoid the time and
expense of dozens of radiation therapy visits over the course of
several weeks as compared to EBRT. The applicant further stated that
the published clinical data provided with its application \68\ shows
that the use of CivaSheet[supreg] is an effective and safe
combinational treatment to external beam radiation therapy. According
to the applicant, radiation oncologists can use CivaSheet[supreg] to
increase the dose of radiation that can be delivered to a tumor margin,
without increasing toxicity and that this may reduce the odds that a
patient experiences cancer recurrence.69 70 71 The applicant
also
[[Page 19300]]
asserted that the targeted radiation approach has demonstrated no toxic
effects for patients. The applicant further stated that other forms of
radiation have a known rate of complications and toxicity that result
in the need for additional therapies and interventions (for example,
topical creams for skin reddening, and medicine for pain). The
applicant indicated that there has been no change in concomitant
medications prescribed because of the use of the CivaSheet[supreg]
implant either on or off trial. The applicant did not link these claims
to any of the studies provided with its application. In addition, the
applicant asserts that, of the case studies they provided, there have
been no instances of therapeutic interventions to resolve an issue that
was induced by the use of the CivaSheet[supreg] device to deliver
radiation.72 73 74
---------------------------------------------------------------------------
\68\ Taunk, N.K., Cohen, G., Taggar, A.S., et al., ``Preliminary
Clinical Experience from a Phase I Feasibility Study of a Novel
Permanent Unidirectional Intraoperative Brachytherapy Device,'' ABS
2017 Annual Meeting.
\69\ Rivard, Mark J., ``Low energy brachytherapy sources for
pelvic sidewall treatment,'' abstract presented at the ABS 2016
Annual Meeting.
\70\ Yoo, S.S., Todor, D.A., Myers, J.M., Kaplan, B.J., Fields,
E.C., ``Widening the therapeutic window using an implantable, uni-
directional LDR brachytherapy sheet as a boost in pancreatic
cancer,'' ASTRO 2018 Annual Meeting San Antonio, TX.
\71\ Howell, K.J., Meyer, J.E., Rivard, M.J., et al., ``Initial
Clinical Experience with Directional LDR Brachytherapy for
Retroperitoneal Sarcoma,'' submitted Int J of Rad Onc Biol Phys,
2018.
\72\ Ibid.
\73\ Rivard, Mark J., ``Low energy brachytherapy sources for
pelvic sidewall treatment,'' abstract presented at the ABS 2016
Annual Meeting.
\74\ Yoo, S.S., Todor, D.A., Myers, J.M., Kaplan, B.J., Fields,
E.C., ``Widening the therapeutic window using an implantable, uni-
directional LDR brachytherapy sheet as a boost in pancreatic
cancer,'' ASTRO 2018 Annual Meeting San Antonio, TX.
---------------------------------------------------------------------------
With regard to improvement in back pain and appetite (compared to
baseline) in pancreatic cancer patients, the applicant asserted that
patients answered standardized, international questionnaire EORTC QLQ-
C30 and PANC26 and that these results are on file at CivaTech. The
applicant provided the baseline, 70 days post-operative and 98 days
postoperative patient responses to ``Have you ever had back pain?''
Baseline response: 1.5; 70 days post-operative response: 1.0 and 98
days post-operative response: 1.0. The applicant also provided
baseline, 70 days post-operative and 98 days post-operative patient
responses to ``Were you restricted in the amounts of food you could eat
as a result of your disease or treatment?'' Baseline response: 2.5; 70
days postoperative response: 1.0 and 98 days postoperative response:
1.0. (Response Values: 1.0 = ``Not at all''; 2.0 = ``A little''; 3.0 =
``Quite a bit''; 4.0 = ``Very much'').
With regard to improved local control for pancreatic cancer
patients, the applicant provided the results of a dosimetric study
entitled, ``Widening the Therapeutic Window Using an Implantable, Uni-
directional LDR Brachytherapy Sheet as a Boost in Pancreatic Cancer
Case Series,'' a poster presented at the ASTRO 2018 Annual Meeting.
According to background information in the applicant's poster,
pancreatic patients often undergo neoadjuvant chemotherapy and
chemoradiation in preparation for surgical resection of the tumor. In
addition, oftentimes after neoadjuvant therapy there are inflammatory
changes that, unfortunately, hinder pre-operative imaging and create
the potential for unreliable determination of tumor resection.
Accompanying the potentially unreliable determination of tumor
resectability are patient concerns when positive retroperitoneal
margins have close proximity to major vasculature. The applicant noted
that additional EBRT boost, initiated post operatively, is an option,
but difficult given bowel constraints and the difficulty in identifying
the area at highest risk. Given these constraints associated with
treating pancreatic cancers, the purpose of this study was to
demonstrate the ability of the LDR brachytherapy CivaSheet[supreg]
device to deliver a focal high-dose boost, targeted to the area at
highest risk in patients who received neoadjuvant chemoradiation. This
dosimetric case series consisted of four patients who had been
diagnosed with borderline resectable pancreatic cancer who received
neoadjuvant FOLFIRINOX followed by gemcitabine-based
chemoradiotherapy (chemoRT) to 50.4 Gy in 28 fractions with dose
prescribed to the gross tumor plus a 1 cm margin. According to the
poster provided by the applicant, after neoadjuvant therapy, the
multidisciplinary team was concerned for close or positive margin
resection. Using the CivaSheet[supreg] device, a 38 Gy EQD2 dose to 5
mm depth was implanted in these patients and a total dose of 88.4 Gy
was delivered to the targeted tissue. Post-operatively, patients had a
CT scan to identify the tumor bed contour, as well as the contour of
surrounding at-risk organs; the small bowel (SB) was contoured as the
bowel bag and included the entire peritoneal cavity. Following the CT
scan, brachytherapy plans, as well as EBRT boost plans, were created
for each patient. A dose-volume histogram (DVH) from initial 3D
treatment plans for all patients showed the SB volume receiving 45 Gy
(V45) was a median of 78.2 cc (range 61.7-107.1 ccs) and maximum bowel
doses were a median of 53.2 Gy, range 53.1-53.6 Gy. According to the
applicant, the V45 for SB should be less than 195 cc, with a maximum of
less than or equal to 58 Gy to prevent SB obstruction, fistula and
perforation. According to the applicant, with the CivaSheet[supreg]
device, the boost dose was dramatically increased while SB exposure was
marginal at about 1/10th of the prescription dose. For the target, the
CivaSheet[supreg] delivered the prescription dose to 5 mm depth with a
large inhomogeneous dose throughout the tumor bed with the minimum dose
of 38 Gy. Dosimetric comparison of a CivaSheet[supreg] tumor bed boost
and a Stereotactic Body Radiation Therapy (SBRT) tumor bed boost to the
SB was 9.6 Gy compared to 24 Gy for external beam plan. According to
the applicant, the conclusions from this case series are that applying
a brachytherapy uni-directional source to the area at highest risk can
serve to improve the therapeutic index by improving the local control
and minimizing toxicities in pancreatic cancer patients after
neoadjuvant therapy.
With regard to whether CivaSheet[supreg] represents a substantial
clinical improvement relative to other brachytherapy technologies
currently available, we are concerned that all of the supporting data
appear to be feasibility studies substantiating the use of the
CivaSheet[supreg] in different cancers and difficult anatomic
locations. We also are concerned that there do not appear to be any
comparisons to other current treatments, nor any long-term follow-up
with comparisons to currently available therapies. We are inviting
public comments on whether CivaSheet[supreg] meets the substantial
clinical improvement criterion.
We did not receive any written comments in response to the New
Technology Town Hall meeting notice published in the Federal Register
regarding the substantial clinical improvement criterion for the
CivaSheet[supreg] or at the New Technology Town Hall meeting.
d. CONTEPOTM (Fosfomycin for Injection)
Nabriva Therapeutics U.S., Inc. submitted an application for new
technology add-on payments for CONTEPOTM for FY 2020.
CONTEPOTM is intended to treat complicated urinary tract
infections (cUTIs) caused by multi-drug resistant (MDR) pathogens in
hospitalized patients. CONTEPOTM has not yet received FDA
approval. The FDA has accepted the applicant's New Drug Application
(NDA) using its Priority Review expedited program.
Complicated urinary tract infections are characterized by chills,
rigors, or fever (temperature of greater than or equal to 38.0 [deg]C);
elevated white blood cell count (greater than 10,000/mm\3\), or
[[Page 19301]]
left shift (greater than 15 percent immature PMNs); nausea or vomiting;
dysuria, increased urinary frequency, or urinary urgency; and lower
abdominal pain or pelvic pain. A related condition, acute
pyelonephritis (AP), is characterized by chills, rigors, or fever
(temperature of greater than or equal to 38.0 [deg]C); elevated white
blood cell count (greater than 10,000/mm\3\), or left shift (greater
than 15 percent immature PMNs); nausea or vomiting; dysuria, increased
urinary frequency, or urinary urgency; flank pain; and costo-vertebral
angle tenderness on physical examination. Risk factors for infection
with drug-resistant organisms do not, on their own, indicate a
cUTI.\75\ The applicant stated that CONTEPOTM would offer a
new potential first-line treatment for patients with cUTIs suspected to
be caused by MDR pathogens in the United States.
---------------------------------------------------------------------------
\75\ Hooton, T. and Kalpana, G., 2018, ``Acute complicated
urinary tract infection (including pyelonephritis) in adults,'' In
A. Bloom (Ed.), UpToDate. Available at: https://www.uptodate.com/contents/acute-complicated-urinary-tract-infectionincluding-pyelonephritis-in-adults.
---------------------------------------------------------------------------
The applicant stated that CONTEPOTM is an epoxide
intravenous antibiotic that eradicates bacteria by inhibiting the
bacteria's ability to form cell walls, which are critical for a cell's
survival and growth. The applicant asserted that CONTEPOTM
offers a broad spectrum of bactericidal Gram-negative and Gram-positive
activity, including activity against Extended-spectrum [beta]-lactamase
(ESBL)-producing Enterobacteriaceae, as well as other contemporary MDR
organisms.
The applicant noted that there are currently no ICD-10-PCS
procedure codes that could be used to uniquely identify the use of
CONTEPOTM. However, the applicant stated that potential
cases representing patients who may be eligible to receive treatment
through the administration of CONTEPOTM could be identified
with ICD-10-PCS codes 3E03329 (Introduction of Other Anti-infective
into Peripheral Vein, Percutaneous Approach) or 3E04329 (Introduction
of Other Anti-infective into Central Vein, Percutaneous Approach). The
applicant has submitted a request for approval for a new ICD-10-PCS
procedure code to uniquely identify CONTEPOTM administration
in FY 2020.
The applicant has recommended that CONTEPOTM be
administered as follows: 6 g every 8 hours by intravenous (IV) infusion
over 1 hour for up to 14 days for patients 18 years of age or older,
with an estimated creatinine clearance (CrCl) greater than or equal to
50 mL/min. Dosage adjustment is required for patients whose creatinine
clearance is 50 mL/min or less.
As discussed earlier, if a technology meets all three of the
substantial similarity criteria, it would be considered substantially
similar to an existing technology and would not be considered ``new''
for purposes of new technology add-on payments.
With regard to the first criterion, whether the product uses a
similar mechanism of action, the applicant stated that
CONTEPOTM's mechanism of action differentiates it from other
approved injectable antibiotics. The applicant reports that
CONTEPOTM, as an injectable epoxide and sole antibiotic
class member, inhibits an early step in peptidoglycan biosynthesis by
covalently binding to MurA, an enzyme that catalyzes the first
committed critical step in a bacteria's ability to form a cell wall
and, therefore, the cell's survival and growth. The applicant indicated
that CONTEPOTM's mechanism of action is unique in comparison
to all other injectable antibiotics by working at a different and
earlier stage of cell wall synthesis inhibition, such that the cell
wall lacks suitable integrity and the bacteria die quickly. The
applicant further stated that because of this unique mechanism of
action, CONTEPOTM lacks cross resistance with other existing
classes of intravenous antibiotics.
With respect to the second criterion, whether the product is
assigned to the same or a different MS-DRG, the applicant asserted that
patients who may be eligible to receive treatment involving
CONTEPOTM include hospitalized patients who have been
diagnosed with a cUTI. The applicant noted that the relevant existing
ICD-10-PCS procedure codes (3E3329 and 3E04329) map to many existing
MS-DRGs. The applicant lists the most common of these MS-DRGs as MS-DRG
871 (Septicemia or Severe Sepsis without MV >96 Hours with MCC); MS-DRG
690 (Kidney and Urinary Tract Infections without MCC); MS-DRG 698
(Other Kidney and Urinary Tract Diagnoses with MCC); MS-DRG 872
(Septicemia or Severe Sepsis without MV >96 hours without MCC); MS-DRG
689 (Kidney and Urinary Tract Infections with MCC); MS-DRG 699 (Other
Kidney and Urinary Tract Diagnoses with CC); MS-DRG (683 Renal Failure
with CC); MS-DRG 682 (Renal Failure with MCC); MS-DRG 853 (Infectious
and Parasitic Diseases with O.R. Procedure with MCC); and MS-DRG 291
(Heart Failure and Shock with MCC). Cases involving the use of
CONTEPOTM would likely be assigned to the same MS-DRGs to
which cases involving treatment with comparator drugs are assigned.
With respect to the third criterion, whether the use of the
technology involves the treatment of the same or similar type of
disease and the same or similar patient population, the applicant
asserted that the use of CONTEPOTM would treat a different
patient population than existing and currently available treatment
options. While many drugs treat the broad population of patients who
have been diagnosed with cUTIs, the applicant asserts that increasing
rates of Enterobacteriaceae resistance to fluoroquinolones and ESBLs
have limited both classes use as first-line therapies among inpatients
with infections caused by suspected or confirmed MDR pathogens. The
applicant cited a study, which estimates the prevalence of drug
resistance among uropathogens isolated from hospitalized patients in
the United States. According to the study, there is a more than a two-
fold increase in ESBL-producing E. coli (from 3.3 percent to 8
percent), ESBL-producing K. pneumoniae (from 9.1 percent to 18.6
percent), and CRE (from 0 percent to 2.3 percent) causing UTIs in the
period between 2000 and 2009.\76\ The applicant further asserts that
the use of CONTEPOTM will also treat a different diseased
patient population than the currently available therapies. According to
the applicant, CONTEPOTM's unique mechanism of action
amongst injectable antibiotics and novel class allows the use of
CONTEPOTM to reach different and expanded patient
populations, particularly those patients who have been diagnosed with a
cUTI that may have pathogens resistant or suspected resistance to ESBL
and CRE, or fluoroquinolone resistance. Further, the applicant stated
that CONTEPOTM's stewardship value to clinicians is as a
carbapenem-sparing potential therapy that may result in real world
reductions in CRE resistance, further sparing a last-line of defense
for critically ill patient populations, which due to unique resistance
profiles, the applicant asserts constitute a different population than
is currently treated.
---------------------------------------------------------------------------
\76\ Shorr, A.F., Zilberberg, M.D., Micek, S.T., Kollef, M.H.,
``Prediction of Infection Due to Antibiotic-Resistant Bacteria by
Select Risk Factors for Health Care-Associated Pneumonia,'' Arch
Intern Med, 2008, vol. 168(20), pp. 2205-10.
---------------------------------------------------------------------------
Based on the applicant's statements as summarized above, the
applicant believes that CONTEPOTM is not substantially
similar to any existing intravenous antibiotic treatment. However, we
are concerned with respect to the first criterion as to whether the
mechanism of action described by the
[[Page 19302]]
applicant is unique to CONTEPOTM or whether it may be
similar to other drugs that inhibit cell wall development, including
penicillins, cephalosporins, and carbapenems. With respect to the
second criterion, we believe that potential cases involving the use of
CONTEPOTM would be assigned to the same MS-DRGs as cases
involving comparator antibiotics. Finally, with respect to the third
criterion, we are concerned whether CONTEPOTM treats a
unique patient population, as the applicant asserts. While the variety
of antibiotic resistance patterns certainly warrants a varied
armamentarium for clinicians, there are many existing antimicrobials
that are approved to generally treat cUTIs and MDR pathogens. We are
concerned as to whether hospitalized patients who have been diagnosed
with cUTIs, including those with MDR pathogens, would constitute a
unique patient population, given that there are existing treatment
options for these patients. This concern as to whether the technology
may be considered to treat a new patient population seems particularly
relevant for an antibiotic due to the evolving nature of global
bacterial resistance patterns, and, specifically, the applicant's
assertion that the use of CONTEPOTM would be a new tool in
the growing battle against MDR bacteria infections. We are inviting
public comments on whether CONTEPOTM is substantially
similar to any existing technologies and whether it meets the newness
criterion, including with respect to the concerns we have raised.
With regard to the cost criterion, the applicant used the FY 2017
MedPAR Limited Data Set (LDS) to assess the MS-DRGs to which potential
cases representing hospitalized patients who may be eligible for
treatment involving CONTEPOTM would most likely be mapped.
According to the applicant, CONTEPOTM is anticipated to be
indicated for the treatment of hospitalized patients who have been
diagnosed with cUTIs. The applicant identified 199 ICD-10-CM diagnosis
code combinations that identify hospitalized patients who have been
diagnosed with a cUTI. Searching the FY 2017 MedPAR data file for these
ICD-10-CM diagnosis codes resulted in a total of 508,821 potential
cases that span 559 unique MS-DRGs, 510 of which contained more than 10
cases. The applicant excluded MS-DRGs with minimal volume (that is, 10
cases or less) from the cohort of the analysis (a total of 201 cases
and 49 MS-DRGs), and this resulted in a total of 508,620 cases across
461 MS-DRGs.
Using 100 percent of the potential cases (508,620), the applicant
determined an average case-weighted unstandardized charge per case of
$59,009. The applicant standardized the charges for each case and
inflated each case's charges by applying the FY 2019 IPPS/LTCH PPS
final rule outlier charge inflation factor of 1.08864 (83 FR 41722).
(We note that the 2-year inflation factor was revised in the FY 2019
IPPS/LTCH PPS final rule correction notice to 1.08986 (83 FR 49844).
However, we further note that even when using the corrected final rule
values to inflate the charges, the average case-weighted standardized
charge per case for each scenario exceeded the average case-weighted
threshold amount.) The applicant examined associated charges per MS-DRG
and removed charges for potential antibiotics that may be replaced by
the use of CONTEPOTM. Specifically, the applicant identified
5 antibiotics currently used for the treatment of patients who have
been diagnosed with a cUTI and calculated the cost of each of these
drugs for administration over a 14-day inpatient hospitalization.
Because patients who have been diagnosed with a cUTI would typically
only be treated with one of these antibiotics at a time, the applicant
estimated an average of the 14-day cost for the 5 antibiotics. The
applicant then took this cost and converted it to a charge by dividing
the costs by the national average CCR of 0.191 for drugs from the FY
2019 IPPS/LTCH PPS final rule (83 FR 41273). The applicant calculated
an average case-weighted standardized charge per case of $71,333 using
the percent distribution of MS-DRGs as case-weights. Based on this
analysis, the applicant determined that the final inflated average
case-weighted standardized charge per case for CONTEPOTM
exceeded the average case-weighted threshold amount of $52,203 by
$19,130.
Because of the large number of cases included in this cost
analysis, the applicant conducted sensitivity analyses. In these
analyses, the applicant repeated the cost analysis above using only the
top 75 percent of cases, the top 20 MS-DRGs, and the top 10 MS-DRGs. In
these three additional sensitivity analyses, the final inflated average
case-weighted standardized charge per case for CONTEPOTM
exceeded the average case-weighted threshold amount by $14,949,
$14,230, and $13,620, respectively. We are inviting public comments on
whether CONTEPOTM meets the cost criterion.
With regard to the substantial clinical improvement criterion, the
applicant asserted that the results from the CONTEPOTM
clinical trial clearly establish that CONTEPOTM represents a
substantial clinical improvement in the treatment of antibiotic
resistant infections as compared to currently available treatments.
Specifically, the applicant asserted that the use of
CONTEPOTM offers a treatment option for a patient population
unresponsive to, or ineligible for, currently available treatments, and
the use of CONTEPOTM significantly improves clinical
outcomes for this patient population compared to currently available
treatments. The applicants cited the ZEUS Study, a multi-center,
randomized, parallel-group, double-blind Phase II/III trial of 464
patients designed to evaluate safety, tolerability, efficacy and
pharmacokinetics of the use of CONTEPOTM in the treatment of
hospitalized adults who have been diagnosed with a cUTI or AP at 92
global sites in 16 countries. Hospitalized adults who have been
diagnosed with suspected or microbiologically confirmed cUTI/AP were
randomized 1:1 to receive treatment with either CONTEPOTM or
piperacillin-tazobactam (PIP-TAZ) for a fixed 7-day course (no oral
switch); patients who had been diagnosed with concomitant bacteremia
could receive up to 14 days. Diagnosis was based on pyuria and cUTI or
AP with at least two of the following signs and symptoms: Chills,
rigors, or warmth associated with fever, nausea or vomiting, dysuria,
lower abdominal pain or pelvic pain, or acute flank pain. Patients who
had been diagnosed with a cUTI had at least one of the following: Use
of intermittent or indwelling bladder catheterization, functional or
anatomical abnormality of urogenital tract, complete or partial
obstructive uropathy, azotemia or chronic urinary retention in men.
Baseline urine culture specimen was obtained within 48 hours prior to
randomization. Indwelling bladder catheters were required to be removed
or replaced, unless considered unsafe or contraindicated, before or
within 24 hours after randomization.
The applicant stated that the primary endpoint of the ZEUS Study
was to demonstrate that CONTEPOTM was non-inferior to PIP-
TAZ in overall success based on clinical cure (complete resolution or
significant improvement of signs and symptoms such that no further
antimicrobial therapy is warranted) and microbiologic eradication
(baseline pathogen was reduced to 77 78 The
applicant also reported that the study had two secondary endpoints.
Secondary objectives were to compare: (1) Clinical cure rates in the
two treatment groups in the MITT, m-MITT, Clinical Evaluable (CE), and
Microbiologic Evaluable (ME) populations at TOC, and (2)
microbiological eradication rates in m-MITT and ME populations at TOC.
---------------------------------------------------------------------------
\77\ Eckburg, et al., ``Phenotypic Antibiotic Resistance in
ZEUS: Multi-center, Randomized, Double-Blind Phase II/III Study of
ZTI-01 versus Piperacillin-Tazobactam (P-T) in the Treatment of
Patients with Complicated Urinary Tract Infections (cUTI) including
Acute Pyelonephritis (AP) Poster,'' 2017.
\78\ Kaye, et al., ``Intravenous Fosfomycin (ZTI-01) for the
Treatment of Complicated Urinary Tract Infections (cUTI) including
Acute Pyelonephritis (AP): Results from a Multi-center, Randomized,
Double-Blind Phase II/III Study in Hospitalized Adults (ZEUS),''
2017.
---------------------------------------------------------------------------
The applicant also included evidence from a post-hoc study wherein
all pathogens isolated from patients who had a baseline and TOC
pathogen underwent blinded, post-hoc, pulsed-field gel electrophoresis
(PFGE) molecular typing analysis. Microbiologic outcome was also
defined utilizing the PFGE results, whereby microbiologic persistence
required the same genus and species of baseline and post-baseline
pathogens, as well as PFGE-confirmed genetic identity.
The applicant stated that the ZEUS Study met its primary objective
of showing non-inferiority of CONTEPOTM compared to PIP-TAZ
with overall success rates (that is, clinical cure and microbiological
eradication of baseline pathogen) of 64.7 percent (119/184
CONTEPOTM patients) versus 54.5 percent (97/178 PIP-TAZ
patients) in the m-MITT population at TOC (treatment difference 10.2
percent, 95 percent CI: -0.4, 20.8). We note that, based on the 95
percent confidence interval reported at the primary endpoint,
CONTEPOTM's success rates were not found to be different
from PIP-TAZ in a statistically significant manner. The applicant
reports that the identity and frequency of pathogens recovered at
baseline from patients in the ZEUS Study were similar in both the
CONTEPOTM and PIP-TAZ treatment groups. The most common
pathogens identified were Enterobacteriaceae, identified in 96.2
percent of the CONTEPOTM patients and 94.9 percent of the
PIP-TAZ patients, including E. coli, identified in 72.3 percent of the
CONTEPOTM patients and 74.7 percent of the PIP-TAZ patients;
K. pneumoniae, identified in 14.7 percent of the CONTEPOTM
patients and 14.0 percent of the PIP-TAZ patients; Enterobacter cloacae
species complex, identified in 4.9 percent of the CONTEPOTM
patients and 1.7 percent of the PIP-TAZ patients; and Proteus
mirabilis, identified in 4.9 percent of the CONTEPOTM
patients and 2.8 percent of the PIP-TAZ patients. Gram-negative aerobes
other than Enterobacteriaceae included Pseudomonas aeruginosa, which
was identified in 4.3 percent of the CONTEPOTM patients and
5.1 percent of the PIP-TAZ patients, and Acinetobacter baumannii-
calcoaceticus species complex, identified in 1.1 percent of the
CONTEPOTM patients and none of the PIP-TAZ patients. The
applicant indicated that these pathogens are representative of the
pathogens that have been recovered in other studies of patients who
have been diagnosed with a cUTI or AP.
In terms of secondary endpoints, the applicant stated that clinical
cure rates were greater than 90 percent in both treatment groups at TOC
in the MITT, m-MITT, CE, and ME analysis groups. In addition to the
findings discussed above, with the post-hoc analysis adjusting for PFGE
results in both treatment arms, CONTEPOTM demonstrated a
10.5 percent treatment difference compared to PIP-TAZ with a
microbiological response rate of 70.7 percent versus 60.1 percent,
respectively, in the m-MITT population at TOC (95 percent CI: 0.2,
20.8). The applicant indicated that by specifying the genus and species
of the bacteria present at the start of treatment, the post-hoc PFGE
analysis shows that when measuring microbiological eradication rates
CONTEPOTM demonstrated a positive difference significant at
the 95 percent confidence level.\79\
---------------------------------------------------------------------------
\79\ Skarinsky, et al., ``Per Pathogen Outcomes from the ZEUS
study, a Multi-center, Randomized, Double-Blind Phase II/III Study
of ZTI-01 (fosfomycin for injection) versus Piperacillin-Tazobactam
(P-T) in the Treatment of Patients with Complicated Urinary Tract
Infections (cUTI) including Acute Pyelonephritis (AP),'' 2017.
---------------------------------------------------------------------------
With respect to safety, the applicant reports that in the ZEUS
Study a total of 42.1 percent of the CONTEPOTM patients and
32.0 percent of the PIP-TAZ patients experienced at least one
treatment-emergent adverse event, or TEAE. Most TEAEs were mild or
moderate in severity, and severe TEAEs were uncommon (2.1 percent of
the CONTEPOTM patients and 1.7 percent of the PIP-TAZ
patients). The most common TEAEs in both treatment groups were
transient, asymptomatic laboratory abnormalities and gastrointestinal
events. Treatment-emergent serious adverse events, or SAEs, were
uncommon in both treatment groups. There were no deaths in the study
and one SAE in each treatment group was deemed related to the study
drug (hypokalemia in a CONTEPOTM patient and renal
impairment in a PIP-TAZ patient), leading to study drug discontinuation
in the PIP-TAZ patient. Study drug discontinuations due to TEAEs were
infrequent and similar between treatment groups (3.0 percent of
CONTEPOTM patients and 2.6 percent of PIP-TAZ patients). The
applicant further stated that the most common laboratory abnormality
TEAEs were increases in the levels of alanine aminotransferase (8.6
percent of CONTEPOTM patients and 2.6 percent of PIP-TAZ
patients) and aspartate transaminase (7.3 percent of
CONTEPOTM patients and 2.6 percent of PIP-TAZ patients).
None of the aminotransferase elevations were symptomatic or treatment-
limiting, and none of the patients met the criteria for Hy's Law (a
method of assessing a patient's risk of fatal drug-induced liver
injury). Outside of the United States, elevated liver aminotransferases
are listed among undesirable effects in labeling for the use of IV
fosfomycin. Finally, the applicant stated that hypokalemia occurred in
71 of the 232 (30.6 percent) CONTEPOTM patients and 29 of
the 230 (12.6 percent) PIP-TAZ patients. Most decreases in potassium
levels were mild to moderate in severity. Shifts in potassium levels
from normal at baseline to hypokalemia, as determined by worst post-
baseline hypokalemia values, were more frequent in the patients in the
CONTEPOTM group than the patients in the PIP-TAZ group for
mild (17.7 percent compared to 11.3 percent), moderate (11.2 percent
compared to 0.9 percent), and severe (1.7 percent compared to 0.4
percent) categories of hypokalemia. Hypokalemia was deemed a TEAE in
6.4 percent of the patients receiving CONTEPOTM and 1.3
percent of the patients receiving PIP-TAZ, and all cases were transient
and asymptomatic. The applicant noted that post-baseline QT intervals
calculated using Fridericia's formula, or QTcF, of greater than 450 to
less than
[[Page 19304]]
or equal to 480 msec (baseline QTcF of less than or equal to 450 msec)
occurred at a higher frequency in CONTEPOTM patients (7.3
percent) compared to PIP-TAZ patients (2.5 percent). In the
CONTEPOTM arm, these results appear to be associated with
the hypokalemia associated with the salt load of the IV formulation.
Only 1 patient in the PIP-TAZ group had a baseline QTcF of less than or
equal to 500 msec and a post-baseline QTcF of greater than 500 msec.
In addition to the assertions of clinical improvement based on its
pivotal study, the applicant stated that CONTEPO\TM\ provides a broad
spectrum of in vitro activity against a variety of clinically important
MDR Gram-negative pathogens, including ESBL-producing
Enterobacteriaceae, CRE, and Gram-positive pathogens, including
methicillin-resistant Staphylococcus aureus, or MRSA, and vancomycin-
resistant enterococci.80 81 82 83 The applicant also
believes that CONTEPO\TM\, due to its unique mechanism of action, has
demonstrated synergistic or additive activity in in vitro studies when
used in combination with other antibiotic classes in preclinical
studies.84 85 86 The applicant further stated that the use
of CONTEPO\TM\ has the potential to spare the use of carbapenems and
other last-line therapies and, thereby, has the potential to reduce the
development of resistance to existing antibiotic classes.\87\
Additionally, the applicant believes that the use of CONTEPO\TM\ has
the potential to reduce patients' hospital lengths of stay and patient
morbidity due to the ability to provide early appropriate therapy in
patients who have been diagnosed with suspected or confirmed MDR
pathogens.88 89 The applicant also stated that the submitted
literature provides cases wherein the use of CONTEPO\TM\ could provide
an important treatment option for patients who have been diagnosed with
infections caused by pathogens resistant to all other available IV
antibiotics.90 91 Finally, the applicant asserted that the
use of CONTEPO\TM\ has immunomodulating activities that potentially may
improve outcomes for serious infections,\92\ and may protect against
gentamicin induced nephrotoxicity.\93\
---------------------------------------------------------------------------
\80\ Flamm, R., et al., ``Activity of fosfomycin when tested
against US contemporary bacterial isolates,'' Diagnostic
Microbiology and Infectious Disease, 2018.
\81\ Mendes, R.E., et al., ``Molecular Characterization of
Clinical Trial Isolates Exhibiting Increased MIC Results during
Fosfomycin (ZTI-01) Treatment in a Phase II/III Clinical Trial for
Complicated Urinary Tract Infections (ZEUS),'' 2018.
\82\ Rhomberg, P., et al., ``Evaluation of Fosfomycin Activity
When Combined with Selected Antimicrobial Agents and Tested against
Bacterial Isolates Using Checkerboard Methods,'' 2017.
\83\ Falagas, M., et al., ``Antimicrobial susceptibility of
multidrug-resistant (MDR) and extensively drug-resistant (XDR)
Enterobacteriaceae isolates to fosfomycin,'' International Journal
of Antimicrobial Agents, 2010.
\84\ Flamm, R., et al., ``Time Kill Analyses of Concerning Gram-
Negative Bacteria with Fosfomycin Alone and in Combination with
Select Antimicrobial Agents,'' 2017.
\85\ Avery & Nicolau, ``In Vitro Synergy of Fosfomycin and
Parenteral Antimicrobials Against Carbapenem-Nonsusceptible
Pseudomonas aeruginosa,'' 2018.
\86\ Albiero, J., et al., ``Pharmacodynamic Evaluation of the
Potential Clinical Utility of Fosfomycin and Meropenem in
Combination Therapy against KPC-2-Producing Klebsiella pneumonia,''
Antimicrobial Agents and Chemotherapy, 2016.
\87\ Hayden, M.K. & Won, S.Y., ``Carbapenem-Sparing Therapy for
Extended-Spectrum [beta]-Lactamase-Producing E coli and Klebsiella
pneumoniae Bloodstream Infection,'' JAMA, 2018.
\88\ Mocarski, et al., ``Economic Burden Associated with Key
Gram-negative Pathogens among Patients with Complicated Urinary
Tract Infections across US Hospitals,'' 2014.
\89\ Lodise, et al., ``Carbapenem-resistant Enterobacteriaceae
(CRE) or Delayed Appropriate Therapy (DAT)--Does One Affect Outcomes
More Than the Other Among Patients With Serious Infections Due to
Enterobacteriaceae?,'' 2017.
\90\ Chen, L., et al., ``Pan-Resistant New Delhi Metallo-Beta-
Lactamase-Producing Klebsiella pneumonia--Washoe County, Nevada,
2016,'' 2017.
\91\ Rios, P., et al., ``Extensively drug-resistant (XDR)
Pseudomonas aeruginosa identified in Lima, Peru co-expressing a VIM-
2 metallo-blactamase, OXA-1 b-lactamase and GES-1 extended-spectrum
b-lactamase,'' JMM Case Reports, 2018.
\92\ Zeitlinger, et al., ``Immunomodulatory effects of
fosfomycin in an endotoxin model in human blood.'' Journal of
Antimicrobial Chemotherapy, 2007.
\93\ Yanagida, et al., ``Protective effect of fosfomycin on
gentamicin-induced lipid peroxidation of rat renal tissue,'' Chem
Biol Interact, 2004.
---------------------------------------------------------------------------
We have several concerns regarding whether CONTEPO\TM\ meets the
substantial clinical improvement criterion. First, we are concerned
that we are unable to identify if any of the patients enrolled in the
ZEUS Study were from the United States. As we have noted in previous
rulemaking (83 FR 41309), given the geographic variability of
antibiotic resistance, we are unsure to what extent results from
studies utilizing an international cohort of patients generate
inferences that are applicable to the U.S. context and, in particular,
to the Medicare-eligible population.
Second, we are unsure if PIP-TAZ is the only proper comparator for
CONTEPO\TM\, or if other treatments should have been considered as
well. There are a number of additional antimicrobials with similar
indications that are available for patients who have been diagnosed
with cUTIs. Such treatments might include meropenem-vaborbactam or
plazomicin. Prior studies include a meta-analysis of 10 studies (7
randomized) comparing the clinical efficacy of IV fosfomycin against
other antibiotics including sulbenicillin, sulbactam/cefoperazone,
cefotaxime, fosfomycin/colistin, and minocycline/cefuzonam. This meta-
analysis did not observe a difference in clinical efficacy between
fosfomycin and respective comparators (odds ratio (OR) 1.44, 95 percent
CI (0.96, 2.15)) irrespective of monotherapy (OR 1.41, 95 percent CI
(0.83, 2.39)) or combination therapy (OR 1.48, 95 percent CI (0.81,
2.71.)). The same results were obtained when studies with poor quality
were excluded (OR 1.45, 95 percent CI (0.94, 2.24)).\94\
---------------------------------------------------------------------------
\94\ Grabien, et al., ``Intravenous fosfomycin--Back to the
Future; Systematic Review and Meta-analysis of the Clinical
Literature,'' Clinical Microbiology and Infection, 2017.
---------------------------------------------------------------------------
Third, we have two methodological concerns regarding the
applicant's assertions based on the ZEUS Study. There does not appear
to be any statistical comparison of the patients in each arm in terms
of demographics and, therefore, it is difficult to assess whether the
two intervention arms are balanced as the applicant inferred. We
acknowledge that use of a double-blinded, randomized study design
(which was used in the ZEUS Study) should minimize bias and control for
unmeasured variables between treatment arms. However, we are concerned
about a lack of detail on the different dropout rates of patients
within each arm of the ZEUS Study, including data on causes and
treatment of patients that dropped out and any bias that might
introduce. We also are concerned that the ZEUS Study did not
demonstrate a superior clinical outcome with statistical significance
in its primary endpoint. Rather, the applicant is asserting the
technology represents a substantial clinical improvement on the basis
of meeting a secondary endpoint, the cure rates based on additional
PFGE analysis. In addition, we are concerned that the use of m-MITT,
rather than ITT, may have biased the results upwards by focusing on a
subset of the treatment group, rather than the entire random
sample.\95\
---------------------------------------------------------------------------
\95\ Beckett, R.D., Loeser, K.C., Bowman, K.R., Towne, T.G.,
``Intention-to-treat and transparency of related practices in
randomized, controlled trials of anti-infectives,'' BMC Med Res
Methodol, 2016, vol. 16(1), pp. 106, Published August 24, 2016,
doi:10.1186/s12874-016-0215-2.
---------------------------------------------------------------------------
Finally, we are concerned that many of the assertions the applicant
has made regarding the efficacy of CONTEPOTM on MDR gram-
negative pathogens and broader public health benefits come from in
vitro studies or may be speculative in nature. It may be helpful
[[Page 19305]]
to have further evidence, particularly prospectively collected and
tested clinical data, to support the assertions that the use of
CONTEPOTM reduces hospital lengths of stay and patient
morbidity, and enhances antibiotic stewardship.
We are inviting public comments on whether CONTEPOTM
meets the substantial clinical improvement criterion.
Below we summarize and respond to a written public comment received
in response to the New Technology Town Hall meeting notice published in
the Federal Register regarding the substantial clinical improvement
criterion for CONTEPOTM.
Comment: In response to a question presented at the New Technology
Town Hall meeting, the applicant explained why the post-hoc reanalysis
of the primary endpoint (overall success, a composite of clinical cure
and microbiologic eradication) from the ZEUS Study using pulse-field
gel electrophoresis, which the applicant asserted demonstrated a
statistically significant difference between CONTEPOTM and
PIP-TAZ, is clinically important. The applicant stated that the post-
hoc analysis was able to differentiate the patients who had eradication
of the identified and treated baseline pathogen from those patients who
developed or were likely to develop another infection from a newly
acquired pathogen (different strain) following the ~2-week period
between the end of IV therapy and the test-of-cure evaluation. However,
the applicant indicated that there are many reasons why patients may
acquire another pathogen and/or develop new infections after completing
IV therapy, including indwelling urinary catheters or instrumentation
(for example, nephrostomy tubes, ureteric stents, etc.) or anatomical
abnormalities. The applicant stated that because of these confounding
factors, the PFGE reanalysis allowed for the differentiation of the
true persistence of the same pathogen that was present at baseline from
a different pathogen that might look the same, but was clearly
genetically distinct.
Response: We appreciate the applicant's further explanation of the
PFGE analysis. We will take this information into consideration when
deciding whether to approve new technology add-on payments for
CONTEPOTM.
e. DuraGraft[supreg] Vascular Conduit Solution
Somahlution, Inc. submitted an application for new technology add-
on payments for DuraGraft[supreg] for FY 2020. (We note that the
applicant previously submitted applications for new technology add-on
payments for DuraGraft[supreg] for FY 2018 and FY 2019, which were
withdrawn.) According to the applicant, DuraGraft[supreg] is designed
to protect the endothelium of the vein graft by mitigating ischemic
reperfusion injury (IRI), the basis of vein graft disease (VGD) and
vein graft failure (VGF), both of which are intimately linked to graft
and patient outcomes.\96\ \97\ \98\ According to the applicant,
specific VGD and VGF clinical outcomes affected by the use of
DuraGraft[supreg] include reductions in myocardial infarction (MI),
repeat revascularization and major adverse cardiovascular events
(MACE). The applicant stated that DuraGraft[supreg] is a preservation
solution, not a storage solution, used during standard graft handling,
flushing, and bathing steps.
---------------------------------------------------------------------------
\96\ Salvadori, M., Rosso, G., and Bertoni, E., ``Update on
Ischemia-reperfusion Injury in Kidney Transplantation: Pathogenesis
and Treatment,'' World Transplant, June 24, 2015, vol. 5(2), pp. 52-
67.
\97\ Osgood, M.J., Hocking, K.M., Voskresensky, I.V., et al.,
``Surgical vein graft preparation promotes cellular dysfunction,
oxidative stress, and intimal hyperplasia in human saphenous vein,''
J Vasc Surg, 2014, vol. 60, pp. 202-211.
\98\ Shuhaiber, J.H., Evans, A.N., Massad, M.G., and Geha, A.S.,
``Mechanisms and Future Directions for Prevention of Vein Graft
Failure in Coronary Bypass Surgery,'' European Journal of Cardio-
Thoracic Surgery, vol. 22, Issue 3, September 1, 2002, pp. 387-396.
---------------------------------------------------------------------------
The applicant indicated that vein graft endothelial damage is the
principal mediator of VGD following grafting in bypass surgeries.\99\
\100\ According to the applicant, the endothelium can be destroyed or
damaged intraoperatively through the acute physical stress of
harvesting, storage, and handling, and through more insidious processes
such as those associated with ischemic injury, metabolic stress and
oxidative damage. The applicant also noted that vein graft solutions
can independently damage the endothelium during the harvesting and
storage stages prior to vein grafting. The applicant also referred to
more recent information to depict that damage associated with the use
of graft storage solutions has the highest correlation with the
development of 12-month VGF following coronary artery bypass grafting
(CABG).\101\ More specifically regarding vein graft solutions, the
applicant asserted that there are two processes associated with current
vein graft solutions that lead to IRI and ultimately VGD: (1) Current
vein graft solutions cause ``solution damage;'' and (2) current vein
graft solutions do not protect against IRI, the basis for VGD.\102\
\103\ \104\ \105\ \106\ \107\ \108\ According to the applicant, current
vein graft solutions are used to flush and store vascular grafts during
the ex vivo ischemic interval of the surgical procedure. However, these
solutions do not protect the graft from ischemia reperfusion injury and
have no preservation ability. Further, the applicant asserted that some
of the solutions are incompatible with graft tissue resulting in
ischemic damage that is compounded by ``solution damage''.\109\ \110\
\111\
---------------------------------------------------------------------------
\99\ Harskamp, R.E., Alexander, J.H., Schulte, P.J., Brophy,
C.M., Mack, M.J., Peterson, E.D., Williams, J.B., Gibson, C.M.,
Califf, R.M., Kouchoukos, N.T., Harrington, R.A., Ferguson, Jr.,
T.B., Lopes, R.D., ``Vein Graft Preservation Solutions, Patency, and
Outcomes After Coronary Artery Bypass Graft Surgery Follow-up From
PREVENT IV Randomized Clinical Trial,'' JAMA Surg., 2014, vol.
149(8), pp. 798-805.
\100\ Testa, L., Bedogni, F., ``Treatment of Saphenous Vein
Graft Disease: Never Ending Story of the Eternal Return,'' Res
Cardiovasc Med., 2014, vol. 3(3), e21092.
\101\ Ibid.
\102\ Shinjo, H., et al., ``Effect of irrigation solutions for
arthroscopic surgery on intraarticular tissue: comparison in human
meniscus-derived primary cell culture between lactate Ringer's
solution and saline solution,'' Journal of Orthopaedic Research,
2002, vol. 20, pp. 1305-1310.
\103\ Breborowicz, A. and Oreopoulos, D.G., ``Is normal saline
harmful to the peritoneum?'', Perit Dial Int., 2005 Apr; 25 Suppl
4:S67-70.
\104\ Pusztaszeri, M.P., Seelentag, Walter, Bosman, F.T.,
``Immunohistochemical Expression of Endothelial Markers CD31, CD34,
von Willebrand Factor, and Fli-1 in Normal Human Tissues,'' Journal
of Histochemistry & Cytochemistry, 2006, vol. 54(4), pp. 385-395.
\105\ Polubinska, A., et al., ``Normal Saline induces oxidative
stress in peritoneal mesoyhelial cells,'' Journel of Pediatric
Surgery, 2008, vol. 43, pp. 1821-1826.
\106\ Sengupta, S., Prabhat, K., Gupta, V., Vij, H., Vij, R.,
Sharma, V., ``Artefacts Produced by Normal Saline When Used as a
Holding Solution for Biopsy Tissues in Transit,'' J. Maxillofac.
Oral Surg., (Apr-June 2014), vol. 13(2), pp. 148-151.
\107\ Wilbring, M., Tugtekin, S.M., Zatschler, B., Ebner, A.,
Reichenspurner, H., Matschke, K., Deussen, A., ``Even short-time
storage in physiological saline solution impairs endothelial
vascular function of saphenous vein grafts,'' Eur J Cardiothorac
Surg., 2011 Oct, vol. 40(4), pp. 811-815.
\108\ Weiss, D.R., et al., ``Extensive deendothelialization and
thrombogenicity in routinely prepared vein grafts for coronary
bypass operations: facts and remedy,'' Int J Clin Exp Med, 2009,
vol. 2, pp. 95-113.
\109\ Weiss, D.R., et al., ``Extensive deendothelialization and
thrombogenicity in routinely prepared vein grafts for coronary
bypass operations: facts and remedy,'' Int J Clin Exp Med, 2009,
vol. 2, pp. 95-113.
\110\ Ibid.
\111\ Thatte, H.S., Biswas, K.S., Najjar, S.F., Birjiniuk, V.,
Crittenden, M.D., Michel, T., and Khuri, S.F., ``Multi-Photon
Microscopic valuation of Saphenous Vein Endothelium and Its
Preservation With a New Solution, GALA,'' Annals Thoracic Surgery,
2003, vol. 75, pp. 1145-52.
---------------------------------------------------------------------------
The applicant explained that there are two mechanisms leading to
VGD: (1) Endothelial damage associated with the
[[Page 19306]]
harvesting and storage processes; and (2) VGD pathophysiological
changes that occur in damaged vein grafts following reperfusion at the
time of graft anastomosis. According to the applicant, these changes
are apparent within minutes to hours of grafting and are manifested as
endothelial dysfunction, death and/or denudation and include pro-
inflammatory, pro-thrombogenic and aberrant proliferative changes
within the graft. The applicant further characterized these changes as
initial endothelial reperfusion phase responses, which set in motion a
damage-response domino-like effect thereby perpetuating a cycle of
prolonged reperfusion phase injury with subsequent VGD.
The applicant further noted that endothelial dysfunction and
inflammation results not only in the diminished ability of the graft to
respond appropriately to new blood flow patterns, but also may thwart
positive adaptive vein graft remodeling. According to the applicant,
this is because proper vein graft remodeling is dependent upon a
functional endothelial response to shear stress that involves the
production of remodeling factors by the endothelium including nitro
vasodilators, prostaglandins, lipoxyoxygenases, hyperpolarizing factors
and other growth factors.\112\ Therefore, damaged, missing and/or
dysfunctional endothelial cells prevent graft adaption, which makes the
graft susceptible to shear mediated endothelial damage. The applicant
explained that the collective damage results in intimal hyperplasia or
graft wall thickening that is the basis for atheroma development,
stenosis and subsequent lumen narrowing leading to the end state of
VGD, VGF.\113\ The applicant also noted that the pathologic changes
leading to VGD, occlusion and loss of vasomotor function, are well
documented.\114\ \115\ \116\ \117\ \118\ \119\ \120\ Presenting an
intact functional endothelial layer at the time of grafting is,
therefore, critical to protecting the graft and its associated
endothelium from damage that occurs post-grafting, in turn conferring
protection against graft failure.\121\ The applicant stated that given
the low success rate of VGF intervention after surgery (for example,
percutaneous coronary intervention and saphenous vein graft
intervention \122\), addressing graft endothelial protection at the
time of surgery is critical.
---------------------------------------------------------------------------
\112\ Owens, C.D., ``Adaptive changes in autogenous vein grafts
for arterial reconstruction: Clinical Implications,'' J Vasc Surg.,
2010 March; vol. 51(3), pp. 736-746.
\113\ Murphy, G.J. and Angelini, G.D., ``Insights into the
pathogenesis of vein graft disease: lessons from intravascular
ultrasound,'' Cardiovascular Ultrasound, 2004, 2:8.
\114\ Verrier, E.D., Boyle, E.M., ``Endothelial cell injury in
cardiovascular surgery: an overview,'' AnnThorac Surg, 1996, vol.
64, pp. S2-S8.
\115\ Harskamp, R.E., Lopes, R.D., Baisden, C.E., et al.,
``Saphenous vein graft failure after coronary artery bypass surgery:
pathophysiology, management, and future directions,'' Ann Surg.,
2013 May, vol. 257(5), pp. 824-33.
\116\ Sellke, F.W., Boyle, E.M., Verrier, E.D., ``The
pathophysiology of vasomotor dysfunction,'' Ann Thorac Surg, 1996,
vol. 64, pp. S9-S15.
\117\ Motwani, J.G., Topol, E.J., ``Aortocoronary saphenous vein
graft disease: pathogenesis, predisposition and prevention,''
Circulation, 1998, vol. 97(9), pp. 916-31.
\118\ Mills, N.L., Everson, C.T., ``Vein graft failure,'' Curr
Opin Cardiol, 1995, vol. 10, pp. 562-8.
\119\ Davies, M.G., Hagen, P.O., ``Pathophysiology of vein graft
failure: a review,'' Eur J Vasc Endovasc Surg, 1995, vol. 9, pp. 7-
18.
\120\ Edmunds, L.H., ``Techniques of myocardial
revascularization. In: Edmunds LH, ed. Cardiac surgery in the
adult,'' New York: McGraw-Hill, 1997, pp. 481-534.
\121\ Kim FY, Marhefka G, Ruggiero NJ, et al. Saphenous vein
graft disease: review of pathophysiology, prevention, and treatment.
Cardiol Rev, 2013;21(2):101-9.
\122\ Testa, L., Bedogni, F., ``Treatment of Saphenous Vein
Graft Disease: Never Ending Story of the Eternal Return,'' Res
Cardiovasc Med., 2014, vol. 3(3), e21092.
---------------------------------------------------------------------------
With respect to the newness criterion, DuraGraft[supreg] has not
received FDA approval as of the time of the development of this
proposed rule. The applicant indicated that it anticipates FDA approval
of its premarket application by July 1, 2019. The applicant also
indicated that ICD-10-PCS code XY0VX83 (Extracorporeal introduction of
endothelial damage inhibitor to vein graft, New Technology Group 3)
would identify procedures involving the use of the DuraGraft[supreg]
technology.
As discussed earlier, if a technology meets all three of the
substantial similarity criteria, it would be considered substantially
similar to an existing technology and would, therefore, not be
considered ``new'' for purposes of new technology add-on payments.
With regard to the first criterion, whether a product uses the same
or similar mechanism of action to achieve a therapeutic outcome,
according to the applicant, there are currently no other treatment
options available with the same mechanism of action as that of
DuraGraft[supreg]. According to the applicant, the currently available
vein graft solutions, which consist of saline, buffered saline, blood,
and electrolyte solutions, are not preservation solutions but
``storage'' solutions that do not protect the graft vascular
endothelium nor mitigate IRI, the basis of VGD.\123\ \124\ \125\ \126\
The applicant stated that these solutions are used merely to keep
grafts wet from the time they are harvested until the time they are
used in CABG. According to the applicant, exposure of saphenous vein
grafts to these solutions has been shown to cause significant damage to
the graft within minutes.\127\ \128\ \129\ \130\
---------------------------------------------------------------------------
\123\ Salvadori, M., Rosso, G., and Bertoni, E., ``Update on
Ischemia-reperfusion Injury in Kidney Transplantation: Pathogenesis
and Treatment,'' World Transplant, June 24, 2015, vol. 5(2), pp. 52-
67.
\124\ Lee, J.C. and Christie, J.D., ``Primary Graft
Dysfunction,'' Proc Am Thorac Soc., 2009, vol. 6, pp 39-46.
\125\ Osgood, M.J., Hocking, K.M., Voskresensky, I.V., et al.,
``Surgical vein graft preparation promotes cellular dysfunction,
oxidative stress, and intimal hyperplasia in human saphenous vein,''
J Vasc Surg, 2014, vol. 60, pp. 202-211.
\126\ Shuhaiber, J.H., Evans, A.N., Massad, M.G., and Geha,
A.S., ``Mechanisms and Future Directions for Prevention of Vein
Graft Failure in Coronary Bypass Surgery,'' European Journal of
Cardio-Thoracic Surgery, vol. 22, Issue 3, September 1, 2002, pp.
387-396.
\127\ Weiss, D.R., et al., ``Extensive deendothelialization and
thrombogenicity in routinely prepared vein grafts for coronary
bypass operations: facts and remedy,'' Int J Clin Exp Med, 2009,
vol. 2, pp. 95-113.
\128\ Wilbring, M., Tugtekin, S.M., Zatschler, B., Ebner, A.,
Reichenspurner, H., Matschke, K., Deussen, A., ``Even short-time
storage in physiological saline solution impairs endothelial
vascular function of saphenous vein grafts,'' Eur J Cardiothorac
Surg., 2011 Oct, vol. 40(4), pp. 811-815.
\129\ Tsakok, M., Montgomery-Taylor, S. and Tsakok, T.,
``Storage of saphenous vein grafts prior to coronary artery bypass
grafting: is autologous whole blood more effective than saline in
preserving graft function?'' Inter Cardiovasc Thorac Surg, 2012,
vol. 15, pp. 720-25.
\130\ Thatte, H.S., Biswas, K.S., Najjar S.F., Birjiniuk, V.,
Crittenden, M.D., Michel, T., and Khuri, S.F., ``Multi-Photon
Microscopic valuation of Saphenous Vein Endothelium and Its
Preservation With a New Solution, GALA.'' Annals Thoracic Surgery,
2003, vol. 75, pp. 1145-52.
---------------------------------------------------------------------------
The applicant explained that DuraGraft[supreg] is a formulated
``preservation'' solution that can be used during handling, flushing,
and bathing steps without changing standard surgical practice.
According to the applicant, the handling step includes using an
atraumatic surgical technique, avoiding over pressurization and
checking for leakage, excessive handling and distortion. The applicant
further noted that vascular segments (that become vascular grafts) are
comprised of a number of different cell types that function together in
an integrated manner post-grafting and, therefore, protection of all
cell types during graft flushing and storage is critical for
maintenance of graft viability and normal graft functioning.
The applicant indicated that DuraGraft[supreg] separates itself
from current vein graft solutions through its unique
[[Page 19307]]
composition of ingredients, a physiologic saline solution that combines
free radical scavengers and antioxidants (glutathione, ascorbic acid)
and nitric oxide synthase substrate (L-arginine), as discussed later in
this section. According to a summary of ex vivo performance data and
studies provided by the applicant, the use of DuraGraft[supreg] has
been shown to preserve vascular graft viability, as well as graft
functional and structural integrity during ex vivo storage and
flushing.\131\ \132\ \133\ The applicant noted that these studies
evaluated graft cellular viability and structural integrity and
assessed molecular and biochemical markers of normal endothelial
functioning. Specifically, endothelial and smooth muscle cells were
assessed.
---------------------------------------------------------------------------
\131\ Thatte, H.S., Biswas, K.S., Najjar S.F., Birjiniuk, V.,
Crittenden, M.D., Michel, T., and Khuri, S.F., ``Multi-Photon
Microscopic valuation of Saphenous Vein Endothelium and Its
Preservation With a New Solution, GALA.'' Annals Thoracic Surgery,
2003, vol. 75, pp. 1145-52.
\132\ Hussaini, B.E., Lu, X.G., Wolfe, A., Thatte, H.S.,
``Evaluation of Endoscopic Vein extraction on Structural and
Functional Viability of Saphenous Vein Endothelium,'' J Cardothorac
Surg, 2011, vol. 6, pp. 82-89.
\133\ Rousou, L.J., Taylor, K.B., Lu, X.G., et al., ``Saphenous
vein conduits harvested by endoscopic technique exhibit structural
and functional damage,'' Ann Thorac Surg, 2009, vol. 87, pp. 62-70.
---------------------------------------------------------------------------
All veins used in these studies were collected from patients
undergoing cardiac bypass surgery at the Boston VA or Saint Joseph's
Hospital of Atlanta. Veins were harvested using the ``Open Saphenous
Vein Harvest'' (OSVH) technique.\134\ \135\ \136\ Segments of the
collected veins not being used for the bypass surgery were used for the
performance bench studies.
---------------------------------------------------------------------------
\134\ Ibid.
\135\ Hussaini, B.E., Lu, X.G., Wolfe, A., Thatte, H.S.,
``Evaluation of Endoscopic Vein extraction on Structural and
Functional Viability of Saphenous Vein Endothelium,'' J Cardothorac
Surg, 2011, vol. 6, vol. 82-89.
\136\ Thatte, H.S., Biswas, K.S., Najjar, S.F., Birjiniuk, V.,
Crittenden, M.D., Michel, T., and Khuri, S.F., ``Multi-Photon
Microscopic valuation of Saphenous Vein Endothelium and Its
Preservation With a New Solution, GALA.'' Annals Thoracic Surgery,
2003, vol. 75, pp. 1145-52.
---------------------------------------------------------------------------
According to the applicant, viability studies conducted in
conjunction with multi-photon microscopy demonstrated a protective
effect from the use of DuraGraft[supreg] on vascular endothelial
viability and graft structural integrity for storage times of up to 5
hours at room temperature (21 [deg]C).\137\ The applicant also stated
that, conversely, vascular segments were not able to be maintained in a
viable condition when stored for as short a time as 15 minutes in
standard-of-care solutions consistent with what has been published by
others. According to the applicant, DuraGraft[supreg] demonstrated its
ability to preserve the viability, structure and function of
endothelium in radial and internal mammary arteries, as well as
saphenous veins for extended periods.\138\
---------------------------------------------------------------------------
\137\ Ibid.
\138\ Ibid.
---------------------------------------------------------------------------
According to the information submitted by the applicant, the
ingredients found in DuraGraft[supreg] play a primary role in
DuraGraft[supreg] exhibiting a different mechanism of action from other
solutions that are commonly used to treat the same disease process and
patient population. According to the study cited by the applicant, the
rapid loss of endothelial cell structural and functional integrity in
saphenous veins stored in standard storage solutions can be avoided by
incorporating a physiologic saline solution that combines free radical
scavengers and antioxidants (glutathione, ascorbic acid) and nitric
oxide synthase substrate (L-arginine) providing a favorable environment
and cellular support during ex vivo storage.\139\ The same study also
indicated that these three ingredients were chosen because of their
putative effect on endothelial cell function and that their use may act
synergistically to enhance the cell preservation properties of the
solution. The authors of the study asserted that glutathione increases
L-arginine transport in endothelial cells and may lead to the formation
of biologically active S-nitrosoglutathione and to the stimulation of
endothelial nitric oxide synthase (eNOS) activity, nitric oxide
generation, and coronary vasodilatation. According to the authors,
ascorbic acid also increases eNOS activity by preserving endothelium-
derived nitric oxide bioactivity by possibly scavenging superoxide
anions and preventing oxidative destruction of tetrahydrobiopterin, an
eNOS cofactor. Furthermore, according to the study, the presence of
ascorbic acid in a physiologic saline solution may prevent the
oxidation of this eNOS cofactor during vessel storage and help maintain
eNOS function and nitric oxide generation in vascular endothelium. The
study authors also noted that ascorbic acid, by its reducing property,
may assist sustained long-term release of nitric oxide from these
compounds in vessels preserved in a physiologic saline solution and,
therefore, help maintain the patency and tone of the vessels during
storage. Additionally, according to the authors of the study, ascorbic
acid mediated reversal of endothelial dysfunction, reduced platelet
activation and leukocyte adhesion, inhibited smooth muscle cell
proliferation and lipid peroxidation, and increased prostacyclin
production which have been demonstrated in numerous cardiovascular
pathologies. Finally, the authors stated that L-arginine is a known
substrate of nitric oxide synthase and has been shown to decrease
neutrophil-endothelial cell interactions in inflamed vessels.\140\
---------------------------------------------------------------------------
\139\ Thatte, H.S., Biswas, K.S., Najjar, S.F., Birjiniuk, V.,
Crittenden, M.D., Michel, T., and Khuri, S.F., ``Multi-Photon
Microscopic valuation of Saphenous Vein Endothelium and Its
Preservation With a New Solution, GALA.'' Annals Thoracic Surgery,
2003, vol. 75, pp. 1145-52.
\140\ Ibid.
---------------------------------------------------------------------------
Regarding the second criterion, whether a product is assigned to
the same or different MS-DRG, according to the applicant, cases
involving patients who may be eligible to receive treatment involving
DuraGraft[supreg] would be assigned to the same MS-DRGs as patients who
received treatment involving heparinized blood, saline, and electrolyte
solutions.
Regarding the third criterion, whether the new use of the
technology involves the treatment of the same or similar type of
disease and the same or similar patient population, the applicant
indicated that heparinized blood, saline and electrolyte solutions
involve treatment of the same disease process and the same patient
population as DuraGraft[supreg].
Based on the applicant's statements presented above, we are
concerned that the mechanism of action of DuraGraft[supreg] may be the
same or similar to other vein graft storage solutions. Specifically, we
are concerned that current solutions used in vein graft surgical
procedures may be similar to DuraGraft[supreg] in composition and
treatment indication and, therefore, have the same or similar mechanism
of action. We are inviting public comments on whether the
DuraGraft[supreg] meets the newness criterion.
With regard to the cost criterion, the applicant conducted the
following analysis to demonstrate that the technology meets the cost
criterion. In order to identify the range of MS-DRGs that cases
representing potential patients who may be eligible for treatment using
DuraGraft[supreg] may map to, the applicant identified all MS-DRGs for
patients who underwent CABG. Specifically, the applicant searched the
FY 2017 MedPAR file for Medicare fee-for-service inpatient hospital
claims submitted between October 1, 2016 and September 30, 2017, and
identified potential cases that may be eligible for treatment using
DuraGraft[supreg] by the following ICD-10-PCS procedure codes:
[[Page 19308]]
------------------------------------------------------------------------
ICD-10-PCS procedure code Code description
------------------------------------------------------------------------
021009W................... Bypass coronary artery, one artery from
aorta with autologous venous tissue, open
approach.
02100AW................... Bypass coronary artery, one artery from
aorta with autologous arterial tissue, open
approach.
021049W................... Bypass coronary artery, one artery from
aorta with autologous venous tissue,
percutaneous endoscopic approach.
02104AW................... Bypass coronary artery, one artery from
aorta with autologous arterial tissue,
percutaneous endoscopic approach.
021109W................... Bypass coronary artery, two arteries from
aorta with autologous venous tissue, open
approach.
02110AW................... Bypass coronary artery, two arteries from
aorta with autologous arterial tissue, open
approach.
021149W................... Bypass coronary artery, two arteries from
aorta with autologous venous tissue,
percutaneous endoscopic approach.
02114AW................... Bypass coronary artery, two arteries from
aorta with autologous arterial tissue,
percutaneous endoscopic approach.
021209W................... Bypass coronary artery, three arteries from
aorta with autologous venous tissue, open
approach.
02120AW................... Bypass coronary artery, three arteries from
aorta with autologous arterial tissue, open
approach.
021249W................... Bypass coronary artery, three arteries from
aorta with autologous venous tissue,
percutaneous endoscopic approach.
02124AW................... Bypass coronary artery, three arteries from
aorta with autologous arterial tissue,
percutaneous endoscopic approach.
021309W................... Bypass coronary artery, four or more
arteries from aorta with autologous venous
tissue, open approach.
02130AW................... Bypass coronary artery, four or more
arteries from aorta with autologous
arterial tissue, open approach.
021349W................... Bypass coronary artery, four or more
arteries from aorta with autologous venous
tissue, percutaneous endoscopic approach.
02134AW................... Bypass coronary artery, four or more
arteries from aorta with autologous
arterial tissue, percutaneous endoscopic
approach.
------------------------------------------------------------------------
This resulted in potential eligible cases spanning 100 MS-DRGs,
with approximately 93 percent of all of these potential cases, 66,553,
mapping to the following 10 MS-DRGs:
------------------------------------------------------------------------
MS-DRG MS-DRG title
------------------------------------------------------------------------
MS-DRG 003................ Extracorporeal Membrane Oxygenation (ECMO)
or Tracheostomy with Mechanical Ventilation
>96 Hours or Principal Diagnosis Except
Face, Mouth & Neck with Major Operating
Room Procedure.
MS-DRG 216................ Cardiac Valve and Other Major Cardiothoracic
Procedures with Cardiac Catheterization
with MCC.
MS-DRG 219................ Cardiac Valve and Other Major Cardiothoracic
Procedures without Cardiac Catheterization
with MCC.
MS-DRG 220................ Cardiac Valve and Other Major Cardiothoracic
Procedures without Cardiac Catheterization
with CC.
MS-DRG 228................ Other Cardiothoracic Procedures with MCC.
MS-DRG 229................ Other Cardiothoracic Procedures without CC.
MS-DRG 233................ Coronary Bypass with Cardiac Catheterization
with MCC.
MS-DRG 234................ Coronary Bypass with Cardiac Catheterization
without MCC.
MS-DRG 235................ Coronary Bypass without Cardiac
Catheterization with MCC.
MS-DRG 236................ Coronary Bypass without Cardiac
Catheterization without MCC.
------------------------------------------------------------------------
Using the 66,553 identified cases, the average case-weighted
unstandardized charge per case was $212,885. The applicant then
standardized the charges. The applicant did not remove charges for any
current treatment because the applicant indicated that there are no
other current treatment options available. The applicant noted that it
did not provide an inflation factor to project future charges. The
applicant added $2,751 in charges for the costs of the
DuraGraft[supreg] technology. This charge was created by assuming the
DuraGraft[supreg] technology will cost $850 per unit as estimated by
the applicant, and by applying the national average CCR for implantable
devices of 0.309 from the FY 2019 IPPS/LTCH PPS final rule (83 FR
41273) to the cost of the device. According to the applicant, no
further charges or related charges were added. Based on the FY 2019
IPPS/LTCH PPS final rule correction notice data file thresholds, the
average case-weighted threshold amount was $172,965. The final average
case-weighted standardized charge per case was $195,799. Because the
final average case-weighted standardized charge per case exceeds the
average case-weighted threshold amount, the applicant maintained that
the technology meets the cost criterion. We are inviting public
comments on whether DuraGraft[supreg] meets the cost criterion.
With respect to the substantial clinical improvement criterion, the
applicant asserted that the use of DuraGraft[supreg] significantly
reduces clinical complications, such as MI, repeat revascularization
and MACE, associated with VGF following CABG surgery. The applicant
cited the following studies and report, each of which is summarized
below, to substantiate its assertions regarding substantial clinical
improvement: (1) Project of Ex-vivo Vein Graft Engineering via
Transfection (PREVENT IV) Subanalysis; (2) European Retrospective Pilot
Study (unpublished); (3) U.S. Department of Veterans Affairs (USDVA)
Hospital Retrospective Study; and (4) the SWEDEHEART 2016 Annual
Report.
PREVENT IV is a prospective study that enrolled 3,000 patients and
included protocol driven angiograms at 12 months post-CABG, as opposed
to clinically-driven angiograms to evaluate the true incidence of VGF
following CABG surgery where standard-of-care solutions were used.\141\
Harskamp, et al. conducted subanalyses of the study data and found from
dozens of factors evaluated for impact on the development of 12-month
VGF (VGF was defined as a stenosis of the vein graft diameter of 75
percent or greater) that exposure to solutions used in PREVENT IV
(saline, blood, or buffered saline) for intra-operative graft wetting
and storage have the largest correlation with the development of
VGF.142 143
[[Page 19309]]
According to the applicant, short-term exposure of free vascular grafts
to these solutions is routine in CABG operations, where 10 minutes to 3
hours may elapse between the vein harvest and
reperfusion.144 145 According to Harskamp, et al., the
results of the PREVENT IV study showed that the majority of patients
had grafts preserved in saline, 1,339 patients (44.4 percent), followed
by 971 patients (32.2 percent) with grafts preserved in blood, and 507
patients (16.8 percent) with grafts preserved in buffered saline. One-
year VGF rates were much lower in the patients who were treated in the
buffered saline group than in the patients who were treated in the
saline group (patient-level odds ratio [OR], 0.59 [95 percent CI, 0.45-
0.78; P147 148 149 150
---------------------------------------------------------------------------
\141\ Alexander, J.H., Hafley, G., Harrington, R.A., et al.,
``Efficacy and safety of Edifoligide, an E2F Transcription Factor
Decoy, for Prevention of Vein Graft Failure Following Coronary
Artery Bypass Graft Surgery: PREVENT IV: A Randomized Controlled
Trial,'' JAMA, 2005, vol. 294, pp. 2446-54.
\142\ Harskamp, R.E., Alexander, J.H., Schulte, P.J., Brophy,
C.M., Mack, M.J., Peterson, E.D., Williams, J.B., Gibson, C.M.,
Califf, R.M., Kouchoukos, N.T., Harrington, R.A., Ferguson, Jr.,
T.B., Lopes, R.D., ``Vein Graft Preservation Solutions, Patency, and
Outcomes After Coronary Artery Bypass Graft Surgery Follow-up From
PREVENT IV Randomized Clinical Trial,'' JAMA Surg., 2014, vol.
149(8), pp. 798-805.
\143\ Hess, C.N., Lopes, R.D., Gibson, C.M., et al., ``Saphenous
vein graft failure after coronary artery bypass surgery: insights
from PREVENT IV,'' Circulation, 2014 Oct 21, vol. 130(17), pp. 1445-
51.
\144\ Motwani, J.G., Topol, E.J., ``Aortocoronary saphenous vein
graft disease: pathogenesis, predisposition and prevention,''
Circulation, 1998, vol. 97(9), pp. 916-31.
\145\ Mills, N.L., Everson, C.T., ``Vein graft failure,'' Curr
Opin Cardiol, 1995, vol. 10, pp. 562-8.
\146\ Harskamp, R.E., Alexander, J.H., Schulte, P.J., Brophy,
C.M., Mack, M.J., Peterson, E.D., Williams, J.B., Gibson, C.M.,
Califf, R.M., Kouchoukos, N.T., Harrington, R.A., Ferguson, Jr.,
T.B., Lopes, R.D., ``Vein Graft Preservation Solutions, Patency, and
Outcomes After Coronary Artery Bypass Graft Surgery Follow-up From
PREVENT IV Randomized Clinical Trial,'' JAMA Surg., 2014, vol.
149(8), pp. 798-805.
\147\ Ibid.
\148\ Weiss, D.R., et al., ``Extensive deendothelialization and
thrombogenicity in routinely prepared vein grafts for coronary
bypass operations: facts and remedy,'' Int J Clin Exp Med, 2009;
vol. 2, pp. 95-113.
\149\ Wilbring, M., Tugtekin, S.M., Zatschler, B., Ebner, A.,
Reichenspurner, H., Matschke, K., Deussen, A., ``Even short-time
storage in physiological saline solution impairs endothelial
vascular function of saphenous vein grafts,'' Eur J Cardiothorac
Surg., 2011 Oct, vol. 40(4), pp. 811-815.
\150\ Thatte, H.S., Biswas, K.S., Najjar, S.F., Birjiniuk, V.,
Crittenden, M.D., Michel, T., and Khuri, S.F., ``Multi-Photon
Microscopic valuation of Saphenous Vein Endothelium and Its
Preservation With a New Solution, GALA.'' Annals Thoracic Surgery,
2003, vol. 75, pp. 1145-52.
---------------------------------------------------------------------------
In order to assess clinical outcomes associated with the use of
DuraGraft[supreg], the applicant opted to use readily available
databases associated with two hospitals that had noncommercial access
to the product through hospital pharmacies and, therefore, had real
world use of DuraGraft[supreg] treatment. The two retrospective cohort
studies, the European Retrospective Pilot Study and the USDVA Hospital
Retrospective Study, used these data bases to evaluate the
effectiveness and safety of the use of DuraGraft[supreg] during CABG
surgical procedures for post-CABG clinical complications associated
with VGF, including MI, repeat revascularization and MACE.
The European Retrospective Pilot Study (which was a feasibility
study) was a retrospective study conducted to assess the safety and
efficacy of DuraGraft[supreg] treatment on both short (less than 30
days) and long-term (greater than or equal to 30 days and up to 5
years) clinical outcomes. This study became the basis for the design of
a larger retrospective study conducted at the USDVA Hospital, discussed
below. The feasibility study is unpublished.
The European Retrospective Pilot study is a single-center clinical
study of CABG patients to evaluate the potential benefits of
DuraGraft[supreg] treatment as compared to a no-treatment control group
(saline). The investigator, who prepared the analysis, remained blinded
to individual patient data. A total of 630 patients who underwent
elective and isolated CABG surgery with at least one saphenous vein
graft between January 2002 and December 2008 were included. Eligibility
criteria were: (1) Patients with first-time CABG surgery in which at
least one vein graft was used; and (2) patients with in-situ internal
mammary artery (IMA) graft(s) only (no saphenous vein or free arterial
grafts). The single patient exclusion criteria were concomitant valve
surgery and/or aortic aneurysm repair. The institutional review board
of the University Health Alliance (UHA) approved the protocol, and
patients gave written informed consent for their follow-up. The no-
treatment control group (saline) included 375 patients who underwent
CABG surgery from January 2002 to May 2005, and the DuraGraft[supreg]
treatment group included 255 patients who underwent CABG surgery from
June 2005 to December 2008. During long-term follow-up, 5 patients were
lost to follow-up, and 10 patients died before the 30-day follow-up.
Therefore, a total of 247 patients from the DuraGraft[supreg] treatment
group (97 percent) and 368 patients from the no-treatment control group
(saline) (98 percent) were available for the long-term analysis.
Patients undergoing CABG surgery whose vascular grafts were treated
intra-operatively with DuraGraft[supreg] demonstrated no statistically
significant differences in MACE within the first 30 days following CABG
surgery. According to the applicant, these data suggest that
DuraGraft[supreg] treatment is at least as safe as the standard-of-care
used in CABG surgeries. Long-term outcomes between the two groups were
not statistically different. However, also according to the applicant,
a consistent numerical trend toward improved clinical outcomes for the
DuraGraft[supreg] treatment group compared to the no-treatment control
(saline) group was clearly identified. Although statistically
insignificant, there was a consistent reduction observed in the rates
for multiple endpoints such as all-cause death, MI, MACE, and
revascularization. This study found reductions in DuraGraft[supreg]-
treated grafts relative to saline for revascularization (57 percent),
MI (70 percent), MACE (37 percent), and all-cause death (23 percent)
compared to standard-of-care (heparinized saline/blood) through 5 years
follow-up. According to the applicant, based on the small sample size
for this evaluation of less than 630 patients and the known frequencies
of these events following CABG surgeries, statistical differences were
not expected. A subsequent post-hoc analysis also was performed by the
researchers at CHU Angers to evaluate whether any long-term clinical
variables (such as dual antiplatelet therapy, beta-blockers,
angiotensin receptor-blockers, statins, diabetes, lifestyle and other
factors) had any impact on the clinical outcomes of the study. The
conclusions of the post-hoc analyses were that the assessed long-term
clinical variables did not impact the clinical study outcomes.
The second study, the USDVA Hospital Retrospective Study, was an
unpublished, independent PI initiated, single-center, multi-surgeon,
retrospective, comparative (DuraGraft[supreg] vs. Saline) clinical
trial, which was conducted to assess the safety and impact of
DuraGraft[supreg] treatment on both short and long-term clinical
outcomes in patients who underwent isolated CABG surgery with saphenous
vein grafts (SVGs) at the Boston (West Roxbury) VA
[[Page 19310]]
Medical Center between 1996 and 2004. From 1996 through 1999,
DuraGraft[supreg] treatment was not available and heparinized saline
was routinely used to wet and store grafts. From 2001 through 2004, the
Boston VA Medical Center began exclusively using DuraGraft[supreg],
which was prepared by the hospital's pharmacy. The applicant
highlighted that 2000 data was omitted from this analysis by the PI due
to the transition into the use of DuraGraft[supreg] and the uncertainty
of whether DuraGraft[supreg] or heparinized saline was used in CABG
patients during the transition period. Short-term clinical outcomes
were defined as perioperative and early post-operative events occurring
within the first 30 days after CABG including perioperative MI,
prolonged ventilation time (greater than 48 hours), prolonged time in a
coma (greater than 24 hours), renal failure, and death. Long-term
clinical outcomes were defined as events occurring greater than 30 days
after CABG including the need for repeat revascularization (that is,
repeat CABG or percutaneous coronary intervention [PCI]), non-fatal
acute MI (NFMI), all-cause death, and a composite of these MACE. The
primary study outcome was repeat revascularization, and the secondary
outcomes included MACE, NFMI, and all cause death.
According to the applicant, although the study represents the non-
contemporaneous use of saline and DuraGraft[supreg], the potential
effect of ``time of CABG'' on outcomes was minimized in large part by
the fact that this was a single-center study in which the same surgeons
performed surgeries throughout the timeframe of this study.
Additionally, the applicant explained that published evidence
(including evidence collected from the same center) indicates that
outcomes from CABG surgery such as mortality, MI, and repeat
revascularization have not changed significantly between the time of
this study and the present day, suggesting that surgical and medical
improvements, differences in patient selection, and other factors which
may have occurred over the timeframe of the study likely had little
influence over the study results and, therefore, the statistically
significant differences that were observed are due to ``study article''
effect.151 152 153
---------------------------------------------------------------------------
\151\ Goldman, S., Zadina, K., Mortiz, T., et al., ``Long-term
patency of saphenous vein and left internal mammary grafts after
coronary artery bypass surgery: results from a Department of
Veterans Affairs Cooperative Study,'' J Am Coll Cardiol, 2004, vol.
44, pp. 2149-2156.
\152\ Granger, D.N. and Kvietys, P.R., ``Reperfusion Injury and
Reactive Oxygen Species: The Evolution of a Concept.'' Redox Biol.
2015 Dec; 6: 524-551. Published online 2015 Oct 8. doi: 10.1016/
j.redox.2015.08.020.
\153\ Guibert, E.E., Petrenko, A.Y., Balaban, C.L., Somov, A.Y.,
Rodriguez, J.V., and Fuller, B.J., ``Organ Preservation: Current
Concepts and New Strategies for the Next Decade,'' Transfus Med
Hemother, 2011, vol. 38, pp. 125-142.
---------------------------------------------------------------------------
Data were extracted from a total of 2,436 patients who underwent a
CABG procedure with at least 1 SVG from 1996 through 1999 (saline
control n=1,400 patients) and 2001 through 2004 (DuraGraft[supreg]
treatment n=1,036 patients). Patients were excluded from the study if
they had a prior history of CABG, had no use of SVG, or underwent
additional procedures during the CABG surgery.
Review of patient characteristics between the two treatment arms
found the median age for the control group was 66 years old and 67
years old for the DuraGraft[supreg] treatment group. Mean follow-up in
the control treatment group was 9.95.6 years and 8.54.2 years for the DuraGraft[supreg] treatment group.
Short-term clinical outcomes showed frequencies for individual
outcomes were low, at less than 5 percent for both treatment groups.
However, according to the applicant, there was a statistically
significant 77 percent reduction of perioperative MI in the
DuraGraft[supreg] group compared to the saline group, which may have
indicated a potential short-term benefit related to preserving the
endothelium.
Long-term clinical outcomes for patients treated with
DuraGraft[supreg] compared to saline showed DuraGraft[supreg] patients
with significantly lower risk of repeat revascularization (primary
endpoint), non-fatal MI, and MACE outcomes. According to the applicant,
the frequency of repeat revascularization was significantly lower after
DuraGraft[supreg] treatment starting at 1,000 days onwards with a
statistically significant adjusted 35 percent risk reduction.
Additionally, the applicant noted that the use of DuraGraft[supreg] was
associated with significantly lower risk for non-fatal MI beginning at
30 days post CABG with an adjusted risk reduction of 36 percent
(HR:0.687; 95 percent CI: 0.499, 0.815; p=0.0003). This effect was even
more profound at 1,000 days onward, with a statistically significant
risk reduction of up to 45 percent. Finally, the applicant noted that
the occurrence of MACE was significantly reduced after
DuraGraft[supreg] treatment, with an adjusted risk reduction of 19
percent starting at 1,000 days after CABG. Both crude and inverse
probability weighting (IPW) adjusted models for these long-term
outcomes were summarized. Long-term mortality was comparable between
treatment groups: neither the crude nor IPW-adjusted model showed a
significant association between DuraGraft[supreg] exposure and time to
death, either beginning 30 days or 1,000 days after initial CABG
surgery. According to the applicant, this study supports not only
safety, but also improved long-term clinical outcomes in
DuraGraft[supreg]-treated CABG patients.
According to the applicant, the data collected from this
statistically-powered USDVA Hospital Retrospective Study are consistent
with data collected in the European Retrospective Pilot Study in which
trend toward reductions of MI, repeat revascularization, and MACE were
observed in the DuraGraft[supreg] treatment group, lending confidence
that the observed trends in this study, as well as the European
Retrospective Pilot Study, represent real differences associated with
DuraGraft[supreg] use.
The applicant also referenced data from the SWEDEHEART 2016 Annual
Report, a report on data extracted from the Swedish Cardiac Surgery
Registry, to assess whether changes in the surgical procedure and post-
op medications over the timeline of the USDVA Hospital Retrospective
Study could have impacted the clinical outcomes. The applicant believed
that these mortality data, which overlapped with the timeframe of the
USDVA Hospital Retrospective Study, would provide an indication of
whether such changes in the CABG procedure occurred over the relevant
time period.
The applicant stated that the SWEDEHEART 2016 Annual Report was
published in 2017 and documented a fairly constant mortality rate
between 1995 and 2005 (we refer readers to the table below), which
overlapped the timeframe of the USDVA Hospital Retrospective Study
(1996 through 2004). The applicant noted that the data from the
SWEDEHEART 2016 Annual Report was extracted from the Swedish Cardiac
Surgery Registry, which collects data from all centers that are
performing, or have been performing, cardiac surgery in Sweden since
1992 and maintains 100 percent of the data covering the number of adult
cardiac surgery procedures. The applicant indicated that mortality data
are derived from the Swedish national population registry and,
therefore, are considered 100 percent complete and accurate. The
applicant noted that the 30-day mortality rate between 1996 and 2004
(the timeframe of the USDVA Hospital Retrospective Study) remained
fairly constant, even with CABG procedures performed by several
different hospitals and surgeons. According to the applicant, these
data indicate that
[[Page 19311]]
changes in the CABG procedure itself over the USDVA Hospital
Retrospective Study time period were not significant enough to impact
post-op mortality.
30-Day Mortality Rate (%) Between 1995 and 2005 Based on SWEDEHEART 2016
Annual Report
------------------------------------------------------------------------
30-day
Year Isolated CABD mortality rate
volume (%)
------------------------------------------------------------------------
1995.................................... 6,001 1.9
1996.................................... 6,283 2.2
1997.................................... 5,076 1.7
1998.................................... 5,797 2
1999.................................... 5,504 1.9
2000.................................... 5,478 2.2
2001.................................... 5,696 1.8
2002.................................... 5,645 1.9
2003.................................... 5,245 1.9
2004.................................... 4,868 2
2005.................................... 4,264 1.7
------------------------------------------------------------------------
According to the applicant, the European Retrospective Pilot Study
and the USDVA Hospital Study demonstrated an association of reduced
risk of non-fatal MI, repeat revascularization, and MACE with
DuraGraft[supreg] treatment. However, we have a number of concerns
relating to whether these results support a finding of substantial
clinical improvement. We note that these studies are unpublished and
consist of a retrospective design, which may contribute to potential
sources of error such as confounding and bias. Moreover, the studies do
not account for other variables that may affect vein integrity such as
method of vein harvest, vein distention pressure, and controlling for
the use of glycoprotein (GP) IIb/IIIa inhibitors.154 155
---------------------------------------------------------------------------
\154\ King, S., Short, M., Harmon, C., ``Glycoprotein IIb/IIIa
inhibitors: the resurgence of tirofiban,'' Vascul Pharmacol, 2016
March; vol. 78, pp. 10-16.
\155\ Harskamp, R.E., Hoedemaker, N., Newby, L.K., Woudstra, P.,
Grundeken, M.J., Beijk, M.A., Piek, J.J., Tijssen, J.G., Mehta,
R.H., de Winter, R.J., ``Procedural and clinical outcomes after use
of the glycoprotein IIb/IIIa inhibitor abciximab for saphenous vein
graft interventions,'' Cardiovasc Revasc Med, 2016 Jan-Feb, vol.
17(1), pp. 19-23. Epub 2015 Oct 31. PMID: 26626961.
---------------------------------------------------------------------------
With regard to the European Retrospective Pilot study,
specifically, we are concerned that there are no defined primary and
secondary long-term outcomes, no statistical plans to incorporate
adjustments for multiple comparisons, and no power calculations for the
expected differences in endpoints that would be biologically important.
Furthermore, we are concerned that saline was used as the control, as
opposed to buffered saline, which at the time was considered to be more
effective than saline and, therefore, may have been a more optimal
comparator.\156\ We also are concerned that certain information was not
available, including mean follow-up, patient-years follow-up and loss-
to-follow-up. Finally, the study did not appear to convey any
statistical differences for any of the short-term or long-term
endpoints.
---------------------------------------------------------------------------
\156\ Williams, J.B., Harskamp, R.E., Bose, S., Lawson, J.H.,
Alexander, J.H., Smith, P.K., Lopes, R.D., ``The Preservation and
Handling of Vein Grafts in Current Surgical Practice: Findings of a
Survey Among Cardiovascular Surgeons of Top-Ranked US Hospitals,''
JAMA Surg, 2015 Jul, vol. 150(7), pp. 681-3. PMID: 25970819.
---------------------------------------------------------------------------
With regard to the USDVA Hospital Retrospective Study, we note that
this study used heparinized saline as the comparator rather than
buffered saline. According to a survey published in 2015 of 90 major
U.S. medical centers, 40 percent were using buffered saline.\157\ Also,
we are concerned that the study population was limited to USDVA
hospital patients and was overwhelmingly white (95 percent) males (99
percent), due to the demographics available through the USDVA hospital
data source. We are concerned that this may affect the completeness of
the study and raise questions as to whether the data and results are
generalizable to other patient groups, to include, as acknowledged by
the applicant, nonveterans, women, and other racial/ethnic groups. We
also note that patients in the heparinized saline arm appeared to have
more comorbidities, more vein grafts, fewer arterial grafts and more
time on cardiopulmonary bypass as compared to the DuraGraft[supreg]
treatment arm suggesting there may have been differences in the health
of the patients in the two treatment arms prior to participation in the
study. Without more context explaining the cause of each of these
characteristics it may be difficult to substantiate the validity of the
study results. We also believe that it would have been helpful to
include coronary imaging studies with the results of the USDVA Hospital
Retrospective Study to correlate MI and revascularizations with vein
grafts. Without data from such studies, it is more difficult to
associate the solutions with the repeat revascularization outcomes.
---------------------------------------------------------------------------
\157\ Ibid.
---------------------------------------------------------------------------
Furthermore, in the FY 2019 IPPS/LTCH PPS proposed rule (83 FR
20308) we noted our concern regarding the timeframe differences in the
saline and DuraGraft[supreg] arms in the USDVA Hospital Retrospective
Study. As discussed earlier in this section, the applicant expressed
that, although the USDVA Hospital Retrospective Study represents the
non-contemporaneous use of saline and DuraGraft[supreg], the potential
effect of ``time of CABG'' on outcomes was minimized in large part by
the fact that this was a single-center study in which the same surgeons
performed surgeries throughout the timeframe of this study. The
applicant also expressed that outcomes from CABG surgery such as
mortality, MI, and repeat revascularization have not changed
significantly between the time of the USDVA Hospital Retrospective
Study and the present day, suggesting that surgical and medical
improvements that may have occurred over the timeframe of the study
likely had little influence over the study results and, therefore, the
statistically significant differences that were observed are due to
``study article'' effect.158 159 160 We appreciate the
[[Page 19312]]
applicant identifying and speaking to this concern, as it was raised by
CMS in the FY 2019 IPPS/LTCH PPS proposed rule. However, we remain
concerned that the timeframe differences between the saline and
DuraGraft[supreg] arms in the USDVA Hospital Retrospective Study were
not accounted for in the analysis of the retrospective data taken from
the study.
---------------------------------------------------------------------------
\158\ Goldman, S., Zadina, K., Mortiz, T., et al., ``Long-term
patency of saphenous vein and left internal mammary grafts after
coronary artery bypass surgery: results from a Department of
Veterans Affairs Cooperative Study,'' J Am Coll Cardiol, 2004, vol.
44, pp. 2149-2156.
\159\ Granger, D.N. and Kvietys, P.R., ``Reperfusion Injury and
Reactive Oxygen Species: The Evolution of a Concept,'' Redox Biol,
2015 Dec, vol. 6, pp. 524-551. Published online 2015 Oct 8. doi:
10.1016/j.redox.2015.08.020.
\160\ Guibert, E.E., Petrenko, A.Y., Balaban, C.L., Somov, A.Y.,
Rodriguez, J.V., and Fuller, B.J., ``Organ Preservation: Current
Concepts and New Strategies for the Next Decade,'' Transfus Med
Hemother, 2011, vol. 38, pp. 125-142.
---------------------------------------------------------------------------
Additionally, although the applicant provided an explanation about
how to match patients via propensity scores, we are concerned that the
statistical plan did not include adjustments for multiple comparisons
nor did it include power calculations for the expected differences in
endpoints that would be biologically important.
The applicant also provided information from the USDVA Hospital
Retrospective Study that suggested there are a significant number of
MACE-type events in the first 3 years after CABG. However, much of the
long-term data for the control group was missing, in particular, data
related to the first 30 to 999 days post-CABG. Finally, regarding the
secondary long-term-outcome of MACE, we are concerned the study did not
appear to include coronary cardiac mortality, non-coronary cardiac
mortality, and other cardiac morbidity within the definition of MACE.
Also, as discussed above, the applicant referenced data from the
SWEDEHEART 2016 Annual Report, which noted a decline in the number of
CABG procedures (by approximately \1/3\) between 1996 and 2005. It is
unclear what contributed to the decline in CABG procedures during this
time period, particularly because, as the applicant indicated,
mortality rates remained fairly constant throughout this timeframe. We
believe the decline in the number of CABG procedures may also reflect
time-related differences in surgical management.
We are inviting public comments on whether DuraGraft[supreg] meets
the substantial clinical improvement criterion. We did not receive any
written comments in response to the New Technology Town Hall meeting
notice published in the Federal Register regarding the substantial
clinical improvement criterion for DuraGraft[supreg] or at the New
Technology Town Hall meeting.
f. EluviaTM Drug-Eluting Vascular Stent System
Boston Scientific Corporation submitted an application for new
technology add-on payments for the EluviaTM Drug-Eluting
Vascular Stent System for FY 2020. EluviaTM, a drug-eluting
stent for the treatment of lesions in the femoropopliteal arteries,
received FDA premarket approval (PMA) on September 18, 2018.
According to the applicant, the EluviaTM system is a
sustained-release drug-eluting stent indicated for improving luminal
diameter in the treatment of peripheral artery disease (PAD) with
symptomatic de novo or restenotic lesions in the native superficial
femoral artery (SFA) and or proximal popliteal artery (PPA) with
reference vessel diameters (RVD) ranging from 4.0 to 6.0 mm and total
lesion lengths up to 190 mm.
The applicant stated that PAD is a circulatory condition in which
narrowed arteries reduce blood flow to the limbs, usually in the legs.
Symptoms of PAD may include lower extremity pain due to varying degrees
of ischemia, claudication which is characterized by pain induced by
exercise and relieved with rest. According to the applicant, risk
factors for PAD include individuals who are age 70 years old and older;
individuals who are between the ages of 50 years old and 69 years old
with a history of smoking or diabetes; individuals who are between the
ages of 40 years old and 49 years old with diabetes and at least one
other risk factor for atherosclerosis; leg symptoms suggestive of
claudication with exertion, or ischemic pain at rest; abnormal lower
extremity pulse examination; known atherosclerosis at other sites (for
example, coronary, carotid, renal artery disease); smoking;
hypertension, hyperlipidemia, and homocysteinemia.\161\ PAD is
primarily caused by atherosclerosis--the buildup of fatty plaque in the
arteries. PAD can occur in any blood vessel, but it is more common in
the legs than the arms. Approximately 8.5 million people in the United
States have PAD, including 12 to 20 percent of individuals who are age
60 years old and older.\162\
---------------------------------------------------------------------------
\161\ Neschis, David G. & MD, Golden, M., ``Clinical features
and diagnosis of lower extremity peripheral artery disease.''
Available at: https://www.uptodate.com/contents/clinical-features-and-diagnosis-of-lower-extremity-peripheral-artery-disease.
\162\ Centers for Disease Control and Prevention, ``Peripheral
Arterial Disease (PAD) Fact Sheet,'' 2018, Retrieved from https://www.cdc.gov/DHDSP/data_statistics/fact_sheets/fs_PAD.htm.
---------------------------------------------------------------------------
A diagnosis of PAD is established with the measurement of an ankle-
brachial index (ABI) less than or equal to 0.9. The ABI is a comparison
of the resting systolic blood pressure at the ankle to the higher
systolic brachial pressure. Duplex ultrasonography is commonly used, in
conjunction with the ABI, to identify the location and severity of
arterial obstruction.\163\
---------------------------------------------------------------------------
\163\ Berger, J. & Davies, M., ``Overview of lower extremity
peripheral artery disease,'' Retrieved October 29, 2018, from
https://www.uptodate.com/contents/overview-of-lower-extremity-peripheral-artery-disease.
---------------------------------------------------------------------------
Management of the disease is aimed at improving symptoms, improving
functional capacity, and preventing amputations and death. Management
of patients who have been diagnosed with lower extremity PAD may
include medical therapies to reduce the risk for future cardiovascular
events related to atherosclerosis, such as myocardial infarction,
stroke, and peripheral arterial thrombosis. Such therapies may include
antiplatelet therapy, smoking cessation, lipid-lowering therapy, and
treatment of diabetes and hypertension. For patients with significant
or disabling symptoms unresponsive to lifestyle adjustment and
pharmacologic therapy, intervention (percutaneous, surgical) may be
needed. Surgical intervention includes angioplasty, a procedure in
which a balloon-tip catheter is inserted into the artery and inflated
to dilate the narrowed artery lumen. The balloon is then deflated and
removed with the catheter. For patients with limb-threatening ischemia
(for example, pain while at rest and or ulceration), revascularization
is a priority to reestablish arterial blood flow. According to the
applicant, treatment of the SFA is problematic due to multiple issues
including high rate of restenosis and significant forces of
compression.
The applicant describes EluviaTM Drug-Eluting Vascular
Stent System as a sustained-release drug-eluting self-expanding, nickel
titanium alloy (nitinol) mesh stent used to reestablish blood flow to
stenotic arteries. According to the applicant, the EluviaTM
stent is coated with the drug paclitaxel, which helps prevent the
artery from restenosis. The applicant stated that EluviaTM's
polymer-based drug delivery system is uniquely designed to sustain the
release of paclitaxel beyond 1 year to match the restenotic process in
the SFA. According to the applicant, the EluviaTM Stent
System is comprised of: (1) The implantable endoprosthesis; and (2) the
stent delivery system (SDS). On both the proximal and distal ends of
the stent, radiopaque markers made of tantalum increase visibility of
the stent to aid in placement. The tri-axial designed delivery system
consists of an outer shaft to stabilize the stent delivery system, a
middle shaft to protect and constrain the stent, and an inner shaft to
provide a guide wire lumen. The delivery system is compatible with
[[Page 19313]]
0.035 in (0.89 mm) guide wires. The EluviaTM stent is
available in a variety of diameters and lengths. The delivery system is
offered in 2 working lengths (75 cm and 130 cm).
As discussed previously, if a technology meets all three of the
substantial similarity criteria, it would be considered substantially
similar to an existing technology and would, therefore, not be
considered ``new'' for purposes of new technology add-on payments.
With regard to the first criterion, whether a product uses the same
or a similar mechanism of action to achieve a therapeutic outcome,
according to the applicant, EluviaTM uses a unique mechanism
of action which has not been utilized by previously available medical
devices for treating stenotic lesions in the SFA. The applicant
asserted that the EluviaTM Drug-Eluting Vascular Stent
System is a device/drug combination product composed of an implantable
stent, combined with a polybutyl methacrylate (PBMA) primer layer, a
paclitaxel/polyvinylidene difluoride (PVDF) polymer, and a stent
delivery system. According to the applicant, the polymer carries and
protects the drug before and during the procedure and ensures that the
drug is released into the tissue in a controlled, sustained manner to
prevent restenosis of the vessel. According to the applicant, the
EluviaTM system continues to deliver paclitaxel to combat
restenosis for 12 to 15 months, which involves a novel and distinct
mechanism of action different than other drug-coated balloons or drug-
coated stents that only deliver the drug to the artery for about 2
months. According to the applicant, the PBMA polymer is clinically
proven to permit the sustained release of paclitaxel to achieve a
therapeutic outcome. We note that, the applicant submitted a request
for consideration for approval at the March 2019 ICD-10 Coordination
and Maintenance Committee Meeting for a unique ICD-10-PCS procedure
code to describe procedures which use the EluviaTM stent
system.
With regard to the second criterion, whether a technology is
assigned to the same or a different MS-DRG, the applicant asserted that
patients who may be eligible for treatment using the
EluviaTM system include hospitalized patients who have been
diagnosed with PAD. According to the applicant, these potential cases
may map to multiple MS-DRGs, the most likely being MS-DRGs 252 (Other
Vascular Procedures With MCC), 253 (Other Vascular Procedures With CC)
and 254 (Other Vascular Procedures Without CC/MCC). Potential cases
representing patients who may be eligible for treatment using the
EluviaTM system would be assigned to the same MS-DRGs as
cases representing hospitalized patients who have been diagnosed with
PAD and treated with currently available technologies.
With regard to the third criterion, whether the new use of the
technology involves the treatment of the same or similar type of
disease and the same or similar patient population when compared to an
existing technology, according to the applicant, clinical conditions
that may require use of the EluviaTM stent system include
treatment of the same patient population as cases identified with a
variety of diagnosis codes from the ICD-10-CM category I70
(Atherosclerosis) as listed in the table below:
------------------------------------------------------------------------
ICD-10-CM diagnosis code Code description
------------------------------------------------------------------------
I70.201............................. Unspecified atherosclerosis of
native arteries of extremities,
right leg.
I70.202............................. Unspecified atherosclerosis of
native arteries of extremities,
left leg.
I70.203............................. Unspecified atherosclerosis of
native arteries of extremities,
bilateral legs.
I70.208............................. Unspecified atherosclerosis of
native arteries of extremities,
other extremity.
I70.209............................. Unspecified atherosclerosis of
native arteries of extremities,
unspecified extremity.
I70.211............................. Atherosclerosis of native arteries
of extremities with intermittent
claudication, right leg.
I70.212............................. Atherosclerosis of native arteries
of extremities with intermittent
claudication, left leg.
I70.213............................. Atherosclerosis of native arteries
of extremities with intermittent
claudication, bilateral legs.
I70.218............................. Atherosclerosis of native arteries
of extremities with intermittent
claudication, other extremity.
I70.219............................. Atherosclerosis of native arteries
of extremities with intermittent
claudication, unspecified
extremity.
I70.221............................. Atherosclerosis of native arteries
of extremities with rest pain,
right leg.
I70.222............................. Atherosclerosis of native arteries
of extremities with rest pain,
left leg.
I70.223............................. Atherosclerosis of native arteries
of extremities with rest pain,
bilateral legs.
I70.228............................. Atherosclerosis of native arteries
of extremities with rest pain,
other extremity.
I70.229............................. Atherosclerosis of native arteries
of extremities with rest pain,
unspecified extremity.
I70.231............................. Atherosclerosis of native arteries
of right leg with ulceration of
thigh.
I70.232............................. Atherosclerosis of native arteries
of right leg with ulceration of
calf.
I70.233............................. Atherosclerosis of native arteries
of right leg with ulceration of
ankle.
I70.234............................. Atherosclerosis of native arteries
of right leg with ulceration of
heel and midfoot.
I70.235............................. Atherosclerosis of native arteries
of right leg with ulceration of
other part of foot.
I70.238............................. Atherosclerosis of native arteries
of right leg with ulceration of
other part of lower right leg.
I70.239............................. Atherosclerosis of native arteries
of right leg with ulceration of
unspecified site.
I70.241............................. Atherosclerosis of native arteries
of left leg with ulceration of
thigh.
I70.242............................. Atherosclerosis of native arteries
of left leg with ulceration of
calf.
I70.243............................. Atherosclerosis of native arteries
of left leg with ulceration of
ankle.
I70.244............................. Atherosclerosis of native arteries
of left leg with ulceration of
heel and midfoot.
I70.245............................. Atherosclerosis of native arteries
of left leg with ulceration of
other part of foot.
I70.248............................. Atherosclerosis of native arteries
of left leg with ulceration of
other part of lower left leg.
I70.249............................. Atherosclerosis of native arteries
of left leg with ulceration of
unspecified site.
I70.25.............................. Atherosclerosis of native arteries
of other extremities with
ulceration.
I70.261............................. Atherosclerosis of native arteries
of extremities with gangrene,
right leg.
I70.262............................. Atherosclerosis of native arteries
of extremities with gangrene,
left leg.
I70.263............................. Atherosclerosis of native arteries
of extremities with gangrene,
bilateral legs.
I70.268............................. Atherosclerosis of native arteries
of extremities with gangrene,
other extremity.
I70.269............................. Atherosclerosis of native arteries
of extremities with gangrene,
unspecified extremity.
I70.291............................. Other atherosclerosis of native
arteries of extremities, right
leg.
I70.292............................. Other atherosclerosis of native
arteries of extremities, left
leg.
I70.293............................. Other atherosclerosis of native
arteries of extremities,
bilateral legs.
[[Page 19314]]
I70.298............................. Other atherosclerosis of native
arteries of extremities, other
extremity.
I70.299............................. Other atherosclerosis of native
arteries of extremities.
------------------------------------------------------------------------
The applicant asserted that the EluviaTM stent is not
substantially similar to any existing technology because it uses a
unique mechanism of action, when compared to existing technologies, to
achieve a therapeutic outcome and, therefore, meets the newness
criterion.
We are concerned as to whether the polymer drug carrier system that
the EluviaTM system uses is, in fact, a new mechanism of
action as compared to stents that contain paclitaxel without the
carrier polymer. We are concerned that the EluviaTM device
may have a mechanism of action similar to the paclitaxel-coated
Zilver[supreg] Drug-Eluting Peripheral Stent, which is indicated for
improving luminal diameter for the treatment of de novo or restenotic
symptomatic lesions in native vascular disease of the above-the-knee
femoropopliteal arteries having reference vessel diameter from 4 mm to
7 mm and total lesion lengths up to 300 mm per patient. We are inviting
public comments on whether the EluviaTM system is
substantially similar to existing technology and whether it meets the
newness criterion, including with respect to the concerns we have
raised. With regard to the cost criterion, the applicant conducted the
following analysis to demonstrate that the technology meets the cost
criterion.
As noted earlier, the applicant asserted that cases involving the
treatment of PAD, involving treatment of lesions in the femoropopliteal
arteries typically, map to MS-DRGs 252, 253, and 254. The applicant
searched the FY 2017 MedPAR data file in MS-DRGs 252, 253 and 254 for
cases reporting an ICD-10-PCS procedure code for the treatment of
Peripheral BMS or DES, which the applicant believed would represent
cases potentially eligible for the use of the EluviaTM stent
system. The applicant identified 109,747 claims for cases representing
patients who may be eligible for treatment involving the
EluviaTM stent system. The applicant applied the following
trims: Claims paid under GHO (that is, Medicare beneficiaries enrolled
in a Medicare Advantage managed care plan), claims for CAHs, IPFs,
IRFs, LTCHs, Children's, Cancer, and RHNCI hospitals excluding Maryland
acute-care hospitals, claims with total charges or lengths-of-stay of
less than or equal to zero, claims with total charge differing from sum
of charges of the 19 cost groups by greater than $30, providers that do
not have charges greater than $0 for at least 14 of the 19 cost groups,
claims with total charges for the MS-DRG +/-3 standard deviations from
the log mean total charges or charges per day, ``IME only'' claims
submitted by a teaching hospital on behalf of a beneficiary enrolled in
a Medicare Advantage plan, claims with claim types ``61 to 64'' (that
is, claim types that refer to encounter claims, Medicare Advantage IME,
and HMO no-pay claims), and claims for which the applicant was unable
to calculate standardized charges (because the Provider Number
associated with the claim does not appear in the FY 2017 impact file).
This resulted in 73,861 claims across MS-DRGs 252, 253, and 254.
Using the 73,861 claims, the applicant determined an average case-
weighted unstandardized charge per case of $96,232. The applicant
removed all device-related charges and then standardized the charges
for each case and inflated each case's charges by applying the FY 2019
IPPS/LTCH PPS final rule outlier charge inflation factor of 1.08864 (83
FR 41722). (We note that the 2-year charge inflation factor was revised
in the FY 2019 IPPS/LTCH PPS final rule correction notice to 1.08986
(83 FR 49844). We further note that even when using the corrected final
rule values to inflate the charges, the average case-weighted
standardized charge per case for each scenario exceeded the average
case-weighted threshold amount.) The applicant then added charges for
EluviaTM by taking the cost of the device and converting it
to a charge by dividing the costs by the national average CCR of 0.309
for devices from the FY 2019 IPPS/LTCH PPS final rule (83 FR 41273).
The applicant calculated an average case-weighted standardized charge
per case of $86,950 using the percent distribution of MS-DRGs as case-
weights. Based on this analysis, the applicant determined that the
final inflated average case-weighted standardized charge per case for
EluviaTM exceeded the average case-weighted threshold of
$81,518 by $5,432.
The applicant conducted additional analyses to demonstrate it meets
the cost criterion. In these analyses, the applicant repeated the cost
analysis above with one analysis of cases reporting the ICD-10-PCS
procedures codes for Peripheral DES procedures and the other analysis
with cases reporting the ICD-10-PCS procedures codes for Peripheral BMS
procedures. In each of these additional sensitivity analyses, the final
inflated average case-weighted standardized charge per case exceeded
the average case-weighted cost threshold amount. We are inviting public
comments on whether EluviaTM meets the cost criterion.
With regard to the substantial clinical improvement criterion, the
applicant asserted that the EluviaTM Drug-Eluting Vascular
Stent System represents a substantial clinical improvement over
existing technologies because it achieves superior primary patency;
reduces the rate of subsequent therapeutic interventions; decreases the
number of future hospitalizations or physician visits; reduces hospital
readmission rates; reduces the rate of device-related complications;
and achieves similar functional outcomes and EQ-5D index values while
associated with half the rate of target lesion revascularizations
(TLRs).
The applicant submitted the results of the MAJESTIC study, a
single-arm, first-in-human study of EluviaTM. The MAJESTIC
\164\ study is a prospective, multi-center, single-arm, open-label
study. According to the applicant, the MAJESTIC study demonstrated
long-term treatment durability among patients whose femoropopliteal
arteries were treated with the EluviaTM stent. The applicant
asserts that the MAJESTIC study demonstrates the sustained impact of
the EluviaTM stent on primary patency. The MAJESTIC study
enrolled 57 patients who had been diagnosed with symptomatic lower limb
ischemia and lesions in the superficial femoral artery or proximal
popliteal artery. Efficacy measures at 2 years included primary
patency, defined as duplex ultrasound peak systolic velocity ratio of
less than 2.5 and the absence of target lesion revascularization (TLR)
or bypass. Safety monitoring through 3 years included adverse events
and TLR. The
[[Page 19315]]
24-month clinic visit was completed by 53 patients; 52 had Doppler
ultrasound evaluable by the core laboratory, and 48 patients had
radiographs taken for stent fracture analysis. The 3-year follow-up was
completed by 54 patients. At 2 years, 90.6 percent (48/53) of the
patients had improved by 1 or more Rutherford categories as compared
with the pre-procedure level without the need for TLR (when those with
TLR were included, 96.2 percent sustained improvement); only 1 patient
exhibited a worsening in level, 66.0 percent (35/53) of the patients
exhibited no symptoms (category 0) and 24.5 percent (13/53) had mild
claudication (category 1) at the 24-month visit. Mean ABI improved from
0.73 0.22 at baseline to 1.02 0.20 at 12
months and 0.93 0.26 at 24 months. At 24 months, 79.2
percent (38/48) of the patients had an ABI increase of at least 0.1
compared with baseline or had reached an ABI of at least 0.9. The
applicant also noted that at 12 months the Kaplan-Meier estimate of
primary patency was 96.4 percent.
---------------------------------------------------------------------------
\164\ M[uuml]ller-H[uuml]lsbeck, S., et al., ``Long-Term Results
from the MAJESTIC Trial of the Eluvia Paclitaxel-Eluting Stent for
Femoropopliteal Treatment: 3-Year Follow-up,'' Cardiovasc Intervent
Radiol, December 2017, vol. 40(12), pp. 1832-1838.
---------------------------------------------------------------------------
With regard to the EluviaTM stent achieving superior
primary patency, the applicant submitted the results of the IMPERIAL
\165\ study in which the EluviaTM stent is compared, head-
to-head, to the Zilver[supreg] PTX Drug-Eluting stent. The IMPERIAL
study is a global, multi-center, randomized controlled trial consisting
of 465 subjects. Eligible patients were aged 18 years old or older and
had a diagnosis of symptomatic lower-limb ischaemia, defined as
Rutherford Category 2, 3, or 4 and stenotic, restenotic (treated with a
drug-coated balloon greater than 12 months before the study or standard
percutaneous transluminal angioplasty only), or occlusive lesions in
the native superficial femoral artery or proximal popliteal artery,
with at least 1 infrapopliteal vessel patent to the ankle or foot.
Patients had to have stenosis of 70 percent or more (via angiographic
assessment), vessel diameter between 4 mm and 6 mm, and total lesion
length between 30 mm and 140 mm.
---------------------------------------------------------------------------
\165\ Gray, W.A., et al., ``A polymer-coated, paclitaxel-eluting
stent (Eluvia) versus a polymer-free, paclitaxel-coated stent
(Zilver PTX) for endovascular femoropopliteal intervention
(IMPERIAL): A randomised, non-inferiority trial,'' Lancet, September
24, 2018.
---------------------------------------------------------------------------
Patients who had previously stented target lesion/vessels treated
with drug-coated balloon less than 12 months prior to randomization/
enrollment and patients who had undergone prior surgery of the SFA/PPA
in the target limb to treat atherosclerotic disease were excluded from
the study. Two concurrent single-group (EluviaTM only) sub-
studies were done: A non-blinded, non-randomized pharmacokinetic sub-
study and a non-blinded, non-randomized study of patients who had been
diagnosed with long lesions (greater than 140 mm in diameter). The
IMPERIAL study is a prospective, multi-center, single-blinded
randomized, controlled (RCT) non-inferiority trial. Patients were
randomized (2:1) to implantation of either a paclitaxel-eluting polymer
stent (EluviaTM) or a paclitaxel-coated stent
(Zilver[supreg] PTX) after the treating physician had successfully
crossed the target lesion with a guide wire. The primary endpoints of
the study are Major Adverse Events defined as all causes of death
through 1 month, Target Limb Major Amputation through 12 months and/or
Target Lesion Revascularization (TLR) through 12 months and primary
vessel patency at 12 months post-procedure. Secondary endpoints
included the Rutherford categorization, Walking Impairment
Questionnaire, and EQ-5D assessments at 1 month and 6 months post-
procedure. Patient demographic and characteristics were balanced
between EluviaTM stent and Zilver[supreg] PTX stent groups.
The applicant noted that lesion characteristics for the patients in
the EluviaTM stent versus the Zilver[supreg] PTX stent arms
were comparable. Clinical follow-up visits related to the study were
scheduled for 1 month, 6 months, and 12 months after the procedure,
with follow-up planned to continue through 5 years, including clinical
visits at 24 months and 5 years and clinical or telephone follow-up at
3 and 4 years.
The applicant asserted that in the IMPERIAL study the
EluviaTM stent demonstrated superior primary patency over
the Zilver[supreg] PTX stent, 86.8 percent versus 77.5 percent,
respectively (p=0.0144). The non-inferiority primary efficacy endpoint
was also met. The applicant asserts that the SFA presents unique
challenges with respect to maintaining long-term patency. There are
distinct pathological differences between the SFA and coronary
arteries. The SFA tends to have higher levels of calcification and
chronic total occlusions when compared to coronary arteries. Following
an intervention within the SFA, the SFA produces a healing response
which often results in restenosis or re-narrowing of the arterial
lumen. This cascade of events leading to restenosis starts with
inflammation, followed by smooth muscle cell proliferation and matrix
formation.\166\ Because of the unique mechanical forces in the SFA,
this restenotic process of the SFA can continue well beyond 300 days
from the initial intervention. Results from the IMPERIAL study showed
that primary patency at 12 months, by Kaplan-Meier estimate, was
significantly greater for EluviaTM than for Zilver[supreg]
PTX, 88.5 percent and 79.5 percent, respectively (p=0.0119). According
to the applicant, these results are consistent with the 96.4 percent
primary patency rate at 12 months in the MAJESTIC study.
---------------------------------------------------------------------------
\166\ Forrester, J.S., Fishbein, M., Helfant, R., Fagin, J., ``A
paradigm for restenosis based on cell biology: clues for the
development of new preventive therapies,'' J Am Coll Cardiol, March
1, 1991, vol. 17(3), pp. 758-69.
---------------------------------------------------------------------------
The IMPERIAL study included two concurrent single-group
(EluviaTM only) sub-studies: A non-blinded, non-randomized
pharmacokinetic sub-study and a non-blinded, non-randomized study of
patients with long lesions (greater than 140 mm in diameter). For the
pharmacokinetic sub-study, patients had venous blood drawn before stent
implantation and at intervals ranging from 10 minutes to 24 hours post
implantation, and again at either 48 hours or 72 hours post
implantation. The pharmacokinetics sub-study confirmed that plasma
paclitaxel concentrations after EluviaTM stent implantation
were well below thresholds associated with toxic effects in studies in
patients who had been diagnosed with cancer (0.05 [mu]M or ~43 ng/mL).
The IMPERIAL sub-study long lesion subgroup consisted of 50
patients with average lesion length of 162.8 mm that were each treated
with two EluviaTM stents. According to the applicant, 12-
month outcomes for the long lesion subgroup are 87 percent primary
patency and 6.5 percent Target Lesion Revascularization (TLR).
According to the applicant, in a separate subgroup analysis of patients
65 years old and older (Medicare population), the primary patency rate
in the EluviaTM stent group is 92.6 percent, compared to
75.0 percent for the Zilver[supreg] PTX stent group (p=0.0386).
With regard to reducing the rate of subsequent therapeutic
interventions, secondary outcomes in the IMPERIAL study included repeat
re-intervention on the same lesion, target lesion revascularization
(TLR). The rate of subsequent interventions, or TLRs, in the
EluviaTM stent group was 4.5 percent compared to 9.0 percent
in the Zilver[supreg] PTX stent group. The applicant asserted that the
TLR rate in the EluviaTM group represents a substantial
reduction in re-intervention on the target lesion compared to that of
the Zilver[supreg] PTX stent group.
[[Page 19316]]
With regard to decreasing the number of future hospitalizations or
physician visits, the applicant asserted that the substantial reduction
in the lesion revascularization rate led to a reduced need to provide
additional intensive care, distinguishing the EluviaTM group
from the Zilver[supreg] PTX stent group. In the IMPERIAL study,
EluviaTM-treated patients required fewer days of re-
hospitalization. Patients in the EluviaTM group averaged
13.9 days of re-hospitalization for all adverse events compared to 17.7
days of re-hospitalization for patients in the Zilver[supreg] PTX stent
group. Patients in the EluviaTM group were re-hospitalized
for 2.8 days for TLR/Total Vessel Revascularization (TVR) compared to
7.1 days in the Zilver[supreg] PTX stent group. And lastly, patients in
the EluviaTM group were re-hospitalized for 2.7 days for
procedure/device-related adverse events compared to 4.5 days from the
Zilver[supreg] PTX stent group.
With regard to reducing hospital readmission rates, the applicant
asserted that patients treated in the EluviaTM group
experienced reduced rates of hospital readmission following the index
procedure compared to those in the Zilver[supreg] PTX stent group.
Hospital readmission rates at 12 months were 3.9 percent for the
EluviaTM group compared to 7.1 percent for the
Zilver[supreg] PTX stent group. Similar results were noted at 1 and 6
months; 1.0 percent versus 2.6 percent and 2.4 percent versus 3.8
percent, respectively.
With regard to reducing the rate of device-related complications,
the applicant asserted that while the rates of adverse events were
similar in total between treatment arms in the IMPERIAL study, there
were measurable differences in device-related complications. Device-
related adverse-events were reported in 8 percent of the patients in
the EluviaTM group compared to 14 percent of the patients in
the Zilver[supreg] PTX stent group.
Lastly, with regard to achieving similar functional outcomes and
EQ-5D index values, while associated with half the rate of TLRs, the
applicant asserted that narrowed or blocked arteries within the SFA can
limit the supply of oxygen-rich blood throughout the lower extremities,
causing pain or discomfort when walking (claudication). The applicant
further asserted that performing physical activities is often
challenging because of decreased blood supply to the legs, typically
causing symptoms to become more challenging over time unless treated.
While functional outcomes appear similar between the
EluviaTM and Zilver[supreg] PTX stent groups at 12 months,
these improvements for the Zilver[supreg] PTX stent group are
associated with twice as many TLRs to achieve similar EQ-5D index
values.\167\ Secondary endpoints improved after stent implantation and
were generally similar between the groups. At 12 months, of the
patients with complete Rutherford assessment data, 241 (86 percent) of
281 patients in the EluviaTM group and 120 (85 percent) of
142 patients in the Zilver[supreg] PTX group had symptoms reported as
Rutherford Category 0 or 1 (none to mild claudication). The mean ankle-
brachial index was 1.0 (SD 0.2) in both groups at 12 months (baseline
mean ankle-brachial index 0.7 [SD 0.2] for EluviaTM; 0.8
[0.2] for Zilver[supreg] PTX), with sustained hemodynamic improvement
for approximately 80 percent of the patients in both groups. Walking
function improved significantly from baseline to 12 months in both
groups, as measured with the Walking Impairment Questionnaire and the
6-minute walk test. In both groups, the majority of patients had
sustained improvement in the mobility dimension of the EQ-5D and
roughly half had sustained improvement in the pain or discomfort
dimension. No significant between-group differences were observed in
the Walking Impairment Questionnaire, 6-minute walk test, or EQ-5D.
Secondary endpoint results for the EluviaTM stent and
Zilver[supreg] PTX stent groups are as follows:
---------------------------------------------------------------------------
\167\ Gray, W.A., Keirse, K., Soga, Y., et al., ``A polymer-
coated, paclitaxel-eluting stent (Eluvia) versus a polymer-free,
paclitaxel-coated stent (Zilver PTX) for endovascular
femoropopliteal intervention (IMPERIAL): a randomized, non-
inferiority trial,'' Lancet, 2018, published online Sept 22, http://dx.doi.org/10.1016/S0140-6736(18)32262-1.
---------------------------------------------------------------------------
Hemodynamic improvement in walking--80.8 percent versus
78.7 percent;
Walking impairment questionnaire scores (change from
baseline)--40.8 (36.5) versus 35.8 (39.5);
Distance (change from baseline)--33.2 (38.3) versus 29.5
(38.2);
Speed (change from baseline)--18.3 (29.5) versus 18.1
(28.7);
Stair climbing (change from baseline)--19.4 (36.7) versus
21.1 (34.6); and
6-Minute walk test distance (m) (change from baseline)--
44.5 (119.5) versus 51.8 (130.5).
We are concerned that the IMPERIAL study, which showed significant
differences in primary patency at 12 months, was designed for non-
inferiority and not superiority. We also note the results of a recently
published meta-analysis of randomized controlled trials of the risk of
death associated with the use of paclitaxel-coated balloons and stents
in the femoropopliteal artery of the leg, which found that there is
increased risk of death following application of paclitaxel-coated
balloons and stents in the femoropopliteal artery of the lower limbs
and that further investigations are urgently warranted,\168\ although
the EluviaTM system was not included in the meta-analysis.
We are inviting public comments on whether the EluviaTM
system meets the substantial clinical improvement criterion, including
the implications of the conclusion of the meta-analysis results with
respect to a finding of substantial clinical improvement for
EluviaTM.
---------------------------------------------------------------------------
\168\ Katsanos, K., et al., ``Risk of Death Following
Application of Paclitaxel-Coated Balloons and Stents in the
Femoropopliteal Artery of the Leg: A Systematic Review and Meta-
Analysis of Randomized Controlled Trials,'' JAHA, vol. 7(24).
---------------------------------------------------------------------------
Below we summarize and respond to a written public comment we
received in response to the New Technology Town Hall meeting notice
published in the Federal Register regarding the substantial clinical
improvement criterion for EluviaTM.
Comment: With regard to the applicant's assertion that the
EluviaTM stent achieves statistically superior primary
patency over the Zilver[supreg] PTX stent, the commenter noted that the
non-inferior primary patency of EluviaTM as compared to the
Zilver[supreg] PTX stent was the primary efficacy endpoint of the
IMPERIAL study. The commenter stated that the authors of the IMPERIAL
study published a paper in The Lancet that noted a post-hoc analysis
that suggested that EluviaTM's primary patency was superior
to Zilver[supreg] PTX stent. The commenter further noted that in the FY
2020 New Technology Add-On Payment Town Hall presentation, the
EluviaTM Drug-Eluting Vascular Stent System's presenter used
this analysis as a predicator to substantiate the substantial clinical
improvement provided by the use of the EluviaTM stent. The
commenter questioned the basis of the applicant's assertion of
substantial clinical improvement contingent upon this rationale
because, according to the commenter, primary patency in this study was
measured by duplex ultrasound obtained on each enrollee at 12 months.
The commenter indicated that this is an endpoint based on imaging, and
in and of itself, may not have any direct clinical significance. The
commenter suggested that a loss of patency alone, without an associated
recurrence or increase of clinical signs or symptoms (pain, walking
impairment, ulcer development, etc.,) is
[[Page 19317]]
not a clinically-relevant measure. As such, the commenter believed that
the rationale used in that post-hoc analysis to determine superiority
in primary patency does not offer support for an assertion of clinical
improvement. The commenter noted that it is an interesting finding, but
as discussed further below, the commenter does not believe this
translates into a representation of substantial clinical improvement.
The commenter further stated that ``the pre-specified primary endpoint
of the study indicated non-inferiority of primary patency of
EluviaTM when compared to the Zilver[supreg] PTX stent, with
a non-significant difference of 5.3 percent (95 percent confidence
interval: -2.5 percent, 13.1 percent); and this information was not
included in the New Technology Town Hall presentation''.
With regard to the applicant's assertion that the
EluviaTM stent reduces the rate of subsequent therapeutic
interventions by 50 percent, the commenter noted that ``Subsequent
Therapeutic Interventions'' was not further defined in the New
Technology Town Hall presentation nor in the IMPERIAL study. The
commenter stated that it would appear from the presentation materials,
however, that it is referring specifically to ``target lesion
revascularizations (TLR)''.
The commenter referred to the EluviaTM New Technology
Town Hall presentation slide deck, and stated that the presenter
displayed graphs showing ``Clinically-driven TLR Rates'' for both the
EluviaTM stent and the Zilver[supreg] PTX stent. The
commenter stated that the graph showed a TLR rate for
EluviaTM of 4.5 percent, and a corresponding TLR rate of 9.0
percent for the Zilver[supreg] PTX stent, with that slide also
displaying a p-value of 0.0672. The commenter explained that because a
p-value of less than 0.05 is widely accepted in the scientific and
clinical communities as a threshold to establish a statistically
significant difference, a p-value of 0.0672 suggests that the
difference between the devices' TLR rates is not statistically
significant. The commenter believed that, given that the difference in
TLR rates is not statistically significant, no conclusions can or
should be drawn regarding substantial clinical improvement based on
these TLR rates. The commenter stated that the Lancet study paper
itself reported a TLR rate of 4.5 percent for EluviaTM and
8.7 percent for the Zilver[supreg] PTX stent, with an even higher p-
value of 0.0746,\169\ and the commenter believes that the difference in
TLR rates is more questionably meaningful. With regard to the
applicant's assertion that EluviaTM achieves similar
functional outcomes with half as many TLRs (repeat procedures) at 1
year, the commenter stated that based on the data presented during the
New Technology Town Hall presentation and discussed at length in the
Lancet study paper, ``functional'' clinical outcomes between the
EluviaTM and the Zilver[supreg] PTX patients were similar.
These clinical outcome measures included walking function (assessed
with the Walking Impairment Questionnaire and 6-minute walk test),
Rutherford scores, EQ-5D quality of life scores, and ankle-brachial
index measures. The commenter believed that these similar results
dispute the conclusion that EluviaTM represents a
substantial clinical improvement compared to the Zilver[supreg] PTX
stent. Further, the commenter stated that this section of the
presentation once again references and is based on the difference in
TLR rates. As noted above, the commenter believed that this difference
in rates was not demonstrated to be significant and, therefore, should
not be the basis for a conclusion of clinical improvement.
Additionally, the commenter also noted that, although not described in
the New Technology Town Hall presentation, the Lancet publication
indicates that the calculations of clinical improvement and hemodynamic
improvement already account for TLR as a failure. Therefore, the
commenter believed that stating that the outcomes are similar with half
as many TLRs is misleading. The commenter further stated that similar
clinical outcomes and TLR rates do support the study's conclusions of
non-inferiority, but should not form the basis for an assertion of
superiority.
---------------------------------------------------------------------------
\169\ Gray, W.A., et al., ``A polymer-coated, paclitaxel-eluting
stent (Eluvia) versus a polymer-free, paclitaxel-coated stent
(Zilver PTX) for endovascular femoropopliteal intervention
(IMPERIAL): a randomised, non-inferiority trial,'' Lancet, September
24, 2018.
---------------------------------------------------------------------------
With regard to the applicant's assertion that the use of the
EluviaTM stent reduces hospital readmission rates, the
commenter noted that during the New Technology Town Hall presentation,
the presenter noted that the EluviaTM group had a hospital
readmission rate at 12 months of 3.9 percent compared to the
Zilver[supreg] PTX group's rate of 7.1 percent, and that no p-value was
included on the slide used for the presentation to offer an assessment
of the statistical significance of this difference. The commenter noted
that this particular data comparison was not discussed in the main body
of the Lancet paper, but could be found in the online appendix. The
commenter further noted that as with the presentation slide, no p-value
was offered in the appendix. The commenter indicated that its
statistics team did, however, calculate a p-value of 0.17 for this
comparison. The commenter noted that a p-value of 0.17 is well above
the standard p-value threshold of 0.05 needed to draw a conclusion of
statistical significance. Given that this difference is not
statistically significant, the commenter believed that based on this
submitted data, this assertion should also not be used to substantiate
a representation of substantial clinical improvement for the
EluviaTM stent.
With regards to longer-term data on the Zilver[supreg] PTX stent
and the EluviaTM stent, the commenter noted that in the
commentary in The Lancet paper accompanying the IMPERIAL study, Drs.
Salvatore Cassese and Robert Byrne write that a follow-up duration of
12 months is insufficient to assess late failure, which is not
infrequently observed. According to Drs. Cassese and Byrne, the
preclinical models of restenosis after stenting of peripheral arteries
have shown that stents permanently overstretch the arterial wall, thus
stimulating persistent neointimal growth, which might cause a catch-up
phenomenon and late failure. The paper noted that in this regard, data
on outcomes beyond 1 year will be important to confirm the durability
of the efficacy of the EluviaTM stent.\170\ The commenter
stated that at this point in time, very limited longer-term data is
available on the use of the EluviaTM stent and that the
IMPERIAL study offers only 12-month data, although data out to 3 years
has been published from the relatively small 57-patient single-arm
MAJESTIC study. The commenter noted that the MAJESTIC study
demonstrates a decrease in primary patency from 96.4 percent at 1 year
to 83.5 percent at 2 years; and a doubling in TLR rates from 1 year to
2 years (3.6 percent to 7.2 percent) and again from 2 years to 3 years
(7.2 percent to 14.7 percent). The commenter stated that this is not
inconsistent with Drs. Cassese and Byrne's commentary regarding late
failure, and that the relatively small, single-arm design of the study
does not lend itself well to direct comparison to other SFA treatment
options such as the Zilver[supreg] PTX stent.
---------------------------------------------------------------------------
\170\ Cassese, S., & Byrne, R.E., ``Endovascular stenting in
femoropopliteal arteries,'' The Lancet, 2018, vol. 392(10157), pp.
1491-1493.
---------------------------------------------------------------------------
The commenter stated that EluviaTM's lack of long-term
data contrasts with 5-year data that is available from the
Zilver[supreg] PTX stent's pivotal 479-patient
[[Page 19318]]
RCT comparing the use of the Zilver[supreg] PTX stent to angioplasty
(with a sub-randomization comparing provisional use of Zilver[supreg]
PTX stenting to bare metal Zilver stenting in patients experiencing an
acute failure of percutaneous transluminal angioplasty (PTA)). The
commenter believed that these 5-year data demonstrate that the
superiority of the use of the Zilver[supreg] PTX stent demonstrated at
12 and 24 months is maintained through 5 years compared to PTA and
provisional bare metal stenting, and actually increases rather than
decreases over time. The commenter also believed that, given that these
stent devices are permanent implants and they are used to treat a
chronic disease, long-term data is important to fully understand an SFA
stent's clinical benefits. The commenter stated that with 5-year data
available to support the ongoing safety and effectiveness of the use of
the Zilver[supreg] PTX stent, but no such corresponding data available
for the use of the EluviaTM stent, it seems incongruous to
suggest that the use of the EluviaTM stent results in a
substantial clinical improvement compared to the Zilver[supreg] PTX
stent.
The commenter further stated that, in addition to the very limited
long-term data available for the EluviaTM stent, there is
also a lack of clinical data for the use of the EluviaTM
stent to confirm the benefit of the device outside of a strictly
controlled clinical study population. The commenter stated that in
contrast, the Zilver[supreg] PTX stent has demonstrated comparable
outcomes across a broad patient population, including a 787-patient
study conducted in Europe with 2-year follow-up and a 904-patient study
of all-comers (no exclusion criteria) in Japan with 5-year follow-up
completed. The commenter believed that with no corresponding data for
the use of the EluviaTM stent in a broad patient population,
it seems unreasonable to suggest that the use of the
EluviaTM stent results in a substantial clinical improvement
compared to the Zilver[supreg] PTX stent.
Response: We appreciate the information provided by the commenter.
We will take these comments into consideration when deciding whether to
approve new technology add-on payments for the EluviaTM
Drug-Eluting Vascular Stent System for FY 2020.
g. ELZONRISTM (tagraxofusp, SL-401)
Stemline Therapeutics submitted an application for new technology
add-on payments for ELZONRISTM for FY 2020.
ELZONRISTM (tagraxofusp, SL-401) is a targeted therapy for
the treatment of blastic plasmacytoid dendritic cell neoplasm (BPDCN)
administered via infusion. The applicant stated that BPDCN, previously
known as blastic natural killer (NK) cell leukemia/lymphoma, is a rare,
highly aggressive hematologic malignancy with a median overall survival
of 8 to 14 months from diagnosis that occurs predominantly in the
elderly (median age at diagnosis is 67 years old) and in male patients
(75 percent). The applicant cited data from the Surveillance,
Epidemiology, and End Results Program (SEER) registry that the
estimated incidence of BPDCN is less than 100 new cases per year in the
U.S. However, the applicant believes that registries likely
underestimate the true incidence of BPDCN due to changing nomenclature
and lack of a standardized disease characterization prior to 2008, and
that additional patients may be eligible for treatment.
According to the applicant, ELZONRISTM is a targeted
therapy directed to the interleukin-3 receptor (IL-3 receptor). The IL-
3 receptor is composed of two chains: An alpha chain, also known as
CD123, and a [beta] chain. Together, the two chains form a high-
affinity cell surface receptor for interleukin-3 (IL-3). The binding of
IL-3 to the IL-3 receptor initiates signaling that stimulates the
proliferation and differentiation of certain hematopoietic cells. The
alpha unit of the IL-3 receptor (also known as CD123) has also been
found to be expressed in a variety of cancers, including BPDCN, a
malignancy derived from plasmacytoid dendrite cells (pDCs).
The applicant explained that ELZONRISTM is a recombinant
protein composed of human IL-3 genetically fused to a truncated
diphtheria toxin (DT) payload. The applicant stated that
ELZONRISTM binds with high affinity to the IL-3 receptor and
is engineered such that IL-3 replaces the native receptor-binding
domain of DT and thereby acts like a homing device, targeting the DT
cytotoxic payload specifically to CD123-expressing cells. Upon binding
to the IL-3 receptor, ELZONRISTM is internalized into
endosomes, where the low pH environment enables proteolytic cleavage
and release of the catalytic domain of DT into the cytoplasm. The
target of DT's catalytic domain is elongation factor 2 (EF-2), a key
protein involved in protein translation. Inactivation of EF-2 leads to
termination of protein synthesis, which ultimately results in cell
death. The applicant asserted that ELZONRISTM is engineered
such that IL-3 targets the cytotoxic payload specifically to CD123-
expressing cells.
The applicant indicated that the regimens historically employed for
the treatment of patients who have been diagnosed with BPDCN have
generally consisted of those regimens, or modified versions of those
regimens, used for aggressive hematologic malignancies, including
regimens normally used in the treatment of acute lymphoblastic
leukemia, acute myeloid leukemia, and lymphoma. The applicant
summarized the mechanisms of various drugs and regimens currently used
to treat BPDCN, including:
Etoposide, which the applicant explained works by
inhibiting topoisomerase II, which in turn disrupts the ligation step
of the cell cycle, leading to apoptosis and cell death.
Hyper CVAD, which the applicant explained is a regimen
consisting of cyclophosphamide, vincristine and doxorubicin,
dexamethasone, methotrexate, and cytarabine. Cyclophosphamide damages
DNA by binding to it and causing the formation of cross-links.
Vincristine prevents cell duplication by binding to the protein
tubulin. Dexamethasone is a steroid to counteract side effects.
Methotrexate is an antimetabolite that competitively inhibits an enzyme
that is used in in folate synthesis, arresting cell reproduction.
CHOP, which the applicant explained is a regimen of
cyclophosphamide, doxorubicin, vincristine, and prednisone.
AspaMetDex L-asparaginase, Methotrexate, Dexamethasone.
The applicant explained that L-asparaginase catalyzes the conversion of
L-asparagine to aspartic acid and ammonia, depriving leukemic cells of
L-asparagine, leading to cell death.
Ara-C regimen (cytarabine), which the applicant explained
interferes with synthesis of DNA by altering the sugar component of
nucleosides.
The applicant stated that there are no approved therapies or
established standards of care for the treatment of patients who have
been diagnosed with BPDCN, either for treatment-naive or previously-
treated patients. The applicant asserted that current treatments for
patients who have been diagnosed with BPDCN might temporarily help to
slow disease progression, but they fail to eradicate cancer stem cells
(CSCs), and no specific treatment regimen has been shown to be
effective or is recommended. According to the applicant, only half of
reported patients show initial response to the regimens historically
employed for treatment of a diagnosis of BPDCN, and these reported
responses do not generally appear to be
[[Page 19319]]
durable, with many patients experiencing a quick relapse. Overall
survival is typically low, ranging from 8 to 14 months across various
treatment regimens.
With respect to the newness criterion, according to the applicant,
the FDA accepted the applicant's Biologics License Application (BLA)
filing for ELZONRISTM in August 2018 for the treatment of
patients who have been diagnosed with blastic plasmacytoid dendritic
cell neoplasm. The FDA granted this application Breakthrough Therapy,
Priority Review, and Orphan Drug designations, and on December 21,
2018, approved ELZONRISTM for the treatment of blastic
plasmacytoid dendritic cell neoplasm in adults and in pediatric
patients 2 years old and older. Currently, there are no ICD-10-PCS
procedure codes to uniquely identify procedures involving
ELZONRISTM. We note that the applicant has submitted a
request for approval for a unique ICD-10-PCS code for the
administration of ELZONRISTM beginning in FY 2020.
As discussed above, if a technology meets all three of the
substantial similarity criteria, it would be considered substantially
similar to an existing technology and would not be considered ``new''
for purposes of new technology add-on payments.
With regard to the first criterion, whether a product uses the same
or a similar mechanism of action to achieve a therapeutic outcome,
according to the applicant, ELZONRISTM treats BPDCN via
target antigen specificity, attacking cells with the IL-3 receptor
(CD123) overexpressed in cancer stem cells (CSCs) and tumor bulk, but
minimally expressed or absent on normal hematopoietic stem cells. The
applicant indicated that ELZONRISTM's mechanism of action
involves a receptor-mediated endocytosis, inhibition of protein
synthesis, and interference with IL-3 signal transduction pathways,
leading to growth arrest and apoptosis in leukemia blasts and CSCs. The
applicant asserted that current BPDCN treatments are not targeted, and
their mechanisms of action aim to arrest quickly-dividing cells through
DNA alkylation and intercalation, as well as through protein binding to
prevent cell duplication. The applicant also asserted that current
treatments for patients who have been diagnosed with BPDCN might
temporarily help to slow disease progression, but they fail to
eradicate CSCs. The applicant stated that in contrast,
ELZONRISTM utilizes a payload that is not cell cycle-
dependent and, therefore, it is able to kill not just highly
proliferative tumor bulk, but also the relatively quiescent CSCs. The
applicant noted that there are similar targeted therapies currently
under investigation, although the applicant asserted that these other
therapies are all in much earlier stages of development. Therefore, the
applicant asserted that ELZONRISTM utilizes a different
mechanism of action than currently available treatment options.
With respect to the second criterion, whether a product is assigned
to the same or a different MS-DRG, the applicant stated that because
BPDCN is a distinct and rare hematologic malignancy and there are no
other approved therapies or established standard-of-care, cases
representing patients receiving treatment involving
ELZONRISTM would not be assigned to the same MS-DRG(s) when
compared to cases representing patients receiving treatment involving
existing technologies. We note that, as explained below in the
discussion of the cost criterion, the applicant stated that potential
cases representing patients who may be eligible for treatment involving
ELZONRISTM would be assigned to MS-DRGs that contain cases
representing patients who are receiving chemotherapy without acute
leukemia as a secondary diagnosis.
With respect to the third criterion, whether the new use of the
technology involves the treatment of the same or similar type of
disease and the same or similar patient population, according to the
applicant, the use of ELZONRISTM would involve treatment of
a dissimilar patient population as compared to other therapies. The
applicant stated that the World Health Organization standardized the
current name and specific category of disease for BPDCN in 2016,
designating it as a distinct entity within the acute myeloid neoplasms
and acute leukemias. The applicant indicated that no BPDCN standard-of-
care has been established and currently patients who have been
diagnosed with BPDCN are being treated with therapies used for other
diseases. Therefore, the applicant asserted that ELZONRISTM
would be used in the treatment of a new patient population because the
patient population in question is distinguishable from others by the
ICD-10-CM diagnosis code specific to BPDCN: C86.4 (Blastic NK-cell
lymphoma), for which there is no specific treatment regimen that has
been shown to be effective or is recommended, as stated above.
As summarized above, the applicant maintains that
ELZONRISTM meets the newness criterion and is not
substantially similar to existing technologies because it has a unique
mechanism of action; potential cases representing patients who may be
eligible for treatment involving the use of ELZONRISTM would
be assigned to a different MS-DRG when compared to existing
technologies; and the use of the technology would treat a new patient
population. We are inviting public comments on whether
ELZONRISTM is substantially similar to any existing
technologies and whether ELZONRISTM meets the newness
criterion.
With regard to the cost criterion, the applicant used the FY 2017
MedPAR Hospital Limited Data Set (LDS) to assess the MS-DRGs to which
cases representing potential patient hospitalizations that may be
eligible for treatment involving ELZONRISTM would most
likely be assigned. The applicant identified these potential cases
using the ICD-10-CM diagnosis code C86.4 (Blastic NK-cell lymphoma),
which the applicant stated is another name for BPDCN. The applicant
identified 65 cases reporting ICD-10-CM diagnosis code C86.4 spanning
28 different MS-DRGs. The applicant asserted that cases representing
patients hospitalized who may be eligible to receive treatment
involving ELZONRISTM would most likely appear in MS-DRGs 847
(Chemotherapy without Acute Leukemia as Secondary Diagnosis with CC)
and 846 (Chemotherapy without Acute Leukemia as Secondary Diagnosis
with MCC). Therefore, the applicant limited the analysis to the cases
in MS-DRG 847 and MS-DRG 846 that also reported the ICD-10-CM diagnosis
code C86.4. The cases identified in these two MS-DRGs accounted for 24
(37 percent) of the 65 cases reporting ICD-10-CM diagnosis code C86.4.
The applicant indicated that because the number of cases reporting
ICD-10-CM diagnosis code C86.4 is so low and it was difficult to
discern the costs of the predecessor therapies that would be replaced
by the use of ELZONRISTM, the applicant performed the cost
criterion analysis under two different scenarios. Both scenarios use
the 24 cases identified in the FY 2017 MedPAR data and increase the
sample size by using an additional 18 cases identified in the FY 2016
MedPAR data mapping to the same MS-DRGs and reporting the same ICD-10-
CM diagnosis code, for a combined total of 42 cases with an average
case-weighted unstandardized charge per case of $67,947. For the first
scenario, because the applicant was unable to determine the appropriate
costs for the predecessor therapies, the applicant did not remove any
predecessor charges from the cases analyzed, although the applicant
noted that it might be extreme
[[Page 19320]]
to assume that no products or services would be replaced if
ELZONRISTM were used. For the second scenario, the applicant
removed all charges from the cases so that only ELZONRISTM
was used as the cost of the case. The applicant characterized this as a
conservative assumption, as it assumes that the only charges related to
these cases would be the cost of ELZONRISTM.
The applicant then standardized the FY 2017 charges using the FY
2017 impact file and then inflated the charges to FY 2019 using the 2-
year inflation factor of 8.59 percent (1.085868) that the applicant
indicated was published in the FY 2019 IPPS/LTCH PPS final rule. The
applicant standardized FY 2016 charges using the FY 2016 impact file
and then inflated the charges to FY 2019 using a 3-year inflation
factor of 13.15 percent (1.131529), which was calculated based on the
1-year inflation factor (1.04205) that the applicant indicated was
listed in the FY 2019 IPPS/LTCH PPS final rule. We note that the
inflation factors used by the applicant were the proposed 1-year and 2-
year inflation factors, which were published in the FY 2019 IPPS/LTCH
PPS final rule in the summary of FY 2019 IPPS proposals (83 FR 41718).
The final 1-year and 2-year inflation factors published in the FY 2019
IPPS/LTCH PPS final rule are 1.04338 and 1.08864, respectively (83 FR
41722), and a 3-year inflation factor calculated based on these numbers
is 1.13587. We note that these figures were revised in the FY 2019
IPPS/LTCH PPS final rule correction notice. The corrected final 1-year
and 2-year inflation factors are 1.04396 and 1.08986, respectively (83
FR 49844), and a 3-year inflation factor calculated based on the
corrected final numbers is 1.13776.
The applicant then added charges for ELZONRISTM in both
scenarios. To determine the charges for ELZONRISTM, the
applicant calculated the average per discharge cost of
ELZONRISTM inflated by the inverse of the national average
CCR for pharmacy costs of 0.191. The applicant then calculated an
average case-weighted standardized charge per case for each scenario
and compared it with the average case-weighted threshold amount. The
applicant stated that ELZONRISTM exceeded the average-case-
weighted threshold amount under each scenario and, therefore, meets the
cost criterion. Results of the analyses of both scenarios are
summarized in the table below:
----------------------------------------------------------------------------------------------------------------
Average case-
weighted new Final inflated
Number of technology average Amount
Medicare cases add-on case[dash]weighted exceeded
payment standardized threshold
threshold charge per case
----------------------------------------------------------------------------------------------------------------
FY 2016 and FY 2017 MedPAR Data; No 42 $52,049 $1,066,195 $1,014,146
Predecessor Charges Removed................
FY 2016 and FY 2017 MedPAR Data; All 42 52,049 1,010,455 958,406
Predecessor Charges Removed................
----------------------------------------------------------------------------------------------------------------
We note that the applicant used the proposed rule values to inflate
the standardized charges. However, we further note that even when using
either the final rule values or corrected final rule values to inflate
the charges, the average case-weighted standardized charge per case for
each scenario exceeded the average case-weighted threshold amount. We
are inviting public comments on whether ELZONRISTM meets the
cost criterion.
With respect to the substantial clinical improvement criterion, the
applicant stated that it believes ELZONRISTM represents a
substantial clinical improvement because: (1) ELZONRISTM is
the only treatment indicated specifically for the treatment of patients
who have been diagnosed with BPDCN, a disease without a defined
standard-of-care; (2) ELZONRISTM offers a treatment option
for a patient population ineligible for aggressive chemotherapy
regimens used to treat BPDCN; (3) ELZONRISTM exhibits high
complete remission rates, potentially superior to other regimens used
to treat a diagnosis of BPDCN; (4) ELZONRISTM significantly
improves overall survival (OS) in the treatment of patients diagnosed
with BPDCN as compared to currently available treatment regimens; (5)
ELZONRISTM significantly improves clinical outcomes in the
BPDCN patient population because it may allow more patients to bridge
to stem cell transplantation, an effective treatment not currently
administered to most patients due to their inability to tolerate the
requisite conditioning therapies; (6) ELZONRISTM exhibits a
manageable profile that is consistent over increasing patient exposure
and experience, demonstrating a well-tolerated targeted therapy
suitable for the majority of patients who are unable to receive
intensive chemotherapy; and (7) ELZONRISTM is more efficient
than other chemotherapeutic drugs at killing BPDCN in preclinical
studies, suggesting clinical benefit would also be exhibited if head-
to-head comparison was pursued.
In support of the claim that ELZONRISTM is the only
treatment indicated specifically for the treatment of patients who have
been diagnosed with BPDCN, the applicant submitted a 2016 review
article which indicated that no standardized therapeutic approach has
been established yet for the treatment of BPDCN, and the optimal
therapy remains to be defined.\171\
---------------------------------------------------------------------------
\171\ Pagano, L., Valentini, C.G., Grammatico, S., Pulsoni, A.,
``Blastic plasmacytoid dendritic cell neoplasm: diagnostic criteria
and therapeutical approaches,'' British Journal of Haematology,
2016, vol. 174(2), pp. 188-202.
---------------------------------------------------------------------------
Second, in support of the claim that ELZONRISTM offers a
treatment option for a patient population ineligible for aggressive
chemotherapy regimens used to treat BPDCN, the applicant submitted a
2016 review of treatment modalities for patients who have been
diagnosed with BPDCN to establish that there is a clear unmet need for
targeted treatment. The study reported that seven BPDCN patients
treated with Hyper-CVAD, an aggressive chemotherapy regimen, achieved
an overall response of 86 percent and complete remission of 67 percent;
\172\ however, the applicant noted that the evidence is limited to a
small number of patients. Another 2016 review article indicated that
supportive care or palliative chemotherapy is used in the treatment of
many patients who have been diagnosed with BPDCN because of their age
or comorbidities, and may be the only option for elderly patients with
a low performance status or characterized by the presence of relevant
co-morbidities, suggesting that targeted therapy has the potential for
improving patient outcomes.\173\
---------------------------------------------------------------------------
\172\ Falcone, U., Sibai, H., Deotare, U., ``A critical review
of treatment modalities for blastic plasmacytoid dendritic cell
neoplasm,'' Critical Reviews in Oncology/Hematology, 2016, vol. 107,
pp. 156-162.
\173\ Pagano, L., Valentini, C.G., Grammatico, S., Pulsoni, A.,
``Blastic plasmacytoid dendritic cell neoplasm: diagnostic criteria
and therapeutical approaches,'' British Journal of Haematology,
2016, vol. 174(2), pp. 188-202.
---------------------------------------------------------------------------
[[Page 19321]]
Third, the applicant maintained that ELZONRISTM exhibits
high complete remission rates, potentially superior to other regimens
used to treat patients who have been diagnosed with BPDCN. The
applicant submitted a 2013 retrospective case study of patients who had
been diagnosed with BPDCN, in which 15/41 (37 percent) of evaluable
patients achieved CR with induction therapies; 2 partial responders
subsequently became complete responders with consolidation therapy (17/
41: 41 percent). This study noted a high death rate of 17 percent
following induction treatment.\174\ The applicant reported prospective
clinical trial data from ELZONRISTM's pivotal trial
(ELZONRISTM 12 [micro]g/kg/day), which observed a complete
response plus a complete clinical response of 72 percent in treatment-
naive patients (21/29 patients).\175\
---------------------------------------------------------------------------
\174\ Pagano, L., Valentini, C.G., Pulsoni, A., et al., for
GIMEMA-ALWP (Gruppo Italiano Malattie EMatologiche dell'Adulto,
Acute Leukemia Working Party), ``Blastic plasmacytoid dendritic cell
neoplasm with leukemic presentation: an Italian multicenter study,''
Haematologica, 2013, vol. 98(2), pp. 239-246.
\175\ Pemmaraju, N., et al., ``Results of Pivotal Phase 2 Trial
of SL-401 in Patients with Blastic Plasmacytoid Dendritic Cell
Neoplasm (BPDCN),'' Proceedings from the 2018 European Hematology
Association Congress, 2018, Abstract 214438.
---------------------------------------------------------------------------
Fourth, the applicant maintained that ELZONRISTM
significantly improves overall survival (OS) in patients who have been
diagnosed with BPDCN as compared to currently available treatment
regimens. The applicant submitted a 2013 retrospective case study of
patients who have been diagnosed with BPDCN, which found that the
median overall survival was just 8.7 months in 43 patients.\176\ The
applicant reported prospective clinical trial data from
ELZONRISTM's pivotal trial (ELZONRISTM 12
[micro]g/kg/day), which found that median overall survival has not yet
been reached, with a median follow-up of 23 months [0.2-41 +
months].\177\
---------------------------------------------------------------------------
\176\ Pagano, L., Valentini, C.G., Pulsoni, A., et al., for
GIMEMA-ALWP (Gruppo Italiano Malattie EMatologiche dell'Adulto,
Acute Leukemia Working Party), ``Blastic plasmacytoid dendritic cell
neoplasm with leukemic presentation: an Italian multicenter study,''
Haematologica, 2013, vol. 98(2), pp. 239-246.
\177\ Pemmaraju, N., et al., ``Results of Pivotal Phase 2
Clinical Trial of Tagraxofusp (SL-401) in Patients with Blastic
Plasmacytoid Dendritic Cell Neoplasm (BPDCN),'' Proceedings from the
2018 American Society of Hematology (ASH), 2018, Abstract S765.
---------------------------------------------------------------------------
Fifth, the applicant maintained that ELZONRISTM
significantly improves clinical outcomes in the treatment of the BPDCN
patient population because it may allow more patients to bridge to stem
cell transplantation, an effective treatment not currently administered
to most patients due to their inability to tolerate the requisite
conditioning therapies. The applicant submitted a 2011 retrospective
study that included 6 cases of elderly patients who had been diagnosed
with BPDCN in which 4 patients underwent allogenic stem cell
transplantation (SCT) following moderately reduced intensity of
conditioning chemotherapy regimens; 2 patients who received stem cell
transplant while in remission lived disease free 57 months and 16
months post-SCT, and 2 patients transplanted with active disease
achieved complete remission but relapsed 6 and 18 months after
transplantation. Conditioning chemotherapy regimens were reduced in
intensity due to the patients' elderly age.\178\ The applicant also
submitted a 2015 retrospective study of 25 BPDCN cases in which
patients were treated with SCT. Of 11 BPDCN patients treated with
autologous SCT and 14 patients treated with allogenic SCT, overall
survival (OS) at 4 years was 82 percent and 69 percent, respectively,
and no relapses were observed.\179\ The applicant also submitted a 2013
retrospective study of 43 BPDCN cases in which only 6 out of 43
patients (14 percent) received allogenic SCT.\180\ The applicant
submitted a 2010 retrospective study of BPDCN cases in which only 10
out of 47 patients (21 percent) received SCT.\181\ The applicant
submitted a 2016 review article which concluded that early results from
clinical trials for ELZONRISTM indicate that it could be
used to consolidate the effects of first-line chemotherapy and/or
reduce minimal residual disease before allogenic SCT.\182\ The
applicant reported prospective clinical trial data from
ELZONRISTM's pivotal trial (ELZONRISTM 12 [mu]g/
kg/day), for which the median age among the patients with BPDCN who
received treatment involving ELZONRISTM was 70 years old, in
which 45 percent (13/29) of treatment-na[iuml]ve patients treated with
ELZONRISTM (12 [micro]g/kg/day) were bridged to SCT in
remission.\183\
---------------------------------------------------------------------------
\178\ Dietrich, S., et al., ``Blastic plasmacytoid dendritic
cell neoplasia (BPDC) in elderly patients: results of a treatment
algorithm employing allogeneic stem cell transplantation with
moderately reduced conditioning intensity,'' Biology of Blood and
Marrow Transplantation, 2011, vol. 17, pp. 1250-1254.
\179\ Aoki, T., et al., ``Long-term survival following
autologous and allogenic stem cell transplantation for Blastic
plasmacytoid dendritic cell neoplasm,'' Blood, 2015, vol. 125(23),
pp. 3559-3562.
\180\ Pagano, L., Valentini, C.G., Pulsoni, A., et al., for
GIMEMA-ALWP (Gruppo Italiano Malattie EMatologiche dell'Adulto,
Acute Leukemia Working Party), ``Blastic plasmacytoid dendritic cell
neoplasm with leukemic presentation: an Italian multicenter study,''
Haematologica, 2013, vol. 98(2), pp. 239-246.
\181\ Dalle, S., et al., ``Blastic plasmacytoid dendritic cell
neoplasm: is transplantation the treatment of choice?,'' The British
Journal of Dermatology, 2010, vol. 162, pp. 74-79.
\182\ Pagano, L., Valentini, C.G., Grammatico, S., Pulsoni, A.,
``Blastic plasmacytoid dendritic cell neoplasm: diagnostic criteria
and therapeutical approaches,'' British Journal of Haematology,
2016, vol. 174(2), pp. 188-202.
\183\ Pemmaraju, N., et al., ``Results of Pivotal Phase 2 Trial
of SL-401 in Patients with Blastic Plasmacytoid Dendritic Cell
Neoplasm (BPDCN),'' Proceedings from the 2018 European Hematology
Association Congress, 2018, Abstract 214438.
---------------------------------------------------------------------------
Sixth, the applicant maintained that ELZONRISTM exhibits
a manageable profile that demonstrates a well-tolerated targeted
therapy suitable for the majority of patients who are unable to receive
intensive chemotherapy. The prospective clinical trial data from
ELZONRISTM's pivotal trial (ELZONRISTM 12
[micro]g/kg/day) found that ELZONRISTM's side effect profile
remained consistent over increasing patient exposure and experience. No
evidence of cumulative toxicity was seen over multiple cycles of
ELZONRISTM.
Myelosuppression (thrombocytopenia, anemia, neutropenia) was
modest, reversible, and was not dose-limiting for any patient. The most
common treatment-related adverse events included increased alanine
aminotransferase levels, increased aspartate aminotransferase levels
and hypoalbuminemia, mostly restricted to the first cycle of therapy.
The most serious side effect was capillary leak syndrome; most reports
were Grade II in severity.\184\
---------------------------------------------------------------------------
\184\ Ibid.
---------------------------------------------------------------------------
Lastly, the applicant asserts that ELZONRISTM is more
efficient than other chemotherapeutic drugs at killing BPDCN in
preclinical studies, suggesting clinical benefit would also be
exhibited if head-to-head comparison to cytotoxic agents commonly used
for the treatment of hematologic malignancies was pursued. The
applicant submitted a 2015 preclinical study that found malignant cells
from patients who had been diagnosed with BPDCN were more sensitive to
ELZONRISTM than to a wide variety of cytotoxic agents
commonly used for treatment of hematologic malignancies, including
drugs such as cytosine arabinoside, cyclophosphamide, vincristine,
dexamethasone, methotrexate, Erwinia L-asparaginase, and
asparaginase.\185\
---------------------------------------------------------------------------
\185\ Angelot-Delettre, F., Roggy, A., Frankel, A.E., Lamarthee,
B., Seilles, E., Biichle, S., et al., ``In vivo and in vitro
sensitivity of blastic plasmacytoid dendritic cell neoplasm to SL-
401, an interleukin-3 receptor targeted biologic agent,''
Haematologica, 2015, vol. 100(2), pp. 223-30.
---------------------------------------------------------------------------
[[Page 19322]]
After reviewing the information submitted by the applicant as part
of its FY 2020 new technology add-on payment application for
ELZONRISTM, we are concerned that some of the evidence
submitted by the applicant to demonstrate substantial clinical
improvement over existing technologies is based on preclinical studies.
We also are unsure if the study populations in the 2013 retrospective
study that the applicant used to compare remission rates are composed
of treatment-na[iuml]ve, previously-treated, or a mix of patients.
In addition, the applicant reported that the interim results of the
Phase II trial of treatment of BPDCN with ELZONRIS TM
demonstrated high response rates in BPDCN, including: 90 percent
overall response in treatment na[iuml]ve patients (26/29) and 69
percent overall response in relapse/refractory patients (9/13); 72
percent complete response plus complete clinical response in treatment
na[iuml]ve patients (21/29) and 38 percent complete response plus
complete clinical response in relapse/refractory patients (5/13); and
45 percent of patients treated in first-line setting were bridged to
stem cell transplant in remission (13/29).\186\ However, we are
concerned that the small number of patients in the study and the lack
of baseline data against which to compare this technology may make it
more difficult to determine whether these interim results support a
finding of substantial clinical improvement. We also note that because
the clinical trial is ongoing and the final outcomes are not available,
we are concerned that there may not be enough information on the
efficacy to determine substantial clinical improvement at this time. We
also note that the applicant's December 2018 New Technology Town Hall
meeting presentation includes information that differs slightly from
the application materials, and we are not clear whether the study
results submitted with the application reflect the most current
information available. We are inviting public comments on whether
ELZONRIS TM meets the substantial clinical improvement
criterion, including with respect to the concerns we have raised.
---------------------------------------------------------------------------
\186\ Pemmaraju, N., et al., ``Results of Pivotal Phase 2 Trial
of SL-401 in Patients with Blastic Plasmacytoid Dendritic Cell
Neoplasm (BPDCN),'' Proceedings from the 2018 European Hematology
Association Congress, 2018, Abstract 214438.
---------------------------------------------------------------------------
We did not receive any written comments in response to the New
Technology Town Hall meeting notice published in the Federal Register
regarding the substantial clinical improvement criterion for ELZONRIS
TM or at the New Technology Town Hall meeting.
h. Erdafitinib
Johnson & Johnson Health Care Systems, Inc. (on behalf of Janssen
Oncology, Inc.) submitted an application for new technology add-on
payments for Erdafitinib for FY 2020. The proposed indication for the
use of Erdafitinib is the second-line treatment of adult patients who
have been diagnosed with locally advanced or metastatic urothelial
carcinoma whose tumors exhibit certain fibroblast growth factor
receptor (FGFR) genetic alterations as detected by an FDA-approved
test, and who have disease progression during or following at least one
line of prior chemotherapy including within 12 months of neoadjuvant or
adjuvant chemotherapy.
According to the applicant, Erdafitinib is an oral pan-fibroblast
growth factor receptor (FGFR) tyrosine kinase inhibitor being evaluated
in Phase II and III clinical trials in patients who have been diagnosed
with advanced urothelial cancer. FGFRs are a family of receptor
tyrosine kinases, which may be upregulated in various tumor cell types
and may be involved in tumor cell differentiation and proliferation,
tumor angiogenesis, and tumor cell survival. Erdafitinib is a pan-
fibroblast FGFR inhibitor with potential antineoplastic activity. Upon
oral administration, Erdafitinib binds to and inhibits FGFR, which may
result in the inhibition of FGFR-related signal transduction pathways
and, therefore, the inhibition of tumor cell proliferation and tumor
cell death in FGFR-overexpressing tumor cells.
The applicant indicated that urothelial cancer (also known as
transitional cell cancer or bladder cancer) is the sixth most common
type of cancer diagnosed in the U.S. In 2018, an estimated 81,190 new
cases of bladder cancer were expected to be diagnosed (approximately
62,380 in men and 18,810 in women), and result in 17,240 deaths
(approximately 1 out of 5 diagnosed men and 1 out of 4 diagnosed
women).\187\ According to the applicant, for patients with metastatic
disease, outcomes can be dire due to the often rapid progression of the
tumor and the lack of efficacious treatments, especially in cases of
relapsed or refractory disease. The applicant further stated that the
relative 5-year survival rate for patients with metastatic disease is 5
percent.
---------------------------------------------------------------------------
\187\ American Cancer Society, ``Key Statistics for Bladder
Cancer,'' www.cancer.org/cancer/bladder-cancer/about/key-statistics.html.
---------------------------------------------------------------------------
According to the applicant, in regard to current second-line
treatment, patients who have been diagnosed with locally advanced or
metastatic urothelial cancer have limited options and favor anti-
programmed death ligand 1/anti-programmed death 1 (anti-PD-L1/anti-PD-
1) therapies (also known as checkpoint inhibitors) as opposed to
conventional cytotoxic chemotherapy. With objective response rates
ranging from approximately 20 to 25 percent with currently approved
therapies and treatments, the applicant stated that new effective
treatment options are needed for this patient population. Although
there are five FDA-approved immune checkpoint inhibitors, the applicant
stated that studies have shown that not all patients benefit from PD-1
blockade. The applicant explained that patients harboring FGFR
alternates, which occurs at a frequency of approximately 20 percent,
are thought to have immunologically ``cold tumors'' that are less
likely to benefit from PD-1 blockade therapy.
The applicant noted that Erdafitinib was granted Breakthrough
Therapy designation by the FDA on March 15, 2018, for the treatment of
patients who have been diagnosed and treated for urothelial cancer
whose tumors have certain FGFR genetic alterations. Erdafitinib has not
received FDA premarket approval as of the time of the development of
this proposed rule. Although there are no currently approved ICD-10-PCS
procedure codes to uniquely identify the use of Erdafitnib, facilities
can report the oral administration of Erdafitinib with the use of the
following ICD-10-PCS code: 3E0DX05 (Introduction of Other
Antineoplastic into Mouth and Pharynx, External Approach). We note that
the applicant has submitted a request for approval at the March 2019
ICD-10 Coordination and Maintenance Committee Meeting for a unique ICD-
10-PCS procedure code to specifically identify cases involving the
administration of Erdafitinib. According to the applicant, this request
was discussed at the September 11, 2018 ICD-10 Coordination and
Maintenance Committee meeting, and at that meeting CMS recommended the
establishment of a New Technology Section ``X'' code to distinctly
identify cases involving the administration of Erdafitinib.
As discussed above, if a technology meets all three of the
substantial similarity criteria, it would be considered substantially
similar to an existing technology and would not be
[[Page 19323]]
considered ``new'' for purposes of new technology add-on payments.
With regard to the first criterion, whether a product uses the same
or a similar mechanism of action to achieve a therapeutic outcome, the
applicant asserted that Erdafitinib is not substantially similar to any
existing treatment options because its inhibitory mechanism of action
is novel. Specifically, the applicant stated that Erdafitinib is a pan-
fibroblast FGFR inhibitor with potential antineoplastic activity. Upon
oral administration, Erdafitinib binds to and inhibits FGFR, which may
result in the inhibition of FGFR-related signal transduction pathways
and, therefore, the inhibition of tumor cell proliferation and tumor
cell death in FGFR-overexpressing tumor cells. The applicant stated
that Erdafitinib is a potent pan-FGFR (1-4) tyrosine kinase inhibitor
with IC50 (drug concentration at which 50 percent of target enzyme
activity is inhibited) in the single-digit nanomolar range. According
to the applicant, Erdafitinib will, therefore, represent a first-in-
class FGFR inhibitor because of its novel mechanism of action.
With respect to the second criterion, whether a product is assigned
to the same or a different MS-DRG, the applicant stated that potential
cases representing patients who may be eligible for treatment involving
Erdafitinib are likely to be assigned to a wide variety of MS-DRGs
because patients who may receive treatment involving Erdafitinib in the
inpatient setting would likely be hospitalized due to other conditions
than urothelial cancer. The applicant stated that potential cases
representing patients who may be eligible for treatment involving the
use of Erdafitinib may be assigned to the same MS-DRGs as cases
representing patients treated with currently available treatment
options for urothelial cancer.
With respect to the third criterion, whether the new use of the
technology involves the treatment of the same or similar type of
disease and the same or similar patient population, the applicant
asserted that the treatment involving Erdafitnib is specific to a
select subset of patients who have been diagnosed with locally advanced
or metastatic urothelial carcinoma and previously treated, but
subsequently present with FGFR alterations. According to the applicant,
while patients who have been diagnosed with metastatic or unresectable
urothelial cancer may be offered second-line therapy options of a
checkpoint inhibitor or systemic chemotherapy, treatment involving
Erdafitinib is specific to a subset of patients with certain FGFR-
genetic alterations. Therefore, the applicant believes that Erdafitinib
treats a different patient population than currently available
treatments.
We are inviting public comments on whether Erdafitinib is
substantially similar to any existing technology and whether it meets
the newness criterion.
With regard to the cost criterion, the applicant conducted the
following analysis. The applicant searched the FY 2017 MedPAR Hospital
Limited Data Set (LDS) for inpatient hospital claims for potential
cases representing patients who may be eligible for treatment using
Erdafitinib. The applicant noted that because the inpatient admission
for the potential cases identified would likely be unrelated to the
proposed indication for the use of Erdafitinib, it is unlikely that the
administration of Erdafitinib would be initiated during an inpatient
hospitalization. In addition, the applicant assumed that most hospitals
would not utilize Erdafitinib for short-stay inpatient hospitalization,
and the applicant therefore eliminated all identified potential cases
representing inpatient hospitalizations of 3 days or fewer from its
analysis. The applicant also assumed that any inpatient hospitalization
of 4 days or longer would involve the daily administration of
Erdafitinib and calculated the drug's costs on a case-by-case basis,
multiplying the length-of-stay times the cost of the drug.
The applicant used a combination of ICD-10-CM diagnosis codes to
identify these potential cases. The applicant first identified claims
with one of the following ICD-10-CM diagnosis codes listed in the table
below.
------------------------------------------------------------------------
ICD-10-CM diagnosis code Code description
------------------------------------------------------------------------
C67.8..................... Malignant neoplasm of overlapping sites of
bladder.
C67.9..................... Malignant neoplasm of bladder, unspecified.
C68.8..................... Malignant neoplasm of overlapping sites of
urinary organs.
C68.9..................... Malignant neoplasm of urinary organ,
unspecified.
------------------------------------------------------------------------
The applicant then searched the MedPAR data file for inpatient
hospital claims that also had one of the following ICD-10-CM diagnosis
codes listed in the table below to identify a combination of applicable
codes.
------------------------------------------------------------------------
ICD-10-CM diagnosis code Code description
------------------------------------------------------------------------
C77.2..................... Secondary and unspecified malignant neoplasm
of intra-abdominal lymphnodes.
C77.4..................... Secondary and unspecified malignant neoplasm
of inguinal and lower limb lymph nodes.
C77.5..................... Secondary and unspecified malignant neoplasm
of intrapelvic lymph nodes.
C77.8..................... Secondary and unspecified malignant neoplasm
of lymph nodes of multiple regions.
C77.9..................... Secondary and unspecified malignant neoplasm
of lymph node, unspecified.
C78.00.................... Secondary malignant neoplasm of unspecified
lung.
C78.7..................... Secondary malignant neoplasm of unspecified
lung.
C79.00.................... Secondary malignant neoplasm of unspecified
kidney and renal pelvis.
C79.19.................... Secondary malignant neoplasm of other
urinary organs.
C79.51.................... Secondary malignant neoplasm of bone.
C79.82.................... Secondary malignant neoplasm of genital
organs.
------------------------------------------------------------------------
Based on this search, the applicant identified 2,844 cases mapping
to a wide range of MS-DRGs. The applicant identified and used in its
analysis those MS-DRGs to which more than 1 percent of the total
identified cases were assigned, as listed in the table below.
[[Page 19324]]
------------------------------------------------------------------------
MS-DRG MS-DRG title
------------------------------------------------------------------------
871....................... Septicemia or Severe Sepsis without MV >96
Hours with MCC.
654....................... Major Bladder Procedures with CC.
687....................... Kidney & Urinary Tract Neoplasms with CC.
686....................... Kidney & Urinary Tract Neoplasms with MCC.
872....................... Septicemia or Severe Sepsis without MV >96
Hours without MCC.
683....................... Renal Failure with CC.
698....................... Other Kidney & Urinary Tract Diagnoses with
MCC.
669....................... Transurethral Procedures with CC.
690....................... Kidney & Urinary Tract Infections without
MCC.
682....................... Renal Failure with MCC.
699....................... Other Kidney & Urinary Tract Diagnoses with
CC.
653....................... Major Bladder Procedures with MCC.
853....................... Infectious & Parasitic Diseases with O.R.
Procedure with MCC.
543....................... Pathological Fractures & Musculoskeletory &
Connective Tissue Malignancy with CC.
948....................... Signs & Symptoms without MCC.
668....................... Transurethral Procedures with MCC.
542....................... Pathological Fractures & Musculoskeletory &
Connective Tissue Malignacy with MCC.
657....................... Kidney & Ureter Procedures For Neoplasm with
CC.
641....................... Miscellaneous Disorders of Nutrition,
Metabolism, Fluids/Electrolytes without
MCC.
180....................... Respiratory Neoplasms with MCC.
291....................... Heart Failure & Shock with MCC or Peripheral
Extracorporeal Membrane Oxygenation (ECMO).
------------------------------------------------------------------------
Using 100 percent of the cases assigned to these MS-DRGs, the
applicant determined an average case-weighted unstandardized charge per
case of $86,302. The applicant did not remove any charges for prior
therapies because the applicant indicated that the use of Erdafitinib
would not replace any other therapies. The applicant standardized the
charges for each case and inflated each case's charges by applying the
FY 2019 IPPS/LTCH PPS final rule outlier charge inflation factor of
1.08864 (83 FR 41722). (We note that the 2-year charge inflation factor
was revised in the FY 2019 IPPS/LTCH PPS final rule correction notice.
The revised factor is 1.08986 (83 FR 49844). However, we note that even
when using either the revised final rule values or the corrected final
rule values published in the correction notice to inflate the charges,
the final inflated average case-weighted standardized charge per case
for Erdafitinib would exceed the average case-weighted threshold
amount.) The applicant then added the charges for the cost of
Erdafitinib. To determine the charges for the cost of Erdafitinib, the
applicant used the inverse of the FY 2019 IPPS/LTCH PPS final rule
pharmacy national average CCR of 0.191. The applicant's reported
average case-weighted threshold amount was $62,435 and its reported
final inflated average case-weighted standardized charge per case was
$111,713. Based on this analysis, the applicant believes Erdafitinib
meets the cost criterion because the final inflated average case-
weighted standardized charge per case exceeds the average case-weighted
threshold amount. We are inviting public comments on whether
Erdafitinib meets the cost criterion.
The applicant asserts that Erdafitinib represents a substantial
clinical improvement over existing technologies because it offers a
treatment option for a patient population unresponsive to or ineligible
for currently available treatments. The applicant stated that
Erdafitinib provides a substantial clinical improvement for a select
group of patients who have been diagnosed with locally advanced or
metastatic urothelial carcinoma who have failed first-line treatment
and have limited second-line treatment options, despite the recent
introduction of checkpoint inhibitors. The applicant further stated
that the use of Erdafitinib will be the first available treatment
option specific for the subset of patients who have certain fibroblast
growth factor receptor (FGFR) genetic alterations that are detected by
an FDA-approved test. The applicant also believes that Erdafitinib
represents a significant clinical improvement because the technology
reduces mortality, decreases pain, and reduces recovery time.
To support its assertions of substantial clinical improvement, the
applicant submitted the results of a Phase I dose-escalation study for
the use of Erdafitinib in the target patient population for which the
applicant asserts Erdafitinib would be the first available treatment
option and represents a substantial clinical improvement, which is
patients who had been diagnosed with advanced solid tumors for which
standard curative treatment appeared no longer effective. With a sample
size of 65 patients, patients received escalating oral doses of
Erdafitinib ranging from 0.5 mg to 12 mg, administered continuously
daily, or oral doses of Erdafitinib of 10 mg or 12 mg administered on a
7-days-on/7-days-off intermittent schedule. The study intended to
identify the Recommended Phase II Dose (RP2D) and investigate the
safety and pharmacodynamics of the drug. The applicant stated that the
initial RP2D was considered 9 mg continuous daily dosing and 10 mg for
intermitted dosing on the basis of improved tolerability.
The applicant also provided data from a multi-center, open-label
Phase II study of 99 patients, ages 36 years old to 87 years old, with
the median age being 68 years old, who had been diagnosed with
metastatic or unresectable urothelial carcinoma that had specific FGFR
alterations and were treated with a starting daily dose of Erdafitinib
of 8 mg. The applicant noted the study included 87 patients who
progressed after at least or more than 1 line of prior chemotherapy or
within 12 months of (neo) adjuvant chemotherapy. According to the
applicant, the objective response rate (ORR) measured by Response
Evaluation Criteria in Solid Tumors (RECIST) version 1.1 criteria was
40.4 percent (95 percent confidence interval [CI], 30.7 percent to 50.1
percent; 3.0 percent complete responses and 37.4 percent partial
responses). The disease control rate (complete responses, partial
responses, and stable disease) was 79.8 percent. The ORRs were similar
in chemotherapy-na[iuml]ve patients versus patients who progressed/
relapsed after chemotherapy (41.7 percent versus 40.2 percent) and in
patients who had visceral metastases versus those who did not (38.5
percent versus 47.6 percent). The median time to response was 1.4
months, and the median duration of response was 5.6
[[Page 19325]]
months (95 percent CI, 4.2 months to 7.2 months). The applicant noted
that the results demonstrated a median progression-free survival of 5.5
months (95 percent CI, 4.2 months to 6.0 months) and a median overall
survival of 13.8 months (95 percent CI, 9.8 months-not estimable). In
an exploratory analysis of 22 patients previously treated with
immunotherapy, the ORR was 59 percent; response to prior immunotherapy
(per investigator) in these patients was 5 percent.188 189
---------------------------------------------------------------------------
\188\ Nishina, T., Takahashi, S., Iwasawa, R., et al., ``Safety,
pharmacokinetic, and pharmacodynamics of erdafitinib, a pan-
fibroblast growth factor receptor (FGFR) tyrosine kinase inhibitor,
in patients with advanced or refractory solid tumors,'' Invest New
Drugs, 2018, vol. 36, pp. 424-434.
\189\ Tabernero, J., Bahleda, R., Dienstmann, R., et al.,
``Phase I Dose-Escalation Study of JNJ-42756493, an Oral Pan-
Fibroblast Growth Factor Receptor Inhibitor, in Patients With
Advanced Solid Tumors,'' J Clin Onc, Vol. 33(30), October 20, 2015,
pp. 3001-3008.
---------------------------------------------------------------------------
The applicant also referenced an ongoing Phase III study, but
indicated that the data was not available at the time of the
application's submission.
We have the following concerns with regard to whether the
technology meets the substantial clinical improvement criterion. First,
the applicant did not provide substantial data comparing Erdafitinib to
existing therapies. Additionally, the studies that were provided were
based on small sample sizes, open-labeled, and presented without a
complete comparison to existing therapies. Due to the limited nature of
available data, we have concerns that we may not have enough
information to determine if Erdafitinib represents a substantial
clinical improvement over existing technologies.
We are inviting public comments on whether Erdafitinib meets the
substantial clinical improvement criterion.
We did not receive any written public comments in response to the
New Technology Town Hall meeting notice published in the Federal
Register regarding the substantial clinical improvement criterion for
Erdafitinib or at the New Technology Town Hall meeting.
i. ERLEADATM (Apalutamide)
Johnson & Johnson Health Care Systems Inc., on behalf of Janssen
Products, LP, Inc., submitted an application for new technology add-on
payments for ERLEADATM (apalutamide) for FY 2020.
ERLEADATM received FDA approval on February 14, 2018. This
oral drug is an androgen receptor inhibitor indicated for the treatment
of patients who have been diagnosed with non-metastatic castration-
resistant prostate cancer (nmCRPC).
Prostate cancer is the second leading cause of cancer death in
men.\190\ Androgens, a type of hormone that includes testosterone, can
promote tumor growth. Androgen-deprivation therapy (ADT) is initially
an effective way to treat prostate cancer. However, almost all men with
prostate cancer eventually develop castration-resistant disease, or
cancer that continues to grow despite treatment with hormone therapy or
surgical castration.\191\ Non-metastatic castration-resistant prostate
cancer (nmCRPC) is a clinical state in which cancer has not spread to
other parts of the body, but continues to grow despite treatment with
ADT, either medical or surgical, that lowers testosterone levels.
Delaying metastases, or extending metastasis-free survival (MFS), may
delay symptomatic progression, morbidity, mortality, and healthcare
resource utilization. According to the applicant, nearly all men who
die from prostate cancer have antecedent metastases to bone or other
sites. ERLEADATM blocks the effect of androgens on the tumor
in order to delay metastases, a major cause of complications and death
among men with prostate cancer. Prior to ERLEADATM, there
were no FDA-approved treatments for nmCRPC to delay the onset of
metastatic castration-resistant prostate cancer (mCRPC).\192\ The U.S.
incidence of nmCRPC is estimated to be 50,000 to 60,000 cases per
year.\193\
---------------------------------------------------------------------------
\190\ American Cancer Society. https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/cancer-facts-figures-2019.html.
\191\ Dai, C., Heemers, H., Sharifi, N., ``Androgen signaling in
prostate cancer,'' Cold Spring Harb Perspect Med, 2017, vol. 7(9),
pp. a030452.
\192\ Center for Drug Evaluation and Research. NDA/BLA Multi-
Disciplinary Review and Evaluation (Summary Review, Office Director,
Cross Discipline Team Leader Review, Clinical Review, Non-Clinical
Review, Statistical Review and Clinical Pharmacology Review) NDA
210951--ERLEADA (apalutamide)--Reference ID: 4221387. Available at:
https://www.accessdata.fda.gov/drugsatfda_docs/nda/2018/210951Orig1s000MultidisciplineR.pdf. Published March 19, 2018.
\193\ Beaver, Julia A., Kluetz, Paul, Pazdur, Richard,
``Metastasis-free Survival--A New End Point in Prostate Cancer
Trials,'' 2018, N Eng J of Med, vol. 378, pp. 2458-2460, 10.1056/
NEJMp1805966.
---------------------------------------------------------------------------
With respect to the newness criterion, ERLEADATM
(apalutamide) was granted Fast Track and Priority Review designations
under FDA's expedited programs, and received FDA approval on February
14, 2018 for the treatment of patients who have been diagnosed with
non-metastatic castration-resistant prostate cancer. Currently, there
are no ICD-10-PCS procedure codes to uniquely identify the
administration of ERLEADATM. We note that the applicant
submitted a request for approval for a unique ICD-10-PCS code for the
administration of ERLEADATM beginning in FY 2020.
As discussed above, if a technology meets all three of the
substantial similarity criteria, it would be considered substantially
similar to an existing technology and would not be considered ``new''
for purposes of new technology add-on payments.
With regard to the first criterion, whether a product uses the same
or a similar mechanism of action to achieve a therapeutic outcome, the
applicant maintained that ERLEADATM is new because it was
the first drug approved by the FDA with its mechanism of action.
Specifically, ERLEADATM is an androgen receptor (AR)
inhibitor that binds directly to the ligand-binding domain of the AR.
It has a trifold mechanism of action. Apalutamide inhibits AR nuclear
translocation, inhibits DNA binding, and impedes AR-mediated
transcription, which together inhibit tumor cell growth.\194\ According
to the applicant, in non-clinical studies, apalutamide administration
caused decreased tumor cell proliferation and increased apoptosis
leading to decreased tumor volume in mouse xenograft models of prostate
cancer. Furthermore, the applicant asserted that in additional non-
clinical studies, apalutamide was shown to have a higher binding
affinity to the androgen receptor than bicalutamide (CASODEX), a first-
generation anti-androgen that has been used in clinical practice for
the treatment of nmCRPC. However, the applicant noted that bicalutamide
is not FDA-approved for this indication nor is there Phase III data
available on its use in this population. In addition, according to the
applicant, apalutamide has a different mechanism of action than
bicalutamide because it does not show antagonist-to-antagonist switch
like bicalutamide.
---------------------------------------------------------------------------
\194\ Clegg, N.J., Wongvipat, J., Joseph, J.D., et al., ``ARN-
509: a novel antiandrogen for prostate cancer treatment,'' Cancer
Res, 2012, vol. 72(6), pp. 1494-503.
---------------------------------------------------------------------------
With regard to the second criterion, whether a product is assigned
to the same or different MS-DRG, the applicant noted that patients who
may be eligible to receive treatment involving ERLEADATM in
the inpatient setting will likely be hospitalized due to other
conditions. Therefore, the applicant explained that potential cases
eligible to receive treatment involving ERLEADATM are likely
to be assigned to a wide variety of MS-DRGs, and
[[Page 19326]]
ERLEADATM is similar to existing technologies in this
respect.
With regard to the third criterion, whether the new use of the
technology involves the treatment of the same or similar type of
disease and the same or similar patient population, the applicant
maintained that ERLEADATM was the first FDA-approved
treatment option for patients who have been diagnosed with nmCRPC.
According to the applicant, there are a number of therapies currently
available for patients who have been diagnosed with mCRPC, including
chemotherapy, continuous ADT, immunotherapy, radiation therapy,
radiopharmaceutical therapy, and androgen pathway treatments, including
secondary hormonal therapies and supportive care. However, prior to
ERLEADATM, there were no FDA-approved treatment options for
patients who have been diagnosed with nmCRPC to delay the onset of
mCRPC. Therefore, according to the applicant, ERLEADATM
provides a treatment option to patients who have been diagnosed with a
stage of prostate cancer that previously had no other approved
treatment options available, and the standard approach was ``watch and
wait/observation.'' The applicant stated that both the National
Comprehensive Cancer Network[supreg] (NCCN[supreg]) guidelines for
prostate cancer and American Urological Association (AUA) guidelines
for castration-resistant prostate cancer note the limited treatment
options for nmCRPC as compared to mCRPC. The applicant pointed out that
apalutamide is highly recommended, as one of the two treatments with a
Category 1 recommendation included in the NCCN[supreg] guidelines and
standard treatment options for asymptomatic nmCRPC based on evidence
level Grade A in the AUA guidelines.195 196 Therefore, the
applicant posited that ERLEADATM involves the treatment of a
new patient population because it is a new treatment option for
patients who have been diagnosed with nmCRPC and have limited available
treatment options.
---------------------------------------------------------------------------
\195\ NCCN Clinical Practice Guidelines in Oncology (NCCN
Guidelines[supreg]): Prostate Cancer (Version 4.2018). National
Comprehensive Cancer Network. Available at: www.nccn.org. Published
August 15, 2018.
\196\ Lowrance, W.T., Murad, M.H., Oh, W.K., et al.,
``Castration-Resistant Prostate Cancer: AUA Guideline Amendment
2018,'' J Urol, 2018, pii: S0022-5347(18)43671-3.
---------------------------------------------------------------------------
As summarized above, the applicant maintained that
ERLEADATM meets the newness criterion and is not
substantially similar to existing technologies because it has a unique
mechanism of action and offers an effective treatment option to a new
patient population with limited available treatment options. We are
inviting public comments on whether ERLEADATM meets the
newness criterion.
With regard to the cost criterion, the applicant conducted the
following analysis to demonstrate that the technology meets the cost
criterion. In order to identify the range of MS-DRGs to which cases
representing potential patients who may be eligible for treatment using
ERLEADATM may map, the applicant identified cases that would
be eligible for use of ERLEADATM by the presence of two ICD-
10-CM diagnosis code combinations: C61 (Malignant neoplasm of prostate)
in combination with R97.21 (Rising PSA following treatment for
malignant neoplasm of prostate); or C61 in combination with Z19.2
(Hormone resistant malignancy status). The applicant searched the FY
2017 MedPAR final rule file (claims from FY 2015) for claims with the
presence of the two code combinations above. Cases identified mapped to
a wide variety of MS-DRGs. The applicant eliminated all hospital stays
of fewer than 4 days from its analysis because of its assumption that
most hospitals would not provide ERLEADATM for short-stay
inpatients. The applicant also assumed that any hospital stay 4 days or
longer would involve the daily provision of ERLEADATM. This
resulted in 493 cases across 152 MS-DRGs, with approximately 33 percent
of all cases mapping to the following 9 MS-DRGs: MS-DRG 871 (Septicemia
or Severe Sepsis without MV >96 Hours with MCC); MS-DRG 543
(Pathological Fractures and Musculoskeletal and Connective Tissue
Malignancy with CC); MS-DRG 683 (Renal Failure with CC); MS-DRG 723
(Malignancy, Male Reproductive System with CC); MS-DRG 722 (Malignancy,
Male Reproductive System with MCC); MS-DRG 698 (Other Kidney and
Urinary Tract Diagnoses with MCC); MS-DRG 699 (Other Kidney and Urinary
Tract Diagnoses with CC); MS-DRG 682 (Renal Failure with MCC); and MS-
DRG 948 (Signs and Symptoms without MCC).
For the 493 identified cases, the average case-weighted
unstandardized charge per case was $66,559. The applicant then
standardized the charges using the FY 2017 IPPS/LTCH PPS final rule
Impact file. Because ERLEADATM would not replace any other
therapies occurring during the inpatient stay, the applicant did not
remove any charges for the current treatment. The applicant then
applied the 2-year inflation factor of 8.59 percent (1.085868)
published in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41718) to
inflate the charges from FY 2017 to FY 2019. We note that the inflation
factors were revised in the FY 2019 IPPS/LTCH PPS final rule correction
notice. The corrected final 2-year inflation factor is 1.08986 (83 FR
49844). The applicant converted the costs of ERLEADATM to
charges using the inverse of the FY 2019 IPPS/LTCH PPS final rule
pharmacy national average CCR of 0.191 (83 FR 41273) to include the
charges in its estimate. Based on the FY 2019 IPPS/LTCH PPS final rule
correction notice data file thresholds, the average case-weighted
threshold amount was $52,362. The average case-weighted standardized
charge per case was $76,901. Because the average case-weighted
standardized charge per case exceeds the average case-weighted
threshold amount, the applicant maintained that the technology meets
the cost criterion.
The applicant submitted an additional cost analysis including
hospital stays shorter than 4 days to demonstrate that
ERLEADATM also meets the cost criterion using all discharges
in the analysis, regardless of length of stay. While the applicant
maintained that ERLEADATM is unlikely to be administered by
the hospital for inpatient stays fewer than 4 days, the applicant
demonstrated that the average case-weighted standardized charge per
case ($57,150) continues to exceed the average case-weighted threshold
amount ($50,225) using all discharges (932 cases).
We note that the applicant used the proposed rule values to inflate
the standardized charges above. However, we further note that even when
using either the final rule values or the corrected final rule values
to inflate the charges, the average case-weighted standardized charge
per case exceeded the average case-weighted threshold amount in each
analysis. We are inviting public comments on whether
ERLEADATM meets the cost criterion.
With respect to the substantial clinical improvement criterion, the
applicant asserted that ERLEADATM represents a substantial
clinical improvement because: (1) The technology offers a treatment
option for a patient population previously ineligible for treatments,
because ERLEADATM is the first FDA-approved treatment for
patients who have been diagnosed with nmCRPC; and (2) use of the
technology significantly improves clinical outcomes for a patient
population because ERLEADATM was shown to significantly
improve a number of clinical outcomes in the
[[Page 19327]]
randomized Phase III SPARTAN trial,\197\ including significant
improvement in metastasis-free survival (MFS).
---------------------------------------------------------------------------
\197\ Smith, M.R., et al., ``Apalutamide Treatment and
Metastasis-free Survival in Prostate Cancer,'' N Engl J Med, 2018,
vol. 12;378(15), pp. 1408-1418.
---------------------------------------------------------------------------
First, the applicant stated that there were no FDA-approved
treatments to delay metastasis for patients who have been diagnosed
with nmCRPC, a small but important clinical state within the spectrum
of prostate cancer, prior to the FDA approval of ERLEADATM.
The applicant emphasized that until the FDA approved the use of
ERLEADATM, Medicare patients who have been diagnosed with
nmCRPC had extremely limited treatment options, and the standard
approach was ``watch and wait/observation.'' The applicant asserted
that ERLEADATM offers a promising new treatment option and
has been shown to improve MFS in a Phase III trial \198\ with a
demonstrated safety and tolerability profile and no negative impact to
health-related quality of life based on patient-reported outcomes.
Therefore, the applicant stated that the ``robust results'' of the
clinical trial demonstrate that ERLEADATM is a substantial
clinical improvement over existing technologies because it provides an
effective treatment option for a patient population previously
ineligible for treatments.
---------------------------------------------------------------------------
\198\ Ibid.
---------------------------------------------------------------------------
Second, the applicant maintained that ERLEADATM is a
substantial clinical improvement because ERLEADATM was shown
to significantly improve a number of clinical outcomes, most notably
MFS. Metastases are a major cause of complications and death among men
with prostate cancer. Therefore, according to the applicant, delaying
metastases may delay symptomatic progression, morbidity, mortality, and
healthcare resource utilization. ERLEADATM was approved by
the FDA based on a prostate cancer trial using the primary endpoint of
MFS, with overall survival used as a secondary endpoint.
The SPARTAN trial was a randomized, double-blind, placebo-
controlled, Phase III trial which included men who had been diagnosed
with nmCRPC and a prostate-specific antigen doubling time of 10 months
or less. Patients were randomly assigned, in a 2:1 ratio, to receive
apalutamide (240 mg per day) or placebo. A total of 1,207 men underwent
randomization (806 to the apalutamide group and 401 to the placebo
group). All of the patients continued to receive androgen-deprivation
therapy. The primary end point of MFS was defined as the time from
randomization to the first detection of distant metastasis on imaging
or death. The study team calculated that a sample of 1,200 patients
with 372 primary end-point events would provide the trial with 90
percent power to detect a hazard ratio for metastasis or death in the
apalutamide group versus the placebo group of 0.70, at a two-sided
significance level of 0.05. The Kaplan-Meier method was used to
estimate medians for each trial group. The primary statistical method
of comparison for time-to-event end points was a log-rank test with
stratification according to the pre-specified factors. Cox
proportional-hazards models were used to estimate the hazard ratios and
95 percent confidence intervals.
According to the applicant, results of the primary endpoint
analysis for MFS were both statistically significant and clinically
meaningful. Median MFS was 40.5 months in the apalutamide group as
compared with 16.2 months in the placebo group (hazard ratio [HR]=0.28;
95 percent confidence interval [CI]: 0.23, 0.35; PTM significantly prolonged MFS by 2 years in
men who had been diagnosed with nmCRPC. In a multi-variate analysis,
treatment with ERLEADATM was an independent predictor for
longer MFS (HR: 0.26; 95 percent CI: 0.21-0.32; PTM on MFS was consistently
favorable across pre-specified subgroups, including patients with
Prostate Specific Antigen doubling time (PSADT) of less than 6 months
versus more than 6 months (short PSA doubling time is a predictor of
metastasis), use of bone-sparing agents, and local-regional disease.
Additionally, the applicant stated that the validity of the primary
endpoint results is supported by improvements in all secondary
endpoints, with significant improvement observed in time to metastasis,
progression-free survival (PFS), and time to symptomatic progression
(all PTM compared to placebo.
According to the applicant, treatment with ERLEADATM
significantly extended time to metastasis by almost 2 years (40.5
months versus 16.6 months, PTM group compared to the
placebo group.
According to the applicant, ERLEADATM was also
associated with a significant improvement in the secondary endpoint of
PFS, at 40.5 months for the ERLEADATM group versus 14.7
months for the placebo group (PTM was an independent predictor for longer time to
symptomatic progression (reached versus not reached; PTM as compared to placebo. The
applicant explained that, according to a statistical analysis model
correlating the proportion of variability of OS attributable to the
variability of MFS, patients who developed metastases at 6, 9, and 12
months had significantly shorter median OS compared with those patients
without metastasis.
The applicant also stated that treatment using ERLEADATM
provides an effective option with a demonstrated safety profile and
tolerability for patients who have been diagnosed with nmCRPC. The
safety of the use of ERLEADATM was assessed in the SPARTAN
trial, and adverse events (AEs) that occurred at >=15 percent in either
group included: Fatigue, hypertension, rash, diarrhea, nausea, weight
loss, arthralgia, and falls. The applicant asserted that in considering
the risks and benefits of treatment involving the use of
ERLEADATM for patients who have been diagnosed with nmCRPC,
the FDA noted that there were no FDA-approved treatments for the
indication and that ERLEADATM had a favorable risk-benefit
profile.
Next, the applicant stated that the use of ERLEADATM
also has a substantial clinical improvement benefit of maintaining
quality of life. According to the applicant, patients who have been
diagnosed with nmCRPC are generally asymptomatic, so it is a positive
outcome if the addition of a therapy does not cause degradation of
health-related quality of life. The applicant maintained that in
asymptomatic men who have been diagnosed with high-risk nmCRPC, health-
related quality of life (HRQOL) was maintained after
[[Page 19328]]
initiation of the use of ERLEADATM.\199\ According to the
applicant, patient-reported outcomes using the Functional Assessment of
Cancer Therapy-Prostate [FACT-P] questionnaire and European Quality of
Life-5 Dimensions-3 Levels [EQ-5D-3L] questionnaire results indicated
that patients who received treatment involving ERLEADATM
maintained stable overall HRQOL outcomes over time from both treatment
groups.
---------------------------------------------------------------------------
\199\ Saad, F., et al., ``Effect of apalutamide on health-
related quality of life in patients with non-metastatic castration-
resistant prostate cancer: an analysis of the SPARTAN randomized,
placebo- controlled, phase 3 trial,'' Lancet Oncology, 2018 Oct;
Epub 2018 Sep 10.
---------------------------------------------------------------------------
Additionally, the applicant discussed prostate specific antigen
(PSA) outcomes as another secondary result demonstrating substantial
clinical improvement. PSA, a protein produced by the prostate gland, is
often present at elevated levels in men who have been diagnosed with
prostate cancer and PSA tests are used to monitor the progression of
the disease. According to the applicant, at 12 weeks after
randomization, the median PSA level had decreased by 89.7 percent in
the ERLEADATM group versus an increase of 40.2 percent in
the placebo group. In an exploratory analysis performed by the
applicant of patients treated in the SPARTAN study, the use of
ERLEADATM decreased the risk of PSA progression by 94
percent compared with the patients in the placebo group (not reached vs
3.71 months; HR: 0.064; 95 percent CI: 0.052-0.080; P=90 percent maximum decline in PSA from baseline at any time during
the study was reported in 66 percent of the patients in the
ERLEADATM group and 1 percent of the patients in the placebo
group, according to the applicant. The applicant noted that increase in
time to PSA progression is relevant from a clinical standpoint for
clinicians and patients alike because PSA monitoring, rather than the
use of regularly scheduled surveillance imaging, as was the case with
SPARTAN, is often the most practical method of screening for
progression of nmCRPC.
We have the following concerns regarding the applicant's assertions
of substantial clinical improvement:
Regarding the SPARTAN trial design, we are concerned that
the study enrollment may not be representative of the U.S. population
considering that North American enrollment was only 35 percent of
patients overall, and only approximately 6 percent of enrolled patients
were black. Underrepresentation of black patients is of particular
concern considering that, in the United States, African-American
patients are disproportionately affected by prostate cancer. According
to the CDC,\200\ the rate of new prostate cancers by race is 158.3 per
100,000 men for African-Americans, compared to 90.2 for whites, 78.8
for Hispanics, 51.0 for Asian/Pacific Islanders, and 49.6 for American
Indians/Alaska Natives. We are concerned that, based on an exploratory
subgroup analysis performed by the applicant, black patients may not
have performed better in the treatment group; while the hazard ratio of
0.63 (95 percent confidence interval: 0.23, 1.72) suggests a benefit to
the group treated with ERLEADATM, the median MFS for this
subgroup was reported as shorter for the ERLEADATM group at
25.8 months than for the placebo group, at 36.8 months.\201\
Additionally, we note that 23 percent of the patients in the SPARTAN
trial did not have definitive local therapy at baseline for their
diagnosis of prostate cancer, which is accepted standard-of-care in the
United States.
---------------------------------------------------------------------------
\200\ U.S. Department of Health and Human Services, Centers for
Disease Control and Prevention and National Cancer Institute, U.S.
Cancer Statistics Working Group, U.S. Cancer Statistics Data
Visualizations Tool, based on November 2017 submission data (1999-
2015), Availavle at: www.cdc.gov/cancer/dataviz, June 2018.
\201\ Smith, M.R., et al., ``Apalutamide Treatment and
Metastasis-free Survival in Prostate Cancer,'' N Engl J Med, 2018,
vol. 12;378(15), pp. 1408-1418.
---------------------------------------------------------------------------
In response to this concern about low North American enrollment and
subgroup underrepresentation, the applicant submitted additional
information claiming a consistent treatment effect across all
subpopulations and regions. The applicant also pointed to the low
hazard ratio for the subgroup of black patients as support for the
benefit of the use of ERLEADATM. We welcome additional
information and public comments on whether the SPARTAN trial results
are generalizable to the U.S. population, and in particular, African-
American patients.
We also note regarding the SPARTAN trial that a total of
7.0 percent of the patients in the ERLEADATM group and 10.6
percent of the patients in the placebo group withdrew consent from the
trial. Additional explanation from the applicant of how those that
withdrew were considered in the analysis, and whether there was any
analysis of potential impact of withdrawals on the study results would
be helpful.
We also have concerns about the primary endpoint used for
the SPARTAN trial, MFS. The applicant explained that MFS was determined
to be a reasonable end point for patients who have been diagnosed with
nmCRPC because of the difficulty in using OS as a primary endpoint;
multiple drugs can be used sequentially for advanced disease,
necessitating larger and longer trials and potentially confounding
interpretation of results if attempting to prove that a prostate cancer
drug lengthens OS. Nevertheless, because MFS is not identical to OS and
data on OS was not mature at the time of the study's results, we note
that it may be difficult to conclude based on the current data whether
the use of ERLEADATM improves OS.
To address this concern, the applicant submitted additional
information on MFS as a surrogate clinical endpoint for OS, including a
recent study by the International Clinical Endpoints for Cancer of the
Prostate (ICECaP) Working Group showing a correlation between MFS and
OS in several prostate cancer studies.\202\ The applicant explained
that based on review of 19 randomized, controlled trials evaluating 21
study units in 12,712 men with localized prostate cancer, the
correlation between OS and MFS was 0.91 (95 percent CI: 0.91-0.91) at
the patient level, as measured by Kendall's [tau]. To demonstrate that
MFS is closely linked with OS, the applicant cited a retrospective
analysis of electronic health record database for patients who have
been diagnosed with nmCRPC in which MFS independently predicted
mortality risk; patients developing metastasis within 1 year had 4.4-
fold greater risk for mortality (95 percent CI: 2.2-8.8) than those who
remained metastasis-free at year 3.\203\ The applicant also reiterated
that a significant positive correlation between MFS and OS was observed
in the SPARTAN trial (Pearson's correlation coefficient=0.66;
Spearman's correlation coefficient=0.62, PTM
meets the substantial clinical improvement criterion for patients who
have been
[[Page 19329]]
diagnosed with nmCRPC. We did not receive any written comments in
response to the New Technology Town Hall meeting notice published in
the Federal Register regarding the substantial clinical improvement
criterion for ERLEADATM or at the New Technology Town Hall
meeting.
j. SPRAVATO (Esketamine)
Johnson & Johnson Health Care Systems, Inc., on behalf of Janssen
Pharmaceuticals, Inc., submitted an application for new technology add-
on payments for SPRAVATO (Esketamine) nasal spray for FY 2020. The FDA
indication for SPRAVATO is treatment-resistant depression (TRD).
According to the applicant, major depressive disorder affects
nearly 300 million people of all ages globally and is the leading cause
of disability worldwide. People with major depressive disorder (MDD)
suffer from a serious, biologically-based disease which has a
significant negative impact on all aspects of life, including quality
of life and function.\204\ Although currently available anti-
depressants are effective for many of these patients, approximately
one-third do not respond to treatment.\205\ Patients who have not
responded to at least two different anti-depressant treatments of
adequate dose and duration for their current depressive episode are
considered to have been diagnosed with TRD. MDD in older age is marked
by lower response and remission rates, greater disability and
functional decline, decreased quality of life, and greater mortality
from suicide.206 207 208
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\204\ World Health Organization. (2018, March). Depression.
Available at: http://www.who.int/mediacentre/factsheets/fs369/en/.
\205\ National Institute of Mental Health. (2006, January).
Questions and Answers about the NIMH Sequenced Treatment
Alternatives to Relieve Depression (STAR*D)--Background. Available
at: https://www.nimh.nih.gov/funding/clinical-research/practical/stard/backgroundstudy.shtml.
\206\ Manthorpe, J., & Iliffe, S., ``Suicide in later life:
Public health and practitioner perspectives,'' International Journal
of Geriatric Psychiatry, 2010, vol. 25(12), pp. 1230-1238.
\207\ Lenze, E., Sheffrin, M., Driscoll, H., Mulsant, B.,
Pollock, B., Dew, M., Reynolds, C., ``Incomplete response in late-
life depression: Getting to remission,'' Dialogues in Clinical
Neuroscience, 2008, vol. 10(4), pp. 419-430.
\208\ Alexopoulos, G., & Kelly, R., ``Research advances in
geriatric depression,'' World Psychiatry, 2009, vol. 8(3), pp. 140-
149.
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According to the applicant, currently available pharmacologic
treatments for depression include Selective Serotonin Reuptake
Inhibitors (SSRIs), Serotonin-norepinephrine reuptake inhibitors
(SNRIs), monoamine oxidase inhibitors (MAOIs), tricyclic anti-
depressants (TCAs), other atypical anti-depressants, and adjunctive
atypical antipsychotics. In addition to SPRAVATO, the only
pharmacologic treatment currently approved for treatment-resistant
depression is a combination of two drugs: An antipsychotic and an SSRI
(fluoxetine/olanzapine combination). Currently available non-
pharmacological medical treatments include electroconvulsive therapy,
vagal nerve stimulation, deep brain stimulation (DBS), transcranial
direct current stimulation (tDCS), and repetitive transcranial magnetic
stimulation (rTMS).
According to the applicant, SPRAVATO is a non-competitive, subtype
non-selective, activity-dependent glutamate receptor modulator. The
applicant indicates that SPRAVATO works through increased glutamate
release resulting in downstream neurotrophic signaling facilitating
synaptic plasticity, thereby bringing about rapid and sustained
improvement in people who have been diagnosed with TRD. The applicant
explained that, through glutamate receptor modulation, SPRAVATO helps
to restore connections between brain cells in people who have been
diagnosed with TRD.\209\
---------------------------------------------------------------------------
\209\ Sanacora, G., et. al., ``Targeting the Glutamatergic
System to Develop Novel, Improved Therapeutics for Mood Disorders,''
Nat Rev Drug Discov., 2008, pp. 426-437.
---------------------------------------------------------------------------
According to the applicant, the nasal spray device is a single-use
device that delivers a total of 28 mg of SPRAVATO in two sprays (one
spray per nostril). The applicant has approved dosages of 56 mg (two
devices) or 84 mg (three devices), with a 28 mg (one device) available
for patients 65 years old and older. The treatment session consists of
healthcare supervision of the patient's self-administration of SPRAVATO
HCL to ensure proper usage and post-administration observation to
ensure patient stability. Specifically, clinicians will need to monitor
blood pressure and mental status changes. The applicant states that
monitoring will be required at every administration session.
With respect to the newness criterion, the applicant submitted a
New Drug Application (NDA) for SPRAVATO HCL Nasal Spray based on a
recently completed Phase III clinical development program for
treatment-resistant depression. According to the applicant, SPRAVATO
was granted a Breakthrough Therapy designation in 2013. SPRAVATO HCL
Nasal Spray was approved by the FDA with an effective date of March 5,
2019. Currently there are no ICD-10-PCS procedure codes to uniquely
identify the administration of SPRAVATO HCL Nasal Spray. The applicant
has submitted a request for approval for a unique ICD-10-PCS procedure
code to specifically identify cases involving the administration of
SPRAVATO HCL, beginning in FY 2020.
As discussed above, if a technology meets all three of the
substantial similarity criteria, it would be considered substantially
similar to an existing technology and would not be considered ``new''
for purposes of new technology add-on payments.
With regard to the first criterion, whether a product uses the same
or similar mechanism of action, the applicant asserts that SPRAVATO has
a unique mechanism of action. The applicant stated that SPRAVATO's
unique mechanism of action is the first new approach in 30 years for
the treatment of major depressive disorder, including treatment-
resistant depression.210 211 According to the applicant,
unlike existing approved anti-depressant pharmacotherapies, SPRAVATO's
anti-depressant activity does not primarily modulate monoamine systems
(norepinephrine, serotonin, or dopamine). The applicant asserts that
SPRAVATO restores connections between brain cells in people with
treatment-resistant depression through glutamate receptor modulation,
which results in downstream neurotropic signaling.\212\
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\210\ Duman, R. (2018). Ketamine and rapid-acting anti-
depressants: a new era in the battle against depression and suicide.
F1000Research, 7, 659. doi:10.12688/f1000research.14344.1.
\211\ Dubovsky, S., ``What Is New about New Anti-depressants?,''
Psychotherapy and Psychosomatics, 2018, vol. 87(3), pp. 129-139,
doi:10.1159/000488945.
\212\ Sanacora, G., et al., ``Targeting the Glutamatergic System
to Develop Novel, Improved Therapeutics for Mood Disorders,'' Nat
Rev Drug Discov., 2008, pp. 426-437.
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With regard to the second criterion, whether the technology is
assigned to the same or different MS-DRG, the applicant asserts that it
is likely that potential cases representing patients who may be
eligible for treatment involving the use of SPRAVATO HCL Nasal Spray
would be assigned to the same MS-DRGs as patients who receive treatment
involving currently available anti-depressants (AD).
With regard to the third criterion, whether the technology treats
the same or a similar disease or the same or similar patient
population, the applicant asserts that potential patients who may be
eligible to receive treatment involving SPRAVATO will be comprised of a
subset of patients who are receiving treatment involving currently
available anti-depressants. The applicant did not specifically
[[Page 19330]]
address the application of this criterion to SPRAVATO.
We are inviting public comments on whether SPRAVATO is
substantially similar to any existing technologies and whether it meets
the newness criterion.
With regard to the cost criterion, the applicant conducted the
following analysis to demonstrate that the technology meets the cost
criterion. To identify cases eligible for SPRAVATO, the applicant
searched the FY 2017 MedPAR data file for claims with the presence of
one of the following ICD-10-CM diagnosis codes: F33 (Major depressive
disorder, recurrent), F33.2 (Major depressive disorder, recurrent
severe without psychotic features), F33.3 (Major depressive disorder,
recurrent, severe with psychotic symptoms), and F33.9 (Major depressive
disorder, recurrent, unspecified). Claims from the FY 2017 MedPAR data
file with the presence of one of these ICD-10-CM diagnosis codes mapped
to a wide variety of MS-DRGs. The applicant excluded claims if they had
one or more diagnoses from the following list: (1) Aneurysmal vascular
disease; (2) intracerebral hemorrhage; (3) dementia; (4)
hyperthyroidism; (5) pulmonary insufficiency; (6) uncontrolled brady-
or tachyarrhythmias; (7) history of brain injury; (8) hypertensive; (9)
encephalopathy; (10) other conditions associated with increased
intracranial pressure; and (10) pregnancy. The applicant believed that
these conditions would preclude the use of SPRAVATO HCL. The applicant
also assumed that hospitals would not allow administration of SPRAVATO
HCL for short-stay inpatient hospitalizations and, therefore, excluded
all hospitalizations of fewer than 5 days. The applicant assumed that
patients would be allowed to administer their first dose on the 5th day
and every 7 days thereafter. Lastly, the applicant assumed that, based
on clinical data, patients would use 2.5 spray devices per treatment,
once a week.
After applying the inclusion and exclusion criteria described
above, the applicant identified a total of 3,437 potential cases
mapping to 439 MS-DRGs, with approximately 54.7 percent of cases
mapping to MS-DRGs 885 (Psychoses), 871 (Septicemia or Severe Sepsis
without MV >96 Hours with MCC), 917 (Poisoning & Toxic Effects of Drugs
with MCC), 897 (Alcohol/Drug Abuse or Dependence without Rehabilitation
Therapy without MCC), 291 (Heart Failure & Shock with MCC or Peripheral
Extracorporeal Membrane Oxygenation (ECMO)), 918 (Poisoning & Toxic
Effects of Drugs without MCC), 190 (Chronic Obstructive Pulmonary
Disease with MCC), 853 (Infectious & Parasitic Diseases with O.R.
Procedure with MCC), 683 (Renal Failure with CC), and 682 (Renal
Failure with MCC). The applicant further defined the potential cases
representing patients who may be eligible for treatment involving the
use of SPRAVATO HCL in the cost criterion analysis by reducing the
number of cases in each MS-DRG by one-third due to clinical data
indicating that approximately one-third of patients who have been
diagnosed with MDD also have been diagnosed with TRD.213 214
---------------------------------------------------------------------------
\213\ National Institute of Mental Health. (2006, January).
Questions and Answers about the NIMH Sequenced Treatment
Alternatives to Relieve Depression (STAR*D)--Background. Available
at: https://www.nimh.nih.gov/funding/clinical-research/practical/stard/backgroundstudy.shtml.
\214\ Rush, A.J., Trivedi, M., Wisniewski, S., Nierenberg, A.,
Steward, J., Warden, D., Fava, M., ``Acute and Longer-term Outcomes
in Depressed Outpatients Requiring One or Several Treatment Steps: A
STAR*D report,'' American Journal of Psychiatry, 2006, vol, 163(11),
pp. 1905-1917.
---------------------------------------------------------------------------
The applicant calculated the average case-weighted unstandardized
charge per case to be $73,119. Because the use of SPRAVATO HCL is not
expected to replace prior treatments, the applicant did not remove any
charges for the prior technology. The applicant then standardized the
charges and applied a 2-year inflation factor of 1.08986 obtained from
the FY 2019 IPPS/LTCH PPS final rule correction notice (83 FR 49844).
The applicant then added charges for the new technology to the inflated
average case-weighted standardized charges per case. No other related
charges were added to the cases. The applicant calculated a final
inflated average case-weighted standardized charge per case of $74,738
and an average case-weighted threshold amount of $48,864. Because the
final inflated average case-weighted standardized charge per case
exceeded the average case-weighted threshold amount, the applicant
maintained that the technology met the cost criterion.
With regard to the analysis above, we are concerned whether it is
appropriate to reduce the number of cases to one-third of the total
potential cases identified. While the supporting statistical data
provided by the applicant suggest that one-third of patients who have
been diagnosed with MDD often also receive diagnoses of TRD, it is
unclear which cases representing patients should be removed. It is
possible that patients who have been diagnosed with MDD are covered by
all 439 MS-DRGs, but patients who have been diagnosed with TRD only
exist in a certain subset of these same MS-DRGs. Further, those
patients who have been diagnosed with TRD could account for the most
costly of patients who have been diagnosed with MDD. Ultimately,
without further evidence, we may not be able to verify that the
assumption that patients who have been diagnosed with TRD comprise one-
third of the identified cases representing patients who have been
diagnosed with MDD and are evenly distributed across all of the MS-DRG
identified cases is appropriate. We are inviting public comments on
this issue and whether the SPRAVATO HCL Nasal Spray meets the cost
criterion.
With respect to the substantial clinical improvement criterion, the
applicant asserted that SPRAVATO HCL Nasal Spray represents a
substantial clinical improvement over existing treatments because it
provides a treatment option for a patient population that failed
available treatments and who have shown inadequate response to at least
two anti-depressants in their current episode of MDD.\215\ According to
the applicant, in addition to SPRAVATO HCL, there is currently only one
other pharmacotherapy used for the treatment for diagnoses of TRD that
is approved by the FDA (Symbyax[supreg], a fluoxetine-olanzapine
combination), but its use is limited by tolerability concerns.\216\ In
support of its assertions of substantial clinical improvement, the
applicant provided several studies regarding SPRAVATO HCL.
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\215\ Rush, A.J., Trivedi, M., Wisniewski, S., Nierenberg, A.,
Steward, J., Warden, D., Fava, M., ``Acute and Longer-term Outcomes
in Depressed Outpatients Requiring One or Several Treatment Steps: A
STAR*D report,'' American Journal of Psychiatry, 2006, vol. 163(11),
pp. 1905-1917.
\216\ Cristancho, M., & Thase, M, ``Drug safety evaluation of
olanzapine/fluoxetine combination,'' Expert Opinion on Drug Safety,
2014, vol. 13(8), pp. 1133-1141.
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The first study is a Phase II, double-blind, doubly-randomized,
placebo-controlled, multi-center study in adults aged 20 years old to
64 years old.\217\ This study consisted of the following four phases:
The screening, double-blind treatment, the optional open-label
treatment, and post-treatment follow-up. During the treatment phase,
two periods of treatment occurred between the 1st and the 8th day and
the 8th and the 15th day. At the beginning of first treatment period,
participants were randomized 3:1:1:1 to an intranasal placebo, SPRAVATO
HCL 28 mg, 56 mg, or 84 mg twice weekly, respectively. During the
second treatment period,
[[Page 19331]]
patients who were initially randomized to treatment groups remained on
the treatment regimen until the 15th day. Patients initially assigned
to the placebo group and who had moderate to severe symptoms (as
measured by the 16-item quick inventory of depressive symptomatology-
self report total score) were re-randomized 1:1:1:1 to placebo,
SPRAVATO HCL 28 mg, 56 mg, or 84 mg twice weekly groups, respectively.
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\217\ Daly, E., Singh, J., Fedgchin, M., Cooper, K., Lim, P.,
Shelton, R., Drevets, W., ``Efficacy and Safety of Intranasal
Esketamine Adjunctive to Oral Anti-depressant Therapy in Treatment-
Resistant Depression,'' JAMA Psychiatry, 2018, vol. 75(2), pp. 139-
148.
---------------------------------------------------------------------------
Of the 126 patients screened, 67 were randomized at the beginning
of the first treatment period, with 33 patients receiving placebo, 11
patients receiving 28 mg of SPRAVATO HCL, 11 patients receiving 56 mg
of SPRAVATO HCL, and 12 patients receiving 84 mg of SPRAVATO HCL in
dosages. At the beginning of the second treatment period, those in the
treated group remained on the same treatment regimen, while the 33
placebo patients were re-randomized. Of the placebo group in the first
treatment period, 6 patients were added to the 4 who remained on
placebo, 8 patients received 28 mg of SPRAVATO HCL, 9 patients received
56 mg of SPRAVATO HCL, and 5 patients received 84 mg SPRAVATO HCL in
dosages. Of the 67 respondents randomized, 63 (94 percent) completed
the first treatment phase and 60 (90 percent) completed the first and
second treatment phases. During both treatment phases patients were
assessed at baseline, 2 hours, 24 hours, and at the study period
endpoints for the Montgomery-Asberg Depression Rating Scale (MADRS)
score, Clinical Global Impression of Severity scale score, adverse
events and other safety assessments including the Clinician
Administered Dissociative States Scale (CADSS). The primary efficacy
endpoint, change from baseline to endpoint in MADRS total score, was
analyzed using the analysis of covariance model including treatment and
country as factors and period baseline MADRS total score as a
covariate.\218\
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\218\ Daly, E., Singh, J., Fedgchin, M., Cooper, K., Lim, P.,
Shelton, R., Drevets, W., ``Efficacy and Safety of Intranasal
Esketamine Adjunctive to Oral Anti-depressant Therapy in Treatment-
Resistant Depression,'' JAMA Psychiatry, 2018, vol. 75(2), pp. 139-
148.
---------------------------------------------------------------------------
At the end of the first treatment period, the least square mean
change (standard error) for the placebo group was -4.9 (1.74). As
compared to the placebo, the least square mean difference from placebo
(standard error) for the SPRAVATO HCL treatment groups was -5.0 (2.99)
for 28 mg of SPRAVATO HCL in dosage, -7.6 (2.91) for 56 mg of SPRAVATO
HCL in dosage, and -10.5 (2.79) for 84 mg of SPRAVATO HCL in dosage;
these differences were statistically significant at or beyond p0.07). For the
measure of patient-rated severity of depressive illness, the SPRAVATO
HCL treatment group had a least square mean difference in PHQ-9 of -3.1
(p228 229 and for the elderly.230 231 The existence
of comorbidities increases the likelihood that the negative effects of
poly-pharmacy and drug-drug interactions could be experienced among the
Medicare population. Given that the provided studies utilized exclusion
criteria, which excluded those with serious comorbidities, we are
concerned that the limited results do not adequately represent the
average or even the majority of the Medicare population.
---------------------------------------------------------------------------
\228\ Thorpe, K., Jain, S., & Joski, P., ``Prevalence and
Spending Associated with Patients Who have a Behavioral Health
Disorder and Other Conditions,'' Health Affairs, 2017, vol. 36(1),
pp. 124-132, doi:10.1377/hlthaff.2016.0875.
\229\ Druss, B., & Walker, E., 2011, ``Mental Disorders and
Medical Comorbidity,'' Robert Wood Johnson Foundation, 2011.
Available at: http://www.policysynthesis.org.
\230\ Kim, J., & Parish, A., ``Polypharmcy and Medication
Management in Older Adults,'' Nurs Clin N Am, 2017, vol. 52, pp.
457-468, doi:http://dx.doi.org/10.1016/j.cnur.2017.04.007.
\231\ Kim, L., Koncilja, K., & Nielsen, C., ``Medication
Management in Older Adults,'' Cleveland Clinic Journal of Medicine,
2018, vol. 85(2), pp. 129-135, doi:10.3949/ccjm.85a.16109.
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Third, we have concerns regarding the primary and secondary
endpoints for several of these studies. It is unclear whether the
primary endpoint of these studies (change in baseline MADRS) is the
most appropriate endpoint to assess substantial clinical improvement,
particularly as it unclear what threshold degree of change was defined
as meeting the definition of change from baseline in the analyses, and
whether this degree of change translates to clinical improvement (for
example, response and remissions rates). In addition, we have concerns
regarding the potential for physician behavior to have introduced bias,
which could impact the study results. The studies state that anti-
depressants are physician assigned and not randomized. Some of the
provided studies control for the type of anti-depressant prescribed
(SSRI and SNRI). We believe there is the potential for an interaction
effect between the prescribed anti-depressant and SPRAVATO HCL. It is
possible that one particular anti-depressant (of the anti-depressants
used in the studies)/SPRAVATO HCL combination accounts for the entirety
of the differences seen between the treated groups and the control
groups. Without consistently controlling for the specific anti-
depressants prescribed in multivariate analyses, we may not be able to
parse this potentially complex relation apart.
Fourth, given that SPRAVATO HCL is comprised of the drug ketamine,
we are concerned with the potential for abuse. Ketamine is accepted as
a medication for which there is a strong possibility for
abuse.232 233 234 As one publication finds, current abuse of
intravenous ketamine occurs intranasally.\235\ While clinical trials
assess the short-term benefits of ketamine treatment, there exists a
paucity of long-term studies to assess whether chronic usage of this
product may increase the likelihood of abuse.\236\ In light of the
potential for addictive behavior, we are concerned that despite any
demonstrated short-term clinical benefits, there may be potential
negatives for the use of this drug in the longer term.
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\232\ Schak, K., Vande Voort, J., Johnson, E., Kung, S., Leung,
J., Rasmussen, K., Frye, M., ``Potential Risks of Poorly Monitored
Ketamine Use in Depression Treatment,'' American Journal of
Psychiatry, 2016, vol. 173(3), pp. 215-218. Available at: http://www.ajp.psychiatryonline.org.
\233\ Freedman, R., Brown, A., Cannon, T., Druss, B., Earls, F.,
Escobar, J., Xin, Y., ``Can a Framework be Established for the Safe
Use of Ketamine?,'' American Journal of Psychiatry, 2018, vol. 7,
pp. 587-589. Available at: http://www.ajp.psychiatryonline.org.
\234\ Sanacora, G., Frye, M., McDonald, W., Mathew, S., Turner,
M., Schatzberg, A., Nemeroff, C., ``A Consensus Statement on the Use
of Ketamine in the Treatment of Mood Disorders,'' JAMA Psychiatry,
2017, Special Communication, E1-E6. doi:10.1001/
jamapsychiatry.2017.0080.
\235\ Schak, K., Vande Voort, J., Johnson, E., Kung, S., Leung,
J., Rasmussen, K., Frye, M., ``Potential Risks of Poorly Monitored
Ketamine Use in Depression Treatment,'' American Journal of
Psychiatry, 2016, vol. 173(3), pp. 215-218. Available at: http://www.ajp.psychiatryonline.org.
\236\ Sanacora, G., Frye, M., McDonald, W., Mathew, S., Turner,
M., Schatzberg, A., Nemeroff, C., ``A Consensus Statement on the Use
of Ketamine in the Treatment of Mood Disorders,'' JAMA Psychiatry,
2017, Special Communication, E1-E6. doi:10.1001/
jamapsychiatry.2017.0080.
---------------------------------------------------------------------------
We are inviting public comments on whether SPRAVATO HCL meets the
substantial clinical improvement criterion. We did not receive any
written comments in response to the New Technology Town Hall meeting
notice published in the Federal Register regarding the substantial
clinical improvement criterion for SPRAVATO HCL or at the New
Technology Town Hall meeting.
k. XOSPATA
Astellas Pharma U.S., Inc. submitted an application for new
technology add-on payments for XOSPATA[supreg] (gilteritinib) for FY
2020. XOSPATA[supreg] received FDA approval November 28, 2018, and is
indicated for the treatment of adult patients who have been diagnosed
with relapsed or refractory acute myeloid leukemia (AML) with a
[[Page 19336]]
FMS-like tyrosine kinase 3 (FLT3) mutation as detected by an FDA-
approved test.
According to the applicant, XOSPATA[supreg] is an oral, small
molecule FMS-like tyrosine kinase 3 (FLT3). The applicant states that
XOSPATA[supreg] inhibits FLT3 receptor signaling and proliferation in
cells exogenously expressing FLT3, including FLT3 internal tandem
duplication (ITD), tyrosine kinase domain mutations (TKD) FLT3D835Y and
FLT3-ITD-D835Y and that it induces apoptosis in leukemic cells
expressing FLT3-ITD. FLT3 is a member of the class III receptor
tyrosine kinase family that is normally expressed on the surface of
hematopoietic progenitor cells, but it is over expressed in the
majority of AML cases.
The applicant states that AML is a type of cancer in which the bone
marrow makes abnormal myeloblasts (a type of white blood cell), red
blood cells, or platelets. According to the applicant, AML is a rare
and rapidly progressing form of cancer of the blood and bone marrow,
characterized by the proliferation of immature white blood cells known
as blast cells. The applicant states that while the specific cause of
AML is unknown, AML is generally characterized by aberrant
differentiation and increased proliferation of malignantly transformed
myeloid progenitor cells. It is considered a heterogeneous disease
state with various molecular and genetic abnormalities, which result in
variable clinical outcomes. When untreated or refractory to available
treatments, AML results in the accumulation of these transformed cells
within the bone marrow and suppression of the production of normal
blood cells (resulting in severe neutropenia and/or thrombocytopenia).
AML may be associated with infiltration of these cells into other
organs and tissues and can be rapidly fatal.
Almost 90 percent of leukemia cases are diagnosed in adults 20
years of age and older, among whom the most common types are chronic
lymphocytic leukemia and AML.\237\ AML accounts for approximately 80
percent of acute leukemias diagnosed in adults, with a median age at
diagnosis of 66 years old. It has been estimated that 19,520 people are
diagnosed annually with AML in the United States.\238\ In general, the
incidence of AML increases with advancing age; the prognosis is poorer
in older patients, and the tolerability of the currently available
standard-of-care treatment for patients who have been diagnosed with
AML is much poorer for older patients.\239\
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\237\ Atlanta: American Cancer Society; 2017 [cited October
2018]. Available from: https://www.cancer.org/content/dam/cancerorg/research/cancer-facts-and-statistics/cancer-treatment-and-survivorship-facts-and-figures/cancer-treatment-and-survivorshipfacts-and-figures-2016-2017.pdf.
\238\ Siegel, R.L., Miller, K.D., Jemal, A., ``Cancer
statistics, 2018,'' CA Cancer J Clin, 2018, vol. 68(1), pp. 7-30.
\239\ Tallman, M.S., ``New strategies for the treatment of acute
myeloid leukemia including antibodies and other novel agents,''
Hematology Am Soc Hematol Educ Program, 2005, pp. 143-50.
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According to the applicant, approximately 30 percent of adult
patients who have been diagnosed with AML are refractory, meaning
unresponsive, to induction therapy. Furthermore, of those who achieve
complete response (CR), approximately 75 percent will relapse. These
patients are then determined to have relapsed/refractory (R/R) AML.
According to the applicant, several chemotherapy regimens have been
used for the treatment of patients who have been diagnosed with
resistant or relapsed disease; however, the chemotherapy combinations
are universally dose-intensive and cannot always be easily administered
to older patients because of a high-risk of unacceptable toxicity. The
applicant indicated that, while these regimens may generate second
remission rates of up to 50 percent in patients with a first remission
of more than 1 year, toxicity is high in most patients who are frail or
over 60 years old.240 241 242 Additionally, the applicant
stated that if patients (including younger patients) relapse within 6
months of their initial CR, the chance of attaining a second remission
is less than 20 percent with chemotherapy alone.\243\ Furthermore, 5-
year survival after first relapse is approximately 10 percent,
demonstrating the lack of an effective cure for patients who have been
diagnosed with relapsed AML.\244\ Salvage therapy utilizing low-dose
chemotherapy provides a therapy that is more tolerable; however, the
low response rates (17 to 21 percent) makes the benefit of these agents
limited.245 246 Patients who are in second relapse or are
refractory to first salvage, meaning unresponsive to both the preferred
treatment, as well as the secondary choice of treatment, have an
extremely poor prognosis, with survival measured in weeks.\247\
Additionally, patients who have been diagnosed with R/R AML have poor
quality of life, higher hospitalization and total resource use burden,
and higher total healthcare costs.248 249 250 251
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\240\ Rowe, J.M., Tallman, M.S., ``How I treat acute myeloid
leukemia,'' Blood, 2010, vol. 116(17), pp. 3147-56.
\241\ Breems, D.A., Van Putten, W.L., Huijgens, P.C.,
Ossenkoppele, G.J., Verhoef, G.E., Verdonck, L.F., et al.,
``Prognostic index for adult patients with acute myeloid leukemia in
first relapse,'' J Clin Oncol, 2005, vol. 23(9), pp. 1969-78.
\242\ Karanes, C., Kopecky, K.J., Head, D.R., Grever, M.R.,
Hynes, H.E., Kraut, E.H., et al., ``A Phase III comparison of high
dose ARA-C (HIDAC) versus HIDAC plus mitoxantrone in the treatment
of first relapsed of refractory acute myeloid leukemia Southwest
Oncology Group Study,'' Leuk Res, 1999, vol. 23(9), pp. 787-94.
\243\ Forman, S.J., Rowe, J.M., ``The myth of the second
remission of acute leukemia in the adult,'' Blood, 2013, vol.
121(7), pp. 1077-82.
\244\ Rowe, J.M., Tallman, M.S., ``How I treat acute myeloid
leukemia,'' Blood, 2010, vol. 116(17), pp. 3147-56.
\245\ Itzykson, R., Thepot, S., Berthon, C., et al.,
``Azacitidine for the treatment of relapsed and refractory AML in
older patients,'' Leuk Res, 2015, vol. 39, pp. 124-130.
\246\ Khan, N., Hantel, A., Knoebel, R., et al., ``Efficacy of
single-agent decitabine in relapsed and refractory acute myeloid
leukemia,'' Leuk Lymphoma, 2017, vol. 58, pp. 1-7.
\247\ Giles, F., O'Brien, S., Cortes, J., Verstovsek, S., Bueso-
Ramos, C., Shan, J., et al., ``Outcome of patients with acute
myelogenous leukemia after second salvage therapy,'' Cancer, 2005,
vol. 104(3), pp. 547-54.
\248\ Goldstone, A.H., et al., ``Attempts to improve treatment
outcomes in acute myeloid leukemia (AML) in older patients: the
results of the United Kingdom Medical Research Council AML11
trial,'' Blood, 2001, vol. 98(5), pp. 1302-1311.
\249\ Pandya, B.J., et al., ``Quality of life of Acute Myeloid
Leukemia Patients in a Real-World Setting,'' JCO, 2017, vol. 35(15)
suppl., e18525.
\250\ Medeiros, B.C., et al., ``Economic Burden of Treatment
Episodes in Acute Myeloid Leukemia (AML) Patients in the US: A
Retrospective Analysis of a Commercial Payer Database,'' ASH, 2017
Poster.
\251\ Aly, A., et al., ``Economic Burden of Relapsed/Refractory
AML in the U.S.,'' ASH, 2017 Poster.
---------------------------------------------------------------------------
The applicant indicated that patients who have been diagnosed with
AML with FLT3 positive mutations are a well-established subpopulation
of AML patients, but there are no approved therapies for patients who
have been diagnosed with R/R AML with FLT3 mutations. Approximately 30
percent of patients newly diagnosed with AML have mutations in the FLT3
gene.252 253 FLT3 is a member of the class III receptor
tyrosine kinase family that is normally expressed on the surface of
hematopoietic progenitor cells. FLT3 and its ligand play an important
role in proliferation, survival, and differentiation of multipotent
stem cells. The applicant explained that FLT3 is overexpressed in the
majority of patients diagnosed with AML. In addition, activated FLT3
with internal tandem duplication (ITD) or tyrosine kinase domain (TKD)
mutations at around D835 in the activation loop are present in 20
percent to 25 percent and
[[Page 19337]]
5 percent to 10 percent of AML cases, respectively.\254\ These
activated mutations in FLT3 are oncogenic and show transforming
activity in cells.\255\
---------------------------------------------------------------------------
\252\ The Cancer Genome Atlas Research Network, ``Genomic and
Epigenomic Landscapes of Adult De Novo Acute Myeloid Leukemia,'' N
Engl J Med, 2013, vol. 368(22), pp. 2059-2074.
\253\ Leukemia and Lymphoma Society Facts 2016-2017. Available
at: https://www.lls.org/facts-and-statistics/facts-and-statistics-overview, [Last accessed March 7, 2018].
\254\ Kindler, T., Lipka, D.B., Fischer, T., ``FLT3 as a
therapeutic target in AML: still challenging after all these
years,'' Blood, 2010, vol. 116(24), pp. 5089-102.
\255\ Yamamoto, Y., Kiyoi, H., Nakano, Y., Suzuki, R., Kodera,
Y., Miyawaki, S., et al., ``Activating mutation of D835 within the
activation loop of FLT3 in human hematologic malignancies,'' Blood,.
2001, vol. 97, pp. 2434-9.En
---------------------------------------------------------------------------
Compared to patients with wild-type FLT3, AML patients with FLT3
mutation experience shorter remission duration at 2 years, according to
the applicant. Approximately 30 percent of FLT3-ITD patients relapse
versus approximately 16 percent of other AML patients.\256\
Additionally, these patients experience poorer survival outcomes. The
estimated median OS for patients who have been newly diagnosed with
FLT3 mutations is 15.2 to 15.5 months compared to 19.3 to 28.6 months
for patients with wild-type FLT3.\257\ Patients who have been diagnosed
with R/R FLT3 mutation positive AML have lower remission rates with
salvage chemotherapy, shorter durations of remission to second relapse
and decreased overall survival relative to FLT3 mutation negative
patients.258 259 260 According to the applicant, patients
who have been diagnosed with FLT3 mutation positive R/R AML have a
substantial unmet medical need for treatment.
---------------------------------------------------------------------------
\256\ Brunet, S., et al., ``Impact of FLT3 Internal Tandem
Duplication on the Outcome of Related and Unrelated Hematopoietic
Transplantation for Adult Acute Myeloid Leukemia in First Remission:
A Retrospective Analysis,'' J Clin Oncol, March 1, 2012, vol. 30(7),
pp. 735-41.
\257\ Sotak, M.L., et al., ``Burden of Illness of FLT3 Mutated
Acute Myeloid Leukemia (AML),'' Blood, 2011, vol. 118(21), pp. 4765
4765.
\258\ Konig, H., Levis, M., ``Targeting FLT3 to treat leukemia.
Expert Opin Ther Targets,'' 2015, vol. 19(1), pp. 37-54.
\259\ Chevallier, P., Labopin, M., Turlure, P., Prebet, T.,
Pigneux, A., Hunault, M., et al., ``A new Leukemia Prognostic
Scoring System for refractory/relapsed adult acute myelogeneous
leukaemia patients: a GOELAMS study,'' Leukemia, 2011, vol. 25(6),
pp. 939-44.
\260\ Levis, M., Ravandi, F., Wang, E.S., Baer, M.R., Perl, A.,
Coutre, S., et al., ``Results from a randomized trial of salvage
chemotherapy followed by lestaurtinib for patients with FLT3 mutant
AML in first relapse,'' Blood, 2011, vol. 117(12), pp. 3294-301.
---------------------------------------------------------------------------
The applicant asserts that currently there are no unique ICD-10-PCS
codes to describe the administration of XOSPATA[supreg]. We note that
the applicant has submitted a request to the ICD-10 Coordination and
Maintenance Committee for approval for a unique ICD-10-PCS code to
identify procedures involving the use of XOSPATA[supreg], beginning in
FY 2020.
As discussed earlier, if a technology meets all three of the
substantial similarity criteria, it would be considered substantially
similar to an existing technology and, therefore, would not be
considered ``new'' for purposes of new technology add-on payments.
With regard to the first criterion, whether a product uses the same
or a similar mechanism of action to achieve a therapeutic outcome, the
applicant asserted that XOSPATA[supreg] has a unique mechanism of
action and, therefore, should be considered new under this criterion.
The applicant stated that XOSPATA[supreg] is an oral, small molecule
FMS-like tyrosine kinase 3 (FLT3) inhibitor. According to the
applicant, XOSPATA[supreg] inhibits FLT3 receptor signaling and
proliferation in cells exogenously expressing FLT3, including FLT3
internal tandem duplication (ITD), tyrosine kinase domain mutations
(TKD) FLT3-D835Y and FLT3-ITD D835Y, and it induces apoptosis in
leukemic cells expressing FLT3-ITD. The applicant asserted that
XOSPATA[supreg] is the only FLT3-targeting agent approved by the FDA
for the treatment of relapsed or refractory FLT3mut+ AML.
With regard to the second criterion, whether a product is assigned
to the same or a different MS-DRG, the applicant asserted that cases
involving patients being medically treated for the type of AML
indicated for XOSPATA[supreg] would map to the following MS-DRGs: 834
(Acute Leukemia without Major O.R. Procedure with MCC), 835 (Acute
Leukemia without Major O.R. Procedure with CC), and 836 (Acute Leukemia
without Major O.R. Procedure without CC/MCC). Under current coding
conventions, it appears likely that cases involving treatment with the
use of XOSPATA[supreg] would map to the same MS-DRGs as existing
therapies.
With regard to the third criterion, whether the new use of the
technology involves the treatment of the same or similar type of
disease and the same or similar patient population when compared to an
existing technology, the applicant stated that XOSPATA[supreg] is FDA-
approved for the treatment of adult patients who have relapsed or
refractory AML with a FLT3 mutation. Cases representing potential
patients that may be eligible for treatment involving XOSPATA[supreg]
would be identified by ICD-10-CM diagnostic codes C92.02 (Acute
myeloblastic leukemia, in relapse) and C92.A2 (Acute myeloid leukemia
with multilineage dysplasia, in relapse). The applicant further
asserted that there are currently no other FLT3-targeting agents
approved for the treatment of patients who have been diagnosed with
relapsed or refractory FLT3mut+ AML. Therefore, the applicant asserted
that XOSPATA[supreg] is indicated to treat a new patient population for
which there are no other technologies currently available.
We are inviting public comments on whether XOSPATA[supreg] is
substantially similar to any existing technologies, and whether it
meets the newness criterion.
With regard to the cost criterion, the applicant conducted the
following analysis to demonstrate that the technology meets the cost
criterion.
The applicant searched the FY 2017 MedPAR data file for cases
reporting ICD-10-CM diagnosis codes C92.02 (Acute myeloblastic
leukemia, in relapse) and C92.A2 (Acute myeloid leukemia with
multilineage dysplasia, in relapse) listed as a primary or secondary
diagnosis that mapped to MS-DRGs 834, 835, and 836. The applicant
applied the following trims to the cases:
Excluded Health Maintenance Organization (HMO) and IME
Only claims;
Excluded cases for bone marrow transplant because
potential eligible patients who may receive treatment involving
XOSPATA[supreg] would not receive a bone marrow transplant during the
same admission as they received chemotherapy;
Excluded cases indicating an O.R. procedure;
Excluded cases treated at 8 providers that were not listed
in the FY 2019 IPPS/LTCH PPS final rule correction notice impact file
(these are predominately cancer hospitals).
After applying the trims above, 407 potential cases remained. The
applicant noted that it used only departmental charges that are used by
CMS for ratesetting.
Using the 407 cases, the applicant determined an average case-
weighted unstandardized charge per case of $166,389. The applicant then
removed all pharmacy charges because the applicant believed that
patients would typically receive other pharmaceuticals such as anti-
emetics during the hospital stay and patients receiving treatment
involving the use of XOSPATA[supreg] would continue to receive those
receive other pharmaceuticals. Additionally, according to the
applicant, blood charges were reduced because some patients receiving
treatment involving the use of XOSPATA[supreg] became infusion
independent in the clinical trial. The applicant standardized the
charges for each case and inflated each case's charges by applying the
proposed outlier charge inflation factor of 1.085868 (included in the
FY 2019
[[Page 19338]]
IPPS/LTCH PPS proposed rule (83 FR 20581)). The applicant calculated an
average case-weighted standardized charge per case of $157,034 using
the percent distribution of MS-DRGs as case-weights. Based on this
analysis, the applicant determined that the technology met the cost
criterion because the final inflated average case-weighted standardized
charge per case for XOSPATA[supreg] exceeded the average case-weighted
threshold amount of $88,479 by $68,555. As noted, the inflation factor
used by the applicant was the proposed 2-year inflation factor, which
was discussed in the FY 2019 IPPS/LTCH PPS final rule summation of the
calculation of the FY 2019 IPPS outlier charge inflation factor for the
proposed rule (83 FR 41718 through 41722). The final 2-year inflation
factor published in the FY 2019 IPPS/LTCH PPS final rule was 1.08864
(83 FR 41722), which was revised in the FY 2019 IPPS/LTCH PPS final
rule correction notice to 1.08986 (83 FR 49844).
We note that, although the applicant used the proposed rule value
to inflate the standardized charges, even when using the final rule
value or the corrected final rule value revised in the correction
notice to inflate the charges, the final inflated average case-weighted
standardized charge per case for XOSPATA[supreg] would exceed the
average case-weighted threshold amount. We are inviting public comments
on whether XOSPATA[supreg] meets the cost criterion.
With regard to substantial clinical improvement, the applicant
submitted one central study to support its assertion that
XOSPATA[supreg] represents a substantial clinical improvement over
existing technologies because it offers a treatment option for FLT3mut+
AML patients ineligible for currently available treatments. The
applicant also asserted that XOSPATA[supreg] represents a substantial
clinical improvement because the technology reduces mortality,
decreases the number of subsequent diagnostic or therapeutic
interventions, and reduces the number of future hospitalizations due to
adverse events as shown by its studies.\261\
---------------------------------------------------------------------------
\261\ Astellas, ``A Phase 3 Open-label, Multicenter, Randomized
Study of ASP2215 versus Salvage Chemotherapy in Patients with
Relapsed or Refractory Acute Myeloid Leukemia (AML) with FLT3
Mutation, Clinical Study Report,'' March 2018.
---------------------------------------------------------------------------
According to the applicant, the efficacy of XOSPATA[supreg] in the
treatment of patients who have been diagnosed with R/R AML has been
demonstrated in a U.S.-based, multi-national, active-controlled, Phase
III study (ADMIRAL, 2215-CL-0301). This study was designed to determine
the clinical benefit of the use of XOSPATA[supreg] in patients who have
been diagnosed with FMS-like tyrosine kinase (FLT3) mutated AML who are
refractory to, or have relapsed, after first-line AML therapy as shown
with overall survival (OS) compared to salvage chemotherapy, and to
determine the efficacy of the use of XOSPATA[supreg] as assessed by the
rate of complete remission and complete remission with partial
hematological recovery (CR/CRh) in these patients.\262\
---------------------------------------------------------------------------
\262\ Ibid.
---------------------------------------------------------------------------
In the ADMIRAL (2215-CL-0301) study, the applicant noted that
XOSPATA[supreg] demonstrated clinically meaningful CR and CRh rates, as
well as a clinically meaningful duration of CR/CRh in the patients
studied. The CR/CRh rate was 21.8 percent, with 31/142 patients
achieving a CR/CRh, 18/142 patients achieving CR (12.7 percent) and 13/
142 patients achieving a CRh (9.2 percent). Of the 31 patients (21.8
percent) who achieved CR/CRh, the median duration of remission was 4.5
months. For the 18 patients who achieved CR and the 13 patients who
achieved CRh, the median duration of response was 8.7 months and 2.9
months, respectively.\263\
---------------------------------------------------------------------------
\263\ Draft XOSPATA[supreg] (package insert) Northbrook, IL,
Astellas Pharma US, Inc., 2018.
---------------------------------------------------------------------------
The safety evaluation of XOSPATA[supreg] is based on 292 patients
who had been diagnosed with relapsed or refractory AML treated with 120
mg of XOSPATA[supreg] daily. The applicant noted that when looking at
the ADMIRAL study, the most common serious adverse events (SAEs) (Grade
III or above) were lab abnormalities of elevation of liver
transaminases in 43 (15 percent) of patients, fatigue in 14 (5 percent)
of patients, myalgia or arthralgia in 13 (5 percent) of patients, and
gastrointestinal disorders of diarrhea in 8 (3 percent) of patients and
nausea in 4 (1 percent) of patients. Due to the number and type of SAEs
reported, the applicant believed that XOSPATA[supreg] has the potential
to decrease the number of subsequent future hospitalizations or
physician visits as a result of management of adverse events, in
particular serious adverse events.
Transfusion dependence was also evaluated in the XOSPATA[supreg]-
treated patients. In some hematologic disorders, becoming transfusion
independent or receiving fewer transfusions over a specified interval
is defined as improvement or response depending on whether therapy is
given.\264\
---------------------------------------------------------------------------
\264\ Gale, R.P., Barosi, G., Barbui, T., Cervantes, F., Dohner,
K., Dupriez, B., et al., ``What are RBC-transfusion-dependence and -
independence?,'' Leuk. Res, 2011, vol. 35(1).
---------------------------------------------------------------------------
In the ADMIRAL study, at baseline prior to therapy initiation, 34
patients in the XOSPATA[supreg] arm were classified as transfusion
independent and 107 patients were classified as transfusion dependent.
Of these transfusion dependent patients, 34 (31.8 percent) patients
became transfusion independent during XOSPATA[supreg] treatment. Of the
34 patients who were transfusion independent at baseline, 18 (52.9
percent) patients maintained transfusion independence during
XOSPATA[supreg] treatment.
The applicant asserted that the use of XOSPATA[supreg] addresses a
medical need in a patient population that has been difficult to manage
in the past due to limited treatment options. In the ADMIRAL study, the
applicant provided data specific to reduced mortality rate compared to
historical data. Because of the small number of SAEs, the applicant
stated that it anticipates reduction of subsequent diagnostic and
therapeutic interventions, as well as decreased number of future
physician visits and hospitalization as noted previously. However, the
applicant did not provide direct numbers for the comparator arm of the
ADMIRAL study in its application. Because of this, we are concerned
that it may be difficult to determine XOSPATA[supreg]'s comparative
effectiveness. We note that, the ADMIRAL study was designed to evaluate
efficacy and head-to-head trials are lacking. Until the comparative
data for both randomized arms are available, we are concerned that
there may be insufficient evidence to determine that XOSPATA[supreg]
provides a substantial clinical improvement over existing technologies.
We are inviting public comments on whether XOSPATA[supreg] meets
the substantial clinical improvement criterion. We did not receive any
written public comments in response to the New Technology Town Hall
meeting notice published in the Federal Register regarding the
substantial clinical improvement criterion for XOSPATA[supreg] or at
the New Technology Town Hall meeting.
l. GammaTileTM
GT Medical Technologies, Inc. submitted an application for new
technology add-on payments for FY 2020 for the GammaTileTM.
We note that Isoray Medical, Inc. and GammaTile, LLC previously
submitted an application for new technology add-on payments for
GammaTileTM for FY
[[Page 19339]]
2018, which was withdrawn, and also for FY 2019, however the technology
did not receive FDA approval or clearance by July 1, 2018 and,
therefore, was not eligible for consideration for new technology add-on
payments. The GammaTileTM is a brachytherapy technology for
use in the treatment of patients who have been diagnosed with brain
tumors, which uses cesium-131 radioactive sources embedded in a
collagen matrix. GammaTileTM is designed to provide adjuvant
radiation therapy to eliminate remaining tumor cells in patients who
required surgical resection of brain tumors. According to the
applicant, the GammaTileTM technology is a new vehicle of
delivery for and inclusive of cesium-131 brachytherapy sources embedded
within the product. The applicant stated that the technology has been
manufactured for use in the setting of a craniotomy resection site
where there is a high chance of local recurrence of a CNS or dual-based
tumor. The applicant asserted that the use of the
GammaTileTM technology provides a new, unique modality for
treating patients who require radiation therapy to augment surgical
resection of malignancies of the brain. By offsetting the radiation
sources with a 3mm gap of a collagen matrix, the applicant asserted
that the use of the GammaTileTM technology resolves issues
with ``hot'' and ``cold'' spots associated with brachytherapy, improves
safety, and potentially offers a treatment option for patients with
limited, or no other, available options. The GammaTileTM is
biocompatible and bioabsorbable, and is left in the body permanently
without need for future surgical removal. The applicant asserted that
the commercial manufacturing of the product will significantly improve
on the process of constructing customized implants with greater speed,
efficiency, and accuracy than is currently available, and requires less
surgical expertise in placement of the radioactive sources, allowing a
greater number of surgeons to utilize brachytherapy techniques in a
wider variety of hospital settings.
The GammaTileTM technology received FDA clearance under
section 510(k) as a Class II medical device on July 6, 2018. The FDA
application included the indication for GammaTileTM to be
used to provide radiation therapy for patients who have been diagnosed
with recurrent intercranial neoplasms. The applicant submitted a
request for approval for a unique ICD-10-PCS code for the use of the
GammaTileTM technology, which was approved effective October
1, 2017 (FY 2018). The ICD-10-PCS procedure code used to identify
procedures involving the use of the GammaTileTM technology
is 00H004Z (Insertion of radioactive element, cesium-131 collagen
implant into brain, open approach).
As discussed earlier, if a technology meets all three of the
substantial similarity criteria, it would be considered substantially
similar to an existing technology and would not be considered ``new''
for purposes of new technology add-on payments.
With regard to the first criterion, whether a product uses the same
or a similar mechanism of action to achieve a therapeutic outcome, the
applicant stated that when compared to treatment using external beam
radiation therapy, GammaTileTM uses a new and unique
mechanism of action to achieve a therapeutic outcome. The applicant
explained that the GammaTileTM technology is fundamentally
different in structure, function, and safety from all external beam
radiation therapies, and delivers treatment through a different
mechanism of action. In contrast to external beam radiation modalities,
the applicant further explained that the GammaTileTM is a
form of internal radiation termed brachytherapy. According to the
applicant, brachytherapy treatments are performed using radiation
sources positioned very close to the area requiring radiation treatment
and deliver radiation to the tissues that are immediately adjacent to
the margin of the surgical resection. Conversely, external beam
radiation therapy travels inward and typically exposes radiation to a
large volume of normal brain tissue. As a result, the common clinical
practice to avoid radiation toxicity is to reduce dosage ranges,
limiting overall efficacy.
Due to the custom positioning of the radiological sources and the
use of the cesium-131 isotope, the applicant noted that the
GammaTileTM technology focuses therapeutic levels of
radiation on an extremely small area of the brain. Unlike all external
beam techniques, the applicant stated that this radiation does not pass
externally inward through the skull and healthy areas of the brain to
reach the targeted tissue and, therefore, may limit neurocognitive
deficits seen with the use of external beam techniques. Because of the
rapid reduction in radiation intensity that is characteristic of
cesium-131, the applicant asserted that the GammaTileTM
technology can target the margin of the excision with greater precision
than any alternative treatment option, while sparing healthy brain
tissue from unnecessary and potentially damaging radiation exposure.
The applicant also stated that, when compared to other types of
brain brachytherapy, GammaTileTM uses a new and unique
mechanism of action to achieve a therapeutic outcome. The applicant
explained that cancerous cells at the margins of a tumor resection
cavity can also be irradiated with the placement of brachytherapy
sources in the tumor cavity. However, the applicant asserted that the
GammaTileTM technology is a pioneering form of brachytherapy
for the treatment of brain tumors that uses the isotope cesium-131
embedded in a collagen implant that is customized to the geometry of
the brain cavity. According to the applicant, the use of cesium-131 and
the custom distribution of seeds offset in a three-dimensional collagen
matrix results in a unique and highly effective delivery of radiation
therapy to brain tissue. Specifically, the applicant asserted that the
offset radiation source permits only a prescribed radiation dose to
reach the target surface, reducing the potential for radiation induced
necrosis and the need for reoperation. Additionally, the applicant
stated that because the half-life of cesium-131 used in
GammaTileTM is shorter compared to other brachytherapy
isotopes, this results in a more rapid and effective energy deposition
than other isotopes with longer half-lives. Therefore, applicant
believes that GammaTileTM is unique due to the greater
relative biological effectiveness compared to other brachytherapy
options.
With regard to the second criterion, whether a product is assigned
to the same or a different MS-DRG, the GammaTileTM
technology is a treatment option for patients who have been diagnosed
with brain tumors that progress locally after initial treatment with
external beam radiation therapy, and cases involving this technology
are assigned to the same MS-DRG (MS-DRG 023 (Craniotomy with Major
Device Implant/Acute Complex CNS PDX with MCC or Chemotherapy Implant))
as other current treatment forms of brachytherapy and external beam
radiation therapy.
With regard to the third criterion, whether the new use of the
technology involves the treatment of the same or similar type of
disease and the same or similar patient population, the applicant
stated that the GammaTileTM technology offers a treatment
option for a patient population with limited, or no other, available
treatment options. The applicant explained that treatment options for
patients who have been
[[Page 19340]]
diagnosed with brain tumors that progress locally after initial
treatment with external beam radiation therapy are limited, and there
is no current standard-of-care in this setting. According to the
applicant, surgery alone for recurrent tumors may provide symptom
relief, but does not remove all of the cancerous cells. The applicant
further stated that repeating external beam radiation therapy for
adjuvant treatment is hampered by an increasing risk of brain injury
because additional external beam radiation therapy will increase the
total dose of radiation to brain tissue, as well as increase the total
volume of irradiated brain tissue. Secondary treatment with external
beam radiation therapy is often performed with a reduced and, therefore
less effective, dose. The applicant stated that the technique of
implanting cesium-131 seeds in a collagen matrix is currently only
available to patients in one location and requires a high degree of
expertise to implant. The manufacturing process of the
GammaTileTM will greatly expand the availability of
treatment beyond research programs at highly specialized cancer
treatment centers.
Based on the above, the applicant concluded that the
GammaTileTM technology is not substantially similar to other
existing technologies and meets the newness criterion.
However, we are concerned that the mechanism of action of the
GammaTileTM may be the same or similar to current forms or
radiation therapy or brachytherapy. Specifically, while the placement
of the cesium-131 source (or any radioactive source) in a collagen
matrix offset may constitute a new delivery vehicle, we are concerned
that this sort of improvement in brachytherapy for the use in the
salvage treatment of radiosensitive malignancies of the brain may not
represent a new mechanism of action. We also question whether the
technology treats a new patient population, as maintained by the
applicant, because of the availability of other implantable treatment
devices that treat the same patient population as the patients treated
by the GammaTileTM.
We are inviting public comments on whether the
GammaTileTM technology is substantially similar to any
existing technologies and whether it meets the newness criterion.
With regard to the cost criterion, the applicant conducted the
following analysis. The applicant worked with the Barrow Neurological
Institute at St. Joseph's Hospital and Medical Center (St. Joseph's) to
obtain actual claims from mid-2015 through mid-2016 for craniotomies
that did not involve placement of the GammaTileTM
technology. The cases were assigned to MS-DRGs 025 through 027
(Craniotomy and Endovascular Intracranial Procedures with MCC, with CC,
and without CC/MCC, respectively). For the 460 claims, the average
case-weighted unstandardized charge per case was $143,831. The
applicant standardized the charges for each case and inflated each
case's charges by applying the outlier charge inflation factor of
1.04205 included in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41718)
by the age of each case (that is, the factor was applied to 2015 claims
3 times and 2016 claims 2 times). The applicant then calculated an
estimate for ancillary charges associated with placement of the
GammaTileTM device, as well as standardized charges for the
GammaTileTM device itself. The applicant determined it meets
the cost criterion because the final inflated average case-weighted
standardized charge per case (including the charges associated with the
GammaTileTM device) of $253,876 exceeds the average case-
weighted threshold amount of $143,749 for MS-DRG 023, the MS-DRG that
would be assigned for cases involving the GammaTileTM
device.
The applicant also noted, in response to a concern expressed by CMS
in the FY 2018 IPPS/LTCH PPS proposed rule, that its analysis does not
include a reduction in costs due to reduced operating room times. The
applicant stated that, while the use the device will reduce operating
times relative to the freehand placement of seeds in other brain
brachytherapy procedures, none of the claims in the cost analysis
involve such freehand placement. We are inviting public comments on
whether the GammaTileTM technology meets the cost criterion.
With regard to substantial clinical improvement, the applicant
stated that the GammaTileTM technology offers a treatment
option for a patient population unresponsive to, or ineligible for,
currently available treatments for recurrent CNS malignancies and
significantly improves clinical outcomes when compared to currently
available treatment options. The applicant explained that therapeutic
options for patients who have been diagnosed with large or recurrent
brain metastases are limited (for example, stereotactic radiotherapy,
additional EBRT, or systemic immunochemotherapy). However, according to
the applicant, the GammaTileTM technology provides a
treatment option for patients who have been diagnosed with
radiosensitive recurrent brain tumors that are not eligible for
treatment with any other currently available treatment option.
Specifically, the applicant stated that the GammaTileTM
device may provide the only radiation treatment option for patients who
have been diagnosed with tumors located close to sensitive vital brain
sites (for example, brain stem) and patients who have been diagnosed
with recurrent brain tumors who may not be eligible for additional
treatment involving the use of external beam radiation therapy. There
is a lifetime limit for the amount of radiation therapy a specific area
of the body can receive. Patients whose previous treatment includes
external beam radiation therapy may be precluded from receiving high
doses of radiation associated with subsequent external beam radiation
therapy, and the GammaTileTM technology can also be used to
treat tumors that are too large for treatment with external beam
radiation therapy. Patients who have been diagnosed with these large
tumors are not eligible for treatment with external beam radiation
therapy because the radiation dose to healthy brain tissue would be too
high.
The applicant summarized how the GammaTileTM technology
improves clinical outcomes compared to existing treatment options,
including external beam radiation therapy and other forms of brain
brachytherapy as: (1) Providing a treatment option for patients with no
other available treatment options; (2) reducing the rate of mortality
compared to alternative treatment options; (3) reducing the rate of
radiation necrosis; (4) reducing the need for re-operation; (5)
reducing the need for additional hospital visits and procedures; and
(6) providing more rapid beneficial resolution of the disease process
treatment.
The applicant cited several sources of data to support these
assertions. The applicant referenced a paper by Brachman, Dardis et
al., which was published in the Journal of Neurosurgery on December 21,
2018.\265\ This study, a follow-up on the progress of 20 patients with
recurrent previously irradiated meningiomasis, is a feasibility or
superior progression-free survival study comparing the patient's own
historical control rate against subsequent treatment with
GammaTileTM.
---------------------------------------------------------------------------
\265\ Brachman, D., et al., ``Resection and permanent
intracranial brachytherpay using modular, biocompatible cesium-131
implants: Results in 20 recurrent previously irradiated
meningiomas,'' J Neurosurgery, December 21, 2018.
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An additional source of clinical data is from Gamma Tech's internal
review of data from two centers treating brain tumors with
GammaTileTM; the two
[[Page 19341]]
centers are the Barrow Neurological Institute (BNI) at St. Joseph's
Hospital and St. Joseph's Medical Center, Phoenix, AZ, and this
internal review is referred to herein as the ``BNI'' study.\266\ The
BNI study summarized Gamma Tech's experience with the
GammaTileTM technology. Another source of data that the
applicant cited to support its assertions regarding substantial
clinical improvement is an abstract by Pinnaduwage, D., et al. Also
submitted in the application were abstracts from 2014 through 2018 in
which updates from the progression-free survival study and the BNI
study were presented at specialty society clinical conferences. The
following summarizes the findings cited by the applicant to support its
assertions regarding substantial clinical improvement.
---------------------------------------------------------------------------
\266\ Brachman, D., et al., ``Surgery and Permanent
Intraoperative Brachytherapy Improves Time to Progress of Recurrent
Intracranial Neoplasms,'' Society for Neuro-Oncology Conference on
Meningioma, June 2016.
---------------------------------------------------------------------------
Regarding the assertion of local control, the 2018 article which
was published in the Journal of Neurosurgery found that, with a median
follow-up of 15.4 months (range 0.03-47.5 months), there were 2
reported cases of recurrence out of 20 meningiomas, with median
treatment site progression time after surgery and brachytherapy with
the GammaTileTM precursor and prototype devices not yet
being reached, compared to 18.3 months in prior instances. Median
overall survival after resection and brachytherapy was 26 months, with
9 patient deaths. In a presentation at the Society for Neuro-Oncology
in November 2014,\267\ the outcomes of 20 patients who were diagnosed
with 27 tumors covering a variety of histological types treated with
the GammaTileTM prototype were presented. The applicant
noted the following with regard to the patients: (1) All tumors were
intracranial, supratentorial masses and included low and high-grade
meningiomas, metastases from various primary cancers, high-grade
gliomas, and others; (2) all treated masses were recurrent following
treatment with surgery and/or radiation and the group averaged two
prior craniotomies and two prior courses of external beam radiation
treatment; and (3) following surgical excision, the prototype
GammaTileTM were placed in the resection cavity to deliver a
dose of 60 Gray to a depth of 5 mm of tissue; and (4) all patients had
previously experienced regrowth of their tumors at the site of
treatment and the local control rate of patients entering the study was
0 percent.
---------------------------------------------------------------------------
\267\ Dardis, C., ``Surgery and Permanent Intraoperative
Brachytherapy Improves Times to Progression of Recurrent
Intracranial Neoplasms,'' Society for Neuro-Oncology, November 2014.
---------------------------------------------------------------------------
With regard to outcomes, the applicant stated that, after their
initial treatment, patients had a median progression-free survival time
of 5.8 months; post treatment with the prototype
GammaTileTM, at the time of this analysis, only 1 patient
had progressed at the treatment site, for a local control rate of 96
percent; and median progression-free survival time, a measure of how
long a patient lives without recurrence of the treated tumor, had not
been reached (as this value can only be calculated when more than 50
percent of treated patients have failed the prescribed treatment).
The applicant also cited the findings from Brachman, et al. to
support local control of recurrent brain tumors. At the Society for
Neuro-Oncology Conference on Meningioma in June 2016,\268\ a second set
of outcomes on the prototype GammaTileTM was presented. This
study enrolled 16 patients with 20 recurrent Grade II or III
meningiomas, who had undergone prior surgical excision external beam
radiation therapy. These patients underwent surgical excision of the
tumor, followed by adjuvant radiation therapy with the prototype
GammaTileTM. The applicant noted the following outcomes: (1)
Of the 20 treated tumors, 19 showed no evidence of radiographic
progression at last follow-up, yielding a local control rate of 95
percent; 2 of the 20 patients exhibited radiation necrosis (1
symptomatic, 1 asymptomatic); and (2) the median time to failure from
the prior treatment with external beam radiation therapy was 10.3
months and after treatment with the prototype GammaTileTM
only 1 patient failed at 18.2 months. Therefore, the median treatment
site progression-free survival time after the prototype
GammaTileTM treatment had not yet been reached (average
follow-up of 16.7 months, range 1 to 37 months).
---------------------------------------------------------------------------
\268\ Brachman, D., et al, ``Surgery and Permanent
Intraoperative Brachytherapy Improves Time to Progress of Recurrent
Intracranial Neoplasms,'' Society for Neuro-Oncology Conference on
Meningioma, June 2016.
---------------------------------------------------------------------------
A third prospective study was accepted for presentation at the
November 2016 Society for Neuro-Oncology annual meeting.\269\ In this
study, 13 patients who were diagnosed with recurrent high-grade gliomas
(9 with glioblastoma and 4 with Grade III astrocytoma) were treated in
an identical manner to the cases described above. Previously, all
patients had failed the international standard treatment for high-grade
glioma, a combination of surgery, radiation therapy, and chemotherapy
referred to as the ``Stupp regimen.'' For the prior therapy, the median
time to failure was 9.2 months (range 1 to 40 months). After therapy
with a prototype GammaTileTM, the applicant noted the
following: (1) The median time to same site local failure had not been
reached and 1 failure was seen at 18 months (local control 92 percent);
and (2) with a median follow-up time of 8.1 months (range 1 to 23
months) 1 symptomatic patient (8 percent) and 2 asymptomatic patients
(15 percent) had radiation-related MRI changes. However, no patients
required re-operation for radiation necrosis or wound breakdown. Dr.
Youssef was accepted to present at the 2017 Society for Neuro-Oncology
annual meeting, where he provided an update of 58 tumors treated with
the GammaTileTM technology. At a median whole group follow-
up of 10.8 months, 12 patients (20 percent) had a local recurrence at
an average of 11.33 months after implant. Six and 18 month recurrence
free survival was 90 percent and 65 percent, respectively. Five
patients had complications, at a rate that was equal to or lower than
rates previously published for patients without access to the
GammaTileTM technology.
---------------------------------------------------------------------------
\269\ Youssef, E., ``C-131 Implants for Salvage Therapy of
Recurrent High Grade Gliomas,'' Society for Neuro-Oncology Annual
Meeting, November 2016.
---------------------------------------------------------------------------
In support of its assertion of a reduction in radiation necrosis,
the applicant also included discussion of a presentation by D.S.
Pinnaduwage, Ph.D., at the August 2017 annual meeting of the American
Association of Physicists in Medicine. Dr. Pinnaduwage compared the
brain radiation dose of the GammaTileTM technology with
other radioactive seed sources. Iodine-125 and palladium-103 were
substituted in place of the cesium-131 seeds. The study reported
findings that other radioactive sources reported higher rates of
radiation necrosis and that ``hot spots'' increased with larger tumor
size, further limiting the use of these isotopes. The study concluded
that the larger high-dose volume with palladium-103 and iodine-125
potentially increases the risk for radiation necrosis, and the
inhomogeneity becomes more pronounced with increasing target volume.
The applicant also cited a presentation by Dr. Pinnaduwage at the
August 2018 annual meeting of the American Association of Physicists in
Medicine, in which research findings demonstrated that seed migration
in
[[Page 19342]]
collagen tile implantations was relatively small for all tested
isotopes, with Cesium-13 showing the least amount of seed migration.
The applicant asserted that, when considered in total, the data
reported in these presentations and studies and the intermittent data
presented in their abstracts support the conclusion that a significant
therapeutic effect results from the addition of GammaTileTM
radiation therapy to the site of surgical removal. According to the
applicant, the fact that these patients had failed prior best available
treatments (aggressive surgical and adjuvant radiation management)
presents the unusual scenario of a salvage therapy outperforming the
current standard-of-care. The applicant noted that follow-up data
continues to accrue on these patients.
Regarding the assertion that GammaTileTM reduces
mortality, the applicant stated that the use of the
GammaTileTM technology reduces rates of mortality compared
to alternative treatment options. The applicant explained that studies
on the GammaTileTM technology have shown improved local
control of tumor recurrence. According to the applicant, the results of
these studies showed local control rates of 92 percent to 96 percent
for tumor sites that had local control rates of 0 percent from previous
treatment. The applicant noted that these studies also have not reached
median progression-free survival time with follow-up times ranging from
1 to 37 months. Previous treatment at these same sites resulted in
median progression-free survival times of 5.8 to 10.3 months.
The applicant further stated that the use of the
GammaTileTM technology reduces rates of radiation necrosis
compared to alternative treatment options. The applicant explained that
the rate of symptomatic radiation necrosis in the
GammaTileTM clinical studies of 5 to 8 percent is
substantially lower than the 26 percent to 57 percent rate of
symptomatic radiation necrosis requiring re-operation historically
associated with brain brachytherapy, and lower than the rates reported
for initial treatment of similar tumors with modern external beam and
stereotactic radiation techniques. The applicant indicated that this is
consistent with the customized and ideal distribution of radiation
therapy provided by the GammaTileTM technology.
The applicant also asserted that the use of the
GammaTileTM technology reduces the need for re-operation
compared to alternative treatment options. The applicant explained that
patients receiving a craniotomy, followed by external beam radiation
therapy or brachytherapy, could require re-operation in the following
three scenarios:
Tumor recurrence at the excision site could require
additional surgical removal;
Symptomatic radiation necrosis could require excision of
the affected tissue; and
Certain forms of brain brachytherapy require the removal
of brachytherapy sources after a given period of time.
However, according to the applicant, because of the high local
control rates, low rates of symptomatic radiation necrosis, and short
half-life of cesium-131, the GammaTileTM technology will
reduce the need for re-operation compared to external beam radiation
therapy and other forms of brain brachytherapy.
Additionally, the applicant stated that the use of the
GammaTileTM technology reduces the need for additional
hospital visits and procedures compared to alternative treatment
options. The applicant noted that the GammaTileTM technology
is placed during surgery, and does not require any additional visits or
procedures. The applicant contrasted this improvement with external
beam radiation therapy, which is often delivered in multiple fractions
that must be administered over multiple days. The applicant provided an
example where whole brain radiotherapy (WBRT) is delivered over 2 to 3
weeks, while the placement of the GammaTileTM technology
occurs during the craniotomy and does not add any time to a patient's
recovery.
Based on consideration of all of the data presented above, the
applicant believed that the use of the GammaTileTM
technology represents a substantial clinical improvement over existing
technologies.
We are concerned that the clinical efficacy and safety data
provided by the applicant may be limited. The findings presented appear
to be derived from relatively small case-studies and not data from FDA
approved clinical trials. While the applicant described increases in
median time to disease recurrence in support of clinical improvement,
we are concerned with the lack of analysis, meta-analysis, or
statistical tests that indicated that seeded brachytherapy procedures
represented a statistically significant improvement over alternative
treatments, such as external beam radiation or other forms of
brachytherapy. We also are concerned with the lack of studies involving
the actual manufactured device. Finally, while the FDA cleared
GammaTileTM under section 510(k), authorization to market
the device for the cleared indications, we note that the FDA's issuance
of a ``substantially equivalent determination'' did not indicate a
review of any specific superiority claims to a predicate device.
We are inviting public comments on whether the
GammaTileTM technology meets the substantial clinical
improvement criterion. We did not receive any written comments in
response to the New Technology Town Hall meeting notice published in
the Federal Register regarding the substantial clinical improvement
criterion for GammaTileTM or at the New Technology Town Hall
meeting.
m. Imipenem, Cilastatin, and Relebactam (IMI/REL) Injection
Merck & Co., Inc. submitted an application for new technology add-
on payments for IMI/REL for FY 2020. The applicant is seeking an
indication for IMI/REL for the treatment of patients 18 years of age
and older who have been diagnosed with: (a) Complicated intra-abdominal
infections (cIAI) caused by susceptible gram-negative microorganisms
where limited or no alternative therapies are available; and (b)
complicated urinary tract infections (cUTIs), including pyelonephritis,
caused by susceptible gram-negative microorganisms where limited or no
alternative therapies are available. The applicant stated that IMI/REL
does not currently have a trade name, although an NDA was accepted and
is being reviewed for IMI/REL.
The applicant reported that complicated intra-abdominal infections
are a subset of intra-abdominal infections, a term which includes a
diverse set of diseases. It is broadly defined as peritoneal
inflammation in response to micro-organisms, resulting in purulence in
the peritoneal cavity. Complicated intra-abdominal infections extend
beyond the source organ into the peritoneal space. These infections
cause peritoneal inflammation, and are associated with localized or
diffuse peritonitis. Localized peritonitis often manifests as an
abscess with tissue debris, bacteria, neutrophils, macrophages, and
exudative fluid contained in a fibrous capsule. Diffuse peritonitis is
categorized as primary, secondary, or tertiary peritonitis.\270\
---------------------------------------------------------------------------
\270\ Lopez, N., Kobayashi, L., Coimbra, R., ``A Comprehensive
review of abdominal infections,'' World J Emerg Surg, 2011, vol. 6,
pp. 7, Published February 23, 2011, doi:10.1186/1749-7922-6-7.
---------------------------------------------------------------------------
In addition, the applicant stated that complicated intra-abdominal
infections
[[Page 19343]]
are characterized by chills, rigors, or fever (temperature of greater
than or equal to 38.0 [deg]C); elevated white blood cell count (greater
than 10,000/mm\3\), or left shift (greater than 15 percent immature
PMNs); nausea or vomiting; dysuria, increased urinary frequency, or
urinary urgency; and lower abdominal pain or pelvic pain. Acute
pyelonephritis is characterized by chills, rigors, or fever
(temperature of greater than or equal to 38.0 [deg]C); elevated white
blood cell count (greater than 10,000/mm\3\), or left shift (greater
than 15 percent immature PMNs); nausea or vomiting; dysuria, increased
urinary frequency, or urinary urgency; flank pain; and costo-vertebral
angle tenderness on physical examination. Risk factors for infection
with drug-resistant organisms do not, on their own, indicate a
cUTI.\271\
---------------------------------------------------------------------------
\271\ Hooton, T. and Kalpana, G., ``Acute complicated urinary
tract infection (including pyelonephritis) in adults,'' In A. Bloom
(Ed.), UpToDate. Available at: https://www.uptodate.com/contents/acute-complicated-urinary-tract-infectionincluding-pyelonephritis-in-adults.
---------------------------------------------------------------------------
According to the applicant, IMI/REL is a fixed-dose combination of
imipenem/cilastatin (IMI), a [beta]-lactam (BL) antibacterial
(specifically, a carbapenem), and relebactam (REL), a novel [beta]-
lactamase inhibitor (BLI). The applicant stated that IMI was the first
marketed carbapenem when approved by the FDA in 1985. It is a sterile
formulation of imipenem (a thienamycin antibacterial) and cilastatin
sodium (inhibitor of the renal dipeptidase, dehydropeptidase-l). The
applicant asserted that IMI is stable against hydrolysis by many
extended spectrum [beta]-lactamases (ESBLs) and is frequently used for
the treatment of serious bacterial infections in which gram-negative
bacteria and/or anaerobes play a significant role. The applicant
additionally stated that REL is a non-[beta]-lactam, small molecule
diazabicyclooctane (DABCO) BLI with inhibitory activity against various
[beta]-lactamases: Class A carbapenemases (such as KPC), Class C
cephalosporinases (including AmpC), and ESBLs.
The applicant stated that procedures involving the administration
of IMI/REL could be, generally, identified with ICD-10-PCS codes
3E03329 (Introduction of other anti-infective into peripheral vein,
percutaneous approach) or 3E04329 (Introduction of other anti-infective
into central vein, percutaneous approach). However, neither code would
uniquely identify procedures involving the administration of IMI/REL.
The applicant has submitted a request to the ICD-10 Coordination and
Maintenance Committee for approval for an ICD-10-PCS procedure code to
distinctly identify procedures involving the administration of IMI/REL.
The applicant anticipates that the recommended dosage of IMI/REL
will be 500 mg imipenem/500 mg cilastatin/250 mg relebactam, via
intravenous infusion over 30 minutes every 6 hours. The applicant
anticipates that the dosage will be decreased proportionally with
decreases in the renal creatinine clearance category.
As discussed earlier, if a technology meets all three of the
substantial similarity criteria, it would be considered substantially
similar to an existing technology and would not be considered ``new''
for purposes of new technology add-on payments.
With regard to the first criterion, whether the product uses the
same or a similar mechanism of action as an existing technology to
achieve the same therapeutic outcome, the applicant stated that IMI/
REL's mechanism of action differentiates it from other approved
injectable antibiotics. The applicant noted that there are three other
BL/BLI antibiotics that have recently been FDA-approved, including
Zerbaxa[supreg], Avycaz[supreg], and VABOMERETM. However,
the applicant stated that the properties of REL, a non-[beta]-lactam,
small molecule diazabicyclooctane (DABCO) BLI with inhibitory activity
against various [beta]-lactamases including: Class A carbapenemases
(such as KPC), Class C cephalosporinases (including AmpC), and ESBLs,
when combined with imipenem and cilastatin, used as [beta]-lactams,
gives IMI/REL a different mechanism of action from that of the
aforementioned BL/BLI antibiotics. The applicant provided comparisons
of efficacy with other BL/BLI antibiotics as evidence of IMI/REL's
unique mechanism of action, and asserted that the combination of REL
and IMI would be efficacious in most imipenem-resistant strains at
clinically achievable doses and concentrations, and that both IMI and
REL are not subject to efflux pumps in P. aeruginosa. The applicant
additionally submitted several studies that noted that REL, as a non-
[beta]-lactam, small-molecule BLI with dual Class A/C activity, is
suited to inactivate [beta]-lactamase subtypes involved in carbapenem
resistance.272 273 By inhibiting these [beta]-lactamases,
the applicant claims that REL has the potential to restore IMI's
efficacy against MDR pathogens previously expressing resistance to IMI.
---------------------------------------------------------------------------
\272\ Sims, et al., ``Prospective, randomized, double-blind,
Phase 2 dose-ranging study comparing efficacy and safety of
imipenem/cilastatin plus relebactam with imipenem/cilastatin alone
in patients with complicated urinary tract infections.'' Journal of
Antimicrobial Chemotherapy. 2017.
\273\ Rhee, et al., ``Pharmacokinetics, Safety, and Tolerability
of Single and Multiple Doses of Relebactam, a b-LactamaseInhibitor,
in Combination with Imipenem and Cilastatin in Healthy
Participants.'' Antimicrobial Agents and Chemotherapy, 2018.
---------------------------------------------------------------------------
With respect to the second criterion, whether the product is
assigned to the same or a different MS-DRG as existing technologies,
the applicant asserted that patients who may be eligible to receive
treatment involving IMI/REL include hospitalized patients who have been
diagnosed with a cUTI or cIAI. We expect that cases involving IMI/REL
would most likely be assigned to the same MS-DRGs to which cases
involving comparator treatments are assigned.
With respect to the third criterion, whether the new use of the
technology involves the treatment of the same or similar type of
disease and the same or similar patient population, the applicant
asserted that the use of IMI/REL would treat a different patient
population than existing and currently available treatment options. As
previously noted, the applicant submitted several studies that noted
REL, as a non-[beta]-lactam, small-molecule BLI with dual Class A/C
activity, is suited to inactivate [beta]-lactamase subtypes involved in
carbapenem resistance.274 275 By inhibiting these [beta]-
lactamases, the applicant asserts that REL has the potential to restore
IMI's efficacy against MDR pathogens previously expressing resistance
to IMI and, therefore, to extend treatment to patient populations that
might have previously been resistant to IMI. Additionally, the
applicant compared the administration of IMI/REL to other comparator
antibiotics to demonstrate its unique place in the armamentarium,
beginning with three older antibiotics. First, in comparison to
polymyxins, the applicant asserts that even in colistin-derived
preparations of polymyxins, nephrotoxicity is still evident and is the
potential adverse experience of most
[[Page 19344]]
concern to prescribing clinicians,\276\ and further asserted that
neither polymyxin B nor colistin have been subjected to contemporary
drug development procedures.\277\ Second, the applicant asserted that
clinical data for fosfomycin in the treatment of MDR bacterial
infections are very scarce. Third, the applicant stated that
tigecycline does not have activity against Pseudomonas spp.\278\
Furthermore, in a safety announcement released by the FDA in 2013, it
was noted that an increased risk of death was observed with tigecycline
compared to other antibacterials used to treat similar infections.\279\
---------------------------------------------------------------------------
\274\ Sims, et al., ``Prospective, randomized, double-blind,
Phase 2 dose-ranging study comparing efficacy and safety of
imipenem/cilastatin plus relebactam with imipenem/cilastatin alone
in patients with complicated urinary tract infections.'' Journal of
Antimicrobial Chemotherapy, 2017.
\275\ Rhee, et al., ``Pharmacokinetics, Safety, and Tolerability
of Single and Multiple Doses of Relebactam, a b-LactamaseInhibitor,
in Combination with Imipenem and Cilastatin in Healthy
Participants.'' Antimicrobial Agents and Chemotherapy, 2018.
\276\ Dalfino, L, et al., ``High-Dose, extended-interval
colistin administration in critically ill patients: is this the
right dosing strategy? A preliminary study,'' Clin Infect Dis, 2012,
vol. 54(12), pp. 1720-6.
\277\ American Thoracic Society, Infectious Diseases Society of
America, ``Guidelines for the management of adults with hospital
lacquired, ventilator-associated, and healthcare-associated
pneumonia,'' Am J Respir Crit Care Med, 2005, vol. 171, pp. 388-416.
\278\ Giamarellou, H., Poulakou, G., ``Multidrug-resistant gram-
negative infections; what are the treatment options? Drugs,'' Drugs,
2009, vol, 69(14), pp. 1879-1901.
\279\ FDA Drug Safety Communication: ``FDA warns of increased
risk of death with IV antibacterial Tygacil (tigecycline) and
approves new Boxed Warning'', Accessed at https://www.fda.gov/Drugs/DrugSafety/ucm369580.htm on 11/10/2018.
---------------------------------------------------------------------------
The applicant also compared the administration of IMI/REL to the
three other aforementioned BL/BLI antibiotics. First, the applicant
asserted that the use of tazobactam in Zerbaxa[supreg] is not effective
against KPC-producing bacteria \280\ and some highly drug-resistant
strains of P. aeruginosa, including some carbapenem-resistant (CR)
strains, which are able to escape the antipseudomonal activity of
Zerbaxa[supreg]. Second, the applicant asserted that there have been
recent reports of resistance to Avycaz[supreg],281 282
including in a recent report published by the European Centre for
Disease Prevention and Control (ECDC).\283\ The applicant reports that
additionally, avibactam has been shown to be subject to efflux in P.
aeruginosa, which the applicant asserts casts further concerns
regarding its utility.284 285 Third, the applicant asserted
that the use of vaborbactam in VABOMERETM has little impact
on the activity of meropenem in vitro against CR P. aeruginosa,
arguably due to vaborbactam being subject to efflux.286 287
In addition, the applicant stated that the U.S. Prescribing Information
(USPI) for VABOMERETM indicates that vaborbactam has no
effect on meropenem activity against meropenem-susceptible
isolates.\288\
---------------------------------------------------------------------------
\280\ Papp-Wallace, K.M., et al., ``Substrate selectivity and a
novel role in inhibitor discrimination by residue 237 in the KPC-2
betalactamase,'' Antimicrob Agents Chemother, Jul 2010, vol. 54(7).
pp. 2867-77, doi: 10.1128/AAC.00197-10, Epub 2010, Apr 26.
\281\ Shields, R.K., et al., ``Emergence of ceftazidime-
avibactam resistance due to plasmid-borne blaKPC-3 mutations during
treatment of carbapenem-resistant Klebsiella pneumoniae
infections,'' Antimicrob Agents Chemother, Feb 23, 2017, vol.
;61(3), pii: e02097-16, doi: 10.1128/AAC.02097-16, Print 2017 Mar.
\282\ Haidar, G,, et al., ``Identifying spectra of activity and
therapeutic niches for ceftazidime-avibactam and imipenem relebactam
against carbapenemresistant Enterobacteriaceae,'' Antimicrob Agents
Chemother, 2017, vol. 61, pp. e00642-17.
\283\ European Centre for Disease Prevention and Control,
``Emergence of resistance to ceftazidime-avibactam in carbapenem-
resistant Enterobacteriaceae, 12 June 2018,'' Stockholm; ECDC; 2018.
\284\ Poster presented at ECCMID 2017 (Apr 22-25), Vienna
(Austria). EP0469: Avibactam is a substrate for MexAB-OprM in
P.aeruginosa.
\285\ Chalhoub, H., et al., ``Loss of activity of ceftazidime-
avibactam due to Mex-AB-OprM efflux and overproduction of AmpC
cephalosporinase in Pseudomonas aeruginosa isolated from patients
suffering from cystic fibrosis,'' Int J Antimicrob Agents, August 3,
2018, pii: S0924-8579(18)30226-7, doi: 10.1016/
j.ijantimicag.2018.07.027. [Epub ahead of print].
\286\ Castanheira, M., et al., ``Meropenem-Vaborbactam Tested
against contemporary gram-negative isolates collected worldwide
during 2014, including carbapenem-resistant, KPC-producing,
multidrug-resistant, and extensively drug-resistant
Enterobacteriaceae,'' Antimicrob Agents Chemother. August, 24, 2017,
vol. 61(9), pii: e00567-17, doi: 10.1128/AAC.00567-17, Print
September 2017.
\287\ Zhanel, G.G., et al., ``Imipenem-relebactam and meropenem-
vaborbactam: two novel carbapenem-[beta]-lactamase inhibitor
combinations,'' Drugs, January 2018, vol. 78(1), pp. 65-98, doi:
10.1007/s40265-017-0851-9.
\288\ USPI for VABOMERETM.
---------------------------------------------------------------------------
Finally, the applicant compared the administration of IMI/REL to
two additional antibiotics. First, the applicant asserted that
XeravaTM has no activity against P. aeruginosa.\289\ Second,
the applicant asserted that aminoglycosides, including
ZemdriTM, usually have minimal lung penetration, limiting
potential efficacy in HABP/VABP. The applicant stated that currently
used aminoglycosides are associated with nephrotoxicity and
ototoxicity, and, outside of UTI, are rarely given as single agents in
the treatment of serious bacterial infections. The applicant stated
that the approved USPI for ZemdriTM includes black-box
warnings for nephrotoxicity, ototoxicity, neuromuscular blockade, and
fetal harm.\290\
---------------------------------------------------------------------------
\289\ USPI for XeravaTM.
\290\ USPI for ZemdriTM.
---------------------------------------------------------------------------
We are concerned that the mechanism of action of IMI/REL may be
similar to the mechanism of action of other BL/BLI antibiotics. While
we recognize that REL is used as a unique molecular structure with
respect to other BLIs in BL/BLI combination, the fundamental mechanism
of action of IMI/REL may be similar to that of other BL/BLIs.
Additionally, with respect to whether the use of IMI/REL would treat a
different patient population than existing treatment options, we note
that, while the variety of antibiotic resistance-patterns certainly
warrants a varied armamentarium for clinicians, there are existing
antimicrobials that are approved to, generally, treat diagnoses of
cUTIs, cIAIs, and MDR pathogens. We are concerned that non-uniform
resistance patterns among patients, necessitating a range of drugs to
treat the same diseases, may not constitute a new patient population.
We are inviting public comments on whether the IMI/REL technology is
substantially similar to any existing technologies and whether it meets
the newness criterion, including with respect to the concerns we have
raised.
The applicant conducted the following analysis to demonstrate that
the technology meets the cost criterion. To determine the MS-DRGs that
potential cases representing patients who may be eligible for treatment
involving the administration of IMI/REL would map to, the applicant
identified all MS-DRGs containing cases that reported ICD-10-CM
diagnosis codes for cUTI or cIAI, as a primary or secondary diagnosis,
as well as a diagnosis code(s) for CRE resistance. Based on the FY 2017
MedPAR data file and Hospital Limited Data Set (LDS), the applicant
identified a total of 21,111 cases representing patients who may be
eligible for treatment with the administration of IMI/REL, which mapped
to 441 unique MS-DRGs. There were 307 MS-DRGs with very minimal
frequencies (fewer than 11 cases), and a total of 1,138 cases
associated with these low-volume MS-DRGs. After trimming the cases that
were mapped to low-volume MS-DRGS, the applicant identified 19,973
cases that were mapped to 134 unique MS-DRGs, with the top 10 MS-DRGs
covering approximately 74.3 percent of all identified cases.
Using 100 percent of the 19,973 cases considered, the applicant
determined an average case-weighted unstandardized charge per case of
$60,506. The applicant standardized the charges for each case and
inflated each case's charges by applying the FY 2019 IPPS/LTCH PPS
final rule outlier charge inflation factor of 1.08864 (83 FR 41722).
(We note that this 2-year charge inflation factor was revised in the FY
2019 IPPS/LTCH PPS final rule correction notice. The corrected factor
is 1.08986 (83 FR 49844). However, we further note that even when using
the corrected final rule values to inflate the
[[Page 19345]]
charges, the average case-weighted standardized charge per case for
each scenario exceeded the average case-weighted threshold amount.) The
applicant then removed 100 percent of the drug charges from the
relevant cases to estimate the charges for drugs that potentially may
be replaced or avoided by the administration of IMI/REL. The applicant
then added charges for the administration of IMI/REL by taking the cost
of the drug and converting it to a charge by dividing the costs by the
national average CCR of 0.191 for drugs from the FY 2019 IPPS/LTCH PPS
final rule (83 FR 41273). The applicant calculated an average case-
weighted standardized charge per case of $74,778, using the percent
distribution of MS-DRGs as case-weights. Based on this analysis, the
applicant determined that the final inflated average case-weighted
standardized charge per case for cases involving the administration of
IMI/REL exceeded the average case-weighted threshold amount of $50,417
by $24,361.
The applicant conducted additional analysis to demonstrate that the
technology meets the cost criterion. In these analyses, the applicant
repeated the cost analysis above with one analysis of cases with a
diagnosis of cUTI and the other analysis of cases with a diagnosis of
cIAI. In each of these additional sensitivity analyses, the applicant
determined that the final inflated average case-weighted standardized
charge per case exceeded the final average case-weighed threshold
amount, by $21,677 and $44,119, respectively. We are inviting public
comments on whether the administration of IMI/REL meets the cost
criterion.
With regard to substantial clinical improvement, the applicant
believes that the administration of IMI/REL represents a substantial
clinical improvement over currently available therapies because of the
efficacy and safety results of the completed Phase III trial RESTORE-
IMI 1. RESTORE-IMI 1 included 47 subjects who were randomized in a
randomized, double-blind, active-controlled, parallel group, multi-
center Phase III trial of IMI/REL (provided together in a single vial
as a fixed-dose combination product) + placebo compared with colistin
(in the form of colistimethate sodium [CMS]) + IMI in patients with
imipenem non-susceptible bacterial infections, including HABP/VABP,
cIAI, and cUTI. The primary efficacy endpoint for RESTORE-IMI 1 was
overall response based on the following: (a) All-cause mortality
through Day 28 post-randomization in patients who had been diagnosed
with HABP/VABP, (b) clinical response at Day 28 post-randomization for
patients who had been diagnosed with cIAI, and (c) composite clinical
and microbiological response at early follow-up (EFU) (Day 5 to 9
following completion of therapy) for patients who had been diagnosed
with cUTI. Key secondary efficacy endpoints include estimation of
clinical response at Day 28 post-randomization and all-cause mortality
through Day 28. A favorable clinical response for all infection sites
refers to resolution of baseline clinical signs and symptoms associated
with the baseline infection. The primary efficacy analysis population
for this study is the microbiological modified intent-to treat (m-MITT)
population (31 patients), defined as all randomized patients who
received at least one dose of the study drug within a given stage/phase
IV study therapy regimen, and who had been diagnosed with a qualifying
baseline bacterial pathogen.
With respect to efficacy, the applicant stated that the
administration of IMI/REL demonstrates a substantial clinical
improvement due to the following three study results: (1) Numerically
comparable overall response of the use of IMI/REL compared to CMS +
IMI, (2) numerically favorable clinical response at Day 28 for the use
of IMI/REL compared to CMS + IMI, and (3), numerically lower all-cause
mortality at Day 28. First, the applicant indicated that a favorable
overall response (primary endpoint) was achieved in 71.4 percent of the
patients who received treatment involving IMI/REL + placebo and 70.0
percent of the patients who received treatment with CMS + IMI.\291\
Second, the applicant asserted that favorable clinical response
(secondary endpoint) was achieved by a higher percentage of the
patients who received treatment involving IMI/REL + placebo (71.4
percent) than patients who received treatment with CMS + IMI (40.0
percent) at Day 28, as well as at all other time points assessed.\292\
Third, the applicant states that all-cause mortality at Day 28 favored
IMI/REL + placebo (9.5 percent) over CMS + IMI (30 percent), although
the difference was not statistically significant at the 90 percent
level.
---------------------------------------------------------------------------
\291\ Motsch, J. et al., ``RESTORE-IMI 1: A Multicenter,
Randomized, Double-Blind, Comparator-Controlled Trial Comparing the
Efficacy and Safety of Imipenem/Relebactam vs Colistin Plus Imipenem
in Patients With Imipenem-Non-susceptible Bacterial Infections.''
\292\ Ibid.
---------------------------------------------------------------------------
With respect to safety, the applicant indicated that the primary
population used for all safety evaluations was the All-Subjects-as-
Treated (ASaT) population, which comprises all patients who received at
least one dose of the study medication. The applicant stated that the
incidence of AEs, including deaths, SAEs, drug-related AEs and SAEs,
and discontinuations due to AEs, was lower in patients who received
treatment involving the administration of IMI/REL + placebo than in
patients who received treatment involving the CMS + IMI. Overall, the
most commonly reported AEs (greater than or equal to 10 percent of the
patients overall) across both treatment groups were pyrexia (12.8
percent of the patients), increased AST (12.8 percent of the patients),
increased ALT (10.6 percent), and nausea (10.6 percent of subjects).
The incidences of increased AST, increased ALT, and nausea were lower
in patients who received treatment involving IMI/REL + placebo than in
patients who received treatment involving CMS + IMI. The applicant
further stated that in accounting for nephrotoxicity associated with
the use of CMS, a pre-specified key secondary objective of the study
was to estimate the proportion of patients who experienced treatment-
emergent nephrotoxicity following receipt of treatment involving IMI/
REL + placebo or CMS + IMI and to compare the treatment groups. From
this analysis, the applicant concluded that the incidence of treatment-
emergent nephrotoxicity was significantly lower in patients who
received treatment involving IMI/REL + placebo (10.3 percent) than in
patients who received treatment involving CMS + IMI (56.3 percent)
(two-sided p-value of 0.002).
We have the following concerns regarding whether IMI/REL meets the
substantial clinical improvement criterion. First, we are concerned
regarding the comparator chosen for the RESTORE-IMI 1 trial. We are not
certain why the combination of CMS + IMI was chosen, and if other
comparators would have been more appropriate. Second, 8 of the 21 cases
in the m-MITT population treated with IMI/REL were cases of HABP/
VABP,\293\ and further 7 out of the 15 cases of positive clinical
response in the m-MITT population to IMI/REL were cases of HABP/
VABP.\294\ Because HABP/VABP are not conditions for which the applicant
is seeking indications for IMI/REL, it is possible that conclusions
drawn from the RESTORE-IMI 1 study regarding safety and efficacy are
not specific to those indications described
[[Page 19346]]
in the application. Third, the favorable clinical response after Day 28
is measured at the 90 percent confidence level,\295\ rather than the
more common 95 percent level, without explanation. Fourth, we note that
the study is composed of an initial sample of only 47 patients.\296\
With such a small sample we are concerned about the external validity
of the conclusions, specifically the generalizability of the results to
the Medicare population, given the specific demographic makeup of that
population. Fifth, we have another methodological concern regarding the
different endpoints present in the study, along with the Day 28
assessment. We note that HABP/VABP, cUTI, and cIAI are measured
respectively by mortality, favorable clinical response (cure), and
favorable clinical response (cure OR sustained eradication).\297\ We
are uncertain why different endpoints were chosen for the different
conditions. Additionally, we are uncertain if the Day 28 assessment
cited in the application reflects microbiological or just clinical
response. Sixth, the applicant defined the m-MITT and ASaT populations
as those patients who received at least one dose of the study drug. We
are not certain whether these analyses should also include those
patients in the comparator arm who did not receive the study drug, as
this could violate the applicant's definition of m-MITT. Seventh, CMS
also notes that both the estimated difference in the favorable overall
response at the primary endpoint and the estimated difference in all-
cause mortality are not statistically significant \298\ and, therefore,
may not represent a substantial clinical improvement. Finally, in
addition, with respect to safety, the applicant asserted that the
administration of IMI/REL induces less nephrotoxicity compared to the
use of CMS + IMI. However, nephrotoxicity is a known adverse effect of
CMS, and other available antimicrobials approved to treat diagnoses of
cUTIs and cIAIs induce less nephrotoxicity (and were not studied in the
data provided to support this application). Therefore, it is not clear
that IMI/REL induces less nephrotoxicity compared to other available
treatments.
---------------------------------------------------------------------------
\293\ 18-1315-D MRPAB18303 IDWeek SmMITT_final.
\294\ Ibid.
\295\ 18-1315-C MRPAB18304 IDWeek Nephrotoxicity_final.
\296\ Ibid.
\297\ 18-1315-D MRPAB18303 IDWeek SmMITT_final.
\298\ Kaye, K.S., et al., ``Results for the Supplemental
Microbiological Modified Intent-to-Treat (SmMITT) Population of the
RESTORE-IMI 1 Trial of Imipenem/Cilastatin/Relebactam Versus
Colistin Plus Imipenem/Cilastatin in Patients With Imipenem-
Nonsusceptible.''
---------------------------------------------------------------------------
We are inviting public comments on whether IMI/REL meets the
substantial clinical improvement criterion, including with respect to
the concerns we have raised. We did not receive any written comments in
response to the New Technology Town Hall meeting notice published in
the Federal Register regarding the substantial clinical improvement
criterion for IMI/REL or at the New Technology Town Hall meeting.
n. JAKAFITM (Ruxolitinib)
Incyte Corporation submitted an application for new technology add-
on payments for JAKAFITM (ruxolitinib) for FY 2020.
JAKAFITM is an oral kinase inhibitor that inhibits Janus-
associated kinases 1 and 2 (JAK1/JAK2). The JAK pathway, which includes
JAK1 and JAK2, is involved in the regulation of immune cell maturation
and function. According to the applicant, JAK inhibition represents a
novel therapeutic approach for the treatment of acute graft-versus-host
disease (GVHD) in patients who have had an inadequate response to
corticosteroids.
Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a
treatment option for patients who have been diagnosed with hematologic
cancers, some solid tumors, and some non-malignant hematologic
disorders. According to the applicant, approximately 9,000 allo-HSCTs
were performed in the U.S. in 2017. The most common cause of death in
allo-HSCT recipients within the first 100 days is relapsed disease (29
percent), infection (16 percent), and GVHD (9 percent).\299\ GVHD is a
condition where donor immunocompetent cells attack the host tissue.
GVHD can be acute (aGVHD), which generally occurs prior to day 100, or
chronic (cGVHD). aGVHD results in systemic inflammation and tissue
destruction affecting multiple organs. Systemic corticosteroids are
used as first-line therapy for the treatment of a diagnosis of aGVHD,
with response rates between 40 percent and 60 percent. However, the
response is often not durable, and there is no consensus on optimal
second-line treatment.\300\ The applicant envisions the use of
JAKAFITM as second-line treatment (that is, first-line
steroid treatment failures) for the treatment of a diagnosis of
steroid-refractory aGVHD.
---------------------------------------------------------------------------
\299\ D'Souza, A., Lee, S., Zhu, X., Pasquini, M., ``Current use
and trends in hematopoietic cell transplantation in the United
States,'' Biol Blood Marrow Transplant, 2017, vol. 23(9), pp. 1417-
1421.
\300\ Martin, P.J., Rizzo, J.D., Wingard, J.R., et al., ``First
and second-line systemic treatment of acute graft-versus-host
disease: recommendations of the American Society of Blood and Marrow
Transplantation,'' Biol Blood Marrow Transplant, 2012, vol. 18(8),
pp. 1150-1163.
---------------------------------------------------------------------------
The applicant reports that there are no FDA-approved treatments for
patients who have been diagnosed with steroid-refractory aGVHD, and
despite available treatment options, according to the applicant,
patients do not always achieve a positive response, underscoring the
need for new and innovative treatments for these patients. The
applicant also states that patients who develop steroid-refractory
aGVHD can progress to severe disease, with 1-year mortality rates of 70
to 80 percent. A number of combination treatment approaches are being
investigated as second-line therapy in patients who have been diagnosed
with steroid-refractory aGVHD, including methotrexate, mycophenolate
mofetil, extracorporeal photopheresis, IL-2R targeting agents
(basiliximab, daclizumab, denileukin, and diftitox), alemtuzumab, horse
antithymocyte globulin, etancercept, infliximab, and sirolimus.
According to the applicant, the American Society for Blood and Marrow
Transplantation (ASBMT) does not provide any recommendations for
second-line therapy for patients who have been diagnosed with steroid-
refractory aGVHD, nor suggest avoidance of any specific agent.
JAKAFITM received FDA approval in 2011 for the treatment
of patients who have been diagnosed with intermediate or high-risk
myelofibrosis (MF). In addition, JAKAFITM received FDA
approval in December 2014 for the treatment of patients who have been
diagnosed with polycythemia vera (PV) who have had an inadequate
response to, or are intolerant of hydroxyurea. JAKAFITM is
primarily prescribed in the outpatient setting for these indications.
The applicant has submitted a supplemental new drug application (sNDA)
(with Orphan Drug and Breakthrough Therapy designations) seeking FDA's
approval for a new indication for JAKAFITM for the treatment
of patients who have been diagnosed with steroid-refractory aGVHD who
have had an inadequate response to treatment with corticosteroids. The
applicant asserts that for this new indication, JAKAFITM is
expected to be used in the inpatient setting, during either hospital
admission for allo-HSCT, or upon need for hospital re-admission for
treating patients who have been diagnosed with aGVHD who have had an
inadequate response to treatment with corticosteroids. Although as of
the time of the development of this FY 2020 IPPS/LTCH PPS proposed rule
it has not yet received FDA approval, the applicant
[[Page 19347]]
indicated that it expects FDA approval for this new indication for the
use of JAKAFITM prior to the July 1, 2019 deadline.
There are currently no ICD-10-PCS procedure codes that uniquely
identify the administration of JAKAFITM. We note that the
applicant submitted a request for approval for a unique ICD-10-PCS
procedure code to describe procedures involving the administration of
JAKAFITM beginning in FY 2020.
As stated above, if a technology meets all three of the substantial
similarity criteria described above, it would be considered
substantially similar to an existing technology and, therefore, would
not be considered ``new'' for purposes of new technology add-on
payments.
With regard to the first criterion, whether a product uses the same
or a similar mechanism of action to achieve a therapeutic outcome, the
applicant asserts that there are no products that utilize the same or
similar mechanism of action (that is, JAK inhibition) to achieve the
same therapeutic outcome for the treatment of acute steroid-resistant
GVHD. The applicant further explained that JAKAFITM
functions to inhibit the JAK pathway, and has been shown in pre-
clinical and clinical trials to reduce GVHD. The applicant explained
that JAKs are intracellular, non-receptor tyrosine kinases that relay
the signaling of inflammatory cytokines. The applicant stated that,
based on their role in immune cell development and function, JAKs might
affect all phases of aGVHD pathogenesis, including cell activation,
expansion, and destruction. Specifically, JAKs regulate activities of
immune cells involved in aGVHD etiology, including antigen-presenting
cells, T-cells, and B-cells, and function downstream of many cytokines
relevant to GVHD-mediated tissue damage. Inhibition of JAK1/JAK2
signaling in aGVHD could be expected to block signal transduction from
proinflammatory cytokines that activate antigen-presenting cells,
expansion and differentiation of T-cells, suppression of regulatory T-
cells, and inflammation and tissue destruction mediated by infiltrating
cytotoxic T-cells.\301\ The applicant stated that other agents that are
being investigated as second-line treatments for patients who have been
diagnosed with steroid-resistant aGVHD, such as methotrexate,
mycophenolate mofetil, extracorporeal photopheresis, IL-2R targeting
agents (basiliximab, daclizumab, denileukin, and diftitox),
alemtuzumab, horse antithymocyte globulin, etancercept, infliximab, and
sirolimus, use a different mechanism of action than that of
JAKAFITM. The applicant believes that the mechanism of
action of JAKAFITM differs from that of existing
technologies used to achieve the same therapeutic outcome.
---------------------------------------------------------------------------
\301\ Martin, P.J., Rizzo, J.D., Wingard, J.R., et al., ``First
and second-line systemic treatment of acute graft-versus-host
disease: recommendations of the American Society of Blood and Marrow
Transplantation,'' Biol Blood Marrow Transplant, 2012, vol. 18(8),
pp. 1150-1163.
---------------------------------------------------------------------------
With regard to the second criterion, whether a product is assigned
to the same or a different MS-DRG, the applicant asserts that there are
currently no FDA-approved medicines for the treatment of patients who
have been diagnosed with steroid-refractory aGVHD who have had an
inadequate response to corticosteroids and, therefore,
JAKAFITM would not be assigned to the same MS-DRG as
existing technologies.
With respect to the third criterion, whether the new use of the
technology involves the treatment of the same or similar type of
disease and the same or similar patient population, the applicant
stated that there are no existing treatment options for patients who
have been diagnosed with steroid-refractory aGVHD who have had an
inadequate response to corticosteroids and, therefore,
JAKAFITM represents a new treatment option for a patient
population without existing or alternative options. The applicant
stated that, based on its knowledge, there are no other prospective
studies evaluating the effects of treatment with JAK inhibitors for the
treatment of aGVHD in this patient population, and there are no FDA-
approved agents for the treatment of patients who have been diagnosed
with steroid-refractory aGVHD who have inadequately responded to
treatment with corticosteroids.
For the reasons summarized above, the applicant maintained that
JAKAFITM is not substantially similar to any existing
technology. We note, however, that there are a number of available
second-line treatment options for a diagnosis of aGVHD that treat the
same patient population. We also note that a number of these treatment
options use a method of immunomodulation and suppress the body's immune
response similar to the mechanics and goals of JAKAFITM and,
therefore, we believe that JAFAKITM may have a similar
mechanism of action as existing therapies. Finally, for patients
receiving treatment involving any current second-line therapies for a
diagnosis of steroid-refractory aGVHD, CMS would expect these patient
cases to be generally assigned to the same MS-DRGs as a diagnosis for
aGVHD, as would cases representing patients who may be eligible for
treatment involving JAKAFITM. We are inviting public
comments on whether JAKAFITM is substantially similar to any
existing technologies, including with respect to the concerns we have
raised, and whether the technology meets the newness criterion.
With regard to the cost criterion, the applicant conducted the
following analysis to demonstrate that the technology meets the cost
criterion. To identify cases representing patients who may be eligible
for treatment involving JAKAFITM, the applicant searched the
FY 2017 MedPAR Limited Data Set (LDS) for cases reporting ICD-10-CM
diagnosis codes for acute or unspecified GVHD in combination with
either ICD-10-CM diagnosis codes for associated complications of bone
marrow transplant or ICD-10-PCS procedure codes for transfusion of
allogeneic bone marrow, as identified in the table below. The applicant
used this methodology to capture patients who developed aGVHD during
their initial stay for allo-HSCT treatment, as well as those patients
who were discharged and needed to be readmitted for a diagnosis of
aGVHD.
The applicant submitted the following table displaying a complete
list of the ICD-10-CM diagnosis codes and ICD-10-PCS procedure codes it
used to identify cases representing patients who may be eligible for
treatment with JAKAFITM.
BILLING CODE 4120-01-P
[[Page 19348]]
[GRAPHIC] [TIFF OMITTED] TP03MY19.017
[[Page 19349]]
[GRAPHIC] [TIFF OMITTED] TP03MY19.018
[[Page 19350]]
[GRAPHIC] [TIFF OMITTED] TP03MY19.019
BILLING CODE 4120-01-C
The applicant identified a total of 210 cases mapping to MS-DRGs
014 (Allogeneic Bone Marrow Transplant), 808 (Major Hematological and
Immunological Diagnoses except Sickle Cell Crisis and Coagulation
Disorders with MCC), 809 (Major Hematological and Immunological
Diagnoses except Sickle Cell Crisis and Coagulation Disorders with CC),
and 871 (Septicemia or Severe Sepsis without MV >96 hours with MCC).
The applicant indicated that, because it is difficult to determine the
realistic amount of drug charges to be replaced or avoided as a result
of the use of JAKAFI\TM\, it provided two scenarios to demonstrate that
JAKAFI\TM\ meets the cost criterion. In the first scenario, the
applicant removed 100 percent of pharmacy charges to conservatively
estimate the charges for drugs that potentially may be replaced or
avoided by the use of JAKAFI\TM\. The applicant then standardized the
charges and applied a 2-year inflation factor of 8.864 percent, which
is the same inflation factor used by CMS to update the outlier
threshold in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41722). (We
note that this figure was revised in the FY 2019 IPPS/LTCH PPS final
rule correction notice. The corrected final 2-year inflation factor is
1.08986 (83 FR 49844).) The applicant then added charges for JAKAFI\TM\
to the inflated average case-weighted standardized charges per case. No
other related charges were added to the cases.
Under the assumption of 100 percent of historical drug charges
removed, the applicant calculated the inflated average case-weighted
standardized charge per case to be $261,512 and the average case-
weighted threshold amount to be $172,493. Based on this analysis, the
applicant believed that JAKAFI\TM\ meets the cost criterion because the
inflated average case-weighted standardized charge per case exceeds the
average case-weighted threshold amount.
As noted above, the applicant also submitted a second scenario to
demonstrate that JAKAFI\TM\ meets the cost criterion. The applicant
indicated that removing all charges for previous technologies as
demonstrated in the first scenario is unlikely to reflect the actual
case because many drugs are used in treating a diagnosis of aGVHD,
especially during the initial bone marrow transplant. Therefore, the
applicant also provided a sensitivity analysis where it did not remove
any pharmacy charges or any other historical charges, which it
indicated could be a more realistic assumption. Under this scenario,
the final average case-weighted standardized charge per case is
$377,494, which exceeds the average case-weighted threshold amount of
$172,493. The applicant maintained that JAKAFI\TM\ also meets the cost
criterion under this scenario.
We are inviting public comments on whether JAKAFI\TM\ meets the
cost criterion.
With respect to the substantial clinical improvement criterion, the
applicant asserted that JAKAFI\TM\ represents a substantial clinical
improvement because: (1) The technology offers a treatment option for a
patient population previously ineligible for treatments because
JAKAFI\TM\ (if approved) would be the first FDA-approved treatment
option for patients who have been diagnosed with GVHD who have had an
inadequate response to corticosteroids; and (2) use of the technology
significantly improves clinical outcomes in patients with steroid-
refractory aGVHD, which the applicant asserts is supported by the
results from REACH1, a prospective, open-label, single-cohort Phase II
study of the use of JAKAFI\TM\, in combination with corticosteroids,
for the treatment of Grade II to IV steroid-refractory aGVHD.
The applicant stated that there are very few prospective studies
evaluating second-line therapy for a diagnosis of steroid-refractory
aGVHD, and interpretation of these studies is hampered by the
heterogeneity of the patient population, small sample sizes, and lack
of standardization in the study design (including timing of the
response, different response criteria, and absence of validated
endpoints). Agents that have been investigated over the last 2 decades
in these studies include low-dose methotrexate, mycophenolate mofetil,
extracorporeal photopheresis, IL-2R targeting (that is, basiliximab,
daclizumab, denileukin, and diftitox), alemtuzumab, horse antithymocyte
globulin, etanercept, infliximab, and sirolimus. The applicant stated
that second-line treatments, especially those associated with
suppression of T-cells, are associated with increased infection and
viral reactivation (including cytomegalovirus (CMV), Epstein-Barr
virus, human herpes virus 6, adenovirus, and polyoma). Numerous
combination approaches (for example, antibodies directed against IL-2
receptor, mammalian target of rapamycin inhibitors, or other
immunosuppressive agents) also have been studied for the treatment of
steroid-refractory aGVHD, but the applicant indicated that data do not
support the recommendation or exclusion of any particular regimen. The
applicant also asserted that such treatment combination approaches have
been associated with significant toxicities, high failure rates, and an
average 6-month survival rate of 49 percent.\302\ Therefore, the
applicant maintains that therapeutic options are limited for patients
who are refractory to corticosteroid treatment for a diagnosis of
aGVHD.
---------------------------------------------------------------------------
\302\ Martin, P.J., Rizzo, J.D., Wingard, J.R., et al., ``First
and second-line systemic treatment of acute graft-versus-host
disease: recommendations of the American Society of Blood and Marrow
Transplantation,'' Biol Blood Marrow Transplant, 2012, vol. 18(8),
pp. 1150-1163.
---------------------------------------------------------------------------
The applicant asserted that the clinical benefit of the use of
JAKAFI\TM\ in patients who have been diagnosed with steroid-refractory
aGVHD is supported by the results from five clinical studies, including
a mixture of prospective and retrospective studies.
The first study is REACH1, a prospective, open-label, single-cohort
Phase II study of the use of JAKAFI\TM\, in combination with
corticosteroids, for the treatment of Grade II to IV steroid-refractory
aGVHD. REACH1 included 71 patients who had been diagnosed with steroid-
refractory aGVHD. Included eligible patients were those that were 12
[[Page 19351]]
years old or older, had undergone at least one allogeneic hematopoietic
stem cell transplantation from any donor source and donor type and were
diagnosed with Grade II to IV steroid-refractory aGVHD, and presented
evidence of myeloid engraftment. The patients' median age was 58 years
old (ages 18 years old to 73 years old); 66 patients were white and 36
patients were female. The majority of patients had peripheral blood
stem cells as the graft source (57 patients or 80.3 percent). The
starting dose of JAKAFI\TM\ was 5 mg twice daily (BID). The dose could
be increased to 10 mg BID after 3 days, if hematologic parameters were
stable and in the absence of any treatment-related toxicities.
Methylprednisolone (or prednisone equivalent) was administered at a
starting dose of 2 mg/kg/day on the first day of treatment and tapered
as appropriate. Patients receiving calcineurin inhibitors or other
medications for GVHD prophylaxis were permitted to continue at the
investigator's discretion. The primary endpoint was overall response
rate (ORR) at Day 28, which the applicant indicated has been shown to
be predictive of non-relapse mortality (NRM). No description of the
statistical methods used in the REACH1 study was provided by the
applicant.
The applicant stated that the ORR at Day 28 was achieved by 54.9
percent of patients; nearly half (48.7 percent) of the responding
patients achieved a complete response (CR). The best ORR was 73.2
percent. Median time to first response for all responders was 7 days.
Median duration of response was 345 days for both Day 28 responders
(lower limit, 159 days) and for other responders (lower limit, 106
days). Event-free probability estimates for Day 28 responders at 3 and
6 months were 81.6 percent and 65.2 percent, respectively. Among all
patients, median (95 percent CI) overall survival was 232.0 (93.0-not
evaluable) days. Mean survival rates for the 39 responders at Day 28
were 73.2 percent at 6 months, 69.9 percent at 9 months, and 66.2
percent at 12 months with non-relapsed mortality of 21.2 percent at 6
months, 24.5 percent at 9 months, and 28.2 percent at 12 months. Mean
survival rates for the 13 other responders were 35.9 percent at 6 and 9
months and were not evaluable at 12 months with non-relapsed mortality
at 64.1 percent at 6 and 9 months and not evaluable at 12 months. Mean
survival rates for non-responders were 15.8 percent at 6 months and
10.5 percent at 9 months and 12 months with non-relapsed mortality at
78.9 percent at 6 months and 84.2 percent at 9 and 12 months. Most
patients (55.8 percent) had a greater than or equal to 50 percent
reduction from baseline in corticosteroid dose.
The applicant stated that the additional use of JAKAFITM
to corticosteroid-based treatment did not result in unexpected
toxicities or exacerbation of known toxicities related to high-dose
corticosteroids or aGVHD. Cytopenias were among the most common
treatment-emergent adverse events. The applicant indicated that
JAKAFITM was well tolerated, and the adverse event profile
was consistent with the observed safety profiles of the use of
JAKAFITM and that of patients who had been diagnosed with
steroid-refractory aGVHD. The most common treatment emergent adverse
events in the REACH1 study were anemia (64.8 percent), hypokalemia
(49.3 percent), peripheral edema (45.1 percent), decreased platelet
count (45.1 percent), decreased neutrophil count (39.4 percent),
muscular weakness (33.8 percent), dyspnea (32.4 percent),
hypomagnesaemia (32.4 percent), hypocalcemia (31 percent), and nausea
(31 percent). The most common treatment emergent infections were sepsis
(12.7 percent) and bacteremia (9.9 percent).
All patients who had a CMV event (n=14) had a positive CMV donor or
recipient serostatus or both at baseline. No deaths were attributed to
CMV events. The applicant asserted that the results of the prospective
REACH1 study demonstrate the potential of the use of
JAKAFITM to meaningfully improve the outcomes of allo-HSCT
patients who develop steroid-refractory aGVHD, and further underscore
the promise of JAK inhibition to advance the treatment of this
potentially-devastating condition. Longer term follow-up analyses from
REACH1 are expected to yield additional insights into the long-term
efficacy and safety profile of the use of JAKAFITM in this
patient population.
In a second prospective, open-label study, 14 patients who had been
diagnosed with acute or chronic GVHD that were refractory to
corticosteroids and at least 2 other lines of treatment were treated
with JAKAFITM at a dose of 5 mg twice a day and increased to
10 mg twice a day. Of the 14 patients, 13 responded with respect to
clinical GVHD symptoms and serum levels of pro-inflammatory cytokines.
Three patients with histologically-proven acute skin or intestinal GVHD
Grade I, achieved a CR. One non-responder discontinued use of
JAKAFITM after 1 week because of lack of efficacy. In all
other patients, corticosteroids could be reduced after a median
treatment period of 1.5 weeks. CMV reactivation was observed in 4 out
of the 14 patients, and they responded well to antiviral therapy. Until
last follow-up, no patient experienced a relapse of GVHD.
The applicant asserted that the efficacy and safety of the use of
JAKAFITM for the treatment of steroid-refractory aGVHD is
further supported by the results from a third study, a retrospective,
multi-center study of 95 patients who received JAKAFITM as
salvage therapy for corticosteroid-refractory GVHD. In the 54 patients
who had been diagnosed with aGVHD, the median number of GVHD therapies
received was 3. The (best) ORR was 81.5 percent. A CR and partial
response (PR) was achieved in 46.3 percent and 35.2 percent of
patients, respectively. Median time to response was 1.5 weeks (range 1
to 11 weeks). Cytopenias and cytomegalovirus reactivation were seen in
55.5 percent (Grade III or IV) and 33.3 percent of patients who had
been diagnosed with aGVHD, respectively. Of those patients responding
to treatment with JAKAFITM, with either CR or PR (n=44), the
rate of GVHD-relapse was 6.8 percent (3/44). The 6-month-survival was
79 percent (67.3 percent to 90.7 percent, 95 percent CI). The median
follow-up time was 26.5 weeks (range 3 to 106 weeks). Underlying
malignancy relapse occurred in 9.2 percent of patients who had been
diagnosed with aGVHD.
A fourth retrospective study evaluated data from the same 95
patients in 19 stem cell transplant centers in Europe and the United
States. For long-term results, CR was defined as the absence of any
symptoms related to GVHD; PR was defined as the improvement of greater
than or equal to 1 in stage severity in one organ, without
deterioration in any other organ. A response had to last for at least
or more than 3 weeks. Of the 54 patients who had been diagnosed with
aGVHD, the 1-year overall survival (OS) rate was 62.4 percent (CI: 49.4
percent to 75.4 percent). The estimated median OS (50 percent death)
was 18 months for aGVHD patients. The median duration of
JAKAFITM treatment was 5 months. At follow-up, 22/54 (41
percent) of the patients had an ongoing response and were free of any
immunosuppression. Cytopenias (any grade) and CMV-reactivation were
observed during JAKAFITM-treatment (30/54, 55.6 percent and
18/54, 33.3 percent, respectively).
A fifth retrospective study evaluated 79 patients who received
treatment
[[Page 19352]]
using JAKAFITM for refractory GVHD at 13 centers in Spain.
Twenty-two patients had a diagnosis of aGVHD (Grades II to IV) and
received a median of 2 previous GVHD therapies (range, 1 to 5
therapies). The median daily dose of JAKAFITM was 20 mg. The
overall response rate was 68.2 percent, which was obtained after a
median of 2 weeks of treatment, and 18.2 percent (4/22) of the patients
reached CR. Overall, steroid doses were tapered in 72 percent of the
patients who had been diagnosed with aGVHD. Cytomegalovirus
reactivation was reported in 54.5 percent of the patients who had been
diagnosed with aGVHD. Overall, 26 patients (32.9 percent) discontinued
treatment using JAKAFITM due to: Lack of response (14),
cytopenias (3 patients had thrombocytopenia, 3 had anemia, and 3 had
both); infections (1 patient); other causes (2 patients). Ten deaths
occurred in patients who had been diagnosed with aGVHD.
We note the following concerns with respect to whether
JAKAFITM represents a substantial clinical improvement.
First, while the applicant has submitted data from several clinical
studies to support the efficacy of the use of JAKAFITM in
treatment of patients who have been diagnosed with steroid-resistant
aGVHD, including an overall response rate at Day 28 for 54.9 percent of
the patients enrolled in one study, with nearly half of the responding
patients achieving CR, the applicant has not provided any data directly
comparing the use of JAKAFITM to any second-line treatments.
As noted previously, a number of different agents can be used for
second-line treatment as described by recommendations from the American
Society of Blood and Marrow Transplantation (ASBMT).\303\ Numerous
combination approaches have been investigated for second-line therapy
for diagnoses of steroid-refractory aGVHD in allo-HSCT patients. These
studied agents include methotrexate, mycophenolate mofetil,
extracorporeal photopheresis, IL-2R targeting agents (basiliximab,
daclizumab, denileukin, and diftitox), alemtuzumab, horse antithymocyte
globulin, etancercept, infliximab, and sirolimus. Recommendations from
professional societies for the treatment of diagnoses of aGVHD describe
the lack of data demonstrating superior efficacy of any single agent as
second-line therapy for patients who have been diagnosed with steroid-
resistant aGVHD and, therefore, suggest that choice of second-line
treatment be guided by clinical considerations.\304\ Because the
applicant has not provided any data directly comparing the use of
JAKAFITM to any other second-line treatments (for example,
current standard-of-care), it may make it difficult to directly assess
whether the use of JAKAFITM provides a substantial clinical
improvement compared to these existing therapies.
---------------------------------------------------------------------------
\303\ Martin, P.J., Rizzo, J.D., Wingard, J.R., et al., ``First
and second-line systemic treatment of acute graft-versus-host
disease: recommendations of the American Society of Blood and Marrow
Transplantation,'' Biol Blood Marrow Transplant, 2012, vol. 18(8),
pp. 1150-1163.
\304\ Martin, P.J., Rizzo, J.D., Wingard, J.R., et al., ``First
and second-line systemic treatment of acute graft-versus-host
disease: recommendations of the American Society of Blood and Marrow
Transplantation,'' Biol Blood Marrow Transplant, 2012, vol. 18(8),
pp. 1150-1163.
---------------------------------------------------------------------------
Second, we have concerns regarding the methodologic approach of the
studies submitted by the applicant in support of its assertions
regarding substantial clinical improvement. While two of the clinical
studies provided by the applicant are prospective in nature, the other
three clinical studies provided in support of the application are
retrospective studies and, therefore, provide a weaker basis of
evidence for making conclusions of the causative effects of the drug
compared to prospective studies. Additionally, no blinding or
randomization occurred to minimize potential biases from the lack of a
control group, and no Phase III study data were submitted by the
applicant, to assist in our evaluation of substantial clinical
improvement. Although we acknowledge that the patient population that
would be eligible for treatment involving JAKAFITM under its
proposed indication is likely relatively small because it is a subset
of the patient population receiving allo-HSCTs, it may be difficult to
evaluate the impact of the technology on longer term outcomes, such as
overall survival and durability of response based on the studies
submitted because the clinical studies are based on relatively small
sample sizes.
Third, given the variable amount of detail provided on the studies
generally (for example, the number of patients from the United States,
how many are Medicare eligible and the results for these Medicare-
eligible patients, what specific first-line treatments enrolled
patients received and for what duration, how CRs and PRs were defined
and assessed, statistical methods and assumptions), it is more
difficult to fully assess the generalizability of the applicant's
assertions to the Medicare population.
Fourth, we note that several patients enrolled in each of the
studies provided by the applicant had safety-related complications,
including cytopenias and CMV reactivation. These complications are
concerning because the target population is already immunocompromised
and at risk of serious infections.
We are inviting public comments on whether JAKAFITM
meets the substantial clinical improvement criterion, including with
respect to the concerns we have raised.
We did not receive any written comments in response to the New
Technology Town Hall Meeting notice published in the Federal Register
regarding the substantial clinical improvement criterion for
JAKAFITM or at the New Technology Town Hall meeting.
o. Supersaturated Oxygen (SSO2) Therapy (DownStream[supreg]
System)
TherOx, Inc. submitted an application for new technology add-on
payments for Supersaturated Oxygen (SSO2) Therapy (the
DownStream[supreg] System) for FY 2020. We note that the applicant
previously submitted an application for new technology add-on payments
for FY 2019, which was withdrawn prior to the issuance of the FY 2019
IPPS/LTCH PPS final rule. The DownStream[supreg] System is an
adjunctive therapy that creates and delivers superoxygenated arterial
blood directly to reperfused areas of myocardial tissue which may be at
risk after an acute myocardial infarction (AMI), or heart attack.
SSO2 Therapy's proposed indication is for patients receiving
treatment for an ST-segment elevation myocardial infarction (STEMI), a
type of AMI where the anterior wall infarction impacts the left
ventricle (LV) and which carries a substantial risk of death and
disability. Elderly patients have an elevated risk of AMI, and the vast
majority of AMI occur in the Medicare population.\305\ The applicant
stated that the net effect of the SSO2 Therapy is to reduce
the size of the infarction and, therefore, lower the risk of heart
failure and mortality, as well as improve quality of life for STEMI
patients.
---------------------------------------------------------------------------
\305\ Wang, Y., Lichtman, J.H., Dharmarajan, K., Masoudi, F.A.,
Ross, J.S., Dodson, J.A., Chen, J., Spertus, J.A., Chaudhry, S.I.,
Nallamothu, B.K., Krumholz, H.M., 2014, ``National trends in stroke
after acute myocardial infarction among Medicare patients in the
United States: 1999 to 2010,'' American Heart Journal, vol. 169(1),
pp. 78-85.e4.
---------------------------------------------------------------------------
SSO2 Therapy consists of three main components: The
DownStream[supreg] System; the DownStream cartridge; and the
SSO2 delivery catheter. The DownStream[supreg] System and
cartridge function together to create an oxygen-enriched saline
solution called SSO2 solution from hospital-supplied oxygen
and physiologic saline. A small amount of
[[Page 19353]]
the patient's blood is then mixed with the SSO2 solution,
producing oxygen-enriched hyperoxemic blood, which is delivered to the
left main coronary artery (LMCA) via the delivery catheter at a flow
rate of 100 ml/min. The duration of the SSO2 Therapy is 60
minutes and the infusion is performed in the catheterization
laboratory. The oxygen partial pressure (pO2) of the
infusion is elevated to ~1,000 mmHg, therefore providing oxygen locally
to the myocardium at a hyperbaric level for 1 hour. After the 60-minute
SSO2 infusion is complete, the cartridge is unhooked from
the patient and discarded per standard practice. Coronary angiography
is performed as a final step before removing the delivery catheter and
transferring the patient to the intensive care unit (ICU).
The applicant for the SSO2 Therapy received premarket
approval from the FDA on April 4, 2019. The applicant stated that use
of the SSO2 Therapy can be identified by the ICD-10-PCS
procedure codes 5A0512C (Extracorporeal supersaturated oxygenation,
intermittent) and 5A0522C (Extracorporeal supersaturated oxygenation,
continuous).
As discussed earlier, if a technology meets all three of the
substantial similarity criteria, it would be considered substantially
similar to an existing technology and would not be considered ``new''
for purposes of new technology add-on payments. The applicant
identified three treatment options currently available to restore
coronary artery blood flow in AMI patients. These options are
fibronolytic therapy (plasminogen activators) with or without
glycoprotein IIb/IIIa inhibitors, percutaneous coronary intervention
(PCI) with or without stent placement, and coronary artery bypass graft
(CABG). The applicant noted that all of these therapies restore blood
flow at the macrovascular level by targeting the coronary artery
thrombosis that is the direct cause of the AMI. The applicant also
noted that PCI with stenting is the preferred treatment for STEMI
patients. The applicant asserted that SSO2 Therapy is not
substantially similar to these existing treatment options and,
therefore, meets the newness criterion. Below we summarize the
applicant's assertions with respect to whether the SSO2
Therapy meets each of the three substantial similarity criteria.
With regard to the first criterion, whether a product uses the same
or a similar mechanism of action to achieve a therapeutic outcome, the
applicant asserted that SSO2 Therapy is a unique therapy
designed to deliver localized hyperbaric oxygen equivalent to the
coronary arteries immediately after administering the standard-of-care,
PCI with stenting. The applicant describes SSO2 Therapy's
mechanism of action as two-fold: (1) First, the increased oxygen levels
act to re-open the microcirculatory system within the infarct zone,
which has experienced ischemia during the occlusion period, and (2)
second, once the microcirculatory system is re-opened, the blood flow
containing the additional oxygen re-starts metabolic processes within
the stunned myocardium. According to the applicant, the net result is
to reduce the extent of necrosis as measured by infarct size in the
myocardium post-AMI and thereby improve left ventricular function,
leading to improved patient outcomes. The applicant maintained that
this mechanism of action is not comparable to that of any existing
treatment because no other therapy has demonstrated an infarct size
reduction over and above the routine delivery of PCI. As mentioned
above, the applicant asserted that currently available therapies
restore blood flow at the macrovascular level by targeting the coronary
artery thrombosis that is the direct cause of the AMI.
With respect to the second criterion, whether a product is assigned
to the same or a different MS-DRG, the applicant reiterated that the
standard procedure for treating patients with AMI is PCI with stent
placement, and that these cases are typically assigned to MS-DRG 246
(Percutaneous Cardiovascular Procedures with Drug-Eluting Stent with
MCC or 4+ Arteries/Stents), MS-DRG 247 (Percutaneous Cardiovascular
Procedures with Drug-Eluting Stent without MCC), MS-DRG 248
(Percutaneous Cardiovascular Procedures with Non-Drug-Eluting Stent
with MCC or 4+ Arteries/Stents), MS-DRG 249 (Percutaneous
Cardiovascular Procedures with Non-Drug-Eluting Stent without MCC), MS-
DRG 250 (Percutaneous Cardiovascular Procedures without Coronary Artery
Stent with MCC), or MS-DRG 251 (Percutaneous Cardiovascular Procedures
without Coronary Artery Stent without MCC). The applicant maintained
that because no other technologies exist that can deliver localized
hyperbaric oxygen in the acute care setting, SSO2 Therapy
has no analogous MS-DRG assignment. However, we note that potential
cases that may be eligible for treatment involving SSO2
Therapy may be assigned to the same MS-DRG(s) as other cases involving
PCI with stent placement also used to treat patients who have been
diagnosed with AMI.
With respect to the third criterion, whether the new use of the
technology involves the treatment of the same or similar type of
disease and the same or similar patient population, according to the
applicant, the target patient population of SSO2 Therapy is
patients who are receiving treatment after a diagnosis of AMI and
specifically ST-segment elevation myocardial infarction (STEMI) where
the anterior wall infarction impacts the left ventricle (LV). The
applicant acknowledged that, because SSO2 Therapy is
administered following completion of successful PCI, its target patient
population includes a subset of patients with the same or similar type
of disease process as patients treated with PCI with stent placement.
However, the applicant also asserted that, while PCI with stenting
achieves the goal of re-opening a blocked artery, SSO2
Therapy delivers localized hyperbaric oxygen to reduce the extent of
the myocardial necrosis that occurs as a consequence of experiencing
AMI. Therefore, the applicant believed that SSO2 Therapy
offers a treatment option for a different type of disease than
currently available treatments.
We are inviting public comments on whether the SSO2
Therapy is substantially similar to existing technologies and whether
it meets the newness criterion.
With regard to the cost criterion, the applicant conducted the
following analysis to demonstrate that SSO2 Therapy meets
the cost criterion. The applicant searched the FY 2017 MedPAR file for
claims reporting diagnoses of anterior STEMI by ICD-10-CM diagnosis
codes I21.0 (ST elevation myocardial infarction of anterior wall),
I21.01 (ST elevation (STEMI) myocardial infarction involving left main
coronary artery), I21.02 (ST elevation (STEMI) myocardial infarction
involving left anterior descending coronary artery), or I21.09 (ST
elevation (STEMI) myocardial infarction involving other coronary artery
of anterior wall) as a primary diagnosis, which the applicant believed
would describe potential cases representing potential patients who may
be eligible for treatment involving the SSO2 Therapy. The
applicant identified 11,668 cases mapping to 4 MS-DRGs, with
approximately 91 percent of all potential cases mapping to MS-DRG 246
(Percutaneous Cardiovascular Procedures with Drug-Eluting Stent with
MCC or 4+ Arteries/Stents) and MS-DRG 247 (Percutaneous Cardiovascular
Procedures with Drug-Eluting Stent without MCC). The remaining 9
percent of potential cases
[[Page 19354]]
mapped to MS-DRG 248 (Percutaneous Cardiovascular Procedures with Non-
Drug-Eluting Stent with MCC or 4+ Arteries/Stents) and MS-DRG 249
(Percutaneous Cardiovascular Procedures with Non-Drug-Eluting Stent
without MCC).
The applicant determined that the average case-weighted
unstandardized charge per case was $98,846. The applicant then
standardized the charges. The applicant did not remove charges for the
current treatment because, as discussed above, SSO2 Therapy
would be used as an adjunctive treatment option following successful
PCI with stent placement. The applicant then added charges for the
technology, which accounts for the use of 1 cartridge per patient, to
the average charges per case. The applicant did not apply an inflation
factor to the charges for the technology. The applicant also added
charges related to the technology, to account for the additional
supplies used in the administration of SSO2 Therapy, as well
as 70 minutes of procedure room time, including technician labor and
additional blood tests. The applicant inflated the charges related to
the technology. Based on the FY 2019 IPPS/LTCH PPS final rule
correction notice data file thresholds, the average case-weighted
threshold amount was $96,267. In the applicant's analysis, the inflated
average case-weighted standardized charge per case was $144,364.
Because the inflated average case-weighted standardized charge per case
exceeds the average case-weighted threshold amount, the applicant
maintained that the technology meets the cost criterion.
We are inviting public comments on whether the SSO2
Therapy meets the cost criterion.
With regard to the substantial clinical improvement criterion, the
applicant asserted that SSO2 Therapy represents a
substantial clinical improvement over existing technologies because it
improves clinical outcomes for STEMI patients as compared to the
currently available standard-of-care treatment, PCI with stenting
alone. Specifically, the applicant asserted that: (1) Infarct size
reduction improves mortality outcomes; (2) infarct size reduction
improves heart failure outcomes; (3) SSO2 Therapy
significantly reduces infarct size; (4) SSO2 Therapy
prevents left ventricular dilation; and (5) SSO2 Therapy
reduces death and heart failure at 1 year. The applicant highlighted
the importance of the SSO2 Therapy's mechanism of action,
which treats hypoxemic damage at the microvascular or microcirculatory
level. Specifically, the applicant noted that microvascular impairment
in the myocardium is irreversible and leads to a greater extent of
infarction. According to the applicant, the totality of the data on
myocardial infarct size, ventricular remodeling, and clinical outcomes
strongly supports the substantial clinical benefit of SSO2
Therapy administration over the standard-of-care.
To support the claims that infarct size reduction improves
mortality and heart failure outcomes, the applicant cited an analysis
of the Collaborative Organization for RheothRx Evaluation (CORE) trial
and a pooled patient-level analysis.
The CORE trial was a prospective, randomized, double-
blinded, placebo-controlled trial of Poloxamer 188, a novel therapy
adjunctive to thrombolysis at the time the study was conducted.\306\
The applicant sought to relate left ventricular ejection fraction (EF),
end-systolic volume index (ESVI) and infarct size (IS), as measured in
a single, randomized trial, to 6-month mortality after myocardial
infarction treated with thrombolysis. According to the applicant,
subsets of clinical centers participating in CORE also participated in
one or two radionuclide sub-studies: (1) Angiography for measurement of
EF and absolute, count-based LV volumes; and (2) single-photon emission
computed tomographic sestamibi measurements of IS. These sub-studies
were performed in 1,194 and 1,181 patients, respectively, of the 2,948
patients enrolled in the trial. Furthermore, ejection fraction, ESVI,
and IS, as measured by central laboratories in these sub-studies, were
tested for their association with 6-month mortality. According to the
applicant, the results of the study showed that ejection fraction
(n=1,137; p=0.0001), ESVI (n=945; p=0.055) and IS (n=1,164; p=0.03)
were all associated with 6-month mortality, therefore, demonstrating
the relationship between these endpoints and mortality.\307\
---------------------------------------------------------------------------
\306\ Burns, R.J., Gibbons, R.J., Yi, Q., et al., ``The
relationships of left ventricular ejection fraction, end-systolic
volume index and infarct size to six-month mortality after hospital
discharge following myocardial infarction treated by thrombolysis,''
J Am Coll Cardiol, 2002, vol. 39, pp. 30-6.
\307\ Ibid.
---------------------------------------------------------------------------
The pooled patient-level analysis was performed from 10
randomized, controlled trials (with a total of 2,632 patients) that
used primary PCI with stenting.\308\ The analysis assessed infarct size
within 1 month after randomization by either cardiac magnetic resonance
(CMR) imaging or technetium-99m sestamibi single-photon emission
computed tomography (SPECT), with clinical follow-up for 6 months.
Infarct size was assessed by CMR in 1,889 patients (71.8 percent of
patients) and by SPECT in 743 patients (28.2 percent of patients)
including both inferior wall and more severe anterior wall STEMI
patients. According to the applicant, median infarct size (or percent
of left ventricular myocardial mass) was 17.9 percent and median
duration of clinical follow-up was 352 days. The Kaplan-Meier estimated
1-year rates of all-cause mortality, re-infarction, and HF
hospitalization were 2.2 percent, 2.5 percent, and 2.6 percent,
respectively. The applicant noted that a strong graded response was
present between infarct size (per 5 percent increase) and the 2 outcome
measures of subsequent mortality (Cox-adjusted hazard ratio: 1.19 [95
percent confidence interval: 1.18 to 1.20]; p2 Therapy
significantly reduces infarct size, the applicant cited the AMIHOT I
and II studies.
The AMIHOT I clinical trial was designed as a prospective,
randomized evaluation of patients who had been diagnosed with AMI,
including both anterior and inferior patients, and received treatment
with either PCI with stenting alone or with SSO2 Therapy as
an adjunct to successful PCI within 24 hours of symptom onset.\310\ The
study included 269 randomized patients and 3 co-primary endpoints:
Infarction size reduction, regional wall motion score improvement at 3
months, and reduction in ST segment elevation. The study was designed
to demonstrate superiority of the SSO2 Therapy group as
compared to the control group for each of these endpoints, as well as
to demonstrate non-inferiority of the SSO2 Therapy group
with respect to 30-day Major Adverse Cardiac Event (MACE). The
applicant stated that results for the control versus SSO2
Therapy group
[[Page 19355]]
comparisons for the three co-primary effectiveness endpoints
demonstrated a nominal improvement in the test group, although this
nominal improvement did not achieve clinical and statistical
significance in the entire population. The applicant further stated
that a pre-specified analysis of the SSO2 Therapy patients
who were revascularized within 6 hours of AMI symptom onset and who had
anterior wall infarction showed a marked improvement in all 3 co-
primary endpoints as compared to the control group.\311\ Key safety
data revealed no statistically significant differences in the composite
primary endpoint of 1-month (30 days) MACE rates between the
SSO2 Therapy and control groups. MACE includes the combined
incidence of death, re-infarction, target vessel revascularization, and
stroke. In total, 9/134 (6.7 percent) of the patients in the
SSO2 Therapy group and 7/135 (5.2 percent) of the patients
in the control group experienced 30-day MACE (p=0.62).\312\
---------------------------------------------------------------------------
\310\ O'Neill, W.W., Martin, J.L., Dixon, S.R., et al., ``Acute
Myocardial Infarction with Hyperoxemic Therapy (AMIHOT), J Am Coll
Cardiol, 2007, vol. 50(5), pp. 397-405.
\311\ Ibid.
\312\ Ibid.
---------------------------------------------------------------------------
The AMIHOT II trial randomized 301 patients who had been
diagnosed with and receiving treatment for anterior AMI with either PCI
plus the SSO2 Therapy or PCI alone.\313\ The AMIHOT II trial
had a Bayesian statistical design that allows for the informed
borrowing of data from the previously completed AMIHOT I trial. The
primary efficacy endpoint of the study required proving superiority of
the infarct size reduction, as assessed by Tc-99m Sestamibi SPECT
imaging at 14 days post PCI/stenting, with the use of SSO2
Therapy as compared to patients who were receiving treatment involving
PCI with stenting alone. The primary safety endpoint for the AMIHOT II
trial required a determination of non-inferiority in the 30-day MACE
rate, comparing the SSO2 Therapy group with the control
group, within a safety delta of 6.0 percent.\314\ Endpoint evaluation
was performed using a Bayesian hierarchical model that evaluated the
AMIHOT II result conditionally in consideration of the AMIHOT I 30-day
MACE data. According to the applicant, the results of the AMIHOT II
trial showed that the use of SSO2 therapy, together with PCI
and stenting, demonstrated a relative reduction of 26 percent in the
left ventricular infarct size and absolute reduction of 6.5 percent
compared to PCI and stenting alone.\315\
---------------------------------------------------------------------------
\313\ Stone, G.W., Martin, J.L., de Boer, M.J., et al., ``Effect
of Supersaturated Oxygen Delivery on Infarct Size after Percutaneous
Coronary Intervention in Acute Myocardial Infarction,'' Circ
Cardiovasc Intervent, 2009, vol. 2, pp. 366-75.
\314\ Ibid.
\315\ Ibid.
---------------------------------------------------------------------------
Next, to support the claim that SSO2 Therapy prevents
left ventricular dilation, the applicant cited the Leiden study, which
represents a single-center, sub-study of AMIHOT I patients treated at
Leiden University in the Netherlands. The study describes outcomes of
randomized selective treatment with intracoronary aqueous oxygen (AO),
the therapy delivered by SSO2 Therapy, versus standard care
in patients who had acute anterior wall myocardial infarction within 6
hours of onset. Of the 50 patients in the sub-study, 24 received
treatment using adjunctive AO and 26 were treated according to standard
care after PCI, with no significant differences in baseline
characteristics between groups. LV volumes and function were assessed
by contrast echocardiography at baseline and 1 month. According to the
applicant, the results demonstrated that treatment with aqueous oxygen
prevents LV remodeling, showing a reduction in LV volumes (3 percent
decrease in LV end-diastolic volume and 11 percent decrease in LV end-
systolic volume) at 1 month as compared to baseline in AO-treated
patients, as compared to increasing LV volumes (14 percent increase in
LV end diastolic volume and 18 percent increase in LV end-systolic
volume) at 1 month in control patients.\316\ The results also show that
treatment using AO preserves LV ejection fraction at 1 month, with AO-
treated patients experiencing a 10 percent increase in LV ejection
fraction as compared to a 2 percent decrease in LV ejection fraction
among patients in the control group.\317\
---------------------------------------------------------------------------
\316\ Warda, H.M., Bax, J.J., Bosch, J.G., et al., ``Effect of
intracoronary aqueous oxygen on left ventricular remodeling after
anterior wall ST-elevation acute myocardial infarction,'' Am J
Cardiol, 2005, vol. 96(1), pp. 22-4.
\317\ Ibid.
---------------------------------------------------------------------------
Finally, to support the claim that SSO2 Therapy reduces
death and heart failure at 1 year, the applicant submitted the results
from the IC-HOT clinical trial, which was designed to confirm the
safety and efficacy of the use of the SSO2 Therapy in those
individuals presenting with a diagnosis of anterior AMI who have
undergone successful PCI with stenting of the proximal and/or mid left
anterior descending artery within 6 hours of experiencing AMI symptoms.
It is an IDE, nonrandomized, single arm study. The study primarily
focused on safety, utilizing a composite endpoint of 30-day Net Adverse
Clinical Events (NACE). A maximum observed event rate of 10.7 percent
was established based on a contemporary PCI trial of comparable
patients who had been diagnosed with anterior wall STEMI. The results
of the IC-HOT trial exhibited a 7.1 percent observed NACE rate, meeting
the study endpoint. Notably, no 30-day mortalities were observed, and
the type and frequency of 30-day adverse events occurred at similar or
lower rates than in contemporary STEMI studies of PCI-treated patients
who had been diagnosed with anterior AMI.\318\ Furthermore, according
to the applicant, the results of the IC-HOT study supported the
conclusions of effectiveness established in AMIHOT II with a measured
30-day median infarct size = 19.4 percent (as compared to the AMIHOT II
SSO2 Therapy group infarct size = 20.0 percent).\319\ The
applicant stated that notable measures include 4-day microvascular
obstruction (MVO), which has been shown to be an independent predictor
of outcomes, 4-day and 30-day left ventricular end diastolic and end
systolic volumes, and 30-day infarct size.\320\ The applicant also
stated that the IC-HOT study results exhibited a favorable MVO as
compared to contemporary trial data, and decreasing left ventricular
volumes at 30 days, compared to contemporary PCI populations that
exhibit increasing left ventricular size.\321\ The applicant asserted
that the IC-HOT clinical trial data continue to demonstrate the
substantial clinical benefit of the use of SSO2 Therapy as
compared to the standard-of-care, PCI with stenting alone.
---------------------------------------------------------------------------
\318\ David, SW, Khan, Z.A., Patel, N.C., et al., ``Evaluation
of intracoronary hyperoxemic oxygen therapy in acute anterior
myocardial infarction: The IC-HOT study,'' Catheter Cardiovasc
Interv, 2018, pp. 1-9.
\319\ Ibid.
\320\ Ibid.
\321\ Ibid.
---------------------------------------------------------------------------
The applicant also performed controlled studies in both porcine and
canine AMI models to determine the safety, effectiveness, and mechanism
of action of the SSO2 Therapy.322 323 According
to the applicant, the key summary points from these animal studies are:
---------------------------------------------------------------------------
\322\ Spears, J.R., Henney, C., Prcevski, P., et al., ``Aqueous
Oxygen Hyperbaric Reperfusion in a Porcine Model of Myocardial
Infarction,'' J Invasive Cardiol, 2002, vol. 14(4), pp. 160-6.
\323\ Spears, J.R., Prcevski, P., Xu, R., et al., ``Aqueous
Oxygen Attenuation of Reperfusion Microvascular Ischemia in a Canine
Model of Myocardial Infarction,'' ASAIO J, 2003, vol. 49(6), pp.
716-20.
---------------------------------------------------------------------------
SSO2 Therapy administration post-AMI acutely
improves heart function as measured by left ventricular ejection
fraction (LVEF) and regional wall
[[Page 19356]]
motion as compared with non-treated control subjects.
SSO2 Therapy administration post-AMI results in
tissue salvage, as determined by post-sacrifice histological
measurements of the infarct size. Control animals exhibit larger
infarcts than the SSO2-treated animals.
SSO2 Therapy has been shown to be non-toxic to
the coronary arteries, myocardium, and end organs in randomized,
controlled swine studies with or without induced acute myocardial
infarction.
SSO2 Therapy administration post-AMI has
exhibited regional myocardial blood flow improvement in treated animals
as compared to controls.
A significant reduction in myeloperoxidase (MPO) levels in
the SSO2-treated animals versus controls, which indicate
improvement in underlying myocardial hypoxia.
Transmission electron microscopy (TEM) photographs showing
amelioration of endothelial cell edema and restoration of capillary
patency in ischemic zone cross-sectional histological examination of
the SSO2-treated animals, while non-treated controls exhibit
significant edema and vessel constriction at the microvascular level.
We have the following concerns regarding whether the technology
meets the substantial clinical improvement criterion. We note that the
standard-of-care for STEMI has evolved since the AMIHOT I and AMIHOT II
studies were conducted, such that it is unclear whether use of
SSO2 Therapy would demonstrate the same clinical improvement
as compared to the current standard-of-care. We also note that the
AMIHOT II study used SPECT infarct size data 14 days post-MI for
efficacy and MACE events (including death, re-infarction,
revascularization, and stroke) by 30 days post-MI for safety. We are
concerned that there is no long-term data to demonstrate the validity
of these statistics, and that infarct size has not been completely
validated as a surrogate marker for the combination of PCI plus
SSO2. With respect to the IC-HOT study, we are concerned
that the lack of a control may limit the interpretation of the data. We
also are concerned that the safety data (death, re-infarction, re-
vascularization, stent thrombosis, severe heart failure, and bleeding)
for the IC-HOT study were limited to the 30 days post-MI, with no long-
term data being available.
We are inviting public comments on whether the SSO2
Therapy meets the substantial clinical improvement criterion, including
with respect to whether the results of the AMIHOT I and AMIHOT II
studies remain valid given the advancements in STEMI care since these
trials were conducted, and the availability of long-term data to
validate the efficacy and safety data of the AMIHOT II and IC-HOT
studies.
We did not receive any written comments in response to the New
Technology Town Hall meeting notice published in the Federal Register
regarding the substantial clinical improvement criterion for the
SSO2 Therapy or at the New Technology Town Hall meeting.
p. T2Bacteria[supreg] Panel (T2 Bacteria Test Panel)
T2 Biosystems, Inc. submitted an application for new technology
add-on payments for the T2 Bacteria Test Panel (T2Bacteria[supreg]
Panel) for FY 2020. According to the applicant, the T2Bacteria[supreg]
Panel is indicated as an aid in the diagnosis of bacteremia, bacterial
presence in the blood which is a precursor for sepsis. It is a
multiplex diagnostic panel that detects five major bacterial pathogens
(Enterococcus faecium, Escherichia coli, Klebsiella pneumoniae,
Pseudomonas aeruginosa, and Staphylococcus aureus) associated with
sepsis. According to the applicant, the T2Bacteria[supreg] Panel is
capable of detecting bacterial pathogens directly in whole blood more
rapidly and with greater sensitivity as compared to the current
standard-of-care, blood culture. The applicant noted that the
T2Bacteria[supreg] Panel's major detected species are five of the most
common and virulent sepsis-causing organisms.324 325 The
applicant asserted that, by enabling the rapid administration of
species-specific antimicrobial therapies, the T2Bacteria[supreg] Panel
helps to reduce patients' hospital lengths-of-stay and substantially
improves clinical outcomes. Furthermore, the applicant asserted that
the T2Bacteria[supreg] Panel helps to reduce the overuse of ineffective
or unnecessary antimicrobial therapy, reducing patient side effects,
lowering hospital costs, and potentially counteracting the growing
resistance to antimicrobial therapy.
---------------------------------------------------------------------------
\324\ Boucher, H., Talbot, G., Bradley, J., Edwards, J.,
Gilbert, D., Rice, L., Bartlett, J., ``Bad Bugs, No Drugs: No
ESKAPE! An update from the infectious disease society of America,''
Clinical Infectious Diseases, 2009, vol. 48, pp. 1-12, doi:10.1086/
595011.
\325\ Rice, L., ``Federal Funding for the Study of Antimicrobial
Resistance in Nosocomial Pathogens: No ESKAPE,'' Journal of
Infectious Diseases, 2008, vol. 197, pp. 1079-1081, doi:10.1086/
533452.
---------------------------------------------------------------------------
The applicant stated that the T2Bacteria[supreg] Panel runs on the
T2Dx Instrument, which is a bench-top diagnostic instrument that
utilizes developments in magnetic resonance and nanotechnology to
detect pathogens directly in whole blood, plasma, serum, saliva, sputum
and urine at limits of detection as low as one colony forming unit per
milliliter. The applicant explained that the T2Dx breaks down red blood
cells, concentrates microbial cells and cellular debris, amplifies DNA
using a thermostable polymerase and target-specific primers, and
detects amplified product by amplicon-induced agglomeration of
supermagnetic particles and T2MR measurement.\326\ To perform a
diagnostic test, the patient's sample tube is snapped onto the
disposable test cartridge, which is pre-loaded with all necessary
reagents. The cartridge is then inserted into the T2Dx, which
automatically processes the sample and then delivers a diagnostic test
result. The applicant asserted that each test panel is comprised of a
test cartridge and a reagent tray and that each are required to run the
T2Bacteria[supreg] Test Panel.
---------------------------------------------------------------------------
\326\ Clancy, C., & Nguyen, H., ``T2 magnetic resonance for the
diagnosis of bloodstream infections: charting a path forward,''
Journal of Antimicrobial Chemotherapy, 2018, vol. 73(4), pp. iv2-
iv5, doi:10.1093/jac/dky050.
---------------------------------------------------------------------------
As stated above, the current standard-of-care for identifying
bacterial bloodstream infections that cause sepsis is a blood culture.
The applicant explained that blood culture diagnostics have many
limitations, beginning with a series of time and labor intensive
analyses. According to the applicant, completing a blood culture
requires typically 20 mLs or more of a patient's blood, which is
obtained in two 10 mL draws and placed into two blood culture bottles
containing nutrients formulated to grow bacteria. The applicant
explained that before the blood culture indicates if a patient is
infected, pathogens typically must reach a concentration of 1,000,000
to 100,000,000 CFU/mL in the blood specimen. This growth process
typically takes 1 to 6 or more days because the pathogen's initial
concentration in the blood specimen is often less than 10 CFU/mL. The
applicant stated that a typical blood culture provides a result in a 2
to 4 day timeframe for species ID and yields 50 to 65 percent clinical
sensitivity.327 328 According to the applicant, a recent
retrospective analysis of 13 U.S. hospitals and over
[[Page 19357]]
150,000 cultures found a median blood culture time for species ID of 43
hours.\329\
---------------------------------------------------------------------------
\327\ Clancy, C., & Nguyen, M. H., ``Finding the ``Missing 50%''
of Invasive Candidiasis: How nonculture Diagnostics will improve
understanding of disease spectrum and transform patient care,''
Clinical Infectious Diseases, 2013, vol. 56(9), pp. 1284-1292,
doi:10.1093/cid/cit006.
\328\ Cockerill, F., Wilson, J., Vetter, E., Goodman, K.,
Torgerson, C., Harmsen, W., Wilson, W., ``Optimal Testing Parameters
for Blood Cultures,'' Clinical Infectious Diseases, 2004, vol. 38,
pp. 1724-1730.
\329\ Tabak, Y., Vankeepuram, L., Ye, G., Jeffers, K., Gupta,
V., & Murray, P., ``Blood Culture Turanaround Time in US Acute Care
Hospitals and Implications for Laboratory Process Optimization,''
Journal of Clinical Microbiology, August 2018, pp. 1-15.
---------------------------------------------------------------------------
According to the applicant, blood cultures provide results at
multiple stages. A negative test result requires a minimum of 5 days
for blood cultures. A positive blood culture typically means that some
pathogen is present, but additional steps must be performed to identify
the specific pathogen and provide targeted therapy. The applicant
submitted data stating that during the T2Bacteria[supreg] Panel's
pivotal study, blood cultures took an average of 63.2 hours (off
T2Bacteria[supreg] Panel) and 38.5 hours (on T2Bacteria[supreg] Panel)
to obtain positive results and 96.0 hours (off T2Bacteria[supreg]
Panel) and 71.7 hours (on T2Bacteria[supreg] Panel) to achieve species
identification.\330\ The applicant stated that, given this length of
time to species identification, the first therapy for a patient at risk
of sepsis is often broad-spectrum antibiotics, which treats some, but
not all bacteria types. In addition, the applicant indicated that the
time to species identification in blood culture diagnostics causes
delays in administration of species-specific targeted therapies,
increasing hospital lengths-of-stay and risk of death.
---------------------------------------------------------------------------
\330\ T2 Biosystems, Inc., ``T2Bacteria[supreg] Panel for use on
the T2Dx[supreg] Instrument, 510(k) summary,'' Lexington, 2018.
---------------------------------------------------------------------------
With respect to the newness criterion, the applicant filed a
section 510(k) premarket notification with the FDA on September 8, 2017
for the T2Bacteria[supreg] Panel. According to the applicant, the
T2Bacteria[supreg] Panel received FDA 510(k) clearance on May 24, 2018,
based on a determination of substantial equivalence to a legally
marketed predicate device. The applicant noted that the
T2Bacteria[supreg] Panel has a very broad application in the inpatient
hospital setting and, as a result, potential cases available for use of
the T2Bacteria[supreg] Panel may be identified by thousands of ICD-10-
CM diagnosis codes. We note that the applicant has submitted a request
to the ICD-10 Coordination and Maintenance Committee for approval for a
unique ICD-10-PCS procedure code, effective in FY 2020, to describe
procedures which use the T2Bacteria[supreg] Panel. Currently, there are
no ICD-10-PCS procedure codes to uniquely identify procedures involving
the use of the T2Bacteria[supreg] Panel.
As discussed above, if a technology meets all three of the
substantial similarity criteria, it would be considered substantially
similar to an existing technology and would not be considered ``new''
for purposes of new technology add-on payments.
With regard to the first criterion, whether a product uses the same
or a similar mechanism of action to achieve a therapeutic outcome, the
applicant asserted that the T2Bacteria[supreg] Panel: (1) Has a
different mechanism of action when compared to the current standard-of-
care for the diagnosis of bacterial pathogens directly from whole
blood; and (2) is designed to achieve a different therapeutic outcome
when compared to the other diagnostic test panel that is based on the
same technological diagnostic platform. Specifically, the applicant
asserted that the standard-of-care blood culture is a laboratory test
in which blood, taken from the patient, is inoculated into bottles
containing culture media and incubated over a period of time to
determine whether infection-causing micro-organisms (bacteria or fungi)
are present in the patient's bloodstream. In contrast, the applicant
stated that the T2Bacteria[supreg] Panel relies on developments in
magnetic resonance and nanotechnology to determine the presence of
bacterial pathogens in a patient's blood by exploiting the physics of
magnetic resonance. Furthermore, the applicant indicated that the only
other product on the U.S. market that uses the same or similar
mechanism of action as the T2Bacteria[supreg] Panel is the T2Candida
Panel, which detects five clinically relevant species of Candida, a
fungal pathogen known to cause sepsis. However, the applicant noted
that the T2Candida Panel achieves a different therapeutic outcome than
the T2Bacteria[supreg] Panel, which is the diagnostic aid in the
treatment of sepsis caused by fungal infections in the blood.
With regard to the second criterion, whether the technology is
assigned to the same or different MS-DRG, the applicant did not
comment. However, we believe that cases involving the use of the
technology would be assigned to the same MS-DRGs as cases involving the
current standard-of-care laboratory blood cultures.
With respect to the third criterion, whether the new use of the
technology involves the treatment of the same or similar type of
disease and the same or similar patient population, according to the
applicant, the T2Bacteria[supreg] Panel would be used as a diagnostic
aid in the treatment of similar diseases and patient populations as the
current standard-of-care laboratory blood cultures.
We are concerned that the mechanism of action of the
T2Bacteria[supreg] Test Panel may be similar to the mechanism of action
used by the current standard-of-care laboratory blood cultures or other
available diagnostic tests. While the applicant states that the
technology has a different mechanism of action because its differs from
the standard-of-care, blood cultures, we note that like other available
diagnostic tests, the T2Bacteria[supreg] Test Panel uses DNA to
identify bacterial species. Similarly, in order to obtain species
identification from the current standard-of-care, blood cultures, a DNA
test is also required. Therefore, we are concerned with the similarity
of this mechanism of action. We are inviting public comments on whether
the T2Bacteria[supreg] Test Panel is substantially similar to the
standard-of-care laboratory blood cultures or other diagnostic tests
and whether this technology meets the newness criterion.
With regard to the cost criterion, the applicant provided the
following analysis. To identify the MS-DRGs to which potential cases
available for use of the T2Bacteria[supreg] Panel would most likely
map, a selection of ICD-10-CM diagnosis codes associated with the
clinical presence of the on-panel sepsis-causing bacteria for which the
T2Bacteria[supreg] Test Panel tests was
identified.331 332 333 334 335 The applicant asserted that
the T2Bacteria[supreg] Test Panel can identify three Gram-negative
blood
[[Page 19358]]
stream infections (Escherichia coli, Klebsiella pneumoniae, Pseudomonas
aeruginosa) and two Gram-positive bloodstream infection species
(Staphylococcus aureus, and Enterococcus faecium). A total of 67 ICD-
10-CM diagnosis codes were identified and segmented by two categories,
infections (39 codes) and sepsis (28 codes). The applicant asserted
that the former category represents potential cases available to be
diagnosed by the T2Bacteria[supreg] Panel for patients who are at risk
for sepsis and the latter represents potential cases available for use
of the T2Bacteria[supreg] Panel for patients who have been diagnosed
with a confirmed sepsis. The applicant stated that distinguishing
between the two was necessary due to the varying costs associated with
the treatment of patients at risk for sepsis versus confirmed cases of
sepsis.
---------------------------------------------------------------------------
\331\ Calderwood, S., ``Clinical manifestations, diagnosis and
treatment of enterohemorrhagic Escherichia coli (EHEC) infection,''
September 2017. Available at: https://www.uptodate.com/contents/clinical-manifestations-diagnosis-and-treatment-of-enterohemorrhagic-escherichia-coli-ehec-infection.
\332\ Yu, W.L., & Chuang, Y.C., ``Clinical features, diagnosis,
and treatment of Klebsiella pneumoniae infection,'' May 18, 2017.
Available at: https://www.uptodate.com/contents/clinical-features-
diagnosis-and-treatment-of-klebsiella-pneumoniae-
infection?search=Klebsiella%20pneumoniae&source=search_result&selecte
dTitle=1~150&usage_type=default&display_rank=1.
\333\ Kanj, S., & Sexton, D., ``Epidemiology, microbiology, and
pathogenesis of Pseudomonas aeruginosa infection,'' October 9, 2018.
Available at: https://www.uptodate.com/contents/epidemiology-
microbiology-and-pathogenesis-of-pseudomonas-aeruginosa-
infection?search=Pseudomonas%20aeruginosa&source=search_result&select
edTitle=2~150&usage_type=default&display_rank=2.
\334\ Holland, T., & Fowler, V., ``Clinical manifestations of
Staphylococcus aureus infection in adults,'' September 22, 2017.
Available at: https://www.uptodate.com/contents/clinical-
manifestations-of-staphylococcus-aureus-infection-in-
adults?search=Staphylococcus%20aureus&source=search_result&selectedTi
tle=3~150&usage_type=default&display_rank=3.
\335\ Murray, B., ``Microbiology of enterococci,'' August 31,
2017. Available at: https://www.uptodate.com/contents/microbiology-
of-
enterococci?search=Enterococcus%20faecium&source=search_result&select
edTitle=2~21&usage_type=default&display_rank=2.
---------------------------------------------------------------------------
After the identification of the 39 infection and 28 sepsis
diagnosis codes, both selections were refined by the applicant with the
removal of cases identified by a total of 15 codes that represent
pathogens not within the spectrum of blood infections that the
T2Bacteria[supreg] Panel has been tested with and/or has been confirmed
to detect. From the infection diagnosis codes, cases identified by two
ICD-10-CM diagnosis codes: A021 (Salmonella sepsis); and A227 (Anthrax
sepsis) were removed. From the sepsis diagnosis codes, cases identified
by 13 diagnosis codes were removed: A021 (Salmonella sepsis); A227
(Anthrax sepsis); A400 (Sepsis due to streptococcus, group A); A401
(Sepsis due to streptococcus, group B); A403 (Sepsis due to
streptococcus pneumonia); A408 (Other streptococcal sepsis); A409
(Streptococcal sepsis, unspecified); A413 (Sepsis due to hemophilus
influenza); A414 (Sepsis due to anaerobes); A4153 (Sepsis due to
serratia); A427 (Actinomycotic sepsis); A5486 (Gonococcal sepsis); and
B377 (Candidal sepsis). The remaining infection and sepsis diagnosis
codes were then used to query the FY 2017 MedPAR database to identify
inpatient discharges reporting these diagnosis codes under the primary
and secondary position.
According to the applicant, the resulting sets of MS-DRGs from both
diagnosis code selection queries had visible commonalities when looking
at only the MS-DRGs that contained potential cases which represented at
least 1 percent of the discharge volume for the specific diagnoses.
According to the applicant, due to the high volume of cases pulled and
visible trends, provider-specific discharges at the MS-DRG level with
fewer than 11 discharges were omitted from the analysis. In reconciling
the list of MS-DRGs containing potential cases identified for the
specific infection and sepsis codes, the applicant stated that MS-DRGs
853 (Infectious & Parasitic Diseases with O.R. Procedure with MCC), 870
(Septicemia or Severe Sepsis with Mechanical Ventilation >96 Hours),
871 (Septicemia or Severe Sepsis without Mechanical Ventilation >96
Hours with MCC) and 872 (Septicemia or Severe Sepsis without Mechanical
Ventilation >96 Hours without MCC) contain at least 1 percent of the
potential case volume under both scenarios and are the MS-DRGs to which
these potential cases available for use of the T2Bacteria[supreg] Test
Panel would most closely map.
The applicant provided multiple cost analysis scenarios to
demonstrate that the T2Bacteria[supreg] Test Panel meets the cost
criterion. Eight scenarios were provided for the Sepsis and Infection
diagnosis codes, separately, using the ICD-10-CM selections and based
on the following methodologies: (1) Applicable discharges for the
potential cases contained in 4 MS-DRGs (853, 870, 871 and 872); (2)
applicable discharges for cases inclusive of all identified MS-DRGs;
(3) applicable discharges with ICU usage for potential cases contained
in 4 MS-DRGs (853, 870, 871 and 872); (4) applicable discharges with
ICU usage for potential cases inclusive of all identified MS-DRGs; (5)
applicable discharges for cases contained in 4 MS-DRGs (853, 870, 871
and 872) with removal of 50 percent of pharmacy charges for prior
technology; (6) applicable discharges for potential cases inclusive of
all identified MS-DRGs with removal of 50 percent of pharmacy charges
for prior technology; (7) applicable discharges with ICU usage for
potential cases contained in 4 MS-DRGs (853, 870, 871 and 872) with
removal of 75 percent of pharmacy charges for prior technology; and (8)
applicable discharges with ICU usage for potential cases contained
inclusive of all identified MS-DRGs with removal of 75 percent of
pharmacy charges for prior technology.
The applicant's order of operations used for each analysis is as
follows: (1) Using the 15 sepsis or 37 infection diagnosis codes; (2)
using the complete set of cases or those who had an ICU stay; (3)
removing pharmacy charges at 0 percent, 50 percent, or 75 percent (for
ICU patients only); and (4) standardizing the charges per cases using
the Impact File published with the FY 2019 IPPS/LTCH PPS final rule
correction notice data file. After removing the charges for the prior
technology and standardizing charges, the applicant applied an
inflation factor of 1.08986, which is the 2-year inflation factor from
the FY 2019 IPPS/LTCH PPS final rule correction notice (83 FR 49844) to
update the charges from FY 2017 to FY 2019. The applicant then added
charges for the T2Bacteria[supreg] Panel. Under each scenario, the
applicant stated that the inflated average case-weighted standardized
charge per case exceeded the average case-weighted threshold amount.
Below we provide a table depicting the applicant's results for all 16
scenarios that the applicant indicated demonstrates that the technology
meets the cost criterion.
------------------------------------------------------------------------
Final inflated
average case- Average
weighted case[dash]
Scenario standardized weighted
charge per threshold
case amount
------------------------------------------------------------------------
Sepsis Discharges for Cases Contained in $69,088 $62,699
4 MS-DRGs (872, 871, 870 and 853)......
Sepsis Discharges for Cases Inclusive of 74,630 64,991
All Identified MS-DRGs.................
Sepsis Discharges for Cases with ICU 94,385 69,194
Usage Contained in 4 MS-DRGs (872, 871,
870 and 853)...........................
Sepsis Discharges for Cases with ICU 103,285 73,349
Usage Inclusive of All Identified MS-
DRGs...................................
Sepsis Discharges for Cases Contained in 63,503 62,699
4 MS-DRGs (872, 871, 870 and 853) with
Removal of 50 Percent of Pharmacy
Charges for Prior Technology...........
Sepsis Discharges for Cases Inclusive of 68,555 64,991
All Identified MS-DRGs with Removal of
50 Percent of Pharmacy Charges for
Prior Technology.......................
[[Page 19359]]
Sepsis Discharges for Cases with ICU 82,415 69,194
Usage Contained in 4 MS-DRGs (872, 871,
870, and 853) with Removal of 75
Percent of Pharmacy Charges for Prior
Technology.............................
Sepsis Discharges for Cases with ICU 90,151 73,350
usage Inclusive of All Identified MS-
DRGs with Removal of 75 Percent of
Pharmacy Charges for Prior Technology..
Infection Discharges for Cases Contained 69,349 60,696
in 4 MS-DRGs (872, 871, 870 and 853)...
Infection Discharges for Cases Inclusive 61,299 52,595
of All Identified MS-DRGs..............
Infection Discharges for Cases with ICU 95,952 67,024
Usage Contained in 4 MS-DRGs (872, 871,
870 and 853)...........................
Infection Discharges for Cases with ICU 102,171 68,682
Usage Inclusive of All Identified MS-
DRGs...................................
Infection Discharges for Cases Contained 63,744 60,696
in 4 MS-DRGs (872, 871, 870 and 853)
with Removal of 50 Percent of Pharmacy
Charges for Prior Technology...........
Infection Discharges for Cases Inclusive 56,833 52,595
of All Identified MS-DRGs with Removal
of 50 Percent of Pharmacy Charges for
Prior Technology.......................
Infection Discharges for Cases with ICU 83,760 67,024
Usage Contained in 4 MS-DRGs (872, 871,
870, and 853) with Removal of 75
Percent of Pharmacy Charges for Prior
Technology.............................
Infection Discharges for Cases with ICU 90,091 68,683
Usage Inclusive of All Identified MS-
DRGs with Removal of 75 Percent of
Pharmacy Charges for Prior Technology..
------------------------------------------------------------------------
The applicant noted that, in all 16 scenarios, the average case-
weighted standardized charge per case for potential cases available for
aid by use of the T2Bacteria[supreg] Test Panel would exceed the
average case-weighted threshold amounts in the FY 2019 IPPS/LTCH PPS
final rule correction notice data file by between $803.87 and
$33,488.82. Supplementary analyses were provided by the applicant,
which included eight additional scenarios that combined the 15 sepsis
and 37 infection diagnosis codes into one set of 52 diagnosis codes.
The applicant again utilized an inflation factor of 1.08986 and
followed the same methodology as the previously discussed cost
analyses. The applicant again noted that the final inflated average
case-weighted standardized charge per case exceeded the average case-
weighted threshold amounts in all scenarios, ranging between $1,083.67
and $32,430.57.
We are inviting public comments on whether the T2Bacteria[supreg]
Panel meets the cost criterion.
With respect to the substantial clinical improvement criterion, the
applicant asserted that the T2Bacteria[supreg] Panel represents a
substantial clinical improvement over existing technologies. According
to the applicant, the T2Bacteria[supreg] Panel is the only FDA-cleared
diagnostic aid that has the ability to rapidly and accurately identify
sepsis-causing bacteria species directly from whole blood within 3 to 5
hours, instead of the 1 to 5 days required by current standard-of-care
laboratory blood cultures or other diagnostic technology. The applicant
also asserted that the use of the T2Bacteria[supreg] Panel provides
more rapid beneficial resolution of the disease process due to enabling
faster treatment. Several studies provided by the applicant suggest
that effective detection prior to therapy can lead to a reduction in
hospital lengths-of-stay and likelihood of death.336 337
According to the applicant, in these studies for every hour reduction
in time to effective therapy or species ID, the length-of-stay
decreased by 2.7 hours.
---------------------------------------------------------------------------
\336\ Huang, A., Newton, D., Kunapuli, A., Gandhi, T., Washer,
L., Isip, J., Nagel, J., ``Impact of Rapid Organism Identification
via Matrix-Assisted Laser Desorption/Ionization Time-of-Flight
Combined with Antimicrobial Stewardship Team Intervention in Adult
Patients with Bacteremia and Candidemia,'' Clinical Infectious
Diseases, 2013, vol. 57(9), pp. 1237-1245.
\337\ Perez, K., Olsen, R., Musick, W., Cernoch, P., Davis, J.,
Peterson, L., & Musser, J., ``Integrating Rapid Diagnostics and
Antimicrobial Stewardship Improves Outcomes in Patients with
Antibiotic-Resistant Gram-Negative Bacteremia,'' Journal of
Infection, 2014, vol. 69(3), pp. 216-225.
---------------------------------------------------------------------------
The applicant stated that the T2Bacteria[supreg] pivotal trial that
led to the FDA clearance enrolled 11 hospitals in the United States and
1,427 patients with a blood culture ordered as the standard-of-care,
with species ID determined by MALDI-TOF or Vitek2.\338\ Furthermore,
due to the low prevalence of panel specific organisms, an additional
250 contrived specimens were evaluated. The T2Bacteria[supreg] Panel
result was blinded to the managing staff and did not influence care.
Blood samples were drawn for culture and T2Bacteria[supreg] Panel from
the same line at the same time. The mean time to blood culture
positivity was 51.0 43.0 hours (mean SD) and
the mean time to species ID was 83.7 47.6 hours (mean
SD). In contrast, the mean time to T2Bacteria[supreg]
Panel result was 6.5 1.9 hours, where a full load of 7
samples completed in 7.70 1.4 hours and a single sample
completed in 3.6 0.02 hours. Therefore, the difference in
mean time to result between blood culture and the T2Bacteria[supreg]
Panel assay was 77.2 hours or 3.2 days (p 0.2 hours up to 7.70 1.38 hours
(mean time dependent on the number of samples loaded, 1 to 7), which
was shorter than that of the standard-of-care blood culture with a
[[Page 19360]]
mean time of 71.7 39.3 hours.\339\ In addition to faster
species identification, the applicant asserted that the
T2Bacteria[supreg] Panel identifies more infection-positive cases than
blood cultures when verified by non-concurrent test results \340\ or
when verified with proven, probably, or possible criteria (concurrent
blood culture positive results, non-concurrent blood culture results
with positive culture results from another site within 21 days, and no
culture match, but the T2Bacteria[supreg] Panel bacteria was a
plausible cause of disease, respectively). In this study, 66 percent of
patients with concomitant blood culture results and T2Bacteria[supreg]
Panel positive results were not on active antibiotics at the time of
the blood draw, while 24 percent of patients with probable or possible
blood stream infections that were positive by T2Bacteria[supreg] Panel
alone were not on effective therapy.
---------------------------------------------------------------------------
\339\ Nguyen, M.H., Clancy, C., Pasculle, A.W., Pappas, P.,
Alangaden, G., Pankey, G., Mylonakis, E. ``Clinical performance of
the T2Bacteria panel for diagnosis bloodstream infections due to
five common bacterial pathogens,'' Manuscript for submission.
\340\ T2 Biosystems, Inc., ``T2Bacteria[supreg] Panel for use on
the T2Dx[supreg] Instrument, 510(k) summary,'' Lexington, 2018.
---------------------------------------------------------------------------
In another study submitted by the applicant, 137 blood cultures and
T2Bacteria[supreg] Panel tests were obtained from participants in the
emergency department.\341\ T2Bacteria[supreg] Panel results were
verified with concordant blood culture results, or when discordant with
blood cultures from another location drawn within 14 days of the
matched draw, or with the whole blood Sanger sequencing method. No
samples generated an invalid result for the T2Bacteria[supreg] assay.
The T2Bacteria[supreg] Panel identified 15 positives for which blood
cultures had concordant matches for 12. The three unmatched positives
were verified via other means. As compared to blood cultures, the
T2Bacteria[supreg] Panel had an overall positive percent agreement of
100 percent (12/12) and a negative percent agreement of 98.4 percent
(662/673). The negative percent agreement is shown to be due to blood
culture results that are indeterminate, or false positive.
---------------------------------------------------------------------------
\341\ Voigt, C., Silbert, S., Widen, R., Marturano, J., Lowery,
T., Ashcraft, D., & Pankey, G., ``The T2Bacteria assay is a
sensitive and rapid detector of bacteremia that can be initiated in
the emergency department and has potential to favorably influence
subsequent therapy,'' Journal of Emergency Medical Review, pp. 1-30.
---------------------------------------------------------------------------
In the same study,\342\ the T2Bacteria[supreg] Panel results
relative to standard-of-care blood culture identification were
classified into four impact level categories: (1) Minimal impact
results have negative blood culture results with no evidence of
infection for which results would have little to no impact; (2) some
impact results occur for patients who have an effective therapy at the
time of results, but the number of antibiotics administered could have
been reduced; (3) moderate impact results are for those on effective
therapy at the time of results, but were switched to species-directed
therapy within 12 hours of a standard-of-care blood culture
identification; and (4) direct impact results relate to those who could
have been placed on effective therapy earlier based on the results of
the T2Bacteria[supreg] Panel.\343\ The study identified 7 ``minimal
impact'' incidents, 8 ``some impact'' incidents, 4 ``moderate impact''
incidents, and 4 ``direct impact'' incidents, indicating that 16/23
(69.6 percent) of positive test results could have potentially
influenced patient care.
---------------------------------------------------------------------------
\342\ Ibid.
\343\ Voigt, C., Silbert, S., Widen, R., Marturano, J., Lowery,
T., Ashcraft, D., & Pankey, G., ``The T2Bacteria assay is a
sensitive and rapid detector of bacteremia that can be initiated in
the emergency department and has potential to favorably influence
subsequent therapy,'' Journal of Emergency Medical Review, pp. 1-30.
---------------------------------------------------------------------------
In articles provided by the applicant which concerned separate
studies, the T2Bacteria[supreg] Panel was found to have a shorter time
to species identification than blood cultures.344 345 The
study analysis by De Angelis, et al., 2018, an international,
prospective observational study involving 129 patients (144 enrolled)
18 years of age and older who had a blood culture and for whom a
T2Bacteria[supreg] Panel was also obtained, showed that the
T2Bacteria[supreg] Panel provided a mean time to species identification
and negative result of 5.5 1.4 hours and 6.1
1.5 hours, respectively as compared to 25.2 15.2 hours and
120 0.0 hours resulting from the standard-of-care blood
culture method, respectively.\346\ There were a total of 10
concordantly identified micro-organisms, 2 identified by standard-of-
care blood culture only, and 20 detected by the T2Bacteria[supreg]
Panel only. As compared to the results from the standard-of-care blood
culture method, the results from the T2Bacteria[supreg] Panel had a
sensitivity that ranged from 50 percent to 100 percent across the 5
detection channels, with an aggregate of 83.3 percent and a specificity
that ranged from 94.8 percent to 100 percent, with an aggregate of 97.6
percent. For patients who had a matched blood culture positive (n=8)
and who met the criterion of infection (n=6), a total of 36 percent (5/
14) of the patients were receiving inappropriate antimicrobial therapy
at the time of the T2Bacteria[supreg] Panel result. The results of this
study are again discussed in another article submitted by the
applicant, which states that these results may have the potential to
rapidly identify the five on-panel pathogens that may include cases
missed by results of the standard-of-care blood culture.\347\
---------------------------------------------------------------------------
\344\ De Angelis, G., Posteraro, B., Dr Carolis, E.,
Menchinelli, G., Franceschi, F., Tumbarello, M., Sanguinetti, M.,
``T2Bacteria magnetic resonance assay for the rapid detection of
ESKAPEc pathogens directly in whole blood,'' Journal of
Antimicrobial Chemotherapy, 2018, vol. 73, pp. iv20-iv26,
doi:10.1093/jac/dky049.
\345\ Nguyen, M. H., Clancy, C., Pasculle, A. W., Pappas, P.,
Alangaden, G., Pankey, G., Mylonakis, E., ``Clinical performance of
the T2Bacteria panel for diagnosis bloodstream infections due to
five common bacterial pathogens,'' Manuscript for submission.
\346\ De Angelis, G., Posteraro, B., Dr Carolis, E.,
Menchinelli, G., Franceschi, F., Tumbarello, M., Sanguinetti, M.,
``T2Bacteria magnetic resonance assay for the rapid detection of
ESKAPEc pathogens directly in whole blood,'' Journal of
Antimicrobial Chemotherapy, 2018, vol. 73, pp. iv20-iv26,
doi:10.1093/jac/dky049.
\347\ Clancy, C., & Nguyen, H., ``T2 magnetic resonance for the
diagnosis of bloodstream infections: charting a path forward,''
Journal of Antimicrobial Chemotherapy, 2018, vol. 73(4), pp. iv2-
iv5, doi:10.1093/jac/dky050.
---------------------------------------------------------------------------
The applicant further asserted that the T2Bacteria[supreg] Panel
provides a decreased rate of subsequent diagnostic or therapeutic
interventions. The applicant discussed the results of a meta-analysis
of 70 studies, in which the proportion of patients on an inappropriate
empiric therapy was 46.5 percent.\348\ The applicant indicated that the
results show that amongst patients with a blood culture draw, typical
antibiotic administration rates range from 50 to 70
percent.349 350 351 The applicant asserted that based on the
results of the analysis by the Voigt, et al., manuscript, 35 percent
(8/23) of the patients, receiving 3.6 1.1 (mean SD) unique antibiotics per patient, could have potentially seen
[[Page 19361]]
a reduction in the number of administered antibiotics.\352\ The
applicant further stated via a supplementary presentation to CMS that
the use of the T2Bacteria[supreg] Panel allows for earlier species
directed therapy than that allowed for by standard-of-care blood
cultures. The applicant believed that the use of the T2Bacteria[supreg]
Panel may allow the provider to move from broad potentially unnecessary
empiric to species-targeted therapy. The applicant stated that using
hospital antibiograms and being informed of the species by the
T2Bacteria[supreg] Panel, the physician is able to use species-directed
therapy and place up to 90 percent of patients on an effective therapy
in a few hours instead of 2 to 3 days.
---------------------------------------------------------------------------
\348\ Paul, M., Shani, V., Muchtar, E., Kariv, G., Robenshtok,
E., & Leibovici, L., ``Systematic Review and Meta-Analysis of the
Efficacy of Appropriate Empiric Antibiotic Therapy for Sepsis,''
Antimicrobial Agents and Chemotherapy, 2010, vol. 54(11), pp. 4851-
4863.
\349\ Castellanos-Ortega, A., Suberviola, B., Garcia-Astudillo,
L., Holanda, M., Ortiz, F., Llorca, J., & Delgado-Rodriguez, M.,
``Impact of the Surviving Sepsis Campaign Protocols on Hospital
Length of Stay and Mortality in Septic Shock Patients: Results of a
three-year follow-up quasi-experimental study,'' Crit Care Med,
2010, vol. 38(4), pp. 1036-1043, doi:10.1097/CCM.0b0bl3e3181d455b6.
\350\ Karlsson, S., Varpula, M., Pettila, V., & Parvlainen, I.,
``Incidence, Treatment, and Outcome of Severe Sepsis in ICU-treated
Adults in Finland: The Finnsepsis study,'' Intensive Care Medicine,
2007, vol. 33, pp. 435-443, doi:10.1007/s00134-006-0504-z.
\351\ Suberviola, B., Marquez-Lopez, A., Castellanos-Ortega, A.,
Fernandez-Mazarrasa, C., Santibanez, M., & Martinez, L.,
``Microbiological Diagnosis of Speis: Polymerase chain reaction
system versus blood cultures,'' American Journal of Critical Care,
2016, vol. 25(1), pp. 68-75.
\352\ Voigt, C., Silbert, S., Widen, R., Marturano, J., Lowery,
T., Ashcraft, D., & Pankey, G., ``The T2Bacteria assay is a
sensitive and rapid detector of bacteremia that can be initiated in
the emergency department and has potential to favorably influence
subsequent therapy,'' Journal of Emergency Medical Review, pp. 1-30.
---------------------------------------------------------------------------
According to the applicant, the practice of antibiotic de-
escalation was recently evaluated across 23 studies and found to be
safe and effective.\353\ Given the toxicity associated with
antibiotics, where some antibiotics cause encephalopathies including
seizures \354\ and in extreme cases show up to a 4.5 percent mortality
rate due to the antibiotic itself,\355\ the applicant asserted that
judicious use of antibiotics is necessary. The applicant further stated
that rapid diagnostics such as that able to be accomplished by the use
of the T2Bacteria[supreg] Panel assay, due to its negative predictive
value (NPV) of 99.7 percent,\356\ will enable physicians to focus
therapy and reduce the use of unnecessary drugs, where a targeted
therapy is possible in 3.8 hours instead of 2 days, reducing toxicity
and development of resistance.\357\
---------------------------------------------------------------------------
\353\ Ohji, G., Doi, A., Yamamoto, S., & Iwata, K., ``Is De-
escalation of Antimicrobials Effective? A systematic review and
meta-analysis,'' International Journal of Infectious Diseases, 2016,
vol. 49, pp. 71-79, Retrieved from http://dx.doi.org/10.1016/j.ijid.2016.06.002.
\354\ Bhattacharyya, S., Darby, R.R., Raibagkar, P., Gonzalez
Castro, L.N., & Berkowitz, A., ``Antibiotic-associated
Encephalopathy,'' American Academy of Neurology, 2016, pp. 963-971.
\355\ Koch-Weser, J., Sidel, V., Federman, E., Kanarek, P.,
Finer, D., & Eaton, A., ``Adverse Effects of Sodium Colistimethate;
Manifestations and specific reaction rates during 317 courses of
therapy,'' Annals of Internal Medicine, 1970, vol. 72, pp. 857-868.
\356\ Nguyen, M. H., Clancy, C., Pasculle, A.W., Pappas, P.,
Alangaden, G., Pankey, G., Mylonakis, E., ``Clinical performance of
the T2Bacteria panel for diagnosis bloodstream infections due to
five common bacterial pathogens,'' Manuscript for submission.
\357\ Weisz, E., Newton, E., Estrada, S., & Saunders, M.,
``Early Experience with the T2Bacteria Research Use Only (RUO) Panel
at a Community Hospital,'' Lee Memorial Hospital, Fort Meyers.
---------------------------------------------------------------------------
The applicant stated that the use of the T2Bacteria[supreg] Panel
will result in reduced mortality. The applicant indicated that the
results of large retrospective analyses show that every hour delaying
time to appropriate antibiotic therapy increased odds of death by 4
percent or reduced survival by 7.6 percent.358 359 360 The
applicant stated that the results of the T2Bacteria[supreg] Panel
Pivotal trial show that out of 23 positive patients, 4 (17 percent)
could have seen a reduction in time to effective therapy, with mean
time of 28.0 hours. An additional 4 (17 percent) could have seen a
reduction in time to species-directed therapy, with mean time reduction
of 52.6 hours. The applicant stated that by using the
T2Bacteria[supreg] Panel assay relative to standard-of-care blood
cultures, they expect a potential reduction in the odds of death to be
52.8 percent. According to the applicant, this factor of 2 difference
is consistent with a two-time higher odds of death in patients given
inappropriate empiric antibiotics relative to appropriate empiric
antibiotics.\361\ The applicant indicated that this result suggests
that employing the use of the T2Bacteria[supreg] Panel assay should
reduce mortality in bacteremia patients who are not immediately on
appropriate therapy.
---------------------------------------------------------------------------
\358\ Paul, M., Shani, V., Muchtar, E., Kariv, G., Robenshtok,
E., & Leibovici, L., ``Systematic Review and Meta-Analysis of the
Efficacy of Appropriate Empiric Antibiotic Therapy for Sepsis,''
Antimicrobial Agents and Chemotherapy, 2010, vol. 54(11), pp. 4851-
4863.
\359\ Kumar, A., Roberts, D., Wood, K., Light, B., Parrillo, J.,
Sharma, S., Cheang, M., ``Duration of Hypotension before Initiation
of Effective Antimicrobial Therapy is the Critical Determinant of
Survival in Human Septic Shock,'' Crit Care Med, 2006, vol. 34(6),
pp. 1589-1596, doi:10.1097/01.CCM.0000217961.75225.E9.
\360\ Seymour, C., Gesten, F., Prescott, H., Friedrich, M.,
Iwashyna, T., Phillips, G., Levy, M., ``Time to Treatment and
Mortality during Mandated Emergency Care for Sepsis,'' The New
England Journal of Medicine, 2017, vol. 376(23), pp. 2235-2244,
doi:10.1056/NEJMoa1703058.
\361\ Paul, M., Shani, V., Muchtar, E., Kariv, G., Robenshtok,
E., & Leibovici, L., ``Systematic Review and Meta-Analysis of the
Efficacy of Appropriate Empiric Antibiotic Therapy for Sepsis,''
Antimicrobial Agents and Chemotherapy, 2010, vol. 54(11), pp. 4851-
4863.
---------------------------------------------------------------------------
In the form of supplementary information, the applicant stated that
the use of the T2Bacteria[supreg] Panel covers 5 species, which account
for 50 percent to 70 percent of all blood stream infections, depending
on local epidemiology. According to the applicant, the remaining 30
percent to 50 percent of patients would continue to need standard-of-
care blood cultures for species identification. Based on all of the
above, the applicant believed that the T2Bacteria[supreg] Test Panel
represents a substantial clinical improvement over existing
technologies.
We have the following concerns regarding whether the
T2Bacteria[supreg] Panel meets the substantial clinical improvement
criterion. First, we are not certain that the applicant has provided
sufficient evidence to demonstrate that the early identification
without antibiotic susceptibility provided by the use of the T2
Bacteria[supreg] Panel is enough to prevent unnecessary empiric therapy
because specific identification and antibiotic susceptibilities may
still be required by blood cultures to adequately treat sepsis. For
instance, if an on-panel bacteria were identified it remains possible
that this species could be resistant to the standard-of-care treatment
for such bacteria used in a hospital. In addition, we believe that not
only is it possible for an identified species to be resistant to
typical empiric therapy, therefore diminishing the utility of its early
identification, it also is possible for off-panel organisms to be
present and also not be affected by species-targeted empiric treatment.
The applicant provided supplemental information in which it stated that
consistent with its labeling, the use of the T2Bacteria[supreg] Test
Panel would not replace blood cultures for specific organisms. Given
this information, we are concerned that the use of the
T2Bacteria[supreg] Panel may not be a substantial clinical improvement
over standard-of-care blood cultures, the existing comparator.
Second, the applicant provided research and analyses, which is
suggestive that the use of the T2Bacteria[supreg] Test Panel may lead
to decreased hospital lengths-of-stay, and decreased mortality.
Specifically, these analyses and articles show that there is a
possibility for a correlated relationship between the
T2Bacteria[supreg] Panel's time to species ID and these identified
outcomes. The applicant addressed this issue in a qualitative
manuscript analysis involving identification of potential impacts of
the T2Bacteria[supreg] Test Panel.\362\ We recognize that this
qualitative analysis is informative, but we are concerned that the low
number of cases (under 10) may limit generalizability of these results.
Given this information, we are concerned that in lieu of direct
testing, these suggestive
[[Page 19362]]
findings may not show a causative relationship.
---------------------------------------------------------------------------
\362\ Voigt, C., Silbert, S., Widen, R., Marturano, J., Lowery,
T., Ashcraft, D., & Pankey, G., ``The T2Bacteria assay is a
sensitive and rapid detector of bacteremia that can be initiated in
the emergency department and has potential to favorably influence
subsequent therapy,'' Journal of Emergency Medical Review, pp. 1-30.
---------------------------------------------------------------------------
Third, we are concerned that in all of the studies provided, the
comparator for the T2Bacteria[supreg] Panel is a single blood culture
draw. It is well established that blood culture sensitivity and
specificity increase with repeat blood draws. According to research
provided by the applicant, a single set of blood cultures should not be
drawn, but rather surveillance blood cultures, involving multiple draws
over time, should be practiced.\363\ Therefore, we believe that initial
blood cultures followed by repeated blood draws would have been a
better comparator. Furthermore, we believe an even stronger comparator
for the T2Bacteria[supreg] Test Panel would be other DNA based tests,
such as polymerase chain reaction (PCR), which also utilize DNA to
identify bacterial infections.
---------------------------------------------------------------------------
\363\ Wilson, M., Mitchell, M., Morris, A., Murray, P., Reimer,
L., Reller, L. B., Welch, D., ``Prinicples and Procedures for Blood
Cultures; Approved Guildeline,'' Clinical and Laboratory Standards
Institute, 2007.
---------------------------------------------------------------------------
Ultimately, we are concerned that the use of the T2Bacteria[supreg]
Test Panel may not alter the clinical course of treatment. We believe
that the variable sensitivity and specificity for the
T2Bacteria[supreg] Panel may be of concern if these results do not
compare favorably to other available DNA tests. While some of the false
positives in the pivotal trial were explained by reagent contamination
(43 of the 63 false positives),\364\ the high false positive rate seen
in the applicant's literature, (for example, 13 of 32 positives (40.6
percent),\365\ 58 of 146 positives (39.7 percent),\366\ and a potential
20 of 63 (31.7 percent) from the pivotal trial) may result in
unnecessary treatment of patients. Furthermore, use of a contrived arm
in the pivotal trial and low overall incidence of these five specific
sepsis-causing organisms may make it difficult to determine a
substantial clinical improvement in the complex clinical setting.
Lastly, it seems that blood cultures may still be necessary to identify
species susceptibility because the T2Bacteria[supreg] Test Panel does
not identify susceptibility and subsequent treatment based upon its
results will still require empiric treatment. If these points are true,
then the inferred decreased hospital lengths-of-stay, decreased
mortality, and better clinical outcomes may not be achieved with the
use of the T2Bacteria[supreg] Test Panel.
---------------------------------------------------------------------------
\364\ T2 Biosystems, Inc., ``T2Bacteria[supreg] Panel for use on
the T2Dx[supreg] Instrument, 510(k) summary,'' Lexington, 2018.
\365\ De Angelis, G., Posteraro, B., Dr Carolis, E.,
Menchinelli, G., Franceschi, F., Tumbarello, M., Sanguinetti, M.,
``T2Bacteria magnetic resonance assay for the rapid detection of
ESKAPEc pathogens directly in whole blood,'' Journal of
Antimicrobial Chemotherapy, 2018, vol. 73, pp. iv20-iv26,
doi:10.1093/jac/dky049.
\366\ Nguyen, M. H., Clancy, C., Pasculle, A. W., Pappas, P.,
Alangaden, G., Pankey, G., Mylonakis, E., ``Clinical performance of
the T2Bacteria panel for diagnosis bloodstream infections due to
five common bacterial pathogens,'' Manuscript for submission.
---------------------------------------------------------------------------
We are inviting public comments on whether the T2Bacteria[supreg]
Test Panel technology meets the substantial clinical improvement
criterion, including with respect to the specific concerns we have
raised. We did not receive any written comments in response to the New
Technology Town Hall meeting notice published in the Federal Register
regarding the substantial clinical improvement criterion for the
T2Bacteria[supreg] Test Panel or at the New Technology Town Hall
meeting.
q. VENCLEXTA[supreg]
AbbVie Pharmaceuticals, Inc. submitted an application for new
technology add-on payments for VENCLEXTA[supreg] (venetoclax tablets)
for FY 2020. According to the applicant, VENCLEXTA[supreg] is an oral
anti-cancer drug previously FDA-approved for the treatment of patients
who have been diagnosed with chronic lymphocytic leukemia (CLL) with
17p deletion, as detected by an FDA-approved test, who have received at
least one prior therapy. VENCLEXTA[supreg] received additional FDA
approval on November 21, 2018, for the treatment of adult patients who
have been diagnosed with CLL or small lymphocytic lymphoma (SLL), with
or without 17p deletion, who have received at least one prior therapy,
and in combination with azacitidine or decitabine or low-dose
cytarabine for the treatment of newly-diagnosed acute myeloid leukemia
(AML) in adults who are age 75 years old or older, or who have
comorbidities that preclude use of intensive induction chemotherapy.
AML is a type of cancer in which the bone marrow makes abnormal
myeloblasts (a type of white blood cell), red blood cells, or
platelets.\367\ The applicant stated that more than half of the
patients who are diagnosed with AML annually (19,520) \368\ are of
Medicare age.\369\ The leukemic cells proliferate in the marrow and
interfere with production of normal blood cells, causing weakness,
infection, bleeding, and other symptoms and complications. In
approximately half of these patients, nonrandom chromosomal
abnormalities are found by cytogenetic analysis, and these are used for
classification, management, and prognostication. AML is generally
rapidly lethal unless treated with intensive chemotherapy and/or
targeted therapies together with supportive care.\370\
---------------------------------------------------------------------------
\367\ National Cancer Institute, ``Adult Acute Myeloid Leukemia
Treatment--Patient Version,'' https://www.cancer.gov/types/leukemia/patient/adult-aml-treatment-pdq, Accessed September 11, 2018.
\368\ Siegel, R.L., Miller, K.D., Jemal, A., ``Cancer
Statistics,'' CA: A Cancer Journal for Clinicians, 2018, vol, 68(1),
pp. 7-30, doi:10.3322/caac.21442.
\369\ National Cancer Institute. ``SEER Stat Fact Sheets: Acute
Myeloid Leukemia,'' Bethesda, MD, http://seer.cancer.gov/statfacts/html/amyl.html, Accessed September 11, 2018.
\370\ Wolters Kluwer Health, ``Overview of acute myeloid
leukemia in adults,'' https://www.uptodate.com/contents/induction-therapy-for-acute-myeloid-leukemia-in-younger-adults, Accessed
October 9, 2018.
---------------------------------------------------------------------------
According to the applicant, in younger patients who have been
diagnosed with AML, intensive combination chemotherapy is the primary
treatment modality.\371\ Options for induction chemotherapy include
standard or high-dose cytarabine in combination with an anthracycline.
The most commonly used induction regimens for diagnoses of AML are the
so-called ``7+3'' regimens, which combine a 7-day continuous
intravenous infusion of cytarabine with a short infusion or bolus of an
anthracycline given on days 1 through 3. The applicant indicated that
the most commonly used anthracycline in this regimen is daunorubicin,
but other anthracyclines or synthetic anthracycline analogs have been
used. Depending on age and patient selection, up to 70 to 80 percent of
younger adults achieve complete remission with the use of these
regimens.372 373
---------------------------------------------------------------------------
\371\ Wolters Kluwer Health, ``Induction therapy for acute
myeloid leukemia in younger adults,'' https://www.uptodate.com/contents/induction-therapy-for-acute-myeloid-leukemia-in-younger-adults, Accessed September 11, 2018.
\372\ Ohtake, S., Miyawaki, S., Fujita, H., et al., ``Randomized
study of induction therapy comparing standard-dose idarubicin with
high-dose daunorubicin in adult patients with previously untreated
acute myeloid leukemia: the JALSG AML201 Study,'' Blood, 2010, vol.
117(8), pp. 2358-65, doi:10.1182/blood-2010-03-273243.
\373\ Fernandez, H.F., Sun, Z., Yao, X., et al., ``Anthracycline
Dose Intensification in Acute Myeloid Leukemia,'' New England
Journal of Medicine, 2009, vol. 361(13), pp. 1249-59, doi:10.1056/
nejmoa0904544.
---------------------------------------------------------------------------
However, the applicant indicated that older adults over the age of
55 years old \374\ are more frequently refractory to such cytotoxic-
intensive induction chemotherapy when compared to younger patients
because of biological disease-related factors such as increased
[[Page 19363]]
frequency of adverse-risk cytogenetic and molecular features, secondary
AML, and increased expression of multi-drug resistance phenotypes.\375\
Elderly patients also present with more comorbidities and compromised
organ function than do younger patients, which means they have
decreased tolerance to intensive therapies which can lead to
unacceptably high treatment-related mortality.376 377 378
The applicant explained that prognostic algorithms that can predict the
probability of achieving a complete response (CR) and the risk for an
early death for elderly patients with untreated AML have been
developed, and can help a physician determine whether or not the
patient is eligible for intensive chemotherapy.\379\ For these reasons,
only 40 percent of Medicare-aged patients who have been diagnosed with
AML receive chemotherapy for the treatment of the disease.\380\ The
applicant stated that, in patients not considered fit for intensive
treatment and who, therefore, were treated with lower intensity
regimens of low-dose cytarabine and hydroxyurea, with or without, all-
trans retinoic acid for diagnoses of AML and high-risk myelodysplastic
syndrome, only 25 percent of the patients on low-dose cytarabine
survived for 12 months.\381\ According to the applicant, in an
international Phase III study comparing the use of azacitidine with
conventional care regimens in older patients who had been newly
diagnosed with AML, only 18.6 percent of the patients receiving best
supportive care survived for 12 months.\382\ Accordingly, the applicant
believed that more effective, better-tolerated therapies for elderly
patients who have been diagnosed with AML are needed.\383\
---------------------------------------------------------------------------
\374\ Wolters Kluwer Health, ``Induction therapy for acute
myeloid leukemia in younger adults,'' https://www.uptodate.com/contents/induction-therapy-for-acute-myeloid-leukemia-in-younger-adults, Accessed September 11, 2018.
\375\ Krug, U., B[uuml]chner, T., Berdel, W.E., M[uuml]ller-
Tidow, C., ``The treatment of elderly patients with acute myeloid
leukemia,'' Dtsch Arztebl Int, 2011, vol. 108, pp. 863-70.
\376\ Pettit, K., Odenike, O., ``Defining and treating older
adults with acute myeloid leukemia who are ineligible for intensive
therapies,'' Front Oncol, 2015, vol. 5, pp. 280.
\377\ Kantarjian, H., Ravandi, F., O'Brien, S., et al.,
``Intensive chemotherapy does not benefit most older patients (age
70 years or older) with acute myeloid leukemia,'' Blood, 2010, vol.
116, pp. 4422-9.
\378\ Kantarjian, H., O'Brien, S., Cortes, J., et al., ``Results
of intensive chemotherapy in 998 patients age 65 years or older with
acute myeloid leukemia or high-risk myelodysplastic syndrome:
predictive prognostic models for outcome,'' Cancer, 2006, vol. 106,
pp. 1090-98.
\379\ O'Donnell, Margaret R., et al. ``Acute Myeloid Leukemia,
Version 3.2017, NCCN Clinical Practice Guidelines in Oncology.''
Journal of the National Comprehensive Cancer Network, vol. 15, no.
7, 2017, pp. 926-957., doi:10.6004/jnccn.2017.0116.
\380\ Medeiros, B.C., Satram-Hoang, S., Hurst, D., Hoang, K.Q.,
Momin, F., Reyes, C., ``Big data analysis of treatment patterns and
outcomes among elderly acute myeloid leukemia patients in the United
States,'' Annals of Hematology, 2015, vol. 94(7), pp. 1127-38,
doi:10.1007/s00277-015-2351-x.
\381\ Burnett, Alan K., et al., ``A Comparison of Low-Dose
Cytarabine and Hydroxyurea with or without All-Trans Retinoic Acid
for Acute Myeloid Leukemia and High-Risk Myelodysplastic Syndrome in
Patients Not Considered Fit for Intensive Treatment,'' Cancer, vol.
109, no. 6, 2007, pp. 1114-1124, doi:10.1002/cncr.22496.
\382\ Dombret, H., et al., ``International Phase 3 Study of
Azacitidine vs Conventional Care Regimens in Older Patients with
Newly Diagnosed AML with >30% Blasts,'' Blood, vol. 126, no. 3,
2015, pp. 291-299, doi:10.1182/blood-2015-01-621664.
\383\ DiNardo, C.D., Pratz, K.W., Letai, A., et al., ``Safety
and preliminary efficacy of venetoclax with decitabine or
azacitidine in elderly patients with previously untreated acute
myeloid leukemia: a non-randomized, open-label, phase Ib study,''
The Lancet Oncology, 2018, vol. 19(2), pp. 216-28, doi:10.1016/
s1470-2045(18)30010-x.
---------------------------------------------------------------------------
We note that, the applicant has submitted a request for approval
for a unique ICD-10-PCS code to identify procedures involving the
administration of VENCLEXTA[supreg], effective for FY 2020.
As discussed earlier, if a technology meets all three of the
substantial similarity criteria, it would be considered substantially
similar to an existing technology and, therefore, would not be
considered ``new'' for purposes of new technology add-on payments.
Current treatments include decitabine, azacitidine, low-dose
cytarabine, MYLOTARGTM, and supportive care such as anti-
emetics, transfusions, and antibiotics/antifungals.384 385
---------------------------------------------------------------------------
\384\ Ibid.
\385\ Wolters Kluwer Health, ``Induction therapy for acute
myeloid leukemia in younger adults,'' https://www.uptodate.com/contents/induction-therapy-for-acute-myeloid-leukemia-in-younger-adults, Accessed September 11, 2018.
---------------------------------------------------------------------------
With regard to the first criterion, whether a product uses the same
or a similar mechanism of action to achieve a therapeutic outcome, the
applicant asserted that VENCLEXTA[supreg] does not use the same or
similar mechanism of action when compared with an existing technology
to achieve a therapeutic outcome for patients diagnosed with AML who
are ineligible for intensive chemotherapy The applicant stated that
VENCLEXTA[supreg] is the first and only FDA-approved, selective oral
anti-apoptotic B-cell lymphoma 2 (BCL-2) inhibitor, and works by
inhibiting the BCL-2 protein, which regulates cell death and is
associated with chemotherapy-resistance and poor outcomes in patients
who have been diagnosed with AML.\386\ The applicant further asserted
that VENCLEXTA[supreg] is known to synergize with hypomethylating
agents (azacitidine/decitabine) and low-dose cytarabine in the
treatment of AML.\387\ In AML, malignant cells are dependent on BCL-2
and other pro-survival proteins such as MCL-1 for their survival. A
hypomethylator like azacitidine increases BCL-2 dependence and
sensitivity to VENCLEXTA[supreg] through inhibition of MCL-1, therefore
sensitizing the cell to VENCLEXTA[supreg]-induced
apoptosis.388 389 The applicant indicated that because the
combination of drugs in the recently-approved indication for the
treatment of AML is new, and VENCLEXTA[supreg] works synergistically
when administered as part of this treatment combination, this creates a
unique mechanism of action for the treatment of AML.
---------------------------------------------------------------------------
\386\ Pan, R., Hogdal, L.J., Benito, J.M., et al., ``Selective
BCL-2 inhibition by ABT-199 causes on-target cell death in acute
myeloid leukemia,'' Cancer Discov, 2014, vol. 4(3), pp. 362-75.
\387\ Bogenberger, J.M., Delman, D., Hansen, N., et al., ``Ex
vivo activity of BCL-2 family inhibitors ABT-199 and ABT-737
combined with 5-azacitidine in myeloid malignancies,'' Leukemia &
Lymphoma, 2014, vol. 56(1), pp. 226-229, doi:10.3109/
10428194.2014.910657.
\388\ Konopleva, M., et al., ``Efficacy and Biological
Correlates of Response in a Phase II Study of Venetoclax Monotherapy
in Patients with Acute Myelogenous Leukemia,'' Cancer Discovery,
vol. 6, no. 10, Dec. 2016, pp. 1106-1117, doi:10.1158/2159-8290.cd-
16-0313.
\389\ Valentin, Rebecca, et al., ``The Rise of Apoptosis:
Targeting Apoptosis in Hematologic Malignancies,'' Blood, 2018, vol.
132, no. 12, pp. 1248-1264, doi:10.1182/blood-2018-02-791350.
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With respect to the second criterion, whether a product is assigned
to the same or a different MS-DRG, the applicant asserted that
potential cases representing patients who have been diagnosed with CLL
who may be eligible for treatment using VENCLEXTA[supreg] would be
assigned to different MS-DRGs than cases representing patients who have
been diagnosed with AML. According to the applicant, potential cases
representing patients who have been diagnosed with CLL who may be
eligible for treatment using VENCLEXTA[supreg] would be assigned to the
following MS-DRGs: 808 (Major Hematological And Immunological Diagnoses
Except Sickle Cell Crisis And Coagulation Disorders With MCC), 809
(Major Hematological And Immunological Diagnoses Except Sickle Cell
Crisis And Coagulation Disorders With CC), 823 (Lymphoma And Non-Acute
Leukemia With Other Procedure With MCC), 824 (Lymphoma And Non-Acute
Leukemia With Other Procedure With CC), 825 (Lymphoma And Non-Acute
Leukemia With Other Procedure Without CC/MCC), 834 (Acute Leukemia
Without Major O.R. Procedure With MCC), 835 (Acute Leukemia Without
Major O.R. Procedure With CC), 836 (Acute Leukemia Without Major O.R.
Procedure Without CC/MCC), and 839
[[Page 19364]]
(Chemotherapy With Acute Leukemia As SDX Without CC/MCC). We believe
that potential cases representing patients who have been newly
diagnosed with AML, as well as potential cases representing patients
who have been diagnosed with CLL, could both be assigned to the
following 3 MS-DRGs: 820 (Lymphoma and Leukemia With Major O.R.
Procedure With MCC), 821 (Lymphoma and Leukemia With Major O.R.
Procedure With CC), and 822 (Lymphoma and Leukemia With Major O.R.
Procedure Without CC/MCC). We expect that cases involving treatment
with VENCLEXTA[supreg] would most likely be assigned to the same MS-
DRGs to which cases involving comparable treatments are assigned.
With respect to the third criterion, whether the new use of the
technology involves the treatment of the same or similar type of
disease and the same or similar patient population, the applicant
asserted that VENCLEXTA[supreg] does not involve the treatment of the
same or similar type of disease or same or similar patient population
because there are currently no curative treatment options available for
elderly patients who have been newly diagnosed with AML who are
ineligible for intensive chemotherapy.
The applicant further asserted that the disease and patient
population for which VENCLEXTA[supreg] provides treatment is unique.
There are no other FDA-approved therapies specific to this patient
population--newly diagnosed AML patients who are ineligible for
intensive chemotherapy--and currently these patients receive only
lower-intensity treatments without curative intent, but rather
treatment is focused on alleviating symptoms, prolonging life, and/or
improving quality of life.\390\ The applicant stated that where
patients on intensive chemotherapy have benefited from improvements in
overall survival over the past 50 years, ineligible patients have not;
and more effective, better-tolerated therapies for elderly patients who
have been diagnosed with AML are urgently needed.\391\ The applicant
further stated that this unmet medical need is one reason why
VENCLEXTA[supreg] received Breakthrough Therapy designation from the
FDA for this patient population.\392\
---------------------------------------------------------------------------
\390\ Wolters Kluwer Health, ``Acute myeloid leukemia: Treatment
and outcomes in older adults,'' https://www.uptodate.com/contents/acute-myeloid-leukemia-treatment-and-outcomes-in-older-adults,
Accessed September 11, 2018.
\391\ DiNardo, C.D., Pratz, K.W., Letai, A., et al., ``Safety
and preliminary efficacy of venetoclax with decitabine or
azacitidine in elderly patients with previously untreated acute
myeloid leukemia: a non-randomized, open-label, phase Ib study,''
The Lancet Oncology, 2018, vol. 19(2), pp. 216-28, doi:10.1016/
s1470-2045(18)30010-x.
\392\ Hoffjman-LaRoche, Ltd., F., ``FDA grants breakthrough
therapy designation for VENCLEXTA[supreg] in acute myeloid
Leukaemia,'' https://www.roche.com/dam/jcr:0cf1ad70-02c8-44b4-94ac-ccdf1dbca95a/en/inv-update-2017-07-28-e.pdf, Accessed October 9,
2018.
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With respect to whether the technology involves the treatment of a
unique patient population, we note that as the applicant indicated,
there are lower-intensity chemotherapeutic regimens available as
standard-of-care therapies for patients who have been newly diagnosed
with AML who are ineligible for intensive chemotherapy. We are inviting
public comments on whether VENCLEXTA[supreg] is substantially similar
to any existing technology and whether it meets the newness criterion,
including with respect to the concerns we have raised.
With regard to the cost criterion, the applicant conducted the
following analysis. The applicant used the FY 2017 MedPAR Hospital
Limited Data Set (LDS) to assess the MS-DRGs to which cases
representing potential patient hospitalizations that may be eligible
for treatment involving VENCLEXTA[supreg] would most likely be
assigned. These potential cases representing patients who may be
VENCLEXTA[supreg] candidates were identified if these cases reported a
diagnosis of AML. The cohort was limited by excluding patients who were
discharged as not classified with one of the relevant ICD-10-CM codes.
From the resulting data, the applicant determined the most
applicable MS-DRGs to use in order to determine the average length-of-
stay by identifying the codes with at least 1 percent of total
discharge volume, which limited the selection to 16 codes. According to
the applicant, in an effort to limit impact from MS-DRGs with probable
low relevance and/or not usually representing solely AML inpatient
stays, a number of high-volume MS-DRGs were not included in the
calculation. These excluded codes included those representing high-dose
chemotherapy inpatient stays, sepsis cases, pneumonia inpatient stays,
and heart failure and circulation disorders. This left potential cases
represented in MS-DRGs 808, 809, 834, 835, 836, and 839 to determine
the average length-of-stay, which under this criterion resulted in 7.25
days.
The applicant noted that two limitations of this calculation method
are: (1) That the average length-of-stay may have changed since FY 2017
for the MS-DRGs selected; and (2) the approach of relevant case
identification may not adequately capture patients who are ineligible
for intensive chemotherapy.
The applicant provided additional analyses with the
VENCLEXTA[supreg] charges under six separate cost threshold scenarios.
According to the applicant, the cost criterion was satisfied in each of
these scenarios, with charges in excess of the average case-weighted
threshold amount. Scenario 1 captures discharges classified with one or
more of seven subtypes of patients who have been diagnosed with AML who
have not achieved remission or who have been diagnosed with AML in
relapse; a subgroup to capture patients who have not been responsive to
existing treatments. Scenario 2 captures discharges classified with one
or more of seven subtypes of patients who had been diagnosed with AML
who never have achieved remission; a population that will have a high
concentration of patients who have been newly diagnosed with AML.
Lastly, scenario 3 is a combination of all discharges that classified
patients who have been diagnosed with AML who have not relapsed.
While the VENCLEXTA[supreg] Breakthrough Therapy designation is for
use in elderly patients who have been newly diagnosed with AML, the
applicant determined it was necessary to produce separate cost
threshold calculations based on the three diagnosis code selections
pending the final VENCLEXTA[supreg] label. Scenarios 1 through 3 have
additional exclusions and inclusion codes that: (1) Add comorbidities
to patients between 65 years old and 74 years old; (2) remove affects
from related non-AML conditions; and (3) ensure that all discharges
were administered drugs. Scenarios 4, 5, and 6 use the same base ICD-
10-CM inclusion codes as scenarios 1, 2, and 3, respectively, however,
they do not use additional inclusion and exclusion codes, which makes
the cost threshold results representative of a broader patient
population. For each cost threshold scenario, the applicant also
applied a deduction of 50 percent of pharmacy charges to account for
the replacement of hospital expenditures when VENCLEXTA[supreg] is used
as first-line therapy.
The applicant produced cost threshold results for 6 scenarios, each
with 4 MS-DRGs, for a total of 24 cost threshold calculations. All four
MS-DRGs had identical volume percentages in each of the six scenarios.
The average dollar amount by which the average case-weighted
standardized charges per case exceeded the average case-weighted
threshold amount is
[[Page 19365]]
$17,612.75 for scenario 1, $15,730.27 for scenario 2, $15,566.70 for
scenario 3, $33,868.18 for scenario 4, $32,098.60 for scenario 5, and
$30,860.67 for scenario 6. The applicant asserted that considering only
the most applicable MS-DRGs, MS-DRG 834 and MS-DRG 835, the average
case-weighted threshold amounts were exceeded by a range of $16,169.02
at the lowest (scenario 2) and $50,185.99 at the highest (scenario 4)
and, therefore, the applicant believes VENCLEXTA[supreg] meets the cost
criterion.
Based on all of the analyses above, the applicant maintained that
VENCLEXTA[supreg] meets the cost criterion. We are inviting public
comments on whether VENCLEXTA[supreg] meets the cost criterion.
With regard to substantial clinical improvement, the applicant
asserted that VENCLEXTA[supreg], in combination with either azacitidine
or decitabine, and VENCLEXTA[supreg], in combination with low-dose
cytarabine, both constitute a substantial clinical improvement over
currently available treatments for patients who have been newly
diagnosed with AML who are ineligible for intensive chemotherapy. The
applicant submitted two main studies to support its assertion that the
technology represents a substantial clinical improvement over existing
technologies.
The first study submitted was M14-358, a Phase Ib, open-label,
multi-center, non-randomized study of the use of VENCLEXTA[supreg], in
combination with azacitidine or decitabine, in the treatment of
patients who have been newly diagnosed with AML who are not eligible
for standard induction therapy. Eligible patients were 60 years old and
older, had previously undiagnosed AML, had intermediate- or poor-risk
cytogenetics, and were not eligible for standard induction therapy.
Patients received VENCLEXTA[supreg] via a daily ramp-up to a final 400
mg once-daily dose. During the ramp-up, patients received tumor lysis
syndrome (TLS) prophylaxis and were hospitalized for monitoring.
Azacitidine at 75 mg/m2 was administered either intravenously or
subcutaneously on Days 1 through 7 of each 28-day cycle beginning on
Cycle 1 Day 1. Decitabine at 20 mg/m2 was administered intravenously on
Days 1 through 5 of each 28-day cycle beginning on Cycle 1 Day 1.
Patients continued to receive treatment cycles until disease
progression or unacceptable toxicity. Azacitidine dose reduction was
implemented in the clinical trial for management of hematologic
toxicity. Dose reductions for decitabine were not implemented in the
clinical trial.
The primary objective of the escalation stage of this trial was to
evaluate the safety and pharmacokinetics of orally-administered
VENCLEXTA[supreg], combined with decitabine or azacitidine, at standard
doses and schedules in patients who had been newly diagnosed with AML
who were 60 years old and older and who are not eligible for standard
induction therapy due to comorbidities. Secondary objectives for the
dose escalation included assessing the preliminary efficacy of the use
of VENCLEXTA[supreg] administered orally, in combination with either
decitabine or azacitidine, in this patient population. The primary
objectives of the expansion stage were to confirm the safety and to
assess efficacy including complete remission (CR) and complete
remission with incomplete blood count recovery (CRi) and determine
overall survival (OS) of the use of VENCLEXTA[supreg] combined with
decitabine or azacitidine in the treatment of patients who had been
newly diagnosed with AML. A secondary objective for the expansion was
to evaluate duration of response (DOR). Complete remission was defined
as absolute neutrophil count greater than 1,000/microliter, platelets
greater than 100,000/microliter, red blood cell transfusion
independence, and bone marrow with less than 5 percent blast, absence
of circulating blasts and blasts with Auer rods, and absence of
extramedullary disease. Complete remission with partial hematological
recovery (CRh) was defined as less than 5 percent of blasts in the bone
marrow, no evidence of disease, and partial recovery of peripheral
blood counts (platelets greater than 50,000/microliter and ANC greater
500/microliter).
The study arm with VENCLEXTA[supreg], in combination with
azacitadine, had 67 patients with a mean age of 76 years old (range 61
years old to 90 years old). Eighty-seven percent of this group was
white, 64 percent had an ECOG performance status of 0 to 1, and 34
percent had poor cytogenetic risk detected. The study arm with
VENCLEXTA[supreg], in combination with decitabine, had 13 patients with
a mean age of 75 years old (range 68 years old to 86 years old). Seven-
seven percent of this group was white, 92 percent had an ECOG
performance status of 0 to 1, and 62 percent had poor cytogenetic risk
detected.
For patients who received VENCLEXTA[supreg], in combination with
azacitadine, 37.5 percent (95 percent CI 26, 50) achieved CR and 24
percent (95 percent CI 14, 36) achieved CRh. Sixty-one percent of the
patients achieved CR or CRh. The median time to first CR or CRh was 1
month (range 0.7 months to 8.9 months), and median observed time in
remission for those patients who achieved CR was 5.5 months (range 0.4
months to 30 months) for this group. The median OS was 16.9 months, the
12-month OS estimate was 57 percent, and median duration of response
was 21.2 months. For patients who received VENCLEXTA[supreg], in
combination with decitabine, 54 percent (95 percent CI, 25 months to 81
months) achieved CR and 8 percent (95 percent CI, 0.2 months to 36
months) achieved CRh. Sixty-two percent of the patients achieved CR or
CRh. The median time to first CR or CRh was 1.9 months (range 0.8
months to 4.2 months), and median observed time in remission for those
who achieved CR was 4.7 months (range 1 month to 18 months) for this
group. The median OS was 16.2 months, the 12-month OS estimate was 61
percent, and median duration of response was 15 months. The study
enrolled 35 additional patients (age range 65 years old to 74 years
old) who did not have known comorbidities that precluded the use of
intensive induction chemotherapy and were treated with
VENCLEXTA[supreg], in combination with azacitidine (n=17) or decitabine
(n=18). For the additional patients treated with VENCLEXTA[supreg], in
combination with azacitidine, the CR rate was 35 percent (95 percent CI
14, 62). The CRh rate was 41 percent (95 percent CI 18, 67). For the
additional patients treated with VENCLEXTA[supreg], in combination with
decitabine, the CR rate was 56 percent (95 percent CI 31, 79). The CRh
rate was 22 percent (95 percent CI 6.4, 48).
In terms of safety, for patients receiving azacitadine, the most
common adverse reactions (greater than or equal to 30 percent) of any
grade were nausea, diarrhea, constipation, neutropenia,
thrombocytopenia, hemorrhage, peripheral edema, vomiting, fatigue,
febrile neutropenia, rash, and anemia. Serious adverse reactions were
reported in 75 percent of the patients. The most frequent serious
adverse reactions (greater than or equal to 5 percent) were febrile
neutropenia, pneumonia (excluding fungal), sepsis (excluding fungal),
respiratory failure, and multiple organ dysfunction syndrome. The
incidence of fatal adverse drug reactions was 1.5 percent within 30
days of starting treatment. No reaction had an incidence of greater
than or equal to 2 percent. Discontinuations due to adverse reactions
occurred in 21 percent of the patients. The most frequent adverse
reactions leading to drug
[[Page 19366]]
discontinuation (greater than or equal to 2 percent) were febrile
neutropenia and pneumonia (excluding fungal). Dosage interruptions due
to adverse reactions occurred in 61 percent of the patients. The most
frequent adverse reactions leading to dose interruption (greater than
or equal to 5 percent) were neutropenia, febrile neutropenia, and
pneumonia (excluding fungal). Dosage reductions due to adverse
reactions occurred in 12 percent of the patients. The most frequent
adverse reaction leading to dose reduction (greater than or equal to 5
percent) was neutropenia.
For patients receiving decitabine, the most common adverse
reactions (greater than or equal to 30 percent) of any grade were
febrile neutropenia, constipation, fatigue, thrombocytopenia, abdominal
pain, dizziness, hemorrhage, nausea, pneumonia (excluding fungal),
sepsis (excluding fungal), cough, diarrhea, neutropenia, back pain,
hypotension, myalgia, oropharyngeal pain, peripheral edema, pyrexia,
and rash. Serious adverse reactions were reported in 85 percent of the
patients. The most frequent serious adverse reactions (greater than or
equal to 5 percent) were febrile neutropenia, sepsis (excluding
fungal), pneumonia (excluding fungal), diarrhea, fatigue, cellulitis,
and localized infection. One (8 percent) fatal adverse drug reaction of
bacteremia occurred within 30 days of starting treatment.
Discontinuations due to adverse reactions occurred in 38 percent of the
patients. The most frequent adverse reaction leading to drug
discontinuation (greater than or equal to 5 percent) was pneumonia
(excluding fungal). Dosage interruptions due to adverse reactions
occurred in 62 percent of the patients. The most frequent adverse
reactions leading to dose interruption (greater than or equal to 5
percent) were febrile neutropenia, neutropenia, and pneumonia
(excluding fungal). Dosage reductions due to adverse reactions occurred
in 15 percent of the patients. The most frequent adverse reaction
leading to dose reduction (greater than or equal to 5 percent) was
neutropenia.
The second study submitted was M14-387, a non-randomized, open-
label Phase I/II study of the use of VENCLEXTA[supreg], in combination
with low-dose cytarabine, in patients who had been newly diagnosed with
AML who are ineligible for standard anthracycline-based induction
therapy. The study enrolled patients who were 60 years old and older
who had been diagnosed with AML and who were not eligible for standard
induction therapy.
Patients initiated use of VENCLEXTA[supreg] via daily ramp-up to a
final 600 mg once-daily dose. During the ramp-up, patients received TLS
prophylaxis and were hospitalized for monitoring. Cytarabine at a dose
of 20 mg/m2 was administered subcutaneously once-daily on Days 1
through 10 of each 28-day cycle beginning on Cycle 1 Day 1.
This study consisted of three distinct portions. The first portion
of the study was a Phase I, or dose-escalation portion, that evaluated
the safety and pharmacokinetics (PK) profile of VENCLEXTA[supreg]
administered with low-dose azacitidine with the objectives of defining
the maximum-tolerated dose (MTD) and generating data to support a
recommended Phase II dose (RPTD). A subsequent initial Phase II portion
evaluated whether the RPTD had sufficient efficacy and acceptable
toxicity to warrant further development of the combination therapy.
Subsequently, a Phase II, Cohort C was enrolled to evaluate the ORR for
patients who were allowed additional supportive medications (for
example, strong CYP3A inhibitors), if medically indicated, because new
PK data emerged from external studies demonstrating that these
previously excluded concomitant medications may be tolerable with an
appropriate VENCLEXTA[supreg] dose adjustment during co-administration.
The primary objectives of the Phase I portion were to assess the
safety profile, characterize the (PK), and determine the dose schedule,
the MTD, and the RPTD of the use of VENCLEXTA[supreg], in combination
with low-dose azacitidine or cytarabine in the treatment of patients
who had been newly diagnosed with AML who were 60 years old and older
and who were not eligible for standard induction therapy due to co-
morbidity or other factors. The primary objectives of the initial Phase
II portion of the study were to evaluate the preliminary estimates of
efficacy including the overall response rate (ORR) and to characterize
the toxicities of the combination at the RPTD. The primary objective of
Phase II, Cohort C was to evaluate the ORR for patients allowed
additional supportive medications (strong cytochrome P450 [CYP]3A
inhibitors), if medically indicated. The secondary objectives of the
initial Phase II portion and Phase II, Cohort C were to evaluate
leukemia response (rates of complete remission (CR)), complete
remission with incomplete blood count recovery (Cri), partial remission
(PR), and morphologically leukemia-free status (MLFS)), duration of
response (DOR), and OS. Patients continued to receive treatment cycles
until disease progression or unacceptable toxicity. Dose reduction for
low-dose cytarabine was not implemented in the clinical trial.
The study enrolled 61 patients with a median age of 76 years old
(range 63 years old to 90 years old), 92 percent of whom were white, 66
percent of whom had an ECOG performance status of 0 to 1, and 34
percent of whom had poor cytogenetic risk detected. Twenty-one percent
(95 percent CI 12, 34) achieved CR and 21 percent (95 percent CI 12,
34) achieved CRh. Overall 43 percent of the patients achieved CR or
CRh. The median OS was 10.1 months and median duration of response was
8.1 months. The study enrolled 21 additional patients (age ranged 67
years old to 74 years old) who did not have known comorbidities that
precluded the use of intensive induction chemotherapy and were treated
with VENCLEXTA[supreg], in combination with low-dose cytarabine. The CR
rate was 33 percent (95 percent CI: 15, 57). The CRh rate was 24
percent (95 percent CI: 8.2, 47).
In terms of safety, the most common adverse reactions (greater than
or equal to 30 percent) of any grade were nausea, thrombocytopenia,
hemorrhage, febrile neutropenia, neutropenia, diarrhea, fatigue,
constipation, and dyspnea. Serious adverse reactions were reported in
95 percent of the patients. The most frequent serious adverse reactions
(greater than or equal to 5 percent) were febrile neutropenia, sepsis
(excluding fungal), hemorrhage, pneumonia (excluding fungal), and
device-related infection. The incidence of fatal adverse drug reactions
was 4.9 percent within 30 days of starting treatment with no reaction
having an incidence of greater than or equal to 2 percent.
Discontinuations due to adverse reactions occurred in 33 percent of the
patients. The most frequent adverse reactions leading to drug
discontinuation (greater than or equal to 2 percent) were hemorrhage
and sepsis (excluding fungal). Dosage interruptions due to adverse
reactions occurred in 52 percent of the patients. The most frequent
adverse reactions leading to dose interruption (greater than or equal
to 5 percent) were thrombocytopenia, neutropenia, and febrile
neutropenia. Dosage reductions due to adverse reactions occurred in 8
percent of the patients. The most frequent adverse reaction leading to
dose reduction (greater than or equal to 2 percent) was
thrombocytopenia. On the basis of these studies, the applicant asserted
that median OS, 12-month OS, CR + CRi, and DOR for VENCLEXTA[supreg]
are all substantially higher than the outcomes
[[Page 19367]]
achieved by standard-of-care as reported by studies. The applicant
asserted that these improvements, especially the more than doubling of
the remission rates as compared to other available low-intensity
therapies (range reported as 0 to 28 percent), are substantial and
clinically meaningful.
In regard to the substantial clinical improvement criterion for
VENCLEXTA[supreg], we reviewed the data the applicant provided on
outcomes (for example, CR, CRh, CRi, DOR, and OS) using historical
controls of other chemotherapeutic regimens used for this target
patient population, and we note that the data is lacking information
with regard to a direct comparator. The studies did not detail the
demographics and outcomes for patients over the age of 75 versus
younger patients. We note that the applicant did not provide any
information on how many enrolled patients are from the United States.
We further note that fatal adverse drug reactions occurred in both
submitted studies in patients receiving treatment involving the use of
VENCLEXTA[supreg], and dosage interruptions due to adverse events
occurred in a significant proportion of the patients receiving the
drug. We also are concerned about the lack of conclusive data on the
efficacy of VENCLEXTA[supreg].
We are inviting public comments on whether VENCLEXTA[supreg] meets
the substantial clinical improvement criterion. We did not receive any
written public comments in response to the New Technology Town Hall
meeting notice published in the Federal Register regarding the
substantial clinical improvement criterion for VENCLEXTA[supreg] or at
the New Technology Town Hall meeting.
6. Request for Information on the New Technology Add-On Payment
Substantial Clinical Improvement Criterion
Under the Hospital Inpatient Prospective Payment System (IPPS), CMS
has established policies to provide additional payment for new medical
services and technologies. Similarly, under the Hospital Outpatient
Prospective Payment System (OPPS), CMS has established policies to
provide separate payment for innovative medical devices, drugs and
biologicals. Sections 1886(d)(5)(K) and (L) of the Act require the
Secretary to establish a mechanism to recognize the costs of new
medical services and technologies under the IPPS, and section
1833(t)(6) of the Act requires the Secretary to provide an additional
payment amount, known as a transitional pass-through payment, for the
additional costs of innovative medical devices, drugs, and biologicals
under the OPPS. The substantial clinical improvement criterion that is
used to evaluate a technology that is the subject of an application for
new technology add-on payments under the IPPS or an application for the
transitional pass-through payment for the additional costs of
innovative devices under the OPPS (both categories of technologies are
hereafter collectively referred to as ``new technology'') is the
subject of the potential revisions discussed in this section to the new
technology add-on payment policy's substantial clinical improvement
criteria.
Under the IPPS, the regulations at Sec. 412.87 implement these
provisions and specify three criteria for a new medical service or
technology to receive the additional payment: (1) The medical service
or technology must be new; (2) the medical service or technology must
be costly such that the DRG rate otherwise applicable to discharges
involving the medical service or technology is determined to be
inadequate; and (3) the service or technology must demonstrate a
substantial clinical improvement over existing services or
technologies. Under this third criterion, Sec. 412.87(b)(1) of our
existing regulations provides that a new technology is an appropriate
candidate for an additional payment when it represents an advance that
substantially improves, relative to technologies previously available,
the diagnosis or treatment of Medicare beneficiaries (we refer readers
to the September 7, 2001 final rule for a more detailed discussion of
this criterion (66 FR 46902)). For more background on add-on payments
for new medical services and technologies under the IPPS, we refer
readers to the FY 2009 IPPS/LTCH PPS final rule (73 FR 48552).
In the CY 2001 OPPS interim final rule with comment period (65 FR
67798), we implemented the transitional device pass-through payment
requirements in section 1833(t)(6) of the Act under our regulation at
42 CFR 419.66. Under Sec. 419.66(b), a medical device must meet the
following requirements to be eligible for transitional pass-through
payments: (1) If required by FDA, the device must have received FDA
premarket approval or clearance (except for a device that has received
an FDA investigational device exemption (IDE) and has been classified
as a Category B device by the FDA), or another appropriate FDA
exemption; and the pass-through payment application must be submitted
within 3 years from the date of the initial FDA approval or clearance,
if required, unless there is a documented, verifiable delay in U.S.
market availability after FDA approval or clearance is granted, in
which case CMS will consider the pass-through payment application if it
is submitted within 3 years from the date of market availability; (2)
the device is determined to be reasonable and necessary for the
diagnosis or treatment of an illness or injury or to improve the
functioning of a malformed body part, as required by section
1862(a)(1)(A) of the Act; and (3) the device is an integral part of the
service furnished, is used for one patient only, comes in contact with
human tissue, and is surgically implanted or inserted (either
permanently or temporarily), or applied in or on a wound or other skin
lesion. In addition, according to Sec. 419.66(b)(4), a device is not
eligible to be considered for device pass-through payment if it is any
of the following: (1) Equipment, an instrument, apparatus, implement,
or item of this type for which depreciation and financing expenses are
recovered as depreciation assets as defined in Chapter 1 of the
Medicare Provider Reimbursement Manual (CMS Pub. 15-1); or (2) a
material or supply furnished incident to a service (for example, a
suture, customized surgical kit, or clip, other than a radiological
site marker).
Finally, we use the following criteria, as set forth under Sec.
419.66(c), to determine whether a new category of pass-through payment
devices should be established. The devices to be included in the new
category must:
Not be appropriately described by an existing category or
by any category previously in effect established for transitional pass-
through payments, and were not being paid for as an outpatient service
as of December 31, 1996;
Have an average cost that is not ``insignificant''
relative to the payment amount for the procedure or service with which
the device is associated as determined under Sec. 419.66(d) by
demonstrating: (1) The estimated average reasonable costs of the
devices in the category exceeds 25 percent of the applicable APC
payment amount for the service related to the category of devices; (2)
the estimated average reasonable cost of the devices in the category
exceeds the cost of the device-related portion of the APC payment
amount for the related service by at least 25 percent; and (3) the
difference between the estimated average reasonable cost of the devices
in the category and the portion of the APC payment amount for the
device exceeds 10 percent of the APC payment amount for the related
service (with the exception of brachytherapy and temperature-monitored
cryoblation, which are exempt from the cost
[[Page 19368]]
requirements as specified at Sec. Sec. 419.66(c)(3) and (e)); and
Demonstrate a substantial clinical improvement, that is,
substantially improve the diagnosis or treatment of an illness or
injury or improve the functioning of a malformed body part compared to
the benefits of a device or devices in a previously established
category or other available treatment.
For more background on transitional pass-through payments for
devices under the OPPS, we refer readers to the CMS website at: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HospitalOutpatientPPS/passthrough_payment.html.
CMS posts on its website the application forms (OMB control #:
0938-1347 for IPPS, and OMB control #: 0938-0857 for OPPS) that
applicants must use to apply for IPPS new technology add-on payments
at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/newtech.html and for OPPS transitional pass-through
payments for devices at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HospitalOutpatientPPS/passthrough_payment.html). Each
application describes the information specifically requested from each
applicant, including what information is needed to support claims of
substantial clinical improvement. For example, CMS requests that the
applicant provide a summary of substantial clinical improvement
claim(s), along with the data supporting each claim. For IPPS new
technology add-on payments, in order to provide an opportunity for
public input prior to publication of each proposed rule, CMS publishes
a notice in the Federal Register to announce a town hall meeting at the
CMS Headquarters Office in Baltimore, MD, which provides an opportunity
for public discussion of the substantial clinical improvement criterion
for each IPPS application. This meeting can be attended in-person or
through a telephone line, and is also live-streamed on the CMS YouTube
web page. CMS considers each IPPS applicant's presentation made at the
town hall meeting, as well as written comments submitted on the
applications that were received by the applicable deadline, in our
evaluation of the new technology add-on payment applications in the
IPPS/LTCH PPS proposed rule. For both IPPS and OPPS applicants, CMS
summarizes each applicant's claim(s) of substantial clinical
improvement as part of its discussion of the entire application in the
relevant proposed rule, as well as any concerns regarding those claims.
In the relevant final rule for the IPPS, CMS summarizes and responds to
public comments received on the proposed rule and presents its decision
whether to approve or disapprove the application for additional payment
for the technology for the upcoming fiscal year. In the relevant final
rule for the OPPS, CMS similarly responds to public comments and
discusses its decision to approve or deny the application for separate
transitional pass-through payment for the device for the upcoming
calendar year.
A stakeholder comment received in response to the most recent New
Technology Town Hall meeting held in December 2018 expressed
appreciation for CMS' statements in the FY 2019 IPPS/LTCH PPS proposed
rule (83 FR 20278 through 20279) related to the relationship between
the data which satisfies FDA designations and the data which satisfies
the substantial clinical improvement criterion under the IPPS
regulations, and stated that the clarification would help future
applicants understand which types of data can serve as the foundation
for satisfying the substantial clinical improvement criterion.
Commenters also stated that CMS' statements presented in the FY 2019
IPPS/LTCH PPS proposed rule explaining that it accepts a wide range of
data, including peer-reviewed articles, study results, letters from
major associations, or other evidence that would support the conclusion
of substantial clinical improvement were appreciated. However, feedback
from applicants for new technology add-on payments and commenters in
prior years have indicated that it would be helpful for CMS to provide
greater guidance on what constitutes ``substantial clinical
improvement.'' We understand that greater clarity regarding what would
substantiate the requirements of this criterion would help the public,
including innovators, better understand how CMS evaluates new
technology applications for add-on payments and provide greater
predictability about which applications will meet the criterion for
substantial clinical improvement. We are considering potential
revisions to the substantial clinical improvement criteria under the
IPPS new technology add-on payment policy, and the OPPS transitional
pass-through payment policy for devices, and are seeking public
comments on the type of additional detail and guidance that the public
and applicants for new technology add-on payments would find useful.
This request for public comments is intended to be broad in scope and
provide a foundation for potential rulemaking in future years.
In addition to this broad request for public comments for potential
rulemaking in future years, as discussed in greater detail in section
II.H.7. of the preamble of this proposed rule, in order to respond to
stakeholder feedback requesting greater understanding of CMS' approach
to evaluating substantial clinical improvement, we are soliciting
comments from the public on specific changes or clarifications to the
IPPS and OPPS substantial clinical improvement criterion that CMS might
consider making in the FY 2020 IPPS/LTCH PPS final rule to provide
greater clarity and predictability.
In the applications for both the IPPS new technology add-on
payment, and for OPPS limited to the transitional pass-through payment
for devices, CMS lists the following criteria that it uses to determine
whether a new medical service or technology would represent a
substantial clinical improvement:
(1) The technology offers a treatment option for a patient
population unresponsive to, or ineligible for, currently available
treatments.
(2) The technology offers the ability to diagnose a medical
condition in a patient population where that medical condition is
currently undetectable or offers the ability to diagnose a medical
condition earlier in a patient population than allowed by currently
available methods. There must also be evidence that use of the device
to make a diagnosis affects the management of the patient.
(3) Use of the technology significantly improves clinical outcomes
for a patient population as compared to currently available treatments.
Some examples of outcomes that are frequently evaluated in studies of
technologies are the following:
Reduced mortality rate with use of the device;
Reduced rate of device-related complications;
Decreased rate of subsequent diagnostic or therapeutic
interventions (for example, due to reduced rate of recurrence of the
disease process);
Decreased number of future hospitalizations or physician
visits;
More rapid beneficial resolution of the disease process
treatment because of the use of the device;
Decreased pain, bleeding, or other quantifiable symptom;
and
Reduced recovery time.
CMS considers the totality of the substantial clinical improvement
claims and supporting data, as well as public
[[Page 19369]]
comments, when evaluating this aspect of each application.
We are requesting feedback on whether new or changed regulatory
provisions or new or changed guidance regarding additional aspects of
the substantial clinical improvement evaluation process in the
following areas would be helpful. Comments we receive in response to
the following general questions will inform future rulemaking after the
issuance of the final rule for FY 2020:
What role should substantial clinical improvement play in
our payment policies to ensure these policies do not discourage
appropriate utilization of new medical services and technologies?
How should CMS determine what existing technologies are
appropriate comparators to new technologies? How should CMS evaluate a
technology when its comparators have different measured clinical
outcomes?
Should CMS provide more specificity or greater clarity on
the types of evidence or study designs that may be considered by the
agency in evaluating substantial clinical improvement?
For example, what data should be used to demonstrate whether the
use of the technology substantially improves clinical outcomes for
patients relative to existing technologies? To what extent, if any,
should the data be focused on the Medicare population? What clinical
outcomes data and patient reported measures data should be assessed to
demonstrate substantial clinical improvement?
What particular types of study designs, types of inclusion and
exclusion criteria, or types of statistical methodologies, either
generally or in comparison to existing technologies, could a new
technology use to demonstrate that the technology meets the substantial
clinical improvement criterion?
Are there certain study designs that are technically or ethically
challenging for specific medical technologies and, if so, should that
be more explicitly reflected in the regulations?
Should potential limitations related to cross-trial comparisons
with any existing therapies be more explicitly reflected in the
regulations?
For non-inferiority studies, the goal of such studies is to show
that the difference between the new and active control treatment is
small--small enough to allow the known effectiveness of the active
control, based on its performance in past studies and the assumed
effectiveness of the active control in the current study, to support
the conclusion that the new technology is also effective. Are there
particular instances where non-inferiority studies should be considered
sufficient for an evaluation for substantial clinical improvement
because a non-inferiority study is the most appropriate study design
for a given technology?
Are there instances where it would be appropriate for CMS
to infer substantial clinical improvement (for example, technical or
financial challenges to study accrual)?
Should CMS consider evidence regarding the off-label use
of a new technology? If so, what is the appropriate use of that
evidence when evaluating a new technology for an FDA approved or
cleared indication? Are there other new technology add-on payment or
device pass-through payment changes that CMS should consider regarding
off-label use?
We note that, while additional specificity and guidance on
substantial clinical improvement may be helpful, this may also have the
unintended consequence of limiting future flexibility in the evaluation
of future applications, especially as new technologies are continually
emerging. How should CMS balance these considerations in the evaluation
of new technologies as it considers potential future steps? Towards
this end, would it be helpful to the goal of both predictability and
flexibility if the agency explained the types of information or
evidence that are not required for a finding of substantial clinical
improvement?
Currently, our regulations at Sec. 412.87 require that we
announce the results of the new technology add-on payment
determinations in the Federal Register as part of our annual updates
and changes to the IPPS. We also are seeking public comments on
revising this requirement to allow the new technology add-on payment
determinations, including but not limited to determinations of
substantial clinical improvement, to be announced annually in the
Federal Register separate from the annual updates and changes to the
IPPS.
7. Potential Revisions to the New Technology Add-On Payment and
Transitional Device Pass-Through Payment Substantial Clinical
Improvement Criterion for Applications Received Beginning in FY 2020
for IPPS and CY 2020 for OPPS
In addition to future possible rulemaking and further guidance
based on the responses to the general questions in the preceding
section, we also are considering adopting, in the FY 2020 IPPS/LTCH PPS
final rule, the following potential regulatory changes to the
substantial clinical improvement criteria for applications received
beginning in FY 2020 for IPPS (that is, for FY 2021 and subsequent new
technology add-on payment) and beginning in CY 2020 for OPPS, after
consideration of the public comments we receive in response to this
proposed rule. We also are seeking public comments on whether any or
all of these potential regulatory changes might be more appropriate as
changes in guidance rather than or in addition to changes to our
regulations.
Adopting a policy in regulation or sub-regulatory guidance
that explicitly specifies that the requirement for substantial clinical
improvement can be met if the applicant demonstrates that new
technology would be broadly adopted among applicable providers and
patients. A broad adoption criterion would reflect the choices of
patients and providers, and thus the marketplace, in determining
whether a technology represents a substantial clinical improvement.
This patient-centered approach would acknowledge that patients and
providers can together determine the potential for substantial clinical
improvement on an individual basis. As part of the policy being
considered, we would add a provision at Sec. 412.87(b)(1) and Sec.
419.66(c)(2) stating that ``substantially improves'' means, inter alia,
broad adoption by applicable providers and patients. We are seeking
public comments on whether, if such a provision is finalized, it should
specify that a ``majority'' is the appropriate way to further define
and specify ``broad adoption'', or if some other measure of ``broad''
(for example, more than the current standard-of-care, more than a
particular percentage) is more appropriate. Furthermore, we are seeking
public comments on whether to further specify that ``broad adoption''
is in the context of applicable providers and patients for the
technology, and does not mean broadly adopted across the entire IPPS or
OPPS. We are interested in whether commenters have particular
suggestions regarding how, in implementing such a provision, CMS could
provide other helpful regulatory clarification or sub-regulatory
guidance regarding how ``broad adoption'' could be measured and
demonstrated prospectively as a basis for substantial clinical
improvement. If adopted, such a policy would establish, by regulation,
predictability and clarity regarding the meaning and application of
substantial clinical improvement by providing a specific and clear path
to one way
[[Page 19370]]
substantial clinical improvement can be established.
Adopting in regulations or through sub-regulatory guidance
a definition that the term ``substantially improves'' means, inter
alia, that the new technology has demonstrated positive clinical
outcomes that are different from existing technologies. As part of the
policy being considered, we would specify that the term ``improves''
can always be met by comparison to existing technology. Then, we would
further specify that such improvement may always be demonstrated by
reference and comparison to diagnosis or treatment achieved by existing
technology. This would provide a standard for innovators that is
predictable and based on comparison to outcomes from existing
technologies, and would reflect that an evaluation of ``improvement''
involves a comparison relative to existing technology. If adopted, such
a policy, would establish, by regulation or through sub-regulatory
guidance, predictability and clarity regarding the meaning and
application of substantial clinical improvement by clarifying how
existing and new technologies are compared.
Adopting a policy in regulation or through sub-regulatory
guidance that specifies that ``substantially improves'' can be met
through real-world data and evidence, including a non-exhaustive list
of such data and evidence, but that such evidence is not a requirement.
Real-world evidence reflects usage in everyday settings outside of a
clinical trial, which is the majority of care delivered in the United
States. For example, between 3 percent and 5 percent of patients with
cancer are enrolled in a clinical trial.\393\
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\393\ https://ascopubs.org/doi/full/10.1200/jop.0922001.
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As part of the policy being considered, the regulation or sub-
regulatory guidance would list the kinds of data and evidence and
particular findings that CMS would consider in determining whether the
technology meets the substantial clinical improvement criterion and
that such kinds of data can be sufficient to meet that standard. Then,
we would provide a non-exhaustive list of such kinds of data and
findings, including: a decreased mortality rate; a reduction in length
of stay; a reduced recovery time; a reduced rate of at least one
significant complication; a decreased rate of at least one subsequent
diagnostic or therapeutic intervention; a reduction in at least one
clinically significant adverse event; a decreased number of future
hospitalizations or physician visits; a more rapid beneficial
resolution of the disease process treatment; an improvement in one or
more activities of daily living; or, an improved quality of life.
Outcomes relating to quality of life, length of stay, and activities of
daily living may reflect meaningful endpoints not often captured by
clinical trials or other pivotal trials designed primarily for
regulatory purposes. We are seeking public comments on whether we
should adopt such a policy and list, and if so, what the list should
contain. We also are seeking comments on whether, as a general matter,
data exists on patients' experience with new medical devices outside of
the clinician's office, on the effects of a treatment on patients'
activities of daily living, or on any of the other areas listed above.
These comments would at least inform our adoption of a policy in
regulations or sub-regulatory guidance. If adopted, such a policy,
would establish, by regulation or guidance, predictability and clarity
regarding the meaning and application of substantial clinical
improvement by providing a specific and clear path to one way
substantial clinical improvement can be established.
To address the impression that a peer-reviewed journal
article is required for the agency to find that a new technology meets
the requirement for substantial clinical improvement, explicitly
adopting a policy in regulations or sub-regulatory guidance that the
relevant information for purposes of a finding of substantial clinical
improvement may not require a peer-reviewed journal article. We
recognize the value of both academic and other traditional and non-
traditional emerging sources of information in determining substantial
clinical improvement. We are seeking public comments on whether, in
addition to making clear that a peer-reviewed journal article is not
required, types of relevant information that could be helpful should be
specified in such a regulation or guidance to include but not be
limited to other particular formats or sources of information, such as
consensus statements, white papers, patient surveys, editorials and
letters to the editor, systematic reviews, meta-analyses, inferences
from other literature or evidence, and case studies, reports or series,
in addition to randomized clinical trials, study results, or letters
from major associations, whether published or not. If adopted, such a
policy, would establish, by regulation or guidance, predictability and
clarity that the agency is open, in every case, to all types of
information in considering whether a new technology meets the
substantial clinical improvement criterion, consistent with our current
practice of not requiring any particular type of information.
Adopting a policy in regulations or sub-regulatory
guidance that, if there is a demonstrated substantial clinical
improvement based on the use of a new medical service or technology for
any subset of beneficiaries, the substantial clinical improvement
criterion may be met regardless of the size of that subset patient
population. Substantial clinical improvement may be confounded by
comorbidities, patient factors, or other concomitant therapies which
are not readily controlled in research studies. This potential change
recognizes that subset populations may have unique needs. As part of
the policy being considered, we would include a statement in regulation
or guidance that a technology may meet the ``substantial clinical
improvement'' criterion by demonstrating a substantial improvement for
any subset of beneficiaries regardless of size. This potential change
would reflect that many medical technologies are designed for limited
subset populations. Many personalized and precision medicine approaches
aspire for ``n=1 therapy.''
We are seeking public comments on whether, in adopting such a
policy, we should also specify that the add-on payment would be limited
to use in that subset of patient population. If not, why not? For
example, if a new technology that treats cancer only demonstrates
substantial clinical improvement for a select subset of patients with
that diagnosis, should the additional inpatient payments for use of the
new technology be limited to only when that new technology is used in
the treatment of that select subset of Medicare beneficiaries, and, if
so, how could that subset of patient population be defined in advance,
and in what circumstances should there be an exception to any such
limitation? If such a policy were adopted, how could it be constructed
or written to not create new limitations or obstacles to innovation
that are not present in our regulations today?
We also are seeking public comments as to whether there are special
approaches that CMS should adopt in regulations or through sub-
regulatory guidance for new technologies that treat low-prevalence
medical conditions in which substantial clinical improvement may be
more challenging to evaluate. Specifically, we are seeking comment on
how to categorize and specify these conditions, including how to define
``low-prevalence'', whether CMS should adopt any of the potential
changes
[[Page 19371]]
under consideration in this section which are not adopted more broadly,
or any special approaches suggested by commenters. The goal is to
establish, by regulation or guidance, predictability and clarity that
the substantial clinical improvement criterion can be met, either in
all cases or for cases involving low-prevalence medical conditions,
regardless of the size of the patient population which would benefit.
Adopting a policy in regulations or sub-regulatory
guidance that specifically addresses that the substantial clinical
improvement criterion can be met without regard to the FDA pathway for
the technology. As part of the policy being considered, we would
clarify in regulation that the notion of ``improvement'' includes
situations where there is an extant technology such as a predicate
device for 510(k) purposes, and explicitly state that the agency will
not require a device to be approved or cleared through a basis other
than a 510(k) clearance in order for the device to be considered a
substantial clinical improvement. If adopted, the policy described
here, would establish, by regulation or guidance, predictability and
clarity by clarifying that the substantial clinical improvement
criterion can be met without regard to the FDA pathway for the
technology, consistent with our current practice.
We are soliciting comments on the potential revisions and
regulatory or sub-regulatory changes described above, and also welcome
suggestions on other information that would help us clarify and/or
modify in the FY 2020 IPPS/LTCH PPS final rule or through sub-
regulatory guidance CMS' expectations regarding substantial clinical
improvement for payments for new technologies.
8. Proposed Alternative Inpatient New Technology Add-On Payment Pathway
for Transformative New Devices
Under section 1886(d)(5)(K)(vi) of the Act, a medical service or
technology will be considered a ``new medical service or technology''
if the service or technology meets criteria established by the
Secretary after notice and an opportunity for public comment. For a
more complete discussion of the establishment of the current criteria
for the new technology add-on payment, we refer readers to the
September 7, 2001 final rule (66 FR 46913), where we finalized the
``substantial improvement'' criterion to limit new technology add-on
payments under the IPPS to those technologies that afford clear
improvements over the use of previously available technologies.
Specifically, we stated that we would evaluate a request for new
technology add-on payments against the following criteria to determine
if the new medical service or technology would represent a substantial
clinical improvement over existing technologies:
The device offers a treatment option for a patient
population unresponsive to, or ineligible for, currently available
treatments.
The device offers the ability to diagnose a medical
condition in a patient population where that medical condition is
currently undetectable or offers the ability to diagnose a medical
condition earlier in a patient population than allowed by currently
available methods. There must also be evidence that use of the device
to make a diagnosis affects the management of the patient.
Use of the device significantly improves clinical outcomes
for a patient population as compared to currently available treatments.
We also noted examples of outcomes that are frequently evaluated in
studies of medical devices.
In the September 7, 2001 final rule (66 FR 46913), we stated that
we believed the special payments for new technology should be limited
to those new technologies that have been demonstrated to represent a
substantial improvement in caring for Medicare beneficiaries, such that
there is a clear advantage to creating a payment incentive for
physicians and hospitals to utilize the new technology. We also stated
that where such an improvement is not demonstrated, we continued to
believe the incentives of the DRG system would provide a useful balance
to the introduction of new technologies. In that regard, we also
pointed out that various new technologies introduced over the years
have been demonstrated to have been less effective than initially
thought, or in some cases even potentially harmful. We stated that we
believe that it is in the best interest of Medicare beneficiaries to
proceed very carefully with respect to the incentives created to
quickly adopt new technology.
Since 2001 when we first established the substantial clinical
improvement criterion, the FDA programs for helping to expedite the
development and review of transformative new technologies that are
intended to treat serious conditions and address unmet medical needs
(referred to as FDA's expedited programs) have continued to evolve in
tandem with advances in medical innovations and technology. We note
that at the time of the development of the September 7, 2001 final
rule, devices were the predominant new technology entering the market
and, therefore, the substantial clinical improvement criterion was
developed with innovative new devices as a focus. At the time, the FDA
had three expedited programs (Priority Review, Accelerated Approval,
and Fast Track) for drugs and biologicals and no expedited programs for
devices. Now, as described in FDA guidance (available on the website
at: https://www.fda.gov/downloads/Drugs/Guidances/UCM358301.pdf and
https://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/UCM581664.pdf), there are
four expedited FDA programs for drugs (the three expedited FDA programs
named above and a fourth, Breakthrough Therapy, which was established
in 2012) and one expedited FDA program for devices, the Breakthrough
Devices Program. The 21st Century Cures Act (Cures Act) (Pub. L. 144-
255) established the Breakthrough Devices Program to expedite the
development of, and provide for priority review of, medical devices and
device-led combination products that provide for more effective
treatment or diagnosis of life-threatening or irreversibly debilitating
diseases or conditions and which meet one of the following four
criteria: that represent breakthrough technologies; for which no
approved or cleared alternatives exist; that offer significant
advantages over existing approved or cleared alternatives, including
the potential, compared to existing approved alternatives, to reduce or
eliminate the need for hospitalization, improve patient quality of
life, facilitate patients' ability to manage their own care (such as
through self-directed personal assistance), or establish long-term
clinical efficiencies; or the availability of which is in the best
interest of patients.
Some stakeholders over the years have requested that new
technologies that receive marketing authorization and are part of an
FDA expedited program be deemed as representing a substantial clinical
improvement for purposes of the inpatient new technology add-on
payments, even in the initial rulemaking on this issue. We understand
this request would arguably create administrative efficiency because
they currently view the two sets of criteria as the same, overlapping,
similar, or otherwise duplicative or unnecessary. As discussed in the
September 7, 2001 final rule in which we initially adopted the
requirement that a new technology must represent a substantial clinical
improvement, we proposed to consult a
[[Page 19372]]
Federal panel of experts in evaluating new technology under the
``substantial improvement'' criterion. One commenter believed the panel
would be unnecessary and that CMS should automatically deem drugs and
biologicals approved by FDA that were included in its expedited
programs (which the commenter referred to as ``fast track'' processes)
as new technology (66 FR 46914). We stated in response that the panel
would consider all relevant information (including FDA expedited
program approval) in making its determinations. However, we stated that
we did not envision an automatic approval process.
Since 2001, we have continued to receive similar comments. More
recently, in response to the FY 2019 New Technology Town Hall meeting
notice (83 FR 50379) and the meeting, a commenter stated that the Food
and Drug Administration Modernization Act of 1997 authorized a category
of medical devices that are eligible for FDA Priority Review
designation (83 FR 20278). The commenter explained that, to qualify,
products must be designated by the FDA as offering the potential for
significant improvements in the diagnosis or treatment of the most
serious illnesses, including those that are life-threatening or
irreversibly debilitating. The commenter indicated that the processes
by which products meeting the statutory standard for priority review
are considered by the FDA are specified in greater detail in FDA's
Expedited Access Pathway Program, and in the 21st Century Cures Act.
The commenter believed that the criteria for FDA Priority Review
designation of devices are very similar to the substantial clinical
improvement criteria and, therefore, devices used in the inpatient
setting determined to be eligible for expedited review and approved by
the FDA should automatically be considered as meeting the substantial
clinical improvement criterion, without further consideration by CMS.
The Administration is committed to addressing barriers to
healthcare innovation and ensuring Medicare beneficiaries have access
to critical and life-saving new cures and technologies that improve
beneficiary health outcomes. As detailed in the President's FY 2020
Budget, HHS is pursuing several policies that will instill greater
transparency and consistency around how Medicare covers and pays for
innovative technology.
Therefore, given the FDA programs for helping to expedite the
development and review of transformative new drugs and devices that
meet expedited program criteria (that is, new drugs and devices that
treat serious or life-threatening diseases or conditions for which
there is an unmet medical need), we considered whether it would also be
appropriate to similarly facilitate access to these transformative new
technologies for Medicare beneficiaries taking into consideration that
marketing authorization (that is, Premarket Approval (PMA); 510(k)
clearance; the granting of a De Novo classification request; or
approval of a New Drug Application (NDA)) for a product that is the
subject of one of FDA's expedited programs could lead to situations
where the evidence base for demonstrating substantial clinical
improvement in accordance with CMS' current standard has not fully
developed at the time of FDA marketing authorization (that is, PMA;
510(k) clearance; the granting of a De Novo classification request; or
approval of a NDA) (as applicable). We also considered whether FDA
marketing authorization of a product that is part of an FDA expedited
program is evidence that the product is sufficiently different from
existing products for purposes of newness.
After consideration of these issues, and consistent with the
Administration's commitment to addressing barriers to healthcare
innovation and ensuring Medicare beneficiaries have access to critical
and life-saving new cures and technologies that improve beneficiary
health outcomes, we concluded that it would be appropriate to develop
an alternative pathway for transformative medical devices. In
situations where a new medical device is part of the Breakthrough
Devices Program and has received FDA marketing authorization (that is,
the device has received PMA; 510(k) clearance; or the granting of a De
Novo classification request), we are proposing an alternative inpatient
new technology add-on payment pathway to facilitate access to this
technology for Medicare beneficiaries.
Specifically, we are proposing that, for applications received for
new technology add-on payments for FY 2021 and subsequent fiscal years,
if a medical device is part of the FDA's Breakthrough Devices Program
and received FDA marketing authorization, it would be considered new
and not substantially similar to an existing technology for purposes of
the new technology add-on payment under the IPPS. In light of the
criteria applied under the FDA's Breakthrough Device Program, and
because the technology may not have a sufficient evidence base to
demonstrate substantial clinical improvement at the time of FDA
marketing authorization, we also are proposing that the medical device
would not need to meet the requirement under Sec. 412.87(b)(1) that it
represent an advance that substantially improves, relative to
technologies previously available, the diagnosis or treatment of
Medicare beneficiaries. We are proposing to add a new paragraph (c)
under Sec. 412.87 to codify this proposed policy; existing paragraph
(c) would be redesignated as paragraph (d) and amendments would be made
to proposed redesignated paragraph (d) to reflect this proposed
alternative pathway and to make clear that a new medical device may
only be approved under Sec. 412.87(b) or proposed new Sec. 412.87(c).
Under this proposed alternative pathway, a medical device that has
received FDA marketing authorization (that is, has been approved or
cleared by, or had a De Novo classification request granted by, the
FDA) and that is part of the FDA's Breakthrough Devices Program would
need to meet the cost criterion under Sec. 412.87(b)(3), as reflected
in proposed new Sec. 412.87(c)(3), and would be considered new as
reflected in proposed Sec. 412.87(c)(2).
Given the lack of an evidence base to demonstrate substantial
clinical improvement at the time of FDA marketing authorization, we are
soliciting public comment on how CMS should weigh the benefits of this
proposed alternative pathway to facilitate beneficiary access to
transformative new medical devices, including the benefits of
mitigating potential delayed access to innovation and adoption, against
any potential risks, such as the risk of adverse events or negative
outcomes that might come to light later.
We further note that section 1886(d)(5)(K)(ii)(II) of the Act
provides for the collection of data with respect to the costs of a new
medical service or technology described in subclause (I) for a period
of not less than 2 years and not more than 3 years beginning on the
date on which an inpatient hospital code is issued with respect to the
service or technology. We also are seeking public comments on whether
the newness period under the proposed alternative new technology add-on
payment pathway for transformative new medical devices should be
limited to a period of time sufficient for the evidence base for the
new transformative medical device to develop to the point where a
substantial clinical improvement determination can be made (for
example, 1 to 2 years after approval, depending on whether the
transformative new medical device would be eligible for a third year of
new
[[Page 19373]]
technology add-on payments). We note that, if we were to adopt such a
policy in the future, the proposed amended regulation text would be
revised accordingly. We further note that the newness period for a
transformative new medical device cannot exceed 3 years, regardless of
whether it is approved under the current eligibility criteria, the
proposed alternative pathway, or potentially first under the proposed
alternative pathway, and subsequently under the current eligibility
criteria later in its newness period.
As stated above, for the reasons discussed in section I.O. of
Appendix A to this proposed rule, we are not proposing an alternative
inpatient new technology add-on payment pathway for drugs at this time.
9. Proposed Change to the Calculation of the Inpatient New Technology
Add-On Payment
As noted earlier, section 1886(d)(5)(K)(ii)(I) of the Act specifies
that a new medical service or technology may be considered for a new
technology add-on payment if, based on the estimated costs incurred
with respect to discharges involving such service or technology, the
DRG prospective payment rate otherwise applicable to such discharges
under this subsection is inadequate. As discussed in the September 7,
2001 final rule, in deciding which treatment is most appropriate for
any particular patient, it is expected that physicians would balance
the clinical needs of patients with the efficacy and costliness of
particular treatments. In the May 4, 2001 proposed rule (66 FR 22695),
we stated that we believed it is appropriate to limit the additional
payment to 50 percent of the additional cost of the new technology to
appropriately balance the incentives. We stated that this proposed
limit would provide hospitals an incentive for continued cost-effective
behavior in relation to the overall costs of the case. In addition, we
stated that we believed hospitals would face an incentive to balance
the desirability of using the new technology versus the old; otherwise,
there would be a large and perhaps inappropriate incentive to use the
new technology.
As such, the current calculation of the new technology add-on
payment is based on the cost to hospitals for the new medical service
or technology. Specifically, under Sec. 412.88, if the costs of the
discharge (determined by applying CCRs as described in Sec. 412.84(h))
exceed the full DRG payment (including payments for IME and DSH, but
excluding outlier payments), Medicare will make an add-on payment equal
to the lesser of: (1) 50 percent of the costs of the new medical
service or technology; or (2) 50 percent of the amount by which the
costs of the case exceed the standard DRG payment. Unless the discharge
qualifies for an outlier payment, the additional Medicare payment is
limited to the full MS-DRG payment plus 50 percent of the estimated
costs of the new technology or medical service.
Since the 50-percent limit to the new technology add-on payment was
first established, we have received feedback from stakeholders that our
current policy does not adequately reflect the costs of new technology
and does not sufficiently support healthcare innovations. For example,
stakeholders have stated that a maximum add-on payment of 50 percent
does not allow for accurate payment of a new technology with an
unprecedented high cost, such as the CAR T-cell technologies
KYMRIAH[supreg] and YESCARTA[supreg] (83 FR 41173).
After consideration of the concerns raised by commenters and other
stakeholders, and consistent with the Administration's commitment to
addressing barriers to healthcare innovation and ensuring Medicare
beneficiaries have access to critical and life-saving new cures and
technologies that improve beneficiary health outcomes, we agree that
there may be merit to the recommendations to increase the maximum add-
on amount, and that capping the add-on payment amount at 50 percent
could in some cases no longer provide a sufficient incentive for the
use of a new technology. Costs of new medical technologies have
increased over the years to the point where 50 percent of the estimated
cost may not be adequate, and we have received feedback that hospitals
may potentially choose not to provide certain technologies for that
reason alone.
At the same time, we continue to believe that it is important to
preserve the incentives inherent under an average-based prospective
payment system through the use of a percentage of the estimated costs
of a new technology or service. We stated in the September 7, 2001
final rule (66 FR 46919) that we do not believe it is appropriate to
pay an add-on amount equal to 100 percent of the costs of new
technology because there is no similar methodology to reduce payments
for cost-saving technology. For example, as new technologies permit the
development of less-invasive surgical procedures, the total costs per
case may begin to decline as patients recover and leave the hospital
sooner. Finally, we stated our concern that, because these payments are
linked to charges submitted by hospitals, there is the potential that
hospitals may adapt their charge structure to maximize payments for
DRGs that include eligible new technologies. The higher the marginal
cost factor, the greater the incentive hospitals face in this regard.
It is challenging to determine empirically a precise payment
percentage between the current 50 percent and 100 percent payment that
would be the most appropriate. We believe that 65 percent is an
incremental increase that would reasonably balance the need to maintain
the incentives inherent to the prospective payment system while also
encouraging the development and use of new technologies.
Therefore, we are proposing that, beginning with discharges on or
after October 1, 2019, if the costs of a discharge involving a new
technology (determined by applying CCRs as described in Sec.
412.84(h)) exceed the full DRG payment (including payments for IME and
DSH, but excluding outlier payments), Medicare will make an add-on
payment equal to the lesser of: (1) 65 percent of the costs of the new
medical service or technology; or (2) 65 percent of the amount by which
the costs of the case exceed the standard DRG payment. Unless the
discharge qualifies for an outlier payment, the additional Medicare
payment would be limited to the full MS-DRG payment plus 65 percent of
the estimated costs of the new technology or medical service. We also
are proposing to revise paragraphs (a)(2) and (b) under Sec. 412.88 to
reflect these proposed changes to the calculation of the new technology
add-on payment amount beginning in FY 2020.
III. Proposed Changes to the Hospital Wage Index for Acute Care
Hospitals
A. Background
1. Legislative Authority
Section 1886(d)(3)(E) of the Act requires that, as part of the
methodology for determining prospective payments to hospitals, the
Secretary adjust the standardized amounts for area differences in
hospital wage levels by a factor (established by the Secretary)
reflecting the relative hospital wage level in the geographic area of
the hospital compared to the national average hospital wage level. We
currently define hospital labor market areas based on the delineations
of statistical areas established by the Office of Management and Budget
(OMB). A
[[Page 19374]]
discussion of the proposed FY 2020 hospital wage index based on the
statistical areas appears under section III.A.2. of the preamble of
this proposed rule.
Section 1886(d)(3)(E) of the Act requires the Secretary to update
the wage index annually and to base the update on a survey of wages and
wage-related costs of short-term, acute care hospitals. (CMS collects
these data on the Medicare cost report, CMS Form 2552-10, Worksheet S-
3, Parts II, III, and IV. The OMB control number for approved
collection of this information is 0938-0050.) This provision also
requires that any updates or adjustments to the wage index be made in a
manner that ensures that aggregate payments to hospitals are not
affected by the change in the wage index. The proposed adjustment for
FY 2020 is discussed in section II.B. of the Addendum to this proposed
rule.
As discussed in section III.I. of the preamble of this proposed
rule, we also take into account the geographic reclassification of
hospitals in accordance with sections 1886(d)(8)(B) and 1886(d)(10) of
the Act when calculating IPPS payment amounts. Under section
1886(d)(8)(D) of the Act, the Secretary is required to adjust the
standardized amounts so as to ensure that aggregate payments under the
IPPS after implementation of the provisions of sections 1886(d)(8)(B),
1886(d)(8)(C), and 1886(d)(10) of the Act are equal to the aggregate
prospective payments that would have been made absent these provisions.
The proposed budget neutrality adjustment for FY 2020 is discussed in
section II.A.4.b. of the Addendum to this proposed rule.
Section 1886(d)(3)(E) of the Act also provides for the collection
of data every 3 years on the occupational mix of employees for short-
term, acute care hospitals participating in the Medicare program, in
order to construct an occupational mix adjustment to the wage index. A
discussion of the occupational mix adjustment that we are proposing to
apply to the FY 2020 wage index appears under sections III.E.3. and F.
of the preamble of this proposed rule.
2. Core-Based Statistical Areas (CBSAs) for the Proposed FY 2020
Hospital Wage Index
The wage index is calculated and assigned to hospitals on the basis
of the labor market area in which the hospital is located. Under
section 1886(d)(3)(E) of the Act, beginning with FY 2005, we delineate
hospital labor market areas based on OMB-established Core-Based
Statistical Areas (CBSAs). The current statistical areas (which were
implemented beginning with FY 2015) are based on revised OMB
delineations issued on February 28, 2013, in OMB Bulletin No. 13-01.
OMB Bulletin No. 13-01 established revised delineations for
Metropolitan Statistical Areas, Micropolitan Statistical Areas, and
Combined Statistical Areas in the United States and Puerto Rico based
on the 2010 Census, and provided guidance on the use of the
delineations of these statistical areas using standards published on
June 28, 2010 in the Federal Register (75 FR 37246 through 37252). We
refer readers to the FY 2015 IPPS/LTCH PPS final rule (79 FR 49951
through 49963) for a full discussion of our implementation of the OMB
labor market area delineations beginning with the FY 2015 wage index.
Generally, OMB issues major revisions to statistical areas every 10
years, based on the results of the decennial census. However, OMB
occasionally issues minor updates and revisions to statistical areas in
the years between the decennial censuses through OMB Bulletins. On July
15, 2015, OMB issued OMB Bulletin No. 15-01, which provided updates to
and superseded OMB Bulletin No. 13-01 that was issued on February 28,
2013. The attachment to OMB Bulletin No. 15-01 provided detailed
information on the update to statistical areas since February 28, 2013.
The updates provided in OMB Bulletin No. 15-01 were based on the
application of the 2010 Standards for Delineating Metropolitan and
Micropolitan Statistical Areas to Census Bureau population estimates
for July 1, 2012 and July 1, 2013. In the FY 2017 IPPS/LTCH PPS final
rule (81 FR 56913), we adopted the updates set forth in OMB Bulletin
No. 15-01 effective October 1, 2016, beginning with the FY 2017 wage
index. For a complete discussion of the adoption of the updates set
forth in OMB Bulletin No. 15-01, we refer readers to the FY 2017 IPPS/
LTCH PPS final rule. In the FY 2018 IPPS/LTCH PPS final rule (82 FR
38130), we continued to use the OMB delineations that were adopted
beginning with FY 2015 to calculate the area wage indexes, with updates
as reflected in OMB Bulletin No. 15-01 specified in the FY 2017 IPPS/
LTCH PPS final rule.
On August 15, 2017, OMB issued OMB Bulletin No. 17-01, which
provided updates to and superseded OMB Bulletin No. 15-01 that was
issued on July 15, 2015. The attachments to OMB Bulletin No. 17-01
provide detailed information on the update to statistical areas since
July 15, 2015, and are based on the application of the 2010 Standards
for Delineating Metropolitan and Micropolitan Statistical Areas to
Census Bureau population estimates for July 1, 2014 and July 1, 2015.
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41362 through 41363), we
adopted the updates set forth in OMB Bulletin No. 17-01 effective
October 1, 2018, beginning with the FY 2019 wage index. For a complete
discussion of the adoption of the updates set forth in OMB Bulletin No.
17-01, we refer readers to the FY 2019 IPPS/LTCH PPS final rule.
For FY 2020, we are continuing to use the OMB delineations that
were adopted beginning with FY 2015 (based on the revised delineations
issued in OMB Bulletin No. 13-01) to calculate the area wage indexes,
with updates as reflected in OMB Bulletin Nos. 15-01 and 17-01.
3. Codes for Constituent Counties in CBSAs
CBSAs are made up of one or more constituent counties. Each CBSA
and constituent county has its own unique identifying codes. There are
two different lists of codes associated with counties: Social Security
Administration (SSA) codes and Federal Information Processing Standard
(FIPS) codes. Historically, CMS has listed and used SSA and FIPS county
codes to identify and crosswalk counties to CBSA codes for purposes of
the hospital wage index. As we discussed in the FY 2018 IPPS/LTCH PPS
final rule (82 FR 38129 through 38130), we have learned that SSA county
codes are no longer being maintained and updated. However, the FIPS
codes continue to be maintained by the U.S. Census Bureau. We believe
that using the latest FIPS codes will allow us to maintain a more
accurate and up-to-date payment system that reflects the reality of
population shifts and labor market conditions.
The Census Bureau's most current statistical area information is
derived from ongoing census data received since 2010; the most recent
data are from 2015. The Census Bureau maintains a complete list of
changes to counties or county equivalent entities on the website at:
https://www.census.gov/geo/reference/county-changes.html. We believe
that it is important to use the latest counties or county equivalent
entities in order to properly crosswalk hospitals from a county to a
CBSA for purposes of the hospital wage index used under the IPPS.
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38129 through
38130), we adopted a policy to discontinue the use of the SSA county
codes and began using only the FIPS county codes for purposes of
crosswalking counties to
[[Page 19375]]
CBSAs. In addition, in the same rule, we implemented the latest FIPS
code updates which were effective October 1, 2017, beginning with the
FY 2018 wage indexes. These updates have been used to calculate the
wage indexes in a manner generally consistent with the CBSA-based
methodologies finalized in the FY 2005 IPPS final rule and the FY 2015
IPPS/LTCH PPS final rule.
For FY 2020, we are continuing to use only the FIPS county codes
for purposes of crosswalking counties to CBSAs. For FY 2020, Tables 2
and 3 associated with this proposed rule and the County to CBSA
Crosswalk File and Urban CBSAs and Constituent Counties for Acute Care
Hospitals File posted on the CMS website reflect these county changes.
B. Worksheet S-3 Wage Data for the Proposed FY 2020 Wage Index
The proposed FY 2020 wage index values are based on the data
collected from the Medicare cost reports submitted by hospitals for
cost reporting periods beginning in FY 2016 (the FY 2019 wage indexes
were based on data from cost reporting periods beginning during FY
2015).
1. Included Categories of Costs
The proposed FY 2020 wage index includes all of the following
categories of data associated with costs paid under the IPPS (as well
as outpatient costs):
Salaries and hours from short-term, acute care hospitals
(including paid lunch hours and hours associated with military leave
and jury duty);
Home office costs and hours;
Certain contract labor costs and hours, which include
direct patient care, certain top management, pharmacy, laboratory, and
nonteaching physician Part A services, and certain contract indirect
patient care services (as discussed in the FY 2008 final rule with
comment period (72 FR 47315 through 47317)); and
Wage-related costs, including pension costs (based on
policies adopted in the FY 2012 IPPS/LTCH PPS final rule (76 FR 51586
through 51590)) and other deferred compensation costs.
2. Excluded Categories of Costs
Consistent with the wage index methodology for FY 2019, the
proposed wage index for FY 2020 also excludes the direct and overhead
salaries and hours for services not subject to IPPS payment, such as
skilled nursing facility (SNF) services, home health services, costs
related to GME (teaching physicians and residents) and certified
registered nurse anesthetists (CRNAs), and other subprovider components
that are not paid under the IPPS. The proposed FY 2020 wage index also
excludes the salaries, hours, and wage-related costs of hospital-based
rural health clinics (RHCs), and Federally qualified health centers
(FQHCs) because Medicare pays for these costs outside of the IPPS (68
FR 45395). In addition, salaries, hours, and wage-related costs of CAHs
are excluded from the wage index for the reasons explained in the FY
2004 IPPS final rule (68 FR 45397 through 45398). For FY 2020 and
subsequent years, other wage-related costs are also excluded from the
calculation of the wage index. As discussed in the FY 2019 IPPS/LTCH
final rule (83 FR 41365 through 41369), other wage-related costs
reported on Worksheet S-3, Part II, Line 18 and Worksheet S-3, Part IV,
Line 25 and subscripts, as well as all other wage-related costs, such
as contract labor costs, are excluded from the calculation of the wage
index.
3. Use of Wage Index Data by Suppliers and Providers Other Than Acute
Care Hospitals Under the IPPS
Data collected for the IPPS wage index also are currently used to
calculate wage indexes applicable to suppliers and other providers,
such as SNFs, home health agencies (HHAs), ambulatory surgical centers
(ASCs), and hospices. In addition, they are used for prospective
payments to IRFs, IPFs, and LTCHs, and for hospital outpatient
services. We note that, in the IPPS rules, we do not address comments
pertaining to the wage indexes of any supplier or provider except IPPS
providers and LTCHs. Such comments should be made in response to
separate proposed rules for those suppliers and providers.
C. Verification of Worksheet S-3 Wage Data
The wage data for the proposed FY 2020 wage index were obtained
from Worksheet S-3, Parts II and III of the Medicare cost report (Form
CMS-2552-10, OMB Control Number 0938-0050) for cost reporting periods
beginning on or after October 1, 2015, and before October 1, 2016. For
wage index purposes, we refer to cost reports during this period as the
``FY 2016 cost report,'' the ``FY 2016 wage data,'' or the ``FY 2016
data.'' Instructions for completing the wage index sections of
Worksheet S-3 are included in the Provider Reimbursement Manual (PRM),
Part 2 (Pub. 15-2), Chapter 40, Sections 4005.2 through 4005.4. The
data file used to construct the proposed FY 2020 wage index includes FY
2016 data submitted to us as of February 7, 2019. As in past years, we
performed an extensive review of the wage data, mostly through the use
of edits designed to identify aberrant data.
We asked our MACs to revise or verify data elements that result in
specific edit failures. For the proposed FY 2020 wage index, we
identified and excluded 81 providers with aberrant data that should not
be included in the wage index, although if data elements for some of
these providers are corrected, we intend to include data from those
providers in the final FY 2020 wage index. We also adjusted certain
aberrant data and included these data in the proposed wage index. For
example, in situations where a hospital did not have documentable
salaries, wages, and hours for housekeeping and dietary services, we
imputed estimates, in accordance with policies established in the FY
2015 IPPS/LTCH PPS final rule (79 FR 49965 through 49967). We
instructed MACs to complete their data verification of questionable
data elements and to transmit any changes to the wage data no later
than March 22, 2019. In addition, as a result of the April and May
appeals processes, and posting of the April 30, 2019 PUF, we may make
additional revisions to the FY 2020 wage data, as described further
below. The revised data would be reflected in the FY 2020 IPPS/LTCH PPS
final rule.
Among the hospitals we identified and excluded with aberrant data
that should not be included in the proposed FY 2020 wage index are
eight hospitals that are part of a health care delivery system that is
unique in several ways. The vast majority of the system's hospitals
(38) are located in a single State, with one union representing most of
their hospital employees in the ``northern'' region of the State, while
another union represents most of their hospital employees in the
``southern'' region of the State. The salaries negotiated do not
reflect competitive local labor market salaries; rather, the salaries
reflect negotiated salary rates for the ``northern'' and ``southern''
regions of the State respectively. For example, all medical assistants
in the ``northern'' region start at $24.31 per hour, and medical
assistants in the ``southern'' region start at $20.36 per hour. Thus,
all salaries for similar positions and levels of experience in the
northern region, for example, are the same regardless of prevailing
labor market conditions in the area in which the hospital is located.
In addition, this chain is part of a managed care organization and an
integrated delivery system wherein the hospitals rely on the system's
health care plans for funding. For the FY 2020 proposed wage index
calculation, we have identified and excluded eight of the hospitals
that are part of this health
[[Page 19376]]
care system. The average hourly wages of these eight hospitals differ
most from their respective CBSA average hourly wages, and there is a
large gap between the average hourly wage of each of the eight
hospitals and the next closest average hourly wage in their respective
CBSAs. We do not believe that the average hourly wages of these eight
hospitals accurately reflect the economic conditions in their
respective labor market areas during the FY 2016 cost reporting period.
Therefore, we believe the inclusion of the wage data for these eight
hospitals in the proposed wage index would not ensure that the FY 2020
wage index represents the relative hospital wage level in the
geographic area of the hospital as compared to the national average of
wages. Rather, the inclusion of these data would distort the comparison
of the average hourly wage of each of these hospitals' labor market
areas to the national average hourly wage. We believe that under
section 1886(d)(3)(E) of the Act, which requires the Secretary to
establish an adjustment factor (the wage index) reflecting the relative
hospital wage level in the geographic area of a hospital compared to
the national average hospital wage level, we have the discretion to
remove hospital data from the wage index that is not reflective of the
relative hospital wage level in the hospitals' geographic area. In
previous rulemaking (80 FR 49491), we explained that we remove
hospitals from the wage index because their average hourly wages are
either extraordinarily high or extraordinarily low compared to their
labor market areas, even though their data were properly documented.
For this reason, we have removed the data of other hospitals in the
past; for example, data from government-owned hospitals and hospitals
providing unique or niche services which affect their average hourly
wages. We note that we are considering removing all of the hospitals in
this health care system from the FY 2021 and subsequent wage index
calculations, not because they are failing edits due to inaccuracy, but
because of the uniqueness of this chain of hospitals, in particular,
the fact that the salaries of their employees are not based on local
labor market rates.
In constructing the proposed FY 2020 wage index, we included the
wage data for facilities that were IPPS hospitals in FY 2016, inclusive
of those facilities that have since terminated their participation in
the program as hospitals, as long as those data did not fail any of our
edits for reasonableness. We believe that including the wage data for
these hospitals is, in general, appropriate to reflect the economic
conditions in the various labor market areas during the relevant past
period and to ensure that the current wage index represents the labor
market area's current wages as compared to the national average of
wages. However, we excluded the wage data for CAHs as discussed in the
FY 2004 IPPS final rule (68 FR 45397 through 45398); that is, any
hospital that is designated as a CAH by 7 days prior to the publication
of the preliminary wage index public use file (PUF) is excluded from
the calculation of the wage index. For this proposed rule, we removed 4
hospitals that converted to CAH status on or after January 26, 2018,
the cut-off date for CAH exclusion from the FY 2019 wage index, and
through and including January 24, 2019, the cut-off date for CAH
exclusion from the FY 2020 wage index. After excluding CAHs and
hospitals with aberrant data, we calculated the proposed wage index
using the Worksheet S-3, Parts II and III wage data of 3,221 hospitals.
For the proposed FY 2020 wage index, we allotted the wages and
hours data for a multicampus hospital among the different labor market
areas where its campuses are located in the same manner that we
allotted such hospitals' data in the FY 2019 wage index (83 FR 41364
through 41365); that is, using campus full-time equivalent (FTE)
percentages as originally finalized in the FY 2012 IPPS/LTCH PPS final
rule (76 FR 51591). Table 2, which contains the proposed FY 2020 wage
index associated with this proposed rule (available via the internet on
the CMS website), includes separate wage data for the campuses of 17
multicampus hospitals. The following chart lists the multicampus
hospitals by CSA certification number (CCN) and the FTE percentages on
which the wages and hours of each campus were allotted to their
respective labor market areas:
------------------------------------------------------------------------
Full-time
equivalent
CCN of multicampus hospital (FTE)
percentages
------------------------------------------------------------------------
050121.................................................. 0.83
05B121.................................................. 0.17
070033.................................................. 0.92
07B033.................................................. 0.08
100029.................................................. 0.54
10B029.................................................. 0.46
100167.................................................. 0.39
10B167.................................................. 0.61
140010.................................................. 0.83
14B010.................................................. 0.17
220074.................................................. 0.86
22B074.................................................. 0.14
330195.................................................. 0.90
33B195.................................................. 0.10
330234.................................................. 0.73
33B234.................................................. 0.27
340115.................................................. 0.96
34B115.................................................. 0.04
360020.................................................. 0.99
36B020.................................................. 0.01
370041.................................................. 0.89
37B041.................................................. 0.11
390006.................................................. 0.94
39B006.................................................. 0.06
390115.................................................. 0.86
39B115.................................................. 0.14
390142.................................................. 0.83
39B142.................................................. 0.17
460051.................................................. 0.82
46B051.................................................. 0.18
510022.................................................. 0.95
51B022.................................................. 0.05
670062.................................................. 0.55
67B062.................................................. 0.45
------------------------------------------------------------------------
We note that, in past years, in Table 2, we have placed a ``B'' to
designate the subordinate campus in the fourth position of the hospital
CCN. However, for the FY 2019 IPPS/LTCH PPS proposed and final rules
and subsequent rules, we have moved the ``B'' to the third position of
the CCN. Because all IPPS hospitals have a ``0'' in the third position
of the CCN, we believe that placement of the ``B'' in this third
position, instead of the ``0'' for the subordinate campus, is the most
efficient method of identification and interferes the least with the
other, variable, digits in the CCN.
D. Method for Computing the Proposed FY 2020 Unadjusted Wage Index
In the FY 2019 IPPS/LTCH PPS proposed rule (83 FR 41365), we
indicated we were committed to transforming the health care delivery
system, including the Medicare program, by putting an additional focus
on patient-centered care and working with providers, physicians, and
patients to improve outcomes. One key to that transformation is
ensuring that the Medicare payment rates are as accurate and
appropriate as possible, consistent with the law. We invited the public
to submit comments, suggestions, and recommendations for regulatory and
policy changes to address wage index disparities. Our proposals for FY
2020 to address wage index disparities, particularly for rural
hospitals, to the extent permitted under current law, are discussed in
section III.N. of the preamble to this proposed rule. We continue to
believe that broader statutory wage index reform is needed.
[[Page 19377]]
1. Proposed Methodology for FY 2020
The method used to compute the proposed FY 2020 wage index without
an occupational mix adjustment follows the same methodology that we
used to compute the proposed wage indexes without an occupational mix
adjustment since FY 2012 (76 FR 51591 through 51593), except as
discussed below. Typically, we do not restate all of the steps of the
methodology to compute the wage indexes in each proposed and final
rulemaking; instead, we refer readers to the FY 2012 IPPS/LTCH PPS
final rule. However, below in this FY 2020 IPPS/LTCH PPS proposed rule,
we are (1) restating the steps of the methodology in order to update
outdated references to certain cost report lines which were then
reflected on Medicare CMS Form 2552-96 but are now reflected on
Medicare CMS Form 2552-10; (2) proposing to change the calculation of
the Overhead Rate in Step 4; (3) proposing to modify our methodology
with regard to how dollar amounts, hours, and other numerical values in
the wage index calculation are rounded; and (4) proposing a methodology
for calculating the wage index for urban areas without wage data. We
are otherwise not proposing to make any other policy changes in this
section to the methodology set forth in the FY 2012 IPPS/LTCH PPS
proposed rule (76 FR 51591 through 51593) for computing the proposed
wage index without an occupational mix adjustment. Unless otherwise
specified, all cost report line references below refer to CMS Form
2552-10.
Step 1.--We gathered data from each of the non-Federal, short-term,
acute care hospitals for which data were reported on the Worksheet S-3,
Parts II and III of the Medicare cost report for the hospital's cost
reporting period relevant to the proposed wage index (in this case, for
FY 2020, these would be data from cost reports for cost reporting
periods beginning on or after October 1, 2015, and before October 1,
2016). In addition, we include data from some hospitals that had cost
reporting periods beginning before October 2015 and reported a cost
reporting period covering all of FY 2016. These data are included
because no other data from these hospitals would be available for the
cost reporting period described above, and because particular labor
market areas might be affected due to the omission of these hospitals.
However, we generally describe these wage data as FY 2016 data. We note
that, if a hospital had more than one cost reporting period beginning
during FY 2016 (for example, a hospital had two short cost reporting
periods beginning on or after October 1, 2015, and before October 1,
2016), we include wage data from only one of the cost reporting
periods, the longer, in the wage index calculation. If there was more
than one cost reporting period and the periods were equal in length, we
included the wage data from the later period in the wage index
calculation.
Step 2.--Salaries.--The method used to compute a hospital's average
hourly wage excludes certain costs that are not paid under the IPPS.
(We note that, beginning with FY 2008 (72 FR 47315), we included what
were then Lines 22.01, 26.01, and 27.01 of Worksheet S-3, Part II of
CMS Form 2552-96 for overhead services in the wage index. Currently,
these lines are lines 28, 33, and 35 on CMS Form 2552-10. However, we
note that the wages and hours on these lines are not incorporated into
Line 101, Column 1 of Worksheet A, which, through the electronic cost
reporting software, flows directly to Line 1 of Worksheet S-3, Part II.
Therefore, the first step in the wage index calculation is to compute a
``revised'' Line 1, by adding to the Line 1 on Worksheet S-3, Part II
(for wages and hours respectively) the amounts on Lines 28, 33, and
35.) In calculating a hospital's Net Salaries (we note that we
previously used the term ``average'' salaries in the FY 2012 IPPS/LTCH
PPS final rule (76 FR 51592), but we now use the term ``net'' salaries)
plus wage-related costs, we first compute the following: Subtract from
Line 1 (total salaries) the GME and CRNA costs reported on CMS Form
2552-10, Lines 2, 4.01, 7, and 7.01, the Part B salaries reported on
Lines 3, 5 and 6, home office salaries reported on Line 8, and exclude
salaries reported on Lines 9 and 10 (that is, direct salaries
attributable to SNF services, home health services, and other
subprovider components not subject to the IPPS). We also subtract from
Line 1 the salaries for which no hours were reported. Therefore, the
formula for Net Salaries (from Worksheet S-3, Part II) is the
following:
((Line 1 + Line 28 + Line 33 + Line 35) - (Line 2 + Line 3 + Line 4.01
+ Line 5 + Line 6 + Line 7 + Line 7.01 + Line 8 + Line 9 + Line 10))
To determine Total Salaries plus Wage-Related Costs, we add to the
Net Salaries the costs of contract labor for direct patient care,
certain top management, pharmacy, laboratory, and nonteaching physician
Part A services (Lines 11, 12 and 13), home office salaries and wage-
related costs reported by the hospital on Lines 14.01, 14.02, and 15,
and nonexcluded area wage-related costs (Lines 17, 22, 25.50, 25.51,
and 25.52). We note that contract labor and home office salaries for
which no corresponding hours are reported are not included. In
addition, wage-related costs for nonteaching physician Part A employees
(Line 22) are excluded if no corresponding salaries are reported for
those employees on Line 4.
The formula for Total Salaries plus Wage-Related Costs (from
Worksheet S-3, Part II) is the following: ((Line 1 + Line 28 + Line 33
+ Line 35) - (Line 2 + Line 3 + Line 4.01 + Line 5 + Line 6 + Line 7 +
Line 7.01 + Line 8 + Line 9 + Line 10)) + (Line 11 + Line 12 + Line 13
+ Line 14.01 + 14.02 + Line 15) + (Line 17 + Line 22 + 25.50 + 25.51 +
25.52)
Step 3.--Hours.--With the exception of wage-related costs, for
which there are no associated hours, we compute total hours using the
same methods as described for salaries in Step 2.
The formula for Total Hours (from Worksheet S-3, Part II) is the
following: ((Line 1 + Line 28 + Line 33 + Line 35) - (Line 2 + Line 3 +
Line 4.01 + Line 5 + Line 6 + Line 7 + Line 7.01 + Line 8 + Line 9 +
Line 10)) + (Line 11 + Line 12 + Line 13 + Line 14.01 + 14.02 + Line
15).
Step 4.--For each hospital reporting both total overhead salaries
and total overhead hours greater than zero, we then allocate overhead
costs to areas of the hospital excluded from the wage index
calculation. First, we determine the ``excluded rate'', which is the
ratio of excluded area hours to Revised Total Hours (from Worksheet S-
3, Part II) with the following formula: (Line 9 + Line 10)/(Line 1 +
Line 28 + Line 33 + Line 35) - (Lines 2, 3, 4.01, 5, 6, 7, 7.01, and 8
and Lines 26 through 43).
We then compute the amounts of overhead salaries and hours to be
allocated to excluded areas by multiplying the above ratio by the total
overhead salaries and hours reported on Lines 26 through 43 of
Worksheet S-3, Part II. Next, we compute the amounts of overhead wage-
related costs to be allocated to excluded areas using three steps:
(1) We determine the ``overhead rate'' (from Worksheet S-3, Part
II), which is the ratio of overhead hours (Lines 26 through 43 minus
the sum of Lines 28, 33, and 35) to revised hours excluding the sum of
lines 28, 33, and 35 (Line 1 minus the sum of Lines 2, 3, 4.01, 5, 6,
7, 7.01, 8, 9, 10, 28, 33, and 35). We note that, for the FY 2008 and
subsequent wage index calculations, we have been excluding the overhead
contract labor (Lines 28, 33, and 35) from the determination of the
ratio of overhead hours to revised hours because hospitals
[[Page 19378]]
typically do not provide fringe benefits (wage-related costs) to
contract personnel. Therefore, it is not necessary for the wage index
calculation to exclude overhead wage-related costs for contract
personnel. Further, if a hospital does contribute to wage-related costs
for contracted personnel, the instructions for Lines 28, 33, and 35
require that associated wage-related costs be combined with wages on
the respective contract labor lines.
The formula for the Overhead Rate (from Worksheet S-3, Part II) has
been the following: (Lines 26 through 43-Lines 28, 33 and 35)/((((Line
1 + Lines 28, 33, 35) - (Lines 2, 3, 4.01, 5, 6, 7, 7.01, 8, 26 through
43)) - (Lines 9, 10, 28, 33, and 35)) + (Lines 26 through 43 - Lines
28, 33, and 35)).
We note that, for the calculation for FY 2020 and subsequent fiscal
years, we are reexamining this step above regarding removal of the sum
of overhead contract labor hours on Lines 28, 33, and 35. In the
denominator of this calculation of the overhead rate, we have been
subtracting out the sum of the overhead contract labor hours from
Revised Total Hours. However, this requires modification because
Revised Total Hours do not include these overhead contract labor hours.
We are proposing to modify this step of the calculation of the overhead
rate as follows:
The formula for the Overhead Rate (from Worksheet S-3, Part II)
would be the following: (Lines 26 through 43-Lines 28, 33 and 35)/
((((Line 1 + Lines 28, 33, 35) - (Lines 2, 3, 4.01, 5, 6, 7, 7.01, 8,
and 26 through 43)) - (Lines 9 and 10)) + (Lines 26 through 43 - Lines
28, 33, and 35)).
(2) We compute overhead wage-related costs by multiplying the
overhead hours ratio by wage-related costs reported on Part II, Lines
17, 22, 25.50, 25.51, and 25.52.
(3) We multiply the computed overhead wage-related costs by the
above excluded area hours ratio.
Finally, we subtract the computed overhead salaries, wage-related
costs, and hours associated with excluded areas from the total salaries
(plus wage-related costs) and hours derived in Steps 2 and 3.
Step 5.--For each hospital, we adjust the total salaries plus wage-
related costs to a common period to determine total adjusted salaries
plus wage-related costs. To make the wage adjustment, we estimate the
percentage change in the employment cost index (ECI) for compensation
for each 30-day increment from October 14, 2015 through April 15, 2017,
for private industry hospital workers from the BLS' Compensation and
Working Conditions. We use the ECI because it reflects the price
increase associated with total compensation (salaries plus fringes)
rather than just the increase in salaries. In addition, the ECI
includes managers as well as other hospital workers. This methodology
to compute the monthly update factors uses actual quarterly ECI data
and assures that the update factors match the actual quarterly and
annual percent changes. We also note that, since April 2006 with the
publication of March 2006 data, the BLS' ECI uses a different
classification system, the North American Industrial Classification
System (NAICS), instead of the Standard Industrial Codes (SICs), which
no longer exist. We have consistently used the ECI as the data source
for our wages and salaries and other price proxies in the IPPS market
basket, and we are not proposing to make any changes to the usage for
FY 2020. The factors used to adjust the hospital's data were based on
the midpoint of the cost reporting period, as indicated below.
Step 6.--Each hospital is assigned to its appropriate urban or
rural labor market area before any reclassifications under section
1886(d)(8)(B), section 1886(d)(8)(E), or section 1886(d)(10) of the
Act. Within each urban or rural labor market area, we add the total
adjusted salaries plus wage-related costs obtained in Step 5 for all
hospitals in that area to determine the total adjusted salaries plus
wage-related costs for the labor market area.
Step 7.--We divide the total adjusted salaries plus wage-related
costs obtained under Step 6 by the sum of the corresponding total hours
(from Step 4) for all hospitals in each labor market area to determine
an average hourly wage for the area.
Step 8.--We add the total adjusted salaries plus wage-related costs
obtained in Step 5 for all hospitals in the Nation and then divide the
sum by the national sum of total hours from Step 4 to arrive at a
national average hourly wage.
Step 9.--For each urban or rural labor market area, we calculate
the hospital wage index value, unadjusted for occupational mix, by
dividing the area average hourly wage obtained in Step 7 by the
national average hourly wage computed in Step 8.
Step 10.--For each urban labor market area for which we do not have
any hospital wage data (either because there are no IPPS hospitals in
that labor market area, or there are IPPS hospitals in that area but
their data are either too new to be reflected in the current year's
wage index calculation, or their data are aberrant and are deleted from
the wage index), we are proposing that, for FY 2020 and subsequent
years' wage index calculations, such CBSA's wage index would be equal
to total urban salaries plus wage-related costs (from Step 5) in the
State, divided by the total urban hours (from Step 4) in the State,
divided by the national average hourly wage from Step 8. We believe
that, in the absence of wage data for an urban labor market area, it is
reasonable to propose to use a statewide urban average, which is based
on actual, acceptable wage data of hospitals in that State, rather than
impute some other type of value using a different methodology.
For calculation of the proposed FY 2020 wage index, we note there
are 2 urban CBSAs for which we do not have IPPS hospital wage data. In
Table 3 associated with this proposed rule (which is available via the
internet on the CMS website) which contains the area wage indexes, we
are including a footnote to indicate to which CBSAs this proposed
policy would apply. We are proposing that these CBSAs' wage indexes
would be equal to total urban salaries plus wage-related costs (from
Step 5) in the respective State, divided by the total urban hours (from
Step 4) in the respective State, divided by the national average hourly
wage (from Step 8). Under this step, we also are proposing to apply our
proposed policy with regard to how dollar amounts, hours, and other
numerical values in the wage index calculations are rounded.
We refer readers to section II. of the Appendix of this proposed
rule for the policy regarding rural areas that do not have IPPS
hospitals.
Step 11.--Section 4410 of Public Law 105-33 provides that, for
discharges on or after October 1, 1997, the area wage index applicable
to any hospital that is located in an urban area of a State may not be
less than the area wage index applicable to hospitals located in rural
areas in that State. The areas affected by this provision are
identified in Table 2 which is listed in section VI. of the Addendum to
this proposed rule and available via the internet on the CMS website.
As we noted previously in this section, we are proposing to modify
our methodology with regard to how dollar amounts, hours, and other
numerical values in the unadjusted and adjusted wage index calculation
are rounded, in order to help ensure consistency in the calculation.
For example, we have received questions from stakeholders who use data
printed in our proposed and final rules and online in our public use
files (PUFs) to calculate the wage indexes, and it has come to our
attention that, due in part to occasional inconsistencies in rounding
of data,
[[Page 19379]]
CMS' calculations and stakeholders' calculations may not match.
Therefore, to help ensure consistency in the calculation, we are
proposing to modify how the wage data numbers are rounded, as follows.
For data that we consider to be ``raw data,'' such as the cost report
data on Worksheets S-3, Parts II and III, and the occupational mix
survey data, we are proposing to use such data ``as is,'' and not round
any of the individual line items or fields. However, for any dollar
amounts within the wage index calculations, including any type of
summed wage amount, average hourly wages, and the national average
hourly wage (both the unadjusted and adjusted for occupational mix), we
are proposing to round the dollar amounts to 2 decimals. For any hour
amounts within the wage index calculations, we are proposing to round
such hour amounts to the nearest whole number. For any numbers not
expressed as dollars or hours within the wage index calculations, which
could include ratios, percentages, or inflation factors, we are
proposing to round such numbers to 5 decimals. However, we are
proposing to continue rounding the actual unadjusted and adjusted wage
indexes to 4 decimals, as we have done historically.
As discussed in the FY 2012 IPPS/LTCH PPS final rule, in ``Step
5,'' for each hospital, we adjust the total salaries plus wage-related
costs to a common period to determine total adjusted salaries plus
wage-related costs. To make the wage adjustment, we estimate the
percentage change in the employment cost index (ECI) for compensation
for each 30-day increment from October 14, 2015, through April 15,
2017, for private industry hospital workers from the BLS' Compensation
and Working Conditions. We have consistently used the ECI as the data
source for our wages and salaries and other price proxies in the IPPS
market basket, and we are not proposing any changes to the usage of the
ECI for FY 2020. The factors used to adjust the hospital's data were
based on the midpoint of the cost reporting period, as indicated in the
following table.
Midpoint of Cost Reporting Period
------------------------------------------------------------------------
Adjustment
After Before factor
------------------------------------------------------------------------
10/14/2015.................................... 11/15/2015 1.03058
11/14/2015.................................... 12/15/2015 1.02885
12/14/2015.................................... 01/15/2016 1.02708
01/14/2016.................................... 02/15/2016 1.02532
02/14/2016.................................... 03/15/2016 1.02357
03/14/2016.................................... 04/15/2016 1.02177
04/14/2016.................................... 05/15/2016 1.01988
05/14/2016.................................... 06/15/2016 1.01790
06/14/2016.................................... 07/15/2016 1.01585
07/14/2016.................................... 08/15/2016 1.01375
08/14/2016.................................... 09/15/2016 1.01162
09/14/2016.................................... 10/15/2016 1.00952
10/14/2016.................................... 11/15/2016 1.00751
11/14/2016.................................... 12/15/2016 1.00560
12/14/2016.................................... 01/15/2017 1.00374
01/14/2017.................................... 02/15/2017 1.00187
02/14/2017.................................... 03/15/2017 1.00000
03/14/2017.................................... 04/15/2017 0.99818
------------------------------------------------------------------------
For example, the midpoint of a cost reporting period beginning
January 1, 2016, and ending December 31, 2016, is June 30, 2016. An
adjustment factor of 1.01585 was applied to the wages of a hospital
with such a cost reporting period.
Previously, we also would provide a Puerto Rico overall average
hourly wage. As discussed in the FY 2017 IPPS/LTCH PPS final rule (81
FR 56915), prior to January 1, 2016, Puerto Rico hospitals were paid
based on 75 percent of the national standardized amount and 25 percent
of the Puerto Rico-specific standardized amount. As a result, we
calculated a Puerto Rico-specific wage index that was applied to the
labor-related share of the Puerto Rico-specific standardized amount.
Section 601 of the Consolidated Appropriations Act, 2016 (Pub. L. 114-
113) amended section 1886(d)(9)(E) of the Act to specify that the
payment calculation with respect to operating costs of inpatient
hospital services of a subsection (d) Puerto Rico hospital for
inpatient hospital discharges on or after January 1, 2016, shall use
100 percent of the national standardized amount. As we stated in the FY
2017 IPPS/LTCH PPS final rule (81 FR 56915 through 56916), because
Puerto Rico hospitals are no longer paid with a Puerto Rico-specific
standardized amount as of January 1, 2016, under section 1886(d)(9)(E)
of the Act, as amended by section 601 of the Consolidated
Appropriations Act, 2016, there is no longer a need to calculate a
Puerto Rico-specific average hourly wage and wage index. Hospitals in
Puerto Rico are now paid 100 percent of the national standardized
amount and, therefore, are subject to the national average hourly wage
(unadjusted for occupational mix) and the national wage index, which is
applied to the national labor-related share of the national
standardized amount. Therefore, for FY 2020, there is no Puerto Rico-
specific overall average hourly wage or wage index.
Based on the above methodology, the proposed unadjusted national
average hourly wage is the following:
------------------------------------------------------------------------
------------------------------------------------------------------------
Proposed FY 2020 Unadjusted National Average Hourly Wage..... $44.03
------------------------------------------------------------------------
2. Policies Regarding Rural Reclassification and Special Statuses for
Multicampus Hospitals
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41369 through
41374), we codified policies regarding rural reclassification and
special statuses for multicampus hospitals in the regulations at Sec.
412.92 for sole community hospitals (SCHs), Sec. 412.96 for rural
referral centers (RRCs), Sec. 412.103 for rural reclassification, and
Sec. 412.108 for Medicare-dependent, small rural hospitals (MDHs).
We stated that these policies apply to hospitals that have a main
campus and one or more remote locations under a single provider
agreement where services are provided and billed under the IPPS and
that meet the provider-based criteria at Sec. 413.65 as a main campus
and a remote location of a hospital, also referred to as multicampus
hospitals or hospitals with remote locations. As discussed in the FY
2019 IPPS/LTCH PPS final rule (83 FR 41369), a main campus of a
hospital cannot obtain an SCH, RRC, or MDH status or rural
reclassification independently or separately from its remote
location(s), and vice versa. Rather, if the criteria are met in the
regulations at Sec. 412.92 for SCHs, Sec. 412.96 for RRCs, Sec.
412.103 for rural reclassification, or Sec. 412.108 for MDHs, the
hospital (that is, the main campus and its remote location(s)) will be
granted the special treatment or rural reclassification afforded by the
aforementioned regulations.
We stated that, to qualify for rural reclassification or SCH, RRC,
or MDH status, a hospital with remote locations must demonstrate that
both the main campus and its remote location(s) satisfy the relevant
qualifying criteria. If the regulations at Sec. 412.92, Sec. 412.96,
Sec. 412.103, and Sec. 412.108 require data, such as bed count,
number of discharges, or case-mix index, for example, to demonstrate
that the hospital meets the qualifying criteria, the combined data from
the main campus and its remote location(s) are to be used.
[[Page 19380]]
For other qualifying criteria set forth in the regulations at
Sec. Sec. 412.92, 412.96, 412.103, and 412.108 that do not involve
data that can be combined, specifically qualifying criteria related to
location, mileage, travel time, and distance requirements, a hospital
would need to demonstrate that the main campus and its remote
location(s) each independently satisfy those requirements in order for
the entire hospital, including its remote location(s), to be
reclassified or obtain a special status.
We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR
41369 through 41374) for a detailed discussion of our policies for
multicampus hospitals.
E. Proposed Occupational Mix Adjustment to the FY 2020 Wage Index
As stated earlier, section 1886(d)(3)(E) of the Act provides for
the collection of data every 3 years on the occupational mix of
employees for each short-term, acute care hospital participating in the
Medicare program, in order to construct an occupational mix adjustment
to the wage index, for application beginning October 1, 2004 (the FY
2005 wage index). The purpose of the occupational mix adjustment is to
control for the effect of hospitals' employment choices on the wage
index. For example, hospitals may choose to employ different
combinations of registered nurses, licensed practical nurses, nursing
aides, and medical assistants for the purpose of providing nursing care
to their patients. The varying labor costs associated with these
choices reflect hospital management decisions rather than geographic
differences in the costs of labor.
1. Use of 2016 Medicare Wage Index Occupational Mix Survey for the FY
2019, FY 2020, and FY 2021 Wage Indexes
Section 304(c) of the Consolidated Appropriations Act, 2001 (Pub.
L. 106-554) amended section 1886(d)(3)(E) of the Act to require CMS to
collect data every 3 years on the occupational mix of employees for
each short-term, acute care hospital participating in the Medicare
program. We collected data in 2013 to compute the occupational mix
adjustment for the FY 2016, FY 2017, and FY 2018 wage indexes. As
discussed in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 19903) and
final rule (82 FR 38137), a new measurement of occupational mix (the
2016 survey) was required for FY 2019, FY 2020, and FY 2021.
The FY 2020 occupational mix adjustment is based on the calendar
year (CY) 2016 survey. Hospitals were required to submit their
completed 2016 surveys (Form CMS-10079, OMB number 0938-0907) to their
MACs by July 3, 2017. The preliminary, unaudited CY 2016 survey data
were posted on the CMS website on July 12, 2017. As with the Worksheet
S-3, Parts II and III cost report wage data, as part of the FY 2020
desk review process, the MACs revised or verified data elements in
hospitals' occupational mix surveys that resulted in certain edit
failures.
2. Calculation of the Occupational Mix Adjustment for FY 2020
For FY 2020, we are proposing to calculate the occupational mix
adjustment factor using the same methodology that we have used since
the FY 2012 wage index (76 FR 51582 through 51586) and to apply the
occupational mix adjustment to 100 percent of the FY 2020 wage index.
As we explained in section III.D. of the preamble of this proposed
rule, we are proposing to modify our methodology with regard to how
dollar amounts, hours, and other numerical values in the unadjusted and
adjusted wage index calculation are rounded, in order to ensure
consistency in the calculation. For data that we consider to be ``raw
data,'' such as the cost report data on Worksheets S-3, Parts II and
III, and the occupational mix survey data, we are proposing to use
these data ``as is'', and not round any of the individual line items or
fields. However, for any dollar amounts within the wage index
calculations, including any type of summed wage amount, average hourly
wages, and the national average hourly wage (both the unadjusted and
adjusted for occupational mix), we are proposing to round such dollar
amounts to 2 decimals. We are proposing to round any hour amounts
within the wage index calculations to the nearest whole number. We are
proposing to round any numbers not expressed as dollars or hours in the
wage index calculations, which could include ratios, percentages, or
inflation factors, to 5 decimals. However, we are proposing to continue
rounding the actual unadjusted and adjusted wage indexes to 4 decimals,
as we have done historically.
Similar to the method we use for the calculation of the wage index
without occupational mix, salaries and hours for a multicampus hospital
are allotted among the different labor market areas where its campuses
are located. Table 2 associated with this proposed rule (which is
available via the internet on the CMS website), which contains the
proposed FY 2020 occupational mix adjusted wage index, includes
separate wage data for the campuses of multicampus hospitals. We refer
readers to section III.C. of the preamble of this proposed rule for a
chart listing the multicampus hospitals and the FTE percentages used to
allot their occupational mix data.
Because the statute requires that the Secretary measure the
earnings and paid hours of employment by occupational category not less
than once every 3 years, all hospitals that are subject to payments
under the IPPS, or any hospital that would be subject to the IPPS if
not granted a waiver, must complete the occupational mix survey, unless
the hospital has no associated cost report wage data that are included
in the FY 2020 wage index. For the proposed FY 2020 wage index, we are
using the Worksheet S-3, Parts II and III wage data of 3,221 hospitals,
and we are using the occupational mix surveys of 3,119 hospitals for
which we also have Worksheet S-3 wage data, which represented a
``response'' rate of 97 percent (3,119/3,221). For the proposed FY 2020
wage index, we are applying proxy data for noncompliant hospitals, new
hospitals, or hospitals that submitted erroneous or aberrant data in
the same manner that we applied proxy data for such hospitals in the FY
2012 wage index occupational mix adjustment (76 FR 51586). As a result
of applying this methodology, the proposed FY 2020 occupational mix
adjusted national average hourly wage is the following:
------------------------------------------------------------------------
------------------------------------------------------------------------
Proposed FY 2020 Occupational Mix Adjusted National Average $43.99
Hourly Wage.................................................
------------------------------------------------------------------------
F. Analysis and Implementation of the Proposed Occupational Mix
Adjustment and the Proposed FY 2020 Occupational Mix Adjusted Wage
Index
As discussed in section III.E. of the preamble of this proposed
rule, for FY 2020, we are proposing to apply the occupational mix
adjustment to 100 percent of the FY 2020 wage index. We calculated the
proposed occupational mix adjustment using data from the 2016
occupational mix survey data, using the methodology described in the FY
2012 IPPS/LTCH PPS final rule (76 FR 51582 through 51586).
The proposed FY 2020 national average hourly wages for each
occupational mix nursing subcategory as calculated in Step 2 of the
occupational mix calculation are as follows. (We note that the average
hourly wage figures are rounded to two decimal places as we are
proposing in section III.D. of the preamble of this proposed rule.)
[[Page 19381]]
------------------------------------------------------------------------
Average
Occupational mix nursing subcategory hourly
wage
------------------------------------------------------------------------
National RN................................................... $41.54
National LPN and Surgical Technician.......................... 24.67
National Nurse Aide, Orderly, and Attendant................... 16.95
National Medical Assistant.................................... 18.14
National Nurse Category....................................... 34.91
------------------------------------------------------------------------
The proposed national average hourly wage for the entire nurse
category is computed in Step 5 of the occupational mix calculation.
Hospitals with a nurse category average hourly wage (as calculated in
Step 4) of greater than the national nurse category average hourly wage
receive an occupational mix adjustment factor (as calculated in Step 6)
of less than 1.0. Hospitals with a nurse category average hourly wage
(as calculated in Step 4) of less than the national nurse category
average hourly wage receive an occupational mix adjustment factor (as
calculated in Step 6) of greater than 1.0.
Based on the 2016 occupational mix survey data, we determined (in
Step 7 of the occupational mix calculation) that the national
percentage of hospital employees in the nurse category is 42 percent,
and the national percentage of hospital employees in the all other
occupations category is 58 percent. At the CBSA level, the percentage
of hospital employees in the nurse category ranged from a low of 27
percent in one CBSA to a high of 82 percent in another CBSA.
We compared the FY 2020 proposed occupational mix adjusted wage
indexes for each CBSA to the proposed unadjusted wage indexes for each
CBSA. Applying the proposed occupational mix adjustment to the wage
data resulted in the following:
Comparison of the FY 2020 Proposed Occupational Mix Adjusted Wage
Indexes to the Proposed Unadjusted Wage Indexes by CBSA
------------------------------------------------------------------------
------------------------------------------------------------------------
Number of Urban Areas Wage Index 233 (56.8 percent).
Increasing.
Number of Rural Areas Wage Index 23 (48.9 percent).
Increasing.
Number of Urban Areas Wage Index 113 (27.6 percent).
Increasing by Greater Than or Equal to 1
Percent But Less Than 5 Percent.
Number of Urban Areas Wage Index 7 (1.7 percent).
Increasing by 5 percent or More.
Number of Rural Areas Wage Index 10 (21.3 percent).
Increasing by Greater Than or Equal to 1
Percent But Less Than 5 percent.
Number of Rural Areas Wage Index 0 (0 percent).
Increasing by 5 Percent or More.
Number of Urban Areas Wage Index 175 (42.7 percent).
Decreasing.
Number of Rural Areas Wage Index 24 (51.1 percent).
Decreasing.
Number of Urban Areas Wage Index 80 (19.5 percent).
Decreasing by Greater Than or Equal to 1
Percent But Less Than 5 percent.
Number of Urban Areas Wage Index 1 (0.2 percent).
Decreasing by 5 Percent or More.
Number of Rural Areas Wage Index 7 (14.9 percent).
Decreasing by Greater Than or Equal to 1
Percent But Less than 5 Percent.
Number of Rural Areas Wage Index 0 (0 percent).
Decreasing by 5 Percent or More.
Largest Proposed Positive Impact for an 6.39 percent.
Urban Area.
Largest Proposed Positive Impact for a 3.82 percent.
Rural Area.
Largest Proposed Negative Impact for an 5.90 percent.
Urban Area.
Largest Proposed Negative Impact for a 1.66 percent.
Rural Area.
Urban Areas Unchanged by Application of 2.
the Proposed Occupational Mix Adjustment.
Rural Areas Unchanged by Application of 0.
the Proposed Occupational Mix Adjustment.
------------------------------------------------------------------------
These results indicate that a larger percentage of urban areas
(56.8 percent) would benefit from the occupational mix adjustment than
would rural areas (48.9 percent).
G. Proposed Application of the Rural Floor, Summary of Expired Imputed
Floor Policy, and Proposed Application of the State Frontier Floor
1. Proposed Rural Floor
Section 4410(a) of Public Law 105-33 provides that, for discharges
on or after October 1, 1997, the area wage index applicable to any
hospital that is located in an urban area of a State may not be less
than the area wage index applicable to hospitals located in rural areas
in that State. This provision is referred to as the ``rural floor''.
Section 3141 of Public Law 111-148 also requires that a national budget
neutrality adjustment be applied in implementing the rural floor. Based
on the proposed FY 2020 wage index associated with this proposed rule
(which is available via the internet on the CMS website) and our
proposal, as discussed in section III.N. of the preamble of this
proposed rule, to calculate the rural floor without the wage data of
hospitals that have reclassified as rural under Sec. 412.103, we
estimated that 166 hospitals would receive an increase in their FY 2020
proposed wage index due to the application of the rural floor.
2. Summary of Expired Imputed Floor Policy
As discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41376
through 41380), the imputed floor under both the original methodology
and the alternative methodology expired on September 30, 2018. As such,
the wage index and impact tables associated with this FY 2020 IPPS/LTCH
PPS proposed rule (which are available on the internet via the CMS
website) do not reflect the imputed floor policy, and we are not
applying a national budget neutrality adjustment for the imputed floor
for FY 2020. For a complete discussion, we refer readers to the FY 2019
IPPS/LTCH PPS final rule (83 FR 41376 through 41380). As discussed in
section III.N. of the preamble of this proposed rule, we are seeking
public comments on proposals to help address wage index disparities
under the IPPS. We also are seeking public comments on how the
expiration of the imputed floor has impacted hospitals in FY 2019.
3. Proposed State Frontier Floor for FY 2020
Section 10324 of Public Law 111-148 requires that hospitals in
frontier States cannot be assigned a wage index of less than 1.0000.
(We refer readers to the regulations at 42 CFR 412.64(m) and to a
discussion of the implementation of this provision in the FY 2011 IPPS/
LTCH PPS final rule (75 FR 50160 through 50161).) In this FY 2020 IPPS/
LTCH PPS proposed rule, we are not proposing any changes to the
frontier floor policy for FY 2020. In this proposed rule, 45 hospitals
would receive the frontier floor value of 1.0000 for their FY 2020 wage
index. These hospitals are located in Montana, Nevada, North Dakota,
South Dakota, and Wyoming.
The areas affected by the proposed rural and frontier floor
policies for the proposed FY 2020 wage index are identified in Table 2
associated with this proposed rule, which is available via the internet
on the CMS website.
[[Page 19382]]
H. Proposed FY 2020 Wage Index Tables
In the FY 2016 IPPS/LTCH PPS final rule (80 FR 49498 and 49807
through 49808), we finalized a proposal to streamline and consolidate
the wage index tables associated with the IPPS proposed and final rules
for FY 2016 and subsequent fiscal years. Prior to FY 2016, the wage
index tables had consisted of 12 tables (Tables 2, 3A, 3B, 4A, 4B, 4C,
4D, 4E, 4F, 4J, 9A, and 9C) that were made available via the internet
on the CMS website. Effective beginning FY 2016, with the exception of
Table 4E, we streamlined and consolidated 11 tables (Tables 2, 3A, 3B,
4A, 4B, 4C, 4D, 4F, 4J, 9A, and 9C) into 2 tables (Tables 2 and 3). As
discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41380),
beginning with FY 2019, we added Table 4 which is titled and includes a
``List of Counties Eligible for the Out-Migration Adjustment under
Section 1886(d)(13) of the Act'' for the relevant fiscal year. We refer
readers to section VI. of the Addendum to this proposed rule for a
discussion of the proposed wage index tables for FY 2020.
I. Revisions to the Wage Index Based on Hospital Redesignations and
Reclassifications
1. General Policies and Effects of Reclassification and Redesignation
Under section 1886(d)(10) of the Act, the Medicare Geographic
Classification Review Board (MGCRB) considers applications by hospitals
for geographic reclassification for purposes of payment under the IPPS.
Hospitals must apply to the MGCRB to reclassify not later than 13
months prior to the start of the fiscal year for which reclassification
is sought (usually by September 1). Generally, hospitals must be
proximate to the labor market area to which they are seeking
reclassification and must demonstrate characteristics similar to
hospitals located in that area. The MGCRB issues its decisions by the
end of February for reclassifications that become effective for the
following fiscal year (beginning October 1). The regulations applicable
to reclassifications by the MGCRB are located in 42 CFR 412.230 through
412.280. (We refer readers to a discussion in the FY 2002 IPPS final
rule (66 FR 39874 and 39875) regarding how the MGCRB defines mileage
for purposes of the proximity requirements.) The general policies for
reclassifications and redesignations and the policies for the effects
of hospitals' reclassifications and redesignations on the wage index
are discussed in the FY 2012 IPPS/LTCH PPS final rule for the FY 2012
final wage index (76 FR 51595 and 51596). In addition, in the FY 2012
IPPS/LTCH PPS final rule, we discussed the effects on the wage index of
urban hospitals reclassifying to rural areas under 42 CFR 412.103.
Hospitals that are geographically located in States without any rural
areas are ineligible to apply for rural reclassification in accordance
with the provisions of 42 CFR 412.103.
On April 21, 2016, we published an interim final rule with comment
period (IFC) in the Federal Register (81 FR 23428 through 23438) that
included provisions amending our regulations to allow hospitals
nationwide to have simultaneous Sec. 412.103 and MGCRB
reclassifications. For reclassifications effective beginning FY 2018, a
hospital may acquire rural status under Sec. 412.103 and subsequently
apply for a reclassification under the MGCRB using distance and average
hourly wage criteria designated for rural hospitals. In addition, we
provided that a hospital that has an active MGCRB reclassification and
is then approved for redesignation under Sec. 412.103 will not lose
its MGCRB reclassification; such a hospital receives a reclassified
urban wage index during the years of its active MGCRB reclassification
and is still considered rural under section 1886(d) of the Act and for
other purposes.
We discussed that when there is both a Sec. 412.103 redesignation
and an MGCRB reclassification, the MGCRB reclassification controls for
wage index calculation and payment purposes. We exclude hospitals with
Sec. 412.103 redesignations from the calculation of the reclassified
rural wage index if they also have an active MGCRB reclassification to
another area. That is, if an application for urban reclassification
through the MGCRB is approved, and is not withdrawn or terminated by
the hospital within the established timelines, we consider the
hospital's geographic CBSA and the urban CBSA to which the hospital is
reclassified under the MGCRB for the wage index calculation. We refer
readers to the April 21, 2016 IFC (81 FR 23428 through 23438) and the
FY 2017 IPPS/LTCH PPS final rule (81 FR 56922 through 56930) for a full
discussion of the effect of simultaneous reclassifications under both
the Sec. 412.103 and the MGCRB processes on wage index calculations.
2. MGCRB Reclassification and Redesignation Issues for FY 2020
a. FY 2020 Reclassification Application Requirements and Approvals
As previously stated, under section 1886(d)(10) of the Act, the
MGCRB considers applications by hospitals for geographic
reclassification for purposes of payment under the IPPS. The specific
procedures and rules that apply to the geographic reclassification
process are outlined in regulations under 42 CFR 412.230 through
412.280.
At the time this proposed rule was constructed, the MGCRB had
completed its review of FY 2020 reclassification requests. Based on
such reviews, there are 357 hospitals approved for wage index
reclassifications by the MGCRB starting in FY 2020. Because MGCRB wage
index reclassifications are effective for 3 years, for FY 2020,
hospitals reclassified beginning in FY 2018 or FY 2019 are eligible to
continue to be reclassified to a particular labor market area based on
such prior reclassifications for the remainder of their 3-year period.
There were 332 hospitals approved for wage index reclassifications in
FY 2018 that will continue for FY 2020, and 274 hospitals approved for
wage index reclassifications in FY 2019 that will continue for FY 2020.
Of all the hospitals approved for reclassification for FY 2018, FY
2019, and FY 2020, based upon the review at the time of this proposed
rule, 963 hospitals are in a MGCRB reclassification status for FY 2020
(with 32 of these hospitals reclassified back to their geographic
location).
Under the regulations at 42 CFR 412.273, hospitals that have been
reclassified by the MGCRB are permitted to withdraw their applications
if the request for withdrawal is received by the MGCRB any time before
the MGCRB issues a decision on the application, or after the MGCRB
issues a decision, provided the request for withdrawal is received by
the MGCRB within 45 days of the date that CMS' annual notice of
proposed rulemaking is issued in the Federal Register concerning
changes to the inpatient hospital prospective payment system and
proposed payment rates for the fiscal year for which the application
has been filed. For information about withdrawing, terminating, or
canceling a previous withdrawal or termination of a 3-year
reclassification for wage index purposes, we refer readers to Sec.
412.273, as well as the FY 2002 IPPS final rule (66 FR 39887 through
39888) and the FY 2003 IPPS final rule (67 FR 50065 through 50066).
Additional discussion on withdrawals and terminations, and
clarifications regarding reinstating reclassifications and ``fallback''
reclassifications were included in the FY 2008 IPPS final rule (72 FR
47333) and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38148 through
38150).
[[Page 19383]]
Changes to the wage index that result from withdrawals of requests
for reclassification, terminations, wage index corrections, appeals,
and the Administrator's review process for FY 2020 will be incorporated
into the wage index values published in the FY 2020 IPPS/LTCH PPS final
rule. These changes affect not only the wage index value for specific
geographic areas, but also the wage index value that redesignated/
reclassified hospitals receive; that is, whether they receive the wage
index that includes the data for both the hospitals already in the area
and the redesignated/reclassified hospitals. Further, the wage index
value for the area from which the hospitals are redesignated/
reclassified may be affected.
Applications for FY 2021 reclassifications (OMB control number
0938-0573) are due to the MGCRB by September 3, 2019 (the first working
day of September 2019). We note that this is also the deadline for
canceling a previous wage index reclassification withdrawal or
termination under 42 CFR 412.273(d). Applications and other information
about MGCRB reclassifications may be obtained beginning in mid-July
2019, via the internet on the CMS website at: https://www.cms.gov/Regulations-and-Guidance/Review-Boards/MGCRB/index.html, or by calling
the MGCRB at (410) 786-1174.
b. Proposed Elimination of Copy Requirement to CMS
Under regulations in effect prior to FY 2018 (42 CFR
412.256(a)(1)), applications for reclassification were required to be
mailed or delivered to the MGCRB, with a copy to CMS, and were not
allowed to be submitted through the facsimile (FAX) process or by other
electronic means. Because we believed this previous policy was outdated
and overly restrictive and to promote ease of application for FY 2018
and subsequent years, in the FY 2017 IPPS/LTCH PPS final rule (81 FR
56928), we revised this policy to require applications and supporting
documentation to be submitted via the method prescribed in instructions
by the MGCRB, with an electronic copy to CMS.
Beginning with applications from hospitals to reclassify for FY
2020, the MGCRB requires applications, supporting documents, and
subsequent correspondence to be filed electronically through the MGCRB
module of the Office of Hearings Case and Document Management System
(``OH CDMS''). Also, the MGCRB issues all of its notices and decisions
via email and these documents are accessible electronically through OH
CDMS. Registration instructions and the system user manual are
available at: https://www.cms.gov/Regulations-and-Guidance/Review-Boards/MGCRB/Electronic-Filing.html.
Filing a reclassification application using OH CDMS entails
completing required fields electronically and uploading supporting
documentation. We believe that the requirement for hospitals to submit
a copy of the application to CMS would now require hospitals to compile
their application information in a different format than what is
required by the MGCRB, which would result in additional burden for
hospitals. Furthermore, we believe that CMS can forgo the copy of
applications provided by hospitals because the MGCRB's electronic
module will facilitate CMS' verification of reclassification statuses
during the wage index development process. Therefore, we are proposing
to reduce burden for hospitals by eliminating the requirement to copy
CMS. Specifically, we are proposing to revise Sec. 412.256(a)(1) to
delete the requirement that an electronic copy of the application be
sent to CMS, so that this section would specify that an application
must be submitted to the MGCRB according to the method prescribed by
the MGCRB.
c. Proposed Revision To Clarify Criteria for a Hospital Seeking
Reclassification to Another Rural Area or Urban Area
Section 412.230(a)(4) of our regulations currently specifies that
the rounding of numbers to meet certain mileage or qualifying
percentage standards is not permitted when an individual hospital seeks
wage index reclassification through the MGCRB. In this section, the
regulation specifically cites paragraphs (b)(1), (b)(2), (d)(1)(iii),
and (d)(1)(iv)(A) and (B). The qualifying percentage standards included
in these paragraphs have been periodically updated, and additional
paragraphs have been added in Sec. 412.230 to reflect these changes.
Specifically, paragraphs (d)(1)(iv)(C), (D), and (E) have been added to
Sec. 412.230 to reflect changes in the percentage standards
implemented in FY 2002, FY 2010, and FY 2011, respectively. Although we
have continued to apply the policy set forth at Sec. 412.230(a)(4) to
the updated percentage standards set forth in paragraphs (d)(1)(iv)(C),
(D), and (E) in Sec. 412.230, conforming changes to Sec.
412.230(a)(4) were not made to reflect these new paragraphs. This
oversight has caused some confusion. Therefore, we are proposing to
revise Sec. 412.230(a)(4) to clarify that the policy prohibiting the
rounding of qualifying percentage standards applies to paragraphs
(d)(1)(iv)(C), (D), and (E) in Sec. 412.230. Specifically, we are
proposing to remove specific references to paragraphs (d)(1)(iv)(A) and
(B) and instead cite paragraph (d)(1)(iv) as a more general reference
to the specific standards.
3. Redesignations Under Section 1886(d)(8)(B) of the Act
a. Lugar Status Determinations
In the FY 2012 IPPS/LTCH PPS final rule (76 FR 51599 through
51600), we adopted the policy that, beginning with FY 2012, an eligible
hospital that waives its Lugar status in order to receive the out-
migration adjustment has effectively waived its deemed urban status
and, thus, is rural for all purposes under the IPPS effective for the
fiscal year in which the hospital receives the out-migration
adjustment. In addition, in that rule, we adopted a minor procedural
change that would allow a Lugar hospital that qualifies for and accepts
the out-migration adjustment (through written notification to CMS
within 45 days from the publication of the proposed rule) to waive its
urban status for the full 3-year period for which its out-migration
adjustment is effective. By doing so, such a Lugar hospital would no
longer be required during the second and third years of eligibility for
the out-migration adjustment to advise us annually that it prefers to
continue being treated as rural and receive the out-migration
adjustment. In the FY 2017 IPPS/LTCH PPS final rule (81 FR 56930), we
further clarified that if a hospital wishes to reinstate its urban
status for any fiscal year within this 3-year period, it must send a
request to CMS within 45 days of publication of the proposed rule for
that particular fiscal year. We indicated that such reinstatement
requests may be sent electronically to [email protected]. In the FY
2018 IPPS/LTCH PPS final rule (82 FR 38147 through 38148), we finalized
a policy revision to require a Lugar hospital that qualifies for and
accepts the out-migration adjustment, or that no longer wishes to
accept the out-migration adjustment and instead elects to return to its
deemed urban status, to notify CMS within 45 days from the date of
public display of the proposed rule at the Office of the Federal
Register. These revised notification timeframes were effective
beginning October 1, 2017. In addition, in the FY 2018 IPPS/LTCH PPS
final rule (82 FR 38148), we clarified that both requests to waive and
to reinstate ``Lugar'' status may be sent to
[[Page 19384]]
[email protected]. To ensure proper accounting, we request
hospitals to include their CCN, and either ``waive Lugar'' or
``reinstate Lugar'', in the subject line of these requests.
b. Clarification Regarding Accepting the Out-Migration Adjustment When
the Outmigration Adjustment Changes After Reclassification
Section 1886(d)(8)(B) of the Act provides that for purposes a
reclassification under this subsection, the Secretary shall treat a
hospital located in a rural county adjacent to one or more urban areas
as being located in the urban metropolitan statistical area to which
the greatest number of workers in the county commute if certain
criteria are met. Rural hospitals in these counties are commonly known
as ``Lugar'' hospitals. This statutory provision specifies that Lugar
status is mandatory (not optional) if the statutory criteria are met.
However, as discussed in the FY 2012 IPPS/LTCH PPS proposed and final
rules (76 FR 25885 through 25886 and 51599), Lugar hospitals located in
counties that qualify for the out-migration adjustment are required to
waive their Lugar urban status in its entirety in order to receive the
out-migration adjustment. We stated our belief that this represents one
permissible reading of the statute, given that section 1886(d)(13)(G)
of the Act states that a hospital in a county that has an out-migration
adjustment and that has not waived that adjustment under section
1886(d)(13)(F) of the Act is not eligible for reclassification under
section 1886(d)(8) or (10) of the Act. Therefore, a hospital may opt to
receive either its county's out-migration adjustment or the wage index
determined by its Lugar reclassification.
We have become aware of a potential issue with the current election
process that requires further clarification. As discussed in the
following section, the out-migration adjustment is calculated to
provide a positive adjustment to the wage index for hospitals located
in certain counties that have a relatively high percentage of hospital
employees who reside in the county but work in a different county (or
counties) with a higher wage index. When a county is determined to
qualify for an out-migration adjustment, the final adjustment value is
determined in accordance with section 1886(d)(13)(D) of the Act and is
fixed by statute for a 3-year period under section 1886(d)(13)(F) of
the Act. CMS performs an annual analysis to evaluate all counties
without current out-migration adjustment values assigned, including
counties where the out-migration adjustment value will be expiring
after a 3-year period. Initial out-migration adjustment values are
published in Table 4 associated with the IPPS proposed and final rules
(which are available via the internet on the CMS website). Due to
various factors, including hospitals withdrawing or terminating MGCRB
reclassifications, obtaining Sec. 412.103 rural reclassifications, or
corrections to hospital wage data, the amount of newly proposed (1st
year) out-migration adjustment values may fluctuate between the
proposed rule and the final rule (and subsequent correction notices).
These fluctuations are typically minimal. However, in certain
circumstances, after processing varying forms of reclassification, wage
index values may change so that a county would no longer qualify for an
out-migration adjustment. In particular, when changes in wage index
reclassification status alter the State rural floor so that multiple
CBSAs would be assigned the same wage index value, an out-migration
adjustment may no longer be indicated for a county as there would be
little, if any, differential in nearby wage index values. This can lead
to a situation where a hospital has opted to receive a non-existent
out-migration adjustment. We believe this situation is not compatible
with longstanding CMS policy preventing a hospital from waiving its
deemed urban Lugar status outside the prescribed out-migration
adjustment election process described above. Section 1886(d)(13)(G) of
the Act specifies that a hospital in a county that has a wage index
increase under section 1886(d)(13)(F) of the Act (the out-migration
adjustment) and that has not waived such increase under section
1886(d)(13)(F) of the Act is not eligible for reclassification under
section 1886(d)(8) or (10) of the Act during that period. If there is
no out-migration adjustment available to provide a wage index increase,
the fact pattern for which CMS established the process for a hospital
to opt to receive a county out-migration adjustment in lieu of its
``Lugar'' reclassification no longer applies, and the hospital must be
assigned its deemed urban status. Therefore, we are clarifying that, in
circumstances where an eligible hospital elects to receive the out-
migration adjustment within 45 days of the public display date of the
proposed rule at the Office of the Federal Register in lieu of its
Lugar wage index reclassification, and the county in which the hospital
is located would no longer qualify for an out-migration adjustment when
the final rule (or a subsequent correction notice) wage index
calculations are completed, the hospital's request to accept the out-
migration adjustment would be denied, and the hospital would be
automatically assigned to its deemed urban status under section
1886(d)(8)(B) of the Act. Final rule wage index values would be
recalculated to reflect this reclassification, and in some instances,
after taking into account this reclassification, the out-migration
adjustment for the county in question could be restored in the final
rule. However, as the hospital is assigned a Lugar reclassification
under section 1886(d)(8)(B) of the Act, it would be ineligible to
receive the county out-migration adjustment under section
1886(d)(13)(G) of the Act. Because the out-migration adjustment, once
finalized, is locked for a 3-year period under section 1886(d)(13)(F)
of the Act, the hospital would be eligible to accept its out-migration
adjustment in either the second or third year.
c. Proposed Change to Lugar County Assignments
Section 1886(d)(8)(B) of the Act establishes a wage index
reclassification process by which the Secretary is required to treat a
hospital located in a rural county adjacent to one or more urban areas
as being located in the urban metropolitan statistical area (MSA), or
core based statistical area (CBSA), to which the greatest number of
workers in the county commute if certain criteria are met. Rural
hospitals in these counties are known as ``Lugar'' hospitals and the
counties themselves are often referred to as ``Lugar'' counties. These
Lugar counties are not located in any urban area, but are adjacent to
two or more urban CBSAs. In determining whether a county qualifies as a
Lugar county, sections 1886(d)(8)(B)(i) and (ii) of the Act require us
to use the standards for designating MSAs published in the Federal
Register by OMB based on the most recent available decennial population
data. Based on OMB definitions (75 FR 37246 through 37252), a CBSA is
composed of ``central'' counties and ``outlying'' counties. While
``central'' counties meet certain population density requirements and
other urban characteristics, a county qualifies as an ``outlying''
county of a CBSA if it meets one of the following commuting
requirements: (a) At least 25 percent of the workers living in the
county work in the central county or counties of the CBSA; or (b) at
least 25 percent of the employment in the county is accounted for by
workers who reside in the central county or counties
[[Page 19385]]
of the CBSA. Given the OMB standards above, when a county is located
between two or more urban centers, these ``central'' county commuting
patterns may be split between two or more CBSAs, and the 25-percent
thresholds to qualify as an outlying county for any single CBSA may not
be met. In such situations, the county would be considered rural
according to CMS, based on the OMB definitions above, as it would not
be part of an urban CBSA. Section 1886(d)(8)(B) of the Act addresses
this issue where a county would have qualified as an outlying urban
county if all its central county commuting data to adjacent urban CBSAs
were combined. Specifically, section 1886(d)(8)(B)(i) of the Act
requires CMS to consider a rural county to be part of an adjacent CBSA
if the rural county would otherwise be considered part of an urban area
under the OMB standards for designating MSAs if the commuting rates
used in determining outlying counties were determined on the basis of
the aggregate number of resident workers who commute to (and, if
applicable under the standards, from) the central county or counties of
all contiguous MSAs. Section 1886(d)(8)(B)(i) further requires CMS to
assign these Lugar counties to the CBSA to which the greatest number of
workers in the county commute. Since the implementation of section
1886(d)(8)(B) of the Act for discharges occurring after October 1,
1988, CMS' policy has been that, once a county qualifies as Lugar, the
proper methodology for determining the CBSA to which the greatest
number of workers in the county commute should be based on the same OMB
dataset used to determine whether a county qualifies as an ``outlying''
county of a CBSA. These data are a summary of commuting patterns
between the non-central county being evaluated and the ``central''
county or counties of an urban metropolitan area (without taking into
account outlying counties). Section 1886(d)(8)(B) of the Act clearly
instructs CMS to use the OMB criteria for determining ``outlying''
counties when determining the list of qualifying Lugar counties. These
criteria are limited to assessing commuting patterns to and from
central counties. Further, we do not believe the statute requires that
CMS perform an additional and separate community analysis, taking into
account outlying counties, to determine to which CBSA a Lugar county
should be assigned. When CMS updated the OMB labor market delineations
based on 2010 decennial census in FY 2015, we were made aware that a
hospital in Henderson County, TX (a Lugar county) disagreed with CMS'
interpretation of the statute. In particular, the hospital stated that
section 1886(d)(8)(B)(i) of the Act requires that CMS assign a
qualified Lugar county to ``the urban metropolitan statistical area to
which the greatest number of workers in the county commute,'' and that
this instruction does not distinguish between an urban CBSA's central
counties and outlying counties. The hospital claimed that the
assignment of a Lugar county to a CBSA should not be based solely on
commuting data and commuting patterns to and from the central county or
counties of a CBSA, but should consider outlying counties as well.
After consideration of this matter, we continue to believe that
CMS' methodology is a reasonable interpretation of the statute.
However, upon further consideration and analysis, we have determined
that the Henderson, TX hospital's interpretation of section
1886(d)(8)(B) of the Act is a reasonable alternative. After reanalyzing
the commuting data used when developing the FY 2015 IPPS/LTCH PPS final
rule (the American Community Survey commuting data for 2006-2010), we
identified 10 instances where a rural county would have been assigned
to a different CBSA if we had considered outlying counties in our
analysis of the urban metropolitan statistical area to which the
greatest number of workers in the county commute, as shown in the table
below.
BILLING CODE 4120-01-P
[[Page 19386]]
[GRAPHIC] [TIFF OMITTED] TP03MY19.020
BILLING CODE 4120-01-C
Of these 10 counties, currently only 3 counties (Talladega, AL,
Pearl River, MS, and Henderson, TX) contain IPPS hospitals (4 hospitals
in total). When including ``outlying'' counties in the commuting
analysis, the analysis suggests that generally (but not always) the
revised CBSA assignment would be to a larger CBSA, which would be
expected as larger CBSAs generally include a greater number of
``outlying'' counties. After further consideration of this issue, we
believe that inclusion of outlying counties in the commuting analysis
for purposes of assigning counties that qualify as Lugar counties (the
second step of the Lugar analysis),
[[Page 19387]]
although not unambiguously required by statute, is a reasonable, and
arguably more natural, reading of the language in section
1886(d)(8)(B)(i) of the Act. Accordingly, we are proposing to modify
the assigned CBSA for the 10 Lugar counties specified in the table
above for FY 2020. We also plan to fully reevaluate this proposed
policy and underlying methodologies, if finalized, when CMS updates
Lugar county assignments, which typically occurs after OMB labor market
delineations are updated in response to the next decennial census.
J. Proposed Out-Migration Adjustment Based on Commuting Patterns of
Hospital Employees
In accordance with section 1886(d)(13) of the Act, as added by
section 505 of Public Law 108-173, beginning with FY 2005, we
established a process to make adjustments to the hospital wage index
based on commuting patterns of hospital employees (the ``out-
migration'' adjustment). The process, outlined in the FY 2005 IPPS
final rule (69 FR 49061), provides for an increase in the wage index
for hospitals located in certain counties that have a relatively high
percentage of hospital employees who reside in the county but work in a
different county (or counties) with a higher wage index.
Section 1886(d)(13)(B) of the Act requires the Secretary to use
data the Secretary determines to be appropriate to establish the
qualifying counties. When the provision of section 1886(d)(13) of the
Act was implemented for the FY 2005 wage index, we analyzed commuting
data compiled by the U.S. Census Bureau that were derived from a
special tabulation of the 2000 Census journey-to-work data for all
industries (CMS extracted data applicable to hospitals). These data
were compiled from responses to the ``long-form'' survey, which the
Census Bureau used at that time and which contained questions on where
residents in each county worked (69 FR 49062). However, the 2010 Census
was ``short form'' only; information on where residents in each county
worked was not collected as part of the 2010 Census. The Census Bureau
worked with CMS to provide an alternative dataset based on the latest
available data on where residents in each county worked in 2010, for
use in developing a new out-migration adjustment based on new commuting
patterns developed from the 2010 Census data beginning with FY 2016.
To determine the out-migration adjustments and applicable counties
for FY 2016, we analyzed commuting data compiled by the Census Bureau
that were derived from a custom tabulation of the American Community
Survey (ACS), an official Census Bureau survey, utilizing 2008 through
2012 (5-year) Microdata. The data were compiled from responses to the
ACS questions regarding the county where workers reside and the county
to which workers commute. As we discussed in the FYs 2016, 2017, 2018,
and 2019 IPPS/LTCH PPS final rules (80 FR 49501, 81 FR 56930, 82 FR
38150, and 83 FR 41384, respectively), the same policies, procedures,
and computation that were used for the FY 2012 out-migration adjustment
were applicable for FYs 2016 through 2019, and we are proposing to use
them again for FY 2020. We have applied the same policies, procedures,
and computations since FY 2012, and we believe they continue to be
appropriate for FY 2020. We refer readers to the FY 2016 IPPS/LTCH PPS
final rule (80 FR 49500 through 49502) for a full explanation of the
revised data source.
For FY 2020, the out-migration adjustment will continue to be based
on the data derived from the custom tabulation of the ACS utilizing
2008 through 2012 (5-year) Microdata. For future fiscal years, we may
consider determining out-migration adjustments based on data from the
next Census or other available data, as appropriate. For FY 2020, we
are not proposing any changes to the methodology or data source that we
used for FY 2016 (81 FR 25071). (We refer readers to a full discussion
of the out-migration adjustment, including rules on deeming hospitals
reclassified under section 1886(d)(8) or section 1886(d)(10) of the Act
to have waived the out-migration adjustment, in the FY 2012 IPPS/LTCH
PPS final rule (76 FR 51601 through 51602).)
Table 2 associated with this proposed rule (which is available via
the internet on the CMS website) includes the proposed out-migration
adjustments for the FY 2020 wage index. In addition, as discussed in
the FY 2019 IPPS/LTCH PPS proposed rule (83 FR 20367), we have added a
Table 4, ``List of Counties Eligible for the Out-Migration Adjustment
under Section 1886(d)(13) of the Act.'' For this proposed rule, Table 4
consists of the following: A list of counties that would be eligible
for the out-migration adjustment for FY 2020 identified by FIPS county
code, the proposed FY 2020 out-migration adjustment, and the number of
years the adjustment would be in effect. We believe this table makes
this information more transparent and provides the public with easier
access to this information. We note that we intend to make the
information available annually via Table 4 associated with the IPPS/
LTCH PPS proposed and final rules, and are including it among the
tables associated with this FY 2020 IPPS/LTCH PPS proposed rule that
are available via the internet on the CMS website.
K. Reclassification From Urban to Rural Under Section 1886(d)(8)(E) of
the Act, Implemented at 42 CFR 412.103
1. Application for Rural Status and Lock-In Date
Under section 1886(d)(8)(E) of the Act, a qualifying prospective
payment hospital located in an urban area may apply for rural status
for payment purposes separate from reclassification through the MGCRB.
Specifically, section 1886(d)(8)(E) of the Act provides that, not later
than 60 days after the receipt of an application (in a form and manner
determined by the Secretary) from a subsection (d) hospital that
satisfies certain criteria, the Secretary shall treat the hospital as
being located in the rural area (as defined in paragraph (2)(D)) of the
State in which the hospital is located. We refer readers to the
regulations at 42 CFR 412.103 for the general criteria and application
requirements for a subsection (d) hospital to reclassify from urban to
rural status in accordance with section 1886(d)(8)(E) of the Act. The
FY 2012 IPPS/LTCH PPS final rule (76 FR 51595 through 51596) includes
our policies regarding the effect of wage data from reclassified or
redesignated hospitals.
Hospitals must meet the criteria to be reclassified from urban to
rural status under Sec. 412.103, as well as fulfill the requirements
for the application process. There may be one or more reasons that a
hospital applies for the urban to rural reclassification, and the
timeframe that a hospital submits an application is often dependent on
those reason(s). Because the wage index is part of the methodology for
determining the prospective payments to hospitals for each fiscal year,
we stated in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56931) that we
believed there should be a definitive timeframe within which a hospital
should apply for rural status in order for the reclassification to be
reflected in the next Federal fiscal year's wage data used for setting
payment rates.
Therefore, after notice of proposed rulemaking and consideration of
public comments, in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56931
through 56932), we revised Sec. 412.103(b) by
[[Page 19388]]
adding paragraph (6) to specify that, in order for a hospital to be
treated as rural in the wage index and budget neutrality calculations
under Sec. Sec. 412.64(e)(1)(ii), (e)(2), (e)(4), and (h) for payment
rates for the next Federal fiscal year, the hospital's filing date (the
lock-in date) must be no later than 70 days prior to the second Monday
in June of the current Federal fiscal year and the application must be
approved by the CMS Regional Office in accordance with the requirements
of Sec. 412.103.
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41384 through
41386), we changed the lock-in date to provide for additional time in
the ratesetting process and to match the lock-in date with another
existing deadline, the usual public comment deadline for the IPPS
proposed rule. We revised Sec. 412.103(b)(6) to specify that, in order
for a hospital to be treated as rural in the wage index and budget
neutrality calculations under Sec. Sec. 412.64(e)(1)(ii), (e)(2),
(e)(4), and (h) for payment rates for the next Federal fiscal year, the
hospital's application must be approved by the CMS Regional Office in
accordance with the requirements of Sec. 412.103 no later than 60 days
after the public display date at the Office of the Federal Register of
the IPPS proposed rule for the next Federal fiscal year.
The lock-in date does not affect the timing of payment changes
occurring at the hospital-specific level as a result of
reclassification from urban to rural under Sec. 412.103. As we
discussed in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56931) and the
FY 2019 IPPS/LTCH PPS final rule (83 FR 41385 through 41386), this
lock-in date also does not change the current regulation that allows
hospitals that qualify under Sec. 412.103(a) to request, at any time
during a cost reporting period, to reclassify from urban to rural. A
hospital's rural status and claims payment reflecting its rural status
continue to be effective on the filing date of its reclassification
application, which is the date the CMS Regional Office receives the
application, in accordance with Sec. 412.103(d). The hospital's IPPS
claims will be paid reflecting its rural status beginning on the filing
date (the effective date) of the reclassification, regardless of when
the hospital applies.
2. Proposed Change to the Regulations To Allow for Electronic
Submission of Applications for Reclassification From Urban to Rural
Status
The application requirements at Sec. 412.103(b)(3) for
reclassification from urban to rural status currently state that an
application must be mailed to the CMS Regional Office by the requesting
hospital and may not be submitted by facsimile or other electronic
means. We believe that this policy is outdated and overly restrictive.
In the interest of burden reduction and to promote ease of application,
in this proposed rule, we are proposing to eliminate the restriction on
submitting an application by facsimile or other electronic means so
that hospitals may also submit applications to the CMS Regional Office
electronically. Accordingly, we are proposing to revise Sec.
412.103(b)(3) to allow a requesting hospital to submit an application
to the CMS Regional Office by mail or by facsimile or other electronic
means.
3. Proposed Changes to Cancellation Requirements for Rural
Reclassifications
Under current regulations at Sec. 412.103(g)(1), hospitals, other
than those hospitals that are rural referral centers (RRCs), may cancel
a rural reclassification by submitting a written request to the CMS
Regional Office not less than 120 days before the end of its current
cost reporting period, effective beginning with the next full cost
reporting period. Under the current regulations at Sec. 412.103(g)(2),
a hospital that was classified as an RRC under Sec. 412.96 based on
rural reclassification under Sec. 412.103 may cancel its rural
reclassification by submitting a written request to the CMS Regional
Office not less than 120 days prior to the end of the Federal fiscal
year and after being paid as rural for at least one 12-month cost
reporting period. The RRC's cancellation of a Sec. 412.103 rural
reclassification is not effective until it has been paid as rural for
at least one 12-month cost reporting period, and not until the
beginning of the Federal fiscal year following both the request for
cancellation and the 12-month cost reporting period.
In this proposed rule, we are proposing to revise the rural
reclassification cancellation requirements at Sec. 412.103(g) for
hospitals classified as RRCs. Currently, Sec. 412.103(g)(2) requires
that, for a hospital that has been classified as an RRC based on rural
reclassification under Sec. 412.103, cancellation of a Sec. 412.103
rural reclassification is not effective until the hospital that is
classified as an RRC has been paid as rural for at least one 12-month
cost reporting period, and not until the beginning of the Federal
fiscal year following both the request for cancellation and the 12-
month cost reporting period. We stated in the FY 2008 IPPS final rule
(72 FR 47371 through 47373) that the goal of creating this minimum time
period was to disincentivize hospitals from receiving a rural
redesignation, obtaining RRC status to take advantage of special MGCRB
reclassification rules, and then terminating their rural status.
However, as suggested by a commenter in response to the April 22, 2016
interim final rule with comment period (81 FR 56926), this disincentive
is no longer necessary now that hospitals can have simultaneous MGCRB
and Sec. 412.103 reclassifications. Accordingly, in this proposed
rule, we are proposing to revise Sec. 412.103(g)(2)(iii) to specify
that the provisions set forth at Sec. 412.103(g)(2)(i) and (ii) are
effective for all written requests submitted by hospitals on or after
October 1, 2007 and before October 1, 2019 to cancel rural
reclassifications. Therefore, the reclassification cancellation
requirements specific to RRCs at Sec. 412.103(g)(2) would no longer
apply for cancellation requests submitted on or after October 1, 2019.
In addition, as further discussed below, we are proposing to revise
Sec. 412.103(g) to include uniform reclassification cancellation
requirements that would be applied to all hospitals effective for
cancellation requests submitted on or after October 1, 2019.
As further discussed below, we are proposing to revise the
regulations at Sec. 412.103(g) to set forth uniform requirements
applicable to all hospitals for cancelling rural reclassifications.
Currently, for non-RRCs, the cancellation of rural status is effective
beginning with the hospital's next cost reporting period. A hospital
that has a Sec. 412.103 rural reclassification and that does not have
an additional MGCRB or ``Lugar'' reclassification is assigned the rural
wage index value for its State. Because wage index values are
determined and assigned to hospitals on a Federal fiscal year basis,
when such an aforementioned hospital cancels its rural
reclassification, the wage index value must be manually updated by the
MAC to its appropriate urban wage index value. Because the end dates of
cost reporting periods vary among hospitals, this process can be
cumbersome and some cancellation requests may not be processed in time
to be accurately reflected in the IPPS final rule appendix tables.
Because there is no apparent advantage to continuing to link the rural
reclassification cancellation date to a hospital's cost reporting
period, we believe that, in the interests of reducing overall
complexity and administrative burden, the cancellation of rural
reclassification should be effective for all hospitals
[[Page 19389]]
beginning with the next Federal fiscal year (that is, the Federal
fiscal year following the cancellation request). In addition, similar
to the current requirements at Sec. 412.103(g)(2), we believe it would
be appropriate to require hospitals to request cancellation not less
than 120 days prior to the end of a Federal fiscal year. We believe
this proposed 120-day timeframe would provide hospitals adequate time
to assess and review reclassification options, and provide CMS adequate
time to incorporate the cancellation in the wage index development
process. As discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR
41384 through 41386), we finalized a lock-in date for a new rural
reclassification to be approved in order for a hospital to be treated
as rural in the wage index and budget neutrality calculations under
Sec. Sec. 412.64(e)(1)(ii), (e)(2), (e)(4), and (h) for payment rates
for the next Federal fiscal year. We considered using this deadline,
which is 60 days after the public display date at the Office of the
Federal Register of the IPPS proposed rule for the next Federal fiscal
year, as the deadline to submit cancellation requests effective for the
next Federal fiscal year as well. While we see certain advantages with
aligning various wage index deadlines to the same date, based on the
public display date of the proposed rule, we believe the proposed
deadline of not less than 120 days prior to the end of the Federal
fiscal year would give hospitals adequate time to assess and review
reclassification options, and CMS adequate time to incorporate the
cancellation in the wage index and budget neutrality calculations under
Sec. Sec. 412.64(e)(1)(ii), (e)(2), (e)(4), and (h) for payment rates
for the next Federal fiscal year. In addition, this proposed 120-day
deadline is already familiar to many hospitals because it is similar to
the current deadline under Sec. 412.103(g)(2), and therefore, we
believe implementation of the proposed deadline may pose less of a
burden overall for many hospitals. For these reasons, we are proposing
to add paragraph (g)(3) to Sec. 412.103 to specify that, for all
written requests submitted by hospitals on or after October 1, 2019 to
cancel rural reclassifications, a hospital may cancel its rural
reclassification by submitting a written request to the CMS Regional
Office not less than 120 days prior to the end of a Federal fiscal
year, and the hospital's cancellation of the classification would be
effective beginning with the next Federal fiscal year. In addition, we
are proposing to add paragraph (g)(1)(iii) to Sec. 412.103 to specify
that the provisions of paragraphs (g)(1)(i) and (ii) of Sec. 412.103
are effective only for written requests submitted by hospitals before
October 1, 2019 to cancel rural reclassification.
In addition, we are proposing to codify into regulations a
longstanding CMS policy regarding canceling a Sec. 412.103
reclassification when a hospital opts to accept and receives its county
out-migration adjustment in lieu of its ``Lugar'' reclassification. As
discussed in section III.I.3. of the preamble of this proposed rule, a
hospital may opt to receive either its ``Lugar'' county
reclassification established under section 1886(d)(8)(B) of the Act, or
the county out-migration adjustment determined under section
1886(d)(13) of the Act. Such requests may be submitted to CMS by email
to [email protected] within 45 days of the public display date of
the proposed rule for the next Federal fiscal year. We established this
process because section 1886(d)(13)(G) of the Act prohibits a hospital
from having both an out-migration wage index adjustment and
reclassification under section 1886(d)(8) or (10) of the Act. Because
Sec. 412.103 reclassifications were established under section
1886(d)(8)(E) of the Act, a hospital cannot simultaneously have an out-
migration adjustment and be reclassified as rural under Sec. 412.103.
In the FY 2012 IPPS/LTCH PPS final rule (76 FR 51600), we addressed a
commenter's concern regarding timing issues for some hospitals that
wish to receive their county out-migration adjustment, but would not
have adequate time to also cancel their rural reclassification. In that
rule, we stated that ``we will allow the act of waiving Lugar status
for the out-migration adjustment to simultaneously waive the hospital's
deemed urban status and cancel the hospital's acquired rural status,
thus treating the hospital as a rural provider effective on October
1.'' While this policy modification was initially discussed in the FY
2012 IPPS/LTCH PPS final rule in the context of hospitals wishing to
obtain or maintain sole community hospital (SCH) or Medicare-dependent
hospital (MDH) status, its application has not been limited to current
or potential SCHs or MDHs. We continue to believe this policy of
automatically canceling rural reclassifications when a hospital waives
its Lugar reclassification to receive its out-migration adjustment
reduces overall burden on hospitals by not requiring them to file a
separate rural reclassification cancellation request. We also believe
this policy reduces overall complexity for CMS, avoiding the need to
track and process multiple cancellation requests. Accordingly, we
believe this policy should be codified in the regulations at Sec.
412.103.
Therefore, we are proposing to add paragraph (g)(4) to Sec.
412.103 to specify that a rural reclassification will be considered
cancelled effective for the next Federal fiscal year when a hospital
opts (by submitting a request to CMS within 45 days of the date of
public display of the proposed rule for the next Federal fiscal year at
the Office of the Federal Register in accordance with the procedure
described in section III.I.3. of the preamble of this proposed rule) to
accept and receives its county out-migration wage index adjustment
determined under section 1886(d)(13) of the Act in lieu of its
geographic reclassification described under section 1886(d)(8)(B) of
the Act. If the hospital wishes to once again obtain a Sec. 412.103
rural reclassification, it would have to reapply through the CMS
Regional Office in accordance with Sec. 412.103, and the hospital
would once again be ineligible to receive its out-migration adjustment.
We note that, in a case where a hospital reclassified as rural under
Sec. 412.103 wishes to receive its out-migration adjustment but does
not qualify for a ``Lugar'' reclassification, the hospital would need
to formally cancel its Sec. 412.103 rural reclassification by written
request to the CMS Regional Office within the timeframe specified at
Sec. 412.103. Finally, in order to address the scenario described in
section III.I.3.b. of the preamble of this proposed rule, we note that,
in proposed Sec. 412.103(g)(4), we are providing that the hospital
must not only opt to accept, but also receive, its county out-migration
wage index adjustment to trigger cancellation of rural reclassification
under that provision. In such cases where an out-migration adjustment
is no longer applicable based on the wage index in the final rule, a
hospital's rural reclassification remains in effect (unless otherwise
cancelled by written request to the CMS Regional Office within the
timeframe specified at Sec. 412.103).
L. Process for Requests for Wage Index Data Corrections
1. Process for Hospitals To Request Wage Index Data Corrections
The preliminary, unaudited Worksheet S-3 wage data files and the
preliminary CY 2016 occupational mix data files for the proposed FY
2020 wage index were made available on June 5, 2018 through the
internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-
Fee-for-Service-
[[Page 19390]]
Payment/AcuteInpatientPPS/Wage-Index-Files-Items/FY2020-Wage-Index-
Home-Page.html.
On January 31, 2019, we posted a public use file (PUF) at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatient
PPS/Wage-Index-Files-Items/FY2020-Wage-Index-Home-Page.html containing
FY 2020 wage index data available as of January 30, 2019. This PUF
contains a tab with the Worksheet S-3 wage data (which includes
Worksheet S-3, Parts II and III wage data from cost reporting periods
beginning on or after October 1, 2015 through September 30, 2016; that
is, FY 2016 wage data), a tab with the occupational mix data (which
includes data from the CY 2016 occupational mix survey, Form CMS-
10079), a tab containing the Worksheet S-3 wage data of hospitals
deleted from the January 31, 2019 wage data PUF, and a tab containing
the CY 2016 occupational mix data of the hospitals deleted from the
January 31, 2019 occupational mix PUF. In a memorandum dated January
18, 2019, we instructed all MACs to inform the IPPS hospitals that they
service of the availability of the January 31, 2019 wage index data
PUFs, and the process and timeframe for requesting revisions in
accordance with the FY 2020 Wage Index Timetable.
In the interest of meeting the data needs of the public, beginning
with the proposed FY 2009 wage index, we post an additional PUF on the
CMS website that reflects the actual data that are used in computing
the proposed wage index. The release of this file does not alter the
current wage index process or schedule. We notify the hospital
community of the availability of these data as we do with the current
public use wage data files through our Hospital Open Door Forum. We
encourage hospitals to sign up for automatic notifications of
information about hospital issues and about the dates of the Hospital
Open Door Forums at the CMS website at: http://www.cms.gov/Outreach-and-Education/Outreach/OpenDoorForums/index.html.
In a memorandum dated April 20, 2018, we instructed all MACs to
inform the IPPS hospitals that they service of the availability of the
preliminary wage index data files and the CY 2016 occupational mix
survey data files posted on May 18, 2018, and the process and timeframe
for requesting revisions.
In a memorandum dated June 6, 2018, we corrected and reposted the
preliminary wage file on our website because we realized that the PUF
originally posted on May 18 2018 did not include new line items that
were first included in cost reports for cost reporting periods
beginning on or after October 1, 2015 (and will be used for the first
time in the FY 2020 wage index). Specifically, the lines are: Worksheet
S-3, Part II, lines 14.01 and 14.02, and 25.50, 25.51, 25.52, and
25.53; and Worksheet S-3, Part IV, lines 8.01, 8.02, 8.03. In the same
memorandum, we instructed all MACs to inform the IPPS hospitals that
they service of the availability of the corrected and reposted
preliminary wage index data files and the CY 2016 occupational mix
survey data files posted on June 6, 2018, and the process and timeframe
for requesting revisions.
If a hospital wished to request a change to its data as shown in
the June 6, 2018 preliminary wage and occupational mix data files, the
hospital had to submit corrections along with complete, detailed
supporting documentation to its MAC by September 4, 2018. Hospitals
were notified of this deadline and of all other deadlines and
requirements, including the requirement to review and verify their data
as posted in the preliminary wage index data files on the internet,
through the letters sent to them by their MACs. November 16, 2018 was
the deadline for MACs to complete all desk reviews for hospital wage
and occupational mix data and transmit revised Worksheet S-3 wage data
and occupational mix data to CMS.
November 6, 2018 was the date by when MACs notified State hospital
associations regarding hospitals that failed to respond to issues
raised during the desk reviews. Additional revisions made by the MACs
were transmitted to CMS throughout January 2019. CMS published the wage
index PUFs that included hospitals' revised wage index data on January
31, 2019. Hospitals had until February 15, 2019, to submit requests to
the MACs to correct errors in the January 31, 2019 PUF due to CMS or
MAC mishandling of the wage index data, or to revise desk review
adjustments to their wage index data as included in the January 31,
2019 PUF. Hospitals also were required to submit sufficient
documentation to support their requests.
After reviewing requested changes submitted by hospitals, MACs were
required to transmit to CMS any additional revisions resulting from the
hospitals' reconsideration requests by March 22, 2019. Under our
current policy as adopted in the FY 2018 IPPS/LTCH PPS final rule (82
FR 38153), the deadline for a hospital to request CMS intervention in
cases where a hospital disagreed with a MAC's handling of wage data on
any basis (including a policy, factual, or other dispute) was April 4,
2019. Data that were incorrect in the preliminary or January 31, 2019
wage index data PUFs, but for which no correction request was received
by the February 15, 2019 deadline, are not considered for correction at
this stage. In addition, April 4, 2019 was the deadline for hospitals
to dispute data corrections made by CMS of which the hospital is
notified after the January 31, 2019 PUF and at least 14 calendar days
prior to April 4, 2019 (that is, March 21, 2018), that do not arise
from a hospital's request for revisions. We note that, as with previous
years, for the proposed FY 2020 wage index, in accordance with the FY
2020 wage index timeline posted on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatient
PPS/Wage-Index-Files-Items/FY2020-Wage-Index-Home-Page.html, the April
appeals have to be sent via mail and email. We refer readers to the
wage index timeline for complete details.
Hospitals are given the opportunity to examine Table 2 associated
with this proposed rule, which is listed in section VI. of the Addendum
to this proposed rule and available via the internet on the CMS website
at: https://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/AcuteInpatientPPS-FY2020-IPPS-Proposed-Rule-Home-Page.html. Table 2
contains each hospital's proposed adjusted average hourly wage used to
construct the wage index values for the past 3 years, including the FY
2016 data used to construct the proposed FY 2020 wage index. We note
that the proposed hospital average hourly wages shown in Table 2 only
reflect changes made to a hospital's data that were transmitted to CMS
by early February 2019.
We plan to post the final wage index data PUFs in late April 2019
via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatient PPS/Wage-Index-Files-
Items/FY2020-Wage-Index-Home-Page.html. The April 2019 PUFs are made
available solely for the limited purpose of identifying any potential
errors made by CMS or the MAC in the entry of the final wage index data
that resulted from the correction process previously described (the
process for disputing revisions submitted to CMS by the MACs by March
21, 2019, and the process for disputing data corrections made by CMS
that did not arise from a hospital's request for wage data revisions as
discussed earlier).
After the release of the April 2019 wage index data PUFs, changes
to the wage and occupational mix data can only be made in those very
limited situations involving an error by the
[[Page 19391]]
MAC or CMS that the hospital could not have known about before its
review of the final wage index data files. Specifically, neither the
MAC nor CMS will approve the following types of requests:
Requests for wage index data corrections that were
submitted too late to be included in the data transmitted to CMS by the
MACs on or before March 21, 2018.
Requests for correction of errors that were not, but could
have been, identified during the hospital's review of the January 31,
2019 wage index PUFs.
Requests to revisit factual determinations or policy
interpretations made by the MAC or CMS during the wage index data
correction process.
If, after reviewing the April 2019 final wage index data PUFs, a
hospital believes that its wage or occupational mix data are incorrect
due to a MAC or CMS error in the entry or tabulation of the final data,
the hospital is given the opportunity to notify both its MAC and CMS
regarding why the hospital believes an error exists and provide all
supporting information, including relevant dates (for example, when it
first became aware of the error). The hospital is required to send its
request to CMS and to the MAC no later than May 30, 2019. May 30, 2019
is also the deadline for hospitals to dispute data corrections made by
CMS of which the hospital is notified on or after 13 calendar days
prior to April 4, 2019 (that is, March 22, 2019), and at least 14
calendar days prior to May 30, 2019 (that is, May 16, 2019), that do
not arise from a hospital's request for revisions. (Data corrections
made by CMS of which a hospital is notified on or after 13 calendar
days prior to May 30, 2019 (that is, May 17, 2019) may be appealed to
the Provider Reimbursement Review Board (PRRB)). Similar to the April
appeals, beginning with the FY 2015 wage index, in accordance with the
FY 2020 wage index timeline posted on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Wage-Index-Files-Items/FY2020-Wage-Index-Home-Page.html, the May appeals must be sent via mail and email to CMS and
the MACs. We refer readers to the wage index timeline for complete
details.
Verified corrections to the wage index data received timely (that
is, by May 30, 2019) by CMS and the MACs will be incorporated into the
final FY 2020 wage index, which will be effective October 1, 2019.
We created the processes previously described to resolve all
substantive wage index data correction disputes before we finalize the
wage and occupational mix data for the FY 2020 payment rates.
Accordingly, hospitals that do not meet the procedural deadlines set
forth earlier will not be afforded a later opportunity to submit wage
index data corrections or to dispute the MAC's decision with respect to
requested changes. Specifically, our policy is that hospitals that do
not meet the procedural deadlines set forth above (requiring requests
to MACs by the specified date in February and, where such requests are
unsuccessful, requests for intervention by CMS by the specified date in
April) will not be permitted to challenge later, before the PRRB, the
failure of CMS to make a requested data revision. We refer readers also
to the FY 2000 IPPS final rule (64 FR 41513) for a discussion of the
parameters for appeals to the PRRB for wage index data corrections. As
finalized in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38154 through
38156), this policy also applies to a hospital disputing corrections
made by CMS that do not arise from a hospital's request for a wage
index data revision. That is, a hospital disputing an adjustment made
by CMS that did not arise from a hospital's request for a wage index
data revision would be required to request a correction by the first
applicable deadline. Hospitals that do not meet the procedural
deadlines set forth earlier will not be afforded a later opportunity to
submit wage index data corrections or to dispute CMS' decision with
respect to requested changes.
Again, we believe the wage index data correction process described
earlier provides hospitals with sufficient opportunity to bring errors
in their wage and occupational mix data to the MAC's attention.
Moreover, because hospitals have access to the final wage index data
PUFs by late April 2019, they have the opportunity to detect any data
entry or tabulation errors made by the MAC or CMS before the
development and publication of the final FY 2020 wage index by August
2019, and the implementation of the FY 2020 wage index on October 1,
2019. Given these processes, the wage index implemented on October 1
should be accurate. Nevertheless, in the event that errors are
identified by hospitals and brought to our attention after May 30,
2019, we retain the right to make midyear changes to the wage index
under very limited circumstances.
Specifically, in accordance with 42 CFR 412.64(k)(1) of our
regulations, we make midyear corrections to the wage index for an area
only if a hospital can show that: (1) The MAC or CMS made an error in
tabulating its data; and (2) the requesting hospital could not have
known about the error or did not have an opportunity to correct the
error, before the beginning of the fiscal year. For purposes of this
provision, ``before the beginning of the fiscal year'' means by the May
deadline for making corrections to the wage data for the following
fiscal year's wage index (for example, May 30, 2019 for the FY 2020
wage index). This provision is not available to a hospital seeking to
revise another hospital's data that may be affecting the requesting
hospital's wage index for the labor market area. As indicated earlier,
because CMS makes the wage index data available to hospitals on the CMS
website prior to publishing both the proposed and final IPPS rules, and
the MACs notify hospitals directly of any wage index data changes after
completing their desk reviews, we do not expect that midyear
corrections will be necessary. However, under our current policy, if
the correction of a data error changes the wage index value for an
area, the revised wage index value will be effective prospectively from
the date the correction is made.
In the FY 2006 IPPS final rule (70 FR 47385 through 47387 and
47485), we revised 42 CFR 412.64(k)(2) to specify that, effective on
October 1, 2005, that is, beginning with the FY 2006 wage index, a
change to the wage index can be made retroactive to the beginning of
the Federal fiscal year only when CMS determines all of the following:
(1) The MAC or CMS made an error in tabulating data used for the wage
index calculation; (2) the hospital knew about the error and requested
that the MAC and CMS correct the error using the established process
and within the established schedule for requesting corrections to the
wage index data, before the beginning of the fiscal year for the
applicable IPPS update (that is, by the May 30, 2019 deadline for the
FY 2020 wage index); and (3) CMS agreed before October 1 that the MAC
or CMS made an error in tabulating the hospital's wage index data and
the wage index should be corrected.
In those circumstances where a hospital requested a correction to
its wage index data before CMS calculated the final wage index (that
is, by the May 30, 2019 deadline for the FY 2020 wage index), and CMS
acknowledges that the error in the hospital's wage index data was
caused by CMS' or the MAC's mishandling of the data, we believe that
the hospital should not be penalized by our delay in publishing or
implementing the correction. As with our current policy, we indicated
that the provision is not available to a hospital seeking to revise
another hospital's data.
[[Page 19392]]
In addition, the provision cannot be used to correct prior years' wage
index data; and it can only be used for the current Federal fiscal
year. In situations where our policies would allow midyear corrections
other than those specified in 42 CFR 412.64(k)(2)(ii), we continue to
believe that it is appropriate to make prospective-only corrections to
the wage index.
We note that, as with prospective changes to the wage index, the
final retroactive correction will be made irrespective of whether the
change increases or decreases a hospital's payment rate. In addition,
we note that the policy of retroactive adjustment will still apply in
those instances where a final judicial decision reverses a CMS denial
of a hospital's wage index data revision request.
2. Process for Data Corrections by CMS After the January 31 Public Use
File (PUF)
The process set forth with the wage index timeline discussed in
section III.L.1. of the preamble of this proposed rule allows hospitals
to request corrections to their wage index data within prescribed
timeframes. In addition to hospitals' opportunity to request
corrections of wage index data errors or MACs' mishandling of data, CMS
has the authority under section 1886(d)(3)(E) of the Act to make
corrections to hospital wage index and occupational mix data in order
to ensure the accuracy of the wage index. As we explained in the FY
2016 IPPS/LTCH PPS final rule (80 FR 49490 through 49491) and the FY
2017 IPPS/LTCH PPS final rule (81 FR 56914), section 1886(d)(3)(E) of
the Act requires the Secretary to adjust the proportion of hospitals'
costs attributable to wages and wage-related costs for area differences
reflecting the relative hospital wage level in the geographic areas of
the hospital compared to the national average hospital wage level. We
believe that, under section 1886(d)(3)(E) of the Act, we have
discretion to make corrections to hospitals' data to help ensure that
the costs attributable to wages and wage-related costs in fact
accurately reflect the relative hospital wage level in the hospitals'
geographic areas.
We have an established multistep, 15-month process for the review
and correction of the hospital wage data that is used to create the
IPPS wage index for the upcoming fiscal year. Since the origin of the
IPPS, the wage index has been subject to its own annual review process,
first by the MACs, and then by CMS. As a standard practice, after each
annual desk review, CMS reviews the results of the MACs' desk reviews
and focuses on items flagged during the desk review, requiring that, if
necessary, hospitals provide additional documentation, adjustments, or
corrections to the data. This ongoing communication with hospitals
about their wage data may result in the discovery by CMS of additional
items that were reported incorrectly or other data errors, even after
the posting of the January 31 PUF, and throughout the remainder of the
wage index development process. In addition, the fact that CMS analyzes
the data from a regional and even national level, unlike the review
performed by the MACs that review a limited subset of hospitals, can
facilitate additional editing of the data that may not be readily
apparent to the MACs. In these occasional instances, an error may be of
sufficient magnitude that the wage index of an entire CBSA is affected.
Accordingly, CMS uses its authority to ensure that the wage index
accurately reflects the relative hospital wage level in the geographic
area of the hospital compared to the national average hospital wage
level, by continuing to make corrections to hospital wage data upon
discovering incorrect wage data, distinct from instances in which
hospitals request data revisions.
We note that CMS corrects errors to hospital wage data as
appropriate, regardless of whether that correction will raise or lower
a hospital's average hourly wage. For example, as discussed in section
III.C. of the preamble of the FY 2019 IPPS/LTCH PPS final rule (83 FR
41364), in situations where a hospital did not have documentable
salaries, wages, and hours for housekeeping and dietary services, we
imputed estimates, in accordance with policies established in the FY
2015 IPPS/LTCH PPS final rule (79 FR 49965 through 49967). Furthermore,
if CMS discovers after conclusion of the desk review, for example, that
a MAC inadvertently failed to incorporate positive adjustments
resulting from a prior year's wage index appeal of a hospital's wage-
related costs such as pension, CMS would correct that data error and
the hospital's average hourly wage would likely increase as a result.
While we maintain CMS' authority to conduct additional review and
make resulting corrections at any time during the wage index
development process, in accordance with the policy finalized in the FY
2018 IPPS/LTCH PPS final rule (82 FR 38154 through 38156) and as first
implemented with the FY 2019 wage index (83 FR 41389), hospitals are
able to request further review of a correction made by CMS that did not
arise from a hospital's request for a wage index data correction.
Instances where CMS makes a correction to a hospital's data after the
January 31 PUF based on a different understanding than the hospital
about certain reported costs, for example, could potentially be
resolved using this process before the final wage index is calculated.
We believe this process and the timeline for requesting such
corrections (as described earlier and in the FY 2018 IPPS/LTCH PPS
final rule) promote additional transparency to instances where CMS
makes data corrections after the January 31 PUF, and provide
opportunities for hospitals to request further review of CMS changes in
time for the most accurate data to be reflected in the final wage index
calculations. These additional appeals opportunities are described
earlier and in the FY 2020 Wage Index Development Time Table, as well
as in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38154 through 38156).
M. Proposed Labor-Related Share for the Proposed FY 2020 Wage Index
Section 1886(d)(3)(E) of the Act directs the Secretary to adjust
the proportion of the national prospective payment system base payment
rates that are attributable to wages and wage-related costs by a factor
that reflects the relative differences in labor costs among geographic
areas. It also directs the Secretary to estimate from time to time the
proportion of hospital costs that are labor-related and to adjust the
proportion (as estimated by the Secretary from time to time) of
hospitals' costs that are attributable to wages and wage-related costs
of the DRG prospective payment rates. We refer to the portion of
hospital costs attributable to wages and wage-related costs as the
labor-related share. The labor-related share of the prospective payment
rate is adjusted by an index of relative labor costs, which is referred
to as the wage index.
Section 403 of Public Law 108-173 amended section 1886(d)(3)(E) of
the Act to provide that the Secretary must employ 62 percent as the
labor-related share unless this would result in lower payments to a
hospital than would otherwise be made. However, this provision of
Public Law 108-173 did not change the legal requirement that the
Secretary estimate from time to time the proportion of hospitals' costs
that are attributable to wages and wage-related costs. Thus, hospitals
receive payment based on either a 62-percent labor-related share, or
the labor-related share estimated from time to time by the Secretary,
depending on which labor-
[[Page 19393]]
related share resulted in a higher payment.
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38158 through
38175), we rebased and revised the hospital market basket. We
established a 2014-based IPPS hospital market basket to replace the FY
2010-based IPPS hospital market basket, effective October 1, 2017.
Using the 2014-based IPPS market basket, we finalized a labor-related
share of 68.3 percent for discharges occurring on or after October 1,
2017. In addition, in FY 2018, we implemented this revised and rebased
labor-related share in a budget neutral manner (82 FR 38522). However,
consistent with section 1886(d)(3)(E) of the Act, we did not take into
account the additional payments that would be made as a result of
hospitals with a wage index less than or equal to 1.0000 being paid
using a labor-related share lower than the labor-related share of
hospitals with a wage index greater than 1.0000. In the FY 2019 IPPS/
LTCH PPS final rule (83 FR 41389 and 41390), for FY 2019, we continued
to use a labor-related share of 68.3 percent for discharges occurring
on or after October 1, 2018.
The labor-related share is used to determine the proportion of the
national IPPS base payment rate to which the area wage index is
applied. We include a cost category in the labor-related share if the
costs are labor intensive and vary with the local labor market. In this
proposed rule, for FY 2020, we are not proposing to make any further
changes to the national average proportion of operating costs that are
attributable to wages and salaries, employee benefits, professional
fees: Labor-related, administrative and facilities support services,
installation, maintenance, and repair services, and all other labor-
related services. Therefore, for FY 2020, we are proposing to continue
to use a labor-related share of 68.3 percent for discharges occurring
on or after October 1, 2019.
As discussed in section IV.B. of the preamble of this proposed
rule, prior to January 1, 2016, Puerto Rico hospitals were paid based
on 75 percent of the national standardized amount and 25 percent of the
Puerto Rico-specific standardized amount. As a result, we applied the
Puerto Rico-specific labor-related share percentage and nonlabor-
related share percentage to the Puerto Rico-specific standardized
amount. Section 601 of the Consolidated Appropriations Act, 2016 (Pub.
L. 114-113) amended section 1886(d)(9)(E) of the Act to specify that
the payment calculation with respect to operating costs of inpatient
hospital services of a subsection (d) Puerto Rico hospital for
inpatient hospital discharges on or after January 1, 2016, shall use
100 percent of the national standardized amount. Because Puerto Rico
hospitals are no longer paid with a Puerto Rico-specific standardized
amount as of January 1, 2016, under section 1886(d)(9)(E) of the Act as
amended by section 601 of the Consolidated Appropriations Act, 2016,
there is no longer a need for us to calculate a Puerto Rico-specific
labor-related share percentage and nonlabor-related share percentage
for application to the Puerto Rico-specific standardized amount.
Hospitals in Puerto Rico are now paid 100 percent of the national
standardized amount and, therefore, are subject to the national labor-
related share and nonlabor-related share percentages that are applied
to the national standardized amount. Accordingly, for FY 2020, we are
not proposing a Puerto Rico-specific labor-related share percentage or
a nonlabor-related share percentage.
Tables 1A and 1B, which are published in section VI. of the
Addendum to this FY 2020 IPPS/LTCH PPS proposed rule and available via
the internet on the CMS website, reflect the proposed national labor-
related share, which is also applicable to Puerto Rico hospitals. For
FY 2020, for all IPPS hospitals (including Puerto Rico hospitals) whose
wage indexes are less than or equal to 1.0000, we are proposing to
apply the wage index to a labor-related share of 62 percent of the
national standardized amount. For all IPPS hospitals (including Puerto
Rico hospitals) whose wage indexes are greater than 1.000, for FY 2020,
we are proposing to apply the wage index to a proposed labor-related
share of 68.3 percent of the national standardized amount.
N. Proposals To Address Wage Index Disparities Between High and Low
Wage Index Hospitals
In the FY 2019 IPPS/LTCH PPS proposed rule (83 FR 20372), we
invited the public to submit further comments, suggestions, and
recommendations for regulatory and policy changes to the Medicare wage
index. Many of the responses received from this request for information
(RFI) reflect a common concern that the current wage index system
perpetuates and exacerbates the disparities between high and low wage
index hospitals. Many respondents also expressed concern that the
calculation of the rural floor has allowed a limited number of States
to manipulate the wage index system to achieve higher wages for many
urban hospitals in those states at the expense of hospitals in other
states, which also contributes to wage index disparities.
To help mitigate these wage index disparities, including those
resulting from the inclusion of hospitals with rural reclassifications
under 42 CFR 412.103 in the calculation of the rural floor, we are
proposing to reduce the disparity between high and low wage index
hospitals by increasing the wage index values for certain hospitals
with low wage index values and decreasing the wage index values for
certain hospitals with high wage index values to maintain budget
neutrality, and changing the calculation of the rural floor, as further
discussed below. We also are proposing a transition for hospitals
experiencing significant decreases in their wage index values as a
result of our proposed wage index policies. We discuss these proposed
changes to the wage index in more detail below.
1. Prior Rulemaking Public Comments
As described in the FY 2019 IPPS/LTCH PPS proposed rule (83 FR
20372 through 20377), there have been numerous studies, analyses, and
reports on ways to revise the Medicare wage index. In public comments
received on prior rulemakings for FYs 2009, 2010, and 2011, many
commenters argued that the current labor market definitions and wage
data sources used by CMS, in many instances, are not reflective of the
true cost of labor for any given hospital or are inappropriate to use
for this purpose because of, for example, the resulting payment
disparities, or both. For our responses to public comments received on
the FY 2009 IPPS/LTCH PPS proposed rule, we refer readers to the FY
2009 IPPS/LTCH PPS final rule (73 FR 48563 through 48567); for
responses to public comments on the FY 2010 IPPS/LTCH PPS proposed
rule, we refer readers to the FY 2010 IPPS/LTCH PPS final rule (74 FR
43824 through 43826); and for responses to public comments on the FY
2011 IPPS/LTCH PPS proposed rule, we refer readers to the FY 2011 IPPS/
LTCH PPS final rule (75 FR 50157 through 50160). The public comments on
these proposed rules are available at www.regulations.gov under file
numbers CMS-1390-P, CMS-1406-P, and CMS-1498-P, respectively.
In the FY 2019 IPPS/LTCH proposed rule, we invited the public to
submit further comments, suggestions, and recommendations for
regulatory and policy changes to the Medicare wage index. We requested
the public to submit appropriate supporting data and specific
recommendations in their comments. We also welcomed analysis
[[Page 19394]]
regarding CMS' authority for our consideration. We received many
comments, many of which addressed wage index disparities between high
and low wage index hospitals. The following is a summary of the
comments we received on the wage index disparity issue. We note that we
also received comments regarding other aspects of the wage index
system, including current labor market areas, MGCRB reclassifications,
use of alternative data, and the use of the hospital wage index by
nonhospital providers. We will continue to consider those comments for
potential future rulemaking.
2. Public Comments on Wage Index Disparities in Response to the Request
for Information in the FY 2019 IPPS/LTCH PPS Proposed Rule
One of the concerns regarding the wage index system expressed by
hospitals in low wage index areas is the disparity in wage index values
between high and low wage index areas. The following comment, received
in response to the request for information in the FY 2019 IPPS/LTCH PPS
proposed rule, is a typical comment in this regard:
``The most significant issue with the current system can be traced
to the data sources used to calculate the wage index. Relying
exclusively on hospital cost reports as the source to calculate the
wage index allows hospitals in States with significantly higher wage
indexes to maintain and improve their favorable position in the current
system by setting higher than market value wages for their employees.
The higher wage hospitals can, by virtue of higher Medicare payments,
afford to pay wages that allow them to continue as a high wage index
State. Low wage index States . . . cannot afford to pay wages that
would allow their hospitals to climb back toward the median wage index.
Over time this condition of circularity has increased the gap between
the wage indexes of the high and low wage States to a much larger
degree than what the wage index was initially designed to address, the
difference in labor markets across the country for comparable
services.''
For discussion purposes, we will refer to this situation as the
``downward spiral,'' as this term has been used by some stakeholders to
describe this issue. Some respondents stated that the disparity between
the higher and lower wage index areas continues to grow and suggested
that the problem is, in large part, due to providers in low wage index
areas having difficulty keeping pace with competitive labor costs and
having to reduce expenses in other areas to make up for it. Some
respondents indicated that the downward spiral faced by hospitals in
low wage index areas was the most important wage index issue facing the
system and it needed to be addressed quickly.
Some respondents recommended that CMS create a wage index floor for
low wage hospitals, and that, in order to maintain budget neutrality,
CMS reduce the wage index values for high wage hospitals through the
creation of wage index ceiling.
Some respondents also indicated that the current wage index
methodology encourages misuse and opportunist gaming, especially in the
area of urban to rural reclassifications and the rural floor. According
to these respondents, under current policies, providers in some urban
areas are able to reclassify to a rural area and substantially raise
the rural floor for an entire State. Several respondents suggested that
this is inconsistent with the intent of the rural floor policy, which
is to protect vulnerable urban hospitals, and that the policy was not
intended to allow urban hospitals to artificially inflate the rural
floor through urban to rural reclassification. These respondents
indicated that, because the rural floor policy is budget neutral
nationally, all providers throughout the country that do not benefit
from the rural floor policy have their payments lowered due to this
misuse and opportunistic gaming. These respondents stressed that this
further contributes to financial distress of hospitals in low wage
index areas.
Some respondents stated that CMS has the regulatory authority to
determine how it calculates the rural floor. They stated that the
calculation should mirror the spirit and intent of law by only
considering the geographically rural providers in a State when
calculating a rural floor. According to these respondents, CMS should
consider changing the existing calculation to include only the
geographically rural providers when calculating the rural floor for a
State in order to ensure that existing regulatory policy around the
rural floor calculation meets the intent of law and does not harm
vulnerable providers the law intended to protect.
Other commenters were not critical in their comments regarding wage
index disparities. The following is a typical comment arguing that the
reflection of such disparities in the wage index is appropriate:
``CMS has requested comments on wage index disparities, but we urge
the agency to continue to recognize that as long as there are
`disparities' in the cost of labor and cost of living between different
parts of the country, there will and should always be wage index
`disparities'. The area wage index is intended to recognize differences
in resource use across types and location of hospitals. In a quest to
smooth out so-called `disparities', we urge CMS to continue to
adequately account for these resource differences in its payment
systems.''
Some commenters indicated that further analysis and study are
needed. The following comment is a typical comment expressing this
view:
``The area wage index is intended to recognize differences in
resource use across types and location of hospitals. If these resource
differences are not adequately accounted for by Medicare payment
adjustments, hospitals are either inappropriately rewarded or put under
fiscal pressure. Taking this into account, hospitals have repeatedly
expressed concern that the wage index is greatly flawed in many
respects, including its accuracy, volatility, circularity, and
substantial reclassifications and exceptions. Members of Congress and
Medicare officials also have voiced concerns with the present system.
While a consensus solution to the wage index's shortcomings has not yet
been developed, further analysis of alternatives is needed to identify
approaches that promote payment adjustments that are accurate, fair,
and effective.''
As noted earlier, we also received comments regarding other aspects
of the wage index system. We will continue to consider those responses
for potential future rulemaking. We encourage interested members of the
public to review all the comments on the wage index received in
response to the request for information in their entirety, which are
available at www.regulations.gov under file number CMS-1694-P.
3. Proposals To Address Wage Index Disparities
a. Providing an Opportunity for Low Wage Index Hospitals To Increase
Employee Compensation
As CMS and other entities have stated in the past, comprehensive
wage index reform would require both statutory and regulatory changes,
and could require new data sources. Notwithstanding the challenges
associated with comprehensive wage index reform, we agree with
respondents to the request for information who indicated that some
current wage index policies create barriers to hospitals with low wage
index values from being able to increase employee compensation due to
the lag
[[Page 19395]]
between when hospitals increase the compensation and when those
increases are reflected in the calculation of the wage index. (We note
that this lag results from the fact that the wage index calculations
rely on historical data.) We also agree that addressing this systemic
issue does not need to wait for comprehensive wage index reform given
the growing disparities between low and high wage index hospitals,
including rural hospitals that may be in financial distress and facing
potential closure. Therefore, in response to these concerns, we are
proposing a policy that would provide certain low wage index hospitals
with an opportunity to increase employee compensation without the usual
lag in those increases being reflected in the calculation of the wage
index.
In general terms, as discussed further below, we are proposing to
increase the wage index values for hospitals with a wage index value in
the lowest quartile of the wage index values across all hospitals.
Quartiles are a common way to divide a distribution, and therefore we
believe it is appropriate to divide the wage indexes into quartiles for
this purpose. For example, the interquartile range is a common measure
of variability based on dividing data into quartiles. Furthermore,
quartiles are used to divide distributions for other purposes under the
Medicare program. For example, when determining Medicare Advantage
benchmarks, excluding quality bonuses, counties are organized into
quartiles based on their Medicare fee-for-service (FFS) spending. Also,
Congress chose the worst performing quartile of hospitals for the
Hospital-Acquired Condition Reduction Program penalty. (We refer
readers to section IV.J. of the preamble of this proposed rule for a
discussion of the Hospital-Acquired Condition Reduction Program.)
Having determined that quartiles are a reasonable method of dividing
the distribution of hospitals' wage index values, we believe that
identifying hospitals in the lowest quartile as low wage index
hospitals, hospitals in the second and third ``middle'' quartiles as
hospitals with wages index values that are neither low nor high, and
hospitals in the highest quartile as hospitals with high wage index
values, is then a reasonable method of determining low wage index and
high wage index hospitals for purposes of our proposals (discussed
below) addressing wage index disparities. While we acknowledge that
there is no set standard for identifying hospitals as having low or
high wage index values, we believe our proposed quartile approach is
reasonable for this purpose, given that, as discussed above, quartiles
are a common way to divide distributions, and this proposed approach is
consistent with approaches used in other areas of the Medicare program.
Based on the data for this proposed rule, for FY 2020, the 25th
percentile wage index value across all hospitals is 0.8482. If this
policy is adopted in the final rule, this number would be updated in
the final rule based on the final wage index values.
Under our proposed methodology, we are proposing to increase the
wage index for hospitals with a wage index value below the 25th
percentile wage index. The proposed increase in the wage index for
these hospitals would be equal to half the difference between the
otherwise applicable final wage index value for a year for that
hospital and the 25th percentile wage index value for that year across
all hospitals. For example, assume the otherwise applicable final FY
2020 wage index value for a geographically rural hospital in Alabama is
0.6663, and the 25th percentile wage index value for FY 2020 is 0.8482.
Half the difference between the otherwise applicable wage index value
and the 25th percentile wage index value is 0.0910 (that is, (0.8482 -
0.6663)/2). Under our proposal, the FY 2020 wage index value for such a
hospital would be 0.7573 (that is, 0.6663 + 0.0910).
Some respondents to the request for information indicated that CMS
should establish a wage index floor for hospitals with low wage index
values. However, we believe that it is important to preserve the rank
order of the wage index values under the current policy and, therefore,
are proposing to increase the wage index for the low-wage index
hospitals described above by half the difference between the otherwise
applicable final wage index value and the 25th percentile wage index
value. We believe the rank order generally reflects meaningful
distinctions between the employee compensation costs faced by hospitals
in different geographic areas. Although wage index value differences
between areas may be artificially magnified by the current wage index
policies, we do not believe those differences are nonexistent. For
example, if we were to instead create a floor to address the lag issue
discussed above, it does not seem likely that hospitals in Puerto Rico
and Alabama would have the same wage index value after hospitals in
both areas have had the opportunity increase their employee
compensation costs. We believe a distinction between their wage index
values would remain because hospitals in these areas face different
employee compensation costs in their respective labor market areas.
We are proposing that this policy would be effective for at least 4
years, beginning in FY 2020, in order to allow employee compensation
increases implemented by these hospitals sufficient time to be
reflected in the wage index calculation. For the FY 2020 wage index, we
are proposing to use data from the FY 2016 cost reports. Four years is
the minimum time before increases in employee compensation included in
the Medicare cost report could be reflected in the wage index data, and
additional time may be necessary. We intend to revisit the issue of the
duration of the policy in future rulemaking as we gain experience under
the policy if adopted.
b. Budget Neutrality for Providing an Opportunity for Low Wage Index
Hospitals To Increase Employee Compensation
As noted earlier, in response to the request for information on
wage index disparities in the FY 2019 IPPS/LTCH PPS proposed rule, some
respondents recommended that CMS create a wage index floor for low wage
index hospitals, and that, in order to maintain budget neutrality, CMS
reduce the wage index values for high wage index hospitals through the
creation of wage index ceiling.
While we do not believe it would be appropriate to create a wage
index floor or a wage index ceiling as suggested in the comment
summarized above, we believe the suggestion that we provide a mechanism
to increase the wage index of low wage index hospitals (as we have
proposed in section III.N.3.a. of the preamble of this proposed rule)
while maintaining budget neutrality for that increase through an
adjustment to the wage index of high wage index hospitals has two key
merits. First, by compressing the wage index for hospitals on the high
and low ends, that is, those hospitals with a low wage index and those
hospitals with a high wage index, such a methodology increases the
impact on existing wage index disparities more than by simply
addressing one end. Second, such a methodology ensures those hospitals
in the middle, that is, those hospitals whose wage index is not
considered high or low, do not have their wage index values affected by
this proposed policy. Thus, given the growing disparities between low
wage index hospitals and high wage index hospitals, consistent with the
comment summarized above, we believe it would
[[Page 19396]]
be appropriate to maintain budget neutrality for the low wage index
policy proposed in section III.N.3.a. of the preamble of this proposed
rule by adjusting the wage index for high wage index hospitals.
As discussed earlier, we believe it is important to preserve the
rank order of wage index values because the rank order generally
reflects meaningful distinctions between the employee compensation
costs faced by hospitals in different geographic areas. Although wage
index value differences between areas (including areas with high wage
index hospitals) may be artificially magnified by the current wage
index policies, we do not believe those differences are nonexistent,
and therefore, we do not believe it would be appropriate to set a wage
index ceiling or floor. Accordingly, in order to offset the estimated
increase in IPPS payments to hospitals with wage index values below the
25th percentile under our proposal in section III.N.3.a. of the
preamble of this proposed rule, we are proposing to decrease the wage
index values for hospitals with high wage index values, but preserve
the rank order among those values, as further discussed below.
As discussed in section III.N.3.a. of the preamble of this proposed
rule, we believe it is reasonable to divide all hospitals into
quartiles based on their wage index value whereby we identify hospitals
in the lowest quartile as low wage index hospitals, hospitals in the
second and third ``middle'' quartiles as hospitals with wage index
values that are neither high nor low, and hospitals in the highest
quartile as hospitals with high wage index values. We believe our
proposed quartile approach is reasonable for this purpose, given that,
as discussed above, quartiles are a common way to divide distributions,
and this proposed approach is consistent with approaches used in other
areas of the Medicare program. Therefore, we are proposing to identify
high wage index hospitals as hospitals in the highest quartile, and in
the budget neutrality discussion that follows, we refer to hospitals
with wage index values above the 75th percentile wage index value
across all hospitals for a fiscal year as ``high wage index
hospitals.''
To ensure our proposal in section III.N.3.a. of the preamble of
this proposed rule is budget neutral, we are proposing to reduce the
wage index values for high wage index hospitals using a methodology
analogous to the methodology used to increase the wage index values for
low wage index hospitals described in section III.N.3.a. of the
preamble of this proposed rule; that is, we are proposing to decrease
the wage index values for high wage index hospitals by a uniform factor
of the distance between the hospital's otherwise applicable wage index
and the 75th percentile wage index value for a fiscal year across all
hospitals. As described below, the proposed budget neutrality
adjustment factor is 3.4 percent for FY 2020.
In calculating the proposed budget neutrality adjustment factor for
our proposal in section III.N.3.a. of the preamble of this proposed
rule, we would first examine the distance between the wage index values
for high wage index hospitals and the 75th percentile wage index value
across all hospitals for a fiscal year. Based on the data for this
proposed rule, the 75th percentile wage index value is 1.0351.
Therefore, for example, if high wage index Hospital A had an otherwise
applicable wage index value of 1.7351, the distance between that
hospital's wage index value and the 75th percentile is 0.7000 (that is,
1.7351 - 1.0351). If high wage index Hospital B had an otherwise
applicable wage index value of 1.2351, the distance between that
hospital's wage index value and the 75th percentile is 0.2000 (that is,
1.2351 - 1.0351).
We would next estimate the uniform multiplicative budget neutrality
factor needed to reduce those distances for all high wage index
hospitals so that the estimated decreased aggregate payments to high
wage index hospitals offset the estimated increased aggregate payments
to low wage index hospitals under our proposed policy in section
III.N.3.a. of the preamble of this proposed rule. Based on the data for
this proposed rule, we estimate this factor is 3.4 percent for FY 2020.
Therefore, in the examples we provided earlier, the distance
between Hospital A's wage index value and the 75th percentile would be
reduced by 0.0238 (that is, the prior distance of 0.7000 * 0.034), and
therefore the wage index for Hospital A after application of the
proposed budget neutrality adjustment would be 1.7113 (that is, 1.7351
- 0.0238). The distance between Hospital B's wage index value and the
75th percentile would be reduced by 0.0068 (that is, the prior distance
of 0.2000 * 0.034), and therefore the wage index for Hospital B after
application of the proposed budget neutrality adjustment would be
1.2283 (that is, 1.2351-0.0068).
We believe we have authority to implement our lowest quartile wage
index proposal in section III.N.3.a. of the preamble of this proposed
rule and our budget neutrality proposal in this section III.N.3.b. of
the preamble of this proposed rule under section 1886(d)(3)(E) of the
Act (which gives the Secretary broad authority to adjust for area
differences in hospital wage levels by a factor (established by the
Secretary) reflecting the relative hospital wage level in the
geographic area of the hospital compared to the national average
hospital wage level, and requires those adjustments to be budget
neutral), and under our exceptions and adjustments authority under
section 1886(d)(5)(I) of the Act.
c. Preventing Inappropriate Payment Increases Due to Rural
Reclassifications Under the Provisions of 42 CFR 412.103
We also agree with respondents to the request for information who
indicated that another contributing systemic factor to wage index
disparities is the rural floor. As discussed in section III.G.1. of the
preamble of this proposed rule, section 4410(a) of Public Law 105-33
provides that, for discharges on or after October 1, 1997, the area
wage index applicable to any hospital that is located in an urban area
of a State may not be less than the area wage index applicable to
hospitals located in rural areas in that State. Section 3141 of Public
Law 111-148 also requires that a national budget neutrality adjustment
be applied in implementing the rural floor.
The rural floor policy was addressed by the Office of the Inspector
General (OIG) in its recent November 2018 report, ``Significant
Vulnerabilities Exist in the Hospital Wage Index System for Medicare
Payment'' (A-01-17-00500), which is available on the OIG website at:
https://oig.hhs.gov/oas/reports/region1/11700500.pdf. The OIG stated
(we note that the footnote references included here were in the
original document but are not carried here):
``The stated legislative intent of the rural floor was to correct
the `anomaly' of `some urban hospitals being paid less than the average
rural hospital in their States.' \9\ However, MedPAC, an independent
congressional advisory board, has since stated that it is `not aware of
any empirical support for this policy,\10\ and that the policy is built
on the false assumption that hospital wage rates in all urban labor
markets in a State are always higher than the average hospital wage
rate in rural areas of that State.\11\ ''
As one simplified example for purposes of illustrating the rural
floor policy, assume that the rural wage index for a State is 1.1000.
Therefore, under current policy, the rural floor for that State would
be 1.1000. Any urban hospital with a wage index value below
[[Page 19397]]
1.1000 in that State would have its wage index value raised to 1.1000.
The additional Medicare payments to those urban hospitals in that State
increase the national budget neutrality adjustment for the rural floor
provision.
For a real world example of the impact of the rural floor policy,
we point to FY 2018, in which 366 urban hospitals benefitted from the
rural floor. The increase in the wage indexes of urban hospitals
receiving the rural floor was offset by a nationwide decrease in all
hospitals' wage indexes of approximately 0.67 percent. In
Massachusetts, that meant that 36 urban hospitals received a wage index
based on hospital wages in Nantucket, an island that is home to the
only rural hospital contributing to the State's rural floor wage index.
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38557), we estimated
that those 36 hospitals would receive an additional $44 million in
inpatient payments for the year. These increased payments were offset
by decreased payments to hospitals nationwide, and those decreases were
not based on actual local wage rates but on the current rural floor
calculation.
As acknowledged by the OIG, CMS has long recognized the disparate
impacts and unintended outcomes of the rural floor. We have stated that
the rural floor creates a benefit for a minority of States that is then
funded by a majority of States, including States that are
overwhelmingly rural in character (73 FR 23528 and 23622). We also have
stated that ``as a result of hospital actions not envisioned by
Congress, the rural floor is resulting in significant disparities in
wage index and, in some cases, resulting in situations where all
hospitals in a State receive a wage index higher than that of the
single highest wage index urban hospital in the State'' (76 FR 42170
and 42212).
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41748), we indicated
that wage index disparities associated with the rural floor
significantly increased in FY 2019 with the urban to rural
reclassification of an urban hospital in Massachusetts. We also note
that Massachusetts is not the only State where urban hospitals
reclassified as rural under Sec. 412.103 have a significant impact on
the State's rural floor. This also occurs, for example, in Arizona and
Connecticut. The rural floor policy was meant to address anomalies of
some urban hospitals being paid less than the average rural hospital in
their States, not to raise the payments of many hospitals in a State to
the high wage level of a geographically urban hospital.
We note that, for FY 2020, the urban Massachusetts hospital
reclassified as rural under Sec. 412.103 has an approved MGCRB
reclassification back to its geographic location, and, therefore, its
MGCRB reclassification is used for wage index calculation and payment
purposes in this proposed rule (that is, this hospital would not be
considered rural for wage index purposes). However, under our current
wage index policy, the hospital would be able to influence the
Massachusetts rural floor by withdrawing or terminating its MGCRB
reclassification in accordance with the regulation at Sec. 412.273 for
FY 2020 or subsequent years.
Returning to our simplified example, for purposes of illustrating
the impact of an urban to rural reclassification on the calculation of
the rural floor under current policy, again assume that the rural wage
index for a State is 1.1000. Therefore, under current policy, the rural
floor for that State would be 1.1000. Any urban hospital with a wage
index value below 1.1000 in that State would have its wage index value
raised to 1.1000. However, now assume that one urban hospital in that
State subsequently reclassifies from urban to rural and raises the
rural wage index from 1.1000 to 1.2000. Now, solely because of a
geographically urban hospital, the rural floor in that State would go
from 1.1000 to 1.2000 under current policy.
As noted by OIG in the November 2018 report referenced above, the
stated legislative intent of the rural floor was to correct the
``anomaly'' of ``some urban hospitals being paid less than the average
rural hospital in their States.'' (Report 105-149 of the Committee on
the Budget, House of Representatives, to Accompany H.R. 2015, June 24,
1997, section 10205, page 1305.) We believe that urban to rural
reclassifications have stretched the rural floor provision beyond a
policy designed to address such anomalies. Rather than raising the
payment of some urban hospitals to the level of the average rural
hospital in their State, urban hospitals may have their payments raised
to the relatively high level of one or more geographically urban
hospitals reclassified as rural. The current state of affairs with
respect to urban to rural reclassifications goes beyond the general
criticisms of the rural floor policy by MedPAC, CMS, OIG, and many
stakeholders. We believe an adjustment is necessary to address the
unanticipated effects of urban to rural reclassifications on the rural
floor and the resulting wage index disparities, including the
inappropriate wage index disparities caused by the manipulation of the
rural floor policy by some hospitals.
Therefore, given the circumstances described above, the comments
received on the request for information, and that urban to rural
reclassifications have stretched the rural floor provision beyond a
policy designed to address anomalies of some urban hospitals being paid
less than the average rural hospital in their States, we are proposing
to remove urban to rural reclassifications from the calculation of the
rural floor. In other words, under our proposal, beginning in FY 2020,
the rural floor would be calculated without including the wage data of
urban hospitals that have reclassified as rural under section
1886(d)(8)(E) of the Act (as implemented at Sec. 412.103). We believe
our proposed calculation methodology is permissible under section
1886(d)(8)(E) of the Act and the rural floor statute (section 4410 of
Pub. L. 105-33). Section 1886(d)(8)(E) of the Act does not specify
where the wage data of reclassified hospitals must be included.
Therefore, we believe we have discretion to exclude the wage data of
such hospitals from the calculation of the rural floor. Furthermore,
the rural floor statute does not specify how the rural floor wage index
is to be calculated or what data are to be included in the calculation.
Therefore, we also believe we have discretion under the rural floor
statute to exclude the wage data of hospitals reclassified under
section 1886(d)(8)(E) of the Act from the calculation of the rural
floor. We believe this proposed policy is necessary and appropriate to
address the unanticipated effects of rural reclassifications on the
rural floor and the resulting wage index disparities, including the
effects of the manipulation of the rural floor by certain hospitals. As
discussed above, the inclusion of reclassified hospitals in the rural
floor calculation has had the unforeseen effect of exacerbating the
wage index disparities between low and high wage index hospitals.
Therefore, under our proposal, in the case of Massachusetts, for
example, the geographically rural hospital in Nantucket would still be
included in the calculation of the rural floor for Massachusetts, but a
geographically urban hospital reclassified under Sec. 412.103 would
not.
Returning to our simplified example for purposes of illustrating
the impact of the proposed policy, again assume that the rural wage
index for a State is 1.1000 without any hospital in the State having
reclassified from urban to rural. Therefore, the rural floor for that
State would be 1.1000. Any urban hospital
[[Page 19398]]
with a wage index value below 1.1000 in that State would have its wage
index value raised to 1.1000. However, again assume that one urban
hospital in that State subsequently reclassifies from urban to rural
and raises the rural wage index from 1.1000 to 1.2000. Under our
proposed policy, the rural floor in that State would not go from 1.1000
to 1.2000, but would remain at 1.1000 because urban to rural
reclassifications would no longer impact the rural floor.
As we discuss earlier, the purpose of our proposal to calculate the
rural floor without including the wage data of urban hospitals
reclassified as rural under section 1886(d)(8)(E) of the Act (as
implemented at Sec. 412.103) is to address wage index disparities that
result when urban hospitals may have their payments raised to the
relatively high level of one or more geographically urban hospitals
reclassified as rural. In particular, we believe that no urban hospital
not reclassified as rural should have its payments raised to the
relatively high level of one or more geographically urban hospitals
reclassified as rural, and we believe it would be inappropriate to
prevent this for one class of urban hospitals not reclassified as rural
(that is, under the rural floor provision) but allow this for another.
As such, for consistent treatment of urban hospitals not reclassified
as rural, we also are proposing to apply the provisions of section
1886(d)(8)(C)(iii) of the Act without including the wage data of urban
hospitals that have reclassified as rural under section 1886(d)(8)(E)
of the Act (as implemented at Sec. 412.103). Because section
1886(d)(8)(C)(iii) of the Act provides that reclassifications under
section 1886(d)(8)(B) of the Act and section 1886(d)(10) of the Act may
not reduce any county's wage index below the wage index for rural areas
in the State, we are making this proposal to help ensure no urban
hospitals not reclassified as rural, including those hospitals with no
reclassification as well as those hospitals reclassified under section
1886(d)(8)(B) of the Act or section 1886(d)(10) of the Act, have their
payments raised to the relatively high level of one or more
geographically urban hospitals reclassified as rural. Specifically, for
purposes of applying the provisions of section 1886(d)(8)(C)(iii) of
the Act, we are proposing to remove urban to rural reclassifications
from the calculation of ``the wage index for rural areas in the State
in which the county is located'' referred to in section
1886(d)(8)(C)(iii) of the Act.
d. Proposed Transition for Hospitals Negatively Impacted
We recognize that, absent further adjustments, the combined effect
of the proposed changes to the FY 2020 wage index could lead to
significant decreases in the wage index values for some hospitals
depending on the data for the final rule. In the past, we have proposed
and finalized budget neutral transition policies to help mitigate any
significant negative impacts on hospitals of certain wage index
proposals, and we believe it would be appropriate to propose a
transition policy here for the same purpose. For example, in the FY
2015 IPPS/LTCH PPS final rule (79 FR 49957 through 49963), we finalized
a budget neutral transition to address certain wage index changes that
occurred under the new OMB CBSA delineations.
Therefore, for FY 2020, we are proposing a transition wage index to
help mitigate any significant decreases in the wage index values of
hospitals compared to their final wage indexes for FY 2019.
Specifically, for FY 2020, we are proposing to place a 5-percent cap on
any decrease in a hospital's wage index from the hospital's final wage
index in FY 2019. In other words, we are proposing that a hospital's
final wage index for FY 2020 would not be less than 95 percent of its
final wage index for FY 2019. This proposed transition would allow the
effects of our proposed policies to be phased in over 2 years with no
estimated reduction in the wage index of more than 5 percent in FY 2020
(that is, no cap would be applied the second year). We believe 5
percent is a reasonable level for the cap because it would effectively
mitigate any significant decreases in the wage index for FY 2020.
However, we are seeking public comments on alternative levels for the
cap and accompanying rationale. Under the proposed transition policy,
we would compute the proposed FY 2020 wage index for each hospital as
follows.
Step 1.--Compute the proposed FY 2020 ``uncapped'' wage index that
would result from the implementation of proposed changes to the FY 2020
wage index.
Step 2.--Compute a proposed FY 2020 ``capped'' wage index which
would equal 95 percent of that provider's FY 2019 final wage index.
Step 3.--The proposed FY 2020 wage index is the greater of the
``uncapped'' wage index computed in Step 1 or the ``capped'' wage index
computed in Step 2.
e. Transition Budget Neutrality
We are proposing to apply a budget neutrality adjustment to the
standardized amount so that our proposed transition (described in
section III.N.3.c. of the preamble of this proposed rule) for hospitals
that could be negatively impacted is implemented in a budget neutral
manner under our authority in section 1886(d)(5)(I) of the Act. We note
that implementing the proposed transition wage index in a budget
neutral manner is consistent with past practice (for example, 79 FR
50372) where CMS has used its exceptions and adjustments authority
under section 1886(d)(5)(I)(i) of the Act to budget neutralize
transition wage index policies when such policies allow for the
application of a transitional wage index only when it benefits the
hospital. We believed, and continue to believe, that it would be
appropriate to ensure that such policies do not increase estimated
aggregate Medicare payments beyond the payments that would be made had
we never proposed these transition policies (79 FR 50732). Therefore,
for FY 2020, we are proposing to use our exceptions and adjustments
authority under section 1886(d)(5)(I)(i) of the Act to apply a budget
neutrality adjustment to the standardized amount so that our proposed
transition (described in section III.N.3.d. of the preamble of this
proposed rule) for hospitals negatively impacted is implemented in a
budget neutral manner.
Specifically, we are proposing to apply a budget neutrality
adjustment to ensure that estimated aggregate payments under our
proposed transition (described in section III.N.3.d. of the preamble of
this proposed rule) for hospitals negatively impacted by our proposed
wage index policies would equal what estimated aggregate payments would
have been without the proposed transition for hospitals negatively
impacted. To determine the associated budget neutrality factor, we
compared estimated aggregate IPPS payments with and without the
proposed transition. To achieve budget neutrality for the proposed
transition policy, we are proposing to apply a budget neutrality
adjustment factor of 0.998349 to the FY 2020 standardized amount, as
further discussed in section I.A.4.f. of the Addendum to this proposed
rule. If this policy is adopted in the final rule, this number would be
updated based on the final rule data.
We note that our proposal, discussed in section III.N.3.c. of the
preamble of this proposed rule, to prevent inappropriate payment
increases due rural reclassifications under Sec. 412.103 would also be
budget neutral, but this budget neutrality would occur through the
proposed budget neutrality
[[Page 19399]]
adjustments for geographic reclassifications and the rural floor that
are discussed in the Addendum to this proposed rule.
IV. Other Decisions and Proposed Changes to the IPPS for Operating
System
A. Proposed Changes to MS-DRGs Subject to Postacute Care Transfer
Policy and MS-DRG Special Payments Policies (Sec. 412.4)
1. Background
Existing regulations at 42 CFR 412.4(a) define discharges under the
IPPS as situations in which a patient is formally released from an
acute care hospital or dies in the hospital. Section 412.4(b) defines
acute care transfers, and Sec. 412.4(c) defines postacute care
transfers. Our policy set forth in Sec. 412.4(f) provides that when a
patient is transferred and his or her length of stay is less than the
geometric mean length of stay for the MS-DRG to which the case is
assigned, the transferring hospital is generally paid based on a
graduated per diem rate for each day of stay, not to exceed the full
MS-DRG payment that would have been made if the patient had been
discharged without being transferred.
The per diem rate paid to a transferring hospital is calculated by
dividing the full MS-DRG payment by the geometric mean length of stay
for the MS-DRG. Based on an analysis that showed that the first day of
hospitalization is the most expensive (60 FR 45804), our policy
generally provides for payment that is twice the per diem amount for
the first day, with each subsequent day paid at the per diem amount up
to the full MS-DRG payment (Sec. 412.4(f)(1)). Transfer cases also are
eligible for outlier payments. In general, the outlier threshold for
transfer cases, as described in Sec. 412.80(b), is equal to the fixed-
loss outlier threshold for nontransfer cases (adjusted for geographic
variations in costs), divided by the geometric mean length of stay for
the MS-DRG, and multiplied by the length of stay for the case, plus 1
day.
We established the criteria set forth in Sec. 412.4(d) for
determining which DRGs qualify for postacute care transfer payments in
the FY 2006 IPPS final rule (70 FR 47419 through 47420). The
determination of whether a DRG is subject to the postacute care
transfer policy was initially based on the Medicare Version 23.0
GROUPER (FY 2006) and data from the FY 2004 MedPAR file. However, if a
DRG did not exist in Version 23.0 or a DRG included in Version 23.0 is
revised, we use the current version of the Medicare GROUPER and the
most recent complete year of MedPAR data to determine if the DRG is
subject to the postacute care transfer policy. Specifically, if the MS-
DRG's total number of discharges to postacute care equals or exceeds
the 55th percentile for all MS-DRGs and the proportion of short-stay
discharges to postacute care to total discharges in the MS-DRG exceeds
the 55th percentile for all MS-DRGs, CMS will apply the postacute care
transfer policy to that MS-DRG and to any other MS-DRG that shares the
same base MS-DRG. The statute directs us to identify MS-DRGs based on a
high volume of discharges to postacute care facilities and a
disproportionate use of postacute care services. As discussed in the FY
2006 IPPS final rule (70 FR 47416), we determined that the 55th
percentile is an appropriate level at which to establish these
thresholds. In that same final rule (70 FR 47419), we stated that we
will not revise the list of DRGs subject to the postacute care transfer
policy annually unless we are making a change to a specific MS-DRG.
To account for MS-DRGs subject to the postacute care policy that
exhibit exceptionally higher shares of costs very early in the hospital
stay, Sec. 412.4(f) also includes a special payment methodology. For
these MS-DRGs, hospitals receive 50 percent of the full MS-DRG payment,
plus the single per diem payment, for the first day of the stay, as
well as a per diem payment for subsequent days (up to the full MS-DRG
payment (Sec. 412.4(f)(6)). For an MS-DRG to qualify for the special
payment methodology, the geometric mean length of stay must be greater
than 4 days, and the average charges of 1-day discharge cases in the
MS-DRG must be at least 50 percent of the average charges for all cases
within the MS-DRG. MS-DRGs that are part of an MS-DRG severity level
group will qualify under the MS-DRG special payment methodology policy
if any one of the MS-DRGs that share that same base MS-DRG qualifies
(Sec. 412.4(f)(6)).
Prior to the enactment of the Bipartisan Budget Act of 2018 (Pub.
L. 115-123), under section 1886(d)(5)(J) of the Act, a discharge was
deemed a ``qualified discharge'' if the individual was discharged to
one of the following postacute care settings:
A hospital or hospital unit that is not a subsection (d)
hospital.
A skilled nursing facility.
Related home health services provided by a home health
agency provided within a timeframe established by the Secretary
(beginning within 3 days after the date of discharge).
Section 53109 of the Bipartisan Budget Act of 2018 amended section
1886(d)(5)(J)(ii) of the Act to also include discharges to hospice care
provided by a hospice program as a qualified discharge, effective for
discharges occurring on or after October 1, 2018. Accordingly,
effective for discharges occurring on or after October 1, 2018, if a
discharge is assigned to one of the MS-DRGs subject to the postacute
care transfer policy and the individual is transferred to hospice care
by a hospice program, the discharge is subject to payment as a transfer
case. In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41394), we made
conforming amendments to Sec. 412.4(c) of the regulation to include
discharges to hospice care occurring on or after October 1, 2018 as
qualified discharges. We specified that hospital bills with a Patient
Discharge Status code of 50 (Discharged/Transferred to Hospice--Routine
or Continuous Home Care) or 51 (Discharged/Transferred to Hospice,
General Inpatient Care or Inpatient Respite) are subject to the
postacute care transfer policy in accordance with this statutory
amendment. Consistent with our policy for other qualified discharges,
CMS claims processing software has been revised to identify cases in
which hospice benefits were billed on the date of hospital discharge
without the appropriate discharge status code. Such claims will be
returned as unpayable to the hospital and may be rebilled with a
corrected discharge code.
2. Proposed Changes for FY 2020
As discussed in section II.F. of the preamble of this FY 2020 IPPS/
LTCH PPS proposed rule, based on our analysis of FY 2018 MedPAR claims
data, we are proposing to make changes to a number of MS-DRGs,
effective for FY 2020. Specifically, we are proposing to:
Reassign procedure codes from MS-DRGs 216 through 218
(Cardiac Valve and Other Major Cardiothoracic Procedures with Cardiac
Catheterization with MCC, CC and without CC/MCC, respectively), MS-DRGs
219 through 221 (Cardiac Valve and Other Major Cardiothoracic
Procedures without Cardiac Catheterization with MCC, CC and without CC/
MCC, respectively), and MS-DRGs 273 and 274 (Percutaneous Intracardiac
Procedures with and without MCC, respectively) and create new MS-DRGs
319 and 320 (Other Endovascular Cardiac Valve Procedures with and
without MCC, respectively); and
Delete MS-DRGs 691 and 692 (Urinary Stones with ESW
Lithotripsy with CC/MCC and without CC/MCC,
[[Page 19400]]
respectively) and revise the titles for MS-DRGs 693 and 694 to
``Urinary Stones with MCC'' and ``Urinary Stones without MCC'',
respectively.
In light of the proposed changes to these MS-DRGs for FY 2020,
according to the regulations under Sec. 412.4(d), we evaluated these
MS-DRGs using the general postacute care transfer policy criteria and
data from the FY 2018 MedPAR file. If an MS-DRG qualified for the
postacute care transfer policy, we also evaluated that MS-DRG under the
special payment methodology criteria according to regulations at Sec.
412.4(f)(6). We continue to believe it is appropriate to reassess MS-
DRGs when proposing reassignment of procedure codes or diagnosis codes
that would result in material changes to an MS-DRG. MS-DRGs 216, 217,
218, 219, 220, and 221 are currently subject to the postacute care
transfer policy. As a result of our review, these MS-DRGs, as proposed
to be revised, would continue to qualify to be included on the list of
MS-DRGs that are subject to the postacute care transfer policy. MS-DRGs
273 and 274 are also currently subject to the postacute care transfer
policy and MS-DRGs 693 and 694 are currently not subject to the
postacute care transfer policy. As a result of our review, these MS-
DRGs, as proposed to be revised, would not qualify to be included on
the list of MS-DRGs that are subject to the postacute care transfer
policy. Proposed new MS-DRGs 319 and 320 also would not qualify to be
included on the list of MS-DRGs that are subject to the postacute care
transfer policy. Therefore, we are proposing to remove MS-DRGs 273 and
274 from the list of MS-DRGs that are subject to the postacute care
transfer policy. We note that MS-DRGs that are subject to the postacute
care transfer policy for FY 2019 and are not revised will continue to
be subject to the policy in FY 2020.
Using the December 2018 update of the FY 2018 MedPAR file, we
developed the chart below, which sets forth the most recent analysis of
the postacute care transfer policy criteria completed for this proposed
rule with respect to each of these proposed new or revised MS-DRGs. For
the FY 2020 final rule, we intend to update this analysis using the
most recent available data at that time.
--------------------------------------------------------------------------------------------------------------------------------------------------------
Percent of
short-stay
Postacute care postacute care
Proposed new or transfers Short-stay transfers to Current postacute Proposed postacute
revised MS-DRGS MS-DRG title Total cases (55th postacute care all cases care transfer policy care transfer policy
percentile: transfers (55th status status
1,400) percentile:
8.5132%)
--------------------------------------------------------------------------------------------------------------------------------------------------------
216................. Cardiac Valve & Other 5,733 4,196 1,643 28.6586 Yes................. Yes.
Major Cardiothoracic
Procedure with
Cardiac
Catheterization with
MCC.
217................. Cardiac Valve & Other 2,317 1,551 424 18.2995 Yes................. Yes.
Major Cardiothoracic
Procedure with
Cardiac
Catheterization with
CC.
218................. Cardiac Valve & Other 599 * 328 67 11.1853 Yes................. ** Yes.
Major Cardiothoracic
Procedure with
Cardiac
Catheterization
without CC/MCC.
219................. Cardiac Valve & Other 13,177 9,216 3,450 26.182 Yes................. Yes.
Major Cardiothoracic
Procedure without
Cardiac
Catheterization with
MCC.
220................. Cardiac Valve & Other 16,201 10,247 2,914 17.9865 Yes................. Yes.
Major Cardiothoracic
Procedure without
Cardiac
Catheterization with
CC.
221................. Cardiac Valve & Other 6,070 3,205 239 * 3.9374 Yes................. ** Yes.
Major Cardiothoracic
Procedure without
Cardiac
Catheterization
without CC/MCC.
273................. Percutaneous 5,958 2,152 280 * 4.6996 Yes................. No.
Intracardiac
Procedures with MCC.
274................. Percutaneous 0 * 0 0 * 0 Yes................. No.
Intracardiac
Procedures without
MCC.
319................. Other Endovascular 1,651 * 842 191 11.5687 New................. No.
Cardiac Valve
Procedures with MCC.
320................. Other Endovascular 707 * 229 30 * 4.2433 New................. No.
Cardiac Valve
Procedures without
MCC.
693................. Urinary Stones with 1,300 * 541 81 * 6.2308 No.................. No.
MCC.
694................. Urinary Stones without 8,025 1,739 185 * 2.3053 No.................. No.
MCC.
--------------------------------------------------------------------------------------------------------------------------------------------------------
* Indicates a current postacute care transfer policy criterion that the MS-DRG did not meet.
** As described in the policy at 42 CFR 412.4(d)(3)(ii)(D), MS-DRGs that share the same base MS-DRG will all qualify under the postacute care transfer
policy if any one of the MS-DRGs that share that same base MS-DRG qualifies.
During our annual review of proposed new or revised MS-DRGs and
analysis of the December 2018 update of the FY 2018 MedPAR file, we
reviewed the list of proposed revised or new MS-DRGs that qualify to be
included on the list of MS-DRGs subject to the postacute care transfer
policy for FY 2020 to determine if any of these MS-DRGs would also be
subject to the special payment methodology policy for FY 2020. Based on
our analysis of proposed changes to MS-DRGs included in this proposed
rule, we determined that proposed revised MS-DRGs 216, 217, 218, 219,
220, and 221 would continue to meet the criteria for the MS-DRG special
payment methodology. Because we are proposing to remove MS-DRGs 273 and
274 from the list of MS-DRGs subject to the postacute care transfer
policy, we also are proposing to remove these MS-DRGs from the list of
MS-DRGs subject to the MS-DRG special payment methodology, effective FY
2020.
For the FY 2020 final rule, we intend to update this analysis using
the most recent available data at that time.
[[Page 19401]]
--------------------------------------------------------------------------------------------------------------------------------------------------------
50 Percent of
Geometric mean Average average
Proposed revised MS- MS-DRG title length of charges of 1- charges for Current special Proposed special
DRG stay day all cases payment policy status payment policy status
discharges within MS-DRG
--------------------------------------------------------------------------------------------------------------------------------------------------------
216..................... Cardiac Valve & Other 14.1126 0 $186,087.76 Yes..................... Yes.
Major Cardiothoracic
Procedure with Cardiac
Catheterization with MCC.
217..................... Cardiac Valve & Other 8.9229 147,964.00 128,141.91 Yes..................... Yes.
Major Cardiothoracic
Procedure with Cardiac
Catheterization with CC.
218..................... Cardiac Valve & Other 6.46878 203,555.50 101,286.68 Yes..................... Yes.
Major Cardiothoracic
Procedure with Cardiac
Catheterization without
CC/MCC.
219..................... Cardiac Valve & Other 9.48987 185,157.20 152,482.54 Yes..................... Yes.
Major Cardiothoracic
Procedure without Cardiac
Catheterization with MCC.
220..................... Cardiac Valve & Other 6.3373 115,955.36 101,812.54 Yes..................... Yes.
Major Cardiothoracic
Procedure without Cardiac
Catheterization with CC.
221..................... Cardiac Valve & Other 4.66413 127,074.88 82,400.23 Yes..................... Yes.
Major Cardiothoracic
Procedure without Cardiac
Catheterization without
CC/MCC.
--------------------------------------------------------------------------------------------------------------------------------------------------------
The proposed postacute care transfer and special payment policy
status of these MS-DRGs is reflected in Table 5 associated with this
proposed rule, which is listed in section VI. of the Addendum to this
proposed rule and available via the internet on the CMS website.
B. Proposed Changes in the Inpatient Hospital Update for FY 2020 (Sec.
412.64(d))
1. Proposed FY 2020 Inpatient Hospital Update
In accordance with section 1886(b)(3)(B)(i) of the Act, each year
we update the national standardized amount for inpatient hospital
operating costs by a factor called the ``applicable percentage
increase.'' For FY 2020, we are setting the applicable percentage
increase by applying the adjustments listed in this section in the same
sequence as we did for FY 2019. (We note that section
1886(b)(3)(B)(xii) of the Act required an additional reduction each
year only for FYs 2010 through 2019.) Specifically, consistent with
section 1886(b)(3)(B) of the Act, as amended by sections 3401(a) and
10319(a) of the Affordable Care Act, we are setting the applicable
percentage increase by applying the following adjustments in the
following sequence. The applicable percentage increase under the IPPS
for FY 2020 is equal to the rate-of-increase in the hospital market
basket for IPPS hospitals in all areas, subject to--
(a) A reduction of one-quarter of the applicable percentage
increase (prior to the application of other statutory adjustments; also
referred to as the market basket update or rate-of-increase (with no
adjustments)) for hospitals that fail to submit quality information
under rules established by the Secretary in accordance with section
1886(b)(3)(B)(viii) of the Act;
(b) A reduction of three-quarters of the applicable percentage
increase (prior to the application of other statutory adjustments; also
referred to as the market basket update or rate-of-increase (with no
adjustments)) for hospitals not considered to be meaningful EHR users
in accordance with section 1886(b)(3)(B)(ix) of the Act; and
(c) An adjustment based on changes in economy-wide productivity
(the multifactor productivity (MFP) adjustment).
Section 1886(b)(3)(B)(xi) of the Act, as added by section 3401(a)
of the Affordable Care Act, states that application of the MFP
adjustment may result in the applicable percentage increase being less
than zero.
In compliance with section 404 of the MMA, in the FY 2018 IPPS/LTCH
PPS final rule (82 FR 38158 through 38175), we replaced the FY 2010-
based IPPS operating market basket with the rebased and revised 2014-
based IPPS operating market basket, effective with FY 2018.
We are proposing to base the proposed FY 2020 market basket update
used to determine the applicable percentage increase for the IPPS on
IHS Global Inc.'s (IGI's) fourth quarter 2018 forecast of the 2014-
based IPPS market basket rate-of-increase with historical data through
third quarter 2018, which is estimated to be 3.2 percent. We also are
proposing that if more recent data subsequently become available (for
example, a more recent estimate of the market basket and the MFP
adjustment), we would use such data, if appropriate, to determine the
FY 2020 market basket update and the MFP adjustment in the final rule.
For FY 2020, depending on whether a hospital submits quality data
under the rules established in accordance with section
1886(b)(3)(B)(viii) of the Act (hereafter referred to as a hospital
that submits quality data) and is a meaningful EHR user under section
1886(b)(3)(B)(ix) of the Act (hereafter referred to as a hospital that
is a meaningful EHR user), there are four possible applicable
percentage increases that can be applied to the standardized amount, as
specified in the table that appears later in this section.
In the FY 2012 IPPS/LTCH PPS final rule (76 FR 51689 through
51692), we finalized our methodology for calculating and applying the
MFP adjustment. As we explained in that rule, section
1886(b)(3)(B)(xi)(II) of the Act, as added by section 3401(a) of the
Affordable Care Act, defines this productivity adjustment as equal to
the 10-year moving average of changes in annual economy-wide, private
nonfarm business MFP (as projected by the Secretary for the 10-year
period ending with the applicable fiscal year, calendar year, cost
reporting period, or other annual period). The Bureau of Labor
Statistics (BLS) publishes the official measure of private nonfarm
business MFP. We refer readers to the BLS website at http://www.bls.gov/mfp for the BLS historical published MFP data.
MFP is derived by subtracting the contribution of labor and capital
input growth from output growth. The projections of the components of
MFP are currently produced by IGI, a nationally recognized economic
[[Page 19402]]
forecasting firm with which CMS contracts to forecast the components of
the market baskets and MFP. As we discussed in the FY 2016 IPPS/LTCH
PPS final rule (80 FR 49509), beginning with the FY 2016 rulemaking
cycle, the MFP adjustment is calculated using the revised series
developed by IGI to proxy the aggregate capital inputs. Specifically,
in order to generate a forecast of MFP, IGI forecasts BLS aggregate
capital inputs using a regression model. A complete description of the
MFP projection methodology is available on the CMS website at: http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch.html. As
discussed in the FY 2016 IPPS/LTCH PPS final rule, if IGI makes changes
to the MFP methodology, we will announce them on our website rather
than in the annual rulemaking.
For FY 2020, we are proposing an MFP adjustment of 0.5 percentage
point. Similar to the market basket update, for this proposed rule, we
used IGI's fourth quarter 2018 forecast of the MFP adjustment to
compute the proposed FY 2020 MFP adjustment. As noted previously, we
are proposing that if more recent data subsequently become available,
we would use such data, if appropriate, to determine the FY 2020 market
basket update and the MFP adjustment for the final rule.
Based on these data, for this proposed rule, we have determined
four proposed applicable percentage increases to the standardized
amount for FY 2020, as specified in the following table:
Proposed FY 2020 Applicable Percentage Increases for the IPPS
----------------------------------------------------------------------------------------------------------------
Hospital Hospital Hospital did Hospital did
submitted submitted NOT submit NOT submit
quality data quality data quality data quality data
FY 2020 and is a and is NOT a and is a and is NOT a
meaningful EHR meaningful EHR meaningful EHR meaningful EHR
user user user user
----------------------------------------------------------------------------------------------------------------
Proposed Market Basket 3.2 3.2 3.2 3.2
Rate[dash]of[dash]Increase.....................
Proposed Adjustment for Failure to Submit 0 0 -0.8 -0.8
Quality Data under Section 1886(b)(3)(B)(viii)
of the Act.....................................
Proposed Adjustment for Failure to be a 0 -2.4 0 -2.4
Meaningful EHR User under Section
1886(b)(3)(B)(ix) of the Act...................
Proposed MFP Adjustment under Section -0.5 -0.5 -0.5 -0.5
1886(b)(3)(B)(xi) of the Act...................
Proposed Applicable Percentage Increase Applied 2.7 0.3 1.9 -0.5
to Standardized Amount.........................
----------------------------------------------------------------------------------------------------------------
We are proposing to revise the existing regulations at 42 CFR
412.64(d) to reflect the current law for the update for FY 2020 and
subsequent fiscal years. Specifically, in accordance with section
1886(b)(3)(B) of the Act, we are proposing to add paragraph (viii) to
Sec. 412.64(d)(1) to set forth the applicable percentage increase to
the operating standardized amount for FY 2020 and subsequent fiscal
years as the percentage increase in the market basket index, subject to
the reductions specified under Sec. 412.64(d)(2) for a hospital that
does not submit quality data and Sec. 412.64(d)(3) for a hospital that
is not a meaningful EHR user, less an MFP adjustment. (As noted above,
section 1886(b)(3)(B)(xii) of the Act required an additional reduction
each year only for FYs 2010 through 2019.)
Section 1886(b)(3)(B)(iv) of the Act provides that the applicable
percentage increase to the hospital-specific rates for SCHs and MDHs
equals the applicable percentage increase set forth in section
1886(b)(3)(B)(i) of the Act (that is, the same update factor as for all
other hospitals subject to the IPPS). Therefore, the update to the
hospital-specific rates for SCHs and MDHs also is subject to section
1886(b)(3)(B)(i) of the Act, as amended by sections 3401(a) and
10319(a) of the Affordable Care Act. (Under current law, the MDH
program is effective for discharges on or before September 30, 2022, as
discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41429 through
41430).)
For FY 2020, we are proposing the following updates to the
hospital-specific rates applicable to SCHs and MDHs: A proposed update
of 2.7 percent for a hospital that submits quality data and is a
meaningful EHR user; a proposed update of 1.9 percent for a hospital
that fails to submit quality data and is a meaningful EHR user; a
proposed update of 0.3 percent for a hospital that submits quality data
and is not a meaningful EHR user; and a proposed update of -0.5 percent
for a hospital that fails to submit quality data and is not a
meaningful EHR user. As noted previously, for this FY 2020 IPPS/LTCH
PPS proposed rule, we are using IGI's fourth quarter 2018 forecast of
the 2014-based IPPS market basket update with historical data through
third quarter 2018. Similarly, we are using IGI's fourth quarter 2018
forecast of the MFP adjustment. We are proposing that if more recent
data subsequently become available (for example, a more recent estimate
of the market basket increase and the MFP adjustment), we would use
such data, if appropriate, to determine the update in the final rule.
2. Proposed FY 2020 Puerto Rico Hospital Update
As discussed in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56937
through 56938), prior to January 1, 2016, Puerto Rico hospitals were
paid based on 75 percent of the national standardized amount and 25
percent of the Puerto Rico-specific standardized amount. Section 601 of
Public Law 114-113 amended section 1886(d)(9)(E) of the Act to specify
that the payment calculation with respect to operating costs of
inpatient hospital services of a subsection (d) Puerto Rico hospital
for inpatient hospital discharges on or after January 1, 2016, shall
use 100 percent of the national standardized amount. Because Puerto
Rico hospitals are no longer paid with a Puerto Rico-specific
standardized amount under the amendments to section 1886(d)(9)(E) of
the Act, there is no longer a need for us to determine an update to the
Puerto Rico standardized amount. Hospitals in Puerto Rico are now paid
100 percent of the national standardized amount and, therefore, are
subject to the same update to the national standardized amount
discussed under section IV.B.1. of the preamble of this proposed rule.
Accordingly, in this FY 2020 IPPS/LTCH PPS proposed rule, for FY 2020,
we are proposing an applicable percentage increase of 2.7 percent to
the
[[Page 19403]]
standardized amount for hospitals located in Puerto Rico.
We note that section 1886(b)(3)(B)(viii) of the Act, which
specifies the adjustment to the applicable percentage increase for
``subsection (d)'' hospitals that do not submit quality data under the
rules established by the Secretary, is not applicable to hospitals
located in Puerto Rico.
In addition, section 602 of Public Law 114-113 amended section
1886(n)(6)(B) of the Act to specify that Puerto Rico hospitals are
eligible for incentive payments for the meaningful use of certified EHR
technology, effective beginning FY 2016, and also to apply the
adjustments to the applicable percentage increase under section
1886(b)(3)(B)(ix) of the Act to Puerto Rico hospitals that are not
meaningful EHR users, effective FY 2022. Accordingly, because the
provisions of section 1886(b)(3)(B)(ix) of the Act are not applicable
to hospitals located in Puerto Rico until FY 2022, the adjustments
under this provision are not applicable for FY 2020.
C. Rural Referral Centers (RRCs) Proposed Annual Updates to Case-Mix
Index and Discharge Criteria (Sec. 412.96)
Under the authority of section 1886(d)(5)(C)(i) of the Act, the
regulations at Sec. 412.96 set forth the criteria that a hospital must
meet in order to qualify under the IPPS as a rural referral center
(RRC). RRCs receive some special treatment under both the DSH payment
adjustment and the criteria for geographic reclassification.
Section 402 of Public Law 108-173 raised the DSH payment adjustment
for RRCs such that they are not subject to the 12-percent cap on DSH
payments that is applicable to other rural hospitals. RRCs also are not
subject to the proximity criteria when applying for geographic
reclassification. In addition, they do not have to meet the requirement
that a hospital's average hourly wage must exceed, by a certain
percentage, the average hourly wage of the labor market area in which
the hospital is located.
Section 4202(b) of Public Law 105-33 states, in part, that any
hospital classified as an RRC by the Secretary for FY 1991 shall be
classified as such an RRC for FY 1998 and each subsequent fiscal year.
In the August 29, 1997 IPPS final rule with comment period (62 FR
45999), we reinstated RRC status for all hospitals that lost that
status due to triennial review or MGCRB reclassification. However, we
did not reinstate the status of hospitals that lost RRC status because
they were now urban for all purposes because of the OMB designation of
their geographic area as urban. Subsequently, in the August 1, 2000
IPPS final rule (65 FR 47089), we indicated that we were revisiting
that decision. Specifically, we stated that we would permit hospitals
that previously qualified as an RRC and lost their status due to OMB
redesignation of the county in which they are located from rural to
urban, to be reinstated as an RRC. Otherwise, a hospital seeking RRC
status must satisfy all of the other applicable criteria. We use the
definitions of ``urban'' and ``rural'' specified in Subpart D of 42 CFR
part 412. One of the criteria under which a hospital may qualify as an
RRC is to have 275 or more beds available for use (Sec.
412.96(b)(1)(ii)). A rural hospital that does not meet the bed size
requirement can qualify as an RRC if the hospital meets two mandatory
prerequisites (a minimum case-mix index (CMI) and a minimum number of
discharges), and at least one of three optional criteria (relating to
specialty composition of medical staff, source of inpatients, or
referral volume). (We refer readers to Sec. 412.96(c)(1) through
(c)(5) and the September 30, 1988 Federal Register (53 FR 38513) for
additional discussion.) With respect to the two mandatory
prerequisites, a hospital may be classified as an RRC if--
The hospital's CMI is at least equal to the lower of the
median CMI for urban hospitals in its census region, excluding
hospitals with approved teaching programs, or the median CMI for all
urban hospitals nationally; and
The hospital's number of discharges is at least 5,000 per
year, or, if fewer, the median number of discharges for urban hospitals
in the census region in which the hospital is located. The number of
discharges criterion for an osteopathic hospital is at least 3,000
discharges per year, as specified in section 1886(d)(5)(C)(i) of the
Act.
1. Case-Mix Index (CMI)
Section 412.96(c)(1) provides that CMS establish updated national
and regional CMI values in each year's annual notice of prospective
payment rates for purposes of determining RRC status. The methodology
we used to determine the national and regional CMI values is set forth
in the regulations at Sec. 412.96(c)(1)(ii). The proposed national
median CMI value for FY 2020 is based on the CMI values of all urban
hospitals nationwide, and the proposed regional median CMI values for
FY 2020 are based on the CMI values of all urban hospitals within each
census region, excluding those hospitals with approved teaching
programs (that is, those hospitals that train residents in an approved
GME program as provided in Sec. 413.75). These proposed values are
based on discharges occurring during FY 2018 (October 1, 2017 through
September 30, 2018), and include bills posted to CMS' records through
December 2018.
In this FY 2020 IPPS/LTCH PPS proposed rule, we are proposing that,
in addition to meeting other criteria, if rural hospitals with fewer
than 275 beds are to qualify for initial RRC status for cost reporting
periods beginning on or after October 1, 2019, they must have a CMI
value for FY 2018 that is at least--
1.68555 (national--all urban); or
The median CMI value (not transfer-adjusted) for urban
hospitals (excluding hospitals with approved teaching programs as
identified in Sec. 413.75) calculated by CMS for the census region in
which the hospital is located.
The proposed median CMI values by region are set forth in the table
below. We intend to update the proposed CMI values in the FY 2020 final
rule to reflect the updated FY 2018 MedPAR file, which will contain
data from additional bills received through March 2019.
------------------------------------------------------------------------
Proposed
Region case-mix
index value
------------------------------------------------------------------------
1. New England (CT, ME, MA, NH, RI, VT).................... 1.4231
2. Middle Atlantic (PA, NJ, NY)............................ 1.492
3. South Atlantic (DE, DC, FL, GA, MD, NC, SC, VA, WV)..... 1.576
4. East North Central (IL, IN, MI, OH, WI)................. 1.5921
5. East South Central (AL, KY, MS, TN)..................... 1.5579
6. West North Central (IA, KS, MN, MO, NE, ND, SD)......... 1.67025
7. West South Central (AR, LA, OK, TX)..................... 1.7172
8. Mountain (AZ, CO, ID, MT, NV, NM, UT, WY)............... 1.7769
9. Pacific (AK, CA, HI, OR, WA)............................ 1.6699
------------------------------------------------------------------------
A hospital seeking to qualify as an RRC should obtain its hospital-
specific CMI value (not transfer-adjusted) from its MAC. Data are
available on the Provider Statistical and Reimbursement (PS&R) System.
In keeping with our policy on discharges, the CMI values are computed
based on all Medicare patient discharges subject to the IPPS MS-DRG-
based payment.
2. Discharges
Section 412.96(c)(2)(i) provides that CMS set forth the national
and regional numbers of discharges criteria in each year's annual
notice of prospective
[[Page 19404]]
payment rates for purposes of determining RRC status. As specified in
section 1886(d)(5)(C)(ii) of the Act, the national standard is set at
5,000 discharges. For FY 2020, we are proposing to update the regional
standards based on discharges for urban hospitals' cost reporting
periods that began during FY 2017 (that is, October 1, 2016 through
September 30, 2017), which are the latest cost report data available at
the time this proposed rule was developed. Therefore, we are proposing
that, in addition to meeting other criteria, a hospital, if it is to
qualify for initial RRC status for cost reporting periods beginning on
or after October 1, 2019, must have, as the number of discharges for
its cost reporting period that began during FY 2017, at least--
5,000 (3,000 for an osteopathic hospital); or
If less, the median number of discharges for urban
hospitals in the census region in which the hospital is located. The
proposed numbers of discharges are set forth in the table below. We
intend to update these numbers in the FY 2020 final rule based on the
latest available cost report data.
------------------------------------------------------------------------
Number of
Region discharges
------------------------------------------------------------------------
1. New England (CT, ME, MA, NH, RI, VT).................... 8,542
2. Middle Atlantic (PA, NJ, NY)............................ 10,154
3. South Atlantic (DE, DC, FL, GA, MD, NC, SC, VA, WV)..... 10,653
4. East North Central (IL, IN, MI, OH, WI)................. 8,379
5. East South Central (AL, KY, MS, TN)..................... 7,627
6. West North Central (IA, KS, MN, MO, NE, ND, SD)......... 7,850
7. West South Central (AR, LA, OK, TX)..................... 5,468
8. Mountain (AZ, CO, ID, MT, NV, NM, UT, WY)............... 8,618
9. Pacific (AK, CA, HI, OR, WA)............................ 8,618
------------------------------------------------------------------------
We note that because the median number of discharges for hospitals
in each census region is greater than the national standard of 5,000
discharges, under this proposed rule, 5,000 discharges is the minimum
criterion for all hospitals, except for osteopathic hospitals for which
the minimum criterion is 3,000 discharges.
D. Proposed Payment Adjustment for Low-Volume Hospitals (Sec. 412.101)
1. Background
Section 1886(d)(12) of the Act provides for an additional payment
to each qualifying low-volume hospital under the IPPS beginning in FY
2005. The additional payment adjustment to a low-volume hospital
provided for under section 1886(d)(12) of the Act is in addition to any
payment calculated under section 1886 of the Act. Therefore, the
additional payment adjustment is based on the per discharge amount paid
to the qualifying hospital under section 1886 of the Act. In other
words, the low-volume hospital payment adjustment is based on total per
discharge payments made under section 1886 of the Act, including
capital, DSH, IME, and outlier payments. For SCHs and MDHs, the low-
volume hospital payment adjustment is based in part on either the
Federal rate or the hospital-specific rate, whichever results in a
greater operating IPPS payment.
As discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41398
through 41399), section 50204 of the Bipartisan Budget Act of 2018
(Pub. L. 115-123) modified the definition of a low-volume hospital and
the methodology for calculating the payment adjustment for low-volume
hospitals for FYs 2019 through 2022. (Section 50204 also extended prior
changes to the definition of a low-volume hospital and the methodology
for calculating the payment adjustment for low-volume hospitals through
FY 2018.) Beginning with FY 2023, the low-volume hospital qualifying
criteria and payment adjustment will revert to the statutory
requirements that were in effect prior to FY 2011. (For additional
information on the low-volume hospital payment adjustment prior to FY
2018, we refer readers to the FY 2017 IPPS/LTCH PPS final rule (81 FR
56941 through 56943). For additional information on the low-volume
hospital payment adjustment for FY 2018, we refer readers to the FY
2018 IPPS notice (CMS-1677-N) that appeared in the Federal Register on
April 26, 2018 (83 FR 18301 through 18308).)
2. Temporary Changes to the Low-Volume Hospital Definition and Payment
Adjustment Methodology for FYs 2019 Through 2022
As discussed earlier, section 50204 of the Bipartisan Budget Act of
2018 further modified the definition of a low-volume hospital and the
methodology for calculating the payment adjustment for low-volume
hospitals for FYs 2019 through 2022. Specifically, the qualifying
criteria for low-volume hospitals under section 1886(d)(12)(C)(i) of
the Act were amended to specify that, for FYs 2019 through 2022, a
subsection (d) hospital qualifies as a low-volume hospital if it is
more than 15 road miles from another subsection (d) hospital and has
less than 3,800 total discharges during the fiscal year. Section
1886(d)(12)(D) of the Act was also amended to provide that, for
discharges occurring in FYs 2019 through 2022, the Secretary shall
determine the applicable percentage increase using a continuous, linear
sliding scale ranging from an additional 25 percent payment adjustment
for low-volume hospitals with 500 or fewer discharges to a zero percent
additional payment for low-volume hospitals with more than 3,800
discharges in the fiscal year. Consistent with the requirements of
section 1886(d)(12)(C)(ii) of the Act, the term ``discharge'' for
purposes of these provisions refers to total discharges, regardless of
payer (that is, Medicare and non-Medicare discharges).
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41399), to implement
this requirement, we specified a continuous, linear sliding scale
formula to determine the low volume hospital payment adjustment for FYs
2019 through 2022 that is similar to the continuous, linear sliding
scale formula used to determine the low-volume hospital payment
adjustment originally established by the Affordable Care Act and
implemented in the regulations at Sec. 412.101(c)(2)(ii) in the FY
2011 IPPS/LTCH PPS final rule (75 FR 50240 through 50241). Consistent
with the statute, we provided that qualifying hospitals with 500 or
fewer total discharges will receive a low-volume hospital payment
adjustment of 25 percent. For qualifying hospitals with fewer than
3,800 discharges but more than 500 discharges, the low-volume payment
adjustment is calculated by subtracting from 25 percent the proportion
of payments associated with the discharges in excess of 500. As such,
for qualifying hospitals with fewer than 3,800 total discharges but
more than 500 total discharges, the low-volume hospital payment
adjustment for FYs 2019 through 2022 is calculated using the following
formula:
Low-Volume Hospital Payment Adjustment = 0.25-[0.25/3300] x (number of
total discharges-500) = (95/330)-(number of total discharges/13,200).
For this purpose, we specified that the ``number of total
discharges'' is determined as total discharges, which includes Medicare
and non-Medicare discharges during the fiscal year, based on the
hospital's most recently submitted cost report. The low-volume hospital
payment adjustment for FYs 2019 through 2022 is set forth in the
regulations at 42 CFR 412.101(c)(3).
[[Page 19405]]
3. Process for Requesting and Obtaining the Low-Volume Hospital Payment
Adjustment
In the FY 2011 IPPS/LTCH PPS final rule (75 FR 50238 through 50275
and 50414) and subsequent rulemaking (for example, the FY 2019 IPPS/
LTCH PPS final rule (83 FR 41399 through 41401), we discussed the
process for requesting and obtaining the low-volume hospital payment
adjustment. Under this previously established process, a hospital makes
a written request for the low-volume payment adjustment under Sec.
412.101 to its MAC. This request must contain sufficient documentation
to establish that the hospital meets the applicable mileage and
discharge criteria. The MAC will determine if the hospital qualifies as
a low-volume hospital by reviewing the data the hospital submits with
its request for low-volume hospital status in addition to other
available data. Under this approach, a hospital will know in advance
whether or not it will receive a payment adjustment under the low-
volume hospital policy. The MAC and CMS may review available data such
as the number of discharges, in addition to the data the hospital
submits with its request for low-volume hospital status, in order to
determine whether or not the hospital meets the qualifying criteria.
(For additional information on our existing process for requesting the
low-volume hospital payment adjustment, we refer readers to the FY 2019
IPPS/LTCH PPS final rule (83 FR 41399 through 41401).)
As explained earlier, for FY 2019 and subsequent fiscal years, the
discharge determination is made based on the hospital's number of total
discharges, that is, Medicare and non-Medicare discharges, as was the
case for FYs 2005 through 2010. Under Sec. 412.101(b)(2)(i) and Sec.
412.101(b)(2)(iii), a hospital's most recently submitted cost report is
used to determine if the hospital meets the discharge criterion to
receive the low-volume payment adjustment in the current year. As
discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41399 and
41400), we use cost report data to determine if a hospital meets the
discharge criterion because this is the best available data source that
includes information on both Medicare and non-Medicare discharges. (For
FYs 2011 through 2018, the most recently available MedPAR data were
used to determine the hospital's Medicare discharges because non-
Medicare discharges were not used to determine if a hospital met the
discharge criterion for those years.) Therefore, a hospital should
refer to its most recently submitted cost report for total discharges
(Medicare and non-Medicare) in order to decide whether or not to apply
for low-volume hospital status for a particular fiscal year.
As also discussed in the FY 2019 IPPS/LTCH PPS final rule, in
addition to the discharge criterion, for FY 2019 and for subsequent
fiscal years, eligibility for the low-volume hospital payment
adjustment is also dependent upon the hospital meeting the applicable
mileage criterion specified in Sec. 412.101(b)(2)(i) or Sec.
412.101(b)(2)(iii) for the fiscal year. Specifically, to meet the
mileage criterion to qualify for the low-volume hospital payment
adjustment for FY 2020, as was the case for FY 2019, a hospital must be
located more than 15 road miles from the nearest subsection (d)
hospital. (We define in Sec. 412.101(a) the term ``road miles'' to
mean ``miles'' as defined in Sec. 412.92(c)(1) (75 FR 50238 through
50275 and 50414).) For establishing that the hospital meets the mileage
criterion, the use of a web-based mapping tool as part of the
documentation is acceptable. The MAC will determine if the information
submitted by the hospital, such as the name and street address of the
nearest hospitals, location on a map, and distance from the hospital
requesting low-volume hospital status, is sufficient to document that
it meets the mileage criterion. If not, the MAC will follow up with the
hospital to obtain additional necessary information to determine
whether or not the hospital meets the applicable mileage criterion.
In accordance with our previously established process, a hospital
must make a written request for low-volume hospital status that is
received by its MAC by September 1 immediately preceding the start of
the Federal fiscal year for which the hospital is applying for low-
volume hospital status in order for the applicable low-volume hospital
payment adjustment to be applied to payments for its discharges for the
fiscal year beginning on or after October 1 immediately following the
request (that is, the start of the Federal fiscal year). For a hospital
whose request for low-volume hospital status is received after
September 1, if the MAC determines the hospital meets the criteria to
qualify as a low-volume hospital, the MAC will apply the applicable
low-volume hospital payment adjustment to determine payment for the
hospital's discharges for the fiscal year, effective prospectively
within 30 days of the date of the MAC's low-volume status
determination.
Consistent with this previously established process, for FY 2020,
we are proposing that a hospital must submit a written request for low-
volume hospital status to its MAC that includes sufficient
documentation to establish that the hospital meets the applicable
mileage and discharge criteria (as described earlier). Consistent with
historical practice, for FY 2020, we are proposing that a hospital's
written request must be received by its MAC no later than September 1,
2019 in order for the low-volume hospital payment adjustment to be
applied to payments for its discharges beginning on or after October 1,
2019. If a hospital's written request for low-volume hospital status
for FY 2020 is received after September 1, 2019, and if the MAC
determines the hospital meets the criteria to qualify as a low-volume
hospital, the MAC would apply the low-volume hospital payment
adjustment to determine the payment for the hospital's FY 2020
discharges, effective prospectively within 30 days of the date of the
MAC's low-volume hospital status determination. We note that this
proposal is consistent with the process for requesting and obtaining
the low-volume hospital payment adjustment for FY 2019 (83 FR 41399
through 41400).
Under this process, a hospital receiving the low-volume hospital
payment adjustment for FY 2019 may continue to receive a low-volume
hospital payment adjustment for FY 2020 without reapplying if it
continues to meet the applicable mileage and discharge criteria (which,
as discussed previously, are the same qualifying criteria that apply
for FY 2019). In this case, a hospital's request can include a
verification statement that it continues to meet the mileage criterion
applicable for FY 2020. (Determination of meeting the discharge
criterion is discussed earlier in this section.) We note that a
hospital must continue to meet the applicable qualifying criteria as a
low-volume hospital (that is, the hospital must meet the applicable
discharge criterion and mileage criterion for the fiscal year) in order
to receive the payment adjustment in that fiscal year; that is, low-
volume hospital status is not based on a ``one-time'' qualification (75
FR 50238 through 50275). Consistent with historical policy, a hospital
must submit its request, including this written verification, for each
fiscal year for which it seeks to receive the low-volume hospital
payment adjustment, and in accordance with the timeline described
earlier.
[[Page 19406]]
4. Proposed Conforming Changes To Codify Certain Changes to the Low-
Volume Hospital Payment Adjustment for FYs 2011 Through 2017 Provided
by Section 429 of the Consolidated Appropriations Act, 2018
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38188 through
38189), for the reasons discussed in that rule, we adopted a parallel
adjustment in the regulations at Sec. 412.101(e) which specifies that,
for discharges occurring in FY 2018 and subsequent years, only the
distance between Indian Health Service (IHS) and Tribal hospitals
(collectively referred to here as ``IHS hospitals'') will be considered
when assessing whether an IHS hospital meets the mileage criterion
under Sec. 412.101(b)(2), and similarly, only the distance between
non-IHS hospitals would be considered when assessing whether a non-IHS
hospital meets the mileage criterion under Sec. 412.101(b)(2). Section
429 of the Consolidated Appropriations Act, 2018, which was enacted on
March 23, 2018, subsequently amended section 1886(d)(12)(C) of the Act
by adding a new clause (iii) specifying that, for purposes of
determining whether an IHS or a non-IHS hospital meets the mileage
criterion under section 1886(d)(12)(C)(i) of the Act with respect to FY
2011 or a succeeding year, the Secretary shall apply the policy
described in the regulations at Sec. 412.101(e) (as in effect on the
date of enactment). In other words, under this statutory change, the
special treatment with respect to the proximities between IHS and non-
IHS hospitals as set forth in Sec. 412.101(e) for discharges occurring
in FY 2018 and subsequent fiscal years is also applicable for purposes
of applying the mileage criterion for the low-volume hospital payment
adjustment for FYs 2011 through 2017. We refer readers to the notice
that appeared in the Federal Register on August 23, 2018 (83 FR 42596
through 42600) for further detail on the process for requesting the
low-volume hospital payment adjustment for any applicable fiscal years
between FY 2011 and FY 2017 under the provisions of section 429 of the
Consolidated Appropriations Act, 2018, including the details on the
limitations under the reopening rules at 42 CFR 405.1885.
In this proposed rule, we are proposing to make conforming changes
to the regulatory text at Sec. 412.101(e) to reflect the changes to
the low-volume hospital payment adjustment policy in accordance with
the amendments made by section 429 of the Consolidated Appropriations
Act, 2018. Specifically, we are proposing to revise Sec. 412.101(e) to
specify that, subject to the reopening rules at 42 CFR 405.1885, a
qualifying hospital may request the application of the policy set forth
in proposed amended Sec. 412.101(e)(1) for FYs 2011 through 2017. As
noted previously, the process for requesting the low-volume hospital
payment adjustment for any applicable fiscal years between FY 2011 and
2017 under the provisions of section 429 of the Consolidated
Appropriations Act, 2018, as well as further discussion on the
limitations under the reopening rules at 42 CFR 405.1885, are described
in the August 23, 2018 Federal Register notice (83 FR 42596 through
425600). We note that proposed amended Sec. 412.101(e) would apply to
discharges occurring in FY 2011 through FY 2017, consistent with the
provisions of section 429 of the Consolidated Appropriations Act, 2018.
To the extent that these proposed revisions could be viewed as
retroactive rulemaking, they would be authorized under section
1871(e)(1)(A)(i) of the Act as the Secretary has determined that these
changes are necessary to comply with the statute as amended by the
Consolidated Appropriations Act, 2018.
E. Indirect Medical Education (IME) Payment Adjustment Factor (Sec.
412.105)
Under the IPPS, an additional payment amount is made to hospitals
with residents in an approved graduate medical education (GME) program
in order to reflect the higher indirect patient care costs of teaching
hospitals relative to nonteaching hospitals. The payment amount is
determined by use of a statutorily specified adjustment factor. The
regulations regarding the calculation of this additional payment, known
as the IME adjustment, are located at Sec. 412.105. We refer readers
to the FY 2012 IPPS/LTCH PPS final rule (76 FR 51680) for a full
discussion of the IME adjustment and IME adjustment factor. Section
1886(d)(5)(B)(ii)(XII) of the Act provides that, for discharges
occurring during FY 2008 and fiscal years thereafter, the IME formula
multiplier is 1.35. Accordingly, for discharges occurring during FY
2020, the formula multiplier is 1.35. We estimate that application of
this formula multiplier for the FY 2020 IME adjustment will result in
an increase in IPPS payment of 5.5 percent for every approximately 10
percent increase in the hospital's resident-to-bed ratio.
F. Proposed Payment Adjustment for Medicare Disproportionate Share
Hospitals (DSHs) for FY 2020 (Sec. 412.106)
1. General Discussion
Section 1886(d)(5)(F) of the Act provides for additional Medicare
payments to subsection (d) hospitals that serve a significantly
disproportionate number of low-income patients. The Act specifies two
methods by which a hospital may qualify for the Medicare
disproportionate share hospital (DSH) adjustment. Under the first
method, hospitals that are located in an urban area and have 100 or
more beds may receive a Medicare DSH payment adjustment if the hospital
can demonstrate that, during its cost reporting period, more than 30
percent of its net inpatient care revenues are derived from State and
local government payments for care furnished to needy patients with low
incomes. This method is commonly referred to as the ``Pickle method.''
The second method for qualifying for the DSH payment adjustment, which
is the most common, is based on a complex statutory formula under which
the DSH payment adjustment is based on the hospital's geographic
designation, the number of beds in the hospital, and the level of the
hospital's disproportionate patient percentage (DPP). A hospital's DPP
is the sum of two fractions: The ``Medicare fraction'' and the
``Medicaid fraction.'' The Medicare fraction (also known as the ``SSI
fraction'' or ``SSI ratio'') is computed by dividing the number of the
hospital's inpatient days that are furnished to patients who were
entitled to both Medicare Part A and Supplemental Security Income (SSI)
benefits by the hospital's total number of patient days furnished to
patients entitled to benefits under Medicare Part A. The Medicaid
fraction is computed by dividing the hospital's number of inpatient
days furnished to patients who, for such days, were eligible for
Medicaid, but were not entitled to benefits under Medicare Part A, by
the hospital's total number of inpatient days in the same period.
Because the DSH payment adjustment is part of the IPPS, the
statutory references to ``days'' in section 1886(d)(5)(F) of the Act
have been interpreted to apply only to hospital acute care inpatient
days. Regulations located at 42 CFR 412.106 govern the Medicare DSH
payment adjustment and specify how the DPP is calculated as well as how
beds and patient days are counted in determining the Medicare DSH
payment adjustment. Under Sec. 412.106(a)(1)(i), the number of beds
for
[[Page 19407]]
the Medicare DSH payment adjustment is determined in accordance with
bed counting rules for the IME adjustment under Sec. 412.105(b).
Section 3133 of the Patient Protection and Affordable Care Act, as
amended by section 10316 of the same Act and section 1104 of the Health
Care and Education Reconciliation Act (Pub. L. 111-152), added a
section 1886(r) to the Act that modifies the methodology for computing
the Medicare DSH payment adjustment. (For purposes of this final rule,
we refer to these provisions collectively as section 3133 of the
Affordable Care Act.) Beginning with discharges in FY 2014, hospitals
that qualify for Medicare DSH payments under section 1886(d)(5)(F) of
the Act receive 25 percent of the amount they previously would have
received under the statutory formula for Medicare DSH payments. This
provision applies equally to hospitals that qualify for DSH payments
under section 1886(d)(5)(F)(i)(I) of the Act and those hospitals that
qualify under the Pickle method under section 1886(d)(5)(F)(i)(II) of
the Act.
The remaining amount, equal to an estimate of 75 percent of what
otherwise would have been paid as Medicare DSH payments, reduced to
reflect changes in the percentage of individuals who are uninsured, is
available to make additional payments to each hospital that qualifies
for Medicare DSH payments and that has uncompensated care. The payments
to each hospital for a fiscal year are based on the hospital's amount
of uncompensated care for a given time period relative to the total
amount of uncompensated care for that same time period reported by all
hospitals that receive Medicare DSH payments for that fiscal year.
As provided by section 3133 of the Affordable Care Act, section
1886(r) of the Act requires that, for FY 2014 and each subsequent
fiscal year, a subsection (d) hospital that would otherwise receive DSH
payments made under section 1886(d)(5)(F) of the Act receives two
separately calculated payments. Specifically, section 1886(r)(1) of the
Act provides that the Secretary shall pay to such subsection (d)
hospital (including a Pickle hospital) 25 percent of the amount the
hospital would have received under section 1886(d)(5)(F) of the Act for
DSH payments, which represents the empirically justified amount for
such payment, as determined by the MedPAC in its March 2007 Report to
Congress. We refer to this payment as the ``empirically justified
Medicare DSH payment.''
In addition to this empirically justified Medicare DSH payment,
section 1886(r)(2) of the Act provides that, for FY 2014 and each
subsequent fiscal year, the Secretary shall pay to such subsection (d)
hospital an additional amount equal to the product of three factors.
The first factor is the difference between the aggregate amount of
payments that would be made to subsection (d) hospitals under section
1886(d)(5)(F) of the Act if subsection (r) did not apply and the
aggregate amount of payments that are made to subsection (d) hospitals
under section 1886(r)(1) of the Act for such fiscal year. Therefore,
this factor amounts to 75 percent of the payments that would otherwise
be made under section 1886(d)(5)(F) of the Act.
The second factor is, for FY 2018 and subsequent fiscal years, 1
minus the percent change in the percent of individuals who are
uninsured, as determined by comparing the percent of individuals who
were uninsured in 2013 (as estimated by the Secretary, based on data
from the Census Bureau or other sources the Secretary determines
appropriate, and certified by the Chief Actuary of CMS), and the
percent of individuals who were uninsured in the most recent period for
which data are available (as so estimated and certified), minus 0.2
percentage point for FYs 2018 and 2019.
The third factor is a percent that, for each subsection (d)
hospital, represents the quotient of the amount of uncompensated care
for such hospital for a period selected by the Secretary (as estimated
by the Secretary, based on appropriate data), including the use of
alternative data where the Secretary determines that alternative data
are available which are a better proxy for the costs of subsection (d)
hospitals for treating the uninsured, and the aggregate amount of
uncompensated care for all subsection (d) hospitals that receive a
payment under section 1886(r) of the Act. Therefore, this third factor
represents a hospital's uncompensated care amount for a given time
period relative to the uncompensated care amount for that same time
period for all hospitals that receive Medicare DSH payments in the
applicable fiscal year, expressed as a percent.
For each hospital, the product of these three factors represents
its additional payment for uncompensated care for the applicable fiscal
year. We refer to the additional payment determined by these factors as
the ``uncompensated care payment.''
Section 1886(r) of the Act applies to FY 2014 and each subsequent
fiscal year. In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50620
through 50647) and the FY 2014 IPPS interim final rule with comment
period (78 FR 61191 through 61197), we set forth our policies for
implementing the required changes to the Medicare DSH payment
methodology made by section 3133 of the Affordable Care Act for FY
2014. In those rules, we noted that, because section 1886(r) of the Act
modifies the payment required under section 1886(d)(5)(F) of the Act,
it affects only the DSH payment under the operating IPPS. It does not
revise or replace the capital IPPS DSH payment provided under the
regulations at 42 CFR part 412, subpart M, which were established
through the exercise of the Secretary's discretion in implementing the
capital IPPS under section 1886(g)(1)(A) of the Act.
Finally, section 1886(r)(3) of the Act provides that there shall be
no administrative or judicial review under section 1869, section 1878,
or otherwise of any estimate of the Secretary for purposes of
determining the factors described in section 1886(r)(2) of the Act or
of any period selected by the Secretary for the purpose of determining
those factors. Therefore, there is no administrative or judicial review
of the estimates developed for purposes of applying the three factors
used to determine uncompensated care payments, or the periods selected
in order to develop such estimates.
2. Eligibility for Empirically Justified Medicare DSH Payments and
Uncompensated Care Payments
As explained earlier, the payment methodology under section 3133 of
the Affordable Care Act applies to ``subsection (d) hospitals'' that
would otherwise receive a DSH payment made under section 1886(d)(5)(F)
of the Act. Therefore, hospitals must receive empirically justified
Medicare DSH payments in a fiscal year in order to receive an
additional Medicare uncompensated care payment for that year.
Specifically, section 1886(r)(2) of the Act states that, in addition to
the payment made to a subsection (d) hospital under section 1886(r)(1)
of the Act, the Secretary shall pay to such subsection (d) hospitals an
additional amount. Because section 1886(r)(1) of the Act refers to
empirically justified Medicare DSH payments, the additional payment
under section 1886(r)(2) of the Act is limited to hospitals that
receive empirically justified Medicare DSH payments in accordance with
section 1886(r)(1) of the Act for the applicable fiscal year.
In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50622) and the FY
2014
[[Page 19408]]
IPPS interim final rule with comment period (78 FR 61193), we provided
that hospitals that are not eligible to receive empirically justified
Medicare DSH payments in a fiscal year will not receive uncompensated
care payments for that year. We also specified that we would make a
determination concerning eligibility for interim uncompensated care
payments based on each hospital's estimated DSH status for the
applicable fiscal year (using the most recent data that are available).
We indicated that our final determination on the hospital's eligibility
for uncompensated care payments will be based on the hospital's actual
DSH status at cost report settlement for that payment year.
In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50622) and in the
rulemaking for subsequent fiscal years, we have specified our policies
for several specific classes of hospitals within the scope of section
1886(r) of the Act. In this proposed rule, we are discussing our
specific policies for FY 2020 with respect to the following hospitals:
Subsection (d) Puerto Rico hospitals that are eligible for
DSH payments also are eligible to receive empirically justified
Medicare DSH payments and uncompensated care payments under the new
payment methodology (78 FR 50623 and 79 FR 50006).
Maryland hospitals are not eligible to receive empirically
justified Medicare DSH payments and uncompensated care payments under
the payment methodology of section 1886(r) of the Act because they are
not paid under the IPPS. As discussed in the FY 2019 IPPS/LTCH PPS
final rule (83 FR 41402 through 41403), CMS and the State have entered
into an agreement to govern payments to Maryland hospitals under a new
payment model, the Maryland Total Cost of Care (TCOC) Model, which
began on January 1, 2019. Under the Maryland TCOC Model, Maryland
hospitals will not be paid under the IPPS in FY 2020, and will be
ineligible to receive empirically justified Medicare DSH payments and
uncompensated care payments under section 1886(r) of the Act.
Sole community hospitals (SCHs) that are paid under their
hospital-specific rate are not eligible for Medicare DSH payments. SCHs
that are paid under the IPPS Federal rate receive interim payments
based on what we estimate and project their DSH status to be prior to
the beginning of the Federal fiscal year (based on the best available
data at that time) subject to settlement through the cost report, and
if they receive interim empirically justified Medicare DSH payments in
a fiscal year, they also will receive interim uncompensated care
payments for that fiscal year on a per discharge basis, subject as well
to settlement through the cost report. Final eligibility determinations
will be made at the end of the cost reporting period at settlement, and
both interim empirically justified Medicare DSH payments and
uncompensated care payments will be adjusted accordingly (78 FR 50624
and 79 FR 50007).
Medicare-dependent, small rural hospitals (MDHs) are paid
based on the IPPS Federal rate or, if higher, the IPPS Federal rate
plus 75 percent of the amount by which the Federal rate is exceeded by
the updated hospital-specific rate from certain specified base years
(76 FR 51684). The IPPS Federal rate that is used in the MDH payment
methodology is the same IPPS Federal rate that is used in the SCH
payment methodology. Section 50205 of the Bipartisan Budget Act of 2018
(Pub. L. 115-123), enacted on February 9, 2018, extended the MDH
program for discharges on or after October 1, 2017, through September
30, 2022. Because MDHs are paid based on the IPPS Federal rate, they
continue to be eligible to receive empirically justified Medicare DSH
payments and uncompensated care payments if their DPP is at least 15
percent, and we apply the same process to determine MDHs' eligibility
for empirically justified Medicare DSH and uncompensated care payments
as we do for all other IPPS hospitals. Due to the extension of the MDH
program, MDHs will continue to be paid based on the IPPS Federal rate
or, if higher, the IPPS Federal rate plus 75 percent of the amount by
which the Federal rate is exceeded by the updated hospital-specific
rate from certain specified base years. Accordingly, we will continue
to make a determination concerning eligibility for interim
uncompensated care payments based on each hospital's estimated DSH
status for the applicable fiscal year (using the most recent data that
are available). Our final determination on the hospital's eligibility
for uncompensated care payments will be based on the hospital's actual
DSH status at cost report settlement for that payment year. In
addition, as we do for all IPPS hospitals, we will calculate a
numerator for Factor 3 for all MDHs, regardless of whether they are
projected to be eligible for Medicare DSH payments during the fiscal
year, but the denominator for Factor 3 will be based on the
uncompensated care data from the hospitals that we have projected to be
eligible for Medicare DSH payments during the fiscal year.
IPPS hospitals that elect to participate in the Bundled
Payments for Care Improvement Advanced Initiative (BPCI Advanced) model
starting October 1, 2018, will continue to be paid under the IPPS and,
therefore, are eligible to receive empirically justified Medicare DSH
payments and uncompensated care payments. For further information
regarding the BPCI Advanced model, we refer readers to the CMS website
at: https://innovation.cms.gov/initiatives/bpci-advanced/.
IPPS hospitals that are participating in the Comprehensive
Care for Joint Replacement Model (80 FR 73300) continue to be paid
under the IPPS and, therefore, are eligible to receive empirically
justified Medicare DSH payments and uncompensated care payments.
Hospitals participating in the Rural Community Hospital
Demonstration Program are not eligible to receive empirically justified
Medicare DSH payments and uncompensated care payments under section
1886(r) of the Act because they are not paid under the IPPS (78 FR
50625 and 79 FR 50008). The Rural Community Hospital Demonstration
Program was originally authorized for a 5-year period by section 410A
of the Medicare Prescription Drug, Improvement, and Modernization Act
of 2003 (MMA) (Pub. L. 108-173), and extended for another 5-year period
by sections 3123 and 10313 of the Affordable Care Act (Pub. L. 114-
255). The period of performance for this 5-year extension period ended
December 31, 2016. Section 15003 of the 21st Century Cures Act (Pub. L.
114-255), enacted December 13, 2016, again amended section 410A of
Public Law 108-173 to require a 10-year extension period (in place of
the 5-year extension required by the Affordable Care Act), therefore
requiring an additional 5-year participation period for the
demonstration program. Section 15003 of Public Law 114-255 also
required a solicitation for applications for additional hospitals to
participate in the demonstration program. At the time of issuance of
this proposed rule, there are 29 hospitals participating in the
demonstration program. Under the payment methodology that applies
during the second 5 years of the extension period under the
demonstration program, participating hospitals do not receive
empirically justified Medicare DSH payments, and they are also excluded
from receiving interim and final uncompensated care payments.
[[Page 19409]]
3. Empirically Justified Medicare DSH Payments
As we have discussed earlier, section 1886(r)(1) of the Act
requires the Secretary to pay 25 percent of the amount of the Medicare
DSH payment that would otherwise be made under section 1886(d)(5)(F) of
the Act to a subsection (d) hospital. Because section 1886(r)(1) of the
Act merely requires the program to pay a designated percentage of these
payments, without revising the criteria governing eligibility for DSH
payments or the underlying payment methodology, we stated in the FY
2014 IPPS/LTCH PPS final rule that we did not believe that it was
necessary to develop any new operational mechanisms for making such
payments. Therefore, in the FY 2014 IPPS/LTCH PPS final rule (78 FR
50626), we implemented this provision by advising MACs to simply adjust
the interim claim payments to the requisite 25 percent of what would
have otherwise been paid. We also made corresponding changes to the
hospital cost report so that these empirically justified Medicare DSH
payments can be settled at the appropriate level at the time of cost
report settlement. We provided more detailed operational instructions
and cost report instructions following issuance of the FY 2014 IPPS/
LTCH PPS final rule that are available on the CMS website at: http://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/2014-Transmittals-Items/R5P240.html.
4. Uncompensated Care Payments
As we discussed earlier, section 1886(r)(2) of the Act provides
that, for each eligible hospital in FY 2014 and subsequent years, the
uncompensated care payment is the product of three factors. These three
factors represent our estimate of 75 percent of the amount of Medicare
DSH payments that would otherwise have been paid, an adjustment to this
amount for the percent change in the national rate of uninsurance
compared to the rate of uninsurance in 2013, and each eligible
hospital's estimated uncompensated care amount relative to the
estimated uncompensated care amount for all eligible hospitals. Below
we discuss the data sources and methodologies for computing each of
these factors, our final policies for FYs 2014 through 2019, and our
proposed policies for FY 2020.
a. Proposed Calculation of Factor 1 for FY 2020
Section 1886(r)(2)(A) of the Act establishes Factor 1 in the
calculation of the uncompensated care payment. Section 1886(r)(2)(A) of
the Act states that this factor is equal to the difference between: (1)
The aggregate amount of payments that would be made to subsection (d)
hospitals under section 1886(d)(5)(F) of the Act if section 1886(r) of
the Act did not apply for such fiscal year (as estimated by the
Secretary); and (2) the aggregate amount of payments that are made to
subsection (d) hospitals under section 1886(r)(1) of the Act for such
fiscal year (as so estimated). Therefore, section 1886(r)(2)(A)(i) of
the Act represents the estimated Medicare DSH payments that would have
been made under section 1886(d)(5)(F) of the Act if section 1886(r) of
the Act did not apply for such fiscal year. Under a prospective payment
system, we would not know the precise aggregate Medicare DSH payment
amount that would be paid for a Federal fiscal year until cost report
settlement for all IPPS hospitals is completed, which occurs several
years after the end of the Federal fiscal year. Therefore, section
1886(r)(2)(A)(i) of the Act provides authority to estimate this amount,
by specifying that, for each fiscal year to which the provision
applies, such amount is to be estimated by the Secretary. Similarly,
section 1886(r)(2)(A)(ii) of the Act represents the estimated
empirically justified Medicare DSH payments to be made in a fiscal
year, as prescribed under section 1886(r)(1) of the Act. Again, section
1886(r)(2)(A)(ii) of the Act provides authority to estimate this
amount.
Therefore, Factor 1 is the difference between our estimates of: (1)
The amount that would have been paid in Medicare DSH payments for the
fiscal year, in the absence of the new payment provision; and (2) the
amount of empirically justified Medicare DSH payments that are made for
the fiscal year, which takes into account the requirement to pay 25
percent of what would have otherwise been paid under section
1886(d)(5)(F) of the Act. In other words, this factor represents our
estimate of 75 percent (100 percent minus 25 percent) of our estimate
of Medicare DSH payments that would otherwise be made, in the absence
of section 1886(r) of the Act, for the fiscal year.
As we did for FY 2019, in this FY 2020 IPPS/LTCH PPS proposed rule,
in order to determine Factor 1 in the uncompensated care payment
formula for FY 2020, we are proposing to continue the policy
established in the FY 2014 IPPS/LTCH PPS final rule (78 FR 50628
through 50630) and in the FY 2014 IPPS interim final rule with comment
period (78 FR 61194) of determining Factor 1 by developing estimates of
both the aggregate amount of Medicare DSH payments that would be made
in the absence of section 1886(r)(1) of the Act and the aggregate
amount of empirically justified Medicare DSH payments to hospitals
under 1886(r)(1) of the Act. These estimates will not be revised or
updated after we know the final Medicare DSH payments for FY 2020.
Therefore, in order to determine the two elements of proposed Factor 1
for FY 2020 (Medicare DSH payments prior to the application of section
1886(r)(1) of the Act, and empirically justified Medicare DSH payments
after application of section 1886(r)(1) of the Act), for this proposed
rule, we used the most recently available projections of Medicare DSH
payments for the fiscal year, as calculated by CMS' Office of the
Actuary using the most recently filed Medicare hospital cost reports
with Medicare DSH payment information and the most recent Medicare DSH
patient percentages and Medicare DSH payment adjustments provided in
the IPPS Impact File. The determination of the amount of DSH payments
is partially based on the Office of the Actuary's Part A benefits
projection model. One of the results of this model is inpatient
hospital spending. Projections of DSH payments require projections for
expected increases in utilization and case-mix. The assumptions that
were used in making these projections and the resulting estimates of
DSH payments for FY 2017 through FY 2020 are discussed in the table
titled ``Factors Applied for FY 2017 through FY 2020 to Estimate
Medicare DSH Expenditures Using FY 2016 Baseline.''
For purposes of calculating Factor 1 and modeling the impact of
this FY 2020 IPPS/LTCH PPS proposed rule, we used the Office of the
Actuary's December 2018 Medicare DSH estimates, which were based on
data from the September 2018 update of the Medicare Hospital Cost
Report Information System (HCRIS) and the FY 2019 IPPS/LTCH PPS final
rule IPPS Impact File, published in conjunction with the publication of
the FY 2019 IPPS/LTCH PPS final rule. Because SCHs that are projected
to be paid under their hospital-specific rate are excluded from the
application of section 1886(r) of the Act, these hospitals also were
excluded from the December 2018 Medicare DSH estimates. Furthermore,
because section 1886(r) of the Act specifies that the uncompensated
care payment is in addition to the empirically justified Medicare DSH
payment (25 percent of DSH payments
[[Page 19410]]
that would be made without regard to section 1886(r) of the Act),
Maryland hospitals, which are not eligible to receive DSH payments,
were also excluded from the Office of the Actuary's December 2018
Medicare DSH estimates. The 29 hospitals that are participating in the
Rural Community Hospital Demonstration Program were also excluded from
these estimates because, under the payment methodology that applies
during the second 5 years of the extension period, these hospitals are
not eligible to receive empirically justified Medicare DSH payments or
interim and final uncompensated care payments.
For this proposed rule, using the data sources discussed above, the
Office of the Actuary's December 2018 estimate for Medicare DSH
payments for FY 2020, without regard to the application of section
1886(r)(1) of the Act, is approximately $16.857 billion. Therefore,
also based on the December 2018 estimate, the estimate of empirically
justified Medicare DSH payments for FY 2020, with the application of
section 1886(r)(1) of the Act, is approximately $4.214 billion (or 25
percent of the total amount of estimated Medicare DSH payments for FY
2020). Under Sec. 412.l06(g)(1)(i) of the regulations, Factor 1 is the
difference between these two estimates of the Office of the Actuary.
Therefore, in this proposed rule, we are proposing that Factor 1 for FY
2020 would be $12,643,011,209.74, which is equal to 75 percent of the
total amount of estimated Medicare DSH payments for FY 2020
($16,857,348,279.65 minus $4,214,337,069.91).
The Factor 1 estimates for proposed rules are generally consistent
with the economic assumptions and actuarial analysis used to develop
the President's Budget estimates under current law, and the Factor 1
estimates for the final rule are generally consistent with those used
for the Midsession Review of the President's Budget. As we have in the
past, for additional information on the development of the President's
Budget, we refer readers to the Office of Management and Budget website
at: https://www.whitehouse.gov/omb/budget. We recognize that our
reliance on the economic assumptions and actuarial analysis used to
develop the President's Budget in estimating Factor 1 has an impact on
stakeholders who wish to replicate the Factor 1 calculation, such as
modelling the relevant Medicare Part A portion of the budget, but we
believe commenters are able to meaningfully comment on our proposed
estimate of Factor 1 without replicating the President's Budget.
For a general overview of the principal steps involved in
projecting future inpatient costs and utilization, we refer readers to
the ``2018 Annual Report of the Boards of Trustees of the Federal
Hospital Insurance and Federal Supplementary Medical Insurance Trust
Funds'' available on the CMS website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/ReportsTrust
Funds/index.html?redirect=/reportstrustfunds/ under ``Downloads.'' We
note that the annual reports of the Medicare Boards of Trustees to
Congress represent the Federal Government's official evaluation of the
financial status of the Medicare Program. The actuarial projections
contained in these reports are based on numerous assumptions regarding
future trends in program enrollment, utilization and costs of health
care services covered by Medicare, as well as other factors affecting
program expenditures. In addition, although the methods used to
estimate future costs based on these assumptions are complex, they are
subject to periodic review by independent experts to ensure their
validity and reasonableness.
We also refer readers to the Actuarial Report on the Financial
Outlook for Medicaid for a discussion of general issues regarding
Medicaid projections.
In this proposed rule, we include information regarding the data
sources, methods, and assumptions employed by the actuaries in
determining the OACT's estimate of Factor 1. In summary, we indicate
the historical HCRIS data update OACT used to identify Medicare DSH
payments, we explain that the most recent Medicare DSH payment
adjustments provided in the IPPS Impact File were used, and we provide
the components of all the update factors that were applied to the
historical data to estimate the Medicare DSH payments for the upcoming
fiscal year, along with the associated rationale and assumptions. This
discussion also includes a description of the ``Other'' and
``Discharges'' assumptions, and also provides additional information
regarding how we address the Medicaid and CHIP expansion.
The Office of the Actuary's estimates for FY 2020 for this proposed
rule began with a baseline of $13.981 billion in Medicare DSH
expenditures for FY 2016. The following table shows the factors applied
to update this baseline through the current estimate for FY 2020:
Factors Applied for FY 2017 Through FY 2020 To Estimate Medicare DSH Expenditures Using FY 2016 Baseline
--------------------------------------------------------------------------------------------------------------------------------------------------------
Estimated DSH
FY Update Discharges Case-mix Other Total payment (in
billions) *
--------------------------------------------------------------------------------------------------------------------------------------------------------
2017.................................................... 1.0015 0.9986 1.004 1.0751 1.0795 15.093
2018.................................................... 1.018088 0.9819 1.018 1.0345 1.0528 15.889
2019.................................................... 1.0185 0.9791 1.005 1.02206 1.0243 16.275
2020.................................................... 1.032 1.0055 1.005 0.9932 1.0358 16.857
--------------------------------------------------------------------------------------------------------------------------------------------------------
* Rounded.
In this table, the discharges column shows the increase in the
number of Medicare fee-for-service (FFS) inpatient hospital discharges.
The figures for FY 2017 are based on Medicare claims data that have
been adjusted by a completion factor. The discharge figure for FY 2018
is based on preliminary data for 2018. The discharge figures for FY
2019 and FY 2020 are assumptions based on recent trends recovering back
to the long-term trend and assumptions related to how many
beneficiaries will be enrolled in Medicare Advantage (MA) plans. The
case-mix column shows the increase in case-mix for IPPS hospitals. The
case-mix figures for FY 2017 and FY 2018 are based on actual data
adjusted by a completion factor. The FY 2019 and FY 2020 increases are
estimates based on the recommendation of the 2010-2011 Medicare
Technical Review Panel. The ``Other'' column shows the increase in
other factors that contribute to the Medicare DSH estimates. These
factors include the difference between the total inpatient
[[Page 19411]]
hospital discharges and the IPPS discharges, and various adjustments to
the payment rates that have been included over the years but are not
reflected in the other columns (such as the change in rates for the 2-
midnight stay policy). In addition, the ``Other'' column includes a
factor for the Medicaid expansion due to the Affordable Care Act. The
factor for Medicaid expansion was developed using public information
and statements for each State regarding its intent to implement the
expansion. Based on this information, it is assumed that 50 percent of
all individuals who were potentially newly eligible Medicaid enrollees
in 2016 resided in States that had elected to expand Medicaid
eligibility and, for 2017 and thereafter, that 55 percent of such
individuals would reside in expansion States. In the future, these
assumptions may change based on actual participation by States. For a
discussion of general issues regarding Medicaid projections, we refer
readers to the 2017 Actuarial Report on the Financial Outlook for
Medicaid, which is available on the CMS website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/ActuarialStudies/Downloads/MedicaidReport2017.pdf. We note that, in
developing their estimates of the effect of Medicaid expansion on
Medicare DSH expenditures, our actuaries have assumed that the new
Medicaid enrollees are healthier than the average Medicaid recipient
and, therefore, use fewer hospital services. Specifically, based on
data from the President's Budget, the OACT assumed per capita spending
for Medicaid beneficiaries who enrolled due to the expansion to be 50
percent of the average per capita expenditures for a pre-expansion
Medicaid beneficiary due to the better health of these beneficiaries.
This assumption is consistent with recent internal estimates of
Medicaid per capita spending pre-expansion and post-expansion.
The table below shows the factors that are included in the
``Update'' column of the above table:
----------------------------------------------------------------------------------------------------------------
Affordable
Market basket Care Act Multifactor Documentation Total update
FY percentage payment productivity and coding percentage
reductions adjustment
----------------------------------------------------------------------------------------------------------------
2017............................ 2.7 -0.75 -0.3 -1.5 0.15
2018............................ 2.7 -0.75 -0.6 0.4588 1.8088
2019............................ 2.9 -0.75 -0.8 0.5 1.885
2020............................ 3.2 0 -0.5 0.5 3.2
----------------------------------------------------------------------------------------------------------------
Note: All numbers are based on the FY 2020 President's Budget projections, except for the FY 2020 percentages,
which are based on the most recent forecast. We refer readers to section IV.B. of the preamble of this
proposed rule for a complete discussion of the proposed changes in the inpatient hospital update for FY 2020.
b. Calculation of Proposed Factor 2 for FY 2020
(1) Background
Section 1886(r)(2)(B) of the Act establishes Factor 2 in the
calculation of the uncompensated care payment. Section
1886(r)(2)(B)(ii) of the Act provides that, for FY 2018 and subsequent
fiscal years, the second factor is 1 minus the percent change in the
percent of individuals who are uninsured, as determined by comparing
the percent of individuals who were uninsured in 2013 (as estimated by
the Secretary, based on data from the Census Bureau or other sources
the Secretary determines appropriate, and certified by the Chief
Actuary of CMS) and the percent of individuals who were uninsured in
the most recent period for which data are available (as so estimated
and certified), minus 0.2 percentage point for FYs 2018 and 2019. In FY
2020 and subsequent fiscal years, there is no longer a reduction. We
note that, unlike section 1886(r)(2)(B)(i) of the Act, which governed
the calculation of Factor 2 for FYs 2014, 2015, 2016, and 2017, section
1886(r)(2)(B)(ii) of the Act permits the use of a data source other
than the CBO estimates to determine the percent change in the rate of
uninsurance beginning in FY 2018. In addition, for FY 2018 and
subsequent years, the statute does not require that the estimate of the
percent of individuals who are uninsured be limited to individuals who
are under 65 years of age.
As we discussed in the FY 2018 IPPS/LTCH PPS final rule (82 FR
38197), in our analysis of a potential data source for the rate of
uninsurance for purposes of computing Factor 2 in FY 2018, we
considered the following: (a) The extent to which the source accounted
for the full U.S. population; (b) the extent to which the source
comprehensively accounted for both public and private health insurance
coverage in deriving its estimates of the number of uninsured; (c) the
extent to which the source utilized data from the Census Bureau; (d)
the timeliness of the estimates; (e) the continuity of the estimates
over time; (f) the accuracy of the estimates; and (g) the availability
of projections (including the availability of projections using an
established estimation methodology that would allow for calculation of
the rate of uninsurance for the applicable Federal fiscal year). As we
explained in the FY 2018 IPPS/LTCH PPS final rule, these considerations
are consistent with the statutory requirement that this estimate be
based on data from the Census Bureau or other sources the Secretary
determines appropriate and help to ensure the data source will provide
reasonable estimates for the rate of uninsurance that are available in
conjunction with the IPPS rulemaking cycle. We are proposing to use the
same methodology as was used in FY 2018 and FY 2019 to determine Factor
2 for FY 2020.
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38197 and 38198), we
explained that we determined the source that, on balance, best meets
all of these considerations is the uninsured estimates produced by CMS'
Office of the Actuary (OACT) as part of the development of the National
Health Expenditure Accounts (NHEA). The NHEA represents the
government's official estimates of economic activity (spending) within
the health sector. The information contained in the NHEA has been used
to study numerous topics related to the health care sector, including,
but not limited to, changes in the amount and cost of health services
purchased and the payers or programs that provide or purchase these
services; the economic causal factors at work in the health sector; the
impact of policy changes, including major health reform; and
comparisons to other countries' health spending. Of relevance to the
determination of Factor 2 is that the comprehensive and integrated
structure of the NHEA creates an ideal tool for evaluating changes to
the health care system, such as the mix of the insured and uninsured
because this mix is
[[Page 19412]]
integral to the well-established NHEA methodology. Below we describe
some aspects of the methodology used to develop the NHEA that were
particularly relevant in estimating the percent change in the rate of
uninsurance for FY 2018 and FY 2019 that we believe continue to be
relevant in developing the estimate for FY 2020. A full description of
the methodology used to develop the NHEA is available on the CMS
website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/Downloads/DSM-15.pdf.
The NHEA estimates of U.S. population reflect the Census Bureau's
definition of the resident-based population, which includes all people
who usually reside in the 50 States or the District of Columbia, but
excludes residents living in Puerto Rico and areas under U.S.
sovereignty, members of the U.S. Armed Forces overseas, and U.S.
citizens whose usual place of residence is outside of the United
States, plus a small (typically less than 0.2 percent of population)
adjustment to reflect Census undercounts. In past years, the estimates
for Factor 2 were made using the CBO's uninsured population estimates
for the under 65 population. For FY 2018 and subsequent years, the
statute does not restrict the estimate to the measurement of the
percent of individuals under the age of 65 who are uninsured.
Accordingly, as we explained in the FY 2018 IPPS/LTCH PPS proposed and
final rules, we believe it is appropriate to use an estimate that
reflects the rate of uninsurance in the United States across all age
groups. In addition, we continue to believe that a resident-based
population estimate more fully reflects the levels of uninsurance in
the United States that influence uncompensated care for hospitals than
an estimate that reflects only legal residents. The NHEA estimates of
uninsurance are for the total U.S. population (all ages) and not by
specific age cohort, such as the population under the age of 65.
The NHEA includes comprehensive enrollment estimates for total
private health insurance (PHI) (including direct and employer-sponsored
plans), Medicare, Medicaid, the Children's Health Insurance Program
(CHIP), and other public programs, and estimates of the number of
individuals who are uninsured. Estimates of total PHI enrollment are
available for 1960 through 2017, estimates of Medicaid, Medicare, and
CHIP enrollment are available for the length of the respective
programs, and all other estimates (including the more detailed
estimates of direct-purchased and employer-sponsored insurance) are
available for 1987 through 2017. The NHEA data are publicly available
on the CMS website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealth ExpendData/
index.html.
In order to compute Factor 2, the first metric that is needed is
the proportion of the total U.S. population that was uninsured in 2013.
In developing the estimates for the NHEA, OACT's methodology included
using the number of uninsured individuals for 1987 through 2009 based
on the enhanced Current Population Survey (CPS) from the State Health
Access Data Assistance Center (SHADAC). The CPS, sponsored jointly by
the U.S. Census Bureau and the U.S. Bureau of Labor Statistics (BLS),
is the primary source of labor force statistics for the population of
the United States. (We refer readers to the website at: http://www.census.gov/programs-surveys/cps.html.) The enhanced CPS, available
from SHADAC (available at: http://datacenter.shadac.org) accounts for
changes in the CPS methodology over time. OACT further adjusts the
enhanced CPS for an estimated undercount of Medicaid enrollees (a
population that is often not fully captured in surveys that include
Medicaid enrollees due to a perceived stigma associated with being
enrolled in the Medicaid program or confusion about the source of their
health insurance).
To estimate the number of uninsured individuals for 2010 through
2014, the OACT extrapolates from the 2009 CPS data using data from the
National Health Interview Survey (NHIS). The NHIS is one of the major
data collection programs of the National Center for Health Statistics
(NCHS), which is part of the Centers for Disease Control and Prevention
(CDC). The U.S. Census Bureau is the data collection agent for the
NHIS. The NHIS results have been instrumental over the years in
providing data to track health status, health care access, and progress
toward achieving national health objectives. For further information
regarding the NHIS, we refer readers to the CDC website at: https://www.cdc.gov/nchs/nhis/index.htm.
The next metrics needed to compute Factor 2 are projections of the
rate of uninsurance in both calendar years 2019 and 2020. On an annual
basis, OACT projects enrollment and spending trends for the coming 10-
year period. Those projections (currently for years 2018 through 2027)
use the latest NHEA historical data, which presently run through 2017.
The NHEA projection methodology accounts for expected changes in
enrollment across all of the categories of insurance coverage
previously listed. The sources for projected growth rates in enrollment
for Medicare, Medicaid, and CHIP include the latest Medicare Trustees
Report, the Medicaid Actuarial Report, or other updated estimates as
produced by OACT. Projected rates of growth in enrollment for private
health insurance and the uninsured are based largely on OACT's
econometric models, which rely on the set of macroeconomic assumptions
underlying the latest Medicare Trustees Report. Greater detail can be
found in OACT's report titled ``Projections of National Health
Expenditure: Methodology and Model Specification,'' which is available
on the CMS website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/Downloads/ProjectionsMethodology.pdf.
The use of data from the NHEA to estimate the rate of uninsurance
is consistent with the statute and meets the criteria we have
identified for determining the appropriate data source. Section
1886(r)(2)(B)(ii) of the Act instructs the Secretary to estimate the
rate of uninsurance for purposes of Factor 2 based on data from the
Census Bureau or other sources the Secretary determines appropriate.
The NHEA utilizes data from the Census Bureau; the estimates are
available in time for the IPPS rulemaking cycle; the estimates are
produced by OACT on an annual basis and are expected to continue to be
produced for the foreseeable future; and projections are available for
calendar year time periods that span the upcoming fiscal year.
Timeliness and continuity are important considerations because of our
need to be able to update this estimate annually. Accuracy is also a
very important consideration and, all things being equal, we would
choose the most accurate data source that sufficiently meets our other
criteria.
(2) Proposed Factor 2 for FY 2020
Using these data sources and the methodologies described above, the
OACT estimates that the uninsured rate for the historical, baseline
year of 2013 was 14 percent and for CYs 2019 and 2020 is 9.4 percent
and 9.3 percent, respectively.\394\ As required by section
1886(r)(2)(B)(ii) of the Act, the Chief Actuary of CMS has certified
these estimates.
---------------------------------------------------------------------------
\394\ Certification of Rates of Uninsured. March 28, 2019.
Available at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInPatientPPS/dsh.html.
---------------------------------------------------------------------------
[[Page 19413]]
As with the CBO estimates on which we based Factor 2 in prior
fiscal years, the NHEA estimates are for a calendar year. In the
rulemaking for FY 2014, many commenters noted that the uncompensated
care payments are made for the fiscal year and not on a calendar year
basis and requested that CMS normalize the CBO estimate to reflect a
fiscal year basis. Specifically, commenters requested that CMS
calculate a weighted average of the CBO estimate for October through
December 2013 and the CBO estimate for January through September 2014
when determining Factor 2 for FY 2014. We agreed with the commenters
that normalizing the estimate to cover FY 2014 rather than CY 2014
would more accurately reflect the rate of uninsurance that hospitals
would experience during the FY 2014 payment year. Accordingly, we
estimated the rate of uninsurance for FY 2014 by calculating a weighted
average of the CBO estimates for CY 2013 and CY 2014 (78 FR 50633). We
have continued this weighted average approach in each fiscal year since
FY 2014.
We continue to believe that, in order to estimate the rate of
uninsurance during a fiscal year more accurately, Factor 2 should
reflect the estimated rate of uninsurance that hospitals will
experience during the fiscal year, rather than the rate of uninsurance
during only one of the calendar years that the fiscal year spans.
Accordingly, we are proposing to continue to apply the weighted average
approach used in past fiscal years in order to estimate the rate of
uninsurance for FY 2020. The OACT has certified this estimate of the
fiscal year rate of uninsurance to be reasonable and appropriate for
purposes of section 1886(r)(2)(B)(ii) of the Act.
The calculation of the proposed Factor 2 for FY 2020 using a
weighted average of the OACT's projections for CY 2019 and CY 2020 is
as follows:
Percent of individuals without insurance for CY 2013: 14
percent.
Percent of individuals without insurance for CY 2019: 9.4
percent.
Percent of individuals without insurance for CY 2020: 9.4
percent.
Percent of individuals without insurance for FY 2020 (0.25
times 0.094) + (0.75 times 0.094): 9.4 percent 1 - [bond]((0.094 -
0.14)/0.14)[bond] = 1 - 0.3286 = 0.6714 (67.14 percent).
For FY 2020 and subsequent fiscal years, section 1886(r)(2)(B)(ii)
of the Act no longer includes any reduction to the above calculation.
Therefore, we are proposing that Factor 2 for FY 2020 will be 67.14
percent.
The proposed FY 2020 uncompensated care amount is
$12,643,011,209.74 x 0.6714 = $8,488,517,726.22.
------------------------------------------------------------------------
------------------------------------------------------------------------
Proposed FY 2020 Uncompensated Care Amount........ $8,488,517,726.22
------------------------------------------------------------------------
We are inviting public comments on our proposed methodology for
calculating Factor 2 for FY 2020.
c. Calculation of Proposed Factor 3 for FY 2020
(1) General Background
Section 1886(r)(2)(C) of the Act defines Factor 3 in the
calculation of the uncompensated care payment. As we have discussed
earlier, section 1886(r)(2)(C) of the Act states that Factor 3 is equal
to the percent, for each subsection (d) hospital, that represents the
quotient of: (1) The amount of uncompensated care for such hospital for
a period selected by the Secretary (as estimated by the Secretary,
based on appropriate data (including, in the case where the Secretary
determines alternative data are available that are a better proxy for
the costs of subsection (d) hospitals for treating the uninsured, the
use of such alternative data)); and (2) the aggregate amount of
uncompensated care for all subsection (d) hospitals that receive a
payment under section 1886(r) of the Act for such period (as so
estimated, based on such data).
Therefore, Factor 3 is a hospital-specific value that expresses the
proportion of the estimated uncompensated care amount for each
subsection (d) hospital and each subsection (d) Puerto Rico hospital
with the potential to receive Medicare DSH payments relative to the
estimated uncompensated care amount for all hospitals estimated to
receive Medicare DSH payments in the fiscal year for which the
uncompensated care payment is to be made. Factor 3 is applied to the
product of Factor 1 and Factor 2 to determine the amount of the
uncompensated care payment that each eligible hospital will receive for
FY 2014 and subsequent fiscal years. In order to implement the
statutory requirements for this factor of the uncompensated care
payment formula, it was necessary to determine: (1) The definition of
uncompensated care or, in other words, the specific items that are to
be included in the numerator (that is, the estimated uncompensated care
amount for an individual hospital) and the denominator (that is, the
estimated uncompensated care amount for all hospitals estimated to
receive Medicare DSH payments in the applicable fiscal year); (2) the
data source(s) for the estimated uncompensated care amount; and (3) the
timing and manner of computing the quotient for each hospital estimated
to receive Medicare DSH payments. The statute instructs the Secretary
to estimate the amounts of uncompensated care for a period based on
appropriate data. In addition, we note that the statute permits the
Secretary to use alternative data in the case where the Secretary
determines that such alternative data are available that are a better
proxy for the costs of subsection (d) hospitals for treating
individuals who are uninsured.
In the course of considering how to determine Factor 3 during the
rulemaking process for FY 2014, the first year this provision was in
effect, we considered defining the amount of uncompensated care for a
hospital as the uncompensated care costs of that hospital and
determined that Worksheet S-10 of the Medicare cost report potentially
provides the most complete data regarding uncompensated care costs for
Medicare hospitals. However, because of concerns regarding variations
in the data reported on Worksheet S-10 and the completeness of these
data, we did not use Worksheet S-10 data to determine Factor 3 for FY
2014, or for FYs 2015, 2016, or 2017. Instead, we believed that the
utilization of insured low-income patients, as measured by patient
days, would be a better proxy for the costs of hospitals in treating
the uninsured and therefore appropriate to use in calculating Factor 3
for these years. Of particular importance in our decision making was
the relative newness of Worksheet S-10, which went into effect on May
1, 2010. At the time of the rulemaking for FY 2014, the most recent
available cost reports would have been from FYs 2010 and 2011, which
were submitted on or after May 1, 2010, when the new Worksheet S-10
went into effect. We believed that concerns about the standardization
and completeness of the Worksheet S-10 data could be more acute for
data collected in the first year of the Worksheet's use (78 FR 50635).
In addition, we believed that it would be most appropriate to use data
elements that have been historically publicly available, subject to
audit, and used for payment purposes (or that the public understands
will be used for payment purposes) to determine the amount of
uncompensated care for purposes of Factor 3 (78 FR 50635). At the time
we issued the FY 2014 IPPS/LTCH PPS final rule, we did not believe that
the available data regarding uncompensated care from Worksheet S-10 met
these criteria and, therefore, we believed they were not reliable
enough to use for
[[Page 19414]]
determining FY 2014 uncompensated care payments. For FYs 2015, 2016,
and 2017, the cost reports used for calculating uncompensated care
payments (that is, FYs 2011, 2012, and 2013) were also submitted prior
to the time that hospitals were on notice that Worksheet S-10 could be
the data source for calculating uncompensated care payments. Therefore,
we believed it was also appropriate to use proxy data to calculate
Factor 3 for these years. We indicated our belief that Worksheet S-10
could ultimately serve as an appropriate source of more direct data
regarding uncompensated care costs for purposes of determining Factor 3
once hospitals were submitting more accurate and consistent data
through this reporting mechanism.
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38202), we stated
that we could no longer conclude that alternative data to the Worksheet
S-10 are available for FY 2014 that are a better proxy for the costs of
subsection (d) hospitals for treating individuals who are uninsured.
Hospitals were on notice as of FY 2014 that Worksheet S-10 could
eventually become the data source for CMS to calculate uncompensated
care payments. Furthermore, hospitals' cost reports from FY 2014 had
been publicly available for some time, and CMS had analyses of
Worksheet S-10, conducted both internally and by stakeholders,
demonstrating that Worksheet S-10 accuracy had improved over time.
Analyses performed by MedPAC had already shown that the correlation
between audited uncompensated care data from 2009 and the data from the
FY 2011 Worksheet S-10 was over 0.80, as compared to a correlation of
approximately 0.50 between the audited uncompensated care data and 2011
Medicare SSI and Medicaid days. Based on this analysis, MedPAC
concluded that use of Worksheet S-10 data was already better than using
Medicare SSI and Medicaid days as a proxy for uncompensated care costs,
and that the data on Worksheet S-10 would improve over time as the data
are actually used to make payments (81 FR 25090). In addition, a 2007
MedPAC analysis of data from the Government Accountability Office (GAO)
and the American Hospital Association (AHA) had suggested that Medicaid
days and low-income Medicare days are not an accurate proxy for
uncompensated care costs (80 FR 49525).
Subsequent analyses from Dobson/DaVanzo, originally commissioned by
CMS for the FY 2014 rulemaking and updated in later years, compared
Worksheet S-10 and IRS Form 990 data and assessed the correlation in
Factor 3s derived from each of the data sources. Our analyses on
balance led us to believe that we had reached a tipping point in FY
2018 with respect to the use of the Worksheet S-10 data. We refer
readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 38201 through
38203) for a complete discussion of these analyses.
We found further evidence for this tipping point when we examined
changes to the FY 2014 Worksheet S-10 data submitted by hospitals
following the publication of the FY 2017 IPPS/LTCH PPS final rule. In
the FY 2017 IPPS/LTCH PPS final rule, as part of our ongoing quality
control and data improvement measures for the Worksheet S-10, we
referred readers to Change Request 9648, Transmittal 1681, titled ``The
Supplemental Security Income (SSI)/Medicare Beneficiary Data for Fiscal
Year 2014 for Inpatient Prospective Payment System (IPPS) Hospitals,
Inpatient Rehabilitation Facilities (IRFs), and Long Term Care
Hospitals (LTCHs),'' issued on July 15, 2016 (available at: https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/Downloads/R1681OTN.pdf). In this transmittal, as part of the process for ensuring
complete submission of Worksheet S-10 by all eligible DSH hospitals, we
instructed MACs to accept amended Worksheets S-10 for FY 2014 cost
reports submitted by hospitals (or initial submissions of Worksheet S-
10 if none had been submitted previously) and to upload them to the
Health Care Provider Cost Report Information System (HCRIS) in a timely
manner. The transmittal stated that, for revisions to be considered,
hospitals were required to submit their amended FY 2014 cost report
containing the revised Worksheet S-10 (or a completed Worksheet S-10 if
no data were included on the previously submitted cost report) to the
MAC no later than September 30, 2016. For the FY 2018 IPPS/LTCH PPS
proposed rule (82 FR 19949 through 19950), we examined hospitals' FY
2014 cost reports to see if the Worksheet S-10 data on those cost
reports had changed as a result of the opportunity for hospitals to
submit revised Worksheet S-10 data for FY 2014. Specifically, we
compared hospitals' FY 2014 Worksheet S-10 data as they existed in the
first quarter of CY 2016 with data from the fourth quarter of CY 2016.
We found that the FY 2014 Worksheet S-10 data had changed over that
time period for approximately one quarter of hospitals that receive
uncompensated care payments. The fact that the Worksheet S-10 data
changed for such a significant number of hospitals following a review
of the cost report data they originally submitted and that the revised
Worksheet S-10 information is available to be used in determining
uncompensated care costs contributed to our belief that we could no
longer conclude that alternative data are available that are a better
proxy than the Worksheet S-10 data for the costs of subsection (d)
hospitals for treating individuals who are uninsured.
We also recognized commenters' concerns that, in using Medicaid
days as part of the proxy for uncompensated care, it would be possible
for hospitals in States that choose to expand Medicaid to receive
higher uncompensated care payments because they may have more Medicaid
patient days than hospitals in a State that does not choose to expand
Medicaid. Because the earliest Medicaid expansions under the Affordable
Care Act began in 2014, the 2011, 2012, and 2013 Medicaid days used to
calculate uncompensated care payments in FYs 2015, 2016, and 2017 are
the latest available data on Medicaid utilization that do not reflect
the effects of these Medicaid expansions. Accordingly, if we had used
only low-income insured days to estimate uncompensated care in FY 2018,
we would have needed to hold the time period of these data constant and
use data on Medicaid days from 2011, 2012, and 2013 in order to avoid
the risk of any redistributive effects arising from the decision to
expand Medicaid in certain States. As a result, we would have been
using older data that may provide a less accurate proxy for the level
of uncompensated care being furnished by hospitals, contributing to our
growing concerns regarding the continued use of low-income insured days
as a proxy for uncompensated care costs in FY 2018.
In summary, as we stated in the FY 2018 IPPS/LTCH PPS final rule
(82 FR 38203), when weighing the new information regarding the
correlation between the Worksheet S-10 data and IRS 990 data that
became available to us after the FY 2017 rulemaking in conjunction with
the information regarding Worksheet S-10 data and the low-income days
proxy that we analyzed as part of our consideration of this issue in
prior rulemaking, we determined that we could no longer conclude that
alternative data to the Worksheet S-10 are available for FY 2014 that
are a better proxy for the costs of subsection (d) hospitals for
treating individuals who are uninsured. We also stated that we believe
that continued use of Worksheet S-10 will improve the
[[Page 19415]]
accuracy and consistency of the reported data, especially in light of
CMS' concerted efforts to allow hospitals to review and resubmit their
Worksheet S-10 data for past years and the use of trims for potentially
aberrant data (82 FR 38207, 38217, and 38218). We also committed to
continue to work with stakeholders to address their concerns regarding
the accuracy of the reporting of uncompensated care costs through
provider education and refinement of the instructions to Worksheet S-
10.
For FY 2019, as discussed in the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41413), we continued to monitor the reporting of Worksheet S-10
data in anticipation of using Worksheet S-10 data from hospitals' FY
2014 and FY 2015 cost reports in the calculation of Factor 3. We
acknowledged the concerns that had been raised regarding the
instructions for Worksheet S-10. In particular, commenters had
expressed concerns that the lack of clear and concise line-level
instructions prevented accurate and consistent data from being reported
on Worksheet S-10. We noted that, in November 2016, CMS issued
Transmittal 10, which clarified and revised the instructions for the
Worksheet S-10, including the instructions regarding the reporting of
charity care charges. Transmittal 10 is available for download on the
CMS website at: https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/Downloads/R10P240.pdf. In Transmittal 10, we clarified
that hospitals may include discounts given to uninsured patients who
meet the hospital's charity care criteria in effect for that cost
reporting period. This clarification applied to cost reporting periods
beginning prior to October 1, 2016, as well as cost reporting periods
beginning on or after October 1, 2016. As a result, nothing prohibits a
hospital from considering a patient's insurance status as a criterion
in its charity care policy. A hospital determines its own financial
criteria as part of its charity care policy. The instructions for the
Worksheet S-10 set forth that hospitals may include discounts given to
uninsured patients, including patients with coverage from an entity
that does not have a contractual relationship with the provider, who
meet the hospital's charity care criteria in effect for that cost
reporting period. In addition, we revised the instructions for the
Worksheet S-10 for cost reporting periods beginning on or after October
1, 2016, to provide that charity care charges must be determined in
accordance with the hospital's charity care criteria/policy and written
off in the cost reporting period, regardless of the date of service.
During the FY 2018 rulemaking, commenters pointed out that, in the
FY 2017 IPPS/LTCH PPS final rule (81 FR 56963), CMS agreed to institute
certain additional quality control and data improvement measures prior
to moving forward with incorporating Worksheet S-10 data into the
calculation of Factor 3. However, the commenters indicated that, aside
from a brief window in 2016 for hospitals to submit corrected data on
their FY 2014 Worksheet S-10 by September 30, 2016, and the issuance of
revised instructions (Transmittal 10) in November 2016 that are
applicable to cost reports beginning on or after October 1, 2016, CMS
had not implemented any additional quality control and data improvement
measures. We stated in the FY 2018 IPPS/LTCH PPS final rule that we
would continue to work with stakeholders to address their concerns
regarding the reporting of uncompensated care through provider
education and refinement of the instructions to the Worksheet S-10 (82
FR 38206).
On September 29, 2017, we issued Transmittal 11, which clarified
the definitions and instructions for uncompensated care, non-Medicare
bad debt, non-reimbursed Medicare bad debt, and charity care, as well
as modified the calculations relative to uncompensated care costs and
added edits to ensure the integrity of the data reported on Worksheet
S-10. Transmittal 11 is available for download on the CMS website at:
https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/2017Downloads/R11p240.pdf. We further clarified that full or partial
discounts given to uninsured patients who meet the hospital's charity
care policy or financial assistance policy/uninsured discount policy
(hereinafter referred to as Financial Assistance Policy or FAP) may be
included on Line 20, Column 1 of Worksheet S-10. These clarifications
apply to cost reporting periods beginning on or after October 1, 2013.
We also modified the application of the CCR. We specified that the CCR
will not be applied to the deductible and coinsurance amounts for
insured patients approved for charity care and non-reimbursed Medicare
bad debt. The CCR will be applied to the charges for uninsured patients
approved for charity care or an uninsured discount, non-Medicare bad
debt, and charges for noncovered days exceeding a length of stay limit
imposed on patients covered by Medicaid or other indigent care
programs.
We also provided another opportunity for hospitals to submit
revisions to their Worksheet S-10 data for FY 2014 and FY 2015 cost
reports. We refer readers to Change Request 10378, Transmittal 1981,
titled ``Fiscal Year (FY) 2014 and 2015 Worksheet S-10 Revisions:
Further Extension for All Inpatient Prospective Payment System (IPPS)
Hospitals,'' issued on December 1, 2017 (available at: https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/2017Downloads/R1981OTN.pdf). In this transmittal, we instructed MACs to
accept amended Worksheets S-10 for FY 2014 and FY 2015 cost reports
submitted by hospitals (or initial submissions of Worksheet S-10 if
none had been submitted previously) and to upload them to the Health
Care Provider Cost Report Information System (HCRIS) in a timely
manner. The transmittal included the deadlines by which hospitals
needed to submit their amended FY 2014 and FY 2015 cost reports
containing the revised Worksheet S-10 (or a completed Worksheet S-10 if
no data were included on the previously submitted cost report) to the
MAC, as well as the dates by which MACs must have accepted these data
and uploaded the revised cost report to the HCRIS, in order for the
data to be considered for purposes of the FY 2019 rulemaking.
(2) Background on the Methodology Used To Calculate Factor 3 for FY
2019
Section 1886(r)(2)(C) of the Act governs both the selection of the
data to be used in calculating Factor 3, and also allows the Secretary
the discretion to determine the time periods from which we will derive
the data to estimate the numerator and the denominator of the Factor 3
quotient. Specifically, section 1886(r)(2)(C)(i) of the Act defines the
numerator of the quotient as the amount of uncompensated care for such
hospital for a period selected by the Secretary. Section
1886(r)(2)(C)(ii) of the Act defines the denominator as the aggregate
amount of uncompensated care for all subsection (d) hospitals that
receive a payment under section 1886(r) of the Act for such period. In
the FY 2014 IPPS/LTCH PPS final rule (78 FR 50638), we adopted a
process of making interim payments with final cost report settlement
for both the empirically justified Medicare DSH payments and the
uncompensated care payments required by section 3133 of the Affordable
Care Act. Consistent with that process, we also determined the time
period from which to calculate the numerator and denominator of the
Factor 3 quotient in a way that would be consistent with making interim
and
[[Page 19416]]
final payments. Specifically, we must have Factor 3 values available
for hospitals that we estimate will qualify for Medicare DSH payments
and for those hospitals that we do not estimate will qualify for
Medicare DSH payments but that may ultimately qualify for Medicare DSH
payments at the time of cost report settlement.
In the FY 2017 IPPS/LTCH PPS final rule, in order to mitigate undue
fluctuations in the amount of uncompensated care payments to hospitals
from year to year and smooth over anomalies between cost reporting
periods, we finalized a policy of calculating a hospital's share of
uncompensated care based on an average of data derived from three cost
reporting periods instead of one cost reporting period. As explained in
the preamble to the FY 2017 IPPS/LTCH PPS final rule (81 FR 56957
through 56959), instead of determining Factor 3 using data from a
single cost reporting period as we did in FY 2014, FY 2015, and FY
2016, we used data from three cost reporting periods (Medicaid data for
FYs 2011, 2012, and 2013 and SSI days from the three most recent
available years of SSI utilization data (FYs 2012, 2013, and 2014)) to
compute Factor 3 for FY 2017. Furthermore, instead of determining a
single Factor 3 as we had done since the first year of the
uncompensated care payment in FY 2014, we calculated an individual
Factor 3 for each of the three cost reporting periods, which we then
averaged by the number of cost reporting years with data to compute the
final Factor 3 for a hospital. Under this policy, if a hospital had
merged, we would combine data from both hospitals for the cost
reporting periods in which the merger was not reflected in the
surviving hospital's cost report data to compute Factor 3 for the
surviving hospital. Moreover, to further reduce undue fluctuations in a
hospital's uncompensated care payments, if a hospital filed multiple
cost reports beginning in the same fiscal year, we combined data from
the multiple cost reports so that a hospital could have a Factor 3
calculated using more than one cost report within a cost reporting
period. We codified these changes for FY 2017 by amending the
regulation at Sec. 412.106(g)(1)(iii)(C).
As we stated in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41414),
with the additional steps we had taken to ensure the accuracy and
consistency of the data reported on Worksheet S-10 since the
publication of the FY 2018 IPPS/LTCH PPS final rule, we continued to
believe that we can no longer conclude that alternative data to the
Worksheet S-10 are currently available for FY 2014 that are a better
proxy for the costs of subsection (d) hospitals for treating
individuals who are uninsured. Similarly, the actions that we have
taken to improve the accuracy and consistency of the Worksheet S-10
data, including the opportunity for hospitals to resubmit Worksheet S-
10 data for FY 2015, led us to conclude that there are no alternative
data to the Worksheet S-10 data currently available for FY 2015 that
are a better proxy for the costs of subsection (d) hospitals for
treating uninsured individuals. As such, in the FY 2019 IPPS/LTCH PPS
final rule (83 FR 41428), we finalized our proposal to advance the time
period of the data used in the calculation of Factor 3 forward by 1
year and to use data from FY 2013, FY 2014, and FY 2015 cost reports to
determine Factor 3 for FY 2019. For the reasons we described earlier,
we stated that we continue to believe it is inappropriate to use
Worksheet S-10 data for periods prior to FY 2014. Rather, for cost
reporting periods prior to FY 2014, we indicated that we believe it is
appropriate to continue to use low-income insured days. Accordingly,
with a time period that includes 3 cost reporting years consisting of
FY 2013, FY 2014, and FY 2015, we used Worksheet S-10 data for the FY
2014 and FY 2015 cost reporting periods and the low-income insured days
proxy data for the earliest cost reporting period. As in previous
years, in order to perform this calculation for the FY 2019 final rule,
we drew three sets of data (1 year of Medicaid utilization data and 2
years of Worksheet S-10 data) from the most recent available HCRIS
extract, which was the June 30, 2018 update of HCRIS, due to the unique
circumstances related to the impact of the hurricanes in 2017 (Harvey,
Irma, Maria, and Nate) and the extension of the deadline to resubmit
Worksheet S-10 data through January 2, 2018, and the subsequent impact
on the MAC review timeline (83 FR 41421).
Accordingly, for FY 2019, in addition to the Worksheet S-10 data
for FY 2014 and FY 2015, we used Medicaid days from FY 2013 cost
reports and FY 2016 SSI ratios. We noted that cost report data from
Indian Health Service and Tribal hospitals are included in HCRIS
beginning in FY 2013 and no longer need to be incorporated from a
separate data source. We also continued the policies that were
finalized in the FY 2015 IPPS/LTCH PPS final rule (79 FR 50020) to
address several specific issues concerning the process and data to be
employed in determining Factor 3 in the case of hospital mergers. In
addition, we continued the policies that were finalized in the FY 2018
IPPS/LTCH PPS final rule to address technical considerations related to
the calculation of Factor 3 and the incorporation of Worksheet S-10
data (82 FR 38213 through 38220). In that final rule, we adopted a
policy, for purposes of calculating Factor 3, under which we annualize
Medicaid days data and uncompensated care cost data reported on the
Worksheet S-10 if a hospital's cost report does not equal 12 months of
data. As in FY 2018, for FY 2019, we did not annualize SSI days because
we do not obtain these data from hospital cost reports in HCRIS.
Rather, we obtained these data from the latest available SSI ratios
posted on the Medicare DSH homepage (https://www.cms.gov/Medicare/
Medicare-fee-for-service-payment/AcuteInpatientPPS/dsh.html), which
were aggregated at the hospital level and did not include the
information needed to determine if the data should be annualized. To
address the effects of averaging Factor 3s calculated for 3 separate
fiscal years, we continued to apply a scaling factor to the Factor 3
values of all DSH eligible hospitals such that total uncompensated care
payments are consistent with the estimated amount available to make
uncompensated care payments for the applicable fiscal year. With
respect to the incorporation of data from Worksheet S-10, we indicated
that we believe that the definition of uncompensated care adopted in FY
2018 is still appropriate because it incorporates the most commonly
used factors within uncompensated care as reported by stakeholders,
including charity care costs and non-Medicare bad debt costs, and
correlates to Line 30 of Worksheet S-10. Therefore, for purposes of
calculating Factor 3 and uncompensated care costs in FY 2019, we again
defined ``uncompensated care'' as the amount on Line 30 of Worksheet S-
10, which is the cost of charity care (Line 23) and the cost of non-
Medicare bad debt and non-reimbursable Medicare bad debt (Line 29).
We noted that we were discontinuing the policy finalized in the FY
2017 IPPS/LTCH PPS final rule concerning multiple cost reports
beginning in the same fiscal year (81 FR 56957). Under this policy, we
would first combine the data across the multiple cost reports before
determining the difference between the start date and the end date to
determine if annualization was needed. This policy was developed in
response to commenters' concerns regarding the unique circumstances of
[[Page 19417]]
hospitals that file cost reports that are shorter or longer than 12
months. As we explained in the FY 2017 IPPS/LTCH PPS final rule (81 FR
56957 through 56959) and in the FY 2018 IPPS/LTCH PPS proposed rule (82
FR 19953), we believed that, for hospitals that file multiple cost
reports beginning in the same year, combining the data from these cost
reports had the benefit of supplementing the data of hospitals that
filed cost reports that are less than 12 months, such that the basis of
their uncompensated care payments and those of hospitals that filed
full-year 12-month cost reports would be more equitable. As we stated
in the FY 2019 IPPS/LTCH PPS proposed and final rules, we now believe
that concerns about the equitability of the data used as the basis of
hospital uncompensated care payments are more thoroughly addressed by
the policy finalized in the FY 2018 IPPS/LTCH PPS final rule, under
which CMS annualizes the Medicaid days and uncompensated care cost data
of hospital cost reports that do not equal 12 months of data. Based on
our experience, we stated that we believe that in many cases where a
hospital files two cost reports beginning in the same fiscal year,
combining the data across multiple cost reports before annualizing
would yield a similar result to choosing the longer of the two cost
reports and then annualizing the data if the cost report is shorter or
longer than 12 months. Furthermore, even in cases where a hospital
files more than one cost report beginning in the same fiscal year, it
is not uncommon for one of those cost reports to span exactly 12
months. In this case, if Factor 3 is determined using only the full 12-
month cost report, annualization would be unnecessary as there would
already be 12 months of data. Therefore, for FY 2019, we stated that we
believed it was appropriate to eliminate the additional step of
combining data across multiple cost reports if a hospital filed more
than one cost report beginning in the same fiscal year. Instead, for
purposes of calculating Factor 3, we used data from the cost report
that is equivalent to 12 months or, if no such cost report existed, the
cost report that was closest to 12 months, and annualized the data.
Furthermore, we acknowledged that, in rare cases, a hospital may have
more than one cost report beginning in one fiscal year, where one
report also spans the entirety of the following fiscal year, such that
the hospital has no cost report beginning in that fiscal year. For
instance, a hospital's cost reporting period may have started towards
the end of FY 2012 but cover the duration of FY 2013. In these rare
situations, we would use data from the cost report that spans both
fiscal years in the Factor 3 calculation for the latter fiscal year as
the hospital would already have data from the preceding cost report
that could be used to determine Factor 3 for the previous fiscal year.
In FY 2019, we also continued to apply statistical trims to
anomalous hospital CCRs using a similar methodology to the one adopted
in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38217 through 38219),
where we stated our belief that, just as we apply trims to hospitals'
CCRs to eliminate anomalies when calculating outlier payments for
extraordinarily high cost cases (Sec. 412.84(h)(3)(ii)), it is
appropriate to apply statistical trims to the CCRs on Worksheet S-10,
Line 1, that are considered anomalies. Specifically, Sec.
412.84(h)(3)(ii) states that the Medicare contractor may use a
statewide CCR for hospitals whose operating or capital CCR is in excess
of 3 standard deviations above the corresponding national geometric
mean (that is, the CCR ``ceiling''). The geometric means for purposes
of the Worksheet S-10 trim of CCRs and for purposes of Sec.
412.84(h)(3)(ii) are separately calculated annually by CMS and
published in the applicable sections of the proposed and final IPPS
rules each year. We refer readers to the FY 2019 IPPS/LTCH PPS final
rule (83 FR 41415) for a detailed description of the CCR trim
methodology for purposes of the Worksheet S-10 trim of CCRs, which
included calculating 3 standard deviations above the national geometric
mean CCR for each of the applicable cost report years (FY 2014 and FY
2015) that were part of the Factor 3 methodology for FY 2019.
Similar in concept to the policy that we adopted for FY 2018, for
FY 2019, we stated that we continued to believe that uncompensated care
costs that represent an extremely high ratio of a hospital's total
operating expenses (such as the ratio of 50 percent used in the FY 2018
IPPS/LTCH PPS final rule) may be potentially aberrant, and that using
the ratio of uncompensated care costs to total operating costs to
identify potentially aberrant data when determining Factor 3 amounts
has merit. We noted that we had instructed the MACs to review
situations where a hospital has an extremely high ratio of
uncompensated care costs to total operating costs with the hospital,
but also indicated that we did not intend to make the MACs' review
protocols public (83 FR 41416). Similarly, we believe that situations
where there were extremely large dollar increases or decreases in a
hospital's uncompensated care costs when it resubmitted its FY 2014
Worksheet S-10 or FY 2015 Worksheet S-10 data, or when the data it had
previously submitted were reprocessed by the MAC, may reflect
potentially aberrant data and warrant further review. In the FY 2019
IPPS/LTCH PPS proposed rule (83 FR 20399), we noted that our
calculation of Factor 3 for the final rule would be contingent on the
results of the ongoing MAC reviews of hospitals' Worksheet S-10 data,
and in the event those reviews necessitate supplemental data edits, we
would incorporate such edits in the final rule for the purpose of
correcting aberrant data. After the completion of the MAC reviews, we
did not incorporate any additional edits to the Worksheet S-10 data
that we did not propose in the FY 2019 IPPS/LTCH PPS proposed rule. We
refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41416) for
a detailed discussion of our policies for trimming aberrant data. In
brief summary, in cases where a hospital's uncompensated care costs for
FY 2014 or FY 2015 were an extremely high ratio of its total operating
costs, and the hospital could not justify the amount it reported, we
determined the ratio of uncompensated care costs to the hospital's
total operating costs from another available cost report, and applied
that ratio to the total operating expenses for the potentially aberrant
fiscal year to determine an adjusted amount of uncompensated care
costs. For example, if the FY 2015 cost report was determined to
include potentially aberrant data, data from the FY 2016 cost report
would be used for the ratio calculation. In this case, the hospital's
uncompensated care costs for FY 2015 would be trimmed by multiplying
its FY 2015 total operating costs by the ratio of uncompensated care
costs to total operating costs from the hospital's FY 2016 cost report
to calculate an estimate of the hospital's uncompensated care costs for
FY 2015 for purposes of determining Factor 3 for FY 2019.
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41416), for Indian
Health Service and Tribal hospitals, subsection (d) Puerto Rico
hospitals, and all-inclusive rate providers, we continued the policy we
first adopted for FY 2018 of substituting data regarding FY 2013 low-
income insured days for the Worksheet S-10 data when determining Factor
3. As we discussed in the FY 2018 IPPS/LTCH PPS final rule (82 FR
38209), the use of data from Worksheet S-10 to calculate the
uncompensated care amount for Indian Health Service and Tribal
hospitals may jeopardize
[[Page 19418]]
these hospitals' uncompensated care payments due to their unique
funding structure. With respect to Puerto Rico hospitals, we indicated
that we continue to agree with concerns raised by commenters that the
uncompensated care data reported by these hospitals need to be further
examined before the data are used to determine Factor 3 (82 FR 38209).
Finally, we acknowledged that the CCRs for all-inclusive rate providers
are potentially erroneous and still in need of further examination
before they can be used in the determination of uncompensated care
amounts for purposes of Factor 3 (82 FR 38212). For the reasons
described earlier related to the impact of the Medicaid expansion
beginning in FY 2014, we stated that we also continue to believe that
it is inappropriate to calculate a Factor 3 using FY 2014 and FY 2015
low-income insured days. Because we did not believe it was appropriate
to use the FY 2014 or FY 2015 uncompensated care data for these
hospitals and we also did not believe it was appropriate to use the FY
2014 or FY 2015 low-income insured days, we stated that the best proxy
for the costs of Indian Health Service and Tribal hospitals, subsection
(d) Puerto Rico hospitals, and all-inclusive rate providers for
treating the uninsured continues to be the low-income insured days data
for FY 2013. Accordingly, for these hospitals, we determined Factor 3
only on the basis of low-income insured days for FY 2013. We stated our
belief that this approach was appropriate as the FY 2013 data reflect
the most recent available information regarding these hospitals' low-
income insured days before any expansion of Medicaid. In addition,
because we continued to use 1 year of insured low-income patient days
as a proxy for uncompensated care and residents of Puerto Rico are not
eligible for SSI benefits, we continued to use a proxy for SSI days for
Puerto Rico hospitals consisting of 14 percent of the hospital's
Medicaid days, as finalized in the FY 2017 IPPS/LTCH PPS final rule (81
FR 56953 through 56956).
Therefore, for FY 2019, we computed Factor 3 for each hospital by--
Step 1: Calculating Factor 3 using the low-income insured days
proxy based on FY 2013 cost report data and the FY 2016 SSI ratio (or,
for Puerto Rico hospitals, 14 percent of the hospital's FY 2013
Medicaid days);
Step 2: Calculating Factor 3 based on the FY 2014 Worksheet S-10
data;
Step 3: Calculating Factor 3 based on the FY 2015 Worksheet S-10
data; and
Step 4: Averaging the Factor 3 values from Steps 1, 2, and 3; that
is, adding the Factor 3 values from FY 2013, FY 2014, and FY 2015 for
each hospital, and dividing that amount by the number of cost reporting
periods with data to compute an average Factor 3 (or for Puerto Rico
hospitals, Indian Health Service and Tribal hospitals, and all-
inclusive rate providers, using the Factor 3 value from Step 1).
We also amended the regulations at Sec. 412.106(g)(1)(iii)(C) by
adding a new paragraph (5) to reflect the above methodology for
computing Factor 3 for FY 2019.
In the FY 2019 IPPS/LTCH PPS final rule, we noted that if a
hospital does not have both Medicaid days for FY 2013 and SSI days for
FY 2016 available for use in the calculation of Factor 3 in Step 1, we
would consider the hospital not to have data available for the fiscal
year, and would remove that fiscal year from the calculation and divide
by the number of years with data. A hospital would be considered to
have both Medicaid days and SSI days data available if it reported zero
days for either component of the Factor 3 calculation in Step 1.
However, if a hospital was missing data due to not filing a cost report
in one of the applicable fiscal years, we would divide by the remaining
number of fiscal years.
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41417), we noted
that we did not make any proposals with respect to the development of
Factor 3 for FY 2020 and subsequent fiscal years. However, we noted
that the above methodology would have the effect of fully transitioning
the incorporation of data from Worksheet S-10 into the calculation of
Factor 3 if used in FY 2020, and therefore, the use of low-income
insured days would be phased out by FY 2020 if the same methodology
were to be proposed and finalized for that year. We also indicated that
it was possible that when we examine the FY 2016 Worksheet S-10 data,
we might determine that the use of multiple years of Worksheet S-10
data is no longer necessary in calculating Factor 3 for FY 2020. We
stated that, given the efforts hospitals have already undertaken with
respect to reporting their Worksheet S-10 data and the subsequent
reviews by the MACs that had already been conducted prior to the
development of the FY 2019 IPPS/LTCH PPS final rule, along with
additional review work that might take place following the issuance of
the FY 2019 final rule, we might consider using 1 year of Worksheet S-
10 data as the basis for calculating Factor 3 for FY 2020.
For new hospitals that did not have data for any of the three cost
reporting periods used in the Factor 3 calculation for FY 2019, we
continued to apply the new hospital policy finalized in the FY 2014
IPPS/LTCH PPS final rule (78 FR 50643). That is, the hospital would not
receive either interim empirically justified Medicare DSH payments or
interim uncompensated care payments. However, if the hospital is later
determined to be eligible to receive empirically justified Medicare DSH
payments based on its FY 2019 cost report, the hospital would also
receive an uncompensated care payment calculated using a Factor 3,
where the numerator is the uncompensated care costs reported on
Worksheet S-10 of the hospital's FY 2019 cost report, and the
denominator is the sum of the uncompensated care costs reported on
Worksheet S-10 of the FY 2015 cost reports for all DSH eligible
hospitals (that is, the most recent year of the 3-year time period used
in the development of Factor 3 for FY 2019). We noted that, given the
time period of the data used to calculate Factor 3, any hospitals with
a CCN established after October 1, 2015, would be considered new and
subject to this policy.
(3) Proposed Methodology for Calculating Factor 3 for FY 2020
(a) Proposal to Use of Audited FY 2015 Data
Since the publication of the FY 2019 IPPS/LTCH PPS final rule, we
have continued to monitor the reporting of Worksheet S-10 data in order
to determine the most appropriate data to use in the calculation of
Factor 3 for FY 2020. As stated in the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41424), due to the overwhelming feedback from commenters
emphasizing the importance of audits in ensuring the accuracy and
consistency of data reported on the Worksheet S-10, we expected audits
of the Worksheet S-10 to begin in the Fall of 2018. The audit protocol
instructions were still under development at the time of the FY 2019
IPPS/LTCH PPS final rule; yet, we noted the audit protocols would be
provided to the MACs in advance of the audit. Once the audit protocol
instructions were complete, we began auditing the Worksheet S-10 data
for selected hospitals in the Fall of 2018 so that the audited
uncompensated care data from these hospitals would be available in time
for use in this FY 2020 proposed rule. We chose to audit 1 year of data
(that is, FY 2015) in order to maximize the available audit resources
and not spread those audit resources over multiple years, potentially
diluting their effectiveness. We chose to focus the audit on the FY
2015 cost reports primarily because this was the most
[[Page 19419]]
recent year of data that we had broadly allowed to be resubmitted by
hospitals, and many hospitals had already made considerable efforts to
amend their FY 2015 reports for the FY 2019 rulemaking. We also
considered that we had previously used the FY 2015 data as part of the
calculation of the FY 2019 uncompensated care payments; therefore, the
data had previously been subject to public comment and scrutiny.
Given that we have conducted audits of the FY 2015 Worksheet S-10
data and have previously used the FY 2015 data to determine
uncompensated care payments, and the fact that the FY 2015 data are the
most recent data that we have allowed to be resubmitted to date, we
believe that, on balance, the FY 2015 Worksheet S-10 data are the best
available data to use for calculating Factor 3 for FY 2020. However, as
discussed in more detail later in the next section, an alternative we
also considered is the use of FY 2017 data. We are seeking public
comments on this alternative and, based on the public comments we
receive, could adopt it in the FY 2020 final rule.
We recognize that, in FY 2019, we used 3 years of data in the
calculation of Factor 3 in order to smooth over anomalies between cost
reporting periods and to mitigate undue fluctuations in the amount of
uncompensated care payments from year to year. However, we believe
that, for FY 2020, mixing audited and unaudited data for individual
hospitals by averaging multiple years of data could potentially lead to
a less smooth result, which is counter to our original goal in using 3
years of data. To the extent that the audited FY 2015 data for a
hospital are relatively different from its unaudited FY 2014 data and/
or its unaudited FY 2016 data, we potentially would be diluting the
effect of our considerable auditing efforts and introducing unnecessary
variability into the calculation if we continued to use 3 years of data
to calculate Factor 3. For example, approximately 10 percent of audited
hospitals have more than a $20 million difference between their audited
FY 2015 data and their unaudited FY 2016 data.
Accordingly, we are proposing to use a single year of Worksheet S-
10 data from FY 2015 cost reports to calculate Factor 3 in the FY 2020
methodology. We note that the proposed uncompensated care payments to
hospitals whose FY 2015 Worksheet S-10 data were audited represent
approximately half of the proposed total uncompensated care payments
for FY 2020. For purposes of this FY 2020 proposed rule, we have used
the most recent available HCRIS extract available, which is the HCRIS
data updated through February 15, 2019. We expect to use the March 2019
update of HCRIS for the final rule.
(b) Alternative Considered To Use FY 2017 Data
Although we are proposing to use Worksheet S-10 data from the FY
2015 cost reports, we acknowledge that some hospitals have raised
concerns regarding some of the adjustments made to the FY 2015 cost
reports following the audits of these reports (for example, adjustments
made to Line 22 of Worksheet S-10). These hospitals contend that there
are issues regarding the instructions in effect for FY 2015, especially
compared to the reporting instructions that were effective for cost
reporting periods beginning on or after October 1, 2016, and some of
these adjustments would not have been made if CMS had chosen as an
alternative to audit the FY 2017 reports.
Accordingly, we are seeking public comments on whether the changes
in the reporting instructions between the FY 2015 cost reports and the
FY 2017 cost reports have resulted in a better common understanding
among hospitals of how to report uncompensated care costs and improved
relative consistency and accuracy across hospitals in reporting these
costs. We also are seeking public comments on whether, due to the
changes in the reporting instructions, we should use a single year of
uncompensated care cost data from the FY 2017 reports, instead of the
FY 2015 reports, to calculate Factor 3 for FY 2020. We note that we are
not proposing to use FY 2016 reports because the reporting instructions
for that year were similar to the reporting instructions for the FY
2015 reports. If, based on the public comments received, we were to
adopt a final policy in which we use Worksheet S-10 data from the FY
2017 cost reports to determine Factor 3 for FY 2020, we would also
expect to use the March 2019 update of HCRIS for the final rule.
Under the alternative considered on which we are seeking public
comment, the FY 2017 Worksheet S-10 data would be used instead of the
FY 2015 Worksheet S-10 data, but, in general, the proposed Factor 3
methodology would be unchanged. The limited circumstances where the
methodology would need to differ from the proposed methodology using FY
2015 data, if we were to adopt the alternative of using FY 2017 data in
the final rule based on the public comments received, are outlined in
section IV.F.4.c.(3)(d) of the preamble of this proposed rule
(Methodological Considerations for Calculating Factor 3). If an aspect
of the proposed methodology described below does not specifically
indicate that we would modify it under the alternative considered, that
aspect of the methodology would be unchanged, regardless of whether we
use FY 2015 data or FY 2017 data. We note that we are providing all of
the same public information regarding the alternative considered,
including the Factor 3 values for each hospital and the impact
information, that we are providing for our proposal to use FY 2015
data.
(c) Proposed Definition of ``Uncompensated Care''
We continue to believe that the definition of ``uncompensated
care'' first adopted in FY 2018 when we started to incorporate data
from Worksheet S-10 into the determination of Factor 3 and used again
in FY 2019 is appropriate, as it incorporates the most commonly used
factors within uncompensated care as reported by stakeholders, namely,
charity care costs and bad debt costs, and correlates to Line 30 of
Worksheet S-10. Therefore, we are proposing that, for purposes of
determining uncompensated care costs and calculating Factor 3 for FY
2020, ``uncompensated care'' would continue to be defined as the amount
on Line 30 of Worksheet S-10, which is the cost of charity care (Line
23) and the cost of non-Medicare bad debt and non-reimbursable Medicare
bad debt (Line 29).
(d) Methodological Considerations for Calculating Factor 3
For FY 2020, we are proposing to continue the merger policies that
were finalized in the FY 2015 IPPS/LTCH PPS final rule (79 FR 50020).
In addition, we are proposing to continue the policy that was finalized
in the FY 2018 IPPS/LTCH PPS final rule of annualizing uncompensated
care cost data reported on the Worksheet S-10 if a hospital's cost
report does not equal 12 months of data.
We are proposing to modify the new hospital policy first adopted in
the FY 2014 IPPS/LTCH PPS final rule (78 FR 50643) and continued
through the FY 2019 IPPS/LTCH PPS final rule (83 FR 41417), for new
hospitals that do not have data for the cost reporting period(s) used
in the proposed Factor 3 calculation. For FY 2020, new hospitals that
are eligible for Medicare DSH would receive interim empirically
justified DSH payments. Generally, new hospitals do not yet have
available data to project their eligibility for DSH
[[Page 19420]]
payments because there is a lag until the SSI ratio and the Medicaid
ratio become available. However, we note that there are some new
hospitals (that is, hospitals with CCNs established after October 1,
2015) that have a preliminary projection of being eligible for DSH
payments based on their most recent available DSH percentages. Because
these hospitals do not have a FY 2015 cost report to use in the Factor
3 calculation and the projection of eligibility for DSH payments is
still preliminary, we are proposing that the MAC would make a final
determination concerning whether the hospital is eligible to receive
Medicare DSH payments at cost report settlement based on its FY 2020
cost report. If the hospital is ultimately determined to be eligible
for Medicare DSH payments for FY 2020, the hospital would receive an
uncompensated care payment calculated using a Factor 3, where the
numerator is the uncompensated care costs reported on Worksheet S-10 of
the hospital's FY 2020 cost report, and the denominator is the sum of
the uncompensated care costs reported on Worksheet S-10 of the FY 2015
cost reports for all DSH-eligible hospitals. This denominator would be
the same denominator that is determined prospectively for purposes of
determining Factor 3 for all DSH-eligible hospitals, excluding Puerto
Rico hospitals and Indian Health Service and Tribal hospitals. The new
hospital would not receive interim uncompensated care payments before
cost report settlement because we would have no FY 2015 uncompensated
care data on which to determine what those interim payments should be.
We note that, given the time period of the data we are proposing to use
to calculate Factor 3, any hospitals with a CCN established on or after
October 1, 2015, would be considered new and subject to this policy.
However, under the alternative policy considered of using FY 2017 data,
we would modify the new hospital policy, such that any hospital with a
CCN established on or after October 1, 2017, would be considered new
and subject to this policy with conforming changes to provide for the
use of FY 2017 uncompensated care data.
We have received questions regarding the new hospital policy for
new Puerto Rico hospitals. In FY 2018 and FY 2019, Factor 3 for all
Puerto Rico hospitals, including new Puerto Rico hospitals, was based
on the low-income insured proxy data. Under this approach, the MAC will
calculate a Factor 3 for new Puerto Rico hospitals at cost report
settlement for the applicable fiscal year using the Medicaid days from
the hospital's cost report and the SSI day proxy (that is, 14 percent
of the hospital's Medicaid days) divided by the low-income insured
proxy data denominator that was established for that fiscal year. For
FY 2020, we are proposing that Puerto Rico hospitals that do not have a
FY 2013 report would be considered new hospitals and would be subject
to the proposed new hospital policy, as discussed above. Specifically,
the numerator would be the uncompensated care costs reported on
Worksheet S-10 of the hospital's FY 2020 cost report and the
denominator would be the same denominator that is determined
prospectively for purposes of determining Factor 3 for all DSH-eligible
hospitals. We believe this notice of proposed rulemaking provides
sufficient time for all new hospitals to take the steps necessary to
ensure that their uncompensated care costs for FY 2020 are accurately
reported on their FY 2020 Worksheet S-10. In addition, we expect MACs
to review FY 2020 reports from new hospitals, as necessary, which will
address past commenters' concerns regarding the need for further review
of Puerto Rico hospitals' uncompensated care data before the data are
used to determine Factor 3. Therefore, we believe the uncompensated
care costs reported on their FY 2020 Worksheet S-10 are the best
available and appropriate data to use to calculate Factor 3 for new
Puerto Rico hospitals. This proposed would also allow our new hospital
policy to be more uniform, given that Worksheet S-10 would be the
source of the uncompensated care cost data across all new hospitals.
For Indian Health Service and Tribal hospitals and subsection (d)
Puerto Rico hospitals that have a FY 2013 cost report, we are proposing
to adapt the policy first adopted for the FY 2018 rulemaking regarding
FY 2013 low-income insured days when determining Factor 3. As we
discussed in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38209), the
use of data from Worksheet S-10 to calculate the uncompensated care
amount for Indian Health Service and Tribal hospitals may jeopardize
these hospitals' uncompensated care payments due to their unique
funding structure. With respect to Puerto Rico hospitals that would not
be subject to the proposed new hospital policy, we continue to agree
with concerns raised by commenters that the uncompensated care data
reported by these hospitals need to be further examined before the data
are used to determine Factor 3 (82 FR 38209). Accordingly, for these
hospitals, we are proposing to determine Factor 3 based on Medicaid
days from FY 2013 and the most recent update of SSI days. The aggregate
amount of uncompensated care that is used in the Factor 3 denominator
for these hospitals would continue to be based on the low-income
patient proxy; that is, the aggregate amount of uncompensated care
determined for all DSH eligible hospitals using the low-income insured
days proxy. We believe this approach is appropriate because the FY 2013
data reflect the most recent available information regarding these
hospitals' Medicaid days before any expansion of Medicaid. At the time
of development of this proposed rule, for modeling purposes, we
computed Factor 3 for these hospitals using FY 2013 Medicaid days and
the most recent available FY 2017 SSI days. In addition, because we are
continuing to use 1 year of insured low-income patient days as a proxy
for uncompensated care for Puerto Rico hospitals and residents of
Puerto Rico are not eligible for SSI benefits, we are proposing to
continue to use a proxy for SSI days for Puerto Rico hospitals,
consisting of 14 percent of a hospital's Medicaid days, as finalized in
the FY 2017 IPPS/LTCH PPS final rule (81 FR 56953 through 56956).
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41417), we noted
that further examination of the CCRs for all-inclusive rate providers
was necessary before we considered incorporating Worksheet S-10 into
the Factor 3 calculation for these hospitals. We have examined the CCRs
from the FY 2015 cost reports and believe the risk that all-inclusive
rate providers will have aberrant CCRs and, consequently, aberrant
uncompensated care data, is mitigated by the proposal to apply trim
methodologies for potentially aberrant uncompensated care costs for all
hospitals. Therefore, we believe it is no longer necessary to propose
specific Factor 3 policies for all-inclusive rate providers.
Because we are proposing to use 1 year of cost report data, as
opposed to averaging 3 cost report years, it is also no longer
necessary to propose to apply a scaling factor to the Factor 3 of all
DSH eligible hospitals similar to the scaling factor that was finalized
in FY 2018 IPPS/LTCH PPS final rule (82 FR 38214) and also applied in
the FY 2019 IPPS/LTCH PPS final rule. The primary purpose of the
scaling factor was to account for the averaging effect of the use of 3
years of data on the Factor 3 calculation.
However, we are proposing to continue certain other policies
finalized
[[Page 19421]]
in the FY 2019 IPPS/LTCH PPS final rule, specifically: (1) For
providers with multiple cost reports, beginning in the same fiscal
year, using the longest cost report and annualizing Medicaid data and
uncompensated care data if a hospital's cost report does not equal 12
months of data; (2) in the rare case where a provider has multiple cost
reports, beginning in the same fiscal year, but one report also spans
the entirety of the following fiscal year, such that the hospital has
no cost report for that fiscal year, using the cost report that spans
both fiscal years for the latter fiscal year; and (3) applying
statistical trim methodologies to potentially aberrant CCRs and
potentially aberrant uncompensated care costs reported on the Worksheet
S-10. Thus, if a hospital's uncompensated care costs for FY 2015 are an
extremely high ratio of its total operating costs, and the hospital
cannot justify the amount it reported, we are proposing to determine
the ratio of uncompensated care costs to the hospital's total operating
costs from another available cost report, and apply that ratio to the
total operating expenses for the potentially aberrant fiscal year to
determine an adjusted amount of uncompensated care costs. For example,
if the FY 2015 cost report is determined to include potentially
aberrant data, data from the FY 2016 cost report would be used for the
ratio calculation. In this case, similar to the trim methodology used
for FY 2019, the hospital's uncompensated care costs for FY 2015 would
be trimmed by multiplying its FY 2015 total operating costs by the
ratio of uncompensated care costs to total operating costs from the
hospital's FY 2016 cost report to calculate an estimate of the
hospital's uncompensated care costs for FY 2015 for purposes of
determining Factor 3 for FY 2020.
In support of the alternative policy considered of using
uncompensated care data from FY 2017 and to improve the quality of the
Worksheet S-10 data generally, we are currently in a process of
outreach to hospitals related to potentially aberrant data reported in
their FY 2017 cost reports. For example, a significant positive or
negative difference in the percent of total uncompensated care costs to
total operating costs when comparing the hospital's FY 2015 cost report
to its FY 2017 cost report may indicate potentially aberrant data.
While hospitals may see uncompensated care cost fluctuations from year
to year, if a hospital experiences a significant change compared to
other comparable hospitals, this could be an indication of potentially
aberrant data. A hospital with such changes would have the opportunity
to justify its reporting fluctuation to the MAC and, if necessary, to
amend its FY 2017 cost report. If a hospital's FY 2017 cost report
remains unchanged without an acceptable response or explanation from
the provider, under the alternative policy considered, we would trim
the data in the provider's FY 2017 cost report using data from the
provider's FY 2015 cost report in order to determine Factor 3 for
purposes of the final rule.
While we expect all providers will have FY 2017 cost reports in
HCRIS by the time that any data would be taken from HCRIS for the final
rule, if such data are not reflected in HCRIS for an unforeseen reason
unrelated to any inappropriate action or improper reporting on the part
of the hospital, we would substitute the Worksheet S-10 data from the
FY 2015 cost report for the data from the FY 2017 cost report.
Similar to the process used in the FY 2018 IPPS/LTCH PPS final rule
(82 FR 38217 through 38218) and the FY 2019 IPPS/LTCH PPS (83 FR 41415
and 41416) for trimming CCRs, in this FY 2020 IPPS/LTCH PPS proposed
rule, we are proposing the following steps:
Step 1: Remove Maryland hospitals. In addition, we would remove
all-inclusive rate providers because their CCRs are not comparable to
the CCRs calculated for other IPPS hospitals.
Step 2: For FY 2015 cost reports, calculate a CCR ``ceiling'' with
the following data: For each IPPS hospital that was not removed in Step
1 (including non-DSH eligible hospitals), we would use cost report data
to calculate a CCR by dividing the total costs on Worksheet C, Part I,
Line 202, Column 3 by the charges reported on Worksheet C, Part I, Line
202, Column 8. (Combining data from multiple cost reports from the same
fiscal year is not necessary, as the longer cost report would be
selected.) The ceiling would be calculated as 3 standard deviations
above the national geometric mean CCR for the applicable fiscal year.
This approach is consistent with the methodology for calculating the
CCR ceiling used for high-cost outliers. Remove all hospitals that
exceed the ceiling so that these aberrant CCRs do not skew the
calculation of the statewide average CCR. (For this proposed rule, this
trim would remove 8 hospitals that have a CCR above the calculated
ceiling of 0.925 for FY 2015 cost reports.) (Under the alternative
policy considered, the trim would remove 13 hospitals that have a CCR
above the calculated ceiling of 0.942 for FY 2017 cost reports.)
Step 3: Using the CCRs for the remaining hospitals in Step 2,
determine the urban and rural statewide average CCRs for FY 2015 for
hospitals within each State (including non-DSH eligible hospitals),
weighted by the sum of total inpatient discharges and outpatient visits
from Worksheet S-3, Part I, Line 14, Column 14.
Step 4: Assign the appropriate statewide average CCR (urban or
rural) calculated in Step 3 to all hospitals with a CCR for FY 2015
greater than 3 standard deviations above the national geometric mean
for that fiscal year (that is, the CCR ``ceiling''). For this proposed
rule, the statewide average CCR would therefore be applied to 8
hospitals, of which 4 hospitals have FY 2015 Worksheet S-10 data.
(Under the alternative policy considered, the statewide average CCR
would be applied to 13 hospitals, of which 5 hospitals have FY 2017
Worksheet S-10 data.)
For providers that did not report a CCR on Worksheet S-10, Line 1,
we would assign them the statewide average CCR in step 4.
After applying the applicable trims to a hospital's CCR as
appropriate, we are proposing that we would calculate a hospital's
uncompensated care costs for the applicable fiscal year as being equal
to Line 30, which is the sum of Line 23, Column 3, and Line 29
determined using the hospital's CCR or the statewide average CCR (urban
or rural), if applicable.
Therefore, for FY 2020, we are proposing to compute Factor 3 for
each hospital by--
Step 1: Selecting the provider's longest cost report from its
Federal fiscal year (FFY) 2015 cost reports. (Alternatively, in the
rare case when the provider has no FFY 2015 cost report because the
cost report for the previous Federal fiscal year spanned the FFY 2015
time period, the previous Federal fiscal year cost report would be used
in this step.)
Step 2: Annualizing the uncompensated care costs (UCC) from
Worksheet S-10 Line 30, if the cost report is more than or less than 12
months. (If applicable, use the statewide average CCR (urban or rural)
to calculate uncompensated care costs.)
Step 3: Combining annualized uncompensated care costs for hospitals
that merged.
Step 4: Calculating Factor 3 for Indian Health Service and Tribal
hospitals and Puerto Rico hospitals using the low-income insured days
proxy based on FY 2013 cost report data and the most recent available
SSI ratio (or, for Puerto Rico hospitals, 14 percent of the
[[Page 19422]]
hospital's FY 2013 Medicaid days). The denominator is calculated using
the low-income insured days proxy data from all DSH eligible hospitals.
Step 5: Calculating Factor 3 for the remaining DSH eligible
hospitals using annualized uncompensated care costs (Worksheet S-10
Line 30) based on FY 2015 cost report data (from Step 3). The hospitals
for which Factor 3 was calculated in Step 4 are excluded from this
calculation.
We also are proposing to amend the regulations at Sec.
412.106(g)(1)(iii)(C) by adding a new paragraph (6) to reflect the
above proposed methodology for computing Factor 3 for FY 2020.
We note that, if a hospital does not have Worksheet S-10 data for
FY 2015 and the hospital is not a new hospital (that is, its CCN was
established before October 1, 2015) nor has the rare case of no FY 2015
cost report, we are proposing to apply the steps above with
uncompensated care costs of zero for the hospital. In addition, if, in
the course of the Worksheet S-10 reviews by MACs, a hospital is unable
to provide sufficient documentation or is unwilling to justify its cost
report, which subsequently results in the hospital's Worksheet S-10
being adjusted to zero, we also are proposing to use the above steps to
calculate Factor 3. We recognize that, under this proposal, these
hospitals would be treated as having reported no uncompensated care
costs on the Worksheet S-10 for FY 2015, which would result in their
not receiving uncompensated care payments for FY 2020. However, we
believe this proposal is equitable to other hospitals because all
short-term acute care hospitals are required to report Worksheet S-10
and must maintain sufficient documentation to support the information
reported. In addition, hospitals have been on notice since the
beginning of FY 2014 that Worksheet S-10 could eventually become the
data source for CMS to calculate uncompensated care payments.
Furthermore, we have previously given hospitals the opportunity to
amend their Worksheet S-10 for FY 2015 cost reports (or to submit a
Worksheet S-10 for FY 2015 if none had been submitted previously).
As we have done for every proposed and final rule beginning in FY
2014, in conjunction with both the FY 2020 IPPS/LTCH PPS proposed rule
and final rule, we will publish on the CMS website a table listing
Factor 3 computed using both the proposed methodology and the potential
alternative methodology for all hospitals that we estimate would
receive empirically justified Medicare DSH payments in FY 2020 (that
is, those hospitals that would receive interim uncompensated care
payments during the fiscal year), and for the remaining subsection (d)
hospitals and subsection (d) Puerto Rico hospitals that have the
potential of receiving a Medicare DSH payment in the event that they
receive an empirically justified Medicare DSH payment for the fiscal
year as determined at cost report settlement. We note that, at the time
of development of this proposed rule, the FY 2017 SSI ratios were
available. Accordingly, for purposes of this proposed rule, we have
computed Factor 3 for Indian Health Service and Tribal hospitals and
Puerto Rico hospitals using the most recent available data regarding
SSI days from the FY 2017 SSI ratios. We also will publish in the
supplemental data file a list of the mergers that we are aware of and
the computed uncompensated care payment for each merged hospital.
Hospitals have 60 days from the date of public display of this FY
2020 IPPS/LTCH PPS proposed rule to review the table and supplemental
data file published on the CMS website in conjunction with the proposed
rule and to notify CMS in writing of any inaccuracies. Comments that
are specific to the information included in the table and supplemental
data file can be submitted to the CMS inbox at
[email protected]. We will address these comments as
appropriate in the table and the supplemental data file that we publish
on the CMS website in conjunction with the publication of the FY 2020
IPPS/LTCH PPS final rule. After the publication of the FY 2020 IPPS/
LTCH PPS final rule, hospitals will have until August 31, 2019, to
review and submit comments on the accuracy of the table and
supplemental data file published in conjunction with the final rule.
Comments may be submitted to the CMS inbox at
[email protected] through August 31, 2019, and any changes to
Factor 3 will be posted on the CMS website prior to October 1, 2019.
We are inviting public comments on our proposed methodology for
calculating Factor 3 for FY 2020, including, but not limited to, our
proposed use of the FY 2015 Worksheet S-10 data and the alternative
policy considered of using the FY 2017 Worksheet S-10 data instead of
the FY 2015 Worksheet S-10 data.
5. Request for Public Comments on Ways To Reduce Provider Reimbursement
Review Board (PRRB) Appeals Related to a Hospital's Medicaid Fraction
Used in the Disproportionate Share Hospital (DSH) Payment Adjustment
Calculation
As part of our ongoing efforts to reduce regulatory burden on
providers, we are examining the backlog of appeals cases at the
Provider Reimbursement Review Board (PRRB). A large number of appeals
before the PRRB relate to the calculation of a hospital's
disproportionate patient percentage (DPP) used in the calculation of
the DSH payment adjustment. (We refer readers to section IV.F. 1. of
the preamble of this proposed rule for a discussion of the calculation
of a hospitals DPP.) Many of these appeals before the PRRB focus on the
calculation of a hospital's Medicaid fraction, which is one of the two
fractions comprising the DPP, particularly the data used to determine
an individual's Medicaid eligibility in the calculation. Specifically,
it is possible that updated data on Medicaid eligibility are available
following cost report submission. As a result, many hospitals annually
appeal their cost reports to the PRRB in an effort to try and use
updated State Medicaid eligibility data to calculate the Medicaid
fraction. We believe it is in both CMS' and the providers' interest to
seek a solution to issues related to the Medicaid fraction that appear
to have led to a large volume and backlog of PRRB appeals. Therefore,
we believe it is appropriate to explore options that may prevent the
need for such appeals. We note that the Provider Reimbursement Review
Board Rules, Version 2.0, August 29, 2018, contain revisions in Rules
46 and 47 pertaining to ``Withdrawal of an Appeal or Issue Within an
Appeal'' and ``Reinstatement'', respectively. These changes may lower
the number of tracked PRRB appeals. In exploring possible solutions, we
are concerned about balancing the competing interests of administrative
finality, ease of implementation for both CMS and providers, and the
use of the most appropriate data.
We believe one such solution might be to develop regulations
governing the timing of the data for determining Medicaid eligibility,
somewhat similar to our existing policy on entitlement to SSI benefits
which is determined at a specific time. For more information on this
policy, we refer readers to the FY 2011 IPPS/LTCH PPS final rule (75 FR
50276). Under this possible solution, a provider would submit a cost
report
[[Page 19423]]
with Medicaid days based on the best available Medicaid eligibility
data at the time of filing and could request a ``reopening'' when the
cost report is settled without filing an appeal. CMS would issue
directives to the MACs requiring them to reopen those cost reports for
this issue at a specific time and set a realistic period during which
the provider could submit updated data. This would be an expansion of
the preamble instructions finalized in the CY 2016 OPPS/ASC final rule
with comment period issued on November 13, 2015 (80 FR 70563 and 70564)
which requires the MACs to accept one amended cost report submitted
within 12 months after the due date of the cost report solely for the
purpose of revising Medicaid days. (We note that an amendment of the
cost report is initiated by the provider prior to final settlement of
the cost report, while a reopening of the cost report occurs after
final settlement and can be requested by the provider or initiated by
the MAC.) Under this possible expansion, we would require MACs to
reopen cost reports for the purpose of revising the Medicaid fraction
near the end of the 3-year reopening window and use the Medicaid data
at that time to settle the cost report. We believe the 3 years of the
reopening period could provide adequate time to update the Medicaid
data used to determine an individual's Medicaid eligibility for
purposes of calculating a hospital's Medicaid fraction. However, we are
generally interested in public comments on using reopenings as a
mechanism to use updated Medicaid eligibility data and reduce the
filing of PRRB appeals--in particular, the optimal time for review of
data to occur taking into account the hospital's desire to receive
accurate payment and CMS' and the MACs' desire to settle cost reports
in a timely manner (for example, whether it makes sense to review data
2 years after cost report submission, near the end of the 3 years
mentioned in the reopening regulations, or at some other time).
We also are considering allowing hospitals, for a one-time option,
to resubmit a cost report with updated Medicaid eligibility
information, somewhat similar to our existing DSH policy allowing
hospitals a one-time option to have their SSI ratios calculated based
on their cost reporting period rather than the Federal fiscal year
under 42 CFR 412.106(a)(3). Under this option, we would undertake
rulemaking to determine the timeframe for exercising the option (which
may be a maximum allowable time after the close of a cost reporting
period or a specific window during which the request could be made). We
are interested in feedback and comments concerning the viability of
these options, as well as any alternative approaches, that could help
reduce the number of DSH-related appeals and inform our future
rulemaking efforts.
G. Hospital Readmissions Reduction Program: Proposed Updates and
Changes (Sec. Sec. 412.150 Through 412.154)
1. Statutory Basis for the Hospital Readmissions Reduction Program
Section 1886(q) of the Act, as amended by section 15002 of the 21st
Century Cures Act, establishes the Hospital Readmissions Reduction
Program. Under the Hospital Readmissions Reduction Program, Medicare
payments under the acute inpatient prospective payment system for
discharges from an applicable hospital, as defined under section
1886(d) of the Act, may be reduced to account for certain excess
readmissions. Section 15002 of the 21st Century Cures Act requires the
Secretary to compare hospitals with respect to the number of their
Medicare-Medicaid dual-eligible beneficiaries (dual-eligibles) in
determining the extent of excess readmissions. We refer readers to the
FY 2016 IPPS/LTCH PPS final rule (80 FR 49530 through 49531) and the FY
2018 IPPS/LTCH PPS final rule (82 FR 38221 through 38240) for a
detailed discussion of and additional information on the statutory
history of the Hospital Readmissions Reduction Program.
2. Regulatory Background
We refer readers to the following final rules for detailed
discussions of the regulatory background and descriptions of the
current policies for the Hospital Readmissions Reduction Program:
FY 2012 IPPS/LTCH PPS final rule (76 FR 51660 through
51676);
FY 2013 IPPS/LTCH PPS final rule (77 FR 53374 through
53401);
FY 2014 IPPS/LTCH PPS final rule (78 FR 50649 through
50676);
FY 2015 IPPS/LTCH PPS final rule (79 FR 50024 through
50048);
FY 2016 IPPS/LTCH PPS final rule (80 FR 49530 through
49543);
FY 2017 IPPS/LTCH PPS final rule (81 FR 56973 through
56979);
FY 2018 IPPS/LTCH PPS final rule (82 FR 38221 through
38240); and
FY 2019 IPPS/LTCH PPS final rule (83 FR 41431 through
41439).
These rules describe the general framework for the implementation
of the Hospital Readmissions Reduction Program, including: (1) The
selection of measures for the applicable conditions/procedures; (2) the
calculation of the excess readmission ratio (ERR), which is used, in
part, to calculate the payment adjustment factor; (3) beginning in FY
2019, the calculation of the proportion of ``dually eligible'' Medicare
beneficiaries which is used to stratify hospitals into peer groups and
establish the peer group median ERRs; (4) the calculation of the
payment adjustment factor, specifically addressing the base operating
DRG payment amount, aggregate payments for excess readmissions
(including calculating the peer group median ERRs), aggregate payments
for all discharges, and the neutrality modifier; (5) the opportunity
for hospitals to review and submit corrections using a process similar
to what is currently used for posting results on Hospital Compare; (6)
the adoption of an extraordinary circumstances exception policy to
address hospitals that experience a disaster or other extraordinary
circumstance; (7) the clarification that the public reporting of ERRs
will be posted on an annual basis to the Hospital Compare website as
soon as is feasible following the review and corrections period; and
(8) the specification that the definition of ``applicable hospital''
does not include hospitals and hospital units excluded from the IPPS,
such as LTCHs, cancer hospitals, children's hospitals, IRFs, IPFs,
CAHs, and hospitals in United States territories and Puerto Rico.
We also have codified certain requirements of the Hospital
Readmissions Reduction Program at 42 CFR 412.152 through 412.154, which
we are proposing to update in this proposed rule to reflect both
proposed and previously finalized policies.
The Hospital Readmissions Reduction Program strives to put patients
first by ensuring they are empowered to make decisions about their own
healthcare along with their clinicians, using information from data-
driven insights that are increasingly aligned with meaningful quality
measures. We believe the Hospital Readmissions Reduction Program
incentivizes hospitals to improve health care quality and value, while
giving patients the tools and information needed to make the best
decisions for them. To that end, we are committed to monitoring the
efficacy of the program to ensure that the Hospital Readmissions
Reduction Program improves the lives of patients and reduces cost.
[[Page 19424]]
3. Summary of Proposed Policies for the Hospital Readmissions Reduction
Program
In this proposed rule, we are proposing the following policies: (1)
A measure removal policy that aligns with the removal factor policies
previously adopted in other quality reporting and quality payment
programs; (2) an update to the program's definition of ``dual-
eligible'' beginning with the FY 2021 program year, to allow for a 1-
month lookback period in data sourced from the State Medicare
Modernization Act (MMA) files to determine dual-eligible status for
beneficiaries who die in the month of discharge; (3) a subregulatory
process to address any potential future nonsubstantive changes to the
payment adjustment factor components; and (4) an update to the
regulations at 42 CFR 412.152 and 412.154 to reflect proposed policies
and to codify additional previously finalized policies.
We discuss these proposals in greater detail below.
4. Current Measures and Proposed Measure Policies for FY 2020 and
Subsequent Years
a. Current Measures
The Hospital Readmissions Reduction Program currently includes six
applicable conditions/procedures: Acute myocardial infarction (AMI);
heart failure (HF); pneumonia; elective primary total hip arthroplasty/
total knee arthroplasty (THA/TKA); chronic obstructive pulmonary
disease (COPD); and coronary artery bypass graft (CABG) surgery. We
refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41431
through 41439) for more information about how the Hospital Readmissions
Reduction Program supports CMS' goal of bringing quality measurement,
transparency, and improvement together with value-based purchasing to
the hospital inpatient care setting through the Meaningful Measures
Initiative. We continue to believe the measures we have adopted
adequately meet the goals of the Hospital Readmissions Reduction
Program. Therefore, we are not proposing to remove or adopt any
additional measures at this time.
b. Proposed Measure Removal Factors Policy
While we are not proposing to remove any measures from the Hospital
Readmissions Reduction Program in this proposed rule, we are proposing
to adopt a measure removal factors policy as part of our efforts to
ensure that the Hospital Readmissions Reduction Program measure set
continues to promote improved health outcomes for beneficiaries while
minimizing the overall burden and costs associated with the program.
The adoption of measure removal factors would align the Hospital
Readmissions Reduction Program with our other quality reporting and
quality payment programs and help ensure consistency in our measure
evaluation methodology across programs.
In the FY 2019 IPPS/LTCH PPS final rule, we updated a number of CMS
programs' considerations for removing measures from the respective
programs. Specifically, we finalized eight measure removal factors for
the Hospital IQR Program (83 FR 41540 through 41544), the Hospital VBP
Program (83 FR 41441 through 41446), the PCHQR Program (83 FR 41609
through 41611), and the LTCH QRP (83 FR 41625 through 41627).
We believe these removal factors are also appropriate for the
Hospital Readmissions Reduction Program, and we believe that alignment
between CMS quality programs is important to provide stakeholders with
a clear, consistent, and transparent process. Therefore, to align with
our other quality reporting and quality payment programs, we are
proposing to adopt the following removal factors for the Hospital
Readmissions Reduction Program:
Factor 1. Measure performance among hospitals is so high
and unvarying that meaningful distinctions and improvements in
performance can no longer be made (``topped-out'' measures);
Factor 2. Measure does not align with current clinical
guidelines or practice;
Factor 3. Measure can be replaced by a more broadly
applicable measure (across settings or populations) or a measure that
is more proximal in time to desired patient outcomes for the particular
topic;
Factor 4. Measure performance or improvement does not
result in better patient outcomes;
Factor 5. Measure can be replaced by a measure that is
more strongly associated with desired patient outcomes for the
particular topic;
Factor 6. Measure collection or public reporting leads to
negative unintended consequences other than patient harm; \395\
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\395\ When there is reason to believe that the continued
collection of a measure as it is currently specified raises
potential patient safety concerns, CMS will take immediate action to
remove a measure from the program and not wait for the annual
rulemaking cycle. In such situations, we would promptly retire such
measures followed by subsequent confirmation of the retirement in
the next IPPS rulemaking. When we do so, we will notify hospitals
and the public through the usual hospital and QIO communication
channels used for the Hospital Readmissions Reduction Program, which
include memo and email notification and QualityNet website articles
and postings.
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Factor 7. Measure is not feasible to implement as
specified; and
Factor 8. The costs associated with a measure outweigh the
benefit of its continued use in the program.\396\
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\396\ We refer readers to the Hospital IQR Program's measure
removal factors discussions in the FY 2016 IPPS/LTCH PPS final rule
(80 FR 49641 through 49643) and the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41540 through 41544) for additional details on the removal
factors and the rationale supporting them.
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We note that these factors are considerations taken into account
when deciding whether or not to remove measures, not firm requirements,
and that we will propose to remove measures based on these factors on a
case-by-case basis. We continue to believe that there may be
circumstances in which a measure that meets one or more factors for
removal should be retained regardless, because the benefits of a
measure can outweigh its drawbacks. Our goal is to move the program
forward in the least burdensome manner possible, while maintaining a
parsimonious set of meaningful quality measures and continuing to
incentivize improvement in the quality of care provided to patients.
5. Proposed Updated Definition of ``Dual-Eligible'' Beginning in FY
2021
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38226 through
38229), as part of implementing the 21st Century Cures Act, we
finalized the definition of dual-eligible as follows: ``Dual-eligible
is a patient beneficiary who has been identified as having full benefit
status in both the Medicare and Medicaid programs in the State Medicare
Modernization Act (MMA) files for the month the beneficiary was
discharged from the hospital.'' In the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41437 through 41438), we finalized our proposal to codify this
definition at 42 CFR 412.152 along with other definitions pertinent to
dual-eligibility calculations for assigning hospitals into peer groups.
In this proposed rule, we are proposing to update our previously
finalized definition of ``dual-eligible'' to specify that, for the
payment adjustment factors beginning with the FY 2021 program year,
``dual-eligible'' is a patient beneficiary who has been identified as
having full benefit status in both the Medicare and Medicaid programs
in data sourced from the State MMA files for the month the beneficiary
was discharged from the hospital, except for those patient
beneficiaries
[[Page 19425]]
who die in the month of discharge, who will be identified using the
previous month's data sourced from the State MMA files.\397\
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\397\ In addition, it has come to our attention that the
determination of dual eligibility is made from data sourced from the
State MMA files, not the original State MMA files. The program also
considers this to be a nonsubstantive change as the data are
obtained from the specified source.
---------------------------------------------------------------------------
The updated definition is necessary to account for
misidentification of the dual-eligible status of patient beneficiaries
who die in the month of discharge, which can occur under the current
definition. We were not aware at the time we finalized our current
definition of ``dual-eligible'' that there are times when the data
sourced from the State MMA files may underreport the number of
beneficiaries with dual-eligibility status for the month in which the
beneficiaries dies, and, therefore, these data are not fully accurate
reflections of dual-eligible status for the month in which a
beneficiary dies. We have identified two situations that lead to the
underreporting of dual-eligible patients: (1) The dual-eligible status
is not recorded in the month of death; and (2) the dual-eligible status
changes from dual in the months prior to death to non-dual in the month
of death. While the number of misidentified patient beneficiaries is
very small and did not have a substantive impact, we believe that using
the most accurate information available is the most appropriate policy
for the program and consistent with our initial rationale for using the
State MMA files as the source to identify dual-eligibles. When we
adopted the current definition of ``dual-eligible'' in the FY 2018
IPPS/LTCH PPS final rule (82 FR 38226), we stated, and many commenters
agreed, that the State MMA file is considered the most current and most
accurate source of data for identifying dual-eligible beneficiaries
because the data are also used for operational purposes related to the
administration of Medicare Part D benefits.
Our intent was and remains to use the most accurate data available
to determine ``dual-eligible'' status in the hospital grouping portion
of the payment adjustment. Through our analysis, we believe using a 1-
month lookback period within the data sourced from the State MMA files
to determine dual-eligible status for beneficiaries who die in the
month of discharge will improve the accuracy of the number of
beneficiaries identified as having dual-eligible status. We note that
we are proposing to update this definition for FY 2021 instead of FY
2020 because of the time associated with updates to the data systems is
inconsistent with our ability to finalize this proposal in time for FY
2020 and the lack of a subregulatory policy, which would allow us to
make nonsubstantive changes outside of the rulemaking schedule.
We are proposing to revise the definition of ``dual-eligible''
codified at 42 CFR 412.152 to incorporate this update.
6. Proposed Adoption of a Subregulatory Process for Changes to Payment
Adjustment Factor Components
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41434), we
reiterated our policy regarding the maintenance of technical
specifications for quality measures. In adopting our policy for the
maintenance of technical specifications in the FY 2015 IPPS/LTCH PPS
final rule (79 FR 50039), we stated that it is important to have in
place a subregulatory process to incorporate nonsubstantive updates
required by the National Quality Forum into the measure specifications
we have adopted for the Hospital Readmissions Reduction Program, so
that these measures remain up to date. We also stated that we would
continue to use notice-and-comment rulemaking for any substantive
changes to measure specification. We continue to believe this process
is the most expeditious manner possible to ensure that quality measures
remain fully up to date while preserving the public's ability to
comment on updates that so fundamentally change a measure that it is no
longer the same measure that we originally adopted. When we adopted
this policy, we received commenter support for our policy of handling
substantive and nonsubstantive changes to measures. The policy allows
CMS two mechanisms to address measure updates: (1) The use of future
proposed rules and public comment periods for substantive changes; and
(2) subregulatory processes for nonsubstantive changes which also
preserve CMS' autonomy and flexibility, in order to rapidly implement
nonsubstantive updates to measures (79 FR 50039).
We now believe it is important for the Hospital Readmissions
Reduction Program to adopt an analogous subregulatory process for
changes to the payment adjustment factor components to provide similar
flexibility to rapidly implement nonsubstantive updates to implement
data sourcing and other minor changes when payment adjustment factor
components are impacted. We are proposing to adopt a policy under which
we would use a subregulatory process to make nonsubstantive changes to
the payment adjustment factor components used for the Hospital
Readmissions Reduction Program. We previously adopted our payment
adjustment factor components policies through the notice-and-comment
rulemaking process. The Hospital Readmissions Reduction Program relies
on these payment adjustment factor components, including, but not
limited to, dual proportion, peer group assignment, peer group median
ERR, neutrality modifier, and ratio of DRG payments to total payments,
to determine hospital payments in each fiscal year. Each year, we
provide details on most of that information in the Hospital Specific
Report (HSR) User Guide located on QualityNet website at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228772412669. However, there are times when data sourcing and other technical
aspects of the payment adjustment factor components change and require
updating, even when those changes do not alter the intent of our
previously finalized policies. Because the updates to data sourcing and
technical aspects of the components are not always linked to the timing
of regulatory actions, we believe this proposed policy is prudent to
allow for the use of the most up-to-date, accurate information. We
reiterate that we would continue to consider all changes to the
framework of the components themselves as substantive changes that we
would propose through the notice-and-comment rulemaking process.
Most recently, as discussed earlier, we identified an issue with
data accuracy for determining dual-eligible status from data sourced
from the State MMA files for beneficiaries who die in the same month as
discharge. In this proposed rule, we are proposing to amend the
definition of ``dual-eligible'' to account for this data issue.
However, we would like to clarify that the proposal is not altering the
intent of our previously finalized policy. Instead, the proposed
updated definition of ``dual-eligible'' allows for the use of the month
preceding discharge for identifying dual-eligibles who died during the
discharge month after learning that the current files misidentified the
dual-eligibility status of certain patient beneficiaries who die in the
month of discharge. Although we have identified this issue, and do not
believe that it is a substantive change to our policy for determining
dual-eligibles, we believe
[[Page 19426]]
that we should utilize the notice-and-comment rulemaking process to
address this clarification because we do not currently have a
subregulatory policy in place to address this type of data issue.
However, we believe that a subregulatory process for addressing
nonsubstantive data issues like the dual-eligible update could be used
for similar situations in the future. We would publish these
nonsubstantive data changes in the HSR User Guide annually. We note
that we would continue to use notice-and-comment rulemaking for
substantive changes.
With respect to what constitutes substantive changes versus
nonsubstantive changes, we expect to make this determination on a case-
by-case basis. In other quality reporting and quality payment programs
(77 FR 53504), we stated that substantive changes are those that are so
significant that the measures could no longer be considered the same
measure. For this proposed policy, we would utilize the same principle;
we would deem a change to be substantive and to require notice-and-
comment rulemaking when the impact of the change to the payment
adjustment factor component was so significant that it could no longer
be considered to be the same as the previously finalized component.
Examples of nonsubstantive changes would include, but not be limited
to, updated naming or locations of data files and/or other minor
discrepancies that do not change the intent of the policy. Examples of
substantive changes to data might include use of different
methodologies to use data than finalized for the payment adjustment
factor component or the use of a different component in the methodology
for payment calculations.
7. Proposed Applicable Period for FY 2022
We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR
51671) and the FY 2013 IPPS/LTCH PPS final rule (77 FR 53675) for
discussion of our previously finalized policy for defining applicable
periods. In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41434 through
41435), we finalized the following ``applicable periods'' to calculate
the readmission payment adjustment factor for FY 2019, FY 2020, and FY
2021, respectively:
The 3-year time period of July 1, 2014 through June 30,
2017 for FY 2019;
The 3-year time period of July 1, 2015 through June 30,
2018 for FY 2020; and
The 3-year time period of July 1, 2016 through June 30,
2019 for FY 2021.
These are the 3-year periods from which data are being collected in
order to calculate ERRs and payment adjustment factors for the fiscal
year; this includes aggregate payments for excess readmissions and
aggregate payments for all discharges used in the calculation of the
payment adjustment. The ``applicable period'' for dual-eligibles is the
same as the ``applicable period'' that we otherwise adopt for purposes
of the Hospital Readmissions Reduction Program.
We are proposing, for FY 2022, consistent with the definition
specified at Sec. 412.152, that the ``applicable period'' for the
Hospital Readmissions Reduction Program would be the 3-year period from
July 1, 2017 through June 30, 2020. The applicable period for dual-
eligibles for FY 2022 would similarly be the 3-year period from July 1,
2017 through June 30, 2020.
8. Identification of Aggregate Payments for Each Condition/Procedure
and All Discharges for FY 2020
When calculating the numerator (aggregate payments for excess
readmissions), we determine the base operating DRG payment amount for
an individual hospital for the applicable period for such condition/
procedure, using Medicare inpatient claims from the MedPAR file with
discharge dates that are within the applicable period. Under our
established methodology, we use the update of the MedPAR file for each
Federal fiscal year, which is updated 6 months after the end of each
Federal fiscal year within the applicable period, as our data source.
In identifying discharges for the applicable conditions/procedures
to calculate the aggregate payments for excess readmissions, we apply
the same exclusions to the claims in the MedPAR file as are applied in
the measure methodology for each of the applicable conditions/
procedures. For the FY 2020 applicable period, this includes the
discharge diagnoses for each applicable condition/procedure based on a
list of specific ICD-9-CM or ICD-10-CM and ICD-10-PCS code sets, as
applicable, for that condition/procedure, because diagnoses and
procedure codes for discharges occurring prior to October 1, 2015 were
reported under the ICD-9-CM code set, while discharges occurring on or
after October 1, 2015 (FY 2016), were reported under the ICD-10-CM and
ICD-10-PCS code sets.
We identify Medicare fee-for-service (FFS) claims that meet the
criteria described above for each applicable condition/procedure to
calculate the aggregate payments for excess readmissions (that is,
claims paid for under Medicare Part C (Medicare Advantage) are not
included in this calculation). This policy is consistent with the
methodology to calculate ERRs based solely on admissions and
readmissions for Medicare FFS patients. Therefore, consistent with our
established methodology, for FY 2020, we are proposing to continue to
exclude admissions for patients enrolled in Medicare Advantage, as
identified in the Medicare Enrollment Database.
In this proposed rule, for FY 2020, we are proposing to determine
aggregate payments for excess readmissions, aggregate payments for all
discharges using data from MedPAR claims with discharge dates that are
on or after July 1, 2015, and not later than June 30, 2018. As we
stated in FY 2018 IPPS/LTCH PPS final rule (82 FR 38232), we will
determine the neutrality modifier using the most recently available
full year of MedPAR data. However, we note that, for the purpose of
modeling the proposed FY 2020 readmissions payment adjustment factors
for this proposed rule, we are using the proportion of dual-eligibles,
excess readmission ratios, and aggregate payments for each condition/
procedure and all discharges for applicable hospitals from the FY 2019
Hospital Readmissions Reduction Program applicable period. For the FY
2020 program year, applicable hospitals will have the opportunity to
review and correct calculations based on the proposed FY 2020
applicable period of July 1, 2015 to June 30, 2018, before they are
made public under our policy regarding reporting of hospital-specific
information. Again, we reiterate that this period is intended to review
the program calculations, and not the underlying data. For more
information on the review and corrections process, we refer readers to
the FY 2013 IPPS/LTCH PPS final rule (77 FR 53399 through 53401).
In this proposed rule, for FY 2020, we are proposing to use MedPAR
data from July 1, 2015 through June 30, 2018 for the FY 2020 Hospital
Readmissions Reduction Program calculations. Specifically--
The March 2016 update of the FY 2015 MedPAR file to
identify claims within FY 2015 with discharges dates that are on or
after July 1, 2015;
The March 2017 update of the FY 2016 MedPAR file to
identify claims within FY 2016;
The March 2018 update of the FY 2017 MedPAR file to
identify claims within FY 2017; and
The March 2019 update of the FY 2018 MedPAR file to
identify claims
[[Page 19427]]
within FY 2018 with discharge dates that are on or before June 30,
2018.
9. Calculation of Payment Adjustment Factors for FY 2020
As we discussed in the FY 2018 IPPS/LTCH PPS final rule (82 FR
38226), section 1886(q)(3)(D) of the Act requires the Secretary to
group hospitals and apply a methodology that allows for separate
comparisons of hospitals within peer groups in determining a hospital's
adjustment factor for payments applied to discharges beginning in FY
2019.
To implement this provision, in the FY 2018 IPPS/LTCH PPS final
rule (82 FR 38226 through 38237), we finalized several changes to the
payment adjustment methodology for FY 2019. First, we finalized that an
individual would be counted as a full-benefit dual-eligible patient if
the beneficiary was identified as full-benefit dual status in the State
Medicare Modernization Act (MMA) files for the month he or she was
discharged from the hospital (82 FR 38226 through 38228). Second, we
finalized our policy to define the proportion of full benefit dual-
eligible beneficiaries as the proportion of dual-eligible patients
among all Medicare FFS and Medicare Advantage stays (82 FR 38226
through 38228). Third, we finalized our policy to define the data
period for determining dual-eligibility as the 3-year data period
corresponding to the Program's applicable period (82 FR 38229). Fourth,
we finalized our policy to stratify hospitals into quintiles, or five
peer groups, based on their proportion of dual-eligible patients (82 FR
38229 through 38231). Finally, we finalized our policy to use the
median ERR for the hospital's peer group in place of 1.0 in the payment
adjustment formula and apply a uniform modifier to maintain budget
neutrality (82 FR 38231 through 38237). The payment adjustment formula
would then be:
[GRAPHIC] [TIFF OMITTED] TP03MY19.021
where dx is AMI, HF, pneumonia, COPD, THA/TKA or CABG and payments
refers to the base operating DRG payments. The payment reduction (1-P)
resulting from use of the median ERR for the peer group is scaled by a
neutrality modifier to achieve budget neutrality. We refer readers to
the FY 2018 IPPS/LTCH PPS final rule (82 FR 38226 through 38237) for a
detailed discussion of the payment adjustment methodology. We are not
proposing any changes to this payment adjustment calculation
methodology for FY 2020.
10. Calculation of Payment Adjustment for FY 2020
Section 1886(q)(3)(A) of the Act defines the payment adjustment
factor for an applicable hospital for a fiscal year as ``equal to the
greater of: (i) The ratio described in subparagraph (B) for the
hospital for the applicable period (as defined in paragraph (5)(D)) for
such fiscal year; or (ii) the floor adjustment factor specified in
subparagraph (C).'' Section 1886(q)(3)(B) of the Act, in turn,
describes the ratio used to calculate the adjustment factor.
Specifically, it states that the ratio is equal to 1 minus the ratio
of--(i) the aggregate payments for excess readmissions, and (ii) the
aggregate payments for all discharges, scaled by the neutrality
modifier. The calculation of this ratio is codified at Sec.
412.154(c)(1) of the regulations and the floor adjustment factor is
codified at Sec. 412.154(c)(2) of the regulations. Section
1886(q)(3)(C) of the Act specifies the floor adjustment factor at 0.97
for FY 2015 and subsequent fiscal years.
Consistent with section 1886(q)(3) of the Act, codified in our
regulations at Sec. 412.154(c)(2), for FY 2020, the payment adjustment
factor will be either the greater of the ratio or the floor adjustment
factor of 0.97. Under our established policy, the ratio is rounded to
the fourth decimal place. In other words, for FY 2020, a hospital
subject to the Hospital Readmissions Reduction Program would have an
adjustment factor that is between 1.0 (no reduction) and 0.9700
(greatest possible reduction).
For additional information on the FY 2020 payment calculation, we
refer readers to the QualityNet website at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename= QnetPublic%2FPage%2FQnetTier3&cid=
1228776124112.
11. Confidential Reporting of Stratified Data for Hospital Quality
Measures
Beginning as early as the spring of 2020, CMS plans to include in
confidential hospital-specific reports (HSR) data stratified by patient
dual eligible status for the six readmissions measures included in the
Hospital Readmissions Reduction Program. These data will include two
disparity methodologies designed to illuminate potential disparities
within individual hospitals and across hospitals nationally and will
supplement the measure data currently publicly reported on the Hospital
Compare website. The first methodology, the Within-Hospital Disparity
Method highlights differences in outcomes for dual eligible versus non-
dual eligible patients within an individual hospital, while the second
methodology, the Dual Eligible Outcome Method, allows for a comparison
of performance in care for dual-eligible patients across hospitals (82
FR 38405 through 38407; 83 FR 41598). These two disparity methods are
separate from the stratified methodology used by the Hospital
Readmissions Reduction Program, and we emphasize that the two disparity
methods would not be used in payment adjustment factors calculations
under the Hospital Readmissions Reduction Program. We believe that
providing the results of both disparity methods alongside a hospital's
measure data as a point of reference allows for a more meaningful
comparison and comprehensive assessment of the quality of care for
patients with social risk factors and the identification of providers
where disparities in health care may exist. We also believe the two
disparity methods provide additional perspectives on health care equity
(83 FR 41598).
We believe hospitals can use their results from the disparity
methods to identify and develop strategies to reduce disparities in the
quality of care for patients through targeted improvement efforts (83
FR 41598). The two disparity methods and the stratified methodology
used by the Hospital Readmissions Reduction Program are part of CMS'
broader effort to account for social risk factors in quality
measurement and quality payment programs. We refer readers to section
VIII.A.9. of the preamble of this proposed rule for more information on
confidential reporting of stratified data for hospital quality
measures. We further refer readers to the FY 2017 IPPS/LTCH PPS final
rule (81 FR 57167 through 57168), the FY 2018 IPPS/LTCH PPS final rule
(82 FR 38324 through 38326; 82 FR 38403 through 38409), and the FY 2019
IPPS/LTCH PPS final rule (83 FR 41597 through 41601) for detailed
discussions on disparity reporting.
[[Page 19428]]
We note that the two disparity methods do not place any additional
collection or reporting burden on hospitals because dual-eligibility
data are readily available in claims data. In addition, we reiterate
that these confidential hospital-specific reports data do not impact
the calculation of hospital payment adjustment factors under the
Hospital Readmissions Reduction Program.
12. Proposed Revisions of Regulatory Text
We are proposing to revise 42 CFR 412.152 to reflect proposed
policies and to codify previously finalized policies. Specifically, we
are proposing to revise the definition of ``aggregate payments for
excess readmissions'', as discussed earlier, to specify that it means
the sum of the product for each applicable condition, among others, of
``the excess readmission ratio for the hospital for the applicable
period minus the peer group median excess readmission ratio'' (instead
of minus 1) (proposed paragraph (3) of the definition) and to include
the neutrality modifier--a multiplicative factor that equates total
Medicare savings under the current stratified methodology to the
previous non-stratified methodology (proposed paragraph (4) of the
definition).
We are proposing to revise the definition of ``applicable
condition'' to include other conditions and procedures as determined
appropriate by the Secretary. In expanding the applicable conditions,
the Secretary will seek endorsement of the entity with a contract under
section 1890(a) of the Act, but may apply such measures without such an
endorsement in the case of a specified area or medical topic determined
appropriate by the Secretary for which a feasible and practical measure
has not been endorsed by the entity with a contract under section
1890(a) of the Act as long as due consideration is given to measures
that have been endorsed or adopted by a consensus organization
identified by the Secretary.
We are proposing to revise the definition of ``base operating DRG
payment amount'', with respect to a sole community hospital that
receives payments under Sec. 412.92(d) or a Medicare-dependent, small
rural hospital that receives payments under Sec. 412.108(c), to remove
the applicability date of FY 2013, and to specify that this amount also
includes the difference between the hospital-specific payment rate and
the Federal payment rate determined under the subpart. This proposal is
intended to align the regulatory text with section 1886(q)(2)(b)(i) of
the Act, because the regulatory text was not updated following the
expiration of the FY 2013 changes.
We are proposing to revise the definition of ``dual-eligible'' to
specify that, for payment adjustment factors beginning in FY 2021,
dual-eligible is a patient beneficiary who has been identified as
having full benefit status in both the Medicare and Medicaid programs
in data sourced from the State MMA files for the month the beneficiary
was discharged from the hospital except for those patient beneficiaries
who die in the month of discharge, which will be identified using the
previous month's data as sourced from the State MMA files, as discussed
earlier.
We are proposing to revise Sec. 412.154(e) to specify that the
limitations on administrative or judicial review would include the
neutrality modifier and the proportion of dual-eligibles as discussed
earlier (proposed new paragraphs (e)(4) and (5); existing paragraph
(e)(4) would be redesignated as paragraph (e)(6)).
H. Hospital Value-Based Purchasing (VBP) Program: Proposed Policy
Changes
1. Background
a. Statutory Background and Overview of Past Program Years
Section 1886(o) of the Act requires the Secretary to establish a
hospital value-based purchasing program (the Hospital VBP Program)
under which value-based incentive payments are made in a fiscal year
(FY) to hospitals that meet performance standards established for a
performance period for such fiscal year. Both the performance standards
and the performance period for a fiscal year are to be established by
the Secretary.
For more of the statutory background and descriptions of our
current policies for the Hospital VBP Program, we refer readers to the
Hospital Inpatient VBP Program final rule (76 FR 26490 through 26547);
the FY 2012 IPPS/LTCH PPS final rule (76 FR 51653 through 51660); the
CY 2012 OPPS/ASC final rule with comment period (76 FR 74527 through
74547); the FY 2013 IPPS/LTCH PPS final rule (77 FR 53567 through
53614); the FY 2014 IPPS/LTCH PPS final rule (78 FR 50676 through
50707); the CY 2014 OPPS/ASC final rule (78 FR 75120 through 75121);
the FY 2015 IPPS/LTCH PPS final rule (79 FR 50048 through 50087); the
FY 2016 IPPS/LTCH PPS final rule (80 FR 49544 through 49570); the FY
2017 IPPS/LTCH PPS final rule (81 FR 56979 through 57011); the CY 2017
OPPS/ASC final rule with comment period (81 FR 79855 through 79862);
the FY 2018 IPPS/LTCH PPS final rule (82 FR 38240 through 38269); and
the FY 2019 IPPS/LTCH PPS final rule (83 FR 41440 through 41472).
We also have codified certain requirements for the Hospital VBP
Program at 42 CFR 412.160 through 412.167.
b. FY 2020 Program Year Payment Details
Section 1886(o)(7)(B) of the Act instructs the Secretary to reduce
the base operating DRG payment amount for a hospital for each discharge
in a fiscal year by an applicable percent. Under section 1886(o)(7)(A)
of the Act, the sum total of these reductions in a fiscal year must
equal the total amount available for value-based incentive payments for
all eligible hospitals for the fiscal year, as estimated by the
Secretary. We finalized details on how we would implement these
provisions in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53571 through
53573), and we refer readers to that rule for further details.
Under section 1886(o)(7)(C)(v) of the Act, the applicable percent
for the FY 2020 program year is 2.00 percent. Using the methodology we
adopted in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53571 through
53573), we estimate that the total amount available for value-based
incentive payments for FY 2020 is approximately $1.9 billion, based on
the December 2018 update of the FY 2018 MedPAR file. We intend to
update this estimate for the FY 2020 IPPS/LTCH PPS final rule using the
March 2019 update of the FY 2018 MedPAR file.
As finalized in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53573
through 53576), we will utilize a linear exchange function to translate
this estimated amount available into a value-based incentive payment
percentage for each hospital, based on its Total Performance Score
(TPS). We will then calculate a value-based incentive payment
adjustment factor that will be applied to the base operating DRG
payment amount for each discharge occurring in FY 2020, on a per-claim
basis. We are publishing proxy value-based incentive payment adjustment
factors in Table 16 associated with this proposed rule (which is
available via the internet on the CMS website). The proxy factors are
based on the TPSs from the FY 2019 program year. These FY 2019
performance scores are the most recently available performance scores
hospitals have been given the opportunity to review and correct. The
slope of the linear exchange function used to calculate the proxy
value-based incentive payment adjustment factors in
[[Page 19429]]
Table 16 is 2.8391388973. This slope, along with the estimated amount
available for value-based incentive payments, is also published in
Table 16.
We intend to update this table as Table 16A in the final rule
(which will be available on the CMS website) to reflect changes based
on the March 2019 update to the FY 2018 MedPAR file. We also intend to
update the slope of the linear exchange function used to calculate
those updated proxy value-based incentive payment adjustment factors.
The updated proxy value-based incentive payment adjustment factors for
FY 2020 will continue to be based on historic FY 2019 program year TPSs
because hospitals will not have been given the opportunity to review
and correct their actual TPSs for the FY 2020 program year until after
the FY 2020 IPPS/LTCH PPS final rule is published.
After hospitals have been given an opportunity to review and
correct their actual TPSs for FY 2020, we will post Table 16B (which
will be available via the internet on the CMS website) to display the
actual value-based incentive payment adjustment factors, exchange
function slope, and estimated amount available for the FY 2020 program
year. We expect Table 16B will be posted on the CMS website in the fall
of 2019.
2. Retention and Removal of Quality Measures
a. Retention of Previously Adopted Hospital VBP Program Measures and
Relationship Between the Hospital IQR and Hospital VBP Program Measure
Sets
In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53592), we finalized
a policy to retain measures from prior program years for each
successive program year, unless otherwise proposed and finalized. In
the FY 2019 IPPS/LTCH PPS final rule (83 FR 41440 through 41441), we
finalized a revision to our regulations at 42 CFR 412.164(a) to clarify
that once we have complied with the statutory prerequisites for
adopting a measure for the Hospital VBP Program (that is, we have
selected the measure from the Hospital IQR Program measure set and
included data on that measure on Hospital Compare for at least one year
prior to its inclusion in a Hospital VBP Program performance period),
the Hospital VBP Program statute does not require that the measure
continue to remain in the Hospital IQR Program. We are not proposing
any changes to these policies in this proposed rule.
b. Measure Removal Factors for the Hospital VBP Program
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41441 through
41446), in alignment with the Hospital IQR Program, we finalized the
following measure removal factors for the Hospital VBP Program:
Factor 1. Measure performance among hospitals is so high
and unvarying that meaningful distinctions and improvements in
performance can no longer be made (``topped out'' measures), defined
as: Statistically indistinguishable performance at the 75th and 90th
percentiles; and truncated coefficient of variation Factor 2. A measure does not align with current clinical
guidelines or practice;
Factor 3. The availability of a more broadly applicable
measure (across settings or populations), or the availability of a
measure that is more proximal in time to desired patient outcomes for
the particular topic;
Factor 4. Performance or improvement on a measure does not
result in better patient outcomes;
Factor 5. The availability of a measure that is more
strongly associated with desired patient outcomes for the particular
topic;
Factor 6. Collection or public reporting of a measure
leads to negative unintended consequences other than patient harm;
Factor 7. It is not feasible to implement the measure
specifications; and
Factor 8. The costs associated with a measure outweigh the
benefit of its continued use in the program.
We noted that these removal factors will be considerations taken
into account when deciding whether or not to remove measures, not firm
requirements. We continue to believe that there may be circumstances in
which a measure that meets one or more factors for removal should be
retained regardless, because the drawbacks of removing a measure could
be outweighed by other benefits to retaining the measure. In addition,
to further align with policies adopted in the Hospital IQR Program (74
FR 43864), in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41446), we
finalized a policy that if we believe continued use of a measure poses
specific patient safety concerns, we may promptly remove the measure
from the program without rulemaking and notify hospitals and the public
of the removal of the measure along with the reasons for its removal
through routine communication channels and then confirm the removal of
the measure from the Hospital VBP Program measure set in rulemaking. We
are not proposing any changes to these policies in this proposed rule.
c. Summary of Previously Adopted Measures for the FY 2022 and FY 2023
Program Years
We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR
41454 through 41456) and below for tables showing summaries of
previously adopted measures for the FY 2022 and FY 2023 program years.
We note that we are not proposing to add new measures to or remove
measures from the Hospital VBP Program in this proposed rule.
Summary of Previously Adopted Measures for the FY 2022 Program Year
------------------------------------------------------------------------
Measure short name Domain/measure name NQF No.
------------------------------------------------------------------------
Person and Community Engagement Domain
------------------------------------------------------------------------
HCAHPS......................... Hospital Consumer 0166 (0228)
Assessment of
Healthcare Providers
and Systems (HCAHPS)
(including Care
Transition Measure).
------------------------------------------------------------------------
Safety Domain
------------------------------------------------------------------------
CAUTI.......................... National Healthcare 0138
Safety Network (NHSN)
Catheter-Associated
Urinary Tract
Infection (CAUTI)
Outcome Measure.
CLABSI......................... National Healthcare 0139
Safety Network (NHSN)
Central Line-
Associated Bloodstream
Infection (CLABSI)
Outcome Measure.
[[Page 19430]]
Colon and Abdominal American College of 0753
Hysterectomy SSI. Surgeons--Centers for
Disease Control and
Prevention Harmonized
Procedure Specific
Surgical Site
Infection (SSI)
Outcome Measure.
MRSA Bacteremia................ National Healthcare 1716
Safety Network (NHSN)
Facility-wide
Inpatient Hospital-
onset Methicillin-
resistant
Staphylococcus aureus
(MRSA) Bacteremia
Outcome Measure.
CDI............................ National Healthcare 1717
Safety Network (NHSN)
Facility-wide
Inpatient Hospital-
onset Clostridium
difficile Infection
(CDI) Outcome Measure.
------------------------------------------------------------------------
Clinical Outcomes Domain
------------------------------------------------------------------------
MORT-30-AMI.................... Hospital 30-Day, All- 0230
Cause, Risk-
Standardized Mortality
Rate Following Acute
Myocardial Infarction
(AMI) Hospitalization.
MORT-30-HF..................... Hospital 30-Day, All- 0229
Cause, Risk-
Standardized Mortality
Rate Following Heart
Failure (HF)
Hospitalization.
MORT-30-PN (updated cohort).... Hospital 30-Day, All- 0468
Cause, Risk-
Standardized Mortality
Rate Following
Pneumonia
Hospitalization.
MORT-30-COPD................... Hospital 30-Day, All- 1893
Cause, Risk-
Standardized Mortality
Rate Following Chronic
Obstructive Pulmonary
Disease (COPD)
Hospitalization.
MORT-30-CABG................... Hospital 30-Day, All- 2558
Cause, Risk-
Standardized Mortality
Rate Following
Coronary Artery Bypass
Graft (CABG) Surgery.
COMP-HIP-KNEE *................ Hospital-Level Risk- 1550
Standardized
Complication Rate
Following Elective
Primary Total Hip
Arthroplasty (THA) and/
or Total Knee
Arthroplasty (TKA).
------------------------------------------------------------------------
Efficiency and Cost Reduction Domain
------------------------------------------------------------------------
MSPB........................... Medicare Spending Per 2158
Beneficiary (MSPB)--
Hospital.
------------------------------------------------------------------------
* We note that we are updating the short name of the Hospital-Level Risk-
Standardized Complication Rate Following Elective Primary Total Hip
Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA) measure (NQF
#1550) from THA/TKA to COMP-HIP-KNEE in order to maintain consistency
with the updated Measure ID and short name used in tables on the
Hospital Compare website and hospital reports for the Hospital VBP
Program. This updated name is used throughout section IV.H. of the
preamble of this proposed rule.
Summary of Previously Adopted Measures for the FY 2023 Program Year
----------------------------------------------------------------------------------------------------------------
Measure short name Domain/measure name NQF No.
----------------------------------------------------------------------------------------------------------------
Person and Community Engagement Domain
----------------------------------------------------------------------------------------------------------------
HCAHPS.................................................... Hospital Consumer Assessment of 0166 (0228)
Healthcare Providers and Systems
(HCAHPS) (including Care Transition
Measure).
----------------------------------------------------------------------------------------------------------------
Safety Domain
----------------------------------------------------------------------------------------------------------------
CAUTI..................................................... National Healthcare Safety Network 0138
(NHSN) Catheter-Associated Urinary
Tract Infection (CAUTI) Outcome
Measure.
CLABSI.................................................... National Healthcare Safety Network 0139
(NHSN) Central Line-Associated
Bloodstream Infection (CLABSI)
Outcome Measure.
Colon and Abdominal Hysterectomy SSI...................... American College of Surgeons-- 0753
Centers for Disease Control and
Prevention Harmonized Procedure
Specific Surgical Site Infection
(SSI) Outcome Measure.
MRSA Bacteremia........................................... National Healthcare Safety Network 1716
(NHSN) Facility-wide Inpatient
Hospital-onset Methicillin-
resistant Staphylococcus aureus
(MRSA) Bacteremia Outcome Measure.
CDI....................................................... National Healthcare Safety Network 1717
(NHSN) Facility-wide Inpatient
Hospital-onset Clostridium
difficile Infection (CDI) Outcome
Measure.
CMS PSI 90 *.............................................. CMS Patient Safety and Adverse 0531
Events Composite *.
----------------------------------------------------------------------------------------------------------------
Clinical Outcomes Domain
----------------------------------------------------------------------------------------------------------------
MORT-30-AMI............................................... Hospital 30-Day, All-Cause, Risk- 0230
Standardized Mortality Rate
Following Acute Myocardial
Infarction (AMI) Hospitalization.
MORT-30-HF................................................ Hospital 30-Day, All-Cause, Risk- 0229
Standardized Mortality Rate
Following Heart Failure (HF)
Hospitalization.
MORT-30-PN (updated cohort)............................... Hospital 30-Day, All-Cause, Risk- 0468
Standardized Mortality Rate
Following Pneumonia Hospitalization.
MORT-30-COPD.............................................. Hospital 30-Day, All-Cause, Risk- 1893
Standardized Mortality Rate
Following Chronic Obstructive
Pulmonary Disease (COPD)
Hospitalization.
MORT-30-CABG.............................................. Hospital 30-Day, All-Cause, Risk- 2558
Standardized Mortality Rate
Following Coronary Artery Bypass
Graft (CABG) Surgery.
COMP-HIP-KNEE............................................. Hospital-Level Risk-Standardized 1550
Complication Rate Following
Elective Primary Total Hip
Arthroplasty (THA) and/or Total
Knee Arthroplasty (TKA).
----------------------------------------------------------------------------------------------------------------
[[Page 19431]]
Efficiency and Cost Reduction Domain
----------------------------------------------------------------------------------------------------------------
MSPB...................................................... Medicare Spending Per Beneficiary 2158
(MSPB)--Hospital.
----------------------------------------------------------------------------------------------------------------
* We note that we have updated the name of the Patient Safety and Adverse Events Composite (PSI 90) to the CMS
Patient Safety and Adverse Events Composite (CMS PSI 90) when it is used in CMS programs due to transition of
the measure from AHRQ to CMS.
3. Previously Adopted Baseline and Performance Periods
a. Background
Section 1886(o)(4) of the Act requires the Secretary to establish a
performance period for the Hospital VBP Program that begins and ends
prior to the beginning of such fiscal year. We refer readers to the FY
2017 IPPS/LTCH PPS final rule (81 FR 56998 through 57003) for baseline
and performance periods that we have adopted for the FY 2019, FY 2020,
FY 2021, and FY 2022 program years. In the same final rule, we
finalized a schedule for all future baseline and performance periods
for previously adopted measures. We refer readers to the FY 2018 IPPS/
LTCH PPS final rule (82 FR 38256 through 38261) and the FY 2019 IPPS/
LTCH PPS final rule (83 FR 41466 through 41469) for additional baseline
and performance periods that we have adopted for the FY 2022, FY 2023,
and subsequent program years.
b. Person and Community Engagement Domain
Since the FY 2015 program year, we have adopted a 12-month baseline
period and a 12-month performance period for measures in the Person and
Community Engagement domain (previously referred to as the Patient- and
Caregiver-Centered Experience of Care/Care Coordination domain) (77 FR
53598; 78 FR 50692; 79 FR 50072; 80 FR 49561). In the FY 2017 IPPS/LTCH
PPS final rule (81 FR 56998), we finalized our proposal to adopt a 12-
month performance period for the Person and Community Engagement domain
that runs on the calendar year 2 years prior to the applicable program
year and a 12-month baseline period that runs on the calendar year 4
years prior to the applicable program year, for the FY 2019 program
year and subsequent years.
We are not proposing any changes to these policies in this proposed
rule.
c. Clinical Outcomes Domain
For the FY 2020 and FY 2021 program years, we adopted a 36-month
baseline period and a 36-month performance period for measures in the
Clinical Outcomes domain (previously referred to as the Clinical Care
domain) (79 FR 50073; 80 FR 49563 through 49564). In the FY 2017 IPPS/
LTCH PPS final rule (81 FR 57001), we also adopted a 22-month
performance period and a 36-month baseline period specifically for the
MORT-30-PN (updated cohort) measure for the FY 2021 program year.
In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57000), we adopted a
36-month performance period and a 36-month baseline period for the FY
2022 program year for each of the previously finalized measures in the
Clinical Outcomes domain--that is, the MORT-30-AMI, MORT-30-HF, MORT-
30-COPD, COMP-HIP-KNEE, and MORT-30-CABG measures. In the same final
rule, we adopted a 34-month performance period and a 36-month baseline
period for the MORT-30-PN (updated cohort) measure for the FY 2022
program year.
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38259), we adopted a
36-month performance period and a 36-month baseline period for the
MORT-30-AMI, MORT-30-HF, MORT-30-COPD, MORT-30-CABG, MORT-30-PN
(updated cohort), and COMP-HIP-KNEE measures for the FY 2023 program
year and subsequent years. Specifically, for the mortality measures
(MORT-30-AMI, MORT-30-HF, MORT-30-COPD, MORT-30-CABG, and MORT-30-PN
(updated cohort)), the performance period runs for 36 months from July
1, five years prior to the applicable fiscal program year, to June 30,
two years prior to the applicable fiscal program year, and the baseline
period runs for 36 months from July 1, ten years prior to the
applicable fiscal program year, to June 30, seven years prior to the
applicable fiscal program year. For the COMP-HIP-KNEE measure, the
performance period runs for 36 months from April 1, five years prior to
the applicable fiscal program year, to March 31, two years prior to the
applicable fiscal program year, and the baseline period runs for 36
months from April 1, ten years prior to the applicable fiscal program
year, to March 31, seven years prior to the applicable fiscal program
year.
We are not proposing any changes to the length of these performance
or baseline periods in this proposed rule.
d. Safety Domain
In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57000), we finalized
our proposal to adopt a performance period for all measures in the
Safety domain--with the exception of the CMS Patient Safety and Adverse
Events Composite (CMS PSI 90) measure--that runs on the calendar year 2
years prior to the applicable program year and a baseline period that
runs on the calendar year 4 years prior to the applicable program year
for the FY 2019 program year and subsequent program years.
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38258), for the FY
2023 program year, we adopted a 21-month baseline period (October 1,
2015 to June 30, 2017) and a 24-month performance period (July 1, 2019
to June 30, 2021) for the CMS PSI 90 measure. In the FY 2018 IPPS/LTCH
PPS final rule (82 FR 38258 through 38259), we adopted a 24-month
performance period and a 24-month baseline period for the CMS PSI 90
measure for the FY 2024 program year and subsequent years.
Specifically, the performance period runs from July 1, four years prior
to the applicable fiscal program year, to June 30, two years prior to
the applicable fiscal program year, and the baseline period runs from
July 1, eight years prior to the applicable fiscal program year, to
June 30, six years prior to the applicable fiscal program year.
We are not proposing any changes to these policies in this proposed
rule.
e. Efficiency and Cost Reduction Domain
Since the FY 2016 program year, we have adopted a 12-month baseline
period and a 12-month performance period for the MSPB measure in the
Efficiency and Cost Reduction domain (78 FR 50692; 79 FR 50072; 80 FR
49562). In the FY 2017 IPPS/LTCH PPS final rule (81 FR 56998), we
finalized our proposal to adopt a 12-month performance period for the
MSPB measure that runs on the calendar year 2 years prior to the
applicable program year and a 12-month baseline period
[[Page 19432]]
that runs on the calendar year 4 years prior to the applicable program
year for the FY 2019 program year and subsequent years.
We are not proposing any changes to these policies in this proposed
rule.
f. Summary of Previously Adopted Baseline and Performance Periods for
the FY 2022 Through FY 2025 Program Years
The tables below summarize the baseline and performance periods
that we have previously adopted.
[[Page 19433]]
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[[Page 19434]]
[GRAPHIC] [TIFF OMITTED] TP03MY19.023
[[Page 19435]]
[GRAPHIC] [TIFF OMITTED] TP03MY19.024
4. Performance Standards for the Hospital VBP Program
a. Background
Section 1886(o)(3)(A) of the Act requires the Secretary to
establish performance standards for the measures selected under the
Hospital VBP Program for a performance period for the applicable fiscal
year. The performance standards must include levels of achievement and
improvement, as required by section 1886(o)(3)(B) of the Act, and must
be established no later than 60 days before the beginning of the
performance period for the fiscal year involved, as required by section
1886(o)(3)(C) of the Act. We refer readers to the Hospital Inpatient
VBP Program final rule (76 FR 26511 through 26513) for further
discussion of achievement and improvement standards under the Hospital
VBP Program.
In addition, when establishing the performance standards, section
1886(o)(3)(D) of the Act requires the Secretary to consider appropriate
factors, such as: (1) Practical experience with the measures, including
whether a significant proportion of hospitals failed to meet the
performance standard during previous performance periods; (2)
historical performance standards; (3) improvement rates; and (4) the
opportunity for continued improvement.
We refer readers to the FY 2013, FY 2014, and FY 2015 IPPS/LTCH PPS
final rules (77 FR 53599 through 53605; 78 FR 50694 through 50699; and
79 FR 50077 through 50081, respectively) for a more detailed discussion
of the general scoring methodology used in the Hospital VBP Program. We
refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41469
through 41470) for previously established performance standards for the
FY 2021 program year.
We note that the performance standards for the following measures
are calculated with lower values representing better performance:
CDC NHSN HAI measures (CLABSI, CAUTI, CDI, MRSA
Bacteremia, and Colon and Abdominal Hysterectomy SSI);
CMS PSI 90 measure;
COMP-HIP-KNEE measure; and
MSPB measure.
This distinction is made in contrast to other measures--HCAHPS and
the mortality measures, which use survival rates rather than mortality
rates--for which higher values indicate better performance. As
discussed further in the FY 2014 IPPS/LTCH PPS final rule (78 FR
50684), the performance standards for the Colon and Abdominal
Hysterectomy SSI measure are computed separately for each procedure
stratum, and we first award achievement and improvement points to each
stratum separately, and then compute a weighted average of the points
awarded to each stratum by predicted infections.
b. Previously Established and Estimated Performance Standards for the
FY 2022 Program Year
In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57009), we
established performance standards for the FY 2022
[[Page 19436]]
program year for the Clinical Outcomes domain measures (MORT-30-AMI,
MORT-30-HF, MORT-30-PN (updated cohort), MORT-30-COPD, MORT-30-CABG,
and COMP-HIP-KNEE) and the Efficiency and Cost Reduction domain measure
(MSPB). We note that the performance standards for the MSPB measure are
based on performance period data. Therefore, we are unable to provide
numerical equivalents for the standards at this time.
In accordance with our methodology for calculating performance
standards discussed more fully in the Hospital Inpatient VBP Program
final rule (76 FR 26511 through 26513) and codified at 42 CFR 412.160,
we are estimating additional performance standards for the FY 2022
program year. We note that the numerical values for the performance
standards for the Safety and Person and Community Engagement domains
for the FY 2022 program year in the tables below are estimates based on
the most recently available data, and we intend to update the numerical
values in the FY 2020 IPPS/LTCH PPS final rule.
The previously established and estimated performance standards for
the measures in the FY 2022 program year are set out in the tables
below.
[GRAPHIC] [TIFF OMITTED] TP03MY19.025
[[Page 19437]]
The eight dimensions of the HCAHPS measure are calculated to
generate the HCAHPS Base Score. For each of the eight dimensions,
Achievement Points (0-10 points) and Improvement Points (0-9 points)
are calculated, the larger of which is then summed across the eight
dimensions to create the HCAHPS Base Score (0-80 points). Each of the
eight dimensions is of equal weight; therefore, the HCAHPS Base Score
ranges from 0 to 80 points. HCAHPS Consistency Points are then
calculated, which range from 0 to 20 points. The Consistency Points
take into consideration the scores of all eight Person and Community
Engagement dimensions. The final element of the scoring formula is the
summation of the HCAHPS Base Score and the HCAHPS Consistency Points,
which results in the Person and Community Engagement Domain score that
ranges from 0 to 100 points.
Estimated Performance Standards for the FY 2022 Program Year: Person and Community Engagement Domain
----------------------------------------------------------------------------------------------------------------
Achievement
Floor threshold Benchmark
HCAHPS survey dimension (minimum) (50th (mean of top
percentile) decile)
----------------------------------------------------------------------------------------------------------------
Communication with Nurses....................................... 10.93 79.06 87.42
Communication with Doctors...................................... 13.98 79.69 87.97
Responsiveness of Hospital Staff................................ 16.92 65.97 81.33
Communication about Medicines................................... 8.50 63.60 74.56
Hospital Cleanliness & Quietness................................ 4.39 65.47 79.49
Discharge Information........................................... 65.62 87.17 91.96
Care Transition................................................. 5.11 51.88 63.18
Overall Rating of Hospital...................................... 18.86 71.48 85.32
----------------------------------------------------------------------------------------------------------------
The estimated performance standards displayed in this table were calculated using one quarter (Q4)
CY 2017 data and three quarters (Q1, Q2, and Q3) CY 2018 data. We will update this table's performance
standards using four quarters of CY 2018 data in the FY 2020 IPPS/LTCH PPS final rule.
c. Previously Established Performance Standards for Certain Measures
for the FY 2023 Program Year
We have adopted certain measures for the Safety domain, Clinical
Outcomes domain, and Efficiency and Cost Reduction domain for future
program years in order to ensure that we can adopt baseline and
performance periods of sufficient length for performance scoring
purposes. In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38264 through
38265), we established performance standards for the FY 2023 program
year for the Clinical Outcomes domain measures (MORT-30-AMI, MORT-30-
HF, MORT-30-PN (updated cohort), MORT-30-COPD, MORT-30-CABG, and COMP-
HIP-KNEE) and for the Efficiency and Cost Reduction domain measure
(MSPB). In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41471 through
41472), we established, for the FY 2023 program year, the performance
standards for the Safety domain measure, CMS PSI 90. We note that the
performance standards for the MSPB measure are based on performance
period data. Therefore, we are unable to provide numerical equivalents
for the standards at this time. The previously established performance
standards for these measures are set out in the table below.
Previously Established Performance Standards for the FY 2023 Program
Year
------------------------------------------------------------------------
Achievement
Measure short name threshold Benchmark
------------------------------------------------------------------------
Safety Domain
------------------------------------------------------------------------
CMS PSI 90 *.................... 0.972658.......... 0.760882.
------------------------------------------------------------------------
Clinical Outcomes Domain
------------------------------------------------------------------------
MORT-30-AMI..................... 0.866548.......... 0.885499.
MORT-30-HF...................... 0.881939.......... 0.906798.
MORT-30-PN (updated cohort)..... 0.840138.......... 0.871741.
MORT-30-COPD.................... 0.919769.......... 0.936349.
MORT-30-CABG.................... 0.968747.......... 0.979620.
COMP-HIP-KNEE *................. 0.027428.......... 0.019779.
------------------------------------------------------------------------
Efficiency and Cost Reduction Domain
------------------------------------------------------------------------
MSPB *.......................... Median Medicare Mean of the lowest
Spending per decile Medicare
Beneficiary ratio Spending per
across all Beneficiary
hospitals during ratios across all
the performance hospitals during
period. the performance
period
------------------------------------------------------------------------
* Lower values represent better performance.
[[Page 19438]]
d. Previously Established and Newly Established Performance Standards
for Certain Measures for the FY 2024 Program Year
We have adopted certain measures for the Safety domain, Clinical
Outcomes domain, and Efficiency and Cost Reduction domain for future
program years in order to ensure that we can adopt baseline and
performance periods of sufficient length for performance scoring
purposes. In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41472), we
established performance standards for the FY 2024 program year for the
Clinical Outcomes domain measures (MORT-30-AMI, MORT-30-HF, MORT-30-PN
(updated cohort), MORT-30-COPD, MORT-30-CABG, and COMP-HIP-KNEE) and
the Efficiency and Cost Reduction domain measure (MSPB). We note that
the performance standards for the MSPB measure are based on performance
period data. Therefore, we are unable to provide numerical equivalents
for the standards at this time.
In accordance with our methodology for calculating performance
standards discussed more fully in the Hospital Inpatient VBP Program
final rule (76 FR 26511 through 26513) and codified at 42 CFR 412.160,
we are establishing performance standards for the CMS PSI 90 measure
for the FY 2024 program year. The previously established and newly
established performance standards for these measures are set out in the
table below.
Previously Established and Newly Established Performance Standards for
the FY 2024 Program Year
------------------------------------------------------------------------
Achievement
Measure short name threshold Benchmark
------------------------------------------------------------------------
Safety Domain
------------------------------------------------------------------------
CMS PSI 90 *.................... 0.968841.......... 0.754176
------------------------------------------------------------------------
Clinical Outcomes Domain
------------------------------------------------------------------------
MORT-30-AMI #................... 0.869247.......... 0.887868
MORT-30-HF #.................... 0.882308.......... 0.907733
MORT-30-PN (updated cohort) #... 0.840281.......... 0.872976
MORT-30-COPD #.................. 0.916491.......... 0.934002
MORT-30-CABG #.................. 0.969499.......... 0.980319
COMP-HIP-KNEE *#................ 0.025396.......... 0.018159
------------------------------------------------------------------------
Efficiency and Cost Reduction Domain
------------------------------------------------------------------------
MSPB *#......................... Median Medicare Mean of the lowest
Spending per decile Medicare
Beneficiary ratio Spending per
across all Beneficiary
hospitals during ratios across all
the performance hospitals during
period. the performance
period
------------------------------------------------------------------------
* Lower values represent better performance.
# Previously established performance standards.
e. Newly Established Performance Standards for Certain Measures for the
FY 2025 Program Year
As discussed above, we have adopted certain measures for the
Clinical Outcomes domain (MORT-30-AMI, MORT-30-HF, MORT-30-PN (updated
cohort), MORT-30-COPD, MORT-30-CABG, and COMP-HIP-KNEE) and the
Efficiency and Cost Reduction domain (MSPB) for future program years in
order to ensure that we can adopt baseline and performance periods of
sufficient length for performance scoring purposes. In accordance with
our methodology for calculating performance standards discussed more
fully in the Hospital Inpatient VBP Program final rule (76 FR 26511
through 26513), and our performance standards definitions codified at
42 CFR 412.160, we are establishing the following performance standards
for the FY 2025 program year for the Clinical Outcomes domain and the
Efficiency and Cost Reduction domain. We note that the performance
standards for the MSPB measure are based on performance period data.
Therefore, we are unable to provide numerical equivalents for the
standards at this time. The newly established performance standards for
these measures are set out in the table below.
Newly Established Performance Standards for the FY 2025 Program Year
------------------------------------------------------------------------
Achievement
Measure short name threshold Benchmark
------------------------------------------------------------------------
Clinical Outcomes Domain
------------------------------------------------------------------------
MORT-30-AMI..................... 0.872624.......... 0.889994.
MORT-30-HF...................... 0.883990.......... 0.910344.
MORT-30-PN (updated cohort)..... 0.841475.......... 0.874425.
MORT-30-COPD.................... 0.915127.......... 0.932236.
MORT-30-CABG.................... 0.970100.......... 0.979775.
COMP-HIP-KNEE **................ 0.025332.......... 0.017946.
------------------------------------------------------------------------
[[Page 19439]]
Efficiency and Cost Reduction Domain
------------------------------------------------------------------------
MSPB *#......................... Median Medicare Mean of the lowest
Spending per decile Medicare
Beneficiary ratio Spending per
across all Beneficiary
hospitals during ratios across all
the performance hospitals during
period. the performance
period.
------------------------------------------------------------------------
* Lower values represent better performance.
5. Scoring Methodology and Data Requirements
a. Domain Weighting for the FY 2022 Program Year and Subsequent Years
for Hospitals That Receive a Score on All Domains
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38266), we finalized
our proposal to retain the equal weight of 25 percent for each of the
four domains in the Hospital VBP Program for the FY 2020 program year
and subsequent years for hospitals that receive a score in all domains.
In FY 2019 IPPS/LTCH PPS rulemaking (83 FR 20416 through 20420; 41459
through 41464), we proposed, but did not adopt, any changes to the
Hospital VBP Program domains and weighting. We are not proposing any
changes to these domain weights in this proposed rule.
b. Domain Weighting for the FY 2022 Program Year and Subsequent Years
for Hospitals Receiving Scores on Fewer Than Four Domains
In the FY 2015 IPPS/LTCH PPS final rule (79 FR 50084 through
50085), for the FY 2017 program year and subsequent years, we adopted a
policy that hospitals must receive domain scores on at least three of
four quality domains in order to receive a TPS, and hospitals with
sufficient data on only three domains will have their TPSs
proportionately reweighted. We are not proposing any changes to these
domain weights in this proposed rule.
c. Minimum Numbers of Measures for Hospital VBP Program Domains
Based on our previously finalized policies (82 FR 38266), for a
hospital to receive domain scores for the FY 2021 program year and
subsequent years:
A hospital must report a minimum number of 100 completed
HCAHPS surveys for a hospital to receive a Person and Community
Engagement domain score.
A hospital must receive a minimum of two measure scores
within the Clinical Outcomes domain to receive a Clinical Outcomes
domain score.
A hospital must receive a minimum of two measure scores
within the Safety domain to receive a Safety domain score.
A hospital must receive a minimum of one measure score
within the Efficiency and Cost Reduction domain to receive an
Efficiency and Cost Reduction domain score.
We are not proposing any changes to these policies in this proposed
rule.
d. Minimum Numbers of Cases for Hospital VBP Program Measures
(1) Background
Section 1886(o)(1)(C)(ii)(IV) of the Act requires the Secretary to
exclude for the fiscal year hospitals that do not report a minimum
number (as determined by the Secretary) of cases for the measures that
apply to the hospital for the performance period for the fiscal year.
For additional discussion of the previously finalized minimum numbers
of cases for measures under the Hospital VBP Program, we refer readers
to the Hospital Inpatient VBP Program final rule (76 FR 26527 through
26531); the CY 2012 OPPS/ASC final rule (76 FR 74532 through 74534);
the FY 2013 IPPS/LTCH PPS final rule (77 FR 53608 through 53610); the
FY 2015 IPPS/LTCH PPS final rule (79 FR 50085 through 50086); the FY
2016 IPPS/LTCH PPS final rule (80 FR 49570); the FY 2017 IPPS/LTCH PPS
final rule (81 FR 57011); the FY 2018 IPPS/LTCH PPS final rule (82 FR
38266 through 38267); and the FY 2019 IPPS/LTCH PPS final rule (83 FR
41465 through 41466). We are not proposing any changes to these
policies in this proposed rule.
(2) Summary of Previously Adopted Minimum Numbers of Cases
The previously adopted minimum numbers of cases for these measures
are set forth in the table below.
Previously Adopted Minimum Case Number Requirements for the FY 2022
Program Year and Subsequent Years
------------------------------------------------------------------------
Measure short name Minimum number of cases
------------------------------------------------------------------------
Person and Community Engagement Domain
------------------------------------------------------------------------
HCAHPS............................ Hospitals must report a minimum
number of 100 completed HCAHPS
surveys.
------------------------------------------------------------------------
Clinical Outcomes Domain
------------------------------------------------------------------------
MORT-30-AMI....................... Hospitals must report a minimum
number of 25 cases.
MORT-30-HF........................ Hospitals must report a minimum
number of 25 cases.
MORT-30-PN (updated cohort)....... Hospitals must report a minimum
number of 25 cases.
MORT-30-COPD...................... Hospitals must report a minimum
number of 25 cases.
MORT-30-CABG...................... Hospitals must report a minimum
number of 25 cases.
COMP-HIP-KNEE..................... Hospitals must report a minimum
number of 25 cases.
------------------------------------------------------------------------
Safety Domain
------------------------------------------------------------------------
CAUTI............................. Hospitals have a minimum of 1.000
predicted infections as calculated
by the CDC.
CLABSI............................ Hospitals have a minimum of 1.000
predicted infections as calculated
by the CDC.
[[Page 19440]]
Colon and Abdominal Hysterectomy Hospitals have a minimum of 1.000
SSI. predicted infections as calculated
by the CDC.
MRSA Bacteremia................... Hospitals have a minimum of 1.000
predicted infections as calculated
by the CDC.
CDI............................... Hospitals have a minimum of 1.000
predicted infections as calculated
by the CDC.
CMS PSI 90........................ Hospitals must report a minimum of
three eligible cases on any one
underlying indicator.
------------------------------------------------------------------------
Efficiency and Cost Reduction Domain
------------------------------------------------------------------------
MSPB.............................. Hospitals must report a minimum
number of 25 cases.
------------------------------------------------------------------------
e. Proposed Administrative Policies for NHSN Healthcare-Associated
Infection (HAI) Measure Data
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41553), beginning
with the CY 2020 reporting period, the Hospital IQR Program finalized
removal of the five CDC NHSN HAI measures that are used in both the
Hospital VBP and HAC Reduction Programs (CAUTI, CLABSI, Colon and
Abdominal Hysterectomy SSI, MRSA Bacteremia, and CDI). Since these
measures were adopted in the Hospital VBP Program, the Hospital VBP
Program has used the same data to calculate the CDC NHSN HAI measures
that is used by the Hospital IQR Program. In the FY 2019 IPPS/LTCH PPS
final rule (83 FR 41475 through 41478), the HAC Reduction Program
adopted data collection policies for the CDC NHSN HAI measures,
beginning on January 1, 2020 with CY 2020 submissions, which will use
the same process as the Hospital IQR Program for hospitals to report,
review, and correct CDC NHSN HAI measure data. Furthermore, the HAC
Reduction Program also adopted processes to validate the CDC NHSN HAI
measures used in the HAC Reduction Program beginning with Q3 2020
discharges (83 FR 41478 through 41483). These processes are intended to
reflect, to the greatest extent possible, the processes previously
established for the Hospital IQR Program in order to aid continued
hospital reporting through clear and consistent requirements. In
section IV.I.7. of the preamble of this proposed rule, the HAC
Reduction Program is proposing additional refinements to its validation
process for the CDC NHSN HAI measures in the HAC Reduction Program and
providing clarifications regarding validation processes.
To streamline and simplify processes across hospital programs, we
are proposing that the Hospital VBP Program will use the same data to
calculate the CDC NHSN HAI measures that the HAC Reduction Program uses
for purposes of calculating the measures under that program, beginning
on January 1, 2020 for CY 2020 data collection, which would apply to
the Hospital VBP Program starting with data for the FY 2022 program
year performance period. This proposed start date aligns with the
effective date of the removal of the measures from the Hospital IQR
Program and the date when data on those measures will begin to be
reported for the HAC Reduction Program, allowing for a seamless
transition. We note that the data used by the HAC Reduction Program
will be the same data previously used by the Hospital IQR Program, and
therefore, we do not anticipate any changes in the use of such data for
the Hospital VBP Program.
We also are proposing that the Hospital VBP Program will use the
same processes adopted by the HAC Reduction Program for hospitals to
review and correct data for the CDC NHSN HAI measures and will rely on
HAC Reduction Program validation to ensure the accuracy of CDC NHSN HAI
measure data used in the Hospital VBP Program. We note that the
processes for hospitals to submit, review, and correct their data for
these measures are the same processes previously used by the Hospital
IQR Program. We believe that using the HAC Reduction Program review and
correction process will satisfy the requirement in section
1886(o)(10)(A)(ii) of the Act to allow hospitals to review and submit
corrections for Hospital VBP Program information that will be made
public with respect to each hospital. In addition, as noted earlier,
the HAC Reduction Program's validation processes are intended to
reflect, to the greatest extent possible, the processes previously
established for the Hospital IQR Program. We refer readers to the FY
2019 IPPS/LTCH PPS final rule (83 FR 41478 through 41483) for a
discussion of those processes in the HAC Reduction Program.\399\ We
believe relying on the HAC Reduction Program's validation process would
be sufficient for purposes of ensuring the accuracy of CDC NHSN HAI
measure data under the Hospital VBP Program. We believe that these
policies will ensure that the use of the same data for the Hospital VBP
Program will result in accurate measure scores under the Hospital VBP
Program.
---------------------------------------------------------------------------
\399\ The FY 2019 IPPS/LTCH PPS final rule (83 FR 41478 through
41483) includes additional information regarding provider selection,
targeting criteria, calculation of the confidence, education review
process, and application of validation penalty for the HAC Reduction
Program's validation processes compared to the Hospital IQR
Program's processes. We also refer readers to section IV.I.7. of the
preamble of this proposed rule for proposed changes to the
validation selection methodology and proposed clarifications to the
validation filtering methodology for the HAC Reduction Program.
---------------------------------------------------------------------------
We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR
41475 through 41484) for additional details on the HAC Reduction
Program's data collection, review and correction, validation, and data
accuracy policies for the CDC NHSN HAI measures. We also refer readers
to sections IV.I.6. and IV.I.7. of the preamble of this proposed rule
for additional information about HAC Reduction Program data collection,
review and correction, and proposed refinements to validation policies
for the CDC NHSN HAI measures.
I. Hospital-Acquired Condition (HAC) Reduction Program
1. Background
We refer readers to the FY 2014 IPPS/LTCH PPS final rule (78 FR
50707 through 50708) for a general overview of the HAC Reduction
Program. For a detailed discussion of the statutory basis of the HAC
Reduction Program, we refer readers to the FY 2014 IPPS/LTCH PPS final
rule (78 FR 50708 through 50709). For a further description of our
previously finalized policies for the HAC Reduction Program, we refer
readers to the FY 2014 IPPS/LTCH PPS
[[Page 19441]]
final rule (78 FR 50707 through 50729), the FY 2015 IPPS/LTCH PPS final
rule (79 FR 50087 through 50104), the FY 2016 IPPS/LTCH PPS final rule
(80 FR 49570 through 49581), the FY 2017 IPPS/LTCH PPS final rule (81
FR 57011 through 57026), the FY 2018 IPPS/LTCH PPS final rule (82 FR
38269 through 38278), and the FY 2019 IPPS/LTCH PPS final rule (83 FR
41472 through 41492). These policies describe the general framework for
implementation of the HAC Reduction Program, including: (1) The
relevant definitions applicable to the program; (2) the payment
adjustment under the program; (3) the measure selection process and
conditions for the program, including a risk adjustment- and scoring
methodology; (4) performance scoring; (5) data collection; (6)
validation; (7) the process for making hospital-specific performance
information available to the public, including the opportunity for a
hospital to review the information and submit corrections; and (8)
limitation of administrative and judicial review. We remind readers
that data collection and validation (items (5) and (6)) policies were
newly finalized in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41472
through 41492).
We also have codified certain requirements of the HAC Reduction
Program at 42 CFR 412.170 through 412.172. In section IV.I.12. of the
preamble of this proposed rule, we are proposing to update 42 CFR
412.172(f) to reflect policies finalized in the FY 2019 IPPS/LTCH PPS
final rule.
2. Implementation of the HAC Reduction Program for FY 2020
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41472 through
41492), we reviewed the HAC Reduction Program in the context of our
Meaningful Measures Initiative. The HAC Reduction Program addresses the
priority areas of making care safer by reducing harm caused in the
delivery of care. The measures in the Program generally represent
``never events'' \400\ and often, if not always, assess the incidence
of preventable conditions. In the FY 2019 IPPS/LTCH PPS final rule (83
FR 41547 through 41553), for the Hospital IQR Program, as part of the
Meaningful Measures Initiative, we deduplicated the CMS Patient Safety
and Adverse Events Composite (CMS PSI 90) beginning with the Hospital
IQR Program's FY 2020 payment determination, and the Centers for
Disease Control and Prevention (CDC) National Healthcare Safety Network
(NHSN) Healthcare-Associated Infection (HAI) measures (CDC NHSN HAI
measures) from the Hospital IQR Program beginning in CY 2020/FY 2022
payment determination. However, we retained these measures in the HAC
Reduction Program because we believe these measures will continue to
encourage hospitals to address the serious harm caused by these adverse
events while still using the most parsimonious measure set available.
To that end, however, we were required to adopt numerous HAC Reduction
Program-specific CDC NHSN HAI measure policies, including data
collection, validation requirements, and scoring associated with data
completeness, timeliness, and accuracy, to transition the
administrative processes on which the HAC Reduction Program had
historically relied on the Hospital IQR Program to support. In the FY
2019 IPPS/LTCH PPS final rule (83 FR 41475 through 41484), for the HAC
Reduction Program, we formally adopted analogous processes to
independently manage these administrative processes to receive CDC NHSN
data beginning in CY 2020 and with validation beginning with Q3 CY 2020
infectious events.
---------------------------------------------------------------------------
\400\ The term ``Never Event'' was first introduced in 2001 by
Ken Kizer, MD, former CEO of the National Quality Forum (NQF), in
reference to particularly shocking medical errors (such as wrong-
site surgery) that should never occur. Over time, the list has been
expanded to signify adverse events that are unambiguous (clearly
identifiable and measurable), serious (resulting in death or
significant disability), and usually preventable. The NQF initially
defined 27 such events in 2002. The list has been revised since
then, most recently in 2011, and now consists of 29 events grouped
into 7 categories: Surgical, product or device, patient protection,
care management, environmental, radiologic, and criminal.'' Never
Events are available at: https://psnet.ahrq.gov/primers/primer/3/neverevents.
---------------------------------------------------------------------------
In this proposed rule, we are proposing to clarify policies that we
finalized for the HAC Reduction Program in the FY 2019 IPPS/LTCH PPS
final rule, so that they are implemented as intended. We are
specifically proposing to: (1) Adopt a measure removal policy that
aligns with the removal factor policies previously adopted in other
quality reporting and quality payment programs; (2) clarify
administrative policies for validation of the CDC NHSN HAI measures;
(3) adopt the data collection periods for the FY 2022 program year; and
(4) update regulations for the HAC Reduction Program at 42 CFR
412.172(f) to reflect policies finalized in the FY 2019 IPPS/LTCH PPS
final rule.
3. Current Measures for FY 2020 and Subsequent Years
The HAC Reduction Program has adopted six measures. In the FY 2014
IPPS/LTCH PPS final rule (78 FR 50717), we finalized the use of five
CDC NHSN HAI measures: (1) CAUTI; (2) CDI; (3) CLABSI; (4) Colon and
Abdominal Hysterectomy SSI; and (5) MRSA Bacteremia. In the FY 2017
IPPS/LTCH PPS final rule (81 FR 57014), we finalized the use of the CMS
Patient Safety and Adverse Events Composite (CMS PSI 90) measure. These
previously finalized measures, with their full measure names, are shown
in the table below.\401\
---------------------------------------------------------------------------
\401\ In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41485
through 41489), we finalized the equal weighting of measures to
coincide with the removal of Domains for scoring purposes, so these
measures are no longer grouped by Domain.
HAC Reduction Program Measures for FY 2019
----------------------------------------------------------------------------------------------------------------
Short name Measure name NQF #
----------------------------------------------------------------------------------------------------------------
CMS PSI 90............................... CMS Patient Safety Indicator (PSI) 90................ 0531
CAUTI.................................... CDC NHSN Catheter-associated Urinary Tract Infection 0138
(CAUTI) Outcome Measure.
CDI...................................... CDC NHSN Facility-wide Inpatient Hospital-onset 1717
Clostridium difficile Infection (CDI) Outcome
Measure.
CLABSI................................... CDC NHSN Central Line-Associated Bloodstream 0139
Infection (CLABSI) Outcome Measure.
Colon and Abdominal Hysterectomy SSI..... American College of Surgeons--Centers for Disease 0753
Control and Prevention (ACS-CDC) Harmonized
Procedure Specific Surgical Site Infection (SSI)
Outcome Measure.
MRSA Bacteremia.......................... CDC NHSN Facility-wide Inpatient Hospital-onset 1716
Methicillin-resistant Staphylococcus aureus (MRSA)
Bacteremia Outcome Measure.
----------------------------------------------------------------------------------------------------------------
[[Page 19442]]
In this proposed rule, we are not proposing to add or remove any
measures.
4. Measures Specification and Technical Specifications
As we stated in the FY 2015 IPPS/LTCH PPS final rule (79 FR 50100
through 50101) and reiterated in the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41475), we will use a subregulatory process to make
nonsubstantive updates to measures used for the HAC Reduction Program
and use notice-and-comment rulemaking to adopt substantive updates to
measures. We are not making any substantive changes to the measures
this year. Technical specifications for the CMS PSI 90 measure can be
found on the QualityNet website at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetBasic&cid=1228695355425. Technical specifications for the CDC NHSN HAI measures can be
found at CDC's NHSN website at: http://www.cdc.gov/nhsn/acute-care-hospital/index.html. Both websites provide measure updates and other
information necessary to guide hospitals participating in the
collection of HAC Reduction Program data.
5. Proposed Measure Removal Factors
While we are not proposing to remove any measures in this proposed
rule, we are proposing to adopt a removal factor policy as part of our
ongoing efforts to ensure that the HAC Reduction Program measure set
continues to promote improved health outcomes for beneficiaries while
minimizing the overall burden and costs associated with the program. In
addition, the adoption of measure removal factors would align the HAC
Reduction Program with our other quality reporting and quality payment
programs and help ensure consistency in our measure evaluation
methodology across programs.
In the FY 2019 IPPS/LTCH PPS final rule, we updated considerations
for removing measures from several CMS quality reporting and quality
payment programs. Specifically, we finalized eight measure removal
factors for the Hospital IQR Program (83 FR 41540 through 41544), the
Hospital VBP Program (83 FR 41441 through 41446), the PCHQR Program (83
FR 41609 through 41611), and the LTCH QRP (83 FR 41625 through 41627).
We believe these removal factors are also appropriate for the HAC
Reduction Program, and we believe that alignment among CMS quality
programs is important to provide stakeholders with a clear, consistent,
and transparent process. Therefore, to align with our other quality
reporting and quality payment programs, we are proposing to adopt the
following removal factors for the HAC Reduction Program:
Factor 1. Measure performance among hospitals is so high
and unvarying that meaningful distinctions and improvements in
performance can no longer be made (``topped-out'' measures);
Factor 2. Measure does not align with current clinical
guidelines or practice;
Factor 3. Measure can be replaced by a more broadly
applicable measure (across settings or populations) or a measure that
is more proximal in time to desired patient outcomes for the particular
topic;
Factor 4. Measure performance or improvement does not
result in better patient outcomes;
Factor 5. Measure can be replaced by a measure that is
more strongly associated with desired patient outcomes for the
particular topic;
Factor 6. Measure collection or public reporting leads to
negative unintended consequences other than patient harm; \402\
---------------------------------------------------------------------------
\402\ When there is reason to believe that the continued
collection of a measure as it is currently specified raises
potential patient safety concerns, CMS will take immediate action to
remove a measure from the program and not wait for the annual
rulemaking cycle. In such situations, we would promptly retire such
measures followed by subsequent confirmation of the retirement in
the next IPPS rulemaking. When we do so, we will notify hospitals
and the public through the usual hospital and QIO communication
channels used for the HAC Reduction Program, which include memo and
email notification and QualityNet website articles and postings.
---------------------------------------------------------------------------
Factor 7. Measure is not feasible to implement as
specified; and
Factor 8. The costs associated with a measure outweigh the
benefit of its continued use in the program.\403\
---------------------------------------------------------------------------
\403\ We refer readers to the Hospital IQR Program's removal
factors discussions in the FY 2016 IPPS/LTCH PPS final rule (80 FR
49641 through 49643) and the FY 2019 IPPS/LTCH PPS final rule (83 FR
41540 through 41544) for additional details on the removal factors
and the rationale supporting them.
---------------------------------------------------------------------------
We note that these removal factors are considerations taken into
account when deciding whether or not to remove measures, not firm
requirements, and that we will propose to remove measures based on
these factors on a case-by-case basis. We continue to believe that
there may be circumstances in which a measure that meets one or more
factors for removal should be retained regardless because the benefits
of a measure can outweigh its drawbacks. Our goal is to move the
program forward in the least burdensome manner possible, while
maintaining a parsimonious set of meaningful quality measures and
continuing to incentivize improvement in the quality of care provided
to patients.
6. Administrative Policies for the HAC Reduction Program for FY 2020
and Subsequent Years
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41475 through
41485), we discussed our previously finalized administrative polices
for the HAC Reduction Program and adopted several HAC Reduction
Program-specific policies for CDC NHSN HAI data collection and
validation.
a. Data Collection Beginning CY 2020
As finalized in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41475
through 41477), the HAC Reduction Program will assume responsibility
for receiving CDC NHSN HAI data from the CDC beginning with CY 2020
(January 1, 2020) submissions. All reporting requirements, including,
but not limited to, quarterly frequency, CDC collection system and
deadlines, will remain constant from the current Hospital IQR Program
requirements to aid continued hospital reporting through clear and
consistent requirements. We refer readers to the Hospital IQR Program's
prior years' rules for reference of these requirements \404\ and to
QualityNet for the current reporting requirements and deadlines.
---------------------------------------------------------------------------
\404\ FY 2011 IPPS/LTCH PPS final rule (75 FR 50223 through
50224); FY 2012 IPPS/LTCH PPS final rule (76 FR 51644 through
51645); FY 2013 IPPS/LTCH PPS final rule (77 FR 53539); FY 2014
IPPS/LTCH PPS final rule (78 FR 50821 through 50822); FY 2015 IPPS/
LTCH PPS final rule (79 FR 50259 through 50262); FY 2016 IPPS/LTCH
PPS final rule (80 FR 49710); FY 2017 IPPS/LTCH PPS final rule (81
FR 57173); FY 2018 IPPS/LTCH PPS final rule (82 FR 38398); FY 2019
IPPS/LTCH PPS final rule (83 FR 41607).
---------------------------------------------------------------------------
Hospitals will continue to submit data through the CDC NHSN portal
by selecting ``NHSN Reporting'' after signing in at: https://sams.cdc.gov. The HAC Reduction Program will receive the CDC NHSN data
directly from the CDC instead of through the Hospital IQR Program as an
intermediary. We note that some hospitals may not have locations that
meet the CDC NHSN criteria for CLABSI or CAUTI reporting, and that some
hospitals may perform so few procedures requiring surveillance under
the Colon and Abdominal Hysterectomy SSI measure that the data may not
be meaningful for public reporting or sufficiently reliable to be
utilized for a program year. If a hospital does not have adequate
locations or procedures, it should submit the Measure Exception Form to
the HAC
[[Page 19443]]
Reduction Program beginning on January 1, 2020. The IPPS Quality
Reporting Programs Measure Exception Form is located using the link
located on the QualityNet website under the Hospitals Inpatient >
Hospital Inpatient Quality Reporting Program tab at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier2&cid=1228760487021. As has been the case under the Hospital IQR Program, hospitals
seeking an exception would submit this form at least annually to be
considered.
We reiterate that no additional collection mechanisms are required
for the CMS PSI 90 measure because it is a claims-based measure
calculated using data submitted to CMS by hospitals for Medicare
payment, and therefore imposes no additional administrative or
reporting requirements on participating hospitals.
In this proposed rule, we are not proposing any updates to our
previously finalized data collection processes.
b. Review and Correction of Claims Data and Chart-Abstracted CDC NHSN
HAI Data Used in the HAC Reduction Program for FY 2020 and Subsequent
Years
For the review and correction of claims data, hospitals are
encouraged to ensure that their claims are accurate prior to the
snapshot date, which is taken after the 90-day period following the
last date of discharge used in the applicable period. In the FY 2014
IPPS/LTCH PPS final rule (78 FR 50726 through 50727) and FY 2019 IPPS/
LTCH PPS final rule (83 FR 41477 through 41478), we detailed the
process for the review and correction of claims-based data, and we
refer readers to those rules for more information on the process for
the review and correction of claims-based data.
For the review and correction of chart-abstracted CDC NHSN HAI
measures, we reiterate that hospitals can submit, review, and correct
any of the chart-abstracted information for the full 4\1/2\ months
after the end of the reporting quarter. We refer readers to the FY 2014
IPPS/LTCH PPS final rule (78 FR 50726), the FY 2018 IPPS/LTCH PPS final
rule (82 FR 38270 through 38271), and the FY 2019 IPPS/LTCH PPS final
rule (83 FR 41477 through 41478) for more information.
In this proposed rule, we are not proposing any change to our
current administrative policies regarding the review and correction of
claims data or chart-abstracted CDC NHSN HAI data.
7. Proposed Change to Validation Targeting Methodology and
Clarifications Regarding Validation Processes
a. Summary of Existing Validation Processes
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41478 through
41484), we adopted processes to validate the CDC NHSN HAI measure data
used in the HAC Reduction Program because the Hospital IQR Program
finalized its proposals to remove CDC NHSN HAI measures from its
program. We finalized the HAC Reduction Program's processes to reflect,
to the greatest extent possible, the processes previously established
under the Hospital IQR Program. We refer readers to the FY 2019 IPPS/
LTCH PPS final rule (83 FR 41478 through 41484), for detailed
information on the following HAC Reduction Program validation
processes:
Measures Subject to Validation
Educational Review Process
Calculation of Confidence Intervals
Application of Validation Scoring and Penalty
Validation Period
Data Accuracy and Completeness Acknowledgement
We also refer readers to the QualityNet website for more
information regarding measure abstraction: https://www.qualitynet.org/dcs/ContentServer?cid=%201228776288808&pagename=QnetPublic%2FPage%2FQnetTier3&c=Page.
We would also like to remind stakeholders of the finalized
validation periods for the HAC Reduction Program.
[GRAPHIC] [TIFF OMITTED] TP03MY19.026
[[Page 19444]]
In this proposed rule, we are proposing to change the number of
hospitals selected under the validation targeting methodology and are
providing two clarifications to this validation process.
---------------------------------------------------------------------------
\405\ The CMS Clinical Data Abstraction Center (CDAC) performs
the validation.
---------------------------------------------------------------------------
b. Proposed Change to the Previously Finalized Validation Selection
Methodology
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41480), we finalized
our policy to select 200 additional hospitals for targeted validation
and five targeting criteria.
While we are retaining the same targeting criteria that we
finalized last year, we are proposing to change the number of hospitals
targeted from exactly 200 hospitals to ``up to 200 hospitals.'' We
believe this change is necessary to provide flexibility in the
selection process for the HAC Reduction Program so that we can
implement a targeting process for validation of chart-abstracted
measures in both the Hospital IQR Program and HAC Reduction Program in
a manner that does not unnecessarily subject hospitals to selection
just to meet the 200 number. This proposed policy would allow us to
only select hospitals that meet the targeting criteria and allow us to
remove hospitals that do not have the requisite number of CDC NHSN HAI
events from the targeted validation pool. We note that this will not
affect the statistical reliability of the validation sample because
statistical methodologies are only applied to data within hospitals for
validation.
c. Clarifications to the Validation Selection Methodology
As discussed in section IV.I.7.a. of the preamble of this proposed
rule, in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41478 through
41484), we finalized several proposals to implement validation of the
CDC NHSN HAI measures in the HAC Reduction Program, in as similar a
manner to the validation process used by the Hospital IQR Program as
prudent. In this proposed rule, in addition to proposing to change the
number of targeted hospitals from ``200'' to ``up to 200'', we also are
clarifying our selection process for both the random and targeted
sample of subsection (d) hospitals subject to HAC Reduction Program
validation.
During the comment period for the FY 2019 IPPS/LTCH PPS proposed
rule (83 FR 41479), some commenters expressed concern that hospitals
could now be selected for validation under both the Hospital IQR
Program and the HAC Reduction Program during the same reporting period,
thereby increasing the burden to selected hospitals. As we stated last
year, one of the goals of our deduplication efforts has been and
continues to be a reduction in provider burden. To that end and to
allay stakeholder concerns, we are clarifying the provider selection
process and reassuring providers that we will work to reduce validation
burden to the greatest extent possible.
We are clarifying that the HAC Reduction Program, in conjunction
with the Hospital IQR Program, will use an aggregated random sample
selection methodology through which the validation team would select
one pool of 400 subsection (d) hospitals for validation of chart-
abstracted measures in both the Hospital IQR Program and HAC Reduction
Program. The pool of 400 hospitals will be selected randomly and
validated for both the CDC NHSN HAI measures for the HAC Reduction
Program and the Hospital IQR Program's chart-abstracted measures. The
HAC Reduction Program will include all subsection (d) hospitals,
whereas the Hospital IQR Program will remove any subsection (d)
hospital without an active notice of participation in the Hospital IQR
Program (83 FR 41479).
This approach will ensure that the Programs' validation samples are
selected at random and would avoid any perception associated with the
selection of one program's sample before the other program's sample. We
will begin using this selection process with Q3 CY 2020 infectious
events, which is when the HAC Reduction Program is scheduled to begin
its validation process. We refer readers to section VIII.A.11. of the
preamble of this proposed rule for more information on the Hospital IQR
Program's validation policies.
After the random selection process, an additional targeted \406\
aggregated sample of up to 200 hospitals will be selected for the HAC
Reduction and Hospital IQR Programs' validation processes using
existing targeting criteria.
---------------------------------------------------------------------------
\406\ We refer readers to the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41480), where we detailed the criteria for selecting
additional hospitals for targeted validation.
---------------------------------------------------------------------------
We also note that any nonsubstantive updates to the specifications
for validation of chart-abstracted measures will be provided on the
QualityNet website at: https://www.qualitynet.org/dcs/ContentServer?cid=%201228776288808&pagename=QnetPublic%2FPage%2FQnetTier3&c=Page. Further, any substantive changes, such as the measures
validated, changes to passing confidence intervals, and the number of
providers selected, will be proposed through notice-and-comment
rulemaking.
We believe this clarification of our approach to the random
selection of one pool of 400 hospitals and our proposal to select up to
200 targeted hospitals will avoid increasing provider burden because
the total number of hospitals selected for validation is not
increasing, nor are the measures that were subject to validation for
the selected hospitals prior to deduplication.
Moreover, we do not anticipate any increased burden to hospitals
because we are not increasing the number of cases selected for
validation. For HAC Reduction Program validation, we will continue to
select up to 40 cases annually from each hospital selected for
validation (four CAUTI, four CLABSI, and two Colon and Abdominal
Hysterectomy SSI per quarter; or four CDI, four MRSA, and two Colon and
Abdominal Hysterectomy SSI per quarter). As we stated in the FY 2019
IPPS/LTCH PPS rulemaking, we intend this process to be as efficient as
possible and we believe this clarification and our proposal help meet
that expectation.
d. Proposed Clarification to Validation Filtering Methodology
As we discussed for the Hospital IQR Program in the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53542), CMS has the option to target the
sample selection to cases, referred to as candidate events, that are
more likely to be true CDC NHSN HAIs events, or those that meet CDC
NHSN HAI criteria. To better target true events for CDC NHSN HAI
validation, we are proposing to clarify our approach for selecting
CLABSI and CAUTI cases for chart-abstracted validation when CDC NHSN
HAI validation that is currently performed under the Hospital IQR
Program migrates to the HAC Reduction Program, beginning with the
reporting of Q3 CY 2020 infections events. To date, our experience has
shown us that many candidate cases selected for validation have all
their positive cultures collected during the first or second day
following admission and, as such, would be considered community onset
events for CLABSI and CAUTI.\407\ Therefore, we
[[Page 19445]]
are proposing to clarify that we will eliminate these candidate CLABSI
and CAUTI cases from the CDC NHSN HAI selection process prior to random
case selection via a filtering method. The filtering method would
eliminate any cases from the validation pool for which all positive
blood or urine cultures were collected during the first or second day
following admission. We estimate that, by implementing this proposed
filtering method, the number of true events validated for CLABSI and
CAUTI will increase without increasing the sample size, which will help
us better understand the overreporting and underreporting of such
events. This proposed approach is also in support of the
recommendations provided by a recent HHS Office of Inspector General
(OIG) report, which recommended that we make better use of analytics to
ensure the integrity of hospital-reported quality data and the
resulting payment adjustments by identifying potential gaming or other
inaccurate reporting of quality data.\408\
---------------------------------------------------------------------------
\407\ We refer readers to CDC guidance on this issue and the
``CLABSI Tool Display'' on the CDC website and on QualityNet,
located at: http://www.cdc.gov/nhsn/PDFs/pscManual/2PSC_IdentifyingHAIs_NHSNcurrent.pdf and https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier3&cid=1140537256076.
\408\ April 2017 OIG report titled ``CMS Validated Hospital
Inpatient Quality Reporting Program Data, But Should Use Additional
Tools to Identify Gaming.'' Available at: https://www.oig.hhs.gov/oei/reports/oei-01-15-00320.asp.
---------------------------------------------------------------------------
A key rationale for this proposed approach is that we have found
that the yield rate for CLABSI and CAUTI, which is defined as the ratio
of the number of true CDC NHSN HAI events to the total sample size of
candidate events, is low (13 percent for CLABSI and 9 percent for
CAUTI, based on the FY 2017 validation sample). After applying the
proposed filtering method to the FY 2017 sample, we estimated that the
yield rate increased from 13 percent to 24 percent for CLABSI and from
9 percent to 17 percent for CAUTI. This increase will help CMS better
understand the number of overreporting and underreporting of such
events. A higher yield rate improves the power of the validation
methodology, meaning that CMS could potentially select fewer cases for
validation while still increasing the predictive power of the
validation methodology. A potential reduction in the amount of cases
selected for validation would decrease burden for hospitals.
In addition, because hospitals may now have fewer than four events
each of CLABSI and CAUTI that meet validation filtering requirements,
we expect a reduction in burden from some hospitals being required to
submit three or fewer medical records as part of the validation
process. We anticipate this filtering method to allow for both a richer
data sample and reduced provider burden.
We also note that the agreement rates between hospital-reported
MRSA and CDI events compared to events identified as infections by a
trained CMS abstractor using a standardized protocol (77 FR 53548) have
been lower than the agreement rates for CLABSI and CAUTI. Unlike the
true event rate issue for CLABSI and CAUTI, we have determined that the
lower overall agreement rates for MRSA and CDI is due to the
overreporting of such events. This overreporting appears to be caused
by missing or incomplete laboratory record information submitted by
hospitals on the validation templates. As a result, we will provide
additional training to hospitals regarding template completion and
medical record submission with the hope of increasing hospital
validation performance on MRSA and CDI measures.
Colon and Abdominal Hysterectomy SSI has a similarly low yield
rate, and we have begun testing a filtering option to apply to Colon
and Abdominal Hysterectomy SSI cases to increase the yield rate for
that measure as well. We anticipate providing further guidance for
Colon and Abdominal Hysterectomy SSI in future rulemaking cycles. In
this proposed rule, we are not proposing any changes to the validation
of Colon and Abdominal Hysterectomy SSI events.
8. HAC Reduction Program Scoring Methodology
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41485 through
41489), we finalized our proposal to remove domains from the HAC
Reduction Program and simply assign equal weight to each measure for
which a hospital has a measure score. As a result of this policy, we
calculate each hospital's Total HAC Score as the equally weighted
average of the hospital's measure scores. The table below displays the
weights applied to each measure under this approach. All other aspects
of the HAC Reduction Program scoring methodology remained the same,
including the calculation of measure scores as Winsorized z-scores (FY
2017 IPPS/LTCH PPS final rule 81 FR 57022 through 57025), the
determination of the 75th percentile Total HAC Score (83 FR 41480), and
the determination of the worst-performing quartile (83 FR 41481 through
41482). In this proposed rule, we are not proposing any changes to this
methodology.
Weight Applied to Each Measure by Number of Measures With Measure Score
for Hospitals With and Without a CMS PSI 90 Score Under Equal Measure
Weights Approach
------------------------------------------------------------------------
Weight applied to:
Number of CDC NHSN HAI measures ----------------------------------------
with measure score Each CDC NHSN HAI
CMS PSI 90 measure
------------------------------------------------------------------------
0.............................. 100.0 N/A.
1.............................. 50.0 50.0.
2.............................. 33.3 33.3.
3.............................. 25.0 25.0.
4.............................. 20.0 20.0.
5.............................. 16.7 16.7.
Any number..................... N/A 100.0 (equally divided
among each CDC NHSN
HAI measure with
measure score).
------------------------------------------------------------------------
9. Scoring Calculations Review and Correction Period
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41484), we renamed
the annual 30-day review and correction period to the ``Scoring
Calculations Review and Correction Period.'' The purpose of the annual
30-day review and corrections period is to allow hospitals to review
the calculation of their HAC Reduction Program scores.
The HAC Reduction Program will continue to provide hospitals with
annual confidential hospital-specific reports and discharge level
information used in the calculation of their Total HAC Scores via the
QualityNet Secure
[[Page 19446]]
Portal. Hospitals must register at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier2&cid=1138115992011 for a QualityNet Secure Portal account in order to access their
annual hospital-specific reports.
As we stated in the FY 2014 IPPS/LTCH PPS final rule (78 FR 50725
through 50728), hospitals have a period of 30 days after the
information is posted to the QualityNet Secure Portal to review their
HAC Reduction Program scores, submit questions about the calculation of
their results, and request corrections for their HAC Reduction Program
scores prior to public reporting. Hospitals may use the 30-day Scoring
Calculations Review and Correction Period to request corrections to the
following information prior to public reporting:
CMS PSI 90 measure score;
CMS PSI 90 measure result and Winsorized measure result;
CLABSI measure score;
CAUTI measure score;
Colon and Abdominal Hysterectomy SSI measure score;
MRSA Bacteremia measure score;
CDI measure score; and
Total HAC Score.
As we clarified in the FY 2018 IPPS/LTCH PPS final rule (82 FR
38270 through 38271), this 30-day period is not an opportunity for
hospitals to submit additional corrections related to the underlying
claims data for the CMS PSI 90, or to add new claims to the data
extract used to calculate the results. Hospitals have an opportunity to
review and correct claims and CDC NHSN HAI data used in the HAC
Reduction Program as detailed in the FY 2014 IPPS/LTCH PPS final rule
(78 FR 50726 through 50727), the FY 2018 IPPS/LTCH PPS final rule (82
FR 38270 through 38271), and the FY 2019 IPPS/LTCH PPS final rule (83
FR 41477 through 41478).
In this proposed rule, we are not proposing any changes our
policies regarding the scoring calculations review and correction
period.
10. Proposed Applicable Period for FY 2022 Program Year
In the FY 2018 IPPS/LTCH PPS final rule, we finalized the
applicable period for the CMS Patient Safety and Adverse Events
Composite (CMS PSI 90) as the 24-month period from July 1, 2016 through
June 30, 2018. For the CDC NHSN HAI measures (CLABSI, CAUTI, Colon and
Abdominal Hysterectomy SSI, MRSA Bacteremia, and CDI), we finalized the
use of data from CYs 2017 and 2018, that is, January 1, 2017 through
December 31, 2018, for the FY 2020 program.
Consistent with the definition specified at Sec. 412.170, we are
proposing to adopt the applicable period for the FY 2022 HAC Reduction
Program for the CMS PSI 90 as the 24-month period from July 1, 2018
through June 30, 2020, and the applicable period for CDC NHSN HAI
measures as the 24-month period from January 1, 2019 through December
31, 2020.
11. Limitation on Administrative and Judicial Review
Section 1886(p)(7) of the Act, as codified at 42 CFR 412.172(g),
provides that there will be no administrative or judicial review under
section 1869 of the Act, under section 1878 of the Act, or otherwise
for any of the following:
The criteria describing an applicable hospital in
paragraph 1886(p)(2)(A) of the Act;
The specification of hospital acquired conditions under
paragraph 1886(p)(3) of the Act;
The specification of the applicable period under paragraph
1886(p)(4) of the Act;
The provision of reports to applicable hospitals under
paragraph 1886(p)(5) of the Act; and
The information made available to the public under
paragraph 1886(p)(6) of the Act.
For additional information, we refer readers to FY 2014 IPPS/LTCH
PPS final rule (78 FR 50729) and FY 2015 IPPS/LTCH PPS final rule (79
FR 50100).
12. Proposed Regulatory Updates (42 CFR 412.172)
We are proposing to update 42 CFR 412.172(f)(2) and (4) to reflect
current policies and align across our quality programs. We are
proposing these updates to remove references to domains, which were
removed from the scoring methodology beginning with the FY 2020
calculation. We refer readers to the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41485 through 41489) for a discussion of the removal of domains
from the HAC Reduction Program and more information about the equal
weighting scoring methodology.
J. Payments for Indirect and Direct Graduate Medical Education Costs
(Sec. Sec. 412.105 and 413.75 Through 413.83)
1. Background
Section 1886(h) of the Act, as added by section 9202 of the
Consolidated Omnibus Budget Reconciliation Act (COBRA) of 1985 (Pub. L.
99-272), establishes a methodology for determining Medicare payments to
hospitals for the direct costs of approved graduate medical education
(GME) programs. Section 1886(h)(2) of the Act sets forth a methodology
for the determination of a hospital-specific base-period per resident
amount (PRA) that is calculated by dividing a hospital's allowable
direct costs of GME in a base period by its number of full-time
equivalent (FTE) residents in the base period. The base period is, for
most hospitals, the hospital's cost reporting period beginning in FY
1984 (that is, October 1, 1983 through September 30, 1984). The base
year PRA is updated annually for inflation. In general, Medicare direct
GME payments are calculated by multiplying the hospital's updated PRA
by the weighted number of FTE residents working in all areas of the
hospital complex (and at nonprovider sites, when applicable), and the
hospital's Medicare share of total inpatient days. The provisions of
section 1886(h) of the Act are implemented in regulations at 42 CFR
413.75 through 413.83.
Section 1886(d)(5)(B) of the Act provides for a payment adjustment
known as the indirect medical education (IME) adjustment under the IPPS
for hospitals that have residents in an approved GME program, in order
to account for the higher indirect patient care costs of teaching
hospitals relative to nonteaching hospitals. The regulation regarding
the calculation of this additional payment is located at 42 CFR
412.105. The hospital's IME adjustment applied to the MS-DRG payments
is calculated based on the ratio of the hospital's number of FTE
residents training in either the inpatient or outpatient departments of
the IPPS hospital to the number of inpatient hospital beds.
The calculation of both direct GME and IME payments is affected by
the number of FTE residents that a hospital is allowed to count.
Generally, the greater the number of FTE residents a hospital counts,
the greater the amount of Medicare direct GME and IME payments the
hospital will receive. Congress, through the Balanced Budget Act of
1997 (Pub. L. 105-33), established a limit (that is, a cap) on the
number of allopathic and osteopathic residents that a hospital may
include in its FTE resident count for direct GME and IME payment
purposes. Under section 1886(h)(4)(F) of the Act, for cost reporting
periods beginning on or after October 1, 1997, a hospital's unweighted
FTE count of residents for purposes of direct GME may not exceed the
hospital's unweighted FTE count for direct GME in its most recent cost
reporting period ending on or before
[[Page 19447]]
December 31, 1996. Under section 1886(d)(5)(B)(v) of the Act, a similar
limit based on the FTE count for IME during that cost reporting period
is applied effective for discharges occurring on or after October 1,
1997. Dental and podiatric residents are not included in this
statutorily mandated cap.
Section 5504 of the Affordable Care Act (Pub. L. 111-148) made a
number of statutory changes relating to the determination of a
hospital's FTE resident count for direct GME and IME payment purposes
and the manner in which FTE resident limits are calculated and applied
to hospitals under certain circumstances. Regulations implementing
these changes are discussed in the November 24, 2010 final rule (75 FR
72133) and the FY 2013 IPPS/LTCH PPS final rule (77 FR 53416).
2. Proposed Policy Changes Related to Critical Access Hospitals (CAHs)
as Nonproviders for Direct GME and IME Payment Purposes
Under the regulation governing direct GME payments to nonprovider
sites at 42 CFR 413.78(g) (and the corresponding IME regulation at 42
CFR 412.105(f)(1)(ii)(E)), a hospital can include residents training in
a nonprovider setting in its FTE count if the hospital incurs the
residents' salaries and fringe benefits while the residents are
training at that site, in addition to other requirements. Under current
policy, critical access hospitals (CAHs) that train residents in
approved residency training programs are paid 101 percent of the
reasonable costs for any costs they incur associated with training
residents in approved programs, consistent with the CAH payment
regulations at 42 CFR 413.70. We have heard concerns related to CMS'
current policy that CAHs are not considered nonprovider sites for
purposes of direct GME and IME payments, including the concern that
CMS' current policy is creating barriers to training residents in rural
areas, thereby also hindering efforts to increase the practice of
physicians in rural areas. We previously heard concerns that not
considering CAHs to be nonprovider sites would reduce training in rural
and underserved areas and affect primary care and community-based
residency training programs, such as family medicine, which train in
those areas (78 FR 50737). Stakeholders also raised concerns that not
considering CAHs to be nonprovider sites would hinder collaborative
efforts between hospitals and CAHs to recruit and retain physicians in
rural areas (78 FR 50737) and that some CAHs may be too small to
support residency training programs or may not be in a financial
position to incur the costs associated with residency training programs
(78 FR 50738). In light of these concerns, we have reexamined the
statutory language associated with this policy, issues raised in prior
rulemaking related to this policy, and the intent of the changes made
by section 5504 of the Affordable Care Act. As a result, we are
proposing to modify our policy, such that a hospital could include
residents training in a CAH in its FTE count as long as the nonprovider
setting requirements at 42 CFR 413.78(g) are met. Below we discuss our
proposal for this policy change.
We adopted our current GME payment policy regarding nonprovider
settings and CAHs in the FY 2014 IPPS/LTCH PPS final rule (78 FR 50734
through 50739). Prior to this time, we allowed a CAH the option to
either function as a nonhospital site or to incur costs for training
residents in an approved program and be paid 101 percent of the
reasonable costs for any costs associated with training residents in an
approved program. In part, our policy was driven by how we have
regarded nonhospital settings and the unique nature of CAHs. Although
we generally had used the term ``nonhospital'' to describe the training
sites in which time spent by residents training outside of the hospital
setting may be counted for both direct GME and IME payment purposes, we
acknowledged in the FY 2014 IPPS/LTCH PPS final rule that we sometimes
used the terms ``nonhospital'' and ``nonprovider'' interchangeably (78
FR 50735). We considered that a CAH is a unique facility that, by
definition, is not always a hospital and noted that, because a CAH is
generally not considered a ``hospital'' under section 1861(e) of the
Act, a CAH could be treated as a nonhospital site for GME purposes (78
FR 50735).
Section 5504(a) of the Affordable Care Act amended sections
1886(d)(5)(B)(iv)(II) and 1886(h)(4)(E) of the Act, on a prospective
basis, to further address the setting in which time spent by residents
training outside of the hospital setting may be counted for both direct
GME and IME payment purposes. In particular, the statute was amended to
reference a ``nonprovider.'' As a result of this legislative change and
because a CAH is defined as a ``provider of services'' under section
1861(u) of the Act, we finalized our current policy, effective for
portions of cost reporting periods occurring on or after October 1,
2013.
Section 5504 of the Affordable Care Act made several changes to the
requirements a hospital must meet in order to include residents
training in a nonprovider setting in its FTE count. As we noted in
prior rulemaking, these changes include the requirement that a hospital
need only incur residents' salaries and fringe benefits in order to
count the residents as opposed to incurring ``all or substantially
all'' of the costs of the training at the nonprovider site and the
ability for more than one hospital to count FTE residents training at a
single nonprovider site (75 FR 72136 through 72139). We believe these
changes were intended to promote the training of residents at sites
outside of the IPPS hospital setting, many of which provide access to
care for patients in rural and underserved areas. Furthermore, we
reassessed and agree with prior comments we have received stating that
the intent of section 5504 was to reduce the administrative burden
associated with counting residency training time in settings engaged in
patient care outside of the IPPS hospital setting (78 FR 50736).
Therefore, we believe that, to the extent possible, in accordance with
current statutory language, it is important to support residency
training in rural and underserved areas, including residency training
at CAHs.
While a CAH is considered a ``provider of services'' under section
1861(u) of the Act, we acknowledge that the term ``nonprovider'' is not
explicitly defined in the statute. Furthermore, section 1861(e) of the
Act, which states in part that the term ``hospital'' does not include,
unless the context otherwise requires, a critical access hospital (as
defined in section 1861(mm)(1) of the Act), underscores the sometimes
ambiguous status of CAHs. We believe that the lack of both an explicit
statutory definition of ``nonprovider'' and a definitive determination
as to whether a CAH is considered a hospital along with the fact that a
CAH is a facility primarily engaged in patient care (we refer readers
to section 1886(h)(5)(K) of the Act which states that the term
``nonprovider setting that is primarily engaged in furnishing patient
care'' means a nonprovider setting in which the primary activity is the
care and treatment of patients, as defined by the Secretary), provides
flexibility within the current statutory language to consider a CAH as
a ``nonprovider'' setting for direct GME and IME payment purposes.
Therefore, in order to support the training of residents in rural
and underserved areas, we are proposing that, effective with portions
of cost
[[Page 19448]]
reporting periods beginning October 1, 2019, a hospital may include FTE
residents training at a CAH in its FTE count as long as it meets the
nonprovider setting requirements currently included at 42 CFR
412.105(f)(1)(ii)(E) and 413.78(g). We are not proposing to change our
policy with respect to CAHs incurring the costs of training residents.
That is, a CAH may continue to incur the costs of training residents in
an approved residency training program(s) and receive payment based on
101 percent of the reasonable costs for these training costs. If this
proposal is finalized, CMS will work closely with HRSA and the Federal
Office of Rural Health Policy to communicate the increased regulatory
flexibility to CAHs as well as existing residency programs and the
options it affords for increasing rural residency training. We are
seeking public comments on this proposed policy change.
3. Notice of Closure of Teaching Hospital and Opportunity To Apply for
Available Slots
a. Background
Section 5506 of the Affordable Care Act (Pub. L. 111-148), as
amended by the Health Care and Education Reconciliation Act of 2010
(Pub. L. 111-152) (collectively, the ``Affordable Care Act''),
authorizes the Secretary to redistribute residency slots after a
hospital that trained residents in an approved medical residency
program closes. Specifically, section 5506 of the Affordable Care Act
amended the Act by adding subsection (vi) to section 1886(h)(4)(H) of
the Act and modifying language at section 1886(d)(5)(B)(v) of the Act,
to instruct the Secretary to establish a process to increase the FTE
resident caps for other hospitals based upon the FTE resident caps in
teaching hospitals that closed ``on or after a date that is 2 years
before the date of enactment'' (that is, March 23, 2008). In the CY
2011 Outpatient Prospective Payment System (OPPS) final rule with
comment period (75 FR 72212), we established regulations at 42 CFR
413.79(o) and an application process for qualifying hospitals to apply
to CMS to receive direct GME and IME FTE resident cap slots from the
hospital that closed. We made certain modifications to those
regulations in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53434), and
we made changes to the section 5506 application process in the FY 2015
IPPS/LTCH PPS final rule (79 FR 50122 through 50134). The procedures we
established apply both to teaching hospitals that closed on or after
March 23, 2008, and on or before August 3, 2010, and to teaching
hospitals that close after August 3, 2010.
b. Notice of Closure of Good Samaritan Hospital Located in Dayton, OH
and the Application Process--Round 14
CMS has learned of the closure of Good Samaritan Hospital, located
in Dayton, OH (CCN 360052). Accordingly, this notice serves to notify
the public of the closure of this teaching hospital and initiate
another round of the section 5506 application and selection process.
This round will be the 14th round (``Round 14'') of the application and
selection process. The table below contains the identifying information
and IME and direct GME FTE resident caps for the closed teaching
hospital, which is part of the Round 14 application process under
section 5506 of the Affordable Care Act.
--------------------------------------------------------------------------------------------------------------------------------------------------------
Direct GME FTE
CBSA IME FTE resident cap resident cap
CCN Provider name City and state code Terminating date (including +/-MMA (including +/-MMA
sec. 422 \1\) sec. 422 \1\)
--------------------------------------------------------------------------------------------------------------------------------------------------------
360052........................... Good Samaritan Dayton, OH.......... 19380 July 23, 2018....... 55.60 + 7.00 sec. 58.89 + 3.14 sec.
Hospital. 422 increase = 422 increase =
62.60.\2\ 62.03.\3\
--------------------------------------------------------------------------------------------------------------------------------------------------------
\1\ Section 422 of the MMA, Public Law 108-173, redistributed unused IME and direct GME residency slots effective July 1, 2005.
\2\ Good Samaritan Hospital's 1996 IME FTE resident cap is 55.60. Under section 422 of the MMA, the hospital received an increase of 7.00 to its IME FTE
resident cap: 55.60 + 7.00 = 62.60.
\3\ Good Samaritan Hospital's 1996 direct GME FTE resident cap is 58.89. Under section 422 of the MMA, the hospital received an increase of 3.14 to its
direct GME FTE resident cap: 58.89 + 3.14 = 62.03.
c. Application Process for Available Resident Slots
The application period for hospitals to apply for slots under
section 5506 of the Affordable Care Act is 90 days following notice to
the public of a hospital closure (77 FR 53436). Therefore, hospitals
that wish to apply for and receive slots from the FTE resident caps of
closed Good Samaritan Hospital, located in Dayton, OH, must submit
applications (Section 5506 Application Form posted on Direct Graduate
Medical Education (DGME) website as noted at the end of this section)
directly to the CMS Central Office no later than July 22, 2019. The
mailing address for the CMS Central Office is included on the
application form. Applications must be received by the CMS Central
Office by the July 22, 2019 deadline date. It is not sufficient for
applications to be postmarked by this date.
After an applying hospital sends a hard copy of a section 5506 slot
application to the CMS Central Office mailing address, the hospital is
encouraged to notify the CMS Central Office of the mailed application
by sending an email to: [email protected]. In the email,
the hospital should state: ``On behalf of [insert hospital name and
Medicare CCN#], I, [insert your name], am sending this email to notify
CMS that I have mailed to CMS a hard copy of a section 5506 application
under Round 14 due to the closure of Good Samaritan Hospital. If you
have any questions, please contact me at [insert phone number] or
[insert your email address].'' An applying hospital should not attach
an electronic copy of the application to the email. The email will only
serve to notify the CMS Central Office to expect a hard copy
application that is being mailed to the CMS Central Office.
We have not established a deadline by when CMS will issue the final
determinations to hospitals that receive slots under section 5506 of
the Affordable Care Act. However, we review all applications received
by the deadline and notify applicants of our determinations as soon as
possible.
We refer readers to the CMS Direct Graduate Medical Education
(DGME) website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/DGME.html to download a copy of the
section 5506 application form (Section 5506 Application Form) that
hospitals must use to apply for slots under section 5506 of the
Affordable Care Act. Hospitals should also access this same
[[Page 19449]]
website for a list of additional section 5506 guidelines for the policy
and procedures for applying for slots, and the redistribution of the
slots under sections 1886(h)(4)(H)(vi) and 1886(d)(5)(B)(v) of the Act.
K. Rural Community Hospital Demonstration Program
1. Introduction
The Rural Community Hospital Demonstration was originally
authorized for a 5-year period by section 410A of the Medicare
Prescription Drug, Improvement, and Modernization Act of 2003 (MMA)
(Pub. L. 108-173), and extended for another 5-year period by sections
3123 and 10313 of the Affordable Care Act (Pub. L. 111-148).
Subsequently, section 15003 of the 21st Century Cures Act (Pub. L. 114-
255), enacted December 13, 2016, amended section 410A of Public Law
108-173 to require a 10-year extension period (in place of the 5-year
extension required by the Affordable Care Act, as further discussed
below). Section 15003 also required that, no later than 120 days after
enactment of Public Law 114-255, the Secretary had to issue a
solicitation for applications to select additional hospitals to
participate in the demonstration program for the second 5 years of the
10-year extension period, so long as the maximum number of 30 hospitals
stipulated by Public Law 114-148 was not exceeded. In this proposed
rule, we are providing a description of the provisions of section 15003
of Public Law 114-255, our final policies for implementation, and the
finalized budget neutrality methodology for the extension period
authorized by section 15003 of Public Law 114-255. We are including a
discussion of the budget neutrality methodology used in previous final
rules for periods prior to the extension period, as well as for this
upcoming fiscal year. In addition, we will provide an update on the
reconciliation of actual and estimated costs of the demonstration for
FYs 2014 and 2015.
2. Background
Section 410A(a) of Public Law 108-173 required the Secretary to
establish a demonstration program to test the feasibility and
advisability of establishing rural community hospitals to furnish
covered inpatient hospital services to Medicare beneficiaries. The
demonstration pays rural community hospitals under a reasonable cost-
based methodology for Medicare payment purposes for covered inpatient
hospital services furnished to Medicare beneficiaries. A rural
community hospital, as defined in section 410A(f)(1), is a hospital
that--
Is located in a rural area (as defined in section
1886(d)(2)(D) of the Act) or is treated as being located in a rural
area under section 1886(d)(8)(E) of the Act;
Has fewer than 51 beds (excluding beds in a distinct part
psychiatric or rehabilitation unit) as reported in its most recent cost
report;
Provides 24-hour emergency care services; and
Is not designated or eligible for designation as a CAH
under section 1820 of the Act.
Section 410A of Public Law 108-173 required a 5-year period of
performance. Subsequently, sections 3123 and 10313 of Public Law 111-
148 required the Secretary to conduct the demonstration program for an
additional 5-year period, to begin on the date immediately following
the last day of the initial 5-year period. Public Law 111-148 required
the Secretary to provide for the continued participation of rural
community hospitals in the demonstration program during the 5-year
extension period, in the case of a rural community hospital
participating in the demonstration program as of the last day of the
initial 5-year period, unless the hospital made an election to
discontinue participation. In addition, Public Law 111-148 limited the
number of hospitals participating to no more than 30. We refer readers
to previous final rules for a summary of the selection and
participation of these hospitals. Starting from December 2014 and
extending through December 2016, the 21 hospitals that were still
participating in the demonstration ended their scheduled periods of
performance on a rolling basis, respectively, according to the end
dates of the hospitals' cost report periods.
3. Provisions of the 21st Century Cures Act (Pub. L. 114-255) and
Finalized Policies for Implementation
a. Statutory Provisions
As stated earlier, section 15003 of Public Law 114-255 further
amended section 410A of Public Law 108-173 to require the Secretary to
conduct the Rural Community Hospital Demonstration for a 10-year
extension period (in place of the 5-year extension period required by
Pub. L. 111-148), beginning on the date immediately following the last
day of the initial 5-year period under section 410A(a)(5) of Public Law
108-173. Thus, the Secretary is required to conduct the demonstration
for an additional 5-year period. Specifically, section 15003 of Public
Law 114-255 amended section 410A(g)(4) of Public Law 108-173 to require
that, for hospitals participating in the demonstration as of the last
day of the initial 5-year period, the Secretary shall provide for
continued participation of such rural community hospitals in the
demonstration during the 10-year extension period, unless the hospital
makes an election, in such form and manner as the Secretary may
specify, to discontinue participation. Furthermore, section 15003 of
Public Law 114-255 added subsection (g)(5) to section 410A of Public
Law 108-173 to require that, during the second 5 years of the 10-year
extension period, the Secretary shall apply the provisions of section
410A(g)(4) of Public Law 108-173 to rural community hospitals that are
not described in subsection (g)(4) but that were participating in the
demonstration as of December 30, 2014, in a similar manner as such
provisions apply to hospitals described in subsection (g)(4).
In addition, section 15003 of Public Law 114-255 amended section
410A of Public Law 108-173 to add paragraph (g)(6)(A) which requires
that the Secretary issue a solicitation for applications no later than
120 days after enactment of paragraph (g)(6) to select additional rural
community hospitals located in any State to participate in the
demonstration program for the second 5 years of the 10-year extension
period, without exceeding the maximum number of hospitals (that is, 30)
permitted under section 410A(g)(3) of Pub. L. 108-173 (as amended by
Public Law 111-148). Section 410A(g)(6)(B) provides that, in
determining which hospitals submitting an application pursuant to this
solicitation are to be selected for participation in the demonstration,
the Secretary must give priority to rural community hospitals located
in one of the 20 States with the lowest population densities, as
determined using the 2015 Statistical Abstract of the United States.
The Secretary may also consider closures of hospitals located in rural
areas in the State in which an applicant hospital is located during the
5-year period immediately preceding the date of enactment of Public Law
114-255 (December 13, 2016), as well as the population density of the
State in which the rural community hospital is located.
(b) Terms of Participation for the Extension Period Authorized by
Public Law 114-255
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38280), we finalized
our policy with regard to the effective date for the application of the
reasonable cost-based payment methodology under
[[Page 19450]]
the demonstration for those previously participating hospitals choosing
to participate in the second 5-year extension period. According to our
finalized policy, each previously participating hospital began the
second 5 years of the 10-year extension period and payment for services
provided under the cost-based payment methodology under section 410A of
Public Law 108-173 (as amended by section 15003 of Pub. L. 114-255) on
the date immediately after the period of performance ended under the
first 5-year extension period.
Seventeen of the 21 hospitals that completed their periods of
participation under the extension period authorized by Public Law 111-
148 elected to continue in the second 5-year extension period for the
full second 5-year extension period. (Of the four hospitals that did
not elect to continue participating, three hospitals converted to CAH
status during the time period of the second 5-year extension period.)
Therefore, the 5-year period of performance for each of these hospitals
started on dates beginning May 1, 2015 and extending through January 1,
2017. On November 20, 2017, we announced that, as a result of the
solicitation issued earlier in the year responding to the requirement
in Public Law 114-255, 13 additional hospitals were selected to
participate in the demonstration in addition to these 17 hospitals
continuing participation from the first 5-year extension period.
(Hereafter, these two groups are referred to as ``newly participating''
and ``previously participating'' hospitals, respectively.) In addition,
we announced that each of these newly participating hospitals would
begin its 5-year period of participation effective with the start of
the first cost reporting period on or after October 1, 2017. One of the
hospitals selected from the solicitation in 2017 withdrew from the
demonstration program, prior to beginning participation in the
demonstration on July 1, 2018. Therefore, 29 hospitals participated in
the demonstration in FYs 2018 and 2019, and are scheduled to
participate in FY 2020.
4. Budget Neutrality
a. Statutory Budget Neutrality Requirement
Section 410A(c)(2) of Public Law 108-173 requires that, in
conducting the demonstration program under this section, the Secretary
shall ensure that the aggregate payments made by the Secretary do not
exceed the amount which the Secretary would have paid if the
demonstration program under this section was not implemented. This
requirement is commonly referred to as ``budget neutrality.''
Generally, when we implement a demonstration program on a budget
neutral basis, the demonstration program is budget neutral on its own
terms; in other words, the aggregate payments to the participating
hospitals do not exceed the amount that would be paid to those same
hospitals in the absence of the demonstration program. Typically, this
form of budget neutrality is viable when, by changing payments or
aligning incentives to improve overall efficiency, or both, a
demonstration program may reduce the use of some services or eliminate
the need for others, resulting in reduced expenditures for the
demonstration program's participants. These reduced expenditures offset
increased payments elsewhere under the demonstration program, thus
ensuring that the demonstration program as a whole is budget neutral or
yields savings. However, the small scale of this demonstration program,
in conjunction with the payment methodology, made it extremely unlikely
that this demonstration program could be held to budget neutrality
under the methodology normally used to calculate it--that is, cost-
based payments to participating small rural hospitals were likely to
increase Medicare outlays without producing any offsetting reduction in
Medicare expenditures elsewhere. In addition, a rural community
hospital's participation in this demonstration program would be
unlikely to yield benefits to the participants if budget neutrality
were to be implemented by reducing other payments for these same
hospitals. Therefore, in the 12 IPPS final rules spanning the period
from FY 2005 through FY 2016, we adjusted the national inpatient PPS
rates by an amount sufficient to account for the added costs of this
demonstration program, thus applying budget neutrality across the
payment system as a whole rather than merely across the participants in
the demonstration program. (A different methodology was applied for FY
2017.) As we discussed in the FYs 2005 through 2017 IPPS/LTCH PPS final
rules (69 FR 49183; 70 FR 47462; 71 FR 48100; 72 FR 47392; 73 FR 48670;
74 FR 43922, 75 FR 50343, 76 FR 51698, 77 FR 53449, 78 FR 50740, 77 FR
50145; 80 FR 49585; and 81 FR 57034, respectively), we believe that the
language of the statutory budget neutrality requirements permits the
agency to implement the budget neutrality provision in this manner.
b. Methodology Used in Previous Final Rules for Periods Prior to the
Extension Period Authorized by the 21st Century Cures Act (Pub. L. 114-
255)
We have generally incorporated two components into the budget
neutrality offset amounts identified in the final IPPS rules in
previous years. First, we have estimated the costs of the demonstration
for the upcoming fiscal year, generally determined from historical,
``as submitted'' cost reports for the hospitals participating in that
year. Update factors representing nationwide trends in cost and volume
increases have been incorporated into these estimates, as specified in
the methodology described in the final rule for each fiscal year.
Second, as finalized cost reports became available, we determined the
amount by which the actual costs of the demonstration for an earlier,
given year, differed from the estimated costs for the demonstration set
forth in the final IPPS rule for the corresponding fiscal year, and
incorporated that amount into the budget neutrality offset amount for
the upcoming fiscal year. If the actual costs for the demonstration for
the earlier fiscal year exceeded the estimated costs of the
demonstration identified in the final rule for that year, this
difference was added to the estimated costs of the demonstration for
the upcoming fiscal year when determining the budget neutrality
adjustment for the upcoming fiscal year. Conversely, if the estimated
costs of the demonstration set forth in the final rule for a prior
fiscal year exceeded the actual costs of the demonstration for that
year, this difference was subtracted from the estimated cost of the
demonstration for the upcoming fiscal year when determining the budget
neutrality adjustment for the upcoming fiscal year. (We note that we
have calculated this difference for FYs 2005 through 2013 between the
actual costs of the demonstration as determined from finalized cost
reports once available, and estimated costs of the demonstration as
identified in the applicable IPPS final rules for these years.)
c. Budget Neutrality Methodology for the Extension Period Authorized by
the 21st Century Cures Act (Pub. L. 114-255)
(1) General Approach
We finalized our budget neutrality methodology for periods of
participation under the second 5 years of the 10-year extension period
in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38285 through 38287).
Similar to previous
[[Page 19451]]
years, we stated in this rule, as well as in the FY 2019 IPPS/LTCH PPS
proposed and final rules (83 FR 20444 and 41503, respectively) that we
would incorporate an estimate of the costs of the demonstration,
generally determined from historical, ``as submitted'' cost reports for
the participating hospitals and appropriate update factors, into a
budget neutrality offset amount to be applied to the national IPPS
rates for the upcoming fiscal year. In addition, we stated that we
would continue to apply our general policy from previous years of
including, as a second component to the budget neutrality offset
amount, the amount by which the actual costs of the demonstration for
an earlier, given year (as determined from finalized cost reports when
available) differed from the estimated costs for the demonstration set
forth in the final IPPS rule for the corresponding fiscal year.
In the FY 2018 IPPS/LTCH PPS final rule and FY 2019 IPPS/LTCH PPS
proposed and final rules, we described several distinct components to
the budget neutrality offset amount for the specific fiscal years of
the extension period authorized by Public Law 114-255.
We will include a component to our overall methodology
similar to previous years, according to which an estimate of the costs
of the demonstration for both previously and newly participating
hospitals for the upcoming fiscal year is incorporated into a budget
neutrality offset amount to be applied to the national IPPS rates for
the upcoming fiscal year. In the FY 2019 IPPS final rule (83 FR 41506),
we included such an estimate of the costs of the demonstration for each
of FYs 2018 and 2019 into the budget neutrality offset amount for FY
2019. In this proposed rule, we are including an estimate of the costs
of the demonstration for FY 2020.
Similar to previous years, we will continue to implement
the policy of determining the difference between the actual costs of
the demonstration as determined from finalized cost reports for a given
fiscal year and the estimated costs indicated in the corresponding
year's final rule, and including that difference as a positive or
negative adjustment in the upcoming year's final rule. (For each
previously participating hospital that has decided to participate in
the second 5 years of the 10-year extension period, the cost-based
payment methodology under the demonstration began on the date
immediately following the end date of its period of performance for the
first 5-year extension period. In addition, for previously
participating hospitals that converted to CAH status during the time
period of the second 5-year extension period, the demonstration payment
methodology was applied to the date following the end date of its
period of performance for the first extension period to the date of
conversion). Therefore, for cost reporting periods starting in FYs
2015, 2016, and 2017, we will use available finalized cost reports that
detail the actual costs of the demonstration for each of these fiscal
years and incorporate these amounts into the budget neutrality
calculation.
In this proposed rule, we are identifying the amount of the
difference between actual and estimated costs based on finalized cost
reports for FY 2014; and, in addition, we are proposing that if
finalized cost reports are available we will include the amount for FY
2015 in the budget neutrality offset adjustment to be applied to the
national IPPS rates for FY 2020. In future IPPS rules, we will continue
this reconciliation, calculating the difference between actual and
estimated costs for the remaining years of the first extension period
and, as described above, the additional years of the demonstration
under the second extension period, applying this difference to the
budget neutrality offset adjustments identified in future years' final
rules.
(2) Methodology for Estimating Demonstration Costs for FY 2020
We are using a methodology similar to previous years, according to
which an estimate of the costs of the demonstration for the upcoming
fiscal year is incorporated into a budget neutrality offset amount to
be applied to the national IPPS rates for the upcoming fiscal year,
that is, FY 2020. The methodology for calculating the amount for FY
2020 will proceed according to the following steps:
Step 1: For each of the 29 participating hospitals, we will
identify the reasonable cost amount calculated under the reasonable
cost-based methodology for covered inpatient hospital services,
including swing beds, as indicated on the ``as submitted'' cost report
for the most recent cost reporting period available. (For each of these
hospitals, these ``as submitted'' cost reports are those with cost
report period end dates in CY 2017. We note that, for 3 of these
hospitals, the 5-year participation authorized by Pub. L. 114-255 will
end prior to the end of FY 2020. Therefore, consistent with previous
practice, we will prorate the cost amounts for these hospitals by the
fraction of total months in the demonstration period of participation
that fall within FY 2020 out of the total of 12 months in the fiscal
year. For example, for a hospital whose period of performance ends June
30, 2020, this prorating factor is .75. We will sum these hospital-
specific amounts to arrive at a total general amount representing the
costs for covered inpatient hospital services, including swing beds,
across the 29 participating hospitals.
Then, we will multiply this amount by the FYs 2018, 2019 and 2020
IPPS market basket percentage increases, which are formulated by the
CMS Office of the Actuary. The result for each participating hospital
will be the general estimated reasonable cost amount for covered
inpatient hospital services for FY 2020.
Consistent with our methods in previous years for formulating this
estimate, we will apply the IPPS market basket percentage increases for
FYs 2018 through 2020 to the applicable estimated reasonable cost
amounts (described above) in order to model the estimated FY 2020
reasonable cost amount under the demonstration. We believe that the
IPPS market basket percentage increases appropriately indicate the
trend of increase in inpatient hospital operating costs under the
reasonable cost methodology for the years involved.
Step 2: For each of the participating hospitals, we identify the
estimated amount that would otherwise be paid in FY 2020 under
applicable Medicare payment methodologies for covered inpatient
hospital services, including swing beds (as indicated on the same set
of ``as submitted'' cost reports as in Step 1), if the demonstration
were not implemented. (Also, similar to step 1, we are prorating the
amounts for hospitals whose period of participation ends during FY 2020
by the fraction of total months in the demonstration period of
participation for the hospital that falls within FY 2020 out of the
total of 12 months in the fiscal year). We will sum these hospital-
specific amounts, and, in turn, multiply this sum by the FYs 2018, 2019
and 2020 IPPS applicable percentage increases. This methodology differs
from Step 1, in which we apply the market basket percentage increases
to the hospitals' applicable estimated reasonable cost amount for
covered inpatient hospital services. We believe that the IPPS
applicable percentage increases are appropriate factors to update the
estimated amounts that generally would otherwise be paid without the
demonstration. This is because IPPS payments constitute the majority of
payments that would otherwise be made without the demonstration and the
[[Page 19452]]
applicable percentage increase is the factor used under the IPPS to
update the inpatient hospital payment rates.
Step 3: We will subtract the amount derived in Step 2 from the
amount derived in Step 1. According to our methodology, the resulting
amount indicates the total difference for the 29 hospitals (for covered
inpatient hospital services, including swing beds), which will be the
general estimated amount of the costs of the demonstration for FY 2020.
For this proposed rule, the resulting amount is $61,970,567, which
we are proposing to include in the budget neutrality offset adjustment
for FY 2020. This estimated amount is based on the specific assumptions
regarding the data sources used, that is, recently available ``as
submitted'' cost reports and historical update factors for cost and
payment. If updated data become available prior to the FY 2020 IPPS/
LTCH PPS final rule, we will use them as appropriate to estimate the
costs for the demonstration program for FY 2020 in accordance with our
methodology for determining the budget neutrality estimate. Therefore,
the estimated budget neutrality offset amount may change in the final
rule, depending on the availability of updated data.
(3) Reconciling Actual and Estimated Costs of the Demonstration for
Previous Years (2014 and 2015)
As described earlier, we have calculated the difference for FYs
2005 through 2013 between the actual costs of the demonstration, as
determined from finalized cost reports once available, and estimated
costs of the demonstration as identified in the applicable IPPS final
rules for these years. In this proposed rule, we are identifying the
difference between the total cost of the demonstration as indicated on
finalized FY 2014 cost reports and the estimates for the costs of the
demonstration for that year's final rule, and we are proposing to
adjust the current year's budget neutrality amount by the amount
identified. If any information relevant to the determination of these
amounts (for example, a cost report reopening) would necessitate a
revision of these amounts, we will make the appropriate change and
include the determination in the FY 2020 IPPS/LTCH PPS final rule.
Furthermore, if the needed costs reports are available in time for the
FY 2020 IPPS/LTCH PPS final rule, we also will identify the difference
between the total cost of the demonstration based on finalized FY 2015
cost reports and the estimates for the costs of the demonstration for
that year, and incorporate that amount into the budget neutrality
offset amount for FY 2020.
Currently, finalized cost reports are available for the 22
hospitals that completed a cost reporting period beginning in FY 2014
according to the demonstration's reasonable cost-based payment
methodology. The actual costs of the demonstration for FY 2014 (that
is, the amount from finalized cost reports for the 22 hospitals that
were paid under the demonstration reasonable cost-based payment
methodology for cost reporting periods with start dates during FY
2014), fell short of the estimated amount that was finalized in the FY
2014 IPPS/LTCH final rule for FY 2014 by $14,932,060.
We note that the amounts identified for the actual cost of the
demonstration, determined from finalized cost reports, is less than the
amount that was identified in the final rule for the respective year.
Therefore, in keeping with previous policy finalized in situations when
the costs of the demonstration fell short of the amount estimated in
the corresponding year's final rule, we will be including this
component as a negative adjustment to the budget neutrality offset
amount for the current fiscal year.
(4) Total Proposed Budget Neutrality Offset Amount for FY 2020
Therefore, for this FY 2020 IPPS/LTCH PPS proposed rule, we are
proposing to incorporate the following components into the calculation
of the total budget neutrality offset for FY 2020:
The amount determined under section IV.K.4.c.(2) of the
preamble of this proposed rule, representing the difference applicable
to FY 2020 between the sum of the estimated reasonable cost amounts
that would be paid under the demonstration to the 29 participating
hospitals for covered inpatient hospital services and the sum of the
estimated amounts that would generally be paid if the demonstration had
not been implemented. This estimated amount is $61,970,567.
The amount determined under section IV.K.4.c.(3) of the
preamble of this proposed rule according to which the actual costs of
the demonstration for FY 2014 for the 22 hospitals that completed a
cost reporting period beginning in FY 2014 differ from the estimated
amount that was incorporated into the budget neutrality offset amount
for FY 2014 in the FY 2014 IPPS/LTCH PPS final rule. Analysis of this
set of cost reports shows that the actual costs of the demonstration
fell short of the estimated amount finalized in the FY 2014 IPPS/LTCH
PPS final rule by $14,932,060. In keeping with previously finalized
policy, we are proposing to apply this difference, according to which
the actual costs of the demonstration for FY 2014 fell short of the
estimated amount determined in the final rule for that fiscal year by
reducing the budget neutrality offset amount for FY 2020 by this
amount.
Therefore, for FY 2020, the proposed total budget neutrality offset
amount that we will be applying is the estimated amount for FY 2020
(that is, $61,970,567) minus the amount by which the actual costs of
the demonstration fell short of the estimated amount for FY 2014 (that
is, $14,932,060). This total is $47,038,507. If updated data become
available prior to the FY 2020 IPPS/LTCH PPS final rule, we would use
them to the extent appropriate to determine the budget neutrality
offset amount for FY 2020. Therefore, the amount of the budget
neutrality offset amount may change in the FY 2020 IPPS/LTCH PPS final
rule. Furthermore, if the needed costs reports are available in time
for the FY 2020 IPPS/LTCH PPS final rule, we also will identify the
difference between the total cost of the demonstration based on
finalized FY 2015 cost reports and the estimates for the costs of the
demonstration for that year, and incorporate that amount into the final
budget neutrality offset amount for FY 2020.
V. Proposed Changes to the IPPS for Capital-Related Costs
A. Overview
Section 1886(g) of the Act requires the Secretary to pay for the
capital-related costs of inpatient acute hospital services in
accordance with a prospective payment system established by the
Secretary. Under the statute, the Secretary has broad authority in
establishing and implementing the IPPS for acute care hospital
inpatient capital-related costs. We initially implemented the IPPS for
capital-related costs in the FY 1992 IPPS final rule (56 FR 43358). In
that final rule, we established a 10-year transition period to change
the payment methodology for Medicare hospital inpatient capital-related
costs from a reasonable cost-based payment methodology to a prospective
payment methodology (based fully on the Federal rate).
FY 2001 was the last year of the 10-year transition period that was
established to phase in the IPPS for hospital inpatient capital-related
costs. For cost reporting periods beginning in FY 2002, capital IPPS
payments are based solely on the Federal rate for
[[Page 19453]]
almost all acute care hospitals (other than hospitals receiving certain
exception payments and certain new hospitals). (We refer readers to the
FY 2002 IPPS final rule (66 FR 39910 through 39914) for additional
information on the methodology used to determine capital IPPS payments
to hospitals both during and after the transition period.)
The basic methodology for determining capital prospective payments
using the Federal rate is set forth in the regulations at 42 CFR
412.312. For the purpose of calculating capital payments for each
discharge, the standard Federal rate is adjusted as follows:
(Standard Federal Rate) x (DRG Weight) x (Geographic Adjustment
Factor (GAF)) x (COLA for hospitals located in Alaska and Hawaii) x (1
+ Capital DSH Adjustment Factor + Capital IME Adjustment Factor, if
applicable).
In addition, under Sec. 412.312(c), hospitals also may receive
outlier payments under the capital IPPS for extraordinarily high-cost
cases that qualify under the thresholds established for each fiscal
year.
B. Additional Provisions
1. Exception Payments
The regulations at 42 CFR 412.348 provide for certain exception
payments under the capital IPPS. The regular exception payments
provided under Sec. Sec. 412.348(b) through (e) were available only
during the 10-year transition period. For a certain period after the
transition period, eligible hospitals may have received additional
payments under the special exceptions provisions at Sec. 412.348(g).
However, FY 2012 was the final year hospitals could receive special
exceptions payments. For additional details regarding these exceptions
policies, we refer readers to the FY 2012 IPPS/LTCH PPS final rule (76
FR 51725).
Under Sec. 412.348(f), a hospital may request an additional
payment if the hospital incurs unanticipated capital expenditures in
excess of $5 million due to extraordinary circumstances beyond the
hospital's control. Additional information on the exception payment for
extraordinary circumstances in Sec. 412.348(f) can be found in the FY
2005 IPPS final rule (69 FR 49185 and 49186).
2. New Hospitals
Under the capital IPPS, the regulations at 42 CFR 412.300(b) define
a new hospital as a hospital that has operated (under previous or
current ownership) for less than 2 years and lists examples of
hospitals that are not considered new hospitals. In accordance with
Sec. 412.304(c)(2), under the capital IPPS, a new hospital is paid 85
percent of its allowable Medicare inpatient hospital capital-related
costs through its first 2 years of operation, unless the new hospital
elects to receive full prospective payment based on 100 percent of the
Federal rate. We refer readers to the FY 2012 IPPS/LTCH PPS final rule
(76 FR 51725) for additional information on payments to new hospitals
under the capital IPPS.
3. Payments for Hospitals Located in Puerto Rico
In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57061), we revised
the regulations at 42 CFR 412.374 relating to the calculation of
capital IPPS payments to hospitals located in Puerto Rico beginning in
FY 2017 to parallel the change in the statutory calculation of
operating IPPS payments to hospitals located in Puerto Rico, for
discharges occurring on or after January 1, 2016, made by section 601
of the Consolidated Appropriations Act, 2016 (Pub. L. 114-113). Section
601 of Public Law 114-113 increased the applicable Federal percentage
of the operating IPPS payment for hospitals located in Puerto Rico from
75 percent to 100 percent and decreased the applicable Puerto Rico
percentage of the operating IPPS payments for hospitals located in
Puerto Rico from 25 percent to zero percent, applicable to discharges
occurring on or after January 1, 2016. As such, under revised Sec.
412.374, for discharges occurring on or after October 1, 2016, capital
IPPS payments to hospitals located in Puerto Rico are based on 100
percent of the capital Federal rate.
C. Proposed Annual Update for FY 2020
The proposed annual update to the national capital Federal rate, as
provided for in 42 CFR 412.308(c), for FY 2020 is discussed in section
III. of the Addendum to this FY 2020 IPPS/LTCH PPS proposed rule.
In section II.D. of the preamble of this FY 2020 IPPS/LTCH PPS
proposed rule, we present a discussion of the MS-DRG documentation and
coding adjustment, including previously finalized policies and
historical adjustments, as well as the adjustment to the standardized
amount under section 1886(d) of the Act that we are proposing for FY
2020, in accordance with the amendments made to section 7(b)(1)(B) of
Public Law 110-90 by section 414 of the MACRA. Because these provisions
require us to make an adjustment only to the operating IPPS
standardized amount, we are not proposing to make a similar adjustment
to the national capital Federal rate (or to the hospital-specific
rates).
VI. Proposed Changes for Hospitals Excluded From the IPPS
A. Proposed Rate-of-Increase in Payments to Excluded Hospitals for FY
2020
Certain hospitals excluded from a prospective payment system,
including children's hospitals, 11 cancer hospitals, and hospitals
located outside the 50 States, the District of Columbia, and Puerto
Rico (that is, hospitals located in the U.S. Virgin Islands, Guam, the
Northern Mariana Islands, and American Samoa) receive payment for
inpatient hospital services they furnish on the basis of reasonable
costs, subject to a rate-of-increase ceiling. A per discharge limit
(the target amount, as defined in Sec. 413.40(a) of the regulations)
is set for each hospital based on the hospital's own cost experience in
its base year, and updated annually by a rate-of-increase percentage.
For each cost reporting period, the updated target amount is multiplied
by total Medicare discharges during that period and applied as an
aggregate upper limit (the ceiling as defined in Sec. 413.40(a)) of
Medicare reimbursement for total inpatient operating costs for a
hospital's cost reporting period. In accordance with Sec. 403.752(a)
of the regulations, religious nonmedical health care institutions
(RNHCIs) also are subject to the rate-of-increase limits established
under Sec. 413.40 of the regulations discussed previously.
Furthermore, in accordance with Sec. 412.526(c)(3) of the regulations,
extended neoplastic disease care hospitals also are subject to the
rate-of-increase limits established under Sec. 413.40 of the
regulations discussed previously.
As explained in the FY 2006 IPPS final rule (70 FR 47396 through
47398), beginning with FY 2006, we have used the percentage increase in
the IPPS operating market basket to update the target amounts for
children's hospitals, cancer hospitals, and RNHCIs. Consistent with the
regulations at Sec. Sec. 412.23(g), 413.40(a)(2)(ii)(A), and
413.40(c)(3)(viii), we also have used the percentage increase in the
IPPS operating market basket to update target amounts for short-term
acute care hospitals located in the U.S. Virgin Islands, Guam, the
Northern Mariana Islands, and American Samoa. In the FYs 2014 and 2015
IPPS/LTCH PPS final rules (78 FR 50747 through 50748 and 79 FR 50156
through 50157, respectively), we adopted a policy of
[[Page 19454]]
using the percentage increase in the FY 2010-based IPPS operating
market basket to update the target amounts for FY 2014 and subsequent
fiscal years for children's hospitals, cancer hospitals, RNHCIs, and
short-term acute care hospitals located in the U.S. Virgin Islands,
Guam, the Northern Mariana Islands, and American Samoa. However, in the
FY 2018 IPPS/LTCH PPS final rule, we rebased and revised the IPPS
operating basket to a 2014 base year, effective for FY 2018 and
subsequent years (82 FR 38158 through 38175), and finalized the use of
the percentage increase in the 2014-based IPPS operating market basket
to update the target amounts for children's hospitals, the 11 cancer
hospitals, RNHCIs, and short-term acute care hospitals located in the
U.S. Virgin Islands, Guam, the Northern Mariana Islands, and American
Samoa for FY 2018 and subsequent years. Accordingly, for FY 2020, the
rate-of-increase percentage to be applied to the target amount for
these hospitals would be the FY 2020 percentage increase in the 2014-
based IPPS operating market basket.
For this FY 2020 IPPS/LTCH PPS proposed rule, based on IGI's 2018
fourth quarter forecast, we estimated that the 2014-based IPPS
operating market basket update for FY 2020 would be 3.2 percent (that
is, the estimate of the market basket rate-of-increase). Based on this
estimate, the FY 2020 rate-of-increase percentage that would be applied
to the FY 2019 target amounts in order to calculate the FY 2020 target
amounts for children's hospitals, cancer hospitals, RNCHIs, and short-
term acute care hospitals located in the U.S. Virgin Islands, Guam, the
Northern Mariana Islands, and American Samoa would be 3.2 percent, in
accordance with the applicable regulations at 42 CFR 413.40. However,
we are proposing that if more recent data become available for the
final rule, we would use them to calculate the final IPPS operating
market basket update for FY 2020.
In addition, payment for inpatient operating costs for hospitals
classified under section 1886(d)(1)(B)(vi) of the Act (which we refer
to as ``extended neoplastic disease care hospitals'') for cost
reporting periods beginning on or after January 1, 2015, is to be made
as described in 42 CFR 412.526(c)(3), and payment for capital costs for
these hospitals is to be made as described in 42 CFR 412.526(c)(4).
(For additional information on these payment regulations, we refer
readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 38321 through
38322).) Section 412.526(c)(3) provides that the hospital's Medicare
allowable net inpatient operating costs for that period are paid on a
reasonable cost basis, subject to that hospital's ceiling, as
determined under Sec. 412.526(c)(1), for that period. Under section
412.526(c)(1), for each cost reporting period, the ceiling was
determined by multiplying the updated target amount, as defined in
Sec. 412.526(c)(2), for that period by the number of Medicare
discharges paid during that period. Section 412.526(c)(2)(i) describes
the method for determining the target amount for cost reporting periods
beginning during FY 2015. Section 412.526(c)(2)(ii) specifies that, for
cost reporting periods beginning during fiscal years after FY 2015, the
target amount will equal the hospital's target amount for the previous
cost reporting period updated by the applicable annual rate-of-increase
percentage specified in Sec. 413.40(c)(3) for the subject cost
reporting period (79 FR 50197).
For FY 2020, in accordance with Sec. 412.22(i) and Sec.
412.526(c)(2)(ii) of the regulations, for cost reporting periods
beginning during FY 2020, the proposed update to the target amount for
long-term care neoplastic disease hospitals (that is, hospitals
described under Sec. 412.22(i)) is the applicable annual rate-of-
increase percentage specified in Sec. 413.40(c)(3) for FY 2020, which
would be equal to the percentage increase in the hospital market basket
index, which is estimated to be the percentage increase in the 2014-
based IPPS operating market basket (that is, the estimate of the market
basket rate-of-increase). Accordingly, the proposed update to an
extended neoplastic disease care hospital's target amount for FY 2020
is 3.2 percent, which is based on IGI's 2018 fourth quarter forecast.
Furthermore, we are proposing that if more recent data become available
for the final rule, we would use that updated data to calculate the
IPPS operating market basket update for FY 2020.
B. Request for Public Comments on Methodologies and Requirements for
TEFRA Adjustments to the Rate-of-Increase Ceiling
1. General Background
Section 1886(b) of the Act, as amended by the Tax Equity and Fiscal
Responsibility Act (TEFRA) of 1982, establishes a ceiling on the
allowable rate of increase in hospital inpatient operating costs per
discharge applicable to cost reporting periods beginning on or after
October 1, 1982. However, effective with cost reporting periods
beginning on or after October 1, 1983, most hospitals are paid under
the prospective payment system (PPS) as described in section 1886(d) of
the Act, 42 CFR part 412, and Chapter 28 of the Provider Reimbursement
Manual (PRM) (CMS Pub. 15-1). Currently, hospitals that are paid under
TEFRA include cancer hospitals (11 qualified by statute under section
1886(d)(1)(B)(v) of the Act), children's hospitals, and hospitals
outside the 50 States, the District of Columbia, and Puerto Rico (that
is, short-term acute care hospitals located in the U.S. Virgin Islands,
Guam, American Samoa, and the Northern Mariana Islands). Under certain
circumstances, CMS may provide for an adjustment to the rate-of-
increase ceiling or may assign a new base period.
Medicare payment for inpatient hospital services under the TEFRA
system is made on a reasonable cost basis, as noted above, subject to a
limit or ceiling. The ceiling is determined from a hospital's target
amount per discharge updated from its base year. Specifically, a
hospital's TEFRA target amount per discharge is determined from its
total Medicare inpatient operating costs per Medicare discharge in its
base year. This target amount per discharge is updated each year for
inflation based on the IPPS operating market basket increase.
Multiplying the TEFRA target amount per discharge by the Medicare
discharges in a particular cost reporting period produces the maximum
amount (the ceiling) Medicare will pay the hospital for inpatient
hospital services. In other words, under the TEFRA system, Medicare
payment is the lesser of the reasonable costs incurred or the ceiling
amount. If a hospital's inpatient operating costs exceed the ceiling in
a cost reporting period, section 1886(b)(4)(A)(i) of the Act and
implementing regulations at Sec. 413.40 allow hospitals paid under the
TEFRA system to request adjustments to increase their Medicare payment
limits (that is, their ceiling) or to request a new base year (a
permanent revised TEFRA target amount per discharge for determining the
ceiling) to account for certain factors such as a significant change in
services or patient population.
2. TEFRA Adjustment Requests
Under the regulations at 42 CFR 413.40(g), if a hospital's
inpatient operating costs exceed the ceiling in a cost reporting
period, hospitals may request an increase to their Medicare payment
limits (that is, their ceiling) to account for cost distortions between
the base year and current year. Section 3004.1 of the PRM states that
distortions
[[Page 19455]]
in inpatient operating costs resulting in noncomparability of the cost
reporting periods are generally the result of extraordinary
circumstances, an increase in the average length of stay of Medicare
patients, or changes in the volume or intensity of direct patient care
services. Section 3004 of the PRM provides extensive examples of
noncomparability of cost reporting periods due to direct patient care
changes with calculations for increases of average length of stay,
changes in the intensity of care, as well as for additions/deletions of
services. These examples were developed many years ago to assist
providers in filing an adjustment request and to provide guidance to
MACs when reviewing and evaluating a provider's adjustment request. The
examples emphasize that the methodologies used to determine the amount
of the adjustment are based on comparisons between the base year costs
and current year costs. To receive an adjustment to its ceiling, the
provider must demonstrate that the increased Medicare costs are
reasonable, related to direct patient care services, attributable to
the circumstances specified, separately identified by the hospital,
verified by the contractor, and tie to costs quantified in its cost
report. In some cases, an adjustment may be adopted permanently and
reflected in the hospital's ceiling in subsequent cost reporting
periods.
The delivery of direct patient care services, as well as the cost
report form and instructions, have evolved since the guidance and
examples currently in section 3004 of the PRM (Pub. 15-1) were
originally developed. In this proposed rule, we are soliciting public
comments, suggestions, and recommendations regarding the methodologies
and examples provided in section 3004 of the PRM to determine an
appropriate adjustment amount, considering the current environment
facing providers paid by Medicare under the TEFRA system.
As noted above, under 42 CFR 413.40(i), hospitals can request a
permanent change to their ceiling by requesting a new base year for
determining their target amount per discharge. In accordance with 42
CFR 413.40(i)(1)(i)(B), this process is meant to account for
substantial and permanent changes in furnishing patient care services
since the base period, and, as such, the requirements are stringent.
Historically, CMS has rarely authorized assignment of a new base year
period because the adjustment mechanism discussed above is meant to
address most situations where there is distortion in costs between the
base year and the current period and providers seldom meet the criteria
for a new base period. We are requesting public comments, suggestions,
and recommendations on the possible criteria and circumstances needed
to warrant a new base period, and, importantly, the documentation that
would be required to qualify, particularly relative to and
differentiating it from an adjustment.
As stated earlier, we are inviting comments, suggestions, and
recommendations for regulatory and other policy changes to the TEFRA
adjustment process. We also are interested in feedback on whether or
not there should be standardization in the supporting documentation
(such as electronic workbooks) as part of TEFRA adjustment requests
and, if so, we invite commenters to provide specific examples.
C. Critical Access Hospitals (CAHs)
1. Background
Section 1820 of the Act provides for the establishment of Medicare
Rural Hospital Flexibility Programs (MRHFPs), under which individual
States may designate certain facilities as critical access hospitals
(CAHs). Facilities that are so designated and meet the CAH conditions
of participation under 42 CFR part 485, subpart F, will be certified as
CAHs by CMS. Regulations governing payments to CAHs for services to
Medicare beneficiaries are located in 42 CFR part 413.
2. Proposed Change Related to CAH Payment for Ambulance Services
a. Background
Section 1834(l) of the Act sets forth the payment rules for
ambulance services. Generally, payment to ambulance providers and
suppliers for ambulance services are made under the Ambulance Fee
Schedule. Section 205 of BIPA (Pub. L. 106-554) amended section 1834(l)
of the Act by adding a paragraph (8), which, effective for services
furnished on or after December 21, 2000, provided that the Secretary
would pay the reasonable costs incurred in furnishing ambulance
services if such services are furnished by a CAH (as defined in section
1861(mm)(1) of the Act), or by an entity that is owned and operated by
a CAH, but only if the CAH or entity is the only provider or supplier
of ambulance services that is located within a 35-mile drive of the
CAH. Regulations implementing section 1834(l)(8) of the Act are set
forth at 42 CFR 413.70(b)(5). For purposes of this discussion, the term
``provider'' of ambulance services means all Medicare-participating
providers that submit claims under Medicare for ambulance services (for
example, hospitals, CAHs, skilled nursing facilities (SNFs), and home
health agencies (HHAs)), and the term ``supplier'' of ambulance
services means an entity that provides ambulance services and that is
independent of any Medicare-participating or non-Medicare-participating
provider. The terms ``supplier'' and ``provider of services'' are
defined in sections 1861(d) and (u) of the Act, respectively, and the
term ``provider or supplier of ambulance services'' appears in section
1834(l)(8) of the Act.
Section 3128(a) of the Affordable Care Act (Pub. L. 111-148)
amended section 1834(l)(8) of the Act by specifying that payment for
the reasonable costs incurred by a CAH or by an entity that is owned
and operated by a CAH in furnishing ambulance services would be at
``101 percent'' of the reasonable costs incurred in furnishing such
services. As such, section 3128(a) of the Affordable Care Act increased
payment for ambulance services furnished by CAHs or entities owned and
operated by CAHs to 101 percent of the reasonable costs, subject to the
requirements outlined in section 1834(l)(8) of the Act, effective for
cost reporting periods beginning on or after January 1, 2004. We
amended Sec. 413.70(b)(5)(i) in the FY 2011 IPPS/LTCH PPS final rule
(75 FR 50361) to conform to the statute, as amended.
More recently, in the FY 2012 IPPS/LTCH PPS final rule (76 FR
51729), to ensure consistency between the regulations and statute, we
revised Sec. 413.70(b)(5)(i) by adding a new paragraph (C) to state
that, effective for cost reporting periods beginning on or after
October 1, 2011, payment for ambulance services furnished by a CAH or
by a CAH-owned and operated entity is 101 percent of the reasonable
costs of the CAH or the entity in furnishing those services, but only
if the CAH or the entity is the only provider or supplier of ambulance
services located within a 35-mile drive of the CAH. If there is no
provider or supplier of ambulance services located within a 35-mile
drive of the CAH and there is an entity that is owned and operated by a
CAH that is more than a 35-mile drive from the CAH, payment for
ambulance services furnished by that entity is 101 percent of the
reasonable costs of the entity in furnishing those services, but only
if the entity is the closest provider or supplier of ambulance services
to the CAH. Therefore, a CAH is paid 101 percent of the reasonable
costs for its ambulance services only if there is no other provider or
supplier of ambulance
[[Page 19456]]
services within a 35-mile drive of the CAH. If there is another
provider or supplier of ambulance services located within a 35-mile
drive of the CAH, the CAH is paid for its ambulance services using the
Ambulance Fee Schedule.
b. Proposed Change
As indicated above and in accordance with statutory language at
section 1834(l)(8) of the Act, Sec. 413.70(b)(5)(i)(C) currently
states in relevant part that payment for ambulance services furnished
by a CAH or an entity that is owned and operated by a CAH is 101
percent of the reasonable costs of the CAH or the entity in furnishing
those services, but only if the CAH or the entity is the only provider
or supplier of ambulance services located within a 35-mile drive of the
CAH. It has been brought to our attention that there may be instances
where a provider or supplier of ambulance services that is not owned or
operated by the CAH is located within a 35-mile drive of the CAH, but
that provider or supplier of ambulance services is not legally
authorized to furnish ambulance services to transport individuals
either to or from the CAH. For example, consider the scenario where an
ambulance supplier is located within a 35-mile drive of a CAH, but in a
different State, and the ambulance supplier is not legally authorized
(for example, the supplier of ambulance services does not have the
appropriate State licensure) to furnish ambulance services in the State
in which the CAH is located. Under this scenario, Sec.
413.70(b)(5)(i)(C) requires that the CAH be paid for its ambulance
services using the Ambulance Fee Schedule, even though the out-of-state
ambulance supplier cannot actually furnish ambulance services to
transport individuals either to or from the CAH. We believe this
outcome is not consistent with the intent of the Medicare Rural
Hospital Flexibility Program, which is to provide access to care to
individuals living in remote and rural areas. A CAH may provide crucial
health care services to individuals living in a remote and rural area;
however, if transport services to that CAH are limited due to lack of
ambulance services, health care services available to individuals
living in the CAH's service area may also be limited. A lack of
ambulance services within the CAH's service area could limit access to
care for individuals living in these remote and rural areas,
particularly in emergency situations and when individuals have no other
mode of transportation due to hazardous traveling conditions. In
general, payment for ambulance services based on 101 percent of the
reasonable costs is higher than payment made under the Ambulance Fee
Schedule. This higher payment is intended to provide CAHs with
sufficient payment to sustain their own ambulance services when no
other ambulance services are available in their service area. If a CAH
does not receive reasonable cost-based payments for its ambulance
services because there is another provider or supplier of ambulance
services within a 35-mile drive of the CAH, even if that provider or
supplier is not legally authorized to transport individuals either to
or from the CAH, the CAH may be unable to support the costs of
providing ambulance services in its service area.
Therefore, we are proposing to address this ``gap'' in the current
regulation at Sec. 413.70(b)(5)(i)(C) by revising our interpretation
of the requirement in section 1834(l)(8)(B) of the Act that the CAH or
the entity owned and operated by the CAH be the only provider or
supplier of ambulance services that is located within a 35-mile drive
of such a CAH, to exclude consideration of ambulance providers or
suppliers that are not legally authorized to furnish ambulance services
to transport individuals either to or from the CAH. Specifically, we
would interpret section 1834(l)(8)(B) of the Act to mean that the CAH
or the CAH-owned and operated entity must be the only provider or
supplier of ambulance services within a 35-mile drive of the CAH that
is legally authorized to furnish ambulance services to individuals
transported to or from the CAH. We believe this is a reasonable reading
of the statutory language because it retains the requirement that the
CAH or the CAH-owned and operated entity be the only provider or
supplier of ambulance services within a 35-mile drive of the CAH that
is available to transport individuals either to or from the CAH. We are
proposing to revise Sec. 413.70(b)(5)(i) of the regulations to reflect
this revised interpretation by adding a new paragraph (D) to state
that, effective for cost reporting periods beginning on or after
October 1, 2019, payment for ambulance services furnished by a CAH or
by an entity that is owned and operated by a CAH is 101 percent of the
reasonable costs of the CAH or the entity in furnishing those services,
but only if the CAH or the entity is the only provider or supplier of
ambulance services located within a 35-mile drive of the CAH, excluding
ambulance providers or suppliers that are not legally authorized to
furnish ambulance services to transport individuals either to or from
the CAH. Consistent with the existing policy under Sec.
413.70(b)(5)(i)(C), if there is no provider or supplier of ambulance
services located within a 35-mile drive of the CAH and there is an
entity that is owned and operated by a CAH that is more than a 35-mile
drive from the CAH, payment for ambulance services furnished by that
entity is 101 percent of the reasonable costs of the entity in
furnishing those services, but only if the entity is the closest
provider or supplier of ambulance services to the CAH. We also are
proposing a conforming change to Sec. 413.70(b)(5)(i)(C) to make that
existing provision effective only through September 30, 2019.
As stated earlier in this discussion, if a CAH does not receive
reasonable cost-based payments for its ambulance services, which in
general provide higher payment compared to the Ambulance Fee Schedule,
the CAH may be unable to support the costs of providing ambulance
services in its service area. As such, we believe that our proposed
change to allow for payment based on 101 percent of the reasonable
costs of the CAH or the CAH-owned and operated entity in furnishing
ambulance services, in a situation where there is another provider or
supplier of ambulance services located within a 35-mile drive of the
CAH that is not legally authorized to transport individuals either to
or from the CAH, would improve access to care in remote and rural
areas, particularly in situations where an individual is experiencing
an emergency and can only receive the necessary services through
ambulance transport to or from the CAH or in situations where no other
mode of transportation is advisable. Furthermore, we believe our
proposal is consistent with the original purpose of section 1834(l)(8)
of the Act, which was to help ensure that areas served by CAHs would
have adequate access to ambulance services.
3. Frontier Community Health Integration Project (FCHIP) Demonstration
As discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41516
through 41517), section 123 of the Medicare Improvements for Patients
and Providers Act of 2008 (Pub. L. 110-275), as amended by section 3126
of the Affordable Care Act, authorizes a demonstration project to allow
eligible entities to develop and test new models for the delivery of
health care services in eligible counties in order to improve access to
and better integrate the delivery of acute care, extended care and
other health care services to
[[Page 19457]]
Medicare beneficiaries. The demonstration is titled ``Demonstration
Project on Community Health Integration Models in Certain Rural
Counties,'' and is commonly known as the Frontier Community Health
Integration Project (FCHIP) demonstration.
The authorizing statute states the eligibility criteria for
entities to be able to participate in the demonstration. An eligible
entity, as defined in section 123(d)(1)(B) of Public Law 110-275, as
amended, is an MRHFP grantee under section 1820(g) of the Act (that is,
a CAH); and is located in a State in which at least 65 percent of the
counties in the State are counties that have 6 or less residents per
square mile.
The authorizing statute stipulates several other requirements for
the demonstration. Section 123(d)(2)(B) of Public Law 110-275, as
amended, limits participation in the demonstration to eligible entities
in not more than 4 States. Section 123(f)(1) of Public Law 110-275
requires the demonstration project to be conducted for a 3-year period.
In addition, section 123(g)(1)(B) of Public Law 110-275 requires that
the demonstration be budget neutral. Specifically, this provision
states that, in conducting the demonstration project, the Secretary
shall ensure that the aggregate payments made by the Secretary do not
exceed the amount which the Secretary estimates would have been paid if
the demonstration project under the section were not implemented.
Furthermore, section 123(i) of Public Law 110-275 states that the
Secretary may waive such requirements of titles XVIII and XIX of the
Act as may be necessary and appropriate for the purpose of carrying out
the demonstration project, thus allowing the waiver of Medicare payment
rules encompassed in the demonstration.
In January 2014, CMS released a request for applications (RFA) for
the FCHIP demonstration. Using 2013 data from the U.S. Census Bureau,
CMS identified Alaska, Montana, Nevada, North Dakota, and Wyoming as
meeting the statutory eligibility requirement for participation in the
demonstration. The RFA solicited CAHs in these five States to
participate in the demonstration, stating that participation would be
limited to CAHs in four of the States. To apply, CAHs were required to
meet the eligibility requirements in the authorizing legislation, and,
in addition, to describe a proposal to enhance health-related services
that would complement those currently provided by the CAH and better
serve the community's needs. In addition, in the RFA, CMS interpreted
the eligible entity definition in the statute as meaning a CAH that
receives funding through the MHRFP. The RFA identified four
interventions, under which specific waivers of Medicare payment rules
would allow for enhanced payment for telehealth, skilled nursing
facility/nursing facility beds, ambulance services, and home health
services, respectively. These waivers were formulated with the goal of
increasing access to care with no net increase in costs.
Ten CAHs were selected for participation in the demonstration,
which started on August 1, 2016. These CAHs are located in Montana,
Nevada, and North Dakota, and they are participating in three of the
four interventions identified in the FY 2017 IPPS/LTCH PPS final rule
(81 FR 57064 through 57065), the FY 2018 IPPS/LTCH PPS final rule (82
FR 38294 through 38296), and the FY 2019 IPPS/LTCH PPS final rule (83
FR 41516 through 41517). Eight CAHs are participating in the telehealth
intervention, three CAHs are participating in the skilled nursing
facility/nursing facility bed intervention, and two CAHs are
participating in the ambulance services intervention. Each CAH is
allowed to participate in more than one of the interventions. None of
the selected CAHs are participants in the home health intervention,
which was the fourth intervention included in the RFA.
In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57064 through
57065), the FY 2018 IPPS/LTCH PPS final rule (82 FR 38294 through
38296), and the FY 2019 IPPS/LTCH PPS final rule (83 FR 41516 through
41517), we finalized a policy to address the budget neutrality
requirement for the demonstration. As explained in the FY 2019 IPPS/
LTCH PPS final rule, we based our selection of CAHs for participation
with the goal of maintaining the budget neutrality of the demonstration
on its own terms (that is, the demonstration will produce savings from
reduced transfers and admissions to other health care providers, thus
offsetting any increase in payments resulting from the demonstration).
However, because of the small size of this demonstration and
uncertainty associated with projected Medicare utilization and costs,
we adopted a contingency plan to ensure that the budget neutrality
requirement in section 123 of Public Law 110-275 is met. If analysis of
claims data for Medicare beneficiaries receiving services at each of
the participating CAHs, as well as from other data sources, including
cost reports for these CAHs, shows that increases in Medicare payments
under the demonstration during the 3-year period are not sufficiently
offset by reductions elsewhere, we will recoup the additional
expenditures attributable to the demonstration through a reduction in
payments to all CAHs nationwide. Because of the small scale of the
demonstration, we indicated that we did not believe it would be
feasible to implement budget neutrality by reducing payments to only
the participating CAHs. Therefore, in the event that this demonstration
is found to result in aggregate payments in excess of the amount that
would have been paid if this demonstration were not implemented, we
will comply with the budget neutrality requirement by reducing payments
to all CAHs, not just those participating in the demonstration. We
stated that we believe it is appropriate to make any payment reductions
across all CAHs because the FCHIP demonstration is specifically
designed to test innovations that affect delivery of services by the
CAH provider category. We explained our belief that the language of the
statutory budget neutrality requirement at section 123(g)(1)(B) of
Public Law 110-275 permits the agency to implement the budget
neutrality provision in this manner. The statutory language merely
refers to ensuring that aggregate payments made by the Secretary do not
exceed the amount which the Secretary estimates would have been paid if
the demonstration project was not implemented, and does not identify
the range across which aggregate payments must be held equal.
Based on actuarial analysis using cost report settlements for FYs
2013 and 2014, the demonstration is projected to satisfy the budget
neutrality requirement and likely yield a total net savings. As we
estimated for the FY 2019 IPPS/LTCH PPS final rule, for this FY 2020
IPPS/LTCH PPS proposed rule, we estimate that the total impact of the
payment recoupment will be no greater than 0.03 percent of CAHs' total
Medicare payments within one fiscal year (that is, Medicare Part A and
Part B). The final budget neutrality estimates for the FCHIP
demonstration will be based on the demonstration period, which is
August 1, 2016 through July 31, 2019.
The demonstration is projected to impact payments to participating
CAHs under both Medicare Part A and Part B. As stated in the FY 2019
IPPS/LTCH PPS final rule, in the event the demonstration is found not
to have been budget neutral, any excess costs will be recouped over a
period of 3 cost reporting years, beginning in CY 2020.
[[Page 19458]]
The 3-year period for recoupment will allow for a reasonable timeframe
for the payment reduction and to minimize any impact on CAHs'
operations. Based on the currently available data and because any
reduction to CAH payments in order to recoup excess costs under the
demonstration will not begin until CY 2020, this policy will likely
have no impact for any national payment system for FY 2020.
VII. Proposed Changes to the Long-Term Care Hospital Prospective
Payment System (LTCH PPS) for FY 2020
A. Background of the LTCH PPS
1. Legislative and Regulatory Authority
Section 123 of the Medicare, Medicaid, and SCHIP (State Children's
Health Insurance Program) Balanced Budget Refinement Act of 1999 (BBRA)
(Pub. L. 106-113), as amended by section 307(b) of the Medicare,
Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000
(BIPA) (Pub. L. 106-554), provides for payment for both the operating
and capital-related costs of hospital inpatient stays in long-term care
hospitals (LTCHs) under Medicare Part A based on prospectively set
rates. The Medicare prospective payment system (PPS) for LTCHs applies
to hospitals that are described in section 1886(d)(1)(B)(iv) of the
Act, effective for cost reporting periods beginning on or after October
1, 2002.
Section 1886(d)(1)(B)(iv)(I) of the Act originally defined an LTCH
as a hospital which has an average inpatient length of stay (as
determined by the Secretary) of greater than 25 days. Section
1886(d)(1)(B)(iv)(II) of the Act (``subclause II'' LTCHs) also provided
an alternative definition of LTCHs. However, section 15008 of the 21st
Century Cures Act (Pub. L. 114-255) amended section 1886 of the Act to
exclude former ``subclause II'' LTCHs from being paid under the LTCH
PPS and created a new category of IPPS-excluded hospitals, which we
refer to as ``extended neoplastic disease care hospitals''), to be paid
as hospitals that were formally classified as ``subclause (II)'' LTCHs
(82 FR 38298).
Section 123 of the BBRA requires the PPS for LTCHs to be a ``per
discharge'' system with a diagnosis-related group (DRG) based patient
classification system that reflects the differences in patient
resources and costs in LTCHs.
Section 307(b)(1) of the BIPA, among other things, mandates that
the Secretary shall examine, and may provide for, adjustments to
payments under the LTCH PPS, including adjustments to DRG weights, area
wage adjustments, geographic reclassification, outliers, updates, and a
disproportionate share adjustment.
In the August 30, 2002 Federal Register, we issued a final rule
that implemented the LTCH PPS authorized under the BBRA and BIPA (67 FR
55954). For the initial implementation of the LTCH PPS (FYs 2003
through FY 2007), the system used information from LTCH patient records
to classify patients into distinct long-term care diagnosis-related
groups (LTC-DRGs) based on clinical characteristics and expected
resource needs. Beginning in FY 2008, we adopted the Medicare severity
long-term care diagnosis-related groups (MS-LTC-DRGs) as the patient
classification system used under the LTCH PPS. Payments are calculated
for each MS-LTC-DRG and provisions are made for appropriate payment
adjustments. Payment rates under the LTCH PPS are updated annually and
published in the Federal Register.
The LTCH PPS replaced the reasonable cost-based payment system
under the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA)
(Pub. L. 97-248) for payments for inpatient services provided by an
LTCH with a cost reporting period beginning on or after October 1,
2002. (The regulations implementing the TEFRA reasonable cost-based
payment provisions are located at 42 CFR part 413.) With the
implementation of the PPS for acute care hospitals authorized by the
Social Security Amendments of 1983 (Pub. L. 98-21), which added section
1886(d) to the Act, certain hospitals, including LTCHs, were excluded
from the PPS for acute care hospitals and were paid their reasonable
costs for inpatient services subject to a per discharge limitation or
target amount under the TEFRA system. For each cost reporting period, a
hospital-specific ceiling on payments was determined by multiplying the
hospital's updated target amount by the number of total current year
Medicare discharges. (Generally, in this section of the preamble of
this proposed rule, when we refer to discharges, we describe Medicare
discharges.) The August 30, 2002 final rule further details the payment
policy under the TEFRA system (67 FR 55954).
In the August 30, 2002 final rule, we provided for a 5-year
transition period from payments under the TEFRA system to payments
under the LTCH PPS. During this 5-year transition period, an LTCH's
total payment under the PPS was based on an increasing percentage of
the Federal rate with a corresponding decrease in the percentage of the
LTCH PPS payment that is based on reasonable cost concepts, unless an
LTCH made a one-time election to be paid based on 100 percent of the
Federal rate. Beginning with LTCHs' cost reporting periods beginning on
or after October 1, 2006, total LTCH PPS payments are based on 100
percent of the Federal rate.
In addition, in the August 30, 2002 final rule, we presented an in-
depth discussion of the LTCH PPS, including the patient classification
system, relative weights, payment rates, additional payments, and the
budget neutrality requirements mandated by section 123 of the BBRA. The
same final rule that established regulations for the LTCH PPS under 42
CFR part 412, subpart O, also contained LTCH provisions related to
covered inpatient services, limitation on charges to beneficiaries,
medical review requirements, furnishing of inpatient hospital services
directly or under arrangement, and reporting and recordkeeping
requirements. We refer readers to the August 30, 2002 final rule for a
comprehensive discussion of the research and data that supported the
establishment of the LTCH PPS (67 FR 55954).
In the FY 2016 IPPS/LTCH PPS final rule (80 FR 49601 through
49623), we implemented the provisions of the Pathway for Sustainable
Growth Rate (SGR) Reform Act of 2013 (Pub. L. 113-67), which mandated
the application of the ``site neutral'' payment rate under the LTCH PPS
for discharges that do not meet the statutory criteria for exclusion
beginning in FY 2016. For cost reporting periods beginning on or after
October 1, 2015, discharges that do not meet certain statutory criteria
for exclusion are paid based on the site neutral payment rate.
Discharges that do meet the statutory criteria continue to receive
payment based on the LTCH PPS standard Federal payment rate. For more
information on the statutory requirements of the Pathway for SGR Reform
Act of 2013, we refer readers to the FY 2016 IPPS/LTCH PPS final rule
(80 FR 49601 through 49623) and the FY 2017 IPPS/LTCH PPS final rule
(81 FR 57068 through 57075).
In the FY 2018 IPPS/LTCH PPS final rule, we implemented several
provisions of the 21st Century Cures Act (``the Cures Act'') (Pub. L.
114-255) that affected the LTCH PPS. For more information on these
provisions, we refer readers to 82 FR 38299.
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41529), we made
conforming changes to our regulations to implement the provisions of
section 51005 of the Bipartisan Budget Act of
[[Page 19459]]
2018, Public Law 115-123, which extends the transitional blended
payment rate for site neutral payment rate cases for an additional 2
years. We refer readers to section VII.C. of the preamble of the FY
2019 IPPS/LTCH PPS final rule for a discussion of our final policy. In
addition, in the FY 2019 IPPS/LTCH PPS final rule, we removed the 25-
percent threshold policy under 42 CFR 412.538.
In this FY 2020 IPPS/LTCH PPS proposed rule, we are proposing
revisions to our regulations to implement the provisions of the Pathway
for SGR Reform Act of 2013 (Pub. L. 113-67) that relate to the payment
adjustment for discharges from LTCHs that do not maintain the requisite
discharge payment percentage and the process by which such LTCHs may
have the payment adjustment discontinued.
2. Criteria for Classification as an LTCH
a. Classification as an LTCH
Under the regulations at Sec. 412.23(e)(1), to qualify to be paid
under the LTCH PPS, a hospital must have a provider agreement with
Medicare. Furthermore, Sec. 412.23(e)(2)(i), which implements section
1886(d)(1)(B)(iv) of the Act, requires that a hospital have an average
Medicare inpatient length of stay of greater than 25 days to be paid
under the LTCH PPS. In accordance with section 1206(a)(3) of the
Pathway for SGR Reform Act of 2013 (Pub. L. 113-67), as amended by
section 15007 of Public Law 114-255, we amended our regulations to
specify that Medicare Advantage plans' and site neutral payment rate
discharges are excluded from the calculation of the average length of
stay for all LTCHs, for discharges occurring in cost reporting period
beginning on or after October 1, 2015.
b. Hospitals Excluded From the LTCH PPS
The following hospitals are paid under special payment provisions,
as described in Sec. 412.22(c) and, therefore, are not subject to the
LTCH PPS rules:
Veterans Administration hospitals.
Hospitals that are reimbursed under State cost control
systems approved under 42 CFR part 403.
Hospitals that are reimbursed in accordance with
demonstration projects authorized under section 402(a) of the Social
Security Amendments of 1967 (Pub. L. 90-248) (42 U.S.C. 1395b-1),
section 222(a) of the Social Security Amendments of 1972 (Pub. L. 92-
603) (42 U.S.C. 1395b-1 (note)) (Statewide all-payer systems, subject
to the rate-of-increase test at section 1814(b) of the Act), or section
3201 of the Patient Protection and Affordable Care Act (Pub. L. 111-148
(42 U.S.C. 1315a).
Nonparticipating hospitals furnishing emergency services
to Medicare beneficiaries.
3. Limitation on Charges to Beneficiaries
In the August 30, 2002 final rule, we presented an in-depth
discussion of beneficiary liability under the LTCH PPS (67 FR 55974
through 55975). This discussion was further clarified in the RY 2005
LTCH PPS final rule (69 FR 25676). In keeping with those discussions,
if the Medicare payment to the LTCH is the full LTC-DRG payment amount,
consistent with other established hospital prospective payment systems,
Sec. 412.507 currently provides that an LTCH may not bill a Medicare
beneficiary for more than the deductible and coinsurance amounts as
specified under Sec. Sec. 409.82, 409.83, and 409.87, and for items
and services specified under Sec. 489.30(a). However, under the LTCH
PPS, Medicare will only pay for services furnished during the days for
which the beneficiary has coverage until the short-stay outlier (SSO)
threshold is exceeded. If the Medicare payment was for a SSO case (in
accordance with Sec. 412.529), and that payment was less than the full
LTC-DRG payment amount because the beneficiary had insufficient
coverage as a result of the remaining Medicare days, the LTCH also is
currently permitted to charge the beneficiary for services delivered on
those uncovered days (in accordance with Sec. 412.507). In the FY 2016
IPPS/LTCH PPS final rule (80 FR 49623), we amended our regulations to
expressly limit the charges that may be imposed upon beneficiaries
whose LTCHs' discharges are paid at the site neutral payment rate under
the LTCH PPS. In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57102), we
amended the regulations under Sec. 412.507 to clarify our existing
policy that blended payments made to an LTCH during its transitional
period (that is, an LTCH's payment for discharges occurring in cost
reporting periods beginning in FY 2016 or FY 2017) are considered to be
site neutral payment rate payments.
B. Proposed Medicare Severity Long-Term Care Diagnosis-Related Group
(MS-LTC-DRG) Classifications and Relative Weights for FY 2020
1. Background
Section 123 of the BBRA required that the Secretary implement a PPS
for LTCHs to replace the cost-based payment system under TEFRA. Section
307(b)(1) of the BIPA modified the requirements of section 123 of the
BBRA by requiring that the Secretary examine the feasibility and the
impact of basing payment under the LTCH PPS on the use of existing (or
refined) hospital DRGs that have been modified to account for different
resource use of LTCH patients.
When the LTCH PPS was implemented for cost reporting periods
beginning on or after October 1, 2002, we adopted the same DRG patient
classification system utilized at that time under the IPPS. As a
component of the LTCH PPS, we refer to this patient classification
system as the ``long-term care diagnosis-related groups (LTC-DRGs).''
Although the patient classification system used under both the LTCH PPS
and the IPPS are the same, the relative weights are different. The
established relative weight methodology and data used under the LTCH
PPS result in relative weights under the LTCH PPS that reflect the
differences in patient resource use of LTCH patients, consistent with
section 123(a)(1) of the BBRA (Pub. L. 106-113).
As part of our efforts to better recognize severity of illness
among patients, in the FY 2008 IPPS final rule with comment period (72
FR 47130), the MS-DRGs and the Medicare severity long-term care
diagnosis-related groups (MS-LTC-DRGs) were adopted under the IPPS and
the LTCH PPS, respectively, effective beginning October 1, 2007 (FY
2008). For a full description of the development, implementation, and
rationale for the use of the MS-DRGs and MS-LTC-DRGs, we refer readers
to the FY 2008 IPPS final rule with comment period (72 FR 47141 through
47175 and 47277 through 47299). (We note that, in that same final rule,
we revised the regulations at Sec. 412.503 to specify that for LTCH
discharges occurring on or after October 1, 2007, when applying the
provisions of 42 CFR part 412, subpart O applicable to LTCHs for policy
descriptions and payment calculations, all references to LTC-DRGs would
be considered a reference to MS-LTC-DRGs. For the remainder of this
section, we present the discussion in terms of the current MS-LTC-DRG
patient classification system unless specifically referring to the
previous LTC-DRG patient classification system that was in effect
before October 1, 2007.)
The MS-DRGs adopted in FY 2008 represent an increase in the number
of DRGs by 207 (that is, from 538 to 745) (72 FR 47171). The MS-DRG
classifications are updated annually. There are currently 761 MS-DRG
[[Page 19460]]
groupings. For FY 2020, there would be 761 MS-DRG groupings based on
the proposed changes, as discussed in section II.F. of the preamble of
this FY 2020 IPPS/LTCH PPS proposed rule. Consistent with section 123
of the BBRA, as amended by section 307(b)(1) of the BIPA, and Sec.
412.515 of the regulations, we use information derived from LTCH PPS
patient records to classify LTCH discharges into distinct MS-LTC-DRGs
based on clinical characteristics and estimated resource needs. We then
assign an appropriate weight to the MS-LTC-DRGs to account for the
difference in resource use by patients exhibiting the case complexity
and multiple medical problems characteristic of LTCHs.
In this section of the proposed rule, we provide a general summary
of our existing methodology for determining the proposed FY 2020 MS-
LTC-DRG relative weights under the LTCH PPS.
In this FY 2020 IPPS/LTCH PPS proposed rule, in general, for FY
2020, we are proposing to continue to use our existing methodology to
determine the proposed MS-LTC-DRG relative weights (as discussed in
greater detail in section VII.B.3. of the preamble of this proposed
rule). As we established when we implemented the dual rate LTCH PPS
payment structure codified under Sec. 412.522, which began in FY 2016,
we are proposing that the annual recalibration of the MS-LTC-DRG
relative weights are determined: (1) Using only data from available
LTCH PPS claims that would have qualified for payment under the new
LTCH PPS standard Federal payment rate if that rate had been in effect
at the time of discharge when claims data from time periods before the
dual rate LTCH PPS payment structure applies are used to calculate the
relative weights; and (2) using only data from available LTCH PPS
claims that qualify for payment under the new LTCH PPS standard Federal
payment rate when claims data from time periods after the dual rate
LTCH PPS payment structure applies are used to calculate the relative
weights (80 FR 49624). That is, under our current methodology, our MS-
LTC-DRG relative weight calculations do not use data from cases paid at
the site neutral payment rate under Sec. 412.522(c)(1) or data from
cases that would have been paid at the site neutral payment rate if the
dual rate LTCH PPS payment structure had been in effect at the time of
that discharge. For the remainder of this discussion, we use the phrase
``applicable LTCH cases'' or ``applicable LTCH data'' when referring to
the resulting claims data set used to calculate the relative weights
(as described later in greater detail in section VII.B.3.c. of the
preamble of this proposed rule). In addition, in this FY 2020 IPPS/LTCH
PPS proposed rule, for FY 2020, we are proposing to continue to exclude
the data from all-inclusive rate providers and LTCHs paid in accordance
with demonstration projects, as well as any Medicare Advantage claims
from the MS-LTC-DRG relative weight calculations for the reasons
discussed in section VII.B.3.c. of the preamble of this proposed rule.
Furthermore, for FY 2020, in using data from applicable LTCH cases
to establish MS-LTC-DRG relative weights, we are proposing to continue
to establish low-volume MS-LTC-DRGs (that is, MS-LTC-DRGs with less
than 25 cases) using our quintile methodology in determining the MS-
LTC-DRG relative weights because LTCHs do not typically treat the full
range of diagnoses as do acute care hospitals. Therefore, for purposes
of determining the relative weights for the large number of low-volume
MS-LTC-DRGs, we grouped all of the low-volume MS-LTC-DRGs into five
quintiles based on average charges per discharge. Then, under our
existing methodology, we account for adjustments made to LTCH PPS
standard Federal payments for short-stay outlier (SSO) cases (that is,
cases where the covered length of stay at the LTCH is less than or
equal to five-sixths of the geometric average length of stay for the
MS-LTC-DRG), and we make adjustments to account for nonmonotonically
increasing weights, when necessary. The methodology is premised on more
severe cases under the MS-LTC-DRG system requiring greater expenditure
of medical care resources and higher average charges such that, in the
severity levels within a base MS-LTC-DRG, the relative weights should
increase monotonically with severity from the lowest to highest
severity level. (We discuss each of these components of our MS-LTC-DRG
relative weight methodology in greater detail in section VII.B.3.g. of
the preamble of this proposed rule.)
2. Patient Classifications Into MS-LTC-DRGs
a. Background
The MS-DRGs (used under the IPPS) and the MS-LTC-DRGs (used under
the LTCH PPS) are based on the CMS DRG structure. As noted previously
in this section, we refer to the DRGs under the LTCH PPS as MS-LTC-DRGs
although they are structurally identical to the MS-DRGs used under the
IPPS.
The MS-DRGs are organized into 25 major diagnostic categories
(MDCs), most of which are based on a particular organ system of the
body; the remainder involve multiple organ systems (such as MDC 22,
Burns). Within most MDCs, cases are then divided into surgical DRGs and
medical DRGs. Surgical DRGs are assigned based on a surgical hierarchy
that orders operating room (O.R.) procedures or groups of O.R.
procedures by resource intensity. The GROUPER software program does not
recognize all ICD-10-PCS procedure codes as procedures affecting DRG
assignment. That is, procedures that are not surgical (for example,
EKGs), or minor surgical procedures (for example, a biopsy of skin and
subcutaneous tissue (procedure code 0JBH3ZX)) do not affect the MS-LTC-
DRG assignment based on their presence on the claim.
Generally, under the LTCH PPS, a Medicare payment is made at a
predetermined specific rate for each discharge that varies based on the
MS-LTC-DRG to which a beneficiary's discharge is assigned. Cases are
classified into MS-LTC-DRGs for payment based on the following six data
elements:
Principal diagnosis;
Additional or secondary diagnoses;
Surgical procedures;
Age;
Sex; and
Discharge status of the patient.
Currently, for claims submitted using version ASC X12 5010 format,
up to 25 diagnosis codes and 25 procedure codes are considered for an
MS-DRG assignment. This includes one principal diagnosis and up to 24
secondary diagnoses for severity of illness determinations. (For
additional information on the processing of up to 25 diagnosis codes
and 25 procedure codes on hospital inpatient claims, we refer readers
to section II.G.11.c. of the preamble of the FY 2011 IPPS/LTCH PPS
final rule (75 FR 50127).)
Under the HIPAA transactions and code sets regulations at 45 CFR
parts 160 and 162, covered entities must comply with the adopted
transaction standards and operating rules specified in Subparts I
through S of Part 162. Among other requirements, on or after January 1,
2012, covered entities were required to use the ASC X12 Standards for
Electronic Data Interchange Technical Report Type 3--Health Care Claim:
Institutional (837), May 2006, ASC X12N/005010X223, and Type 1 Errata
to Health Care Claim: Institutional (837) ASC X12 Standards for
Electronic Data Interchange Technical Report Type 3, October 2007, ASC
X12N/005010X233A1 for the health care claims or equivalent
[[Page 19461]]
encounter information transaction (45 CFR 162.1102(c)).
HIPAA requires covered entities to use the applicable medical data
code set requirements when conducting HIPAA transactions (45 CFR
162.1000). Currently, upon the discharge of the patient, the LTCH must
assign appropriate diagnosis and procedure codes from the most current
version of the International Classification of Diseases, 10th Revision,
Clinical Modification (ICD-10-CM) for diagnosis coding and the
International Classification of Diseases, 10th Revision, Procedure
Coding System (ICD-10-PCS) for inpatient hospital procedure coding,
both of which were required to be implemented October 1, 2015 (45 CFR
162.1002(c)(2) and (3)). For additional information on the
implementation of the ICD-10 coding system, we refer readers to section
II.F.1. of the FY 2017 IPPS/LTCH PPS final rule (81 FR 56787 through
56790) and section II.F.1. of the preamble of this final rule.
Additional coding instructions and examples are published in the AHA's
Coding Clinic for ICD-10-CM/PCS.
To create the MS-DRGs (and by extension, the MS-LTC-DRGs), base
DRGs were subdivided according to the presence of specific secondary
diagnoses designated as complications or comorbidities (CCs) into one,
two, or three levels of severity, depending on the impact of the CCs on
resources used for those cases. Specifically, there are sets of MS-DRGs
that are split into 2 or 3 subgroups based on the presence or absence
of a CC or a major complication or comorbidity (MCC). We refer readers
to section II.D. of the FY 2008 IPPS final rule with comment period for
a detailed discussion about the creation of MS-DRGs based on severity
of illness levels (72 FR 47141 through 47175).
MACs enter the clinical and demographic information submitted by
LTCHs into their claims processing systems and subject this information
to a series of automated screening processes called the Medicare Code
Editor (MCE). These screens are designed to identify cases that require
further review before assignment into a MS-LTC-DRG can be made. During
this process, certain cases are selected for further explanation (74 FR
43949).
After screening through the MCE, each claim is classified into the
appropriate MS-LTC-DRG by the Medicare LTCH GROUPER software on the
basis of diagnosis and procedure codes and other demographic
information (age, sex, and discharge status). The GROUPER software used
under the LTCH PPS is the same GROUPER software program used under the
IPPS. Following the MS-LTC-DRG assignment, the MAC determines the
prospective payment amount by using the Medicare PRICER program, which
accounts for hospital-specific adjustments. Under the LTCH PPS, we
provide an opportunity for LTCHs to review the MS-LTC-DRG assignments
made by the MAC and to submit additional information within a specified
timeframe as provided in Sec. 412.513(c).
The GROUPER software is used both to classify past cases to measure
relative hospital resource consumption to establish the MS-LTC-DRG
relative weights and to classify current cases for purposes of
determining payment. The records for all Medicare hospital inpatient
discharges are maintained in the MedPAR file. The data in this file are
used to evaluate possible MS-DRG and MS-LTC-DRG classification changes
and to recalibrate the MS-DRG and MS-LTC-DRG relative weights during
our annual update under both the IPPS (Sec. 412.60(e)) and the LTCH
PPS (Sec. 412.517), respectively.
b. Proposed Changes to the MS-LTC-DRGs for FY 2020
As specified by our regulations at Sec. 412.517(a), which require
that the MS-LTC-DRG classifications and relative weights be updated
annually, and consistent with our historical practice of using the same
patient classification system under the LTCH PPS as is used under the
IPPS, in this FY 2020 IPPS/LTCH PPS proposed rule, we are proposing to
update the MS-LTC-DRG classifications effective October 1, 2019,
through September 30, 2020 (FY 2020), consistent with the proposed
changes to specific MS-DRG classifications presented in section II.F.
of the preamble of this proposed rule. Accordingly, the proposed MS-
LTC-DRGs for FY 2020 presented in this proposed rule are the same as
the proposed MS-DRGs that are being used under the IPPS for FY 2020. In
addition, because the MS-LTC-DRGs for FY 2020 are the same as the
proposed MS-DRGs for FY 2020, the other proposed changes that affect
MS-DRG (and by extension MS-LTC-DRG) assignments under proposed GROUPER
Version 37 as discussed in section II.F. of the preamble of this
proposed rule, including the proposed changes to the MCE software and
the ICD-10-CM/PCS coding system, also would be applicable under the
LTCH PPS for FY 2020.
3. Development of the Proposed FY 2020 MS-LTC-DRG Relative Weights
a. General Overview of the Development of the MS-LTC-DRG Relative
Weights
One of the primary goals for the implementation of the LTCH PPS is
to pay each LTCH an appropriate amount for the efficient delivery of
medical care to Medicare patients. The system must be able to account
adequately for each LTCH's case-mix in order to ensure both fair
distribution of Medicare payments and access to adequate care for those
Medicare patients whose care is more costly (67 FR 55984). To
accomplish these goals, we have annually adjusted the LTCH PPS standard
Federal prospective payment rate by the applicable relative weight in
determining payment to LTCHs for each case. In order to make these
annual adjustments under the dual rate LTCH PPS payment structure,
beginning with FY 2016, we recalibrate the MS-LTC-DRG relative
weighting factors annually using data from applicable LTCH cases (80 FR
49614 through 49617). Under this policy, the resulting MS-LTC-DRG
relative weights would continue to be used to adjust the LTCH PPS
standard Federal payment rate when calculating the payment for LTCH PPS
standard Federal payment rate cases.
The established methodology to develop the MS-LTC-DRG relative
weights is generally consistent with the methodology established when
the LTCH PPS was implemented in the August 30, 2002 LTCH PPS final rule
(67 FR 55989 through 55991). However, there have been some
modifications of our historical procedures for assigning relative
weights in cases of zero volume and/or nonmonotonicity resulting from
the adoption of the MS-LTC-DRGs, along with the change made in
conjunction with the implementation of the dual rate LTCH PPS payment
structure beginning in FY 2016 to use LTCH claims data from only LTCH
PPS standard Federal payment rate cases (or LTCH PPS cases that would
have qualified for payment under the LTCH PPS standard Federal payment
rate if the dual rate LTCH PPS payment structure had been in effect at
the time of the discharge). (For details on the modifications to our
historical procedures for assigning relative weights in cases of zero
volume and/or nonmonotonicity, we refer readers to the FY 2008 IPPS
final rule with comment period (72 FR 47289 through 47295) and the FY
2009 IPPS final rule (73 FR 48542 through 48550).) For details on the
change in our historical methodology to use LTCH claims data only from
LTCH PPS standard Federal
[[Page 19462]]
payment rate cases (or cases that would have qualified for such payment
had the LTCH PPS dual payment rate structure been in effect at the
time) to determine the MS-LTC-DRG relative weights, we refer readers to
the FY 2016 IPPS/LTCH PPS final rule (80 FR 49614 through 49617). Under
the LTCH PPS, relative weights for each MS-LTC-DRG are a primary
element used to account for the variations in cost per discharge and
resource utilization among the payment groups (Sec. 412.515). To
ensure that Medicare patients classified to each MS-LTC-DRG have access
to an appropriate level of services and to encourage efficiency, we
calculate a relative weight for each MS-LTC-DRG that represents the
resources needed by an average inpatient LTCH case in that MS-LTC-DRG.
For example, cases in an MS-LTC-DRG with a relative weight of 2 would,
on average, cost twice as much to treat as cases in an MS-LTC-DRG with
a relative weight of 1.
b. Development of the Proposed MS-LTC-DRG Relative Weights for FY 2020
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41521 through
41529), we presented our policies for the development of the MS-LTC-DRG
relative weights for FY 2019.
In this FY 2020 IPPS/LTCH PPS proposed rule, we are proposing to
continue to use our current methodology to determine the proposed MS-
LTC-DRG relative weights for FY 2020, including the continued
application of established policies related to: The hospital-specific
relative value methodology, the treatment of severity levels in the
proposed MS-LTC-DRGs, proposed low-volume and no-volume MS-LTC-DRGs,
proposed adjustments for nonmonotonicity, the steps for calculating the
proposed MS-LTC-DRG relative weights with a proposed budget neutrality
factor, and only using data from applicable LTCH cases (which includes
our policy of only using cases that would meet the criteria for
exclusion from the site neutral payment rate (or, for discharges
occurring prior to the implementation of the dual rate LTCH PPS payment
structure, would have met the criteria for exclusion had those criteria
been in effect at the time of the discharge)).
In this section, we present our proposed application of our
existing methodology for determining the proposed MS-LTC-DRG relative
weights for FY 2020, and we discuss the effects of our proposals
concerning the data used to determine the proposed FY 2020 MS-LTC-DRG
relative weights on the various components of our existing methodology
in the discussion that follows.
As discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41522),
we now generally provide the low-volume quintiles and no-volume
crosswalk data previously published in Tables 13A and 13B for each
annual proposed and final rule as one of our supplemental IPPS/LTCH PPS
related data files that are made available for public use via the
internet on the CMS website for the respective rule and fiscal year
(that is, FY 2019 and subsequent fiscal years) at: http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html to streamline the information made
available to the public that is used in the annual development of IPPS
Table 11 and to make it easier for the public to navigate and find the
relevant data and information used for the development of proposed and
final payment rates or factors for the applicable payment year while
continuing to furnish the same information the tables provided in
previous fiscal years. We refer readers to the CMS website for the low-
volume quintiles and no-volume crosswalk data previously furnished via
Tables 13A and 13B.
c. Data
For this FY 2020 IPPS/LTCH PPS proposed rule, consistent with our
proposals regarding the calculation of the proposed MS-LTC-DRG relative
weights for FY 2020, we obtained total charges from FY 2018 Medicare
LTCH claims data from the December 2018 update of the FY 2018 MedPAR
file, which are the best available data at this time, and we are
proposing to use Version 37 of the GROUPER to classify LTCH cases.
Consistent with our historical practice, we are proposing that if more
recent data become available, we would use those data and the finalized
Version 37 of the GROUPER in establishing the FY 2020 MS-LTC-DRG
relative weights in the final rule. To calculate the proposed FY 2020
MS-LTC-DRG relative weights under the dual rate LTCH PPS payment
structure, we are proposing to continue to use applicable LTCH data,
which includes our policy of only using cases that meet the criteria
for exclusion from the site neutral payment rate (or would have met the
criteria had they been in effect at the time of the discharge) (80 FR
49624). Specifically, we began by first evaluating the LTCH claims data
in the December 2018 update of the FY 2018 MedPAR file to determine
which LTCH cases would meet the criteria for exclusion from the site
neutral payment rate under Sec. 412.522(b) had the dual rate LTCH PPS
payment structure applied to those cases at the time of discharge. We
identified the FY 2018 LTCH cases that were not assigned to MS-LTC-DRGs
876, 880, 881, 882, 883, 884, 885, 886, 887, 894, 895, 896, 897, 945
and 946, which identify LTCH cases that do not have a principal
diagnosis relating to a psychiatric diagnosis or to rehabilitation; and
that either--
The admission to the LTCH was ``immediately preceded'' by
discharge from a subsection (d) hospital and the immediately preceding
stay in that subsection (d) hospital included at least 3 days in an
ICU, as we define under the ICU criterion; or
The admission to the LTCH was ``immediately preceded'' by
discharge from a subsection (d) hospital and the claim for the LTCH
discharge includes the applicable procedure code that indicates at
least 96 hours of ventilator services were provided during the LTCH
stay, as we define under the ventilator criterion. Claims data from the
FY 2017 MedPAR file that reported ICD-10-PCS procedure code 5A1955Z
were used to identify cases involving at least 96 hours of ventilator
services in accordance with the ventilator criterion. We note that, for
purposes of developing the proposed FY 2020 MS-LTC-DRG relative weights
using our current methodology, we are not making any proposals for
exceptions regarding the identification of cases that would have been
excluded from the site neutral payment rate under the statutory
provisions that provided for temporary exception from the site neutral
payment rate under the LTCH PPS for certain severe wound care
discharges from certain LTCHs or for certain spinal cord specialty
hospitals provided by sections 15009 and 15010 of Public Law 114-255,
respectively, had our implementation of that law and the dual rate LTCH
PPS payment structure been in effect at the time of the discharge. At
this time, it is uncertain how many LTCHs and how many cases in the
claims data we are using for this proposed rule meet the criteria to be
excluded from the site neutral payment rate under those exceptions (or
would have met the criteria for exclusion had the dual rate LTCH PPS
payment structure been in effect at the time of the discharge).
Therefore, for the remainder of this section, when we refer to LTCH
claims only from cases that meet the criteria for exclusion from the
site neutral payment rate (or would have met the criteria had the
applicable statutes been in effect at the time of the discharge), such
data do not include any discharges that would have been paid
[[Page 19463]]
based on the LTCH PPS standard Federal payment rate under the
provisions of sections 15009 and 15010 of Public Law 114-255, had the
exception been in effect at the time of the discharge.
Furthermore, consistent with our historical methodology, we are
excluding any claims in the resulting data set that were submitted by
LTCHs that were all-inclusive rate providers and LTCHs that are paid in
accordance with demonstration projects authorized under section 402(a)
of Public Law 90-248 or section 222(a) of Public Law 92-603. In
addition, consistent with our historical practice and our policies, we
are excluding any Medicare Advantage (Part C) claims in the resulting
data. Such claims were identified based on the presence of a GHO Paid
indicator value of ``1'' in the MedPAR files. The claims that remained
after these three trims (that is, the applicable LTCH data) were then
used to calculate the proposed MS-LTC-DRG relative weights for FY 2020.
In summary, in general, we identified the claims data used in the
development of the proposed FY 2020 MS-LTC-DRG relative weights in this
proposed rule, as we are proposing, by trimming claims data that were
paid the site neutral payment rate (or would have been paid the site
neutral payment rate had the dual payment rate structure been in
effect, except for discharges which would have been excluded from the
site neutral payment under the temporary exception for certain severe
wound care discharges from certain LTCHs and under the temporary
exception for certain spinal cord specialty hospitals), as well as the
claims data of 8 all-inclusive rate providers reported in the December
2018 update of the FY 2018 MedPAR file and any Medicare Advantage
claims data. (We note that, there were no data from any LTCHs that are
paid in accordance with a demonstration project reported in the
December 2018 update of the FY 2018 MedPAR file. However, had there
been we would trim the claims data from those LTCHs as well, in
accordance with our established policy.) We are proposing to use the
remaining data (that is, the applicable LTCH data) to calculate the
proposed relative weights for FY 2020.
d. Hospital-Specific Relative Value (HSRV) Methodology
By nature, LTCHs often specialize in certain areas, such as
ventilator-dependent patients. Some case types (MS-LTC-DRGs) may be
treated, to a large extent, in hospitals that have, from a perspective
of charges, relatively high (or low) charges. This nonrandom
distribution of cases with relatively high (or low) charges in specific
MS-LTC-DRGs has the potential to inappropriately distort the measure of
average charges. To account for the fact that cases may not be randomly
distributed across LTCHs, consistent with the methodology we have used
since the implementation of the LTCH PPS, in this FY 2020 IPPS/LTCH PPS
proposed rule, we are proposing to continue to use a hospital-specific
relative value (HSRV) methodology to calculate the proposed MS-LTC-DRG
relative weights for FY 2020. We believe that this method removes this
hospital-specific source of bias in measuring LTCH average charges (67
FR 55985). Specifically, under this methodology, we are proposing to
reduce the impact of the variation in charges across providers on any
particular MS-LTC-DRG relative weight by converting each LTCH's charge
for an applicable LTCH case to a relative value based on that LTCH's
average charge for such cases.
Under the HSRV methodology, we standardize charges for each LTCH by
converting its charges for each applicable LTCH case to hospital-
specific relative charge values and then adjusting those values for the
LTCH's case-mix. The adjustment for case-mix is needed to rescale the
hospital-specific relative charge values (which, by definition, average
1.0 for each LTCH). The average relative weight for an LTCH is its
case-mix; therefore, it is reasonable to scale each LTCH's average
relative charge value by its case-mix. In this way, each LTCH's
relative charge value is adjusted by its case-mix to an average that
reflects the complexity of the applicable LTCH cases it treats relative
to the complexity of the applicable LTCH cases treated by all other
LTCHs (the average LTCH PPS case-mix of all applicable LTCH cases
across all LTCHs).
In accordance with our established methodology, for FY 2020, we are
proposing to continue to standardize charges for each applicable LTCH
case by first dividing the adjusted charge for the case (adjusted for
SSOs under Sec. 412.529 as described in section VII.B.3.g. (Step 3) of
the preamble of this proposed rule) by the average adjusted charge for
all applicable LTCH cases at the LTCH in which the case was treated.
SSO cases are cases with a length of stay that is less than or equal to
five-sixths the average length of stay of the MS-LTC-DRG (Sec. 412.529
and Sec. 412.503). The average adjusted charge reflects the average
intensity of the health care services delivered by a particular LTCH
and the average cost level of that LTCH. The resulting ratio is
multiplied by that LTCH's case-mix index to determine the standardized
charge for the case.
Multiplying the resulting ratio by the LTCH's case-mix index
accounts for the fact that the same relative charges are given greater
weight at an LTCH with higher average costs than they would at an LTCH
with low average costs, which is needed to adjust each LTCH's relative
charge value to reflect its case-mix relative to the average case-mix
for all LTCHs. By standardizing charges in this manner, we count
charges for a Medicare patient at an LTCH with high average charges as
less resource intensive than they would be at an LTCH with low average
charges. For example, a $10,000 charge for a case at an LTCH with an
average adjusted charge of $17,500 reflects a higher level of relative
resource use than a $10,000 charge for a case at an LTCH with the same
case-mix, but an average adjusted charge of $35,000. We believe that
the adjusted charge of an individual case more accurately reflects
actual resource use for an individual LTCH because the variation in
charges due to systematic differences in the markup of charges among
LTCHs is taken into account.
e. Treatment of Severity Levels in Developing the Proposed MS-LTC-DRG
Relative Weights
For purposes of determining the MS-LTC-DRG relative weights, under
our historical methodology, there are three different categories of MS-
DRGs based on volume of cases within specific MS-LTC-DRGs: (1) MS-LTC-
DRGs with at least 25 applicable LTCH cases in the data used to
calculate the relative weight, which are each assigned a unique
relative weight; (2) low-volume MS-LTC-DRGs (that is, MS-LTC-DRGs that
contain between 1 and 24 applicable LTCH cases that are grouped into
quintiles (as described later in this section of the proposed rule) and
assigned the relative weight of the quintile); and (3) no-volume MS-
LTC-DRGs that are cross-walked to other MS-LTC-DRGs based on the
clinical similarities and assigned the relative weight of the cross-
walked MS-LTC-DRG (as described in greater detail below). For FY 2020,
we are proposing to continue to use applicable LTCH cases to establish
the same volume-based categories to calculate the proposed FY 2020 MS-
LTC-DRG relative weights.
In determining the proposed FY 2020 MS-LTC-DRG relative weights,
when necessary, as is our longstanding practice, we are proposing to
make adjustments to account for nonmonotonicity, as discussed in
[[Page 19464]]
greater detail later in Step 6 of section VII.B.3.g. of the preamble of
this proposed rule. We refer readers to the discussion in the FY 2010
IPPS/RY 2010 LTCH PPS final rule for our rationale for including an
adjustment for nonmonotonicity (74 FR 43953 through 43954).
f. Proposed Low-Volume MS-LTC-DRGs
In order to account for proposed MS-LTC-DRGs with low-volume (that
is, with fewer than 25 applicable LTCH cases), consistent with our
existing methodology, we are proposing to continue to employ the
quintile methodology for proposed low-volume MS-LTC-DRGs, such that we
group the proposed ``low-volume MS-LTC-DRGs'' (that is, proposed MS-
LTC-DRGs that contain between 1 and 24 applicable LTCH cases into one
of five categories (quintiles) based on average charges (67 FR 55984
through 55995; 72 FR 47283 through 47288; and 81 FR 25148).) In cases
where the initial assignment of a low-volume proposed MS-LTC-DRG to a
quintile results in nonmonotonicity within a base-DRG, we are proposing
to make adjustments to the resulting low-volume proposed MS-LTC-DRGs to
preserve monotonicity, as discussed in detail in section VII.B.3.g.
(Step 6) of the preamble of this proposed rule.
In this proposed rule, based on the best available data (that is,
the December 2018 update of the FY 2018 MedPAR files), we identified
259 proposed MS-LTC-DRGs that contained between 1 and 24 applicable
LTCH cases. This list of proposed MS-LTC-DRGs was then divided into 1
of the 5 low-volume quintiles, each containing at least proposed 51 MS-
LTC-DRGs (259/5 = 51 with a remainder of 4). We assigned the proposed
low-volume MS-LTC-DRGs to specific proposed low-volume quintiles by
sorting the proposed low-volume MS-LTC-DRGs in ascending order by
average charge in accordance with our established methodology. Based on
the data available for this proposed rule, the number of proposed MS-
LTC-DRGs with less than 25 applicable LTCH cases was not evenly
divisible by 5 and, therefore, we are proposing to employ our
historical methodology for determining which of the proposed low-volume
quintiles would contain the additional proposed low-volume MS-LTC-DRG.
Specifically for this proposed rule, after organizing the proposed MS-
LTC-DRGs by ascending order by average charge, we assigned the first 52
(1st through 52nd) of proposed low-volume MS-LTC-DRGs (with the lowest
average charge) into Quintile 1. Because the average charge of the 52nd
proposed low-volume MS-LTC-DRG in the sorted list was closer to the
average charge of the 51st proposed low-volume MS-LTC-DRG (assigned to
Quintile 1) than to the average charge of the 53rd proposed low-volume
MS-LTC-DRG (assigned to Quintile 2), we assigned it to Quintile 1 (such
that Quintile 1 contains 52 proposed low-volume MS-LTC-DRGs before any
adjustments for nonmonotonicity, as discussed below). The 51 proposed
MS-LTC-DRGs with the highest average charge were assigned into Quintile
5. This resulted in 4 of the 5 proposed low-volume quintiles containing
52 proposed MS-LTC-DRGs (Quintiles 1 through 4) and 1 proposed low-
volume quintile containing 51 proposed MS-LTC-DRGs (Quintile 5). As
discussed earlier, for this proposed rule, we are providing the list of
the composition of the proposed low-volume quintiles for proposed low-
volume MS-LTC-DRGs for FY 2020 in a supplemental data file for public
use posted via the internet on the CMS website for this proposed rule
at: http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/Acute InpatientPPS/index.html in order to streamline the information
made available to the public that is used in the annual development of
Table 11.
In order to determine the proposed FY 2020 relative weights for the
proposed low-volume MS-LTC-DRGs, consistent with our historical
practice, we are proposing to use the five low-volume quintiles
described previously. We determined a proposed relative weight and
(geometric) average length of stay for each of the five proposed low-
volume quintiles using the methodology described in section VII.B.3.g.
of the preamble of this proposed rule. We are proposing to assign the
same proposed relative weight and average length of stay to each of the
proposed low-volume MS-LTC-DRGs that make up an individual low-volume
quintile. We note that, as this system is dynamic, it is possible that
the number and specific type of MS-LTC-DRGs with a low-volume of
applicable LTCH cases will vary in the future. Furthermore, we note
that we continue to monitor the volume (that is, the number of
applicable LTCH cases) in the low-volume quintiles to ensure that our
quintile assignments used in determining the MS-LTC-DRG relative
weights result in appropriate payment for LTCH cases grouped to
proposed low-volume MS-LTC-DRGs and do not result in an unintended
financial incentive for LTCHs to inappropriately admit these types of
cases.
g. Steps for Determining the Proposed FY 2020 MS-LTC-DRG Relative
Weights
In this proposed rule, we are proposing to continue to use our
current methodology to determine the proposed FY 2020 MS-LTC-DRG
relative weights.
In summary, to determine the proposed FY 2020 MS-LTC-DRG relative
weights, we are proposing to group applicable LTCH cases to the
appropriate proposed MS-LTC-DRG, while taking into account the proposed
low-volume quintiles (as described above) and cross-walked proposed no-
volume MS-LTC-DRGs (as described later in this section). After
establishing the appropriate proposed MS-LTC-DRG (or proposed low-
volume quintile), we are proposing to calculate the proposed FY 2020
relative weights by first removing cases with a length of stay of 7
days or less and statistical outliers (Steps 1 and 2 below). Next, we
are proposing to adjust the number of applicable LTCH cases in each
proposed MS-LTC-DRG (or proposed low-volume quintile) for the effect of
SSO cases (Step 3 below). After removing applicable LTCH cases with a
length of stay of 7 days or less (Step 1 below) and statistical
outliers (Step 2 below), which are the SSO-adjusted applicable LTCH
cases and corresponding charges (Step 3 below), we are proposing to we
calculate proposed ``relative adjusted weights'' for each proposed MS-
LTC-DRG (or proposed low-volume quintile) using the HSRV method.
Step 1--Remove cases with a length of stay of 7 days or less.
The first step in our proposed calculation of the proposed FY 2020
MS-LTC-DRG relative weights is to remove cases with a length of stay of
7 days or less. The MS-LTC-DRG relative weights reflect the average of
resources used on representative cases of a specific type. Generally,
cases with a length of stay of 7 days or less do not belong in an LTCH
because these stays do not fully receive or benefit from treatment that
is typical in an LTCH stay, and full resources are often not used in
the earlier stages of admission to an LTCH. If we were to include stays
of 7 days or less in the computation of the FY 2020 MS-LTC-DRG relative
weights, the value of many relative weights would decrease and,
therefore, payments would decrease to a level that may no longer be
appropriate. We do not believe that it would be appropriate to
compromise the integrity of the payment determination for those LTCH
cases that actually benefit from and receive a full course of treatment
at an LTCH by including data from these very
[[Page 19465]]
short stays. Therefore, consistent with our existing relative weight
methodology, in determining the proposed FY 2020 MS-LTC-DRG relative
weights, we are proposing to remove LTCH cases with a length of stay of
7 days or less from applicable LTCH cases. (For additional information
on what is removed in this step of the relative weight methodology, we
refer readers to 67 FR 55989 and 74 FR 43959.)
Step 2--Remove statistical outliers.
The next step in our proposed calculation of the proposed FY 2020
MS-LTC-DRG relative weights is to remove statistical outlier cases from
the LTCH cases with a length of stay of at least 8 days. Consistent
with our existing relative weight methodology, we are proposing to
continue to define statistical outliers as cases that are outside of
3.0 standard deviations from the mean of the log distribution of both
charges per case and the charges per day for each MS-LTC-DRG. These
statistical outliers are removed prior to calculating the proposed
relative weights because we believe that they may represent aberrations
in the data that distort the measure of average resource use. Including
those LTCH cases in the calculation of the proposed relative weights
could result in an inaccurate relative weight that does not truly
reflect relative resource use among those MS-LTC-DRGs. (For additional
information on what is removed in this step of the proposed relative
weight methodology, we refer readers to 67 FR 55989 and 74 FR 43959.)
After removing cases with a length of stay of 7 days or less and
statistical outliers, we were left with applicable LTCH cases that have
a length of stay greater than or equal to 8 days. In this proposed
rule, we refer to these cases as ``trimmed applicable LTCH cases.''
Step 3--Adjust charges for the effects of SSOs.
As the next step in the proposed calculation of the proposed FY
2020 MS-LTC-DRG relative weights, consistent with our historical
approach, we are proposing to adjust each LTCH's charges per discharge
for those remaining cases (that is, trimmed applicable LTCH cases) for
the effects of SSOs (as defined in Sec. 412.529(a) in conjunction with
Sec. 412.503). Specifically, we are proposing to make this adjustment
by counting an SSO case as a fraction of a discharge based on the ratio
of the length of stay of the case to the average length of stay for the
MS-LTC-DRG for non-SSO cases. This has the effect of proportionately
reducing the impact of the lower charges for the SSO cases in
calculating the average charge for the MS-LTC-DRG. This process
produces the same result as if the actual charges per discharge of an
SSO case were adjusted to what they would have been had the patient's
length of stay been equal to the average length of stay of the MS-LTC-
DRG.
Counting SSO cases as full LTCH cases with no adjustment in
determining the proposed FY 2020 MS-LTC-DRG relative weights would
lower the proposed FY 2020 MS-LTC-DRG relative weight for affected MS-
LTC-DRGs because the relatively lower charges of the SSO cases would
bring down the average charge for all cases within a MS-LTC-DRG. This
would result in an ``underpayment'' for non-SSO cases and an
``overpayment'' for SSO cases. Therefore, we are proposing to continue
to adjust for SSO cases under Sec. 412.529 in this manner because it
would result in more appropriate payments for all LTCH PPS standard
Federal payment rate cases. (For additional information on this step of
the relative weight methodology, we refer readers to 67 FR 55989 and 74
FR 43959.)
Step 4--Calculate the proposed FY 2020 MS-LTC-DRG relative weights
on an iterative basis.
Consistent with our historical relative weight methodology, we are
proposing to calculate the proposed FY 2020 MS-LTC-DRG relative weights
using the HSRV methodology, which is an iterative process. First, for
each SSO-adjusted trimmed applicable LTCH case, we calculated a
hospital-specific relative charge value by dividing the charge per
discharge after adjusting for SSOs of the LTCH case (from Step 3) by
the average charge per SSO-adjusted discharge for the LTCH in which the
case occurred. The resulting ratio is then multiplied by the LTCH's
case-mix index to produce an adjusted hospital-specific relative charge
value for the case. We used an initial case-mix index value of 1.0 for
each LTCH.
For each proposed MS-LTC-DRG, we calculated the proposed FY 2020
relative weight by dividing the SSO-adjusted average of the hospital-
specific relative charge values for applicable LTCH cases for the
proposed MS-LTC-DRG (that is, the sum of the hospital-specific relative
charge value from above divided by the sum of equivalent cases from
Step 3 for each proposed MS-LTC-DRG) by the overall SSO-adjusted
average hospital-specific relative charge value across all applicable
LTCH cases for all LTCHs (that is, the sum of the hospital-specific
relative charge value from above divided by the sum of equivalent
applicable LTCH cases from Step 3 for each proposed MS-LTC-DRG). Using
these recalculated MS-LTC-DRG relative weights, each LTCH's average
relative weight for all of its SSO-adjusted trimmed applicable LTCH
cases (that is, its case-mix) was calculated by dividing the sum of all
the LTCH's MS-LTC-DRG relative weights by its total number of SSO-
adjusted trimmed applicable LTCH cases. The LTCHs' hospital-specific
relative charge values (from previous) are then multiplied by the
hospital-specific case-mix indexes. The hospital-specific case-mix
adjusted relative charge values are then used to calculate a new set of
proposed MS-LTC-DRG relative weights across all LTCHs. This iterative
process continued until there was convergence between the relative
weights produced at adjacent steps, for example, when the maximum
difference was less than 0.0001.
Step 5--Determine a proposed FY 2020 relative weight for MS-LTC-
DRGs with no applicable LTCH cases.
Using the trimmed applicable LTCH cases, consistent with our
historical methodology, we identified the proposed MS-LTC-DRGs for
which there were no claims in the December 2018 update of the FY 2018
MedPAR file and, therefore, for which no charge data was available for
these proposed MS-LTC-DRGs. Because patients with a number of the
diagnoses under these proposed MS-LTC-DRGs may be treated at LTCHs,
consistent with our historical methodology, we generally assign a
proposed relative weight to each of the proposed no-volume MS-LTC-DRGs
based on clinical similarity and relative costliness (with the
exception of ``transplant'' proposed MS-LTC-DRGs, ``error'' proposed
MS-LTC-DRGs, and proposed MS-LTC-DRGs that indicate a principal
diagnosis related to a psychiatric diagnosis or rehabilitation
(referred to as the ``psychiatric or rehabilitation'' MS-LTC-DRGs), as
discussed later in this section of this proposed rule). (For additional
information on this step of the relative weight methodology, we refer
readers to 67 FR 55991 and 74 FR 43959 through 43960.)
We are proposing to cross-walk each no-volume proposed MS-LTC-DRG
to another proposed MS-LTC-DRG for which we calculated a proposed
relative weight (determined in accordance with the methodology
described above). Then, the ``no-volume'' proposed MS-LTC-DRG was
assigned the same proposed relative weight (and average length of stay)
of the proposed MS-LTC-DRG to which it was cross-walked
[[Page 19466]]
(as described in greater detail in this section of this proposed rule).
Of the 761 proposed MS-LTC-DRGs for FY 2020, we identified 320 MS-
LTC-DRGs for which there were no trimmed applicable LTCH cases (the
number identified includes the 8 ``transplant'' MS-LTC-DRGs, the 2
``error'' MS-LTC-DRGs, and the 15 ``psychiatric or rehabilitation'' MS-
LTC-DRGs, which are discussed below). We are proposing to assign
proposed relative weights to each of the 320 no-volume proposed MS-LTC-
DRGs that contained trimmed applicable LTCH cases based on clinical
similarity and relative costliness to 1 of the remaining 441 (761-320 =
441) proposed MS-LTC-DRGs for which we calculated proposed relative
weights based on the trimmed applicable LTCH cases in the FY 2018
MedPAR file data using the steps described previously. (For the
remainder of this discussion, we refer to the ``cross-walked'' proposed
MS-LTC-DRGs as the proposed MS-LTC-DRGs to which we cross-walked 1 of
the 320 ``no-volume'' proposed MS-LTC-DRGs.) Then, we are generally
proposing to assign the 320 no-volume proposed MS-LTC-DRGs the proposed
relative weight of the cross-walked proposed MS-LTC-DRG. (As explained
below in Step 6, when necessary, we made adjustments to account for
nonmonotonicity.)
We cross-walked the no-volume proposed MS-LTC-DRG to a proposed MS-
LTC-DRG for which we calculated proposed relative weights based on the
December 2018 update of the FY 2018 MedPAR file, and to which it is
similar clinically in intensity of use of resources and relative
costliness as determined by criteria such as care provided during the
period of time surrounding surgery, surgical approach (if applicable),
length of time of surgical procedure, postoperative care, and length of
stay. (For more details on our process for evaluating relative
costliness, we refer readers to the FY 2010 IPPS/RY 2010 LTCH PPS final
rule (73 FR 48543).) We believe in the rare event that there would be a
few LTCH cases grouped to one of the no-volume proposed MS-LTC-DRGs in
FY 2020, the proposed relative weights assigned based on the cross-
walked proposed MS-LTC-DRGs would result in an appropriate LTCH PPS
payment because the crosswalks, which are based on clinical similarity
and relative costliness, would be expected to generally require
equivalent relative resource use.
We then assigned the proposed relative weight of the cross-walked
proposed MS-LTC-DRG as the proposed relative weight for the no-volume
proposed MS-LTC-DRG such that both of these proposed MS-LTC-DRGs (that
is, the no-volume proposed MS-LTC-DRG and the cross-walked proposed MS-
LTC-DRG) have the same proposed relative weight (and average length of
stay) for FY 2020. We note that, if the cross-walked proposed MS-LTC-
DRG had 25 applicable LTCH cases or more, its proposed relative weight
(calculated using the methodology described in Steps 1 through 4 above)
is assigned to the no-volume proposed MS-LTC-DRG as well. Similarly, if
the proposed MS-LTC-DRG to which the no-volume proposed MS-LTC-DRG was
cross-walked had 24 or less cases and, therefore, was designated to 1
of the proposed low-volume quintiles for purposes of determining the
proposed relative weights, we assigned the proposed relative weight of
the applicable proposed low-volume quintile to the no-volume proposed
MS-LTC-DRG such that both of these proposed MS-LTC-DRGs (that is, the
no-volume proposed MS-LTC-DRG and the cross-walked proposed MS-LTC-DRG)
have the same proposed relative weight for FY 2020. (As we noted
previously, in the infrequent case where nonmonotonicity involving a
no-volume proposed MS-LTC-DRG resulted, additional adjustments as
described in Step 6 are required in order to maintain monotonically
increasing proposed relative weights.)
As discussed earlier, for this proposed rule, we are providing the
list of the no-volume proposed MS-LTC-DRGs and the proposed MS-LTC-DRGs
to which each was cross-walked (that is, the cross-walked proposed MS-
LTC-DRGs) for FY 2020 in a supplemental data file for public use posted
via the internet on the CMS website for this proposed rule at: http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html in order to streamline the information
made available to the public that is used in the annual development of
Table 11.
To illustrate this methodology for determining the proposed
relative weights for the proposed FY 2020 MS-LTC-DRGs with no
applicable LTCH cases, we are providing the following example, which
refers to the no-volume proposed MS-LTC-DRGs crosswalk information for
FY 2020 (which, as previously stated, we are providing in a
supplemental data file posted via the internet on the CMS website for
this proposed rule).
Example: There were no trimmed applicable LTCH cases in the FY 2018
MedPAR file that we are using for this proposed rule for proposed MS-
LTC-DRG 061 (Acute Ischemic Stroke with Use of Thrombolytic Agent with
MCC). We determined that proposed MS-LTC-DRG 070 (Nonspecific
Cerebrovascular Disorders with MCC) is similar clinically and based on
resource use to proposed MS-LTC-DRG 061. Therefore, we assigned the
same proposed relative weight (and average length of stay) of proposed
MS-LTC-DRG 70 of 0.8909 for FY 2020 to proposed MS-LTC-DRG 061 (we
refer readers to Table 11, which is listed in section VI. of the
Addendum to this proposed rule and is available via the internet on the
CMS website).
Again, we note that, as this system is dynamic, it is entirely
possible that the number of proposed MS-LTC-DRGs with no volume will
vary in the future. Consistent with our historical practice, we are
proposing to use the most recent available claims data to identify the
trimmed applicable LTCH cases from which we determine the relative
weights in the final rule.
For FY 2020, consistent with our historical relative weight
methodology, we are proposing to establish a proposed relative weight
of 0.0000 for the following transplant proposed MS-LTC-DRGs: Heart
Transplant or Implant of Heart Assist System with MCC (MS-LTC-DRG 001);
Heart Transplant or Implant of Heart Assist System without MCC (MS-LTC-
DRG 002); Liver Transplant with MCC or Intestinal Transplant (MS-LTC-
DRG 005); Liver Transplant without MCC (MS-LTC-DRG 006); Lung
Transplant (MS-LTC-DRG 007); Simultaneous Pancreas/Kidney Transplant
(MS-LTC-DRG 008); Pancreas Transplant (MS-LTC-DRG 010); and Kidney
Transplant (MS-LTC-DRG 652). This is because Medicare only covers these
procedures if they are performed at a hospital that has been certified
for the specific procedures by Medicare and presently no LTCH has been
so certified. At the present time, we include these eight proposed
transplant MS-LTC-DRGs in the GROUPER program for administrative
purposes only. Because we use the same GROUPER program for LTCHs as is
used under the IPPS, removing these MS-LTC-DRGs would be
administratively burdensome. (For additional information regarding our
treatment of transplant MS-LTC-DRGs, we refer readers to the RY 2010
LTCH PPS final rule (74 FR 43964).) In addition, consistent with our
historical policy, we are proposing to establish a relative weight of
0.0000 for the 2 ``error'' MS-LTC-DRGs (that is, MS-LTC-DRG 998
(Principal Diagnosis Invalid as Discharge Diagnosis) and MS-LTC-DRG 999
(Ungroupable)) because applicable LTCH cases grouped to these MS-LTC-
DRGs cannot be properly assigned to an
[[Page 19467]]
MS-LTC-DRG according to the grouping logic.
Section 51005 of the Bipartisan Budget Act of 2018 (Pub. L. 115-
123) extended the transitional blended payment rate for site neutral
payment rate cases for an additional 2 years (that is, discharges
occurring in cost reporting periods beginning in FYs 2018 and 2019
continued to be paid under the blended payment rate). Therefore, in the
FY 2019 IPPS/LTCH PPS final rule (83 FR 41529), consistent with our
practice in FYs 2016 through 2018, we established a relative weight for
FY 2019 equal to the respective FY 2015 relative weight of the MS-LTC-
DRGs for the following ``psychiatric or rehabilitation'' MS-LTC-DRGs:
MS-LTC-DRG 876 (O.R. Procedure with Principal Diagnoses of Mental
Illness); MS-LTC-DRG 880 (Acute Adjustment Reaction & Psychosocial
Dysfunction); MS-LTC-DRG 881 (Depressive Neuroses); MS-LTC-DRG 882
(Neuroses Except Depressive); MS-LTC-DRG 883 (Disorders of Personality
& Impulse Control); MS-LTC-DRG 884 (Organic Disturbances & Mental
Retardation); MS-LTC-DRG 885 (Psychoses); MS-LTC-DRG 886 (Behavioral &
Developmental Disorders); MS-LTC-DRG 887 (Other Mental Disorder
Diagnoses); MS-LTC-DRG 894 (Alcohol/Drug Abuse or Dependence, Left
Ama); MS-LTC-DRG 895 (Alcohol/Drug Abuse or Dependence, with
Rehabilitation Therapy); MS-LTC-DRG 896 (Alcohol/Drug Abuse or
Dependence, without Rehabilitation Therapy with MCC); MS-LTC-DRG 897
(Alcohol/Drug Abuse or Dependence, without Rehabilitation Therapy
without MCC); MS-LTC-DRG 945 (Rehabilitation with CC/MCC); and MS-LTC-
DRG 946 (Rehabilitation without CC/MCC). As we discussed when we
implemented the dual rate LTCH PPS payment structure, LTCH discharges
that are grouped to these 15 ``psychiatric and rehabilitation'' MS-LTC-
DRGs do not meet the criteria for exclusion from the site neutral
payment rate. As such, under the criterion for a principal diagnosis
relating to a psychiatric diagnosis or to rehabilitation, there are no
applicable LTCH cases to use in calculating a relative weight for the
``psychiatric and rehabilitation'' MS-LTC-DRGs. In other words, any
LTCH PPS discharges grouped to any of the 15 ``psychiatric and
rehabilitation'' MS-LTC-DRGs would always be paid at the site neutral
payment rate, and, therefore, those MS-LTC-DRGs would never include any
LTCH cases that meet the criteria for exclusion from the site neutral
payment rate. However, section 1886(m)(6)(B) of the Act establishes a
transitional payment method for cases that would be paid at the site
neutral payment rate for LTCH discharges occurring in cost reporting
periods beginning during FY 2016 or FY 2017, which was extended to
include FYs 2018 and 2019 under Public Law 115-123. (We refer readers
to section VII.C. of the preamble of the FY 2019 IPPS/LTCH PPS final
rule for a detailed discussion of the extension of the transitional
blended payment method provisions under Public Law 115-123 and our
policies for FY 2019). Under the transitional blended payment method
for site neutral payment rate cases, for LTCH discharges occurring in
cost reporting periods beginning on or after October 1, 2018, and on or
before September 30, 2019, site neutral payment rate cases are paid a
blended payment rate, calculated as 50 percent of the applicable site
neutral payment rate amount for the discharge and 50 percent of the
applicable LTCH PPS standard Federal payment rate. Because this
transitional blended payment method for site neutral payment rate cases
is applicable for LTCH discharges occurring in cost reporting periods
beginning on or after October 1, 2018, and on or before September 30,
2019, some LTCHs' site neutral payment rate cases that are discharged
during FY 2020 will be paid a blended payment rate.
Because the LTCH PPS standard Federal payment rate is based on the
relative weight of the MS-LTC-DRG, in order to determine the
transitional blended payment for site neutral payment rate cases
grouped to one of the ``psychiatric or rehabilitation'' MS-LTC-DRGs in
FY 2020, consistent with past practice, we are proposing to assign a
relative weight to these MS-LTC-DRGs for FY 2020 that is the same as
the FY 2019 relative weight (which is also the same as the FYs 2016
through 2019 relative weight). We believed that using the respective FY
2015 relative weight for each of the ``psychiatric or rehabilitation''
MS-LTC-DRGs results in appropriate payments for LTCH cases that are
paid at the site neutral payment rate under the transition policy
provided by the statute because there are no clinically similar MS-LTC-
DRGs for which we were able to determine relative weights based on
applicable LTCH cases in the December 2018 update of the FY 2018 MedPAR
file data using the steps described above. Furthermore, we believed
that it would be administratively burdensome and introduce unnecessary
complexity to the MS-LTC-DRG relative weight calculation to use the
LTCH discharges in the MedPAR file data to calculate a relative weight
for those 15 ``psychiatric and rehabilitation'' MS-LTC-DRGs to be used
for the sole purposes of determining half of the transitional blended
payment for site neutral payment rate cases during the transition
period (80 FR 49631 through 49632) or payment for discharges from
spinal cord specialty hospitals under Sec. 412.522(b)(4).
In summary, for FY 2020, we are proposing to establish a relative
weight (and average length of stay thresholds) equal to the respective
FY 2015 relative weight of the MS-LTC-DRGs for the 15 ``psychiatric or
rehabilitation'' MS-LTC-DRGs listed previously (that is, MS-LTC-DRGs
876, 880, 881, 882, 883, 884, 885, 886, 887, 894, 895, 896, 897, 945,
and 946). Table 11, which is listed in section VI. of the Addendum to
this proposed rule and is available via the internet on the CMS
website, reflects this policy.
Step 6--Adjust the proposed FY 20120MS-LTC-DRG relative weights to
account for nonmonotonically increasing relative weights.
The MS-DRGs contain base DRGs that have been subdivided into one,
two, or three severity of illness levels. Where there are three
severity levels, the most severe level has at least one secondary
diagnosis code that is referred to as an MCC (that is, major
complication or comorbidity). The next lower severity level contains
cases with at least one secondary diagnosis code that is a CC (that is,
complication or comorbidity). Those cases without an MCC or a CC are
referred to as ``without CC/MCC.'' When data do not support the
creation of three severity levels, the base MS-DRG is subdivided into
either two levels or the base MS-DRG is not subdivided. The two-level
subdivisions may consist of the MS-DRG with CC/MCC and the MS-DRG
without CC/MCC. Alternatively, the other type of two-level subdivision
may consist of the MS-DRG with MCC and the MS-DRG without MCC.
In those base MS-LTC-DRGs that are split into either two or three
severity levels, cases classified into the ``without CC/MCC'' MS-LTC-
DRG are expected to have a lower resource use (and lower costs) than
the ``with CC/MCC'' MS-LTC-DRG (in the case of a two-level split) or
both the ``with CC'' and the ``with MCC'' MS-LTC-DRGs (in the case of a
three-level split). That is, theoretically, cases that are more severe
typically require greater expenditure of medical care resources and
would result in higher average charges. Therefore, in the three
severity levels, relative
[[Page 19468]]
weights should increase by severity, from lowest to highest. If the
relative weights decrease as severity increases (that is, if within a
base MS-LTC-DRG, an MS-LTC-DRG with CC has a higher relative weight
than one with MCC, or the MS-LTC-DRG ``without CC/MCC'' has a higher
relative weight than either of the others), they are nonmonotonic. We
continue to believe that utilizing nonmonotonic relative weights to
adjust Medicare payments would result in inappropriate payments because
the payment for the cases in the higher severity level in a base MS-
LTC-DRG (which are generally expected to have higher resource use and
costs) would be lower than the payment for cases in a lower severity
level within the same base MS-LTC-DRG (which are generally expected to
have lower resource use and costs). Therefore, in determining the
proposed FY 2020 MS-LTC-DRG relative weights, consistent with our
historical methodology, we are proposing to continue to combine MS-LTC-
DRG severity levels within a base MS-LTC-DRG for the purpose of
computing a relative weight when necessary to ensure that monotonicity
is maintained. For a comprehensive description of our existing
methodology to adjust for nonmonotonicity, we refer readers to the FY
2010 IPPS/RY 2010 LTCH PPS final rule (74 FR 43964 through 43966). Any
adjustments for nonmonotonicity that were made in determining the
proposed FY 2020 MS-LTC-DRG relative weights in this proposed rule by
applying this methodology are denoted in Table 11, which is listed in
section VI. of the Addendum to this proposed rule and is available via
the internet on the CMS website.
Step 7-- Calculate the proposed FY 2020 MS-LTC-DRG reclassification
and recalibration budget neutrality factor.
In accordance with the regulations at Sec. 412.517(b) (in
conjunction with Sec. 412.503), the annual update to the MS-LTC-DRG
classifications and relative weights is done in a budget neutral manner
such that estimated aggregate LTCH PPS payments would be unaffected,
that is, would be neither greater than nor less than the estimated
aggregate LTCH PPS payments that would have been made without the MS-
LTC-DRG classification and relative weight changes. (For a detailed
discussion on the establishment of the budget neutrality requirement
for the annual update of the MS-LTC-DRG classifications and relative
weights, we refer readers to the RY 2008 LTCH PPS final rule (72 FR
26881 and 26882).)
The MS-LTC-DRG classifications and relative weights are updated
annually based on the most recent available LTCH claims data to reflect
changes in relative LTCH resource use (Sec. 412.517(a) in conjunction
with Sec. 412.503). To achieve the budget neutrality requirement at
Sec. 412.517(b), under our established methodology, for each annual
update, the MS-LTC-DRG relative weights are uniformly adjusted to
ensure that estimated aggregate payments under the LTCH PPS would not
be affected (that is, decreased or increased). Consistent with that
provision, we are proposing to update the MS-LTC-DRG classifications
and relative weights for FY 2020 based on the most recent available
LTCH data for applicable LTCH cases, and continue to apply a budget
neutrality adjustment in determining the proposed FY 2020 MS-LTC-DRG
relative weights.
In this FY 2020 IPPS/LTCH PPS proposed rule, to ensure budget
neutrality in the update to the MS-LTC-DRG classifications and relative
weights under Sec. 412.517(b), we are proposing to continue to use our
established two-step budget neutrality methodology.
To calculate the proposed normalization factor for FY 2020, we are
proposing to group applicable LTCH cases using the proposed FY 2020
Version 37 GROUPER, and the recalibrated proposed FY 2020 MS-LTC-DRG
relative weights to calculate the average case-mix index (CMI); we
grouped the same applicable LTCH cases using the FY 2019 GROUPER
Version 36 and MS-LTC-DRG relative weights and calculated the average
CMI; and computed the ratio by dividing the average CMI for FY 2019 by
the average CMI for proposed FY 2020. That ratio is the proposed
normalization factor. Because the calculation of the proposed
normalization factor involves the proposed relative weights for the
proposed MS-LTC-DRGs that contained applicable LTCH cases to calculate
the average CMIs, any low-volume proposed MS-LTC-DRGs are included in
the calculation (and the proposed MS-LTC-DRGs with no applicable LTCH
cases are not included in the calculation).
To calculate the proposed budget neutrality adjustment factor, we
simulated estimated total FY 2020 LTCH PPS standard Federal payment
rate payments for applicable LTCH cases using the proposed FY 2020
normalized relative weights and proposed GROUPER Version 37; simulated
estimated total FY 2020 LTCH PPS standard Federal payment rate payments
for applicable LTCH cases using the FY 2019 MS-LTC-DRG relative weights
and the FY 2019 GROUPER Version 36; and calculated the ratio of these
estimated total payments by dividing the simulated estimated total LTCH
PPS standard Federal payment rate payments using the FY 2019 MS-LTC-DRG
relative weights and the GROUPER Version 36 by the simulated estimated
total LTCH PPS standard Federal payment rate payments using the
proposed FY 2020 MS-LTC-DRG relative weights and the proposed GROUPER
Version 37. The resulting ratio is the proposed budget neutrality
adjustment factor. The calculation of the proposed budget neutrality
factor involves the proposed relative weights for the LTCH cases used
in the payment simulation, which includes any cases grouped to low-
volume proposed MS-LTC-DRGs or to proposed MS-LTC-DRGs with no
applicable LTCH cases, and generally does not include payments for
cases grouped to a proposed MS-LTC-DRG with no applicable LTCH cases.
(Occasionally, a few LTCH cases (that is, those with a covered length
of stay of 7 days or less), which are removed from the proposed
relative weight calculation in step (2) that are grouped to a proposed
MS-LTC-DRG with no applicable LTCH cases are included in the payment
simulations used to calculate the proposed budget neutrality factor.
However, the number and payment amount of such cases have a negligible
impact on the proposed budget neutrality factor calculation).
In this proposed rule, to ensure budget neutrality in the update to
the MS-LTC-DRG classifications and relative weights under Sec.
412.517(b), we are proposing to continue to use our established two-
step budget neutrality methodology. Therefore, in this proposed rule,
in the first step of our proposed MS-LTC-DRG budget neutrality
methodology, for FY 2020, we are proposing to calculate and apply a
proposed normalization factor to the recalibrated proposed relative
weights (the result of Steps 1 through 6 discussed previously) to
ensure that estimated payments are not affected by changes in the
composition of case types or the proposed changes to the classification
system. That is, the proposed normalization adjustment is intended to
ensure that the recalibration of the proposed MS-LTC-DRG relative
weights (that is, the process itself) neither increases nor decreases
the average case-mix index.
To calculate the proposed normalization factor for FY 2020 (the
first step of our proposed budget neutrality methodology), we used the
following three steps: (1.a.) Used the most recent available applicable
LTCH cases from the most recent available data (that is, LTCH
discharges from the
[[Page 19469]]
FY 2018 MedPAR file) and grouped them using the proposed FY 2020
GROUPER (that is, proposed Version 37 for FY 2020) and the recalibrated
proposed FY 2020 MS-LTC-DRG relative weights (determined in Steps 1
through 6 above) to calculate the average case-mix index; (1.b.)
grouped the same applicable LTCH cases (as are used in Step 1.a.) using
the FY 2019 GROUPER (Version 36) and FY 2019 MS-LTC-DRG relative
weights and calculated the average case-mix index; and (1.c.) computed
the ratio of these average case-mix indexes by dividing the average CMI
for FY 2020 (determined in Step 1.a.) by the average case-mix index for
FY 2019 (determined in Step 1.b.). As a result, in determining the
proposed MS-LTC-DRG relative weights for FY 2020, each recalibrated
proposed MS-LTC-DRG relative weight is multiplied by the proposed
normalization factor of 1.271 (determined in Step 1.c.) in the first
step of the proposed budget neutrality methodology, which produced
``normalized relative weights.''
In the second step of our proposed MS-LTC-DRG budget neutrality
methodology, we calculated a second proposed budget neutrality factor
consisting of the ratio of estimated aggregate FY 2020 LTCH PPS
standard Federal payment rate payments for applicable LTCH cases (the
sum of all calculations under Step 1.a. mentioned previously) after
reclassification and recalibration to estimated aggregate payments for
FY 2020 LTCH PPS standard Federal payment rate payments for applicable
LTCH cases before reclassification and recalibration (that is, the sum
of all calculations under Step 1.b. mentioned previously).
That is, for this proposed rule, for FY 2020, under the second step
of the proposed budget neutrality methodology, we are proposing to
determine the proposed budget neutrality adjustment factor using the
following three steps: (2.a.) Simulated estimated total FY 2020 LTCH
PPS standard Federal payment rate payments for applicable LTCH cases
using the proposed normalized relative weights for FY 2020 and proposed
GROUPER Version 37 (as described above); (2.b.) simulated estimated
total FY 2020 LTCH PPS standard Federal payment rate payments for
applicable LTCH cases using the FY 2019 GROUPER (Version 36) and the FY
2019 MS-LTC-DRG relative weights in Table 11 of the FY 2019 IPPS/LTCH
PPS final rule available on the internet, as described in section VI.
of the Addendum of that final rule; and (2.c.) calculated the ratio of
these estimated total payments by dividing the value determined in Step
2.b. by the value determined in Step 2.a. In determining the proposed
FY 2020 MS-LTC-DRG relative weights, each normalized proposed relative
weight is then multiplied by a budget neutrality factor of 0.9971599
(the value determined in Step 2.c.) in the second step of the proposed
budget neutrality methodology to achieve the budget neutrality
requirement at Sec. 412.517(b).
Accordingly, in determining the proposed FY 2020 MS-LTC-DRG
relative weights in this proposed rule, consistent with our existing
methodology, we are proposing to apply a normalization factor of 1.271
and a budget neutrality factor of 0.9971599. Table 11, which is listed
in section VI. of the Addendum to this proposed rule and is available
via the internet on the CMS website, lists the proposed MS-LTC-DRGs and
their respective proposed relative weights, geometric mean length of
stay, and five-sixths of the geometric mean length of stay (used to
identify SSO cases under Sec. 412.529(a)) for FY 2020.
C. Proposed Payment Adjustment for LTCH Discharges That Do Not Meet the
Applicable Discharge Payment Percentage
Section 1886(m)(6)(C) of the Act, as added by section 1206 of the
Pathway for SGR Reform Act of 2013 (Pub. L. 113-67), imposes several
requirements related to an LTCH's discharge payment percentage. As
defined by section 1886(m)(6)(C)(iv) of the Act, the term ``LTCH
discharge payment percentage'' is a ratio, expressed as a percentage,
of Medicare fee-for-service (FFS) discharges not paid the site neutral
payment rate to total number of Medicare FFS discharges occurring
during the cost reporting period. In other words, an LTCH's discharge
payment percentage is the ratio of an LTCH's Medicare discharges that
meet the criteria for exclusion from the site neutral payment rate (as
described under Sec. 412.522(a)), that is, discharges paid the LTCH
PPS standard Federal payment rate, to an LTCH's total number of
Medicare FFS discharges paid under the LTCH PPS during the cost
reporting period. Section 1886(m)(6)(C)(ii)(I) of the Act, requires
that, for cost reporting periods beginning on or after October 1, 2019,
any LTCH with a discharge payment percentage for the cost reporting
period that is not at least 50 percent be informed of such a fact; and
section 1886(m)(6)(C)(ii)(II) of the Act requires that all of the
LTCH's discharges in each successive cost reporting period be paid the
payment amount that would apply under subsection (d) for the discharge
if the hospital were a subsection (d) hospital, subject to the LTCH's
compliance with the process for reinstatement provided for by section
1886(m)(6)(C)(iii) of the Act.
Section 1886(m)(6)(C)(i) of the Act requires that we provide notice
to each LTCH of the LTCH's discharge payment percentage for LTCH cost
reporting periods beginning during or after FY 2016. We implemented
this requirement in the FY 2016 IPPS/LTCH PPS final rule (80 FR 49613),
and we have established subregulatory policies and timeframes by which
we calculate and inform LTCHs of their discharge payment percentage. We
note that, because the discharge payment percentage for a cost
reporting period cannot be calculated until after the cost reporting
period has ended, in order to ensure claims for the entire period are
reflected, an LTCH is typically informed of the results of the
calculation of the discharge payment percentage between 5 and 6 months
after the end of the cost reporting period.
To implement the provisions of section 1886(m)(6)(C)(ii)(I) of the
Act, as established by the amendments made by Public Law 113-67, we are
proposing to continue to use our existing policy to calculate the
discharge payment percentage and to inform LTCHs when their discharge
payment percentage for the cost reporting period is not at least 50
percent. To implement the provisions of section 1886(m)(6)(C)(ii)(II)
of the Act, as established by the amendments made by Public Law 113-67,
we are proposing to establish the policy that an LTCH would become
subject to a payment adjustment for all of its cost reporting periods
beginning on or after October 1, 2019, and is notified that its
calculated discharge payment percentage did not equal at least 50
percent. For example, if an LTCH has a calendar year cost reporting
period, its first cost reporting period beginning on or after October
1, 2019 would be its January 1, 2020 through December 31, 2020 cost
reporting period (that is, its FY 2020 cost reporting period). Because
a cost reporting period must have ended and claims from the reporting
period must be processed prior to the calculation of the discharge
payment percentage, a hospital's discharge payment percentage for its
FY 2020 cost reporting period cannot be calculated for approximately 6
months; that is, not completed until sometime during its FY 2021 cost
reporting period. If the discharge payment percentage for its FY 2020
cost reporting period is not at least 50
[[Page 19470]]
percent (when calculated during its FY 2021 cost reporting period),
under our proposal, the LTCH would become subject to a payment
adjustment, applied to all discharges, for its FY 2022 cost reporting
period (the first cost reporting period after its discharge payment
percentage for a cost reporting period had been calculated to not have
been at least 50 percent). We are proposing to codify the proposed
implementation of these regulations establishing the policy to adjust
payment to an LTCH for all discharges when the LTCH does not meet the
discharge payment percentage after it is notified for cost reporting
periods beginning on or after October 1, 2019, under proposed new Sec.
412.522(d)(3).
As noted above, section 1886(m)(6)(C)(iii) of the Act, as
established by the amendments made by Public Law 113-67, provides for
the establishment of a reinstatement process whereby an LTCH can have
the payment adjustment discontinued. To implement and maintain a
reinstatement process as required by the statute, we are proposing to
discontinue the payment adjustment for an LTCH's discharges as a result
of its discharge payment percentage not equaling at least 50 percent
beginning with the discharges occurring in the cost reporting period
after the LTCH's discharge payment percentage is calculated to be at
least 50 percent. For example, the LTCH with a calendar year cost
reporting period that did not have a discharge payment percentage of at
least 50 percent during its FY 2020 cost reporting period would be
subject to the payment adjustment for its FY 2022 cost reporting
period, as described above. However, if the discharge payment
percentage for its FY 2021 cost reporting period equaled at least 50
percent, the calculation (and notification thereof) of such percentage
would be made during FY 2022, and the payment adjustment would be
discontinued beginning with discharges occurring at the start of its FY
2023 cost reporting period. We note that this proposed policy is based
on cost reporting periods, is cyclical in nature, and, as such, an LTCH
that has been reinstated would be subject to the payment adjustment
again (in a future cost reporting period) if its discharge payment
percentage is again calculated not to meet the required threshold. We
are proposing to codify the proposed policy reinstatement process for
LTCHs under the discharge payment percentage requirements in proposed
new Sec. 412.522(d)(5).
While we believe the proposed policy reinstatement process would
satisfy the statutory requirement without further modification, because
there could be unusual circumstances that result in a discharge payment
percentage for a cost reporting period that may not be fully reflective
of an LTCH's typical mix of site neutral and LTCH PPS standard Federal
payment rate discharges (for example, patients require a shorter period
of ventilation than was expected on admission), we also are proposing a
special probationary reinstatement process, which is consistent with
public comments we received during the FY 2016 rulemaking when the
dual-rate payment system was implemented. While the public comments
from the FY 2016 rulemaking cycle did not request that the special
reinstatement process be probationary, we are concerned that, while
there are unusual circumstances that may result in the discharge
payment percentage for a cost reporting period not being fully
reflective of an LTCH's typical mix of site neutral and LTCH PPS
standard Federal payment rate discharges, if the special reinstatement
process were not probationary, hospitals may be able to manipulate
discharges or delay billing in such a way as to artificially inflate
their discharge payment percentage for purposes of qualifying for the
special reinstatement process. To alleviate these concerns, we are
proposing that the special reinstatement process be probationary. Under
this proposed special probationary reinstatement process, a
probationary-cure period would allow an LTCH the opportunity to have
the payment adjustment delayed during the applicable cost reporting
period if, for the period of at least 5 consecutive months of the 6-
month period immediately preceding the beginning of the cost reporting
period during which the adjustment would apply (we note this time
period is consistent with our current policy for the average length-of-
stay determination), the discharge payment percentage is calculated to
be at least 50 percent. Under such circumstances, the LTCH would not
ultimately be subject to the payment adjustment for the cost reporting
period during which the adjustment would apply--provided that the
discharge payment percentage for that cost reporting period is at least
50 percent. If the discharge payment percentage for that cost reporting
period is not at least 50 percent, the adjustment will be applied to
the cost reporting period at settlement. For example, an LTCH with a
calendar year cost reporting period that does not have a discharge
payment percentage of at least 50 percent during its FY 2020 cost
reporting period would be informed of this during its FY 2021 cost
reporting period. The payment adjustment would then apply during its FY
2022 cost reporting period. However, if in the 6-month period
immediately preceding the cost reporting period for which the payment
adjustment would apply (July 1, 2021 through December 31, 2021), the
LTCH achieved at least 5 consecutive months with a discharge payment
percentage that is calculated to be at least 50 percent, application of
the payment adjustment would be delayed during the FY 2022 cost
reporting period (that is, the payment adjustment would not be applied
to any discharges that occur during the FY 2022 cost reporting period).
However, if the discharge payment percentage that is ultimately
calculated for that LTCH's FY 2022 cost reporting period (the period
for which the payment adjustment would have applied if the LTCH had not
met the requirements during the probationary-cure period) is not at
least 50 percent, the payment adjustment delay would be lifted, and the
penalty would be applied to payments made for all of the discharges
that occurred during the FY 2022 cost reporting period at settlement.
We are proposing to codify the policy for a special probationary
reinstatement process under proposed new Sec. 412.522(d)(6). We note
that we expect to issue subregulatory guidance to describe the specific
procedures for implementing this proposed probationary-cure period, if
the policy is finalized. However, we are inviting public comments on
suggestions regarding the specific process to be used, including
whether the process should mirror the existing process used by LTCHs
for the greater than 25-day average length-of-stay requirements.
Section 1886(m)(6)(C)(ii) of the Act specifies that, subject to the
process for reinstatement, when the requisite discharge patient
percentage threshold is not met, all of the LTCH's discharges in each
successive cost reporting period will be paid the payment amount that
would apply under subsection (d) for the discharge if the hospital were
a subsection (d) hospital. We note that ``subsection (d)'' as it is
referred to under section 1886(d) of the Act refers to IPPS hospitals.
For purposes of implementing the payment adjustment provisions of
section 1886(m)(6)(C)(ii) of the Act, as established by the amendments
of Public Law 113-67, we are proposing to establish the policy at
proposed new Sec. 412.522(d)(4) that, for cost reporting periods
beginning on or after October 1, 2019, under this payment adjustment,
the LTCH would receive payment for all discharges in the
[[Page 19471]]
cost reporting periods beginning after the LTCH is informed that its
calculated discharge payment percent is not at least 50 percent at the
amount comparable to the IPPS amount determined under Sec. Sec.
412.529(d)(4)(i)(A) and (ii), with an additional payment for high-cost
outlier cases that would be based on the IPPS fixed-loss amount in
effect at the time of the LTCH discharge. We note that the amount
comparable to the IPPS amount determined under Sec. Sec.
412.529(d)(4)(i)(A) and (ii) is the basis of the IPPS comparable per
diem amount (for which the per diem is calculated in accordance with
the provisions of Sec. Sec. 412.529(d)(4)(i)(B) and (C)) that are also
used to calculate payments under the SSO policy at Sec. 412.529(c)(4)
and site neutral payment rate payments at Sec. 412.522(c).
D. Proposed Changes to the LTCH PPS Payment Rates and Other Proposed
Changes to the LTCH PPS for FY 2020
1. Overview of Development of the LTCH PPS Standard Federal Payment
Rates
The basic methodology for determining LTCH PPS standard Federal
payment rates is currently set forth at 42 CFR 412.515 through 412.533
and 412.535. In this section, we discuss the factors that we are
proposing to use to update the LTCH PPS standard Federal payment rate
for FY 2020, that is, effective for LTCH discharges occurring on or
after October 1, 2019 through September 30, 2020. Under the dual rate
LTCH PPS payment structure required by statute, beginning with
discharges in cost reporting periods beginning in FY 2016, only LTCH
discharges that meet the criteria for exclusion from the site neutral
payment rate are paid based on the LTCH PPS standard Federal payment
rate specified at Sec. 412.523. (For additional details on our
finalized policies related to the dual rate LTCH PPS payment structure
required by statute, we refer readers to the FY 2016 IPPS/LTCH PPS
final rule (80 FR 49601 through 49623).)
Prior to the implementation of the dual payment rate system in FY
2016, all LTCH discharges were paid similarly to those now exempt from
the site neutral payment rate. That legacy payment rate was called the
standard Federal rate. For details on the development of the initial
standard Federal rate for FY 2003, we refer readers to the August 30,
2002 LTCH PPS final rule (67 FR 56027 through 56037). For subsequent
updates to the standard Federal rate (FYs 2003 through 2015)/LTCH PPS
standard Federal payment rate (FY 2016 through present) as implemented
under Sec. 412.523(c)(3), we refer readers to the following final
rules: RY 2004 LTCH PPS final rule (68 FR 34134 through 34140); RY 2005
LTCH PPS final rule (69 FR 25682 through 25684); RY 2006 LTCH PPS final
rule (70 FR 24179 through 24180); RY 2007 LTCH PPS final rule (71 FR
27819 through 27827); RY 2008 LTCH PPS final rule (72 FR 26870 through
27029); RY 2009 LTCH PPS final rule (73 FR 26800 through 26804); FY
2010 IPPS/RY 2010 LTCH PPS final rule (74 FR 44021 through 44030); FY
2011 IPPS/LTCH PPS final rule (75 FR 50443 through 50444); FY 2012
IPPS/LTCH PPS final rule (76 FR 51769 through 51773); FY 2013 IPPS/LTCH
PPS final rule (77 FR 53479 through 53481); FY 2014 IPPS/LTCH PPS final
rule (78 FR 50760 through 50765); FY 2015 IPPS/LTCH PPS final rule (79
FR 50176 through 50180); FY 2016 IPPS/LTCH PPS final rule (80 FR 49634
through 49637); FY 2017 IPPS/LTCH PPS final rule (81 FR 57296 through
57310); the FY 2018 IPPS/LTCH PPS final rule (82 FR 58536 through
58547); and the FY 2019 IPPS/LTCH PPS final rule (83 FR 41530 through
41537).
In this FY 2020 IPPS/LTCH PPS proposed rule, we present our
proposals related to the annual update to the LTCH PPS standard Federal
payment rate for FY 2020.
The proposed update to the LTCH PPS standard Federal payment rate
for FY 2020 is presented in section V.A. of the Addendum to this
proposed rule. The components of the proposed annual update to the LTCH
PPS standard Federal payment rate for FY 2020 are discussed below,
including the statutory reduction to the annual update for LTCHs that
fail to submit quality reporting data for FY 2020 as required by the
statute (as discussed in section VII.D.2.c. of the preamble of this
proposed rule). We also are proposing to make an adjustment to the LTCH
PPS standard Federal payment rate to account for the estimated effect
of the changes to the area wage level for FY 2020 on estimated
aggregate LTCH PPS payments, in accordance with Sec. 412.523(d)(4) (as
discussed in section V.B. of the Addendum to this proposed rule).
In addition, as discussed in the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41532 through 41537), we eliminated the 25-percent threshold
policy in a budget neutral manner. The budget neutrality requirements
are codified in the regulations at Sec. 412.523(d)(6). Under these
regulations, a temporary, one-time factor is applied to the standard
Federal payment rate in FY 2019 and FY 2020, and a permanent, one-time
factor in FY 2021. These factors as established in the FY 2019 IPPS/
LTCH PPS final rule (83 FR 41536) are:
For FY 2019, a temporary, one-time factor of 0.990884;
For FY 2020, a temporary, one-time factor of 0.990741; and
For FY 2021 and subsequent years, a permanent, one-time
factor of 0.991249.
Therefore, in determining the proposed FY 2020 LTCH PPS standard
Federal payment rate, we are proposing to:
(1) Remove the temporary, one-time factor of 0.990884 for the
estimated cost of the elimination of the 25-percent threshold policy in
FY 2019 by applying a factor of (1/0.990884); and
(2) Apply a temporary, one-time factor of 0.990741 for the
estimated cost of the elimination of the 25-percent threshold policy in
FY 2020.
Equivalently, in determining the proposed FY 2020 LTCH PPS standard
Federal payment rate, we are proposing to apply a temporary, one-time
factor of 0.999856 (1/0.990884 x 0.990741) to the FY 2019 LTCH PPS
standard Federal payment rate. The proposed FY 2020 LTCH PPS standard
Federal payment rate shown in Table 1E in section VI. of the Addendum
to this proposed rule reflects this adjustment.
2. Proposed FY 2020 LTCH PPS Standard Federal Payment Rate Annual
Market Basket Update
a. Overview
Historically, the Medicare program has used a market basket to
account for input price increases in the services furnished by
providers. The market basket used for the LTCH PPS includes both
operating and capital related costs of LTCHs because the LTCH PPS uses
a single payment rate for both operating and capital-related costs. We
adopted the 2013-based LTCH market basket for use under the LTCH PPS
beginning in FY 2017 (81 FR 57100 through 57102). For additional
details on the historical development of the market basket used under
the LTCH PPS, we refer readers to the FY 2013 IPPS/LTCH PPS final rule
(77 FR 53467 through 53476), and for a complete discussion of the LTCH
market basket and a description of the methodologies used to determine
the operating and capital-related portions of the 2013-based LTCH
market basket, we refer readers to section VII.D. of the preamble of
the FY 2017 IPPS/LTCH PPS proposed and final rules (81 FR 25153 through
25167 and 81 FR 57086 through 57099, respectively).
Section 3401(c) of the Affordable Care Act provides for certain
adjustments to
[[Page 19472]]
any annual update to the LTCH PPS standard Federal payment rate and
refers to the timeframes associated with such adjustments as a ``rate
year.'' We note that, because the annual update to the LTCH PPS
policies, rates, and factors now occurs on October 1, we adopted the
term ``fiscal year'' (FY) rather than ``rate year'' (RY) under the LTCH
PPS beginning October 1, 2010, to conform with the standard definition
of the Federal fiscal year (October 1 through September 30) used by
other PPSs, such as the IPPS (75 FR 50396 through 50397). Although the
language of sections 3004(a), 3401(c), 10319, and 1105(b) of the
Affordable Care Act refers to years 2010 and thereafter under the LTCH
PPS as ``rate year,'' consistent with our change in the terminology
used under the LTCH PPS from ``rate year'' to ``fiscal year,'' for
purposes of clarity, when discussing the annual update for the LTCH PPS
standard Federal payment rate, including the provisions of the
Affordable Care Act, we use ``fiscal year'' rather than ``rate year''
for 2011 and subsequent years.
b. Proposed Annual Update to the LTCH PPS Standard Federal Payment Rate
for FY 2020
CMS has used an estimated market basket increase to update the LTCH
PPS. As noted above, we adopted the 2013-based LTCH market basket for
use under the LTCH PPS beginning in FY 2017. The 2013-based LTCH market
basket is based solely on the Medicare cost report data submitted by
LTCHs and, therefore, specifically reflects the cost structures of only
LTCHs. (For additional details on the development of the 2013-based
LTCH market basket, we refer readers to the FY 2017 IPPS/LTCH PPS final
rule (81 FR 57085 through 57099).) We continue to believe that the
2013-based LTCH market basket appropriately reflects the cost structure
of LTCHs for the reasons discussed when we adopted its use in the FY
2017 IPPS/LTCH PPS final rule (81 FR 57100). Therefore, in this
proposed rule, we are proposing to use the 2013-based LTCH market
basket to update the LTCH PPS standard Federal payment rate for FY
2020.
Section 1886(m)(3)(A) of the Act provides that, beginning in FY
2010, any annual update to the LTCH PPS standard Federal payment rate
is reduced by the adjustments specified in clauses (i) and (ii) of
subparagraph (A). Clause (i) of section 1886(m)(3)(A) of the Act
provides for a reduction, for FY 2012 and each subsequent rate year, by
the productivity adjustment described in section 1886(b)(3)(B)(xi)(II)
of the Act (that is, ``the multifactor productivity (MFP)
adjustment''). Clause (ii) of section 1886(m)(3)(A) of the Act provided
for a reduction, for each of FYs 2010 through 2019, by the ``other
adjustment'' described in section 1886(m)(4)(F) of the Act; therefore,
it is not applicable for FY 2020.
Section 1886(m)(3)(B) of the Act provides that the application of
paragraph (3) of section 1886(m) of the Act may result in the annual
update being less than zero for a rate year, and may result in payment
rates for a rate year being less than such payment rates for the
preceding rate year.
c. Proposed Adjustment to the LTCH PPS Standard Federal Payment Rate
Under the Long-Term Care Hospital Quality Reporting Program (LTCH QRP)
In accordance with section 1886(m)(5) of the Act, the Secretary
established the Long-Term Care Hospital Quality Reporting Program (LTCH
QRP). The reduction in the annual update to the LTCH PPS standard
Federal payment rate for failure to report quality data under the LTCH
QRP for FY 2014 and subsequent fiscal years is codified under 42 CFR
412.523(c)(4). The LTCH QRP, as required for FY 2014 and subsequent
fiscal years by section 1886(m)(5)(A)(i) of the Act, applies a 2.0
percentage point reduction to any update under Sec. 412.523(c)(3) for
an LTCH that does not submit quality reporting data to the Secretary in
accordance with section 1886(m)(5)(C) of the Act with respect to such a
year (that is, in the form and manner and at the time specified by the
Secretary under the LTCH QRP) (Sec. 412.523(c)(4)(i)). Section
1886(m)(5)(A)(ii) of the Act provides that the application of the 2.0
percentage points reduction may result in an annual update that is less
than 0.0 for a year, and may result in LTCH PPS payment rates for a
year being less than such LTCH PPS payment rates for the preceding
year. Furthermore, section 1886(m)(5)(B) of the Act specifies that the
2.0 percentage points reduction is applied in a noncumulative manner,
such that any reduction made under section 1886(m)(5)(A) of the Act
shall apply only with respect to the year involved, and shall not be
taken into account in computing the LTCH PPS payment amount for a
subsequent year. These requirements are codified in the regulations at
Sec. 412.523(c)(4). (For additional information on the history of the
LTCH QRP, including the statutory authority and the selected measures,
we refer readers to section VIII.C. of the preamble of this proposed
rule.)
d. Proposed Annual Market Basket Update Under the LTCH PPS for FY 2020
Consistent with our historical practice and our proposal, we
estimate the market basket increase and the MFP adjustment based on
IGI's forecast using the most recent available data. Based on IGI's
fourth quarter 2018 forecast, the FY 2020 full market basket estimate
for the LTCH PPS using the 2013-based LTCH market basket is 3.2
percent. The current estimate of the MFP adjustment for FY 2020 based
on IGI's fourth quarter 2018 forecast is 0.5 percent.
For FY 2020, section 1886(m)(3)(A)(i) of the Act requires that any
annual update to the LTCH PPS standard Federal payment rate be reduced
by the productivity adjustment (``the MFP adjustment'') described in
section 1886(b)(3)(B)(xi)(II) of the Act. Consistent with the statute,
we are proposing to reduce the full estimated FY 2020 market basket
increase by the proposed FY 2020 MFP adjustment. To determine the
proposed market basket increase for LTCHs for FY 2020, as reduced by
the proposed MFP adjustment, consistent with our established
methodology, we are subtracting the proposed FY 2020 MFP adjustment
from the estimated FY 2020 market basket increase. (We note that
sections 1886(m)(3)(A)(ii) and 1886(m)(4)(F) of the Act required an
additional reduction each year only for FYs 2010 through 2019.) (For
additional details on our established methodology for adjusting the
market basket increase by the MFP adjustment, we refer readers to the
FY 2012 IPPS/LTCH PPS final rule (76 FR 51771).)
For FY 2020, section 1886(m)(5) of the Act requires that, for LTCHs
that do not submit quality reporting data as required under the LTCH
QRP, any annual update to an LTCH PPS standard Federal payment rate,
after application of the adjustments required by section 1886(m)(3) of
the Act, shall be further reduced by 2.0 percentage points. Therefore,
for LTCHs that fail to submit quality reporting data under the LTCH
QRP, the proposed 3.2 percent update to the LTCH PPS standard Federal
payment rate for FY 2020 will be reduced by the proposed 0.5 percentage
point MFP adjustment as required under section 1886(m)(3)(A)(i) of the
Act and the additional 2.0 percentage points reduction required by
section 1886(m)(5) of the Act.
In this FY 2020 IPPS/LTCH PPS proposed rule, in accordance with the
statute, we are proposing to reduce the proposed FY 2020 full market
basket estimate of 3.2 percent (based on IGI's
[[Page 19473]]
fourth quarter 2018 forecast of the 2013-based LTCH market basket) by
the proposed FY 2020 MFP adjustment of 0.5 percentage point (based on
IGI's fourth quarter 2018 forecast). Therefore, under the authority of
section 123 of the BBRA as amended by section 307(b) of the BIPA, we
are proposing to establish an annual market basket update to the LTCH
PPS standard Federal payment rate for FY 2020 of 2.7 percent (that is,
the most recent estimate of the proposed LTCH PPS market basket
increase of 3.2 percent, less the proposed MFP adjustment of 0.5
percentage point). Accordingly, we are proposing to revise Sec.
412.523(c)(3) by adding a new paragraph (xvi), which would specify that
the LTCH PPS standard Federal payment rate for FY 2020 is the LTCH PPS
standard Federal payment rate for the previous LTCH PPS payment year
updated by 2.7 percent, and as further adjusted, as appropriate, as
described in Sec. 412.523(d) (including the application of the
proposed adjustment factor for the cost of the elimination of the 25-
percent threshold policy under Sec. 412.523(d)(6) discussed above).
For LTCHs that fail to submit quality reporting data under the LTCH
QRP, under proposed Sec. 412.523(c)(3)(xvi) in conjunction with Sec.
412.523(c)(4), we are proposing to further reduce the proposed annual
update to the LTCH PPS standard Federal payment rate by 2.0 percentage
points, in accordance with section 1886(m)(5) of the Act. Accordingly,
we are proposing to establish an annual update to the LTCH PPS standard
Federal payment rate of 0.7 percent (that is, 2.7 percent minus 2.0
percentage points) for FY 2020 for LTCHs that fail to submit quality
reporting data as required under the LTCH QRP. Consistent with our
historical practice, we are proposing to use a more recent estimate of
the market basket and the MFP adjustment in the final rule to establish
an annual update to the LTCH PPS standard Federal payment rate for FY
2020 under proposed Sec. 412.523(c)(3)(xvi). (We note that, consistent
with historical practice, we also are proposing to adjust the proposed
FY 2020 LTCH PPS standard Federal payment rate by an area wage level
budget neutrality factor in accordance with Sec. 412.523(d)(4) (as
discussed in section V.B.5. of the Addendum to this proposed rule).)
VIII. Quality Data Reporting Requirements for Specific Providers and
Suppliers
In section VIII. of the preamble of this proposed rule, we are
proposing changes to the following Medicare quality reporting systems:
In section VIII.A., the Hospital IQR Program;
In section VIII.B., the PCHQR Program; and
In section VIII.C., the LTCH QRP.
In addition, in section VIII.D. of the preamble of this proposed
rule, we are proposing changes to the Medicare and Medicaid Promoting
Interoperability Programs (previously known as the Medicare and
Medicaid EHR Incentive Programs) for eligible hospitals and critical
access hospitals (CAHs).
A. Hospital Inpatient Quality Reporting (IQR) Program
1. Background
a. History of the Hospital IQR Program
The Hospital IQR Program strives to put patients first by ensuring
they are empowered to make decisions about their own healthcare along
with their clinicians using information from data-driven insights that
are increasingly aligned with meaningful quality measures. We support
technology that reduces burden and allows clinicians to focus on
providing high quality health care for their patients. We also support
innovative approaches to improve quality, accessibility, and
affordability of care, while paying particular attention to improving
clinicians' and beneficiaries' experiences when interacting with CMS
programs. In combination with other efforts across the Department of
Health and Human Services, we believe the Hospital IQR Program
incentivizes hospitals to improve health care quality and value, while
giving patients the tools and information needed to make the best
decisions for them.
We seek to promote higher quality and more efficient health care
for Medicare beneficiaries. This effort is supported by the adoption of
widely-agreed upon quality and cost measures. We have worked with
relevant stakeholders to define measures in almost every care setting
and currently measure some aspect of care for almost all Medicare
beneficiaries. These measures assess clinical processes, patient safety
and adverse events, patient experiences with care, care coordination,
and clinical outcomes, as well as cost of care. We have implemented
quality measure reporting programs for multiple settings of care. To
measure the quality of hospital inpatient services, we implemented the
Hospital IQR Program, previously referred to as the Reporting Hospital
Quality Data for Annual Payment Update (RHQDAPU) Program. We refer
readers to the FY 2010 IPPS/LTCH PPS final rule (74 FR 43860 through
43861) and the FY 2011 IPPS/LTCH PPS final rule (75 FR 50180 through
50181) for detailed discussions of the history of the Hospital IQR
Program, including the statutory history, and to the FY 2015 IPPS/LTCH
PPS final rule (79 FR 50217 through 50249), the FY 2016 IPPS/LTCH PPS
final rule (80 FR 49660 through 49692), the FY 2017 IPPS/LTCH PPS final
rule (81 FR 57148 through 57150), the FY 2018 IPPS/LTCH PPS final rule
(82 FR 38326 through 38328 and 82 FR 38348), and the FY 2019 IPPS/LTCH
PPS final rule (83 FR 41538 through 41609) for the measures we have
previously adopted for the Hospital IQR Program measure set for the FY
2022 payment determination and subsequent years.
b. Maintenance of Technical Specifications for Quality Measures
We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR
41538) in which we summarized how the Hospital IQR Program maintains
the technical measure specifications for quality measures and the
subregulatory process for incorporation of nonsubstantive updates to
the measure specifications to ensure that measures remain up-to-date.
We are not proposing any changes to these policies in this proposed
rule.
c. Public Display of Quality Measures
We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR
41538 through 41539) in which we stated the Hospital IQR Program's
policy for public display of quality measures. We are not proposing any
changes to these policies in this proposed rule.
2. Retention of Previously Adopted Hospital IQR Program Measures for
Subsequent Payment Determinations
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53512 through 53513) for our finalized measure retention policy.
Pursuant to this policy, when we adopt measures for the Hospital IQR
Program beginning with a particular payment determination, we
automatically readopt these measures for all subsequent payment
determinations unless we propose to remove, suspend, or replace the
measures. We are not proposing any changes to this policy in this
proposed rule.
3. Removal Factors for Hospital IQR Program Measures
We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR
41540 through 41544) for a summary of the Hospital IQR Program's
removal factors. We are not proposing any changes to
[[Page 19474]]
our policies regarding measure removal in this proposed rule.
4. Considerations in Expanding and Updating Quality Measures
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53510 through 53512) for a discussion of the previous considerations we
have used to expand and update quality measures under the Hospital IQR
Program. We also refer readers to the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41147 through 41148), in which we describe the Meaningful
Measures Initiative,\409\ our objectives under this new framework for
quality measurement, and the quality topics that we have identified as
high impact measurement areas that are relevant and meaningful to both
patients and providers. Furthermore, in selecting measures for the
Hospital IQR Program, we are mindful that measures adopted for the
Hospital VBP Program must first have been adopted under the Hospital
IQR Program and publicly reported on the Hospital Compare website for
at least 1 year. We view the value-based purchasing programs, including
the Hospital VBP Program, as the next step in promoting higher quality
care for Medicare beneficiaries by transforming Medicare from a passive
payer of claims into an active purchaser of quality health care for its
beneficiaries. We are not proposing any changes to these policies in
this proposed rule.
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\409\ Meaningful Measures web page: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.html.
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5. Proposed New Measures for the Hospital IQR Program Measure Set
In this proposed rule, we are proposing to: (1) Adopt two new
quality measures beginning with the FY 2023 payment determination; and
(2) expand the voluntary reporting status of the Hybrid Hospital-Wide
Readmission Measure with Claims and Electronic Health Record Data
(Hybrid HWR measure), and then require mandatory reporting of this
measure beginning with the FY 2026 payment determination, as discussed
in detail below.
a. Proposed Adoption of Two Opioid-Related eCQMs
In this proposed rule, we are proposing to add the following two
opioid-related electronic clinical quality measures (eCQMs) to the
Hospital IQR Program eCQM measure set, beginning with the CY 2021
reporting period/FY 2023 payment determination: (1) Safe Use of
Opioids--Concurrent Prescribing eCQM (NQF #3316e); and (2) Hospital
Harm--Opioid-Related Adverse Events eCQM.
We believe these opioid-related measures are valuable patient
safety measures and are responsive to stakeholder feedback expressing
support for eCQMs that focus on higher priority measurement areas and
patient outcomes. While both measures are designed to reduce adverse
events or harms associated with opioid use, the main focus of each
measure's intent is different.
The Safe Use of Opioids--Concurrent Prescribing eCQM focuses on
concurrent prescriptions of opioids and benzodiazepines at discharge,
an area of high-risk prescribing. Implementation of the measure has the
potential to reduce preventable mortality and costs of adverse events
associated with prescription opioid use and could contribute to efforts
to combat the current opioid epidemic, which is a high-priority focus
area for measurement.
The Hospital Harm--Opioid-Related Adverse Events eCQM is designed
to reduce adverse events associated with the administration of opioids
in the hospital setting by assessing the administration of naloxone as
an indicator of harm. Implementation of the measure can lead to safer
patient care by incentivizing hospitals to track and improve their
monitoring of patients who receive opioids during hospitalization.
Adopting these two opioid-related eCQMs would further diversify the
eCQM measure set by addressing two additional Meaningful Measures
quality priorities that are not currently addressed by the eCQM measure
set: ``Promoting Effective Prevention and Treatment of Chronic
Disease'' and ``Making Care Safer by Reducing Harm Caused in the
Delivery of Care'' through the Meaningful Measures Areas of
``Prevention and Treatment of Opioid and Substance Use Disorders'' and
``Preventable Healthcare Harm,'' respectively.
Additional details on each of the opioid-related eCQMs are
presented below. We also refer readers to two related proposals in this
proposed rule: (1) Section VIII.A.10.d.(1) through (4) of the preamble
of this proposed rule for a discussion of proposed reporting and
submission requirements for eCQMs through the CY 2022 reporting period/
FY 2024 payment determination, including our proposal to require
hospitals to report on the Safe Use of Opioids--Concurrent Prescribing
eCQM as one of the four required eCQMs effective beginning with the CY
2022 reporting period/FY 2024 payment determination; and (2) section
VIII.D.6.a. and b. of the preamble of this proposed rule for similar
proposals to adopt these two opioid-related eCQMs in the Medicare and
Medicaid Promoting Interoperability Programs (previously known as the
Medicare and Medicaid EHR Incentive Programs).
(1) Safe Use of Opioids--Concurrent Prescribing eCQM (NQF #3316e)
(a) Background
Fatalities from unintentional opioid overdose have become an
epidemic in the last 20 years, representing a major public health
concern in the United States.\410\ According to the Centers for Disease
Control and Prevention (CDC), opioid overdose resulted in more than
42,000 deaths in 2016, and 40 percent of those deaths involved
prescription opioids.\411\ In addition, a recent retrospective study of
claims data found that concurrent benzodiazepine and opioid use
increased by 80 percent between 2001 and 2013 in a large sample of
privately insured patients, and significantly contributed to the
overall population risk of opioid overdose in the United States.\412\
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\410\ Rudd, R., Aleshire, N., Zibbell, J. & Gladden, R.M.
(2016). Increases in Drug and Opioid Overdose Deaths--United States,
2000-2014. Morbidity and Mortality Weekly Report, 64(50): 1378-82.
Available at: http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6450a3.htm.
\411\ Centers for Disease Control and Prevention. Drug Overdose
Epidemic: Behind the Numbers. Available at: https://www.cdc.gov/drugoverdose/data/index.html.
\412\ Sun, E., Dixit, A., Humphreys, K., Darnall, B., Baker, L.
& Mackey, S. (2017). Association Between Concurrent Use of
Prescription Opioids and Benzodiazepines and Overdose: Retrospective
Analysis. BMJ, 356: j760.
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Concurrent prescriptions of opioids or opioids and benzodiazepines
place patients at a greater risk of unintentional overdose due to the
increased risk of respiratory depression.\413\ According to the
National Institute on Drug Abuse, concurrent use of benzodiazepines
with opioids was present in more than 30 percent of fatal overdoses,
but many people continue to be prescribed both drugs
simultaneously.414 415 Rates of fatal overdose are 10 times
higher in
[[Page 19475]]
patients who are co-dispensed opioid analgesics and benzodiazepines
versus opioids alone.\416\ Studies of multiple claims and prescription
databases show that 5 to 15 percent of patients receive concurrent
opioid prescriptions, and 5 to 20 percent of patients receive
concurrent opioid and benzodiazepine prescriptions across various
settings.417 418 419 On average, the number of opioid
overdose deaths involving benzodiazepines increased 14 percent each
year from 2006 to 2011, whereas the number of opioid analgesic overdose
deaths not involving benzodiazepines did not change significantly.\420\
One study showed that reducing concurrent use of opioids and
benzodiazepines could reduce the risk of opioid overdose-related
emergency department (ED) and inpatient visits by 15 percent, and could
have prevented an estimated 2,630 deaths related to opioid painkiller
overdoses in 2015.\421\ In the FY 2018 IPPS/LTCH PPS rulemaking (82 FR
20059 through 20060; 82 FR 38377 through 38378), we sought public
comment on the potential future adoption of this measure.
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\413\ Dowell, D., Haegerich, T. & Chou, R. (2016). CDC Guideline
for Prescribing Opioids for Chronic Pain--United States, 2016.
Morbidity and Mortality Weekly Report: Recommendations and Reports,
65. Available at: http://www.cdc.gov/media/dpk/2016/dpk-opioid-prescription-guidelines.html.
\414\ National Institute on Drug Abuse. Benzodiazepines and
Opioids. Available at: https://www.drugabuse.gov/drugs-abuse/opioids/benzodiazepines-opioids.
\415\ Sun, E., Dixit, A., Humphreys, K., Darnall, B., Baker, L.
& Mackey, S. (2017). Association Between Concurrent Use of
Prescription Opioids and Benzodiazepines and Overdose: Retrospective
Analysis. BMJ, 356: j760.
\416\ Dasgupta, N., Jonsson Funk, M., Proescholdbell, S.,
Hirsch, A., Ribisl, K.M. & Marshall, S. (2015). Cohort Study of the
Impact of High-Dose Opioid Analgesics on Overdose Mortality. Pain
Medicine. Available at: http://onlinelibrary.wiley.com/doi/10.1111/pme.12907/abstract.
\417\ Liu, Y., Logan, J., Paulozzi, L., Zhang, K., Jones, C.
(2013). Potential Misuse and Inappropriate Prescription Practices
Involving Opioid Analgesics. American Journal of Managed Care,
19(8): 648-65.
\418\ Mack, K., Zhang, K., Paulozzi, L. & Jones, C. (2015).
Prescription Practices Involving Opioid Analgesics Among Americans
with Medicaid, 2010. Journal of Health Care for the Poor and
Underserved, 26(1): 182-98.
\419\ Park, T., Saitz, R., Ganoczy, D., Ilgen, M.A. & Bohnert,
A.S.B. (2015). Benzodiazepine Prescribing Patterns and Deaths from
Drug Overdose Among U.S. Veterans Receiving Opioid Analgesics: Case-
Cohort Study. BMJ, 350: h2698.
\420\ Jones, C.M. & McAninch, J.K. (2015). Emergency Department
Visits and Overdose Deaths from Combined Use of Opioids and
Benzodiazepines. American Journal of Preventive Medicine, 49(4):
493-501.
\421\ Sun, E., Dixit, A., Humphreys, K., Darnall, B., Baker, L.
& Mackey, S. (2017). Association Between Concurrent Use of
Prescription Opioids and Benzodiazepines and Overdose: Retrospective
Analysis. BMJ, 356: j760.
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(b) Overview of Measure
We believe that a measure that calculates the proportion of
patients who were concurrently prescribed two or more opioids or
opioids and benzodiazepines has the potential to reduce preventable
mortality and the costs of adverse events associated with opioid use.
Therefore, we are proposing to adopt the Safe Use of Opioids--
Concurrent Prescribing eCQM (NQF #3316e) beginning with the CY 2021
reporting period/FY 2023 payment determination. The Safe Use of
Opioids--Concurrent Prescribing eCQM seeks to reduce preventable
mortality and the costs of adverse events associated with opioid use by
encouraging providers to identify patients who have concurrent
prescriptions for opioids or opioids and benzodiazepines, and
discouraging providers from prescribing these drugs concurrently
whenever possible. The goal of the measure is to provide a patient-
centric measure to help systems identify and monitor patients at risk,
and ultimately to reduce the risk of harm to patients across the
continuum of care. This measure also seeks to combat the opioid crisis,
which has been declared a public health emergency,\422\ and is
recognized as a priority focus area for measurement by CMS and HHS.
Specifically, by collecting and reporting concurrent prescribing rates
with minimal lag time, this measure advances one of the key strategies
prioritized by HHS in its five-point Opioid Strategy, which is to
improve our understanding of the crisis through more timely, specific
public health data collection and reporting.\423\ In addition, under
CMS' Meaningful Measures framework, the Safe Use of Opioids--Concurrent
Prescribing eCQM addresses the quality priority of ``Promoting
Effective Prevention and Treatment of Chronic Disease'' through the
Meaningful Measures Area of ``Prevention and Treatment of Opioid and
Substance Use Disorders.'' \424\
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\422\ Office of the Assistant Secretary for Preparedness and
Response (ASPR). Public Health Emergency Declarations. Available at:
https://www.phe.gov/emergency/news/healthactions/phe/pages/default.aspx.
\423\ In April 2017, HHS identified the opioid crisis as a top
priority and prioritized five specific strategies to combat the
epidemic, including ``Better Data'' on the epidemic to improve our
understanding of the crisis. HHS aims to strengthen public health
data collection and reporting to improve the timeliness and
specificity of data and to inform a real-time public health response
as the epidemic evolves. In its Strategy to Combat Opioid Abuse,
Misuse, and Overdose, HHS sets forth a number of activities that can
be taken by the Secretary and HHS agencies to advance its ``Better
Data'' strategy, including the collection of data on opioid
prescriptions, new drug patterns, and related harms, with minimal
lag time. More information on HHS' Opioid Strategy is available at:
https://www.hhs.gov/opioids/about-the-epidemic/hhs-response/index.html.
\424\ The Safe Use of Opioids--Concurrent Prescribing measure
also addresses the quality priority of ``Promoting Effective
Communication and Coordination of Care'' through the Meaningful
Measure area of ``Medication Management.'' More information on CMS'
Meaningful Measures Initiative is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.html.
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The measure's concept is based on the 2016 CDC Guideline for
Prescribing Opioids for Chronic Pain, which recommends that clinicians
should avoid prescribing opioids and benzodiazepines concurrently
whenever possible.\425\ It is also in line with many state-issued and
professional society guidelines on concurrent prescribing, which
recommend that providers should avoid prescribing multiple opioids and
opioids and benzodiazepines concurrently because it puts patients at
high risk for respiratory depression, overdose, and death.\426\
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\425\ Dowell, D., Haegerich, T. & Chou, R. (2016). CDC Guideline
for Prescribing Opioids for Chronic Pain--United States, 2016.
Morbidity and Mortality Weekly Report: Recommendations and Reports,
65. Available at: https://www.cdc.gov/mmwr/volumes/65/rr/rr6501e1.htm.
\426\ See, for example, American Academy of Emergency Medicine,
Emergency Department Opioid Prescribing Guidelines for the Treatment
of Non-Cancer Related Pain (available at: https://www.deepdyve.com/lp/elsevier/american-academy-of-emergency-medicine-PlQtPNi8J4)
(recommending that clinicians should avoid prescribing opioid
analgesics to patients currently taking sedative hypnotic
medications or concurrent opioid analgesics); Washington State
Agency Medical Directors' Group, Interagency Guideline on
Prescribing Opioids for Pain (available at: http://agencymeddirectors.wa.gov/Files/2015AMDGOpioidGuideline.pdf)
(recommending that clinicians should avoid combining opioids with
benzodiazepines, sedative-hypnotics or barbiturates when prescribing
opioid for chronic noncancer pain).
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In addition, stakeholders involved during development, including
the project TEP and public commenters, stated that the measure was
useful not only because it could promote adherence to recommended
clinical guidelines, but also because capturing data on hospital-level
prescribing practices could assist in identifying strategies to address
the issue of concurrent prescriptions of opioids and benzodiazepines.
Stakeholders also stated that the measure could reduce opioid-related
mortality resulting from concurrent opioid prescriptions or opioid-
benzodiazepine prescriptions, with minimal implementation costs.\427\
Measure testing demonstrated that almost all of the data elements
required to calculate and report the measure are collected as part of
required clinical workflow protocols in structured fields within the
EHR. The NQF Patient Safety Standing Committee did not raise any
concerns on the feasibility of the measure during endorsement review.
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\427\ Gao, A., Bandyopadhyay, J., Barrett, K., Morales, N. & Tu,
D. (2017). Beta Testing Report on the Safe Use of Opioids--
Concurrent Prescribing Electronic Clinical Quality Measure. Hospital
Inpatient and Outpatient Process and Structural Measure Development
and Maintenance Project (HHSM-500-2013-13011I, Task Order HHSM-500-
T0003).
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[[Page 19476]]
The Safe Use of Opioids--Concurrent Prescribing measure (MUC16-167)
was included in the publicly available ``List of Measures Under
Consideration for December 1, 2016.'' \428\ The measure was reviewed by
the NQF MAP in December 2016 and January 2017, which recommended that
the measure be refined and resubmitted prior to rulemaking due to the
importance of the opioid epidemic.\429\ The MAP noted that there are
instances where concurrent prescribing may be clinically appropriate,
and that the measure could potentially cause unintentional consequences
associated with withdrawal of medications. For more information on the
concerns and considerations raised by the MAP related to this measure,
we refer readers to the January 2017 NQF MAP Coordinating Committee
Meeting Transcript.\430\ In response to the MAP's recommendation, and
as suggested by the project's TEP and expert work group, we explored
single-condition exclusions, specifically for patients with sickle cell
disease and those undergoing substance use therapy, and found that
these instances comprised a very small portion of eligible cases
captured by the numerator during testing.
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\428\ List of Measures Under Consideration for December 1, 2016.
Available at: http://www.qualityforum.org/ProjectMaterials.aspx?
projectID=75367.
\429\ 2016-2017 Spreadsheet of Final Recommendations to HHS and
CMS. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75367.
\430\ Measure Applications Partnership, January 2017 NQF MAP
Coordinating Committee Meeting Transcript. Available at: http://www.quality forum.org/ProjectMaterials.aspx?projectID=75367.
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After reviewing these testing results, expert opinions from
clinicians recommended continuing to include patients for whom
concurrent prescribing may be clinically necessary because experts
stated that these populations are at highest risk of adverse drug
events due to concurrent prescriptions and should continue to be
monitored by clinicians throughout the continuum of care. In addition,
there are currently no guidelines supporting exclusion of patients who
may require concurrent prescriptions from the measure, other than
cancer and palliative care; a broader set of evidence-based exclusions
may increase the face validity of the measure, but there are currently
no strong evidence-based indicators to support other exclusions beyond
what is currently included in the measure that would continue to
maintain the strength of the measure's evidence base.
To strengthen the measure's feasibility and usability, the measure
was refined to address other feedback from the MAP such as: (1)
Including only encounters for inpatient, ED, and hospital observation
stays (rather than including encounters spanning inpatient and hospital
outpatient settings); and (2) including only medications prescribed at
discharge (rather than those spanning the duration of the encounter).
An update on the measure was presented to the MAP on November 8,
2018.\431\
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\431\ November 8, 2018 meeting agenda and presentation slides
available at: http://www.qualityforum.org/ProjectMaterials.aspx
?projectID=75369.
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The NQF Patient Safety Standing Committee also recommended
endorsement of the proposed measure in 2018, acknowledging that there
is strong evidence for an association between increased use of multiple
opioids, or opioids and benzodiazepines together, as well as increased
risk of unintentional and fatal overdoses.\432\ The committee agreed
that this measure will likely reduce concurrent prescribing of opioid-
opioid and opioid-benzodiazepine medications at discharge in inpatient
and ED settings.\433\ This measure was endorsed by the NQF in May
2018.\434\
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\432\ National Quality Forum. (2018). Patient Safety Fall 2017
Final Report. Available at: http://www.qualityforum.org/Publications/2018/07/Patient_Safety_Fall_2017_Final_Report.aspx.
\433\ Ibid.
\434\ Ibid.
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Concurrent opioid or opioid-benzodiazepine prescription use
contributes significantly to the overall population's risk of opioid
overdose. Currently, however, no measure exists to assess nationwide
rates of the concurrent prescribing of opioids and benzodiazepines at
the hospital-level.\435\ Adopting the Safe Use of Opioids--Concurrent
Prescribing eCQM would thus enhance the information available to
providers in this area of high-risk prescribing. In addition, we
believe the measure is a valuable patient safety measure that has the
potential to reduce preventable mortality and other adverse events
associated with prescription opioid use, with minimal implementation
costs.
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\435\ The Veterans Health Administration (VHA), as part of its
Opioid Safety Initiative, implemented a measure of concurrent opioid
and benzodiazepine prescribing that is similar to the Safe Use of
Opioids--Concurrent Prescribing measure. The Opioid Safety
Initiative was associated with a decrease in patients receiving
benzodiazepine concurrently with an opioid--specifically, a recent
study showed a 20.67 percent decrease overall and a 0.86 percent
decrease in patients per month (781 patients per month)--among all
adult VHA patients who filled outpatient opioid prescriptions from
October 2012 to September 2014. See Lin, L.A., Bohnert, A.S., Kerns,
R.D., Clay, M.A., Ganoczy, D. & Ilgen, M.A. (2017). Impact of the
Opioid Safety Initiative on Opioid-Related Prescribing in Veterans.
Pain, 158(5): 833-39.
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The measure is intended to facilitate safer patient care not only
by promoting adherence to recommended clinical guidelines on concurrent
prescribing practices, but also by incentivizing hospitals to develop
strategies to identify and monitor patients on concurrent opioids and
opioid-benzodiazepine prescriptions who might be at higher risk of
adverse drug events. For instance, the measure could encourage hospital
prescribers to use data from prescription drug-monitoring programs when
assessing whether to prescribe concurrent substances. The measure could
also encourage more effective communication among providers to
coordinate care across hospital and ambulatory care settings. The
measure could also help establish a national benchmark of opioid
prescribing in hospital inpatient settings.
(c) Data Sources
The proposed measure is an eCQM that uses data collected through
EHRs to determine hospital performance. Between July 2016 and July
2017, the Safe Use of Opioids--Concurrent Prescribing measure was
tested at three health systems (eight hospitals in total) with two
different EHR systems for reliability, validity, and feasibility based
on the endorsement criteria outlined by NQF.\436\ The testing showed
that the measure is feasible, valid, and reliable. The measure is
feasible as 96 percent of the data elements required to calculate the
performance rate are: (1) Collected during routine care; (2)
extractable from structured fields in the electronic health systems of
test sites; and (3) likely to be accurate. The measure is valid as all
data elements needed to calculate the measure had levels of agreement
of 84 to 99 percent between electronically extracted and manually
abstracted data elements. The measure also has a reliability
coefficient of 0.99 across the three health systems' sites with two
different EHR systems. This finding indicates that differences in
hospital performance reflect true differences in quality, rather than
measurement error or noise. For encounters where the patient had at
least one active opioid or benzodiazepine prescription at discharge,
measure testing also showed concurrent prescribing rates of 18.2
percent in the inpatient setting and 6.1 percent in ED settings. This
aligned
[[Page 19477]]
with the rates found in the literature. We note that NQF reviewed these
data as part of their measure endorsement process and endorsed the
measure in 2018.\437\
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\436\ National Quality Forum. What NQF Endorsement Means.
Available at: http://www.qualityforum.org/Measuring_Performance/ABCs/What_NQF_Endorsement_Means.aspx.
\437\ National Quality Forum. (2018). Patient Safety, Fall 2017
Final Report. Available at: http://www.qualityforum.org/Publications/2018/07/Patient_Safety_Fall_2017_Final_Report.aspx.
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(d) Measure Calculation
The Safe Use of Opioids--Concurrent Prescribing eCQM is a process
measure that calculates the proportion of patients age 18 years and
older prescribed two or more opioids or an opioid and benzodiazepine
concurrently at discharge from a hospital-based encounter (inpatient or
emergency department [ED], including observation stays). An improvement
in quality of care is indicated by a decrease in the measure score. We
recognize that there may be some clinically appropriate situations for
concurrent prescriptions of two unique opioids or an opioid and
benzodiazepine. Thus, we do not expect the measure rate to be zero;
rather, the goal of the measure is to help systems identify and monitor
patients at risk, and ultimately, to reduce the risk of harm to
patients across the continuum of care.
The measure's cohort includes all patients aged 18 years and older
who were prescribed a new or continued opioid or a benzodiazepine at
discharge from a hospital-based encounter (inpatient stay less than or
equal to 120 days or ED encounters, including observation stays) that
ended during the measurement period. To reduce hospital burden, the
definition of ``hospital-based encounter'' is aligned with that of
other eCQMs in the Hospital IQR Program.
Patients are included in the numerator if their discharge
medications include two or more active opioids or an active opioid and
benzodiazepine resulting in concurrent therapy at discharge from the
hospital-based encounter.
Patients are included in the denominator if they were discharged
from a hospital-based encounter during the measurement period (which
includes inpatient stays less than or equal to 120 days or ED visits,
including observation stays) and their medications at discharge
included a new or continued Schedule II or III opioid, or a new or
continued Schedule IV benzodiazepine prescription. Patients are
excluded from the denominator if they have an active diagnosis of
cancer or order for palliative care (including comfort measures,
terminal care, dying care, and hospice care) during the encounter.
These exclusions align with the populations excluded from the 2016 CDC
Guideline for Prescribing Opioids for Chronic Pain.
We note risk adjustment is not applicable to the Safe Use of
Opioids--Concurrent Prescribing eCQM because it is a process measure.
The measure addresses any difference in risk levels for patients via
the current denominator exclusions as supported by the available
evidence, that is, the measure excludes patients with cancer or
patients receiving palliative care.
For more information about the Safe Use of Opioids--Concurrent
Prescribing eCQM, we refer readers to the measure specifications.\438\
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\438\ Ibid.
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We also refer readers to section VIII.A.10.d.(1) through (4) of the
preamble of this proposed rule where we discuss our proposed eCQM
reporting and submission requirements through the CY 2022 reporting
period/FY 2024 payment determination, including proposing that all
participating hospitals report the Safe Use of Opioids--Concurrent
Prescribing eCQM (NQF #3316e) as one of the four required eCQMs
beginning with the CY 2022 reporting period/FY 2024 payment
determination. In addition, we refer readers to section VIII.D.6.a. and
b. of the preamble of this proposed rule for a similar proposal to
adopt the Safe Use of Opioids--Concurrent Prescribing eCQM (NQF #3316e)
for the Promoting Interoperability Program beginning with the reporting
period in CY 2021.
(2) Hospital Harm--Opioid-Related Adverse Events eCQM
(a) Background
Opioids are among the most frequently implicated medications in
adverse drug events among hospitalized patients. The most serious
opioid-related adverse events include those with respiratory
depression, which can lead to brain damage and death. Opioid-related
adverse events have both negative impact on patients and financial
implications. Patients who experience adverse events due to opioid
administration have been noted to have 55 percent longer lengths of
stay, 47 percent higher costs, 36 percent higher risk of 30-day
readmission, and 3.4 times higher payments than patients without these
adverse events.\439\ While noting that data are limited, The Joint
Commission suggested that opioid-induced respiratory arrest may
contribute substantially to the 350,000 to 750,000 in-hospital cardiac
arrests annually.\440\
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\439\ Kessler, E.R., Shah, M., Gruschkkus, S.K., et al. (2013).
Cost and quality implications of opioid-based postsurgical pain
control using administrative claims data from a large health system:
opioid-related adverse events and their impact on clinical and
economic outcomes. Pharmacotherapy, 33(4): 383-91.
\440\ Overdyk, F.J. (2009). Postoperative Respiratory Depression
and Opioids. Initiatives in Safe Patient Care.
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Most opioid-related adverse events are preventable. Of the opioid-
related adverse drug events reported to The Joint Commission's Sentinel
Event database, 47 percent were due to a wrong medication dose, 29
percent due to improper monitoring, and 11 percent due to other causes
(for example, medication interactions and/or drug reactions).\441\ In
addition, in a review of cases from a malpractice claims database in
which there was opioid-induced respiratory depression among post-
operative surgical patients, 97 percent of these adverse events were
judged preventable with better monitoring and response.\442\ While
hospital quality interventions such as proper dosing, adequate
monitoring, and attention to potential drug interactions that can lead
to overdose are key to prevention of opioid-related adverse events, the
use of these practices can vary substantially across hospitals.
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\441\ The Joint Commission. (2012.) Safe Use of Opioids in
Hospitals. The Joint Commission Sentinel Event Alert, 49:1-5.
\442\ Lee, L.A., Caplan, R.A., Stephens, L.S., et al. (2015).
Postoperative opioid-induced respiratory depression: a closed claims
analysis. Anesthesiology, 122(3): 659-65.
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Administration of opioids also varies widely by hospital, ranging
from 5 percent in the lowest-use hospital to 72 percent in the highest-
use hospital.\443\ Notably, hospitals that use opioids most frequently
have increased adjusted risk of severe opioid-related adverse
events.\444\ We have developed the Hospital Harm--Opioid-Related
Adverse Events eCQM to assess the rates of adverse events as well as
the variation in rates among hospitals. In the FY 2019 IPPS/LTCH PPS
rulemaking (83 FR 20493 through 20494; 83 FR 41588 through 41592), we
solicited public comment on the potential future adoption of this
measure.
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\443\ Herzig, S.J., Rothberg, M.B., Cheung, M., et al. (2014).
Opioid utilization and opioid-related adverse events in nonsurgical
patients in US hospitals. Journal of Hospital Medicine, 9(2): 73-81.
\444\ Ibid.
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(b) Overview of Measure
The Hospital Harm--Opioid-Related Adverse Events eCQM is an outcome
measure focusing specifically on opioid-related adverse events during
an
[[Page 19478]]
admission to an acute care hospital by assessing the administration of
naloxone. Naloxone is a lifesaving emergent therapy with clear and
unambiguous applications in the setting of opioid
overdose.445 446 447 448 Naloxone administration has also
been used in a number of studies as an indicator of opioid-related
adverse events to indicate a harm to a patient during inpatient
admission to a hospital.449 450 The intent of this measure
is for hospitals to track and improve their monitoring and response to
patients administered opioids during hospitalization, and to avoid
harm, such as respiratory depression, which can lead to brain damage
and death. This measure focuses specifically on in-hospital opioid-
related adverse events, rather than opioid overdose events that happen
in the community and may bring a patient into the emergency department.
---------------------------------------------------------------------------
\445\ Surgeon General's Advisory on Naloxone and Opioid
Overdose. Available at: https://www.surgeongeneral.gov/priorities/opioid-overdose-prevention/naloxone-advisory.html.
\446\ Agency for Healthcare Research and Quality (AHRQ). (2017).
Management of Suspected Opioid Overdose with Naloxone by Emergency
Medical Services Personnel. Comparative Effectiveness Review No.
193. Available at: https://effectivehealthcare.ahrq.gov/topics/emt-naloxon/systematic-review.
\447\ Substance Abuse and Mental Health Services Administration
(SAMHSA). (2018). Opioid Overdose Prevention Toolkit: Information
for Prescribers. Available at: https://store.samhsa.gov/system/files/information-for-prescribers.pdf.
\448\ Harm Reduction Coalition. (2012). Guide To Developing and
Managing Overdose Prevention and Take-Home Naloxone Projects.
Available at: https://harmreduction.org/issues/overdose-prevention/tools-best-practices/manuals-best-practice/od-manual/.
\449\ Eckstrand, J.A., Habib, A.S., Williamson, A., et al.
(2009). Computerized surveillance of opioid-related adverse drug
events in perioperative care: A cross-sectional study. Patient
Safety Surgery, 3:18.
\450\ Nwulu, U., Nirantharakumar, K., Odesanya, R., et al.
(2013). Improvement in the detections of adverse drug events by the
use of electronic health and prescription records: An evaluation of
two trigger tools. European Journal of Clinical Pharmacology, 69(2):
255-59.
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As we state below, this measure would be added to the eCQM measure
set from which hospitals could choose to report. For hospitals that
select this measure, the measure would provide them with measurement of
opioid-related adverse event rates and incentivize improved clinical
workflows and monitoring when administering opioids.
The goal of this measure is to incentivize hospitals to closely
monitor patients who receive opioids during their hospitalization to
prevent respiratory depression. The measure requires evidence of
hospital opioid administration prior to the naloxone administration
during the first 24 hours after hospital arrival to ensure that the
harm was hospital acquired and not due to an overdose that happened
outside of the hospital. In addition, the aim of this measure is not to
identify preventability of an individual harm instance or whether each
instance of harm was an error, but rather to assess the overall rate of
harm within a hospital by incorporating a definition of harm that is
likely to be reduced as a result of hospital best practice.
The Hospital Harm--Opioid-Related Adverse Events measure (MUC17-
210) was included in the publicly available ``List of Measures Under
Consideration for December 1, 2017.'' \451\ The measure was reviewed by
the NQF MAP Hospital Workgroup in December 2017, and received the
recommendation to refine and resubmit prior to rulemaking, as
referenced in the ``2017-2018 Spreadsheet of Final Recommendations to
HHS and CMS.'' \452\ The MAP acknowledged the significant health risks
associated with opioid-related adverse events but recommended adjusting
the numerator to consider the impact on chronic opioid users.\453\
Patients on chronic opioids remain at risk of preventable over- or mis-
administration of opioids in the hospital and ideally would remain in
the measure cohort. This decision was supported by the TEP during
measure development. In addition, although chronic opioid users may
require higher doses of opioids to achieve adequate pain control,
providers have the ability to apply appropriate monitoring to prevent
severe adverse events requiring naloxone administration.
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\451\ List of Measures Under Consideration for December 1, 2017.
Available at: http://www.qualityforum.org/ProjectMaterials.aspx
?projectID=75369.
\452\ 2017-2018 Spreadsheet of Final Recommendations to HHS and
CMS. Available at: http://www.qualityforum.org/ProjectMaterials.aspx
?projectID=75369.
\453\ National Quality Forum, Measure Applications Partnership,
MAP 2018 Considerations for Implementing Measures in Federal
Programs: Hospitals. Available at: http://www.qualityforum.org/Publications/2018/02/MAP_2018_Considerations_for_Implementing_Measures_Final_Report_-_Hospitals.aspx.
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In response to the MAP's concerns that the measure needed to be
tested in more facilities to demonstrate reliability and validity, we
have completed testing the Measure Authoring Tool (MAT) \454\ output
for this measure in multiple hospitals that use a variety of EHR
systems,\455\ and the measure was shown to be feasible to implement,
reliable, and valid. For more information on the concerns and
considerations raised by the MAP related to this measure, we refer
readers to the December 2017 NQF MAP Hospital Workgroup Meeting
Transcript.\456\ In response to the MAP's recommendation, the measure
was refined and presented to the MAP on November 8, 2018 for any
additional feedback; however, there was no additional MAP feedback at
that time.
---------------------------------------------------------------------------
\454\ The Measure Authoring Tool (MAT) is a web-based tool used
to develop the electronic measure specifications, which expresses
complicated measure logic in several formats including a human-
readable document. For additional information, we refer readers to:
https://www.emeasuretool.cms.gov/.
\455\ National Quality Forum, Measure Applications Partnership,
MAP 2018 Considerations for Implementing Measures in Federal
Programs: Hospitals. Available at: http://www.qualityforum.org/Publications/2018/02/MAP_2018_Considerations_for_Implementing_Measures_Final_Report_-_Hospitals.aspx.
\456\ Measure Applications Partnership, December 2017 NQF MAP
Hospital Workgroup Meeting Transcript. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
---------------------------------------------------------------------------
This measure was submitted for endorsement by NQF's Patient Safety
Standing Committee for the Spring 2019 cycle, with a complete review of
measure validity and reliability scheduled for June 2019. However, we
also note that section 1866(b)(3)(B)(viii)(IX)(bb) of the Act provides
an exception under which, in the case of a specified area or medical
topic determined appropriate by the Secretary for which a feasible and
practical measure has not been endorsed by the entity with a contract
under section 1890(a) of the Act, the Secretary may specify a measure
that is not so endorsed as long as due consideration is given to
measures that have been endorsed or adopted by a consensus organization
identified by the Secretary.
We believe this measure will provide hospitals with reliable and
timely measurement of their opioid-related adverse event rates, which
are a high-priority measurement area. We believe implementation of this
measure can lead to safer patient care by incentivizing hospitals to
implement or refine clinical workflows that facilitate evidence-based
use and monitoring when administering opioids. We also believe
implementation of this measure may result in fewer patients
experiencing adverse events associated with the administration of
opioids, such as respiratory depression, which can lead to brain damage
and death. This measure addresses the quality priority of ``Making Care
Safer by Reducing Harm Caused in the Delivery of Care'' through the
Meaningful Measures Area of ``Preventable Harm.'' \457\ We also note
[[Page 19479]]
that adoption of this measure would introduce the first outcomes
measure to the eCQM measure set under the Hospital IQR Program, which
currently is comprised entirely of process measures.
---------------------------------------------------------------------------
\457\ More information on CMS' Meaningful Measures Initiative is
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.html.
---------------------------------------------------------------------------
(c) Data Sources
The data source for this measure is entirely EHR data. The measure
is designed to be calculated by the hospitals' EHRs, as well as by CMS
using the patient level data submitted by hospitals to CMS. As with all
quality measures we develop, testing was performed to confirm the
feasibility of the measure, data elements, and validity of the
numerator, using clinical adjudicators who validated the EHR data
compared with medical chart-abstracted data. Based on testing, results
showed that rates of missing data elements required for measure
calculation were very low (range 0 percent to 0.8 percent). Testing
also showed that the positive predictive value (PPV),\458\ which
describes the probability that a patient with a positive result
(numerator case) identified by the EHR data was also a positive result
verified by review of the patient's medical record done by a clinical
adjudicator, was high at all hospital testing sites (94 percent to 98
percent). For more information on the measure testing and data, we
refer readers to the measure's methodology report on the CMS measure
methodology page at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html. Testing was completed using output from the MAT in
five hospitals, using two different EHR systems.
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\458\ ``Predictive Value.'' Farlex Partner Medical Dictionary.
Available at: https://medical-dictionary.thefreedictionary.com/predictive+value.
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(d) Measure Calculation
The Hospital Harm--Opioid-Related Adverse Events eCQM is an outcome
measure that assesses, by hospital, the proportion of patients who had
an opioid-related adverse event during an admission to an acute care
hospital by assessing the administration of naloxone. The measure
includes inpatient admissions that were initiated in the emergency
department or in observational status followed by a hospital admission.
The measure denominator includes all patients 18 years or older
discharged from an inpatient hospital admission during the measurement
period.
The numerator is the number of patients who received naloxone
outside of the operating room either: (1) After 24 hours from hospital
arrival; or (2) during the first 24 hours after hospital arrival with
evidence of hospital opioid administration prior to the naloxone
administration. We do not include naloxone use in the operating room
where it could be part of the sedation plan as administered by an
anesthesiologist or nurse anesthetist. Uses of naloxone for procedures
outside of the operating room (such as bone marrow biopsy) are counted
in the numerator as its use would indicate the patient was over
sedated. These criteria exist to ensure patients are not considered to
have experienced harm if they receive naloxone in the first 24 hours
due to an opioid overdose that occurred in the community prior to
hospital arrival. We do not require the administration of an opioid
prior to naloxone after 24 hours from hospital arrival because an event
occurring 24 hours after admission is most likely due to hospitals'
administration of opioids. By limiting the requirement of documented
opioid administration to the first 24 hours of the encounter, we are
reducing the complexity of the measure logic, and therefore, the burden
of implementation for hospitals. The measure numerator identifies a
harm using the administration of naloxone, and purposely does not
include any medications that combine naloxone with other agents.
The measure is intended to capture a type of rare event, such that
a full year of data would most reliably capture the quality of care
that is associated with low rates. While reliability of this measure
was established using 1 year of data, we note that under the eCQM
reporting and submission requirements we are proposing in section
VIII.A.10.d.(1) through (4) of the preamble of this proposed rule,
initial reporting of this measure, if finalized, would only require
hospitals to submit one self-selected calendar quarter of data;
hospitals may submit more than one quarter of data for this measure
should they so desire. We are considering a 1-year measurement period
for the future public reporting of this measure.
(e) Outcome
This eCQM assesses the proportion of encounters where naloxone is
administered as a proxy for administration of excessive amounts of
opioid medications, not including naloxone given while in the operating
room. In the first 24 hours of the hospitalization, an opioid must have
been administered prior to receiving naloxone to be considered part of
the outcome.
We note this measure is not risk adjusted for chronic opioid use,
as most instances of opioid-related adverse events should be
preventable for all patients regardless of prior exposure to opioids or
chronic opioid use. In addition, there are several risk factors that
affect sensitivity to opioids that physicians should consider when
dosing opioids. Risk adjustment would only be needed if certain
hospitals have patients with distinctly different risk profiles that
cannot be mitigated by providing high-quality care. Similarly, the
current measure specification does not include stratification of
patients for chronic opioid use for three reasons: (1) This is a
challenging data element to capture consistently in the EHR; (2)
chronic opioid use should be taken into consideration by clinicians in
determining dosing in the hospital and theoretically should not be
considered a different risk level for patients; and (3) stratification
can reduce the effective sample size of a measure and make the measure
less useable. During measure development, TEP members gave feedback on
whether the measure required risk adjustment. The majority of TEP
members voted against risk adjustment of this measure with the
rationale that it would be difficult to capture chronic opioid use
within the EHR and that the increased risk of harm associated with
these patients can be mitigated by hospital monitoring. For more
information on the Hospital Harm--Opioid-Related Adverse Events eCQM,
we refer readers to the measure specifications available on the CMS
Measure Methodology website, at: https://www.cms.gov/medicare/quality-
initiatives-patient-assessment-instruments/hospitalqualityinits/
measure-methodology.html.
We also refer readers to section VIII.A.10.d.(1) through (4) of the
preamble of this proposed rule where we discuss our proposed eCQM
reporting and submission requirements through the CY 2022 reporting
period/FY 2024 payment determination. In addition, we refer readers to
section VIII.D.6.a. and b. of the preamble of this proposed rule for a
similar proposal to adopt the Hospital Harm--Opioid-Related Adverse
Events eCQM for the Promoting Interoperability Program beginning with
the reporting period in CY 2021.
We acknowledge that some stakeholders have expressed concern that
some providers could withhold the use of naloxone for patients who are
in respiratory depression, believing that
[[Page 19480]]
may help those providers avoid poor performance on the proposed
Hospital Harm--Opioid-Related Adverse Events eCQM (83 FR 41591).
Therefore, we are soliciting public comment on the potential for this
measure to disincentivize the appropriate use of naloxone in the
hospital setting or withholding opioids when they are medically
necessary in patients requiring palliative care or who are at end of
life out of an overabundance of caution.
b. Proposed Adoption of Hybrid Hospital-Wide Readmission Measure With
Claims and Electronic Health Record Data (NQF #2879)
In this proposed rule, we are proposing to adopt the Hybrid
Hospital-Wide Readmission Measure with Claims and Electronic Health
Record Data (NQF #2879) (Hybrid HWR measure) into the Hospital IQR
Program in a stepwise fashion. First, we would accept data submissions
for the Hybrid HWR measure during two voluntary reporting periods. In
those periods, we would collect data on the Hybrid HWR measure in
accordance with, and to the extent permitted by, the HIPAA Privacy and
Security Rules (45 CFR parts 160 and 164, Subparts A, C, and E), and
other applicable law. The first voluntary reporting period would run
from July 1, 2021 through June 30, 2022, and the second would run from
July 1, 2022 through June 30, 2023. These voluntary reporting periods
would last for four quarters, which is an expansion upon the 2018
Voluntary Reporting Period for the Hybrid HWR measure, which only
collected two quarters of data. Immediately thereafter, we are
proposing to require reporting of the Hybrid HWR measure for the
reporting period which runs from July 1, 2023 through June 30, 2024,
impacting the FY 2026 payment determination, and for subsequent years.
This proposal to adopt the Hybrid HWR measure with a stepwise
implementation timeline is being made in conjunction with our proposal
to remove the Claims-Based Hospital-Wide All-Cause Unplanned
Readmission Measure (NQF #1789) (HWR claims-only measure) (discussed in
section VIII.A.6. of the preamble of this proposed rule, below). These
proposals are discussed in detail below.
(1) Background
Hospital readmission rates are affected by complex and critical
aspects of care such as communication between providers or between
providers and patients; prevention of, and response to, complications;
patient safety; and coordinated transitions to the outpatient
environment (82 FR 38350 through 38355). Some readmissions are
unavoidable, for example, those that result from inevitable progression
of disease or worsening of chronic conditions. However, readmissions
may also result from poor quality of care or inadequate transitional
care (77 FR 53521). From a patient perspective, an unplanned
readmission for any cause is an adverse event. For the July 1, 2016
through June 30, 2017 measurement period (the most recent data
available), the readmission rate from the hospital-wide population
ranged from 10.6 percent to 20.3 percent, showing a performance gap
across hospitals with wide variation and an opportunity to improve
quality.\459\
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\459\ Centers for Medicare & Medicaid Services. (2018). 2018
All-Cause Hospital-Wide Measure Updates and Specifications Report:
Hospital-Wide Readmission. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
---------------------------------------------------------------------------
Consistent with our goal of increasing the use of EHR data in
quality measurement and in response to stakeholder feedback encouraging
the use of clinical data in outcome measures, we developed the Hybrid
HWR measure (NQF #2879). The Hybrid HWR measure is designed to capture
all unplanned readmissions that arise from acute clinical events
requiring urgent rehospitalization within 30 days of discharge. Planned
readmissions, which are generally not a signal of quality of care, are
not considered readmissions in the measure outcome and all unplanned
readmissions are considered an outcome, regardless of cause. The Hybrid
HWR measure provides a facility-wide picture of this aspect of care
quality in hospitals and was designed to promote hospital quality
improvement. The Hybrid HWR measure aligns with the Meaningful Measures
Initiative quality priority of ``Promoting Effective Communication and
Coordination of Care.''
The Hybrid HWR measure was first included in a publicly available
document entitled ``List of Measures Under Consideration for December
1, 2014.'' \460\ Upon review, the MAP supported further development of
the Hybrid HWR measure, which was an expression of their conditional
support pending endorsement for the National Quality Forum (NQF).\461\
Thereafter, the Hybrid HWR measure was endorsed by the NQF on December
9, 2016.\462\ The Hybrid HWR measure was first discussed in the FY 2016
IPPS/LTCH PPS final rule (80 FR 49698 through 49704).
---------------------------------------------------------------------------
\460\ List of Measures Under Consideration for December 1, 2014.
Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
\461\ Measure Applications Partnership, 2015 Considerations for
Implementing Measures in Federal Programs: Hospitals. Available at:
http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=78711.
\462\ National Quality Forum. (2017). All-Cause Admissions and
Readmissions 2015-2017 Technical Report. Available at: https://www.qualityforum.org/Publications/2017/04/All-Cause_Admissions_and_Readmissions_2015-2017_Technical_Report.aspx.
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In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38350 through
38355), we finalized a 6-month, limited, voluntary reporting period for
the EHR-derived data elements used in the Hybrid HWR measure
(hereinafter referred to as the 2018 Voluntary Reporting Period).
Specifically, for the 2018 Voluntary Reporting Period, we invited
participating hospitals and their health IT vendors to report data on
discharges over a 6-month period in the first two quarters of CY 2018
(January 1, 2018 through June 30, 2018). We finalized that a hospital's
annual payment determination would not be affected by the 2018
Voluntary Reporting Period. Hospitals that participated in the 2018
Voluntary Reporting Period will receive confidential hospital-specific
reports in early summer of 2019 that detail submission results from the
reporting period, as well as the Hybrid HWR measure results assessed
from merged files created by our merging of the EHR data elements
submitted by each participating hospital with claims data from the same
set of index admissions.
Hospitals that volunteered to submit data increased their
familiarity with submitting data for hybrid quality measures from their
EHR systems. Participating hospitals received information and
instruction on the use of the electronic specifications for this
measure, had an opportunity to test extraction and submission of data
to CMS, and received submission feedback reports from CMS, available
via the QualityNet Secure Portal, with details on the success of their
submissions. In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38354), we
stated that we were considering proposing the Hybrid HWR measure (NQF
#2879) as a required measure as early as the FY 2023 payment
determination. We also stated that any requirement for mandatory
reporting on this measure would be proposed through future rulemaking.
During the 2018 Voluntary Reporting Period, approximately 80
hospitals submitted data for the Hybrid HWR measure. We are currently
merging the EHR data with the claims data and will provide hospitals
with confidential hospital-specific reports which will
[[Page 19481]]
reflect submission results from the reporting period. The assessment
will be based on the merged files containing both submitted EHR data
elements as well as claims data from the same set of index admissions.
We note that the Hybrid HWR measure cohort and outcome are
identical to those in the HWR claims-only measure, which was adopted
into the Hospital IQR Program beginning with the FY 2015 payment
determination (77 FR 53521 through 53528). Therefore, we intend for the
Hybrid HWR measure to replace the previously finalized HWR claims-only
measure, as further discussed in section VIII.A.6. of the preamble of
this proposed rule, where we are proposing to remove the HWR claims-
only measure beginning with the July 1, 2023 through June 30, 2024
reporting period, for the FY 2026 payment determination, the same year
the Hybrid HWR measure would be required if this proposal is finalized.
(2) Measure Overview
Both the previously finalized HWR claims-only measure and proposed
Hybrid HWR measure capture the hospital-level, risk-standardized
readmission rate (RSRR) of unplanned, all-cause readmissions within 30
days of hospital discharge for any eligible condition. The measure
reports a single summary RSRR, derived from the volume-weighted results
of five different models, one for each of the following specialty
cohorts based on groups of discharge condition categories or procedure
categories: (1) Surgery/gynecology; (2) general medicine; (3)
cardiorespiratory; (4) cardiovascular; and (5) neurology. The measure
also indicates the hospital-level standardized readmission ratios (SRR)
for each of these five specialty cohorts. The outcome is defined as
unplanned readmission for any cause within 30 days of the discharge
date for the index admission (the admission included in the measure
cohort). A specified set of readmissions are planned and do not count
in the readmission outcome. The target population is Medicare fee-for-
service (FFS) beneficiaries who are 65 years or older and hospitalized
in non-federal hospitals.
(3) Data Sources
The Hybrid HWR measure uses a combination of administrative data
and a set of core clinical data elements extracted from hospital EHRs
for each hospitalized Medicare FFS beneficiary over the age of 65
years, which is why it is referred to as a ``hybrid'' measure. The
measure also requires a set of linking variables which are present in
both the EHR and claims data, so each patient's core clinical data
elements can be matched to the claim for the relevant admission
(examples of linking variables are patient unique identifier and
patient date of birth).
The administrative data consist of Medicare Part A and Part B
claims data and Medicare beneficiary enrollment data, and are used to
identify index admissions included in the measure cohort, to create a
risk-adjustment model, and to assess the 30-day unplanned readmission
outcome. The claims data are merged with EHR-based core clinical data
elements, which are routinely collected on hospitalized adults, and are
used in this hybrid measure for risk-adjustment of patients' severity
of illness. The specific set of core clinical data elements that are
used in the Hybrid HWR measure are listed below.
------------------------------------------------------------------------
Additional
Data elements Units of measurement accepted units
of measurement
------------------------------------------------------------------------
Heart Rate.................... Beats per minute......
Systolic Blood Pressure....... Millimeter of mercury
(mmHg).
Respiratory Rate.............. Breath per minute.....
Temperature................... Degrees Fahrenheit (F) Degrees Celsius
(C).
Oxygen Saturation............. Percent (%)...........
Weight........................ Kilogram (KG)......... Pounds (LB).
Hematocrit.................... Percent (%)...........
White Blood Cell Count........ 10[supcaret]9 per Thousands of
liter (X10E+09/L). cells per
microliter (K/
MCL).
Potassium..................... Millimole per liter MEQ/L.
(MMOL/L).
Sodium........................ Millimole per liter MEQ/L.
(MMOL)/L.
Bicarbonate................... Millimole per liter MEQ/L.
(MMOL)/L.
Creatinine.................... Milligrams per
deciliter (MG/DL).
Glucose....................... Milligrams per
deciliter (MG/DL).
------------------------------------------------------------------------
As we stated in the FY 2016 IPPS/LTCH PPS final rule (80 FR 49703),
the core clinical data elements use existing value sets where possible.
Because core clinical data elements are data that are routinely
collected on hospitalized adults, they are widely available in hospital
EHR systems. We have confirmed through testing that extraction of core
clinical data elements from hospital EHRs is feasible and can be
utilized as part of specific quality outcome measures.\463\ The core
clinical data elements utilize EHR data, therefore, we developed and
tested a MAT output and identified value sets for extraction of the
core clinical data elements, which are available at the eCQI Resource
Center.\464\
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\463\ For more detail about core clinical data elements used in
the Hybrid HWR measure, we refer readers to our discussion in the FY
2016 IPPS/LTCH PPS final rule (80 FR 49698 through 49704) and to the
QualityNet website at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier2&cid=1228763452133.
\464\ Electronic Clinical Quality Improvement (eCQI) Resource
Center. Hybrid Hospital-Wide Readmission. Available at: https://ecqi.healthit.gov/ecqm/measures/cms529v0.
---------------------------------------------------------------------------
We tested the electronic specifications in four separate health
systems that used three different EHR systems. During development and
testing of the Hybrid HWR measure, we demonstrated that the core
clinical data elements were feasibly extracted from hospital EHRs for
nearly all adult patients admitted. We also demonstrated that the use
of the core clinical data elements to risk-adjust the Hybrid HWR
measure improves the discrimination of the measure, or the ability to
distinguish patients with a low risk of readmission from those at high
risk of readmission, as assessed by the c-statistic.\465\ In addition,
inclusion of patients' clinical information from EHRs is responsive to
stakeholders who prefer to use clinical information that is available
to the clinical care team at the time treatment is rendered to account
[[Page 19482]]
for patients' severity of illness rather than relying solely on data
from claims (80 FR 49702). The Hybrid HWR measure is now fully
developed, tested, and NQF-endorsed (NQF #2879).
---------------------------------------------------------------------------
\465\ Hybrid 30-day Risk-standardized Acute Myocardial
Infarction Mortality Measure with Electronic Health Record Extracted
Risk Factors (Version 1.1); Hybrid Hospital-Wide Readmission Measure
with Electronic Health Record Extracted Risk Factors (Version 1.1);
164 2013 Core Clinical Data Elements Technical Report (Version 1.1);
all available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
---------------------------------------------------------------------------
We note the Hybrid HWR measure was initially developed using claims
coded in ICD-9. However, we have identified and tested ICD-10
specifications for all information used in the measure derived from
Medicare claims for both the HWR claims-only measure, which is
currently in use under the Hospital IQR Program, and for the proposed
Hybrid HWR measure. The ICD-10 specifications are identical for both
the Hybrid and claims-only HWR measures. Only the Hybrid HWR measure's
use of the core clinical data elements in the risk-adjustment model
differs between the two measures. Those data elements are not affected
by ICD-10 implementation. We update the measure specifications annually
for both measures to incorporate new and revised ICD-10 codes effective
October 1 of each year after clinical review.
We also clinically and empirically review updates to the Agency for
Healthcare Research and Quality (AHRQ) Clinical Classifications
Software (CCS) map that incorporate new codes and shifts in CCS
categories of existing codes.\466\ These updates may impact assignment
to HWR sub-cohorts or modify the planned readmission algorithm. For
additional details regarding the measure specifications that
accommodate ICD-10-coded claims, we refer readers to the 2018 All-Cause
Hospital-Wide Measure Updates and Specifications Report, which is
posted on the QualityNet website.\467\ We will update and publicly
release the MAT output annually to include any updates to the
electronic quality measure standards and all included value sets for
the measure-specific data elements. We note that the data sources are
the same as those used for the 2018 Voluntary Reporting Period.
---------------------------------------------------------------------------
\466\ https://www.hcup-us.ahrq.gov/toolssoftware/ccs10/ccs10.jsp. Version 2019.1 of CCS for ICD-10-CM and CCS for ICD-10
for PCS.
\467\ Centers for Medicare & Medicaid Services. (2018). 2018 All
Cause Hospital Wide Measure Updates and Specifications Report.
Available at: https://www.qualitynet.org/dcs/ContentServer?cid=1228774371008&pagename=QnetPublic%2FPage%2FQnetTier4&c=Page.
---------------------------------------------------------------------------
(4) Measure Calculation
The methods used to calculate the Hybrid HWR measure align with the
methods used to calculate the currently adopted HWR claims-only
measure. Index admissions are assigned to one of five mutually
exclusive specialty cohort groups consisting of related conditions or
procedures. An index admission is the hospitalization to which the
readmission outcome is attributed and includes admissions for patients:
Enrolled in Medicare FFS Part A for the 12 months prior to
the date of admission and during the index admission;
Aged 65 or over;
Discharged alive from a non-federal short-term acute care
hospital; and
Not transferred to another acute care facility.
This measure excludes index admissions for patients:
Admitted to Prospective Payment System (PPS)-exempt cancer
hospitals;
Without at least 30 days of post-discharge enrollment in
Medicare FFS;
Discharged against medical advice;
Admitted for primary psychiatric diagnoses;
Admitted for rehabilitation; or
Admitted for medical treatment of cancer.
The five specialty cohort groups are: (1) Surgery/gynecology; (2)
general medicine; (3) cardiorespiratory; (4) cardiovascular; and (5)
neurology. For each specialty cohort group, the standardized
readmission ratio (SRR) is calculated as the ratio of the number of
``predicted'' readmissions to the number of ``expected'' readmissions
at a given hospital. For each hospital, the numerator of the ratio is
the number of readmissions predicted within 30 days based on the
hospital's performance with its observed case mix and service mix. The
denominator for each hospital is the number of readmissions expected
based on the nation's performance with each particular hospital's case
mix and service mix. This approach is analogous to a ratio of
``observed'' to ``expected'' used in other types of statistical
analyses. The specialty cohort SRRs are then pooled for each hospital
using a volume-weighted geometric mean to create a hospital-wide
composite SRR. The composite SRR is multiplied by the national observed
readmission rate to produce the Risk-Standardized Readmission Rate
(RSRR). For additional details regarding the measure specifications to
calculate the RSRR, we refer readers to the 2018 All-Cause Hospital-
Wide Measure Updates and Specifications Report, which is posted on the
QualityNet website.\468\
---------------------------------------------------------------------------
\468\ Centers for Medicare & Medicaid Services. (2018). 2018 All
Cause Hospital Wide Measure Updates and Specifications Report.
Available at: https://www.qualitynet.org/dcs/ContentServer?cid=1228774371008&pagename=QnetPublic%2FPage%2FQnetTier4&c=Page.
---------------------------------------------------------------------------
We also note an important distinguishing factor about hybrid
measures: Hybrid measure results must be calculated by CMS to determine
hospitals' risk-adjusted rates relative to national rates using data
from all reporting hospitals. With a hybrid measure, hospitals submit
data extracted from the EHR, and CMS performs the measure calculations
and disseminates results.
(5) Outcome
As stated above, the proposed Hybrid HWR measure outcome is aligned
with the currently adopted HWR claims-only measure. The Hybrid HWR
measure outcome assesses unplanned readmissions for any cause within 30
days of discharge from the index admission. It does not consider
planned readmissions as part of the readmission outcome and identifies
them by using the CMS Planned Readmission Algorithm, which is a set of
criteria for classifying readmissions as planned using Medicare claims.
The algorithm for the Hybrid HWR measure \469\ is the same algorithm
used in the HWR claims-only measure (77 FR 53521).\470\ The algorithm
and outcomes are also the same as those used for the 2018 Voluntary
Reporting Period, although the algorithm is updated annually to reflect
changes in the ICD-10 coding system and the CCS map. The algorithm
identifies admissions that are typically planned and may occur within
30 days of discharge from the hospital.\471\ The most recent version (v
4.0) was described in the FY 2015 IPPS/LTCH PPS final rule (79 FR 50211
through 50216) for the HWR claims-only measure, and the code
specifications are updated annually. A complete description of the CMS
Planned Readmission Algorithm, which includes lists of planned
procedures and acute diagnoses, can be found in the 2018 All-Cause
Hospital-Wide Measure Updates and Specifications Report.\472\
---------------------------------------------------------------------------
\469\ Centers for Medicare & Medicaid Services. Hybrid Hospital-
Wide Readmission Measure with Electronic Health Record Extracted
Risk Factors (Version 1.1). Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
\470\ Centers for Medicare & Medicaid Services. Measure
Methodology. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
\471\ Ibid.
\472\ Centers for Medicare & Medicaid Services. (2018). 2018 All
Cause Hospital Wide Measure Updates and Specifications Report.
Available at: https://www.qualitynet.org/dcs/ContentServer?cid=1228774371008&pagename=QnetPublic%2FPage%2FQnetTier4&c=Page.
---------------------------------------------------------------------------
(6) Risk Adjustment
The proposed Hybrid HWR measure adjusts both for case-mix
differences
[[Page 19483]]
(how severely ill patients are when they are admitted) as well as
differences in hospitals' service-mix (the types of conditions that
cause patients' admissions). The case-mix variables include patients'
ages and comorbidities as well as laboratory test results and vital
signs. As listed in detail above, the Hybrid HWR measure specifically
uses 13 core clinical data elements from EHRs--seven laboratory test
results (hematocrit, white blood cell count, sodium, potassium,
bicarbonate, creatinine, glucose) and six vital signs (heart rate,
respiratory rate, temperature, systolic blood pressure, oxygen
saturation, weight). The use of the core clinical data elements to
risk-adjust the Hybrid HWR measure improves the discrimination of the
measure, and inclusion of patients' clinical information from EHRs is
responsive to stakeholders who prefer to use clinical information that
is available to the clinical care team at the time treatment is
rendered to account for patients' severity of illness rather than
relying solely on data from claims (80 FR 49702).
The service-mix variables include principal discharge diagnoses
grouped into AHRQ Clinical Classification Software. Patient
comorbidities are based on the index admission, the admission included
in the measure cohort, and a full year of prior history. The risk-
adjustment variables included in the development and testing of the
proposed Hybrid HWR measure are derived from both claims and clinical
EHR data. As identified in the measure specifications, the variables
are: (1) 13 core clinical data elements derived from hospital EHRs;
\473\ (2) the Clinical Classification Software (CCS) categories \474\
for the principal discharge diagnosis associated with each index
admission derived from ICD-10 codes in administrative claims data; and
(3) comorbid conditions of each patient identified from inpatient
claims in the 12 months prior to and including the index admission
derived from ICD-10 codes and grouped into the CMS condition categories
(CC).\475\ The condition categories used in the risk-adjustment model
and the ICD-10 codes grouped into each condition category can be found
in the Annual Updates and Specification Report on the QualityNet
website.
---------------------------------------------------------------------------
\473\ Electronic Clinical Quality Improvement (eCQI) Resource
Center. Hybrid Hospital-Wide Readmission. Available at: https://ecqi.healthit.gov/ecqm/measures/cms529v0.
\474\ Centers for Medicare & Medicaid Services. (2018). 2018
All-Cause Hospital-Wide Measure Updates and Specifications Report:
Hospital-Wide Readmission. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
\475\ Centers for Medicare & Medicaid Services. (2018). 2018
All-Cause Hospital-Wide Measure Updates and Specifications Report:
Hospital-Wide Readmission. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
---------------------------------------------------------------------------
All 13 core clinical data elements were shown to be statistically
significant predictors of readmission in one or more risk-adjustment
models of the five specialty cohort groups used to calculate the
proposed Hybrid HWR measure.\476\ The testing results demonstrate that
the core clinical data elements enhanced the discrimination (assessed
using the c-statistic) when used in combination with administrative
claims data.\477\ For additional details regarding the risk-adjustment
model, we refer readers to the Hybrid Hospital-Wide Readmission Measure
with Electronic Health Record Extracted Risk Factors (Version
1.1).\478\ We note that the risk adjustment methods are the same as
those used for the 2018 Voluntary Reporting Period.
---------------------------------------------------------------------------
\476\ Centers for Medicare & Medicaid Services. Hybrid Hospital-
Wide Readmission Measure with Electronic Health Record Extracted
Risk Factors (Version 1.1). Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
\477\ Centers for Medicare & Medicaid Services. Hybrid Hospital-
Wide Readmission Measure with Electronic Health Record Extracted
Risk Factors (Version 1.1). Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
\478\ Ibid.
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(7) Data Submission
As with the 2018 Voluntary Reporting Period (82 FR 38350 through
38355), we are proposing that hospitals would use Quality Reporting
Data Architecture (QRDA) Category I files for each Medicare FFS
beneficiary who is 65 years and older. Submission of data to CMS using
QRDA I files is the current EHR data and measure reporting standard
adopted for eCQMs implemented in the Hospital IQR Program. This same
standard would be used for reporting the core clinical data elements to
the CMS data receiving system via the QualityNet Secure Portal.
To successfully submit the Hybrid HWR measure, hospitals would need
to submit the core clinical data elements included in the Hybrid HWR
measure, as described in the measure specifications, for all Medicare
FFS beneficiaries 65 and older discharged from an acute care
hospitalization in the 1-year measurement period (July 1 to June 30 of
each year). We note this is the same measurement period as the HWR
claims-only measure (77 FR 53521 through 53528). Voluntary submission
would run from July 1, 2021 through June 30, 2022, and from July 1,
2022 through June 30, 2023. Required submission would begin with the
reporting period which runs July 1, 2023 through June 30, 2024,
impacting the FY 2026 payment determination.
Hospitals would also be required to successfully submit the
following six linking variables that are necessary in order to merge
the core clinical data elements with the CMS claims data to calculate
the measure:
CMS Certification Number;
Health Insurance Claims Number or Medicare Beneficiary
Identifier;
Date of birth;
Sex;
Admission date, and
Discharge date.
In order for us to be able to calculate the Hybrid HWR measure
results, each hospital would need to report vital signs for 90 percent
or more of the hospital discharges for Medicare FFS patients, 65 years
or older in the measurement period (as determined from the claims
submitted to CMS for admissions that ended during the same reporting
period). Vital signs are measured on nearly every adult patient
admitted to an acute care hospital and should be present for nearly 100
percent of discharges (identified in Medicare FFS claims submitted
during the same period). In addition, calculating the measure with more
than 10 percent of hospital discharges missing these data elements
could cause poor reliability of the measure score and instability of
hospitals' results from measurement period to measurement period.
Hospitals would also be required to submit the laboratory test
results for 90 percent or more of discharges for non-surgical
patients,\479\ meaning those not included in the surgical specialty
cohort of the HWR measure. For many patients admitted following
elective surgery, there are no laboratory values available in the
appropriate time window. Therefore, laboratory test results are not
used in the risk adjustment of the surgical cohort.
---------------------------------------------------------------------------
\479\ Centers for Medicare & Medicaid Services. (2018). 2018
All-Cause Hospital-Wide Measure Updates and Specifications Report:
Hospital-Wide Readmission. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
---------------------------------------------------------------------------
The six variables required for linking EHR and claims data should
be submitted for 100 percent of discharges in the measurement period.
Because these linking variables are required for
[[Page 19484]]
billing,\480\ they should be available on all Medicare FFS patients and
are ideally suited to support merging claims and EHR data. However,
hospitals would meet Hospital IQR Program requirements if they submit
linking variables on 95 percent or more of discharges with a Medicare
FFS claim for the same hospitalization during the measurement period.
Beginning with the reporting period which runs from July 1, 2023
through June 30, 2024, a hospital that does not submit any EHR data for
the Hybrid HWR measure, or that submits data for less than the
specified percentage of applicable patients, would be considered as not
having met this Hospital IQR Program requirement and would receive a
one-fourth reduction of its Annual Payment Update (APU) for the
applicable fiscal year.
---------------------------------------------------------------------------
\480\ CMS, Medicare Claims Processing Manual (100-04). Available
at: https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/internet-Only-Manuals-IOMs.html.
---------------------------------------------------------------------------
Under our stepwise approach, for the voluntary reporting periods
which run from July 1, 2021 through June 30, 2022, and July 1, 2022
through June 30, 2023, if a hospital submits data for this proposed
measure, it should do so according to the requirements described above
in order for CMS to calculate the measure. However, a hospital's annual
payment determination would not be affected during this timeframe. The
benefits to hospitals that submit the data in the initial 2-year
voluntary reporting period include the opportunity to provide feedback
on the measure specifications, to confirm mapping and extraction of
data elements, to hone and improve quality assurance practices, and to
troubleshoot any problems populating QRDA templates for successful
submission to CMS. As described above, hospitals would receive detailed
patient discharge information which would help them perfect these
processes before hospitals' payment determinations would be impacted
beginning with the FY 2026 payment determination. We refer readers to
section VIII.A.10.e. of the preamble of this proposed rule for more
information about the form and manner of hybrid measure data
submission.
(8) Confidential Feedback Reports
Hospitals that submit data for this measure during the voluntary
reporting periods, which run from July 1, 2021 through June 30, 2022,
and July 1, 2022 through June 30, 2023, would receive confidential
hospital-specific reports that detail submission results from the
applicable reporting period, as well as the Hybrid HWR measure results
assessed from merged files created by our merging of the EHR data
elements submitted by each participating hospital with claims data from
the same set of index admissions. Participating hospitals would receive
information and instructions on the use of the electronic
specifications for this measure, have an opportunity to test extraction
and submission of data to CMS, and receive feedback reports from CMS,
available via the QualityNet Secure Portal, with details on the success
of their submissions.
We are proposing to take an incremental approach to implementing
this proposed measure in an effort to be responsive to provider and
vendor feedback (82 FR 38355), which requested sufficient time to
undertake the data mapping, validation, adjustments to clinician
workflow (specifically, changes to documentation practices to ensure
accurate and complete mapping of the required data elements), and
training needed to effectively implement EHR-based quality reporting to
CMS. We believe that two additional years of voluntary reporting of the
Hybrid HWR measure, in addition to the 2018 Voluntary Reporting Period,
would allow hospitals more time to update and validate their systems,
to ensure data mapping is accurate and complete, and to implement
workflow changes and clinician training as necessary to better prepare
for submitting data when the Hybrid HWR measure becomes required
beginning with the reporting period which runs from July 1, 2023
through June 30, 2024 (impacting the FY 2026 payment determination) if
our proposal is finalized. We believe those hospitals that can
implement the Hybrid HWR measure more quickly can have the opportunity
to submit their data to CMS and refine their data collection and
submission processes. Starting with voluntary and confidential
reporting for the Hybrid HWR measure would enable hospitals and their
vendors to gain further experience collecting and reporting the core
clinical data elements and linking variables so they would be ready for
public reporting of the Hybrid HWR measure data on the Hospital Compare
website starting with the FY 2026 payment determination.
Under our proposal, the first year of voluntary data collection for
confidential reporting would be for the July 1, 2021 through June 30,
2022 reporting period. The 12-month measurement period that runs from
July 1 through June 30 would be consistent with the calculation of the
HWR claims-only measure. To support hospital reporting, we intend to
publish the electronic specifications for this reporting period in the
2021 Annual Update \481\ in the spring of 2020, providing hospitals and
vendors with the electronic specifications approximately 15 months
before the beginning of the reporting period on July 1, 2021. We intend
to deliver the first set of confidential hospital-specific feedback
reports in the spring of 2023, after we merge the EHR data with the
associated claims data for the same reporting period, which is
historically pulled from CMS' claims data system at the end of
September following the end of the reporting period. During the first
year of voluntary data collection, which runs from July 1, 2021 through
June 30, 2022, we would not publicly report Hybrid HWR measure data,
nor would incomplete or non-submission of the EHR data impact
hospitals' APU determinations for the FY 2024 payment determination.
---------------------------------------------------------------------------
\481\ Electronic Clinical Quality Improvement (eCQI) Resource
Center. 2018 Measure Specifications. Available at: https://ecqi.healthit.gov/ecqm/measures/cms529v0. Note that the measure
specifications may be further refined in the 2021 Annual Update.
---------------------------------------------------------------------------
The second year of voluntary data collection for confidential
reporting would be for the July 1, 2022 through June 30, 2023 reporting
period. Similar to the first year of voluntary reporting, hospitals
would use the electronic specifications for this reporting period as
published in the 2022 Annual Update planned for the spring of 2021. We
plan to deliver confidential hospital-specific feedback reports in the
spring of 2024, after we merge the EHR data with the associated claims
data. As with the first year of voluntary data collection, there would
not be any associated public reporting, nor impact on hospitals' APU
determinations for the FY 2025 payment determination. As discussed
above, hospitals' payment determinations could be affected beginning
with the FY 2026 payment determination.
(9) Public Reporting
Under our stepwise approach, data collected specifically during the
voluntary reporting periods, which run from July 1, 2021 through June
30, 2022, and July 1, 2022 through June 30, 2023, would not be publicly
reported, as mentioned above. However, we are proposing that after the
end of the proposed voluntary reporting periods, we would begin public
reporting of the Hybrid HWR measure results, beginning with data
collected from the July 1, 2023 through June 30, 2024 reporting period,
impacting the FY 2026 payment determination. This would be the first
[[Page 19485]]
set of Hybrid HWR measure data to be publicly reported on the Hospital
Compare website, which we anticipate would be included in the July 2025
refresh of Hospital Compare. The EHR data would be merged with the
associated claims data, and then Hybrid HWR measure results would be
shared with hospitals in the confidential hospital-specific feedback
reports planned for the spring of 2025, providing hospitals a 30-day
review period prior to public reporting. Thereafter, in subsequent
reporting years, we would follow a similar operational timeline for EHR
data submissions, availability of hospital-specific reports, and public
reporting on the Hospital Compare website.
We note that this proposal is being made in conjunction with our
proposal to remove the Claims-Based Hospital-Wide All-Cause Unplanned
Readmission Measure (NQF #1789) beginning with the FY 2026 payment
determination as discussed below. We also refer readers to section
VIII.D.6.c. of preamble of this proposed rule, which includes a request
for feedback on whether to consider adopting the Hybrid HWR measure for
the Promoting Interoperability Program.
6. Proposed Removal of Claims-Based Hospital-Wide All-Cause Unplanned
Readmission Measure (NQF #1789) (HWR Claims-Only Measure)
In this proposed rule, we are proposing to remove the Claims-Based
Hospital-Wide All-Cause Unplanned Readmission Measure (NQF #1789) in
conjunction with our proposal to replace the measure by making the
Hybrid HWR measure mandatory beginning with the reporting period which
runs from July 1, 2023 through June 30, 2024, impacting the FY 2026
payment determination. This is discussed in detail below.
The HWR claims-only measure was adopted in the FY 2013 IPPS/LTCH
PPS final rule (77 FR 53521 through 53528) for the FY 2015 payment
determination and subsequent years, to allow us to provide a broader
assessment of the quality of care at hospitals, especially for
hospitals with too few disease specific readmissions to count
separately.
In this proposed rule, we are proposing to remove the HWR claims-
only measure, beginning with the July 1, 2023 through June 30, 2024
reporting period, for the FY 2026 payment determination. As discussed
in section VIII.A.5.b. of the preamble of this proposed rule above, the
Hybrid HWR measure is an enhanced version of HWR claims-only measure,
in that it provides substantive improvement to the current claims-based
measure, which is why we are proposing to replace it. The Hybrid HWR
measure includes clinical variables in the risk adjustment, which
improves face validity of the measure. Furthermore, we have heard from
stakeholders that they strongly favor electronic measures over claims-
based versions due to the incorporation of clinical data (80 FR 49694).
We are proposing to remove the HWR claims-only measure under
removal Factor 3, ``the availability of a more broadly applicable
measure (across settings, populations, or the availability of a measure
that is more proximal in time to desired patient outcomes for the
particular topic).'' We took into particular consideration the aspect
of removal Factor 3 which emphasizes when there is a different measure
that is more proximal in time to desired patient outcomes. Aspects of
the Hybrid HWR measure are more proximal in time to desired patient
outcomes for this measure because the measurement of the core clinical
data elements for each patient in the measure cohort is taken from the
beginning of the applicable inpatient stay, in comparison to the claims
data used for risk adjustment, which accounts for 1-year preceding
admission. In other words, the patient data used for risk adjustment of
the Hybrid HWR measure are data that come from the very start of the
inpatient stay that is evaluated for a readmission. In addition, as
noted above and discussed in detail in section VIII.A.5.b. of the
preamble of this proposed rule, the Hybrid HWR measure includes
clinical variables in the risk adjustment, which improves face validity
of the measure, and is responsive to provider stakeholder feedback
strongly in favor of electronic measures over claims-based versions due
to the incorporation of clinical data. For these reasons, we are
proposing to remove the HWR claims-only measure and replace it with the
Hybrid HWR measure.
We refer readers to sections VIII.A.5.b. and VIII.A.10.e. of the
preamble of this proposed rule for more detail on our proposals to
adopt the Hybrid HWR measure with a stepwise implementation timeline
starting with 2 years of voluntary confidential reporting, followed by
mandatory data submission and public reporting of the Hybrid HWR
measure results beginning with data collected from the July 1, 2023
through June 30, 2024 reporting period, impacting the FY 2026 payment
determination. To ensure continuity of public reporting on Hospital-
Wide All-Cause Unplanned Readmission measure data, we are proposing to
align the removal of the HWR claims-only measure such that its removal
aligns with the end of the 2-year confidential reporting period and
beginning of the mandatory data submission and public reporting of the
Hybrid HWR measure. In short, the Hybrid HWR measure is intended to
replace the HWR claims-only measure. Our proposal to remove the HWR
claims-only measure is contingent upon our proposals for the Hybrid HWR
measure being finalized.
7. Summary of Previously Finalized and Proposed Hospital IQR Program
Measures
a. Summary of Previously Finalized Hospital IQR Program Measures for
the FY 2022 Payment Determination
The table below summarizes the previously finalized Hospital IQR
Program measure set for the FY 2022 payment determination:
Measures for the FY 2022 Payment Determination
----------------------------------------------------------------------------------------------------------------
Short name Measure name NQF No.
----------------------------------------------------------------------------------------------------------------
National Healthcare Safety Network Measures
----------------------------------------------------------------------------------------------------------------
HCP............................................. Influenza Vaccination Coverage Among 0431
Healthcare Personnel.
----------------------------------------------------------------------------------------------------------------
Claims-Based Patient Safety Measures
----------------------------------------------------------------------------------------------------------------
COMP-HIP-KNEE *\++\............................. Hospital-Level Risk-Standardized Complication 1550
Rate (RSCR) Following Elective Primary Total
Hip Arthroplasty (THA) and/or Total Knee
Arthroplasty (TKA).
CMS PSI 04...................................... CMS Death Rate among Surgical Inpatients with (\+\)
Serious Treatable Complications.
----------------------------------------------------------------------------------------------------------------
[[Page 19486]]
Claims-Based Mortality Measures
----------------------------------------------------------------------------------------------------------------
MORT-30-STK..................................... Hospital 30-Day, All-Cause, N/A
Risk[dash]Standardized Mortality Rate
Following Acute Ischemic Stroke.
----------------------------------------------------------------------------------------------------------------
Claims-Based Coordination of Care Measures
----------------------------------------------------------------------------------------------------------------
READM-30-HWR.................................... Hospital-Wide All-Cause Unplanned Readmission 1789
Measure (HWR).
AMI Excess Days................................. Excess Days in Acute Care after 2881
Hospitalization for Acute Myocardial
Infarction.
HF Excess Days.................................. Excess Days in Acute Care after 2880
Hospitalization for Heart Failure.
PN Excess Days.................................. Excess Days in Acute Care after 2882
Hospitalization for Pneumonia.
----------------------------------------------------------------------------------------------------------------
Claims-Based Payment Measures
----------------------------------------------------------------------------------------------------------------
AMI Payment..................................... Hospital-Level, Risk-Standardized Payment 2431
Associated with a 30-Day Episode-of-Care for
Acute Myocardial Infarction (AMI).
HF Payment...................................... Hospital-Level, Risk-Standardized Payment 2436
Associated with a 30-Day Episode-of-Care For
Heart Failure (HF).
PN Payment...................................... Hospital-Level, Risk-Standardized Payment 2579
Associated with a 30-day Episode-of-Care For
Pneumonia.
THA/TKA Payment................................. Hospital[hyphen]Level, N/A
Risk[hyphen]Standardized Payment Associated
with an Episode-of-Care for Primary Elective
Total Hip Arthroplasty and/or Total Knee
Arthroplasty.
----------------------------------------------------------------------------------------------------------------
Chart-Abstracted Clinical Process of Care Measures
----------------------------------------------------------------------------------------------------------------
PC-01........................................... Elective Delivery............................. 0469
Sepsis.......................................... Severe Sepsis and Septic Shock: Management 0500
Bundle (Composite Measure).
----------------------------------------------------------------------------------------------------------------
EHR-based Clinical Process of Care Measures (that is, Electronic Clinical Quality Measures (eCQMs))
----------------------------------------------------------------------------------------------------------------
ED-2............................................ Admit Decision Time to ED Departure Time for 0497
Admitted Patients.
PC-05........................................... Exclusive Breast Milk Feeding................. 0480
STK-02.......................................... Discharged on Antithrombotic Therapy.......... 0435
STK-03.......................................... Anticoagulation Therapy for Atrial 0436
Fibrillation/Flutter.
STK-05.......................................... Antithrombotic Therapy by the End of Hospital 0438
Day Two.
STK-06.......................................... Discharged on Statin Medication............... 0439
VTE-1........................................... Venous Thromboembolism Prophylaxis............ 0371
VTE-2........................................... Intensive Care Unit Venous Thromboembolism 0372
Prophylaxis.
----------------------------------------------------------------------------------------------------------------
Patient Experience of Care Survey Measures
----------------------------------------------------------------------------------------------------------------
HCAHPS **....................................... Hospital Consumer Assessment of Healthcare 0166 (0228)
Providers and Systems Survey (including Care
Transition Measure).
----------------------------------------------------------------------------------------------------------------
* Finalized for removal from the Hospital IQR Program beginning with the FY 2023 payment determination, as
discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41558 through 41559).
** In the CY 2019 OPPS/ASC PPS final rule with comment period (83 FR 59140 through 59149), we finalized removal
of the Communication About Pain questions from the HCAHPS Survey effective with October 2019 discharges, for
the FY 2021 payment determination and subsequent years.
\+\ Measure is no longer endorsed by the NQF, but was endorsed at time of adoption. Section
1886(b)(3)(B)(viii)(IX)(bb) of the Act authorizes the Secretary to specify a measure that is not endorsed by
the NQF as long as due consideration is given to measures that have been endorsed or adopted by a consensus
organization identified by the Secretary. We attempted to find available measures for each of these clinical
topics that have been endorsed or adopted by a consensus organization and found no other feasible and
practical measures on the topics for the inpatient setting.
\++\ We have updated the short name for the Hospital-Level Risk-Standardized Complication Rate Following
Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA) measure (NQF #1550) measure
from Hip/Knee Complications to COMP-HIP-KNEE in order to maintain consistency with the updated Measure ID and
hospital reports for the Hospital Compare website.
b. Summary of Previously Finalized and Newly Proposed Hospital IQR
Program Measures for the FY 2023 Payment Determination
The table below summarizes the previously finalized and newly
proposed Hospital IQR Program measure set for the FY 2023 payment
determination:
Measures for the FY 2023 Payment Determination
----------------------------------------------------------------------------------------------------------------
Short name Measure name NQF No.
----------------------------------------------------------------------------------------------------------------
National Healthcare Safety Network Measures
----------------------------------------------------------------------------------------------------------------
HCP............................................. Influenza Vaccination Coverage Among 0431
Healthcare Personnel.
----------------------------------------------------------------------------------------------------------------
Claims-Based Patient Safety Measures
----------------------------------------------------------------------------------------------------------------
CMS PSI 04...................................... CMS Death Rate among Surgical Inpatients with (+)
Serious Treatable Complications.
----------------------------------------------------------------------------------------------------------------
Claims-Based Mortality Measures
----------------------------------------------------------------------------------------------------------------
MORT-30-STK..................................... Hospital 30-Day, All-Cause, N/A
Risk[dash]Standardized Mortality Rate
Following Acute Ischemic Stroke.
----------------------------------------------------------------------------------------------------------------
Claims-Based Coordination of Care Measures
----------------------------------------------------------------------------------------------------------------
READM-30-HWR *.................................. Hospital-Wide All-Cause Unplanned Readmission 1789
Measure (HWR).
[[Page 19487]]
AMI Excess Days................................. Excess Days in Acute Care after 2881
Hospitalization for Acute Myocardial
Infarction.
HF Excess Days.................................. Excess Days in Acute Care after 2880
Hospitalization for Heart Failure.
PN Excess Days.................................. Excess Days in Acute Care after 2882
Hospitalization for Pneumonia.
----------------------------------------------------------------------------------------------------------------
Claims-Based Payment Measures
----------------------------------------------------------------------------------------------------------------
AMI Payment..................................... Hospital-Level, Risk-Standardized Payment 2431
Associated with a 30-Day Episode-of-Care for
Acute Myocardial Infarction (AMI).
HF Payment...................................... Hospital-Level, Risk-Standardized Payment 2436
Associated with a 30-Day Episode-of-Care For
Heart Failure (HF).
PN Payment...................................... Hospital-Level, Risk-Standardized Payment 2579
Associated with a 30-day Episode-of-Care For
Pneumonia.
THA/TKA Payment................................. Hospital[hyphen]Level, N/A
Risk[hyphen]Standardized Payment Associated
with an Episode-of-Care for Primary Elective
Total Hip Arthroplasty and/or Total Knee
Arthroplasty.
----------------------------------------------------------------------------------------------------------------
Chart-Abstracted Clinical Process of Care Measures
----------------------------------------------------------------------------------------------------------------
PC-01........................................... Elective Delivery............................. 0469
Sepsis.......................................... Severe Sepsis and Septic Shock: Management 0500
Bundle (Composite Measure).
----------------------------------------------------------------------------------------------------------------
EHR-based Clinical Process of Care Measures (that is, Electronic Clinical Quality Measures (eCQMs))
----------------------------------------------------------------------------------------------------------------
ED-2............................................ Admit Decision Time to ED Departure Time for 0497
Admitted Patients.
Harm--ORAE **................................... Hospital Harm--Opioid-Related Adverse Events.. (\++\)
PC-05........................................... Exclusive Breast Milk Feeding................. 0480
Safe Use of Opioids **.......................... Safe Use of Opioids--Concurrent Prescribing... 3316e
STK-02.......................................... Discharged on Antithrombotic Therapy.......... 0435
STK-03.......................................... Anticoagulation Therapy for Atrial 0436
Fibrillation/Flutter.
STK-05.......................................... Antithrombotic Therapy by the End of Hospital 0438
Day Two.
STK-06.......................................... Discharged on Statin Medication............... 0439
VTE-1........................................... Venous Thromboembolism Prophylaxis............ 0371
VTE-2........................................... Intensive Care Unit Venous Thromboembolism 0372
Prophylaxis.
----------------------------------------------------------------------------------------------------------------
Patient Experience of Care Survey Measures
----------------------------------------------------------------------------------------------------------------
HCAHPS.......................................... Hospital Consumer Assessment of Healthcare 0166 (0228)
Providers and Systems Survey (including Care
Transition Measure).
----------------------------------------------------------------------------------------------------------------
* In section VIII.A.6. of the preamble of this proposed rule, we are proposing to remove the claims-only
Hospital-Wide All-Cause Unplanned Readmission (HWR claims-only) measure (NQF #1789) and in VIII.A.5.b. of the
preamble of this proposed rule we are proposing to replace it with the Hybrid Hospital-Wide Readmission
Measure with Claims and Electronic Health Record Data (NQF #2879) (Hybrid HWR measure), beginning with the FY
2026 payment determination. The proposed removal of the HWR claims-only measure is contingent on our
finalizing our proposal to adopt the Hybrid HWR measure. We are proposing to align the removal of the HWR
claims only measure such that its removal aligns with the end of the proposed 2-year voluntary reporting
period and the beginning of the proposed mandatory data submission and public reporting of the Hybrid HWR
measure.
** Newly proposed in this proposed rule to add to the eCQM measure set, beginning with the CY 2021 reporting
period/FY 2023 payment determination.
\+\ Measure is no longer endorsed by the NQF but was endorsed at time of adoption. Section
1886(b)(3)(B)(viii)(IX)(bb) of the Act authorizes the Secretary to specify a measure that is not endorsed by
the NQF as long as due consideration is given to measures that have been endorsed or adopted by a consensus
organization identified by the Secretary. We attempted to find available measures for each of these clinical
topics that have been endorsed or adopted by a consensus organization and found no other feasible and
practical measures on the topics for the inpatient setting.
\++\ This measure was submitted for endorsement by NQF's Patient Safety Standing Committee for the Spring 2019
cycle, with a complete review of measure validity and reliability current scheduled for June 2019.
8. Potential Future Quality Measures
In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53510 through
53512), we outlined considerations to guide us in selecting new quality
measures to adopt into the Hospital IQR Program. We also refer readers
to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41147 through 41148),
where we describe the Meaningful Measures Initiative and the quality
priorities and high impact measurement areas under the Meaningful
Measures framework that we have identified as relevant and meaningful
to both patients and providers. In keeping with these considerations,
we are inviting public comment on the possible future inclusion of the
following three measures in the Hospital IQR Program. We note that
these measures are also being considered for potential future inclusion
in the Promoting Interoperability Program.
a. Hospital Harm--Severe Hypoglycemia eCQM
(1) Background
Hypoglycemic events in the hospital are among the most common
adverse drug events.\482\ Hypoglycemia can cause a wide range of
symptoms, including mild symptoms of dizziness, sweating, and confusion
to more severe symptoms such as seizure, tachycardia or loss of
consciousness. Most individuals with hypoglycemia recover fully, but in
rare instances, hypoglycemia can progress to coma and death.\483\
Hypoglycemia (defined as a blood glucose level of less than 70 mg/dl in
this study) is associated with higher in-hospital mortality, increased
length of stay, and consequently, increased resource use.\484\ In a
2003-2004 study examining clinical outcomes associated with
hypoglycemia in hospitalized people with diabetes, patients who had at
least one hypoglycemic episode (a blood glucose level of less than 50
mg/dL) were hospitalized 2.8 days longer than patients who did not
experience hypoglycemia.\485\ Another retrospective cohort study showed
hospitalized patients with diabetes who experienced
[[Page 19488]]
hypoglycemia (a blood glucose level of less than 70 mg/dL) had higher
medical costs (by 38.9 percent), longer length of stay (by 3.0 days),
and higher odds of being discharged to a skilled nursing facility (odds
ratio 1.58; 95 percent Confidence Interval 1.48-1.69) than patients
with diabetes without hypoglycemia (phttps://health.gov/hcq/pdfs/ADE-Action-Plan-508c.pdf.
\483\ Diabetes Control and Complications Trial Research Group.
(1993). The effect of intensive treatment of diabetes on the
development and progression of long-term complications in insulin-
dependent diabetes mellitus. New England Journal of Medicine,
329(14): 977-86.
\484\ Krinsley, J.S., Schultz, M.J., Spronk, P.E., van Braam
Houckgeest, F., van der Sluijs, J.P., Melot, C. & Preiser, J.C.
(2011). Mild hypoglycemia is strongly associated with increased
intensive care unit length of stay. Ann Intensive Care, 1, 49.
\485\ Turchin, A., Matheny, M.E., Shubina, M., Scanlon, J.V.,
Greenwood, B., & Pendergrass, M.L. (2009). Hypoglycemia and clinical
outcomes in patients with diabetes hospitalized in the general ward.
Diabetes Care, 32(7): 1153-57.
\486\ Curkendall, S.M., Natoli, J.L., Alexander, C.M.,
Nathanson, B.H., Haidar, T., & Dubois, R.W. (2009). Economic and
clinical impact of inpatient diabetic hypoglycemia. Endocrine
Practice, 15(4): 302-312.
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The rate of severe hypoglycemia (a blood glucose level of less than
40 mg/dL) varies across hospitals indicating an opportunity for
improvement in care. Severe hypoglycemia rates have been reported to
range from 2.3 percent to 5 percent of hospitalized patients with
diabetes, and from 0.4 percent of non-ICU patient days to 1.9 percent
of ICU patient days.487 488 489 Severe hypoglycemic events
are largely avoidable by careful use of anti-diabetic medication and
close monitoring of blood glucose values.
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\487\ Nirantharakumar, K., Marshall, T., Kennedy, A., Narendran,
P., Hemming, K., & Coleman, J.J. (2012). Hypoglycemia is associated
with increased length of stay and mortality in people with diabetes
who are hospitalized. Diabetic Medicine, 29(12): e445-e448.
\488\ Wexler, D.J., Meigs, J.B., Cagliero, E., Nathan, D.M., &
Grant, R.W. (2007). Prevalence of hyper- and hypoglycemia among
inpatients with diabetes: A national survey of 44 U.S. hospitals.
Diabetes Care, 30(2): 367-369.
\489\ Cook, C.B., Kongable, G.L., Potter, D.J., Abad, V.J.,
Leija, D.E., & Anderson, M. (2009). Inpatient glucose control: A
glycemic survey of 126 U.S. hospitals. Journal of Hospital Medicine,
4(9): E7-E14.
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Although there are many occurrences of hypoglycemia in hospital
settings, many of which are preventable, there is currently no measure
in a CMS quality program that quantifies how often hypoglycemic events
happen to patients while in inpatient acute care. AHRQ identified
insulin and other hypoglycemic agents as high-alert medications and
associated adverse drug events to be included as a measure in the
Medicare Patient Safety Monitoring System (MPSMS),\490\ signifying the
importance of measuring this hospital harm. Unlike the MPSMS which
relies on chart abstracted data, the Hospital Harm--Severe Hypoglycemia
eCQM identifies hypoglycemic events using direct extraction of
structured data from the EHR. In addition, the National Action Plan for
Adverse Drug Event Prevention notes the opportunity for health care
quality reporting measures and meaningful utilization of EHR data to
advance hypoglycemic adverse drug event prevention.\491\ To address
these gaps in measurement, we developed the Hospital Harm--Severe
Hypoglycemia eCQM to identify the rates of severe hypoglycemic events
using direct extraction of structured data from the EHR. We believe
this measure will provide reliable and timely measurement of the rate
at which severe hypoglycemia events occur in the setting of hospital
administration of medication during hospitalization, which will create
transparency for providers and patients with respect to variation in
rates of these events among hospitals.
---------------------------------------------------------------------------
\490\ Classen, DC, Jaser, L., Budnitz, D.S. (2010). Adverse Drug
Events among Hospitalized Medicare Patients: Epidemiology and
national estimates from a new approach to surveillance. Joint
Commission Journal on Quality and Patient Safety, 36(1): 12-21.
\491\ Office of Disease Prevention and Health Promotion. (2014).
National Action Plan for Adverse Drug Event Prevention. Available
at: https://health.gov/hcq/pdfs/ADE-Action-Plan-508c.pdf.
---------------------------------------------------------------------------
(2) Overview of Measure
The Hospital Harm--Severe Hypoglycemia eCQM is an outcome measure
focusing specifically on in-hospital severe hypoglycemic events in the
setting of hospital administered antihyperglycemic medications. The
measure identifies the proportion of patients who experienced a severe
hypoglycemic event using a low glucose test result of less than 40 mg/
dL, within 24 hours of the administration of an antihyperglycemic
agent, which indicates harm to a patient. The intent of this measure is
for hospitals to track and improve their practices of appropriate
dosing and adequate monitoring of patients receiving glycemic control
agents, and to avoid patient harm leading to increased risk of
mortality and disability. This measure addresses the quality priority
of ``Making Care Safer by Reducing Harm Caused in the Delivery of
Care'' through the Meaningful Measure Area of ``Preventable Healthcare
Harm.'' \492\
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\492\ More information on CMS' Meaningful Measures Initiative
can be found at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.html.
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This measure is a respecification of a measure of hypoglycemia
originally endorsed by the NQF, Glycemic Control--Severe Hypoglycemia
(NQF #2363).\493\ The original measure was not implementable because
the MAT could not support the measure as specified when it was
originally developed due to limitations in the Quality Data Model (QDM)
to express the measure logic or syntax as specified. The measure was
respecified using the updates to the MAT including expression of the
logic with CQL to create a measure that can now be implemented.
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\493\ For more information on the Glycemic Control--Severe
Hypoglycemia measure, we refer readers to the measure
specifications, available at: http://www.qualityforum.org/QPS/MeasureDetails.aspx?standardID=2363&print=1&entityTypeID=1.
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The Hospital Harm--Severe Hypoglycemia (MUC18-109) measure was
included in the publicly available ``List of Measures Under
Consideration for December 1, 2018.'' \494\ This measure was reviewed
by the NQF MAP Hospital Workgroup in December 2018 and received
conditional support pending NQF review and reendorsement once the
revised measure is fully tested.495 496 MAP stakeholders
agreed that severe hypoglycemia events are largely avoidable by careful
use of antihyperglycemic medication and blood glucose monitoring. The
MAP recommended continuously assessing the low blood glucose threshold
of http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
\495\ 2018-2019 Spreadsheet of Final Recommendations to HHS and
CMS. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
\496\ National Quality Forum, Measure Applications Partnership,
MAP 2019 Considerations for Implementing Measures in Federal
Programs: Hospitals. Available at: http://www.qualityforum.org/Publications/2019/02/MAP_2019_Considerations_for_Implementing_Measures_Final_Report_-_Hospitals.aspx.
\497\ Measure Applications Partnership, December 2018 NQF MAP
Hospital Workgroup Meeting Transcript. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
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(3) Data Sources
The data source for this measure is entirely EHR data. The measure
is designed to be calculated by the hospitals' EHRs as well as by CMS
using the patient level data submitted by hospitals to CMS.
As with all quality measures we develop, testing was performed to
establish the feasibility of the measure, data elements, and validity
of the numerator, using clinical adjudicators who validated the EHR
data compared with medical chart-abstracted data. Testing was completed
using output from the MAT in multiple hospitals, using multiple EHR
systems, with the measure shown to be both reliable and valid.
(4) Measure Calculation
This measure assesses the rate at which severe hypoglycemia events
caused by hospital administration of medications occur in the acute
care hospital setting. It assesses the proportion of patients who had
an antihyperglycemic medication given within the 24 hours prior to the
harm event; and a laboratory test for glucose with a result of low
glucose (less than 40 mg/dL); and no subsequent laboratory test for
glucose with a result greater than 80 mg/dL within 5 minutes of the low
glucose result. This measure only counts one severe hypoglycemia event
per patient admission.
The measure denominator includes all patients 18 years or older
discharged from an inpatient hospital encounter during the measurement
period, who were administered at least one antihyperglycemic medication
during their hospital stay. The measure includes inpatient admissions
for patients initially seen in the emergency department or in
observation status and subsequently became an inpatient. There are no
denominator exclusions for this measure.
The numerator for this measure is the number of hospitalized
patients with a blood glucose test result of less than 40 mg/dL
(indicating severe hypoglycemia) with no repeat glucose test result
greater than 80 mg/dL within 5 minutes of the low glucose test, and
where an antihyperglycemic medication was administered within 24 hours
prior to the low glucose result. We counted instances of low glucose of
less than 40 mg/dL to identify only severe cases of hypoglycemia. Not
including severe hypoglycemic events with a repeat test over 80 mg/dL
within 5 minutes is to avoid counting false positives (mostly from
point-of-care tests that might have returned an initial erroneous
result). There are no numerator exclusions for this measure.
For more information on the Hospital Harm--Severe Hypoglycemia
eCQM, we refer readers to the measure specifications available on the
CMS Measure Methodology website, at: https://www.cms.gov/medicare/
quality-initiatives-patient-assessment-instruments/
hospitalqualityinits/measure-methodology.html.
(5) Outcome
The outcome of interest is to reduce the rate of severe
hypoglycemia events caused by hospital administration of medications
that occur in the acute care hospital setting.
In evaluating our measures, we generally consider the following
criteria in determining whether risk adjustment is warranted: (1) If
many patients are at risk of the harm regardless of their age, clinical
status, comorbidities, or reason for admission; (2) if the majority of
incidents of the harm are linkable to care provision under the control
of providers (for example, harms caused by excessive or inappropriate
medication dosing); and (3) if there is evidence that the risk of a
harm can be largely ameliorated by best care practices regardless of a
patient's inherent risk profile. For example, there may be evidence
that even complex patients with multiple risk factors can avoid harm
events when providers closely adhere to care guidelines.
In the case of the Hospital Harm--Severe Hypoglycemia eCQM, there
is evidence indicating that most hypoglycemic events of this severity
(498 499 500 501 Although specific
patients may be particularly vulnerable to hypoglycemia in certain
settings (for example, due to organ failure and not related to
administration of diabetic agents), the most common causes are lack of
caloric intake, overuse of anti-diabetic agents, or both. As these
causes are controllable in hospital environments, and risk can easily
be reduced by following best practices, we do not think risk adjustment
is warranted for this measure. We will continue to evaluate the
appropriateness of risk adjustment in measure reevaluation.
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\498\ Cook, C.B., Kongable, G.L., Potter, D.J., Abad, V.J.,
Leija, D.E., & Anderson, M. (2009). Inpatient glucose control: A
glycemic survey of 126 U.S. hospitals. Journal of Hospital Medicine,
4(9), E7-E14.
\499\ Moghissi, E.S., Korytkowski, M.T., DiNardo, M., et al.
(2009). American Association of Clinical Endocrinologists and
American Diabetes Association Consensus Statement on Inpatient
Glycemic Control. Diabetes Care, 32(6):1119-1131.
\500\ Office of the Inspector General (OIG). (2010). Adverse
Events in Hospitals: National Incidence Among Medicare
Beneficiaries.
\501\ Wexler, D.J., Meigs, J.B., Cagliero, E., Nathan, D.M., &
Grant, R.W. (2007). Prevalence of hyper- and hypoglycemia among
inpatients with diabetes: A national survey of 44 U.S. hospitals.
Diabetes Care, 30(2): 367-69.
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We are inviting public comment on potential future inclusion of the
Hospital Harm--Severe Hypoglycemia eCQM in the Hospital IQR Program,
including any potential unintended consequences that might result from
future adoption of this measure, as well as ways to address those
potential unintended consequences. We note that we are also considering
this measure for potential future inclusion in the Promoting
Interoperability Program.
b. Hospital Harm--Pressure Injury eCQM
(1) Background
Pressure injuries are a common patient hospital harm and can be
serious health events. An estimated 1.19 million hospital acquired
pressure injuries occurred in the year 2015.\502\ Pressure injuries
commonly can lead to local infection, osteomyelitis, anemia, and
sepsis,\503\ in addition to causing significant depression, pain, and
discomfort to patients.\504\ The presence or development of a pressure
injury can increase the length of a patient's hospital stay by an
average of four days, which can increase the spending ranging from
$20,900 to $151,700 per pressure injury.505 506
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\502\ Agency for Healthcare Research and Quality. National
Scorecard on Rates of Hospital-Acquired Conditions 2010 to 2015:
Interim Data From National Efforts to Make Health Care Safer.
(2016). Available at: https://www.ahrq.gov/professionals/quality-patient-safety/pfp/2015-interim.html?utm_source=AHRQ&utm_medium=PSLS&utm_term=&utm_content=14
&utm_campaign=AHRQ_NSOHAC_2016.
\503\ Brem, H., Maggi, J., Nierman, D., Rolnitzky, L., Bell, D.,
Rennert, R., Golinko, M., Yan, A., Lyder, C., Vladeck, B. (2010).
High cost of stage IV. The American Journal of Surgery, 200: 473-
477.
\504\ Gunningberg, L., Donaldson, N., Aydin, C. & Idvall, E.
(2012). Exploring variation in pressure ulcer prevalence in Sweden
and the USA: benchmarking in action. Journal of Evaluation in
Clinical Practice, 18: 904-910.
\505\ Agency for Healthcare Research and Quality. National
Scorecard on Rates of Hospital-Acquired Conditions 2010 to 2015:
Interim Data From National Efforts to Make Health Care Safer.
(2016). Available at: https://www.ahrq.gov/professionals/quality-patient-safety/pfp/2015-interim.html?utm_source=AHRQ&utm_medium=PSLS&utm_term=&utm_content=14
&utm_campaign=AHRQ_NSOHAC_2016.
\506\ Bauer, K., Rock, K., Nazzai, M.J., & Qu, W. (2016).
Pressure Ulcers in the United States Inpatient Population from 2008
to 2012: Results of a Retrospective Nationwide Study. Ostomy Wound
Management, 62(11): 30-38.
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[[Page 19490]]
The rate of pressure injuries varies across hospitals suggesting
that there may be opportunity for further improvement. One study of
51,842 patients found that 4.5 percent of patients developed at least
one new pressure injury during their hospitalization, with a 3.2
percent between-state variance.\507\ Another study revealed pressure
injury prevalence rates in U.S. hospitals participating in a registry
was 2.0 percent for hospital-acquired pressure injuries,\508\ while a
third national study found 1.8 percent of inpatients had at least one
pressure injury based on ICD-9 codes.\509\ Pressure injury is
considered a serious reportable event by the NQF,\510\ CMS established
non-payment for pressure injury,\511\ and it is an indicator of the
quality of nursing care a hospital provides.\512\ It is well-accepted
that pressure injury can be reduced through best practices \513\ such
as frequent repositioning, proper skin care, and specialized cushions
or beds.\514\ AHRQ published data that showed 3.1 million fewer
incidents of hospital-acquired harm in 2011-2015 compared with 2010; 23
percent of this reduction was from a reduction in hospital-acquired
pressure injuries.\515\ Research has also suggested a link between a
hospital's processes of care and the outcome of hospital-acquired
pressure injury.\516\ We therefore believe that pressure injuries are
an important issue to address in the Hospital IQR Program.
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\507\ Lyder, C.H., Wang, Y., Metersky, M., Curry, M., Kliman,
R., Verzier, N.R., Hunt, D.R. (2012). Hospital-acquired pressure
ulcers: results from the national Medicare Patient Safety Monitoring
System study. Journal of American Geriatrics Society, 60(9): 1603-8.
\508\ Gunningberg, L., Donaldson, N., Aydin, C. & Idvall, E.
(2012). Exploring variation in pressure ulcer prevalence in Sweden
and the USA: benchmarking in action. Journal of Evaluation in
Clinical Practice, 18: 904-910.
\509\ Bauer, K., Rock, K., Nazzai, M.J., & Qu, W. (2016).
Pressure Ulcers in the United States Inpatient Population from 2008
to 2012: Results of a Retrospective Nationwide Study. Ostomy Wound
Management, 62(11): 30-38.
\510\ National Quality Forum, List of SREs. Available at: http://www.qualityforum.org/Topics/SREs/List_of_SREs.aspx.
\511\ Centers for Medicare & Medicaid Services. Hospital-
Acquired Conditions. Available at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HospitalAcqCond/Hospital-Acquired_Conditions.html.
\512\ National Quality Forum. (2004). National Voluntary
Consensus Standards for Nursing-Sensitive Care: An Initial
Performance Measure Set 2005. Available at: http://www.qualityforum.org/Publications/2004/10/National_Voluntary_Consensus_Standards_for_Nursing-Sensitive_Care__An_Initial_Performance_Measure_Set.aspx.
\513\ Agency for Healthcare Research and Quality. (2012).
Preventing Pressure Ulcers in Hospitals: A Toolkit for Improving
Quality of Care. Available at: https://www.ahrq.gov/sites/default/files/publications/files/putoolkit.pdf.
\514\ Gunningberg, L., Donaldson, N., Aydin, C. & Idvall, E.
(2012). Exploring variation in pressure ulcer prevalence in Sweden
and the USA: benchmarking in action. Journal of Evaluation in
Clinical Practice, 18: 904-910.
\515\ Agency for Healthcare Research and Quality. (2016).
National Scorecard on Rates of Hospital-Acquired Conditions 2010-
2015: Interim Data From Nation Efforts to Make Health Care Safer.
Available at: https://www.ahrq.gov/professionals/quality-patient-safety/pfp/2015-interim.html.
\516\ Gunningberg, L., Donaldson, N., Aydin, C. & Idvall, E.
(2012). Exploring variation in pressure ulcer prevalence in Sweden
and the USA: benchmarking in action. Journal of Evaluation in
Clinical Practice, 18: 904-910.
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(2) Overview of Measure
The intent of the Hospital Harm--Pressure Injury eCQM is to reduce
pressure injury prevalence by creating transparency in the rate of
these harms which should encourage hospitals to promote best practices
such as frequent monitoring of patients at high risk, documenting skin
assessments, frequent repositioning, proper skin care, and use of
specialized cushions or beds. This measure identifies pressure injuries
using direct extraction of structured data from the EHR and will
provide hospitals with reliable and timely measurement of their
pressure injury rates as well as creating transparency for providers
and patients about the variation in rates of these events among
hospitals. Pressure injuries staged 3 and staged 4 (or unstageable) are
currently measured and publicly reported in the HAC Reduction Program
as a component of the CMS Patient Safety and Adverse Events Composite
(CMS PSI 90) measure, but this potential Hospital Harm--Pressure Injury
measure improves measurement of pressure injuries by using EHR data
rather than administrative claims.
The Hospital Harm--Pressure Injury eCQM was included in the
publicly available document entitled ``List of Measures Under
Consideration for December 1, 2018.'' \517\ This measure was reviewed
by the NQF MAP Hospital Workgroup in December 2018 and received
conditional support pending NQF review and endorsement once the measure
is fully tested.\518\ The MAP expressed their broad support for the
measure and agreed this measure can reduce patient harm due to pressure
injury. Recommendations from the MAP included, excluding patients
undergoing certain types of treatment that may not be appropriate to
receive evidence-based pressure injury reducing interventions, such as
patients at the end of life, as well as considering clinical data such
as albumin if the measure were to be risk adjusted in the future. The
MAP also recommended that the developer consider how multiple pressure
injuries are identified and assessed in the same encounter. Based on
the evidence gathered during testing and expert input, the measure is
currently not risk adjusted and it does not exclude patients with
certain conditions from the denominator as evidence shows that most
newly acquired pressure injuries can be mitigated through best care and
the most common causes of pressure injuries (limited mobility during
acute illness, friction against skin) put all hospitalized patients at
similar risk.519 520 This measure only includes one event
per hospitalization, which was supported by the TEP during measure
development, to provide a quality signal without imposing undue burden
on hospitals to have to enumerate every instance of a pressure injury.
However, this measure was submitted for endorsement by NQF's Patient
Safety Standing Committee for the Spring 2019 cycle, and these aspects
of the measure specifications will be considered during NQF scientific
review currently scheduled for June 2019. For additional information
and discussion of concerns and considerations raised by the MAP related
to the measure, we refer readers to the December 2018 NQF MAP Hospital
Workgroup meeting transcript.\521\
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\517\ List of Measures Under Consideration for December 1, 2018.
Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
\518\ 2018-2019 Spreadsheet of Final Recommendations to HHS and
CMS. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
\519\ Gunningberg, L., Donaldson, N., Aydin, C., Idvall, E.
(2011). Exploring variation in pressure ulcer prevalence in Sweden
and the USA: Benchmarking in action. 18. 10.1111/j.1365-
2753.2011.01702.x. Journal of evaluation in clinical practice., 904-
910.
\520\ Berlowitz, D., VanDeusen Lukas, C., Parker, V.,
Niederhauser, A., Silver, J., Logan, C., Ayello, E., Zulkowski, K.
(2012). Preventing Pressure Ulcers in Hospitals--A Toolkit for
Improving Quality of Care.
\521\ Measure Application Partnership, 2018 NQF MAP Hospital
Workgroup Meeting Transcript. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
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[[Page 19491]]
(3) Data Sources
The data source for this measure is entirely EHR data. The measure
is designed to be calculated by the hospitals' EHRs, as well as by CMS
using the patient level data submitted by hospitals to CMS.
As with all quality measures we develop, testing was performed to
confirm the feasibility of the measure, data elements, and validity of
the numerator, using clinical adjudicators who validated the EHR data
by comparison to medical chart abstracted data. Testing was completed
using output from the MAT in multiple hospitals, using multiple EHR
systems, and the measure was shown to be both reliable and valid. In
addition, testing showed data element feasibility is higher at
hospitals with a designated ``pressure injury'' field in the EHR, as
opposed to a generic ``wound'' field.
(4) Measure Calculation
This measure assesses the rate at which new hospital-acquired
pressure injuries occur during an acute care hospitalization. It
assesses the proportion of encounters with a newly developed stage 2,
stage 3, stage 4, deep tissue pressure injury, or unstageable pressure
injury during hospitalization.
The measure denominator includes all patients 18 years or older
discharged from an inpatient hospital encounter during the measurement
period. The measure includes inpatient admissions for patients
initially seen in the emergency department or in observation status.
There are no exclusions for this measure.
The numerator for this electronic outcome measure is defined as the
number of admissions where a patient has a newly-developed pressure
injury stage 2, stage 3, stage 4, deep tissue pressure injury, or
unstageable pressure injury that was not documented as present in the
first 24 hours of hospital arrival. Measure developers and guideline
organizations recommend skin assessment within 24 hours of hospital
arrival.522 523 524 525 This measure assumes that any
pressure injury not documented within 24 hours of arrival is hospital-
acquired. For more information on the Hospital Harm--Pressure Injury
eCQM, we refer readers to the measure specifications available on the
CMS Measure Methodology website, at: https://www.cms.gov/medicare/
quality-initiatives-patient-assessment-instruments/
hospitalqualityinits/measure-methodology.html.
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\522\ National Pressure Ulcer Advisory Panel. (2016). NPAUAP
Pressure Injury Stages. Available at: http://www.npuap.org/resources/educational-and-clinical-resources/npuap-pressure-injury-stages/.
\523\ Agency for Healthcare Research and Quality. (2012).
Preventing Pressure Ulcers in Hospitals: A Toolkit for Improving
Quality of Care. Available at: https://www.ahrq.gov/sites/default/files/publications/files/putoolkit.pdf.
\524\ Catania, K. et al. (2007). PUPPI: The Pressure Ulcer
Prevention Protocol Interventions. American Journal of Nursing,
107(4): 44-52.
\525\ National Quality Forum. (2004). National Voluntary
Consensus Standards for Nursing-Sensitive Care: An Initial
Performance Measure Set 2005. Available at: http://www.qualityforum.org/Publications/2004/10/National_Voluntary_Consensus_Standards_for_Nursing-Sensitive_Care__An_Initial_Performance_Measure_Set.aspx.
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(5) Outcome
The outcome of interest is to reduce the rate at which new
hospital-acquired pressure injuries occur during an acute care
hospitalization.
In evaluating our measures, we generally consider the following
criteria in determining whether risk adjustment is warranted: (1) If
many patients are at risk of the harm regardless of their age, clinical
status, comorbidities, or reason for admission; (2) if the majority of
incidents of the harm are linkable to care provision under the control
of providers (for example, harms caused by inappropriate skin care or
lack of frequent repositioning); and (3) if there is evidence that the
risk of a harm can be largely ameliorated by best care practices
regardless of a patient's inherent risk profile. For example, there may
be evidence that even complex patients with multiple risk factors can
avoid harm events when providers closely adhere to care guidelines.
In the case of the Hospital Harm-Pressure Injury eCQM, there is
evidence indicating that most newly acquired pressure injuries are
avoidable with best practice.526 527 Although specific
patients may be particularly vulnerable to pressure injuries in certain
settings (for example, permanent or prolonged immobility), the most
common causes are limited mobility during an acute illness and friction
or shear against sensitive skin. Many hospitalized patients are at risk
of these injuries. There are many actions hospitals can take to reduce
patient harm risk, such as conducting a structured risk assessment to
identify individuals at risk for pressure injury as soon as possible
upon arrival and repeating at regular intervals, as well as proper skin
care, nutrition, and careful repositioning of patients. As many of the
causes can be mitigated through best care in hospital environments, we
do not think risk adjustment is warranted for this measure. We will
continue to evaluate the appropriateness of risk adjustment in measure
reevaluation.
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\526\ Gunningberg, L., Donaldson, N., Aydin, C., Idvall, E.
(2011). Exploring variation in pressure ulcer prevalence in Sweden
and the USA: Benchmarking in action. 18. 10.1111/j.1365-
2753.2011.01702.x. Journal of evaluation in clinical practice., 904-
910.
\527\ Berlowitz, D., VanDeusen Lukas, C., Parker, V.,
Niederhauser, A., Silver, J., Logan, C., Ayello, E., Zulkowski, K.
(2012). Preventing Pressure Ulcers in Hospitals--A Toolkit for
Improving Quality of Care.
---------------------------------------------------------------------------
We are inviting public comment on potential future inclusion of the
Hospital Harm--Pressure Injury eCQM in the Hospital IQR Program. We are
specifically seeking public comment on any unintended consequences that
might result from future adoption of this measure, as well as ways to
address those potential unintended consequences. We note that we are
also considering this measure for potential future inclusion in the
Promoting Interoperability Program.
c. Cesarean Birth (PC-02) eCQM (NQF #0471e)
(1) Background
A Cesarean section (C-section) is the use of surgery to deliver a
baby (or babies) in lieu of vaginal delivery. The procedure therefore
entails surgical and anesthesia risks and requires mothers to undergo
several days of inpatient, postoperative recovery. A C-section may
occur on an emergency basis or elective basis.\528\ Elective C-sections
may be necessary due to preexisting medical conditions, such as high
blood pressure (preeclampsia), other medical indications, or may be
preferred for non-medical reasons. Non-medical reasons for elective C-
section can relate to maternal preference, local practice patterns,
fear of malpractice litigation, reimbursement anomalies, or other
factors.529 530 531
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\528\ National Quality Forum, Quality Measure PC-02 (Cesarean
Birth). Available at: https://www.qualityforum.org/QPS/MeasureDetails.aspx?standardID=291&print=1&entityTypeID=1.
\529\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. Safe prevention
of the primary cesarean delivery. Am J Obstet Gynecol. 2014
Mar;210(3):179-93. doi: 10.1016/j.ajog.2014.01.026.
\530\ Schifrin BS, Cohen WR. The effect of malpractice claims on
the use of caesarean section. Best Pract Res Clin Obstet Gynaecol.
2013 Apr;27(2):269-83. doi: 10.1016/j.bpobgyn.2012.10.004. Epub 2012
Dec 1. Review.
\531\ Chen CS, Liu TC, Chen B, Lin CL. The failure of financial
incentive? The seemingly inexorable rise of cesarean section. Soc
Sci Med. 2014 Jan;101:47-51. doi: 10.1016/j.socscimed.2013.11.010.
Epub 2013 Nov 15.
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The total rate of (emergency and elective) C-sections has risen
since the 1990s in the United States.\532\ C-sections
[[Page 19492]]
accounted for about one-third of U.S. deliveries in 2016,\533\ and
there is a considerable amount of variation in the rates based on U.S.
region, State, and healthcare institution.\534\ U.S. practice
guidelines have not indicated an optimal rate of C-section or an
appropriate variance rate, but international studies suggest a
preference for a lower range than current U.S.
rates.535 536 537 When medically justified, a C-section can
effectively prevent maternal and perinatal mortality and morbidities.
However, clinicians and consensus groups agree that increased C-section
rates have not improved overall maternal-fetal outcomes and that C-
sections are overused.538 539 Below, we include literature
outlining maternal and neonatal C-section outcomes.
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\532\ Osterman, M.J.K., Martin, J.A. (2014). Trends in Low-risk
Cesarean Delivery in the United States, 1990-2013. National Vital
Statistics Reports, 63(6): 1-16.
\533\ Martin, J.A., Hamilton, B.E., Osterman, M.J.K., Driscoll,
A.K., Drake, P. (2018). Births: Final Data for 2016. National Vital
Statistics Reports, 67(1): 1-55.
\534\ Kozhimannil, K.B., Law, M.R. & Virnig, B.A. (2013).
Cesarean delivery rates vary tenfold among US hospitals; reducing
variation may address quality and cost issues. Health Affairs,
32(3): 527-35.
\535\ National Collaborating Centre for Women's and Children's
Health. (2011). Caesarean Section: NICE Clinical Guideline
(commissioned by the United Kingdom National Institute for Health
and Clinical Excellence).
\536\ American College of Obstetricians and Gynecologists,
Society for Maternal-Fetal Medicine. (2014). Safe prevention of the
primary cesarean delivery. American Journal of Obstetrics and
Gynecology, 210(3): 179-93.
\537\ Keag, O.E., Norman, J.E. & Stock, S.J. (2018). Long-term
risks and benefits associated with cesarean delivery for mother,
baby, and subsequent pregnancies: Systematic review and meta-
analysis. Plos Med, 15(1): e1002494.
\538\ American College of Obstetricians and Gynecologists,
Society for Maternal-Fetal Medicine. (2014). Safe prevention of the
primary cesarean delivery. American Journal of Obstetrics and
Gynecology, 210(3): 179-93.
\539\ National Collaborating Centre for Women's and Children's
Health. (2011). Caesarean Section: NICE Clinical Guideline
(commissioned by the United Kingdom National Institute for Health
and Clinical Excellence).
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For maternal outcomes, C-sections have significantly higher
prenatal and postpartum morbidity and mortality (9.2 percent) than
vaginal births (8.6 percent).\540\ Existing literature largely does not
distinguish whether inferior outcomes derive from cause (higher risk
patients undergo C-section) or effect (surgery carries inherent risks
due to anesthesia, bleeding, infection, postoperative recovery, etc.).
However, taking an aggregate view of multiple studies over time, it
appears that C-sections carry a higher risk of subsequent miscarriage,
placental abnormalities, and repeat C-section.\541\ Conversely, urinary
incontinence and pelvic organ prolapse occur less frequently after C-
section than after vaginal delivery.\542\
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\540\ American College of Obstetricians and Gynecologists,
Society for Maternal-Fetal Medicine. (2014). Safe prevention of the
primary cesarean delivery. American Journal of Obstetrics and
Gynecology, 210(3): 179-93.
\541\ Keag, O.E., Norman, J.E. & Stock, S.J. (2018). Long-term
risks and benefits associated with cesarean delivery for mother,
baby, and subsequent pregnancies: Systematic review and meta-
analysis. Plos Med, 15(1): e1002494.
\542\ Keag, O.E., Norman, J.E. & Stock, S.J. (2018). Long-term
risks and benefits associated with cesarean delivery for mother,
baby, and subsequent pregnancies: Systematic review and meta-
analysis. Plos Med, 15(1): e1002494.
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In terms of neonatal outcomes, C-sections have higher respiratory
morbidity (1 to 4 percent) than vaginal births (549 550 Full-term births have better
outcomes than preterm births. Vertex presentations carry less risk than
breach or transverse presentations.\551\ However, this population still
includes some patients with medical indications for elective C-section
(for example, dystocia, chorioamnionitis, pelvic deformity,
preeclampsia, fetal distress, prolapsed cord, placenta previa, abnormal
lie, uterine rupture, macrosomia).\552\ While the chart-abstracted and
eCQM versions of PC-02 do not exclude those medical indications,
extensive testing of the chart-abstracted version of the measure has
shown that excluding them does not significantly increase a hospital's
adjusted C-section rate, partially because the majority of these
indications are rare in the NTSV population.\553\
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\548\ National Quality Forum, Quality Measure PC-02 (Cesarean
Birth). Available at: https://www.qualityforum.org/QPS/MeasureDetails.aspx?standardID=291&print=1&entityTypeID=1.
\549\ American College of Obstetricians and Gynecologists,
Society for Maternal-Fetal Medicine. (2014). Safe prevention of the
primary cesarean delivery. American Journal of Obstetrics and
Gynecology, 210(3): 179-93.
\550\ National Quality Forum, Perinatal and Reproductive Health
2015-2016 Final Report. Available at: http://www.qualityforum.org/Publications/2016/12/Perinatal_and_Reproductive_Health_2015-2016_Final_Report.aspx.
\551\ American College of Obstetricians and Gynecologists,
Society for Maternal-Fetal Medicine. (2014). Safe prevention of the
primary cesarean delivery. American Journal of Obstetrics and
Gynecology, 210(3): 179-93.
\552\ Mylonas, I. & Friese, K. (2015). Indications for and Risks
of Elective Cesarean Section. Deutsches Arzteblatt International,
112(29-30): 489-95.
\553\ Centers for Medicare & Medicaid Services. (2015). Cesarean
Birth (PC-02) Measure Public Comment Summary. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/PC-02-Public-Comment-Summary-Memo.pdf. The
PC-02 eCQM cannot capture all possible medical indications. Thus,
PC-02 does not equate to elective C-section for non-medical reasons.
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[[Page 19493]]
Determining the NTSV C-section rate permits a hospital to compare
its outcomes to other hospitals while focusing only on a lower-risk
population. NQF has endorsed the chart-based form of this measure as a
voluntary consensus standard since 2008.\554\ NQF stated that
decreasing the rate of unnecessary C-sections ``will result in
increased patient safety, a substantial decrease in maternal and
neonatal morbidity and substantial savings in health care costs.''
\555\ Reducing the number of NSTV deliveries by C-section would also
reduce the rate of repeat cesarean births.\556\ We acknowledge that
there are instances where C-sections are medically indicated, and we
emphasize that this measure is not intended to discourage practitioners
from performing C-sections when they are medically indicated. We
believe that assessing the rate of NTSV C-sections may ultimately
reduce the occurrence of non-medically indicated C-sections. We have
encouraged hospitals whose measure rates are higher than rates at other
hospitals to explore and evaluate differences in the medical and
nursing management of women in labor.\557\ Further, including this
measure could help ensure that the Hospital IQR Program includes
measures which are applicable to rural hospitals. The Rural Health
Workgroup of the NQF's Measure Applications Partnership also identified
the chart-abstracted version of PC-02 as a measure that holds
particular relevance for rural hospitals, noting how important it is to
focus on best practices in obstetric care in rural areas.\558\
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\554\ National Quality Forum, Quality Measure PC-02 (Cesarean
Birth). Available at: https://www.qualityforum.org/QPS/MeasureDetails.aspx?standardID=291&print=1&entityTypeID=1.
\555\ National Quality Forum (NQF), Perinatal and Reproductive
Health Project. NQF #0471 PC-02 Cesarean Section: Measure Submission
and Evaluation Worksheet 5.0. October 24, 2008. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=69252.
\556\ Curtin, S.C., Gregory, K.D., Korst, L.M., & Uddin, S.F.
(2015). Maternal Morbidity for Vaginal and Cesarean Deliveries,
According to Previous Cesarean History: New Data From the Birth
Certificate, 2013. National Vital Statistics Reports, 64(4): 1-13.
\557\ Centers for Medicare & Medicaid Services. (2015). Cesarean
Birth (PC-02) Measure Public Comment Summary. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/PC-02-Public-Comment-Summary-Memo.pdf.
\558\ National Quality Forum, Measure Applications Partnership.
(2018). A Core Set of Rural-Relevant Measures and Measuring and
Improving Access to Care: 2018 Recommendations from the MAP Rural
Health Workgroup. Available at: http://www.qualityforum.org/Publications/2018/08/MAP_Rural_Health_Final_Report_-_2018.aspx.
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The PC-02 eCQM was included in a publicly available document
entitled ``List of Measures Under Consideration for December 1, 2018.''
\559\ The MAP Coordinating Committee voted to conditionally support the
PC-02 eCQM, citing the failure of the eCQM version of the measure to
attain endorsement by the NQF as an area of concern.\560\ The
Coordinating Committee encouraged The Joint Commission to resubmit the
eCQM version of PC-02 to the NQF for endorsement with additional
clarifying data that has been collected since the previous attempt to
attain endorsement. The MAP's Final Report of February 15, 2019,
conditionally supports the PC-02 eCQM for rulemaking pending NQF
evaluation and endorsement.\561\ The MAP suggested feasibility testing,
consultation with multiple stakeholders, and examination of unintended
consequences.
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\559\ List of Measures Under Consideration for December 1, 2018.
Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
\560\ Measure Applications Partnership, December 2018 NQF MAP
Hospital Workgroup Meeting Transcript. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
\561\ National Quality Forum, Measure Applications Partnership,
MAP 2019 Considerations for Implementing Measures in Federal
Programs: Hospitals. Available at: http://www.qualityforum.org/Publications/2019/02/MAP_2019_Considerations_for_Implementing_Measures_Final_Report_-_Hospitals.aspx.
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(3) Data Sources
Hospitals would provide data for this measure from their EHRs.
Incorporating this eCQM would align with our goal to encourage greater
use of EHR data for quality measurement.
(4) Measure Calculation
This measure assesses the rate of nulliparous women with a term,
singleton baby in a vertex position delivered by cesarean birth. As the
measure steward for both the chart-abstracted version of PC-02 (NQF
#0471) and the eCQM version (NQF #0471e), The Joint Commission
publishes a detailed methodology for its calculation.\562\
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\562\ See, for example, The Joint Commission. Specifications
Manual for Joint Commission National Quality Measures, Measure
Information Form PC-02. Available at: https://manual.jointcommission.org/releases/TJC2018A1/MIF0167.html.
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The measure's denominator consists of the number of nulliparous
women with a singleton, vertex fetus at >=37 weeks of gestation who
deliver a liveborn infant. Its numerator consists of the subset
delivering by C-section. The numerator includes women delivering by
planned C-section due to obstetric indications and for other
reasons.\563\ This measure excludes patients with abnormal
presentations or single stillbirth during the encounter, or patients
with multiple gestations recorded less than or equal to 42 weeks prior
to the end of the encounter.
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\563\ List of Measures Under Consideration for December 1, 2018.
Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
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The cohort consists of all patients in the denominator: Nulliparous
women with a singleton, vertex fetus at >=37 weeks of gestation who
deliver a liveborn infant. The cohort includes all pertinent patients
regardless of payer (for example, Medicare, Medicaid, other public
programs, private insurance, self-pay, charity care) or admission
source (for example, home, emergency department, nursing home, hospice,
another hospital, law enforcement).\564\ The cohort for a region,
hospital, and practitioner may differ from the national rate because of
higher medical indications for C-section.
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\564\ Ibid.
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(5) Outcome
The outcome of interest is the number of C-sections to nulliparous
women with a term, singleton baby in a vertex position divided by all
deliveries to nulliparous women with a term, singleton baby in a vertex
position.\565\
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\565\ The Joint Commission, Specifications Manual for Joint
Commission National Quality Measures, Measure Information Form PC-
02. Available at: https://manual.jointcommission.org/releases/TJC2018A1/MIF0167.html.
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This measure is not risk adjusted. The Joint Commission decided to
exclude risk-adjustment from this measure based on careful
consideration of a Technical Advisory Panel's recommendations and data
that indicated the results adjusted by age were sensitive to low sample
sizes and applying age as a risk factor only marginally impacted the
outcome.\566\ The Joint Commission removed all risk adjustments from
this measure, effective with discharges beginning July 1, 2016.\567\
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\566\ National Quality Forum, (2016) Perinatal and Reproductive
Health 2015-2016 Final Report. Available at: http://www.qualityforum.org/Publications/2016/12/Perinatal_and_Reproductive_Health_2015-2016_Final_Report.aspx.
\567\ National Quality Forum, Perinatal and Reproductive Health
2015-2016 Final Report. Available at: http://www.qualityforum.org/Publications/2016/12/Perinatal_and_Reproductive_Health_2015-2016_Final_Report.aspx.
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[[Page 19494]]
We are inviting public comment on potential future inclusion of the
Cesarean Birth (PC-02) eCQM (NQF #0471e) in the Hospital IQR Program.
We are specifically seeking public comment on any unintended
consequences that might result from future adoption of this measure, as
well as ways to address those potential unintended consequences. We
note that we are also considering this measure for potential future
inclusion in the Promoting Interoperability Program.
9. Accounting for Social Risk Factors: Update on Confidential Reporting
of Stratified Data for Hospital Quality Measures
a. Background
We first sought public comment on potentially publicly reporting
Hospital IQR Program measure data stratified by social risk factors in
the FY 2017 IPPS/LTCH PPS proposed rule (81 FR 57167 through 57168). In
the FY 2018 IPPS/LTCH PPS final rule (82 FR 38404), we explained that
due to the complexity of interpreting stratified measure data, we would
first consider confidentially reporting such data prior to any future
public display on the Hospital Compare website. We also noted that
providing confidential hospital-specific reports (HSRs) would enable us
to obtain hospital feedback on reporting options and ensure the
information is valid, reliable, and understandable prior to any future
public display (82 FR 38404).
In the FY 2018 IPPS/LTCH PPS rulemaking (82 FR 20070 through 20074;
38403 through 38409), we presented and responded to comments on whether
to provide hospitals with confidential results of the Hospital 30-Day,
All-Cause, Risk-Standardized Readmission Rate (RSRR) Following
Pneumonia Hospitalization (NQF #0506) (Pneumonia Readmission measure)
and the Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate
Following Pneumonia Hospitalization (NQF #0468) (Pneumonia Mortality
measure) stratified by patient dual eligible status as early as summer
of 2018, and described two potential methodologies designed to
illuminate potential disparities by calculating outcome measure results
stratified by patient dual eligible status (a within-hospital method
and an across-hospital method).\568\ We selected the two pneumonia
measures as the first measures to potentially stratify because
pneumonia is a condition that is common in the elderly population and
because the results of both measures are publicly reported for a large
cohort of hospitals (83 FR 41598).\569\ We also explained that the
additional information provided by the two disparity methods
supplements the overall readmission and mortality measure rates
publicly reported on the Hospital Compare website by highlighting
disparities based on patient dual eligible status (82 FR 38405).
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\568\ The Within-Hospital Disparity Method (also referred to as
the Dual Eligible Disparity Method for Within-Hospital Comparison)
highlights differences in outcomes for dual eligible versus non-dual
eligible patients within an individual hospital, while the Dual
Eligible Outcome Method (also referred to as the Dual Eligible
Outcome Method for Across Hospital Comparison) allows for a
comparison of performance in care for dual eligible patients across
hospitals.
\569\ Assessing Hospital Disparities for Dual Eligible Patients:
Thirty-Day All-Cause Unplanned Readmission Following Pneumonia
Hospitalization, Measure Methodology Report for 2018 Confidential
Reporting. Available at: https://www.qualitynet.org/dcs/ContentServer?cid=%201228776709103&pagename=QnetPublic%2FPage%2FQnetTier3&c=Page.
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In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41598), we explained
that as a first step, in the interest of simplicity and minimizing
confusion for hospitals, we planned to provide hospitals with
confidential HSRs containing stratified results of the Pneumonia
Readmission measure only, using both disparity methods, during a month-
long confidential reporting period in late summer of 2018. We also
noted that for the future, we were considering: (1) Expanding our
efforts to provide stratified data in confidential HSRs for other
measures; (2) including other social risk factors beyond dual eligible
status in confidential HSRs; and (3) eventually, making stratified data
publicly available on the Hospital Compare website (83 FR 41598).
Confidential HSRs containing the results of Pneumonia Readmission
measure data using the two disparity methods (disparity results) were
made available for hospitals and their QIN-QIOs to download through the
QualityNet Secure Portal from August 24 to September 24, 2018. The
confidential HSRs also contained additional information to enable a
more meaningful comparison and comprehensive assessment of the quality
of care for dual eligible patients, including a hospital's overall
Pneumonia Readmission measure rate and State and national results for
each disparity method. To ensure hospitals and stakeholders would have
sufficient information to understand and interpret their disparity
results during the confidential reporting period, background materials
and educational resources were posted on the QualityNet website,
including detailed instructions for interpreting a hospital's HSR and a
technical report describing the two disparity methods in detail.\570\
We also hosted a National Provider Call and established a monitored
email inbox to receive and address questions and comments from
hospitals and other stakeholders during the confidential reporting
period.\571\
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\570\ These materials, as well as other confidential reporting
resources such as Frequently Asked Questions (FAQs), Disparity
Methods HSR User Guide, and National Provider Call materials, are
available on the confidential reporting pages of the QualityNet
website, available at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228776708906.
\571\ Available at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228776708906.
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b. Additional Confidential Reporting of Measures Stratified Using Two
Disparity Methods
As noted above, we have been considering, among other things,
expanding our efforts to provide stratified data using the two
disparity methods in confidential HSRs for additional measures.
Although our preliminary efforts have focused on the Pneumonia
Readmission measure, the two disparity methods previously used can be
applied to other outcome measures. We believe that it is important to
expand our efforts to provide disparity results for additional outcome
measures because we believe that providing the results of both
disparity methods alongside a hospital's measure data, as a point of
reference, allows for a more meaningful comparison. As mentioned, the
disparity results could supplement the overall measure data already
publicly reported on the Hospital Compare website by providing
additional information regarding disparities measured within individual
hospitals and across hospitals nationally. The disparity results thus
enable a more comprehensive assessment of quality of care for patients
with social risk factors and identifies where disparities in health
care may exist. This approach also furthers Recommendation 2 of NQF's
Disparities Project final report to use and prioritize stratified
health equity outcome measures, wherein the two disparity methods were
highlighted as exemplary of health equity performance measure alignment
such that data collection burden is minimized, measure impact is
maximized, and peer group comparisons are enabled.\572\ We believe
[[Page 19495]]
hospitals can use their results from the disparity methods to identify
and develop strategies to reduce disparities in the quality of care for
patients with social risk factors, including targeted improvement
efforts to improve health outcomes for all of their patients, those
with and without social risk factors (83 FR 41598). As discussed in the
FY 2019 IPPS/LTCH PPS final rule (83 FR 41599), the two disparity
methods do not place any additional collection or reporting burden on
hospitals because dual eligible data are readily available in claims
data. For additional information on the two disparity methods, we refer
readers to the technical report describing the methods in detail,\573\
as well as the FY 2018 IPPS/LTCH PPS final rule (82 FR 38405 through
38407).
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\572\ National Quality Forum. (2017). A Roadmap for Promoting
Health Equity and Eliminating Disparities: The Four I's for Health
Equity. Available at: http://www.qualityforum.org/Publications/2017/09/A_Roadmap_for_Promoting_Health_Equity_and_Eliminating_Disparities__The_Four_I_s_for_Health_Equity.aspx.
\573\ Assessing Hospital Disparities for Dual Eligible Patients:
Thirty-Day All-Cause Unplanned Readmission Following Pneumonia
Hospitalization, Measure Methodology Report for 2018 Confidential
Reporting. Available at: https://www.qualitynet.org/dcs/ContentServer?cid=%201228776709103&pagename=QnetPublic%2FPage%2FQnetTier3&c=Page.
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In the spring of 2019, we will continue to provide confidential
reporting of disparity results for the Pneumonia Readmission measure in
the confidential HSRs for claims-based measures that are made available
for hospitals to download through the QualityNet Secure Portal as was
done in 2018. We are also planning to expand our efforts to apply the
two disparity methods to additional outcome measures for confidential
reporting in a phased manner. As a next step, in the spring of 2020, we
plan to add to the confidential HSRs for claims-based measures the
confidential reporting of disparity results for five additional claims-
based condition- and procedure-specific readmission measures as
follows: (1) Hospital 30-Day, All-Cause, Risk-Standardized Readmission
Rate (RSRR) Following Acute Myocardial Infarction (AMI) Hospitalization
(NQF #0505) (AMI Readmission measure); (2) Hospital 30-Day, All-Cause,
Risk-Standardized Readmission Rate (RSRR) Following Coronary Artery
Bypass Graft (CABG) Surgery (NQF #2515) (CABG Readmission measure); (3)
Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR)
Following Chronic Obstructive Pulmonary Disease (COPD) Hospitalization
(NQF #1891) (COPD Readmission measure); (4) Hospital 30-Day, All-Cause,
Risk-Standardized Readmission Rate (RSRR) Following Heart Failure (HF)
Hospitalization (NQF #0330) (HF Readmission measure); and (5) Hospital-
Level 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR)
Following Elective Primary Total Hip Arthroplasty (THA) and/or Total
Knee Arthroplasty (TKA) (NQF #1551) (THA/TKA Readmission measure). To
simplify and minimize the number of confidential HSRs that hospitals
receive, going forward we plan to include hospitals' disparity results
in the regular annual confidential HSRs for claims-based measure
results that are made available for hospitals to download through the
QualityNet Secure Portal each spring, as opposed to a separate
confidential HSR for only the confidential reporting of disparity
results as was done for the first confidential reporting of disparity
results for the Pneumonia Readmission measure in late summer of 2018.
We believe that expanding our efforts by providing disparity
results for the six condition- and procedure-specific readmission
measures discussed above, while a different set of calculations than
those used in the Hospital Readmissions Reduction Program, can
complement the stratified methodology used to assess a hospital's
performance on these measures for payment penalty scoring purposes
under the Hospital Readmissions Reduction Program. To implement the
requirements of the 21st Century Cures Act, the Hospital Readmissions
Reduction Program developed a stratification methodology to account for
social risk factors by which it assigns hospitals into five peer groups
based on proportion of dual eligible stays, and assesses hospital
performance relative to the performance of hospitals within the same
peer group.\574\ While this approach is used by the Hospital
Readmissions Reduction Program for purposes of payment calculations,
the two disparity methods are intended to account for social risk
factors by providing additional information that identifies potential
disparities in care provided to dual eligible patients within
individual hospitals and across hospitals nationally. We believe that
providing data from the two disparity methods for the readmission
measures complements the payment stratification approach using these
measures under the Hospital Readmissions Reduction Program by
increasing transparency around, and contributing to an improved
understanding of, differences in care on the basis of patient dual
eligible status. The two disparity methods and the stratified
methodology used by the Hospital Readmissions Reduction Program are all
part of CMS' broader efforts to account for social risk factors in
quality measurement and value-based purchasing programs. We note that
the confidential reporting of disparity results discussed in this
section is not driven by a specific quality program, but rather, is
intended to supplement already publicly reported measure performance
data and is only one part of CMS' overall strategy for accounting for
social risk factors. We refer readers to section IV.G.11. of the
preamble of this proposed rule for a similar discussion under the
Hospital Readmissions Reduction Program. In the future, we also plan to
provide confidential reporting of disparity results for additional
outcome measures included in other quality programs.
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\574\ As required by the 21st Century Cures Act, the Hospital
Readmissions Reduction Program implemented a transitional adjustment
methodology for dual eligible patients beginning in FY 2019. For
additional details on the stratified methodology used in the
Hospital Readmissions Reduction Program, we refer readers to the FY
2018 IPPS/LTCH PPS final rule (82 FR 38226 through 38237) and the FY
2019 IPPS/LTCH PPS final rule (83 FR 41436 through 41438).
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We plan to continue soliciting feedback from hospitals based on
their experiences with the confidential disparity methods reporting
process, which will allow hospitals to understand their disparity
results prior to any potential future public reporting. As discussed in
the FY 2019 IPPS/LTCH PPS final rule (83 FR 41600), we have not yet
determined future plans with respect to publicly reporting stratified
data, and intend to continue to engage with hospitals and relevant
stakeholders about their experiences with and recommendations for the
stratification of measure data, and to ensure the reliability of such
data before proposing to publicly display stratified measure data in
the future. Any proposal to display stratified quality measure data on
the Hospital Compare website would be made through future rulemaking.
We are inviting public comment on our plans to expand our efforts
to apply the disparity methods to additional outcome measures for
confidential reporting in a phased manner, specifically for five
additional measures (AMI Readmission measure; CABG Readmission measure;
COPD Readmission measure; HF Readmission measure; and THA/TKA
Readmission measure) starting in spring of 2020, and additional outcome
measures after spring of 2020, as discussed above. We refer readers to
section IV.G.11. of the preamble of this proposed rule for a similar
discussion under the Hospital Readmissions Reduction Program.
[[Page 19496]]
10. Form, Manner, and Timing of Quality Data Submission
a. Background
Sections 1886(b)(3)(B)(viii)(I) and (b)(3)(B)(viii)(II) of the Act
state that the applicable percentage increase for FY 2015 and each
subsequent year shall be reduced by one-quarter of such applicable
percentage increase (determined without regard to sections
1886(b)(3)(B)(ix), (xi), or (xii) of the Act) for any subsection (d)
hospital that does not submit data required to be submitted on measures
specified by the Secretary in a form and manner, and at a time,
specified by the Secretary. Previously, the applicable percentage
increase for FY 2007 and each subsequent fiscal year until FY 2015 was
reduced by 2.0 percentage points for subsection (d) hospitals failing
to submit data in accordance with the description above. In accordance
with the statute, the FY 2020 payment determination will begin the
sixth year that the Hospital IQR Program will reduce the applicable
percentage increase by one-quarter of such applicable percentage
increase.
In order to participate in the Hospital IQR Program, hospitals must
meet specific procedural, data collection, submission, and validation
requirements. For each Hospital IQR Program payment determination, we
require that hospitals submit data on each specified measure in
accordance with the measure's specifications for a particular period of
time. The data submission requirements, Specifications Manual, and
submission deadlines are posted on the QualityNet website at: http://www.QualityNet.org/. The technical specifications used for electronic
clinical quality measures (eCQMs) are contained in the CMS Annual
Update for the Hospital Quality Reporting Programs (Annual Update). We
generally update the measure specifications on an annual basis through
the Annual Update, which includes code updates, logic corrections,
alignment with current clinical guidelines, and additional guidance for
hospitals and electronic health record (EHR) vendors to use in order to
collect and submit data on eCQMs from hospital EHRs. The Annual Update
and implementation guidance documents are available on the Electronic
Clinical Quality Improvement (eCQI) Resource Center website at: https://ecqi.healthit.gov/. For example, for the CY 2019 reporting period/FY
2021 payment determination, hospitals would need to submit eCQM data
using the May 2018 Annual Update and any applicable addenda. We refer
readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41602 through
41603), in which we discuss the transition to Clinical Quality Language
(CQL) for all eCQM specifications published in CY 2018 for the CY 2019
reporting period/FY 2021 payment determination and subsequent years
(beginning with the Annual Update that was published in May 2018 for
implementation in CY 2019).
Hospitals must register and submit quality data through the secure
portion of the QualityNet website. There are safeguards in place in
accordance with the HIPAA Privacy and Security Rules to protect patient
information submitted through this website. See 45 CFR parts 160 and
164, subparts A, C and E.
b. Procedural Requirements
The Hospital IQR Program's procedural requirements are codified in
regulation at 42 CFR 412.140. We refer readers to these codified
regulations for participation requirements, as further explained by the
FY 2014 IPPS/LTCH PPS final rule (78 FR 50810 through 50811) and the FY
2017 IPPS/LTCH PPS final rule (81 FR 57168). We are not proposing any
changes to these procedural requirements in this proposed rule.
c. Data Submission Requirements for Chart-Abstracted Measures
We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR
51640 through 51641), the FY 2013 IPPS/LTCH PPS final rule (77 FR 53536
through 53537), and the FY 2014 IPPS/LTCH PPS final rule (78 FR 50811)
for details on the Hospital IQR Program data submission requirements
for chart-abstracted measures. We are not proposing any changes to the
data submission requirements for chart-abstracted measures in this
proposed rule.
d. Reporting and Submission Requirements for eCQMs
(1) Background
For a discussion of our previously finalized eCQMs and policies, we
refer readers to the FY 2014 IPPS/LTCH PPS final rule (78 FR 50807
through 50810; 50811 through 50819), the FY 2015 IPPS/LTCH PPS final
rule (79 FR 50241 through 50253; 50256 through 50259; and 50273 through
50276), the FY 2016 IPPS/LTCH PPS final rule (80 FR 49692 through
49698; and 49704 through 49709), the FY 2017 IPPS/LTCH PPS final rule
(81 FR 57150 through 57161; and 57169 through 57172), the FY 2018 IPPS/
LTCH PPS final rule (82 FR 38355 through 38361; 38386 through 38394;
38474 through 38485; and 38487 through 38493), and the FY 2019 IPPS/
LTCH PPS final rule (83 FR 41567 through 41575; 83 FR 41602 through
41607).
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38361), we finalized
eCQM reporting and submission requirements such that hospitals are
required to report only one, self-selected calendar quarter of data for
four self-selected eCQMs for the CY 2018 reporting period/FY 2020
payment determination. In the FY 2019 IPPS/LTCH PPS final rule (83 FR
41603 through 41604), we extended the same eCQM reporting and
submission requirements, such that hospitals are required to report
one, self-selected calendar quarter of data for four self-selected
eCQMs for the CY 2019 reporting period/FY 2021 payment determination.
In this proposed rule, we are proposing to establish eCQM reporting
and submission requirements for the CY 2020 reporting period/FY 2022
payment determination through the CY 2022 reporting period/FY 2024
payment determination, as detailed below.
(2) Proposed Reporting and Submission Requirements for eCQMs for the CY
2020 Reporting Period/FY 2022 Payment Determination
For the CY 2020 reporting period/FY 2022 payment determination, we
are proposing to extend the current eCQM reporting and submission
requirements, such that hospitals would be required to report one,
self-selected calendar quarter of data for four self-selected eCQMs. We
believe continuing the same eCQM reporting and submission requirements
is appropriate because it offers hospitals reporting flexibility and
does not increase the information collection burden on data submitters,
allowing them to shift resources to support system upgrades, data
mapping, and staff training related to eCQM documentation and
reporting.
We also refer readers to section VIII.D.6.d.(1) of the preamble of
this proposed rule for a similar proposal in the Promoting
Interoperability Programs for the CY 2020 reporting period.
(3) Proposed Reporting and Submission Requirements for eCQMs for the CY
2021 Reporting Period/FY 2023 Payment Determination
For the CY 2021 reporting period/FY 2023 payment determination, we
are proposing to extend the same eCQM reporting and submission
requirements, such that hospitals would continue to be required to
report one, self-selected calendar quarter of data for four self-
selected eCQMs for the same reasons as discussed above.
[[Page 19497]]
We also refer readers to section VIII.D.6.d.(1) of the preamble of
this proposed rule for a similar proposal in the Medicare Promoting
Interoperability Program.
(4) Proposed Reporting and Submission Requirements for eCQMs for the CY
2022 Reporting Period/FY 2024 Payment Determination
For the CY 2022 reporting period/FY 2024 payment determination, we
are proposing to modify the eCQM reporting and submission requirements,
such that hospitals would be required to report one, self-selected
calendar quarter of data for: (a) Three self-selected eCQMs, and (b)
the proposed Safe Use of Opioids--Concurrent Prescribing eCQM (NQF
#3316e), for a total of four eCQMs. We note that the number of calendar
quarters of data and total number of eCQMs required would remain the
same.
This proposal is being made in conjunction with our proposal in
section VIII.A.5.a.(1) of the preamble of this proposed rule, in which
we are proposing to adopt the Safe Use of Opioids--Concurrent
Prescribing eCQM (NQF #3316e) beginning with the CY 2021 reporting
period/FY 2023 payment determination. We believe this measure has the
potential to reduce preventable mortality and costs associated with
other adverse events related to opioid use. As discussed in section
VIII.A.5.a.(1) of the preamble of this proposed rule, concurrent opioid
or opioid-benzodiazepine prescription use contributes significantly to
the overall population's risk of opioid overdose. Currently, however,
no measure exists to assess nationwide rates of concurrent prescribing
of opioids and benzodiazepines at the hospital-level.
In developing this proposal, we also considered an alternative
whereby hospitals would have the option to select one of the two
proposed opioids-related eCQMs, the Safe Use of Opioids--Concurrent
Prescribing eCQM (NQF #3316e) or the Hospital Harm--Opioid-Related
Adverse Events eCQM, as their fourth required eCQM. However, such an
approach would add complexity to the eCQM reporting requirements, and
we believe that the Safe Use of Opioids--Concurrent Prescribing eCQM
(NQF #3316e) is more closely related to combating the current opioid
epidemic, as discussed above and in section VIII.A.5.a. of the preamble
of this proposed rule, than the Hospital Harm--Opioid-Related Adverse
Events eCQM, which is focused on improved monitoring of patients who
receive opioids during hospitalization.
If our proposal to adopt the Safe Use of Opioids--Concurrent
Prescribing eCQM (NQF #3316e) beginning with the CY 2021 reporting
period/FY 2023 payment determination is finalized, we are proposing
that while this measure would be available for hospitals to select as
one of their four self-selected eCQMs for the CY 2021 reporting period,
all hospitals would be required to report this eCQM beginning with the
CY 2022 reporting period/FY 2024 payment determination. We believe this
measure would provide valuable information on this area of high-risk
prescribing to providers, and further our efforts to combat the
negative impacts of the opioid crisis. We also believe this proposal is
consistent with CMS' goal of incrementally increasing the use of EHR
data for quality measurement and is responsive to the feedback of some
stakeholders urging a faster transition to full electronic
reporting.\575\
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\575\ The Office of the National Coordinator for Health
Information Technology. (2018). Strategy on Reducing Regulatory and
Administrative Burden Relating to the Use of Health IT and EHRs
(Draft for Public Comment). Available at: https://www.healthit.gov/sites/default/files/page/2018-11/Draft%20Strategy%20on%20Reducing%20Regulatory%20and%20Administrative%20Burden%20Relating.pdf.
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We note that this proposal is contingent on finalization of our
proposal in section VIII.A.5.a.(1) of the preamble of this proposed
rule to adopt the Safe Use of Opioids--Concurrent Prescribing eCQM (NQF
#3316e). We also refer readers to section VIII.D.6.d.(2) of the
preamble of this proposed rule for a similar proposal by the Medicare
Promoting Interoperability Program.
(5) Continuation of Certification Requirements for eCQM Reporting
(A) Requiring Use of 2015 Edition Certification Criteria
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41604 through
41607), to align the Hospital IQR Program with the Promoting
Interoperability Program, we finalized a policy to require hospitals to
use the 2015 Edition certification criteria for certified EHR
technology (CEHRT) for the CY 2019 reporting period/FY 2021 payment
determination and subsequent years. We are not proposing any changes to
this policy in this proposed rule.
(B) Requiring EHR Technology to be Certified to All Available eCQMs
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38391 through
38393), for the CY 2017 reporting period/FY 2019 payment determination
and the CY 2018 reporting period/FY 2020 payment determination, we
finalized a requirement that EHR technology used for eCQM reporting be
certified to all eCQMs, but noted that such certified EHR technology
does not need to be recertified each time it is updated to a more
recent version of the eCQM electronic specifications.
In this proposed rule, we are proposing to continue the requirement
that EHRs be certified to all available eCQMs used in the Hospital IQR
Program for the CY 2020 reporting period/FY 2022 payment determination
and subsequent years. The 2015 Edition Base EHR definition (as defined
by HHS' Office of the National Coordinator for Health Information
Technology (ONC) 2015 Edition Health Information Technology (Health IT)
Certification Criteria, 2015 Edition Base Electronic Health Record
(EHR) Definition, and ONC Health IT Certification Program Modifications
Final Rule (80 FR 62649 through 62655)) requires certified health IT to
have the capability to capture and query information relevant to health
care quality,\576\ which can be ensured by meeting the clinical quality
measure certification criteria to record and export (45 CFR
170.315(c)(1)). The 2015 Edition Base EHR definition does not require
certified health IT to meet additional clinical quality measure
certification criteria such as to import and calculate (45 CFR
170.315(c)(2)), report (45 CFR 170.315(c)(3)), or filter (45 CFR
170.315(c)(4)).
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\576\ 45 CFR 170.102.
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ONC's Health IT Certification Program is ``agnostic'' to settings
and programs, but can support many different use cases and needs.\577\
Because the ONC Health IT Certification Program supports multiple
program and setting needs, ONC does not include requirements that are
specific to CMS programs. CMS may impose more stringent requirements
for EHR-based reporting under its programs.
---------------------------------------------------------------------------
\577\ ONC, 2015 Edition Final Rule: Overview of the 2015 Edition
Health IT Certification Criteria & ONC Health IT Certification
Program Provisions. Available at: https://www.healthit.gov/sites/default/files/onc_2015_edition_final_rule_presentation_10-28-15.pdf.
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The Hospital IQR and Promoting Interoperability Programs have
previously required EHRs to be certified to all available eCQMs used in
the programs (that is, individual testing of each eCQM) in order to
support flexibility for hospitals when they select the eCQMs on which
to report.\578\ When EHRs are certified to all available eCQMs in the
eCQM measure set, hospitals are able to select and report on those
measures that best reflect their
[[Page 19498]]
patient populations and reporting capabilities. In addition to
supporting hospital flexibility, we believe the continuation of this
requirement promotes more accurate electronic quality reporting by
incentivizing EHR and other health IT vendors to test all available
eCQMs and to offer reporting modules with certified eCQMs. This
requirement would produce greater certainty for hospitals that their
EHR systems would be capable of accurately calculating the particular
eCQMs they select to report to CMS. We believe this would help reduce
burden for hospitals by potentially reducing the frequency of needing
to consult with their EHR and other health IT vendors to troubleshoot
implementation or reporting issues.
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\578\ 82 FR 38391 through 38393; 83 FR 41672.
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We have continued to hear from hospital stakeholders during a
series of provider listening sessions in 2018 that they believe
certification is an important part of ensuring successful reporting to
CMS. In addition, because this has been the current policy for the
Hospital IQR and Promoting Interoperability Programs (82 FR 38391
through 38393; 83 FR 41672), vendors and providers should be familiar
with this requirement, and we expect that most providers' EHR systems
are already certified to all currently available eCQMs. Since certified
EHR technology does not need to be recertified each time it is updated
to a more recent version of the eCQM electronic specifications under
the Hospital IQR Program (82 FR 38393), there should be no added burden
with regard to the currently adopted eCQMs in the eCQM measure set.
We also refer readers to section VIII.D.6.e.(1) of the preamble of
this proposed rule for a similar proposal for the Promoting
Interoperability Program.
(6) File Format for EHR Data, Zero Denominator Declarations, and Case
Threshold Exemptions
We refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR
49705 through 49708) and the FY 2017 IPPS/LTCH PPS final rule (81 FR
57170) for our previously adopted eCQM file format requirements. Under
these requirements, hospitals: (1) Must submit eCQM data via the
Quality Reporting Document Architecture Category I (QRDA I) file format
as was previously required; (2) may use third parties to submit QRDA I
files on their behalf; and (3) may either use abstraction or pull the
data from non-certified sources in order to then input these data into
CEHRT for capture and reporting QRDA I. Hospitals can continue to meet
the reporting requirements by submitting data via QRDA I files, zero
denominator declaration, or case threshold exemption (82 FR 38387). We
are not proposing any changes to these requirements for eCQMs in this
proposed rule.
(7) Submission Deadlines for eCQM Data
We refer readers to the FY 2015 IPPS/LTCH PPS final rule (79 FR
50256 through 50259), the FY 2016 IPPS/LTCH PPS final rule (80 FR 49705
through 49709), and the FY 2017 IPPS/LTCH PPS final rule (81 FR 57169
through 57172) for our previously adopted policies to align eCQM data
reporting periods and submission deadlines for both the Hospital IQR
and Medicare Promoting Interoperability Programs. In the FY 2017 IPPS/
LTCH PPS final rule (81 FR 57172), we finalized the alignment of the
Hospital IQR Program eCQM submission deadline with that of the Medicare
Promoting Interoperability Program--the end of two months following the
close of the calendar year--for the CY 2017 reporting period/FY 2019
payment determination and subsequent years. We note the submission
deadline may be moved to the next business day if it falls on a weekend
or federal holiday. We are not proposing any changes to the eCQM
submission deadlines in this proposed rule.
e. Data Submission and Reporting Requirements for Hybrid Measures
(1) Background
In section VIII.A.5.b. of the preamble of this proposed rule, we
are proposing to adopt the Hybrid HWR measure in the Hospital IQR
Program beginning with the FY 2026 payment determination, with 2 years
of voluntary reporting prior to that time. In the FY 2018 IPPS/LTCH PPS
final rule (82 FR 38350 through 38355), we finalized voluntary
reporting of the Hybrid HWR measure for the CY 2018 reporting period.
For data submission and reporting requirements under the 2018 Voluntary
Reporting Period, we finalized that the 13 core clinical data elements
and six linking variables for the Hybrid HWR measure be submitted using
the QRDA I file format, and that hospitals voluntarily reporting data
for the Hybrid HWR measure could use EHR technology certified to the
2014 Edition, the 2015 Edition, or a combination thereof (82 FR 38394
through 38397). During the 2018 Voluntary Reporting Period,
participating hospitals and their health IT vendors reported data on
discharges for the January 1, 2018 through June 30, 2018 reporting
period by the submission deadline of January 4, 2019, and approximately
80 hospitals submitted data. We expect that hospitals that voluntarily
submitted data for this measure will receive confidential hospital-
specific reports detailing submission results from the reporting period
in early summer of 2019.
(2) Certification and File Format Requirements
In this proposed rule, we are proposing to require that hospitals
use EHR technology certified to the 2015 Edition to submit data on the
Hybrid HWR measure. This is consistent with our policy finalized in the
FY 2019 IPPS/LTCH PPS final rule (83 FR 41604 through 41607), which
requires use of the 2015 Edition certification criteria for CEHRT when
reporting eCQMs beginning with the CY 2019 reporting period/FY 2021
payment determination.
In addition, we are proposing that the core clinical data elements
and linking variables identified in hybrid measure specifications, for
example as described in section VIII.A.5.b. of the preamble of this
proposed rule, be submitted using the QRDA I file format. In order to
ensure that the data have been appropriately connected to the
encounter, the core clinical data elements specified for risk
adjustment need to be captured in relation to the start of an inpatient
encounter. The QRDA I standard enables the creation of an individual
patient-level quality report that contains quality data for one patient
for one or more quality measures. Based on the experience of the CY
2018 Voluntary Reporting Period, the use of the QRDA I file format is
feasible. In addition, hospitals and health IT vendors have been using
the QRDA I file format for eCQM reporting for several years.
For details on the implementation guidance provided for the Hybrid
HWR measure 2018 Voluntary Reporting Period, we refer readers to the
2018 CMS QRDA I Implementation Guide for Hospital Quality Reporting and
the 2018 CMS QRDA I Schematrons and Sample Files for HQR, available on
the eCQI Resource Center website.\579\ If our proposal to adopt the
Hybrid HWR measure is finalized, updated implementation guidance,
schematrons, and sample files will become available on the eCQI
Resource Center website.
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\579\ The Electronic Clinical Quality Improvement (eCQI)
Resource Center. Eligible Hospitals/Critical Access Hospital eCQMs.
Available at: https://ecqi.healthit.gov/eligible-hospital/critical-access-hospital-ecqms.
---------------------------------------------------------------------------
As with eCQM reporting, we also encourage all hospitals and their
health IT vendors to submit QRDA I files early,
[[Page 19499]]
and to use one of the pre-submission testing tools for electronic
reporting, such as the CMS Pre-Submission Validation Application (PSVA)
tool (81 FR 57113), to allow additional time for testing and to make
sure all required data files are successfully submitted by the
deadline. The PSVA tool can be downloaded from the Secure File Transfer
(SFT) section of the QualityNet Secure Portal at: https://cportal.qualitynet.org/QNet/pgm_select.jsp.
(3) Additional Submission Requirements
In this proposed rule, we are proposing to allow hospitals to meet
the hybrid measure reporting and submission requirements by submitting
any combination of data via QRDA I files, zero denominator
declarations, and/or case threshold exemptions. We recognize the
challenges associated with electronic reporting and encourage hospitals
of all sizes to work with their vendors to achieve electronic capture
and reporting of data necessary for hybrid measure reporting. We also
acknowledge that there are situations in which a hospital may be
prepared for electronic reporting, but may not have data to report on a
particular measure. For example, hospitals with small patient
populations may not have sufficient patient population to report on
specific measures, such that those hospitals may find it necessary to
utilize a zero denominator declaration and/or case threshold exemption.
In addition, there may be situations in which case number thresholds
are appropriate, given the burden on hospitals that very seldom have
the types of cases addressed by certain measures.
In this proposed rule, we are proposing to apply similar zero
denominator declaration and case threshold exemption policies to hybrid
measure reporting as we allow for eCQM reporting. In other words, for a
zero denominator declaration, if a hospital's EHR is otherwise capable
of reporting hybrid measure data, but the hospital does not have
patients that meet the denominator criteria of that hybrid measure, the
hospital may submit a zero in the denominator for that measure.
Submission of a zero in the denominator for a hybrid measure would
count as a successful submission for that hybrid measure for the
Hospital IQR Program. In addition, for the case threshold exemption,
hospitals that have five or fewer inpatient discharges per quarter or
twenty or fewer inpatient discharges per year as defined by a hybrid
measure's denominator population, would be exempted from reporting on
that hybrid measure. Hospitals can submit zero denominator declarations
or case threshold exemptions by logging into the QualityNet Secure
Portal and completing the Denominator Declaration screen.
(4) Submission Deadlines for Hybrid Measures
We are proposing that hospitals must submit the core clinical data
elements and linking variables within three months following the end of
the applicable reporting period (submissions would be required no later
than the first business day three months following the end of the
reporting period) for hybrid measures in the Hospital IQR Program.
As discussed earlier in this proposed rule, we are proposing that
the first voluntary reporting period would run from July 1, 2021
through June 30, 2022. Under this proposal, for example, hospitals
would be required to submit the core clinical data elements and linking
variable data no later than Friday, September, 30, 2022, which is the
first business day three months following the end of the reporting
period. Similarly, for the July 1, 2022 through June 30, 2023 voluntary
reporting period, for example, the submission deadline would be Monday,
October 2, 2023. If our proposal to adopt the Hybrid HWR measure is
finalized, this submission deadline would apply to all reporting
periods for which data are submitted.
f. Sampling and Case Thresholds for Chart-Abstracted Measures
We refer readers to the FY 2011 IPPS/LTCH PPS final rule (75 FR
50221), the FY 2012 IPPS/LTCH PPS final rule (76 FR 51641), the FY 2013
IPPS/LTCH PPS final rule (77 FR 53537), the FY 2014 IPPS/LTCH PPS final
rule (78 FR 50819), and the FY 2016 IPPS/LTCH PPS final rule (80 FR
49709) for details on our sampling and case thresholds for the FY 2016
payment determination and subsequent years. We are not proposing any
changes to our sampling and case threshold policies in this proposed
rule.
g. HCAHPS Administration and Submission Requirements
We refer readers to the FY 2011 IPPS/LTCH PPS final rule (75 FR
50220), the FY 2012 IPPS/LTCH PPS final rule (76 FR 51641 through
51643), the FY 2013 IPPS/LTCH PPS final rule (77 FR 53537 through
53538), and the FY 2014 IPPS/LTCH PPS final rule (78 FR 50819 through
50820) for details on previously-adopted HCAHPS submission
requirements. We also refer hospitals and HCAHPS Survey vendors to the
official HCAHPS website at: http://www.hcahpsonline.org for new
information and program updates regarding the HCAHPS Survey, its
administration, oversight, and data adjustments.
In the CY 2019 OPPS/ASC final rule with comment period (83 FR 59140
through 59149), we updated the HCAHPS Survey by removing the
Communication About Pain questions effective with October 2019
discharges, for the FY 2021 payment determination and subsequent years,
and finalizing a policy of not publicly reporting data regarding these
questions. We are not proposing any changes to the HCAHPS Survey or its
administration and submission requirements in this proposed rule.
h. Data Submission Requirements for Structural Measures
There are no remaining structural measures in the Hospital IQR
Program.
i. Data Submission and Reporting Requirements for CDC NHSN HAI Measures
For details on the data submission and reporting requirements for
Healthcare-Associated Infection (HAI) measures reported via the CDC's
National Healthcare Safety Network (NHSN), we refer readers to the FY
2012 IPPS/LTCH PPS final rule (76 FR 51629 through 51633; 51644 through
51645), the FY 2013 IPPS/LTCH PPS final rule (77 FR 53539), the FY 2014
IPPS/LTCH PPS final rule (78 FR 50821 through 50822), and the FY 2015
IPPS/LTCH PPS final rule (79 FR 50259 through 50262). The data
submission deadlines are posted on the QualityNet website at: http://www.QualityNet.org/. We are not proposing any changes to those
requirements in this proposed rule.
We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR
41547 through 41553), in which we finalized the removal of five of
these measures (CLABSI, CAUTI, Colon and Abdominal Hysterectomy SSI,
MRSA Bacteremia, and CDI) from the Hospital IQR Program. As a result,
hospitals will not be required to submit any data for those measures
under the Hospital IQR Program following their removal beginning with
the CY 2020 reporting period/FY 2022 payment determination. However,
the five CDC NHSN HAI measures will be included in the HAC Reduction
and Hospital VBP Programs and reported via the CDC NHSN portal (83 FR
41474 through 41477; 83 FR 41449 through 41452). Lastly, we refer
readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41472 through
41492) as well as sections IV.I.6. and 7. and
[[Page 19500]]
IV.H.5.e. of the preamble of this proposed rule for more information
and proposals regarding NHSN HAI measure data collection and validation
under the HAC Reduction Program and use in the HAC Reduction and
Hospital VBP Programs. We further note that the HCP measure remains in
the Hospital IQR Program and will continue to be reported via NHSN.
11. Validation of Hospital IQR Program Data
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53539 through 53553), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50822
through 50835), the FY 2015 IPPS/LTCH PPS final rule (79 FR 50262
through 50273), the FY 2016 IPPS/LTCH PPS final rule (80 FR 49710
through 49712), the FY 2017 IPPS/LTCH PPS final rule (81 FR 57173
through 57181), and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38398
through 38403) for detailed information on chart-abstracted and eCQM
validation processes and previous updates to these processes for the
Hospital IQR Program.
In this proposed rule, we are not proposing any changes to the
existing processes for validation of chart-abstracted and eCQM measure
data. We note that if our proposal to adopt the Hybrid HWR measure is
finalized, we intend to propose a validation process for core clinical
data elements in future rulemaking.
12. Data Accuracy and Completeness Acknowledgement (DACA) Requirements
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53554) for previously adopted details on DACA requirements. We are not
proposing any changes to the DACA requirements in this proposed rule.
13. Public Display Requirements
We refer readers to the FY 2008 IPPS/LTCH PPS final rule (72 FR
47364), the FY 2011 IPPS/LTCH PPS final rule (75 FR 50230), the FY 2012
IPPS/LTCH PPS final rule (76 FR 51650), the FY 2013 IPPS/LTCH PPS final
rule (77 FR 53554), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50836),
the FY 2015 IPPS/LTCH PPS final rule (79 FR 50277), the FY 2016 IPPS/
LTCH PPS final rule (80 FR 49712 through 49713), and the FY 2018 IPPS/
LTCH PPS final rule (82 FR 38403 through 38409) for details on public
display requirements. The Hospital IQR Program quality measures are
typically reported on the Hospital Compare website at: http://www.medicare.gov/hospitalcompare, but on occasion are reported on other
CMS websites such as: https://data.medicare.gov. We are not proposing
any changes to the public display requirements in this proposed rule.
14. Reconsideration and Appeal Procedures
We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR
51650 through 51651), the FY 2014 IPPS/LTCH PPS final rule (78 FR
50836), and 42 CFR 412.140(e) for details on reconsideration and appeal
procedures for the FY 2017 payment determination and subsequent years.
We are not proposing any changes to the reconsideration and appeals
procedures in this proposed rule.
15. Hospital IQR Program Extraordinary Circumstances Exceptions (ECE)
Policy
We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR
51651 through 51652), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50836
through 50837), the FY 2015 IPPS/LTCH PPS final rule (79 FR 50277), the
FY 2016 IPPS/LTCH PPS final rule (80 FR 49713), the FY 2017 IPPS/LTCH
PPS final rule (81 FR 57181 through 57182), the FY 2018 IPPS/LTCH PPS
final rule (82 FR 38409 through 38411), and 42 CFR 412.140(c)(2) for
details on the current Hospital IQR Program ECE policy. We also refer
readers to the QualityNet website at: http://www.QualityNet.org/ for
our current requirements for submission of a request for an exception.
We are not proposing any changes to the ECE policy in this proposed
rule.
B. PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) Program
1. Background
Section 1866(k) of the Act establishes a quality reporting program
for hospitals described in section 1886(d)(1)(B)(v) of the Act
(referred to as ``PPS-Exempt Cancer Hospitals'' or ``PCHs'') that
specifically applies to PCHs that meet the requirements under 42 CFR
412.23(f). Section 1866(k)(1) of the Act states that, for FY 2014 and
each subsequent fiscal year, a PCH must submit data to the Secretary in
accordance with section 1866(k)(2) of the Act with respect to such
fiscal year.
The PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) Program
strives to put patients first by ensuring they, along with their
clinicians, are empowered to make decisions about their own health care
using data-driven insights that are increasingly aligned with
meaningful quality measures. To this end, we support technology that
reduces burden and allows clinicians to focus on providing high quality
health care to their patients. We also support innovative approaches to
improve quality, accessibility, and affordability of care, while paying
particular attention to improving clinicians' and beneficiaries'
experiences when participating in CMS programs. In combination with
other efforts across the Department of Health and Human Services (HHS),
we believe the PCHQR Program incentivizes PCHs to improve their health
care quality and value, while giving patients the tools and information
needed to make the best decisions.
For additional background information, including previously
finalized measures and other policies for the PCHQR Program, we refer
readers to the following final rules: The FY 2013 IPPS/LTCH PPS final
rule (77 FR 53556 through 53561); the FY 2014 IPPS/LTCH PPS final rule
(78 FR 50838 through 50846); the FY 2015 IPPS/LTCH PPS final rule (79
FR 50277 through 50288); the FY 2016 IPPS/LTCH PPS final rule (80 FR
49713 through 49723); the FY 2017 IPPS/LTCH PPS final rule (81 FR 57182
through 57193); the FY 2018 IPPS/LTCH PPS final rule (82 FR 38411
through 38425); the FY 2019 IPPS/LTCH PPS final rule (83 FR 41609
through 41624); and the CY 2019 OPPS/ASC final rule with comment period
(83 FR 59149 through 59154).
In this proposed rule, we are proposing several new policies for
the PCHQR Program. We developed these proposals after conducting an
overall review of the program under our new Meaningful Measures
Initiative, which is discussed in more detail in I.A.2. of the preamble
of the FY 2019 IPPS/LTCH PPS final rule (83 FR 41147 through 41148) and
this FY 2020 proposed rule. The proposals reflect our efforts to ensure
that the PCHQR Program measure set continues to promote improved health
outcomes for our beneficiaries. The proposals also reflect our efforts
to improve the usefulness of the data that we publicly report in the
PCHQR Program.
2. Proposed Refinement of the Hospital Consumer Assessment of
Healthcare Providers and Systems (HCAHPS) Survey (NQF #0166): Removal
of the Pain Management Questions
a. Background
The HCAHPS Survey (NQF #0166) (OMB Control Number 0938-0981) is the
first national, standardized, publicly reported survey of patients'
experience of hospital care and asks discharged patients 32 questions
about their recent
[[Page 19501]]
hospital stay. In May 2005, the HCAHPS Survey was endorsed for the
first time by the National Quality Forum (NQF). The HCAHPS Survey is
available in English, Spanish, Chinese, Russian, Vietnamese, and
Portuguese versions. The HCAHPS Survey, along with its protocols for
sampling, data collection and coding, and file submission, can be found
in the current HCAHPS Quality Assurance Guidelines, which is available
on the official HCAHPS website at: http://www.hcahpsonline.org/en/quality-assurance/.
We adopted the HCAHPS Survey into the PCHQR Program beginning with
the FY 2016 program year in the FY 2014 IPPS/LTCH PPS final rule (78 FR
50844 through 50845); we refer readers to this final rule for a
detailed discussion of the survey. Further, we finalized in the FY 2016
IPPS/LTCH PPS final rule (80 FR 49722) that we would begin publicly
reporting this measure in the PCHQR Program in CY 2016. For HCAHPS
Survey data reported in years prior to CY 2018, we refer readers to:
http://hcahpsonline.org/en/summary-analyses/.
In this proposed rule, we are proposing to adopt a substantive
change to the HCAHPS Survey by removing the three Pain Management
questions beginning with October 1, 2019 discharges, as described
below.
The patients treated by the 11 PPS-exempt cancer hospitals eligible
to participate in the PCHQR Program have been diagnosed with cancer,
which frequently causes substantial pain. Cancer treatment also
frequently involves surgery, chemotherapy, and/or radiation therapy,
all of which can also cause substantial pain beyond that experienced by
the general Medicare population.\580\ Pain management is therefore an
important safeguard against the unintended consequences of appropriate
clinical care in these patients.\581\
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\580\ American Cancer Society. ``Cancer Pain.'' Available at:
https://www.cancer.org/treatment/treatments-and-side-effects/physical-side-effects/pain.html.
\581\ Mayo Clinic. ``Cancer Pain: Relief is Possible.''
Available at: https://www.mayoclinic.org/diseases-conditions/cancer/in-depth/cancer-pain/art-20045118.
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The version of the HCAHPS Survey currently implemented in the PCHQR
Program includes three Pain Management questions, Q12, Q13, and Q14.
The questions are as follows:
12. During this hospital stay, did you need medicine for pain?
1 [ballot] Yes
2 [ballot] No [rarr] If No, Go to Question 15
13. During this hospital stay, how often was your pain well
controlled?
1 [ballot] Never
2 [ballot] Sometimes
3 [ballot] Usually
4 [ballot] Always
14. During this hospital stay, how often did the hospital staff do
everything they could to help you with your pain?
1 [ballot] Never
2 [ballot] Sometimes
3 [ballot] Usually
4 [ballot] Always
The pain management questions that the PCHQR Program currently uses
were previously also adopted as part of the HCAHPS survey used by the
Hospital IQR Program (71 FR 68202 through 68204) and the Hospital VBP
Program (76 FR 26510), but the questions have been removed from the
survey in both of those programs.
Specifically, in the CY 2017 OPPS/ASC final rule with comment
period (81 FR 79862), we noted that that we had received feedback that
some stakeholders were concerned about the Pain Management dimension
questions being used in a program, including the Hospital VBP Program,
where there was any link between scoring well on the questions and
higher hospital payments (81 FR 79856). Some stakeholders also stated
that they believed that the linkage of the pain management questions to
the Hospital VBP Program payment incentives created pressure on
hospital staff to prescribe more opioids in order to achieve higher
scores on the pain management dimension. We also noted that many
factors outside of CMS control could contribute to a perception of a
link between the questions and opioid prescribing practices, including
misuse of the survey (such as using it for outpatient emergency room
care instead of inpatient care, or using it for determining physician
performance) and failure to recognize that the HCAHPS survey excludes
certain populations from the sampling frame (such as those with a
primary substance use disorder diagnosis).
We stated that we had heard that some hospitals have identified
patient experience as a potential source of competitive advantage, and
that some hospitals may be disaggregating their raw HCAHPS data to
compare, assess, and incentivize individual physicians, nurses and
other hospital staff. We further stated that some hospitals may be
using the HCAHPS survey to assess their emergency and outpatient
departments. We stated that the HCAHPS survey was never intended to be
used in any of these ways.
In the CY 2017 OPPS/ASC final rule with comment period (81 FR 79859
through 79860), we further noted that numerous commenters had offered
support for the development of modified questions regarding pain
management for the HCAHPS Survey and that some commenters expressed
support for modified pain management questions that focused on
effective communication with patients about pain management-related
issues. In response, we stated we would follow our standard survey
development processes, which include drafting alternative questions,
cognitive interviews and focus group evaluation, field testing,
statistical analysis, stakeholder input, the Paperwork Reduction Act,
and NQF endorsement (81 FR 79856).
We continue to believe that pain control is an appropriate part of
routine patient care that hospitals should manage and is an important
concern for patients, their families, and their caregivers. It is
important to note that the HCAHPS Survey does not specify any
particular type of pain control method. In addition, appropriate pain
management includes communication with patients about pain-related
issues, setting expectations about pain, shared decision-making, and
proper prescription practices. However, due to some potential confusion
about the appropriate use of the Pain Management dimension questions in
the Hospital VBP Program and the public health concern about the
ongoing prescription opioid overdose epidemic, in an abundance of
caution, we finalized removal of the Pain Management dimension of the
HCAHPS Survey in the Patient- and Caregiver-Centered Experience of
Care/Care Coordination domain of the Hospital VBP Program beginning
with the FY 2018 program year (81 FR 79862).
Subsequently, out of an abundance of caution and in the face of a
nationwide epidemic of opioid over-prescription, in the FY 2018 IPPS/
LTCH PPS final rule (82 FR 38328 through 38342), we finalized a
refinement to the HCAHPS Survey measure as used in the Hospital IQR
Program by removing the same pain management questions.
b. Proposal To Refine the HCAHPS Survey by Removing the Existing Pain
Management Questions
We are proposing to refine the HCAHPS Survey used in the PCHQR
Program by removing the three Pain Management questions beginning with
October 1, 2019 discharges. As discussed in the CY 2019 OPPS/ASC final
rule with comment period (83 FR
[[Page 19502]]
59141), some hospitals have identified patient experience of care as a
potential source of competitive advantage, and stakeholders have also
informed CMS that some hospitals may be disaggregating their raw HCAHPS
Survey data to compare, assess, and incentivize individual physicians,
nurses, and other hospital staff. While this issue was raised in regard
to acute care facilities, we are concerned that similar activity might
be occurring in PCHs because the incentives to improve patient
experience exist across care settings.
We are also concerned about potential confusion about the
appropriate use of the pain management questions in the PCHQR Program,
given the public health concern about the ongoing prescription opioid
overdose epidemic, and believe that removing the pain management
questions would eliminate any such potential misuse. We note that the
HCAHPS Quality Assurance Guidelines,\582\ which set forth current
survey administration protocols, strongly discourage the unofficial use
of HCAHPS scores for comparisons within hospitals, such as for
comparisons of particular wards, floors, and individual staff hospital
members.
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\582\ HCAHPS Quality Assurance Guidelines (v.13.0), available
at: http://www.hcahpsonline.org/en/quality-assurance/.
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While we recognize the importance of being able to provide
performance results within the context of pain management for cancer
patients, we also note that pain items in generic patient experience
surveys (for example, HCAHPS) have limitations when implemented. As
noted above, many factors outside the control of CMS quality program
requirements may contribute to the perception of a link between the
pain management questions and opioid prescribing practices, including
misuse of the HCAHPS Survey (for example, using it for outpatient
emergency room care instead of inpatient care, or using it for
determining individual physician performance), and failure to recognize
that the HCAHPS Survey excludes certain populations from the sampling
frame (such as those with a primary substance use disorder diagnosis).
Further, in its draft final report, the President's Commission on
Combatting Drug Addiction and the Opioid Crisis recommended removal of
the HCAHPS Pain Management questions in order to ensure providers are
not incentivized to offer opioids to raise their HCAHPS Survey
score.\583\ We believe that all of these issues support the removal of
the pain management questions in the HCAHPS survey used by PCHs.
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\583\ President's Commission on Combating Drug Addiction and the
Opioid Crisis draft report, available at: https://www.whitehouse.gov/sites/whitehouse.gov/files/images/Final_Report_Draft_11-15-2017.pdf.
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We also believe that the removal of the questions will promote
programmatic alignment with both the Hospital IQR Program and the
Hospital VBP Program. Accordingly, we are proposing to remove the Pain
Management questions from the version of the HCAHPS Survey currently
implemented in the PCHQR Program, beginning with the October 1, 2019
discharges. If finalized as proposed, this would result in the
reduction of the number of HCAHPS Survey questions from 32 to 29. We
note that this proposed change would not impact how scores are
calculated for the remainder of the survey and would not have a
significant effect on the reliability of the HCAHPS Survey instrument
as a whole.
We also are proposing to not publicly report the data collected on
the Pain Management questions beginning with October 2018 discharges in
order to address the potential misunderstanding associated with these
questions as soon as possible. While the data will not be publicly
reported, we still plan to provide performance results to PCHs in
confidential preview reports upon the availability of four quarters of
CY 2018 data, as early as July 2019.
3. Measure Retention and Removal Factors for the PCHQR Program
a. Measure Retention Factors
We generally retain measures from the previous year's PCHQR Program
measure set for subsequent years' measure sets, except when we
specifically propose to remove or replace a measure. We have also
recognized that there are times when measures may meet one or more of
the outlined criteria for removal from the program but continue to
bring value to the program. Therefore, we adopted the following factors
for consideration in determining whether to retain a measure in the
PCHQR Program, which also are based on factors established in the
Hospital IQR Program (81 FR 57182 through 57183):
Measure aligns with other CMS and HHS policy goals;
Measure aligns with other CMS programs, including other
quality reporting programs; and
Measure supports efforts to move PCHs towards reporting
electronic measures.
We are not proposing any changes to these measure retention factors
in this proposed rule.
b. Measure Removal Factors
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41609 through
41611), we discussed our existing measure removal factors for the PCHQR
Program.\584\ We note that these factors are based on factors adopted
for the Hospital IQR Program (81 FR 57182 through 57183; 83 FR 41540
through 41544). We also adopted a new measure removal factor, for a
total of eight measure removal factors:
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\584\ We note that we previously referred to these factors as
``criteria'' (for example, 81 FR 57182 through 57183); we now use
the term ``factors'' to align the PCHQR Program terminology with the
terminology we use in other CMS quality reporting and pay for
performance value-based purchasing programs.
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Factor 1. Measure performance among PCHs is so high and
unvarying that meaningful distinctions and improvements in performance
can no longer be made (that is, ``topped-out'' measures): Statistically
indistinguishable performance at the 75th and 90th percentiles; and
truncated coefficient of variation Factor 2. A measure does not align with current clinical
guidelines or practice;
Factor 3. The availability of a more broadly applicable
measure (across settings or populations) or the availability of a
measure that is more proximal in time to desired patient outcomes for
the particular topic;
Factor 4. Performance or improvement on a measure does not
result in better patient outcomes;
Factor 5. The availability of a measure that is more
strongly associated with desired patient outcomes for the particular
topic;
Factor 6. Collection or public reporting of a measure
leads to negative unintended consequences other than patient harm;
Factor 7. It is not feasible to implement the measure
specifications; and
Factor 8. The costs associated with a measure outweigh the
benefit of its continued use in the program.
We are not proposing any changes to these measure removal factors
in this proposed rule.
4. Proposed Removal of the Web-Based Structural Measure: External Beam
Radiotherapy (EBRT) for Bone Metastases From the PCHQR Program
Beginning With the FY 2022 Program Year
In this proposed rule, we are proposing to remove the External Beam
[[Page 19503]]
Radiotherapy (EBRT) for Bone Metastases (formerly NQF #1822) \585\
measure from the PCHQR Program beginning with the FY 2022 program year,
based on removal Factor 8: The costs associated with a measure outweigh
the benefit of its continued use in the program.
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\585\ This measure was initially endorsed by NQF, with
corresponding measure number 1822. This measure lost its NQF
endorsement in March 2018. National Quality Forum Cancer Project
Final Report--Spring 2018. Available at: http://www.qualityforum.org/Publications/2018/08/Cancer_Final_Report_-_Spring_2018_Cycle.aspx.
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a. Background
We adopted the EBRT measure beginning with the FY 2017 program year
(October 1, 2015) in the FY 2015 IPPS/LTCH PPS final rule (79 FR 50278
through 50279). The EBRT measure reports the percentage of patients,
regardless of age, with a diagnosis of painful bone metastases and no
history of previous radiation who receive EBRT with an acceptable
fractionation scheme as defined by the guideline.
When the EBRT measure was adopted into the PCHQR Program, it
initially used ``radiation planning'' current procedural terminology
(CPT) codes that were billable at the physician level. After finalizing
the measure, we learned that at least one of the 11 PCHs did not have
access to physician billing data, making reporting complete data on
this measure unduly burdensome and difficult. To address this issue,
beginning in March 2016, the measure was updated in the PCHQR Program
to enable the use of ``radiation delivery'' CPT codes, which are
billable at the hospital level.\586\
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\586\ 2018 EBRT Measure Information Form. Retrieved from:
https://www.qualitynet.org/dcs/ContentServer?cid=1228774479863&pagename=QnetPublic%2FPage%2FQnetTier4&c=Page.
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b. Analysis of Measure Use
After implementation of the updated EBRT measure in the PCHQR
Program, the measure steward conducted testing of data collection of
the updated measure in the outpatient setting and discovered that there
are new and significant concerns regarding the revised ``radiation
delivery'' CPT coding used to report the EBRT measure. Although this
testing was done in the outpatient setting, we believe that the issues
with the measure that were identified in the outpatient setting
similarly affect the inpatient cancer hospital community, as PCHs need
to take the same steps as hospital outpatient departments (HOPDs) to
report the measure using ``radiation delivery'' CPT codes. In
particular, the measure steward has observed that implementing the
updated measure in the outpatient setting has proven to be very
burdensome on hospitals. The use of ``radiation delivery'' CPT codes
requires more complicated measure exclusions to be used because the
change to ``radiation delivery'' CPT codes caused the administration of
EBRT to different anatomic sites to be considered separate cases for
this measure. Because there is no way to determine the different
anatomic sites until detailed review of the patient's record is
complete, sampling has become a significant concern, and confounded the
task of determining which sites should be included or excluded from the
measure denominator. In addition, hospitals have difficulty determining
if sample size requirements for the measure are being met. As a result,
we believe that the complexity of reporting this measure places
substantial administrative burden on hospitals.
We also note that the measure lost NQF endorsement in 2018 and that
the measure steward is no longer maintaining the measure or seeking NQF
re-endorsement. As a result, especially because the steward is no
longer maintaining the measure, we no longer believe that we can ensure
that the measure is in line with clinical guidelines and standards,
which further diminishes the value of the measure.
c. Summary
Ultimately, we believe the burden associated with the measure
outweighs the value of its inclusion in the PCHQR Program. We are
proposing, under removal Factor 8, to remove the EBRT measure from the
PCHQR Program beginning with the FY 2022 program year.
5. Proposed New Quality Measure Beginning With the FY 2022 Program Year
a. Considerations in the Selection of Quality Measures
Under current policy, we take many principles into consideration
when developing and selecting measures for the PCHQR Program, and many
of these principles are modeled on those we use for measure development
and selection under the Hospital IQR Program. In section I.A.2. of the
preamble of the FY 2019 IPPS/LTCH PPS final rule (83 FR 41147 through
41148), we also discuss our Meaningful Measures Initiative and its
relation to how we will assess and select quality measures for the
PCHQR Program.
Section 1866(k)(3)(A) of the Act requires that any measure
specified by the Secretary must have been endorsed by the entity with a
contract under section 1890(a) of the Act (the NQF is the entity that
currently holds this contract). Section 1866(k)(3)(B) of the Act
provides an exception under which, in the case of a specified area or
medical topic determined appropriate by the Secretary for which a
feasible and practical measure has not been endorsed by the entity with
a contract under section 1890(a) of the Act, the Secretary may specify
a measure that is not so endorsed as long as due consideration is given
to measures that have been endorsed or adopted by a consensus
organization.
After considering these principles for measure selection in the
PCHQR Program, in this proposed rule, we are proposing to adopt one new
measure beginning with the FY 2022 program year, as described below.
b. Proposed New Quality Measure Beginning With the FY 2022 Program
Year: Surgical Treatment Complications for Localized Prostate Cancer
We are proposing to adopt the Surgical Treatment Complications for
Localized Prostate Cancer measure for the FY 2022 program year and
subsequent years.
(1) Background
Prostate cancer is the most common non-dermatologic malignancy
among men in the United States, with an estimated 180,000 new cases/
year.\587\ Approximately 80 percent of patients are diagnosed with
localized disease and therefore may be eligible for prostate directed
therapy.\588\ This could involve surgical removal of the prostate,
radiation therapy, or both. The majority of patients who undergo
prostate-directed therapy survive, but these treatments can have
serious and potentially longstanding adverse effects, including
incontinence, urinary tract obstruction, hydronephrosis, erectile
dysfunction, urinary fistula formation, hematuria, cystitis, bowel
fistula, proctitis/colitis, bowel bleeding, diarrhea, rectal/anal
fissure, abscess, stricture, incision hernia, infection, or
others.589 590 Patients consistently report
[[Page 19504]]
that these adverse effects, which are patient-centered outcomes, can
have a significant detrimental impact on their quality of
life.591 592
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\587\ Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016.
CA: a cancer journal for clinicians. 2016;66(1):7-30.
\588\ Ibid.
\589\ Bekelman JE, Mitra N, Efstathiou J, et al. Outcomes after
intensity-modulated versus conformal radiotherapy in older men with
nonmetastatic prostate cancer. International journal of radiation
oncology, biology, physics. 2011;81(4):e325-334.
\590\ Potosky AL, Warren JL, Riedel ER, Klabunde CN, Earle CC,
Begg CB. Measuring complications of cancer treatment using the SEER-
Medicare data. Medical care. 2002;40(8 Suppl):IV-62-68.
\591\ Aizer AA, Gu X, Chen MH, et al. Cost implications and
complications of overtreatment of low-risk prostate cancer in the
United States. Journal of the National Comprehensive Cancer Network.
2015; 13(1):61-68.
\592\ Hayes JH, Ollendorf DA, Pearson SD, et al. Active
surveillance compared with initial treatment for men with low-risk
prostate cancer: a decision analysis. JAMA. 2010; 304(21):2373-2380.
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Clinical trials and population-based data have been used to
determine whether different prostate-directed treatments result in
different patient-centered outcomes. These studies have evaluated a
range of prostate-directed treatments, including open radical
prostatectomy, robot-assisted radical prostatectomy, minimally invasive
radical prostatectomy, brachytherapy, external beam radiation therapy,
conformal radiation therapy, intensity modulated radiation therapy
(IMRT), and proton therapy, and have demonstrated that some treatments
are associated with inferior patient-centered outcomes when compared to
others. A number of these studies used Medicare claims after therapy
for prostate cancer to identify specific
outcomes.593 594 595 Very few studies have explored whether
the patient-centered outcomes experienced after prostate-directed
therapy vary by treating facility. However, studies of other cancers
have demonstrated that outcomes can vary by treating facility. For
example, operative mortality after major cancer surgery varies
inversely with hospital volume.\596\
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\593\ Schmid M, Meyer CP, Reznor G, et al acial Differences in
the Surgical Care of Medicare Beneficiaries With Localized Prostate
Cancer. JAMA oncology. 2016; 2(1):85-93.
\594\ Jiang R, Tomaszewski JJ, Ward KC, Uzzo RG, Canter DJ. The
burden of overtreatment: comparison of toxicity between single and
combined modality radiation therapy among low risk prostate cancer
patients. The Canadian journal of urology. 2015; 22(1):7648-7655.
\595\ Loeb S, Carter HB, Berndt SI, Ricker W, Schaeffer EM.
Complications after prostate biopsy: data from SEER-Medicare. The
Journal of urology. 2011; 186(5):1830-1834.
\596\ Begg CB, Cramer LD, Hoskins WJ, Brennan MF. Impact of
hospital volume on operative mortality for major cancer surgery.
JAMA. 1998; 280(20):1747-1751.
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In recognition of the potential impact of this variation, the
Surgical Treatment Complications for Localized Prostate Cancer measure
was developed. This measure is based on the Localized Prostate Cancer
Standard Set (the Standard Set) developed by the International
Consortium for Health Outcome Measurement (ICHOM).\597\ The Standard
Set is a conceptual framework that is supported by a rigorous,
evidence-based consensus approach to identify the outcomes that matter
most to prostate cancer patients. The Localized Prostate Cancer
Standard Set recommends key outcomes that should be measured to improve
the lives of patients with localized prostate cancer. We believe that
this measure is in line with the Standard Set framework, which
recommends measuring complications of prostate-directed surgical
treatments. We believe the Surgical Treatment Complications for
Localized Prostate Cancer measure would add value to the PCHQR Program
measure set, as discussed in detail below.
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\597\ Localized Prostate Cancer Standard Set, available at:
http://www.ichom.org/medical-conditions/localized-prostate-cancer/.
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(2) Overview of Measure
The Surgical Treatment Complications for Localized Prostate Cancer
measure addresses complications of a prostatectomy. The outcomes
selected for this measure are urinary incontinence (UI) and erectile
dysfunction (ED). Specifically, the measure uses claims to identify
urinary incontinence and erectile dysfunction among patients undergoing
localized prostate cancer surgery and uses this information to derive
hospital-specific rates. A strong body of literature, including
numerous recent systematic reviews, have demonstrated the burden of UI
and ED for men following localized prostate surgery and
ED.598 599 600 601 602 By identifying facilities where
adverse outcomes associated with prostatectomy are more common, this
measure will help to highlight opportunities for quality improvement
activities that will address and hopefully mitigate unwarranted
variation in prostatectomy procedures.
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\598\ Garcia-Baquero R, Fernandez-Avila CM, Alvarez-Ossorio JL.
Functional results in the treatment of localized prostate cancer. An
updated literature review. Rev Int Androl. 2018 Nov 22. pii: S1698-
031X(18)30085-2.
\599\ Du Y, Long Q, Guan B, Mu L, Tian J, Jiang Y, Bai X, Wu D.
Robot-Assisted Radical Prostatectomy Is More Beneficial for Prostate
Cancer Patients: A System Review and Meta-Analysis. Med Sci Monit.
2018 Jan 14;24:272-287.
\600\ Wang X, Wu Y, Guo J, Chen H, Weng X, Liu X. Intrafascial
nerve-sparing radical prostatectomy improves patients' postoperative
continence recovery and erectile function: A pooled analysis based
on available literatures. Medicine (Baltimore). 2018 Jul;
97(29):e11297.
\601\ Wallis CJD, Glaser A, Hu JC, Huland H, Lawrentschuk N,
Moon D, Murphy DG, Nguyen PL, Resnick MJ, Nam RK. Survival and
Complications Following Surgery and Radiation for Localized Prostate
Cancer: An International Collaborative Review. Eur Urol. 2018 Jan;
73(1):11-20.
\602\ Huang X, Wang L, Zheng X, Wang X. Comparison of
perioperative, functional, and oncologic outcomes between standard
laparoscopic and robotic-assisted radical prostatectomy: a systemic
review and meta-analysis. Surg Endosc. 2017 Mar; 31(3):1045-1060.
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The proposed measure would be calculated using information from
Medicare fee-for-service (FFS) claims, resulting in no new data
reporting for PCHs. We would publicly report the measure results to
enable patients to make informed decisions about accessing localized
prostate surgery and about the rates of potential complications. We
will identify a specified timeframe for public reporting of this
measure in future rulemaking. In addition, we note that there are
currently no measures assessing complications of prostate surgery in
the PCHQR Program measure set.
(3) Data Sources
We are proposing that we would calculate this measure on a yearly
basis using Medicare administrative claims data. Specifically, we are
proposing that the data collection period for each program year would
span from July 1 of the year 2 years prior to the start of the program
year to June 30 of the year 1 year prior to the start of the program
year. Therefore, for the FY 2022 program year, we would begin
calculating measure rates using PCH claims data from July 1, 2019
through June 30, 2020.
During the development of the measure, the measure steward convened
a technical expert panel (TEP), comprising diverse clinical and quality
measurement experts from the 11 PPS-exempt cancer hospitals, in 2016.
We note that the TEP endorsed the ICHOM's recommendation to measure
prostate-directed surgical treatment complication. Because the measure
methodology assesses complications pre-surgery and post-surgery
directed to the prostate, this necessitates the availability of claims
data. In order to examine data collection burden and data reliability,
the TEP requested an analysis of using Medicare claims to assess
treatment complications in the ICHOM standard set. For this purpose, a
SEER-Medicare dataset \603\ was used to validate Medicare claims data.
SEER datasets are commonly considered ``gold standard'' data for cancer
stage and other clinical characteristics, and are often used to
validate Medicare claims data, which are lacking in these details. The
results of this analysis showed that the claims-based algorithm used by
the
[[Page 19505]]
measure could successfully identify patients with prostate cancer,
thereby substantiating the use of Medicare claims as the data source
for this measure.
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\603\ SEER-Medicare Dataset. Available at: https://healthcaredelivery.cancer.gov/seermedicare/overview/.
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(4) Measure Calculation
This outcome measure analyzes hospital/facility-level variation in
patient-relevant outcomes during the year after prostate-directed
surgery. Specifically, the measure uses claims to identify urinary
incontinence and erectile dysfunction among patients undergoing
localized prostate cancer surgery and uses this information to derive
hospital-specific rates. Those outcomes are rescaled to a 0-100 scale,
with 0=worst and 100=best. The numerator includes patients with
diagnosis claims that could indicate adverse outcomes following
prostate-directed surgery. The numerator is determined by: (1)
Calculating the difference in the number of days with claims for
incontinence or erectile dysfunction in the year after versus the year
before prostate surgery for each patient; (2) truncating (by
Winsorizing) to reduce the impact of outliers; (3) rescaling the
difference from 0 (worst) to 100 (best); and (4) calculating the mean
score for each hospital based on all of the difference values for all
of the patients treated at that hospital. The denominator is determined
by the following: Men age 66 or older at the time of prostate cancer
diagnosis with at least two ICD diagnosis codes for prostate cancer
separated by at least 30 days; men who survived at least one year after
prostate directed therapy; codes for prostate cancer surgery (either
open or minimally invasive/robotic prostatectomy) at any time after the
first prostate cancer diagnosis; and continuous enrollment in Medicare
Parts A and B (and no Medicare Part C (Medicare Advantage) enrollment))
from one year before through one year after prostate directed therapy.
The measure code lists include all codes required for the numerator and
denominator calculation.\604\
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\604\ 2018-2019 Measure Applications Partnership Workgroup Final
Recommendations Excel spreadsheet. Available at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
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The proposed measure excludes patients with metastatic disease,
patients with more than one nondermatologic malignancy, patients
receiving chemotherapy, patients receiving radiation, and/or patients
who die within 1 year after prostatectomy. We note that the validity of
this measure would be threatened by inclusion of patients who did not
meet the denominator criteria. Specifically, patients with more than
one nondermatologic malignancy are excluded because a second cancer
diagnosis during the measurement period could influence the outcomes.
Further, patients receiving chemotherapy are excluded because
guidelines for localized prostate cancers do not recommend chemotherapy
for routine care; therefore, chemotherapy can indicate advanced disease
or other unique clinical characteristics. Patients receiving radiation
therapy are excluded because radiation therapy to the prostate can
impact the occurrence of complications in these patients. Therefore,
the impact of the surgery versus the radiation therapy in these
patients cannot be determined. Lastly, patients who die within 1 year
after prostatectomy are excluded because death is highly unlikely to be
related to localized prostate cancer and unlikely to be related to the
surgical complications. Thus, patients who die within the year
following surgery likely die from an unrelated reason. As such, the
measure will be calculated as the numerator divided by the denominator
(in accordance with the denominator exclusions described above).
Complete measure specifications for the proposed measure are available
in the ``2018 Measures Under Consideration List'' Excel file, which can
be accessed at: http://www.qualityforum.org/map/.
(5) Cohort
This measure includes adult male Medicare FFS beneficiaries, age 66
years and older, who have received prostate cancer directed surgery
within the defined measurement period. We note that this measure cohort
was determined in accordance with the defined measure denominator and
its specified exclusions (discussed above) and based on testing
conducted on the minimum number of patients attributed to the hospital
associated with the claims for the procedure code for prostatectomy.
The age of 66 at the time of prostate cancer diagnosis was chosen
because per the denominator, a patient must have had Medicare claims
data for 1 year prior to and 1 year after surgery. Additional
methodology and measure development details are available in the ``2018
Measures Under Consideration List,'' which can be accessed at: http://www.qualityforum.org/map/.
(6) Risk Adjustment
The measure steward developed a mock risk-adjustment testing
protocol based on the case-mix variables identified in the ICHOM data
dictionary,\605\ and TEP guidance. Specifically, the measure steward
identified covariates that could be incorporated for potential risk-
adjustment modeling. The covariates were not limited to those available
in claims data; clinical covariates were also identified for analysis
from SEER to determine adequacy of claims alone for valid measurement.
Specifically, the following patient factors were controlled for when
deriving the patient-level complication score: Age; year of surgery;
other/unknown prostate cancer grade; and prostatectomy type.
Hierarchical linear modeling was used to identify which patient, tumor,
and hospital factors are associated with a higher IED score. After
review of the results of the mock risk-adjustment testing efforts, it
was determined that risk adjusting the measure did not yield results
that demonstrate any statistically significant differences from the
non-risk-adjusted results. The measure steward analyzed the correlation
between the unadjusted performance scores and risk-adjusted performance
scores, and observed that the correlation coefficients were above 95
percent in both analyses. Consequently, the measure steward elected to
finalize the development of the measure without the implementation of a
risk-adjustment model.
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\605\ International Consortium for Health Outcomes Measurement
(ICHOM) in the Localized Prostate Cancer Standard Set. https://www.ichom.org/medical-conditions/localized-prostate-cancer/.
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(7) Measure Application Partnership (MAP) Assessment of the Proposed
Measure
In compliance with section 1890A(a)(2) of the Act, the proposed
measure was included on a publicly available document entitled ``2018
Measures under Consideration Spreadsheet,'' \606\ a list of quality and
efficiency measures under consideration for use in various Medicare
programs, and was reviewed by the MAP Hospital Workgroup. The MAP noted
the importance of patient-relevant outcomes for patients who have
undergone surgical treatment for prostate care, but encouraged CMS to
resubmit the measure once the measure developer has better streamlined
the reliability and validity testing methodologies.\607\
[[Page 19506]]
Specifically, the MAP discussed the differences between surgical
procedures (for example, open, closed, minimally invasive, robotic,
among others) and recommended that non-open procedures be grouped
separately.\608\ The MAP also suggested the measure be risk-adjusted
because of the concern of different rates of complications related to
how the surgery is performed.\609\
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\606\ Measures Application Partnership ``2018 measures Under
Consideration Spreadsheet.'' Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=88813.
\607\ MAP 2019 Considerations for Implementing Measures, Final
Report. Available at: http://www.qualityforum.org/Publications/2019/02/MAP_2019_Considerations_for_Implementing_Measures_Final_Report_-_Hospitals.aspx.
\608\ Ibid.
\609\ Ibid.
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In response to the concern raised by the MAP regarding the grouping
of surgical procedures, we note that the measure is intended to
calculate one overall facility rate for accountability purposes.
However, given the guidance from the MAP, the steward has notified CMS
that each hospital's performance will be stratified by prostatectomy
procedure type (open versus not open) to add meaning for consumers and
for hospital quality improvement. In response to the MAP's question of
risk-adjustment, we note that risk-adjustment is limited for cancer
patients when using claims data (for example, cancer stage not captured
in claims data). Despite this, we reiterate that the steward conducted
a mock risk-adjustment testing protocol and observed that risk-
adjusting the measure did not demonstrate any statistically significant
differences. As such, the steward chose not to include the risk-
adjustment methodology for the measure.
Currently, we are unaware of an alternative quality measure
assessing this measurement topic that is appropriate for the PCHQR
Program. This measure is not endorsed by the NQF, and in our
environmental scan of the NQF measures portfolio, we have not been able
to identify a feasible and practical endorsed measure that addresses
surgical procedures for localized prostate cancer. We believe this
measure meets the requirement under section 1866(k)(3)(B) of the Act,
which provides that in the case of a specified area or medical topic
determined appropriate by the Secretary for which a feasible and
practical measure has not been endorsed by the entity with a contract
under section 1890(a) of the Act, the Secretary may specify a measure
that is not so endorsed as long as due consideration is given to
measures that have been endorsed or adopted by a consensus organization
identified by the Secretary. In addition, we note this measure aligns
with recent initiatives to increase the number of outcome measures in
quality reporting programs. Lastly, this measure also aligns with the
``Make Care Safer by Reducing Harm Caused in the Delivery of Care''
domain of our Meaningful Measures Initiative,\610\ and would fill an
existing gap area of patient-focused episode of care in the PCHQR
Program.
---------------------------------------------------------------------------
\610\ Overview of CMS ``Meaningful Measures'' Initiative.
Available at: https://www.cms.gov/Newsroom/MediaReleaseDatabase/Press-releases/2017-Press-releases-items/2017-10-30.html.
---------------------------------------------------------------------------
(8) Proposed Adoption of the Surgical Treatment Complications for
Localized Prostate Cancer Measure
We believe this measure would be a valuable addition to the PCHQR
Program because it is a high impact (as prostate cancer is a prevalent
disease) outcome measure and it addresses reduction in harm. This is a
hospital/facility-level, claims-based measure that analyzes variation
in the occurrence of incontinence and/or erectile dysfunction during
the year after prostate-directed surgery, which is one of the standard
treatments for localized prostate cancer. Further, this measure has the
potential to improve patient outcomes and decrease costs associated
with managing adverse events. By identifying facilities where adverse
outcomes associated with prostatectomy are more common, this measure
would help to highlight opportunities for quality improvement that
address unwarranted variation. This will facilitate improved compliance
with guidelines from the American Urology Association (AUA) and other
professional societies that call for minimizing the potential for
therapy-related adverse outcomes.\611\
---------------------------------------------------------------------------
\611\ Prostate Cancer Clinical Guidelines. Available at: http://www.auanet.org/guidelines/clinically-localized-prostate-cancer-new-
(aua/astro/suo-guideline-2017.
---------------------------------------------------------------------------
Lastly, this measure could be utilized as a tool to foster quality
improvement and optimize outcomes for patients with localized prostate
cancer. For the reasons outlined above, we are proposing to adopt the
Surgical Treatment Complications for Localized Prostate Cancer measure
for the FY 2022 program year and subsequent years.
c. Summary of Previously Finalized and Proposed PCHQR Program Measures
for the FY 2022 Program Year and Subsequent Years
The table below summarizes the PCHQR Program measure set for the FY
2022 program year if we finalized our proposal to remove the External
Beam Radiotherapy (EBRT) for Bone Metastases measure and our proposal
to adopt the proposed Surgical Treatment Complications for Localized
Prostate Cancer measure.
FY 2022 PCHQR Program Measure Set if Proposals To Remove One Measure and
Adopt One Measure are Finalized
------------------------------------------------------------------------
Short name NQF No. Measure name
------------------------------------------------------------------------
Safety and Healthcare-Associated Infection (HAI)
------------------------------------------------------------------------
CAUTI.......................... 0138 Catheter-associated
Urinary Tract
Infection (CAUTI)
Outcome Measure.
CLABSI......................... 0139 Central Line-associated
Bloodstream Infection
(CLABSI) Outcome
Measure.
HCP............................ 0431 National Healthcare
Safety Network (NHSN)
Influenza Vaccination
Coverage Among
Healthcare Personnel.
Colon and Abdominal 0753 American College of
Hysterectomy SSI. Surgeons--Centers for
Disease Control and
Prevention (ACS-CDC)
Harmonized Procedure
Specific Surgical Site
Infection (SSI)
Outcome Measure
[currently includes
SSIs following Colon
Surgery and Abdominal
Hysterectomy Surgery].
MRSA........................... 1716 National Healthcare
Safety Network (NHSN)
Facility[dash]wide
Inpatient Hospital-
onset
Methicillin[dash]resis
tant Staphylococcus
aureus Bacteremia
Outcome Measure.
CDI............................ 1717 National Healthcare
Safety Network (NHSN)
Facility[dash]wide
Inpatient Hospital-
onset Clostridium
difficile Infection
(CDI) Outcome Measure.
------------------------------------------------------------------------
Clinical Process/Oncology Care Measures
------------------------------------------------------------------------
EOL-Chemo...................... 0210 Proportion of Patients
Who Died from Cancer
Receiving Chemotherapy
in the Last 14 Days of
Life.
EOL-Hospice.................... 0215 Proportion of Patients
Who Died from Cancer
Not Admitted to
Hospice.
[[Page 19507]]
N/A............................ 0383 Oncology: Plan of Care
for Pain--Medical
Oncology and Radiation
Oncology.
------------------------------------------------------------------------
Intermediate Clinical Outcome Measures
------------------------------------------------------------------------
EOL-ICU........................ 0213 Proportion of Patients
Who Died from Cancer
Admitted to the ICU in
the Last 30 Days of
Life.
EOL-3DH........................ 0216 Proportion of Patients
Who Died from Cancer
Admitted to Hospice
for Less Than Three
Days.
------------------------------------------------------------------------
Patient Engagement/Experience of Care
------------------------------------------------------------------------
HCAHPS......................... 0166 Hospital Consumer
Assessment of
Healthcare Providers
and Systems.
------------------------------------------------------------------------
Claims Based Outcome Measures
------------------------------------------------------------------------
N/A............................ N/A Admissions and
Emergency Department
(ED) Visits for
Patients Receiving
Outpatient
Chemotherapy.
N/A............................ 3188 30-Day Unplanned
Readmissions for
Cancer Patients.
N/A*........................... N/A Surgical Treatment
Complications for
Localized Prostate
Cancer Measure.
------------------------------------------------------------------------
* Measure proposed for adoption for the FY 2022 program year and
subsequent years.
6. Possible New Quality Measure Topics for Future Years
a. Background
As discussed in section I.A.2. of the preamble of the FY 2019 IPPS/
LTCH PPS final rule (83 FR 41147 through 41148), we have begun
analyzing our quality reporting and quality payment programs' measures
using the framework we developed for the Meaningful Measures
Initiative. We have also discussed future quality measure topics and
quality measure domain areas in the FY 2015 IPPS/LTCH PPS final rule
(79 FR 50280), the FY 2016 IPPS/LTCH PPS final rule (80 FR 4979), the
FY 2017 IPPS/LTCH PPS final rule (81 FR 25211), the FY 2018 IPPS/LTCH
PPS final rule (82 FR 38421 through 38423), and the FY 2019 IPPS/LTCH
PPS final rule (83 FR 41618 through 41621).
In this proposed rule, we are again seeking public comment on the
topics we should consider for quality measurement in the PCHQR Program.
We are particularly interested in public comments on measures that
could balance the need to assess pain management against efforts to
ensure that providers are not incentivized to overprescribe opioids to
patients in the PCH setting. We also are seeking public comment on
potential future measures that could assess alternative pain management
methodologies for cancer patients.
b. Overview of Pain Management Issues and Request for Comments on Pain
Management Measures and Measurement Concepts for the Cancer Patient
Population
As discussed earlier, we are proposing to remove the current pain
management questions from the version of the HCAHPS Survey implemented
in the PCHQR Program beginning with October 1, 2019 discharges in order
to avoid any potential unintended consequences related to the
perception that providers may be incentivized to overprescribe opioids
to cancer patients. The opioid epidemic is a national crisis, and we
are interested in the feasibility of adopting quality measures that
examine a PCH's utilization of pain management strategies other than
opioid prescriptions when furnishing care to its patients. We recognize
that unintended opioid overdose fatalities have reached epidemic
proportions in the last 20 years and are a major public health concern
in the United States.\612\ As such, reducing the number of unintended
opioid overdoses is a priority for HHS. Concurrent prescriptions of
opioids or opioids and benzodiazepines put patients at greater risk of
unintended opioid overdose due to increased risk of respiratory
depression.613 614 In addition, an analysis of more than 1
million hospital admissions in the United States found that over 43
percent of all patients with nonsurgical admissions were exposed to
multiple opioids during their hospitalization.\615\ As such, we believe
that it is imperative to not inadvertently support the over-
prescription of opioids by promoting opioids as a primary pain
management remedy for cancer patients. In conjunction with that, we
also recognize the need to be responsive to the unique needs of the
cancer patient cohort by continually examining the quality measurement
landscape for quality measures that balance pain management with
efforts to address the opioid epidemic.
---------------------------------------------------------------------------
\612\ Rudd, R., Aleshire, N., Zibbell, J., et al. ``Increases in
Drug and Opioid Overdose Deaths--United States, 2000-2014.'' MMWR,
Jan 2016. 64(50);1378-82. Available at: http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6450a3.htm.
\613\ Dowell, D., Haegerich, T., Chou, R. ``CDC Guideline for
Prescribing Opioids for Chronic Pain--United States, 2016.'' MMWR
Recomm Rep 2016;65. Available at: http://www.cdc.gov/media/dpk/2016/dpk-opioid-prescription-guidelines.html.
\614\ Jena, A., et al. ``Opioid prescribing by multiple
providers in Medicare: retrospective observational study of
insurance claims.'' BMJ. 2014; 348:g1393 doi: 10.1136/bmj.g1393.
Available at: http://www.bmj.com/content/348/bmj.g1393.
\615\ Herzig, S., Rothberg, M., Cheung, M., et al. ``Opioid
utilization and opioid-related adverse events in nonsurgical
patients in U.S. hospitals.'' Nov 2013. DOI: 10.1002/jhm.2102.
Available at: http://onlinelibrary.wiley.com/doi/10.1002/jhm.2102/abstract.
---------------------------------------------------------------------------
We recognize the importance of including quality measures that
adequately assess cancer patient pain and quality measures that assess
a PCH's use of alternative pain management methodologies. We believe
that these types of measures can assess critical components of cancer
care. Studies examining the frequency and quality of cancer pain
management show room for improvement in these areas--for example, a
systematic review revealed that, despite a 25-percent decrease in
under-treatment of cancer pain between 2007 and 2013, approximately
one-third of patients living with cancer still have pain that is
inadequately treated.\616\ Further, postsurgical complications related
to inadequate pain management negatively affect patient welfare and
hospital performance because of extended lengths of stay and
readmissions, both
[[Page 19508]]
of which increase the cost of care.\617\ This raises concern in the
context of the patient safety issues related to pain management (that
is, a patient's physical safety during the administration of sedatives
and complications associated with catheter administration).\618\ In
addition, patients who have not been treated adequately for pain
management may be reluctant to seek medical care for other health
problems.\619\
---------------------------------------------------------------------------
\616\ Optimal Pain Management for Patients with Cancer in the
Modern Era. Available at: https://onlinelibrary.wiley.com/doi/full/10.3322/caac.21453.
\617\ Patient Safety and Quality: An Evidence-Based Handbook for
Nurses. Available at: https://www.ncbi.nlm.nih.gov/books/NBK2658/.
\618\ Ibid.
\619\ Ibid.
---------------------------------------------------------------------------
On August 7, 2018, the Alliance of Dedicated Cancer Centers,\620\
which is a consortium of cancer hospitals that includes among its
members 10 of the 11 participating PCHs for the PCHQR Program, convened
a group of expert stakeholders to discuss and provide recommendations
regarding best practices for the future of pain measurement among
cancer patients, within the context of the opioid crisis in the United
States. Participants included cancer patient advocates, clinicians,
researchers, and health care quality professionals. The participants
discussed the pros and cons of various methods to collect and report
performance measures related to cancer pain and cancer pain management.
The participants acknowledged the importance of addressing the national
opioid crisis. However, for cancer patients specifically, the
participants unanimously supported ongoing pain-related quality
measurement. Further, the participants indicated that the relatively
high prevalence of pain symptoms in the cancer patient population,\621\
particularly in patients with advanced disease or metastatic cancer,
underscores the need for feasible, valid, and reliable pain measures.
They also added that pain assessment offers clinicians the greatest
utility when the information collected can be used to identify
personalized pain management goals for patients.
---------------------------------------------------------------------------
\620\ Alliance of Dedicate Cancer Centers website: http://www.adcc.org/.
\621\ National Quality Forum. Patient Reported Outcomes (PROs)
in Performance Measurement. Available at: http://www.qualityforum.org/Publications/2012/12/Patient-Reported_Outcomes_in_Performance_Measurement.aspx. Published
December 2012.
---------------------------------------------------------------------------
Further, we are aware of the existence of other cancer-specific,
non-survey, patient experience assessment tools that evaluate cancer
patient pain and may be more appropriate than the HCAHPS Survey pain
questions which we are proposing to remove in this proposed rule. As
such, we believe there should be consideration given to the use of
pain-related patient experience items for cancer patients, with a
shifting focus toward Patient-Reported Outcome (PRO)-Performance
Measures (PRO-PMs) in the mid and longer term (for example, 3 years, 5
years). Specifically, a growing body of research demonstrates the
benefits of integration of PROs into oncology practice, including
improved patient outcomes and survival.622 623
---------------------------------------------------------------------------
\622\ Basch E, Deal AM, Dueck AC, et al. Overall Survival
Results of a Trial Assessing Patient-Reported Outcomes for Symptom
Monitoring During Routine Cancer Treatment. JAMA. 2017; 318(2):197-
198. doi:10.1001/jama.2017.7156.
\623\ Denis, F et al. Patient-Reported Outcomes, Mobile
Technology, and Response Burden. 2018 ASCO Annual Meeting. Abstract
No: 6500.
---------------------------------------------------------------------------
Accordingly, we are seeking public comment on measures and
measurement concepts that can be further developed that would assess
appropriate pain management in the cancer patient population. Specific
topics could include measures that assess cancer patient safety,
patient and family education, and patient experience and engagement
(specifically PRO-PMs) in the context of cancer pain management. We are
inviting public comment on the potential future adoption of measures
that assess post-treatment addiction prevention for cancer patients.
Lastly, we are inviting public comment on existing measures or
measurement concepts that evaluate pain management for cancer patients,
and do not involve opioid use.
7. Maintenance of Technical Specifications for Quality Measures
We maintain technical specifications for the PCHQR Program
measures, and we periodically update those specifications. The
specifications may be found on the QualityNet website at: https://qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier2&cid=1228774479863.
We also use a subregulatory process to make nonsubstantive updates
to measures used for the PCHQR Program (79 FR 50281).
8. Public Display Requirements
a. Background
Under section 1866(k)(4) of the Act, we are required to establish
procedures for making the data submitted under the PCHQR Program
available to the public. Such procedures must ensure that a PCH has the
opportunity to review the data that are to be made public with respect
to the PCH prior to such data being made public. Section 1866(k)(4) of
the Act also provides that the Secretary must report quality measures
of process, structure, outcome, patients' perspective on care,
efficiency, and costs of care that relate to services furnished in such
hospitals on the CMS website.
In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57191 through
57192), we finalized that although we would continue to use rulemaking
to establish what year we first publicly report data on each measure,
we would publish the data as soon as feasible during that year. We also
stated that our intent is to make the data available on at least a
yearly basis, and that the time period for PCHs to review their data
before the data are made public would be approximately 30 days in
length. We announce the exact data review and public reporting
timeframes on a CMS website and/or on our applicable Listservs.
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41623) and the CY
2019 OPPS/ASC final rule with comment period (83 FR 59149 through
59153), we finalized our public display requirements for the FY 2021
program year.
We recognize the importance of being transparent with stakeholders
and keeping them abreast of any changes that arise with the PCHQR
Program measure set. As such, we are making two proposals in this
proposed rule regarding the timetable for the public display of data
for specific PCHQR Program measures.
b. Proposed Public Display of the Admissions and Emergency Department
(ED) Visits for Patients Receiving Outpatient Chemotherapy Measure
Beginning With CY 2020
We are proposing to begin public reporting of the Admissions and
Emergency Department (ED) Visits for Patients Receiving Outpatient
Chemotherapy measure in CY 2020. In the FY 2017 IPPS/LTCH PPS final
rule (81 FR 57187), we stated that we would publicly report the risk-
standardized admission rate (RSAR) and risk-standardized ED visit rate
(RSEDR) for the Admissions and Emergency Department (ED) Visits for the
Patients Receiving Outpatient Chemotherapy measure for all
participating PCHs with 25 or more eligible patients per measurement
period. We stated that this threshold allowed us to maintain a
reliability of at least 0.4 for publicly reported data (as measured by
the interclass correlation coefficient (ICC). We also noted that if a
PCH did not meet the 25-eligible patient threshold, we would include a
footnote on the Hospital Compare website indicating that the number of
cases is too small to reliably measure that PCH's rate, but
[[Page 19509]]
that these patients and PCHs would still be included when calculating
the national rates for both the RSAR and RSEDR (81 FR 57187). To
prepare PCHs for the public reporting of this measure, we also
indicated that we would conduct a confidential national reporting (dry
run) of measure results. The objectives of the confidential national
reporting were to: (1) Educate PCHs and other stakeholders about the
measure; (2) allow PCHs to review their measure results and data prior
to public reporting; (3) answer questions from PCHs and other
stakeholders; (4) test the production and reporting process; and (5)
identify potential technical changes to the measure specifications that
might be needed.
We recently completed the confidential national reporting for this
measure and have assessed the preliminary results to ensure data
accuracy and completeness. Further, we confidentially reported results
for the measure to the participating PCHs in October 2018, based on
Medicare claims data that were collected on chemotherapy treatments
performed from July 1, 2016-June 30, 2017. To execute this confidential
reporting, we utilized facility-specific reports (FSRs), which allow
facilities to preview measure results and patient data prior to public
reporting. The FSRs included the following elements: Measure
performance results; national results; detailed patient-level data used
to calculate measure results; and a summary of each facility's patient-
mix. To ensure continuity in the observed measure performance results,
we intend to complete a subsequent round of confidential national
reporting in the spring of 2019, using Medicare claims data from July
1, 2017 through June 30, 2018.
Given the success of our first round of confidential reporting and
the associated timeline of our subsequent round of confidential
reporting, we are proposing to begin publicly reporting performance
data on the Admissions and Emergency Department (ED) Visits for
Patients Receiving Outpatient Chemotherapy measure in CY 2020. We
believe that this proposed timeline allows for more accurate assessment
of measure results and allows both CMS and the participating PCHs
adequate time to review all the confidential reporting results.
c. Public Display of Centers for Disease Control and Prevention (CDC)
National Healthcare Safety Network (NHSN) Measures
(1) Proposed Public Display of the Colon and Abdominal Hysterectomy
SSI, MRSA, CDI and HCP Measures in CY 2019
At present, all PCHs are reporting the CDC NHSN Healthcare-
Associated Infection (HAI) Colon and Abdominal Hysterectomy SSI, MRSA,
CDI, and HCP data to the National Healthcare Safety Network (NHSN) for
purposes of the PCHQR Program. We finalized in the FY 2019 IPPS/LTCH
PPS final rule (83 FR 41622) that we would provide stakeholders with
performance data for these measures as soon as practicable (that is, we
will publicly report it on the Hospital Compare website via the next
available Hospital Compare release). In addition, we noted that the CDC
announced that HAI data reported to the NHSN for 2015 will be used as
the new baseline, serving as a new ``reference point'' for comparing
progress.\624\ Currently, these rebaselining efforts--specifically,
generation and implementation of new predictive models used to
calculate SIRs--are complete. As such, we are proposing to publicly
report data for the Colon and Abdominal Hysterectomy SSI, MRSA, CDI,
and HCP measures beginning with the October 2019 Hospital Compare
release.
---------------------------------------------------------------------------
\624\ Centers for Disease Control and Prevention. ``Paving Path
Forward: 2015 Rebase line.'' Available at: https://www.cdc.gov/nhsn/2015rebaseline/index.html.
---------------------------------------------------------------------------
(2) Continued Deferral of Public Display of the CAUTI and CLABSI
Measures
In the CY 2019 OPPS/ASC final rule with comment period (83 FR 59149
through 59153), we finalized that we would not remove the Catheter-
Associated Urinary Tract Infection (CAUTI) Outcome Measure (PCH-5/NQF
#0138) and the Central Line-Associated Bloodstream Infection (CLABSI)
Outcome Measure (PCH-4/NQF #0139) from the PCHQR measure set. We also
noted that we will continue to defer public reporting for the CAUTI and
CLABSI measures (83 FR 59153).
We are continuing to work alongside the CDC to evaluate the
performance data for the updated, risk-adjusted versions of the CAUTI
and CLABSI measures so that we can draw conclusions about their
statistical significance in accordance with current risk adjustment
methods defined by CDC. In order to allow adequate time for data
collection by the CDC, submission of those data to CMS, and our review
of the data for accuracy and completeness, we believe that the earliest
we will be able to publicly display information on the revised versions
of the CAUTI and CLABSI measures will be CY 2022. Therefore, we will
continue to defer public reporting of the CAUTI and CLABSI measures and
intend to provide stakeholders with performance data on the measures as
soon as practicable.
d. Summary of Previously Finalized and Proposed Public Display
Requirements for the PCHQR Program
Our previously finalized and proposed public display requirements
for the PCHQR Program are shown in the following table:
Previously Finalized and Proposed Public Display Requirements for the
PCHQR Program
[Summary of previously adopted and newly proposed public display
requirements]
------------------------------------------------------------------------
Measures Public reporting
------------------------------------------------------------------------
HCAHPS (NQF #0166) *................... 2016 and subsequent
years.
Oncology: Plan of Care for Pain-- ......................
Medical Oncology and Radiation Oncology (NQF
#0383).
External Beam Radiotherapy for Bone 2017 and subsequent
Metastases (EBRT) (NQF #1822) **. years.
American College of Surgeons--Centers October of CY 2019.
for Disease Control and Prevention (ACS-CDC)
Harmonized Procedure Specific Surgical Site
Infection (SSI) Outcome Measure [currently
includes SSIs following Colon Surgery and
Abdominal Hysterectomy Surgery] (NQF #0753).
National Healthcare Safety Network ......................
(NHSN) Facility[dash]wide Inpatient Hospital-
onset Methicillin[dash]resistant Staphylococcus
aureus Bacteremia Outcome Measure (NQF #1716).
National Healthcare Safety Network ......................
(NHSN) Facility[dash]wide Inpatient Hospital-
onset Clostridium difficile Infection (CDI)
Outcome Measure (NQF #1717).
National Healthcare Safety Network ......................
(NHSN) Influenza Vaccination Coverage Among
Healthcare Personnel (NQF #0431).
[[Page 19510]]
Admissions and Emergency Department CY 2020.
(ED) Visits for Patients Receiving Outpatient
Chemotherapy.
CAUTI (NQF #0138)...................... Deferred until CY
2022.
CLABSI (NQF #0139)..................... ......................
------------------------------------------------------------------------
* In section VIII.B.2.b. of the preamble of this this proposed rule, we
are proposing that beginning with October 2018 discharges, publicly
reported data will not include responses Pain Management questions.
** In section VIII.B.4. of the preamble of this this proposed rule, we
are proposing to remove this measure, beginning with the FY 2022
program year.
9. Form, Manner, and Timing of Data Submission
a. Background
Data submission requirements and deadlines for the PCHQR Program
are posted on the QualityNet website at: http://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228772864228.
b. Proposed Confidential National Reporting for Certain Existing PCHQR
Measures
We are proposing to conduct a confidential national reporting for
data collection of the following measures in the PCHQR measure set:
Proportion of patients who died from cancer receiving
chemotherapy in the last 14 days of life (NQF #0210);
Proportion of patients who died from cancer admitted to
the ICU in the last 30 days of life (NQF #0213);
Proportion of patients who died from cancer not admitted
to hospice (NQF #0215);
Proportion of patients who died from cancer admitted to
hospice for less than 3 days (NQF #0216); and
30-Day Unplanned Readmissions for Cancer Patients measure
(NQF #3188).
(1) Background
We initially adopted the four end-of-life care measures in the FY
2018 IPPS/LTCH PPS final rule (82 FR 38414 through 38420) for inclusion
in the PCHQR Program beginning with the FY 2020 program year. We also
finalized that the initial data collection period would be from July 1,
2017 through June 30, 2018 (82 FR 38424). After we adopted the
measures, the American Society of Clinical Oncology (ASCO), which is
the measure steward, updated their technical specifications. We believe
that these updates are not substantive and that we do not need to use
the rulemaking process to incorporate them. We also note that there has
been no change in the measures' data source. Specifically, the measures
will continue to be calculated using Medicare claims data.
We initially adopted the 30-Day Unplanned Readmissions for Cancer
Patients measure (NQF #3188) in the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41614 through 41616). This is also a claims-based measure;
adopted for implementation beginning with the FY 2021 program year and
with an initial data collection period of October 1, 2018 through
September 30, 2019 (83 FR 41616).
(2) Proposed Confidential National Reporting for Data Collection
To prepare PCHs for public reporting, we are proposing to conduct
two confidential reporting periods of measure results prior to public
reporting. Consistent with previous confidential national reporting
efforts for measures in the PCHQR Program, the objectives of the
confidential national reporting are to: (1) Educate PCHs and other
stakeholders about the measures; (2) allow PCHs to review their measure
results and data prior to public reporting; (3) answer questions from
PCHs and other stakeholders; (4) test the production and reporting
process; and (5) identify potential additional technical changes to the
measure specifications that might be needed. We believe these
confidential national reporting activities will enable hospitals to
gain data collection and reporting experience familiarity with these
refined measures for their efforts to improve quality and better
understand the measure specifications and associated data. Confidential
national reporting is important because it affords CMS an opportunity
to examine a measure's performance prior to publicly sharing data with
stakeholders and is a method of ensuring that the publicly reported
measure performance results are as accurate as possible. Confidential
national reporting will also allow both CMS and participating PCHs
adequate time to review all the performance results for the respective
measures. This will mitigate the possibility of CMS having to suppress
inaccurate and/or inadequate measure data, because we will have had an
opportunity to preview it over a broader span of time than the standard
30-day preview period associated with public reporting.
For the group end-of-life care measures, we are proposing to
conduct confidential national reporting using Medicare claims data
collected from July 1, 2019 through June 30, 2020. For the 30-Day
Unplanned Readmissions for Cancer Patients measure, we are proposing to
conduct confidential national reporting using Medicare claims data
collected from October 1, 2019 through September 30, 2020. We plan to
include measure results from the confidential national reporting in the
facility-specific feedback reports (FSRs) that we provide to PCHs. The
FSRs will include the following elements: Measure performance results,
national results (based on the performance of the 11 PCHs), detailed
patient-level data used to calculate measure results and a summary of
each PCH's patient-mix.
10. Extraordinary Circumstances Exceptions (ECE) Policy Under the PCHQR
Program
We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR
41623 through 41624), for a discussion of the Extraordinary
Circumstances Exceptions (ECE) policy under the PCHQR Program. In this
proposed rule, we are not proposing any changes to this policy.
C. Long-Term Care Hospital Quality Reporting Program (LTCH QRP)
1. Background
The Long-Term Care Hospital Quality Reporting Program (LTCH QRP) is
authorized by section 1886(m)(5) of the Act, and it applies to all
hospitals certified by Medicare as long-term care hospitals (LTCHs).
Under the LTCH QRP, the Secretary must reduce by 2 percentage points
the annual update to the LTCH PPS standard Federal rate for discharges
for an LTCH during a fiscal year if the LTCH has not complied with the
LTCH QRP requirements specified for that fiscal year. For more
information on the requirements we
[[Page 19511]]
have adopted for the LTCH QRP, we refer readers to the FY 2012 IPPS/
LTCH PPS final rule (76 FR 51743 through 51744), the FY 2013 IPPS/LTCH
PPS final rule (77 FR 53614), the FY 2014 IPPS/LTCH PPS final rule (78
FR 50853), the FY 2015 IPPS/LTCH PPS final rule (79 FR 50286), the FY
2016 IPPS/LTCH PPS final rule (80 FR 49723 through 49725), the FY 2017
IPPS/LTCH PPS final rule (81 FR 57193), the FY 2018 IPPS/LTCH PPS final
rule (82 FR 38425 through 38426), and the FY 2019 IPPS/LTCH PPS final
rule (83 FR 41624 through 41634).
2. General Considerations Used for the Selection of Measures for the
LTCH QRP
For a detailed discussion of the considerations we historically
used for the selection of LTCH QRP quality, resource use, and other
measures, we refer readers to the FY 2016 IPPS/LTCH PPS final rule (80
FR 49728).
3. Quality Measures Currently Adopted for the FY 2021 LTCH QRP
The LTCH QRP currently has 15 measures for the FY 2021 LTCH QRP,
which are set out in the following table:
Quality Measures Currently Adopted for the FY 2021 LTCH QRP
------------------------------------------------------------------------
Short name Measure name and data source
------------------------------------------------------------------------
LTCH CARE Data Set
------------------------------------------------------------------------
Pressure Ulcer/Injury........ Changes in Skin Integrity Post-Acute
Care: Pressure Ulcer/Injury.
Application of Falls......... Application of Percent of Residents
Experiencing One or More Falls with
Major Injury (Long Stay) (NQF #0674).
Functional Assessment........ Percent of Long-Term Care Hospital (LTCH)
Patients with an Admission and Discharge
Functional Assessment and a Care Plan
That Addresses Function (NQF #2631).
Application of Functional Application of Percent of Long-Term Care
Assessment. Hospital (LTCH) Patients with an
Admission and Discharge Functional
Assessment and a Care Plan That
Addresses Function (NQF #2631).
Change in Mobility........... Functional Outcome Measure: Change in
Mobility Among Long-Term Care Hospital
(LTCH) Patients Requiring Ventilator
Support (NQF #2632).
DRR.......................... Drug Regimen Review Conducted With Follow-
Up for Identified Issues-Post Acute Care
(PAC) Long-Term Care Hospital (LTCH)
Quality Reporting Program (QRP).
Compliance with SBT.......... Compliance with Spontaneous Breathing
Trial (SBT) by Day 2 of the LTCH Stay.
Ventilator Liberation........ Ventilator Liberation Rate.
------------------------------------------------------------------------
NHSN
------------------------------------------------------------------------
CAUTI........................ National Healthcare Safety Network (NHSN)
Catheter-Associated Urinary Tract
Infection (CAUTI) Outcome Measure (NQF
#0138).
CLABSI....................... National Healthcare Safety Network (NHSN)
Central Line-associated Bloodstream
Infection (CLABSI) Outcome Measure (NQF
#0139).
CDI.......................... National Healthcare Safety Network (NHSN)
Facility-wide Inpatient Hospital-onset
Clostridium difficile Infection (CDI)
Outcome Measure (NQF #1717).
HCP Influenza Vaccine........ Influenza Vaccination Coverage among
Healthcare Personnel (NQF #0431).
------------------------------------------------------------------------
Claims-Based
------------------------------------------------------------------------
MSPB LTCH.................... Medicare Spending Per Beneficiary (MSPB)-
Post Acute Care (PAC) Long-Term Care
Hospital (LTCH) Quality Reporting
Program (QRP).
DTC.......................... Discharge to Community--Post Acute Care
(PAC) Long-Term Care Hospital (LTCH)
Quality Reporting Program (QRP).
PPR.......................... Potentially Preventable 30-Day Post-
Discharge Readmission Measure for Long-
Term Care Hospital (LTCH) Quality
Reporting Program (QRP).
------------------------------------------------------------------------
4. LTCH QRP Quality Measure Proposals Beginning With the FY 2022 LTCH
QRP
In this proposed rule, we are proposing to adopt two process
measures for the LTCH QRP that would satisfy section 1899B(c)(1)(E)(ii)
of the Act, which requires that the quality measures specified by the
Secretary include measures with respect to the quality measure domain
titled ``Accurately communicating the existence of and providing for
the transfer of health information and care preferences of an
individual to the individual, family caregiver of the individual, and
providers of services furnishing items and services to the individual
when the individual transitions from a post-acute care (PAC) provider
to another applicable setting, including a different PAC provider, a
hospital, a critical access hospital, or the home of the individual.''
Given the length of this domain title, hereafter, we will refer to this
quality measure domain as ``Transfer of Health Information.''
The two measures we are proposing to adopt are: (1) Transfer of
Health Information to the Provider-Post-Acute Care (PAC); and (2)
Transfer of Health Information to the Patient-Post-Acute Care (PAC).
Both of these proposed measures support our Meaningful Measures
priority of promoting effective communication and coordination of care,
specifically the Meaningful Measure area of the transfer of health
information and interoperability.
In addition to the two measure proposals, we are proposing to
update the specifications for the Discharge to Community--Post Acute
Care (PAC) LTCH QRP measure to exclude baseline nursing facility (NF)
residents from the measure.
a. Proposed Transfer of Health Information to the Provider--Post-Acute
Care (PAC) Measure
The proposed Transfer of Health Information to the Provider-Post-
Acute Care (PAC) Measure is a process-based measure that assesses
whether or not a current reconciled medication list is given to the
subsequent provider when a patient is discharged or transferred from
his or her current PAC setting.
[[Page 19512]]
(1) Background
In 2013, 22.3 percent of all acute hospital discharges were
discharged to PAC settings, including 11 percent who were discharged to
home under the care of a home health agency, and 9 percent who were
discharged to SNFs.\625\ The proportion of patients being discharged
from an acute care hospital to a PAC setting was greater among
beneficiaries enrolled in Medicare fee-for-service (FFS). Among
Medicare FFS patients discharged from an acute hospital, 42 percent
went directly to PAC settings. Of that 42 percent, 20 percent were
discharged to a SNF, 18 percent were discharged to a home health agency
(HHA), 3 percent were discharged to an IRF, and 1 percent were
discharged to an LTCH.\626\ Of the Medicare FFS beneficiaries with an
LTCH stay in FYs 2016 and 2017, an estimated 9 percent were discharged
or transferred to an acute care hospital, 18 percent discharged home
with home health services, 38 percent discharged or transferred to a
SNF, and 10 percent discharged or transferred to another PAC setting
(for example, an IRF, a hospice, or another LTCH).\627\
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\625\ Tian, W. ``An all-payer view of hospital discharge to
post-acute care,'' May 2016. Available at: https://www.hcup-us.ahrq.gov/reports/statbriefs/sb205-Hospital-Discharge-Postacute-Care.jsp.
\626\ Ibid.
\627\ RTI International analysis of Medicare claims data for
index stays in LTCH 2016/2017. (RTI program reference: MM150).
---------------------------------------------------------------------------
The transfer and/or exchange of health information from one
provider to another can be done verbally (for example, clinician-to-
clinician communication in-person or by telephone), paper-based (for
example, faxed or printed copies of records), and via electronic
communication (for example, through a health information exchange (HIE)
network using an electronic health/medical record (EHR/EMR), and/or
secure messaging). Health information, such as medication information,
that is incomplete or missing increases the likelihood of a patient or
resident safety risk, and is often life-
threatening.628 629 630 631 632 633 Poor communication and
coordination across health care settings contributes to patient
complications, hospital readmissions, emergency department visits, and
medication errors.634 635 636 637 638 639 640 641 642 643
Communication has been cited as the third most frequent root cause in
sentinel events, which The Joint Commission defines \644\ as a patient
safety event that results in death, permanent harm, or severe temporary
harm. Failed or ineffective patient handoffs are estimated to play a
role in 20 percent of serious preventable adverse events.\645\ When
care transitions are enhanced through care coordination activities,
such as expedited patient information flow, these activities can reduce
duplication of care services and costs of care, resolve conflicting
care plans, and prevent medical errors.646 647 648 649 650
---------------------------------------------------------------------------
\628\ Kwan, J.L., Lo, L., Sampson, M., & Shojania, K.G.,
``Medication reconciliation during transitions of care as a patient
safety strategy: a systematic review,'' Annals of Internal Medicine,
2013, Vol. 158(5), pp. 397-403.
\629\ Boockvar, K.S., Blum, S., Kugler, A., Livote, E.,
Mergenhagen, K.A., Nebeker, J.R., & Yeh, J., ``Effect of admission
medication reconciliation on adverse drug events from admission
medication changes,'' Archives of Internal Medicine, 2011, Vol.
171(9), pp. 860-861.
\630\ Bell, C.M., Brener, S.S., Gunraj, N., Huo, C., Bierman,
A.S., Scales, D.C., & Urbach, D.R., ``Association of ICU or hospital
admission with unintentional discontinuation of medications for
chronic diseases,'' JAMA, 2011, Vol. 306(8), pp. 840-847.
\631\ Basey, A.J., Krska, J., Kennedy, T.D., & Mackridge, A.J.,
``Prescribing errors on admission to hospital and their potential
impact: a mixed-methods study,'' BMJ Quality & Safety, 2014, Vol.
23(1), pp. 17-25.
\632\ Desai, R., Williams, C.E., Greene, S.B., Pierson, S., &
Hansen, R.A., ``Medication errors during patient transitions into
nursing homes: characteristics and association with patient harm,''
The American Journal of Geriatric Pharmacotherapy, 2011, Vol. 9(6),
pp. 413-422.
\633\ Boling, P.A., ``Care transitions and home health care,''
Clinical Geriatric Medicine, 2009, Vol. 25(1), pp. 135-48.
\634\ Barnsteiner, J.H., ``Medication Reconciliation: Transfer
of medication information across settings--keeping it free from
error,'' The American Journal of Nursing, 2005, Vol. 105(3), pp. 31-
36.
\635\ Arbaje, A.I., Kansagara, D.L., Salanitro, A.H., Englander,
H.L., Kripalani, S., Jencks, S.F., & Lindquist, L.A., ``Regardless
of age: incorporating principles from geriatric medicine to improve
care transitions for patients with complex needs,'' Journal of
General Internal Medicine, 2014, Vol. 29(6), pp. 932-939.
\636\ Jencks, S.F., Williams, M.V., & Coleman, E.A.,
``Rehospitalizations among patients in the Medicare fee-for-service
program,'' New England Journal of Medicine, 2009, Vol. 360(14), pp.
1418-1428.
\637\ Institute of Medicine. ``Preventing medication errors:
quality chasm series,'' Washington, DC: The National Academies Press
2007. Available at: https://www.nap.edu/read/11623/chapter/1.
\638\ Kitson, N.A., Price, M., Lau, F.Y., & Showler, G.,
``Developing a medication communication framework across continuums
of care using the Circle of Care Modeling approach,'' BMC Health
Services Research, 2013, Vol. 13(1), pp. 1-10.
\639\ Mor, V., Intrator, O., Feng, Z., & Grabowski, D.C., ``The
revolving door of rehospitalization from skilled nursing
facilities,'' Health Affairs, 2010, Vol. 29(1), pp. 57-64.
\640\ Institute of Medicine. ``Preventing medication errors:
quality chasm series,'' Washington, DC: The National Academies Press
2007. Available at: https://www.nap.edu/read/11623/chapter/1.
\641\ Kitson, N.A., Price, M., Lau, F.Y., & Showler, G.,
``Developing a medication communication framework across continuums
of care using the Circle of Care Modeling approach,'' BMC Health
Services Research, 2013, Vol. 13(1), pp. 1-10.
\642\ Forster, A.J., Murff, H.J., Peterson, J.F., Gandhi, T.K.,
& Bates, D.W., ``The incidence and severity of adverse events
affecting patients after discharge from the hospital.'' Annals of
Internal Medicine, 2003, 138(3), pp. 161-167.
\643\ King, B.J., Gilmore-Bykovskyi, A.L., Roiland, R.A.,
Polnaszek, B.E., Bowers, B.J., & Kind, A.J. ``The consequences of
poor communication during transitions from hospital to skilled
nursing facility: a qualitative study,'' Journal of the American
Geriatrics Society, 2013, Vol. 61(7), 1095-1102.
\644\ The Joint Commission, ``Sentinel Event Policy'' available
at: https://www.jointcommission.org/sentinel_event_policy_and_procedures/.
\645\ The Joint Commission. ``Sentinel Event Data Root Causes by
Event Type 2004-2015.'' 2016. Available at: https://www.jointcommission.org/assets/1/23/jconline_Mar_2_2016.pdf.
\646\ Mor, V., Intrator, O., Feng, Z., & Grabowski, D.C., ``The
revolving door of rehospitalization from skilled nursing
facilities,'' Health Affairs, 2010, Vol. 29(1), pp. 57-64.
\647\ Institute of Medicine, ``Preventing medication errors:
quality chasm series,'' Washington, DC: The National Academies
Press, 2007. Available at: https://www.nap.edu/read/11623/chapter/1.
\648\ Starmer, A.J., Sectish, T.C., Simon, D.W., Keohane, C.,
McSweeney, M.E., Chung, E.Y., Yoon, C.S., Lipsitz, S.R., Wassner,
A.J., Harper, M.B., & Landrigan, C.P., ``Rates of medical errors and
preventable adverse events among hospitalized children following
implementation of a resident handoff bundle,'' JAMA, 2013, Vol.
310(21), pp. 2262-2270.
\649\ Pronovost, P., M.M.E. Johns, S. Palmer, R.C. Bono, D.B.
Fridsma, A. Gettinger, J., Goldman, W. Johnson, M. Karney, C.
Samitt, R.D. Sriram, A. Zenooz, and Y.C. Wang, Editors. Procuring
Interoperability: Achieving High-Quality, Connected, and Person-
Centered Care. Washington, DC, 2018. National Academy of Medicine.
Available at: https://nam.edu/wp-content/uploads/2018/10/Procuring-Interoperability_web.pdf.
\650\ Balaban R.B., Weissman J.S., Samuel P.A., & Woolhandler,
S., ``Redefining and redesigning hospital discharge to enhance
patient care: a randomized controlled study,'' J Gen Intern Med,
2008, Vol. 23(8), pp. 1228-33.
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Care transitions across health care settings have been
characterized as complex, costly, and potentially hazardous, and may
increase the risk for multiple adverse outcomes.651 652 The
rising incidence of preventable adverse events, complications, and
hospital readmissions have drawn attention to the importance of the
timely transfer of health information and care preferences at the time
of transition. Failures of care coordination, including poor
communication of information, were estimated to cost the U.S. health
care system between $25 billion and $45
[[Page 19513]]
billion in wasteful spending in 2011.\653\ The communication of health
information and patient care preferences is critical to ensuring safe
and effective transitions from one health care setting to
another.654 655
---------------------------------------------------------------------------
\651\ Arbaje, A.I., Kansagara, D.L., Salanitro, A.H., Englander,
H.L., Kripalani, S., Jencks, S.F., & Lindquist, L.A., ``Regardless
of age: incorporating principles from geriatric medicine to improve
care transitions for patients with complex needs,'' Journal of
General Internal Medicine, 2014, Vol. 29(6), pp. 932-939.
\652\ Simmons, S., Schnelle, J., Slagle, J., Sathe, N.A.,
Stevenson, D., Carlo, M., & McPheeters, M.L., ``Resident safety
practices in nursing home settings.'' Technical Brief No. 24
(Prepared by the Vanderbilt Evidence-based Practice Center under
Contract No. 290-2015-00003-I.) AHRQ Publication No. 16-EHC022-EF.
Rockville, MD: Agency for Healthcare Research and Quality. May 2016.
Available at: https://www.ncbi.nlm.nih.gov/books/NBK384624/.
\653\ Berwick, D.M. & Hackbarth, A.D. ``Eliminating Waste in US
Health Care,'' JAMA, 2012, Vol. 307(14), pp. 1513-1516.
\654\ McDonald, K.M., Sundaram, V., Bravata, D.M., Lewis, R.,
Lin, N., Kraft, S.A. & Owens, D.K. Care Coordination. Vol. 7 of:
Shojania K.G., McDonald K.M., Wachter R.M., Owens D.K., editors.
``Closing the quality gap: A critical analysis of quality
improvement strategies.'' Technical Review 9 (Prepared by the
Stanford University-UCSF Evidence-based Practice Center under
contract 290-02-0017). AHRQ Publication No. 04(07)-0051-7.
Rockville, MD: Agency for Healthcare Research and Quality. June
2006. Available at: https://www.ncbi.nlm.nih.gov/books/NBK44015/.
\655\ Lattimer, C., ``When it comes to transitions in patient
care, effective communication can make all the difference,''
Generations, 2011, Vol. 35(1), pp. 69-72.
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Patients in PAC settings often have complicated medication regimens
and require efficient and effective communication and coordination of
care between settings, including detailed transfer of medication
information.656 657 658 Individuals in PAC settings may be
vulnerable to adverse health outcomes due to insufficient medication
information on the part of their health care providers, and the higher
likelihood for multiple comorbid chronic conditions, polypharmacy, and
complicated transitions between care settings.659 660
Preventable adverse drug events (ADEs) may occur after hospital
discharge in a variety of settings including PAC.\661\ A 2014 Office of
Inspector General report found that 21 percent of Medicare patients in
LTCHs experienced adverse events, with 31 percent of those events being
medication related. Over half of the adverse events and temporary harm
events were clearly or likely preventable.\662\ Patient stays in LTCHs
present more opportunities for harm events than other settings because
the stays are longer. Medication errors and one-fifth of ADEs occur
during transitions between settings, including admission to or
discharge from a hospital to home or a PAC setting, or transfer between
hospitals.663 664
---------------------------------------------------------------------------
\656\ Starmer A.J, Spector N.D., Srivastava R., West, D.C.,
Rosenbluth, G., Allen, A.D., Noble, E.L., & Landrigen, C.P.,
``Changes in medical errors after implementation of a handoff
program,'' N Engl J Med, 2014, Vol. 37(1), pp. 1803-1812.
\657\ Kruse, C.S. Marquez, G., Nelson, D., & Polomares, O.,
``The use of health information exchange to augment patient handoff
in long-term care: a systematic review,'' Applied Clinical
Informatics, 2018, Vol. 9(4), pp. 752-771.
\658\ Brody, A.A., Gibson, B., Tresner-Kirsch, D., Kramer, H.,
Thraen, I., Coarr, M.E., & Rupper, R., ``High prevalence of
medication discrepancies between home health referrals and Centers
for Medicare and Medicaid Services home health certification and
plan of care and their potential to affect safety of vulnerable
elderly adults,'' Journal of the American Geriatrics Society, 2016,
Vol. 64(11), pp. e166-e170.
\659\ Chhabra, P.T., Rattinger, G.B., Dutcher, S.K., Hare, M.E.,
Parsons, K., L., & Zuckerman, I.H., ``Medication reconciliation
during the transition to and from long-term care settings: a
systematic review,'' Res Social Adm Pharm, 2012, Vol. 8(1), pp. 60-
75.
\660\ Health and Human Services Office of Inspector General.
Adverse Events in Long-Term-Care Hospitals: National Incidence Among
Medicare Beneficiaries. (OEI-06-14-00530). 2018. Available at:
https://oig.hhs.gov/oei/reports/oei-06-14-00530.asp.
\661\ Battles J., Azam I., Grady M., & Reback K., ``Advances in
patient safety and medical liability,'' AHRQ Publication No. 17-
0017-EF. Rockville, MD: Agency for Healthcare Research and Quality,
August 2017. Available at: https://www.ahrq.gov/sites/default/files/publications/files/advances-complete_3.pdf.
\662\ Health and Human Services Office of Inspector General.
Adverse Events in Long-Term-Care Hospitals: National Incidence Among
Medicare Beneficiaries. (OEI-06-14-00530). 2018. Available at:
https://oig.hhs.gov/oei/reports/oei-06-14-00530.asp.
\663\ Barnsteiner, J.H., ``Medication Reconciliation: Transfer
of medication information across settings--keeping it free from
error,'' The American Journal of Nursing, 2005, Vol. 105(3), pp. 31-
36.
\664\ Gleason, K.M., Groszek, J.M., Sullivan, C., Rooney, D.,
Barnard, C., Noskin, G.A., ``Reconciliation of discrepancies in
medication histories and admission orders of newly hospitalized
patients,'' American Journal of Health System Pharmacy, 2004, Vol.
61(16), pp. 1689-1694.
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Patients in PAC settings are often taking multiple medications.
Consequently, PAC providers regularly are in the position of starting
complex new medication regimens with little knowledge of the patients
or their medication history upon admission. Furthermore, inter-facility
communication barriers delay resolving medication discrepancies during
transitions of care.\665\ Medication discrepancies are common,\666\ and
found to occur in 86 percent of all transitions, increasing the
likelihood of ADEs.667 668 669 Up to 90 percent of patients
experience at least one medication discrepancy in the transition from
hospital to home care, and discrepancies occur within all therapeutic
classes of medications.670 671
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\665\ Patterson M., Foust J.B., Bollinger, S., Coleman, C.,
Nguyen, D., ``Inter-facility communication barriers delay resolving
medication discrepancies during transitions of care,'' Research in
Social & Administrative Pharmacy (2018), doi: 10.1016/
j.sapharm.2018.05.124.
\666\ Manias, E., Annaikis, N., Considine, J., Weerasuriya, R.,
& Kusljic, S. ``Patient-, medication- and environment-related
factors affecting medication discrepancies in older patients,''
Collegian, 2017, Vol. 24, pp. 571-577.
\667\ Tjia, J., Bonner, A., Briesacher, B.A., McGee, S.,
Terrill, E., Miller, K., ``Medication discrepancies upon hospital to
skilled nursing facility transitions,'' J Gen Intern Med, 2009, Vol.
24(5), pp. 630-635.
\668\ Sinvani, L.D., Beizer, J., Akerman, M., Pekmezaris, R.,
Nouryan, C., Lutsky, L., Cal, C., Dlugacz, Y., Masick, K., Wolf-
Klein, G.,``Medication reconciliation in continuum of care
transitions: a moving target,'' J Am Med Dir Assoc, 2013, Vol.
14(9), 668-672.
\669\ Coleman E.A., Parry C., Chalmers S., & Min, S.J., ``The
Care Transitions Intervention: results of a randomized controlled
trial,'' Arch Intern Med, 2006, Vol. 166, pp. 1822-28.
\670\ Corbett C.L., Setter S.M., Neumiller J.J., & Wood, l.D.,
``Nurse identified hospital to home medication discrepancies:
implications for improving transitional care,'' Geriatr Nurs, 2011,
Vol. 31(3), pp. 188-96.
\671\ Setter S.M., Corbett C.F., Neumiller J.J., Gates, B. J.,
Sclar, D.A., & Sonnett, T.E., ``Effectiveness of a pharmacist-nurse
intervention on resolving medication discrepancies in older patients
transitioning from hospital to home care: impact of a pharmacy/
nursing intervention,'' Am J Health Syst Pharm, 2009, Vol. 66, pp.
2027-31.
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Transfer of a medication list between providers is necessary for
medication reconciliation interventions, which have been shown to be a
cost-effective way to avoid ADEs by reducing
errors,672 673 674 especially when medications are reviewed
by a pharmacist using electronic medical records.\675\
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\672\ Boockvar, K.S., Blum, S., Kugler, A., Livote, E.,
Mergenhagen, K.A., Nebeker, J.R., & Yeh, J., ``Effect of admission
medication reconciliation on adverse drug events from admission
medication changes,'' Archives of Internal Medicine, 2011, Vol.
171(9), pp. 860-861.
\673\ Kwan, J.L., Lo, L., Sampson, M., & Shojania, K.G.,
``Medication reconciliation during transitions of care as a patient
safety strategy: a systematic review,'' Annals of Internal Medicine,
2013, Vol. 158(5), pp. 397-403.
\674\ Chhabra, P.T., Rattinger, G.B., Dutcher, S.K., Hare, M.E.,
Parsons, K., L., & Zuckerman, I.H., ``Medication reconciliation
during the transition to and from long-term care settings: a
systematic review,'' Res Social Adm Pharm, 2012, Vol. 8(1), pp. 60-
75.
\675\ Agrawal A, Wu WY. ``Reducing medication errors and
improving systems reliability using an electronic medication
reconciliation system,'' The Joint Commission Journal on Quality and
Patient Safety, 2009, Vol. 35(2), pp. 106-114.
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(2) Stakeholder and Technical Expert Panel (TEP) Input
The proposed measure was developed after consideration of feedback
we received from stakeholders and four TEPs convened by our
contractors. Further, the proposed measure was developed after
evaluation of data collected during two pilot tests we conducted in
accordance with the CMS Measures Management System Blueprint.
Our measure development contractors constituted a TEP which met on
September 27, 2016,\676\ January 27,
[[Page 19514]]
2017, and August 3, 2017 \677\ to provide input on a prior version of
this measure. Based on this input, we updated the measure concept in
late 2017 to include the transfer of a specific component of health
information--medication information. Our measure development
contractors reconvened this TEP on April 20, 2018 for the purpose of
obtaining expert input on the proposed measure, including the measure's
reliability, components of face validity, and feasibility of being
implemented across PAC settings. Overall, the TEP was supportive of the
proposed measure, affirming that the measure provides an opportunity to
improve the transfer of medication information. A summary of the April
20, 2018 TEP proceedings titled ``Transfer of Health Information TEP
Meeting 4--June 2018'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
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\676\ Technical Expert Panel Summary Report: Development of two
quality measures to satisfy the Improving Medicare Post-Acute Care
Transformation Act of 2014 (IMPACT Act) Domain of Transfer of health
Information and Care Preferences When an Individual Transitions to
Skilled Nursing Facilities (SNFs), Inpatient Rehabilitation
Facilities (IRFs), Long Term Care Hospitals (LTCHs) and Home Health
Agencies (HHAs). Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/Transfer-of-Health-Information-TEP_Summary_Report_Final-June-2017.pdf.
\677\ Technical Expert Panel Summary Report: Development of two
quality measures to satisfy the Improving Medicare Post-Acute Care
Transformation Act of 2014 (IMPACT Act) Domain of Transfer of health
Information and Care Preferences When an Individual Transitions to
Skilled Nursing Facilities (SNFs), Inpatient Rehabilitation
Facilities (IRFs), Long Term Care Hospitals (LTCHs) and Home Health
Agencies (HHAs). Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/Transfer-of-Health-Information-TEP-Meetings-2-3-Summary-Report_Final_Feb2018.pdf.
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Our measure development contractors solicited stakeholder feedback
on the proposed measure by requesting comment on the CMS Measures
Management System Blueprint website, and accepted comments that were
submitted from March 19, 2018 to May 3, 2018. The comments received
expressed overall support for the measure. Several commenters suggested
ways to improve the measure, primarily related to what types of
information should be included at transfer. We incorporated this input
into development of the proposed measure. The summary report for the
March 19 to May 3, 2018 public comment period titled ``IMPACT--
Medication Profile Transferred Public Comment Summary Report'' is
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
(3) Pilot Testing
The proposed measure was tested between June and August 2018 in a
pilot test that involved 24 PAC facilities/agencies, including five
IRFs, six SNFs, six LTCHs, and seven HHAs. The 24 pilot sites submitted
a total of 801 records. Analysis of agreement between coders within
each participating facility (266 qualifying pairs) indicated a 93-
percent agreement for this measure. Overall, pilot testing enabled us
to verify its reliability, components of face validity, and feasibility
of being implemented across PAC settings. Further, more than half of
the sites that participated in the pilot test stated during the
debriefing interviews that the measure could distinguish facilities or
agencies with higher quality medication information transfer from those
with lower quality medication information transfer at discharge. The
pilot test summary report titled ``Transfer of Health Information 2018
Pilot Test Summary Report'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
(4) Measure Applications Partnership (MAP) Review and Related Measures
We included the proposed measure in the LTCH QRP section of the
2018 Measures Under Consideration (MUC) list. The MAP conditionally
supported this measure pending NQF endorsement, noting that the measure
can promote the transfer of important medication information. The MAP
also suggested that CMS consider a measure that can be adapted to
capture bi-directional information exchange, and recommended that the
medication information transferred include important information about
supplements and opioids. More information about the MAP's
recommendations for this measure is available at: http://www.qualityforum.org/Publications/2019/02/MAP_2019_Considerations_for_Implementing_Measures_Final_Report_-_PAC-LTC.aspx.
As part of the measure development and selection process, we also
identified one NQF-endorsed quality measure similar to the proposed
measure, titled Documentation of Current Medications in the Medical
Record (NQF #0419, CMS eCQM ID: CMS68v8). This measure was adopted as
one of the recommended adult core clinical quality measures for
eligible professionals for the EHR Incentive Program beginning in 2014
and was also adopted under the Merit-based Incentive Payment System
(MIPS) quality performance category beginning in 2017. The measure is
calculated based on the percentage of visits for patients aged 18 years
and older for which the eligible professional or eligible clinician
attests to documenting a list of current medications using all
resources immediately available on the date of the encounter.
The proposed Transfer of Health Information to the Provider-Post-
Acute Care (PAC) measure addresses the transfer of information whereas
the NQF-endorsed measure #0419 assesses the documentation of
medications, but not the transfer of such information. This is
important as the proposed measure assesses for the transfer of
medication information for the proposed measure calculation. Further,
the proposed measure utilizes standardized patient assessment data
elements (SPADEs), which is a requirement for measures specified under
the Transfer of Health Information measure domain under section
1899B(c)(1)(E) of the Act, whereas NQF #0419 does not.
After review of the NQF-endorsed measure, we determined that the
proposed Transfer of Health Information to the Provider--Post-Acute
Care (PAC) measure better addresses the Transfer of Health Information
measure domain, which requires that at least some of the data used to
calculate the measure be collected as standardized patient assessment
data through the post-acute care assessment instruments. Section
1886(m)(5)(D)(i) of the Act requires that any measure specified by the
Secretary be endorsed by the entity with a contract under section
1890(a) of the Act, which is currently the National Quality Form (NQF).
However, when a feasible and practical measure has not been NQF
endorsed for a specified area or medical topic determined appropriate
by the Secretary, section 1886(m)(5)(D)(ii) of the Act allows the
Secretary to specify a measure that is not NQF endorsed as long as due
consideration is given to the measures that have been endorsed or
adopted by a consensus organization identified by the Secretary. For
the reasons discussed above, we believe that there is currently no
feasible NQF-endorsed measure that we could adopt under section
1886(m)(5)(D)(ii) of the Act. However, we note that we intend to submit
the proposed measure to the NQF for consideration of endorsement when
feasible.
[[Page 19515]]
(5) Quality Measure Calculation
The proposed Transfer of Health Information to the Provider--Post-
Acute Care (PAC) quality measure is calculated as the proportion of
patient stays with a discharge assessment indicating that a current
reconciled medication list was provided to the subsequent provider at
the time of discharge. The proposed measure denominator is the total
number of LTCH patient stays, regardless of payer, ending in discharge
to a ``subsequent provider,'' which is defined as a short-term general
acute-care hospital, intermediate care (intellectual and developmental
disabilities providers), home under care of an organized home health
service organization or hospice, hospice in an institutional facility,
a SNF, another LTCH, an IRF, an inpatient psychiatric facility, or a
CAH. These health care providers were selected for inclusion in the
denominator because they are identified as subsequent providers on the
discharge destination item that is currently included on the LTCH
Continuity Assessment Record and Evaluation Data Set (LTCH CARE Data
Set or LCDS). The proposed measure numerator is the number of LTCH
patient stays with an LCDS discharge assessment indicating a current
reconciled medication list was provided to the subsequent provider at
the time of discharge. For additional technical information about this
proposed measure, we refer readers to the document titled, ``Proposed
Specifications for LTCH QRP Quality Measures and Standardized Patient
Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html. The data source for the proposed quality measure is the
LCDS assessment instrument for LTCH patients.
For more information about the data submission requirements we are
proposing for this measure, we refer readers to section VIII.C.8.d. of
the preamble of this proposed rule.
b. Proposed Transfer of Health Information to the Patient--Post-Acute
Care (PAC) Measure
Beginning with the FY 2022 LTCH QRP, we are proposing to adopt the
Transfer of Health Information to the Patient--Post-Acute Care (PAC)
measure, a measure that satisfies the IMPACT Act domain of Transfer of
Health Information, with data collection for discharges beginning
October 1, 2020. This process-based measure assesses whether or not a
current reconciled medication list was provided to the patient, family,
or caregiver when the patient was discharged from a PAC setting to a
private home/apartment, a board and care home, assisted living, a group
home, transitional living or home under care of an organized home
health service organization, or a hospice.
(1) Background
In 2013, 22.3 percent of all acute hospital discharges were
discharged to PAC settings, including 11 percent who were discharged to
home under the care of a home health agency.\678\ Of the Medicare FFS
beneficiaries with an LTCH stay in fiscal years 2016 and 2017, an
estimated 18 percent were discharged home with home health services,
nine percent were discharged home with self-care, and two percent were
discharged with home hospice services.\679\
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\678\ Tian, W. ``An all-payer view of hospital discharge to
postacute care,'' May 2016. Available at: https://www.hcup-us.ahrq.gov/reports/statbriefs/sb205-Hospital-Discharge-Postacute-Care.jsp.
\679\ RTI International analysis of Medicare claims data for
index stays in LTCH 2016/2017. (RTI program reference: MM150).
---------------------------------------------------------------------------
The communication of health information, such as a reconciled
medication list, is critical to ensuring safe and effective patient
transitions from health care settings to home and/or other community
settings. Incomplete or missing health information, such as medication
information, increases the likelihood of a patient safety risk, often
life-threatening.680 681 682 683 684 Individuals who use PAC
care services are particularly vulnerable to adverse health outcomes
due to their higher likelihood of having multiple comorbid chronic
conditions, polypharmacy, and complicated transitions between care
settings.685 686 Upon discharge to home, individuals in PAC
settings may be faced with numerous medication changes, new medication
regimes, and follow-up details.687 688 689 The efficient and
effective communication and coordination of medication information may
be critical to prevent potentially deadly adverse effects. When care
coordination activities enhance care transitions, these activities can
reduce duplication of care services and costs of care, resolve
conflicting care plans, and prevent medical errors.690 691
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\680\ Kwan, J.L., Lo, L., Sampson, M., & Shojania, K.G.
``Medication reconciliation during transitions of care as a patient
safety strategy: A systematic review,'' Annals of Internal Medicine,
2013, Vol. 158(5), pp. 397-403.
\681\ Boockvar, K.S., Blum, S., Kugler, A., Livote, E.,
Mergenhagen, K.A., Nebeker, J.R., & Yeh, J. ``Effect of admission
medication reconciliation on adverse drug events from admission
medication changes,'' Archives of Internal Medicine, 2011, Vol.
171(9), pp. 860-861.
\682\ Bell, C.M., Brener, S.S., Gunraj, N., Huo, C., Bierman,
A.S., Scales, D.C., & Urbach, D.R. ``Association of ICU or hospital
admission with unintentional discontinuation of medications for
chronic diseases,'' JAMA, 2011, Vol. 306(8), pp. 840-847.
\683\ Basey, A.J., Krska, J., Kennedy, T.D., & Mackridge, A.J.
``Prescribing errors on admission to hospital and their potential
impact: A mixed-methods study,'' BMJ Quality & Safety, 2014, Vol.
23(1), pp. 17-25.
\684\ Desai, R., Williams, C.E., Greene, S.B., Pierson, S., &
Hansen, R.A. ``Medication errors during patient transitions into
nursing homes: Characteristics and association with patient harm,''
The American Journal of Geriatric Pharmacotherapy, 2011, Vol. 9(6),
pp. 413-422.
\685\ Brody, A.A., Gibson, B., Tresner-Kirsch, D., Kramer, H.,
Thraen, I., Coarr, M.E., & Rupper, R. ``High prevalence of
medication discrepancies between home health referrals and Centers
for Medicare and Medicaid Services home health certification and
plan of care and their potential to affect safety of vulnerable
elderly adults,'' Journal of the American Geriatrics Society, 2016,
Vol. 64(11), pp. e166-e170.
\686\ Chhabra, P.T., Rattinger, G.B., Dutcher, S.K. Hare, M.E.,
Parsons, K.L., & Zuckerman, I.H. ``Medication reconciliation during
the transition to and from long-term care settings: A systematic
review,'' Res Social Adm Pharm, 2012, Vol. 8(1), pp. 60-75.
\687\ Brody, A.A., Gibson, B., Tresner-Kirsch, D., Kramer, H.,
Thraen, I., Coarr, M.E., & Rupper, R. ``High prevalence of
medication discrepancies between home health referrals and Centers
for Medicare and Medicaid Services home health certification and
plan of care and their potential to affect safety of vulnerable
elderly adults,'' Journal of the American Geriatrics Society, 2016,
Vol. 64(11), pp. e166-e170.
\688\ Bell, C.M., Brener, S.S., Gunraj, N., Huo, C., Bierman,
A.S., Scales, D.C., & Urbach, D.R. ``Association of ICU or hospital
admission with unintentional discontinuation of medications for
chronic diseases,'' JAMA, 2011, Vol. 306(8), pp. 840-847.
\689\ Sheehan, O.C., Kharrazi, H., Carl, K.J., Leff, B., Wolff,
J.L., Roth, D.L., Gabbard, J., & Boyd, C.M. ``Helping older adults
improve their medication experience (HOME) by addressing medication
regimen complexity in home healthcare,'' Home Healthcare Now. 2018,
Vol. 36(1), pp. 10-19.
\690\ Mor, V., Intrator, O., Feng, Z., & Grabowski, D.C. ``The
revolving door of rehospitalization from skilled nursing
facilities,'' Health Affairs, 2010, Vol. 29(1), pp. 57-64.
\691\ Starmer, A.J., Sectish, T.C., Simon, D.W., Keohane, C.,
McSweeney, M.E., Chung, E.Y., Yoon, C.S., Lipsitz, S.R., Wassner,
A.J., Harper, M.B., & Landrigan, C.P. ``Rates of medical errors and
preventable adverse events among hospitalized children following
implementation of a resident handoff bundle,'' JAMA, 2013, Vol.
310(21), pp. 2262-2270.
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Finally, the transfer of a patient's discharge medication
information to the patient, family, or caregiver is common practice and
supported by discharge planning requirements for participation in
Medicare and Medicaid programs.692 693 Most PAC EHR systems
[[Page 19516]]
generate a discharge medication list to promote patient participation
in medication management, which has been shown to be potentially useful
for improving patient outcomes and transitional care.\694\
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\692\ CMS, ``Revision to state operations manual (SOM), Hospital
Appendix A--Interpretive Guidelines for 42 CFR 482.43, Discharge
Planning'' May 17, 2013. Available at: https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/SurveyCertificationGenInfo/Downloads/Survey-and-Cert-Letter-13-32.pdf.
\693\ The State Operations Manual Guidance to Surveyors for Long
Term Care Facilities (Guidance Sec. 483.21(c)(1) Rev. 11-22-17) for
discharge planning process. Available at: https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/downloads/som107ap_pp_guidelines_ltcf.pdf.
\694\ Toles, M., Colon-Emeric, C., Naylor, M.D., Asafu-Adjei,
J., Hanson, L.C. ``Connect-home: Transitional care of skilled
nursing facility patients and their caregivers,'' Am Geriatr Soc.,
2017, Vol. 65(10), pp. 2322-2328.
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(2) Stakeholder and TEP Input
The proposed measure was developed after consideration of feedback
we received from stakeholders and four TEPs convened by our
contractors. Further, the proposed measure was developed after
evaluation of data collected during two pilot tests we conducted in
accordance with the CMS Measures Management System Blueprint.
Our measure development contractors constituted a TEP which met on
September 27, 2016,\695\ January 27, 2017, and August 3, 2017 \696\ to
provide input on a prior version of this measure. Based on this input,
we updated the measure concept in late 2017 to include the transfer of
a specific component of health information--medication information. Our
measure development contractors reconvened this TEP on April 20, 2018
to seek expert input on the measure. Overall, the TEP members supported
the proposed measure, affirming that the measure provides an
opportunity to improve the transfer of medication information. Most of
the TEP members believed that the measure could improve the transfer of
medication information to patients, families, and caregivers. Several
TEP members emphasized the importance of transferring information to
patients and their caregivers in a clear manner using plain language. A
summary of the April 20, 2018 TEP proceedings titled ``Transfer of
Health Information TEP Meeting 4--June 2018'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
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\695\ Technical Expert Panel Summary Report: Development of two
quality measures to satisfy the Improving Medicare Post-Acute Care
Transformation Act of 2014 (IMPACT Act) Domain of Transfer of health
Information and Care Preferences When an Individual Transitions to
Skilled Nursing Facilities (SNFs), Inpatient Rehabilitation
Facilities (IRFs), Long Term Care Hospitals (LTCHs) and Home Health
Agencies (HHAs). Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/Transfer-of-Health-Information-TEP_Summary_Report_Final-June-2017.pdf.
\696\ Technical Expert Panel Summary Report: Development of two
quality measures to satisfy the Improving Medicare Post-Acute Care
Transformation Act of 2014 (IMPACT Act) Domain of Transfer of health
Information and Care Preferences When an Individual Transitions to
Skilled Nursing Facilities (SNFs), Inpatient Rehabilitation
Facilities (IRFs), Long Term Care Hospitals (LTCHs) and Home Health
Agencies (HHAs). Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/Transfer-of-Health-Information-TEP-Meetings-2-3-Summary-Report_Final_Feb2018.pdf.
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Our measure development contractors solicited stakeholder feedback
on the proposed measure by requesting comment on the CMS Measures
Management System Blueprint website, and accepted comments that were
submitted from March 19, 2018 to May 3, 2018. Several commenters noted
the importance of ensuring that the instruction provided to patients
and caregivers is clear and understandable to promote transparent
access to medical record information and meet the goals of the IMPACT
Act. The summary report for the March 19 to May 3, 2018 public comment
period titled ``IMPACT--Medication Profile Transferred Public Comment
Summary Report'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
(3) Pilot Testing
Between June and August 2018, we held a pilot test involving 24 PAC
facilities/agencies, including five IRFs, six SNFs, six LTCHs, and
seven HHAs. The 24 pilot sites submitted a total of 801 assessments.
Analysis of agreement between coders within each participating facility
(241 qualifying pairs) indicated an 87-percent agreement for this
measure. Overall, pilot testing enabled us to verify its reliability,
components of face validity, and feasibility of being implemented
across PAC settings. Further, more than half of the sites that
participated in the pilot test stated, during debriefing interviews,
that the measure could distinguish facilities or agencies with higher
quality medication information transfer from those with lower quality
medication information transfer at discharge. The pilot test summary
report titled ``Transfer of Health Information 2018 Pilot Test Summary
Report'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
(4) Measure Applications Partnership (MAP) Review and Related Measures
We included the proposed measure in the LTCH QRP section of the
2018 MUC list. The MAP conditionally supported this measure pending NQF
endorsement, noting that the measure can promote the transfer of
important medication information to the patient. The MAP recommended
that providers transmit medication information to patients that is easy
to understand because health literacy can impact a person's ability to
take medication as directed. More information about the MAP's
recommendations for this measure is available at: http://www.qualityforum.org/Publications/2019/02/MAP_2019_Considerations_for_Implementing_Measures_Final_Report_-_PAC-LTC.aspx.
Section 1886(m)(5)(D)(i) of the Act, requires that any measure
specified by the Secretary be endorsed by the entity with a contract
under section 1890(a) of the Act, which is currently the NQF. However,
when a feasible and practical measure has not been NQF endorsed for a
specified area or medical topic determined appropriate by the
Secretary, section 1886(m)(5)(D)(ii) of the Act allows the Secretary to
specify a measure that is not NQF endorsed as long as due consideration
is given to the measures that have been endorsed or adopted by a
consensus organization identified by the Secretary. Therefore, in the
absence of any NQF-endorsed measures that address the proposed Transfer
of Health Information to the Patient--Post-Acute Care (PAC), which
requires that at least some of the data used to calculate the measure
be collected as standardized patient assessment data through the post-
acute care assessment instruments, we believe that there is currently
no feasible NQF-endorsed measure that we could adopt under section
1886(m)(5)(D)(ii) of the Act. However, we note that we intend to submit
the proposed measure to the NQF for consideration of endorsement when
feasible.
(5) Quality Measure Calculation
The calculation of the proposed Transfer of Health Information to
the Patient--Post-Acute Care (PAC) measure would be based on the
proportion of patient stays with a discharge assessment indicating that
a current
[[Page 19517]]
reconciled medication list was provided to the patient, family, or
caregiver at the time of discharge.
The proposed measure denominator is the total number of LTCH
patient stays, regardless of payer, ending in discharge to a private
home/apartment, a board and care home, assisted living, a group home,
transitional living or home under care of an organized home health
service organization, or a hospice. These locations were selected for
inclusion in the denominator because they are identified as home
locations on the discharge destination item that is currently included
on the LCDS. The proposed measure numerator is the number of LTCH
patient stays with an LCDS discharge assessment indicating a current
reconciled medication list was provided to the patient, family, or
caregiver at the time of discharge. For technical information about
this proposed measure, we refer readers to the document titled
``Proposed Specifications for LTCH QRP Quality Measures and
Standardized Patient Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html. Data for the proposed quality
measure would be calculated using data from the LCDS assessment
instrument for LTCH patients.
For more information about the data submission requirements we are
proposing for this measure, we refer readers to section VIII.C.8.d. of
the preamble of this proposed rule.
c. Proposed Update to the Discharge to Community--Post Acute Care (PAC)
Long-Term Care Hospital (LTCH) Quality Reporting Program (QRP) Measure
We are proposing to update the specifications for the Discharge to
Community--PAC LTCH QRP measure to exclude baseline nursing facility
(NF) residents from the measure. This measure reports an LTCH's risk-
standardized rate of Medicare FFS patients who are discharged to the
community following an LTCH stay, do not have an unplanned readmission
to an acute care hospital or LTCH in the 31 days following discharge to
community, and who remain alive during the 31 days following discharge
to community. We adopted this measure in the FY 2017 IPPS/LTCH PPS
final rule (81 FR 57207 through 57215).
In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57211), we addressed
public comments recommending exclusion of LTCH patients who were
baseline NF residents, as these patients lived in a NF prior to their
LTCH stay and may not be expected to return to the community following
their LTCH stay. In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38449),
we addressed public comments expressing support for a potential future
modification of the measure that would exclude baseline NF residents;
commenters stated that the exclusion would result in the measure more
accurately portraying quality of care provided by LTCHs, while
controlling for factors outside of LTCH control.
We assessed the impact of excluding baseline NF residents from the
measure using CY 2015 and CY 2016 data and found that this exclusion
impacted both patient- and facility-level discharge to community rates.
We defined baseline NF residents as LTCH patients who had a long-term
NF stay in the 180 days preceding their hospitalization and LTCH stay,
with no intervening community discharge between the NF stay and
qualifying hospitalization for measure inclusion. Baseline NF residents
represented 9.2 percent of the measure population after all measure
exclusions were applied. Observed patient-level discharge to community
rates were significantly lower for baseline NF residents (1.44 percent)
compared with non-NF residents (23.89 percent). The national observed
patient-level discharge to community rate was 21.82 percent when
baseline NF residents were included in the measure, increasing to 23.89
percent when they were excluded from the measure. After excluding
baseline NF residents, 39.2 percent of LTCHs had an increase in their
risk-standardized discharge to community rate that exceeded the
increase in the national observed patient-level discharge to community
rate.
Based on public comments received and our impact analysis, we are
proposing to exclude baseline NF residents from the Discharge to
Community--PAC LTCH QRP measure beginning with the FY 2020 LTCH QRP,
with baseline NF residents defined as LTCH patients who had a long-term
NF stay in the 180 days preceding their hospitalization and LTCH stay,
with no intervening community discharge between the NF stay and
hospitalization.
For additional technical information regarding the Discharge to
Community--PAC LTCH QRP measure, including technical information about
the proposed exclusion, we refer readers to the document titled
``Proposed Specifications for LTCH QRP Quality Measures and
Standardized Patient Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
5. LTCH QRP Quality Measures, Measure Concepts, and Standardized
Patient Assessment Data Elements Under Consideration for Future Years:
Request for Information
We are seeking input on the importance, relevance, appropriateness,
and applicability of each of the measures, standardized patient
assessment data elements (SPADEs), and concepts under consideration
listed in the table below for future years in the LTCH QRP.
Future Measures, Measure Concepts, and Standardized Patient Assessment
Data Elements (SPADEs) Under Consideration for the LTCH QRP
------------------------------------------------------------------------
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Quality Measures and Measure Concepts
------------------------------------------------------------------------
Functional mobility outcomes.
Sepsis.
Opioid use and frequency.
Exchange of electronic health information and interoperability.
Nutritional status.
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Standardized Patient Assessment Data Elements (SPADEs)
------------------------------------------------------------------------
Cognitive complexity, such as executive function and memory.
Dementia.
Bladder and bowel continence including appliance use and episodes of
incontinence.
[[Page 19518]]
Care preferences, advance care directives, and goals of care.
Caregiver Status.
Veteran Status.
Health disparities and risk factors, including education, sex and gender
identity, and sexual orientation.
------------------------------------------------------------------------
While we will not be responding to specific comments submitted in
response to this Request for Information in the FY 2020 IPPS/LTCH PPS
final rule, we intend to use this input to inform our future measure
and SPADE development efforts.
6. Proposed Standardized Patient Assessment Data Reporting Beginning
With the FY 2022 LTCH QRP
Section 1886(m)(5)(F)(ii) of the Act requires that, for fiscal year
2019 and each subsequent year, LTCHs must report standardized patient
assessment data (SPADE), required under section 1899B(b)(1) of the Act.
Section 1899B(a)(1)(C) of the Act requires, in part, the Secretary to
modify the PAC assessment instruments in order for PAC providers,
including LTCHs, to submit SPADEs under the Medicare program. Section
1899B(b)(1)(A) of the Act requires PAC providers to submit SPADEs under
applicable reporting provisions (which, for LTCHs, is the LTCH QRP)
with respect to the admissions and discharges of an individual (and
more frequently as the Secretary deems appropriate), and section
1899B(b)(1)(B) of the Act defines standardized patient assessment data
as data required for at least the quality measures described in section
1899B(c)(1) of the Act and that is with respect to the following
categories: (1) Functional status, such as mobility and self-care at
admission to a PAC provider and before discharge from a PAC provider;
(2) cognitive function, such as ability to express ideas and to
understand, and mental status, such as depression and dementia; (3)
special services, treatments, and interventions, such as need for
ventilator use, dialysis, chemotherapy, central line placement, and
total parenteral nutrition; (4) medical conditions and comorbidities,
such as diabetes, congestive heart failure, and pressure ulcers; (5)
impairments, such as incontinence and an impaired ability to hear, see,
or swallow; and (6) other categories deemed necessary and appropriate
by the Secretary.
In the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20100 through
20116), we proposed to adopt SPADEs that would satisfy the first five
categories. In the FY 2018 IPPS/LTCH PPS final rule, commenters
expressed support for our adoption of SPADEs in general, including
support for our broader standardization goal and support for the
clinical usefulness of specific proposed SPADEs. However, we did not
finalize the majority of our SPADE proposals in recognition of the
concern raised by many commenters that we were moving too fast to adopt
the SPADEs and modify our assessment instruments in light of all of the
other requirements we were also adopting under the IMPACT Act at that
time (82 FR 38457 through 38458). In addition, we noted our intention
to conduct extensive testing to ensure that the standardized patient
assessment data elements we select are reliable, valid, and appropriate
for their intended use (82 FR 38451 through 38452).
We did, however, finalize the adoption of SPADEs for two of the
categories described in section 1899B(b)(1)(B) of the Act: (1)
Functional status: Data elements currently reported by LTCHs to
calculate the measure Application of Percent of Long-Term Care Hospital
Patients with an Admission and Discharge Functional Assessment and a
Care Plan That Addresses Function (NQF #2631); and (2) Medical
conditions and comorbidities: The data elements used to calculate the
pressure ulcer measures, Percent of Residents or Patients with Pressure
Ulcers That Are New or Worsened (Short Stay) (NQF #0678) and the
replacement measure, Changes in Skin Integrity Post-Acute Care:
Pressure Ulcer/Injury. We stated that these data elements were
important for care planning, known to be valid and reliable, and
already being reported by LTCHs for the calculation of quality measures
(82 FR 38453 through 38454).
Since we issued the FY 2018 IPPS/LTCH PPS final rule, LTCHs have
had an opportunity to familiarize themselves with other new reporting
requirements that we have adopted under the IMPACT Act. We have also
conducted further testing of the SPADEs, as described more fully below,
and believe this testing supports the use of the SPADEs in our PAC
assessment instruments. Therefore, we are now proposing to adopt many
of the same SPADEs that we previously proposed to adopt, along with
other SPADEs.
We are proposing that LTCHs would be required to report these
SPADEs beginning with the FY 2022 LTCH QRP. If finalized as proposed,
LTCHs would be required to report these data with respect to LTCH
admissions and discharges that occur between October 1, 2020 and
December 31, 2020 for the FY 2022 LTCH QRP. Beginning with the FY 2023
LTCH QRP, we are proposing that LTCHs must report data with respect to
admissions and discharges that occur during the subsequent calendar
year (for example, CY 2021 for the FY 2023 LTCH QRP, CY 2022 for the FY
2024 LTCH QRP).
We are also proposing that LTCHs that submit the Hearing, Vision,
Race, and Ethnicity SPADEs with respect to admission only will be
deemed to have submitted those SPADEs with respect to both admission
and discharge, because it is unlikely that the assessment of those
SPADEs at admission will differ from the assessment of the same SPADEs
at discharge.
In selecting the proposed SPADEs below, we considered the burden of
assessment-based data collection and aimed to minimize additional
burden by evaluating whether any data that is currently collected
through one or more PAC assessment instruments could be collected as
SPADE. In selecting the proposed SPADEs below, we also took into
consideration the following factors with respect to each data element:
(1) Overall clinical relevance;
(2) Interoperable exchange to facilitate care coordination during
transitions in care;
(3) Ability to capture medical complexity and risk factors that can
inform both payment and quality; and
(4) Scientific reliability and validity, general consensus
agreement for its usability.
In identifying the SPADEs proposed below, we also drew on input
from several sources, including TEPs held by our data element
contractor, public input, and the results of a recent National Beta
Test of candidate data elements conducted by our data element
contractor (hereafter ``National Beta Test'').
The National Beta Test collected data from 3,121 patients and
residents across 143 LTCHs, SNFs, IRFs, and HHAs from November 2017 to
August 2018 to
[[Page 19519]]
evaluate the feasibility, reliability, and validity of the candidate
data elements across PAC settings. The National Beta Test also gathered
feedback on the candidate data elements from staff who administered the
test protocol in order to understand usability and workflow of the
candidate data elements. More information on the methods, analysis
plan, and results for the National Beta Test are available in the
document titled, ``Development and Evaluation of Candidate Standardized
Patient Assessment Data Elements: Findings from the National Beta Test
(Volume 2),'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Further, to inform the proposed SPADEs, we took into account
feedback from stakeholders, as well as from technical and clinical
experts, including feedback on whether the candidate data elements
would support the factors described above. Where relevant, we also took
into account the results of the Post-Acute Care Payment Reform
Demonstration (PAC PRD) that took place from 2006 to 2012.
7. Proposed Standardized Patient Assessment Data by Category
a. Functional Status Data
We are proposing to adopt six functional status data elements as
SPADEs under the category of functional status under section
1899B(b)(1)(B)(i) of the Act. These six data elements are: Car
transfer; Walking 10 feet on uneven surfaces; 1-step (curb); 4 steps;
12 steps; and Picking up object. We are proposing to add these to the
LCDS as SPADEs under section 1899B(b)(1)(B)(i) of the Act. We adopted
these six mobility data elements into the SNF, IRF, and HH QRPs as
SPADEs under their respective patient/resident assessment instruments.
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38429 through 38430), we
finalized our definition of ``standardized patient assessment data'' as
patient assessment questions and response options that are identical in
all four PAC assessment instruments, and to which identical standards
and definitions apply. In order for these six mobility data elements to
be in all four PAC assessment instruments, we are proposing that they
also meet the definition of standardized patient assessment data for
functional status under section 1899B(b)(1)(B)(i) of the Act, and that
the successful reporting of such data under section 1886(m)(5)(F)(i) of
the Act will also satisfy the requirement to report standardized
patient assessment data under section 1886(m)(5)(F)(ii) of the Act.
The data elements listed above were implemented in the IRF QRP and
SNF QRP when we adopted the quality measures, Change in Mobility Score
(NQF #2634) and Discharge Mobility Score (NQF #2636), into the IRF QRP
in the FY 2016 IRF PPS final rule (80 FR 47111 through 47120) and the
SNF QRP in the FY 2018 SNF PPS final rule (82 FR 36577 through 36593).
In addition, we implemented these six mobility data elements in the HH
setting. The CY 2018 HH PPS final rule (82 FR 51733 through 51734)
finalized that these six mobility data elements meet the definition of
standardized patient assessment data for functional status under
section 1899B(b)(1)(B)(i) of the Act.
The six mobility data elements are currently collected in Section
GG: Functional Abilities and Goals located in the current versions of
the MDS, OASIS, and the IRF-PAI assessment instruments. For more
information on the six functional mobility data elements, we refer
readers to the document titled ``Proposed Specifications for LTCH QRP
Quality Measures and Standardized Patient Assessment Data Elements,''
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We are proposing to adopt the functional mobility data elements as
SPADEs for use in the LTCH QRP.
b. Cognitive Function and Mental Status Data
A number of underlying conditions, including dementia, stroke,
traumatic brain injury, side effects of medication, metabolic and/or
endocrine imbalances, delirium, and depression, can affect cognitive
function and mental status in PAC patient and resident
populations.\697\ The assessment of cognitive function and mental
status by PAC providers is important because of the high percentage of
patients and residents with these conditions,\698\ and because these
assessments provide opportunity for improving quality of care.
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\697\ National Institute on Aging. (2014). Assessing Cognitive
Impairment in Older Patients. A Quick Guide for Primary Care
Physicians. Retrieved from: https://www.nia.nih.gov/alzheimers/publication/assessing-cognitive-impairment-older-patients.
\698\ Gage B., Morley M., Smith L., et al. (2012). Post-Acute
Care Payment Reform Demonstration (Final report, Volume 4 of 4).
Research Triangle Park, NC: RTI International.
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Symptoms of dementia may improve with pharmacotherapy, occupational
therapy, or physical activity,699 700 701 and promising
treatments for severe traumatic brain injury are currently being
tested.702 For older patients and residents diagnosed with
depression, treatment options to reduce symptoms and improve quality of
life include antidepressant medication and
psychotherapy,703 704 705 706 and targeted services, such as
therapeutic recreation, exercise, and restorative nursing, to increase
opportunities for psychosocial interaction.707
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\699\ Casey D.A., Antimisiaris D., O'Brien J. (2010). Drugs for
Alzheimer's Disease: Are They Effective? Pharmacology &
Therapeutics, 35, 208-11.
\700\ Graff M.J., Vernooij-Dassen M.J., Thijssen M., Dekker J.,
Hoefnagels W.H., Rikkert M.G.O. (2006). Community Based Occupational
Therapy for Patients with Dementia and their Care Givers: Randomised
Controlled Trial. BMJ, 333(7580): 1196.
\701\ Bherer L., Erickson K.I., Liu-Ambrose T. (2013). A Review
of the Effects of Physical Activity and Exercise on Cognitive and
Brain Functions in Older Adults. Journal of Aging Research, 657508.
\702\ Giacino J.T., Whyte J., Bagiella E., et al. (2012).
Placebo-controlled trial of amantadine for severe traumatic brain
injury. New England Journal of Medicine, 366(9), 819-826.
\703\ Alexopoulos G.S., Katz I.R., Reynolds C.F. 3rd, Carpenter
D., Docherty J.P., Ross R.W. (2001). Pharmacotherapy of depression
in older patients: A summary of the expert consensus guidelines.
Journal of Psychiatric Practice, 7(6), 361-376.
\704\ Arean P.A., Cook B.L. (2002). Psychotherapy and combined
psychotherapy/pharmacotherapy for late life depression. Biological
Psychiatry, 52(3), 293-303.
\705\ Hollon S.D., Jarrett R.B., Nierenberg A.A., Thase M.E.,
Trivedi M., Rush A.J. (2005). Psychotherapy and medication in the
treatment of adult and geriatric depression: Which monotherapy or
combined treatment? Journal of Clinical Psychiatry, 66(4), 455-468.
\706\ Wagenaar D, Colenda CC, Kreft M, Sawade J, Gardiner J,
Poverejan E. (2003). Treating depression in nursing homes: Practice
guidelines in the real world. J Am Osteopath Assoc. 103(10), 465-
469.
\707\ Crespy SD, Van Haitsma K, Kleban M, Hann CJ. Reducing
Depressive Symptoms in Nursing Home Residents: Evaluation of the
Pennsylvania Depression Collaborative Quality Improvement Program. J
Healthc Qual. 2016. Vol. 38, No. 6, pp. e76-e88.
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In alignment with our Meaningful Measures Initiative, accurate
assessment of cognitive function and mental status of patients and
residents in PAC is expected to make care safer by reducing harm caused
in the delivery of care; promote effective prevention and treatment of
chronic disease; strengthen person and family engagement as partners in
their care; and promote effective communication and coordination of
care. For example, standardized assessment of cognitive function and
mental status of patients and residents in PAC will support
establishing a baseline for identifying
[[Page 19520]]
changes in cognitive function and mental status (for example,
delirium), anticipating the patient's or resident's ability to
understand and participate in treatments during a PAC stay, ensuring
patient and resident safety (for example, risk of falls), and
identifying appropriate support needs at the time of discharge or
transfer. SPADEs will enable or support clinical decision-making and
early clinical intervention; person-centered, high quality care through
facilitating better care continuity and coordination; better data
exchange and interoperability between settings; and longitudinal
outcome analysis. Therefore, reliable SPADEs assessing cognitive
function and mental status are needed in order to initiate a management
program that can optimize a patient's or resident's prognosis and
reduce the possibility of adverse events. We describe each of the
proposed cognitive function and mental status data SPADEs below.
Brief Interview for Mental Status (BIMS)
We are proposing that the data elements that comprise the BIMS meet
the definition of standardized patient assessment data with respect to
cognitive function and mental status under section 1899B(b)(1)(B)(ii)
of the Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20100 through 20101), dementia and cognitive impairment are associated
with long-term functional dependence and, consequently, poor quality of
life and increased health care costs and mortality.\708\ This makes
assessment of mental status and early detection of cognitive decline or
impairment critical in the PAC setting. The intensity of routine
nursing care is higher for patients and residents with cognitive
impairment than those without, and dementia is a significant variable
in predicting readmission after discharge to the community from PAC
providers.\709\
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\708\ Ag[uuml]ero-Torres, H., Fratiglioni, L., Guo, Z.,
Viitanen, M., von Strauss, E., & Winblad, B. (1998). ``Dementia is
the major cause of functional dependence in the elderly: 3-year
follow-up data from a population-based study.'' Am J of Public
Health 88(10): 1452-1456.
\709\ RTI International. Proposed Measure Specifications for
Measures Proposed in the FY 2017 LTCH QRP NPRM. Research Triangle
Park, NC. 2016.
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The BIMS is a performance-based cognitive assessment screening tool
that assesses repetition, recall with and without prompting, and
temporal orientation. The data elements that make up the BIMS are seven
questions on the repetition of three words, temporal orientation, and
recall that result in a cognitive function score. The BIMS was
developed to be a brief, objective screening tool, with a focus on
learning and memory. As a brief screener, the BIMS was not designed to
diagnose dementia or cognitive impairment, but rather to be a
relatively quick and easy to score assessment that could identify
cognitively impaired patients as well as those who may be at risk for
cognitive decline and require further assessment. It is currently in
use in two of the PAC assessments: The MDS used by SNFs and the IRF-PAI
used by IRFs. For more information on the BIMS, we refer readers to the
document titled ``Proposed Specifications for LTCH QRP Quality Measures
and Standardized Patient Assessment Data Elements,'' available at:
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The data elements that comprise the BIMS were first proposed as
SPADEs in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20100 through
20101). In that proposed rule, we stated that the proposal was informed
by input we received through a call for input published on the CMS
Measures Management System Blueprint website. Input submitted from
August 12 to September 12, 2016 expressed support for use of the BIMS,
noting that it is reliable, feasible to use across settings, and will
provide useful information about patients and residents. We also stated
that those commenters had noted that the data collected through the
BIMS will provide a clearer picture of patient or resident complexity,
help with the care planning process, and be useful during care
transitions and when coordinating across providers. A summary report
for the August 12 to September 12, 2016 public comment period titled
``SPADE August 2016 Public Comment Summary Report'' is available at:
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received public comments in support of the BIMS, with several
commenters noting the importance of routine assessment of cognitive
status and supporting the use of the BIMS to identify individuals with
cognitive impairment. However, commenters expressed concerns about not
having recent, comprehensive field testing of the proposed data
elements. In addition, some commenters were critical of the BIMS,
citing burden of administering the items and its limitation in
assessing mild cognitive impairment and ``functional'' cognition
related to executive function and everyday decision-making.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the BIMS was included in the National Beta Test of
candidate data elements conducted by our data element contractor from
November 2017 to August 2018. Results of this test found the BIMS to be
feasible and reliable for use with PAC patients and residents. More
information about the performance of the BIMS in the National Beta Test
can be found in the document titled ``Proposed Specifications for LTCH
QRP Quality Measures and Standardized Patient Assessment Data
Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In, addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the proposed
standardized patient assessment data elements, and the TEP supported
the assessment of patient or resident cognitive status at both
admission and discharge. A summary of the September 17, 2018 TEP
meeting titled ``SPADE Technical Expert Panel Summary (Third
Convening)'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our on-going SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. Some commenters expressed concern that the BIMS, if used alone,
may not be sensitive enough to capture the range of cognitive
impairments, including mild cognitive impairment. A summary of the
[[Page 19521]]
public input received from the November 27, 2018 stakeholder meeting
titled ``Input on Standardized Patient Assessment Data Elements
(SPADEs) Received After November 27, 2018 Stakeholder Meeting'' is
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We understand the concerns raised by stakeholders that BIMS, if
used alone, may not be sensitive enough to capture the range of
cognitive impairments, including functional cognition and MCI, but note
that the purpose of the BIMS data elements as SPADEs is to screen for
cognitive impairment in a broad population. We also acknowledge that
further cognitive tests may be required based on a patient's condition
and will take this feedback into consideration in the development of
future standardized assessment data elements. However, taking together
the importance of assessing for cognitive status, stakeholder input,
and strong test results, we are proposing that the BIMS data elements
meet the definition of standardized patient assessment data with
respect to cognitive function and mental status under section
1899B(b)(1)(B)(ii) of the Act, and to adopt the BIMS as standardized
patient assessment data for use in the LTCH QRP.
Confusion Assessment Method (CAM)
We are proposing that the data elements that comprise the Confusion
Assessment Method (CAM) meet the definition of standardized patient
assessment data with respect to cognitive function and mental status
under section 1899B(b)(1)(B)(ii) of the Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20101 through 20102), the CAM was developed to identify the signs and
symptoms of delirium. It results in a score that suggests whether a
patient or resident should be assigned a diagnosis of delirium. Because
patients and residents with multiple comorbidities receive services
from PAC providers, it is important to assess delirium, which is
associated with a high mortality rate and prolonged duration of stay in
hospitalized older adults.\710\ Assessing these signs and symptoms of
delirium is clinically relevant for care planning by PAC providers.
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\710\ Fick, D.M., Steis, M.R., Waller, J.L., & Inouye, S.K.
(2013). ``Delirium superimposed on dementia is associated with
prolonged length of stay and poor outcomes in hospitalized older
adults.'' J of Hospital Med 8(9): 500-505.
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The CAM is a patient assessment that screens for overall cognitive
impairment, as well as distinguishes delirium or reversible confusion
from other types of cognitive impairment. The CAM is currently in use
in two of the PAC assessments: A four-item version of the CAM is used
in the MDS in SNFs, and a six-item version of the CAM is used in the
LCDS in LTCHs. We are proposing to replace the version of the CAM
currently used in the LCDS with the four-item version of the CAM
currently used in the MDS. The proposed four-item version assesses
acute change in mental status, inattention, disorganized thinking, and
altered level of consciousness. For more information on the CAM, we
refer readers to the document titled ``Proposed Specifications for LTCH
QRP Quality Measures and Standardized Patient Assessment Data
Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The data elements that comprise the CAM were first proposed as
SPADEs in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20101 through
20102). In that proposed rule, we stated that the proposal was informed
by input we received through a call for input published on the CMS
Measures Management System Blueprint website. Input submitted from
August 12 to September 12, 2016 expressed support for use of the CAM,
noting that it would provide important information for care planning
and care coordination and, therefore, contribute to quality
improvement. We also stated that those commenters noted it is
particularly helpful in distinguishing delirium and reversible
confusion from other types of cognitive impairment. A summary report
for the August 12 to September 12, 2016 public comment period titled
``SPADE August 2016 Public Comment Summary Report'' is available at:
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received public comments (82 FR 20101 through 20102) in
support of the CAM. Commenters supported the continued use of the CAM
in the LCDS. However, commenters expressed concerns about not having
recent, comprehensive field testing of proposed data elements.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the CAM was included in the National Beta Test of
candidate data elements conducted by our data element contractor from
November 2017 to August 2018. Results of this test found the CAM to be
feasible and reliable for use with PAC patients and residents. More
information about the performance of the CAM in the National Beta Test
can be found in the document titled ``Proposed Specifications for LTCH
QRP Quality Measures and Standardized Patient Assessment Data
Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018, for the purpose of soliciting input on the proposed
standardized patient assessment data elements. Although they did not
specifically discuss the CAM data elements, the TEP supported the
assessment of patient or resident cognitive status with respect to both
admission and discharge. A summary of the September 17, 2018 TEP
meeting titled ``SPADE Technical Expert Panel Summary (Third
Convening)'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-
Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-
Initiatives/IMPACT-Act-of-2014/
[[Page 19522]]
IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for delirium,
stakeholder input, and strong test results, we are proposing that the
CAM data elements meet the definition of standardized patient
assessment data with respect to cognitive function and mental status
under section 1899B(b)(1)(B)(ii) of the Act, and to adopt the CAM as
standardized patient assessment data for use in the LTCH QRP.
Patient Health Questionnaire-2 to 9 (PHQ-2 to 9)
We are proposing that the Patient Health Questionnaire-2 to 9 (PHQ-
2 to 9) data elements meet the definition of standardized patient
assessment data with respect to cognitive function and mental status
under section 1899B(b)(1)(B)(ii) of the Act. The proposed data elements
are based on the PHQ-2 mood interview, which focuses on only the two
cardinal symptoms of depression, and the longer PHQ-9 mood interview,
which assesses presence and frequency of nine signs and symptoms of
depression. The name of the data element, the PHQ-2 to 9, refers to an
embedded a skip pattern that transitions patients with a threshold
level of symptoms in the PHQ-2 to the longer assessment of the PHQ-9.
The skip pattern is described further below.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20102 through 20103), depression is a common and under-recognized
mental health condition. Assessments of depression help PAC providers
better understand the needs of their patients and residents by:
Prompting further evaluation after establishing a diagnosis of
depression; elucidating the patient's or resident's ability to
participate in therapies for conditions other than depression during
their stay; and identifying appropriate ongoing treatment and support
needs at the time of discharge.
The proposed PHQ-2 to 9 is based on the PHQ-9 mood interview. The
PHQ-2 consists of questions about only the first two symptoms addressed
in the PHQ-9: Depressed mood and anhedonia (inability to feel
pleasure), which are the cardinal symptoms of depression. The PHQ-2 has
performed well as both a screening tool for identifying depression, to
assess depression severity, and to monitor patient mood over
time.711 712 If a patient demonstrates signs of depressed
mood and anhedonia under the PHQ-2, then the patient is administered
the lengthier PHQ-9. This skip pattern (also referred to as a gateway)
is designed to reduce the length of the interview assessment for
patients who fail to report the cardinal symptoms of depression. The
design of the PHQ-2 to 9 reduces the burden that would be associated
with the full PHQ-9, while ensuring that patients with indications of
depressive symptoms based on the PHQ-2 receive the longer assessment.
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\711\ Li, C., Friedman, B., Conwell, Y., & Fiscella, K. (2007).
``Validity of the Patient Health Questionnaire 2 (PHQ[hyphen]2) in
identifying major depression in older people.'' J of the A
Geriatrics Society, 55(4): 596-602.
\712\ L[ouml]we, B., Kroenke, K., & Gr[auml]fe, K. (2005).
``Detecting and monitoring depression with a two-item questionnaire
(PHQ-2).'' J of Psychosomatic Research, 58(2): 163-171.
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Components of the proposed data elements are currently used in the
OASIS for HHAs (PHQ-2) and the MDS for SNFs (PHQ-9). For more
information on the PHQ-2 to 9, we refer readers to the document titled
``Proposed Specifications for LTCH QRP Quality Measures and
Standardized Patient Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We proposed the PHQ-2 data elements as SPADEs in the FY 2018 IPPS/
LTCH PPS proposed rule (82 FR 20102 through 20103). In that proposed
rule we stated that the proposal was informed by input we received from
the TEP convened by our data element contractor on April 6 and 7, 2016.
The TEP members particularly noted that the brevity of the PHQ-2 made
it feasible to administer with low burden for both assessors and PAC
patients or residents. A summary of the April 6 and 7, 2016 TEP meeting
titled ``SPADE Technical Expert Panel Summary (First Convening)'' is
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
That rule proposal was also informed by public input that we
received through a call for input published on the CMS Measures
Management System Blueprint website. Input was submitted from August 12
to September 12, 2016 on three versions of the PHQ depression screener:
The PHQ-2; the PHQ-9; and the PHQ-2 to 9 with the skip pattern design.
Many commenters were supportive of the standardized assessment of mood
in PAC settings, given the role that depression plays in well-being.
Several commenters expressed support for an approach that would use
PHQ-2 as a gateway to the longer PHQ-9 while still potentially reducing
burden on most patients and residents, as well as test administrators,
and ensuring the administration of the PHQ-9, which exhibits higher
specificity,\713\ for patients and residents who showed signs and
symptoms of depression on the PHQ-2. A summary report for the August 12
to September 12, 2016 public comment period titled ``SPADE August 2016
Public Comment Summary Report'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
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\713\ Arroll B, Goodyear-Smith F, Crengle S, Gunn J, Kerse N,
Fishman T, et al. Validation of PHQ-2 and PHQ-9 to screen for major
depression in the primary care population. Annals of family
medicine. 2010;8(4):348-53. doi: 10.1370/afm.1139 pmid:20644190;
PubMed Central PMCID: PMC2906530.
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In response to our proposal to use the PHQ-2 in the FY 2018 IPPS/
LTCH PPS proposed rule, we received comments agreeing that it was
important to standardize the assessment of depression in patients
receiving PAC services. Many commenters also raised concerns about the
ability of the PHQ-2 to correctly identify all patients with signs and
symptoms of depression and noted that the proposed PHQ-2 was not
supported by recent, comprehensive field testing. In response to these
comments, we carried out additional testing, and we provide our
findings below.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the PHQ-2 to 9 data elements were included in the
National Beta Test of candidate data elements conducted by our data
element contractor from November 2017 to August 2018. Results of this
test found the PHQ-2 to 9 to be feasible and reliable for use with PAC
patients and residents. More information about the performance of the
PHQ-2 to 9 in the National Beta Test can be found in the document
titled ``Proposed Specifications for LTCH QRP Quality Measures and
Standardized Patient Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of
[[Page 19523]]
soliciting input on the PHQ-2 to 9. The TEP was supportive of the PHQ-2
to 9 data element set as a screener for signs and symptoms of
depression. The TEP's discussion noted that symptoms evaluated by the
full PHQ-9 (for example, concentration, sleep, appetite) had relevance
to care planning and the overall well-being of the patient or resident,
but that the gateway approach of the PHQ-2 to 9 would be appropriate as
a depression screening assessment, as it depends on the well-validated
PHQ-2 and focuses on the cardinal symptoms of depression. A summary of
the September 17, 2018 TEP meeting titled ``SPADE Technical Expert
Panel Summary (Third Convening)'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our on-going SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for depression,
stakeholder input, and strong test results, in this proposed rule, we
are proposing that the PHQ-2 to 9 data elements meet the definition of
standardized patient assessment data with respect to cognitive function
and mental status under section 1899B(b)(1)(B)(ii) of the Act, and to
adopt the PHQ-2 to 9 as standardized patient assessment data for use in
the LTCH QRP.
c. Special Services, Treatments, and Interventions Data
Special services, treatments, and interventions performed in PAC
can have a major effect on an individual's health status, self-image,
and quality of life. The assessment of these special services,
treatments, and interventions in PAC is important to ensure the
continuing appropriateness of care for the patients and residents
receiving them, and to support care transitions from one PAC provider
to another, an acute care hospital, or discharge. In alignment with our
Meaningful Measures Initiative, accurate assessment of special
services, treatments, and interventions of patients and residents
served by PAC providers is expected to make care safer by reducing harm
caused in the delivery of care; promote effective prevention and
treatment of chronic disease; strengthen person and family engagement
as partners in their care; and promote effective communication and
coordination of care.
For example, standardized assessment of special services,
treatments, and interventions used in PAC can promote patient and
resident safety through appropriate care planning (for example,
mitigating risks such as infection or pulmonary embolism associated
with central intravenous access), and identifying life-sustaining
treatments that must be continued, such as mechanical ventilation,
dialysis, suctioning, and chemotherapy, at the time of discharge or
transfer. Standardized assessment of these data elements will enable or
support: Clinical decision-making and early clinical intervention;
person-centered, high quality care through, for example, facilitating
better care continuity and coordination; better data exchange and
interoperability between settings; and longitudinal outcome analysis.
Therefore, reliable data elements assessing special services,
treatments, and interventions are needed to initiate a management
program that can optimize a patient's or resident's prognosis and
reduce the possibility of adverse events.
A TEP convened by our data element contractor provided input on the
proposed data elements for special services, treatments, and
interventions. In a meeting held on January 5 and 6, 2017, this TEP
found that these data elements are appropriate for standardization
because they would provide useful clinical information to inform care
planning and care coordination. The TEP affirmed that assessment of
these services and interventions is standard clinical practice, and
that the collection of these data by means of a list and checkbox
format would conform with common workflow for PAC providers. A summary
of the January 5 and 6, 2017 TEP meeting titled ``SPADE Technical
Expert Panel Summary (Second Convening)'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Comments on the category of special services, treatments, and
interventions were also submitted by stakeholders during the FY 2018
IPPS/LTCH PPS proposed rule public comment period. Although a few
commenters noted the burden that the data elements for special
services, treatments, and interventions will place on assessors and
providers, we also received support for these data elements, noting
their ability to inform care planning and care coordination.
Information on data element performance in the National Beta Test,
which collected data between November 2017 and August 2018, is reported
within each data element proposal below. Clinical staff who
participated in the National Beta Test supported these data elements
because of their importance in conveying patient or resident
significant health care needs, complexity, and progress. However,
clinical staff also noted that, despite the simple ``check box'' format
of these data element, they sometimes needed to consult multiple
information sources to determine a patient's or resident's treatments.
Cancer Treatment: Chemotherapy (IV, Oral, Other)
We are proposing that the Chemotherapy (IV, Oral, Other) data
element meets the definition of standardized patient assessment data
with respect to special services, treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20103 through 20104), chemotherapy is a type of cancer treatment that
uses drugs to destroy cancer cells. It is sometimes used when a patient
has a malignancy (cancer), which is a serious, often life-threatening
or life-limiting condition. Both intravenous (IV) and oral chemotherapy
have serious side effects, including nausea/vomiting, extreme fatigue,
risk of infection due to a suppressed immune system, anemia, and an
increased risk of bleeding due to low platelet counts. Oral
chemotherapy can be as potent as chemotherapy given by IV, and can be
significantly more convenient and less resource-intensive to
administer. Because of the toxicity of these agents, special care must
be
[[Page 19524]]
exercised in handling and transporting chemotherapy drugs. IV
chemotherapy is administered either peripherally or more commonly given
via an indwelling central line, which raises the risk of bloodstream
infections. Given the significant burden of malignancy, the resource
intensity of administering chemotherapy, and the side effects and
potential complications of these highly-toxic medications, assessing
the receipt of chemotherapy is important in the PAC setting for care
planning and determining resource use. The need for chemotherapy
predicts resource intensity, both because of the complexity of
administering these potent, toxic drug combinations under specific
protocols, and because of what the need for chemotherapy signals about
the patient's underlying medical condition. Furthermore, the resource
intensity of IV chemotherapy is higher than for oral chemotherapy, as
the protocols for administration and the care of the central line (if
present) for IV chemotherapy require significant resources.
The Chemotherapy (IV, Oral, Other) data element consists of a
principal data element (Chemotherapy) and three response option sub-
elements: IV chemotherapy, which is generally resource-intensive; Oral
chemotherapy, which is less invasive and generally requires less
intensive administration protocols; and a third category, Other,
provided to enable the capture of other less common chemotherapeutic
approaches. This third category is potentially associated with higher
risks and is more resource intensive due to chemotherapy delivery by
other routes (for example, intraventricular or intrathecal). If the
assessor indicates that the patient is receiving chemotherapy on the
principal Chemotherapy data element, the assessor would then indicate
by which route or routes (for example, IV, Oral, Other) the
chemotherapy is administered.
A single Chemotherapy data element that does not include the
proposed three sub-elements is currently in use in the MDS in SNFs. For
more information on the Chemotherapy (IV, Oral, Other) data element, we
refer readers to the document titled ``Proposed Specifications for LTCH
QRP Quality Measures and Standardized Patient Assessment Data
Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The Chemotherapy data element was proposed as a SPADE in the FY
2018 IPPS/LTCH PPS proposed rule (82 FR 20103 through 20104). In that
proposed rule, we stated that the proposal was informed by input we
received through a call for input published on the CMS Measures
Management System Blueprint website. Input submitted from August 12 to
September 12, 2016 expressed support for the IV Chemotherapy data
element and suggested it be included as standardized patient assessment
data. Commenters stated that assessing the use of chemotherapy services
is relevant to share across the care continuum to facilitate care
coordination and care transitions and noted the validity of the data
element. Commenters also noted the importance of capturing all types of
chemotherapy, regardless of route, and stated that collecting data only
on patients and residents who received chemotherapy by IV would limit
the usefulness of this standardized data element. A summary report for
the August 12 to September 12, 2016 public comment period titled
``SPADE August 2016 Public Comment Summary Report'' is available at:
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received public comments in support of the special services,
treatments, and interventions data elements in general; no additional
comments were received that were specific to the Chemotherapy data
element other than concerns about not having recent, comprehensive
field testing of proposed data elements.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the Chemotherapy data element was included in the
National Beta Test of candidate data elements conducted by our data
element contractor from November 2017 to August 2018. Results of this
test found the Chemotherapy data element to be feasible and reliable
for use with PAC patients and residents. More information about the
performance of the Chemotherapy data element in the National Beta Test
can be found in the document titled ``Proposed Specifications for LTCH
QRP Quality Measures and Standardized Patient Assessment Data
Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the special
services, treatments, and interventions. Although the TEP members did
not specifically discuss the Chemotherapy data elements, the TEP
supported the assessment of the special services, treatments, and
interventions included in the National Beta Test with respect to both
admission and discharge. A summary of the September 17, 2018 TEP
meeting titled ``SPADE Technical Expert Panel Summary (Third
Convening)'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for chemotherapy,
stakeholder input, and strong test results, we are proposing that the
Chemotherapy (IV, Oral, Other) data element with a principal data
element and three sub-elements meets the definition of standardized
patient assessment data with respect to special services, treatments,
and interventions under section 1899B(b)(1)(B)(iii) of the Act, and to
adopt the Chemotherapy (IV, Oral, Other) data element as standardized
patient assessment data for use in the LTCH QRP.
Cancer Treatment: Radiation
We are proposing that the Radiation data element meets the
definition of
[[Page 19525]]
standardized patient assessment data with respect to special services,
treatments, and interventions under section 1899B(b)(1)(B)(iii) of the
Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20104 through 20105), radiation is a type of cancer treatment that uses
high-energy radioactivity to stop cancer by damaging cancer cell DNA,
but it can also damage normal cells. Radiation is an important therapy
for particular types of cancer, and the resource utilization is high,
with frequent radiation sessions required, often daily for a period of
several weeks. Assessing whether a patient or resident is receiving
radiation therapy is important to determine resource utilization
because PAC patients and residents will need to be transported to and
from radiation treatments, and monitored and treated for side effects
after receiving this intervention. Therefore, assessing the receipt of
radiation therapy, which would compete with other care processes given
the time burden, would be important for care planning and care
coordination by PAC providers.
The proposed data element consists of the single Radiation data
element. The Radiation data element is currently in use in the MDS in
SNFs. For more information on the Radiation data element, we refer
readers to the document titled ``Proposed Specifications for LTCH QRP
Quality Measures and Standardized Patient Assessment Data Elements,''
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The Radiation data element was first proposed as a SPADE in the FY
2018 IPPS/LTCH PPS proposed rule (82 FR 20104 through 20105). In that
proposed rule, we stated that the proposal was informed by input we
received through a call for input published on the CMS Measures
Management System Blueprint website. Input submitted from August 12 to
September 12, 2016 expressed support for the Radiation data element,
noting its importance and clinical usefulness for patients in PAC
settings, due to the side effects and consequences of radiation
treatment on patients that need to be considered in care planning and
care transitions, the feasibility of the item, and the potential for it
to improve quality. A summary report for the August 12 to September 12,
2016 public comment period titled ``SPADE August 2016 Public Comment
Summary Report'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received public comments in support of the special services,
treatments, and interventions data elements in general; no additional
comments were received that were specific to the Radiation data element
other than concerns about not having recent, comprehensive field
testing of proposed data elements.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the Radiation data element was included in the National
Beta Test of candidate data elements conducted by our data element
contractor from November 2017 to August 2018. Results of this test
found the Radiation data element to be feasible and reliable for use
with PAC patients and residents. More information about the performance
of the Radiation data element in the National Beta Test can be found in
the document titled ``Proposed Specifications for LTCH QRP Quality
Measures and Standardized Patient Assessment Data Elements,'' available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the special
services, treatments, and interventions and the TEP supported the
assessment of the special services, treatments, and interventions
included in the National Beta Test with respect to both admission and
discharge. A summary of the September 17, 2018 TEP meeting titled
``SPADE Technical Expert Panel Summary (Third Convening)'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present results of the National Beta
Test and solicit additional comments. General input on the testing and
item development process and concerns about burden were received from
stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for radiation,
stakeholder input, and strong test results, we are proposing that the
Radiation data element meets the definition of standardized patient
assessment data with respect to special services, treatments, and
interventions under section 1899B(b)(1)(B)(iii) of the Act, and to
adopt the Radiation data element as standardized patient assessment
data for use in the LTCH QRP.
Respiratory Treatment: Oxygen Therapy (Intermittent,
Continuous, High-Concentration Oxygen Delivery System)
We are proposing that the Oxygen Therapy (Intermittent, Continuous,
High-Concentration Oxygen Delivery System) data element meets the
definition of standardized patient assessment data with respect to
special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act.
In the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20105), we
proposed a similar set of data elements related to oxygen therapy.
Oxygen therapy provides a patient or resident with extra oxygen when
medical conditions such as chronic obstructive pulmonary disease,
pneumonia, or severe asthma prevent the patient or resident from
getting enough oxygen from breathing. Oxygen administration is a
resource-intensive intervention, as it requires specialized equipment
such as a source of oxygen, delivery systems (for example, oxygen
concentrator, liquid oxygen containers, and high-pressure systems), the
patient interface (for example, nasal cannula or mask), and other
accessories (for example, regulators, filters, tubing). The data
element proposed here captures patient or resident use of three types
of oxygen therapy (intermittent, continuous, and high-concentration
oxygen delivery system), which reflects the intensity of care needed,
including the level of monitoring and bedside care required. Assessing
the receipt of this service is
[[Page 19526]]
important for care planning and resource use for PAC providers.
The proposed data element, Oxygen Therapy, consists of the
principal Oxygen Therapy data element and three response option sub-
elements: Continuous (whether the oxygen was delivered continuously,
typically defined as >=14 hours per day); Intermittent; or High-
concentration oxygen delivery system. Based on public comments and
input from expert advisors about the importance and clinical usefulness
of documenting the extent of oxygen use, we added a third sub-element,
high-concentration oxygen delivery system, to the sub-elements, which
previously included only intermittent and continuous. If the assessor
indicates that the patient is receiving oxygen therapy on the principal
oxygen therapy data element, the assessor then would indicate the type
of oxygen the patient receives (for example, Continuous, Intermittent,
High-concentration oxygen delivery system).
These three proposed sub-elements were developed based on similar
data elements that assess oxygen therapy, currently in use in the MDS
in SNFs (``Oxygen Therapy''), previously used in the OASIS-C2 (``Oxygen
(intermittent or continuous)''), and a data element tested in the PAC
PRD that focused on intensive oxygen therapy (``High O2 Concentration
Delivery System with FiO2 >40 percent''). For more information on the
proposed Oxygen Therapy (Continuous, Intermittent, High-concentration
oxygen delivery system) data element, we refer readers to the document
titled ``Proposed Specifications for LTCH QRP Quality Measures and
Standardized Patient Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The Oxygen Therapy (Continuous, Intermittent) data element was
first proposed as a SPADE in the FY 2018 IPPS/LTCH PPS proposed rule
(82 FR 20105). In that proposed rule, we stated that the proposal was
informed by input we received on the single data element, Oxygen
(inclusive of intermittent and continuous oxygen use), through a call
for input published on the CMS Measures Management System Blueprint
website. Input submitted from August 12 to September 12, 2016 expressed
the importance of the Oxygen data element, noting feasibility of this
item in PAC, and the relevance of it to facilitating care coordination
and supporting care transitions, but suggesting that the extent of
oxygen use be documented. A summary report for the August 12 to
September 12, 2016 public comment period titled ``SPADE August 2016
Public Comment Summary Report'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received public comments in support of the special services,
treatments, and interventions data elements in general, which are
summarized above. In response to our proposal, we received comments in
support of the Oxygen Therapy (Continuous, Intermittent) data element.
A commenter also requested the addition of a third sub-element to
differentiate between receipt of high-flow oxygen (6 or more liters per
minute) and regular oxygen, noting that it is a form of respiratory
support commonly used on patients with acute respiratory failure and,
therefore, could be used as an indicator of patient severity in future
analysis. We also received public comments related to concerns about
not having recent, comprehensive field testing of proposed data
elements. In response to public comments, we added a third sub-element
to the Oxygen Therapy data element and carried out additional testing,
which we provide our findings below.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the Oxygen Therapy data element was included in the
National Beta Test of candidate data elements conducted by our data
element contractor from November 2017 to August 2018. Results of this
test found the Oxygen Therapy data element to be feasible and reliable
for use with PAC patients and residents. More information about the
performance of the Oxygen Therapy data element in the National Beta
Test can be found in the document titled ``Proposed Specifications for
LTCH QRP Quality Measures and Standardized Patient Assessment Data
Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the special
services, treatments, and interventions and the TEP supported the
assessment of the special services, treatments, and interventions
included in the National Beta Test with respect to both admission and
discharge. A summary of the September 17, 2018 TEP meeting titled
``SPADE Technical Expert Panel Summary (Third Convening)'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for oxygen therapy,
stakeholder input, and strong test results, we are proposing that the
Oxygen Therapy (Intermittent, Continuous, High-concentration oxygen
delivery system) data element with a principal data element and three
sub-elements meets the definition of standardized patient assessment
data with respect to special services, treatments, and interventions
under section 1899B(b)(1)(B)(iii) of the Act, and to adopt the Oxygen
Therapy (Intermittent, Continuous, High-concentration oxygen delivery
system) data element as standardized patient assessment data for use in
the LTCH QRP.
Respiratory Treatment: Suctioning (Scheduled, As Needed)
We are proposing that the Suctioning (Scheduled, As needed) data
element meets the definition of standardized patient assessment data
with respect to special services, treatments, and
[[Page 19527]]
interventions under section 1899B(b)(1)(B)(iii) of the Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20105 through 20106), suctioning is a process used to clear secretions
from the airway when a person cannot clear those secretions on his or
her own. It is done by aspirating secretions through a catheter
connected to a suction source. Types of suctioning include
oropharyngeal and nasopharyngeal suctioning, nasotracheal suctioning,
and suctioning through an artificial airway such as a tracheostomy
tube. Oropharyngeal and nasopharyngeal suctioning are a key part of
many patients' care plans, both to prevent the accumulation of
secretions than can lead to aspiration pneumonias (a common condition
in patients with inadequate gag reflexes), and to relieve obstructions
from mucus plugging during an acute or chronic respiratory infection,
which often lead to desaturations and increased respiratory effort.
Suctioning can be done on a scheduled basis if the patient is judged to
clinically benefit from regular interventions, or can be done as needed
when secretions become so prominent that gurgling or choking is noted,
or a sudden desaturation occurs from a mucus plug. As suctioning is
generally performed by a care provider rather than independently, this
intervention can be quite resource intensive if it occurs every hour,
for example, rather than once a shift. It also signifies an underlying
medical condition that prevents the patient from clearing his/her
secretions effectively (such as after a stroke, or during an acute
respiratory infection). Generally, suctioning is necessary to ensure
that the airway is clear of secretions which can inhibit successful
oxygenation of the individual. The intent of suctioning is to maintain
a patent airway, the loss of which can lead to death, or complications
associated with hypoxia.
The Suctioning (Scheduled, As needed) data element consists of a
principal data element, and two sub-elements: Scheduled; and As needed.
These sub-elements capture two types of suctioning. Scheduled indicates
suctioning based on a specific frequency, such as every hour. As needed
means suctioning only when indicated. If the assessor indicates that
the patient is receiving suctioning on the principal Suctioning data
element, the assessor would then indicate the frequency (for example,
Scheduled, As needed). The proposed data element is based on an item
currently in use in the MDS in SNFs which does not include our proposed
two sub-elements, as well as data elements tested in the PAC PRD that
focused on the frequency of suctioning required for patients with
tracheostomies (``Trach Tube with Suctioning: Specify most intensive
frequency of suctioning during stay [Every _ hours]''). For more
information on the Suctioning data element, we refer readers to the
document titled ``Proposed Specifications for LTCH QRP Quality Measures
and Standardized Patient Assessment Data Elements,'' available at:
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The Suctioning data elements were first proposed as SPADEs in the
FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20105 through 20106). In
that proposed rule, we stated that the proposal was informed by input
we received through a call for input published on the CMS Measures
Management System Blueprint website. Input submitted from August 12, to
September 12, 2016 expressed support of the Suctioning data element
currently used in the MDS in SNFs. The input noted the feasibility of
this item in PAC, and the relevance of this data element to
facilitating care coordination and supporting care transitions. We also
received public comments suggesting that we examine the frequency of
suctioning in order to better understand the use of staff time, the
impact on a patient or resident's capacity to speak and swallow, and
intensity of care required. Based on these comments, we decided to add
two sub-elements (Scheduled and As needed) to the suctioning element.
The proposed Suctioning data element includes both the principal
Suctioning data element that is included on the MDS in SNFs and two
sub-elements, Scheduled and As needed. A summary report for the August
12 to September 12, 2016 public comment period titled ``SPADE August
2016 Public Comment Summary Report'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received public comments in support of the special services,
treatments, and interventions data elements in general; no additional
comments were received that were specific to the Suctioning data
element other than concerns about not having recent, comprehensive
field testing of proposed data elements.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the Suctioning data element was included in the National
Beta Test of candidate data elements conducted by our data element
contractor from November 2017 to August 2018. Results of this test
found the Suctioning data element to be feasible and reliable for use
with PAC patients and residents. More information about the performance
of the Suctioning data element in the National Beta Test can be found
in the document titled ``Proposed Specifications for LTCH QRP Quality
Measures and Standardized Patient Assessment Data Elements,'' available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the special
services, treatments, and interventions and the TEP supported the
assessment of the special services, treatments, and interventions
included in the National Beta Test with respect to both admission and
discharge. A summary of the September 17, 2018 TEP meeting titled
``SPADE Technical Expert Panel Summary (Third Convening)'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicited additional comments. General input on the
testing and item development process and concerns about burden were
received from stakeholders during this meeting and via email through
February 1, 2019. A summary of the public input received from the
November 27, 2018 stakeholder meeting titled ``Input on Standardized
Patient Assessment Data Elements (SPADEs) Received After November 27,
2018 Stakeholder Meeting'' is available at: https://www.cms.gov/
Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-
Care-Quality-
[[Page 19528]]
Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for suctioning,
stakeholder input, and strong test results, we are proposing that the
Suctioning (Scheduled, As needed) data element with a principal data
element and two sub-elements meets the definition of standardized
patient assessment data with respect to special services, treatments,
and interventions under section 1899B(b)(1)(B)(iii) of the Act, and to
adopt the Suctioning (Scheduled, As needed) data element as
standardized patient assessment data for use in the LTCH QRP.
Respiratory Treatment: Tracheostomy Care
We are proposing that the Tracheostomy Care data element meets the
definition of standardized patient assessment data with respect to
special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20106 through 20107), a tracheostomy provides an air passage to help a
patient or resident breathe when the usual route for breathing is
obstructed or impaired. Generally, in all of these cases, suctioning is
necessary to ensure that the tracheostomy is clear of secretions, which
can inhibit successful oxygenation of the individual. Often,
individuals with tracheostomies are also receiving supplemental
oxygenation. The presence of a tracheostomy, albeit permanent or
temporary, warrants careful monitoring and immediate intervention if
the tracheostomy becomes occluded or if the device used becomes
dislodged. While in rare cases the presence of a tracheostomy is not
associated with increased care demands (and in some of those instances,
the care of the ostomy is performed by the patient) in general the
presence of such as device is associated with increased patient risk,
and clinical care services will necessarily include close monitoring to
ensure that no life-threatening events occur as a result of the
tracheostomy. In addition, tracheostomy care, which primarily consists
of cleansing, dressing changes, and replacement of the tracheostomy
cannula (tube), is a critical part of the care plan. Regular cleansing
is important to prevent infection such as pneumonia and to prevent any
occlusions with which there are risks for inadequate oxygenation.
The proposed data element consists of the single Tracheostomy Care
data element. The proposed data element is currently in use in the MDS
in SNFs (``Tracheostomy care''). For more information on the
Tracheostomy Care data element, we refer readers to the document titled
``Proposed Specifications for LTCH QRP Quality Measures and
Standardized Patient Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The Tracheostomy Care data element was first proposed as a SPADE in
the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20106 through 20107). In
that proposed rule, we stated that the proposal was informed by input
we received through a call for input published on the CMS Measures
Management System Blueprint website. Input submitted from August 12 to
September 12, 2016 expressed support of the Tracheostomy Care data
element, noting the feasibility of this item in PAC, and the relevance
of this data element to facilitating care coordination and supporting
care transitions. A summary report for the August 12 to September 12,
2016 public comment period titled ``SPADE August 2016 Public Comment
Summary Report'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
During the FY 2018 IPPS/LTCH PPS proposed rule comment period, we
received public comments in support of the special services,
treatments, and interventions data elements in general; no additional
comments were received that were specific to the Tracheostomy Care data
element other than concerns about not having recent, comprehensive
field testing of proposed data elements.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the Tracheostomy Care data element was included in the
National Beta Test of candidate data elements conducted by our data
element contractor from November 2017 to August 2018. Results of this
test found the Tracheostomy Care data element to be feasible and
reliable for use with PAC patients and residents. More information
about the performance of the Tracheostomy Care data element in the
National Beta Test can be found in the document titled ``Proposed
Specifications for LTCH QRP Quality Measures and Standardized Patient
Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the special
services, treatments, and interventions and the TEP supported the
assessment of the special services, treatments, and interventions
included in the National Beta Test with respect to both admission and
discharge. A summary of the September 17, 2018 TEP meeting titled
``SPADE Technical Expert Panel Summary (Third Convening)'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for tracheostomy care,
stakeholder input, and strong test results, we are proposing that the
Tracheostomy Care data element meets the definition of standardized
patient assessment data with respect to special services, treatments,
and interventions under section 1899B(b)(1)(B)(iii) of the Act, and to
adopt the Tracheostomy Care data element as standardized patient
assessment data for use in the LTCH QRP.
[[Page 19529]]
Respiratory Treatment: Non-Invasive Mechanical Ventilator
(BiPAP, CPAP)
We are proposing that the Non-invasive Mechanical Ventilator
(Bilevel Positive Airway Pressure [BiPAP], Continuous Positive Airway
Pressure [CPAP]) data element meets the definition of standardized
patient assessment data with respect to special services, treatments,
and interventions under section 1899B(b)(1)(B)(iii) of the Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20107), BiPAP and CPAP are respiratory support devices that prevent the
airways from closing by delivering slightly pressurized air via
electronic cycling throughout the breathing cycle (BiPAP) or through a
mask continuously (CPAP). Assessment of non-invasive mechanical
ventilation is important in care planning, as both CPAP and BiPAP are
resource-intensive (although less so than invasive mechanical
ventilation) and signify underlying medical conditions about the
patient or resident who requires the use of this intervention.
Particularly when used in settings of acute illness or progressive
respiratory decline, additional staff (for example, respiratory
therapists) are required to monitor and adjust the CPAP and BiPAP
settings and the patient or resident may require more nursing
resources.
The proposed data element, Non-invasive Mechanical Ventilator
(BIPAP, CPAP), consists of the principal Non-invasive Mechanical
Ventilator data element and two sub-elements: BiPAP and CPAP. If the
assessor indicates that the patient is receiving non-invasive
mechanical ventilation on the principal Non-invasive Mechanical
Ventilator data element, the assessor would then indicate which type
(that is, BIPAP, CPAP). Data elements that assess non-invasive
mechanical ventilation are currently included on LCDS for the LTCH
setting (``Non-invasive Ventilator (BIPAP, CPAP)''), and the MDS for
the SNF setting (``Non-invasive Mechanical Ventilator (BiPAP/CPAP)'').
We are proposing to expand the existing ``Non-invasive Ventilator
(BiPAP, CPAP)'' data element on the LCDS, by retaining and renaming the
main data element to be Non-invasive Mechanical Ventilator and adding
two sub-elements for BiPAP and CPAP. For more information on the Non-
invasive Mechanical Ventilator (BIPAP, CPAP) data element, we refer
readers to the document titled ``Proposed Specifications for LTCH QRP
Quality Measures and Standardized Patient Assessment Data Elements,''
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The Non-invasive Mechanical Ventilator data element was first
proposed as SPADEs in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20107). In that proposed rule, we stated that the proposal was informed
by input we received through a call for input published on the CMS
Measures Management System Blueprint website on a single data element,
BiPAP/CPAP, that captures equivalent clinical information but uses a
different label, to what is currently in use on the MDS in SNFs and
LCDS in LTCHs. Input submitted from August 12 to September 12, 2016
expressed support of the data element, noting the feasibility in PAC,
and the relevance to facilitating care coordination and supporting care
transitions. In addition, there was support in the public comment
responses for separating out BiPAP and CPAP as distinct sub-elements,
as they are therapies used for different types of patients and
residents. A summary report for the August 12 to September 12, 2016
public comment period titled ``SPADE August 2016 Public Comment Summary
Report'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received public comments in support of the special services,
treatments, and interventions data elements in general; no additional
comments were received that were specific to the Non-invasive
Mechanical Ventilator data element other than concerns about not having
recent, comprehensive field testing of proposed data elements.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the Non-invasive Mechanical Ventilator data element was
included in the National Beta Test of candidate data elements conducted
by our data element contractor from November 2017 to August 2018.
Results of this test found the Non-invasive Mechanical Ventilator data
element to be feasible and reliable for use with PAC patients and
residents. More information about the performance of the Non-invasive
Mechanical Ventilator data element in the National Beta Test can be
found in the document titled ``Proposed Specifications for LTCH QRP
Quality Measures and Standardized Patient Assessment Data Elements,''
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the special
services, treatments, and interventions and the TEP supported the
assessment of the special services, treatments, and interventions
included in the National Beta Test with respect to both admission and
discharge. A summary of the September 17, 2018 TEP meeting titled
``SPADE Technical Expert Panel Summary (Third Convening)'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for non-invasive
mechanical ventilation, stakeholder input, and strong test results, we
are proposing that the Non-invasive Mechanical Ventilator (BiPAP, CPAP)
data element, with a principal data element and two sub-elements, meets
the definition of standardized patient assessment data with respect to
special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act, and to adopt the Non-invasive
Mechanical Ventilator (BiPAP, CPAP) data element as standardized
patient
[[Page 19530]]
assessment data for use in the LTCH QRP.
Respiratory Treatment: Invasive Mechanical Ventilator
We are proposing that the Invasive Mechanical Ventilator data
element meets the definition of standardized patient assessment data
with respect to special services, treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20107 through 20108), invasive mechanical ventilation includes
ventilators and respirators that ventilate the patient through a tube
that extends via the oral airway into the pulmonary region or through a
surgical opening directly into the trachea. Thus, assessment of
invasive mechanical ventilation is important in care planning and risk
mitigation. Ventilation in this manner is a resource-intensive therapy
associated with life-threatening conditions without which the patient
or resident would not survive. However, ventilator use has inherent
risks requiring close monitoring. Failure to adequately care for the
patient or resident who is ventilator dependent can lead to iatrogenic
events such as death, pneumonia and sepsis. Mechanical ventilation
further signifies the complexity of the patient's underlying medical or
surgical condition. Of note, invasive mechanical ventilation is
associated with high daily and aggregate costs.\714\
---------------------------------------------------------------------------
\714\ Wunsch, H., Linde-Zwirble, W. T., Angus, D.C., Hartman,
M.E., Milbrandt, E. B., & Kahn, J.M. (2010). ``The epidemiology of
mechanical ventilation use in the United States.'' Critical Care Med
38(10): 1947-1953.
---------------------------------------------------------------------------
The proposed data element, Invasive Mechanical Ventilator, consists
of a single data element. Data elements that capture invasive
mechanical ventilation are currently in use in the MDS in SNFs and LCDS
in LTCHs. We are proposing that this data element will be collected at
admission from the ``Invasive Mechanical Ventilation Support upon
Admission to the LTCH'' data element that is already included on the
LCDS, and through a new, added data element at discharge. For more
information on the Invasive Mechanical Ventilator data element, we
refer readers to the document titled ``Proposed Specifications for LTCH
QRP Quality Measures and Standardized Patient Assessment Data
Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The Invasive Mechanical Ventilator data element was first proposed
as a SPADE in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20107
through 20108). In that proposed rule, we stated that the proposal was
informed by input we received through a call for input published on the
CMS Measures Management System Blueprint website on data elements that
assess invasive ventilator use and weaning status that were tested in
the PAC PRD (``Ventilator--Weaning'' and ``Ventilator--Non-Weaning'').
Input submitted from August 12 to September 12, 2016 expressed support
for this data element, highlighting the importance of this information
in supporting care coordination and care transitions. Some commenters
expressed concern about the appropriateness for standardization, given
the prevalence of ventilator weaning across PAC providers; the timing
of administration; how weaning is defined; and how weaning status
relates to quality of care. These public comments guided our decision
to propose a single data element focused on current use of invasive
mechanical ventilation only, which does not attempt to capture weaning
status. A summary report for the August 12 to September 12, 2016 public
comment period titled ``SPADE August 2016 Public Comment Summary
Report'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received public comments in support of the Special Services,
Treatments, and Interventions data elements in general, and support
from one commenter on the Invasive Mechanical Ventilator data element.
However, concerns were expressed about not having recent, comprehensive
field testing of proposed data elements.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the Invasive Mechanical Ventilator data element was
included in the National Beta Test of candidate data elements conducted
by our data element contractor from November 2017 to August 2018.
Results of this test found the Invasive Mechanical Ventilator data
element to be feasible and reliable for use with PAC patients and
residents. More information about the performance of the Invasive
Mechanical Ventilator data element in the National Beta Test can be
found in the document titled ``Proposed Specifications for LTCH QRP
Quality Measures and Standardized Patient Assessment Data Elements,''
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the special
services, treatments, and interventions and the TEP supported the
assessment of the special services, treatments, and interventions
included in the National Beta Test with respect to both admission and
discharge. A summary of the September 17, 2018 TEP meeting titled
``SPADE Technical Expert Panel Summary (Third Convening)'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present results of the National Beta
Test and solicit additional comments. General input on the testing and
item development process and concerns about burden were received from
stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for invasive mechanical
ventilation, stakeholder input, and strong test results, we are
proposing that the Invasive Mechanical Ventilator data element that
assesses the use of an invasive mechanical ventilator meets the
definition of standardized patient assessment data with respect to
special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act, and to adopt the Invasive Mechanical
Ventilator data element as
[[Page 19531]]
standardized patient assessment data for use in the LTCH QRP.
Intravenous (IV) Medications (Antibiotics, Anticoagulants,
Vasoactive Medications, Other)
We are proposing that the IV Medications (Antibiotics,
Anticoagulants, Vasoactive Medications, Other) data element meets the
definition of standardized patient assessment data with respect to
special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act.
We proposed a similar set of data elements related to IV
medications in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20108
through 20109). IV medications are solutions of a specific medication
(for example, antibiotics, anticoagulants) administered directly into
the venous circulation via a syringe or intravenous catheter (tube). IV
medications are administered via intravenous push, single,
intermittent, or continuous infusion through a tube placed into the
vein. Further, IV medications are more resource intensive to administer
than oral medications, and signify a higher patient complexity (and
often higher severity of illness).
The clinical indications for each of the sub-elements of the IV
Medications data element (Antibiotics, Anticoagulants, Vasoactive
Medications, and Other) are very different. IV antibiotics are used for
severe infections when: The bioavailability of the oral form of the
medication would be inadequate to kill the pathogen; an oral form of
the medication does not exist; or the patient is unable to take the
medication by mouth. IV anticoagulants refer to anti-clotting
medications (that is, ``blood thinners''). IV anticoagulants are
commonly used for hospitalized patients who have deep venous
thrombosis, pulmonary embolism, or myocardial infarction, as well as
those undergoing interventional cardiac procedures. Vasoactive
medications refer to the IV administration of vasoactive drugs,
including vasopressors, vasodilators, and continuous medication for
pulmonary edema, which increase or decrease blood pressure or heart
rate. The indications, risks, and benefits of each of these classes of
IV medications are distinct, making it important to assess each
separately in PAC. Knowing whether or not patients are receiving IV
medication and the type of medication provided by each PAC provider
will improve quality of care.
The IV Medications (Antibiotics, Anticoagulants, Vasoactive
Medications, and Other) data element we are proposing consists of a
principal data element (IV Medications) and four response option sub-
elements: Antibiotics; Anticoagulants; Vasoactive Medications; and
Other. The Vasoactive Medications sub-element was not proposed in the
FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20108 through 20109). We
added the Vasoactive Medications sub-element to our proposal in order
to harmonize the proposed IV Mediciations element with the data
currently collected in the LCDS.
If the assessor indicates that the patient is receiving IV
medications on the principal IV Medications data element, the assessor
would then indicate which types of medications (for example,
Antibiotics, Anticoagulants, Vasoactive Medications, Other). An IV
Medications data element is currently in use on the MDS in SNFs and
there is a related data element in OASIS that collects information on
Intravenous and Infusion Therapies. The LCDS in LTCHs currently
collects data on IV Vasoactive Medications. We are proposing to modify
the existing IV Vasoactive Medications data element in the LCDS to
include additional sub-elements included in the standardized form of
the IV Medications (Antibiotics, Anticoagulation, Vasoactive
Medications, Other) data element and a principal data element for IV
Medications. For more information on the IV Medications (Antibiotics,
Anticoagulants, Vasoactive Medications, Other) data element, we refer
readers to the document titled ``Proposed Specifications for LTCH QRP
Quality Measures and Standardized Patient Assessment Data Elements,''
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
An IV Medications data element was first proposed as a SPADE in the
FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20108 through 20109). In
that proposed rule, we stated that the proposal was informed by input
we received on Vasoactive Medications through a call for input
published on the CMS Measures Management System Blueprint website.
Input submitted from August 12 to September 12, 2016 supported this
data element, with one noting the importance of this data element in
supporting care transitions. We also stated that these commenters had
criticized the need for collecting specifically Vasoactive Medications,
giving feedback that the data element was too narrowly focused. In
addition, public comment received indicated that the clinical
significance of vasoactive medications administration alone was not
high enough in PAC to merit mandated assessment, noting that related
and more useful information could be captured in an item that assessed
all IV medication use. A summary report for the August 12 to September
12, 2016 public comment period titled ``SPADE August 2016 Public
Comment Summary Report'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received public comments in support of the Special Services,
Treatments, and Interventions data elements in general; no additional
comments were received that were specific to the IV Medications data
element. However, general concerns were expressed about not having
recent, comprehensive field testing of proposed data elements.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the IV Medications data element was included in the
National Beta Test of candidate data elements conducted by our data
element contractor from November 2017 to August 2018. Results of this
test found the IV Medications data element to be feasible and reliable
for use with PAC patients and residents. More information about the
performance of the IV Medications data element in the National Beta
Test can be found in the document titled ``Proposed Specifications for
LTCH QRP Quality Measures and Standardized Patient Assessment Data
Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the special
services, treatments, and interventions and the TEP supported the
assessment of the special services, treatments, and interventions
included in the National Beta Test with respect to both admission and
discharge. A summary of the September 17, 2018 TEP meeting titled
``SPADE Technical Expert Panel Summary (Third Convening)'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-
Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-
of-
[[Page 19532]]
2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for IV medications,
stakeholder input, and strong test results, we are proposing that the
IV Medications (Antibiotics, Anticoagulation, Vasoactive Medications,
Other) data element with a principal data element and four sub-elements
meets the definition of standardized patient assessment data with
respect to special services, treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act, and to adopt the IV Medications
(Antibiotics, Anticoagulation, Vasoactive Medications, Other) data
element as standardized patient assessment data for use in the LTCH
QRP.
Transfusions
We are proposing that the Transfusions data element meets the
definition of standardized patient assessment data with respect to
special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20109 through 20110), transfusion refers to introducing blood or blood
products into the circulatory system of a person. Blood transfusions
are based on specific protocols, with multiple safety checks and
monitoring required during and after the infusion in case of adverse
events. Coordination with the provider's blood bank is necessary, as
well as documentation by clinical staff to ensure compliance with
regulatory requirements. In addition, the need for transfusions
signifies underlying patient complexity that is likely to require care
coordination and patient monitoring, and impacts planning for
transitions of care, as transfusions are not performed by all PAC
providers.
The proposed data element consists of the single Transfusions data
element. A data element on transfusion is currently in use in the MDS
in SNFs (``Transfusions'') and a data element tested in the PAC PRD
(``Blood Transfusions'') was found feasible for use in each of the four
PAC settings. For more information on the Transfusions data element, we
refer readers to the document titled ``Proposed Specifications for LTCH
QRP Quality Measures and Standardized Patient Assessment Data
Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The Transfusions data element was first proposed as a SPADE in the
FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20109 through 20110).
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received public comments in support of the Special Services,
Treatments, and Interventions data elements in general. In response to
our proposal, we received comments in support of the Transfusions data
element. A commenter supported the inclusion of the Transfusions data
element because transfusions are increasingly being performed outside
of the hospital setting and reporting transfusions as a SPADE will
contribute to higher quality, coordinated care for patients who rely on
these life-saving treatments. However, concerns were expressed about
not having recent, comprehensive field testing of proposed data
elements.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the Transfusions data element was included in the
National Beta Test of candidate data elements conducted by our data
element contractor from November 2017 to August 2018. Results of this
test found the Transfusions data element to be feasible and reliable
for use with PAC patients and residents. More information about the
performance of the Transfusions data element in the National Beta Test
can be found in the document titled ``Proposed Specifications for LTCH
QRP Quality Measures and Standardized Patient Assessment Data
Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the special
services, treatments, and interventions. Although the TEP did not
specifically discuss the Transfusions data element, the TEP supported
the assessment of the special services, treatments, and interventions
included in the National Beta Test with respect to both admission and
discharge. A summary of the September 17, 2018 TEP meeting titled
``SPADE Technical Expert Panel Summary (Third Convening)'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for transfusions,
stakeholder input, and strong test results, we are proposing that the
Transfusions data element that is currently in use in the MDS in SNFs
meets the definition of standardized patient assessment data with
respect to special services, treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act, and to adopt the Transfusion
data element as standardized patient assessment data for use in the
LTCH QRP.
[[Page 19533]]
Dialysis (Hemodialysis, Peritoneal Dialysis)
We are proposing that the Dialysis (Hemodialysis, Peritoneal
dialysis) data element meets the definition of standardized patient
assessment data with respect to special services, treatments, and
interventions under section 1899B(b)(1)(B)(iii) of the Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20110), dialysis is a treatment primarily used to provide replacement
for lost kidney function. Both forms of dialysis (hemodialysis and
peritoneal dialysis) are resource intensive, not only during the actual
dialysis process but before, during and following. Patients and
residents who need and undergo dialysis procedures are at high risk for
physiologic and hemodynamic instability from fluid shifts and
electrolyte disturbances as well as infections that can lead to sepsis.
Further, patients or residents receiving hemodialysis are often
transported to a different facility, or at a minimum, to a different
location in the same facility for treatment. Close monitoring for fluid
shifts, blood pressure abnormalities, and other adverse effects is
required prior to, during and following each dialysis session. Nursing
staff typically perform peritoneal dialysis at the bedside, and as with
hemodialysis, close monitoring is required.
The proposed data element, Dialysis (Hemodialysis, Peritoneal
dialysis) consists of the principal Dialysis data element and two
response option sub-elements: Hemodialysis; and Peritoneal dialysis. If
the assessor indicates that the patient is receiving dialysis on the
principal Dialysis data element, the assessor would then indicate which
type (Hemodialysis or Peritoneal dialysis). Dialysis data elements are
currently included on the MDS in SNFs and the LCDS in LTCHs and assess
the overall use of dialysis. We are proposing to expand the existing
Dialysis data element currently in the LCDS to include sub-elements for
Hemodialysis and Peritoneal dialysis.
As the result of public feedback described below, in this proposed
rule, we are proposing data elements that include the principal
Dialysis data element and two sub-elements (Hemodialysis and Peritoneal
dialysis). For more information on the Dialysis data elements, we refer
readers to the document titled ``Proposed Specifications for LTCH QRP
Quality Measures and Standardized Patient Assessment Data Elements,''
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The Dialysis data element was first proposed as a SPADE in the FY
2018 IPPS/LTCH PPS proposed rule (82 FR 20110). In that proposed rule,
we stated that the proposal was informed by input we received on a
singular Hemodialysis data element through a call for input published
on the CMS Measures Management System Blueprint website. Input
submitted from August 12 to September 12, 2016 supported the assessment
of hemodialysis and recommended that the data element be expanded to
include peritoneal dialysis. We also noted that several commenters had
supported the singular Hemodialysis data element, noting the relevance
of this information for sharing across the care continuum to facilitate
care coordination and care transitions, the potential for this data
element to be used to improve quality, and the feasibility for use in
PAC. In addition, we received comment that the item would be useful in
improving patient and resident transitions of care. We also noted that
several commenters had also stated that peritoneal dialysis should be
included in a standardized data element on dialysis and recommended
collecting information on peritoneal dialysis in addition to
hemodialysis. The rationale for including peritoneal dialysis from
commenters included the fact that patients and residents receiving
peritoneal dialysis will have different needs at post-acute discharge
compared to those receiving hemodialysis or not having any dialysis.
Based on these comments, the Hemodialysis data element was expanded to
include a principal Dialysis data element and two sub-elements,
Hemodialysis and Peritoneal dialysis. We are proposing the version of
the Dialysis element that includes two types of dialysis. A summary
report for the August 12 to September 12, 2016 public comment period
titled ``SPADE August 2016 Public Comment Summary Report'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received comments in support of the Special Services,
Treatments, and Interventions data elements in general. No additional
comments were received that were specific to the Dialysis data element.
However, concerns were expressed about not having recent, comprehensive
field testing of proposed data elements.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the Dialysis data element was included in the National
Beta Test of candidate data elements conducted by our data element
contractor from November 2017 to August 2018. Results of this test
found the Dialysis data element to be feasible and reliable for use
with PAC patients and residents. More information about the performance
of the Dialysis data elements in the National Beta Test can be found in
the document titled ``Proposed Specifications for LTCH QRP Quality
Measures and Standardized Patient Assessment Data Elements,'' available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the special
services, treatments, and interventions and the TEP supported the
assessment of the special services, treatments, and interventions
included in the National Beta Test with respect to both admission and
discharge. A summary of the September 17, 2018 TEP meeting titled
``SPADE Technical Expert Panel Summary (Third Convening)'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-
Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-
Initiatives/IMPACT-Act-of-2014/
[[Page 19534]]
IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for dialysis,
stakeholder input, and strong test results, we are proposing that the
Dialysis (Hemodialysis, Peritoneal dialysis) data element with a
principal data element and two sub-elements meets the definition of
standardized patient assessment data with respect to special services,
treatments, and interventions under section 1899B(b)(1)(B)(iii) of the
Act, and to adopt the Dialysis (Hemodialysis, Peritoneal dialysis) data
element as standardized patient assessment data for use in the LTCH
QRP.
Intravenous (IV) Access (Peripheral IV, Midline, Central Line)
We are proposing that the IV Access (Peripheral IV, Midline,
Central line) data element meets the definition of standardized patient
assessment data with respect to special services, treatments, and
interventions under section 1899B(b)(1)(B)(iii) of the Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20110 through 20111), patients or residents with central lines,
including those peripherally inserted or who have subcutaneous central
line ``port'' access, always require vigilant nursing care to keep
patency of the lines and ensure that such invasive lines remain free
from any potentially life-threatening events such as infection, air
embolism, or bleeding from an open lumen. Clinically complex patients
and residents are likely to be receiving medications or nutrition
intravenously. The sub-elements included in the IV Access data element
distinguish between peripheral access and different types of central
access. The rationale for distinguishing between a peripheral IV and
central IV access is that central lines confer higher risks associated
with life-threatening events such as pulmonary embolism, infection, and
bleeding.
The proposed data element, IV Access (Peripheral IV, Midline,
Central line), consists of the principal IV Access data element and
three response option sub-elements: Peripheral IV, Midline, and Central
line. The proposed IV Access data element is not currently included on
any of the PAC assessment instruments. For more information on the IV
Access (Peripheral IV, Midline, Central line) data element, we refer
readers to the document titled ``Proposed Specifications for LTCH QRP
Quality Measures and Standardized Patient Assessment Data Elements,''
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
An IV Access data element was first proposed as a SPADE in the FY
2018 IPPS/LTCH PPS proposed rule (82 FR 20110 through 20111). In that
proposed rule, we stated that the proposal was informed by input we
received on one of the PAC PRD data elements, Central Line Management,
a type of IV access, through a call for input published on the CMS
Measures Management System Blueprint website. Input submitted from
August 12 to September 12, 2016 expressed support for the assessment of
central line management and recommended that the data element be
broadened to also include other types of IV access in addition to
central lines. Several commenters supported the data element, noting
feasibility and importance for facilitating care coordination and care
transitions. However, a few commenters recommended that this data
element be broadened to include peripherally inserted central catheters
(``PICC lines'') and midline IVs. Based on public comment feedback and
in consultation with expert input, we expanded the Central Line
Management data element to include more types of IV access (that is,
peripheral IV and midline). This expanded version of IV Access is the
data element being proposed. A summary report for the August 12 to
September 12, 2016 public comment period titled ``SPADE August 2016
Public Comment Summary Report'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received public comments in support of the Special Services,
Treatments, and Interventions data elements in general. No additional
comments were received that were specific to the IV Access data
element. However, concerns were expressed about not having recent,
comprehensive field testing of proposed data elements.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the IV Access data element was included in the National
Beta Test of candidate data elements conducted by our data element
contractor from November 2017 to August 2018. Results of this test
found the IV Access data element to be feasible and reliable for use
with PAC patients and residents. More information about the performance
of the IV Access data element in the National Beta Test can be found in
the document titled ``Proposed Specifications for LTCH QRP Quality
Measures and Standardized Patient Assessment Data Elements,'' available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the special
services, treatments, and interventions and the TEP supported the
assessment of the special services, treatments, and interventions
included in the National Beta Test with respect to both admission and
discharge. A summary of the September 17, 2018 TEP meeting titled
``SPADE Technical Expert Panel Summary (Third Convening)'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present results of the National Beta
Test and solicit additional comments. General input on the testing and
item development process and concerns about burden were received from
stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for IV access,
stakeholder input, and strong test results, we are proposing that the
IV access (Peripheral IV, Midline, Central line) data element with a
principal data element and three sub-elements meets the definition of
standardized patient assessment data with respect to special services,
treatments, and interventions under section 1899B(b)(1)(B)(iii) of the
Act,
[[Page 19535]]
and to adopt the IV access (Peripheral IV, Midline, Central line) data
element as standardized patient assessment data for use in the LTCH
QRP.
Nutritional Approach: Parenteral/IV Feeding
We are proposing that the Parenteral/IV Feeding data element meets
the definition of standardized patient assessment data with respect to
special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20111 through 20112), parenteral nutrition/IV feeding refers to a
patient or resident being fed intravenously using an infusion pump,
bypassing the usual process of eating and digestion. The need for IV/
parenteral feeding indicates a clinical complexity that prevents the
patient or resident from meeting his or her nutritional needs
enterally, and is more resource intensive than other forms of
nutrition, as it often requires monitoring of blood chemistries and
maintenance of a central line. Therefore, assessing a patient's or
resident's need for parenteral feeding is important for care planning
and resource use. In addition to the risks associated with central and
peripheral intravenous access, total parenteral nutrition is associated
with significant risks such as embolism and sepsis.
The proposed data element consists of the single Parenteral/IV
Feeding data element. The proposed Parenteral/IV Feeding data element
is currently in use in the MDS in SNFs, and equivalent or related data
elements are in use in the LCDS, IRF-PAI, and OASIS. We are proposing
to replace the existing Total Parenteral Nutrition data element in the
LCDS with the proposed Parenteral/IV Feeding data element. For more
information on the Parenteral/IV Feeding data element, we refer readers
to the document titled ``Proposed Specifications for LTCH QRP Quality
Measures and Standardized Patient Assessment Data Elements,'' available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The Parenteral/IV Feeding data element was first proposed as a
SPADE in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20111 through
20112). In that proposed rule, we stated that the proposal was informed
by input we received on Total Parenteral Nutrition (an item with nearly
the same meaning as the proposed data element, but with the label used
in the PAC PRD), through a call for input published on the CMS Measures
Management System Blueprint website. Input submitted from August 12 to
September 12, 2016, supported this data element, noting its relevance
to facilitating care coordination and supporting care transitions.
After the public input period, the Total Parenteral Nutrition data
element was renamed Parenteral/IV Feeding, to be consistent with how
this data element is referred to in the MDS in SNFs. A summary report
for the August 12 to September 12, 2016 public comment period titled
``SPADE August 2016 Public Comment Summary Report'' is available at:
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received comments in support of the Special Services,
Treatments, and Interventions data elements in general. In response to
our proposal, we received public comments in support of the Parenteral/
IV Feeding data element. Several commenters supported the inclusion of
nutrition data elements and noted their importance in capturing
information on additional resources necessary to treat patients with
altered dietary needs. However, one commenter noted limitations of the
proposed data elements, such as not recording clinical rationale for
nutritional or diet needs. We also received public comments expressing
concern about not having recent, comprehensive field testing of
proposed data elements.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the Parenteral/IV Feeding data element was included in
the National Beta Test of candidate data elements conducted by our data
element contractor from November 2017 to August 2018. Results of this
test found the Parenteral/IV Feeding data element to be feasible and
reliable for use with PAC patients and residents. More information
about the performance of the Parenteral/IV Feeding data element in the
National Beta Test can be found in the document titled ``Proposed
Specifications for LTCH QRP Quality Measures and Standardized Patient
Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the special
services, treatments, and interventions and the TEP supported the
assessment of the special services, treatments, and interventions
included in the National Beta Test with respect to both admission and
discharge. A summary of the September 17, 2018 TEP meeting titled
``SPADE Technical Expert Panel Summary (Third Convening)'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for parenteral/IV
feeding, stakeholder input, and strong test results, we are proposing
that the Parenteral/IV Feeding data element meets the definition of
standardized patient assessment data with respect to special services,
treatments, and interventions under section 1899B(b)(1)(B)(iii) of the
Act, and to adopt the Parenteral/IV Feeding data element as
standardized patient assessment data for use in the LTCH QRP.
Nutritional Approach: Feeding Tube
We are proposing that the Feeding Tube data element meets the
definition of standardized patient assessment data with respect to
special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act.
[[Page 19536]]
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20112), the majority of patients admitted to acute care hospitals
experience deterioration of their nutritional status during their
hospital stay, making assessment of nutritional status and method of
feeding if unable to eat orally very important in PAC. A feeding tube
can be inserted through the nose or the skin on the abdomen to deliver
liquid nutrition into the stomach or small intestine. Feeding tubes are
resource intensive and, therefore, are important to assess for care
planning and resource use. Patients with severe malnutrition are at
higher risk for a variety of complications.\715\ In PAC settings, there
are a variety of reasons that patients and residents may not be able to
eat orally (including clinical or cognitive status).
---------------------------------------------------------------------------
\715\ Dempsey, D.T., Mullen, J.L., & Buzby, G.P. (1988). ``The
link between nutritional status and clinical outcome: can
nutritional intervention modify it?'' Am J of Clinical Nutrition,
47(2): 352-356.
---------------------------------------------------------------------------
The proposed data element consists of the single Feeding Tube data
element. The Feeding Tube data element is currently included in the MDS
for SNFs, and in the OASIS for HHAs, where it is labeled Enteral
Nutrition. A related data element, collected in the IRF-PAI for IRFs
(Tube/Parenteral Feeding), assesses use of both feeding tubes and
parenteral nutrition. For more information on the Feeding Tube data
element, we refer readers to the document titled ``Proposed
Specifications for LTCH QRP Quality Measures and Standardized Patient
Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The Feeding Tube data element was first proposed as a SPADE in the
FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20112). In that proposed
rule, we stated that the proposal was informed by input we received
through a call for input published on the CMS Measures Management
System Blueprint website. Input submitted from August 12 to September
12, 2016 on an Enteral Nutrition data element (which is the same as the
data element we are proposing in this proposed rule, but is used in the
OASIS under a different name) supported the data element, noting the
importance of assessing enteral nutrition status for facilitating care
coordination and care transitions. After the public comment period, the
Enteral Nutrition data element used in public comment was renamed
``Feeding Tube'', indicating the presence of an assistive device. A
summary report for the August 12 to September 12, 2016 public comment
period titled ``SPADE August 2016 Public Comment Summary Report'' is
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received public comments in support of the Special Services,
Treatments, and Interventions data elements in general. In response to
our proposal, we received public comments in support of the Feeding
Tube data element. Several commenters supported the inclusion of
nutrition data elements, noting their importance when capturing dietary
needs. However, we also received recommendations to increase the
specificity of the data element by using more clinical terminology and
assessing clinical rationale for nutritional or dietary needs as well
as concerns about not having recent, comprehensive field testing of
proposed data elements.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the Feeding Tube data element was included in the
National Beta Test of candidate data elements conducted by our data
element contractor from November 2017 to August 2018. Results of this
test found the Feeding Tube data element to be feasible and reliable
for use with PAC patients and residents. More information about the
performance of the Feeding Tube data element in the National Beta Test
can be found in the document titled ``Proposed Specifications for LTCH
QRP Quality Measures and Standardized Patient Assessment Data
Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the special
services, treatments, and interventions and the TEP supported the
assessment of the special services, treatments, and interventions
included in the National Beta Test with respect to both admission and
discharge. A summary of the September 17, 2018 TEP meeting titled
``SPADE Technical Expert Panel Summary (Third Convening)'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for feeding tubes,
stakeholder input, and strong test results, we are proposing that the
Feeding Tube data element meets the definition of standardized patient
assessment data with respect to special services, treatments, and
interventions under section 1899B(b)(1)(B)(iii) of the Act, and to
adopt the Feeding Tube data element as standardized patient assessment
data for use in the LTCH QRP.
Nutritional Approach: Mechanically Altered Diet
We are proposing that the Mechanically Altered Diet data element
meets the definition of standardized patient assessment data with
respect to special services, treatments, and interventions under
section 1899B(b)(1)(B)(iii) of the Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20112 through 20113), the Mechanically Altered Diet data element refers
to food that has been altered to make it easier for the patient or
resident to chew and swallow, and this type of diet is used for
patients and residents who have difficulty performing these functions.
Patients with severe malnutrition are at higher risk for a variety of
complications.\716\
---------------------------------------------------------------------------
\716\ Dempsey, D.T., Mullen, J.L., & Buzby, G.P. (1988). ``The
link between nutritional status and clinical outcome: can
nutritional intervention modify it?'' Am J of Clinical Nutrition,
47(2): 352-356.
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[[Page 19537]]
In PAC settings, there are a variety of reasons that patients and
residents may have impairments related to oral feedings, including
clinical or cognitive status. The provision of a mechanically altered
diet may be resource intensive, and can signal difficulties associated
with swallowing/eating safety, including dysphagia. In other cases, it
signifies the type of altered food source, such as ground or puree,
that will enable the safe and thorough ingestion of nutritional
substances and ensure safe and adequate delivery of nourishment to the
patient. Often, patients on mechanically altered diets also require
additional nursing supports such as individual feeding, or direct
observation, to ensure the safe consumption of the food product.
Assessing whether a patient or resident requires a mechanically altered
diet is therefore important for care planning and resource
identification.
The proposed data element consists of the single Mechanically
Altered Diet data element. The proposed data element for a mechanically
altered diet is currently included on the MDS for SNFs. A related data
element for modified food consistency/supervision is currently included
on the IRF-PAI for IRFs. Another related data element is included in
the OASIS for HHAs that collects information about independent eating
that requires ``a liquid, pureed or ground meat diet.'' For more
information on the Mechanically Altered Diet data element, we refer
readers to the document titled ``Proposed Specifications for LTCH QRP
Quality Measures and Standardized Patient Assessment Data Elements,''
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The Mechanically Altered Diet data element was first proposed as a
SPADE in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20112 through
20113).
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received public comments in support of the Special Services,
Treatments, and Interventions data elements in general. In response to
our proposal, we received comments in support of the Mechanically
Altered Diet data element. Several commenters supported the inclusion
of nutrition data elements noting their importance in capturing
information on additional resources necessary to treat patients with
altered dietary needs. However, one commenter noted limitations of the
proposed data elements, such as not recording clinical rationale for
nutritional or diet needs. We received further concerns regarding not
having recent, comprehensive field testing of proposed data elements.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the Mechanically Altered Diet data element was included
in the National Beta Test of candidate data elements conducted by our
data element contractor from November 2017 to August 2018. Results of
this test found the Mechanically Altered Diet data element to be
feasible and reliable for use with PAC patients and residents. More
information about the performance of the Mechanically Altered Diet data
element in the National Beta Test can be found in the document titled
``Proposed Specifications for LTCH QRP Quality Measures and
Standardized Patient Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the special
services, treatments, and interventions and the TEP supported the
assessment of the special services, treatments, and interventions
included in the National Beta Test with respect to both admission and
discharge. A summary of the September 17, 2018 TEP meeting titled
``SPADE Technical Expert Panel Summary (Third Convening)'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for mechanically
altered diet, stakeholder input, and strong test results, we are
proposing that the Mechanically Altered Diet data element meets the
definition of standardized patient assessment data with respect to
special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act, and to adopt the Mechanically Altered
Diet data element as standardized patient assessment data for use in
the LTCH QRP.
Nutritional Approach: Therapeutic Diet
We are proposing that the Therapeutic Diet data element meets the
definition of standardized patient assessment data with respect to
special services, treatments, and interventions under section
1899B(b)(1)(B)(iii) of the Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20113), a therapeutic diet refers to meals planned to increase,
decrease, or eliminate specific foods or nutrients in a patient or
resident's diet, such as a low-salt diet, for the purpose of treating a
medical condition. The use of therapeutic diets among patients in PAC
provides insight on the clinical complexity of these patients and their
multiple comorbidities. Therapeutic diets are less resource intensive
from the bedside nursing perspective, but do signify one or more
underlying clinical conditions that preclude the patient from eating a
regular diet. The communication among PAC providers about whether a
patient is receiving a particular therapeutic diet is critical to
ensure safe transitions of care.
The proposed data element consists of the single Therapeutic Diet
data element. The Therapeutic Diet data element is currently in use in
the MDS in SNFs. For more information on the Therapeutic Diet data
element, we refer readers to the document titled ``Proposed
Specifications for LTCH QRP Quality Measures and Standardized Patient
Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-
Quality-Initiatives/IMPACT-Act-of-
[[Page 19538]]
2014/IMPACT-Act-Downloads-and-Videos.html.
The Therapeutic Diet data element was first proposed as a SPADE in
the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20113).
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received public comments in support of the Special Services,
Treatments, and Interventions data elements in general. Several
commenters supported the inclusion of nutrition data elements noting
their importance in capturing information on additional resources
necessary to treat patients with altered dietary needs. However, one
commenter noted limitations of the proposed data elements, such as not
recording clinical rationale for nutritional or diet needs. Other
commenters recommended the addition of specific terminology to these
data elements, as well as aligning the definition of Therapeutic Diet
with the Academy of Nutrition and Dietetics' definition. One commenter
suggested use of the term ``medically altered diet'' instead of
``therapeutic diet.'' We also received comments related to concerns
about not having recent, comprehensive field testing of proposed data
elements.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the Therapeutic Diet data element was included in the
National Beta Test of candidate data elements conducted by our data
element contractor from November 2017 to August 2018. Results of this
test found the Therapeutic Diet data element to be feasible and
reliable for use with PAC patients and residents. More information
about the performance of the Therapeutic Diet data element in the
National Beta Test can be found in the document titled ``Proposed
Specifications for LTCH QRP Quality Measures and Standardized Patient
Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on
September 17, 2018 for the purpose of soliciting input on the special
services, treatments, and interventions and the TEP supported the
assessment of the special services, treatments, and interventions
included in the National Beta Test with respect to both admission and
discharge. A summary of the September 17, 2018 TEP meeting titled
``SPADE Technical Expert Panel Summary (Third Convening)'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. A summary of the public input received from the November 27, 2018
stakeholder meeting titled ``Input on Standardized Patient Assessment
Data Elements (SPADEs) Received After November 27, 2018 Stakeholder
Meeting'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for therapeutic diet,
stakeholder input, and strong test results, we are proposing that the
Therapeutic Diet data element meets the definition of standardized
patient assessment data with respect to special services, treatments,
and interventions under section 1899B(b)(1)(B)(iii) of the Act, and to
adopt the Therapeutic Diet data element as standardized patient
assessment data for use in the LTCH QRP.
High-Risk Drug Classes: Use and Indication
We are proposing that the High-Risk Drug Classes: Use and
Indication data element meets the definition of standardized patient
assessment data with respect to special services, treatments, and
interventions under section 1899B(b)(1)(B)(iii) of the Act.
Most patients receiving PAC services depend on short- and long-term
medications to manage their medical conditions. However, as a
treatment, medications are not without risk; medications are in fact a
leading cause of adverse events. A study by the U.S. Department of
Health and Human Services found that 31 percent of adverse events that
occurred in 2008 among hospitalized Medicare beneficiaries were related
to medication.\717\ Moreover, changes in a patient's condition,
medications, and transitions between care settings put patients at risk
of medication errors and adverse drug events (ADEs). ADEs may be caused
by medication errors such as drug omissions, errors in dosage, and
errors in dosing frequency.\718\
---------------------------------------------------------------------------
\717\ U.S. Department of Health and Human Services. Office of
Inspector General. Daniel R. Levinson Adverse Events in Hospitals:
National Incidence Among Medicare Beneficiaries. OEI-06-09-00090.
November 2010. Available at: https://www.oig.hhs.gov/oei/reports/oei-06-09-00090.pdf.
\718\ Boockvar KS, Liu S, Goldstein N, Nebeker J, Siu A, Fried
T. Prescribing discrepancies likely to cause adverse drug events
after patient transfer. Qual Saf Health Care. 2009;18(1):32-6.
---------------------------------------------------------------------------
ADEs are known to occur across different types of healthcare
settings. For example, the incidence of ADEs in the outpatient setting
has been estimated at 1.15 ADEs per 100 person-months,\719\ while the
rate of ADEs in the long-term care setting is approximately 9.80 ADEs
per 100 resident-months.\720\ In the hospital setting, the incidence
has been estimated at 15 ADEs per 100 admissions.\721\ In addition,
approximately half of all hospital-related medication errors and 20
percent of ADEs occur during transitions within, admission to, transfer
to, or discharge from a hospital.722 723 724 ADEs are more
common among older adults, who make up most patients receiving PAC
services. The rate of emergency department visits for ADEs is three
times higher among adults 65 years of age and older compared to that
among those younger than age 65.\725\
---------------------------------------------------------------------------
\719\ Gandhi TK, Seger AC, Overhage JM, et al. Outpatient
adverse drug events identified by screening electronic health
records. J Patient Saf 2010;6:91-6.doi:10.1097/PTS.0b013e3181dcae06.
\720\ Gurwitz JH, Field TS, Judge J, Rochon P, Harrold LR,
Cadoret C, et al. The incidence of adverse drug events in two large
academic long-term care facilities. Am J Med. 2005; 118(3):2518. Epub 2005/03/05. Available at: https://doi.org/10.1016/j.amjmed.2004.09.018 PMID: 15745723.
\721\ Hug BL, Witkowski DJ, Sox CM, Keohane CA, Seger DL, Yoon
C, Matheny ME, Bates DW. Occurrence of adverse, often preventable,
events in community hospitals involving nephrotoxic drugs or those
excreted by the kidney. Kidney Int. 2009; 76:1192-1198. [PubMed:
19759525].
\722\ Barnsteiner JH. Medication reconciliation: transfer of
medication information across settings-keeping it free from error. J
Infus Nurs. 2005;28(2 Suppl):31-36.
\723\ Rozich J, Roger, R. Medication safety: one organization's
approach to the challenge. Journal of Clinical Outcomes Management.
2001(8):27-34.
\724\ Gleason KM, Groszek JM, Sullivan C, Rooney D, Barnard C,
Noskin GA. Reconciliation of discrepancies in medication histories
and admission orders of newly hospitalized patients. Am J Health
Syst Pharm. 2004;61(16):1689-1695.
\725\ Shehab N, Lovegrove MC, Geller AI, Rose KO, Weidle NJ,
Budnitz DS. US emergency department visits for outpatient adverse
drug events, 2013-2014. JAMA. doi: 10.1001/jama.2016.16201.
---------------------------------------------------------------------------
Understanding the types of medication a patient is taking and the
[[Page 19539]]
reason for its use are key facets of a patient's treatment with respect
to medication. Some classes of drugs are associated with more risk than
others.\726\ We are proposing one High-Risk Drug Class data element
with six medication classes as sub-elements. The six medication classes
we are proposing as response options for the High-Risk Drug Classes:
Use and Indication data element are: Anticoagulants; antiplatelets;
hypoglycemics (including insulin); opioids; antipsychotics; and
antibiotics. These drug classes are high-risk due to the adverse
effects that may result from use. In particular, bleeding risk is
associated with anticoagulants and antiplatelets; 727 728
fluid retention, heart failure, and lactic acidosis are associated with
hypoglycemics; \729\ misuse is associated with opioids; \730\ fractures
and strokes are associated with antipsychotics; 731 732 and
various adverse events such as central nervous systems effects and
gastrointestinal intolerance are associated with antimicrobials,\733\
the larger category of medications that include antibiotics. Moreover,
some medications in five of the six drug classes included in this data
element are included in the 2019 Updated Beers Criteria[supreg] list as
potentially inappropriate medications for use in older adults.\734\
Finally, although a complete medication list should record several
important attributes of each medication (for example, dosage, route,
stop date), recording an indication for the drug is of crucial
importance.\735\
---------------------------------------------------------------------------
\726\ Ibid.
\727\ Shoeb M, Fang MC. Assessing bleeding risk in patients
taking anticoagulants. J Thromb Thrombolysis. 2013;35(3):312-319.
doi: 10.1007/s11239-013-0899-7.
\728\ Melkonian M, Jarzebowski W, Pautas E. Bleeding risk of
antiplatelet drugs compared with oral anticoagulants in older
patients with atrial fibrillation: a systematic review and
meta[hyphen]analysis. J Thromb Haemost. 2017;15:1500-1510. DOI:
10.1111/jth.13697.
\729\ Hamnvik OP, McMahon GT. Balancing Risk and Benefit with
Oral Hypoglycemic Drugs. The Mount Sinai journal of medicine, New
York. 2009; 76:234-243.
\730\ Naples JG, Gellad WF, Hanlon JT. The Role of Opioid
Analgesics in Geriatric Pain Management. Clin Geriatr Med.
2016;32(4):725-735.
\731\ Rigler SK, Shireman TI, Cook-Wiens GJ, Ellerbeck EF,
Whittle JC, Mehr DR, Mahnken JD. Fracture risk in nursing home
residents initiating antipsychotic medications. J Am Geriatr Soc.
2013; 61(5):715-722. [PubMed: 23590366].
\732\ Wang S, Linkletter C, Dore D et al. Age, antipsychotics,
and the risk of ischemic stroke in the Veterans Health
Administration. Stroke 2012;43:28-31. doi:10.1161/
STROKEAHA.111.617191.
\733\ Faulkner CM, Cox HL, Williamson JC. Unique aspects of
antimicrobial use in older adults. Clin Infect Dis. 2005;40(7):997-
1004.
\734\ American Geriatrics Society 2015 Beers Criteria Update
Expert Panel. American Geriatrics Society. Updated Beers Criteria
for Potentially Inappropriate Medication Use in Older Adults. J Am
Geriatr Soc 2015; 63:2227-2246.
\735\ Li Y, Salmasian H, Harpaz R, Chase H, Friedman C.
Determining the reasons for medication prescriptions in the EHR
using knowledge and natural language processing. AMIA Annu Symp
Proc. 2011;2011:768-76.
---------------------------------------------------------------------------
The High-Risk Drug Classes: Use and Indication data element
requires an assessor to record whether or not a patient is taking any
medications within six drug classes. The six response options for this
data element are high-risk drug classes with particular relevance to
PAC patients and residents, as identified by our data element
contractor. The six data response options are Anticoagulants,
Antiplatelets, Hypoglycemics, Opioids, Antipsychotics, and Antibiotics.
For each drug class, the assessor is asked to indicate if the patient
is taking any medications within the class, and, for drug classes in
which medications were being taken, whether indications for all drugs
in the class are noted in the medical record. For example, for the
response option Anticoagulants, if the assessor indicates that the
patient is taking anticoagulant medication, the assessor would then
indicate if an indication is recorded in the medication record for the
anticoagulant(s).
The High-Risk Drug Classes: Use and Indication data element that is
being proposed as a SPADE was developed as part of a larger set of data
elements to assess medication reconciliation, the process of obtaining
a patient's multiple medication lists and reconciling any
discrepancies. For more information on the High-Risk Drug Classes: Use
and Indication data element, we refer readers to the document titled
``Proposed Specifications for LTCH QRP Quality Measures and
Standardized Patient Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We sought public input on the relevance of conducting assessments
on medication reconciliation and specifically on the proposed High-Risk
Drug Classes: Use and Indication data element. Our data element
contractor presented data elements related to medication reconciliation
to the TEP convened on April 6 and 7, 2016. The TEP supported a focus
on high-risk drugs, because of higher potential for harm to patients
and residents, and were in favor of a data element to capture whether
or not indications for medications were recorded in the medical record.
A summary of the April 6 and 7, 2016 TEP meeting titled ``SPADE
Technical Expert Panel Summary (First Convening)'' is available at:
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html. Medication reconciliation data
elements were also discussed at a second TEP meeting on January 5 and
6, 2017, convened by our data element contractor. At this meeting, the
TEP agreed about the importance of evaluating the medication
reconciliation process, but disagreed about how this could be
accomplished through standardized assessment. The TEP also disagreed
about the usability and appropriateness of using the Beers Criteria to
identify high-risk medications.\736\ A summary of the January 5 and 6,
2017 TEP meeting titled ``SPADE Technical Expert Panel Summary (Second
Convening)'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
---------------------------------------------------------------------------
\736\ American Geriatrics Society 2015 Beers Criteria Update
Expert Panel. American Geriatrics Society. Updated Beers Criteria
for Potentially Inappropriate Medication Use in Older Adults. J Am
Geriatr Soc 2015; 63:2227-2246.
---------------------------------------------------------------------------
We also solicited public input on data elements related to
medication reconciliation during a public input period from April 26 to
June 26, 2017. Several commenters expressed support for the medication
reconciliation data elements that were put on display, noting the
importance of medication reconciliation in preventing medication errors
and stated that the items seemed feasible and clinically useful. A few
commenters were critical of the choice of 10 drug classes posted during
that comment period, arguing that ADEs are not limited to high-risk
drugs, and raised issues related to training assessors to correctly
complete a valid assessment of medication reconciliation. A summary
report for the April 26 to June 26, 2017 public comment period titled
``SPADE May-June 2017 Public Comment Summary Report'' is available at:
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The High-Risk Drug Classes: Use and Indication data element was
included in the National Beta Test of candidate data elements conducted
by our data element contractor from November 2017 to
[[Page 19540]]
August 2018. Results of this test found the High-Risk Drug Classes: Use
and Indication data element to be feasible and reliable for use with
PAC patients and residents. More information about the performance of
the High-Risk Drug Classes: Use and Indication data element in the
National Beta Test can be found in the document titled ``Proposed
Specifications for LTCH QRP Quality Measures and Standardized Patient
Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In, addition, our contractor convened a TEP on September 17, 2018
for the purpose of soliciting input on the standardized patient
assessment data elements. The TEP acknowledged the challenges of
assessing medication safety, but was supportive of some of the data
elements focused on medication reconciliation that were tested in the
National Beta Test. The TEP was especially supportive of the focus on
the six high-risk drug classes and using these classes to assess
whether the indication for a drug is recorded. A summary of the
September 17, 2018 TEP meeting titled ``SPADE Technical Expert Panel
Summary (Third Convening)'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts. These
activities provided updates on the field-testing work and solicited
feedback on data elements considered for standardization, including the
High-Risk Drug Classes: Use and Indication data element. One
stakeholder group was critical of the six drug classes included as
response options in the High-Risk Drug Classes: Use and Indication data
element, noting that potentially risky medications (for example, muscle
relaxants) are not included in this list; that there may be important
differences between drugs within classes (for example, more recent
versus older style antidepressants); and that drug allergy information
is not captured. Finally, on November 27, 2018, our data element
contractor hosted a public meeting of stakeholders to present the
results of the National Beta Test and solicit additional comments.
General input on the testing and item development process and concerns
about burden were received from stakeholders during this meeting and
via email through February 1, 2019. In addition, one commenter
questioned whether the time to complete the High-Risk Drug Classes: Use
and Indication data element would differ across settings. A summary of
the public input received from the November 27, 2018 stakeholder
meeting titled ``Input on Standardized Patient Assessment Data Elements
(SPADEs) Received After November 27, 2018 Stakeholder Meeting'' is
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for the use and having
indications recorded for high-risk drugs, stakeholder input, and strong
test results, we are proposing that the High-Risk Drug Classes: Use and
Indication data element meets the definition of standardized patient
assessment data with respect to special services, treatments, and
interventions under section 1899B(b)(1)(B)(iii) of the Act, and to
adopt the High-Risk Drug Classes: Use and Indication data element as
standardized patient assessment data for use in the LTCH QRP.
d. Medical Condition and Comorbidity Data
Assessing medical conditions and comorbidities is critically
important for care planning and safety for patients and residents
receiving PAC services, and the standardized assessment of selected
medical conditions and comorbidities across PAC providers is important
for managing care transitions and understanding medical complexity.
Below we discuss our proposals for data elements related to the
medical condition of pain as standardized patient assessment data.
Appropriate pain management begins with a standardized assessment, and
thereafter establishing and implementing an overall plan of care that
is person-centered, multi-modal, and includes the treatment team and
the patient. Assessing and documenting the effect of pain on sleep,
participation in therapy, and other activities may provide information
on undiagnosed conditions and comorbidities and the level of care
required, and do so more objectively than subjective numerical scores.
With that, we assess that taken separately and together, these proposed
data elements are essential for care planning, consistency across
transitions of care, and identifying medical complexities including
undiagnosed conditions. We also conclude that it is the standard of
care to always consider the risks and benefits associated with a
personalized care plan, including the risks of any pharmacological
therapy, especially opioids.\737\ We also conclude that in addition to
assessing and appropriately treating pain through the optimum mix of
pharmacologic, non-pharmacologic, and alternative therapies, while
being cognizant of current prescribing guidelines, clinicians in
partnership with patients are best able to mitigate factors that
contribute to the current opioid crisis.738 739 740
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\737\ Department of Health and Human Services: Pain Management
Best Practices Inter-Agency Task Force. Draft Report on Pain
Management Best Practices: Updates, Gaps, Inconsistencies, and
Recommendations. Accessed April 1, 2019. https://www.hhs.gov/sites/default/files/final-pmtf-draft-report-on-pain-management%20-best-practices-2018-12-12-html-ready-clean.pdf.
\738\ Department of Health and Human Services: Pain Management
Best Practices Inter-Agency Task Force. Draft Report on Pain
Management Best Practices: Updates, Gaps, Inconsistencies, and
Recommendations. Accessed April 1, 2019. https://www.hhs.gov/sites/default/files/final-pmtf-draft-report-on-pain-management%20-best-practices-2018-12-12-html-ready-clean.pdf.
\739\ Fishman SM, Carr DB, Hogans B, et al. Scope and Nature of
Pain- and Analgesia-Related Content of the United States Medical
Licensing Examination (USMLE). Pain Med Malden Mass. 2018;19(3):449-
459. doi:10.1093/pm/pnx336.
\740\ Fishman SM, Young HM, Lucas Arwood E, et al. Core
competencies for pain management: results of an interprofessional
consensus summit. Pain Med Malden Mass. 2013;14(7):971-981.
doi:10.1111/pme.12107.
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In alignment with our Meaningful Measures Initiative, accurate
assessment of medical conditions and comorbidities of patients and
residents in PAC is expected to make care safer by reducing harm caused
in the delivery of care; promote effective prevention and treatment of
chronic disease; strengthen person and family engagement as partners in
their care; and promote effective communication and coordination of
care. The SPADEs will enable or support clinical decision-making and
early clinical intervention; person-centered, high quality care
through: Facilitating better care continuity and coordination; better
data exchange and interoperability between settings; and longitudinal
outcome analysis. Therefore, reliable data elements assessing medical
conditions and comorbidities are needed in order to initiate a
management program that can optimize a patient or resident's prognosis
and reduce the possibility of adverse events.
[[Page 19541]]
We are inviting comment that apply specifically to the standardized
patient assessment data for the category of medical conditions and
comorbidities, specifically on:
Pain Interference (Pain Effect on Sleep, Pain Interference
With Therapy Activities, and Pain Interference With Day-to-Day
Activities)
In acknowledgement of the opioid crisis, we specifically are
seeking comment on whether or not we should add these pain items in
light of those concerns. Commenters should address to what extent the
collection of the SPADES described below through patient queries might
encourage providers to prescribe opioids.
We are proposing that a set of three data elements on the topic of
Pain Interference (Pain Effect on Sleep, Pain Interference with Therapy
Activities, and Pain Interference with Day-to-Day Activities) meet the
definition of standardized patient assessment data with respect to
medical condition and comorbidity data under section 1899B(b)(1)(B)(iv)
of the Act.
The practice of pain management began to undergo significant
changes in the 1990s because the inadequate, non-standardized, non-
evidence-based assessment and treatment of pain became a public health
issue.\741\ In pain management, a critical part of providing
comprehensive care is performance of a thorough initial evaluation,
including assessment of both the medical and any biopsychosocial
factors causing or contributing to the pain, with a treatment plan to
address the causes of pain and to manage pain that persists over
time.\742\ Quality pain management, based on current guidelines and
evidence-based practices, can minimize unnecessary opioid prescribing
both by offering alternatives or supplemental treatment to opioids and
by clearly stating when they may be appropriate, and how to utilize
risk-benefit analysis for opioid and non-opioid treatment
modalities.\743\
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\741\ Institute of Medicine. Relieving Pain in America: A
Blueprint for Transforming Prevention, Care, Education, and
Research. Washington (DC): National Academies Press (US); 2011.
http://www.ncbi.nlm.nih.gov/books/NBK91497/.
\742\ Department of Health and Human Services: Pain Management
Best Practices Inter-Agency Task Force. Draft Report on Pain
Management Best Practices: Updates, Gaps, Inconsistencies, and
Recommendations. Accessed April 1, 2019. https://www.hhs.gov/sites/default/files/final-pmtf-draft-report-on-pain-management%20-best-practices-2018-12-12-html-ready-clean.pdf.
\743\ National Academies. Pain Management and the Opioid
Epidemic: Balancing Societal and Individual Benefits and Risks of
Prescription Opioid Use. Washington DC: National Academies of
Sciences, Engineering, and Medicine.; 2017.
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Pain is not a surprising symptom in PAC patients and residents,
where healing, recovery, and rehabilitation often require regaining
mobility and other functions after an acute event. Standardized
assessment of pain that interferes with function is an important first
step towards appropriate pain management in PAC settings. The National
Pain Strategy called for refined assessment items on the topic of pain,
and describes the need for these improved measures to be implemented in
PAC assessments.\744\ Further, the focus on pain interference, as
opposed to pain intensity or pain frequency, was supported by the TEP
convened by our data element contractor as an appropriate and
actionable metric for assessing pain. A summary of the September 17,
2018 TEP meeting titled ``SPADE Technical Expert Panel Summary (Third
Convening)'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
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\744\ National Pain Strategy: A Comprehensive Population-Health
Level Strategy for Pain. Available at: https://iprcc.nih.gov/sites/default/files/HHSNational_Pain_Strategy_508C.pdf.
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We appreciate the important concerns related to the misuse and
overuse of opioids in the treatment of pain and to that end we note
that in this proposed rule we have also proposed a SPADE that assesses
for the use of, as well as importantly the indication for that use of,
high risk drugs, including opioids. Further, in the FY 2017 IPPS/LTCH
PPS final rule (81 FR 57193), we adopted the Drug Regimen Review
Conducted With Follow-Up for Identified Issues-Post Acute Care (PAC)
Long-Term Care Hospital (LTCH) Quality Reporting Program (QRP) measure
which assesses whether PAC providers were responsive to potential or
actual clinically significant medication issue(s), which includes
issues associated with use and misuse of opioids for pain management,
when such issues were identified.
We also note that the proposed SPADE related to pain assessment are
not associated with any particular approach to management. Since the
use of opioids is associated with serious complications, particularly
in the elderly,745 746 747 an array of successful non-
pharmacologic and non-opioid approaches to pain management may be
considered. PAC providers have historically used a range of pain
management strategies, including non-steroidal anti-inflammatory drugs,
ice, transcutaneous electrical nerve stimulation (TENS) therapy,
supportive devices, acupuncture, and the like. In addition, non-
pharmacological interventions for pain management include, but are not
limited to, biofeedback, application of heat/cold, massage, physical
therapy, nerve block, stretching and strengthening exercises,
chiropractic, electrical stimulation, radiotherapy, and
ultrasound.748 749 750
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\745\ Chau, D.L., Walker, V., Pai, L., & Cho, L.M. (2008).
Opiates and elderly: use and side effects. Clinical interventions in
aging, 3(2), 273-8.
\746\ Fine, P.G. (2009). Chronic Pain Management in Older
Adults: Special Considerations. Journal of Pain and Symptom
Management, 38(2): S4-S14.
\747\ Solomon, D.H., Rassen, J.A., Glynn, R.J., Garneau, K.,
Levin, R., Lee, J., & Schneeweiss, S.. (2010). Archives Internal
Medicine, 170(22):1979-1986.
\748\ Byrd L. Managing chronic pain in older adults: a long-term
care perspective. Annals of Long-Term Care: Clinical Care and Aging.
2013;21(12):34-40.
\749\ Kligler, B., Bair, M.J., Banerjea, R. et al. (2018).
Clinical Policy Recommendations from the VHA State-of-the-Art
Conference on Non-Pharmacological Approaches to Chronic
Musculoskeletal Pain. Journal of General Internal Medicine, 33(Suppl
1): 16. https://doi.org/10.1007/s11606-018-4323-z.
\750\ Chou, R., Deyo, R., Friedly, J., et al. (2017).
Nonpharmacologic Therapies for Low Back Pain: A Systematic Review
for an American College of Physicians Clinical Practice Guideline.
Annals of Internal Medicine, 166(7):493-505.
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We believe that standardized assessment of pain interference will
support PAC clinicians in applying best-practices in pain management
for chronic and acute pain, consistent with current clinical
guidelines. For example, the standardized assessment of both opioids
and pain interference would support providers in successfully tapering
patients/residents who arrive in the PAC setting with long-term opioid
use off of opioids onto non-pharmacologic treatments and non-opioid
medications, as recommended by the Society for Post-Acute and Long-Term
Care Medicine,\751\ and consistent with HHS' 5-Point Strategy To Combat
the Opioid Crisis \752\ which includes ``Better Pain Management.''
---------------------------------------------------------------------------
\751\ Society for Post-Acute and Long-Term Care Medicine (AMDA).
(2018). Opioids in Nursing Homes: Position Statement. Available at:
https://paltc.org/opioids%20in%20nursing%20homes.
\752\ https://www.hhs.gov/opioids/about-the-epidemic/hhs-response/index.html.
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The Pain Interference data element set consists of three data
elements: Pain Effect on Sleep, Pain Interference with Therapy
Activities, and Pain Interference with Day-to-Day Activities. Pain
Effect on Sleep assesses the frequency with which pain effects a
patient's sleep. Pain Interference with Therapy Activities assesses the
frequency with which pain interferes with a patient's ability to
participate in therapies. Pain Interference with Day-to-Day Activities
assesses the extent to
[[Page 19542]]
which pain interferes with a patient's ability to participate in day-
to-day activities excluding therapy.
A similar data element on the effect of pain on activities is
currently included in the OASIS. A similar data element on the effect
on sleep is currently included in the MDS instrument. For more
information on the Pain Interference data elements, we refer readers to
the document titled ``Proposed Specifications for LTCH QRP Quality
Measures and Standardized Patient Assessment Data Elements,'' available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We sought public input on the relevance of conducting assessments
on pain and specifically on the larger set of Pain Interview data
elements included in the National Beta Test. The proposed data elements
were supported by comments from the TEP meeting held by our data
element contractor on April 7 to 8, 2016. The TEP affirmed the
feasibility and clinical utility of pain as a concept in a standardized
assessment. The TEP agreed that data elements on pain interference with
ability to participate in therapies versus other activities should be
addressed. Further, during a more recent convening of the same TEP on
September 17, 2018, the TEP supported the interview-based pain data
elements included in the National Beta Test. The TEP members were
particularly supportive of the items that focused on how pain
interferes with activities (that is, Pain Interference data elements),
because understanding the extent to which pain interferes with function
would enable clinicians to determine the need for appropriate pain
treatment. A summary of the September 17, 2018 TEP meeting titled
``SPADE Technical Expert Panel Summary (Third Convening)'' is available
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We held a public input period in 2016 to solicit feedback on the
standardization of pain and several other items that were under
development in prior efforts. From the prior public comment period, we
included several pain data elements (Pain Effect on Sleep; Pain
Interference--Therapy Activities; Pain Interference--Other Activities)
in a second call for public input, open from April 26 to June 26, 2017.
The items we sought comment on were modified from all stakeholder and
test efforts. Commenters provided general comments about pain
assessment in general in addition to feedback on the specific pain
items. A few commenters shared their support for assessing pain, the
potential for pain assessment to improve the quality of care, and for
the validity and reliability of the data elements. Commenters affirmed
that the item of pain and the effect on sleep would be suitable for PAC
settings. Commenters' main concerns included redundancy with existing
data elements, feasibility and utility for cross-setting use, and the
applicability of interview-based items to patients and residents with
cognitive or communication impairments, and deficits. A summary report
for the April 26 to June 26, 2017 public comment period titled ``SPADE
May-June 2017 Public Comment Summary Report'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The Pain Interference data elements were included in the National
Beta Test of candidate data elements conducted by our data element
contractor from November 2017 to August 2018. Results of this test
found the Pain Interference data elements to be feasible and reliable
for use with PAC patients and residents. More information about the
performance of the Pain Interference data elements in the National Beta
Test can be found in the document titled ``Proposed Specifications for
LTCH QRP Quality Measures and Standardized Patient Assessment Data
Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. In addition, one commenter expressed strong support for the Pain
data elements and was encouraged by the fact that this portion of the
assessment goes beyond merely measuring the presence of pain. A summary
of the public input received from the November 27, 2018 stakeholder
meeting titled ``Input on Standardized Patient Assessment Data Elements
(SPADEs) Received After November 27, 2018 Stakeholder Meeting'' is
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for the effect of pain
on function, stakeholder input, and strong test results, we are
proposing that the three data elements (Pain Effect on Sleep, Pain
Interference with Therapy Activities, and Pain Interference with Day-
to-Day Activities) that comprise the set of Pain Interference data
elements meet the definition of standardized patient assessment data
with respect to medical conditions and comorbidities under section
1899B(b)(1)(B)(iv) of the Act, and to adopt the Pain Interference data
elements as standardized patient assessment data for use in the LTCH
QRP.
e. Impairment Data
Hearing and vision impairments are conditions that, if unaddressed,
affect activities of daily living, communication, physical functioning,
rehabilitation outcomes, and overall quality of life. Sensory
limitations can lead to confusion in new settings, increase isolation,
contribute to mood disorders, and impede accurate assessment of other
medical conditions. Failure to appropriately assess, accommodate, and
treat these conditions increases the likelihood that patients will
require more intensive and prolonged treatment. Onset of these
conditions can be gradual, so individualized assessment with accurate
screening tools and follow-up evaluations are essential to determining
which patients need hearing- or vision-specific medical attention or
assistive devices and accommodations, including auxiliary aids and/or
services, and to ensure that person-directed care plans are developed
to accommodate a patient's or resident's needs. Accurate diagnosis and
management of hearing or vision impairment would likely improve
rehabilitation outcomes and care transitions, including transition from
institutional-based care to the community. Accurate assessment of
hearing and vision impairment would be expected to lead to appropriate
treatment, accommodations, including
[[Page 19543]]
the provision of auxiliary aids and services during the stay, and
ensure that patients continue to have their vision and hearing needs
met when they leave the facility.
In alignment with our Meaningful Measures Initiative, we expect
accurate individualized assessment, treatment, and accommodation of
hearing and vision impairments of patients and residents in PAC to make
care safer by reducing harm caused in the delivery of care; promote
effective prevention and treatment of chronic disease; strengthen
person and family engagement as partners in their care; and promote
effective communication and coordination of care. For example,
standardized assessment of hearing and vision impairments used in PAC
will support ensuring patient safety (for example, risk of falls),
identifying accommodations needed during the stay, and appropriate
support needs at the time of discharge or transfer. Standardized
assessment of these data elements will enable or support clinical
decision-making and early clinical intervention; person-centered, high
quality care (for example, facilitating better care continuity and
coordination); better data exchange and interoperability between
settings; and longitudinal outcome analysis. Therefore, reliable data
elements assessing hearing and vision impairments are needed to
initiate a management program that can optimize a patient or resident's
prognosis and reduce the possibility of adverse events.
Hearing
We are proposing that the Hearing data element meets the definition
of standardized patient assessment data with respect to impairments
data under section 1899B(b)(1)(B)(v) of the Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20114 through 20115), accurate assessment of hearing impairment is
important in the PAC setting for care planning and resource use.
Hearing impairment has been associated with lower quality of life,
including poorer physical, mental, and social functioning, and
emotional health.753 754 Treatment and accommodation of
hearing impairment led to improved health outcomes, including but not
limited to quality of life.755 For example, hearing loss in
elderly individuals has been associated with depression and cognitive
impairment,756 757 758 higher rates of incident cognitive
impairment and cognitive decline,759 and less time in
occupational therapy.760 Accurate assessment of hearing
impairment is important in the PAC setting for care planning and
defining resource use.
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\753\ Dalton DS, Cruickshanks KJ, Klein BE, Klein R, Wiley TL,
Nondahl DM. The impact of hearing loss on quality of life in older
adults. Gerontologist. 2003;43(5):661-668.
\754\ Hawkins K, Bottone FG, Jr., Ozminkowski RJ, et al. The
prevalence of hearing impairment and its burden on the quality of
life among adults with Medicare Supplement Insurance. Qual Life Res.
2012;21(7):1135-1147.
\755\ Horn KL, McMahon NB, McMahon DC, Lewis JS, Barker M,
Gherini S. Functional use of the Nucleus 22-channel cochlear implant
in the elderly. The Laryngoscope. 1991;101(3):284-288.
\756\ Sprinzl GM, Riechelmann H. Current trends in treating
hearing loss in elderly people: A review of the technology and
treatment options--a mini-review. Gerontology. 2010;56(3):351-358.
\757\ Lin FR, Thorpe R, Gordon-Salant S, Ferrucci L. Hearing
Loss Prevalence and Risk Factors Among Older Adults in the United
States. The Journals of Gerontology Series A: Biological Sciences
and Medical Sciences. 2011;66A(5):582-590.
\758\ Hawkins K, Bottone FG, Jr., Ozminkowski RJ, et al. The
prevalence of hearing impairment and its burden on the quality of
life among adults with Medicare Supplement Insurance. Qual Life Res.
2012;21(7):1135-1147.
\759\ Lin FR, Metter EJ, O'Brien RJ, Resnick SM, Zonderman AB,
Ferrucci L. Hearing Loss and Incident Dementia. Arch Neurol.
2011;68(2):214-220.
\760\ Cimarolli VR, Jung S. Intensity of Occupational Therapy
Utilization in Nursing Home Residents: The Role of Sensory
Impairments. J Am Med Dir Assoc. 2016;17(10):939-942.
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The proposed data element consists of the single Hearing data
element. This data consists of one question that assesses level of
hearing impairment. This data element is currently in use in the MDS in
SNFs. For more information on the Hearing data element, we refer
readers to the document titled ``Proposed Specifications for LTCH QRP
Quality Measures and Standardized Patient Assessment Data Elements,''
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The Hearing data element was first proposed as a SPADE in the FY
2018 IPPS/LTCH PPS proposed rule (82 FR 20114 through 20115). In that
proposed rule, we stated that the proposal was informed by input we
received on the PAC PRD form of the data element (``Ability to Hear'')
through a call for input published on the CMS Measures Management
System Blueprint website. Input submitted from August 12 to September
12, 2016 recommended that hearing, vision, and communication
assessments be administered at the beginning of patient assessment
process. A summary report for the August 12 to September 12, 2016
public comment period titled ``SPADE August 2016 Public Comment Summary
Report'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received public comments in support of the Hearing data
element as well as concerns about not having recent, comprehensive
field testing of proposed data elements. Commenters were supportive of
adopting the Hearing data element for standardized cross-setting use,
noting that it would help address the needs of patient and residents
with disabilities and that failing to identify impairments during the
initial assessment can result in inaccurate diagnoses of impaired
language or cognition and can invalidate other information obtained
from patient assessment.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed rule, the Hearing data element was included in the National
Beta Test of candidate data elements conducted by our data element
contractor from November 2017 to August 2018. Results of this test
found the Hearing data element to be feasible and reliable for use with
PAC patients and residents. More information about the performance of
the Hearing data element in the National Beta Test can be found in the
document titled ``Proposed Specifications for LTCH QRP Quality Measures
and Standardized Patient Assessment Data Elements,'' available at:
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on January
5 and 6, 2017 for the purpose of soliciting input on all the SPADEs,
including the Hearing data element. The TEP affirmed the importance of
standardized assessment of hearing impairment in PAC patients and
residents. A summary of the January 5 and 6, 2017 TEP meeting titled
``SPADE Technical Expert Panel Summary (Second Convening)'' is
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing
[[Page 19544]]
SPADE development efforts. Finally, on November 27, 2018, our data
element contractor hosted a public meeting of stakeholders to present
the results of the National Beta Test and solicit additional comments.
General input on the testing and item development process and concerns
about burden were received from stakeholders during this meeting and
via email through February 1, 2019. In addition, a commenter expressed
support for the Hearing data element and suggested administration at
the beginning of the patient assessment to maximize utility. A summary
of the public input received from the November 27, 2018 stakeholder
meeting titled ``Input on Standardized Patient Assessment Data Elements
(SPADEs) Received After November 27, 2018 Stakeholder Meeting'' is
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for hearing,
stakeholder input, and strong test results, we are proposing that the
Hearing data element meets the definition of standardized patient
assessment data with respect to impairments under section
1899B(b)(1)(B)(v) of the Act, and to adopt the Hearing data element as
standardized patient assessment data for use in the LTCH QRP.
Vision
We are proposing that the Vision data element meets the definition
of standardized patient assessment data with respect to impairments
under section 1899B(b)(1)(B)(v) of the Act.
As described in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR
20115 through 20116), evaluation of an individual's ability to see is
important for assessing for risks such as falls and provides
opportunities for improvement through treatment and the provision of
accommodations, including auxiliary aids and services, which can
safeguard patients and improve their overall quality of life. Further,
vision impairment is often a treatable risk factor associated with
adverse events and poor quality of life. For example, individuals with
visual impairment are more likely to experience falls and hip fracture,
have less mobility, and report depressive
symptoms.761 762 763 764 765 766 767 Individualized initial
screening can lead to life-improving interventions such as
accommodations, including the provision of auxiliary aids and services,
during the stay and/or treatments that can improve vision and prevent
or slow further vision loss. In addition, vision impairment is often a
treatable risk factor associated with adverse events which can be
prevented and accommodated during the stay. Accurate assessment of
vision impairment is important in the LTCH setting for care planning
and defining resource use.
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\761\ Colon-Emeric CS, Biggs DP, Schenck AP, Lyles KW. Risk
factors for hip fracture in skilled nursing facilities: who should
be evaluated? Osteoporos Int. 2003;14(6):484-489.
\762\ Freeman EE, Munoz B, Rubin G, West SK. Visual field loss
increases the risk of falls in older adults: the Salisbury eye
evaluation. Invest Ophthalmol Vis Sci. 2007;48(10):4445-4450.
\763\ Keepnews D, Capitman JA, Rosati RJ. Measuring patient-
level clinical outcomes of home health care. J Nurs Scholarsh.
2004;36(1):79-85.
\764\ Nguyen HT, Black SA, Ray LA, Espino DV, Markides KS.
Predictors of decline in MMSE scores among older Mexican Americans.
J Gerontol A Biol Sci Med Sci. 2002;57(3):M181-185.
\765\ Prager AJ, Liebmann JM, Cioffi GA, Blumberg DM. Self-
reported Function, Health Resource Use, and Total Health Care Costs
Among Medicare Beneficiaries With Glaucoma. JAMA ophthalmology.
2016;134(4):357-365.
\766\ Rovner BW, Ganguli M. Depression and disability associated
with impaired vision: the MoVies Project. J Am Geriatr Soc.
1998;46(5):617-619.
\767\ Tinetti ME, Ginter SF. The nursing home life-space
diameter. A measure of extent and frequency of mobility among
nursing home residents. J Am Geriatr Soc. 1990;38(12):1311-1315.
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The proposed data element consists of the single Vision data
element (Ability To See in Adequate Light) that consists of one
question with five response categories. The Vision data element that we
are proposing for standardization was tested as part of the development
of the MDS and is currently in use in that assessment in SNFs. Similar
data elements, but with different wording and fewer response option
categories, are in use in the OASIS. For more information on the Vision
data element, we refer readers to the document titled ``Proposed
Specifications for LTCH QRP Quality Measures and Standardized Patient
Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
The Vision data element was first proposed as a SPADE in the FY
2018 IPPS/LTCH PPS proposed rule (82 FR 20115 through 20116). In that
proposed rule, we stated that the proposal was informed by input we
received on the Ability to See in Adequate Light data element (version
tested in the PAC PRD with three response categories) through a call
for input published on the CMS Measures Management System Blueprint
website. Although the data element on which we solicited input differed
from the proposed data element, input submitted from August 12 to
September 12, 2016 supported the assessment of vision in PAC settings
and the useful information such a vision data element would provide.
The commenters stated that the Ability to See item would provide
important information that would facilitate care coordination and care
planning, and consequently improve the quality of care. Other
commenters suggested it would be helpful as an indicator of resource
use and noted that the item would provide useful information about the
abilities of patients and residents to care for themselves. Additional
commenters noted that the item could feasibly be implemented across PAC
providers and that its kappa scores from the PAC PRD support its
validity. Some commenters noted a preference for MDS version of the
Vision data element over the form put forward in public comment, citing
the widespread use of this data element. A summary report for the
August 12 to September 12, 2016 public comment period titled ``SPADE
August 2016 Public Comment Summary Report'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In response to our proposal in the FY 2018 IPPS/LTCH PPS proposed
rule, we received comments in support of the Vision data element as
well as concerns about not having recent, comprehensive field testing
of proposed data elements. Commenters supported addressing the needs of
persons with disabilities and noted the importance of the Vision data
element because unaddressed impairments during the initial assessment
can result in inaccurate diagnoses of impaired language or cognition
and can invalidate other information obtained from the patient
assessment. Commenters recommended that hearing, vision, and
communication assessments be administered at the beginning of the
patient assessment process. One commenter expressed concern that the
Ability to See data element would not capture all aspects of functional
vision--that is, the person's ability to use vision to complete daily
activities and participate in environments--because it fails to assess
visual field and low contract visual acuity.
Subsequent to receiving comments on the FY 2018 IPPS/LTCH PPS
proposed
[[Page 19545]]
rule, the Vision data element was included in the National Beta Test of
candidate data elements conducted by our data element contractor from
November 2017 to August 2018. Results of this test found the Vision
data element to be feasible and reliable for use with PAC patients and
residents. More information about the performance of the Vision data
element in the National Beta Test can be found in the document titled
``Proposed Specifications for LTCH QRP Quality Measures and
Standardized Patient Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In addition, our data element contractor convened a TEP on January
5 and 6, 2017 for the purpose of soliciting input on all the SPADEs,
including the Vision data element. The TEP affirmed the importance of
standardized assessment of vision impairment in PAC patients and
residents. A summary of the January 5 and 6, 2017 TEP meeting titled
``SPADE Technical Expert Panel Summary (Second Convening)'' is
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We also held Special Open Door Forums and small-group discussions
with PAC providers and other stakeholders in 2018 for the purpose of
updating the public about our ongoing SPADE development efforts.
Finally, on November 27, 2018, our data element contractor hosted a
public meeting of stakeholders to present the results of the National
Beta Test and solicit additional comments. General input on the testing
and item development process and concerns about burden were received
from stakeholders during this meeting and via email through February 1,
2019. In addition, a commenter expressed support for the Vision data
element and suggested administration at the beginning of the patient
assessment to maximize utility. A summary of the public input received
from the November 27, 2018 stakeholder meeting titled ``Input on
Standardized Patient Assessment Data Elements (SPADEs) Received After
November 27, 2018 Stakeholder Meeting'' is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Taking together the importance of assessing for vision, stakeholder
input, and strong test results, we are proposing that the Vision data
element meets the definition of standardized patient assessment data
with respect to impairments under section 1899B(b)(1)(B)(v) of the Act,
and to adopt the Vision data element as standardized patient assessment
data for use in the LTCH QRP.
f. Proposed New Category: Social Determinants of Health
(1) Proposed Social Determinants of Health Data Collection To Inform
Measures and Other Purposes
Subparagraph (A) of section 2(d)(2) of the IMPACT Act requires CMS
to assess appropriate adjustments to quality measures, resource
measures, and other measures, and to assess and implement appropriate
adjustments to payment under Medicare, based on those measures, after
taking into account studies conducted by ASPE on social risk factors
(described below) and other information, and based on an individual's
health status and other factors. Subparagraph (C) of section 2(d)(2) of
the IMPACT Act further requires the Secretary to carry out periodic
analyses, at least every 3 years, based on the factors referred to
subparagraph (A) so as to monitor changes in possible relationships.
Subparagraph (B) of section 2(d)(2) of the IMPACT Act requires CMS to
collect or otherwise obtain access to data necessary to carry out the
requirement of the paragraph (both assessing adjustments described
above in such subparagraph (A) and for periodic analyses in such
subparagraph (C)). Accordingly we are proposing to use our authority
under subparagraph (B) of section 2(d)(2) of the IMPACT Act to
establish a new data source for information to meet the requirements of
subparagraphs (A) and (C) of section 2(d)(2) of the IMPACT Act. In this
rule, we are proposing to collect and access data about social
determinants of health (SDOH) to perform CMS' responsibilities under
subparagraphs (A) and (C) of section 2(d)(2) of the IMPACT Act, as
explained in more detail below. Social determinants of health, also
known as social risk factors, or health-related social needs, are the
socioeconomic, cultural and environmental circumstances in which
individuals live that impact their health. We are proposing to collect
information on seven proposed SDOH SPADE data elements relating to
race, ethnicity, preferred language, interpreter services, health
literacy, transportation, and social isolation; a detailed discussion
of each of the proposed SDOH data elements is found in section
VIII.C.7.f.(2) of the preamble of this proposed rule.
We are also proposing to use the assessment instrument for the LTCH
QRP, the LCDS, described as a PAC assessment instrument under section
1899B(a)(2)(B) of the Act, to collect these data via an existing data
collection mechanism. We believe this approach will provide CMS with
access to data with respect to the requirements of section 2(d)(2) of
the IMPACT Act, while minimizing the reporting burden on PAC health
care providers by relying on a data reporting mechanism already used
and an existing system to which PAC health care providers are already
accustomed.
The IMPACT Act includes several requirements applicable to the
Secretary, in addition to those imposing new data reporting obligations
on certain PAC providers as discussed in section VIII.C.7.f.(2) of the
preamble of this proposed rule. Subparagraphs (A) and (B) of section
2(d)(1) of the IMPACT Act require the Secretary, acting through the
Office of the Assistant Secretary for Planning and Evaluation (ASPE),
to conduct two studies that examine the effect of risk factors,
including individuals' socioeconomic status, on quality, resource use
and other measures under the Medicare program. The first ASPE study was
completed in December 2016 and is discussed below, and the second study
is to be completed in the fall of 2019. We recognize that ASPE, in its
studies, is considering a broader range of social risk factors than the
SDOH data elements in this proposal, and address both PAC and non-PAC
settings. We acknowledge that other data elements may be useful to
understand, and that some of those elements may be of particular
interest in non-PAC settings. For example, for beneficiaries receiving
care in the community, as opposed to an in-patient facility, housing
stability and food insecurity may be more relevant. We will continue to
take into account the findings from both of ASPE's reports in future
policy making.
One of the ASPE's first actions under the IMPACT Act was to
commission the National Academies of Sciences, Engineering, and
Medicine (NASEM) to define and conceptualize socioeconomic status for
the purposes of ASPE's two studies under section 2(d)(1) of the IMPACT
Act. The NASEM convened a panel of experts in the field and conducted
an extensive literature
[[Page 19546]]
review. Based on the information collected, the 2016 NASEM panel report
titled, ``Accounting for Social Risk Factors in Medicare Payment:
Identifying Social Risk Factors,'' concluded that the best way to
assess how social processes and social relationships influence key
health-related outcomes in Medicare beneficiaries is through a
framework of social risk factors instead of socioeconomic status.
Social risk factors discussed in the NASEM report include socioeconomic
position, race, ethnicity, gender, social context, and community
context. These factors are discussed at length in chapter 2 of the
NASEM report, titled ``Social Risk Factors.'' \768\ Consequently NASEM
framed the results of its report in terms of ``social risk factors''
rather than ``socioeconomic status'' or ``sociodemographic status.''
The full text of the ``Social Risk Factors'' NASEM report is available
for reading on the website at: https://www.nap.edu/read/21858/chapter/1.
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\768\ National Academies of Sciences, Engineering, and Medicine.
2016. Accounting for social risk factors in Medicare payment:
Identifying social risk factors. Chapter 2. Washington, DC: The
National Academies Press.
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Each of the data elements we are proposing to collect and access
pursuant to our authority under section 2(d)(2)(B) of the IMPACT Act is
identified in the 2016 NASEM report as a social risk factor that has
been shown to impact care use, cost and outcomes for Medicare
beneficiaries. CMS uses the term social determinants of health (SDOH)
to denote social risk factors, which is consistent with the objectives
of Healthy People 2020.\769\
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\769\ Social Determinants of Health. Healthy People 2020.
https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-of-health. (February 2019).
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ASPE issued its first Report to Congress, titled ``Social Risk
Factors and Performance Under Medicare's Value-Based Purchasing
Programs,'' under section 2(d)(1)(A) of the IMPACT Act on December 21,
2016.\770\ Using NASEM's social risk factors framework, ASPE focused on
the following social risk factors, in addition to disability: (1) Dual
enrollment in Medicare and Medicaid as a marker for low income, (2)
residence in a low-income area, (3) Black race, (4) Hispanic ethnicity,
and; (5) residence in a rural area. ASPE acknowledged that the social
risk factors examined in its report were limited due to data
availability. The report also noted that the data necessary to
meaningfully attempt to reduce disparities and identify and reward
improved outcomes for beneficiaries with social risk factors have not
been collected consistently on a national level in post-acute care
settings. Where these data have been collected, the collection
frequently involves lengthy questionnaires. More information on the
Report to Congress on Social Risk Factors and Performance under
Medicare's Value-Based Purchasing Programs, including the full report,
is available on the website at: https://aspe.hhs.gov/social-risk-factors-and-medicares-value-based-purchasing-programs-reports.
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\770\ U.S. Department of Health and Human Services, Office of
the Assistant Secretary for Planning and Evaluation. 2016. Report to
Congress: Social Risk Factors and Performance Under Medicare's
Value-Based Payment Programs. Washington, DC.
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Section 2(d)(2) of the IMPACT Act relates to CMS activities and
imposes several responsibilities on the Secretary relating to quality,
resource use, and other measures under Medicare. As mentioned
previously, under subparagraph (A) of section 2(d)(2) of the IMPACT
Act, the Secretary is required, on an ongoing basis, taking into
account the ASPE studies and other information, and based on an
individual's health status and other factors, to assess appropriate
adjustments to quality, resource use, and other measures, and to assess
and implement appropriate adjustments to Medicare payments based on
those measures. Section 2(d)(2)(A)(i) of the IMPACT Act applies to
measures adopted under subsections (c) and (d) of section 1899B of the
Act and to other measures under Medicare. However, CMS' ability to
perform these analyses, and assess and make appropriate adjustments is
hindered by limits of existing data collections on SDOH data elements
for Medicare beneficiaries. In its first study in 2016, in discussing
the second study, ASPE noted that information relating to many of the
specific factors listed in the IMPACT Act, such as health literacy,
limited English proficiency, and Medicare beneficiary activation, are
not available in Medicare data.
Subparagraph 2(d)(2)(A) of the IMPACT Act specifically requires the
Secretary to take the studies and considerations from ASPE's reports to
Congress, as well as other information as appropriate, into account in
assessing and implementing adjustments to measures and related payments
based on measures in Medicare. The results of the ASPE's first study
demonstrated that Medicare beneficiaries with social risk factors
tended to have worse outcomes on many quality measures, and providers
who treated a disproportionate share of beneficiaries with social risk
factors tended to have worse performance on quality measures. As a
result of these findings, ASPE suggested a three-pronged strategy to
guide the development of value-based payment programs under which all
Medicare beneficiaries receive the highest quality healthcare services
possible.
The three components of this strategy are to: (1) Measure and
report quality of care for beneficiaries with social risk factors; (2)
set high, fair quality standards for care provided to all
beneficiaries; and (3) reward and support better outcomes for
beneficiaries with social risk factors. In discussing how measuring and
reporting quality for beneficiaries with social risk factors can be
applied to Medicare quality payment programs, the report offered nine
considerations across the three-pronged strategy, including enhancing
data collection and developing statistical techniques to allow
measurement and reporting of performance for beneficiaries with social
risk factors on key quality and resource use measures.
Congress, in section 2(d)(2)(B) of the IMPACT Act, required the
Secretary to collect or otherwise obtain access to the data necessary
to carry out the provisions of paragraph (2) of section 2(d)of the
IMPACT Act through both new and existing data sources. Taking into
consideration NASEM's conceptual framework for social risk factors
discussed above, ASPE's study, considerations under section 2(d)(1)(A)
of the IMPACT Act, as well as the current data constraints of ASPE's
first study and its suggested considerations, we are proposing to
collect and access data about SDOH under section 2(d)(2) of the IMPACT
Act. Our collection and use of the SDOH data described in section
VIII.C.7.f.(1) of the preamble of this proposed rule, under section
2(d)(2) of the IMPACT Act, would be independent of our proposal below
(in section VIII.C.7.f.(2) of the preamble of this proposed rule) and
our authority to require submission of that data for use as SPADE under
section 1899B(a)(1)(B) of the Act.
Accessing standardized data relating to the SDOH data elements on a
national level is necessary to permit CMS to conduct periodic analyses,
to assess appropriate adjustments to quality measures, resource use
measures, and other measures, and to assess and implement appropriate
adjustments to Medicare payments based on those measures. We agree with
ASPE's observations, in the value-based purchasing context, that the
ability to measure and track quality, outcomes, and costs for
beneficiaries with social
[[Page 19547]]
risk factors over time is critical as policymakers and providers seek
to reduce disparities and improve care for these groups. Collecting the
data as proposed will provide the basis for our periodic analyses of
the relationship between an individual's health status and other
factors and quality, resource use, and other measures, as required by
section 2(d)(2) of the IMPACT Act, and to assess appropriate
adjustments. These data will also permit us to develop the statistical
tools necessary to maximize the value of Medicare data, reduce costs
and improve the quality of care for all beneficiaries. Collecting and
accessing SDOH data in this way also supports the three-part strategy
put forth in the first ASPE report, specifically ASPE's consideration
to enhance data collection and develop statistical techniques to allow
measurement and reporting of performance for beneficiaries with social
risk factors on key quality and resource use measures.
For the reasons discussed above, we are proposing under section
2(d)(2) of the IMPACT Act, to collect the data on the following SDOH:
(1) Race, as described in section VIII.C.7.f.(2)(a) of the preamble of
this proposed rule; (2) Ethnicity, as described in section
VIII.C.7.f.(2)(a) of the preamble of this proposed rule; (3) Preferred
Language, as described in section VIII.C.7.f.(2)(b) of the preamble of
this proposed rule; (4) Interpreter Services as described in section
VIII.C.7.f.(2)(b) of the preamble of this proposed rule; (5) Health
Literacy, as described in section VIII.C.7.f.(2)(c) of the preamble of
this proposed rule; (6) Transportation, as described in section
VIII.C.7.f.(2)(d) of the preamble of this proposed rule; and (7) Social
Isolation, as described in section VIII.C.7.f.(2)(e) of the preamble of
this proposed rule. These data elements are discussed in more detail
below in section VIII.C.7.f.(2) of the preamble of this proposed rule.
We welcome comment on this proposal.
(2) Standardized Patient Assessment Data
Section 1899B(b)(1)(B)(vi) of the Act authorizes the Secretary to
collect SPADEs with respect to other categories deemed necessary and
appropriate. Below we are proposing to create a Social Determinants of
Health SPADE category under section 1899B(b)(1)(B)(vi) of the Act. In
addition to collecting SDOH data for the purposes outlined above under
section 2(d)(2)(B) of the IMPACT Act, we are also proposing to collect
as SPADE these same data elements (race, ethnicity, preferred language,
interpreter services, health literacy, transportation, and social
isolation) under section 1899B(b)(1)(B)(vi) of the Act. We believe that
this proposed new category of Social Determinants of Health will inform
provider understanding of individual patient risk factors and treatment
preferences, facilitate coordinated care and care planning, and improve
patient outcomes. We are proposing to deem this category necessary and
appropriate, for the purposes of SPADE, because using common standards
and definitions for PAC data elements is important in ensuring
interoperable exchange of longitudinal information between PAC
providers and other providers to facilitate coordinated care,
continuity in care planning, and the discharge planning process from
post-acute care settings.
All of the Social Determinants of Health data elements we are
proposing under section 1899B(b)(1)(B)(vi) of the Act have the capacity
to take into account treatment preferences and care goals of patients
and to inform our understanding of patient complexity and risk factors
that may affect care outcomes. While acknowledging the existence and
importance of additional SDOH, we are proposing to assess some of the
factors relevant for patients receiving post-acute care that PAC
settings are in a position to impact through the provision of services
and supports, such as connecting patients with identified needs with
transportation programs, certified interpreters, or social support
programs.
As previously mentioned, and described in more detail below, we are
proposing to adopt the following seven data elements as SPADE under the
proposed Social Determinants of Health category: Race, ethnicity,
preferred language, interpreter services, health literacy,
transportation, and social isolation. To select these data elements, we
reviewed the research literature, a number of validated assessment
tools and frameworks for addressing SDOH currently in use (for example,
Health Leads, NASEM, Protocol for Responding to and Assessing Patients'
Assets, Risks, and Experiences (PRAPARE), and ICD-10), and we engaged
in discussions with stakeholders. We also prioritized balancing the
reporting burden for PAC providers with our policy objective to collect
SPADEs that will inform care planning and coordination and quality
improvement across care settings. Furthermore, incorporating SDOH data
elements into care planning has the potential to reduce readmissions
and help beneficiaries achieve and maintain their health goals.
We also considered feedback received during a listening session
that we held on December 13, 2018. The purpose of the listening session
was to solicit feedback from health systems, research organizations,
advocacy organizations and state agencies, and other members of the
public on collecting patient-level data on SDOH across care settings,
including consideration of race, ethnicity, spoken language, health
literacy, social isolation, transportation, sex, gender identity, and
sexual orientation. We also gave participants an option to submit
written comments. A full summary of the listening session, titled
``Listening Session on Social Determinants of Health Data Elements:
Summary of Findings,'' includes a list of participating stakeholders
and their affiliations, and is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
(a) Race and Ethnicity
The persistence of racial and ethnic disparities in health and
health care is widely documented, including in PAC
settings.771 772 773 774 775 Despite the trend toward
overall improvements in quality of care and health outcomes, the Agency
for Healthcare Research and Quality, in its National Healthcare Quality
and Disparities Reports, consistently indicates that racial and ethnic
disparities persist, even after controlling for factors such as income,
geography, and insurance.\776\ For example, racial and ethnic
minorities tend to have higher rates of infant mortality, diabetes and
other chronic conditions, and visits to the emergency department, and
lower
[[Page 19548]]
rates of having a usual source of care and receiving immunizations such
as the flu vaccine.\777\ Studies have also shown that African Americans
are significantly more likely than white Americans to die prematurely
from heart disease and stroke.\778\ However, our ability to identify
and address racial and ethnic health disparities has historically been
constrained by data limitations, particularly for smaller populations
groups such as Asians, American Indians and Alaska Natives, and Native
Hawaiians and other Pacific Islanders.\779\
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\771\ 2017 National Healthcare Quality and Disparities Report.
Rockville, MD: Agency for Healthcare Research and Quality; September
2018. AHRQ Pub. No. 18-0033-EF.
\772\ Fiscella, K. and Sanders, M.R. Racial and Ethnic
Disparities in the Quality of Health Care. (2016). Annual Review of
Public Health. 37:375-394.
\773\ 2018 National Impact Assessment of the Centers for
Medicare & Medicaid Services (CMS) Quality Measures Reports.
Baltimore, MD: U.S. Department of Health and Human Services, Centers
for Medicare and Medicaid Services; February 28, 2018.
\774\ Smedley, B.D., Stith, A.Y., & Nelson, A.R. (2003). Unequal
treatment: Confronting racial and ethnic disparities in health care.
Washington, DC, National Academy Press.
\775\ Chase, J., Huang, L. and Russell, D. (2017). Racial/ethnic
disparities in disability outcomes among post-acute home care
patients. J of Aging and Health. 30(9):1406-1426.
\776\ National Healthcare Quality and Disparities Reports.
(December 2018). Agency for Healthcare Research and Quality,
Rockville, MD. http://www.ahrq.gov/research/findings/nhqrdr/index.html.
\777\ National Center for Health Statistics. Health, United
States, 2017: With special feature on mortality. Hyattsville,
Maryland. 2018.
\778\ HHS. Heart disease and African Americans. 2016b. (October
24, 2016). http://minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=19.
\779\ National Academies of Sciences, Engineering, and Medicine;
Health and Medicine Division; Board on Population Health and Public
Health Practice; Committee on Community-Based Solutions to Promote
Health Equity in the United States; Baciu A, Negussie Y, Geller A,
et al., editors. Communities in Action: Pathways to Health Equity.
Washington (DC): National Academies Press (US); 2017 Jan 11. 2, The
State of Health Disparities in the United States. Available from:
https://www.ncbi.nlm.nih.gov/books/NBK425844/.
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The ability to improve understanding of and address racial and
ethnic disparities in PAC outcomes requires the availability of better
data. There is currently a Race and Ethnicity data element, collected
in the MDS, LCDS, IRF-PAI, and OASIS, that consists of a single
question, which aligns with the 1997 Office of Management and Budget
(OMB) minimum data standards for federal data collection efforts.\780\
The 1997 OMB Standard lists five minimum categories of race: (1)
American Indian or Alaska Native; (2) Asian; (3) Black or African
American; (4) Native Hawaiian or Other Pacific Islander; (5) and White.
The 1997 OMB Standard also lists two minimum categories of ethnicity:
(1) Hispanic or Latino; and (2) Not Hispanic or Latino. The 2011 HHS
Data Standards requires a two-question format when self-identification
is used to collect data on race and ethnicity. Large federal surveys
such as the National Health Interview Survey, Behavioral Risk Factor
Surveillance System, and the National Survey on Drug Use and Health,
have implemented the 2011 HHS race and ethnicity data standards. CMS
has similarly updated the Medicare Current Beneficiary Survey, Medicare
Health Outcomes Survey, and the Health Insurance Marketplace
Application for Health Coverage with the 2011 HHS data standards. More
information about the HHS Race and Ethnicity Data Standards are
available on the website at: https://minorityhealth.hhs.gov/omh/browse.aspx?lvl=3&lvlid=54.
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\780\ ``Revisions to the Standards for the Classification of
Federal Data on Race and Ethnicity (Notice of Decision)''. Federal
Register 62:210 (October 30, 1997) pp. 58782-58790. Available from:
https://www.govinfo.gov/content/pkg/FR-1997-10-30/pdf/97-28653.pdf.
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We are proposing to revise the current Race and Ethnicity data
element for purposes of this proposal to conform to the 2011 HHS Data
Standards for person-level data collection, while also meeting the 1997
OMB minimum data standards for race and ethnicity. Rather than one data
element that assesses both race and ethnicity, we are proposing two
separate data elements: One for Race and one for Ethnicity, that would
conform with the 2011 HHS Data Standards and the 1997 OMB Standard. In
accordance with the 2011 HHS Data Standards, a two-question format
would be used for the proposed race and ethnicity data elements.
The proposed Race data element asks, ``What is your race?'' We are
proposing to include fourteen response options under the race data
element: (1) White; (2) Black or African American; (3) American Indian
or Alaska Native; (4) Asian Indian; (5) Chinese; (6) Filipino; (7)
Japanese; (8) Korean; (9) Vietnamese; (10) Other Asian; (11) Native
Hawaiian; (12) Guamanian or Chamorro; (13) Samoan; and, (14) Other
Pacific Islander.
The proposed Ethnicity data element asks, ``Are you Hispanic,
Latino/a, or Spanish origin?'' We are proposing to include five
response options under the ethnicity data element: (1) Not of Hispanic,
Latino/a, or Spanish origin; (2) Mexican, Mexican American, Chicano/a;
(3) Puerto Rican; (4) Cuban; and, (5) Another Hispanic, Latino, or
Spanish Origin.
We believe that the two proposed data elements for race and
ethnicity conform to the 2011 HHS Data Standards for person-level data
collection, while also meeting the 1997 OMB minimum data standards for
race and ethnicity, because under those standards, more detailed
information on population groups can be collected if those additional
categories can be aggregated into the OMB minimum standard set of
categories.
In addition, we received stakeholder feedback during the December
13, 2018 SDOH listening session on the importance of improving response
options for race and ethnicity as a component of health care
assessments and for monitoring disparities. Some stakeholders
emphasized the importance of allowing for self-identification of race
and ethnicity for more categories than are included in the 2011 HHS
Standard to better reflect state and local diversity, while
acknowledging the burden of coding an open-ended health care assessment
question across different settings.
We believe that the proposed modified race and ethnicity data
elements more accurately reflect the diversity of the U.S. population
than the current race/ethnicity data element included in MDS, LCDS,
IRF-PAI, and OASIS.781 782 783 784 We believe, and research
consistently shows, that improving how race and ethnicity data are
collected is an important first step in improving quality of care and
health outcomes. Addressing disparities in access to care, quality of
care, and health outcomes for Medicare beneficiaries begins with
identifying and analyzing how SDOH, such as race and ethnicity, align
with disparities in these areas.\785\ Standardizing self-reported data
collection for race and ethnicity allows for the equal comparison of
data across multiple healthcare entities.\786\ By collecting and
analyzing these data, CMS and other healthcare entities will be able to
identify challenges and monitor progress. The growing diversity of the
U.S. population and knowledge of racial and ethnic disparities within
and across population groups supports the collection of more granular
data beyond the 1997 OMB minimum standard for reporting categories. The
2011 HHS race and ethnicity data standard includes additional detail
that may be used by
[[Page 19549]]
PAC providers to target quality improvement efforts for racial and
ethnic groups experiencing disparate outcomes. For more information on
the Race and Ethnicity data elements, we refer readers to the document
titled ``Proposed Specifications for LTCH QRP Measures and Standardized
Patient Assessment Data Elements,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
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\781\ Penman-Aguilar, A., Talih, M., Huang, D., Moonesinghe, R.,
Bouye, K., Beckles, G. (2016). Measurement of Health Disparities,
Health Inequities, and Social Determinants of Health to Support the
Advancement of Health Equity. J Public Health Manag Pract. 22 Suppl
1: S33-42.
\782\ Ramos, R., Davis, J.L., Ross, T., Grant, C.G., Green, B.L.
(2012). Measuring health disparities and health inequities: do you
have REGAL data? Qual Manag Health Care. 21(3):176-87.
\783\ IOM (Institute of Medicine). 2009. Race, Ethnicity, and
Language Data: Standardization for Health Care Quality Improvement.
Washington, DC: The National Academies Press.
\784\ ``Revision of Standards for Maintaining, Collecting, and
Presenting Federal Data on Race and Ethnicity: Proposals From
Federal Interagency Working Group (Notice and Request for
Comments).'' Federal Register 82: 39 (March 1, 2017) p. 12242.
\785\ National Academies of Sciences, Engineering, and Medicine;
Health and Medicine Division; Board on Population Health and Public
Health Practice; Committee on Community-Based Solutions to Promote
Health Equity in the United States; Baciu A, Negussie Y, Geller A,
et al., editors. Communities in Action: Pathways to Health Equity.
Washington (DC): National Academies Press (US); 2017 Jan 11. 2, The
State of Health Disparities in the United States. Available from:
https://www.ncbi.nlm.nih.gov/books/NBK425844/.
\786\ IOM (Institute of Medicine). 2009. Race, Ethnicity, and
Language Data: Standardization for Health Care Quality Improvement.
Washington, DC: The National Academies Press.
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In an effort to standardize the submission of race and ethnicity
data among IRFs, HHAs, SNFs and LTCHs, for the purposes outlined in
section 1899B(a)(1)(B) of the Act, while minimizing the reporting
burden, we are proposing to adopt the Race and Ethnicity data elements
described above as SPADEs with respect to the proposed Social
Determinants of Health category.
Specifically, we are proposing to replace the current Race/
Ethnicity data element with the proposed Race and Ethnicity data
elements on the LCDS. We are also proposing that LTCHs that submit the
Race and Ethnicity data elements with respect to admission will be
considered to have submitted with respect to discharge as well, because
it is unlikely that the results of these assessment findings will
change between the start and end of the LTCH stay, making the
information submitted with respect to a patient's admission the same
with respect to a patient's discharge.
(b) Preferred Language and Interpreter Services
More than 64 million Americans speak a language other than English
at home, and nearly 40 million of those individuals have limited
English proficiency (LEP).\787\ Individuals with LEP have been shown to
receive worse care and have poorer health outcomes, including higher
readmission rates.788 789 790 Communication with individuals
with LEP is an important component of high quality health care, which
starts by understanding the population in need of language services.
Unaddressed language barriers between a patient and provider care team
negatively affects the ability to identify and address individual
medical and non-medical care needs, to convey and understand clinical
information, as well as discharge and follow up instructions, all of
which are necessary for providing high quality care. Understanding the
communication assistance needs of patients with LEP, including
individuals who are Deaf or hard of hearing, is critical for ensuring
good outcomes.
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\787\ U.S. Census Bureau, 2013-2017 American Community Survey 5-
Year Estimates.
\788\ Karliner LS, Kim SE, Meltzer DO, Auerbach AD. Influence of
language barriers on outcomes of hospital care for general medicine
inpatients. J Hosp Med. 2010 May-Jun;5(5):276-82. doi: 10.1002/
jhm.658.
\789\ Kim EJ, Kim T, Paasche-Orlow MK, et al. Disparities in
Hypertension Associated with Limited English Proficiency. J Gen
Intern Med. 2017 Jun;32(6):632-639. doi: 10.1007/s11606-017-3999-9.
\790\ National Academies of Sciences, Engineering, and Medicine.
2016. Accounting for social risk factors in Medicare payment:
Identifying social risk factors. Washington, DC: The National
Academies Press.
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Presently, the preferred language of patients and need for
interpreter services are assessed in two PAC assessment tools. The LCDS
and the MDS use the same two data elements to assess preferred language
and whether a patient or resident needs or wants an interpreter to
communicate with health care staff. The MDS initially implemented
preferred language and interpreter services data elements to assess the
needs of SNF residents and patients and inform care planning. For
alignment purposes, the LCDS later adopted the same data elements for
LTCHs. The 2009 NASEM (formerly Institute of Medicine) report on
standardizing data for health care quality improvement emphasizes that
language and communication needs should be assessed as a standard part
of health care delivery and quality improvement strategies.\791\
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\791\ IOM (Institute of Medicine). 2009. Race, Ethnicity, and
Language Data: Standardization for Health Care Quality Improvement.
Washington, DC: The National Academies Press.
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In developing our proposal for a standardized language data element
across PAC settings, we considered the current preferred language and
interpreter services data elements that are in LCDS and MDS. We also
considered the 2011 HHS Primary Language Data Standard and peer-
reviewed research. The current preferred language data element in LCDS
and MDS asks, ``What is your preferred language?'' Because the
preferred language data element is open-ended, the patient or resident
is able to identify their preferred language, including American Sign
Language (ASL). Finally, we considered the recommendations from the
2009 NASEM (formerly Institute of Medicine) report, ``Race, Ethnicity,
and Language Data: Standardization for Health Care Quality
Improvement.'' In it, the committee recommended that organizations
evaluating a patient's language and communication needs for health care
purposes, should collect data on the preferred spoken language and on
an individual's assessment of his/her level of English proficiency.
A second language data element in LCDS and MDS asks, ``Do you want
or need an interpreter to communicate with a doctor or health care
staff?'' and includes yes or no response options. In contrast, the 2011
HHS Primary Language Data Standard recommends either a single question
to assess how well someone speaks English or, if more granular
information is needed, a two-part question to assess whether a language
other than English is spoken at home and if so, identify that language.
However, neither option allows for a direct assessment of a patient's
or resident's preferred spoken or written language nor whether they
want or need interpreter services for communication with a doctor or
care team, both of which are an important part of assessing patient and
resident needs and the care planning process. More information about
the HHS Data Standard for Primary Language is available on the website
at: https://minorityhealth.hhs.gov/omh/browse.aspx?lvl=3&lvlid=54.
Research consistently recommends collecting information about an
individual's preferred spoken language and evaluating those responses
for purposes of determining language access needs in health care.\792\
However, using ``preferred spoken language'' as the metric does not
adequately account for people whose preferred language is ASL, which
would necessitate adopting an additional data element to identify
visual language. The need to improve the assessment of language
preferences and communication needs across PAC settings should be
balanced with the burden associated with data collection on the
provider and patient. Therefore we are proposing to retain the
Preferred Language and Interpreter Services data elements currently in
use on the LCDS.
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\792\ Guerino, P. and James, C. Race, Ethnicity, and Language
Preference in the Health Insurance Marketplaces 2017 Open Enrollment
Period. Centers for Medicare & Medicaid Services, Office of Minority
Health. Data Highlight: Volume 7--April 2017. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Data-Highlight-Race-Ethnicity-and-Language-Preference-Marketplace.pdf.
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In addition, we received feedback during the December 13, 2018
listening session on the importance of evaluating and acting on
language preferences early to facilitate communication and allowing for
patient self-identification of preferred language. Although the
discussion about language was focused on preferred spoken language,
there was
[[Page 19550]]
general consensus among participants that stated language preferences
may or may not accurately indicate the need for interpreter services,
which supports collecting and evaluating data to determine language
preference, as well as the need for interpreter services. An alternate
suggestion was made to inquire about preferred language specifically
for discussing health or health care needs. While this suggestion does
allow for ASL as a response option, we do not have data indicating how
useful this question might be for assessing the desired information and
thus we are not including this question in our proposal.
Improving how preferred language and need for interpreter services
data are collected is an important component of improving quality by
helping PAC providers and other providers understand patient needs and
develop plans to address them. For more information on the Preferred
Language and Interpreter Services data elements, we refer readers to
the document titled ``Proposed Specifications for LTCH QRP Measures and
Standardized Patient Assessment Data Elements,'' available on the
website at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In an effort to standardize the submission of language data among
IRFs, HHAs, SNFs and LTCHs, for the purposes outlined in section
1899B(a)(1)(B) of the Act, while minimizing the reporting burden, we
are proposing to adopt the Preferred Language and Interpreter Services
data elements currently used on the LCDS, and describe above, as SPADEs
with respect to the Social Determinants of Health category.
(c) Health Literacy
The Department of Health and Human Services defines health literacy
as ``the degree to which individuals have the capacity to obtain,
process, and understand basic health information and services needed to
make appropriate health decisions.'' \793\ Similar to language
barriers, low health literacy can interfere with communication between
the provider and patient and the ability for patients or their
caregivers to understand and follow treatment plans, including
medication management. Poor health literacy is linked to lower levels
of knowledge about health, worse health outcomes, and the receipt of
fewer preventive services, but higher medical costs and rates of
emergency department use.\794\
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\793\ U.S. Department of Health and Human Services, Office of
Disease Prevention and Health Promotion. National action plan to
improve health literacy. Washington (DC): Author; 2010.
\794\ National Academies of Sciences, Engineering, and Medicine.
2016. Accounting for social risk factors in Medicare payment:
Identifying social risk factors. Washington, DC: The National
Academies Press.
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Health literacy is prioritized by Healthy People 2020 as an
SDOH.\795\ Healthy People 2020 is a long-term, evidence-based effort
led by the Department of Health and Human Services that aims to
identify nationwide health improvement priorities and improve the
health of all Americans. Although not designated as a social risk
factor in NASEM's 2016 report on accounting for social risk factors in
Medicare payment, the NASEM noted that health literacy is impacted by
other social risk factors and can affect access to care as well as
quality of care and health outcomes.\796\ Assessing for health literacy
across PAC settings would facilitate better care coordination and
discharge planning. A significant challenge in assessing the health
literacy of individuals is avoiding excessive burden on patients and
health care providers. The majority of existing, validated health
literacy assessment tools use multiple screening items, generally with
no fewer than four, which would make them burdensome if adopted in MDS,
LCDS, IRF-PAI, and OASIS.
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\795\ Social Determinants of Health. Healthy People 2020.
https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-of-health. (February 2019).
\796\ U.S. Department of Health & Human Services, Office of the
Assistant Secretary for Planning and Evaluation. Report to Congress:
Social Risk Factors and Performance Under Medicare's Value-Based
Purchasing Programs. Available at: https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs. Washington, DC: 2016.
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The Single Item Literacy Screener (SILS) question asks, ``How often
do you need to have someone help you when you read instructions,
pamphlets, or other written material from your doctor or pharmacy?''
Possible response options are: (1) Never; (2) Rarely; (3) Sometimes;
(4) Often; and (5) Always. The SILS question, which assesses reading
ability, (a primary component of health literacy), tested reasonably
well against the 36 item Short Test of Functional Health Literacy in
Adults (S-TOFHLA), a thoroughly vetted and widely adopted health
literacy test, in assessing the likelihood of low health literacy in an
adult sample from primary care practices participating in the Vermont
Diabetes Information System.797 798 The S-TOFHLA is a more
complex assessment instrument developed using actual hospital related
materials such as prescription bottle labels and appointment slips, and
often considered the instrument of choice for a detailed evaluation of
health literacy.\799\ Furthermore, the S-TOFHLA instrument is
proprietary and subject to purchase for individual entities or
users.\800\ Given that SILS is publicly available, shorter and easier
to administer than the full health literacy screen, and research found
that a positive result on the SILS demonstrates an increased likelihood
that an individual has low health literacy, we are proposing to use the
single-item reading question for health literacy in the standardized
data collection across PAC settings. We believe that use of this data
element will provide sufficient information about the health literacy
of LTCH patients to facilitate appropriate care planning, care
coordination, and interoperable data exchange across PAC settings.
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\797\ Morris, N.S., MacLean, C.D., Chew, L.D., & Littenberg, B.
(2006). The Single Item Literacy Screener: Evaluation of a brief
instrument to identify limited reading ability. BMC family practice,
7, 21. doi:10.1186/1471-2296-7-21.
\798\ Brice, J.H., Foster, M.B., Principe, S., Moss, C., Shofer,
F.S., Falk, R.J., Ferris, M.E., DeWalt, D.A. (2013). Single-item or
two-item literacy screener to predict the S-TOFHLA among adult
hemodialysis patients. Patient Educ Couns. 94(1):71-5.
\799\ University of Miami, School of Nursing & Health Studies,
Center of Excellence for Health Disparities Research. Test of
Functional Health Literacy in Adults (TOFHLA). (March 2019).
Available from: https://elcentro.sonhs.miami.edu/research/measures-library/tofhla/index.html.
\800\ Nurss, J.R., Parker, R.M., Williams, M.V., &Baker, D.W.
David W. (2001). TOFHLA. Peppercorn Books & Press. Available from:
http://www.peppercornbooks.com/catalog/information.php?info_id=5.
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In addition, we received feedback during the December 13, 2018 SDOH
listening session on the importance of recognizing health literacy as
more than understanding written materials and filling out forms, as it
is also important to evaluate whether patients understand their
conditions. However, the NASEM recently recommended that health care
providers implement health literacy universal precautions instead of
taking steps to ensure care is provided at an appropriate literacy
level based on individualized assessment of health literacy.\801\ Given
the dearth of Medicare data on health literacy and gaps in addressing
health literacy in practice,
[[Page 19551]]
we recommend the addition of a health literacy data element.
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\801\ Hudson, S., Rikard, R.V., Staiculescu, I. & Edison, K.
(2017). Improving health and the bottom line: The case for health
literacy. In Building the case for health literacy: Proceedings of a
workshop. Washington, DC: The National Academies Press.
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The proposed Health Literacy data element is consistent with
considerations raised by NASEM and other stakeholders and research on
health literacy, which demonstrates an impact on health care use, cost,
and outcomes.\802\ For more information on the proposed Health Literacy
data element, we refer readers to the document titled ``Proposed
Specifications for LTCH QRP Measures and Standardized Patient
Assessment Data Elements,'' available on the website at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
---------------------------------------------------------------------------
\802\ National Academies of Sciences, Engineering, and Medicine.
2016. Accounting for Social Risk Factors in Medicare Payment:
Identifying Social Risk Factors. Washington, DC: The National
Academies Press.
---------------------------------------------------------------------------
In an effort to standardize the submission of health literacy data
among IRFs, HHAs, SNFs and LTCHs, for the purposes outlined in section
1899B(a)(1)(B) of the Act, while minimizing the reporting burden, we
are proposing to adopt the SILS question, described above for the
Health Literacy data element, as SPADE under the Social Determinants of
Health category. We are proposing to add the Health Literacy data
element to the LCDS.
(d) Transportation
Transportation barriers commonly affect access to necessary health
care, causing missed appointments, delayed care, and unfilled
prescriptions, all of which can have a negative impact on health
outcomes.\803\ Access to transportation for ongoing health care and
medication access needs, particularly for those with chronic diseases,
is essential to successful chronic disease management. Adopting a data
element to collect and analyze information regarding transportation
needs across PAC settings would facilitate the connection to programs
that can address identified needs. We are therefore proposing to adopt
as SPADE a single transportation data element that is from the Protocol
for Responding to and Assessing Patients' Assets, Risks, and
Experiences (PRAPARE) assessment tool and currently part of the
Accountable Health Communities (AHC) Screening Tool.
---------------------------------------------------------------------------
\803\ Syed, S.T., Gerber, B.S., and Sharp, L.K. (2013).
Traveling Towards Disease: Transportation Barriers to Health Care
Access. J Community Health. 38(5): 976-993.
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The proposed Transportation data element from the PRAPARE tool
asks, ``Has lack of transportation kept you from medical appointments,
meetings, work, or from getting things needed for daily living?'' The
three response options are: (1) Yes, it has kept me from medical
appointments or from getting my medications; (2) Yes, it has kept me
from non-medical meetings, appointments, work, or from getting things
that I need; and (3) No. The patient would be given the option to
select all responses that apply. We are proposing to use the
transportation data element from the PRAPARE Tool, with permission from
National Association of Community Health Centers (NACHC), after
considering research on the importance of addressing transportation
needs as a critical SDOH.\804\
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\804\ Health Research & Educational Trust. (2017, November).
Social determinants of health series: Transportation and the role of
hospitals. Chicago, IL. Available at: www.aha.org/transportation.www.aha.org/transportation.
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The proposed data element is responsive to research on the
importance of addressing transportation needs as a critical SDOH and
would adopt the Transportation item from the PRAPARE tool.\805\ This
data element comes from the national PRAPARE social determinants of
health assessment protocol, developed and owned by NACHC, in
partnership with the Association of Asian Pacific Community Health
Organization, the Oregon Primary Care Association, and the Institute
for Alternative Futures. Similarly the Transportation data element used
in the AHC Screening Tool was adapted from the PRAPARE tool. The AHC
screening tool was implemented by the Center for Medicare and Medicaid
Innovation's AHC Model and developed by a panel of interdisciplinary
experts that looked at evidence-based ways to measure SDOH, including
transportation. While the transportation access data element in the AHC
screening tool serves the same purposes as our proposed SPADE
collection about transportation barriers, the AHC tool has binary yes
or no response options that do not differentiate between challenges for
medical versus non-medical appointments and activities. We believe that
this is an important nuance for informing PAC discharge planning to a
community setting, as transportation needs for non-medical activities
may differ than for medical activities and should be taken into
account.\806\ We believe that use of this data element will provide
sufficient information about transportation barriers to medical and
non-medical care for LTCH patients to facilitate appropriate discharge
planning and care coordination across PAC settings. As such, we are
proposing to adopt the Transportation data element from PRAPARE. More
information about development of the PRAPARE tool is available on the
website at: https://protect2.fireeye.com/url?k=7cb6eb44-20e2f238-7cb6da7b-0cc47adc5fa2-1751cb986c8c2f8c&u=http://www.nachc.org/prapare.
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\805\ Health Research & Educational Trust. (2017, November).
Social determinants of health series: Transportation and the role of
hospitals. Chicago, IL. Available at: www.aha.org/transportation.
\806\ Northwestern University. (2017). PROMIS Item Bank v. 1.0--
Emotional Distress--Anger--Short Form 1.
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In addition, we received stakeholder feedback during the December
13, 2018 SDOH listening session on the impact of transportation
barriers on unmet care needs. While recognizing that there is no
consensus in the field about whether providers should have
responsibility for resolving patient transportation needs, discussion
focused on the importance of assessing transportation barriers to
facilitate connections with available community resources.
Adding a Transportation data element to the collection of SPADE
would be an important step to identifying and addressing SDOH that
impact health outcomes and patient experience for Medicare
beneficiaries. For more information on the Transportation data element,
we refer readers to the document titled ``Proposed Specifications for
LTCH QRP Measures and Standardized Patient Assessment Data Elements,''
available on the website at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In an effort to standardize the submission of transportation data
among IRFs, HHAs, SNFs and LTCHs, for the purposes outlined in section
1899B(a)(1)(B) of the Act, while minimizing the reporting burden, we
are proposing to adopt the Transportation data element described above
as SPADE with respect to the proposed Social Determinants of Health
category. If finalized as proposed, we would add the Transportation
data element to the LCDS.
(e) Social Isolation
Distinct from loneliness, social isolation refers to an actual or
perceived lack of contact with other people, such as living alone or
residing in a remote
[[Page 19552]]
area.807 808 Social isolation tends to increase with age, is
a risk factor for physical and mental illness, and a predictor of
mortality.809 810 811 Post-acute care providers are well-
suited to design and implement programs to increase social engagement
of patients, while also taking into account individual needs and
preferences. Adopting a data element to collect and analyze information
about social isolation in LTCHs and across PAC settings would
facilitate the identification of patients who are socially isolated and
who may benefit from engagement efforts.
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\807\ Tomaka, J., Thompson, S., and Palacios, R. (2006). The
Relation of Social Isolation, Loneliness, and Social Support to
Disease Outcomes Among the Elderly. J of Aging and Health. 18(3):
359-384.
\808\ Social Connectedness and Engagement Technology for Long-
Term and Post-Acute Care: A Primer and Provider Selection Guide.
(2019). Leading Age. Available at: https://www.leadingage.org/white-papers/social-connectedness-and-engagement-technology-long-term-and-post-acute-care-primer-and#1.1.
\809\ Landeiro, F., Barrows, P., Nuttall Musson, E., Gray, A.M.,
and Leal, J. (2017). Reducing Social Loneliness in Older People: A
Systematic Review Protocol. BMJ Open. 7(5): e013778.
\810\ Ong, A.D., Uchino, B.N., and Wethington, E. (2016).
Loneliness and Health in Older Adults: A Mini-Review and Synthesis.
Gerontology. 62:443-449.
\811\ Leigh-Hunt, N., Bagguley, D., Bash, K., Turner, V.,
Turnbull, S., Valtorta, N., and Caan, W. (2017). An overview of
systematic reviews on the public health consequences of social
isolation and loneliness. Public Health. 152:157-171.
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We are proposing to adopt as SPADE a single social isolation data
element that is currently part of the AHC Screening Tool. The AHC item
was selected from the Patient-Reported Outcomes Measurement Information
System (PROMIS[supreg]) Item Bank on Emotional Distress and asks, ``How
often do you feel lonely or isolated from those around you?'' The five
response options are: (1) Never; (2) Rarely; (3) Sometimes; (4) Often;
and (5) Always.\812\ The AHC Screening Tool was developed by a panel of
interdisciplinary experts that looked at evidence-based ways to measure
SDOH, including social isolation. More information about the AHC
Screening Tool is available on the website at: https://innovation.cms.gov/Files/worksheets/ahcm-screeningtool.pdf.
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\812\ Northwestern University. (2017). PROMIS Item Bank v. 1.0--
Emotional Distress--Anger--Short Form 1.
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In addition, we received stakeholder feedback during the December
13, 2018 SDOH listening session on the value of receiving information
on social isolation for purposes of care planning. Some stakeholders
also recommended assessing social isolation as an SDOH as opposed to
social support.
The proposed Social Isolation data element is consistent with NASEM
considerations about social isolation as a function of social
relationships that impacts health outcomes and increases mortality
risk, as well as the current work of a NASEM committee examining how
social isolation and loneliness impact health outcomes in adults 50
years and older. We believe that adding a Social Isolation data element
would be an important component of better understanding patient
complexity and the care goals of patients, thereby facilitating care
coordination and continuity in care planning across PAC settings. For
more information on the Social Isolation data element, we refer readers
to the document titled ``Proposed Specifications for LTCH QRP Measures
and Standardized Patient Assessment Data Elements,'' available on the
website at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
In an effort to standardize the submission of social isolation data
among IRFs, HHAs, SNFs and LTCHs, for the purposes outlined in section
1899B(a)(1)(B) of the Act, while minimizing the reporting burden, we
are proposing to adopt the Social Isolation data element described
above as SPADE with respect to the proposed Social Determinants of
Health category. We are proposing to add the Social Isolation data
element to the LCDS.
We are soliciting comment on these proposals.
8. Proposed Form, Manner, and Timing of Data Submission Under the LTCH
QRP
a. Background
We refer readers to the regulations at Sec. 412.560(b) for
information regarding the current policies for reporting LTCH QRP data.
b. Update to the CMS System for Reporting Quality Measures and
Standardized Patient Assessment Data and Associated Procedural
Proposals
LTCHs are currently required to submit LCDS data to CMS using the
Quality Improvement and Evaluation System (QIES) Assessment and
Submission Processing (ASAP) system. We have recently migrated to a new
internet Quality Improvement and Evaluation System (iQIES) that will
enable real-time upgrades, and we are proposing to designate that
system as the data submission system for the LTCH QRP beginning October
1, 2019. We are also proposing to revise our regulations at Sec.
412.560(d)(1) by replacing the reference to ``Quality Improvement and
Evaluation System (QIES) Assessment Submission and Processing (ASAP)
system'' with ``CMS designated data submission system'', and to revise
Sec. 412.560(d)(3) and Sec. 412.560(f)(1) by replacing the references
to ``QIES ASAP system'' with ``CMS designated data submission system''
effective October 1, 2019. In addition, we are proposing to notify the
public of any future changes to the CMS designated system using
subregulatory mechanisms such as website postings, listserv messaging,
and webinars.
c. Proposed Reporting Requirement Updates Beginning With the FY 2022
LTCH QRP
In the FY 2019 IPPS/LTCH PPS proposed rule (83 FR 20515), we sought
public comment on moving the implementation date of any new version of
the LCDS from April to October of the same year. In the FY 2019 IPPS/
LTCH PPS final rule (83 FR 41633), we summarized the comments we
received on this topic. After considering those comments, and to align
with the MDS and IRF-PAI implementation dates, in this proposed rule,
we are proposing to move the implementation date of any new version of
the LCDS from April to October, beginning October 1, 2020. This would
provide LTCHs an additional 6 months to prepare for any changes to the
reporting requirements.
We are also proposing that, for the first program year in which
measures or standardized patient assessment data are adopted, LTCHs
would only be required to report data on patients who are admitted and
discharged during the last quarter (October 1 to December 31) of the
calendar year that applies to the program year. For subsequent program
years, LTCHs would be required to report data on patients who are
admitted and discharged during the 12-month calendar year that applies
to the program year.
The tables below illustrate the proposed quarterly data collection
reporting periods and data submission deadlines using the FY 2022 LTCH
QRP and FY 2023 LTCH QRP. The data submission deadline applies to all
measures and standardized patient assessment data except the Influenza
Vaccination Coverage Among Healthcare Personnel (NQF #0431)
[[Page 19553]]
measure data, which is submitted annually.
Initial Reporting Period for Quality Measures * and Standardized Patient
Assessment Data Reporting for the FY 2022 LTCH QRP **
------------------------------------------------------------------------
Proposed data submission
Proposed data collection quarterly quarterly deadlines beginning
reporting period with the FY 2022 LTCH QRP
------------------------------------------------------------------------
CY 2020 Q4: 10/1/2020-12/31/2020....... CY 2020 Q4 Deadline: May 15,
2021.
------------------------------------------------------------------------
* The submission deadline for the Influenza Vaccination Coverage Among
Healthcare Personnel measure (NQF #0431) is annual, not quarterly. The
proposed data collection reporting period for the Influenza
Vaccination Coverage Among Healthcare Personnel measure (NQF #0431)
for the FY 2022 LTCH QRP is 10/1/2020-3/31/2021 and its proposed
deadline is May 15, 2021.
** Applies to data reporting using the LCDS and CDC's NHSN.
Calendar Year Reporting Period for Quality Measures * and Standardized
Patient Assessment Data Reporting for the FY 2023 LTCH QRP **
------------------------------------------------------------------------
Proposed data submission
Proposed data collection quarterly quarterly deadlines beginning
reporting period with the FY 2023 LTCH QRP
------------------------------------------------------------------------
CY 2021 Q1: 1/1/2021-3/31/2021......... CY 2021 Q1 Deadline: August 15,
2021.
CY 2021 Q2: 4/1/2021-6/30/2021......... CY 2021 Q2 Deadline: November
15, 2021.
CY 2021 Q3: 7/1/2021-9/30/2021......... CY 2021 Q3 Deadline: February
15, 2022.
CY 2021 Q4: 10/1/2021-12/31/2021....... CY 2021 Q4 Deadline: May 15,
2022.
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* The submission deadline for the Influenza Vaccination Coverage Among
Healthcare Personnel measure (NQF #0431) is annual, not quarterly. The
proposed data collection reporting period for the Influenza
Vaccination Coverage Among Healthcare Personnel measure (NQF #0431)
for the FY 2023 LTCH QRP is 10/1/2021-3/31/2022 and its proposed
deadline is May 15, 2022.
** Applies to data reporting using the LCDS and CDC's NHSN.
d. Proposed Schedule for Reporting the Transfer of Health Information
Quality Measures Beginning With the FY 2022 LTCH QRP
As discussed in section VIII.C.4. of the preamble of this proposed
rule, we are proposing to adopt the Transfer of Health Information to
the Provider--Post-Acute Care (PAC) and Transfer of Health Information
to the Patient--Post-Acute Care (PAC) quality measures beginning with
the FY 2022 LTCH QRP. We also are proposing that LTCHs would report the
data on those measures using the LCDS. LTCHs would be required to
collect data on both measures for all patients beginning with October
1, 2020 discharges. We refer readers to the tables in section
VIII.C.8.c. of the preamble of this proposed rule for an illustration
of the initial and calendar year reporting cycles.
e. Proposed Schedule for Reporting Standardized Patient Assessment Data
Elements Beginning With the FY 2022 LTCH QRP
As discussed in section VIII.C.7. of the preamble of this proposed
rule, we are proposing to adopt SPADEs beginning with the FY 2022 LTCH
QRP. We are proposing that LTCHs would report the data using the LCDS.
Similar to the proposed schedule for reporting the Transfer of Health
Information to the Provider--Post-Acute Care (PAC) and Transfer of
Health Information to the Patient--Post-Acute Care (PAC) quality
measures, LTCHs would be required to collect the SPADEs for all
patients beginning with October 1, 2020 admissions and discharges.
LTCHs that submit data with respect to admission for the Hearing,
Vision, Race, and Ethnicity SPADEs would be considered to have
submitted data with respect to discharge. We refer readers to the
tables in section VIII.C.8.c. of the preamble of this proposed rule for
an illustration of the initial and calendar year reporting cycles.
9. Proposed Removal of the List of Compliant LTCHs
In the FY 2016 IPPS/LTCH PPS final rule (80 FR 49754 through
49755), we finalized that we would publish a list of LTCHs that
successfully met the reporting requirements for the applicable payment
determination on the LTCH QRP website and update the list on an annual
basis.
We have received feedback from stakeholders that this list offers
minimal benefit. Although the posting of successful providers was the
final step in the applicable payment determination process, it does not
provide new information or clarification to the providers regarding
their annual payment update status. Therefore, in this proposed rule,
we are proposing that we will no longer publish a list of compliant
LTCHs on the LTCH QRP website effective beginning with the FY 2020
payment determination.
10. Proposed Policies Regarding Public Display of Measure Data for the
LTCH QRP
Section 1886(m)(5)(E) of the Act requires the Secretary to
establish procedures for making the LTCH QRP data available to the
public after ensuring that LTCHs have the opportunity to review their
data prior to public display. Measure data are currently displayed on
the LTCH Compare website, an interactive web tool that assists
individuals by providing information on LTCH quality of care. For more
information on LTCH Compare, we refer readers to our website at:
https://www.medicare.gov/longtermcarehospitalcompare/. For a more
detailed discussion about our policies regarding public display of LTCH
QRP measure data and procedures for the opportunity to review and
correct data and information, we refer readers to the FY 2017 IPPS/LTCH
PPS final rule (81 FR 57231 through 57236). In this proposed rule, we
are proposing to begin publicly displaying data for the Drug Regimen
Review Conducted With Follow-Up for Identified Issues--Post Acute Care
(PAC) Long-Term Care Hospital (LTCH) Quality Reporting Program (QRP)
measure beginning CY 2020 or as soon as technically feasible. We
finalized the Drug Regimen Review Conducted With Follow-Up for
Identified Issues--Post Acute Care (PAC) Long-Term Care Hospital (LTCH)
Quality Reporting Program (QRP) measure in the FY 2017
[[Page 19554]]
IPPS/LTCH PPS final rule (81 FR 57219 through 57223).
Data collection for this assessment-based measure began with
patients admitted and discharged on or after July 1, 2018. We are
proposing to display data based on four rolling quarters, initially
using discharges from January 1, 2019 through December 31, 2019
(Quarter 1 2019 through Quarter 4 2019). To ensure the statistical
reliability of the data, we are proposing that we would not publicly
report an LTCH's performance on the measure if the LTCH had fewer than
20 eligible cases in any four consecutive rolling quarters. LTCHs that
have fewer than 20 eligible cases would be distinguished with a
footnote that states: ``The number of cases/patient stays is too small
to publicly report.''
D. Proposed Changes to the Medicare and Medicaid Promoting
Interoperability Programs
1. Background
a. Statutory Authority for the Medicare and Medicaid Promoting
Interoperability Programs
The HITECH Act (Title IV of Division B of the ARRA, together with
Title XIII of Division A of the ARRA) authorizes incentive payments
under Medicare and Medicaid for the adoption and meaningful use of
certified electronic health record technology (CEHRT). Incentive
payments under Medicare were available to eligible hospitals and CAHs
for certain payment years (as authorized under sections 1886(n) and
1814(l) of the Act, respectively) if they successfully demonstrated
meaningful use of CEHRT, which included reporting on clinical quality
measures (CQMs) using CEHRT. Incentive payments were available to
Medicare Advantage (MA) organizations under section 1853(m)(3) of the
Act for certain affiliated hospitals that meaningfully used CEHRT. In
accordance with the timeframe set forth in the statute, these incentive
payments under Medicare generally are no longer available, except for
Puerto Rico eligible hospitals (for more information on the Medicare
incentive payments available to Puerto Rico eligible hospitals, we
refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41672
through 41675).
Sections 1886(b)(3)(B)(ix) and 1814(l)(4) of the Act also establish
downward payment adjustments under Medicare, beginning with FY 2015,
for eligible hospitals and CAHs that do not successfully demonstrate
meaningful use of CEHRT for certain associated reporting periods.
Section 1853(m)(4) of the Act establishes a negative payment adjustment
to the monthly prospective payments of a qualifying MA organization if
its affiliated eligible hospitals are not meaningful users of CEHRT,
beginning in 2015.
Section 1903(a)(3)(F)(i) of the Act establishes 100 percent Federal
financial participation (FFP) to States for providing incentive
payments to eligible Medicaid providers (described in section
1903(t)(2) of the Act) to adopt, implement, upgrade and meaningfully
use CEHRT.
b. Goals of Proposed Changes to the Medicare and Medicaid Promoting
Interoperability Programs
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41635), we affirmed
our commitment to furthering interoperability by changing the name of
the EHR Incentive Program to the Promoting Interoperability Program. As
we look toward the future of the Promoting Interoperability Program,
the general goals of our proposals in this proposed rule include: (1) A
priority of stability within the program after the recent changes made
in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41634 through 41677)
while continuing to further interoperability through the use of CEHRT;
(2) reducing administrative burden; (3) continued use of the 2015
Edition CEHRT; and (4) improving patient access to their EHRs so they
can make fully informed health care decisions.
2. EHR Reporting Period
a. Proposed Change to the EHR Reporting Period in CY 2019 for Eligible
Hospitals
Under Sec. 495.4, in the definition of ``EHR reporting period for
a payment adjustment year,'' for 2019, if an eligible hospital has not
successfully demonstrated it is a meaningful EHR user in a prior year,
the EHR reporting period is any continuous 90-day period within CY 2019
and applies for the FY 2020 and 2021 payment adjustment years. For the
FY 2020 payment adjustment year, the EHR reporting period must end
before and the eligible hospital must successfully register for and
attest to meaningful use no later than October 1, 2019.
We are proposing that, if we finalize our proposal to modify the
Query of PDMP measure to require a ``yes/no'' attestation response
instead of a numerator/denominator, as discussed in greater detail in
section VIII.D.3.b. of the preamble of this proposed rule, we would
eliminate the October 1, 2019 deadline for an eligible hospital that
has not successfully demonstrated it is a meaningful EHR user in a
prior year. This proposal would provide such eligible hospitals all of
CY 2019 to complete their respective 90-day EHR reporting period for
the FY 2020 payment adjustment year. We are proposing to revise the
definition of ``EHR reporting period for a payment adjustment year'' at
42 CFR 495.4 to reflect this proposal.
b. Proposed EHR Reporting Period in CY 2021
As finalized in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41636),
and codified in the definitions of ``EHR reporting period'' and ``EHR
reporting period for a payment adjustment year'' at 42 CFR 495.4, the
EHR reporting period in CY 2020 is a minimum of any continuous 90-day
period in CY 2020 for new and returning participants in the Promoting
Interoperability Programs attesting to CMS or their State Medicaid
agency. Eligible professionals, eligible hospitals, and CAHs may select
an EHR reporting period of a minimum of any continuous 90-day period in
CY 2020 from January 1, 2020 through December 31, 2020.
For CY 2021, we are proposing an EHR reporting period of a minimum
of any continuous 90-day period in CY 2021 for new and returning
participants (eligible hospitals and CAHs) in the Medicare Promoting
Interoperability Program attesting to CMS. We believe that this is an
appropriate length of time for the EHR reporting period because of the
updates to measures and other changes being proposed in this proposed
rule. In addition, a minimum of any continuous 90-day period in CY 2021
would offer stability to the Promoting Interoperability Program after
the changes that were finalized in the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41634 through 41677). We are proposing corresponding changes to
the definitions of ``EHR reporting period'' and ``EHR reporting period
for a payment adjustment year'' at 42 CFR 495.4.
In the July 28, 2010 final rule titled ``Medicare and Medicaid
Programs; Electronic Health Record Incentive Program'' at 75 FR 44319,
we established that, in accordance with section 1903(t)(5)(D) of the
Act, in no case may any Medicaid eligible hospital receive an incentive
after 2021 (see 42 CFR 495.310(f)). Therefore, December 31, 2021 is the
last date that States could make Medicaid Promoting Interoperability
Program payments to Medicaid eligible hospitals (other than pursuant to
a successful appeal related to 2021 or a prior year). For additional
discussion of this issue, we refer readers
[[Page 19555]]
to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41676 through 41677) and
the CY 2019 PFS/QPP final rule (83 FR 59704 through 59706). As
discussed in those rules, the same deadline applies to Medicaid
Promoting Interoperability Program incentive payments to Medicaid
eligible professionals, under section 1903(t)(4)(A)(iii) of the Act and
42 CFR 495.310(a)(2)(v). To help States meet this deadline, in the CY
2019 PFS/QPP final rule (83 FR 59704 through 59706), we changed the CY
2021 EHR and CQM reporting periods for Medicaid eligible professionals.
However, we did not change the 2021 EHR and CQM reporting periods for
Medicaid eligible hospitals in that rule, and are not proposing to do
so in this proposed rule.
That is because, based on attestation data and information from
State Medicaid Health Information Technology Plans regarding the number
of years States disburse Medicaid Promoting Interoperability Program
payments to hospitals, we believe that there will be no hospitals
eligible to receive Medicaid Promoting Interoperability Program
payments in 2021 due to the requirement that, after 2016, eligible
hospitals cannot receive a Medicaid Promoting Interoperability Program
payment unless they have received such a payment for the prior fiscal
year. At this time, we believe that there are no Medicaid-only eligible
hospitals or ``dually-eligible'' hospitals (those that are eligible for
an incentive payment under Medicare for meaningful use of CEHRT and/or
subject to the Medicare payment reduction for failing to demonstrate
meaningful use of CEHRT, and are also eligible to earn a Medicaid
incentive payment for meaningful use of CEHRT) that will be able to
receive Medicaid Promoting Interoperability Program payments in 2021.
We invited comments on whether this belief was accurate in the CY 2019
PFS/QPP rulemaking (83 FR 35873) and received one comment agreeing with
us, but we also stated that we would solicit additional comments on
this issue in a proposed rule that is more specifically related to
hospital payment (83 FR 59705 through 59706). Accordingly, we are again
inviting comments on whether we are correct in thinking that there are
no hospitals that would be able to receive Medicaid Promoting
Interoperability Program payments in 2021. If this is not true, we are
seeking comment on how we should adjust 2021 reporting periods for
Medicaid eligible hospitals in a manner that limits the burden on
hospitals and States.
b. Promoting Interoperability Measures: Actions Must Occur Within the
EHR Reporting Period
Stakeholders have questioned whether the actions in the numerator
for the Medicare Promoting Interoperability Program are limited to the
EHR reporting period or if we allow the numerator to continue to
increment outside of the EHR reporting period but within the calendar
year. We note that we had issued a frequently asked question (FAQ
number 8231 \813\) applicable to the Medicare and Medicare EHR
Incentive Programs. The FAQ stated that, regarding the reporting of
numerators, ``the . . . numerator is not constrained to the EHR
reporting period unless expressly stated in the numerator statement.''
The FAQ went further to state that, for some measures, ``the actions
may reasonably fall outside of the EHR reporting period time frame but
must take place no earlier than the start of the reporting year and no
later than the date of attestation, in order for patients to be counted
in the numerator.'' When we adopted a new scoring methodology and
revised objectives and measures for eligible hospitals and CAHs under
the Medicare Promoting Interoperability Program last year in the FY
2019 IPPS/LTCH PPS final rule (83 FR 41634 through 41677), we neglected
to state whether the policy in the FAQ would still be applicable in
light of the changes to the objectives and measures. As we have
established an EHR reporting period that is a minimum of 90 consecutive
days, eligible hospitals and CAHs may select an EHR reporting period
that ranges from 90 days to the entire CY so that the numerators would
increment over a longer period of time. Therefore, we are proposing
that, beginning with the EHR reporting period in CY 2020, for eligible
hospitals and CAHs that submit an attestation to CMS under the Medicare
Promoting Interoperability Program, both the numerators and
denominators of measures in the Medicare Promoting Interoperability
Program would only increment based on actions that have occurred during
the EHR reporting period that was selected by the eligible hospital or
CAH. We are proposing to codify this proposed policy at Sec.
495.24(e)(1)(ii).
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\813\ https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Downloads/FAQs.pdf.
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However, there is one exception to this proposed policy, and that
is the Security Risk Analysis measure. In the FY 2019 IPPS/LTCH PPS
final rule (83 FR 41644), we finalized that the actions included in the
Security Risk Analysis measure may occur any time during the calendar
year in which the EHR reporting period occurs. We are proposing to
revise Sec. 495.24(e)(4)(iii) to reflect this existing policy for the
Security Risk Analysis measure.
While this proposed policy is reflected in certain denominators and
measure descriptions in the FY 2019 IPPS/LTCH PPS final rule (83 FR
41659 through 41660), we did not apply this policy to all of the
measures. As mentioned above, our intent is to have this policy apply
to all measures of the Medicare Promoting Interoperability Program,
with the Security Risk Analysis measure being the only exception.
Currently, the following measures limit the actions to the EHR
reporting period: E-Prescribing; Query of PDMP; Verify Opioid Treatment
Agreement; Support Electronic Referral Loops by Sending Health
Information; Provide Patients Electronic Access to Their Health
Information; and Support Electronic Referral Loops by Receiving and
Incorporating Health Information. The measures associated with the
Public Health and Clinical Data Exchange Objective do not contain this
limitation.
However, these proposals would not apply to the Medicaid Promoting
Interoperability Program. In the FY 2019 IPPS/LTCH PPS final rule (83
FR 41658 through 41665), we removed several measures from the Medicare
Promoting Interoperability Program that remained in the Medicaid
Promoting Interoperability Program for eligible hospitals. Among those
are measures that we believe it would be appropriate to continue our
current policy of allowing eligible hospitals to count actions in the
numerator that were taken outside the EHR reporting period, but within
the calendar year in which the EHR reporting period occurs and no later
than the date of attestation. For example, Objective 6: Coordination of
Care through Patient Engagement, Measure 1 (view, download, or
transmit) and Measure 2 (secure messaging) allow hospitals to count
actions taken outside of the EHR reporting period in the numerator. We
believe that the patient engagement that this objective promotes is
important throughout the entire year and not just during the hospital's
chosen EHR reporting period. We believe it is a more appropriate policy
to continue to allow eligible hospitals to report actions in the
numerators of these measures that are taken outside of the EHR
reporting period, but within the calendar year in which the EHR
reporting period occurs and no later than the date of attestation.
Therefore, we are not proposing to change to the Medicaid Promoting
Interoperability
[[Page 19556]]
Program policy for either eligible hospitals or eligible professionals.
Unless the numerator of a measure is specifically restricted to the EHR
reporting period in the measure specifications, we will continue to
allow health care providers to include actions taken before, during, or
after the EHR reporting period if the period is less than one full
year; however, these actions must be taken no earlier than the start of
the same year as the EHR reporting period and no later than the date of
attestation.
We do not believe this variation in policies would place burden on
any health care providers. While our current policy gives discretion to
health care providers who attest to a State Medicaid agency to include
actions taken outside of the EHR reporting period, it does not require
them to do so. Eligible hospitals that attest to a State Medicaid
agency may choose to follow the policy proposed in this proposed rule
for eligible hospitals and CAHs that attest to CMS under the Medicare
Promoting Interoperability Program and only include actions taken
within the EHR reporting period. Similarly, eligible professionals that
attest to a State Medicaid agency may choose to follow the policy
adopted for the MIPS Promoting Interoperability performance category.
3. Proposed Changes to Measures Under the Electronic Prescribing
Objective
a. Background
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41648 through
41656), we adopted two opioid measures as for the Electronic
Prescribing objective: (1) Query of Prescription Drug Monitoring
Program (PDMP), which is optional in CY 2019 and required beginning in
CY 2020; and (2) Verify Opioid Treatment Agreement, which is optional
in CY 2019 and 2020. In addition, we stated that we intended to propose
in rulemaking this year that EHR-PDMP integration would be required
beginning in CY 2020 as part of the Query of PDMP measure (83 FR
41652). We believe incorporating a requirement for integration between
PDMPs and the CEHRT utilized by eligible hospitals and CAHs would
advance access to and usability of PDMP data by health care providers
and reduce health care provider burden associated with the actions of
this measure. Integration could reflect a variety of different
approaches for interaction between EHRs and PDMPs that are currently
being pursued in different locations and settings.
We received extensive comments on the Query of PDMP measure and our
intent to require EHR-PDMP integration, as well as on the Verify Opioid
Treatment Agreement measure, from stakeholders both during the comment
period for the FY 2019 IPPS/LTCH PPS proposed rule (83 FR 41648 through
41656), and subsequently through public forums and correspondence.
While this feedback is the main catalyst for our proposals, below,
there have also been significant legislative changes that have the
potential to positively impact the Promoting Interoperability Program,
specifically the Substance Use--Disorder Prevention that Promotes
Opioid Recovery and Treatment for Patients and Communities Act (SUPPORT
for Patients and Communities Act) (Pub. L. 115-271). This legislation
was enacted to address the opioid crisis and affects a wide range of
HHS programs and policies. While this legislation is not the main
reason for our proposals, we believe it may significantly affect the
maturation, requirements, and use of PDMPs and State networks upon
which the Query of PDMP measure is dependent.
In this proposed rule, we are aiming to be responsive to the
comments that we have received from stakeholders since the FY 2019
IPPS/LTCH PPS final rule was published and to take into account certain
aspects of the SUPPORT for Patients and Communities Act that may have
implications for the policy goals of the Promoting Interoperability
Program.
As explained in further detail below, we are proposing to make
certain changes to the Query of PDMP and Verify Opioid Treatment
Agreement measures. In section VIII.D.6.b. of the preamble of this
proposed rule, we are proposing to adopt two opioid clinical quality
measures beginning with the reporting period in CY 2021. In section
VIII.D.7.a. and b. of the preamble of this proposed rule, we are also
requesting information on potential new opioid use disorder (OUD)
prevention and treatment-related measures. We believe the request for
information will help to inform future rulemaking and not only help
prevent and treat substance use disorder, but allow us to adopt
measures that enable flexibility without added burden for health care
providers. We value stakeholders' continued interest in and support for
combating the nation's opioid epidemic.
b. Query of PDMP Measure
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41637 through
41645), we finalized that the Query of PDMP measure is optional and
available for bonus points for CY 2019, and required in CY 2020. We
stated that we would be moving towards requiring EHR-PDMP integration
in CY 2020 (83 FR 41652). We gave eligible hospitals and CAHs
flexibility in implementing this measure, including the flexibility to
query the PDMP in any manner allowed under their State law (83 FR
41649).
However, we have received substantial feedback from health IT
vendors and hospitals that this flexibility presents unintended
challenges, such as the significant burden associated with IT system
design and development needed to accommodate the measure and any future
changes to it. During the FY 2019 IPPS/LTCH PPS proposed rule comment
period (83 FR 41649 through 41653) and after the final rule was
published, these stakeholders stated that it is premature to require
the Query of PDMP measure in CY 2020 especially given the maturation
needed in PDMP development.
We agree with stakeholders that PDMPs are still maturing in their
development and use. As stated by the Substance Abuse and Mental Health
Services Administration (SAMHSA), ``PDMPs operate independently within
states and are not currently linked into a larger system; therefore, no
comprehensive national PDMP prescription data are available. Moreover,
there is no uniform way of accessing PDMP data across states, as data
platforms differ by state.'' \814\
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\814\ https://www.samhsa.gov/capt/sites/default/files/resources/pdmp-overview.pdf.
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Stakeholders also mentioned the challenge posed by the current lack
of integration of PDMPs into the EHR workflow. Historically, health
care providers have had to go outside of the EHR workflow in order to
separately log in to and access the State PDMP. In addition,
stakeholders noted the wide variation in whether PDMP data can be
stored in the EHR. By integrating PDMP data into the health record,
health care providers can improve clinical decision making by utilizing
this information to identify potential opioid use disorders, inform the
development of care plans, and develop effective interventions. ONC is
currently engaged in an assessment to better understand the current
state of policy and technical factors impacting PDMP integration across
States. This assessment is exploring factors like PDMP data
integration, standards and hubs used to facilitate interstate PMDP data
exchange, access permissions, and laws
[[Page 19557]]
and regulations governing PDMP data storage.
In October 2018, the SUPPORT for Patients and Communities Act
became law, signifying an important investment and approach for our
nation in combating the opioid epidemic. The provisions of this law aim
to provide for opioid use disorder prevention, recovery, and treatment
and aim to increase access to evidence-based treatment and follow-up
care included through legislative changes specific to the Medicare and
Medicaid programs. Specifically, with respect to PDMPs, the SUPPORT for
Patients and Communities Act includes new requirements and federal
funding for PDMP enhancement, integration, and interoperability, and
establishes mandatory use of PDMPs by certain Medicaid providers, in an
effort to help reduce opioid misuse and overprescribing, and in an
effort to help promote the overall effective prevention and treatment
of opioid use disorder.
Section 5042(a) of the SUPPORT for Patients and Communities Act
added section 1944 to the Act, titled ``Requirements relating to
qualified prescription drug monitoring programs and prescribing certain
controlled substances.'' This section increases federal Medicaid
matching rates during FY 2019 and 2020 for certain State expenditures
relating to qualified PDMPs administered by States. Under section
1944(b)(1) of the Act, to be a qualified PDMP, a PDMP must facilitate
access by a covered provider to, at a minimum, the following
information with respect to a covered individual, in as close to real-
time as possible: Information regarding the prescription drug history
of a covered individual with respect to controlled substances; the
number and type of controlled substances prescribed to and filled for
the covered individual during at least the most recent 12-month period;
and the name, location, and contact information of each covered
provider who prescribed a controlled substance to the covered
individual during at the least the most recent 12-month period. Under
section 1944(b)(2) of the Act, a qualified PDMP must also facilitate
the integration of the information described in section 1944(b)(1) of
the Act into the workflow of a covered provider, which may include the
electronic system used by the covered provider for prescribing
controlled substances.
Section 1944(f) of the Act establishes, for FY 2019 and FY 2020, a
100 percent Federal Medicaid matching rate for state expenditures to
design, develop, or implement a PDMP that meets the requirements
outlined in section 1944(b)(1) and (2) of the Act, and to make
connections to that PDMP. Section 1944(f)(2) of the Act specifies that,
to qualify for the 100 percent Federal matching rate, a State must have
in place agreements with all contiguous States that, when combined,
enable covered providers in all the contiguous States to access,
through the PDMP, all information described in 1944(b)(1) of the Act.
Section 5042(b) of the SUPPORT for Patients and Communities Act
requires CMS, in consultation with the Centers for Disease Control and
Prevention (CDC), to issue guidance not later than October 1, 2019 on
best practices on the uses of PDMPs required of prescribers and on
protecting the privacy of Medicaid beneficiary information maintained
in and accessed through PDMPs. Further, section 5042(c) of the SUPPORT
for Patients and Communities Act requires that HHS develop and publish,
not later than October 1, 2020, model practices to assist State
Medicaid program operations in identifying and implementing strategies
to utilize data-sharing agreements described in section 1944(b) of the
Act for the following purposes: Monitoring and preventing fraud, waste,
and abuse; and improving health care for individuals enrolled in
Medicaid who transition in and out of Medicaid coverage, who may have
sources of health care coverage in addition to Medicaid coverage, or
who pay for prescription drugs with cash. We note that section 7162 of
the SUPPORT for Patients and Communities Act also supports PDMP
integration as part of the CDC's grant programs aimed at efficiency and
enhancement by States, including improvement in the intrastate and
interstate interoperability of PDMPs.
In addition, the explanatory statement that accompanied Title II of
Division H of the Consolidated Appropriations Act, 2018 (Pub. L. 115-
141),\815\ encouraged the CDC to work with the ONC to enhance the
integration of PDMPs and EHRs. As part of this effort, the CDC and ONC
are collaborating to expand upon previous and leverage input from
current federal efforts to advance and scale PDMP integration with
health IT systems. This collaboration includes testing and refining
standard-based approaches to enable effective integration into clinical
workflows, exploring emerging technical solutions to enhance access and
use of PDMP data, providing technical resources to a variety of
stakeholders to advance and scale the interoperability of health IT
systems and PDMPs, and incorporating policy considerations, as
relevant, to inform the implementation and success of integration
approaches.
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\815\ https://www.govinfo.gov/content/pkg/CREC-2018-03-22/html/CREC-2018-03-22-pt3-PgH2697.htm.
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We understand that there is wide variation across the country in
how health care providers are implementing and integrating PDMP queries
into health IT and clinical workflows, and that it could be burdensome
for health care providers if we were to narrow the measure to allow
only a single workflow. At the same time, we have heard extensive
feedback from EHR developers that incorporating the ability to count
the number of PDMP queries in CEHRT would require more robust
certification specifications and standards. These stakeholders state
that health IT developers may face significant cost burdens under the
current flexibility allowed for health care providers if they either
fully develop numerator and denominator calculations for all the
potential use cases and are required to change the specification at a
later date. Developers have noted that the costs of additional
development will likely be passed on to health care providers without
additional benefit as this development would be solely for the purpose
of calculating the measure rather than furthering the clinical goal of
the measure.
Given the stakeholder concerns discussed above regarding the lack
of integration, the recent enactment of the SUPPORT for Patients and
Communities Act (in particular, its provisions specific to Medicaid
providers and qualified PDMPs), and the activities funded by the CDC,
we believe that additional time is needed to evaluate the changing PDMP
landscape prior to requiring a Query of PDMP measure, or introducing
requirements related to EHR-PDMP integration.
Therefore, we are proposing to make the Query of PDMP measure
optional in CY 2020 and eligible for 5 bonus points, and we are
proposing corresponding changes to the regulations at Sec. Sec.
495.24(e)(5)(ii)(B) and 495.24(e)(5)(iii)(B). Making the measure
optional in CY 2020 would allow time for further integration of PDMPs
and EHRs to minimize the burden on eligible hospitals and CAHs
reporting this measure while still giving hospitals an opportunity to
report on and earn points for the measure. We are proposing that, in
the event we finalize the proposed changes to the Query of PDMP
measure, the e-Prescribing measure would be worth up to 10 points in CY
2020 and subsequent years, and we are proposing corresponding changes
to the regulations at Sec. 495.24(e)(5)(iii)(A).
[[Page 19558]]
In addition, beginning with the EHR reporting period in CY 2019, we
are proposing to remove the numerator and denominator that we
established for the Query of PDMP measure in the FY 2019 IPPS/LTCH PPS
final rule (83 FR 41649 through 41653) and instead require a ``yes/no''
response. Under this proposal, the measure description at Sec.
495.24(e)(5)(iii)(B) and 83 FR 41653 would remain the same, but instead
of submitting numerator and denominator information for the measure,
eligible hospitals and CAHs would submit a ``yes/no'' response during
attestation. A ``yes'' response would indicate that for at least one
Schedule II opioid electronically prescribed using CEHRT during the EHR
reporting period, the eligible hospital or CAH used data from CEHRT to
conduct a query of a PDMP for prescription drug history, except where
prohibited and in accordance with applicable law.
We are proposing these changes to the measure to give us more time
to restructure the measure and develop a robust measure that meets the
needs of both health care providers and other stakeholders. Because
currently there are not standards-based interfaces between CEHRT and
the PDMPs, health care providers must manually track the number of
times that they query the PDMP outside of CEHRT. We are proposing these
changes to reduce the burden on health care providers of having to
manually keep track of information related to the measure and to
mitigate the burden on health IT developers who would otherwise have to
develop the measure's numerator and denominator calculations when we
expect to propose changes to the measure in the near future. Therefore,
health care providers and health IT developers have suggested that,
given the current state, there would be a significant reduction in
burden by allowing health care providers to satisfy the measure by
submitting a ``yes/no'' attestation, rather than reporting a numerator
and denominator.
We are also proposing this change to help reduce the burden of
manually counting on health care providers and the need to mitigate the
burden on developers caused by the developing the measure's numerator
and denominator calculations when the measure is expected to be
modified in the near future. Health care providers and developers have
suggested that, given the current state, there would be a significant
reduction in burden by allowing health care providers to satisfy the
measure by submitting a ``yes/no'' attestation, rather than reporting a
numerator and denominator. We do not believe that these changes would
result in additional costs (time or money) for health care providers,
and instead would reduce the burden of manually tracking information
needed to report on this measures in its current form.
We also are proposing to remove the exclusions associated with the
Query of PDMP measure beginning in CY 2020, and we are proposing
corresponding changes to the regulations at Sec. Sec. 495.24(e)(5)(iv)
and 495.24(e)(5)(v)(B) through (D). For CY 2019, we did not provide
exclusions for the Query of PDMP and Verify Opioid Treatment Agreement
measures because they were optional and eligible for bonus points, and
similarly, we do not believe exclusions would be necessary for the
Query of PDMP measure if we finalize our proposal to make the measure
optional and eligible for bonus points in CY 2020.
Finally, we are proposing to address the scoring of the Query of
PDMP measure. In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41644), we
stated that the measure is optional in CY 2019 and worth ``up to 5
bonus points.'' Our intent, however, was to refer to a full 5 bonus
points; we did not intend for the optional measure to be scored based
on performance in CY 2019. In the FY 2019 IPPS/LTCH PPS proposed rule
(83 FR 20522 through 20523), we provided tables illustrating the
proposed new scoring methodology and a numerical example of how that
scoring methodology would be applied for CY 2019. We referred to these
tables again in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41642). The
table containing the numerical example demonstrates our intent to award
a full 5 bonus points for the measure regardless of the eligible
hospital or CAH's performance rate. We are proposing to revise Sec.
495.24(e)(5)(iii)(B) to better reflect our intended policy that the
Query of PDMP measure is worth a full 5 bonus points (not up to 5 bonus
points) in CY 2019, and in the event we finalize the proposed changes
to the Query of PDMP measure discussed above, in CY 2020 as well. In
the event we finalize those proposed changes, if an eligible hospital
or CAH submits a ``yes'' for this measure, it would earn 5 bonus points
in CY 2019 and 2020.
We also welcome comments on future timing for requiring a measure
that includes EHR-PDMP integration and on the value of the measure for
advancing the effective prevention and treatment of opioid use disorder
especially in relation to the requirements of the SUPPORT for Patients
and Communities Act described above. Specifically, we are interested in
stakeholder comments related to potential opportunities for the
Medicare Promoting Interoperability Program to take into account
States' Medicaid investments and requirements.
We also note that some stakeholders have asked us to define a value
set for controlled substances for the opioid-related measures, Query of
PDMP and Verify Opioid Treatment Agreement. In the FY 2019 IPPS/LTCH
PPS final rule (83 FR 41648 through 41656), for the Query of PDMP and
Verify Opioid Treatment Agreement measures, we defined opioids as
Schedule II controlled substances under 21 CFR 1308.12. We recognize
that some challenges remain related to electronic prescribing of
controlled substances, including more restrictive State laws and lack
of products both for health care providers and pharmacies that include
the necessary functionalities. We anticipate working closely with the
DEA on future technical requirements that can better support
measurement of adoption and use of electronic prescribing of controlled
substances, which may include the definition of a value set related to
such measures. As more information on developing technical requirements
becomes available, we will provide additional information.
As we seek comment and continue to advance this measure, we are
excited about future innovations that may help improve PDMPs and
support the electronic prescribing of controlled substances. We
envision a future state where PDMP data is integrated into the clinical
workflow and where clinicians do not have to access multiple systems to
find and reconcile the information. Rather, all the functions would be
contained within one system. While we may have a long distance to go to
get to this state, we feel that it is an achievable goal for the future
of the Medicare Promoting Interoperability Program.
c. Verify Opioid Treatment Agreement Measure
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41653 through
41656), we finalized the Verify Opioid Treatment Agreement measure as
optional in both CYs 2019 and 2020. Since we proposed this measure (83
FR 20528 through 20530), we have received feedback from stakeholders
that this measure presents significant implementation challenges, leads
to an increase in burden, and does not further interoperability. Below,
we outline some of the ongoing concerns we have heard during the
comment period and since the measure was finalized in the FY 2019 IPPS/
LTCH
[[Page 19559]]
PPS final rule (83 FR 41653 through 41656).
(1) Lack of Certification Standards and Criteria
Stakeholders have continued to express concern regarding the lack
of defined data elements, structure, standards and criteria for the
electronic exchange of opioid treatment agreements and how this impacts
verifying whether there is an opioid treatment agreement to meet this
measure. We acknowledged these concerns in the FY 2019 IPPS/LTCH PPS
final rule (83 FR 41653 through 41656).
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41654), we stated
that there are a number of ways certified health IT may be able to
support the electronic exchange of opioid abuse-related treatment data,
such as the care plan template within the Consolidated-Clinical
Document Architecture (C-CDA). We noted that this information could be
considered as part of an opioid treatment agreement, even though we did
not define the elements of one. However, we understand that while such
standards may include relevant information, the lack of clarity around
a specific standard to support incorporation of an opioid treatment
agreement presents an additional source of burden to health care
providers seeking to report on the measure.
(2) Calculating 30 Cumulative Day Look-Back Period
Another area where stakeholders have expressed concern is how to
calculate 30 cumulative days of Schedule II opioid prescriptions in a
6-month period. One possible solution we offered was to utilize the
NCPDP 10.6 Medication History query. In the FY 2019 IPPS/LTCH PPS final
rule (83 FR 41655), we noted that the Medication History query does not
contain a discrete field for prescription days and relies on third
party data that may not be discrete. Since the FY 2019 IPPS/LTCH PPS
final rule was published, stakeholders have continued to express this
concern and impress upon us that the 30 cumulative day total in a 6-
month look-back period cannot be automatically calculated, requiring
health care providers to engage in a burdensome, manual calculation
process if they wish to report on this measure.
In addition, we have heard concerns over which medications should
be used to determine the 30 cumulative day threshold. For example,
stakeholders were unsure if medications given while a patient is
admitted to the hospital should count towards the 30 cumulative days
and also how as needed, or PRN, medications should be addressed.
Stakeholders have also noted how this measure could present timing
challenges. For example, it may cause patients being discharged on
opioids to be delayed in their discharge to account for the possible
time consuming nature of having to search for an opioid treatment
agreement.
(3) Unintended Burden Caused by Lack of Definition and Standards
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41653), we did not
define what constitutes an opioid treatment agreement. While we
believed that this would allow flexibility for health care providers to
determine which elements they felt were most important to an opioid
treatment agreement, we have heard from stakeholders that the lack of
definition and standards around what would constitute an opioid
treatment agreement has created an unintended burden. Specifically,
some stakeholders felt that we should define an opioid treatment
agreement so that eligible hospitals and CAHs would have a standardized
definition of an opioid treatment agreement and the criteria to make up
an opioid treatment agreement. However, other stakeholders noted that
given the lack of consensus within the industry on what should or
should not be included in an opioid treatment agreement and on the
clinical efficacy of various options for such agreements, that it would
be inappropriate for us to define what should constitute an opioid
treatment agreement at this time.
We have heard from stakeholders that the challenges described above
result in a measure that is vague, burdensome to measure and does not
necessarily offer a clinical value to the health care providers or
support the clinical goal of supporting OUD treatment. Therefore, we
are proposing to remove the Verify Opioid Treatment Agreement measure
from the Promoting Interoperability Program beginning with the EHR
reporting period in CY 2020, and we are proposing corresponding changes
to the regulations at Sec. Sec. 495.24(e)(5)(ii)(B) and
495.24(e)(5)(iii)(C).
While we are proposing to remove the Verify Opioid Treatment
Agreement measure, we believe there may be other opioid measures that
would be more effective in combatting the opioid epidemic, offer value
for health care providers in measuring the impacts of health IT-enabled
resources on OUD prevention and treatment, and engage patients in care
coordination and planning. In section VIII.D.6.b. of the preamble of
this proposed rule, we are proposing to adopt two opioid clinical
quality measures beginning with the reporting period in CY 2021. We
also are seeking public comment on a series of questions regarding new
opioid measures in section VIII.D.7.a. and b. of the preamble of this
proposed rule.
Finally, we are proposing to address the scoring of the Verify
Opioid Treatment Agreement measure. In the FY 2019 IPPS/LTCH PPS final
rule (83 FR 41644) we stated that the measure is optional in CYs 2019
and 2020 and worth ``up to five bonus points.'' As with the Query of
PDMP measure discussed in section VIII.D.3.b. of the preamble of this
proposed rule, above, our intent was to refer to a full 5 bonus points;
we did not intend for the optional Verify Opioid Treatment Agreement
measure to be scored based on performance in CY 2019 or CY 2020.
Accordingly, we are proposing to revise Sec. 495.24(e)(5)(iii)(C) to
better reflect our intended policy that the Verify Opioid Treatment
Agreement measure is worth a full 5 bonus points (not up to 5 bonus
points) in CY 2019, and in the event we do not finalize our proposal to
remove the measure beginning with CY 2020, in CY 2020 as well.
4. Health Information Exchange Objective: Support Electronic Referral
Loops by Receiving and Incorporating Health Information
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41661), we finalized
the Support Electronic Referral Loops by Receiving and Incorporating
Health Information measure. Although the numerator and denominator of
the measure state that CEHRT must be used (83 FR 41661), we
inadvertently omitted a reference to the use of CEHRT from the measure
description in the regulations at Sec. 495.24(e)(6)(ii)(B). In
addition, we stated at 83 FR 41660 that an eligible hospital or CAH
must use the capabilities and standards for CEHRT at 45 CFR
170.315(b)(1) and (b)(2).
In an effort to more clearly capture the previously established
policy, we are proposing to revise the regulations for the Support
Electronic Referral Loops by Receiving and Incorporate Health
Information measure. We are proposing to revise Sec.
495.24(e)(6)(ii)(B) to provide that the electronic summary of care
record must be received using CEHRT and that clinical information
reconciliation for medication, medication allergy, and current problem
list must be conducted using CEHRT.
[[Page 19560]]
5. Proposed Changes to the Scoring Methodology for Eligible Hospitals
and CAHs Attesting to CMS Under the Medicare Promoting Interoperability
Program for an EHR Reporting Period in CY 2020
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41636 through
41668), we finalized under Sec. 495.24(e) a new performance-based
scoring methodology and changes to the objectives and measures for
eligible hospitals and CAHs that submit an attestation to CMS under the
Medicare Promoting Interoperability Program beginning with the EHR
reporting period in CY 2019. For more information, we refer readers to
that final rule (83 FR 41636 through 41668) and Sec. 495.24(e). As
previously discussed in sections VIII.D.3. and 4. of the preamble of
this proposed rule, we are proposing for CY 2020 to: (1) Remove the
Verify Opioid Treatment Agreement measure; (2) continue the Query of
PDMP measure as optional with 5 bonus points; and (3) change the
maximum points available for the e Prescribing measure to 10 points
beginning in CY 2020, in the event we finalize the proposed changes to
the Query of PDMP measure. The tables below reflects the proposed
policy for the objectives, measures, and maximum points available for
the EHR reporting period in CY 2020. The maximum points available do
not include points that would be redistributed in the event that an
exclusion is claimed.
Proposed Performance-Based Scoring Methodology EHR Reporting Period in CY 2020
----------------------------------------------------------------------------------------------------------------
Objective Measure Maximum points
----------------------------------------------------------------------------------------------------------------
Electronic Prescribing.................. e-Prescribing *................ 10 points.
Bonus: Query of PDMP *......... 5 points (bonus).
Health Information Exchange............. Support Electronic Referral 20 points.
Loops by Sending Health
Information.
Support Electronic Referral 20 points.
Loops by Receiving and
Incorporating Health
Information.
Provider to Patient Exchange............ Provide Patients Electronic 40 points.
Access to Their Health
Information.
Public Health and Clinical Data Exchange Choose any two:................ 10 points.
Syndromic Surveillance
Reporting.
Immunization Registry
Reporting.
Electronic Case
Reporting.
Public Health Registry
Reporting.
Clinical Data Registry
Reporting.
Electronic Reportable
Laboratory Result Reporting.
----------------------------------------------------------------------------------------------------------------
Note. The Security Risk Analysis measure is required, but will not be scored.
* Measures with proposed changes to scoring are denoted with an asterisk (*).
6. Clinical Quality Measurement for Eligible Hospitals and Critical
Access Hospitals (CAHs) Participating in the Medicare and Medicaid
Promoting Interoperability Programs
a. Background and Current CQMs
Under sections 1814(l)(3)(A), 1886(n)(3)(A), and
1903(t)(6)(C)(i)(II) of the Act and the definition of ``meaningful EHR
user'' under 42 CFR 495.4, eligible hospitals and CAHs must report on
clinical quality measures (referred to as CQMs) selected by CMS using
CEHRT, as part of being a meaningful EHR user under the Medicare and
Medicaid Promoting Interoperability Programs.
The table below lists the CQMs available for eligible hospitals and
CAHs to report under the Medicare and Medicaid Promoting
Interoperability Programs beginning with the reporting period in CY
2020 (83 FR 41670 through 41671).
CQMs for Eligible Hospitals and CAHs Beginning With CY 2020
------------------------------------------------------------------------
------------------------------------------------------------------------
ED-2........................ Admit Decision Time 0497
to ED Departure
Time for Admitted
Patients (ED-2).
PC-05....................... Exclusive Breast 0480
Milk Feeding.
STK-02...................... Discharged on 0435
Antithrombotic
Therapy.
STK-03...................... Anticoagulation 0436
Therapy for Atrial
Fibrillation/
Flutter.
STK-05...................... Antithrombotic 0438
Therapy by the End
of Hospital Day Two.
STK-06...................... Discharged on Statin 0439
Medication.
VTE-1....................... Venous 0371
Thromboembolism
Prophylaxis.
VTE-2....................... Intensive Care Unit 0372
Venous
Thromboembolism
Prophylaxis.
------------------------------------------------------------------------
b. Proposed Additional CQMs for Reporting Periods Beginning With CY
2021
As we have stated previously in rulemaking (82 FR 38479), we plan
to continue to align the CQM reporting requirements for the Promoting
Interoperability Programs with similar requirements under the Hospital
IQR Program. To do this in a way that would minimize burden, while
maintaining a set of meaningful clinical quality measures and
continuing to incentivize improvement in the quality of care provided
to patients, we are proposing to adopt two new opioid-related clinical
quality measures and are seeking comments on whether we should consider
proposing to adopt the Hybrid Hospital-Wide Readmission (HWR) Measure
with Claims and EHR Data in future rulemaking for the Promoting
Interoperability Program.
In this proposed rule, we are proposing to add the following two
opioid-related CQMs to the Promoting Interoperability Program measure
set beginning with the reporting period in CY 2021: (1) Safe Use of
Opioids--Concurrent Prescribing CQM (NQF #3316e); and (2) Hospital
Harm--Opioid-Related Adverse Events eCQM.
[[Page 19561]]
We are also proposing to adopt these measures under the Hospital IQR
Program and we refer readers to the discussion of the Hospital IQR
Program in sections VIII.A.5.a. of the preamble of this proposed rule
for more information about these proposed measures.
We believe these opioid-related measures are valuable patient
safety measures and are responsive to stakeholder feedback expressing
support for CQMs that focus on higher priority measurement areas and
patient outcomes. While both measures are designed to reduce adverse
events or harms associated with opioid use, the main focus of each
measure's intent is different.
The Safe Use of Opioids--Concurrent Prescribing CQM (NQF #3316e)
seeks to reduce preventable mortality and the costs of adverse events
associated with opioid use by encouraging heath care providers to
identify patients who have concurrent prescriptions for opioids or
opioids and benzodiazepines, and discouraging health care providers
from prescribing these drugs concurrently, whenever possible.
Concurrent prescriptions of opioids or opioids and benzodiazepines
place patients at a greater risk of unintentional overdose due to the
increased risk of respiratory depression. Therefore, we are proposing
to adopt the Safe Use of Opioids--Concurrent Prescribing CQM (NQF
#3316e) beginning with the reporting period in CY 2021. The Safe Use of
Opioids--Concurrent Prescribing CQM seeks to encourage health care
providers to identify patients who have concurrent prescriptions for
opioids or opioids and benzodiazepines, and discourage health care
providers from prescribing these drugs concurrently, whenever possible.
The goal of the measure is to provide a patient-centric measure to help
systems identify and monitor patients at risk, and, ultimately, reduce
the risk of harm to patients across the continuum of care.
The Hospital Harm--Opioid-Related Adverse Events eCQM is designed
to reduce adverse events associated with the administration of opioids
in the hospital setting by assessing the administration of naloxone as
an indicator of harm. Implementation of the measure can lead to safer
patient care by incentivizing hospitals to track and improve their
monitoring and response to patients administered opioids during
hospitalization, and to avoid harm, such as respiratory depression,
which can lead to brain damage and death. This EHR-based measure
focuses, specifically, on in-hospital opioid-related adverse events, by
requiring evidence of hospital opioid administration, prior to the
naloxone administration, during the first 24 hours after hospital
arrival. This ensures that the harm was hospital-acquired and not due
to an overdose that happened outside of the hospital. We believe that
this measure will provide hospitals with reliable and timely
measurement of their opioid-related adverse event rates, which is a
high-priority measurement area, and therefore we are proposing to adopt
the Hospital Harm--Opioid-Related Adverse Events eCQM beginning with
the reporting period in CY 2021.
We acknowledge that some stakeholders have expressed concern that
some providers could withhold the use of naloxone for patients who are
in respiratory depression, believing that may help those providers
avoid poor performance on the proposed Hospital Harm--Opioid-Related
Adverse Events eCQM (83 FR 41591). Therefore, we are soliciting public
comment on the potential for this measure to disincentivize the
appropriate use of naloxone in the hospital setting or withholding
opioids when they are medically necessary in patients requiring
palliative care or who are at end of life out of an overabundance of
caution.
c. Request for Information (RFI) Regarding Potential Adoption of the
Hybrid Hospital-Wide Readmission (HWR) Measure With Claims and EHR Data
(Hybrid HWR Measure) for Reporting Periods Beginning With CY 2023
We refer readers to section VIII.A.5.b. of the preamble of this
proposed rule for a discussion of our proposals under the Hospital IQR
Program to adopt the Hybrid Hospital-Wide Readmission (HWR) Measure
with Claims and EHR Data, beginning with the July 1, 2023 through June
30, 2024 reporting period. The Hybrid HWR measure is designed to
capture all unplanned readmissions that arise from acute clinical
events requiring urgent re-hospitalization within 30 days of discharge,
and it provides a facility-wide picture of this aspect of care quality
for Medicare fee-for-service (FFS) beneficiaries who are 65 years or
older and hospitalized in non-federal hospitals. In addition, the
measure reports a single summary risk-standardized readmission rate
(RSRR) of unplanned, all-cause readmission within 30 days of hospital
discharge for any eligible condition, and indicates the hospital-level
standardized readmission ratios (SRR) for each category. The discharge
condition categories or procedure categories for this measure are: (1)
Surgery/gynecology; (2) general medicine; (3) cardiorespiratory; (4)
cardiovascular; and (5) neurology.
We are seeking comment on whether we should consider proposing to
adopt the Hybrid HWR CQM in future rulemaking for the Promoting
Interoperability Program starting with the reporting period in CY 2023.
We note that the Hospital IQR Program, as discussed in sections
VIII.A.5.b. and VIII.A.10.e. of the preamble of this proposed rule, is
proposing that this Hybrid HWR measure be required with the reporting
period from July 1, 2023 through June 30, 2024. The 12-month
measurement period that runs from July 1 through June 30 is consistent
with the calculation of the Hospital IQR Program's current HWR claims-
only measure; however, it does not align with the reporting period for
CQMs, which is one self-selected calendar quarter.
d. Proposed CQM Reporting Periods and Criteria for the Medicare and
Medicaid Promoting Interoperability Programs in CY 2020, 2021, and 2022
(1) Proposed CQM Reporting Periods and Criteria in CY 2020 and 2021
For CY 2020 and 2021, we are proposing generally the same CQM
reporting periods and criteria as established in the FY 2019 IPPS/LTCH
PPS final rule for the Medicare and Medicaid Promoting Interoperability
Programs in CY 2019 (83 FR 41671). We are proposing that the CQM
reporting period and criteria under the Medicare and Medicaid Promoting
Interoperability Programs for eligible hospitals and CAHs reporting
CQMs electronically would be as follows: For eligible hospitals and
CAHs participating only in the Promoting Interoperability Program, or
participating in the both Promoting Interoperability Program and the
Hospital IQR Program, report one, self-selected calendar quarter of
data for four self-selected CQMs from the set of available CQMs. We are
proposing the following reporting criteria for eligible hospitals and
CAHs that report CQMs by attestation under the Medicare Promoting
Interoperability Program as a result of electronic reporting not being
feasible--report on all CQMs from the set of available CQMs. For
eligible hospitals and CAHs that report CQMs by attestation, we
previously established a CQM reporting period of the full CY
(consisting of 4 quarterly data reporting periods) (80 FR 62893).
We are proposing a submission period for the Medicare Promoting
Interoperability Program that would be the 2 months following the close
of the calendar year, ending February 28, 2021
[[Page 19562]]
(for the CQM reporting period in CY 2020) and February 28, 2022 (for
the CQM reporting period in CY 2021). With regard to the Medicaid
Promoting Interoperability Program, we provide States with the
flexibility to determine the method of reporting CQMs (attestation or
electronic reporting) and the submission periods for reporting CQMs,
subject to prior approval by CMS.
We believe that continuing the same CQM reporting and submission
requirements is appropriate because it continues to offer hospitals
reporting flexibility and does not increase the information collection
burden on data submitters. In addition, we believe that alignment with
the requirements of the Hospital IQR program reduces burden for
hospitals as they may report once and fulfill the requirements of both
programs.
(2) Proposed CQM Reporting Periods and Criteria in CY 2022
For CY 2022, we are proposing that the CQM reporting period and
criteria under the Medicare Promoting Interoperability Program for
eligible hospitals and CAHs reporting CQMs electronically would be as
follows--for eligible hospitals and CAHs participating only in the
Promoting Interoperability Program or participating in both the
Promoting Interoperability Program and in the Hospital IQR Program,
report one, self-selected calendar quarter of data for: (a) Three self-
selected CQMs from the set of available CQMs; and (b) the proposed Safe
Use of Opioids--Concurrent Prescribing CQM (NQF #3316e), for a total of
four CQMs. Under this proposal, we would not change the number of CQMs
that hospitals must report while ensuring that health care providers
still have meaningful choice among the set of available CQMs. We are
proposing the following reporting criteria for eligible hospitals and
CAHs that report CQMs by attestation under the Medicare Promoting
Interoperability Program as a result of electronic reporting not being
feasible--report on all CQMs from the set of available CQMs. For
eligible hospitals and CAHs that report CQMs by attestation, we
previously established a CQM reporting period of the full CY
(consisting of 4 quarterly data reporting periods) (80 FR 62893).
We are proposing that the submission period for the Medicare
Promoting Interoperability Program would be the 2 months following the
close of the calendar year 2022, ending February 28, 2023.
We also refer readers to section VIII.A.10.d. of the preamble of
this proposed rule for the reporting and submission requirements
associated with the proposal to add the Safe Use of Opioids--Concurrent
Prescribing CQM (NQF #3316e) to the measure set for the Hospital IQR
Program.
e. CQM Reporting Form and Method Requirements for the Medicare
Promoting Interoperability Program in CY 2020
(1) Requiring EHR Technology To Be Certified to All Available CQMs
We are proposing to continue requiring that EHRs be certified to
all available CQMs adopted for the Medicare Promoting Interoperability
Program for CY 2020 and subsequent years. This policy was previously
finalized in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38483 through
38485) for CY 2018 and in the FY 2019 IPPS/LTCH PPS final rule (83 FR
41671 through 41672) for CY 2019. We require this so that eligible
hospitals and CAHs have flexibility in selecting the CQMs to report
that best reflect their patient populations and reporting capabilities.
In addition, this requirement would produce greater certainty for
eligible hospitals and CAHs that their EHR systems would be capable of
accurately calculating the particular CQMs they select to report to
CMS. Because this is the current policy for the Hospital IQR and
Medicare Promoting Interoperability Programs, vendors and health care
providers should be familiar with this requirement, and their EHR
systems should already be certified to all currently available CQMs.
We refer readers to section VIII.A.10.d.(5)(B) of the preamble of
this proposed rule for a similar proposal for hospitals under the
Hospital IQR Program.
(2) Other CQM Form and Method Requirements
As we stated in the FY 2016 IPPS/LTCH PPS final rule (80 FR 49759
through 49760), for the reporting periods in 2016 and future years, we
are requiring QRDA-I for CQM electronic submissions for the Medicare
EHR Incentive (now Promoting Interoperability) Program. As noted in the
FY 2016 IPPS/LTCH PPS final rule (80 FR 49760), States would continue
to have the option, subject to our prior approval, to allow or require
QRDA-III for CQM reporting.
The form and method of electronic submission are further explained
in subregulatory guidance and the certification process. For example,
the following documents are updated annually to reflect the most recent
CQM electronic specifications: The CMS Implementation Guide for QRDA;
program specific performance calculation guidance; and CQM electronic
specifications and guidance documents. These documents are located on
the eCQI Resource Center web page at: https://ecqi.healthit.gov/. For
further information on CQM reporting, we refer readers to the EHR
Incentive Program (now Promoting Interoperability Program) website
where guides and tip sheets are located at: http://www.cms.gov/ehrincentiveprograms.
For the reporting period in CY 2020, we are proposing the following
for CQM submission under the Medicare Promoting Interoperability
Program:
Eligible hospitals and CAHs participating in the Medicare
Promoting Interoperability Program (single program participation)--
electronically report CQMs through QualityNet Portal.
Eligible hospital and CAH options for electronic reporting
for multiple programs (that is, Promoting Interoperability Program and
Hospital IQR Program participation)--electronically report through
QualityNet Portal.
As noted in the 2015 EHR Incentive Programs final rule (80 FR
62894), starting in 2018, eligible hospitals and CAHs participating in
the Medicare EHR Incentive Program must electronically report CQMs
where feasible; and attestation to CQMs will no longer be an option
except in certain circumstances where electronic reporting is not
feasible. For the Medicaid Promoting Interoperability Program, States
continue to be responsible for determining whether and how electronic
reporting of CQMs would occur, or if they wish to allow reporting
through attestation. Any changes that States make to their CQM
reporting methods must be submitted through the State Medicaid Health
IT Plan (SMHP) process for CMS review and approval prior to being
implemented.
For CY 2020, we are proposing to continue our policy regarding the
electronic submission of CQMs, which requires the use of the most
recent version of the CQM electronic specification for each CQM to
which the EHR is certified. For the CY 2020 electronic reporting of
CQMs, this means eligible hospitals and CAHs are required to use the
2018 CQM specifications update (published in May 2018) and any
applicable addenda available on the eCQI Resource Center web page at:
https://ecqi.healthit.gov/. As noted in the FY 2019 IPPS/LTCH PPS final
rule (83 FR 41635 through 41636), participants are required to use
[[Page 19563]]
2015 Edition CEHRT for the Medicare and Medicaid Promoting
Interoperability Programs, beginning with the EHR reporting period in
CY 2019. We reiterate that an EHR certified for CQMs under the 2015
Edition certification criteria does not have to be recertified each
time it is updated to a more recent version of the CQMs (82 FR 38485).
(3) Proposed Modification to Reporting Methods for CQMs Beginning With
the Reporting Period in CY 2023
We currently allow eligible hospitals and CAHs to report CQMs by
attestation for the Medicare Promoting Interoperability Program only in
certain circumstances where electronic reporting is not feasible (80 FR
62893 through 62894). Beginning with the CQM reporting period in CY
2023, we are proposing to eliminate attestation as a method for
reporting CQMs for the Medicare Promoting Interoperability Program and
instead require all eligible hospitals and CAHs to submit their CQM
data electronically through the reporting methods available for the
Hospital IQR Program. We believe that data submitted electronically is
preferable so that we can use the data to analyze trends across
hospitals and further refine quality data in the future. Limiting the
available reporting methods to electronic submission would enable us to
have a more robust data set so that we can ensure that hospitals are
delivering effective, safe, efficient, patient-centered, equitable, and
timely care. Also, we believe that we are allowing an adequate
transition period for eligible hospitals and CAHs to migrate to
electronic submission.
7. Future Direction of the Promoting Interoperability Program
a. Request for Information (RFI) on Potential Opioid Measures for
Future Inclusion in the Promoting Interoperability Program
In the past, the Promoting Interoperability Program measures
focused on very general process focused actions supported by health IT.
In the Medicare and Medicaid Programs; Electronic Health Record
Incentive Program--Stage 3 and Modifications to Meaningful Use in 2015
through 2017 final rule (80 FR 62766 through 62768), we sought to
expand the potential for Medicare and Medicaid Promoting
Interoperability Program measures to include more complex measures and
closer relationships to high priority health outcomes.
In this RFI, we are seeking comment on Promoting Interoperability
program measures in addition to the CQMs we are proposing to adopt in
section VIII.D.6.b. of the preamble of this proposed rule ((1) Safe Use
of Opioids--Concurrent Prescribing CQM (NQF #3316e); and (2) Hospital
Harm--Opioid-Related Adverse Events eCQM) that might be relevant to
specific clinical priorities or goals related to addressing OUD
prevention and treatment. As the Query of PDMP measure matures, we
believe it will be essential in improving prescribing practices. As
outlined in section VIII.D.3.c. of the preamble of this proposed rule,
stakeholders indicated that the Verify Opioid Treatment Agreement
measure presented significant implementation challenges for eligible
hospitals and CAHs. Therefore, we are seeking comment on potential new
measures for OUD prevention and treatment that could be included in
future years of the Promoting Interoperability Program. We welcome all
comments, but we are seeking comment specifically on possible OUD
prevention and treatment measures that include the following
characteristics:
Are applicable to all hospital settings (for example,
rural, urban, small hospitals, large hospitals);
Are represented by a measure description, numerator/
denominator or ``yes/no'' attestation statement, and possible
exclusions;
Include evidence of positive impact on outcome-focused
improvement activities, and the opioid crisis overall;
Leverage the capabilities of CEHRT, including: automatic
calculation and reporting of numerator, denominator, exclusions and
exceptions, and timing elements to reduce quality measurement and
reporting burdens to the greatest extent possible;
Are based on well-defined clinical concepts, measure logic
and timing elements that can be captured by CEHRT in standard clinical
workflow and/or routine business operations. Well-defined clinical
concepts include those that can be discretely represented by available
clinical and/or claims vocabularies such as SNOMED CT, LOINC, RxNorm,
ICD-10 or CPT; and
Align with clinical workflows in such a way that data used
in the calculation of the measure is collected as part of a standard
workflow and does not require any additional steps or actions by the
health care provider.
b. Request for Information (RFI) on NQF and CDC Opioid Quality Measures
We also are specifically seeking public comment on the development
of potential measures for consideration for the Promoting
Interoperability Program that are based on existing efforts to measure
clinical and process improvements specifically related to the opioid
epidemic, including the opioid quality measures endorsed by the
National Quality Forum (NQF) and the CDC Quality Improvement (QI)
opioid measures discussed below. The NQF measures represent a reference
point for evaluating opioid prescribing behaviors based on measures
that have undergone the rigorous NQF measure endorsement process. The
CDC guidelines ``encourage careful and selective use of opioid therapy
in the context of managing chronic pain through . . . an evidence-based
prescribing guideline.'' \816\ The guidelines have led to the
development of CDC measures on prescribing practices on which are
seeking comment. We believe that these measures may help participants
understand the relationship between the measure description and the use
of health IT to support the actions of the measures.
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\816\ https://www.cdc.gov/drugoverdose/pdf/prescribing/CDC-DUIP-QualityImprovementAndCareCoordination-508.pdf.
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For example, the measures may describe a clinical concept, such as
the CDC Measure 12: Counsel on Risks and Benefits Annually. The actions
for this activity can be supported by CEHRT through the use of
standards to record key health information for the patient and to
identify which patients should be included in the denominator based on
information in the medication list, information gained through
medication reconciliation of data received through health information
exchange with another health care provider, and/or information
incorporated after a query of a PDMP is completed. The actions for the
numerator could include leveraging CEHRT to provide patient-specific
education, to capture or record Patient-Generated Health Data (PGHD),
to engage in secure messaging with the patient and ensure the patient
is engaging with their record through a patient portal or an API.
We believe that the clinical actions identified within both the NQF
quality measures and the CDC QI opioid measures can be supported by the
standards and functionalities of certified health IT and we welcome
public comment on the specific use cases for health IT implementation
for the potential measure actions. We recognize that modifications to
the NQF and CDC measures may be necessary to make the measures as
applicable as possible to all participants of the Promoting
Interoperability Program, and are
[[Page 19564]]
seeking comment on any modifications that would be necessary. In
addition, we note that there is some overlap between some of the NQF
quality measures and the CDC QI opioid measures and are seeking comment
on whether there are ways in which the two sets of measures could be
correlated to support potential new measures of the meaningful use of
health IT for the Promoting Interoperability Programs. Finally, we are
seeking comment on which measures might best advance the implementation
and use of interoperable health IT and encourage information exchange
between care teams and with patients.
(1) NQF Quality Measures
Three NQF-endorsed quality measures stewarded by the Pharmacy
Quality Alliance (PQA) to evaluate patients with prescriptions for
opioids in combination with benzodiazepines, at high-dosage, or from
multiple prescribes and pharmacies. Each measure was evaluated and
recommended for endorsement by the NQF's Patient Safety Standing
Committee \817\ and endorsed by the Consensus Standards Approval
Committee.\818\ These measures, NQF #2940, #2950, and #2951 were
recommended by the NQF Measure Application Partnership for inclusion on
the December 2018 Measures Under Consideration List for the Medicare
Shared Savings Program. (As noted in section VIII.D.6.b. of the
preamble of this proposed rule, we are also proposing to add two
opioid-related CQMs to the Promoting Interoperability Program CQM
measure set beginning with the reporting period in CY 2021, including
the NQF-endorsed measure, Safe Use of Opioids--Concurrent Prescribing
(NQF #3316e), a CQM.) We are seeking comment on the following three NQF
measures for possible inclusion in the Promoting Interoperability
Program and any modifications that may be necessary to maximize their
use in the Promoting Interoperability Program:
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\817\ https://www.qualityforum.org/News_And_Resources/Press_Releases/2017/NQF_Statement_on_Endorsement_of_Opioid_Patient_Safety_Measures.aspx.
\818\ Ibid.
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Use of Opioids at High Dosage in Persons Without Cancer
(NQF #2940).
Use of Opioids from Multiple Providers in Persons Without
Cancer (NQF #2950).
Use of Opioids from Multiple Providers and at High Dosage
in Persons Without Cancer (NQF #2951).
We believe these measures relate to activities that hold promise in
combatting the opioid epidemic and can be supported using CEHRT to
complete the actions of the measures and are seeking comment on the
best method to incorporate the description of the use of technology
into measure guidance if these measures were considered for use by
participants. For example, the actions related to the Use of Opioids
from Multiple Providers in Persons Without Cancer (NQF #2950) measure
could include using health IT to electronically prescribe the
medication, to query a PDMP, to identify other care team members, to
conduct medication reconciliation based on information received through
health information exchange with other health care providers, and
recording key health information in a structured format. Additional
information regarding each measure can be found using NQF's Quality
Positioning System at: http://www.qualityforum.org/QPS/QPSTool.aspx.
(2) CDC Quality Improvement (QI) Opioid Measures
We believe there may be promise in the CDC QI opioid measures based
on the prescribing best practices found in Appendix B in the CDC
document ``Quality Improvement and Care Coordination: Implementing the
CDC Guideline for Prescribing Opioids for Chronic Pain'' (Implementing
the CDC Prescribing Guideline).\819\
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\819\ https://www.cdc.gov/drugoverdose/pdf/prescribing/CDC-DUIP-QualityImprovementAndCareCoordination-508.pdf.
---------------------------------------------------------------------------
CDC developed its Implementing the CDC Prescribing Guideline
document to help health care providers and systems integrate the CDC
Prescribing Guideline \820\ and the associated QI opioid measures found
in the Implementing the CDC Prescribing Guideline document into their
clinical practices. The CDC developed 16 QI opioid measures to align
with the recommendations in the CDC Prescribing Guideline and to
improve opioid prescribing. These measures are intended to provide
healthcare systems tracking of their implementation of the recommended
practices. We believe this is generally consistent with the to the
objective and measure concept of the Promoting Interoperability Program
where the recommendation in the CDC Prescribing Guideline is the
overarching objective and the QI opioid measure is a description of the
patient population focus (denominator) and the desired action
(numerator). The Implementing the CDC Prescribing Guideline document
also includes practice-level strategies to help organize and improve
the management and coordination of long-term opioid therapy:
---------------------------------------------------------------------------
\820\ https://www.cdc.gov/mmwr/volumes/65/rr/rr6501e1.htm.
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Using an interdisciplinary team approach.
Establishing practice policies and standards.
Using EHR data to develop registries and track QI opioid
measures.
These measures address treatment guidelines for both initial
treatment practices and long-term treatment and outcomes. Examples of
measures related to short term OUD prevention and treatment activities
include:
CDC Measure 2: Check PDMP Before Prescribing Opioids.
CDC Measure 4: Evaluate Within Four Weeks of Starting
Opioids.
Examples of measures related to long term OUD prevention and
treatment activities include:
CDC Measure 11: Check PDMP Quarterly.
CDC Measure 12: Counsel On Risks and Benefits Annually.
The data sources from these measures include State PDMP data or the
practice EHR data field.
The CDC and the Agency for Healthcare Research and Quality are also
developing electronic clinical decision support tools which can provide
real-time clinical decision support (CDS) for some of the best
practices included in the Implementing the CDC Prescribing Guideline
document.\821\ In the context of quality improvement measures,
components of these CDS artifacts, including the clinical conditions or
prescribed medications that trigger the decision support are the same
well-defined clinical concepts required for developing quality
improvement measures for the Promoting Interoperability Program related
to OUD prevention and treatment. This creates a tight linkage between
the guidelines, the recommended clinical actions based on the
guidelines, and the improved outcomes based on the recommended clinical
actions.
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\821\ https://cds.ahrq.gov/cdsconnect/topic/opioids-and-pain-management.
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Therefore, we are seeking comment on which of the 16 CDC QI opioid
measures have value for potential consideration for the Promoting
Interoperability Program. We are further seeking comment on whether we
should consider a different type of measurement concept for the OUD
prevention and treatment measures, such as reporting on a set of cross
cutting activities and measures to earn credit in the Promoting
Interoperability Program (for example, a set of one CDS,
[[Page 19565]]
the related CDC QI opioid measure, and a potentially relevant clinical
quality measure).
We refer readers to Implementing the CDC Prescribing Guideline
document and the related measures available in Appendix B of that
document available at: https://www.cdc.gov/drugoverdose/pdf/prescribing/CDC-DUIP-QualityImprovementAndCareCoordination-508.pdf.
c. Request for Information (RFI) on a Metric To Improve Efficiency of
Providers Within EHRs
One of the benefits of adopting EHRs is increasing the efficiency
of health care processes and generating cost savings by eliminating
time-consuming paper-based processes. Through the use of EHRs, health
care providers are able to automate administrative aspects of delivery
system management such as coding and scheduling, easily locate patient
information in electronic charts, and streamline communications with
other health care providers through electronic means.
However, research also points to variable results from the
implementation of health IT across practice settings, suggesting health
IT adoption is not a universal remedy for inefficient practice.
Stakeholders continue to describe ways in which the potential benefits
of EHRs have not been fully realized, pointing to non-optimized
electronic workflows and poor system design that can increase rather
than reduce administrative burden, contributing to physician
burnout.\822\ We believe in the value of EHRs in today's health care
environment and understand the way forward must include reductions in
persistent sources of technology-related burden, and more effective use
of technology to achieve true efficiency gains.
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\822\ https://www.ahrq.gov/professionals/clinicians-providers/ahrq-works/burnout/index.html.
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In November 2018, ONC released the draft report ``Strategy on
Reducing Regulatory and Administrative Burden Relating to the Use of
Health IT and EHRs,'' \823\ as required by section 4001 of the 21st
Century Cures Act. In the draft report, ONC describes a variety of
factors that may contribute to EHR-related burden, and provides draft
recommendations for how HHS as well as other stakeholders may be able
to address these factors. Specifically, the draft report discusses
processes where adoption of improved electronic processes could reduce
EHR-related burden, such as processes related to prior authorization
requests. The draft report also discusses EHR usability and design
challenges which may contribute to EHR-related burden, and identifies
best practices for design, as well as a variety of emerging system
features which may improve efficiency in health IT usage. We believe
further adoption of more efficient workflows and technologies such as
those identified in the draft report will help health care providers
with overall improvements in patient care and interoperability, and we
are seeking comment on how such implementation of such processes can be
effectively measured and encouraged as part of the Promoting
Interoperability Program.
---------------------------------------------------------------------------
\823\ https://www.healthit.gov/sites/default/files/page/2018-11/Draft%20Strategy%20on%20Reducing%20Regulatory%20and%20Administrative%20Burden%20Relating.pdf.
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We are also interested in comments regarding how to measure and
incentivize efficiency as it relates to the meaningful use of CEHRT and
the furthering of interoperability. In 2017, the NQF released ``A
Measurement Framework to Assess Nationwide Progress Related to
Interoperable Health Information Exchange to Support the National
Quality Strategy,'' \824\ which included discussion of measure concepts
of productivity and efficiency, which can result from the use of health
IT, specifically health information exchange. For instance, the NQF
report identifies a measure concept for the ``percentage of reduction
of duplicate labs and imaging over time,'' which could capture the
impact of electronic availability of imaging studies on duplicative
studies that are often conducted when health care providers do not have
the ability to locate an existing study. However, we recognize that
there are challenges associated with tying such measures of economic
efficiency to a single factor such as electronic workflow
improvements.\825\
---------------------------------------------------------------------------
\824\ https://www.qualityforum.org/Publications/2017/09/Interoperability_2016-2017_Final_Report.aspx.
\825\ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2699907/.
---------------------------------------------------------------------------
Consistent with our commitment to reducing administrative burden,
increasing efficiencies, and improving beneficiary experience via the
Patients over Paperwork initiative,\826\ we are seeking stakeholder
feedback on a potential metric to evaluate health care provider
efficiency using EHRs. Specifically, we are looking at the following
questions:
---------------------------------------------------------------------------
\826\ https://www.cms.gov/About-CMS/story-page/patients-over-paperwork.html.
---------------------------------------------------------------------------
What do stakeholders believe would be useful ways to
measure the efficiency of health care processes due to the use of
health IT? What are measurable outcomes demonstrating greater
efficiency in costs or resource use that can be linked to the use of
health IT-enabled processes? This includes measure description,
numerator/denominator or ``yes/no'' reporting, and exclusions.
What are specific technologies, capabilities, or system
features (beyond those currently addressed in the Promoting
Interoperability Program) that can increase the efficiency of health
care provider interactions with technology systems, for instance,
alternate authentication technologies that can simplify health care
provider logon? How could we reward health care providers for adoption
and use of these technologies?
What are key administrative processes that could benefit
from more efficient electronic workflows, for instance, conducting
prior authorization requests? How could we measure and reward health
care providers for uptake of more efficient electronic workflows?
d. Request for Information (RFI) on Including Medicare Promoting
Interoperability Program Data on the Hospital Compare Website
As the Medicare Promoting Interoperability Program continues to
evolve, we are seeking comment on posting Medicare Promoting
Interoperability Program measure(s) on the Hospital Compare website.
Section 1886(n)(4)(B) of the Act requires the Secretary to post in
an easily understandable format a list of the names and other relevant
data, as determined appropriate by the Secretary, of eligible hospitals
and CAHs who are meaningful EHR users under the Medicare FFS program,
on a CMS website. In addition, section 1886(n)(4)(B) of the Act
requires the Secretary to ensure that an eligible hospital or CAH has
the opportunity to review the other relevant data that are to be made
public with respect to the eligible hospital or CAH prior to such data
being made public. We believe an eligible hospital or CAH's performance
rate on one or more of the Medicare Promoting Interoperability Program
measures would constitute other relevant data because it would help
consumers make informed decisions regarding their health care team,
such as knowing whether and to what extent their health care provider
is involved in health information exchange or providing patients with
electronic access to their health information.
As we considers posting information regarding the Medicare
Promoting Interoperability Program measures in
[[Page 19566]]
the future, we are seeking comment on the following:
Of the six required measures and one bonus measure that
would apply for an EHR reporting period in CY 2020, how many and which
ones should we consider posting?
What process should be in place to allow eligible
hospitals and CAHs the opportunity to review the data prior to
publication? This includes comment on how many days the preview period
should be for eligible hospitals and CAHs to review data prior to
publication and a correction process for those who may have identified
an error in their data.
We are seeking comment on posting the data on the our
Hospital Compare website, found at: www.medicare.gov/hospitalcompare.\827\
---------------------------------------------------------------------------
\827\ https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/hospitalqualityinits/hospitalcompare.html.
---------------------------------------------------------------------------
e. Request for Information (RFI) on the Provider to Patient Exchange
Objective
In March 2018, the White House Office of American Innovation and
the CMS Administrator announced the launch of MyHealthEData, and our
role in improving patient access and advancing interoperability. As
part of the MyHealthEData initiative, we are taking a patient-centered
approach to health information access and moving to a system in which
patients have immediate access to their computable health information
and can be assured that their health information will follow them as
they move throughout the health care system from provider to provider,
payer to payer. To accomplish this, we have launched several
initiatives related to data sharing and interoperability to empower
patients and encourage plan and provider competition. One example is
our overhaul of the EHR Incentive Program and Advancing Care
Information performance category under the MIPS to create the new
Promoting Interoperability programs, which put a heavy emphasis on
patient access to their health information through the Provide Patients
Electronic Access to Their Health Information measure.
Through the Provide Patients Electronic Access to Their Health
Information measure, we are ensuring that patients have access to their
information through any application of their choice that is configured
to meet the technical specifications of the Application Programing
Interface (API) in the eligible hospital or CAH's CEHRT. To make these
APIs fully useful to patients, they should provide immediate access to
updated information whenever the patient needs that information, should
be always available, configured using standardized technology and
contain the information a patient needs to make informed decisions
about their care.
In the FY 2019 IPPS/LTCH PPS proposed rule (83 FR 20537 through
20538), we introduced a potential future Promoting Interoperability
Program concept which explored creating a set of priority health IT
activities that would serve as alternatives to the traditional
Promoting Interoperability Program measures. We specifically noted that
the 21st Century Cures Act requires HHS to take steps to enable the
electronic sharing of health information, including helping to ensure
interoperability for health care providers and settings across the care
continuum. We requested public comment on whether eligible hospitals
and CAHs should earn credit by attesting to health IT or
interoperability activities in lieu of reporting on specific measures.
We identified specific health IT activities and sought public comment
on those and additional activities that would add value for patients
and health care providers, are relevant to patient care and clinical
workflows, support alignment with existing objectives, promote
flexibility, are feasible for implementation, are innovative in the use
of health IT, and promote interoperability. We received feedback in
support of this future concept.
One such activity we specifically requested comment on was a health
IT activity in which eligible hospitals and CAHs could obtain credit in
the Promoting Interoperability Program if they maintain an ``open
API,'' or standards-based API, which allows patients to access their
health information through a preferred third party application. An API
can be thought of as a set of commands, functions, protocols, or tools
published by one software developer (``developer A'') that enables
other software developers to create programs (applications or ``apps'')
that can interact with developer A's software without needing to know
the internal workings of developer A's software, all while maintaining
consumer privacy data standards. This is how API technology enables the
seamless user experiences associated with applications familiar from
other aspects of many consumers' daily lives, such as travel and
personal finance. Standardized, transparent, and pro-competitive API
technology can enable similar benefits to consumers of health care
services.\828\
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\828\ ONC has made available a succinct, non-technical overview
of APIs in context of consumers' access to their own medical
information across multiple providers' EHR systems, which is
available at the HealthIT.gov website at: https://www.healthit.gov/api-education-module/story_html5.html.
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We received feedback from several commenters regarding concerns
that an ``open'' API may open the door to patient data without
security, leaving eligible hospitals and CAHs' EHR systems open for
cyber-attacks. We wish to note, however, that the term ``open API''
does not imply that any and all applications or application developers
would have unfettered access to individuals' personal or sensitive
information nor would it allow for any reduction in the required
protections for privacy and security of patient health information. In
addition, with respect to patient access, a patient will need to
authenticate themselves to a health care organization that is the
steward of their data (for example, username and password) and the
access provided to an app will be for that one patient. The overall
HIPAA Security Rule and other cybersecurity obligations that apply to
HIPAA Covered Entities remain the same and would need to be applied to
an API in the same way they are currently applied to any and all other
interfaces a health care organization deploys in production.
ONC's 21st Century Cures Act proposed rule (84 FR 7424 through
7610) includes new proposals that focus on how certified health IT can
use APIs to allow health information to be accessed, exchanged, and
used without special effort through the use of APIs or successor
technology or standards, as provided for under applicable law. For
instance, ONC has proposed to adopt a new criterion for a standards-
based API at Sec. 170.315(g)(10). This standards-based API criterion
would replace the existing API criterion with one that requires the use
of the HL7 Fast Healthcare Interoperability Resources (FHIR[supreg])
standard. ONC has also proposed a series of requirements for the
standards-based API that would improve interoperability by focusing on
standardized, transparent, and pro-competitive API practices.
ONC has proposed to make the standards-based API criterion part of
the 2015 Edition base EHR definition, which would ensure that this
functionality is ultimately included in the CEHRT definition required
for participation in the Promoting Interoperability Program. If
finalized, ONC has proposed that health IT
[[Page 19567]]
developers would have 24 months from the publication of the final rule
to implement these changes to certified health IT products.
(1) Immediate Access
The existing Provide Patients Electronic Access to Their Health
Information measure specifies that the eligible hospital or CAH provide
the patient timely access to view online, download, and transmit his or
her health information, and further specifies that patient health
information must be made available to the patient within 36 hours of
its availability to the eligible hospital or CAH. We believe it is
critical for patients to have access to their health information when
making decisions about their care. In the recently published Medicare
and Medicaid Programs; Patient Protection and Affordable Care Act;
Interoperability and Patient Access for Medicare Advantage Organization
and Medicaid Managed Care Plans, State Medicaid Agencies, CHIP Agencies
and CHIP Managed Care Entities, Issuers of Qualified Health Plans in
the Federally-facilitated Exchanges and Health Care Providers proposed
rule (84 FR 7610 through 7680), (hereinafter referred to as the CMS
Interoperability and Patient Access proposed rule), we proposed that
certain health plans and payers be required to make patient health
information available through an open, standards-based API no later
than one business day after it is received by the health plan or payer.
Recognizing the importance of patients having access to their
complete health information, including clinical information from the
eligible hospital or CAH's CEHRT, and appreciating the new technical
flexibility a standards-based API provides, we are seeking comment on
whether eligible hospitals and CAHs should make patient health
information available immediately through the open, standards-based
API, no later than one business day after it is available to the
eligible hospital or CAH in their CEHRT. We are also seeking comment on
the barriers to more immediate access to patient information. And, we
are seeking comment on if there are specific data elements that may be
more or less feasible to share no later than one business day.
(2) Persistent Access and Standards-Based APIs
As discussed above, the ONC 21st Century Cures Act proposed rule
(84 FR 7479), includes a proposal for adoption of API conditions of
certification that ensure a standards-based API is implemented in a
manner that provides unimpeded access to technical documentation, is
non-discriminatory, preserves rights of access, and minimizes costs or
other burdens that could result in special effort. The ONC 21st Century
Cures Act proposed rule (84 FR 7575), also includes requirements for
the standardized API related to privacy and security to ensure that
patient health information is protected.
The existing Provide Patients Electronic Access to Their Health
Information measure does not specify the overall operational
expectations associated with enabling patients' access to their health
information. For instance, the measure only specifies that access must
be ``timely.'' As a result, we are requesting public comment on whether
we should revise the measure to be more specific with respect to the
experience, patients should have regarding their access. For instance,
in the ONC 21st Century Cures Act proposed rule (84 FR 7481 through
7484) there is a proposal regarding requirements around persistent
access to APIs, which would accommodate a patient's routine access to
their health information without needing to reauthorize their app and
re-authenticate themselves. We are seeking comment on whether the
Promoting Interoperability Program measure should be updated to
reinforce this proposed technical requirement for persistent access.
As we work to advance interoperability and empower patients through
access to their health information, we continue to explore the role of
APIs. We support ONC's 21st Century Cures Act proposed rule (84 FR
7424) proposal to move to an HL7 FHIR[supreg]-based API under 2015
Edition certification (84 FR 7479). Health care providers committed to
a standards-based API could benefit from joining in on the industry's
new FHIR standards framework to reduce burden in, and improve on,
quality measurement through automation and simplification. Use of FHIR-
based APIs could help push forward interoperability regardless of EHR
systems used providing standardized way to share information.
Understanding this, we are, specifically, seeking public comment on
the following question: If ONC's proposal for a FHIR-based API
certification criteria is finalized, would stakeholders support a
possible bonus under the Promoting Interoperability Programs for early
adoption of a certified FHIR-based API in the intermediate time before
ONC's final rule's compliance date for implementation of a FHIR
standard for certified APIs?
(3) Available Data
Recognizing the overall burden that switching EHR systems places on
health care providers, ONC has introduced a new proposal that seeks to
minimize that burden. In the 21st Century Cures Act proposed rule (84
FR 7424 through 7610), ONC has proposed to adopt a new 2015 Edition
certification criterion for the Electronic Health Information (EHI)
export in 45 CFR 170.315(b)(10). The purpose of this criterion is to
provide patients and health IT users the ability to securely export the
entire electronic health record for a single patient, or all patients,
in a computable, electronic format, and facilitate receiving the health
IT system's interpretation, and use of the EHI, to the extent that is
reasonably practicable using the existing technology of developers.
This patient-focused export capability complements other provisions of
the proposed rule that support patients' access to their EHI, including
information that may eventually be accessible via the proposed
standardized API in 45 CFR 170.215. It is also complementary to the
proposals in the CMS Interoperability and Patient Access proposed rule,
which has proposed to require certain health plans under CMS to provide
patients access to their health data through a standardized API.
Building on these proposals, we are seeking comment on an
alternative measure under the Provider to Patient Exchange objective
that would require health care providers to use technology certified to
the EHI criteria to provide the patient(s) their complete electronic
health data contained within an EHR.
Specifically, we are seeking comment on the following questions:
Do stakeholders believe that incorporating this
alternative measure into the Provider to Patient Exchange objective
will be effective in encouraging the availability of all data stored in
health IT systems?
In relation to the Provider to Patient Exchange objective
as a whole, how should a measure focused on using the proposed total
EHI export function in CEHRT be scored?
If this certification criterion is finalized and
implemented, should a measure based on the criterion be established as
a bonus measure? Should this measure be established as an attestation
measure?
In the long term, how do stakeholders believe such an
alternative measure would impact burden?
[[Page 19568]]
What data elements do stakeholders believe are of greatest
clinical value or would be of most use to health care providers to
share in a standardized electronic format if the complete record was
not immediately available?
In addition to the above questions, we have some general questions
that are related to health IT activities, for which we are also seeking
public comment:
Do stakeholders believe that we should consider including
a health IT activity that promotes engagement in the health information
exchange across the care continuum that would encourage bi-directional
exchange of health information with community partners, such as post-
acute care, long term care, behavioral health, and home and community
based services to promote better care coordination for patients with
chronic conditions and complex care needs? If so, what criteria should
we consider when implementing a health information exchange across the
care continuum health IT activity in the Promoting Interoperability
Program?
What criteria should we employ, such as specific goals or
areas of focus, to identify high priority health IT activities for the
future of the program?
Are there additional health IT activities we should
consider recognizing in lieu of reporting on existing measures and
objectives that would most effectively advance priorities for
nationwide interoperability and spur innovation?
(4) Patient Matching
ONC has stated that patient matching is critically important to
interoperability and the nation's health IT infrastructure as health
care providers must be able to share patient health information and
accurately match a patient to his or her data from a different health
care provider in order for many anticipated interoperability benefits
to be realized. We continue to support ONC's work promoting the
development of patient matching initiatives. Per Congress `guidance,
ONC is looking at innovative ways to provide technical assistance to
private sector-led initiatives to further develop accurate patient
matching solutions in order to promote interoperability without
requiring a unique patient identifier (UPI). We understand the
significant health information privacy and security concerns raised
around the development of a UPI standard and the current prohibition
against using HHS funds to adopt a UPI standard.
Recognizing Congress' statement regarding patient matching and
stakeholder comments stating that a patient matching solution would
accomplish the goals of a UPI, we are seeking comment for future
consideration on ways for ONC and CMS to continue to facilitate private
sector efforts on a workable and scalable patient matching strategy so
that the lack of a specific UPI does not impede the free flow of
information. We are also seeking comment on how we may leverage our
program authority to provide support to those working to improve
patient matching. We note that we intend to use comments we receive for
the development of policy and future rulemaking.
f. Request for Information (RFI) on Integration of Patient-Generated
Health Data Into EHRs Using CEHRT
The Medicare and Medicaid Promoting Interoperability Programs are
continuously seeking ways to prioritize the advanced use of CEHRT
functionalities, encourage movement away from paper-based processes
that increase heath care provider burden, and empower individual
beneficiaries to take a more impactful role in managing their health to
achieve their goals. Increased availability of patient-generated health
data (PGHD) \829\ offers health care providers an opportunity to
monitor and track a patient's health-related data from information that
is provided by the patient and not the provider. Increasingly
affordable wearable devices, sensors, and other technologies capture
PGHD, providing new ways to monitor and track a patient's healthcare
experience. Capturing important health information through devices and
other tools between medical visits could help improve care management
and patient outcomes, potentially resulting in increased cost savings.
Although many types of PGHD are being used in clinical settings today,
the continuous collection and integration of patients' health-data into
EHRs to inform clinical care has not been widely achieved across the
health care system.
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\829\ For more information, we refer readers to: https://www.healthit.gov/topic/scientific-initiatives/patient-generated-health-data.
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In the 2015 Edition Health IT Certification Criteria final rule (80
FR 62661; 45 CFR 170.315(e)(3), ONC finalized a criterion for patient
health information capture functionality within certified health IT
that allows a user to identify, record, and access information directly
and electronically shared by a patient. We finalized a PGHD measure
requiring health care providers to incorporate patient generated health
data or data from a nonclinical setting into CEHRT (80 FR 62851).
However, we removed this measure in the FY 2019 IPPS/LTCH PPS final
rule (83 FR 41663 through 41664), due to concerns that the measure was
not fully health IT-based and could include paper-based actions, an
approach which did not align with program priorities to advance the use
of CEHRT. Stakeholder comments regarding this measure also noted that
manual processes to conduct actions associated with the measure could
increase health care provider reporting burden and that there was
confusion over which types of data would be applicable and the
situations in which the patient data would apply (83 FR 41663 through
41664). At the same time, there was ample support from the public for
ONC and CMS to continue to advance certified health IT capabilities to
capture PGHD.
However, we continue to believe that it is important for the
Promoting Interoperability Program to explore new ways to incentivize
health care providers who take proactive steps to advance the emerging
use of PGHD. As relevant technologies and standards continue to evolve,
there may be new program approaches through which we can address
challenges related to emerging standards for PGHD capture, appropriate
clinical workflows for receiving and reviewing PGHD, and advance the
technical architecture needed to support PGHD use.
In 2018, ONC released the white paper ``Conceptualizing a Data
Infrastructure for the Capture, Use, and Sharing of Patient-Generated
Health Data in Care Delivery and Research through 2024,'' \830\ which
describes key challenges, opportunities and enabling actions for
different stakeholders, including clinicians, to advance the use of
PGHD. For instance, the report identifies an enabling action around
supporting ``clinicians to work within and across organizations to
incorporate prioritized PGHD use cases into their workflows.'' This
action urges clinicians and care teams to identify priority use cases
and relevant PGHD types that would be valuable to improving care
delivery for patient populations. It also highlights the importance of
developing clinical workflows that avoid overwhelming the care team
with extraneous data, by encouraging care teams to develop management
strategies for shared responsibilities around collecting, verifying,
and analyzing PGHD. A second enabling action the white paper identifies
for clinicians is ``collaboration between clinicians and
[[Page 19569]]
developers to advance technologies supporting PGHD interpretation and
use.'' This enabling action highlights feedback for developers about
prioritized use cases and application features as critical to ensuring
that the necessary refinements are made to technology solutions to
effectively support the capture and use of PGHD. Finally, the report
encourages ``clinicians in providing patient education to encourage
PGHD capture and use in ways that maximize data quality,'' recognizing
the important role that clinicians can play in helping patients
understand how to share PGHD, the differences between solicited and
unsolicited PGHD, and how PGHD are relevant for the patient's care.
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\830\ https://www.healthit.gov/sites/default/files/onc_pghd_final_white_paper.pdf.
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Considering the enabling actions for clinicians identified in the
white paper, we are interested in ways that the Promoting
Interoperability Program could adopt new elements related to PGHD that:
(1) Represent clearly defined uses of health IT; (2) are linked to
positive outcomes for patients; and (3) advance the capture, use, and
sharing of PGHD. In considering how the Promoting Interoperability
Program could continue to advance the use of PGHD, we also note that a
future program element related to PGHD would not necessarily need to be
implemented as a traditional measure requiring reporting of a numerator
and denominator. For instance, in the FY 2019 IPPS/LTCH PPS proposed
rule (83 FR 20538), we requested comment on the concept of ``health
IT'' or ``interoperability'' activities to which a health care provider
could attest, potentially in lieu of reporting on measures associated
with certain objectives. By addressing the use of PGHD through such a
concept, rather than traditional measure reporting, we could
potentially reduce the reporting burden associated with a new PGHD-
related program element.
We are inviting stakeholder comment on these concepts, and the
specific questions below:
What specific use cases for capture of PGHD as part of
treatment and care coordination across clinical conditions and care
settings are most promising for improving patient outcomes? For
instance, use of PGHD for capturing advanced directives and pre/post-
operation instructions in surgery units.
Should the Promoting Interoperability Program explore ways
to include bonus points for health care providers engaging in
activities that pilot promising technical solutions or approaches for
capturing PGHD and incorporating it into CEHRT using standards-based
approaches?
Should inpatient health care providers be expected to
collect information from their patients outside of scheduled
appointments or procedures? What are the benefits and concerns about
doing so?
Should the Promoting Interoperability Program explore ways
to reward health care providers for implementing best practices
associated with optimizing clinical workflows for obtaining, reviewing,
and analyzing PGHD?
We believe the bi-directional availability of data, meaning that
both patients and their health care providers have real-time access to
the patient's electronic health record, is critical. This includes
patients being able to import their health data into their medical
record and have it be available to health care providers. We welcome
input on how we can encourage and enable health care providers to
advance capture, exchange, and use of PGHD.
g. Request for Information (RFI) on Engaging in Activities That Promote
the Safety of the EHR
The widespread adoption of EHRs has transformed the way health care
is delivered, offering improved availability of patient health
information, supporting more informed clinical decision making, and
reduce medical errors.\831\ However, many stakeholders have identified
risks to patient safety as one of the unintended consequences that may
result from implementation of EHRs. By disrupting established workflows
and presenting clinicians with new challenges, EHR implementation may
increase the incidence of certain errors, resulting in harm to
patients.
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\831\ https://www.healthit.gov/topic/health-it-basics/improved-patient-care-using-ehrs.
---------------------------------------------------------------------------
As we continue to advance the use of CEHRT in health care, we are
seeking comment on how to further mitigate the specific safety risks
that may arise from technology implementation. Specifically, we are
seeking comment on ways that the Promoting Interoperability Program may
reward hospitals for engaging in activities that can help to reduce
errors associated with EHR implementation.
For instance, we are requesting comment on a potential future
change to the program under which hospitals would receive points
towards their Promoting Interoperability Program score for attesting to
performance of an assessment based on one of the ONC SAFER Guides. The
SAFER Guides (available at: https://www.healthit.gov/topic/safety/safer-guides) are designed to help healthcare organizations conduct
self-assessments to optimize the safety and safe use of EHRs in nine
different areas: High Priority Practices, Organizational
Responsibilities, Contingency Planning, System Configuration, System
Interfaces, Patient Identification, Computerized Provider Order Entry,
Test Results Reporting and Follow-Up, and Clinician Communication.
Each of the SAFER Guides is based on the best evidence available,
including a literature review, expert opinion, and field testing at a
wide range of healthcare organizations, from small ambulatory practices
to large health systems. A number of EHR developers currently utilize
the SAFER Guides as part of their health care provider training
modules.
Specifically, we might consider offering points towards the
Promoting Interoperability Program score to hospitals that attest to
conducting an assessment based on the High Priority Practices \832\
and/or the Organizational Responsibilities \833\ SAFER Guides which
cover many foundational concepts from across the guides. Alternatively
we might consider awarding points for review of all nine of the SAFER
Guides. We are also inviting comments on alternatives to the SAFER
Guides, including appropriate assessments related to patient safety,
which should also be considered as part of any future bonus option.
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\832\ https://www.healthit.gov/sites/default/files/safer/guides/safer_high_priority_practices.pdf.
\833\ https://www.healthit.gov/sites/default/files/safer/guides/safer_organizational_responsibilities.pdf.
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We are requesting comment on the ideas above, as well as inviting
stakeholders to suggest other approaches we might take to rewarding
activities that promote reduction of safety risks associated with EHR
implementation as part of the Promoting Interoperability Program.
IX. MedPAC Recommendations
Under section 1886(e)(4)(B) of the Act, the Secretary must consider
MedPAC's recommendations regarding hospital inpatient payments. Under
section 1886(e)(5) of the Act, the Secretary must publish in the annual
proposed and final IPPS rules the Secretary's recommendations regarding
MedPAC's recommendations. We have reviewed MedPAC's March 2019 ``Report
to the Congress: Medicare Payment Policy'' and have given the
recommendations in the report consideration in conjunction with the
proposed policies set forth in this proposed rule. MedPAC
[[Page 19570]]
recommendations for the IPPS for FY 2020 are addressed in Appendix B to
this proposed rule.
For further information relating specifically to the MedPAC reports
or to obtain a copy of the reports, contact MedPAC at (202) 653-7226,
or visit MedPAC's website at: http://www.medpac.gov.
X. Other Required Information
A. Publicly Available Files
IPPS-related data are available on the internet for public use. The
data can be found on the CMS website at: http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.
Following is a listing of the IPPS-related data files that are
available.
Commenters interested in discussing any data files used in
construction of this proposed rule should contact Michael Treitel at
(410) 786-4552.
1. CMS Wage Data Public Use File
This file contains the hospital hours and salaries from Worksheet
S-3, Parts II and III from FY 2016 Medicare cost reports used to create
the proposed FY 2020 IPPS wage index. Multiple versions of this file
are created each year. For a discussion of the release of different
versions of this file, we refer readers to section III.L. of the
preamble of this proposed rule.
Media: Internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Wage-Index-Files.html.
Periods Available: FY 2007 through FY 2020 IPPS Update.
2. CMS Occupational Mix Data Public Use File
This file contains the CY 2016 occupational mix survey data to be
used to compute the occupational mix adjusted wage indexes. Multiple
versions of this file are created each year. For a discussion of the
release of different versions of this file, we refer readers to section
III.L. of the preamble of this proposed rule.
Media: Internet at: https://www.cms.gov/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Wage-Index-Files.html.
Period Available: FY 2020 IPPS Update.
3. Provider Occupational Mix Adjustment Factors for Each Occupational
Category Public Use File
This file contains each hospital's occupational mix adjustment
factors by occupational category. Two versions of these files are
created each year to support the rulemaking.
Media: Internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-AService-Payment/AcuteInpatientPPS/Wage-Index-Files.html.
Period Available: FY 2020 IPPS Update.
4. Other Wage Index Files
CMS releases other wage index analysis files after each proposed
and final rule.
Media: Internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Wage-Index-Files.html.
Periods Available: FY 2005 through FY 2020 IPPS Update.
5. FY 2020 IPPS SSA/FIPS CBSA State and County Crosswalk
This file contains a crosswalk of State and county codes used by
the Federal Information Processing Standards (FIPS), county name, and a
list of Core-Based Statistical Areas (CBSAs).
Media: Internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html (on the navigation panel
on the left side of the page, click on the FY 2020 proposed rule home
page or the FY 2020 final rule home page) or https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html.
Period Available: FY 2020 IPPS Update.
6. HCRIS Cost Report Data
The data included in this file contain cost reports with fiscal
years ending on or after September 30, 1996. These data files contain
the highest level of cost report status.
Media: Internet at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/Cost-Reports/Cost-Reports-by-Fiscal-Year.html.
(We note that data are no longer offered on a CD. All of the data
collected are now available free for download from the cited website.)
7. Provider-Specific File
This file is a component of the PRICER program used in the MAC's
system to compute DRG/MS-DRG payments for individual bills. The file
contains records for all prospective payment system eligible hospitals,
including hospitals in waiver States, and data elements used in the
prospective payment system recalibration processes and related
activities. Beginning with December 1988, the individual records were
enlarged to include pass-through per diems and other elements.
Media: Internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ProspMedicareFeeSvcPmtGen/psf_text.html.
Period Available: Quarterly Update.
8. CMS Medicare Case-Mix Index File
This file contains the Medicare case-mix index by provider number
based on the MS-DRGs assigned to the hospital's discharges using the
GROUPER version in effect on the date of the discharge. The case-mix
index is a measure of the costliness of cases treated by a hospital
relative to the cost of the national average of all Medicare hospital
cases, using DRG/MS-DRG weights as a measure of relative costliness of
cases. Two versions of this file are created each year to support the
rulemaking.
Media: Internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html, or for the more recent data files, https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html
(on the navigation panel on the left side of page, click on the
specific fiscal year proposed rule home page or fiscal year final rule
home page desired).
Periods Available: FY 1985 through FY 2020.
9. MS-DRG Relative Weights (Also Table 5--MS-DRGs)
This file contains a listing of MS-DRGs, MS-DRG narrative
descriptions, relative weights, and geometric and arithmetic mean
lengths of stay for each fiscal year. Two versions of this file are
created each year to support the rulemaking.
Media: Internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html, or for the more recent data files, https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html
(on the navigation panel on the left side of page, click on the
specific fiscal year proposed rule home page or the fiscal year final
rule home page desired).
Periods Available: FY 2005 through FY 2020 IPPS Update.
10. IPPS Payment Impact File
This file contains data used to estimate payments under Medicare's
hospital inpatient prospective payment systems for operating and
capital-related
[[Page 19571]]
costs. The data are taken from various sources, including the Provider-
Specific File, HCRIS Cost Report Data, MedPAR Limited Data Sets, and
prior impact files. The data set is abstracted from an internal file
used for the impact analysis of the changes to the prospective payment
systems published in the Federal Register. Two versions of this file
are created each year to support the rulemaking.
Media: Internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Historical-Impact-Files-for-FY-1994-through-Present.html.
Periods Available: FY 1994 through FY 2020 IPPS Update.
11. AOR/BOR Tables
This file contains data used to develop the MS-DRG relative
weights. It contains mean, maximum, minimum, standard deviation, and
coefficient of variation statistics by MS-DRG for length of stay and
standardized charges. The BOR tables are ``Before Outliers Removed''
and the AOR is ``After Outliers Removed.'' (Outliers refer to
statistical outliers, not payment outliers.)
Two versions of this file are created each year to support the
rulemaking.
Media: Internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html, or for the more recent data files, https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html
(on the navigation panel on the left side of page, click on the
specific fiscal year proposed rule home page or fiscal year final rule
home page desired).
Periods Available: FY 2005 through FY 2020 IPPS Update.
12. Prospective Payment System (PPS) Standardizing File
This file contains information that standardizes the charges used
to calculate relative weights to determine payments under the hospital
inpatient operating and capital prospective payment systems. Variables
include wage index, cost-of-living adjustment (COLA), case-mix index,
indirect medical education (IME) adjustment, disproportionate share,
and the Core-Based Statistical Area (CBSA). The file supports the
rulemaking.
Media: Internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html (on the navigation panel
on the left side of the page, click on the FY 2020 proposed rule home
page or the FY 2020 final rule home page) or https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html.
Period Available: FY 2020 IPPS Update.
13. Hospital Readmissions Reduction Program Supplemental File
This file contains information on the calculation of the Hospital
Readmissions Reduction Program (HRRP) payment adjustment. Variables
include the proxy excess readmission ratios for acute myocardial
infarction (AMI), pneumonia (PN) and heart failure (HF), coronary
obstruction pulmonary disease (COPD), total hip arthroplasty (THA)/
total knee arthroplasty (TKA), and coronary artery bypass grafting
(CABG) and the proxy readmissions payment adjustment for each provider
included in the program. In addition, the file contains information on
the number of cases for each of the applicable conditions excluded in
the calculation of the readmission payment adjustment factors as well
as other information used in the calculation of the annual payment
adjustment factors. The file supports the rulemaking.
Media: Internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html (on the navigation panel
on the left side of the page, click on the FY 2020 proposed rule home
page or the FY 2020 final rule home page) or https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html.
Period Available: FY 2020 IPPS Update.
14. Medicare Disproportionate Share Hospital (DSH) Supplemental File
This file contains information on the calculation of the
uncompensated care payments for FY 2020. Variables include the data
used to determine a hospital's share of uncompensated care payments,
total uncompensated care payments and estimated per claim uncompensated
care payment amounts. The file supports the rulemaking.
Media: Internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html (on the navigation panel
on the left side of the page, click on the FY 2020 proposed rule home
page or the FY 2020 final rule home page) or https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html.
Period Available: FY 2020 IPPS Update.
15. New Technology Thresholds File
This file contains the cost thresholds by MS-DRG used to evaluate
applications for new technology add-on payments for the fiscal year
that follows the fiscal year that is otherwise the subject of the
rulemaking. Two versions of this file are created each year to support
rulemaking. (We note that the information in this file was previously
provided in Table 10 of the annual IPPS proposed and final rules (83 FR
41739).)
Media: Internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html (on the navigation panel
on the left side of the page, click on the FY 2019 final rule home page
for the FY 2020 application thresholds, or click on the FY 2020
proposed rule home page for the proposed FY 2021 application thresholds
or on the FY 2020 final rule home page for the final FY 2021
application thresholds) or https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html.
Periods Available: For FY 2020 and FY 2021 applications.
B. Collection of Information Requirements
1. Statutory Requirement for Solicitation of Comments
Under the Paperwork Reduction Act (PRA) of 1995, we are required to
provide 60-day notice in the Federal Register and solicit public
comment before a collection of information requirement is submitted to
the Office of Management and Budget (OMB) for review and approval. In
order to fairly evaluate whether an information collection should be
approved by OMB, section 3506(c)(2)(A) of the PRA of 1995 requires that
we solicit comment on the following issues:
The need for the information collection and its usefulness
in carrying out the proper functions of our agency.
The accuracy of our estimate of the information collection
burden.
The quality, utility, and clarity of the information to be
collected.
Recommendations to minimize the information collection
burden on the affected public, including automated collection
techniques.
In this proposed rule, we are soliciting public comment on each of
these issues for the following sections of this document that contain
information collection requirements (ICRs).
[[Page 19572]]
2. ICRs for Application for GME Resident Slots
The information collection requirements associated with the
preservation of resident cap positions from closed hospitals, addressed
in section IV.J.3. of the preamble of this proposed rule are not
subject to the Paperwork Reduction Act, as stated in section 5506 of
the Affordable Care Act.
3. ICRs for the Hospital Inpatient Quality Reporting (IQR) Program
a. Background
The Hospital IQR Program (formerly referred to as the Reporting
Hospital Quality Data for Annual Payment Update (RHQDAPU) Program) was
originally established to implement section 501(b) of the MMA, Public
Law 108-173. OMB has currently approved 2,520,100 hours of burden and
approximately $92.2 million under OMB Control Number 0938-1022,
accounting for information collection burden experienced by 3,300 IPPS
hospitals and 1,100 non-IPPS hospitals for the FY 2021 payment
determination. Below we describe the burden changes with regards to
collection of information under OMB Control Number 0938-1022 for IPPS
hospitals due to the proposed policies in this proposed rule.
In section VIII.A.5.b. of the preamble of this proposed rule, we
are proposing to adopt the Hybrid Hospital-Wide Readmission Measure
with Claims and Electronic Health Record Data (Hybrid HWR measure) (NQF
#2879) in a stepwise approach, beginning with two years of voluntary
reporting which would run from July 1, 2021 through June 30, 2022, and
from July 1, 2022 through June 30, 2023, before requiring reporting of
the measure for the reporting period that would run from July 1, 2023
through June 30, 2024, impacting the FY 2026 payment determination and
subsequent years. We are also proposing reporting and submission
requirements for the Hybrid HWR measure. We expect these proposals will
affect our collection of information burden estimates. Details on these
proposals, as well as the expected burden changes, are discussed
further below.
In section VIII.A. of the preamble of this proposed rule, we also
are proposing to: (1) Adopt two opioid-related eCQMs beginning with the
CY 2021 reporting period/FY 2023 payment determination: (a) Safe Use of
Opioids--Concurrent Prescribing eCQM (NQF #3316e), and (b) Hospital
Harm--Opioid-Related Adverse Events eCQM; (2) remove the claims-only
version of the Hospital-Wide All-Cause Readmission measure beginning
with the FY 2026 payment determination; (3) extend the current eCQM
reporting and submission requirements for the CY 2020 reporting period/
FY 2022 payment determination and CY 2021 reporting period/FY 2023
payment determination; (4) change the eCQM reporting and submission
requirements for the CY 2022 reporting period/FY 2024 payment
determination, such that hospitals would be required to report one,
self-selected calendar quarter of data for: (a) Three self-selected
eCQMs, and (b) the proposed Safe Use of Opioids--Concurrent Prescribing
eCQM (NQF #3316e), for a total of four eCQMs; and (5) continue the
requirement that EHRs be certified to all available eCQMs used in the
Hospital IQR Program for the CY 2020 reporting period/FY 2022 payment
determination and subsequent years. As discussed further below, we do
not expect these policies to affect our information collection burden
estimates.
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38501 through 38504)
and FY 2019 IPPS/LTCH PPS final rule (83 FR 41689 through 41694), we
estimated that reporting measures for the Hospital IQR Program could be
accomplished by staff with a median hourly wage of $18.29 per hour. We
note that since then, more recent wage data have become available, and
we are updating the wage rate used in these calculations in this
proposed rule. The most recent data from the Bureau of Labor Statistics
reflects a median hourly wage of $18.83 per hour for a Medical Records
and Health Information Technician professional.\834\ We calculated the
cost of overhead, including fringe benefits, at 100 percent of the
median hourly wage, consistent with previous years. This is necessarily
a rough adjustment, both because fringe benefits and overhead costs
vary significantly by employer and methods of estimating these costs
vary widely in the literature. Nonetheless, we believe that doubling
the hourly wage rate ($18.83 x 2 = $37.66) to estimate total cost is a
reasonably accurate estimation method. Accordingly, we will calculate
cost burden to hospitals using a wage plus benefits estimate of $37.66
per hour throughout the discussion below for the Hospital IQR Program.
---------------------------------------------------------------------------
\834\ U.S. Bureau of Labor Statistics. Occupational Outlook
Handbook, Medical Records and Health Information Technicians.
Available at: https://www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.htm.
---------------------------------------------------------------------------
b. Information Collection Burden Estimate for the Proposed Adoption of
Two eCQMs Beginning With the CY 2021 Reporting Period/FY 2023 Payment
Determination
In section VIII.A.5.a. of the preamble of this proposed rule, we
are proposing to adopt two opioid-related eCQMs beginning with the CY
2021 reporting period/FY 2023 payment determination:
Safe Use of Opioids--Concurrent Prescribing eCQM (NQF
#3316e); and
Hospital Harm--Opioid-Related Adverse Events eCQM.
We do not believe that adding two new eCQMs to the measure set will
affect the information collection burden of submitting information to
CMS under the Hospital IQR Program. As discussed in section
VIII.A.10.d.(2) and (3) of the preamble of this proposed rule, we are
proposing to extend, for the CYs 2020 and 2021 reporting periods/FYs
2022 and 2023 payment determinations, our current eCQM reporting
requirements, which require hospitals to submit one self-selected
calendar quarter of data for four self-selected eCQMs each year. These
new proposed measures would be added to the eight available eCQMs in
the eCQM measure set from which hospitals may choose to report in order
to satisfy these requirements.\835\ In other words, while these two new
proposed measures would be added to the eCQM measure set, hospitals
would not be required to report more than a total of four eCQMs as
currently required. Therefore, we do not expect adopting these measures
will impact our burden estimates. However, we refer readers to section
I.K. of Appendix A of this proposed rule for a discussion of the
potential costs associated with the implementation of new eCQMs that
are not strictly related to information collection burden.
---------------------------------------------------------------------------
\835\ We note that in section VIII.A.9.d.(4) of the preamble of
this proposed rule we are proposing that, beginning with the CY 2022
reporting period, hospitals must report data on the Safe Use of
Opioids--Concurrent Prescribing eCQM (NQF #3316e) as one of the four
required eCQMs.
---------------------------------------------------------------------------
c. Information Collection Burden Estimate for the Proposed Voluntary
Reporting Periods and Subsequent Adoption of the Hybrid Hospital-Wide
Readmission Measure With Claims and Electronic Health Record Data
(Hybrid HWR Measure)
In section VIII.A.5.b. of the preamble of this proposed rule, we
are proposing to establish two additional voluntary reporting periods
for the Hybrid Hospital-Wide Readmission Measure with Claims and
Electronic Health Record Data (NQF #2879) (Hybrid HWR
[[Page 19573]]
measure). The first voluntary reporting period would run from July 1,
2021 through June 30, 2022, and the second would run from July 1, 2022
through June 30, 2023. We also are proposing to require reporting of
the Hybrid HWR measure immediately thereafter and for subsequent years,
beginning with the reporting period which runs from July 1, 2023
through June 30, 2024 and which would affect the FY 2026 payment
determination.
As a hybrid measure, this measure uses both claims-based data and
EHR data, specifically, a set of core clinical data elements consisting
of vital signs and laboratory test information and patient linking
variables collected from hospitals' EHR systems. We do not expect any
additional burden to hospitals to report the claims-based portion of
this measure, because these data are already reported to the Medicare
program for payment purposes.
However, we do expect that hospitals will experience burden in
reporting the EHR data. To report the EHR data, as discussed earlier in
this proposed rule, we are proposing that hospitals would use the same
submission process required for eCQM reporting; specifically, these
data would be required to be reported using QRDA I files submitted to
the CMS data receiving system, and using EHR technology certified to
the 2015 Edition of CEHRT. Accordingly, we expect the burden associated
with reporting of this measure to be similar to our estimates for eCQM
reporting; that is, 10 minutes per measure, per quarter. Therefore,
using the estimate of 10 minutes per measure per quarter (10 minutes x
1 measure x 4 quarters = 40 minutes), we estimate that our proposal
will result in a burden increase of 0.67 hours (40 minutes) per
hospital per year. Beginning with the first voluntary reporting period,
which runs from July 1, 2021 through June 30, 2022, we estimate an
annual burden increase of 2,211 hours across participating hospitals
(0.67 hours x 3,300 IPPS hospitals). Using the updated wage estimate
described above, we estimate this to represent a cost increase of
$83,266 ($37.66 hourly wage x 2,211 annual hours) across hospitals. We
acknowledge that reporting during the first two years of this proposal
is voluntary, but if our proposal to adopt the Hybrid HWR measure is
finalized, we will encourage all hospitals to submit data for the
Hybrid HWR measure during these voluntary reporting periods. For that
reason, our burden estimates are based on the assumption that all
hospitals will participate across the two voluntary reporting periods
(July 1, 2021 through June 30, 2022, and July 1, 2022 through June 30,
2023), the reporting period in which public reporting begins (July 1,
2023 through June 30, 2024), and subsequent reporting periods.
d. Information Collection Burden Estimate for Proposed Removal of
Claims-Only Hospital-Wide All-Cause Readmission Measure (HWR Claims-
Only Measure) Beginning With the FY 2026 Payment Determination
In section VIII.A.6. of the preamble of this proposed rule, we are
proposing to remove the HWR claims-only measure, beginning with the FY
2026 payment determination when the Hybrid HWR measure begins to be
publicly reported. Because the HWR claims-only measure is calculated
using data that are already reported to the Medicare program for
payment purposes, we do not anticipate that removing this measure would
decrease our previously finalized burden estimates.
e. Information Collection Burden Estimates for Proposals Related to
eCQM Reporting and Submission Requirements
(1) Information Collection Burden Estimates for Proposed eCQM Reporting
and Submission Requirements for the CYs 2020 and 2021 Reporting
Periods/FYs 2022 and 2023 Payment Determinations
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41602 through
41607), we finalized eCQM reporting and submission requirements such
that hospitals submit one, self-selected calendar quarter of data for
four eCQMs in the Hospital IQR Program measure set for the CY 2019
reporting period/FY 2021 payment determination. Our related information
collection estimates were discussed at 83 FR 41689 through 41694. In
sections VIII.A.10.(d)(2) and (3) of the preamble of this proposed
rule, we are proposing to extend the current requirements for two
additional years, the CY 2020 reporting period/FY 2022 payment
determination and the CY 2021 reporting period/FY 2023 payment
determination. We believe there will be no change to the burden
estimate due to these proposals because the previous burden estimate of
40 minutes per hospital per year (10 minutes per record x 4 eCQMs x 1
quarter) associated with the eCQM reporting and submission requirements
finalized for the CY 2019 reporting period/FY 2021 payment
determination would also apply to the CY 2020 reporting period/FY 2022
payment determination and the CY 2021 reporting period/FY 2023 payment
determination.
(2) Information Collection Burden Estimate for Proposed eCQM Reporting
and Submission Requirements for the CY 2022 Reporting Period/FY 2024
Payment Determination
In section VIII.A.10.d.(4) of the preamble of this proposed rule,
for the CY 2022 reporting period/FY 2024 payment determination, we are
proposing to change the eCQM reporting and submission requirements,
such that hospitals would be required to report one, self-selected
calendar quarter of data for: (1) Three self-selected eCQMs, and (2)
the proposed Safe Use of Opioids--Concurrent Prescribing eCQM (NQF
#3316e), for a total of four eCQMs. We note that the number of calendar
quarters of data and total number of eCQMs required would remain the
same. We believe there will be no change to the burden estimate because
hospitals would still be required to submit one, self-selected calendar
quarter of data for a total of four eCQMs in the Hospital IQR Program
measure set.
(3) Information Collection Burden Estimate for Proposal To Require That
EHRs Be Certified to All Available eCQMs
In section VIII.A.10.d.(5)(B) of the preamble of this proposed
rule, we are proposing to continue requiring that EHRs be certified to
all available eCQMs in the Hospital IQR Program measure set for the CY
2020 reporting period/FY 2022 payment determination and subsequent
years. We do not believe that hospitals will experience an increase in
burden associated with this proposal because the use of EHR technology
that is certified to all available eCQMs has been required for the
Promoting Interoperability Program (83 FR 41672). However, we refer
readers to section I.K. of Appendix A of this proposed rule for a
discussion of the potential costs associated with this proposal that
are not strictly related to information collection burden.
f. Summary of Information Collection Burden Estimates for the Hospital
IQR Program
In summary, under OMB Control Number 0938-1022, we estimate a total
information collection burden increase of 2,211 hours associated with
our proposal to adopt the Hybrid Hospital-Wide All-Cause Readmission
(Hybrid HWR) measure and a total cost increase related to this
information collection of approximately $83,266 (which also reflects
use of an updated hourly wage
[[Page 19574]]
rate as discussed above), beginning with the first voluntary reporting
period which runs July 1, 2021 through June 30, 2022. These are the
total changes to the information collection burden estimates. We will
submit the revised information collection estimates to OMB for approval
under OMB Control Number 0938-1022.
Hospital IQR Program FY 2024 Payment Determination Information Collection Burden Estimates
--------------------------------------------------------------------------------------------------------------------------------------------------------
Annual recordkeeping and reporting requirements under OMB control No. 0938-1022 for the FY 2024
payment determination
-------------------------------------------------------------------------------------------------------
Average Proposed Previously
number Annual annual finalized Net
Activity Estimated Number Number of records burden burden annual difference
time per reporting IPPS per (hours) (hours) burden in annual
record quarters hospitals hospital per across (hours) burden
(minutes) per year reporting per hospital IPPS across IPPS hours
quarter hospitals hospitals
--------------------------------------------------------------------------------------------------------------------------------------------------------
Hybrid HWR Measure Reporting.................... 10 4 3,300 1 0.67 2,211 N/A 2,211
--------------------------------------------------------------------------------------------------------------------------------------------------------
Total Change in Information Collection Burden Hours: 2,211.
--------------------------------------------------------------------------------------------------------------------------------------------------------
Total Cost Estimate: Updated Hourly Wage ($37.66) x Change in Burden Hours (2,211) = $83,266.
--------------------------------------------------------------------------------------------------------------------------------------------------------
4. ICRs for PPS-Exempt Cancer Hospital Quality Reporting (PCHQR)
Program
a. Background
As discussed in sections VIII.B. of the preamble of this proposed
rule, section 1866(k)(1) of the Act requires, for purposes of FY 2014
and each subsequent fiscal year, that a hospital described in section
1886(d)(1)(B)(v) of the Act (a PPS-exempt cancer hospital, or a PCH)
submit data in accordance with section 1866(k)(2) of the Act with
respect to such fiscal year. There is no financial impact to PCH
Medicare payment if a PCH does not participate.
We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR
41694 through 41696), the CY 2019 OPPS/ASC final rule with comment
period ((83 FR 59149 through 59153), and OMB Control Number 0938-1175
for a detailed discussion of the most recently finalized burden
estimates for the program requirements that we have previously adopted.
Below we discuss only changes in burden that would result from the
proposals in this proposed rule.
In the FY 2018 IPPS/LTCH PPS final rule, we finalized a proposal to
utilize the median hourly wage rate, in accordance with the Bureau of
Labor Statistics (BLS), to calculate our burden estimates going forward
(82 FR 38505). The BLS describes Medical Records and Health Information
Technicians as those responsible for organizing and managing health
information data; therefore, we believe it is reasonable to assume that
these individuals will be tasked with abstracting clinical data for
submission for the PCHQR Program. In the FY 2019 IPPS/LTCH PPS final
rule (83 FR 41695), we utilized a median hourly wage of $18.29 per
hour.\836\
---------------------------------------------------------------------------
\836\ In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38505), we
finalized an hourly wage estimate of $18.29 per hour, plus 100
percent overhead and fringe benefits, for the PCHQR Program using
Bureau of Labor Statistics information.
---------------------------------------------------------------------------
We note that since then, more recent wage data have become
available, and we are updating the wage rate used in these
calculations. The most recent data from the Bureau of Labor Statistics
reflects a median hourly wage of $18.83 \837\ per hour for a Medical
Records and Health Information Technician professional. We have
finalized a policy to calculate the cost of overhead, including fringe
benefits, at 100 percent of the mean hourly wage (82 FR 38505). This is
necessarily a rough adjustment, both because fringe benefits and
overhead costs vary significantly from employer-to-employer and because
methods of estimating these costs vary widely from study-to-study.
Nonetheless, we believe that doubling the hourly wage rate ($18.83 x 2
= $37.66) to estimate total cost is a reasonably accurate estimation
method and allows for a conservative estimate of hourly costs. This
approach is consistent with our previously finalized burden calculation
methodology (82 FR 38505). Accordingly, we calculate cost burden to
PCHs using a wage plus benefits estimate of $37.66 per hour throughout
the discussion below.
---------------------------------------------------------------------------
\837\ Occupational Employment and Wages. Available at: https://www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.htm.
---------------------------------------------------------------------------
b. Estimated Burden of PCHQR Program Proposals for the FY 2022 Program
Year
(1) Proposed Removal of One Web-Based Structural Measure
As discussed in section VIII.B.4. of the preamble of this proposed
rule, we are proposing to remove one web-based, structural measure
beginning with the FY 2022 program year: External Beam Radiotherapy
(EBRT) for Bone Metastases (formerly NQF #1822). As finalized in the FY
2019 IPPS/LTCH PPS final rule, we utilize a time estimate of 15-minutes
per measure when assessing web-based and/or structural measures (83 FR
41694). As such, we estimate a reduction of 15 minutes per PCH, and a
total annual reduction of approximately 3 hours for all 11 PCHs (.25
hour x 11 PCHs), due to the proposed removal of this measure.
(2) Proposed New Quality Measure Beginning With the FY 2022 Program
Year
In section VIII.B.5. of the preamble of this proposed rule, we are
proposing to adopt the Surgical Treatment Complications for Localized
Prostate Cancer claims-based measure beginning with the FY 2022 program
year. Because this measure is claims-based, we do not anticipate any
increase in burden on PCHs related to our proposal to adopt this
measure, as it does not require facilities to submit any additional
data.
c. Summary of Burden Estimates Related to the PCHQR Program Proposals
for the FY 2022 Program Year
In summary, if our proposals to remove the External Beam
Radiotherapy (EBRT) for Bone Metastases (formerly NQF #1822) measure
and to adopt the Surgical Treatment Complications for Localized
Prostate Cancer claims-based
[[Page 19575]]
measure are finalized as proposed, we estimate an overall burden
decrease of approximately 3 hours across all 11 PCHs. Coupled with our
estimated salary costs, we estimate that these proposed changes would
result in a reduction in annual labor costs of approximately $113 (3
hours x $37.66 hourly labor cost) across the 11 PCHs beginning with the
FY 2022 PCHQR Program. Further, the PCHQR Program measure set would
consist of 15 measures for the FY 2022 program year. The burden
associated with these reporting requirements is currently approved
under OMB control number 0938-1175. The information collection will be
revised and submitted to OMB.
5. ICRs for the Hospital Value-Based Purchasing (VBP) Program
In section IV.H. of the preamble of this proposed rule, we discuss
proposed requirements for the Hospital VBP Program. Specifically, in
this proposed rule, with respect to quality measures, we are proposing
to calculate scores for the five NHSN HAI measures used in the Hospital
VBP Program using the same data that the HAC Reduction Program uses for
purposes of calculating NHSN HAI measure scores under that program,
beginning on January 1, 2020 for CY 2020 measure data, which would
apply to the Hospital VBP Program starting with data for the FY 2022
program year performance period. Because scores for these measures will
be calculated using the same data that we use to calculate scores for
the same measures in the HAC Reduction Program, there will be no new
data collection burden associated with these measures under the
Hospital VBP Program.
6. ICRs for the Long-Term Care Hospital Quality Reporting Program (LTCH
QRP)
In section VIII.C. of the preamble of this proposed rule, we are
proposing to adopt two Transfer of Health Information quality measures
as well as standardized patient assessment data elements (SPADEs)
beginning with the FY 2022 LTCH QRP.
We estimate the data elements for the two proposed Transfer of
Health Information quality measures will take 1.2 minutes of clinical
staff time to report data on discharge. We believe that the additional
LTCH CARE Data Set data elements will be completed by registered nurses
and licensed vocational nurses. Individual LTCHs determine the staffing
resources necessary. We estimate 102,468 discharges from 415 LTCHs
annually. This equates to an increase of 2,049 hours in burden for all
LTCHs (0.02 hours x 102,468 discharges). Given 0.7 minutes of
registered nurse time at $70.72 per hour and 0.5 minutes of licensed
vocational nurse time at $43.96 per hour to complete an average of 247
sets of LTCH CARE Data Set assessments per provider per year, we
estimated the total cost will be increased by $289.76 per LTCH
annually, or $120,252 for all LTCHs annually. This increase in burden
will be accounted for in the information collection under OMB control
number 0938-1163.
We estimate the proposed SPADEs will take 11.3 minutes of clinical
staff time to report data on admission and 10.5 minutes of clinical
staff time to report data on discharge, for a total of 21.8 minutes. We
believe that the additional LTCH CARE Data Set data elements will be
completed by registered nurses and licensed vocational nurses.
Individual LTCHs determine the staffing resources necessary. We
estimate 102,468 discharges from 415 LTCHs annually. This equates to an
increase of 37,195 hours in burden for all LTCHs (0.363 hours x 102,468
discharges). Given 11.6 minutes of registered nurse time at $70.72 per
hour and 10.2 minutes of licensed vocational nurse time at $43.96 per
hour to complete an average of 247 sets of LTCH CARE Data Set
assessments per provider per year, we estimated the total cost will be
increased by $5,209.86 per LTCH annually, or $2,162,093 for all LTCHs
annually. This increase in burden will be accounted for in the
information collection under OMB control number 0938-1163.
Overall, the proposed changes added 11.3 minutes of clinical staff
time to report data on admission and 11.7 minutes of clinical staff
time to report data on discharge, for a total of 23.0 minutes. As a
result, the cost associated with the proposed changes to the LTCH QRP
is estimated at $5,499.63 per LTCH annually or $2,282,346 for all LTCHs
annually.
7. ICRs Relating to the Hospital-Acquired Condition (HAC) Reduction
Program
In section IV.I. of the preamble of this proposed rule, we discuss
proposed requirements for the HAC Reduction Program. In this proposed
rule, we are not proposing to remove any measures or adopt any new
measures into the HAC Reduction Program. The HAC Reduction Program has
adopted six measures. We do not believe that the claims-based CMS PSI
90 measure in the HAC Reduction Program creates or reduces any burden
for hospitals because it is collected using Medicare FFS claims
hospitals are already submitting to the Medicare program for payment
purposes. We note the burden associated with collecting and submitting
data for the HAI measures (CDI, CAUTI, CLABSI, MRSA, and Colon and
Abdominal Hysterectomy SSI) via the NHSN system is captured under a
separate OMB control number, 0920-0666, and therefore will not impact
our burden estimates.
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41478 through
41484), we finalized our policy to validate NHSN HAI measures under the
HAC Reduction Program, which will require hospitals to submit
validation templates for the NHSN HAI measures beginning with Q3 CY
2020 discharges. We previously estimated that this policy will result
in a net neutral shift of 43,200 hours and approximately $1,580,256.00
with no overall net increase in burden to the HAC Reduction Program (83
FR 41151). OMB has currently approved these 43,200 hours of burden and
approximately $1.6 million under OMB control number 0938-1352,
accounting for information collection requirements experienced by 3,300
IPPS hospitals for FY 2021 program year.
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41697), we used an
hourly wage estimate of $18.29 per hour to estimate information
collection costs.\838\ We note that, since then, more recent wage data
have become available, and we are updating the wage rate used in these
calculations in this proposed rule. The most recent data from the
Bureau of Labor Statistics reflects a median hourly wage of $18.83
\839\ per hour for a Medical Records and Health Information Technician
professional. We calculate the cost of overhead, including fringe
benefits, at 100 percent of the hourly wage estimate, as has been done
under the Hospital IQR Program in the previous years (82 FR 38504
through 38505; 83 FR 41689 through 41690). This is necessarily a rough
adjustment, both because fringe benefits and overhead costs vary
significantly from employer-to-employer and because methods of
estimating these costs vary widely from study-to-study. Nonetheless, we
believe that doubling the hourly wage rate ($18.83 x 2 = $37.66) to
estimate total cost is a
[[Page 19576]]
reasonably accurate estimation method. Accordingly, we calculate cost
burden to hospitals using a wage plus benefits estimate of $37.66 per
hour.
---------------------------------------------------------------------------
\838\ In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41697), we
finalized an hourly wage estimate of $18.29 per hour, plus 100
percent overhead and fringe benefits, for the HAC Reduction Program
using Bureau of Labor Statistics information.
\839\ Occupational Employment and Wages. Available at: https://www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.htm.
---------------------------------------------------------------------------
We estimate a reporting burden of 80 hours (20 hours per record x 1
record per hospital per quarter x 4 quarters) per hospital selected for
validation per year to submit the CLABSI and CAUTI templates, and 64
hours (16 hours per record x 1 record per hospital per quarter x 4
quarters) per hospital selected for validation per year to submit the
MRSA and CDI templates. We estimate a total burden shift of 43,200
hours ([80 hours per hospital to submit CLABSI and CAUTI templates + 64
hours per hospital to submit MRSA and CDI templates] x 300 hospitals
selected for validation) and approximately $1,626,912.00 (43,200 hours
x $37.66 per hour \840\) as a result of our policy to validate NHSN HAI
data under the HAC Reduction Program. A non-substantive information
collection request will be submitted to OMB under control number 0938-
1352 to account for the updated costs.
---------------------------------------------------------------------------
\840\ Occupational Employment and Wages. Available at: https://www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.htm.
---------------------------------------------------------------------------
8. ICRs Relating to the Hospital Readmissions Reduction Program
In section IV.G. of the preamble of this proposed rule, we discuss
proposed requirements for the Hospital Readmissions Reduction Program.
In this proposed rule, we are not proposing to adopt any new measures
into the Hospital Readmissions Reduction Program. All six of the
Hospital Readmissions Reduction Program's measures are claims-based
measures. We do not believe that continuing to use these claims-based
measures creates or reduces any burden for hospitals because they will
continue to be collected using Medicare FFS claims that hospitals are
already submitting to the Medicare program for payment purposes.
9. ICRs for the Promoting Interoperability Programs
a. Background
In section VIII.D. of the preamble of this proposed rule, we
discuss proposed requirements for the Promoting Interoperability
Programs. OMB has currently approved 623,562.19 total burden hours and
approximately $61 million under OMB control number 0938-1278,
accounting for information collection burden experienced by
approximately 3,300 eligible hospitals and CAHs (Medicare-only and
dual-eligible) that attest to CMS under the Medicare Promoting
Interoperability Program. The collection of information burden analysis
below will focus on eligible hospitals and CAHs that attest to the
objectives and measures, and report CQMs, under the Medicare Promoting
Interoperability Program for the reporting period in CY 2020.
b. Summary of Proposals for Eligible Hospitals and CAHs That Attest to
CMS Under the Medicare Promoting Interoperability Program for CY 2020
In section VIII.D.3.b. of the preamble of this proposed rule, we
are proposing to change the reporting requirement for the Query of
Prescription Drug Monitoring Program (PDMP) measure from numerator and
denominator to a ``yes/no'' response beginning with CY 2019 for
eligible hospitals and CAHs that attest to CMS under the Medicare
Promoting Interoperability Program. We expect this proposal to affect
our collection of information burden estimates for CY 2019 and CY 2020.
This proposed rule also includes the following proposals for
eligible hospitals and CAHs that attest to CMS under the Medicare
Promoting Interoperability Program, which we do not expect to affect
our collection of information burden estimates for CY 2020: (1)
Eliminate the requirement that, for the FY 2020 payment adjustment
year, for an eligible hospital that has not successfully demonstrated
it is a meaningful EHR user in a prior year, the EHR reporting period
in CY 2019 must end before and the eligible hospital must successfully
register for and attest to meaningful use no later than October 1, 2019
deadline; (2) establish an EHR reporting period of a minimum of any
continuous 90-day period in CY 2021 for new and returning participants
(eligible hospitals and CAHs) in the Medicare Promoting
Interoperability Program attesting to CMS; (3) require that the
Medicare Promoting Interoperability Program measure actions must occur
within the EHR reporting period beginning with the EHR reporting period
in CY 2020; (4) revise the Query of PDMP measure to make it an optional
measure worth five bonus points in CY 2020, remove the exclusions
associated with this measure in CY 2020, and clearly state our intended
policy that the measure is worth a full 5 bonus points in CY 2019 and
CY 2020; (5) change the maximum points available for the e-Prescribing
measure to 10 points beginning in CY 2020, in the event we finalize the
proposed changes to the Query of PDMP measure; (6) remove the Verify
Opioid Treatment Agreement measure beginning in CY 2020 and clearly
state our intended policy that the measure is worth a full 5 bonus
points in CY 2019; and (7) revise the Support Electronic Referral Loops
by Receiving and Incorporating Health Information measure to more
clearly capture the previously established policy regarding CHERT use.
We also are proposing to amend our regulations to incorporate several
of these proposals.
Although we are proposing to remove the Verify Opioid Treatment
Agreement measure, we do not anticipate a change of burden for the
Electronic Prescribing objective that this measure is associated with.
In the Medicare and Medicaid Programs; Electronic Health Record
Incentive Program--Stage 3 and Modifications to Meaningful Use in 2015
Through 2017 final rule (80 FR 62917), we estimated it would take an
individual provider or designee approximately 10 minutes to attest to
each objective and associated measure that requires a numerator and
denominator to be generated. For objectives and associated measures
requiring a numerator and denominator, we limit our estimates to
actions taken in the presence of certified EHR technology. We do not
anticipate a provider will maintain two recordkeeping systems when
certified EHR technology is present. Therefore, we assume that all
patient records that will be counted in the denominator will be kept
using certified EHR technology. In addition, our estimates, provided in
Table 21--Burden Estimates Stage 3--495.24 of the Medicare and Medicaid
Programs; Electronic Health Record Incentive Program--Stage 3 and
Modifications to Meaningful Use in 2015 Through 2017 final rule (80 FR
62918 through 62922), are calculated at the objective level, not for
each individual measure being reported. We relied on this approach to
create our burden estimates and determined that removing the Verify
Opioid Treatment Agreement measure would not change burden since
eligible hospitals and CAHs would still have to calculate a numerator
and denominator for the e-Prescribing measure, which is associated with
the Electronic Prescribing objective.
We anticipate that the burden will decrease for the Electronic
Prescribing objective due to the proposal to require a ``yes/no''
response instead of a numerator/denominator manual calculation for the
Query of PDMP measure. The current numerator/denominator response for
the Query of PDMP measure may require an eligible hospital or CAH to
manually calculate the numerators and denominators
[[Page 19577]]
outside of the certified EHR technology. The burden that was calculated
for the Electronic Prescribing objective included the numerator/
denominator calculated by the certified EHR technology, which is 10
minutes per respondent, plus the calculations performed manually
outside of the certified EHR technology for the Query of PDMP measure,
which we estimated at 40 minutes per respondent. We estimated that all
eligible hospitals and CAHs would take 40 minutes per respondent to
complete this measure by using the data found in certified EHR
technology and manually tracking the number of times that they query
the PDMP outside of certified EHR technology. This is a reduction in
total burden of 40 minutes per respondent from FY 2019 IPPS/LTCH PPS
final rule (83 FR 41698) reporting estimates which we estimate a total
burden estimate of 7 hours and 10.8 minutes per respondent. With the
proposed reporting requirement change for the Query of PDMP measure
from a numerator and denominator to a ``yes/no'' response beginning CY
2019, the certified EHR technology would be able to capture all of the
actions required for the measures associated with the Electronic
Prescribing objective; as a result, we estimate 10 minutes per
respondent for this objective.
In section VIII.D.6. of the preamble of this proposed rule, we are
making a number of proposals with respect to the reporting of CQM data,
including proposing to add two opioid-related measures beginning with
the reporting period in CY 2021 and proposing the reporting period,
reporting criteria, submission period, and form and method requirements
for CQM reporting in CY 2020. However, for the reporting period in CY
2020, these proposals are continuations of current policies and
therefore we do not believe that there would be a change in burden for
CY 2020.
c. Information Collection Burden Estimates for the Proposed Update to
the Query of PDMP Measure
In section VIII.D.3.b. of the preamble of this proposed rule, we
are proposing to change the Query of PDMP measure's reporting
requirement from a numerator and denominator to a ``yes/no'' response
beginning in CY 2019. We stated in the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41652) that we acknowledge that due to the varying integration
of PDMPs into EHR systems, additional time, workflow changes and manual
data capture and calculation would be needed to complete the query.
This would result in some eligible hospitals and CAHs having to
manually calculate the numerator and denominator for the Query of PDMP
measure. We estimated that the action for eligible hospitals and CAHs
to manually capture this measure would be a total of 40 minutes
respectively for CY 2019 and CY 2020. By proposing to reduce the Query
of PDMP measure reporting requirement from a numerator and denominator
to a ``yes/no'' response, manual calculation would not be required by
eligible hospitals and CAHs. We estimate that the change in reporting
requirement for the Query of PDMP measure would result in a reduction
of collection of information burden of 2,200 hours for eligible
hospitals and CAHs that attest to CMS under the Medicare Promoting
Interoperability Program for CY 2020. The total saving for CY 2019 and
CY 2020 is 4,400 collection of information burden hours.
--------------------------------------------------------------------------------------------------------------------------------------------------------
Total time (+/-
Proposal Estimated time for Total time (+/- hours) Estimated time for Total time (+/- hours) for CYs 2019
reporting CY 2019 for CY 2019 reporting CY 2020 hours) for CY 2020 and 2020
--------------------------------------------------------------------------------------------------------------------------------------------------------
Change reporting requirement for 3300 eligible -132,000 minutes or - 3300 eligible -132,100 minutes or - -264,000 minutes or -
the Query of PDMP measure. hospitals and CAHs x 2,200 hours. hospitals and CAHs x 2,200 hours. 4,400 hours.
40 minutes. 47 minutes.
--------------------------------------------------------------------------------------------------------------------------------------------------------
d. Summary of Collection of Information Burden Estimates
1. Summary of Estimates Used To Calculate the Collection of Information
Burden
In the Medicare and Medicaid Programs; Electronic Health Record
Incentive Program--Stage 3 and Modifications to Meaningful Use in 2015
Through 2017 final rule (80 FR 62917), we estimated it would take an
individual provider or designee approximately 10 minutes to attest to
each objective and associated measure that requires a numerator and
denominator to be generated. The measures that require a ``yes/no''
response would take approximately one minute to complete. We estimated
that the Security Risk Analysis measure would take approximately 6
hours for an individual provider or designee to complete (we note this
measure is still part of the program, but is not subject to
performance-based scoring). We continue to believe these are
appropriate burden estimates for reporting and have used this
methodology in our proposed collection of information burden estimates
for this proposed rule.
Given the proposals in this proposed rule, we estimate a total
burden estimate of 6 hours 31 minutes per respondent. This is a
reduction in total burden of 40 minutes per respondent from FY 2019
IPPS/LTCH PPS final rule (83 FR 41698) reporting estimates which we
estimate a total burden estimate of 7 hours and 10.8 minutes per
respondent. This represents a reduction of 2,200 total reporting hours
(40 minutes * 3300 respondents = 2,200 hours) for the Medicare
Promoting Interoperability Program.
Medicare Promoting Interoperability Program Estimated Annual Information Collection Burden Per Respondent for CY
2020: Sec. 495.24(e)--Objectives/Measures Medicare
[Eligible hospitals/CAHs]
----------------------------------------------------------------------------------------------------------------
Burden estimate per eligible hospital
Objective Measure and CAH
----------------------------------------------------------------------------------------------------------------
N/A..................................... Security Risk Analysis......... 6 hours.
[[Page 19578]]
Electronic Prescribing.................. e-Prescribing measure.......... 10 minutes.
Query of PDMP..................
Health Information Exchange............. Support Electronic Referral 10 minutes.
Loops by Sending Health
Information.
Support Electronic Referral
Loops by Receiving and
Incorporating Health.
Provider to Patient Exchange............ Provide Patients Electronic 10 minutes.
Access to Their Health
Information.
Public Health and Clinical Data Exchange Syndromic Surveillance 1 minute.
Reporting.
Immunization Registry
Reporting.
Electronic Case
Reporting.
Public Health Registry
Reporting.
Clinical Data
Registry--Reporting.
Electronic Reportable
Laboratory Result Reporting.
--------------------------------------
Total Burden Estimate per Respondent ............................... 6 hours 31 minutes (6.52 hours).
----------------------------------------------------------------------------------------------------------------
2. Hourly Labor Costs
In the Medicare and Medicaid Programs; Electronic Health Record
Incentive Program--Stage 3 and Modifications to Meaningful Use in 2015
Through 2017 final rule (80 FR 62917), we estimated a mean hourly rate
of $63.46 for the staff involved in attesting to EHR technology,
meaningful use objectives and associated measures, and electronically
submitting the clinical quality measures. We also used the mean hourly
rate of $67.25 for the staff involved in attesting the objectives and
measures under Sec. 495.24(e) in the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41698). Based on more recent 2017 data from the Bureau of Labor
Statistics (BLS), we are proposing to update this rate to $68.22 per
hour for CY 2020.\841\
---------------------------------------------------------------------------
\841\ https://www.bls.gov/oes/2017/may/oes231011.htm.
---------------------------------------------------------------------------
Based on the number of respondents for the Medicare Promoting
Interoperability Program, the estimated burden response per respondent
and the hourly labor cost of reporting, we estimate a total cost of
$1,442,512.50 for CY 2019 and $1,463,319 for CY 2020.
Medicare Promoting Interoperability Program Estimated Annual Information Collection Burden (Total Cost) for CY 2019
--------------------------------------------------------------------------------------------------------------------------------------------------------
Burden per Hourly labor
Regulations section Number of Number of response Total annual cost of Total cost ($)
respondents responses (hours) burden (hours) reporting ($)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Sec. 495.24(e).................................. 3,300 3,300 6.5 21,494 $67.25 1,442,512.50
--------------------------------------------------------------------------------------------------------------------------------------------------------
Medicare Promoting Interoperability Program Estimated Annual Information Collection Burden (Total Cost) for CY 2020
--------------------------------------------------------------------------------------------------------------------------------------------------------
Burden per Hourly labor
Regulations section Number of Number of response Total annual cost of Total cost ($)
respondents responses (hours) burden (hours) reporting ($)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Sec. 495.24(e).................................. 3,300 3,300 6.5 21,494 68.22 1,463,319
--------------------------------------------------------------------------------------------------------------------------------------------------------
This estimate takes into account the reduction of 2,200 total
reporting hours per CY and the finalized hourly labor cost for CY 2019
and the proposed updated hourly labor cost for CY 2020. This estimate
represents a cost reduction of $150,909.00 ($1,593,421.50-
$1,442,512.50) for the CY 2019 and $130,102.50 ($1,593,421.50-
$1,463,319) for the CY 2020 when comparing to the total cost from the
FY 2019 IPPS/LTCH PPS final rule (83 FR 41698) estimates.
10. ICRs for New Technology Add-On Payments
Section II.H. of the preamble of this proposed rule discusses new
technology add-on payments. Applicants for these add-on payments must
submit a formal request that includes information used to demonstrate
that the medical service or technology meets the new technology add-on
payment criteria. The burden associated with this application process
is the time and effort necessary for an applicant to complete and
submit the application and associated supporting information. The
burden associated with this requirement is subject to the PRA, and is
currently approved under OMB control number 0938-1347.
Section II.H.8. of the preamble of this proposed rule discusses a
proposed alternative inpatient new technology
[[Page 19579]]
add-on payment pathway for transformative new devices. The burden
associated with the changes that would be needed to the new technology
add-on payment application process if this proposal is finalized will
be discussed in a forthcoming revision of the information collection
requirement (ICR) request currently approved under OMB control number
0938-1347. The revised ICR request is currently under development.
However, upon completion of the revised ICR request, we will detail the
proposed revisions of the ICR and publish the required 60-day and 30-
day notices to solicit public comments in accordance with the
requirements of the PRA.
11. Summary of All Burden in This Proposed Rule
Below is a chart reflecting the total burden and associated costs
for the provisions included in this proposed rule.
------------------------------------------------------------------------
Burden hours
Information collection increase/decrease Cost (+/-) *
requests (+/-) *
------------------------------------------------------------------------
Application for GME Resident N/A N/A
Slots........................
Hospital Inpatient Quality +2,211 +$83,266
Reporting Program............
Hospital Value-Based N/A N/A
Purchasing Program \1\.......
HAC Reduction Program......... N/A N/A
Hospital Readmissions N/A N/A
Reduction Program \2\........
Promoting Interoperability -2,200 -$130,102
Programs.....................
LTCH Quality Reporting Program +39,244 +$2,282,346
PPS-Exempt Cancer Hospital -3 -$113
Quality Reporting Program....
-----------------------------------------
Total..................... +39,252 +$2,235,397
------------------------------------------------------------------------
* Numbers rounded.
\1\ Because the FY 2022 Hospital VBP Program will use data that are also
used to calculate quality measures in other programs and Medicare fee-
for-service claims data that hospitals are already submitting to CMS
for payment purposes, the program does not anticipate any change in
burden associated with this proposed rule.
\2\ Because the Hospital Readmissions Reduction Program measures are all
collected via Medicare fee-for-service claims that hospitals are
already submitting to CMS for payment purposes, there is no unique
information collection burden associated with the program.
C. Response to Comments
Because of the large number of public comments we normally receive
on Federal Register documents, we are not able to acknowledge or
respond to them individually. We will consider all comments we receive
by the date and time specified in the DATES section of this proposed
rule, and, when we proceed with a subsequent document(s), we will
respond to those comments in the preamble to that document.
XI. Provider Reimbursement Review Board Appeals
The Provider Reimbursement Review Board (PRRB) was established in
1972 to handle Medicare Part A provider cost reimbursement appeals.
Congress' intent with the creation of the PRRB was to provide an
administrative appeals forum for Medicare payment disputes, and an
opportunity for providers who are dissatisfied with the reimbursement
determination made by their Medicare contractor or CMS to request and
be afforded a hearing to adjudicate the issues involved.
Between 2015 and 2017, Medicare Part A providers filed cost report
appeals at a higher rate than were resolved. On average, 3,000 appeals
were filed per year and approximately 2,200 were resolved. The appeals
inventory is now over 10,000 (including approximately 5,000 group
appeals). The resolution process can take an average of 4 years,
excluding cases in district court. CMS, providers, and MACs must expend
considerable time and resources preparing and processing appeals.
As part of CMS' ongoing efforts to reduce provider burden, we are
examining the growing inventory of PRRB appeals. To date, we have
identified certain action initiatives that could be implemented with
the goal to: Decrease the number of appeals submitted; decrease the
number of appeals in inventory; reduce the time to resolution; and
increase customer satisfaction. Some examples of these initiatives are
as follows:
Develop standard formats and more structured data for
submitting cost reports and supplemental and supporting documentation.
Create more clear standards for documentation to be used
in auditing of cost reports.
Enhance the Medicare Cost Report Electronic Filing (MCReF)
portal by creating more automation for letter notifications, increasing
provider transparency during the cost report reconciliation process,
and improving the ability for providers to see where they are in the
process.
Explore opportunities to improve the process for claiming
DSH Medicaid eligible days as part of the annual Medicare cost report
submission and settlement process.
Utilize artificial intelligence (AI) design risk protocols
based on historical audit outcomes and empirical data to drive the
audit and desk review processes.
Triage the current appeals inventory and expand the
provider's utilization of PRRB rules 46 and 47.2.3 (that is, resolve
appeal issues through the cost report reopening process).
As part of this effort, in section IV.F.5. of the preamble of this
proposed rule, we are requesting public comments on PRRB appeals
related to a hospital's Medicaid fraction in the DSH payment adjustment
calculation.
List of Subjects
42 CFR Part 412
Administrative practice and procedure, Health facilities, Medicare,
Puerto Rico, Reporting and recordkeeping requirements.
42 CFR Part 413
Health facilities, Kidney diseases, Medicare, Puerto Rico,
Reporting and recordkeeping requirements.
42 CFR Part 495
Administrative practice and procedure, Electronic health records,
Health facilities, Health professions, Health maintenance organizations
(HMO), Medicaid, Medicare, Penalties, Privacy, Reporting and
recordkeeping requirements.
For the reasons set forth in the preamble, the Centers for Medicare
and Medicaid Services is proposing to amend 42 CFR Chapter IV as set
forth below:
[[Page 19580]]
PART 412--PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL
SERVICES
0
1. The authority citation for part 412 is revised to read as follows:
Authority: 42 U.S.C. 1302 and 1395hh.
0
2. Section 412.64 is amended by adding paragraph (d)(1)(viii) to read
as follows:
Sec. 412.64 Federal rates for inpatient operating costs for Federal
fiscal year 2005 and subsequent fiscal years.
* * * * *
(d) * * *
(1) * * *
(viii) For fiscal year 2020 and subsequent fiscal years, the
percentage increase in the market basket index (as defined in Sec.
413.40(a)(3) of this chapter) for prospective payment hospitals,
subject to the provisions of paragraphs (d)(2) and (3) of this section,
less a multifactor productivity adjustment (as determined by CMS).
* * * * *
0
3. Section 412.87 is amended by--
0
a. Redesignating paragraph (c) as paragraph (d);
0
b. Adding a new paragraph (c); and
0
c. Revising newly redesignated paragraph (d).
The addition and revision read as follows:
Sec. 412.87 Additional payment for new medical services and
technologies: General provisions.
* * * * *
(c) Eligibility criteria for alternative pathway for certain
transformative new devices. For discharges occurring on or after
October 1, 2020, CMS provides for additional payments (as specified in
Sec. 412.88) beyond the standard DRG payments and outlier payments to
a hospital for discharges involving covered inpatient hospital services
that are new medical devices, if the following conditions are met:
(1) A new medical device has received Food and Drug Administration
(FDA) marketing authorization and is part of the FDA's Breakthrough
Devices Program.
(2) A medical device that meets the condition in paragraph (c)(1)
of this section will be considered new for not less than 2 years and
not more than 3 years after the point at which data begin to become
available reflecting the inpatient hospital code (as defined in section
1886(d)(5)(K)(iii) of the Social Security Act) assigned to the new
technology (depending on when a new code is assigned and data on the
new technology become available for DRG recalibration). After CMS has
recalibrated the DRGs, based on available data, to reflect the costs of
an otherwise new medical technology, the medical technology will no
longer be considered ``new'' under the criterion of this section.
(3) The new medical device meets the conditions described in
paragraph (b)(3) of this section.
(d) Announcement of determinations and deadline for consideration
of new medical service or technology applications. CMS will consider
whether a new medical service or technology meets the eligibility
criteria specified in paragraph (b) or paragraph (c) of this section
and announce the results in the Federal Register as part of its annual
updates and changes to the IPPS. CMS will only consider any particular
new medical service or technology for add-on payments under paragraph
(b) or paragraph (c) of this section, and not both. In addition, CMS
will only consider, for add-on payments for a particular fiscal year,
an application for which the new medical service or technology has
received FDA approval or clearance by July 1 prior to the particular
fiscal year.
0
4. Section 412.88 is amended by revising paragraphs (a)(2) and (b) to
read as follows:
Sec. 412.88 Additional payment for new medical service or
technology.
(a) * * *
(2)(i) For discharges occurring before October 1, 2019. If the
costs of the discharge (determined by applying the operating cost-to-
charge ratios as described in Sec. 412.84(h)) exceed the full DRG
payment, an additional amount equal to the lesser of--
(A) 50 percent of the costs of the new medical service or
technology; or
(B) 50 percent of the amount by which the costs of the case exceed
the standard DRG payment.
(ii) For discharges occurring on or after October 1, 2019. If the
costs of the discharge (determined by applying the operating cost-to-
charge ratios as described in Sec. 412.84(h)) exceed the full DRG
payment, an additional amount equal to the lesser of--
(A) 65 percent of the costs of the new medical service or
technology; or
(B) 65 percent of the amount by which the costs of the case exceed
the standard DRG payment.
(b)(1) For discharges occurring before October 1, 2019. Unless a
discharge case qualifies for outlier payment under Sec. 412.84,
Medicare will not pay any additional amount beyond the DRG payment plus
50 percent of the estimated costs of the new medical service or
technology.
(2) For discharges occurring on or after October 1, 2019. Unless a
discharge case qualifies for outlier payment under Sec. 412.84,
Medicare will not pay any additional amount beyond the DRG payment plus
65 percent of the estimated costs of the new medical service or
technology.
0
5. Section 412.101 is amended by revising paragraph (e) to read as
follows:
Sec. 412.101 Special treatment: Inpatient hospital payment adjustment
for low-volume hospitals.
* * * * *
(e) Special treatment regarding hospitals operated by the Indian
Health Service (IHS) or a Tribe. (1) For discharges occurring in FY
2018 and subsequent fiscal years--
(i) A hospital operated by the IHS or a Tribe will be considered to
meet the applicable mileage criterion specified under paragraph (b)(2)
of this section if it is located more than the specified number of road
miles from the nearest subsection (d) hospital operated by the IHS or a
Tribe.
(ii) A hospital, other than a hospital operated by the IHS or a
Tribe, will be considered to meet the applicable mileage criterion
specified under paragraph (b)(2) of this section if it is located more
than the specified number of road miles from the nearest subsection (d)
hospital other than a subsection (d) hospital operated by the IHS or a
Tribe.
(2) Subject to the requirements set forth in Sec. 405.1885 of this
chapter, a hospital may request the application of the policy described
in paragraph (e)(1) of this section for discharges occurring in FY 2011
through FY 2017.
0
6. Section 412.103 is amended by--
0
a. Revising paragraph (b)(3);
0
b. Adding paragraph (g)(1)(iii);
0
c. Revising paragraph (g)(2)(iii); and
0
d. Adding paragraphs (g)(3) and (4).
The revisions and additions read as follows:
Sec. 412.103 Special treatment: Hospitals located in urban areas and
that apply for reclassification as rural.
* * * * *
(b) * * *
(3) Submission of application. An application may be submitted to
the CMS Regional Office by the requesting hospital by mail or by
facsimile or other electronic means.
* * * * *
(g) * * *
(1) * * *
(iii) The provisions of paragraphs (g)(1)(i) and (ii) of this
section are effective for all written requests submitted by hospitals
before October 1, 2019 to cancel rural reclassifications.
[[Page 19581]]
(2) * * *
(iii) The provisions of paragraphs (g)(2)(i) and (ii) of this
section are effective for all written requests submitted by hospitals
on or after October 1, 2007 and before October 1, 2019, to cancel rural
reclassifications.
(3) Cancellation of rural reclassification on or after October 1,
2019. For all written requests submitted by hospitals on or after
October, 1, 2019 to cancel rural reclassifications, a hospital may
cancel its rural reclassification by submitting a written request to
the CMS Regional Office not less than 120 days prior to the end of a
Federal fiscal year. The hospital's cancellation of the classification
is effective beginning with the next Federal fiscal year.
(4) Special rule for hospitals that opt to receive county out-
migration adjustment. A rural reclassification will be considered
canceled effective for the next Federal fiscal year when a hospital, by
submitting a request to CMS within 45 days of the date of public
display of the proposed rule for the next Federal fiscal year at the
Office of the Federal Register, opts to accept and receives its county
out-migration wage index adjustment determined under section
1886(d)(13) of the Act in lieu of its geographic reclassification
described under section 1886(d)(8)(B) of the Act.
0
7. Section 412.106 is amended by adding paragraph (g)(1)(iii)(C)(6) to
read as follows:
Sec. 412.106 Special treatment: Hospitals that serve a
disproportionate share of low-income patients.
* * * * *
(g) * * *
(1) * * *
(iii) * * *
(C) * * *
(6) For fiscal year 2020, CMS will base its estimates of the amount
of hospital uncompensated care on data on uncompensated care costs,
defined as charity care costs plus non-Medicare and non-reimbursable
Medicare bad debt costs from 2015 cost reports from the most recent
HCRIS database extract, except that, for Puerto Rico hospitals and
Indian Health Service or Tribal hospitals, CMS will base its estimates
on utilization data for Medicaid and Medicare SSI patients, as
determined by CMS in accordance with paragraphs (b)(2)(i) and (b)(4) of
this section, using data on Medicaid utilization from 2013 cost reports
from the most recent HCRIS database extract and the most recent
available year of data on Medicare SSI utilization (or, for Puerto Rico
hospitals, a proxy for Medicare SSI utilization data);
* * * * *
0
8. Section 412.152 is amended by revising the definitions of
``Aggregate payments for excess readmissions'', ``Applicable
condition'', ``Base operating DRG payment amount'', and ``Dual-
eligible'' to read as follows:
Sec. 412.152 Definitions for the Hospital Readmissions Reduction
Program.
* * * * *
Aggregate payments for excess readmissions is, for a hospital for
the applicable period, the sum, for the applicable conditions, of the
product for each applicable condition of:
(1) The base operating DRG payment amount for the hospital for the
applicable period for such condition or procedure;
(2) The number of admissions for such condition or procedure for
the hospital for the applicable period;
(3) The excess readmission ratio for the hospital for the
applicable period minus the peer-group median excess readmission ratio
(ERR); and
(4) The neutrality modifier, a multiplicative factor that equates
total Medicare savings under the current stratified methodology to the
previous non-stratified methodology.
Applicable condition is a condition or procedure selected by the
Secretary--
(1) Among the conditions and procedures for which--
(i) Readmissions represent conditions or procedures that are high
volume or high expenditures; and
(ii) Measures of such readmissions have been endorsed by the entity
with a contract under section 1890(a) of the Act and such endorsed
measures have exclusions for readmissions that are unrelated to the
prior discharge (such as a planned readmission or transfer to another
applicable hospital); or
(2) Among other conditions and procedures as determined appropriate
by the Secretary. In expanding the applicable conditions, the Secretary
will seek endorsement of the entity with a contract under section
1890(a) of the Act, but may apply such measures without such an
endorsement in the case of a specified area or medical topic determined
appropriate by the Secretary for which a feasible and practical measure
has not been endorsed by the entity with a contract under section
1890(a) of the Act as long as due consideration is given to measures
that have been endorsed or adopted by a consensus organization
identified by the Secretary.
* * * * *
Base operating DRG payment amount is the wage-adjusted DRG
operating payment plus any applicable new technology add-on payments
under subpart F of this part. This amount is determined without regard
to any payment adjustments under the Hospital Value-Based Purchasing
Program, as specified under Sec. 412.162. This amount does not include
any additional payments for indirect medical education under Sec.
412.105, the treatment of a disproportionate share of low-income
patients under Sec. 412.106, outliers under subpart F of this part,
and a low volume of discharges under Sec. 412.101. With respect to a
sole community hospital that receives payments under Sec. 412.92(d) or
a Medicare-dependent, small rural hospital that receives payments under
Sec. 412.108(c), this amount also includes the difference between the
hospital-specific payment rate and the Federal payment rate determined
under subpart D of this part. With respect to a hospital that is paid
under section 1814(b)(3) of the Act, this amount is an amount equal to
the wage-adjusted DRG payment amount plus new technology payments that
would be paid to such hospitals, absent the provisions of section
1814(b)(3) of the Act.
Dual-eligible. (1) For payment adjustment factor calculations prior
to the FY 2021 program year, is a patient beneficiary who has been
identified as having full benefit status in both the Medicare and
Medicaid programs in the State Medicare Authorization Act (MMA) files
for the month the beneficiary was discharged from the hospital; and
(2) For payment adjustment factor calculations beginning in the FY
2021 program year, is a patient beneficiary who has been identified as
having full benefit status in both the Medicare and Medicaid programs
in data sourced from the State MMA files for the month the beneficiary
was discharged from the hospital, except for those patient
beneficiaries who die in the month of discharge, which will be
identified using the previous month's data as sourced from the State
MMA files.
* * * * *
0
9. Section 412.154 is amended by redesignating paragraph (e)(4) as
paragraph (e)(6) and adding paragraphs (e)(4) and (5) to read as
follows:
Sec. 412.154 Payment adjustments under the Hospital Readmissions
Reduction Program.
* * * * *
(e) * * *
(4) The neutrality modifier.
(5) The proportion of dual-eligibles.
* * * * *
[[Page 19582]]
0
10. Section 412.172 is amended by revising paragraphs (f)(2) and (4) to
read as follows:
Sec. 412.172 Payment adjustments under the Hospital-Acquired
Condition Reduction Program.
* * * * *
(f) * * *
(2) Hospitals will have a period of 30 days after the receipt of
the information provided under paragraph (f)(1) of this section to
review and submit corrections for the hospital-acquired condition
program scores for each condition that is used to calculate the total
hospital-acquired condition score for the fiscal year.
* * * * *
(4) CMS will post the total hospital-acquired condition score and
the score on each measure for each hospital on the Hospital Compare
website.
* * * * *
0
11. Section 412.230 is amended by revising paragraph (a)(4) to read as
follows:
Sec. 412.230 Criteria for an individual hospital seeking
redesignation to another rural area or an urban area.
(a) * * *
(4) Application of criteria. In applying the numeric criteria
contained in paragraphs (b)(1) and (2) and (d)(1)(iii) and (iv) of this
section, rounding of numbers to meet the mileage or qualifying
percentage standards is not permitted.
* * * * *
0
12. Section 412.256 is amended by revising paragraph (a)(1) to read as
follows:
Sec. 412.256 Application requirements.
(a) * * *
(1) An application must be submitted to the MGCRB according to the
method prescribed by the MGCRB.
* * * * *
0
13. Section 412.522 is amended by adding paragraphs (d)(3) through (6)
to read as follows:
Sec. 412.522 Application of site neutral payment rate.
* * * * *
(d) * * *
(3) For cost reporting periods beginning on or after October 1,
2019, if a long-term care hospital's discharge payment percentage for
the cost reporting period is not at least 50 percent, discharges in all
cost reporting periods beginning after the notification described under
paragraph (d)(2) of this section will be paid under the payment
adjustment described in paragraph (d)(4) of this section until
reinstated under paragraph (d)(5) or (6) of this section.
(4) For cost reporting periods subject to the payment adjustment
under paragraph (d)(3) of this section, the payment for all discharges
consists of--
(i) An amount comparable to the hospital inpatient prospective
payment system amount as determined under Sec. 412.529(d)(4)(i)(A) and
(d)(4)(ii); and
(ii) If applicable, an additional payment for high cost outlier
cases based on the fixed-loss amount established for the hospital
inpatient prospective payment system in effect at the time of the LTCH
discharge.
(5) For full reinstatement--
(i) When the discharge payment percentage for a cost reporting
period is at least 50 percent, the payment adjustment described in
paragraph (d)(4) of this section will be discontinued for cost
reporting periods beginning on or after the notification described
under paragraph (d)(2) of this section.
(ii) A long-term care hospital reinstated under paragraph (d)(5)(i)
of this section will be subject to the payment adjustment under
paragraph (d)(4) of this section if, after being reinstated, it again
meets the criteria in paragraph (d)(3) of this section.
(6) For special probationary reinstatement--
(i) A hospital that would be subject to the payment adjustment
under paragraph (d)(4) of this section for a cost reporting period will
have the payment adjustment delayed for that period if, for the period
of at least 5 consecutive months of the immediately preceding 6-month
period, the discharge payment percentage is at least 50 percent.
(ii) For any cost reporting period for which the payment adjustment
under paragraph (d)(4) of this section was delayed under paragraph
(d)(6)(i) of this section, the payment adjustment under paragraph
(d)(4) of this section will be applied if the discharge payment
percentage for such cost reporting period is not at least 50 percent.
0
14. Section 412.523 is amended by adding paragraph (c)(3)(xvi) to read
as follows:
Sec. 412.523 Methodology for calculating the Federal prospective
payment rate.
* * * * *
(c) * * *
(3) * * *
(xvi) For long-term care prospective payment system fiscal year
beginning October 1, 2019, and ending September 30, 2020. The long-term
care hospital prospective payment system standard Federal payment rate
for the long-term care hospital prospective payment system beginning
October 1, 2019 and ending September 30, 2020 is the standard Federal
payment rate for the previous long-term care prospective payment system
fiscal year updated by 2.7 percent and further adjusted, as
appropriate, as described in paragraph (d) of this section.
* * * * *
0
15. Section 412.560 is amended by revising paragraphs (d)(1) and (3)
and (f)(1) to read as follows:
Sec. 412.560 Requirements under the Long-Term Care Hospital Quality
Reporting Program (LTCH QRP).
* * * * *
(d) * * *
(1) Written letter of non-compliance decision. Long-term care
hospitals that do not meet the requirement in paragraph (b) of this
section for a program year will receive a notification of non-
compliance sent through at least one of the following methods: The CMS
designated data submission system, the United States Postal Service, or
via an email from the MAC.
* * * * *
(3) CMS decision on reconsideration request. CMS will notify long-
term care hospitals, in writing, of its final decision regarding any
reconsideration request through at least one of the following methods:
The CMS designated data submission system, the United States Postal
Service, or via an email from the MAC.
* * * * *
(f) * * *
(1) Long-term care hospitals must meet or exceed two separate data
completeness thresholds: One threshold set at 80 percent for completion
of measures data and standardized patient assessment data collected
using the LTCH CARE Data Set submitted through the CMS designated data
submission system; and a second threshold set at 100 percent for
measures data collected and submitted using the CDC NHSN.
* * * * *
PART 413--PRINCIPLES OF REASONABLE COST REIMBURSEMENT; PAYMENT FOR
END-STAGE RENAL DISEASE SERVICES; OPTIONAL PROSPECTIVELY DETERMINED
PAYMENT RATES FOR SKILLED NURSING FACILITIES
0
16. The authority for part 413 is revised to read as follows:
Authority: 42 U.S.C. 1302, 1395d(d), 1395f(b), 1395g, 1395l(a),
(i), and (n), 1395x(v), 1395hh, 1395rr, 1395tt, and 1395ww.
[[Page 19583]]
0
17. Section 413.70 is amended by revising paragraph (b)(5)(i)(C) and
adding paragraph (b)(5)(i)(D) to read as follows:
Sec. 413.70 Payment for services of a CAH.
* * * * *
(b) * * *
(5) * * *
(i) * * *
(C) Effective for cost reporting periods beginning on or after
October 1, 2011 and on or before September 30, 2019, payment for
ambulance services furnished by a CAH or an entity that is owned and
operated by a CAH is 101 percent of the reasonable costs of the CAH or
the entity in furnishing those services, but only if the CAH or the
entity is the only provider or supplier of ambulance services located
within a 35-mile drive of the CAH. If there is no provider or supplier
of ambulance services located within a 35-mile drive of the CAH and
there is an entity that is owned and operated by a CAH that is more
than a 35-mile drive from the CAH, payment for ambulance services
furnished by that entity is 101 percent of the reasonable costs of the
entity in furnishing those services, but only if the entity is the
closest provider or supplier of ambulance services to the CAH. (D)
Effective for cost reporting periods beginning on or after October 1,
2019, payment for ambulance services furnished by a CAH or by a CAH-
owned and operated entity is 101 percent of the reasonable costs of the
CAH or the entity in furnishing those services, but only if the CAH or
the entity is the only provider or supplier of ambulance services
located within a 35-mile drive of the CAH, excluding ambulance
providers or suppliers that are not legally authorized to furnish
ambulance services to transport individuals to or from the CAH. If
there is no provider or supplier of ambulance services located within a
35-mile drive of the CAH and there is an entity that is owned and
operated by a CAH that is more than a 35-mile drive from the CAH,
payment for ambulance services furnished by that entity is 101 percent
of the reasonable costs of the entity in furnishing those services, but
only if the entity is the closest provider or supplier of ambulance
services to the CAH.
* * * * *
PART 495--STANDARDS FOR THE ELECTRONIC HEALTH RECORD TECHNOLOGY
INCENTIVE PROGRAM
0
18. The authority citation for part 495 continues to read as follows:
Authority: 42 U.S.C. 1302 and 1395hh.
0
19. Section 495.4 is amended--
0
a. In the definition of ``EHR reporting period'', by adding paragraph
(2)(v); and
0
b. In the definition of ``EHR reporting period for a payment
adjustment year'', by revising paragraph (2)(iii)(A) and adding
paragraphs (2)(v) and (3)(v).
The additions and revision read as follows:
Sec. 495.4 Definitions.
* * * * *
EHR reporting period. * * *
(2) * * *
(v) For the FY 2021 payment year as follows: Under the Medicare
Promoting Interoperability Program, for a Puerto Rico eligible
hospital, any continuous 90-day period within CY 2021.
EHR reporting period for a payment adjustment year. * * *
(2) * * *
(iii) * * *
(A) If an eligible hospital has not successfully demonstrated it is
a meaningful EHR user in a prior year, the EHR reporting period is any
continuous 90-day period within CY 2019 and applies for the FY 2020 and
FY 2021 payment adjustment years.
* * * * *
(v) The following are applicable for 2021:
(A) If an eligible hospital has not successfully demonstrated it is
a meaningful EHR user in a prior year, the EHR reporting period is any
continuous 90-day period within CY 2021 and applies for the FY 2022 and
2023 payment adjustment years. For the FY 2022 payment adjustment year,
the EHR reporting period must end before and the eligible hospital must
successfully register for and attest to meaningful use no later than
October 1, 2021.
(B) If in a prior year an eligible hospital has successfully
demonstrated it is a meaningful EHR user, the EHR reporting period is
any continuous 90-day period within CY 2021 and applies for the FY 2023
payment adjustment year.
(3) * * *
(v) The following are applicable for 2021:
(A) If a CAH has not successfully demonstrated it is a meaningful
EHR user in a prior year, the EHR reporting period is any continuous
90-day period within CY 2021 and applies for the FY 2021 payment
adjustment year.
(B) If in a prior year a CAH has successfully demonstrated it is a
meaningful EHR user, the EHR reporting period is any continuous 90-day
period within CY 2021 and applies for the FY 2021 payment adjustment
year.
* * * * *
0
20. Section 495.24 is amended by revising paragraphs (e)(1),
(e)(4)(iii), (e)(5)(ii)(B), (e)(5)(iii) through (v), and (e)(6)(ii)(B)
to read as follows:
Sec. 495.24 Stage 3 meaningful use objectives and measures for EPs,
eligible hospitals and CAHs for 2019 and subsequent years.
* * * * *
(e) * * *
(1) General rule. (i) Except as specified in paragraph (e)(2) of
this section, eligible hospitals and CAHs must meet all objectives and
associated measures of the Stage 3 criteria specified in this paragraph
(e) and earn a total score of at least 50 points to meet the definition
of a meaningful EHR user.
(ii) Beginning in CY 2020, the numerator and denominator of
measures increment based on actions occurring during the EHR reporting
period selected by the eligible hospital or CAH, unless otherwise
indicated.
* * * * *
(4) * * *
(iii) Security risk analysis measure. Conduct or review a security
risk analysis in accordance with the requirements under 45 CFR
164.308(a)(1), including addressing the security (including encryption)
of data created or maintained by CEHRT in accordance with requirements
under 45 CFR 164.312(a)(2)(iv) and 45 CFR 164.306(d)(3), implement
security updates as necessary, and correct identified security
deficiencies as part of the provider's risk management process. Actions
included in the security risk analysis measure may occur any time
during the calendar year in which the EHR reporting period occurs.
(5) * * *
(ii) * * *
(B) In 2020 and subsequent years, eligible hospitals and CAHs must
meet the e-Prescribing measure in paragraph (e)(5)(iii)(A) of this
section and have the option to report on the query of PDMP measure in
paragraph (e)(5)(iii)(B) of this section. In 2020 and subsequent years,
the electronic prescribing objective in paragraph (e)(5)(i) of this
section is worth up to 15 points.
(iii) Measures--(A) e-Prescribing measure. Subject to paragraph
(e)(3) of this section, at least one hospital discharge medication
order for permissible prescriptions (for new and changed prescriptions)
is queried for a drug formulary and transmitted electronically using
CEHRT. This measure is worth up to 10 points in CY 2019 and subsequent
years.
(B) Query of prescription drug monitoring program (PDMP) measure.
Subject to paragraph (e)(3) of this section, for at least one Schedule
II
[[Page 19584]]
opioid electronically prescribed using CEHRT during the EHR reporting
period, the eligible hospital or CAH uses data from CEHRT to conduct a
query of a Prescription Drug Monitoring Program (PDMP) for prescription
drug history, except where prohibited and in accordance with applicable
law. This measure is worth 5 bonus points in CY 2019 and CY 2020.
(C) Verify opioid treatment agreement measure. Subject to paragraph
(e)(3) of this section, for at least one unique patient for whom a
Schedule II opioid was electronically prescribed by the eligible
hospital or CAH using CEHRT during the EHR reporting period, if the
total duration of the patient's Schedule II opioid prescriptions is at
least 30 cumulative days within a 6-month look-back period, the
eligible hospital or CAH seeks to identify the existence of a signed
opioid treatment agreement and incorporates it into the patient's
electronic health record using CEHRT. This measure is worth 5 bonus
points in CY 2019.
(iv) Exclusions in accordance with paragraph (e)(2) of this section
and redistribution of points. An exclusion claimed under paragraph
(e)(5)(v) of this section will redistribute 10 points in CY 2019 and CY
2020 equally among the measures associated with the health information
exchange objective under paragraph (e)(6) of this section.
(v) Exclusion in accordance with paragraph (e)(2) of this section.
Beginning with the EHR reporting period in CY 2019, any eligible
hospital or CAH that does not have an internal pharmacy that can accept
electronic prescriptions and there are no pharmacies that accept
electronic prescriptions within 10 miles at the start of the eligible
hospital or CAH's EHR reporting period may be excluded from the measure
specified in paragraph (e)(5)(iii)(A) of this section.
(6) * * *
(ii) * * *
(B) Support electronic referral loops by receiving and
incorporating health information measure: Subject to paragraph (e)(3)
of this section, for at least one electronic summary of care record
received using CEHRT for patient encounters during the EHR reporting
period for which an eligible hospital or CAH was the receiving party of
a transition of care or referral, or for patient encounters during the
EHR reporting period in which the eligible hospital or CAH has never
before encountered the patient, the eligible hospital or CAH conducts
clinical information reconciliation for medication, medication allergy,
and current problem list using CEHRT.
* * * * *
Dated: March 26, 2019.
Seema Verma,
Administrator, Centers for Medicare and Medicaid Services.
Dated: April 2, 2019.
Alex M. Azar II,
Secretary, Department of Health and Human Services.
Note: The following Addendum and Appendices will not appear in
the Code of Federal Regulations.
Addendum--Schedule of Standardized Amounts, Update Factors, Rate-of-
Increase Percentages Effective With Cost Reporting Periods Beginning on
or After October 1, 2019, and Payment Rates for LTCHs Effective for
Discharges Occurring on or After October 1, 2019
I. Summary and Background
In this Addendum, we are setting forth a description of the methods
and data we used to determine the proposed prospective payment rates
for Medicare hospital inpatient operating costs and Medicare hospital
inpatient capital-related costs for FY 2020 for acute care hospitals.
We also are setting forth the rate-of-increase percentage for updating
the target amounts for certain hospitals excluded from the IPPS for FY
2020. We note that, because certain hospitals excluded from the IPPS
are paid on a reasonable cost basis subject to a rate-of-increase
ceiling (and not by the IPPS), these hospitals are not affected by the
proposed figures for the standardized amounts, offsets, and budget
neutrality factors. Therefore, in this proposed rule, we are setting
forth the rate-of-increase percentage for updating the target amounts
for certain hospitals excluded from the IPPS that will be effective for
cost reporting periods beginning on or after October 1, 2019.
In addition, we are setting forth a description of the methods and
data we used to determine the proposed LTCH PPS standard Federal
payment rate that would be applicable to Medicare LTCHs for FY 2020.
In general, except for SCHs and MDHs, for FY 2020, each hospital's
payment per discharge under the IPPS is based on 100 percent of the
Federal national rate, also known as the national adjusted standardized
amount. This amount reflects the national average hospital cost per
case from a base year, updated for inflation.
SCHs are paid based on whichever of the following rates yields the
greatest aggregate payment: The Federal national rate (including, as
discussed in section IV.G. of the preamble of this proposed rule,
uncompensated care payments under section 1886(r)(2) of the Act); the
updated hospital-specific rate based on FY 1982 costs per discharge;
the updated hospital-specific rate based on FY 1987 costs per
discharge; the updated hospital-specific rate based on FY 1996 costs
per discharge; or the updated hospital-specific rate based on FY 2006
costs per discharge.
Under section 1886(d)(5)(G) of the Act, MDHs historically were paid
based on the Federal national rate or, if higher, the Federal national
rate plus 50 percent of the difference between the Federal national
rate and the updated hospital-specific rate based on FY 1982 or FY 1987
costs per discharge, whichever was higher. However, section 5003(a)(1)
of Public Law 109-171 extended and modified the MDH special payment
provision that was previously set to expire on October 1, 2006, to
include discharges occurring on or after October 1, 2006, but before
October 1, 2011. Under section 5003(b) of Public Law 109-171, if the
change results in an increase to an MDH's target amount, we must rebase
an MDH's hospital specific rates based on its FY 2002 cost report.
Section 5003(c) of Public Law 109-171 further required that MDHs be
paid based on the Federal national rate or, if higher, the Federal
national rate plus 75 percent of the difference between the Federal
national rate and the updated hospital specific rate. Further, based on
the provisions of section 5003(d) of Public Law 109-171, MDHs are no
longer subject to the 12-percent cap on their DSH payment adjustment
factor. Section 50205 of the Bipartisan Budget Act of 2018 extended the
MDH program for discharges on or after October 1, 2017 through
September 30, 2022.
As discussed in section IV.B. of the preamble of this proposed
rule, in accordance with section 1886(d)(9)(E) of the Act as amended by
section 601 of the Consolidated Appropriations Act, 2016 (Pub. L. 114-
113), for FY 2020, subsection (d) Puerto Rico hospitals will continue
to be paid based on 100 percent of the national standardized amount.
Because Puerto Rico hospitals are paid 100 percent of the national
standardized amount and are subject to the same national standardized
amount as subsection (d) hospitals that receive the full update, our
discussion below does not include references to the Puerto Rico
standardized amount or the Puerto Rico-specific wage index.
As discussed in section II. of this Addendum, we are proposing to
make changes in the determination of the prospective payment rates for
Medicare
[[Page 19585]]
inpatient operating costs for acute care hospitals for FY 2020. In
section III. of this Addendum, we discuss our proposed policy changes
for determining the prospective payment rates for Medicare inpatient
capital-related costs for FY 2020. In section IV. of this Addendum, we
are setting forth the rate-of-increase percentage for determining the
rate-of-increase limits for certain hospitals excluded from the IPPS
for FY 2020. In section V. of this Addendum, we discuss proposed policy
changes for determining the LTCH PPS standard Federal rate for LTCHs
paid under the LTCH PPS for FY 2020. The tables to which we refer to in
the preamble of this proposed rule are listed in section VI. of this
Addendum and are available via the internet on the CMS website.
II. Proposed Changes to Prospective Payment Rates for Hospital
Inpatient Operating Costs for Acute Care Hospitals for FY 2020
The basic methodology for determining prospective payment rates for
hospital inpatient operating costs for acute care hospitals for FY 2005
and subsequent fiscal years is set forth under Sec. 412.64. The basic
methodology for determining the prospective payment rates for hospital
inpatient operating costs for hospitals located in Puerto Rico for FY
2005 and subsequent fiscal years is set forth under Sec. Sec. 412.211
and 412.212. Below we discuss the factors we are proposing to use for
determining the proposed prospective payment rates for FY 2020.
In summary, the proposed standardized amounts set forth in Tables
1A, 1B, and 1C that are listed and published in section VI. of this
Addendum (and available via the internet on the CMS website) reflect--
Equalization of the standardized amounts for urban and
other areas at the level computed for large urban hospitals during FY
2004 and onward, as provided for under section 1886(d)(3)(A)(iv)(II) of
the Act.
The labor-related share that is applied to the
standardized amounts to give the hospital the highest payment, as
provided for under sections 1886(d)(3)(E) and 1886(d)(9)(C)(iv) of the
Act. For FY 2020, depending on whether a hospital submits quality data
under the rules established in accordance with section
1886(b)(3)(B)(viii) of the Act (hereafter referred to as a hospital
that submits quality data) and is a meaningful EHR user under section
1886(b)(3)(B)(ix) of the Act (hereafter referred to as a hospital that
is a meaningful EHR user), there are four possible applicable
percentage increases that can be applied to the national standardized
amount. We refer readers to section IV.B. of the preamble of this
proposed rule for a complete discussion on the proposed FY 2020
inpatient hospital update. Below is a table with these four scenarios:
Proposed FY 2020 Applicable Percentage Increases for the IPPS
----------------------------------------------------------------------------------------------------------------
Hospital Hospital Hospital did Hospital did
submitted submitted NOT submit NOT submit
quality data quality data quality data quality data
FY 2020 and is a and is NOT a and is a and is NOT a
meaningful EHR meaningful EHR meaningful EHR meaningful EHR
user user user user
----------------------------------------------------------------------------------------------------------------
Proposed Market Basket 3.2 3.2 3.2 3.2
Rate[dash]of[dash]Increase.....................
Proposed Adjustment for Failure to Submit 0 0 -0.8 -0.8
Quality Data under Section 1886(b)(3)(B)(viii)
of the Act.....................................
Proposed Adjustment for Failure to be a 0 -2.4 0 -2.4
Meaningful EHR User under Section
1886(b)(3)(B)(ix) of the Act...................
Proposed MFP Adjustment under Section -0.5 -0.5 -0.5 -0.5
1886(b)(3)(B)(xi) of the Act...................
Proposed Applicable Percentage Increase Applied 2.7 0.3 1.9 -0.5
to Standardized Amount.........................
----------------------------------------------------------------------------------------------------------------
We note that section 1886(b)(3)(B)(viii) of the Act, which
specifies the adjustment to the applicable percentage increase for
``subsection (d)'' hospitals that do not submit quality data under the
rules established by the Secretary, is not applicable to hospitals
located in Puerto Rico.
In addition, section 602 of Public Law 114-113 amended section
1886(n)(6)(B) of the Act to specify that Puerto Rico hospitals are
eligible for incentive payments for the meaningful use of certified EHR
technology, effective beginning FY 2016, and also to apply the
adjustments to the applicable percentage increase under section
1886(b)(3)(B)(ix) of the Act to Puerto Rico hospitals that are not
meaningful EHR users, effective FY 2022. Accordingly, because the
provisions of section 1886(b)(3)(B)(ix) of the Act are not applicable
to hospitals located in Puerto Rico until FY 2022, the adjustments
under this provision are not applicable for FY 2020.
An adjustment to the standardized amount to ensure budget
neutrality for DRG recalibration and reclassification, as provided for
under section 1886(d)(4)(C)(iii) of the Act.
An adjustment to ensure the wage index and labor-related
share changes (depending on the fiscal year) are budget neutral, as
provided for under section 1886(d)(3)(E)(i) of the Act (as discussed in
the FY 2006 IPPS final rule (70 FR 47395) and the FY 2010 IPPS final
rule (74 FR 44005). We note that section 1886(d)(3)(E)(i) of the Act
requires that when we compute such budget neutrality, we assume that
the provisions of section 1886(d)(3)(E)(ii) of the Act (requiring a 62-
percent labor-related share in certain circumstances) had not been
enacted.
An adjustment to ensure the effects of geographic
reclassification are budget neutral, as provided for under section
1886(d)(8)(D) of the Act, by removing the FY 2019 budget neutrality
factor and applying a revised factor.
A positive adjustment of 0.5 percent in FYs 2019 through
2023 as required under section 414 of the MACRA.
An adjustment to ensure the effects of the Rural Community
Hospital Demonstration program are budget neutral as required under
section 410A(c)(2) of Public Law 108-173. This demonstration program is
required under section 410A of Public Law 108-173, as amended by
sections 3123 and 10313 of Public Law 111-148, which extended the
demonstration program for an additional 5 years, as amended by section
15003 of Public Law 114-255
[[Page 19586]]
which amended section 410A of Public Law 108-173 to provide for a 10-
year extension of the demonstration program (in place of the 5-year
extension required by the Affordable Care Act) beginning on the date
immediately following the last day of the initial 5-year period under
section 410A(a)(5) of Public Law 108-173.
An adjustment to the standardized amount (using our
exceptions and adjustments authority under section 1886(d)(5)(I)(i) of
the Act) to implement in a budget neutral manner our proposed
transition (described in section III.N.3.d. of the preamble of this
proposed rule) for hospitals negatively impacted due to proposed
changes to the wage index. We refer readers to section III.N. of the
preamble of this proposed rule for a detailed discussion.
An adjustment to remove the FY 2019 outlier offset and
apply an offset for FY 2020, as provided for in section 1886(d)(3)(B)
of the Act.
For FY 2020, consistent with current law, we are proposing to apply
the rural floor budget neutrality adjustment to hospital wage indexes.
In addition, our proposals to increase the wage index values for
hospitals with a wage index value in the lowest quartile of the wage
index values across all hospitals and offset the estimated increase in
IPPS payments by decreasing the wage index values for hospitals with a
wage index value in the highest quartile of the wage index values
across all hospitals (high wage index hospitals) are adjustments
applied to hospital wage indexes. We refer readers to section III.N. of
the preamble of this proposed rule for a detailed discussion. Also,
consistent with section 3141 of the Affordable Care Act, instead of
applying a State-level rural floor budget neutrality adjustment to the
wage index, we are proposing to apply a uniform, national budget
neutrality adjustment to the FY 2020 wage index for the rural floor.
A. Calculation of the Proposed Adjusted Standardized Amount
1. Standardization of Base-Year Costs or Target Amounts
In general, the national standardized amount is based on per
discharge averages of adjusted hospital costs from a base period
(section 1886(d)(2)(A) of the Act), updated and otherwise adjusted in
accordance with the provisions of section 1886(d) of the Act. The
September 1, 1983 interim final rule (48 FR 39763) contained a detailed
explanation of how base-year cost data (from cost reporting periods
ending during FY 1981) were established for urban and rural hospitals
in the initial development of standardized amounts for the IPPS.
Sections 1886(d)(2)(B) and 1886(d)(2)(C) of the Act require us to
update base-year per discharge costs for FY 1984 and then standardize
the cost data in order to remove the effects of certain sources of cost
variations among hospitals. These effects include case-mix, differences
in area wage levels, cost-of-living adjustments for Alaska and Hawaii,
IME costs, and costs to hospitals serving a disproportionate share of
low-income patients.
For FY 2020, we are proposing to continue to use the national
labor-related and nonlabor-related shares (which are based on the 2014-
based hospital market basket) that were used in FY 2019. Specifically,
under section 1886(d)(3)(E) of the Act, the Secretary estimates, from
time to time, the proportion of payments that are labor-related and
adjusts the proportion (as estimated by the Secretary from time to
time) of hospitals' costs which are attributable to wages and wage-
related costs of the DRG prospective payment rates. We refer to the
proportion of hospitals' costs that are attributable to wages and wage-
related costs as the ``labor-related share.'' For FY 2020, as discussed
in section III. of the preamble of this proposed rule, we are proposing
to continue to use a labor-related share of 68.3 percent for the
national standardized amounts for all IPPS hospitals (including
hospitals in Puerto Rico) that have a wage index value that is greater
than 1.0000. Consistent with section 1886(d)(3)(E) of the Act, we are
proposing to apply the wage index to a labor-related share of 62
percent of the national standardized amount for all IPPS hospitals
(including hospitals in Puerto Rico) whose wage index values are less
than or equal to 1.0000.
The proposed standardized amounts for operating costs appear in
Tables 1A, 1B, and 1C that are listed and published in section VI. of
the Addendum to this proposed rule and are available via the internet
on the CMS website.
2. Computing the National Average Standardized Amount
Section 1886(d)(3)(A)(iv)(II) of the Act requires that, beginning
with FY 2004 and thereafter, an equal standardized amount be computed
for all hospitals at the level computed for large urban hospitals
during FY 2003, updated by the applicable percentage update.
Accordingly, we are proposing to calculate the FY 2020 national average
standardized amount irrespective of whether a hospital is located in an
urban or rural location.
3. Updating the National Average Standardized Amount
Section 1886(b)(3)(B) of the Act specifies the applicable
percentage increase used to update the standardized amount for payment
for inpatient hospital operating costs. We note that, in compliance
with section 404 of the MMA, in this proposed rule, we are proposing to
use the 2014-based IPPS operating and capital market baskets for FY
2020. As discussed in section IV.B. of the preamble of this proposed
rule, in accordance with section 1886(b)(3)(B) of the Act, as amended
by section 3401(a) of the Affordable Care Act, we are proposing to
reduce the FY 2020 applicable percentage increase (which for this
proposed rule is based on IGI's fourth quarter 2018 forecast of the
2014-based IPPS market basket) by the MFP adjustment (the 10-year
moving average of MFP for the period ending FY 2020) of 0.5 percentage
point, which for this proposed rule is also calculated based on IGI's
fourth quarter 2018 forecast.
Based on IGI's 2018 fourth quarter forecast of the hospital market
basket increase (as discussed in Appendix B of this proposed rule), the
forecast of the hospital market basket increase for FY 2020 for this
proposed rule is 3.2 percent. As discussed earlier, for FY 2020,
depending on whether a hospital submits quality data under the rules
established in accordance with section 1886(b)(3)(B)(viii) of the Act
and is a meaningful EHR user under section 1886(b)(3)(B)(ix) of the
Act, there are four possible applicable percentage increases that can
be applied to the standardized amount. We refer readers to section
IV.B. of the preamble of this proposed rule for a complete discussion
on the FY 2020 inpatient hospital update to the standardized amount. We
also refer readers to the table above for the four possible applicable
percentage increases that would be applied to update the national
standardized amount. The proposed standardized amounts shown in Tables
1A through 1C that are published in section VI. of this Addendum and
that are available via the internet on the CMS website reflect these
differential amounts.
Although the update factors for FY 2020 are set by law, we are
required by section 1886(e)(4) of the Act to recommend, taking into
account MedPAC's recommendations, appropriate update factors for FY
2020 for both IPPS hospitals and hospitals and hospital units excluded
from the IPPS. Section 1886(e)(5)(A) of the Act requires that we
publish our recommendations in the Federal
[[Page 19587]]
Register for public comment. Our recommendation on the update factors
is set forth in Appendix B of this proposed rule.
4. Methodology for Calculation of the Average Standardized Amount
The methodology we used to calculate the proposed FY 2020
standardized amount is as follows:
To ensure we are only including hospitals paid under the
IPPS in the calculation of the standardized amount, we applied the
following inclusion and exclusion criteria: Include hospitals whose
last four digits fall between 0001 and 0879 (section 2779A1 of Chapter
2 of the State Operations Manual on the CMS website at: https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/som107c02.pdf); exclude CAHs at the time of this proposed rule; exclude
hospitals in Maryland (because these hospitals are paid under an all
payer model under section 1115A of the Act); and remove PPS-excluded
cancer hospitals that have a ``V'' in the fifth position of their
provider number or a ``E'' or ``F'' in the sixth position.
As in the past, we are proposing to adjust the FY 2020
standardized amount to remove the effects of the FY 2019 geographic
reclassifications and outlier payments before applying the FY 2020
updates. We then applied budget neutrality offsets for outliers and
geographic reclassifications to the standardized amount based on
proposed FY 2020 payment policies.
We do not remove the prior year's budget neutrality
adjustments for reclassification and recalibration of the DRG relative
weights and for updated wage data because, in accordance with sections
1886(d)(4)(C)(iii) and 1886(d)(3)(E) of the Act, estimated aggregate
payments after updates in the DRG relative weights and wage index
should equal estimated aggregate payments prior to the changes. If we
removed the prior year's adjustment, we would not satisfy these
conditions.
Budget neutrality is determined by comparing aggregate IPPS
payments before and after making changes that are required to be budget
neutral (for example, changes to MS-DRG classifications, recalibration
of the MS-DRG relative weights, updates to the wage index, and
different geographic reclassifications). We include outlier payments in
the simulations because they may be affected by changes in these
parameters.
Consistent with our methodology established in the FY 2011
IPPS/LTCH PPS final rule (75 FR 50422 through 50433), because IME
Medicare Advantage payments are made to IPPS hospitals under section
1886(d) of the Act, we believe these payments must be part of these
budget neutrality calculations. However, we note that it is not
necessary to include Medicare Advantage IME payments in the outlier
threshold calculation or the outlier offset to the standardized amount
because the statute requires that outlier payments be not less than 5
percent nor more than 6 percent of total ``operating DRG payments,''
which does not include IME and DSH payments. We refer readers to the FY
2011 IPPS/LTCH PPS final rule for a complete discussion on our
methodology of identifying and adding the total Medicare Advantage IME
payment amount to the budget neutrality adjustments.
Consistent with the methodology in the FY 2012 IPPS/LTCH
PPS final rule, in order to ensure that we capture only fee-for-service
claims, we are only including claims with a ``Claim Type'' of 60 (which
is a field on the MedPAR file that indicates a claim is an FFS claim).
Consistent with our methodology established in the FY 2017
IPPS/LTCH PPS final rule (81 FR 57277), in order to further ensure that
we capture only FFS claims, we are excluding claims with a ``GHOPAID''
indicator of 1 (which is a field on the MedPAR file that indicates a
claim is not an FFS claim and is paid by a Group Health Organization).
Consistent with our methodology established in the FY 2011
IPPS/LTCH PPS final rule (75 FR 50422 through 50423), we examine the
MedPAR file and remove pharmacy charges for anti-hemophilic blood
factor (which are paid separately under the IPPS) with an indicator of
``3'' for blood clotting with a revenue code of ``0636'' from the
covered charge field for the budget neutrality adjustments. We also
remove organ acquisition charges from the covered charge field for the
budget neutrality adjustments because organ acquisition is a pass-
through payment not paid under the IPPS.
The participation of hospitals under the BPCI (Bundled
Payments for Care Improvement) Advanced Model started on October 1,
2018. The BPCI Advanced Model, tested under the authority of section
3021 of the Affordable Care Act (codified at section 1115A of the Act),
is comprised of a single payment and risk track, which bundles payments
for multiple services beneficiaries receive during a Clinical Episode.
Acute care hospitals may participate in the BPCI Advanced Model in one
of two capacities: As a model Participant or as a downstream Episode
Initiator. Regardless of the capacity in which they participate in the
BPCI Advanced Model, participating acute care hospitals will continue
to receive IPPS payments under section 1886(d) of the Act. Acute care
hospitals that are Participants also assume financial and quality
performance accountability for Clinical Episodes in the form of a
reconciliation payment. For additional information on the BPCI Advanced
Model, we refer readers to the BPCI Advanced web page on the CMS Center
for Medicare and Medicaid Innovation's website at: https://innovation.cms.gov/initiatives/bpci-advanced/.
For FY 2020, consistent with how we treated hospitals that
participated in the BPCI Advanced Model in the FY 2019 IPPS/LTCH PPS
final rule (83 FR 41259), we are proposing to include all applicable
data from subsection (d) hospitals participating in the BPCI Advanced
Model in our IPPS payment modeling and ratesetting calculations. We
believe it is appropriate to include all applicable data from the
subsection (d) hospitals participating in the BPCI Advanced Model in
our IPPS payment modeling and ratesetting calculations because these
hospitals are still receiving regular IPPS fee-for-service payments
under section 1886(d) of the Act. For the same reasons, we also are
proposing to include all applicable data from subsection (d) hospitals
participating in the Comprehensive Care for Joint Replacement (CJR)
Model in our IPPS payment modeling and ratesetting calculations.
Consistent with our methodology established in the FY 2013
IPPS/LTCH PPS final rule (77 FR 53687 through 53688), we believe that
it is appropriate to include adjustments for the Hospital Readmissions
Reduction Program and the Hospital VBP Program (established under the
Affordable Care Act) within our budget neutrality calculations.
Both the hospital readmissions payment adjustment (reduction) and
the hospital VBP payment adjustment (redistribution) are applied on a
claim-by-claim basis by adjusting, as applicable, the base-operating
DRG payment amount for individual subsection (d) hospitals, which
affects the overall sum of aggregate payments on each side of the
comparison within the budget neutrality calculations.
In order to properly determine aggregate payments on each side of
the comparison, consistent with the approach we have taken in prior
years, for FY 2020 and subsequent years, we are proposing to apply a
proposed proxy based on the prior fiscal year hospital readmissions
payment adjustment (for FY 2020, this would be FY 2019 final
[[Page 19588]]
adjustment factors) and a proposed proxy based on the prior fiscal year
hospital VBP payment adjustment (for FY 2020, this would be FY 2019
final adjustment factors) on each side of the comparison, consistent
with the methodology that we adopted in the FY 2013 IPPS/LTCH PPS final
rule (77 FR 53687 through 53688). That is, we are proposing to apply a
proxy readmissions payment adjustment factor and a proxy hospital VBP
payment adjustment factor from the prior final rule on both sides of
our comparison of aggregate payments when determining all budget
neutrality factors described in section II.A.4. of this Addendum.
For the purpose of calculating the proposed proxy FY 2020
readmissions payment adjustment factors, for both this proposed rule
and the final rule, as discussed in section IV.H. of the preamble of
this proposed rule, we are proposing to use the proportion of dually-
eligible Medicare beneficiaries, excess readmission ratios, and
aggregate payments for excess readmissions from the prior fiscal year's
applicable period because, at the time of the development of this
proposed rule and the final rule, hospitals will not yet have had the
opportunity to review and correct the data (program calculations based
on the proposed FY 2020 applicable period of July 1, 2015 to June 30,
2018) before the data are made public under our policy regarding the
reporting of hospital-specific readmission rates, consistent with
section 1886(q)(6) of the Act. (For additional information on our
general policy for the reporting of hospital-specific readmission
rates, consistent with section 1886(q)(6) of the Act, we refer readers
to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53399 through 53400) and
section IV.G. of the preamble of this proposed rule.)
In addition, for FY 2020, for the purpose of modeling aggregate
payments when determining all budget neutrality factors, we are
proposing to use proxy hospital VBP payment adjustment factors for FY
2020 that are based on data from the prior fiscal year's applicable
period because hospitals have not yet had an opportunity to review and
submit corrections for their data from the FY 2020 performance period.
(For additional information on our policy regarding the review and
correction of hospital-specific measure rates under the Hospital VBP
Program, consistent with section 1886(o)(10)(A)(ii) of the Act, we
refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53578
through 53581), the CY 2012 OPPS/ASC final rule with comment period (76
FR 74544 through 74547), and the Hospital Inpatient VBP final rule (76
FR 26534 through 26536).)
The Affordable Care Act also established section 1886(r)
of the Act, which modifies the methodology for computing the Medicare
DSH payment adjustment beginning in FY 2014. Beginning in FY 2014, IPPS
hospitals receiving Medicare DSH payment adjustments receive an
empirically justified Medicare DSH payment equal to 25 percent of the
amount that would previously have been received under the statutory
formula set forth under section 1886(d)(5)(F) of the Act governing the
Medicare DSH payment adjustment. In accordance with section 1886(r)(2)
of the Act, the remaining amount, equal to an estimate of 75 percent of
what otherwise would have been paid as Medicare DSH payments, reduced
to reflect changes in the percentage of individuals who are uninsured
and any additional statutory adjustment, will be available to make
additional payments to Medicare DSH hospitals based on their share of
the total amount of uncompensated care reported by Medicare DSH
hospitals for a given time period. In order to properly determine
aggregate payments on each side of the comparison for budget
neutrality, prior to FY 2014, we included estimated Medicare DSH
payments on both sides of our comparison of aggregate payments when
determining all budget neutrality factors described in section II.A.4.
of this Addendum.
To do this for FY 2020 (as we did for the last 6 fiscal years), we
are proposing to include estimated empirically justified Medicare DSH
payments that will be paid in accordance with section 1886(r)(1) of the
Act and estimates of the additional uncompensated care payments made to
hospitals receiving Medicare DSH payment adjustments as described by
section 1886(r)(2) of the Act. That is, we are proposing to consider
estimated empirically justified Medicare DSH payments at 25 percent of
what would otherwise have been paid, and also the estimated additional
uncompensated care payments for hospitals receiving Medicare DSH
payment adjustments on both sides of our comparison of aggregate
payments when determining all budget neutrality factors described in
section II.A.4. of this Addendum.
When calculating total payments for budget neutrality, to
determine total payments for SCHs, we model total hospital-specific
rate payments and total Federal rate payments and then include
whichever one of the total payments is greater. As discussed in section
IV.F. of the preamble of this proposed rule and below, we are proposing
to continue to use the FY 2014 finalized methodology under which we
take into consideration uncompensated care payments in the comparison
of payments under the Federal rate and the hospital-specific rate for
SCHs. Therefore, we are proposing to include estimated uncompensated
care payments in this comparison.
Similarly, for MDHs, as discussed in section IV.F. of the preamble
of this proposed rule, when computing payments under the Federal
national rate plus 75 percent of the difference between the payments
under the Federal national rate and the payments under the updated
hospital-specific rate, we are proposing to continue to take into
consideration uncompensated care payments in the computation of
payments under the Federal rate and the hospital-specific rate for
MDHs.
We are proposing to include an adjustment to the
standardized amount for those hospitals that are not meaningful EHR
users in our modeling of aggregate payments for budget neutrality for
FY 2020. Similar to FY 2019, we are including this adjustment based on
data on the prior year's performance. Payments for hospitals will be
estimated based on the proposed applicable standardized amount in
Tables 1A and 1B for discharges occurring in FY 2020.
In our determination of all proposed budget neutrality
factors described in section II.A.4. of this Addendum, we use transfer-
adjusted discharges. Specifically, we calculated the transfer-adjusted
discharges using the statutory expansion of the postacute care transfer
policy to include discharges to hospice care by a hospice program as
discussed in section IV.A.2.b. of the preamble of this proposed rule.
a. Proposed Recalibration of MS-DRG Relative Weights
Section 1886(d)(4)(C)(iii) of the Act specifies that, beginning in
FY 1991, the annual DRG reclassification and recalibration of the
relative weights must be made in a manner that ensures that aggregate
payments to hospitals are not affected. As discussed in section II.H.
of the preamble of this proposed rule, we normalized the recalibrated
MS-DRG relative weights by an adjustment factor so that the average
case relative weight after recalibration is equal to the average case
relative weight prior to recalibration. However, equating the average
case relative weight after recalibration to the average case relative
weight before recalibration does not necessarily achieve budget
neutrality with respect to aggregate
[[Page 19589]]
payments to hospitals because payments to hospitals are affected by
factors other than average case relative weight. Therefore, as we have
done in past years, we are proposing to make a budget neutrality
adjustment to ensure that the requirement of section 1886(d)(4)(C)(iii)
of the Act is met.
For FY 2020, to comply with the requirement that MS-DRG
reclassification and recalibration of the relative weights be budget
neutral for the standardized amount and the hospital-specific rates, we
used FY 2018 discharge data to simulate payments and compared the
following:
Aggregate payments using the FY 2019 labor-related share
percentages, the FY 2019 relative weights, and the FY 2019 pre-
reclassified wage data, and applied the proposed FY 2020 hospital
readmissions payment adjustments and estimated FY 2020 hospital VBP
payment adjustments; and
Aggregate payments using the FY 2019 labor-related share
percentages, the proposed FY 2020 relative weights, and the FY 2019
pre-reclassified wage data, and applied the proposed FY 2020 hospital
readmissions payment adjustments and estimated FY 2020 hospital VBP
payment adjustments applied above.
Based on this comparison, we computed a proposed budget neutrality
adjustment factor equal to 0.998768 and applied this factor to the
standardized amount. As discussed in section IV. of this Addendum, we
also are proposing to apply the MS-DRG reclassification and
recalibration budget neutrality factor of 0.998768 to the hospital-
specific rates that are effective for cost reporting periods beginning
on or after October 1, 2019.
b. Updated Wage Index--Budget Neutrality Adjustment
Section 1886(d)(3)(E)(i) of the Act requires us to update the
hospital wage index on an annual basis beginning October 1, 1993. This
provision also requires us to make any updates or adjustments to the
wage index in a manner that ensures that aggregate payments to
hospitals are not affected by the change in the wage index. Section
1886(d)(3)(E)(i) of the Act requires that we implement the wage index
adjustment in a budget neutral manner. However, section
1886(d)(3)(E)(ii) of the Act sets the labor-related share at 62 percent
for hospitals with a wage index less than or equal to 1.0000, and
section 1886(d)(3)(E)(i) of the Act provides that the Secretary shall
calculate the budget neutrality adjustment for the adjustments or
updates made under that provision as if section 1886(d)(3)(E)(ii) of
the Act had not been enacted. In other words, this section of the
statute requires that we implement the updates to the wage index in a
budget neutral manner, but that our budget neutrality adjustment should
not take into account the requirement that we set the labor-related
share for hospitals with wage indexes less than or equal to 1.0000 at
the more advantageous level of 62 percent. Therefore, for purposes of
this budget neutrality adjustment, section 1886(d)(3)(E)(i) of the Act
prohibits us from taking into account the fact that hospitals with a
wage index less than or equal to 1.0000 are paid using a labor-related
share of 62 percent. Consistent with current policy, for FY 2020, we
are proposing to adjust 100 percent of the wage index factor for
occupational mix. We describe the occupational mix adjustment in
section III.E. of the preamble of this proposed rule.
To compute a proposed budget neutrality adjustment factor for wage
index and labor-related share percentage changes, we used FY 2018
discharge data to simulate payments and compared the following:
Aggregate payments using the proposed FY 2020 relative
weights and the FY 2019 pre-reclassified wage indexes, applied the FY
2019 labor-related share of 68.3 percent to all hospitals (regardless
of whether the hospital's wage index was above or below 1.0000), and
applied the proposed FY 2020 hospital readmissions payment adjustment
and the estimated FY 2020 hospital VBP payment adjustment; and
Aggregate payments using the proposed FY 2020 relative
weights and the proposed FY 2020 pre-reclassified wage indexes, applied
the proposed labor-related share for FY 2020 of 68.3 percent to all
hospitals (regardless of whether the hospital's wage index was above or
below 1.0000), and applied the same proposed FY 2020 hospital
readmissions payment adjustments and estimated FY 2020 hospital VBP
payment adjustments applied above.
In addition, we applied the proposed MS-DRG reclassification and
recalibration budget neutrality adjustment factor (derived in the first
step) to the proposed payment rates that were used to simulate payments
for this comparison of aggregate payments from FY 2019 to FY 2020. By
applying this methodology, we determined a proposed budget neutrality
adjustment factor of 1.000915 for proposed changes to the wage index.
c. Reclassified Hospitals--Proposed Budget Neutrality Adjustment
Section 1886(d)(8)(B) of the Act provides that certain rural
hospitals are deemed urban. In addition, section 1886(d)(10) of the Act
provides for the reclassification of hospitals based on determinations
by the MGCRB. Under section 1886(d)(10) of the Act, a hospital may be
reclassified for purposes of the wage index.
Under section 1886(d)(8)(D) of the Act, the Secretary is required
to adjust the standardized amount to ensure that aggregate payments
under the IPPS after implementation of the provisions of sections
1886(d)(8)(B) and (C) and 1886(d)(10) of the Act are equal to the
aggregate prospective payments that would have been made absent these
provisions. We note that, with regard to the requirement under section
1886(d)(8)(C)(iii) of the Act, in our calculation of a proposed budget
neutrality adjustment factor, we applied the provisions of our proposal
discussed in section III.N. of the preamble of this proposed rule to
exclude the wage data of urban hospitals that have reclassified as
rural under section 1886(d)(8)(E) of the Act (as implemented in Sec.
412.103) from the calculation of ``the wage index for rural areas in
the State in which the county is located.'' We refer readers to the FY
2015 IPPS final rule (79 FR 50371 through 50372) for a complete
discussion regarding the requirement of section 1886(d)(8)(C)(iii) of
the Act. We further note that the wage index adjustments provided for
under section 1886(d)(13) of the Act are not budget neutral. Section
1886(d)(13)(H) of the Act provides that any increase in a wage index
under section 1886(d)(13) shall not be taken into account in applying
any budget neutrality adjustment with respect to such index under
section 1886(d)(8)(D) of the Act. To calculate the proposed budget
neutrality adjustment factor for FY 2020, we used FY 2018 discharge
data to simulate payments and compared the following:
Aggregate payments using the proposed FY 2020 labor-
related share percentages, the proposed FY 2020 relative weights, and
the proposed FY 2020 wage data prior to any reclassifications under
sections 1886(d)(8)(B) and (C) and 1886(d)(10) of the Act, and applied
the proposed FY 2020 hospital readmissions payment adjustments and the
estimated FY 2020 hospital VBP payment adjustments; and
Aggregate payments using the proposed FY 2020 labor-
related share percentages, the proposed FY 2020 relative weights, and
the proposed FY 2020 wage data after such
[[Page 19590]]
reclassifications, and applied the same proposed FY 2020 hospital
readmissions payment adjustments and the estimated FY 2020 hospital VBP
payment adjustments applied above.
We note that the reclassifications applied under the second
simulation and comparison are those listed in Table 2 associated with
this proposed rule, which is available via the internet on the CMS
website. This table reflects reclassification crosswalks proposed for
FY 2020, and apply the proposed policies explained in section III. of
the preamble of this proposed rule. Based on these simulations, we
calculated a proposed budget neutrality adjustment factor of 0.986451
to ensure that the effects of these provisions are budget neutral,
consistent with the statute.
The proposed FY 2020 budget neutrality adjustment factor was
applied to the proposed standardized amount after removing the effects
of the FY 2019 budget neutrality adjustment factor. We note that the
proposed FY 2020 budget neutrality adjustment reflects FY 2020 wage
index reclassifications approved by the MGCRB or the Administrator at
the time of development of this proposed rule.
d. Rural Floor Budget Neutrality Adjustment
Under Sec. 412.64(e)(4), we make an adjustment to the wage index
to ensure that aggregate payments after implementation of the rural
floor under section 4410 of the BBA (Pub. L. 105-33) is equal to the
aggregate prospective payments that would have been made in the absence
of this provision. Consistent with section 3141 of the Affordable Care
Act and as discussed in section III.G. of the preamble of this proposed
rule and codified at Sec. 412.64(e)(4)(ii), the budget neutrality
adjustment for the rural floor is a national adjustment to the wage
index. We note, as discussed in section III.N. of the preamble of this
proposed rule, we are proposing to calculate the rural floor without
including the wage data of urban hospitals that have reclassified as
rural under section 1886(d)(8)(E) of the Act (as implemented in Sec.
412.103).
Similar to our calculation in the FY 2015 IPPS/LTCH PPS final rule
(79 FR 50369 through 50370), for FY 2020, we are proposing to calculate
a national rural Puerto Rico wage index. Because there are no rural
Puerto Rico hospitals with established wage data, our calculation of
the proposed FY 2020 rural Puerto Rico wage index is based on the
policy adopted in the FY 2008 IPPS final rule with comment period (72
FR 47323). That is, we use the unweighted average of the wage indexes
from all CBSAs (urban areas) that are contiguous (share a border with)
to the rural counties to compute the rural floor (72 FR 47323; 76 FR
51594). Under the OMB labor market area delineations, except for
Arecibo, Puerto Rico (CBSA 11640), all other Puerto Rico urban areas
are contiguous to a rural area. Therefore, based on our existing
policy, the proposed FY 2020 rural Puerto Rico wage index is calculated
based on the average of the proposed FY 2020 wage indexes for the
following urban areas: Aguadilla-Isabela, PR (CBSA 10380); Guayama, PR
(CBSA 25020); Mayaguez, PR (CBSA 32420); Ponce, PR (CBSA 38660); San
German, PR (CBSA 41900); and San Juan-Carolina-Caguas, PR (CBSA 41980).
To calculate the proposed national rural floor budget neutrality
adjustment factor, we used FY 2018 discharge data to simulate payments
and the proposed post-reclassified national wage indexes and compared
the following:
National simulated payments without the proposed national
rural floor; and
National simulated payments with the proposed national
rural floor.
Based on this comparison, we determined a proposed national rural
floor budget neutrality adjustment factor of 0.996316. The national
adjustment was applied to the national wage indexes to produce a
proposed national rural floor budget neutral wage index.
e. Proposed Rural Community Hospital Demonstration Program Adjustment
In section IV.K. of the preamble of this proposed rule, we discuss
the Rural Community Hospital Demonstration program, which was
originally authorized for a 5-year period by section 410A of the
Medicare Prescription Drug, Improvement, and Modernization Act of 2003
(MMA) (Pub. L. 108-173), and extended for another 5-year period by
sections 3123 and 10313 of the Affordable Care Act (Pub. L. 111-148).
Subsequently, section 15003 of the 21st Century Cures Act (Pub. L. 114-
255), enacted December 13, 2016, amended section 410A of Public Law
108-173 to require a 10-year extension period (in place of the 5-year
extension required by the Affordable Care Act, as further discussed
below). We make an adjustment to the standardized amount to ensure the
effects of the Rural Community Hospital Demonstration program are
budget neutral as required under section 410A(c)(2) of Public Law 108-
173. We refer readers to section IV.K. of the preamble of this proposed
rule for complete details regarding the Rural Community Hospital
Demonstration.
With regard to budget neutrality, as mentioned earlier, we make an
adjustment to the standardized amount to ensure the effects of the
Rural Community Hospital Demonstration are budget neutral, as required
under section 410A(c)(2) of Public Law 108-173. For FY 2020, the total
amount that we are proposing to apply to make an adjustment to the
standardized amounts to ensure the effects of the Rural Community
Hospital Demonstration program are budget neutral is $47,038,507.
Accordingly, using the most recent data available to account for the
estimated costs of the demonstration program, for FY 2020, we computed
a proposed factor of 0.999580 for the Rural Community Hospital
Demonstration budget neutrality adjustment that will be applied to the
IPPS standard Federal payment rate. We refer readers to section IV.K.
of the preamble of this proposed rule for complete details regarding
the calculation of the amount we are applying to make an adjustment to
the standardized amount.
We note that, as discussed in section IV.K. of the preamble of this
proposed rule, if updated or additional data become available prior to
issuance of the FY 2020 IPPS/LTCH PPS final rule, we would use those
data to the extent appropriate to determine the budget neutrality
offset amount for FY 2020. We refer readers to section IV.K. of the
preamble of this proposed rule for complete details regarding the
availability of additional data prior to the FY 2020 IPPS/LTCH PPS
final rule.
f. Proposed Policy for Lowest and Highest Quartile Wage Index Hospitals
As discussed in section III.N. of the preamble of this proposed
rule, to address wage index disparities, we are proposing to increase
the wage index values for hospitals with a wage index value below the
25th percentile wage index value across all hospitals. In addition,
under our proposal, in order to offset the estimated increase in IPPS
payments to hospitals with wage index values below the 25th percentile,
we are proposing to decrease the wage index values for hospitals with a
wage index value above the 75th percentile wage index value across all
hospitals (high wage index hospitals). We note that this budget
neutrality adjustment is applied to the wage index and not to the
standardized amount. In addition, we are proposing that our proposed
policy to increase the wage index for hospitals with wage indexes below
the 25th percentile would be budget neutral using our authority under
both section 1886(d)(3)(E) of the Act, which gives the
[[Page 19591]]
Secretary broad authority to adjust for area differences in hospital
wage levels by a factor (established by the Secretary) reflecting the
relative hospital wage level in the geographic area of the hospital
compared to the national average hospital wage level, and requires
those adjustments to be budget neutral, and our exceptions and
adjustments authority under section 1886(d)(5)(I) of the Act. We refer
readers to section III.N. of the preamble of this proposed rule for a
complete discussion regarding this proposal.
g. Proposed Transition Budget Neutrality Adjustment Reflecting the
Proposed FY 2020 Wage Index Changes
In section III.N. of the preamble of this proposed rule, we state
that we recognize that, absent further adjustments, the combined effect
of the proposed changes to the FY 2020 wage index could lead to
significant decreases in the wage index values for some hospitals
depending on the data for the final rule. Therefore, for FY 2020, we
are proposing a transition wage index to help mitigate any significant
decreases in the wage index values of hospitals compared to their final
wage indexes for FY 2019. Specifically, we are proposing to place a 5-
percent cap on any decrease in a hospital's wage index from the
hospital's final wage index in FY 2019. In other words, we are
proposing that a hospital's final wage index for FY 2020 would not be
less than 95 percent of its final wage index for FY 2019. For FY 2020,
we are proposing to use our exceptions and adjustments authority under
section 1886(d)(5)(I)(i) of the Act to apply a budget neutrality
adjustment to the standardized amount so that our proposed transition
for hospitals negatively impacted (described in section III.N.3.d. of
the preamble of this proposed rule) is implemented in a budget neutral
manner. We refer readers to section III.N. of the preamble of this
proposed rule for a complete discussion regarding this proposal.
To calculate a proposed transition budget neutrality adjustment
factor for FY 2020, we used FY 2018 discharge data to simulate payments
and compared the following:
Aggregate payments using the proposed FY 2020 labor-
related share percentages, the proposed FY 2020 relative weights, and
the proposed FY 2020 wage index for each hospital after adjusting the
wage indexes under the proposed policy for lowest and highest quartile
wage index hospitals but without the proposed 5-percent cap, and
applied the proposed FY 2020 hospital readmissions payment adjustments
and the estimated FY 2020 hospital VBP payment adjustments, and the
proposed operating outlier reconciliation adjusted outlier percentage;
and
Aggregate payments using the proposed FY 2020 labor-
related share percentages, the proposed FY 2020 relative weights, and
the proposed FY 2020 wage index for each hospital after adjusting the
wage indexes under the proposed policy for lowest and highest quartile
wage index hospitals and with the proposed 5-percent cap, and applied
the same proposed FY 2020 hospital readmissions payment adjustments and
the estimated FY 2020 hospital VBP payment adjustments applied above,
and the proposed operating outlier reconciliation adjusted outlier
percentage.
This proposed FY 2020 budget neutrality adjustment factor was
applied to the proposed standardized amount. Based on this comparison,
we determined a proposed transition budget neutrality adjustment factor
of 0.998349. We note that Table 2 associated with this proposed rule
(which is available via the internet on the CMS website) contains the
proposed wage index by provider before adjusting the wage indexes under
the proposed policy for lowest and highest quartile wage index
hospitals and the proposed 5-percent cap and the proposed wage index by
provider after the application of these proposals.
h. Proposed Adjustment for FY 2020 Required Under Section 414 of Public
Law 114-10 (MACRA)
As stated in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56785),
once the recoupment required under section 631 of the ATRA was
complete, we had anticipated making a single positive adjustment in FY
2018 to offset the reductions required to recoup the $11 billion under
section 631 of the ATRA. However, section 414 of the MACRA (which was
enacted on April 16, 2015) replaced the single positive adjustment we
intended to make in FY 2018 with a 0.5 percent positive adjustment for
each of FYs 2018 through 2023. (As noted in the FY 2018 IPPS/LTCH PPS
proposed and final rules, section 15005 of the 21st Century Cures Act
(Pub. L. 114-255), which was enacted December 13, 2016, reduced the
adjustment for FY 2018 from 0.5 percentage points to 0.4588 percentage
points.) Therefore, for FY 2020, we are proposing to implement the
required +0.5 percent adjustment to the standardized amount. This is a
permanent adjustment to the payment rates.
i. Proposed Outlier Payments
Section 1886(d)(5)(A) of the Act provides for payments in addition
to the basic prospective payments for ``outlier'' cases involving
extraordinarily high costs. To qualify for outlier payments, a case
must have costs greater than the sum of the prospective payment rate
for the MS-DRG, any IME and DSH payments, uncompensated care payments,
any new technology add-on payments, and the ``outlier threshold'' or
``fixed-loss'' amount (a dollar amount by which the costs of a case
must exceed payments in order to qualify for an outlier payment). We
refer to the sum of the prospective payment rate for the MS-DRG, any
IME and DSH payments, uncompensated care payments, any new technology
add-on payments, and the outlier threshold as the outlier ``fixed-loss
cost threshold.'' To determine whether the costs of a case exceed the
fixed-loss cost threshold, a hospital's CCR is applied to the total
covered charges for the case to convert the charges to estimated costs.
Payments for eligible cases are then made based on a marginal cost
factor, which is a percentage of the estimated costs above the fixed-
loss cost threshold. The marginal cost factor for FY 2020 is 80
percent, or 90 percent for burn MS-DRGs 927, 928, 929, 933, 934 and
935. We have used a marginal cost factor of 90 percent since FY 1989
(54 FR 36479 through 36480) for designated burn DRGs as well as a
marginal cost factor of 80 percent for all other DRGs since FY 1995 (59
FR 45367).
In accordance with section 1886(d)(5)(A)(iv) of the Act, outlier
payments for any year are projected to be not less than 5 percent nor
more than 6 percent of total operating DRG payments (which does not
include IME and DSH payments) plus outlier payments. Similar to prior
years, when setting the outlier threshold, we compute the percent
target by dividing the total operating outlier payments by the total
operating DRG payments plus outlier payments. As discussed in the next
section, for FY 2020 we are proposing to incorporate an estimate of
outlier reconciliation when setting the outlier threshold. We do not
include any other payments such as IME and DSH within the outlier
target amount. Therefore, it is not necessary to include Medicare
Advantage IME payments in the outlier threshold calculation. Section
1886(d)(3)(B) of the Act requires the Secretary to reduce the average
standardized amount by a factor to account for the estimated proportion
of total DRG payments made to outlier cases. More information on
outlier
[[Page 19592]]
payments may be found on the CMS website at: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/outlier.htm.
(1) Proposed Methodology To Incorporate an Estimate of Outlier
Reconciliation in the FY 2020 Outlier Fixed-Loss Cost Threshold
The regulations in 42 CFR 412.84(i)(4) state that any outlier
reconciliation at cost report settlement will be based on operating and
capital cost-to-charge ratios (CCRs) calculated based on a ratio of
costs to charges computed from the relevant cost report and charge data
determined at the time the cost report coinciding with the discharge is
settled. We have instructed MACs to identify for CMS any instances
where: (1) A hospital's actual CCR for the cost reporting period
fluctuates plus or minus 10 percentage points compared to the interim
CCR used to calculate outlier payments when a bill is processed; and
(2) the total outlier payments for the hospital exceeded $500,000.00
for that cost reporting period. If we determine that a hospital's
outlier payments should be reconciled, we reconcile both operating and
capital outlier payments. We refer readers to section 20.1.2.5 of
Chapter 3 of the Medicare Claims Processing Manual (available on the
CMS website at: https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c03.pdf) for complete details regarding outlier
reconciliation. The regulation at Sec. 412.84(m) further states that
at the time of any outlier reconciliation under Sec. 412.84(i)(4),
outlier payments may be adjusted to account for the time value of any
underpayments or overpayments. Section 20.1.2.6 of Chapter 3 of the
Medicare Claims Processing Manual contains instructions on how to
assess the time value of money for reconciled outlier amounts.
If the operating CCR of a hospital subject to outlier
reconciliation is lower at cost report settlement compared to the
operating CCR used for payment, the hospital will owe CMS money because
it received an outlier overpayment at the time of claim payment.
Conversely, if the operating CCR increases at cost report settlement
compared to the operating CCR used for payment, CMS will owe the
hospital money because the hospital outlier payments were underpaid. In
prior fiscal years, commenters have requested that CMS incorporate
outlier reconciliation in the development of the outlier threshold.
As we have stated in prior rulemaking, outlier reconciliation is a
function of the cost report, and MACs record the outlier reconciliation
amount on each provider's cost report. Therefore, as the MACs continue
to perform these outlier reconciliations, they record these amounts on
the cost report, which are then publicly available through the HCRIS
database. Therefore, the outlier reconciliation data used in the
following proposed process would be publicly available through the cost
report.
In the FY 2004 IPPS final rule (68 FR 45476 through 45477), we
included an estimate for outlier reconciliation that identified and
adjusted the CCRs of hospitals in our calculation of the outlier fixed
loss threshold. However, outlier cases are difficult to predict with
regard to their occurrence for any individual hospital. Generally, an
outlier payment is made if the estimated costs of the case exceed the
sum of the outlier threshold plus the relevant payment amounts. There
are many different variables that determine whether a case will be
eligible for an outlier payment, including the CCR, the estimated costs
of the case, the payment amounts, and the outlier threshold itself. We
refer readers to section II.C.1. of this Addendum for additional detail
regarding how the outlier payment is computed. In addition, predicting
both the specific hospitals that will have outlier payments reconciled
and the dollar amount of any such outlier reconciliation is difficult,
which makes incorporating reconciliation into the modeling of the
outlier threshold challenging.
In the FY 2019 IPPS/LTCH PPS final rule and other prior rulemaking,
we have stated that we continue to believe that, due to the policy
implemented in the June 9, 2003 Outlier Final Rule (68 FR 34494), CCRs
will no longer fluctuate as significantly and, therefore, few hospitals
will actually have their outlier payments reconciled upon cost report
settlement. In addition, we stated that it is difficult to predict the
specific hospitals that will have fluctuating CCRs and outlier payments
reconciled in any given year. In the FY 2019 IPPS/LTCH PPS final rule,
in response to comments expressing concern with CMS' decision not to
consider outlier reconciliation in developing the outlier threshold, we
stated that we intended to revisit this issue in next year's proposed
rule (that is, this FY 2020 proposed rule) as we continue to consider
the feasibility of including outlier reconciliation in the modeling of
the outlier threshold.
Since the issuance of the FY 2019 IPPS/LTCH PPS final rule, we have
continued to consider how outlier reconciliation could be included in
the modeling of the outlier threshold. Rather than trying to predict
which claims and/or hospitals may be subject to outlier reconciliation
for FY 2020, we believe a methodology that incorporates an estimate of
outlier reconciliation dollars based on actual outlier reconciliation
amounts reported in historical cost reports would be a more feasible
approach and provide a better estimate and predictor of outlier
reconciliation for the upcoming fiscal year. We believe this proposed
methodology would address concerns on the impact of outlier
reconciliation on the modeling of the outlier threshold.
We also believe the cost report data available in the HCRIS may be
sufficiently complete for certain historical fiscal years to allow for
calculating an estimate of outlier reconciliation for FY 2020. We
issued Change Request 7192 on December 3, 2010 (available via the
internet on the CMS website at: https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/downloads/R2111CP.pdf) which updated a
utility to reprice outlier claims for purposes of outlier
reconciliation. Prior to this update, cost reports subject to outlier
reconciliation were being held open until there was a mechanism to
perform the outlier reconciliation. The outlier reconciliation amounts
on the cost report are reflected in HCRIS once the cost report is final
settled. As MACs began performing the outlier reconciliations, they
were able to final settle many of these cost reports and the data for
outlier reconciliation began to become available in HCRIS. However,
even with a utility available beginning in 2010, not all cost reports
were final settled for reasons other than outlier reconciliation.
Therefore, HCRIS may not have reflected all of the hospitals subject to
outlier reconciliation. We believe that many of these other reasons for
the delay in cost reports being final settled have now been resolved.
In contrast to prior years, HCRIS now contains more final settled cost
reports that include outlier reconciliation, in particular for FY 2014,
as we discuss below, which can be used to develop an annual estimate of
total dollars related to outlier reconciliation payments based on this
historical cost report data. Therefore, for FY 2020, we are proposing
to incorporate into the outlier model the total outlier reconciliation
dollars based on historical data. We are providing below a step-by-step
explanation of how we are proposing to incorporate these dollars into
the model.
Currently, outlier reconciliation is among the last steps before
the cost
[[Page 19593]]
report is final settled. In order to determine if a hospital meets the
outlier reconciliation criteria, all cost report adjustments must be
finalized in order to compare the final settled operating CCR from the
cost report to the operating CCR used for the original claim payment.
Generally, MACs attempt to have a cost report final settled 12 months
after the cost report is submitted by the provider to CMS. However,
there are sometimes issues or adjustments that are unique to the cost
report that extend the final settlement beyond 12 months. This will
delay the MAC from recording the outlier reconciliation amounts on the
cost report, which will also delay the availability of these amounts in
HCRIS. Because of these potential delays, we are proposing to use the
historical outlier reconciliation amounts from the FY 2014 cost reports
(cost reports with a begin date on or after October 1, 2013, and on or
before September 30, 2014), which are currently the most recent and
complete set of outlier reconciliation data, which are finalized and/or
approved by the MAC as of the time of development of this FY 2020
proposed rule. We note that approximately 90 percent of the FY 2014
cost reports are final settled, as compared to approximately 60 percent
of the FY 2015 cost reports that are final settled. As of the December
2018 HCRIS, 16 of the FY 2014 cost reports and 8 of the FY 2015 cost
reports had completed outlier reconciliation amounts. Therefore, we
believe that the FY 2014 cost reports provide the most recent and
complete available data to estimate the effect of outlier
reconciliation dollars on the outlier cost threshold. We considered
using FY 2015 cost report data. However, because, as previously noted,
the FY 2015 and later years cost reports have a larger percent of not
final settled cost reports, outlier reconciliation dollars for these
years may not be sufficiently available in the HCRIS. Therefore, we
currently believe that it may not be appropriate to use those more
recent cost reports to estimate outlier reconciliation for the FY 2020
proposed and final rules. In order to prospectively determine the
outlier threshold, we are proposing to use the FY 2014 cost reports
from the most recent publically available HCRIS extract at the time of
development of the proposed and final rules. For this FY 2020 proposed
rule, we used the December 2018 HCRIS extract to calculate the proposed
percentage adjustment for outlier reconciliation. For the FY 2020 final
rule, we are proposing to use the latest quarterly HCRIS extract that
is publically available at the time of the development of that rule
which, for FY 2020, would be the March 2019 extract. We believe
hospitals that have a FY 2014 cost report approved for outlier
reconciliation will have had their cost reports final settled by the
issuance of this proposed rule and, therefore, would have outlier
reconciliation estimates available for use in the FY 2020 final rule.
We are proposing the following methodology to incorporate a
projection of outlier payment reconciliations for the FY 2020 outlier
threshold calculation.
Step 1.--Use the Federal FY 2014 cost reports for hospitals paid
under the IPPS from the most recent publicly available quarterly HCRIS
extract available at the time of development of the proposed and final
rules, and exclude sole community hospitals (SCHs) that were paid under
their hospital-specific rate (that is, if Worksheet E, Part A, Line 48
is greater than Line 47). We used the December 2018 HCRIS extract for
this proposed rule and expect to use the March 2019 HCRIS extract for
the FY 2020 final rule.
Step 2.--Calculate the aggregate amount of historical total of
operating outlier reconciliation dollars (Worksheet E, Part A, Line
2.01) using the Federal FY 2014 cost reports from Step 1.
Step 3.--Calculate the aggregate amount of total Federal operating
payments using the Federal FY 2014 cost reports from Step 1. The total
Federal operating payments consist of the Federal payments (Worksheet
E, Part A, Line 1.01 and Line 1.02, plus Line 1.03 and Line 1.04),
outlier payments (Worksheet E, Part A, Line 2 and Line 2.02), and the
outlier reconciliation payments (Worksheet E, Part A, Line 2.01). We
note that a negative amount on Worksheet E, Part A, Line 2.01 for
outlier reconciliation indicates an amount that was owed by the
hospital, and a positive amount indicates this amount was paid to the
hospital.
Step 4.--Divide the amount from Step 2 by the amount from Step 3
and multiply the resulting amount by 100 to produce the percentage of
total operating outlier reconciliation dollars to total Federal
operating payments for FY 2014. This percentage amount would be used to
adjust the outlier target for FY 2020 as described in Step 5.
Step 5.--Because the outlier reconciliation dollars are only
available on the cost reports, and not in the Medicare claims data in
the MedPAR file used to model the outlier threshold, we are proposing
to target 5.1 percent minus the percentage determined in Step 4 in
determining the outlier threshold. Using the FY 2014 cost reports based
on the December 2018 HCRIS extract, because the aggregate outlier
reconciliation dollars from Step 2 are negative, we are targeting an
amount higher than 5.1 percent for outlier payments for FY 2020 under
our proposed methodology.
For this FY 2020 proposed rule, based on the December 2018 HCRIS,
16 hospitals had an outlier reconciliation amount recorded on Worksheet
E, Part A, Line 2.01 for total operating outlier reconciliation dollars
of negative $24,433,087 (Step 2). The total Federal operating payments
based on the December 2018 HCRIS was $82,969,541,296 (Step 3). The
ratio (Step 4) is a negative 0.029448 percent, which, when rounded to
the second digit, is negative 0.03 percent. Therefore, for FY 2020, we
are proposing to incorporate a projection of outlier reconciliation
dollars by targeting an outlier threshold at 5.13 percent [5.1 percent-
(-.03 percent)]. When the percentage of operating outlier
reconciliation dollars to total Federal operating payments is negative
(such is the case when the aggregate amount of outlier reconciliation
is negative), the effect is a decrease to the outlier threshold
compared to an outlier threshold that is calculated without including
this estimate of operating outlier reconciliation dollars. In section
II.A.4.i.(2) of this Addendum, we provide the FY 2020 outlier threshold
as calculated for this proposed rule both with and without including
this proposed percentage estimate of operating outlier reconciliation.
As explained earlier, we believe this is an appropriate method to
include outlier reconciliation dollars in the outlier model because it
uses the total outlier reconciliation dollars based on historic data
rather than predicting which specific hospitals will have outlier
payments reconciled for FY 2020. However, we would continue to use a
5.1 percent target (or an outlier offset factor of 0.949) in
calculating the outlier offset to the standardized amount. In the past,
the outlier offset was six decimals because we targeted and set the
threshold at 5.1 percent by adjusting the standardized amount by the
outlier offset until operating outlier payments divided by total
operating Federal payments plus operating outlier payments equaled
approximately 5.1 percent (this approximation resulted in an offset
beyond three decimals). However, under our proposed methodology, we
believe a three decimal offset of 0.949 reflecting 5.1 percent is
appropriate rather than the
[[Page 19594]]
unrounded six decimal offset that we have calculated for prior fiscal
years. Specifically, as discussed in section II.A.5. of this Addendum,
we are proposing to determine an outlier adjustment by applying a
factor to the standardized amount that accounts for the projected
proportion of total estimated FY 2020 operating Federal payments paid
as outliers. Our proposed modification to the outlier threshold
methodology is designed to adjust the total estimated outlier payments
for FY 2020 by incorporating the projection of negative outlier
reconciliation. That is, under this proposal, total estimated outlier
payments for FY 2020 would be the sum of the estimated FY 2020 outlier
payments based on the claims data from the outlier model and the
estimated FY 2020 total operating outlier reconciliation dollars. We
believe the proposed methodology would more accurately estimate the
outlier adjustment to the standardized amount by increasing the
accuracy of the calculation of the total estimated FY 2020 operating
Federal payments paid as outliers. In other words, the net effect of
our outlier proposal to incorporate a projection for outlier
reconciliation dollars into the threshold methodology would be that FY
2020 outlier payments (which include the estimated recoupment
percentage for FY 2020 of 0.03 percent) would be 5.1 percent of total
operating Federal payments plus total outlier payments. Therefore, the
operating outlier offset to the standardized amount is 0.949 (1-0.051).
Although we are not making any proposals with respect to the
methodology for FY 2021 and subsequent fiscal years, the above-
described proposed methodology could advance by one year the cost
reports used to determine the historical outlier reconciliation (for
example, for FY 2021, the FY 2015 outlier reconciliations would be
expected to be complete). We are considering additional options in
order to have available more recent estimates of outlier reconciliation
for future rulemaking.
We establish an outlier threshold that is applicable to both
hospital inpatient operating costs and hospital inpatient capital
related costs (58 FR 46348). Similar to the calculation of the proposed
adjustment to the standardized amount to account for the projected
proportion of operating payments paid as outlier payments, as discussed
in greater detail in section III.A.2. of this Addendum, we are
proposing to reduce the FY 2020 capital standard Federal rate by an
adjustment factor to account for the projected proportion of capital
IPPS payments paid as outliers. The regulations in 42 CFR 412.84(i)(4)
state that any outlier reconciliation at cost report settlement will be
based on operating and capital CCRs calculated based on a ratio of
costs to charges computed from the relevant cost report and charge data
determined at the time the cost report coinciding with the discharge is
settled. As such, any reconciliation also applies to capital outlier
payments. As part of our proposal for FY 2020 to incorporate into the
outlier model the total outlier reconciliation dollars from the most
recent and most complete fiscal year cost report data, we also are
proposing to adjust our estimate of FY 2020 capital outlier payments to
incorporate a projection of capital outlier reconciliation payments
when determining the adjustment factor to be applied to the capital
standard Federal rate to account for the projected proportion of
capital IPPS payments paid as outliers. To do so, we are proposing to
use the following methodology, which generally parallels the proposed
methodology to incorporate a projection of operating outlier
reconciliation payments for the FY 2020 outlier threshold calculation.
Step 1.--Use the Federal FY 2014 cost reports for hospitals paid
under the IPPS from the most recent publicly available quarterly HCRIS
extract available at the time of development of the proposed and final
rules, and exclude SCHs that were paid under their hospital-specific
rate (that is, if Worksheet E, Part A, Line 48 is greater than Line
47). We used the December 2018 HCRIS extract for this proposed rule and
expect to use the March 2019 HCRIS extract for the FY 2020 final rule.
Step 2.--Calculate the aggregate amount of the historical total of
capital outlier reconciliation dollars (Worksheet E, Part A, Line 93,
Column 1) using the Federal FY 2014 cost reports from Step 1.
Step 3.--Calculate the aggregate amount of total capital Federal
payments using the Federal FY 2014 cost reports from Step 1. The total
capital Federal payments consist of the capital DRG payments, including
capital indirect medical education (IME) and capital disproportionate
share hospital (DSH) payments (Worksheet E, Part A, Line 50, Column 1)
and the capital outlier reconciliation payments (Worksheet E, Part A,
Line 93, Column 1). We note that a negative amount on Worksheet E, Part
A, Line 93 for capital outlier reconciliation indicates an amount that
was owed by the hospital, and a positive amount indicates this amount
was paid to the hospital.
Step 4.--Divide the amount from Step 2 by the amount from Step 3
and multiply the resulting amount by 100 to produce the percentage of
total capital outlier reconciliation dollars to total capital Federal
payments for FY 2014. This percentage amount would be used to adjust
the estimate of capital outlier payments for FY 2020 as described in
Step 5.
Step 5.--Because the outlier reconciliation dollars are only
available on the cost reports, and not in the specific Medicare claims
data in the MedPAR file used to estimate outlier payments, we are
proposing that the estimate of capital outlier payments for FY 2020
would be determined by adding the percentage in Step 4 to the estimated
percentage of capital outlier payments otherwise determined using the
shared outlier threshold that is applicable to both hospital inpatient
operating costs and hospital inpatient capital-related costs. (We note
that this percentage is added for capital outlier payments but
subtracted in the analogous step for operating outlier payments. We
have a unified outlier payment methodology that uses a shared threshold
to identify outlier cases for both operating and capital payments. The
difference stems from the fact that operating outlier payments are
determined by first setting a ``target'' percentage of operating
outlier payments relative to aggregate operating payments which
produces the outlier threshold. Once the shared threshold is set, it is
used to estimate the percentage of capital outlier payments to total
capital payments based on that threshold. Because the threshold is
already set based on the operating target, rather than adjusting the
threshold (or operating target), we adjust the percentage of capital
outlier to total capital payments to account for the estimated effect
of capital outlier reconciliation payments. This percentage is adjusted
by adding the capital outlier reconciliation percentage from Step 4 to
the estimate of the percentage of capital outlier payments to total
capital payments based on the shared threshold.) Because the aggregate
capital outlier reconciliation dollars from Step 2 are negative, the
estimate of capital outlier payments for FY 2020 under our proposed
methodology would be lower than the percentage of capital outlier
payments otherwise determined using the shared outlier threshold.
For this FY 2020 proposed rule, the estimated percentage of FY 2020
capital outlier payments otherwise determined using the shared outlier
threshold is 5.39 percent (estimated capital outlier payments of
$433,416,367 divided by
[[Page 19595]]
(estimated capital outlier payments of $433,416,367 plus the estimated
total capital Federal payment of $7,603,919,535)). Based on the
December 2018 HCRIS, 16 hospitals had an outlier reconciliation amount
recorded on Worksheet E, Part A, Line 93 for total capital outlier
reconciliation dollars of negative $3,860,075 (Step 2). The total
Federal capital payments based on the December 2018 HCRIS was
$7,506,907,042 (Step 3) which results in a ratio (Step 4) of -0.05
percent. Therefore, for FY 2020, taking into account projected capital
outlier reconciliation payments under our proposed methodology would
decrease the estimated percentage of FY 2020 aggregate capital outlier
payments by 0.05 percent.
As explained in our discussion of the outlier threshold methodology
above, we believe this is an appropriate method to include capital
outlier reconciliation dollars in the estimated percentage of capital
outlier payments because it uses the total outlier reconciliation
dollars based on historic data rather than predicting which specific
hospitals will have outlier payments reconciled for FY 2020. As
discussed in section III.A.2. of this Addendum, we are proposing to
incorporate the capital outlier reconciliation dollars from Step 5 when
applying the outlier adjustment factor in determining the capital
Federal rate based on the estimated percentage of capital outlier
payments to total capital Federal rate payments for FY 2020.
We are inviting public comment on our proposed methodology for
projecting the estimate of outlier reconciliation and incorporating
that estimate into the modeling for the fixed-loss cost outlier
threshold and our proposed methodology for projecting the estimate of
capital outlier reconciliation and incorporating that estimate into the
modeling of the estimate of FY 2020 capital outlier payments for
purposes of determining the capital outlier adjustment factor.
(2) Proposed FY 2020 Outlier Fixed-Loss Cost Threshold
In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50977 through
50983), in response to public comments on the FY 2013 IPPS/LTCH PPS
proposed rule, we made changes to our methodology for projecting the
outlier fixed-loss cost threshold for FY 2014. We refer readers to the
FY 2014 IPPS/LTCH PPS final rule for a detailed discussion of the
changes.
As we have done in the past, to calculate the proposed FY 2020
outlier threshold, we simulated payments by applying proposed FY 2020
payment rates and policies using cases from the FY 2018 MedPAR file. As
noted in section II.C. of this Addendum, we specify the formula used
for actual claim payment which is also used by CMS to project the
outlier threshold for the upcoming fiscal year. The difference is the
source of some of the variables in the formula. For example, operating
and capital CCRs for actual claim payment are from the PSF while CMS
uses an adjusted CCR (as described below) to project the threshold for
the upcoming fiscal year. In addition, charges for a claim payment are
from the bill while charges to project the threshold are from the
MedPAR data with an inflation factor applied to the charges (as
described earlier).
In order to determine the proposed FY 2020 outlier threshold, we
inflated the charges on the MedPAR claims by 2 years, from FY 2018 to
FY 2020. To produce the most stable measure of charge inflation, we
applied the following inclusion and exclusion criteria of hospitals
claims in our measure of charge inflation:
Include hospitals whose last four digits fall between 0001
and 0899 (section 2779A1 of Chapter 2 of the State Operations Manual on
the CMS website at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/som107c02.pdf); include CAHs that were IPPS
hospitals for the time period of the MedPAR data being used to
calculate the charge inflation factor; include hospitals in Maryland;
and remove PPS-excluded cancer hospitals who have a ``V'' in the fifth
position of their provider number or a ``E'' or ``F'' in the sixth
position.
Include providers that are in both periods of charge data
that are used to calculate the 1-year average annual rate-of-change in
charges per case. We note this is consistent with the methodology used
since FY 2014 and are providing this as a technical clarification.
We excluded Medicare Advantage IME claims for the reasons
described in section I.A.4. of this Addendum. We refer readers to the
FY 2011 IPPS/LTCH PPS final rule for a complete discussion on our
methodology of identifying and adding the total Medicare Advantage IME
payment amount to the budget neutrality adjustments.
In order to ensure that we capture only FFS claims, we
included claims with a ``Claim Type'' of 60 (which is a field on the
MedPAR file that indicates a claim is an FFS claim).
In order to further ensure that we capture only FFS
claims, we excluded claims with a ``GHOPAID'' indicator of 1 (which is
a field on the MedPAR file that indicates a claim is not an FFS claim
and is paid by a Group Health Organization).
We examined the MedPAR file and removed pharmacy charges
for anti-hemophilic blood factor (which are paid separately under the
IPPS) with an indicator of ``3'' for blood clotting with a revenue code
of ``0636'' from the covered charge field. We also removed organ
acquisition charges from the covered charge field because organ
acquisition is a pass-through payment not paid under the IPPS.
Our general methodology to inflate the charges computes the 1-year
average annual rate-of-change in charges per case which is then applied
twice to inflate the charges on the MedPAR claims by 2 years (for
example, FY 2018 to FY 2020). Specifically, under the methodology we
have used since FY 2014, we compare the average charge per case from
the latest 12 month period of MedPAR claims data available at the time
of the proposed rule and the final rule to the average charge per case
for the 12 month period from the prior year. For example, for the FY
2019 IPPS/LTCH PPS proposed rule (83 FR 20581), we used the December
2017 update of MedPAR claims data to calculate the average charges per
case for the periods of January through December for CYs 2016 and 2017.
Because the publicly released MedPAR claims do not contain claims
beyond the end of the Federal fiscal year, the data for the last
quarter of CY 2017 were not included in the publicly available December
2017 release. As we have in prior rulemaking, we included in the FY
2019 proposed rule a table grouping the claims data used in the
calculation by quarter, and also made available on the CMS website more
detailed summary tables by provider with the monthly charges that were
used to compute the charge inflation factor.
As summarized in the FY 2019 IPPS/LTCH PPS final rule (83 FR
41718), we have continued to receive comments expressing concern with
what commenters stated was a lack of transparency with respect to the
charge inflation component of the fixed-loss threshold calculation. The
commenters concluded that, in the absence of access to the data or more
specific data and information about how CMS arrived at the totals used
in the charge inflation calculation, their ability to comment or to
review the calculation of the charge inflation factor was limited.
Another commenter stated that CMS has not made the necessary data
available or any guidance that describes whether and how CMS edited
such data to arrive at the total of quarterly charges
[[Page 19596]]
and charges per case used to measure charge inflation. Consequently,
the commenter stated that the table of quarterly charges provided in
the proposed rule was not useful in assessing the accuracy of the
charge inflation figure that CMS used in the proposed rule to calculate
the outlier threshold.
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41718), we noted
that we responded to similar comments in the FY 2015 IPPS/LTCH PPS
final rule (79 FR 50375), the FY 2016 IPPS/LTCH PPS final rule (80 FR
49779 through 49780), the FY 2017 IPPS/LTCH PPS final rule (81 FR
57283), and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38524). We also
explained that we have not yet been able to restructure the files (such
as ensuring that personal identification information is compliant with
privacy regulations) for release with the publication of the proposed
rule and the final rule, and we continue to be confronted with the
dilemma of either using older data that commenters can access earlier
or using the most up-to-date data which will be more accurate, but will
not be available to the public until after publication of the proposed
and final rules. We stated that we continue to prefer using the latest
data available at the time of the development of the proposed and final
rules to compute the charge inflation factor because we believe it
leads to greater accuracy in the calculation of the fixed-loss cost
outlier threshold. We also noted that commenters did not recommend
using charge data from a different period to compute the charge
inflation factor. However, we stated that, for this FY 2020 IPPS/LTCH
PPS proposed rule, we are continuing to consider using data that
commenters can access earlier.
For this FY 2020 IPPS/LTCH PPS proposed rule, after further
consideration, we believe balancing our preference to use the latest
available data from the MedPAR files and stakeholders' concerns about
being able to use publicly available MedPAR files to review the charge
inflation factor can be achieved by modifying our methodology to use
the publicly available Federal fiscal year period (that is, for FY
2020, we would use the charge data from Federal fiscal years 2017 and
2018), rather than the most recent data available to CMS. That is, for
FY 2020, we are proposing to use the charge data from Federal fiscal
years 2017 and 2018 to calculate the 1-year average annual rate-of-
change in charges per case for purposes of calculating both the
proposed and final charge inflation factors, rather than the charge
data from CYs 2017 and 2018 for purposes of calculating the proposed
charge inflation factor and charge data from the periods April 1, 2017
through March 31, 2018 and April 1, 2018 through March 31, 2019 for
purposes of calculating the final charge inflation factor as we would
under our prior methodology. We believe there are benefits to using
comparable Federal fiscal year periods rather than the most recent
available data to calculate charge inflation, such as seasonality
effects and the completeness of claims (that is, run-out).
Specifically, under the methodology used for FYs 2014 through 2019,
there is no run-out time between some of the claims and the MedPAR
release. For example, under our current methodology, the most recent
data available for purposes of this proposed rule would be the December
2018 MedPAR release, with the final month of charge data being December
2018, and for the FY 2020 IPPS/LTCH PPS final rule, the most recent
data available would be the March 2019 MedPAR release, with the final
month of charge data being March 2019. With no run-out time between the
end of the claims data period and the MedPAR release, some claims are
not included from the last month of the applicable MedPAR release due
to factors such as when the claim is submitted and claims processing
time. In comparison, there is a 3-month run-out between the end of
Federal fiscal year 2018 (September 30, 2018) and the December 2018
MedPAR release (cut-off as of December 31, 2018) for the proposed rule
and a 6-month run-out between the end of Federal fiscal year 2018
(September 30, 2018) and the March 2019 MedPAR release (cut off as of
March 31, 2019) for the final rule, which allows for more completeness
in those FY 2018 claims. In addition to the completeness of the data,
we believe this would also address commenters' concerns regarding
transparency with respect to the data used to calculate the charge
inflation factor. Adopting a methodology that uses charge data based on
Federal fiscal years would allow for the MedPAR data to be readily
available after publication of the proposed and final rules.
After further consideration of the issue and for the reasons
discussed above, we are proposing to use the publicly available MedPAR
files for the 2 most recent Federal fiscal year time periods to
calculate the charge inflation factor beginning in FY 2020.
Specifically, for this proposed rule, we used the December 2017 MedPAR
file of FY 2017 (October 1, 2016 through September 30, 2017) charge
data (released in conjunction with the FY 2019 IPPS/LTCH PPS proposed
rule) and the December 2018 MedPAR file of FY 2018 (October 1, 2017
through September 30, 2018) charge data (released in conjunction with
this FY 2020 IPPS/LTCH PPS proposed rule) to compute the proposed
charge inflation factor. In addition, we are proposing that, for the FY
2020 final rule, we would use the most recent available data; that is,
the MedPAR files from March 2018 for the FY 2017 charge data and the
MedPAR files from March 2019 for the FY 2018 charge data. Because these
data are publicly available at the time of the issuance of the proposed
and final rules, we are proposing that, beginning with the FY 2020
final rule, we would no longer provide the table of quarterly charges
that we have included in prior rulemaking, if this proposed change to
our methodology is finalized. (We note that we are providing this
information in this proposed rule for comparison purposes below.) We
are inviting public comments on this proposed change to our methodology
to use in this proposed rule the December 2017 and December 2018 MedPAR
releases for the respective FY 2017 and FY 2018 October to September
applicable periods rather than the respective CY 2017 and CY 2018
January to December applicable periods for purposes of calculating the
proposed charge inflation factor for the FY 2020 outlier threshold
calculation.
For FY 2020, under this proposed methodology, to compute the 1-year
average annual rate-of-change in charges per case, we compared the
average covered charge per case of $58,355.91 ($562,621,348,420/
9,641,206) from October 1, 2016 through September 31, 2017, to the
average covered charge per case of $61,533.91 ($583,577,793,654/
9,483,841) from October 1, 2017 through September 31, 2018. This rate-
of-change was 5.4 percent (1.05446) or 11.2 percent (1.11189) over 2
years. The billed charges are obtained from the claims from the MedPAR
file and inflated by the inflation factor specified above.
We also are providing below our calculation of the 1-year average
annual rate-of-change in charges per case based on the December 2018
MedPAR release with applicable periods of January to December for CY
2017 and CY 2018 for comparison consistent with the methodology we used
for FYs 2014 through 2019. As we did for prior rulemaking, we grouped
claims by quarter and present the sum total for each time period in the
table that follows. Specifically, under the methodology we used for FYs
2014
[[Page 19597]]
through 2019, the 1-year average annualized rate-of-change in charges
per case for FY 2020 is computed by comparing the average covered
charge per case of $59,137.57 ($572,976,462,154/9,688,874) from January
1, 2017 through December 31, 2017 to the average covered charge per
case of $62,241.46 ($549,618,561,649/8,830,425) from January 1, 2018
through December 31, 2018. This rate-of-change was 5.2 percent
(1.05249) or 10.8 percent (1.10775) over 2 years.
--------------------------------------------------------------------------------------------------------------------------------------------------------
Covered charges Covered charges
(January 1, 2017 Cases (January 1, 2017 (January 1, 2018 Cases (January 1, 2018
Quarter through December 31, through December 31, through December 31, through December 31,
2017) 2017) 2018) 2018)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Jan-Mar............................................. $149,423,349,880 2,550,360 $155,383,152,668 2,507,345
Apr-Jun............................................. 141,253,933,908 2,407,205 144,511,911,637 2,336,261
Jul-Sep............................................. 137,549,332,685 2,328,520 138,928,539,807 2,238,344
Oct-Dec............................................. 144,749,845,681 2,402,789 110,794,957,537 1,748,475
---------------------------------------------------------------------------------------------------
Total........................................... 572,976,462,154 9,688,874 549,618,561,649 8,830,425
--------------------------------------------------------------------------------------------------------------------------------------------------------
As we have done in the past, in this FY 2020 IPPS/LTCH PPS proposed
rule, we are proposing to establish the proposed FY 2020 outlier
threshold using hospital CCRs from the December 2018 update to the
Provider-Specific File (PSF)--the most recent available data at the
time of the development of this proposed rule. We are proposing to
apply the following edits to providers' CCRs in the PSF. We believe
these edits are appropriate in order to accurately model the outlier
threshold. We first search for Indian Health Service providers and
those providers assigned the statewide average CCR from the current
fiscal year. We then replace these CCRs with the statewide average CCR
for the upcoming fiscal year. We also assign the statewide average CCR
(for the upcoming fiscal year) to those providers that have no value in
the CCR field in the PSF or whose CCRs exceed the ceilings described
later in this section (3.0 standard deviations from the mean of the log
distribution of CCRs for all hospitals). We do not apply the adjustment
factors described below to hospitals assigned the statewide average
CCR. For FY 2020, we also are proposing to continue to apply an
adjustment factor to the CCRs to account for cost and charge inflation
(as explained below). We also are proposing that, if more recent data
become available, we would use that data to calculate the final FY 2020
outlier threshold.
In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50979), we adopted a
new methodology to adjust the CCRs. Specifically, we finalized a policy
to compare the national average case-weighted operating and capital CCR
from the most recent update of the PSF to the national average case-
weighted operating and capital CCR from the same period of the prior
year.
Therefore, as we have done since FY 2014, we are proposing to
adjust the CCRs from the December 2018 update of the PSF by comparing
the percentage change in the national average case-weighted operating
CCR and capital CCR from the December 2017 update of the PSF to the
national average case-weighted operating CCR and capital CCR from the
December 2018 update of the PSF. We note that we used total transfer-
adjusted cases from FY 2018 to determine the national average case-
weighted CCRs for both sides of the comparison. As stated in the FY
2014 IPPS/LTCH PPS final rule (78 FR 50979), we believe that it is
appropriate to use the same case count on both sides of the comparison
because this will produce the true percentage change in the average
case-weighted operating and capital CCR from one year to the next
without any effect from a change in case count on different sides of
the comparison.
Using the proposed methodology above, for this proposed rule, we
calculated a proposed December 2017 operating national average case-
weighted CCR of 0.263267 and a proposed December 2018 operating
national average case-weighted CCR of 0.256730. We then calculated the
percentage change between the two national operating case-weighted CCRs
by subtracting the proposed December 2017 operating national average
case-weighted CCR from the proposed December 2018 operating national
average case-weighted CCR and then dividing the result by the proposed
December 2017 national operating average case-weighted CCR. This
resulted in a proposed national operating CCR adjustment factor of
0.975167.
We used the same methodology proposed above to adjust the capital
CCRs. Specifically, we calculated a proposed December 2017 capital
national average case-weighted CCR of 0.022094 and a proposed December
2018 capital national average case-weighted CCR of 0.021121. We then
calculated the percentage change between the two national capital case-
weighted CCRs by subtracting the proposed December 2017 capital
national average case-weighted CCR from the proposed December 2018
capital national average case-weighted CCR and then dividing the result
by the proposed December 2017 capital national average case-weighted
CCR. This resulted in a proposed national capital CCR adjustment factor
of 0.955983.
For purposes of estimating the proposed outlier threshold for FY
2020, we used a wage index that is based on the proposed FY 2020 wage
index that hospitals would be paid. This includes our proposal to
remove urban to rural reclassifications from the calculation of the
rural floor, the frontier State floor adjustment in accordance with
section 10324(a) of the Affordable Care Act, and the out-migration
adjustment as added by section 505 of Public Law 108-173, and
incorporates our FY 2020 wage index proposals to (1) increase the wage
index values for hospitals with a wage index value below the 25th
percentile wage index value across all hospitals and offset the
estimated increase in IPPS payments to hospitals with wage index values
below the 25th percentile by decreasing the wage index values for
hospitals with a wage index value above the 75th percentile wage index
value across all hospitals, and (2) apply a 5-percent cap for FY 2020
on any decrease in a hospital's final wage index from the hospital's
final wage index in FY 2019. If we did not take the above into account,
our estimate of total FY 2020 payments would be too low, and, as a
result, our proposed outlier threshold would be too high, such that
estimated outlier payments would be less than our projected 5.13
percent of total payments (which reflects the estimate of outlier
reconciliation).
As described in sections IV.G. and IV.H., respectively, of the
preamble of
[[Page 19598]]
this proposed rule, sections 1886(q) and 1886(o) of the Act establish
the Hospital Readmissions Reduction Program and the Hospital VBP
Program, respectively. We do not believe that it is appropriate to
include the proposed hospital VBP payment adjustments and the hospital
readmissions payment adjustments in the proposed outlier threshold
calculation or the proposed outlier offset to the standardized amount.
Specifically, consistent with our definition of the base operating DRG
payment amount for the Hospital Readmissions Reduction Program under
Sec. 412.152 and the Hospital VBP Program under Sec. 412.160, outlier
payments under section 1886(d)(5)(A) of the Act are not affected by
these payment adjustments. Therefore, outlier payments would continue
to be calculated based on the unadjusted base DRG payment amount (as
opposed to using the base-operating DRG payment amount adjusted by the
hospital readmissions payment adjustment and the hospital VBP payment
adjustment). Consequently, we are proposing to exclude the proposed
hospital VBP payment adjustments and the estimated hospital
readmissions payment adjustments from the calculation of the proposed
outlier fixed-loss cost threshold.
We note that, to the extent section 1886(r) of the Act modifies the
DSH payment methodology under section 1886(d)(5)(F) of the Act, the
uncompensated care payment under section 1886(r)(2) of the Act, like
the empirically justified Medicare DSH payment under section 1886(r)(1)
of the Act, may be considered an amount payable under section
1886(d)(5)(F) of the Act such that it would be reasonable to include
the payment in the outlier determination under section 1886(d)(5)(A) of
the Act. As we have done since the implementation of uncompensated care
payments in FY 2014, for FY 2020, we also are proposing to allocate an
estimated per-discharge uncompensated care payment amount to all cases
for the hospitals eligible to receive the uncompensated care payment
amount in the calculation of the outlier fixed-loss cost threshold
methodology. We continue to believe that allocating an eligible
hospital's estimated uncompensated care payment to all cases equally in
the calculation of the outlier fixed-loss cost threshold would best
approximate the amount we would pay in uncompensated care payments
during the year because, when we make claim payments to a hospital
eligible for such payments, we would be making estimated per-discharge
uncompensated care payments to all cases equally. Furthermore, we
continue to believe that using the estimated per-claim uncompensated
care payment amount to determine outlier estimates provides
predictability as to the amount of uncompensated care payments included
in the calculation of outlier payments. Therefore, consistent with the
methodology used since FY 2014 to calculate the outlier fixed-loss cost
threshold, for FY 2020, we are proposing to include estimated FY 2020
uncompensated care payments in the computation of the proposed outlier
fixed-loss cost threshold. Specifically, we are proposing to use the
estimated per-discharge uncompensated care payments to hospitals
eligible for the uncompensated care payment for all cases in the
calculation of the proposed outlier fixed-loss cost threshold
methodology.
Using this methodology, we used the formula described in section
I.C.1. of this Addendum to simulate and calculate the Federal payment
rate and outlier payments for all claims. In addition, as described in
the earlier section to this Addendum, we are proposing to incorporate
an estimate of FY 2020 outlier reconciliation in the methodology for
determining the outlier threshold. Under this proposed approach, we
determined a threshold of $26,994 and calculated total operating
Federal payments of $90,721,309,065 and total outlier payments of
$4,905,819,657. We then divided total outlier payments by total
operating Federal payments plus total outlier payments and determined
that this threshold matched with the 5.13 percent target, which
reflects our proposal to incorporate an estimate of outlier
reconciliation in the determination of the outlier threshold (as
discussed in more detail in the previous section of this Addendum). We
note that, if calculated without applying our proposed methodology for
incorporating an estimate of outlier reconciliation in the
determination of the outlier threshold, the proposed threshold would be
$27,154. We are proposing an outlier fixed-loss cost threshold for FY
2020 equal to the prospective payment rate for the MS-DRG, plus any
IME, empirically justified Medicare DSH payments, estimated
uncompensated care payment, and any add-on payments for new technology,
plus $26,994.
(2) Other Proposed Changes Concerning Outliers
As stated in the FY 1994 IPPS final rule (58 FR 46348), we
establish an outlier threshold that is applicable to both hospital
inpatient operating costs and hospital inpatient capital-related costs.
When we modeled the combined operating and capital outlier payments, we
found that using a common threshold resulted in a lower percentage of
outlier payments for capital-related costs than for operating costs. We
project that the threshold for FY 2020 of $26,994 (which reflects our
proposed methodology to incorporate an estimate of outlier
reconciliations) would result in outlier payments that will equal 5.1
percent of operating DRG payments and 5.33 percent of capital payments
based on the Federal rate.
In accordance with section 1886(d)(3)(B) of the Act and as
discussed above, we are proposing to reduce the FY 2020 standardized
amount by 5.1 percent to account for the projected proportion of
payments paid as outliers.
The proposed outlier adjustment factors that would be applied to
the operating standardized amount and capital Federal rate based on the
proposed FY 2020 outlier threshold are as follows:
------------------------------------------------------------------------
Operating
standardized Capital federal
amounts rate *
------------------------------------------------------------------------
National.............................. 0.949 0.9466388
------------------------------------------------------------------------
* The proposed adjustment factor for the capital Federal rate includes
an adjustment to the estimated percentage of FY 2020 capital outlier
payments for capital outlier reconciliation, as discussed above and in
section II.A.4.j.(1) in the Addendum to this proposed rule.
We are proposing to apply the outlier adjustment factors to the
proposed FY 2020 payment rates after removing the effects of the FY
2019 outlier adjustment factors on the standardized amount.
To determine whether a case qualifies for outlier payments, we
currently apply hospital-specific CCRs to the total covered charges for
the case. Estimated operating and capital costs for the case are
calculated separately by applying
[[Page 19599]]
separate operating and capital CCRs. These costs are then combined and
compared with the outlier fixed-loss cost threshold.
Under our current policy at Sec. 412.84, we calculate operating
and capital CCR ceilings and assign a statewide average CCR for
hospitals whose CCRs exceed 3.0 standard deviations from the mean of
the log distribution of CCRs for all hospitals. Based on this
calculation, for hospitals for which the MAC computes operating CCRs
greater than 1.151 or capital CCRs greater than 0.141, or hospitals for
which the MAC is unable to calculate a CCR (as described under Sec.
412.84(i)(3) of our regulations), statewide average CCRs are used to
determine whether a hospital qualifies for outlier payments. Table 8A
listed in section VI. of this Addendum (and available only via the
internet on the CMS website) contains the proposed statewide average
operating CCRs for urban hospitals and for rural hospitals for which
the MAC is unable to compute a hospital-specific CCR within the above
range. These statewide average ratios would be effective for discharges
occurring on or after October 1, 2019 and would replace the statewide
average ratios from the prior fiscal year. Table 8B listed in section
VI. of this Addendum (and available via the internet on the CMS
website) contains the comparable proposed statewide average capital
CCRs. As previously stated, the proposed CCRs in Tables 8A and 8B would
be used during FY 2020 when hospital-specific CCRs based on the latest
settled cost report either are not available or are outside the range
noted above. Table 8C listed in section VI. of this Addendum (and
available via the internet on the CMS website) contains the proposed
statewide average total CCRs used under the LTCH PPS as discussed in
section V. of this Addendum.
We finally note that we published a manual update (Change Request
3966) to our outlier policy on October 12, 2005, which updated Chapter
3, Section 20.1.2 of the Medicare Claims Processing Manual. The manual
update covered an array of topics, including CCRs, reconciliation, and
the time value of money. We encourage hospitals that are assigned the
statewide average operating and/or capital CCRs to work with their MAC
on a possible alternative operating and/or capital CCR as explained in
Change Request 3966. Use of an alternative CCR developed by the
hospital in conjunction with the MAC can avoid possible overpayments or
underpayments at cost report settlement, thereby ensuring better
accuracy when making outlier payments and negating the need for outlier
reconciliation. We also note that a hospital may request an alternative
operating or capital CCR at any time as long as the guidelines of
Change Request 3966 are followed. In addition, as mentioned above, we
published an additional manual update (Change Request 7192) to our
outlier policy on December 3, 2010, which also updated Chapter 3,
Section 20.1.2 of the Medicare Claims Processing Manual. The manual
update outlines the outlier reconciliation process for hospitals and
Medicare contractors. To download and view the manual instructions on
outlier reconciliation, we refer readers to the CMS website: http://www.cms.hhs.gov/manuals/downloads/clm104c03.pdf.
(3) FY 2018 Outlier Payments
Our current estimate, using available FY 2018 claims data, is that
actual outlier payments for FY 2018 were approximately 4.94 percent of
actual total MS-DRG payments. Therefore, the data indicate that, for FY
2018, the percentage of actual outlier payments relative to actual
total payments is lower than we projected for FY 2018. Consistent with
the policy and statutory interpretation we have maintained since the
inception of the IPPS, we do not make retroactive adjustments to
outlier payments to ensure that total outlier payments for FY 2018 are
equal to 5.1 percent of total MS-DRG payments. As explained in the FY
2003 Outlier Final Rule (68 FR 34502), if we were to make retroactive
adjustments to all outlier payments to ensure total payments are 5.1
percent of MS-DRG payments (by retroactively adjusting outlier
payments), we would be removing the important aspect of the prospective
nature of the IPPS. Because such an across-the-board adjustment would
either lead to more or less outlier payments for all hospitals,
hospitals would no longer be able to reliably approximate their payment
for a patient while the patient is still hospitalized. We believe it
would be neither necessary nor appropriate to make such an aggregate
retroactive adjustment. Furthermore, we believe it is consistent with
the statutory language at section 1886(d)(5)(A)(iv) of the Act not to
make retroactive adjustments to outlier payments. This section states
that outlier payments be equal to or greater than 5 percent and less
than or equal to 6 percent of projected or estimated (not actual) MS-
DRG payments. We believe that an important goal of a PPS is
predictability. Therefore, we believe that the fixed-loss outlier
threshold should be projected based on the best available historical
data and should not be adjusted retroactively. A retroactive change to
the fixed-loss outlier threshold would affect all hospitals subject to
the IPPS, thereby undercutting the predictability of the system as a
whole.
We note that, because the MedPAR claims data for the entire FY 2019
will not be available until after September 30, 2019, we are unable to
provide an estimate of actual outlier payments for FY 2019 based on FY
2019 claims data in this proposed rule. We will provide an estimate of
actual FY 2019 outlier payments in the FY 2021 IPPS/LTCH PPS proposed
rule.
5. Proposed FY 2020 Standardized Amount
The adjusted standardized amount is divided into labor-related and
nonlabor-related portions. Tables 1A and 1B listed and published in
section VI. of this Addendum (and available via the internet on the CMS
website) contain the national standardized amounts that we are
proposing to apply to all hospitals, except hospitals located in Puerto
Rico, for FY 2020. The proposed standardized amount for hospitals in
Puerto Rico is shown in Table 1C listed and published in section VI. of
this Addendum (and available via the internet on the CMS website). The
proposed amounts shown in Tables 1A and 1B differ only in that the
labor-related share applied to the standardized amounts in Table 1A is
68.3 percent, and the labor-related share applied to the standardized
amounts in Table 1B is 62 percent. In accordance with sections
1886(d)(3)(E) and 1886(d)(9)(C)(iv) of the Act, we are proposing to
apply a labor-related share of 62 percent, unless application of that
percentage would result in lower payments to a hospital than would
otherwise be made. In effect, the statutory provision means that we
will apply a labor-related share of 62 percent for all hospitals whose
wage indexes are less than or equal to 1.0000.
In addition, Tables 1A and 1B include the proposed standardized
amounts reflecting the proposed applicable percentage increases for FY
2020.
The proposed labor-related and nonlabor-related portions of the
national average standardized amounts for Puerto Rico hospitals for FY
2020 are set forth in Table 1C listed and published in section VI. of
this Addendum (and available via the internet on the CMS website).
Similar to above, section 1886(d)(9)(C)(iv) of the Act, as amended by
section 403(b) of Public Law 108-173, provides that the labor-related
share for hospitals located in Puerto Rico be 62 percent, unless the
[[Page 19600]]
application of that percentage would result in lower payments to the
hospital.
The following table illustrates the changes from the FY 2019
national standardized amounts to the proposed FY 2020 national
standardized amounts. The second through fifth columns display the
changes from the FY 2019 standardized amounts for each applicable
proposed FY 2020 standardized amount. The first row of the table shows
the updated (through FY 2019) average standardized amount after
restoring the FY 2019 offsets for outlier payments and the geographic
reclassification budget neutrality. The MS-DRG reclassification and
recalibration and wage index budget neutrality adjustment factors are
cumulative. Therefore, those FY 2019 adjustment factors are not removed
from this table. Additionally, for FY 2020, we have applied the
proposed budget neutrality factor for the proposed policy for lowest
quartile wage index hospitals and proposed transition, described above.
BILLING CODE 4120-01-P
[[Page 19601]]
[GRAPHIC] [TIFF OMITTED] TP03MY19.027
[[Page 19602]]
[GRAPHIC] [TIFF OMITTED] TP03MY19.028
BILLING CODE 4120-01-C
B. Proposed Adjustments for Area Wage Levels and Cost-of-Living
Tables 1A through 1C, as published in section VI. of this Addendum
(and available via the internet on the CMS website), contain the
proposed labor-related and nonlabor-related shares that we are
proposing to use to calculate the prospective payment rates for
hospitals located in the 50 States, the District of Columbia, and
Puerto Rico for FY 2020. This section addresses two types of
adjustments to the standardized amounts that are made in determining
the proposed prospective payment rates as described in this Addendum.
1. Proposed Adjustment for Area Wage Levels
Sections 1886(d)(3)(E) and 1886(d)(9)(C)(iv) of the Act require
that we make an adjustment to the labor-related portion of the national
prospective payment rate to account for area differences in hospital
wage levels. This adjustment is made by multiplying the labor-related
portion of the adjusted standardized amounts by the appropriate wage
index for the area in which the hospital is located. For FY 2020, as
discussed in section IV.B.3. of the preamble of this proposed rule, we
are proposing to apply a labor-related share of 68.3 percent for the
national standardized amounts for all IPPS hospitals (including
hospitals in Puerto Rico) that have a wage index value that is greater
than 1.0000. Consistent with section 1886(d)(3)(E) of the Act, we are
proposing to apply the wage index to a labor-related share of 62
percent of the national standardized amount for all IPPS hospitals
(including hospitals in Puerto Rico) whose wage index values are less
than or equal to 1.0000. In section III. of the preamble of this
proposed rule, we discuss the data and methodology for the proposed FY
2020 wage index.
2. Proposed Adjustment for Cost-of-Living in Alaska and Hawaii
Section 1886(d)(5)(H) of the Act provides discretionary authority
to the Secretary to make adjustments as the Secretary deems appropriate
to take into account the unique circumstances of hospitals located in
Alaska and Hawaii. Higher labor-related costs for these two States are
taken into account in the adjustment for area wages described above. To
account for higher nonlabor-related costs for these two States, we
multiply the nonlabor-related portion of the standardized amount for
hospitals located in Alaska and Hawaii by an adjustment factor.
In the FY 2013 IPPS/LTCH PPS final rule, we established a
methodology to update the COLA factors for Alaska and Hawaii that were
published by the U.S. Office of Personnel Management (OPM) every 4
years (at the same time as the update to the labor-related share of the
IPPS market basket), beginning in FY 2014. We refer readers to the FY
2013 IPPS/LTCH PPS proposed and final rules for additional background
and a detailed description of this methodology (77 FR 28145 through
28146 and 77 FR 53700 through 53701, respectively).
For FY 2018, in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38530
through 38531), we updated the COLA factors published by OPM for 2009
(as these are the last COLA factors OPM published prior to
transitioning from COLAs to locality pay) using the methodology that we
finalized in the FY 2013 IPPS/LTCH PPS final rule.
Based on the policy finalized in the FY 2013 IPPS/LTCH PPS final
rule, we are proposing to continue to use the same COLA factors in FY
2020 that were used in FY 2019 to adjust the nonlabor-related portion
of the standardized amount for hospitals located in Alaska and Hawaii.
Below is a table listing the proposed COLA factors for FY 2020.
[[Page 19603]]
Proposed FY 2020 Cost-of-Living Adjustment Factors: Alaska and Hawaii
Hospitals
------------------------------------------------------------------------
Cost of living
Area adjustment
factor
------------------------------------------------------------------------
Alaska:
City of Anchorage and 80-kilometer (50-mile) radius 1.25
by road............................................
City of Fairbanks and 80-kilometer (50-mile) radius 1.25
by road............................................
City of Juneau and 80-kilometer (50-mile) radius by 1.25
road...............................................
Rest of Alaska...................................... 1.25
City and County of Honolulu......................... 1.25
County of Hawaii.................................... 1.21
County of Kauai..................................... 1.25
County of Maui and County of Kalawao................ 1.25
------------------------------------------------------------------------
Based on the policy finalized in the FY 2013 IPPS/LTCH PPS final
rule, the next update to the COLA factors for Alaska and Hawaii would
occur at the same time as the update to the labor-related share of the
IPPS market basket (no later than FY 2022).
C. Calculation of the Proposed Prospective Payment Rates
General Formula for Calculation of the Prospective Payment Rates for FY
2020
In general, the operating prospective payment rate for all
hospitals (including hospitals in Puerto Rico) paid under the IPPS,
except SCHs and MDHs, for FY 2020 equals the Federal rate (which
includes uncompensated care payments).
Under current law, the MDH program has been extended for discharges
through September 30, 2022.
SCHs are paid based on whichever of the following rates yields the
greatest aggregate payment: The Federal national rate (which, as
discussed in section IV.F. of the preamble of this proposed rule,
includes uncompensated care payments); the updated hospital-specific
rate based on FY 1982 costs per discharge; the updated hospital-
specific rate based on FY 1987 costs per discharge; the updated
hospital-specific rate based on FY 1996 costs per discharge; or the
updated hospital-specific rate based on FY 2006 costs per discharge to
determine the rate that yields the greatest aggregate payment.
The prospective payment rate for SCHs for FY 2020 equals the higher
of the applicable Federal rate, or the hospital-specific rate as
described below. The prospective payment rate for MDHs for FY 2020
equals the higher of the Federal rate, or the Federal rate plus 75
percent of the difference between the Federal rate and the hospital-
specific rate as described below. For MDHs, the updated hospital-
specific rate is based on FY 1982, FY 1987, or FY 2002 costs per
discharge, whichever yields the greatest aggregate payment.
1. Operating and Capital Federal Payment Rate and Outlier Payment
Calculation
Note: The formula below is used for actual claim payment and is
also used by CMS to project the outlier threshold for the upcoming
fiscal year. The difference is the source of some of the variables in
the formula. For example, operating and capital CCRs for actual claim
payment are from the PSF while CMS uses an adjusted CCR (as described
above) to project the threshold for the upcoming fiscal year. In
addition, charges for a claim payment are from the bill, while charges
to project the threshold are from the MedPAR data with an inflation
factor applied to the charges (as described earlier).
Step 1--Determine the MS-DRG and MS-DRG relative weight for each
claim based on the ICD-10-CM procedure and diagnosis codes on the
claim.
Step 2--Select the applicable average standardized amount depending
on whether the hospital submitted qualifying quality data and is a
meaningful EHR user, as described above.
Step 3--Compute the operating and capital Federal payment rate:
Federal Payment Rate for Operating Costs = MS-DRG Relative Weight x
[(Labor-Related Applicable Standardized Amount x Applicable CBSA Wage
Index) + (Nonlabor-Related Applicable Standardized Amount x Cost-of-
Living Adjustment)] x (1 + IME + (DSH * 0.25))
Federal Payment for Capital Costs = MS-DRG Relative Weight x Federal
Capital Rate x Geographic Adjustment Fact x (1 + IME + DSH)
Step 4--Determine operating and capital costs:
Operating Costs = (Billed Charges x Operating CCR)
Capital Costs = (Billed Charges x Capital CCR).
Step 5--Compute operating and capital outlier threshold (CMS
applies a geographic adjustment to the operating and capital outlier
threshold to account for local cost variation):
Operating CCR to Total CCR = (Operating CCR)/(Operating CCR + Capital
CCR)
Operating Outlier Threshold = [Fixed Loss Threshold x ((Labor-Related
Portion x CBSA Wage Index) + Nonlabor-Related portion)] x Operating CCR
to Total CCR + Federal Payment with IME, DSH + Uncompensated Care
Payment + New Technology Add-On Payment Amount
Capital CCR to Total CCR = (Capital CCR)/(Operating CCR + Capital CCR)
Capital Outlier Threshold = (Fixed Loss Threshold x Geographic
Adjustment Factor x Capital CCR to Total CCR) + Federal Payment with
IME and DSH
Step 6--Compute operating and capital outlier payments:
Marginal Cost Factor = 0.80 or 0.90 (depending on the MS-DRG)
Operating Outlier Payment = (Operating Costs--Operating Outlier
Threshold) x Marginal Cost Factor
Capital Outlier Payment = (Capital Costs--Capital Outlier Threshold) x
Marginal Cost Factor
The payment rate may then be further adjusted for hospitals that
qualify for a low-volume payment adjustment under section 1886(d)(12)
of the Act and 42 CFR 412.101(b). The base-operating DRG payment amount
may be further adjusted by the hospital readmissions payment adjustment
and the hospital VBP payment adjustment as described under sections
1886(q) and 1886(o) of the Act, respectively. Payments also may be
reduced by the 1-percent adjustment under the HAC Reduction Program as
described in section 1886(p) of the Act. We also make new technology
add-on payments in accordance with section 1886(d)(5)(K) and (L) of the
Act. Finally, we add the uncompensated care payment to the
[[Page 19604]]
total claim payment amount. As noted in the formula above, we take
uncompensated care payments and new technology add-on payments into
consideration when calculating outlier payments.
2. Hospital-Specific Rate (Applicable Only to SCHs and MDHs)
a. Calculation of Hospital-Specific Rate
Section 1886(b)(3)(C) of the Act provides that SCHs are paid based
on whichever of the following rates yields the greatest aggregate
payment: The Federal rate; the updated hospital-specific rate based on
FY 1982 costs per discharge; the updated hospital-specific rate based
on FY 1987 costs per discharge; the updated hospital-specific rate
based on FY 1996 costs per discharge; or the updated hospital-specific
rate based on FY 2006 costs per discharge to determine the rate that
yields the greatest aggregate payment.
As noted above, the MDH program has been extended under current law
for discharges occurring through September 30, 2022. For MDHs, the
updated hospital-specific rate is based on FY 1982, FY 1987, or FY 2002
costs per discharge, whichever yields the greatest aggregate payment.
For a more detailed discussion of the calculation of the hospital-
specific rates, we refer readers to the FY 1984 IPPS interim final rule
(48 FR 39772); the April 20, 1990 final rule with comment period (55 FR
15150); the FY 1991 IPPS final rule (55 FR 35994); and the FY 2001 IPPS
final rule (65 FR 47082).
b. Updating the FY 1982, FY 1987, FY 1996, FY 2002 and FY 2006
Hospital-Specific Rate for FY 2019
Section 1886(b)(3)(B)(iv) of the Act provides that the applicable
percentage increase applicable to the hospital-specific rates for SCHs
and MDHs equals the applicable percentage increase set forth in section
1886(b)(3)(B)(i) of the Act (that is, the same update factor as for all
other hospitals subject to the IPPS). Because the Act sets the update
factor for SCHs and MDHs equal to the update factor for all other IPPS
hospitals, the update to the hospital-specific rates for SCHs and MDHs
is subject to the amendments to section 1886(b)(3)(B) of the Act made
by sections 3401(a) and 10319(a) of the Affordable Care Act.
Accordingly, the proposed applicable percentage increases to the
hospital-specific rates applicable to SCHs and MDHs are the following:
----------------------------------------------------------------------------------------------------------------
Hospital Hospital Hospital did Hospital did
submitted submitted NOT submit NOT submit
quality data quality data quality data quality data
FY 2020 and is a and is NOT a and is a and is NOT a
meaningful EHR meaningful EHR meaningful EHR meaningful EHR
user user user user
----------------------------------------------------------------------------------------------------------------
Proposed Market Basket 3.2 3.2 3.2 3.2
Rate[dash]of[dash]Increase.....................
Proposed Adjustment for Failure to Submit 0 0 -0.8 -0.8
Quality Data under Section 1886(b)(3)(B)(viii)
of the Act.....................................
Proposed Adjustment for Failure to be a 0 -2.4 0 -2.4
Meaningful EHR User under Section
1886(b)(3)(B)(ix) of the Act...................
Proposed MFP Adjustment under Section -0.5 -0.5 -0.5 -0.5
1886(b)(3)(B)(xi) of the Act...................
Proposed Applicable Percentage Increase Applied 2.7 0.3 1.9 -0.5
to Standardized Amount.........................
----------------------------------------------------------------------------------------------------------------
For a complete discussion of the applicable percentage increase
applied to the hospital-specific rates for SCHs and MDHs, we refer
readers to section IV.B. of the preamble of this proposed rule.
In addition, because SCHs and MDHs use the same MS-DRGs as other
hospitals when they are paid based in whole or in part on the hospital-
specific rate, the hospital-specific rate is adjusted by a budget
neutrality factor to ensure that changes to the MS-DRG classifications
and the recalibration of the MS-DRG relative weights are made in a
manner so that aggregate IPPS payments are unaffected. Therefore, the
proposed hospital-specific rate for an SCH or an MDH is adjusted by the
proposed MS-DRG reclassification and recalibration budget neutrality
factor of 0.998768, as discussed in section III. of this Addendum. The
resulting rate is used in determining the payment rate that an SCH or
MDH would receive for its discharges beginning on or after October 1,
2019. We note that, in this proposed rule, for FY 2020, we are not
proposing to make a documentation and coding adjustment to the
hospital-specific rate. We refer readers to section II.D. of the
preamble of this proposed rule for a complete discussion regarding our
proposed policies and previously finalized policies (including our
historical adjustments to the payment rates) relating to the effect of
changes in documentation and coding that do not reflect real changes in
case-mix.
III. Proposed Changes to Payment Rates for Acute Care Hospital
Inpatient Capital-Related Costs for FY 2020
The PPS for acute care hospital inpatient capital-related costs was
implemented for cost reporting periods beginning on or after October 1,
1991. The basic methodology for determining Federal capital prospective
rates is set forth in the regulations at 42 CFR 412.308 through
412.352. Below we discuss the factors that we are proposing to use to
determine the capital Federal rate for FY 2020, which would be
effective for discharges occurring on or after October 1, 2019.
All hospitals (except ``new'' hospitals under Sec. 412.304(c)(2))
are paid based on the capital Federal rate. We annually update the
capital standard Federal rate, as provided in Sec. 412.308(c)(1), to
account for capital input price increases and other factors. The
regulations at Sec. 412.308(c)(2) also provide that the capital
Federal rate be adjusted annually by a factor equal to the estimated
proportion of outlier payments under the capital Federal rate to total
capital payments under the capital Federal rate. In addition, Sec.
412.308(c)(3) requires that the capital Federal rate be reduced by an
adjustment factor equal to the estimated proportion of payments for
exceptions under Sec. 412.348. (We note that, as discussed in the FY
2013 IPPS/LTCH PPS final rule (77 FR 53705), there is generally no
longer a need for an exceptions payment adjustment factor.) However, in
limited circumstances, an additional payment exception for
extraordinary circumstances is provided for under Sec. 412.348(f) for
qualifying hospitals. Therefore, in accordance with Sec.
412.308(c)(3), an exceptions payment adjustment factor may need to be
applied if such payments are made. Section 412.308(c)(4)(ii) requires
that
[[Page 19605]]
the capital standard Federal rate be adjusted so that the effects of
the annual DRG reclassification and the recalibration of DRG weights
and changes in the geographic adjustment factor (GAF) are budget
neutral.
Section 412.374 provides for payments to hospitals located in
Puerto Rico under the IPPS for acute care hospital inpatient capital-
related costs, which currently specifies capital IPPS payments to
hospitals located in Puerto Rico are based on 100 percent of the
Federal rate.
A. Determination of the Proposed Federal Hospital Inpatient Capital-
Related Prospective Payment Rate Update for FY 2020
In the discussion that follows, we explain the factors that we are
proposing to use to determine the capital Federal rate for FY 2020. In
particular, we explain why the proposed FY 2020 capital Federal rate
would increase approximately 0.96 percent, compared to the FY 2019
capital Federal rate. As discussed in the impact analysis in Appendix A
to this proposed rule, we estimate that capital payments per discharge
would increase approximately 1.9 percent during that same period.
Because capital payments constitute approximately 10 percent of
hospital payments, a 1-percent change in the capital Federal rate
yields only approximately a 0.1 percent change in actual payments to
hospitals.
1. Projected Capital Standard Federal Rate Update
Under Sec. 412.308(c)(1), the capital standard Federal rate is
updated on the basis of an analytical framework that takes into account
changes in a capital input price index (CIPI) and several other policy
adjustment factors. Specifically, we adjust the projected CIPI rate of
change, as appropriate, each year for case-mix index-related changes,
for intensity, and for errors in previous CIPI forecasts. The proposed
update factor for FY 2020 under that framework is 1.5 percent based on
a projected 1.5 percent increase in the 2014-based CIPI, a proposed 0.0
percentage point adjustment for intensity, a proposed 0.0 percentage
point adjustment for case-mix, a proposed 0.0 percentage point
adjustment for the DRG reclassification and recalibration, and a
proposed forecast error correction of 0.0 percentage point. As
discussed in section III.C. of this Addendum, we continue to believe
that the CIPI is the most appropriate input price index for capital
costs to measure capital price changes in a given year. We also explain
the basis for the FY 2020 CIPI projection in that same section of this
Addendum. Below we describe the proposed policy adjustments that we are
proposing to apply in the update framework for FY 2020.
The case-mix index is the measure of the average DRG weight for
cases paid under the IPPS. Because the DRG weight determines the
prospective payment for each case, any percentage increase in the case-
mix index corresponds to an equal percentage increase in hospital
payments.
The case-mix index can change for any of several reasons:
The average resource use of Medicare patient changes
(``real'' case-mix change);
Changes in hospital documentation and coding of patient
records result in higher-weighted DRG assignments (``coding effects'');
and
The annual DRG reclassification and recalibration changes
may not be budget neutral (``reclassification effect'').
We define real case-mix change as actual changes in the mix (and
resource requirements) of Medicare patients, as opposed to changes in
documentation and coding behavior that result in assignment of cases to
higher-weighted DRGs, but do not reflect higher resource requirements.
The capital update framework includes the same case-mix index
adjustment used in the former operating IPPS update framework (as
discussed in the May 18, 2004 IPPS proposed rule for FY 2005 (69 FR
28816)). (We no longer use an update framework to make a recommendation
for updating the operating IPPS standardized amounts, as discussed in
section II. of Appendix B to the FY 2006 IPPS final rule (70 FR
47707).)
For FY 2020, we are projecting a 0.5 percent total increase in the
case-mix index. We estimated that the real case-mix increase would
equal 0.5 percent for FY 2020. The net adjustment for change in case-
mix is the difference between the projected real increase in case-mix
and the projected total increase in case-mix. Therefore, the proposed
net adjustment for case-mix change in FY 2020 is 0.0 percentage point.
The capital update framework also contains an adjustment for the
effects of DRG reclassification and recalibration. This adjustment is
intended to remove the effect on total payments of prior year's changes
to the DRG classifications and relative weights, in order to retain
budget neutrality for all case-mix index-related changes other than
those due to patient severity of illness. Due to the lag time in the
availability of data, there is a 2-year lag in data used to determine
the adjustment for the effects of DRG reclassification and
recalibration. For example, we have data available to evaluate the
effects of the FY 2018 DRG reclassification and recalibration as part
of our update for FY 2020. We assume, for purposes of this adjustment,
that the estimate of FY 2018 DRG reclassification and recalibration
would result in no change in the case-mix when compared with the case-
mix index that would have resulted if we had not made the
reclassification and recalibration changes to the DRGs. Therefore, we
are proposing to make a 0.0 percentage point adjustment for
reclassification and recalibration in the update framework for FY 2020.
The capital update framework also contains an adjustment for
forecast error. The input price index forecast is based on historical
trends and relationships ascertainable at the time the update factor is
established for the upcoming year. In any given year, there may be
unanticipated price fluctuations that may result in differences between
the actual increase in prices and the forecast used in calculating the
update factors. In setting a prospective payment rate under the
framework, we make an adjustment for forecast error only if our
estimate of the change in the capital input price index for any year is
off by 0.25 percentage point or more. There is a 2-year lag between the
forecast and the availability of data to develop a measurement of the
forecast error. Historically, when a forecast error of the CIPI is
greater than 0.25 percentage point in absolute terms, it is reflected
in the update recommended under this framework. A forecast error of -
0.1 percentage point was calculated for the FY 2018 update, for which
there are historical data. That is, current historical data indicated
that the forecasted FY 2018 CIPI (1.3 percent) used in calculating the
FY 2018 update factor was 0.1 percentage point higher than actual
realized price increases (1.2 percent). As this does not exceed the
0.25 percentage point threshold, we are not proposing an adjustment for
forecast error in the update for FY 2020.
Under the capital IPPS update framework, we also make an adjustment
for changes in intensity. Historically, we calculate this adjustment
using the same methodology and data that were used in the past under
the framework for operating IPPS. The intensity factor for the
operating update framework reflects how hospital services are utilized
to produce the final product, that is, the discharge. This component
accounts for changes in the use of quality-enhancing services, for
changes within DRG severity, and for expected modification
[[Page 19606]]
of practice patterns to remove noncost-effective services. Our
intensity measure is based on a 5-year average.
We calculate case-mix constant intensity as the change in total
cost per discharge, adjusted for price level changes (the CPI for
hospital and related services) and changes in real case-mix. Without
reliable estimates of the proportions of the overall annual intensity
changes that are due, respectively, to ineffective practice patterns
and the combination of quality-enhancing new technologies and
complexity within the DRG system, we assume that one-half of the annual
change is due to each of these factors. The capital update framework
thus provides an add-on to the input price index rate of increase of
one-half of the estimated annual increase in intensity, to allow for
increases within DRG severity and the adoption of quality-enhancing
technology.
In this proposed rule, we are proposing to continue to use a
Medicare-specific intensity measure that is based on a 5-year adjusted
average of cost per discharge for FY 2020 (we refer readers to the FY
2011 IPPS/LTCH PPS final rule (75 FR 50436) for a full description of
our Medicare-specific intensity measure). Specifically, for FY 2020, we
are proposing to use an intensity measure that is based on an average
of cost per discharge data from the 5-year period beginning with FY
2013 and extending through FY 2017. Based on these data, we estimated
that case-mix constant intensity declined during FYs 2013 through 2017.
In the past, when we found intensity to be declining, we believed a
zero (rather than a negative) intensity adjustment was appropriate.
Consistent with this approach, because we estimated that intensity
would decline during that 5-year period, we believe it is appropriate
to continue to apply a zero intensity adjustment for FY 2020.
Therefore, we are proposing to make a 0.0 percentage point adjustment
for intensity in the update for FY 2020.
Above we described the basis of the components we used to develop
the proposed 1.5 percent capital update factor under the capital update
framework for FY 2020, as shown in the following table.
Proposed FY 2020 Update Factor to the Capital Federal Rate
------------------------------------------------------------------------
------------------------------------------------------------------------
Capital Input Price Index *.................................... 1.5
Intensity...................................................... 0.0
Case-Mix Adjustment Factors:
Real Across DRG Change..................................... 0.5
Projected Case-Mix Change.................................. 0.5
Subtotal....................................................... 1.5
Effect of FY 2018 Reclassification and Recalibration........... 0.0
Forecast Error Correction...................................... 0.0
Total Proposed Update.......................................... 1.5
------------------------------------------------------------------------
* The capital input price index represents the 2014-based CIPI.
2. Outlier Payment Adjustment Factor
Section 412.312(c) establishes a unified outlier payment
methodology for inpatient operating and inpatient capital-related
costs. A shared threshold is used to identify outlier cases for both
inpatient operating and inpatient capital-related payments. Section
412.308(c)(2) provides that the standard Federal rate for inpatient
capital-related costs be reduced by an adjustment factor equal to the
estimated proportion of capital-related outlier payments to total
inpatient capital-related PPS payments. The outlier threshold is set so
that operating outlier payments are projected to be 5.1 percent of
total operating IPPS DRG payments. For FY 2020, we are proposing to
incorporate the estimated outlier reconciliation payment amounts into
the outlier threshold model. (For more details on our proposal to
incorporate estimated outlier reconciliation payment amounts into the
outlier threshold model, we refer readers to section II.A.4.h. of this
Addendum.)
For FY 2019, we estimated that outlier payments for capital-related
PPS payments would equal 5.06 percent of inpatient capital-related
payments based on the capital Federal rate in FY 2019. Based on the
threshold discussed in section II.A. of this Addendum, we estimate that
prior to taking into account projected capital outlier reconciliation
payments, outlier payments for capital-related costs would equal 5.39
percent for inpatient capital-related payments based on the proposed
capital Federal rate in FY 2020. However, using the methodology
outlined in section II.A.4.h. of this Addendum, we estimate that taking
into account projected capital outlier reconciliation payments would
decrease FY 2020 aggregate estimated capital outlier payments by 0.05
percent. Therefore, accounting for estimated capital outlier
reconciliation, the estimated outlier payments for capital-related PPS
payments would equal 5.34 percent (5.39 percent-0.05 percent) of
inpatient capital-related payments based on the capital Federal rate in
FY 2020. Accordingly, we are proposing to apply an outlier adjustment
factor of 0.9466 in determining the capital Federal rate for FY 2020.
Thus, we estimate that the percentage of capital outlier payments to
total capital Federal rate payments for FY 2020 would be higher than
the percentage for FY 2019.
The outlier reduction factors are not built permanently into the
capital rates; that is, they are not applied cumulatively in
determining the capital Federal rate. The proposed FY 2020 outlier
adjustment of 0.9466 is a 0.29 percent change from the FY 2019 outlier
adjustment of 0.9494. Therefore, the proposed net change in the outlier
adjustment to the capital Federal rate for FY 2020 is 0.9971 (0.9466/
0.9494; calculation performed on unrounded numbers) so that the
proposed outlier adjustment would decrease the FY 2020 capital Federal
rate by approximately 0.29 percent compared to the FY 2019 outlier
adjustment.
3. Budget Neutrality Adjustment Factor for Changes in DRG
Classifications and Weights and the GAF
Section 412.308(c)(4)(ii) requires that the capital Federal rate be
adjusted so that aggregate payments for the fiscal year based on the
capital Federal rate, after any changes resulting from the annual DRG
reclassification and recalibration and changes in the GAF, are
projected to equal aggregate payments that would have been made on the
basis of the capital Federal rate without such changes.
In section III.N. of the preamble of this proposed rule, we discuss
our proposals to address wage index disparities between high and low
wage index hospitals. Specifically, we are proposing to: (1) Increase
the wage index for hospitals with a wage index value below the 25th
percentile wage index, where the increase in the wage index value for
these hospitals would be equal to half the difference between the
otherwise applicable final wage index value for a year for that
hospital and the 25th percentile wage index value for that year across
all hospitals; (2) decrease the wage index for hospitals with a wage
index value above the 75th percentile wage index, where the wage index
value for these hospitals would be decreased by a percentage of the
difference between the otherwise applicable final wage index value for
a year for that hospital and the 75th percentile wage index value for
that year across all hospitals in order to offset the estimated
aggregate increase in payments for a fiscal year under the proposal
under (1) above; (3) calculate the rural floor without including the
wage data of urban hospitals that have reclassified as rural under
section 1886(d)(8)(E) of the Act (as
[[Page 19607]]
implemented in Sec. 412.103) and remove urban to rural
reclassifications under Sec. 412.103 from the calculation of ``the
wage index for rural areas in the State in which the county is
located'' in applying the provisions of section 1886(d)(8)(C)(iii) of
the Act; and (4) place a 5-percent cap in FY 2020 on any decrease in a
hospital's wage index from the hospital's final wage index in FY 2019.
These proposals directly affect the GAF because it is calculated based
on the hospital wage index value that is applicable to the hospital
under 42 CFR part 412, subpart D (Basic Methodology for Determining
Prospective Payment Federal Rates for Inpatient Operating Costs). Given
these proposed changes would affect the GAFs, we are proposing to
augment our historical methodology for computing the budget neutrality
factor for proposed changes in the GAFs. Historically, we determine a
budget neutrality factor for changes in the GAF that accounts for
changes resulting from the update to the wage data, wage index
reclassifications and redesignations, and the rural floor in a single
step. (We note that this historical GAF budget neutrality factor does
not reflect changes in the frontier State adjustment or the out-
migration adjustment because these statutory adjustments to the wage
index are not budget neutral.)
In light of these proposed changes to the wage index, which
directly affect the GAF, we are proposing to compute a budget
neutrality factor for proposed changes in the GAFs in two steps. Under
our proposed 2-step methodology, we first calculate a factor to ensure
budget neutrality for proposed changes to the FY 2020 GAFs due to the
update to the wage data, wage index reclassifications and
redesignations, including our proposal to remove urban to rural
reclassifications under Sec. 412.103 from the calculation of ``the
wage index for rural areas in the State in which the county is
located'' in applying the provisions of section 1886(d)(8)(C)(iii) of
the Act, and the rural floor, including our proposal to calculate the
rural floor without including the wage data of urban hospitals that
have reclassified as rural under Sec. 412.103, consistent with our
historical GAF budget neutrality factor methodology. In the second
step, we would calculate a factor to ensure budget neutrality for
proposed changes to the FY 2020 GAFs due to our proposal to increase
the wage index for hospitals with a wage index value below the 25th
percentile wage index, decrease the wage index for hospitals with a
wage index value above the 75th percentile wage index, and place a 5-
percent cap on any decrease in a hospital's wage index from the
hospital's final wage index in FY 2019. In this section, we refer to
these three proposals as the proposed lowest quartile hospital wage
index adjustment, the proposed highest quartile hospital wage index
adjustment, and the proposed 5-percent cap on wage index decreases. We
discuss our proposed 2-step calculation of the GAF budget neutrality
factors below.
To determine the GAF budget neutrality factors for FY 2020, we
first compared estimated aggregate capital Federal rate payments based
on the FY 2019 MS-DRG classifications and relative weights and the FY
2019 GAFs to estimated aggregate capital Federal rate payments based on
the FY 2019 MS-DRG classifications and relative weights and the FY 2020
GAFs without incorporating the effects on the GAFs of our proposed
lowest quartile hospital wage index adjustment, the proposed highest
quartile hospital wage index adjustment, and the proposed 5-percent cap
on wage index decreases. To achieve budget neutrality for these
proposed changes in the GAFs, we calculated an incremental GAF budget
neutrality adjustment factor of 0.9999 for FY 2020. Next, we compared
estimated aggregate capital Federal rate payments based on the FY 2020
GAFs with and without incorporating the effects on the GAFs of the
proposed lowest quartile hospital wage index adjustment, the proposed
highest quartile hospital wage index adjustment, and the proposed 5-
percent cap on wage index decreases. For this calculation, estimated
aggregate capital Federal rate payments were calculated using the
proposed FY 2020 MS-DRG classifications and relative weights, and the
proposed FY 2020 GAFs (both with and without incorporating the effects
on the GAF of our proposed lowest quartile hospital wage index
adjustment, the proposed highest quartile hospital wage index
adjustment, and the proposed 5-percent cap on wage index decreases).
(We note that, for this calculation, the GAFs included the out-
migration and frontier State adjustments.) To achieve budget neutrality
for the effects of the proposed lowest quartile hospital wage index
adjustment, the proposed highest quartile hospital wage index
adjustment, and the proposed 5-percent cap on wage index decreases on
the FY 2020 GAFs, we calculated an incremental GAF budget neutrality
adjustment factor of 0.9977. Therefore, to achieve budget neutrality
for the proposed changes in the GAFs, based on the proposed
calculations described above, we are proposing to apply an incremental
budget neutrality adjustment factor of 0.9976 (0.9999 x 0.9977) for FY
2020 to the previous cumulative FY 2019 adjustment factor.
We also compared estimated aggregate capital Federal rate payments
based on the FY 2019 MS-DRG classifications and relative weights and
the proposed FY 2020 GAFs to estimated aggregate capital Federal rate
payments based on the cumulative effects of the proposed FY 2020 MS-DRG
classifications and relative weights and the proposed FY 2020 GAFs
without the effects of the proposed lowest quartile hospital wage index
adjustment, the proposed highest quartile hospital wage index
adjustment, and the proposed 5-percent cap on wage index decreases. The
proposed incremental adjustment factor for DRG classifications and
changes in relative weights is 0.99998. The proposed incremental
adjustment factor for MS-DRG classifications and changes in relative
weights (0.99998) and for changes in the GAFs through FY 2020 (0.9976)
is 0.9976 (0.99998 x 0.9976). We note that all the values are
calculated with unrounded numbers.
The GAF/DRG budget neutrality adjustment factors are built
permanently into the capital rates; that is, they are applied
cumulatively in determining the capital Federal rate. This follows the
requirement under Sec. 412.308(c)(4)(ii) that estimated aggregate
payments each year be no more or less than they would have been in the
absence of the annual DRG reclassification and recalibration and
changes in the GAFs.
The methodology used to determine the recalibration and geographic
adjustment factor (GAF/DRG) budget neutrality adjustment is similar to
the methodology used in establishing budget neutrality adjustments
under the IPPS for operating costs. One difference is that, under the
operating IPPS, the budget neutrality adjustments for the effect of
geographic reclassifications are determined separately from the effects
of other changes in the hospital wage index and the MS-DRG relative
weights. Under the capital IPPS, there is a single GAF/DRG budget
neutrality adjustment factor for changes in the GAF (including
geographic reclassification and the proposed lowest quartile hospital
wage index adjustment, the proposed highest quartile hospital wage
index adjustment, and the proposed 5-percent cap on wage index
decreases described above) and the MS-DRG relative weights. In
addition, there is no adjustment for the effects that geographic
reclassification or the proposed lowest quartile hospital wage
[[Page 19608]]
index adjustment and the proposed 5-percent cap on wage index decreases
described above have on the other payment parameters, such as the
payments for DSH or IME.
The proposed incremental GAF/DRG adjustment factor of 0.9976 (the
product of the proposed incremental GAF budget neutrality adjustment
factor of 0.9976 and the proposed incremental DRG budget neutrality
adjustment factor of 0.99998) accounts for the MS-DRG reclassifications
and recalibration and for changes in the GAFs. As noted above, it also
incorporates the effects on the GAFs of FY 2020 geographic
reclassification decisions made by the MGCRB compared to FY 2019
decisions and the proposed lowest quartile hospital wage index
adjustment, the proposed highest quartile hospital wage index
adjustment, and the proposed 5-percent cap on wage index decreases
described above. However, it does not account for changes in payments
due to changes in the DSH and IME adjustment factors.
4. Proposed Capital Federal Rate for FY 2020
For FY 2019, we established a capital Federal rate of $459.41 (83
FR 41729, as corrected at 83 FR 49845). We are proposing to establish
an update of 1.5 percent in determining the FY 2020 capital Federal
rate for all hospitals. As a result of this proposed update and the
proposed budget neutrality factors discussed earlier, we are proposing
to establish a national capital Federal rate of $463.81 for FY 2020.
The proposed national capital Federal rate for FY 2020 was calculated
as follows:
The proposed FY 2020 update factor is 1.015; that is, the
proposed update is 1.5 percent.
The proposed FY 2020 budget neutrality adjustment factor
that is applied to the capital Federal rate for changes in the MS-DRG
classifications and relative weights and changes in the GAFs is 0.9976.
The proposed FY 2020 outlier adjustment factor is 0.9466.
We are providing the following chart that shows how each of the
proposed factors and adjustments for FY 2020 affects the computation of
the proposed FY 2020 national capital Federal rate in comparison to the
FY 2019 national capital Federal rate. The proposed FY 2020 update
factor has the effect of increasing the capital Federal rate by 1.5
percent compared to the FY 2019 capital Federal rate. The proposed GAF/
DRG budget neutrality adjustment factor has the effect of decreasing
the capital Federal rate by 0.24 percent. The proposed FY 2020 outlier
adjustment factor has the effect of decreasing the capital Federal rate
by 0.29 percent compared to the FY 2019 capital Federal rate. The
combined effect of all the proposed changes would increase the national
capital Federal rate by approximately 0.96 percent, compared to the FY
2019 national capital Federal rate.
Comparison of Factors and Adjustments: FY 2019 Capital Federal Rate and the Proposed FY 2020 Capital Federal
Rate
----------------------------------------------------------------------------------------------------------------
Proposed FY Proposed Proposed
FY 2019 2020 change percent change
----------------------------------------------------------------------------------------------------------------
Update Factor \1\............................... 1.0140 1.0150 1.015 1.50
GAF/DRG Adjustment Factor \1\................... 0.9969 0.9976 0.9976 -0.24
Outlier Adjustment Factor \2\................... 0.9494 0.9466 0.9971 -0.29
Capital Federal Rate............................ $459.41 $463.81 1.0096 \3\ 0.96
----------------------------------------------------------------------------------------------------------------
\1\ The proposed update factor and the GAF/DRG budget neutrality adjustment factors are built permanently into
the capital Federal rates. Thus, for example, the proposed incremental change from FY 2019 to FY 2020
resulting from the application of the proposed 0.9976 GAF/DRG budget neutrality adjustment factor for FY 2020
is a net change of 0.9976 (or -0.24 percent).
\2\ The outlier reduction factor is not built permanently into the capital Federal rate; that is, the factor is
not applied cumulatively in determining the capital Federal rate. Thus, for example, the proposed net change
resulting from the application of the proposed FY 2020 outlier adjustment factor is 0.9466/0.9494 or 0.9971
(or -0.29 percent) (calculation performed on unrounded numbers).
\3\ Percent change may not sum due to rounding.
B. Calculation of the Proposed Inpatient Capital-Related Prospective
Payments for FY 2020
For purposes of calculating payments for each discharge during FY
2020, the capital Federal rate is adjusted as follows: (Standard
Federal Rate) x (DRG Weight) x (GAF) x (COLA for hospitals located in
Alaska and Hawaii) x (1 + DSH Adjustment Factor + IME Adjustment
Factor, if applicable). The result is the adjusted capital Federal
rate.
Hospitals also may receive outlier payments for those cases that
qualify under the thresholds established for each fiscal year. Section
412.312(c) provides for a single set of thresholds to identify outlier
cases for both inpatient operating and inpatient capital-related
payments. The proposed outlier thresholds for FY 2020 are in section
II.A. of this Addendum. For FY 2020, a case will qualify as a cost
outlier if the cost for the case plus the (operating) IME and DSH
payments (including both the empirically justified Medicare DSH payment
and the estimated uncompensated care payment, as discussed in section
II.A.4.h.(1) of this Addendum) is greater than the prospective payment
rate for the MS-DRG plus the proposed fixed-loss amount of $26,994.
Currently, as provided under Sec. 412.304(c)(2), we pay a new
hospital 85 percent of its reasonable costs during the first 2 years of
operation, unless it elects to receive payment based on 100 percent of
the capital Federal rate. Effective with the third year of operation,
we pay the hospital based on 100 percent of the capital Federal rate
(that is, the same methodology used to pay all other hospitals subject
to the capital PPS).
C. Capital Input Price Index
1. Background
Like the operating input price index, the capital input price index
(CIPI) is a fixed-weight price index that measures the price changes
associated with capital costs during a given year. The CIPI differs
from the operating input price index in one important aspect--the CIPI
reflects the vintage nature of capital, which is the acquisition and
use of capital over time. Capital expenses in any given year are
determined by the stock of capital in that year (that is, capital that
remains on hand from all current and prior capital acquisitions). An
index measuring capital price changes needs to reflect this vintage
nature of capital. Therefore, the CIPI
[[Page 19609]]
was developed to capture the vintage nature of capital by using a
weighted-average of past capital purchase prices up to and including
the current year.
We periodically update the base year for the operating and capital
input price indexes to reflect the changing composition of inputs for
operating and capital expenses. For this FY 2020 IPPS/LTCH PPS proposed
rule, we are proposing to use the rebased and revised IPPS operating
and capital market baskets that reflect a 2014 base year. For a
complete discussion of this rebasing, we refer readers to section IV.
of the preamble of the FY 2018 IPPS/LTCH PPS final rule (82 FR 38170).
2. Forecast of the CIPI for FY 2020
Based on IHS Global Inc.'s fourth quarter 2018 forecast, for this
proposed rule, we are forecasting the 2014-based CIPI to increase 1.5
percent in FY 2020. This reflects a projected 1.7 percent increase in
vintage-weighted depreciation prices (building and fixed equipment, and
movable equipment), and a projected 3.6 percent increase in other
capital expense prices in FY 2020, partially offset by a projected 0.6
percent decline in vintage-weighted interest expense prices in FY 2020.
The weighted average of these three factors produces the forecasted 1.5
percent increase for the 2014-based CIPI in FY 2020.
IV. Proposed Changes to Payment Rates for Excluded Hospitals: Rate-of-
Increase Percentages for FY 2020
Payments for services furnished in children's hospitals, 11 cancer
hospitals, and hospitals located outside the 50 States, the District of
Columbia and Puerto Rico (that is, short-term acute care hospitals
located in the U.S. Virgin Islands, Guam, the Northern Mariana Islands,
and American Samoa) that are excluded from the IPPS are made on the
basis of reasonable costs based on the hospital's own historical cost
experience, subject to a rate-of-increase ceiling. A per discharge
limit (the target amount, as defined in Sec. 413.40(a) of the
regulations) is set for each hospital, based on the hospital's own cost
experience in its base year, and updated annually by a rate-of-increase
percentage specified in Sec. 413.40(c)(3). In addition, as specified
in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38536), effective for
cost reporting periods beginning during FY 2018, the annual update to
the target amount for extended neoplastic disease care hospitals
(hospitals described in Sec. 412.22(i) of the regulations) also is the
rate-of-increase percentage specified in Sec. 413.40(c)(3). (We note
that, in accordance with Sec. 403.752(a), religious nonmedical health
care institutions (RNHCIs) are also subject to the rate-of-increase
limits established under Sec. 413.40 of the regulations.)
The FY 2020 rate-of-increase percentage for updating the target
amounts for the 11 cancer hospitals, children's hospitals, the short-
term acute care hospitals located in the U.S. Virgin Islands, Guam, the
Northern Mariana Islands, and American Samoa, RNHCIs, and extended
neoplastic disease care hospitals is the estimated percentage increase
in the IPPS operating market basket for FY 2020, in accordance with
applicable regulations at Sec. 413.40. Based on IGI's 2018 fourth
quarter forecast, we estimated that the 2014-based IPPS operating
market basket update for FY 2020 is 3.2 percent (that is, the estimate
of the market basket rate-of-increase). However, we are proposing that
if more recent data become available for the final rule, we would use
them to calculate the IPPS operating market basket update for FY 2020.
Therefore, for children's hospitals, the 11 cancer hospitals, hospitals
located outside the 50 States, the District of Columbia, and Puerto
Rico (that is, short-term acute care hospitals located in the U.S.
Virgin Islands, Guam, the Northern Mariana Islands, and American
Samoa), extended neoplastic disease care hospitals, and RNHCIs, the FY
2020 rate-of-increase percentage that would be applied to the FY 2019
target amounts, in order to determine the FY 2020 target amounts is 3.2
percent.
The IRF PPS, the IPF PPS, and the LTCH PPS are updated annually. We
refer readers to section VII. of the preamble of this proposed rule and
section V. of the Addendum to this proposed rule for the proposed
updated changes to the Federal payment rates for LTCHs under the LTCH
PPS for FY 2020. The annual updates for the IRF PPS and the IPF PPS are
issued by the agency in separate Federal Register documents.
V. Proposed Changes to the Payment Rates for the LTCH PPS for FY 2020
A. Proposed LTCH PPS Standard Federal Payment Rate for FY 2020
1. Overview
In section VII. of the preamble of this proposed rule, we discuss
our proposed annual updates to the payment rates, factors, and specific
policies under the LTCH PPS for FY 2020.
Under Sec. 412.523(c)(3) of the regulations, for LTCH PPS FYs 2012
through 2019, we updated the standard Federal payment rate by the most
recent estimate of the LTCH PPS market basket at that time, including
additional statutory adjustments required by sections 1886(m)(3)
(citing sections 1886(b)(3)(B)(xi)(II), and 1886(m)(4) of the Act as
set forth in the regulations at Sec. Sec. 412.523(c)(3)(viii) through
(c)(3)(xv)). (For a summary of the payment rate development prior to FY
2012, we refer readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR
38310 through 38312) and references therein.)
Section 1886(m)(3)(A) specifies that, for rate year 2020 and each
subsequent rate year, any annual update to the standard Federal payment
rate shall be reduced by the productivity adjustment described in
section 1886(b)(3)(B)(xi)(II) of the Act (which we refer to as ``the
multifactor productivity (MFP) adjustment'') as discussed in section
VII.D.2. of the preamble of this proposed rule.
This section of the Act further provides that the application of
section 1886(m)(3)(B) of the Act may result in the annual update being
less than zero for a rate year, and may result in payment rates for a
rate year being less than such payment rates for the preceding rate
year. (As noted in section VII.D.2.a. of the preamble of this proposed
rule, the annual update to the LTCH PPS occurs on October 1 and we have
adopted the term ``fiscal year'' (FY) rather than ``rate year'' (RY)
under the LTCH PPS beginning October 1, 2010. Therefore, for purposes
of clarity, when discussing the annual update for the LTCH PPS,
including the provisions of the Affordable Care Act, we use the term
``fiscal year'' rather than ``rate year'' for 2011 and subsequent
years.)
For LTCHs that fail to submit the required quality reporting data
in accordance with the LTCH QRP, the annual update is reduced by 2.0
percentage points as required by section 1886(m)(5) of the Act.
2. Development of the Proposed FY 2020 LTCH PPS Standard Federal
Payment Rate
Consistent with our historical practice, for FY 2020, we are
proposing to apply the annual update to the LTCH PPS standard Federal
payment rate from the previous year. Furthermore, in determining the
proposed LTCH PPS standard Federal payment rate for FY 2020, we also
are proposing to make certain regulatory adjustments, consistent with
past practices. Specifically, in determining the proposed FY 2020 LTCH
PPS standard Federal payment rate, we are proposing to apply a budget
neutrality adjustment factor for the changes related to the area wage
level adjustment (that is, changes
[[Page 19610]]
to the wage data and labor-related share) in accordance with Sec.
412.523(d)(4) and a temporary budget neutrality adjustment factor
(applied to LTCH PPS standard Federal payment rate cases only) for the
cost of the elimination of the 25-percent threshold policy for FY 2020
(discussed in VII.D. of the preamble of this proposed rule).
In this FY 2020 IPPS/LTCH PPS proposed rule, we are proposing to
establish an annual update to the LTCH PPS standard Federal payment
rate of 2.7 percent. Accordingly, as reflected in proposed Sec.
412.523(c)(3)(xvi), we are proposing to apply a factor of 1.027 to the
FY 2019 LTCH PPS standard Federal payment rate of $41,558.68 to
determine the proposed FY 2020 LTCH PPS standard Federal payment rate.
Also, as reflected in proposed Sec. 412.523(c)(3)(xvi), applied in
conjunction with the provisions of Sec. 412.523(c)(4), we are
proposing to establish an annual update to the LTCH PPS standard
Federal payment rate of 0.7 percent (that is, a proposed update factor
of 1.007) for FY 2020 for LTCHs that fail to submit the required
quality reporting data for FY 2020 as required under the LTCH QRP.
Additionally, we are proposing to apply a temporary budget neutrality
adjustment factor of 0.990741 to the LTCH PPS standard Federal payment
rate for the cost of the elimination of the 25-percent threshold policy
for FY 2020 after removing the temporary budget neutrality adjustment
factor of 0.990884 that was applied to the LTCH PPS standard Federal
payment rate for the cost of the elimination of the 25-percent
threshold policy for FY 2019 (or a temporary, one-time factor of
0.999856 as discussed in VII.D. of the preamble of this proposed rule).
Consistent with Sec. 412.523(d)(4), we also are proposing to apply an
area wage level budget neutrality factor to the proposed FY 2020 LTCH
PPS standard Federal payment rate of 1.0064747, based on the best
available data at this time, to ensure that any changes to the area
wage level adjustment (that is, the proposed annual update of the wage
index values and labor-related share) would not result in any change
(increase or decrease) in estimated aggregate LTCH PPS standard Federal
rate payments. Accordingly, we are proposing to establish an LTCH PPS
standard Federal payment rate of $42,950.91 (calculated as $41,558.68 x
0.999856 x 1.027 x 1.0064747) for FY 2020 (calculations performed on
rounded numbers). For LTCHs that fail to submit quality reporting data
for FY 2020, in accordance with the requirements of the LTCH QRP under
section 1866(m)(5) of the Act, we are proposing to establish an LTCH
PPS standard Federal payment rate of $42,114.47 (calculated as
$41,558.68 x 0.999856 x 1.007 x 1.0064747) (calculations performed on
rounded numbers) for FY 2020.
B. Proposed Adjustment for Area Wage Levels Under the LTCH PPS for FY
2020
1. Background
Under the authority of section 123 of the BBRA, as amended by
section 307(b) of the BIPA, we established an adjustment to the LTCH
PPS standard Federal payment rate to account for differences in LTCH
area wage levels under Sec. 412.525(c). The labor-related share of the
LTCH PPS standard Federal payment rate is adjusted to account for
geographic differences in area wage levels by applying the applicable
LTCH PPS wage index. The applicable LTCH PPS wage index is computed
using wage data from inpatient acute care hospitals without regard to
reclassification under section 1886(d)(8) or section 1886(d)(10) of the
Act.
2. Proposed Geographic Classifications (Labor Market Areas) for the
LTCH PPS Standard Federal Payment Rate
In adjusting for the differences in area wage levels under the LTCH
PPS, the labor-related portion of an LTCH's Federal prospective payment
is adjusted by using an appropriate area wage index based on the
geographic classification (labor market area) in which the LTCH is
located. Specifically, the application of the LTCH PPS area wage level
adjustment under existing Sec. 412.525(c) is made based on the
location of the LTCH--either in an ``urban area,'' or a ``rural area,''
as defined in Sec. 412.503. Under Sec. 412.503, an ``urban area'' is
defined as a Metropolitan Statistical Area (MSA) (which includes a
Metropolitan division, where applicable), as defined by the Executive
OMB and a ``rural area'' is defined as any area outside of an urban
area (75 FR 37246).
The CBSA-based geographic classifications (labor market area
definitions) currently used under the LTCH PPS, effective for
discharges occurring on or after October 1, 2014, are based on the OMB
labor market area delineations based on the 2010 Decennial Census data.
The current statistical areas (which were implemented beginning with FY
2015) are based on revised OMB delineations issued on February 28,
2013, in OMB Bulletin No. 13-01. We adopted these labor market area
delineations because they are based on the best available data that
reflect the local economies and area wage levels of the hospitals that
are currently located in these geographic areas. We also believe that
these OMB delineations will ensure that the LTCH PPS area wage level
adjustment most appropriately accounts for and reflects the relative
hospital wage levels in the geographic area of the hospital as compared
to the national average hospital wage level. We noted that this policy
was consistent with the IPPS policy adopted in FY 2015 under Sec.
412.64(b)(1)(ii)(D) of the regulations (79 FR 49951 through 49963).
(For additional information on the CBSA-based labor market area
(geographic classification) delineations currently used under the LTCH
PPS and the history of the labor market area definitions used under the
LTCH PPS, we refer readers to the FY 2015 IPPS/LTCH PPS final rule (79
FR 50180 through 50185).)
In general, it is our historical practice to update the CBSA-based
labor market area delineations annually based on the most recent
updates issued by OMB. Generally, OMB issues major revisions to
statistical areas every 10 years, based on the results of the decennial
census. However, OMB occasionally issues minor updates and revisions to
statistical areas in the years between the decennial censuses. OMB
Bulletin No. 17-01, issued August 15, 2017, establishes the current
delineations for the Nation's statistical areas, and the corresponding
changes to the CBSA-based labor market areas were adopted in the FY
2019 IPPS/LTCH PPS final rule (83 FR 41731). A copy of this bulletin
may be obtained on the website at: https://www.whitehouse.gov/sites/whitehouse.gov/files/omb/bulletins/2017/b-17-01.pdf.
We believe the current CBSA-based labor market area delineations as
established in OMB Bulletin 17-01 and adopted in the FY 2019 IPPS/LTCH
PPS final rule (83 FR 41731) will ensure that the LTCH PPS area wage
level adjustment most appropriately accounts for and reflects the
relative hospital wage levels in the geographic area of the hospital as
compared to the national average hospital wage level based on the best
available data that reflect the local economies and area wage levels of
the hospitals that are currently located in these geographic areas (81
FR 57298). Therefore, we are proposing to continue to use the CSBA-
based labor market area delineations adopted under the LTCH PPS,
effective October 1, 2019 (as adopted in the FY 2019 IPPS/LTCH PPS
final rule (83 FR 41731)). Accordingly, the proposed FY 2020 LTCH PPS
wage index values in Tables 12A and 12B
[[Page 19611]]
listed in section VI. of the Addendum to this proposed rule (which are
available via the internet on the CMS website) reflect the CBSA-based
labor market area delineations as described above. We noted that, as
discussed in section III.A.2. of the preamble of this proposed rule,
these CBSA-based delineations also are being proposed to be used under
the IPPS.
3. Proposed Labor-Related Share for the LTCH PPS Standard Federal
Payment Rate
Under the payment adjustment for the differences in area wage
levels under Sec. 412.525(c), the labor-related share of an LTCH's
standard Federal payment rate payment is adjusted by the applicable
wage index for the labor market area in which the LTCH is located. The
LTCH PPS labor-related share currently represents the sum of the labor-
related portion of operating costs and a labor-related portion of
capital costs using the applicable LTCH PPS market basket. Additional
background information on the historical development of the labor-
related share under the LTCH PPS can be found in the RY 2007 LTCH PPS
final rule (71 FR 27810 through 27817 and 27829 through 27830) and the
FY 2012 IPPS/LTCH PPS final rule (76 FR 51766 through 51769 and 51808).
For FY 2013, we rebased and revised the market basket used under
the LTCH PPS by adopting a 2009-based LTCH-specific market basket. In
addition, beginning in FY 2013, we determined the labor-related share
annually as the sum of the relative importance of each labor-related
cost category of the 2009-based LTCH-specific market basket for the
respective fiscal year based on the best available data. (For more
details, we refer readers to the FY 2013 IPPS/LTCH PPS final rule (77
FR 53477 through 53479).) As noted previously, we rebased and revised
the 2009-based LTCH-specific market basket to reflect a 2013 base year.
In conjunction with that policy, as discussed in section VII.D. of the
preamble of this FY 2020 IPPS/LTCH PPS proposed rule, we are proposing
to establish that the LTCH PPS labor-related share for FY 2020 is the
sum of the FY 2020 relative importance of each labor-related cost
category in the 2013-based LTCH market basket using the most recent
available data.
Specifically, we are proposing to establish that the labor-related
share for FY 2020 includes the sum of the labor-related portion of
operating costs from the 2013-based LTCH market basket (that is, the
sum of the FY 2020 relative importance share of Wages and Salaries;
Employee Benefits; Professional Fees: Labor-Related; Administrative and
Facilities Support Services; Installation, Maintenance, and Repair
Services; All Other: Labor-related Services) and a portion of the
relative importance of the Capital-Related cost weight from the 2013-
based LTCH PPS market basket. Based on IGI's fourth quarter 2018
forecast of the 2013-based LTCH market basket, we are proposing to
establish a labor-related share under the LTCH PPS for FY 2020 of 66.0
percent. (We note that a proposed labor-related share of 66.0 percent
is the same as the labor-related share for FY 2019, and although the
relative importance of some components of the market basket have
changed, the proposed labor-related share remains at 66.0 percent when
aggregating these components and rounding to one decimal.) This
proposed labor-related share is determined using the same methodology
as employed in calculating all previous LTCH PPS labor-related shares.
Consistent with our historical practice, we also are proposing that if
more recent data became available, we would use that data, if
appropriate, to determine the final FY 2020 labor-related share in the
final rule.
The proposed labor-related share for FY 2020 is the sum of the FY
2020 relative importance of each labor-related cost category, and would
reflect the different rates of price change for these cost categories
between the base year (2013) and FY 2020. The sum of the relative
importance for FY 2020 for operating costs (Wages and Salaries;
Employee Benefits; Professional Fees: Labor-Related; Administrative and
Facilities Support Services; Installation, Maintenance, and Repair
Services; All Other: Labor-Related Services) is 61.9 percent. The
portion of capital-related costs that is influenced by the local labor
market is estimated to be 46 percent (the same percentage applied to
the 2009-based LTCH-specific market basket). Because the relative
importance for capital-related costs under our policies is 9.0 percent
of the 2013-based LTCH market basket in FY 2020, we are proposing to
take 46 percent of 9.0 percent to determine the labor-related share of
capital-related costs for FY 2020 (0.46 x 9.0). The result is 4.1
percent, which we added to 61.9 percent for the operating cost amount
to determine the total proposed labor-related share for FY 2020.
Therefore, we are proposing to establish that the labor-related share
under the LTCH PPS for FY 2020 is 66.0 percent.
4. Proposed Wage Index for FY 2020 for the LTCH PPS Standard Federal
Payment Rate
Historically, we have established LTCH PPS area wage index values
calculated from acute care IPPS hospital wage data without taking into
account geographic reclassification under sections 1886(d)(8) and
1886(d)(10) of the Act (67 FR 56019). The area wage level adjustment
established under the LTCH PPS is based on an LTCH's actual location
without regard to the ``urban'' or ``rural'' designation of any related
or affiliated provider.
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41732), we
calculated the FY 2019 LTCH PPS area wage index values using the same
data used for the FY 2019 acute care hospital IPPS (that is, data from
cost reporting periods beginning during FY 2015), without taking into
account geographic reclassification under sections 1886(d)(8) and
1886(d)(10) of the Act, as these were the most recent complete data
available at that time. In that same final rule, we indicated that we
computed the FY 2019 LTCH PPS area wage index values, consistent with
the urban and rural geographic classifications (labor market areas)
that were in place at that time and consistent with the pre-
reclassified IPPS wage index policy (that is, our historical policy of
not taking into account IPPS geographic reclassifications in
determining payments under the LTCH PPS). As with the IPPS wage index,
wage data for multicampus hospitals with campuses located in different
labor market areas (CBSAs) are apportioned to each CBSA where the
campus (or campuses) are located. We also continued to use our existing
policy for determining area wage index values for areas where there are
no IPPS wage data.
Consistent with our historical methodology, as discussed in this FY
2020 IPPS/LTCH PPS proposed rule, to determine the applicable area wage
index values for the FY 2020 LTCH PPS standard Federal payment rate,
under the broad authority of section 123 of the BBRA, as amended by
section 307(b) of the BIPA, we are proposing to use wage data collected
from cost reports submitted by IPPS hospitals for cost reporting
periods beginning during FY 2016, without taking into account
geographic reclassification under sections 1886(d)(8) and 1886(d)(10)
of the Act because these data are the most recent complete data
available. We also note that these are the same data we are proposing
to use to compute the proposed FY 2020 acute care hospital
[[Page 19612]]
inpatient wage index, as discussed in section III. of the preamble of
this proposed rule. We are proposing to compute the proposed FY 2020
LTCH PPS standard Federal payment rate area wage index values
consistent with the ``urban'' and ``rural'' geographic classifications
(that is, labor market area delineations, including the proposed
updates, as previously discussed in section V.B. of this Addendum) and
our historical policy of not taking into account IPPS geographic
reclassifications under sections 1886(d)(8) and 1886(d)(10) of the Act
in determining payments under the LTCH PPS. We also are proposing to
continue to apportion the wage data for multicampus hospitals with
campuses located in different labor market areas to each CBSA where the
campus or campuses are located, consistent with the IPPS policy.
Lastly, consistent with our existing methodology for determining the
LTCH PPS wage index values, for FY 2020, we are proposing to continue
to use our existing policy for determining area wage index values for
areas where there are no IPPS wage data. Under our existing
methodology, the LTCH PPS wage index value for urban CBSAs with no IPPS
wage data would be determined by using an average of all of the urban
areas within the State, and the LTCH PPS wage index value for rural
areas with no IPPS wage data would be determined by using the
unweighted average of the wage indices from all of the CBSAs that are
contiguous to the rural counties of the State.
Based on the FY 2016 IPPS wage data that we are proposing to use to
determine the proposed FY 2020 LTCH PPS standard Federal payment rate
area wage index values in this proposed rule, there are no IPPS wage
data for the urban area of Hinesville, GA (CBSA 25980). Consistent with
the methodology discussed above, we calculated the proposed FY 2020
wage index value for CBSA 25980 as the average of the wage index values
for all of the other urban areas within the State of Georgia (that is,
CBSAs 10500, 12020, 12060, 12260, 15260, 16860, 17980, 19140, 23580,
31420, 40660, 42340, 46660 and 47580), as shown in Table 12A, which is
listed in section VI. of the Addendum to this proposed rule and
available via the internet on the CMS website. Likewise, based on this
same FY 2016 IPPS wage data that we are proposing to use to determine
the proposed FY 2020 LTCH PPS standard Federal payment rate area wage
index values in this proposed rule, there are no IPPS wage data for the
urban area of Carson City, NV (CBSA 16810). Consistent with the
methodology discussed above, we calculated the proposed FY 2020 wage
index value for CBSA 16810 as the average of the wage index values for
all of the other urban areas within the State of Nevada (that is, CBSAs
29820 and 39900, as shown in Table 12A, which is listed in section VI.
of the Addendum to this proposed rule and available via the internet on
the CMS website). We note that, as IPPS wage data are dynamic, it is
possible that urban areas without IPPS wage data will vary in the
future.
Based on the FY 2016 IPPS wage data that we are proposing to use to
determine the proposed FY 2020 LTCH PPS standard Federal payment rate
area wage index values in this proposed rule, there are no rural areas
without IPPS hospital wage data. Therefore, it is not necessary to use
our established methodology to calculate a proposed LTCH PPS standard
Federal payment rate wage index value for proposed rural areas with no
IPPS wage data for FY 2020. We note that, as IPPS wage data are
dynamic, it is possible that the number of rural areas without IPPS
wage data will vary in the future. The proposed FY 2020 LTCH PPS
standard Federal payment rate wage index values that would be
applicable for LTCH PPS standard Federal payment rate discharges
occurring on or after October 1, 2019, through September 30, 2020, are
presented in Table 12A (for urban areas) and Table 12B (for rural
areas), which are listed in section VI. of the Addendum to this
proposed rule and available via the internet on the CMS website.
Historically, we have calculated the LTCH PPS wage index values
using unadjusted wage index values from the IPPS hospitals.
Stakeholders have frequently commented on certain aspects of the wage
index values and their impact on payments. In this proposed rule, we
are soliciting public comments on concerns that stakeholders may have
regarding the wage index used to adjust LTCH PPS payments and
suggestions for possible updates and improvements to the geographic
adjustment of LTCH PPS payments.
5. Proposed Budget Neutrality Adjustment for Changes to the LTCH PPS
Standard Federal Payment Rate Area Wage Level Adjustment
Historically, the LTCH PPS wage index and labor-related share are
updated annually based on the latest available data. Under Sec.
412.525(c)(2), any changes to the area wage index values or labor-
related share are to be made in a budget neutral manner such that
estimated aggregate LTCH PPS payments are unaffected; that is, will be
neither greater than nor less than estimated aggregate LTCH PPS
payments without such changes to the area wage level adjustment. Under
this policy, we determine an area wage level adjustment budget
neutrality factor that will be applied to the standard Federal payment
rate to ensure that any changes to the area wage level adjustments are
budget neutral such that any changes to the area wage index values or
labor-related share would not result in any change (increase or
decrease) in estimated aggregate LTCH PPS payments. Accordingly, under
Sec. 412.523(d)(4), we apply an area wage level adjustment budget
neutrality factor in determining the standard Federal payment rate, and
we also established a methodology for calculating an area wage level
adjustment budget neutrality factor. (For additional information on the
establishment of our budget neutrality policy for changes to the area
wage level adjustment, we refer readers to the FY 2012 IPPS/LTCH PPS
final rule (76 FR 51771 through 51773 and 51809).)
In this FY 2020 IPPS/LTCH PPS proposed rule, for FY 2020 LTCH PPS
standard Federal payment rate cases, in accordance with Sec.
412.523(d)(4), we are proposing to apply an area wage level adjustment
budget neutrality factor to adjust the LTCH PPS standard Federal
payment rate to account for the estimated effect of the proposed
adjustments or updates to the area wage level adjustment under Sec.
412.525(c)(1) on estimated aggregate LTCH PPS payments using a
methodology that is consistent with the methodology we established in
the FY 2012 IPPS/LTCH PPS final rule (76 FR 51773). Specifically, we
are proposing to determine an area wage level adjustment budget
neutrality factor that would be applied to the LTCH PPS standard
Federal payment rate under Sec. 412.523(d)(4) for FY 2020 using the
following methodology:
Step 1--We simulated estimated aggregate LTCH PPS standard Federal
payment rate payments using the FY 2019 wage index values and the FY
2019 labor-related share of 66.0 percent (as established in the FY 2019
IPPS/LTCH PPS final rule (83 FR 41732)).
Step 2--We simulated estimated aggregate LTCH PPS standard Federal
payment rate payments using the proposed FY 2020 wage index values (as
shown in Tables 12A and 12B listed in the Addendum to this proposed
rule and available via the internet on the CMS website) and the
proposed FY 2020 labor-related share of 66.0 percent
[[Page 19613]]
(based on the latest available data as previously discussed in this
Addendum).
Step 3--We calculated the ratio of these estimated total LTCH PPS
standard Federal payment rate payments by dividing the estimated total
LTCH PPS standard Federal payment rate payments using the FY 2019 area
wage level adjustments (calculated in Step 1) by the estimated total
LTCH PPS standard Federal payment rate payments using the proposed FY
2020 area wage level adjustments (calculated in Step 2) to determine
the proposed area wage level adjustment budget neutrality factor for FY
2020 LTCH PPS standard Federal payment rate payments.
Step 4--We then applied the proposed FY 2020 area wage level
adjustment budget neutrality factor from Step 3 to determine the
proposed FY 2020 LTCH PPS standard Federal payment rate after the
application of the proposed FY 2020 annual update (discussed previously
in section V.A. of this Addendum).
We note that, with the exception of cases subject to the
transitional blended payment rate provisions and certain temporary
exemptions for certain spinal cord specialty hospitals and certain
severe wound cases, under the dual rate LTCH PPS payment structure,
only LTCH PPS cases that meet the statutory criteria to be excluded
from the site neutral payment rate (that is, LTCH PPS standard Federal
payment rate cases) are paid based on the LTCH PPS standard Federal
payment rate. Because the area wage level adjustment under Sec.
412.525(c) is an adjustment to the LTCH PPS standard Federal payment
rate, we only used data from claims that would have qualified for
payment at the LTCH PPS standard Federal payment rate if such rate had
been in effect at the time of discharge to calculate the proposed FY
2020 LTCH PPS standard Federal payment rate area wage level adjustment
budget neutrality factor described above. Moreover, we note that the
estimated proposed LTCH PPS standard Federal payment rate used in the
calculations in Steps 1 through 4 above include the one-time budget
neutrality adjustment factor for the estimated cost of eliminating the
25-percent threshold policy in FY 2020, as discussed in section VII.D.
of the preamble of this proposed rule.
For this proposed rule, using the steps in the methodology
previously described, we determined a proposed FY 2020 LTCH PPS
standard Federal payment rate area wage level adjustment budget
neutrality factor of 1.0064747. Accordingly, in section V.A. of the
Addendum to this proposed rule, to determine the proposed FY 2020 LTCH
PPS standard Federal payment rate, we are proposing to apply an area
wage level adjustment budget neutrality factor of 1.0064747, in
accordance with Sec. 412.523(d)(4).
C. Proposed LTCH PPS Cost-of-Living Adjustment (COLA) for LTCHs Located
in Alaska and Hawaii
Under Sec. 412.525(b), a cost-of-living adjustment (COLA) is
provided for LTCHs located in Alaska and Hawaii to account for the
higher costs incurred in those States. Specifically, we apply a COLA to
payments to LTCHs located in Alaska and Hawaii by multiplying the
nonlabor-related portion of the standard Federal payment rate by the
applicable COLA factors established annually by CMS. Higher labor-
related costs for LTCHs located in Alaska and Hawaii are taken into
account in the adjustment for area wage levels previously described.
The methodology used to determine the COLA factors for Alaska and
Hawaii is based on a comparison of the growth in the Consumer Price
Indexes (CPIs) for Anchorage, Alaska, and Honolulu, Hawaii, relative to
the growth in the CPI for the average U.S. city as published by the
Bureau of Labor Statistics (BLS). It also includes a 25-percent cap on
the CPI-updated COLA factors. Under our current policy, we update the
COLA factors using the methodology described above every 4 years (at
the same time as the update to the labor-related share of the IPPS
market basket), and we last updated the COLA factors for Alaska and
Hawaii published by OPM for 2009 in FY 2018 (82 FR 38539 through
38540).
We continue to believe that determining updated COLA factors using
this methodology would appropriately adjust the nonlabor-related
portion of the LTCH PPS standard Federal payment rate for LTCHs located
in Alaska and Hawaii. Therefore, in this FY 2020 IPPS/LTCH PPS proposed
rule, for FY 2020, under the broad authority conferred upon the
Secretary by section 123 of the BBRA, as amended by section 307(b) of
the BIPA, to determine appropriate payment adjustments under the LTCH
PPS, we are proposing to continue to use the COLA factors based on the
2009 OPM COLA factors updated through 2016 by the comparison of the
growth in the CPIs for Anchorage, Alaska, and Honolulu, Hawaii,
relative to the growth in the CPI for the average U.S. city as
established in the FY 2018 IPPS/LTCH PPS final rule. (For additional
details on our current methodology for updating the COLA factors for
Alaska and Hawaii and for a discussion on the FY 2018 COLA factors, we
refer readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 38539
through 38540).)
Proposed Cost-of-Living Adjustment Factors for Alaska and Hawaii Under
the LTCH PPS for FY 2020
------------------------------------------------------------------------
Proposed FY
Area 2020
------------------------------------------------------------------------
Alaska:
City of Anchorage and 80-kilometer (50-mile) radius 1.25
by road............................................
City of Fairbanks and 80-kilometer (50-mile) radius 1.25
by road............................................
City of Juneau and 80-kilometer (50-mile) radius by 1.25
road...............................................
Rest of Alaska...................................... 1.25
Hawaii:
City and County of Honolulu......................... 1.25
County of Hawaii.................................... 1.21
County of Kauai..................................... 1.25
County of Maui and County of Kalawao................ 1.25
------------------------------------------------------------------------
[[Page 19614]]
D. Proposed Adjustment for LTCH PPS High Cost Outlier (HCO) Cases
1. HCO Background
From the beginning of the LTCH PPS, we have included an adjustment
to account for cases in which there are extraordinarily high costs
relative to the costs of most discharges. Under this policy, additional
payments are made based on the degree to which the estimated cost of a
case (which is calculated by multiplying the Medicare allowable covered
charge by the hospital's overall hospital CCR) exceeds a fixed-loss
amount. This policy results in greater payment accuracy under the LTCH
PPS and the Medicare program, and the LTCH sharing the financial risk
for the treatment of extraordinarily high-cost cases.
We retained the basic tenets of our HCO policy in FY 2016 when we
implemented the dual rate LTCH PPS payment structure under section 1206
of Public Law 113-67. LTCH discharges that meet the criteria for
exclusion from the site neutral payment rate (that is, LTCH PPS
standard Federal payment rate cases) are paid at the LTCH PPS standard
Federal payment rate, which includes, as applicable, HCO payments under
Sec. 412.523(e). LTCH discharges that do not meet the criteria for
exclusion are paid at the site neutral payment rate, which includes, as
applicable, HCO payments under Sec. 412.522(c)(2)(i). In the FY 2016
IPPS/LTCH PPS final rule, we established separate fixed-loss amounts
and targets for the two different LTCH PPS payment rates. Under this
bifurcated policy, the historic 8-percent HCO target was retained for
LTCH PPS standard Federal payment rate cases, with the fixed-loss
amount calculated using only data from LTCH cases that would have been
paid at the LTCH PPS standard Federal payment rate if that rate had
been in effect at the time of those discharges. For site neutral
payment rate cases, we adopted the operating IPPS HCO target (currently
5.1 percent) and set the fixed-loss amount for site neutral payment
rate cases at the value of the IPPS fixed-loss amount. Under the HCO
policy for both payment rates, an LTCH receives 80 percent of the
difference between the estimated cost of the case and the applicable
HCO threshold, which is the sum of the LTCH PPS payment for the case
and the applicable fixed-loss amount for such case.
In order to maintain budget neutrality, consistent with the budget
neutrality requirement for HCO payments to LTCH PPS standard Federal
rate payment cases, we also adopted a budget neutrality requirement for
HCO payments to site neutral payment rate cases by applying a budget
neutrality factor to the LTCH PPS payment for those site neutral
payment rate cases. (We refer readers to Sec. 412.522(c)(2)(i) of the
regulations for further details.) We note that, during the 2-year
transitional period, the site neutral payment rate HCO budget
neutrality factor did not apply to the LTCH PPS standard Federal
payment rate portion of the blended payment rate at Sec. 412.522(c)(3)
payable to site neutral payment rate cases. (For additional details on
the HCO policy adopted for site neutral payment rate cases under the
dual rate LTCH PPS payment structure, including the budget neutrality
adjustment for HCO payments to site neutral payment rate cases, we
refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR 49617
through 49623).)
2. Determining LTCH CCRs Under the LTCH PPS
a. Background
As noted above, CCRs are used to determine payments for HCO
adjustments for both payment rates under the LTCH PPS and also are used
to determine payments for site neutral payment rate cases. As noted
earlier, in determining HCO and the site neutral payment rate payments
(regardless of whether the case is also an HCO), we generally calculate
the estimated cost of the case by multiplying the LTCH's overall CCR by
the Medicare allowable charges for the case. An overall CCR is used
because the LTCH PPS uses a single prospective payment per discharge
that covers both inpatient operating and capital-related costs. The
LTCH's overall CCR is generally computed based on the sum of LTCH
operating and capital costs (as described in Section 150.24, Chapter 3,
of the Medicare Claims Processing Manual (Pub. 100-4)) as compared to
total Medicare charges (that is, the sum of its operating and capital
inpatient routine and ancillary charges), with those values determined
from either the most recently settled cost report or the most recent
tentatively settled cost report, whichever is from the latest cost
reporting period. However, in certain instances, we use an alternative
CCR, such as the statewide average CCR, a CCR that is specified by CMS,
or one that is requested by the hospital. (We refer readers to Sec.
412.525(a)(4)(iv) of the regulations for further details regarding HCO
adjustments for either LTCH PPS payment rate and Sec.
412.522(c)(1)(ii) for the site neutral payment rate.)
The LTCH's calculated CCR is then compared to the LTCH total CCR
ceiling. Under our established policy, an LTCH with a calculated CCR in
excess of the applicable maximum CCR threshold (that is, the LTCH total
CCR ceiling, which is calculated as 3 standard deviations from the
national geometric average CCR) is generally assigned the applicable
statewide CCR. This policy is premised on a belief that calculated CCRs
above the LTCH total CCR ceiling are most likely due to faulty data
reporting or entry, and CCRs based on erroneous data should not be used
to identify and make payments for outlier cases.
b. LTCH Total CCR Ceiling
Consistent with our historical practice, we are proposing to use
the most recent data available to determine the LTCH total CCR ceiling
for FY 2020 in this proposed rule. Specifically, in this proposed rule,
using our established methodology for determining the LTCH total CCR
ceiling based on IPPS total CCR data from the December 2018 update of
the Provider Specific File (PSF), which is the most recent data
available, we are proposing to establish an LTCH total CCR ceiling of
1.247 under the LTCH PPS for FY 2020 in accordance with Sec.
412.525(a)(4)(iv)(C)(2) for HCO cases under either payment rate and
Sec. 412.522(c)(1)(ii) for the site neutral payment rate. (For
additional information on our methodology for determining the LTCH
total CCR ceiling, we refer readers to the FY 2007 IPPS final rule (71
FR 48118 through 48119).)
c. LTCH Statewide Average CCRs
Our general methodology for determining the statewide average CCRs
used under the LTCH PPS is similar to our established methodology for
determining the LTCH total CCR ceiling because it is based on ``total''
IPPS CCR data. (For additional information on our methodology for
determining statewide average CCRs under the LTCH PPS, we refer readers
to the FY 2007 IPPS final rule (71 FR 48119 through 48120).) Under the
LTCH PPS HCO policy for cases paid under either payment rate at Sec.
412.525(a)(4)(iv)(C)(2), the current SSO policy at Sec.
412.529(f)(4)(iii)(B), and the site neutral payment rate at Sec.
412.522(c)(1)(ii), the MAC may use a statewide average CCR, which is
established annually by CMS, if it is unable to determine an accurate
CCR for an LTCH in one of the following circumstances: (1) New LTCHs
that have not yet submitted their first Medicare cost report (a new
LTCH is defined as an entity that has not accepted assignment of an
existing hospital's provider agreement in accordance with
[[Page 19615]]
Sec. 489.18); (2) LTCHs whose calculated CCR is in excess of the LTCH
total CCR ceiling; and (3) other LTCHs for whom data with which to
calculate a CCR are not available (for example, missing or faulty
data). (Other sources of data that the MAC may consider in determining
an LTCH's CCR include data from a different cost reporting period for
the LTCH, data from the cost reporting period preceding the period in
which the hospital began to be paid as an LTCH (that is, the period of
at least 6 months that it was paid as a short-term, acute care
hospital), or data from other comparable LTCHs, such as LTCHs in the
same chain or in the same region.)
Consistent with our historical practice of using the best available
data, in this proposed rule, using our established methodology for
determining the LTCH statewide average CCRs, based on the most recent
complete IPPS ``total CCR'' data from the December 2018 update of the
PSF, we are proposing to establish LTCH PPS statewide average total
CCRs for urban and rural hospitals that will be effective for
discharges occurring on or after October 1, 2019, through September 30,
2020, in Table 8C listed in section VI. of the Addendum to this
proposed rule (and available via the internet on the CMS website).
Consistent with our historical practice, we also are proposing that if
more recent data become available, we would use that data to determine
the LTCH PPS statewide average total CCRs for FY 2020 in the final
rule.
Under the current LTCH PPS labor market areas, all areas in
Delaware, the District of Columbia, New Jersey, and Rhode Island are
classified as urban. Therefore, there are no rural statewide average
total CCRs listed for those jurisdictions in Table 8C. This policy is
consistent with the policy that we established when we revised our
methodology for determining the applicable LTCH statewide average CCRs
in the FY 2007 IPPS final rule (71 FR 48119 through 48121) and is the
same as the policy applied under the IPPS. In addition, although
Connecticut and Nevada have areas that are designated as rural, in our
calculation of the LTCH statewide average CCRs, there was no data
available from short-term, acute care IPPS hospitals to compute a rural
statewide average CCR or there were no short-term, acute care IPPS
hospitals or LTCHs located in these areas as of December 2018.
Therefore, consistent with our existing methodology, we are proposing
to use the national average total CCR for rural IPPS hospitals for
rural Connecticut and Nevada in Table 8C. Furthermore, consistent with
our existing methodology, in determining the urban and rural statewide
average total CCRs for Maryland LTCHs paid under the LTCH PPS, we are
proposing to continue to use, as a proxy, the national average total
CCR for urban IPPS hospitals and the national average total CCR for
rural IPPS hospitals, respectively. We are using this proxy because we
believe that the CCR data in the PSF for Maryland hospitals may not be
entirely accurate (as discussed in greater detail in the FY 2007 IPPS
final rule (71 FR 48120)).
d. Reconciliation of HCO Payments
Under the HCO policy for cases paid under either payment rate at
Sec. 412.525(a)(4)(iv)(D), the payments for HCO cases are subject to
reconciliation. Specifically, any such payments are reconciled at
settlement based on the CCR that was calculated based on the cost
report coinciding with the discharge. For additional information on the
reconciliation policy, we refer readers to Sections 150.26 through
150.28 of the Medicare Claims Processing Manual (Pub. 100-4), as added
by Change Request 7192 (Transmittal 2111; December 3, 2010), and the RY
2009 LTCH PPS final rule (73 FR 26820 through 26821).
3. High-Cost Outlier Payments for LTCH PPS Standard Federal Payment
Rate Cases
a. Proposed Changes to High-Cost Outlier Payments for LTCH PPS Standard
Federal Payment Rate Cases
Under the regulations at Sec. 412.525(a)(2)(ii) and as required by
section 1886(m)(7) of the Act, the fixed-loss amount for HCO payments
is set each year so that the estimated aggregate HCO payments for LTCH
PPS standard Federal payment rate cases are 99.6875 percent of 8
percent (that is, 7.975 percent) of estimated aggregate LTCH PPS
payments for LTCH PPS standard Federal payment rate cases. (For more
details on the requirements for high-cost outlier payments in FY 2018
and subsequent years under section 1886(m)(7) of the Act and additional
information regarding high-cost outlier payments prior to FY 2018, we
refer readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 38542
through 38544).)
b. Proposed Fixed-Loss Amount for LTCH PPS Standard Federal Payment
Rate Cases for FY 2020
When we implemented the LTCH PPS, we established a fixed-loss
amount so that total estimated outlier payments are projected to equal
8 percent of total estimated payments under the LTCH PPS (67 FR 56022
through 56026). When we implemented the dual rate LTCH PPS payment
structure beginning in FY 2016, we established that, in general, the
historical LTCH PPS HCO policy would continue to apply to LTCH PPS
standard Federal payment rate cases. That is, the fixed-loss amount and
target for LTCH PPS standard Federal payment rate cases would be
determined using the LTCH PPS HCO policy adopted when the LTCH PPS was
first implemented, but we limited the data used under that policy to
LTCH cases that would have been LTCH PPS standard Federal payment rate
cases if the statutory changes had been in effect at the time of those
discharges.
To determine the applicable fixed-loss amount for LTCH PPS standard
Federal payment rate cases, we estimate outlier payments and total LTCH
PPS payments for each LTCH PPS standard Federal payment rate case (or
for each case that would have been a LTCH PPS standard Federal payment
rate case if the statutory changes had been in effect at the time of
the discharge) using claims data from the MedPAR files. In accordance
with Sec. 412.525(a)(2)(ii), the applicable fixed-loss amount for LTCH
PPS standard Federal payment rate cases results in estimated total
outlier payments being projected to be equal to 7.975 percent of
projected total LTCH PPS payments for LTCH PPS standard Federal payment
rate cases. We use MedPAR claims data and CCRs based on data from the
most recent PSF (or from the applicable statewide average CCR if an
LTCH's CCR data are faulty or unavailable) to establish an applicable
fixed-loss threshold amount for LTCH PPS standard Federal payment rate
cases.
In this FY 2020 IPPS/LTCH PPS proposed rule, we are proposing to
continue to use our current methodology to calculate an applicable
fixed-loss amount for LTCH PPS standard Federal payment rate cases for
FY 2020 using the best available data that would maintain estimated HCO
payments at the projected 7.975 percent of total estimated LTCH PPS
payments for LTCH PPS standard Federal payment rate cases (based on the
payment rates and policies for these cases presented in this proposed
rule).
Specifically, based on the most recent complete LTCH data available
at this time (that is, LTCH claims data from the December 2018 update
of the FY 2018 MedPAR file and CCRs from the December 2018 update of
the PSF), we are proposing to determine a proposed fixed-loss amount
for LTCH PPS standard Federal payment rate cases for FY 2020 of $29,997
that would result in estimated outlier payments projected to
[[Page 19616]]
be equal to 7.975 percent of estimated FY 2020 payments for such cases.
Under this proposal, we would continue to make an additional HCO
payment for the cost of an LTCH PPS standard Federal payment rate case
that exceeds the HCO threshold amount that is equal to 80 percent of
the difference between the estimated cost of the case and the outlier
threshold (the sum of the proposed adjusted LTCH PPS standard Federal
payment rate payment and the proposed fixed-loss amount for LTCH PPS
standard Federal payment rate cases of $29,997).
We note that the proposed fixed-loss amount for HCO cases that
would be paid under the LTCH PPS standard Federal payment rate in FY
2020 of $29,997 is significantly higher than the FY 2019 fixed-loss
amount of $27,121 (as corrected at 83 FR 49845). However, based on the
most recent available data at the time of the development of this FY
2020 IPPS/LTCH PPS proposed rule, we found that the current FY 2019 HCO
threshold of $27,121 results in estimated HCO payments for LTCH PPS
standard Federal payment rate cases of approximately 8.24 percent of
the estimated total LTCH PPS payments in FY 2018, which exceeds the
7.975 percent target by 0.265 percentage points. We continue to believe
that, as discussed in detail in the FY 2018 IPPS/LTCH PPS final rule
(82 FR 38542 through 38543), this increase is largely attributable to
the rate-of-change (that is, increase) in the Medicare allowable
charges on the claims data in addition to updates to CCRs from the
March 2018 update of the PSF to the December 2018 update of the PSF.
Consistent with our historical practice of using the best data
available, we are proposing that, when determining the fixed-loss
amount for LTCH PPS standard Federal payment rate cases for FY 2020 in
the final rule, we would use the most recent available LTCH claims data
and CCR data at the time.
4. Proposed High-Cost Outlier Payments for Site Neutral Payment Rate
Cases
Under Sec. 412.525(a), site neutral payment rate cases receive an
additional HCO payment for costs that exceed the HCO threshold that is
equal to 80 percent of the difference between the estimated cost of the
case and the applicable HCO threshold (80 FR 49618 through 49629). In
the following discussion, we note that the statutory transitional
payment method for cases that are paid the site neutral payment rate
for LTCH discharges occurring in cost reporting periods beginning
during FY 2016 through FY 2019 used a blended payment rate, which is
determined as 50 percent of the site neutral payment rate amount for
the discharge and 50 percent of the LTCH PPS standard Federal payment
rate amount for the discharge (Sec. 412.522(c)(3)). As such, for FY
2020 discharges paid under the transitional payment method, the
discussion below pertains only to the site neutral payment rate portion
of the blended payment rate under Sec. 412.522(c)(3)(i).
When we implemented the application of the site neutral payment
rate in FY 2016, in examining the appropriate fixed-loss amount for
site neutral payment rate cases issue, we considered how LTCH
discharges based on historical claims data would have been classified
under the dual rate LTCH PPS payment structure and the CMS' Office of
the Actuary projections regarding how LTCHs will likely respond to our
implementation of policies resulting from the statutory payment
changes. We again relied on these considerations and actuarial
projections in FY 2017 and FY 2018 because the historical claims data
available in each of these years were not all subject to the LTCH PPS
dual rate payment system. Similarly, for FY 2019, we continued to rely
on these considerations and actuarial projections because, due to the
transitional blended payment policy for site neutral payment rate
cases, FY 2017 claims for these cases were not subject to the full
effect of the site neutral payment rate.
For FYs 2016 through 2019, at that time our actuaries projected
that the proportion of cases that would qualify as LTCH PPS standard
Federal payment rate cases versus site neutral payment rate cases under
the statutory provisions would remain consistent with what is reflected
in the historical LTCH PPS claims data. Although our actuaries did not
project an immediate change in the proportions found in the historical
data, they did project cost and resource changes to account for the
lower payment rates. Our actuaries also projected that the costs and
resource use for cases paid at the site neutral payment rate would
likely be lower, on average, than the costs and resource use for cases
paid at the LTCH PPS standard Federal payment rate and would likely
mirror the costs and resource use for IPPS cases assigned to the same
MS-DRG, regardless of whether the proportion of site neutral payment
rate cases in the future remains similar to what is found based on the
historical data. As discussed in the FY 2016 IPPS/LTCH PPS final rule
(80 FR 49619), this actuarial assumption is based on our expectation
that site neutral payment rate cases would generally be paid based on
an IPPS comparable per diem amount under the statutory LTCH PPS payment
changes that began in FY 2016, which, in the majority of cases, is much
lower than the payment that would have been paid if these statutory
changes were not enacted. In light of these projections and
expectations, we discussed that we believed that the use of a single
fixed-loss amount and HCO target for all LTCH PPS cases would be
problematic. In addition, we discussed that we did not believe that it
would be appropriate for comparable LTCH PPS site neutral payment rate
cases to receive dramatically different HCO payments from those cases
that would be paid under the IPPS (80 FR 49617 through 49619 and 81 FR
57305 through 57307). For those reasons, we stated that we believed
that the most appropriate fixed-loss amount for site neutral payment
rate cases for FYs 2016 through 2019 would be equal to the IPPS fixed-
loss amount for that particular fiscal year. Therefore, we established
the fixed-loss amount for site neutral payment rate cases as the
corresponding IPPS fixed-loss amounts for FYs 2016 through 2019. In
particular, in FY 2019, we established the fixed-loss amount for site
neutral payment rate cases as the FY 2019 IPPS fixed-loss amount of
$25,743 (as corrected at 83 FR 49845).
As noted earlier, because not all claims in the data used for this
FY 2020 IPPS/LTCH PPS proposed rule were subject to the unblended site
neutral payment rate, we continue to rely on the same considerations
and actuarial projections used in FYs 2016 through 2019 when developing
a fixed-loss amount for site neutral payment rate cases for FY 2020.
Because our actuaries continue to project that site neutral payment
rate cases in FY 2020 will continue to mirror an IPPS case paid under
the same MS-DRG, we continue to believe that it would be inappropriate
for comparable LTCH PPS site neutral payment rate cases to receive
dramatically different HCO payments from those cases paid under the
IPPS. More specifically, as with FYs 2016 through 2019, our actuaries
project that the costs and resource use for FY 2020 cases paid at the
site neutral payment rate would likely be lower, on average, than the
costs and resource use for cases paid at the LTCH PPS standard Federal
payment rate and will likely mirror the costs and resource use for IPPS
cases assigned to the same MS-DRG, regardless of whether the proportion
of site neutral payment rate cases in the future remains similar to
what was found based on the historical data. (Based on the most recent
FY 2018
[[Page 19617]]
LTCH claims data used in the development of this FY 2020 IPPS/LTCH PPS
proposed rule, approximately 71 percent of LTCH cases would have been
paid the LTCH PPS standard Federal payment rate and approximately 29
percent of LTCH cases would have been paid the site neutral payment
rate for discharges occurring in FY 2018.)
For these reasons, we continue to believe that the most appropriate
proposed fixed-loss amount for site neutral payment rate cases for FY
2020 is the proposed IPPS fixed-loss amount for FY 2020. Therefore,
consistent with past practice, in this FY 2020 IPPS/LTCH PPS proposed
rule, we are proposing that the applicable HCO threshold for site
neutral payment rate cases is the sum of the site neutral payment rate
for the case and the proposed IPPS fixed-loss amount. That is, we are
proposing a fixed-loss amount for site neutral payment rate cases of
$26,994, which is the same proposed FY 2020 IPPS fixed-loss amount
discussed in section II.A.4.j.(1) of the Addendum to this proposed
rule. We continue to believe this policy would reduce differences
between HCO payments for similar cases under the IPPS and site neutral
payment rate cases under the LTCH PPS and promote fairness between the
two systems. Accordingly, for FY 2020, we are proposing to calculate a
HCO payment for site neutral payment rate cases with costs that exceed
the HCO threshold amount that is equal to 80 percent of the difference
between the estimated cost of the case and the outlier threshold (the
sum of the site neutral payment rate payment and the proposed fixed-
loss amount for site neutral payment rate cases of $26,994).
In establishing a HCO policy for site neutral payment rate cases,
we established a budget neutrality adjustment under Sec.
412.522(c)(2)(i). We established this requirement because we believed,
and continue to believe, that the HCO policy for site neutral payment
rate cases should be budget neutral, just as the HCO policy for LTCH
PPS standard Federal payment rate cases is budget neutral, meaning that
estimated site neutral payment rate HCO payments should not result in
any change in estimated aggregate LTCH PPS payments.
To ensure that estimated HCO payments payable to site neutral
payment rate cases in FY 2020 would not result in any increase in
estimated aggregate FY 2020 LTCH PPS payments, under the budget
neutrality requirement at Sec. 412.522(c)(2)(i), it is necessary to
reduce site neutral payment rate payments (or the portion of the
blended payment rate payment for FY 2020 discharges occurring in LTCH
cost reporting periods beginning before October 1, 2019) by 5.1 percent
to account for the estimated additional HCO payments payable to those
cases in FY 2020. In order to achieve this, for FY 2020, in general, we
are proposing to continue to use the policy adopted for FY 2019.
As discussed earlier, consistent with the IPPS HCO payment
threshold, we estimate the proposed fixed-loss threshold of $26,994
results in HCO payments for site neutral payment rate cases to equal
5.1 percent of the site neutral payment rate payments that are based on
the IPPS comparable per diem amount. As such, to ensure estimated HCO
payments payable for site neutral payment rate cases in FY 2020 would
not result in any increase in estimated aggregate FY 2020 LTCH PPS
payments, under the budget neutrality requirement at Sec.
412.522(c)(2)(i), it is necessary to reduce the site neutral payment
rate amount paid under Sec. 412.522(c)(1)(i) by 5.1 percent to account
for the estimated additional HCO payments payable for site neutral
payment rate cases in FY 2020. In order to achieve this, for FY 2020,
we are proposing to apply a budget neutrality factor of 0.949 (that is,
the decimal equivalent of a 5.1 percent reduction, determined as 1.0 -
5.1/100 = 0.949) to the site neutral payment rate for those site
neutral payment rate cases paid under Sec. 412.522(c)(1)(i). We note
that, consistent with our current policy, this proposed HCO budget
neutrality adjustment would not be applied to the HCO portion of the
site neutral payment rate amount (81 FR 57309).
E. Proposed Update to the IPPS Comparable Amount To Reflect the
Statutory Changes to the IPPS DSH Payment Adjustment Methodology
In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50766), we
established a policy to reflect the changes to the Medicare IPPS DSH
payment adjustment methodology made by section 3133 of the Affordable
Care Act in the calculation of the ``IPPS comparable amount'' under the
SSO policy at Sec. 412.529 and the ``IPPS equivalent amount'' under
the 25-percent threshold payment adjustment policy at Sec. 412.534 and
Sec. 412.536. Historically, the determination of both the ``IPPS
comparable amount'' and the ``IPPS equivalent amount'' includes an
amount for inpatient operating costs ``for the costs of serving a
disproportionate share of low-income patients.'' Under the statutory
changes to the Medicare DSH payment adjustment methodology that began
in FY 2014, in general, eligible IPPS hospitals receive an empirically
justified Medicare DSH payment equal to 25 percent of the amount they
otherwise would have received under the statutory formula for Medicare
DSH payments prior to the amendments made by the Affordable Care Act.
The remaining amount, equal to an estimate of 75 percent of the amount
that otherwise would have been paid as Medicare DSH payments, reduced
to reflect changes in the percentage of individuals who are uninsured
and any additional statutory adjustment, is made available to make
additional payments to each hospital that qualifies for Medicare DSH
payments and that has uncompensated care. The additional uncompensated
care payments are based on the hospital's amount of uncompensated care
for a given time period relative to the total amount of uncompensated
care for that same time period reported by all IPPS hospitals that
receive Medicare DSH payments.
To reflect the statutory changes to the Medicare DSH payment
adjustment methodology in the calculation of the ``IPPS comparable
amount'' and the ``IPPS equivalent amount'' under the LTCH PPS, we
stated that we will include a reduced Medicare DSH payment amount that
reflects the projected percentage of the payment amount calculated
based on the statutory Medicare DSH payment formula prior to the
amendments made by the Affordable Care Act that will be paid to
eligible IPPS hospitals as empirically justified Medicare DSH payments
and uncompensated care payments in that year (that is, a percentage of
the operating Medicare DSH payment amount that has historically been
reflected in the LTCH PPS payments that are based on IPPS rates). We
also stated that the projected percentage will be updated annually,
consistent with the annual determination of the amount of uncompensated
care payments that will be made to eligible IPPS hospitals. We believe
that this approach results in appropriate payments under the LTCH PPS
and is consistent with our intention that the ``IPPS comparable
amount'' and the ``IPPS equivalent amount'' under the LTCH PPS closely
resemble what an IPPS payment would have been for the same episode of
care, while recognizing that some features of the IPPS cannot be
translated directly into the LTCH PPS (79 FR 50766 through 50767).
For FY 2020, as discussed in greater detail in section IV.F.3. of
the preamble of this proposed rule, based on the most recent data
available, our estimate of 75 percent of the amount that would
[[Page 19618]]
otherwise have been paid as Medicare DSH payments (under the
methodology outlined in section 1886(r)(2) of the Act) is adjusted to
67.14 percent of that amount to reflect the change in the percentage of
individuals who are uninsured. The resulting amount is then used to
determine the amount available to make uncompensated care payments to
eligible IPPS hospitals in FY 2020. In other words, the amount of the
Medicare DSH payments that would have been made prior to the amendments
made by the Affordable Care Act will be adjusted to 50.36 percent (the
product of 75 percent and 67.14 percent) and the resulting amount will
be used to calculate the uncompensated care payments to eligible
hospitals. As a result, for FY 2020, we project that the reduction in
the amount of Medicare DSH payments pursuant to section 1886(r)(1) of
the Act, along with the payments for uncompensated care under section
1886(r)(2) of the Act, will result in overall Medicare DSH payments of
75.36 percent of the amount of Medicare DSH payments that would
otherwise have been made in the absence of the amendments made by the
Affordable Care Act (that is, 25 percent + 50.36 percent = 75.36
percent).
Therefore, for FY 2020, we are proposing to establish that the
calculation of the ``IPPS comparable amount'' under Sec. 412.529 would
include an applicable operating Medicare DSH payment amount that is
equal to 75.36 percent of the operating Medicare DSH payment amount
that would have been paid based on the statutory Medicare DSH payment
formula absent the amendments made by the Affordable Care Act.
Furthermore, consistent with our historical practice, we are proposing
that if more recent data become available, we would use that data to
determine this factor in the final rule.
F. Computing the Proposed Adjusted LTCH PPS Federal Prospective
Payments for FY 2020
Section 412.525 sets forth the adjustments to the LTCH PPS standard
Federal payment rate. Under the dual rate LTCH PPS payment structure,
only LTCH PPS cases that meet the statutory criteria to be excluded
from the site neutral payment rate are paid based on the LTCH PPS
standard Federal payment rate. Under Sec. 412.525(c), the LTCH PPS
standard Federal payment rate is adjusted to account for differences in
area wages by multiplying the labor-related share of the LTCH PPS
standard Federal payment rate for a case by the applicable LTCH PPS
wage index (the proposed FY 2020 values are shown in Tables 12A through
12B listed in section VI. of the Addendum to this proposed rule and are
available via the internet on the CMS website). The LTCH PPS standard
Federal payment rate is also adjusted to account for the higher costs
of LTCHs located in Alaska and Hawaii by the applicable COLA factors
(the proposed FY 2020 factors are shown in the chart in section V.C. of
this Addendum) in accordance with Sec. 412.525(b). In this proposed
rule, we are proposing to establish an LTCH PPS standard Federal
payment rate for FY 2020 of $42,950.91, as discussed in section V.A. of
the Addendum to this proposed rule. We illustrate the methodology to
adjust the proposed LTCH PPS standard Federal payment rate for FY 2020
in the following example:
Example: During FY 2020, a Medicare discharge that meets the
criteria to be excluded from the site neutral payment rate, that is, an
LTCH PPS standard Federal payment rate case, is from an LTCH that is
located in Chicago, Illinois (CBSA 16974). The proposed FY 2020 LTCH
PPS wage index value for CBSA 16974 is 1.0347 (obtained from Table 12A
listed in section VI. of the Addendum to this proposed rule and
available via the internet on the CMS website). The Medicare patient
case is classified into MS-LTC-DRG 189 (Pulmonary Edema & Respiratory
Failure), which has a proposed relative weight for FY 2020 of 0.9602
(obtained from Table 11 listed in section VI. of the Addendum to this
proposed rule and available via the internet on the CMS website). The
LTCH submitted quality reporting data for FY 2020 in accordance with
the LTCH QRP under section 1886(m)(5) of the Act.
To calculate the LTCH's total adjusted Federal prospective payment
for this Medicare patient case in FY 2020, we computed the wage-
adjusted proposed Federal prospective payment amount by multiplying the
unadjusted proposed FY 2020 LTCH PPS standard Federal payment rate
($42,950.91) by the proposed labor-related share (66.0 percent) and the
proposed wage index value (1.0347). This wage-adjusted amount was then
added to the proposed nonlabor-related portion of the unadjusted
proposed LTCH PPS standard Federal payment rate (34.0 percent; adjusted
for cost of living, if applicable) to determine the adjusted proposed
LTCH PPS standard Federal payment rate, which is then multiplied by the
proposed MS-LTC-DRG relative weight (0.9602) to calculate the total
adjusted proposed LTCH PPS standard Federal prospective payment for FY
2020 ($42,185.97). The table below illustrates the components of the
calculations in this example.
------------------------------------------------------------------------
------------------------------------------------------------------------
Unadjusted Proposed LTCH PPS Standard Federal $42,950.91
Prospective Payment Rate...............................
Proposed Labor-Related Share............................ x 0.660
Proposed Labor-Related Portion of the Proposed LTCH PPS = $28,347.60
Standard Federal Payment Rate..........................
Proposed Wage Index (CBSA 16974)........................ x 1.0347
Proposed Wage-Adjusted Labor Share of the Proposed LTCH = $29,331.26
PPS Standard Federal Payment Rate......................
Proposed Nonlabor-Related Portion of the Proposed LTCH + $14,603.31
PPS Standard Federal Payment Rate ($42,950.91 x 0.340).
Adjusted Proposed LTCH PPS Standard Federal Payment = $43,934.57
Amount.................................................
Proposed MS-LTC-DRG 189 Relative Weight................. x 0.9602
---------------
Total Adjusted Proposed LTCH PPS Standard Federal = $42,185.97
Prospective Payment................................
------------------------------------------------------------------------
VI. Tables Referenced in This Proposed Rule Generally Available Through
the Internet on the CMS Website
This section lists the tables referred to throughout the preamble
of this proposed rule and in the Addendum. In the past, a majority of
these tables were published in the Federal Register as part of the
annual proposed and final rules. However, similar to FYs 2012 through
2019, for the FY 2020 rulemaking cycle, the IPPS and LTCH PPS tables
will not be published in the Federal Register in the annual IPPS/LTCH
PPS proposed and final rules and will be available through the
internet. Specifically, all IPPS tables listed below, with the
exception of IPPS Tables 1A, 1B, 1C, and 1D, and LTCH PPS Table 1E,
will generally be available through the internet. IPPS Tables 1A, 1B,
1C, and 1D, and LTCH PPS Table 1E are displayed at the end of this
section and will continue to be published in the Federal Register as
part of the annual proposed and final rules. For additional discussion
of the
[[Page 19619]]
information included in the IPPS and LTCH PPS tables associated with
the IPPS/LTCH PPS proposed and final rules, as well as prior changes to
the information included in these tables, we refer readers to the FY
2019 IPPS/LTCH PPS final rule (83 FR 41739 through 41740).
In addition, under the HAC Reduction Program, established by
section 3008 of the Affordable Care Act, a hospital's total payment may
be reduced by 1 percent if it is in the lowest HAC performance
quartile. The hospital-level data for the FY 2020 HAC Reduction Program
will be made publicly available once it has undergone the review and
corrections process.
As discussed in section IV.G. of the preamble of this proposed
rule, the proposed fiscal year readmissions payment adjustment factors,
which are typically included in Table 15 of the rules, are not
available at this time because hospitals have not yet had the
opportunity to review and correct the data (program calculations based
on the FY 2020 applicable period of July 1, 2015 to June 30, 2018)
before the data are made public under our policy regarding the
reporting of hospital-specific data. After hospitals have been given an
opportunity to review and correct their calculations for FY 2020, we
will post Table 15 (which will be available via the internet on the CMS
website) to display the final FY 2020 readmissions payment adjustment
factors that will be applicable to discharges occurring on or after
October 1, 2019. We expect Table 15 will be posted on the CMS website
in the fall of 2019.
Readers who experience any problems accessing any of the tables
that are posted on the CMS websites identified below should contact
Michael Treitel at (410) 786-4552.
The following IPPS tables for this proposed rule are generally
available through the internet on the CMS website at: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. Click on the link on the left side of the
screen titled, ``FY 2020 IPPS Proposed Rule Home Page'' or ``Acute
Inpatient--Files for Download.''
Table 2.--Proposed Case-Mix Index and Wage Index Table by CCN--FY 2020
Table 3.--Proposed Wage Index Table by CBSA--FY 2020
Table 4.--Proposed List of Counties Eligible for the Out-Migration
Adjustment under Section 1886(d)(13) of the Act--FY 2020
Table 5.--Proposed List of Medicare Severity Diagnosis-Related Groups
(MS-DRGs), Relative Weighting Factors, and Geometric and Arithmetic
Mean Length of Stay--FY 2020
Table 6A.--New Diagnosis Codes--FY 2020
Table 6B.--New Procedure Codes--FY 2020
Table 6C.--Invalid Diagnosis Codes--FY 2020
Table 6D.--Invalid Procedure Codes--FY 2020
Table 6E.--Revised Diagnosis Code Titles--FY 2020
Table 6F.--Revised Procedure Code Titles--FY 2020
Table 6G.1.--Proposed Secondary Diagnosis Order Additions to the CC
Exclusions List--FY 2020
Table 6G.2.--Proposed Principal Diagnosis Order Additions to the CC
Exclusions List--FY 2020
Table 6H.1.--Proposed Secondary Diagnosis Order Deletions to the CC
Exclusions List--FY 2020
Table 6H.2.--Proposed Principal Diagnosis Order Deletions to the CC
Exclusions List--FY 2020
Table 6I.1.--Proposed Additions to the MCC List--FY 2020
Table 6I.2.--Proposed Deletions to the MCC List--FY 2020
Table 6J.1.--Proposed Additions to the CC List--FY 2020
Table 6J.2.--Proposed Deletions to the CC List--FY 2020
Table 6P.--ICD-10-CM and ICD-10-PCS Codes for Proposed MS-DRG Changes--
FY 2020 (Table 6P contains multiple tables, 6P.1a. through 6P.1e., that
include the ICD-10-CM and ICD-10-PCS code lists relating to proposed
specific MS-DRG changes. These tables are referred to throughout
section II.F. of the preamble of this proposed rule.)
Table 7A.--Proposed Medicare Prospective Payment System Selected
Percentile Lengths of Stay: FY 2018 MedPAR Update--December 2018
GROUPER Version 36 MS-DRGs
Table 7B.--Proposed Medicare Prospective Payment System Selected
Percentile Lengths of Stay: FY 2018 MedPAR Update--December 2018
GROUPER Version 37 MS-DRGs
Table 8A.--Proposed FY 2020 Statewide Average Operating Cost-to-Charge
Ratios (CCRs) for Acute Care Hospitals (Urban and Rural)
Table 8B.--Proposed FY 2020 Statewide Average Capital Cost-to-Charge
Ratios (CCRs) for Acute Care Hospitals
Table 16.--Proposed Proxy Hospital Value-Based Purchasing (VBP) Program
Adjustment Factors for FY 2020
Table 18.--Proposed FY 2020 Medicare DSH Uncompensated Care Payment
Factor 3
The following LTCH PPS tables for this FY 2020 proposed rule are
available through the internet on the CMS website at: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/LongTermCareHospitalPPS/index.html under the list item for Regulation
Number CMS-1716-P:
Table 8C.--Proposed FY 2020 Statewide Average Total Cost-to-Charge
Ratios (CCRs) for LTCHs (Urban and Rural)
Table 11.--Proposed MS-LTC-DRGs, Relative Weights, Geometric Average
Length of Stay, and Short-Stay Outlier (SSO) Threshold for LTCH PPS
Discharges Occurring from October 1, 2019 through September 30, 2020
Table 12A.--Proposed LTCH PPS Wage Index for Urban Areas for Discharges
Occurring from October 1, 2019 through September 30, 2020
Table 12B.--Proposed LTCH PPS Wage Index for Rural Areas for Discharges
Occurring from October 1, 2019 through September 30, 2020
Table 1A--Proposed National Adjusted Operating Standardized Amounts, Labor/Nonlabor (68.3 Percent Labor Share/31.7 Percent Nonlabor Share if Wage Index
Is Greater Than 1)--FY 2020
--------------------------------------------------------------------------------------------------------------------------------------------------------
Hospital submitted quality data and is Hospital submitted quality data and Hospital did NOT submit quality data Hospital did NOT submit quality data
a meaningful EHR user (update = 2.7 is NOT a meaningful EHR user (update and is a meaningful EHR user (update and is NOT a meaningful EHR user
percent) = 0.3 percent) = 1.9 percent) (update = -0.5 percent)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Labor Nonlabor Labor Nonlabor Labor Nonlabor Labor Nonlabor
--------------------------------------------------------------------------------------------------------------------------------------------------------
$3,977.31 $1,845.99 $3,884.36 $1,802.85 $3,946.33 $1,831.61 $3,853.38 $1,788.47
--------------------------------------------------------------------------------------------------------------------------------------------------------
[[Page 19620]]
Table 1B--Proposed National Adjusted Operating Standardized Amounts, Labor/Nonlabor (62 Percent Labor Share/38 Percent Nonlabor Share if Wage Index Is
Less Than or Equal To 1)--FY 2020
--------------------------------------------------------------------------------------------------------------------------------------------------------
Hospital submitted quality data and Hospital submitted quality data and Hospital did NOT submit quality data Hospital did NOT submit quality data
is a meaningful EHR user (update = is NOT a meaningful EHR user (update and is a meaningful EHR user (update and is NOT a meaningful EHR user
2.7 percent) = 0.3 percent) = 1.9 percent) (update = -0.5 percent)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Labor Nonlabor Labor Nonlabor Labor Nonlabor Labor Nonlabor
--------------------------------------------------------------------------------------------------------------------------------------------------------
$3,610.45 $2,212.85 $3,526.07 $2,161.14 $3,582.32 $2,195.62 $3,497.95 $2,143.90
--------------------------------------------------------------------------------------------------------------------------------------------------------
Table 1C--Proposed Adjusted Operating Standardized Amounts for Hospitals in Puerto Rico, Labor/Nonlabor
(National: 62 Percent Labor Share/38 Percent Nonlabor Share Because Wage Index Is Less Than or Equal to 1);--FY
2020
----------------------------------------------------------------------------------------------------------------
Rates if wage index is greater than 1 Rates if wage index is less
---------------------------------------------- than or equal to 1
Standardized amount -------------------------------
Labor Nonlabor Labor Nonlabor
----------------------------------------------------------------------------------------------------------------
National \1\...................... Not Applicable....... Not Applicable....... $3,610.45 $2,212.85
----------------------------------------------------------------------------------------------------------------
\1\ For FY 2020, there are no CBSAs in Puerto Rico with a national wage index greater than 1.
Table 1D--Proposed Capital Standard Federal Payment Rate--FY 2020
------------------------------------------------------------------------
Rate
------------------------------------------------------------------------
National............................................... $463.81
------------------------------------------------------------------------
Table 1E--Proposed LTCH PPS Standard Federal Payment Rate--FY 2020
------------------------------------------------------------------------
Full update Reduced update
(2.7 percent) * (0.7 percent)
------------------------------------------------------------------------
Standard Federal Rate................. $42,950.91 $42,114.47
------------------------------------------------------------------------
* For LTCHs that fail to submit quality reporting data for FY 2020 in
accordance with the LTCH Quality Reporting Program (LTCH QRP), the
annual update is reduced by 2.0 percentage points as required by
section 1886(m)(5) of the Act.
Appendix A: Economic Analyses
I. Regulatory Impact Analysis
A. Statement of Need
This proposed rule is necessary in order to make payment and
policy changes under the Medicare IPPS for Medicare acute care
hospital inpatient services for operating and capital-related costs
as well as for certain hospitals and hospital units excluded from
the IPPS. This proposed rule also is necessary to make payment and
policy changes for Medicare hospitals under the LTCH PPS. Also as we
note below, the primary objective of the IPPS and the LTCH PPS is to
create incentives for hospitals to operate efficiently and minimize
unnecessary costs, while at the same time ensuring that payments are
sufficient to adequately compensate hospitals for their legitimate
costs in delivering necessary care to Medicare beneficiaries. In
addition, we share national goals of preserving the Medicare
Hospital Insurance Trust Fund.
We believe that the proposed changes in this proposed rule, such
as the proposed updates to the IPPS and LTCH PPS rates, are needed
to further each of these goals while maintaining the financial
viability of the hospital industry and ensuring access to high
quality health care for Medicare beneficiaries. We expect that these
proposed changes would ensure that the outcomes of the prospective
payment systems are reasonable and equitable, while avoiding or
minimizing unintended adverse consequences.
B. Overall Impact
We have examined the impacts of this proposed rule as required
by Executive Order 12866 on Regulatory Planning and Review
(September 30, 1993), Executive Order 13563 on Improving Regulation
and Regulatory Review (January 18, 2011), the Regulatory Flexibility
Act (RFA) (September 19, 1980, Pub. L. 96-354), section 1102(b) of
the Social Security Act, section 202 of the Unfunded Mandates Reform
Act of 1995 (March 22, 1995; Pub. L. 104-4), Executive Order 13132
on Federalism (August 4, 1999), the Congressional Review Act (5
U.S.C. 804(2)), and Executive Order 13771 on Reducing Regulation and
Controlling Regulatory Costs (January 30, 2017).
Executive Orders 12866 and 13563 direct agencies to assess all
costs and benefits of available regulatory alternatives and, if
regulation is necessary, to select regulatory approaches that
maximize net benefits (including potential economic, environmental,
public health and safety effects, distributive impacts, and equity).
Section 3(f) of Executive Order 12866 defines a ``significant
regulatory action'' as an action that is likely to result in a rule:
(1) Having an annual effect on the economy of $100 million or more
in any 1 year, or adversely and materially affecting a sector of the
economy, productivity, competition, jobs, the environment, public
health or safety, or State, local or tribal governments or
communities (also referred to as ``economically significant''); (2)
creating a serious inconsistency or otherwise interfering with an
action taken or planned by another agency; (3) materially altering
the budgetary impacts of entitlement grants, user fees, or loan
programs or the rights and obligations of recipients thereof; or (4)
raising novel legal or policy issues arising out of legal mandates,
the President's priorities, or the principles set forth in the
Executive Order.
We have determined that this proposed rule is a major rule as
defined in 5 U.S.C. 804(2). We estimate that the proposed changes
for FY 2020 acute care hospital operating and capital payments would
redistribute amounts in excess of $100 million to acute care
hospitals. The proposed applicable percentage increase to the IPPS
rates required by the statute, in conjunction with other proposed
payment changes in this proposed rule, would result in an estimated
$4.67 billion increase in FY 2020 payments,
[[Page 19621]]
primarily driven by a combined $4.4 billion increase in FY 2020
operating payments and uncompensated care payments, and a net
increase of $300 million resulting from estimated changes in FY 2020
capital payments, new technology add-on payments, and low-volume
hospital payments. These proposed changes are relative to payments
made in FY 2019. The impact analysis of the capital payments can be
found in section I.I. of this Appendix. In addition, as described in
section I.J. of this Appendix, LTCHs are expected to experience an
increase in payments by $37 million in FY 2020 relative to FY 2019.
Our operating impact estimate includes the proposed 0.5
percentage point adjustment required under section 414 of the MACRA
applied to the IPPS standardized amount, as discussed in section
II.D. of the preamble of this proposed rule. In addition, our
operating payment impact estimate includes the proposed 2.7 percent
hospital update to the standardized amount (which includes the
estimated 3.2 percent market basket update less the proposed 0.5
percentage point for the multifactor productivity adjustment (MFP)).
The estimates of IPPS operating payments to acute care hospitals do
not reflect any changes in hospital admissions or real case-mix
intensity, which will also affect overall payment changes.
The analysis in this Appendix, in conjunction with the remainder
of this document, demonstrates that this proposed rule is consistent
with the regulatory philosophy and principles identified in
Executive Orders 12866 and 13563, the RFA, and section 1102(b) of
the Act. This proposed rule would affect payments to a substantial
number of small rural hospitals, as well as other classes of
hospitals, and the effects on some hospitals may be significant.
Finally, in accordance with the provisions of Executive Order 12866,
the Executive Office of Management and Budget has reviewed this
proposed rule.
C. Objectives of the IPPS and the LTCH PPS
The primary objective of the IPPS and the LTCH PPS is to create
incentives for hospitals to operate efficiently and minimize
unnecessary costs, while at the same time ensuring that payments are
sufficient to adequately compensate hospitals for their legitimate
costs in delivering necessary care to Medicare beneficiaries. In
addition, we share national goals of preserving the Medicare
Hospital Insurance Trust Fund.
We believe that the proposed changes in this proposed rule would
further each of these goals while maintaining the financial
viability of the hospital industry and ensuring access to high
quality health care for Medicare beneficiaries. We expect that these
proposed changes would ensure that the outcomes of the prospective
payment systems are reasonable and equitable, while avoiding or
minimizing unintended adverse consequences.
Because this proposed rule contains a range of policies, we
refer readers to the section of the proposed rule where each policy
is discussed. These sections include the rationale for our
decisions, including the need for the proposed policy.
D. Limitations of Our Analysis
The following quantitative analysis presents the projected
effects of our proposed policy changes, as well as statutory changes
effective for FY 2020, on various hospital groups. We estimate the
effects of individual proposed policy changes by estimating payments
per case, while holding all other payment policies constant. We use
the best data available, but, generally unless specifically
indicated, we do not attempt to make adjustments for future changes
in such variables as admissions, lengths of stay, case-mix, changes
to the Medicare population, or incentives. In addition, we discuss
limitations of our analysis for specific proposed policies in the
discussion of those proposed policies as needed.
E. Hospitals Included in and Excluded From the IPPS
The prospective payment systems for hospital inpatient operating
and capital-related costs of acute care hospitals encompass most
general short-term, acute care hospitals that participate in the
Medicare program. There were 29 Indian Health Service hospitals in
our database, which we excluded from the analysis due to the special
characteristics of the prospective payment methodology for these
hospitals. Among other short-term, acute care hospitals, hospitals
in Maryland are paid in accordance with the Maryland Total Cost of
Care Model, and hospitals located outside the 50 States, the
District of Columbia, and Puerto Rico (that is, 6 short-term acute
care hospitals located in the U.S. Virgin Islands, Guam, the
Northern Mariana Islands, and American Samoa) receive payment for
inpatient hospital services they furnish on the basis of reasonable
costs, subject to a rate-of-increase ceiling.
As of March 2019, there were 3,242 IPPS acute care hospitals
included in our analysis. This represents approximately 54 percent
of all Medicare-participating hospitals. The majority of this impact
analysis focuses on this set of hospitals. There also are
approximately 1,403 CAHs. These small, limited service hospitals are
paid on the basis of reasonable costs, rather than under the IPPS.
IPPS-excluded hospitals and units, which are paid under separate
payment systems, include IPFs, IRFs, LTCHs, RNHCIs, children's
hospitals, 11 cancer hospitals, 1 extended neoplastic disease care
hospital, and 6 short-term acute care hospitals located in the
Virgin Islands, Guam, the Northern Mariana Islands, and American
Samoa. Changes in the prospective payment systems for IPFs and IRFs
are made through separate rulemaking. Payment impacts of proposed
changes to the prospective payment systems for these IPPS-excluded
hospitals and units are not included in this proposed rule. The
impact of the proposed update and policy changes to the LTCH PPS for
FY 2020 is discussed in section I.J. of this Appendix.
F. Effects on Hospitals and Hospital Units Excluded From the IPPS
As of March 2019, there were 96 children's hospitals, 11 cancer
hospitals, 6 short-term acute care hospitals located in the Virgin
Islands, Guam, the Northern Mariana Islands and American Samoa, 1
extended neoplastic disease care hospital, and 16 RNHCIs being paid
on a reasonable cost basis subject to the rate-of-increase ceiling
under Sec. 413.40. (In accordance with Sec. 403.752(a) of the
regulation, RNHCIs are paid under Sec. 413.40.) Among the remaining
providers, 297 rehabilitation hospitals and 832 rehabilitation
units, and approximately 384 LTCHs, are paid the Federal prospective
per discharge rate under the IRF PPS and the LTCH PPS, respectively,
and 543 psychiatric hospitals and 1,050 psychiatric units are paid
the Federal per diem amount under the IPF PPS. As stated previously,
IRFs and IPFs are not affected by the proposed rate updates
discussed in this proposed rule. The impacts of the proposed changes
on LTCHs are discussed in section I.J. of this Appendix.
For children's hospitals, the 11 cancer hospitals, the 6 short-
term acute care hospitals located in the Virgin Islands, Guam, the
Northern Mariana Islands, and American Samoa, the 1 extended
neoplastic disease care hospital, and RNHCIs, the proposed update of
the rate-of-increase limit (or target amount) is the estimated FY
2020 percentage increase in the 2014-based IPPS operating market
basket, consistent with section 1886(b)(3)(B)(ii) of the Act, and
Sec. Sec. 403.752(a) and 413.40 of the regulations. Consistent with
current law, based on IGI's 2018 fourth quarter forecast of the
2014-based IPPS market basket increase, we are estimating the
proposed FY 2020 update to be 3.2 percent (that is, the estimate of
the market basket rate-of-increase). We are proposing that if more
recent data become available for the final rule, we would use such
data to calculate the IPPS operating market basket update for FY
2020. However, the Affordable Care Act requires an adjustment for
multifactor productivity (proposed 0.5 percentage point for FY
2020), resulting in a proposed 2.7 percent applicable percentage
increase for IPPS hospitals that submit quality data and are
meaningful EHR users, as discussed in section IV.B. of the preamble
of this proposed rule. Children's hospitals, the 11 cancer
hospitals, the 6 short-term acute care hospitals located in the
Virgin Islands, Guam, the Northern Mariana Islands, and American
Samoa, the 1 extended neoplastic disease care hospital, and RNHCIs
that continue to be paid based on reasonable costs subject to rate-
of-increase limits under Sec. 413.40 of the regulations are not
subject to the reductions in the applicable percentage increase
required under the Affordable Care Act. Therefore, for those
hospitals paid under Sec. 413.40 of the regulations, the proposed
update is the percentage increase in the 2014-based IPPS operating
market basket for FY 2020, estimated at 3.2 percent.
The impact of the proposed update in the rate-of-increase limit
on those excluded hospitals depends on the cumulative cost increases
experienced by each excluded hospital since its applicable base
period. For excluded hospitals that have maintained their cost
increases at a level below the rate-of-increase limits since their
base period, the major effect is on the level of incentive payments
these excluded hospitals receive. Conversely, for excluded hospitals
with cost increases above the cumulative update in
[[Page 19622]]
their rate-of-increase limits, the major effect is the amount of
excess costs that would not be paid.
We note that, under Sec. 413.40(d)(3), an excluded hospital
that continues to be paid under the TEFRA system and whose costs
exceed 110 percent of its rate-of-increase limit receives its rate-
of-increase limit plus the lesser of: (1) 50 percent of its
reasonable costs in excess of 110 percent of the limit; or (2) 10
percent of its limit. In addition, under the various provisions set
forth in Sec. 413.40, hospitals can obtain payment adjustments for
justifiable increases in operating costs that exceed the limit.
G. Quantitative Effects of the Proposed Policy Changes Under the
IPPS for Operating Costs
1. Basis and Methodology of Estimates
In this proposed rule, we are announcing proposed policy changes
and payment rate updates for the IPPS for FY 2020 for operating
costs of acute care hospitals. The proposed FY 2020 updates to the
capital payments to acute care hospitals are discussed in section
I.I. of this Appendix.
Based on the overall proposed percentage change in payments per
case estimated using our payment simulation model, we estimate that
total FY 2020 operating payments would increase by 3.6 percent,
compared to FY 2019. In addition to the proposed applicable
percentage increase, this amount reflects the proposed +0.5
percentage point permanent adjustment to the standardized amount
required under section 414 of MACRA. The impacts do not reflect
changes in the number of hospital admissions or real case-mix
intensity, which would also affect overall payment changes.
We have prepared separate impact analyses of the proposed
changes to each system. This section deals with the proposed changes
to the operating inpatient prospective payment system for acute care
hospitals. Our payment simulation model relies on the most recent
available claims data to enable us to estimate the impacts on
payments per case of certain proposed changes in this proposed rule.
However, there are other proposed changes for which we do not have
data available that would allow us to estimate the payment impacts
using this model. For those proposed changes, we have attempted to
predict the payment impacts based upon our experience and other more
limited data.
The data used in developing the quantitative analyses of
proposed changes in payments per case presented in this section are
taken from the FY 2018 MedPAR file and the most current Provider-
Specific File (PSF) that are used for payment purposes. Although the
analyses of the proposed changes to the operating PPS do not
incorporate cost data, data from the most recently available
hospital cost reports were used to categorize hospitals. Our
analysis has several qualifications. First, in this analysis, we do
not make adjustments for future changes in such variables as
admissions, lengths of stay, or underlying growth in real case-mix.
Second, due to the interdependent nature of the IPPS payment
components, it is very difficult to precisely quantify the impact
associated with each proposed change. Third, we use various data
sources to categorize hospitals in the tables. In some cases,
particularly the number of beds, there is a fair degree of variation
in the data from the different sources. We have attempted to
construct these variables with the best available source overall.
However, for individual hospitals, some miscategorizations are
possible.
Using cases from the FY 2018 MedPAR file, we simulate payments
under the operating IPPS given various combinations of payment
parameters. As described previously, Indian Health Service hospitals
and hospitals in Maryland were excluded from the simulations. The
impact of the proposed payments under the capital IPPS, and the
impact of the proposed payments for costs other than inpatient
operating costs, are not analyzed in this section. Estimated payment
impacts of the capital IPPS for FY 2020 are discussed in section
I.I. of this Appendix.
We discuss the following proposed changes:
The effects of the application of the proposed
applicable percentage increase of 2.7 percent (that is, a 3.2
percent market basket update with a proposed reduction of 0.5
percentage point for the multifactor productivity adjustment), and a
proposed 0.5 percentage point adjustment required under section 414
of the MACRA to the IPPS standardized amount, and the proposed
applicable percentage increase (including the market basket update
and the proposed multifactor productivity adjustment) to the
hospital-specific rates.
The effects of the proposed changes to the relative
weights and MS-DRG GROUPER.
The effects of the proposed changes in hospitals' wage
index values reflecting updated wage data from hospitals' cost
reporting periods beginning during FY 2016, compared to the FY 2015
wage data, to calculate the proposed FY 2020 wage index.
The effects of the geographic reclassifications by the
MGCRB (as of publication of this proposed rule) that will be
effective for FY 2020.
The effects of the proposed rural floor with the
application of the national budget neutrality factor to the wage
index and the proposal to calculate the FY 2020 rural floor without
including the wage data of hospitals that have reclassified as rural
under Sec. 412.103.
The effects of the proposed frontier State wage index
adjustment under the statutory provision that requires hospitals
located in States that qualify as frontier States to not have a wage
index less than 1.0. This provision is not budget neutral.
The effects of the implementation of section
1886(d)(13) of the Act, as added by section 505 of Public Law 108-
173, which provides for an increase in a hospital's wage index if a
threshold percentage of residents of the county where the hospital
is located commute to work at hospitals in counties with higher wage
indexes for FY 2020. This provision is not budget neutral.
The effects of the proposals to increase the wage index
for hospitals with wage index values below the 25th percentile wage
index value (that is, the proposed lowest quartile wage index
adjustment), the associated proposal to decrease the wage index for
hospitals with wage index values above the 75th percentile wage
index value for budget neutrality purposes (that is, the proposed
highest quartile wage index adjustment), and to apply a transition
policy in FY 2020 pursuant to which a 5-percent cap would be placed
on any decrease in a hospital's wage index compared to its final FY
2019 wage index value (that is, the proposed 5-percent cap).
The total estimated change in payments based on the
proposed FY 2020 policies relative to payments based on FY 2019
policies, including estimated changes in outlier payments.
To illustrate the impact of the proposed FY 2020 changes, our
analysis begins with a FY 2019 baseline simulation model using: The
FY 2019 applicable percentage increase of 1.35 percent; the 0.5
percentage point adjustment required under section 414 of the MACRA
applied to the IPPS standardized amount; the FY 2019 MS-DRG GROUPER
(Version 36); the FY 2019 CBSA designations for hospitals based on
the OMB definitions from the 2010 Census; the FY 2019 wage index;
and no MGCRB reclassifications. Outlier payments are set at 5.1
percent of total operating MS-DRG and outlier payments for modeling
purposes.
Section 1886(b)(3)(B)(viii) of the Act, as added by section
5001(a) of Public Law 109-171, as amended by section 4102(b)(1)(A)
of the ARRA (Pub. L. 111-5) and by section 3401(a)(2) of the
Affordable Care Act (Pub. L. 111-148), provides that, for FY 2007
and each subsequent year through FY 2014, the update factor will
include a reduction of 2.0 percentage points for any subsection (d)
hospital that does not submit data on measures in a form and manner,
and at a time specified by the Secretary. Beginning in FY 2015, the
reduction is one-quarter of such applicable percentage increase
determined without regard to section 1886(b)(3)(B)(ix), (xi), or
(xii) of the Act, or one-quarter of the market basket update.
Therefore, for FY 2020, we are proposing that hospitals that do not
submit quality information under rules established by the Secretary
and that are meaningful EHR users under section 1886(b)(3)(B)(ix) of
the Act would receive an applicable percentage increase of 1.9
percent. At the time this impact was prepared, 39 hospitals are
estimated to not receive the full market basket rate-of-increase for
FY 2020 because they failed the quality data submission process or
did not choose to participate, but are meaningful EHR users. For
purposes of the simulations shown later in this section, we modeled
the proposed payment changes for FY 2020 using a reduced update for
these hospitals.
For FY 2020, in accordance with section 1886(b)(3)(B)(ix) of the
Act, a hospital that has been identified as not a meaningful EHR
user will be subject to a reduction of three-quarters of such
applicable percentage increase determined without regard to section
1886(b)(3)(B)(ix), (xi), or (xii) of the Act. Therefore, for FY
2020, we are proposing that hospitals that are identified as not
being meaningful EHR users and do submit quality information under
section 1886(b)(3)(B)(viii) of the Act would receive an applicable
[[Page 19623]]
percentage increase of 0.3 percent. At the time this impact analysis
was prepared, 211 hospitals are estimated to not receive the full
market basket rate-of-increase for FY 2020 because they are
identified as not meaningful EHR users that do submit quality
information under section 1886(b)(3)(B)(viii) of the Act. For
purposes of the simulations shown in this section, we modeled the
proposed payment changes for FY 2020 using a reduced update for
these hospitals.
Hospitals that are identified as not meaningful EHR users under
section 1886(b)(3)(B)(ix) of the Act and also do not submit quality
data under section 1886(b)(3)(B)(viii) of the Act would receive a
proposed applicable percentage increase of -0.5 percent, which
reflects a one-quarter reduction of the market basket update for
failure to submit quality data and a three-quarter reduction of the
market basket update for being identified as not a meaningful EHR
user. At the time this impact was prepared, 32 hospitals are
estimated to not receive the full market basket rate-of-increase for
FY 2020 because they are identified as not meaningful EHR users that
do not submit quality data under section 1886(b)(3)(B)(viii) of the
Act.
Each proposed policy change, statutory or otherwise, is then
added incrementally to this baseline, finally arriving at an FY 2020
model incorporating all of the proposed changes. This simulation
allows us to isolate the effects of each change.
Our comparison illustrates the proposed percent change in
payments per case from FY 2019 to FY 2020. Two factors not discussed
separately have significant impacts here. The first factor is the
proposed update to the standardized amount. In accordance with
section 1886(b)(3)(B)(i) of the Act, we are proposing to update the
standardized amounts for FY 2020 using a proposed applicable
percentage increase of 2.7 percent. This includes our forecasted
IPPS operating hospital market basket increase of 3.2 percent with a
proposed 0.5 percentage point reduction for the multifactor
productivity adjustment. Hospitals that fail to comply with the
quality data submission requirements and are meaningful EHR users
would receive a proposed update of 1.9 percent. This proposed update
includes a reduction of one-quarter of the market basket update for
failure to submit these data. Hospitals that do comply with the
quality data submission requirements but are not meaningful EHR
users would receive a proposed update of 0.3 percent, which includes
a reduction of three-quarters of the market basket update.
Furthermore, hospitals that do not comply with the quality data
submission requirements and also are not meaningful EHR users would
receive a proposed update of -0.5 percent. Under section
1886(b)(3)(B)(iv) of the Act, the update to the hospital-specific
amounts for SCHs and MDHs is also equal to the applicable percentage
increase, or 2.7 percent, if the hospital submits quality data and
is a meaningful EHR user.
A second significant factor that affects the proposed changes in
hospitals' payments per case from FY 2019 to FY 2020 is the change
in hospitals' geographic reclassification status from one year to
the next. That is, payments may be reduced for hospitals
reclassified in FY 2019 that are no longer reclassified in FY 2020.
Conversely, payments may increase for hospitals not reclassified in
FY 2019 that are reclassified in FY 2020.
2. Analysis of Table I
Table I displays the results of our analysis of the proposed
changes for FY 2020. The table categorizes hospitals by various
geographic and special payment consideration groups to illustrate
the varying impacts on different types of hospitals. The top row of
the table shows the overall impact on the 3,242 acute care hospitals
included in the analysis.
The next four rows of Table I contain hospitals categorized
according to their geographic location: All urban, which is further
divided into large urban and other urban; and rural. There are 2,476
hospitals located in urban areas included in our analysis. Among
these, there are 1,268 hospitals located in large urban areas
(populations over 1 million), and 1,208 hospitals in other urban
areas (populations of 1 million or fewer). In addition, there are
766 hospitals in rural areas. The next two groupings are by bed-size
categories, shown separately for urban and rural hospitals. The last
groupings by geographic location are by census divisions, also shown
separately for urban and rural hospitals.
The second part of Table I shows hospital groups based on
hospitals' FY 2020 payment classifications, including any
reclassifications under section 1886(d)(10) of the Act. For example,
the rows labeled urban, large urban, other urban, and rural show
that the numbers of hospitals paid based on these categorizations
after consideration of geographic reclassifications (including
reclassifications under sections 1886(d)(8)(B) and 1886(d)(8)(E) of
the Act that have implications for capital payments) are 2,188,
1,283, 905, and 1,054, respectively.
The next three groupings examine the impacts of the proposed
changes on hospitals grouped by whether or not they have GME
residency programs (teaching hospitals that receive an IME
adjustment) or receive Medicare DSH payments, or some combination of
these two adjustments. There are 2,127 nonteaching hospitals in our
analysis, 865 teaching hospitals with fewer than 100 residents, and
250 teaching hospitals with 100 or more residents.
In the DSH categories, hospitals are grouped according to their
DSH payment status, and whether they are considered urban or rural
for DSH purposes. The next category groups together hospitals
considered urban or rural, in terms of whether they receive the IME
adjustment, the DSH adjustment, both, or neither.
The next three rows examine the impacts of the proposed changes
on rural hospitals by special payment groups (SCHs, MDHs and RRCs).
There were 380 RRCs, 305 SCHs, 149 MDHs, 143 hospitals that are both
SCHs and RRCs, and 17 hospitals that are both MDHs and RRCs.
The next series of groupings are based on the type of ownership
and the hospital's Medicare utilization expressed as a percent of
total inpatient days. These data were taken from the FY 2017 or FY
2016 Medicare cost reports.
The next grouping concerns the geographic reclassification
status of hospitals. The first subgrouping is based on whether a
hospital is reclassified or not. The second and third subgroupings
are based on whether urban and rural hospitals were reclassified by
the MGCRB for FY 2020 or not, respectively. The fourth subgrouping
displays hospitals that reclassified from urban to rural in
accordance with section 1886(d)(8)(E) of the Act. The fifth
subgrouping displays hospitals deemed urban in accordance with
section 1886(d)(8)(B).
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BILLING CODE 4120-01-C
a. Effects of the Proposed Hospital Update and Other Proposed
Adjustments (Column 1)
As discussed in section IV.B. of the preamble of this proposed
rule, this column includes the proposed hospital update, including
the proposed 3.2 percent market basket update and the proposed
reduction of 0.5 percentage point for the multifactor productivity
adjustment. In addition, as discussed in section II.D. of the
preamble of this proposed rule, this column includes the FY 2020
+0.5 percentage point adjustment required under section 414 of the
MACRA. As a result, we are proposing to make a 3.2 percent update to
the national standardized amount. This column also includes the
proposed update to the hospital-specific rates which includes the
proposed 3.2 percent market basket update and the proposed
[[Page 19632]]
reduction of 0.5 percentage point for the multifactor productivity
adjustment. As a result, we are proposing to make a 2.7 percent
update to the hospital-specific rates.
Overall, hospitals would experience a 3.1 percent increase in
payments primarily due to the combined effects of the proposed
hospital update to the national standardized amount and the proposed
hospital update to the hospital-specific rate. Hospitals that are
paid under the hospital-specific rate would experience a 2.7 percent
increase in payments; therefore, hospital categories containing
hospitals paid under the hospital-specific rate would experience a
lower than average increase in payments.
b. Effects of the Proposed Changes to the MS-DRG Reclassifications and
Relative Cost-Based Weights With Recalibration Budget Neutrality
(Column 2)
Column 2 shows the effects of the proposed changes to the MS-
DRGs and relative weights with the application of the proposed
recalibration budget neutrality factor to the standardized amounts.
Section 1886(d)(4)(C)(i) of the Act requires us annually to make
appropriate classification changes in order to reflect changes in
treatment patterns, technology, and any other factors that may
change the relative use of hospital resources. Consistent with
section 1886(d)(4)(C)(iii) of the Act, we calculated a proposed
recalibration budget neutrality factor to account for the changes in
MS-DRGs and relative weights to ensure that the overall payment
impact is budget neutral.
As discussed in section II.E. of the preamble of this proposed
rule, the FY 2020 MS-DRG relative weights will be 100 percent cost-
based and 100 percent MS-DRGs. For FY 2020, the MS-DRGs are
calculated using the FY 2018 MedPAR data grouped to the proposed
Version 37 (FY 2020) MS-DRGs. The methodology to calculate the
proposed relative weights and the reclassification changes to the
GROUPER are described in more detail in section II.G. of the
preamble of this proposed rule.
The ``All Hospitals'' line in Column 2 indicates that proposed
changes due to the MS-DRGs and relative weights would result in a
0.0 percent change in payments with the application of the proposed
recalibration budget neutrality factor of 0.998768 to the
standardized amount. As discussed in section II.F.14. of the
preamble of this proposed rule, as a result of our comprehensive CC/
MCC analysis of the diagnosis codes, we proposed changes to the
severity levels of many codes. Hospital categories that generally
treat cases in the higher MS-DRG severity levels, such as large
urban hospitals, would experience a decrease in their payments,
while hospitals that generally treat fewer of these cases would
experience a slight increase in their payments under the proposed
relative weights. For example, rural hospitals would experience a
0.2 percent increase in payments in part because rural hospitals
tend to treat fewer cases in higher MS-DRG severity levels.
Conversely, teaching hospitals with more than 100 residents would
experience a slight decrease in payments of 0.1 percent as those
hospitals typically treat more cases in higher MS-DRG severity
levels.
c. Effects of the Proposed Wage Index Changes (Column 3)
Column 3 shows the impact of the proposed updated wage data
using FY 2016 cost report data, with the application of the proposed
wage budget neutrality factor. The wage index is calculated and
assigned to hospitals on the basis of the labor market area in which
the hospital is located. Under section 1886(d)(3)(E) of the Act,
beginning with FY 2005, we delineate hospital labor market areas
based on the Core Based Statistical Areas (CBSAs) established by
OMB. The current statistical standards used in FY 2020 are based on
OMB standards published on February 28, 2013 (75 FR 37246 and
37252), and 2010 Decennial Census data (OMB Bulletin No. 13-01), as
updated in OMB Bulletin Nos. 15-01 and 17-01. (We refer readers to
the FY 2015 IPPS/LTCH PPS final rule (79 FR 49951 through 49963) for
a full discussion on our adoption of the OMB labor market area
delineations, based on the 2010 Decennial Census data, effective
beginning with the FY 2015 IPPS wage index, to the FY 2017 IPPS/LTCH
PPS final rule (81 FR 56913) for a discussion of our adoption of the
CBSA updates in OMB Bulletin No. 15-01, which were effective
beginning with the FY 2017 wage index, and to the FY 2019 IPPS/LTCH
PPS final rule (83 FR 41362) for a discussion of our adoption of the
CBSA update in OMB Bulletin No. 17-01 for the FY 2019 wage index.)
Section 1886(d)(3)(E) of the Act requires that, beginning
October 1, 1993, we annually update the wage data used to calculate
the wage index. In accordance with this requirement, the proposed
wage index for acute care hospitals for FY 2020 is based on data
submitted for hospital cost reporting periods, beginning on or after
October 1, 2015 and before October 1, 2016. The estimated impact of
the updated wage data using the FY 2016 cost report data and the OMB
labor market area delineations on hospital payments is isolated in
Column 3 by holding the other proposed payment parameters constant
in this simulation. That is, Column 3 shows the proposed percentage
change in payments when going from a model using the FY 2019 wage
index, based on FY 2015 wage data, the labor-related share of 68.3
percent, under the OMB delineations and having a 100-percent
occupational mix adjustment applied, to a model using the proposed
FY 2020 pre-reclassification wage index based on FY 2016 wage data
with the labor-related share of 68.3 percent, under the OMB
delineations, also having a 100-percent occupational mix adjustment
applied, while holding other payment parameters, such as use of the
proposed Version 37 MS-DRG GROUPER constant. The proposed FY 2020
occupational mix adjustment is based on the CY 2016 occupational mix
survey.
In addition, the column shows the impact of the application of
the proposed wage budget neutrality to the national standardized
amount. In FY 2010, we began calculating separate wage budget
neutrality and recalibration budget neutrality factors, in
accordance with section 1886(d)(3)(E) of the Act, which specifies
that budget neutrality to account for wage index changes or updates
made under that subparagraph must be made without regard to the 62
percent labor-related share guaranteed under section
1886(d)(3)(E)(ii) of the Act. Therefore, for FY 2020, we are
proposing to calculate the proposed wage budget neutrality factor to
ensure that payments under updated wage data and the labor-related
share of 68.3 percent are budget neutral, without regard to the
lower labor-related share of 62 percent applied to hospitals with a
wage index less than or equal to 1.0. In other words, the wage
budget neutrality is calculated under the assumption that all
hospitals receive the higher labor-related share of the standardized
amount. The proposed FY 2020 wage budget neutrality factor is
1.000915 and the overall proposed payment change is 0 percent.
Column 3 shows the impacts of updating the wage data using FY
2016 cost reports. Overall, the new wage data and the labor-related
share, combined with the proposed wage budget neutrality adjustment,
would lead to no change for all hospitals, as shown in Column 3.
In looking at the wage data itself, the national average hourly
wage would increase 1.02 percent compared to FY 2019. Therefore, the
only manner in which to maintain or exceed the previous year's wage
index was to match or exceed the proposed 1.02 percent increase in
the national average hourly wage. Of the 3,204 hospitals with wage
data for both FYs 2019 and 2020, 1,620 or 50.6 percent would
experience an average hourly wage increase of 1.02 percent or more.
The following chart compares the shifts in wage index values for
hospitals due to the proposed changes in the average hourly wage
data for FY 2020 relative to FY 2019. Among urban hospitals, 3 would
experience a decrease of 10 percent or more, and 3 urban hospitals
would experience an increase of 10 percent or more. Sixty-three
urban hospitals would experience an increase or decrease of at least
5 percent or more but less than 10 percent. Among rural hospitals,
none would experience an increase of 10 percent or more, and none
would experience a decrease of 10 percent or more. Two rural
hospitals would experience an increase or decrease of at least 5
percent or more but less than 10 percent. However, 750 rural
hospitals would experience increases or decreases of less than 5
percent, while 2,381 urban hospitals would experience increases or
decreases of less than 5 percent. Two urban hospitals and 0 rural
hospitals would experience no change to their wage index. These
figures reflect proposed changes in the ``pre-reclassified,
occupational mix-adjusted wage index,'' that is, the wage index
before the application of geographic reclassification, the rural
floor, the out-migration adjustment, and other wage index exceptions
and adjustments. (We refer readers to sections III.G. through III.L.
of the preamble of this proposed rule for a complete discussion of
the exceptions and adjustments to the wage index.) We note that the
``post-reclassified wage index'' or ``payment wage index,'' which is
the wage index that includes all such exceptions and adjustments (as
reflected in Tables 2 and 3 associated with this proposed rule,
which are available via the internet on the CMS website) is used
[[Page 19633]]
to adjust the labor-related share of a hospital's standardized
amount, either 68.3 percent or 62 percent, depending upon whether a
hospital's wage index is greater than 1.0 or less than or equal to
1.0. Therefore, the proposed pre-reclassified wage index figures in
the following chart may illustrate a somewhat larger or smaller
proposed change than would occur in a hospital's payment wage index
and total payment.
The following chart shows the projected impact of proposed
changes in the area wage index values for urban and rural hospitals.
------------------------------------------------------------------------
Number of hospitals
Proposed FY 2020 percentage change in -------------------------------
area wage index values Urban Rural
------------------------------------------------------------------------
Increase 10 percent or more............. 3 0
Increase greater than or equal to 5 38 2
percent and less than 10 percent.......
Increase or decrease less than 5 percent 2,381 750
Decrease greater than or equal to 5 25 0
percent and less than 10 percent.......
Decrease 10 percent or more............. 3 0
Unchanged............................... 2 0
------------------------------------------------------------------------
d. Effects of MGCRB Reclassifications (Column 4)
Our impact analysis to this point has assumed acute care
hospitals are paid on the basis of their actual geographic location
(with the exception of ongoing policies that provide that certain
hospitals receive payments on bases other than where they are
geographically located). The proposed changes in Column 4 reflect
the per case payment impact of moving from this baseline to a
simulation incorporating the MGCRB decisions for FY 2020.
By spring of each year, the MGCRB makes reclassification
determinations that will be effective for the next fiscal year,
which begins on October 1. The MGCRB may approve a hospital's
reclassification request for the purpose of using another area's
wage index value. Hospitals may appeal denials of MGCRB decisions to
the CMS Administrator. Further, hospitals have 45 days from the date
the IPPS proposed rule is issued in the Federal Register to decide
whether to withdraw or terminate an approved geographic
reclassification for the following year (we refer readers to the
discussion of our clarification of this policy in section III.I.2.
of the preamble to this proposed rule.
The overall effect of geographic reclassification is required by
section 1886(d)(8)(D) of the Act to be budget neutral. Therefore,
for purposes of this impact analysis, we are proposing to apply an
adjustment of 0.986451 to ensure that the effects of the
reclassifications under sections 1886(d)(8)(B) and (C) and
1886(d)(10) of the Act are budget neutral (section II.A. of the
Addendum to this proposed rule). We note that, with regard to the
requirement under section 1886(d)(8)(C)(iii) of the Act, in our
calculation of the proposed budget neutrality adjustment of
0.986451, we applied the provisions of our proposal discussed in
section III.N. of the preamble of this proposed rule to exclude the
wage data of urban hospitals that have reclassified as rural under
section 1886(d)(8)(E) of the Act from the calculation of ``the wage
index for rural areas in the State in which the county is located''
(section II.A.4. of the Addendum to this proposed rule). Geographic
reclassification generally benefits hospitals in rural areas. We
estimate that the geographic reclassification would increase
payments to rural hospitals by an average of 1.0 percent. By region,
all the rural hospital categories would experience increases in
payments due to MGCRB reclassifications.
Table 2 listed in section VI. of the Addendum to this proposed
rule and available via the internet on the CMS website reflects the
reclassifications for FY 2020.
e. Effects of the Proposed Rural Floor, Including Application of
National Budget Neutrality (Column 5)
As discussed in section III.B. of the preamble of the FY 2009
IPPS final rule, the FY 2010 IPPS/RY 2010 LTCH PPS final rule, the
FYs 2011 through 2019 IPPS/LTCH PPS final rules, and this FY 2020
IPPS/LTCH PPS proposed rule, section 4410 of Public Law 105-33
established the rural floor by requiring that the wage index for a
hospital in any urban area cannot be less than the wage index
applicable to hospitals located in rural areas in the same State. We
will apply a uniform budget neutrality adjustment to the wage index.
Column 5 shows the effects of the proposed rural floor.
The Affordable Care Act requires that we apply one rural floor
budget neutrality factor to the wage index nationally. We have
calculated a proposed FY 2020 rural floor budget neutrality factor
to be applied to the wage index of 0.996316, which would reduce wage
indexes by 0.37 percent.
Column 5 shows the projected impact of the proposed rural floor
with the national rural floor budget neutrality factor applied to
the wage index based on the OMB labor market area delineations. The
column compares the post-reclassification FY 2020 wage index of
providers before the rural floor adjustment and the post-
reclassification FY 2020 wage index of providers with the rural
floor adjustment based on the OMB labor market area delineations.
Only urban hospitals can benefit from the rural floor. Because the
provision is budget neutral, all other hospitals (that is, all rural
hospitals and those urban hospitals to which the adjustment is not
made) would experience a decrease in payments due to the budget
neutrality adjustment that is applied nationally to their wage
index. We note that, as discussed in section III.N of the preamble
of this proposed rule, we are proposing to calculate the FY 2020
rural floor without including the wage data of hospitals that have
reclassified as rural under Sec. 412.103. This column reflects
effects of this proposed change to the rural floor calculation
methodology.
We estimate that 166 hospitals would receive the rural floor in
FY 2020. We note that there are approximately 87 fewer hospitals
receiving the proposed rural floor in FY 2020 than in FY 2019. This
is due, in part, to our proposal to calculate the rural floor for FY
2020 and subsequent fiscal years without including the wage data of
hospitals that have reclassified as rural under Sec. 412.103. This
proposal would impact States whose rural floors were heavily
influenced by the wage data of hospitals that reclassified under
Sec. 412.103, such as Massachusetts and Arizona. All IPPS hospitals
in our model would have their wage index reduced by the proposed
rural floor budget neutrality adjustment of 0.996316. We project
that, in aggregate, rural hospitals would experience a 0.1 percent
decrease in payments as a result of the application of the proposed
rural floor budget neutrality because the rural hospitals do not
benefit from the rural floor, but have their wage indexes downwardly
adjusted to ensure that the application of the rural floor is budget
neutral overall. We project that, in the aggregate, hospitals
located in urban areas would experience no change in payments
because increases in payments to hospitals benefitting from the
rural floor offset decreases in payments to nonrural floor urban
hospitals whose wage index is downwardly adjusted by the rural floor
budget neutrality factor. Urban hospitals in the New England region
would experience a 0.3 percent increase in payments primarily due to
the application of the rural floor in Massachusetts. Ten urban
providers in Massachusetts are expected to receive the rural floor
wage index value, including the rural floor budget neutrality
adjustment, which would increase payments overall to hospitals in
Massachusetts by an estimated $21 million. We estimate that
Massachusetts hospitals would receive approximately a 0.5 percent
increase in IPPS payments due to the application of the rural floor
in FY 2020.
Urban Puerto Rico hospitals are expected to experience a 0.2
percent increase in payments as a result of the application of the
proposed rural floor for FY 2020.
The table below shows a comparison of the payment impact of the
rural floor (with budget neutrality) by State based on the proposed
FY 2020 rural floor and the payment impact of the rural floor (with
budget neutrality) by State based on the FY 2019 rural floor.
Columns 1a through 4a in the table below reflect the FY 2019 rural
floor
[[Page 19634]]
calculation. The FY 2019 rural floor, as published in the October 3,
2018 Final Rule Correction Notice (83 FR 49836), was calculated by
including the wage data of hospitals that reclassified as rural
under Sec. 412.103. As indicated earlier, for FY 2020 and
subsequent fiscal years, we are proposing to calculate the rural
floor without including the wage data of hospitals that have
reclassified as rural under Sec. 412.103. Columns 1b through 4b in
the table below reflect this proposed FY 2020 rural floor
calculation. Columns 1a and 1b of the table display the number of
IPPS hospitals located in each State in FY 2019 and FY 2020,
respectively. Columns 2a and 2b display the number of hospitals in
each State that received the rural floor wage index for FY 2019
(column 2a) and those that would receive the rural floor wage index
for FY 2020 (column 2b). Columns 3a and 3b display the percentage
change in total payments to hospitals in each State due to the
application of the rural floor with national budget neutrality for
FY 2019 (column 3a) and FY 2020 (column 3b). To show the percentage
change in total payments for FY 2019 and FY 2020, in columns 3a and
3b, respectively, we calculated total payments using the post-
reclassification wage index of providers prior to the rural floor
adjustment and total payments using the post-reclassification wage
index of providers with the rural floor adjustment for FY 2019 and
FY 2020, respectively. The differences in those payments are
reflected in columns 3a and 3b. Columns 4a and 4b display the
payment amount that hospitals in each State would gain or lose due
to the application of the FY 2019 rural floor with national budget
neutrality (column 4a) and the estimated payment amount that
hospitals in each State would gain or lose due to the application of
the proposed FY 2020 rural floor with national budget neutrality
(column 4b). We note that columns 2b, 3b, and 4b of this table do
not include the application of the proposal to increase the wage
index for hospitals with a wage index value below the 25th
percentile wage index, the associated budget neutrality proposal to
decrease the wage index for hospitals with a wage index value above
the 75th percentile wage index, or the proposed 5-percent cap.
BILLING CODE 4120-01-P
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BILLING CODE 4120-01-C
f. Effects of the Application of the Proposed Frontier State Wage Index
and Proposed Out-Migration Adjustment (Column 6)
This column shows the combined effects of the application of
section 10324(a) of the Affordable Care Act, which requires that we
establish a minimum post-reclassified wage index of 1.00 for all
hospitals located in ``frontier States,'' and the effects of section
1886(d)(13) of the Act, as added by section 505 of Public Law 108-
173, which provides for an increase in the wage index for hospitals
located in certain counties that have a relatively high percentage
of hospital employees who reside in the county, but work in a
different area with a higher wage index. These two wage index
provisions are not budget neutral and would increase
[[Page 19638]]
payments overall by 0.1 percent compared to the provisions not being
in effect.
The term ``frontier States'' is defined in the statute as States
in which at least 50 percent of counties have a population density
less than 6 persons per square mile. Based on these criteria, 5
States (Montana, Nevada, North Dakota, South Dakota, and Wyoming)
are considered frontier States and 45 hospitals located in those
States would receive a frontier wage index of 1.0000. Overall, this
provision is not budget neutral and is estimated to increase IPPS
operating payments by approximately $63 million. Urban hospitals
located in the West North Central region would experience an
increase in payments by 0.6 percent, because many of the hospitals
located in this region are frontier State hospitals.
In addition, section 1886(d)(13) of the Act, as added by section
505 of Public Law 108-173, provides for an increase in the wage
index for hospitals located in certain counties that have a
relatively high percentage of hospital employees who reside in the
county, but work in a different area with a higher wage index.
Hospitals located in counties that qualify for the payment
adjustment will receive an increase in the wage index that is equal
to a weighted average of the difference between the wage index of
the resident county, post-reclassification and the higher wage index
work area(s), weighted by the overall percentage of workers who are
employed in an area with a higher wage index. There are an estimated
171 providers that would receive the out-migration wage adjustment
in FY 2020. Rural hospitals generally would qualify for the
adjustment, resulting in a 0.1 percent increase in payments. This
provision appears to benefit section 401 hospitals and RRCs in that
they would each experience a 0.2 percent increase in payments. This
out-migration wage adjustment also is not budget neutral, and we
estimate the impact of these providers receiving the out-migration
increase would be approximately $40 million.
g. Effects of Application of the Proposed Lowest Quartile and Highest
Quartile Wage Index Policies and Proposed 5-Percent Transition
Column 7 shows the effects of the proposed wage index adjustment
for hospitals with a wage index value below the 25th percentile wage
index value, the associated budget neutrality proposal to decrease
the wage index for hospitals with a wage index value above the 75th
percentile wage index, and the proposed transition policy placing a
5-percent cap for FY 2020 on any decrease in a hospital's wage index
from its final FY 2019 wage index. As discussed in section III.N. of
the preamble to this proposed rule, we are proposing that hospitals
with a wage index value below the 25th percentile wage index value
would receive an increase to their wage index value of half the
difference between the otherwise applicable final wage index value
for a year for that hospital and the 25th percentile wage index
value for that year across all hospitals. We also are proposing to
decrease the wage index for hospitals with a wage index value above
the 75th percentile in order to ensure our proposed increase to the
wage index for hospitals with a wage index value below the 25th
percentile is budget neutral. In addition, for FY 2020, we are
proposing to apply a 5-percent cap on any decrease in a hospital's
wage index from the hospital's final wage index in FY 2019 (which
would include any decrease resulting from our proposal to not
include urban to rural reclassifications in the rural floor
calculation).
We are proposing that the overall effect of the application of
the proposed wage index adjustment for hospitals with a wage index
value below the 25th percentile would be budget neutral. In order to
ensure that the overall effect of the application of the proposed
wage index adjustment for hospitals with a wage index value below
the 25th percentile is budget neutral, we are proposing to reduce
the wage index of hospitals with wage index values above the 75th
percentile by a constant factor of the difference between the
hospital's otherwise applicable wage index and the 75th percentile
(as described in section III.N.3.b. of this proposed rule). In
addition, we are proposing to implement the proposed 5-percent cap
on any decrease in a hospital's wage index in a budget neutral
manner under the authority at section 1886(d)(5)(I) of the Act.
Therefore, for purposes of this impact analysis, we are proposing to
apply a budget neutrality adjustment factor of 0.998349 to the FY
2020 standardized amount to implement the proposed 5-percent cap in
a budget neutral manner.
To show the effects of the proposed lowest and highest quartile
wage index adjustments and the proposed 5-percent cap, column 7
compares payments calculated with the FY 2020 proposed wage index
prior to the application of: (a) The proposed adjustment for
hospitals with a wage index value below the 25th percentile; (b) the
proposed adjustment for hospitals with a wage index value above the
75th percentile; and (c) the proposed 5-percent cap on any decrease
in a hospital's wage index to payments calculated using the FY 2020
proposed wage index with the above mentioned adjustments applied
(that is, the proposed lowest quartile wage index adjustment, the
proposed highest quartile wage index adjustment, and the proposed 5-
percent cap). The combined effect of these three proposals generally
benefits hospitals in rural areas. For example, we estimate that the
proposed adjustments for hospitals with a wage index value below the
25th percentile wage index and above the 75th percentile wage index
and the proposed 5-percent cap on any decrease in a hospital's wage
index would increase payments to rural hospitals by an average of
0.4 percent. By region, rural South Atlantic and West South Central
hospital categories would experience increases in payments by 0.7
and 0.8 percent, respectively. Puerto Rico providers would
experience a 12.7 percent increase in payments due to the
application of the proposed lowest quartile wage index adjustment
because they generally have the lowest wage index values.
h. Effects of All FY 2020 Proposed Changes (Column 8)
Column 8 shows our estimate of the proposed changes in payments
per discharge from FY 2019 and FY 2020, resulting from all proposed
changes reflected in this proposed rule for FY 2020. It includes
combined effects of the year-to-year change of the previous columns
in the table.
The proposed average increase in payments under the IPPS for all
hospitals is approximately 3.5 percent for FY 2020 relative to FY
2019 and for this row is primarily driven by the proposed changes
reflected in Column 1. Column 8 includes the proposed annual
hospital update of 2.7 percent to the national standardized amount.
This proposed annual hospital update includes the proposed 3.2
percent market basket update and the proposed 0.5 percentage point
reduction for the multifactor productivity adjustment. As discussed
in section II.D. of the preamble of this proposed rule, this column
also includes the +0.5 percentage point adjustment required under
section 414 of the MACRA. Hospitals paid under the hospital-specific
rate would receive a 2.7 percent hospital update. As described in
Column 1, the proposed annual hospital update with the proposed +0.5
percent adjustment for hospitals paid under the national
standardized amount, combined with the proposed annual hospital
update for hospitals paid under the hospital-specific rates, would
result in a 3.5 percent increase in payments in FY 2020 relative to
FY 2019. This estimated increase also reflects an estimated increase
in outlier payments of 0.5 percent (from our current estimate of FY
2019 outlier payments of approximately 4.6 percent to 5.1 percent
projected for FY 2020 based on the FY 2018 MedPAR data used for this
proposed rule calculated for purposes of this impact analysis).
There are also interactive effects among the various factors
comprising the payment system that we are not able to isolate, which
contribute to our estimate of the proposed changes in payments per
discharge from FY 2019 and FY 2020 in Column 8.
Overall payments to hospitals paid under the IPPS due to the
proposed applicable percentage increase and proposed changes to
policies related to MS-DRGs, geographic adjustments, and outliers
are estimated to increase by 3.5 percent for FY 2020. Hospitals in
urban areas would experience a 3.5 percent increase in payments per
discharge in FY 2020 compared to FY 2019. Hospital payments per
discharge in rural areas are estimated to increase by 3.6 percent in
FY 2020.
3. Impact Analysis of Table II
Table II below presents the projected impact of the proposed
changes for FY 2020 for urban and rural hospitals and for the
different categories of hospitals shown in Table I. It compares the
estimated average payments per discharge for FY 2019 with the
estimated proposed average payments per discharge for FY 2020, as
calculated under our models. Therefore, this table presents, in
terms of the average dollar amounts paid per discharge, the combined
effects of the proposed changes presented in Table I. The estimated
percentage changes shown in the last column of Table II equal the
estimated percentage changes in average payments per discharge from
Column 8 of Table I.
[[Page 19639]]
Table II--Impact Analysis of Proposed Changes for FY 2020 Acute Care Hospital Operating Prospective Payment
System
[Payments per discharge]
----------------------------------------------------------------------------------------------------------------
Estimated Estimated
Number of average FY 2019 proposed average Proposed FY 2020
hospitals payment per FY 2020 payment changes
discharge per discharge
(1) (2) (3) (4)
----------------------------------------------------------------------------------------------------------------
All Hospitals....................... 3,242 12,722 13,169 3.5
By Geographic Location:
Urban hospitals................. 2,476 13,083 13,542 3.5
Large urban areas............... 1,268 13,512 13,965 3.4
Other urban areas............... 1,208 12,695 13,161 3.7
Rural hospitals................. 766 9,507 9,850 3.6
Bed Size (Urban):
0-99 beds....................... 643 10,365 10,742 3.6
100-199 beds.................... 759 10,799 11,166 3.4
200-299 beds.................... 431 11,908 12,312 3.4
300-499 beds.................... 424 13,186 13,657 3.6
500 or more beds................ 219 16,176 16,753 3.6
Bed Size (Rural):
0-49 beds....................... 302 8,138 8,538 4.9
50-99 beds...................... 272 9,070 9,397 3.6
100-149 beds.................... 108 9,396 9,747 3.7
150-199 beds.................... 45 10,063 10,390 3.2
200 or more beds................ 39 10,995 11,322 3
Urban by Region:
New England..................... 112 14,419 14,659 1.7
Middle Atlantic................. 307 14,637 15,087 3.1
South Atlantic.................. 399 11,666 12,077 3.5
East North Central.............. 386 12,317 12,756 3.6
East South Central.............. 147 10,956 11,448 4.5
West North Central.............. 157 12,618 13,145 4.2
West South Central.............. 375 12,087 12,511 3.5
Mountain........................ 169 13,474 13,882 3
Pacific......................... 374 16,369 17,036 4.1
Puerto Rico..................... 50 10,011 11,372 13.6
Rural by Region:
New England..................... 20 13,020 13,315 2.3
Middle Atlantic................. 53 9,462 9,752 3.1
South Atlantic.................. 120 8,832 9,146 3.6
East North Central.............. 114 9,728 10,054 3.4
East South Central.............. 150 8,378 8,742 4.3
West North Central.............. 93 10,140 10,479 3.3
West South Central.............. 142 8,346 8,718 4.5
Mountain........................ 50 11,616 12,004 3.3
Pacific......................... 24 13,038 13,511 3.6
By Payment Classification:
Urban hospitals................. 2,188 12,808 13,259 3.5
Large urban areas............... 1,283 13,500 13,953 3.4
Other urban areas............... 905 11,827 12,276 3.8
Rural areas..................... 1,054 12,489 12,927 3.5
Teaching Status:
Nonteaching..................... 2,127 10,470 10,844 3.6
Fewer than 100 residents........ 865 12,053 12,476 3.5
100 or more residents........... 250 18,611 19,257 3.5
Urban DSH:
Non-DSH......................... 538 10,979 11,389 3.7
100 or more beds................ 1,393 13,225 13,687 3.5
Less than 100 beds.............. 352 9,704 10,035 3.4
Rural DSH:
SCH............................. 256 10,588 10,908 3
RRC............................. 442 13,267 13,735 3.5
100 or more beds................ 31 10,829 11,142 2.9
Less than 100 beds.............. 230 7,737 8,133 5.1
Urban teaching and DSH:
Both teaching and DSH........... 776 14,386 14,889 3.5
Teaching and no DSH............. 84 12,239 12,692 3.7
No teaching and DSH............. 969 10,835 11,213 3.5
No teaching and no DSH.......... 359 10,155 10,550 3.9
Special Hospital Types:
[[Page 19640]]
RRC............................. 380 13,332 13,821 3.7
SCH............................. 305 11,467 11,819 3.1
MDH............................. 149 8,369 8,702 4
SCH and RRC..................... 143 11,736 12,080 2.9
MDH and RRC..................... 17 10,287 10,553 2.6
Type of Ownership:
Voluntary....................... 1,893 12,819 13,266 3.5
Proprietary..................... 852 11,212 11,618 3.6
Government...................... 496 14,213 14,720 3.6
Medicare Utilization as a Percent of
Inpatient Days:
0-25............................ 596 15,799 16,342 3.4
25-50........................... 2,122 12,520 12,966 3.6
50-65........................... 414 10,126 10,455 3.2
Over 65......................... 73 7,473 8,010 7.2
FY 2020 Reclassifications by the
Medicare Geographic Classification
Review Board:
All Reclassified Hospitals...... 957 12,966 13,401 3.4
Non-Reclassified Hospitals...... 2,285 12,583 13,038 3.6
Urban Hospitals Reclassified.... 679 13,560 14,013 3.3
Urban Non-reclassified Hospitals 1,753 12,808 13,271 3.6
Rural Hospitals Reclassified 278 9,767 10,100 3.4
Full Year......................
Rural Non-reclassified Hospitals 441 9,158 9,519 4
Full Year......................
All Section 401 Reclassified 335 14,090 14,579 3.5
Hospitals:.....................
Other Reclassified Hospitals 47 9,292 9,606 3.4
(Section 1886(d)(8)(B))........
----------------------------------------------------------------------------------------------------------------
H. Effects of Other Proposed Policy Changes
In addition to those proposed policy changes discussed
previously that we are able to model using our IPPS payment
simulation model, we are proposing to make various other changes in
this proposed rule. As noted in section I.G. of this regulatory
impact analysis, our payment simulation model uses the most recent
available claims data to estimate the impacts on payments per case
of certain proposed changes in this proposed rule. Generally, we
have limited or no specific data available with which to estimate
the impacts of these proposed changes using that payment simulation
model. For those proposed changes, we have attempted to predict the
payment impacts based upon our experience and other more limited
data. Our estimates of the likely impacts associated with these
other proposed changes are discussed in this section.
1. Effects of Proposed Policies Relating to New Medical Service and
Technology Add-On Payments
a. Proposed FY 2020 Status of Technologies Approved for FY 2019 New
Technology Add-On Payments
In section II.H. of the preamble to this proposed rule, we
discuss 17 technologies for which we received applications for add-
on payments for new medical services and technologies for FY 2020,
as well as the status of the new technologies that were approved to
receive new technology add-on payments in FY 2019. We note that one
applicant withdrew its application prior to the issuance of this
proposed rule. As explained in the preamble to this proposed rule,
add-on payments for new medical services and technologies under
section 1886(d)(5)(K) of the Act are not required to be budget
neutral. As discussed in section II.H.5. of the preamble of this
proposed rule, we have not yet determined whether any of the 17
technologies discussed in that section will meet the specified
criteria for new technology add-on payments for FY 2020.
Consequently, it is premature to estimate the potential payment
impact of these 17 technologies for any potential new technology
add-on payments for FY 2020. We note that if any of the 17
technologies are found to be eligible for new technology add-on
payments for FY 2020, in the FY 2020 IPPS/LTCH PPS final rule, we
would discuss the estimated payment impact for FY 2020.
In section II.H.4. of the preamble of this proposed rule, we are
proposing to discontinue new technology add-on payments for
Defitelio[supreg] (Defibrotide), Ustekinumab (Stelara[supreg]) and
Bezlotoxumab (ZinplavaTM) for FY 2020 because these
technologies will have been on the U.S. market for 3 years. We also
are proposing to continue to make new technology add-on payments for
AndexXaTM, the AQUABEAM System (Aquablation),
GIAPREZATM, KYMRIAH[supreg] and YESCARTA[supreg], the
remed[emacr][supreg] System, the Sentinel[supreg] Cerebral
Protection System, VABOMERETM, VYXEOSTM, and
ZEMDRITM in FY 2020 because these technologies would
still be considered new for purposes of new technology add-on
payments. Under our proposed change to the calculation of the new
technology add-on payments, the new technology add-on payment for
each case would be limited to the lesser of: (1) 65 Percent of the
costs of the new technology; or (2) 65 percent of the amount by
which the costs of the case exceed the standard MS-DRG payment for
the case. Because it is difficult to predict the actual new
technology add-on payment for each case, our estimates below are
based on the increase in new technology add-on payments for FY 2020
as if every claim that would qualify for a new technology add-on
payment would receive the maximum add-on payment. The following are
estimates for FY 2020 for the 9 technologies for which we are
proposing to continue to make new technology add-on payments in FY
2020:
Based on the applicant's estimate from FY 2019, we
currently estimate that new technology add-on payments for
AndexXaTM would increase overall FY 2020 payments by
$98,755,313 (maximum add-on payment of $18,281.25 * 5,402 patients).
Based on the applicant's estimate from FY 2019, we
currently estimate that new technology add-on payments for the
AQUABEAM System (Aquablation) would increase overall FY 2020
payments by $677,625 (maximum add-on payment of $1,625 * 417
patients).
Based on the applicant's estimate for FY 2019, we
currently estimate that new
[[Page 19641]]
technology add-on payments for GIAPREZATM would increase
overall FY 2020 payments by $11,173,500 (maximum add-on payment of
$1,950 * 5,730 patients).
Based on both applicants' estimates of the average cost
for an administered dose for FY 2019, we currently estimate that new
technology add-on payments for KYMRIAH[supreg] and YESCARTA[supreg]
would increase overall FY 2020 payments by $93,585,700 (maximum add-
on payment of $242,450 * 386 patients).
Based on the applicant's estimate for FY 2019, we
currently estimate that new technology add-on payments for
Sentinel[supreg] Cerebral Protection System would increase overall
FY 2020 payments by $11,830,000 (maximum add-on payment of $1,820 *
6,500 patients).
Based on the applicant's estimate for FY 2019, we
currently estimate that new technology add-on payments for the
remed[emacr][supreg] System would increase overall FY 2020 payments
by $1,794,000 (maximum add-on payment of $22,425 * 80 patients).
Based on the applicant's estimate for FY 2019, we
currently estimate that new technology add-on payments for
VABOMERETM would increase overall FY 2020 payments by
$19,084,666 (maximum add-on payment of $7,207.20 * 2,648 patients).
Based on the applicant's estimate for FY 2019, we
currently estimate that new technology add-on payments for
VYXEOSTM would increase overall FY 2020 payments by
$45,458,400 (maximum add-on payment of $47,352.50 * 960 patients).
Based on the applicant's estimate for FY 2019, we
currently estimate that new technology add-on payments for
ZEMDRITM would increase overall FY 2020 payments by
$8,848,125 (maximum add-on payment of $3,539.25 * 2,500 patients).
b. Proposed Alternative Inpatient New Technology Add-On Payment Pathway
for Transformative New Devices
In section II.H.8. of the preamble of this proposed rule, we
discuss our proposed alternative inpatient new technology add-on
payment pathway for certain new technologies. Specifically, we are
proposing that, for applications received for IPPS new technology
add-on payments for FY 2021 and subsequent fiscal years, if a
medical device is part of the FDA's Breakthrough Devices Program and
received FDA market authorization, such a device would be considered
new and not substantially similar to an existing technology for
purposes of new technology add-on payment under the IPPS. We also
are proposing that the medical device would not need to meet the
requirement under Sec. 412.87(b)(1) that it represent an advance
that substantially improves, relative to technologies previously
available, the diagnosis or treatment of Medicare beneficiaries.
Given the relatively recent introduction of the Breakthrough
Devices Program, there have not been any medical devices that were
part of the Breakthrough Devices Program and received FDA market
authorization, and that applied for a new technology add-on payment
under the IPPS and were not approved. If all of the future new
transformative medical devices that would have applied for new
technology add-on payments would have been approved under the
existing criteria, this proposal has no impact. To the extent that
there are future medical devices that are the subject of
applications for new technology add-on payments, and those
applications would have been denied under the current new technology
add-on payment criteria, this proposal is a cost, but that cost is
not estimable. We also note that as this proposal, if finalized,
would be effective beginning with new technology add-on payment
applications for FY 2021, there would be no impact of this proposal
in FY 2020.
c. Proposed Changes to the Calculation of the Inpatient New Technology
Add-On Payment
In section II.H.9. of the preamble of this proposed rule, we
discuss our proposal to modify the current new technology add-on
payment mechanism to increase the amount of the maximum add-on
payment amount to 65 percent. Specifically, we are proposing that if
the costs of a discharge (determined by applying CCRs as described
in Sec. 412.84(h)) exceed the full DRG payment (including payments
for IME and DSH, but excluding outlier payments), Medicare would
make an add-on payment equal to the lesser of: (1) 65 percent of the
costs of the new medical service or technology; or (2) 65 percent of
the amount by which the costs of the case exceed the standard DRG
payment. Unless the discharge qualifies for an outlier payment, the
additional Medicare payment would be limited to the full MS-DRG
payment plus 65 percent of the estimated costs of the new technology
or medical service.
As discussed above, it is premature to estimate the potential
payment impact for any potential new technology add-on payments for
FY 2020 of the 17 technologies discussed in section II.H.5. of the
preamble of this proposed rule because we have not yet determined
whether any of these technologies will meet the specified criteria
for new technology add-on payments for FY 2020. However, for
purposes of estimating the impact of our proposed changes to the
calculation of the inpatient new technology add-on payment, we are
including the estimated increase in FY 2020 new technology add-on
payments if we determine that all 17 of the technologies discussed
in that section meet the specified criteria for new technology add-
on payments for FY 2020. We estimate that if we finalize our
proposals for the 9 technologies for which we are proposing to
continue to make new technology add-on payments in FY 2020 and if we
determine that all 17 of the FY 2020 new technology add-on payment
applications meet the specified criteria for new technology add-on
payments for FY 2020, proposed changes to the calculation of the
inpatient new technology add-on payment, if finalized, would
increase IPPS spending by approximately $110 million in FY 2020.
2. Effects of Proposed Changes to MS-DRGs Subject to the Postacute Care
Transfer Policy and the MS-DRG Special Payment Policy
In section IV.A. of the preamble of this proposed rule, we
discuss our proposed changes to the list of MS-DRGs subject to the
postacute care transfer policy and the MS-DRG special payment policy
for FY 2020. As reflected in Table 5 listed in section VI. of the
Addendum to this proposed rule (which is available via the internet
on the CMS website), using criteria set forth in regulations at 42
CFR 412.4, we evaluated MS-DRG charge, discharge, and transfer data
to determine which proposed new or revised MS-DRGs would qualify for
the postacute care transfer and MS-DRG special payment policies. As
a result of our proposals to revise the MS-DRG classifications for
FY 2020, which are discussed in section II.F. of the preamble of
this proposed rule, we are proposing to remove two MS-DRGs from the
list of MS-DRGs that would be subject to the postacute care transfer
policy and the MS-DRG special payment policy. Column 2 of Table I in
this Appendix A shows the effects of the proposed changes to the MS-
DRGs and the proposed relative payment weights and the application
of the proposed recalibration budget neutrality factor to the
standardized amounts. Section 1886(d)(4)(C)(i) of the Act requires
us annually to make appropriate DRG classification changes in order
to reflect changes in treatment patterns, technology, and any other
factors that may change the relative use of hospital resources. The
analysis and methods for determining the changes due to the MS-DRGs
and relative payment weights account for and include changes as a
result of the proposed changes to the MS-DRGs subject to the MS-DRG
postacute care transfer and MS-DRG special payment policies. We
refer readers to section I.G. of this Appendix A for a detailed
discussion of payment impacts due to the proposed MS-DRG
reclassification policies for FY 2020.
3. Effects of Low-Volume Hospital Payment Adjustment Policy
In section IV.D. of the preamble of this proposed rule, we
discuss the low-volume hospital payment policy for FY 2020.
Specifically, to qualify for the low-volume hospital payment
adjustment, a hospital must be located more than 15 road miles from
another subsection (d) hospital and have less than 3,800 total
discharges during the fiscal year based on the hospital's most
recently submitted cost report. The low-volume hospital payment
adjustment is a per-discharge payment adjustment calculated as
follows:
25 percent for low-volume hospitals with 500 or fewer
total discharges;
(95/330)-(number of total discharges/13,200) for low-
volume hospitals with fewer than 3,800 discharges but more than 500
discharges.
Based upon the best available data at this time, we estimate
payments made under the low-volume hospital payment adjustment
policy would increase Medicare payments by $25 million in FY 2020 as
compared to FY 2019. More specifically, in FY 2020, we estimate that
588 providers would receive approximately $439 million compared to
our estimate of 588 providers receiving approximately $414 million
in FY 2019. These payment estimates were determined by identifying
providers that, based on the best available data, qualify in FY 2019
(that is, are located at least 15 miles from the nearest
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subsection (d) hospital and have less than 3,800 total discharges).
4. Effects of the Proposed Changes to Medicare DSH and Uncompensated
Care Payments for FY 2020
As discussed in section IV.F. of the preamble of this proposed
rule, under section 3133 of the Affordable Care Act, hospitals that
are eligible to receive Medicare DSH payments will receive 25
percent of the amount they previously would have received under the
statutory formula for Medicare DSH payments under section
1886(d)(5)(F) of the Act. The remainder, equal to an estimate of 75
percent of what formerly would have been paid as Medicare DSH
payments (Factor 1), reduced to reflect changes in the percentage of
uninsured individuals and any additional statutory adjustment
(Factor 2), is available to make additional payments to each
hospital that qualifies for Medicare DSH payments and that has
uncompensated care. Each hospital eligible for Medicare DSH payments
will receive an additional payment based on its estimated share of
the total amount of uncompensated care for all hospitals eligible
for Medicare DSH payments. The uncompensated care payment
methodology has redistributive effects based on the proportion of a
hospital's amount of uncompensated care relative to the aggregate
amount of uncompensated care of all hospitals eligible for Medicare
DSH payments (Factor 3). The change to Medicare DSH payments under
section 3133 of the Affordable Care Act is not budget neutral.
In this proposed rule, we are proposing to establish the amount
to be distributed as uncompensated care payments to DSH eligible
hospitals, which for FY 2020 is $8,488,517,726.22. This figure
represents 75 percent of the amount that otherwise would have been
paid for Medicare DSH payment adjustments adjusted by a proposed
Factor 2 of 67.14 percent. For FY 2019, the amount available to be
distributed for uncompensated care was $8,272,872,447.22, or 75
percent of the amount that otherwise would have been paid for
Medicare DSH payment adjustments adjusted by a Factor 2 of 67.51
percent. To calculate Factor 3 for FY 2020, we are proposing to use
hospitals' FY 2015 cost reports from the HCRIS database, as updated
through February 15, 2019, Medicaid days from hospitals' FY 2013
cost reports from the same extract of HCRIS, and SSI days from the
FY 2017 SSI ratios. For each eligible hospital, with the exception
of Puerto Rico hospitals and Indian Health Service and Tribal
hospitals, we calculated a Factor 3 using information on
uncompensated care costs from cost reports for FY 2015. To calculate
Factor 3 for Puerto Rico hospitals and Indian Health Service and
Tribal hospitals, we used data regarding low-income insured days for
FY 2013. For a complete discussion of the proposed methodology for
calculating Factor 3, we refer readers to section IV.F.4. of the
preamble of this proposed rule.
To estimate the impact of the combined effect of proposed
changes in Factors 1 and 2, as well as the changes to the data used
in determining Factor 3, on the calculation of Medicare
uncompensated care payments, we compared total uncompensated care
payments estimated in the FY 2019 IPPS/LTCH PPS final rule to total
uncompensated care payments estimated in this FY 2020 IPPS/LTCH PPS
proposed rule. For FY 2019, we calculated 75 percent of the
estimated amount that would be paid as Medicare DSH payments absent
section 3133 of the Affordable Care Act, adjusted by a Factor 2 of
67.51 percent and multiplied by a Factor 3 calculated using the
methodology described in the FY 2019 IPPS/LTCH PPS final rule. For
FY 2020, we calculated 75 percent of the estimated amount that would
be paid as Medicare DSH payments absent section 3133 of the
Affordable Care Act, adjusted by a proposed Factor 2 of 67.14
percent and multiplied by a Factor 3 calculated using the proposed
methodology described previously.
Our analysis included 2,430 hospitals that are projected to be
eligible for DSH in FY 2020. It did not include hospitals that
terminated their participation from the Medicare program as of
January 1, 2019, Maryland hospitals, new hospitals, MDHs, and SCHs
that are expected to be paid based on their hospital-specific rates.
The 29 hospitals participating in the Rural Community Hospital
Demonstration Program were excluded from this analysis, as
participating hospitals are not eligible to receive empirically
justified Medicare DSH payments and uncompensated care payments. In
addition, the data from merged or acquired hospitals were combined
under the surviving hospital's CMS certification number (CCN), and
the nonsurviving CCN was excluded from the analysis. The estimated
impact of the proposed changes in Factors 1, 2, and 3 on
uncompensated care payments across all hospitals projected to be
eligible for DSH payments in FY 2020, by hospital characteristic, is
presented in the following table.
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Proposed changes in projected FY 2020 uncompensated care
payments from payments in FY 2019 are driven by a proposed increase
in Factor 1 and a proposed decrease in Factor 2, as well as by a
decrease in the number of hospitals projected to be eligible to
receive DSH in FY 2020 relative to FY 2019. Proposed Factor 1 has
increased from $12.254 billion to $12.643 billion, and the proposed
percent change in the percent of individuals who are uninsured
(Factor 2) has decreased from 67.51 percent to 67.14 percent. Based
on the proposed changes in these two factors, the impact analysis
found that, across all projected DSH eligible hospitals, proposed FY
2020 uncompensated care payments are estimated at approximately
$8.489 billion, or a proposed increase of approximately 2.61 percent
from FY 2019 uncompensated care payments (approximately $8.273
billion). While these proposed changes would result in a net
increase in the amount available to be distributed in uncompensated
care payments, the projected payment increases vary by hospital
type. This redistribution of uncompensated care payments is caused
by proposed changes in Factor 3. As seen in the above table, percent
increases smaller than 2.61 percent indicate that hospitals within
the specified category are projected to experience a smaller
increase in uncompensated care payments, on average, compared to the
universe of projected FY 2020 DSH hospitals. Conversely, percent
increases that are greater than 2.61 percent indicate a hospital
type is projected to have a larger increase than the overall
average. The variation in the distribution of payments by hospital
characteristic is largely dependent on a given hospital's
uncompensated care costs as reported in the Worksheet S-10, or
number of Medicaid days and SSI days for Puerto Rico hospitals and
Indian Health Service and Tribal hospitals, used in the Factor 3
computation.
Rural hospitals, in general, are projected to experience
significantly larger increases in uncompensated care payments than
their urban counterparts. Overall, rural hospitals are projected to
receive a 22.90 percent increase in uncompensated care payments,
while urban hospitals are projected to receive a 1.39 percent
increase in uncompensated care payments.
By bed size, smaller hospitals are projected to receive larger
increases in uncompensated care payments than larger hospitals, in
both rural and urban settings. Rural hospitals with 0-99 beds are
projected to receive a 31.08 percent payment increase, rural
hospitals with 100-249 beds are projected to receive a 15.35 percent
increase, and larger rural hospitals with 250+ beds are projected to
receive a 13.52 percent payment increase. These increases for rural
hospitals are all greater than the overall hospital average. This
trend is also generally true for urban hospitals, with the smallest
urban hospitals (0-99 beds) projected to receive an increase in
uncompensated care payments of 25.79 percent, and urban hospitals
with 100-249 beds projected to receive an increase of 7.15 percent,
both of which are greater than the overall average. Larger urban
hospitals with 250+ beds are projected to receive a 1.65 percent
decrease in uncompensated care payments.
By region, rural hospitals are expected to receive a wide range
of payment increases, except for those in New England, which are
projected to receive a decrease in uncompensated care payments.
Rural hospitals in the South Atlantic Region are expected to receive
a larger than average increase in uncompensated care payments, as
are rural hospitals in the West South Central, West North Central,
East South Central, East North Central, Mountain, and Pacific
Regions. Rural hospitals in the Middle Atlantic Region are projected
to receive smaller than average payment increases. Regionally, urban
hospitals are projected to receive a more varied range of payment
changes. Urban hospitals in the New England, East North Central,
West North Central, Mountain and Pacific Regions are projected to
receive decreases in uncompensated care payments. Smaller than
average increases in uncompensated care payments are projected in
the East South Central Region, while hospitals in the Middle
Atlantic, South Atlantic, and West South Central Regions and in
Puerto Rico are
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projected to receive larger than average increases in uncompensated
care payments.
Nonteaching hospitals are projected to receive a larger than
average payment increase of 7.37 percent. Teaching hospitals with
fewer than 100 residents are projected to receive a payment decrease
of 1.52 percent, while those teaching hospitals with 100+ residents
have a projected payment increase of 2.48 percent, slightly lower
than the overall average. Government hospitals are projected to
receive a larger than average increase of 20.26 percent, while
proprietary hospitals are projected to receive a payment increase
slightly above the average at 3.12 percent. Voluntary hospitals are
expected to receive a payment decrease of 5.11 percent. Hospitals
with 0 to 25 percent Medicare utilization, or above 50 percent
Medicare utilization, are projected to receive increases in
uncompensated care payments. Hospitals with 25-50 percent Medicare
utilization are projected to receive a slight decrease in
uncompensated care payments.
As discussed in section IV.F. of the preamble of this proposed
rule, an alternative methodology that we are considering for FY 2020
would be to use FY 2017 Worksheet S-10 data instead of FY 2015
Worksheet S-10 data to determine Factor 3. Our analysis for this
alternative methodology included 2,433 hospitals that would be
projected to be eligible for DSH in FY 2020 under this approach. We
note that the 3 hospital difference compared to the proposed
methodology is due to a difference in the new hospital definition
under the alternative methodology. (CCN established on or after
October 1, 2017, would be considered new.) The estimated impact of
the proposed changes in Factors 1 and 2 and the alternative
methodology for determining Factor 3 on uncompensated care payments
across all hospitals projected to be eligible for DSH payments in FY
2020 is presented in the following table.
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As seen in the above table for the alternative methodology under
consideration, rural hospitals, in general, are projected to
experience larger increases in uncompensated care payments than
their urban counterparts. Overall, rural hospitals are projected to
receive a 12.04 percent increase in uncompensated care payments,
while urban hospitals are projected to receive a 2.04 percent
increase in uncompensated care payments.
By bed size, smaller hospitals in urban areas are projected to
receive significantly larger increases in uncompensated care
payments than their larger counterparts. The smallest urban
hospitals (0-99 beds) are projected to receive an increase of 28.14
percent in uncompensated care payments, while urban hospitals with
100-249 beds are projected to see an increase of 2.78 percent, and
those with 250+ beds are projected to receive a slight increase of
0.61 percent, which is smaller than the overall average
uncompensated care payment increase. Conversely, among rural
hospitals, the largest rural hospitals (250+ beds) are projected to
receive the largest increase in uncompensated care payments at 20.76
percent. Rural hospitals with 100-249 beds are projected to receive
an increase of 5.54 percent, and the smallest rural hospitals (0-99
beds) are projected receive an increase of 15.95 percent.
By region, urban hospitals in the New England, Middle Atlantic,
East North Central, Mountain and Pacific Regions are projected to
receive decreases in uncompensated care payments. Urban hospitals in
the South Atlantic, East South Central, West North Central, and West
South Central Regions and in Puerto Rico are expected to receive
above average uncompensated care payment increases ranging from 3.56
percent to 18.56 percent. Among rural hospitals, those in the New
England, Middle Atlantic and Mountain Regions are expected to
receive decreases in uncompensated care payments. Rural hospitals in
the South Atlantic, East North Central, East South Central, West
North Central, West South Central, and Pacific Regions are projected
receive varied uncompensated care payment increases, ranging from
2.79 percent to 62.92 percent.
Nonteaching hospitals are projected to receive a larger than
average payment increase of 5.03 percent. Teaching hospitals with
fewer than 100 residents are projected to receive a payment increase
of 2.22 percent, while those teaching hospitals with 100+ residents
have a projected payment increase of 0.91 percent, both of which are
lower than the overall average. Government hospitals are projected
to receive a larger than average increase of 16.65 percent, while
proprietary hospitals are projected to receive a payment increase
below the average at 0.23 percent. Voluntary hospitals are expected
to receive a payment decrease of 2.81 percent. Hospitals with 0 to
25 percent Medicare utilization, or above 50 percent Medicare
utilization, are projected to receive higher than average increases
in uncompensated care payments. Hospitals with 25 to 50 percent
Medicare utilization are projected to receive a lower than average
increase in uncompensated care payments of 0.64 percent.
5. Effects of Proposed Reductions Under the Hospital Readmissions
Reduction Program for FY 2020
In section IV.G. of the preamble of this proposed rule, we
discuss our proposed policies for the FY 2020 Hospital Readmissions
Reduction Program. This program requires a reduction to a hospital's
base operating DRG payment to account for excess readmissions of
selected applicable conditions. The table and analysis below
illustrate the estimated financial impact of
[[Page 19649]]
the Hospital Readmissions Reduction Program payment adjustment
methodology by hospital characteristic. As outlined in section IV.G.
of the preamble of this proposed rule, hospitals are stratified into
quintiles based on the proportion of dual-eligible stays among
Medicare fee-for-service (FFS) and managed care stays between July
1, 2014 and June 30, 2017 (that is, the FY 2019 Hospital
Readmissions Reduction Program's performance period). Hospitals'
excess readmission ratios (ERRs) are assessed relative to their peer
group median and a neutrality modifier is applied in the payment
adjustment factor calculation to maintain budget neutrality. To
analyze the results by hospital characteristic, we used the FY 2019
Hospital IPPS Proposed Rule Impact File.
These analyses include 3,062 non-Maryland hospitals eligible to
receive a penalty during the performance period. Hospitals are
eligible to receive a penalty if they have 25 or more eligible
discharges for at least one measure between July 1, 2014 and June
30, 2017. The second column in the table indicates the total number
of non-Maryland hospitals with available data for each
characteristic that have an estimated payment adjustment factor less
than 1 (that is, penalized hospitals).
The third column in the table indicates the percentage of
penalized hospitals among those eligible to receive a penalty by
hospital characteristic. For example, 82.26 percent of eligible
hospitals characterized as non-teaching hospitals are expected to be
penalized. Among teaching hospitals, 88.60 percent of eligible
hospitals with fewer than 100 residents and 93.95 percent of
eligible hospitals with 100 or more residents are expected to be
penalized.
The fourth column in the table estimates the financial impact on
hospitals by hospital characteristics. The table shows the share of
penalties as a percentage of all base operating DRG payments for
hospitals with each characteristic. This is calculated as the sum of
penalties for all hospitals with that characteristic over the sum of
all base operating DRG payments for those hospitals between October
1, 2016 and September 30, 2017 (FY 2017). For example, the penalty
as a share of payments for urban hospitals is 0.67 percent. This
means that total penalties for all urban hospitals are 0.67 percent
of total payments for urban hospitals. Measuring the financial
impact on hospitals as a percentage of total base operating DRG
payments accounts for differences in the amount of base operating
DRG payments for hospitals within the characteristic when comparing
the financial impact of the program on different groups of
hospitals.
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6. Effects of Proposed Changes Under the FY 2020 Hospital Value-Based
Purchasing (VBP) Program
In section IV.H. of the preamble of this proposed rule, we
discuss the Hospital VBP Program under which the Secretary makes
value-based incentive payments to hospitals based on their
performance on measures during the performance period with respect
to a fiscal year. These incentive payments will be funded for FY
2020 through a reduction to the FY 2020 base operating DRG payment
amount for the discharge for the hospital for such fiscal year, as
required by section 1886(o)(7)(B) of the Act. The applicable
percentage for FY 2020 and subsequent years is 2 percent. The total
amount available for value-based incentive payments must be equal to
the total amount of reduced payments for all hospitals for the
fiscal year, as estimated by the Secretary.
In section IV.H.1.b. of the preamble of this proposed rule, we
estimate the available pool of funds for value-based incentive
payments in the FY 2020 program year, which, in accordance with
section 1886(o)(7)(C)(v) of the Act, would be 2.00 percent of base
operating DRG payments, or a total of approximately $1.9 billion.
This estimated available pool for FY 2020 is based on the historical
pool of hospitals that were eligible to participate in the FY 2019
program year and the payment information from the December 2018
update to the FY 2018 MedPAR file.
The proposed estimated impacts of the FY 2020 program year by
hospital characteristic, found in the table below, are based on
historical TPSs. We used the FY 2019 program year's TPSs to
calculate the proxy adjustment factors used for this impact
analysis. These are the most recently available scores that
hospitals were given an opportunity to review and correct. The proxy
adjustment factors use estimated annual base operating DRG payment
amounts derived from the December 2018 update to the FY 2018 MedPAR
file. The proxy adjustment factors can be found in Table 16
associated with this proposed rule (available via the internet on
the CMS website).
The impact analysis shows that, for the FY 2020 program year,
the number of hospitals that would receive an increase in their base
operating DRG payment amount is higher than the number of hospitals
that would receive a decrease. On average, urban hospitals in the
West North Central region and rural hospitals in the Mountain region
would have the highest positive percent change in base operating
DRG. Urban Middle Atlantic, Urban East South Central, and Urban West
South Central regions would experience an average decrease in base
operating DRG. All other regions, both urban and rural, would
experience an average increase in base operating DRG.
As DSH patient percentage increases, the average percent change
in base operating DRG would tend to decrease. With respect to
hospitals' Medicare utilization as a percent of inpatient days
(MCR), as the MCR percent increases, the average percent change in
base operating DRG would increase. On average, teaching hospitals
would have a decrease in base operating DRG while non-teaching
hospitals would have an increase in base operating DRG.
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Actual FY 2020 program year's TPSs will not be reviewed and
corrected by hospitals until after the FY 2020 IPPS/LTCH PPS final
rule has been published. Therefore, the same historical universe of
eligible hospitals and corresponding TPSs from the FY 2019 program
year will be used for the updated impact analysis in the final rule.
7. Effects of Proposed Requirements Under the HAC Reduction Program for
FY 2020
In section IV.I. of the preamble of this proposed rule, we
discuss proposed requirements for the HAC Reduction Program for FY
2020. In this proposed rule, we are not proposing to remove measures
or to adopt any new measures into the HAC Reduction Program.
a. Burden Associated With Validation
We note the burden associated with collecting and submitting
data via the NHSN system is captured under a separate OMB control
number, 0920-0666, and therefore will not impact our burden
estimates.
We discuss the burden hours associated with NHSN HAI validation
(43,200 hours over 600 hospitals) in section X.B.7. of the preamble
of this proposed rule, and note the burden associated with these
requirements is captured in an information collection request
currently available for review and comment, OMB control number 0938-
1352. We are proposing to update our cost burden to hospitals using
a wage plus benefit rate of $37.66 per hour to account for an
increase in wage rate used in the last year's PRA package from
$18.29 to $18.83. We believe that doubling the hourly wage rate
($18.83 x 2 = $37.66) to estimate total cost is a reasonably
accurate estimation method. Accordingly, we calculate cost burden to
hospitals using a wage plus benefits estimate of $37.66 per hour.
b. The Cumulative Effect of Program Measures and the Scoring
Methodology
We are presenting the estimated impact of the FY 2020 HAC
Reduction Program on hospitals by hospital characteristic. These FY
2020 HAC Reduction Program results were calculated using the Equal
Measure Weights approach finalized in the FY 2019 IPPS/LTCH PPS
final rule (83 FR 41486 through 41489). Each hospital's Total HAC
Score was calculated as the equally weighted average of the
hospital's measure scores. The table below presents the estimated
proportion of hospitals in the worst-performing quartile of the
Total HAC Scores by hospital characteristic.
Hospitals' CMS PSI 90 Composite measure results are based on
Medicare FFS discharges from July 1, 2016 through June 30, 2018 and
the recalibrated version 9.0 of the CMS PSI software. Hospitals'
measure results for the CLABSI, CAUTI, Colon and Abdominal
Hysterectomy SSI, MRSA Bacteremia, and CDI measures are derived from
standardized
[[Page 19655]]
infection ratios (SIRs) calculated with hospital surveillance data
reported to the NHSN for infections occurring between January 1,
2016 and December 31, 2017.\842\
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\842\ Updated FY 2020 data for the CDC NHSN measures (1/1/2017
through 12/31/2018) was not available at the time of publication.
---------------------------------------------------------------------------
To analyze the results by hospital characteristic, we used the
FY 2019 Hospital IPPS Final Rule Impact File. This table includes
3,184 non-Maryland hospitals with a FY 2020 Total HAC Score--
Maryland hospitals and hospitals without a Total HAC Score are
excluded from the table. Of these 3,184 hospitals, 3,170 hospitals
had information for geographic location with bed size, safety-net
status, DSH patient percentages, and teaching status; 3,182
hospitals had information on region; 3,142 hospitals had information
for ownership; and 3,155 hospitals had information for MCR percent.
The first column presents a breakdown of each characteristic.
The second column in the table indicates the total number of
non-Maryland hospitals with an FY 2020 Total HAC Score and available
data for each characteristic. For example, with regard to teaching
status, 2,092 hospitals are characterized as non-teaching hospitals,
831 hospitals are characterized as teaching hospitals with fewer
than 100 residents, and 247 hospitals are characterized as teaching
hospitals with at least 100 residents. This only represents a total
of 3,170 hospitals because the other 14 hospitals are missing from
the FY 2019 Hospital IPPS Final Rule Impact File.
The third column in the table indicates the number of hospitals
for each characteristic that would be in the worst-performing
quartile of Total HAC Scores. These hospitals would receive a
payment reduction under the FY 2020 HAC Reduction Program. For
example, with regard to teaching status, 458 hospitals out of 2,092
hospitals characterized as non-teaching hospitals would be subject
to a payment reduction. Among teaching hospitals, 208 out of 831
hospitals with fewer than 100 residents, and 120 out of 247
hospitals with 100 or more residents would be subject to a payment
reduction.
The fourth column in the table indicates the proportion of
hospitals for each characteristic that would be in the worst-
performing quartile of Total HAC Scores and thus receive a payment
reduction under the FY 2020 HAC Reduction Program. For example, 21.9
percent of the 2,092 hospitals characterized as non-teaching
hospitals, 25.0 percent of the 831 teaching hospitals with fewer
than 100 residents, and 48.6 percent of the 247 teaching hospitals
with 100 or more residents would be subject to a payment reduction.
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8. Effects of Proposed Changes Relating to Critical Access Hospitals
(CAHs) as Nonproviders for Direct GME and IME Payment Purposes
In section IV.J.2. of the preamble of this proposed rule, we
discuss our proposal to consider CAHs as nonprovider settings for
purposes of direct GME and IME payments such that, effective with
portions of cost reporting periods beginning October 1, 2019, a
hospital may include full-time equivalent (FTE) residents training
at a CAH in its FTE count as long as it meets the nonprovider
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setting requirements currently included at 42 CFR 413.78(g). We note
that we are not proposing to change our policy with respect to CAHs
incurring the costs of training residents. That is, a CAH may
continue to incur the costs of training residents in an approved
residency training program(s) and be paid based on 101 percent of
the reasonable costs for these training costs.
We anticipate any impact associated with this proposed change to
be negligible. Because IPPS teaching hospitals have caps in place
for the number of FTE residents they may claim for direct GME and
IME payment purposes, these hospitals could only receive direct GME
and IME payments for the FTE residents for which they incur the
training costs at CAHs within their existing FTE caps. Allowing IPPS
hospitals to claim FTE residents training at CAHs would not mean the
hospitals would be able to claim additional FTE residents above
their FTE caps. Thus, because no additional funded slots would be
created for IPPS hospitals by this proposal, and because CAHs would
no longer be claiming and receiving payment for the salary costs of
the residents in situations where the CAHs are being treated as
nonprovider sites, we believe there is minimal to no impact.
9. Effects of Implementation of the Rural Community Hospital
Demonstration Program in FY 2020
In section IV.K. of the preamble of this proposed rule for FY
2020, we discussed our implementation and budget neutrality
methodology for section 410A of Public Law 108-173, as amended by
sections 3123 and 10313 of Public Law 111-148, and more recently, by
section 15003 of Public Law 114-255, which requires the Secretary to
conduct a demonstration that would modify payments for inpatient
services for up to 30 rural hospitals.
Section 15003 of Public Law 114-255 requires the Secretary to
conduct the Rural Community Hospital Demonstration for a 10-year
extension period (in place of the 5-year extension period required
by the Affordable Care Act), beginning on the date immediately
following the last day of the initial 5-year period under section
410A(a)(5) of Public Law 108-173. Specifically, section 15003 of
Public Law 114-255 amended section 410A(g)(4) of Public Law 108-173
to require that, for hospitals participating in the demonstration as
of the last day of the initial 5-year period, the Secretary shall
provide for continued participation of such rural community
hospitals in the demonstration during the 10-year extension period,
unless the hospital makes an election to discontinue participation.
Furthermore, section 15003 of Public Law 114-255 requires that,
during the second 5 years of the 10-year extension period, the
Secretary shall provide for participation under the demonstration
during the second 5 years of the 10-year extension period for
hospitals that are not described in subsection 410A(g)(4).
Section 15003 of Public Law 114-255 also requires that no later
than 120 days after the enactment of Public Law 114-255 that the
Secretary issue a solicitation for applications to select additional
hospitals to participate in the demonstration program for the second
5 years of the 10-year extension period so long as the maximum
number of 30 hospitals stipulated by Public Law 111-148 is not
exceeded. Section 410A(c)(2) requires that in conducting the
demonstration program under this section, the Secretary shall ensure
that the aggregate payments made by the Secretary do not exceed the
amount which the Secretary would have paid if the demonstration
program under this section was not implemented (budget neutrality).
In the preamble to this FY 2020 IPPS/LTCH PPS proposed rule, we
described the terms of participation for the extension period
authorized by Public Law 114-255. In the FY 2018 IPPS/LTCH PPS final
rule, we finalized our policy with regard to the effective date for
the application of the reasonable cost-based payment methodology
under the demonstration for those among the hospitals that had
previously participated and were choosing to participate in the
second 5-year extension period. According to our finalized policy,
each of these previously participating hospitals began the second 5
years of the 10-year extension period on the date immediately after
the date the period of performance under the 5-year extension period
ended. Seventeen of the 21 hospitals that completed their periods of
participation under the extension period authorized by Public Law
111-148 elected to continue in the second 5-year extension period,
while 13 additional hospitals were selected to participate. One of
the hospitals selected from the solicitation in 2017 withdrew from
the demonstration program prior to beginning participation on July
1, 2018. Each of the remaining newly participating hospitals began
its 5-year period of participation effective with the start of the
first cost reporting period on or after October 1, 2017. Thus, 29
hospitals participated in FYs 2018 and 2019, and are scheduled to
participate in FY 2020.
In the FY 2018 IPPS/LTCH PPS final rule, we finalized the budget
neutrality methodology in accordance with our policies for
implementing the demonstration, adopting the general methodology
used in previous years, whereby we estimated the additional payments
made by the program for each of the participating hospitals as a
result of the demonstration. In order to achieve budget neutrality,
we adjusted the national IPPS rates by an amount sufficient to
account for the added costs of this demonstration. In other words,
we have applied budget neutrality across the payment system as a
whole rather than across the participants of this demonstration. The
language of the statutory budget neutrality requirement permits the
agency to implement the budget neutrality provision in this manner.
The statutory language requires that aggregate payments made by the
Secretary do not exceed the amount which the Secretary would have
paid if the demonstration was not implemented, but does not identify
the range across which aggregate payments must be held equal.
For this proposed rule, the resulting amount applicable to FY
2020 is $61,970,567, which we are proposing to include in the budget
neutrality offset adjustment for FY 2020. This estimated amount is
based on the specific assumptions regarding the data sources used,
that is, recently available ``as submitted'' cost reports and
historical and proposed update factors for cost and payment. If
updated data become available prior to the FY 2020 IPPS/LTCH PPS
final rule, we will use them to the extent appropriate to estimate
the costs of the demonstration program.
In previous years, we have incorporated a second component into
the budget neutrality offset amounts identified in the final IPPS
rules. As finalized cost reports became available, we determined the
amount by which the actual costs of the demonstration for an
earlier, given year differed from the estimated costs for the
demonstration set forth in the final IPPS rule for the corresponding
fiscal year, and we incorporated that amount into the budget
neutrality offset amount for the upcoming fiscal year. We have
calculated this difference for FYs 2005 through 2013 between the
actual costs of the demonstration as determined from finalized cost
reports once available, and estimated costs of the demonstration as
identified in the applicable IPPS final rules for these years.
With the extension of the demonstration for another 5-year
period, as authorized by section 15003 of Public Law 114-255, we
will continue this general procedure. Currently, finalized cost
reports are now available for the 22 hospitals that completed a cost
reporting period beginning in FY 2014 according to the demonstration
cost-based payment methodology. The actual costs of the
demonstration for this fiscal year as determined from the finalized
cost reports fell short of the estimated amount that was finalized
in the FY 2014 IPPS/LTCH PPS final rule by $14,932,060.
We note that, for this proposed rule, the amounts identified for
the actual costs of the demonstration for FY 2014 (determined from
finalized cost reports) is less than the amount that was identified
in the final rule for this fiscal year. Therefore, in keeping with
previous policy finalized in similar situations when the costs of
the demonstration fell short of the amount estimated in the
corresponding year's final rule, we will be including this component
as a negative adjustment to the budget neutrality offset amount for
the current fiscal year.
Therefore, for FY 2020, the total amount that we are proposing
to apply to the national IPPS rates is $47,038,507. If updated data
become available prior to the FY 2020 IPPS/LTCH PPS final rule, we
would use them to the extent appropriate to determine the budget
neutrality offset amount for FY 2020. Furthermore, if the needed
cost reports are available in time for the FY 2020 IPPS/LTCH PPS
final rule, we will also identify the difference between the total
cost of the demonstration based on finalized FY 2015 cost reports
and the estimate of the costs of the demonstration for that year,
and incorporate that amount into the final budget neutrality offset
amount for FY 2020.
10. Effects of Proposed Change Relating to CAH Payment for Ambulance
Services
In section VI.C.2. of the preamble of this proposed rule, we
discuss our proposal to revise the regulations at Sec. 413.70(b)(5)
by
[[Page 19659]]
adding a new paragraph (D) to state that, effective for cost
reporting periods beginning on or after October 1, 2019, payment for
ambulance services furnished by a CAH or by an entity that is owned
and operated by a CAH is 101 percent of the reasonable costs of the
CAH or the entity in furnishing those services, but only if the CAH
or the entity is the only provider or supplier of ambulance services
located within a 35-mile drive of the CAH, excluding ambulance
providers or suppliers that are not legally authorized to furnish
ambulance services to transport individuals either to or from the
CAH. Consistent with the existing policy under Sec.
413.70(b)(5)(i)(C), if there is no provider or supplier of ambulance
services located within a 35-mile drive of the CAH and there is an
entity that is owned and operated by a CAH that is more than a 35-
mile drive from the CAH, payment for ambulance services furnished by
that entity is 101 percent of the reasonable costs of the entity in
furnishing those services, but only if the entity is the closest
provider or supplier of ambulance services to the CAH.
Based on the best data available, assuming no significant change
in the volume of CAH ambulance trips and that approximately 5 CAHs
may be affected by the specific situation described in our proposal,
we estimate Medicare payments will increase by $2 million in FY 2020
as compared to FY 2019.
11. Effects of Continued Implementation of the Frontier Community
Health Integration Project (FCHIP) Demonstration
In section VI.C.3. of the preamble of this proposed rule, we
discuss the implementation of the FCHIP demonstration, which allows
eligible entities to develop and test new models for the delivery of
health care services in eligible counties in order to improve access
to and better integrate the delivery of acute care, extended care,
and other health care services to Medicare beneficiaries in no more
than four States. Budget neutrality estimates for the demonstration
will be based on the demonstration period of August 1, 2016 through
July 31, 2019. The demonstration includes three intervention prongs,
under which specific waivers of Medicare payment rules will allow
for enhanced payment: Telehealth, skilled nursing facility/nursing
facility services, and ambulance services. These waivers are being
implemented with the goal of increasing access to care with no net
increase in costs. (We initially addressed this demonstration in the
FY 2017 IPPS/LTCH PPS final rule (81 FR 57064 through 57065), FY
2018 IPPS/LTCH PPS final rule (82 FR 38294 through 38296) and FY
2019 IPPS/LTCH PPS final rule (83 FR 41516 through 41517).)
We specified the payment enhancements for the demonstration and
selected CAHs for participation with the goal of maintaining the
budget neutrality of the demonstration on its own terms (that is,
the demonstration will produce savings from reduced transfers and
admissions to other health care providers, thus offsetting any
increase in payments resulting from the demonstration). However,
because of the small size of this demonstration program and
uncertainty associated with projected Medicare utilization and
costs, in the FY 2019 IPPS/LTCH PPS final rule we adopted a
contingency plan (83 FR 41516 through 41517) to ensure that the
budget neutrality requirement in section 123 of Public Law 110-275
is met. Accordingly, if analysis of claims data for the Medicare
beneficiaries receiving services at each of the participating CAHs,
as well as of other data sources, including cost reports, shows that
increases in Medicare payments under the demonstration during the 3-
year period are not sufficiently offset by reductions elsewhere, we
will recoup the additional expenditures attributable to the
demonstration through a reduction in payments to all CAHs
nationwide. The demonstration is projected to impact payments to
participating CAHs under both Medicare Part A and Part B. Thus, in
the event that we determine that aggregate payments under the
demonstration exceed the payments that would otherwise have been
made, CMS will recoup payments through reductions of Medicare
payments to all CAHs under both Medicare Part A and Part B. Because
of the small scale of the demonstration, it would not be feasible to
implement budget neutrality by reducing payments only to the
participating CAHs. Therefore, we will make the reduction to
payments to all CAHs, not just those participating in the
demonstration, because the FCHIP demonstration is specifically
designed to test innovations that affect delivery of services by
this provider category. As we explained in the FY 2019 IPPS/LTCH PPS
final rule (83 FR 41516 through 41517), we believe that the language
of the statutory budget neutrality requirement at section
123(g)(1)(B) of the Act permits the agency to implement the budget
neutrality provision in this manner. The statutory language merely
refers to ensuring that aggregate payments made by the Secretary do
not exceed the amount which the Secretary estimates would have been
paid if the demonstration project was not implemented, and does not
identify the range across which aggregate payments must be held
equal.
Given the 3-year period of performance of the FCHIP
demonstration and the time needed to conduct the budget neutrality
analysis, in the event the demonstration is found not to have been
budget neutral, we plan to recoup any excess costs over a period of
three cost report periods, beginning in CY 2020. Therefore, based on
currently available data, this policy will likely have no impact for
any national payment system for FY 2020.
I. Effects of Proposed Changes in the Capital IPPS
1. General Considerations
For the impact analysis presented below, we used data from the
December 2018 update of the FY 2018 MedPAR file and the December
2018 update of the Provider-Specific File (PSF) that was used for
payment purposes. Although the analyses of the proposed changes to
the capital prospective payment system do not incorporate cost data,
we used the December 2018 update of the most recently available
hospital cost report data (FYs 2016 and 2017) to categorize
hospitals. Our analysis has several qualifications. We use the best
data available and make assumptions about case-mix and beneficiary
enrollment, as described later in this section.
Due to the interdependent nature of the IPPS, it is very
difficult to precisely quantify the impact associated with each
proposed change. In addition, we draw upon various sources for the
data used to categorize hospitals in the tables. In some cases (for
instance, the number of beds), there is a fair degree of variation
in the data from different sources. We have attempted to construct
these variables with the best available sources overall. However, it
is possible that some individual hospitals are placed in the wrong
category.
Using cases from the December 2018 update of the FY 2018 MedPAR
file, we simulated payments under the capital IPPS for FY 2019 and
the proposed payments for FY 2020 for a comparison of total payments
per case. Short-term, acute care hospitals not paid under the
general IPPS (for example, hospitals in Maryland) are excluded from
the simulations.
The methodology for determining a capital IPPS payment is set
forth at Sec. 412.312. The basic methodology for calculating the
proposed capital IPPS payments in FY 2020 is as follows:
(Standard Federal rate) x (DRG weight) x (GAF) x (COLA for
hospitals located in Alaska and Hawaii) x (1 + DSH adjustment factor
+ IME adjustment factor, if applicable).
In addition to the other adjustments, hospitals may receive
outlier payments for those cases that qualify under the threshold
established for each fiscal year. We modeled payments for each
hospital by multiplying the capital Federal rate by the GAF and the
hospital's case-mix. We then added estimated payments for indirect
medical education, disproportionate share, and outliers, if
applicable. For purposes of this impact analysis, the model includes
the following assumptions:
An estimated increase in the Medicare case-mix index of
0.5 percent in FY 2019 and 0.5 percent in FY 2020 based on
preliminary FY 2019 data.
We estimate that Medicare discharges would be
approximately 10.8 million in both FYs 2019 and 2020.
The capital Federal rate was updated, beginning in FY
1996, by an analytical framework that considers changes in the
prices associated with capital-related costs and adjustments to
account for forecast error, changes in the case-mix index, allowable
changes in intensity, and other factors. As discussed in section
III.A.1.a. of the Addendum to this proposed rule, the proposed
update to the capital Federal rate is 1.5 percent for FY 2020.
In addition to the proposed FY 2020 update factor, the
proposed FY 2020 capital Federal rate was calculated based on a
proposed GAF/DRG budget neutrality adjustment factor of 0.9976 and a
proposed outlier adjustment factor of 0.9466.
2. Results
We used the actuarial model previously described in section I.I.
of Appendix A of this proposed rule to estimate the potential
[[Page 19660]]
impact of the proposed changes for FY 2020 on total capital payments
per case, using a universe of 3,242 hospitals. As previously
described, the individual hospital payment parameters are taken from
the best available data, including the December 2018 update of the
FY 2018 MedPAR file, the December 2018 update to the PSF, and the
most recent cost report data from the December 2018 update of HCRIS.
In Table III, we present a comparison of estimated proposed total
payments per case for FY 2019 and estimated total payments per case
for FY 2020 based on the proposed FY 2020 payment policies. Column 2
shows estimates of payments per case under our model for FY 2019.
Column 3 shows estimates of proposed payments per case under our
model for FY 2020. Column 4 shows the proposed total percentage
change in payments from FY 2019 to FY 2020. The change represented
in Column 4 includes the proposed 1.5 percent update to the capital
Federal rate and other proposed changes in the adjustments to the
capital Federal rate. The comparisons are provided by: (1)
Geographic location; (2) region; and (3) payment classification.
The simulation results show that, on average, capital payments
per case in FY 2020 are expected to increase as compared to capital
payments per case in FY 2019. This expected increase overall is
largely due to the proposed 1.5 percent update to the capital
Federal rate for FY 2020. Hospitals within both rural and urban
regions may experience an increase or a decrease in capital payments
per case due to changes in the GAFs. These regional effects of the
proposed changes to the GAFs on capital payments are consistent with
the projected changes in payments due to proposed changes in the
wage index (and proposed policies affecting the wage index), as
shown in Table I in section I.G. of this Appendix A.
The net impact of these proposed changes is an estimated 1.9
percent change in capital payments per case from FY 2019 to FY 2020
for all hospitals (as shown in Table III).
The geographic comparison shows that, on average, hospitals in
both urban and rural classifications would experience an increase in
capital IPPS payments per case in FY 2020 as compared to FY 2019.
Capital IPPS payments per case would increase by an estimated 1.7
percent for hospitals in large urban areas and by 1.8 percent for
hospitals in other urban areas, while payments to hospitals in rural
areas would increase by 3.1 percent in FY 2019 to FY 2020.
The comparisons by region show that the estimated changes in
capital payments per case from FY 2019 to FY 2020 in urban areas
range from a 0.4 percent decrease for the New England region to a
3.1 percent increase for the East South Central region. For rural
regions, the Pacific rural region is projected to experience an
increase in capital IPPS payments per case of 4.1 percent, while the
New England rural region is projected to experience an increase in
capital IPPS payments per case of 0.6 percent.
Hospitals of all types of ownership (that is, voluntary
hospitals, government hospitals, and proprietary hospitals) are
expected to experience an increase in capital payments per case from
FY 2019 to FY 2020. The projected increase in capital payments for
voluntary hospitals is estimated to be 1.8 percent. Proprietary
hospitals and government hospitals are expected to experience an
increase in capital IPPS payments of 2.2 percent.
Section 1886(d)(10) of the Act established the MGCRB. Hospitals
may apply for reclassification for purposes of the wage index for FY
2020. Reclassification for wage index purposes also affects the GAFs
because that factor is constructed from the hospital wage index. To
present the effects of the hospitals being reclassified as of the
publication of this proposed rule for FY 2020, we show the proposed
average capital payments per case for reclassified hospitals for FY
2020. Urban reclassified hospitals are expected to experience an
increase in capital payments of 1.4 percent; urban nonreclassified
hospitals are expected to experience an increase in capital payments
of 2.1 percent. The estimated percentage increase for rural
reclassified hospitals is 2.6 percent, and for rural nonreclassified
hospitals, the estimated percentage increase in capital payments is
3.9 percent.
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J. Effects of Proposed Payment Rate Changes and Proposed Policy
Changes Under the LTCH PPS
1. Introduction and General Considerations
In section VII. of the preamble of this proposed rule and
section V. of the Addendum to this proposed rule, we set forth the
proposed annual update to the payment rates for the LTCH PPS for FY
2020. In the preamble of this proposed rule, we specify the
statutory authority for the provisions that are presented, identify
the proposed policies, and present rationales for our decisions as
[[Page 19663]]
well as alternatives that were considered. In this section of
Appendix A to this proposed rule, we discuss the impact of the
proposed changes to the payment rate, factors, and other payment
rate policies related to the LTCH PPS that are presented in the
preamble of this proposed rule in terms of their estimated fiscal
impact on the Medicare budget and on LTCHs.
There are 384 LTCHs included in this impact analysis. We note
that, although there are currently approximately 394 LTCHs, for
purposes of this impact analysis, we excluded the data of all-
inclusive rate providers consistent with the development of the
proposed FY 2020 MS-LTC-DRG relative weights (discussed in section
VII.B.3.c. of the preamble of this proposed rule. Moreover, in the
claims data used for this proposed rule, 2 of these 384 LTCHs only
have claims for site neutral payment rate cases and, therefore, do
not affect our impact analysis for LTCH PPS standard Federal payment
rate cases.) In the impact analysis, we used the proposed payment
rate, factors, and policies presented in this proposed rule, the
proposed 1.027 percent annual update to the LTCH PPS standard
Federal payment rate, the one-time budget neutrality adjustment
factor for the estimated cost of eliminating the 25-percent
threshold policy in FY 2020 as discussed in section VII.D. of the
preamble of this proposed rule, the proposed update to the MS-LTC-
DRG classifications and relative weights, the proposed update to the
wage index values and labor-related share, and the best available
claims and CCR data to estimate the proposed change in payments for
FY 2020.
Under the dual rate LTCH PPS payment structure, payment for LTCH
discharges that meet the criteria for exclusion from the site
neutral payment rate (that is, LTCH PPS standard Federal payment
rate cases) is based on the LTCH PPS standard Federal payment rate.
Consistent with the statute, the site neutral payment rate is the
lower of the IPPS comparable per diem amount as determined under
Sec. 412.529(d)(4), including any applicable outlier payments as
specified in Sec. 412.525(a), reduced by 4.6 percent for FYs 2018
through 2026; or 100 percent of the estimated cost of the case as
determined under existing Sec. 412.529(d)(2). In addition, there
are two separate high cost outlier targets--one for LTCH PPS
standard Federal payment rate cases and one for site neutral payment
rate cases. The statute also establishes a transitional payment
method for cases that are paid the site neutral payment rate for
LTCH discharges occurring in cost reporting periods beginning during
FY 2016 through FY 2019. The transitional payment amount for site
neutral payment rate cases is a blended payment rate, which is
calculated as 50 percent of the applicable site neutral payment rate
amount for the discharge as determined under Sec. 412.522(c)(1) and
50 percent of the applicable LTCH PPS standard Federal payment rate
for the discharge determined under Sec. 412.523. For FY 2019, the
applicability of this transitional payment method for site neutral
payment rate cases is dependent upon both the discharge date of the
case and the start date of the LTCH's FY 2019 cost reporting period.
Specifically, the transitional payment method only applies to those
site neutral payment rate cases whose discharges occur during a
LTCH's cost reporting period that begins before October 1, 2019.
While the transitional payment amount for site neutral payment rate
cases is a blended payment rate, which is calculated as 50 percent
of the applicable site neutral payment rate amount for the discharge
as determined under Sec. 412.522(c)(1) and 50 percent of the
applicable LTCH PPS standard Federal payment rate for the discharge
determined under Sec. 412.523, site neutral payment rate cases
whose discharges from an LTCH occur during the LTCH's cost reporting
period that begins on or after October 1, 2019 are paid the site
neutral payment rate amount determined under Sec. 412.522(c)(1).
Based on the best available data for the 384 LTCHs in our
database that were considered in the analyses used for this proposed
rule, we estimate that overall LTCH PPS payments in FY 2020 will
increase by approximately 0.9 percent (or approximately $37 million)
based on the proposed rates and factors presented in section VII. of
the preamble and section V. of the Addendum to this proposed rule.
The statutory transitional payment method for cases that are
paid the site neutral payment rate for LTCH discharges occurring in
cost reporting periods beginning during FY 2018 or FY 2019 uses a
blended payment rate, which is determined as 50 percent of the site
neutral payment rate amount for the discharge and 50 percent of the
LTCH PPS standard Federal prospective payment rate amount for the
discharge (Sec. 412.522(c)(3)). Therefore, when estimating FY 2019
LTCH PPS payments for site neutral payment rate cases for this
impact analysis, the transitional blended payment rate was applied
to all such cases because all discharges in FY 2019 are either in
the LTCH's cost reporting period that began during FY 2018 or in the
LTCH's cost reporting period that will begin during FY 2019.
However, when estimating FY 2020 LTCH PPS payments for site neutral
payment rate cases for this impact analysis, because the statute
specifies that the site neutral payment rate effective date for a
given LTCH is based on the date that the LTCH's cost reporting
period begins during FY 2020, we included an adjustment to account
for this rolling effective date, consistent with the general
approach used for the LTCH PPS impact analysis presented in the FY
2016 IPPS/LTCH PPS final rule (80 FR 49831). This approach accounts
for the fact that site neutral payment rate cases in FY 2019 that
are in an LTCH's cost reporting period that begins before October 1,
2019 continue to be paid under the transitional payment method until
the start of the LTCH's first cost reporting period beginning on or
after October 1, 2019. Site neutral payment rate cases whose
discharges from LTCHs occurring during an LTCH's cost reporting
period that begins on or after October 1, 2019 will no longer be
paid under the transitional payment method and will instead be paid
the site neutral payment rate amount as determined under Sec.
412.522(c)(1).
For purposes of this impact analysis, to estimate proposed total
FY 2020 LTCH PPS payments for site neutral payment rate cases, we
used the same general approach as was used in the FY 2016 IPPS/LTCH
PPS final rule with modifications to account for the rolling end
date to the transitional blended payment rate in FY 2020 instead of
the rolling effective date for implementation of the transitional
site neutral payment rate in FY 2016. In summary, under this
approach, we grouped LTCHs based on the quarter their cost reporting
periods would begin during FY 2020. For example, LTCHs with cost
reporting periods that begin during October through December 2019
would be grouped to site neutral payment rate cases whose discharges
would occur during the first quarter of FY 2020. For LTCHs grouped
in each quarter of FY 2020, we modeled those LTCHs' estimated FY
2020 site neutral payment rate payments under the transitional
blended payment rate based on the quarter in which the LTCHs in each
group would continue to be paid the transitional payment method for
the site neutral payment rate cases.
For purposes of this estimate, then, we assume the cost
reporting period is the same for all LTCHs in each of the quarterly
groups and that this cost reporting period begins on the first day
of that quarter. (For example, our first group consists of 37 LTCHs
whose cost reporting period will begin in the first quarter of FY
2020 so that, for purposes of this estimate, we assume all 37 LTCHs
will begin their FY 2020 cost reporting period on October 1, 2019.)
Second, we estimated the proportion of FY 2020 site neutral payment
rate cases in each of the quarterly groups, and we then assume this
proportion is applicable for all four quarters of FY 2020. (For
example, as discussed in more detail below, we estimate the first
quarter group will discharge 7.1 percent of all FY 2020 site neutral
payment rate cases and, therefore, we estimate that group of LTCHs
will discharge 7.1 percent of all FY 2018 site neutral payment rate
cases in each quarter of FY 2020.) Then, we modeled estimated FY
2020 payments on a quarterly basis under the LTCH PPS standard
Federal payment rate based on the assumptions described above. We
continue to believe that this approach is a reasonable means of
taking the rolling effective date into account when estimating FY
2020 payments.
Based on the fiscal year begin date information in the December
2018 update of the PSF and the LTCH claims from the December 2018
update of the FY 2018 MedPAR files for the 384 LTCHs in our database
used for this proposed rule, we found the following: 7.1 percent of
site neutral payment rate cases are from 37 LTCHs whose cost
reporting periods will begin during the first quarter of FY 2020;
23.4 percent of site neutral payment rate cases are from 94 LTCHs
whose cost reporting periods will begin in the second quarter of FY
2020; 9.3 percent of site neutral payment rate cases are from 52
LTCHs whose cost reporting periods will begin in the third quarter
of FY 2020; and 60.3 percent of site neutral payment rate cases are
from 201 LTCHs whose cost reporting periods will begin in the fourth
quarter of FY 2020. Therefore, the following percentages apply in
the approach described above:
[[Page 19664]]
First Quarter FY 2020: 7.1 percent of site neutral
payment rate cases (that is, the percentage of discharges from LTCHs
whose FY 2018 cost reporting period will begin in the first quarter
of FY 2020) are no longer eligible for the transitional blended
payment method, while the remaining 92.9 percent of site neutral
payment rate discharges are eligible to be paid under the
transitional payment method.
Second Quarter FY 2020: 30.4 percent of site neutral
payment rate second quarter discharges (that is, the percentage of
discharges from LTCHs whose FY 2020 cost reporting period will begin
in the first or second quarter of FY 2020) are no longer eligible
for the transitional blended payment method, while the remaining
69.6 percent of site neutral payment rate second quarter discharges
are eligible to be paid under the transitional payment method.
Third Quarter FY 2020: 39.7 percent of site neutral
payment rate third quarter discharges (that is, the percentage of
discharges from LTCHs whose FY 2020 cost reporting period will begin
in the first, second, or third quarter of FY 2020) are no longer
eligible for the transitional blended payment method while the
remaining 60.3 percent of site neutral payment rate third quarter
discharges are eligible to be paid under the transitional payment
method.
Fourth Quarter FY 2020: 100.0 percent of site neutral
payment rate fourth quarter discharges (that is, the percentage of
discharges from LTCHs whose FY 2020 cost reporting period will begin
in the first, second, third, or fourth quarter of FY 2020) are no
longer eligible for the transitional blended payment method.
Based on the FY 2018 LTCH cases that were used for the analysis
in this proposed rule, approximately 29 percent of those cases were
classified as site neutral payment rate cases (that is, 29 percent
of LTCH cases did not meet the patient-level criteria for exclusion
from the site neutral payment rate). Our Office of the Actuary
currently estimates that the percent of LTCH PPS cases that will be
paid at the site neutral payment rate in FY 2020 will not change
significantly from the most recent historical data. Taking into
account the transitional blended payment rate and other changes that
will apply to the site neutral payment rate cases in FY 2020, we
estimate that aggregate LTCH PPS payments for these site neutral
payment rate cases will decrease by approximately 4.9 percent (or
approximately $41 million).
Approximately 71 percent of LTCH cases are expected to meet the
patient-level criteria for exclusion from the site neutral payment
rate in FY 2020, and will be paid based on the LTCH PPS standard
Federal payment rate for the full year. We estimate that total LTCH
PPS payments for these LTCH PPS standard Federal payment rate cases
in FY 2020 will increase approximately 2.3 percent (or approximately
$79 million). This estimated increase in LTCH PPS payments for LTCH
PPS standard Federal payment rate cases in FY 2020 is primarily due
to the proposed 2.7 percent annual update to the LTCH PPS standard
Federal payment rate for FY 2020 and the estimated 0.3 percent
decrease in high cost outlier payments discussed in section
V.D.3.b.(3). of the Addendum to this proposed rule.
Based on the 384 LTCHs that were represented in the FY 2018 LTCH
cases that were used for the analyses in this proposed rule
presented in this Appendix, we estimate that aggregate FY 2019 LTCH
PPS payments will be approximately $4.274 billion, as compared to
estimated aggregate FY 2020 LTCH PPS payments of approximately
$4.311 billion, resulting in an estimated overall increase in LTCH
PPS payments of approximately $37 million. We note that the
estimated $37 million increase in LTCH PPS payments in FY 2020 does
not reflect changes in LTCH admissions or case-mix intensity, which
will also affect the overall payment effects of the proposed
policies in this proposed rule.
The LTCH PPS standard Federal payment rate for FY 2019 is
$41,558.68. For FY 2020, we are proposing to establish an LTCH PPS
standard Federal payment rate of $42,950.91 which reflects the
proposed 2.7 percent annual update to the LTCH PPS standard Federal
payment rate, the proposed one-time budget neutrality adjustment
factor of 0.999856 for eliminating the 25-percent threshold policy
in FY 2020 as discussed in section VII.D. of the preamble of this
proposed rule, and the proposed area wage budget neutrality factor
of 1.0064747 to ensure that the changes in the wage indexes and
labor-related share do not influence aggregate payments. For LTCHs
that fail to submit data for the LTCH QRP, in accordance with
section 1886(m)(5)(C) of the Act, we are proposing to establish an
LTCH PPS standard Federal payment rate of $42,114.47. This proposed
LTCH PPS standard Federal payment rate reflects the proposed updates
and factors previously described, as well as the required 2.0
percentage point reduction to the annual update for failure to
submit data under the LTCH QRP. We note that the factors previously
described to determine the proposed FY 2020 LTCH PPS standard
Federal payment rate are applied to the FY 2019 LTCH PPS standard
Federal rate set forth under Sec. 412.523(c)(3)(xiv) (that is,
$41,558.68).
Table IV shows the estimated impact for LTCH PPS standard
Federal payment rate cases. The estimated change attributable solely
to the proposed annual update of 2.7 percent to the LTCH PPS
standard Federal payment rate is projected to result in an increase
of 2.6 percent in payments per discharge for LTCH PPS standard
Federal payment rate cases from FY 2019 to FY 2020, on average, for
all LTCHs (Column 6). In addition to the proposed annual update to
the LTCH PPS standard Federal payment rate for FY 2020, the
estimated increase of 2.6 percent shown in Column 6 of Table IV also
includes estimated payments for SSO cases, a portion of which are
not affected by the annual update to the LTCH PPS standard Federal
payment rate, as well as the reduction that is applied to the annual
update for LTCHs that do not submit the required LTCH QRP data.
Therefore, for all hospital categories, the projected increase in
payments based on the proposed LTCH PPS standard Federal payment
rate to LTCH PPS standard Federal payment rate cases is somewhat
less than the proposed 2.7 percent annual update for FY 2020.
For FY 2020, we are proposing to update the wage index values
based on the most recent available data, and we are proposing to
continue to use labor market areas based on the CBSA delineations
(as discussed in section V.B. of the Addendum to this proposed
rule). In addition, we are proposing the labor-related share would
remain at 66.0 percent under the LTCH PPS for FY 2020, based on the
most recent available data on the relative importance of the labor-
related share of operating and capital costs of the 2013-based LTCH
market basket. We also are proposing to apply a proposed area wage
level budget neutrality factor of 1.0064747 to ensure that the
changes to the wage data and labor-related share do not result in
any change in estimated aggregate LTCH PPS payments to LTCH PPS
standard Federal payment rate cases.
We currently estimate total high cost outlier payments for LTCH
PPS standard Federal payment rate cases would decrease from FY 2019
to FY 2020. Based on the FY 2018 LTCH cases that were used for the
analyses in this proposed rule, we estimate that the FY 2019 high
cost outlier threshold of $27,121 (as established in the FY 2019
IPPS/LTCH PPS final rule correction notice) would result in
estimated high cost outlier payments for LTCH PPS standard Federal
payment rate cases in FY 2019 that are projected to exceed the 7.975
percent target. Specifically, we currently estimate that high cost
outlier payments for LTCH PPS standard Federal payment rate cases
would be approximately 8.24 percent of the estimated total LTCH PPS
standard Federal payment rate payments in FY 2019. Combined with our
estimate that FY 2020 high cost outlier payments for LTCH PPS
standard Federal payment rate cases would be 7.975 percent of
estimated total LTCH PPS standard Federal payment rate payments in
FY 2020, this would result in an estimated decrease in high cost
outlier payments of approximately 0.3 percent between FY 2019 and FY
2020. We note that, consistent with past practice, in calculating
these estimated high cost outlier payments, we increased estimated
costs by an inflation factor of 6.0 percent (determined by the
Office of the Actuary) to update the FY 2018 costs of each case to
FY 2020.
Table IV shows the estimated impact of the proposed payment rate
and proposed policy changes on LTCH PPS payments for LTCH PPS
standard Federal payment rate cases for FY 2020 by comparing
estimated FY 2019 LTCH PPS payments to estimated FY 2020 LTCH PPS
payments. (As noted earlier, our analysis does not reflect changes
in LTCH admissions or case-mix intensity.) We note that these
impacts do not include LTCH PPS site neutral payment rate cases for
the reasons discussed in section I.J.4. of this Appendix.
As we discuss in detail throughout this proposed rule, based on
the most recent available data, we believe that the provisions of
this proposed rule relating to the LTCH PPS, which are projected to
result in an overall increase in estimated aggregate LTCH PPS
payments, and the resulting LTCH PPS
[[Page 19665]]
payment amounts would result in appropriate Medicare payments that
are consistent with the statute.
2. Impact on Rural Hospitals
For purposes of section 1102(b) of the Act, we define a small
rural hospital as a hospital that is located outside of an urban
area and has fewer than 100 beds. As shown in Table IV, we are
projecting a 2.2 percent increase in estimated payments for LTCH PPS
standard Federal payment rate cases for LTCHs located in a rural
area. This estimated impact is based on the FY 2018 data for the 19
rural LTCHs (out of 384 LTCHs) that were used for the impact
analyses shown in Table IV.
3. Effect of Proposed Payment Adjustment for LTCH Discharges That Do
Not Meet the Applicable Discharge Payment Percentage
In section VII.C. of the preamble of this proposed rule, we
discuss our proposal to implement the requirements of section
1886(m)(6)(C)(ii) of the Act, which specifies for cost reporting
periods beginning on or after October 1, 2019, any LTCH with a
discharge payment percentage for the period that is not at least 50
percent will be informed of such a fact, and all of the LTCH's
discharges in each successive cost reporting period will be paid the
payment amount that would apply under subsection (d) for the
discharge if the hospital were a subsection (d) hospital, subject to
the process for reinstatement provided for by section
1886(m)(6)(C)(iii) of the Act. Specifically, we are proposing to
continue to use our existing policy to calculate the discharge
payment percentage and to inform LTCHs when their discharge payment
percentage for the period is not at least 50 percent. We also are
proposing that an LTCH would become subject to this payment
adjustment for each cost reporting period after its calculated
discharge payment percentage that is not at least 50 percent.
To establish a reinstatement process as required by the statute,
we are proposing that the payment adjustment for an LTCH would be
discontinued beginning with the discharges occurring in the cost
reporting period after the LTCH's discharge payment percentage is
calculated to be at least 50 percent. Furthermore, we are proposing
a probationary-cure period that would allow an LTCH the opportunity
to have the payment adjustment suspended for a cost reporting period
if, for the period of at least 5 consecutive months of the
immediately preceding 6-month period, the discharge payment
percentage is at least 50 percent. Under the proposed probationary-
cure period, an LTCH would have an opportunity to delay the
application of the payment adjustment until the end of the cost
reporting period, and waive the payment adjustment for that cost
reporting period if the discharge payment percentage for that cost
reporting period is ultimately found to be at least 50 percent.
As noted above, under our proposal, an LTCH would be first
subject to a potential payment adjustment based on the hospital's
discharge payment percentage for its FY 2020 cost reporting period.
Hospitals would be notified of that percentage in FY 2021, with the
payment adjustment taking effect in FY 2022. Therefore, we do not
estimate any effect on LTCH PPS payments until FY 2022. Based on the
most recent information available at the time of development of this
proposed rule, we estimate that, for FY 2022, our proposal would
reduce Medicare spending under the LTCH PPS by approximately $60
million. While we expect that there would be less than the maximum
estimated savings due to the proposed inclusion of a provisional-
cure period, at this time we do not have a reliable estimate of the
effect of that policy on the estimated savings.
Based on the FY 2017 claims data (the most recent set of full
claims available), on average, each discharge from an LTCH that
fails to meet the 50-percent patient discharge threshold would
result in a payment decrease of approximately $20,200 for LTCH PPS
standard Federal payment rate discharges and an estimated payment
increase of approximately $1,700 for site neutral payment rate
discharges. To estimate the number of discharges, we assumed that
LTCHs that fail to meet the 50-percent patient discharge threshold
are those whose discharge payment percentage is below 40 percent
based on FY 2017 claims data. We expect that an LTCH whose discharge
payment percentage is at least 40 percent based on FY 2017 claims
data will adjust its admission/discharge practices, such that it
would no longer be below the 50-percent patient discharge threshold.
Applying our actuary's assumption of a 74-percent to 26-percent
split between LTCH PPS standard Federal payment rate discharges and
site neutral payment rate discharges in FY 2022, we estimate there
would be 3,475 LTCH PPS standard Federal payment rate discharges and
8,670 site neutral payment rate discharges. The FY 2017 estimate is
inflated to FY 2022, resulting in estimated savings of $60 million
(comprised of approximately $80 million in savings from LTCH PPS
standard Federal payment rate discharges and approximately $20
million in costs from site neutral payment rate discharges).
4. Anticipated Effects of Proposed LTCH PPS Payment Rate Changes and
Policy Changes
a. Budgetary Impact
Section 123(a)(1) of the BBRA requires that the PPS developed
for LTCHs ``maintain budget neutrality.'' We believe that the
statute's mandate for budget neutrality applies only to the first
year of the implementation of the LTCH PPS (that is, FY 2003).
Therefore, in calculating the FY 2003 standard Federal payment rate
under Sec. 412.523(d)(2), we set total estimated payments for FY
2003 under the LTCH PPS so that estimated aggregate payments under
the LTCH PPS were estimated to equal the amount that would have been
paid if the LTCH PPS had not been implemented.
Section 1886(m)(6)(A) of the Act establishes a dual rate LTCH
PPS payment structure with two distinct payment rates for LTCH
discharges beginning in FY 2016. Under this statutory change, LTCH
discharges that meet the patient-level criteria for exclusion from
the site neutral payment rate (that is, LTCH PPS standard Federal
payment rate cases) are paid based on the LTCH PPS standard Federal
payment rate. LTCH discharges paid at the site neutral payment rate
are generally paid the lower of the IPPS comparable per diem amount,
reduced by 4.6 percent for FYs 2018 through 2026, including any
applicable HCO payments, or 100 percent of the estimated cost of the
case, reduced by 4.6 percent. The statute also establishes a
transitional payment method for cases that are paid at the site
neutral payment rate for LTCH discharges occurring in cost reporting
periods beginning during FY 2016 through FY 2019, under which the
site neutral payment rate cases are paid based on a blended payment
rate calculated as 50 percent of the applicable site neutral payment
rate amount for the discharge and 50 percent of the applicable LTCH
PPS standard Federal payment rate for the discharge.
As discussed in section I.J. of this Appendix, we project an
increase in aggregate LTCH PPS payments in FY 2020 of approximately
$37 million. This estimated increase in payments reflects the
projected increase in payments to LTCH PPS standard Federal payment
rate cases of approximately $79 million and the projected decrease
in payments to site neutral payment rate cases of approximately $41
million under the dual rate LTCH PPS payment rate structure required
by the statute beginning in FY 2016.
As discussed in section V.D. of the Addendum to this proposed
rule, our actuaries project cost and resource changes for site
neutral payment rate cases due to the site neutral payment rates
required under the statute. Specifically, our actuaries project that
the costs and resource use for cases paid at the site neutral
payment rate will likely be lower, on average, than the costs and
resource use for cases paid at the LTCH PPS standard Federal payment
rate, and will likely mirror the costs and resource use for IPPS
cases assigned to the same MS-DRG. While we are able to incorporate
this projection at an aggregate level into our payment modeling,
because the historical claims data that we are using in this
proposed rule to project estimated FY 2020 LTCH PPS payments (that
is, FY 2018 LTCH claims data) do not reflect this actuarial
projection, we are unable to model the impact of the proposed change
in LTCH PPS payments for site neutral payment rate cases at the same
level of detail with which we are able to model the impacts of the
proposed changes to LTCH PPS payments for LTCH PPS standard Federal
payment rate cases. Therefore, Table IV only reflects proposed
changes in LTCH PPS payments for LTCH PPS standard Federal payment
rate cases and, unless otherwise noted, the remaining discussion in
section I.J.4. of this Appendix refers only to the impact on
proposed LTCH PPS payments for LTCH PPS standard Federal payment
rate cases. In the following section, we present our provider impact
analysis for the proposed changes that affect LTCH PPS payments for
LTCH PPS standard Federal payment rate cases.
b. Impact on Providers
The basic methodology for determining a per discharge payment
for LTCH PPS standard Federal payment rate cases is
[[Page 19666]]
currently set forth under Sec. Sec. 412.515 through 412.533 and
412.535. In addition to adjusting the LTCH PPS standard Federal
payment rate by the MS-LTC-DRG relative weight, we make adjustments
to account for area wage levels and SSOs. LTCHs located in Alaska
and Hawaii also have their payments adjusted by a COLA. Under our
application of the dual rate LTCH PPS payment structure, the LTCH
PPS standard Federal payment rate is generally only used to
determine payments for LTCH PPS standard Federal payment rate cases
(that is, those LTCH PPS cases that meet the statutory criteria to
be excluded from the site neutral payment rate). LTCH discharges
that do not meet the patient-level criteria for exclusion are paid
the site neutral payment rate, which we are calculating as the lower
of the IPPS comparable per diem amount as determined under Sec.
412.529(d)(4), reduced by 4.6 percent for FYs 2018 through 2026,
including any applicable outlier payments, or 100 percent of the
estimated cost of the case as determined under existing Sec.
412.529(d)(2). In addition, when certain thresholds are met, LTCHs
also receive HCO payments for both LTCH PPS standard Federal payment
rate cases and site neutral payment rate cases that are paid at the
IPPS comparable per diem amount.
To understand the impact of the proposed changes to the LTCH PPS
payments for LTCH PPS standard Federal payment rate cases presented
in this proposed rule on different categories of LTCHs for FY 2020,
it is necessary to estimate payments per discharge for FY 2019 using
the rates, factors, and the policies established in the FY 2019
IPPS/LTCH PPS final rule and estimate payments per discharge for FY
2020 using the proposed rates, factors, and the policies in this FY
2020 IPPS/LTCH PPS proposed rule (as discussed in section VII. of
the preamble of this proposed rule and section V. of the Addendum to
this proposed rule). As discussed elsewhere in this proposed rule,
these estimates are based on the best available LTCH claims data and
other factors, such as the application of inflation factors to
estimate costs for HCO cases in each year. The resulting analyses
can then be used to compare how our policies applicable to LTCH PPS
standard Federal payment rate cases affect different groups of
LTCHs.
For the following analysis, we group hospitals based on
characteristics provided in the OSCAR data, cost report data in
HCRIS, and PSF data. Hospital groups included the following:
Location: Large urban/other urban/rural.
Participation date.
Ownership control.
Census region.
Bed size.
c. Calculation of Proposed LTCH PPS Payments for LTCH PPS Standard
Federal Payment Rate Cases
For purposes of this impact analysis, to estimate the per
discharge payment effects of our proposed policies on proposed
payments for LTCH PPS standard Federal payment rate cases, we
simulated FY 2019 and proposed FY 2020 payments on a case-by-case
basis using historical LTCH claims from the FY 2018 MedPAR files
that met or would have met the criteria to be paid at the LTCH PPS
standard Federal payment rate if the statutory patient-level
criteria had been in effect at the time of discharge for all cases
in the FY 2018 MedPAR files. For modeling FY 2019 LTCH PPS payments,
we used the FY 2019 standard Federal payment rate of $41,558.68 (or
$40,738.57 for LTCHs that failed to submit quality data as required
under the requirements of the LTCH QRP). Similarly, for modeling
payments based on the proposed FY 2020 LTCH PPS standard Federal
payment rate, we used the proposed FY 2020 standard Federal payment
rate of $42,950.91 (or $42,114.47 for LTCHs that failed to submit
quality data as required under the requirements of the LTCH QRP). In
each case, we applied the applicable adjustments for area wage
levels and the COLA for LTCHs located in Alaska and Hawaii.
Specifically, for modeling FY 2019 LTCH PPS payments, we used the
current FY 2019 labor-related share (66.0 percent), the wage index
values established in the Tables 12A and 12B listed in the Addendum
to the FY 2019 IPPS/LTCH PPS final rule (which are available via the
internet on the CMS website), the FY 2019 HCO fixed-loss amount for
LTCH PPS standard Federal payment rate cases of $27,121 (as
reflected in the FY 2019 IPPS/LTCH PPS correction notice to the
final rule), and the FY 2019 COLA factors (shown in the table in
section V.C. of the Addendum to that final rule) to adjust the FY
2019 nonlabor-related share (34.0 percent) for LTCHs located in
Alaska and Hawaii. Similarly, for modeling proposed FY 2020 LTCH PPS
payments, we used the proposed FY 2020 LTCH PPS labor-related share
(66.0 percent), the proposed FY 2020 wage index values from Tables
12A and 12B listed in section VI. of the Addendum to this proposed
rule (which are available via the internet on the CMS website), the
proposed FY 2020 fixed-loss amount for LTCH PPS standard Federal
payment rate cases of $29,997 (as discussed in section V.D.3. of the
Addendum to this proposed rule), and the proposed FY 2020 COLA
factors (shown in the table in section V.C. of the Addendum to this
proposed rule) to adjust the FY 2020 nonlabor-related share (34.0
percent) for LTCHs located in Alaska and Hawaii. We note that in
modeling payments for HCO cases for LTCH PPS standard Federal
payment rate cases, we applied an inflation factor of 2.7 percent
(determined by the Office of the Actuary) to update the FY 2018
costs of each case to FY 2019, and an inflation factor of 6.0
percent (determined by the Office of the Actuary) to update the FY
2018 costs of each case to FY 2020.
The impacts that follow reflect the estimated ``losses'' or
``gains'' among the various classifications of LTCHs from FY 2019 to
FY 2020 based on the proposed payment rates and proposed policy
changes applicable to LTCH PPS standard Federal payment rate cases
presented in this proposed rule. Table IV illustrates the estimated
aggregate impact of the proposed change in LTCH PPS payments for
LTCH PPS standard Federal payment rate cases among various
classifications of LTCHs. (As discussed previously, these impacts do
not include LTCH PPS site neutral payment rate cases.)
The first column, LTCH Classification, identifies the
type of LTCH.
The second column lists the number of LTCHs of each
classification type.
The third column identifies the number of LTCH cases
expected to meet the LTCH PPS standard Federal payment rate
criteria.
The fourth column shows the estimated FY 2019 payment
per discharge for LTCH cases expected to meet the LTCH PPS standard
Federal payment rate criteria (as described previously).
The fifth column shows the estimated FY 2020 payment
per discharge for LTCH cases expected to meet the LTCH PPS standard
Federal payment rate criteria (as described previously).
The sixth column shows the percentage change in
estimated payments per discharge for LTCH cases expected to meet the
LTCH PPS standard Federal payment rate criteria from FY 2019 to FY
2020 due to the proposed annual update to the standard Federal rate
(as discussed in section V.A.2. of the Addendum to this proposed
rule).
The seventh column shows the percentage change in
estimated payments per discharge for LTCH PPS standard Federal
payment rate cases from FY 2019 to FY 2020 for proposed changes to
the area wage level adjustment (that is, the wage indexes and the
labor-related share), including the application of the proposed area
wage level budget neutrality factor (as discussed in section V.B. of
the Addendum to this proposed rule).
The eighth column shows the percentage change in
estimated payments per discharge for LTCH PPS standard Federal
payment rate cases from FY 2019 (Column 4) to FY 2020 (Column 5) for
all proposed changes.
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d. Results
Based on the FY 2018 LTCH cases (from 384 LTCHs) that were used
for the analyses in this proposed rule, we have prepared the
following summary of the impact (as shown in Table IV) of the
proposed LTCH PPS payment rate and proposed policy changes for LTCH
PPS standard Federal payment rate cases presented in this proposed
rule. The impact analysis in Table IV shows that estimated payments
per discharge for LTCH PPS standard Federal payment rate cases are
projected to increase 2.3 percent, on average, for all LTCHs from FY
2019 to FY 2020 as a result of the proposed payment rate and
proposed policy changes applicable to LTCH PPS standard Federal
payment rate cases presented in this proposed rule. This estimated
2.3 percent increase in LTCH PPS
[[Page 19670]]
payments per discharge was determined by comparing estimated FY 2020
LTCH PPS payments (using the proposed payment rates and factors
discussed in this proposed rule) to estimated FY 2019 LTCH PPS
payments for LTCH discharges which would be LTCH PPS standard
Federal payment rate cases if the dual rate LTCH PPS payment
structure was or had been in effect at the time of the discharge (as
described in section I.J.4. of this Appendix).
As stated previously, we are proposing to update the LTCH PPS
standard Federal payment rate for FY 2020 by 2.7 percent. For LTCHs
that fail to submit quality data under the requirements of the LTCH
QRP, as required by section 1886(m)(5)(C) of the Act, a 2.0
percentage point reduction is applied to the annual update to the
LTCH PPS standard Federal payment rate. In addition, we are
proposing to apply the one-time budget neutrality adjustment factor
of 0.999856 for the cost of eliminating the 25-percent threshold
policy in FY 2020 as discussed in section VII.D. of the preamble of
this proposed rule. Consistent with Sec. 412.523(d)(4), we also are
proposing to apply an area wage level budget neutrality factor to
the proposed FY 2020 LTCH PPS standard Federal payment rate of
1.0064747, based on the best available data at this time, to ensure
that any proposed changes to the area wage level adjustment (that
is, the proposed annual update of the wage index values and labor-
related share) will not result in any change (increase or decrease)
in estimated aggregate LTCH PPS standard Federal payment rate
payments. As we also explained earlier in this section, for most
categories of LTCHs (as shown in Table IV, Column 6), the estimated
payment increase due to the proposed 2.7 percent annual update to
the LTCH PPS standard Federal payment rate is projected to result in
approximately a 2.6 percent increase in estimated payments per
discharge for LTCH PPS standard Federal payment rate cases for all
LTCHs from FY 2019 to FY 2020. This is because our estimate of the
proposed changes in payments due to the proposed update to the LTCH
PPS standard Federal payment rate also reflects estimated payments
for SSO cases that are paid using a methodology that is not entirely
affected by the update to the LTCH PPS standard Federal payment
rate. Consequently, for certain hospital categories, we estimate
that payments to LTCH PPS standard Federal payment rate cases may
increase by less than 2.7 percent due to the proposed annual update
to the LTCH PPS standard Federal payment rate for FY 2020.
(1) Location
Based on the most recent available data, the vast majority of
LTCHs are located in urban areas. Only approximately 5 percent of
the LTCHs are identified as being located in a rural area, and
approximately 4 percent of all LTCH PPS standard Federal payment
rate cases are expected to be treated in these rural hospitals. The
impact analysis presented in Table IV shows that the proposed
overall average percent increase in estimated payments per discharge
for LTCH PPS standard Federal payment rate cases from FY 2019 to FY
2020 for all hospitals is 2.3 percent. For rural LTCHs, estimated
payments for LTCH PPS standard Federal payment rate cases are
expected to increase 2.2 percent. For urban LTCHs, we estimate an
increase of 2.3 percent from FY 2019 to FY 2020. Among the urban
LTCHs, large urban LTCHs are projected to experience an increase of
2.2 percent in estimated payments per discharge for LTCH PPS
standard Federal payment rate cases from FY 2019 to FY 2020, and
such payments for the remaining urban LTCHs are projected to
increase 2.4 percent, as shown in Table IV.
(2) Participation Date
LTCHs are grouped by participation date into four categories:
(1) Before October 1983; (2) between October 1983 and September
1993; (3) between October 1993 and September 2002; and (4) October
2002 and after. Based on the most recent available data, the
categories of LTCHs with the largest expected percentage of LTCH PPS
standard Federal payment rate cases (approximately 47 percent) are
in LTCHs that began participating in the Medicare program between
October 1993 and September 2002, and they are projected to
experience a 2.4 percent increase in estimated payments per
discharge for LTCH PPS standard Federal payment rate cases from FY
2019 to FY 2020, as shown in Table IV.
Approximately 11 percent of LTCHs began participating in the
Medicare program before October 1983, and these LTCHs are projected
to experience an average percent increase of 2.0 percent in
estimated payments per discharge for LTCH PPS standard Federal
payment rate cases from FY 2019 to FY 2020. Approximately 3 percent
of LTCHs began participating in the Medicare program between October
1983 and September 1993, and these LTCHs are projected to experience
an increase of 2.6 percent in estimated payments for LTCH PPS
standard Federal payment rate cases from FY 2019 to FY 2020. LTCHs
that began participating in the Medicare program after October 1,
2002, which treat approximately 37 percent of all LTCH PPS standard
Federal payment rate cases, are projected to experience a 2.2
percent increase in estimated payments from FY 2019 to FY 2020.
(3) Ownership Control
LTCHs are grouped into three categories based on ownership
control type: voluntary, proprietary, and government. Based on the
most recent available data, approximately 20 percent of LTCHs are
identified as voluntary (Table IV). The majority (approximately 77
percent) of LTCHs are identified as proprietary, while government
owned and operated LTCHs represent approximately 4 percent of LTCHs.
Based on ownership type, voluntary LTCHs are expected to experience
a 2.5 percent increase in payments to LTCH PPS standard Federal
payment rate cases, while proprietary LTCHs are expected to
experience an average increase of 2.3 percent in payments to LTCH
PPS standard Federal payment rate cases. Government owned and
operated LTCHs, meanwhile, are expected to experience a 2.5 percent
increase in payments to LTCH PPS standard Federal payment rate cases
from FY 2019 to FY 2020.
(4) Census Region
Estimated payments per discharge for LTCH PPS standard Federal
payment rate cases for FY 2020 are projected to increase across all
census regions. LTCHs located in the South Atlantic are projected to
experience the largest increase at 2.5 percent followed by the East
North Central at 2.4 percent. The remaining regions are projected to
increase by either 2.2 or 2.3 percent. These regional variations are
largely due to proposed updates in the wage index.
(5) Bed Size
LTCHs are grouped into six categories based on bed size: 0-24
beds; 25-49 beds; 50-74 beds; 75-124 beds; 125-199 beds; and greater
than 200 beds. We project that LTCHs with 0-24 beds will experience
the largest increase in payments for LTCH PPS standard Federal
payment rate cases of 2.9 percent. LTCHs with 25-49 beds and 50-74
beds are both projected to experience an increase of 2.2 percent.
LTCHs with 75-124 beds and LTCHs with 200+ beds are both projected
to experience an increase of 2.5 percent. LTCHs with 125-199 beds
are projected to experience an increase in payments of 2.3 percent.
5. Effect on the Medicare Program
As stated previously, we project that the provisions of this
proposed rule would result in an increase in estimated aggregate
LTCH PPS payments to LTCH PPS standard Federal payment rate cases in
FY 2020 relative to FY 2019 of approximately $79 million (or
approximately 2.3 percent) for the 384 LTCHs in our database.
Although, as stated previously, the hospital-level impacts do not
include LTCH PPS site neutral payment rate cases, we estimate that
the provisions of this proposed rule would result in a decrease in
estimated aggregate LTCH PPS payments to site neutral payment rate
cases in FY 2020 relative to FY 2019 of approximately $41 million
(or approximately -4.9 percent) for the 384 LTCHs in our database.
Therefore, we project that the provisions of this proposed rule
would result in an increase in estimated aggregate LTCH PPS payments
for all LTCH cases in FY 2020 relative to FY 2019 of approximately
$37 million (or approximately 0.9 percent) for the 384 LTCHs in our
database.
6. Effect on Medicare Beneficiaries
Under the LTCH PPS, hospitals receive payment based on the
average resources consumed by patients for each diagnosis. We do not
expect any changes in the quality of care or access to services for
Medicare beneficiaries as a result of this proposed rule, but we
continue to expect that paying prospectively for LTCH services will
enhance the efficiency of the Medicare program. As discussed above,
we do not expect the continued implementation of the site neutral
payment system to have a negative impact on access to or quality of
care, as demonstrated in areas where there is little or no LTCH
presence, general short-term acute care hospitals are effectively
providing treatment for the same types of patients that are treated
in LTCHs.
[[Page 19671]]
K. Effects of Proposed Requirements for the Hospital Inpatient
Quality Reporting (IQR) Program
In section VIII.A. of the preamble of this proposed rule, we
discuss our current and proposed requirements for hospitals to
report quality data under the Hospital IQR Program in order to
receive the full annual percentage increase for the FY 2021 payment
determination and subsequent years.
In this proposed rule, we are proposing to: (1) Adopt two new
opioid-related eCQMs, Safe Use of Opioids--Concurrent Prescribing
eCQM (NQF #3316e) and Hospital Harm--Opioid-Related Adverse Events
eCQM, beginning with the CY 2021 reporting period/FY 2023 payment
determination; (2) adopt the Hybrid Hospital-Wide Readmission
Measure with Claims and Electronic Health Record Data (Hybrid HWR
measure) (NQF #2879) in a stepwise manner, beginning with two years
of voluntary reporting periods which would run from July 1, 2021
through June 30, 2022, and from July 1, 2022 through June 30, 2023,
before requiring reporting of the measure for the reporting period
that would run from July 1, 2023 through June 30, 2024, impacting
the FY 2026 payment determination and subsequent years; (3) remove
the Claims-Based Hospital-Wide All-Cause Unplanned Readmission
Measure (NQF #1789) (HWR claims-only measure) beginning with the FY
2026 payment determination; (4) extend the current eCQM reporting
and submission requirements for the CY 2020 reporting period/FY 2022
payment determination and CY 2021 reporting period/FY 2023 payment
determination; (5) change the eCQM reporting and submission
requirements for the CY 2022 reporting period/FY 2024 payment
determination, such that hospitals would be required to report one,
self-selected calendar quarter of data for: (a) Three self-selected
eCQMs, and (b) the proposed Safe Use of Opioids--Concurrent
Prescribing eCQM (NQF #3316e), for a total of four eCQMs; (6)
continue requiring that EHRs be certified to all available eCQMs
used in the Hospital IQR Program for the CY 2020 reporting period/FY
2022 payment determination and subsequent years; and (7) establish
reporting and submission requirements for the Hybrid HWR measure.
We estimate a total information collection burden increase of
2,211 hours (associated with our proposal to adopt the Hybrid HWR
measure) and a total cost increase related to information collection
of approximately $83,266 (due to this proposal and our updated
hourly wage plus benefits estimate), beginning with the first
voluntary reporting period, which runs from July 1, 2021 through
June 30, 2022. We refer readers to section X.B.3. of the preamble of
this proposed rule (information collection requirements) for a
detailed discussion of the calculations estimating the changes to
the burden for submitting data to the Hospital IQR Program.
With regard to our proposals to add two new opioid-related eCQMs
to the eCQM measure set, while we expect no change to the
information collection burden for the Hospital IQR Program as
discussed in section X.B.3.b. of the preamble of this proposed rule
because we are also propos eCQM reporting requirements such that the
total number of eCQMs that would be reported and the total quarters
of data would remain unchanged from previously finalized
requirements, we expect some investment in EHR system updates. We
are also proposing that hospitals use certified electronic heath
record technology (CEHRT) that are certified to report all available
eCQMs. We expect no change to the information collection burden for
the Hospital IQR Program as discussed in section X.B.3.e.(3) of the
preamble of this proposed rule because this policy does not require
hospitals to submit new data to CMS and we do not require CEHRT to
be recertified each time it is updated to a more recent version of
the eCQM electronic specifications. However, for certifying new
eCQMs in the eCQM measure set, we expect some costs for hospitals
and EHR vendors in certifying the two new proposed eCQMs so that
hospitals have the option to report the new eCQMs if they are
finalized. For all of these proposals, due to the differences in the
build of respective CEHRT deployed in hospitals, the mapping
required to capture required data for measure calculation, and the
range of hospital participation in the development, implementation,
and testing of new CEHRT functionality, an estimated cost impact of
the proposals is not quantifiable as it will vary by CEHRT and
hospital.
Historically, 100 hospitals, on average, that participate in the
Hospital IQR Program do not receive the full annual percentage
increase in any fiscal year due to the failure to meet all
requirements of this Program. We anticipate that the number of
hospitals not receiving the full annual percentage increase will be
approximately the same as in past years.
L. Effects of Proposed Requirements for the PPS-Exempt Cancer
Hospital Quality Reporting (PCHQR) Program
In section VIII.B. of the preamble of this proposed rule, we
discuss our proposed policies for the quality data reporting program
for PPS-exempt cancer hospitals (PCHs), which we refer to as the
PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) Program. The
PCHQR Program is authorized under section 1866(k) of the Act, which
was added by section 3005 of the Affordable Care Act. There is no
financial impact to PCH Medicare reimbursement if a PCH does not
submit data.
In section VIII.B.3.b. of the preamble of this proposed rule, we
are proposing to remove one web-based, structural measure beginning
with the FY 2022 program year: External Beam Radiotherapy (EBRT) for
Bone Metastases (formerly NQF #1822). In addition, in section
VIII.B.4. of the preamble of this proposed rule, we are proposing to
adopt a claims-based measure for the FY 2022 program year and
subsequent years: Surgical Treatment Complications for Localized
Prostate Cancer.
As explained in section X.B.4. of the preamble of this proposed
rule, we anticipate that the proposed removal of the External Beam
Radiotherapy (EBRT) for Bone Metastases (formerly NQF #1822) measure
will reduce the overall burden on participating PCHs by 15-mins per
PCH. We estimate a total annual reduction of approximately 3 hours
for all 11 PCHs (15 minutes x 11 PCHs/60 minutes per hour), due to
the proposed removal of this measure.
We do not anticipate any change in burden on the PCHs associated
with our proposed adoption of the Surgical Treatment Complications
for Localized Prostate Cancer measure into the PCHQR Program
beginning with the FY 2022 program year. This measure is claims-
based and does not require PCHs to report any additional data beyond
that already submitted on Medicare administrative claims for payment
purposes. Therefore, we do not believe that there would be any
associated change in burden resulting from this proposal.
M. Effects of Proposed Requirements for the Long-Term Care Hospital
Quality Reporting Program (LTCH QRP)
Under the LTCH QRP, the Secretary must reduce by 2 percentage
points the annual update to the LTCH PPS standard Federal rate for
discharges for an LTCH during a fiscal year if the LTCH has not
complied with the LTCH QRP requirements specified for that fiscal
year. Information is not available to determine the precise number
of LTCHs that will not meet the requirements to receive the full
annual update for the FY 2020 payment determination.
We believe that the burden and costs associated with the LTCH
QRP is the time and effort associated with complying with the
requirements of the LTCH QRP. We intend to closely monitor the
effects of this quality reporting program on LTCHs to help
facilitate successful reporting outcomes through ongoing stakeholder
education, national trainings, and help desk support.
We refer readers to section X.B.6. of the preamble of this
proposed rule (information collection requirements) for a detailed
discussion of the burden associated with the proposed new
requirements for the LTCH QRP.
N. Effects of Proposed Requirements Regarding the Promoting
Interoperability Program
In section VIII.D. of the preamble of this proposed rule, we
discuss our current and proposed requirements for eligible hospitals
and CAHs participating in the Medicare and Medicaid Promoting
Interoperability Programs.
In this proposed rule, we are proposing the following changes to
the Medicare Promoting Interoperability Program: (1) Eliminate the
requirement that, for the FY 2020 payment adjustment year, for an
eligible hospital that has not successfully demonstrated it is a
meaningful EHR user in a prior year, the EHR reporting period in CY
2019 must end before and the eligible hospital must successfully
register for and attest to meaningful use no later than October 1,
2019; (2) establish an EHR reporting period of a minimum of any
continuous 90-day period in CY 2021 for new and returning
participants (eligible hospitals and CAHs) in the Medicare Promoting
Interoperability Program attesting to CMS; (3) require that the
Medicare Promoting Interoperability Program measure actions must
occur within the EHR reporting period
[[Page 19672]]
beginning with the EHR reporting period in CY 2020; (4) revise the
Query of PDMP measure to change the reporting requirement from
numerator and denominator to a ``yes/no'' response beginning with CY
2019 for eligible hospitals and CAHs that attest to CMS under the
Medicare Promoting Interoperability Program, make it an optional
measure worth five bonus points in CY 2020, remove the exclusions
associated with this measure in CY 2020, and clearly state our
intended policy that the measure is worth a full 5 bonus points in
CY 2019 and CY 2020; (5) change the maximum points available for the
e-Prescribing measure to 10 points beginning in CY 2020, in the
event we finalize the proposed changes to the Query of PDMP measure;
(6) remove the Verify Opioid Treatment Agreement measure beginning
in CY 2020 and clearly state our intended policy that the measure is
worth a full 5 bonus points in CY 2019; and (7) revise the Support
Electronic Referral Loops by Receiving and Incorporating Health
Information measure to more clearly capture the previously
established policy regarding CHERT use. We are also proposing to
amend our regulations to incorporate several of these proposals.
For CQM reporting under the Medicare and Medicaid Promoting
Interoperability Programs, in section VIII.D.6. of the preamble of
this proposed rule, we are making a number of proposals with respect
to the reporting of CQM data, including proposing to add two opioid-
related measures beginning with the reporting period in CY 2021 and
proposing the reporting period, reporting criteria, submission
period, and form and method requirements for CQM reporting in CY
2020. However, for the reporting period in CY 2020, these proposals
are continuations of current policies and therefore we do not
believe that there would be a change in burden for CY 2020.
As explained in section X.B.9. of the preamble of this proposed
rule, we estimate for CY 2020 a total information collection burden
decrease of 2,200 hours, associated with our proposal to revise the
Query of PDMP measure to change the reporting requirement from
numerator and denominator to a ``yes/no'' response beginning with CY
2019 for eligible hospitals and CAHs that attest to CMS under the
Medicare Promoting Interoperability Program, and a total cost
decrease of $130,102.50 related to information collection burden
cost estimates due to this proposal and our updated hourly wage plus
benefits estimate.
O. Alternatives Considered
This proposed rule contains a range of policies. It also
provides descriptions of the statutory provisions that are
addressed, identifies the proposed policies, and presents rationales
for our decisions and, where relevant, alternatives that were
considered.
1. Wage Index
We considered a number of alternatives to our proposed policies
discussed in section III.N.3. of the preamble of this proposed rule
to address wage index disparities. As described more fully in
section III.N.3.b. of the preamble of this proposed rule, we are
proposing to maintain budget neutrality for our proposal to increase
the wage index for hospitals with wage index values below the 25th
percentile wage index value (that is, low wage index hospitals) by
reducing the wage index of hospitals with wage index values above
the 75th percentile wage index value (that is, high wage index
hospitals). Specifically, as described in section III.N.3.b. of this
proposed rule, we are proposing to implement budget neutrality by
reducing the distance between the otherwise applicable wage index
for high wage index hospitals and the 75th percentile wage index
across all hospitals. As an alternative to this proposed budget
neutrality approach, we considered applying a budget neutrality
factor to the standardized amount rather than focusing the
adjustment on the wage index of high wage index hospitals. This
alternative approach would have been similar to the budget
neutrality approach proposed for the transition, as described more
fully in section III.N.3.d. of the preamble of this proposed rule.
As another alternative to addressing wage index disparities, we
also considered mirroring our proposed approach of raising the wage
index for low wage index hospitals in reducing the wage index values
for high wage index hospitals. As described more fully in section
III.N.3.a. of the preamble of this proposed rule, we are proposing
to increase the wage index for hospitals with a wage index below the
25th percentile wage index. The proposed increase in the wage index
for these hospitals would be equal to half the difference between
the otherwise applicable final wage index value for these hospitals
and the 25th percentile wage index value. Under the alternative
considered, we also would decrease the wage index for hospitals with
a wage index above the 75th percentile wage index by half the
difference between the otherwise applicable final wage index value
for these hospitals and the 75th percentile wage index value. We
would make the estimated net effect on payments of (1) the increase
in the wage index for hospitals below the 25th percentile and (2)
the decrease in the wage index for hospitals above the 75th
percentile budget neutral through an adjustment to the standardized
amount.
A third alternative we considered to address wage index
disparities was the creation of a national rural wage index area. We
considered whether there currently exists a national rural labor
market for hospital labor and, if not, whether we should facilitate
the creation of such a national rural labor market through the
establishment of this national rural wage index area. Currently, we
use statewide rural wage index areas based on the non-MSA area of
each State. Under the alternative we considered, we would create a
single national rural wage index area. A single national rural wage
index area and rural wage index value would arguably partially
address wage index disparities because the current rural area in
each State with a wage index value below the national rural wage
index value would rise to the national rural wage index value. A
national rural labor market area would also act to mitigate the
incentives to manipulate the rural floor because the effect of such
manipulations on the rural average hourly wage would be spread
across the national rural wage index area rather than targeted in a
single State. However, it should also be noted that the
establishment of a national rural wage index area would have a
negative impact on hospitals in the rural areas in States with
current rural wage index values above the national rural wage index
value because these current wage index values would decline to the
national rural wage index value.
In order to facilitate public consideration of these
alternatives considered for addressing wage index disparities, we
have created a file at the hospital level of the different wage
index values for each hospital under each of these alternatives
considered. This file is available on the FY 2020 proposed rule web
page on the CMS website as part of the FY 2020 Proposed Rule Data
Files.
2. New Technology Add-On Payments
As discussed in section II.H.8. of the preamble of this proposed
rule, in situations where a new medical device is part of the
Breakthrough Devices Program and has received FDA marketing
authorization, we are proposing an alternative inpatient new
technology add-on payment pathway to facilitate access to this
technology for Medicare beneficiaries. We also considered whether it
would be appropriate to apply this alternative inpatient new
technology add-on payment pathway in situations where a new drug is
part of an FDA expedited program for drugs and has received FDA
marketing authorization. However, in reviewing this issue, we noted
that the current drug-pricing system provides generous incentives
for innovation, but too often fails to deliver important medications
at an affordable cost. Making this policy applicable to drugs would
further incentive innovation but without decreasing cost, a key
priority of this Administration. In May 2018, President Donald Trump
and HHS Secretary Alex Azar released the American Patients First
blueprint, a comprehensive plan to lower drug prices and out-of-
pocket costs. Since the launch of the blueprint, we have been taking
action to turn the President's vision into action, and improve the
health and well-being of every American. While we continue to work
on these initiatives for drug affordability, we believe that it is
appropriate to distinguish between drugs and devices in our
consideration of a proposed policy change for transformative new
technologies.
3. Uncompensated Care Payments
Another policy area where an alternative was considered was in
the calculation of the FY 2020 Medicare uncompensated care payments
to hospitals, as discussed in greater detail in section IV.F.4.c. of
the preamble of this proposed rule. We are proposing to use
Worksheet S-10 data from the FY 2015 cost reports in the calculation
of Factor 3 for FY 2020. Although we are proposing to use Worksheet
S-10 data from the FY 2015 cost reports, we acknowledge that some
hospitals have raised concerns regarding the cost reporting
instructions in effect for FY 2015, especially compared to the
reporting
[[Page 19673]]
instructions that were effective for cost reporting periods
beginning on or after October 1, 2016. Therefore, as discussed in
section IV.F.4.c. of the preamble of this proposed rule, we also are
seeking public comments on whether, due to the changes in the cost
reporting instructions, we should use a single year of uncompensated
care data from the FY 2017 reports, instead of the FY 2015 reports,
to calculate Factor 3 for FY 2020.
4. LTCHs
Another policy area where an alternative was considered was in
the reinstatement process for LTCHs that do not meet the applicable
discharge payment percentage, as discussed in greater detail in
section VII.C. of the preamble of this proposed rule. We are
proposing to implement a special probationary reinstatement process.
Although we are proposing to use a special probationary
reinstatement process, we believe the normal reinstatement process
discussed in more detail in section VII.C. of the preamble of this
proposed rule would satisfy the statutory requirement without
further modification. Additionally, as discussed in more detail in
section VII.C. of the preamble of this proposed rule, in developing
our proposals for the a special probationary reinstatement process,
we are concerned that hospitals may be able to manipulate discharges
or delay billing in such a way as to artificially inflate their
discharge payment percentage for purposes of a special reinstatement
process if the special reinstatement process were not probationary.
We are soliciting public comments on whether to have a special
reinstatement process and, if so, whether it should be probationary.
5. eCQM
As discussed in section VIII.A.9.d.(4) of the preamble of this
proposed rule, in the context of proposing eCQM reporting and
submission requirements under the Hospital IQR Program for the CY
2022 reporting period/FY 2024 payment determination, hospitals would
be required to report one, self-selected calendar quarter of data
for three self-selected eCQMs and for all hospitals to report the
proposed Safe Use of Opioids--Concurrent Prescribing eCQM (NQF
#3316e) as their fourth eCQM. We also considered an alternative
whereby hospitals would have the option to select one of the two
proposed opioids-related eCQMs, the Safe Use of Opioids eCQM or
Opioid-Related Adverse Events eCQM, as their fourth required eCQM.
However, such an approach would add additional complexity to the
eCQM reporting requirements, and we believe that the Safe Use of
Opioids eCQM is more closely related to combating the current opioid
epidemic, as discussed in sections VIII.A.5.a. and VIII.A.9.d.(4) of
the preamble of this proposed rule, than the Opioid-Related Adverse
Events eCQM, which is focused on improved monitoring of patients who
receive opioids during hospitalization. Because the alternative
considered would not impact the collection of information for
hospitals, we do not expect these alternatives to affect the
reporting burden on hospitals. We considered this alternative and
are seeking public comment on it.
P. Reducing Regulation and Controlling Regulatory Costs
Executive Order 13771, titled Reducing Regulation and
Controlling Regulatory Costs, was issued on January 30, 2017. This
proposed rule, if finalized, is considered an E.O. 13771 regulatory
action. We estimate that this rule generates approximately $2.4
million in annualized costs, discounted at 7 percent relative to
fiscal year 2016, over a perpetual time horizon.
We discuss the estimated burden and costs for the Hospital IQR
Program in section X.B.3. of the preamble of this proposed rule, and
estimate that the impact of these proposed changes is an increase in
costs of approximately $25 per hospital annually or approximately
$83,266 for all hospitals annually.
We discuss the estimated burden and cost reductions for the
PCHQR Program in section X.B.4. of the preamble of this proposed
rule, and estimate that the impact of these proposed changes is a
reduction in costs of approximately $10 per PCH annually or
approximately $113 for all participating PCHs annually.
We discuss the estimated burden for the LTCH QRP in section
X.B.6. of the preamble of this proposed rule, and estimate that the
impact of these proposed changes is an increase in costs of
approximately $5,499.63 per LTCH annually or approximately
$2,282,346 for all LTCHs annually.
We do not anticipate an increase or decrease in burden and costs
for the Hospital Readmissions Reduction Program, the HAC Reduction
Program, or the Hospital Value-Based Purchasing Program based on the
proposed policies in this proposed rule.
Also, as noted in section I.R. of this Appendix, the regulatory
review cost for this proposed rule is $1,905,475.
------------------------------------------------------------------------
Amount of
Section of the proposed rule Description costs or
savings
------------------------------------------------------------------------
Section X.B.3. of the preamble. ICRs for the Hospital $83,266
IQR Program.
Section X.B.4. of the preamble. ICRs for the PCHQR ($113)
Program.
Section X.B.6. of the preamble. ICRs for the LTCH QRP.. 2,282,346
---------------
Total...................... ....................... 2,365,499
------------------------------------------------------------------------
Q. Overall Conclusion
1. Acute Care Hospitals
Acute care hospitals are estimated to experience an increase of
approximately $4.67 billion in FY 2020, taking into account
operating, capital, new technology, and low volume hospital payments
as modeled for this proposed rule. Approximately $4.4 billion of
this estimated increase is due to the proposed changes in operating
payments, including $0.2 billion in uncompensated care payments
(discussed in sections I.G. and I.H. of this Appendix),
approximately $174 million is due to the change in capital payments
(discussed in section I.I. of this Appendix), approximately $110
million is due to the change in new technology add-on payments
(discussed in section I.H. of this Appendix), and approximately $25
million is due to the change in low-volume hospital payments
(discussed in section I.H. of this Appendix). Total differs from the
sum of the components due to rounding.
Table I. of section I.G. of this Appendix also demonstrates the
estimated redistributional impacts of the IPPS budget neutrality
requirements for the proposed MS-DRG and wage index changes, and for
the wage index reclassifications under the MGCRB.
We estimate that hospitals would experience a 1.9 percent
increase in capital payments per case, as shown in Table III. of
section I.I. of this Appendix. We project that there would be a $174
million increase in capital payments in FY 2020 compared to FY 2019.
The discussions presented in the previous pages, in combination
with the remainder of this proposed rule, constitute a regulatory
impact analysis.
2. LTCHs
Overall, LTCHs are projected to experience an increase in
estimated payments per discharge in FY 2020. In the impact analysis,
we are using the proposed rates, factors, and policies presented in
this proposed rule based on the best available claims and CCR data
to estimate the change in payments under the LTCH PPS for FY 2020.
Accordingly, based on the best available data for the 384 LTCHs in
our database, we estimate that overall FY 2020 LTCH PPS payments
will increase approximately $37 million relative to FY 2019 as a
result of the proposed payment rates and factors presented in this
proposed rule.
R. Regulatory Review Costs
If regulations impose administrative costs on private entities,
such as the time needed to read and interpret a rule, we should
estimate the cost associated with regulatory
[[Page 19674]]
review. Due to the uncertainty involved with accurately quantifying
the number of entities that would review the proposed rule, we
assumed that the total number of timely pieces of correspondence on
last year's proposed rule would be the number of reviewers of the
proposed rule. We acknowledge that this assumption may understate or
overstate the costs of reviewing the rule. It is possible that not
all commenters reviewed last year's rule in detail, and it is also
possible that some reviewers chose not to comment on the proposed
rule. For those reasons, and consistent with our approach in
previous rulemakings (82 FR 38585; 83 FR 41777), we believe that the
number of past commenters would be a fair estimate of the number of
reviewers of the proposed rule. We welcome any public comments on
the approach in estimating the number of entities that will review
this proposed rule.
We also recognize that different types of entities are in many
cases affected by mutually exclusive sections of the proposed rule.
Therefore, for the purposes of our estimate, and consistent with our
approach in previous rulemaking (82 FR 38585; 83 FR 41777), we
assume that each reviewer read approximately 50 percent of the
proposed rule. We welcome public comments on this assumption.
We have used the number of timely pieces of correspondence on
the FY 2019 proposed rule as our estimate for the number of
reviewers of this proposed rule. We continue to acknowledge the
uncertainty involved with using this number, but we believe it is a
fair estimate due to the variety of entities affected and the
likelihood that some of them choose to rely (in full or in part) on
press releases, newsletters, fact sheets, or other sources rather
than the comprehensive review of preamble and regulatory text. Using
the wage information from the BLS for medical and health service
managers (Code 11-9111), we estimate that the cost of reviewing the
proposed rule is $107.38 per hour, including overhead and fringe
benefits (https://www.bls.gov/oes/current/oes_nat.htm). Assuming an
average reading speed, we estimate that it would take approximately
21 hours for the staff to review half of this proposed rule. For
each IPPS hospital or LTCH that reviews this proposed rule, the
estimated cost is $2,255 (21 hours x $107.38). Therefore, we
estimate that the total cost of reviewing this proposed rule is
$1,905,475 ($2,255 x 845 reviewers).
II. Accounting Statements and Tables
A. Acute Care Hospitals
As required by OMB Circular A-4 (available at https://obamawhitehouse.archives.gov/omb/circulars_a-004_a-4/ and https://georgewbush-whitehouse.archives.gov/omb/circulars/a004/a-4.html), in
the following Table V., we have prepared an accounting statement
showing the classification of the expenditures associated with the
provisions of this proposed rule as they relate to acute care
hospitals. This table provides our best estimate of the change in
Medicare payments to providers as a result of the proposed changes
to the IPPS presented in this proposed rule. All expenditures are
classified as transfers to Medicare providers.
As shown below in Table V., the net costs to the Federal
Government associated with the proposed policies in this proposed
rule are estimated at $4.67 billion.
Table V--Accounting Statement: Classification of Estimated Expenditures
Under the IPPS From FY 2019 to FY 2020
------------------------------------------------------------------------
Category Transfers
------------------------------------------------------------------------
Annualized Monetized Transfers......... $4.67 billion.
From Whom to Whom...................... Federal Government to IPPS
Medicare Providers.
------------------------------------------------------------------------
B. LTCHs
As discussed in section I.J. of this Appendix, the impact
analysis of the proposed payment rates and factors presented in this
proposed rule under the LTCH PPS is projected to result in an
increase in estimated aggregate LTCH PPS payments in FY 2020
relative to FY 2019 of approximately $37 million based on the data
for 384 LTCHs in our database that are subject to payment under the
LTCH PPS. Therefore, as required by OMB Circular A-4 (available at:
https://obamawhitehouse.archives.gov/omb/circulars_a004_a-4/ and
https://georgewbush-whitehouse.archives.gov/omb/circulars/a004/a-4.html), in Table VI., we have prepared an accounting statement
showing the classification of the expenditures associated with the
provisions of this proposed rule as they relate to the changes to
the LTCH PPS. Table VI. provides our best estimate of the estimated
change in Medicare payments under the LTCH PPS as a result of the
proposed payment rates and factors and other provisions presented in
this proposed rule based on the data for the 384 LTCHs in our
database. All expenditures are classified as transfers to Medicare
providers (that is, LTCHs).
As shown in Table VI. below, the net cost to the Federal
Government associated with the proposed policies for LTCHs in this
proposed rule are estimated at $37 million.
Table VI--Accounting Statement: Classification of Estimated Expenditures
From the FY 2019 LTCH PPS to the FY 2020 LTCH PPS
------------------------------------------------------------------------
Category Transfers
------------------------------------------------------------------------
Annualized Monetized Transfers......... $37 million.
From Whom to Whom...................... Federal Government to LTCH
Medicare Providers.
------------------------------------------------------------------------
III. Regulatory Flexibility Act (RFA) Analysis
The RFA requires agencies to analyze options for regulatory
relief of small entities. For purposes of the RFA, small entities
include small businesses, nonprofit organizations, and small
government jurisdictions. We estimate that most hospitals and most
other providers and suppliers are small entities as that term is
used in the RFA. The great majority of hospitals and most other
health care providers and suppliers are small entities, either by
being nonprofit organizations or by meeting the SBA definition of a
small business (having revenues of less than $7.5 million to $38.5
million in any 1 year). (For details on the latest standards for
health care providers, we refer readers to page 36 of the Table of
Small Business Size Standards for NAIC 622 found on the SBA website
at: http://www.sba.gov/sites/default/files/files/Size_Standards_Table.pdf.)
For purposes of the RFA, all hospitals and other providers and
suppliers are considered to be small entities. Individuals and
States are not included in the definition of a small entity. We
believe that the provisions of this proposed rule relating to acute
care hospitals will have a significant impact on small entities as
explained in this Appendix. For example, because all hospitals are
considered to be small entities for purposes of the RFA, the
hospital impacts described in this proposed rule are impacts on
small entities. For example, we refer readers to ``Table I.--Impact
Analysis of Proposed Changes to the IPPS for Operating Costs for FY
2020.'' Because we lack data on individual hospital receipts, we
cannot determine the number of small proprietary LTCHs. Therefore,
we are assuming that all LTCHs are considered small entities for the
purpose of the analysis in section I.J. of this Appendix. MACs are
not
[[Page 19675]]
considered to be small entities because they do not meet the SBA
definition of a small business. Because we acknowledge that many of
the affected entities are small entities, the analysis discussed
throughout the preamble of this proposed rule constitutes our
regulatory flexibility analysis. This proposed rule contains a range
of proposed policies. It provides descriptions of the statutory
provisions that are addressed, identifies the proposed policies, and
presents rationales for our decisions and, where relevant,
alternatives that were considered.
For purposes of the RFA, as stated above, all hospitals and
other providers and suppliers are considered to be small entities.
We estimate the provisions of this proposed rule would result in an
estimated $4.67 billion increase in FY 2020 payments to IPPS
hospitals, primarily driven by the proposed applicable percentage
increase to the IPPS rates in conjunction with other proposed
payment changes including uncompensated care payments, capital
payments, new technology add-on payments, and low-volume hospital
payments, as discussed in section I.B. of this Appendix. As
discussed in section I.J. of this Appendix, the impact analysis of
the proposed payment rates and factors presented in this proposed
rule under the LTCH PPS is projected to result in an increase in
estimated aggregate LTCH PPS payments in FY 2020 relative to FY 2019
of approximately $37 million. We are soliciting public comments on
our estimates and analysis of the impact of our proposals on those
small entities. Any public comments that we received and our
responses will be presented throughout the final rule.
IV. Impact on Small Rural Hospitals
Section 1102(b) of the Social Security Act requires us to
prepare a regulatory impact analysis for any proposed or final rule
that may have a significant impact on the operations of a
substantial number of small rural hospitals. This analysis must
conform to the provisions of section 604 of the RFA. With the
exception of hospitals located in certain New England counties, for
purposes of section 1102(b) of the Act, we define a small rural
hospital as a hospital that is located outside of an urban area and
has fewer than 100 beds. Section 601(g) of the Social Security
Amendments of 1983 (Pub. L. 98-21) designated hospitals in certain
New England counties as belonging to the adjacent urban area. Thus,
for purposes of the IPPS and the LTCH PPS, we continue to classify
these hospitals as urban hospitals. (As shown in Table I. in section
I.G. of this Appendix, rural IPPS hospitals with 0-49 beds and 50-99
beds are expected to experience an increase in payments from FY 2019
to FY 2020 of 4.9 percent and 3.5 percent, respectively. We refer
readers to Table I. in section I.G. of this Appendix for additional
information on the quantitative effects of the proposed policy
changes under the IPPS for operating costs.)
V. Unfunded Mandates Reform Act Analysis
Section 202 of the Unfunded Mandates Reform Act of 1995 (Pub. L.
104-4) also requires that agencies assess anticipated costs and
benefits before issuing any rule whose mandates require spending in
any 1 year of $100 million in 1995 dollars, updated annually for
inflation. In 2020, that threshold level is approximately $154
million. This proposed rule would not mandate any requirements for
State, local, or tribal governments, nor would it affect private
sector costs.
VI. Executive Order 13175
Executive Order 13175 requires that, to the extent practicable
and permitted by law, no agency shall promulgate any regulation that
has tribal implications, that imposes substantial direct compliance
costs on Indian tribal governments, and that is not required by
statute, unless: (1) Funds necessary to pay the direct costs
incurred by the Indian tribal government or the tribe in complying
with the regulation are provided by the Federal Government; or (2)
the agency, prior to the formal promulgation of the regulation, (A)
consulted with tribal officials early in the process of developing
the proposed regulation; (B) in a separately identified portion of
the preamble to the regulation as it is to be issued in the Federal
Register, provides to the Director of the Office of Management and
Budget (OMB) a tribal summary impact statement, which consists of a
description of the extent of the agency's prior consultation with
tribal officials, a summary of the nature of their concerns and the
agency's position supporting the need to issue the regulation, and a
statement of the extent to which the concerns of tribal officials
have been met; and (C) makes available to the Director of OMB any
written communications submitted to the agency by tribal officials.
Section 1880(a) of the Act states that a hospital of the Indian
Health Service, whether operated by such Service or by an Indian
tribe or tribal organization, is eligible for payments under title
XVIII of the Act, so long as it meets all of the conditions and
requirements for such payments which are applicable generally to
hospitals under title XVIII of the Act.
This proposed rule would not mandate any requirement for Indian
tribal governments, and it would not impose substantial direct
compliance costs on Indian tribal governments.
VII. Executive Order 12866
In accordance with the provisions of Executive Order 12866, the
Executive Office of Management and Budget reviewed this proposed
rule.
Appendix B: Recommendation of Update Factors for Operating Cost Rates
of Payment for Inpatient Hospital Services
I. Background
Section 1886(e)(4)(A) of the Act requires that the Secretary,
taking into consideration the recommendations of MedPAC, recommend
update factors for inpatient hospital services for each fiscal year
that take into account the amounts necessary for the efficient and
effective delivery of medically appropriate and necessary care of
high quality. Under section 1886(e)(5) of the Act, we are required
to publish update factors recommended by the Secretary in the
proposed and final IPPS rules. Accordingly, this Appendix provides
the recommendations for the update factors for the IPPS national
standardized amount, the hospital-specific rate for SCHs and MDHs,
and the rate-of-increase limits for certain hospitals excluded from
the IPPS, as well as LTCHs. In prior years, we made a recommendation
in the IPPS proposed rule and final rule for the update factors for
the payment rates for IRFs and IPFs. However, for FY 2020,
consistent with our approach for FY 2019, we are including the
Secretary's recommendation for the update factors for IRFs and IPFs
in separate Federal Register documents at the time that we announce
the annual updates for IRFs and IPFs. We also discuss our response
to MedPAC's recommended update factors for inpatient hospital
services.
II. Inpatient Hospital Update for FY 2020
A. Proposed FY 2020 Inpatient Hospital Update
As discussed in section IV.B. of the preamble to this proposed
rule, for FY 2020, consistent with section 1886(b)(3)(B) of the Act,
as amended by sections 3401(a) and 10319(a) of the Affordable Care
Act, we are setting the applicable percentage increase by applying
the following adjustments in the following sequence. Specifically,
the applicable percentage increase under the IPPS is equal to the
rate-of-increase in the hospital market basket for IPPS hospitals in
all areas, subject to a reduction of one-quarter of the applicable
percentage increase (prior to the application of other statutory
adjustments; also referred to as the market basket update or rate-
of-increase (with no adjustments)) for hospitals that fail to submit
quality information under rules established by the Secretary in
accordance with section 1886(b)(3)(B)(viii) of the Act and a
reduction of three-quarters of the applicable percentage increase
(prior to the application of other statutory adjustments; also
referred to as the market basket update or rate-of-increase (with no
adjustments)) for hospitals not considered to be meaningful
electronic health record (EHR) users in accordance with section
1886(b)(3)(B)(ix) of the Act, and then subject to an adjustment
based on changes in economy-wide productivity (the multifactor
productivity (MFP) adjustment). Section 1886(b)(3)(B)(xi) of the
Act, as added by section 3401(a) of the Affordable Care Act, states
that application of the MFP adjustment may result in the applicable
percentage increase being less than zero. (We note that section
1886(b)(3)(B)(xii) of the Act required an additional reduction each
year only for FYs 2010 through 2019.)
In compliance with section 404 of the MMA, in the FY 2018 IPPS/
LTCH PPS final rule (82 FR 38587), we replaced the FY 2010-based
IPPS operating and capital market baskets with the rebased and
revised 2014-based IPPS operating and capital market baskets,
effective beginning in FY 2018.
In this FY 2020 IPPS/LTCH PPS proposed rule, in accordance with
section 1886(b)(3)(B) of the Act, we are proposing to base the
proposed FY 2020 market basket update used to determine the
applicable percentage
[[Page 19676]]
increase for the IPPS on IGI's fourth quarter 2018 forecast of the
2014-based IPPS market basket rate-of-increase with historical data
through third quarter 2018, which is estimated to be 3.2 percent. In
accordance with section 1886(b)(3)(B) of the Act, as amended by
section 3401(a) of the Affordable Care Act, in section IV.B. of the
preamble of this FY 2020 IPPS/LTCH PPS proposed rule, based on IGI's
fourth quarter 2018 forecast, we are proposing an MFP adjustment of
0.5 percent for FY 2020. We also are proposing that if more recent
data subsequently become available, we would use such data, if
appropriate, to determine the FY 2020 market basket update and MFP
adjustment for the final rule.
Therefore, based on IGI's fourth quarter 2018 forecast of the
2014-based IPPS market basket and the MFP adjustment, depending on
whether a hospital submits quality data under the rules established
in accordance with section 1886(b)(3)(B)(viii) of the Act (hereafter
referred to as a hospital that submits quality data) and is a
meaningful EHR user under section 1886(b)(3)(B)(ix) of the Act
(hereafter referred to as a hospital that is a meaningful EHR user),
we are proposing four possible applicable percentage increases that
could be applied to the standardized amount, as shown in the table
below.
[GRAPHIC] [TIFF OMITTED] TP03MY19.057
B. Proposed Update for SCHs and MDHs for FY 2020
Section 1886(b)(3)(B)(iv) of the Act provides that the FY 2020
applicable percentage increase in the hospital-specific rate for
SCHs and MDHs equals the applicable percentage increase set forth in
section 1886(b)(3)(B)(i) of the Act (that is, the same update factor
as for all other hospitals subject to the IPPS). Under current law,
the MDH program is effective for discharges through September 30,
2022, as discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR
41429 through 41430).
As previously mentioned, the update to the hospital specific
rate for SCHs and MDHs is subject to section 1886(b)(3)(B)(i) of the
Act, as amended by sections 3401(a) and 10319(a) of the Affordable
Care Act. Accordingly, depending on whether a hospital submits
quality data and is a meaningful EHR user, we are proposing the same
four possible applicable percentage increases in the table above for
the hospital-specific rate applicable to SCHs and MDHs.
C. Proposed FY 2020 Puerto Rico Hospital Update
As discussed in the FY 2017 IPPS/LTCH PPS final rule (81 FR
56939), prior to January 1, 2016, Puerto Rico hospitals were paid
based on 75 percent of the national standardized amount and 25
percent of the Puerto Rico-specific standardized amount. Section 601
of Public Law 114-113 amended section 1886(d)(9)(E) of the Act to
specify that the payment calculation with respect to operating costs
of inpatient hospital services of a subsection (d) Puerto Rico
hospital for inpatient hospital discharges on or after January 1,
2016, shall use 100 percent of the national standardized amount.
Because Puerto Rico hospitals are no longer paid with a Puerto Rico-
specific standardized amount under the amendments to section
1886(d)(9)(E) of the Act, there is no longer a need for us to make
an update to the Puerto Rico standardized amount. Hospitals in
[[Page 19677]]
Puerto Rico are now paid 100 percent of the national standardized
amount and, therefore, are subject to the same update to the
national standardized amount discussed under section IV.B.1. of the
preamble of this proposed rule. Accordingly, for FY 2020, we are
proposing to establish an applicable percentage increase of 2.7
percent to the standardized amount for hospitals located in Puerto
Rico.
D. Proposed Update for Hospitals Excluded From the IPPS for FY 2020
Section 1886(b)(3)(B)(ii) of the Act is used for purposes of
determining the percentage increase in the rate-of-increase limits
for children's hospitals, cancer hospitals, and hospitals located
outside the 50 States, the District of Columbia, and Puerto Rico
(that is, short-term acute care hospitals located in the U.S. Virgin
Islands, Guam, the Northern Mariana Islands, and America Samoa).
Section 1886(b)(3)(B)(ii) of the Act sets the percentage increase in
the rate-of-increase limits equal to the market basket percentage
increase. In accordance with Sec. 403.752(a) of the regulations,
RNHCIs are paid under the provisions of Sec. 413.40, which also use
section 1886(b)(3)(B)(ii) of the Act to update the percentage
increase in the rate-of-increase limits.
Currently, children's hospitals, PPS-excluded cancer hospitals,
RNHCIs, and short-term acute care hospitals located in the U.S.
Virgin Islands, Guam, the Northern Mariana Islands, and American
Samoa are among the remaining types of hospitals still paid under
the reasonable cost methodology, subject to the rate-of-increase
limits. In addition, in accordance with Sec. 412.526(c)(3) of the
regulations, extended neoplastic disease care hospitals (described
in Sec. 412.22(i) of the regulations) also are subject to the rate-
of-increase limits. As discussed in section VI. of the preamble of
this proposed rule, in the FY 2018 IPPS/LTCH PPS final rule, we
finalized the use of the percentage increase in the 2014-based IPPS
operating market basket to update the target amounts for children's
hospitals, PPS-excluded cancer hospitals, RNHCIs, and short-term
acute care hospitals located in the U.S. Virgin Islands, Guam, the
Northern Mariana Islands, and American Samoa for FY 2018 and
subsequent fiscal years. In addition, as discussed in section IV.B.
of the preamble of this proposed rule, the update to the target
amount for extended neoplastic disease care hospitals for FY 2020
would be the percentage increase in the 2014-based IPPS operating
market basket. Accordingly, for FY 2020, the rate-of-increase
percentage to be applied to the target amount for these children's
hospitals, cancer hospitals, RNHCIs, extended neoplastic disease
care hospitals, and short-term acute care hospitals located in the
U.S. Virgin Islands, Guam, the Northern Mariana Islands, and
American Samoa would be the FY 2020 percentage increase in the 2014-
based IPPS operating market basket. For this proposed rule, the
current estimate of the IPPS operating market basket percentage
increase for FY 2020 is 3.2 percent.
E. Proposed Update for LTCHs for FY 2020
Section 123 of Public Law 106-113, as amended by section 307(b)
of Public Law 106-554 (and codified at section 1886(m)(1) of the
Act), provides the statutory authority for updating payment rates
under the LTCH PPS.
As discussed in section V.A. of the Addendum to this proposed
rule, we are proposing to update to the LTCH PPS standard Federal
payment rate for FY 2020 by 2.7 percent, consistent with the
amendments to section 1886(m)(3) of the Act which provides that any
annual update be reduced by the productivity adjustment described in
section 1886(b)(3)(B)(xi)(II) of the Act (that is, the MFP
adjustment). Furthermore, in accordance with the LTCHQR Program
under section 1886(m)(5) of the Act, we are proposing to reduce the
annual update to the LTCH PPS standard Federal rate by 2.0
percentage points for failure of a LTCH to submit the required
quality data. Accordingly, we are proposing to establish an update
factor of 1.027 in determining the LTCH PPS standard Federal rate
for FY 2020. For LTCHs that fail to submit quality data for FY 2020,
we are proposing to apply an annual update to the LTCH PPS standard
Federal rate of 0.7 percent (that is, the proposed annual update for
FY 2020 of 2.7 percent less 2.0 percentage points for failure to
submit the required quality data in accordance with section
1886(m)(5)(C) of the Act and our rules) by applying a proposed
update factor of 1.007 in determining the LTCH PPS standard Federal
rate for FY 2020. (We note that, as discussed in section VII.D. of
the preamble of this proposed rule, the proposed update to the LTCH
PPS standard Federal payment rate of 2.7 percent for FY 2020 does
not reflect any proposed budget neutrality factors.)
III. Secretary's Recommendations
MedPAC is recommending an inpatient hospital update in the
amount specified in current law for FY 2020. MedPAC's rationale for
this update recommendation is described in more detail below. As
mentioned above, section 1886(e)(4)(A) of the Act requires that the
Secretary, taking into consideration the recommendations of MedPAC,
recommend update factors for inpatient hospital services for each
fiscal year that take into account the amounts necessary for the
efficient and effective delivery of medically appropriate and
necessary care of high quality. Consistent with current law,
depending on whether a hospital submits quality data and is a
meaningful EHR user, we are recommending the four applicable
percentage increases to the standardized amount listed in the table
under section II. of this Appendix B. We are recommending that the
same applicable percentage increases apply to SCHs and MDHs.
In addition to making a recommendation for IPPS hospitals, in
accordance with section 1886(e)(4)(A) of the Act, we are
recommending update factors for certain other types of hospitals
excluded from the IPPS. Consistent with our policies for these
facilities, we are recommending an update to the target amounts for
children's hospitals, cancer hospitals, RNHCIs, short-term acute
care hospitals located in the U.S. Virgin Islands, Guam, the
Northern Mariana Islands, and American Samoa and extended neoplastic
disease care hospitals of 3.2 percent.
For FY 2020, consistent with policy set forth in section VII. of
the preamble of this proposed rule, for LTCHs that submit quality
data, we are recommending an update of 2.7 percent to the LTCH PPS
standard Federal rate. For LTCHs that fail to submit quality data
for FY 2020, we are recommending an annual update to the LTCH PPS
standard Federal rate of 0.7 percent.
IV. MedPAC Recommendation for Assessing Payment Adequacy and Updating
Payments in Traditional Medicare
In its March 2019 Report to Congress, MedPAC assessed the
adequacy of current payments and costs, and the relationship between
payments and an appropriate cost base. MedPAC recommended an update
to the hospital inpatient rates by 2 percent with the difference
between this and the update amount specified in current law to be
used to increase payments in a new suggested Medicare quality
program, the ``Hospital Value Incentive Program (HVIP).'' MedPAC
stated that together, these recommendations, paired with the
recommendation to eliminate the current hospital quality program
incentives, would increase hospital payments by increasing the base
payment rate and by increasing the average rewards hospitals receive
under MedPAC's proposed Medicare HVIP.
We refer readers to the March 2019 MedPAC report, which is
available for download at www.medpac.gov, for a complete discussion
on these recommendations.
Response: With regard to MedPAC's recommendation of an update to
the hospital inpatient rates equal to 2 percent, with the remainder
of the 2.7 percent to be used to fund its recommended Medicare HVIP,
section 1886(b)(3)(B) of the Act sets the requirements for the FY
2020 applicable percentage increase. Therefore, consistent with the
statute, we are proposing an applicable percentage increase for FY
2020 of 2.7 percent, provided the hospital submits quality data and
is a meaningful EHR user consistent with these statutory
requirements.
Furthermore, we appreciate MedPAC's recommendation concerning a
new HVIP. We agree that continual improvement motivated by quality
programs is an important incentive of the IPPS. However, under
current law, the inpatient hospital quality programs include the
Hospital Readmissions Reduction Program, the Hospital Value-Based
Purchasing Program, and the Hospital-Acquired Condition Reduction
Program.
We note that, because the operating and capital prospective
payment systems remain separate, we are continuing to use separate
updates for operating and capital payments. The proposed update to
the capital rate is discussed in section III. of the Addendum to
this proposed rule.
[FR Doc. 2019-08330 Filed 4-23-19; 4:15 pm]
BILLING CODE 4120-01-P
