[Federal Register Volume 84, Number 159 (Friday, August 16, 2019)]
[Rules and Regulations]
[Pages 42044-42701]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2019-16762]



[[Page 42043]]

Vol. 84

Friday,

No. 159

August 16, 2019

Part II

Book 2 of 2

Pages 42043-42798





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 Policy Changes and Fiscal Year 2020 Rates; Quality 
Reporting Requirements for Specific Providers; Medicare and Medicaid 
Promoting Interoperability Programs Requirements for Eligible Hospitals 
and Critical Access Hospitals; Final Rule

  Federal Register / Vol. 84 , No. 159 / Friday, August 16, 2019 / 
Rules and Regulations  

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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Medicare & Medicaid Services

42 CFR Parts 412, 413, and 495

[CMS-1716-F]
RIN 0938-AT73


Medicare Program; Hospital Inpatient Prospective Payment Systems 
for Acute Care Hospitals and the Long-Term Care Hospital Prospective 
Payment System and Policy Changes and Fiscal Year 2020 Rates; Quality 
Reporting Requirements for Specific Providers; Medicare and Medicaid 
Promoting Interoperability Programs Requirements for Eligible Hospitals 
and Critical Access Hospitals

AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.

ACTION: Final rule.

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SUMMARY: We are revising 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 making changes relating to Medicare 
graduate medical education (GME) for teaching hospitals and payments to 
critical access hospital (CAHs). In addition, we are providing the 
market basket update that will 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 updating 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 FY 
2020 IPPS/LTCH PPS final rule, we are addressing wage index disparities 
impacting low wage index hospitals; providing for an alternative IPPS 
new technology add-on payment pathway for certain transformative new 
devices and qualified infectious disease products; and revising the 
calculation of the IPPS new technology add-on payment. In addition, we 
are revising and clarifying our policies related to the substantial 
clinical improvement criterion used for evaluating applications for the 
new technology add-on payment under the IPPS.
    We are establishing new requirements or revising existing 
requirements for quality reporting by specific Medicare providers 
(acute care hospitals, PPS-exempt cancer hospitals, and LTCHs). We also 
are establishing new requirements and revising existing requirements 
for eligible hospitals and critical access hospitals (CAHs) 
participating in the Medicare and Medicaid Promoting Interoperability 
Programs. We are updating policies for the Hospital Value-Based 
Purchasing (VBP) Program, the Hospital Readmissions Reduction Program, 
and the Hospital-Acquired Condition (HAC) Reduction Program.

DATES: This final rule is effective October 1, 2019.

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--
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.
    Benjamin Moll, (410) 786-4390, Provider Reimbursement Review Board 
Appeals Issues.

SUPPLEMENTARY INFORMATION: 

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 final rule are 
available through the internet on the CMS website at: https://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 Final Rule Home Page'' or ``Acute 
Inpatient--Files for Download.'' The LTCH PPS tables for this FY 2020 
final 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-F. For further details on the contents of the tables 
referenced in this final rule, we refer readers to section VI. of the 
Addendum to this FY 2020 IPPS/LTCH PPS final rule.
    Readers who experience any problems accessing any of the tables 
that are posted on the CMS websites, as previously identified, 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 Final Rule
    D. Issuance of Notice of Proposed Rulemaking

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    E. Advancing Health Information Exchange
II. 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. FY 2020 MS-DRG Documentation and Coding Adjustment
    E. Refinement of the MS-DRG Relative Weight Calculation
    F. Changes to Specific MS-DRG Classifications
    G. Recalibration of the FY 2020 MS-DRG Relative Weights
    H. Add-On Payments for New Services and Technologies for FY 2020
III. Changes to the Hospital Wage Index for Acute Care Hospitals
    A. Background
    B. Worksheet S-3 Wage Data for the FY 2020 Wage Index
    C. Verification of Worksheet S-3 Wage Data
    D. Method for Computing the FY 2020 Unadjusted Wage Index
    E. Occupational Mix Adjustment to the FY 2020 Wage Index
    F. Analysis and Implementation of the Occupational Mix 
Adjustment and the Final FY 2020 Occupational Mix Adjusted Wage 
Index
    G. Application of the Rural Floor, Expired Imputed Floor Policy, 
and Application of the State Frontier Floor
    H. FY 2020 Wage Index Tables
    I. Revisions to the Wage Index Based on Hospital Redesignations 
and Reclassifications
    J. 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. Labor-Related Share for the FY 2020 Wage Index
    N. Final Policies To Address Wage Index Disparities Between High 
and Low Wage Index Hospitals
IV. Other Decisions and Changes to the IPPS for Operating Costs
    A. Changes to MS-DRGs Subject to Postacute Care Transfer and MS-
DRG Special Payment Policies
    B. Changes in the Inpatient Hospital Updates for FY 2020 (Sec.  
412.64(d))
    C. Rural Referral Centers (RRCs) Annual Updates to Case-Mix 
Index and Discharge Criteria (Sec.  412.96)
    D. Payment Adjustment for Low-Volume Hospitals (Sec.  412.101)
    E. Indirect Medical Education (IME) Payment Adjustment (Sec.  
412.105)
    F. Payment Adjustment for Medicare Disproportionate Share 
Hospitals (DSHs) for FY 2020 (Sec.  412.106)
    G. Hospital Readmissions Reduction Program: Updates and Changes 
(Sec. Sec.  412.150 Through 412.154)
    H. Hospital Value-Based Purchasing (VBP) Program: 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. Changes to the IPPS for Capital-Related Costs
    A. Overview
    B. Additional Provisions
    C. Annual Update for FY 2020
VI. Changes for Hospitals Excluded From the IPPS
    A. Rate-of-Increase in Payments to Excluded Hospitals for FY 
2020
    B. Methodologies and Requirements for TEFRA Adjustments to Rate-
of-Increase Ceiling
    C. Critical Access Hospitals (CAHs)
VII. Changes to the Long-Term Care Hospital Prospective Payment 
System (LTCH PPS) for FY 2020
    A. Background of the LTCH PPS
    B. Medicare Severity Long-Term Care Diagnosis-Related Group (MS-
LTC-DRG) Classifications and Relative Weights for FY 2020
    C. Payment Adjustment for LTCH Discharges That Do Not Meet the 
Applicable Discharge Payment Percentage
    D. Changes to the LTCH PPS Payment Rates and Other Changes to 
the LTCH PPS for FY 2020
VIII. 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. 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
XI. Provider Reimbursement Review Board (PRRB) Appeals

Regulation Text

Addendum--Schedule of Standardized Amounts, Update Factors, and Rate-
of-Increase Percentages Effective With Cost Reporting Periods Beginning 
on or After October 1, 2019 and Payment Rates for LTCHs Effective With 
Discharges Occurring on or After October 1, 2019

I. Summary and Background
II. Changes to the Prospective Payment Rates for Hospital Inpatient 
Operating Costs for Acute Care Hospitals for FY 2020
    A. Calculation of the Adjusted Standardized Amount
    B. Adjustments for Area Wage Levels and Cost-of-Living
    C. Calculation of the Prospective Payment Rates
III. Changes to Payment Rates for Acute Care Hospital Inpatient 
Capital-Related Costs for FY 2020
    A. Determination of Federal Hospital Inpatient Capital-Related 
Prospective Payment Rate Update
    B. Calculation of the Inpatient Capital-Related Prospective 
Payments for FY 2020
    C. Capital Input Price Index
IV. Changes to Payment Rates for Excluded Hospitals: Rate-of-
Increase Percentages for FY 2020
V. Updates to the Payment Rates for the LTCH PPS for FY 2020
    A. LTCH PPS Standard Federal Payment Rate for FY 2020
    B. Adjustment for Area Wage Levels Under the LTCH PPS for FY 
2020
    C. LTCH PPS Cost-of-Living Adjustment (COLA) for LTCHs Located 
in Alaska and Hawaii
    D. Adjustment for LTCH PPS High-Cost Outlier (HCO) Cases
    E. Update to the IPPS Comparable/Equivalent Amounts To Reflect 
the Statutory Changes to the IPPS DSH Payment Adjustment Methodology
    F. Computing the Adjusted LTCH PPS Federal Prospective Payments 
for FY 2020
VI. Tables Referenced in This FY 2020 IPPS/LTCH PPS Final 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 Policy Changes Under the IPPS for 
Operating Costs
    H. Effects of Other Policy Changes
    I. Effects of Changes in the Capital IPPS
    J. Effects of Payment Rate Changes and Policy Changes Under the 
LTCH PPS
    K. Effects of Requirements for Hospital Inpatient Quality 
Reporting (IQR) Program
    L. Effects of Requirements for the PPS-Exempt Cancer Hospital 
Quality Reporting (PCHQR) Program
    M. Effects of Requirements for the Long-Term Care Hospital 
Quality Reporting Program (LTCH QRP)
    N. Effects of 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

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Appendix B: Recommendation of Update Factors for Operating Cost Rates 
of Payment for Inpatient Hospital Services

I. Background
II. Inpatient Hospital Update for FY 2020
    A. FY 2020 Inpatient Hospital Update
    B. Update for SCHs and MDHs for FY 2020
    C. FY 2020 Puerto Rico Hospital Update
    D. Update for Hospitals Excluded From the IPPS
    E. 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 FY 2020 IPPS/LTCH PPS final rule makes 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 makes 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 final 
rule also makes policy changes to programs associated with Medicare 
IPPS hospitals, IPPS-excluded hospitals, and LTCHs. In this final rule, 
we are addressing wage index disparities impacting low wage index 
hospitals; providing for an alternative IPPS new technology add-on 
payment pathway for certain transformative new devices and qualified 
infectious disease products; revising the calculation of the IPPS new 
technology add-on payment; and making revisions and clarifications 
related to the substantial clinical improvement criterion under the 
IPPS.
    We are establishing new requirements and revising 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 establishing new requirements 
and revising existing requirements for eligible hospitals and CAHs 
participating in the Medicare and Medicaid Promoting Interoperability 
Programs. We are updating 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 making 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.
     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 provides for the 
establishment of 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.

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     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 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
    In this final rule, we provide a summary of the major provisions in 
this FY 2020 IPPS/LTCH PPS final rule. In general, these major 
provisions are 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 that were included in the FY 
2020 IPPS/LTCH PPS proposed rule is presented in section I.D. of the 
preamble of this final rule.
a. 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 making an adjustment of +0.5 
percent to the standardized amount.
b. Revisions and Clarifications to the New Technology Add-On Payment 
Policy Substantial Clinical Improvement Criterion Under the IPPS
    In the proposed rule, in addition to a 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 solicited 
public comments on specific changes or clarifications to the IPPS and 
Outpatient Prospective Payment System (OPPS) substantial clinical 
improvement criterion used to evaluate applications for new technology 
add-on payments under the IPPS and the transitional pass-through 
payment for additional costs of innovative devices under the OPPS that 
CMS might consider making in this 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.
    In this final rule, after consideration of public comments, we are 
revising and clarifying certain aspects of our evaluation of the 
substantial clinical improvement criterion under the IPPS in 42 CFR 
412.87.
c. Alternative Inpatient New Technology Add-On Payment Pathway for 
Transformative New Devices and Antimicrobial Resistant Products
    As discussed in section III.H.8. of the preamble of this final 
rule, after consideration of public comments, given 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 are adopting an alternative pathway for 
the inpatient new technology add-on payment for certain transformative 
medical devices. In situations where a new medical device 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) and is the subject of the FDA's Breakthrough 
Devices Program, we are finalizing our proposal to create an 
alternative inpatient new technology add-on payment pathway to 
facilitate access to this technology for Medicare beneficiaries. In 
addition, after consideration of public comments and concerns related 
to antimicrobial resistance and its serious impact on Medicare 
beneficiaries and public health overall, we are finalizing an 
alternative inpatient new technology add-for Qualified Infectious 
Disease Products (QIDPs).
    Specifically, we are establishing that, for applications received 
for IPPS new technology add-on payments for FY 2021 and subsequent 
fiscal years, if a medical device is the subject of the FDA's 
Breakthrough Devices Program or if a medical product technology 
receives the FDA's QIDP designation and received FDA marketing 
authorization, such a device or product will be considered new and not 
substantially similar to an existing technology for purposes of new 
technology add-on payment under the IPPS. We are also establishing that 
the medical device or product will 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. 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.
    As discussed in section III.H.9. of the preamble of this final 
rule, after consideration of the concerns raised by

[[Page 42048]]

commenters and other stakeholders, we agree that capping the add-on 
payment amount at 50 percent could, in some cases, not adequately 
reflect the costs of new technology or sufficiently support healthcare 
innovations.
    After consideration of public comments, we are finalizing the 
proposed modification to the current payment amount to increase the 
maximum add-on payment amount to 65 percent of the costs of the new 
technology or medical service (except with respect to a medical product 
designated by the FDA as a QIDP). Therefore, we are establishing that, 
beginning with discharges occurring on or after October 1, 2019, for a 
new technology other than a medical product designated as a QIDP by the 
FDA, 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 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. In addition, 
after consideration of public comments and concerns related to 
antimicrobial resistance and its serious impact on Medicare 
beneficiaries and public health overall, we are establishing that, 
beginning with discharges occurring on or after October 1, 2019, for a 
new technology that is a medical product designated as a QIDP by the 
FDA, 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 will make an add-on 
payment equal to the lesser of: (1) 75 percent of the costs of the new 
medical service or technology; or (2) 75 percent of the amount by which 
the costs of the case exceed the standard DRG payment.
e. Finalized Policies To Address Wage Index Disparities
    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, in this final rule, we are 
reducing the disparity between high and low wage index hospitals by 
increasing the wage index values for certain hospitals with low wage 
index values and doing so in a budget neutral manner through an 
adjustment applied to the standardized amounts for all hospitals, as 
well as changing the calculation of the rural floor. We also are 
providing for a transition for hospitals experiencing significant 
decreases in their wage index values as compared to their final FY 2019 
wage index. We are making these changes in a budget neutral manner.
    In this final rule, we are increasing 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, this policy will 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. 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 applying a uniform budget 
neutrality factor to the standardized amount.
    In addition, we are removing urban to rural reclassifications from 
the calculation of the rural floor, such that, beginning in FY 2020, 
the rural floor is 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 removing 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 placing 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 applying a budget neutrality adjustment to the 
standardized amount so that our transition for hospitals that could be 
negatively impacted is implemented in a budget neutral manner.
f. 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 final rule, we have updated our 
estimates of the three factors used to determine uncompensated care 
payments for FY 2020. We 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 using 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 continuing to use only data regarding low-
income insured days (Medicaid days for FY 2013 and FY 2017 SSI days) to 
determine the amount of uncompensated care payments for Puerto Rico 
hospitals, and Indian Health Service and Tribal hospitals. We did not 
adopt specific Factor 3 polices for all-inclusive rate providers for FY 
2020. In this final rule, we also are continuing 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;

[[Page 42049]]

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. Changes to the LTCH PPS
    In this FY 2020 IPPS/LTCH PPS final rule, we set forth changes to 
the LTCH PPS Federal payment rates, factors, and other payment rate 
policies under the LTCH PPS for FY 2020. We also are establishing the 
payment adjustment for LTCH discharges when the LTCH does not meet the 
applicable discharge payment percentage and a reinstatement process, as 
required by section 1886(m)(6)(C) of the Act. An LTCH will 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. We are adopting a probationary cure period as part of the 
reinstatement process.
h. Reduction of Hospital Payments for Excess Readmissions
    We are making 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 FY 2020 IPPS/LTCH PPS final rule, we are establishing 
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 
policies we are finalizing in this final rule 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 FY 2020 IPPS/LTCH PPS final rule, we are establishing that the 
Hospital VBP 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, which is 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: (1) Adopting a 
measure removal policy that aligns with the removal factor policies 
previously adopted in other quality reporting and quality payment 
programs; (2) clarifying administrative policies for validation of the 
CDC NHSN HAI measures; (3) adopting the data collection periods for the 
FY 2022 program year; and (4) updating 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 FY 2020 IPPS/LTCH PPS final rule, we are making several 
changes. We are: (1) Adopting the Safe Use of Opioids--Concurrent 
Prescribing eCQM beginning with the CY 2021 reporting period/FY 2023 
payment determination with a clarification and update; (2) adopting the 
Hybrid Hospital-Wide All-Cause Readmission (Hybrid HWR) measure (NQF 
#2879) in a stepwise fashion, beginning with two voluntary reporting 
periods which will 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 will run from July 1, 2023 
through June 30, 2024, impacting the FY 2026 payment determination and 
for subsequent years; and (3) removing the Claims-Based Hospital-Wide 
All-Cause Unplanned Readmission Measure (NQF #1789) (HWR claims-only 
measure), beginning with the FY 2026 payment determination. We are not 
finalizing our proposal to adopt the Hospital Harm--Opioid-Related 
Adverse Events eCQM. We also are establishing reporting and submission 
requirements for eCQMs, including policies 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 the eCQM reporting and 
submission requirements for the CY 2022 reporting period/FY 2024 
payment determination, such that hospitals will be required to report 
one, self-selected calendar quarter of data for three self-selected 
eCQMs and the 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 eCQM reporting and submission policies are 
in alignment with policies under the Promoting Interoperability 
Program. We also are establishing reporting and submission requirements

[[Page 42050]]

for the Hybrid HWR measure. In addition, we are summarizing public 
comments we received on three measures we are considering for potential 
future inclusion in the Hospital IQR Program.
l. 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 finalizing several changes to the Promoting 
Interoperability Program. Specifically, we are: (1) Eliminating 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 the October 1, 
2019 deadline; (2) establishing 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) requiring 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) revising the Query of PDMP measure to make it an 
optional measure worth 5 bonus points in CY 2020, removing the 
exclusions associated with this measure in CY 2020, requiring a yes/no 
response instead of a numerator and denominator for CY 2019 and CY 
2020, and clearly stating our intended policy that the measure is worth 
a full 5 bonus points in CY 2019 and CY 2020; (5) changing the maximum 
points available for the e-Prescribing measure from 5 points to 10 
points beginning in CY 2020; (6) removing the Verify Opioid Treatment 
Agreement measure beginning in CY 2020 and clearly stating our intended 
policy that this measure is worth a full 5 bonus points in CY 2019; and 
(7) revising the Support Electronic Referral Loops by Receiving and 
Incorporating Health Information measure to more clearly capture the 
previously established policy regarding CEHRT use. We also are amending 
our regulations to incorporate several of these finalized policies.
    For CQM reporting under the Medicare and Medicaid Promoting 
Interoperability Programs, we are generally aligning our requirements 
with requirements under the Hospital IQR Program. Specifically, we are: 
(1) Adopting one opioid-related CQM (Safe Use of Opioids--Concurrent 
Prescribing CQM beginning with the reporting period in CY 2021 (we are 
not finalizing our proposal to add the Hospital Harm--Opioid-Related 
Adverse Events CQM); (2) extending current CQM reporting and submission 
requirements for the reporting periods in CY 2020 and CY 2021; and (3) 
establishing CQM reporting and submission requirements for the 
reporting period in CY 2022, which will require all eligible hospitals 
and CAHs to report on the Safe Use of Opioids--Concurrent Prescribing 
eCQM beginning with the reporting period in CY 2022.
    We sought 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 adopted under the Hospital IQR Program, 
and we sought information on a variety of issues regarding the future 
direction of the Medicare and Medicaid Promoting Interoperability 
Programs. We may use the input we received to inform further 
rulemaking.
3. Summary of Costs and Benefits
     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 making an adjustment 
of +0.5 percentage point to the standardized amount consistent with the 
MACRA.
     Alternative Inpatient New Technology Add-On Payment 
Pathway for Transformative New Devices: In this FY 2020 IPPS/LTCH PPS 
final rule, we are establishing an alternative inpatient new technology 
add-on payment pathway for a new medical device that is subject to the 
FDA Breakthrough Devices Program and has received FDA authorization 
(that is, received PMA approval, 510(k) clearance, or the granting of 
De Novo classification request). We are also establishing that, if a 
medical product is designated by the FDA as a Qualified Infectious 
Disease Product (QIDP) and received FDA market authorization. Under 
these alternative inpatient new technology add-on payment pathways, 
such a medical device or product will be considered new and not 
substantially similar to an existing technology for purposes of new 
technology add-on payment under the IPPS, and such a medical product or 
device will 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 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. If all of the 
future new medical devices that were part of the Breakthrough Devices 
Program and QIDPs that would have applied for new technology add-on 
payments would have been approved under the existing criteria, this 
policy has no impact. To the extent that there are future medical 
devices that were part of the Breakthrough Devices Program or QIDPs 
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 policy is a cost, 
but that cost is not estimable. Therefore, it is not possible to 
quantify the impact of this policy.
     Revisions 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.
    As discussed in section II.H.9. of the preamble of this final rule, 
we have modified the current payment mechanism to increase the amount 
of the maximum add-on payment amount to 65 percent (and 75 percent for 
QIDPs). Specifically, for technologies other than QIDPs, 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

[[Page 42051]]

will make an add-on payment equal to the lesser of: (1) 65 percent (or 
75 percent for QIDPs) of the costs of the new medical service or 
technology; or (2) 65 percent (75 percent for QIDPs) of the amount by 
which the costs of the case exceed the standard DRG payment.
    We estimate that for the nine technologies for which we are 
continuing to make new technology add on payments in FY 2020 and for 
the nine FY 2020 new technology add-on payment applications that we are 
approving for new technology add-on payments for FY 2020, these changes 
to the calculation of the new technology add-on payment will increase 
IPPS spending by approximately $94 million in FY 2020.
     Technologies Approved for FY 2020 New Technology 
Add-On Payments: In section II.H.5. of the preamble to this final rule, 
we discuss 13 technologies for which we received applications for add-
on payments for new medical services and technologies for FY 2020. We 
also discuss the status of the new technologies that were approved to 
receive new technology add-on payments in FY 2019 in section II.H.4. of 
the preamble to this final rule. As explained in the preamble to this 
final 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. Based on those technologies approved for new technology add-on 
payments for FY 2020, new technology add-on payment are projected to 
increase approximately $162 million as compared to FY 2019 (which also 
reflects the estimated changes to the calculation of the inpatient new 
technology add-on payment described above).
     Changes To Address Wage Index Disparities. As discussed in 
section III.N. of the preamble of this final 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 reducing the disparity between high and low wage 
index hospitals by increasing the wage index values for certain 
hospitals with low wage index values (that is, hospitals with wage 
index values below the 25th percentile wage index value across all 
hospitals), as well as changing the calculation of the rural floor. In 
order to offset the estimated increase in IPPS payments to hospitals 
with wage index values below the 25th percentile wage index value, we 
have applied a uniform budget neutrality adjustment to the standardized 
amount. We also are establishing a transition for FY 2020 for hospitals 
experiencing significant decreases in their wage index values, and we 
are implementing this in a budget neutral manner by applying a budget 
neutrality adjustment to the standardized amount.
     Medicare DSH Payment Adjustment and Additional Payment for 
Uncompensated Care. For FY 2020, we are updating our estimates of the 
three factors used to determine uncompensated care payments. We are 
continuing to use uninsured estimates produced by OACT, as part of the 
development of the NHEA in the calculation of Factor 2. We also are 
using a single year of data on uncompensated care costs from Worksheet 
S-10 for FY 2015 to determine 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 continuing to use only data regarding low-income insured days 
(Medicaid days for FY 2013 and FY 2017 SSI days).
    We project that the amount available to distribute as payments for 
uncompensated care for FY 2020 will increase by approximately $78 
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.
     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 changes to the payment rates and 
factors that we presented in the preamble of and Addendum to this FY 
2020 IPPS/LTCH PPS final rule, which reflect the end of the transition 
of the statutory application of the site neutral payment rate and the 
update to the LTCH PPS standard Federal payment rate for FY 2020, will 
result in an estimated increase in payments in FY 2020 of approximately 
$43 million.
     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 FY 2020 IPPS/LTCH PPS 
final rule, we estimate that 2,583 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 will save approximately 
$563 million in FY 2020.
     Value-Based Incentive Payments Under the Hospital VBP 
Program. We estimate that there will be no net financial impact to 
participating hospitals under 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.
     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 are implementing our equal measure weights 
scoring methodology. Any significant impact due to the HAC Reduction 
Program changes for FY 2020, including which hospitals will receive the 
adjustment, will depend on the actual experience of hospitals in the 
Program. We also are updating the hourly wage rate associated with 
burden for CDC NHSN HAI validation under the HAC Reduction Program.
     Changes to the Hospital Inpatient Quality Reporting (IQR) 
Program. Across 3,300 IPPS hospitals, we estimate that our changes for 
the Hospital IQR Program in this FY 2020 IPPS/LTCH PPS final rule would 
result in changes to the information collection burden compared to 
previously adopted requirements. The only policy that will affect the 
information collection burden for the Hospital IQR Program is the 
policy 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 will 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 will 
run from July 1, 2023 through

[[Page 42052]]

June 30, 2024, impacting the FY 2026 payment determination and for 
subsequent years. We estimate that the impact of this 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.
     Changes to the Medicare and Medicaid Promoting 
Interoperability Programs. We believe that, overall, the revised 
policies in this FY 2020 IPPS/LTCH PPS final rule will reduce burden, 
as described in detail in section X.B.9. of the preamble and Appendix 
A, section I.N. of this final 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) 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

[[Page 42053]]

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 various 
types of hospitals are located in 42 CFR part 413.

C. Summary of Provisions of Recent Legislation That Are Implemented in 
This Final 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 
FY 2020 IPPS/LTCH PPS final rule, we are continuing 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 final rule, we are continuing 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 continuing to 
implement in this final 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 FY 2020 IPPS/LTCH 
PPS final rule, we are continuing to implement changes to the payment 
adjustment factor to assess penalties, based on a hospital's 
performance, relative to other hospitals

[[Page 42054]]

treating a similar proportion of dual-eligible patients.

D. Issuance of Notice of Proposed Rulemaking

    In the FY 2020 IPPS/LTCH PPS proposed rule appearing in the Federal 
Register on May 3, 2019 (84 FR 19158), 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.
    In this final rule is a general summary of the changes that we 
proposed to make.
1. Proposed Changes to MS-DRG Classifications and Recalibrations of 
Relative Weights
    In section II. of the preamble of the proposed rule, we included--
     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 
were 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 the proposed rule we proposed to 
make revisions to the wage index for acute care hospitals and the 
annual update of the wage data. Specific issues addressed included, but 
were 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 the proposed rule, we discussed 
proposed changes or clarifications of a number of the provisions of the 
regulations in 42 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 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 the proposed rule, we discussed 
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 the proposed rule, we discussed--
     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 the is 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 the proposed rule, we 
addressed--
     Proposed requirements for the Hospital Inpatient Quality 
Reporting (IQR) Program.
     Proposed changes to the requirements for the quality 
reporting

[[Page 42055]]

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 the proposed rule, we discussed 
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 the 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 
proposed 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 
the proposed rule, we addressed 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 the 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 proposed 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 the 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 the proposed rule, as required by sections 
1886(e)(4) and (e)(5) of the Act, we provided 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 recommendations in Appendix B of this FY 2020 IPPS/
LTCH PPS final 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. 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 extended their comment period by 30 days and closed on June 3, 
2019. The proposed rules can be found at: www.regulations.gov.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19158), we 
invited providers to learn more about these important developments and 
how they are likely to affect hospitals paid under the IPPS and the 
LTCH PPS.

[[Page 42056]]

II. 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. 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 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

[[Page 42057]]

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. Adjustment for FY 2020
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19170 through 
19171) consistent with the requirements of section 414 of the MACRA, we 
proposed to implement a 0.5 percentage point positive adjustment to the 
standardized amount for FY 2020. We indicated that this would 
constitute a permanent adjustment to payment rates. We stated in the 
proposed rule that we plan to propose future adjustments required under 
section 414 of the MACRA for FYs 2021 through 2023 in future 
rulemaking.
    Comment: Several commenters stated that in order to comply with 
ATRA requirements, CMS anticipated that a cumulative -3.2 percentage 
point adjustment to the standardized amount would achieve the mandated 
$11 billion recoupment. Commenters stated that CMS misinterpreted the 
relevant statutory authority, which they asserted explicitly assumes 
that recoupment under section 631 of the ATRA would result in an 
estimated -3.2 percentage point cumulative adjustment by FY 2017. 
Commenters asserted that the additional -0.7 percentage point 
adjustment made in FY 2017 has been improperly continued in FY 2018 and 
FY 2019, and failure to restore the additional 0.7 percentage point 
adjustment will make this reduction in hospital payments a permanent 
part of the baseline calculation of the IPPS rates, which, they 
contend, was not Congress's legislative intent in implementing the 
series of adjustments required under section 414 of the MACRA. 
Commenters urged CMS to use its exceptions and adjustments authority 
under section 1886(d)(5)(I) to restore an additional 0.7 percentage 
point payment adjustment in FY2020 to restore payment equity to 
hospitals and comply with what they asserted was Congressional intent. 
Other commenters suggested CMS implement an approximate positive 
adjustment of 1.0 percentage point by FY 2024 to fully and permanently 
restore the entire -3.9 percentage point recoupment adjustment to IPPS 
rates. A commenter requested that CMS provide its rationale for failing 
to do so. Finally, some of the commenters, while acknowledging that CMS 
may be bound by law, expressed opposition to the permanent reductions 
and requested that CMS refrain from making any additional coding 
adjustments in the future.
    Response: As we discussed in the FY 2020 IPPS/LTCH PPS proposed 
rule (84 FR 19170 through 19171), and in response to similar comments 
in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41157), we believe 
section 414 of the MACRA and section 15005 of the 21st Century Cures 
Act set forth the levels of positive adjustments for FYs 2018 through 
2023. We are not convinced that the adjustments prescribed by MACRA 
were predicated on a specific adjustment level estimated or implemented 
by CMS in previous rulemaking. While we had anticipated making a 
positive adjustment in FY 2018 to offset the reductions required to 
recoup the $11 billion under section 631 of the ATRA, section 414 of 
the MACRA required that we implement a 0.5 percentage point positive 
adjustment for each of FYs 2018 through 2023, and not the single 
positive adjustment we intended to make in FY 2018. As discussed in the 
FY 2017 IPPS/LTCH PPS final rule, by phasing in a total positive 
adjustment of only 3.0 percentage points, section 414 of the MACRA 
would not fully restore even the 3.2 percentage point adjustment 
originally estimated by CMS in the FY 2014 IPPS/LTCH PPS final rule (78 
FR 50515). Moreover, as discussed in the FY 2018 IPPS/LTCH PPS final 
rule, Public Law 114-255, which further reduced the positive adjustment 
required for FY 2018 from 0.5 percentage point to 0.4588 percentage 
point, was enacted on December 13, 2016, after CMS had proposed and 
finalized the final negative -1.5 percentage point adjustment required 
under section 631 of the ATRA. We see no evidence that Congress enacted 
these adjustments with the intent that CMS would make an additional 
+0.7 percentage point adjustment in FY 2018 to compensate for the 
higher than expected final ATRA adjustment made in FY 2017, nor are we 
persuaded that it would be appropriate to use the Secretary's 
exceptions and adjustments authority under section 1886(d)(5)(I) of the 
Act to adjust payments in FY 2020 to restore any additional amount of 
the original 3.9 percentage point reduction, given Congress' 
prescriptive adjustment levels under section 414 of the MACRA and 
section 15005 of the 21st Century Cures Act.
    After consideration of the public comments we received, we are 
finalizing our proposal to implement a 0.5 percentage point adjustment 
to the standardized amount for FY 2020.

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 calculated the final 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 adjusted 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 19 CCRs and the MS-DRG relative 
weights for FY 2020 is included in section II.G. of the preamble to 
this FY 2020 IPPS/LTCH PPS final rule. As we did with the FY 2019 IPPS/
LTCH PPS final rule, for this FY 2020 final rule, we are providing the 
version of the HCRIS from which we calculated these 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 Final Rule Home Page'' or 
``Acute Inpatient Files for Download.''

[[Page 42058]]

    Comment: A commenter recommended that CMS work with stakeholders to 
update cost reporting instructions and improve the accuracy and 
validity of the national average CCRs. The commenter expressed concern 
that the differences between hospitals' use of nonstandard cost center 
codes and CMS' procedures for mapping and rolling up nonstandard codes 
to the standard cost centers will continue to result in invalid CCRs 
and inaccurate payments. The commenter stressed the need for 
flexibility in cost reporting, to accommodate any new or unique 
services that certain hospitals may provide, which may not be easily 
captured through the cost reporting software. Finally, the commenter 
again recommended, as it had done in response to prior IPPS rules, that 
CMS pay particular attention to data used for CT scan and MRI cost 
centers; the commenter believed that the hospital payment rates 
established by CMS from the CT scan and MRI CCRs simply do not 
correlate with resources used for these capital-intensive services.
    Response: We have addressed similar public comments in prior 
rulemaking and refer readers to the FY 2017 IPPS/LTCH PPS final rule 
(81 FR 56787) for our response to these issues. We note that we will 
continue to explore ways in which we can improve the accuracy of the 
cost report data and calculated CCRs used in the cost estimation 
process.

F. Changes to Specific MS-DRG Classifications

1. Discussion of Changes to Coding System and Basis for 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 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 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 final rule. As discussed in the proposed rule and 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 proposed to the MS-DRGs for FY 
2020 in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19171 through 
19257). We invited 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 the proposed rule. In some cases, 
we proposed changes to the MS-DRG classifications based on our analysis 
of claims data and consultation with our clinical advisors. In other 
cases, we proposed to maintain the existing MS-DRG classifications 
based on our analysis of claims data and consultation with our clinical 
advisors. For the 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 referred to our analysis of claims data from the 
``September 2018 update of the FY 2018 MedPAR file.''
    In this FY 2020 IPPS/LTCH PPS final rule, we summarize the public 
comments we received on our proposals, present our responses, and state 
our final policies. For this FY 2020 final rule, we generally did not 
perform any further MS-DRG analysis of claims data. Therefore, our MS-
DRG analysis is 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, except as otherwise noted.
    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

[[Page 42059]]

(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.
    We are making the FY 2020 ICD-10 MS-DRG GROUPER and Medicare Code 
Editor (MCE) Software Version 37, the ICD-10 MS-DRG Definitions Manual 
files Version 37 and the Definitions of Medicare Code Edits Manual 
Version 37 available to the public on our CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.html.
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.
    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.

[[Page 42060]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.001

    As noted in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19173), 
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

[[Page 42061]]

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.
    We stated in the proposed rule that 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 noted 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 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. For FY 2020, as discussed in 
the FY 2020 IPPS/LTCH PPS proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.002

    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 9 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 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.
    In the proposed rule, we stated that 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. We also stated that 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. Further, we noted that 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

[[Page 42062]]

secondary diagnosis MCC and secondary diagnosis CC conditions that were 
reported within the claims data with procedure code 5A15223.
[GRAPHIC] [TIFF OMITTED] TR16AU19.003

BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR16AU19.004


[[Page 42063]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.005

BILLING CODE 4120-01-C
    We stated in the proposed rule that 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), we stated that 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, we stated in the proposed rule that 
our clinical advisors agreed 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, we stated that 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 in the proposed 
rule and 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 (84 FR 
19175). 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. We also stated in the proposed rule 
that, 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

[[Page 42064]]

noted 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 
noted in the proposed rule that a request and proposal to create ICD-
10-PCS codes to differentiate between peripheral vessel percutaneous 
and peripheral vessel open cutdown 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 noted 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, in the FY 2020 
IPPS/LTCH PPS proposed rule, we stated that our clinical advisors 
supported 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 proposed 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. We stated 
in the proposed rule that, 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 also noted in the 
proposed rule that this proposal included maintaining the designation 
of these peripheral ECMO procedures as non-O.R. Therefore, we stated in 
the proposed rule that, if finalized, the procedures would be defined 
as non-O.R. affecting the MS-DRG assignment for Pre-MDC MS-DRG 003.
BILLING CODE 4120-01-P

[[Page 42065]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.006

BILLING CODE 4120-01-C
    Comment: Several commenters expressed support for the proposal to 
reassign procedure codes 5A1522G and 5A1522H describing peripheral ECMO 
procedures from their current MS-DRG assignments to Pre-MDC MS-DRG 003 
and to revise the titles for MS-DRGs 207, 291, 296 and 870 as shown in 
the table above. The commenters stated that this reassignment more 
appropriately reflects the resource utilization of patients requiring 
this treatment. A commenter also stated their appreciation of CMS' 
research for the proposal which they believe was needed to maintain the 
financial viability of ECMO programs. Another commenter stated they 
agreed with the non-O.R. designation of peripheral ECMO procedures 
noting these procedures are typically performed at the bedside or in

[[Page 42066]]

an ICU setting due to the emergent condition of the patient. This 
commenter also stated that the delivery of ECMO support in a non-O.R. 
setting does not diminish the resource intensive nature of the 
treatment however, and therefore agreed with the designation of non-
O.R. affecting Pre-MDC MS-DRG 003.
    Response: We thank the commenters for their support.
    Comment: A few commenters recommended that ICD-10-PCS procedure 
codes 5A1522G and 5A1522H be assigned to MS-DRG 215 (Other Heart Assist 
System Implant) as opposed to Pre-MDC MS-DRG 003. The commenters stated 
that MS-DRG 215 is the primary MS-DRG for peripheral heart assist pumps 
with similar patient conditions and clinical coherence. A commenter 
stated that assigning percutaneous (peripheral) ECMO into a different 
category for payment than percutaneous VAD (Ventricular Assist Device) 
creates a system of winners and losers by device.
    Response: We thank the commenters for their recommendation. We note 
that as stated in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41168), 
in cases where a percutaneous external heart assist device is utilized, 
in combination with a percutaneous ECMO procedure, effective October 1, 
2018, the ICD-10 MS-DRG GROUPER logic results in a case assignment to 
MS-DRG 215 because the percutaneous external heart assist device 
procedure is designated as an O.R. procedure and assigned to MS-DRG 
215. We also note that under the ICD-10-PCS classification, ECMO is not 
defined as a device. The procedure codes in Table 5A0, specifically any 
procedure code for ECMO, do not contain a device value for the sixth 
character, rather they contain a function value for the sixth character 
to identify oxygenation.
    Comment: A commenter expressed concern with the proposal to 
continue designating peripheral ECMO procedures as non-O.R. procedures, 
however, the commenter acknowledged that these procedures may be 
performed in non-O.R. locations such as the ER or ICU. The commenter 
noted that the determining factor for the location where ECMO is 
initiated is typically dictated by the patient's situation. According 
to the commenter, for critically ill patients who require life-saving 
ECMO, cannulation and initiation of the ECMO circuit is usually done in 
an emergent manner. The commenter also noted that these patients are 
often at risk of imminent death and cannot safely be moved to another 
location for cannulation and ECMO initiation. The commenter requested 
that CMS review the designation of the ECMO codes and consider the 
unique nature of these procedures during the comprehensive review of 
the ICD-10-PCS procedure codes.
    Response: We appreciate the commenter's feedback. As noted in the 
proposed rule and in section II.F.13.a. of the preamble of this final 
rule, we plan to conduct a comprehensive, systematic review of the ICD-
10-PCS procedure codes, including the ECMO procedure codes, and as part 
of that comprehensive procedure code review, we will also review the 
process for determining when a procedure is considered an operating 
room procedure.
    Comment: A commenter noted that the FY 2020 ICD-10-PCS codes were 
made publicly available in June 2019 and that new procedure codes 
describing intraoperative ECMO were created. The commenter requested 
that CMS provide guidance on the correct reporting of these procedure 
codes when performed in the cardiac catheterization lab, the 
electrophysiology lab or other inpatient places of service, including 
the O.R., since the designation of these new procedure codes is non-
O.R.
    Response: The commenter is correct that the FY 2020 ICD-10-PCS 
procedure code files were made publicly available in June 2019 (which 
are available via the internet on the CMS website at: https://www.cms.gov/Medicare/Coding/ICD10/2020-ICD-10-PCS.html) and that new 
procedure codes describing intraoperative ECMO have been created. As 
shown in Table 6B.--New Procedure Codes, associated with this final 
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), procedure codes 5A15A2F (Extracorporeal 
oxygenation, membrane, central, intraoperative), 5A15A2G 
(Extracorporeal oxygenation, membrane, peripheral veno-arterial, 
intraoperative) and 5A15A2H (Extracorporeal oxygenation, membrane, 
peripheral veno-venous, intraoperative) are effective with discharges 
on and after October 1, 2019 and are designated as non-O.R. procedures. 
We note that, historically, we have not provided coding advice in 
rulemaking with respect to policy. We collaborate with the American 
Hospital Association (AHA) through the Coding Clinic for ICD-10-CM and 
ICD-10-PCS to promote proper coding (81 FR 56841).
    Comment: Some commenters suggested that CMS should assign the new 
procedure codes describing intraoperative peripheral ECMO procedures 
(as discussed above) to Pre-MDC MS-DRG 003 until claims data is 
available to analyze their impact on resource utilization.
    Response: We appreciate the commenters' suggestion, however, as 
discussed at the ICD-10 Coordination and Maintenance Committee meeting 
held on March 5-6, 2019, the request (and subsequent finalization) for 
new procedure codes describing the intraoperative use of ECMO was 
specifically to address those situations in which the use of the ECMO 
was in support of a surgical (O.R.) procedure and the ECMO was 
discontinued at the conclusion of the procedure. For example, a patient 
who undergoes a lung transplant and receives ECMO support during the 
transplant procedure and the ECMO is discontinued at the conclusion of 
the lung transplant procedure. In this scenario, it is the lung 
transplant that is the surgical (O.R.) procedure and case assignment to 
MS-DRG 007 (Lung Transplant) by the GROUPER logic is what is 
appropriately reflected in the MedPAR claims data. As stated in the 
proposed rule and in this final rule, 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 involves review of the predecessor 
procedure code assignment. However, this process does not automatically 
result in the new procedure code being assigned to the same MS-DRG as 
the predecessor code. Consistent with our annual process of reviewing 
the MS-DRGs, we will continue to monitor cases to determine if any 
additional adjustments are warranted to account for changes in resource 
consumption.
    Comment: A few commenters requested that CMS consider reprocessing 
claims for cases reporting procedure code 5A1522G or 5A1522H in MS-DRGs 
207, 291, 296 or 870 in FY 2019 as a result of the financial impact it 
has had on providers and their belief that the codes were 
inappropriately classified. Specifically, commenters questioned if CMS 
would permit acute care hospitals to re-bill all FY 2019 ECMO cases 
under MS-DRG 003 to recoup lost revenues.
    Response: As previously discussed, consistent with our annual 
process of assigning new procedure codes to MDCs and MS-DRGs, we 
reviewed the predecessor procedure code assignments, as well as other 
factors relevant to the MS-DRG assignment. As

[[Page 42067]]

discussed in the proposed rule, after further consideration of these 
factors and review of these cases, including the data analysis 
described previously, CMS proposed to change the assignment of these 
cases beginning in FY 2020. As such, and consistent with our general 
approach to changes in MS-DRG assignment, the finalized policy we are 
adopting with regard to the assignment of cases reporting peripheral 
ECMO procedures is prospective, effective with discharges beginning in 
FY 2020 and is not applicable to discharges in FY 2019. We also note 
that section 1886(d)(5)(A) of the Act provides for Medicare payments to 
Medicare-participating hospitals in addition to the basic prospective 
payments for cases incurring extraordinarily high costs. To qualify for 
outlier payments, a case must have costs above a fixed-loss cost 
threshold amount (a dollar amount by which the costs of a case must 
exceed payments in order to qualify for outliers).
    Comment: A commenter stated that Tables 7A and 7B associated with 
the proposed rule show a decline of the case counts in Pre-MDC MS-DRG 
003 from Version 36 to Version 37 of the ICD-10 MS-DRG GROUPER (15,749 
vs. 15,164). The commenter stated that under the current proposal to 
reassign cases reporting peripheral ECMO procedures, they would expect 
to see a shift in cases to Pre-MDC MS-DRG 003 from MS-DRGs 207, 291, 
296, and 870 for the cases reporting procedures for peripheral ECMO. 
The commenter requested that CMS revisit these tables to provide 
insight and clarification concerning a potential issue with the 
surgical hierarchy given that the peripheral ECMO procedure codes are 
not recognized as O.R. procedures and the Version 36 volume of cases is 
higher than the Version 37 volume of cases based on the data within 
these tables.
    Response: We reviewed the cases assigned to Pre-MDC MS-DRG 003 and 
found that the majority of the reduction in the case counts between 
Version 36 and Version 37 of the GROUPER was attributable to the 
proposed change in the designation of the ICD-10-PCS procedure codes 
describing bronchoalveolar lavage from O.R. to non-O.R. status, which 
is discussed in section II.F.13.b.1. of the preamble of this final 
rule. Since these procedures were the only operating room procedure 
reported for these cases, the proposed change in the O.R. status of 
these codes resulted in the reassignment or ``shift'' of these cases 
reporting these procedures from Pre-MDC MS-DRG 003 to Pre-MDC MS-DRG 
004. As discussed in section II.F.13.b.1, we are finalizing this 
proposed change in designation for these procedure codes, and therefore 
Tables 7A and 7B associated with this final rule reflect similar 
``shifts'' in the volume of cases reported to MS-DRG 003 between 
Version 36 and Version 37 of the GROUPER.
    After consideration of the public comments we received, we are 
finalizing our proposal to reassign the procedure codes describing 
peripheral ECMO procedures from their current MS-DRG assignments to 
Pre-MDC MS-DRG 003 and maintain the designation of the peripheral ECMO 
procedures as non-O.R. We are also finalizing our proposal to make 
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 under the ICD-10 MS-DRGs Version 37, 
effective October 1, 2019.
b. Allogeneic Bone Marrow Transplant
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19176), 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 
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.
    As noted in the proposed rule, 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.

BILLING CODE 4120-01-P

[[Page 42068]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.007

    As noted in the FY 2020 IPPS/LTCH PPS proposed rule, 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 42069]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.245

BILLING CODE 4120-01-C
    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.
    We stated in the proposed rule that 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 noted 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, we stated that, 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. We stated that 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 noted 
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/ICD9ProviderDiagnosticCodes/ICD-9-CM-C-and-M-Meeting-Materials.html for the committee meeting materials and 
discussion regarding this proposal.
    In the proposed rule, 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, we stated that our clinical advisors supported 
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 in the proposed rule 
and 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, in the proposed rule, we stated that we are 
further reviewing the Medicare Claims Processing Manual to identify 
potential revisions to address this duplication. However, we also noted 
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 noted 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, in the proposed rule, we stated that 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, in the 
proposed rule we noted 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 final 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, in the FY 2020 IPPS/LTCH PPS 
proposed

[[Page 42070]]

rule, we did not propose to change the current structure of MS-DRG 014. 
In addition, we did not propose 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 procedure codes for allogeneic HCT procedures that are assigned 
to MS-DRG 014, in the proposed rule, we noted that 8 procedure codes 
for autologous HCT procedures are currently included in MS-DRG 014, as 
shown in the following table. We stated that these codes are not 
properly assigned because MS-DRG 014 is defined by cases reporting 
allogenic HCT procedures.
    In the proposed rule, we stated that 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 noted that, of these 8 
procedure codes, there are 4 procedure codes that describe a 
transfusion via arterial access. As noted in the proposed rule and 
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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.009

    We stated in the proposed rule that, while we believe, as 
indicated, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.010

    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 stay of 11 days and average costs of $33,540.
    As indicated in the FY 2020 IPPS/LTCH PPS proposed rule, the 
results of our analysis indicate that the frequency with which these 
autologous HCT procedure codes were reported in MS-

[[Page 42071]]

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. 
We further stated in the proposed rule that 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, in the 
FY 2020 IPPS/LTCH PPS proposed rule, we proposed 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.011

    As discussed in the proposed rule and 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.
    We stated in the proposed rule that 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 the 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.
    As discussed in the proposed rule, 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 the proposed rule. Our 
clinical advisors agreed that because a transfusion procedure always 
uses venous access rather than arterial access, these codes are 
considered invalid. We stated in the proposed rule that 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.012

    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, in the FY 2020 IPPS/LTCH PPS proposed rule, we 
proposed 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 listed 
in Table 6P.1a associated with the proposed rule. As discussed 
previously, we did not propose 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.
    Comment: Commenters supported the proposal to maintain the current 
structure of MS-DRG 014. Commenters also supported the proposals 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. A commenter 
specifically expressed their appreciation with CMS' diligence in 
ensuring the clinical appropriateness of the ICD-10 codes. This 
commenter also requested that CMS create an edit (similar to what was 
implemented in the CY 2017 Hospital Outpatient Prospective Payment 
System final rule, which states outpatient claims assigned to C-APC 
5224 with CPT code 38240 must be

[[Page 42072]]

reported with revenue code 0815, and if that code is missing, the claim 
is returned by an edit to the provider) for inpatient claims utilizing 
ICD-10-PCS codes and revenue code 0815. According to the commenter, 
this would better inform CMS future ratesetting and reimbursement, as 
well as provide access to the more robust data in revenue code 0815 
which the commenter asserted would allow CMS to do a meaningful 
analysis on the differences between search and procurement costs for 
related versus unrelated transplants. The commenter also recommended 
that CMS look at bone marrow and stem cell transplant services 
holistically and consider the process that providers must follow in 
order to correctly code and submit a claim.
    Response: We appreciate the commenters' support. With regard to the 
recommendation that we create a new code edit for ICD-10-PCS codes 
reported with revenue code 0815 on the claim, as we noted in the 
proposed rule, 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 final rule, it is a software program that detects and 
reports errors in the coding of Medicare claims data. In response to 
the commenter's recommendation that we consider the process that 
providers must follow in order to correctly code and submit a claim, we 
note that, as stated in the proposed rule, and above, 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. As 
indicated, we are considering additional revisions as needed to conform 
the instructions for reporting these codes in the Medicare Claims 
Processing Manual.
    After consideration of the public comments we received, we are 
finalizing our proposal 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 and 
listed in Table 6P.1a associated with the proposed rule and this final 
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) under the ICD-10 MS-DRGs Version 37, 
effective October 1, 2019.
c. Chimeric Antigen Receptor (CAR) T-Cell Therapies
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19180), 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 the development of 
unique CAR T-cell therapy revenue and cost centers for billing and cost 
reporting purposes. In the proposed rule, we stated that we will 
consider these technical and operational suggestions in the development 
of future billing and cost reporting guidelines and instructions.
    In the FY 2020 IPPS/LTCH PPS proposed rule, we noted that, 
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 in the proposed rule and 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. We 
stated in the FY 2020 IPPS/LTCH PPS proposed rule that, 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 stated that we do 
not have the comprehensive clinical and cost data that we generally 
believe are needed to do so. Furthermore, we stated in the proposed 
rule that 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 the proposed rule and this final 
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 did not propose to modify the current MS-DRG 
assignment for cases reporting CAR T-cell therapies for FY 2020. We 
noted that 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. We stated that 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.
    Comment: Several commenters supported our proposal not to modify 
the current MS-DRG assignment for cases reporting CAR T-cell therapies 
for FY 2020, stating that CMS should wait until more clinical and cost 
data are available. Commenters indicated that CMS should wait until 
claims are coded and billed in a uniform manner so that consistent and 
accurate claims data is available for rate-setting. MedPAC also stated 
that incorporating new technologies into the Medicare program by using 
an existing MS-DRG in conjunction with new technology add-on payments 
and outlier payments has created incentives for efficiency and risk-
sharing between providers and the Medicare program.

[[Page 42073]]

    Response: We appreciate the commenters' support for our proposal 
and agree that incorporating new technologies into the Medicare program 
by using an existing MS-DRG in conjunction with new technology add-on 
payments, and outlier payments if applicable, is consistent with our 
policies regarding how new technologies are incorporated into the IPPS.
    Comment: Several other commenters encouraged CMS to develop a new 
MS-DRG for cases reporting CAR T-cell therapies for FY 2020 in order to 
adequately cover the costs of treatment and so as not to dis-
incentivize hospitals from providing CAR T-cell therapies due to 
inadequate reimbursement. Most of these commenters recommended 
alternative payment approaches for the CAR T-cell product if a new MS-
DRG were created.
    A commenter stated that claims analyses from the FY 2019 IPPS/LTCH 
PPS proposed rule for the KYMRIAHTM and 
YESCARTATM new technology add-on payment applications found 
a significant number of patients who may be eligible for use of these 
therapies, which may be reflective of the potential growth of these 
therapies in the future. The commenter also stated that according to 
the FY 2018 MEDPAR update, other pre-MDC MS-DRGs contain fewer cases 
than the 386 CAR T-cell discharges that CMS estimated would qualify for 
new technology add-on payments. The commenter stated that this suggests 
that there are enough cases for CAR T-cell therapies to be considered 
for their own MS-DRG assignment. Another commenter stated that in the 
FY 2019 IPPS/LTCH PPS proposed rule, CMS expressed concern about the 
potential redistributive effects away from core hospital services over 
time toward specialized hospitals and how that may affect payment for 
core services if a new MS-DRG is created. The commenter stated they 
shared these concerns; however, believed they are mitigated to the 
extent that CMS creates a new MS-DRG during a time when the volume of 
CAR T-cell cases is very low. They also noted the technology will 
likely become less expensive, not more expensive over time, as commonly 
occurs with expensive new technologies. The commenter urged CMS to 
create a new MS-DRG specific to CAR T-cell cases for use in FY 2020. 
The commenter expressed concern that if CMS waits to make an MS-DRG 
change at a time when volume is higher, but before the CAR T-cell cases 
have become less expensive, the CAR T-cell cases will draw a higher 
amount of additional payments at the expense of all other cases.
    Response: As discussed in the proposed rule, we continue to believe 
that we do not have the comprehensive clinical and cost data that we 
generally believe is needed to create a new MS-DRG. As stated earlier, 
we also continue to believe that incorporating new technologies into 
the Medicare program by using an existing MS-DRG in conjunction with 
new technology add-on payments, and outlier payments if applicable, is 
consistent with our policies regarding how new technologies are 
incorporated into the IPPS. We note that we address additional comments 
relating to the creation of a separate MS-DRG, including potential 
payment approaches, in the discussion of alternative payment for CAR T-
cell therapy cases that follows.
    With respect to the number of cases, we note that the new 
technology add-on payment estimate is a projection of future cases. Our 
standard practice in determining whether to create a new MS-DRG is to 
examine the number of cases, and the clinical and cost characteristics 
of those cases in the historical claims data. We do not have the 
clinical and cost data about these projected future FY 2020 cases 
available at this time.
    With respect to the commenter who expressed concern that waiting to 
create a new MS-DRG would draw a higher amount of additional payments 
at the expense of all other cases, we are unclear as to the specific 
concern being raised by the commenter. Each year, we calculate the 
relative weights by dividing the average cost for cases within each MS-
DRG by the average cost for cases across all MS-DRGs. Since the 
relative weight is recalculated each year, the implications for the 
payments for other cases do not differ based on when a new MS-DRG is 
created.
    Therefore, after consideration of the comments we received, and for 
the reasons discussed, we are finalizing our proposal not to modify the 
MS-DRG assignment for cases reporting CAR-T cell therapies for FY 2020. 
As noted previously, we address additional comments we received 
relating to the creation of any potential new MS-DRG, including payment 
under any such MS-DRG, in the discussion that follows.
    As part of our solicitation of public comment on the potential 
creation of a new MS-DRG for CAR-T cell therapy procedures, in the 
proposed rule we also invited comment on the most appropriate way to 
develop the relative weight if we were to finalize the creation of a 
new MS-DRG in future rulemaking. We stated that, 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 invited 
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. We stated in the 
proposed rule that, 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. We also stated 
that 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. We stated that 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 
requested public comments on these approaches or other approaches for 
setting the relative weight if we were to finalize a new MS-DRG. We 
noted 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.
    Comment: We received many comments on the most appropriate way to 
develop the relative weight and modify rate setting trims if we were to 
finalize the creation of a new MS-DRG, including different ways to 
determine the cost of the CAR T-cell therapy product, such as the use 
of Average Sales Price data or acquisition cost data, and technical 
comments on claims inclusion and exclusion criteria related to clinical 
trials.
    Response: As discussed previously in this section, we are 
finalizing our proposal not to modify the MS-DRG assignment for cases 
reporting CAR-T cell therapies for FY 2020. We will

[[Page 42074]]

consider these comments in connection with any future rulemaking 
relating to the MS-DRG assignment for the CAR-T cell therapy cases.
    As discussed further in section II.G.7. of the preamble to the 
proposed rule, we also requested public comment on payment alternatives 
for CAR T-cell 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. We also requested public comments on 
whether 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 invited public comments on how payment alternatives for CAR T-
cell therapy would affect access to care, as well as how they would 
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) and the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19279), we are considering approaches and 
authorities to encourage value-based care and lower drug prices. We 
solicited 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.
    Comment: Some commenters indicated that CMS should pay for CAR T-
cell therapy products based on the Average Sales Price. Some commenters 
noted that CMS pays for hemophilia blood clotting factors in this 
manner. A commenter recognized that payment for blood clotting factors 
in this manner was established by statute, but suggested that CMS may 
have the statutory authority to pay using this approach, or CMS could 
seek statutory authority from Congress. Another commenter urged CMS to 
pay for CAR T-cell therapies at Wholesale Acquisition Cost (WAC) plus 
six percent. Some commenters suggested that CMS require hospitals to 
submit on the claim the particular CAR T-cell product's NDC code. Other 
commenters stated given the similarity of CAR T-cell therapies to solid 
organ transplants, in that they are high-cost, low-volume services, CMS 
should pay for CAR T-cell therapies on a reasonable cost basis. Some 
commenters indicated that CMS should require providers to report value 
code 86, the actual invoice/acquisition cost, on their claims and 
include the actual product acquisition cost on the claim for payment 
purposes.
    Several commenters suggested that CMS adopt a CCR of 1.0 for CAR T-
cell products for all payment purposes, including new technology add-on 
payments, outlier payments, and payments to IPPS-excluded cancer 
hospitals. These commenters stated that utilizing a CCR of 1.0 will 
ensure uniformity among providers, many of whom are currently marking 
up the CAR-T charge, which impacts CMS' ability to analyze claims data 
that are critical for rate setting. These commenters also stated that 
they believe the use of a CCR of 1.0 would ensure consistent billing 
practices and payment that would be mutually beneficial for CMS and 
providers, including eliminating the need for providers to mark-up the 
CAR T-cell product cost. MedPAC expressed concern about using a CCR of 
1.0, which would presume the hospitals charged their actual costs 
despite what it stated was the clear financial incentive to increase 
charges. MedPAC also expressed concern that this could set a precedent 
for other items going forward, and instead recommended the use of a 
lagged ASP based payment. Another commenter stated that using a CCR of 
1.0 is a radical departure from previous payment methods and CMS should 
carefully consider possible issues that may result.
    Many commenters requested structural changes in new technology add-
on payments for the drug therapy, including the use of a uniform add-on 
payment. Many commenters also requested a higher new technology add-on 
payment percentage for CAR T-cell therapy products, up to 100 percent, 
rather than our proposed 65 percent for all new technologies, 
indicating that the proposed 65 percent would result in inadequate 
payment.
    Some commenters suggested that CMS develop and release for comment 
an outcomes-based payment model for CAR T-cell therapy payments in the 
future and encouraged CMS to consider a payment alternative for CAR T-
cell therapy under which CMS would test a new payment model through the 
Innovation Center and would pay for these technologies based on outcome 
and value rather than service.
    Response: After a review of the comments received, we continue to 
believe, similar to last year, that given the relative newness of CAR 
T-cell therapy, and our continued consideration of approaches and 
authorities to encourage value-based care and lower drug prices, it 
would be premature to adopt structural changes to our existing payment 
mechanisms, either under the IPPS or for IPPS-excluded cancer 
hospitals, specifically for CAR T-cell therapy. For these reasons, we 
disagree with the commenters' requested changes to our current payment 
mechanisms for FY 2020, including, but not limited to, the creation of 
a pass-through payment; structural changes in new technology add-on 
payments and/or a differentially higher new technology add-on payment 
percentage specifically for CAR T-cell products, and changes in the 
usual cost-to-charge ratios (CCRs) used in ratesetting and payment, 
including those used in determining new technology add-on payments, 
outlier payments, and payments to IPPS excluded cancer hospitals. 
However, as discussed elsewhere in this final rule, we are finalizing a 
maximum new technology add-on payment percentage of 65 percent of the 
costs of the new technology for FY 2020, a 30 percent ((0.65/0.50)-1) 
increase from the current 50 percent. This increase to 65 percent will 
apply to all approved new technologies (except products designated by 
the FDA as a Qualified Infectious Disease Products, for which the 
maximum add-on amount will be 75 percent of the costs of the new 
technology), including CAR T-cell therapy products.
    We stated in the proposed rule that 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, in the proposed 
rule we invited public comments on whether we

[[Page 42075]]

should not geographically adjust the payment for cases assigned to any 
potential new MS-DRG for CAR-T cell therapy procedures. We also invited 
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 noted 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 as those of CAR T-cell therapies, nor would 
they represent as significant a percentage of the average costs for the 
case. We invited 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.
    Comment: Some commenters stated that CMS should include adjustments 
for the wage index in a potential future MS-DRG for CAR T-cell 
therapies, including commenters that expressed concern that not 
applying the wage index would increase provider losses on these 
services. Some commenters stated that they did not believe CMS had the 
statutory flexibility to selectively apply the wage index. Many other 
commenters stated that CMS should not apply the wage index to the cost 
of the drug, as the cost does not vary by location, and hospitals with 
a wage index greater than 1 would be overpaid for the drug, while 
hospitals with a wage index less than 1 would be underpaid.
    Response: We appreciate the commenters' input on the application of 
the wage index to a potential future MS-DRG for CAR T-cell therapies. 
We will consider these comments should we develop a proposed MS-DRG for 
CAR T-cell therapies in the future.
    As discussed in the proposed rule, 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.
    In the proposed rule we stated that, 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 invited 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 invited 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 invited 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.
    Comment: Several commenters stated that CMS should include 
adjustments for DSH and IME in a potential future MS-DRG for CAR T-cell 
therapies (as described below); some commenters stated that they did 
not believe CMS had the statutory flexibility to selectively apply 
these adjustments. Commenters also expressed concern that not applying 
these adjustments would increases provider losses on these services. 
Several commenters stated that the IME adjustment is not based on a 
requirement that the costs for each service at a teaching hospital are 
greater than at a non-teaching hospital, but is instead due to the 
recognition that overall the costs are greater. A commenter stated that 
teaching hospitals are under considerable financial strain, that they 
will disproportionately shoulder the burdens of new, higher cost 
services, and that CMS should consider these costs and burdens before 
determining that the IME adjustment to CAR T-cell therapy cases would 
result in a payment that is too high. This commenter also stated that 
hospitals that receive DSH payments are less profitable than hospitals 
serving better-insured populations. Therefore, in order for these 
hospitals to access expensive new technologies, they need to receive a 
level of reimbursement that can support these services.
    Many commenters stated that CMS should not apply the DSH and IME 
adjustments to the entire MS-DRG payment for CAR T-cell therapy cases, 
as this would result in a higher than appropriate payment. Several of 
these commenters also suggested that CMS consider ``carving out'' 
payment for CAR T-cell therapy cases to avoid this problem.
    Response: We appreciate the commenters' input on the application of 
the DSH and IME adjustments to a potential future MS-DRG for CAR T-cell 
therapies. We will consider these comments should we develop a proposed 
MS-DRG for CAR T-cell therapies in the future.
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''. In the FY 2020 IPPS/LTCH PPS proposed rule, 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

[[Page 42076]]

artery; and 14 codes describing dilation of a vein (jugular, vertebral 
and face), as shown in the following table.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR16AU19.013

BILLING CODE 4120-01-C
    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.

[[Page 42077]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.014

    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 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.
    In the proposed rule, we noted that 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 proposed 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.
    We also indicated in the proposed rule that 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.015

    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.
    In the proposed rule, we stated that 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

[[Page 42078]]

describe a carotid artery stent procedure to MS-DRGs 037, 038, and 039. 
Therefore, we proposed 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. In the 
proposed rule, we stated that 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 the 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 proposed to remove from MS-DRGs 037, 038, and 039.
    We also noted that, as discussed in the proposed rule and section 
II.F.14.f. of the preamble of this final 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 noted in the proposed rule that, of the 96 procedure codes that we 
proposed to remove from the logic for MS-DRGs 037, 038, and 039, there 
are 48 procedure codes that include the qualifier term ``bifurcation''. 
Therefore, we stated in the proposed rule that these 48 procedure codes 
will be deleted effective October 1, 2019. We stated that the 48 
remaining valid procedure codes that do not include the term 
``bifurcation'' that we proposed to remove from MS-DRGs 037, 038, and 
039 will continue to be assigned to MS-DRGs 034, 035, and 036.
    Lastly, we stated in the proposed rule that, 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 definition of these 
MS-DRGs based on the discussion and proposals described above.
    Comment: Several commenters supported this proposal stating that 
only procedures involving dilation of a carotid artery using 
intraluminal devices should be included in MS-DRGs 034-036 and that 
procedures that do not involve both a carotid artery and an 
intraluminal device should be removed from MS-DRGs 034-036. Several 
commenters also supported our proposal to remove 96 ICD-10 PCS codes 
describing dilation of a carotid artery with intraluminal device from 
MS-DRGs 037, 038 and 039 and to delete the 48 procedure codes from MS-
DRGs 037, 038, and 039 that include the qualifier term ``bifurcation.
    Response: We appreciate the commenters' support.
    Comment: A commenter expressed concern and disagreed with the 
proposal to delete the procedure codes that include the qualifier term 
``bifurcation''. The commenter stated that in vascular surgery, use of 
the term bifurcation may be used to document when a procedure occurs in 
a branch vessel.
    Response: We appreciate the commenter's suggestion, however, as 
discussed at the ICD-10 Coordination and Maintenance Committee meeting 
held on September 11-12, 2018, the qualifier value Bifurcation was 
proposed (and subsequently finalized) to be deleted from the following 
ICD-10-PCS tables--037 Dilation of Upper Arteries, 03C Extirpation of 
Upper Arteries, 047 Dilation of Lower Arteries, 04C Extirpation of 
Lower Arteries and 04V Restriction of Lower Arteries. The original 
proposal for the qualifier Bifurcation was intended to capture data 
specifically regarding procedures on coronary arteries. The term 
bifurcation describes diagnosis related information, and generally, 
under ICD-10 PCS we do not include diagnosis related information in the 
procedure classification.
    After consideration of the public comments we received, we are 
finalizing our proposal to remove the procedure codes listed previously 
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. We are also finalizing our proposal to remove 96 ICD-10 PCS 
codes describing dilation of a carotid artery with intraluminal device 
from MS-DRGs 037, 038 and 039 and are finalizing our proposal to 
reassign the 6 procedure codes discussed above 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 final 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 removed from MS-DRGs 037, 038, and 039. 
Additionally, we are finalizing our proposal to delete the 48 procedure 
codes from MS-DRGs 037, 038, and 039 that include the qualifier term 
``bifurcation''. Finally, we are finalizing our proposal to 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 definition 
of these MS-DRGs.
4. MDC 4 (Diseases and Disorders of the Respiratory System): Pulmonary 
Embolism
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19185), we 
discussed that 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.

[[Page 42079]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.016

    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.
    As indicated in the FY 2020 IPPS/LTCH PPS proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.017

    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). We stated in the proposed rule 
that our clinical advisors also agreed 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, in the proposed rule, we 
proposed 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.
    Comment: Commenters supported our proposed reassignment of 
diagnosis codes I26.01, I26.02, and I26.09 to the higher severity level 
MS-DRG 175 and revision of the title for MS-DRG 175 to ``Pulmonary 
Embolism with MCC or Acute Cor Pulmonale'' to more accurately reflect 
the diagnoses.
    Response: We thank the commenters for their support. After 
consideration of the public comments we received, we are finalizing our 
proposal 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''.

[[Page 42080]]

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, as discussed in the FY 2020 IPPS/
LTCH PPS proposed rule (84 FR 19185 through 19193), 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 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).
    As we discussed in the proposed rule, 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).
    As noted in the proposed rule, the ICD-10-PCS procedure codes 
describing a transcatheter cardiac valve repair procedure with an 
implant are listed in the following table.
BILLING CODE 4120-01-P

[[Page 42081]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.018

    As also noted in the proposed rule, the ICD-10-PCS procedure codes 
describing a transcatheter cardiac valve replacement procedure are 
listed in the following table.
[GRAPHIC] [TIFF OMITTED] TR16AU19.019


[[Page 42082]]


BILLING CODE 4120-01-C
    We noted in the proposed rule that 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.020

    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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.021

    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 in the proposed rule and 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

[[Page 42083]]

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.
    As indicated in the proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.022

    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 and in the proposed rule, 
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.
    As also indicated in the proposed rule, 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.

[[Page 42084]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.023

    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 and in the proposed rule, 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 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).
    In the proposed rule, we stated that our clinical advisors continue 
to believe that transcatheter cardiac valve repair procedures are not 
the same as a transcatheter (endovascular) cardiac valve replacement. 
However, we stated that they agreed 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, we 
stated that our clinical advisors agreed 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 also 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.024

    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. As indicated in the proposed rule, 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.
    As stated in the proposed rule, 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.

[[Page 42085]]

    We analyzed the following ICD-10-PCS procedure codes that are 
currently assigned to MS-DRGs 216, 217, 218, 219, 220, and 221.
[GRAPHIC] [TIFF OMITTED] TR16AU19.025

    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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.026

    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 noted in the proposed rule 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).

[[Page 42086]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.027

[GRAPHIC] [TIFF OMITTED] TR16AU19.028

    In the proposed rule, we stated 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 
noted 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.
    We stated in the proposed rule that 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, to 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.

[[Page 42087]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.029

    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. As stated in the proposed rule, 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.
    For FY 2020, we proposed 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 also proposed 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. In addition, we proposed 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 
proposed to reassign the procedure codes from their current MS-DRGs to 
the proposed new MS-DRGs.
    Comment: Several commenters agreed with the proposal to reassign 
the procedure codes describing a transcatheter cardiac valve repair 
(supplement) procedure from their current MS-DRG assignments as 
displayed and discussed above, to proposed revised MS-DRGs 266 and 267. 
Commenters also agreed with our proposal to revise the titles for MS-
DRGs 266 and 267 to reflect the proposed restructuring. Commenters 
noted the procedural technique, skills, staff, equipment and average 
costs of the transcatheter cardiac valve repair (supplement) procedures 
closely correspond with other transcatheter valve procedures that are 
currently classified within MS-DRGs 266 and 267. Commenters stated the 
proposal ensures that the new MS-DRG assignments accurately capture the 
resource utilization and clinical coherence for these transcatheter 
cardiac valve procedures. Commenters stated that the procedure for 
transcatheter mitral valve repair (TMVR) with implant (e.g., 
Mitraclip[supreg]), identified by ICD-10-PCS procedure code 02UG3JZ 
(Supplement mitral valve with synthetic substitute, percutaneous 
approach) has demonstrated evidence-based clinical benefits and the 
proposal would allow effective treatment options for high risk patients 
where open heart surgery is not an option. Other commenters commended 
CMS for reviewing the MS-DRG assignment for transcatheter cardiac valve 
procedures and proposing to reassign the supplement procedures to MS-
DRGs 266 and 267 since, according to the commenters, these MS-DRGs were 
specifically created to classify these kinds of patients. Commenters 
also stated that the proposal ensures more appropriate payment to 
providers for these procedures. A commenter who expressed support for 
the proposal encouraged CMS to continue to monitor these MS-DRGs as 
therapies continue to evolve and future modifications may be warranted.
    Response: We appreciate the commenters' support. We agree the 
proposal would accurately capture the resource utilization and clinical 
coherence for these transcatheter cardiac valve procedures. Consistent 
with our annual process of reviewing the MS-DRGs, we will continue to 
monitor cases to determine if any additional adjustments are warranted.
    Comment: Some commenters also agreed with the proposal to create 
new MS-DRGs 319 and 320 for the other transcatheter (non-supplement) 
cardiac valve procedures and stated this would better reflect the 
resource consumption for these patients. A commenter who supported the 
proposal requested that CMS clarify that the procedures can be 
performed by both interventional cardiologists, as well as 
cardiothoracic surgeons. This commenter agreed that, regardless of the 
provider performing the procedure, additional training and skills are 
required. The commenter also recommended that CMS continue to monitor 
the claims data for the affected procedure codes to ensure that 
unintended consequences do not occur and patient access is not at risk.
    A few commenters recommended that CMS delay the proposed 
reassignment of non-supplement transcatheter cardiac valve procedures 
to proposed new MS-DRGs 319 and 320 until more data informing resource 
use for non-supplement percutaneous cardiac valve procedures becomes 
available and further consideration is given to clinical coherence. A 
commenter believed that reassignment of these procedures at this time 
is premature and that a decision by CMS to delay the implementation of 
this proposed policy specific to non-

[[Page 42088]]

supplement valve procedures by percutaneous approach would have minimal 
impact on the adoption and implementation of the proposed separate 
policy related to the reassignment of transcatheter cardiac valve 
repair (supplement) procedures to MS-DRGs 266 and 267. Another 
commenter expressed concern that not all the procedure codes describing 
non-supplement transcatheter cardiac valve procedures included in the 
proposed reassignment to proposed new MS-DRGs 319 and 320 appear to be 
consistent with the rationale presented in the proposed rule nor did 
the analysis identify all the potentially impacted cases and therefore, 
according to the commenter, the analysis does not sufficiently estimate 
the impact on providers for FY 2020.
    Response: We thank the commenters for their support and feedback. 
We wish to clarify that the transcatheter (non-supplement) cardiac 
valve procedures can be performed by both interventional cardiologists, 
as well as cardiothoracic surgeons. Our clinical advisors agree with 
the commenter that regardless of the provider performing the procedure, 
additional training and skills are required.
    We disagree with delaying the proposed reassignment of non-
supplement transcatheter cardiac valve procedures to proposed new MS-
DRGs 319 and 320 and that reassignment of these procedures at this time 
is premature. We also disagree with the commenter who expressed concern 
that not all the procedure codes describing non-supplement 
transcatheter cardiac valve procedures included in the proposed 
reassignment to proposed new MS-DRGs 319 and 320 appear to be 
consistent with the rationale presented in the proposed rule. As 
discussed in the proposed rule and previously in this section, our 
clinical advisors, as well as several other commenters, supported 
grouping these other cardiac valve procedures 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 special 
additional training and skills, and often require additional ancillary 
procedures and equipment. With regard to the commenter's concern that 
the analysis did not identify all the potentially impacted cases and 
therefore does not sufficiently estimate the impact on providers for FY 
2020, we note that the analysis we provided was based on the MS-DRGs 
that were discussed under the proposal for cases that reported any of 
the non-supplement transcatheter cardiac valve procedures. (If no cases 
were found to report one of the listed procedure codes describing a 
non-supplement transcatheter cardiac valve procedure then that 
procedure code was not reflected in the data analysis table). As stated 
in the proposed rule, we presented the impact of grouping the 
transcatheter (non-supplement) cardiac valve procedures with a 2-way 
severity level split. The analysis was based on the September 2018 
update of the FY 2018 MedPAR data and included the proposed changes to 
the CC/MCC severity level designations. While, as previously noted, we 
do not generally perform any further MS-DRG analysis of claims data for 
purposes of the final rule, in response to the commenter's concern 
regarding whether the analysis identified all potentially impacted 
cases, we further examined the proposed 2-way severity level split 
using the March 2019 update of the FY 2018 MedPAR data.
[GRAPHIC] [TIFF OMITTED] TR16AU19.030

    As shown in the table, there were 1,700 cases for the other 
endovascular cardiac valve procedures with MCC group, with an average 
length of stay of 10.1 days and average costs of $29,181. There was a 
total of 624 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 $16,706. Similar to our process discussed in the 
proposed rule, we again applied the criteria to create subgroups for 
the two way severity level split for the proposed MS-DRGs and found 
that all five criteria were met. We note that, as discussed in section 
II.F.14.c.1. of the preamble of this final rule, we are generally not 
finalizing the proposed changes to the CC/MCC severity level 
designations that were considered under the comprehensive CC/MCC 
analysis. Therefore, the above updated analysis reflects the finalized 
policy.
    For the reasons noted previously, we continue to believe it is 
appropriate to group all the non-supplement transcatheter cardiac valve 
procedures together, and the updated data analysis also continues to 
support the two way severity level split. In response to the 
commenter's recommendation that we monitor the claims data for the 
affected procedure codes to ensure that unintended consequences do not 
occur and patient access is not put at risk, consistent with our annual 
process of reviewing the MS-DRGs, we will continue to monitor cases to 
determine if any additional modifications are warranted. For the 
reasons described above and after consideration of the public comments 
we received, we are finalizing our proposal 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 MS-DRG 266 from ``Endovascular Cardiac 
Valve Replacement with MCC'' to ``Endovascular Cardiac Valve 
Replacement and Supplement Procedures with MCC'' and to revise the 
title of MS-DRG 267 from ``Endovascular Cardiac Valve Replacement 
without MCC'' to ``Endovascular Cardiac Valve Replacement and 
Supplement Procedures without MCC''. In addition, we are finalizing our 
proposal to create new MS-DRG 319 (Other Endovascular Cardiac Valve 
Procedures with MCC) and new MS-DRG 320 (Other Endovascular Cardiac 
Valve Procedures without MCC) and reassigning the non-

[[Page 42089]]

supplement transcatheter cardiac valve procedure codes displayed and 
discussed earlier in this section from their current MS-DRGs to these 
new MS-DRGs, under the ICD-10 MS-DRGs Version 37, effective October 1, 
2019.
b. Revision of Pacemaker Lead
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19193), 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). In the FY 2020 IPPS/LTCH PPS proposed rule, we proposed 
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. We stated in the proposed rule 
that, if the proposal is finalized, we would make conforming changes to 
the ICD-10 MS-DRG Definitions Manual Version 37.
    Comment: Commenters agreed with the proposal 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.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal 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 under the ICD-10 MS-DRGs 
Version 37, effective October 1, 2019, and will 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
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19193 through 19199), 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 M00.9 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.
    We noted in the proposed rule that, 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.
    As indicated in the proposed rule, 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.

[[Page 42090]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.031

    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. As we stated in the proposed rule, 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 noted 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, we stated in the proposed rule that 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.032

    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

[[Page 42091]]

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 in the proposed rule 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 in the proposed rule and 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. As we stated in the proposed rule, 
because these diagnosis codes are not specific to the knee in the code 
description, we 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] TR16AU19.033

    We stated in the proposed rule that 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). We stated in the proposed rule that, 
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. We also noted 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 noted 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

[[Page 42092]]

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 proposed to add ICD-10-CM diagnosis code M00.9 to the list of 
principal diagnosis codes for MS-DRGs 485, 486, and 487.
    Comment: Commenters agreed with CMS' proposal to add ICD-10-CM 
diagnosis code M00.9 to the list of principal diagnosis codes for 
assignment to MS-DRGs 485, 486 and 487. The commenters stated that the 
proposal was reasonable, given the ICD-10-CM diagnosis code and the 
information provided.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add ICD-10-CM diagnosis code M00.9 to the 
list of principal diagnosis codes for assignment to MS-DRGs 485, 486 
and 487 in the ICD-10 MS-DRGs Version 37, effective October 1, 2019.
    In the proposed rule, we stated that 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 did not propose to add 
ICD-10-CM diagnosis code A54.42 to the list of principal diagnosis 
codes for these MS-DRGs.
    Comment: Commenters did not support CMS' proposal to not add ICD-
10-CM diagnosis code A54.42 to the list of codes for these MS-DRGs. 
Commenters noted that although A54.42 is not specific to the knee, the 
code is intended to be used for any joint, similar to code M00.9. 
Commenters also noted that the GROUPER logic for MS-DRGs 485, 486 and 
487 that requires the combination of a principal diagnosis code and an 
ICD-10-PCS procedure code for a knee procedure will ensure that cases 
that report a principal diagnosis code of A54.42 and a knee procedure 
are clinically similar to other cases in MS-DRGs 485, 486 and 487.
    Response: We agree with commenters that diagnosis code A54.42 would 
be the appropriate code for a diagnosis of gonococcal arthritis of the 
knee although the Index entry is not specific. Our clinical advisors 
reviewed this issue and the ICD-10-CM Alphabetic index and noted that 
there are no other diagnosis codes in the subcategory A54.- series 
(Gonococcal infection) that are more specific to the knee. Our clinical 
advisors noted that although there was only one case reporting 
gonococcal arthritis as the principal diagnosis with a knee procedure 
performed in the September 2018 update of the FY 2018 MedPAR file, they 
agreed that based on the result of further review, including 
consideration of the commenters' concerns, there is merit in adding 
A54.42 to MS-DRGs 485, 486 and 487 because diagnosis code A54.42 would 
be the appropriate code to report a diagnosis of gonococcal arthritis 
of the knee. We agree with commenters that this reassignment is 
consistent with the reassignment of ICD-10-CM diagnosis code M00.9 
because, although the Index entries do not specifically include the 
knee or any infection of the knee, diagnosis code A54.42 would also be 
used to report an infection of the knee. Therefore, after consideration 
of the public comments that we received and for the reasons described, 
we are finalizing the assignment of ICD-10-CM diagnosis code A54.42 to 
the list of principal diagnosis codes for assignment to MS-DRGs 485, 
486, and 487 (Knee Procedure with Principal Diagnosis of Infection with 
MCC, with CC, and without CC/MCC, respectively) in the ICD-10 MS-DRGs 
Version 37, effective October 1, 2019.
    In the FY 2020 IPPS/LTCH PPS proposed rule, we stated that 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.034

    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, in the proposed rule, we stated that 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.

[[Page 42093]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.035

    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, in the proposed rule we noted 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 noted 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.
    We stated in the proposed rule that our clinical advisors supported 
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.
    As indicated in the proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.036

    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.
    We stated in the proposed rule that, 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.
    We stated in the proposed rule that 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

[[Page 42094]]

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 and in the proposed rule, 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, in the FY 2020 IPPS/LTCH PPS proposed rule, we 
proposed 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 did not 
propose to change the current assignment of these diagnosis codes in 
MS-DRGs 559, 560, and 561.
    Comment: Many commenters agreed with the proposal to remove the 
eight diagnosis codes that do not describe an infection specific to the 
knee from the list of principal diagnosis codes for MS-DRGs 485, 486, 
and 487, and to maintain their current assignment in MS-DRGs 559, 560, 
and 561. A commenter did not support the proposal and believed the 
diagnosis of osteomyelitis should continue to be included in MS-DRGs 
485, 486 and 487 because osteomyelitis describes an infection of the 
knee which includes cartilage, ligaments, tendons and bones.
    Response: We appreciate the commenters' support. We agree that 
osteomyelitis as a diagnostic term describes an infection which can 
include cartilage, ligaments, tendons and bones. However, as discussed 
in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19196), the diagnosis 
codes that are the subject of this proposal, including diagnosis code 
M86.9 (Osteomyelitis, unspecified) are not specific to the knee. There 
are other diagnosis codes in the subcategory M86.-series 
(Osteomyelitis) that are specific to the knee and will continue to be 
included in MS-DRGs 485, 486 and 487.
    Therefore, after consideration of the comments we received, we are 
finalizing our proposal to remove ICD-10-CM diagnosis codes M86.9, 
T84.50XA, T84.51XA, T84.52XA, T84.59XA, T84.60XA, T84.63XA, and 
T84.69XA from the list of principal diagnosis codes for MS-DRGs 485, 
486, and 487, and maintain their current assignment in MS-DRGs 559, 
560, and 561 in the ICD-10 MS-DRGs Version 37, effective October 1, 
2019.
    In addition, we stated in the proposed rule that 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.037

    As indicated in the proposed rule, 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, in the proposed rule 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 42095]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.038


[[Page 42096]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.039

BILLING CODE 4120-01-C
    We noted 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.040


[[Page 42097]]


    We stated that 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 proposed 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.
    Comment: Commenters agreed with CMS' proposal to add 10 additional 
ICD-10-CM diagnosis codes that are specific to the knee and describe an 
infection to the list of principal diagnosis codes for assignment to 
MS-DRGs 485, 486 and 487. The commenters stated that the proposal was 
reasonable, given the ICD-10-CM diagnosis codes and the information 
provided.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add ICD-10-CM diagnosis codes A18.02, 
M01.X61, M01.X62, M01.X69, M71.061, M71.062, M71.069, M71.161, M71.162, 
and M71.169 to the list of principal diagnosis codes for assignment to 
MS-DRGs 485, 486 and 487 in the ICD-10 MS-DRGs Version 37, effective 
October 1, 2019.
b. Neuromuscular Scoliosis
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19201 through 19202), 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). As we 
stated in the proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.041

    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. We stated in the proposed rule 
that, 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.
    As indicated in the proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.042

    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

[[Page 42098]]

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. We stated in the proposed rule that 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.043

    As we noted in the proposed rule, 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.'' We stated in the proposed rule that our 
clinical advisors agreed 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 in the proposed rule and 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. We stated that our 
clinical advisors agreed 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 proposed 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.
    Comment: Commenters agreed with CMS' proposal to add ICD-10-CM 
diagnosis codes M41.40, M41.44, M41.45, M41.46, and M41.47 that 
describe neuromuscular scoliosis to the list of principal diagnosis 
codes for assignment to MS-DRGs 456, 457 and 458 (Spinal Fusion except 
Cervical with Spinal Curvature of Malignancy or Infection or Extensive 
Fusions with MCC, with CC, and without CC/MCC, respectively). The 
commenters stated that the proposal was reasonable, given the ICD-10-CM 
diagnosis codes and the information provided. A commenter specifically 
expressed appreciation for CMS' display of cost and length of stay data 
in the analysis, in addition to the clinical factors that support our 
decision making.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add ICD-10-CM diagnosis codes M41.40, 
M41.44, M41.45, M41.46, and M41.47 to the list of principal diagnosis 
codes for assignment to MS-DRGs 456, 457 and 458 in the ICD-10 MS-DRGs 
Version 37, effective October 1, 2019.
c. Secondary Scoliosis and Secondary Kyphosis
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19202 through 19204), 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

[[Page 42099]]

Malignancy or Infection or Extensive Fusions with MCC, with CC, and 
without CC/MCC, respectively). As we indicated in the proposed rule, 
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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.044

    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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.045

    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 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.
    As indicated in the proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.046

    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.

[[Page 42100]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.047

    As we stated in the proposed rule, 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.
    We stated in the proposed rule that our clinical advisors agreed 
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 noted 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 proposed to add the following ICD-
10-CM diagnosis codes describing secondary scoliosis and 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.
    Comment: Commenters agreed with CMS' proposal to add ICD-10-CM 
diagnosis codes M40.10, M40.14, M40.15, M41.50, M41.54, M41.55, M41.56, 
and M41.57 that describe secondary scoliosis and secondary kyphosis to 
the list of principal diagnosis codes for assignment to MS-DRGs 456, 
457 and 458 (Spinal Fusion except Cervical with Spinal Curvature of 
Malignancy or Infection or Extensive Fusions with MCC, with CC, and 
without CC/MCC, respectively). The commenters stated that the proposal 
was reasonable, given the ICD-10-CM diagnosis codes and the information 
provided.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add ICD-10-CM diagnosis codes M40.10, 
M40.14, M40.15, M41.50, M41.54, M41.55, M41.56, and M41.57 that 
describe secondary scoliosis and secondary kyphosis to the list of 
principal diagnosis codes for assignment to MS-DRGs 456, 457 and 458 in 
the ICD-10 MS-DRGs Version 37, effective October 1, 2019.
    As also discussed in the proposed rule, during our review of MS-
DRGs 456, 457, and 458, we found the following diagnosis codes that 
describe conditions involving the cervical region.

[[Page 42101]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.048

    We stated that 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, in the FY 2020 IPPS/LTCH PPS proposed rule, we proposed 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.
    Comment: Commenters agreed with the proposal to remove 34 diagnosis 
codes that describe conditions involving the cervical region from the 
list of principal diagnosis codes for MS-DRGs 456, 457, and 458, to 
improve clinical homogeneity and better reflect resource costs since 
these MS-DRGs are defined by non-cervical spinal fusion procedures. The 
commenters stated that the proposal was reasonable, given the ICD-10-CM 
diagnosis codes and the information provided.
    Response: We appreciate the commenters' support. Therefore, we are 
finalizing our proposal to remove the ICD-10-CM diagnosis codes that 
describe conditions involving the cervical region as shown the table 
above from the list of principal diagnosis codes for MS-DRGs 456, 457, 
and 458 in the ICD-10 MS-DRGs Version 37, effective October 1, 2019.
7. MDC 11 (Diseases and Disorders of the Kidney and Urinary Tract): 
Extracorporeal Shock Wave Lithotripsy (ESWL)
    As discussed in the FY 2020 IPPS/LTCH PPS (84 FR 19204 through 
19210), 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.
    As noted in the proposed rule, 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).
    As stated in the proposed rule, 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.

[[Page 42102]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.049

    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 in the proposed rule and 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.
    We stated in the proposed rule that, 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. We noted that 
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 agreed 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, we stated that 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 noted in the proposed rule 
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. We stated that our clinical 
advisors agreed 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 we stated that 
they do not believe that this procedure is a valid indicator of 
resource consumption for cases that involve an infection and 
obstruction. We stated that 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 did 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.
    As also indicated in the proposed rule, 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.

[[Page 42103]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.050

    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 
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.
    As we stated in the proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.051

    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. We stated that 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

[[Page 42104]]

average length of stay for the cases reporting these conditions is 12.8 
days with average costs of $39,069, which we stated in the proposed 
rule 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.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR16AU19.052


[[Page 42105]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.053

BILLING CODE 4120-01-C
    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. We stated that 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 we stated 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 noted 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 believed contributed greatly overall to the longer length of 
stay and higher average costs for those secondary diagnosis CC 
conditions reported among the 24 cases.
    We stated that our clinical advisors agreed 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.
    As also indicated in the proposed rule, 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.

[[Page 42106]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.054

    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. We stated in the proposed 
rule that 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 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 stated in the proposed rule that 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.055

    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. We stated in the proposed rule that 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 we stated 
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.
    We stated in the proposed rule that 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.
    As indicated in the proposed rule, 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

[[Page 42107]]

data findings for all of the cases in their assigned MS-DRG.
    As discussed earlier in this section and the proposed rule, 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, as we stated in the proposed rule, 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 stated that we believe that the resource consumption is more 
likely the result of secondary diagnosis CC and/or MCC diagnosis codes.
    In the proposed rule, 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), we 
stated that 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 did not support adding ICD-10-CM diagnosis code 
T83.192A to the list of principal diagnosis codes for MS-DRGs 691 and 
692.
    As indicated in the proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.056

    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. We stated that 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. We stated that 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. We stated that 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 did not propose to add ICD-10-CM 
diagnosis code T83.192A to the list of principal diagnosis codes for 
MS-DRGs 691 and 692.
    Comment: Commenters supported CMS' proposal to not add ICD-10-CM 
diagnosis codes N13.6 and T83.192A to the list of principal diagnosis 
codes for MS-DRGs 691 and 692. Commenters commended CMS for conducting 
the analysis and continuing to make further refinements to the MS-DRGs. 
The commenters stated that the proposal was reasonable, given the ICD-
10-CM diagnosis codes and the information provided.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to not add ICD-10-CM diagnosis codes N13.6 and 
T83.192A to the list of principal diagnosis codes for MS-DRGs 691 and 
692 in the ICD-10 MS-DRGs Version 37, effective October 1, 2019.
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule, 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.
BILLING CODE 4120-01-P

[[Page 42108]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.057

    As noted in the proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.058


[[Page 42109]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.059


[[Page 42110]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.060

    We stated in the proposed rule that 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 noted 
in the proposed rule 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, we stated that 
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

[[Page 42111]]

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.

[[Page 42112]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.061

BILLING CODE 4120-01-C
    As indicated in the proposed rule, the data show a steady decline 
in the number of cases reporting urinary stones with an ESWL procedure 
for the

[[Page 42113]]

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 and in the proposed rule, an ESWL 
procedure is a non-O.R. procedure which currently groups to medical MS-
DRGs 691 and 692. Therefore, we stated in the proposed rule that 
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 proposed 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.
    Comment: Commenters supported the proposal 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''. Commenters agreed that 
deleting MS-DRGs 691 and 692 and revising the titles for MS-DRGs 693 
and 694 will better reflect utilization of resources for cases 
reporting urinary stones with a EWSL procedure as well as provide for 
appropriate payment for the procedures. The commenters noted that the 
proposal was reasonable, given the data, the ICD-10-PCS procedure 
codes, and information provided.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal 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'', in the ICD-10 MS-DRGs Version 37, 
effective October 1, 2019.
8. MDC 12 (Diseases and Disorders of the Male Reproductive System): 
Diagnostic Imaging of Male Anatomy
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19210 through 10211), we received a request to review four ICD-10-CM 
diagnosis codes describing 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.062

    The requestor recommended that the four diagnosis codes shown in 
this table 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.
    As indicated in the proposed rule, 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.
    We stated in the proposed rule that 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, we stated that our clinical advisors supported reassignment 
of these codes to MDC 12. Our clinical advisors agreed 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, we stated in the 
proposed rule that our clinical advisors suggested 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 proposed 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.
    Comment: Commenters supported our proposed reassignment of ICD-10-
CM diagnosis codes R93.811, R93.812, R93.813, and R93.819 from MDC 5 to 
MDC 12.
    Response: We thank the commenters for their support. After 
consideration of the public comments we received, we are finalizing our 
proposal 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): Reassignment of 
Diagnosis Code O99.89
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19211 through 19214), 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

[[Page 42114]]

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. As we stated in the proposed rule, 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).
    As noted in the proposed rule, 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. We 
stated that, 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), we explained in the proposed rule 
that 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, we stated in the proposed rule that the MS-DRG 
assignment for the example provided by the requestor is grouping 
accurately according to the current GROUPER logic.
    As indicated in the proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.063

    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. We stated in 
the proposed rule that 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 noted in the proposed rule that the description for ICD-10-CM 
diagnosis code O99.89 ``Other specified diseases and conditions 
complicating pregnancy, childbirth and the

[[Page 42115]]

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, we stated that 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. In the proposed rule, we stated that 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 in the proposed rule and 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, we 
stated in the proposed rule that 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.064

    These codes specifically identify at what stage the abnormal 
glucose was a complicating condition. We stated in the proposed rule 
that, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.065

    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

[[Page 42116]]

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 noted in the proposed rule 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 this 
table.
[GRAPHIC] [TIFF OMITTED] TR16AU19.066

    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.
    As we stated in the proposed rule, 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).
    Further, we stated that 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

[[Page 42117]]

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
     O99.895 (Other specified diseases and conditions 
complicating the puerperium).
    We noted in the proposed rule that, 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. We 
stated, 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.)
    We stated in the proposed rule that, 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 proposed to reclassify ICD-10-CM diagnosis code O99.89 
from a postpartum condition to an antepartum condition under MDC 14. We 
stated in the proposed rule that, 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.
    Comment: Commenters supported the proposal to reclassify ICD-10-CM 
diagnosis code O99.89 from a postpartum condition to an antepartum 
condition under MDC 14. Commenters also agreed with the recommendation 
to expand diagnosis code O99.89 to create a new 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.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to reclassify ICD-10-CM diagnosis code O99.89 
from a postpartum condition to an antepartum condition. For FY 2020, 
cases reporting diagnosis code O99.89 will follow the logic as 
previously 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 (Other Antepartum Diagnoses with 
O.R. Procedure with MCC, with CC and without CC/MCC, respectively). 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 (Other Antepartum Diagnoses 
without O.R. Procedure with MCC, with CC and without CC/MCC, 
respectively).
10. MDC 22 (Burns): Skin Graft to Perineum for Burn
    As discussed in the FY 2020 IPPS/LTCH PPS (84 FR 19214 through 
19215), 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.067


[[Page 42118]]


    As indicated in the proposed rule, 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, 
we stated in the proposed rule that 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, we stated that 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, 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.
    As noted in the proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.068

    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 stated that we found no cases reporting a skin graft to the 
perineum procedure in MS-DRG 747, 909, 957, 958, 959, or 987. Further, 
we stated that 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.

[[Page 42119]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.069

    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 noted in the proposed 
rule 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, we stated in 
the proposed rule that 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.
    We further stated that 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. We stated that 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 
did not propose to add the seven identified procedure codes to MS-DRGs 
927, 928, and 929 in the proposed rule.
    Comment: Commenters did not support the proposal to not add ICD-10-
PCS procedure codes 0HR9X73, 0HR9X74, 0HR9XJ3, 0HR9XJ4, 0HR9XJZ, 
0HR9XK3, and 0HR9XK4 that describe a skin graft to the perineum to MS-
DRGs 927, 928 and 929. The commenters noted that in the hypothetical 
scenario in which the principal diagnoses code T21.37XA, third degree 
burn of (female) perineum, or T21.36XA, third degree burn of the (male) 
perineum, is coded as the principal diagnosis in combination with ICD-
10-PCS codes describing skin graft to the perineum, the case would 
group to MS-DRG 934 (Full Thickness Burn without Skin Graft or 
Inhalation Injury). A commenter stated that since CMS' DRG tables are 
referenced nationally by other payers, the GROUPER logic should change 
in spite of the fact that CMS's data reflects little or no volume for 
these cases.
    Response: We appreciate the commenters' feedback.
    In response to public comments, our clinical advisors reviewed the 
claims data in the September 2018 update of the FY 2018 MedPAR file and 
again noted that none of the cases reporting the seven identified 
procedure codes that grouped to MS-DRGs 746, 907, 908, 988, and 989 had 
a principal or secondary diagnosis of a burn. Therefore, our clinical 
advisors continue to 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, in the absence of 
MedPAR data indicating that these skin grafts are performed to treat 
burns. Our clinical advisors believe 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. As additional claims data becomes 
available, we can determine if future modifications to the assignment 
of these procedure codes are warranted at a later date.
    Therefore, after consideration of the public comments we received, 
we are finalizing our proposal to maintain the current structure of MS-
DRGs 927, 928 and 929 for FY 2020.
11. MDC 23 (Factors Influencing Health Status and Other Contacts With 
Health Services): Assignment of Diagnosis Code R93.89
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19216), 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.
    As indicated in the proposed rule, 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.

[[Page 42120]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.070

    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.
    We stated in the proposed rule that 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 supported 
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, we stated in the proposed 
rule that our clinical advisors suggested reassignment of diagnosis 
code R89.93 to MS-DRGs 947 and 948 (Signs and Symptoms with and without 
MCC, respectively). Therefore, we proposed 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.
    Comment: Commenters supported our proposed reassignment of ICD-10-
CM diagnosis code R93.89 from MDC 5 to MDC 23.
    Response: We thank the commenters for their support. After 
consideration of the public comments we received, we are finalizing our 
proposal 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, in the 
FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19216 through 19224), we 
proposed 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
    As discussed in the proposed rule, 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. 
[GRAPHIC] [TIFF OMITTED] TR16AU19.071


[[Page 42121]]


    We stated in the proposed rule that 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. We stated in the proposed rule that 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''.
[GRAPHIC] [TIFF OMITTED] TR16AU19.072

    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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.073

    Of the MDCs to which these gastrointestinal excision procedures are 
currently assigned, we stated that 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.

[[Page 42122]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.074

    In the proposed rule, we stated that 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. Further, we stated that 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 proposed to 
move the GIST diagnosis codes listed above from MDC 8 to MDC 6 within 
MS-DRGs 326, 327, and 328. We stated that, under our proposal, cases 
reporting a principal diagnosis of GIST would group to MS-DRGs 326, 
327, and 328.
    We note that every diagnosis code is assigned to a medical MS-DRG 
to define the logic of the MS-DRG either as a principal or secondary 
diagnosis. We also note that, as discussed in section II.F.13.a., 
certain procedure codes may affect the MS-DRG and result in a surgical 
MS-DRG assignment. We are clarifying that under this proposal, cases 
reporting a principal diagnosis of GIST would group to MS-DRGs 326, 
327, and 328 only in the presence of a surgical procedure assigned to 
MS-DRGs 326, 327, and 328; in the absence of a surgical procedure, 
cases with a principal diagnosis of GIST would group to MS-DRGs 374, 
375, and 376 (Digestive Malignancy with MCC, with CC, and without CC/
MCC, respectively), which is the medical MS-DRG that contains digestive 
malignancies, and to which they would be assigned within MDC 6. We 
refer the reader to the ICD-10 MS-DRG Version 36 Definitions Manual for 
complete documentation of the logic for case assignment to surgical MS-
DRGs 326, 327, and 328 and to medical MS-DRGs 374, 375, and 376 (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).
    Comment: Several commenters supported our proposal. A commenter 
stated that placing the ICD-10-CM diagnosis codes describing GIST in 
the proposed DRGs would better reflect the gastrointestinal nature of 
the underlying GIST disease and the resource use associated with this 
subset of cases relative to others within the same MDC/DRG groupings.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to move the GIST diagnosis codes listed above 
from MDC 8 to MDC 6, with the additional clarification that in the 
absence of a surgical procedure, these cases are assigned to the 
medical MS-DRGs 374, 375 and 376 under the ICD-10 MS-DRGs Version 37, 
effective October 1, 2019. As a result, cases reporting a principal 
diagnosis of GIST and a procedure code that is assigned to MS-DRGs 326, 
327, and 328 (such as ICD-10-PCS codes 0DB60ZZ and 0DB80ZZ) will group 
to MS-DRGs 326, 327, and 328.
(2) Peritoneal Dialysis Catheter Complications
    As discussed in the proposed rule, during our review of the cases 
currently grouping to MS-DRGs 981-983, 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.

[[Page 42123]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.075

    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).
[GRAPHIC] [TIFF OMITTED] TR16AU19.076

    As indicated in the proposed rule, 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 noted in the proposed rule that we did 
not find any such cases in MS-DRG 983.
[GRAPHIC] [TIFF OMITTED] TR16AU19.077


[[Page 42124]]


    We stated that 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.078

    Further, we stated in the proposed rule that 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 
severity level in MS-DRGs 907. However, we further stated that 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 proposed 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. As indicated in the proposed rule, 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.
    Comment: Commenters supported our proposal 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.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal 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.
(3) Bone Excision With Pressure Ulcers
    As discussed in the proposed rule, 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. As noted in the 
proposed rule, the procedures describing excision of the sacrum, pelvic 
bones, and coccyx group to several MDCs, which are listed in the table 
below.
[GRAPHIC] [TIFF OMITTED] TR16AU19.079

    We stated in the proposed rule that, 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.

[[Page 42125]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.080

    As indicated in the proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.081

    We stated that 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, we stated in the 
proposed rule that 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 assigned to MDC 
9 that do not fit within the specific surgical MS-DRGs in MDC 9. 
Therefore, as indicated in the proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.082

    We stated that 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. We further 
stated that the smaller number of cases that group to MS-DRG 983 have 
lower average costs than cases in MS-DRG 581. However, we stated that 
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

[[Page 42126]]

sacrum, hip, and buttocks regions. Therefore, we stated in the proposed 
rule that 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 proposed 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. As noted in the proposed 
rule, 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.
    Comment: Commenters did not support our proposal 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. Commenters stated 
that it is not appropriate for procedures performed on muscles to be 
grouped to MS-DRGs for skin and subcutaneous tissues. A commenter 
stated that once a pressure ulcer extends into the muscle or bone, it 
is no longer a disease of the skin and subcutaneous tissue, but a 
disease of the musculoskeletal tissue.
    Response: We note that all pressure ulcers, including those that 
extend to the muscle or bone, are assigned to MDC 9, so that for 
purposes of DRG assignment, the GROUPER categorizes all pressure ulcers 
as diseases of the skin and subcutaneous tissue. As noted in the 
proposed rule, our clinical advisors believe that these procedures 
would be performed to treat pressure ulcers in the sacrum, hip, and 
buttocks regions. The surgical MS-DRGs within each MDC that include 
`other' procedures are intended to encompass procedures that, while not 
directly related to the MDC, can and do occur with principal diagnoses 
in that MDC with sufficient frequency.
    Comment: A commenter stated that they recognize that CMS may have 
selected MDC 9 as it includes all pressure ulcers, but recommended that 
CMS consider MDC 8 instead. A commenter stated that if the debridement 
is performed to the level of the soft tissue, then the case should 
group to MS-DRGs 501, 502, and 503 (Soft tissue procedures with MCC, 
with CC, and without CC/MCC respectively). The commenter stated that 
they believe it should be the procedure that determines the MDC and DRG 
to which the case groups.
    Response: As explained in the proposed rule, when conducting the 
review of procedures producing assignment to MS-DRGs 981 through 983 or 
MS-DRGs 987 through 989, the objective is to 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, or to move the principal 
diagnosis codes to the MDC in which the procedure falls. During this 
analysis, we noted that procedures describing excision of the sacrum, 
pelvic bones, and coccyx group to MS-DRGs 981 through 983 when reported 
with a principal diagnosis in MDC 9. If we were to add these procedures 
to MDC 8, that would not address the matter of these procedures 
producing assignment to MS-DRGs 981 through 983. Since our clinical 
advisors believe that these procedures are clearly related to the 
principal diagnoses assigned to MDC 9, our clinical advisors believe 
that it is appropriate to add these procedures to MDC 9. We also note 
that, with the exception of the pre-MDC, assignment to MDCs is driven 
by the principal diagnosis and not by the procedure. Therefore, it is 
inconsistent with GROUPER logic to determine the MDC based on the 
procedure.
    After consideration of the public comments we received, we are 
finalizing our proposal 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.
(4) Lower Extremity Muscle and Tendon Excision
    As discussed in the proposed rule, 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. As indicated in 
the proposed rule, these ICD-10-PCS procedure codes are listed in the 
table below, and are assigned to several MS-DRGs, which are also listed 
below.
[GRAPHIC] [TIFF OMITTED] TR16AU19.083


[[Page 42127]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.084

    As noted in the proposed rule, 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. We stated in the proposed rule that the 
combination indicates debridement procedures for more complex diabetic 
ulcers.
[GRAPHIC] [TIFF OMITTED] TR16AU19.085

    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, as 
indicated in the proposed rule, we examined claims data for the average 
length of stay and average costs for these cases. Our findings are 
shown in the table below.
[GRAPHIC] [TIFF OMITTED] TR16AU19.086

    We stated in the proposed rule that 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.

[[Page 42128]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.087

    As indicated in the proposed rule, 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 
proposed to add the procedure codes listed previously describing 
excision of lower extremity muscles and tendons to MDC 10. We stated in 
the proposed rule that, under our proposal, cases reporting these 
procedure codes with a principal diagnosis in MDC 10 would group to MS-
DRGs 622, 623, and 624.
    Comment: A commenter supported our proposal to add the procedure 
codes describing excision of lower extremity muscles and tendons to MDC 
10.
    Response: We appreciate the commenter's support.
    Comment: Other commenters did not support our proposal to add the 
procedure codes describing excision of lower extremity muscles and 
tendons to MDC 10. Commenters stated that muscle and tendon procedures 
are more resource intensive than skin procedures. A commenter stated 
that cases involving tendon excisions should group to MS-DRGs 501, 502, 
and 503 in MDC 8, and that cases involving excisions of muscle group to 
MS-DRGs 515, 516, and 517 in MDC 8. This commenter stated that the 
procedure should drive the MDC and DRGs to which the case is assigned.
    Response: Our clinical advisors believe that these procedures are 
clearly related to the principal diagnoses assigned to MDC 10 with 
which they are most frequently reported (that is, codes describing 
diabetes with complications), and are therefore appropriately assigned 
to MDC 10, and specifically to MS-DRGs 622, 623, and 624, which 
describe wound debridement. We also note that, with the exception of 
the pre-MDC, assignment to MDCs is driven by the principal diagnosis 
and not by the procedure. Therefore, it is inconsistent with the 
GROUPER logic to determine the MDC based on the procedure.
    After consideration of the public comments we received, we are 
finalizing our proposal to add the procedure codes listed previously 
describing excision of lower extremity muscles and tendons to MDC 10.
(5) Kidney Transplantation Procedures
    As discussed in the proposed rule, 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. We stated that 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. As 
indicated in the proposed rule, 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 stated in the proposed rule 
that we did not find any such cases in MS-DRG 983.
[GRAPHIC] [TIFF OMITTED] TR16AU19.088

    We further stated that 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-

[[Page 42129]]

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. As indicated in the proposed rule, we examined claims 
data to determine the average length of stay and 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 for this subset of 
cases in MS-DRG 981). We stated in the proposed rule that 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 
proposed to add ICD-10-PCS procedure codes 0TY00Z0 and 0TY10Z0 to MS-
DRG 264 in MDC 5. We stated in the proposed rule that, 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 also noted in the proposed rule that, because MDC 5 covers 
the circulatory system and kidney transplants generally group to MDC 
11, we invited public comments on whether the procedure codes should 
instead continue to group to MS-DRGs 981 through 983.
    Comment: Commenters opposed our proposal to add ICD-10-PCS 
procedure codes 0TY00Z0 and 0TY10Z0 to MS-DRG 264 in MDC 5. A commenter 
stated that the proposed relative weight for MS-DRG 652, where most 
kidney transplant procedures are grouped, is 3.384, while the proposed 
weight for MS-DRG 264 is 3.2357. Some commenters stated that this 
proposal would reduce the reimbursement for kidney transplantation of 
recipients with serious cardiac conditions by 33 percent. Commenters 
stated that cases that involve both chronic kidney disease and heart 
failure should not be paid less than cases that involve patients 
without serious comorbid conditions. Commenters suggested that CMS 
instead assign these cases to MDC 652, noting that the length of stay 
for the vast majority of kidney transplant cases involving serious 
cardiac conditions approximates the length of stay for kidney 
transplants in general. Commenters also stated that assigning all 
kidney transplant cases to the same MS-DRG simplifies collection of 
cost data, stating that when cases are split among several MS-DRG 
``families'' it complicates the analysis required to determine whether 
additional severity-based MS-DRGs would be appropriate. Commenters 
stated that if it was not possible to assign these cases to MS-DRG 652, 
then the cases should remain in MS-DRGs 981 through 983. Commenters 
disagreed with assigning these cases to a circulatory DRG because the 
procedure is performed on the urinary system.
    Response: We appreciate the comments and concerns raised on our 
proposal. Our clinical advisors generally believe that it is preferable 
to assign these cases to a discrete MS-DRG within the GROUPER rather 
than allowing them to continue to group to MS-DRGs 981 through 983, 
which do not contain a group of clinically coherent principal 
diagnoses, but instead consist of cases from various MDCs that are 
unrelated to one another. However, we believe it would be appropriate 
to take additional time to review the concerns raised by commenters 
consistent with the President's recent Executive Order on Advancing 
American Kidney Health (see https://www.whitehouse.gov/presidential-actions/executive-order-advancing-american-kidney-health/). Therefore, 
after consideration of public comments, we are not finalizing our 
proposal to add ICD-10-PCS procedure codes 0TY00Z0 and 0TY10Z0 to MS-
DRG 264 in MDC 5. Accordingly, cases reporting a principal diagnosis in 
MDC 5 with a procedure describing kidney transplantation (i.e., 
procedure code 0TY00Z0 or 0TY10Z0) will continue to group to MS-DRGs 
981 through 983 under the ICD-10 MS-DRGs Version 37, effective October 
1, 2019.
(6) Insertion of Feeding Device
    As discussed in the proposed rule, 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 stated in 
the proposed rule that 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.
    As indicated in the proposed rule, 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.

[[Page 42130]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.089

    In the proposed rule we stated that 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. We stated that 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.090

[GRAPHIC] [TIFF OMITTED] TR16AU19.091


[[Page 42131]]


    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. We stated in the proposed 
rule that 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. 
We stated that 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 proposed to add ICD-10-PCS procedure 
code 0DH60UZ to MDC 1 and MDC 10. We stated in the proposed rule that, 
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.
    Comment: Commenters supported our proposal to add ICD-10-PCS 
procedure code 0DH60UZ to MDC 1 and MDC 10.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add ICD-10-PCS procedure code 0DH60UZ to MDC 
1 and MDC 10.
(7) Basilic Vein Reposition in Chronic Kidney Disease
    As discussed in the proposed rule, 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. We stated in the proposed rule that 
this code combination suggests a revision of an arterio-venous fistula 
in a patient on chronic hemodialysis. As indicated in the proposed 
rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.092

    We stated in the proposed rule that 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.

[[Page 42132]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.093

    As indicated in the proposed rule, 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, we stated that 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, we stated in the proposed rule that 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 
proposed to add ICD-10-PCS procedures codes 05SB0ZZ, 05SB3ZZ, 05SC0ZZ, 
and 05SC3ZZ to MDC 11. We stated that, 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.
    Comment: Commenters supported our proposal to add ICD-10-PCS 
procedures codes 05SB0ZZ, 05SB3ZZ, 05SC0ZZ, and 05SC3ZZ to MDC 11.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add ICD-10-PCS procedures codes 05SB0ZZ, 
05SB3ZZ, 05SC0ZZ, and 05SC3ZZ to MDC 11.
(8) Colon Resection With Fistula
    As discussed in the proposed rule, 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. We stated that the principal diagnosis most frequently 
reported with ICD-10-PCS procedure code 0DTN0ZZ in MDC 11 is ICD-10-CM 
code N32.1 (Vesicointestinal fistula). As indicated in the proposed 
rule, ICD-10-PCS procedure code 0DTN0ZZ currently groups to several 
MDCs, which are listed in the table below.
[GRAPHIC] [TIFF OMITTED] TR16AU19.094

    As we stated in the proposed rule, 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.

[[Page 42133]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.095

    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 N32.1). We stated in the 
proposed rule that our clinical advisors observed that procedure code 
0DTN0ZZ is the second most common procedure reported in conjunction 
with a principal diagnosis of code N32.1, 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, we stated that 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 proposed to add ICD-10-PCS procedure code 
0DTN0ZZ to MDC 11. We stated in the proposed rule that, under our 
proposal, cases reporting procedure code 0DTN0ZZ with a principal 
diagnosis of vesicointestinal fistula (diagnosis code N32.1) in MDC 11 
would group to MS-DRGs 673, 674, and 675.
    Comment: Some commenters supported our proposal to add ICD-10-PCS 
procedure code 0DTN0ZZ to MDC 11.
    Response: We appreciate the commenters' support.
    Comment: A commenter opposed our proposal to add ICD-10-PCS 
procedure code 0DTN0ZZ to MDC 11 in MS-DRGs 673, 674, and 675 because 
these MS-DRGs does not account for the organ in which the disease 
originates. This commenter stated that the disease process that causes 
the formation of a vesicointestinal fistula generally do not originate 
in the bladder. This commenter recommended that CMS instead consider 
assigning ICD-10-PCS procedure code 0DTN0ZZ to MS-DRGs 329, 330, and 
331 (Major small and large bowel procedures with MCC, with CC, and 
without CC/MCC, respectively).
    Response: As we stated in the proposed rule, ICD-10-PCS procedure 
code 0DTN0ZZ is already assigned to MDC 6 in MS-DRGs 329, 330, and 331. 
As described above, when conducting the review of procedures producing 
assignment to MS-DRGs 981 through 983 or MS-DRGs 987 through 989, the 
objective is to 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, or to move the principal diagnosis codes to the MDC in which the 
procedure falls. During this analysis, we noted that ICD-10-PCS 
procedure code 0DTN0ZZ groups to MS-DRGs 981 through 983 when reported 
with a principal diagnosis in MDC 11. Given that the only way to 
address this grouping issue is to move or add the diagnosis code and 
procedure codes, in this case we proposed to add ICD-10-PCS procedure 
code 0DTN0ZZ to MDC 11. While the disease process that causes the 
formation of a vesicointestinal fistula may not originate in the 
bladder, our clinical advisors believe that when ICD-10-PCS procedure 
code 0DTN0ZZ is reported in conjunction with the vesicointestinal 
fistula, it is related to the diagnosis.
    After consideration of the public comments we received, we are 
finalizing our proposal to add ICD-10-PCS procedure code 0DTN0ZZ to MDC 
11.
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.
    Based on the results of our review of claims data in the September 
2018 update of the FY 2018 MedPAR file, we did not propose to change 
the current structure of MS-DRGs 981 through 983 and MS-DRGs 987 
through 989.
    We did not receive any public comments on our maintaining the 
current structure of MS-DRGs 981 through 983 and MS-DRGs 987 through 
989. Therefore, we are finalizing the

[[Page 42134]]

current structure of MS-DRGs 981 through 983 and MS-DRGs 987 through 
989 without modification.
c. Additions for Diagnosis and Procedure Codes to MDCs
    As we did in the FY 2020 IPPS/LTCH PPS proposed rule, 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.F.12.a. of the preamble of this final 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 proposed, and are 
finalizing, to add to MS-DRGs 579, 580, and 581 in MDC 5. (While the 
requestor only referred to base MS-DRG 579, in the proposed rule we 
stated that we believe it is appropriate to assign the cases to MS-DRGs 
579, 580, and 581 by severity level.) We stated that 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, in the proposed rule 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.096

    As indicated in the proposed rule and earlier, the requestor 
suggested that we move ICD-10-PCS procedure code 0KXP0ZZ to MS-DRG 579. 
However, we stated that 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, as indicated 
in the proposed rule, 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.

[[Page 42135]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.097

    We noted in the proposed rule 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 to MS-DRG 983. However, we stated in the proposed 
rule that 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, we stated 
that they believe that it is clinically appropriate for the procedures 
to group to the same MS-DRGs as the principal diagnoses. Therefore, we 
proposed to add ICD-10-PCS procedure codes 0KXP0ZZ and 0KXN0ZZ to MDC 
9. We stated in the proposed rule that, 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. We are 
clarifying that under our proposal, cases reporting ICD-10-PCS codes 
0KXP0ZZ or 0KXN0ZZ would also group to MS-DRGs 576, 577, and 578 in the 
absence of a principal diagnosis of skin ulcer or cellulitis. The 
reason for this additional assignment is that under the GROUPER logic, 
all of the procedures assigned to MS-DRGs 573, 574, and 575 are also 
assigned to MS-DRGs 576, 577, and 578; the presence or absence of a 
principal diagnosis of skin ulcer or cellulitis determines whether the 
case groups to MS-DRGs 573, 574, and 575 or to MS-DRGs 576, 577, and 
578. 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 573, 574, 575, 576, 577, and 578 (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).
    Comment: A commenter supported our proposal to add ICD-10-PCS 
procedure codes 0KXP0ZZ and 0KXN0ZZ to MDC 9.
    Response: We appreciate the commenter's support.
    Comment: Other commenters did not support our proposal to add ICD-
10-PCS procedure codes 0KXP0ZZ and 0KXN0ZZ to MDC 9. The commenters 
stated that it is not appropriate for procedures performed on muscles 
to group to MS-DRGs for skin and subcutaneous tissues. These commenters 
also stated that transfer procedures are more clinically significant 
and resource intensive than grafts to the skin and subcutaneous tissue.
    Response: Our clinical advisors agree that procedures performed on 
muscles would not generally be expected to group to MS-DRGs for skin 
and subcutaneous tissues. However, while they believe that principal 
diagnoses from MDC 9 would not be the principal diagnoses most often 
reported with ICD-10-PCS procedure codes 0KXP0ZZ and 0KXN0ZZ, the 
claims data indicate that there are cases reporting a principal 
diagnosis assigned to MDC 9, as identified by the requestor. Our 
clinical advisors continue to believe that these cases involving hip 
muscle transfer represent a distinct, recognizable clinical group, 
which is similar to those cases in MS-DRGs 573, 574, and 575, and that 
the procedures are clearly related to the principal diagnosis codes. 
With respect to the comment that transfer procedures are more 
clinically significant and resource intensive than grafts to the skin 
and subcutaneous tissue, our clinical advisors believe that the 
transfer procedures are sufficiently similar to procedures involving 
grafts to the skin and subcutaneous tissue, particularly given that a 
review of the data presented in the proposed rule and described 
previously in this section demonstrate that the average costs for MS-
DRGs 573, 574, and 575 are generally greater than those of the subset 
of cases involving hip muscle transfer with a diagnosis in MDC 9. Most 
of the cases that currently group to MS-DRGs 981 through 983 occur in 
MS-DRGs 981 and 982, which have average costs of $25,023 and $17,955 
respectively, while the MS-DRGs with the same severity level, MS-DRGs 
573 and 574, have average costs of $34,549 and $21,251, respectively. 
We also believe it is preferable to assign these cases to a discrete 
MS-DRG within the GROUPER logic rather than allowing them to continue 
to group to MS-DRGs 981 through 983, which do not contain a group of 
clinically coherent principal diagnoses. MS-DRGs 573, 574, 575, 576, 
577, and 578, which are specific to the care of conditions that 
necessitate skin grafts, represent a group of clinically coherent 
principal diagnoses to which procedures describing transfer of muscles 
are more appropriately assigned than those in MS-DRGs 981 through 983.
    After consideration of the public comments we received, we are 
finalizing our proposal to add ICD-10-PCS procedure codes 0KXP0ZZ and 
0KXN0ZZ to MDC 9.
(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.F.12.a. of 
the preamble of this final rule where we discuss our finalized policy 
to move the listed diagnosis

[[Page 42136]]

codes describing gastrointestinal stromal tumors, including ICD-10-CM 
diagnosis code C49.A2, into MDC 6. Therefore, in the proposed rule, we 
stated that 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.
    We did not receive comments on our proposal to address this 
grouping issue by moving the diagnosis codes to MDC 6 rather than 
moving the procedure codes as requested. We refer the reader to section 
II.F.12.a. of this final rule for the comments regarding our proposal 
to move the GIST diagnosis codes to MDC 6, as well as our finalization 
of this proposal.
(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). In the proposed 
rule, we stated that, 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. As we stated in the 
proposed rule, 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). We stated in the proposed rule that 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.098


[[Page 42137]]


    As noted in the previous discussion and the proposed rule, 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 also noted in the proposed 
rule 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.099

    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.F.12.A.3.of the preamble 
of this final rule.
    We stated in the proposed rule that 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, we stated that 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 proposed to add the procedure 
codes describing excision and resection of phalanx listed above to MS-
DRGs 579, 580, and 581. We stated that, 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.
    Comment: A commenter supported our proposal to add the procedure 
codes describing excision and resection of phalanx listed above to MS-
DRGs 579, 580, and 581 in MDC 9.
    Response: We appreciate the commenter's support.
    Comment: Other commenters did not support our proposal to add the 
procedure codes describing excision and resection of phalanx listed 
above to MS-DRGs 579, 580, and 581 in MDC 9. Commenters stated that it 
does not appear clinically appropriate for bone procedures to be 
grouped to skin and subcutaneous tissue MS-DRGs, and that the small 
number of cases suggests that this may be a coding issue.
    Response: We note that MS-DRGs 579, 580, and 581 already contain 
many bone-related procedures, such as those beginning with 0PD, which 
describe extraction of bone. In addition, our clinical advisors believe 
that 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.
    After consideration of the public comments we received, we are 
finalizing our proposal to add procedure codes describing excision and 
resection of phalanx listed above to MS-DRGs 579, 580, and 581 in MDC 
9.
(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 in tables 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 ICD-10-PCS tables 0SH and 0RH 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.
    We stated in the proposed rule that, while we understand the 
requestor's concern about these multiple significant trauma cases, we 
believe any potential reassignment of these cases requires significant 
analysis. We further stated that, 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

[[Page 42138]]

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 stated that 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 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.100

    We stated in the proposed rule that, while we agreed 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 further stated that 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). We stated in the proposed rule that ICD-10-CM 
diagnosis codes K95.01 (Infection due to gastric band procedure) and 
K95.09

[[Page 42139]]

(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 and in the proposed rule, 
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''.
    As indicated in the proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.101

    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.F.12.a. of the preamble of this final rule. We stated in the 
proposed rule that, 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 diagnoses. In 
addition, we stated that 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 proposed to add ICD-10-PCS procedure codes 0DW64CZ 
and 0DP64CZ to MDC 6 in MS-DRGs 326, 327, and 328. We stated in the 
proposed rule that, 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.
    Comment: Commenters supported our proposal to add ICD-10-PCS 
procedure codes 0DW64CZ and 0DP64CZ to MDC 6 in MS-DRGs 326, 327, and 
328.
    Response: We appreciate the commenters' support.
    After consideration of the public comments received, we are 
finalizing our proposal to add ICD-10-PCS procedure codes 0DW64CZ and 
0DP64CZ to MDC 6 in 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 
stated in the proposed rule that 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.F.12.a. of the preamble of the 
proposed rule, we proposed, and as discussed in this final rule, are 
finalizing, to add procedures

[[Page 42140]]

describing removal, revision, and/or insertion of peritoneal dialysis 
catheters to MS-DRGs 907, 908, and 909 in MDC 21. We refer readers to 
section II.F.12.a. of the preamble of this final rule in which we 
describe our analysis of this issue as part of our broader review of 
the unrelated MS-DRGs.
(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). We stated in the proposed rule that 
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 pelvic veins on the right side, such as the ovarian 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 right 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). We note that there 
was an inadvertent error in the proposed rule in which the term ``renal 
vein'' was referenced rather than ``pelvic veins on the right side'' or 
``ovarian vein''.
    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 and in the proposed rule, 
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.''
    As indicated in the proposed rule, 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, we indicated that our clinical 
advisors reviewed this request and agreed with the requestor that when 
the embolization procedure is performed on the left ovarian 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 ovarian vein. 
Therefore, we proposed 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. We stated in the proposed rule that, 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).
    Comment: A commenter stated that this issue should be reevaluated, 
because 06L03DZ is not the correct code to report procedures done on 
the right renal vein; rather, 06L93DZ (Occlusion of right renal vein 
with intraluminal device, percutaneous approach) would be reported 
instead.
    Response: We appreciate the commenter's request for clarification. 
We wish to clarify that certain specific pelvic veins do not have their 
own body part value in the ICD-10-PCS, and the ICD-10-PCS Body Part Key 
instructs coders to assign the inferior vena cava body part for veins 
such as the right ovarian vein and the right testicular vein, and to 
assign the left renal vein body part for veins such as the left ovarian 
vein and the left testicular vein. Therefore, ICD-10-PCS codes 06L03DZ 
or 06LB3DZ indeed may be reported to describe an embolization procedure 
performed for the treatment of pelvic varices of these respective 
sites. As such, our clinical advisors believe that when the 
embolization procedure is performed on veins classified to the left 
renal vein, such as the left ovarian vein and the left testicular vein, 
it should group to the same MS-DRGs as when it is performed on veins 
classified to the inferior vena cava, such as the right ovarian vein 
and the right testicular vein.
    After consideration of the public comments we received, we are 
finalizing our proposal 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.
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 (``O.R. procedures'') or is not designated

[[Page 42141]]

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 
final 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.
    In the FY 2020 IPPS/LTCH PPS proposed rule, we stated that, 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, as we stated in the proposed rule, 
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.
    We stated in the proposed rule that, 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 noted in the 
proposed rule, 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19231 through 
19235), we addressed 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 noted in the proposed rule 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 proposed to change the designation of 
procedure codes from non-O.R. procedures to O.R. procedures, we also 
proposed 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

[[Page 42142]]

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 determined if the procedure 
should affect the MS-DRG assignment.
    As indicated in the proposed rule, 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, as we did in the 
proposed rule, in this final rule, we detail and respond to some of 
those requests and, further, summarize and respond to the public 
comments we received in response to our proposals, if applicable. With 
regard to the remaining requests, as stated in the proposed rule, 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.
    In the proposed rule, we stated that we agreed with the requestors 
that these procedures do not typically require the resources of an 
operating room. Therefore, we proposed 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. We stated in the proposed rule that, 
under this proposal, these procedures would no longer impact MS-DRG 
assignment.
[GRAPHIC] [TIFF OMITTED] TR16AU19.102

    Comment: Some commenters supported our proposal to designate the 13 
procedure codes above as non-O.R. procedures.
    Response: We appreciate the commenters' support.
    Comment: Other commenters opposed our proposal to designate the 13 
procedure codes above as non-O.R. procedures. A commenter stated that 
due to the complexity of the procedures being performed, they should 
continue to be designated as an O.R. procedure, while another commenter 
stated that CMS should not reassign any procedures as O.R. or non-O.R. 
until it has completed its comprehensive review.
    Response: As indicated in the proposed rule, our clinical advisors 
believe that these procedures do not typically require the resources of 
an operating room. The commenter did not provide information to the 
contrary. We also do not agree with the commenter who stated that we 
should not reassign any procedures as O.R. or non-O.R; rather, while 
some requests may involve a broader review of additional ranges of ICD-
10-PCS codes, such that we believe they are more appropriately 
considered as part of our comprehensive review of procedure codes, we 
generally believe it is more accurate to address requests to change the 
designation of procedures as OR or non-OR as they arise rather than 
waiting for the comprehensive review, which is a multiyear project.
    After consideration of the public comments we received, we are 
finalizing our policy to designate the 13 codes above as non-O.R.
(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

[[Page 42143]]

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 stated in the proposed rule that we agreed with the requestor 
that these procedures do not typically require the resources of an 
operating room. Therefore, we proposed 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. We stated that, under this proposal, this 
procedure would no longer impact MS-DRG assignment.
    Comment: Commenters supported the proposal to change the 
designation of 0W9J3ZX to a non-O.R. procedure. The commenters stated 
that the proposal was reasonable, given the data and information 
provided.
    A commenter stated that CMS should not consider any requests to 
modify the designation of procedures as O.R. or non-O.R. for FY 2020. 
As stated in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19230), CMS 
plans to conduct a comprehensive systematic review of the ICD-10-PCS 
procedure codes. The commenter suggested that reassignment requests 
should be held until the review has been completed.
    Response: We appreciate the commenters' support. We do not agree 
with the commenter who stated that we should not reassign any 
procedures as O.R. or non-O.R; rather, while some requests may involve 
a broader review of additional ranges of ICD-10-PCS codes, such that we 
believe they are more appropriately considered as part of our 
comprehensive review of procedure codes, we generally believe it is 
more accurate to address requests to change the designation of 
procedures as OR or non-OR as they arise rather than waiting for the 
comprehensive review, which is a multiyear project. After consideration 
of the public comments we received, we are finalizing our proposal to 
change the designation of 0W9J3ZX from an O.R. procedure to non-O.R. 
procedure, effective October 1, 2019.
(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 stated in the proposed rule that we agreed with the requestor 
that these procedures do not typically require the resources of an 
operating room. Therefore, we proposed 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. We stated that, under this proposal, 
this procedure would no longer impact MS-DRG assignment.
    Comment: Commenters supported the proposal to change the 
designation of 0FPG30Z to a non-O.R. procedure. The commenters stated 
that the proposal was reasonable, given the data and information 
provided.
    A commenter stated that CMS should not consider any requests to 
modify the designation of procedures as O.R. or non-O.R. for FY 2020. 
As stated in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19230), CMS 
plans to conduct a comprehensive systematic review of the ICD-10-PCS 
procedure codes. The commenter suggested that reassignment requests 
should be held until the review has been completed.
    Response: We appreciate the commenters' support. We do not agree 
with the commenter who stated that we should not reassign any 
procedures as O.R. or non-O.R; rather, while some requests may involve 
a broader review of additional ranges of ICD-10-PCS codes, such that we 
believe they are more appropriately considered as part of our 
comprehensive review of procedure codes, we generally believe it is 
more accurate to address requests to change the designation of 
procedures as OR or non-OR as they arise rather than waiting for the 
comprehensive review, which is a multiyear project. After consideration 
of the public comments we received, we are finalizing our proposal to 
change the designation of 0FPG30Z from an O.R. procedure to a non-O.R. 
procedure, effective October 1, 2019.
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 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 stated in the proposed rule that we agreed with the requestor 
that ICD-10-PCS procedure code 04L23DZ typically requires the resources 
of an operating room. Therefore, we proposed 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,

[[Page 42144]]

CC, without CC/MCC, respectively) in MDC 24 (Multiple Significant 
Trauma).
    Comment: Commenters supported the proposal to change the 
designation of 04L23DZ from a non-O.R. to O.R. procedure. The 
commenters stated that the proposal was reasonable, given the data and 
information provided. A commenter noted that this change better 
reflects the resources required to perform the procedure and better 
aligns its designation with the designation of other procedures of 
similar technical difficulty.
    A commenter stated that CMS should not consider any requests to 
modify the designation of procedures as O.R. or non-O.R. for FY 2020. 
As stated in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19230), CMS 
plans to conduct a comprehensive systematic review of the ICD-10-PCS 
procedure codes. The commenter suggested that reassignment requests 
should be held until the review has been completed.
    Response: We appreciate the commenters' support. We do not agree 
with the commenter who stated that we should not reassign any 
procedures as O.R. or non-O.R; rather, while some requests may involve 
a broader review of additional ranges of ICD-10-PCS codes, such that we 
believe they are more appropriately considered as part of our 
comprehensive review of procedure codes, we generally believe it is 
more accurate to address requests to change the designation of 
procedures as OR or non-OR as they arise rather than waiting for the 
comprehensive review, which is a multiyear project. After consideration 
of the public comments we received, we are finalizing our proposal to 
change the designation of 04L23DZ from non-O.R. procedure to O.R. 
procedure, effective October 1, 2019.
(2) Endoscopic Insertion of Endobronchial Valves
    As noted in the FY 2020 IPPS/LTCH PPS proposed rule, 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.103

    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

[[Page 42145]]

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.
    As indicated in the FY 2020 IPPS/LTCH PPS proposed rule, we 
examined claims data from the September 2018 update of the FY 2018 
MedPAR file for MS-DRGs 163, 164 and 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. We 
stated that 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.104

    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). We further stated that 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

[[Page 42146]]

surgical MS-DRGs where cases reporting a respiratory diagnosis within 
MDC 4 would be assigned. Our findings are shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR16AU19.105

    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 indicated that 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. We stated in the proposed rule that 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 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.106


[[Page 42147]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.107

    We further stated in the proposed rule that 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 agreed 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. We stated that 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 final 
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, we stated that 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. We 
stated that 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, we stated in the proposed rule that, 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 and in the proposed rule, we did 
not propose 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, we stated that because we agreed that 
endoscopic insertion of an endobronchial valve procedures are performed 
on clinically complex patients, we believe it may be

[[Page 42148]]

appropriate to consider designating these procedures as non-O.R. 
affecting specific MS-DRGs for FY 2020. Therefore, we requested 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 of an endobronchial valve 
should affect for FY 2020. As we noted in the proposed rule, 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 solicited comment on whether cases reporting the 
endoscopic insertion of an endobronchial valve should affect any of 
these MS-DRGs or other MS-DRGs.
    Comment: Several commenters disagreed with our proposal to not 
designate the eight procedure codes describing endoscopic insertion of 
an endobronchial valve procedure as an O.R. procedure until additional 
analyses can be performed as part of the comprehensive procedure code 
review. Commenters urged CMS to include the eight procedure codes 
discussed above in the GROUPER logic for MS-DRGs 163, 164, and 165 
based on the analysis that was presented in the proposed rule effective 
FY 2020. A commenter noted that the analysis showed that cases in 
surgical MS-DRGs 163, 164, 165, 166 and 167 reporting the endoscopic 
insertion of an endobronchial valve had longer length of stays and 
higher average costs than other cases in those MS-DRGs. The commenter 
stated that the analysis showed that most cases in the medical MS-DRGs 
reporting the endoscopic insertion of an endobronchial valve had costs 
significantly higher than the relative weights of the medical DRGs. 
This commenter also stated that the skill level required for placement, 
anesthesia (even if performed outside the O.R.), and the severity level 
of the patient increase costs beyond that recognized within the medical 
MS-DRGs. The commenter further stated that because CMS's data supports 
a higher severity level, higher costs, and longer length of stays for 
patients who undergo endoscopic insertion of an endobronchial valve, 
they recommended reclassifying the eight procedure codes to O.R. status 
effective FY 2020, and grouping to MS-DRGs 163, 164 and 165 within MDC 
4, to MS-DRG 853 when sepsis is principal diagnosis, and to MS-DRGs 
981, 982, and 983 when there is an unrelated principal diagnosis. The 
commenter stated their belief that further delay of a relative weight 
increase for these procedures is not warranted nor supported. Another 
commenter commended CMS for soliciting comments on whether to consider 
any of the eight procedure codes describing the endoscopic insertion of 
an endobronchial valve procedure as non-O.R. impacting the MS-DRG 
assignment. This commenter recommended assigning all eight procedure 
codes identifying the endoscopic insertion of an endobronchial valve 
without another O.R. procedure to MS-DRGs 163, 164, and 165 for 
clinical coherence. According to the commenter, there are currently no 
medical MS-DRGs with clinically similar procedures or costs, therefore, 
assignment to MS-DRGs 163, 164 and 165 would ensure adequate payment to 
providers for these procedures. This commenter also stated that the 
costs associated with the endoscopic insertion of an endobronchial 
valve are a significant contributing factor to the higher average costs 
and length of stay in comparison to clinically similar cases that do 
not involve the endoscopic insertion of an endobronchial valve.
    Response: We appreciate the commenters' feedback on the designation 
of the eight procedure codes describing the endoscopic insertion of an 
endobronchial valve. We agree with the commenter that the analysis in 
the proposed rule showed 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. As noted 
above, we stated in the proposed rule that because the data are based 
on surgical MS-DRGs 163, 164, 165, 166 and 167, there was at least one 
other O.R. procedure reported on the claim resulting in case assignment 
to one of those MS-DRGs. We also acknowledge that the analysis in the 
proposed rule showed that most cases in the medical MS-DRGs reporting 
the endoscopic insertion of an endobronchial valve demonstrated costs 
higher than the relative weights of the medical DRGs. While our 
clinical advisors continue to believe it is unclear (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, they agree, as noted 
in the proposed rule, 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. Our clinical advisors also continue 
to believe that further refinement of surgical MS-DRGs 163, 164, 165, 
166 and 167 may be warranted because there are other procedure codes 
describing the insertion of endobronchial valve procedures by various 
approaches that are currently assigned to MS-DRGs 163, 164, and 165 and 
are designated as O.R. procedures, which our clinical advisors believe 
may require further analysis with respect to utilization of resources 
and designation as O.R. versus non-O.R. There are also other procedure 
codes currently assigned to MS-DRGs 163, 164 and 165 that describe 
procedures being performed on body parts other than those related to 
the chest. For example, we found codes describing laser interstitial 
thermal therapy (LITT) of several gastrointestinal body parts that do 
not appear to be clinically coherent. With regard to MS-DRGs 166 and 
167, our clinical advisors believe that these MS-DRGs may require 
further consideration for potential restructuring in connection with 
the ongoing evaluation of severity level designations and also as a 
result of the finalized policy (as discussed in section II.F.3. of the 
preamble of this final rule) regarding the deletion of several 
procedure codes that contain the qualifier ``bifurcation'' which are 
currently assigned to MS-DRGs 166 and 167 (as well as MS-DRG 168). For 
these reasons, our clinical advisors believe additional analysis of 
these surgical MS-DRGs is needed. In response to the commenter who 
suggested that cases reporting one of the eight procedure codes 
describing the endoscopic insertion of an endobronchial procedure 
should group to MS-DRG 853 (Infectious & Parasitic Diseases with O.R. 
Procedure with MCC) when sepsis is the principal diagnosis, and to MS-
DRGs 981, 982, and 983 when there is an unrelated principal diagnosis, 
we note that, as shown in the proposed rule and above, our analysis of 
the cases reporting the endoscopic insertion of an endobronchial valve 
in a medical MS-DRG did not result in any cases being found in MS-DRG 
853 and our clinical advisors do not agree with assignment of these 
procedures to that MS-DRG in the absence of further analysis. We also 
note that, because our clinical advisors continue to believe that 
endoscopic insertion of an endobronchial valve

[[Page 42149]]

should not be designated as an O.R. procedure, they do not support the 
recommendation for assignment to MS-DRGs 981, 982, and 983 as those MS-
DRGs are defined by procedures designated as extensive O.R. procedures. 
We refer the reader to section II.F.13.a. of the preamble in this final 
rule, for detailed information on how the designation of each ICD-10-
PCS procedure code on a claim impacts the MS-DRG assignment.
    In the proposed rule we stated that we agreed that endoscopic 
insertion of an endobronchial valve procedures are performed on 
clinically complex patients and that we believed it may be appropriate 
to consider designating these procedures as non-O.R. affecting specific 
MS DRGs for FY 2020. Our clinical advisors support the commenters' 
recommendation for the assignment of cases reporting the endoscopic 
insertion of an endobronchial valve to MS-DRGs 163, 164, and 165 under 
the current structure of the ICD-10 MS-DRGs for clinical coherence with 
the other insertion of endobronchial valve procedures currently 
assigned to those MS-DRGs and based on the data analysis. Our clinical 
advisors acknowledge that the data analysis presented in the proposed 
rule demonstrated 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, however, the average costs 
and length of stay for those cases are more aligned with MS-DRGs 163, 
164 and 165 than MS- DRGs 166, 167, and 168 or any other MS-DRGs within 
MDC 4 at this time. (As noted in the proposed rule, we did not find any 
cases reporting a procedure for the insertion of an endobronchial valve 
in MS-DRG 168).
    After consideration of the public comments we received and for the 
reasons described above, we are finalizing the designation of the eight 
procedure codes listed earlier in this section that describe the 
endoscopic insertion of an endobronchial valve as non-O.R. affecting 
MS-DRGs 163, 164 and 165 (Major Chest Procedures with MCC, with CC and 
without CC/MCC, respectively) under the ICD-10 MS-DRGs Version 37, 
effective October 1, 2019.
14. 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 stated in the 
proposed rule that we believe it is necessary to conduct a 
comprehensive analysis once again. We further stated that we had 
completed this analysis and we were discussing our findings in the 
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:
[GRAPHIC] [TIFF OMITTED] TR16AU19.108


[[Page 42150]]


    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:
[GRAPHIC] [TIFF OMITTED] TR16AU19.109

    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. Changes to Severity Levels
(1) General
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19235 through 19246), the diagnosis codes for which we proposed a 
change in severity level designation as a result of the analysis 
described in that proposed rule were shown in Table 6P.1c. associated 
with that 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). 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 the FY 
2020 IPPS/LTCH PPS proposed rule, the proposed changes to severity 
level resulting from our comprehensive analysis moved 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. We refer readers to the FY 2020 IPPS/
LTCH PPS proposed rule (84 FR 19235 through 19246) for a complete 
discussion of our proposals, including a summary of the proposed 
changes and illustrations of proposed severity level changes.
    We invited public comments on our proposed severity level 
designations for the diagnosis codes as shown in Table 6P.1c associated 
with the proposed rule. We received many comments on the proposals, 
with the majority of commenters requesting that the adoption of the 
proposed changes be delayed in order to provide additional time to 
evaluate given the broad scope of the proposed changes. As discussed in 
more detail below, after consideration of the public comments we 
received, we are generally not finalizing our proposed changes to the 
severity level designations for the ICD-10-CM diagnosis codes as shown 
in Table 6P.1c associated with the proposed rule, with the exception of 
the proposed changes to the codes related to antimicrobial resistance 
as discussed in greater detail below. Below we provide a summary of the 
comments we received and our response.
    Comment: Commenters expressed support for a limited number of the 
proposed changes in severity level, including the proposed change in 
severity level designation for diagnosis codes E83.39 (Other disorders 
of phosphorus metabolism), E83.51 (Hypocalcemia), R62.7 (Adult failure 
to thrive), R63.3 (Feeding difficulties), Z16.12 (Extended spectrum 
beta lactamase (ESBL) resistance), Z16.21 (Resistance to vancomycin), 
Z16.24 (Resistance to multiple antibiotics), and Z16.39 (Resistance to 
other specified antimicrobial drug) from a non-CC to a CC. Commenters 
stated their belief that these proposals were reasonable and reflect 
the resource utilization for these diagnoses.
    However, many commenters expressed concern with the proposed 
severity level designation changes overall and recommended CMS conduct 
further analysis prior to finalizing any proposals. Specifically, 
commenters expressed concern that the extensive changes proposed to the 
severity level designations for the ICD-10-CM diagnosis codes as shown 
in Table 6P.1c, the majority of which would be a lower severity level 
(for example, CC to a non-CC), would no longer appropriately reflect 
resource use for patient care and could have a significant unintended 
or improper adverse financial impact. In addition, some commenters 
believed there was not sufficient time to review the nearly 1,500 
diagnosis codes for which a change to the severity designation was 
proposed, noting that CMS engaged in its analysis for over a year 
before making any comprehensive proposals, and because there have been 
significant changes that have occurred to diagnosis codes since the 
transition to ICD-10-CM, in particular the exponential increase in the 
number of codes. Other general themes reflected in the comments 
included desire for more transparency and stakeholder

[[Page 42151]]

engagement, the belief that clinical severity was not consistently 
reflected in the proposed severity level designations, and concern 
regarding the impact on Medicaid and private payers, stating such 
payers often base their payment amount on Medicare.
    Some commenters stated that the information provided was not 
sufficient to adequately explain the proposed changes in severity level 
designations for certain diagnosis codes or families of codes. Other 
commenters were concerned that CMS' stated criteria were not met for 
some of the proposed changes to severity designations and specifically 
noted instances where diagnoses that appear to be clinically less 
severe (and therefore require less resources) were proposed to be 
assigned a higher severity level designation than other diagnoses that 
they believe require more resources. Another commenter recommended that 
any changes be phased in to allow time to assess the impacts such 
modifications would have on hospitals and patients.
    Response: We thank commenters for their comments on our proposed 
changes. After consideration of the public comments we received, and 
for the reasons discussed below, we agree it would be premature to 
adopt broad changes to the severity designations at this time. We agree 
with commenters that there have been significant changes to the scope 
and complexity of diagnosis codes since the transition to ICD-10-CM. We 
also believe that at this time it would be prudent to further examine 
the proposed severity designations to ensure they would appropriately 
reflect resource use based on review of the data as well as 
consideration of relevant clinical factors (for example, the clinical 
nature of each of the secondary diagnoses and the severity level of 
clinically similar diagnoses, as explained above) and improve the 
overall accuracy of the IPPS payments. Postponing the adoption of 
comprehensive changes in severity level designations will allow us to 
incorporate review of additional ICD-10 claims data as it becomes 
available and to fully consider the technical feedback provided from 
the public on the proposed rule. This would also allow further 
opportunity to provide additional background to the public on the 
methodology utilized and clinical rationale applied across diagnostic 
categories to assist the public in its review, such as making a test 
GROUPER publicly available to allow for impact testing. In addition, we 
can consider further whether it is appropriate to propose to make such 
comprehensive changes all at once or in phases, as suggested by some 
commenters.
    Furthermore, this will afford an opportunity for us to explore 
additional means of eliciting feedback on the current severity level 
designations after the final rule and prior to the November 1, 2019 
deadline for MS-DRG requests, comments and suggestions for FY 2021, 
such as holding an open door forum to solicit additional feedback. When 
providing additional feedback or comments, we encourage the public to 
provide a detailed explanation of why a specific severity level 
designation for a diagnosis code would ensure that designation 
appropriately reflects resource use. We also invite feedback regarding 
other possible ways we can approach the implementation of our proposed 
comprehensive changes to severity level designations, such as a phased-
in approach or changes by specific code categories or MDCs. In summary, 
for the reasons discussed above, we are generally not finalizing our 
proposed changes to the severity designations for the ICD-10-CM 
diagnosis codes as shown in Table 6P.1c associated with the proposed 
rule, other than the changes to the severity level designations for the 
diagnosis codes in category Z16- (Resistance to antimicrobial drugs) 
from a non-CC to a CC, as discussed in more detail below.
    Comment: As noted above, we received comments supporting our 
proposed change in severity level designation for diagnosis codes 
related to antimicrobial resistance (that is, Z16.12 (Extended spectrum 
beta lactamase (ESBL) resistance), Z16.21 (Resistance to vancomycin), 
Z16.24 (Resistance to multiple antibiotics), and Z16.39 (Resistance to 
other specified antimicrobial drug) from a non-CC to a CC. These 
commenters stated that they agree that patients with an ICD-10-CM 
secondary diagnosis code indicating that they were treated for an 
infection resistant to antibiotics should be, at a minimum, assigned a 
CC severity level designation. They asserted that the resources 
required to treat patients suffering from antimicrobial resistant 
infections should warrant a higher severity designation, and indicated 
that caring for patients with these complications is more resource 
intensive, including the need for stronger, different, or extra 
antibiotics. Commenters further indicated that the higher resources 
required to treat patients suffering from antimicrobial resistant 
infections are particularly relevant with respect to Medicare 
beneficiaries because they are vulnerable to drug-resistant infections 
due to greater exposure to resistant bacteria (e.g., via catheter 
infection or from other chronic diseases). These commenters expressed 
significant concerns related to the public health crisis represented by 
antimicrobial resistance and urged CMS to also apply the change in the 
severity level designation from non-CC to CC to the other ICD 10-CM 
diagnosis codes specifying antimicrobial drug resistance. A few of 
these commenters made recommendations for certain ICD-10-CM diagnosis 
codes that specify antimicrobial drug resistance either in addition to 
or in lieu of the codes included in our proposal. However, many of 
these commenters recommended that we also apply the change in the 
severity level designation from non-CC to CC to the other ICD-10-CM 
diagnosis codes specifying antimicrobial drug resistance (that is, the 
other diagnosis codes in category Z16-(Resistance to antimicrobial 
drugs).
    Response: We understand the concerns expressed by commenters 
related to the public health crisis that antimicrobial resistance 
represents. Addressing these concerns is consistent with the 
Administration's key priorities, and we have taken into consideration 
their statements that it clinically requires greater resources to treat 
patients suffering from antimicrobial resistant infections. For 
example, antimicrobial resistance results in a substantial number of 
additional hospital days for Medicare beneficiaries (estimated to be 
more than 600,000 additional days in the hospital each year), resulting 
in additional costs and resources to care for these patients.\1\ For 
these reasons, while we are continuing to examine the implementation of 
broader comprehensive changes to the CC/MCC designations, we believe it 
is appropriate to finalize the change in the severity level 
designations from non-CC to CC for the ICD-10-CM diagnosis codes 
specifying antimicrobial drug resistance. We also agree with the 
commenters that the change in severity level designation should also 
apply to the other ICD-10-CM diagnosis codes that specify antimicrobial 
drug resistance. We believe this would be consistent with our proposal 
because these codes, which identify the resistance and non-
responsiveness of a condition to antimicrobial drugs, are in the same 
family of codes (Z16) as the previously listed diagnosis codes related 
to antimicrobial resistance (that is, Z16.12, Z16.21, Z16.24, and 
Z16.39). Therefore, we are finalizing a change to the severity level 
designation for all of

[[Page 42152]]

the codes in category Z16- (Resistance to antimicrobial drugs), which 
are listed below, from a non-CC to a CC designation.
---------------------------------------------------------------------------

    \1\ Internal analysis from the Centers for Disease Control and 
Prevention.
[GRAPHIC] [TIFF OMITTED] TR16AU19.110

    (We refer readers to sections II.H.8. and II.H.9. of the preamble 
of this final rule for a discussion of new technology add-on payment 
policies related to antimicrobial resistance.)
d. Requested Changes to Severity Levels
    In the FY 2020 IPPS/LTCH PPS proposed rule (19246 through 19250) we 
discussed the external requests we received to make changes for the 
severity level designations of diagnosis codes in seven specific groups 
which included (1) Acute Right Heart Failure, (2) Chronic Right Heart 
Failure, (3) Ascites in Alcoholic Liver Disease and Toxic Liver 
Disease, (4) Factitious Disorder Imposed on Self, (5) Nonunion and 
Malunion of Physeal Metatarsal Fractures, (6) Other Encephalopathy, and 
(7) Obstetrics Chapter Codes. As these requests were external requests 
we discussed them separately from the comprehensive CC/MCC analysis, 
however, we utilized the same approach and methodology, consistent with 
our annual process of reviewing requested changes to severity levels. 
We note that, for the seven groups of external requests we received, we 
did not propose any changes to the severity levels of the diagnosis 
codes based on the results of our data analysis and the input of our 
clinical advisors, with the exception of group (7) Obstetrics Chapter 
Codes. We also note that we solicited comments on, but did not 
specifically propose changes for, the diagnosis codes discussed from 
group (1) Acute Right Heart Failure.
    Some commenters disagreed with our decision not to propose changes 
in the severity level designation for certain groups of codes, for 
example the acute right heart failure and ascites codes, and 
recommended that we finalize changes to the severity levels, stating 
that the resources required are similar to the existing codes. Other 
commenters specifically recommended that we postpone any decisions 
related to the obstetrics chapter codes and work with a panel of 
provider stakeholders. As we indicated in the proposed rule, given the 
limited number of cases reporting ICD-10-CM obstetrical codes in the 
Medicare claims data, we are considering 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.
    As discussed above, after consideration of the public comments 
received, we are generally not finalizing our proposed changes to the 
severity level designations for the ICD-10-CM diagnosis codes that were 
reviewed as part of the comprehensive CC/MCC analysis and shown in 
Table 6P.1c associated with the proposed rule. Similarly, we are not 
finalizing any proposed changes to the obstetric chapter diagnosis 
codes for FY 2020, to allow for further consideration of these codes as 
part of our comprehensive analysis as well as further consideration of 
the use of additional data sets for these particular codes, given the 
limited number of cases reported in the Medicare claims data. We are 
also finalizing our proposals to maintain the current severity level 
designations for the remaining six groups of diagnosis codes listed 
above for FY 2020. We will continue to consider the public comments 
received on the external requests for changes to severity level 
designations as we review and consider the public comments on our 
comprehensive CC/MCC analysis.
e. Additions and Deletions to the Diagnosis Code Severity Levels for FY 
2020
    The following tables identify the additions and deletions to the 
diagnosis code MCC severity levels list and the

[[Page 42153]]

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--Additions to the MCC List--FY 2020;
    Table 6I.2--Deletions to the MCC List--FY 2020;
    Table 6J.1--Additions to the CC List--FY 2020; and
    Table 6J.2--Deletions to the CC List--FY 2020.
f. 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.
    The ICD-10 MS-DRGs Version 36 CC Exclusion List is included as 
Appendix C in the ICD-10 MS-DRG 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, and includes two lists identified as 
Part 1 and Part 2. Part 1 is the list of all diagnosis codes that are 
defined as a CC or MCC when reported as a secondary diagnosis. If the 
code designated as a CC or MCC is allowed with all principal diagnoses, 
the phrase ``NoExcl'' (for no exclusions) follows the CC or MCC 
designation. For example, ICD-10-CM diagnosis code A17.83 (Tuberculous 
neuritis) has this ``NoExcl'' entry. For all other diagnosis codes on 
the list, a link is provided to a collection of diagnosis codes which, 
when used as the principal diagnosis, would cause the CC or MCC 
diagnosis to be considered as a non-CC. Part 2 is the list of diagnosis 
codes designated as a MCC only for patients discharged alive; 
otherwise, they are assigned as a non-CC. After publication of the 
proposed rule, we found inconsistencies in the assignment of this 
``NoExcl'' entry to the diagnoses designated as a CC or MCC. Generally, 
each CC or MCC diagnosis excludes itself from acting as a CC or MCC 
diagnosis, however, there are approximately 229 diagnosis codes we 
identified in Appendix C that have the phrase ``NoExcl'' and should 
instead contain a link to exclude themselves from acting as a CC or 
MCC. Therefore, we have corrected the list of diagnosis codes for the 
ICD-10 MS-DRG Definitions Manual Version 37, Appendix C--Complications 
or Comorbidities Exclusion List by providing a link to a collection of 
diagnosis codes which, when used as the principal diagnosis, will cause 
the CC or MCC to be considered as only a non-CC, for each of the 229 
diagnosis codes identified. We have also removed the sentence that 
states, ``If the CC or MCC is allowed with all principal diagnoses, 
then the phrase NoExcl follows the CC/MCC indicator'' as there are no 
longer any entries for which this phrase applies. We note that these 
corrections to Appendix C do not represent a change in MS-DRG 
assignment (or IPPS payment) and are being made to conform the appendix 
and tables to current policy. We also note these corrections are 
reflected for Table 6K.--Complete List of CC Exclusions--FY 2020.
    In the FY 2020 IPPS/LTCH PPS proposed rule, for FY 2020, we 
proposed changes to the ICD-10 MS-DRGs Version 37 CC Exclusion List. 
Therefore, we 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 the 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.
    The proposed CC Exclusions for a subset of the diagnosis codes as 
set forth in Tables 6G.1, 6G.2, 6H.1 and 6H.2 associated with the FY 
2020 IPPS/LTCH PPS proposed rule reflected the proposed severity level 
designations as discussed in section II.F.14.c.1. of the preamble of 
the proposed rule which were based on our comprehensive CC/MCC 
analysis. As discussed in section II.F.14.c.1. of the preamble of this 
final rule, we are not finalizing the proposed changes to the severity 
level designations after consideration of the public comments received 
(with the exception of the specified ICD-10-CM diagnosis codes in 
category Z16-Resistance to antimicrobial drugs). Therefore, the 
finalized CC Exclusions List as displayed in Tables 6G.1, 6G.2,

[[Page 42154]]

6H.1, 6H.2. and 6K. associated with this final rule reflect the 
severity levels under Version 36 of the ICD-10 MS-DRGs for a subset of 
the diagnosis codes.
15. 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 final rule.
    These tables are not published in the Addendum to the proposed rule 
or final 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 final rule. As discussed in section II.F.18. of the 
preamble of this final 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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19250) we 
proposed the MDC and MS-DRG assignments for the new diagnosis codes and 
procedure codes as set forth in Table 6A.--New Diagnosis Codes and 
Table 6B.--New Procedure Codes. We also stated that the proposed 
severity level designations for the new diagnosis codes were set forth 
in Table 6A. and the proposed O.R. status for the new procedure codes 
were set forth in Table 6B.
    Comment: A commenter expressed support for the proposed MS-DRG 
assignments under MDC 5 (Diseases and Disorders of the Circulatory 
System) for new procedure codes describing the insertion, removal, and 
revision of subcutaneous defibrillator leads via open and percutaneous 
approaches as reflected in Table 6B.--New Procedure Codes, that was 
associated with the proposed rule. However, the commenter stated it was 
not clear why MS-DRGs 040 (Peripheral, Cranial Nerve and Other Nervous 
System Procedures with MCC), 041 (Peripheral, Cranial Nerve and Other 
Nervous System Procedures with CC or Peripheral Neurostimulator), and 
042 (Peripheral, Cranial Nerve and Other Nervous System Procedures 
without CC/MCC) under MDC 1 (Diseases and Disorders of the Nervous 
System) were also proposed as MS-DRG assignments for the procedures 
describing removal and revision of subcutaneous defibrillator lead. The 
commenter requested that CMS provide information in the FY 2020 IPPS/
LTCH PPS final rule regarding those proposed MS-DRG assignments, 
including the diagnosis and procedure codes that would result in 
assignment to those MS-DRGs. The commenter provided the following table 
to display the proposed MS-DRG assignments as reflected in Table 6B- 
New Procedure Codes that was associated with the proposed rule.
[GRAPHIC] [TIFF OMITTED] TR16AU19.111

    Response: We thank the commenter for their support. With regard to 
why MS-DRGs 040, 041, and 042 under MDC 1 were also proposed as MS-DRG 
assignments for the procedures describing removal and revision of 
subcutaneous defibrillator lead, we note that, as described in section 
II.F.2.a. of the preamble of this final rule, 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. The predecessor 
procedure codes for the above listed removal and revision of 
subcutaneous defibrillator lead procedure codes are procedure codes 
0JPT0PZ (Removal of cardiac rhythm related device from trunk 
subcutaneous

[[Page 42155]]

tissue and fascia, open approach), 0JPT3PZ (Removal of cardiac rhythm 
related device from trunk subcutaneous tissue and fascia, percutaneous 
approach), 0JWT0PZ (Revision of cardiac rhythm related device in trunk 
subcutaneous tissue and fascia, open approach) and 0JWT3PZ (Revision of 
cardiac rhythm related device in trunk subcutaneous tissue and fascia, 
percutaneous approach) which are currently assigned to MS-DRGs 040, 
041, and 042 under MDC 1. We also note that, in each MDC there is 
usually a medical and a surgical class referred to as ``other medical 
diseases'' and ``other surgical procedures,'' respectively. The 
``other'' medical and surgical classes are not as precisely defined 
from a clinical perspective. The other classes would include diagnoses 
or procedures which were infrequently encountered or not well defined 
clinically. The ``other'' surgical category contains surgical 
procedures which, while infrequent, could still reasonably be expected 
to be performed for a patient in the particular MDC. Within MDC 1, MS-
DRGs 040, 041, and 042 are defined as a set of the ``other'' surgical 
classes as indicated in their MS-DRG titles with the ``Other Nervous 
System Procedures'' terminology. With regard to the diagnosis codes, we 
note that the diagnoses in each MDC correspond to a single organ system 
or etiology and in general are associated with a particular medical 
specialty. As such, the diagnoses assigned to MDC 1 correspond to the 
central nervous system. While we agree that it would be rare for a 
diagnosis related to a disease or disorder of the nervous system to be 
reported with a procedure that involves the removal or revision of a 
subcutaneous defibrillator lead, we note that, as discussed and 
displayed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41184), cases 
with procedure codes that identify the insertion of a cardiac rhythm 
related device (the predecessor code for insertion of subcutaneous 
defibrillator lead procedures) were previously assigned to MS-DRGs 040, 
041, and 042 and a small number of cases were found to be reported in 
those MS-DRGs, thus indicating that the combination of a diagnosis code 
from MDC 1 and one of the procedures describing the insertion of a 
cardiac rhythm related device did occur. While we did not specifically 
conduct analysis of claims data for the procedures describing a removal 
or revision of a cardiac rhythm related device, our clinical advisors 
continue to support assignment of the new procedure codes describing 
removal and revision of subcutaneous defibrillator lead procedures to 
MS-DRGs 040, 041, and 042 as reflected in Table 6B. New Procedure 
Codes, associated with this final rule.
    Additionally, as discussed in section II.F.2.a. of the preamble of 
this final rule, in our discussion of the annual process for assigning 
new procedure codes to MS-DRGs, a similar process is also utilized for 
assigning new diagnosis codes to MS-DRGs that involves review of the 
predecessor diagnosis code's MDC and MS-DRG assignment and severity 
level designation. However, this process does not automatically result 
in the new diagnosis code being assigned (or proposed for assignment) 
to the same severity level and/or MS-DRG and MDC as the predecessor 
code. There are several factors to consider during this process that 
our clinical advisors take into account.
    The proposed severity level designations for a subset of the new 
diagnosis codes as set forth in Table 6A associated with the FY 2020 
IPPS/LTCH PPS proposed rule reflected the proposed severity level 
designations as discussed in section II.F.14.c.1. of the preamble of 
the proposed rule which were based on our comprehensive CC/MCC 
analysis. For example, new diagnosis codes in the category L89- series 
describing pressure-induced deep tissue damage of various anatomical 
sites were proposed to be designated at a CC severity level. However, 
as discussed in section II.F.14.c.1. of the preamble of this final 
rule, we are not finalizing the proposed changes to the severity level 
designations based on our comprehensive CC/MCC analysis after 
consideration of the public comments received (with the exception of 
the specified ICD-10-CM diagnosis codes in category Z16-Resistance to 
antimicrobial drugs). Therefore, consistent with our annual process for 
assigning new diagnosis codes to MDCs and MS-DRGs and designating a new 
diagnosis code as an MCC, a CC or a non-CC, we reviewed the predecessor 
code MDC and MS-DRG assignments and the severity level designations for 
for these new codes and determined the appropriate severity level 
designation for these codes is the same severity level as the 
predecessor code under Version 36 of the ICD-10 MS-DRGs. The finalized 
severity level designations for these new diagnosis codes as set forth 
in Table 6A associated with this final rule therefore reflect the same 
severity level as the predecessor code under Version 36 of the ICD-10 
MS-DRGs.
    We also note that after publication of the proposed rule we 
identified procedures identified by procedure codes beginning with the 
prefix 0D1 describing bypass procedures of the small and large 
intestines in Table 6B.--New Procedure Codes that were inadvertently 
proposed for assignment to MS-DRGs 829 and 830 (Myeloproliferative 
Disorders Or Poorly Differentiated Neoplasms with Other Procedure with 
CC/MCC and without CC/MCC, respectively). Assignment of these 
procedures to MS-DRGs 829 and 830 is not applicable because the 
procedures would not result in assignment to these MS-DRGs due to the 
logic of the surgical hierarchy. Therefore, we have removed MS-DRGs 829 
and 830 from the list of MS-DRGs to which these bypass procedures of 
the small and large intestine are assigned for FY 2020 as reflected in 
Table 6B.--New Procedure Codes associated with this final rule.
    We are finalizing 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 finalized 
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 
the following tables associated with this final 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.--Secondary Diagnosis Order Additions to the CC 
Exclusions List-FY 2020;
     Table 6G.2.--Principal Diagnosis Order Additions to the CC 
Exclusions List-FY 2020;
     Table 6H.1.--Secondary Diagnosis Order Deletions to the CC 
Exclusions List-FY 2020;
     Table 6H.2.--Principal Diagnosis Order Deletions to the CC 
Exclusions List-FY 2020;
     Table 6I.--Complete MCC List-FY 2020;
     Table 6I.1.--Additions to the MCC List-FY 2020;
     Table 6I.2.-Deletions to the MCC List-FY 2020;
     Table 6J.--Complete CC List-FY 2020;
     Table 6J.1.--Additions to the CC List-FY 2020;

[[Page 42156]]

     Table 6J.2.--Deletions to the CC List-FY 2020; and
     Table 6K.--Complete List of CC Exclusions-FY 2020
16. 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.
    In the FY 2020 IPPS/LTCH PPS proposed rule, we addressed the MCE 
requests we received by the November 1, 2018 deadline. We also 
discussed the proposals we were making based on internal review and 
analysis. In this FY 2020 IPPS/LTCH PPS final rule, we present a 
summation of the comments we received in response to the MCE requests 
and proposals presented based on internal reviews and analyses in the 
proposed rule, our responses to those comments, and our finalized 
policies.
    In addition, as a result of new and modified code updates approved 
after the annual spring ICD-10 Coordination and Maintenance Committee 
meeting, we routinely make changes to the MCE. In the past, in both the 
IPPS proposed and final rules, we have only provided the list of 
changes to the MCE that were brought to our attention after the prior 
year's final rule. We historically have not listed the changes we have 
made to the MCE as a result of the new and modified codes approved 
after the annual spring ICD-10 Coordination and Maintenance Committee 
meeting. These changes are approved too late in the rulemaking schedule 
for inclusion in the proposed rule. Furthermore, although our MCE 
policies have been described in our proposed and final rules, we have 
not provided the detail of each new or modified diagnosis and procedure 
code edit in the final rule. However, we make available the finalized 
Definitions of Medicare Code Edits (MCE) file. Therefore, we are making 
available the FY 2020 ICD-10 MCE Version 37 Manual file, along with the 
link to the mainframe and computer software for the MCE Version 37 (and 
ICD-10 MS-DRGs), on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.html.
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 stated in the proposed rule that 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 agreed with the requestor that pregnancies can and do occur 
prior to the age of 12 and after the age of 55. We further stated in 
the proposed rule that we also agreed that the suggested range, age 9 
to age 64, is an appropriate age range. Therefore, we proposed to 
revise the maternity diagnoses category for the Age conflict edit to 
consider the new age range of 9 to 64 years inclusive.
    Comment: Commenters agreed with CMS' proposal to revise the 
maternity diagnoses category for the Age conflict edit by expanding the 
age range.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to revise the maternity diagnoses category for 
the Age conflict edit to consider the new age range of 9 to 64 years 
inclusive under the ICD-10 MCE Version 37, effective October 1, 2019.
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 final 
rule, Table 6A.--New Diagnosis Codes which is associated with this 
final 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. We stated in the proposed rule that 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 
proposed to add this diagnosis code to the Diagnoses for Females Only 
edit code list under the Sex conflict edit.
    Comment: Commenters agreed with the proposal to add diagnosis code 
N99.85 to the Diagnoses for Females Only edit code list under the Sex 
conflict edit.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add diagnosis code N99.85 (Post endometrial 
ablation syndrome) to the Diagnoses for Females Only edit code list 
under the Sex conflict edit under the ICD-10 MCE Version 37, effective 
October 1, 2019.

[[Page 42157]]

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.
    In the proposed rule we stated that 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 proposed 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 final 
rule, Table 6A.--New Diagnosis Codes associated with this final 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 codes that have 
been approved to date that will be effective with discharges occurring 
on and after October 1, 2019.
    As indicated in the proposed rule, we proposed 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.112

    Comment: Commenters agreed with our proposal to add diagnosis codes 
I46.2 and I46.8, as well as the new ICD-10-CM diagnosis codes listed in 
the table above, to the Unacceptable Principal Diagnosis Category edit 
code list.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add diagnosis codes I46.2 and I46.8 to the 
Unacceptable Principal Diagnosis Category edit code list. We are also 
finalizing our proposal to add the new ICD-10-CM diagnosis codes 
previously listed in the table to the Unacceptable Principal Diagnosis 
Category edit code list under the ICD-10 MCE Version 37, effective 
October 1, 2019.

[[Page 42158]]

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/DeterminationProcess/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 final 
rule, Table 6D.--Invalid Procedure Codes associated with this final 
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 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.113

    In the proposed rule, we proposed 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 
the 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 proposed 
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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.114

    Comment: Commenters agreed with our proposal to remove the ICD-10-
PCS procedure codes previously listed in the tables from the Non-
Covered Procedure edit code list.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to remove the ICD-10-PCS procedure codes 
previously listed in the tables that are no longer valid from the Non-
Covered Procedure edit code list within the ICD-10 MCE Version 37 
effective October 1, 2019. We note that the proposal involving ICD-10-
PCS procedure codes describing bone marrow transplant procedures was 
finalized after the March 5-6, 2019 ICD-10 Coordination and Maintenance 
Committee meeting, as reflected in Table 6D.--Invalid Procedure Codes 
associated with this final 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).
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

[[Page 42159]]

processing. As we indicated in the FY 2019 IPPS/LTCH PPS final rule (83 
FR 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. 
As noted in the FY 2020 IPPS/LTCH PPS proposed rule, 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 FY 2021 rulemaking.
17. 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 final 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 proposed to make in the FY 2020 IPPS/
LTCH PPS proposed rule, as discussed in section II.F.5.a. of the 
preamble of this final rule, in the proposed rule we proposed to revise 
the surgical hierarchy for MDC 5 (Diseases and Disorders of the 
Circulatory System) as follows: In MDC 5, we proposed 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 the preamble of this final 
rule, we proposed 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.115


[[Page 42160]]


    Comment: Commenters supported our proposal to sequence proposed new 
MS-DRGs 319 and 320 above MS-DRGs 222, 223, 224, 225, 226, and 227, and 
below MS- DRGs 266 and 267. However, a commenter proposed an alternate 
option upon reviewing Table 5.--List Of Medicare Severity Diagnosis-
Related Groups (MS-DRGs), Relative Weighting Factors, And Geometric And 
Arithmetic Mean Length Of Stay--FY 2020 associated with the proposed 
rule. The commenter noted that because multiple procedures may be 
performed during an encounter and MS-DRGs 215, 216, 217, 218, 219, 220, 
221, 222, 223, 224, 225, 226, 227, 228, 229, 231, 232, 233, 234, 235, 
and 236 (MS-DRG 230 was deleted effective FY 2017) are weighted higher 
than the proposed new MS-DRGs 319 and 320, sequencing proposed new MS-
DRGs 319 and 320 above MS-DRGs 239, 240, and 241 (Amputation for 
Circulatory System Disorders except Upper Limb & Toe with MCC, with CC, 
and without CC/MCC, respectively) and below MS-DRG 270, 271 and 272 
(Other Major Cardiovascular Procedures with MCC, with CC, and without 
CC/MCC, respectively) appeared more appropriate to result in the most 
resource intensive MS-DRG assignment when multiple cardiac procedures 
are performed.
    Response: We thank the commenters for their support. As discussed 
in section II.F.5.a. of the preamble of this final rule, we are 
finalizing our proposal to create new MS-DRGs 319 and 320. In response 
to the commenter's suggestion that we sequence new MS-DRGs 319 and 320 
above MS-DRGs 239, 240, and 241 and below MS-DRGs 270, 271 and 272, we 
reviewed the surgical hierarchy once again. Upon our review, we agree 
that the initial proposed sequencing did not adequately account for the 
most resource intensive MS-DRG assignment. However, our clinical 
advisors also did not completely agree with the suggested alternative 
option offered by the commenter and recommended that new MS-DRGs 319 
and 320 be sequenced above MS-DRGs 270, 271 and 272 and below MS-DRGs 
268 and 269 (Aortic and Heart Assist Procedures Except Pulsation 
Balloon with and without MCC, respectively) because they believe this 
sequencing more appropriately reflects resource utilization when 
multiple cardiac procedures are performed and will result in the most 
suitable MS-DRG assignment.
    After consideration of the public comments we received and the 
input of our clinical advisors, we are finalizing the below changes to 
the surgical hierarchy for new MS-DRGs 319 and 320 within Appendix D--
MS-DRG Surgical Hierarchy by MDC and MS-DRG of the ICD-10 MS-DRG 
Definitions Manual Version 37 as illustrated in the following table.
[GRAPHIC] [TIFF OMITTED] TR16AU19.116

    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

[[Page 42161]]

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 was 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 final 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 final 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 the 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: [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 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

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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. We indicated in the proposed rule that 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.
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    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. Changes for FY 2020
    As discussed in the FY 2020 IPPS/LTCH proposed rule (84 FR 19255 
through 19257), for FY 2020, we proposed 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 ``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

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Replacement and Supplement Procedures without MCC''.
    We noted in the proposed rule, 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 was proposed for assignment to proposed new 
MS-DRGs 319 and 320. Therefore, we proposed 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 proposed to continue 
to include the existing MS-DRGs currently subject to the policy as also 
displayed in the table below.
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    As discussed in section II.F.5.a. of the preamble of this final 
rule, we are finalizing our proposal to add new MS-DRGs 319 and 320. We 
did not receive any public comments opposing our proposal to add MS-
DRGs 319 and 320 to the policy for replaced devices offered without 
cost or with credit, make conforming changes to the titles of MS-DRGs 
266 and 267 as reflected in the table above or to continue to include 
the existing MS-DRGs currently subject to the policy. Therefore, we are 
finalizing the list of MS-DRGs in the table included in the proposed 
rule and above that will be subject to the replaced devices offered 
without cost or with a credit policy effective October 1, 2019.
    The final list of MS-DRGs subject to the IPPS policy for replaced 
devices offered without cost or with a credit will also be issued to 
providers in the form of a Change Request (CR).
20. Out of Scope Public Comments Received
    We received public comments regarding a number of MS-DRG and 
related issues that were outside the scope of the proposals included in 
the FY 2020 IPPS/LTCH PPS proposed rule.
    Because we consider these public comments to be outside the scope 
of the proposed rule, we are not addressing them in this final rule. As 
stated in section II.F.1.b. of the preamble of this final rule, we 
encourage individuals with comments about MS-DRG classification to 
submit these comments no later than November 1 of each year so that 
they can be considered for possible inclusion in the annual proposed 
rule. We will consider these public comments for possible proposals in 
future rulemaking as part of our annual review process.

G. Recalibration of the FY 2020 MS-DRG Relative Weights

1. Data Sources for Developing the Relative Weights
    In developing the FY 2020 system of weights, we proposed 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 final rule include 
discharges occurring on October 1, 2017, through September 30, 2018, 
based on bills received by CMS through March 31, 2019, 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 relative weights includes data 
for approximately 9,514,788 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 relative weights for FY 2020 
also excludes claims with claim type values not equal

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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 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 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 March 31, 
2018 update of the FY 2017 HCRIS for calculating the FY 2020 cost-based 
relative weights.
2. Methodology for Calculation of the Relative Weights
    As we explain in section II.E.2. of the preamble of this final 
rule, we calculated the FY 2020 relative weights based on 19 CCRs, as 
we did for FY 2019. The methodology we proposed 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 FY 2020 MS-DRG classifications discussed in sections II.B. 
and II.F. of the preamble of this final rule.
     The transplant cases that were used to establish the 
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 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).

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    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/. As noted in the proposed 
rule, 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 19 cost groups for each claim were 
standardized to remove the effects of differences in area wage levels, 
IME and DSH payments, and for hospitals located in Alaska and Hawaii, 
the applicable 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 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 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 national average CCRs developed from 
the FY 2017 cost report data.
    The 19 cost centers that we used in the 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 
19 national cost center CCRs. We stated in the proposed rule that, if 
stakeholders had comments about the groupings in this table, we may 
consider those comments as we finalize our policy. However, we did not 
receive any comments on the groupings in this table, and therefore, we 
are finalizing the groupings as proposed.
    We invited public comments on our proposals related to 
recalibration of the FY 2020 relative weights and the changes in 
relative weights from FY 2019.
    Comment: Several commenters expressed concern about significant 
reductions to the relative weight for MS-DRG 215. Commenters stated 
that the reduction in the proposed relative weight was 29 percent, 
which is the largest decrease of any MS-DRG; commenters also noted that 
the cumulative decrease to the relative weight for MS-DRG 215 would be 
43% since FY 2017. Commenters stated that the proposed relative weights 
would result in significant underpayments to facilities, which would in 
turn limit access to heart assist devices.
    Some commenters specifically referenced the Impella[supreg], one of 
the heart assist devices used to provide ventricular support. 
Commenters also stated that the proposed reduction in the relative 
weight resulted from several coding changes and a new FDA indication 
for the Impella[supreg], for the treatment of cardiomyopathy with 
cardiogenic shock. The commenters stated that these changes in coding 
guidance are still not reflected in claims for the FY 2020 proposed 
rule, and that 68% of claims for procedures utilizing the 
Impella[supreg] device did not have a charge for the Impella[supreg] in 
the Other Implants revenue center. Other commenters stated that 22% of 
claims did not have a charge for the device. Some commenters stated 
that they expect the future claims data to result in an increase to the 
relative weight for MS-DRG 215 for FY 2021.
    Commenters requested that CMS maintain the relative weight at the 
FY 2018 relative weight for any MS-DRG that was held harmless last year 
and continues to face a 20% or greater reduction from its FY 2018 
relative weight. Commenters stated that a hold harmless policy is 
consistent with prior rulemaking, in which CMS provided for transition 
periods for changes that have significant payment implications.
    Response: As we indicated in the FY 2018 IPPS/LTCH final rule (82 
FR 38103), and in response to similar comments in the FY 2019 IPPS/LTCH 
PPS final rule (83 FR 41273), we do not believe it is normally 
appropriate to address relative weight fluctuations that appear to be 
driven by changes in the underlying data. Nevertheless, after reviewing 
the comments received and the data used in our ratesetting 
calculations, we acknowledge an outlier circumstance where the weight 
for an MS-DRG is seeing a significant reduction for each of the 3 years 
since CMS began using the ICD-10 data in calculating the relative 
weights. While we would ordinarily consider this weight change to be 
appropriately driven by the underlying data, given the comments 
received and the potential for these declines to be associated with the 
implementation of ICD-10, we are adopting a temporary one-time measure 
for FY 2020 for an MS-DRG where the FY 2018 relative weight declined by 
20 percent from the FY 2017 relative weight and the FY 2020 relative 
weight would have declined by 20 percent or more from the FY 2019 
relative weight, which was maintained at the FY 2018 relative weight. 
Specifically, for an MS-DRG meeting this criterion, we will continue 
the current policy of maintaining the relative weight at the FY 2018 
level. In other words, the FY 2020 relative weight will be set equal to 
the FY 2019 relative weight, which was in turn set equal to the FY 2018 
relative weight.
    We believe this policy is consistent with our general authority to 
assign and update appropriate weighting factors under sections 
1886(d)(4)(B) and (C) of the Act. We also believe that it appropriately 
addresses the situation in which the reduction to the FY 2020 relative 
weights may potentially continue to be associated with the 
implementation of ICD-10. We continue to believe that changes in 
relative weights that are not of this outlier magnitude over the 3 
years since we first incorporated the ICD-10 data in our ratesetting 
are appropriately being driven by the underlying data and not 
associated with the implementation of ICD-10.
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3. Development of National Average CCRs
    We developed the 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 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

[[Page 42179]]

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 19 cost centers by the corresponding national average CCR, we 
summed the 19 ``costs'' across each MS-DRG to produce a total 
standardized cost for the MS-DRG. The average standardized cost for 
each MS-DRG was then computed as the total standardized cost for the 
MS-DRG divided by the transfer-adjusted case count for the MS-DRG. The 
average cost for each MS-DRG was then divided by the national average 
standardized cost per case to determine the relative weight.
    The FY 2020 cost-based relative weights were then normalized by an 
adjustment factor of 1.789031 so that the average case weight after 
recalibration was equal to the average case weight before 
recalibration. The 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 19 national average CCRs for FY 2020 are as follows:
    [GRAPHIC] [TIFF OMITTED] TR16AU19.131
    
    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 proposed to use that same case 
threshold in recalibrating the 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 proposed to compute relative weights 
for the 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.

[[Page 42180]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.132

    After consideration of the comments we received, we are finalizing 
our proposals, with the modification for recalibrating the relative 
weights for FY 2020 for an MS-DRG where the FY 2018 relative weight 
declined by 20 percent from the FY 2017 relative weight and the FY 2020 
relative weight would have declined by 20 percent or more from the FY 
2019 relative weight, which was maintained at the FY 2018 relative 
weight.

H. 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 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. In this final rule, 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

[[Page 42181]]

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 final 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 final rule, by 
clicking on the FY 2020 IPPS Final 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 final 
rule for a discussion of our final policy regarding an alternative 
inpatient new technology add-on payment pathway for transformative new 
devices. We also refer readers to section II.H.10. of the preamble of 
this final rule for a discussion of our final policy regarding an 
alternative inpatient new technology add-on payment pathway for certain 
antimicrobials.)
    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 final rule for a discussion of our final policy 
regarding the change to the calculation of the new technology add-on 
payment beginning in FY 2020, including our finalized 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 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

[[Page 42182]]

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].
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19274), we noted 
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, as applicable, 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 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 being revised based on the finalized policies discussed 
in this section of the final rule and 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 the 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.
    We stated in the FY 2020 IPPS/LTCH PPS proposed rule that 
approximately 100 individuals registered to attend the town hall 
meeting in person, while additional individuals listened over an open 
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 the

[[Page 42183]]

development of the 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 refer 
readers to section II.H.2. of the preamble of the FY 2020 IPPS/LTCH PPS 
proposed rule (84 FR 19275) for summaries of the comments we received 
in response to the published notice and the New Technology Town Hall 
meeting and our responses.) We also noted in the FY 2020 IPPS/LTCH PPS 
proposed rule 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 did not summarize those 
written comments in the proposed rule that are unrelated to the 
substantial clinical improvement criterion. In section II.H.5. of the 
preamble of the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19284 
through 19367), we summarized comments regarding individual 
applications, or, if applicable, indicated that there were no comments 
received in response to the New Technology Town Hall meeting notice or 
New Technology Town Hall meeting, at the end of each discussion of the 
individual applications.
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.
4. 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

[[Page 42184]]

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) would occur during FY 2019, in the FY 
2020 IPPS/LTCH PPS proposed rule (84 FR 19276), we proposed to 
discontinue new technology add-on payments for this technology for FY 
2020. We invited public comments on our proposal to discontinue new 
technology add-on payments for Defitelio[supreg] for FY 2020.
    Comment: A commenter supported CMS' proposal to discontinue new 
technology add-on payments for FY 2020 for Defitelio[supreg].
    Response: We appreciate the commenter's support. After 
consideration of the public comments we received, we are finalizing 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 are administered 260 mg of Stelara[supreg] (2 vials); 
patients weighing more than (>) 55 kg, but 85 kg or less than (<) 85 kg 
are administered 390 mg of Stelara[supreg] (3 vials); and patients 
weighing more 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, 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, in the FY 2020 IPPS/
LTCH PPS proposed rule (84 FR 19276 through 19277), we proposed to 
discontinue new technology add-on payments for this technology for FY 
2020. We invited public comments on our proposal to discontinue new 
technology add-on payments for Stelara[supreg] for FY 2020.
    Comment: A commenter supported CMS' proposal to discontinue new 
technology add-on payments for FY 2020 for Stelara[supreg].
    Response: We appreciate the commenter's support. After 
consideration of the public comments we received, we are finalizing 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,

[[Page 42185]]

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, in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19277), we 
proposed to discontinue new technology add-on payments for this 
technology for FY 2020. We invited public comments on our proposal to 
discontinue new technology add-on payments for ZINPLAVATM 
technology for FY 2020.
    Comment: A commenter supported CMS' proposal to discontinue new 
technology add-on payments for FY 2020 for ZINPLAVATM.
    Response: We appreciate the commenter's support. After 
consideration of the public comments we received, we are finalizing our 
proposal to discontinue new technology add-on payments for 
ZINPLAVATM for FY 2020.
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].

[[Page 42186]]

    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. As stated 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 for purposes 
of new technology add-on payments under the IPPS. As we noted in the FY 
2020 IPPS/LTCH PPS proposed rule, 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 for purposes of new technology add-on payments under the 
IPPS. In the proposed rule, similar to last year, we welcomed 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 previously stated, 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 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 
previously stated, 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, in 
the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19278 through 19279), we 
proposed to continue new technology add-on payments for KYMRIAH[supreg] 
and YESCARTA[supreg] for FY 2020. In addition, 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 the proposed rule (84 
FR 19373), we proposed 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, we stated 
that if we did not finalize the proposed change to the calculation of 
the new technology add-on payment amount, we were 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.
    For the reasons discussed in section II.F.2.c. of the proposed rule 
(84 FR 19180 through 19182), we proposed not to modify the current MS-
DRG assignment for cases reporting CAR T-cell therapies for FY 2020. 
Alternatively, we stated that we were seeking public comments on 
payment alternatives for CAR-T cell therapies. We also invited 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 solicited 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. In the proposed rule, we stated 
that 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 noted 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 requested 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

[[Page 42187]]

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 stated in the proposed rule that, 
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.
    We refer readers to section II.F.2.c. of this final rule for 
discussion of the comments we received in response to the proposals and 
solicitations for public comment above.
    After consideration of the public comments we received, we are 
finalizing our proposal to continue new technology add-on payments for 
KYMRIAH[supreg] and YESCARTA[supreg]. Under the revised calculation of 
the new technology add-on payment amount discussed in section II.H.9. 
of the preamble of this final rule, the maximum new technology add-on 
payment amount for a case involving the use of KYMRIAH[supreg] and 
YESCARTA[supreg] will be $242,450 for FY 2020; that is, 65 percent of 
the average cost of the technology. (As discussed in section II.H.9. of 
the preamble of this final rule, we are revising the maximum new 
technology add-on payment to 65 percent, or 75 percent for certain 
antimicrobial products, of the average cost of the technology.)
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, 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, in 
the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19279 through 19280), we 
proposed to continue new technology add-on payments for this technology 
for FY 2020. In addition, 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 the proposed rule (84 FR 19373), we proposed 
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, we stated that if we did not finalize the proposed change to 
the calculation of the new technology add-on payment amount, we were 
proposing that the maximum new technology add-on payment for a case 
involving VYXEOSTM would remain at $36,425 for FY 2020. We 
invited public comments on our proposals to continue new technology 
add-on payments for VYXEOSTM for FY 2020.
    Comment: A commenter supported CMS' proposal to continue new 
technology add-on payments for FY 2020 for VYXEOSTM.
    Response: We appreciate the commenter's support. After 
consideration of the public comments we received, we are finalizing our 
proposal to continue new technology add-on payments for 
VYXEOSTM for FY 2020. Under the revised calculation of the 
new technology add-on payment amount discussed in section II.H.9. of 
the preamble of this final rule, the maximum new technology add-on 
payment amount for a case involving the use of VYXEOSTM will 
be $47,352.50 for FY 2020; that is, 65 percent of the average cost of 
the technology. (As discussed in section II.H.9. of the preamble of 
this final rule, we are revising the maximum new technology add-on 
payment to 65

[[Page 42188]]

percent, or 75 percent for certain antimicrobial products, of the 
average cost of the technology.)
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, 
in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19280 through 19281), 
we proposed to continue new technology add-on payments for this 
technology for FY 2020. In addition, 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 the proposed rule (84 FR 19373), we 
proposed 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, we stated that if we did not finalize the proposed change to 
the calculation of the new technology add-on payment amount, we were 
proposing that the maximum new technology add-on payment for a case 
involving VABOMERETM would remain at $5,544 for FY 2020.
    As we previously noted in this rule and in the proposed rule, 
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 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 the FY 2020 IPPS final 
rule and available via the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html and then clicking on the link on the left 
titled ``FY 2022 IPPS Final Rule Home Page''. Therefore, we stated in 
the proposed rule that, 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 stated in the proposed rule that we are concerned that 
limiting new technology add-on payments only to cases reporting

[[Page 42189]]

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 proposed 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 proposed 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 invited 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.
    Comment: A commenter supported CMS' proposal to continue new 
technology add-on payments for FY 2020 for VABOMERETM. This 
commenter also supported CMS' proposal to identify cases involving the 
use of VABOMERETM that are eligible for new technology add-
on payments for FY 2020 using ICD-10-PCS codes XW033N5 or XW043N5 or 
NDCs 65293-0009-01 or 70842-0120-01.
    Response: We appreciate the commenter's support. After 
consideration of the public comments we received, we are finalizing our 
proposal to continue new technology add-on payments for 
VABOMERETM for FY 2020, as well as our proposal to identify 
cases involving the use of VABOMERETM that are eligible for 
new technology add-on payments for FY 2020 using ICD-10-PCS codes 
XW033N5 or XW043N5 or NDCs 65293-0009-01 or 70842-0120-01. Under the 
revised calculation of the new technology add-on payment amount 
discussed in section II.H.9. of the preamble of this final rule, the 
maximum new technology add-on payment amount for a case involving the 
use of VABOMERETM will be $8,316 for FY 2020; that is, 75 
percent of the average cost of the technology. (As discussed in section 
II.H.9. of the preamble of this final rule, we are revising the maximum 
new technology add-on payment to 65 percent, or 75 percent for certain 
antimicrobial products, of the average cost of the technology.)
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 (CSA). 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, in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19281), we proposed to continue new technology add-on payments for this 
technology for FY 2020. In addition, 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 the proposed rule (84 FR 19373), we 
proposed 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, we stated that if we did not finalize the proposed 
change to the calculation of the new technology add-on payment amount, 
we were 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 invited public comments on our proposals to continue 
new technology add-on payments for the remed[emacr][supreg] System for 
FY 2020.
    Comment: Several commenters supported CMS' proposal to continue new 
technology add-on payments for FY 2020 for the remed[emacr][supreg] 
System. A commenter, who was also the applicant, believed that the 
newness period for the remed[emacr][supreg] System should start on 
February 1, 2018 instead of the FDA approval date of October 6, 2017. 
The commenter stated that due to the required build out of operational 
and commercial capabilities, the remed[emacr][supreg] System was not 
commercially available upon FDA approval and the first case involving 
its use did not occur until February 1, 2018. The commenter asserted 
that the date of the first implant should mark the start of the newness 
period as before that the technology was not commercially available.
    Several commenters asserted that the descriptor of one of the ICD-
10-PCS procedure codes used to uniquely identify cases involving the 
use of the remed[emacr][supreg] System is incorrect. Per the 
commenters, CMS indicated in the proposed rule that 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

[[Page 42190]]

procedure 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). The commenters 
asserted that the descriptor of the code 05H03MZ was incorrectly stated 
in the proposed rule as involving the right innominate vein, whereas 
the correct body part for this code is the azygos vein.
    Furthermore, the commenters noted that the codes listed for the 
remed[emacr][supreg] System in the proposed rule do not match the 
advice that was published in the Fourth Quarter 2016 issue of Coding 
Clinic for ICD-10-CM/PCS regarding insertion of a phrenic 
neurostimulator. Per the commenters, the Coding Clinic advised 
assigning code 0JH60MZ for insertion of the stimulator generator into 
the chest subcutaneous tissue and fascia and code 05H032Z for the 
insertion of monitoring device into the azygos vein, plus the 
appropriate code for insertion of neurostimulator lead into either the 
left or right innominate vein. The commenters asserted that the device 
values for both the code for the stimulator generator and the code for 
the insertion of the lead in the azygos vein in the Coding Clinic 
advice were different than the ones indicated by CMS in the proposed 
rule. Commenters indicated that, according to Coding Clinic, for coding 
purposes, the sensing lead is designated as a monitoring device to 
differentiate between the sensing lead that monitors the respiratory 
activity and the electrode that delivers the electrical stimulation. 
The commenters requested that CMS revisit this topic and revise as 
applicable the stated codes to identify placement of the 
remed[emacr][supreg] System to be consistent with the advice published 
in Coding Clinic for ICD-10-CM/PCS. A commenter requested that CMS also 
make the appropriate retroactive payments consistent with the revised 
codes.
    Response: We appreciate the commenters' support. Regarding newness, 
we will consider the additional information the applicant provided when 
proposing whether to continue new technology add-on payments for the 
remed[emacr][supreg] System for FY 2021.
    Regarding codes, we acknowledge the error in our description of the 
ICD-10-PCS procedure code 05H03MZ in the Proposed Rule and agree with 
the commenters that the correct body part for this code is the azygos 
vein, not the innominate vein as stated in the Proposed Rule. We also 
acknowledge that the finalized codes used to identify cases involving 
the remed[emacr][supreg] System that are eligible for the add-on 
payment differ from those that were published in the Fourth Quarter 
2016 issue of Coding Clinic for ICD-10-CM/PCS regarding insertion of a 
phrenic neurostimulator. However, we believe that the finalized codes 
from the March 2018 Coordination & Maintenance Committee meeting 
supercede the Coding Clinic advice for the technology. Therefore, cases 
involving the remed[emacr][supreg] System that are eligible for the 
add-on payment will continue to be identified with the procedure codes 
0JH60DZ (Insertion of multiple array stimulator generator into chest 
subcutaneous tissue and fascia, open approach) and 05H03MZ (Insertion 
of neurostimulator lead into azygos vein, percutaneous approach) in 
combination with procedure code 05H33MZ (Insertion of neurostimulator 
lead into right innominate vein, percutaneous approach) or 05H43MZ 
(Insertion of neurostimulator lead into left innominate vein, 
percutaneous approach).
    After consideration of the public comments we received, we are 
finalizing our proposal to continue new technology add-on payments for 
the remed[emacr][supreg] System for FY 2020. Under the revised 
calculation of the new technology add-on payment amount discussed in 
section II.H.9. of the preamble of this final rule, the maximum new 
technology add-on payment amount for a case involving the use of the 
remed[emacr][supreg] System will be $22,425 for FY 2020; that is, 65 
percent of the average cost of the technology. (As discussed in section 
II.H.9. of the preamble of this final rule, we are revising the maximum 
new technology add-on payment to 65 percent, or 75 percent for certain 
antimicrobial products, of the average cost of the technology.)
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 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, in the FY 
2020 IPPS/LTCH PPS proposed rule (84 FR 19281 through 19282), we 
proposed to continue new technology add-on payments for this technology 
for FY 2020. In addition, 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 the proposed rule (84 FR 19373), we proposed 
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, we stated that if we did not finalize the proposed change to 
the calculation of the new technology add-on payment amount, we were 
proposing that the maximum new technology add-on payment for a case 
involving ZEMDRITM would remain at $2,722.50 for FY 2020.

[[Page 42191]]

We invited public comments on our proposals to continue new technology 
add-on payments for ZEMDRITM for FY 2020.
    Comment: A commenter supported CMS' proposal to continue new 
technology add-on payments for FY 2020 for ZEMDRITM.
    Response: We appreciate the commenter's support. After 
consideration of the public comments we received, we are finalizing our 
proposal to continue new technology add-on payments for 
ZEMDRITM for FY 2020. Under the revised calculation of the 
new technology add-on payment amount discussed in section II.H.9. of 
the preamble of this final rule, the maximum new technology add-on 
payment amount for a case involving the use of ZEMDRITM will 
be $4,083.75 for FY 2020; that is, 75 percent of the average cost of 
the technology. (As discussed in section II.H.9. of the preamble of 
this final rule, we are revising the maximum new technology add-on 
payment to 65 percent, or 75 percent for certain antimicrobial 
products, of the average cost of the technology.)
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, in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19282), we proposed to continue new technology add-on payments for this 
technology for FY 2020. In addition, under the proposed change to the 
calculation of the new technology add-on payment discussed in section 
II.H.9. of the preamble of the proposed rule (84 FR 19373), we proposed 
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, we 
stated that if we did not finalize the proposed change to the 
calculation of the new technology add-on payment amount, we were 
proposing that the maximum new technology add-on payment for a case 
involving GIAPREZATM would remain at $1,500 for FY 2020. We 
invited public comments on our proposals to continue new technology 
add-on payments for GIAPREZATM for FY 2020.
    Comment: A commenter supported CMS' proposal to continue new 
technology add-on payments for FY 2020 for GIAPREZATM.
    Response: We appreciate the commenter's support. After 
consideration of the public comments we received, we are finalizing our 
proposal to continue new technology add-on payments for 
GIAPREZATM for FY 2020. Under the revised calculation of the 
new technology add-on payment amount discussed in section II.H.9. of 
the preamble of this final rule, the maximum new technology add-on 
payment amount for a case involving the use of GIAPREZATM 
will be $4,083.75 for FY 2020; that is, 65 percent of the average cost 
of the technology. (As discussed in section II.H.9. of the preamble of 
this final rule, we are revising the maximum new technology add-on 
payment to 65 percent, or 75 percent for certain antimicrobial 
products, of the average cost of the technology.)
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

[[Page 42192]]

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, in the 
FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19282 through 19283), we 
proposed to continue new technology add-on payments for this technology 
for FY 2020. In addition, 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 the proposed rule (84 FR 19373), we proposed 
that the maximum new technology add-on payment amount for 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, we stated that if we did not finalize the 
proposed change to the calculation of the new technology add-on payment 
amount, we were 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 invited public comments 
on our proposals to continue new technology add-on payments for the 
Sentinel[supreg] Cerebral Protection System for FY 2020.
    Comment: Several commenters supported CMS' proposal to continue new 
technology add-on payments for FY 2020 for the Sentinel[supreg] 
Cerebral Protection System.
    Response: We appreciate the commenters' support. After 
consideration of the public comments we received, we are finalizing our 
proposal to continue new technology add-on payments for the 
Sentinel[supreg] Cerebral Protection System for FY 2020. Under the 
revised calculation of the new technology add-on payment amount 
discussed in section II.H.9. of the preamble of this final rule, the 
maximum new technology add-on payment amount for a case involving the 
use of the Sentinel[supreg] Cerebral Protection System will be $1,820 
for FY 2020; that is, 65 percent of the average cost of the technology. 
(As discussed in section II.H.9. of the preamble of this final rule, we 
are revising the maximum new technology add-on payment to 65 percent, 
or 75 percent for certain antimicrobial products, of the average cost 
of the technology.)
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. The applicant stated that, 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. Per the applicant, 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 
previously 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

[[Page 42193]]

in the FY 2006 IPPS final rule (70 FR 47349)). We stated in the FY 2019 
IPPS/LTCH PPS proposed rule that consistent with this response, and as 
indicated in the FY 2019 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. We 
stated in the FY 2020 IPPS/LTCH PPS proposed rule that, as we indicated 
in the FY 2019 IPPS/LTCH PPS final rule, we welcomed 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, in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19283), we 
proposed to continue new technology add-on payments for this technology 
for FY 2020. In addition, 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 the proposed rule (84 FR 19373), we proposed 
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, we 
stated that if we did not finalize the proposed change to the 
calculation of the new technology add-on payment amount, we were 
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 
invited public comments on our proposals to continue new technology 
add-on payments for the AQUABEAM System for FY 2020.
    Comment: A few commenters supported CMS' proposal to continue new 
technology add-on payments for the AQUABEAM System for FY 2020.
    Several commenters disagreed with CMS' belief that the newness 
period for the AQUABEAM System commenced on December 21, 2017, the day 
that FDA granted the De Novo request for the AQUABEAM System. These 
commenters, including the applicant, asserted that the American Medical 
Association assigned Aquablation therapy to a Category III CPT code 
prior to FDA clearance, and as a result Aquablation therapy was non-
covered by all Medicare Administrative Contractors prior to the date of 
FDA clearance through to the present day. Per the commenters, this is 
equivalent to a uniform, non-coverage policy for the entire nation. The 
commenters further stated that CMS has consistently recognized that the 
start of the newness period can occur months after FDA approval if 
there are delays in availability--including nationwide non-coverage--as 
indicated in the FY 2005 IPPS Final Rule, the FY 2006 IPPS Final Rule, 
and the CY 2016 OPPS Final Rule. The commenters asserted that based on 
longstanding rules and policy statements, the appropriate beginning of 
the newness period for the AQUABEAM System should be April 19, 2018, or 
the date of the first procedure in a commercially-insured patient.
    Response: We appreciate the commenters' support. With regard to 
newness, we note that Category III CPT codes are not recognized on 
inpatient claims. We continue to consider the beginning of the newness 
period for the AQUABEAM System to commence on December 21, 2017, or the 
date the FDA granted the applicant's De Novo request.
    After consideration of the public comments we received, we are 
finalizing our proposal to continue new technology add-on payments for 
the AQUABEAM System for FY 2020. Under the revised calculation of the 
new technology add-on payment amount discussed in section II.H.9. of 
the preamble of this final rule, the maximum new technology add-on 
payment amount for a case involving the use of the AQUABEAM System will 
be $1,625 for FY 2020; that is, 65 percent of the average cost of the 
technology. (As discussed in section II.H.9. of the preamble of this 
final rule, we are revising the maximum new technology add-on payment 
to 65 percent, or 75 percent for certain antimicrobial products, of the 
average cost of the technology.)
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 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, in the FY 2020 
IPPS/LTCH PPS proposed rule (84 FR 19283 through 19284), we proposed to 
continue new technology add-on payments for this technology for FY 
2020. In addition, 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 the proposed rule (84 FR 19373), we proposed 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, we stated 
that if we did not finalize the proposed change to the calculation of 
the new technology add-on payment amount, we were proposing that the 
maximum new technology add-on payment for a case involving 
AndexXaTM would remain at $14,062.50 for FY 2020. We invited 
public comments on our proposals to

[[Page 42194]]

continue new technology add-on payments for AndexXaTM for FY 
2020.
    Comment: A commenter supported CMS' proposal to continue new 
technology add-on payments for FY 2020 for AndexXaTM.
    Response: We appreciate the commenter's support. After 
consideration of the public comments we received, we are finalizing our 
proposal to continue new technology add-on payments for 
AndexXaTM for FY 2020. Under the revised calculation of the 
new technology add-on payment amount discussed in section II.H.9. of 
the preamble of this final rule, the maximum new technology add-on 
payment amount for a case involving the use of AndexXaTM 
will be $18,281.25 for FY 2020; that is, 65 percent of the average cost 
of the technology. (As discussed in section II.H.9. of the preamble of 
this final rule, we are revising the maximum new technology add-on 
payment to 65 percent, or 75 percent for certain antimicrobial 
products, of the average cost of the technology.)
5. 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 the proposed rule.
    Since the issuance of the FY 2020 IPPS/LTCH PPS proposed rule, 
three applicants, AbbVie Pharmaceuticals, Inc. (the applicant for 
VENCLEXTA[supreg]), Somahlution, Inc. (the applicant for 
DURAGRAFT[supreg]), and Nabriva Therapeutics U.S., Inc. (the applicant 
for CONTEPOTM), withdrew their applications. One applicant, 
Merck & Co., Inc (the applicant for Imipenem, Cilastatin, and 
Relebactam (IMI/REL) Injection), did not meet the deadline of July 1 
for FDA approval or clearance of the technology and, therefore, the 
technology is not eligible for consideration for new technology add-on 
payments for FY 2020. A discussion of the remaining 13 applications is 
presented in this final rule.
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 (PPGL). 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 PPGLs are rare tumors with an incidence 
of approximately 2 to 8 people per million per year.2 3 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.4 5 
Approximately one-half of malignant tumors are pronounced at diagnosis, 
while other malignant tumors develop slowly within 5 years.\6\ 
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.\7\ 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.\8\ The applicant stated that 
controlling catecholamine 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.
---------------------------------------------------------------------------

    \2\ Beard, C.M., Sheps, S.G., Kurland, L.T., Carney, J.A., Lie, 
J.T., ``Occurrence of pheochromocytoma in Rochester, Minnesota'', 
pp. 1950-1979.
    \3\ 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.
    \4\ Fishbein, Lauren, ``Pheochromocytoma and Paraganglioma,'' 
Hematology/Oncology Clinics 30, no. 1, 2016, pp. 135-150.
    \5\ 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).
    \6\ Kantorovich, Vitaly, and Karel Pacak. ``Pheochromocytoma and 
paraganglioma.'' Progress in Brain Research., 2010, vol. 182, pp. 
343-373.
    \7\ Carty, S.E., 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.
    \8\ 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 \9\ 
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

[[Page 42195]]

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.\10\
---------------------------------------------------------------------------

    \9\ 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.
    \10\ Carty, S.E., 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).\11\ According to the applicant, AZEDRA[supreg] is a 
more consistent form of \131\I-MIBG compared to compounded formulations 
of \131\I-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.\12\ However, the applicant 
stated that EBRT irradiated tissues are unresponsive to subsequent 
treatment with \131\I- MIBG radionuclide.\13\ 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 \131\I-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 \131\I-MIBG therapy based on having 
MIBG uptake with diagnostic imaging. According to the applicant, 
despite uptake by tumors, studies have also found that \131\I-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.\14\ 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.\15\
---------------------------------------------------------------------------

    \11\ Ibid.
    \12\ Ibid.
    \13\ 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.
    \14\ Loh, K.C., Fitzgerald, P.A., Matthay, K.K., Yeo, P.P., 
Price, D.C., ``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.
    \15\ 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.\16\ 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.17 18 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.\19\ According to the 
applicant, use of CVD relative to other tumor burden reduction options 
is not 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.\20\ 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.
---------------------------------------------------------------------------

    \16\ Carty, S.E., 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.
    \17\ 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.
    \18\ 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.
    \19\ 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.
    \20\ Carty, S.E., 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

[[Page 42196]]

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]. In the FY 2020 IPPS/
LTCH PPS proposed rule (84 FR 19286), we noted 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. The following 
ICD-10-PCS codes are now assigned for the use of AZEDRA[supreg]: 
XW033S5 (Introduction of Iobenguane I-131 Antineoplastic into 
Peripheral Vein, Percutaneous Approach, New Technology Group 5), and 
XW043S5 (Introduction of Iobenguane I-131 Antineoplastic into Central 
Vein, Percutaneous Approach, New Technology Group 5).
    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 stated in the proposed rule that we believed 
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 in this final rule, 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 invited public comments on whether AZEDRA[supreg] is 
substantially similar to other currently available therapies and/or 
technologies and meets the ``newness'' criterion.
    Comment: We received multiple comments in support of applicant's 
assertion that AZEDRA[supreg] is not substantially similar to other 
currently available therapies and/or technologies. A commenter 
described AZEDRA[supreg] as highly unique technology that is unlike any 
pre-existing treatment with a structure unlike any pre-existing 
treatment option given the use of the proprietary Ultratrace[supreg] 
technology, leading to increases in efficacy due to its unique 
``carrier-free'' structure with less non-radioactive drug to compete 
for uptake by tumors. Commenters mentioned that prior to 
AZEDRA[supreg]'s approval, there was no FDA-approved drug treatment for 
advanced pheochromocytomas and paragangliomas patients. Commenters 
asserted that compared to other off-label treatments, AZEDRA provides 
an important new option with substantial clinical improvement in terms 
of both safety and efficacy for patients with metastatic and/or 
recurrent and/or unresectable PPGL.
    Response: We thank commenters for their input. After consideration 
of the comments received, we agree that AZEDRA[supreg] utilizes a new 
mechanism of action from prior therapeutic uses of MIBG and therefore 
is not substantially

[[Page 42197]]

similar to an existing technology and meets the criteria for 
``newness.''
    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 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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19287), we stated 
that we were concerned with the limited number of cases the applicant 
analyzed. However, we acknowledged the difficulty in obtaining cost 
data for such a rare condition. We invited public comments on whether 
the AZEDRA[supreg] technology meets the cost criterion.
    Comment: The applicant submitted a comment in response to CMS's 
concern, stating that although the number of cases under each MS-DRG 
identified for its analysis included fewer than 11 total cases, the 
information provided a meaningful and workable data set based on the 
MedPAR files and is consistent with a product used to treat an ultra-
rare disease. Furthermore, the applicant stated that the cost 
information and analysis submitted with the application demonstrated 
that AZEDRA[supreg] will significantly exceed the relevant cost 
threshold for the MS-DRGs to which cases map, both in the aggregate 
(based on case-weighted threshold amounts), and for each individual MS-
DRG.
    Response: We appreciate the applicant's comment in response to our 
concerns. After consideration of the public comments we received, we 
believe that AZEDRA[supreg] 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; \21\ 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. In the proposed 
rule, we noted 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).
---------------------------------------------------------------------------

    \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.
---------------------------------------------------------------------------

    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. In the proposed 
rule, we stated that we understand that the applicant used 
antihypertensive medications as a

[[Page 42198]]

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, in the proposed rule, 
we stated that 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, in the proposed 
rule we noted that the IB12 study was a dose-escalating study and did 
not compare current therapies with the use of AZEDRA[supreg]. We also 
noted 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 agreed with the study's conductor \22\ 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.\23\ 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 
stated in the proposed rule that we were unclear which patients 
benefited from treatment involving AZEDRA[supreg], especially in view 
of the finding of a Fitzgerald, et al. study cited earlier \24\ 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 stated that 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.
---------------------------------------------------------------------------

    \22\ 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.
    \23\ Ibid.
    \24\ 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.\25\ 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. In the proposed rule, we 
stated that 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 (500mCi). We also noted that, regardless of total 
administered activity (for example, greater than or less than 18.5 GBq 
(500mCi)), 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 (500mCi) had 
progressive disease. Finally, we also stated that we noticed that, for 
most tumor biomarkers, there were no dose relationship trends. We 
stated that 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 had 
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.
---------------------------------------------------------------------------

    \25\ 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 stated in the proposed rule that we noted 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 noted 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.
    The applicant provided study data results from the IB12B study 
(MIP-IB12B), an open-label, prospective 5-year follow-up, single-arm, 
multi-center,

[[Page 42199]]

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 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. 
In the proposed rule, we stated that we noted 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 >=100 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.
    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.\26\ 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.
---------------------------------------------------------------------------

    \26\ 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. In the proposed rule, we stated that we 
noted 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 
noted 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. 
In the proposed rule, we stated that we agreed with the applicant 
regarding the difficulties in comparing the results of the published 
clinical studies, and also believed 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 stated that 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, in the proposed rule, we stated we were 
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. We stated that only very limited nonpublished data from two, 
single-arm, noncomparative studies were available to evaluate the 
safety and

[[Page 42200]]

effectiveness of AZEDRA[supreg], leading to a comparison of outcomes 
with historical controls.
    We invited 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 had raised, which 
included 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 PPGL tumors, and whether the 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.
    Comment: We received multiple comments in support of 
AZEDRA[supreg]'s meeting the substantial clinical improvement 
criterion. Commenters stated that the clinical data demonstrates 
important benefits and meaningful clinical improvements for patients 
compared to other treatments that may be unavailable to patients with 
advanced PPGL. Commenters stated that certain drug treatments have been 
used that are not specifically approved by FDA, such as certain 
chemotherapy regimens or low specific-activity iobenguane I-131, are 
not effective and frequently lead to serious and harmful side effects, 
including chemical toxicity and acute hypertensive crisis. Another 
commenter encouraged CMS to consider the very rare nature of advanced 
PPGL when considering the sizes of the clinical study patient 
populations and other aspects of the information relating to 
AZEDRA[supreg]'s application, particularly when a therapy is for an 
orphan condition and/or is the first and only FDA approved treatment 
option for the relevant patient population.
    The applicant also provided comments regarding substantial clinical 
improvement. The applicant highlighted AZEDRA[supreg]'s FDA 
``Breakthrough Therapy'', ``Fast Track'', ``Priority Review'', and 
``Orphan Drug'' designations to demonstrate the meaningful efficacy and 
safety criteria that a product must meet to obtain these statuses. The 
applicant also reiterated its contention that AZEDRA[supreg] represents 
a substantial clinical improvement over currently available treatments 
because it (1) offers a treatment option for a patient population that 
is unresponsive to or ineligible for currently available treatments for 
advanced disease and (2) significantly improves clinical outcomes 
compared to existing treatments for patients who have advanced PPGL and 
require systemic anticancer treatment. The applicant also responded to 
some specific issues raised by CMS in the proposed rule. The applicant 
pointed out that at one point, CMS incorrectly described the IB12B and 
IB12 as ``retrospective'' studies, when in fact they were prospective 
in nature. The applicant clarified that, consistent with prospectively 
designed clinical trials, the protocol for IB12B included pre-specified 
endpoints that were statistically powered to demonstrate clinical 
benefit for patients with advanced PPGL. These endpoints and 
statistical analyses were used to define the study's success criteria 
prior to collecting any subject data to prevent the possibility of 
bias. As such, Study IB12B was a prospective study, specifically 
designed to demonstrate that AZEDRA[supreg] offers a treatment option 
for a patient population that is unresponsive to or ineligible for 
currently available treatments. The applicant also provided background 
to support its claim that the number of patients enrolled in IB12B was 
statistically meaningful and noteworthy for a last-line therapy study 
for an ultra-rare disease state.
    In response to CMS's concern whether safety data from the IB12 
study could provide relevant clinical improvement data, the applicant 
stated that while the IB12 study was prospectively designed to assess 
the safety, dosimetry, and preliminary efficacy for AZEDRA[supreg] in 
patients with advanced PPGL, it included several secondary efficacy 
endpoints that provide preliminary data such as overall tumor response 
(RECIST), biochemical tumor response, and survival time. The applicant 
stated that the overall tumor response endpoints were included in FDA's 
consideration of AZEDRA[supreg]'s efficacy, although it was not 
included in the final AZEDRA[supreg] prescribing information.
    The applicant stated the primary endpoint of reduction in 
antihypertension medication was selected because a more traditional 
endpoint, such as overall survival, was not practical or possible given 
the nature of PPGL. The applicant stated: ``PPGL may progress slowly, 
and overall have a variable natural history, which makes the use of a 
traditional endpoint such as overall survival difficult and time-
consuming.'' According to the applicant, the endpoint was chosen to 
evaluate a key cause of morbidity in PPGL and thereby reflect direct 
clinical benefit.
    Response: We appreciate the additional information provided by the 
applicant, and the input from all commenters. After a review of the 
public comments we received, and upon review of all information 
provided by the applicant and review of the FDA Evaluation and Review 
of AZEDRA[supreg]'s NDA/BLA 209607 (https://www.accessdata.fda.gov/drugsatfda_docs/nda/2019/021200Orig1s015MultidisciplineR.pdf), we 
believe the technology offers a treatment option for the FDA indicated 
approved population for whom no other FDA approved treatment is 
available. Additionally, we note that, per the FDA's Multidisciplinary 
Evaluation and Review, use of the technology suggested a durable 
response in the reduction of hypertension as measured by the primary 
endpoint plus the confirmed overall tumor response measures of direct 
clinical benefit in this population of patients with serious, life 
threatening and rare disease (https://www.accessdata.fda.gov/drugsatfda_docs/nda/2019/021200Orig1s015MultidisciplineR.pdf pages 12, 
20). CMS also notes FDA's adverse events of cytopenias, sialoadenitis 
and renal failure in those who received two doses of 131I-MIBG, as well 
as the most common adverse reactions of Myelosuppression and 
Gastrointestinal related adverse events. CMS notes FDA's postmarketing 
requirement (PMR) for the applicant to fully characterize the risk of 
developing secondary malignancies (i.e., development of myelodysplastic 
syndrome, acute leukemia, and other secondary malignancies) in patients 
treated with \131\I-MIBG. Risk management will also include product 
labeling and routine pharmacovigilance to ensure the safe and effective 
use of \131\I-MIBG (https://www.accessdata.fda.gov/drugsatfda_docs/nda/2019/021200Orig1s015MultidisciplineR.pdf page 21). Also, CMS will 
monitor any additional data as it becomes available.
    In summary, we have determined that AZEDRA[supreg] meets all of the 
criteria for approval of new technology add-on payments, and we are 
approving new technology add-on payments for FY 2020.
    Cases involving AZEDRA[supreg] that are eligible for new technology 
add-on payments will be identified by ICD-10-PCS code XW033S5 and 
XW043S5. In its application, the applicant stated that the price of 
AZEDRA (Wholesale Acquisition Cost) is $302.00 per millicurie (mCi) 
prescribed. Most patients (i.e., those weighing 62.5 kg or more) 
receive a therapeutic dose of 500

[[Page 42201]]

mCi. Accordingly, the applicant estimated an average cost of $302/mCi 
times 500 mCi, or approximately $151,000. Therefore, according to the 
applicant, the cost of AZEDRA[supreg] is $151,000. Under Sec.  
412.88(a)(2) (revised as discussed in this final rule), we limit new 
technology add-on payments to the lesser of 65 percent of the average 
cost of the technology, or 65 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 AZEDRA[supreg] is $98,150 
for FY 2020.
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 
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.27 28 29 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.
---------------------------------------------------------------------------

    \27\ 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.
    \28\ 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.
    \29\ 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.30 31 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.32 33 34 35 36 37 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.\38\
---------------------------------------------------------------------------

    \30\ 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.
    \31\ George, J.N., ``Corticosteroids and rituximab as adjunctive 
treatments for thrombotic thrombocytopenic Purpura,'' Am. J. 
Hematol., 2012, vol. 87 Suppl 1, pp. S88-91.
    \32\ Form for Notification of a Compassionate Use Programme to 
the Paul-Ehrlich-Institut.
    \33\ 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.
    \34\ 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.
    \35\ Rajan, S.K., ``BMJ Best Practice; Thrombotic 
thrombocyopenic purpura,'' May 27, 2016.
    \36\ 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.
    \37\ 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.
    \38\ 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

[[Page 42202]]

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 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]. In the FY 2020 IPPS/LTCH PPS 
proposed rule (84 FR 19291), we noted 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. The applicant 
was granted approval for the following procedure codes: XW013W5 
(Introduction of Caplacizumab into Subcutaneous Tissue, Percutaneous 
Approach, New Technology Group 5), XW033W5 (Introduction of 
Caplacizumab into Peripheral Vein, Percutaneous Approach, New 
Technology Group 5) and XW043W5 (Introduction of Caplacizumab into 
Central Vein, Percutaneous Approach, New Technology Group 5).
    As previously discussed, 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 in this final rule 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,39 40 but their use is based on historical evidence 
that some patients with limited symptoms might respond to 
corticosteroids alone.41 42 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),

[[Page 42203]]

and even longer to restore ADAMTS13 activity levels.43 44
---------------------------------------------------------------------------

    \39\ 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.
    \40\ George, J.N., ``Corticosteroids and rituximab as adjunctive 
treatments for thrombotic thrombocytopenic Purpura,'' Am. J. 
Hematol., 2012, vol. 87 Suppl 1, pp. S88-91.
    \41\ 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.
    \42\ 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.
    \43\ Coppo, P., ``Management of thrombotic thrombocytopenic 
purpura,'' Transfus Clin Biol., Sep 2017, vol. 24(3), pp. 148-153.
    \44\ 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 previously summarized, the 
applicant believes that CABLIVI[supreg] provides a new treatment option 
for patients who have been diagnosed with aTTP. However, we stated in 
the proposed rule that 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. We stated that 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 invited public comments on whether CABLIVI[supreg] is 
substantially similar to other technologies and whether CABLIVI[supreg] 
meets the newness criterion.
    Comment: Several commenters stated that CABLIVI[supreg] is not 
substantially similar to other technologies and meets the newness 
criterion. Commenters stated that CABLIVI[supreg] is the only FDA 
approved therapy for aTTP and is a novel technological approach to the 
disease. Other commenters stated that CABLIVI[supreg] is a unique anti-
vWF blocking nanobody and the first of its kind in treating acute TTP 
that should be used at the earliest possible time after presentation of 
patients with immune-mediated TTP. The commenters stated that they 
believe CABLIVI[supreg] to be potentially lifesaving because no other 
treatment modalities act in this specific manner. A commenter stated 
that CABLIVI[supreg] differs from the treatments currently available 
for aTTP because it immediately prevents platelets from binding to the 
abnormally large vWF molecules, a key abnormality of TTP. A commenter 
stated that CABLIVI[supreg] is a nanobody that directly and 
specifically targets the pathophysiologic interaction between vWF and 
platelets, thus rapidly halting the life-threatening process that 
causes morbidity and mortality in those with aTTP. According to this 
commenter, no other drug is capable of doing this. Finally, this 
commenter stated that CABLIVI[supreg] is a novel therapy against a rare 
but potentially fatal autoimmune disease, aTTP that has not had 
significant short-term developments in almost 30 years.
    The applicant commented that CABLIVI[supreg] has been approved for 
the treatment of aTTP in a similar patient population as currently 
available treatment options. However the applicant also stated that 
CABLIVI[supreg] is a very different technology consisting of a 
different mode of action that results in improved outcomes with respect 
to platelet count response, recurrence, and other pre-specified 
clinical outcome endpoints. The applicant stated that CABLIVI[supreg] 
is the only FDA-approved therapy for treating aTTP in conjunction with 
PE and immunosuppressive therapy.
    The applicant also re-iterated information previously submitted 
with its application, and previously summarized in this final rule, 
that CABLIVI[supreg] is the only therapeutic agent that is designed to 
rapidly and specifically reduce the microthrombi formation via 
reduction in platelet aggregation for patients with an acute aTTP 
episode. According to the applicant, CABLIVI[supreg]'s novel mechanism 
of action works by targeting the A1 domain of vWF, thus preventing the 
interaction between vWF and platelets and thereby reducing the 
subsequent microvascular thrombosis. Regarding the current SOC, the 
applicant stated that as no randomized controlled prospective clinical 
studies have been performed to evaluate the efficacy and safety of the 
immunosuppressive therapies currently used to treat aTTP, the safe and 
effective dosing regimens of these agents are not known. The applicant 
further stated that while PE can provide rapid replenishment of new 
platelets and new ADAMTS 13 to reduce large platelet string formation, 
it is suboptimal in efficacy with a remaining mortality of up to 20 
percent and substantial patient burden and side effects.
    Response: We appreciate the commenters' input and the additional 
detail regarding whether CABLIVI[supreg] is substantially similar to 
existing technologies.
    After consideration of the public comments we received and 
information submitted by the applicant in its application, we believe 
that while 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, and 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 agree with the 
applicant that CABLIVI[supreg] does not use the same or similar 
mechanism of action as other technologies used for the treatment of 
aTTP. We believe that CABLIVI[supreg]'s mechanism of action, which 
targets the A1 domain of vWF, thus preventing the interaction between 
vWF and platelets and thereby reducing the subsequent microvascular 
thrombosis, is unique and distinct from other available forms of 
treatment for aTTP and, therefore, we believe that CABLIVI[supreg] 
meets the newness criterion. We consider the beginning of the newness 
period to commence when CABLIVI[supreg] was approved by the FDA on 
February 6, 2019.
    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:

[[Page 42204]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.133

    Using the 242 identified cases that mapped to the top 5 MS-DRGs 
previously described, the applicant determined that 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). (In the FY 2020 IPPS/LTCH PPS proposed rule, we noted 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 noted 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 invited public comments on 
whether CABLIVI[supreg] meets the cost criterion.
    Comment: The applicant submitted a revised analysis using the 2-
year inflation factor of 1.08986 from the FY 2019 IPPS correction 
notice to inflate charges from FY 2017 to FY 2019. The applicant also 
added charges to reflect the current wholesale acquisition cost (WAC) 
price for CABLIVI[supreg]. According to the applicant, after changing 
the 2-year inflation factor from 8.864 percent to 8.986 percent and 
adding charges for the new technology, the inflated average case-
weighted standardized charge per case was $413,246. Based on this 
analysis, the applicant determined that the inflated average case-
weighted standardized charge per case for CABLIVI[supreg] exceeded the 
threshold amount of $49,904 and that CABLIVI[supreg] meets the cost 
criterion.
    Response: We appreciate the applicant's input and revised analysis. 
After consideration of the public comments we received, we believe that 
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.\45\ 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.
---------------------------------------------------------------------------

    \45\ 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

[[Page 42205]]

relapses occurring within 10 days of 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.\46\ 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.
---------------------------------------------------------------------------

    \46\ 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 (p<0.0001).
    The applicant noted that the proportion of patients with a 
recurrence of an aTTP diagnosis in the Phase III study period (that is, 
the drug treatment period plus the 28-day follow-up after 
discontinuation of the drug treatment) was 67 percent lower in the 
CABLIVI[supreg] group (12.7 percent) compared to the placebo group 
(38.4 percent) (p<0.001). The applicant also indicated that in all 6 
patients in the CABLIVI[supreg] group who experienced a recurrence of 
an aTTP diagnosis during the follow-up period (that is, a relapse), 
ADAMTS13 activity levels were less than 10 percent at the end of the 
study drug treatment, indicating that the underlying immunological 
disease was still active at the time CABLIVI[supreg] was discontinued. 
Furthermore, the applicant stated that there were no patients who were 
treated with CABLIVI[supreg] that had refractory disease (defined as 
absence of platelet count doubling after 4 days of standard treatment 
and elevated LDH), compared to 3 patients (4.2 percent) who had 
refractory disease that were treated with placebo. The applicant also 
explained that a trend to faster normalization of the organ damage 
markers lactate dehydrogenase, cardiac troponin I and serum creatinine 
was observed in patients who were treated with CABLIVI[supreg]. The 
applicant noted that during the study drug treatment, there were no 
deaths in patients who were treated with CABLIVI[supreg], while 3 of 
the 73 placebo-treated patients (4.1 percent) died. Finally, the 
applicant stated that during the Phase III study drug treatment period, 
treatment with CABLIVI[supreg] resulted in a 38 percent reduction in 
the mean number of PE treatment days versus placebo (reduction of 3.6 
days) and a 41 percent reduction in the mean volume of PE (reduction of 
14.6L). Furthermore, treatment with CABLIVI[supreg] resulted in a 65 
percent reduction in the mean length of ICU stay (reduction of 6.3 
days) and a 31 percent reduction in the mean length of hospitalization 
(reduction of 4.5 days) during the Phase III study drug treatment 
period.
    The applicant submitted integrated data from the blinded periods of 
the Phase II and Phase III studies that show a statistically 
significant difference in favor of CABLIVI[supreg] (n=108) in time to 
platelet count response compared to placebo (n=112). The applicant 
indicated that patients who were treated with CABLIVI[supreg] were 1.65 
times more likely to achieve platelet count response at any given time 
point during the blinded period than patients who were treated with 
placebo (95 percent CI: 1.23, 2.20; p<0.001). Additionally, according 
to the applicant, integrated data from the blinded periods of the Phase 
II and Phase III studies showed that compared to placebo, treatment 
with CABLIVI[supreg] resulted in a 72.6 percent reduction in the 
percentage of patients with aTTP-related death, a recurrence of a aTTP 
diagnosis, or at least one treatment-emergent major thromboembolic 
event during the blinded treatment period (p<0.0001). More 
specifically, the applicant indicated that during the blinded treatment 
period no aTTP-related deaths occurred in the CABLIVI[supreg] group 
compared to 4 aTTP-related deaths in the placebo group (p<0.05), 
treatment with CABLIVI[supreg] resulted in an 84.0 percent reduction in 
the proportion of patients with a recurrence of a aTTP diagnosis 
(exacerbation, relapse) during the blinded treatment period (p<0.0001), 
and treatment with CABLIVI[supreg] resulted in a reduction of 40.8 
percent in the proportion of patients with at least one treatment-
emergent major thromboembolic event during the blinded treatment 
period.
    According to the applicant, pooled data from the two studies showed 
that none of the patients who were treated with CABLIVI[supreg] 
developed refractory disease (that is, absence of platelet

[[Page 42206]]

count doubling after 4 days of standard treatment and elevated LDH) 
compared to 7 patients (6.3 percent; 7/112) who were treated with 
placebo during the blinded period (p<0.01). Finally, the applicant 
noted that across both studies, treatment with CABLIVI[supreg] resulted 
in a 37.5 percent reduction in the mean number of days of PE treatment 
(reduction of 3.9 days).
    In the FY 2020 IPPS/LTCH PPS proposed rule, we stated that although 
the applicant asserts that CABLIVI[supreg] represents a substantial 
clinical improvement compared to the use of currently available 
treatments (PE and immunosuppressants), we were concerned that the 
Phase II TITAN and Phase III HERCULES studies may not provide enough 
evidence to support that the use of CABLIVI[supreg] represents a 
substantial clinical improvement.
    Regarding the Phase II TITAN study, we stated that we were 
concerned that because 66 of the 75 patients in the study population 
were white, the results of the study may not be generalizable to a more 
diverse population that may be at risk for diagnosis of aTTP. 
Additionally, we noted that CABLIVI[supreg] was associated with fewer 
aTTP exacerbations during therapy, but was associated with more aTTP 
exacerbations after therapy was discontinued, suggesting a lack of 
effect on long-term anti-ADAMTS13 antibody levels. Although this is 
consistent with CABLIVI[supreg]'s mechanism of action, we stated our 
concern in the proposed rule that without long-term data to determine 
the impact of adjunct use of CABLIVI[supreg] on exacerbations and 
relapse it may be difficult to determine if the use of CABLIVI[supreg] 
represents a substantial clinical improvement over existing therapy.
    Based on data from the Oklahoma TTP-HUS Registry, the incidence of 
aTTP is approximately three cases per 1 million adults per year.\47\ 
Additionally, the median age for a diagnosis of aTTP is 41, with a wide 
range between 9 years old and 78 years old. In the proposed rule, we 
acknowledged the challenges of constructing robust clinical studies due 
to the extremely rare occurrence of patients who have been diagnosed 
with aTTP. However, we stated that we were nonetheless concerned that 
the study population in the Phase III HERCULES study was small, 145 
people. Additionally, we indicated that it was unclear if the response 
rate may differ in those who have a de novo diagnosis versus those with 
recurrent disease. We noted that PE treatment alone has been attributed 
to an 80 percent survival rate,\48\ and because CABLIVI[supreg] is 
given in combination with or after SOC therapies, we stated in the 
proposed rule that we were concerned that we may not have sufficient 
information to determine the extent to which the study results were 
attributable to the use of CABLIVI[supreg]. Furthermore, we stated that 
with the follow-up period for the Phase III HERCULES study being only 
28 days, we were concerned that there is a lack of long-term data. We 
further stated that, in the absence of long-term data, we were 
concerned about the impact of the use of CABLIVI[supreg] on the relapse 
rate beyond the overall study period, including the 28-day follow-up 
period.
---------------------------------------------------------------------------

    \47\ Reese, J.A., Muthurajah, D.S., Kremer-Hovinga, J.A., 
Vesely, S.K., Terrell, D.R., George, J.N., ``Children and adults 
with thrombotic thrombocytopenic purpura associated with severe, 
acquired Adamts13 deficiency: comparison of incidence, demographic 
and clinical features,'' Pediatr Blood Cancer, October 2013, vol. 
60(10), pp. 1676-82, Epub June 1, 2013.
    \48\ 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.
---------------------------------------------------------------------------

    Finally, although both the Phase II and III studies consisted of 
key secondary endpoints such as death or major thromboembolic events, 
in the proposed rule we indicated that we were concerned these 
endpoints were not clearly defined. We also stated that we were 
concerned the studies did not appear to account for other clearly 
defined endpoints such as heart attack, stroke, a bleeding episode, and 
power calculations for the expected differences in such endpoints that 
would be biologically important.
    We invited public comments on whether CABLIVI[supreg] meets the 
substantial clinical improvement criterion.
    Comment: Several commenters provided comments in support of 
CABLIVI[supreg]. A commenter stated that CABLIVI[supreg] utilizes a 
monoclonal antibody that binds to vWF, causing platelets to clump and 
clog up the microcirculation of patients and thereby reducing the 
number of plasma exchanges required to bring patients back to normal 
platelet counts. The commenter stated that the clinical benefit of 
reducing the amount of plasma exchanges include lowering the amount of 
plasma required to maintain the blood bank's supply, lessening the 
chance of TRALI, reducing time spent in the intensive care unit, 
reducing time in hospitalization, replacing many hours of expensive 
plasma exchange in the inpatient and outpatient settings with a 
subcutaneous injection, and tremendous increase in patient satisfaction 
in their overall care.
    A commenter stated that CABLIVI[supreg] has the potential to save 
the lives of those individuals who do not respond to current 
conventional treatment, plasma exchange, corticosteroids, and 
rituximab. The commenter stated that without bound platelets, the 
thrombosis is prevented. Finally, the commenter stated that 
CABLIVI[supreg] blocks the tissue injury, but corticosteroids, 
rituximab, and plasma exchange are still needed to affect the cause of 
the disease.
    Another commenter stated that with the pathophysiology of aTTP 
rapidly and durably crippled as long as CABLIVI[supreg] is 
administered, immunosuppression and other therapies such as plasma 
exchange can be provided to these patients to help obtain a prolonged 
remission after cessation of CABLIVI[supreg]. The commenter stated that 
CABLIVI[supreg] is a valuable tool for the treatment of aTTP that 
provides significantly improved clinical care compared to the current 
standard of care. According to the commenter, by creating a window 
period during CABLIVI[supreg] administration in which the 
pathophysiology of aTTP is crippled in a targeted fashion, patients 
with aTTP can be treated for existing organ damage (for example, 
injuries to heart, brain, gut, RBCs) and have an earlier opportunity 
for immunosuppression to begin working against this dangerous 
autoimmune disease. The commenter stated that in two randomized 
controlled trials, CABLIVI[supreg] has demonstrated the ability to 
rapidly normalize platelet count in a sustained manner while drug is 
being administered, as well as decrease the composite endpoint of 
death, disease recurrence, and thromboembolic events.
    The applicant provided information in response to CMS' concerns 
regarding whether CABLIVI[supreg] meets the substantial clinical 
improvement criterion. The information provided by the applicant was in 
response to CMS' concerns regarding whether CABLIVI[supreg] meets the 
overall substantial clinical improvement criterion, the demographics of 
the Phase II TITAN study patient population, the need for longer-term 
studies to identify the effect of CABLIVI[supreg] on exacerbations and 
relapse, the small sample size included in the Phase III HERCULES study 
and the clinical trial design of the Phase II TITAN and Phase III 
HERCULES studies due to short follow-up period, unclear defined 
secondary endpoints and inclusion of biologically important endpoints.
    The applicant stated that the multi-discipline review of 
CABLIVI[supreg] by the

[[Page 42207]]

FDA concluded that the Phase III HERCULES study provided substantial 
evidence of CABLIVI[supreg]'s effectiveness when added to daily PE and 
immunosuppression compared to PE and immunosuppression alone. The 
applicant stated that the primary endpoint of the Phase III HERCULES 
study was time to platelet response in which the study produced a 
median time to platelet response of 2.7 days in the CABLIVI[supreg] 
treatment group compared to 2.9 days in the placebo treatment group. 
According to the applicant, other equally important clinical outcomes 
consist of the proportion of patients with aTTP-related death, 
recurrence of aTTP or at least one treatment emergent major 
thromboembolic event (a composite endpoint). The applicant stated that 
these outcomes were significantly lower in the CABLIVI[supreg] 
treatment group (9/72 (13 percent) compared to the placebo treatment 
group 36/73 (49 percent) (p<0.0001). The applicant further stated that 
the proportion of patients with a recurrence of aTTP in the overall 
study period was significantly lower in the CABLIVI[supreg] treatment 
group (9/72 (13 percent) patients) compared to the placebo treatment 
group (28/73 (38 percent) patients) (p<0.001). The applicant noted that 
in the 6 patients treated with CABLIVI[supreg] who experienced a 
recurrence of aTTP during the follow-up period (that is, a relapse 
defined as recurrent thrombocytopenia after initial recovery of 
platelet count (platelet count 2: 150,000/[mu]L) that required re-
initiation of daily plasma exchange, occurring after the 30-day post 
daily plasma exchange period), ADAMTS13 activity levels were <10 
percent at the end of the study drug treatment suggesting that the 
underlying immunological disease was still active at the time 
CABLIVI[supreg] was stopped.
    The applicant also stated that during the overall study drug 
treatment period, which included, for all patients, the period on 
double-blind treatment, as well as, for patients who had an 
exacerbation and were switched, the period on open-label 
CABLIVI[supreg]-treatment resulted in a 38 percent reduction in the 
number of PE days (average reduction 3.6 days) and a 41 percent 
reduction in the volume of plasma exchanged (average reduction 15 L). 
The applicant also stated that there was a 65 percent reduction in 
length of intensive care unit (ICU) stay (average reduction 6.3 days) 
and a 31 percent reduction in length of hospitalization (average 
reduction 4.5 days).
    In response to CMS's concerns regarding the patient population 
demographics of the Phase II TITAN trial, the applicant stated that the 
FDA assessed the substantial clinical improvement of CABLIVI[supreg] 
based on the Phase III HERCULES study, whereas the Phase II TITAN trial 
was considered supportive evidence. The applicant also noted that it is 
important to understand that both the Phase II TITAN and Phase III 
HERCULES studies included US sites (8 sites/15 patients in TITAN and 10 
sites/32 patients in HERCULES). According to the applicant the Phase 
III HERCULES study is the pivotal study for efficacy evaluation and was 
a study in which US patients represented overall 22 percent of the 
overall patient population. Also, the applicant stated that in the 
Phase III HERCULES study, 28 patients were black or African American 
(21.1 percent of the overall aTTP population and only 13.8 percent of 
the US population) and as such the applicant considers the results of 
the studies applicable to the US population. The applicant also stated 
that the FDA did not raise any concerns related to the demographics of 
the patient population during the Biologics License Application (BLA) 
review process.
    Regarding the CMS concern on the need for longer-term studies to 
identify the effect of CABLIVI[supreg] on exacerbations and relapse the 
applicant re-iterated information previously submitted with its 
application and previously summarized. The applicant stated that the 
trial results show the proportion of patients with a recurrence of aTTP 
in the overall study period was significantly lower in the 
CABLIVI[supreg] group (9/72 (13 percent) patients) compared to the 
placebo group (28/73 (38 percent) patients) (p<0.001) and that in the 6 
patients treated with CABLIVI[supreg] who experienced a recurrence of 
aTTP during the follow-up period, ADAMTS13 activity levels were <10 
percent at the end of the study drug treatment suggesting that the 
underlying immunological disease was still active at the time 
CABLIVI[supreg] was stopped.
    The applicant also acknowledged that long-term studies and clinical 
experiences are needed to better understand CABLIVI[supreg]'s 
effectiveness in preventing recurrences of aTTP episodes and as such it 
is conducting a 3 year follow-up study for those patients enrolled in 
the Phase III HERCULES study in which data will be available in the 
near future. In addition, the applicant stated they are working with 
the medical community to explore real world data generation 
opportunities, including registries.
    In response to CMS' concerns regarding the small sample size 
included in the Phase III HERCULES study, the applicant stated that as 
aTTP is an ultra-rare blood disorder with a reported incidence of 4 to 
5 cases per million in the US, enrolling a large number of patients in 
a clinical study is challenging. Furthermore, the applicant explained 
that the sample size calculation of the Phase III HERCULES study was 
assessed in the BLA review process by the FDA and described accurately 
as being based on superiority testing of CABLIVI[supreg] over placebo 
with respect to time to platelet response and satisfying the following 
criteria:
     80 percent power;
     Log-rank test at 2-sided a = 0.05;
     Accrual period lasting 2.5 years;
     Time-to-event period set at 45 days (note: for the primary 
endpoint, a patient is censored if there is no platelet response by day 
45);
     40 percent reduction in time-platelet response. Assuming a 
median time-to-response of 7 days among placebo, this is tantamount to 
a median time-to-response of 4.2 days in the CABLIVI[supreg] arm; and
     Expected dropout rate of 10 percent in the first 10 days 
after first administration of study drug.
    The applicant stated that under these criteria, 121 events are 
required resulting in a sample size of 132 patients and that the actual 
number of patients randomized in the study exceeded this threshold at 
145. Also, according to the applicant, the FDA did not have any major 
comments or concerns about the sample size of Phase III HERCULES study, 
endpoint definition or other relevant methodological questions or 
concerns during the BLA review process. The applicant also stated that 
the Phase III HERCULES study was the largest study ever conducted in 
this rare condition in which the results were recently published in the 
New England Journal of Medicine with no significant questions or 
remarks from the editors on the sample size, endpoint definition or any 
other relevant methodological questions raised by journal editors or 
reviewers.
    In response to CMS' concerns regarding the clinical trial design of 
the Phase II TITAN and Phase III HERCULES studies due to short follow-
up period, the applicant stated that the 1-month follow-up period was 
defined based on current evidence that this is the period for which 
patients are at higher risk of recurrence for the presenting episode of 
a TTP. The applicant re-iterated information previously submitted with 
its application and previously summarized in this final rule stating 
that the proportion of patients with a recurrence of aTTP in the 
overall study period was

[[Page 42208]]

significantly lower in the CABLIVI[supreg] group (9/72 (13 percent) 
patients) compared to the placebo group (28/73 (38 percent) patients) 
(p<0.001). Again, the applicant indicated that in the 6 patients 
treated with CABLIVI[supreg] who experienced a recurrence of aTTP 
during the follow-up period, ADAMTS13 activity levels were <10 percent 
at the end of the study drug treatment suggesting that the underlying 
immunological disease was still active at the time CABLIVI[supreg] was 
stopped.
    In response to CMS' concerns regarding clinical trial design of the 
Phase II TITAN and Phase III HERCULES studies due to unclear defined 
secondary endpoints and inclusion of biologically important endpoints, 
the applicant stated that the Phase III HERCULES study was designed to 
understand the potential role of CABLIVI[supreg] in the treatment of 
aTTP by comparing CABLIVI[supreg] with placebo with respect to time to 
normalization of platelet count (primary endpoint) and the risk of 
death and complications caused by thrombotic events and organ damage 
(secondary and other endpoints). According to the applicant, the trial 
also evaluated the potential of CABLIVI[supreg] to reduce the risk of 
recurrence by allowing for treatment to continue until 
immunosuppressive therapy resolved the underlying autoimmune disease. 
The applicant noted that the endpoints of this study were defined a 
priori and detailed in the clinical study protocol.
    The applicant re-iterated information previously submitted with its 
application and previously summarized in this final rule stating that 
primary outcome of the studies was the time to a response, which was 
defined as the time from the first intravenous administration of 
CABLIVI[supreg] or placebo to normalization of the platelet count (that 
is, a platelet count of at least 150,000 per cubic millimeter), with 
discontinuation of daily plasma exchange within 5 days thereafter. 
According to the applicant, the results showed a statistically 
significant shorter median time to normalization of platelet count in 
CABLIVI[supreg] group (p=0.01) comparing to placebo.
    The applicant also referenced four key secondary outcomes of the 
studies, which were hierarchically ranked on the basis of clinical 
relevance, as the following:
    1. A composite of TTP-related death, recurrence of TTP, or a major 
thromboembolic event (for example, myocardial infarction, stroke, 
bleeding episodes) during the trial treatment period. Results were 
statistically significant favoring CABLIVI[supreg] arm (p<0.001);
    2. Recurrence of TTP at any time during the trial, including the 
follow-up period. Results were statistically significant favoring 
CABLIVI[supreg] arm (p<0.001);
    3. Refractory TTP (defined by the lack of a doubling of the 
platelet count after 4 days of treatment and a lactate dehydrogenase 
level that remained above the upper limit of the normal range). Results 
were not statistically significant (p=0.06); and
    4. The time to normalization (that is, to a level below the defined 
upper limit of the normal range) of three organ-damage markers (lactate 
dehydrogenase, cardiac troponin I, and serum creatinine). Not tested 
for statistical significance as prior endpoint was not statistically 
significant.
    The applicant stated that a recurrence was defined as a new 
decrease in the platelet count that necessitated the re-initiation of 
plasma exchange after normalization of the platelet count had occurred, 
an exacerbation was defined as a recurrence that occurred within 30 
days after the last plasma exchange and a relapse was defined as a 
recurrence that occurred more than 30 days after cessation of plasma 
exchange. Furthermore, the applicant conveyed that outcomes that were 
not part of the hierarchy included the number of days of PE and the 
volume of plasma exchanged, the duration of stay in an ICU and in the 
hospital, mortality rate, pharmacodynamic and pharmacokinetic 
variables, and immunogenicity. Finally, according to the applicant, 
safety assessments were performed throughout the course of the trial 
and included evaluation of vital signs, physical examinations, clinical 
laboratory testing, and 12-lead electrocardiography.
    Response: We appreciate all the comments received related to 
CABLIVI[supreg], including the applicant's submission of additional 
information to address the concerns presented in the proposed rule.
    After consideration of the public comments we received, we believe 
that the applicant has addressed our concerns regarding whether 
CABLIVI[supreg] meets the substantial clinical improvement criterion, 
and that CABLIVI[supreg] represents a substantial clinical improvement 
over existing technologies (PE and immunosuppression alone) based on 
the results of the Phase II TITAN and Phase III HERCULES studies with 
respect to time to platelet count response, which is consistent with 
the halting of platelet consumption in microthrombi; the number of 
patients with aTTP-related death and recurrence of aTTP-related 
episodes or a major thromboembolic event, and mortality. Additionally, 
we note that CABLIVI[supreg] is the only FDA-approved therapy for 
treating aTTP in conjunction with PE and immunosuppressive therapy.
    In summary, we have determined that CABLIVI[supreg] meets all of 
the criteria for approval of new technology add-on payments. Therefore, 
we are approving new technology add-on payments for CABLIVI[supreg] for 
FY 2020. Cases involving CABLIVI[supreg] that are eligible for new 
technology add-on payments will be identified by ICD-10-PCS procedure 
codes XW013W5, XW033W5 and XW043W5. In its application and subsequent 
public comment, the applicant estimated that the average Medicare 
beneficiary would require a dosage of 11 mg/kg administered as an 
intravenous injection as a single dose and of 10 mg/kg administered as 
a subcutaneous injection as a single dose. According to the applicant, 
the WAC for one dose of 10 mg/kg is $7,300, and patients will typically 
require 1.16 vials for the course of treatment with CABLIVI[supreg] per 
day for an average duration of 6 days for an average total of 7 vials. 
Therefore, the total cost of CABLIVI[supreg] per patient is $51,100. 
Under Sec.  412.88(a)(2) (revised as discussed in this final rule), we 
limit new technology add-on payments to the lesser of 65 percent of the 
average cost of the technology, or 65 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 
CABLIVI[supreg] is $33,215 for FY 2020.
c. CivaSheet[supreg]
    CivaTech Oncology, Inc. submitted an application for new technology 
add-on payments for CivaSheet[supreg] for FY 2020. CivaSheet[supreg] 
received FDA clearance of a 510(k) premarket notification on August 29, 
2014. CivaSheet[supreg] was approved as a ``sealed source'' by the 
Nuclear Regulatory Commission (NRC) and added to the Registry of 
Radioactive Sealed Source and Devices on October 24, 2014. On May 9, 
2018, CivaSheet[supreg] was registered by the American Association of 
Physicists in Medicine (AAPM) on the ``Joint AAPM/IROC Houston Registry 
of Brachytherapy Sources Complying with AAPM Dosimetric 
Prerequisites.'' According to the applicant, inclusion on this AAPM 
registry is a long-standing requirement imposed on brachytherapy 
sources used in all National Cancer Institute clinical trials and that 
all other available brachytherapy sources are included on

[[Page 42209]]

this registry. According to the applicant, CivaSheet[supreg] was not 
commercially distributed among IPPS hospitals until May 2018, after 
meeting the requirements for inclusion in the AAPM registry. Therefore, 
according to the applicant the ``newness'' period for the 
CivaSheet[supreg], if approved for FY 2020 new technology add-on 
payments, should commence on May 9, 2018. Based on this information, in 
the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19295), we stated that 
we believe the newness period for CivaSheet[supreg] would begin on May 
9, 2018. However, we invited public comments on whether inclusion on 
the AAPM registry is an appropriate indicator of the first availability 
of the CivaSheet[supreg] brachytherapy sources on the U.S. market and 
whether the date of inclusion on the AAPM registry is appropriate to 
consider as the beginning of the newness period for CivaSheet[supreg].
    Comment: The applicant submitted public comments reiterating that 
CivaSheet was registered by the American Association of Physicists in 
Medicine (AAPM) on the Joint AAPM/IROC Houston Registry of 
Brachytherapy Sources Complying with AAPM Dosimetric Prerequisites. The 
applicant reiterated that while the CivaSheet was cleared by the Food 
and Drug Administration and approved by the Nuclear Regulatory 
Commission as a ``sealed source'' somewhat earlier, inclusion of a 
brachytherapy source on this Registry is essentially a prerequisite for 
commercial acceptance of such a source. For acceptance of a new 
brachytherapy source outside of essentially experimental contexts, 
completion of dosimetric studies is necessary. The applicant indicated 
that it is the AAPM's validation that the results of these studies 
indicate compliance with its prerequisites, rather than FDA clearance, 
that appropriately marks the readiness of a source for the market and 
the CivaSheet[supreg] was added to the registry, May 9, 2018.
    Response: We appreciate the applicant's comments. After 
consideration of the comments we received, it appears that 
CivaSheet[supreg] was not commercially distributed among IPPS hospitals 
until May 2018, after meeting the requirements for inclusion in the 
AAPM registry. As we have stated in prior rulemaking (69 FR 28237), the 
2-year to 3-year period of newness for a technology or medical service 
would ordinarily begin with FDA approval, unless there was some 
documented delay in bringing the product onto the market after that 
approval. Therefore, we believe that the newness period for the 
CivaSheet[supreg] would begin May 9, 2018. CivaSheet[supreg] is 
intended for medical purposes to be placed into a body cavity or tissue 
as a source for the delivery of radiation therapy. CivaSheet[supreg] is 
indicated for use as a permanent interstitial brachytherapy source for 
the treatment of selected localized tumors. The device may be used 
either for primary treatment or for the treatment of residual disease 
after excision of the primary tumor. CivaSheet[supreg] may be used 
concurrently, or sequentially, with other treatment modalities, such as 
external beam radiation therapy or chemotherapy. In the proposed rule, 
we noted that the applicant had submitted a request for approval for a 
unique ICD-10-PCS procedure code to describe procedures involving the 
use of the CivaSheet[supreg] device, beginning in FY 2020. Approval was 
granted for the following procedure codes effective October 1, 2019:

[[Page 42210]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.134


[[Page 42211]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.135


[[Page 42212]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.136

    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, therefore, would not be 
considered ``new'' for

[[Page 42213]]

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, CivaSheet[supreg] does not have a similar 
mechanism of action in comparison to existing brachytherapy 
technologies. The applicant asserted that the unique construction and 
configuration of the CivaSheet[supreg] device permits delivery of 
radiation intra-operatively in a highly targeted fashion. The applicant 
explained that the CivaSheet[supreg] is cut to size in the operation 
room (OR) and conformed to the patient's anatomy and surgical site, 
which allows radiation to be delivered to the resected tumor bed 
margins at the time of the original surgery. The applicant further 
explained that, it is generally believed that ``hot'' spots should be 
avoided in the delivery of radiotherapy because they lead to 
complications, citing the finding that ``[i]n brachytherapy, dose 
homogeneity is difficult to achieve, but efforts to minimize ``hot'' 
spots have been regarded as virtuous and implant-planning guidelines 
were developed to assist in this regard.'' \49\ The applicant stated 
that implants are rarely geometrically perfect and, to avoid under-
dosing some parts of the target volume, it may be necessary to create 
``hot spots'' in other parts of the anatomy. However, as a result, a 
``hotter'' dose compared to that achievable with external beam 
technologies can be delivered to the intended area. In contrast, the 
applicant indicated that CivaSheet[supreg]'s unidirectional 
configuration substantially reduces the dose delivered to neighboring 
radiosensitive structures. The applicant further stated that other 
forms of radiation delivery do not have these capabilities, and no 
other shielded low-dose radiation (LDR) sources are currently available 
on the market. According to the applicant, external beam radiation 
generally cannot be delivered intra-operatively, partly because dosage 
requirements make this impractical and potentially risky and because 
appropriate aiming cannot be computed in the timeframe of a performed 
surgery.
---------------------------------------------------------------------------

    \49\ Bhadrasain, M.D., Vikram, Shivaji, Ph.D., Deore, Beitler, 
M.D., Jonathan J., Sood, M.D., Brij, Mullokandov, Ph.D., Eduard, 
Kapulsky, Ph.D., Alexander, Fontenla, Ph,d, Doracy P, ``The 
relationship between dose heterogeneity (``hot'' spots) and 
complications following high-dose rate brachytherapy,'' Int. J. 
Radiation Oncology Biol. Phys., 1999, vol. 43, no. 5, pp. 983-987.
---------------------------------------------------------------------------

    The applicant believed that, in the absence of the use of the 
CivaSheet[supreg] device, a patient requiring radiation therapy to 
accompany surgery would most likely receive radiation therapy as an 
outpatient service following the inpatient hospitalization after 
surgery. Moreover, the applicant stated that not only does this 
typically require multiple, fractionated treatments, in some cases, 
outpatient external beam radiation may not be possible due to excessive 
toxicity to normal surrounding tissues. According to the applicant, 
radiation therapy can be delivered intra-operatively directly to 
surgical margins through use of a linear accelerator. However, the 
applicant stated that these technologies deliver radiation in a single 
``flash,'' whereas the CivaSheet[supreg] device enables the delivery of 
radiation over time, increasing the efficacy of the radiation therapy.
    Further, the applicant stated that external beam radiation devices 
have a fixed ball or cone-shaped applicator, which does not necessarily 
conform well to the irregular shapes of surgical cavities or permit 
effective screening of adjacent tissues. Additionally, the applicant 
stated that this form of radiation therapy requires a specialized 
linear accelerator and a specially shielded operating room, which the 
applicant believes restricts its use to IPPS-exempt cancer centers.
    The applicant further stated that, in the past, cylindrical 
brachytherapy seeds have been used with various mesh products as a form 
of intra-operative radiation therapy (IORT). However, according to the 
applicant, the use of cylindrical brachytherapy seeds used with various 
mesh products has not developed as part of standard clinical practice. 
According to the applicant, patients treated with previous cylindrical 
brachytherapy seeds faced considerable challenges with toxicity from 
the unfocused, unshielded seed sources when placed in proximity of 
sensitive organs.\50\ Additionally the surgical meshes previously used 
were not designed to maximize source orientation and spacing, and also 
ran the risk of source dispersion as the mesh degraded.\51\ The 
applicant maintains that the CivaSheet[supreg] is the first low-dose 
radiation (LDR) brachytherapy device designed specifically for the 
delivery of IORT. CivaSheet[supreg]'s individual brachytherapy sources 
are flat with a gold shielding on one side of the seed, a design that 
focuses radiation in one direction, in contrast to the cylindrical 
shape of LDR brachytherapy seeds, which emit radiation in all 
directions. According to the applicant, properties of the flat, gold-
shielded sources and the bioabsorbable polymer encapsulation make the 
CivaSheet[supreg] uniquely suited for intra-operative delivery. As 
such, the applicant asserted that the CivaSheet[supreg] does not have a 
similar mechanism of action when compared to existing LDR 
brachytherapies.
---------------------------------------------------------------------------

    \50\ Rivard, Mark J., ``Low energy brachytherapy sources for 
pelvic sidewall treatment,'' abstract presented at the ABS 2016 
Annual Meeting.
    \51\ Seneviratne, Danushka, et al., ``The CivaSheet: The new 
frontier of intraoperative radiation therapy or a pricer alternative 
to LDR brachytherapy,'' Advances in Radiation Oncology, 2018, vol. 
3, pp. 87-91.
---------------------------------------------------------------------------

    With regard to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant asserted that patients 
who may be eligible for treatment using the CivaSheet[supreg] include 
hospitalized patients having tumors removed from the pancreas, colon 
and anus, pelvic area, head and neck, soft tissue sarcomas, non-small-
cell lung cancer, ocular melanoma, atypical meningioma and 
retroperitoneum and that cases involving the use of the 
CivaSheet[supreg] would map primarily into the following MS-DRGs listed 
below. In the proposed rule, we indicated that we believe that cases 
involving the use of existing technologies would be assigned to these 
same MS-DRGs as previously listed.

[[Page 42214]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.137

[GRAPHIC] [TIFF OMITTED] TR16AU19.246


[[Page 42215]]


    With regard 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, according to the 
applicant, clinical conditions that may require use of the 
CivaSheet[supreg] include treatment of the same patient population as 
those who have been diagnosed with a variety of types of cancer, 
including pancreatic cancer, colorectal cancer, anal cancer, pelvic 
area/gynecological cancer, retroperitoneal sarcoma and head and neck 
cancers.
    The applicant asserted that the CivaSheet[supreg] device is not 
substantially similar to any existing technology because it uses a 
unique mechanism of action, when compared to existing LDR brachytherapy 
technologies, to achieve a therapeutic outcome and, therefore, meets 
the newness criterion.
    We invited public comments on whether the CivaSheet[supreg] device 
meets the newness criterion.
    Comment: The applicant submitted public comments stating that it 
believes that the CivaSheet[supreg] meets CMS' newness criterion. The 
applicant stated that in particular, the CivaSheet[supreg] enables 
intraoperative delivery of radiation in circumstances where this was 
not previously possible, whether using brachytherapy or other forms of 
radiation, without adverse effects on neighboring, radiosensitive 
tissue. The applicant stated that the capability for one-directional 
delivery of radiation, attributable to the gold shielding on each 
source and the persisting matrix in which the sources are embedded and 
which maintains their orientation within the body as the surgical wound 
is closed and heals, is unique. The applicant further stated that the 
customizable, conformable, planar design allows positional stability, 
homogenous distribution of radiation in the surgical cavity, features 
not available in radioactive seed technology previously available. 
Response: We appreciate the applicant's comments with regard to the 
newness criterion. After consideration of the comments we received, we 
believe the mechanism of action of the CivaSheet[supreg] is unique from 
other brachytherapy technologies because of. the unidirectional 
delivery of intraoperatively applied radiation due to its shielded gold 
layer. Therefore, we believe the CivaSheet[supreg] is not substantially 
similar to existing technology and that 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 determine the MS-DRGs that potential cases representing 
patients who may be eligible for treatment involving CivaSheet[supreg] 
would map to, the applicant identified all MS-DRGs for cases that 
included ICD-10-CM diagnosis codes for either pancreatic cancer, 
colorectal cancer, anal cancer, pelvic area/gynecological cancer, 
retroperitoneal sarcoma and head and neck cancers as a primary or 
secondary diagnosis. Based on the FY 2017 MedPAR Hospital Limited Data 
Set (LDS), the applicant identified a total of 22,835 potential cases. 
The applicant limited its analyses to the most relevant 32 MS-DRGs, 
which represented 80 percent of all the cases. The applicant excluded 
the following cases: statistical outliers which the applicant defined 
as 3 standard deviations from the geometric mean, HMO cases and claims 
submitted only for graduate medical education payments and cases at 
hospitals that were not included in the FY 2019 IPPS/LTCH PPS final 
rule impact file (the applicant noted that these are predominately 
cancer hospitals not subject to the IPPS). After applying the trims as 
previously described, the applicant identified 17,173 remaining cases.
    Using the 17,173 cases, the applicant determined an average case-
weighted unstandardized charge per case of $122,565. The applicant 
standardized the charges for each case and inflated each case's charges 
from FY 2017 to FY 2019 by applying the outlier charge inflation factor 
of 1.085868 from the FY 2019 IPPS/LTCH PPS proposed rule (83 FR 20581). 
The applicant indicated that the current average cost of the 
CivaSheet[supreg] device is $24,132.86. The applicant then added 
charges for CivaSheet[supreg] 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 implants from the FY 2019 IPPS/LTCH PPS final rule (83 
FR 41273). The applicant calculated an average case-weighted 
standardized charge per case of $188,897 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 CivaSheet[supreg] exceeded the average case-
weighted threshold amount of $87,446 by $101,451.
    In the proposed rule, we noted that 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). However, we noted that 
even when using either the 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 CivaSheet[supreg] would exceed the average case-weighted threshold 
amount. We invited public comments on whether the CivaSheet[supreg] 
meets the cost criterion.
    Comment: The applicant submitted public comments reiterating its 
previously submitted cost analysis. The applicant further stated that 
it believes the technology meets the cost criterion.
    Response: After consideration of the public comments we received, 
we agree that the CivaSheet[supreg] meets the cost criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant asserted that CivaSheet[supreg] represents a substantial 
clinical improvement over existing technologies because it provides the 
following: (1) Improved local control of different cancers; \52\ (2) 
reduced rate of device-related complications; \53\ (3) reduced rate of 
radiation toxicity; \54\ (4) decreased future hospitalizations; \55\ 
(5) decreased rate of subsequent therapeutic interventions; \56\ (6) 
improvement in back pain and appetite in pancreatic cancer patients 
\57\ and (7) improved local control for pancreatic cancer patients.\58\
---------------------------------------------------------------------------

    \52\ Castaneda SA, Emrich J, Bowne WB, Kemmerer EJ, Sangani R, 
Khalili M, Rivard MJ, Poli J. ``Clinical outcomes using a novel 
directional Pd-103 brachytherapy device: 20-month report of a 
patient with leiomyosarcoma of the pelvic sidewall.'' ACRO 2018 
Annual Meeting.
    \53\ 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.
    \54\ 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.
    \55\ Cavanaugh, S.X., Rothley, D.J., Richman, C., ``Directional 
LDR Intraoperative Brachytherapy for Head and Neck Cancer,'' 
Presented at ABS 2017 Annual Meeting.
    \56\ On file at CivaTech.
    \57\ Ibid.
    \58\ 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 improved local control of different cancers, the 
applicant provided the clinical outcomes results

[[Page 42216]]

of a 20-month report of a patient who had been diagnosed with 
leiomyosarcoma of the pelvic sidewall.\59\ According to the report, the 
purpose of the report was to document the experience of using the 
CivaSheet[supreg] implant as adjuvant intraoperative treatment in a 
patient who had been diagnosed with locally advanced leiomyosarcoma of 
the lateral pelvic sidewall. The patient analyzed in this report is a 
62-year-old African American male who was found to have a mass 
incidentally in the left pelvic sidewall. The patient presented with 
lower abdominal pain, hematuria, and lower left flank pain radiating to 
the left groin. A CT scan revealed a mass in the left pelvic sidewall 
that measured 8.1 x 6.4 x 3.7 cm, with encasement of the left common 
iliac vein and no distant metastasis. A biopsy revealed a high-grade 
leiomyosarcoma. Given his advanced clinical stage and iliac vein 
encasement, neoadjuvant pelvic radiotherapy with IMRT, surgical 
resection with reconstruction, and a boost with intraoperative LDR 
brachytherapy were performed. The patient was treated with pelvic IMRT 
(50.4 Gy/28 fractions). The patient then underwent gross total 
resection and the CivaSheet[supreg] was implanted intraoperatively. The 
patient recovered well from the interventions, according to the report. 
At 20 months after implantation of the LDR brachytherapy device, 
clinical evaluations and CT imaging surveillance demonstrated no 
evidence of residual disease, according to the report.
---------------------------------------------------------------------------

    \59\ Castaneda, S.A., Emrich, J., Bowne, W.B., Kemmerer, E.J., 
Sangani, R., Khalili, M., Rivard, M.J., Poli, J., ``Clinical 
outcomes using a novel directional Pd-103 brachytherapy device: 20-
month report of a patient with leiomyosarcoma of the pelvic 
sidewall,'' ACRO 2018 Annual Meeting.
---------------------------------------------------------------------------

    With regard to reducing the rate of device-related complications, 
the applicant summarized four case series. In the four case series, the 
CivaSheet[supreg] device was used to treat: (1) Axillary squamous cell 
carcinoma; \60\ (2) retroperitoneal sarcoma; 61 62 63 (3) 
gastric signet ring adenocarcinoma; (4) pancreatic cancer; and (5) 
other abdominal malignancies. There were 13 patients associated with 
these 4 case series.
---------------------------------------------------------------------------

    \60\ 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.
    \61\ 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.
    \62\ 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.
    \63\ 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 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

[[Page 42217]]

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.,\64\ and Turian, et 
al.,\65\ 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.
---------------------------------------------------------------------------

    \64\ 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.
    \65\ 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.\66\ 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 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.
---------------------------------------------------------------------------

    \66\ 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.\67\ 
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

[[Page 42218]]

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.,\68\ 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.
---------------------------------------------------------------------------

    \67\ 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.
    \68\ 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 \69\ 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.70 71 72 The applicant 
also 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.73 74 75
---------------------------------------------------------------------------

    \69\ 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.
    \70\ Rivard, Mark J., ``Low energy brachytherapy sources for 
pelvic sidewall treatment,'' abstract presented at the ABS 2016 
Annual Meeting.
    \71\ 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.
    \72\ 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.
    \73\ Ibid.
    \74\ Rivard, Mark J., ``Low energy brachytherapy sources for 
pelvic sidewall treatment,'' abstract presented at the ABS 2016 
Annual Meeting.
    \75\ 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

[[Page 42219]]

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, in the proposed rule we stated that we were 
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 we stated that we 
were 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 invited public comments on whether 
CivaSheet[supreg] meets the substantial clinical improvement criterion.
    Comment: The applicant submitted public comments regarding CMS' 
concerns. With regard to our concern that the supporting data provided 
by the applicant appear to be feasibility studies, the applicant stated 
that the feasibility studies substantiate the experience with such 
uses. The applicant further stated that it believes that CMS' 
characterization fails to reflect other aspects of these studies as 
they are not limited to investigating whether intraoperative radiation 
therapy can be delivered with the CivaSheet[supreg], but also show 
positive outcomes, including providing information following patients 
for periods that range up to 24 or even 35 months. The applicant 
further stated that in the case of radiation therapy, the likely 
effects in the body of specific doses on target tumors and on healthy 
tissues are well known and can be quantified with well-developed 
treatment planning systems. The applicant stated that the major 
research questions at this stage of the product's development are not 
focused on either the safety or efficacy of the treatment (since the 
product is already cleared by the FDA) but on whether physicians in 
clinical practice can position it appropriately in the surgical field 
and on the effects of the localized, unidirectional delivery of 
intraoperatively applied radiation that CivaSheet[supreg] provides on 
outcomes of interest, including indications of toxicity and recurrence.
    With regard to CMS' concern that there do not appear to be any 
comparisons to other current treatments, or any long-term follow-up 
with comparison to currently available therapies, the applicant stated 
that it believes that the results detailed in the following categories 
for CivaSheet[supreg] patients compare favorably with the results 
presented in the clinical literature regarding the toxicity rates for 
EBRT and with historical recurrence rates for patients receiving common 
adjunctive therapies:
     Reduced radiation toxicity--None of the patients in the 
associated clinical literature whose treatments have included 
CivaSheet[supreg] have suffered nausea, vomiting, diarrhea, 
constipation or fatigue, all side effects that are common with other 
forms of radiation therapy, due to the CivaSheet[supreg] treatment. The 
applicant stated that the company keeps records of all patients 
treated, and to date has not received any reports or complaints of 
acute or chronic radiation toxicity attributable to the 
CivaSheet[supreg] in any of the 78 patients who have received the 
therapy. The applicant believes this record compares favorably with the 
rates for toxicity for EBRT.
     Fewer therapeutic interventions and hospitalizations--The 
applicant stated that for the same group of patients, the local 
recurrence rate for disease in the treatment field of the device for 
patients treated with CivaSheet[supreg] is none, regardless of site of 
the cancer treated. The applicant stated that comparison with 
information drawn from the clinical literature regarding the local 
recurrence rate by site that would be expected if the patient were 
treated by the existing standards of care following surgery, including 
the common adjunctive procedures, external beam radiation and 
chemotherapy, reveals the extent of local recurrence is more favorable 
for CivaSheet[supreg] patients. The applicant believes that because of 
the absence of local recurrence in the treatment fields, patients have 
not required additional procedures following the primary cancer 
surgery, on either outpatient or inpatient basis, related to treating 
disease recurrence in the area treated by CivaSheet[supreg]. The 
applicant further stated that in addition, patients have not

[[Page 42220]]

required further interventions or hospitalizations to treat radiation 
related side effects, as none have been recorded.
    The applicant also provided information, by indication, to studies 
involving CivaSheet[supreg] and on which they have information on file. 
These include the literature cited in their FY 2020 new technology add-
on payment application and the ongoing clinical trials. The applicant 
also provided an appendix summarizing key information for comparison 
available in the clinical literature. For each cancer type treated with 
CivaSheet, the applicant displayed the toxicity rates for EBRT, the 
most common and widely available alternative, with references cited. 
These range from 1.1 percent (gastrointestinal following prostatectomy) 
to as high as 80 percent for retroperitoneal sarcoma. According to the 
applicant, the comparative rates for CivaSheet treatments are zero in 
the published literature presented to CMS, and the company has received 
no reports of local recurrence or toxicity for patients treated outside 
of a clinical trial setting. The appendix also showed similar 
information for local recurrence rates. According to the applicant, in 
the literature, these range from 6 percent for breast cancer to as high 
as 60 percent for gynecogical cancers.
    The applicant provided a second appendix, Appendix 2, to provide 
links of the claims noted in the studies provided with its application. 
Appendix 2 presented information, by indication, to studies involving 
CivaSheet[supreg] and on which the applicant has information on file to 
include the literature cited in its application and the ongoing 
clinical trials.
    The applicant believes that the data it provided demonstrates a 
substantial clinical improvement for the treatment of Medicare patients 
with cancer.
    We also received a public comment stating that CivaSheet provides a 
targeted and high enough dose to the surgical margin to control local 
disease without inducing side effect and that CivaSheet[supreg] has 
benefits for pancreatic, sarcoma and colorectal patients. The commenter 
did not provide additional data in support of these statements.
    Response: We appreciate the public comments we received regarding 
whether the CivaSheet meets the substantial clinical improvement 
criterion, including the comments submitted by the applicant. While the 
applicant provided additional references and a summary of the clinical 
trials underway, we believe the data remains limited as most of the 
clinical trials will not complete enrollment until 2020. Further, the 
majority of the evidence submitted to date still focuses on limited 
numbers of patients who participated in feasibility studies with no 
comparator arms nor clinical outcome results. Finally, the single 
clinical trial that has been completed is not anticipated to have data 
available until third quarter 2019. For these reasons, we are unable to 
determine that the CivaSheet[supreg] represents a substantial clinical 
improvement over existing therapies. Therefore, we are not approving 
new technology add-on payments for the CivaSheet[supreg] for FY 2020.
    d. 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.\76\ 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.\77\
---------------------------------------------------------------------------

    \76\ 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.
    \77\ 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.\78\
---------------------------------------------------------------------------

    \78\ 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.

[[Page 42221]]

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 
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. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19313), we noted 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. 
Approval was granted for the following procedure codes effective 
October 1, 2019:

[[Page 42222]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.138


[[Page 42223]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.139


[[Page 42224]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.140


[[Page 42225]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.244

    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). In the proposed 
rule, we stated that 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 this table:

[[Page 42226]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.141


[[Page 42227]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.142

    The applicant asserted that the Eluvia\TM\ 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.
    In the proposed rule, we stated that we were concerned as to 
whether the polymer drug carrier system that the Eluvia\TM\ system uses 
is, in fact, a new mechanism of action as compared to stents that 
contain paclitaxel without the carrier polymer. We stated that we were 
concerned that the Eluvia\TM\ 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 invited public comments on whether the 
Eluvia\TM\ system is substantially similar to existing technology and 
whether it meets the newness criterion, including with respect to the 
concerns we raised.
    Comment: The applicant commented that the Eluvia\TM\ device's 
mechanism of action is different from that of the paclitaxel-coated 
Zilver PTX (Zilver[supreg] Drug-Eluting Peripheral Stent) because the 
Eluvia\TM\ device's polymer matrix layer allows for targeted, 
localized, sustained, low-dose amorphous paclitaxel delivery to 
peripheral artery lesions over the course of the peripheral restenotic 
cascade with minimal systemic distribution or particulate loss. The 
applicant provided a comparison of the polymer matrix stent vs. the 
paclitaxel-coated stent. According to the applicant, the polymer matrix 
stent is encased in a polymer matrix, the paclitaxel-coated stent is 
not. The dose density of paclitaxel for the polymer matrix vs the 
paclitaxel coated stent is 0.167ug/mm\2\ vs 3ug/mm\2\. Paclitaxel is 
delivered to the lesion via a diffusion gradient with the polymer 
matrix stent whereas the paclitaxel-coated stent has no diffusion 
gradient. Paclitaxel is released directly to the target lesion with the 
polymer matrix stent. Paclitaxel release is non-specific to the target 
lesion with paclitaxel-coated stent. Paclitaxel is released over 
approximately 12-15 months with the polymer matrix stent. Paclitaxel 
release is complete at two months with paclitaxel coated stents.
    Response: We appreciate the applicant's comments and comparison of 
the polymer matrix Eluvia\TM\ vs the paclitaxel-coated Zilver PTX with 
regard to the mechanism of action. After consideration of the 
applicant's comments, we believe that the Eluvia\TM\ device uses a 
unique mechanism of action to achieve a therapeutic outcome when 
compared to existing technologies such as the paclitaxel-coated stent. 
Therefore the Eluvia\TM\ device 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.
    As noted in the proposed rule and 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

[[Page 42228]]

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). (In the proposed rule, we noted 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 noted 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, as previously described, 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 
invited public comments on whether EluviaTM meets the cost 
criterion.
    Comment: The applicant submitted public comments reiterating the 
various cost analyses results. The applicant maintained that the 
technology meets the cost criterion.
    Response: We appreciate the applicant's comments concerning the 
cost criterion. After consideration of the public comments we received, 
we agree that the EluviaTM device 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 
\79\ 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 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.
---------------------------------------------------------------------------

    \79\ 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 
\80\ 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.
---------------------------------------------------------------------------

    \80\ 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

[[Page 42229]]

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.\81\ 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.
---------------------------------------------------------------------------

    \81\ 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[middot]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.
    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.\82\ Secondary endpoints improved after stent implantation and 
were generally similar between the groups. At 12 months, of the 
patients

[[Page 42230]]

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[middot]0 (SD 0[middot]2) in both groups at 12 
months (baseline mean ankle-brachial index 0[middot]7 [SD 0[middot]2] 
for EluviaTM; 0[middot]8 [0[middot]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:
---------------------------------------------------------------------------

    \82\ 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).
    In the proposed rule, we stated that we were 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 noted 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,\83\ although the 
EluviaTM system was not included in the meta-analysis. We 
invited 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.
---------------------------------------------------------------------------

    \83\ 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).
---------------------------------------------------------------------------

    Comment: The applicant submitted public comments regarding CMS' 
concerns. With regard to our concern that the IMPERIAL study was 
designed for non-inferiority and not superiority, the applicant stated 
that superiority testing was performed after the 12-month follow-up 
window for all enrolled subjects had closed. The applicant also stated 
that from a statistical perspective, the pre-specified success criteria 
for superiority used the same logic as the pre-specified success 
criteria for non-inferiority: ``ELUVIA will be concluded to be superior 
to Zilver PTX for device effectiveness if the one-sided lower 95 
percent confidence bound on the difference between treatment groups in 
12-month primary patency is greater than zero.'' The applicant stated 
that a more stringent one-sided lower 97.5 percent confidence bound 
(shown as two-sided 95 percent confidence interval) on the difference 
between treatment groups was observed to be greater than zero and the 
corresponding p-value was 0.0144.
    In addition to the internal analysis performed by the applicant, 
the applicant stated that the data were published in The Lancet \84\ 
following its rigorous peer-review process. The applicant quoted the 
following from The Lancet: ``The superiority analysis of primary 
patency in the full-analysis cohort was a pre-specified post-hoc 
analysis'' and ``In this head-to-head randomized trial, the primary 
non-inferiority endpoints for efficacy and safety at 12 months were 
met, and post-hoc analysis of the 12-month patency rate showed 
superiority for Eluvia over Zilver PTX.''
---------------------------------------------------------------------------

    \84\ Gray W.A., Keirse K., Soga Y., Benko A., Babaev A., Yokoi 
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 randomised 
non-inferiority trial. Lancet. 2018;392:1541-1551.
---------------------------------------------------------------------------

    According to the applicant, clinical trial guidelines support 
performing a pre-specified post-hoc superiority analysis in this 
situation, provided ``(1) the trial has been properly designed and 
carried out in accordance with the strict requirements of a non-
inferiority trial. (2) actual p-values for superiority are presented to 
allow independent assessment of the strength of the evidence and (3) 
analysis according to the intention-to-treat (ITT) principle is given 
greatest emphasis.''\85\ The applicant contends that the IMPERIAL trial 
met all those requirements.
---------------------------------------------------------------------------

    \85\ Committee for Proprietary Medicinal Products. Points to 
consider on switching between superiority and non-inferiority. Br J 
Clin Pharmacol. 2001 Sep;52(3):223-8.
---------------------------------------------------------------------------

    With respect to the results of the 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, in its public comment, the 
applicant maintained that the EluviaTM device is different 
from the devices evaluated in the meta-analysis. The applicant also 
noted that the EluviaTM device was not addressed in the 
meta-analysis and that the EluviaTM device delivers 
paclitaxel in much lower doses than the products discussed in the meta-
analysis. The applicant contends that the EluviaTM device is 
the only peripheral device to deliver paclitaxel through a sustained-
release mechanism of action where delivery of paclitaxel is controlled 
and focused on the target lesion. The applicant believes that the 
suggestion in the meta-analysis of a late-term mortality risk 
associated with paclitaxel coated devices is not directly applicable to 
the EluviaTM device. The applicant further stated that they 
submitted information (available at https://www.fda.gov/media/127704/download) to the FDA on paclitaxel relative to the EluviaTM 
device in advance of FDA's June 19-20 Circulatory System Devices Panel 
of the Medical Devices Advisory Committee Meeting. Consequently, the 
applicant does not believe that the findings of limited 
generalizability suggested in the meta-analysis should inhibit CMS from 
determining that the EluviaTM satisfies the substantial 
clinical improvement criterion.
    In addition to the applicant's public comments, we also received 
several public comments supporting the EluviaTM Drug-Eluting 
Stent System's application for New Technology Add-on Payment in FY2020. 
Commenters expressed that it is important for PAD patients to have 
access to this technology.
    We also received a comment expressing safety concerns with 
paclitaxel devices used to treat PAD. The commenter stated they were 
aware of an FDA alert concerning paclitaxel

[[Page 42231]]

devices. The commenter stated the applicant and other manufacturers of 
devices using paclitaxel should consider an alternative to paclitaxel.
    Response: We appreciate the applicant's and other public comments. 
We are aware of the FDA's March 15, 2019 Letter to healthcare providers 
regarding the ``Treatment of Peripheral Arterial Disease with 
Paclitaxel-Coated Balloons and Paclitaxel-Eluting Stents Potentially 
Associated with Increased Mortality'' and that on June 19-20, 2019, the 
FDA convened a public meeting of the Circulatory System Devices Panel 
of the Medical Devices Advisory Committee to share information and 
perspectives from all interested parties on a potential late mortality 
signal associated with the use of paclitaxel-coated balloons and 
paclitaxel-eluting stents in patients with peripheral arterial disease.
    In March 2019, the FDA conducted a preliminary analysis of long-
term follow-up data (up to five years in some studies) of the pivotal 
premarket randomized trials for paclitaxel-coated products indicated 
for PAD. While the analyses are ongoing, according to the FDA, the 
preliminary review of the data has identified a potentially concerning 
signal of increased long-term mortality in study subjects treated with 
paclitaxel-coated products compared to patients treated with uncoated 
devices.\86\ Of the three trials with 5-year follow-up data, each 
showed higher mortality in subjects treated with paclitaxel-coated 
products than subjects treated with uncoated devices. In total, among 
the 975 subjects in these 3 trials, there was an approximately 50 
percent increased risk of mortality in subjects treated with 
paclitaxel-coated devices versus those treated with control devices 
(20.1 percent versus 13.4 percent crude risk of death at 5 years).
---------------------------------------------------------------------------

    \86\ https://www.fda.gov/medical-devices/letters-health-care-providers/update-treatment-peripheral-arterial-disease-paclitaxel-coated-balloons-and-paclitaxel-eluting.
---------------------------------------------------------------------------

    The FDA stated that the data should be interpreted with caution for 
several reasons. First, there is large variability in the risk estimate 
of mortality due to the limited amount of long-term data. Second, the 
studies were not originally designed to be pooled, introducing greater 
uncertainty in the results. Third, the specific cause and mechanism of 
the increased mortality is unknown.
    Based on the preliminary review of available data, the FDA made the 
following recommendations regarding the use of paclitaxel-coated 
balloons and paclitaxel-eluting stents: That health care providers 
consider the following until further information is available; continue 
diligent monitoring of patients who have been treated with paclitaxel-
coated balloons and paclitaxel-eluting stents; when making treatment 
recommendations and as part of the informed consent process, consider 
that there may be an increased rate of long-term mortality in patients 
treated with paclitaxel-coated balloons and paclitaxel-eluting stents; 
discuss the risks and benefits of all available PAD treatment options 
with your patients; for most patients, alternative treatment options to 
paclitaxel-coated balloons and paclitaxel-eluting stents should 
generally be used until additional analysis of the safety signal has 
been performed; for some individual patients at particularly high risk 
for restenosis, clinicians may determine that the benefits of using a 
paclitaxel-coated product may outweigh the risks; ensure patients 
receive optimal medical therapy for PAD and other cardiovascular risk 
factors as well as guidance on healthy lifestyles including weight 
control, smoking cessation, and exercise.
    The FDA further stated that paclitaxel-coated balloons and stents 
are known to improve blood flow to the legs and decrease the likelihood 
of repeat procedures to reopen blocked blood vessels. However, because 
of this concerning safety signal, the FDA stated that it believes 
alternative treatment options should generally be used for most 
patients while the FDA continues to further evaluate the increased 
long-term mortality signal and its impact on the overall benefit-risk 
profile of these devices. The FDA stated it intends to conduct 
additional analyses to determine whether the benefits continue to 
outweigh the risks for approved paclitaxel-coated balloons and 
paclitaxel-eluting stents when used in accordance with their 
indications for use. The FDA stated it will also evaluate whether these 
analyses impact the safety of patients treated with these devices for 
other indications, such as treatment of arteriovenous access stenosis 
or critical limb ischemia.
    Because of concerns regarding this issue, the FDA convened an 
Advisory Committee meeting of the Circulatory System Devices Panel on 
June 19-20, 2019 to: Facilitate a public, transparent, and unbiased 
discussion on the presence and magnitude of a long-term mortality 
signal; discuss plausible reasons, including any potential biological 
mechanisms, for a long-term mortality signal; re-examine the benefit-
risk profile of this group of devices; consider modifications to 
ongoing and future US clinical trials evaluating devices containing 
paclitaxel, including added surveillance, updated informed consent, and 
enhanced adjudication for drug-related adverse events and deaths; and 
guide other regulatory actions, as needed. The June 19-20, 2019 
Advisory Committee meeting of the Circulatory System Devices Panel 
concluded that analyses of available data from FDA-approved devices 
show an increase in late mortality (between two and five years) 
associated with paclitaxel-coated devices intended to treat 
femoropopliteal disease. However, causality for the late mortality rate 
increase could not be determined. Additional data may be needed to 
further assess the magnitude of the late mortality signal, determine 
any potential causes, identify patient sub-groups that may be at 
greater risk, and to update benefit-risk considerations of this device 
class.\87\
---------------------------------------------------------------------------

    \87\ https://www.fda.gov/advisory-committees/advisory-committee-calendar/june-19-20-2019-circulatory-system-devices-panel-medical-devices-advisory-committee-meeting#event-materials.
---------------------------------------------------------------------------

    The FDA continues to recommend that health care providers report 
any adverse events or suspected adverse events experienced with the use 
of paclitaxel-coated balloons and paclitaxel-eluting stents. The FDA 
stated that it will keep the public informed as any new information or 
recommendations become available.
    After consideration of the public comments we received and the 
latest available information from the FDA advisory panel, we note the 
FDA panel's preliminary review of the data that has identified a 
potentially concerning signal of increased long-term mortality in study 
subjects treated with paclitaxel-coated products compared to patients 
treated with uncoated devices. Additionally, since the FDA has stated 
that it believes alternative treatment options should generally be used 
for most patients while the FDA continues to further evaluate the 
increased long-term mortality signal and its impact on the overall 
benefit-risk profile of these devices, we remain concerned that we do 
not have enough information to determine that the EluviaTM 
device represents a substantial clinical improvement over existing 
technologies. Therefore, we are not approving the EluviaTM 
device for FY 2020 new technology add-on payments. We will monitor any 
new information or recommendations as they become available.
e. ELZONRISTM (tagraxofusp, SL-401)
    Stemline Therapeutics submitted an application for new technology 
add-on

[[Page 42232]]

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 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. The applicant submitted a request for 
approval for a unique ICD-10-PCS code for the administration of 
ELZONRISTM beginning in FY 2020 and was granted approval for 
the following procedure codes effective October 1, 2019: XW033Q5 
(Introduction of Tagraxofusp-erzs Antineoplastic into peripheral vein, 
percutaneous approach, new technology, group 5) and XW043Q5 
(Introduction of Tagraxofusp-erzs Antineoplastic into central vein, 
percutaneous approach, new technology group 5).
    As previously discussed, 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

[[Page 42233]]

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. In the proposed rule, we noted that, as 
explained 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 previously stated.
    As presented in the proposed rule and previously summarized, 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 invited public comments on 
whether ELZONRISTM is substantially similar to any existing 
technologies and whether ELZONRISTM meets the newness 
criterion.
    Comment: The applicant submitted a comment reiterating that 
ELZONRISTM is the first approved treatment for patients with 
BPDCN and the first approved CD123-targeted therapy.
    Response: Based on the applicant's comment and information 
submitted by the applicant as part of its FY 2020 new technology add-on 
payment application for ELZONRISTM, as discussed in the 
proposed rule (84 FR 19319) and previously summarized, we believe that 
ELZONRISTM has a unique mechanism of action and the use of 
the technology would treat a new patient population. Therefore, we 
believe ELZONRISTM is not substantially similar to existing 
treatment options and meets the newness criterion. We consider the 
beginning of the newness period to commence when ELZONRISTM 
was approved by the FDA on December 21, 2018.
    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 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. In the proposed rule, 
we noted 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

[[Page 42234]]

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 further noted 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 ELZONRIS\TM\ in both 
scenarios. To determine the charges for ELZONRIS\TM\, the applicant 
calculated the average per discharge cost of ELZONRIS\TM\ 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 ELZONRIS\TM\ 
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 this table:
[GRAPHIC] [TIFF OMITTED] TR16AU19.143

    In the proposed rule, we noted that the applicant used the proposed 
rule values to inflate the standardized charges. However, we further 
noted 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 invited public comments on whether 
ELZONRIS\TM\ meets the cost criterion.
    We did not receive any public comments on whether ELZONRIS\TM\ 
meets the cost criterion. Based on the information submitted by the 
applicant as part of its FY 2020 new technology add-on payment 
application for ELZONRIS\TM\, as discussed in the proposed rule (84 FR 
19319 through 19320) and previously summarized, the average case-
weighted standardized charge per case exceeded the average case-
weighted threshold amount. Therefore, ELZONRIS\TM\ meets the cost 
criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant stated that it believes ELZONRIS\TM\ represents a substantial 
clinical improvement because: (1) ELZONRIS\TM\ 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) 
ELZONRIS\TM\ offers a treatment option for a patient population 
ineligible for aggressive chemotherapy regimens used to treat BPDCN; 
(3) ELZONRIS\TM\ exhibits high complete remission rates, potentially 
superior to other regimens used to treat a diagnosis of BPDCN; (4) 
ELZONRIS\TM\ significantly improves overall survival (OS) in the 
treatment of patients diagnosed with BPDCN as compared to currently 
available treatment regimens; (5) ELZONRIS\TM\ 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) 
ELZONRIS\TM\ 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) ELZONRIS\TM\ 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 ELZONRIS\TM\ 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.\88\
---------------------------------------------------------------------------

    \88\ 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 ELZONRIS\TM\ 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; 
\89\ however, the applicant noted

[[Page 42235]]

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.\90\
---------------------------------------------------------------------------

    \89\ 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.
    \90\ 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.
---------------------------------------------------------------------------

    Third, the applicant maintained that ELZONRIS\TM\ 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.\91\ The applicant reported prospective clinical 
trial data from ELZONRIS\TM\'s pivotal trial (ELZONRIS\TM\ 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).\92\
---------------------------------------------------------------------------

    \91\ 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.
    \92\ 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 ELZONRIS\TM\ 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.\93\ The applicant reported 
prospective clinical trial data from ELZONRIS\TM\'s pivotal trial 
(ELZONRIS\TM\ 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].\94\
---------------------------------------------------------------------------

    \93\ 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.
    \94\ 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.\95\ 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.\96\ 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.\97\ The applicant 
submitted a 2010 retrospective study of BPDCN cases in which only 10 
out of 47 patients (21 percent) received SCT.\98\ 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.\99\ 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-naive patients treated with ELZONRISTM 
(12 [mu]g/kg/day) were bridged to SCT in remission.\100\
---------------------------------------------------------------------------

    \95\ 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.
    \96\ 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.
    \97\ 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.
    \98\ 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.
    \99\ 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.
    \100\ 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 [mu]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.\101\
---------------------------------------------------------------------------

    \101\ 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

[[Page 42236]]

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.\102\
---------------------------------------------------------------------------

    \102\ 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.
---------------------------------------------------------------------------

    After reviewing the information submitted by the applicant as part 
of its FY 2020 new technology add-on payment application for 
ELZONRISTM, in the FY 2020 IPPS/LTCH PPS proposed rule, we 
stated we were 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 stated that we 
were unsure if the study populations in the 2013 retrospective study 
that the applicant used to compare remission rates are composed of 
treatment-naive, 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 ELZONRISTM 
demonstrated high response rates in BPDCN, including: 90 percent 
overall response in treatment naive patients (26/29) and 69 percent 
overall response in relapse/refractory patients (9/13); 72 percent 
complete response plus complete clinical response in treatment naive 
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).\103\ However, we stated that we were 
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 noted that because 
the clinical trial is ongoing and the final outcomes are not available, 
we stated we were concerned that there may not be enough information on 
the efficacy to determine substantial clinical improvement at this 
time. We also noted that the applicant's December 2018 New Technology 
Town Hall meeting presentation included information that differs 
slightly from the application materials, and we were not clear whether 
the study results submitted with the application reflect the most 
current information available. We invited public comments on whether 
ELZONRISTM meets the substantial clinical improvement 
criterion, including with respect to the concerns we have raised.
---------------------------------------------------------------------------

    \103\ 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.
---------------------------------------------------------------------------

    Comment: The applicant submitted comments in response to CMS's 
concerns in the proposed rule regarding whether ELZONRISTM 
meets the substantial clinical improvement criterion.
    With respect to the concern that some of the evidence submitted by 
the applicant to demonstrate substantial clinical improvement over 
existing technologies is based on preclinical studies, the applicant 
stated that at the time of the new technology add-on payment 
application submission (December 2018), the peer reviewed publications 
of ELZONRISTM (tagraxofusp-erzs) included preclinical 
studies by Angelot-Delettre (2015) and Delettre (2013) and initial 
prospective evidence of the clinical activity of ELZONRISTM 
in patients with BPDCN (Frankel 2014). The applicant stated that since 
the new technology add-on payment application submission, 
ELZONRISTM was approved by the FDA for the treatment of 
BPDCN in adults and pediatric patients two years and older on December 
21, 2018, and the efficacy and safety data from the pivotal study of 
ELZONRISTM that formed the basis for the FDA approval was 
published in the April 25th issue of the New England Journal of 
Medicine (NEJM). The applicant stated that Study STML-401-0114 
(ELZONRISTM BPDCN Clinical Trial), the subject of the NEJM 
article, was a multicenter, multistage study of ELZONRISTM 
in patients with BPDCN and the largest prospective clinical trial 
designed to evaluate outcomes in patients with BPDCN. The applicant 
submitted the 2019 study as part of its comment, which reported that 
among the 29 previously untreated patients receiving 
ELZONRISTM at a dose of 12 [micro]g/kg/day, the overall 
response rate was 90 percent, 72 percent (21/29) achieved a complete 
response plus a complete clinical response, and 45 percent (13/29) 
bridged to SCT. Survival rates at 18 and 24 months were 59 percent and 
52 percent, respectively. Among the 15 previously-treated patients, the 
overall response rate was 67 percent, and the median overall survival 
was 8.5 months. The study concluded that in adult patients with 
untreated or relapsed BPDCN, the use of ELZONRISTM led to 
clinical responses, though serious adverse events were common.\104\
---------------------------------------------------------------------------

    \104\ Pemmaraju, N., et al., ``Tagraxofusp in Blastic 
Plasmacytoid Dendritic-Cell Neoplasm.'' N Engl J Med. 2019, doi: 
10.1056/NEJMoa1815105.
---------------------------------------------------------------------------

    With respect to the concern that we were 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, the applicant stated that the 
2013 Pagano et al. study was a multi-center retrospective study that 
evaluated 43 treatment-na[iuml]ve BPDCN patients from 2005-2011 who 
received traditional chemotherapy. The applicant noted that the results 
included 41 percent of patients achieving a CR; a median overall 
survival of 8.7 months, and 14 percent of patients bridged to receive a 
SCT.\105\ In contrast, the ELZONRISTM clinical trial 
consisted of a mix of patients (N=47), of which 32 were receiving 
ELZONRISTM as first-line treatment. The applicant stated 
that among the 29 treatment-naive patients who received ELZONRIS at a 
dose of 12 mcg/kg, 72 percent of patients (21/29) achieved a CR; 
survival rates at 18 and 24 months were 59 percent and 52 percent, 
respectively; and 45 percent of patients (13/29) bridged to receive a 
SCT.\106\
---------------------------------------------------------------------------

    \105\ 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.
    \106\ Pemmaraju, N., et al., ``Tagraxofusp in Blastic 
Plasmacytoid Dendritic-Cell Neoplasm.'' N Engl J Med. 2019, doi: 
10.1056/NEJMoa1815105.
---------------------------------------------------------------------------

    With respect to the concern that the small number of patients in 
the clinical trial 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, the applicant stated that BPDCN is a very rare and highly 
aggressive hematologic malignancy, with an estimated incidence of 0.41/
1,000,000 patients age-adjusted to the 2000 US standard population, 
corresponding to less than 100 new cases per year. The applicant stated 
that the ELZONRISTM BPDCN Clinical Trial was the first study 
prospectively designed to assess the safety and efficacy of a therapy 
in patients with BPDCN, including a pre-defined cohort for confirmation 
of

[[Page 42237]]

efficacy. The applicant stated that to date, it is considered the 
largest prospective study of patients with BPDCN ever conducted (N=47); 
a cohort that is sizeable and adequately represents the `real-world' 
population in terms of demographics and baseline characteristics. The 
applicant stated that as such, this study, for the first time, provided 
prospectively acquired data for any therapy in this patient population 
and are therefore considered to be more robust and reliable than 
previously reported retrospective data. The applicant stated further 
that in the absence of available therapies for patients with BPDCN, 
empirical chemotherapies have been employed in the past for both 
treatment-na[iuml]ve and previously treated BPDCN, and the published 
literature regarding BPDCN treatment consists primarily of case reports 
and retrospective data reviews with limited published data from 
prospective clinical studies. The applicant stated that the accuracy 
and ability to interpret the response rates reported in the literature 
is limited, given the general lack of well-defined response criteria, 
especially related to measurement of the extent of cutaneous disease 
and other extramedullary sites of disease. As such, the applicant 
stated that published response rates should be viewed with caution and 
may represent artificially high response rates in some instances.
    With respect to the concern that there may not be enough 
information on the efficacy of ELZONRISTM to determine 
substantial clinical improvement at this time given that the clinical 
trial is ongoing and the final outcomes are not available, the 
applicant stated that FDA approval was based on the efficacy and safety 
results from the ELZONRISTM BPDCN Clinical Trial in patients 
with treatment-naive or previously treated BPDCN. The applicant 
explained that the clinical trial was a multi-stage study, with each 
study stage featuring its own objectives and design elements. The 
applicant stated that Stage 1 (dose escalation), Stage 2 (expansion), 
and Stage 3 (pivotal, confirmatory for efficacy) are complete and the 
results were published in the NEJM on April 25th, 2019. The applicant 
stated that patients were also enrolled in an additional cohort (Stage 
4) to enable ongoing access to ELZONRISTM in a clinical 
study.
    With respect to the concern that the applicant's December 2018 New 
Technology Town Hall meeting presentation included information that 
differs slightly from the application materials, and we were not clear 
whether the study results submitted with the application reflect the 
most current information available, the applicant stated that the most 
current ELZONRISTM data was reported by Pemmaraju and 
colleagues and published in the April 25th, 2019 issue of the 
NEJM,\107\ and the applicant submitted a copy of the article as part of 
its comment.
---------------------------------------------------------------------------

    \107\ Ibid.
---------------------------------------------------------------------------

    Response: We appreciate the additional information and analysis 
provided by the applicant and the applicant's input in response to our 
concerns regarding substantial clinical improvement. After reviewing 
the information submitted by the applicant addressing our concerns 
raised in the proposed rule, we agree with the applicant that 
ELZONRISTM represents a substantial clinical improvement 
over existing technologies because, based on the information provided 
by the applicant, the technology offers a treatment option for a 
patient population unresponsive to, or ineligible for, currently 
available treatments and substantially improves response rates and 
clinical outcomes for patients with BPDCN.
    After consideration of the public comments we received, we have 
determined that ELZONRISTM meets all of the criteria for 
approval for new technology add-on payments. Therefore, we are 
approving new technology add-on payments for ELZONRISTM for 
FY 2020. Cases involving the use of ELZONRISTM that are 
eligible for new technology add-on payments will be identified by ICD-
10-PCS procedure codes XW033Q5 and XW043Q5.
    In its application, the applicant stated that ELZONRISTM 
is supplied as a non-preserved, sterile, single-use liquid dosage in 2 
mL glass vials containing 1 mL of solution at a concentration of 1 mg/
mL (1 mg/vial). It is administered by intravenous infusion at 
12[micro]g/kg/day over 15 minutes once daily on days 1-5 of a 21 day 
cycle. The dosing period may be extended for dose delays up to day 10 
of the cycle. The applicant stated that the first administration cycle 
should occur in the inpatient setting; subsequent cycles may be 
administered in the inpatient or appropriate outpatient setting. The 
applicant stated that in clinical studies, roughly 70 percent of 
treatment-naive patients received 2 vials per dose (the remaining 
patients received 1 vial per dose). Relapsed/refractory patients were 
more likely to have 1 vial per dose (70 percent vs. 30 percent). In 
all, about 70 percent of patients are treatment naive, and 30 percent 
are relapsed/refractory. Using this information, the applicant 
calculated that the average inpatient hospitalization would require 7.9 
vials. According to the applicant, the WAC per vial is $24,430. 
Therefore, the average total cost of ELZONRISTM per patient 
is $192,997. Under Sec.  412.88(a)(2) (revised as discussed in this 
final rule), we limit new technology add-on payments to the lesser of 
65 percent of the costs of the new medical service or technology, or 65 
percent of the amount by which the costs of the case exceed the MS-DRG 
payment. As a result, the maximum new technology add-on payment for a 
case involving the use of ELZONRISTM is $125,448.05 for FY 
2020. (As discussed in section II.H.9. of the preamble of this final 
rule, we are revising the maximum new technology add-on payment to 65 
percent, or 75 percent for certain antimicrobial products, of the 
average cost of the technology.)
f. BalversaTM (Erdafitinib)
    Johnson & Johnson Health Care Systems, Inc. (on behalf of Janssen 
Oncology, Inc.) submitted an application for new technology add-on 
payments for BalversaTM for FY 2020. BalversaTM 
is indicated for 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, BalversaTM 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. 
BalversaTM is a pan-fibroblast FGFR inhibitor with potential 
antineoplastic activity. Upon oral administration, 
BalversaTM 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,

[[Page 42238]]

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).\108\ 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.
---------------------------------------------------------------------------

    \108\ 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 believed to have immunologically ``cold tumors'' that are less 
likely to benefit from PD-1 blockade therapy.
    The applicant noted that BalversaTM 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. 
BalversaTM received accelerated FDA approval on April 12, 
2019. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19322), we 
noted that the applicant 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 BalversaTM. BalversaTM was 
granted approval for the ICD-10-PCS procedure code XW0DXL5 
(Introduction of Erdafitinib Antineoplastic into Mouth and Pharynx, 
External Approach, New Technology Group 5), with an effective date of 
October 1, 2019.
    As previously discussed, 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 BalversaTM is not substantially 
similar to any existing treatment options because its inhibitory 
mechanism of action is novel. Specifically, the applicant stated that 
BalversaTM is a pan-fibroblast FGFR inhibitor with potential 
antineoplastic activity. Upon oral administration, 
BalversaTM 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 
BalversaTM 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, BalversaTM 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 
BalversaTM are likely to be assigned to a wide variety of 
MS-DRGs because patients who may receive treatment involving 
BalversaTM 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 BalversaTM 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 BalversaTM 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 
BalversaTM is specific to a subset of patients with certain 
FGFR-genetic alterations. Therefore, the applicant believes that 
BalversaTM treats a different patient population than 
currently available treatments.
    We invited public comments on whether BalversaTM is 
substantially similar to any existing technology and whether it meets 
the newness criterion.
    Comment: The applicant noted that CMS did not object to the 
assertion that BalversaTM meets the newness criterion 
because BalversaTM is not substantially similar to existing 
technologies and because it is the first drug with its mechanism of 
action approved by the FDA.
    Response: We agree with the applicant that BalversaTM 
meets the newness criterion. We agree that BalversaTM is not 
substantially similar to existing treatment options because it has a 
unique mechanism of action. We consider April 12, 2019 as the beginning 
of the newness period for BalversaTM.
    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 
BalversaTM. 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 BalversaTM, it is 
unlikely that the administration of BalversaTM would be 
initiated during an inpatient hospitalization. In addition, the 
applicant assumed that most hospitals would not utilize 
BalversaTM 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 
BalversaTM and calculated the drug's costs on a case-by-case 
basis, multiplying the length-of-stay times the cost of the drug.

[[Page 42239]]

    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 this 
table.
[GRAPHIC] [TIFF OMITTED] TR16AU19.144

    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 this table to identify a combination of applicable 
codes.
[GRAPHIC] [TIFF OMITTED] TR16AU19.145

    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 this table.

[[Page 42240]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.146

[GRAPHIC] [TIFF OMITTED] TR16AU19.147

    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 Balversa\TM\ 
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). (In the proposed rule, we noted 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 further noted 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 Balversa\TM\ would 
exceed the average case-weighted threshold amount.) The applicant then 
added the charges for the cost of Balversa\TM\. To determine the 
charges for the cost of Balversa\TM\, 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 Balversa\TM\ meets the cost criterion because the 
final inflated average case-weighted standardized charge per case 
exceeds the average case-weighted threshold amount. We invited public 
comments on whether Balversa\TM\ meets the cost criterion.
    Comment: The applicant submitted a comment stating that CMS did not 
object to its assertion that BalversaTM meets the cost 
criterion. The applicant also submitted an updated analysis. The 
applicant stated that in the analysis presented to CMS for the proposed 
rule, the average case-weighted threshold amount was $62,435 and the 
final inflated average case-weighted standardized charge per case was 
$111,713. After BalversaTM received FDA approval, the 
analysis was updated with charges added to reflect the wholesale 
acquisition cost for BalversaTM, resulting in a final 
inflated average case-weighted standardized charge per case $109,211. 
The applicant noted that this remains above the case-weighted threshold 
amount of $62,435 and that BalversaTM therefore continues to 
meet the cost criterion.
    Response: We appreciate the additional information provided by the 
applicant regarding whether BalversaTM meets the cost 
criterion. We agree that BalversaTM meets the cost 
criterion.
    The applicant asserted that BalversaTM represents a 
substantial clinical improvement over existing technologies because it 
offers a

[[Page 42241]]

treatment option for a patient population unresponsive to or ineligible 
for currently available treatments. The applicant stated that 
BalversaTM 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 BalversaTM 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 
BalversaTM 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 BalversaTM in the target patient population for 
which the applicant asserts BalversaTM 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 BalversaTM ranging from 0.5 mg to 
12 mg, administered continuously daily, or oral doses of 
BalversaTM 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 
BalversaTM 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 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.109 110
---------------------------------------------------------------------------

    \109\ 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.
    \110\ 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.
    In the proposed rule, we stated that we have the following concerns 
with regard to whether the technology meets the substantial clinical 
improvement criterion. First, we stated that the applicant did not 
provide substantial data comparing BalversaTM 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 stated we have concerns that we may not have enough 
information to determine if BalversaTM represents a 
substantial clinical improvement over existing technologies.
    We invited public comments on whether BalversaTM meets 
the substantial clinical improvement criterion.
    Comment: The applicant submitted a comment in response to CMS' 
concerns about the limited nature of available data. The applicant 
referenced the Phase II study (n=87) previously detailed in the 
proposed rule. The applicant stated that an objective response rate 
(ORR) of 32.2 percent (95 percent confidence interval [CI]: 22.4-42.0) 
was observed. The applicant also noted that among the majority of 
patients (n=64) enrolled with FGFR 3 point mutations, the ORR was 40.6 
percent (95 percent CI: 28.6-52.7).
    In response to CMS' concern about the lack of comparison of 
BalversaTM to existing therapies, the applicant stated that 
in the absence of head-to-head data, effectiveness comparisons can be 
made based on approved therapies in metastatic urothelial carcinoma for 
which BalversaTM is approved. Per the applicant, FDA-
approved systemic therapies for locally advanced or mUC following 
platinum-based chemotherapy include KEYTRUDA[supreg] (pembrolizumab), 
TECENTRIQ[supreg] (atezolizumab), BAVENCIO[supreg] (avelumab), 
IMFINZI[supreg] (durvalumab), and OPDIVO[supreg] (nivolumab). The 
applicant noted that of the five approved checkpoint inhibitors, 
pembrolizumab observed the highest ORR of 21 percent in their 
registration trial.\111\ Furthermore, the applicant noted that in the 
United States, docetaxel is an acceptable systemic chemotherapy 
following progression after platinum-based chemotherapy. The applicant 
stated that although docetaxel is not approved for the treatment of mUC 
in the US, a Phase 2 study conducted in 30 patients demonstrated a 
partial response in 4 (13.3 percent) patients.\112\
---------------------------------------------------------------------------

    \111\ KEYTRUDA[supreg] (pembrolizumab injection) [package 
insert]. Whitehouse Station, NJ: Merck Sharp & Dohme Corp.; April 
2019.
    \112\ McCaffrey JA, Hilton S, Mazumdar M, et al. Phase 2 trial 
of docetaxel in patients with advanced or metastatic transitional-
cell carcinoma. J Clin Oncol. 1997;15(5):1853-1857.
---------------------------------------------------------------------------

    Response: We appreciate the additional information and analysis 
provided by the applicant in response to our concerns regarding 
substantial clinical improvement, including the additional information 
on data trends supporting an improved ORR for BalversaTM 
when compared to other FDA approved medications. We note that in the 
cited study regarding the ORR for pembrolizumab, ORRs of 33 percent and 
21 percent were achieved in two separate efficacy randomized trials 
with sample sizes of 834 and 540 respectively.\113\ These are 
independent

[[Page 42242]]

studies with varying sample and study characteristics and lacking 
unifying statistical testing. However, in light of the severity of the 
disease and patient population with limited treatment options, and the 
results provided by the applicant from its Phase II study, which 
featured an objective response rate of 40.4 percent, a disease control 
of 79.8 percent, and a median progression-free survival of 5.5 months, 
we agree with the applicant that Balversa\TM\ meets the substantial 
clinical improvement criterion.
---------------------------------------------------------------------------

    \113\ KEYTRUDA[supreg] (pembrolizumab injection) [package 
insert]. Whitehouse Station, NJ: Merck Sharp & Dohme Corp.; April 
2019.
---------------------------------------------------------------------------

    After consideration of the public comment we received, we have 
determined that BalversaTM meets all of the criteria for 
approval of new technology add-on payments. Therefore, we are approving 
new technology add-on payments for BalversaTM for FY 2020. 
Cases involving BalversaTM that are eligible for new 
technology add-on payments will be identified by ICD-10-PCS procedure 
code XW0DXL5. In its application, the applicant stated that 
BalversaTM will be supplied as 3 mg, 4 mg and 5 mg tablets 
with a recommended starting dose of 8 mg daily. According to the 
applicant, the WAC for one dose of BalversaTM is $613.20 per 
day for an average duration of 8.9 days. Therefore, the total cost of 
BalversaTM per patient is $5,481.89. Under Sec.  
412.88(a)(2) (revised as discussed in this final rule), we limit new 
technology add-on payments to the lesser of 65 percent of the costs of 
the new medical service or technology, or 65 percent of the amount by 
which the costs of the case exceed the MS-DRG payment. As a result, the 
maximum new technology add-on payment for a case involving the use of 
BalversaTM is $3,563.23 for FY 2020.
g. 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.\114\ 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.\115\ 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).\116\ The U.S. 
incidence of nmCRPC is estimated to be 50,000 to 60,000 cases per 
year.\117\
---------------------------------------------------------------------------

    \114\ American Cancer Society. https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/cancer-facts-figures-2019.html
    \115\ Dai, C., Heemers, H., Sharifi, N., ``Androgen signaling in 
prostate cancer,'' Cold Spring Harb Perspect Med, 2017, vol. 7(9), 
pp. a030452.
    \116\ 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.
    \117\ 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. In the FY 2020 
IPPS/LTCH PPS proposed rule (84 FR 19325), we noted that the applicant 
submitted a request for approval for a unique ICD-10-PCS code for the 
administration of ERLEADATM beginning in FY 2020. Approval 
was granted for the following procedure code effective October 1, 2019: 
XW0DXJ5 (Introduction of Apalutamide Antineoplastic into Mouth and 
Pharynx, External Approach, New Technology Group 5).
    As previously discussed, 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.\118\ 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.
---------------------------------------------------------------------------

    \118\ 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 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

[[Page 42243]]

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.119 120 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.
---------------------------------------------------------------------------

    \119\ 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.
    \120\ 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 noted in the proposed rule and previously summarized, 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 invited public comments on whether 
ERLEADATM meets the newness criterion.
    Comment: The applicant commented that CMS did not express concern 
about the newness criterion, and reiterated that ERLEADATM 
is not substantially similar to existing technologies and qualifies as 
new because it was the first drug with its mechanism of action approved 
by the FDA to treat patients with nmCRPC.
    Response: We agree that ERLEADATM is not substantially 
similar to existing technologies and that it meets the newness 
criterion because it was the first drug with its mechanism of action 
approved by the FDA to treat patients with nmCRPC. We consider February 
14, 2018 as the beginning of the newness period for 
ERLEADATM.
    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 meoplasm 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 these two code combinations. 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. In the proposed rule, we 
noted 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).
    In the proposed rule, we noted that the applicant used the proposed 
rule values to inflate the previously discussed standardized charges. 
However, we further noted 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

[[Page 42244]]

invited public comments on whether ERLEADATM meets the cost 
criterion.
    Comment: The applicant commented that the average case-weighted 
standardized charge per case was above the average case-weighted 
threshold amount in both the initial and second analysis.
    Response: We agree that 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 randomized Phase III 
SPARTAN trial,\121\ including significant improvement in metastasis-
free survival (MFS).
---------------------------------------------------------------------------

    \121\ 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 \122\ 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.
---------------------------------------------------------------------------

    \122\ 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; P<0.0001). In 
other words, ERLEADATM 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; 
P<0.0001). The treatment effect of ERLEADATM 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 P<0.001) for ERLEADATM 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, P<0.001). In addition, time to bone 
metastasis and nodal metastasis in particular were both significantly 
longer (P<0.0001) in the ERLEADATM 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 (P<0.001). In a multi-variate analysis of 
patients treated in the SPARTAN study, treatment with 
ERLEADATM was an independent predictor for longer time to 
symptomatic progression (reached versus not reached; P<0.001).
    The applicant also included the results of additional secondary 
endpoints for CMS consideration as evidence of substantial clinical 
improvement, including a suggested overall survival (OS) benefit; 
demonstrated safety profile; maintained quality of life; and decreased 
prostate specific antigen (PSA) levels.
    While OS data were not mature at the time of final MFS analysis 
(only 24 percent of the required number of OS events were available for 
analysis), the applicant asserted that OS results suggested a benefit 
of treatment using ERLEADATM 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,

[[Page 42245]]

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 initiation of the 
use of ERLEADATM.\123\ 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.
---------------------------------------------------------------------------

    \123\ 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<0.0001). Overall, 
a >=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.
    In the proposed rule, we stated that we had the following concerns 
regarding the applicant's assertions of substantial clinical 
improvement:
     Regarding the SPARTAN trial design, we stated we were 
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,\124\ 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 stated that we were 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.\125\ Additionally, we noted 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.
---------------------------------------------------------------------------

    \124\ 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), Available at: www.cdc.gov/cancer/dataviz, June 2018.
    \125\ 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. In the proposed rule, we 
welcomed 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 noted 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. In the proposed rule, we stated that 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 stated in the proposed rule that we had 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 noted 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.\126\ 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

[[Page 42246]]

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.\127\ 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, P<0.0001; and Kendall [tau] 
statistic = 0.52, parametric Fleischer's statistical model correlation 
coefficient of 0.69 (standard error, 0.002; 95 percent CI: 0.69-0.70)).
---------------------------------------------------------------------------

    \126\ ICECaP Working Group, Sweeney, C., Nakabayashi, M., et 
al., ``The development of intermediate clinical endpoints in cancer 
of the prostate (ICECaP)'', J Natl Cancer Inst, 2015, vol. 107(12), 
pp. djv261
    \127\ Li S., Ding Z, Lin J.H., et al., ``Association of 
prostate-specific antigen (PSA) trajectories with risk for 
metastasis and mortality in nonmetastatic castration-resistant 
prostate cancer (nmCRPC),'' Abstract presented at: 2018 
Genitorurinary Cancers Symposium, February 8-10, 2018, San 
Francisco, CA.
---------------------------------------------------------------------------

    We invited public comments on whether ERLEADATM meets 
the substantial clinical improvement criterion for patients who have 
been diagnosed with nmCRPC.
    Comment: The applicant submitted comments in response to concerns 
about the applicability of the data from the SPARTAN study to the US 
population, including African-American patients. The applicant stated 
that ERLEADATM treatment benefit was evaluated by region 
(North America, Europe, Asia-Pacific), and the treatment effect showing 
benefit from ERLEADATM in each region was consistent with 
the overall population. Also, the applicant pointed to the additional 
data summarized in the proposed rule (84 FR 19328) supplied in response 
to this concern, and reiterated that analyses by race also indicate 
that the SPARTAN study results are generalizable to the US patient 
population with nmCRPC, including African-Americans.
    The applicant also responded to our request for additional 
explanation of how those that withdrew were considered in the analysis 
and the potential impact of withdrawals on the study results. According 
to the applicant, the small proportion of subjects who withdrew consent 
for the study are not expected to affect the analysis' conclusions; all 
subjects randomized to treatment were included in the Intention-to-
Treat analysis for efficacy, including subjects who withdrew consent. 
The applicant stated that only 1.7 percent (n = 14) of subjects in the 
ERLEADATM group and 2.7 percent (n = 11) of subjects in the 
placebo group were censored due to withdrawal of consent, and that 
small proportion is not expected to impact the conclusion of the MFS 
analysis.
    Finally, in response to our concern about the SPARTAN study primary 
endpoint, MFS, the applicant submitted information to demonstrate that 
MFS is accepted as a study endpoint by the FDA and the oncologic 
community. The applicant described draft guidance from the FDA \128\ as 
stating that the prolonged disease course and assessment period for 
patients with nmCRPC may make the use of overall survival (OS) 
impractical as a primary endpoint to support approval of treatments, 
and that endpoints that can be measured earlier in the course of 
disease, including MFS, are useful and clinically relevant assessments.
---------------------------------------------------------------------------

    \128\ Center for Drug Evaluation and Research (CDER) & Center 
for Biologics Evaluation and Research (CBER). Nonmetastatic, 
Castration-Resistant Prostate Cancer: Considerations for Metastasis-
Free Survival Endpoint in Clinical Trials Guidance for Industry 
DRAFT GUIDANCE; 2018. https://www.fda.gov/regulatory-information/search-fda-guidancedocuments/nonmetastatic-castration-resistant-prostate-cancer-considerations-metastasis-free-survival-endpoint. 
Accessed June 1, 2019.
---------------------------------------------------------------------------

    Additionally, the applicant commented further on the clinical 
relevance of MFS and the correlation of metastasis with morbidity and 
the need for additional medical interventions. The applicant discussed 
the International Clinical Endpoints for Cancer of the Prostate 
(ICECaP) Working Group's review of 19 randomized controlled trials 
evaluating 21 study units in 12,712 patients with localized prostate 
cancer, in which 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]. At the trial level, R 2 was 0.83 (95 percent CI: 0.71-0.88) from 
weighted linear regression of 8-year OS rates vs 5-year MFS rates. The 
applicant asserted that the treatment effect (measured by log HR) for 
MFS and OS was well correlated (R2, 0.92 [95 percent CI: 0.81-
0.95]).\129\ The applicant also referred to the study of an electronic 
health record database in patients with nmCRPC in which MFS 
independently predicted mortality risk: 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.\130\ The applicant also stated 
that the correlational analysis between MFS and OS in patients with 
nmCRPC included in the SPARTAN study showed that patients who developed 
metastases at 6, 9, and 12 months had significantly shorter median OS 
compared with those patients without metastasis. Finally, the applicant 
commented that the clinical benefit of MFS was further supported by an 
analysis of the SPARTAN study performed after one year of additional 
follow up, which assessed the time from randomization to the start of 
the next subsequent therapy after discontinuation of the study 
medication, known as second progression free survival (PFS2). According 
to the applicant, that analysis supported treating patients with nmCRPC 
with ERLEADATM provides a significantly longer response than 
ADT alone followed by a second therapy and support treatment of these 
patients with ERLEADATM.
---------------------------------------------------------------------------

    \129\ Xie W., Regan M.M., Buyse M., et al. Metastasis-free 
survival is a strong surrogate of overall survival in localized 
prostate cancer. J Clin Oncol. 2017;35(27):3097-3104.
    \130\ Li S., Ding Z., Lin J.H., et al. Association of prostate-
specific antigen (PSA) trajectories with risk for metastasis and 
mortality in non- metastatic castration-resistant prostate cancer 
(nmCRPC). Abstract presented at: 2018 Genitorurinary Cancers 
Symposium; February 8-10, 2018; San Francisco, CA.
---------------------------------------------------------------------------

    Response: We appreciate the additional information and analysis 
provided by the applicant in response to our concerns regarding 
substantial clinical improvement. After reviewing the information 
submitted by the applicant addressing our concerns raised in the 
proposed rule, we agree that ERLEADATM represents a 
substantial clinical improvement because it significantly delays 
metastasis in patients with nmCRPC.
    After consideration of the public comment we received, we have 
determined that ERLEADATM meets all of the criteria for 
approval for new technology add-on payments. Therefore, we are 
approving new technology add-on payments for ERLEADATM for 
FY 2020. Cases involving the use of ERLEADATM that are 
eligible for new technology add-on payments will be identified by ICD-
10-PCS procedure code XW0DXJ5. In its application, the applicant 
estimated that the average Medicare beneficiary would require a dosage 
of 4 tablets per day. The applicant explained that the WAC is $10,920 
for a thirty day supply, or $91.00 per tablet. Typical dosage for 
ERLEADATM is 4 tablets per day, resulting in a daily cost of 
$364. Because the drug is administered daily, the cost to the hospital 
would depend on the patient's length of stay. The applicant's MedPAR 
analysis determined an average length of stay of approximately 7.854 
days. Multiplying the length of stay of 7.854 by the daily cost of $364 
resulted in an average cost per patient of $2,858.84. Under Sec.  
412.88(a)(2) (revised as discussed in this final rule), we limit new 
technology add-on payments to the lesser of 65 percent of the costs of 
the new medical service or technology, or 65 percent of

[[Page 42247]]

the amount by which the costs of the case exceed the MS-DRG payment. As 
a result, the maximum new technology add-on payment for a case 
involving the use of ERLEADATM is $1,858.25 for FY 2020.
h. 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.\131\ Although currently available anti-
depressants are effective for many of these patients, approximately 
one-third do not respond to treatment.\132\ 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.133 134 135
---------------------------------------------------------------------------

    \131\ World Health Organization. (2018, March). Depression. 
Available at: http://www.who.int/mediacentre/factsheets/fs369/en/.
    \132\ 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.
    \133\ 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.
    \134\ 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.
    \135\ 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.\136\
---------------------------------------------------------------------------

    \136\ 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 
the patient's self-administration of SPRAVATO under healthcare 
supervision 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 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 Nasal Spray was 
approved by the FDA with an effective date of March 5, 2019. In the FY 
2020 IPPS/LTCH PPS proposed rule (84 FR 19329), we noted that the 
applicant had submitted a request to the ICD-10 Coordination and 
Maintenance Committee for approval for a unique ICD-10-PCS procedure 
code to specifically identify cases involving the use of SPRAVATO, 
beginning in FY 2020. As of the time of the development of this final 
rule, a unique ICD-10-PCS procedure code to specifically identify cases 
involving the use of SPRAVATO has not yet been finalized in response to 
the applicant's request. Therefore, cases reporting SPRAVATO will be 
identified by ICD-10-PCS procedure code 3E097GC (Introduction of Other 
Therapeutic Substance into Nose, Via Natural or Artificial Opening) for 
FY 2020.
    As previously discussed, 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 is the 
first new approach in 30 years for the treatment of major depressive 
disorder, including treatment-resistant depression.137 138 
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.\139\
---------------------------------------------------------------------------

    \137\ 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.
    \138\ Dubovsky, S., ``What Is New about New Anti-depressants?,'' 
Psychotherapy and Psychosomatics, 2018, vol. 87(3), pp. 129-139, 
doi:10.1159/000488945.
    \139\ Sanacora, G., et. al., ``Targeting the Glutamatergic 
System to Develop Novel, Improved Therapeutics for Mood Disorders,'' 
Nat Rev Drug Discov., 2008, pp. 426-437.
---------------------------------------------------------------------------

    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 Nasal Spray would 
be assigned to the same MS-DRGs as patients who receive treatment 
involving currently available anti-depressants (AD).

[[Page 42248]]

    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 address 
the application of this criterion to SPRAVATO.
    We invited public comments on whether SPRAVATO is substantially 
similar to any existing technologies and whether it meets the newness 
criterion.
    Comment: The applicant submitted a public comment in response to 
the proposed rule. The applicant stated that SPRAVATO is not 
substantially similar to existing technologies and qualifies as new 
because it is the first new antidepressant mechanism of action in 
decades to treat Treatment Resistant Depression 
(TRD).140 141 The applicant stated that unlike existing 
pharmacotherapies for depression, the primary antidepressant activity 
of SPRAVATO is not believed to directly involve inhibition of 
serotonin, norepinephrine, or dopamine reuptake.142 143 144
---------------------------------------------------------------------------

    \140\ Duman R.S. Ketamine and rapid-acting antidepressants: A 
new era in the battle against depression and suicide. F1000Research. 
2018;7:F1000 Faculty Rev-659. doi:10.12688/f1000research.14344.1.
    \141\ Dubovsky S.L. What Is New about New Antidepressants? 
Psychotherapy and Psychosomatics. 2018;87(3):129-139. doi:10.1159/
000488945.
    \142\ Duman R.S., Li N., Liu R.J., et al. Signaling pathways 
underlying the rapid antidepressant actions of ketamine. 
Neuropharmacology. 2012;62(1):35-41.
    \143\ Duman R.S., Aghajanian G.K., Sanacora G., et al. Synaptic 
plasticity and depression: New insights from stress and rapid-acting 
antidepressants. Nat Med. 2016;22(3):238-249.
    \144\ Sanacora G., Zarate C.A., Krystal J.H., et al. Targeting 
the glutaminergic system to develop novel, improved therapeutics for 
mood disorders. Nat Rev Drug Discov. 2008;7(5):426-437.
---------------------------------------------------------------------------

    With regard to SPRAVATO treating the same or a similar disease or 
the same or similar patient population as existing technologies, the 
applicant reiterated that SPRAVATO treats, in conjunction with an oral 
antidepressant, TRD. According to the applicant, even with currently 
available antidepressant treatments, an estimated one-third of people 
in the U.S. who suffer with MDD fail to respond to treatment.\145\ The 
applicant stated that TRD has no universally accepted definition; 
however, one definition consists of those patients with major 
depressive disorder (MDD) who have not responded to at least two 
different antidepressants of adequate dose and duration in the current 
depressive episode.\146\
---------------------------------------------------------------------------

    \145\ Rush A.J., Trivedi M.H., Wisniewski S.R., et al. Acute and 
longer-term outcomes in depressed outpatients requiring one or 
several treatment steps: A STAR*D report. Am J Psychiatry. 
2006;163(11):1905-1917.
    \146\ AHRQ 2018
---------------------------------------------------------------------------

    Response: We appreciate the additional information provided by the 
applicant regarding whether SPRAVATO meets the newness criterion. After 
consideration of the public comments we received and information 
submitted by the applicant in its application, we believe that SPRAVATO 
uses a unique mechanism of action to achieve a therapeutic outcome 
because it works differently than currently available therapies, 
through glutamate receptor modulation rather than the inhibition of 
serotonin, norepinephrine, or dopamine reuptake. Therefore, we believe 
SPRAVATO is not substantially similar to existing treatment options and 
meets the newness criterion. We consider the beginning of the newness 
period to commence when SPRAVATO was approved by the FDA on March 5, 
2019.
    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. The applicant also 
assumed that hospitals would not allow administration of SPRAVATO 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 as previously 
described, 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 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.\147 148\
---------------------------------------------------------------------------

    \147\ 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.
    \148\ 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 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

[[Page 42249]]

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 previous analysis, in the FY 2020 IPPS/LTCH PPS 
proposed rule we stated that we were 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, we stated 
that it is unclear which cases representing patients should be removed. 
We further stated that 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. We noted in the proposed rule that, 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 invited public comments on this issue and whether the 
SPRAVATO Nasal Spray meets the cost criterion.
    Comment: The applicant submitted a comment in regard to our 
concerns on the cost criterion. The applicant reiterated that there are 
no ICD-10 codes with which to identify patients with TRD and about \1/
3\ of people with MDD have TRD. The applicant then stated that in its 
original cost analysis they found cases with diagnosis codes signifying 
MDD and randomly selected \1/3\ of those cases for the cost analysis. 
In response to CMS' concerns, the applicant updated the analysis 
selecting the \1/3\ of cases with the highest charges. This choice was 
made in response to a study comparing Medicare beneficiaries with TRD 
and Medicare beneficiaries without TRD which found that the cost of the 
inpatient hospitalizations for the TRD cohort were clearly higher 
(average $9,947 vs. $5,426).\149\ With this new sample selection the 
applicant performed the cost analysis using the inverse of the FY 2019 
pharmacy national average CCR of 0.191 to determine the charges for 
SPRAVATO, and a 2-year inflation factor of 1.08986 from the FY 2019 
IPPS final rule correction notice to inflate the charges from FY 2017 
to FY 2019. The applicant stated that with the new selection 
methodology, SPRAVATO meets the cost criterion, with an inflated 
average case-weighted standardized charge per case of $165,669 that 
exceeds the average case-weighted threshold amount of $74,682.
---------------------------------------------------------------------------

    \149\ Benson, C, Szukis, H. An Evaluation of Increased Clinical 
and Economic Burden Among Elderly Medicare-covered Beneficiaries 
With Treatment-Resistant Depression. Poster Presented at the Academy 
of Managed Care Pharmacy (AMCP) Annual Meeting; April 23-26, 2018; 
Boston, Massachusetts.
---------------------------------------------------------------------------

    Response: We appreciate the comment and additional information 
provided by the applicant. After consideration of the public comment we 
received, we agree that SPRAVATO meets the cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that SPRAVATO 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.\150\ According to the 
applicant, in addition to SPRAVATO, 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.\151\ In 
support of its assertions of substantial clinical improvement, the 
applicant provided several studies regarding SPRAVATO.
---------------------------------------------------------------------------

    \150\ 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.
    \151\ Cristancho, M., & Thase, M, ``Drug safety evaluation of 
olanzapine/fluoxetine combination,'' Expert Opinion on Drug Safety, 
2014, vol. 13(8), pp. 1133-1141.
---------------------------------------------------------------------------

    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.\152\ 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 
28 mg, 56 mg, or 84 mg twice weekly, respectively. During the second 
treatment period, 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 28 mg, 56 mg, or 84 mg twice weekly groups, 
respectively.
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    \152\ 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, 11 patients receiving 56 mg of 
SPRAVATO, and 12 patients receiving 84 mg of SPRAVATO 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, 9 patients received 56 
mg of SPRAVATO, and 5 patients received 84 mg SPRAVATO 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.\153\
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    \153\ 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.

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[[Page 42250]]

    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 treatment groups was -5.0 (2.99) for 
28 mg of SPRAVATO in dosage, -7.6 (2.91) for 56 mg of SPRAVATO in 
dosage, and -10.5 (2.79) for 84 mg of SPRAVATO in dosage; these 
differences were statistically significant at or beyond p < 0.05. 
Similar differences were seen at 2 hours and 24 hours for these groups 
with the only non-significant difference occurring for 56 mg of 
SPRAVATO in dosage at 2 hours as compared to baseline. At the end of 
the second treatment period, the least square mean change (standard 
error) for the placebo group was -4.5 (2.92), for the SPRAVATO-treated 
groups was -3.1 (2.99) from the placebo for 28 mg of SPRAVATO in 
dosage, -4.4 (3.06) from the placebo for 56 mg of SPRAVATO in dosage, 
and -6.9 (3.41) from the placebo for 84 mg of SPRAVATO in dosage. Only 
the 84 mg of SPRAVATO dosage difference from the mean was statistically 
significant (p<0.05). When the results from the first and second 
treatment periods were pooled, all three groups had statistically 
significant differences from the placebo. Based on these results, the 
applicant asserts that all three SPRAVATO treatment groups were 
superior to the placebo.
    When considering the safety profile of the use of SPRAVATO, the 
study reports that 3 (5 percent) of the treated patients and 1 (2 
percent) open-label patient experienced adverse events leading to 
discontinuation (syncope, headache, dissociative syndrome, ectopic 
pregnancy). There was a noted dose response for the adverse events of 
dizziness and nausea only. Most of the treated patients experienced 
transient elevations in blood pressure and heart rate on dosing days, 
as well as perceptual changes and/or dissociate symptoms (as measured 
by CADSS) that began shortly after dosing and typically resolved by 2 
hours.\154\
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    \154\ 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.
---------------------------------------------------------------------------

    The study titled Transform One submitted by the applicant is a 
Phase III, randomized, double-blind, active controlled, multi-center 
study which enrolled patients 18 years old to 64 years old who had been 
diagnosed with treatment-resistant depression for 28 days.\155\ 
Patients were randomized (1:1:1) to receive SPRAVATO 56 mg, 84 mg, or a 
placebo nasal spray administered twice weekly combined with a newly 
initiated, open-label oral anti-depressant (AD) administered daily 
(duloxetine, escitalopram, sertraline, or venlafaxine extended 
release), which was dosed according to a fixed titration schedule. 
Patients were assessed on the MADRS, CADSS, and discharge readiness as 
measured by overall clinical status and the Global Assessment of 
Discharge Readiness (CGADR). Discharge status was assessed at 1 and 1.5 
hours. MADRS was assessed at 24 hours post initial dose and weekly 
thereafter. CADSS was assessed at baseline and all dosing visits.
---------------------------------------------------------------------------

    \155\ Fedgchin, M., Trivedi, M., Daly, E., Melkote, R., Lane, 
R., Lim, P., Singh, J., ``Randominzed, Double-blind Study of Fixed-
dosed Intranasal Esketamine Plus Oral Anti-depressant vs. Active 
Control in Treatment-resistant Depression,'' 9th Biennial Conference 
of the International Society for Affective Disorders (ISAD) and the 
Houston Mood Disorders Conference, September 2018.
---------------------------------------------------------------------------

    Three hundred and fifteen patients of the 346 were randomized and 
completed the treatment phase; 115 patients were randomized to the 56 
mg of SPRAVATO dosage group along with 114 to the 84 mg of SPRAVATO 
dosage group and 113 to the placebo group. The withdrawal rate was 3-
fold higher in the 84 mg of SPRAVATO dosage group (16.4 percent) than 
the 56 mg of SPRAVATO dosage group (5.1 percent) and the placebo group 
(5.3 percent). Eleven of the 19 84 mg of SPRAVATO dosage withdrawals 
withdrew after only receiving the first 56 mg SPRAVATO dose; the 
withdrawal rate was not a dose-related safety finding. Baseline 
statistics show few differences between groups: The 56 mg of SPRAVATO 
dosage group has a higher proportion of patients who have 1 or 2 
previous AD medications (69 percent) as compared to the patients in the 
84 mg of SPRAVATO dosage group (51.8 percent) and placebo group (59.3 
percent), and the placebo group (193.1) has a notably shorter duration 
of the current episode of depression in weeks as compared to the 56 mg 
of SPRAVATO dosage group (202.8) and 84 mg of SPRAVATO dosage group 
(212.7). The MADRS score was assessed by a mixed model for repeated 
measures with change from baseline as the response variable and the 
fixed effect model terms for treatment dosage, day, region, class of 
oral AD, a treatment-by-day moderating effect, and baseline value as a 
covariate.
    The primary efficacy measure was assessed by change in MADRS score 
from baseline at 28 days. At the end of the study the 56 mg and 84 mg 
of SPRAVATO dosage groups had a difference of least square means of -
4.1 and -3.2, respectively. Neither of these were statistically 
significant differences as compared to the placebo. The least square 
mean treatment difference of MADRS score as compared to the placebo 
were also assessed longitudinally at baseline and the 2nd day (-3.0 for 
the 56 mg of SPRAVATO dosage group and -2.2 for the 84 mg of SPRAVATO 
dosage group), the 8th day (-3.0 for the 56 mg of SPRAVATO dosage group 
and -2.7 for the 84 mg of SPRAVATO dosage group), the 15th day (-3.8 
for the 56 mg of SPRAVATO dosage group and -3.6 for the 84 mg of 
SPRAVATO dosage group), the 22nd day (-5.0 for the 56 mg of SPRAVATO 
dosage group and -3.7 for the 84 mg of SPRAVATO dosage group), and the 
28th day (-4.0 for the 56 mg of SPRAVATO dosage group and -3.6 for the 
84 mg of SPRAVATO dosage group). In a graph provided by the applicant, 
the lines plus standard errors plotted for the 56 mg and 84 mg of 
SPRAVATO dosage groups overlap with each other at each time point, but 
do not appear to overlap with the placebo group (calculated confidence 
intervals would necessarily be wider and would possibly overlap).
    A secondary efficacy measure was the rate of patients who are 
responders and remitters. Response is defined as greater than or equal 
to 50 percent improvement on MADRS from baseline. Remission is defined 
as a MADRS total score less than or equal to 12. The 56 mg and 84 mg of 
SPRAVATO dosage treatment groups, 54.1 percent and 53.1 percent, 
respectively, had higher response rates than the placebo treatment 
group at 38.9 percent. The 56 mg and 84 mg of SPRAVATO dosage treatment 
groups, 36.0 percent and 38.8 percent, had higher remission rates than 
the placebo treatment group at 30.6 percent.
    Lastly, safety was assessed by adverse events and CADSS. Both the 
56 mg and 84 mg of SPRAVATO dosage treatment groups had spikes of CADSS 
scores, which spiked approximately 40 minutes post dose and resolved at 
90 minutes. These post dose spikes gradually decreased from day 1 to 
day 25, but remained higher than the placebo group. The 84 mg of 
SPRAVATO dosage treatment group had higher CADSS score spikes than the 
56 mg of SPRAVATO dosage treatment group at all periods except day 1. 
The top 5 of 12 pooled treatment group adverse events and percentages 
experienced are as follows: Nausea (29.4 percent), dissociation (26.8 
percent), dizziness

[[Page 42251]]

(25.1 percent), vertigo (20.8 percent), and headache (20.3 percent).
    The study titled Transform Two is a Phase III, randomized (1:1), 
control trial, multi-center study enrolling patients 18 years old to 64 
years old who had been diagnosed with treatment-resistant 
depression.\156\ One hundred and fourteen patients were randomized to 
the treatment group and 109 to the control group; 101 and 100 of the 
treated and control groups respectively finished the study. For the 
treatment group, doses of SPRAVATO began at 56 mg on the 1st day, with 
potential increases up to 84 mg until the 15th day at which point the 
dose remained stable. Two-thirds of the SPRAVATO-treated patients were 
receiving the 84 mg dosage at the end of the study. For both the 
placebo and treatment groups, a newly-initiated AD was assigned by the 
investigator (duloxetine, escitalopram, sertraline, and venlafaxine 
extended release) following a fixed titration dosing.
---------------------------------------------------------------------------

    \156\ Popova, V., Daly, E., Trivedi, M., Cooper, K., Lane, R., 
Lim, P., Singh, J., ``Randomized, Double-blind Study of Flexibly-
dosed Intranasal Esketamine Pus Oral Anti-depressant vs. Active 
Control in Treatment-resistant Depression,'' Canadian College of 
Neuropsychopharmacology (CCNP) 41st Annual Meeting, 2018.
---------------------------------------------------------------------------

    The primary efficacy endpoint was the change from baseline at day 
28 in MADRS total score, which was analyzed using a mixed-effects model 
using repeated measures (MMRM). The model included baseline MADRS total 
score as a covariate, and treatment, country, class of AD (SNRI or 
SSRI), day, and day-by-treatment moderator as fixed effects, and a 
random patient effect. The key secondary efficacy endpoints were as 
follows: The proportion of patients showing onset of clinical response 
by the 2nd day that was maintained for the duration of the treatment 
phase, the change from baseline in socio-occupational disability using 
the Sheehan Disability Scale (SDS) using the MMRM model, and the change 
from baseline in depressive symptoms using the patient health 
questionnaire 9-item (PHQ-9) using the MMRM model.
    There were no apparent differences between the SPRAVATO treatment 
and placebo groups at baseline. At day 28, the difference of least 
square means (standard error) for the SPRAVATO-treated group was -4.0 
(1.69) as compared to the placebo-treated group (p<0.05). Similar to 
Transform One, the difference of least square means for the SPRAVATO-
treated group as compared to the placebo-treated group were plotted for 
baseline and the 2nd, 8th, 15th, 22nd, and 28th day. At all treatment 
periods, except baseline and the 15th day, the SPRAVATO treatment group 
had statistically significant lower scores than the placebo-treated 
group as indicated by 95 percent confidence intervals. The difference 
between the SPRAVATO-treated and placebo-treated groups for the early 
onset of sustained clinical response was substantively similar and not 
statistically different. The difference of least square means (standard 
error) in socio-occupational disability as measured by SDS was -4.0 
(1.17) for those in the SPRAVATO-treated group as compared to the 
placebo-treated group (p<0.05). The difference of least square means 
(standard error) for the PHQ-9 total score for the SPRAVATO-treated 
group compared to the placebo-treated group was -2.4 (0.88) (p<0.05). 
Lastly, 69.3 percent of the SPRAVATO-treated patients as compared to 
52.0 percent of the placebo-treated patients were considered responders 
and 52.5 percent of the SPRAVATO-treated patients as compared to 31.0 
percent of the placebo patients were considered remitters. The adverse 
events list, post dosing blood pressure increase, and post dosing CADSS 
spike were similar to those seen in the previous Transform One 
study.\157\
---------------------------------------------------------------------------

    \157\ Fedgchin, M., Trivedi, M., Daly, E., Melkote, R., Lane, 
R., Lim, P., Singh, J., ``Randominzed, Double-blind Study of Fixed-
dosed Intranasal Esketamine Plus Oral Anti-depressant vs. Active 
Control in Treatment-resistant Depression,'' 9th Biennial Conference 
of the International Society for Affective Disorders (ISAD) and the 
Houston Mood Disorders Conference, September 2018.
---------------------------------------------------------------------------

    A post-hoc analysis based on Transform Two, which included 46 
SPRAVATO-treated and 44 placebo-treated patients was conducted to 
assess for differences in efficacy and safety between the U.S. 
population and the overall study population.\158\ Efficacy was again 
assessed by MADRS, SDS, and PHQ-9 scores using the MMRM and with safety 
assessments for treatment-emergent adverse events (TEAEs), serious 
adverse events (SAEs), CADSS and other measures. At baseline the 
treated group of SPRAVATO plus an AD was similar to the placebo-treated 
group who took only an AD on most measures to include average age, sex, 
race, class of oral ADs, MADRS, CGI-S, SDS, and PHQ-9 scores. The 
placebo-treated group had a longer average duration of current episode 
at 177.6 days as compared to 132.2 days for the SPRAVATO-treated group; 
the placebo-treated group had a higher proportion of patients having 3 
or more previous AD medications (50.1 percent) as compared to the 
SPRAVATO treatment group (32.7 percent).
---------------------------------------------------------------------------

    \158\ Alphs, L., Cooper, K., Starr, L., DiBernardo, A., Shawi, 
M., Jamieson, C., Singh, J., ``Clinical Efficacy and Safety of 
Flexibly Dosed Esketamine Nasal Spray in a US Population of Patients 
With Treatment-Resistant Depression,'' American Psychiatry 
Association, 2018, Chicago.
---------------------------------------------------------------------------

    Both the SPRAVATO-treated and placebo-treated groups showed 
improvement on the efficacy measures after 28 days. At the endpoint of 
28 days, the SPRAVATO treatment group had a statistically significant 
MADRS total score least square mean difference of -5.5 (p < 0.05) from 
the placebo treatment group. At the endpoint the median scores on the 
clinician-rated severity of depressive illness as measured by CGI-S 
were -1.5 and -1.0 for the SPRAVATO-treated and placebo-treated groups 
respectively (one-sided p value > 0.07). For the measure of patient-
rated severity of depressive illness, the SPRAVATO treatment group had 
a least square mean difference in PHQ-9 of -3.1 (p<0.05) as compared to 
the placebo treatment group. On the measure of functional impairment, 
the SPRAVATO treatment group had a least square mean difference in SDS 
of -5.2 (p<0.01) as compared to the placebo treatment group. Overall 
treatment-emergent adverse events were observed in 91.3 percent of 
SPRAVATO-treated patients and 77.3 percent of placebo-treated patients. 
One SPRAVATO-treated patient experienced a serious adverse event of 
cerebral hemorrhage. Lastly, the top five most common adverse events 
were dizziness, nausea, headache, dysgeusia, and throat irritation.
    The study titled Transform Three is a randomized (1:1), double-
blind, active-controlled, multi-center study in elderly patients 65 
years old and older who had been diagnosed with TRD.\159\ Randomization 
was stratified by country and class of oral AD (SNRI and SSRI). All 
treatment patients started on a 28 mg dosage of SPRAVATO and flexibly 
increased dosages of 56 mg or 84 mg based on investigator's 
determination of efficacy and tolerability. Both SPRAVATO-treated (n = 
72) and placebo-treated (n = 66) patients were started on a newly 
initiated AD (duloxetine, escitalopram, sertraline, and venlafaxine 
extended release). One hundred and twenty-two patients completed the 
double-blind phase, with 63 patients in the SPRAVATO-treated group and 
60 patients in the placebo-treated group.
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    \159\ Ochs-Ross, R., Daly, E., Lane, R., Zhang, Y., Lim, P., 
Foster, K., Sign, J., ``Efficacy and Safety of Esketamine Nasal 
Spray Plus an Oral Anti-depressant in Elderly Patients with 
Treatment-resistant Depression,'' 2018 Annual Meeting of the 
American Psychiatric Association (APA), 2018, New York.
---------------------------------------------------------------------------

    The primary endpoint was the change in MADRS total score from the 
1st day

[[Page 42252]]

to the 28th day. Secondary endpoints included the evaluation of 
response and remission rates by group and the Clinical Global 
Impression--Severity (CGI-S) scores. The safety endpoints were 
evaluated by adverse event occurrence, laboratory tests, vital sign 
measurements, physical exams, and other exams.
    At baseline, there were substantive differences between the 
placebo-treated and SPRAVATO treatment groups in three measures. 
Patients from the SPRAVATO treatment group (48.6 percent) were more 
likely to be from the European Union as compared to the placebo-treated 
group (36.9 percent). Patients from the SPRAVATO treatment group were 
more likely to have 1 (20.8 percent versus 9.2 percent) to 4 (16.7 
percent versus 6.2 percent) previous ADs as compared to the placebo-
treated group. On the measure of duration of current episode of 
depression in weeks, the SPRAVATO-treated group had an average 
(standard deviation) of 163.1 (277.04) as compared to the placebo-
treated group with 274.1 (395.47). The primary endpoint, the change 
from baseline to Day 28 of MADRS score difference of least square means 
(95 percent CI) for the SPRAVATO treatment group was -3.6 (-7.20,0.07) 
as compared to the placebo group. As with previous studies, the 
longitudinal change in MADRS total score is presented for baseline and 
at the 8th, 15th, 22nd, and 28th day. The results for the SPRAVATO-
treated group overlap with the placebo-treated group at each time 
point. At Day 28, 27.0 percent of the SPRAVATO-treated patients as 
compared to 13.3 percent of the placebo-treated patients were 
considered responders and 17.5 percent of the SPRAVATO-treated patients 
as compared to 6.7 percent of the placebo-treated patients were 
considered remitters. At baseline and the end of the study, 83.4 
percent and 38.1 percent, respectively, of the SPRAVATO-treated 
patients were rated as experiencing severe or marked symptoms on the 
CGI-S scale as compared to 66.1 percent and 54.4 percent, respectively, 
for those on the placebo.
    Of the 72 patients who were treated with SPRAVATO, 51 (70.8 
percent) experienced a treatment-emergent adverse event (TEAE) as 
compared to 39 of the 65 (60.0 percent) placebo-treated patients. Five 
patients reported serious adverse events during the double-blind phase, 
three of whom were SPRAVATO-treated patients and two of whom were 
placebo-treated patients. The top 5 of the 16 adverse events among the 
treated patients are dizziness (20.8 percent), nausea (18.1 percent), 
blood pressure increase (12.5 percent), fatigue (12.5 percent), and 
headache (12.5 percent).
    A post-hoc analysis, which included 34 SPRAVATO-treated patients 
and 36 placebo-treated patients from the Transform Three study, was 
performed to examine the response and remission associated with 
treatments in a subset of respondents 65 years old and older in the 
United States.\160\ The MADRS, CGI-S, PHQ-9, and adverse event data 
were utilized to assess clinical outcomes. Remission was defined as a 
50 percent or greater decrease in MADRS baseline score and remission 
was defined as a MADRS score of 12 or lower or a PHQ-9 score of less 
than 5. At baseline the SPRAVATO-treated and placebo-treated groups 
were similar on the measures of age, sex, race, class of oral AD, age 
at major depressive disorder diagnosis, MADRS score, and CGI-S score. 
The SPRAVATO treatment group differed from the placebo treatment group 
on the measures of mean duration of current depressive episode in weeks 
(187.6 versus 420.9) and mean PHQ-9 score (15.2 versus 18.2).
---------------------------------------------------------------------------

    \160\ Starr, L., Ochs-Ross, R., Zhang, Y., Singh, J., Lim, P., 
Lane, R., Alphs, L., ``Clinical Response, Remission, and Safety of 
Esketamine Nasal Spray in a US Population of Geriatric Patients With 
Treatment-Resistant Depression,'' American Psychiatric Association, 
2018, New York.
---------------------------------------------------------------------------

    At the 28-day endpoint, response rates based on MADRS scores were 
26.7 percent (n = 30) for the SPRAVATO-treated group and 14.7 percent 
(n = 34) for the placebo-treated group. At the endpoint, remission 
rates based on MADRS scores were 16.7 percent (n = 30) for the 
SPRAVATO-treated group and 2.9 percent (n = 34) for the placebo-treated 
group. Patient remission rates based on the PHQ-9 scores for SPRAVATO-
treated and placebo-treated patients were 9.4 percent (n = 32) and 22.6 
percent (n = 31), respectively. Clinically meaningful response as 
measured by a one point or greater decrease in the CGI-S score was 63.3 
percent (n = 30) for the SPRAVATO-treated group and 29.4 percent (n = 
34) for those on the placebo. Clinically significant response as 
measured by a decrease of two or greater on the CGI-S scale was 43.3 
percent (n = 30) for the SPRAVATO-treated group and 11.8 percent (n = 
34) for those on the placebo. Lastly, 67.7 percent of the SPRAVATO-
treated patients and 58.3 percent of placebo-treated patients 
experienced a treatment-emergent adverse event. There was one serious 
adverse event in the SPRAVATO-treated group (hip fracture) and placebo-
treated group (dizziness) each. The top 5 most common adverse events in 
the 34 SPRAVATO-treated patients were dysphoria (11.8 percent), fatigue 
(11.8 percent), headache (11.8 percent), insomnia (11.8 percent), and 
nausea (11.8 percent).
    The study titled Sustain One concerns a double-blind, randomized 
withdrawal, multi-center study entering either directly or after 
completing the double-blind phase of an acute, short-term study.\161\ A 
total of 705 patients were enrolled in this study of which 437 entered 
directly into the study and the remainder transferred from one of two 
short-term SPRAVATO studies (fixed dose, n = 150; flexible dose, n = 
118). During the maintenance phase of this study, analyses were 
performed on two mutually exclusive groups: (1) On the stable remitters 
who were those randomized patients who were in stable remission at the 
end of the optimization phase and who received at least one dose of the 
study drug with one dose of an AD; and (2) on the stable responders who 
were those randomized patients who were stable responders at the end of 
optimization and who received at least one dose of the study drug with 
one dose of an AD. A relapse was defined as a MADRS total score of 22 
or greater for 2 consecutive assessments separated by 5 to 15 days or 
hospitalization for worsening depression or any other clinically 
relevant event suggestive of relapse.
---------------------------------------------------------------------------

    \161\ Daly, E., Trivedi, M., Janik, A., Li, H., Zhang, Y., Li, 
X., Singh, J., ``A Randomized Withdrawal, Double-blind, Multicenter 
Study of Esketamine Nasal Spray Plus an Oral Anti-depressant for 
Relapse Prevent in Treatment-resistant Depression,'' 2018 Annual 
Meeting of the American Society of Clinical Psychopharmacology 
(ASCP), 2018, Miami.
---------------------------------------------------------------------------

    Of those classified in stable remission, 90 patients were receiving 
treatment with SPRAVATO in combination with an AD and 86 patients were 
receiving treatment with the placebo in combination with an AD. Of 
those classified in stable response, 62 patients were receiving 
treatment with SPRAVATO in combination with an AD and 59 patients were 
receiving treatment with the placebo in combination with an AD. At 
baseline, between group and within group randomization seems 
substantively successful, except for a lower proportion of placebo-
treated stable responders being male (28.8 percent) as compared to 
SPRAVATO-treated stable responders (38.7 percent), placebo-treated 
stable remitters (31.4 percent), and SPRAVATO-treated stable remitters 
(35.6 percent).
    Kaplan-Meier estimates of patients who remained relapse free were 
performed for both study groups. For both remitters and responders, the 
SPRAVATO-treated had a higher

[[Page 42253]]

percent of patients without relapse for longer than the control group. 
Overall, among the stable remitters, 24 (26.7 percent) of the patients 
in the SPRAVATO-treated group and 39 (45.3 percent) of the patients in 
the placebo-treated group experienced a relapse event during the 
maintenance phase; among stable responders, 16 (25.8 percent) of the 
patients and 34 (57.6 percent) of the patients in the respective groups 
relapsed. Treatment with SPRAVATO in combination with an AD decreased 
the risk of relapse by 51 percent (estimated hazard ratio = 0.49; 95 
percent CI: 0.29, 0.84) among stable remitters and by 70 percent 
(hazard ratio = 0.30; 95 percent CI: 0.16, 0.55) among stable 
responders, as compared to the placebo.
    Safety and adverse events were presented similarly to the 
previously discussed study data. The top 5 of the 22 adverse events 
were dysgeusia (27.0 percent), vertigo (25.0 percent), dissociation 
(22.4 percent), somnolence (21.1 percent), and dizziness (20.4 
percent). The applicant stated that most adverse events were mild to 
moderate, observed post dose on dosing days, and generally resolved in 
the same day. Serious adverse events considered related to the study 
drug were reported for six patients in the SPRAVATO treatment group 
(disorientation, hypothermia, lacunar stroke, sedation, and suicidal 
ideation for one patient each, and autonomic nervous system imbalance 
and simple partial seizure for one patient). The investigator 
considered the lacunar infarct as probably related to the treatment, 
while the sponsor considered the events of lacunar infarct and 
hypothermia as doubtfully related to the treatment. As with the 
previous studies, present-state dissociative symptoms and transient 
perceptual effects measured by the CADSS total score began shortly 
after the start of SPRAVATO dosing, peaked at 40 minutes, and resolved 
by 1.5 hours.
    The next study presented by the applicant titled Sustain Two 
concerns an open-label, long-term (up to 1 year of exposure), multi-
center, single-arm, Phase III study for patients who had been diagnosed 
with TRD who entered into the study as either direct-entry or 
transferred-entry (patients who completed the double-blind, randomized, 
4-week, Phase III, efficacy and safety study in elderly patients).\162\ 
A total of 802 patients were enrolled; 779 entered in the induction 
phase (691 as direct-entry and 88 as transferred-entry non-responders). 
A total of 603 patients entered the optimization/maintenance phase (580 
from the induction phase and 23 were transferred-entry responders). A 
total of 150 (24.9 percent) of the patients completed the optimization/
maintenance phase. At that time, the predefined total patient exposure 
was met and the study was stopped by the sponsor; 331 (54.9 percent) of 
the patients were still receiving treatment and, therefore, 
discontinued the study. Patients treated had a starting dose of 56 mg 
of SPRAVATO, or 28 mg for patients who were 65 years old or older, 
followed by flexible dosing increases (28 mg to 84 mg per clinical 
judgment) twice a week for 4 weeks. Dosages became stable at 15 days 
for those under 65 years old, and at 18 days for those 65 years old and 
older.
---------------------------------------------------------------------------

    \162\ Wajs, E., Aluisio, L., Morrison, R., Daly, E., Lane, R., 
Lim, P., Singh, J., ``Long-term Safety of Esketamine Nasal Spray 
Plus Oral Anti-depressant in Patients with Treatment-resistant 
Depression: Phase III, Open-label, Safety and Efficacy Study 
(SUSTAIN-2),'' 2018 Annual Meeting of the American Society of 
Clinical Psychopharmacology (ASCP), 2018, Miami.
---------------------------------------------------------------------------

    At baseline, 802 respondents had an average age of 52.2 years old, 
62.6 percent were women, 85.5 percent were white, an average BMI of 
27.9 percent, and 43.1 percent with a family history of depression. The 
anti-depressants prescribed to these respondents were duloxetine (31.1 
percent), escitalopram (29.6 percent), sertraline (19.6 percent), and 
venlafaxine extended release (19.5 percent). Of the respondents at 
baseline, 39.9 percent had used 3 or more ADs prior to the study with 
no response. Safety measures were reported at 4 weeks, 48 weeks, and 
pooled. For TEAEs, 83.8 percent of patients experienced at least one at 
4 weeks and 85.6 percent at 48 weeks. TEAEs occurred in 90.1 percent (n 
= 723) of all patients and led to discontinuation in 9.5 percent of 
both the pooled 4 and 48 week patient samples. TEAEs caused 2 deaths 
(acute respiratory and cardiac failure, and completed suicide; neither 
death considered as related by investigator) at 48 weeks. The top 5 
most common TEAEs for the 4-week and 48-week time points were dizziness 
(29.3 percent and 22.4 percent), dissociation (23.1 percent and 18.6 
percent), nausea (20.2 percent and 13.9 percent), headache (17.6 
percent and 18.9 percent), and somnolence (12.1 percent and 14.1 
percent). At 4 weeks, 2.2 percent of the patients experienced at least 
1 serious adverse event and 6.3 percent at 48 weeks. Of the 68 serious 
adverse events, 63 were assessed as not related or doubtfully related 
to treatment involving SPRAVATO by the investigator. Five of the 
serious adverse events (anxiety, delusion, delirium, suicidal ideation 
and suicide attempt) were considered as treatment related. Overall, 
performance on multiple cognitive domains including visual learning and 
memory, as well as spatial memory/executive function either improved or 
remained stable post baseline in both elderly and younger patients.
    Based on all of the previous discussion, the applicant concluded 
that the use of SPRAVATO represents a substantial clinical improvement 
over existing technologies. In the proposed rule, we stated the 
following concerns regarding whether SPRAVATO meets the substantial 
clinical improvement criterion.
    First, we stated we were concerned that the use of the placebo in 
combination with a newly prescribed anti-depressant may not be the most 
appropriate comparator when assessing the clinical improvement of the 
use of SPRAVATO as compared to existing therapies. In its application, 
the applicant listed multiple treatment options aside from the use of 
anti-depressants, which are currently available to treat diagnoses of 
TRD. It is possible that other treatments approved for diagnoses of TRD 
may obtain better treatment outcomes than changing to a new single 
anti-depressant (as was the method used in the studies submitted in 
support of this application). We stated that comparisons with existing 
treatments for treatment-resistant major depressive disorders would 
help us better evaluate the clinical improvements offered by the use of 
SPRAVATO.
    Second, we stated that we were not certain that the results in the 
studies submitted consistently show that the use of SPRAVATO represents 
a substantial clinical improvement when compared to existing therapies. 
We stated that there does not appear to be a consistent statistically 
significant positive primary efficacy outcome for SPRAVATO-treated 
patients compared to placebo-treated patients. Based on the data 
provided, we stated that we also were uncertain of the extent to which 
the findings from the submitted studies apply to the broader Medicare 
population. We further stated that we were particularly concerned that 
there are few substantive and statistically significant improvements in 
depression outcomes with SPRAVATO treatment among the Medicare-aged 
participants of the study samples. In addition, we stated that the 
studies which limit their analyses to Medicare-aged study participants 
have limited racial diversity amongst small samples. In

[[Page 42254]]

addition, we noted that the submitted studies excluded patients with 
significant medical and psychiatric comorbidities through exclusion 
criteria. However, we noted the likelihood of having multiple chronic 
comorbid conditions is increased amongst those with a mental health 
disorder 163 164 and for the elderly.165 166 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 stated that we were concerned that the limited 
results did not adequately represent the average or even the majority 
of the Medicare population.
---------------------------------------------------------------------------

    \163\ 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.
    \164\ Druss, B., & Walker, E., 2011, ``Mental Disorders and 
Medical Comorbidity,'' Robert Wood Johnson Foundation, 2011. 
Available at: http://www.policysynthesis.org.
    \165\ 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.
    \166\ 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.
---------------------------------------------------------------------------

    Third, we indicated that we had concerns regarding the primary and 
secondary endpoints for several of these studies. We stated that it was 
unclear whether the primary endpoint of these studies (change in 
baseline MADRS) was the most appropriate endpoint to assess substantial 
clinical improvement, particularly as it was 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 translated 
to clinical improvement (for example, response and remissions rates). 
In addition, we stated that we had 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 stated that 
we believed there was the potential for an interaction effect between 
the prescribed anti-depressant and SPRAVATO. We stated that it was 
possible that one particular anti-depressant (of the anti-depressants 
used in the studies)/SPRAVATO combination accounts for the entirety of 
the differences seen between the treated groups and the control groups. 
We further stated that 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 is comprised of the drug ketamine, we 
stated in the proposed rule that we were concerned with the potential 
for abuse. Ketamine is accepted as a medication for which there is a 
strong possibility for abuse.167 168 169 As one publication 
finds, current abuse of intravenous ketamine occurs intranasally.\170\ 
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.\171\ In light of the potential for addictive behavior, we stated 
we were 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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    \167\ 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.
    \168\ 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.
    \169\ 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.
    \170\ 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.
    \171\ 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 invited public comments on whether SPRAVATO meets the 
substantial clinical improvement criterion.
    Comment: The applicant submitted a comment addressing concerns 
raised by CMS in the proposed rule regarding whether SPRAVATO meets the 
substantial clinical improvement criterion. In response to CMS' concern 
that a placebo may be an insufficient comparator for SPRAVATO, the 
applicant stated that the use of a placebo was an appropriate method to 
assess clinical improvements in TRD. According to the applicant, two 
treatments (Symbyax [olanzapine and fluoxetine hydrochloride]) and 
electroconvulsive therapy) are available for use in place of a placebo 
but are not appropriate comparators due to tolerability concerns \172\ 
for the former and poor side effects and limited availability for the 
latter.173 174
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    \172\ Cristancho MA., Thase ME. Drug safety evaluation of 
olanzapine/fluoxetine combination. Expert Opin Drug Saf. 
2014;13(8):1133-1141.
    \173\ Ochs-Ross R., Daly EJ., Lane R., et al. Efficacy and 
safety of esketamine nasal spray plus an oral antidepressant in 
elderly patients with treatment-resistant depression. Poster 
presented at: Annual Meeting of the American Society of Clinical 
Psychopharmacology (ASCP); May 29-June 1, 2018; Miami, Florida.
    \174\ Amos T., Tandon N., Lefebvre P., et al. Direct and 
indirect cost burden and change of employment status in treatment-
resistant depression: a matched-cohort study using a U.S. commercial 
claims database. J. Clin Psychiatry. 2018;79(2).
---------------------------------------------------------------------------

    In response to CMS' concern that the results of studies did not 
consistently show substantial clinical improvement of SPRAVATO when 
compared to existing therapies, the applicant referenced previously 
submitted studies, Transform-2 and Sustain-1. According to the 
applicant, in the Transform-2 trial, patients with TRD achieved 
clinically meaningful and statistically significant improvement in 
depressive symptoms after being switched to SPRAVATO vs. a placebo 
\175\ which resulted in a group treatment difference which exceeded 
minimum clinically important difference thresholds reported 
elsewhere.176 177 Similarly the applicant asserted that, for 
Sustain-1, SPRAVATO demonstrated a significantly delayed time to 
relapse versus those treated with a placebo after 16 weeks of treatment 
with SPRAVATO.\178\ The applicant further added that in a recent 
publication in the New England Journal of Medicine, data from the 
SPRAVATO Phase 3 studies provided evidence of clinically meaningful 
efficacy when

[[Page 42255]]

SPRAVATO is used in combination with a newly initiated oral 
antidepressant.\179\ The applicant concluded that SPRAVATO consistently 
shows efficacy at both the short and long-term time points.
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    \175\ Popova V, Daly EJ, Trivedi M, et al. Efficacy and safety 
of flexibly dosed esketamine nasal spray combined with a newly 
initiated oral antidepressant in treatment-resistant depression: a 
randomized double-blind active-controlled study. Am J Psychiatry. 
2019a;176(6):428-438.
    \176\ Montgomery SA, M[ouml]ller HJ. Is the significant 
superiority of escitalopram compared with other antidepressants 
clinically relevant? Int Clin Psychopharmacol. 2009;24(3):111-118.
    \177\ Montgomery SA, Nielsen RZ, Poulsen LH, et al. A 
randomised, double-blind study in adults with major depressive 
disorder with an inadequate response to a single course of selective 
serotonin reuptake inhibitor or serotonin-noradrenaline reuptake 
inhibitor treatment switched to vortioxetine or agomelatine. Hum 
Psychopharmacol. 2014;29(5):470-482.
    \178\ Daly EJ, Trivedi MH, Janik A, et al. Efficacy of 
Esketamine Nasal Spray Plus Oral Antidepressant Treatment for 
Relapse Prevention in Patients with Treatment-Resistant Depression: 
A Randomized Clinical Trial [Epub ahead of print]. JAMA Psychiatry. 
2019a. doi:10.1001/jamapsychiatry.2019.1189
    \179\ Kim J, Farchione T, Potter A, et al. Esketamine for 
treatment-resistant depression--first FDA-approved antidepressant in 
a new class [epub ahead of print]. N Engl J Med. 2019 May 22. doi: 
10.1056/NEJMp1903305
---------------------------------------------------------------------------

    In regard to CMS' concern about SPRAVATO's applicability to the 
Medicare population, the applicant reiterated results from the 
Transform-3 and Sustain-2 studies which included samples targeting ages 
65 years of age and older. The applicant stated in their comment that 
they acknowledge the limitations of the clinical trials given the 
inclusion and exclusion criteria of the studies. The applicant also 
recognized that people under 65 years of age with long-term 
disabilities are also included in the Medicare population. Although the 
applicant did not capture in the trials whether or not patients were on 
disability, it indicated that many of the patients enrolled were not 
working because of their depression. In the Transform-2 and Sustain-1 
studies 30.9 percent and 25.5 percent respectively of patients were 
unemployed; the applicant stated that many of the patients enrolled 
were not working because of their depression and therefore the percent 
unemployed was used as a proxy for chronically disabled.
    In response to CMS' concern regarding studies lacking data to show 
efficacy across various racial groups, the applicant conceded that 
there is limited racial diversity amongst the Phase 3 clinical trials 
for TRD, and that their intent is to continue gathering evidence based 
on real world data as available. However, the applicant noted that 
based on the limited sample size, there did not appear to be any 
difference in efficacy for this variable.
    In response to CMS' concern that studies provided exclude patients 
with certain medical and psychiatric comorbidities, the applicant 
stated that patients with other comorbid anxiety disorders, post-
traumatic stress disorder, and certain chronic medical conditions were 
included. The applicant provided data from the Transform-3 study and 
pooled studies (Transform-1, Transform-2, and Sustain-1) showing the 
incidence of common psychiatric comorbidities upon enrollment in the 
phase three trials in adults 18-64 treated with SPRAVATO.
[GRAPHIC] [TIFF OMITTED] TR16AU19.148

    In response to CMS' concern that the primary endpoint (change in 
baseline MADRS) may not be the most appropriate for evaluating SPRAVATO 
success, the applicant stated the MADRS is a 10 item, clinician-
administered scale designed to measure overall severity of depressive 
symptoms in subjects with MDD. The applicant stated that the scale was 
selected because it is validated, reliable, and acceptable to 
regulatory health authorities as a primary efficacy endpoint in a 
patient population with MDD. Each item is scored between 0-6, leading 
to a total score 0-60. The 10 items include the following symptoms: 
apparent sadness; reported sadness; inner tension; reduced sleep; 
reduced appetite; concentration difficulties; lassitude; inability to 
feel; pessimistic thoughts; suicidal thoughts. Cutoffs generally used 
for severity include: 0-6 normal; 7-19 mild depression; 20-34 moderate 
depression; >34 severe depression.\180\ A ``clinically meaningful'' 
change from baseline on the MADRS (within-patient change) has been 
reported to range between a 6-9 point reduction in total score. Change 
in total scores is dependent, in part, on baseline MDD 
severity.181 182 In contrast, when groups are compared to 
each other at the conclusion of a trial, a 2-point difference between 
groups has been found to be clinically meaningful.183 184
---------------------------------------------------------------------------

    \180\ Snaith RP, Harrop FM, Newby DA, Teale C. Grade scores of 
the Montgomery-Asberg Depression and the Clinical Anxiety Scales. Br 
J Psychiatry. 1986;148:599-601.
    \181\ Leucht S, Fennema H, Engel RR, et la. What does the MADRS 
mean? Equipercentile linking with the CGI using a company database 
of mirtazapine studies. J Affect Disord.2017; 210:287-293.
    \182\ Turkoz I, Alphs, L, Singh J, et al. Demonstration of the 
relationship among Clinical Global Impression of Severity of 
Depression Scale and Montgomery-[Aring]sberg Depression Rating, 
Patient Health Questionnaire-9, and Sheehan Disability Scales 
[poster]. Presented at: The International Society for CNS Clinical 
Trials and Methodology (ISCTM) Annual Scientific Meeting; February 
20-22, 2018; Washington, DC.
    \183\ Montgomery SA, M[ouml]ller HJ. Is the significant 
superiority of escitalopram compared with other antidepressants 
clinically relevant? Int Clin Psychopharmacol. 2009;24(3):111-118.
    \184\ Montgomery SA, Nielsen RZ, Poulsen LH, et al. A 
randomised, double-blind study in adults with major depressive 
disorder with an inadequate response to a single course of selective 
serotonin reuptake inhibitor or serotonin-noradrenaline reuptake 
inhibitor treatment switched to vortioxetine or agomelatine. Hum 
Psychopharmacol. 2014;29(5):470-482.
---------------------------------------------------------------------------

    In response to CMS' concern about the potential for bias from 
clinical staff, the applicant commented that as SPRAVATO has known 
transient dissociative effects that are difficult to blind, potentially 
biasing the research staff who observed these adverse events (AEs), the 
MADRS was performed prior to dosing throughout the DB studies by 
independent remote (by phone) blinded raters using the Structured 
Interview Guide for the MADRS. Blinded, independent raters were 
specifically trained not to inquire about AEs, and study subjects were 
reminded not to discuss AEs with the MADRS raters. To enhance remote 
rating quality and reliability, and to prevent rater drift, audio-
recording of the remote MADRS

[[Page 42256]]

assessments was implemented.\185\ As an additional measure to enhance 
blinding, a bittering agent was added to the placebo nasal spray to 
simulate the taste of SPRAVATO nasal spray.186 187
---------------------------------------------------------------------------

    \185\ Daly EJ, Trivedi MH, Janik A, et al. Supplementary Online 
Content for: Efficacy of Esketamine Nasal Spray Plus Oral 
Antidepressant Treatment for Relapse Prevention in Patients with 
Treatment-Resistant Depression: A Randomized Clinical Trial [epub 
ahead of print]. JAMA Psychiatry. 2019b. doi:10.1001/
jamapsychiatry.2019.1189
    \186\ Popova V, Daly EJ, Trivedi M, et al. Efficacy and safety 
of flexibly dosed esketamine nasal spray combined with a newly 
initiated oral antidepressant in treatment-resistant depression: a 
randomized double-blind active-controlled study. Am J Psychiatry. 
2019a;176(6):428-438.
    \187\ Daly EJ, Trivedi MH, Janik A, et al. Efficacy of 
Esketamine Nasal Spray Plus Oral Antidepressant Treatment for 
Relapse Prevention in Patients with Treatment-Resistant Depression: 
A Randomized Clinical Trial [Epub ahead of print]. JAMA Psychiatry. 
2019a. doi:10.1001/jamapsychiatry.2019.1189
---------------------------------------------------------------------------

    In response to CMS' concern about the potential for medication 
interactions between the newly prescribed antidepressant and SPRAVATO, 
the applicant provided subgroup analyses in a pooled adult population 
with TRD from the Transform-1 and -2 studies which showed no major 
differences in the MADRS total score from baseline to day 28 by class 
of antidepressant. Further, the applicant stated that the rate of 
treatment-emergent adverse events reported in subjects from the SSRI 
subgroup (87.4 percent) was similar to the rate in subjects from the 
SNRI subgroup (86.7 percent).
    In response to CMS' concern for the potential abuse of SPRAVATO the 
applicant stated that the medication is mandated by the FDA to be 
accompanied by a Risk Evaluation and Mitigation Strategy (REMS) program 
and other procedures to mitigate potential risk for misuse and abuse in 
longer term use patients.\188\ The applicant states that additional 
safeguards, such as safety surveillance using aggregate data from 
external sources and the restricted distribution of SPRAVATO to a 
limited number of wholesalers and distributers, are aimed at minimizing 
the risk of misuse. Finally, the applicant stated that the Phase 3 
programs assessed for evidence of withdrawal or rebound symptoms after 
the cessation of SPRAVATO \189\ and found no evidence up to four weeks 
later.
---------------------------------------------------------------------------

    \188\ Kim J, Farchione T, Potter A, et al. Esketamine for 
treatment-resistant depression--first FDA-approved antidepressant in 
a new class [epub ahead of print]. N Engl J Med. 2019 May 22. doi: 
10.1056/NEJMp1903305.
    \189\ Popova V, Daly EJ, Trivedi M, et al. Data Supplement for: 
Efficacy and safety of flexibly dosed esketamine nasal spray 
combined with a newly initiated oral antidepressant in treatment-
resistant depression: a randomized double-blind active-controlled 
study. Am J Psychiatry. 2019b;176(6):428-438.
---------------------------------------------------------------------------

    Response: We appreciate the thorough response and additional 
information provided by the applicant in response to our concerns 
regarding substantial clinical improvement. We agree with the applicant 
that due to difficulties arising from treatment with Symbyax or 
electroconvulsive therapy that it may be clinically challenging to use 
these current treatments for TRD as comparators for SPRAVATO. We also 
agree that SPRAVATO shows evidence of clinically meaningful efficacy 
based on the additional information provided by the applicant's comment 
regarding change in baseline MADRS score as an appropriate measure to 
assess substantial clinical improvement. We also appreciate the 
applicant's efforts to address clinical bias and the potential for 
abuse of SPRAVATO. In light of this information we agree that SPRAVATO 
meets the substantial clinical improvement criterion.
    After consideration of the public comments we received, we have 
determined that Spravato meets all of the criteria for approval of new 
technology add-on payments. Therefore, we are approving new technology 
add-on payments for Spravato for FY 2020. Cases involving Spravato that 
are eligible for new technology add-on payments will be identified by 
ICD-10-PCS procedure code 3E097GC (Introduction of Other Therapeutic 
Substance into Nose, Via Natural or Artificial Opening). According to 
the applicant, the cost for one dose of SPRAVATO is $295, and patients 
will typically require 2.5 nasal spray units per treatment for a cost 
per day of $737.50. The applicant states that patients undergoing 
induction typically receive treatment twice per week while those 
undergoing maintenance receive treatment once per week or every two 
weeks. Because the applicant assumed that hospitals would not provide 
Spravato for stays shorter than 5 days the applicant assumed a dosage 
schedule where the 1st dosage is administered on day 5, the 2nd dosage 
is administered on day 12, and the 3rd dosage is administered on day 
19, and so forth. The applicant found that there would be an average 
dosage of 2.1169 nasal spray units per discharge. The applicant 
therefore estimates that the average total cost of Spravato per patient 
per discharge is $1,561.21 ($737.50 x 2.1169). Under Sec.  412.88(a)(2) 
(revised as discussed in this final rule), we limit new technology add-
on payments to the lesser of 65 percent of the average cost of the 
technology, or 65 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 Spravato is $1,014.79 for FY 2020.
i. XOSPATA[supreg] (gilteritinib)
    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 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

[[Page 42257]]

leukemia and AML.\190\ 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.\191\ 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.\192\
---------------------------------------------------------------------------

    \190\ 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.
    \191\ Siegel, R.L., Miller, K.D., Jemal, A., ``Cancer 
statistics, 2018,'' CA Cancer J Clin, 2018, vol. 68(1), pp. 7-30.
    \192\ 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.
---------------------------------------------------------------------------

    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.193 194 195 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.\196\ 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.\197\ 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.198 199 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.\200\ 
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.201 202 203 204
---------------------------------------------------------------------------

    \193\ Rowe, J.M., Tallman, M.S., ``How I treat acute myeloid 
leukemia,'' Blood, 2010, vol. 116(17), pp. 3147-56.
    \194\ 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.
    \195\ 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.
    \196\ 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.
    \197\ Rowe, J.M., Tallman, M.S., ``How I treat acute myeloid 
leukemia,'' Blood, 2010, vol. 116(17), pp. 3147-56.
    \198\ 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.
    \199\ 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.
    \200\ 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.
    \201\ 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.
    \202\ 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.
    \203\ 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.
    \204\ 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.205 206 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 5 percent to 10 percent of AML cases, 
respectively.\207\ These activated mutations in FLT3 are oncogenic and 
show transforming activity in cells.\208\
---------------------------------------------------------------------------

    \205\ 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.
    \206\ 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].
    \207\ 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.
    \208\ 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.\209\ 
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.\210\ 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. \211 212 213\ According to the applicant,

[[Page 42258]]

patients who have been diagnosed with FLT3 mutation positive R/R AML 
have a substantial unmet medical need for treatment.
---------------------------------------------------------------------------

    \209\ 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.
    \210\ Sotak, M.L., et al., ``Burden of Illness of FLT3 Mutated 
Acute Myeloid Leukemia (AML),'' Blood, 2011, vol. 118(21), pp. 4765 
4765.
    \211\ Konig, H., Levis, M., ``Targeting FLT3 to treat leukemia. 
Expert Opin Ther Targets,'' 2015, vol. 19(1), pp. 37-54.
    \212\ 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.
    \213\ 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.
---------------------------------------------------------------------------

    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19337), we noted 
that the applicant had 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. Approval was granted for the following ICD-10-PCS procedure 
code effective October 1, 2019: XW0DXV5 (Introduction of Gilteritinib 
Antineoplastic into Mouth and Pharynx, External Approach, New 
Technology Group 5).
    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). In the proposed rule, we 
indicated that under current coding conventions it appeared 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 invited public comments on whether XOSPATA[supreg] is 
substantially similar to any existing technologies, and whether it 
meets the newness criterion.
    We did not receive any public comments concerning whether 
XOSPATA[supreg] meets the newness criterion.
    After consideration of the information provided by the applicant, 
we believe that XOSPATA[supreg] has a unique mechanism of action and 
treats a new patient population for which there are no other 
technologies currently available, and therefore is not substantially 
similar to existing technologies and 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 previously discussed trims, 407 potential cases 
remained. The applicant noted that it used only departmental charges 
that are used by CMS for rate setting.
    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 
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 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 in the FY 2020 IPPS/
LTCH PPS proposed rule, 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 further noted that, although the applicant used the proposed 
rule value to inflate the standardized charges, even when using the 
final rule value or the

[[Page 42259]]

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 invited public comments on whether 
XOSPATA[supreg] meets the cost criterion.
    We did not receive any comments on whether XOSPATA[supreg] meets 
the cost criterion. Based on the analysis described previously, we 
believe that 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.\214\
---------------------------------------------------------------------------

    \214\ 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.\215\
---------------------------------------------------------------------------

    \215\ 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.\216\
---------------------------------------------------------------------------

    \216\ 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.\217\
---------------------------------------------------------------------------

    \217\ 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, we 
stated in the proposed rule the applicant did not provide direct 
numbers for the comparator arm of the ADMIRAL study in its application. 
Because of this, we further stated we were concerned that it may be 
difficult to determine XOSPATA[supreg]'s comparative effectiveness. We 
noted that the ADMIRAL study was designed to evaluate efficacy and 
head-to-head trials were lacking. We indicated in the proposed rule 
that until the comparative data for both randomized arms were 
available, we were concerned that there may be insufficient evidence to 
determine that XOSPATA[supreg] provides a substantial clinical 
improvement over existing technologies.
    We invited public comments on whether XOSPATA[supreg] meets the 
substantial clinical improvement criterion.
    Comment: The applicant provided updated information on the results 
of the Phase 3 ADMIRAL trial. As noted above, patients in the ADMIRAL 
trial with relapsed or refractory AML were randomized to receive either 
XOSPATA[supreg] or salvage chemotherapy. The applicant provided 
additional information that the median overall survival for patients 
who received XOSPATA[supreg] was 9.3 months compared to 5.6 months for 
patients who received salvage chemotherapy. Hazard ratio was 0.64 with 
95 percent confidence levels of 0.49 to 0.83. The p-value was 0.0004. 
The applicant also provided information showing that the ADMIRAL trial 
showed a decrease of 34.5 percent in number of patients requiring the 
transfusion with RBC or platelets.
    Response: We appreciate the comments and additional data submitted 
by the applicant in response to our concerns. After consideration of 
the additional data provided, which shows an improvement in median 
overall survival for patients who received XOSPATA[supreg] compared to 
patients who received salvage chemotherapy, we believe XOSPATA[supreg] 
meets the substantial clinical improvement criterion.
    After consideration of the public comments we received, we have 
determined that XOSPATA[supreg] meets all of the criteria for approval 
of new technology add-on payments. Therefore, we are approving new 
technology add-on payments for FY 2020. Cases involving XOSPATA[supreg] 
that are eligible for new technology add-on payments will be identified 
by ICD-10-PCS code XW0DXV5 (Introduction of Gilteritinib

[[Page 42260]]

Antineoplastic into Mouth and Pharynx, External Approach, New 
Technology Group 5). In its application, the applicant estimated that 
the average Medicare beneficiary would require a dosage of 120mg/day 
administered as oral tablets in three divided doses. According to the 
applicant, the WAC for one dose is $250, and patients will typically 
require 3 tablets for the course of treatment with XOSPATA[supreg] per 
day for an average duration of 15 days. Therefore, the total cost of 
XOSPATA[supreg] per patient is $11,250. Under Sec.  412.88(a)(2) 
(revised as discussed in this final rule), we limit new technology add-
on payments to the lesser of 65 percent of the average cost of the 
technology, or 65 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 XOSPATA[supreg] is $7,312.50 for FY 
2020.
j. GammaTile TM
    GT Medical Technologies, Inc. submitted an application for new 
technology add-on payments for FY 2020 for the GammaTile TM. 
We note that Isoray Medical, Inc. and GammaTile, LLC previously 
submitted an application for new technology add-on payments for 
GammaTile TM for FY 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 for FY 2019. The 
GammaTile TM is a brachytherapy device for use in the 
treatment of patients who have been diagnosed with recurrent 
intracranial neoplasms, which uses cesium-131 radioactive sources 
embedded in a collagen matrix. GammaTile TM is designed to 
provide adjuvant radiation therapy to eliminate remaining tumor cells 
in patients who required surgical resection of recurrent brain tumors. 
According to the applicant, the GammaTile TM 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 
GammaTile TM 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 GammaTile TM 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 GammaTile TM 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 GammaTile TM 
technology received FDA clearance as a Class II medical device on July 
6, 2018. The cleared indications for use state that GammaTile 
TM is intended to deliver radiation therapy (brachytherapy) 
in 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 GammaTile TM 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 
GammaTile TM 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, GammaTile TM uses a new and unique 
mechanism of action to achieve a therapeutic outcome. The applicant 
explained that the GammaTile TM 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 GammaTile TM 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 GammaTile 
TM 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 GammaTile TM 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, GammaTile TM 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 
GammaTile TM 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 GammaTile TM is shorter compared to other 
brachytherapy isotopes, this results in a more rapid and effective 
energy deposition than other isotopes

[[Page 42261]]

with longer half-lives. Therefore, applicant believes that GammaTile 
TM 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 GammaTile TM 
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 GammaTile TM 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 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 
GammaTile TM will greatly expand the availability of 
treatment beyond research programs at highly specialized cancer 
treatment centers.
    Based on the previous discussion, the applicant concluded that the 
GammaTile TM technology is not substantially similar to 
other existing technologies and meets the newness criterion.
    However, in the proposed rule we stated that we were concerned that 
the mechanism of action of the GammaTile TM may be the same 
or similar to current forms of radiation therapy or brachytherapy. 
Specifically, we stated that while the placement of the cesium-131 
source (or any radioactive source) in a collagen matrix offset may 
constitute a new delivery vehicle, we were 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 questioned 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 GammaTile 
TM.
    We invited public comments on whether the GammaTile TM 
technology is substantially similar to any existing technologies and 
whether it meets the newness criterion.
    Comment: We received multiple comments in support of the claim that 
GammaTile TM is not substantially similar to existing 
technologies. A commenter stated that GammaTile TM was 
designed to provide a fundamentally new mechanism, permitting cells 
within the targeted area surrounding the tumor excision cavity to 
receive therapeutic levels of radiation while eliminating hot spots 
that have occurred with traditional brachytherapy. Commenters stated 
that due to the consistency of construction and relative ease of 
placement, GammaTile TM would provide a promising 
therapeutic treatment to patients nationwide. The applicant also 
provided additional information to support its assertion that GammaTile 
TM meets the newness criterion. Specifically, the applicant 
stated that the GammaTileTM is the only brachytherapy 
implant device with an indication cleared by the U.S. FDA that 
specifies an indication for treating recurrent brain tumors. The 
applicant stated that it is the only brachytherapy implant device 
designed to realign and retarget radiation in a three-dimensional 
surgical excision using a new mechanism of action with the integration 
of a geometric spacer to offset the brachytherapy sources from the 
tissues. According to the applicant, this focused radiation therapy is 
not possible either with external-beam radiation therapy (EBRT) using 
photons, electrons, protons, or other forms of external beam radiation, 
or with other brachytherapy sources or delivery devices. The applicant 
also asserted that GammaTileTM should not be disqualified 
from new technology add-on payments due to having the same or similar 
mechanism of action because it is a type of radiation therapy. The 
applicant stated that many pharmaceutical technologies utilize similar 
microscopic chemical effects, yet may yield differing macroscopic 
effects, and have been considered to utilize new mechanisms of action. 
The applicant asserts that radiation therapy agents should be similarly 
evaluated, asserting that otherwise, it could be argued that there can 
be no new mechanisms of action for either drugs or radiation sources, 
and that such a conclusion would be inconsistent with Congressional 
intent and efforts to promote patient access to innovation, or the 
overall mission of CMS. The applicant stated that 
GammaTileTM provides a new mechanism of action when compared 
to existing technologies and this new mechanism plays a primary role in 
achieving the positive therapeutic outcomes seen in the clinical data.
    Response: We appreciate the information provided by the applicant 
and commenters. After consideration of comments, we believe that the 
GammaTileTM mechanism of action is different from current 
forms of radiation therapy and brachytherapy as it is the first FDA 
cleared device to use a manufactured collagen matrix which offsets 
radiation sources for use for the treatment of recurrent intracranial 
neoplasms. Therefore, the GammaTileTM is not substantially 
similar to existing brachytherapy technology and 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 GammaTile TM 
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

[[Page 42262]]

charges associated with placement of the GammaTile TM 
device, as well as standardized charges for the GammaTile TM 
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 GammaTile 
TM 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 GammaTile TM device.
    As indicated in the proposed rule, 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 invited 
public comments on whether the GammaTile TM technology meets 
the cost criterion.
    We received no comments on whether the GammaTile TM 
technology meets the cost criterion. Based on the analysis above, we 
believe that GammaTile TM meets the cost criterion.
    With regard to substantial clinical improvement, the applicant 
stated that the GammaTile TM 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 GammaTile TM 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 GammaTile TM 
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 GammaTile TM 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.\218\ 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.
---------------------------------------------------------------------------

    \218\ 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.
---------------------------------------------------------------------------

    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 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.\219\ 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.
---------------------------------------------------------------------------

    \219\ 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,\220\ 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.
---------------------------------------------------------------------------

    \220\ 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

[[Page 42263]]

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 \221\, 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).
---------------------------------------------------------------------------

    \221\ 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.\222\ 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 previously described. 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.
---------------------------------------------------------------------------

    \222\ 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 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;

[[Page 42264]]

     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 previously presented data, the 
applicant believed that the use of the GammaTileTM 
technology represents a substantial clinical improvement over existing 
technologies. In the proposed rule, we stated a concern that the 
clinical efficacy and safety data provided by the applicant may be 
limited. We indicated that the findings presented appear to be derived 
from relatively small case-studies and not data from clinical trials 
conducted under an FDA-approved investigational device exemption 
application. We further stated that, while the applicant described 
increases in median time to disease recurrence in support of clinical 
improvement, we were 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 were concerned that many of the studies 
involved the use of prototype devices, and not the actual manufactured 
device. Finally, while the FDA cleared the 510(k) submission for 
GammaTileTM authorizing marketing of the device for the 
cleared indications for use, we noted in the proposed rule that the 
FDA's issuance of a ``substantial equivalence determination'' for the 
GammaTile did not indicate a review of any specific superiority claims 
to a predicate device.
    We invited public comments on whether the GammaTileTM 
technology meets the substantial clinical improvement criterion.
    Comment: Multiple commenters wrote in support that 
GammaTileTM meets the substantial clinical improvement 
criterion. A commenter stated that GammaTileTM provides a 
meaningful benefit to a vulnerable population of patients, and promises 
substantial clinical improvement over the management options currently 
available for the treatment of recurrent brain tumors. Another stated 
that there was growing evidence that that patients are living longer 
without tumor recurrence, and with less associated morbidity and an 
improved quality of life.
    The applicant also provided additional information, including in 
response to several of CMS's concerns. First, they stated that the data 
are not limited and the data do not come from relatively small studies. 
The applicant stated that most of the clinical data come from a robust, 
comprehensive study. The applicant included a reference to its study, 
described on ClinicalTrials.gov under NCT03088579, which included 79 
recurrent, previously irradiated intracranial neoplasms. The applicant 
clarified that over the course of previous submissions to CMS, they 
presented interim data which may have given the impression that the 
data came from smaller, disconnected studies, which was not the case. 
The applicant stated that they received two peer-reviewed awards for 
comprehensive clinical trial reporting on the treatment of 79 recurrent 
brain tumors treated with GammaTile.TM
    The applicant noted CMS's statement that the data did not appear to 
come from ``FDA approved trials'' and CMS's statement that the FDA 
review did not indicate a review of superiority claims. The applicant 
responded that in its initial review of the GammaTileTM, the 
FDA required information regarding the effect of radiation exposure on 
the collagen tile and extensive animal model implant testing, including 
brain implantation, and that the applicant also provided to FDA 
information regarding the Gamma TileTM clinical trial data 
involving 79 consecutive recurrent brain tumors. The applicant further 
noted that the Gamma TileTM is the only brachytherapy 
implant device with an indication cleared or approved by the U.S. Food 
and Drug Administration that specifies an indication for treating 
recurrent brain tumors.
    In response to CMS's concern as to whether additional analysis, 
meta-analysis, or statistical tests are needed to compare the 
GammaTileTM to other treatment modalities, such as external 
beam radiation or other forms of brachytherapy, the applicant commented 
that there is ample information and data available to conclude that the 
GammaTileTM is a substantial clinical improvement over 
existing options. The applicant stated that they collaborated with a 
biostatistics firm to advise to ensure the analysis of their data meets 
the highest standards. Specifically, they stated that in the clinical 
trial involving 79 recurrent brain tumors, each patient served as their 
own control. The applicant asserted that this minimized the potential 
influence of confounding variables such as age, gender, and treatment 
team. The clinical endpoints included time to tumor progression and 
survival, which the applicant states provided objective, clinically 
important measures. The median local control after 
GammaTileTM therapy versus prior treatment was 12.0 versus 
9.5 months for high-grade glioma patients and 48.8 months versus 23.3 
months for menigioma patients. For the metastasis patients, the median 
local control had not been reached versus 5.1 months with prior 
treatment. The median overall survival was 12.0 months for high grade 
glioma patients, 12.0 months for brain metastasis patients, and 49.2 
months for the meningioma patients.
    Additionally, the applicant pointed out that the majority of 
patients in the studies had failed a course of treatment that included 
external beam radiation. The applicant stated that most had already 
reached the maximum allowable amount of external beam radiation, and 
repeating more of the same treatment as a control arm could not be 
justified. The applicant reiterated that multiple studies demonstrated 
that GammaTileTM performed in a superior manner compared to 
adverse event rates for other therapies. In response to CMS's concern 
that studies were performed with prototype devices, not commercially-
manufactured final products, the applicant stated that in the 
manufacturing process, the assembly of the GammaTileTM is 
reproduced to exacting specifications that are highly consistent with 
the process used with the prototype and from patient to patient.
    Finally, the applicant provided study data with updated analysis of 
patient

[[Page 42265]]

outcome data to CMS. The applicant provided a recent summary 
presentation on the 79 cases at The American Brachytherapy 
Society.\223\ The applicant stated that these data demonstrate 
dramatic, clinically meaningful difference in Kaplan-Meier curves 
comparing time to local recurrence at same site in the same patients. 
The applicant stated that GammaTileTM is significantly 
outperforming the initial therapies attempted in this patient 
population and the pattern in findings is consistent across all three 
sub-groups of patients (recurrent meningiomas, recurrent gliomas, and 
recurrent brain metastases). The applicant stated that the data 
demonstrate reduced complication rates compared to external beam 
radiation and standard brachytherapy.
---------------------------------------------------------------------------

    \223\ Brachman D., Youssef E., Dardis C., et al.: Surgically 
Targeted Radiation Therapy: Safety Profile of Collagen Tile 
Brachytherapy in 79 Recurrent, Previously Irradiated Intracranial 
Neoplasms on a Prospective Clinical Trial. Brachytherapy 18 (2019) 
S35-36.
---------------------------------------------------------------------------

    Response: After further review, CMS continues to have concerns with 
respect to whether GammaTileTM meets the substantial 
clinical improvement criterion to be approved for new technology add-on 
payments. In particular, we note that the study performed on 79 
patients was a single-arm and single-institution study, where each 
patient functioned as their own control and the study goal was to 
compare the time to local recurrence after GammaTileTM 
treatment to the time of local recurrence after initial treatment of 
intracranial tumors. That is, the control arm were patients treated for 
initial intracranial brain tumors, and the treatment arm or the 
GammaTileTM treatment arm were the same control patients now 
experiencing local recurrent intracranial brain tumors in the same site 
with the same brain tumor type. In this clinical trial, the applicant 
compared the time from initial treatment to first local recurrence 
(control arm) vs. time from GammaTileTM treatment of first 
local recurrence to second local recurrence of the same brain tumor 
site and tumor type. Based on the data, there was no statistically 
significant difference between the control arm treatment and 
GammaTileTM treatment.
    Additionally, the applicant also shared the data on the initial 20 
of 79 patients which was published (Brachman D, Youssef E, Dardis CJ, 
et al. ``Resection and permanent intracranial brachytherapy using 
modular, biocompatible cesium-131 implants: results in 20 recurrent, 
previously irradiated meningiomas'' J Neurosurg Dec212018 pp1-10). The 
authors of this published article identified the following potential 
study limitations related to a single-arm, single-institution trial 
design: (1) Potential confounding, due to a lack of a control group, 
from the possibility that some tumors may have achieved local control 
due to repeat surgery alone and not necessarily from 
GammaTileTM intraoperative placement; (2) a lack of 
technical generalizability since all the initial patients were treated 
in a single center; and (3) reporting on a subset of a study's enrolled 
patients can either overestimate or underestimate the utility of the 
reported therapy. While we acknowledge the difficulty in establishing 
randomized control groups in studies involving recurrent brain tumors, 
after careful review of all data received to date, we find the data did 
not show a statistically significant difference between the time to 
first recurrence in the control arm in comparison to the time to second 
recurrence in the GammaTileTM treatment arm. Based on the 
information stated above, we are unable to make a determination that 
GammaTileTM technology represents a substantial clinical 
improvement over existing therapies. Therefore, we are not approving 
new technology add-on payments for the GammaTileTM for FY 
2020.
k. 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).\224\ 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.\225\ The applicant stated that it envisioned 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.
---------------------------------------------------------------------------

    \224\ 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.
    \225\ 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.
---------------------------------------------------------------------------

    In its application for new technology add-on payments, the 
applicant reported 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 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

[[Page 42266]]

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 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 and 
received FDA approval on May 24, 2019 for the treatment of steroid-
refractory aGVHD in adult and pediatric patients 12 years and older 
226 227. 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.
---------------------------------------------------------------------------

    \226\ FDA website: https//www.fda.gpv/drugs/resources-
information-approved-drugs/fda-approves-ruxolitinib-acute-graft-
versus-host-disease.
    \227\ Jakafi Prescribing Information: https://www.acessdata.fda.gov/drugsatfda_docs/label/2019/202192s017lb1.pdf.
---------------------------------------------------------------------------

    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19347), we noted 
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. The 
applicant was approved for an ICD-10-PCS code, XW0DXT5 (Introduction of 
ruxolitinib into mouth and pharynx, external approach, new technology 
group 5), effective October 1, 2019.
    As previously stated, if a technology meets all three of the 
substantial similarity criteria as previously described, 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.\228\ 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.
---------------------------------------------------------------------------

    \228\ 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, in its application for new 
technology add-on payments, the applicant asserted 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 in the proposed rule and in this final 
rule, the applicant maintained that JAKAFITM is not 
substantially similar to any existing technology. We noted in the 
proposed rule, 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 noted 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 
stated that, therefore, we believed that JAFAKITM may have a 
similar mechanism of action as existing therapies. Finally, we stated 
in the proposed rule that 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 invited public comments on whether 
JAKAFITM is substantially similar to any existing 
technologies, including with respect to the concerns we raised, and 
whether the technology meets the newness criterion.
    Comment: In its public comment, the applicant stated that CMS is 
incorrectly comparing JAKAFITM to other therapies that treat 
similar patient populations and utilize the same MS-DRG for the 
diagnosis of aGVHD. They stated that JAKAFITM is the first 
and only FDA-approved medicine for the aGVHD patient population and has 
a novel mechanism of action that is distinct from the unapproved 
treatment options that attempt to suppress the body's immune response 
in patients with steroid-refractory aGVHD. Furthermore, they stated 
that JAKAFITM, a kinase inhibitor, inhibits Janus Associated 
Kinases (JAKs) JAK1 and JAK2, which mediate the signaling of a number 
of cytokines and growth factors that are important for hematopoiesis 
and

[[Page 42267]]

immune function.\229\ They also stated that JAK signaling involves 
recruitment of signal transducers and activators of transcription 
(STATs) to cytokine receptors, activation and subsequent localization 
of STATs to the nucleus leading to modulation of gene expression and 
that JAK-STAT signaling pathways play a key role in regulating the 
development, proliferation, and activation of several immune cell types 
important for GVHD pathogenesis. The commenter further stated that 
JAKAFITM has been extensively evaluated in preclinical 
models in steroid-refractory acute GVHD and that in a mouse model of 
acute GVHD, oral administration of JAKAFITM was associated 
with decreased expression of inflammatory cytokines in colon 
homogenates and reduced immune-cell infiltration in the colon. 
Additionally, they stated that in this study, significant improvements 
in body weight were observed in JAKAFITM-treated mice and 
that in the same mouse model, steroids were shown to not be as 
effective in ameliorating disease severity, as compared to 
JAKAFITM and steroid-treated animals had shown significant 
disease improvement upon switching to JAKAFITM. Lastly they 
stated that, treatment with JAKAFITM was shown to 
significantly enhance survival in the major histocompatibility (MHC)-
mismatched mouse model of aGVHD as compared to vehicle control.
---------------------------------------------------------------------------

    \229\ 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 also asserted that MS-DRGs are broad payment 
groupings that are organized based on diagnosis and/or procedures 
performed during an inpatient hospitalization (for example, Allogeneic 
Bone Marrow Transplantation; Major Hematological and Immunological 
Diagnoses Except Sickle Cell Crisis and Coagulation Disorders) and that 
MS-DRGs do not provide a relevant means to determine newness. Per the 
applicant, the fact that JAKAFITM and the unapproved 
treatment options overlap in the same MS-DRG does not acknowledge the 
clinical benefit that JAKAFITM offers patients with aGVHD.
    Another commenter expressed support for JAKAFI\TM\. They stated 
that aGVHD remains the most important barrier to successful outcomes of 
an allogeneic stem cell transplant and that only ~50 percent of 
patients respond to corticosteroids. They stated that those who do not, 
have a 1 year mortality of ~70 percent to 80 percent. They also stated 
that prior to the FDA approval of JAKAFI\TM\ on May 24, 2019, this 
remained an unmet need since most of the available off-label therapies 
are non-targeted in their approach. They asserted that the mechanism of 
JAKAFI\TM\ is well-defined, and novel. They stated that none of the 
alternative ``best available therapies'', which are all off-label, have 
a well-defined mechanism of action or targeted approach. Thus, the 
commenter believed that JAKAFI\TM\ represents a first-in kind approach 
to steroid-refractory acute GVHD and that it meets the threshold for 
``newness'' as defined by CMS.
    Response: We appreciate the commenters' input on whether JAKAFI\TM\ 
meets the newness criterion. Upon review of the public comments and the 
clinical information presented by the applicant, we agree with the 
commenters that JAKAFI\TM\ meets the newness criterion. As noted by the 
applicant, JAKAFI\TM\ inhibits JAK1 and JAK2, which mediate the 
signaling of a number of cytokines and growth factors that are 
important for hematopoiesis and immune function and these signaling 
pathways play a key role in regulating the development, proliferation, 
and activation of several immune cell types important for GVHD 
pathogenesis, whereby other treatments that are used for aGVHD suppress 
the body's immune response in patients with steroid-refractory aGVHD. 
We believe this is a unique mechanism of action and therefore 
JAKAFI\TM\ is not substantially similar to other drug therapies used to 
treat steroid-refractory aGVHD and may provide treatment options for 
certain patients with steroid-refractory aGVHD who have not responded 
to other therapies. We consider May 24, 2019 the beginning of the 
newness period for JAKAFI\TM\.
    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 JAKAFI\TM\, 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 this table. 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 JAKAFI\TM\.

[[Page 42268]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.149


[[Page 42269]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.150

    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 JAKAFITM, it provided two scenarios to 
demonstrate that JAKAFITM 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 JAKAFITM. 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). (In the proposed rule, we noted 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 JAKAFITM 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 JAKAFITM meets the cost criterion 
because the inflated average case-weighted standardized

[[Page 42270]]

charge per case exceeds the average case-weighted threshold amount.
    As noted in the proposed rule and this final rule, the applicant 
also submitted a second scenario to demonstrate that 
JAKAFITM 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 JAKAFITM also meets the cost criterion under 
this scenario.
    We invited public comments on whether JAKAFITM meets the 
cost criterion.
    Comment: The applicant submitted a revised analysis of the two 
scenarios used to demonstrate that JAKAFITM meets the cost 
criterion. The applicant used a 2-year inflation factor of 1.08986 from 
the FY 2019 IPPS/LTCH PPS final rule correction notice to inflate the 
charges in both scenarios from FY 2017 to FY 2019. The applicant also 
added charges for the new technology. Under the first scenario, in 
which 100 percent of pharmacy charges were removed, the inflated 
average case-weighted standardized charge per case increased from 
$261,512 to $263,002. Under the second scenario, in which the applicant 
did not remove any pharmacy charges, the inflated average case-weighted 
standardized charge per case increased from $377,494 to $379,114. Based 
on this revised analysis, for both scenarios, the applicant determined 
that the inflated average case-weighted standardized charge per case 
for JAKAFITM exceeds the average case-weighted threshold 
amount of $172,493, and that JAKAFITM meets the cost 
criterion.
    Response: We appreciate the applicant's input and additional 
analysis. After consideration of the public comments we received, we 
agree with the applicant that JAKAFITM meets the cost 
criterion.
    With respect to the substantial clinical improvement criterion, in 
its application for new technology add-on payments, the applicant 
asserted that JAKAFITM represents a substantial clinical 
improvement because: (1) The technology offers a treatment option for a 
patient population previously ineligible for treatments because 
JAKAFITM 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 JAKAFITM, 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.\230\ Therefore, the 
applicant maintains that therapeutic options are limited for patients 
who are refractory to corticosteroid treatment for a diagnosis of 
aGVHD.
---------------------------------------------------------------------------

    \230\ 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 
JAKAFITM 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 JAKAFITM, 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 
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 JAKAFITM 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

[[Page 42271]]

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 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.
    In the proposed rule, we noted the following concerns with respect 
to whether JAKAFITM represents a substantial clinical 
improvement. First, we stated that 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 in the proposed rule 
and this final rule, 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).\231\ Numerous

[[Page 42272]]

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. In addition, we 
stated that 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.\232\ We stated that, 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.
---------------------------------------------------------------------------

    \231\ 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.
    \232\ 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 stated that 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, we noted that 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 acknowledged 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, we stated that 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, we stated that 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 was more 
difficult to fully assess the generalizability of the applicant's 
assertions to the Medicare population.
    Fourth, we noted that several patients enrolled in each of the 
studies provided by the applicant had safety-related complications, 
including cytopenias and CMV reactivation. We stated that these 
complications were concerning because the target population is already 
immunocompromised and at risk of serious infections.
    We invited public comments on whether JAKAFITM meets the 
substantial clinical improvement criterion, including with respect to 
the concerns we raised.
    Comment: The applicant submitted a comment addressing our concerns 
regarding substantial clinical improvement as indicated in the proposed 
rule. With respect to our concern that the applicant did not provide 
any data directly comparing the use of JAKAFITM to any 
second-line treatments, the applicant stated that no head-to-head, 
multicenter, randomized, well-controlled studies have been carried out 
to assess the efficacy and safety of second-line therapy for aGVHD and 
that clinicians rely on reports of retrospective studies and single-arm 
phase II studies to evaluate the merits of any given treatment \233\. 
They stated that comparison of results between these studies is 
complicated by the lack of standardized endpoints and the small numbers 
of patients included in most reports.
---------------------------------------------------------------------------

    \233\ Martin PJ, Rizzo JD, Wingard JR, 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;18(8):1150-1163.
---------------------------------------------------------------------------

    With respect to our concern regarding the methodologic approach of 
the studies submitted by the applicant in support of its assertions 
regarding substantial clinical improvement, the applicant stated that 
the FDA granted JAKAFITM Breakthrough Therapy Designation 
and Priority Review for aGVHD and asserted that these designations 
indicate that the FDA believes the product offers a significant and 
substantial clinical improvement when compared to standard therapies. 
The applicant also referred to the prospective, open-label, single-arm, 
multicenter, pivotal study (REACH1) that was the basis for the FDA's 
approval of JAKAFITM for treatment of steroid-refractory 
acute GVHD in adults and pediatric patients 12 years and older. The 
applicant reiterated that the primary endpoint in the REACH1 study was 
Day 28 overall response rate (ORR) (complete response, very good 
partial response or partial response) as defined by Center for 
International Blood and Marrow Transplant Research (CIBMTR) criteria, 
and that the ORR at Day 28 in the patients who were refractory to 
steroids alone and evaluable for efficacy was 57.1 percent (28/49). The 
applicant stated that the majority of these 28 patients had achieved a 
CR (53.6 percent, 15/28) and that Day 28 ORR was 100 percent for Grade 
II aGVHD, 40.7 percent for Grade III aGVHD, and 44.4 percent for Grade 
IV2 aGVHD.
    The applicant also stated that the key secondary endpoint in REACH1 
was duration of response. The duration of response, at the time of the 
3-month data cutoff, was calculated using two measures:
     From Day-28 response to progression, new salvage therapy 
for acute GVHD or death from any cause (with progression being defined 
as worsening by one stage in any organ without improvement in other 
organs in comparison to prior response assessment). The median duration 
of response by this definition was 16 days (95 percent CI 9, 83).
     From Day-28 response to either death or need for new 
therapy for aGVHD (additional salvage therapy or increase in steroids). 
The median duration of response by this definition was 173 days (95 
percent CI 66, NE).
    The applicant further stated that, as described in its initial 
application, patients who develop steroid-refractory aGVHD can progress 
to severe disease, with 1-year mortality rates of 70-80 percent; the 
weighted average 6-month survival estimate across 25 studies that 
reported 6-month overall survival was 49 percent; the overall 
distribution of 6-month survival rates was similar for prospective and 
retrospective studies; the largest study tested horse antithymocyte 
globulin (ATG) in 79 patients, and reported a 6-month survival estimate 
of 44 percent; and hence, this study has previously been used as a 
reference point for the

[[Page 42273]]

interpretation of survival results in other studies.
    With respect to our concerns about the generalizability of the 
applicant's assertions to the Medicare population, the applicant stated 
that of the 49 patients that were evaluable for efficacy, the mean age 
was 57 (range, 18-72 years). They also stated that the exploratory 
subgroup analysis shows that 12 percent were of Medicare-eligible age 
(that is, >= 65 years) and that the exploratory subgroup analysis 
showed that JAKAFITM demonstrates clinical activity across 
patients <65 and >= 65 years. Lastly they stated that of all patients 
enrolled in REACH1 (n = 71), 18 percent were of Medicare-eligible age, 
and is supportive of the Medicare patient population of 25 percent 
estimated in their new technology add-on payment application.
    Finally, with respect to our concern that several patients enrolled 
in each of the studies provided by the applicant had safety-related 
complications, including cytopenias and CMV reactivation, which is 
concerning because the target population is already immunocompromised 
and at risk of serious infections, the applicant stated that in the 
REACH1 study, the adverse event profile was consistent with the 
observed safety profiles of JAKAFITM and that of patients 
with steroid-refractory acute GVHD. They also stated that hematologic 
laboratory abnormalities were evaluated in the REACH1 study during 
JAKAFITM treatment and based on laboratory parameters, all 
grade anemia, thrombocytopenia, and neutropenia were reported in 75 
percent, 75 percent, and 58 percent of patients, respectively. They 
also presented the following information: Anemia, thrombocytopenia, and 
neutropenia were reported as Grade 3 or 4 (worst grade during 
treatment) in 45 percent, 61 percent, and 40 percent of patients, 
respectively; treatment-emergent cytopenias led to discontinuation of 
Jakafi in 2 patients; infections occurred in 55 percent of enrolled 
patients, with 41 percent being Grade \3/4\ in severity; infections led 
to treatment discontinuation in 10 percent of patients; related to 
cytomegalovirus (CMV), all patients who had a CMV event (n = 14, 19.7%; 
includes CMV infection [n = 10, 14.1%] and recurrent CMV viremia [n = 
4, 5.6%]) had a positive CMV donor or recipient serostatus or both at 
baseline. They stated that no deaths were attributed to CMV events in 
the study.
    Another commenter stated that steroid-refractory aGVHD has a dismal 
outcome with currently ``best-available therapy'' that are all off-
label, and the 1 year survival rate of these patients is less than 20 
percent to 30 percent. The commenter stated that in the REACH1 study, 
among the 49 patients evaluable for efficacy, the median survival was 
333 days (95 percent CI, 93-NE) at the time of the 3-month data cutoff. 
The estimated 6-month and 12-month survival for Day 28 responders was 
70.6 percent (95 percent CI, 47.3 percent-85 percent) for both time 
points. The commenter concluded that a significant proportion of 
patients are impacted favorably. Regarding the risk of infections, the 
commenter provided the following information: There is global immune 
dysfunction in patients with corticosteroid refractory acute GVHD; in 
the setting of a clinical trial for this subset of patients, it is 
tough to assess the impact of the intervention versus the baseline risk 
of infection; and in the REACH-1 study, it was noted that there were no 
treatment emergent fatal events related to CMV, which is an important 
viral infection in patients undergoing allogeneic stem cell transplant. 
The commenter stated that as a clinical investigator, they believe that 
early intervention with JAKAFITM (in patients meeting 
criteria of steroid-refractory aGVHD) will further decrease the risk of 
global immune-dysfunction, and lead to further decrease in infection in 
responders, as clinicians will be able to spare corticosteroids.
    Response: We appreciate the commenters' input. After consideration 
of the public comments we received, we agree that JAKAFITM 
is a treatment option which offers a substantial clinical improvement 
over standard therapies for patients who have been diagnosed with 
steroid-refractory aGVHD. We agree that current treatment options for 
patients with steroid-refractory aGVHD have a poor outcome and that the 
one year survival rate is not favorable. Additionally, the data cited 
by the applicant in its public comments from the Phase II REACH1 study 
demonstrated improved outcomes, including the following: Overall 
response rate at Day 28 in the patients who were refractory to steroids 
alone and evaluable for efficacy was 57.1 percent (28/49); the majority 
of the 28 patients who were refractory to steroids alone and evaluable 
for efficacy had achieved a CR (53.6 percent, 15/28); Day 28 ORR was 
100 percent for Grade II aGVHD, 40.7 percent for Grade III aGVHD, and 
44.4 percent for Grade IV2 aGVHD. In terms of safety, there were no 
treatment emergent fatal events related to CMV, which is an important 
viral infection in patients undergoing allogeneic stem cell transplant. 
Additionally, the REACH1 study included patients (18 percent) that were 
of Medicare-eligible age demonstrating the effectiveness of 
JAKAFITM in the Medicare population. Finally, the clinical 
information for JAKAFITM presented by the applicant 
demonstrates that certain patients with steroid-refractory aGVHD have 
better clinical outcomes than those who were not treated with 
JAKAFITM. Therefore, we believe that JAKAFITM 
meets the substantial clinical improvement criterion.
    After consideration of the public comments we received, we have 
determined that JAKAFITM meets all of the criteria for 
approval of new technology add-on payments. Therefore, we are approving 
new technology add-on payments for JAKAFITM for FY 2020. 
Cases involving JAKAFITM that are eligible for new 
technology add-on payments will be identified by ICD-10-PCS procedure 
code XW0DXT5, Introduction of ruxolitinib into mouth and pharynx, 
external approach, new technology group 5. According to the applicant, 
JAKAFITM has a WAC of $13,111 for 60 tablets/30 day supply 
(or approximately $218.52) per tablet, and patients will take 
JAKAFITM orally, twice per day, with an anticipated duration 
of treatment of 14 days. Therefore, the total cost of 
JAKAFITM per patient is $6,118.56. Under Sec.  412.88(a)(2 
(revised as discussed in this final rule), we limit new technology add-
on payments to the lesser of 65 percent of the costs of the new medical 
service or technology, or 65 percent of the amount by which the costs 
of the case exceed the MS-DRG payment. As a result, the maximum new 
technology add-on payment for a case involving the use of 
JAKAFITM is $3,977.06 for FY 2020.
l. Supersaturated Oxygen (SSO2) Therapy (DownStream[supreg] 
System)
    TherOx, Inc. submitted an application for new technology add-on 
payments for Supersaturated Oxygen (SSO2) Therapy (the 
TherOx 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. Per 
the FDA, SSO2 Therapy is indicated for the preparation and 
delivery of

[[Page 42274]]

SuperSaturated Oxygen Therapy (SSO2 Therapy) to targeted 
ischemic regions perfused by the patient's left anterior descending 
coronary artery immediately following revascularization by means of 
percutaneous coronary intervention (PCI) with stenting that has been 
completed within 6 hours after the onset of anterior acute myocardial 
infarction (AMI) symptoms caused by a left anterior descending artery 
infarct lesion. 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.
    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 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 2, 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. In this final rule, as in the 
proposed rule, 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 previously 
mentioned, 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, in the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19353), we noted 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 invited public comments on whether SSO2 Therapy is 
substantially similar to existing technologies and whether it meets the 
newness criterion.
    We did not receive any public comments on whether SSO2 
Therapy is substantially similar to existing technologies and whether 
it meets the newness criterion. However, based on

[[Page 42275]]

the information submitted by the applicant as part of its FY 2020 new 
technology add-on payment application for SSO2 Therapy, as 
discussed in the proposed rule (84 FR 19353) and as previously 
summarized in this final rule, we believe that SSO2 Therapy 
has a unique mechanism of action as it delivers a localized hyperbaric 
oxygen equivalent to the coronary arteries immediately after 
administering the standard-of-care, PCI with stenting, in order to 
restart metabolic processes within the stunned myocardium and reduce 
infarct size. Therefore, we believe SSO2 Therapy is not 
substantially similar to existing technologies and meets the newness 
criterion. We consider the beginning of the newness period to commence 
when SSO2 Therapy was approved by the FDA on April 2, 2019.
    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 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 previously discussed, 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 invited public comments on whether the SSO2 Therapy 
meets the cost criterion.
    We did not receive any public comments on whether SSO2 
Therapy meets the cost criterion. Based on the information submitted by 
the applicant as part of its FY 2020 new technology add-on payment 
application for SSO2 Therapy, as discussed in the proposed 
rule (84 FR 19353 through 19354) and as previously summarized in this 
final rule, the average case-weighted standardized charge per case 
exceeded the average case-weighted threshold amount. Therefore, 
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.\234\ 
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.\235\
---------------------------------------------------------------------------

    \234\ 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.
    \235\ 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.\236\ The analysis assessed infarct size 
within 1 month after randomization by either cardiac magnetic resonance 
(CMR) imaging or

[[Page 42276]]

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]; p<0.0001) and hospitalization for heart 
failure (adjusted hazard ratio: 1.20 [95 percent confidence interval: 
1.19 to 1.21]; p<0.0001), independent of other baseline factors.\237\ 
The applicant concluded from this study that infarct size, as measured 
by CMR or technetium-99m sestamibi SPECT within 1 month after primary 
PCI, is strongly associated with all-cause mortality and 
hospitalization for heart failure within 1 year.
---------------------------------------------------------------------------

    \236\ Stone, G.W., Selker, H.P., Thiele, H., et al., 
``Relationship between infarct size and outcomes following primary 
PCI,'' J Am Coll Cardiol, 2016, vol. 67(14), pp. 1674-83.
    \237\ Ibid.
---------------------------------------------------------------------------

    Next, to support the claim that SSO2 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.\238\ 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 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.\239\ 
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).\240\
---------------------------------------------------------------------------

    \238\ 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.
    \239\ Ibid.
    \240\ 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.\241\ 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.\242\ 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.\243\
---------------------------------------------------------------------------

    \241\ 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.
    \242\ Ibid.
    \243\ 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.\244\ 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.\245\
---------------------------------------------------------------------------

    \244\ 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.
    \245\ 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

[[Page 42277]]

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.\246\ 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).\247\ 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.\248\ 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.\249\ 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.
---------------------------------------------------------------------------

    \246\ 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.
    \247\ Ibid.
    \248\ Ibid.
    \249\ 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.250 251 According 
to the applicant, the key summary points from these animal studies are:
---------------------------------------------------------------------------

    \250\ 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.
    \251\ 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 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.
    In the proposed rule, we stated that we had the following concerns 
regarding whether the technology meets the substantial clinical 
improvement criterion. We noted that the standard-of-care for STEMI had 
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 noted 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. Therefore, we stated that we were 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 stated that we were concerned that 
the lack of a control may limit the interpretation of the data. We also 
were 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 invited 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.
    Comment: Several commenters submitted comments regarding CMS's 
concerns about whether SSO2 Therapy meets the substantial 
clinical improvement criterion. Many of these commenters summarized the 
history of STEMI care, beginning with the first breakthrough of 
thrombolytic therapy followed by interventional procedures with balloon 
angioplasty and subsequent stenting of the coronary blockage, which 
became widely accepted as the standard of care. These commenters 
affirmed the relationship between myocardial infarct size and long term 
clinical outcomes such as heart failure, rehospitalization and 
mortality. Several commenters referenced the CORE trial in which the 
size of the measured infarct was directly correlated with the rates of 
6-month death in 1,164 STEMI patients treated with thrombolytic 
therapy. The CORE trial found that every reduction in infarct size by 
an absolute 5 percent of the left ventricle correlated with a 17-18 
percent improvement in survival). The commenters also referenced a 
recent meta-analysis of 2,632 patients from 10 randomized controlled 
trials with STEMI who underwent PCI and then had their infarct size 
measured within the next several days. The meta-analysis showed that 
myocardial infarction size was strongly associated with 1-year 
hospitalization for heart failure and all-cause mortality, and that for 
every 5 percent increase in MI size, there was a 20 percent increase in 
relative hazard ratio for 1-year hospitalization for heart failure and 
all-cause mortality. A commenter emphasized that the relationship 
between infarct size and outcomes is not dependent on the mode of 
therapy delivered during patient treatment; reduced infarct size, no 
matter how it is accomplished, has been associated with improved 
survival and reduced heart failure and rehospitalization.
    With respect to the validity of the AMIHOT I and AMIHOT II studies 
given the advancements in STEMI care since the trials were conducted, 
the commenters believed that the treatment of STEMI patients had not 
changed since the AMIHOT II study was conducted, and that no new 
adjunct pharmacology or device had been proven clinically beneficial 
until SSO2 Therapy. Several commenters asserted

[[Page 42278]]

that SSO2 Therapy is the first treatment (adjunctive or 
otherwise) in three decades of trials to significantly reduce 
myocardial infarct size and that it has not been superseded by any 
recent strategies or devices. Another commenter explained that the 
evolution in STEMI care since the advent of stenting can be attributed 
to improvement in the stents' material (for instance, the introduction 
of drug coating) and the organization of medical care, including 
reducing time from symptom onset to first medical contact, door-to-
balloon time, total ischemic time, and improved antithrombotic therapy. 
The commenter acknowledged that these developments improved clinical 
outcomes and reduced mortality, but that they all occur in the clinical 
workflow prior to the therapeutic intervention, which has remained 
unchanged since the advent of drug-eluting stents. A commenter noted 
that short term 30 day mortality for STEMI patients has dropped 
steadily from 10-20 percent to under 5 percent with the latest 
generation drug eluting stents. However, another commenter pointed out 
that the mortality rate has not changed in recent years for STEMI 
treated with PCI. Another commenter noted that large infarctions still 
occur in spite of the advances in PCI, and that many therapies have 
failed to demonstrate better outcomes beyond that obtained from timely 
reperfusion alone.
    A commenter stated that until the development of the 
SSO2 Downstream System there was no practicable method 
available for treating critically ill STEMI patients with hyperoxemic 
coronary perfusion. The commenter stated that even with rapid treatment 
of AMI itself by PCI, the infarct size and loss of heart muscle is 
often substantial, resulting in heart failure. The commenter also 
stated that numerous drugs and devices have been studied to reduce 
heart failure after STEMI, including fluosol, magnesium, RheothRx, 
trimetazidine, hSOD, cylexin, adenosine, anti-CD18 antibodies, 
eniporide, pexelizumab, tilarginine, EPO, sodium nitrate, cyclosporine, 
TRO40303, delcasertib, metformin, bendavia, aspiration thrombectomy, 
distal embolic protection, hypothermia, pre- and post-conditioning, 
cell therapy and others. According to the commenter, none have been 
convincingly effective, and most have been costly and have had side-
effects.
    With respect to the availability of long-term data to validate the 
efficacy and safety data of the AMIHOT II and IC-HOT studies, many of 
the commenters reiterated the results of these studies as presented in 
the original application and as previously summarized in this final 
rule. Specifically, the commenters highlighted (1) the 26 percent 
relative and 6.5 percent absolute reduction in median infarct size 
compared to the control group (p = 0.02) in the AMIHOT II study, and 
(2) the 0 percent mortality and 1 percent incidence of congestive heart 
failure at both 30 days and at 1 year in the IC-HOT study. A commenter 
noted that the relatively low, median infarct size by CMR at 30 days in 
the IC- HOT trial was nearly identical to the median value at 2 weeks 
by perfusion imaging in the AMIHOT II trial. The commenter stated that 
infarct size remained unchanged over the 30 day follow up period, and 
asserted that further changes in infarct size are therefore extremely 
unlikely. The same commenter noted that the very low percentage of 
microvascular occlusion that was found in the IC-HOT trial at day 30 
also portends a favorable long term outcome.
    Most commenters also referred to a formal analysis comparing the 
clinical outcomes in SSO2 treated patients to those of a 
case-matched historical control population. This analysis compared the 
1-year clinical outcomes from the IC-HOT study to a propensity score-
matched population from a similar patient cohort of high-risk anterior 
STEMI patients enrolled in the INFUSE-AMI trial (n=83 patients per arm 
for the matched analysis). Per the commenters, statistically 
significant reductions in mortality and heart failure were observed at 
one year post treatment. At 1 year after PCI, mortality was 7.6 percent 
in the control group from the INFUSE-AMI trial vs. 0.0 percent in the 
SSO2 therapy group (p = 0.01). Furthermore, new onset heart 
failure or heart failure readmissions occurred in 7.4 percent in the 
INFUSE-AMI group vs. 0.0 percent in the SSO2 Therapy group 
(p = 0.01). A commenter noted that because these results are non-
randomized, were drawn from 2 separate studies, are from a modest 
number of patients, and the effect size is better than would be 
expected in a large trial (noting that no therapy will completely 
eliminate death and HF after anterior STEMI), they should be considered 
hypothesis generating. Nonetheless, the commenter stated that they do 
suggest long-term clinical improvement with SSO2 Therapy, 
consistent with the proven reduction in infarct size.
    Response: We thank the commenters for their input. We appreciate 
the additional background on the evolution of STEMI care and agree with 
the commenters that infarct size can be strongly correlated with 
outcomes such as heart failure, rehospitalization, and mortality. We 
agree that the results of the AMIHOT I, AMIHOT II, and IC-HOT studies 
are promising and suggest the potential for long term clinical 
improvement with SSO2 Therapy consistent with the reduction 
in infarct size demonstrated by imaging. However, we are uncertain if 
the clinical improvement seen in these studies is necessarily a result 
of infarct size reduction after SSO2 Therapy use, or other 
developments in STEMI care delivery. That is, it is unclear, based on 
the information provided, the incremental effect of SSO2 
Therapy on clinical outcomes as compared to the current standard of 
care, PCI with stenting but without the SSO2 Therapy as an 
adjunctive treatment.
    After consideration of all the information from the applicant, as 
well as the public comments we received, we are unable to determine 
that SSO2 Therapy represents a substantial clinical 
improvement over the currently available therapies used to treat STEMI 
patients. We remain concerned that the current data does not adequately 
support a sufficient association between the outcome measures of heart 
failure, rehospitalization, and mortality with the use of 
SSO2 Therapy specifically to determine that the technology 
represents a substantial clinical improvement over existing available 
options. Therefore, we are not approving new technology add-on payments 
for SSO2 Therapy for FY 2020.
m. 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. Per the FDA 
cleared indication, results from the T2Bacteria Panel are not intended 
to be used as the sole basis for diagnosis, treatment, or other patient 
management decisions in patients with suspected bacteremia. Concomitant 
blood cultures are necessary to recover organisms for susceptibility 
testing or further identification, and for organisms not detected by 
the T2Bacteria Panel. However, the applicant noted that the T2 Bacteria 
Panel is a multiplex diagnostic panel that detects five major bacterial 
pathogens (Enterococcus faecium, Escherichia coli, Klebsiella

[[Page 42279]]

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.252 253 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.
---------------------------------------------------------------------------

    \252\ 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.
    \253\ 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.\254\ 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.
---------------------------------------------------------------------------

    \254\ 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 in the FY 2020 IPPS/LTCH PPS proposed rule and as 
previously stated in this final rule, 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.255 256 According to the applicant, a recent 
retrospective analysis of 13 U.S. hospitals and over 150,000 cultures 
found a median blood culture time for species ID of 43 hours.\257\
---------------------------------------------------------------------------

    \255\ 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.
    \256\ 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.
    \257\ 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.\258\ 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.
---------------------------------------------------------------------------

    \258\ 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 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. In the 
proposed rule (84 FR 19357), we noted that the applicant had 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. 
T2Bacteria[supreg] Panel was granted approval for the ICD-10-PCS code 
XXE5XM5 (Measurement of Infection, Whole Blood Nucleic Acid-base 
Microbial Detection, New Technology Group 5), effective October 1, 
2019.
    As previously discussed, 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

[[Page 42280]]

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 is 
a diagnostic aid in the treatment of sepsis caused by fungal infections 
in the blood and thus achieves a different therapeutic outcome than the 
T2Bacteria[supreg] Panel.
    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 stated in the proposed rule that we believed cases 
involving the use of the technology would be assigned to the same MS-
DRGs as cases involving the current standard-of-care of 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.
    In the proposed rule, we stated our concern that the mechanism of 
action of the T2Bacteria[supreg] Test Panel may be similar to the 
mechanism of action used by laboratory blood cultures or other 
available diagnostic tests that are the current standard of care. While 
the applicant stated that the T2Bacteria[supreg] Test Panel has a 
unique mechanism of action, we noted 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 stated that we were concerned with 
the similarity of this mechanism of action. We invited 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.
    Comment: A commenter submitted a comment in response to CMS' 
concern that the T2Bacteria[supreg] Test Panel has a mechanism of 
action which is similar to currently available diagnostic tests. The 
commenter stated that while it is the case that the T2Bacteria[supreg] 
Test Panel uses DNA to identify bacteria species, its unique feature is 
the rapid identification of bacteria without the requirement for blood 
culture and/or other diagnostic techniques. The commenter stated that 
they knew of no other FDA cleared diagnostics for which this is the 
case.
    Two commenters stated that the T2Bacteria[supreg] Test Panel 
detects bacterial-associated DNA differently than all other FDA cleared 
products because it does not depend on a positive blood culture and 
bacterial cell growth to detect pathogens. The commenters added that 
this innovation is due to magnetic resonance detection used by the 
T2Bacteria[supreg] Test Panel.
    The applicant submitted a comment stating that the 
T2Bacteria[supreg] Test Panel does not use the same or similar 
mechanism of action compared to an existing technology. The applicant 
stated that all other bloodstream pathogen identification methods 
require a positive blood culture and that the T2Bacteria[supreg] Test 
Panel has a limit of detection greater than 1,000 times lower than any 
bloodstream pathogen identification method, allowing it to be used 
directly on patient blood samples without culturing. Lastly the 
applicant stated that while the T2Bacteria Panel does identify species 
with DNA, the differences from direct and independent detection, lack 
of growth, and lack of interference from antibiotics and competitive 
growth relative to all other FDA cleared diagnostics distinguishes the 
T2Bacteria Panel as a novel technology.
    In response to CMS' concern that the T2Bacteria[supreg] Test Panel 
was similar to the blood cultures in that they both require DNA tests 
to identify bacterial species, a commenter stated that DNA tests are 
not required to identify bacteria from blood cultures. The commenter 
stated that most institutions still use traditional microbiology 
techniques (for example, biochemical reaction tests) to identify 
bacterial species.
    Response: We appreciate the commenters' input and the additional 
information provided by the applicant in response to our concerns in 
the proposed rule. After consideration of the public comments we 
received and information submitted by the applicant in its application, 
we believe that the T2Bacteria[supreg] Test Panel uses a unique 
mechanism of action to achieve a therapeutic outcome because it works 
differently than currently available therapies through magnetic 
resonance detection to detect bacterial DNA directly from patient blood 
samples. Therefore, we believe T2Bacteria[supreg] Test Panel is not 
substantially similar to existing technologies and 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.259 260 261 262 263 The applicant asserted that 
the T2Bacteria[supreg] Test Panel can identify three Gram-negative 
blood 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

[[Page 42281]]

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.
---------------------------------------------------------------------------

    \259\ 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.
    \260\ 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.
    \261\ 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.
    \262\ 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.
    \263\ 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. In 
this final rule, as in the proposed rule, 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.

[[Page 42282]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.151


[[Page 42283]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.152

    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 invited public comments on whether the T2Bacteria[supreg] Panel 
meets the cost criterion.
    Comment: A commenter stated that cost remains a major impediment to 
the use of the T2Bacteria technology despite its vital importance. In 
addition, the applicant submitted a statement reaffirming that the 
T2Bacteria Test Panel fulfills the cost criterion as demonstrated by 
multiple cost analysis scenarios presented in their original 
application and as previously summarized in this final rule.
    Response: We thank the commenter for their input. After 
consideration of the comments received and the analyses described 
previously we agree that 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

[[Page 42284]]

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.264 265 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.
---------------------------------------------------------------------------

    \264\ 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.
    \265\ 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 
it submitted to support 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.\266\ 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 < 0.001). 
Compared to the matched draw blood culture and contrived samples, the 
overall sensitivity ranged from 81.3 percent to 100 percent and 
specificity ranged from 95.0 percent to 100 percent, respectively. Of 
the 190 positive T2Bacteria[supreg] Panel results, 35 had matching 
blood culture results and 155 were potentially false positive. Of these 
155, 35 had a positive blood culture at another blood draw within 14 
days; 30 had positive results by amplification and gene sequencing; and 
23 had other positive non-blood specimens for the same organism. Sixty-
three of the 190 (33 percent) positive results were not associated with 
evidence of infection. Later testing by the applicant confirmed that 
reagent contamination caused the high false positive rates specifically 
for E. coli of 1.7 percent and P. aeruginosa (1.7 percent) in stored 
blood samples. Compared to blood culture results for species identified 
with the T2Bacteria[supreg] Panel, the assay detected 3.2-times more 
positives associated with infection.
---------------------------------------------------------------------------

    \266\ T2 Biosystems, Inc., ``T2Bacteria[supreg] Panel for use on 
the T2Dx[supreg] Instrument, 510(k) summary,'' Lexington, 2018.
---------------------------------------------------------------------------

    Nguyen, et al., a submitted publication manuscript based on the 
pivotal study data, found that the species identification of the 
T2Bacteria[supreg] Panel took an average mean time of 3.61  
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 mean time of 71.7  39.3 hours.\267\ 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 \268\ 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.
---------------------------------------------------------------------------

    \267\ 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.
    \268\ 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.\269\ 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.
---------------------------------------------------------------------------

    \269\ 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 \270\, 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.\271\ 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.
---------------------------------------------------------------------------

    \270\ Ibid.
    \271\ 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.

---------------------------------------------------------------------------

[[Page 42285]]

    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.272 273 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.\274\ 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.\275\
---------------------------------------------------------------------------

    \272\ 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.
    \273\ 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.
    \274\ 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.
    \275\ 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.\276\ 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.277 278 279 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 
a reduction in the number of administered antibiotics.\280\ 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.
---------------------------------------------------------------------------

    \276\ 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.
    \277\ 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.
    \278\ 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.
    \279\ 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.
    \280\ 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.\281\ Given the toxicity associated with 
antibiotics, where some antibiotics cause encephalopathies including 
seizures \282\ and in extreme cases show up to a 4.5 percent mortality 
rate due to the antibiotic itself,\283\ 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,\284\ 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.\285\
---------------------------------------------------------------------------

    \281\ 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.
    \282\ Bhattacharyya, S., Darby, R. R., Raibagkar, P., Gonzalez 
Castro, L. N., & Berkowitz, A., ``Antibiotic-associated 
Encephalopathy,'' American Academy of Neurology, 2016, pp. 963-971.
    \283\ 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.
    \284\ 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.
    \285\ 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.286 287 288 The 
applicant stated that the results of the T2Bacteria[supreg] Panel 
Pivotal trial show that out of 23 positive patients, 4 (17 percent) 
could

[[Page 42286]]

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.\289\ 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.
---------------------------------------------------------------------------

    \286\ 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.
    \287\ 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.
    \288\ 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.
    \289\ 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 
previous discussions, the applicant believed that the 
T2Bacteria[supreg] Test Panel represents a substantial clinical 
improvement over existing technologies.
    In the proposed rule, we stated that we have the following concerns 
regarding whether the T2Bacteria[supreg] Panel meets the substantial 
clinical improvement criterion. First, we stated that we were not 
certain that the applicant had 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 stated that 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 stated that we were 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 suggest 
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.\290\ In the proposed 
rule, we stated that we recognized that this qualitative analysis is 
informative, but we were concerned that the low number of cases (under 
10) may limit generalizability of these results. Given this 
information, we stated that we were concerned that in lieu of direct 
testing, these suggestive findings may not show a causative 
relationship.
---------------------------------------------------------------------------

    \290\ 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 stated that we were 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.\291\ Therefore, in the 
proposed rule, we stated that we believed initial blood cultures 
followed by repeated blood draws would have been a better comparator. 
Furthermore, we stated that we believed 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.
---------------------------------------------------------------------------

    \291\ 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 stated that we were concerned that the use of the 
T2Bacteria[supreg] Test Panel may not alter the clinical course of 
treatment. We stated that we believed 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. We 
stated that while some of the false positives in the pivotal trial were 
explained by reagent contamination (43 of the 63 false positives),\292\ 
the high false positive rate seen in the applicant's literature, (for 
example, 13 of 32 positives (40.6 percent),\293\ 58 of 146 positives 
(39.7 percent),\294\ and a potential 20 of 63 (31.7 percent) from the 
pivotal trial) may result in unnecessary treatment of patients. 
Furthermore, we stated that 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, we stated that it 
seemed 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. We stated that 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.
---------------------------------------------------------------------------

    \292\ T2 Biosystems, Inc., ``T2Bacteria[supreg] Panel for use on 
the T2Dx[supreg] Instrument, 510(k) summary,'' Lexington, 2018.
    \293\ 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.
    \294\ 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 invited 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.
    Comment: Several commenters responded to our concern that early 
identification without antibiotic susceptibility of a bacteria may not 
be enough to prevent unnecessary empiric therapy. These commenters 
stated that the T2Bacteria Test Panel is a favorable complement to 
blood cultures that can

[[Page 42287]]

rapidly identify sick patients given the limitations of the current 
standard of care, with a commenter stating that the Test Panel should 
not be considered a comparator to blood cultures.
    A commenter stated that even without susceptibility results the 
T2Bacteria Test Panel enables the tailoring of therapy faster than any 
other technology, especially in patients known to be infected but with 
negative blood cultures. A second commenter stated that the Test Panel 
has the potential to impact both skin and urinary tract infections 
without the need for susceptibility testing. The commenter stated that 
a negative test result for patients with cellulitis could provide 
strong evidence against the need for vancomycin in certain patients and 
could also potentially facilitate the de-escalation of treatment. The 
commenter added as an example that in urinary tract infections which 
are primarily caused by E. coli and K. pneumonia, a positive test along 
with an institutional antibiogram can help shape therapy, while a 
negative for P. aeruginosa can lead to the reduced use of a key driver 
of antimicrobial resistance.
    The applicant submitted a comment stating that the vast majority of 
bacteremia episodes are correctly treated after a positive species 
identification 295 296 297 and physicians acknowledge the 
value of species ID without susceptibility.\298\ The applicant 
acknowledged that the T2Bacteria Test Panel is not a replacement for 
blood cultures but asserted that a diagnostic does not need to replace 
another to improve patient outcomes. According to the applicant, 
depending on the patient population and hospital ward, the T2Bacteria 
Panel will cover 50 to 70 percent of all bacteremia, including 90 
percent of bacteremia by ESKAPE pathogens that are at particularly high 
risk of resisting broad spectrum antibiotics and could benefit from a 
species-directed change in therapy.299 300 301 302 303 The 
applicant further noted that with a mean time difference between blood 
cultures and T2Bacteria Test Panel species identification of 77.2 
hours,\304\ clinicians could escalate or de-escalate therapy based on 
species ID 3 days in advance of the current standard of care. Lastly 
the applicant stated that a recent and independent economic analysis of 
direct-from-sample molecular diagnostic assays in an emergency 
department showed cost savings with technologies similar to the 
T2Bacteria Panel.\305\
---------------------------------------------------------------------------

    \295\ Doern GV, Vautour R, Gaudet M, Levy B. Clinical impact of 
rapid in vitro susceptibility testing and bacterial identification. 
J Clin Microbiol. 1994;32(7):1757-62.
    \296\ Byl B, Clevenbergh P, Jacobs F, et al. Impact of 
infectious diseases specialists and microbiological data on the 
appropriateness of antimicrobial therapy for bacteremia. Clin Infect 
Dis. 1999;29(1):60-6; discussion 7-8. Epub 1999/08/05.
    \297\ Kerremans JJ, Verbrugh HA, Vos MC. Frequency of 
microbiologically correct antibiotic therapy increased by infectious 
disease consultations and microbiological results. J Clin Microbiol. 
2012;50(6):2066-8. Epub 2012/03/17.
    \298\ She RC, Alrabaa S, Lee SH, Norvell M, Wilson A, Petti CA. 
Survey of physicians' perspectives and knowledge about diagnostic 
tests for bloodstream infections. PLoS One. 2015;10(3):e0121493.
    \299\ Karlowsky JA, Jones ME, Draghi DC, Thornsberry C, Sahm DF, 
Volturo GA. Prevalence and antimicrobial susceptibilities of 
bacteria isolated from blood cultures of hospitalized patients in 
the United States in 2002. Ann Clin Microbiol Antimicrob. 2004;3:7. 
Epub 2004/05/12.
    \300\ Kumar A, Ellis P, Arabi Y, et al. Initiation of 
inappropriate antimicrobial therapy results in a fivefold reduction 
of survival in human septic shock. Chest. 2009;136(5):1237-48.
    \301\ Boucher HW, Talbot GH, Bradley JS, et al. Bad bugs, no 
drugs: no ESKAPE! An update from the Infectious Diseases Society of 
America. Clin Infect Dis. 2009;48(1):1-12. Epub 2008/11/28.
    \302\ Karlowsky JA, Jones ME, Draghi DC, Thornsberry C, Sahm DF, 
Volturo GA. Prevalence and antimicrobial susceptibilities of 
bacteria isolated from blood cultures of hospitalized patients in 
the United States in 2002. Ann Clin Microbiol Antimicrob. 2004;3:7. 
Epub 2004/05/12.
    \303\ Kumar A, Ellis P, Arabi Y, et al. Initiation of 
inappropriate antimicrobial therapy results in a fivefold reduction 
of survival in human septic shock. Chest. 2009;136(5):1237-48.
    \304\ Nguyen MH, Clancy CJ, Pasculle AW, et al. Performance of 
the T2Bacteria Panel for Diagnosing Bloodstream Infections: A 
Diagnostic Accuracy Study. Ann Intern Med. 2019. Epub 2019/05/15.
    \305\ Zacharioudakis IM, Zervou FN, Shehadeh F, Mylonakis E. 
Cost-effectiveness of molecular diagnostic assays for the therapy of 
severe sepsis and septic shock in the emergency department. PLoS 
One. 2019;14(5):e0217508. Epub 2019/05/28.
---------------------------------------------------------------------------

    Response: We appreciate the commenters' input and the applicant's 
response, including the additional information provided by the 
applicant and commenter in regards to the potential for early species 
identification to impact care provided by physicians.
    Comment: Several commenters provided comments in response to our 
concern that the T2Bacteria Test Panel may not lead to decreased 
hospital lengths-of-stay and mortality due to a lack of supportive 
data. A commenter stated that the panel obviates the need for waiting 
for cells to grow as clinicians still face the challenge of selecting 
therapy while waiting for a positive blood culture, and that a major 
predictor of mortality in sepsis and septic shock is time to 
appropriate therapy. The commenter added that the T2Bacteria Test Panel 
helps place patients on appropriate therapy earlier than previously 
possible, leading to faster resolution and shorter lengths of stay.
    The applicant reiterated results from an observational study 
summarized in the proposed rule in which 70 percent of patients with 
positive results from the T2Bacteria Test Panel may have realized 
benefits in their care. The applicant stated that a meta-analysis of 70 
studies found the proportion of patients not on appropriate empiric 
antibiotic therapy was found to be 46.5 percent.\306\ The applicant 
asserted, given these observations, that the T2Bacteria Panel has 
potential to substantially reduce the proportion of patients on 
inappropriate therapy, which for a significant proportion of patients 
will reduce unnecessary use of antibiotics and time to effective 
therapy. The applicant stated that to date a total of 125 patients in 
seven studies have been found to benefit from the T2Bacteria Test 
Panel, with 28.6 percent of patients benefitting after a T2Bacteria 
positive result, 53.7 percent benefitting after a T2Bacteria negative 
result, and 41.8 percent of patients benefitting overall. Finally, the 
applicant emphasized that the T2Bacteria Test Panel was cleared by the 
FDA less than one year ago and interventional studies are ongoing.
---------------------------------------------------------------------------

    \306\ 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. Antimicrob Agents 
Chemother. 2010;54(11):4851-63. Epub 2010/08/25.
---------------------------------------------------------------------------

    A commenter stated that they collaborated with T2 Biosystems in the 
study of the T2Bacteria Test panel on patients with leukemia and those 
undergoing hematopoietic cell transplantation. The commenter stated 
that among 84 patients, 4.8 percent and 13.1 percent were positive for 
an infection as identified by blood cultures and the T2Bacteria Test 
Panel respectively. Of seven patients, five had organisms detected that 
would have altered antibacterial therapy. The commenter added that the 
median time to detection for the T2Bacteria Test Panel as compared to 
blood cultures was 3.7 hours as compared to 12.5 hours respectively.
    Response: We thank both commenter and applicant for their input, 
and appreciate the additional information regarding the correlation 
between T2Bacteria Test Panel, hospital length-of-stay, and mortality.
    Comment: Regarding our concern that the single blood culture draw 
used in the applicant's pivotal trial may be a poor comparator to the 
T2Bacteria Test Panel in light of the well-established, increasing 
sensitivity and specificity involved in repeated blood draws, a 
commenter stated that a major advantage of the T2Bacteria Test Panel is 
the ability to potentially obviate multiple blood draws for blood 
culture. The commenter added that since the

[[Page 42288]]

T2Bacteria Test Panel is the only FDA cleared direct-from-blood test 
for bacteremia it is well positioned to have a major impact on the 
clinical workflow.
    The applicant stated since no other direct-from-blood, culture-
independent DNA based tests are FDA cleared, they were required to use 
blood cultures as a comparator. The applicant maintained that the 
purpose of the comparator in the prospective arm of the T2Bacteria 
pivotal study was to demonstrate that the T2Bacteria assay can detect 
clinical infections. The applicant also maintained that comparator 
selection for an FDA diagnostic accuracy study has no impact on the 
clinical utility of the T2Bacteria Panel, as clinical impact analyses 
evaluate clinical diagnoses, patient outcomes, and the timing of 
effective antibiotic therapy. Finally, the applicant agreed with our 
statement in the proposed rule that repeat blood draws are the standard 
of care; however, the applicant stated that they also present a problem 
for comparative analyses. Per the applicant, bacteria may enter and 
exit the bloodstream for short durations over time during the course of 
disease and effective antibiotics can have a strong influence on the 
ability of bacteria to grow in culture. According to the applicant, by 
using repeat blood draws as the comparator, the applicant would record 
an inflated number of apparent false negatives from the effects of 
antibiotics and transient bacteremia.
    Response: We thank the commenter and the applicant for their input. 
We appreciate the additional information regarding the use of repeat 
blood draws as a comparator to the T2Bacteria Test Panel.
    Comment: In response to CMS' concern that the use of the T2Bacteria 
Test Panel may not alter the clinical course of treatment, the 
applicant stated that there are two dimensions to this concern, the 
impact on therapy escalations and de-escalations. First the applicant 
noted the T2Bacteria Test Panel has a specificity of 96 percent and 
therefore false positives would raise unnecessary treatment by 1 to 2 
percent. The applicant added that this increase represents a worst case 
estimate because it assumes blind adherence to the T2Bacteria Panel 
result, with no consideration of the clinical course of the patient.
    Second, the applicant stated that the increase in unnecessary 
treatment from false positive results ignores the potential for de-
escalation. Per the applicant, within the context of the clinical 
course, a negative T2 Bacteria result could be an opportunity to reduce 
unnecessary antibiotic use, particularly due to a 99.7 percent negative 
predictive value. For example, vancomycin is frequently prescribed 
empirically; reported vancomycin empiric therapy rates include 23 
percent \307\, 54 percent \308\, 65 percent \309\, and 67 percent 
\310\. The applicant stated that if clinicians de-escalated vancomycin 
based on clinical indicators and a negative T2Bacteria result, a major 
reduction in vancomycin administration could be realized, which would 
likely more than compensate for the additional unnecessary therapy from 
the panel.
---------------------------------------------------------------------------

    \307\ Roustit M, Francois P, Sellier E, et al. Evaluation of 
glycopeptide prescription and therapeutic drug monitoring at a 
university hospital. Scand J Infect Dis. 2010;42(3):177-84. Epub 
2009/12/17.
    \308\ Logsdon BA, Lee KR, Luedtke G, Barrett FF. Evaluation of 
vancomycin use in a pediatric teaching hospital based on CDC 
criteria. Infect Control Hosp Epidemiol. 1997;18(11):780-2. Epub 
1997/12/16.
    \309\ Kim NH, Koo HL, Choe PG, et al. Inappropriate continued 
empirical vancomycin use in a hospital with a high prevalence of 
methicillin-resistant Staphylococcus aureus. Antimicrob Agents 
Chemother. 2015;59(2):811-7. Epub 2014/11/19.
    \310\ Junior MS, Correa L, Marra AR, Camargo LF, Pereira CA. 
Analysis of vancomycin use and associated risk factors in a 
university teaching hospital: a prospective cohort study. BMC Infect 
Dis. 2007;7:88. Epub 2007/08/07.
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    A commenter stated that the ability to know if a patient is 
infected with an ESKAPE pathogen within three to five hours of a blood 
draw is a major clinical advantage. They added that the test will 
reduce unnecessary use of antibiotics, save hospitals money, and save 
lives. When addressing the concern for false positives, the commenter 
stated that the likelihood of infection is significantly higher with a 
T2Bacteria positive than without. They added that the current overuse 
of antibiotics is driven by a lack of information for time-critical 
patients and that with the T2Bacteria Test Panel this issue is 
addressed.
    Response: We appreciate the commenter's and applicant's input 
regarding the potential of the T2Bacteria Test Panel to alter the 
clinical workflow of treating infections and impact on antibiotic 
resistance.
    After consideration of the public comments we received, we agree 
that the T2Bacteria Test Panel represents a substantial clinical 
improvement over existing technologies because it reduces the 
proportion of patients on inappropriate therapy, thus reducing the rate 
of subsequent diagnostic or therapeutic intervention as well as length 
of stay and mortality rates caused by sepsis causing bacterial 
infections. In summary, we have determined that the T2Bacteria test 
panel meets all of the criteria for approval for new technology add-on 
payments. Therefore, we are approving new technology add-on payments 
for the T2Bacteria test panel for FY 2020. Cases involving the use of 
the T2Bacteria test panel that are eligible for new technology add-on 
payments will be identified by ICD-10-PCS procedure code XXE5XM5. In 
its application, the applicant estimated that the cost of the 
T2Bacteria test panel is $150. Under Sec.  412.88(a)(2) (revised as 
discussed in this final rule), we limit new technology add-on payments 
to the lesser of 65 percent of the average cost of the technology, or 
65 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 T2Bacteria test panel is $97.50 for FY 2020.
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.
    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

[[Page 42289]]

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). 
Similar regulations exists for the OPPS; we refer interested readers to 
the FY 2020 IPPS/LTCH PPS proposed rule discussion of those regulations 
(84 FR 19367).
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19368), we stated 
that we understood that greater clarity regarding what would 
substantiate the requirements of the substantial clinical improvement 
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. 
Therefore, in the proposed rule, we announced that we were 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 invited 
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 request for public comments was intended to be broad in 
scope and provide a foundation for potential rulemaking in future 
years. We refer readers to the FY 2020 IPPS/LTCH PPS proposed rule for 
additional detail regarding this request for public comments (84 FR 
19367 through 19369).
    CMS appreciates the many comments received in response to our 
request for information on longer term changes to the substantial 
clinic improvement criteria. CMS remains committed to helping ensure 
that Medicare beneficiaries have access to potentially life-saving 
diagnostics and therapies that improve beneficiary health outcomes. The 
comments received from the public will help us achieve these goals. In 
addition to the policies that we are finalizing in this FY 2020 final 
rule with respect to new medical services and technologies, we intend 
to continue to review the comments received in response to our Request 
for Information in order to continue our work in this area and inform 
our future rulemaking.
7. Revisions and Clarifications to the New Technology Add-On Payment 
Substantial Clinical Improvement Criterion Under the IPPS
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19369) we also 
announced that we were 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 the 
proposed rule. We also invited 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 invited 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 invited 
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 stated that we were 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. We stated that 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 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. We stated that 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. We stated that 
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.\311\
---------------------------------------------------------------------------

    \311\ https://ascopubs.org/doi/full/10.1200/jop.0922001.
---------------------------------------------------------------------------

    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

[[Page 42290]]

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. We stated that 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 
invited public comments on whether we should adopt such a policy and 
list, and if so, what the list should contain. We also invited 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 as previously listed. We stated that these 
comments would at least inform our adoption of a policy in regulations 
or sub-regulatory guidance. We stated that 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 stated 
that we recognize the value of both academic and other traditional and 
non-traditional emerging sources of information in determining 
substantial clinical improvement. We invited 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. We stated that 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. We stated that 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 invited 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 invited 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 invited comment on how 
to categorize and specify these conditions, including how to define 
``low-prevalence'', whether CMS should adopt any of the potential 
changes under consideration in this section which are not adopted more 
broadly, or any special approaches suggested by commenters. We stated 
that 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. We indicated that 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 receive an FDA marketing 
authorization other than a 510(k) clearance in order for the device to 
be considered a substantial clinical improvement. We stated that 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 solicited comments on the potential revisions and regulatory or 
sub-regulatory changes as previously described, and also welcomed 
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.
    Comments: With respect to the use of ``broad adoption'' in 
evaluating substantial clinical improvement, some commenters urged CMS 
to proceed cautiously through additional rulemaking. Some of these 
comments stated that ``broad adoption'' should not be a prerequisite 
for new technology add on payment eligibility. MedPAC indicated it did 
not equate substantial clinical improvement with broad adoption, and 
that it is not appropriate for the Medicare program to provide higher 
payment for services that have not been proven to have a clinical

[[Page 42291]]

advantage over existing treatment options. MedPAC indicated that it has 
written extensively about items and services provided to Medicare 
beneficiaries that lack evidence of comparative clinical effectiveness, 
yet are broadly used.
    With respect to indicating that ``substantially improves'' means 
that the new technology has demonstrated positive clinical outcomes 
that are different from existing technologies, some commenters were 
concerned that such a standard might restrict alternative study designs 
or impose standards that exceed realistic requirements. These 
commenters noted that for many novel technologies, there may be no 
existing technologies that could appropriately serve as a comparator. 
Some commenters indicated that such a comparison should not be a 
requirement for meeting the substantial clinical improvement criterion. 
If CMS decides to advance a comparison to existing technologies as a 
standard for demonstrating substantial clinical improvement, these 
commenters indicated that it is important to note that the comparator 
should be the standard of care, which may be a procedure or no 
intervention, rather than existing technology.
    With respect to indicating that ``substantially improves'' can be 
met through real-world data and evidence, many commenters supported the 
continued development of real-world data as evidence to demonstrate 
substantial clinical improvement. Some commenters indicated that would 
allow applicants greater flexibility to gather evidence in support of 
new technology add on payment or pass-through either in conjunction 
with or as a part of their data collection for FDA approval purposes. 
These commenters indicated that data registries that collect real world 
data are an important part of modern product development and 
monitoring. Some commenters supported a non-exhaustive list of the data 
and findings, including the following: 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. Some 
commenters indicated that CMS should consider other outcomes or 
findings that would positively impact patient care, and that one such 
outcome would be anticipated greater medication adherence or 
compliance. Some commenters indicated that real-world evidence should 
not be required for meeting the substantial clinical improvement 
criterion since it may not necessarily be available when a new 
technology is first approved or cleared by the FDA. Some commenters 
indicated that if CMS allows real-world evidence to be used for 
demonstrating substantial clinical improvement, CMS should also 
consider real-world evidence obtained from markets outside the U.S. 
since U.S.-based real-world evidence may not be available. Some 
commenters indicated that while in certain instances real world 
evidence would be appropriate to supplement other evidence, it would 
not be appropriate to only rely on the use of real world data. Some 
commenters indicated that CMS should consider how the FDA and the 
National Evaluation System for health Technology (NEST) consider real 
world data.
    With respect to indicating that the relevant information for 
purposes of a finding of substantial clinical improvement may not 
require a peer-reviewed journal article, many commenters supported 
this. These commenters indicated that the peer-review process used for 
publications in medical journals often suffers from long timelines that 
are often out of the control of the new technology add on payment 
applicants. These commenters indicated that these lengthy processes can 
sometimes jeopardize a new technology add on payment or pass-through 
application, both of which have time limits based on the newness 
criterion. These commenters believed that peer-reviewed journal 
articles do play an important role by having studies evaluated through 
the peer-review process and through the dissemination of the 
information to the medical community, but peer-review publication 
should not be a requirement for submission of studies or data for new 
technology add on payment or pass-through. Some commenters indicated 
that CMS should accept the documents that evaluate and summarize the 
clinical study data that is submitted to FDA for review as a part of 
the FDA approval or clearance process. They indicated that this 
information and its format are sufficient for FDA to conduct its review 
and CMS should be able to evaluate the evidence in a similar manner. 
These commenters indicated that CMS should explicitly state that peer-
reviewed publications are not required and that other forms of evidence 
submission are acceptable for substantial clinical improvement 
evaluation.
    Many commenters supported an approach 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. These commenters believed that 
this is consistent with several of the other policies discussed in the 
proposed rule, especially to allow for the submission of real-world 
evidence. These commenters indicated that subgroup analysis is often a 
key aspect of clinical investigation, and sometimes substantial 
clinical improvements will apply to a subset of patients. The 
commenters further indicated that these subsets are sometimes 
populations without currently adequate treatment options for which a 
new technology would be particularly beneficial. Some commenters noted 
that this policy could also help incentivize the development of new 
anti-infective drugs because new anti-infectives, or anti-infectives 
that are investigated for new indications, are often studied for 
particular subpopulations in which there are gaps among the currently 
available drugs.
    Response: As with the comments on longer term changes, CMS 
appreciates the many comments received regarding potential revisions 
and clarifications to the substantial clinical improvement criterion 
beginning with applications received beginning in FY 2020 for IPPS 
(that is, for FY 2021 and subsequent new technology add-on payment).
    We agree with the commenters who indicated that it may be premature 
to incorporate ``broad adoption'' into our evaluation of substantial 
clinical improvement. However, we also believe that many of the ideas 
supported by commenters are consistent with the principles underlying 
our existing approach for evaluating substantial clinical improvement. 
After reviewing the comments we have received, we believe it would 
helpful to prospectively codify in our regulations at Sec.  412.87 the 
following aspects of how we evaluate substantial clinical improvement 
for purposes of new technology add-on payments under the IPPS.
    First, and most importantly, the totality of the circumstances is 
considered when making a determination that a new medical service or 
technology represents an advance that substantially improves,

[[Page 42292]]

relative to services or technologies previously available, the 
diagnosis or treatment of Medicare beneficiaries.
    Second, a determination that a new medical service or technology 
represents an advance that substantially improves, relative to services 
or technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries means:
     The new medical service or technology offers a treatment 
option for a patient population unresponsive to, or ineligible for, 
currently available treatments; or
     The new medical service or 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, and there must also be evidence 
that use of the new medical service or technology to make a diagnosis 
affects the management of the patient; or
     The use of the new medical service or technology 
significantly improves clinical outcomes relative to services or 
technologies previously available as demonstrated by one or more of the 
following: A reduction in at least one clinically significant adverse 
event, including a reduction in mortality or a clinically significant 
complication; a decreased rate of at least one subsequent diagnostic or 
therapeutic intervention; a decreased number of future hospitalizations 
or physician visits; a more rapid beneficial resolution of the disease 
process treatment including, but not limited to, a reduced length of 
stay or recovery time; an improvement in one or more activities of 
daily living; an improved quality of life; or, a demonstrated greater 
medication adherence or compliance; or,
     The totality of the circumstances otherwise demonstrates 
that the new medical service or technology substantially improves, 
relative to technologies previously available, the diagnosis or 
treatment of Medicare beneficiaries.
    Third, evidence from the following published or unpublished 
information sources from within the United States or elsewhere may be 
sufficient to establish that a new medical service or technology 
represents an advance that substantially improves, relative to services 
or technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries: Clinical trials, peer reviewed journal 
articles; study results; meta-analyses; consensus statements; white 
papers; patient surveys; case studies; reports; systematic literature 
reviews; letters from major healthcare associations; editorials and 
letters to the editor; and public comments. Other appropriate 
information sources may be considered. This is consistent with our 
current approach, as discussed in the proposed rule, in which we accept 
a wide range of data and other evidence to support the conclusion of 
substantial clinical improvement.
    Fourth, the medical condition diagnosed or treated by the new 
medical service or technology may have a low prevalence among Medicare 
beneficiaries. This is consistent with our current approach, in which 
we do not require a certain prevalence among Medicare beneficiaries.
    Fifth, the new medical service or technology may represent an 
advance that substantially improves, relative to services or 
technologies previously available, the diagnosis or treatment of a 
subpopulation of patients with the medical condition diagnosed or 
treated by the new medical service or technology. This is consistent 
with our current approach, in which the medical service or technology 
may be a substantial clinical improvement for a subpopulation of 
patients.
    In addition to codifying these at Sec.  412.87, we will consider 
the other suggestions made by commenters along with review of the 
comments received in response to our Request for Information in order 
to continue our critical work in this area and inform our future 
rulemaking.
8. 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. (We note our codification of certain 
aspects of our evaluation of the substantial clinical improvement 
criterion as discussed in section II.H.7. of this preamble.)
    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 
believed, 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. In the FY 
2020 IPPS/LTCH PPS proposed rule (84 FR 19371), we noted that at the 
time of the development of the September 7,

[[Page 42293]]

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.
    In the proposed rule, we explained that 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 some stakeholders 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 Federal panel of experts in evaluating new 
technology under the ``substantial improvement'' criterion. A 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.
    As we discussed in the proposed rule, 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 note a biological product can 
be the subject of an expedited program as the subject of the FDA's 
Biologics License Application (BLA).) 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 proposed an alternative inpatient new 
technology add-on payment pathway to facilitate access to this 
technology for Medicare beneficiaries (84 FR 19372).
    Specifically, we proposed 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

[[Page 42294]]

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 proposed 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 proposed 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 
solicited 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.
    As discussed in the proposed rule (84 FR 19373), for the reasons 
discussed in section I.O. of Appendix A to the proposed rule, we did 
not propose an alternative inpatient new technology add-on payment 
pathway for drugs at this time. In that section, we stated that while 
we continue to work on these initiatives for drug affordability, we 
believed that it was appropriate to distinguish between drugs and 
devices in our consideration of a proposed policy change for 
transformative new technologies (84 FR 19672).
    Comment: The majority of commenters supported our proposed 
alternative new technology add-on payment pathway for a new medical 
device that is part of the Breakthrough Devices Program and has 
received FDA marketing authorization. In general, these commenters 
agreed that this policy will afford an opportunity to gather evidence 
to demonstrate substantial clinical improvement while enhancing 
hospital adoption, which will increase beneficiary access to new 
technologies that improve health outcomes. Some of the other reasons 
cited by commenters who supported this proposed policy include reduced 
burden and redundancy, improved administrative efficiency, greater 
transparency, predictability and certainty in the regulatory and 
reimbursement processes, and consistency across federal programs, 
including support of greater interagency collaboration between CMS and 
FDA. In particular, some of the commenters who expressed support for 
this policy indicated that they believe that the FDA's Breakthrough 
Device program is designed to appropriately balance benefits to 
patients with life threatening illnesses against potential risks for 
devices that receive marketing authorization.
    Some commenters urged CMS not to adopt this proposed alternative 
new technology add-on payment pathway for certain transformative 
medical devices. These commenters believe that devices that receive 
market authorization through FDA's Breakthrough Device program are 
unlikely to include data applicable to the Medicare beneficiary 
population, and have more uncertainty of benefit than the current 
evidence standard under the current new technology add-on payment 
policy. As such they believe this proposed policy, if finalized, would 
offer a financial incentive for the use of such transformative medical 
devices without improving clinical outcomes for beneficiaries.
    A few commenters, notwithstanding their general support for the 
proposal, expressed uncertainty about adopting the proposed policy, 
because the FDA's Breakthrough Device program is still relatively new. 
These commenters recommend that CMS continue to work jointly with FDA 
to understand the achievements and challenges of this program as it 
progresses. A few other commenters conditionally supported the adoption 
of the proposal, indicating that they believe an expansion of the 
evidence standard for establishing substantial clinical improvements 
could be preferable to eliminating the substantial clinical improvement 
criterion for medical devices that have received FDA market 
authorization and are subject to the Breakthrough Device Program. In 
contrast, another commenter indicated because new technology add-on 
payments result in an additional cost to the Medicare program, CMS 
should ensure that clinical benefit is clearly established before 
approving any technology under the new technology add-on payment 
policy.
    Other commenters also expressed concerns about the proposed policy. 
Specifically, with respect to a medical device that receives a 510(k) 
clearance, some commenters stated it would not be appropriate to 
consider a product ``new and not substantially similar'' to an existing 
technology when the 510(k) clearance process is based on a predicate 
device and can be met by demonstrating that it is substantially 
equivalent to a medical device already on the market. Most of these 
same commenters, however, did support that devices that receive either 
a PMA approval or for which FDA has granted a De Novo classification 
request would be considered new, stating their belief that such FDA 
designations indicate that such a medical device would not be 
substantially similar to an existing technology.
    We also received comments requesting that CMS extend or develop 
similar alternative new technology add-on payment pathways for all 
expedited FDA pathways (for example, Fast Track, Accelerated Approval, 
Breakthrough Therapy, and Priority Review, including Qualified 
Infectious Disease Products (QIDPs)), as well as other categories of 
technologies such as those with a Regenerative Medicine Advanced 
Therapy (RMAT) designation, devices granted a Humanitarian Device 
Exemption (HDE), and those that do not currently fit into existing CMS 
benefit categories, such as Software as a Medical Device (SaMD). In 
particular, many of these commenters explicitly urged CMS to expand the 
proposed policy to include drugs that have also received Breakthrough 
Therapy designation from the FDA, arguing that the rationale to and 
CMS's stated goal of the proposal to facilitate access to technology 
for Medicare beneficiaries applies equally to all technologies that 
receive market authorization under an expedited FDA pathway. Some of 
these commenters stated their belief that contrary to CMS's 
assumptions, the current drug-pricing system does not provide generous 
incentives for innovation, and argued that instead costly innovative 
drugs, which are not separately or adequately reimbursed in inpatient 
settings, can lead to a significant barrier to access for new treatment 
options for beneficiaries. Other commenters argued that CMS

[[Page 42295]]

should have a consistent new technology add-on payment policy for all 
``breakthrough'' technologies, that is, devices and drugs that have 
received FDA marketing authorization and are subject to an expedited 
FDA program. These commenters indicated that there is no reason for CMS 
to adopt inconsistent reimbursement policies for technologies that are 
market authorized as the subject of an expedited FDA program just 
because one technology is a device and the other is a drug. They 
believe the data and requirements needed to support a Breakthrough 
Therapy designation are as sufficient for new technology add-on payment 
purposes for drugs as the Breakthrough Device Program requirements are 
for devices. In advocating that CMS consider expanding the proposal to 
include drugs that receive market authorization as part of an expedited 
FDA program, it was suggested that CMS could also consider including 
additional criteria to qualify under an alternative pathway; for 
example, if a drug improves patient quality of life, produces long-term 
clinical treatment efficiencies, or such other criteria as specified by 
the Secretary.
    Several commenters urged CMS to extend the proposed alternative new 
technology add-on payment pathway to a product that is designated by 
the FDA as a QIDP. The commenters expressed significant concerns 
related to the public health crisis represented by antimicrobial 
resistance, which occurs when germs like bacteria and fungi develop the 
ability to resist drugs designed to kill them. The Federal Food, Drug, 
and Cosmetic Act defines QIDPs as ``an antibacterial or antifungal drug 
for human use intended to treat serious or life-threatening infections, 
including those caused by (1) an antibacterial or antifungal resistant 
pathogen, including novel or emerging infectious pathogens; or (2) 
qualifying pathogens listed by the Secretary . . . .'' \312\ These 
commenters asserted that timely access to appropriate antimicrobial 
therapy is key to clinical success and improved patient outcomes. They 
further maintained that resistant infections result in higher costs to 
healthcare systems, including Medicare, because patients experience 
illnesses of a longer duration, require additional tests, and require 
the use of more expensive drugs and related services. These commenters 
believed extending the proposed alternative new technology add-on 
payment pathway to QIDPs would be one way to address regulatory 
barriers and payment disincentives to innovation related to 
antimicrobial resistance, while improving Medicare beneficiaries' 
access to new treatments that improve health outcomes and save lives.
---------------------------------------------------------------------------

    \312\ 21 U.S.C. 355f(g)(l)-(2).
---------------------------------------------------------------------------

    Some commenters who supported the proposal also encouraged CMS to 
consider other changes to the new technology add-on payment policy, 
such as further revising and clarifying the substantial clinical 
improvement criteria (as also discussed in the proposed rule), updating 
or eliminating the ``substantial similarity'' criteria (stating those 
criteria are not required by statute), and adopting a policy to 
automatically assess new MS-DRG creation or assignment for new 
technologies when their new technology add-on payment status expires.
    Lastly, several commenters that supported this proposal also 
recommended that CMS likewise expedite beneficiary access to 
``breakthrough'' devices in the outpatient hospital setting by adopting 
a similar pathway to obtain OPPS pass-through device status.
    Response: We appreciate the commenters' support of the proposed 
alternative new technology add-on payment pathway for a new medical 
device that is part of the Breakthrough Devices Program and has 
received FDA marketing authorization. As discussed in the proposed rule 
and as previously discussed in this final rule, after considering that 
the evidence base to demonstrate substantial clinical improvement may 
not be fully developed at the time of FDA marketing authorization, we 
proposed an alternative inpatient new technology add on payment pathway 
to facilitate access for Medicare beneficiaries to new medical devices 
that are part of the Breakthrough Devices Program and have received FDA 
marketing authorization. It is for this reason that we believe that 
with respect to these technologies, even though, as some commenters 
assert, there may be less certainty of clinical benefit or data 
representing the Medicare beneficiary population as compared to the 
evidence standard for substantial clinical improvement under the 
current new technology add-on payment policy, we believe the benefits 
of providing early access to critical and life-saving new cures and 
technologies that improve beneficiary health outcomes support 
establishing this alternative pathway. While we appreciate the 
commenter's concern regarding additional Medicare program expenditures, 
for the previously stated reasons, we believe it is appropriate to 
facilitate beneficiary access to transformative new medical devices by 
establishing an alternative pathway for a device that receives FDA 
marketing authorization and is subject to the FDA's Breakthrough 
Devices Program that does not require substantial clinical improvement 
be demonstrated as a condition of approval because the evidence base to 
demonstrate substantial clinical improvement may not be fully developed 
at the time of FDA marketing authorization for such devices.
    We agree with commenters that this policy supports greater 
interagency collaboration between CMS and FDA, and CMS is committed to 
continue to work collaboratively with the FDA as the FDA's expedited 
programs, including the Breakthrough Devices Program, evolve. We refer 
commenters that conditionally supported the adoption of the proposed 
alternative pathway, but preferred that the evidence standard for 
establishing substantial clinical improvement be expanded, to the 
discussion of substantial clinical improvement in section II.H.7. of 
this final rule. With respect to commenters that expressed concern 
regarding the ``newness'' criterion for a medical device that receives 
a 510(k) clearance under the proposed alternative new technology add-on 
payment pathway for transformative medical devices, we do not agree 
that such a product cannot be ``new and not substantially similar'' to 
an existing technology for purposes of the new technology add-on 
payment policy. FDA's clearance of a 510(k) is based on a determination 
that the device at issue is ``substantially equivalent'' to a legally 
marketed (predicate) device, which is not subject to PMA. As we have 
discussed in prior rulemakings, under our current policy, a new 
technology, including a device that receives a 510k clearance, can be 
considered ``new'' for purposes of the new technology add-on payment if 
it does not meet at least one of the three substantial similarity 
criteria (and therefore would not be considered substantially similar 
to an existing technology). (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).) Therefore, we believe it is 
appropriate to include a device that has received PMA, 510(k) 
clearance, or has been granted a De Novo classification request for FDA 
marketing authorization under the alternative inpatient new technology 
add-on payment pathway for transformative new devices.
    In response to comments that requested that the proposed 
alternative inpatient new technology add-on

[[Page 42296]]

payment pathway be extended to, or an alternative pathway similarly be 
created for, drugs and biologicals (that is, Priority Review, 
Accelerated Approval, Fast Track, and Breakthrough Therapy), we 
recognize that the goal of facilitating access to new technologies for 
Medicare beneficiaries could also apply to these designations. However, 
as we discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19373 
and 19672), we believed that making this policy applicable to drugs 
would further incentives for innovation but without decreasing cost, a 
key priority of this Administration. As we also stated in the proposed 
rule, while we continue to work on 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, and therefore we disagree with 
commenters that there is no reason to adopt different new technology 
add-on payment policies for devices and drugs that receive market 
authorization and are subject to an expedited FDA pathway. We continue 
to believe that it is appropriate to distinguish between drugs and 
devices in our consideration of a policy change for transformative new 
technologies while we continue to work on these initiatives for drug 
affordability for the reasons stated in the proposed rule. Therefore we 
are not applying this alternative inpatient new technology add-on 
payment pathway in situations where a new drug designated for or 
approved under an FDA expedited program for drugs has received FDA 
marketing authorization. We will continue to consider this issue for 
future rulemaking, including the suggestion to develop additional 
criteria to qualify under an alternative pathway for technologies that 
receive FDA marketing authorization under or are designated for an FDA 
expedited program for drugs.
    While we are not applying this alternative inpatient new technology 
add-on payment pathway to new drugs more generally, we understand and 
share commenters' concerns related to antimicrobial resistance and its 
serious impact on Medicare beneficiaries and public health overall. The 
Center for Disease Control and Prevention (CDC) describes antimicrobial 
resistance as ``one of the biggest public health challenges of our 
time.'' \313\ We believe Medicare beneficiaries may be 
disproportionately impacted by antimicrobial resistance due in large 
part to the elderly's unique vulnerability to drug-resistant infections 
(e.g., due to age-related and/or disease-related immunosuppression, 
greater pathogen exposure from via catheter use). Medicare 
beneficiaries account for the majority of cases of both new diagnoses 
of antimicrobial resistant infections (approximately 62 percent) and 
the resulting deaths (approximately 65 percent) in hospitals in the 
United States.\314\ Antimicrobial resistance results in a substantial 
number of additional hospital days for Medicare beneficiaries 
(estimated to be more than 600,000 additional days each year), 
resulting in significant unnecessary health care expenditures.\315\ 
While we continue to believe, for the reasons stated, that it is 
appropriate to distinguish between drugs and devices in the application 
of an alternative new technology add-on payment pathway, after 
consideration of these specific concerns and consistent with the 
Administration's commitment to address issues related to antimicrobial 
resistance, in order to help secure access to antibiotics, and improve 
health outcomes for Medicare beneficiaries in a manner that is as 
expeditious as possible, at this time we believe it would be 
appropriate to extend the proposed alternative new technology add-on 
payment pathway to a product that is designated by the FDA as a QIDP. 
Therefore, under our finalized policy we are providing that for 
applications received for new technology add-on payments for FY 2021 
and subsequent fiscal years, if a technology receives the FDA's QIDP 
designation and received FDA marketing authorization, it will be 
considered new and not substantially similar to an existing technology 
for purposes of new technology add-on payments and will not need to 
meet the requirement that it represent an advance that substantially 
improves, relative to technologies previously available, the diagnosis 
or treatment of Medicare beneficiaries.
---------------------------------------------------------------------------

    \313\ ``Antibiotic/Antimicrobial Resistance (AR/AMR),'' Centers 
for Disease Control and Prevention, (page last updated Sept. 10, 
2018), https://www.cdc.gov/drugresistance/index.html.
    \314\ Internal analysis from the Centers for Disease Control and 
Prevention.
    \315\ Id.
---------------------------------------------------------------------------

    Regarding the requests to develop an alternative pathway for new 
technology add-on payments for other special designations (other than 
those that receive market authorization under an expedited FDA pathway 
as previously discussed), while we recognize that the goal of 
facilitating access to new technologies for Medicare beneficiaries 
could also apply to other designations, in general we believe it is 
prudent to gain experience under this new alternative pathway for 
certain transformative new devices before expanding it to other special 
designations to allow us to evaluate the benefits of this proposed 
alternative pathway to facilitate beneficiary access to transformative 
new medical devices as well as any other considerations that may come 
to light after application of this new pathway. We will keep these 
suggestions in mind for consideration in future rulemaking.
    With respect to the commenters that recommended other changes to 
the IPPS new technology add-on payment policy, we appreciate these 
suggestions and will take them into consideration for future 
rulemaking. In addition, we note that we are proposing to adopt a 
similar pathway to obtain OPPS pass-through status for medical devices 
that receive FDA marketing authorization and are part of the FDA's 
Breakthrough Devices Program in the CY 2020 OPPS/ASC proposed rule.
    Therefore, after consideration of public comments, we are 
finalizing our proposed alternative new technology add-on payment 
pathway for certain medical devices and, for the reasons discussed 
above, we are also extending that alternative new technology add-on 
payment pathway to a product that is designated by the FDA as a QIDP. 
Therefore, 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 or a product is designated by 
the FDA as a QIDP, and received FDA marketing authorization, it will be 
considered new and not substantially similar to an existing technology 
for purposes of the new technology add-on payment under the IPPS, and 
not need to meet the requirement that it represent an advance that 
substantially improves, relative to technologies previously available, 
the diagnosis or treatment of Medicare beneficiaries. We are also 
adopting our proposed changes to Sec.  412.87 to codify this proposed 
policy, as modified to reflect the finalized alternative pathway for 
QIDPs.
    Specifically, to codify this final policy, under Sec.  412.87 we 
are adding new paragraphs (c) and (d) and redesignating existing 
paragraph (c) as paragraph (e); redesignated paragraph (e) is being 
amended to reflect these alternative pathways and to make clear that a 
new medical service or technology may only be approved under Sec.  
412.87(b), new Sec.  412.87(c), or new Sec.  412.87(d). Under this 
alternative pathway for QIDPs, a medical product that has received FDA 
marketing

[[Page 42297]]

authorization and is designated by the FDA as a QIDP will need to meet 
the cost criterion under Sec.  412.87(b)(3), as reflected in new Sec.  
412.87(d)(3), and will be considered new as reflected in new Sec.  
412.87(d)(2).
    In the proposed rule, we further noted 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 invited 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 technology add-on payments). 
We noted that, if we were to adopt such a policy in the future, the 
proposed amended regulation text would be revised accordingly. We 
further noted 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.
    Comment: Some commenters supported limiting the duration of the 
payment under the alternative new technology add-on payment pathway for 
transformative new medical devices to 2 years. These commenters 
believed that revaluation of available evidence of substantial clinical 
improvement for the third year achieves an appropriate balance of 
potential risks with access for new treatment options for 
beneficiaries.
    In contrast, other commenters recommend that the timeframe align 
with the full eligibility period available under the existing new 
technology add-on payment policy. That is, the new technology add-on 
payment should be applicable for not less than 2 years and not more 
than 3 years to allow sufficient time for CMS to collect hospital cost 
and claims data to inform MS-DRG assignment and relative weights. These 
commenters indicated that re-evaluating a device that received 
marketing authorization as part of the FDA's Breakthrough Devices 
Program 1 or 2 years after approval may not provide adequate time to 
collect and evaluate data needed to demonstrate substantial clinical 
improvement, and believed the full new technology add-on payment policy 
eligibility period is necessary to ensure Medicare beneficiaries have 
access to the latest innovations. Commenters also stated that 
establishing different eligibility timelines for devices approved for 
new technology add-on payments through the traditional and alternative 
pathways could limit the development and adoption of devices that are 
part of the FDA's Breakthrough Devices Program.
    Response: We appreciate the feedback and recommendations provided 
by commenters on limiting the newness period under the proposed 
alternative new technology add-on payment pathway for transformative 
new medical devices. We will take these comments in consideration, and 
may consider adopting such a policy in the future through rulemaking.
9. Change to the Calculation of the Inpatient New Technology Add-On 
Payment
    As noted in the proposed rule and 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.
    We stated in the FY 2020 IPPS/LTCH PPS proposed rule that 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 stated in the 
proposed rule that 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

[[Page 42298]]

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.
    As noted in the FY 2020 IPPS/LTCH PPS proposed rule, 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. However, we stated that we believed that 65 
percent would be 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, in the proposed rule, we proposed 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 
proposed 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.
    Comment: The vast majority of the comments we received supported an 
increase in the new technology add-on payment percentage, citing 
reasons such as providing more adequate payments to hospitals on a per 
case basis; increased efficacy, effectiveness, and overall quality of 
patient care; reduction in price barriers that previously may have 
disincentivized the use of the most innovative technology; and to the 
extent that more hospitals are able to adopt technologies approved for 
new technology add-on payments as a result of higher Medicare payments, 
the more claims data will be available to fully reflect the costs of 
these technologies in and improve the accuracy of MS-DRG weights. Some 
commenters indicated that they remained concerned that hospitals will 
continue to endure a significant shortfall between their costs and 
their payments when using technologies approved for new technology add-
on payments, even with the proposed increase to 65 percent. These 
commenters believed that even if the payment percentage were increased 
to 65 percent, a hospital that provides a costly medical service or 
technology that qualifies for a for new technology add-on payment would 
still lose money on the case regardless of how efficient it is. 
Therefore, these commenters stated that an increase to only 65 percent 
would not be adequate to accomplish CMS's stated goals of 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.
    While commenters generally supported the proposed increase in the 
new technology add-on payment percentage, many indicated that a 
percentage between 80 and 100 percent would be more appropriate to 
sufficiently incentivize the use of new technologies and ensure 
Medicare beneficiaries' access to innovations in care and improved 
health outcomes. A few commenters stated that the proposal to increase 
the new technology add-on payment percentage from 50 percent to 65 
percent was consistent with CMS's stated goals of addressing barriers 
to healthcare innovation and ensuring Medicare beneficiaries access to 
new technologies. Similarly, MedPAC indicated that a percentage up to 
65 should be sufficient to achieve access given the continued growth in 
the number of new technology applications.
    Many commenters stated that a strong case could be made that the 
new technology add-on payment percentage should be higher than 65 
percent. Some commenters encouraged CMS to consider setting the 
percentage as close to 100 percent as possible, indicating that any 
percentage that is less than 100 percent would continue to provide a 
disincentive for appropriate use of a new technology. The majority of 
commenters suggested that the most appropriate new technology add-on 
payment amount increase would be 80 percent; however, there were also 
commenters that suggested new technology add-on payment amount 
increases of 75, 85 and 100 percent. Commenters who supported an 
increase to 80 percent indicated a variety of reasons, including that 
80 percent strikes an appropriate balance of including a cost sharing 
element with the hospitals for new technologies, alleviates enough of 
the financial disincentive to allow hospitals to provide greater access 
to Medicare patients who may benefit from these innovative 
technologies, preserves the incentives inherent under the MS-DRG 
payment system without creating an undue financial burden, and 
encourages more swift adoption of new technologies. Several commenters 
indicated that increasing the new technology add-on payment percentage 
to 80 percent would be consistent with other CMS shared-risk 
mechanisms, and in particular it would align with the IPPS outlier 
payment, under which hospitals are reimbursed based on a marginal cost 
factor equal to 80 percent of the combined operating and capital costs 
in excess of the fixed-loss threshold.
    Some commenters also pointed to an analysis by Avalere Health LLC 
that they state found that despite receiving $40.5 million in new 
technology add-on payments between FY 2006 and FY 2013, hospitals also 
received $23.2 million in outlier payments on these same cases. These 
commenters believe that the fact that so many new technology add-on 
payment cases also qualify for outlier payments underscores how 
inadequate the new technology add-on payment is, and they state that 
for this reason they believe that an 80 percent level would mitigate 
those losses, further encourage adoption of new technologies, and 
continue to provide incentives for hospitals to act as prudent 
purchasers. A few commenters also indicated that although an 80 percent 
new technology add-on payment percentage would not fully compensate all 
hospitals for the cost of using new technologies, it would bring CMS 
closer to fulfilling the statutory obligation to make payments in ``an 
amount that adequately reflects the estimated average cost of such 
service or technology.''
    While most commenters indicated that the percentage should be 
raised uniformly for all technologies approved for new technology add-
on payments, some commenters indicated that the percentage for certain 
technologies (for example, CAR T-cell therapy) needed to be higher, up 
to 100 percent, due to the high cost of the therapy, while other

[[Page 42299]]

commenters pointed to other specific types of new technologies where 
they indicated that the new technology add-on payment percentage should 
be higher. In particular, several commenters urged CMS to adopt a new 
technology add-on payment percentage of 100 percent for products 
designated by the FDA as QIDPs given the significant concerns they 
expressed related to the public health crisis represented by 
antimicrobial resistance (as further described in section II.H.8. of 
this preamble). Some of these commenters further urged CMS to at least 
finalize a policy that would provide for an increased percentage for 
QIDPs above the proposed 65 percent, for example, 80 percent or 90 
percent, if a maximum percentage of 100 percent for QIDPs was not 
adopted. As discussed in section II.H.8. of this preamble where we 
discuss our finalized policy to extend the alternative new technology 
add-on payment pathway for certain transformative medical devices to 
QIDPs, these commenters asserted that timely access to appropriate 
antimicrobial therapy is key to clinical success and improved patient 
outcomes. In addition, they maintained that resistant infections result 
in higher costs to healthcare systems, including Medicare, because 
patients experience illnesses of a longer duration, require additional 
tests, and require the use of more expensive drugs and related 
services. These commenters asserted that further increasing the new 
technology add-on payment percentage for QIDPs above the proposed 65 
percent (and specifically, to between 80 to 100 percent) would address 
regulatory barriers and payment disincentives to innovation related to 
antimicrobial resistance, while improving Medicare beneficiaries' 
access to new treatments that improve health outcomes and save lives.
    Commenters also suggested CMS consider other modifications to the 
new technology add-on payment policy, such as no longer using the 
current ``lesser of'' methodology and instead making a uniform add-on 
payment for all new technology cases, using the acquisition cost 
reported on the claim as the basis for the add-on payment amount, and 
establishing a more frequent inpatient new technology add-on payment 
policy approval process.
    Response: We appreciate the commenters' support for the proposed 
increase in the new technology add-on payment percentage. As discussed 
in the proposed rule and previously in this final rule, it is 
challenging to determine empirically a precise payment percentage 
between the current 50 percent and 100 percent payment 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. In response to commenters that encouraged CMS 
to consider setting the percentage as close to 100 percent as possible, 
indicating that any percentage that is less than 100 percent would 
continue to provide a disincentive for appropriate use of a new 
technology, we strongly disagree. Setting the percentage as close to 
100 percent as possible maintains very little of the incentives 
inherent to the prospective payment system. In response to commenters 
who suggested that the most appropriate new technology add-on payment 
amount increase would be in the 75 or 80 percent range, while we agree 
this would better maintain the incentives for cost-effective behavior 
than a 100 percent payment, we do not believe there is evidence that a 
payment in this range is required to ensure appropriate access to new 
technologies. We also disagree that the new technology add-on payment 
amount should necessarily align with the IPPS outlier payment 
methodology. We note that there are different policy considerations for 
new technology payments and outlier payments. We also disagree that the 
existence of outlier payments for some new technology cases is evidence 
that those payments are necessarily inadequate, as there may be 
unrelated reasons why a hospital would receive outlier payments. There 
may also be circumstances where new technology payments and outlier 
payments work in a complimentary manner for related reasons, that do 
not necessarily mean the appropriate policy is to increase new 
technology payments; for example, we note that MedPAC in its comment 
letter recommended that CAR T-cell therapy continue to be paid in FY 
2020 using a combination of new technology add-on payments and outlier 
payments. Lastly, we generally disagree that our proposed 65 percent 
payment does not adequately reflect the estimated average cost of a new 
technology. Commenters did not cite evidence that our proposed 65 
percent payment, a 30 percent increase (= (0.65/0.50)-1)) over the 
current 50 percent payment, would generally be an insufficient 
incremental increase to ensure appropriate access to new technologies.
    However, while we generally disagree with commenters that our 
proposed 65 percent new technology add-on payment would be inadequate, 
as noted earlier in section II.H.8, we understand and share commenters' 
concerns related to antimicrobial resistance and its serious impact on 
Medicare beneficiaries and public health overall. As we noted in that 
section, the Center for Disease Control and Prevention (CDC) describes 
antimicrobial resistance as ``one of the biggest public health 
challenges of our time.'' We believe Medicare beneficiaries may be 
disproportionately impacted by antimicrobial resistance due in large 
part to the elderly's unique vulnerability to drug-resistant infections 
(e.g., due to age-related and/or disease-related immunosuppression, 
greater pathogen exposure from via catheter use). As such, 
antimicrobial resistance results in a substantial number of additional 
hospital days for Medicare beneficiaries, resulting in significant 
unnecessary health care expenditures. Although we continue to believe, 
for the reasons discussed, that our proposed new technology add-on 
payment percentage of 65 percent is generally appropriate, after 
consideration of these specific concerns and consistent with the 
Administration's commitment to address issues related to antimicrobial 
resistance, in order to help secure access to antibiotics, and improve 
health outcomes for Medicare beneficiaries in a manner that is as 
expeditious as possible, at this time we believe it would be 
appropriate to apply a higher new technology add-on payment of 75 
percent for a product that is designated by the FDA as a QIDP and 
receives FDA marketing authorization.
    With regard to the comments that requested an increase to the new 
technology add-on payment percentage for CAR T-cell therapy, as we 
discuss in greater detail in section II.F.2.c. of this preamble, after 
a review of the comments received, we continue to believe, similar to 
last year, that given the relative newness of CAR T-cell therapy, and 
our continued consideration of approaches and authorities to encourage 
value-based care and lower drug prices, it would be premature to adopt 
structural changes to our existing payment mechanisms, either under the 
IPPS or for IPPS-excluded cancer hospitals, specifically for CAR T-cell 
therapy. For these reasons, we are not adopting the commenters' 
requested changes to our current payment mechanisms for FY 2020, 
including, but not limited to, structural changes in new technology 
add-on payments and/or a differentially higher new technology add-on 
payment percentage specifically for CAR T-cell therapy products. (For 
additional details on the comments we received in

[[Page 42300]]

response to our request for public comment on payment alternatives for 
CAR T-cell cases that was included in the proposed rule, and our 
responses, refer to section II.F.2.c. of the preamble of this final 
rule.)
    We appreciate the commenters' suggestions for other modifications 
to the new technology add-on payment policy, such as making a uniform 
add-on payment, using the acquisition cost reported on the claim as the 
basis for the add-on payment, and developing a more frequent approval 
process, and will consider them for future rule-making.
    After consideration of public comments, we are finalizing an 
increase in the new technology add-on payment percentage. Specifically, 
for a new technology other than a medical product designated by the FDA 
as a QIDP, 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. For a new technology that is a medical 
product designated by the FDA as a QIDP, 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) 75 percent of the costs of the new 
medical service or technology; or (2) 75 percent of the amount by which 
the costs of the case exceed the standard DRG payment. Under this 
finalized policy, unless the discharge qualifies for an outlier 
payment, the additional Medicare payment will be limited to the full 
MS-DRG payment plus 65 percent (or 75 percent for a medical product 
designated by the FDA as a QIDP) of the estimated costs of the new 
technology or medical service. We are also finalizing our proposed 
revisions to paragraphs (a)(2) and (b) under Sec.  412.88 to reflect 
these changes to the calculation of the new technology add-on payment 
amount beginning in FY 2020, as modified to reflect the finalized 
percentage for a medical product designated by the FDA as a QIDP.

II. 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 discussion of the FY 2020 hospital wage index based on the 
statistical areas appears under section III.A.2. of the preamble of 
this final 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, which expires on March 31, 
2022.) 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 
adjustment for FY 2020 is discussed in section II.B. of the Addendum to 
this final rule.
    As discussed in section III.I. of the preamble of this final 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), (d)(8)(C), 
and (d)(10) of the Act are equal to the aggregate prospective payments 
that would have been made absent these provisions. The budget 
neutrality adjustment for FY 2020 is discussed in section II.A.4.b. of 
the Addendum to this final 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 applying to 
the FY 2020 wage index appears under sections III.E.3. and F. of the 
preamble of this final rule.
2. Core-Based Statistical Areas (CBSAs) for the 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 in 
the June 28, 2010 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

[[Page 42301]]

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 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 final 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 FY 2020 Wage Index

    The 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 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)).
     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 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 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 FY 2020 wage index were obtained from 
Worksheet S-3, Parts II and III of the Medicare cost report (Form CMS-
2552-10, OMB

[[Page 42302]]

Control Number 0938-0050 with expiration date March 31, 2022) 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 FY 2020 wage 
index includes FY 2016 data submitted to us as of June 19, 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 we stated in the FY 2020 IPPS/
LTCH PPS proposed rule that 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 (84 FR 19375). 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 have made 
additional revisions to the FY 2020 wage data, as described further 
below. The revised data are reflected in this FY 2020 IPPS/LTCH PPS 
final rule.
    Among the hospitals we identified with aberrant data and excluded 
from the proposed rule wage index were eight hospitals that are part of 
a health care delivery system that is unique in several ways. As we 
explained in the proposed rule, (84 FR 19375), 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 identified and excluded 
eight of the hospitals that are part of this health 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. In the proposed 
rule (84 FR 19376), we stated that 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 stated that 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 stated that 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. In the proposed rule 
(84 FR 19376), we noted 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 stated in the proposed rule that we 
believe 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 
the 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. Since 
issuance of the proposed rule, we learned of 3 more CAHs that converted 
to CAH status on or after January 26, 2018, through and including 
January 24, 2019, for a total of 7 CAH exclusions. Also, since issuance 
of the proposed rule and in preparation for the April 30, 2019 PUF, we 
identified and deleted 2 more hospitals (one whose data changed since 
the January PUF and became aberrant, and the other whose data did not 
change, but it became evident for the first time that it was aberrantly 
low), while restoring 17 hospitals (including 1 hospital that is part 
of the unique healthcare chain discussed in the proposed rule at 84 FR 
19375-6) whose data improved. After the April 30, 2019 PUF we 
identified and deleted 1 more hospital (whose data did not change, but 
it became evident

[[Page 42303]]

for the first time that it was aberrantly low), while restoring the 
wage data of the 7 hospitals that are part of the unique health care 
chain. That is, we have restored to the final rule wage index 
calculation for FY 2020 the wage data of the 8 hospitals that are part 
of the unique health care chain discussed in the proposed rule (84 FR 
19375-6), as discussed further below. In summary, in the calculation of 
the FY 2020 final wage index, we have restored the wage data of the 8 
hospitals that are part of the unique health care chain referenced 
above plus the wage data of 16 additional hospitals, while deleting the 
wage data of 3 additional hospitals and 3 additional CAHs. 
Consequently, we calculated the proposed wage index using the Worksheet 
S-3, Parts II and III wage data of 3,239 hospitals.
    For the final 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 final FY 2020 wage index associated 
with this final 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:
[GRAPHIC] [TIFF OMITTED] TR16AU19.153

    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.
    Comment: Several commenters strongly opposed the exclusion of seven 
hospitals' wage data (we note that as previously stated, the data for 
one of the eight hospitals excluded from the proposed rule PUF was 
included in the April 30, 2019 PUF due to improved data). These 
commenters stated that excluding accurate and verified data is 
inconsistent with the extensive process established by CMS to ensure 
the accuracy and reliability of hospital wage index data. In addition, 
commenters specifically raised the following concerns: Section 
1395ww(d)(3)(E) of the Statute does not provide the authority for CMS 
to delete accurately-reported wage data; excluding hospitals without 
any definable standards is an abuse of discretion, creates uncertainty, 
and is arbitrary and capricious; the proposed exclusion is procedurally 
improper without formal notice-and-comment rulemaking in accordance 
with the Administrative Procedures Act (APA); excluding accurate wage 
data disregards labor costs and improperly substitutes CMS' judgment of 
reasonable wage levels for actual, free-market wage data; and singling 
out a health system due to its collective bargaining practices 
undermines the National Labor Relations Act (NLRA).
    Several commenters stated that high labor costs are a true 
reflection of the challenging labor markets in California and the fact 
that wages are influenced by labor negotiations does not render them 
any less valid. A commenter stated that the exclusion of these seven 
hospitals raises constitutional concerns as it would impermissibly 
apply a rule that is directed at and penalizes a single party.
    Commenters also expressed concern regarding the far-reaching 
effects of excluding the seven hospitals' wage data. A few commenters 
stated that excluding the wage data for the seven hospitals will 
decrease payments to hospitals in those CBSAs significantly, 
jeopardizing access to care for Medicare beneficiaries across 
California. Many commenters stated that excluding the seven hospitals' 
wage data will also harm inpatient psychiatric facilities, inpatient 
rehabilitation facilities, skilled nursing facilities, and other 
provider types whose payments are impacted by the wage index, and noted 
that CMS did not identify the fiscal impacts of the exclusions in its 
respective regulatory impact analyses for the IPF, IRF, SNF, and the 
IPPS proposed rules.
    Additionally, commenters strongly opposed removing all 38 of the 
Health System's hospitals from the wage index data beginning in FY 
2021.
    Response: In consideration of comments received, and to allow more 
time to consider the appropriateness of including or excluding the wage 
data of this unique health care chain, the wage data of all eight 
hospitals in this health

[[Page 42304]]

care chain that were deleted from the proposed rule calculation (84 FR 
19375 through 19376) are included in the FY 2020 final rule wage index.

D. Method for Computing the 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, to the extent permitted under 
current law, are discussed in the FY 2020 IPPS/LTCH PPS proposed rule 
(84 FR 19393 through 19399). We stated in the proposed rule that we 
continue to believe that broader statutory wage index reform is needed.
1. 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 in this final rule. 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, in the FY 2020 IPPS/LTCH PPS proposed 
rule (84 FR 19377 through 19379), we (1) restated 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) proposed to change 
the calculation of the Overhead Rate in Step 4; (3) proposed to modify 
our methodology with regard to how dollar amounts, hours, and other 
numerical values in the wage index calculation are rounded; and (4) 
proposed a methodology for calculating the wage index for urban areas 
without wage data. We otherwise did not propose 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. Our methodology, including our proposals (as set forth 
above), is discussed below. Unless otherwise specified, all cost report 
line references in this section of this final rule 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 were data from cost reports for cost reporting periods 
beginning on or after October 1, 2015, and before October 1, 2016). In 
addition, we included 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 were included because no 
other data from these hospitals would be available for the cost 
reporting period as previously described, 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

[[Page 42305]]

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 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 stated in the proposed rule that, for the calculation for FY 
2020 and subsequent fiscal years, we were reexamining this step as 
previously described 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, 
we stated in the proposed rule that this requires modification because 
Revised Total Hours do not include these overhead contract labor hours. 
We proposed 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 
previously described 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 did not propose 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 in this final rule.
    Step 6.--Each hospital is assigned to its appropriate urban or 
rural labor market area before any reclassifications under section 
1886(d)(8)(B), 1886(d)(8)(E), or 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 proposed 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 stated in the proposed 
rule (84 FR 19378) that 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 noted there 
are 2 urban CBSAs for which we do not have IPPS hospital wage data. In 
Table 3 associated with the proposed rule (which is available via the 
internet on the CMS website) which contains the proposed area wage 
indexes, we included a footnote to indicate to which CBSAs this 
proposed policy would apply. We proposed that these CBSAs' wage indexes 
would be equal to total urban salaries plus wage-related costs (from 
Step 5) in the respective State,

[[Page 42306]]

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 proposed to apply our proposed policy with regard to how 
dollar amounts, hours, and other numerical values in the wage index 
calculations are rounded.
    We referred readers to section II. of the Appendix of the 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 were 
identified in Table 2 which was listed in section VI. of the Addendum 
to the proposed rule and available via the internet on the CMS website.
    As we noted previously in this section, we proposed 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 as we noted in the 
proposed rule, it has come to our attention that, due in part to 
occasional inconsistencies in rounding of data, CMS' calculations and 
stakeholders' calculations may not match. Therefore, to help ensure 
consistency in the calculation, we proposed 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 proposed 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 proposed to round the dollar amounts to 2 
decimals. For any hour amounts within the wage index calculations, we 
proposed 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 proposed to round such numbers to 5 decimals. However, we 
proposed 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 did not propose 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.154

    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-

[[Page 42307]]

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 previously described methodology, we stated that the 
proposed unadjusted national average hourly wage was the following:

------------------------------------------------------------------------
 
------------------------------------------------------------------------
Proposed FY 2020 Unadjusted National Average Hourly Wage.....    $44.03
------------------------------------------------------------------------

    Comment: A commenter appreciated and supported CMS's proposal to 
provide more transparency and consistency by clarifying the rules of 
rounding data in the wage index calculation. However, the commenter 
suggested that average hourly wages be treated as a ratio rather than a 
dollar amount, and alleged that average hourly wages are actually 
imputed ratios and not actual dollar figures. The commenter believed 
that rounding average hourly wages to two decimal places as proposed, 
rather than the previous method of rounding to 5 decimals, decreases 
the precision and accuracy of the wage indexes. The commenter provided 
a hypothetical example to support their assertion.
    Response: In the proposed rule (84 FR 19379 and 19380), we proposed 
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 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 proposed 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 proposed to round the dollar amounts to 2 decimals. For any 
hour amounts within the wage index calculations, we proposed 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 proposed to 
round such numbers to 5 decimals. We proposed to continue rounding the 
actual unadjusted and adjusted wage indexes to 4 decimals, as we have 
done historically.
    We appreciate the commenter's careful review of our proposal on 
rounding, but we disagree with the commenter that average hourly wages 
are actually imputed ratios and not actual dollar figures. While the 
average hourly wage for each CBSA and the national average hourly wage 
are computed by dividing summed wages in the numerator by summed hours 
in the denominator, similar to a ratio, the purpose of this division is 
to calculate a dollar amount, not a ratio, that is representative of a 
typical wage per hour in that CBSA and nationally. Because dollar 
amounts, if not expressed in whole numbers, are typically expressed 
with 2 decimal places, we believe it is appropriate to compute average 
hourly wages with 2 decimals. Regarding the commenter's concern that 
average hourly wages rounded to 2 decimals may result in less precise 
wage indexes, we note that our proposal to round to 2 decimals is not 
inherently biasing any wage indexes to be artificially too high or too 
low; neither is one wage index biased against another, since, as a 
relative system, all wage indexes are rounded to 2 decimals. Therefore, 
we believe that average hourly wages rounded to 2 decimals can and do 
result in wage indexes for each CBSA that are an appropriate gage of 
the wages in that area, which is an important feature of the wage index 
adjustment.
    Comment: We received a couple of other comments about home office/
related organization wages and hours reported on Worksheet S-3, Part 
II, lines 14.01 and 14.02, and that these lines may improperly include 
wages and hours for Part B and nonreimbursable areas of the hospital. 
The commenters requested clarification of the cost report instructions 
for these line items.
    Response: Because we consider these comment to be outside the scope 
of the FY 2020 wage index proposals, we are not directly responding to 
these comments in this final rule. However, we will take that 
commenter's concerns into consideration for future cost report 
clarifications.
    After consideration of public comments received, we are finalizing 
without modification our proposed methodology as discussed above for 
computing the FY 2020 unadjusted wage index, including our proposals 
with respect to--(1) rounding dollar amounts, hours, and other 
numerical values used in the wage index calculation; (2) revising the 
Overhead Rate in Step 4; and (3) the methodology for calculating the 
wage index for urban areas without wage data.
    Based on the methodology finalized above, the final unadjusted 
national average hourly wage is the following:

------------------------------------------------------------------------
 
------------------------------------------------------------------------
Final FY 2020 Unadjusted National Average Hourly Wage........    $44.19
------------------------------------------------------------------------

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,

[[Page 42308]]

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.
    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.
    Comment: A few commenters referred to CMS' statement in the FY 2019 
IPPS/LTCH PPS final rule (83 FR 41373 and 41374) that it will take the 
feedback received regarding multicampus hospitals and SCH 
determinations into consideration for potential future rulemaking. The 
commenters ``wholeheartedly agreed'' with CMS' reasoning behind the use 
of remote campus locations for purposes of determining whether the 
distance criteria is met when evaluating SCH status criteria, but 
stated that they had hoped for clarification in the FY 2020 Medicare 
IPPS rulemaking regarding the definition of a remote location to be 
used in this determination. The commenters stated that there remains 
the potential that facilities that would otherwise qualify as a SCH may 
be precluded from doing so by the presence of a remote location that 
does not offer services originally intended in the creation of the SCH 
framework. Specifically, the commenters requested that CMS consider the 
following two policy clarifications:
     CMS should define a remote location as one that provides 
general acute care services to the community. If the remote location 
does not offer general acute care services reasonably available to the 
entire community, the campus should not be considered a remote location 
for purposes of determining SCH mileage criteria under 412.92(a)(4). 
For example, a facility providing only inpatient psychiatric services, 
inpatient OB/GYN women's services, or a provider-based Rural Health 
Clinic should not considered a remote location, according to the 
commenters.
     CMS should define a remote location as one that also meets 
the criteria of Sec.  412.92(c)(2) which states, ``the term like 
hospital means a hospital furnishing short term, acute care. CMS will 
not consider the nearby hospital to be a like hospital if the total 
inpatient days attributable to units of the nearby hospital that 
provides a level of care characteristic of the level of care payable 
under the acute care hospital inpatient prospective payment system are 
less than or equal to 8 percent of the similarly calculated total 
inpatient days of the hospital seeking sole community hospital 
designation.''
    Response: We appreciate the commenters input. However, because we 
consider these comments to be outside the scope of the FY 2020 wage 
index proposals, we are not finalizing any changes to these policies in 
this final rule, but may consider these comments for future rulemaking.

E. 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 Control Number 0938-0907 
with expiration date 09/30/2019) 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
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19380), for FY 
2020, we proposed 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 
the proposed rule (84 FR 19378 through 19380), we proposed 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 proposed 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

[[Page 42309]]

wage (both the unadjusted and adjusted for occupational mix), we 
proposed to round such dollar amounts to 2 decimals. We proposed to 
round any hour amounts within the wage index calculations to the 
nearest whole number. We proposed 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 
proposed 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 final rule (which is 
available via the internet on the CMS website), which contains the 
final 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 final 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 used 
the Worksheet S-3, Parts II and III wage data of 3,221 hospitals, and 
we used 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 applied 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 was the following:

 
 
 
Proposed FY 2020 Occupational Mix Adjusted National Average      $43.99
 Hourly Wage.................................................
 

    Comment: A commenter stated that all hospitals should be obligated 
to submit the occupational mix survey because failure to complete the 
survey jeopardizes the accuracy of the wage index. The commenter 
suggested that a penalty be instituted for nonsubmitters. This 
commenter also requested that, pending CMS' analysis of the Commuting 
Based Wage Index and given the Institute of Medicine's study on 
geographic variation in hospital wage costs, CMS eliminate the 
occupational mix survey and the significant reporting burden it 
creates.
    Response: We appreciate the commenter's concern about the accuracy 
of the wage index. We have continually requested that all hospitals 
complete and submit the occupational mix surveys, although we did not 
establish a penalty for hospitals that did not submit the surveys. We 
did not establish a penalty for hospitals that did not submit the 2016 
surveys. However, we are continuing to consider for future rulemaking 
various options for ensuring full compliance with future occupational 
mix surveys. Regarding the commenter's concern about the administrative 
burden of the occupational mix survey and the suggestion that we 
eliminate it, this survey is necessary to meet the provisions of 
section 1886(d)(3)(E) of the Act which requires us to measure the 
earnings and paid hours of employment by occupational category.
    After consideration of the public comments we received, for the 
reasons discussed in the final rule and the proposed rule, for FY 2020, 
we are adopting as final our proposal to calculate the occupational mix 
adjustment factor using the same methodology that we have used since 
the FY 2012 wage index. In addition, as proposed, we are modifying 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 greater 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 will 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 will round such 
dollar amounts to 2 decimals. We will round any hour amounts within the 
wage index calculations to the nearest whole number. We will 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 will continue rounding the actual 
unadjusted and adjusted wage indexes to 4 decimals, as we have done 
historically.
    For the final rule FY 2020 wage index, we used the Worksheet S-3, 
Parts II and III wage data of 3,239 hospitals, and we used the 
occupational mix surveys of 3,136 hospitals for which we also have 
Worksheet S-3 wage data, which represented a ``response'' rate of 97 
percent (3,136/3,239). (We note that the number of occupational mix 
surveys in this final rule differs from that of the proposed rule 
because for this final rule we have generally been able to include the 
occupational mix surveys of hospitals whose wage data were aberrant for 
the proposed rule but have since been improved and were used for this 
final rule. However, since a proportional number of occupational mix 
surveys to the number of hospitals included in the wage index are 
included, the response rate remains the same. For the final FY 2020 
wage index, we applied 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 final FY 2020 occupational mix 
adjusted national average hourly wage is the following:

------------------------------------------------------------------------
 
------------------------------------------------------------------------
Final FY 2020 Occupational Mix Adjusted National Average         $44.15
 Hourly Wage.................................................
------------------------------------------------------------------------

F. Analysis and Implementation of the Occupational Mix Adjustment and 
the FY 2020 Occupational Mix Adjusted Wage Index

    As discussed in section III.E. of the preamble of this final rule, 
for FY 2020, we are applying the occupational mix adjustment to 100 
percent of the FY 2020 wage index. We calculated the 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 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 finalizing in 
section III.D. of the preamble of this final rule.)

[[Page 42310]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.155

    The 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 occupational mix adjusted wage indexes for 
each CBSA to the unadjusted wage indexes for each CBSA. Applying the 
occupational mix adjustment to the wage data resulted in the following:
[GRAPHIC] [TIFF OMITTED] TR16AU19.156

    These results indicate that a larger percentage of urban areas 
(56.6 percent) would benefit from the occupational mix adjustment than 
would rural areas (48.9 percent).

G. Application of the Rural Floor, Summary of Expired Imputed Floor 
Policy, and Application of the State Frontier Floor

1. 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 FY 2020 wage index associated with this final rule (which is 
available via the internet on the CMS website) and, as discussed in 
section III.N. of the preamble of this final rule, based on the 
calculation of the rural floor without the wage data of hospitals that 
have reclassified as rural under Sec.  412.103, we estimate that 166 
hospitals will receive an increase in their FY 2020 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 final 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 
the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19393 through 19399), we 
sought public comments on proposals to help address wage index 
disparities under the IPPS. We refer readers to section III.N of this 
final rule for a summary of these public comments and our responses. We 
also sought public comments on how the expiration of the imputed floor 
has impacted hospitals in FY 2019.
    Comment: Multiple commenters stated that hospitals in all-urban 
states are subject to financial and competitive disadvantage as they 
face unique

[[Page 42311]]

conditions including close proximity to some of the most competitive 
and densely populated labor markets in the country. Commenters stated 
that residents of all-urban states have a multitude of options in 
employment opportunities and, as such, competition further drives up 
the cost of labor in the region. Multiple commenters stated that 
without the imputed floor policy, all-urban states lack the protection 
for hospitals located outside of predominant labor markets. Commenters 
also stated that rural and urban populations have unique health needs 
and access issues which should be addressed equitably to ensure that 
all patients have sufficient access to care and that all physicians are 
compensated fairly for their work. Multiple commenters also stated that 
they support a permanent fix to the geographic disadvantage faced by 
hospitals in all-urban states and that they urge CMS look at ways to 
maintain the rural floor for urban hospitals while also addressing the 
needs of rural hospitals. Commenters further stated that CMS should 
maintain the imputed floor policy, just as it had for more than a 
decade, since the policy was effective at addressing the competitive 
disadvantage suffered by all-urban states in the absence of an imputed 
floor index. Finally, multiple commenters urged CMS to consider the 
significant negative impact of discontinuing the imputed floor policy, 
and urged the agency to consider how this action has impacted the 
ability of hospitals within all-urban states to compete in high-wage 
labor markets while providing high-quality services to patients.
    A commenter stated that prior to the expiration of the imputed 
floor policy, hospitals in Rhode Island had some of the slimmest 
operating margins in the nation and the immediate impact of the 
elimination of the imputed floor to hospitals in Rhode Island was a 9.5 
percent reduction in Medicare payments resulting in a direct loss of 
$28 million in fee-for-service Medicare payments and an additional loss 
of approximately $12 million in Medicare managed care payments. This 
commenter stated that it is without question that the expiration of the 
imputed floor policy has already had a dramatic impact on the financial 
solvency of every hospital in Rhode Island that is evidenced by the 
negative hospital operating margins reported in the first and second 
quarter of FY 2019. According to the commenter, the decision to 
eliminate the imputed floor policy did not consider the unique 
characteristics of Rhode Island that exist in the labor market in 
Southeastern New England which contributes to strong competition for 
healthcare workers. The commenter stated that the hospitals in Rhode 
Island operate and compete for workforce within a short distance of the 
high wage labor markets in Massachusetts and Connecticut that currently 
benefit from higher reimbursement rates due to their state's rural 
floor. The commenter stated that every Rhode Island resident lives 
within 30 minutes of either Massachusetts or Connecticut and the 
commuter rail runs from Providence, Rhode Island to Boston, 
Massachusetts and takes less than one hour resulting in thousands of 
Rhode Island residents commuting to jobs in Massachusetts and 
Connecticut every day. The commenter further stated that the Medicare 
wage index policies in effect today placed their hospitals at a 
distinct labor market disadvantage with Massachusetts and Connecticut 
evidenced by the fact that Rhode Island currently exports 22 percent of 
its nurses to Massachusetts and Connecticut, while Massachusetts 
exports 3.5 percent to Connecticut and Rhode Island and Connecticut 
exports 4.7 percent to Massachusetts and Rhode Island. The commenter 
stated that if Rhode Island is unable to compete for skilled healthcare 
professionals, it will ultimately impact the access to care for 
Medicare beneficiaries and all Rhode Islanders. Finally the commenter 
stated that they request that CMS restore the imputed floor policy 
retroactively to October 1, 2018 in a non-budget neutral manner, due to 
the tremendous immediate impact on the hospitals in Rhode Island.
    Multiple commenters stated that it is important to note that the 
discontinuation of the imputed floor policy for all-urban states 
further exacerbates the disproportionate impact of the wage index 
disparities proposals on hospitals within all-urban states. A commenter 
stated that the imputed floor policy addressed the inequities in the 
wage index, which CMS' FY 2020 wage index disparities proposals will 
compound. A commenter explained that in FY 2019 CMS stated, ``By 
allowing the imputed rural floor to expire for all urban states . . . 
CMS has begun the process of making the wage index more equitable.'' 
The commenter explained, however, that in FY 2020, CMS recognized that 
the FY 2020 wage index disparities proposals will have significant 
adverse financial impacts on hospitals. More specifically, the 
commenter stated that CMS' elimination of the imputed floor policy did 
not account for the immediate impact to hospitals in Rhode Island; 
however, CMS acknowledged with the FY 2020 wage index disparities 
proposal that it is aware of and attempting to account for potential 
impact of that proposal by proposing to cap any wage index decreases 
for FY 2020 (including wage index decreases experienced by hospitals 
with wage indexes in the top 25th percentile) at 5 percent under the 
reasoning that hospitals so harmed should not face such immediate and 
drastic cuts. The commenter stated that it is unfortunate that CMS did 
not act with this same deliberation when it summarily eliminated the 
imputed rural floor in FY 2019.
    According to the commenter, as CMS continues to address what it 
considers to be disparities in the wage index and how it is 
implemented, it unfortunately creates yet another disparity for Rhode 
Island hospitals. The commenter stated that if CMS is unable to develop 
a reasonable alternative methodology, then the elimination of the 
imputed floor policy should be considered as part of the broader 
Medicare wage index disparities proposal which recognizes and includes 
protection from significant losses in one year. The commenter also 
requested consideration for reinstatement of the imputed floor policy 
in FY 2020, and that the imputed floor policy be applied to the FY 2020 
wage index.
    A commenter stated that the expiration of the imputed floor policy 
resulted in a loss of approximately $11 million for New Jersey 
hospitals in areas that receive a lower overall wage index than 
hospitals classified into major metropolitan areas. Another commenter 
stated they estimated that the imputed floor policy's benefit to New 
Jersey in FY 2019 would have been approximately $13 million. According 
to commenters, the elimination of this policy is added to the total 
tally of cuts and disadvantageous policies from which hospitals in high 
wage and all-urban states suffer. According to a commenter, New 
Jersey's geographic location bordering the first and sixth largest 
cities in the country and the compact size of the state, along with 
numerous commuting options, put further strain on the labor market. A 
commenter stated that due to the expiration of the imputed floor 
policy, their hospitals are now receiving $5.5 million less in payments 
from Medicare that could have been used to benefit patient care in 
myriad ways, particularly in the underserved areas, such as: Employment 
of additional physicians including primary care and specialists to 
ensure continued access to care; expansion of programs to provide 
needed services such as addressing food

[[Page 42312]]

insecurity and childhood early intervention; and expansion of the 
numerous health programs already subsidized by their hospitals. The 
commenter stated not just one program was negatively affected by the 
elimination of the imputed floor policy, as there are numerous programs 
and opportunities to provide essential care in the communities they 
serve.
    Response: We thank the commenters for their comments regarding how 
the expiration of the imputed floor has impacted hospitals in FY 2019. 
As discussed in the FY 2019 final rule (83 FR 41378), we have expressed 
reservations about the imputed floor considering that the imputed rural 
floor methodology creates a disadvantage in the application of the wage 
index to hospitals in States with rural hospitals but no urban 
hospitals receiving the rural floor. As we discussed in the FY 2008 
IPPS/LTCH PPS final rule (72 FR 47322), the FY 2012 IPPS/LTCH PPS final 
rule (76 FR 51593), the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 
19905), and the FY 2019 IPPS/LTCH PPS proposed rule (83 FR 20363), the 
application of the rural and imputed floors requires transfer of 
payments from hospitals in States with rural hospitals but where the 
rural floor is not applied to hospitals in States where the rural or 
imputed floor is applied. While we continue to have such reservations 
about the application of an imputed floor, we are summarizing the 
comments we received in this final rule for the public's information.
3. 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 the FY 2020 IPPS/
LTCH PPS proposed rule, we did not propose any changes to the frontier 
floor policy for FY 2020. We stated in the proposed rule that 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.
    We did not receive any public comments on the application of the 
State frontier floor for FY 2020. In this final rule, 45 hospitals will 
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 final rural and frontier floor policies 
for the final FY 2020 wage index are identified in Table 2 associated 
with this final rule, which is available via the internet on the CMS 
website.

H. 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 final rule for a 
discussion of the final 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.

[[Page 42313]]

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 final rule was constructed, the MGCRB had 
completed its review of FY 2020 reclassification requests. Based on 
such reviews, there are 294 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 290 hospitals approved for wage index reclassifications in 
FY 2018 that will continue for FY 2020, and 275 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 final 
rule, 859 hospitals are in a MGCRB reclassification status for FY 2020 
(with 30 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).
    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 are incorporated 
into the wage index values published in this 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, expiration date January 31, 2021) 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. 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.
    We stated in the proposed rule (84 FR 19383) that, 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, we stated that 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 stated in the proposed rule that we believe 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 stated that 
we believe 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, in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19383), we 
proposed to reduce burden for hospitals by eliminating the requirement 
to copy CMS. Specifically, we proposed 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.
    Comment: Many commenters supported our proposal to no longer 
require that a copy of the application be submitted to CMS. The 
commenters stated that it will be less of a burden on hospitals. A few 
commenters applauded the proposal as a positive effort by CMS toward 
reducing administrative burden and duplication for hospitals, and 
encouraged CMS to continue seeking ways to modernize processes.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, for the 
reasons discussed in this final rule and the proposed rule, we are 
finalizing as proposed, without modification, our revisions to Sec.  
412.256(a)(1) to delete the requirement that an electronic copy of the 
application be sent to CMS, so that this section specifies that an 
application must be submitted to the MGCRB

[[Page 42314]]

according to the method prescribed by the MGCRB.
c. 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, in the FY 2020 IPPS/
LTCH PPS proposed rule (84 FR 19383), we proposed 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 proposed 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.
    We did not receive any public comments regarding this proposal. For 
the reasons discussed in this final rule and the proposed rule, we are 
finalizing the proposal, without modification, to revise Sec.  
412.230(a)(4) by removing 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 [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 Out-Migration Adjustment Changes After Reclassification
    Section 1886(d)(8)(B) of the Act provides that for purposes of 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 stated in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19384) 
that 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). We stated in 
the proposed rule that, 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). We stated that these fluctuations are 
typically minimal. However, we explained that in certain

[[Page 42315]]

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. We stated in 
the proposed rule that this can lead to a situation where a hospital 
has opted to receive a nonexistent out-migration adjustment. We further 
stated that 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 as previously described. 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. As we 
discussed in the proposed rule, 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, in the proposed rule, we clarified 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. 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 
one 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 of the CBSA. Given 
the OMB standards, as previously discussed, 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 as previously discussed, 
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) of the Act further requires CMS to assign 
these Lugar counties to the CBSA to which the greatest number of 
workers in the county commute. We stated in the proposed rule (84 FR 
19385) that 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 
noncentral county being evaluated and the ``central'' county or 
counties of an urban metropolitan area (without taking into account 
outlying counties). We stated in the proposed rule that 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 further 
stated that 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. We explained that when CMS updated the OMB labor market 
delineations based on the 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

[[Page 42316]]

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.
    We stated in the proposed rule that after consideration of this 
matter, we continue to believe that CMS' methodology is a reasonable 
interpretation of the statute. However, we stated that 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. We explained that, after reanalyzing the 
commuting data used when developing the FY 2015 IPPS/LTCH PPS final 
rule (the American Community Survey commuting data for 2006 to 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 
in this section of this final rule.

[[Page 42317]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.157

    Of these 10 counties, currently only 3 counties (Talladega, AL, 
Pearl River, MS, and Henderson, TX) contain IPPS hospitals (4 hospitals 
in total). We explained in the proposed rule (84 FR 19386) that when 
including ``outlying''

[[Page 42318]]

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. We stated in the proposed 
rule (84 FR 19887 through 19387) that 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), 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, in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19387), we proposed to modify the assigned CBSA for the 10 Lugar 
counties specified in the table set forth in the proposed rule for FY 
2020. We stated in the proposed rule that we also planned 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.
    Comment: A commenter supported CMS' proposal to modify the assigned 
CBSA for the 10 Lugar counties. The commenter concurred that inclusion 
of both ``central'' and ``outlying'' counties in the commuting analysis 
for purposes of assigning counties that qualify as Lugar counties is a 
reasonable interpretation of section 1886(d)(8)(B)(i) of the Act.
    Response: We appreciate the commenter's support of our proposal.
    After consideration of the public comments we received, for the 
reasons discussed in this final rule and the proposed rule, we are 
finalizing as proposed, without modification, the revised CBSA 
assignments as described in the table set forth in the proposed rule 
(84 FR 19386) and as reflected in the table in this final rule. We 
further intend to reevaluate this policy and underlying methodologies 
when CMS updates Lugar county assignments after OMB labor market 
delineations are updated in response to the next decennial census.

J. 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 in the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19387), we proposed 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 
did not propose 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).) We did not receive any 
public comments on this proposed policy for FY 2020. Therefore, for FY 
2020, we are finalizing our proposal, without modification, to continue 
using the same policies, procedures, and computation that were used for 
the FY 2012 outmigration adjustment and that were applicable for FY 
2016, FY 2017, FY 2018, and FY 2019.
    Table 2 associated with this final rule (which is available via the 
internet on the CMS website) includes the final 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 final rule, Table 4 
consists of the following: A list of counties that are eligible for the 
out-migration adjustment for FY 2020 identified by FIPS county code, 
the final FY 2020 out-migration adjustment, and the number of years the 
adjustment will 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 final rule that are 
available via the internet on the CMS website.

[[Page 42319]]

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 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.
    Comment: A commenter stated that denying rural reclassifications 
based on an arbitrary date would have significant negative impacts on 
the financial operations on many hospitals. The commenter also stated 
that section 1886(d)(8)(E) of the Act and the regulation at Sec.  
412.103 enable urban hospitals that meet certain criteria to reclassify 
as rural, and that the hospital needs to submit the reclassification 
request during the last quarter of a hospital's fiscal year.
    Response: We reiterate that the lock-in date 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. In other words, we will not deny rural 
reclassifications after the lock-in date. Rather, the lock-in date is 
for ratesetting purposes only. With regard to the comment that 
hospitals need to submit a reclassification request during the last 
quarter of a hospital's fiscal year, we believe the commenter may be 
referring to the requirement at section 1886(d)(5)(C)(i) of the Act 
pursuant to which a hospital must submit its application for rural 
referral center (RRC) status during the last quarter of its cost 
reporting period. No such timing requirement applies to rural 
reclassifications under Sec.  412.103, even those applications meeting 
the criteria at Sec.  412.103(a)(3).
2. 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 stated in the proposed rule (84 FR 19388) that we believe 
that this policy is outdated and overly restrictive. In the interest of 
burden reduction and to promote ease of application, in the FY 2020 
IPPS/LTCH PPS proposed rule (84 FR 19388), we proposed 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 proposed 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.
    Comment: Many commenters supported this proposal to change the 
rural reclassification application requirements to allow for electronic 
submission. Commenters specifically expressed appreciation for the 
added flexibility and applauded CMS' effort to reduce burden and 
promote ease of application. A commenter stated that this proposal 
signifies a positive effort by CMS toward reducing administrative 
burden and duplication for hospitals, and encouraged the agency to 
continue to seek ways to modernize processes. Commenters urged CMS to 
finalize this proposed change to the regulations at Sec.  
412.103(b)(3).
    Response: We appreciate the commenters' support of our proposal.
    After consideration of the public comments we received, for the 
reasons discussed in this final rule and the proposed rule, we are 
finalizing as

[[Page 42320]]

proposed, without modification, our change to the regulations at 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. 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19388), we 
proposed 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, we stated in the proposed rule that, 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 the proposed rule, we 
proposed 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, we stated in the proposed rule that 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 proposed 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 proposed 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. We stated in the proposed rule (84 FR 19389) that 
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. We 
further started that 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. We stated that 
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 beginning with 
the next Federal fiscal year (that is, the Federal fiscal year 
following the cancellation request). In addition, we explained in the 
proposed rule that, 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 stated that 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 stated that 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. We explained that, 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, we 
stated that 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 proposed 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 proposed 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.

[[Page 42321]]

    In addition, we proposed 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 
the proposed rule (84 FR 19383), 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.'' We explained in the proposed rule 
(84 FR 19389) that, 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 stated that 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 stated that we believe 
this policy reduces overall complexity for CMS, avoiding the need to 
track and process multiple cancellation requests. Accordingly, we 
stated that we believe this policy should be codified in the 
regulations at Sec.  412.103.
    Therefore, we proposed 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 the FY 2020 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. We stated that 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 noted 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 the proposed rule (84 FR 19384), we noted that, in proposed 
Sec.  412.103(g)(4), we were 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. We stated that 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).
    Comment: Many commenters supported the proposal to apply uniform 
cancellation requirements that would allow all hospitals to cancel 
reclassifications 120 days before the end of the federal fiscal year, 
without having to be paid as rural for one 12 month cost reporting 
period. Some commenters specifically applauded CMS' efforts to reduce 
administrative burden.
    Response: We appreciate the commenters' support and the 
acknowledgment of CMS' administrative burden reduction efforts.
    After consideration of the public comments we received, for the 
reasons discussed in this final rule and in the proposed rule, we are 
finalizing, without modification, our proposed revisions discussed 
above with respect to cancellation of rural reclassification. 
Specifically, as proposed, our reclassification cancellation 
requirements specific to RRCs at Sec.  412.103(g)(2) will no longer 
apply for cancellation requests submitted on or after October 1, 2019. 
As proposed, we are revising 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. In addition, as proposed, we are finalizing uniform 
reclassification cancellation requirements that will be applied to all 
hospitals effective for cancellation requests submitted on or after 
October 1, 2019. Specifically, we are adding 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, effective beginning 
with the next Federal fiscal year. Furthermore, as proposed, we are 
adding 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.
    We are also finalizing our proposal, without modification, to add 
paragraph (g)(4) to Sec.  412.103 to codify our longstanding policy 
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 the FY 2020 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.
    When these changes go into effect, there will not be a minimum 
period that a hospital must maintain its rural reclassification before 
it is eligible to cancel it. Currently, RRCs are required to maintain a 
rural reclassification for at

[[Page 42322]]

least 1 year. As previously described above, this policy was finalized 
in the FY 2008 IPPS final rule (72 FR 47371 through 47373) to 
disincentivize hospitals from receiving a rural redesignation to obtain 
a certain benefit, and then immediately cancel the rural redesignation. 
While we no longer believe it is necessary to retain this specific 
policy to maintain acquired rural status for 1 year, we are aware of 
other potential situations where hospitals may attempt to exploit the 
rural reclassification process in order to obtain higher wage index 
values. For example, a hospital may obtain a rural reclassification 
with the intention of receiving its State's rural wage index. If the 
application is approved by the CMS Regional Office after our 
ratesetting ``lock-in date'', the final rule rural wage index value 
would most likely not include the data for this hospital in the 
ratesetting calculation. This may incentivize relatively low wage index 
hospitals to time their applications to avoid reducing the State's 
rural wage index. These hospitals could then conceivably cancel their 
rural reclassifications (effective for next FY), and then reapply again 
after the ``lock date.'' We plan to monitor this situation over the 
course of FY 2020, and determine if it is necessary to take action to 
prevent this type of gaming in future rulemaking.

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-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/AcuteInpatientPPS/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 l, 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-

[[Page 42323]]

for-Service-Payment/AcuteInpatientPPS/Wage-Index-Files-Items/FY2020-
Wage-Index-Home-Page.html, the April appeals had to be sent via mail 
and email. We refer readers to the wage index timeline for complete 
details.
    Hospitals were given the opportunity to examine Table 2 associated 
with the proposed rule, which was listed in section VI. of the Addendum 
to the proposed rule and available via the internet 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. Table 2 associated with the proposed rule contained 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 noted in the proposed 
rule (84 FR 19390) that the proposed hospital average hourly wages 
shown in Table 2 only reflected changes made to a hospital's data that 
were transmitted to CMS by early February 2019.
    We posted the final wage index data PUFs on April 30, 2019 via the 
internet 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 April 2019 PUFs were 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 could only be made in those very 
limited situations involving an error by the 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 believed that its wage or occupational mix data were incorrect 
due to a MAC or CMS error in the entry or tabulation of the final data, 
the hospital was given the opportunity to notify both its MAC and CMS 
regarding why the hospital believed an error exists and provide all 
supporting information, including relevant dates (for example, when it 
first became aware of the error). The hospital was required to send its 
request to CMS and to the MAC no later than May 30, 2019. May 30, 2019 
was also the deadline for hospitals to dispute data corrections made by 
CMS of which the hospital was 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 did 
not arise from a hospital's request for revisions. (Data corrections 
made by CMS of which a hospital was 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 were required to 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 were incorporated into the 
final FY 2020 wage index, which is 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 did 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 previously set forth (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 had access to the final wage index data 
PUFs by late April 2019, they had 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

[[Page 42324]]

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. 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 final 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

[[Page 42325]]

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. Labor-Related Share for the 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-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 the 
FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19393), for FY 2020, we did 
not propose 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 proposed 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 final 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 did 
not propose a Puerto Rico-specific labor-related share percentage or a 
nonlabor-related share percentage.
    We did not receive any public comments on our proposals related to 
the labor-related share percentage. Therefore, we are finalizing our 
proposals, without modification, to continue to use a labor-related 
share of 68.3 percent for discharges occurring on or after October 1, 
2019 for all hospitals (including Puerto Rico hospitals) whose wage 
indexes are greater than 1.0000.
    Tables 1A and 1B, which are published in section VI. of the 
Addendum to this FY 2020 IPPS/LTCH PPS final rule and available via the 
internet on the CMS website, reflect the 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 applying 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 applying the wage 
index to a labor-related share of 68.3 percent of the national 
standardized amount.

N. Policies 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. For a summary 
of these comments and public comments received on wage index 
disparities in previous rules, see the FY 2020 IPPS/LTCH PPS proposed 
rule (84

[[Page 42326]]

FR 19393 through 19394) and the references therein.
    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, in the FY 
2020 IPPS/LTCH PPS proposed rule (84 FR 19393), we proposed 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 
proposed a transition for hospitals experiencing significant decreases 
in their wage index values.
1. Policies 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. We stated in the proposed rule (84 
FR 19394) that 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 between 
when hospitals increase the compensation and when those increases are 
reflected in the calculation of the wage index. (We noted that this lag 
results from the fact that the wage index calculations rely on 
historical data.) We also agreed 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, in the FY 
2020 IPPS/LTCH PPS proposed rule (84 FR 19395), we proposed 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, we proposed 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. As we discussed in the proposed 
rule, quartiles are a common way to divide a distribution, and 
therefore, we stated in the proposed rule 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 final 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 stated in the proposed rule that 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. We stated that while we acknowledge 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 previously discussed, quartiles are a 
common way to divide distributions, and that our proposed approach is 
consistent with approaches used in other areas of the Medicare program.
    We stated in the proposed rule that, based on the data for the 
proposed rule, for FY 2020, the 25th percentile wage index value across 
all hospitals was 0.8482. We stated in the proposed rule that 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 proposed to increase the wage 
index for hospitals with a wage index value below the 25th percentile 
wage index. In the proposed rule (84 FR 19395), we proposed that the 
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, as described in the 
proposed rule, 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).
    We explained in the proposed rule (84 FR 19395) that some 
respondents to the request for information had indicated that CMS 
should establish a wage index floor for hospitals with low wage index 
values. However, as stated in the proposed rule, we believe that it is 
important to preserve the rank order of the wage index values under the 
current policy and, therefore, we proposed to increase the wage index 
for the low-wage index hospitals previously described by half the 
difference between the otherwise applicable final wage index value and 
the 25th percentile wage index value. We stated that we believe the 
rank order generally reflects meaningful distinctions between the 
employee compensation costs faced by hospitals in different geographic 
areas. We noted that 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 previously 
discussed, 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 stated that 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 proposed 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 
proposed to use data from the FY 2016 cost reports. We stated in the 
proposed rule (84 FR 19395) that 4 years is the minimum time before 
increases in employee compensation

[[Page 42327]]

included in the Medicare cost report could be reflected in the wage 
index data, and additional time may be necessary. We stated in the 
proposed rule that we intend to revisit the issue of the duration of 
the policy in future rulemaking as we gain experience under the policy 
if adopted.
    The following are summaries of the comments we received regarding 
our proposal to provide an opportunity for low wage index hospitals to 
increase employee compensation, and our responses.
    Comment: Many commenters expressed their support of our proposal to 
provide an opportunity for low wage index hospitals to increase 
employee compensation and indicated the negative impact low wage index 
values have on their local hospital's ability to attract and maintain a 
sufficient labor force. Many commenters indicated that the increase in 
wage index would allow employee compensation at low wage hospitals to 
rise to more competitive levels to help attract and retain skilled 
health care workers. Many commenters indicated that although the 
increase in the wage index is not permanent, it would still allow low 
wage hospitals to increase compensation and must be in place for 4 
years to allow the employee compensation changes to be reflected in the 
wage index data. Many low wage index hospitals indicated that they have 
long desired to increase wages for employees and reinvest in their 
communities, and our proposal will give them the opportunity to do so.
    Response: We appreciate the commenters' support of our proposal to 
provide an opportunity for low wage index hospitals to increase 
employee compensation. We agree with the commenters that in order to 
attract and maintain a sufficient labor force a hospital must provide 
adequate employee compensation. As further discussed later in this 
section, we believe our proposal to increase the wage index for low 
wage index hospitals will increase the accuracy of the wage index by 
appropriately reflecting the increased employee compensation that would 
occur (to attract and maintain a sufficient labor force) if not for the 
lag in the process between when a hospital increases its employee 
compensation and when that increase is reflected in the calculation of 
the wage index.
    Comment: Some commenters who supported our proposal to provide an 
opportunity for low wage index hospitals to increase employee 
compensation also requested the proposal be expanded to address other 
hospitals, such as hospitals that have seen a significant decrease in 
their wage index over the past twenty years. In particular, some 
commenters argued that hospitals in eight specific CBSAs struggle to 
raise employee wages for many of the same reasons hospitals in low wage 
index areas struggle to raise employee wages. These commenters 
requested that over the next 4 years, for CBSAs meeting all of the 
following criteria:
     The CBSA does not benefit from implementation of our 
adjustment to the lowest quartile of wage index values.
     The CBSAs' wage index is less than 1.0000.
     The CBSA's wage index has fallen more than 10 percent from 
FY 2000 to FY 2019.
    CMS increase the wage index in those CBSAs by half of the 
difference of the twenty year decline (that is, half of the difference 
in the FY 2000 wage index and the FY 2020 wage index).
    Response: We disagree with these commenters. Raising the wage index 
values of certain hospitals above the 25th percentile and not other 
hospitals with similar wage index values distorts the rank order of the 
wage index, which for the reasons discussed above is a critical aspect 
of our proposal.
    Comment: Many commenters objected to our proposal to provide an 
opportunity for low wage index hospitals to increase employee 
compensation. Such commenters generally noted that since we did not 
propose any method to ensure such hospitals increase employee 
compensation, there is no guarantee benefiting hospitals will increase 
employee compensation. Other commenters argued against the notion that 
a lag in wage data suppresses a hospital's ability to increase wages, 
and stated that any potential impact of this lag on a given hospital is 
mitigated by other factors, including the presence of other hospitals 
in their labor market area, and our proposal would therefore have 
little impact on the average hourly wage rates of low wage hospitals. 
Other commenters asserted that doing this through an increase in the 
wage index for low wage index hospitals removes the wage index's 
ability to provide a relative measure for wages across different 
geographic regions.
    Response: We disagree with these commenters. In response to 
commenters who indicated that there is no method to ensure that 
hospitals increase their employee compensation, we note the policy is 
intended to provide an opportunity for low wage hospitals to increase 
their employee compensation, and we expect them to do so based on 
responses received to the request for information indicating that the 
lag between when hospitals increase the compensation and when those 
increases are reflected in the calculation of the wage index creates 
barriers to hospitals with low wage index values from being able to 
increase employee compensation as well as comments received on our 
proposal as summarized previously. However, as we indicated in the 
proposed rule, this was not proposed as a permanent policy. Once there 
has been sufficient time for that increased employee compensation to be 
reflected in the wage data, there should not be a continuing need for 
this policy. At the expiration of the policy, hospitals that have not 
increased their employee compensation in response to the wage index 
increase may experience a reduction in their wage index compared to 
when the policy was in effect. Conversely, at the expiration of the 
policy, hospitals that have increased their employee compensation may 
experience relatively little change in their wage index compared to 
when the policy was in effect. The future wage data from those 
hospitals will help us assess our reasonable expectation based on 
comments received in response to the request for information as well as 
proposal that low wage hospitals would increase employee compensation 
as a result of our proposal. This wage data will also help us and the 
public to assess the assertion by some commenters opposed to our 
proposal that any potential impact of the wage index data lag on a 
given hospital is mitigated by other factors and our proposal would 
have little impact on the average hourly wage rates of low wage 
hospitals. We disagree with these commenters. Based on the comments 
received from the low wage hospitals, we do expect them to increase 
their employee compensation and this increased compensation is expected 
to increase their average hourly wages.
    In response to commenters who asserted that increasing the wage 
index for low wage index hospitals removes the wage index's ability to 
provide a relative measure for wages across different geographic 
regions, we believe, as noted earlier, that our proposal increases the 
accuracy of the wage index as a relative measure. As we discussed in 
the proposed rule (84 FR 19394 through 19395), under our current cost 
reporting process, there is a lag between the time a hospital makes 
employee compensation adjustments and the time these adjustments are 
reflected in the wage index. As we stated in the proposed rule, 4 years 
is the minimum time before increases in employee

[[Page 42328]]

compensation included in the Medicare cost report could be reflected in 
the wage index data. We believe that if the lag did not exist and 
employee compensation increases could be more quickly reflected in the 
wage index values, low wage index hospitals would have been able to 
increase employee compensation. Our proposal will increase the accuracy 
of the wage index as a relative measure because it allows low wage 
index hospitals to increase their employee compensation in ways that we 
would expect if there were no lag in reflecting compensation 
adjustments in the wage index. Furthermore, as we stated in the 
proposed rule (84 FR 19395), our proposal to increase the wage index 
values for low wage index hospitals continues to preserve the rank 
order of wage index values and thus continues to reflect meaningful 
distinctions between the employee compensation costs faced by hospitals 
in different geographic areas. Based on comments received in response 
to our request for information and comments received on our proposed 
policy, we expect low wage hospitals to increase their employee 
compensation as a result of our proposed wage index increase. Our 
proposed policy will allow these expected increases to be more timely 
reflected in the wage index.
    Comment: Some commenters indicated that the proposal is not 
consistent with the quartile system used in the Hospital-Acquired 
Condition Reduction Program as referenced in the proposed rule, noting 
that the Hospital-Acquired Condition Reduction Program uses quartiles 
based on ranking hospital performance against a particular metric. 
Commenters stated that in programs such as the Hospital-Acquired 
Condition Reduction Program, quartiles are used to incentivize or 
decentivize certain behaviors, but they do not augment or replace 
existing measures.
    Response: As we noted in the proposed rule, the reference to the 
Hospital-Acquired Condition Reduction Program was intended just to show 
that quartiles are a common way to divide distributions, as the 
Hospital-Acquired Condition Reduction Program is a program that divides 
a distribution based on quartiles. It is immaterial that the Hospital-
Acquired Condition Reduction Program itself serves a different purpose 
than our wage index proposal, in the same way it is immaterial the 
Medicare Advantage program serves a different purpose. The main point 
is not any commonality of purpose of the underlying programs, but that 
those programs use quartiles as a way a dividing a distribution. As we 
stated in the proposed rule, while we acknowledge there is no set 
standard for identifying hospitals as having low or high wage index 
values, we believe this quartile approach is reasonable for this 
purpose because it is a common way to divide distributions and is 
consistent with approaches used in other areas of the Medicare program.
    Comment: Many commenters asserted that the rationale for our 
proposal was to address non-wage issues related to rural hospitals, the 
overall financial health of hospitals in low wage areas, or the broader 
issue of wage index reform. These commenters critiqued our proposal 
according to its effect on these issues and indicated that CMS should 
pursue alternative means to address these issues rather than the policy 
under consideration here.
    Response: The wage index is a technical payment adjustment. The 
intent of our proposal is to increase the accuracy of the wage index as 
a technical adjustment, and not to use the wage index as a policy tool 
to address non-wage issues related to rural hospitals, or the laudable 
goals of the overall financial health of hospitals in low wage areas or 
broader wage index reform. As noted earlier, our proposal increases the 
accuracy of the wage index as a relative measure because it allows low 
wage index hospitals to increase their employee compensation in ways 
that we would expect if there were no lag between the time a hospital 
increases employee compensation and the time these increases are 
reflected in the wage index, and allows those increases to be more 
timely reflected in the wage index. While one effect of our proposal 
may be to improve the overall well-being of low wage hospitals, and we 
would welcome that effect, that is not the primary rationale for our 
proposal.
    Comment: While many commenters were supportive of CMS' proposal to 
make this policy effective for 4 years, many other commenters objected. 
Some commenters pointed to the difficulty in sunsetting a policy that 
has been in effect for a number of years. Others argued there is no 
certainty that wage data 4 years from implementation would show that 
benefiting hospitals have raised wages (that is, the data may show 
benefiting hospitals gradually raised wages or not at all). Some argued 
that not all low wage hospitals will be able to raise wages 
immediately.
    Response: As noted earlier, our proposal to increase the wage index 
for low wage index hospitals is intended to provide an opportunity for 
low wage hospitals to increase their employee compensation, which we 
believe, based on responses to the request for information as well as 
comments received on this proposal, that low wage index hospitals have 
been prevented from doing because of the lag between the time hospitals 
increase employee compensation and the time these increases are 
reflected in the wage index. Based on responses to the request for 
information as well as comments received on our proposal, we expect 
such hospitals to increase employee compensation as a result of this 
policy as noted previously. Once that increased employee compensation 
is reflected in the wage data, there may be no need for the 
continuation of the policy, given that we would expect the resulting 
increases in the wage index to continue after the temporary policy is 
discontinued.
    We still intend to revisit the issue of the duration of the policy 
in future rulemaking as we gain experience under the policy. In 
response to commenters who indicated that it is difficult to sunset a 
policy that has been in effect for a number of years, we have routinely 
allowed transition policies related to changes in the wage index as a 
result of updated labor market areas to expire, and in the FY 2019 IPPS 
final rule we allowed the temporary imputed floor policy to expire. 
Just as it is within our rulemaking authority to adopt this policy, it 
also lies within our authority to discontinue it after it no longer 
serves to increase the accuracy of the wage index.
    After consideration of the public comments we received, for the 
reasons discussed in this final rule and in the proposed rule, we are 
finalizing our proposal to increase the wage index for hospitals with a 
wage index value below the 25th percentile wage index 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, as proposed without modification. Based 
on the data for this final rule, for FY 2020, the 25th percentile wage 
index value across all hospitals is 0.8457. As proposed, this policy 
will be in effect for at least 4 fiscal years beginning October 1, 
2019. As discussed above, we intend to revisit the issue of the 
duration of this policy in future rulemaking as we gain experience 
under the policy.
b. Budget Neutrality for Providing an Opportunity for Low Wage Index 
Hospitals To Increase Employee Compensation
    As noted earlier and discussed in the FY 2020 IPPS/LTCH PPS 
proposed rule (84 FR 19393 through 19399), in

[[Page 42329]]

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 a wage 
index ceiling.
    In the proposed rule (84 FR 19395 through 19396), we stated our 
belief that while it would not be appropriate to create a wage index 
floor or a wage index ceiling as suggested in the previously summarized 
comment, we believed the suggestion that we provide a mechanism to 
increase the wage index of low wage index hospitals (as finalized in 
section III.N.2.a. of this final 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 previously summarized comment, we 
stated in the proposed rule our belief that it would be appropriate to 
maintain budget neutrality for the low wage index policy proposed in 
section III.N.3.a. of the preamble of the 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. As indicated in 
the proposed rule, 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 the proposed rule, we proposed to 
decrease the wage index values for hospitals with high wage index 
values, but preserve the rank order among those values, as further 
discussed in this final rule.
    As discussed in section III.N.3.a. of the preamble of the 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 stated in the 
proposed rule we believe our proposed quartile approach is reasonable 
for this purpose, given that, as previously discussed, 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 proposed 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 the 
proposed rule is budget neutral, we proposed 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 the 
proposed rule; that is, we proposed 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.
    We stated in the proposed rule that we believe we have authority to 
implement our lowest quartile wage index proposal in section III.N.3.a. 
of the preamble of the proposed rule and our budget neutrality proposal 
in section III.N.3.b. of the preamble of the 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.
    Comment: The vast majority of commenters believed CMS should not 
apply budget neutrality at all to our proposed increase in the wage 
index for low wage hospitals as there are strong policy reasons not to 
do so, CMS does not have the statutory authority to do so, and/or it is 
not required by law. Many commenters specifically objected to our 
proposal to reduce the wage index values for hospitals in the top 
quartile indicating that it arbitrarily results in an inaccurate wage 
index for high wage hospitals, and it ignores the CMS audited wage data 
from high wage hospitals reflecting the actual labor costs of these 
hospitals. These commenters indicated that our proposed reduction to 
high wage hospitals undermines and is inconsistent with a wage index 
that is required to reflect real differences in labor costs based on 
data collected from IPPS hospitals.
    Some commenters indicated that while they appreciate CMS' 
recognition of the fact that certain hospitals, including rural 
hospitals, may be in financial distress, facing potential closure, and 
in need of relief, there are high wage hospitals that have negative 
margins and also are struggling financially. Therefore, these 
commenters questioned whether a link can be made between the level of 
the Medicare wage index and hospitals' financial performance. These 
commenters stated that CMS has conducted no analysis or study 
establishing such a link, making the proposal a poorly researched, 
expensive, redistributive experiment. These commenters indicated our 
proposal effectively means that a struggling community hospital in a 
high-wage area would have to sustain Medicare payment cuts in order to 
subsidize arbitrary and possibly unfounded positive payment adjustments 
for hospitals in low-wage areas. These commenters questioned whether 
the Medicare wage index is the appropriate mechanism to attempt to 
improve the financial performance of low-wage index hospitals at the 
expense of high wage index hospitals.
    Many commenters indicated that there is a high and increasing cost 
of living in high wage areas, and that high cost of living is reflected 
in the compensation provided to hospitals employees in those areas. 
These commenters indicated that our proposed budget neutrality 
adjustment targeted on high wage hospitals arbitrarily

[[Page 42330]]

disregards these actual cost of living differences.
    Many commenters indicated that the agency should not apply budget 
neutrality at all given the below-cost reimbursement that all inpatient 
PPS hospitals face and the lack of evidence to justify reductions to 
wage index values. Specifically, many of these commenters stated that 
Medicare currently reimburses IPPS hospitals less than the cost of care 
as evidenced both by survey data and declining Medicare margins over 
time. Many also stated that CMS did not indicate or provide evidence to 
show that wage index values above the 75th percentile are inaccurate or 
that those values do not reflect the wages paid by those hospitals. 
They indicated that CMS did not make any claims that these higher wage 
hospitals have wage index values that are unrepresentative of real wage 
information. They indicated that a policy that penalizes certain 
hospitals simply because of where they fall in the wage index 
distribution is not based on evidence and is arbitrary. They indicated 
that our proposed budget neutrality on high wage hospitals contradicts 
the efforts that both hospitals and CMS make in order to have 
consistent and accurate wage data reporting, including regular data 
submissions, revisions and audits.
    Some commenters asserted that CMS has acknowledged that it is not 
required to increase the wage index values for low wage hospitals 
budget neutrally. Rather, CMS stated that ``it would be appropriate to 
maintain budget neutrality'' for the policy.
    Some commenters indicated that our proposed budget neutrality 
adjustment on high wage hospitals penalizes certain rural hospitals. 
Specifically, these commenters indicated that the 75th percentile 
policy would reduce payments to 5 percent of rural IPPS hospitals, 
putting them at even more financial risk and likely worsening financial 
health and access concerns in certain rural areas. Other commenters 
indicated that it would negatively impact some safety net hospitals. A 
few commenters indicated that the proposal would negatively impact 
hospitals in all-urban states already suffering from the expiration of 
the imputed floor policy.
    Commenters disagreed as to the budget neutrality approach CMS 
should take if our proposed increase in the wage index for low wage 
hospitals was implemented in a budget neutral manner. Some commenters 
supported our proposed budget neutrality adjustment on the top quartile 
indicating that hospitals in the middle two quartiles should not be 
impacted by increases in the lowest quartile. Other commenters, 
however, indicated that CMS should fund the increase through a national 
budget neutrality adjustment as is CMS's usual policy. (We note 
national budget neutrality on the standardized amount was one of the 
alternatives considered in the proposed rule (84 FR 19672)). These 
commenters claimed ``selective'' budget neutrality, as proposed by CMS, 
whereby a small subset of hospitals bears the entire burden of budget 
neutrality for a given CMS policy change is unprecedented, and it 
violates both the statutory purpose of the wage index and CMS' own 
long-standing policy of ensuring budget neutrality by spreading the 
cost of payment adjustments across all hospitals equally.
    Similar to some comments made regarding our increase of the wage 
index values of hospitals in the lowest quartile, many commenters 
stated that the law does not provide CMS with the authority to reduce 
the wage index values of the high wage index hospitals and/or any wage 
index values to offset the increase in payments to the hospitals in the 
lowest quartile. Many of these commenters discussed both our authority 
under section 1886(d)(3)(E) and (d)(5)(I) of the Act. The legal 
comments included the following arguments.
    With respect to our authority under 1886(d)(3)(E) of the Act, these 
commenters asserted that CMS states, but does not explain why, the 
statute setting forth the wage index provision gives it broad authority 
to institute a wage compression policy that, in essence, makes 
inaccurate the wage data values for half of the nation's hospitals. 
These commenters indicated that section 1886(d)(3)(E) of the Act 
provides a process for the adjustment of hospital payments to account 
``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. These commenters indicated that the wage compression proposal 
violates the plain language of the statute because it will not result 
in an adjustment to the payment rates that reflect the actual wage data 
difference between the relative hospital wage levels in a geographic 
area compared to the national average, subject only to those 
adjustments that have been specifically set forth by Congress. The 
commenters indicated that our proposal clearly contradicts Congress' 
mandate.
    Some commenters indicated that while certain of the details of the 
creation and implementation of the wage index may have been delegated 
by Congress to the agency, the statute nevertheless requires the 
Secretary to develop a mechanism to remove the effects of local wage 
differences. These commenters indicated that the payment adjustments to 
reflect area wage differences must be accurate. These commenters 
indicated that CMS' wage compression proposal does not remove the 
effects of local wage differences, but instead disregards accurately 
reported wage data for 50% of the nation's hospitals. These commenters 
asserted this is beyond the authority delegated to the agency and 
ignores the text of the statute whereby CMS is to adjust IPPS payments 
by a factor ``reflecting the relative hospital wage level in the 
geographic area of the hospital compared to the national average 
hospital wage level.''
    These commenters indicated that Congress instituted this statutory 
provision to identify actual differences in geographic labor costs 
relative to the national average and to account for them in the 
payments to hospitals, subject only to those adjustments that Congress 
has specifically authorized. These commenters indicated that Congress 
has authorized several adjustments in section 1886(d)(3)(E) of the Act 
to the hospital wage index adjustment, such as a budget neutrality 
adjustment, an adjustment to fix the wage-related portion at 62 
percent, and a floor for frontier hospitals. These commenters stated 
that CMS has acted consistently with Congress' directives in the past, 
and has calculated the wage index based on actual wage data, subject 
only to those modifications specifically permitted by Congress and 
Congress has not authorized the wage compression adjustment. Moreover, 
these commenters asserted that CMS has instituted a process--the Wage 
Index Development Timetable--with detailed instructions for the sole 
purpose of ensuring that CMS has accurate wage index data from all IPPS 
hospitals. These commenters also noted that the data reported on 
Worksheet S-3 of the Medicare cost report are the only section of the 
cost report that is subject to a Medicare administrative contractor 
(MAC) review every single year. In addition to the MAC review, there is 
a subsequent additional secondary auditor with oversight of the MACs to 
ensure data are reported accurately. They indicated CMS has invested 
significant resources to ensure that the data reported and reflected in 
each

[[Page 42331]]

year's cost reports are reliable and valid for the purposes of payment.
    However, these commenters believe CMS is now proposing a policy 
that would use the wage data in a manner to rank the various hospitals 
so that the data of 25 percent of hospitals will be inaccurately and 
artificially pushed downwards to allow the data of a different 25 
percent of hospitals to be inaccurately and artificially pushed 
upwards. They indicated that nothing in section 1886(d)(3)(E) of the 
Act suggests that Congress authorized CMS to institute a policy whereby 
half of the hospitals would receive wage index values that did not 
accurately match their actual values. Thus, these commenters asserted 
that CMS' proposal is beyond the authority granted by Congress, and CMS 
cannot lawfully institute our proposal under section 1886(d)(3)(E) of 
the Act.
    These commenters also asserted that CMS' proposed action is ultra 
vires. They indicated that section 1886(d)(3)(E) of the Act contains 
only two exceptions. They indicated that Congress writes rules as well 
as exceptions. They stated that in section 1886(d)(3)(E) of the Act, 
Congress did both, establishing the basic rule in clause (i), and 
exceptions in clauses (ii) and (iii). Commenters stated these are the 
only exceptions that Congress has made, and that. Congress has not made 
any type of special exception to the first clause that would allow CMS 
to institute the wage compression policy. Thus, these commenters 
asserted that Congress did not give CMS the authority to implement the 
wage compression policy. As such, these commenters stated that the CMS-
proposed action is ultra vires, and that the agency could not institute 
this proposal in conformance with section 1886(d)(3)(E) of the Act. 
These commenters further stated that, if Congress wanted to change the 
wage index in the manner proposed by CMS, it could have.
    With respect to our exceptions and adjustments authority under 
section 1886(d)(5)(I) of the Act, these commenters stated--(1) this 
``catchall'' cannot be used in a manner that vitiates the language and 
purpose of the rest of the statute, including section 1886(d)(5)(A) 
through (H) of the Act, as there must be limits to the authority 
granted to CMS under this section; (2) CMS is not acting by regulation, 
and, therefore, is not following 1886(d)(5)(I); and (3) if CMS does 
have the authority to make this change, this special authority is not 
required to be done in a budget neutral manner, as is clear from the 
statute where paragraph (d)(5)(I)(ii) references budget neutrality, but 
paragraph (d)(5)(I)(i) does not, and as is clear from relevant case 
law.
    Response: As noted earlier, the intent of our proposal to increase 
the wage index for low wage hospitals is to increase the accuracy of 
the wage index as a technical adjustment, and not to use the wage index 
as a policy tool to address non-wage issues related to rural hospitals, 
or the laudable goals of the overall financial health of hospitals in 
low wage areas or broader wage index reform. As discussed previously, 
our proposal to increase the wage index for low wage index hospitals 
increases the accuracy of the wage index as a relative measure because 
it will allow low wage index hospitals to increase their employee 
compensation in ways that we would expect if there were no lag in 
reflecting compensation adjustments in the wage index. As we noted 
previously, we believe that many low wage index hospitals have been 
prevented from increasing compensation because of the lag under our 
cost reporting process between the time hospitals increase employee 
compensation and the time these increases are reflected in the wage 
index. Thus, under our proposal, we believe the wage index for low wage 
index hospitals will appropriately reflect the relative hospital wage 
level in those areas compared to the national average hospital wage 
level. Because our proposal is based on the actual wages that we expect 
low wage hospitals to pay, it falls within the scope of the authority 
of section 1886(d)(3)(E) of the Act. In particular, since our proposal 
will increase the accuracy of the wage index, we disagree with 
commenters' assertions that our proposal does not remove the effects of 
local wage differences, that it disregards accurately reported wage 
data, or that our proposal is beyond the authority granted to the 
agency under section 1886(d)(3)(E) of the Act whereby CMS is to adjust 
IPPS payments by a factor ``reflecting the relative hospital wage level 
in the geographic area of the hospital compared to the national average 
hospital wage level.''
    Under section 1886(d)(3)(E) of the Act, the wage index adjustment 
is required to be implemented in a budget neutral manner. However, even 
if the wage index were not required to be budget neutral under section 
1886(d)(3)(E) of the Act, we would consider it inappropriate to use the 
wage index to increase or decrease overall IPPS spending. As noted 
above, the wage index not a policy tool but rather a technical 
adjustment designed to be a relative measure of the wages and wage-
related costs of subsection (d) hospitals in the United States. As a 
result, if it is determined that section 1886(d)(3)(E) of the Act does 
not require the wage index to be budget neutral, we invoke our 
authority at 1886(d)(5)(I) of the Act in support of such a budget 
neutrality adjustment. Contrary to the suggestions of many commenters, 
we believe we could use our broad authority under that provision to 
promulgate such an adjustment to the extent it was determined that 
section 1886(d)(3)(E) of the Act was not available for that purpose.
    We acknowledge, however, that some commenters have presented 
reasonable policy arguments that we should consider further regarding 
the relationship between our proposed budget neutrality adjustment 
targeting high wage hospitals and the design of the wage index to be a 
relative measure of the wages and wage-related costs of subsection (d) 
hospitals in the United States. Therefore, given that budget neutrality 
is required under section 1886(d)(3)(E) of the Act, given that even if 
it were not required, we believe it would be inappropriate to use the 
wage index to increase or decrease overall IPPS spending, and given 
that we wish to consider further the policy arguments raised by 
commenters regarding our budget neutrality proposal, we are finalizing 
a budget neutrality adjustment for our low wage hospital policy, but we 
are not finalizing our proposal to target that budget neutrality 
adjustment on high wage hospitals. Instead, consistent with CMS's 
current methodology for implementing wage index budget neutrality under 
section 1886(d)(3)(E) of the Act and the alternative approach we 
considered in the proposed rule (84 FR 19672), we are finalizing a 
budget neutrality adjustment to the national standardized amount for 
all hospitals so that the increase in the wage index for low wage index 
hospitals, as finalized in this rule, is implemented in a budget 
neutral manner.
    As discussed above, some commenters asserted that the only 
adjustments to the wage index that are permitted under section 1886(d) 
of the Act are those specified by Congress in the statute (commenters 
specifically referred to the budget neutrality adjustment, the 
adjustment to set an alternative wage-related portion of 62 percent, 
and the floor for frontier hospitals). As we discussed in the proposed 
rule (84 FR 19396), section 1886(d)(3)(E) of the Act 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

[[Page 42332]]

hospital compared to the national average hospital wage level. The fact 
that section 1886(d) of the Act sets forth certain adjustments to the 
wage index calculation, such as those referred to by commenters, does 
not limit the exercise of our discretion under section 1886(d)(3)(E) of 
the Act in other respects.
    After consideration of the public comments received, for the 
reasons discussed in this final rule and in the proposed rule, we are 
finalizing a budget neutrality adjustment for our low wage index 
hospital policy finalized in section III.N.2.a. of this final rule, but 
we are not finalizing our proposal to target that budget neutrality 
adjustment on high wage hospitals as we proposed (84 FR 19395 through 
19396). Instead, consistent with CMS's current methodology for 
implementing wage index budget neutrality under section 1886(d)(3)(E) 
of the Act, and consistent with the alternative we considered in the 
proposed rule, we are finalizing a budget neutrality adjustment to the 
national standardized amount for all hospitals so that the increase in 
the wage index for low wage index hospitals, as finalized in this rule, 
is implemented in a budget neutral manner.
c. Preventing Inappropriate Payment Increases Due to Rural 
Reclassifications Under the Provisions of 42 CFR 412.103
    We stated in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19396 
through 19399) that 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 the 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.
    As we explained in the proposed rule, 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 are 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, we noted that 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 that we presented in the proposed rule, 
for purposes of illustrating the rural floor policy, assume that the 
rural wage index for a State is 1.1000. Therefore, as we stated in the 
proposed rule, 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. 
We further explained that the additional Medicare payments to those 
urban hospitals in that State increase the national budget neutrality 
adjustment for the rural floor provision.
    As we discussed in the proposed rule (84 FR 19397), 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.
    We stated that 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).
    As explained in the proposed rule, 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 noted 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. We stated that this also 
occurs, for example, in Arizona and Connecticut. As discussed in the 
proposed rule, 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 noted in the proposed rule 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 was used for wage index 
calculation and payment purposes in the proposed rule (that is, this 
hospital was not considered rural for wage index purposes). However, we 
stated in the proposed rule that under our current wage index policy as 
of the time of the FY 2020 proposed rule, 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. We note that this hospital did 
in fact withdraw its MGCRB reclassification back to its geographic 
location for the FY 2020 final rule, so absent our proposal, the 
Massachusetts rural floor would have been calculated using the high 
wages of this hospital.
    Returning to our simplified example presented in the proposed rule, 
for purposes of illustrating the impact of an urban to rural 
reclassification on the calculation of the rural floor under current 
policy as of the time of the FY 2020 proposed rule, 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

[[Page 42333]]

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 previously noted by OIG in the November 2018 report referenced, 
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 stated in the proposed rule that we 
believe that urban to rural reclassifications have stretched the rural 
floor provision beyond a policy designed to address such anomalies. We 
explained that, 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. We 
further stated that 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 
stated in the proposed rule 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, as previously described, 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, in the FY 
2020 IPPS/LTCH PPS proposed rule (84 FR 19397), we proposed to remove 
urban to rural reclassifications from the calculation of the rural 
floor. In other words, we stated that 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 stated 
in the proposed rule 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). We stated that section 
1886(d)(8)(E) of the Act does not specify where the wage data of 
reclassified hospitals must be included. Therefore, we stated that we 
believe we have discretion to exclude the wage data of such hospitals 
from the calculation of the rural floor. Furthermore, we explained that 
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 stated that 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 stated that 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 in the proposed rule, 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, we explained that 
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 presented in the proposed rule 
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 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. We stated 
that 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 discussed earlier, we stated in the proposed rule that 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) was 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 
stated in the proposed rule 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 proposed 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). We stated that 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 made 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 proposed 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.
    Comment: Many commenters, including MedPAC, supported our proposal 
to remove urban to rural reclassifications from the calculation of the 
rural floor wage index. Some commenters asserted that CMS has the 
regulatory authority to determine how it calculates the rural floor, 
and the calculation should mirror the spirit and intent of law 
resulting in only the natural rural providers in a state to be 
considered when calculating a rural floor. Commenters strongly 
commended CMS for curbing the manipulative practice of some hospitals 
abusing the rural floor provision to inappropriately influence the 
rural floor wage index value, which many commenters stated exacerbates 
the wage index disparity between urban and rural hospitals.

[[Page 42334]]

Commenters agreed with CMS that the use of urban to rural 
reclassifications to artificially inflate the rural floor has stretched 
the rural floor provision beyond its original intent. They stated that 
hospitals should not be penalized and bear the burden of declining 
reimbursement due to other hospitals manipulating their state wage 
index.
    Many commenters stated that, in particular, the three states cited 
as examples in the proposed rule have benefitted to the detriment of 
hospitals in every other state due to budget neutrality. Commenters 
also stated they hope CMS will not be swayed by comments from hospitals 
that have been ``unjustly enriched'' by this policy over a number of 
years.
    Several commenters stated that including urban to rural 
reclassifications in the rural floor calculation especially 
disadvantaged small, more rural states and financially distraught, 
struggling rural hospitals. In the words of a commenter, this 
``egregious loophole'' has consistently disadvantaged rural and low 
wage hospitals.
    Commenters stated that geographically urban hospitals should have 
no impact on the rural floor, and the proposal fairly achieves CMS' 
intent to address wage index disparities. Similarly, several commenters 
stated that the proposal allows hospitals to still seek designations 
requiring rural status and keeps the rural floor concept intact while 
preventing improper influencing of the area wage index. A commenter 
stated that removing the wage data of urban hospitals that have 
reclassified as rural from the rural floor is a ``step in the right 
direction'' to have the wage index reflect local labor prices.
    A commenter stated that the proposal seems reasonable, but 
suggested that CMS monitor its impacts and reassess whether it 
accomplishes the intended policy goals.
    Response: We appreciate the many comments in support of our 
proposal to remove the wage data of hospitals reclassified under Sec.  
412.103 from the rural floor calculation. As stated in the proposed 
rule, 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. We 
intend to monitor whether the proposal accomplishes the aforementioned 
policy goals.
    Comment: We also received many comments in opposition of this 
proposal. Many commenters requested that CMS continue to consider the 
wage data of hospitals reclassified under Sec.  412.103 in the rural 
floor calculation. A few commenters requested CMS leave the current 
calculation of the rural floor in place until there is a broader 
solution resulting from CMS working with Congress. A commenter stated 
the proposal would actually penalize many rural states, rather than 
support them because many hospitals in states that are mostly rural in 
character benefit from the inclusion of urban hospitals reclassified as 
rural in the wage index rural floor. Commenters also stated that 
excluding reclassified hospitals from the rural floor is plainly 
inconsistent with the statutory language. Commenters stated that the 
statute does not draw any distinction between the ``rural areas'' used 
to calculate the rural floor under section 4410(a) of the Balanced 
Budget Act of 1997 and the ``rural areas'' that reclassified hospitals 
are to be treated as located in under section 1886(d)(8)(E) of the Act. 
According to these commenters, Congress intended the term ``rural 
area'' to have the same definition when applied to the rural floor and 
section 1886(d)(8)(E) of the Act. A commenter specifically stated that 
Congress did not create a subcategory of rural hospitals that are 
eligible for the rural wage index, but whose wages are not included in 
the calculation of a state's rural floor. Furthermore, this commenter 
stated that the precedent set by two cases, Geisinger Community Medical 
Center v. Burwell, and Lawrence + Memorial Hospital v. Burwell 
establishes that a reclassified hospital should be treated as a rural 
hospital for all purposes under IPPS, including wage reclassification.
    Response: In the absence of broader wage index reform from 
Congress, we believe it is appropriate to revise the rural floor 
calculation as part of an effort to reduce wage index disparities. In 
response to the comment that many hospitals in states that are mostly 
rural benefit from the inclusion of urban hospitals in the wage index 
rural floor, the volume of comments that we received from stakeholders 
in mostly rural states supporting our proposal indicate that hospitals 
in such states were hurt more than helped by including hospitals with 
urban to rural reclassifications in the calculation of the rural floor. 
While urban hospitals in mostly rural states may benefit from an 
increase in the rural floor due to urban to rural reclassification, as 
the commenters suggest, other states with high wage urban hospitals 
using Sec.  412.103 reclassifications to raise the rural floor can 
mitigate those gains for mostly rural states, due to budget neutrality.
    Regarding CMS' statutory authority, as stated in the proposed rule, 
we believe our proposed calculation methodology is permissible under 
section 1886(d)(8)(E) of the Act (as implemented in Sec.  412.103) 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 note that under our 
proposal we would continue to calculate the rural floor based on the 
physical non-MSA area of a state, which is the same rural area to which 
a hospital is reclassified under section 1886(d)(8)(E) of the Act. 
However, for purposes of calculating the rural floor wage index for a 
state, we would not include in the rural area the data of hospitals 
that have reclassified as rural under section 1886(d)(8)(E) of the Act. 
As we discussed in the proposed rule (84 FR 19397), 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). Under the current rural floor wage index 
calculation, 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. We believe 
excluding the data of hospitals that reclassify as rural under section 
1886(d)(8)(E) of the Act from the rural floor wage index is necessary 
and appropriate to address these unanticipated effects of rural 
reclassifications on the rural floor and the resulting wage index 
disparities, and is consistent with our authority under section 
1886(d)(8)(E) of the Act and the rural floor statute.
    We also note that our proposal is consistent with the decisions in 
Geisinger Community Medical Center v. Secretary, United States 
Department of Health and Human Services, 794 F.3d

[[Page 42335]]

383 (3d Cir. 2015) and Lawrence + Memorial Hospital v. Burwell, 812 
F.3d 257 (2d Cir. 2016) in which the courts found that hospitals 
reclassified under Sec.  412.013 must be considered rural for all 
purposes. Accordingly, it is CMS policy to consider hospitals 
reclassified as rural under Sec.  412.103 as having rural status. For 
example, a hospital with a Sec.  412.103 rural reclassification would 
receive the rural wage index and would use the rural mileage and wage 
criteria when applying for an MGCRB reclassification. But the issue 
whether to include the hospital's wage data for purposes of calculating 
the rural floor is separate from issues of the treatment of the 
hospital itself. The hospital is being treated as rural for section 
1886(d) purposes regardless of whether its data is included for 
purposes of calculating the rural floor. We do not believe that the 
decisions in Geisinger and Lawrence+Memorial require any particular 
treatment of the wage data of hospitals reclassified under Sec.  
412.103 for purposes of calculating the rural floor. Those hospitals 
are being treated as rural because they are being allowed to reclassify 
through the MGCRB based on their rural designation under Sec.  412.103, 
regardless of the treatment of their wage data for purposes of 
calculating the rural floor.
    We believe that the strict reading of ``rural for all purposes'' to 
which the commenters subscribe is neither required by the text of the 
court decisions they cite nor appropriate from a policy perspective. 
For example, the wage data of a hospital with a Sec.  412.103 rural 
redesignation is considered in its home geographic area in addition to 
the rural area to which it is reclassified for purposes of calculating 
the wage index. We believe that the commenters' reading would 
inappropriately require that the wage data for hospitals reclassified 
under Sec.  412.103 be excluded from the wage index calculation of 
their geographic locations. Similarly, we believe that the commenters' 
reading that hospitals redesignated under Sec.  412.103 must be treated 
as rural for all purposes could, if taken to its logical extreme, mean 
we must treat those hospitals as geographically located in the rural 
area. That could in turn potentially reduce a State's rural wage index 
value. The rural area wage index is held harmless from decreases due to 
any effect of wage index reclassification, but the hold harmless 
protection does not apply to the effect on the area wage index of 
hospitals geographically located in the area.
    Comment: A commenter stated that rather than eliminating the 
benefit of gaming, CMS has created a competitive advantage for large, 
high cost urban hospitals that are able to reclassify as rural and 
receive the benefit of an increased rural area wage index while their 
lower cost competitors in their urban home geographic area that are not 
reclassified as rural are left with a reduced area wage index. Another 
commenter suggested reducing the potential for gaming by applying the 
rural floor only to rural hospitals in primarily urban states with only 
one or two rural facilities. Similarly, a commenter stated that any 
proposal should not disincentivize hospitals from reporting accurate 
data. Another commenter expressed understanding for CMS' concerns about 
the potential for gaming by engineering a rural floor for a state that 
is not reflective of the overall labor market for the state, but 
believed that the proposed solution ``swings the pendulum too far in 
the other direction'' by failing to recognize the unique healthcare 
skillset that requires urban and rural hospitals to compete in the same 
labor market. This commenter suggested the following alternative 
solutions:
     Allow urban hospitals to apply for reclassification to 
rural under the MGCRB for wage index purposes only. To prevent 
inflating the reclassified wage index, threshold criteria to show that 
the hospital operates in the same labor market as the State's rural 
hospitals could include an additional test that the hospital's average 
hourly wage is not more than 108 percent of the statewide rural average 
hourly wage.
     Set the floor for both urban and rural hospitals at the 
statewide average hourly wage. The commenter stated that state 
licensure of healthcare professions promotes a statewide healthcare 
labor market, and that this would therefore be a more realistic concept 
for a floor than a rural floor (even if comprised solely of 
geographically rural hospitals) which perpetuates the possibly 
erroneous perception that urban wages should not be lower than rural 
wages.
    Another commenter requested that CMS calculate each rural 
reclassified wage index independently, by excluding all other 
reclassified hospitals from the calculation.
    Response: We appreciate the commenters' recognition of our efforts 
to address gaming. In response to the first commenter who was concerned 
that CMS is creating a competitive advantage for large, high cost urban 
hospitals that are able to reclassify as rural and receive the benefit 
of an increased rural area wage index while their lower cost 
competitors in the home urban geographic area that are not reclassified 
as rural are left with a reduced area wage index, we note that the wage 
data of reclassified hospitals are included in both the hospital's 
geographic CBSA and the CBSA to which the hospital is reclassified for 
the wage index calculation. Accordingly, the wage data for a hospital 
with a Sec.  412.103 redesignation are included in the wage index for 
its home geographic area and are also included in its State rural wage 
index (if including wage data for hospitals with a reclassification to 
a rural area raises the state's rural wage index). Therefore, we are 
unsure why the commenter believes that lower cost competitors are left 
with a reduced area wage index when a hospital reclassifies out of the 
urban area. In response to the second commenter, we do not believe we 
can apply the rural floor to rural hospitals because section 4410(a) of 
Public Law 105-33 provides that the area wage index applicable to any 
hospital that is located in an urban (emphasis added) area of a State 
may not be less than the area wage index applicable to hospitals 
located in rural areas in that State. With regard to the third comment, 
we agree that any proposal should not disincentivize hospitals from 
reporting accurate data and do not believe that our proposal 
disincentivizes accurate data reporting. Finally, with regard to the 
commenters' suggested alternatives, because we consider these comments 
to be outside the scope of the FY 2020 wage index proposals, we are not 
addressing them in this final rule but may consider them in future 
rulemaking.
    Comment: A commenter requested that CMS completely eliminate the 
national budget neutral impact of the rural floor policy, but 
recognized this may be difficult to achieve absent legislative action.
    Response: We agree with the commenter that this would be difficult 
to achieve without legislative action, as section 3141 of Public Law 
111-148 requires that a national budget neutrality adjustment be 
applied in implementing the rural floor.
    Comment: A commenter specifically supported CMS' proposed 
``thoughtful changes'' to the rural floor wage index methodology so 
that the wage index of a State rural area could be differentiated from 
the state rural floor wage index. Several other commenters requested 
that CMS clarify the examples given in the proposed rule to confirm 
that the urban hospital reclassified as rural does obtain a wage index 
inclusive of that hospital's wage data.
    Response: We appreciate the first commenter's support. In response 
to the commenters requesting clarification, we are confirming that an 
urban hospital

[[Page 42336]]

reclassified as rural would obtain a wage index inclusive of that 
hospital's wage data under the proposed rural floor wage index policy. 
In the example in the proposed rule referred to by the commenter, where 
one urban hospital in a State reclassifies from urban to rural and 
raises the rural wage index from 1.1000 to 1.2000, 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. The rural wage index, however, would be raised to 
1.2000 for the geographically rural hospitals and for hospitals 
reclassified as rural.
    Comment: A commenter stated that hospitals that are reclassified as 
rural hospitals by CMS did so under allowable HHS authority and should 
not be penalized. Another commenter stated CMS' proposal will adversely 
impact urban hospitals that have made decisions to reclassify as rural 
under current policy and urged CMS to consider a three-year hold 
harmless period during which urban hospitals that have already 
reclassified as rural would be counted in each state's rural floor.
    Response: We do not believe that this proposal penalizes or 
adversely impacts urban hospitals that have reclassified as rural. 
Hospitals reclassified as rural under Sec.  412.103 would continue to 
maintain the benefits conferred by rural reclassification, as well as 
receive the rural wage index calculated including their data (provided 
that the hospital does not also have an MGCRB reclassification under 
section 1886(d)(10) of the Act or Lugar status under section 
1886(d)(8)(B) of the Act).
    After consideration of the public comments we received, for the 
reasons discussed in this final rule and in the proposed rule, we are 
finalizing without modification 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). Additionally, we are finalizing without modification 
our proposal, for purposes of applying the provisions of section 
1886(d)(8)(C)(iii) of the Act, to remove the wage data of urban 
hospitals reclassified as rural under section 1886(d)(8)(E) of the Act 
(as implemented at Sec.  412.103) 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. Transition for Hospitals Negatively Impacted
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19398), we stated 
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 stated in the proposed rule 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 proposed 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 proposed 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 proposed 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. We stated that 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 stated 
in the proposed rule 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 sought public comments on 
alternative levels for the cap and accompanying rationale. We stated 
that, 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.
    Comment: Commenters, including MedPAC, commended CMS for proposing 
the 5 percent cap to help transition providers through the proposed 
wage index changes. A commenter specifically agreed that the cap should 
only be applied for one year, while other commenters requested that 
hospitals negatively impacted should be given a longer transition to 
support hospitals continuing to experience a significant decrease, so 
as not to inflict financial harm on community hospitals.
    Several commenters stated that the funding cliff created by the 
proposed policies for impacted hospitals is of sufficient magnitude 
that it will not be mitigated by a 5 percent cap. A commenter 
specifically recommended that the cap be extended for the entire 
proposal and that a cumulative cap be added as well to ensure no 
hospital loses more than 10 percent of its current cap overall. Another 
commenter stated that even a reduction of 5 percent could create 
significant financial problems for rural IPPS hospitals and that the 
cap does not provide long-term protection from reductions after one 
year, so CMS should exempt rural IPPS hospitals from any wage index 
reduction for FY 2020 and subsequent years. Additionally, MedPAC stated 
that the cap on wage index movements of more than 5 percent in one year 
should also be applied to increases in the wage index.
    Some commenters indicated that there should be no transition policy 
because the transition policy benefits hospitals that have historically 
seen increases in their wage index due to one or more urban hospital in 
a state reclassifying as rural and increasing the rural floor in that 
state.
    Response: We appreciate the commenters' input. We agree that a 
transition policy to help mitigate significant negative impacts on 
hospitals would be appropriate here. We believe that the proposed 
transition, which caps a hospital's final wage index for FY 2020 at not 
less than 95 percent of its final wage index for FY 2019, is sufficient 
to allow the effects of our proposed policies to be phased in over 2 
years (that is, no cap would be applied the second year). As we stated 
in the proposed rule, we believe that 5 percent is a reasonable level 
for the cap because it would effectively mitigate any significant 
decreases in the wage index for FY 2020. We note that commenters did 
not suggest any alternate levels for the cap that they believed would 
be more appropriate. Regarding the commenter advocating for an 
additional cumulative cap, it is unclear what is

[[Page 42337]]

meant by ``10 percent of the current cap overall''. We are unsure what 
the commenter intended or how the commenter believes such a cumulative 
cap would work. As we stated above, we believe the 5 percent cap would 
effectively mitigate significant decreases in the wage index for FY 
2020 and provide sufficient time for hospitals to adapt to the wage 
index policies that will be effective October 1, 2019.
    Additionally, we do not believe it would be necessary or 
appropriate to have a longer transition. We believe a one year cap 
provides hospitals with declining payments sufficient time to plan 
appropriately for FY 2021 and future years, especially because some 
hospitals may be able to make reclassification choices to mitigate the 
decline. Furthermore, we disagree that there should be no transition. 
Because we are finalizing wage index changes that have significant 
payment implications, and consistent with our provision of transition 
periods in the past to mitigate large negative impacts on hospitals, we 
believe it would be appropriate to provide a wage index transition as 
proposed for FY 2020.
    In response to the commenter requesting that CMS exempt IPPS rural 
hospitals from any wage index reduction for FY 2020 and subsequent 
years, we do not believe that such an exemption for all IPPS rural 
hospitals from any wage index reduction would promote an accurate wage 
index. Such an exemption for all IPPS rural hospitals would ignore the 
reality that average hourly wages may sometimes decline relative to the 
national average. Furthermore, such an exemption is not necessary as we 
believe that a 5 percent cap on wage index decreases for one year is 
sufficient to allow such hospitals to adjust to the wage index policies 
that will be effective October 1, 2019.
    Finally, we appreciate MedPAC's suggestion that the cap on wage 
index movements of more than 5 percent should also be applied to 
increases in the wage index. However, as we discussed in the proposed 
rule, the purpose of the proposed transition policy, as well as those 
we have implemented in the past, is to help mitigate the significant 
negative impacts of certain wage index changes, not to curtail the 
positive impacts of such changes, and thus we do not think it would be 
appropriate to apply the 5 percent cap on wage index increases as well.
    Comment: A few commenters sought clarification whether the 5 
percent cap will be applied to all hospitals experiencing a wage index 
decrease from FY 2019 to FY 2020 regardless of circumstance, not just 
as a result of the proposals to address wage index disparities. The 
commenters specifically questioned whether hospitals that experience a 
wage index decrease for reasons such as losing an MGCRB 
reclassification, reclassifying from urban to rural under Sec.  
412.103, or changes to their wage index data would also have any 
decrease in their FY 2020 wage indexes compared to their final FY 2019 
wage indexes capped at 5 percent. A commenter suggested that CMS move 
the budget neutrality computation and comparison earlier in the 
calculation so that it is only comparing the changes resulting from the 
proposed modifications to address wage index disparities, to eliminate 
the unintended consequences of the ``flawed'' approach in the proposed 
rule which limits losses even from normal, anticipated changes in the 
wage index calculations.
    A few commenters also requested clarification regarding the 
applicability of the 5 percent cap on the wage index of a provider if 
it changes from urban to rural reclassification after the FY 2020 final 
rule is issued. For example, commenters questioned whether the 
hospital's wage index decrease would also be capped at a -5 percent 
change from their FY 2019 wage index if a decrease to a hospital's wage 
index occurs midyear during FY 2020 due to an urban to rural 
reclassification under Sec.  412.103.
    Additionally, a few commenters requested that CMS define the term 
``the hospital's final wage index in FY 2019'' to clarify whether that 
refers to the final amount published in the FY 2019 IPPS final rule, 
the wage index paid to the hospital on the final day of FY 2019, or 
something else.
    Response: We are clarifying that all hospitals will have any 
decrease in their wage indexes capped at 5 percent for FY 2020, 
regardless of circumstance causing the decline. With regard to the 
commenter who suggested that CMS only apply the transition to changes 
resulting from the proposed modifications to address wage index 
disparities, we note that it would be difficult to isolate changes due 
to the wage index disparities proposals because these proposals 
influence wage index and rural floor values, which may change 
hospitals' reclassification decisions as a result. Therefore, we 
believe that it is preferable in the interest of administrative 
simplicity, ease of implementation, and hospital financial planning, to 
apply the cap universally to all decreases in the wage index that occur 
during FY 2020, not just those resulting from our proposals to address 
wage index disparities.
    In response to the commenters' requests for clarification regarding 
how the cap would be applied to midyear wage index changes, we will 
also apply this transition policy for FY 2020 to decreases in the FY 
2020 final wage indexes that occur after FY 2020 final rule 
ratesetting. For example, a decrease in a hospital's wage index caused 
by a midyear FY 2020 wage index change would also be capped at a -5 
percent change from FY 2019.
    In response to the commenters who requested that we define the term 
``the hospital's final wage index in FY 2019'', we are clarifying that 
this refers to the final amount published in the FY 2019 IPPS final 
rule. We believe that using the publicly available wage indexes from 
the FY 2019 IPPS final rule facilitates transparency. A hospital can 
contact its MAC for assistance if it believes the incorrect wage index 
value was used as the basis for its transition and the MAC can make any 
appropriate correction.
    After consideration of the public comments we received, for the 
reasons discussed in this final rule and the proposed rule, we are 
finalizing without modification our proposal, as clarified previously, 
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 so that a hospital's 
final wage index for FY 2020 will not be less than 95 percent of its 
final wage index for FY 2019.
e. Transition Budget Neutrality
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19398), we proposed to apply a budget neutrality adjustment to the 
standardized amount so that our proposed transition (as previously 
described and in section III.N.3.d. of the preamble of the proposed 
rule (84 FR 19398)) 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 noted 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 stated that 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

[[Page 42338]]

never proposed these transition policies (79 FR 50732). Therefore, for 
FY 2020, we proposed 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 previously and in section III.N.3.d. of the preamble of the 
proposed rule) for hospitals negatively impacted is implemented in a 
budget neutral manner.
    Specifically, we proposed to apply a budget neutrality adjustment 
to ensure that estimated aggregate payments under our proposed 
transition (as previously described in section III.N.3.d. of the 
preamble of the 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 proposed to apply a budget neutrality adjustment 
factor of 0.998349 to the FY 2020 standardized amount, as further 
discussed in the Addendum to the proposed rule (84 FR 19398). We stated 
in the proposed rule that if this policy is adopted in the final rule, 
this number would be updated based on the final rule data.
    We noted in the proposed rule (84 FR 19398 through 19399) that our 
proposal, discussed in section III.N.3.c. of the preamble of the 
proposed rule (84 FR 19396 through 19398), to prevent inappropriate 
payment increases due to rural reclassifications under Sec.  412.103 
would also be budget neutral, but this budget neutrality would occur 
through the proposed budget neutrality adjustments for geographic 
reclassifications and the rural floor that were discussed in the 
Addendum to the proposed rule.
    Comment: MedPAC agreed that the 5 percent cap should be applied in 
a budget-neutral manner. Another commenter requested that CMS budget 
neutralize the impact of the 5 percent cap transition by reducing the 
wage indexes of the upper quartile rather than the standardized amount. 
The commenter stated that it would be much more appropriate to increase 
the upper quartile budget neutrality factor to whatever factor would be 
necessary to fund the 5 percent cap.
    Response: We appreciate MedPAC and the commenter's input. As 
discussed previously, in order to further consider policy arguments 
raised by commenters, we are not finalizing our proposal to apply an 
adjustment to the wage index of high wage index hospitals to budget 
neutralize the wage index increase for low wage index hospitals 
(finalized in section III.N.3.b. of this final rule). We would need to 
further consider the same policy arguments before applying an 
adjustment to the wage indexes of high wage index hospitals to budget 
neutralize the transition policy finalized in this final rule. However, 
we continue to believe that it is appropriate and consistent with past 
practice (for example, 79 FR 50372) to budget neutralize this 
transition wage index policy by applying an adjustment to the 
standardized amount for all hospitals.
    After consideration of the public comments we received, for the 
reasons discussed in this final rule and the proposed rule, we are 
finalizing our proposal, without modification, to apply a budget 
neutrality adjustment factor to the FY 2020 standardized amount for all 
hospitals to achieve budget neutrality for the transition policy, as 
further discussed in the Addendum of this final rule. Based on the 
final rule data, the budget neutrality adjustment factor to achieve 
budget neutrality for the transition policy is 0.998838. We refer 
readers to the Addendum of this final rule for further information 
regarding this budget neutrality calculation.
f. Alternatives Considered in the Proposed Rule
    In the proposed rule (84 FR 19672), we considered a number of 
alternatives to our proposed policies to address wage index 
disparities. First, as an alternative to the proposed approach to 
budget neutralize the wage index increase for low wage index hospitals, 
we considered applying a budget neutrality adjustment factor to the 
standardized amount rather than focusing the adjustment on the wage 
index of high wage index hospitals. Second, we also considered 
mirroring our proposed approach of raising the wage index for low wage 
index hospitals by reducing the wage index values for high wage index 
hospitals by half the difference between the otherwise applicable final 
wage index value for these hospitals and the 75th percentile wage index 
value across all hospitals. We stated we would then make the estimated 
net effect on payments of--(1) the increase in the wage index for low 
wage index hospitals; and (2) the decrease in the wage index for high 
wage index hospitals budget neutral through an adjustment to the 
standardized amount. Finally, we considered creating a single national 
rural wage index area and rural wage index value, as further described 
in the proposed rule (84 FR 19672). 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.
    Comments: In section III.N.2.b. of the preamble of this final rule, 
we summarized comments regarding the first alternative considered to 
budget neutralize the wage index increase for low wage index hospitals 
by applying a budget neutrality adjustment factor to the standardized 
amount rather than focusing the adjustment on the wage index of high 
wage index hospitals.
    A few commenters provide feedback on the other two alternatives to 
CMS' wage index disparities proposals discussed in the proposed rule, 
namely (1) mirroring CMS' approach of raising the wage index for low 
wage index hospitals by reducing the wage index values for high wage 
index hospitals by half the difference between the otherwise applicable 
final wage index value for these hospitals and the 75th percentile wage 
index value, and (2) creating a national rural wage index area and 
national rural wage index. Some commenters who indicated that they 
supported a national rural wage index area indicated that they compete 
with bordering states for labor, or that a national rural wage index 
area would result in a higher wage index for many hospitals in their 
state. There was little support for the other alternative considered 
regarding reducing the wage index values for high wage index hospitals 
by half the difference between the otherwise applicable final wage 
index value for these hospitals and the 75th percentile wage index 
value due to the substantial redistributive effects of this 
alternative.
    Response: In section III.N.2.b. of the preamble of this final rule, 
we address comments regarding the first alternative considered to 
budget neutralize the wage index increase for low wage index hospitals 
by applying a budget neutrality adjustment factor to the standardized 
amount rather than focusing the adjustment on the wage index of high 
wage index hospitals. For the reasons discussed in section III.N.2.b. 
of the preamble to this final rule, we are adopting this alternative 
considered in this final rule.
    We appreciate the comments supporting the creation of a national 
rural wage index area and national rural

[[Page 42339]]

wage index, but as we do not have evidence a national rural labor 
market exists or would be created if we were to adopt this alternative, 
this alternative would not increase the accuracy of the wage index. 
With respect to the comments we received on the alternative of reducing 
the wage index values for high wage index hospitals by half the 
difference between the otherwise applicable final wage index value for 
these hospitals and the 75th percentile wage index value, we believe 
the commenters' concerns regarding this alternative merit further 
consideration.

IV. Other Decisions and Changes to the IPPS for Operating System

A. 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. Changes for FY 2020
    As discussed in section II.F. of the preamble of the FY 2020 IPPS/
LTCH PPS proposed rule (84 FR 19399 through 19401), based on our 
analysis of FY 2018 MedPAR claims data, we proposed to make changes to 
a number of MS-DRGs, effective for FY 2020. Specifically, we proposed 
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

[[Page 42340]]

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, respectively) and revise 
the titles for MS-DRGs 693 and 694 to ``Urinary Stones with MCC'' and 
``Urinary Stones without MCC'', respectively.
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19400), 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 stated in the proposed rule that 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. We noted that MS-DRGs 216, 217, 218, 219, 220, 
and 221 are currently subject to the postacute care transfer policy. We 
stated that 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. In 
addition, we noted that 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. We stated 
that 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. We noted that 
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 proposed 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, as discussed in section II.F. of the preamble of this 
final rule, we are finalizing these proposed changes to the MS-DRGs.
    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 a chart for the proposed rule (84 FR 
19400) which set forth the analysis of the postacute care transfer 
policy criteria completed for the proposed rule with respect to each of 
these proposed new or revised MS-DRGs. We stated that, for the FY 2020 
final rule, we intended to update this analysis using the most recent 
available data at that time. The following chart reflects our updated 
analysis for the finalized new and revised MS-DRGs using the postacute 
care transfer policy criteria and the March 2019 update of the FY 2018 
MedPAR file.

[[Page 42341]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.158


[[Page 42342]]


    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 the 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 proposed to remove MS-DRGs 273 and 274 
from the list of MS-DRGs subject to the postacute care transfer policy, 
we also proposed to remove these MS-DRGs from the list of MS-DRGs 
subject to the MS-DRG special payment methodology, effective FY 2020 
(84 FR 19400).
    In the proposed rule, we indicated that, for the FY 2020 final 
rule, we intended to update this analysis using the most recent 
available data at that time. The following chart reflects our updated 
analysis for the finalized new and revised MS-DRGs using our criteria 
and the March 2019 update of the FY 2018 MedPAR file.
[GRAPHIC] [TIFF OMITTED] TR16AU19.159

    Comment: A commenter stated that CMS has applied the postacute care 
transfer policy criteria consistently with the regulation and agreeing 
with the assignment of post-acute care transfer policy and special 
payment policy status for the proposed new or revised MS-DRGs under the 
proposed rule.
    Response: We appreciate the commenter's support.
    After consideration of the public comments we received, and review 
of updated MedPAR data, we are finalizing the proposal to remove MS-
DRGs 273 and 274 from the list of MS-DRGs that are subject to the 
postacute care transfer policy and the special payment policy.
    The postacute care transfer and special payment policy status of 
these MS-DRGs is reflected in Table 5 associated with this final rule, 
which is listed in section VI. of the Addendum to this final rule and 
available via the internet on the CMS website.

B. Changes in the Inpatient Hospital Update for FY 2020 (Sec.  
412.64(d))

1. 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 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;
     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
     An adjustment based on changes in economy-wide 
productivity (the

[[Page 42343]]

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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19401), we 
proposed 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 was estimated to be 3.2 percent. We also proposed 
that if more recent data subsequently became 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.
    Based on the most recent data available for this FY 2020 IPPS/LTCH 
PPS final rule (that is, IGI's second quarter 2019 forecast of the 
2014-based IPPS market basket rate-of-increase with historical data 
through the first quarter of 2019), we estimate that the FY 2020 market 
basket update used to determine the applicable percentage increase for 
the IPPS is 3.0 percent.
    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.
    Based on the most recent data available as previously described, we 
determined final applicable percentage increases to the standardized 
amount for FY 2020, 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 
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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19402), for FY 
2020, we proposed an MFP adjustment of 0.5 percentage point. Similar to 
the market basket update, for the 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 proposed that if more 
recent data subsequently became 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 the most recent data available for this FY 2020 IPPS/LTCH 
PPS final rule (that is, IGI's second quarter 2019 forecast of the MFP 
adjustment), the current estimate of the MFP adjustment for FY 2020 is 
0.4 percentage point.
    We did not receive any public comments on our proposal to use the 
most recent available data to determine the final market basket update 
and the MFP adjustment. Therefore, for this final rule, we are 
finalizing a market basket update of 3.0 percent and an MFP adjustment 
of 0.4 percentage point for FY 2020 based on the most recent available 
data.
    Based on these most recent data available, for this final rule, we 
have determined four applicable percentage increases to the 
standardized amount for FY 2020, as specified in the following table:

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[GRAPHIC] [TIFF OMITTED] TR16AU19.160

    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19402), we 
proposed 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 proposed 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 previously 
noted, section 1886(b)(3)(B)(xii) of the Act required an additional 
reduction each year only for FYs 2010 through 2019.)
    We did not receive any public comments on our proposal and 
therefore, we are finalizing our proposed changes to Sec.  412.64(d) as 
proposed.
    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).)
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19402), for FY 
2020, we proposed 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 the FY 2020 IPPS/LTCH PPS proposed rule, 
we used IGI's fourth quarter 2018 forecast of the 2014-based IPPS 
market basket update with historical data through third quarter 2018. 
Similarly, we used IGI's fourth quarter 2018 forecast of the MFP 
adjustment. We proposed that if more recent data subsequently became 
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.
    We did not receive any public comments on our proposal. Therefore 
are finalizing the proposal to determine the update to the hospital-
specific rates for SCHs and MDHs in this final rule using the most 
recent available data.
    For this final rule, based on the most recent available data, we 
are finalizing the following updates to the hospital specific rates 
applicable to SCHs and MDHs: An update of 2.6 percent for a hospital 
that submits quality data and is a meaningful EHR user; an update of 
1.85 percent for a hospital that fails to submit quality data and is a 
meaningful EHR user; an update of 0.35 percent for a hospital that 
submits quality data and is not a meaningful EHR user; and an update of 
-0.4 percent for a hospital that fails to submit quality data and is 
not a meaningful EHR user.
2. 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 final rule. 
Accordingly, in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19402 
through 19403), for FY 2020, we proposed an applicable percentage 
increase of 2.7 percent to the standardized amount for hospitals 
located in Puerto Rico.
    We did not receive any public comments on our proposal.
    Based on the most recent data available for this final rule (as 
discussed previously in section IV.B.1. of the preamble of this final 
rule), we are finalizing an applicable percentage increase of 2.6 
percent to the

[[Page 42345]]

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) 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 national median CMI 
value for FY 2020 is based on the CMI values of all urban hospitals 
nationwide, and the 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 values are based on discharges 
occurring during FY 2018 (October 1, 2017 through September 30, 2018), 
and include bills posted to CMS' records through March 2019.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19403), we 
proposed 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 were set forth in a table 
in the proposed rule (84 FR 19403). We stated in the proposed rule that 
we intended 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.
    We did not receive any public comments on our proposals. Based on 
the latest available data (FY 2018 bills received through March 2019), 
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:
     1.68645 (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 final CMI values by region are set forth in the following 
table.

[[Page 42346]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.161

    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 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. In the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19404), for FY 2020, we proposed 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 were the latest cost report data 
available at the time the proposed rule was developed. Therefore, we 
proposed 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. (We 
refer readers to the table set forth in the FY 2020 IPPS/LTCH PPS 
proposed rule at 84 FR 19404.) In the proposed rule, we stated we 
intended to update these numbers in the FY 2020 final rule based on the 
latest available cost report data.
    We did not receive any public comments on our proposals.
    Based on the latest discharge data available at this time, that is, 
for cost reporting periods that began during FY 2017, the final median 
number of discharges for urban hospitals by census region are set forth 
in the following table.
[GRAPHIC] [TIFF OMITTED] TR16AU19.162

    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 final 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. Payment Adjustment for Low-Volume Hospitals (Sec.  412.101)

1. Background

[[Page 42347]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.162

    >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 final 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. 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).) In section IV.D.2. of the 
preamble of this final rule, we discuss the low-volume hospital payment 
adjustment policies for FY 2020.
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).
    Comment: Commenters expressed continued support of the low-volume 
hospital adjustment changes included in the Bipartisan Budget Act of 
2018.

[[Page 42348]]

    Response: While these changes are statutory, we appreciate 
commenters' support.
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, in the FY 2020 
IPPS/LTCH PPS proposed rule (84 FR 19405), for FY 2020, we proposed 
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 proposed 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 noted in the proposed rule that this proposal was 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 noted in the 
proposed rule 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,

[[Page 42349]]

and in accordance with the timeline described earlier.
    Comment: A commenter suggested we alter our previously established 
process for requesting and obtaining the low-volume hospital payment 
adjustment for providers who have previously qualified for the low-
volume hospital payment adjustment with the process used for sole 
community hospitals whereby hospitals would be required to notify the 
MAC within 30 days of any changes as opposed to a yearly verification 
statement.
    Response: We appreciate the comment and will consider this 
suggestion for future rulemaking.
    After consideration of the public comments we received, we are 
finalizing our proposals relating to the process for requesting and 
obtaining the low-volume hospital payment adjustment as previously 
described, without modification.
4. 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19406), we 
proposed 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 proposed 
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 FY 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 42600). We noted 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. We stated that 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.
    We did not receive any public comments on our proposal. Therefore, 
we are finalizing, without modification, our proposed conforming 
changes to paragraph (e) of Sec.  412.101 as previously discussed.

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.
    Comment: A commenter stated they agreed with and supported the 
proposal regarding the IME adjustment factor.
    Response: We appreciate the commenter's support. As previously 
noted, the IME adjustment factor is statutory. Accordingly, for 
discharges occurring during FY 2020, the IME formula multiplier is 
1.35.

F. 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

[[Page 42350]]

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 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

[[Page 42351]]

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 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19408), we discussed 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,

[[Page 42352]]

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 the proposed rule, there were 29 hospitals 
participating in the demonstration program. At the time of development 
of this final rule, there are 28 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.
    We received a comment in response to the discussion in the proposed 
rule 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).
    Comment: A commenter stated that CMS had wrongly calculated its 
disproportionate patient percentage due to a ``slight shift in the SSI 
percent and a delay in the pending Medicaid approvals,'' which 
contributed to the determination of DSH eligible ``NO'' in Table 18 
from the FY 2020 IPPS/LTCH proposed rule. The commenter urged CMS to 
consider its history of meeting the DSH threshold and reverse the 
``NO'' to a ``YES'' for FY 2020 DSH payments, further noting that the 
DSH payment calculation for FY 2020 combines Medicaid utilization and 
an SSI percent from 2 years prior. The commenter noted that its amended 
Medicare cost report shows an increased disproportionate patient 
percentage ratio.
    Response: In response to the comment concerning the hospital's 
projection of DSH eligibility, we note that regulations located at 42 
CFR 412.106 govern the Medicare DSH payment adjustment and specify how 
the disproportionate patient percentage is calculated. Further, a 
hospital's eligibility to receive empirically justified DSH payments, 
can change throughout the year as the MACs receive and review updated 
data. Consistent with historical policy, an estimate of DSH eligibility 
is used to determine eligibility to receive interim uncompensated care 
payments prior to the start of the fiscal year based on each hospital's 
estimated DSH status for the applicable fiscal year (using the most 
recent data that are available at the time of the development of the 
proposed and final rules). The 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.
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
a. 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 the FY 2020 IPPS/LTCH PPS proposed rule, 
in order to determine Factor 1 in the uncompensated care payment 
formula for FY 2020, we proposed 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

[[Page 42353]]

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 the 
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 our proposal for Factor 1 and modeling 
the impact of the 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 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 the proposed rule, using the data sources that were previously 
discussed, 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, was 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, was 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 the proposed rule, we proposed 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).
    Comment: A few commenters discussed our proposals regarding Factor 
1 in their FY 2020 IPPS/LTCH PPS public comment submissions. A common 
theme, carrying over from comments in previous years, was the request 
for greater transparency in the methodology used by CMS and the OACT. 
This request was made with respect to the calculation of estimated 
Medicare DSH payments for purposes of determining Factor 1, and in 
particular the ``Other'' factor that is used to estimate Medicare DSH 
expenditures. Some commenters believed that the lack of opportunity 
afforded to hospitals to review the data used to develop our estimate 
is in violation of the Administrative Procedure Act.
    Some commenters requested that CMS use the traditional payment 
reconciliation process to calculate final Medicare uncompensated care 
payments. A commenter asserted that reconciliation of Factor 1 and 
Factor 3 was necessary as a result of underestimates of Factor 1 in FY 
2017 and FY 2018, resulting in underpayment of uncompensated care 
payments for those years. The commenter asserted that the section 
1886(r)(2) of the Act allows for the Factors 1, 2, and 3 to be based on 
actual data for the specific fiscal year. The commenter stated using 
actual data from the specific fiscal year in which those costs are 
incurred, would result in more accurate estimates of these factors, 
instead of projections from prior-period figures.
    Some commenters expressed concern about whether underreporting of 
Medicaid coverage was factored into the calculation of Factor 1, as it 
was for Factor 2. However, others noted that, from the FY 2020 proposed 
rule, it can be presumed that the Medicaid population decreased because 
the ``Other'' adjustment is less than 1.0. However, these commenters 
urged CMS to provide a detailed explanation, including calculations, of 
the assumptions used to make these projections.
    A commenter noted that the adjustments made by CMS include an 
adjustment to account for the estimated effects of Medicaid expansion, 
but do not include the impact of including days for individuals who are 
entitled to benefits under Part A but received Medicare benefits 
through enrollment in a Medicare Advantage plan under Part C (Part C 
days) in the Part A/SSI fraction, thus leaving Factor 1 substantially 
understated. This commenter referenced the recent Supreme Court 
decision in which the Court held that the question of how to count Part 
C enrollees had to be addressed through notice and comment rulemaking. 
The commenter asserted that the inclusion of these Part C days in the 
Part A/SSI fraction could materially impact the DSH reimbursement used 
for Factor 1 by nearly 10 percent. The commenter suggested that CMS 
should estimate and adjust for the impact of removing Part C days from 
the Part A/SSI fraction. Similarly, another commenter asserted that, 
since FY 2014, hospitals have been deprived of DSH funding because of 
what the commenter perceives to be underestimates of Factor 1.
    Response: We thank the commenters for their input. Regarding the 
comments referencing the Administrative Procedure Act, we note that 
under the Administrative Procedure Act, a proposed rule is required to 
include either the terms or substance of the proposed rule or a 
description of the subjects and issues involved. In this case, the FY 
2020 IPPS/LTCH PPS proposed rule did include a detailed discussion of 
our proposed Factor 1 methodology and the data sources that would be 
used in making our estimate. Furthermore, we have been, and continue to 
be, transparent with respect

[[Page 42354]]

to the methodology and data used to estimate Factor 1 and we disagree 
with commenters who assert otherwise. To provide context, we first note 
that Factor 1 is not estimated in isolation from other OACT 
projections. 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. For 
additional information on the specific economic assumptions used in the 
Midsession Review of the President's FY 2020 Budget, we refer readers 
to the ``Midsession Review of the President's FY 2020 Budget'' 
available on 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 and the Midsession Review of 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 budget.
    For a general overview of the principal steps involved in 
projecting future inpatient costs and utilization, we refer readers to 
the ``2019 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/ReportsTrustFunds/index.html 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 the public to the Actuarial Report on the Financial 
Outlook for Medicaid for a discussion of general issues regarding 
Medicaid projections.
    Second, as described in more detail later in this section, in the 
FY 2020 IPPS/LTCH PPS proposed rule, we included information regarding 
the data sources, methods, and assumptions employed by the actuaries in 
determining the OACT's estimate of Factor 1. In summary, we indicated 
the historical HCRIS data update OACT used to identify Medicare DSH 
payments, explained that the most recent Medicare DSH payment 
adjustments provided in the IPPS Impact File were used, and provided 
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 included a description of the ``Other'' and 
``Discharges'' assumptions, and also provided additional information 
regarding how we address the Medicaid and CHIP expansion.
    In response to the commenters' assertion that Medicaid expansion is 
not adequately accounted for in the ``Other'' column, we note that the 
discussion in the proposed rule made clear that, based on data from the 
Midsession Review of 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. Taken as a whole, this description of our proposed 
methodology for estimating Factor 1 and the data sources used in making 
this estimate was entirely consistent with the requirements of the 
Administrative Procedure Act, and gave stakeholders adequate notice of, 
and a meaningful opportunity to comment on, the proposed estimate of 
Factor 1.
    Regarding the commenters' assertion that, similar to the adjustment 
for Medicaid underreporting on survey data in the estimation of Factor 
2, we should also account for this underreporting in our estimate of 
Factor 1, we note that the Factor 1 calculation uses Medicaid 
enrollment data and estimates and does not require the adjustment 
because it does not use survey data.
    Regarding commenters' assertion that Factor 1 would be higher if 
Part C days were treated different, and their suggestion that CMS 
should estimate and adjust for the impact of removing Part C days from 
the Medicare/SSI fraction, we note that in the FY 2014 IPPS/LTCH PPS 
final rule (78 FR 50614 through 50620), we readopted the policy of 
counting Medicare Advantage days in the SSI ratio for FY 2014 and all 
subsequent fiscal years (79 FR 50012). Accordingly, the rulemaking 
required by Azar v. Allina Health Services was completed for FY 2014 
and all subsequent fiscal years in the FY 2014 IPPS/LTCH final rule. 
Thus, consistent with the policy adopted in that final rule, our 
estimate of Factor 1 for FY 2020 appropriately accounts for Medicare 
Advantage days by including them in the SSI ratio.
    Lastly, regarding the commenters' perception that Factor 1 has been 
underestimated and their suggestion that CMS consider reconciling the 
estimates of Factors 1, 2, and 3, we continue to believe that applying 
our best estimates prospectively is most conducive to administrative 
efficiency, finality, and predictability in payments (78 FR 50628; 79 
FR 50010; 80 FR 49518; 81 FR 56949; and 82 FR 38195). We believe that, 
in affording the Secretary the discretion to estimate the three factors 
used to determine uncompensated care payments and by including a 
prohibition against administrative and judicial review of those 
estimates in section 1886(r)(3) of the Act, Congress recognized the 
importance of finality and predictability under a prospective payment 
system. As a result, we do not agree with the commenters' suggestion 
that we should establish a process for reconciling our estimates of the 
three factors, which would be contrary to the notion of prospectivity. 
We also address comments specifically requesting that we establish 
procedures for reconciling Factor 3 later in this section, as part of 
the discussion of the comments received on the proposed methodology for 
Factor 3.
    After consideration of the public comments we received, we are 
finalizing, as proposed, the methodology for calculating Factor 1 for 
FY 2020. We discuss the resulting Factor 1 amount for FY 2020 in this 
final rule. For this final rule, the OACT used the most recently 
submitted Medicare cost report data from the March 2019 update of HCRIS 
to identify Medicare DSH payments and the most recent Medicare DSH 
payment adjustments provided in the Impact File published in 
conjunction with the

[[Page 42355]]

publication of the FY 2019 IPPS/LTCH PPS final rule and applied update 
factors and assumptions for future changes in utilization and case-mix 
to estimate Medicare DSH payments for the upcoming fiscal year. The 
June 2019 OACT estimate for Medicare DSH payments for FY 2020, without 
regard to the application of section 1886(r)(1) of the Act, was 
approximately $16.583 billion. This estimate excluded Maryland 
hospitals participating in the Maryland All-Payer Model, hospitals 
participating in the Rural Community Hospital Demonstration, and SCHs 
paid under their hospital-specific payment rate. Therefore, based on 
the June 2019 estimate, the estimate of empirically justified Medicare 
DSH payments for FY 2020, with the application of section 1886(r)(1) of 
the Act, was approximately $4.146 billion (or 25 percent of the total 
amount of estimated Medicare DSH payments for FY 2020). Under Sec.  
412.106(g)(1)(i) of the regulations, Factor 1 is the difference between 
these two estimates of the OACT. Therefore, in this final rule, Factor 
1 for FY 2020 is $12,437,591,742.69, which is equal to 75 percent of 
the total amount of estimated Medicare DSH payments for FY 2020 
($16,583,455,656.92 minus $4,145,863,914.23).
    The Office of the Actuary's final estimates for FY 2020 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:
[GRAPHIC] [TIFF OMITTED] TR16AU19.163

    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 and FY 2018 are based on Medicare claims data 
that have been adjusted by a completion factor. The discharge figure 
for FY 2019 is based on preliminary data for 2019. The discharge figure 
for FY 2020 is an assumption 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 increase is based on preliminary data. 
The FY 2020 increase is an estimate 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 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.
    This table shows the factors that are included in the ``Update'' 
column of the previous table:

[[Page 42356]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.164

b. Calculation of 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: (1) The extent to which the source accounted 
for the full U.S. population; (2) 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; (3) the 
extent to which the source utilized data from the Census Bureau; (4) 
the timeliness of the estimates; (5) the continuity of the estimates 
over time; (6) the accuracy of the estimates; and (7) 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. In the FY 2020 IPPS/LTCH 
PPS proposed rule, we proposed 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 integral to the well-established NHEA methodology. 
In the FY 2020 IPPS/LTCH PPS proposed rule, we described 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

[[Page 42357]]

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/NationalHealthExpendData/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) Factor 2 for FY 2020
    Using these data sources and the methodologies as previously 
described, the OACT has estimated 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 9.4 percent, respectively.\316\ As required by 
section 1886(r)(2)(B)(ii) of the Act, the Chief Actuary of CMS has 
certified these estimates.
---------------------------------------------------------------------------

    \316\ Certification of Rates of Uninsured. March 28, 2019. 
Available at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInPatientPPS/dsh.html.
---------------------------------------------------------------------------

    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 proposed 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 was 
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.

[[Page 42358]]

     Percent of individuals without insurance for FY 2020 (0.25 
times 0.094) + (0.75 times 0.094): 9.4 percent.
    1-[verbar]((0.094-0.14)/0.14)[verbar] = 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 proposed that Factor 2 for FY 2020 would be 67.14 
percent.
    The proposed FY 2020 uncompensated care amount was 
$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 invited public comments on our proposed methodology for 
calculating Factor 2 for FY 2020.
    Comment: A few commenters asserted that CMS did not adequately 
explain how the OACT derived the estimates that were used in 
calculating Factor 2. According to commenters, the coverage level and 
underlying assumptions used by the agency resulted in the 
underestimation of Factor 2, which in turn diminished uncompensated 
care payments for hospitals. Commenters also expressed concerns 
generally about the amount of money available to make uncompensated 
payments and noted that the amount of money available for overall 
Medicare DSH payments, including both empirically justified DSH 
payments and uncompensated care payments, drastically changed under the 
new methodology established in the Affordable Care Act. They pointed 
out that as the number of uninsured people in the country increases, it 
is imperative that hospitals receive adequate Medicare DSH payments to 
cover the costs of increasing numbers of underinsured and uninsured 
patients. A commenter requested that CMS either revise Factor 2 to 
account for the estimated reduction in Medicaid enrollment as suggested 
by the 0.9932 ``Other'' adjustment in determining Factor 1 or explain 
why such a revision is unnecessary.
    Response: We have been and continue to be transparent with respect 
to the methodology and data used to estimate Factor 2, and we disagree 
with commenters who assert otherwise. The FY 2020 IPPS/LTCH PPS 
proposed rule included a detailed discussion of our proposed Factor 2 
methodology and the data sources that would be used in making our 
estimate. Section 1886(r)(2)(B)(ii) of the Act permits us to use a data 
source other than CBO estimates to determine the percent change in the 
rate of uninsurance beginning in FY 2018. As we explained in the 
proposed rule, we believe that the NHEA data, on balance, best meets 
all of our considerations, including the statutory requirement that the 
estimate be based on data from the Census Bureau or other sources the 
Secretary determines appropriate, and will allow reasonable estimates 
of the rate of uninsurance to be available in conjunction with the IPPS 
rulemaking cycle.
    In response to the commenter that requested that CMS either revise 
Factor 2 to account for the estimated reduction in Medicaid enrollment 
as suggested by the 0.9932 ``Other'' adjustment in determining Factor 1 
or explain why such a revision is unnecessary, we note that the 
``Other'' adjustment relates to a number of factors, and does not 
represent only the effects of Medicaid expansion under the Affordable 
Care Act. As discussed in the proposed rule, the ``Other'' column shows 
the increase or decrease in certain other factors that also contribute 
to the estimate of Medicare DSH payments. These factors include the 
difference between total inpatient hospital discharges and IPPS 
discharges (particularly those in DSH hospitals) and various 
adjustments to the payment rates that have been included over the years 
but are not picked up in the other columns (such as the increase in 
rates for the two midnight policy). We note that the ``Other'' factor 
used in determining Factor 1 in this FY 2020 final rule is 1.0012.
    After consideration of the public comments we received, we are 
finalizing the calculation of Factor 2 for FY 2020 as proposed. The 
estimates of the percent of uninsured individuals have been certified 
by the Chief Actuary of CMS, as discussed in the proposed rule. The 
calculation of the final Factor 2 for FY 2020 using a weighted average 
of 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).
     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).
    Therefore, the final Factor 2 for FY 2020 is 67.14 percent.
    The final FY 2020 uncompensated care amount is $12,437,591,742.69 x 
0.6714 = $8,350,599,096.04.
    FY 2020 Uncompensated Care Amount: $8,350,599,096.04.
c. Calculation of 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

[[Page 42359]]

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 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

[[Page 42360]]

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 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

[[Page 42361]]

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 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 the 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).
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38213 through 
38214), to address the issue of both long and short cost reporting 
periods, we finalized a policy of annualizing cost reports that do not 
have 12 months of data. As stated in the FY 2018 IPPS/LTCH PPS final 
rule, if the time between the start date of a hospital's cost reporting 
year and the end date of its cost reporting year is less than 12 
months, we annualize the data so that the hospital has 12 months of 
data included in its Factor 3 calculation. Conversely, if the time 
between the aforementioned start date and the end date is greater than 
12 months, we annualize the Medicaid days to achieve 12 months of 
Medicaid day's data. Under the policy adopted in the FY 2018 IPPS/LTCH 
PPS final rule, if a hospital filed more than one cost report beginning 
in the same fiscal year, we would first combine the data across the 
multiple cost reports before determining the difference between the 
start date and the end date to see if annualization is needed.
    To address the effects of averaging Factor 3s calculated for three 
separate fiscal years, in the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38214 through 38215), we finalized a policy under which we apply a 
scaling factor to the Factor 3 values of all DSH eligible hospitals so 
that total uncompensated care payments will be consistent with the 
estimated amount available to make uncompensated care payments for the 
fiscal year. Specifically, we adopted a policy under which we divide 1 
(the expected sum of all eligible hospitals' Factor 3 values) by the 
actual sum of all eligible hospitals' Factor 3 values and multiply the 
quotient by each hospital's total uncompensated care payment to obtain 
scaled uncompensated care payment amounts whose sum is consistent with 
the estimate of the total amount available to make uncompensated care 
payments.
    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

[[Page 42362]]

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 nonreimbursable 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 
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

[[Page 42363]]

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 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 previously discussed 
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

[[Page 42364]]

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 previously discussed 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) Methodology for Calculating Factor 3 for FY 2020
(a) Use of Audited FY 2015 Data
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19418 through 19419), 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 the 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 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, in the 
FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19419), we stated that we 
believe, on balance, that 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, we also considered 
using the FY 2017 data. In the proposed rule, we sought public comments 
on this alternative and stated that, based on the public comments we 
received, we could adopt this alternative in the FY 2020 final rule.
    In the FY 2020 proposed rule, we recognized 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 stated that, for FY 2020, we believe 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. As we stated in 
the proposed rule, 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. As an example, we noted that 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, in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19419), we proposed 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 
also noted that the proposed uncompensated care payments to hospitals 
whose FY 2015 Worksheet S-10 data were audited represented 
approximately half of the proposed total uncompensated care payments 
for FY 2020. For purposes of the FY 2020 proposed rule, we used the 
most recent available HCRIS extract available, which was the HCRIS data 
updated through February 15, 2019. We stated in the proposed rule that 
we expected to use the March 2019 update of HCRIS for the final rule.
    Comment: Many commenters expressed support for CMS' proposal to 
utilize FY 2015 Worksheet S-10 data to determine each hospital's share 
of overall uncompensated care costs (UCC) in FY 2020. These commenters 
argued that data from the FY 2015 Worksheet S-10 are most appropriate 
for calculating Factor 3 because the data have been at least partially 
audited, and the audits result in data that are appropriate for use in 
determining

[[Page 42365]]

uncompensated care payments. These commenters reiterated the discussion 
in the proposed rule, in which we explained that the audited hospitals 
were projected to receive approximately 50 percent of the total amount 
of the uncompensated care payments, and that CMS has afforded hospitals 
several opportunities to revise and resubmit FY 2015 Worksheet S-10 
data to make it more accurate. To this end, a commenter indicated that 
uncompensated care costs calculated from the FY 2015 cost reports for 
DSH-eligible hospitals had declined nearly 18 percent between last year 
and this year as a result of amended data reported on the Worksheet S-
10. These commenters believe that the corrective actions resulting from 
the FY 2015 Worksheet S-10 data audits outweigh the improved cost 
reporting instructions for the FY 2017 Worksheet S-10.
    Conversely, many commenters opposed the proposed policy of using 1 
year of FY 2015 Worksheet S-10 data to determine UCC. These commenters 
asserted that the instructions for completing the FY 2015 Worksheet S-
10 were unclear and confusing, resulting in incomplete and inaccurate 
uncompensated care data. They believe that since the audited hospitals 
represent only half of the proposed total uncompensated care payments 
for FY 2020, the remaining half is highly susceptible to errors, due to 
the concerns with the instructions for the FY 2015 Worksheet S-10. In 
addition, many commenters voiced concerns with the auditing of the FY 
2015 Worksheet S-10 data and opposed its use as a result of these 
concerns. Some commenters asserted that as a result of selective and 
inconsistent audits the FY 2015 Worksheet S-10 data may not be reliable 
for some providers. Additionally, some commenters stated that the 
mixing of data from audited and unaudited hospitals results in an 
uneven playing field, harming those hospitals that were audited to the 
benefit of those that were not. Finally, some commenters believed that 
the FY 2015 Worksheet S-10 data have already been used for FY 2019 
uncompensated care payments and that more updated information needs to 
be used for FY 2020. These commenters also stated that continuing to 
use FY 2015 Worksheet S-10 data as the source of UCC creates a 
substantial lag in compensating hospitals for charity care that was 
provided in prior years.
    Response: We thank commenters for their support of our proposal to 
use the FY 2015 Worksheet S-10 data to determine each hospital's share 
of UCC in FY 2020. We also appreciate the input from commenters who 
disagreed with the proposal. 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 proposed 
uncompensated care payments to hospitals whose FY 2015 Worksheet S-10 
data were audited represent approximately half of the total proposed 
uncompensated care payments for FY 2020, 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. In response to the comment that the 
FY 2015 Worksheet S-10 data are outdated, we note that at the time we 
began auditing the FY 2015 Worksheet S-10 data in the Fall of 2018, the 
FY 2017 Worksheet S-10 data were incomplete as some hospitals were 
still submitting their cost reports. We chose to focus the audit on the 
FY 2015 cost reports primarily because this was the most 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 prior to the FY 2019 rulemaking. We acknowledge that FY 
2015 Worksheet S-10 data has not been audited for all hospitals . To 
the extent commenters believe that all hospitals' Worksheet S-10 data 
must be audited for there to be ``level playing field'' and for the 
data to be appropriate to use for FY 2020, we do not agree. We note 
that it was not feasible to audit all hospitals' FY 2015 report data 
for the FY 2020 rulemaking. The selection of hospitals for the FY 2015 
Worksheet S-10 audits was based on a risk-based assessment process, 
which we believe was effective and appropriate. Regarding the 
commenter's assertion that the FY 2015 Worksheet S-10 data became 
unreliable as a result of the audit selection, process and/or 
adjustments, we refer readers to the discussion below. With respect to 
the commenters' concerns with Worksheet S-10 instructions for the FY 
2015 cost reporting period, we refer readers to the discussion of these 
instructions in the later section on methodological considerations, 
where we address the comments related to the Worksheet S-10 
instructions. We note that we will consider further commenters' 
concerns regarding data lag in future rulemaking in the determination 
of the best available data to calculate Factor 3 for future years.
    Comment: A great number of commenters, whether in support of or in 
opposition to the proposed policy and the alternative considered, 
stated that as CMS moves from using a 3-year average to a single year 
of Worksheet S-10 data, the potential for anomalies and undue 
fluctuations in uncompensated care payments increases. Commenters 
stated that bad debt and charity write-offs can vary significantly from 
year to year for a given hospital, even if data are clean and accurate, 
and can cause large variations in uncompensated care payments. Several 
of these commenters questioned whether the proposal to move to a single 
year of the Worksheet S-10 data is a permanent decision by CMS, and 
many commenters recommended that CMS continue using a 3-year average to 
mitigate year-over-year volatility in uncompensated care payments, 
either now or in the future when additional years of audited Worksheet 
S-10 data become available. Some commenters remarked that the proposed 
CMS policy of relying on data from a single year increases the 
possibility of aberrant data from any 1 year or any one provider 
skewing the distribution of uncompensated care payments. They stated 
that a 3-year average could offer a stop-gap approach by providing a 
transition to a major change in the distribution of uncompensated care 
payments. A number of commenters requested that, if CMS does move to 
using 1 year of Worksheet S-10 data to calculate Factor 3, it also 
implement a stop-loss policy to protect hospitals that have a decrease 
of 5 to 10 percent in uncompensated care payments for any given year. 
Additionally, some commenters stated that there is variability in the 
amount of the per-discharge uncompensated care payment among hospitals, 
with the amount of the uncompensated care payment being higher than all 
other inpatient payments combined for some hospitals. These commenters 
recommended placing a limit on per-discharge uncompensated care 
payments, regardless of a hospital's Factor 3.
    At the same time, other commenters stated that mixing audited and 
unaudited data is counterintuitive and would result in a poorly 
constructed 3-year average, in which the audited data would be diluted. 
Thus, many commenters believe that CMS should ultimately strive to 
average three years of audited data to determine hospitals' UCC. In 
contrast, other commenters supported the use of 1 year of data rather 
than a 3-year average. A commenter stated that if a provider has UCC 
that are rapidly changing, a 3-year average makes for a slow response. 
Additionally, the commenter believed that using a 3-year average hurts 
the

[[Page 42366]]

newest of providers that don't have a full complement of data to 
report.
    Response: We appreciate the commenters' support for our proposal to 
use 1 year of Worksheet S-10 data, as well as the requests from some 
commenters that we continue to use a 3-year average in the calculation 
of Factor 3 for FY 2020. Our primary reason for using a 3-year average 
in the past was to provide assurance that hospitals' uncompensated care 
payments would remain reasonably stable and predictable, and less 
subject to unpredictable swings and anomalies in a hospital's low-
income insured days or reported uncompensated care costs between 
reporting periods. However, as we stated in the FY 2020 IPPS/LTCH PPS 
proposed rule (84 FR 19419), 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, FY 2016, and/or FY 2017 data, we 
potentially would be diluting the effect of our considerable auditing 
efforts and introducing unnecessary variability into the calculation if 
we were to continue to use three years of data to calculate Factor 3. 
Still, given concerns raised by commenters regarding our proposal to 
use 1 year of data from the FY 2015 Worksheet S-10 to calculate Factor 
3 for FY 2020, CMS may consider returning to the use of a 3-year 
average in rulemaking for future years, if appropriate.
    Regarding commenters' recommendation that we adopt a stop-loss 
policy, we note that section 1886(r) does not provide CMS with 
authority to implement a stop-loss policy. Rather, section 
1886(r)(2)(C) requires that we determine Factor 3 for each hospital 
based upon the ratio of the amount of uncompensated care furnished by 
the hospital compared to the uncompensated care furnished by all DSH-
eligible hospitals, and there is no authority under section 1886(r) to 
adjust this amount. In the absence of such authority, we believe that 
the use of three years of data to determine Factor 3 for FYs 2018 and 
2019, as discussed in the FY 2018 and FY 2019 IPPS/LTCH PPS final 
rules, provided a mechanism that had the effect of smoothing the 
transition from the use of low-income insured days to the use of 
Worksheet S-10 data. However, as we explained in the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19419), for FY 2020, we believe 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. When more years 
of audited data are available, we may consider returning to the use an 
average of more than 1 year (for example, a 3-year average), in 
rulemaking for future years. Regarding the comments recommending that 
CMS place a cap on the amount of per-discharge uncompensated care 
payments, we may consider the issue of per-discharge uncompensated care 
payments in future rulemaking including whether modifying the amount of 
interim uncompensated care payments would be administratively feasible 
in specific situations.
    Comment: Many commenters proposed alternative ways to blend prior 
years' data for purposes of incorporating Worksheet S-10 data into the 
calculation of Factor 3. These alternative methodologies included 
suggestions to use data from the FY 2014, FY 2015, FY 2016, and FY 2017 
Worksheet S-10 averaged together in various 3-year combinations, as 
well as suggestions to use later years when available. In addition to 
these suggestions, there were also commenters who supported the use of 
the FY 2015 Worksheet S-10 data, or the FY 2017 Worksheet S-10 data, 
but only in the context of an approach that also involved sources of 
data other than the Worksheet S-10. For example, some commenters 
recommended that CMS implement a blend utilizing low-income insured 
days, FY 2014 Worksheet S-10 data, and audited FY 2015 Worksheet S-10 
data to calculate uncompensated care payments in FY 2020. A number of 
commenters suggested using a blend consisting of two-thirds of the 
uncompensated care payments hospitals received in FY 2019 and one third 
of hospitals' share of UCC based on the FY 2017 Worksheet S-10 data. 
Similarly, other commenters suggested using a blend of one-third low-
income days and two-thirds UCC, including but not limited to using 
updated SSI days or FY 2019 Factor 3 shares, to calculate Factor 3 for 
FY 2020, in order to reduce payment variability. Some commenters 
believed a SSI day based proxy would produce a better estimate of 
uncompensated care costs Although these alternative methodologies were 
not proposed by CMS, commenters believe that CMS would have the 
authority to adopt one of the blends proposed by commenters as a 
logical outgrowth of the policies discussed in the proposed rule. Some 
commenters believed that ultimately, CMS should develop a review 
process similar to the one used to determine the hospital wage index, 
under which by FY 2023, CMS would utilize fully audited Worksheet S-10 
data from FY 2017, FY 2018, and FY 2019 to determine Factor 3.
    Response: We appreciate the comments regarding alternative ways to 
blend prior years' data for purposes of incorporating Worksheet S-10 
data into the calculation of Factor 3 and the suggestions for 
alternative methods for computing proxies for uncompensated care costs. 
However, as we stated in the FY 2020 IPPS/LTCH PPS proposed rule, we 
can no longer conclude that alternative data to the Worksheet S-10 are 
available that are a better proxy for the costs of subsection (d) 
hospitals for treating individuals who are uninsured. As stated 
previously, we also believe that the FY 2015 Worksheet S-10 data are 
the best available data to use for calculating Factor 3 for FY 2020. As 
we continue to audit additional years of the Worksheet S-10 data and 
monitor the stability of uncompensated care payments, we may consider 
the use of multiple years of audited Worksheet S-10 data in rulemaking 
for future years. Regarding the comments recommending that CMS develop 
an audit process similar to hospital wage index reviews, we refer 
readers to the discussion below, which addresses the comments and 
suggestions on the audit process.
    Comment: The auditing process for the FY 2015 Worksheet S-10 was a 
common topic within the public comments, and many commenters raised 
concerns regarding the audit process, in general, as well as with 
specific adjustments. Some commenters believed that auditing FY 2016 
data would have been more effective than auditing FY 2015 data, because 
hospitals would have had an additional year of experience in 
understanding the reporting requirements and refining their data, 
resulting in fewer occasions for subjective audit differences. Another 
commenter expressed concern that the roughly 600 providers that were 
audited represented only approximately 25 percent of those eligible to 
receive Medicare DSH. Although some commenters acknowledged that these 
roughly 600 providers represented a large share of the total amount of 
uncompensated care payments, others observed that this sample of 
audited hospitals resulted in the proposed use of both audited and 
unaudited data for FY 2020. Some commenters believed that our proposal 
to use a mix of audited and unaudited FY 2015 data to be ``arbitrary 
and capricious'' and beyond the agency's legal authority. Other

[[Page 42367]]

commenters believe that this mixture of data was disadvantageous to 
audited hospitals, to the benefit of those not audited.
    A commenter believed that the auditing process for the FY 2015 
Worksheet S-10 data was subjective and biased against providers with 
either high uncompensated care costs or with uncompensated care costs 
that may have changed significantly for good reason. Some commenters 
asserted that the audits lacked standardization, and that there were 
inconsistencies in the review adjustments made by the MACs and/or 
subcontractors, as well as variation across MACs in documentation 
requirements. According to these commenters, MACs made inconsistent 
adjustments across audited hospitals' UCC because they did not apply 
CMS's audit guidelines in a standardized and comprehensive manner. In 
addition, some commenters stated that cost report instructions still 
need to be clarified for issues that were addressed in the guidance 
included in the Worksheet S-10 Q&A issued following the FY 2018 final 
rule and in the audit protocols, and stated that the data elements 
needed for the audits should also be spelled out, like those required 
for bad debt logs.
    Many commenters asserted that the audits of the FY 2015 Worksheet 
S-10 data were intense and rushed. Some commenters asserted that audit 
adjustments seemed inconsistent with the Worksheet S-10 instructions 
and were beyond the scope of the audit and the authority of the MACs. 
Examples of the types of concerns raised regarding the adjustments, 
include assertions that the adjustments were made under tight deadlines 
without providing hospitals the opportunity to review or appeal MAC 
decisions and that MACs made adjustments based on their own 
interpretation of language in hospitals' financial assistance policies, 
including disallowing discounts given to uninsured patients under the 
hospital's own financial assistance policy. The commenters believed 
these issues were a result of the MACs' lack of training and/or 
understanding of the charity care process. The issue of adjustments to 
charity care amounts for copayments was also prevalent among the 
comments related to adjustments. Commenters also described MAC 
adjustments related to increases made to expected patient payment 
amounts in Line 22 of Worksheet S-10 such that expected payments for 
patients provided with uninsured discounts exceeded the computed cost 
for charity care, in contradiction of what providers actually 
experience. (For example, some hospitals believed the expected payment 
amount would usually become bad debt in a future cost report.) 
Commenters also raised a concern that sizeable adjustments to the 
uncompensated care costs reported by a hospital were often based on 
extrapolations from small samples of hospital data.
    Despite these perceived audit-related concerns and issues, many 
commenters were supportive of CMS' efforts in the continued auditing of 
Worksheet S-10 data and applauded the efforts to improve the data 
accuracy and integrity. Many commenters also recommended auditing the 
FY 2017 Worksheet S-10 data for use in FY 2021 rulemaking. Commenters 
also provided recommendations for future audits. They suggested that 
CMS audit all hospitals and utilize a single auditor, or at least 
establish and enforce a formal and uniform audit process, similar to 
the desk reviews conducted for the purposes of the wage index. 
Commenters requested that the standardized audit process include 
standardized timelines for information submission with adequate lead 
time, standardized documentation to meet information requirements, and 
adequate communication about expectations. Several commenters also 
urged CMS to consider targeting specific data elements, reducing the 
scope of the audits to reduce the burden placed on providers, and 
making audit instructions publicly available to improve accuracy in 
reporting and make the interpretation of audit guidelines by the MACs 
and providers more consistent. These commenters claimed that not making 
audit instructions public only results in the various MACs and 
providers taking different interpretations of CMS audit guidance, which 
results in inconsistent reporting.
    In addition, some commenters requested that CMS make public the 
results of the audits of the FY 2015 Worksheet S-10 data so that all 
providers might benefit from the lessons learned. Other commenters 
suggested using findings from the audits to develop outreach and 
educational materials for providers. Some commenters requested that CMS 
provide examples of acceptable language for financial assistance 
policies to increase the reliability of provider reporting and MAC 
review, in light of the adjustments that have been made as a result of 
MAC interpretation of language in some hospitals' financial assistance 
policies.
    Many commenters, particularly those that believed that claims 
sampling, extrapolations, determination of adjustments, and the impact 
of adjustments were different across hospitals subject to review of the 
FY 2015 Worksheet S-10 data, recommended that CMS consider statistical 
relevance and apply standard extrapolation in finding thresholds to 
ensure audit consistency across all providers.
    Finally, a number of commenters expressed the need for an appeals 
process and recommended the use of an experienced third party to 
mediate audit adjustment disputes.
    Response: We thank commenters for their feedback on the audits of 
the FY 2015 Worksheet S-10 data. As we stated in the FY 2019 IPPS/LTCH 
PPS final rule, 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 the FY 2020 proposed rule. As discussed in the FY 2020 IPPS/
LTCH PPS 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. At that time, the FY 2016 Worksheet S-10 data and the FY 
2017 Worksheet S-10 data were incomplete, as not all providers would 
necessarily have submitted those cost reports. We therefore chose to 
focus the audit on the FY 2015 cost reports primarily because this was 
the most 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 prior to their use 
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. We note again that, while 
limited resources meant that auditing all hospitals was not feasible, 
the proposed uncompensated care payments to hospitals whose FY 2015 
Worksheet S-10 data were audited

[[Page 42368]]

represented a significant portion (approximately half) of the total 
proposed uncompensated care payments for FY 2020. As a result, we have 
more confidence in the accuracy of the FY 2015 data, as a whole, from 
the combined efforts from hospitals, who may not have been part of 
audit selection but resubmitted cost reports, as well as the results of 
the audits of the FY 2015 reports, in contrast to the data for later 
years which have not yet been audited, at this time.
    As acknowledged by some commenters, we believe that the audits of 
the FY 2015 Worksheet S-10 data have resulted in improvements to the 
accuracy and integrity of reported hospital uncompensated care costs. 
We acknowledge that some hospitals have raised concerns with the audit 
process for Worksheet S-10 of the FY 2015 cost reports. With respect to 
the comments raising concerns regarding the timeframe of audits, it is 
not generally possible for providers to have extensions for additional 
time, during the audit process, as that would lead to excessive 
administrative inefficiencies and potentially delay the timeline for 
completing the audits across all audited providers. We strive for 
increased standardization as MACs continue to gain experience with 
these audits. Regarding the adjustments made by MACs during audits, 
when a provider has no documentation or insufficient documentation to 
support the information reported on its Worksheet S-10, then the MAC 
must adjust the information reported on the applicable lines to reflect 
only those uncompensated care costs that can be documented. This 
approach is necessary in order to be equitable to other hospitals that 
did maintain adequate documentation to support their reported 
uncompensated care information.
    Regarding comments on the instructions for reporting on the 
Worksheet S-10 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 how some of the FY 2015 
report adjustments would not have been necessary if CMS had chosen as 
an alternative to audit the FY 2017 reports, we recognize that there 
were many comments and suggestions on the cost report instructions and/
or auditing process of Worksheet S-10 data for FY 2015 reports. CMS 
strives to use the lessons learned from the audits of the FY 2015 data 
to improve the instructions and/or audits of Worksheet S-10 data in the 
future. For example, in recognition of the importance of additional 
audits and to allow for additional lead time, the audits of the FY 2017 
Worksheet S-10 data have already begun and are currently in progress.
    Regarding commenters' requests that CMS release the audit 
instructions, as noted in the FY 2017 IPPS/LTCH PPS final rule (81 FR 
56964), we stated that we do not make the MACs' review protocol public, 
as all CMS desk review and audit protocols are confidential and are for 
CMS and MAC use only. However, we will continue to work with 
stakeholders to address their concerns regarding the accuracy and 
consistency of data reported on the Worksheet S-10 through provider 
education and further refinement of the instructions for the Worksheet 
S-10 as appropriate. Regarding the comments requesting that we 
establish an appeal process, we note that for the reasons discussed 
previously, we have confidence in the reviews of FY 2015 reports. 
Moreover, we believe that the audit process will continue to improve. 
As a result, we do not believe, on balance, that the creation of an 
appeals process justifies an additional delay in the use of an entire 
year's Worksheet S-10 data at this time. We may consider this topic 
further in the future as we gain more experience with the use of 
Worksheet S-10 data in determining uncompensated care payments.
    After consideration of the public comments we received, we are 
finalizing our proposal to use the FY 2015 Worksheet S-10 cost report 
data in the methodology of Factor 3, as discussed further in later 
sections.
(b) Alternative Considered to Use FY 2017 Data
    Although we proposed to use Worksheet S-10 data from the FY 2015 
cost reports, in the proposed rule we acknowledged that some hospitals 
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 
certain adjustments would not have been made if CMS had chosen as an 
alternative to audit the FY 2017 reports.
    Accordingly, in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19419), we sought 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 sought 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 did 
not propose to use FY 2016 reports because the reporting instructions 
for that year were similar to the reporting instructions for the FY 
2015 reports. In the proposed rule, we stated that 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 on which we sought 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. In the proposed rule, we explained that 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, were outlined in section IV.F.4.c.(3)(d) of the 
preamble of the proposed rule (Methodological Considerations for 
Calculating Factor 3). We specified that if an aspect of the proposed 
methodology did not specifically indicate that we would modify it under 
the alternative considered, that aspect of the methodology would be 
unchanged, regardless of whether we were to use FY 2015 data or FY 2017 
data. We note that in the proposed rule we provided all of the same 
public information regarding the alternative considered, including the 
Factor 3 values for each hospital and the impact information, that we 
provided for our proposal to use FY 2015 data.
    Comment: Many commenters who opposed the use of FY 2015 Worksheet 
S-10 data supported the use of the alternative approach of using FY 
2017 Worksheet S-10 data to determine Factor 3 for FY 2020. In general, 
supporters of the alternative policy believe that the increased clarity 
in the cost reporting instructions in place for the FY 2017 Worksheet 
S-10 outweighs the benefit derived from the audit work performed on a 
subset of the FY 2015 data. These commenters believe that FY 2017 
Worksheet S-10 data were

[[Page 42369]]

reported based on revised and improved instructions established through 
Transmittal 11, which some commenters indicated were easier to follow 
and improved providers' reporting of UCC. Specifically, commenters 
stated that the new instructions to report charity care based on write-
off dates, consistent with reporting of bad debt based write-off dates, 
are less confusing and use hospital financial data that are more 
commonly available to hospital personnel. These commenters provided 
analyses which indicated that there are fewer reporting errors using 
the FY 2017 Worksheet S-10 instructions than the FY 2015 Worksheet S-10 
instructions, in particular regarding reporting of high amounts of 
charity care coinsurance and deductibles. Specifically, a commenter 
asserted that fewer hospitals reported coinsurance and deductible 
amounts greater than 25 percent of total charity care charges on the FY 
2017 Worksheet S-10 than on the FY 2015 Worksheet S-10. Other 
commenters believe that using data from the FY 2017 Worksheet S-10 
would better address the issue of data lag, which could be a concern 
with the FY 2015 data.
    In contrast, other commenters stated that FY 2017 Worksheet S-10 
data may benefit from improvements in cost reporting instructions but 
with unknown precision. That is, the commenters stated that the FY 2017 
data have not yet been audited, pointed to analyses that identify cases 
in which hospitals' uncompensated care costs account for more than 50 
percent of their total operating expenses, and suggested that these 
data aberrancies indicate that the use of unaudited data is not 
appropriate. Furthermore, these commenters stated that there is no 
indication that providers whose FY 2015 Worksheet S-10 data were not 
audited would have been given the guidance necessary to improve the 
accuracy of their FY 2017 data, nor is there any indication that 
providers whose FY 2015 data were audited had the time to make 
corrections when filing their FY 2017 cost reports. Furthermore, a 
commenter expressed concern that the instructions for Worksheet S-10 
had changed for FY 2017 in a way that created an incentive for 
hospitals to inflate charges, while other commenters stated that 
implementing new instructions is problematic as a general matter, as 
providers have varied interpretations of how to report data every time 
instructions change.
    Some commenters further reflected that the Worksheet S-10 
instructions have been revised several times in the last few years, and 
so the use of data from the FY 2017 Worksheet S-10 should be delayed 
until there are final and consistent instructions and the data have 
been reviewed. These commenters pointed specifically to problems with 
the reporting of coinsurance and deductibles in FY 2017, as well as 
significant increases in uncompensated care costs for some hospitals 
between FY 2015 and FY 2017. The commenters believe that these problems 
provide an example of the residual misreporting of data that remains 
even after the issuance of improved cost reporting instructions for FY 
2017. Furthermore, commenters stated that only trims and some recent 
requests to some hospitals for additional information regarding 
potentially aberrant data had occurred for the FY 2017 data, and it was 
unclear to the commenters whether CMS would receive a timely response 
to these requests for use as part of this rulemaking. However, many 
commenters believed that the FY 2017 Worksheet S-10 data, once audited, 
would be appropriate for use in calculating Factor 3. These commenters 
recommended that CMS begin the auditing process as soon as possible and 
incorporate audited FY 2017 data into the methodology for FY 2021.
    Response: We appreciate the input from commenters who expressed 
their support for the alternative policy of using the FY 2017 Worksheet 
S-10 data to determine each hospital's share of UCC in FY 2020. As 
noted in the FY 2019 IPPS/LTCH PPS final rule, on September 29, 2017, 
we issued Transmittal 11, which clarified the definitions and 
instructions for reporting 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 improve the integrity of the data reported on Worksheet S-10. We 
agree that these revisions have improved the reporting of uncompensated 
care costs. However, due to the feedback from commenters in response to 
last year's proposed rule and also in response to the FY 2020 IPPS/LTCH 
PPS proposed rule, emphasizing the importance of audits in ensuring the 
accuracy and consistency of data reported on the Worksheet S-10, we 
believe that the FY 2017 Worksheet S-10 data should be audited before 
they are used in determining Factor 3. To this end, we began auditing 
the FY 2017 Worksheet S-10 data in July 2019, with the goal having the 
FY 2017 audited data available for future rulemaking.
(c) 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, in the FY 2020 IPPS/LTCH PPS proposed rule 
(84 FR 19419), we proposed 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).
    Comment: Several commenters supported the proposed definition of 
uncompensated care as charity care plus non-Medicare bad debt and non-
reimbursable Medicare bad debt. However, as in the past, some 
commenters suggested that uncompensated care should include shortfalls 
from Medicaid, CHIP, and State and local indigent care programs, as the 
commenters believed these inclusions would make the distribution of 
uncompensated care payments more equitable. As a result, several of 
these commenters urged CMS to use Worksheet S-10, Line 31 to identify a 
hospital's share of uncompensated care costs rather than Line 30, as 
Line 31 includes Medicaid unreimbursed costs. The commenters stated 
that the purpose of uncompensated care payments is to partially 
subsidize unmet costs for treating low-income patients and the 
exclusion of Medicaid shortfalls exacerbates the problems faced by 
hospitals in states with lower Medicaid rates and locks in financing 
inequities that currently exist.
    Furthermore, commenters stated their view that excluding Medicaid 
shortfalls from the definition of uncompensated care severely penalizes 
hospitals that care for large numbers of Medicaid patients because many 
States do not fully cover the costs associated with newly insured 
Medicaid recipients. Commenters believed that patients covered by 
Medicaid may still have uncompensated care costs. Some commenters 
believe that under the proposed policy, which did not include Medicaid 
shortfalls in the definition of uncompensated care costs, Medicare 
would significantly subsidize those

[[Page 42370]]

States with Medicaid payment rates that cover the cost of care relative 
to those with lower Medicaid payment rates that do not cover the cost 
of care. The commenters indicated that this concern is further 
compounded if a state has higher Medicaid enrollment either because it 
has expanded its Medicaid program under the Affordable Care Act, has 
more permissive Medicaid eligibility criteria, or simply has a high 
proportion of its citizens that qualify for Medicaid. Finally, some 
commenters believed that Worksheet S-10 provides an incomplete picture 
of Medicaid shortfalls and should be revised to instruct hospitals to 
deduct inter-governmental transfers, certified public expenditures, and 
provider taxes from their Medicaid revenue.
    Response: In response to the comments regarding Medicaid 
shortfalls, we recognize commenters' concerns but continue to believe 
there are compelling arguments for excluding Medicaid shortfalls from 
the definition of uncompensated care, including the fact that several 
key stakeholders, such as MedPAC, do not consider Medicaid shortfalls 
in their definition of uncompensated care, and that it is most 
consistent with section 1886(r)(2) of the Act for Medicare 
uncompensated care payments to target hospitals that incur a 
disproportionate share of uncompensated care for patients with no 
insurance coverage. Conceptual issues aside, we note that even if we 
were to adjust the definition of uncompensated care to include Medicaid 
shortfalls, this would not be a feasible option at this time due to 
computational limitations. Specifically, computing such shortfalls is 
operationally problematic because Medicaid pays hospitals a single DSH 
payment that in part covers the hospital's costs in providing care to 
the uninsured and in part covers estimates of the Medicaid 
``shortfalls.'' Therefore, it is not clear how CMS would determine how 
much of the ``shortfall'' is left after the Medicaid DSH payment is 
made. In addition, in some States, hospitals return a portion of their 
Medicaid revenues to the State via provider taxes, making the 
computation of ``shortfalls'' even more complex.
    We refer readers to the next section for our responses to 
additional comments on the Worksheet S-10 cost report instructions. In 
general, we will attempt to address commenters' concerns through future 
cost report clarifications to further improve and refine the 
information that is reported on Worksheet S-10 in order to support 
collection of the information necessary to implement section 1886(r)(2) 
of the Act.
    Accordingly, after consideration of the public comments we received 
and for the reasons discussed in the proposed rule and previously in 
this final rule, we are finalizing our proposal to define uncompensated 
care costs 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
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19419 through 
19422), we proposed to continue the merger policies that were finalized 
in the FY 2015 IPPS/LTCH PPS final rule (79 FR 50020). In addition, we 
proposed 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 proposed 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. As we discussed in the proposed rule, 
for FY 2020, new hospitals that are projected to be eligible for 
Medicare DSH will receive interim empirically justified DSH payments. 
Generally, new hospitals do not yet have available data to project 
their eligibility for DSH payments because there is a lag until the SSI 
ratio and the Medicaid ratio become available. However, we noted 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 proposed 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. We stated 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 noted that, given 
the time period of the data we proposed 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, we stated that 
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.
    As discussed in the proposed rule, 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 proposed 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 previously 
discussed. 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. As we stated in the proposed rule, we believe the notice of 
our intent in the proposed rule will provide sufficient time for all 
new

[[Page 42371]]

Puerto Rico 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 indicated that 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 stated our belief that the 
uncompensated care costs reported on the FY 2020 Worksheet S-10 for new 
Puerto Rico hospitals are the best available and most appropriate data 
to use to calculate Factor 3 for these hospitals. We indicated this 
proposal 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 proposed 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 explained 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. Accordingly, 
for these hospitals, we proposed 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 indicated that 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 the 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 proposed to continue 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 proposed 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. In the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19420), we stated that we had 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 stated that we believe it is no longer 
necessary to propose specific Factor 3 policies for all-inclusive rate 
providers.
    As discussed in the proposed rule, because we proposed 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 the 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, in the FY 2020 IPPS/LTCH PPS proposed rule, we did propose 
to continue certain other policies finalized 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 proposed 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 explained in the proposed rule that 
we were then in the 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 have 
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 stated 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.

[[Page 42372]]

    We stated in the proposed rule that 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 its 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 final rule 
(83 FR 41415 and 41416) for trimming CCRs, in the FY 2020 IPPS/LTCH PPS 
proposed rule (84 FR 19421 through 19422), we proposed 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 the proposed rule, this 
trim would have removed 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 have removed 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, excluding all-inclusive 
rate providers, 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 the proposed rule, the statewide average 
CCR would therefore have been applied to 8 hospitals, of which 4 
hospitals had FY 2015 Worksheet S-10 data. (Under the alternative 
policy considered, the statewide average CCR would have been applied to 
13 hospitals, of which 5 hospitals had FY 2017 Worksheet S-10 data.). 
We note that in the proposed rule, we inadvertently omitted the 
information noted earlier regarding the exclusion of all-inclusive rate 
providers from this calculation, but have corrected this omission in 
the description of Step 4 in this final rule to clarify that the CCR 
trim methodology excludes all-inclusive rate providers.
    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 proposed 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 proposed 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 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 proposed to amend the regulations at Sec.  
412.106(g)(1)(iii)(C) by adding a new paragraph (6) to reflect the 
proposed methodology for computing Factor 3 for FY 2020.
    In the FY 2020 IPPS/LTCH PPS proposed rule, we proposed 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 would 
apply the steps as previously discussed 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 proposed to use the previously discussed 
steps to calculate Factor 3. We recognized 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 explained our belief that this proposal would be 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, we noted that 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, we stated that 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 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

[[Page 42373]]

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. For purposes of the proposed 
rule, the table published on the CMS website included Factor 3 computed 
using both the proposed methodology and the potential alternative 
methodology. We noted that, at the time of development of the proposed 
rule, the FY 2017 SSI ratios were available. Accordingly, for purposes 
of the proposed rule, we 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 
stated that we would also publish in the supplemental data file a list 
of the mergers that we were aware of and the computed uncompensated 
care payment for each merged hospital.
    Hospitals had 60 days from the date of public display of the 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. We stated that 
comments that are specific to the information included in the table and 
supplemental data file could be submitted to the CMS inbox at 
[email protected]. We indicated we would 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 this 
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 this 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 invited 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.
    We also note that, consistent with the policy adopted in FY 2014 
and applied in each subsequent fiscal year, a 3-year average of 
discharges is used to produce an estimate of the amount of the 
uncompensated care payment per discharge. Specifically, the hospital's 
total uncompensated care payment amount from Factor 3, is divided by 
the hospital's historical 3-year average of discharges computed using 
most recent available data. The result of that calculation for each 
projected DSH eligible hospital is used to make interim uncompensated 
care payments through a per discharge payment amount. The interim 
uncompensated care payments made to the hospital during the fiscal year 
are reconciled following the end of the year to ensure that the final 
payment amount is consistent with the hospital's prospectively 
determined uncompensated care payment for the Federal fiscal year.
    Comment: A commenter recommended that CMS apply a growth factor, 
such as the CBO's projected average monthly Part A fee-for-service 
enrollment, to the claims average in the FY 2020 proposed rule DSH 
Public Use File. The commenter notes that the 3-year discharge average, 
does not currently consider the growth of Medicare eligibility due to 
the aging of baby boomers since 2018. As a result, approximately 7.3-8 
million new Medicare beneficiaries will be incurring additional 
inpatient claims by the end of FY 2020. To mitigate these risks, the 
commenter recommended CMS incorporate a growth factor designed to 
adjust for the increase in Medicare discharges caused by the growth in 
the number of Medicare eligible beneficiaries between 2018 and 2020 and 
apply this factor to the 3-year claims average for each hospital. The 
commenter stated that, in their view, discharge growth discrepancies 
create the risk of overpayments of uncompensated care payments and 
unstable cash flows for CMS, hospitals, and MA plans.
    Response: We thank the commenter for their suggestions related to 
the 3-year discharge average. Although we did not propose any new 
policy related to determination of the discharge average for FY 2020, 
this is a topic we may consider in future rulemaking. For FY 2020, we 
will continue to calculate the interim uncompensated care payments on a 
per discharge basis using historical 3-year average of discharges 
without a growth factor. Consistent with the cost report settlement 
process that we have used since FY 2014, we note that a hospital's 
total amount of interim uncompensated care payments for the cost 
reporting period will be reconciled, in order to ensure consistency 
with the hospital's prospectively determined uncompensated care payment 
for the Federal fiscal year.
    Comment: Some commenters recommended that CMS use the traditional 
payment reconciliation process to calculate final payments for 
uncompensated care costs pursuant to section 1886(r)(2) of the Act. In 
general, commenters did not object to CMS using prospective estimates, 
derived from the best data available, to calculate interim payments for 
uncompensated care costs in a Federal fiscal year after 2013. However, 
some commenters stated that these interim payments should be subject to 
later reconciliation based on estimates derived from actual data from 
the Federal fiscal year.
    Response: Consistent with the position that we have taken in the 
rulemaking for previous years, we continue to believe that applying our 
best estimates prospectively is most conducive to administrative 
efficiency, finality, and predictability in payments (78 FR 50628; 79 
FR 50010; 80 FR 49518; 81 FR 56949; and 82 FR 38195). We believe that, 
in affording the Secretary the discretion to estimate the three factors 
used to determine uncompensated care payments and by including a 
prohibition against administrative and judicial review of those 
estimates in section 1886(r)(3) of the Act, Congress recognized the 
importance of finality and predictability under a prospective payment 
system. As a result, we do not agree with the commenters' suggestion 
that we should establish a process for reconciling our estimates of 
uncompensated care payments, as this would be contrary to the overall 
framework of a prospective payment system like the IPPS.
    The following comments relate to the Worksheet S-10 instructions:
    Comment: Many commenters acknowledged the efforts CMS has taken to 
improve the guidance and the instructions for Worksheet S-10. 
Commenters commended the instructional clarifications implemented via 
Transmittals 10 and 11, and recognized that these improved instructions 
have allowed hospitals to better understand the intent of CMS' 
guidelines. In addition, some commenters stated that the information 
requested by auditors in reviewing the FY 2015 Worksheet S-10 data and 
the corresponding clarifications in the instructions have given 
facilities a better understanding of reporting requirements, which has 
led to more accurate reporting. Conversely, some commenters recognized 
that there are remaining issues with Worksheet S-10 and requested that 
CMS continue to

[[Page 42374]]

revise the instructions to ensure additional clarity going forward.
    Some commenters provided general suggestions to improve the 
Worksheet S-10 instructions. For example, several commenters urged CMS 
to implement fatal edits to ensure that the information reported on 
Worksheet S-10 is complete and internally consistent, and to instruct 
the MAC to audit negative, missing or suspicious information. A 
commenter requested that CMS provide further guidance regarding the 
Worksheet S-10 reporting requirements so as to avoid leaving the 
interpretation of the cost report instructions to the discretion of 
hospital reimbursement staff and/or MAC auditors, which would 
ultimately lead to inconsistent treatment of uncompensated care costs 
across hospitals. According to the commenter, CMS' clarification on 
this issue would also improve the comparability of uncompensated care 
cost data collected across hospitals. Similarly, another commenter 
noted that there remains hospital variation in the interpretation of a 
bad debt ``write-off.'' While the commenter recognized that all bad 
debt amounts should be net of recovery, in the absence a standard 
definition of what a ``write-off'' is, it is in the hands of individual 
provider accounting practices to arrive at such determination. Other 
commenters also requested that CMS release further clarification and 
guidance regarding its expectations as to what is charity care as 
opposed to other uncompensated care costs that may not match the spirit 
of the DSH program, and stated that this clarification is important as 
some providers may have an incentive to report other forms of cost as 
uncompensated care. Lastly, a commenter requested confirmation of 
whether the wording, ``total facility, except physician and other 
professional services,'' in relation to charity care and bad debt 
write-offs includes acute inpatient, exempt inpatient, outpatient, and 
long-term care services.
    A few commenters stated that the instructions still need to be 
revised to clarify the issues that were addressed in the Worksheet S-10 
Q&A issued following the FY 2018 final rule and in the audit protocols. 
To this end, a commenter asserted that several such issues, including 
expected patient payments and the definition of ``uninsured,'' were not 
included or clarified in Worksheet S-10 instructions nor, in the 
commenters' view, had CMS addressed these issues in rulemaking. A 
commenter specifically stated that one of the audit adjustments that 
was made during its audit was moving charity write-offs from Insured 
charity care in Worksheet S-10, Line 20, Column 2, to Uninsured charity 
care in Line 20, Column 1, when an insurance payment had not been made 
on the account. In this case, the commenter stated that definition of 
``uninsured'' being used in Worksheet S-10 is different from the 
definition of ``uninsured'' that is used for the hospital-specific DSH 
limit at 42 CFR 447.295(c) which states that, ``individuals who have no 
source of third party coverage for specific inpatient or outpatient 
hospital services must be considered, for purposes of that service, to 
be uninsured. This determination is not dependent on the receipt of 
payment by the hospital from the third party.''
    Another area of concern raised by commenters was the potential for 
gaming of costs related to charity care and partial discounts. To 
ameliorate this problem, a commenter suggested that CMS develop more 
specific definitions of ``uninsured'' and ``non-covered'' in the 
reporting instructions as well as a standard format for providers to 
submit more detailed data about their charity care write-offs and non-
Medicare bad debt. The commenter further stated that additional 
specificity could also be helpful in the determination of which costs 
are and are not allowable as part of future audits.
    Some commenters also requested that CMS provide specific guidance, 
either regulatory or subregulatory, regarding the treatment of costs 
associated with patients insured under a third-party insurance. 
Commenters requested that CMS provide guidance both for patients with 
coverage from third-party companies that have a contractual 
relationship with the hospital, and patients with coverage from third-
party companies that do not have a contractual relationship with the 
hospital. Commenters also requested clarification regarding the 
treatment of costs associated with patients that have a responsibility 
related to noncovered charges under a third-party insurance company, 
and patients covered under a catastrophic plan or limited benefit plan 
with a limited amount covered daily. A commenter posed questions 
regarding comprehensive examples of multiple coverage scenarios.
    In addition to these concerns, many commenters had more specific 
suggestions, which would require column and line level modifications to 
Worksheet S-10. One of the most prevalent suggestions among commenters 
involved the application of the CCR to non-reimbursed Medicare bad debt 
and non-Medicare bad debt, which commenters classified as 
``unjustifiable'' since Medicare bad debt and insured bad debt should 
be recorded at the full amount of the deductibles and/or coinsurance 
written-off. Specifically, commenters explained that applying a 
provider's CCR to Line 28 understates the cost of bad debt because 
``deductibles, coinsurances based on the negotiated payment rate, and 
the portion of allowable, non-reimbursable Medicare bad debt are not 
marked up to reflect the charged amount.'' Given this, attempting to 
arrive at the cost of bad debt expense from ``multiplying uncollectable 
deductibles, coinsurance based on the negotiated rate, and the portion 
of allowable Medicare bad debt that is non-reimbursable times a 
hospital's cost-to-charge ratio'' is inappropriate and understates the 
``true cost of forgone revenue resulting from uncollectible accounts.'' 
Commenters' general recommendation to resolve this issue was for CMS to 
create separate columns for insured and uninsured patients, with the 
column for ``uninsured patients being multiplied by a hospital's cost-
to-charge ratio to arrive at the cost of bad debt . . . and the column 
for insured patients (which should include amounts related to Medicare 
allowable, non-reimbursable bad debt) not being multiplied by the 
CCR.'' In connection with these recommendations regarding the structure 
of Worksheet S-10, another commenter suggested that CMS add two new 
columns in the charity care section, before Column 2, so that hospitals 
can separately report charges subject to adjustment by the CCR 
(currently Line 25) and charges that are not subject to adjustment by 
the CCR. The commenter suggested similar changes to the bad debt 
section, creating two columns before the total column in which 
hospitals would separately report bad debt charges that should be 
adjusted by the CCR and bad debt write offs for cost-sharing that 
should not be multiplied by the CCR.
    A topic broadly raised by commenters was the clarification of 
charity care, such as in the context of public programs, especially 
Medicaid, as well as third-party insurance. A commenter specifically 
requested clarification of which types of denials by state Medicaid FFS 
and managed care payers can be included as charity care, also asking if 
``charity care eligibility [can] be inferred by enrollment in Medicaid 
manage care plan?'' The commenter also requested clarification of 
whether discounts or reductions to the standard managed care rate can 
be reported as charity care or an uninsured discount for patients who 
are eligible for discounts under a given hospital's

[[Page 42375]]

charity care policy. In addition, the commenter sought clarification of 
the definition of ``non-covered'' charges related to days exceeding the 
length of stay limit and with respect to Medicare, Medicaid, Workers' 
Compensation/No Fault, and commercial plans with which the hospital has 
a contractual relationship, but for which it is not allowed to pursue 
patient collections for losses (for example unpaid claims). The 
commenter questioned whether a hospital is permitted to include such 
losses on Line 20 of Worksheet S-10, if it includes them in its 
financial assistance policy (FAP).
    Several commenters perceived that there appears to be a general 
misunderstanding regarding non-covered Medicaid charges. A commenter 
pointed out that hospitals rely on different sources of information to 
report non-covered Medicaid services; for example, sources can 
primarily be patient transaction detail from hospital records or 
remittance advice (R/A) reports provided by Medicaid Fee for Service 
and Managed Care payers. The commenter believed that each source comes 
with a set of limitations, and stated it is important that the 
definition of uncompensated care for non-covered Medicaid services be 
further clarified. Given this, the commenter suggested that CMS provide 
definitive guidance to prevent inconsistent provider reporting of non-
covered Medicaid charges, which can ultimately impact uncompensated 
care payment distributions.
    A commenter specifically suggested that reporting charges from 
Medicaid days beyond the length of stay limit with insured patient 
coinsurance and deductibles may cause erroneous reporting (those three 
items are currently reported in Line 20 Column 2), such as when 
providers inadvertently do not report these same charges in Worksheet 
S-10 Line 25, where the CCR applies. According to the commenter, the 
instruction to report these charges on Worksheet S-10 Line 25 appears 
to be unnecessary; and they recommend that CMS could avoid misreporting 
of this information by requesting that providers report Medicaid days 
exceeding the length of stay limit with the rest of non-covered charges 
for Medicaid patients on Line 20 Column 1 to ensure the CCR is applied.
    A commenter requested that CMS clarify recent guidance on Medicaid 
cross over bad debt and confirm the commenter's understanding regarding 
hospitals claiming Medicaid cross over bad debt for an unpaid Medicare 
deductible or coinsurance amount. The commenter stated that currently 
the deductible or coinsurance amount must be written-off to a bad debt 
expense account. According to the commenter, hospitals have 
historically written-off Medicare cross over bad debts to contractual 
allowance accounts because they considered these amounts an adjustment 
to the Medicaid allowed amount. Accordingly, the commenter perceived 
the CMS guidance on Medicare crossover bad debt as requiring hospitals 
to modify their own current patient account practices.
    Finally, several commenters requested that CMS clarify whether 
there are implications for Worksheet S-10 from the recent Financial 
Accounting Standards Board Topic 606 on Medicare bad debt reporting.
    Response: We appreciate commenters' concerns regarding the need for 
further clarification of the Worksheet S-10 instructions, as well as 
their suggestions on how to revise the form to continue improving 
provider reporting. As noted by some commenters, our continued efforts 
to refine the instructions and guidance have improved provider 
understanding of the Worksheet S-10. We also recognize that there are 
always continuing opportunities for further improvement, and to the 
extent that commenters have raised new questions and concerns, we will 
attempt to address them through future refinements to the Worksheet S-
10 and the accompanying instructions. Nevertheless, we continue to 
believe that the Worksheet S-10 instructions are sufficiently clear to 
allow hospitals to accurately complete Worksheet S-10.
    Regarding the commenter who referenced the Medicaid definition of 
``uninsured'' used for purposes of the hospital-specific DSH limit at 
42 CFR 447.295(c), we note the Medicare cost report instructions do not 
reference a Medicaid definition of uninsured patient.
    As a general matter, hospitals have the discretion to design their 
charity care policies as they deem appropriate. However, we note that 
hospitals are not permitted to report Medicaid shortfalls (that is, 
situations where Medicaid payment is made for the patient care, but 
that reimbursement may be less than the actual cost of care or the 
billed amount) as charity care on line 20 column 1 or as bad debt on 
line 26, as that would not comply with the Worksheet S-10 cost 
reporting instructions nor the definition of uncompensated care we are 
adopting in this final rule and that has applied for every fiscal year 
starting with the FY 2014, even if under the hospitals' charity care 
policy a Medicaid shortfall would be considered charity care. We refer 
the reader to the earlier section for further discussion of the 
finalized definition of uncompensated care. In general, Medicaid 
patient charges should be reported on Worksheet S-10 line 6. However, 
charges for non-covered services provided to patients eligible for 
Medicaid or other indigent care programs may be reported on line 20, if 
such inclusion is specified in the hospital's charity care policy or 
FAP and the patient meets the hospital's charity care or FAP criteria. 
Additionally, non-covered charges for days exceeding a length-of-stay 
limit for patients covered by Medicaid or other indigent care program 
may be reported on line 25 and line 20 column 2, if such inclusion is 
specified in the hospital's charity care policy or FAP. We note a stay 
that exceeds the length-of-stay limit imposed on patients covered by 
Medicaid or other indigent care program does not mean a length of stay 
that just happens to be longer than an individual hospital's average 
length of stay, but is one that exceeds a Medicaid or other indigent 
care program's length of stay limit. In addition, a DRG-based Medicaid 
payment that is less than the cost of the services furnished to a 
Medicaid patient is considered a Medicaid shortfall and would not be 
for a non-covered service or charity care; therefore, the related 
charges must not be reported as charity care on line 20 column 1 of 
Worksheet S-10. As previously explained, a Medicaid shortfall, or a 
Medicaid contractual allowance, must not be re-characterized as charity 
care.
    In conclusion, we note that the comments recommending structural 
changes to Worksheet S-10 fall outside the scope of this final rule. We 
therefore refer commenters to the forthcoming Paper Reduction Act (PRA) 
package for Form CMS 2552-10 approved OMB No. 0938-0050 expiring March 
31, 2022. The forthcoming PRA package includes proposed changes to the 
Worksheet S-10 instructions, which will provide for a public comment 
period and is the appropriate forum for questions about and suggestions 
for modifications to Worksheet S-10.
    Comment: Many commenters expressed concerns about the accuracy and 
integrity of the FY 2015 Worksheet S-10 data. A commenter noted that, 
for FY 2015, some hospitals incorrectly reported charity care 
transaction amounts based on write-off date, and that reporting of bad 
debts often duplicated charity care charges. The commenter stated that 
this duplication occurs because under the Worksheet S-10 instructions 
for FY 2015, charity care

[[Page 42376]]

is reported as the total charge, while bad debt is reported as the 
write-off amount. This issue, according to the commenter, is not as 
prevalent in the FY 2017 data, because charity care is reported using a 
separate transaction (write-off) amount as opposed to total charges.
    On a separate issue, a commenter asserted that in the FY 2015 
Worksheet S-10 data, charity care amounts related to coinsurance and 
deductible amounts are overstated for more than 20 percent of eligible 
DSH hospitals. The commenter observed that in some cases, the 
overstating of such amounts can be attributed to the header in 
Worksheet S-10, Line 20, Column 2, which states, ``Charity Care for 
Insured Patients.'' Such description, according to the commenter, has 
caused several hospitals to inadvertently report other types of charges 
on this line, commonly for non-covered Medicaid services. The commenter 
noted that this issue has improved in the FY 2017 data due to increased 
provider education and cited analytic results in support of this 
notion. However, several commenters expressed concern regarding 
continued misreporting of coinsurance and deductibles in the FY 2017 
Worksheet S-10. These commenters stated that it may be possible that 
the reported amounts of deductibles and coinsurance are excessive for 
some hospitals now that CMS has issued Transmittals 10 and 11, and the 
CCR is not being applied. Commenters provided analytic results which 
demonstrated an increase in the amounts of deductibles and coinsurance 
reported on the Worksheet S-10 between FY 2015 and FY 2017, as well as 
an increase in the number of hospitals reporting deductibles and 
coinsurance that exceeded the costs of uninsured patients. The 
commenter stated that the significant problems with reporting of 
deductibles and coinsurance in FY 2017 provide an example of continued 
misreporting of data, even after the issuance of improved cost 
reporting instructions for FY 2017.
    Many commenters provided suggestions to enhance the accuracy and 
integrity of the Worksheet S-10 data. Several commenters urged that CMS 
continue its work to accurately capture hospital uncompensated care 
costs in its allocation of Medicare DSH payments. According to some 
commenters, this work could include providing ample opportunity for 
stakeholder feedback and education before issuing substantive revisions 
to Worksheet S-10, as well as conducting additional educational 
outreach to hospitals. A commenter encouraged CMS to invest resources 
in developing educational forums and opportunities for ongoing dialogue 
between CMS, MACs and hospitals prior to releasing significant 
revisions to guidance on cost report instructions. Commenters also 
suggested that CMS build infrastructure and look to the field for 
technology solutions, which could produce an industry standard for how 
data should be prepared and submitted to the MACs and CMS itself.
    Response: We thank commenters for their continued concern and 
constructive feedback regarding the accuracy of Worksheet S-10 data. We 
believe that continued use of Worksheet S-10 will improve the accuracy 
and consistency of the reported data. In addition, we intend to 
continue with and further refine our efforts to review the Worksheet S-
10 data submitted by hospitals based on what we have learned from the 
review and audit process we conducted for the FY 2020 rulemaking 
period. We also intend to consider the various issues raised by the 
commenters specifically related to the reporting of charity care and 
bad debt costs on Worksheet S-10 as we continue to review the Worksheet 
S-10 data.
    We agree with commenters that continuing our ongoing educational 
effort is appropriate, including provider education that may occur 
during Worksheet S-10 reviews. We also appreciate the suggestions 
provided by commenters regarding areas for further education. We 
reiterate that we will continue the education efforts undertaken in the 
past as well as our collaboration with stakeholders to address their 
concerns regarding the accuracy and consistency of reporting of 
uncompensated care costs.
    Comment: Several commenters urged CMS to allow hospitals to submit 
revisions to their cost reports in order to improve the accuracy of the 
data. Related to the FY 2015 Worksheet S-10 data, a commenter requested 
that CMS address and allow for corrections of what the commenter 
asserted were MAC adjustment errors made during the audits so that 
hospitals are allowed an opportunity to resubmit corrected Worksheet S-
10 data in an expedited fashion for use in the final rule. The 
commenter stated that if CMS believes such corrected Worksheet S-10 
data must be reviewed and/or approved before they can be used, then it 
must provide for an expedited review process that allows for high level 
agency review in order to overrule the MAC, and only permit 
disallowances to stand if applied consistently and uniformly to all 
providers.
    Some commenters stated that CMS afforded hospitals several 
opportunities to improve FY 2015 data, but these opportunities have not 
been offered with respect to FY 2017 data. Commenters believe that many 
hospitals that might desire to reopen their FY 2017 cost report based 
on their FY 2015 audit findings have not had time to start that 
process. Finally, a commenter recommended that CMS indicate in the FY 
2020 final rule that it intends to use FY 2017 Worksheet S-10 data to 
calculate uncompensated care payments for FY 2021 in order to provide 
sufficient notice to allow providers to begin amending their unaudited 
FY 2017 data before these data are used to determine payments.
    Response: We acknowledge commenters' requests regarding the 
opportunity to resubmit cost reports for purposes of calculating FY 
2020 uncompensated care payments. However, we do not agree that we 
should continue to offer hospitals multiple opportunities to amend 
their cost reports outside of the normal process. We expect a hospital 
to submit correct cost report data to its MAC and to use the normal 
timelines and procedures in place to amend its cost report, if 
appropriate. With respect to the commenter who recommended that we 
indicate in the FY 2020 final rule that we intend to use FY 2017 
Worksheet S-10 data to calculate uncompensated care payments for FY 
2021, we note that we will address proposed policies for FY 2021 in the 
FY 2021 IPPS/LTCH proposed rule.
    Comment: Several commenters voiced concern that their most recent 
Worksheet S-10 data were not reflected in the data used for the 
proposed rule, and some were concerned that their most recent data 
would not be included in the final rule data file if CMS decides to use 
the March HCRIS extract, as proposed. For example, some commenters 
noted that the public use file from the proposed rule did not include 
audit adjustment reversals for the FY 2015 Worksheet S-10. Some 
commenters noted that because CMS had not given a directive as to the 
deadline for amending FY 2017 Worksheet S-10 data, many providers were 
still in the process of correcting their data and did not have enough 
time to submit the corrected data for use in the proposed rule, while 
other commenters stated that their amended cost report for FY 2017 had 
been accepted well after the cut-off for the proposed March HCRIS 
extract. Thus, commenters requested that CMS use the latest HCRIS 
extract possible, to allow providers and CMS to correct aberrant data 
identified for potential revision, as well as account for any hospital 
that

[[Page 42377]]

voluntarily submitted Worksheet S-10 revisions. Some commenters 
attached copies of their updated Worksheet S-10 for CMS to consider on 
the record.
    Response: We appreciate the commenters' diligence in checking that 
their own reports and data were properly processed. We recognize that 
some hospitals' data in the March HCRIS update may not have reflected 
all corrections and/or adjustments made to Worksheet S-10 data in 
response to our hospital outreach and auditing efforts. Given those 
circumstances and consistent with our historical practice of using the 
best data available, we are using a June 30, 2019 HCRIS extract, which 
is the most recent available data at the time of development of this 
final rule, to calculate Factor 3 for this FY 2020 IPPS/LTCH PPS final 
rule. We note that we expect to able to use the March HCRIS in future 
rulemaking, which is generally a more appropriate data source for a 
number of reasons, including that the data is available to the public 
to review for a longer period of time prior to the publication of the 
final rule, and the use of the June 30th extract presents ratesetting 
challenges for CMS to incorporate the data in time for the statutory 
publication of the final rule.
    Following the publication of this 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 this 
final rule. We believe the supplemental data file reflects the most 
recent available data in HCRIS at the time of development of this final 
rule. We have not considered information from any revised Worksheets S-
10 that were submitted as attachments to comments. We do not believe it 
would be appropriate to allow a hospital to use the rulemaking process 
to circumvent the requirement that cost report data need to be 
submitted to the MAC or the requirement that requests to reopen cost 
reports need to be submitted to the MAC. Otherwise we would have 
multiple potentially conflicting sources of information about a 
hospital's uncompensated care data or, more broadly, any cost report 
data that might be submitted during the rulemaking process. In 
addition, there are validity checks and other safeguards incorporated 
into the cost report submission process that would not be automatically 
applied to cost reports only submitted through rulemaking.
    Comment: A few commenters also noted that the February 15, 2019 
HCRIS extract used for the proposed rule may have misled some providers 
choosing between the proposed and alternative methodologies for 
calculating Factor 3 because certain changes to the FY 2015 data, such 
as audit corrections, would only be reflected when CMS uses the March 
HCRIS extract, as proposed for the final rule. Similarly, another 
commenter asserted that CMS has used different data and calculations in 
the final rules without the opportunity for hospitals to comment, that 
is, hospitals do not see their final DSH payment amounts until the 
final rule, in violation of the Administrative Procedural Act.
    Response: Regarding the concerns related to the Administrative 
Procedure Act, we note that, under the Administrative Procedure Act, a 
proposed rule is required to include either the terms or substance of 
the proposed rule or a description of the subjects and issues involved. 
In this case, the FY 2020 IPPS/LTCH PPS proposed rule included a 
detailed discussion of our proposed methodology for calculating Factor 
3 and the data that would be used. We made public the best data 
available at the time of the proposed rule, in order to allow hospitals 
to understand the anticipated impact of the proposed methodology. 
Moreover, following the publication of the proposed rule, we continued 
our efforts to ensure that information hospitals had properly submitted 
to their MAC in the prescribed timeframes would be available to be used 
in this final rule in the event we finalized our proposed methodology. 
We believe the fact that we provided data with the proposed rule, while 
concurrently continuing to review that data with individual hospitals 
is entirely consistent with the Administrative Procedure Act and 
established CMS practice. There is no requirement under either the 
Administrative Procedure Act or the Medicare statute that CMS make the 
actual data that will be used in a final rule available as part of the 
notice of proposed rulemaking. Rather, it is sufficient that we provide 
stakeholders with notice of our proposed methodology and the data 
sources that will be used, so that they may have a meaningful 
opportunity to submit their views on the proposed methodology and the 
adequacy of the data for the intended purpose. This requirement for 
notice and comment does not, however, extend to a requirement that we 
make all data that will be used to compute payments available to the 
public, so that they may have an opportunity to comment on accuracy of 
the data reported for individual hospitals. Similarly, there is no 
requirement that we provide an opportunity for comment on the actual 
payment amounts determined for each hospital.
    Comment: Several commenters supported CMS' proposal to trim 
hospitals' uncompensated care costs to control for anomalies. However, 
many of these commenters recommended that CMS substitute aberrant data 
from the FY 2015 Worksheet S-10 with data from FY 2014, since the FY 
2014 data have been previously available for public scrutiny and 
utilized in determining uncompensated care payments. A few commenters 
also voiced concerns regarding the agency's proposed policy for 
trimming uncompensated care costs. A commenter considered that it is 
unnecessary to substitute 1 year of Worksheet S-10 data for another, 
unless there has been some inappropriate action or improper reporting 
by the provider. Other commenters stated that CMS has not clarified how 
hospitals with high uncompensated care costs, which are subject to the 
trimming policy, are identified. The commenter added that CMS has 
failed to account for situations in which a hospital might legitimately 
have high uncompensated care costs for reasons such payer mix 
composition. The commenter suggested that CMS must take steps to 
discern when high uncompensated care costs arise from erroneous data 
rather than from a legitimate cause by ensuring that MACs work 
collaboratively with hospitals to distinguish inaccurate uncompensated 
care values from legitimately high values. According to the commenter, 
if a hospital can justify its high values, its uncompensated care costs 
should not be subject to the substitution.
    Response: We appreciate the comments and suggestions regarding our 
policy for trimming uncompensated care costs that are an extremely high 
ratio of a hospital's total operating costs for the same year. We 
believe the proposed approach balances our desire to exclude 
potentially aberrant data with our concern regarding inappropriately 
reducing FY 2020 uncompensated care payments to a hospital that may 
have a legitimately high ratio. We note that no hospitals exceeded the 
50 percent trim threshold for the FY 2015 Worksheet S-10. We will 
continue to consider the commenters' recommendations for the aberrant 
UCC data trim in future rulemaking.
    Comment: Several commenters stated that the current Worksheet S-10 
does not account for all patient care costs when converting charges to 
costs. These commenters stated that the current worksheet ignores 
substantial costs hospitals incur in training medical

[[Page 42378]]

residents, supporting physician and professional services, and paying 
provider taxes associated with Medicaid revenue. Thus, these commenters 
requested that CMS refine the Worksheet S-10 to incorporate all patient 
care costs into the CCR. Commenters most often recommended that the CCR 
include the cost of graduate medical education (GME) to account for the 
costs associated with the training of interns and residents. The 
commenters stated that GME represents a significant portion of the 
overhead costs of teaching hospitals, where a large number of interns 
and residents treat patients from all financial backgrounds, including 
the uninsured. Therefore, the commenters believed that including GME 
costs in the CCR calculation and then using this adjusted CCR for 
Worksheet S-10 would more accurately represent the true uncompensated 
care costs for teaching hospitals. A commenter also stated that 
including GME cost in determining the CCR used on the Worksheet S-10 
will better align with the Medicaid DSH program, as well as with the 
approach used by the IRS in calculating the hospital community benefit 
provided by non-profit hospitals.
    In addition, commenters provided several suggestions for revising 
the CCR on Worksheet S-10. One suggestion was for CMS to use the total 
of Worksheet S, Column 3, Lines 1 through 117, reduced by the amount on 
Worksheet A-8, Line 10, as the cost component, and Worksheet C, Column 
8, Line 200 as the charge component. Another commenter stated that GME 
costs can be included in the formula for calculating the CCR for 
Worksheet S-10 by using costs from Worksheet B, Part 1, Column 24, line 
118, and by removing the reasonable compensation equivalency (RCE) 
limits from Worksheet S-10.
    Response: As we have stated previously in response to this issue 
(83 FR 41425), we believe that the purpose of uncompensated care 
payments is to provide additional payment to hospitals for treating the 
uninsured, not for the costs incurred in training residents. In 
addition, because the CCR on Line 1 of Worksheet S-10 is pulled from 
Worksheet C, Part I, and is also used in other IPPS ratesetting 
contexts (such as high-cost outliers and the calculation of the MS-DRG 
relative weights) from which it is appropriate to exclude GME because 
GME is paid separately from the IPPS, we hesitate to adjust the CCR in 
the narrower context of calculating uncompensated care costs. 
Therefore, we continue to believe that it is not appropriate to modify 
the calculation of the CCR on Line 1 of Worksheet S-10 to include GME 
costs in the numerator. With regard to the comment that the CCRs on 
Worksheet S-10 are reported with the reasonable compensation equivalent 
(RCE) limits applied, we believe the commenter is mistaken. Line 1 of 
Worksheet S-10 instructs hospitals to compute the CCR by dividing the 
costs from Worksheet C, Part I, Line 202, Column 3, by the charges on 
Worksheet C, Part I, Line 202, Column 8. The RCE limits are applied in 
Column 4, not in Column 3; thus, the RCE limits do not affect the CCR 
on line 1 of Worksheet S-10.
    Comment: Several commenters supported the proposal to use one cost 
report beginning in each fiscal year to derive the uncompensated care 
costs for that year, and to annualize Medicaid days and uncompensated 
care data for hospitals with less than 12 months of data. In addition, 
several commenters supported the proposed policy of allowing new 
hospitals that appear to be eligible for empirical DSH payments to 
receive empirically justified DSH payments but not interim 
uncompensated care payments.
    Response: We appreciate the support for our proposal to use one 
cost report beginning in each fiscal year to derive the uncompensated 
care costs for that year, to annualize cost reports that do not equal 
12 months of data, and to allow new hospitals that appear to be 
eligible for empirical DSH payments to receive interim empirically 
justified DSH payments but not interim uncompensated care payments.
    Comment: Many commenters from Puerto Rico expressed their general 
support for the DSH policies proposed for FY 2020, and urged that CMS 
implement these policies as proposed. More specifically, several 
commenters supported the proposed policy for Puerto Rico, Indian Health 
Service, and Tribal hospitals, under which low-income patient days 
would continue to be utilized instead of the Worksheet S-10 UCC data to 
determine each hospital's share of uncompensated care payments. In 
addition, these commenters supported the proposal to continue to use 14 
percent of Medicaid days as a proxy for Medicare SSI days when 
determining Factor 3 of the uncompensated care payment methodology for 
hospitals located in Puerto Rico. These commenters stated that the 
continued use of these proxies is appropriate, adding that they agree 
with CMS and other stakeholders that uncompensated care data reported 
by these hospitals need to be further examined before the data are used 
in calculating uncompensated care payments.
    Response: We appreciate the support for our proposal to use low-
income insured days as a proxy for UCC for Puerto Rico, Indian Health 
Service, and Tribal hospitals, as well as for our proposal to use 14 
percent of a Puerto Rico hospital's Medicaid days as a proxy for SSI 
days. Because we are continuing to use insured low-income insured 
patient days as a proxy for uncompensated care for these hospitals in 
determining Factor 3 for FY 2020, and residents of Puerto Rico are not 
eligible for SSI benefits, we believe it is important to create a proxy 
for SSI days for Puerto Rico hospitals in the Factor 3 calculation.
    The following comments address the proposed CCR trimming 
methodology:
    Comment: A few commenters stated that the current CCR trimming 
methodology is not adequate to address the CCR anomalies in the 
Worksheet S-10 data reported by certain hospitals. Other commenters 
supported the current methodology. Some commenters also stated that 
hospitals that have been identified as potential outliers should have 
the opportunity to explain their data and correct errors before the 
trim methodology is applied, which would facilitate data validity. In 
addition, other commenters requested that the trimming methodology not 
be finalized until an audit of the data has been conducted, and that 
hospitals with extremely high CCRs be audited and an appropriate CCR 
determined instead of applying an arbitrary trim to a statewide 
average. For example, a number of commenters proposed that the four-
step methodology for trimming CCRs should be used as an outlier 
identification process to alert auditors, not as a policy in and of 
itself. These commenters expect that as CMS continues to work on the 
Worksheet S-10 audit process, the proposed CCR trims would become an 
audit tool rather than a mechanism to trim what appears to be aberrant 
data.
    A commenter stated that CMS should focus on understanding the 
underlying reason for varying CCRs, and that if CMS intends to require 
hospitals to revise their charge structures and cost apportionment 
methodologies, CMS should give the hospitals sufficient time to bring 
their systems into line with these requirements. Similarly, several 
commenters expressed concern over the proposed trim methodology because 
hospitals that are considered ``all-inclusive rate providers'' are not 
required to complete Worksheet C, Part I, which is used for reporting 
the CCR on Line 1 of the Worksheet S-10. As a result, these commenters 
believed that the proposed trim methodology would inappropriately 
modify their

[[Page 42379]]

uncompensated care costs, and that a high CCR could be accurate if the 
hospital's charges are close to costs, as is usually the case for all-
inclusive rate hospitals. These commenters recommended that CMS assess 
how the current CCR trim methodology affects all-inclusive rate 
providers, or work with MACs to derive an appropriate CCR.
    In addition, commenters encouraged CMS to engage with hospitals in 
determining the best way to use Worksheet S-10 data to distribute 
uncompensated care payments to all-inclusive rate providers in the 
future, and some suggested that CMS continue to use the low-income 
patient days proxy to distribute Medicare DSH uncompensated care 
payments to these providers. A commenter stated that there was a 
contradiction in the proposed rule because CMS indicated that it was no 
longer necessary to propose specific Factor 3 policies for all-
inclusive providers, yet later indicated that CMS would remove all-
inclusive providers from the CCR trimming methodology because their 
CCRs are not comparable to the CCRs calculated for other IPPS 
hospitals. The commenter requested that CMS take a consistent approach 
in the final rule, and encouraged CMS to revisit its trimming 
methodology in the final rule and to also focus its audit activity for 
the FY 2017 Worksheet S-10 data on whether high CCR hospitals, 
particularly those that use an all-inclusive rate structure, are 
generating an accurate portrayal of uncompensated care costs.
    Response: We appreciate the additional information provided by the 
commenters related to our proposed methodology for applying trims to 
the CCRs. We intend to further explore which trims are most appropriate 
to apply to the CCRs on Line 1 of Worksheet S-10, including whether it 
would be appropriate to apply a unique trim for certain subsets of 
hospitals, such as all-inclusive rate providers. We note that all-
inclusive rate providers have the ability to compute and enter their 
appropriate information (for example, departmental cost statistics) on 
Worksheet S-10, Line 1, by answering ``Yes'' to the question on 
Worksheet S-2, Part I, Line 115, rather than having it computed using 
information from Worksheet C, Part I. We also intend to give additional 
consideration to the utilization of statewide averages in place of 
outlier CCRs, and will also consider other approaches that could ensure 
the validity of the trim methodology, while not penalizing hospitals 
that use alternative methods of cost apportionment. We may consider 
incorporating these alternative approaches through rulemaking for 
future years.
    However, as discussed in the FY 2020 IPPS/LTCH PPS proposed rule, 
we have examined the CCRs from the FY 2015 cost reports and believe 
that 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. As outlined in the proposed 
rule, we remove all-inclusive rate providers from the CCR trim in Step 
1 of the trimming methodology because their CCRs are not comparable to 
the CCRs calculated for other IPPS hospitals. Thus, the CCRs for all-
inclusive rate providers are excluded from the CCR trimming process. 
Regarding the commenters' view that CCR trims should not take place 
before we give providers further opportunities to explain or amend 
their data, we agree that, under ideal circumstances, CCR trims without 
audits would not be needed. However, providers have had sufficient time 
to amend their data and/or contact CMS to explain that the FY 2020 DSH 
Supplemental Data File posted in conjunction with FY 2020 IPPS/LTCH PPS 
proposed rule had incorrect data. As a result, we consider CCRs greater 
than 3 standard deviations above the national geometric mean CCR for 
the applicable fiscal year to be aberrant CCRs.
    After consideration of the public comments we received, and for the 
reasons discussed in the proposed rule and in this final rule, we are 
finalizing our proposal to use 1 year of Worksheet S-10 data from FY 
2015 cost reports to determine Factor 3 of the uncompensated care 
methodology.
    Therefore, for FY 2020, we are finalizing the following methodology 
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 applicable cost report because 
the cost report for the previous Federal fiscal year spanned the 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 annualized 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 hospital's FY 2013 Medicaid days). (Alternatively, in the rare 
case when the provider has no FFY applicable cost report because the 
cost report for the previous Federal fiscal year spanned the time 
period, the previous Federal fiscal year cost report would be used in 
this step.) We combine low-income insured days for hospitals that 
merged. The denominator is calculated using the low-income insured days 
proxy data from all DSH eligible hospitals. We note, that consistent 
with the policy adopted in the FY 2019 IPPS/LTCH final rule, if a 
hospital does not have both Medicaid days for FY 2013 and SSI days for 
FY 2017 available for use in the calculation of Factor 3 in Step 4, we 
would consider the hospital not to have data available for Step 4.
    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 finalizing the following proposals: (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) 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 CCRs and potentially aberrant uncompensated care 
costs.
    For this FY 2020 IPPS/LTCH PPS final rule, we are finalizing a 
HCRIS cutoff of June 30, 2019, for purposes of calculating Factor 3. We 
are also finalizing our proposal to amend the regulations at Sec.  
412.106(g)(1)(iii)(C) by adding a new paragraph (6) to reflect the 
methodology for computing Factor 3 for FY 2020.

[[Page 42380]]

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 discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19422 through 19423), 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 final rule for a discussion of the calculation of a 
hospital's 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.
    As stated in the proposed rule, 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 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, as indicated in 
the proposed rule, we were 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 stated in the proposed rule that 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 indicated in the proposed rule we were 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.
    Comment: We received several comments in response to this request 
for information. Commenters were generally supportive of the options 
presented.
    Response: We thank commenters for responding to this request for 
information. We will take these comments into consideration for future 
rulemaking.

G. Hospital Readmissions Reduction Program: 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 proportion of 
beneficiaries who are dually eligible for Medicare and full-benefit 
Medicaid (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).

[[Page 42381]]

     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).
     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. In 
section IV.G.12. of the preamble of this final rule, we are finalizing 
our proposals to update the regulatory text to reflect both the 
proposed policies that we are finalizing in this final rule as well as 
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.
    We note that we received public comments on the effectiveness and 
design of the Hospital Readmissions Reduction Program in response to 
the FY 2020 IPPS/LTCH PPS proposed rule. While we appreciate the 
commenters' feedback, because we did not include in the proposed rule 
any proposals related to these topics, we consider the public comments 
to be out of the scope of the proposed rule. Therefore, we are not 
addressing most of these comments in this final rule. However, all 
topics that we consider to be out of scope of the proposed rule will be 
taken into consideration when developing policies and program 
requirements for future years.
    Comment: Several commenters urged CMS to work with a range of 
stakeholders--including hospitals, patients and health services 
researchers--to assess whether the Hospital Readmissions Reduction 
Program has had a negative impact on hospital mortality rates and other 
unintended consequences, and noted that some emerging research may 
suggest that the Hospital Readmissions Reduction Program's strong 
incentive to reduce readmissions could be associated with higher 
mortality rates.
    Response: We believe that the Hospital Readmissions Reduction 
Program has successfully reduced readmissions, which are both harmful 
to patients and costly for the health care system. In June 2018, the 
Medicare Payment Advisory Commission also stated that ``Readmission 
rates clearly declined from 2010 to 2016. Given the totality of the 
evidence and the findings in the literature, it appears that at least 
some of this reduction was due to the incentives in the HRRP. The exact 
share that is due to the HRRP and the share due to other factors is 
difficult to disentangle.'' \317\ Keeping patients healthy is one of 
our highest priorities, and we welcome any research reports pertaining 
to the unintended consequences of the program. We will continue to 
monitor literature that discusses the Program, and take this 
information into account during future policymaking. We are committed 
to monitoring any unintended consequences over time, such as the 
inappropriate shifting of care or increased patient morbidity and 
mortality, to ensure that the Hospital Readmissions Reduction Program 
improves the lives of patients and reduces cost.
---------------------------------------------------------------------------

    \317\ Medicare Payment Advisory Commission (MedPAC), ``Chapter 
1, The Effects of the Hospital Readmissions Reduction Program,'' 
Report to Congress: Medicare and Health Care Delivery System, June 
2018. http://www.medpac.gov/docs/default-source/reports/jun18_ch1_medpacreport_sec.pdf?sfvrsn=0.
---------------------------------------------------------------------------

3. Summary of Policies for the Hospital Readmissions Reduction Program
    In the FY 2020 IPPS/LTCH PPS proposed rule, we proposed 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.
    In this final rule, we are finalizing our proposals as proposed. We 
discuss these finalized proposals in greater detail below.
4. Current Measures and Newly Finalized 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

[[Page 42382]]

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. In the FY 2020 IPPS/LTCH PPS proposed 
rule (84 FR 19424), we did not propose to remove or adopt any 
additional measures at this time.
b. Measure Removal Factors Policy
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19424), while we 
did not propose to remove any measures from the Hospital Readmissions 
Reduction Program, we proposed 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 proposed 
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; \318\
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    \318\ 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.
---------------------------------------------------------------------------

     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.\319\
---------------------------------------------------------------------------

    \319\ 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.
---------------------------------------------------------------------------

    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.
    We received several public comments on our proposed measure removal 
factors.
    Comment: Many commenters supported the adoption of the eight 
measure removal factors previously adopted by the Hospital IQR Program 
and the Hospital VBP Program into the Hospital Readmissions Reduction 
Program. A few commenters stated that adoption of these factors would 
allow for consistency and alignment in measure evaluation methodology 
across programs. Some commenters also believed that the factors are 
well-established and ensure that a variety of valid reasons to remove a 
measure are considered by CMS. A few commenters also believed the 
proposal would reduce burden and increase efficiency.
    Response: We thank the commenters for their support.
    Comment: Some commenters encouraged CMS to be transparent in how 
these factors are applied when a measure is considered for removal and 
urged CMS to use the factors as a guide to removal rather than an 
automatic process.
    Response: As we stated in the proposed rule and as described above, 
we consider these removal factors as considerations for removal, not 
firm requirements. We value transparency in our processes, and plan to 
seek stakeholder input through education and outreach, rulemaking and 
other stakeholder engagement before removing measures.
    Comment: One commenter opposed the adoption of the removal criteria 
because this commenter believed the criteria lack specificity and 
empirical support. The commenter believed that CMS should include more 
detail on how the removal factors would apply to beneficiaries, and 
develop and publicly share how the terminology in each criterion would 
be applied. The commenter requested transparency around how such terms 
were tested and what results will empirically determine whether the 
criterion is met or not.
    Response: We thank the commenter for these recommendations. As we 
discussed in the proposed rule, the removal factors are intended to be 
considerations that we take into account when deciding whether or not 
to remove measures. There may be circumstances in which we decide that 
a measure that meets one or more factors for removal should be retained 
regardless of the criteria, because any benefit of removing a measure 
could be outweighed by the benefits of retaining it. We intend to take 
multiple considerations and stakeholder feedback into account when 
determining whether to propose a measure for removal under any of the 
removal factors.
    Comment: Several commenters supported removal Factor 1: ``measure 
performance among hospitals is so high and unvarying that meaningful 
distinctions and improvement in performance can no longer be made 
(``topped-out'' measures),'' but encouraged CMS to enhance the removal 
factor by adding quantitative criteria or empirical criteria similar to 
the criteria adopted by Hospital IQR and

[[Page 42383]]

Hospital VBP Programs. Some commenters specifically recommended adding 
the ``topped out'' definition adopted by the Hospital IQR and Hospital 
VBP Programs (79 FR 50055):
     The difference in performance between the 75th and 90th 
percentile is statistically indistinguishable. In general, this means 
that the 75th and 90th percentile scores differ by less than two 
standard deviations.
     The truncated coefficient of variation (TCV) is less or 
equal to 0.10. CMS's definition of ``truncated'' is to remove the top 
and bottom 5% of hospitals before calculating the CV. Applying these 
two criteria to current data shows that the program's measure set may 
already be ``topped out'' in performance.
    Response: We thank the commenters for these recommendations. 
Because the Hospital Readmissions Reduction Program focuses on improved 
coordination and communication to prevent readmissions that are harmful 
to patients and costly to Medicare, the empirical criteria developed 
for the Hospital IQR and Hospital VBP Programs may not be appropriate 
for all readmissions. The Hospital Readmissions Reduction Program 
strives to encourage hospitals to reduce excess readmissions, not 
within a statistical standard, but to as close to zero as possible. 
While we do not believe that the Hospital IQR Program or Hospital VBP 
Programs' empirical standards are appropriate for the Hospital 
Readmissions Reduction Program at this time, we will consider whether 
other statistical standards may be more appropriate for the Hospital 
Readmissions Reduction Program in the future. Therefore, we believe 
adding quantitative or empirical criteria at this time would not be 
appropriate.
    Comment: A few commenters opposed adoption of measure removal 
Factor 1: ``measure performance among hospitals is so high and 
unvarying that meaningful distinctions and improvement in performance 
can no longer be made (``topped out'' measures).'' One commenter 
believed that removal of a measure immediately upon a ``topped out'' 
analysis would eliminate the ability to determine whether performance 
regresses or that the removal of the measure may result in lower 
quality of care over the long term. The commenter recommended CMS 
either consolidate measures that meet the ``topped out'' criteria but 
are still considered meaningful to stakeholders into a composite 
measure or include them as an evidence-based standard in a verification 
program. One commenter expressed its belief that the policy would 
eliminate many important measures and would therefore not address true 
quality improvement. Another commenter believed that many measures are 
``never events'' and a low prevalence still can be unacceptably high. 
The commenter also believed the quantitative criteria CMS uses for 
determining topped out status is problematic, as beneficiaries and 
payers often avoid the lowest performers, and that CMS's topped out 
methodology does not account for variation in lower performing 
percentiles; additionally, a potential high degree of variation outside 
of the narrow 75th-90th percentiles is unaccounted for.
    Response: We thank the commenters for these recommendations. As we 
discussed in the proposed rule, the removal factors are intended to be 
considerations taken into account when deciding whether or not to 
remove measures but are not firm requirements. There may be 
circumstances in which a measure that meets one or more factors for 
removal should be retained regardless, because any benefit of removing 
a measure could be outweighed by other benefits to retaining the 
measure. We intend to take multiple considerations into account when 
determining whether to propose a measure for removal under Factor 1 or 
any of the other removal factors. Additionally, we note that we have 
intentionally not provided numerical guidelines for Factor 1 in order 
to retain flexibility when assessing measures.
    Comment: Several commenters expressed concern that retaining 
``topped out'' measures could detract from quality improvements because 
hospitals might expend more resources trying to improve measures that 
have limited opportunity for improvement rather than focusing on 
measures that could provide greater opportunities for improvement. 
Another expressed concern that CMS might retire measures using the 
``topped-out'' criteria before identifying and adopting replacement 
measures, and urged CMS to be thoughtful before removing measures.
    Response: We thank the commenters for sharing their concerns. The 
removal factors are intended to be considerations that we take into 
account when deciding whether or not to remove measures as part of a 
holistic review of the program's measure set. There may be 
circumstances in which a measure that meets one or more factors for 
removal should be retained regardless of the criteria because any 
benefit of removing a measure could be outweighed by benefits of 
retaining the measure. We intend to take multiple considerations and 
stakeholder feedback into account when determining whether to propose a 
measure for removal under any of the removal factors.
    Comment: Several commenters supported the adoption of Factor 8: 
``costs associated with a measure outweigh the benefit of its continued 
use in the program.''
    Response: We thank the commenters for the support.
    Comment: A few commenters raised specific concerns regarding Factor 
8: ``the costs associated with the measure outweigh the benefit of its 
continued use in the program.'' A commenter supported the addition of 
Factor 8, but suggested that CMS seek stakeholder input specifically 
each time Factor 8 is considered for application. Another commenter 
opposed the adoption of Factor 8 unless ``costs'' and ``benefits'' are 
defined as ``costs to Medicare beneficiaries and the public'' and 
``benefits to Medicare beneficiaries and the public.'' A few commenters 
expressed the belief that CMS should develop empirical criteria to 
determine whether this factor has been met. A few commenters strongly 
opposed Factor 8 because of their belief that it is extremely 
subjective, lacks clear criteria and guidelines, and that costs should 
not be the driving factor when deciding whether to remove a measure. A 
few commenters also argued that the other criteria were sufficient.
    Response: We thank the commenters for sharing these concerns 
regarding Factor 8. We value transparency in our process and will seek 
stakeholder input prior to removing any measures from the Hospital 
Readmissions Reduction Program. We intend to be transparent in our 
assessment of measures under this measure removal factor. There are 
various considerations of costs and benefits that we will evaluate in 
applying removal Factor 8, and we will take into consideration the 
perspectives of multiple stakeholders. However, because we intend to 
evaluate each measure on a case-by-case basis, and each measure has 
been adopted to fill different needs in the Hospital Readmissions 
Reduction Program, we do not believe it would be meaningful to identify 
a specific set of assessment criteria to apply to all measures. We 
believe costs include costs to stakeholders such as patients, 
caregivers, providers, CMS, and other entities. In addition, we note 
that the benefits we will consider center on benefits to patients and 
caregivers as the primary beneficiaries of our quality reporting and 
value-based payment programs. When we propose to remove a measure under 
this measure removal factor, we will provide information on

[[Page 42384]]

the costs and benefits we considered in evaluating the measure.
    Comment: One commenter recommended that CMS adopt an additional 
measure removal factor, considering ``whether the measure is important 
to beneficiaries or the public at large.'' The commenter believed that 
the measure removal policy should center on the best interests of 
Medicare beneficiaries and Medicaid recipients and then the best 
interests of the public at large. The commenter recommended that the 
additional measure removal factor be Factor 1 to denote its primary 
importance, and the proposed measure removal factors be renumbered 
accordingly.
    Response: We thank the commenter for this recommendation. We will 
consider the perspectives of all stakeholders when applying any of the 
measure removal factors, and importance to beneficiaries and the public 
at large are certainly part of this consideration. Additionally, we 
proposed these measure removal factors to support alignment with our 
other quality programs, and we do not believe that adopting additional 
measure removal factors for the Hospital Readmissions Reduction Program 
and renumbering the factors would facilitate alignment and could result 
in confusion when stakeholders review our programs' measure removal 
proposals in the future.
    Comment: Another commenter recommended the loss of NQF-endorsement 
as an additional criterion for removal and encouraged CMS to remove 
measures that fail to pass NQF requirements or are replaced by more 
appropriate competing measures.
    Response: We thank the commenter for this recommendation. As 
previously noted, 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. We review the Program's 
measure set on a regular basis and will continue to review and monitor 
the program's measure set, newly developed measures, and NQF guidance 
to ensure the program's measures remain evidence based. Additionally, 
we proposed these measure removal factors to support alignment with our 
other quality programs, and we do not believe that adopting additional 
measure removal factors for the Hospital Readmissions Reduction Program 
would facilitate alignment and could result in confusion when 
stakeholders review our programs' measure removal proposals in the 
future.
    We intend to be transparent in our assessment of measures under the 
finalized measure removal factor. As mentioned in a previous comment 
response, because we intend to evaluate each measure on a case-by-case 
basis, and each measure has been adopted to fill different needs in the 
Hospital Readmissions Reduction Program, we do not believe it would be 
meaningful to identify a specific set of assessment criteria to apply 
to all measures.
    After consideration of the public comments we received, we are 
finalizing our proposals to adopt for the Hospital Readmissions 
Reduction Program the eight measure removal factors currently in the 
Hospital IQR Program and Hospital VBP Program beginning with the FY 
2020 program year.
5. 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19424 through 
19425), we proposed 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 who die in the month 
of discharge, who will be identified using the previous month's data 
sourced from the State MMA files.\320\
---------------------------------------------------------------------------

    \320\ 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 previously finalized 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 
beneficiary 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. We estimated that the number of misidentified patient 
beneficiaries is very small. We currently predict a 0.2% total increase 
in dual eligible beneficiaries admitted across all participating 
hospitals. Our analysis shows that this very small total increase did 
not have a large impact on peer grouping assignments or payment 
adjustments. Only 20 hospitals (less than 1 percent of open subsection 
(d) hospitals included in the Hospital Readmissions Reduction Program 
with measure results) would change peer group assignments under the 
proposed definition of dual-eligible stays. Of those 20 hospitals, 18 
hospitals would receive a penalty under either definition of dual-
eligible stays, and two hospitals would not receive a penalty under 
either definition. Nine of those 18 hospitals would have a slightly 
higher payment adjustment factor (PAF) and the largest increase would 
be 0.0023. Eight hospitals would have a slightly lower PAF and the 
largest decrease would be 0.0023. One hospital would have the same PAF 
under the revised definition. Based on our analysis, 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

[[Page 42385]]

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 proposed to update this definition for FY 2021 instead of 
FY 2020 because 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 also proposed to revise the definition of ``dual-eligible'' 
codified at 42 CFR 412.152 to incorporate this update.
    We received several public comments on our proposed modification to 
the definition of ``dual-eligible'' beginning in FY 2021.
    Comment: Many commenters supported our proposal to modify the 
definition of a ``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. Many 
commenters noted their beliefs that this update will more accurately 
reflect a hospital's dual eligible population and improve data 
reliability. Some commenters noted their understanding that only a 
small number of dual eligible beneficiaries' status would change as a 
result of the definition modification.
    Response: We thank the commenters for their support. We would also 
like to provide additional information regarding the number of 
beneficiaries' statuses that are expected to change as a result of the 
definition modification. We anticipate about a 0.2% increase in dual 
eligible stays due to the definition modification based on the FY 2019 
performance period (July 1, 2014 through June 30, 2017), or an increase 
from 8,769,611 dual stays under the previous definition to 8,786,367 
dual stays under the modified definition, an increase of 16,756 dual 
eligible stays.
    After consideration of the public comments we received, we are 
finalizing, without modification, that beginning in FY 2021, a ``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, who will be identified using the 
previous month's data sourced from the State MMA files.
6. 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 previously finalized data 
components and other minor changes when payment adjustment factor 
components are impacted.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19425 through 
19426), we proposed 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, the 
proportion of dual-eligibles, 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 from previously 
finalized data sources and files 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 section IV.G.5. of the preamble of this final rule, we 
are finalizing our proposal to amend the definition of ``dual-
eligible'' to account for this data issue. However, we would like to 
clarify that the finalized proposal is not altering the intent of our 
previously finalized policy. Instead, the 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

[[Page 42386]]

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 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. Additionally, we 
would like to specify that decisions regarding substantive and 
nonsubstantive changes will be made in accordance with the recent 
Supreme Court ruling in Azar v. Allina Health Services, 587 U.S. ___, 
139 S.Ct. 1804 (2019). 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.
    We received several public comments on our proposed subregulatory 
process for nonsubstantive updates to the payment adjustment factor 
components.
    Comment: Several commenters supported our proposal to adopt a 
subregulatory process that would allow us to administer the Hospital 
Readmissions Reduction Program efficiently and address nonsubstantive 
requirements such as updating file names and or locations, the use of 
improved data files, or responses to unintended consequences of 
technical programmatic changes.
    Response: We thank the commenters for their support.
    Comment: Several commenters requested that CMS provide additional 
clarity on the proposed subregulatory process, including providing 
further definition of ``nonsubstantive'' and the criteria CMS would use 
to determine if something was nonsubstantive. A few other commenters 
urged CMS to better articulate the circumstances under which 
nonsubstantive changes can be made without formal review and comment 
from public stakeholders to ensure appropriate transparency.
    Response: The proposed subregulatory process is intended to 
establish a mechanism to address nonsubstantive changes to the payment 
adjustment factor components used for the Program. Nonsubstantive 
updates are those that are technical in nature and include, but are not 
limited to, updates to file names or their locations, data processing 
through standard procedures and/or the correction of other minor 
discrepancies in data preparation that are required to implement the 
program, but do not change the intent of the previously finalized 
policies. We believe this subregulatory process is necessary because 
updates to previously finalized data sourcing and technical aspects of 
the components are not always linked to the timing of regulatory 
actions, such as rulemaking. Therefore, this policy will allow for the 
Program to use the most up-to-date, accurate files and data in payment 
adjustment calculations.
    We believe this policy is particularly important as we are 
providing additional transparency into the Program's payment adjustment 
calculations. Beginning in FY 2020, we will begin providing additional 
details regarding the payment adjustment factors in the technical 
appendix of the HSR User Guide to provide greater insight and detail 
about the payment methodology, including information on how non-ERR 
components of the payment adjustment factor are calculated, such as 
information on the data processing used to prepare the analytic files 
for the payment adjustment factor calculations. This information 
includes details about our standard processing rules to produce clean 
data, such as the removal of duplicate stays, and the files used to 
produce aspects of the final payment adjustment factors. Depending on 
the state of the data received, or if files received by the program 
change due to factors outside of the program's control, the program 
would hope for flexibility to amend and update the nonsubstantive 
standard processing rules and data processing to ensure quality data 
are used for the payment adjustment calculations, rather than stall the 
program for lack of a mechanism to improve the data. We would similarly 
expect to use subregulatory policy to address other nonsubstantive 
updates that could have an impact on program operation.
    Comment: Many commenters agreed that CMS should be able to make 
minor program changes without notice-and-comment rulemaking but urged 
CMS to develop safeguards that would require any programmatic changes 
impacting hospital performance or payment to be communicated in advance 
of implementation. These commenters suggested that the annual IPPS 
rulemaking process provides hospitals with a predictable opportunity to 
review and provide input on policy changes that could affect their 
performance in the program. Several commenters also noted that they 
believed that the proposal to change to the ``dual-eligible'' 
definition to allow for a one-month look back was a substantive change 
and would not have been appropriate to implement through the proposed 
subregulatory process.
    Response: We thank the commenters for their support of the 
subregulatory process to address minor, nonsubstantive changes to the 
program, and acknowledge their desire for safeguards to ensure we do 
not use the policy to effect policy change. The proposed subregulatory 
policy is intended to serve as a mechanism to address nonsubstantive 
changes and ensure that the Program can rapidly implement updates to 
technical issues. It is not intended to address substantive policy 
changes outside of notice-and-comment rulemaking, nor would we use it 
in such a manner. As stated in our proposal, we intend to use the 
subregulatory policy for nonsubstantive changes that are purely 
technical in nature. When making determinations on whether to use the 
subregulatory process or not, we intend to adopt a conservative 
approach and ensure that the subregulatory policy is not used to alter 
or amend policies in a manner inconsistent with any previously 
finalized policy.
    Additionally, we understand commenters' concerns about using the 
proposal to update the definition of ``dual-eligible'' in FY 2021 to 
allow for a one-month lookback as an example use case for the 
subregulatory process.

[[Page 42387]]

We continue to believe that when minor, previously unknown 
discrepancies in data are discovered and those discrepancies frustrate 
but do not change the stated intent of our policies, a subregulatory 
process may be the best approach to address them in a timely manner. We 
will make those determinations on a case by case basis. We will take 
commenters' feedback into consideration for any future consideration of 
the application of the subregulatory process.
    Comment: Several commenters expressed concerns that some 
nonsubstantive regulatory changes may result in significant changes for 
hospitals, such as programming measure changes, which could impact 
hospitals' internal monitoring systems. They encouraged CMS to 
establish a process for obtaining stakeholder input prior to making any 
changes to ensure the change is not substantive and to identify any 
burden or unintended consequences that may result from changes using 
the subregulatory process.
    Response: We thank the commenters for this feedback. We plan to 
communicate any subregulatory changes to the payment adjustment factors 
via our standard outreach channels, most notably the HSR User Guides, 
which hospitals receive annually with their HSRs at the start of the 
review and correction period. Additionally, the HSR User Guide is 
posted on QualityNet at the start of the review and correction period. 
Because the subregulatory policy is intended to facilitate technical 
aspects of the program calculations, we expect that subregulatory 
changes will only impact internal CMS processes and do not expect these 
updates to impact hospitals' internal monitoring systems or create 
additional burden for hospitals.
    After consideration of the public comments we received, we are 
finalizing our policy to adopt a subregulatory process to make 
nonsubstantive updates to payment adjustment factor components to 
facilitate the program's operation when minor changes are required, but 
do not substantively impact the program's previously finalized 
policies.
7. 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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19426), we 
proposed, 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.
    We received one comment on the proposed applicable period for FY 
2022.
    Comment: A commenter supported CMS's proposal to continue using a 
three-year performance period for the Program.
    Response: We thank the commenter for the support.
    After consideration of the public comments that we received, we are 
finalizing the applicable periods for the Hospital Readmissions 
Reduction Program as proposed.
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 previously described 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 proposed to continue to 
exclude admissions for patients enrolled in Medicare Advantage, as 
identified in the Medicare Enrollment Database.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19426 through 
19427), for FY 2020, we proposed 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 estimated FY 
2020 readmissions payment adjustment factors for this final rule, we 
used the proportion of dual-eligibles, excess readmission ratios, and 
aggregate payments for each condition/procedure and all discharges for 
applicable hospitals from the FY 2020 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

[[Page 42388]]

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 the proposed rule, for FY 2020, we proposed 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 within FY 2018 with discharge dates that are on or 
before June 30, 2018.
    We did not receive any public comments on our proposal to use the 
MedPAR data from July 1, 2015 through June 30, 2018 for the FY 2020 
Hospital Readmissions Reduction Program calculations. Therefore, we are 
finalizing the use of the MedPAR data from July 1, 2015 through June 
30, 2018 for FY 2020 as proposed.
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] TR16AU19.000

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. In the FY 
2020 IPPS/LTCH PPS proposed rule (84 FR 19427), we did not propose 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
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19427 through 
19128), we noted that 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

[[Page 42389]]

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 final 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.
    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.
    We received a number of public comments on our decision to provide 
hospitals with information from two disparity methods through 
confidential hospital-specific reports.
    Comment: Many commenters supported CMS' plan to continue to provide 
hospitals with confidential hospital specific reports on the Pneumonia 
Readmission measure using the two disparity methods and to expand that 
effort to include five additional readmission measures. Several of 
these commenters specifically believed the effort would be useful to 
hospitals. Some commenters noted that it would help hospitals recognize 
potential disparities in care, implement targeted improvement efforts, 
and reduce disparities in the quality of care for this vulnerable 
population. A commenter specifically noted that differences in care 
based on beneficiaries' dual-eligible status is a reasonable social 
risk factor to begin assessing for disparities in care for quality 
measurement and value-based purchasing programs.
    Response: We thank the commenters for their support for our efforts 
to provide data on disparities to hospitals. At present, dual-eligible 
status is the only social risk factor used for assessing disparities in 
hospital outcomes. We continue to explore the use of additional social 
risk factors for the hospital disparity methods.
    Comment: Several commenters requested that CMS provide enough 
opportunity to review and understand the stratified performance and 
methodology used to develop these reports. They appreciated CMS's 
intention to remain engaged with stakeholders and to solicit feedback 
on hospital experiences and recommendations, including the format and 
usefulness of these reports. One commenter requested that CMS provide 
educational materials to help stakeholders interpret the information.
    Response: We thank the commenters for their feedback. We intend to 
continue to provide educational resources for stakeholders as they 
continue to become familiar with the data provided from the two 
disparity methods provided in the confidential reports, including 
measure methodology overview, fact sheet, and frequently asked 
questions resources.\321\ For additional information on the reliability 
of the measure data using the two disparity methods, we refer readers 
to the Hospital IQR Program's discussion in section VIII.A.9. of the 
preamble of this final rule.
---------------------------------------------------------------------------

    \321\ QualityNet. Confidential Reporting Overview: Disparity 
Methods. Available at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228776708906.
---------------------------------------------------------------------------

    Comment: A commenter suggested that attribution details for each 
measure be included within the respective programs' measures' technical 
specifications guides before publicly reporting data using the two 
disparity methods because they believed it is important to be clear 
about who is responsible for the reported outcomes and performance 
rates.
    Response: To minimize the possibility of confusion, the attribution 
used when applying the disparity methods mirror those used by the 
corresponding measure in the Hospital Readmissions Reduction Program. 
Attribution details and other technical specifications for the 
readmission measures are publicly available in Measure Methodology 
Reports on our QualityNet website.\322\
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    \322\ https://www.qualitynet.org/dcs/ContentServer?cid=%201219069855841&pagename=QnetPublic%2FPage%2FQnetTier3&c=Page.
---------------------------------------------------------------------------

    Comment: A commenter expressed the belief that additional 
information in the confidential HSRs will help CMS make appropriate 
decisions as it considers disparity and risk-adjustment. A commenter 
encouraged CMS to study the differences between the disparity 
methodologies and Hospital Readmissions Reduction Program methodology.
    Response: We thank the commenters for their feedback. We intend to 
continue to engage with hospitals and relevant stakeholders about their 
experiences with and recommendations for the data from the two 
disparity methods and to ensure the reliability of such data. We 
appreciate commenter's feedback regarding the harmonization with 
existing quality programs including the Hospital Readmission Reduction 
Program. We believe these two disparity methods complement each other 
in that they use the same social risk factor and serve two 
complementary purposes. The Hospital Readmissions Reduction Program 
stratifies hospitals based on dual-eligible proportion and compares a 
hospital's excess readmissions to other hospitals in its peer group to 
assess a hospital's performance, as mandated by the 21st Century Cures 
Act, whereas the disparities methods discussed in this section 
highlight opportunities to close the gap in performance among different 
patient groups. We also reiterate that the confidential reporting of 
disparity factors does not impact the payment adjustment factors for 
the Hospital Readmissions Reduction Program. We will continue to engage 
with hospitals and relevant stakeholders about their experiences with 
the two disparity methods.
    Comment: Several commenters urged CMS to seek recommendations on 
the measure data and ensure that the data is reliable and easily 
understandable before any future proposals to publicly report the 
information. A commenter strongly supported sharing confidential HSR 
reports with the public for both the within-hospital and across-
hospital disparity information because it believes this data should be 
available and transparent to the public and further stated its 
opposition to the use of any social risk-adjustment in measures. 
Another commenter believed this information should only be made public 
after the hospitals have had time to review and correct their data and 
that

[[Page 42390]]

unadjusted data should be publicly available to enable communities to 
study and improve interventions to address disparities. A few 
commenters discouraged the use of any unadjusted data in public 
reporting or pay-for-performance measures.
    Response: We thank the commenters for their feedback. We have not 
yet determined future plans with respect to publicly reporting data 
using the two disparity methods and intend to continue to engage with 
hospitals and relevant stakeholders about their experiences with and 
recommendations for the data from the two disparity methods and to 
ensure the reliability of such data before proposing to publicly 
display results from the two disparity methods in the future.
    Comment: A few commenters expressed concern with stratifying 
measure data based only on dual eligible status. A commenter noted that 
dual eligibility may be sensitive to differences in state coverage and 
benefit policies, and may not fully reflect the level of poverty in 
communities.
    Response: At present, dual eligibility is the only social risk 
factor used in the disparity methods. We have focused our initial 
efforts on providing disparity results based on dual eligible status 
because of strong evidence demonstrating worse health outcomes among 
dual eligible Medicare beneficiaries, and because reliable information 
is readily available in CMS administrative claims data. Because dual 
eligible status is available in CMS administrative data, it also does 
not require any additional reporting by hospitals for the purposes of 
applying the disparity methods. With respect to commenter's concern 
about the differences in state policies, the disparity methods evaluate 
differences in hospital quality only for adults 65 years and older. 
Federal minimum standards for allowable income and assets exist for 
older adults, contributing to more uniformity in Medicaid eligibility 
status across states relative to other groups, although state-level 
differences in eligibility standards for optional coverage pathways and 
benefits are noted. Our internal analyses accounting for state Medicaid 
eligibility policies reveal no substantive differences in the disparity 
method results. We continue to examine the impact of state Medicaid 
policies on the disparity methods.
    We thank the commenters for their feedback and suggestions. We will 
take them into account and consider commenters' views as we develop 
future policies regarding the confidential reporting of disparity data. 
For additional information on the confidential reporting of stratified 
data for hospital quality measures, we refer readers to the Hospital 
IQR Program's discussion in section VIII.A.9. of the preamble of this 
final rule.
12. Revisions of Regulatory Text
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19428), we 
proposed to revise 42 CFR 412.152 to reflect our proposed policies and 
to codify previously finalized policies. Specifically, we proposed 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 proposed 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 proposed 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 for a Medicare-
dependent, small rural hospital that receives payments under Sec.  
412.108(c) and does not include the difference between the hospital-
specific payment rate and the Federal payment rate determined under the 
subpart for a sole community hospital that receives payment under Sec.  
412.92(d).\323\ This proposal was intended to align the regulatory text 
with section 1886(q)(2)(B)(i) of the Act by specifying the differential 
treatment following the expiration of the special treatment for 
Medicare-dependent, small rural hospitals for FY 2013 in the statute.
---------------------------------------------------------------------------

    \323\ Please note that this sentence was updated via the 
Correction Notice (CMS-1716-CN) published on June 18, 2019. We refer 
readers to the correction notice for more information.
---------------------------------------------------------------------------

    We proposed 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 proposed 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)).
    As discussed in section IV.G.5. of the preamble of this final rule, 
we received a number of supportive comments on our proposal to update 
the definition of ``dual-eligible'' beginning in FY 2021, which we 
addressed previously in this rule. We did not receive any public 
comments on our other proposals to update the regulatory text to align 
with previously finalized policies.
    After consideration of the public comments we received, we are 
finalizing our proposal to update the regulatory text as proposed.

H. Hospital Value-Based Purchasing (VBP) Program: 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.

[[Page 42391]]

    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 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). Then, we will 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 published proxy value-based incentive payment adjustment 
factors in Table 16 associated with the FY 2020 IPPS/LTCH PPS proposed 
rule (which is available via the internet on the CMS website). We are 
publishing updated proxy value-based incentive payment adjustment 
factors in Table 16A associated with this final 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 
updated slope of the linear exchange function used to calculate the 
proxy value-based incentive payment adjustment factors in Table 16A is 
2.8392502375. This slope, along with the estimated amount available for 
value-based incentive payments, has been updated based on the March 
2019 update to the FY 2018 MedPAR file and is also published in Table 
16A (which is available via the internet on the CMS website).
    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 1 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. In the FY 2020 IPPS/
LTCH PPS proposed rule (84 FR 19429), we did not propose any changes to 
these policies.
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 all of 
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 <=0.10.\324\
---------------------------------------------------------------------------

    \324\ We previously adopted the two criteria for determining the 
``topped-out'' status of Hospital VBP Program measures in the FY 
2015 IPPS/LTCH PPS final rule (79 FR 50055).
---------------------------------------------------------------------------

     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.
     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

[[Page 42392]]

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. In the FY 2020 IPPS/LTCH PPS 
proposed rule (84 FR 19429), we did not propose any changes to these 
policies.
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 to the tables in this section showing 
summaries of previously adopted measures for the FY 2022 and FY 2023 
program years. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19429 
through 19431), we did not propose to add new measures to or remove 
measures from the Hospital VBP Program.
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BILLING CODE 4120-01-C
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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19431), we did 
not propose any changes to these policies.

[[Page 42394]]

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, 5 years prior to the applicable fiscal program year, to June 30, 2 
years prior to the applicable fiscal program year, and the baseline 
period runs for 36 months from July 1, 10 years prior to the applicable 
fiscal program year, to June 30, 7 years prior to the applicable fiscal 
program year. For the COMP-HIP-KNEE measure, the performance period 
runs for 36 months from April 1, 5 years prior to the applicable fiscal 
program year, to March 31, 2 years prior to the applicable fiscal 
program year, and the baseline period runs for 36 months from April 1, 
10 years prior to the applicable fiscal program year, to March 31, 7 
years prior to the applicable fiscal program year.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19431), we did 
not propose any changes to the length of these performance or baseline 
periods.
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, 4 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, 8 years prior to the applicable fiscal program year, to June 30, 6 
years prior to the applicable fiscal program year.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19431), we did 
not propose any changes to these policies.
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 that runs on the 
calendar year 4 years prior to the applicable program year for the FY 
2019 program year and subsequent years.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19431 through 
19432), we did not propose any changes to these policies.
f. Summary of Previously Adopted Baseline and Performance Periods for 
the FY 2022 Through FY 2025 Program Years
    These tables summarize the baseline and performance periods that we 
have previously adopted.
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BILLING CODE 4120-01-C
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

[[Page 42396]]

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 all of 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.
     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 Newly Established 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 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19435 through 
19437), 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 estimated additional performance standards for the FY 2022 program 
year. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19436), we 
noted that the numerical values for the performance standards for the 
Safety and Person and Community Engagement domains for the FY 2022 
program year were estimates based on the most recently available data, 
and that we intended to update the numerical values in the FY 2020 
IPPS/LTCH PPS final rule.
    The previously established and newly established performance 
standards for the measures in the FY 2022 program year are set out in 
these tables.
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[[Page 42397]]


    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.
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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 these tables.
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[[Page 42398]]


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 
this table.
[GRAPHIC] [TIFF OMITTED] TR16AU19.174

e. Newly Established Performance Standards for Certain Measures for the 
FY 2025 Program Year
    As previously discussed, 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 this table.

[[Page 42399]]

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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. In the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19439), we did not propose any changes to 
these domain weights.
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. In the FY 2020 IPPS/LTCH PPS proposed rule 
(84 FR 19439), we did not propose any changes to these domain weights.
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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19439), we did 
not propose any changes to these policies.
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). In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19439), we did not propose any changes to these policies.
(2) Summary of Previously Adopted Minimum Numbers of Cases
    The previously adopted minimum numbers of cases for these measures 
are set forth in this table.

[[Page 42400]]

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e. 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 are 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 3rd quarter 
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 final rule, the HAC 
Reduction Program is finalizing additional refinements to its 
validation process for the CDC NHSN HAI measures in the HAC Reduction 
Program and discusses clarifications regarding validation processes.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19440), in order 
to streamline and simplify processes across hospital programs, we 
proposed 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. We stated that this proposed start date would 
align 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 noted 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 proposed that the Hospital VBP Program would 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 noted 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 stated our belief that using the HAC Reduction Program 
review and correction process would 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 we noted earlier, 
the HAC Reduction Program's validation processes are intended to 
reflect, to the

[[Page 42401]]

greatest extent possible, the processes previously established for the 
Hospital IQR Program. We referred 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.\325\ We stated our belief that 
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 also stated our belief 
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.
---------------------------------------------------------------------------

    \325\ 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 final rule for changes to the validation selection 
methodology and clarifications to the validation filtering 
methodology for the HAC Reduction Program.
---------------------------------------------------------------------------

    We referred 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 final rule for 
additional information about HAC Reduction Program data collection, 
review and correction, and refinements to validation policies for the 
CDC NHSN HAI measures.
    Comment: Several commenters supported using the same HAI measure 
administrative requirements for the Hospital VBP Program as used in the 
HAC Reduction Program. Several commenters specifically supported our 
proposal to 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. A few commenters specifically supported 
using the same policies and processes as the HAC Reduction Program for 
submitting, reviewing, correcting, and validating the HAI data within 
the Hospital VBP Program.
    A few commenters believed using the same administrative 
requirements for the CDC NHSN HAI measures across the two programs 
would bring more consistency across programs. A few commenters believed 
using the same administrative requirements used in the HAC Reduction 
Program will help reduce administrative burden associated with the 
programs. A commenter believed that removing redundancy will lead to 
more focused quality reporting and targets for hospitals.
    A few commenters supported adopting the HAC Reduction Program 
processes for validating the CDC NHSN HAI measures in the Hospital VBP 
Program because they believed the validation process under the HAC 
Reduction Program is sufficient for ensuring data integrity. A 
commenter supported relying on the HAC Reduction Program validation 
process and data to ensure the accuracy of the CDC NHSN HAI measure 
data in the Hospital VBP Program to avoid any duplication of validation 
processes and efforts since the HAI measures continue to remain in two 
payment programs.
    Response: We thank commenters for their support.
    Comment: A few commenters requested clarification on the proposal 
for the Hospital VBP Program to 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 does not affect the 
previously adopted and differing measurement periods used for 
calculating performance under the Hospital VBP and HAC Reduction 
Programs. Such commenters noted that the measurement period for the CDC 
NHSN HAI measures is 2 calendar years for the HAC Reduction Program and 
1 calendar year for the Hospital VBP Program.
    Response: We did not propose any changes to the previously adopted 
baseline or performance periods of the CDC NHSN HAI measures for the 
Hospital VBP Program. In the FY 2017 IPPS/LTCH PPS final rule, we 
adopted a performance period for the CDC NHSN HAI measures in the 
Safety domain 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 (81 FR 57000). We also refer 
readers to section IV.H.3.f of the preamble of this final rule for a 
summary of previously adopted baseline and performance periods for the 
FY 2022 through FY 2025 Hospital VBP Program years.
    Comment: Several commenters requested that CMS clarify how the 
results of the HAI measure validation in the HAC Reduction Program 
would affect hospital scoring and ability to participate in the 
Hospital VBP Program. Several commenters noted that hospitals that do 
not meet HAI measure validation requirements will receive the lowest 
possible HAC Reduction Program score for the measure(s) on which they 
do not meet validation requirements, that the Hospital VBP Program has 
both baseline and performance periods, and the Hospital VBP Program 
statute expressly excludes from participation in the Hospital VBP 
Program hospitals that do not meet Hospital IQR Program administrative 
requirements. A commenter expressed a belief that even though the 
process is the same across programs, CMS should evaluate compliance 
separately for each program. One commenter expressed concern that using 
the same measure or a variation of it in multiple quality-based 
programs would inappropriately penalize hospitals multiple times for 
the same issue. Several commenters urged CMS to engage with 
stakeholders to determine a process for scoring hospitals that fail HAI 
measure validation in the Hospital VBP Program.
    Response: While there is no statutory provision that automatically 
excludes a hospital from participation in the Hospital VBP Program if 
it does not meet HAC Reduction Program measure validation requirements, 
we intend to look closely at the issue of whether a hospital not 
meeting HAI validation requirements in the HAC Reduction Program has 
unintended consequences for its participation in the Hospital VBP 
Program and if so, whether we should consider the feasibility of 
changes to the Hospital VBP scoring methodology that would address 
those unintended consequences. Any such changes to the Hospital VBP 
Program policies would be proposed in future rulemaking. We appreciate 
commenters' questions and concerns and will review the Hospital VBP 
Program policies accordingly.
    Comment: A few commenters expressed concern with the proposal for 
the Hospital VBP Program to rely on the HAC Reduction Program 
validation of the CDC NHSN HAI measures, expressing concern with the 
adequacy of the HAC Reduction Program methods for validation of the 
data quality and noting that the changes proposed by the HAC Reduction 
Program in the FY 2019 IPPS/LTCH PPS proposed rule were solely on the 
selection process of hospitals for validation and not the methods for 
validation of the data elements.
    Response: As noted in the FY 2020 IPPS/LTCH PPS proposed rule (84 
FR 19440), the validation processes adopted for the CDC NHSN HAI 
measures in the HAC Reduction Program are intended to reflect, to the 
greatest extent possible, the processes previously established for the 
Hospital IQR Program, therefore, we continue to

[[Page 42402]]

believe the validation processes adopted for the CDC NHSN HAI measures 
in the HAC Reduction Program are sufficient for purposes of ensuring 
the accuracy of CDC NHSN HAI measure data under the Hospital VBP 
Program. We also note in section IV.I.7. of the preamble of this final 
rule, the HAC Reduction Program is finalizing additional refinements to 
its validation selection methodology for the CDC NHSN HAI measures in 
the HAC Reduction Program and discusses clarifications regarding 
validation processes. We refer readers to section IV.I.7. of the 
preamble of this final rule for further discussion of the CDC NHSN HAI 
measure validation under the HAC Reduction Program.
    Comment: A few commenters expressed concern with using the same 
measures in both the Hospital VBP Program and HAC Reduction Program 
because of redundancy and a belief that it is inappropriate to penalize 
hospitals multiple times for the same issue, with a commenter 
requesting that CMS consider consolidating the programs to reduce 
duplication.
    Response: In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41449 
through 41452), we describe our previous proposal to de-duplicate the 
five HAI measures and the CMS PSI 90 measure from the Hospital VBP 
Program to reduce program complexity for hospitals, and our decision in 
response to stakeholder concerns to not finalize removal of these 
measures from the Hospital VBP Program. We stated that these measures 
cover topics of critical importance to quality improvement and patient 
safety in the inpatient hospital setting, and track infections and 
adverse events that could cause significant health risks and other 
costs to Medicare beneficiaries, and therefore, it is appropriate and 
important to provide appropriate incentives for hospitals to avoid them 
through inclusion in more than one program (83 FR 41450). We refer 
readers to the FY 2019 IPPS/LTCH PPS final rule (83 FY 41449 through 
41452) for further information regarding the decision to not remove the 
CDC NHSN HAI measures and CMS PSI 90 measure from the Hospital VBP 
Program. We also note that the Hospital VBP Program and HAC Reduction 
Program are each separately required by the Act. The Hospital VBP 
Program, required under section 1886(o) of the Act, is an incentive 
program that redistributes a portion of the Medicare payments made to 
hospitals under the IPPS based on their performance on a variety of 
measures. The HAC Reduction Program, as outlined in section 1886(p) of 
the Act, reduces payments to the lowest quartile of hospitals for 
excess hospital-acquired conditions in order to increase patient safety 
in hospitals.
    Comment: A commenter urged CMS to provide greater detail on the 
future public reporting of the CDC NHSN HAI measures on Hospital 
Compare, specifically with regard to data refresh, reporting frequency, 
and display of hospital performance that is evaluable and consumer 
friendly.
    Response: Section 1886(o)(10)(A) of the Act requires the Hospital 
VBP Program to make information available to the public regarding the 
performance of individual hospitals, including performance with respect 
to each measure that applies to the hospital, on the Hospital Compare 
website in an easily understandable format. We also note that section 
1886(p)(6) of the Act requires the HAC Reduction Program to make 
information available to the public regarding hospital-acquired 
conditions of each applicable hospital on the Hospital Compare website 
in an easily understandable format. As discussed in the FY 2019 IPPS/
LTCH PPS final rule, we intend to maintain as much consistency as 
possible in how the measures are currently reported on the Hospital 
Compare website, including how they are displayed and the frequency of 
reporting. We intend to continue making CDC NHSN HAI measure data 
available to the public on a quarterly basis as soon as it is feasible 
on CMS websites such as the Hospital Compare website and through 
downloadable files at: https://data.medicare.gov/, after a 30-day 
preview period. We appreciate commenters' feedback and will consider it 
as we continue to evaluate the presentation of information on the 
Hospital Compare website.
    After consideration of the public comments we received, we are 
finalizing, as proposed, 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, and to use the same 
processes adopted by the HAC Reduction Program for hospitals to review 
and correct data for the CDC NHSN HAI measures and rely on HAC 
Reduction Program validation to ensure the accuracy of CDC NHSN HAI 
measure data used in the Hospital VBP Program.
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 and to the same final rule (78 FR 50708 through 50709) for a 
detailed discussion of the statutory basis for the Program. For 
additional descriptions of our previously finalized policies for the 
HAC Reduction Program, we also refer readers to the FY 2014 IPPS/LTCH 
PPS 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 the HAC Reduction Program's implementation, 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 policies (items (5) and (6)) were 
newly finalized in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41472 
through 41492).
    We have also 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 final rule, we are finalizing our proposal to update 
42 CFR 412.172(f) to reflect policies that we 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

[[Page 42403]]

represent ``never events'' \326\ 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 needed 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 manage 
these administrative processes independently and to receive CDC NHSN 
data beginning in CY 2020, with validation beginning with Q3 CY 2020 
infectious events.
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    \326\ 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.
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    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19440 through 
19446), we proposed 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 specifically proposed 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 to date. 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 also finalized the use of 
the CMS PSI 90 measure. These previously finalized measures, with their 
full measure names, are shown in this table.\327\
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    \327\ 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.177

    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19441 through 
19442), we did not propose to add or remove any measures. However, we 
received several comments regarding the HAC Reduction Program's measure

[[Page 42404]]

set. We would like to reassure stakeholders that we review the HAC 
Reduction Program's measure set on an ongoing basis to ensure that the 
program continues to maintain a parsimonious set of meaningful quality 
measures. While we consider these comments out of scope, we will take 
these comments into consideration for future policy making.
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 did not propose to adopt 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. Measure Removal Factors
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19442), while we 
did not propose to remove any measures, we proposed 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 proposed 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.\328\
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    \328\ 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 initially 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, and if necessary, will proceed via notice and comment 
rulemaking.
---------------------------------------------------------------------------

     Factor 7. Measure is not feasible to implement as 
specified.
     Factor 8. The costs associated with a measure outweigh the 
benefit of its continued use in the program.\329\
---------------------------------------------------------------------------

    \329\ 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.
    We received several public comments on our proposed measure removal 
factors.
    Comment: Several commenters supported the adoption of the eight 
measure removal factors previously adopted by the Hospital IQR Program 
and the Hospital VBP Program into the HAC Reduction Program. A few 
commenters stated that adoption of these factors would allow for 
consistency and alignment in measure evaluation methodology across 
programs. Some commenters also believed that the factors are well-
established and ensure that a variety of valid reasons to remove a 
measure are considered by CMS. A few commenters also believed the 
proposal would reduce burden and increase efficiency.
    Response: We thank the commenters for their support.
    Comment: Some commenters encouraged CMS be transparent in how these 
factors are applied when a measure is considered for removal and urged 
CMS to use the factors as a guide to removal rather than an automatic 
process.
    Response: As we stated in the proposed rule and as previously 
described, we consider these removal factors as considerations for 
removal, not firm requirements. We value transparency in our processes, 
and plan to seek stakeholder input through education and outreach, 
rulemaking, and other stakeholder engagement before removing measures.
    Comment: A commenter opposed the adoption of the removal criteria 
because this commenter believed the criteria lack specificity and 
empirical support. The commenter believed that CMS should include more 
detail on how the removal factors apply to beneficiaries and develop 
and publicly share how the terminology in each criterion is 
operationalized. The commenter requested transparency around how such 
terms are tested and what results will empirically determine whether 
the criterion is met or not.

[[Page 42405]]

    Response: As we discussed in the proposed rule, the removal factors 
are intended to be considerations that we take into account when 
deciding whether or not to remove measures. There may be circumstances 
in which a measure that meets one or more factors for removal should be 
retained regardless of the criteria because any benefit of removing a 
measure could be outweighed by benefits of retaining the measure. We 
intend to take multiple considerations and stakeholder feedback into 
account when determining whether to propose a measure for removal under 
any of the removal factors.
    Comment: Several commenters supported removal Factor 1: ``Measure 
performance among hospitals is so high and unvarying that meaningful 
distinctions and improvement in performance can no longer be made 
(``topped-out'' measures),'' but encouraged CMS to enhance the removal 
factor by adding quantitative criteria or empirical criteria similar to 
the criteria adopted by Hospital IQR and Hospital VBP Programs. Some 
commenters specifically recommended adding the ``topped out'' 
definition adopted by the Hospital IQR and Hospital VBP Programs (79 FR 
50055):
     The difference in performance between the 75th and 90th 
percentile is statistically indistinguishable. In general, this means 
that the 75th and 90th percentile scores differ by less than two 
standard deviations.
     The truncated coefficient of variation (TCV) is less or 
equal to 0.10. Our definition of ``truncated'' is to remove the top and 
bottom 5 percent of hospitals before calculating the CV. Applying these 
two criteria to current data shows that the program's measure set may 
already be ``topped out'' in performance.
    Response: Because the HAC Reduction Program focuses on patient 
safety and ``never events,'' the empirical criteria developed for the 
Hospital IQR and Hospital VBP Programs may not be appropriate for 
hospital-acquired conditions. The HAC Reduction Program strives to 
encourage hospitals to reduce HACs, not within a statistical standard, 
but to as close to zero as possible. While we do not believe that the 
Hospital IQR Program or Hospital VBP Programs' empirical standards are 
appropriate for HAC Reduction Program at this time, we will consider 
whether other statistical standards may be more appropriate for the HAC 
Reduction Program in the future. Therefore, we believe adding 
quantitative or empirical criteria at this time would be contrary to 
our holistic approach.
    Comment: A few commenters opposed adoption of measure removal 
Factor 1, ``measure performance among hospitals is so high and 
unvarying that meaningful distinctions and improvement in performance 
can no longer be made (``topped out'' measures).'' A commenter believed 
that removal of a measure immediately upon a ``topped out'' analysis 
would eliminate the ability to determine whether performance regresses 
or that the removal of the measure may result in lower quality of care 
over the long term. The commenter recommended CMS either consolidate 
measures that meet the ``topped out'' criteria but are still considered 
meaningful to stakeholders into a composite measure or include them as 
an evidence-based standard in a verification program. Another commenter 
believed that many measures are ``never events'' and a low prevalence 
still can be unacceptably high. The commenter also believed the 
quantitative criteria CMS uses for determining topped out status is 
problematic, as beneficiaries and payers often avoid the lowest 
performers, and that CMS's topped out methodology does not account for 
variation in lower performing percentiles; additionally, a potential 
high degree of variation outside of the narrow 75th to 90th percentiles 
is unaccounted for.
    Response: As we discussed in the proposed rule, the removal factors 
are intended to be considerations taken into account when deciding 
whether or not to remove measures but are not firm requirements. There 
may be circumstances in which a measure that meets one or more factors 
for removal should be retained regardless, because any benefit of 
removing a measure could be outweighed by other benefits to retaining 
the measure. We intend to take multiple considerations into account 
when determining whether to propose a measure for removal under Factor 
1 or any of the other removal factors. Additionally, we note that we 
have intentionally not provided numerical guidelines for Factor 1 to 
retain flexibility when assessing measures.
    Comment: Several commenters supported the adoption of Factor 8 
(``costs associated with a measure outweigh the benefit of its 
continued use in the program'').
    Response: We thank the commenters for the support.
    Comment: A few commenters raised specific concerns regarding Factor 
8 (``the costs associated with the measure outweigh the benefit of its 
continued use in the program''). A commenter supported the addition of 
Factor 8, but asked CMS to seek stakeholder input specifically each 
time Factor 8 is considered for application. Another commenter opposed 
the adoption of Factor 8 unless ``costs'' and ``benefits'' are defined 
as ``costs to Medicare beneficiaries and the public'' and ``benefits to 
Medicare beneficiaries and the public.'' A few commenters expressed the 
belief that CMS should develop empirical criteria to determine whether 
this factor has been met. A few commenters strongly opposed Factor 8 
because of their belief that it is extremely subjective, lacks clear 
criteria and guidelines, and that costs should not be the driving 
factor when deciding to remove a measure. A few commenters opposed 
Factor 8, noting their belief that cost should not be a factor in 
whether measures should be in a quality reporting program and that the 
other criteria were sufficient.
    Response: We thank the commenters for sharing these concerns 
regarding Factor 8. We value transparency in our process and will seek 
stakeholder input prior to removing any measures from the HAC Reduction 
Program. We intend to be transparent in our assessment of measures 
under this measure removal factor. There are various considerations of 
costs and benefits, direct and indirect, financial and otherwise, that 
we will evaluate in applying removal Factor 8, and we will take into 
consideration the perspectives of multiple stakeholders. However, 
because we intend to evaluate each measure on a case-by-case basis, and 
each measure has been adopted to fill different needs in the HAC 
Reduction Program, we do not believe it would be meaningful to identify 
a specific set of assessment criteria to apply to all measures. We 
believe costs include costs to stakeholders such as patients, 
caregivers, providers, CMS, and other entities. In addition, we note 
that the benefits we will consider center on benefits to patients and 
caregivers as the primary beneficiaries of our quality reporting and 
value-based payment programs. When we propose to remove a measure under 
this measure removal factor, we will provide information on the costs 
and benefits we considered in evaluating the measure.
    Comment: A commenter recommended that CMS adopt an additional 
measure removal factor, considering ``whether the measure is important 
to beneficiaries or the public at large.'' The commenter believed that 
the measure removal policy should center on the best interests of 
Medicare beneficiaries and Medicaid recipients and then the best 
interests of the public at large. The commenter recommended that the 
additional measure removal

[[Page 42406]]

factor be Factor 1 to denote its primary importance, and the proposed 
measure removal factors be renumbered.
    Response: We will consider the perspectives of all stakeholders 
when applying any of the measure removal factors, and importance to 
beneficiaries and the public at large are certainly part of this 
consideration.
    We intend to be transparent in our assessment of measures under the 
finalized measure removal factor. As mentioned in a previous comment 
response, because we intend to evaluate each measure on a case-by-case 
basis, and each measure has been adopted to fill different needs in the 
HAC Reduction Program, we do not believe it would be meaningful to 
identify a specific set of assessment criteria to apply to all 
measures. Additionally, we proposed these measure removal factors in 
alignment with our other quality programs, and we do not believe that 
adopting an additional measure removal factor for HAC Reduction Program 
and renumbering the factors would facilitate that alignment and could 
result in confusion when stakeholders review our programs' measure 
removal factors in the future.
    After consideration of the public comments we received, we are 
finalizing our proposals to adopt for the HAC Reduction Program the 
eight measure removal factors currently in the Hospital IQR Program and 
Hospital VBP Program beginning with the FY 2020 program year.
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 policies 
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 additional discussion of these requirements 
\330\ and to QualityNet for the current reporting requirements and 
deadlines.
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    \330\ 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 Reduction Program beginning on January 1, 2020. The IPPS 
Quality Reporting Programs Measure Exception Form can be found 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19442 through 
19443), we did not propose 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19443), we did 
not propose any change to our current administrative policies regarding 
the review and correction of claims data or chart-abstracted CDC NHSN 
HAI data.
7. 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 all of the following HAC Reduction Program 
validation processes:
     Measures Subject to Validation.
     Educational Review Process.
     Calculation of Confidence Intervals.
     Application of Validation Scoring and Penalty.

[[Page 42407]]

     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] TR16AU19.178

    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19443 through 
19445), we proposed to change the number of hospitals selected under 
the validation targeting methodology and provided two clarifications to 
this validation process.
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    \331\ The CMS Clinical Data Abstraction Center (CDAC) performs 
the validation.
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b. 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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19444), while we 
retained the same targeting criteria that we finalized last year, we 
proposed 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 
hospital target. This proposed policy would allow us to select only 
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.
    Comment: Several commenters supported the change in number of 
hospitals selected for targeted validation from exactly 200 hospitals 
to ``up to 200 hospitals.'' The commenters cited reasons such as 
increased flexibility, neutral effect on statistical reliability, 
avoidance of duplicative efforts, and avoidance of arbitrary selection.
    Response: We thank the commenters for the support.
    After consideration of the public comments we received, we are 
finalizing our proposal to change the number of hospitals selected for 
targeted validation from ``200'' to ``up to 200.''
c. Clarifications to the Validation Selection Methodology
    As discussed in section IV.I.7.a. of the preamble of this final 
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 
was prudent. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19444), 
in addition to proposing to change the number of targeted hospitals 
from ``200'' to ``up to 200'', we also clarified 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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19444), we 
clarified 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

[[Page 42408]]

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 in the sample, whereas the Hospital IQR 
Program will remove from the sample 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 final rule for more information on the Hospital IQR 
Program's validation policies.
    After the random selection process, an additional targeted \332\ 
aggregated sample of up to 200 hospitals will be selected for the HAC 
Reduction and Hospital IQR Programs' validation processes using 
existing targeting criteria.
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    \332\ 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.
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    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 finalized 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 is the number of measures that are 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 finalized proposal 
help meet that expectation.
    We received a number of comments on our validation policy 
proposals.
    Comment: A few commenters supported the proposal to create a 
combined HAC Reduction Program and Hospital IQR Program pool of 
hospitals for validation selection to ensure that hospitals do not 
incur duplicative validation requirements during the same validation 
period.
    Response: We reiterate that selected hospitals will be validated 
for both the CDC NHSN HAI measures for the HAC Reduction Program and 
the Hospital IQR Program's chart-abstracted measures, but this 
clarification avoids increasing provider burden because the total 
number of hospitals selected for validation is not increasing, nor is 
the number of measures and cases that are subject to validation for the 
selected hospitals prior to deduplication.
    Comment: A few commenters believed that the proposal does not 
extend far enough to ensure that hospitals do not incur duplicative 
validation requirements. The commenters cited the excess burden of 
validation for separate programs with overlapping timeframes, 
specifically for Inpatient Quality Reporting Program validation and 
Outpatient Quality Reporting Program validation. Another commenter 
suggested that CMS also consider state validation policies and the 
associated burden in these policies.
    Response: The Hospital Inpatient Quality Reporting Program and the 
Hospital Outpatient Quality Reporting Program are separate Programs 
with separate validation requirements. We continue to believe that 
validation is important to both programs and the states but will keep 
the recommendations under consideration when considering future 
policies for the HAC Reduction Program.
    After consideration of the public comments we received, we are 
finalizing our proposal to use a combined HAC Reduction Program and 
Hospital IQR Program validation pool of subsection (d) hospitals and 
use an aggregated random sample selection methodology.
d. 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 HAI events, or those that meet CDC NHSN 
HAI criteria. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19444), 
in order to better target true events for CDC NHSN HAI validation, we 
proposed 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 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 (or non-
hospital acquired) for CLABSI and CAUTI.\333\ Therefore, we proposed to 
clarify that we would 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

[[Page 42409]]

gaming or other inaccurate reporting of quality data.\334\
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    \333\ 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.
    \334\ 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.
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    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 received several public comments on this topic.
    Comment: Many commenters supported the proposed filtering 
methodology for CLABSI/CAUTI, with most citing reduced provider burden 
and a focus on true hospital-acquired infections rather than community-
acquired or community-onset infections.
    Response: We thank the commenters for the support.
    Comment: A few commenters expressed concerns about potential 
unintended consequences from the filtering methodology. A commenter 
agreed that the new filtering methodology will help CMS better 
understand over and under reporting of CLABSI and CAUTI but expressed 
concern that accurate clinical designation of both community-onset and 
hospital acquired infections are important. A few commenters expressed 
concern that the potential for even less validation samples may 
negatively impact smaller hospitals with very few HAIs despite the new 
equal weighting methodology.
    Response: We understand the commenters' concerns about how a filter 
could potentially impact the MRSA/CDI sample if only `Hospital Onset' 
are selected to be validated. However, for CLABSI/CAUTI validation, 
this is not a concern, because CLABSI/CAUTI measures are validated 
differently than MRSA/CDI measures. For CLABSI/CAUTI validation, there 
are no `Hospital Onset' vs. `Community Onset' conditions and/or 
restrictions, whereas for MRSA/CDI, there are. CMS will continue to 
monitor validation and how it may impact hospitals differently. 
However, CMS does not currently have reason to believe that the 
proposed validation process for the HAC Reduction Program will change 
the validation performance of smaller hospitals relative to the 
previous validation process. CMS also notes that the proposed filtering 
option will only affect the cases subject to validation among hospitals 
selected for validation and will not impact the sample of HAIs that 
hospitals report to NHSN and that are used in the HAC Reduction Program 
scoring.
    Comment: A commenter encouraged CMS to consider additional 
validation improvements to improve data quality and cited a number of 
studies and reports, specifically MedPAC's March 2019 Report to 
Congress and OIG Report, ``CMS Validated Hospital Inpatient Quality 
Reporting Program Data, But Should Use Additional Tools to Identify 
Gaming,'' which highlight the potential for improving reliability and 
accuracy for reporting infections and patient safety issues and 
encourage better analytics for validation.
    Response: We thank the commenter for the suggestions and will take 
them into account during future policy planning.
    After consideration of the public comments we received, we are 
finalizing the proposed CLABSI and CAUTI validation filtering 
methodology to remove cases in which all positive blood or urine 
cultures were collected during the first or second day following 
admission.
    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.
    Comment: A commenter believed that the disagreement between the 
trained CMS abstractors and case reports may be due to differences 
between LabID criteria and clinical criteria and believed that LabID 
criteria over report cases of MRSA and CDI.
    Response: We use the CDC measure protocol for abstracting the 
validation infection measure records. The CDC measures experts utilize 
most current and evidence-based criteria for the MRSA and CDI measure 
specifications. We encourage the commenter to submit any specific 
measure specification questions to the CDC NHSN Help Desk for 
additional clarification.
    Comment: A commenter sought clarification on what is meant by ``the 
lower overall agreement rates for MRSA and CDI is due to over reporting 
of such events.'' The commenter is concerned that this could increase 
hospital risk, and the proposed filtering methodology may create undue 
burden.
    Response: We have determined that the disagreement rate between 
trained CMS abstractors and hospital reported MRSA and CDI is due to 
hospitals erroneously classifying community onset infections as 
hospital-acquired infections. At this time, we are not proposing or 
finalizing any filtering methodology for MRSA and CDI. We are only 
increasing our educational efforts on this topic, which will not create 
burden for hospitals.
    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 
the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19445), we did not 
propose any changes to the validation of Colon and Abdominal 
Hysterectomy SSI events.
    Comment: A commenter supports CMS's development of a filtering 
method for SSI to increase yield rate and improve the power of the 
validation methodology.
    Response: We thank the commenter for the support.

[[Page 42410]]

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 in this section of 
this final rule 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 the FY 2020 IPPS/LTCH PPS 
proposed rule (84 FR 19445), we did not propose any changes to this 
methodology.
[GRAPHIC] [TIFF OMITTED] TR16AU19.179

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 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 
all of 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.
     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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19445 through 
19446), we did not propose any changes to our policies regarding the 
scoring calculations review and correction period.
10. Applicable Period for FY 2022 Program Year
    In the FY 2018 IPPS/LTCH PPS final rule, we finalized the 
applicable period for the CMS PSI 90 as the 24-month period from July 
1, 2016 through June 30, 2018. Additionally, we finalized the 
applicable period for the CDC NHSN HAI measures (CLABSI, CAUTI, Colon 
and Abdominal Hysterectomy SSI, MRSA Bacteremia, and CDI), as the 24-
month period from January 1, 2017 through December 31, 2018, or CY 2017 
and 2018. These two 24-month applicable periods apply to payments for 
FY 2020, and set the timelines for subsequent applicable periods.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19446), 
consistent with the definition specified at Sec.  412.170, we proposed 
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.
    We did not receive any public comments on this topic. Therefore, we 
are finalizing the applicable period for the FY 2022 Program year as 
proposed.

[[Page 42411]]

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.
     The information made available to the public under 
paragraph 1886(p)(6) of the Act.
    For additional information, we refer readers to the FY 2014 IPPS/
LTCH PPS final rule (78 FR 50729) and the FY 2015 IPPS/LTCH PPS final 
rule (79 FR 50100).
12. Regulatory Updates (42 CFR 412.172)
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19446), we 
proposed to update 42 CFR 412.172(f)(2) and (4) to reflect current 
policies and align across our quality programs. We proposed 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.
    We did not receive any public comments on this topic. Therefore, we 
are finalizing the updates to the Program's regulatory text as 
proposed.

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 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. Policy Changes Related to Critical Access Hospitals (CAHs) as 
NonProviders for Direct GME and IME Payment Purposes
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19447 through 19448), 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

[[Page 42412]]

residency training programs (78 FR 50738). In light of these concerns, 
we 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, in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19447), 
we proposed 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. In this section of 
this final rule, we discuss our proposal, respond to public comments 
received, and provide our final policy.
    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, as noted 
in the proposed rule, we reassessed and agreed with prior comments we 
have received stating that the intent of section 5504 of the Affordable 
Care Act 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.
    As discussed in the proposed rule, 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, in the FY 2020 IPPS/LTCH PPS proposed rule, we 
proposed that, effective with portions of cost 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 did not propose 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. We stated in the 
proposed rule that 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 sought public comments on this proposed policy 
change.
    Comment: Most commenters supported the proposed policy to consider 
CAHs as nonproviders for direct GME and IME payment purposes. A 
commenter stated it concurred with CMS's assessment that the terms 
``nonprovider'' and ``nonhospital'' have been used interchangeably, 
such that the statute leaves some ambiguity as to whether a CAH may be 
considered a nonprovider site. Commenters stated that although more 
policies are needed to fully address workforce gaps in rural America, 
the proposed policy would help to recruit and retain physicians in 
rural underserved areas. Some commenters described the rural primary 
care residency training programs in their specific states and noted 
that these training programs emphasize rotations at CAHs. A commenter 
stated they have a long history of supporting CAH rotations wherein 
residents receive a deeper understanding of the community that they 
practice in, as well as the challenges and opportunities that can be 
found in remote settings versus those in more urban settings. Another 
commenter stated that 40 percent of the hospitals in its state are CAHs 
and therefore, the proposed policy is vitally important to increasing 
recruitment efforts by CAHs and provider access for patients in rural 
areas of its state.
    Commenters noted the challenges faced by rural facilities as well 
as flexibilities that could result from the proposed policy. A 
commenter stated that workforce shortages are a persistent challenge 
for rural providers as only 10 percent of U.S. physicians practice in

[[Page 42413]]

rural areas despite nearly 20 percent of Americans residing in these 
communities. Another commenter stated that in addition to having a 
positive impact on both the residents and physicians practicing in 
rural areas, the proposed policy would ease the paperwork burden on 
cash strapped CAHs. Another commenter stated rural hospitals represent 
more than half of all hospitals in the U.S., yet they struggle to 
recruit and retain a health care workforce sufficient to meet the needs 
of the communities they serve due to financial distress. The commenter 
stated training facilities in rural hospitals operate on very narrow 
margins and are cautious to commit to ongoing residency training costs 
without a stable, predicable source of funding. Modifying the 
definition of non-provider setting will reduce financial vulnerability 
and promote greater training of physicians in rural hospitals. Another 
commenter stated they believe the proposal would expand clinical 
rotation opportunities to sites of care that cannot alone bear the 
costs associated with starting and maintaining approved residency 
programs. The commenter stated the proposal would also allow hospitals 
that are under their residency caps greater flexibility in offering 
residents a broad array of clinical rotations in approved residency 
training programs, including in rural areas. A commenter stated that if 
the proposal is finalized, it encourages CMS to work with the Health 
Resources and Services Administration (HRSA) and Federal Office of 
Rural Health Policy to communicate such information to CAHs and 
residency programs, as well as to explore additional opportunities for 
regulatory flexibility that could further increase rural residency 
training.
    Response: We appreciate the commenters' support of the proposed 
policy to consider CAHs as nonprovider sites for purposes of direct GME 
and IME payments. As stated in the proposed rule, if the 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. Any additional 
opportunities for regulatory flexibility would likely need to be a part 
of the proposed and final rulemaking process.
    Comment: A commenter disagreed with the proposed policy. The 
commenter disagreed with CMS' assessment that there is flexibility 
within the current statutory language to consider a CAH a nonprovider 
for direct GME and IME payment purposes. The commenter disagreed with 
the statement in the proposed rule that the lack of both an explicit 
statutory definition of nonprovider and a definitive determination as 
to whether a CAH is considered a hospital allows CMS to consider a CAH 
a nonprovider for direct GME and IME payment purposes. The commenter 
stated that the fact that a CAH is explicitly considered to be a 
``provider of services'' under section 1861(u) of the Act, firmly 
establishes a CAH to be a ``provider'' and would, therefore, also 
firmly preclude a CAH from being considered a ``nonprovider''.
    The commenter stated that regardless of the propagated intent of 
the changes made by section 5504 of the Affordable Care Act, it does 
not appear that the existing statutory language will allow for CMS to 
modify its current policy in order to allow a hospital to include FTE 
residents training at a CAH in its FTE count. The commenter strongly 
cautioned CMS in moving forward with the proposal, as it seems as 
though the proposal could just as easily be reversed back to the 
current policy upon some future reexamination (falling more in line 
with the original examination as noted in the FY 2014 IPPS/LTCH PPS 
final rule (78 FR 50734 through 50739)).
    The commenter stated there may also be an increased potential that 
Medicare funding of residency training time will be incorrectly 
duplicated if hospitals are allowed to include FTE residents training 
at CAHs in their FTE counts. The commenter stated that since CAHs 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, hospitals that 
sponsor residency training programs may simply be invoicing CAHs for 
the cost of the residents' salaries and fringe benefits while the 
residents are training at the CAHs or may otherwise be generally 
invoicing the CAHs for portions of the costs of the residency training 
programs. Those same hospitals, which sponsor the residency training 
programs, may then incorrectly represent themselves as having incurred 
the residents' salaries and fringe benefits while the residents were 
training at the CAHs and include the residents training at the CAHs in 
their FTE resident counts for direct GME and IME payment purposes. The 
commenter stated that this potential situation would be a difficult one 
to uncover under normal auditing procedures and the proposed change in 
policy opens up a great risk of Medicare double funding residency 
training time. The commenter stated that another instance of 
duplication of payment would occur in the instance where the indirect 
costs incurred by the CAHs for the residency training time are paid to 
the CAHs at 101 percent of the reasonable costs and also be 
(conceptually) paid to the hospitals through the IME payments. The 
commenter stated that in addition, any direct costs incurred by the 
CAHs such as teaching physician time would be paid to the CAHs at 101 
percent of the reasonable costs and would also then be (conceptually) 
paid to the hospitals through the direct GME payments.
    The commenter questioned why the current policy with respect to 
CAHs and nonproviders would be a concern for the large community of 
teaching hospitals presently in existence, many of which are already 
training at levels which are limited by their caps. The commenter 
stated they assume the current policy with respect to CAHs and 
nonproviders may be more of a concern for hospitals that either are or 
plan to train residents in new programs and may therefore be eligible 
to receive adjustments to the statutorily mandated caps. The commenter 
stated these hospitals' FTE resident counts would be uncapped for 
direct GME and IME payment purposes during an allotted cap-building 
period in the initial years of the new medical residency training 
programs and would then be used to establish permanent cap adjustments 
for these hospitals. These hospitals, if allowed to include residents 
training at a CAHs in their FTE counts, could potentially utilize CAHs 
as participating sites for the new medical residency training programs 
and claim the residents training at the CAHs in their FTE counts until 
such time that these hospitals have established permanent cap 
adjustments. The commenter stated these hospitals would then be able to 
proprietarily and immediately use their caps to fund FTE residents 
training at sites other than those CAHs that had originally helped them 
to attain the very same permanent cap adjustments, or even to fund FTE 
residents training at their hospital sites in other established 
residency training programs. The commenter stated that once the 
hospitals' potential for additional Medicare reimbursement has been 
limited by the statutorily mandated caps, these hospitals might then no 
longer be incentivized to provide resident training rotations at the 
CAHs. The training of residents in rural and underserved areas would 
again be reduced, contrary to the propagated intent of the changes made 
by section 5504 of the Affordable Care Act.
    Response: We appreciate hearing the commenter's concerns with 
respect to

[[Page 42414]]

the proposed policy. While the commenter is correct that CAHs are 
included in the definition of ``provider of services'' under section 
1861(u) of the Act, we continue to believe, upon reexamination of the 
current statutory language, that the lack of a statutory definition of 
``nonprovider'' as well as the consideration that a CAH is a facility 
primarily engaged in patient care consistent with the term 
``nonprovider setting that is primarily engaged in furnishing patient 
care'' included at section 1886(h)(5)(K) of the Act, provides enough 
flexibility within the current statutory language to consider CAHs as 
nonproviders for purposes of direct GME and IME payments.
    Regarding the concern that hospitals may simply invoice CAHs for 
the cost of the residents' salaries and fringe benefits or for portions 
of the costs of the residency training program, we note that just as 
with any FTEs training in a nonprovider setting, the hospital must show 
its MAC the location of the residents and that it actually paid the 
residents' salaries and fringe benefits. That is, the hospital must 
clearly show it had the residents training at a CAH on its payroll or 
that it made payments to the CAH to cover the residents' salaries and 
fringe benefits.
    In response to the concern of duplicative payments with respect to 
direct GME costs, if a CAH is including direct costs in the GME cost 
centers on its cost report, the MAC can ask which entity is claiming 
the FTE residents and which entity is incurring the salaries and fringe 
benefits. If the applicable nonprovider site requirements are not being 
met, the MAC would be able to disallow the FTE residents from the 
hospital. Regarding the concern of duplicative payments with respect to 
indirect costs, we understand that as a natural consequence of 
receiving payment based on reasonable costs under section 1861(v)(1)(A) 
of the Act, CAHs would be permitted to claim the indirect costs of 
residency training, regardless of whether or not another hospital 
claims the FTE residents for IME payment purposes. Nevertheless, in the 
event a hospital pays the salaries and fringe benefits of the FTE 
residents training in a nonprovider setting and meets all other 
applicable requirements, section 1886(d)(5)(B)(iv)(II) of the Act 
permits that hospital to receive IME payments for those FTE residents.
    In response to the concern that hospitals may use CAHs as training 
sites to establish their caps and then move the training from the CAH 
to their hospital or other hospitals, while in general cap slots are 
fungible such that FTE cap slots could be moved from a CAH to a 
hospital(s), the purpose of the policy finalized in this rule is to 
address stakeholders' concerns that the previous policy regarding CAHs 
and nonprovider sites was negatively affecting residency training in 
rural areas. We would expect then, that the policy finalized in this 
rule would promote residency training at CAHs rather than promote 
scenarios where the CAH is acting as a temporary training site for cap-
building purposes.
    Comment: While many commenters supported our proposed policy, the 
majority asked that CMS finalize a policy which expands upon our 
proposed policy in a number of ways. Commenters requested that CMS 
reconsider the effective date of the proposed policy, specifically that 
CMS finalize the proposed policy with an effective date retroactive to 
FY 2014. The commenters stated that those hospitals that partnered with 
CAHs in rural residency programs, which completed their cap-building 
period during the six intervening years since implementation of the 
2014 IPPS final rule, are permanently and continually harmed by an 
effective date of October 1, 2019. The commenters stated some hospitals 
have been harmed by CMS' previous position since the hospitals could 
not claim FTEs for reimbursement (under the IPPS system) and the 
participating CAHs did not claim any direct educational costs. One 
commenter requested that CMS reconsider the effective date of its 
proposed policy because hospital residency programs, such as its 
internal medicine program, that were in their cap-building period 
during the six intervening years since implementation of the FY 2014 
IPPS/LTCH PPS final rule are permanently affected by the historical 
exclusion of CAH rotations. The commenter stated that since these 
rotations were not allowed to be included in its initial counts in its 
cap-building period, adding the CAH rotations in later years without 
some sort of cap adjustment, will merely push the hospital over its 
cap. The commenter stated they hope CMS will provide this additional 
consideration for underserved rural areas which will enhance 
institutions' ability to produce physicians who will practice in rural 
areas and serve underserved rural populations.
    Commenters expressed significant concerns over the permanent impact 
the current policy with respect to CAHs will have on hospitals that had 
or will have their caps set based on training residents in new programs 
during the period of October 1, 2013 through September 30, 2019. Many 
commenters requested that CMS allow a cap recalculation for those 
hospitals that partnered with CAHs and set their caps during this 
period and have cost reports that are still within the 3-year reopening 
period. The commenters stated this approach would not require any 
changes or resubmissions of cost reports. Rather, Medicare MACs would 
recalculate the cap to include time spent by residents in CAHs and help 
remedy harm caused by CMS' previous policy. A commenter stated there 
are many teaching hospitals that are several years into, or at the end 
of, their cap-building period that have struggled to accommodate 
rotations to CAHs as a result of this restriction. Permitting these 
hospitals to count FTEs that would have otherwise been counted toward 
their cap under the proposed policy would allow for additional training 
in rural and underserved areas each year. Another commenter stated they 
were concerned that the CAH policy in effect for Medicare GME payment 
purposes during the period October 1, 2013, through October 1, 2019, 
may have inappropriately set certain new teaching hospitals' direct GME 
and IME caps too low. The commenter stated that CMS' current 
methodology for the calculation of a new teaching hospital's caps 
utilizes a 5-year cap-building window as a representative time period 
during which a proper determination of the future steady state can be 
made. The regulatory text makes clear that the purpose is to ensure 
that the new teaching hospital does not receive credit for training 
occurring at another hospital. The commenter believes that CMS has 
ample authority to separate specific Medicare reimbursement 
determinations made during the period October 1, 2013, to September 30, 
2019, from FTE resident cap determinations made applicable (and 
permanent) for portions of cost reporting periods beginning on or after 
July 1, 2020. The commenter recommended CMS permit MACs to consider 
rotations to a CAH during the period October 1, 2013, to October 1, 
2019, as training at a nonprovider setting solely for purpose of 
calculating a new teaching hospital's permanent direct GME and IME 
caps. Such clarification would not result in any retroactive payment 
implications. The commenter stated as CMS' preamble discussion makes 
clear, the status of CAHs as a hospital/provider/nonprovider in the 
context of Medicare GME payment policy has been ambiguous at best. CMS 
has ample authority to address this issue for the betterment of those 
hospitals seeking to promote the practice of physicians in

[[Page 42415]]

rural areas. A commenter gave the example of how it first started 
training residents in a new internal medicine program and therefore is 
currently in its 5-year cap building period. The commenter stated it 
strives to teach residents in community settings, to expose trainees to 
diverse settings of care, which includes a CAH within the commenter's 
health system. The commenter stated it has struggled to permit 
residents to spend significant amounts of time at this CAH given the 
financial incentives created by CMS' current policies. The commenter 
stated the proposed policy change is particularly helpful in the final 
year of its cap-building period allowing the hospital to establish 
resident rotations to the CAH that can be continued long after the 
Medicare GME cap-building period has closed. The commenter strongly 
encouraged CMS to provide additional flexibilities by allowing 
hospitals to count residency training time at CAHs during the entire 5-
year cap building window, even for FTE time prior to October 1, 2019. 
Such an approach would recognize the hospitals need for space within 
its GME caps to accommodate resident training time and would support 
new teaching hospitals in continuing to send residents to CAHs in 
increasing numbers, all the while not requiring the reopening of prior 
year cost reports.
    Some commenters stated that while training time in CAHs during 
October 1, 2013 through October 1, 2019 could not be counted by 
hospitals, in many cases CAHs did not claim any direct education costs 
during this time period either. The commenters requested CMS allow 
hospitals to claim CAH rotation time for unsettled cost reports (in the 
2013 to 2019 window) should they wish to and if the CAH agrees. This 
claiming of resident training time by the hospital, would be with the 
understanding that the CAH where the resident was training may also 
have its cost report(s) opened for the affected year(s), but solely for 
the purpose of assuring that the CAH did not claim allowable costs for 
these resident rotations.
    Response: We appreciate hearing the commenters' concerns with 
respect to the proposed policy. As we noted in the proposed rule, in 
light of concerns expressed by stakeholders, we 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. We determined there is 
enough flexibility within the current statutory language to consider a 
CAH a nonprovider setting for direct GME and IME payment purposes. 
However, the interpretation of CAHs as nonproviders presented in the 
proposed rule, does not invalidate our previous policy of not 
considering CAHs to be nonproviders for purposes of direct GME and IME 
payments established in the FY 2014 IPPS/LTCH PPS final rule, 
applicable through September 30, 2019. We continue to believe that this 
policy and interpretation of the applicable law was and is a legally 
viable alternative reading of the statute. In considering the comments 
received, we note that none of the commenters' recommendations provide 
policy alternatives which are purely prospective; but rather, all 
contain elements which are retroactive in nature. As we do not believe 
engaging in retroactive rulemaking is appropriate with respect to this 
policy, we are finalizing our policy as proposed. Specifically, 
effective with portions of cost 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). 
Therefore, if a hospital is at some point in its 5-year cap-building 
period as of October 1, 2019, and as of that date is sending residents 
in a new program to train at a CAH, assuming the regulations governing 
nonprovider site training are met, the time spent by FTE residents 
training at the CAH on or after October 1, 2019 will be included in the 
hospital's FTE cap calculation. Alternatively, as we noted in the 
proposed rule, a CAH may decide to 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. In that situation no hospital can include the residents 
training at the CAH in its direct GME and IME FTE counts.
    Comment: We received public comments regarding GME issues that were 
outside of the scope of the proposals included in the FY 2020 IPPS/LTCH 
PPS proposed rule. These comments requested that--
     While the commenter appreciated the proposed change, the 
commenter stated it will not help the many teaching hospitals that have 
resident counts above their 1996 resident counts and still choose to 
rotate residents to CAHs and other sites. The commenter urged CMS to 
support bipartisan legislation, the Resident Physician Shortage 
Reduction Act of 2019 (S. 348/H.R. 1763), which will provide moderate 
increases to these caps.
     CMS support and advocate for other programs that address 
health care workforce shortages. The commenter stated the Conrad 30 J-1 
Waiver Program was created to address physician shortages across the 
country and allows each state's department of health to sponsor up to 
30 international medical graduates each year for waiver of the 2-year 
home residency requirement if they serve in federally designated 
shortages areas. The commenter stated that although each state is 
eligible to sponsor up to 30 medical graduates, some states do not fill 
their slots, which results in unused physician slots in some areas when 
there is a need for more slots in other areas. The commenter urged CMS 
to work with Congress and other applicable departments to seek ways to 
increase the number of slots for states that consistently fill their 
slots, or allow slots that are not used by some states to be 
distributed to other states that have greater need.
     CMS release its findings with respect to section 5503 of 
the Affordable Care Act. The commenter referenced the requirement under 
section 5503 of the Affordable Care Act that a hospital, which is 
awarded slots, must use 75 percent of the awarded slots for residency 
training in primary care and/or general surgery. The commenter stated 
that while they believe that the 75 percent threshold was intended to 
bolster the primary care and general surgery workforce as part of 
healthcare delivery for current and future Medicare beneficiaries, CMS 
has not provided information on the effects of this program, such as: 
The specialties of the training programs that lost unused slots; how 
many of the redistributed slots were filled; how many of the 
redistributed slots were awarded to primary care programs compared to 
how many were awarded to general surgery programs; whether general 
surgery experienced a net loss or net gain of residency slots; and how 
CMS monitored hospitals' adoption of the 75 percent threshold. The 
commenter stated that now that the 5-year redistribution period has 
ended, they strongly urge CMS to release its findings regarding awardee 
hospitals' use of their section 5503 slots and the hospitals' 
compliance with the terms and conditions of the program. The commenter 
stated they remain concerned with the lack of consistent, unbiased 
statistics on physician supply and demand and believe that CMS can 
provide more accurate and actionable workforce data based on the 
initial round of unused residency slot

[[Page 42416]]

redistribution. The commenter requested that in the interest of 
transparency and accountability, CMS make public a comprehensive 
description of the specialties from which the unused slots were drawn 
and subsequently redistributed; the number of slots designated as 
primary care versus general surgery under the 75 percent threshold; how 
the Agency and its contractors tracked hospitals' participation and 
enforced the program's statutory and regulatory requirements; and, in 
the event that it was determined a hospital did not satisfy these 
requirements, how its awarded slots were redistributed to another 
hospital(s) in accordance with section 5503 of the Affordable Care Act.
    Response: Because we consider these public comments to be outside 
of the scope of the proposed rule, we are not addressing them in this 
final rule.
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 Providence Hospital Located in Washington, DC 
and the Application Process--Round 15
    CMS has learned of the closure of Providence Hospital, located in 
Washington, DC (CCN 090006). 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 15th round (``Round 15'') 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 are part of the Round 15 application process under 
section 5506 of the Affordable Care Act.
[GRAPHIC] [TIFF OMITTED] TR16AU19.180

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 Providence Hospital, located in Washington, DC, 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 October 31, 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 October 31, 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 15 due to the closure of Providence 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 website for 
a list of additional section 5506 guidelines for the policy and

[[Page 42417]]

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 in 
this final rule). 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 final 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) of Public Law 108-
173, 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 Public Law 108-173 (as amended by 
Pub. L. 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 42418]]

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.) 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. In addition, one of the previously participating hospitals 
closed effective January 2019. Therefore, 28 hospitals are scheduled to 
participate in the demonstration 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 42419]]

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 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 the 
FY 2020 IPPS proposed rule, we included an estimate of the costs of the 
demonstration for FY 2020 for 29 hospitals.
     Similar to previous years, we 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 the proposed rule, we identified the amount of the difference 
between actual and estimated costs based on finalized cost reports for 
FY 2014; and, in addition, we proposed that if finalized cost reports 
were available we would 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 
previously described, 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. (In the proposed rule, we conducted this estimate on 
the basis of 29 participating hospitals; with one closing earlier this 
year, in this final rule we are limiting this estimate to the 28 
currently participating hospitals.) The methodology for calculating 
this amount for FY 2020 proceeds according to the following steps:
    Step 1: For each of the 28 participating hospitals, we 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 Public Law 114-255 will end prior to 
the end of FY 2020. Therefore, consistent with previous practice, we 
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 0.75. We 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 28 
participating hospitals.
    Then, we 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. (We are using the finalized market basket 
percentage increase for FY 2020, which can be found at section IV.B of 
the preamble to this final rule). The result for the 28 participating 
hospitals is 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 are applying the IPPS market basket percentage increases 
for FYs 2018 through 2020 to the applicable estimated reasonable cost 
amount (previously described) 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 prior to the 
end of FY 2020 by the fraction of total months in the demonstration 
period of participation for the hospital that fall within FY 2020 out 
of the total of 12 months in the fiscal year). We sum these hospital-
specific amounts, and, in turn, multiply this sum by the FYs 2018, 2019 
and 2020 IPPS applicable percentage increases. (Again, for FY 2020, we 
are using the finalized applicable percentage increase, per section 
IV.B of this final rule). This

[[Page 42420]]

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 applicable percentage increase is the factor used 
under the IPPS to update the inpatient hospital payment rates.
    Step 3: We 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 28 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 final rule, the resulting amount is $60,972,359, which we 
are incorporating into 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. (This estimated amount differs from the corresponding figure 
identified in the proposed rule for 2 reasons: (1) Taking into account 
the hospital closure earlier this year, we are conducting the estimate 
on the basis of 28 participating hospitals, instead of 29; and (2) we 
are using the finalized market basket and applicable percentage 
increase updated for FY 2020. In the proposed rule, we said that if 
updated data become available prior to the final rule, we would 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).
(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 the FY 2020 IPPS/LTCH proposed rule, we 
identified 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 
proposed to adjust the current year's budget neutrality amount by the 
amount identified. We stated that if any information relevant to the 
determination of these amounts (for example, a cost report reopening) 
would necessitate a revision of these amounts, we would make the 
appropriate change and include the determination in the FY 2020 IPPS/
LTCH PPS final rule. Furthermore, we stated, furthermore, that if the 
needed costs reports were available in time for the FY 2020 IPPS/LTCH 
PPS final rule, we also would 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.
    For the proposed rule, we found that 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 have since then found no circumstance relevant to the 
determination of this amount that would require any change, and are 
incorporating this amount into the budget neutrality offset for the FY 
2020 IPPS final rule.
    Currently, finalized cost reports are available for the 21 
hospitals that completed cost reports for periods of participation 
under the demonstration beginning in FY 2015. Accordingly, the actual 
costs of the demonstration for FY 2015 (that is, the amount from 
finalized cost reports for these hospitals), fell short of the 
estimated amount that was finalized in the FY 2015 IPPS/LTCH final rule 
for FY 2015 by $20,297,477. We note that for both of these fiscal years 
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 final rule, we are 
incorporating the following components into the calculation of the 
total budget neutrality offset for FY 2020:
     The amount determined under section IV.K. 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 28 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 $60,972,359.
     The amount determined under section IV.K. of the preamble 
of this final 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.
     The amount determined under section IV.K. of the preamble 
of this final rule according to which the actual costs of the 
demonstration for FY 2015 for the 21 hospitals that completed a cost 
reporting period beginning in FY 2015 differ from the estimated amount 
that was incorporated into the budget neutrality offset amount for FY 
2015 in the FY 2015 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 2015 IPPS/LTCH PPS 
final rule by $20,297,477.
     In keeping with previously finalized policy, we are 
proposing to apply these differences, for FYs 2014 and 2015, according 
to which the actual costs of the demonstration fell short of the 
estimated amount determined in the final rule for the respective fiscal 
year by reducing the budget neutrality offset amount for FY 2020 by 
these amounts.
    Therefore, in this FY 2020 IPPS/LTCH final rule, the total budget 
neutrality offset amount that we are applying to the national IPPS 
rates for FY 2020 is the estimated amount for FY 2020 ($60,972,359) 
minus the amount by which the actual costs of the demonstration fell 
short of the estimated amount for FY 2014 ($14,932,060)

[[Page 42421]]

minus the amount by which the actual costs of the demonstration fell 
short of the estimated amount for FY 2015 ($20,297,477). This total is 
$25,742,822.

V. 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 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. Annual Update for FY 2020

    The 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 final rule.
    In section II.D. of the preamble of this FY 2020 IPPS/LTCH PPS 
final 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 making 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 making a similar adjustment to the 
national capital Federal rate (or to the hospital-specific rates).

VI. Changes for Hospitals Excluded from the IPPS

A. 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

[[Page 42422]]

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, the 11 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 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, 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. 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 is the FY 2020 percentage increase in the 2014-based IPPS 
operating market basket.
    For the FY 2020 IPPS/LTCH PPS proposed rule, based on IGI's fourth 
quarter 2018 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, we stated in the proposed rule (84 FR 19454) that 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, the 11 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 proposed 
that if more recent data became available for the final rule, we would 
use them to calculate the final IPPS operating market basket update for 
FY 2020. For this FY 2020 IPPS/LTCH PPS final rule, based on IGI's 
second quarter 2019 forecast (which is the most recent data available), 
we calculated the 2014-based IPPS operating market basket update for FY 
2020 to be 3.0 percent. Therefore, the FY 2020 rate-of-increase 
percentage that is applied to the FY 2019 target amounts in order to 
calculate the FY 2020 target amounts for children's hospitals, the 11 
cancer hospitals, RNCHIs, and short-term acute care hospitals located 
in the U.S. Virgin Islands, Guam, the Northern Mariana Islands, and 
American Samoa is 3.0 percent, in accordance with the applicable 
regulations at 42 CFR 413.40.
    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 update to the target amount for extended 
neoplastic disease care 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, in 
the proposed rule, was 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, for the FY 2019 IPPS/LTCH 
PPS proposed rule, the update to an extended neoplastic disease care 
hospital's target amount for FY 2020 was 3.2 percent, which was based 
on IGI's fourth quarter 2018 forecast. Furthermore, we proposed that if 
more recent data became available for the final rule, we would use that 
updated data to calculate the IPPS operating market basket update for 
FY 2020. For this final rule, based on IGI's second quarter 2019 
forecast (which is the most recent data available), the update to an 
extended neoplastic disease care hospital's target amount for FY 2020 
is 3.0 percent.
    We received no comments in response to the proposals discussed 
above. Thus, for the reasons discussed above and in the proposed rule, 
we are finalizing these policies as proposed without modification.
    We received several public comments related to excluded hospitals 
that addressed issues that were outside the scope of the FY 2020 
proposed rule. We will keep these comments in mind and may consider 
them for future rulemaking.

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

[[Page 42423]]

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, acute care hospitals located in the U.S. Virgin Islands, Guam, 
American Samoa, and the Northern Mariana Islands). Under certain 
circumstances, we 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 previously noted, 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 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 the FY 2020 IPPS/LTCH proposed rule (84 FR 
19454-19455), we solicited 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 previously noted, 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, we have rarely authorized assignment of a new base year 
period because the adjustment mechanism as previously discussed 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 requested 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 invited comments, suggestions, and 
recommendations for regulatory and other policy changes to the TEFRA 
adjustment process. We also requested 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 invited commenters to provide specific examples.
    Comment: Several commenters stated their appreciation for CMS's 
consideration of improvements to the TEFRA adjustment process currently 
afforded to providers exempted from the IPPS and reimbursed under 
TEFRA.
    Response: We thank commenters for responding and we will take these 
comments into consideration for future rulemaking.
C. Report on Adjustment (Exception) Payments
    Section 4419(b) of Pub. L. 105-33 requires the Secretary to publish 
annually in the Federal Register a report describing the total amount 
of adjustment payments made to excluded hospitals and hospital units by 
reason of section 1886(b)(4) of the Act during the previous fiscal 
year.
    The process of requesting, adjusting, and awarding an adjustment 
payment is likely to occur over a 2-year period or longer. First, 
generally, an excluded hospital must file its cost report for the 
fiscal year in accordance with Sec.  413.24(f)(2) of the regulations. 
The MAC reviews the cost report and issues a notice of provider 
reimbursement (NPR). Once the hospital receives the NPR, if its 
operating costs are in excess of the ceiling, the hospital may file a 
request for an adjustment payment. After the MAC receives the 
hospital's request in accordance with applicable regulations, the MAC 
or CMS, depending on the type of adjustment requested, reviews the 
request and determines if an adjustment payment is warranted. This 
determination is sometimes not made until more than

[[Page 42424]]

180 days after the date the request is filed because there are times 
when the request applications are incomplete and additional information 
must be requested in order to have a completed request application. 
However, in an attempt to provide interested parties with data on the 
most recent adjustment payments for which we have data, we are 
publishing data on adjustment payments that were processed by the MAC 
or CMS during FY 2018.
    This table includes the most recent data available from the MACs 
and CMS on adjustment payments that were adjudicated during FY 2018. As 
previously indicated, the adjustments made during FY 2018 only pertain 
to cost reporting periods ending in years prior to FY 2018. Total 
adjustment payments made to IPPS-excluded hospitals during FY 2018 are 
$20,095,056. The table depicts for each class of hospitals, in the 
aggregate, the number of adjustment requests adjudicated, the excess 
operating costs over the ceiling, and the amount of the adjustment 
payments.
[GRAPHIC] [TIFF OMITTED] TR16AU19.181

D. 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. 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 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 and Final Policy
    As previously indicated, consistent with the statutory provision 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

[[Page 42425]]

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, in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19455 
through 19456), we proposed 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 
proposed to 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 stated that 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 proposed 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 proposed 
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 stated that 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 stated that 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.
    Comment: Commenters supported CMS' proposal to interpret section 
1834(l)(8)(B) of the Act to mean that 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 CAH-owned and 
operated entity is 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 transport individuals to or from the CAH.
    Commenters stated that this proposal supports rural health care, 
removes artificial reimbursement barriers to regional health care 
delivery, and will improve access to care for individuals living in 
remote and rural areas, particularly in emergency situations and when 
individuals have no other mode of transportation due to hazardous 
traveling conditions.
    Response: We appreciate the commenters' support for the proposed 
change to the regulation governing payment for ambulance services 
furnished by a CAH or by a CAH-owned and operated entity.
    Comment: Several commenters urged CMS to expand the availability of 
cost-based reimbursement to ambulance services where patient transfer 
is required based on the CAH conditions of participation (CoPs). The 
commenters stated that CAHs are uniquely required to transfer certain 
patients to receive care at other facilities. However, in many rural 
areas, even those that are otherwise served by an ambulance

[[Page 42426]]

service, CAHs often struggle to find medical transport for facility to 
facility transfers. The commenters stated that rural ambulance services 
are often staffed by a limited number of volunteers and are unable to 
provide urgently needed facility to facility transfers because of 
limited equipment and staffing. The commenters stated that expansion of 
cost-based reimbursement to transportation that is required under the 
CoPs is consistent with the statute and CMS' commitment to ensuring 
rural Americans have access to care.
    A commenter stated that within a 35-mile radius of its CAH there 
are two Emergency Medical Services (EMS) agencies, both of which have a 
mutual aid agreement with the CAH allowing either agency or the CAH to 
respond to a 911 call in the rare occurrence when another member of the 
agreement is unavailable or unable to respond. However, neither EMS 
agency would be able to absorb the needs of the community should the 
CAH no longer be able to provide ambulance services.
    This commenter also stated that its CAH ambulance service operates 
significantly in the red, primarily due to its payer mix, the majority 
of patients being Medicare beneficiaries. The commenter indicated that 
due to the way the proposed rule is written, its CAH ambulance service 
does not qualify for cost-based reimbursement due to the EMS exclusion. 
The commenter stated they are concerned they will not be able to 
sustain the CAH's EMS service due to significant financial loses and 
there is not another service that is willing or able to take over their 
work should they have to discontinue or reduce EMS services. The 
commenter requested that CMS consider language that may allow their 
ambulance service and similarly situated organizations to participate 
in cost-based reimbursement.
    Another commenter stated they believe the proposal only benefits a 
small number of CAHs across the country and urged CMS to either make 
exceptions to allow all CAHs providing paramedic-level ambulance 
services to receive reimbursement at 101 percent of reasonable costs or 
consider making changes to the distance requirements in the IPPS to 
address reimbursement struggles CAHs are experiencing with respect to 
EMS. The commenter specified that many of the CAHs in their state are 
closer than 35 miles and many are the sole provider of ambulance 
services and the only paramedic-level provider serving their community. 
The commenter stated that in order for the people of their state to 
have guaranteed access to EMS, the services would need to be provided 
by the CAH and to do so, CAHs need cost-based reimbursement as the fee 
schedule payments do not come close to covering the costs of these 
services.
    Another commenter suggested that CMS consider an additional change 
that the commenter believed would be consistent with the intent of the 
proposal and would provide sustainable payments for CAH-operated 
ambulance services that are functionally the only ambulance services 
available to a CAH and its community The commenter stated that there 
are many cases where there is another ambulance service within 35 miles 
of a CAH, but the ambulance does not serve the CAH or the CAH's 
community due to geographic and/or economic factors, rather than legal 
constraints. For example, there are many cases in which the other 
ambulance service does not serve the CAH or its adjacent community, 
other than for inter-facility transport or in the event of a regional 
emergency that exceeds the capacity of the local service. The commenter 
recommended that CMS consider amending the proposal to allow 
reimbursement at 101 percent of reasonable costs for CAH ambulance 
services where the CAH or the CAH-owned and operated entity can 
demonstrate it is the single source of ambulance services for its 
community, other than during unusual circumstances.
    Response: We are not certain of the specific CoPs that are being 
referenced by the commenters. We note that the regulation at Sec.  
485.603 specifies that a rural health network is an organization that 
includes the provision of emergency and nonemergency transportation 
among members. The regulation at Sec.  485.616 includes a requirement 
that if a CAH is a member of a rural health network as defined in Sec.  
485.603, the CAH must have in effect an agreement with at least one 
hospital that is a member of the network for the provision of emergency 
and nonemergency transportation between the facility and the hospital. 
Separately, section 1867 of the Act and the implementing regulations at 
Sec.  489.24 outline the requirements CAHs and hospitals must meet to 
ensure compliance with the Emergency Medical Treatment and Labor Act 
(EMTALA), including the provision of appropriate transfers between 
participating hospitals.
    We also commend the commenters for their efforts to ensure that 
individuals living in rural areas have access to sufficient ambulance 
and EMS services, including transportation to other facilities to 
receive specialty care. We acknowledge the point made by commenters 
that because CAHs have a legal obligation to transfer patients, the 
reimbursement they receive for ambulance services should reflect that 
requirement. However, we note that most of the scenarios described by 
the commenters, including those regarding transfer of patients, appear 
to involve situations where there is another provider or supplier of 
ambulance services within a 35-mile drive of the CAH, and that 
ambulance provider or supplier is not legally precluded from providing 
ambulance services to individuals living within the CAH's service area. 
Section 1834(l)(8) of the Act specifies that payment to a CAH or CAH 
owned and operated entity is 101 percent of the reasonable costs 
incurred in furnishing ambulance services ``only if the critical access 
hospital or entity is the only provider or supplier of ambulance 
services that is located within a 35-mile drive of such critical access 
hospital.'' As we explained in the FY 2020 IPPS proposed rule (84 FR 
19456), we believe an interpretation of this statutory language that 
excludes providers and suppliers of ambulance services that are not 
legally authorized to transport individuals either to or from the CAH 
is reasonable because it retains the requirement that the CAH or the 
CAH-owned or 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. In contrast, we do 
not believe section 1834(l)(8) of the Act can be interpreted to allow 
CMS to provide payment to CAHs at 101 percent of the reasonable costs 
incurred in furnishing ambulance services in situations where there is 
another provider or supplier of ambulance services within a 35-mile 
drive of the CAH that is legally authorized, and thus available, to 
provide ambulance services to transport individuals to or from the CAH.
    After consideration of the public comments we received, we are 
finalizing our proposal to interpret the requirement in section 
1834(l)(8)(B) of the Act 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, to exclude consideration of ambulance 
providers or suppliers that are not legally authorized to furnish 
ambulance services to transport individuals to or from the CAH. As 
indicated earlier in this section, the term ``provider'' of ambulance 
services means all Medicare-participating providers that submit claims 
under Medicare for ambulance services (for example, hospitals, CAHs,

[[Page 42427]]

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. We are also 
finalizing our proposal to revise Sec.  413.70(b)(5)(i) of the 
regulations to reflect our revised interpretation of section 1834(l)(8) 
of the Act 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), paragraph (D) will also 
state that 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 are also finalizing the proposed 
conforming change to Sec.  413.70(b)(5)(i)(C), which will make that 
provision effective only for cost reporting periods starting on or 
before September 30, 2019.
3. Frontier Community Health Integration Project (FCHIP) Demonstration
    As discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41516 
through 41517) and in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19456 through 19458), 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 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 Law110-275 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

[[Page 42428]]

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 final 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 1 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. 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.
    We did not receive any public comments on our discussion of the 
FCHIP demonstration in the FY 2020 IPPS/LTCH PPS proposed rule.

VII. 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

[[Page 42429]]

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 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19469), we 
proposed 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. In section 
VII.C. of the preamble of this final rule, we discuss in detail the 
proposed revisions to our regulations, provide summations of the public 
comments we received in response to our proposals, including the 
Agency's responses, and present the finalized policy to implement the 
provisions of Public Law 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.
    We received several public comments that addressed issues that were 
outside the scope of the FY 2020 IPPS/LTCH PPS proposed rule. We will 
keep these comments in mind and may consider them for future 
rulemaking.
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

[[Page 42430]]

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 FYs 2016 
through 2019) are considered to be site neutral payment rate payments.

B. 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 
groupings. For FY 2020, there will be 761 MS-DRG groupings based on the 
changes, as discussed in section II.F. of the preamble of this FY 2020 
IPPS/LTCH PPS final 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. Then,we 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 final rule, we provide a general summary of 
our existing methodology for determining the FY 2020 MS-LTC-DRG 
relative weights under the LTCH PPS.
    As we proposed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19460), in general, for FY 2020, we are continuing to use our existing 
methodology to determine the MS-LTC-DRG relative weights (as discussed 
in greater detail in section VII.B.3. of the of this final rule). As we 
established when we implemented the dual rate LTCH PPS payment 
structure codified under Sec.  412.522, which began in FY 2016, as we 
proposed, 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 final rule). In addition, in this FY 2020 IPPS/LTCH 
PPS final rule, for FY 2020, as we proposed, we are continuing 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 
final rule.
    Furthermore, for FY 2020, in using data from applicable LTCH cases 
to establish MS-LTC-DRG relative weights, as we proposed, we are 
continuing 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 accounted 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 made 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

[[Page 42431]]

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 final 
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.
     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 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. 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 final rule, as we proposed, we 
updated the MS-LTC-DRG classifications effective October 1, 2019 
through September 30, 2020 (FY 2020), consistent with the changes to 
specific MS-DRG classifications presented in

[[Page 42432]]

section II.F. of the preamble of this final rule. Accordingly, the MS-
LTC-DRGs for FY 2020 presented in this final rule are the same as the 
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 MS-DRGs for FY 
2020, the other changes that affect MS-DRG (and by extension MS-LTC-
DRG) assignments under GROUPER Version 37 as discussed in section II.F. 
of the preamble of this final rule, including the changes to the MCE 
software and the ICD-10-CM/PCS coding system, also are applicable under 
the LTCH PPS for FY 2020.
3. Development of the 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 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 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 final rule, as we proposed in the FY 
2020 IPPS/LTCH PPS proposed rule (84 FR 19462), we are continuing to 
use our current methodology to determine the 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 MS-LTC-DRGs, low-volume and no-
volume MS-LTC-DRGs, adjustments for nonmonotonicity, the steps for 
calculating the MS-LTC-DRG relative weights with a 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 application of our existing 
methodology for determining the MS-LTC-DRG relative weights for FY 
2020, and we discuss the effects of our policies concerning the data 
used to determine the 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19462), 
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 was the best available data at that time, 
and we proposed to use Version 37 of the GROUPER to classify LTCH 
cases. Consistent with our historical practice, we proposed 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. Accordingly, for this final

[[Page 42433]]

rule, we are establishing the FY 2020 MS-LTC-DRG relative weights based 
on updated FY 2018 Medicare LTCH claims data from the March 2019 update 
of the FY 2018 MedPAR file, which is the best available data at the 
time of development of this final rule, and used the finalized Version 
37 of the GROUPER to classify LTCH cases.
    To calculate the FY 2020 MS-LTC-DRG relative weights under the dual 
rate LTCH PPS payment structure, as we proposed, we continued 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 March 2019 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 2018 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 FY 2020 MS-LTC-DRG relative weights using 
our current methodology, we did not make any 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 final 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 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 
excluded 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 
excluded 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 MS-LTC-DRG relative weights for FY 2020.
    In summary, in general, we identified the claims data used in the 
development of the FY 2020 MS-LTC-DRG relative weights in this final 
rule, as we proposed, 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. As described 
in the proposed rule, due to data limitations, we did not except from 
that trimmed data any discharges which were or would have been excluded 
from the site neutral payment rate under the temporary exception for 
certain severe wound care discharges from certain LTCHs and under the 
temporary exception for certain spinal cord specialty hospitals). 
Finally, we trimmed the claims data of all-inclusive rate providers 
reported in the March 2019 update of the FY 2018 MedPAR file and any 
Medicare Advantage claims data. There were no data from any LTCHs that 
are paid in accordance with a demonstration project reported in the 
March 2019 update of the FY 2018 MedPAR file, but, had there been any, 
we would have trimmed the claims data from those LTCHs as well, in 
accordance with our established policy. As we proposed, we used the 
remaining data (that is, the applicable LTCH data) to calculate the 
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 
final rule, as we proposed in the FY 2020 IPPS/LTCH PPS proposed rule 
(84 FR 19463), we continued to use a hospital-specific relative value 
(HSRV) methodology to calculate the 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 reduced 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

[[Page 42434]]

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, as we 
proposed, we continued 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 final 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 was 
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 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 final 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 in this final rule). 
For FY 2020, as we proposed in the FY 2020 IPPS/LTCH PPS proposed rule 
(84 FR 19463), we are continuing to use applicable LTCH cases to 
establish the same volume-based categories to calculate the FY 2020 MS-
LTC-DRG relative weights.
    In determining the FY 2020 MS-LTC-DRG relative weights, when 
necessary, as is our longstanding practice, as we proposed, we made 
adjustments to account for nonmonotonicity, as discussed in greater 
detail later in Step 6 of section VII.B.3.g. of the preamble of this 
final 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).
    Comment: Some commenters objected to some of the proposed changes 
in the severity level designations for certain ICD-10-CM diagnosis 
codes based on our comprehensive CC/MCC analysis.
    Response: As discussed more fully in section II.F. of the preamble 
of this final rule, in general we are not finalizing the proposed 
changes to the severity levels for certain ICD-10-CM diagnosis codes 
based on our comprehensive CC/MCC analysis in order to allow additional 
opportunity for the public to provide further feedback given the broad 
scope and impact of those proposed changes. These comments are included 
in the summary of comments presented in section II.F. of the preamble 
of this final rule for more information.
f. Low-Volume MS-LTC-DRGs
    In order to account for MS-LTC-DRGs with low-volume (that is, with 
fewer than 25 applicable LTCH cases), consistent with our existing 
methodology, as we proposed in the FY 2020 IPPS/LTCH PPS proposed rule 
(84 FR 19464), we are continuing to employ the quintile methodology for 
low-volume MS-LTC-DRGs, such that we grouped the ``low-volume MS-LTC-
DRGs'' (that is, 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 MS-
LTC-DRG to a quintile results in nonmonotonicity within a base-DRG, as 
we proposed, we made adjustments to the resulting low-volume MS-LTC-
DRGs to preserve monotonicity, as discussed in detail in section 
VII.B.3.g. (Step 6) of the preamble of this final rule.
    In this final rule, based on the best available data (that is, the 
March 2019 update of the FY 2018 MedPAR files), we identified 259 MS-
LTC-DRGs that contained between 1 and 24 applicable LTCH cases. This 
list of MS-LTC-DRGs was then divided into 1 of the 5 low-volume 
quintiles, each containing at least 51 MS-LTC-DRGs (259/5 = 51 with a 
remainder of 4). We assigned the low-volume MS-LTC-DRGs to specific 
low-volume quintiles by sorting the low-volume MS-LTC-DRGs in ascending 
order by average charge in accordance with our established methodology. 
Based on the data available for this final rule, the number of MS-LTC-
DRGs with less than 25 applicable LTCH cases was not evenly divisible 
by 5 and, therefore, as we proposed, we employed our historical 
methodology for determining which of the low-volume quintiles would 
contain the additional low-volume MS-LTC-DRG. Specifically for this 
final rule, after organizing the MS-LTC-DRGs by ascending order by 
average charge, we assigned the first 51 (1st through 51st) of low-
volume MS-LTC-DRGs (with the lowest average charge) into Quintile 1. 
Because the average charge of the 52nd low-volume MS-LTC-DRG in the 
sorted list was closer to the average charge of the 53rd low-volume MS-
LTC-DRG (assigned to Quintile 1) than to the average charge of the 51st 
low-volume MS-LTC-DRG (assigned to Quintile 2), we assigned it to 
Quintile 2 (such that Quintile 1 contains 51 low-volume MS-LTC-DRGs 
before any adjustments for nonmonotonicity, as discussed in this final 
rule). The 52 MS-LTC-DRGs with the highest average charge were assigned 
into Quintile 5. This resulted in 4 of the 5 low-volume quintiles 
containing 52 MS-LTC-DRGs (Quintiles 2 through 5) and 1 low-volume 
quintile containing 51 MS-LTC-DRGs (Quintile 1). As discussed earlier, 
for this final rule, we are providing the list of the composition of 
the low-volume quintiles for 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 final rule at: http://www.cms.hhs.gov/Medicare/
Medicare-Fee-for-Service-

[[Page 42435]]

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.
    In order to determine the FY 2020 relative weights for the low-
volume MS-LTC-DRGs, consistent with our historical practice, as we 
proposed, we used the five low-volume quintiles described previously. 
We determined a relative weight and (geometric) average length of stay 
for each of the five low-volume quintiles using the methodology 
described in section VII.B.3.g. of the preamble of this final rule. We 
assigned the same relative weight and average length of stay to each of 
the 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 low-
volume MS-LTC-DRGs and do not result in an unintended financial 
incentive for LTCHs to inappropriately admit these types of cases.
    Comment: A commenter objected to the number of low-volume MS-LTC-
DRGs. The commenter expressed concern that these low-volume MS-LTC-DRGs 
may not have relative weights which accurately reflect the resource use 
for the cases.
    Response: While we appreciate the commenter's concern about the 
number of low-volume MS-LTC-DRGs, we believe our existing methodology 
for assigning relative weights to low-volume DRGs is appropriate. The 
commenter provided no alternative to the existing methodology nor any 
argument which would suggest that our current methodology, which was 
adopted beginning with the initial implementation of the LTCH PPS for 
FY 2003, is somehow inappropriate. Additionally, the use of quintiles 
in assigning weights to low-volume DRGs does account for differences in 
resource use among these DRGs, at least in so far as the resource use 
is reflected in the data. As such, we are finalizing the methodology 
for establishing relative weights for low-volume MS-LTC-DRGs as 
proposed.
g. Steps for Determining the FY 2020 MS-LTC-DRG Relative Weights
    In this final rule, as we proposed in the FY 2020 IPPS/LTCH PPS 
proposed rule (84 FR 19464), we are continuing to use our current 
methodology to determine the FY 2020 MS-LTC-DRG relative weights.
    In summary, to determine the FY 2020 MS-LTC-DRG relative weights, 
as we proposed, we grouped applicable LTCH cases to the appropriate MS-
LTC-DRG, while taking into account the low-volume quintiles (as 
previously described) and cross-walked no-volume MS-LTC-DRGs (as 
described later in this section). After establishing the appropriate 
MS-LTC-DRG (or low-volume quintile), as we proposed, we calculated the 
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 in this 
section). Next, as we proposed, we adjusted the number of applicable 
LTCH cases in each MS-LTC-DRG (or low-volume quintile) for the effect 
of SSO cases (Step 3 in this section). After removing applicable LTCH 
cases with a length of stay of 7 days or less (Step 1 in this section) 
and statistical outliers (Step 2 in this section), which are the SSO-
adjusted applicable LTCH cases and corresponding charges (Step 3 in 
this section), as we proposed, we calculated ``relative adjusted 
weights'' for each MS-LTC-DRG (or 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 calculation of the 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 short stays. Therefore, 
consistent with our existing relative weight methodology, in 
determining the FY 2020 MS-LTC-DRG relative weights, as we proposed, we 
removed 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 calculation of the 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, as we proposed, we continued 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 were removed prior to calculating the 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 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 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 final 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 final calculation of the FY 2020 MS-LTC-DRG 
relative weights, consistent with our historical approach, as we 
proposed, we adjusted 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, as we proposed, we made 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 had 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 
produced 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

[[Page 42436]]

determining the FY 2020 MS-LTC-DRG relative weights would lower the 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, as we proposed, we continued 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 FY 2020 MS-LTC-DRG relative weights on an 
iterative basis.
    Consistent with our historical relative weight methodology, as we 
proposed, we calculated the 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 was 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 MS-LTC-DRG, we calculated the FY 2020 relative weight by 
dividing the SSO-adjusted average of the hospital-specific relative 
charge values for applicable LTCH cases for the 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 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 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) were then 
multiplied by the hospital-specific case-mix indexes. The hospital-
specific case-mix adjusted relative charge values were then used to 
calculate a new set of 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 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 MS-LTC-DRGs for which there 
were no claims in the March 2019 update of the FY 2018 MedPAR file and, 
therefore, for which no charge data was available for these MS-LTC-
DRGs. Because patients with a number of the diagnoses under these MS-
LTC-DRGs may be treated at LTCHs, consistent with our historical 
methodology, we generally assign a relative weight to each of the no-
volume MS-LTC-DRGs based on clinical similarity and relative costliness 
(with the exception of ``transplant'' MS-LTC-DRGs, ``error'' MS-LTC-
DRGs, and 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 final 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.)
    As we proposed, we cross-walked each no-volume MS-LTC-DRG to 
another MS-LTC-DRG for which we calculated a relative weight 
(determined in accordance with the methodology as previously 
described). Then, the ``no-volume'' MS-LTC-DRG was assigned the same 
relative weight (and average length of stay) of the MS-LTC-DRG to which 
it was cross-walked (as described in greater detail in this section of 
this final rule).
    Of the 761 MS-LTC-DRGs for FY 2020, we identified 361 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 in this final rule). As we proposed, we assigned 
relative weights to each of the 361 no-volume MS-LTC-DRGs that 
contained trimmed applicable LTCH cases based on clinical similarity 
and relative costliness to one of the remaining 400 (761 - 361 = 400) 
MS-LTC-DRGs for which we calculated 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'' MS-LTC-DRGs as the MS-LTC-DRGs to which 
we cross-walked one of the 361 ``no-volume'' MS-LTC-DRGs.) Then, as we 
generally proposed, we assigned the 361 no-volume MS-LTC-DRGs the 
relative weight of the cross-walked MS-LTC-DRG. (As explained in Step 6 
of this section, when necessary, we made adjustments to account for 
nonmonotonicity.)
    We cross-walked the no-volume MS-LTC-DRG to a MS-LTC-DRG for which 
we calculated relative weights based on the March 2019 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 MS-LTC-DRGs in FY 2020, the relative weights assigned 
based on the cross-walked 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 relative weight of the cross-walked MS-LTC-DRG 
as the relative weight for the no-volume MS-LTC-DRG such that both of 
these MS-LTC-DRGs (that is, the no-volume MS-LTC-DRG and the cross-
walked MS-LTC-DRG) have the same relative weight (and average length of 
stay) for FY 2020. We note that, if the cross-walked MS-LTC-DRG had 25 
applicable LTCH cases or more, its relative weight (calculated using 
the methodology described in Steps 1 through 4 above) is assigned to 
the no-volume MS-LTC-DRG as well. Similarly, if the MS-LTC-DRG to which 
the no-volume MS-LTC-DRG was cross-walked had 24 or less cases and, 
therefore, was designated to 1 of the low-volume quintiles for purposes 
of determining the relative weights, we assigned the relative weight of 
the applicable low-volume quintile to the no-volume MS-LTC-DRG such 
that both of these MS-LTC-DRGs (that is,

[[Page 42437]]

the no-volume MS-LTC-DRG and the cross-walked MS-LTC-DRG) have the same 
relative weight for FY 2020. (As we noted previously, in the infrequent 
case where nonmonotonicity involving a no-volume MS-LTC-DRG resulted, 
additional adjustments as described in Step 6 were required in order to 
maintain monotonically increasing relative weights.)
    As discussed earlier, for this final rule, we are providing the 
list of the no-volume MS-LTC-DRGs and the MS-LTC-DRGs to which each was 
cross-walked (that is, the cross-walked MS-LTC-DRGs) for FY 2020 in a 
supplemental data file for public use posted via the internet on the 
CMS website for this final 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 relative weights 
for the FY 2020 MS-LTC-DRGs with no applicable LTCH cases, we are 
providing the following example, which refers to the no-volume 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 final rule).
    Example: There were no trimmed applicable LTCH cases in the FY 2018 
MedPAR file that we used for this final rule for MS-LTC-DRG 061 (Acute 
Ischemic Stroke with Use of Thrombolytic Agent with MCC). We determined 
that MS-LTC-DRG 070 (Nonspecific Cerebrovascular Disorders with MCC) is 
similar clinically and based on resource use to MS-LTC-DRG 061. 
Therefore, we assigned the same relative weight (and average length of 
stay) of MS-LTC-DRG 70 of 0.8629 for FY 2020 to MS-LTC-DRG 061 (we 
refer readers to Table 11, which is listed in section VI. of the 
Addendum to this final 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 MS-LTC-DRGs with no volume will vary in the 
future. Consistent with our historical practice, as we proposed, we 
used the most recent available claims data to identify the trimmed 
applicable LTCH cases from which we determined the relative weights in 
this final rule.
    For FY 2020, consistent with our historical relative weight 
methodology, as we proposed, we established a relative weight of 0.0000 
for the following transplant 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 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, as we proposed, we established 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 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 Pub. L. 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

[[Page 42438]]

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, as we proposed in the FY 2020 
IPPS/LTCH PPS proposed rule (84 FR 19467), in this final rule we 
assigned 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 March 2019 
update of the FY 2018 MedPAR file data using the steps previously 
described. Furthermore, we believe 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, as we proposed, we established 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 FY 2020 MS-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 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 FY 2020 MS-LTC-DRG relative 
weights, consistent with our historical methodology, as we proposed, we 
continued 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 FY 2020 MS-LTC-DRG relative weights in this final rule 
by applying this methodology are denoted in Table 11, which is listed 
in section VI. of the Addendum to this final rule and is available via 
the internet on the CMS website.
    Step 7-- Calculate the 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, as we proposed, we updated the MS-LTC-DRG classifications 
and relative weights for FY 2020 based on the most recent available 
LTCH data for applicable LTCH cases, and continued to apply a budget 
neutrality adjustment in determining the FY 2020 MS-LTC-DRG relative 
weights.
    In this FY 2020 IPPS/LTCH PPS final rule, to ensure budget 
neutrality in the update to the MS-LTC-DRG classifications and relative 
weights under Sec.  412.517(b), as we proposed, we continued to use our 
established two-step budget neutrality methodology.

[[Page 42439]]

    To calculate the normalization factor for FY 2020, as we proposed 
in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19468), we grouped 
applicable LTCH cases using the FY 2020 Version 37 GROUPER, and the 
recalibrated 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 FY 2020. That ratio is 
the normalization factor. Because the calculation of the normalization 
factor involves the relative weights for the MS-LTC-DRGs that contained 
applicable LTCH cases to calculate the average CMIs, any low-volume MS-
LTC-DRGs are included in the calculation (and the MS-LTC-DRGs with no 
applicable LTCH cases are not included in the calculation).
    To calculate the budget neutrality adjustment factor, we simulated 
estimated total FY 2020 LTCH PPS standard Federal payment rate payments 
for applicable LTCH cases using the FY 2020 normalized relative weights 
and 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 FY 2020 MS-LTC-DRG 
relative weights and the GROUPER Version 37. The resulting ratio is the 
budget neutrality adjustment factor. The calculation of the budget 
neutrality factor involves the relative weights for the LTCH cases used 
in the payment simulation, which includes any cases grouped to low-
volume MS-LTC-DRGs or to MS-LTC-DRGs with no applicable LTCH cases, and 
generally does not include payments for cases grouped to a 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 relative weight calculation in step (2) that are 
grouped to a MS-LTC-DRG with no applicable LTCH cases) are included in 
the payment simulations used to calculate the budget neutrality factor. 
However, the number and payment amount of such cases have a negligible 
impact on the budget neutrality factor calculation).
    In this final rule, to ensure budget neutrality in the update to 
the MS-LTC-DRG classifications and relative weights under Sec.  
412.517(b), as we proposed, we continued to use our established two-
step budget neutrality methodology. Therefore, in this final rule, in 
the first step of our MS-LTC-DRG budget neutrality methodology, for FY 
2020, as we proposed, we calculated and applied a normalization factor 
to the recalibrated 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 changes to 
the classification system. That is, the normalization adjustment is 
intended to ensure that the recalibration of the MS-LTC-DRG relative 
weights (that is, the process itself) neither increases nor decreases 
the average case-mix index.
    To calculate the normalization factor for FY 2020 (the first step 
of our 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 FY 
2018 MedPAR file) and grouped them using the FY 2020 GROUPER (that is, 
Version 37 for FY 2020) and the recalibrated FY 2020 MS-LTC-DRG 
relative weights (as previously determined in Steps 1 through 6) 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 MS-LTC-DRG 
relative weights for FY 2020, each recalibrated MS-LTC-DRG relative 
weight was multiplied by the normalization factor of 1.27367 
(determined in Step 1.c.) in the first step of the budget neutrality 
methodology, which produced ``normalized relative weights.''
    In the second step of our MS-LTC-DRG budget neutrality methodology, 
we calculated a second 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 final rule, for FY 2020, under the second step of 
the budget neutrality methodology, as we proposed, we determined the 
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 normalized 
relative weights for FY 2020 and GROUPER Version 37 (as previously 
described); (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 FY 2020 MS-LTC-DRG relative weights, 
each normalized relative weight was then multiplied by a budget 
neutrality factor of 0.9959342 (the value determined in Step 2.c.) in 
the second step of the budget neutrality methodology to achieve the 
budget neutrality requirement at Sec.  412.517(b).
    Accordingly, in determining the FY 2020 MS-LTC-DRG relative weights 
in this final rule, consistent with our existing methodology, as we 
proposed, we applied a normalization factor of 1.27367 and a budget 
neutrality factor of 0.9959342. Table 11, which is listed in section 
VI. of the Addendum to this final rule and is available via the 
internet on the CMS website, lists the MS-LTC-DRGs and their respective 
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. 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''

[[Page 42440]]

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 first 
implemented this requirement in the FY 2016 IPPS/LTCH PPS final rule 
(80 FR 49613), and established subregulatory policies and timeframes by 
which we then calculated and informed LTCHs of their discharge payment 
percentage. Such policies included the form letter to be used in the 
notification. As we noted in our proposed rule, 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 has typically been 
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. (For more information on these policies and timelines, we refer 
readers to the FY 2016 IPPS/LTCH PPS final rule at 80 FR 49601 through 
49614.)
    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, in the 
FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19469), we proposed to 
continue to use our established policies and timelines to calculate the 
discharge payment percentage and to continue to inform LTCHs as we have 
in the past when their discharge payment percentage for the cost 
reporting period is not at least 50 percent.
    Comment: Some commenters requested that we require MACs use 
additional data, for example matching the related inpatient PPS and 
LTCH claims data, when determining whether a discharge qualifies for 
exclusion from the site neutral payment rate for the purpose of 
calculating the discharge payment percentage. These commenters believe 
such a requirement would mitigate LTCH disputes when there is a delay 
in the availability of the information on the prior hospital stay, such 
as, data confirming the patient's ICU days during the prior hospital 
stay. Similarly, some commenters further requested that we revise our 
existing policy on the requirements for providing supplementary 
information to exclude a discharge from the site neutral payment rate 
by requiring MACs to obtain certain information from IPPS hospitals. 
Other commenters asked that we exclude the use of updated claims data 
from IPPS hospitals in our calculation of the discharge payment 
percentage if the original claims data supported exclusion, but the 
updated claims data does not. In support of this request, some 
commenters cited concerns about having relied on the initial 
information they receive from referring hospitals, and that it is 
unfair to retroactively penalize them in-so-far as the calculation of 
their discharge payment percentage when their belief that they were 
admitting a case that would be excluded from the site neutral payment 
rate was reasonable.
    Response: We believe our existing policies, which require MACs to 
accept supplementary information from LTCHs in circumstances when the 
data in the Medicare claims system does not contain the applicable 
information demonstrating the discharge meets the criteria for 
exclusion from the site neutral payment rate provides a reasonable 
opportunity for an LTCH to provide additional information to supplement 
the CMS claims data. (For example, if the subsection (d) hospital from 
which the patient was immediately discharged was a Veterans 
Administration hospital, the Medicare claims processing systems would 
not have data from that discharge.) Furthermore, those policies 
appropriately balance the interests of ensuring claims are only 
excluded from the site neutral payment rate when the statutory criteria 
are met while allowing sufficient flexibility for unusual instances 
when information that would support exclusion is not contained in the 
Medicare claims processing system. We believe that in determining 
whether a discharge is excluded from the site neutral payment rate we 
should use the best data reasonably available in accordance with the 
current policy that we proposed continuing to use for purposes of the 
calculation of the discharge payment percentage (which is based on the 
actual determination used for making Medicare payment to the LTCH for 
that discharge). We note our policies for determining whether a 
discharge is excluded from the site neutral payment rate for purposes 
of making Medicare payments, which we proposed to continue to use for 
calculating the discharge payment percentage, were adopted through 
notice and comment rulemaking in the FY 2016 final rule (for more 
information on these policies we refer readers to the FY 2016 IPPS/LTCH 
PPS final rule 80 FR 49601). Finally, in response to specific concerns 
regarding the accuracy of the information received by the LTCH from the 
referring hospital at the time an LTCH makes an admission decision, we 
again encourage LTCHs to work closely with their referring hospitals 
and vice versa to ensure the accuracy of the information to be used in 
admission decisions as well as in discharge planning and case 
management. For these reasons, we believe it is appropriate to finalize 
our proposal to continue to use the current policies and timelines for 
determining when a discharge meets the criteria for exclusion from the 
site neutral payment rate (including those which allow hospitals to 
submit information to supplement information in the Medicare claims 
processing system).
    In addition to our proposed policies regarding notification of 
their calculated discharge payment percentage, 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, in the FY 2020 IPPS/LTCH 
PPS proposed rule we also proposed to establish the policies and timing 
for when an LTCH that does not meet the required discharge payment 
percentage would become subject to a payment adjustment for cost 
reporting periods beginning on or after October 1, 2019. Under our 
proposal, the LTCH would first be notified of the failure to meet that 
requirement (we note that, as discussed above, we proposed to use our 
existing policies regarding notifying an LTCH of its discharge payment 
percentage). Then, if the LTCH is found not to have met the requisite 
discharge

[[Page 42441]]

payment percentage, the LTCH would be subject to the payment adjustment 
for the first cost reporting period after it has been notified that its 
discharge payment percentage for a cost reporting period had been 
calculated to not have been 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, generally 
a hospital's discharge payment percentage for its FY 2020 cost 
reporting period cannot be calculated for approximately 5-6 months; 
that is, it would not be 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 percent (when calculated 
during its FY 2021 cost reporting period), under our proposal, the LTCH 
would be notified of that failure during its FY 2021 cost reporting 
period, and it would become subject to a payment adjustment, which 
would be applied to all of the LTCH's discharges that occur during its 
FY 2022 cost reporting period (that is, the first cost reporting period 
after receiving notification that its discharge payment percentage for 
a cost reporting period had been calculated to not have been at least 
50 percent). In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19470), 
we proposed to codify the proposed implementation of these regulations 
establishing this policy under proposed new Sec.  412.522(d)(3).
    Comment: Most commenters supported our proposal to apply the 
payment adjustment for failure to maintain the required discharge 
payment percentage prospectively, which is to discharges in the cost 
reporting period after the calculation is performed and the facility is 
notified of its percentage. A few commenters objected in general to the 
application of the payment adjustment to facilities that failed to meet 
the required discharge payment percentage, or requested that its 
application be delayed.
    Response: While we sympathize with commenters requesting an 
implementation delay, the payment adjustment for LTCHs which do not 
maintain the requisite discharge payment percentage, we do not have an 
option to forgo implementation or delay application of this statutory 
payment adjustment.
    Comment: Some commenters requested confirmation that the discharge 
payment percentage would be calculated based on the LTCH as a whole 
(for example, for all campuses of a multi-campus LTCH).
    Response: As we stated in the proposed rule, the discharge payment 
percentage is calculated for the hospital, not individual locations of 
the hospital. Therefore, consistent with our proposal, the discharge 
payment percentage will be calculated based on the LTCH as a whole 
using the CMS Certification Number (CCN) on hospital claims submitted 
to Medicare.
    Comment: Some commenters requested confirmation that the LTCH would 
maintain its IPPS-excluded hospital status when subject to the payment 
adjustment.
    Response: A hospital subject to the payment adjustment will remain 
an LTCH as long as it maintains an average length of stay of 25 or more 
days as required under the existing regulations.
    After considering the comments received, we are finalizing our 
proposed payment adjustment policy at Sec.  412.522(d)(3) which will be 
applied to discharges occurring in cost reporting periods beginning on 
or after October 1, 2019, with the initial penalties applied to the 
cost reporting period after the percentage is calculated and the LTCH 
is notified as to the failure to meet the discharge payment percentage 
requirement.
    As previously noted, 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 do so, in the FY 2020 IPPS/LTCH 
PPS proposed rule we proposed to discontinue the payment adjustment 
beginning with the discharges occurring in the cost reporting period 
after the LTCH has been notified that its discharge payment percentage 
was calculated to be at least 50 percent. For example, an 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 previously described. However, if the 
discharge payment percentage for its FY 2021 cost reporting period 
equaled at least 50 percent, the calculation of such percentage (and 
notification thereof) 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 noted 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 the same manner as described 
previously) if its discharge payment percentage is again calculated not 
to meet the required threshold. For instance, if the LTCH in the 
example above were to once again fail to meet the requisite percentage 
in FY 2022, it would be subject to a new payment penalty in FY 2024. We 
proposed to codify this reinstatement process policy at Sec.  
412.522(d)(5).
    Comment: Several commenters supported our reinstatement process 
proposals regarding the discontinuation of penalties. In addition, some 
commenters requested discontinuation of the penalty as soon as an LTCH 
can demonstrate it has met the required discharge payment percentage 
using real-time monitoring, as delaying the removal of the penalty 
until the following cost reporting period would be unduly burdensome 
for hospitals subject to the adjustment for an entire cost reporting 
period.
    Response: We appreciate the commenters' support of the proposed 
discontinuation of penalties under our proposed reinstatement process. 
We do not believe allowing discontinuation of the penalty at any point 
an LTCH demonstrates it has attained the requisite discharge payment 
percentage is appropriate. The calculation of the discharge payment 
percentage is a ratio of discharges paid at the standard Federal 
payment rate to total discharges. Therefore, by definition, every 
discharge from the LTCH will change that percentage. We believe that 
adopting a policy without clear timeframes designated for when the 
calculation of the discharge payment percentage would apply introduces 
instability and unpredictability into the LTCH PPS. Additionally, the 
statute specifically references a hospital's cost reporting period when 
describing when an LTCH should be subject to the adjustment. Therefore, 
we believe that applying the payment adjustment by cost reporting 
period for the entire cost reporting period is most consistent with the 
statute is. As such we are not adopting the commenters' suggestions.
    As discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19470), while we believe the proposed reinstatement process policy 
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

[[Page 42442]]

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 proposed 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, in the FY 
2020 IPPS/LTCH PPS proposed rule we proposed 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 (in this example, 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). (We note that the 
period of time which is used for the cure period calculation must allow 
sufficient time for the MAC to complete the calculation and notify the 
LTCH of the results of the calculation prior to the beginning of the 
cost reporting period during which the payment adjustment otherwise 
would apply if the hospital fails to cure.) 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 proposed to codify the policy for a special probationary 
reinstatement process at Sec.  412.522(d)(6). In the FY 2020 IPPS/LTCH 
PPS proposed rule, we noted that we expect to issue subregulatory 
guidance to describe the specific procedures for implementing this 
proposed probationary-cure period, if the policy is finalized. We also 
invited 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.
    Comment: Many commenters supported our proposal to adopt a special 
probationary cure period, while some commenters opposed it. The 
commenters that opposed the proposed special probationary cure period 
stated that such a policy is not required by statute and as such 
creates unnecessary work for MACs and hospitals.
    Response: We appreciate the commenters' support for our proposal to 
adopt a special probationary cure period as part of the reinstatement 
process. While we agree that a probationary reinstatement process is 
not required under the statute, as we stated in the proposed rule, at 
this time we believe that the use of a probationary cure period is the 
best way to balance concern for administrative simplicity while 
allowing for unusual circumstances where the discharge payment 
percentage calculated for a cost reporting period is not fully 
representative of the general mix of standard and site neutral 
discharges for a hospital.
    Comment: Some commenters requested that we align the timing of the 
special probationary reinstatement process with the existing timing for 
the calculation of the average length of stay cure period.
    Response: As we described in the proposed rule and in more detail 
in this final rule, the timing of the calculations for both the special 
probationary reinstatement process and the average length of stay cure 
period are the same, namely at least 5 consecutive months of the 6 
months immediately preceding the cost reporting period for which, in 
the case of the special probationary reinstatement process, the payment 
adjustment would apply or, in the case of the average length of stay 
cure period, the hospital would lose its IPPS-excluded status. 
Therefore, we believe that these comments are generally supportive of 
our proposal and thank commenters for their support. To the extent that 
any of these comments were referring to the lack of a provisional 
determination under the existing timing for the calculation of the 
average length of stay cure period, we refer reader to our response to 
the comments opposing the probationary nature of the proposed cure 
period discussed below.
    Comment: Some commenters opposed the probationary nature of the 
proposed special reinstatement process (that is, probationary cure 
period). Some commenters objected to the period of time between when 
the discharges in a cost reporting period may be subject to a payment 
adjustment and the final determination of whether such an adjustment 
would be applied, indicating it would be unduly burdensome for 
hospitals. Other commenters pointed out that because the cure period 
for the calculation of an LTCH's average length of stay is not 
probationary, it should not be in this context either. Some commenters 
argued that our policy concerns underlying the probationary nature of 
the special reinstatement process are unfounded, some of which cited 
timely filing requirements that allow for up to a year to bill the 
Medicare program.
    Other commenters argued that the special probationary reinstatement 
process would result in an LTCH being penalized twice for not 
maintaining the requisite discharge payment percentage

[[Page 42443]]

during the same cost reporting period because, in the commenters' view, 
the payment adjustment would be applied twice based on a single cost 
reporting period's calculation. Some commenters stated that using a 
probationary cure period as part of the reinstatement would result in 
increased unpredictably to payments and is contrary to the principles 
of prospective payment. Some commenters requested that we also adopt a 
policy which would allow for application of the payment adjustment to 
be reversed if, after having been applied it is determined that the 
hospital met the requisite discharge payment percentage during the cost 
reporting period in which the penalty is applied (we note that under 
our proposed policy, the only situation in which this would occur would 
be if the LTCH did not meet the requisite threshold during its cure 
period). Lastly, a few commenters stated that our proposal on the 
mechanics of the special probationary reinstatement process was unclear 
and did not allow for meaningful comment.
    Response: As we previously stated, we believe a probationary 
reinstatement process balances the ability to provide for an 
opportunity to allow for unusual circumstances where the discharge 
payment percentage may not be fully representative of the general mix 
of an LTCH's discharges and the desire for administrative simplicity, 
as well as the concerns stated in the proposed rule (and discussed 
further in this final rule) related to maintaining the integrity of the 
statutory payment adjustment for LTCHs that do not maintain the 
required discharge patient percentage. We recognize the special 
probationary cure period inherently requires additional time between 
when the discharges in a cost reporting period may be subject to the 
payment adjustment and when a final determination is made as to whether 
the adjustment is applied. However, we believe the special probationary 
cure period appropriately balances the competing goals previously 
outlined. We also note that under our proposed policy, the timing of 
final settlement of the cost report will be unaffected. If, as we gain 
experience under this policy, it appears that the probationary nature 
of the cure period feature of the reinstatement process results in 
excessive burden to LTCHs we could re-examine the need for the special 
probationary reinstatement process entirely as it is not required under 
the statute (as noted previously). A final prospective determination 
based on the entirety of a cost reporting period as described in the 
general reinstatement process would eliminate the concerns regarding 
the probationary reinstatement process while fulfilling statutory 
obligations.
    In response to the argument that our policy concerns, such as 
potential manipulation of billing during the cure period, is unfounded, 
we disagree. As pointed out by commenters, timely filing rules allow 
for up to a year to bill the Medicare program, and, as such, an LTCH 
could engineer its discharge payment percentage for the 5 to 6 month 
cure period, to be greater than 50 percent. For example, within the 1-
year timely filing period, an LTCH could purposely chose to hold its 
claims for site neutral discharges during the cure period (or submit 
claims for standard Federal payment rate discharges which had been held 
prior to the start of the cure period) for no reason other than to 
ensure that its discharge payment percentage for the cure period meets 
the requisite percentage. While such billing practices may be 
permissible under the timely filing requirements, it could encourage 
artificially inflated discharge payment percentages during the cure 
period in an effort to game the discharge payment percentage to avoid 
the payment adjustment required by the statute. In such a case, when 
those held claims are finally submitted and processed, we would expect 
the discharge payment percentage for discharges occurring during the 
cure period to be lower than it was calculated to have been based on 
claims data available at the time it was calculated. As such, the LTCH 
compliance with the discharge payment percentage requirement could 
fluctuate solely based on its billing practices. For these reasons, we 
believe it is appropriate that the cure period component of the 
reinstatement process be probationary in order to effectively preclude 
such behavior.
    In response to the commenters' observation that the average length 
of stay cure period is not probationary, we note the loss of IPPS-
excluded status as a result of failure to maintain the requisite 
average length of stay, may only happen at the beginning of a cost 
reporting period. As we stated in response to previous comments, 
failure to maintain the requisite discharge payment percentage does not 
in itself result in a change in the classification of the hospital 
(that is, a hospital which does not maintain its average length of stay 
will cease to be an LTCH, while a hospital which does not maintain its 
discharge payment percentage, but remains in compliance with other 
requirements will remain an LTCH). The regulations at 42 CFR 412.22(d) 
require that a change in a hospital's status from IPPS-excluded to non-
excluded may only occur at the beginning of a cost reporting period, 
therefore it is impractical for the average length of stay cure period 
to be probationary. Because being subject to the payment adjustment is 
not a change in the hospital's IPPS-excluded status (provided the LTCH 
remains in compliance with other requirements), this same concern does 
not exist here, and given the possibility for selective billing 
practices that could result in manipulation of the calculation of the 
discharge payment percentage during the cure period discussed 
previously, we believe the best way to maintain the integrity of the 
program is to use a special probationary reinstatement process.
    As for the assertion that under the probationary cure period an 
LTCH would be penalized twice for failing to make its discharge payment 
percent, we note that there is only one penalty for any given cost 
reporting period in which an LTCH fails to meet the required discharge 
payment percentage. For example, if an LTCH has an cost reporting 
period beginning on January 1, and it is found in 2021 to have failed 
have met the requisite discharge payment percentage for its 2020 cost 
reporting period, the payment adjustment would be applied in its 2022 
cost reporting period. However, if during the cure period (that is, at 
least 5 consecutive months between July and December 2021) the 
discharge payment percentage is at least 50 percent, the payment 
adjustment in 2022 is suspended. If the LTCH failed to cure and its 
discharge payment percentage for the hospital's FY 2022 cost reporting 
period did not meet the requisite discharge payment percentage, the 
suspended adjustment (which is a result of its failure to maintain the 
requisite discharge payment percentage during the FY 2020 cost 
reporting period) will be applied to that period. Failure to meet the 
requisite percentage during the FY 2022 cost reporting period would 
also mean the LTCH would be notified of that failure in FY 2023, and 
subject to a separate adjustment (as a result of its failure to 
maintain the requisite discharge payment percentage) during its FY 2024 
period. Prior to the application of the adjustment during its FY 2024 
cost reporting period, the LTCH would (again) be allowed to take 
advantage of the probationary cure period. Thus, while the penalty 
operates on a 2- year delay, and the granting or denying of the cure is 
based on a later

[[Page 42444]]

year's performance, there is only ever one penalty imposed per cost 
reporting period.
    In response to concerns about introducing increased 
unpredictability, as previously discussed, we believe a probationary 
cure period appropriately balances providing an opportunity to 
recognize unusual circumstances when the discharge payment percentage 
does not fully reflect the general mix of an LTCH's discharges while 
affording protections to the Medicare program from potential 
manipulation of discharges or billing practices in an effort to qualify 
for the special reinstatement process. As previously discussed, if the 
special reinstatement process is found to be overly burdensome, we will 
re-examine these policies in a future rulemaking.
    In response to concerns that suspending the payment adjustment 
during interim claims payment but the applying the payment adjustment 
at final settlement of the cost report is contrary to the principles of 
prospective payment, we note that there are several other instances 
where LTCH PPS payments made during a cost reporting period are ``trued 
up'' at cost report settlement (for example, periodic interim payments 
or outlier reconciliation). Therefore we do not believe the special 
probationary reinstatement policy would be contrary to the principles 
of prospective payment.
    In response to requests to add a second cure period in which 
adjusted payments may be unadjusted if, during the cost reporting 
period in which the adjustment was applied, the discharge payment 
percentage is determined to have exceeded 50 percent, as we noted 
previously, the only way this is possible is if an LTCH does not 
maintain the requisite discharge payment percentage during its cure 
period. Under our proposal, for the LTCH with a January--December cost 
reporting period, if it fails to meet the requisite discharge payment 
percentage during its FY 2020 cost reporting period the LTCH would be 
subject to the payment adjustment during its FY 2022 cost reporting 
only if the discharge payment percentage threshold for the probationary 
cure period were not met. As explained above, such an LTCH's cure 
period would be at least 5 consecutive months between July and December 
2021. As such prior to the application of the adjustment, the LTCH will 
have already had (and failed) two opportunities to demonstrate that it 
met requisite discharge payment percentage (that is, its 2020 cost 
reporting period and the cure period (which occurs prior to the start 
of its FY 2022 cost reporting period). Taking the commenter's 
suggestion would allow the LTCH a third chance (the FY 2022 cost 
reporting period) to meet the statutorily required discharge payment 
percentage.). We note that this would further complicate a cure process 
that other commenters are already concerned about being overly complex. 
In addition, our proposed probationary cure period already gives LTCHs 
an opportunity to earn suspension of the payment adjustment. Such 
opportunity is not required by statute, but serves to address what we 
find to be valid concerns about unusual circumstances that could result 
in fluctuations in patient populations that would lead to an aberrant 
discharge payment percentage that is not reflective of an LTCH's 
general admissions practices--we do not believe a second opportunity to 
cure 2 years' distant from the initial nonconforming cost reporting 
period is necessary to address such unusual circumstances. That is, we 
would not anticipate any such unusual circumstances resulting in 2 
years-worth of non-compliance. Furthermore, any such reopening process 
would introduce additional unpredictability and administrative expense 
that we do not find justified in light of the issue we intended to 
address with the cure period.
    Finally, we disagree with commenters' allegations that our proposal 
did not provide sufficient details on the mechanics of the special 
probationary reinstatement process to allow for meaningful comment. As 
we have previously summarized, we received many comments on various 
facets of the proposal which would not have been possible had our 
proposal been as unclear as these commenters allege. For these reasons 
we believe that the proposed rule provided ample opportunity for 
meaningful notice and comment rulemaking.
    After considering the comments received, for the reasons previously 
discussed, we are finalizing our policy as proposed.
    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. In the FY 2020 IPPS/LTCH PPS proposed rule, 
we noted 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 Pub. 
L. 113-67, we proposed 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 cost reporting periods beginning 
after the LTCH is informed that its calculated discharge payment 
percent is not at least 50 percent at the 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 noted that the 
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).
    Comment: Several commenters supported our proposed methodology for 
calculating the adjusted payment amount. Some commenters requested 
clarification that the payment adjustment would be the full amount 
calculated under Sec.  412.529(d)(4)(i)(A), not the per diem amount.
    Response: The commenters are correct that the adjusted payment 
would be the full amount, not the per diem. As noted in the proposed 
rule and in this final rule stated, the IPPS comparable per diem amount 
is calculated in accordance with the provisions of Sec. Sec.  
412.529(d)(4)(i)(B) and (C), and our proposed codification of our 
proposed policy at new Sec.  412.522(d)(4) does not incorporate the 
provisions of Sec. Sec.  412.529(d)(4)(i)(B) and (C). In the interests 
of providing clarity, we are revising our proposed regulation text in 
response to these comments. In order to distinguish the amount paid 
under this adjustment from the IPPS comparable per diem amount (used 
for site neutral payment rate payments and SSO payments), rather than 
referring to payments under the adjustment as made at ``an amount 
comparable'' to the IPPS amount we are finalizing regulations which 
will refer to the amount paid under this adjustment to ``an amount 
equivalent'' to the IPPS amount. We believe this change will prevent 
any possible confusion of the regulations or any incorrect application 
of a per diem payment under this adjustment.

[[Page 42445]]

    Additionally, in light of this comment, we carefully reviewed the 
proposed regulations text to ensure clarity. It stated that the payment 
amount for discharges subject to this adjustment is determined under 
Sec. Sec.  412.529(d)(4)(i)(A) and (ii). The calculation defined at 
Sec.  412.529(d)(4)(i)(A) is the calculation of the full IPPS 
comparable amount, not the per diem (the calculation of the per diem is 
calculated in Sec.  412.529(d)(4)(i)(B)). As stated in Sec.  
412.529(d)(4)(i)(A), the calculation is based on the sum of the 
applicable operating IPPS standardized amount and the capital IPPS 
Federal rate in effect at the time of the LTCH discharge. Subclause 
(ii) of Sec.  412.529(d)(4) sets forth the IPPS operating standardized 
amount component of the calculation at Sec.  412.529(d)(4)(i)(A), and 
the IPPS capital Federal rate component of the calculation referenced 
at Sec.  412.529(d)(4)(i)(A) is set forth at subclause (iii) of Sec.  
412.529(d)(4). Having provided a citation to one portion of the cited 
variables found in Sec.  412.529(d)(4)(i)(A), that is, Sec.  
412.529(d)(4)(i)(A)(ii), we should have provided the other, Sec.  
412.529(d)(4)(i)(A)(iii), or omitted both and simply relied upon Sec.  
412.529(d)(4)(i)(A). As we believe it is clearer to cite to both (ii) 
and (iii) as well as Sec.  412.529(d)(4)(i)(A), we are adding the 
citation to the IPPS capital Federal rate component at Sec.  
412.529(d)(4)(iii). Therefore, in the interest of clarity, we are 
including the specific citation to Sec.  412.529(d)(4)(iii) in addition 
to the proposed citations to Sec.  412.529(d)(4)(i)(A) and (ii). 
Accordingly, under this payment adjustment at new Sec.  412.522(d)(4), 
an LTCH will receive payment at the amount equivalent to the IPPS 
amount determined under Sec. Sec.  412.529(d)(4)(i)(A), (ii) and (iii), 
with an additional payment for high cost outlier cases based on the 
IPPS fixed-loss amount in effect at the time of the LTCH discharge.
    While we did not receive any comments specifically related to our 
proposal to include a payment for high cost outlier cases based on the 
IPPS fixed-loss amount in the payment adjustment set forth at new Sec.  
412.522(d)(4), we are taking this opportunity to clarify that the 
outlier payment included as part of the calculation under this 
adjustment differs from our policy for making LTCH PPS outlier payments 
for site neutral discharges. This is due to the difference in the 
applicable statutory language. Section 1886(m)(6)(c)(ii)(II) of the Act 
states the adjusted payment for failing to maintain the requisite 
discharge payment percentage shall be the amount that ``would apply 
under subsection (d) for the discharge if the hospital were a 
subsection (d) hospital.'' To effectuate this statutory direction, we 
proposed to use the unadjusted IPPS comparable amount including an 
amount that would account for any high cost outliers payment which 
would have been paid to an IPPS hospital for the discharge (that is the 
amount of outlier payment would be determined based on the IPPS HCO 
threshold and fixed-loss amount) since high cost outlier payments are 
provided for under subparagraph (5)(A)(ii) of ``subsection (d)''.
    Furthermore, while this amount is the same as fixed-loss amount 
used to determine LTCH PPS outlier payments for the site neutral 
payment rate for FY 2020 (as discussed in section V.D.4. of the 
Addendum of this final rule), this may not be the case in the future. 
As we discussed in the FY 2016 IPPS/LTCH PPS final rule (80 FR 49617), 
we have stated that when we have sufficiently stable data for site 
neutral payment rate cases, we intend to calculate an HCO threshold and 
fixed-loss amount specifically for site neutral discharges rather than 
continue to use the IPPS HCO threshold and fixed loss amount. At that 
time, the outlier payment included as part of the calculation under the 
payment adjustment applied to discharges under this section will 
continue to use the IPPS HCO threshold and fixed loss amounts because 
those would determine the payment for a discharge from a subsection (d) 
hospital. The provisions for payment for site neutral discharges at 
section 1886(m)(6)(b) of the Act instruct CMS to use the IPPS 
comparable per diem amount and outliers. CMS' longstanding policy (of 
which Congress was aware when the site neutral payment rate was 
enacted) is that high cost outlier payments under a particular 
prospective payment system are made in a budget neutral manner within 
that system. This is done through the application of a budget 
neutrality adjustment to payments in the system. The statutory language 
that directs adjustment of the payments to hospitals which do not 
maintain the requisite discharge payment percentage instructs payment 
equivalent to the amount that would be paid to a subsection (d) 
hospital.
    Comment: Some commenters requested confirmation that the adjustment 
would be appealable to the PRRB.
    Response: These payment adjustments would constitute final agency 
action which is appealable to the PRRB, assuming all other applicable 
appeal requirements are met.
    After consideration of the comments we received, for the reasons 
previously discussed, we are finalizing our proposed codification at 
new Sec.  412.522(d)(4)(i)(A) and (ii) with a modification to add a 
citation to Sec.  412.529(d)(4)(iii) for the reasons described above, 
and the substitution of the word ``equivalent'' for the word 
``comparable'' in the interests of providing clarity in response to 
commenter's concerns regarding the possibility of the creation of 
confusion with the IPPS comparable per diem amount.

D. Changes to the LTCH PPS Payment Rates and Other 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 proposed 
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

[[Page 42446]]

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 final rule, we present our policies 
related to the annual update to the LTCH PPS standard Federal payment 
rate for FY 2020.
    The update to the LTCH PPS standard Federal payment rate for FY 
2020 is presented in section V.A. of the Addendum to this final rule. 
The components of the annual update to the LTCH PPS standard Federal 
payment rate for FY 2020 are discussed in this rule, 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 final rule). As 
we proposed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19471), 
we also made 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 final 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 correction to 
the FY 2019 IPPS/LTCH PPS final rule (83 FR 41536) are--
     For FY 2019, a temporary, one-time factor of 0.990878;
     For FY 2020, a temporary, one-time factor of 0.990737; and
     For FY 2021 and subsequent years, a permanent, one-time 
factor of 0.991249.
    Therefore, in determining the FY 2020 LTCH PPS standard Federal 
payment rate, as we proposed, we--
     Removed the temporary, one-time factor of 0.990878 for the 
estimated cost of the elimination of the 25-percent threshold policy in 
FY 2019 by applying a factor of (1/0.990878); and
     Applied a temporary, one-time factor of 0.990737 for the 
estimated cost of the elimination of the 25-percent threshold policy in 
FY 2020.
    Equivalently, in determining the FY 2020 LTCH PPS standard Federal 
payment rate, as we proposed, we applied a temporary, one-time factor 
of 0.999858 (1/0.990878 x 0.990737) to the FY 2019 LTCH PPS standard 
Federal payment rate. The FY 2020 LTCH PPS standard Federal payment 
rate shown in Table 1E in section VI. of the Addendum to this final 
rule reflects this adjustment.
2. 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 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. 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 previously noted, 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 final rule, as we proposed in the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19472-19473), we used 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

[[Page 42447]]

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. 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 final 
rule.)
d. 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 
second quarter 2019 forecast, the FY 2020 full market basket estimate 
for the LTCH PPS using the 2013-based LTCH market basket is 2.9 
percent. The current estimate of the MFP adjustment for FY 2020 based 
on IGI's second quarter 2019 forecast is 0.4 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, 
as we proposed in the FY 2020 IPPS/LTCH PPS proposed rule, we are 
reducing the full estimated FY 2020 market basket increase by the FY 
2020 MFP adjustment. To determine the market basket increase for LTCHs 
for FY 2020, as reduced by the MFP adjustment, consistent with our 
established methodology, we subtracted the 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 2.9 percent update to the LTCH PPS standard Federal payment 
rate for FY 2020 is reduced by the 0.4 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 final rule, in accordance with the 
statute, as we proposed in the FY 2020 IPPS/LTCH PPS proposed rule, we 
reduced the FY 2020 full market basket estimate of 2.9 percent (based 
on IGI's second quarter 2019 forecast of the 2013-based LTCH market 
basket) by the FY 2020 MFP adjustment of 0.4 percentage point (based on 
IGI's second quarter 2019 forecast). Therefore, under the authority of 
section 123 of the BBRA as amended by section 307(b) of the BIPA, as we 
proposed in the FY 2020 IPPS/LTCH PPS proposed rule, we are 
establishing an annual market basket update to the LTCH PPS standard 
Federal payment rate for FY 2020 of 2.5 percent (that is, the most 
recent estimate of the LTCH PPS market basket increase of 2.9 percent 
less the MFP adjustment of 0.4 percentage point). Accordingly, as we 
proposed, we are revising Sec.  412.523(c)(3) by adding a new paragraph 
(xvi), which will 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 2.5 percent, and as further 
adjusted, as appropriate, as described in Sec.  412.523(d) (including 
the application of the adjustment factor for the cost of the 
elimination of the 25-percent threshold policy under Sec.  
412.523(d)(6) as previously discussed). For LTCHs that fail to submit 
quality reporting data under the LTCH QRP, under Sec.  
412.523(c)(3)(xvi) in conjunction with Sec.  412.523(c)(4), as we 
proposed, we further reduced the 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, as we proposed, we are 
establishing an annual update to the LTCH PPS standard Federal payment 
rate of 0.5 percent (that is, 2.5 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, 
as we proposed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19473), we used a more recent estimate of the market basket and the MFP 
adjustment in this final rule to establish an annual update to the LTCH 
PPS standard Federal payment rate for FY 2020 under Sec.  
412.523(c)(3)(xvi). (We note that, consistent with historical practice, 
as we also proposed, we adjusted the 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 final rule).)

VIII. Quality Data Reporting Requirements for Specific Providers and 
Suppliers

    In section VIII. of the preamble of the FY 2020 IPPS/LTCH PPS 
proposed rule (84 FR 19473 through 19554), we proposed changes to the 
following Medicare quality reporting systems:
     In section VIII.A., the Hospital IQR Program;

[[Page 42448]]

     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 that proposed 
rule (84 FR 19554 through 19569), we proposed 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. 
In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19473), we did not 
propose any changes to these policies.
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. In the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19473), we did not propose any changes to 
these policies.
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. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19473), we 
did not propose any changes to this policy.
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. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19473 through 19474), we did not propose any changes to our policies 
regarding measure removal.
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,\335\ 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. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19474), we did not propose any changes to these policies.
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    \335\ 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. New Measures for the Hospital IQR Program Measure Set
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19474 through 
19485), we proposed 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 in this rule.
a. Adoption of Two Opioid-Related eCQMs
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19474 through 
19480), we proposed to add the

[[Page 42449]]

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; 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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19474), we stated 
that 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 in this final rule. We also refer readers to two related 
proposals discussed in this final rule: (1) Section VIII.A.10.d.(1) 
through (4) of the preamble of this final rule where we discuss our 
proposed reporting and submission requirements for eCQMs through the CY 
2022 reporting period/FY 2024 payment determination, including a 
discussion of our proposal to require hospitals to report on the Safe 
Use of Opioids--Concurrent Prescribing eCQM as one of the four required 
eCQMs 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 final rule for a discussion of 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
(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.\336\ 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.\337\ 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.\338\
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    \336\ 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.
    \337\ Centers for Disease Control and Prevention. Drug Overdose 
Epidemic: Behind the Numbers. Available at: https://www.cdc.gov/drugoverdose/data/index.html.
    \338\ 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.\339\ 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.340 341 Rates of fatal overdose are 10 times 
higher in patients who are co-dispensed opioid analgesics and 
benzodiazepines versus opioids alone.\342\ 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.343 344 345 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.\346\ 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.\347\ 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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    \339\ 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.
    \340\ National Institute on Drug Abuse. Benzodiazepines and 
Opioids. Available at: https://www.drugabuse.gov/drugs-abuse/opioids/benzodiazepines-opioids.
    \341\ 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.
    \342\ 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.
    \343\ 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.
    \344\ 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.
    \345\ 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.
    \346\ 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.
    \347\ 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

[[Page 42450]]

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, in 
the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19474 through 19477), we 
proposed to adopt the Safe Use of Opioids--Concurrent Prescribing eCQM 
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 reduce the risk of harm to patients across the continuum 
of care. This measure also seeks to help combat the opioid crisis, 
which has been declared a public health emergency,\348\ 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.\349\ 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.'' \350\
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    \348\ 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.
    \349\ 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.
    \350\ 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.\351\ 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.\352\
---------------------------------------------------------------------------

    \351\ 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.
    \352\ 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).
---------------------------------------------------------------------------

    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.\353\ 
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. We note that the NQF Patient Safety Standing Committee did not 
raise any concerns on the feasibility of the measure during endorsement 
review. In this final rule, we are clarifying that the Safe Use of 
Opioids--Concurrent Prescribing eCQM was developed with broader 
specifications and flexibility in mind. Specifically, the measure, as 
initially developed, captured both encounters from the hospital 
outpatient and inpatient settings so that it could be implemented in 
either setting, with program implementation in either the Hospital 
Outpatient Quality Reporting (OQR) Program and/or the Hospital IQR 
Program to be determined at a later date.
---------------------------------------------------------------------------

    \353\ 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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    We are also clarifying here in the final rule that the measure was 
included in the publicly available ``List of Measures Under 
Consideration for December 1, 2016'' for both the Hospital OQR and 
Hospital IQR Programs,\354\ and considered by the MAP for potential 
inclusion in both programs 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.\355\ 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 if 
previously prescribed opioids and/or benzodiazepines are reduced or 
stopped prior to discharge. 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.\356\
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    \354\ List of Measures Under Consideration for December 1, 2016. 
Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=83923.
    \355\ 2016-2017 Spreadsheet of Final Recommendations to HHS and 
CMS. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=84452.
    \356\ Measure Applications Partnership, January 2017 NQF MAP 
Coordinating Committee Meeting Transcript. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75367.
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    In response to the MAP's recommendation, and as suggested by the 
project's TEP and expert work group, we explored instances where 
concurrent prescribing may be clinically appropriate and assessed the 
impact of adding single-condition exclusions,

[[Page 42451]]

specifically for patients with sickle cell disease and those receiving 
pharmacotherapy for an opioid use disorder. We found that these 
instances comprised a very small portion of eligible cases captured by 
the numerator during testing. After reviewing these testing results, 
clinicians from our expert work group recommended continuing to include 
patients for whom concurrent prescribing may be clinically necessary 
because 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.
    In addition, to address the MAP's feedback regarding the measure's 
feasibility and usability, in May 2017 we refined the measure to: (1) 
Include only encounters for inpatient, ED, and hospital observation 
stays (rather than including encounters spanning inpatient and hospital 
outpatient settings); and (2) include only medications prescribed at 
discharge (rather than those spanning the duration of the encounter) 
(84 FR 19476). In this final rule, we are elaborating on those 
refinements to provide additional clarity as there seemed to be some 
confusion from commenters. These refinements were made to address 
feedback from the MAP concerning the evidence for measuring concurrent 
prescribing across other hospital settings, such as outpatient 
departments, as the available evidence primarily focused on the ED and 
inpatient settings, as well as feasibility and usability concerns 
around capturing medications active on admission and during the care 
encounter which may be modified at discharge. For the MAP review that 
occurred in December 2016 and January 2017, the measure denominator 
included: (a) Encounters for inpatient stays less than or equal to 120 
days, ED, or outpatient stays, and (b) medications prescribed spanning 
the duration of the encounter. After the MAP's review, we refined the 
measure to limit: (a) non-ED hospital outpatient encounters to 
observation stays, and (b) the medications prescribed to only those 
prescribed at discharge.
    The refined measure was submitted to the NQF in late 2017. In this 
final rule, we are clarifying that when the measure was submitted for 
endorsement consideration, the testing and analysis data (for example, 
performance rates, reliability assessment) were separately presented by 
the hospital inpatient and hospital outpatient (ED and observation) 
settings.\357\ The Patient Safety Standing Committee specifically 
reviewed the measure testing results for both the inpatient and 
outpatient settings separately.\358\ As a result, the Patient Safety 
Standing Committee evaluated the measure with data presented for both 
settings and recommended the measure for endorsement in April 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.\359\ 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.\360\ This measure was endorsed by the NQF in May 2018.\361\ 
On November 8, 2018, we shared with the MAP an update on the progress 
of the Safe Use of Opioids--Concurrent Prescribing measure since their 
review in December 2016 and January 2017, as the measure had been 
refined and became endorsed.\362\
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    \357\ Measure Worksheet. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=86521.
    \358\ Ibid.
    \359\ 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.
    \360\ Ibid.
    \361\ Ibid.
    \362\ Meeting agenda from November 8, 2018 web meeting are 
available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=88674. Presentation slides are 
available at: http://www.qualityforum.org/Projects/i-m/MAP/Hospital_Workgroup/Slides_11082018.aspx.
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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.\363\ 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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    \363\ 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.\364\ 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

[[Page 42452]]

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 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.\365\
---------------------------------------------------------------------------

    \364\ National Quality Forum. What NQF Endorsement Means. 
Available at: http://www.qualityforum.org/Measuring_Performance/ABCs/What_NQF_Endorsement_Means.aspx.
    \365\ 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
    While we stated in the FY 2020 IPPS/PPS LTCH proposed rule (84 FR 
19475) that 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), as further discussed below, in this final rule, we 
are clarifying that there may be occasions for which patients admitted 
to the emergency department or for observation stays are not ultimately 
admitted as inpatients; those patients would be excluded from the 
measure. As such, we are clarifying that the measure description to 
reflect that the Safe Use of Opioids--Concurrent Prescribing eCQM is a 
process measure that calculates the proportion of inpatient 
hospitalizations for patients 18 years of age and older prescribed, or 
continued on, two or more opioids or an opioid and benzodiazepine 
concurrently at discharge. 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.
    In the FY 2020 IPPS/PPS LTCH proposed rule (84 FR 19475), we stated 
that 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. We also stated that to reduce 
hospital burden, the definition of ``hospital-based encounter'' is 
aligned with that of other eCQMs in the Hospital IQR Program (84 FR 
19477). In this final rule, we are elaborating on the description of 
the measure cohort to provide additional clarity as there seemed to be 
some confusion from commenters. Specifically, we would like to clarify 
that ED encounters, including observation stays, are only included in 
the measure if such encounters lead to an inpatient hospitalization for 
purposes of the Hospital IQR Program. We further discuss this 
clarification of the measure cohort in response to comments as 
described below.
    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.
    As discussed above, while we stated in the FY 2020 IPPS/PPS LTCH 
proposed rule (84 FR 19475) that patients are included in the 
denominator if they were discharged from a hospital-based encounter 
(inpatient stay less than or equal to 120 days or ED encounters, 
including observation stays) during the measurement period, and their 
medications at discharge included a new or continued Schedule II or III 
opioid, or a new or continued Schedule IV benzodiazepine prescription, 
we would like to clarify that ED encounters, including observation 
stays, are only included in the measure if such encounters lead to an 
inpatient hospitalization for purposes of the Hospital IQR Program. 
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.
    As mentioned earlier in this discussion, in the FY 2020 IPPS/PPS 
LTCH proposed rule (84 FR 19477), we referred readers to the measure 
specifications located on the NQF website for more information about 
the Safe Use of Opioids--Concurrent Prescribing eCQM.\366\ We wish to 
clarify that given this measure was proposed and is being finalized 
under the Hospital IQR Program, we believe it is appropriate to focus 
on inpatient stays. As such, and as further discussed in response to 
comments below, in this final rule, we are providing an updated version 
of the measure specifications, which can be found at the eCQI Resource 
Center's Pre-Rulemaking Eligible Hospital/Critical Access Hospital 
eCQMs website, available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
---------------------------------------------------------------------------

    \366\ 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.
---------------------------------------------------------------------------

    We also refer readers to section VIII.A.10.d.(1) through (4) of the 
preamble of this final rule where we discuss our proposed eCQM 
reporting and submission requirements through the CY 2022 reporting 
period/FY 2024 payment determination, including a discussion of our 
proposal that all participating hospitals report the Safe Use of 
Opioids--Concurrent Prescribing eCQM 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 final rule for a discussion of 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.
    Comment: Many commenters supported adopting the Safe Use of 
Opioids--Concurrent Prescribing eCQM. Noting that concurrent 
prescribing presents a significant public health risk, many commenters 
supported the measure because it would promote safer prescribing 
practices and help focus efforts to address the opioid crisis. Some 
commenters supported the measure based on their belief that it would 
reduce the usage of unnecessary

[[Page 42453]]

opioid prescriptions, provide valuable data about hospital prescribing 
practices, and help provider efforts to monitor opioid prescribing 
patterns. A commenter noted that the measure may serve to increase 
provider awareness of the overall rate of opioid use and potentially 
increase the use of non-opioid alternatives for pain management when 
appropriate. Another commenter expressed support for the measure and 
further noted that the measure could be incorporated into decision 
support tools via flags or drug warnings.
    A commenter supported the measure because it aligns with the goals 
set forth in the National Action Plan for Adverse Drug Event Prevention 
(ADE Action Plan), which has identified accidental overdose or 
respiratory depression associated with opioid use as high-priority 
areas.\367\
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    \367\ Office of Disease Prevention and Health Promotion (ODPHP). 
(2014). National Action Plan for Adverse Drug Event Prevention. 
Available at: https://health.gov/hcq/ade-action-plan.asp.
---------------------------------------------------------------------------

    Response: We thank commenters for their support. We agree that this 
measure promotes safer prescribing practices that may help efforts to 
combat the negative impacts of the opioid crisis.
    Comment: Some commenters did not support the measure because the 
outpatient observation and emergency department (ED) settings are 
included with the inpatient setting, based on concerns that many 
concurrent prescriptions originate in outpatient settings. One 
commenter requested that CMS provide further clarification about how 
this measure should be appropriately applied for certain patients who 
are discharged from the ED. A commenter expressed their belief that it 
is considered poor clinical care for emergency providers to discontinue 
preexisting medications for patient conditions they are not managing on 
a day-to-day basis. A few commenters recommended implementation of the 
measure in the outpatient setting as a separate measure. A commenter 
noted that a patient's focus in the acute care setting should be on 
healing from the acute episode, and suggested that implementing the 
measure in the outpatient setting when the patient is more stable as 
more appropriate.
    Response: We thank commenters for pointing out this discrepancy. We 
wish to clarify that given that this measure was proposed and is being 
finalized under the Hospital IQR Program, we believe it is appropriate 
to focus on inpatient stays. As we stated in the proposed rule, to 
reduce hospital burden, the definition of ``hospital-based encounter'' 
with regard to this measure is aligned with that of other eCQMs in the 
Hospital IQR Program (84 FR 19477). We are clarifying here that 
qualifying encounters for the Safe Use of Opioids--Concurrent 
Prescribing eCQM are consistent with other eCQMs in the Hospital IQR 
Program by also evaluating discharge data from inpatient 
hospitalizations only, including inpatient admissions that were 
initiated in the emergency department or in observation status followed 
by hospital admission. For example, the cohort for the ED-02 eCQM 
includes ``inpatient encounters ending during the measurement period 
with length of stay (discharge date minus admission date) less than or 
equal to 120 days'' (78 FR 50807).\368\ This is because there may be 
occasions in which patients admitted to the emergency department or for 
observation stays are not ultimately admitted as inpatients. We agree 
that those patients should be excluded from the measure and this was 
our intent in the proposed rule; however, the technical specifications 
referenced in the proposed rule were overly broad and not clearly 
consistent with the proposal. As noted previously, the Safe Use of 
Opioids--Concurrent Prescribing eCQM was developed with broader 
specifications with flexibility in mind. Specifically, the measure, as 
initially developed, captured both encounters from the hospital 
outpatient and inpatient settings so that it could be implemented in 
either setting, with program implementation in either the Hospital 
Outpatient Quality Reporting (OQR) Program and/or the Hospital IQR 
Program to be determined at a later date.
---------------------------------------------------------------------------

    \368\ Measure specifications for ED-02 are available at: https://ecqi.healthit.gov/ecqm/measures/cms111v8.
---------------------------------------------------------------------------

    To correct this inconsistency, we have adjusted the technical 
specifications to remove discharges from the emergency department and 
observation stays such that the measure unambiguously reflects 
discharges from inpatient hospitalizations only. We have made this 
minor refinement to the technical specifications to address confusion 
about which emergency department or observation stay encounters are 
included in the measure for implementation in the Hospital IQR Program, 
which are available here at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms. We believe this minor refinement aligns with the scope of 
the Hospital IQR Program and more accurately reflects the original 
intent of the measure as proposed--the measure will only capture data 
at discharge for those ED or observation stay encounters for which the 
patients are admitted to and ultimately discharged from the inpatient 
setting for purposes of the Hospital IQR Program. Moreover, we note 
that the definition of ``hospital-based encounter'' of the corrected 
measure specifications is now aligned with that of other eCQMs in the 
Hospital IQR Program by evaluating discharge data from inpatient 
hospitalizations only, in keeping with our stated intention when we 
proposed this measure (84 FR 19477). In addition, the update has 
simplified the measure specifications by removing a value set and a 
piece of logic from the original measure specifications. In this final 
rule, we are providing an updated version of the measure specifications 
narrowly tailored to the inpatient setting, which can be found at the 
eCQI Resource Center's Pre-Rulemaking Eligible Hospital/Critical Access 
Hospital eCQMs website, available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms. Thus, we are finalizing this measure with a 
clarification and update to the technical specifications so that the 
measure is clearly applicable only to the inpatient setting for 
implementation into the Hospital IQR Program.
    As to the commenter's concern that the emergency department is not 
the appropriate setting to discontinue preexisting medications for 
patient conditions they are not managing on a day-to-day basis--we 
reiterate that the goal of this measure is not to discontinue 
concurrent prescriptions of opioids and/or benzodiazepines that are 
clinically appropriate. Rather, the goal of this measure is to promote 
accountability and awareness of medication combinations that potentiate 
adverse events, help hospitals identify and monitor patients at risk, 
and provide valuable data about a high-risk prescribing area at 
discharge from inpatient hospitalizations, including care that 
originates in the emergency department.
    Comment: A commenter recommended that the measure be implemented in 
other programs that encompass outpatient care, such as Accountable Care 
Organization (ACO) and Bundled Payments for Care Improvement (BPCI) 
participants.
    Response: We thank commenter for their recommendation, which we 
will share with these programs.
    Comment: Many commenters appreciated that the measure excludes 
patients with an active diagnosis of cancer or order for palliative 
care (including hospice care) during the encounter.
    Response: We thank commenters for their support. The measure 
excludes

[[Page 42454]]

patients with an active diagnosis of cancer or order for palliative 
care (including comfort measures, terminal care, dying care, and 
hospital care) during the encounter. These exclusions align with the 
populations excluded from the 2016 CDC Guideline for Prescribing 
Opioids for Chronic Pain.
    Comment: A commenter supported the measure and also recommended 
that CMS measure the degree to which orders for opioids involve the use 
of a Computerized Physician Order Entry (CPOE) system, noting that the 
checks and balances of CPOE results in safer prescriptions and that 
this would help measure the measurement gap area of medication errors.
    Response: We thank commenter for their support. We note that 
providers are required to submit eCQMs using certified EHR technology 
(CEHRT), and that CPOE functionality is part of the 2015 Edition Base 
EHR definition.\369\
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    \369\ https://www.healthit.gov/test-method/computerized-provider-order-entry-cpoe-medications.
---------------------------------------------------------------------------

    Comment: Some commenters welcomed the addition of the measure to 
the eCQM measure set and supported the measure from an implementation 
perspective. A commenter that was involved in feasibility testing of 
the measure noted that the data elements were reasonable to collect, 
not disruptive to clinical workflow, and did not cause undue burden. A 
few commenters noted that the measure used straightforward logic and 
would be relatively easy to implement within the EHR with discrete data 
sources. Many commenters noted that the data sources that the measure 
draws upon are the same ones that hospitals use to evaluate prescribing 
patterns.
    Response: We thank commenters for their support. The measure was 
developed with implementation feasibility and ease in mind. We note 
that testing showed that 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.
    Comment: A commenter who supported the measure noted that care 
decisions ultimately rest on the provider-patient relationship in 
coordination with the clinical best practices based on diagnosis.
    Response: We agree with the commenter and note that the Safe Use of 
Opioids--Concurrent Prescribing eCQM is intended to reduce preventable 
mortality and adverse outcomes related to opioid use by encouraging 
providers to identify and be aware of patients with documentation of 
concurrent prescriptions and discouraging providers from concurrent 
prescribing whenever appropriate.
    Comment: A few commenters who supported the measure recommended 
that CMS continue to monitor the measure to identify and address any 
potential unintended consequences.
    Response: As with all measures, we monitor and evaluate quality 
measures after they are adopted and implemented into the Hospital IQR 
Program. We will continue engaging with stakeholders through education 
and outreach opportunities, which include webinars and submitted help 
desk questions through the ONC JIRA's eCQM issue tracker for eCQM 
implementation and maintenance,\370\ for any feedback about potential 
unintended consequences.
---------------------------------------------------------------------------

    \370\ Available at: https://oncprojectracking.healthit.gov/support/secure/BrowseProjects.jspa?selectedCategory=all&selectedProjectType=all.
---------------------------------------------------------------------------

    Comment: A few commenters recommended that the measure should be 
limited to new prescriptions only and not renewals, or to medications 
initiated during and related to that encounter. A commenter noted that 
measuring new concurrent prescriptions would provide valuable data 
about hospital prescribing practices and may be a more relevant and 
useful indicator of hospital care than assessing continued opioid 
concurrent prescriptions given at discharge. A number of commenters 
recommended refinements to exclude patients who are already on two 
opioids or an opioid and a benzodiazepine prior to hospital admission. 
A commenter noted that such exclusions could be identified through 
present on admission codes.
    Response: We believe it is important to monitor concurrent 
prescribing of opioids and/or benzodiazepines regardless of whether the 
prescriptions are new or existing. As previously discussed, the goal of 
this measure is to help hospitals identify and monitor patients at risk 
of an adverse event from opioid use and provide valuable data about a 
high-risk prescribing area. Patients at risk of an adverse event from 
opioid use include not only patients prescribed new concurrent 
prescriptions of opioids and/or benzodiazepines, but also patients on 
existing concurrent regimens of opioids and/or benzodiazepines 
identified as medications present on admission. The focus of the 
measure is to encourage providers to identify patients on medications 
combinations that could lead to adverse drug events at discharge and 
inform decision-making about whether reevaluation of the current 
medications regimen is warranted. We reiterate that the goal of this 
measure is not to discontinue concurrent prescriptions of opioids and/
or benzodiazepines that are clinically appropriate.
    Comment: Several commenters expressed concern that the measures do 
not evaluate the process used by hospital-based providers in reaching 
the decision to initially prescribe opioids, and therefore may not 
improve the quality of care or drive the types of changes that would 
impact the opioid crisis.
    Response: We acknowledge commenters' concerns, but note that the 
Safe Use of Opioids--Concurrent Prescribing eCQM is a measure that 
seeks to encourage compliance with guidance from several national, 
state-level, and professional society guidelines and safer prescribing 
practices by identifying high-risk patients with concurrent regimens by 
measuring the proportion of patients aged 18 years and older prescribed 
two or more opioids or an opioid and benzodiazepine concurrently at 
discharge from a hospital-based encounter. By capturing denominator 
patients whose discharge medications included a new or continued 
Schedule II or III opioid, or a new or continued Schedule IV 
benzodiazepine prescription, and identifying numerator patients who 
have concurrent medication regimens at discharge from hospitalization, 
this measure provides a way for hospitals to identify and target 
interventions to patients in order to reduce risk of adverse drug 
events and, ultimately, the risk of harm to patients across the 
continuum of care. By enhancing availability of the measure's 
information to hospital providers, experts consulted during measure 
development suggested that the measure would be useful in offering 
organization insights into the scope of the problem and could result in 
process improvements such as care coordination with other providers who 
care for the patient, additional patient education and counselling, or 
consideration of alternative pain treatment, which is another important 
strategy in preventing adverse drug events.
    Comment: Several commenters expressed concern with the measure 
exclusions, with a commenter stating their belief that CMS has not 
provided sufficient data to demonstrate that the measure will capture 
only those patients for whom concurrent prescribing is not appropriate. 
A few commenters recommended that the measure's exclusion for cancer 
and palliative care

[[Page 42455]]

be expanded, with a commenter expressing concern that the measure's 
exclusion for palliative care does not fully capture terminally ill 
patients.
    Several commenters recommended that the measure exclude patients 
with sickle cell disease. A commenter noted that the CDC recently 
clarified in a letter to three specialty societies that the CDC 
Guideline for Prescribing Opioids for Chronic Pain do not apply to 
patients with a diagnosis of sickle cell disease.\371\
---------------------------------------------------------------------------

    \371\ Clarification letter to NCCN, ASCO, and ASH on the CDC's 
Guideline for Prescribing Opioids for Chronic Pain. February 2019. 
Available at: https://www.asco.org/sites/new-www.asco.org/files/content-files/advocacy-and-policy/documents/2019-CDC-Opioid-Guideline-Clarification-Letter-to-ASCO-ASH-NCCN.pdf.
---------------------------------------------------------------------------

    Some commenters recommended excluding patients receiving medication 
for the treatment of opioid use disorder (OUD). A few commenters 
specifically recommended that the measure exclude patients being 
treated with buprenorphine or methadone for OUD, with a commenter 
citing guidance from the U.S. Food & Drug Administration regarding 
buprenorphine.\372\
---------------------------------------------------------------------------

    \372\ U.S. Dep't of Food & Drug Administration. (2019). Opioid 
Use Disorder: Developing Depot Buprenorphine Products for Treatment 
Guidance for Industry. Available at: https://www.fda.gov/media/112739/download.
---------------------------------------------------------------------------

    Response: We recognize that there may be some clinically necessary 
situations for concurrent prescriptions of opioids and benzodiazepines, 
and we agree with the need to properly treat these patients. Regarding 
the commenter's concern that the measure's exclusion for palliative 
care does not fully capture terminally ill patients, we note that 
patients with an order for palliative care during the encounter are 
excluded from the denominator, which includes comfort measures, 
terminal care, dying care, and hospice care, and that these exclusions 
align with the populations excluded from the 2016 CDC Guideline for 
Prescribing Opioids for Chronic Pain. As recommended by our expert 
panels, we looked into single-condition exclusions--specifically sickle 
cell disease and opioid use disorder, and found that a very small 
portion of cases eligible for the numerator (0 to 3.4 percent) fell 
into this category. Furthermore, after reviewing the testing results, 
clinicians from our expert panel recommended continuing to include 
patients for whom concurrent prescribing is medically necessary, 
because experts stated these populations: (1) Have the highest risk of 
receiving concurrent prescriptions; and (2) can experience a lag in 
adverse events. However, we will consider these comments and other 
suggested exclusions, such as patients on medication assisted therapy 
for opioid use disorder (OUD) and patients being treated with 
buprenorphine or methadone for OUD, when evaluating opportunities to 
refine the measure in the future.
    Comment: A number of commenters recommended expanding the 
denominator exclusions to include patients with chronic pain and 
patients who are receiving opioids for the treatment of addiction. A 
commenter recommended excluding patients with advanced stages of 
diseases including cancer, AIDS, dementia and other incurable 
neurodegenerative diseases, chronic lung disease, end stage renal 
disease, cirrhosis, heart failure, hemophilia, or sickle cell disease. 
Another commenter recommended excluding patients suffering from complex 
poly trauma, spinal cord injury with spasticity and extensive burns. A 
few commenters also suggested excluding patients discharged to other 
healthcare facilities, such as skilled nursing facilities or hospices, 
as those patients have more serious disease(s) and require closer 
monitoring and supervision.
    Response: We note that the measure currently excludes patients with 
an active diagnosis of cancer. Also, as previously discussed, we 
considered excluding patients with sickle cell disease but found that a 
very small portion of cases eligible for the numerator fell into this 
category. We recognize that there are many types of cases in which 
concurrent prescribing may be clinically appropriate and thus 
appreciate commenters' recommended exclusions. However, we wish to 
reiterate that we do not expect the measure rate to be zero; rather, 
the goal of this measure is to help hospital systems identify and 
monitor patients at risk, and ultimately, to reduce the risk of harm to 
patients across the continuum of care.
    Comment: A few commenters expressed concern that the measure may 
show high rates of non-compliance or unfair poor performance for 
hospitals which disproportionately treat patients for whom concurrent 
prescribing is appropriate, such as patients with sickle cell disease, 
or practices that are highly focused on surgical interventions 
requiring concurrent prescriptions (such as orthopedic/neurosurgery 
cases). A commenter suggested that an appropriate risk adjustment 
methodology would incorporate factors such as cognition, functional 
status, and socioeconomic status, as well as standard demographic and 
claims-based health factors. A commenter expressed concern with the 
measure because it does not have clear benchmarks or target levels of 
performance. Another commenter recommended excluding orthopedic/
neurosurgery cases entirely, or grading cases based on surgical 
intervention performed.
    Response: The Safe Use of Opioids--Concurrent Prescribing eCQM is a 
process measure and therefore is not risk adjusted; rather, the target 
population of the measure is defined to include all patients for whom 
the measure is appropriate. The goal of this measure is to help 
hospital systems identify and monitor patients at risk, and ultimately, 
to reduce the risk of harm to patients across the continuum of care by 
providing valuable data about a high-risk prescribing area. Surgical 
patients and other types of patients that commenters have suggested be 
excluded from the measure have a high risk of receiving concurrent 
prescriptions, as well as an increased risk of unintentional and fatal 
overdose, and thus are included in the measure population. Regarding 
commenters' concern about high rates of non-compliance or poor 
performance for hospitals which disproportionately treat patients for 
whom concurrent prescribing is appropriate, we note that as the 
Hospital IQR Program is a pay-for-reporting, not a pay-for-performance, 
quality program, there are no financial penalties based on performance. 
Payment determinations are based on hospitals meeting all of the 
reporting requirements, not performance on the measures. As such, the 
Hospital IQR Program does not implement benchmarks or target levels of 
performance for its measures. Nor do we expect the measure rate to be 
zero; rather, the goal of this measure is to help hospital systems 
identify and monitor patients at risk, and ultimately, to reduce the 
risk of harm to patients across the continuum of care.
    Comment: Some commenters recommended that instead of focusing on 
the number of concurrent prescriptions, CMS conduct further studies to 
evaluate different quality indicators, such as the total opioid dose 
prescribed quantified in morphine milligram equivalents (MME) per day.
    Response: The opioid prescribing guidance developed by professional 
organizations, states, and federal agencies share some common elements 
for evaluating patient care related to opioids, including dosing 
thresholds, cautious titration, and risk mitigation strategies such as 
using risk assessment tools, treatment contracts, and urine

[[Page 42456]]

drug testing.\373\ However, there is considerable variability in the 
specific recommendations for the range of dosing thresholds (for 
example, 90 MME/day to 200 MME/day), audience (for example, primary 
care clinicians versus specialists) and use of evidence (for example, 
systematic review, grading of evidence and recommendations, and role of 
expert opinion).\374\ CMS will take commenters' suggestions into 
consideration to evaluate different quality indicators, as well as 
continue to explore the strength of the evidence to determine whether 
there is a dose range that is valid and not overly burdensome to 
compute for potential future inclusion in an eCQM.
---------------------------------------------------------------------------

    \373\ 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); 
Washington State Agency Medical Directors' Group, Interagency 
Guideline on Prescribing Opioids for Pain (available at: http://agencymeddirectors.wa.gov/Files/2015AMDGOpioidGuideline.pdf); and 
American Society of Interventional Pain Physicians (ASIPP), 
Guidelines for Responsible Opioid Prescribing in Chronic Noncancer 
Pain (available at: https://www.asipp.org/opioidguidelines.htm).
    \374\ 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.
---------------------------------------------------------------------------

    Comment: Many commenters did not support the measure because of 
potential unintended consequences, including that the measure could 
change clinically appropriate management practices by incentivizing 
providers to discontinue opioids and/or benzodiazepine in an unsafe and 
potentially life-threatening manner. In particular, some commenters 
expressed concern that such changes to a patient's established 
medication regimen would be conducted by physicians who do not 
primarily manage the patient's care, or by clinicians not familiar with 
dose reductions, which could endanger patient safety and lead to 
patient harm. A few commenters also expressed concern that the measure 
would incentivize such changes in an abrupt manner given the current 
average length of stay in the acute care setting. A commenter also 
noted that dedicating resources to change medication regimens might 
prove futile if the outpatient receiving team re-instituted the 
previous regimen. A few commenters noted that disincentivizing 
appropriate therapies to those for whom medications have been warranted 
may result in not only undertreatment or mistreatment of pain, but 
other potential adverse outcomes such as seizures, development of 
withdrawal syndrome, depression, and loss of function. A commenter 
expressed concern that patients could turn to other drugs for relief or 
hesitate to seek medical care due to decreased likelihood that their 
pain would be effectively managed as hospitals seek to reduce opioid 
use.
    Response: We acknowledge commenters' concerns about implementation 
of the measure. While we recognize commenters' concerns about potential 
adverse outcomes--such as seizures, development of withdrawal syndrome, 
depression, and loss of function, as well as patients turning to other 
drugs for relief or hesitating to seek medical care due to decreased 
likelihood that their pain would be effectively managed--we note that 
pain management is an appropriate part of routine patient care upon 
which hospitals should focus, and an important concern for patients, 
their families, and their caregivers. Clinicians on our expert panel 
noted that if the prescriber believes the patient should continue 
concurrent opioids and benzodiazepines until further follow-up, that 
decision should arise in the best interest of the patient to avoid 
unintended consequences such as adverse outcomes. We remain confident 
that hospitals will continue to focus on appropriate pain management as 
part of their commitment to quality of care and ongoing quality 
improvement efforts, and it is our belief that providers will avoid 
inappropriate discontinuation of necessary treatment. The focus of the 
measure is to encourage providers to identify patients on medications 
combinations that could lead to adverse drug events at discharge and 
inform decision-making about whether reevaluation of the current 
medications regimen is warranted. As such, we do not believe 
implementation of the measure would change clinically appropriate pain 
management practices by incentivizing providers to discontinue opioids 
and/or benzodiazepine in an unsafe or abrupt and potentially life-
threatening manner. However, we will monitor and evaluate the measure 
following implementation for any potential unintended consequences, 
such as the ones noted by commenters. We will also continue engaging 
with stakeholders through education and outreach opportunities, which 
include webinars and submitted help desk questions through the ONC 
JIRA's eCQM issue tracker for eCQM implementation and maintenance,\375\ 
for any feedback about potential unintended consequences.
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    \375\ Available at: https://oncprojectracking.healthit.gov/support/secure/BrowseProjects.jspa?selectedCategory=all&selectedProjectType=all.
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    We reiterate that the Safe Use of Opioids--Concurrent Prescribing 
eCQM is intended to reduce preventable mortality and adverse outcomes 
related to opioid use by encouraging providers to identify and be aware 
of patients with documentation of concurrent prescriptions and 
discouraging providers from concurrent prescribing whenever clinically 
appropriate. We also recognize that there may be some clinically 
necessary situations for concurrent prescriptions of opioids and 
benzodiazepines, and we agree with the need to properly treat these 
patients.
    Comment: Many commenters expressed concern with the measure and 
noted that there are valid clinical reasons for prescribing concurrent 
prescriptions and that concurrent prescribing is not necessarily a sign 
of poor management. A few commenters noted that there are situations in 
which the prescribing of long-term and short-term opioids are 
clinically appropriate.
    Response: We recognize that there are many types of cases in which 
concurrent prescribing may be clinically appropriate and thus 
appreciate commenters' concerns. However, we reiterate that the measure 
is not expected to have a zero rate, as clinician judgment, clinical 
appropriateness, or both might result in concurrent prescribing of two 
unique opioids or an opioid and benzodiazepine that is medically 
necessary. Clinicians on our expert panel noted that if the prescriber 
believes the patient should continue concurrent opioids and 
benzodiazepines until further follow-up, that decision should arise in 
the best interest of the patient to avoid unintended consequences such 
as adverse outcomes. As stated above, we remain confident that 
hospitals will continue to focus on appropriate pain management as part 
of their commitment to quality of care and ongoing quality improvement 
efforts, and it is our belief that providers will avoid inappropriate 
discontinuation of clinically necessary treatment.
    Regarding commenters' concerns about situations in which the 
prescribing of long-term and short-term opioids are clinically 
appropriate, we note that experts we engaged during testing agreed and 
recommended continuing to include patients for whom concurrent 
prescribing is medically necessary because experts stated that these 
populations (1) have the highest risk of receiving concurrent

[[Page 42457]]

prescriptions; and (2) can experience a lag in adverse events, which is 
why they should be captured by the measure as the measure is intended 
to promote accountability and awareness for concurrent prescribing, 
especially in these high-risk populations. This aligns with the intent 
of the measure, which is to reduce preventable mortality and adverse 
outcomes related to opioid use by encouraging providers to identify and 
be aware of patients with documentation of concurrent prescriptions, as 
well as by discouraging providers from concurrent prescribing whenever 
possible.
    Comment: Some commenters expressed concern with the measure due to 
its reliance on recommendations from the CDC's Guideline for 
Prescribing Opioids for Chronic Pain, noting that that the Guideline 
was developed to provide recommendations for primary care clinicians 
who prescribe opioids for chronic pain outside of active cancer 
treatment, palliative care, and end-of-life care, and that some of the 
recommendations are not strongly supported by the available evidence 
when applied to the inpatient setting. A few commenters cited a 
recently published article in the New England Journal of Medicine 
clarifying the intent of the CDC Guideline and noted that measures that 
lead to patient harms through abrupt tapering or discontinuation of 
opioids for patients already receiving these medications are not 
consistent with the Guideline's recommendations.\376\
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    \376\ Dowell, D., Haegerich, T. & Chou, R. No Shortcuts to Safer 
Opioid Prescribing. N. Engl. J. Med. 380:24 (June 13, 2019).
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    Response: The intent of this measure is to address post-discharge 
medication use. Thus we considered both primary care and inpatient 
opioid prescribing guidelines for the evidence base for this measure. 
The CDC guideline states that, ``Although the focus [of the guideline] 
is on primary care clinicians, because clinicians work within team-
based care, the recommendations refer to and promote integrated pain 
management and collaborative working relationships with other providers 
(for example, behavioral health providers, pharmacists, and pain 
management specialists)'' \377\ The guideline further refers readers to 
other sources for prescribing recommendations within acute care 
settings and in dental practice, including the American College of 
Emergency Physicians' guideline for prescribing opioids in the 
emergency department;\378\ the American Society of Anesthesiologists' 
guideline for acute pain management in the perioperative setting;\379\ 
and the Washington Agency Medical Directors' Group Interagency 
Guideline on Prescribing Opioids for Pain, Part II: Prescribing Opioids 
in the Acute and Subacute Phase.\380\ The additional guidelines 
referenced within the CDC guideline also emphasize that the pain 
management regimen selected by the prescriber should reflect the 
individual safe application of the modality in each practice setting, 
which includes the ability to recognize and treat adverse effects that 
emerge after initiation of therapy, such as use of multiple opioids or 
opioids and benzodiazepines.381 382 383 Clinicians should 
avoid new prescriptions of benzodiazepines and sedative-hypnotics and 
consider tapering or discontinuing benzodiazepines and/or sedative-
hypnotics when appropriate.384 385 386
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    \377\ Dowell, D., Haegerich, T., Chou, R. ``CDC Guideline for 
Prescribing Opioids for Chronic Pain--United States, 2016''. MMWR 
Recomm Rep 2016;65. http://www.cdc.gov/media/dpk/2016/dpk-opioid-prescription-guidelines.html.
    \378\ Cantrill SV, Brown MD, Carlisle RJ, et al.; American 
College of Emergency Physicians Opioid Guideline Writing Panel. 
Clinical policy: Critical issues in the prescribing of opioids for 
adult patients in the emergency department. Ann Emerg Med 
2012;60:499-525.
    \379\ American Society of Anesthesiologists Task Force on Acute 
Pain Management. Practice guidelines for acute pain management in 
the perioperative setting: An updated report by the American Society 
of Anesthesiologists Task Force on Acute Pain Management. 
Anesthesiology 2012;116:248-73.
    \380\ Washington State Agency Medical Directors' Group. AMDG 
2015 interagency guideline on prescribing opioids for pain. Olympia, 
WA: Washington State Agency Medical Directors' Group; 2015. http://www.agencymeddirectors.wa.gov/guidelines.asp.
    \381\ Cantrill SV, Brown MD, Carlisle RJ, et al.; American 
College of Emergency Physicians Opioid Guideline Writing Panel. 
Clinical policy: Critical issues in the prescribing of opioids for 
adult patients in the emergency department. Ann Emerg Med 
2012;60:499-525.
    \382\ American Society of Anesthesiologists Task Force on Acute 
Pain Management. Practice guidelines for acute pain management in 
the perioperative setting: An updated report by the American Society 
of Anesthesiologists Task Force on Acute Pain Management. 
Anesthesiology 2012;116:248-73.
    \383\ Washington State Agency Medical Directors' Group. AMDG 
2015 interagency guideline on prescribing opioids for pain. Olympia, 
WA: Washington State Agency Medical Directors' Group; 2015. http://www.agencymeddirectors.wa.gov/guidelines.asp.
    \384\ Cantrill SV, Brown MD, Carlisle RJ, et al.; American 
College of Emergency Physicians Opioid Guideline Writing Panel. 
Clinical policy: Critical issues in the prescribing of opioids for 
adult patients in the emergency department. Ann Emerg Med 
2012;60:499-525.
    \385\ American Society of Anesthesiologists Task Force on Acute 
Pain Management. Practice guidelines for acute pain management in 
the perioperative setting: An updated report by the American Society 
of Anesthesiologists Task Force on Acute Pain Management. 
Anesthesiology 2012;116:248-73.
    \386\ Washington State Agency Medical Directors' Group. AMDG 
2015 interagency guideline on prescribing opioids for pain. Olympia, 
WA: Washington State Agency Medical Directors' Group; 2015. http://www.agencymeddirectors.wa.gov/guidelines.asp.
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    Comment: A few commenters did not support the measure because of 
their belief that there is a lack of evidence and literature on when 
the risks of concurrent prescribing outweigh the benefits. A commenter 
noted that CMS has not provided adequate evidence to demonstrate that 
the use of the measure would drive improvements in patient care without 
also potentially creating negative unintended consequences.
    Response: As previously noted, opioid prescribing guidelines issued 
by various state agencies and professional societies for various 
settings (including hospital inpatient and emergency department 
settings) agree with the recommendation to avoid concurrently 
prescribing opioids and opioids and benzodiazepines whenever possible 
as the combination of these medications may increase the likelihood of 
opioid-induced respiratory depression.\387\ Emerging data continue to 
show that concurrent prescribing of the medication in scope of the 
measure is a problem; specifically, that opioids and benzodiazepines 
are frequently used in hospitals, and measures assessing prescribing 
patterns and follow up interventions such as educating providers and 
patients about risks and alternatives can impact care,\388\ and no 
nationwide measure of the problem at the hospital and inpatient setting 
currently exists. Data also show that concurrent benzodiazepine and 
opioid use increased by 80 percent between 2001 and 2013 in the United 
States and significantly contributes to the overall population risk of 
opioid overdose.\389\ Initial measure testing demonstrated that there 
was no one point in the care continuum that this scenario was

[[Page 42458]]

isolated to.\390\ Providers and experts engaged during field testing 
considered the potential for unintended consequences and found that the 
benefits of the measure outweighed the risks. These providers and 
experts supported the patient-centric focus of the measure, advocating 
for the measure's potential to promote individualized care and 
collaboration between providers across settings. Also, during the 
endorsement process, the NQF Patient Safety Standing Committee agreed 
that this measure will likely reduce concurrent prescribing of opioid-
opioid and opioid-benzodiazepine medications at discharge in inpatient 
and ED settings.\391\
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    \387\ 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); 
Washington State Agency Medical Directors' Group, Interagency 
Guideline on Prescribing Opioids for Pain (available at: http://agencymeddirectors.wa.gov/Files/2015AMDGOpioidGuideline.pdf).
    \388\ Meisenberg BR, Grover J, Campbell C, Korpon D. Assessment 
of Opioid Prescribing Practices Before and After Implementation of a 
Health System Intervention to Reduce Opioid Overprescribing. JAMA 
Netw Open. Sept. 28, 2018. 1(5):e182908. doi:10.1001/
jamanetworkopen.2018.2908.
    \389\ 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.
    \390\ 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).
    \391\ 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.
---------------------------------------------------------------------------

    Comment: Some commenters did not support adoption of the two opioid 
eCQMs until eCQMs are proven to be at least as valid and reliable as 
their traditional claims-based or administrative counterparts. A few 
commenters urged CMS to balance the usefulness of the information 
reported through EHRs with the challenges of extracting such data and 
the accuracy of the data captured before adopting the two eCQMs.
    Response: We acknowledge commenters' concerns, but note that eCQMs, 
like all other types of quality measures in the Hospital IQR Program, 
including claims-based measures, undergo rigorous testing during the 
measure development process for feasibility, validity, and reliability. 
We note that there are no claims-based or chart-abstracted versions of 
the two opioid-related eCQMs. We further note that reporting eCQMs has 
been an existing requirement for the Hospital IQR Program for several 
years, and is part of our ongoing commitment to promote innovation and 
efficiency through the use of health information technology to improve 
the quality of care for patients while ultimately decreasing reporting 
burden for providers by increasingly automating the collection of 
quality data. Over the past several years, hospitals have continued to 
build and refine their EHR systems and gain experience with reporting 
eCQM data, resulting in more complete data submissions with fewer 
errors. We also began validation of eCQM data submissions, beginning 
with CY 2017 reported data, to incentivize increased accuracy of data 
submissions. We are finalizing more lead time for hospitals to 
implement the new eCQM by waiting until the CY 2021 reporting period, 
with a submission deadline of Monday, February 28, 2022 (84 FR 19475). 
Further, as discussed in section VIII.A.10.(d)(4) of the preamble of 
this final rule, hospitals are not required to report on the Safe Use 
of Opioids--Concurrent Prescribing eCQM until the CY 2022 reporting 
period, with a submission deadline of Tuesday, February 28, 2023. We 
acknowledge that there are some initial implementation activities and 
costs associated with using new eCQMs, but we believe the long-term 
benefits of electronic data capture for quality improvement outweigh 
the burden of using eCQMs. eCQM data enable hospitals to efficiently 
capture and calculate quality data that can be used to address quality 
at the point of care and track improvements over time. We further note 
that based on internal monitoring of eCQM submissions, approximately 97 
percent of eligible hospitals successfully submitted eCQMs for CY 2018.
    Comment: A few commenters recommended that CMS delay implementation 
of the Safe Use of Opioids--Concurrent Prescribing eCQM by a year, 
until the CY 2022 reporting period/FY 2024 payment determination 
instead of the CY 2021 reporting period/FY 2023 payment determination, 
in order to allow time for vendors to properly assess the measure 
specifications, complete development work, and allow hospitals to adopt 
the measures in a safe and effective way.
    Response: We believe our proposal to add the Safe Use of Opioids--
Concurrent Prescribing eCQM to the eCQM measure set beginning with the 
CY 2021 reporting period/FY 2023 payment determination strikes an 
appropriate balance between CMS' goal of incrementally increasing the 
use of EHR data for quality measurement as well as the feedback of some 
stakeholders urging a faster transition to full electronic 
reporting.\392\ We believe adding the Safe Use of Opioids--Concurrent 
Prescribing eCQM beginning with the CY 2021 reporting period/FY 2023 
payment determination allows for a reasonable amount of time for 
vendors to properly assess the new measure specifications, complete 
development work, and allow hospitals to adopt the measure in a safe 
and effective way. We note that testing demonstrated 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. Furthermore, hospitals have 
had several years to report data electronically for both the Hospital 
IQR and Promoting Interoperability Programs, and we have maintained the 
same eCQM reporting and submission requirements for several years in 
order to enable hospitals enough time to update systems and workflows 
to facilitate EHR-based reporting in the least burdensome manner 
possible. We note that several commenters appreciated and supported the 
consistency of the eCQM reporting and submission requirements that we 
are finalizing for the CYs 2020 and 2021 reporting periods, as further 
discussed in sections VIII.A.10(d)(2) and (3) of the preamble of this 
final rule, because they believe it will allow vendors and hospitals 
more time to acclimate to electronic reporting, adopt technology, 
implement and test measures, and prepare for new measures. We will 
continue engaging with stakeholders through education and outreach 
opportunities, including webinars and submitted help desk questions 
such as through the ONC JIRA's eCQM issue tracker for eCQM 
implementation and maintenance,\393\ during the implementation process.
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    \392\ 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.
    \393\ Available at: https://oncprojectracking.healthit.gov/support/secure/BrowseProjects.jspa?selectedCategory=all&selectedProjectType=all.
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    Comment: A commenter requested that value sets be developed and 
published on the Value Set Authority Center for opioid medications, 
which would streamline implementation and ensure that all hospitals are 
using the same values for reporting. The commenter noted that this 
could be done by providing a value set and standard drug codes to 
identify opioids.
    Response: The Safe Use of Opioids--Concurrent Prescribing eCQM uses 
value sets published on the Value Set Authority Center (VSAC) for 
opioid medications. Value sets define clinical concepts to support 
effective and interoperable health information exchange.\394\ We note 
that the value sets

[[Page 42459]]

for eCQMs that have been finalized and adopted through rulemaking 
(along with eCQMs that are developed but not finalized for reporting in 
a CMS program) can be found at the Value Set Authority Center's website 
at: https://vsac.nlm.nih.gov/welcome.\395\ Value sets are referenced in 
eCQMs by their unique numeric identifier, the value set object 
identifier (OID), which can be found within the measure specification. 
The measure's published value sets contain RxNorm codes--standard drug 
codes--to identify the opioid medication name, type, and dose 
combination, and are located on the VSAC.
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    \394\ Value sets are lists of codes and corresponding terms from 
National Library of Medicine (NLM)-hosted standard clinical 
vocabularies (such as SNOMED CT, RxNorm, LOINC and others). Value 
Set Authority Center. Available at: https://vsac.nlm.nih.gov/welcome.
    \395\ While the VSAC does not create value set content, it is a 
central repository for, and provides downloadable access to, all 
official versions of value sets that support CMS' eCQMs. The VSAC 
provides measure developers with tools to search existing value 
sets, create new value sets, and maintain value set content 
consistent with current versions of the terminologies they use. The 
VSAC is provided by the NLM in collaboration with ONC and CMS. More 
information is available at the VSAC website (available at: https://vsac.nlm.nih.gov/welcome) and the eCQI Resource Center (available 
at: https://ecqi.healthit.gov/ecqi-tools-key-resources/content/vsac).
---------------------------------------------------------------------------

    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Safe Use of Opioids--Concurrent 
Prescribing eCQM beginning with the CY 2021 reporting period/FY 2023 
payment determination with a clarification and update to the technical 
specifications so that the measure is clearly applicable only to the 
inpatient setting for implementation under the Hospital IQR Program as 
discussed above. The updated measure specifications can be found at the 
eCQI Resource Center's Pre-rulemaking Eligible Hospital/Critical Access 
Hospital eCQMs website, available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
(2) Hospital Harm--Opioid-Related Adverse Events eCQM
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19477 through 
19480), we proposed to adopt the Hospital Harm--Opioid-Related Adverse 
Events eCQM beginning with the CY 2021 reporting period/FY 2023 payment 
determination.
(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.\396\ 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.\397\
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    \396\ 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.
    \397\ 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).\398\ 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.\399\ 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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    \398\ The Joint Commission. (2012.) Safe Use of Opioids in 
Hospitals. The Joint Commission Sentinel Event Alert, 49:1-5.
    \399\ 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.\400\ Notably, hospitals that use opioids most frequently 
have increased adjusted risk of severe opioid-related adverse 
events.\401\ 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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    \400\ 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.
    \401\ 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 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.402 403 404 405 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.406 407 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.
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    \402\ Surgeon General's Advisory on Naloxone and Opioid 
Overdose. Available at: https://www.surgeongeneral.gov/priorities/opioid-overdose-prevention/naloxone-advisory.html.
    \403\ 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.
    \404\ 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.
    \405\ 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/.
    \406\ 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.
    \407\ 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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    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19477 through 
19480), we proposed to add this

[[Page 42460]]

measure 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.'' \408\ 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.'' \409\ 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.\410\ 
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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    \408\ List of Measures Under Consideration for December 1, 2017. 
Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \409\ 2017-2018 Spreadsheet of Final Recommendations to HHS and 
CMS. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \410\ 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) \411\ output 
for this measure in multiple hospitals that use a variety of EHR 
systems,\412\ 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.\413\ 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.
---------------------------------------------------------------------------

    \411\ 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/.
    \412\ 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.
    \413\ 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 (held on June 17, 2019), as further 
discussed in our responses to public comments received below.
    As we stated in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19478), 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.'' \414\ We also stated 
in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19479) that adoption 
of this measure would introduce the first outcome measure to the eCQM 
measure set under the Hospital IQR Program, which currently is 
comprised entirely of process measures.
---------------------------------------------------------------------------

    \414\ 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),\415\ 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.
---------------------------------------------------------------------------

    \415\ ``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

[[Page 42461]]

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 proposed eCQM reporting and 
submission requirements, which we discuss in section VIII.A.10.d.(1) 
through (4) of the preamble of this final rule, with initial reporting 
that would only require hospitals to submit one self-selected calendar 
quarter of data. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19479), we stated that hospitals may submit more than one quarter of 
data for this measure should they so desire, and that were 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 final 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 final rule where we 
discuss 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 acknowledged 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, out of an overabundance 
of caution, in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19480), 
we solicited 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.
    Comment: Many commenters supported the proposal to adopt the 
Hospital Harm--Opioid-Related Adverse Events eCQM. They noted the 
importance of monitoring inpatient medication administration practices 
and the ready availability of the necessary data from existing EHRs. 
Commenters appreciated that CMS has developed metrics aimed at reducing 
opioid-related adverse events and believed that the measure would lead 
to safer patient care by incentivizing tracking and improvements to the 
monitoring of patients who receive opioids during hospitalization. Some 
commenters noted that the measure would be a welcome addition to the 
Hospital IQR Program eCQM measure set.
    Response: We thank commenters for their support of this measure. We 
agree with commenters that it is important to reduce adverse drug 
events (ADEs). We note that ADEs present the single greatest source of 
harm to patients in hospitals.\416\ Traditional efforts to detect ADEs 
have focused on voluntary reporting and tracking of errors. However, 
studies show that only 10 to 20 percent of errors are ever 
reported.\417\ We believe a more effective way is needed to assist 
hospitals in identifying the events that are causing harm to patients. 
While this measure addresses a high priority measurement area, as 
discussed further in this section of the final rule, we are not 
finalizing the

[[Page 42462]]

adoption of the Hospital Harm--Opioid-Related Adverse Events eCQM in 
this final rule so that we can further assess stakeholder 
recommendations about the measure and determine what changes, if any, 
should be incorporated into this important measure for the future. 
Additional detail is discussed below in this rule.
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    \416\ Rozich, J., Haraden, C., & Resar, R. (2003). Adverse drug 
event trigger tool: A practical methodology for measuring medication 
related harm. Quality and Safety in Health Care, 12(3), 194-200.
    \417\ Institute for Healthcare Improvement (IHI). Measures, 
Adverse Drug Events Per 1,000 Doses. Available at: http://www.ihi.org/resources/Pages/Measures/ADEsper1000Doses.aspx.
---------------------------------------------------------------------------

    Comment: Many commenters expressed that they would prefer that CMS 
secure NQF endorsement before adoption of this measure.
    Response: We acknowledge the importance of NQF endorsement and 
reiterate our strong preference to use endorsed measures when 
available. Following publication of the proposed rule, the NQF 
Scientific Methods Panel reviewed and passed the measure for scientific 
acceptability.\418\ The NQF Patient Safety Standing Committee then 
reviewed the measure for endorsement at its June 2019 meeting. The NQF 
Patient Safety Standing Committee expressed concerns about using 
naloxone as a proxy for harm in the numerator because of the potential 
circumstances where it may trigger numerator cases not as intended, 
such as for diagnostic purposes, opioid side effects, or to reverse 
overdoses caused by the administration of opioids that were not 
hospital-prescribed.419 420 The NQF Patient Safety Standing 
Committee also expressed concern with the denominator including all 
patients admitted to the hospital rather than being limited to patients 
administered opioids by the hospital.\421\ The NQF Patient Safety 
Standing Committee voted not to move forward with endorsement of this 
measure.\422\ We note that section 1886(b)(3)(B)(viii)(IX)(bb) of the 
Act provides an exception: 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 attempted to find available measures 
for this clinical topic that have been endorsed or adopted by a 
consensus organization and found no other feasible and practical 
measures on the topic for the inpatient setting. While endorsement is 
not always required, we give serious consideration to the NQF's 
assessments. We also take into consideration stakeholder input. After 
considering stakeholder concerns--primarily, concerns about the 
requirement of evidence of prior opioid administration only during the 
initial 24 hours after arrival and the broad nature of the denominator 
that may result in the calculation of very low rates of adverse events, 
as discussed further in this section--as well as the concerns expressed 
by NQF, we plan to reevaluate the measure in response to this feedback 
and are thus, not finalizing the measure in this final rule. We intend 
to take NQF's concerns into account when considering what changes, if 
any, should be incorporated into this important measure for future use.
---------------------------------------------------------------------------

    \418\ NQF. Transcript of March 19, 2019 NQF Scientific Methods 
Panel Transcript. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=89690.
    \419\ NQF. Transcript of June 17, 2019 NQF Patient Safety 
Standing Committee Meeting. http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=90487.
    \420\ National Quality Forum (NQF) Patient Safety Standing 
Committee. Meeting Summary--Measure Evaluation In-person Meeting--
Spring 2019 Cycle. Available at: http://www.qualityforum.org/Work 
Area/linkit.aspx?LinkIdentifier=id&ItemID=90662.
    \421\ NQF. Transcript of June 17, 2019 NQF Patient Safety 
Standing Committee Meeting. http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=90487.
    \422\ National Quality Forum (NQF) Patient Safety Standing 
Committee. Meeting Summary--Measure Evaluation In-person Meeting--
Spring 2019 Cycle. Available at: http://www.qualityforum.org/Work 
Area/linkit.aspx?LinkIdentifier=id&ItemID=90662.
---------------------------------------------------------------------------

    Comment: Many commenters expressed concern with the measure because 
of the potential unintended consequence of disincentivizing clinically 
appropriate treatment. Specifically, commenters expressed concern that 
implementation of the measure could result in deterring or delaying 
clinically appropriate administration of naloxone or underprescribing 
of opioids for pain control when clinically necessary. A commenter 
expressed particular caution about the measure in the absence of 
balancing measures related to the appropriate use of naloxone and 
ensuring that patients receive adequate pain control during their 
hospitalization. Some commenters expressed concern that the measure 
could cause hospitals to turn to more invasive alternatives to 
naloxone, such as BiPAP \423\ or intubation.
---------------------------------------------------------------------------

    \423\ A bilevel positive airway pressure (BiPAP or BPap) is a 
type of ventilator that helps with breathing.
---------------------------------------------------------------------------

    Response: We acknowledge commenters' concerns about potential 
unintended consequences, but reiterate that naloxone is a life-saving 
emergent therapy with clear and unambiguous applications in the setting 
of opioid overdose. 424 425 426 427 We also note that it 
would be unethical to withhold life-saving medication. Moreover, 
opioid-related adverse events are avoidable by following clinical 
practice guidelines such as proper dosing and monitoring of patients on 
opioids for signs of overdose such as pinpoint pupils, unconsciousness, 
and respiratory depression.\428\ The goal of this measure is to 
incentivize hospitals to avoid over-sedation and to closely monitor 
patients on opioids.
---------------------------------------------------------------------------

    \424\ Surgeon General's Advisory on Naloxone and Opioid 
Overdose. Available at: https://www.surgeongeneral.gov/priorities/opioid-overdose-prevention/naloxone-advisory.html.
    \425\ 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.
    \426\ 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.
    \427\ 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/.
    \428\ Centers for Disease Control and Prevention (CDC) 
Preventing an Opioid Overdose. Available at: https://www.cdc.gov/drugoverdose/pdf/patients/Preventing-an-Opioid-Overdose-Tip-Card-a.pdf.
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    Regarding commenters' concerns about disincentivizing the 
administration of opioids, we remain confident that hospitals will 
continue to focus on appropriate pain management as part of their 
commitment to quality of care and ongoing quality improvement efforts, 
and use the least invasive means necessary to treat their patients. We 
appreciate the commenter's recommendation that this measure could 
benefit from being paired with a balancing measure capturing pain 
management and will take this into consideration as we consider new 
measures for future inclusion in the program.
    Comment: Some commenters expressed concern with the measure because 
naloxone may be used to treat conditions other than opioid-related 
overdose such as side effects from narcotics like itching or nausea/
vomiting, or change in mental status where opioids are not the cause of 
the change in status. Some commenters also expressed concern with the 
measure as currently specified because naloxone may be administered in 
situations in which the hospital did not administer opioids, such as 
patient self-administration of prescribed or illicit drugs during the 
encounter.

[[Page 42463]]

    Response: We thank commenters for their suggestions, and will 
assess these recommendations when considering what changes, if any, 
should be incorporated into this important measure for future use. 
While we agree with some commenters that naloxone administration does 
not in and of itself indicate that an overdose occurred in every 
instance, we believe that the administration of naloxone is most 
commonly used for reversing opioid overdoses.\429\ As such, we continue 
to believe that using naloxone as an indicator of overdose is 
appropriate. While we are not finalizing the measure as currently 
specified, we will further assess the various stakeholder 
recommendations about the measure and determine what changes, if any, 
should be incorporated into this important measure for the future.
---------------------------------------------------------------------------

    \429\ Louy C. ``IV Naloxone Infusion: A Forgotten Gem,'' 
presented at PAINWeek 2018, September 4-8, in Las Vegas, Nevada.
---------------------------------------------------------------------------

    Comment: A few commenters recommended modifying the measure 
specifications to only include opioid administration prior to naloxone 
use by extending the requirement of prior opioid administration to the 
entire hospital stay, rather than just the initial 24 hours after 
admission.
    Response: We thank commenters for their recommendation, and will 
assess this concern in concert with other recommendations when 
considering what changes, if any, should be incorporated into this 
important measure for future use.
    Comment: Some commenters noted that the measure as proposed 
includes a very broad denominator that may result in the calculation of 
very low rates of adverse events.
    Response: We thank commenters for their observation and will assess 
this concern in concert with other recommendations when considering 
what changes, if any, should be incorporated into this important 
measure for future use.
    Comment: Many commenters requested exclusions or risk adjustment 
for special cases (for example, chronic opioid users, patients with 
opioid sensitivity, patients with sickle cell anemia, patients 
receiving palliative care, clinical indications not related to opioid 
overdose, code blues, and manual reviews that confirm appropriate use). 
Some commenters also recommended exclusions for smaller doses of 
naloxone for opioid related side effects such as itching or nausea and 
vomiting.
    Response: We thank commenters for their suggestions for potential 
refinements specific to risk adjustment and/or exclusions. As stated 
above, we are not finalizing the measure at this time and will consider 
what changes, if any, should be incorporated into this important 
measure for future use. We note, however, that while we understand that 
some hospitals may serve patients with different risk profiles, we 
believe avoidance of hospital-administered opioid overdoses should 
apply to all patients.
    We also note that this measure is constructed to identify naloxone 
administration regardless of brand name, dosage, or route of 
administration. The intention of this measure is to look at hospital-
administered opioid overdoses by tracking naloxone administration based 
on Food and Drug Administration (FDA)-approved indication of opioid 
depression (including respiratory depression).\430\ CMS continues to 
monitor FDA guidance regarding indications for the use of naloxone 
431 432 as well as standardization of alternate-use 
guidelines that support eCQM feasibility.\433\
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    \430\ Gottlieb, S., Unprecedented new efforts to support 
development of over-the-counter naloxone to help reduce opioid 
overdose deaths (2019) Available at: https://www.fda.gov/news-events/press-announcements/statement-fda-commissioner-scott-gottlieb-md-unprecedented-new-efforts-support-development-over
    \431\ December 2018 HHS Press Release (Adm. Brett P. Giroir, 
MD). Available at: https://www.hhs.gov/about/news/2018/12/19/hhs-recommends-prescribing-or-co-prescribing-naloxone-to-patients-at-high-risk-for-an-opioid-overdose.html.
    \432\ AMA Opioid Task Force, AMA Opioid Task Force Issues 
Updated Naloxone Guidance. Available at: https://www.aafp.org/news/health-of-the-public/20170828naloxoneresource.html.
    \433\ Doheney, K., More Potential Uses for Low-Dose IV Naloxone 
(2018) Available at: https://www.practicalpainmanagement.com/meeting-summary/more-potential-uses-low-dose-iv-naloxone
---------------------------------------------------------------------------

    Comment: A few commenters recommended clarification that the 
appropriate measure rate is not zero.
    Response: The intent of this measure is not to reduce clinically 
appropriate use of naloxone, nor to bring the measure rate to zero, but 
to identify if hospitals have particularly high rates of naloxone use 
as an indicator of high rates of over-administration of opioids in the 
inpatient setting, and thereby incentivize improved clinical practices 
when administering opioids. Proper dosing of opioids and monitoring of 
patients on opioids can reduce the need for naloxone use in patient 
care. We recognize that naloxone is indicated for the complete or 
partial reversal of opioid overdose and is also indicated for diagnosis 
of suspected or known acute opioid over-dosage.\434\ We note that of 
the adverse drug events reported to The Joint Commission's Sentinel 
Event database, 47 percent were due to a wrong medication dose, 29 
percent to improper monitoring, and 11 percent to other causes (for 
example, medication interactions and drug reactions).\435\
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    \434\ Barrie, J. (2006) Diagnosis of drug overdose by rapid 
reversal with naloxone, Emergency Medicine Journal, 23(11): 874-875. 
Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2464401/.
    \435\ The Joint Commission. (2012). Safe Use of Opioids in 
Hospitals. The Joint Commission Sentinel Event Alert, 49:1-5.
---------------------------------------------------------------------------

    Comment: Some commenters did not support the measure concept and 
expressed their belief that naloxone administration is not the most 
appropriate outcome to measure in the context of excessive dosing of 
opioids in the hospital setting. A commenter instead recommended 
measuring the reverse of the proposed measure--the proportion of 
patients after 24 hours who die from opioid administration because 
naloxone was not administered. Other commenters stated that the 
administration of naloxone does not necessarily imply unsafe opioid 
prescribing practices. A commenter noted that respiratory depression 
may be caused by non-opioid factors. Another commenter noted that this 
measure could penalize hospitals that order rescue naloxone but do not 
ultimately administer it.
    Response: The Hospital Harm--Opioid-Related Adverse Events eCQM 
focuses on monitoring hospital-administered opioid overdoses through 
the administration of naloxone. While we agree that naloxone 
administration does not in and of itself indicate that an overdose 
occurred in every instance, we continue to believe that the 
administration of naloxone is most commonly used for reversing opioid 
overdoses, and developed a measure based on this concept accordingly. 
We note that the alternative measure recommended by a commenter to 
focus on assessing mortality resulting from failure to reverse opioid 
overdoses by administration of naloxone--the proportion of patients 
after 24 hours who die from opioid administration because naloxone was 
not administered--would be addressing a different patient safety issue 
than that intended by this measure. Regarding commenters' concerns that 
respiratory depression may be caused by other non-opioid factors and 
that this measure could penalize hospitals that order rescue naloxone 
but ultimately do not administer it, we note that as specified, the 
administration rather than the ordering of naloxone is required to

[[Page 42464]]

trigger a numerator case.\436\ Respiratory depression alone does not 
trigger a numerator case, nor do cases in which naloxone was only 
ordered but not administered.
---------------------------------------------------------------------------

    \436\ As noted by the Guidance provided in the measure 
specifications, the numerator includes only encounters in which a 
patient was administered rather than ordered naloxone during their 
hospitalization. The measure specifications are on the CMS Measure 
Methodology website, available at: https://www.cms.gov/medicare/
quality-initiatives-patient-assessment-instruments/
hospitalqualityinits/measure-methodology.html.
---------------------------------------------------------------------------

    Comment: Several commenters expressed concern that the measure does 
not evaluate the process used by hospital-based providers in reaching 
the decision to initially prescribe the opioids, and therefore may not 
improve the quality of care or drive the types of changes that would 
impact the opioid crisis.
    Response: We acknowledge commenters' concerns, but note that the 
Hospital Harm--Opioid-Related Adverse Events eCQM is a not a process 
measure, and therefore would not evaluate the process used by hospital-
based providers in reaching the decision to initially prescribe opioids 
as commenters suggest. Rather, the Hospital Harm--Opioid-Related 
Adverse Events eCQM is an outcome measure that seeks to promote greater 
awareness of in-hospital administration of opioids and incentivize 
providers to identify and improve appropriate opioid prescribing and 
administration workflows and monitoring of high-risk patients. The 
measure addresses this intent by measuring the proportion of patients 
who had an opioid-related adverse event during a hospital stay by 
assessing the administration of naloxone. We believe the Hospital 
Harm--Opioid-Related Adverse Events eCQM is a valuable patient safety 
measure that, by shedding light on opioid use in hospitals, driving 
improvements in quality of care, and incentivizing the monitoring of 
patients who receive opioids during hospitalization, can contribute to 
the multipronged effort to addressing the opioid crisis. We also note 
that these strategies address the Meaningful Measures quality priority 
of ``Making Care Safer by Reducing Harm Caused in the Delivery of 
Care'' through the Meaningful Measures Area of ``Preventable Healthcare 
Harm.''
    Comment: A commenter noted that the eCQM may be nearly topped-out. 
A few commenters expressed their beliefs that since testing results 
showed little variation in hospital performance, the measure would not 
provide useful information to providers or consumers. A commenter 
stated its belief that since the use of naloxone in inpatient care 
remains extremely rare, there is little reliable evidence to support 
using the administration of naloxone as a quality indicator. Another 
commenter expressed concern with this measure because it does not have 
clear benchmarks or target levels of performance.
    Response: In the FY 2015 IPPS/LTCH PPS final rule (79 FR 50203), we 
finalized in the Hospital IQR Program that a measure is ``topped-out'' 
when measure performance among hospitals is so high and unvarying that 
meaningful distinctions and improvements in performance can no longer 
be made. While testing results showed low average rates for opioid-
related adverse events between the sites tested (as expected for this 
important patient safety area), there was statistically significant 
variation in performance across the hospitals tested. We further noted 
in the FY 2015 IPPS/LTCH PPS final rule (79 FR 50203) that quality 
measures, once ``topped-out,'' represent care standards that have been 
widely adopted by hospitals. As we noted in the proposed rule, 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. 
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.\437\ The number of harms potentially prevented and lives 
potentially saved is significant, as thousands of Americans experience 
severe adverse events related to hospital administered opioids each 
year, representing significant opportunities for improvement.\438\ We 
intend for this measure to incentivize hospitals to avoid over-
sedation, to reduce concomitant opioid and benzodiazepine 
administration, and to closely monitor patients on opioids by measuring 
the proportion of encounters of patients who had an opioid-related 
adverse event during an an inpatient stay at an acute care hospital by 
assessing the administration of naloxone.\439\
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    \437\ 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.
    \438\ Herzig SJ, Rothberg MB, Cheung M, Ngo LH, Marcantonio ER. 
Opioid utilization and opioid-related adverse events in nonsurgical 
patients in US hospitals. J Hosp Med. 2014;9(2):73-81. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3976956/.
    \439\ The measure specifications are on the CMS Measure 
Methodology website, available at: https://www.cms.gov/medicare/
quality-initiatives-patient-assessment-instruments/
hospitalqualityinits/measure-methodology.html.
---------------------------------------------------------------------------

    Regarding the commenter's concern that there is little reliable 
evidence to support using the administration of naloxone as a quality 
indicator, we note that naloxone administration has 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.440 441
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    \440\ 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.
    \441\ 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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    Regarding the commenter's concern about the measure's lack of 
benchmarks or target levels of performance, we note that the Hospital 
IQR Program is a pay for reporting, not a pay for performance, quality 
program. This means that its payment determinations are based on 
hospitals meeting all of the reporting requirements, not performance on 
the measures. As such, the Hospital IQR Program does not implement 
benchmarks or target levels of performance for its measures. Moreover, 
we note that the intent of this measure is not to reduce clinically 
appropriate use of naloxone, nor to bring the measure rate to zero, but 
to identify if hospitals have particularly high rates of naloxone use 
as an indicator of high rates of over-administration of opioids in the 
inpatient setting, and thereby incentivize improved clinical practices 
when administering opioids.
    Comment: Some commenters did not support adoption of the two 
opioids eCQMs until eCQMs are proven to be at least as valid and 
reliable as their traditional claims-based or administrative 
counterparts. A few commenters urged CMS to balance the usefulness of 
the information reported through EHRs with the challenges of extracting 
such data and the accuracy of the data captured before adopting the two 
eCQMs.
    Response: We acknowledge commenters' concerns, but note that eCQMs, 
like all other types of quality measures in the Hospital IQR Program, 
including claims-based measures, undergo rigorous testing during the 
measure development process for feasibility, validity, and reliability. 
We

[[Page 42465]]

note that there are no claims-based or chart-abstracted versions of the 
two opioid-related eCQMs. We further note that reporting eCQMs has been 
an existing requirement for the Hospital IQR Program for several years, 
and is part of our ongoing commitment to promote innovation and 
efficiency through the use of health information technology and improve 
the quality of care for patients while ultimately decreasing reporting 
burden for providers by increasingly automating the collection of 
quality data. Over the past several years, hospitals have continued to 
build and refine their EHR systems and gain experience with reporting 
eCQM data, resulting in more complete data submissions with fewer 
errors. We also began validation of eCQM data submissions, beginning 
with CY 2017 reported data, to incentivize increased accuracy of data 
submissions. As discussed section VIII.A.5.a.(1) of the preamble of 
this final rule, we are finalizing more lead time for hospitals to 
implement the new Safe Use of Opioids--Concurrent Prescribing eCQM by 
waiting until the CY 2021 reporting period, with a submission deadline 
of Monday, February 28, 2022 (84 FR 19475). Further, as discussed in 
section VIII.A.10.(d)(4) of the preamble of this final rule, hospitals 
are not required to report on the Safe Use of Opioids--Concurrent 
Prescribing eCQM until the CY 2022 reporting period, with a submission 
deadline of Tuesday, February 28, 2023. We acknowledge that there are 
some initial implementation activities and costs associated with using 
new eCQMs, but we believe the long-term benefits of electronic data 
capture for quality improvement outweigh the burden of using eCQMs. 
eCQM data enable hospitals to efficiently capture and calculate quality 
data that can be used to address quality at the point of care and track 
improvements over time. We further note that based on internal 
monitoring of eCQM submissions, approximately 97 percent of eligible 
hospitals successfully submitted eCQMs for CY 2018.
    Comment: A number of commenters provided additional measure 
suggestions or potential refinements to the measure. These suggestions 
include considering multiple doses of naloxone or multiple opioid-
related adverse events for the same patient; specific thresholds for 
the administration of naloxone; restricting the measure to documented 
respiratory failure tied to opioid administration and/or then transfer 
to a higher level of care with IV use; and recommending that surgical 
and emergency department patients be considered for future inclusion in 
the measure.
    Response: We thank commenters for their suggestions, and will take 
them into consideration as we consider potential refinements to the 
measure and new measures for future inclusion in the program. We note 
that emergency department patients who are ultimately admitted are 
captured in the measure, as currently specified.\442\
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    \442\ For more information about the denominator, we refer 
readers to the measure specifications on the CMS Measure Methodology 
website, available at: https://www.cms.gov/medicare/quality-
initiatives-patient-assessment-instruments/hospitalqualityinits/
measure-methodology.html.
---------------------------------------------------------------------------

    Comment: A commenter suggested that CMS instead consider 
alternative measures to address the opioid epidemic, such as the rate 
of prescribing opioids over 90 morphine milligram equivalent (MME) per 
day at discharge for patients who did not have opioid prescriptions 
present at admissions. The commenter recommended that CMS look beyond 
opioid prescribing measures to measures that assess opioid use disorder 
treatment, such as percentage of patients initiated on treatment at 
discharge.
    Response: As further discussed in section VIII.A.5.a.(1), where we 
discuss our adoption of the Safe Use of Opioids--Concurrent Prescribing 
eCQM, the opioid prescribing recommendations developed by professional 
organizations, states, and federal agencies share some common elements 
for evaluating patient care related to opioids, including dosing 
thresholds, cautious titration, and risk mitigation strategies such as 
using risk assessment tools, treatment contracts, and urine drug 
testing.\443\ However, there is considerable variability in the 
specific recommendations for the range of dosing thresholds (for 
example, 90 MME/day to 200 MME/day), audience (for example, primary 
care clinicians versus specialists) and use of evidence (for example, 
systematic review, grading of evidence and recommendations, and role of 
expert opinion).\444\ We will continue to consider additional opioid-
related measures and evaluate evidence to determine dose ranges that 
are valid and not overly burdensome to compute for potential future 
inclusion in an eCQM. We will also take into consideration the 
commenter's suggestion about measures that evaluate opioid use disorder 
treatment as we consider new measures for future inclusion in the 
program.
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    \443\ 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); 
Washington State Agency Medical Directors' Group, Interagency 
Guideline on Prescribing Opioids for Pain (available at: http://agencymeddirectors.wa.gov/Files/2015AMDGOpioidGuideline.pdf); and 
American Society of Interventional Pain Physicians (ASIPP), 
Guidelines for Responsible Opioid Prescribing in Chronic Noncancer 
Pain (available at: https://www.asipp.org/opioidguidelines.htm).
    \444\ 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.
---------------------------------------------------------------------------

    After consideration of the public comments we received, we are not 
finalizing our proposal to adopt the Hospital Harm--Opioid-Related 
Adverse Events eCQM. We thank the commenters for their comments and 
suggestions, which we will take into consideration when assessing what 
changes, if any, should be incorporated into this important measure for 
the future.
b. Adoption of Hybrid Hospital-Wide Readmission Measure With Claims and 
Electronic Health Record Data (NQF #2879)
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19480 through 
19485), we proposed 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. Each voluntary reporting period would be for four quarters 
(or one year), 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 proposed 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 was made in 
conjunction with our proposal to remove the Claims-Based Hospital-Wide 
All-Cause Unplanned

[[Page 42466]]

Readmission Measure (NQF #1789) (HWR claims-only measure) (discussed in 
section VIII.A.6. of the preamble of this final rule, in this section). 
These proposals are discussed in detail in this section of this final 
rule.
(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.\445\
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    \445\ 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.'' \446\ 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).\447\ 
Thereafter, the Hybrid HWR measure was endorsed by the NQF on December 
9, 2016.\448\ The Hybrid HWR measure was first discussed in the FY 2016 
IPPS/LTCH PPS final rule (80 FR 49698 through 49704).
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    \446\ List of Measures Under Consideration for December 1, 2014. 
Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \447\ 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.
    \448\ 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. We stated in the FY 2020 IPPS/LTCH PPS 
proposed rule (84 FR 19480) that 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 150 
hospitals submitted data for the Hybrid HWR measure.\449\ We stated in 
the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19480 through 19481) 
that we were merging the EHR data with the claims data and will provide 
hospitals with confidential hospital-specific reports which will 
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.
---------------------------------------------------------------------------

    \449\ In this final rule, we are updating this figure from 80 to 
150, to reflect an update to the total number of hospitals that 
participated.
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    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 final rule, where we discuss our proposal 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

[[Page 42467]]

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 in this section of this final 
rule.
[GRAPHIC] [TIFF OMITTED] TR16AU19.182

    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.\450\ 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.\451\
---------------------------------------------------------------------------

    \450\ 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=12287
63452133.
    \451\ 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.\452\ 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 
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).
---------------------------------------------------------------------------

    \452\ 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.

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[[Page 42468]]

    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.\453\ 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.\454\ 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.
---------------------------------------------------------------------------

    \453\ 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.
    \454\ 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.
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(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.\455\
---------------------------------------------------------------------------

    \455\ 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.
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    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 previously stated, 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 \456\ is the 
same algorithm used in the HWR claims-only measure (77 FR 53521).\457\ 
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.\458\ 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.\459\
---------------------------------------------------------------------------

    \456\ 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.
    \457\ Centers for Medicare & Medicaid Services. Measure 
Methodology. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
    \458\ Ibid.
    \459\ 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.
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(6) Risk Adjustment
    The proposed Hybrid HWR measure adjusts both for case-mix 
differences (how severely ill patients are when they are admitted) as 
well as differences in hospitals' service-mix (the types of conditions 
that cause patients'

[[Page 42469]]

admissions). The case-mix variables include patients' ages and 
comorbidities as well as laboratory test results and vital signs. As 
previously listed in detail, 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; 
\460\ (2) the Clinical Classification Software (CCS) categories \461\ 
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).\462\ 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.\463\
---------------------------------------------------------------------------

    \460\ Electronic Clinical Quality Improvement (eCQI) Resource 
Center. Hybrid Hospital-Wide Readmission. Available at: https://ecqi.healthit.gov/ecqm/measures/cms529v0.
    \461\ 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.
    \462\ 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.
    \463\ Available at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier4&cid=1219069855841.
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    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.\464\ 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.\465\ 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).\466\ We note that the risk adjustment methods are the same as 
those used for the 2018 Voluntary Reporting Period.
---------------------------------------------------------------------------

    \464\ 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.
    \465\ 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.
    \466\ Ibid.
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(7) Data Submission
    As with the 2018 Voluntary Reporting Period (82 FR 38350 through 
38355), we proposed 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 
reporting periods 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,\467\ 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.
---------------------------------------------------------------------------

    \467\ 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.
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    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 42470]]

billing,\468\ 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.
---------------------------------------------------------------------------

    \468\ 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 previously 
described 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 previously described, 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 final 
rule for a discussion 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 proposed 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 \469\ 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.
---------------------------------------------------------------------------

    \469\ 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 previously 
discussed, 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 would run from July 1, 2021 through 
June 30, 2022, and July 1, 2022 through June 30, 2023, would not be 
publicly reported, as previously mentioned. However, we proposed 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

[[Page 42471]]

2026 payment determination. This would be the first 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 was 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 in this final rule. We also refer readers to 
section VIII.D.6.c. of preamble of this final rule, which includes a 
discussion of our request for feedback on whether to consider adopting 
the Hybrid HWR measure for the Promoting Interoperability Program.
    Comment: Several commenters supported our proposal to adopt the 
Hybrid HWR measure. Many commenters noted that the introduction of the 
Hybrid HWR measure will prove to be more precise in amassing clinical 
information relative to the claims-based measure. Many commenters 
stated that they agree with the introduction of clinical data elements 
in risk adjustment, noting that it is a step forward in improving both 
reliability and validity of hospitals' all-cause readmission rates. 
Many commenters supported the measure being included in the Hospital 
IQR Program. A number of commenters expressed appreciation for the 
voluntary reporting periods.
    Response: We agree and thank the commenters for their support.
    Comment: Many commenters noted conditional support for the Hybrid 
HWR measure. These commenters stated that integrating EHR data with 
claims data is a positive move towards improving risk adjustment and 
being able to capture meaningful data; however, they believed that 
reporting of the measure should remain voluntary at this time to allow 
any potential data collection issues to be timely addressed.
    Response: We thank the commenters for their support and appreciate 
their perspectives. We are finalizing our proposal to allow for two 
more years of voluntary reporting, in addition to the 2018 Voluntary 
Reporting Period, before requiring mandatory reporting of the Hybrid 
HWR measure, beginning with the reporting period, which runs from July 
1, 2023 through June 30, 2024, impacting the FY 2026 payment 
determination. We believe that providing this additional opportunity 
for hospitals to voluntarily report on the Hybrid HWR measure gives 
hospitals sufficient time to address potential data collection issues 
before mandatory reporting is required.
    Comment: A number of commenters suggested that we delay the 
implementation of this measure. Many commenters urged us to allow for 
additional time before the measure becomes mandatory for the Hospital 
IQR Program, citing concerns about implementation challenges. A 
commenter stated that low participation in the 2018 Voluntary Reporting 
Period might result in a failure to fully detect implementation 
challenges. A commenter stated that based on varying levels of 
sophistication related to connectivity in hospitals, a hybrid measure 
may be premature at this time.
    Response: We acknowledge the commenters' concerns. As stated above, 
150 hospitals successfully participated in the voluntary reporting of 
2018 data for the Hybrid HWR measure, either individually or through a 
vendor, and we respectfully disagree with the commenter that 
participation was low. We successfully merged 76 percent of the EHR 
submissions with matching claims data and calculated results on 149 
hospitals whose discharges met all inclusion and exclusion criteria. 
Based on the review of the 2018 Voluntary Reporting Period, we are not 
concerned that implementation issues went undetected, especially 
because hospitals will be given an additional two years of voluntary 
reporting to implement this measure and identify and resolve any 
implementation challenges.
    We acknowledge that hospitals have varying levels of resources to 
support implementation activities, including varying levels of 
experience among hospital staff related to EHR implementation and use, 
but we reiterate that this measure is comprised of claims data, which 
requires no additional submissions by hospitals, and core clinical data 
elements, which we believe are readily accessible in EHRs. In the 
development of the Hybrid HWR measure, we conducted extensive testing 
to ensure that all EHR data elements used in the measure specifications 
were readily available for the patient population and feasibly 
extracted from most commercial EHR systems. The information on 
patients' vital signs and laboratory test values should be available in 
all certified EHR systems. Additionally, the 2018 Voluntary Reporting 
Period provided useful information about the measure's electronic 
specifications that may lead to non-substantive refinements to clarify 
value sets in addition to routine annual updates of the measure 
specifications to ease burden of data extraction on providers.
    We proposed two additional years of confidential reporting without 
impact on hospitals' Hospital IQR Program payment determination to 
ensure that all hospitals have an opportunity to gain even more 
experience with the measure specifications and compare their results to 
those obtained from the claims-only HWR measure prior to mandatory 
reporting and public reporting. Given that we are finalizing our 
proposal to adopt the Hybrid HWR measure in a stepwise fashion, first 
accepting voluntary data submissions during two reporting periods, 
followed by mandatory reporting, which begins with the reporting period 
that runs from July 1, 2023 through June 30, 2024, impacting the FY 
2026 payment determination, we believe that there will be sufficient 
time to allow hospitals and their health IT vendors to familiarize 
themselves with the measure reporting process. We strongly encourage 
hospitals to participate in the voluntary reporting periods.
    Comment: Several commenters noted that a slower implementation 
schedule would allow the measure to be implemented with: (a) The Fast 
Healthcare Interoperability Resources (FHIR) standard,\470\ (b) 
additional feedback from voluntary reporters regarding implementation 
challenges, (c) better awareness of the impact on performance the 
hybrid measure might have, and (d) a longer overlap between the claims-
only and Hybrid versions of the measure to account for any unplanned 
implementation delays and to ensure continuity of hospital-wide 
readmissions data.
---------------------------------------------------------------------------

    \470\ FHIR, developed by Health Level Seven International (HL7), 
is designed to enable information exchange to support the provision 
of healthcare in a wide variety of settings. The specification 
builds on and adapts modern, widely used RESTful practices to enable 
the provision of integrated healthcare across a wide range of teams 
and organizations. Additional information is available at: https://www.hl7.org/fhir/overview.html.
---------------------------------------------------------------------------

    Response: We appreciate the various comments related to the 
implementation of this measure. We are currently investigating and 
testing the potential uses of the FHIR standard for EHR-based quality 
measure data reporting, however, it is not required at this time.

[[Page 42472]]

We will inform stakeholders of any updates related to the FHIR standard 
for quality measure reporting as they become available. In the 
development of the Hybrid HWR measure, we conducted extensive testing 
to ensure that all EHR data elements used in the measure specifications 
were readily available for the patient population and feasibly 
extracted from most commercial EHR systems. The information on 
patients' vital signs and laboratory test values should be available in 
all certified EHR systems. Additionally, the 2018 Voluntary Reporting 
Period provided useful information about the measure's electronic 
specifications that may lead to non-substantive refinements to clarify 
value sets in addition to routine annual updates of the measure 
specifications to ease burden of data extraction on providers. We have 
already begun to solicit feedback from hospitals and vendors who 
participated to better understand stakeholders' experiences, challenges 
they faced, and recommendations for improvement. We will consider 
applying feedback received from these stakeholders to future 
confidential and mandatory reporting of this measure.
    Hospitals that submit Hybrid HWR measure data will receive 
confidential hospital-specific reports that detail results in each of 
the confidential reporting years. This will provide hospitals with 
opportunities to preview their results on the Hybrid HWR measure and 
compare it with their performance on the claims-only HWR measure. We do 
not anticipate that the replacement of the claims-only HWR measure with 
the Hybrid HWR measure will negatively impact data reporting. We intend 
to monitor the transition.
    Comment: Some commenters expressed concerns regarding the 
capabilities of the QualityNet Secure Portal and the management of the 
EHR data submissions given the large volume of data that would be 
submitted to CMS for the Hybrid HWR measure. Commenters suggested that 
we consider enhancing our data infrastructure in order to collect data 
and ensure timely upload and receipt of data. A commenter stated that 
previous CMS requirements involving submission of large amounts of eCQM 
data did not perform well, stating that previous CMS platforms were 
unable to handle the volume.
    Response: We recognize stakeholders' concerns about CMS' data 
receiving infrastructure. The 2018 Voluntary Reporting Period served, 
in part, to test the capacity of our data receiving and processing 
systems to accommodate the EHR data and create files with EHR and 
claims data for measure calculation--150 hospitals successfully 
participated in the voluntary reporting of 2018 data for the Hybrid HWR 
measure, either individually or through a vendor. We successfully 
merged 76 percent of the EHR submissions with matching claims data and 
calculated results on 149 hospitals whose discharges met all inclusion 
and exclusion criteria. This demonstrates the feasibility of receiving, 
processing, and reporting data for the Hybrid HWR measure. We encourage 
all hospitals to participate in the voluntary reporting period as an 
opportunity to obtain detailed feedback on their performance on the 
measure, to provide us with additional feedback on the measure 
specifications and their implementation experience, to confirm mapping 
and extraction of data elements, to perform quality assurance, and to 
troubleshoot any problems during QRDA file submissions. We continue to 
pursue efficiencies in our data receiving systems to accommodate large 
QRDA I files.
    Comment: A commenter suggested that we partner with EHR vendors to 
ensure that their products are built to accommodate the technical 
demands a hybrid measure will require. A commenter expressed concerns 
that this measure will create a dependency on EHR vendors' ability to 
build or map the proposed metrics with their respective costs and 
timeframes.
    Response: We appreciate the commenters' position and acknowledge 
that a degree of reliance on EHR vendors is inherent in quality 
reporting using EHR-based data. However, as previously discussed, we 
conducted extensive testing to ensure that all EHR data elements used 
in the measure specifications were readily available for the patient 
population and feasibly extracted from most commercial EHR systems. The 
information on patients' vital signs and laboratory test values should 
be available in all certified EHR systems. We will continue to engage 
with vendors and encourage them to support reporting of the Hybrid HWR 
measure. We note that there are a number of channels for vendors and 
other stakeholders to provide feedback earlier in the measure 
development process, including the eCQI Resource Center, which provides 
numerous current resources to support electronic clinical quality 
improvement. We anticipate that finalizing future mandatory reporting 
of the Hybrid HWR measure will incentivize greater vendor 
participation.
    Comment: A few commenters were unsure of the value of adding core 
clinical data elements to the measure. A commenter noted that they 
would be interested in further information regarding the added value of 
capturing other data elements that should be captured in the ICD-CM 
codes included in the claims, such as weight, glucose, or temperature.
    Response: The Hybrid HWR measure uses a combination of 
administrative data and a set of core clinical data elements extracted 
from EHRs for each hospitalized Medicare FFS beneficiary over the age 
65 years (84 FR 19481). Administrative data consist of Medicare Part A 
and Part B claims data and Medicare beneficiary enrollment data used to 
both identify index admissions included in the measure cohort, as well 
as to create a risk adjustment model. The elements of the clinical data 
improve the discrimination of hospital outcome measures as assessed by 
c-statistic and enhances the face validity of measures for the clinical 
community.471 472
---------------------------------------------------------------------------

    \471\ We refer readers to the 2015 Hybrid HWR Measure with 
Electronic Health Record Extracted Risk Factors report, available 
at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228776337297.
    \472\ 80 FR 49699
---------------------------------------------------------------------------

    There are 13 specific core clinical data elements used in the 
Hybrid HWR measure. Claims data are merged with the EHR-based core 
clinical data elements to calculate the risk-adjustment for patients' 
severity of illness. During measure development, we addressed 
stakeholder concerns that clinical data garnered from patients, and 
used by clinicians to guide diagnostic decisions and treatment, are 
preferable to administrative claims data when profiling hospitals' case 
mix.\473\ To reduce the reporting burden on hospitals, the core 
clinical data elements were developed as a minimum dataset that could 
be feasibly collected and used across a variety of condition cohorts 
and measures.
---------------------------------------------------------------------------

    \473\ Centers for Medicare and Medicaid Services (CMS). Hybrid 
Hospital-Wide Readmission Methodology Report (2013). Available at: 
https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228776337297.
---------------------------------------------------------------------------

    Comment: A few commenters questioned whether using the core 
clinical data elements has presented any significant differences in 
risk adjustment relative to the claims data, and a commenter questioned 
whether the EHR variables required were related to readmissions 
outcomes. Commenters stated that additional testing should be completed 
prior to hospitals having to participate to ensure the addition of the 
proposed thirteen core clinical data

[[Page 42473]]

elements makes a significant impact on risk adjustment.
    Response: The Hybrid HWR measure uses data from patients' EHRs as 
well as claims data in the risk adjustment model. When added to claims 
data, the core clinical data elements enhanced the ability of the risk 
model to distinguish higher and lower risk patients. Results of testing 
conducted during original measure development showed that the core 
clinical data elements combined with the original claims-only HWR 
measure approach to risk adjustment yielded the best predictive model 
of readmission. During testing of the 30-day readmission model, the 
core clinical data elements were statistically significant predictors 
of readmission in the risk-adjusted hospital-wide cohort. The testing 
results demonstrate that the core clinical data elements enhanced the 
discrimination (assessed using the c-statistic) when used either in 
combination with or in place of administrative claims data for risk 
adjustment of currently reported CMS 30-day mortality and readmission 
outcome measures.\474\ In addition, inclusion of clinical information 
from patient EHRs is responsive to stakeholders who find it preferable 
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 in addition to data from claims.
---------------------------------------------------------------------------

    \474\ 80 FR 49699.
---------------------------------------------------------------------------

    As described in the proposed rule (84 FR 19482 through 19483), the 
methods used to calculate the Hybrid HWR measure align with the methods 
used to calculate the claims-only HWR measure. In the Hybrid HWR 
measure, index admissions are assigned to one of five mutually 
exclusive specialty cohort groups consisting of related conditions or 
procedures. For each specialty cohort group, we calculate a 
standardized readmission ratio (SRR), the ratio of the number of 
``predicted'' readmissions to the number of ``expected'' readmissions. 
For each hospital, the numerator of the SRR is the number of 
readmissions within 30 days predicted based on the hospital's 
performance with its observed case mix and service mix. The denominator 
is the number of readmissions expected based on the performance of an 
average hospital with similar 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 hospital's 
risk-standardized readmission rate (RSRR).
    Comment: A few commenters believed that the approach to Hybrid HWR 
measure scoring lacks transparency.
    Response: We refer commenters to the 2018 All-Cause Hospital-Wide 
Measure Updates and Specifications Report for more calculation details 
for Hybrid HWR scores.\475\ Hybrid measure results must be calculated 
by CMS to determine hospitals' risk-adjustment rates relative to other 
hospitals participating in the voluntary reporting.
---------------------------------------------------------------------------

    \475\ 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.
---------------------------------------------------------------------------

    Comment: A commenter questioned the impact this measure will have 
on readmission rates if patients' claims data do not match their EHR 
data.
    Response: In relation to linking variables, we expect that the 
claims data submitted by hospitals match the information hospitals 
submit in their QRDA files. We clarify that mismatched data cases would 
not be included in the measure calculation. For the 2018 Voluntary 
Reporting Period, we excluded EHR-based admissions that could not be 
linked to claims data obtained from the measure calculation. We 
provided feedback to hospitals on all EHR-based admissions they 
submitted core clinical data elements for, regardless of whether or not 
it was linked to claims data. Hospitals are encouraged to participate 
in future voluntary reporting periods if they are interested in 
monitoring their performance on the Hybrid HWR measure. For the 2018 
Voluntary Reporting Period, we have posted the methodology we used to 
match EHR-based data to claims-based data in the Hybrid HWR Hospital-
Specific Report User Guide, available at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier4&cid=1228778821616.
    Comment: Several commenters expressed concern about the impact that 
adopting the Hybrid HWR measure could have on hospital resources. 
Several commenters noted that prior eCQMs have been difficult to 
collect and costly for hospitals, resulting in greater administrative 
burden. A commenter expressed doubt as to whether the increased 
administrative burden of the Hybrid HWR measure outweighed the benefit 
of the improvements. A commenter stated that reporting data using the 
Quality Reporting Document Architecture (QRDA) file format for hybrid 
measures is innately burdensome for eligible hospitals.
    Response: We understand the commenters' perspective that eCQMs have 
been difficult to collect and that they are concerned about the impact 
that adopting a hybrid measure could have on hospital resources. We 
acknowledge that there may be costs beyond information collection 
burden associated with EHR-based quality measures, such as related to 
data mapping and validation. However, we do not believe that hospitals 
will need a great deal of time to evaluate and re-design their EHRs 
because the EHR data used in the Hybrid HWR measure are standard core 
clinical data elements. The EHR data was selected in part because they 
are consistently obtained on adult inpatients based on current clinical 
practice; are captured with a standard definition and recorded in a 
standard format across providers; and are entered in structured fields 
that are feasibly retrieved from current EHR systems.\476\ The purpose 
of the core clinical data elements is to extract clinical data that are 
already routinely captured in EHRs among hospitalized adult patients. 
We sought to include data available on all patients and to avoid 
selecting data elements that might require clinical staff to perform 
additional measurements or tests that are not needed for diagnostic 
assessment or treatment of patients.
---------------------------------------------------------------------------

    \476\ For additional details regarding the measure 
specifications, we refer readers to the 2018 All-Cause Hospital-Wide 
Measure Updates and Specifications Report. (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.)
---------------------------------------------------------------------------

    For the Hybrid HWR measure, we anticipate that hospitals will 
experience a slight information collection burden increase for 
reporting the core clinical data elements and linking variables used in 
the measure population, but we believe the burden is outweighed by the 
improved discrimination of the measure, or the ability to distinguish 
between patients of high risk of the outcome and low risk of the 
outcome. There is no additional burden on hospitals to report the 
claims-based portion of this measure because these data are already 
reported to the Medicare program for payment purposes. Hospitals are 
also not responsible for combining the claims data with the EHR data, 
which

[[Page 42474]]

ultimately results in the measure score. Therefore, we anticipate 
hospitals will experience modest costs related to the initial mapping 
and extraction. We refer readers to sections X.B.3 and I.K. of Appendix 
A of this final rule for a more detailed discussion of information 
collection burden and effects, respectively, related to the Hybrid HWR 
measure.
    We acknowledge that submission of EHR data using QRDA I files may 
be an added burden to hospitals. However, we believe that many 
stakeholders maintain a strong preference for the use of more timely 
clinical data in performance measures, which is most readily available 
in EHRs. Currently, QRDA I is the EHR data and measure reporting 
standard adopted for eCQMs implemented in the Hospital IQR Program. We 
continue to pursue efficiencies in our data receiving systems to 
accommodate large QRDA I files.
    Comment: A commenter stated that rural hospitals would be at a 
disadvantage since they may not have the ability to accurately capture 
the required EHR data, claiming it could be expensive. A commenter did 
not support adoption of this measure because it is not specifically 
recommended by the MAP Rural Health Workgroup.
    Response: With respect to rural hospitals, the EHR-derived core 
clinical data elements used in this measure were selected because they 
are already routinely captured in EHRs among hospitalized adult 
patients and readily available in standard formats within structured 
fields in certified EHR systems. This measure does not require that 
clinical staff perform additional measurements or tests. It also does 
not require hospitals to calculate measure results. It only requires 
hospitals to submit the patients' vital signs and laboratory test 
results that are already captured in routine care. We believe that 
rural hospitals have these data available in standard EHR data fields 
for most adult hospitalized patients. Additionally, twelve rural 
hospitals successfully participated in the 2018 Voluntary Reporting 
Period. Finally, because the MAP's Rural Health Workgroup noted that 
the majority of Critical Access Hospitals meet the threshold number of 
cases for the claims-only HWR measure, we believe that many small 
hospitals will have enough data to report on the Hybrid HWR 
measure.\477\ The MAP supported further development of the Hybrid HWR 
measure, which was an expression of their conditional support pending 
endorsement from the National Quality Forum (NQF).\478\ Thereafter, the 
Hybrid HWR measure was endorsed by the NQF on December 9, 2016.\479\ 
Therefore, we believe this measure will be feasible for all hospitals. 
We will continue to monitor the participation of rural hospitals during 
the confidential reporting periods.
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    \477\ MAP Rural Health Workgroup, A Core Set of Rural-Relevant 
Measures and Measuring and Improving Access to Care: 2018 
Recommendations from the MAP Rural Health Workgroup, August 31, 
2018, available at: http://www.qualityforum.org/Publications/2018/08/MAP_Rural_Health_Final_Report_-_2018.aspx.
    \478\ 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.
    \479\ 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.
---------------------------------------------------------------------------

    Comment: Some commenters expressed concerns that the hybrid measure 
requires a measurement period of a full year, as opposed to eCQMs which 
only require a hospital-selected quarter. Several commenters noted that 
the measurement years for the Hybrid HWR measure do not align with the 
eCQMs because the eCQMs are based on a calendar year reporting cycle 
and the Hybrid HWR measure is based on a measurement year of July 
through June. Commenters expressed concern that the misalignment in 
submission timelines will result in confusion and data reporting 
burden.
    Response: We acknowledge the different measurement periods and 
reporting timelines between eCQMs and the Hybrid HWR measure as well as 
potential confusion among some caused by the July 1 to June 30 
measurement and reporting period for the Hybrid HWR measure. The 
measurement period of the Hybrid HWR measure aligns with the claims-
only HWR measurement period.\480\ This aligned measurement period is 
intended to facilitate a smooth transition from the claims-only 
measure, which currently uses a 12-month measurement period from July 1 
to June 30 of the following year, to the hybrid measure in the Hospital 
IQR Program and for uninterrupted public reporting of the HWR measure 
on the Hospital Compare website without a gap or overlap in reporting 
periods.
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    \480\ 77 FR 53522 through 53528.
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    We note that we are finalizing the Hybrid HWR measure reporting 
requirements as proposed, including the hybrid measure submission 
deadlines. Hospitals must submit the core clinical data elements and 
linking variables within 3 months following the end of the applicable 
reporting period (submissions would be required no later than the first 
business day 3 months following the end of the reporting period). This 
allows hospitals and their health IT vendors to stagger their efforts 
during the year with eCQM submissions due in the spring and hybrid 
measure data submissions due in the fall, rather than being required to 
submit all of the data at once. We refer readers to section 
VIII.A.10.e. of the preamble of this final rule for more detail on the 
submission deadlines for hybrid measures. The current claims-only HWR 
measure is publicly reported on our Hospital Compare website each July 
based on claims data pulled during the fall of the previous year. In 
order to continue this schedule and allow for more rapid reporting of 
measure results, we proposed to use EHR data from the same July 1 to 
June 30 measurement period that is used for the currently implemented 
claims-only HWR measure. We will continue to evaluate the ease and 
feasibility of this schedule through the confidential reporting 
periods.
    Comment: A commenter recommended that data field definitions be 
included to ensure consistency in data submission across hospitals. Two 
commenters noted that CMS' push for interoperability may ease the data 
collection process over time. A few commenters requested that we 
clarify how frequently hospitals will be required to submit data, and 
some commenters suggested we consider requiring more frequent reporting 
of EHR data.
    Response: We interpret the commenter's reference to data field 
definitions as a reference to the data element descriptions. In 
response to the comment, we refer readers to the Value Set Authority 
Center (VSAC), which provides the available value set information, 
including the data element descriptions and codes used.\481\
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    \481\ Value Set Authority Center. Available at: https://vsac.nlm.nih.gov/.
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    We also refer readers to section VIII.A.10.e. of the preamble of 
this final rule for more detail on the annual submission deadlines for 
hybrid measures. As the Hybrid HWR measure uses a 12-month measurement 
period from July 1 to June 30 of the following year, we believe that 
annual submission of the core clinical data elements and linking 
variables is an appropriate frequency of reporting.
    Comment: Several commenters expressed concern about the claims data

[[Page 42475]]

extraction process, stating that this measure's reliance on claims data 
will limit its clinical applicability considering the limitations of 
claims data.
    Response: The scientific acceptability of assessing hospital 
performance using claims data has been well established over many 
years.\482\ The issue of the validity and reliability of claims data in 
the readmission measures given its limitations has been carefully 
considered by CMS and NQF over many cycles of review the conclusion of 
which has been continued support of the validity of the measure by 
experts by empiric testing of the measure score and continued 
endorsement of the measure by NQF.483 484 We acknowledge 
that many stakeholders express a preference for the use of clinical 
information that is collected directly from the patient and used to 
diagnose and determine treatment.\485\ For this reason, we have 
augmented the risk adjustment models in the Hybrid HWR measure to 
include data from EHRs indicating patients' severity of illness when 
they present to the hospital for care.\486\ We believe that this 
enhancement addresses an important stakeholder concern and also 
enhances the performance of the measure.
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    \482\ We refer readers to the Hospital 30-Day AMI Readmission 
Measure Methodology Report, available at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier4&cid=1219069855841.
    \483\ http://www.qualityforum.org/QPS/2879e.
    \484\ We refer readers to the Hospital 30-Day AMI Readmission 
Measure Methodology Report, available at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier4&cid=1219069855841.
    \485\ 80 FR 49702 through 49703.
    \486\ For additional details regarding the measure 
specifications, we refer readers to the 2018 All-Cause Hospital-Wide 
Measure Updates and Specifications Report. (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.)
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    Comment: A few commenters noted that it is possible for patient lab 
values to not be captured in the inpatient encounter if the lab tests 
were performed prior to an admission. A commenter questioned how lab 
values would be used if they are not attached to an encounter. Several 
commenters noted that hospitals will need time to reevaluate and design 
their EHRs to collect and validate the data.
    Response: With respect to concerns about laboratory data that are 
not available in the EHR, the Hybrid HWR measure methodology allows 
hospitals to report the first captured core clinical data element 
values even if they occur within the facility's outpatient 
setting.\487\ If no core clinical data element values were captured 
within an outpatient setting owned by the facility in the 24 hours 
prior to the inpatient admission, the hospitals are asked to report the 
first core clinical data elements captured within the 2 hours (for 
vital signs) or 24 hours (for laboratory test values) after 
admission.\488\ We performed extensive testing which demonstrated that 
most patients in the non-surgical specialty cohorts of the Hybrid HWR 
measure have laboratory data captured within this timeframe.
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    \487\ For additional details regarding the measure 
specifications, we refer readers to the 2018 All-Cause Hospital-Wide 
Measure Updates and Specifications Report. (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.)
    \488\ For additional details regarding the measure 
specifications, we refer readers to the 2018 All-Cause Hospital-Wide 
Measure Updates and Specifications Report. (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.)
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    We do not believe that hospitals will need a great deal of time to 
evaluate and design their EHRs because the EHR data used in the Hybrid 
HWR measure are standard core clinical data elements. The EHR data was 
selected in part because they are consistently obtained on adult 
inpatients based on current clinical practice; are captured with a 
standard definition and recorded in a standard format across providers; 
and are entered in structured fields that are feasibly retrieved from 
current EHR systems.\489\ The purpose of the core clinical data 
elements is to extract clinical data that are already routinely 
captured in EHRs among hospitalized adult patients. We sought to 
include data available on all patients and to avoid selecting data 
elements that might require clinical staff to perform additional 
measurements or tests that are not needed for diagnostic assessment or 
treatment of patients.
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    \489\ For additional details regarding the measure 
specifications, we refer readers to the 2018 All-Cause Hospital-Wide 
Measure Updates and Specifications Report. (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.)
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    However, we do recognize that hospitals that did not elect to 
participate in the 2018 Voluntary Reporting Period will require time to 
map, extract, conduct quality assurance, and develop QRDA templates in 
collaboration with health IT vendors. To support time needed for this 
implementation work, we are finalizing two more years of voluntary 
reporting during which the success of data submission will not impact 
hospitals' Hospital IQR Program payment determinations. Participating 
hospitals and their vendors will be able to review the confidential 
hospital-specific reports provided during the voluntary reporting 
periods to support learning and improvement in their procedures for 
extracting data and completing QRDA templates.
    Comment: A commenter stated that since this is the first-time 
clinical data on vital signs and lab data are being used to risk-
adjust, they recommend alignment and consistency across CMS programs 
that use risk-adjusted data.
    Response: In an effort to ensure harmonization across CMS programs, 
the core clinical data elements use existing value sets that are 
already used in other program measures. We agree with the importance of 
aligning these required core clinical data elements in measures used 
across CMS programs to reduce burden on hospitals and improve 
interoperability, and we will take this feedback into consideration as 
we maintain and refine the core clinical data elements for potential 
future hybrid measures.
    Comment: A commenter encouraged the integration of elements from 
the Certified Electronic Health Record Technology (CEHRT) to improve 
the original HWR measure by including core clinical data elements for 
risk adjustment.
    Response: We thank the commenter for their recommendation to 
consider integrating elements from the Certified Electronic Health 
Record Technology (CEHRT) when working to improve the HWR measure. The 
2015 Edition of CEHRT successfully passed testing on specific standards 
and criteria by CMS for use in specific programs.\490\ CEHRT 
requirements include laboratory test results, as well as all elements 
required for reporting on the Hospital IQR Program's eCQMs. This 
includes vital signs identical to those included in the Hybrid HWR 
measure, such as heart rate, systolic blood pressure, respiratory rate, 
temperature, and weight.\491\

[[Page 42476]]

Therefore, given the overlap in requirements, we believe the current 
electronic specifications for this measure are aligned with CEHRT 
requirements.
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    \490\ For additional details about the updates to the 2015 
Edition, we refer readers to ONC's Common Clinical Data Set 
resource, available at: https://www.healthit.gov/sites/default/files/commonclinicaldataset_ml_11-4-15.pdf.
    \491\ 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?cid=1228776337082&pagename=QnetPublic%2FPage%2FQnetTier3&%20c=Page.
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    Comment: A commenter expressed concerns with the clinical data 
elements selected, stating that the measure may not accurately reflect 
the level of acuity for patients.
    Response: We agree that the data elements used in this measure 
cannot fully account for acuity for all patients, for example, some 
indicators of acuity such as mental status might not be captured in 
these elements. The EHR data used in the Hybrid HWR measure do capture 
important aspects of patient acuity and are also standard core clinical 
data elements, selected because they: (1) Reflect patients' clinical 
status when they first present to the hospital; (2) are clinically and 
statistically relevant to patient outcomes; (3) are consistently 
obtained on adult inpatients based on current clinical practice; (4) 
are captured with a standard definition and recorded in a standard 
format across providers; and (5) are entered in structured fields that 
are feasibly retrieved from current EHR systems. The purpose of the 
core clinical data elements is to extract clinical data that are 
already routinely captured in EHRs among hospitalized adult patients.
    Comment: A commenter suggested that we include emergency department 
(ED) data for patients admitted to the hospital from the ED.
    Response: This measure does include vital signs and laboratory test 
values for patients directly admitted to the hospital from the 
ED.492 493 If the patient has values captured prior to 
admission, for example from the emergency department or pre-operative 
or other outpatient area within the hospital, the logic supports 
extraction of the first captured vital signs and laboratory test 
results within 24 hours prior to the start of the inpatient 
admission.494 495 All clinical systems used in inpatient and 
outpatient locations within the hospital facility should be queried 
when looking for core clinical data element values related to a patient 
who is subsequently admitted. The purpose of reporting the first core 
clinical data elements collected after the patient presented to the 
hospital is to better assess and risk-adjust for the health status of 
the patient prior to coming to the hospital and receiving care.
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    \492\ 84 FR 19480 through 19485; Centers for Medicare & Medicaid 
Services. (2018).
    \493\ 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.
    \494\ 84 FR 19480 through 19485; Centers for Medicare & Medicaid 
Services. (2018).
    \495\ 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.
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    Comment: A commenter suggested including medication data in risk-
adjustment.
    Response: We thank the commenter for their suggestion regarding 
medication data to risk adjustment. We are not aware of a reliable way 
to capture upon admission medications that patients take at home, 
meaning that hospitals would only be able to extract and report those 
medications on patients for whom they also had reliable outpatient 
records. Additionally, requiring extraction and submission of 
medications prescribed at discharge from previous hospitalizations 
(before the index admission captured in the measure cohort) would add 
significant burden to hospitals and might not provide more predictive 
information compared with the conditions encoded in the Medicare 
claims. As data capture in EHRs is dynamic and evolving, we will 
continue to consider the feasibility of adding important data in 
measure reevaluation.
    Comment: Many commenters provided feedback regarding measure 
validity, reliability, and additional testing. Several commenters 
suggested that we conduct thorough testing on accuracy and usability of 
the core clinical data elements before mandatory reporting on the 
Hybrid HWR measure and before the data are publicly reported. A 
commenter expressed concerns around the accuracy and reliability of 
eCQMs, encouraged us to postpone implementation of new eCQMs until 
improvements in the technology occur, and suggested that reporting of 
the Hybrid HWR measure remain voluntary until eCQM performance 
improves.
    Response: We appreciate the comments about measure testing. We 
believe that the accuracy and usability of the Hybrid HWR measure has 
been clearly established. We conducted extensive testing of the 
validity of the EHR data elements used in this measure in multiple 
hospitals, health systems, and EHR vendors. During the development of 
this measure, we tested the validity of the data elements, and assessed 
how often data were missing in 8 different health systems. We also 
tested the validity and reliability of the hospital-level measure 
score. Details about this testing can be found in the materials 
submitted to the NQF when this measure was endorsed in 2016.\496\ In 
summary, we have established adequate reliability and validity 
according to NQF experts' standards.
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    \496\ National Quality Forum. Hybrid Hospital-Wide Readmission 
(HWR) Measure with Claims and Electronic Health Record Data (2879e), 
eHWR Tech Report 01-29-16 v1.0. Available at: http://www.qualityforum.org/QPS/QPSTool.aspx?m=2879&e=1#qpsPageState=%7B%22TabType%22%3A1,%22TabContentType%22%3A2,%22ItemsToCompare%22%3A%5B%5D,%22StandardID%22%3A2879,%22EntityTypeID%22%3A1%7D.
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    In addition, we have also demonstrated that the addition of the EHR 
data elements enhance the risk adjustment model, as assessed by 
improvement in the c-statistic with HWR;HWR+CCDE showing; Surgery/
Gynecology 0.800; 0.802, Cardiorespiratory 0.653; 0.668, Cardiovascular 
0.713; 0.731, Neurology 0.670;0.708, Medicine 0.646;0.651which 
demonstrates improved ability to identify patients at high and low risk 
of the outcome.\497\ The measure was reviewed and endorsed by the NQF 
in 2016, meaning it meets their standards for reliability and 
validity.\498\
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    \497\ https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228776337297.
    \498\ https://www.qualityforum.org/QPS/2879e.
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    Furthermore, 150 hospitals successfully submitted the EHR data 
elements required for measure calculation in the 2018 Voluntary 
Reporting Period. Those QRDA files were successfully merged with claims 
data and the measure was calculated among the participating hospitals. 
The Voluntary Reporting Period confirmed the validity of the electronic 
specifications and data elements, the capacity of data receiving and 
processing systems, and the success of measure score calculation. As a 
result, we are confident in the scientific acceptability as well as 
feasibility of the measure. Additionally, we note that based on 
internal monitoring of eCQM submissions, approximately 97 percent of 
eligible hospitals successfully submitted eCQMs for CY 2018; thus, we 
believe hospitals will be ready for mandatory reporting of the Hybrid 
HWR measure that we are finalizing to begin with the July 1, 2023 
through June 30, 2024 measurement period. Nonetheless and as necessary, 
we will continue to test and modify the measure through the process of 
routine measure maintenance and reevaluation during the two additional 
voluntary reporting periods and during mandatory reporting.

[[Page 42477]]

    Comment: A few commenters stated that not all EHR vendors supported 
the voluntary submission process. They expressed a belief that the 80 
hospitals that voluntarily submitted the QRDA I files are biased 
towards the few vendors that supported voluntary submission. Four 
commenters stated that only one major EHR vendor has a module that 
supports the Hybrid HWR measure data submission requirements. Many 
commenters urged us to ensure that the reporting specifications of the 
Hybrid HWR measure remain stable throughout the reporting period.
    Response: We clarify that more than one major vendor and 150 
hospitals participated in and successfully submitted core clinical data 
elements during the 2018 Voluntary Reporting Period for the Hybrid HWR 
measure. We anticipate that finalizing two additional years of 
confidential reporting and finalizing a clear timeline for the future 
mandatory reporting for the measure will incentivize additional vendors 
to participate in reporting for this measure. We will continue to 
monitor vendor participation during confidential reporting periods and 
encourage all hospitals to submit data for both years. We also 
appreciate the suggestion that the specification remain stable through 
confidential reporting. We will continue to engage stakeholders in the 
annual reevaluation and updates of measure specifications to ensure 
stability.
    We realize that hospitals which did not elect to participate in the 
2018 Voluntary Reporting Period did not receive results that they could 
compare to their performance on the claims-only measure. However, all 
hospitals that submit data during the confidential reporting period 
will receive data regarding their performance on the Hybrid HWR 
measure. We are finalizing that hospitals will receive this feedback 
for two consecutive years before this reporting could affect their 
Hospital IQR Program payment determination as proposed.
    Comment: Several commenters expressed a desire for the measure to 
be adjusted for social risk factors (SRF). They noted that experts have 
weighed in on the inclusion of SRFs and have demonstrated the 
feasibility and significance of SRF inclusions. Another commenter noted 
that we should not include outcome measures that are sensitive to 
sociodemographic factors in the Hospital IQR Program.
    Response: We understand the important role that sociodemographic 
factors play in the care of patients. However, we believe the Hybrid 
HWR measure's risk adjustment is appropriate and reliable. The measure 
already incorporates a risk adjustment methodology that accounts for 
age and comorbidities, as well as vital signs and laboratory values at 
the start of the inpatient encounter.\499\ Furthermore, we note that 
the HWR claims only measure was re-endorsed by the National Quality 
Forum (NQF) without adjustment for patient-level social risk factors. 
Although this was not directly tested for the Hybrid HWR measure 
(because of the smaller, limited sample for measure development), the 
two measures have identical specifications except for the EHR data 
elements added to the risk adjustment of the hybrid version. Therefore, 
the results of the claims measure are directly relevant and demonstrate 
that social risk factors exert the majority of their effect at the 
hospital level rather than the patient level. We interpret this to mean 
that the worst outcome observed in patients with social risk factors is 
due more to their increased likelihood of receiving care at a lower 
quality hospital. More information about this decision can be found on 
the NQF website.\500\ We continue to believe that the empiric evidence 
shows that the measures as currently specified provide accurate and 
reliable information about hospital performance on readmission without 
inclusion of social risk factors.\501\ We also refer readers to section 
VIII.A.9. of the preamble of this final rule for a general discussion 
of accounting for social risk factors.
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    \499\ 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.
    \500\ https://www.qualityforum.org/home.aspx.
    \501\ National Quality Forum (July 2017). Social Risk Trial 
Final Report: Evaluation of the NQF Trial Period for Risk Adjustment 
for Social Risk Factors, available at: https://www.qualityforum.org/Publications/2017/07/Social_Risk_Trial_Final_Report.aspx.
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    Comment: Several commenters urged us to continue to test and 
identify new social risk factors that are known to affect rates of 
readmission that are beyond hospitals' control. A commenter believed 
that risk adjustment is needed to prevent disproportionally penalizing 
safety-net providers and academic medical centers.
    Response: We have become aware of recent studies that have 
demonstrated the feasibility and significance of social/demographic 
data that can be obtained from CMS claims data,\502\ and we continue to 
pursue analyses examining whether inclusion of data on social risk 
factors can enhance assessment of hospital performance without 
obscuring important signals of the quality of care they deliver. We 
agree with the important role that sociodemographic factors play in the 
care of patients as well as maintaining access to care as provided by 
safety-net providers, however, this measure is only being finalized for 
the Hospital IQR Program, which does not assess financial penalties 
based on hospital performance on measures. We also note that in most of 
the publicly reported claims-based readmission measures, there are some 
safety net providers observed to be better than average performers, 
demonstrating that they are able to achieve high performance despite 
caring for a larger proportion of socially vulnerable patients.
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    \502\ Assistant Secretary for Planning and Evaluation (ASPE). 
2016 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.
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    Comment: A few commenters expressed concern about the potential 
unintended consequences of the measure. A commenter encouraged CMS to 
monitor this measure for potential unintended consequences that could 
stem from the extraction of EHR data during the voluntary reporting 
period.
    Response: We thank the commenters for their concerns regarding 
unintended consequences. The EHR data used in the Hybrid HWR measure 
are standard core clinical data elements that were selected because 
they: (1) Reflect patients' clinical status when they first present to 
the hospital; (2) are clinically and statistically relevant to patient 
outcomes; (3) are consistently obtained on adult inpatients based on 
current clinical practice; (4) are captured with a standard definition 
and recorded in a standard format across providers; and (5) are entered 
in structured fields that are feasibly retrieved from current EHR 
systems. The purpose of the core clinical data elements is to extract 
clinical data that are already routinely captured in EHRs among 
hospitalized adult patients. It is not intended to require that 
clinical staff perform additional measurements or tests that are not 
needed for diagnostic assessment or treatment of patients. Therefore, 
we do not anticipate any unintended consequences or additional burden 
to providers. The EHR data submission process would align as much as 
possible with existing electronic clinical quality measure (eCQM) 
standards and data reporting procedures for hospitals. Submission of 
data using QRDA I files is the current EHR data and measure reporting 
standard adopted for eCQMs implemented in the Hospital IQR Program.

[[Page 42478]]

    Comment: A commenter stated that an unintended consequence could be 
that reductions in readmissions will create increasing mortality costs.
    Response: We believe that requiring quality reporting on 
readmissions measures has successfully reduced readmissions which are 
both harmful to patients and costly for the health care system. Keeping 
patients healthy is one of our highest priorities, and we welcome any 
research reports pertaining to the unintended consequences of including 
readmissions measures in the Hospital IQR Program. In conjunction with 
the Hospital Readmissions Reduction Program, we are committed to 
monitoring any unintended consequences over time, such as the 
inappropriate shifting of care or increased patient morbidity and 
mortality, to ensure that our quality reporting initiatives improves 
the lives of patients and reduces cost.
    Comment: A few commenters suggested retaining the HWR claims-only 
measure as opposed to replacing it with the Hybrid HWR measure.
    Response: We thank the commenters for their feedback. We disagree 
that we should retain the HWR claims-only measure and not replace it 
with the Hybrid HWR measure, because the addition of the clinical 
information from the EHR improves the ability to distinguish patients 
with higher and lower risk of the outcome as demonstrated by the 
improved c-statistic. We refer readers to section VIII.A.6. of the 
preamble of this final rule where we finalize the removal of the HWR 
claims-only measure. We will continue to engage with stakeholders 
during the voluntary reporting period when those hospitals that choose 
to report on the Hybrid HWR measure will receive performance results 
for the Hybrid and claims-only versions of the HWR measure.
    Comment: A commenter stated that they have concerns with the 
measure because they believed it could be incorrectly applied at the 
clinician level, rather than the hospital level.
    Response: We would like to emphasize that the Hybrid HWR measure, 
like all Hospital IQR Program measures, is only applied at the hospital 
level and not the clinician level. We are finalizing its use to assess 
hospital performance only.
    Comment: A commenter expressed concern that the Hybrid HWR measure 
may not be entirely accurate in determining healthcare-associated 
infections (HAIs) and shared their belief that administrative coded 
data could be useful as supplemental to traditional HAI surveillance, 
but only after validation.
    Response: We would like to clarify that HAI data are not a part of 
the Hybrid HWR measure. The measure uses a combination of 
administrative data and a set of 13 core clinical data elements 
extracted from the hospital's EHR to assess readmission occurring 
within 30 days of discharge from a qualifying index hospital 
admission.\503\ The measure uses an algorithm in the risk adjustment 
step to exclude diagnoses coded only in the index admission claim that 
might be related to the quality of care provided in the hospital from 
the risk model.\504\
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    \503\ 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.
    \504\ 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.
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    Comment: A few commenters believed that CMS will need to 
collaborate with stakeholders to identify the methods for determining 
whether a readmission is related or not to a previous diagnosis to 
ensure fair adjustment of hospital payments and better align with the 
enacting statute of the Hospital Readmissions Reduction Program. A few 
commenters recommended that hospital readmissions not be accounted for 
if they are planned due to treatment staging, reoccurring blood 
transfusions, other treatments or incidents unrelated to the previous 
admission or diagnosis. A few commenters noted that the Hybrid HWR 
measure should only account for unplanned admission that are related to 
previous admission diagnosis. A few commenters recommended that we 
focus our efforts on adjusting condition-specific measures that are 
currently being used in the Hospital Readmissions Reduction Program.
    Response: We appreciate the commenters' concerns and suggestions. 
We clarify that the readmission need not be connected to the original 
diagnosis for purposes of the Hybrid HWR measure. We emphasize that we 
sought feedback during the development of the claims-only HWR measure 
from a Technical Expert Panel regarding the planned readmission 
algorithm that is used to determine if admissions are likely to be 
planned and therefore should not count in the measure outcome. We also 
conducted a validation study across seven hospitals to confirm the 
accuracy of the planned readmission algorithm through medical record 
review. We refer readers to the 2018 All Cause Hospital Wide Measure 
Updates and Specifications Report for more information.\505\ Further, 
we received feedback from experts and the public through the initial 
NQF measure endorsement processes as well as endorsement maintenance. 
We refer readers to 84 FR 19480 through 19485 for a detailed discussion 
of the development, history (including NQF endorsement), and details of 
this measure. Finally, because the measure is implemented in the 
Hospital IQR Program, we regularly correspond with the public and 
experts through our inbox for questions and technical assistance about 
the readmission measure specifications at 
[email protected].
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    \505\ 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.
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    We believe a number of these commenters are addressing the Hospital 
Readmissions Reduction Program, and not the Hospital IQR Program. We 
appreciate the suggestion to focus on the measures that are already 
included in the Hospital Readmissions Reduction Program, but we note 
that the Hospital IQR Program is also an important area of focus. We 
refer readers to section IV.G. of the preamble of this final rule for 
more information on the Hospital Readmissions Reduction Program.
    We reiterate that the Hybrid HWR measure assesses all-cause 
unplanned readmissions within 30 days of discharge; that is, unplanned 
readmissions are considered for any reason, not only those that are due 
to the same or a ``related'' condition. There are several reasons for 
measuring all-cause readmissions. First, from the patient perspective, 
an unplanned readmission is disruptive and costly regardless of cause. 
Second, restricting the measure outcomes to those readmissions that 
seem to be directly related to the initial hospitalization may make the 
measures susceptible to changes in coding practices. Although most 
hospitals would not engage in such practices, we want to eliminate any 
incentive for hospitals to change coding practices in an effort to 
prevent readmissions from being captured in their readmission measure 
results. Third, an apparently unrelated readmission may represent a 
complication related to the underlying condition. Finally, hospitals 
can act to reduce readmissions from all causes. While we do not presume 
that every readmission is preventable, measuring

[[Page 42479]]

all-cause readmission incentivizes hospitals to evaluate the full range 
of factors that increase patients' risk for unplanned readmissions. For 
example, unclear discharge instructions, poor communication with post-
acute care providers, and inadequate follow-up are factors that 
typically increase the risk for an unplanned readmission. Although 
measuring all-cause readmissions will include some patients whose 
readmission may be unrelated to their care (for example, a casualty in 
a motor vehicle accident), such events should occur randomly across 
hospitals and therefore will not affect results on measures that assess 
relative performance.
    Comment: Several commenters did not believe there is sufficient 
evidence to attribute responsibility of readmission rates to hospitals. 
A commenter believed that a hospital-wide readmission measure is too 
imprecise to be an accurate indicator of quality. A commenter expressed 
their belief that the readmissions methodology holds hospitals 
accountable for admissions that happen outside their facility. A 
commenter requested for further clarification on how the hospital-wide 
approach would generate further quality improvement relative to 
existing condition-specific readmission measures.
    Response: The goal of the Hybrid HWR measure is to improve patient 
outcomes by providing patients, clinicians, and hospitals with 
information about hospital level, risk-standardized readmission rates 
of unplanned, all-cause readmission after admission for any eligible 
condition within 30 days of hospital discharge. Measurement of patient 
outcomes allows for a broad view of quality of care that encompasses 
more than what can be captured by individual process-of-care measures. 
Complex and critical aspects of care, such as communication between 
providers, prevention of, and response to, complications, patient 
safety and coordinated transitions to the outpatient environment, all 
contribute to patient outcomes but are difficult to measure by 
individual process measures.
    In general, randomized controlled trials have shown that 
improvement in the following areas can directly reduce readmission 
rates: Quality of care during the initial admission; improvement in 
communication with patients, their caregivers, and their clinicians; 
patient education; pre-discharge assessment; and coordination of care 
after discharge. Evidence that hospitals have been able to reduce 
readmission rates through these quality-of-care initiatives illustrates 
the degree to which hospital practices can affect readmission 
rates.\506\ The HWR measure provides an overall signal of quality for 
hospitals in contrast to condition-specific measures which provide more 
narrowly focused quality information. We believe that both types of 
readmission measures provide beneficiaries and providers with useful 
information that allows them to improve patient outcomes.
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    \506\ We refer readers to the following sources for more detail 
on these issues: 1. Jack BW, Chetty VK, Anthony D, Greenwald JL, 
Sanchez GM, Johnson AE, et al. A reengineered hospital discharge 
program to decrease rehospitalization: A randomized trial. Ann 
Intern Med 2009;150(3):178-87; 2. Coleman EA, Smith JD, Frank JC, 
Min SJ, Parry C, Kramer AM. Preparing patients and caregivers to 
participate in care delivered across settings: The Care Transitions 
Intervention. J Am Geriatr Soc 2004;52(11):1817-25; 3. Courtney M, 
Edwards H, Chang A, Parker A, Finlayson K, Hamilton K. Fewer 
emergency readmissions and better quality of life for older adults 
at risk of hospital readmission: A randomized controlled trial to 
determine the effectiveness of a 24-week exercise and telephone 
follow-up program. J Am Geriatr Soc 2009;57(3):395-402; 4. Garasen 
H, Windspoll R, Johnsen R. Intermediate care at a community hospital 
as an alternative to prolonged general hospital care for elderly 
patients: A randomised controlled trial. BMC Public Health 
2007;7:68; 5. Koehler BE, Richter KM, Youngblood L, Cohen BA, 
Prengler ID, Cheng D, et al. Reduction of 30-day postdischarge 
hospital readmission or emergency department (ED) visit rates in 
high-risk elderly medical patients through delivery of a targeted 
care bundle. J Hosp Med 2009;4(4):211-218; 6. Mistiaen P, Francke 
AL, Poot E. Interventions aimed at reducing problems in adult 
patients discharged from hospital to home: A systematic metareview. 
BMC Health Serv Res 2007;7:47; 7. Naylor M, Brooten D, Jones R, 
Lavizzo-Mourey R, Mezey M, Pauly M. Comprehensive discharge planning 
for the hospitalized elderly. A randomized clinical trial. Ann 
Intern Med 1994;120(12):999-1006; 8. Naylor MD, Brooten D, Campbell 
R, Jacobsen BS, Mezey MD, Pauly MV, et al. Comprehensive discharge 
planning and home follow-up of hospitalized elders: A randomized 
clinical trial. Jama 1999;281(7):613-20; 9. van Walraven C, Seth R, 
Austin PC, Laupacis A. Effect of discharge summary availability 
during post-discharge visits on hospital readmission. J Gen Intern 
Med 2002;17(3):186-92; 10. Weiss M, Yakusheva O, Bobay K. Nurse and 
patient perceptions of discharge readiness in relation to 
postdischarge utilization. Med Care 2010;48(5):482-6; and 11. 
Krumholz HM, Amatruda J, Smith GL, et al. Randomized trial of an 
education and support intervention to prevent readmission of 
patients with heart failure. J Am Coll Cardiol. Jan 2 
2002;39(1):8389.
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    Comment: A commenter expressed concern regarding the possibility of 
the Hybrid HWR measure being included in the Medicare Beneficiary 
Quality Improvement Project (MBQIP).
    Response: We thank the commenter for their comment and clarify that 
MBQIP is administered by HHS' Health Resources & Services 
Administration (HRSA).\507\ The Hybrid HWR measure was proposed for 
adoption in the Hospital IQR Program. We will share this comment with 
HRSA.
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    \507\ https://www.ruralcenter.org/tasc/mbqip.
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    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Hybrid HWR measure into the 
Hospital IQR Program in a stepwise fashion as proposed. We will first 
accept data submissions for the Hybrid HWR measure during two voluntary 
reporting periods. The first voluntary reporting period will run from 
July 1, 2021 through June 30, 2022, and the second will run from July 
1, 2022 through June 30, 2023. Hospitals will be required to report the 
Hybrid HWR measure, beginning with the reporting period which runs from 
July 1, 2023 through June 30, 2024, impacting the FY 2026 payment 
determination, and for subsequent years.
6. Removal of Claims-Based Hospital-Wide All-Cause Unplanned 
Readmission Measure (NQF #1789) (HWR Claims-Only Measure)
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19485), we 
proposed 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 in this final rule.
    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 the proposed rule, we proposed 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 previously 
discussed in section VIII.A.5.b. of the preamble of this final rule, 
the Hybrid HWR measure is an enhanced version of the HWR claims-only 
measure, in that it provides substantive improvement to the current 
claims-based measure, which is why we proposed 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

[[Page 42480]]

versions due to the incorporation of clinical data (80 FR 49694).
    We proposed 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 
previously noted and discussed in detail in section VIII.A.5.b. of the 
preamble of this final 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 proposed 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 final 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 proposed 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 was contingent upon our proposals for the Hybrid HWR measure 
being finalized.
    Comment: Many commenters supported our proposal to remove the HWR 
claims-only measure. A few commenters appreciated that the Hybrid HWR 
measure is an improved approach to measuring hospital-wide 
readmissions, as integrating EHR data and claims data is a step toward 
improving risk adjustment. A few commenters' support was contingent 
upon the adoption of the Hybrid HWR measure. A commenter encouraged 
that we time the removal of the HWR claims-only measure to ensure 
continuity of available data. A commenter recommended we work with 
hospitals during the voluntary reporting period to ensure that any 
issues are identified and addressed before the HWR claims-only measure 
is removed and the Hybrid HWR measure is adopted as a mandatory 
measure.
    Response: We thank the commenters for their support, and we agree 
that the Hybrid HWR measure is an improved approach toward measuring 
hospital-wide readmissions. We reiterate that our proposal to remove 
the HWR claims-only measure was contingent upon the adoption of the 
Hybrid HWR measure, which is being finalized in section VIII.A.5.b. of 
the preamble of this final rule. In this final rule, we are finalizing 
the removal of the claims-based HWR measure starting with the July 1, 
2023 through June 30, 2024 reporting period, for the FY 2026 payment 
determination, which directly coincides with the mandatory reporting 
for the Hybrid HWR measure. Hospitals will be required to report the 
Hybrid HWR measure, beginning with the reporting period which runs from 
July 1, 2023 through June 30, 2024, impacting the FY 2026 payment 
determination, and for subsequent years. The first voluntary reporting 
period will run from July 1, 2021 through June 30, 2022, and the second 
will run from July 1, 2022 through June 30, 2023. Therefore, we do not 
anticipate a gap in data. We appreciate the commenter's suggestion and 
will continue to monitor reporting issues during the voluntary 
reporting periods for the Hybrid HWR measure through our standard 
channels of education and outreach, including webinars and help desk 
questions.
    Comment: Several commenters expressed support for the removal of 
the HWR claims-only measure because they believed it to be an 
inaccurate representation of quality. Those commenters stated that 
claims data are not clinically validated and, therefore, believed that 
the data do not accurately represent quality of care.
    Response: We thank the commenters for this feedback. We disagree 
with commenters regarding the value of claims-based measures and 
continue to believe that claims-based measures are an appropriate and 
relatively low-burden approach to quality measurement. We proposed to 
remove this measure to replace it with the hybrid version, which also 
relies on claims data. In constructing claims-based measures, we aim to 
utilize only those data elements from the claims that have both face 
validity and reliability. We avoid the use of fields that are believed 
to be coded inconsistently across hospitals. Specifically, we use 
fields that are consequential for payment and which are audited. We 
therefore believe these data have low enough reporting error for the 
data elements we collect for our claims-based measures to be an 
accurate representation of quality. For more information about CMS' 
Medicare fee for service recovery audit program, we refer readers to: 
https://www.cms.gov/Research-Statistics-Data-and-Systems/Monitoring-Programs/Medicare-FFS-Compliance-Programs/Recovery-Audit-Program/.
    In addition, during measure development of the HWR claims-only 
measure, CMS validated the claims-based risk adjustment for the 
readmission measures against a medical record data-based model with the 
same cohort of patients.\508\ The medical record data included chart-
based risk adjusters, such as blood pressure, not available in the 
claims data. We then compared the output of the two measures, in the 
same group of patients. The performance of the administrative and 
medical record models was similar. The areas under the receiver 
operating characteristic (ROC) curve were 0.61 and 0.58, respectively; 
the correlation coefficient of the hospital-level risk-standardized 
rates from the administrative and medical record models was 0.97. We 
will continue to explore multiple options to account for the effect of 
social risk factors on quality measures and in quality programs.
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    \508\ Center for Medicare and Medicaid Services (CMS). 2019 
Condition-Specific Readmission Measures Updates and Specifications 
Report. Available at: https://www.qualitynet.org/dcs/BlobServer?blobkey=id&blobnocache=true&blobwhere=1228890945658&blobheader=multipart%2Foctet-stream&blobheadername1=Content-Disposition&blobheadervalue1=attachment%3Bfilename%3D2019CondSpecific_Readmission_AUS_Report.pdf&blobcol=urldata&blobtable=MungoBlobs.

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[[Page 42481]]

    Comment: A number of commenters believed that the claims-based data 
used in claims-only measures cannot be adequately adjusted to account 
for clinical and social risk factors and that hospitals that care for 
vulnerable patient populations may be disadvantaged by the claims-based 
version of this measure. Most of those commenters also believed that 
adopting the Hybrid HWR measure is a positive step towards improvements 
to risk adjustment.
    Response: We agree that adopting the Hybrid HWR measure is an 
important improvement to the risk adjustment methodology by not only 
accounting for age and comorbidities, but also vital signs and 
laboratory values at the start of the inpatient encounter, which is why 
we are finalizing replacing the HWR claims-only measure with the Hybrid 
HWR measure. We note that neither version of the HWR measure includes 
social risk factors in the risk adjustment. The HWR claims-only measure 
underwent extensive testing with social risk factors, which included an 
assessment of the potential impact on hospital-level performance of 
including social risk factors in the risk model, as well an estimation 
of the relative contribution of hospital quality or patient-level risk 
on the statistical association of social risk variables and the 
readmission outcome.509 510 These data were successfully 
presented to the National Quality Forum (NQF) during endorsement 
maintenance. The data showed that the hospital-level effects of social 
risk were significantly greater than the patient-effects in the risk 
models, suggesting that the greater risk of readmission was 
attributable to the greater likelihood of patients with social risk to 
receive care and lower quality hospitals. Therefore, if we were to 
adjust for patient-level differences in social risk, then some of the 
differences between hospitals would also be adjusted for, potentially 
obscuring a signal of hospital quality. Therefore, we determined that 
it is not appropriate to include these variables in the risk adjustment 
model.
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    \509\ National Quality Forum (NQF). Hospital-Wide All-Cause 
Unplanned Readmission Measure (HWR) Specifications, 2018. Available 
at: http://www.qualityforum.org/QPS/QpsMeasureExport.aspx?exportType=pdf&exportFrom=s&measureIDs=1789.
    \510\ http://www.qualityforum.org/QPS/2879e.
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    Comment: A few commenters supported the proposal to remove this 
measure and also recommended that we remove it earlier than proposed.
    Response: We appreciate the commenters' support for removing the 
claims-only version earlier than proposed; however, as previously 
discussed, we have coordinated the removal timing to ensure continuity 
of public reporting on Hospital-Wide All-Cause Unplanned Readmission 
measure data.
    Comment: A few commenters opposed our proposal to remove the HWR 
claims-only measure. Some commenters opposed the removal of the claims-
only version because of concerns about the reliability of the hybrid 
version that would replace it. A commenter suggested that we retain the 
HWR claims-only measure until the Hybrid HWR measure is proven to be a 
reliable measure. Another commenter recommended that we retain the 
measure while allowing additional time for the Hybrid HWR measure to be 
reported on a voluntary basis.
    Response: We appreciate the commenters' concerns regarding the 
reliability of the Hybrid HWR measure. We refer readers to section 
VIII.A.5.b. of this final rule in which we provide a more detailed 
discussion of the reliability of the hybrid version of this measure. We 
believe that the accuracy and usability of the Hybrid HWR measure has 
been clearly established. Nonetheless, we will continue to assess and 
modify the measure through the process of measure reevaluation during 
the two additional voluntary reporting periods and in mandatory 
reporting.
    We reiterate that the claims-only version of the measure will 
remain in the Hospital IQR Program for 2 more years during voluntary 
reporting of the Hybrid HWR measure, which we believe provides 
hospitals and vendors with sufficient time to implement the Hybrid HWR 
measure. As previously noted, we are finalizing our proposal as 
proposed to adopt the Hybrid HWR measure in a stepwise fashion, with 
mandatory reporting beginning with the reporting period which runs from 
July 1, 2023 through June 30, 2024, impacting the FY 2026 payment 
determination.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed to remove the Claims-Based 
Hospital-Wide All-Cause Unplanned Readmission Measure in conjunction 
with finalizing 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.
7. Summary of Previously Finalized and Newly Finalized Hospital IQR 
Program Measures
a. Summary of Previously Finalized Hospital IQR Program Measures for 
the FY 2022 Payment Determination
    This table summarizes the previously finalized Hospital IQR Program 
measure set for the FY 2022 payment determination:
[GRAPHIC] [TIFF OMITTED] TR16AU19.183


[[Page 42482]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.184


[[Page 42483]]


b. Summary of Previously Finalized and Newly Finalized Hospital IQR 
Program Measures for the FY 2023 Payment Determination
    This table summarizes the previously finalized and newly finalized 
Hospital IQR Program measure set for the FY 2023 payment determination:
[GRAPHIC] [TIFF OMITTED] TR16AU19.185


[[Page 42484]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.186

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, 
in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19487 through 19494), 
we invited 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.\511\ 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.\512\ 
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.\513\ 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.\514\ Another retrospective cohort study showed 
hospitalized patients with diabetes who experienced 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 (p<0.01 for all).\515\
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    \511\ 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.
    \512\ 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.
    \513\ 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.
    \514\ 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.
    \515\ 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

[[Page 42485]]

patient days.516 517 518 Severe hypoglycemic events are 
largely avoidable by careful use of anti-diabetic medication and close 
monitoring of blood glucose values.
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    \516\ 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.
    \517\ 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.
    \518\ 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),\519\ 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.\520\ 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.
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    \519\ Classen, D.C., 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.
    \520\ 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.
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(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.'' \521\
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    \521\ 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 hypoglycemia measure 
originally endorsed by the NQF, Glycemic Control--Severe Hypoglycemia 
(NQF #2363).\522\ 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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    \522\ 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.'' \523\ 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.524 525 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 <40 mg/dL for defining harm events to assess unintended 
consequences. Other recommendations from the MAP included defining the 
numerator as the total number of hypoglycemia events per 
hospitalization instead of the current numerator definition as a count 
of hospitalizations with at least one hypoglycemia event. The numerator 
definition was discussed at length with the measure TEP during 
development. The TEP members agreed with the current numerator 
definition of a count of hospitalizations with at least one 
hypoglycemic event because this adequately captures differences in 
quality among hospitals while simultaneously minimizing measure burden 
by not requiring hospitals to extract every single hypoglycemic event 
during a hospitalization. We agree with the importance of continually 
monitoring for unintended consequences once this measure is 
implemented. We recognize the importance of measuring hyperglycemia in 
conjunction with hypoglycemia and are currently developing a severe 
hyperglycemia eCQM. For additional information and discussion of 
concerns and considerations raised by the MAP related to this measure, 
we refer readers to the December 2018 NQF MAP Hospital Workgroup 
meeting transcript.\526\ In the proposed rule, we noted that 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. In this final rule, 
we add that the Scientific Methods Panel reviewed the scientific 
acceptability (reliability and validity of data elements and the 
measure as a whole) in March 2019 and the Patient Safety Standing 
Committee reviewed the measure for all NQF criteria in June 2019. For 
additional information and

[[Page 42486]]

discussion of concerns and considerations raised during these reviews, 
we refer readers to the March 2019 Scientific Methods Panel meeting 
transcript and the Spring 2019 Patient Safety Standing Committee 
meeting transcript.527 528
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    \523\ List of Measures Under Consideration for December 1, 2018. 
Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \524\ 2018-2019 Spreadsheet of Final Recommendations to HHS and 
CMS. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \525\ 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.
    \526\ Measure Applications Partnership, December 2018 NQF MAP 
Hospital Workgroup Meeting Transcript. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \527\ March 2019 Scientific Methods Panel meeting transcript. 
Available at: https://www.qualityforum.org/Measuring_Performance/Scientific_Methods_Panel/Meetings/2019_Scientific_Methods_Panel_Meetings.aspx.
    \528\ Spring 2019 Patient Safety Standing Committee meeting 
transcript. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=86057.
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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. In this final rule, we 
also refer readers to the new space on the eCQI Resource Center for 
eCQMs that have been developed but are not finalized for reporting in a 
CMS program by clicking on the ``Pre-Rulemaking eCQMs'' tab on the 
right-hand side of the screen. We have posted draft specifications for 
this eCQM as well as several other eCQMs being finalized, as well as 
those we sought comment on, in this years' rule on the eCQI Resource 
Center at the following location: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
(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 
(<40 mg/DL) are avoidable.529 530 531 532 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 believe risk 
adjustment is warranted for this measure. We will continue to evaluate 
the appropriateness of risk adjustment in measure reevaluation.
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    \529\ 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.
    \530\ 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.
    \531\ Office of the Inspector General (OIG). (2010). Adverse 
Events in Hospitals: National Incidence Among Medicare 
Beneficiaries.
    \532\ 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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    In the proposed rule, we invited 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.
    Comment: Many commenters expressed support for the potential future 
inclusion of the Hospital Harm--Severe Hypoglycemia eCQM in the 
Hospital IQR Program. A few commenters noted that the information 
required to report this measure is easily available in current 
workflows and EHRs, and that the results accurately reflect true 
hypoglycemic events. Commenters believed that glycemic control in the 
hospital setting is very important, and that implementation of the 
measure reduces patient harm, length of stay, and reduces costs. A few 
commenters conditioned their support on the feasibility of the 
specifications and a reasonable implementation timeline.

[[Page 42487]]

    Response: We thank commenters for their support and input. We agree 
that this measure captures important quality information that is 
critical to patient safety. We understand the importance of feasibility 
for implementing new measures, and we note that this measure was 
submitted to NQF for the 2019 Spring cycle and received a favorable 
feasibility rating from the NQF Patient Standing Committee based on an 
evaluation of the required eCQM feasibility scorecard.\533\ We will 
consider implementation timelines as we continue to assess this measure 
for potential future adoption into the Hospital IQR Program.
---------------------------------------------------------------------------

    \533\ National Quality Forum (NQF) Patient Safety Standing 
Committee. Meeting Summary--Measure Evaluation In-person Meeting--
Spring 2019 Cycle. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=90662.
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    Comment: A commenter supported our proposal because the inclusion 
of the Severe Hypoglycemia eCQM would expand the options of eCQMs 
available to hospitals.
    Response: We appreciate the commenter's support.
    Comment: A commenter supported the intent of the measure and agreed 
with the 40mg/dL blood glucose threshold, but also encouraged CMS to 
consider exclusions to the measure.
    Response: We thank this commenter for their feedback. We note that 
this measure aims to capture a broad population and achieve measure 
feasibility while reducing burden in data collection and measure 
calculation. We believe that the measure logic accurately identifies 
patients who received antihyperglycemic medications in the previous 24 
hours, thereby filtering out cases in which patients present with 
severe hypoglycemia due to sepsis, severe liver disease, insulinoma, 
and other conditions.
    Comment: Some commenters supported the intent of the measure but 
urged CMS to consider clinical evidence for defining the low glucose 
value for the Hospital Harm--Severe Hypoglycemia eCQM. A few commenters 
strongly recommended increasing the target blood glucose threshold from 
40 mg/dL to 54 mg/dL to align with clinical standards defined by the 
American Association of Clinical Endocrinologists (AACE), ADA, Advanced 
Technologies & Treatments for Diabetes (ATTD), European Association for 
the Study of Diabetes (EASD), the Endocrine Society (ES), and Juvenile 
Diabetes Research Foundation (JDRF).
    Response: We appreciate the commenters' concerns, and we understand 
the importance of aligning with clinical standards. The American 
Diabetes Association (ADA) classifies hypoglycemia using three levels: 
<70 (hypoglycemia alert), <54 (clinically significant hypoglycemia), 
and no specific glucose threshold (severe hypoglycemia).\534\ A 
threshold of 40 mg/dL aligns with a prior NQF-endorsed measure, has 
received confirmation from the TEP, and helps to reduce false 
positives.\535\ This threshold is also in line with the empiric 
literature regarding severe hypoglycemia.536 537 538
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    \534\ American Diabetes Association. 14. Diabetes care in the 
hospital: Standards of Medical Care in Diabetesd2018. Diabetes Care 
2018;41(Suppl. 1):S144-S151.
    \535\ National Quality Forum. Glycemic Control--Hypoglycemia. 
Available at: http://www.qualityforum.org/Qps/MeasureDetails.aspx?standardID=2363&print=0&entityTypeID=1.
    \536\ Krinsley, J.S., Grover A. (2007). Severe hypoglycemia in 
critically ill patients: Risk factors and outcomes. Critical Care 
Medicine, 35(10):2262-7.
    \537\ Cook, C.B., Kongable, G.L., Potter, D.J., Abad, V.J., 
Leija, D.E., & Anserson, M, (2009). Inpatient glucose control: A 
glycemic survey of 126 U.S. hospitals. Journal of Hospital Medicine, 
4(9):E7-E14.
    \538\ Egi, M., et al. (2010). Hypoglycemia and outcome in 
critically ill patients. Mayo Clinic Proc, 85(3):217-224.
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    Comment: A commenter noted that they were ambivalent toward the 
Hospital Harm--Severe Hypoglycemia eCQM, but expressed concern that the 
logic seemed convoluted in order to prevent false positives in the 
numerator.
    Response: We thank this commenter for their input, and we will 
consider their perspective as we continue to evaluate the Hospital 
Harm--Severe Hypoglycemia eCQM for inclusion in the Hospital IQR 
Program. We note that, as the standards and tools to support eCQM 
development evolve, we will continue to explore opportunities to 
simplify eCQM logic to support implementation.
    Comment: A number of commenters urged CMS not to include the 
Hospital Harm--Severe Hypoglycemia eCQM in the Hospital IQR Program 
until it is fully tested and has received NQF endorsement. Several 
commenters expressed concern about the need for additional testing for 
reliability and validity. A few commenters did not support future 
inclusion of the measure and expressed concern that testing in only two 
vendor systems does not provide an adequate understanding of the 
validity of data elements and does not ensure the measure is feasible 
to implement in the Hospital IQR Program. Commenters also noted that 
performance scores observed from testing across six hospitals ranged 
from 1.05 to 3.56 percent and expressed concern that these scores 
lacked sufficient variation to yield meaningful information about the 
quality of care provided.
    Response: We thank commenters for providing their perspective. 
Please note that signal-to-noise reliability, which describes how well 
the measure can distinguish the performance of one hospital from 
another, was assessed in testing. The signal is the proportion of the 
variability in measured performance that can be explained by real 
differences in performance. Beta testing of 13,636 eligible encounters 
across 6 hospitals for the signal-to-noise ratio yielded a median 
reliability score of 0.889 (range: 0.815-0.924), which indicates 
excellent or near perfect agreement that all the variability is 
attributable to real differences in performance between hospitals.\539\ 
The intent of this outcome measure is to reduce the frequency of 
hypoglycemic adverse events and to improve hospitals' practices for 
appropriate dosing of medication and adequate monitoring of patients 
receiving glycemic control agents. We also note that the Medicare 
Patient Safety Monitoring System (MPSMS), a national surveillance 
system designed to identify and track adverse drug events within the 
hospitalized fee-for-service Medicare population, found that out of 
25,145 hospital visits that the adverse event rate for 
antihyperglycemic agents to be as high as 10.7 
percent.540 541 542 Although, severe hypoglycemic events are 
largely avoidable by careful use of anti-diabetic medication and proper 
glucose monitoring, studies have shown that up to 84 percent of 
patients with an episode of severe hypoglycemia (<40 mg/dL) had a prior 
episode of hypoglycemia (<70 mg/dL) during the same admission, and that 
despite recognition of hypoglycemia, up to 75 percent of patients did 
not have their dose of basal insulin changed before the

[[Page 42488]]

next insulin administration.543 544 Other studies have shown 
that hypoglycemic events can be reduced by 56 to 80 percent by careful 
use of antihyperglycemic medication, monitoring of patient blood 
glucose levels, enhanced use of technology, and implementation of 
evidence-based best practices.545 546 547 We also note that 
this measure has also been submitted to the NQF for the 2019 Spring 
Cycle and received a favorable recommendation by the Scientific Methods 
Panel and the Patient Safety Standing Committee for all endorsement 
criteria including importance, performance gap, scientific 
acceptability of measurement properties (reliability and validity), 
feasibility, usability, and use.\548\
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    \539\ Landis J, Koch G. The measurement of observer agreement 
for categorical data. Biometrics 1977;33:159-174. PubMedLink: 
https://www.ncbi.nlm.nih.gov/pubmed/843571.
    \540\ AHRQ Quality and Safety Review System. Content last 
reviewed September 2018. Agency for Healthcare Research and Quality, 
Rockville, MD. https://www.ahrq.gov/professionals/quality-patient-safety/qsrs/index.html.
    \541\ New System Aims To Improve Patient Safety Monitoring. 
Content last reviewed October 2016. Agency for Healthcare Research 
and Quality, Rockville, MD. https://www.ahrq.gov/news/blog/ahrqviews/new-system-aims-to-improve-patient-safety-monitoring.html.
    \542\ Classen DC, Jaser L, Budnitz DS. Adverse drug events among 
hospitalized Medicare patients: epidemiology and national estimates 
from a new approach to surveillance. Jt Comm J Qual Patient Saf. 
2010;36(1):12-21.
    \543\ Dendy JA, Chockalingam, V, Tirumalasetty NN, et al. 
Identifying risk factors for severe hypoglycemia in hospitalized 
patients with diabetes. Endocr Pract 2014;20:1051-1056.
    \544\ Ulmer BJ, Kara A, Mariash CN. Temporal occurrences and 
recurrence patterns of hypoglycemia during hospitalization. Endocr 
Pract 2015;21:501-507.
    \545\ Maynard G, Kulasa K, Ramos P, et al. Impact of a 
hypoglycemia reduction bundle and a systems approach to inpatient 
glycemic management. Endocr Pract 2015;21:355-367.
    \546\ Milligan PE, Bocox MC, Pratt E, Hoehner CM, Krettek JE, 
Dunagan WC. Multifaceted approach to reducing occurrence of severe 
hypoglycemia in a large healthcare system. Am J Health Syst Pharm 
2015;72:1631-1641.
    \547\ American Diabetes Association. Diabetes Care in the 
Hospital: Standards of Medical Care in Diabetes--2018. Diabetes 
Care. 2018;41(Supplement 1):S144.
    \548\ National Quality Forum (NQF) Patient Safety Standing 
Committee. Meeting Summary--Measure Evaluation In-person Meeting--
Spring 2019 Cycle. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=90662.
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    Additionally, we understand the value of sample size in measure 
testing, and note that measure testing was done in compliance with the 
NQF requirements for eCQM development.\549\ The Hospital Harm--Severe 
Hypoglycemia eCQM was tested in two EHR systems that had good 
representation of hospitals across the country. This aligns with NQF's 
recommendation to conduct eCQM testing in more than one EHR 
system.\550\ Empirical results also showed that the measure exhibited 
high reliability and data element validity. We understand the concern 
about the usability of this measure given the range of performance 
rates. We note that such a wide variation indicates ample room for 
improvement with this serious harm event.
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    \549\ National Quality Forum. Measure Evaluation Criteria and 
Guidance for Evaluating Measures for Endorsement. 2016. Available 
at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=83123.
    \550\ Ibid.
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    Comment: A number of commenters referenced inclusion of a potential 
future hyperglycemia measure. Several commenters agreed with the MAP's 
recommendation to pair the Hospital Harm--Severe Hypoglycemia eCQM with 
a balancing measure on hyperglycemia to mitigate potential unintended 
consequences. A few commenters recommended that CMS not move forward 
with the Hospital Harm--Severe Hypoglycemia until a balancing 
hyperglycemia measure could be included in the Hospital IQR Program as 
well. These commenters expressed concerns about potential unintended 
consequences of only addressing hypoglycemia.
    Several commenters expressed concern that providers may be 
discouraged from administering anti-hyperglycemic agents to lower 
glucose for patients who are hyperglycemic as a potential unintended 
consequence of the Hospital Harm--Severe Hypoglycemia eCQM. A commenter 
suggested that adopting a measure addressing hospital-acquired diabetic 
ketoacidosis (DKA) could mitigate potential unintended consequences as 
well.
    Response: We recognize the importance of measuring hyperglycemia in 
conjunction with hypoglycemia and are currently developing a severe 
hyperglycemia eCQM. We agree with the importance of continually 
monitoring for unintended consequences, and we intend to consider these 
comments when assessing which measures to propose for inclusion in the 
Hospital IQR Program in future rulemaking.
    Comment: A commenter expressed concern that the current Hospital 
Harm--Severe Hypoglycemia eCQM does not include risk adjustment for 
sociodemographic factors or stratification, which could result in 
disproportionately penalizing facilities like teaching hospitals and 
safety hospitals that treat more complex patients.
    Response: We thank commenters for their feedback. We note that this 
measure has been submitted to the NQF and received a favorable 
recommendation by the Scientific Methods Panel and the Patient Safety 
Standing Committee for all endorsement criteria including importance, 
scientific acceptability of measurement properties (reliability and 
validity), feasibility, usability and use.551 552 The 
remaining steps during endorsement consideration are generally a review 
of public comments and review by the Consensus Standards Approval 
Committee (CSAC). However, there is also potential for review by the 
NQF Disparities Standing Committee (DSC) if NQF determines that to be 
appropriate.
---------------------------------------------------------------------------

    \551\ National Quality Forum (NQF) Patient Safety Standing 
Committee. Meeting Summary--Measure Evaluation In-person Meeting--
Spring 2019 Cycle. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=90662.
    \552\ National Quality Forum (NQF) Scientific Methods Panel. 
Subgroup #4--Evaluation Meeting Transcript. March 19, 2019. 
Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=89690.
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    In the case of the Hospital Harm--Severe Hypoglycemia eCQM, there 
is evidence indicating that hypoglycemic events of this severity (<40 
mg/DL) are avoidable. While specific patients may be more vulnerable to 
hypoglycemia in certain settings, the most common causes are lack of 
sufficient caloric intake, overuse of anti-diabetic agents, or 
both.\553\ These causes are largely controllable in hospital 
environments, and risk can be reduced by following best practices, we 
believe risk adjustment is not warranted in this case.
---------------------------------------------------------------------------

    \553\ American Diabetes Association. 14. Diabetes care in the 
hospital: Standards of Medical Care in Diabetesd2018. Diabetes Care 
2018;41(Suppl. 1):S144-S151.
---------------------------------------------------------------------------

    Comment: Many commenters recommended that CMS consider the feedback 
it received in discussing the measure with the MAP earlier this year, 
specifically the MAP's recommendation to continuously assess and 
monitor potential unintended consequences, including whether the time 
interval included in this measure (5 minutes between tests) leads to 
unintended consequences. A commenter noted that the timeframe specified 
to repeat a blood glucose test for the Hospital Harm--Severe 
Hypoglycemia eCQM may not be sufficient to properly document measure 
values, potentially resulting in false positives or erroneous results.
    Response: We appreciate commenters' response, and we will take 
their perspective under consideration, as well as the MAP's, as we 
continue to assess the appropriateness of including the Hospital Harm--
Severe Hypoglycemia eCQM in the Hospital IQR Program. To clarify, the 
measure logic does not require a repeat blood glucose test to be 
performed. The expectation is that, in most cases of severe 
hypoglycemia, the clinical team will treat the patient and will not 
immediately repeat the test.\554\ However, if the severe hypoglycemic 
event is suspected to be spurious, for example if the patient is 
clinically

[[Page 42489]]

asymptomatic, and the staff repeat the point-of-care test to confirm 
that suspicion, this step will remove false positive results.\555\ We 
use the 5-minute threshold to maintain consistency with a previously 
endorsed NQF measure for glycemic control.\556\
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    \554\ eCQI Resource Center. Hospital Harm--Severe Hypoglycemia. 
Available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
    \555\ Ibid.
    \556\ National Quality Forum. Glycemic Control--Hypoglycemia. 
Available at: http://www.qualityforum.org/Qps/MeasureDetails.aspx?standardID=2363&print=0&entityTypeID=1.
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    Comment: A few commenters, including a commenter who did not 
support future inclusion of the Hospital Harm--Severe Hypoglycemia 
measure, expressed concern on the lack of clear guidance regarding the 
medications to be monitored for this measure. Commenters also requested 
clarification on where this measure would be abstracted from the EHR. A 
commenter requested that CMS clarify whether point-of-care testing 
(POCT) lab values would be included in the definition of ``laboratory 
values'' for purposes of documenting the measure. The commenter noted 
that POCT values may not always be in discrete fields and expressed 
concern for how CMS will receive and process lab values that are not 
numeric.
    Response: We thank commenters for their perspective. We refer 
readers to the CMS Pre-rulemaking eCQM Value Set available on the Value 
Set Authority Center (https://vsac.nlm.nih.gov/valueset/expansions?pr=CMS-Pre-rulemaking) for the clinical terminologies and 
associated values that indicate which proposed anti-hyperglycemic 
medications will be monitored and the types of glucose tests applicable 
to the measure. Both lab test results and point of care results are 
included in the measure. During measure testing, we did not note 
feasibility issues with capturing results from point of care testing. 
In addition, this measure was submitted to NQF for the 2019 Spring 
cycle and received a favorable feasibility rating from the NQF Patient 
Standing Committee based on an evaluation of the required eCQM 
feasibility scorecard.\557\
---------------------------------------------------------------------------

    \557\ National Quality Forum (NQF) Patient Safety Standing 
Committee. Meeting Summary--Measure Evaluation In-person Meeting--
Spring 2019 Cycle. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=90662.
---------------------------------------------------------------------------

    Comment: A commenter recommended that CMS should clearly define the 
Hospital Harm--Severe Hypoglycemia eCQM's measure terms, utilize data 
elements that are already captured in the EHR to avoid additional 
collection burden, and publish measurement specifications at least 18 
months prior to the measure's inclusion in the Hospital IQR Program.
    Response: We thank commenters for their input, and we refer readers 
to the new space on the eCQI Resource Center for ``Pre-Rulemaking 
eCQMs''. We have posted draft specifications for this eCQM as well as 
several other eCQMs being finalized, as well as those we sought comment 
on, in this year's rule on the eCQI Resource Center at the following 
location: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
    Comment: A commenter expressed concern that the measure is too 
broad and does not consider enough factors to accurately capture issues 
with insulin administration and/or hypoglycemia. A few commenters 
questioned whether severe hypoglycemia was an issue of sufficient scale 
to include in a national reporting program.
    Response: We thank the commenter for their input. We believe that 
this measure captures important quality information that is critical to 
patient safety. We note that this measure has been submitted to the NQF 
and received a favorable recommendation by the Patient Safety Standing 
Committee for all endorsement criteria including importance to measure. 
We will consider the commenters' views as we develop future policy 
regarding potential inclusion of the Hospital Harm--Severe Hypoglycemia 
eCQM in the Hospital IQR Program.
    We thank the commenters and we will consider their views as we 
develop future policy regarding the potential inclusion of the Hospital 
Harm--Severe Hypoglycemia eCQM in the Hospital IQR 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.\558\ Pressure injuries 
commonly can lead to local infection, osteomyelitis, anemia, and 
sepsis,\559\ in addition to causing significant depression, pain, and 
discomfort to patients.\560\ The presence or development of a pressure 
injury can increase the length of a patient's hospital stay by an 
average of 4 days, which can increase the spending ranging from $20,900 
to $151,700 per pressure injury.561 562
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    \558\ 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.
    \559\ 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.
    \560\ 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.
    \561\ 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.
    \562\ 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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    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.\563\ Another study revealed pressure 
injury prevalence rates in U.S. hospitals participating in a registry 
was 2.0 percent for hospital-acquired pressure injuries,\564\ while a 
third national study found 1.8 percent of inpatients had at least one 
pressure injury based on ICD-9 codes.\565\ Pressure injury is 
considered a serious reportable event by the NQF,\566\ CMS established 
non-payment for pressure injury,\567\ and it is an indicator of the 
quality of nursing care a hospital provides.\568\ It is well-

[[Page 42490]]

accepted that pressure injury can be reduced through best practices 
\569\ such as frequent repositioning, proper skin care, and specialized 
cushions or beds.\570\ 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.\571\ Research has also suggested a link 
between a hospital's processes of care and the outcome of hospital-
acquired pressure injury.\572\ We therefore believe that pressure 
injuries are an important issue to address in the Hospital IQR Program.
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    \563\ 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.
    \564\ 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.
    \565\ 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.
    \566\ National Quality Forum, List of SREs. Available at: http://www.qualityforum.org/Topics/SREs/List_of_SREs.aspx.
    \567\ 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.
    \568\ 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.
    \569\ 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.
    \570\ 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.
    \571\ Agency for Healthcare Research and Quality. (2016). 
National Scorecard on Rates of Hospital-Acquired Conditions 2010-
2015: Interim Data From Nation Efforts to Male Health Care Safer. 
Available at: https://www.ahrq.gov/professionals/quality-patient-safety/pfp/2015-interim.html.
    \572\ 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.'' \573\ 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.\574\ The MAP expressed its 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.575 576 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. 
For additional information and discussion of concerns and 
considerations raised by the MAP related to this measure, we refer 
readers to the December 2018 NQF MAP Hospital Workgroup meeting 
transcript.\577\ In this final rule, we add that the Hospital Harm--
Pressure Injury eCQM was submitted to NQF for endorsement consideration 
during the Spring 2019 cycle and received a favorable recommendation by 
the Patient Safety Standing Committee for all endorsement criteria 
including importance, scientific acceptability of measurement 
properties (reliability and validity), feasibility, usability, and 
use.\578\
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    \573\ List of Measures Under Consideration for December 1, 2018. 
Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \574\ 2018-2019 Spreadsheet of Final Recommendations to HHS and 
CMS. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \575\ 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.
    \576\ 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.
    \577\ Measure Applications Partnership, December 2018 NQF MAP 
Hospital Workgroup Meeting Transcript. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \578\ National Quality Forum (NQF) Patient Safety Standing 
Committee. Meeting Summary--Measure Evaluation In-person Meeting--
Spring 2019 Cycle. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=90662.
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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 
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 acute care hospitalizations. 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

[[Page 42491]]

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.579 580 581 582 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. In this final rule, we 
also refer readers to the new space on the eCQI Resource Center for 
eCQMs that have been developed but are not finalized for reporting in a 
CMS program by clicking on the ``Pre-Rulemaking eCQMs'' tab on the 
right-hand side of the screen. We have posted draft specifications for 
this eCQM as well as several other eCQMs being finalized, as well as 
those we sought comment on, in this years' rule on the eCQI Resource 
Center at the following location: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
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    \579\ 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/.
    \580\ 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.
    \581\ Catania, K. et al. (2007). PUPPI: The Pressure Ulcer 
Prevention Protocol Interventions. American Journal of Nursing, 
107(4): 44-52.
    \582\ 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 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.583 584 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 believe risk adjustment is warranted for this measure. We will 
continue to evaluate the appropriateness of risk adjustment in measure 
reevaluation.
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    \583\ 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.
    \584\ 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.
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    In the proposed rule, we invited public comment on potential future 
inclusion of the Hospital Harm--Pressure Injury eCQM in the Hospital 
IQR Program. We specifically sought 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.
    Comment: Many commenters support future adoption of the Hospital 
Harm--Pressure Injury eCQM in the Hospital IQR Program because they 
believe that pressure injury rate transparency will lead hospitals to 
identify and implement best practice improvements, which will reduce 
hospital-acquired pressure injuries. A few commenters noted that the 
data elements are accessible and that the measure would not require 
changes to clinician workflows. A commenter urged CMS to expedite the 
measure development process for this measure. A few commenters 
conditioned their support on the feasibility of the specifications and 
a reasonable implementation timeline.
    Response: We thank the commenters for their support. As we continue 
to assess this measure, we will also consider timelines for potential 
future proposal.
    Comment: Several commenters did not support future adoption of the 
Hospital Harm--Pressure Injury eCQM. Commenters expressed concern about 
potential confusion and redundancy because they believe that the 
measure concept is already being captured by other quality improvement 
measures and efforts. A commenter recommended removing other measures 
that assess similar cohorts.
    Response: We thank the commenters for their feedback. We understand 
that some commenters are concerned with measuring similar harm events 
in both chart abstracted and eCQM measures. We remind stakeholders that 
the PSI-90 composite component, PSI-03, is included in the HAC 
Reduction Program and not the Hospital IQR Program at this time. 
Although we acknowledge that similar measures exist in more than one 
program, these measures are used and calculated from different data 
sources (Medicare FFS claims vs. all payer EHR data) and we believe 
that the universal significance of pressure injuries may warrant 
potential future inclusion of the Hospital Harm--Pressure Injury eCQM.
    Comment: A number of commenters recommended that CMS modify the 
Hospital Harm--Pressure Injury eCQM to exclude certain patient 
populations, including but not limited to: Those receiving end-of-life 
care, hospice services and/or patients on extracorporeal membrane 
oxygenation (ECMO). A few commenters suggested excluding stage 2 
pressure injuries while another suggested limiting the measure to only 
include ICU patients with stage 2 pressure injuries.
    Response: We will take these recommendations into consideration as 
we continue to assess the suitability of this measure for the Hospital 
IQR Program. We note that this measure aims to be as inclusive as 
possible so that it ensures the measure will have the most impact on 
important subgroups of patients. We emphasize that we considered if 
patients are at risk regardless of age or clinical factors and

[[Page 42492]]

whether there is evidence that the risk of a harm can be largely 
ameliorated by best care practices regardless of patients' inherent 
risk profile. All patients require risk assessment and those at higher 
risk require individualized care plans specifically tailored to 
ameliorate those risks. Hence, adjusting away this variation may create 
an incentive for hospitals to defer implementation of best practices 
(For example, more frequent assessment, specialty beds and cushions) in 
higher risk patients.
    We clarify that all pressure injuries stage 2-4, unstageable 
pressure injuries, and deep tissue injuries, which are not present on 
arrival, are included as harms in this measure because all of these 
injuries represent patient harm such as pain and/or distress, and that 
such harms are avoidable by adherence to clinical practice guidelines 
and best practices such as preventive skin care and frequent 
repositioning.\585\ The measure does not assume a linear progression 
through the stages of pressure injury.
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    \585\ Hospital Harm--Pressure Injury eCQM Measure 
Specifications. Available at: https://www.cms.gov/medicare/quality-
initiatives-patient-assessment-instruments/hospitalqualityinits/
measure-methodology.html.
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    Comment: Several commenters did not support the future inclusion of 
the Hospital Harm--Pressure Injury eCQM and expressed concern that the 
requirement for patients to be assessed for pressure injury within 24 
hours of arrival provides too narrow a window for an appropriate skin 
assessment and wound evaluation. A few commenters expressed concern 
that the measure specifications provide insufficient time for inpatient 
staff to document injury if patients transition from the emergency 
department. Commenters also noted that the EHR may not accurately 
capture pressure injury documentation upon admission. Some commenters 
believe that it would be too easy for patients to be included in the 
measure calculation even though their pressure injuries were present on 
admission. A few commenters expressed concern that the Hospital Harm--
Pressure Injury eCQM will reflect documentation variation rather than 
pressure injury performance and noted that documentation of pressure 
injuries may be in free text, not structured EHR fields. A few 
commenters also noted that, in order to ensure proper documentation of 
measure data elements, new workflows may have to be implemented in 
facilities.
    Response: We appreciate the commenters' feedback. We note that 
clinical guidelines, the TEP, and previous public commenters supported 
the requirement for patients to be assessed for pressure injuries 
within 24 hours of hospital arrival.\586\ The information required for 
this eCQM is collected during routine patient assessment in accordance 
with national clinical guidelines. During measure development and 
testing, we noted that the eCQM requirement for documentation in 
discrete fields resulted in a need to adjust clinical workflow in some 
hospitals, but this was offset by the benefit of capturing accurate 
information from which to drive quality improvement efforts. 
Documentation is an important component of the quality signal as 
hospitals cannot measure what is not documented. In addition, this 
measure was submitted to NQF for the 2019 Spring cycle and received a 
favorable feasibility rating from the NQF Patient Standing Committee 
based on an evaluation of the required eCQM feasibility scorecard.\587\
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    \586\ National Pressure Ulcer Advisory Panel, European Pressure 
Ulcer Advisory Panel and Pan Pacific Pressure Injury Alliance. 
Prevention and Treatment of Pressure Ulcers: Clinical Practice 
Guideline. Emily Haesler (Ed.). Cambridge Media: Osborne Park, 
Western Australia; 2014. Available at: http://www.internationalguideline.com/static/pdfs/NPUAP-EPUAP-PPPIA-CPG-2017.pdf.
    \587\ National Quality Forum (NQF) Patient Safety Standing 
Committee. Meeting Summary--Measure Evaluation In-person Meeting--
Spring 2019 Cycle. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=90662.
---------------------------------------------------------------------------

    Comment: Many commenters, including a few commenters who did not 
support future inclusion of the measure, expressed concern that the 
Hospital Harm-Pressure Injury eCQM does not adequately adjust for 
various risk factors that affect clinical risk associated with pressure 
injuries. Commenters recommended that CMS continue to evaluate the 
appropriateness of risk adjustment during measure reevaluation. A few 
commenters recommended including clinical factors such as proportion of 
ICU patients, frailty, nutrition, ECMO patients, and multiple injuries. 
Several commenters also noted that teaching hospitals and safety net 
hospitals care for patients that are more complex and more susceptible 
to pressure injuries, such that a lack of risk adjustment may 
disproportionately affect performance scores for those facilities. A 
commenter recommended CMS consider using site stratification to 
establish separate performance benchmarks across different hospitals 
settings to account for different patient populations. A commenter also 
recommend that CMS should account for factors beyond clinical factors, 
such as socioeconomic and sociodemographic complexities of vulnerable 
populations.
    Response: We appreciate the commenters' concerns. We note that in 
evaluating measures for adoption into the Hospital IQR Program, we 
consider if patients are at risk regardless of age or clinical factors 
and whether there is evidence that the risk of a harm can be largely 
ameliorated by best care practices regardless of patients' inherent 
risk profile. In this case, published clinical practice guidelines 
recommend preventive skin care, frequent repositioning, and nutritional 
supplementation, which all can ameliorate these 
risks.588 589 All patients require risk assessment and those 
at higher risk require individualized care plans specifically tailored 
to ameliorate those risks. Hence, adjusting away this variation may 
create an incentive for hospitals to defer implementation of best 
practices (for example, more frequent assessment, specialty beds and 
cushions) in higher risk patients. We will continue to assess 
commenters' concerns and whether risk adjustment should be implemented 
for the Hospital Harm--Pressure Injury eCQM.
---------------------------------------------------------------------------

    \588\ National Pressure Ulcer Advisory Panel, European Pressure 
Ulcer Advisory Panel and Pan Pacific Pressure Injury Alliance. 
Prevention and Treatment of Pressure Ulcers: Clinical Practice 
Guideline. Emily Haesler (Ed.). Cambridge Media: Osborne Park, 
Western Australia; 2014 Available at: http://www.internationalguideline.com/static/pdfs/NPUAP-EPUAP-PPPIA-CPG-2017.pdf.
    \589\ The Joint Commission. (2016). Preventing Pressure Injuries 
Quick Safety. Available at: https://www.jointcommission.org/issues/article.aspx?Article=n+OspqDzBBeZ/tRoyTzpsyZ4GrBDhJpdtlQvqSl5hsQ=.
---------------------------------------------------------------------------

    Comment: Several commenters recommended that CMS only include the 
Hospital Harm--Pressure Injury eCQM once it has been fully tested and 
received NQF endorsement. A commenter strongly encouraged CMS to assess 
the feasibility and validity of collecting the required data elements 
because testing occurred in only three EHRs. A few commenters suggested 
that the measure be reviewed by the NQF Disparities Committee.
    Response: We clarify that this measure was submitted to NQF for 
endorsement consideration during the Spring 2019 cycle and received a 
favorable recommendation by the Scientific Methods Panel and the 
Patient Safety Standing Committee for all endorsement criteria 
including importance, scientific acceptability of measurement 
properties (reliability and validity), feasibility, usability, and use. 
The remaining steps during endorsement consideration are generally a 
review of public comments and review by the Consensus Standards 
Approval

[[Page 42493]]

Committee (CSAC). However, there is also potential for review by the 
NQF Disparities Standing Committee (DSC) if NQF determines that to be 
appropriate.
    Comment: Many commenters expressed concern about variability in 
determining and documenting pressure injuries for the Hospital Harm--
Pressure Injury eCQM. Several commenters noted that it is unclear how 
this measure would affect clinician workflow and expressed concern 
about the subjective nature of determining stages of pressure injuries. 
Some commenters did not support the future inclusion of this measure 
and also noted that physician documentation of pressure injuries may 
differ from documentation by nursing staff and may vary between 
individual practitioners. Several commenters urged CMS to ensure 
consistent reporting by hospitals. A commenter expressed concern that 
because experts are continuously updating documentation requirements to 
meet prevention needs, adapting an inherently more static eCQM would 
not result in quality improvements. A few commenters also expressed 
concern that data elements for this measure are complex and may be 
burdensome to document consistently across providers and entities and 
requested adequate time to develop proper workflow before 
implementation.
    Response: We thank the commenters for their perspective. We agree 
that clinician variability in documenting stages of pressure injuries 
does present certain challenges, hence all new hospital-acquired 
pressure injuries stage 2-4, unstageable pressure injuries, and deep 
tissue pressure injury are included as a harm in the measure numerator. 
The measure, as specified, does not penalize hospitals based on 
variability in clinician staging of pressure injuries.\590\ For 
example, if a bedside nurse documents a stage 2 pressure injury and a 
wound care certified nurse practitioner later stages the pressure 
injury as a stage 3, this is counted as one numerator event. The 
information required for this eCQM is collected during routine patient 
assessment in accordance with national clinical guidelines. During 
measure development and testing, we noted that the eCQM requirement for 
documentation in discrete fields resulted in a need to adjust to 
clinical workflow in some hospitals, but this was offset by the benefit 
of capturing accurate information from which to drive quality 
improvement efforts. Documentation is an important component of the 
quality signal as hospitals cannot measure what is not documented.
---------------------------------------------------------------------------

    \590\ eCQI Resource Center. Pre-rulemaking Eligible Hospital/
Critical Access Hospital eCQMs. Hospital Harm--Pressure Injury. 
Available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
---------------------------------------------------------------------------

    Comment: A number of commenters sought clarification and guidance 
on elements of this measure. A few commenters requested standardization 
in the reporting of what is present on admission and the duration of 
time for the discovery of an injury before it is deemed hospital-
acquired. A commenter encouraged CMS to clearly define measure terms 
and publish measure specifications for this measure at least 18 months 
prior to including the measure in the program. A commenter requested 
clarification on how to document: (1) Multiple pressure injuries, and 
(2) pressure injuries that are charted at different stages during 
hospitalization.
    Response: We thank the commenters for their perspective. We note 
that clinical guidelines, TEP panelists, and previous public commenters 
supported the requirement for patients to be assessed for pressure 
injuries within 24 hours of hospital arrival.\591\ This measure assumes 
that any pressure injury not documented within 24 hours of arrival is 
hospital-acquired. We intend to provide implementation guidance to 
address the documentation of multiple pressure injuries for consistent 
implementation in the future if this measure is proposed and 
implemented.
---------------------------------------------------------------------------

    \591\ National Pressure Ulcer Advisory Panel, European Pressure 
Ulcer Advisory Panel and Pan Pacific Pressure Injury Alliance. 
Prevention and Treatment of Pressure Ulcers: Clinical Practice 
Guideline. Emily Haesler (Ed.). Cambridge Media: Osborne Park, 
Western Australia; 2014 Available at: http://www.internationalguideline.com/static/pdfs/NPUAP-EPUAP-PPPIA-CPG-2017.pdf.
---------------------------------------------------------------------------

    Comment: A few commenters expressed concern that the difference in 
Hospital Harm--Pressure Injury eCQM performance scores across hospitals 
during testing may not vary enough to ensure comparisons that are 
useful for distinguishing higher quality of care between hospitals..
    Response: We appreciate commenters' concerns. We understand the 
concern about the usability of this measure given the range of 
performance rates during testing. We note that the variation in 
hospital performance during testing is sufficiently wide and indicates 
ample room for improvement with this serious harm event. We believe 
that measuring the occurrence of a new pressure injury among patients 
who were hospitalized is a signal of quality of care provided in the 
hospital, and. that this measure will incentivize hospitals to support 
resources needed and to follow best practices to ameliorate the risk of 
new pressure injury. We will take commenters' concern under 
consideration as we continue to assess this measure's suitability for 
the Hospital IQR Program.
    We thank the commenters and we will consider their views as we 
develop future policy regarding the potential inclusion of the Hospital 
Harm--Pressure Injury eCQM in the Hospital IQR 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.\592\ 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.593 594 595
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    \592\ National Quality Forum, Quality Measure PC-02 (Cesarean 
Birth). Available at: https://www.qualityforum.org/QPS/MeasureDetails.aspx?standardID=291&print=1&entityTypeID=1.
    \593\ 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.
    \594\ 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.
    \595\ 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.\596\ C-sections accounted for 
about one-third of U.S. deliveries in 2016,\597\ and there is a 
considerable amount of variation in the rates based on U.S. region, 
State, and healthcare institution.\598\ U.S. practice

[[Page 42494]]

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.599 600 601 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.602 603 In this final rule, we include 
literature outlining maternal and neonatal C-section outcomes.
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    \596\ 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.
    \597\ 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.
    \598\ 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.
    \599\ 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).
    \600\ 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.
    \601\ 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.
    \602\ 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.
    \603\ 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).
---------------------------------------------------------------------------

    For maternal outcomes, C-sections have significantly higher 
prenatal and postpartum morbidity and mortality (9.2 percent) than 
vaginal births (8.6 percent).\604\ 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.\605\ Conversely, urinary 
incontinence and pelvic organ prolapse occur less frequently after C-
section than after vaginal delivery.\606\
---------------------------------------------------------------------------

    \604\ 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.
    \605\ 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.
    \606\ 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.
---------------------------------------------------------------------------

    In terms of neonatal outcomes, C-sections have higher respiratory 
morbidity (1 percent to 4 percent) than vaginal births (<1 
percent).\607\ Children delivered by C-section also have a higher risk 
of asthma and obesity.\608\ However, C-sections have better outcomes 
for shoulder dystocia (0 percent versus 1--2 percent).\609\ Again, 
cause (high risk fetuses more likely to be delivered by C-section) 
versus effect (surgery increases risk to the fetus) remains 
epidemiologically obscure. The medical indications for C-section 
necessarily entail broad obstetrician discretion because of the need 
to: (1) Balance any conflicting medical conditions of mother versus 
fetus; and (2) balance C-section against any other competing clinical 
considerations or external constraints (for example, availability of 
operating room, personnel, and/or blood).
---------------------------------------------------------------------------

    \607\ 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.
    \608\ 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.
    \609\ 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.
---------------------------------------------------------------------------

    Furthermore, C-sections receive higher reimbursement than vaginal 
deliveries (typically about 50 percent more). Patient cost sharing may 
differ, depending upon insurance coverage. Insurance experiments 
suggest that higher cost sharing causes patients to consume less health 
care,\610\ but that patients distinguish poorly between necessary and 
unnecessary services. The pervasive use of cesarean births carries 
economic impacts because C-sections are more expensive than vaginal 
deliveries and may be accompanied by adverse outcomes and complications 
which similarly have substantial cost implications.\611\
---------------------------------------------------------------------------

    \610\ Aron-Dine, A., Einav, L. & Finkelstein, A. (2013). The 
RAND Health Insurance Experiment, Three Decades Later. The Journal 
of Economic Perspectives, 27(1): 197-222.
    \611\ 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.
---------------------------------------------------------------------------

    For these reasons, we are considering including the electronic 
version of PC-02 (NQF #0471e) in the eCQM measure set to enable 
hospitals to track C-sections and reduce unnecessary instances of C-
sections.
(2) Overview of Measure
    The Joint Commission is the steward of the PC-02 measure, which 
assesses the rate of nulliparous women with a normal-term, singleton 
fetus in the vertex position (NTSV) undergoing C-section.\612\ 
Nulliparous women are those who have never given birth. They have a 
lower risk during vaginal birth than do women who have undergone a 
previous C-section.613 614 Full-term births have better 
outcomes than preterm births. Vertex presentations carry less risk than 
breach or transverse presentations.\615\ 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).\616\ 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.\617\
---------------------------------------------------------------------------

    \612\ National Quality Forum, Quality Measure PC-02 (Cesarean 
Birth). Available at: https://www.qualityforum.org/QPS/MeasureDetails.aspx?standardID=291&print=1&entityTypeID=1.
    \613\ 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.
    \614\ 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.
    \615\ 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.
    \616\ Mylonas, I. & Friese, K. (2015). Indications for and Risks 
of Elective Cesarean Section. Deutsches Arzteblatt International, 
112(29-30): 489-95.
    \617\ 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.
---------------------------------------------------------------------------

    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

[[Page 42495]]

chart-based form of this measure as a voluntary consensus standard 
since 2008.\618\ 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.'' \619\ Reducing the number of NSTV deliveries by C-
section would also reduce the rate of repeat cesarean births.\620\ 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.\621\ 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.\622\
---------------------------------------------------------------------------

    \618\ National Quality Forum, Quality Measure PC-02 (Cesarean 
Birth). Available at: https://www.qualityforum.org/QPS/MeasureDetails.aspx?standardID=291&print=1&entityTypeID=1.
    \619\ 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.
    \620\ 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.
    \621\ 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.
    \622\ 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.
---------------------------------------------------------------------------

    The PC-02 eCQM was included in a publicly available document 
entitled ``List of Measures Under Consideration for December 1, 2018.'' 
\623\ 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.\624\ 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.\625\ The MAP suggested feasibility testing, 
consultation with multiple stakeholders, and examination of unintended 
consequences.
---------------------------------------------------------------------------

    \623\ List of Measures Under Consideration for December 1, 2018. 
Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \624\ Measure Applications Partnership, December 2018 NQF MAP 
Hospital Workgroup Meeting Transcript. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \625\ 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.
---------------------------------------------------------------------------

(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.\626\
---------------------------------------------------------------------------

    \626\ 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.
---------------------------------------------------------------------------

    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.\627\ 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.
---------------------------------------------------------------------------

    \627\ List of Measures Under Consideration for December 1, 2018. 
Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
---------------------------------------------------------------------------

    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).\628\ The cohort for a region, 
hospital, and practitioner may differ from the national rate because of 
higher medical indications for C-section.
---------------------------------------------------------------------------

    \628\ Ibid.
---------------------------------------------------------------------------

(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.\629\
---------------------------------------------------------------------------

    \629\ 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.
---------------------------------------------------------------------------

    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.\630\ The Joint Commission removed all risk adjustments from 
this measure, effective with discharges beginning July 1, 2016.\631\
---------------------------------------------------------------------------

    \630\ 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.
    \631\ 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.
---------------------------------------------------------------------------

    In the proposed rule, we invited public comment on potential future 
inclusion of the Cesarean Birth (PC-02) eCQM (NQF #0471e) in the 
Hospital IQR Program. We specifically sought 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

[[Page 42496]]

we are also considering this measure for potential future inclusion in 
the Promoting Interoperability Program.
    Comment: Many commenters supported the adoption of the PC-02 
measure. Their reasons included decreased maternal and perinatal 
morbidity and mortality, reduced costs, personal use of the resulting 
information, minimal data collection burden, and increased pool of 
eCQMs from which hospitals can select for reporting.
    Response: We thank the commenters for their feedback.
    Comment: A few commenters supported the adoption of PC-02 and 
recommended that CMS accelerate the implementation date.
    Response: We thank the commenters for these suggestions and clarify 
that the PC-02 has not yet been proposed for adoption into the Hospital 
IQR Program. There is currently no planned implementation date. Any 
proposal to add PC-02 to the Hospital IQR Program would be made through 
future rulemaking
    Comment: A few commenters supported the adoption of PC-02 and 
recommended that CMS adopt additional birth-related quality measures 
because they believed such additional measures would help decrease 
maternal and perinatal morbidity and mortality.
    Response: We thank the commenters for these suggestions. We 
continue to monitor for measures that may be beneficial to adopt in the 
Hospital IQR Program.
    Comment: A few commenters recommended emulating The Joint 
Commission practice of disclosing data only for hospitals with C-
section rates that exceed a threshold (For example, 30 percent).
    Response: We appreciate the commenters' position. Dissemination of 
C-section rates permits hospitals to compare their performance to other 
institutions, not just to high-rate institutions. We intend to take the 
commenters' recommendations into consideration as we continue to 
evaluate PC-02 for adoption into the Hospital IQR Program.
    Comment: Several commenters did not support the measure because of 
their belief that the lack of risk adjustment would disadvantage 
referral centers for high risk deliveries and because it does not 
exclude eclampsia and pre-eclampsia patients.
    Response: We appreciate the commenters' concern. As previously 
noted, The Joint Commission removed the risk adjustments from this 
measure in 2016, after considering the recommendations of the Technical 
Advisory Panel.\632\ We will continue to monitor this issue and The 
Joint Commission's ongoing attention to it.
---------------------------------------------------------------------------

    \632\ 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.
---------------------------------------------------------------------------

    Comment: A number of commenters addressed the data elements 
necessary to calculate this measure. A few commenters stated that the 
necessary data elements are generally already captured by their EHRs, 
and a commenter noted they could calculate this measure. Meanwhile, 
other commenters questioned the availability of data elements for this 
measure from current EHRs. A few commenters supported feasibility 
testing before implementation of this measure.
    Response: We thank the commenters for their perspective. Any future 
adoption of this measure would be made through notice and comment 
rulemaking. Hospitals and EHRs would receive advance notice for 
application development and testing. We appreciate the recommendation 
for additional feasibility testing and will take it into consideration.
    Comment: A commenter could not find specifications for this 
measure.
    Response: This measure is stewarded by The Joint Commission and the 
NQF has published a detailed specification for calculating this 
measure.633 634
---------------------------------------------------------------------------

    \633\ https://www.qualityforum.org/QPS/MeasureDetails.aspx?standardID=291&print=1&entityTypeID=1.
    \634\ http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=69252.
---------------------------------------------------------------------------

    Comment: A few commenters noted the limited number of Medicare-
funded C-sections and expressed concern that the measure rate would be 
calculated using only Medicare-funded deliveries.
    Response: As previously discussed in more detail, the measure 
includes all births regardless of payer.
    Comment: A few commenters did not support the measure because it 
lacks current NQF endorsement.
    Response: As previously discussed further in the proposed rule and 
in this section, the chart-based version of this measure has NQF 
endorsement.\635\ The MAP Coordinating Committee encouraged The Joint 
Commission to resubmit the eCQM version of PC-02 to the NQF for 
endorsement with additional clarifying data.\636\ The MAP's Final 
Report of February 15, 2019, conditionally supports the PC-02 eCQM for 
rulemaking pending NQF evaluation and endorsement.\637\ We will 
continue to monitor the NQF endorsement process.
---------------------------------------------------------------------------

    \635\ National Quality Forum, Quality Measure PC-02 (Cesarean 
Birth). Available at: https://www.qualityforum.org/QPS/MeasureDetails.aspx?standardID=291&print=1&entityTypeID=1.
    \636\ Measure Applications Partnership, December 2018 NQF MAP 
Hospital Workgroup Meeting Transcript. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \637\ 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.
---------------------------------------------------------------------------

    We thank the commenters and we will consider their views as we 
develop future policy regarding the potential inclusion of the PC-02 
eCQM in the Hospital IQR 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

[[Page 42497]]

method).\638\ 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).\639\ 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).
---------------------------------------------------------------------------

    \638\ 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.
    \639\ 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.
---------------------------------------------------------------------------

    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.\640\ 
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.\641\
---------------------------------------------------------------------------

    \640\ 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.
    \641\ Available at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228776708906.
---------------------------------------------------------------------------

b. Additional Confidential Reporting of Measures Stratified Using Two 
Disparity Methods
    As previously noted, 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.\642\ 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 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,\643\ 
as well as the FY 2018 IPPS/LTCH PPS final rule (82 FR 38405 through 
38407).
---------------------------------------------------------------------------

    \642\ 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.
    \643\ 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.
---------------------------------------------------------------------------

    In April 2019, we continued to provide confidential reporting of 
disparity results for the Pneumonia Readmission measure in the 
confidential HSRs for claims-based measures that were 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-

[[Page 42498]]

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 as previously discussed, 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.\644\ 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 final 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.
---------------------------------------------------------------------------

    \644\ 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).
---------------------------------------------------------------------------

    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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19495), we 
invited 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 previously discussed. We refer readers to section 
IV.G.11. of the preamble of this final rule for a similar discussion 
under the Hospital Readmissions Reduction Program.
    Comment: Many commenters supported our plan to continue to provide 
hospitals with confidential hospital-specific reports on the Pneumonia 
Readmission measure using the two disparity methods and to expand that 
effort to include five additional readmission measures. Several of 
these commenters specifically believed that the effort would be useful 
to hospitals. Some commenters noted that it would help hospitals 
identify potential disparities in care, implement targeted improvement 
efforts, and reduce disparities in the quality of care for this 
vulnerable population. A commenter believed the information in the 
confidential HSRs will help hospitals and CMS make appropriate 
decisions as they consider disparities and risk-adjustment. A few 
commenters noted that dual eligible status is a reasonable social risk 
factor to begin using when assessing for disparities in care for 
quality measurement and value-based purchasing programs.
    Response: We thank commenters for their support for our efforts to 
provide data on disparities to hospitals. At present, dual eligible 
status is the only social risk factor used for assessing disparities in 
hospital outcomes. We continue to explore the use of additional social 
risk factors for the hospital disparity methods.
    Comment: Several commenters requested that CMS provide sufficient 
opportunity to review and understand the stratified performance and 
methodology used to develop these reports. They appreciated CMS' 
intention to remain engaged with stakeholders and to solicit feedback 
on hospital experiences and recommendations, including the format and 
usefulness of the reports. A commenter requested that CMS provide 
educational materials to help stakeholders interpret the information.
    Response: We intend to continue to provide educational resources 
for stakeholders as they continue to become familiar with the data 
provided from the two disparity methods provided in the confidential 
reports, including the measure methodology overview, fact

[[Page 42499]]

sheet, and frequently asked questions resources.\645\
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    \645\ QualityNet. Confidential Reporting Overview: Disparity 
Methods. Available at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228776708906.
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    Comment: A few commenters encouraged CMS to make the disparity 
methods' results in the confidential HSRs available to the public to 
foster transparency. A few commenters believed that any consideration 
of publicly reporting these data in the future should be proposed as 
part of notice and comment rulemaking. A commenter believed that 
stratified data should not be publicly reported but should be used by 
hospital staff for internal purposes only in identifying disparities in 
their patient populations. A commenter encouraged CMS to make the data 
public once hospitals are able to review and correct their data. A 
commenter opposed CMS privately sharing reports containing social risk 
factor data with hospitals because of a belief that the Hospital 
Compare website should inform the public on how hospitals differentiate 
in quality and safety and should be fully transparent to the public. 
Another commenter suggested that CMS be cautious in making these 
reports public as hospitals are just beginning to gain familiarity with 
them. A few commenters encouraged CMS to engage with stakeholders 
before any future public reporting. A few commenters believed it is 
important to ensure the reliability of the measure data using the two 
disparity methods before proposing to publicly display it and 
encouraged CMS to continue to engage with stakeholders to ensure that 
the data is accurate, fairly assesses hospitals, and is understandable 
to patients before it is made public. A commenter encouraged CMS to 
seek input from stakeholders on the usefulness of con[filig]dential 
HSRs before publicly reporting such data, speci[filig]cally, whether 
these reports support continuous quality improvement efforts.
    Response: The measure data used in the disparity methods are, 
except for dual eligibility status, the same as the data used in 
validated and NQF endorsed publicly reported measures. Dual eligibility 
data have been assessed separately for reliability and consistency of 
coding across states. In addition, we believe confidential reporting of 
the measure data using the two disparity methods will enable us to 
obtain hospital feedback on reporting options and provide additional 
certainty that the information is valid, reliable, and understandable 
prior to any future public display. It will also allow hospitals to 
better understand the complex data from the two disparity methods prior 
to any potential future public reporting.
    We have not yet determined future plans with respect to publicly 
reporting data using the two disparity methods.
    We intend to continue to engage with hospitals and relevant 
stakeholders about their experiences with and recommendations for the 
results from the two disparity methods and to ensure the accuracy and 
reliability of the results from the two disparity methods before 
proposing to publicly display them in the future. Any proposal to 
display measure data based on the two disparity methods on the Hospital 
Compare website would be made through future notice and comment 
rulemaking.
    Comment: A commenter believed that the differences in the results 
between the two disparity methods used in the confidential reports as 
compared to the stratified methodology used by the Hospital 
Readmissions Reduction Program could lead to confusion and may yield 
conflicting information that may not contribute to informing patients 
and the public. The commenter recommended that CMS study these 
differences, the potential impact on decision-making each may have, and 
what efforts should be made to harmonize these approaches before 
publicly reporting the data.
    Response: We appreciate commenter's feedback regarding the 
importance of harmonization with existing quality programs, such as the 
Hospital Readmissions Reduction Program. We believe these two disparity 
methods complement each other in that they use the same social risk 
factor and serve two complementary purposes. The Hospital Readmissions 
Reduction Program stratifies hospitals based on dual-eligible 
proportion and compares a hospital's excess readmissions to other 
hospitals in its peer group to assess a hospital's performance, as 
mandated by the 21st Century Cures Act,\646\ whereas the disparity 
methods discussed in this section highlight opportunities to close the 
gap in performance among different patient groups. We will continue to 
examine alignment, wherever appropriate, and intend to continue to 
engage with hospitals and relevant stakeholders about their experiences 
with the two disparity methods.
---------------------------------------------------------------------------

    \646\ 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).
---------------------------------------------------------------------------

    Comment: A commenter suggested that attribution model details for 
each measure be included within the respective programs' measures' 
technical specifications guides before publicly reporting data using 
the two disparity methods because they believed it is important to be 
clear about who is responsible for the reported outcomes and 
performance rates.
    Response: To minimize the possibility of confusion, the attribution 
used when applying the disparity methods mirror those used by the 
corresponding measure in the Hospital Readmissions Reduction Program. 
Attribution details and other technical specifications for the 
readmission measures are publicly available in Measure Methodology 
Reports on our QualityNet website.\647\
---------------------------------------------------------------------------

    \647\ https://www.qualitynet.org/dcs/ContentServer?cid=%201219069855841&pagename=QnetPublic%2FPage%2FQnetTier3&c=Page.
---------------------------------------------------------------------------

    Comment: A few commenters expressed concern with stratifying 
measure data based only on dual eligible status. A commenter noted that 
dual eligibility may be sensitive to differences in state coverage and 
benefit policies, and may not fully reflect the level of poverty in 
communities. A commenter believed that more information may be needed 
to specify the factors that result in higher spending and/or poorer 
health care outcomes. A few commenters recommended that CMS continue to 
consider and refine the social risk factors for stratification in 
confidential HSRs and consider additional factors that might affect 
outcomes or result in higher spending, including race, ethnicity, 
geographic area, sex, disability, education, and access to health care. 
A commenter expressed concern about the reliability of race and 
ethnicity data if CMS should consider stratifying hospital quality data 
by such factors and recommended that CMS develop a proposal to improve 
the collection of race and ethnicity data, or propose how to promote 
public transparency using data that are of mixed quality, before 
reporting such data publicly.
    Response: At present, dual eligibility is the only social risk 
factor used in the disparity methods. We have focused our initial 
efforts on providing disparity results based on dual eligible status 
because of strong evidence demonstrating worse health outcomes among 
dual eligible Medicare beneficiaries, and because reliable information 
is readily available in CMS administrative claims data. Because

[[Page 42500]]

dual eligible status is available in CMS administrative data, it also 
does not require any additional reporting by hospitals for the purposes 
of applying the disparity methods. With respect to commenter's concern 
about the differences in state policies, the disparity methods evaluate 
differences in hospital quality only for adults 65 years and above. 
Federal minimum standards for allowable income and assets exist for 
older adults, contributing to more uniformity in Medicaid eligibility 
status across states relative to other groups, although state-level 
differences in eligibility standards for optional coverage pathways and 
benefits are noted. Our internal analyses accounting for state Medicaid 
eligibility policies reveal no substantive differences in the disparity 
method results. We continue to examine the impact of state Medicaid 
policies on the disparity methods. We also continue to explore 
opportunities to account for additional social risk factors in the 
future, including evaluating new sources of social risk factor data and 
how to capture such data, engaging with stakeholders, and examining the 
availability and feasibly of accounting for social risk factors which 
might influence quality outcome measures.
    Comment: A commenter recommended that CMS consider data concerns 
related to the use of hospital quality data stratified by 
sociodemographic factors for hospital-acquired infection measures due 
to the concern that limited sample sizes at the individual hospital 
level could limit the statistical reliability of reporting quality 
measures by race or other sociodemographic characteristics.
    Response: We do not currently have plans to provide stratified data 
for hospital-acquired infection measures, but will take commenter's 
concerns into account as we continue to consider expanding our efforts 
to provide stratified data in confidential HSRs for other measures.
    Comment: Several commenters recommended that CMS adjust for social 
risk factors at the measure level for quality reporting and value-based 
programs, with some commenters expressing concern that hospitals that 
disproportionately care for vulnerable patient populations are 
disadvantaged or that customers could be misled with regard to the 
quality of care provided. However, another commenter expressed concern 
about incorporating social risk factors at the measure level because of 
a concern that it could mask the quality of care provided to people of 
different backgrounds. A commenter suggested providing both risk-
adjusted and unadjusted results to providers.
    Response: The primary objectives of the disparity methods are to 
assess and report disparities of care as reflected by differences in 
outcomes for patients with social risk factors, both within and across 
hospitals. It is important to note that adjusting for social risk 
factors within the quality measures would not serve this objective.
    Risk adjustment is one strategy which can be used to account for 
patient-level risk associated with social risk factors in the 
statistical model to incorporate such factors into calculating expected 
outcome rates for providers. Extensive previous work from ASPE, 
National Academies of Science, Engineering and, Medicine (NAM), and NQF 
have provided guiding recommendations towards the incorporation of risk 
adjustment for social risk factors at the patient 
level.648 649 650
---------------------------------------------------------------------------

    \648\ Department of Health and Human Services Office of the 
Assistant Secretary for Planning and Evaluation (ASPE), ``Accounting 
for Social Risk Factors in Medicare Payment.'' Jan. 2017. Available 
at: http://nationalacademies.org/hmd/Reports/2017/accounting-for-social-risk-factors-in-medicare-payment-5.aspx.
    \649\ Department of Health and Human Services Office of the 
Assistant Secretary for Planning and Evaluation (ASPE), ``Report to 
Congress: Social Risk Factors and Performance Under Medicare's 
Value-Based Purchasing Programs.'' December 2016. Available at: 
https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
    \650\ National Quality Forum (NQF). ``Evaluation of the NQF 
Trial Period for Risk Adjustment for Social Risk Factors.'' 
Available at: https://www.qualityforum.org/Publications/2017/07/Social_Risk_Trial_Final_Report.aspx.
---------------------------------------------------------------------------

    The disparity methods we have presented here serves a complementary 
purpose and is intended to allow examination of outcome differences 
between subgroups of patients. Providing information to providers on 
disparity results aims to support transparency around disparate health 
outcomes and incentivize improvements in care for patients with social 
risk factors. The goals of the methods presented are to demonstrate 
whether a gap in outcomes exists between patients with and without a 
given social risk factor (such as dual eligibility) within a single 
hospital, and to provide comparative information on hospital 
performance for patients with social risks across all hospitals.
    We also note, that applying the two disparity methods 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 an exemplary of health equity 
performance measure alignment such that data collection burden is 
minimized, measure impact is maximized, and peer group comparisons are 
enabled.\651\ We will continue to explore multiple options to account 
for the effect of social risk factors on quality measures and in 
quality programs.
---------------------------------------------------------------------------

    \651\ National Quality Forum. (2017). A Roadmap for Promoting 
Health Equity and Eliminating Disparities: The Four I's for Health 
Equity.
---------------------------------------------------------------------------

    Comment: A few commenters recommended that CMS improve data capture 
to better allow for risk adjustment related to social determinants of 
health, including collection of such data, including non-clinical data, 
via EHRs.
    Response: We continue to explore opportunities to account for 
additional social risk factors in the future, including evaluating new 
sources of social risk factor data and how to capture such data, 
engaging with stakeholders, and examining the availability and feasibly 
of accounting for social risk factors which might influence quality 
outcome measures.
    We thank the commenters for their feedback and suggestions. We will 
take them into account and consider commenters' views as we develop 
future policies regarding the accounting for social risk factors and 
reporting of disparity data.
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 previous description. 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,

[[Page 42501]]

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). In the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19496), we did not propose any changes to 
these procedural requirements.
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. In the FY 2020 IPPS/LTCH PPS proposed 
rule (84 FR 19496), we did not propose any changes to the data 
submission requirements for chart-abstracted measures.
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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19496 through 
19497), we proposed 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 in this final rule.
(2) Reporting and Submission Requirements for eCQMs for the CY 2020 
Reporting Period/FY 2022 Payment Determination
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19496), for the 
CY 2020 reporting period/FY 2022 payment determination, we proposed 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 refer readers to section VIII.D.6.d.(1). of the preamble of this 
final rule where we discuss a similar proposal in the Promoting 
Interoperability Programs for the CY 2020 reporting period.
    We note that the commenters who commented on the proposal for the 
CY 2020 reporting period uniformly also provided similar comments for 
the CY 2021 reporting period. We therefore refer readers to section 
VIII.A.10.D.(3). of the preamble of this final rule, where we provide a 
summary of the comments and responses that apply to the proposals for 
both the CY 2020 and CY 2021 reporting periods.
(3) Reporting and Submission Requirements for eCQMs for the CY 2021 
Reporting Period/FY 2023 Payment Determination
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19496 through 
19497), for the CY 2021 reporting period/FY 2023 payment determination, 
we proposed 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 previously discussed. We refer 
readers to section VIII.D.6.d.(1). of the preamble of this final rule 
where we discuss a similar proposal in the Medicare Promoting 
Interoperability Program.
    We note that the following comment and response summaries reflect 
the comments received on proposals for both the CY 2020 reporting 
period and the CY 2021 reporting period.
    Comment: Many commenters supported our proposals to extend the 
current eCQM reporting and submission

[[Page 42502]]

requirements, such that hospitals would be required to report one, 
self-selected calendar quarter of data for four self-selected eCQMs for 
the CY 2020 and CY 2021 reporting periods. Several commenters 
appreciated and supported the consistency of the proposals because they 
believe it will allow vendors and hospitals more time to acclimate to 
electronic reporting, adopt technology, implement and test measures, 
and prepare for new measures. One commenter supported the proposal 
because of their belief that it reduces regulatory burden and gives 
hospitals the flexibility to focus on measures that are most meaningful 
to their quality improvement priorities. One commenter specifically 
noted their support for the proposed CY 2021 eCQM reporting and 
submission requirements, but was silent as to the proposal for CY 2020.
    Response: We appreciate the commenters' support.
    Comment: A few commenters recommended that we also continue these 
same reporting and submission requirements for future years. A few 
commenters suggested that the requirement to report only one quarter of 
data be made permanent to allow vendors and hospitals to plan into the 
future.
    Response: We thank the commenters for their recommendations. 
However, we reiterate our previously stated goal of incrementally 
increasing the use of EHR data for quality measurement. We believe 
taking an incremental approach to increasing electronic reporting will 
allow hospitals and vendors to acclimate to electronic reporting. In 
keeping with that goal, we are finalizing requirements for the CY 2022 
reporting period in this final rule such that hospitals will be 
required to submit one, self-selected calendar quarter of data for: (1) 
Three self-selected eCQMs; and (2) the finalized Safe Use of Opioids--
Concurrent Prescribing eCQM with a clarification and update, for a 
total of four eCQMs. We refer readers to section XIII.A.10.d.(4). of 
the preamble of this final rule, for a discussion of eCQM reporting and 
submission requirements for the CY 2022 reporting period/FY 2024 
payment determination. Any eCQM reporting and submission requirements 
beyond that time will be addressed in future notice and comment 
rulemaking.
    Comment: A few commenters urged us to consider other approaches to 
support the advancement of eCQM reporting. A commenter encouraged us to 
allow hospitals to voluntarily substitute eCQM versions for the chart-
abstracted versions of the same measures and suggested that we could 
establish a bonus structure for hospitals that were willing to progress 
beyond the standard reporting requirements. Another commenter 
recommended that we require thresholds be met for the eCQMs on which 
hospitals chose to report, that we allow for comparisons in 
performance, and that we penalize facilities for poor performance.
    Response: We appreciate the commenters' feedback and 
recommendations, and will take these recommendations into consideration 
as we assess how to advance eCQM reporting in the Hospital IQR Program. 
Increasing the use of EHR data is a goal of the Hospital IQR Program. 
We remind readers, however, that the Hospital IQR Program is a pay-for-
reporting program rather than a pay-for-performance program, meaning 
the impact on payment is based on whether a hospital complies with the 
reporting requirements of the program, rather than how well a hospital 
performs on individual measures. At this time, the Hospital IQR Program 
does not publicly report eCQM data and any future public reporting of 
eCQM data would be established through notice and comment rulemaking.
    Regarding the commenter's recommendation to allow voluntary 
substitution of eCQM versions for the chart-abstracted versions of the 
same measures, we note that following the removal of several chart-
abstracted clinical process of care measures in the FY 2019 IPPS/LTCH 
PPS final rule (83 FR 41562 through 41567), the only chart-abstracted 
measures that remain in the Hospital IQR Program are the PC-01 and 
Sepsis measures. The eCQM version of the PC-01 measure was removed in 
the FY 2019 IPPS/LTCH PPS final rule (83 FR 41569) because the measure 
data are already collected and publicly reported in the chart-
abstracted form of this measure in the Hospital IQR Program. We also 
note that it would not be feasible for hospitals to submit eCQM data 
for the Sepsis measure as that measure is not currently electronically 
specified and remains a chart-abstracted measure in the Hospital IQR 
Program at this time.
    Comment: A commenter expressed concerns about our self-selection 
policies and recommended that we mandate the specific eCQMs for 
hospitals to report and that we require hospitals to submit a year's 
worth of data. The commenter noted that when the reporting period is 
limited to one quarter of data, hospitals can select the quarter in 
which their rates are the best and expressed concern that rural 
hospitals have trouble meeting the minimum reporting threshold when the 
measurement period is one quarter. Another commenter suggested that if 
we begin to require a full year of reporting for eCQMs, that we should 
align the reporting period with the calendar year.
    Response: We appreciate the commenters' feedback and 
recommendations, and will take these recommendations into consideration 
as we assess how to advance eCQM reporting in the Hospital IQR Program. 
Regarding the commenter's concerns about allowing self-selection of 
eCQMs and recommendation to mandate specific eCQMs, as further 
discussed in this final rule, we are finalizing requirements for the CY 
2022 reporting period such that hospitals will be required to submit 
one, self-selected calendar quarter of data for: (1) The finalized Safe 
Use of Opioids--Concurrent Prescribing eCQM with a clarification and 
update; and (2) three self-selected eCQMs, for a total of four eCQMs, 
as part of our goal to incrementally increase eCQM reporting 
requirements as hospitals continue to gain experience with eCQMs. Any 
additional changes to our eCQM reporting requirements would be done 
through notice and comment rulemaking. We will take under consideration 
for future reporting policies the commenter's concerns about the 
ability of rural hospitals to meet the minimum reporting threshold 
based on one quarter of data, and in the meantime, note our zero 
denominator declaration and case threshold exemption policies in place 
for eCQM reporting.\652\ Finally, while we are not yet requiring the 
reporting of a full year of data for eCQMs, we will take the 
commenter's suggestion to align with the calendar year into 
consideration for the future.
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    \652\ FY 2018 IPPS/LTCH PPS final rule (82 FR 38387).
---------------------------------------------------------------------------

    Comment: A few commenters urged us not to publicly report eCQM data 
for some time. One commenter recommended that CMS develop a feedback 
loop to monitor for unintended consequences for all quality measures 
before publicly reporting eCQM data.
    Response: At this time, the Hospital IQR Program does not publicly 
report eCQM data and any future public reporting of eCQM data would be 
established through notice and comment rulemaking. There are a number 
of channels for stakeholders to provide feedback on an eCQM throughout 
the eCQM lifecycle.\653\ The eCQI Resource Center provides

[[Page 42503]]

numerous current resources to support electronic clinical quality 
improvement.\654\ Within the eCQI Resource Center, the Collaborative 
Measure Development (CMD) Workspace \655\ brings together a set of 
interconnected resources, tools, and processes to promote clarity, 
transparency, and better interaction across stakeholder communities 
that develop, implement, and report eCQMs. During the measure 
development process, stakeholders may also provide feedback through 
public comment periods,\656\ and ONC JIRA's issue tracker for measures 
under development.\657\ We further note that the value sets for both 
proposed eCQMs and eCQMs that have been finalized and adopted through 
rulemaking can be found at the Value Set Authority Center's 
website.\658\
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    \653\ CMS, How CMS Engages You. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/How-CMS-Engages-You.html.
    \654\ https://ecqi.healthit.gov/.
    \655\ https://ecqi.healthit.gov/collaborative-measure-development.
    \656\ CMS, Public Comment Page. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/PC-Currently-Accepting-Comments.html.
    \657\ Available at: https://oncprojectracking.healthit.gov/support/secure/BrowseProjects.jspa?selectedCategory=all&selectedProjectType=all.
    \658\ Value Set Authority Center. Available at: https://vsac.nlm.nih.gov/welcome.
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    After consideration of the public comments we received, we are 
finalizing our proposals as proposed for both the CY 2020 reporting 
period/FY 2022 payment determination and the CY 2021 reporting period/
FY 2023 payment determination: 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.
(4) Reporting and Submission Requirements for eCQMs for the CY 2022 
Reporting Period/FY 2024 Payment Determination
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19497), for the 
CY 2022 reporting period/FY 2024 payment determination, we proposed to 
modify 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, 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 was made in conjunction with our proposal discussed 
in section VIII.A.5.a.(1). of the preamble of this final rule, in which 
we proposed to adopt the Safe Use of Opioids--Concurrent Prescribing 
eCQM 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 final 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 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 is more closely 
related to combating the current opioid epidemic, as previously 
discussed and in section VIII.A.5.a. of the preamble of this final 
rule, than the Hospital Harm--Opioid-Related Adverse Events eCQM, which 
is focused on improved monitoring of patients who receive opioids 
during hospitalization.
    In the proposed rule, we proposed that if our proposal to adopt the 
Safe Use of Opioids--Concurrent Prescribing eCQM beginning with the CY 
2021 reporting period/FY 2023 payment determination were finalized, 
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.\659\
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    \659\ 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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    In the proposed rule, we noted that this proposal was contingent on 
finalization of our proposal discussed in section VIII.A.5.a.(1). of 
the preamble of this final rule to adopt the Safe Use of Opioids--
Concurrent Prescribing eCQM. We also refer readers to section 
VIII.D.6.d.(2). of the preamble of this final rule for a discussion of 
a similar proposal by the Medicare Promoting Interoperability Program.
    Comment: Many commenters supported CMS' proposal for CY 2022 
reporting period/FY 2024 payment determination to modify 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, for a total of four eCQMs. Most of these 
commenters focused their comments on the proposal to require reporting 
of the Safe Use of Opioids--Concurrent Prescribing measure. One 
commenter specifically expressed appreciation for the continued 
flexibility of the eCQM reporting requirements. Another commenter 
appreciated that our proposal would standardize the measures required 
for reporting. One commenter expressed their belief that the 
significance of the opioid crisis justifies requiring reporting on the 
Safe Use of Opioids--Concurrent Prescribing eCQM. Another commenter 
requested that we consider approaches to require the reporting of the 
Safe Use of Opioids--Concurrent Prescribing eCQM earlier than the CY 
2022 reporting period to capture a greater volume of data.
    Response: We note that the proposal to require reporting of the 
Safe Use of Opioids--Concurrent Prescribing eCQM for the CY 2022 
reporting period was timed to prevent increasing the complexity of the 
eCQM reporting requirements too quickly, while also taking into 
consideration that this measure seeks to combat the negative impacts of 
the opioid crisis and has the potential to reduce preventable mortality 
and costs associated with other adverse events related to opioid use. 
Regarding the commenter recommending to require reporting of the Safe 
Use of Opioids--Concurrent Prescribing eCQM earlier than CY 2022, we 
believe that adopting the Safe Use of Opioids--Concurrent Prescribing 
eCQM beginning with the CY 2021 reporting

[[Page 42504]]

period is appropriate to give hospitals time to implement the measure 
and submit data on the measure as one of four eCQMs for the CY 2021 
reporting period/FY 2023 payment determination should they wish to 
before it is required as one of the four eCQMs for the CY 2022 
reporting period/FY 2024 payment determination. We strongly encourage 
hospitals to report the Safe Use of Opioids--Concurrent Prescribing 
eCQM beginning with the CY 2021 reporting period as one of their eCQMs.
    Comment: A few commenters supported required reporting of the Safe 
Use of Opioids--Concurrent Prescribing eCQM, but suggested that a few 
exclusions be added to the measure and potentially delay required 
reporting by 1 year.
    Response: We refer readers to section XIII.A.5.a.(1). of the 
preamble of this final rule where we discuss finalizing the adoption of 
the Safe Use of Opioids--Concurrent Prescribing eCQM with a 
clarification and update, including a discussion of the measure 
exclusions as well as exclusions that were considered during the 
measure development process but not incorporated into the 
specifications. As discussed in that section, we are finalizing our 
proposal to adopt the Safe Use of Opioids--Concurrent Prescribing eCQM 
with a clarification and update beginning with the CY 2021 reporting 
period/FY 2023 payment determination. We believe requiring reporting on 
the measure beginning with the CY 2022 reporting period is an 
appropriate timeframe, as it will enable hospitals sufficient time to 
work through implementation, testing, and reporting challenges. In 
addition, hospitals may submit data on the measure as one of four eCQMs 
for the CY 2021 reporting period/FY 2023 payment determination should 
they wish to before the measure is required as one of four eCQMs for 
the CY 2022 reporting period/FY 2024 payment determination.
    Comment: A commenter supported required reporting of the Safe Use 
of Opioids--Concurrent Prescribing eCQM, but suggested that we not 
publicly report data until further testing has demonstrated the 
measure's validity and reliability.
    Response: We disagree that the Safe Use of Opioids--Concurrent 
Prescribing eCQM has not been demonstrated to be valid and reliable. We 
refer readers to section XIII.A.5.a.(1). of the preamble of this final 
rule for a discussion of how this measure was tested for feasibility, 
reliability, and validity and received NQF endorsement. We further note 
that eCQM measure data are currently not publicly reported. We will 
provide confidential feedback reports to hospitals reporting this 
measure in advance of any public reporting. We believe that these 
advance reports will provide hospitals with additional time and 
information to ask CMS questions and learn more about the measure 
before public reporting. Any future plans for publicly reporting eCQM 
data would be conducted through rulemaking.
    Comment: A commenter stated their belief that it would be premature 
to require electronic reporting before all measures are fully 
electronically specified and field tested and also expressed concern 
about the extensive impact that eCQM adoption has on hospital 
resources.
    Response: Regarding commenters' concerns about the level of testing 
that eCQMs have undertaken, we note that eCQMs, like all other types of 
quality measures in the Hospital IQR Program, undergo rigorous testing 
during the measure development process for feasibility, validity, and 
reliability. We refer readers to the eCQI Resource Center for the full 
measure specifications of the eCQMs used in the Hospital IQR 
Program.\660\ We further note that reporting eCQMs has been an existing 
requirement for the Hospital IQR Program for several years,\661\ and is 
part of our ongoing commitment to promote efficiency through health 
information technology while also promoting high quality costs and 
ultimately decreasing reporting burden to providers. Over the past few 
years, hospitals have continued to build and refine their EHR systems 
and gain familiarity with reporting eCQM data, resulting in more 
accurate data submissions with fewer errors. We recognize that adopting 
new eCQMs can impact a hospital's resource use, but we believe the 
long-term benefits associated with electronic data capture outweigh 
these costs and further advances our goal of incrementally increasing 
the use of EHR data for quality measurement and improvement.
---------------------------------------------------------------------------

    \660\ Available at: https://ecqi.healthit.gov/ecqms.
    \661\ FY 2016 IPPS/LTCH PPS final rule (80 FR 49693 through 
49698).
---------------------------------------------------------------------------

    Comment: A few commenters addressed the availability of measure 
specifications, with one noting that the proposal allowed for 
sufficient time for clarifying the measure specifications, and a few 
commenters requesting that the specifications be made available as soon 
as possible or at least 18 months in advance of the CY 2022 reporting 
period. A few commenters noted that accurate eCQM reporting depends on 
using the correct version of the specifications, which they believe is 
in control of vendors and not hospitals. A commenter conditioned their 
support on their vendor's ability to build out new eCQMs.
    Response: We note that measure specifications for eCQMs can be 
found on the eCQI Resource Center,\662\ which provides a centralized 
location for news, information, tools, and standards related to 
eCQMs.\663\ We understand that many hospitals work with vendors to 
implement measure specifications in their EHRs, and we believe that the 
proposed timeline for required reporting of the Safe Use of Opioids--
Concurrent Prescribing eCQM--the CY 2022 reporting period--will allow 
hospitals and vendors time to work through implementation, testing, and 
reporting challenges before reporting on the measure to CMS is 
required.
---------------------------------------------------------------------------

    \662\ We refer readers to the eCQI Resource Center's Pre-
Rulemaking Eligible Hospital/Critical Access Hospital eCQMs website, 
available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
    \663\ https://ecqi.healthit.gov/content/about-ecqi.
---------------------------------------------------------------------------

    Comment: A number of commenters did not support our proposal for 
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: (1) Three self- selected eCQMs; and (2) the proposed Safe Use of 
Opioids--Concurrent Prescribing eCQM, for a total of four eCQMs. Many 
commenters urged us not to finalize the proposed required reporting of 
the Safe Use of Opioids--Concurrent Prescribing eCQM, and suggested 
that we retain the current reporting requirements into the future. Some 
commenters suggested a delay in required reporting of the Safe Use of 
Opioids--Concurrent Prescribing eCQM for a year or two, while others 
suggested that we give hospitals and vendors more time, including a 
period of voluntary reporting, before requiring reporting on this 
measure. These commenters generally expressed concern about ensuring 
hospitals and vendors have more time to implement and refine reporting 
on the measure. Some commenters encouraged us to engage in outreach 
activities with affected stakeholders.
    Response: We acknowledge the commenters' concerns. However, we 
believe it is important to our goal of incrementally increasing the use 
of EHR data for quality measurement to require the reporting of the 
Safe Use of Opioids--Concurrent Prescribing eCQM with a clarification 
and update beginning with the CY 2022 reporting

[[Page 42505]]

period/FY 2024 payment determination. While we understand that 
implementing a new eCQM demands hospital and vendor resources, we also 
believe that the Safe Use of Opioids--Concurrent Prescribing eCQM could 
play an important role in improving awareness of the risk of concurrent 
prescribing and could help address the negative impacts of the opioid 
epidemic. Regarding commenters' requests for a voluntary reporting 
period, we note that hospitals may submit data on the measure as one of 
four eCQMs for the CY 2021 reporting period/FY 2023 payment 
determination should they wish to before the measure is required as one 
of four eCQMs for the CY 2022 reporting period/FY 2024 payment 
determination.
    As discussed in section XIII.A.5.a.(1). of the preamble of this 
final rule, currently no measure exists to assess nationwide rates of 
the concurrent prescribing of opioids and benzodiazepines at the 
hospital level. We believe that requiring reporting on this measure 
beginning with the CY 2022 reporting period will advance our efforts to 
combat the opioid crisis by enhancing the information available to 
providers in this area of high-risk prescribing.
    We will continue engaging with stakeholders through education and 
outreach opportunities, including webinars, listserves, and help desk 
questions, as they implement this new eCQM. In addition, we note that 
there are other resources available to hospitals and vendors during the 
implementation process, including: (1) eCQI Resource Center's 
Collaborative Measure Development (CMD) Workspace, which assists 
clinicians, eCQM developers, implementers, and submitters during the 
entire eCQM lifecycle, from initial measure concept through 
development, implementation, and reporting to CMS; \664\ and (2) ONC 
JIRA's eCQM issue tracker for eCQM implementation and maintenance.\665\
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    \664\ Available at: https://ecqi.healthit.gov/.
    \665\ Available at: https://oncprojectracking.healthit.gov/support/secure/BrowseProjects.jspa?selectedCategory=all&selectedProjectType=all.
---------------------------------------------------------------------------

    Comment: A commenter opposed the proposal to require the Safe Use 
of Opioids--Concurrent Prescribing eCQM because they believe that 
hospitals should retain the flexibility to choose to report on those 
eCQMs most applicable to their quality improvement priorities.
    Response: We appreciate the commenter's feedback, however, we 
believe that allowing hospitals to still self-select three eCQMs for 
the CY 2022 reporting period provides enough flexibility to report on 
eCQMs applicable to their quality improvement priorities, while also 
reporting on a measure that may help address the opioid epidemic. As 
discussed in section XIII.A.5.a.(1). of the preamble of this final 
rule, currently no measure exists to assess nationwide rates of the 
concurrent prescribing of opioids and benzodiazepines at the hospital 
level. We believe that requiring reporting on this measure beginning 
with the CY 2022 reporting period will advance our efforts to combat 
the opioid crisis by enhancing the information available to providers 
in this area of high-risk prescribing.
    Furthermore, we 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. Hospitals have had several 
years to report data electronically for both the Hospital IQR Program 
and the Promoting Interoperability Programs, and we have maintained the 
same eCQM reporting and submission requirements for several years in 
order to enable hospitals enough time to update systems and workflows 
in the least burdensome manner possible. Based on internal monitoring 
of eCQM submissions, approximately 97 percent of eligible hospitals 
successfully submitted eCQMs for CY 2018. Therefore, we believe that 
hospitals will be ready for the required reporting of the Safe Use of 
Opioids--Concurrent Prescribing eCQM beginning with the CY 2022 
reporting period/FY 2024 payment determination.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed to require hospitals to report one, 
self-selected calendar quarter of data for: (1) Three self-selected 
eCQMs; and (2) the finalized Safe Use of Opioids--Concurrent 
Prescribing eCQM with a clarification and update, for a total of four 
eCQMs, for the CY 2022 reporting period/FY 2024 payment determination.
(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. In the FY 2020 IPPS/LTCH PPS 
proposed rule (84 FR 19497), we did not propose any changes to this 
policy.
(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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19497 through 
19498), we proposed 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,\666\ 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)).
---------------------------------------------------------------------------

    \666\ 45 CFR 170.102.
---------------------------------------------------------------------------

    ONC's Health IT Certification Program is ``agnostic'' to settings 
and programs, but can support many different use cases and needs.\667\ 
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.
---------------------------------------------------------------------------

    \667\ 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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[[Page 42506]]

    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.\668\ 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 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.
---------------------------------------------------------------------------

    \668\ 82 FR 38391 through 38393; 83 FR 41672.
---------------------------------------------------------------------------

    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 final rule for discussion of a similar proposal for the Promoting 
Interoperability Program.
    Comment: Several commenters supported our proposal to require that 
EHR technology used for eCQM reporting be certified to all eCQMs. A 
number of those commenters expressed appreciation for this policy and 
noted that it helps preserve hospitals' ability to choose eCQMs which 
reflect their patient populations and quality improvement goals.
    Response: We thank the commenters for their support of our 
proposal.
    Comment: A few commenters requested clarification as to whether we 
are also requiring health IT developers/vendors to certify their EHR 
products to the Hybrid HWR measure, such as for eCQMs.
    Response: The Hybrid HWR measure only uses core clinical data 
elements and linking variables from EHRs. The 13 core clinical data 
elements consist of data captured during a patient evaluation or 
laboratory test and are included in a structured manner in the 2015 
Edition Base EHR, such as Heart Rate, Systolic Blood Pressure and 
Weight. The six linking variables consist of data included in a 
structured manner in the 2015 Edition Base EHR, such as Date of Birth; 
Sex; Admission Date. The 2015 Edition Base EHR definition includes the 
clinical quality measure certification criteria to record and export 
EHR data (45 CFR 170.315(c)(1)). It requires that the EHRs be able to 
record all of the data necessary to calculate each clinical quality 
measure, enabling users to export a data file that is formatted in 
accordance with the QRDA-I standard and including all of the data 
captured for each and every clinical quality measure to which 
technology was certified. Under the 2015 Edition Base EHR definition, a 
user must be able to export the data file at any time the user chooses 
and without subsequent developer assistance to operate. We therefore 
believe that the technological requirements associated with reporting 
the Hybrid HWR measure are sufficiently addressed. This approach 
balances the benefits of certification without increasing burden of 
additional certification requirements that are not as necessary for 
this measure, such as the criteria to import and calculate (45 CFR 
170.315(c)(2)).
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed to require 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.
(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). In 
the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19498), we did not 
propose any changes to these requirements for eCQMs.
(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. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19498), we did not propose any changes to the eCQM submission 
deadlines.
e. Data Submission and Reporting Requirements for Hybrid Measures
(1) Background
    In section VIII.A.5.b. of the preamble of this final rule, we 
discuss our proposal 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

[[Page 42507]]

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 150 \669\ hospitals submitted 
data. In the proposed rule, we stated that we expected that hospitals 
that voluntarily submitted data for this measure would receive 
confidential hospital-specific reports detailing submission results 
from the reporting period in early summer of 2019. In July 2019, we 
provided confidential hospital-specific reports to those hospitals that 
participated in the 2018 Voluntary Reporting Period via the QualityNet 
Secure Portal.
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    \669\ We have updated the number of hospitals that submitted 
Hybrid HWR measure data for the 2018 Voluntary Reporting Period 
since the publication of the proposed rule (from approximately 80 to 
150 hospitals).
---------------------------------------------------------------------------

(2) Certification and File Format Requirements
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19498 through 
19499), we proposed 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 CEHRT when reporting eCQMs beginning with the CY 2019 
reporting period/FY 2021 payment determination.
    In addition, we proposed that the core clinical data elements and 
linking variables identified in hybrid measure specifications, for 
example as discussed in section VIII.A.5.b. of the preamble of this 
final 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 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 
(HQR) and the 2018 CMS QRDA I Schematrons and Sample Files for HQR, 
available on the eCQI Resource Center website.\670\ In the proposed 
rule, we stated that if our proposal to adopt the Hybrid HWR measure is 
finalized, updated implementation guidance, schematrons, and sample 
files would become available on the eCQI Resource Center website.
---------------------------------------------------------------------------

    \670\ 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, 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.
    Comment: A commenter supported the proposal to require that 
hospitals use EHR technology certified to the 2015 Edition to submit 
data on the Hybrid HWR measure and expressed appreciation for our 
efforts to align reporting standards.
    Response: We thank the commenter for their support.
    Comment: A commenter supported the proposal that core clinical data 
elements and linking variables identified in hybrid measure 
specifications be submitted using the QRDA I file format.
    Response: We thank the commenter for their support.
    After consideration of the public comments we received, we are 
finalizing our proposals as proposed to require that hospitals use EHR 
technology certified to the 2015 Edition to submit data on the Hybrid 
HWR measure, and that the core clinical data elements and linking 
variables identified in the hybrid measure specifications be submitted 
using the QRDA I file format.
(3) Additional Submission Requirements
    In the proposed rule (84 FR 19499), we proposed 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 the proposed rule, we proposed 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.
    Comment: A few commenters supported our proposal 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

[[Page 42508]]

exemptions and expressed appreciation for the consistency across 
requirements. One commenter sought clarification about the submission 
process for zero denominator declarations and case threshold 
exemptions.
    Response: As stated in the proposed rule (84 FR 19499) and 
previously in this final rule, hospitals will be able to submit zero 
denominator declarations and case threshold exemptions through the 
QualityNet Secure Portal. Use of the zero denominator declarations and 
case threshold exemptions will not be needed until reporting on the 
Hybrid HWR measure is mandatory, which begins with the reporting period 
which runs from July 1, 2023 through June 30, 2024, impacting the FY 
2026 payment determination. We anticipate that the process for 
submitting zero denominator declarations and case threshold exemptions 
for hybrid measures would be very similar to the process for eCQMs (82 
FR 38387).
    After consideration of the public comments we received, we are 
finalizing our proposals as proposed 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; and apply similar zero denominator 
declaration and case threshold exemption policies to hybrid measure 
reporting as we allow for eCQM reporting.
(4) Submission Deadlines for Hybrid Measures
    In the proposed rule, we proposed that hospitals must submit the 
core clinical data elements and linking variables within 3 months 
following the end of the applicable reporting period (submissions would 
be required no later than the first business day 3 months following the 
end of the reporting period) for hybrid measures in the Hospital IQR 
Program.
    As discussed earlier in this final rule, we proposed 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 
3 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. In 
the proposed rule, we stated that 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.
    Comment: A commenter supported our proposal to require that 
hospitals submit core clinical data elements and linking variables 
within 3 months following the end of the applicable reporting period.
    Response: We thank the commenter for their support.
    Comment: A few commenters suggested that submission of the Hybrid 
HWR measure should be counted as reporting on one of the four eCQMs 
required for the Hospital IQR Program.
    Response: Since the Hybrid HWR measure is being adopted to replace 
the HWR claims-only measure, the Hybrid HWR measure will necessarily 
require different reporting and submission requirements compared to the 
current eCQM reporting policy. We refer readers to section VIII.A.5.b. 
of the preamble of this final rule for a detailed discussion in which 
we finalize our proposal 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.
    Comment: A few commenters recommended that a single submission of 
the Hybrid HWR measure should count toward both the Hospital IQR 
Program and the Promoting Interoperability Program, in keeping with the 
single submission of eCQM data for both programs.
    Response: The Promoting Interoperability Program for eligible 
hospitals and critical access hospitals has not yet adopted the Hybrid 
HWR measure but sought comment on potential future adoption in the 
proposed rule. We refer readers to section VIII.D.6.c. of the preamble 
of this final rule for a discussion of the Hybrid HWR measure and the 
Promoting Interoperability Program. We will take commenters' 
suggestions into consideration for future rulemaking.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed to require that hospitals submit 
core clinical data elements and linking variables within 3 months 
following the end of the applicable reporting period (submissions would 
be required no later than the first business day 3 months following the 
end of the reporting period) for hybrid measures in the Hospital IQR 
Program.
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. In the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19499), we did not propose any changes to our 
sampling and case threshold policies.
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. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19499), we 
did not propose any changes to the HCAHPS Survey or its administration 
and submission requirements.
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

[[Page 42509]]

are posted on the QualityNet website at: http://www.QualityNet.org/. In 
the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19499), we did not 
propose any changes to those requirements.
    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 IV.H.5.e. of the preamble 
of this final 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), the FY 2018 IPPS/LTCH PPS final rule (82 FR 38398 
through 38403), and the FY 2019 IPPS/LTCH PPS final rule (83 FR 41607 
through 41608) for detailed information on chart-abstracted and eCQM 
validation processes and previous updates to these processes for the 
Hospital IQR Program.\671\
---------------------------------------------------------------------------

    \671\ We note that in the FY 2020 IPPS/LTCH PPS proposed rule, 
we inadvertently omitted reference to the FY 2019 IPPS/LTCH PPS 
final rule. We have added the citation to the language above.
---------------------------------------------------------------------------

    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19500), we did 
not propose any changes to the existing processes for validation of 
chart-abstracted and eCQM measure data. In the proposed rule, we noted 
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. In the FY 
2020 IPPS/LTCH PPS proposed rule (84 FR 19500), we did not propose any 
changes to the DACA requirements.
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. In the FY 2020 IPPS/
LTCH PPS proposed rule (84 FR 19500), we did not propose any changes to 
the public display requirements.
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. 
In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19500), we did not 
propose any changes to the reconsideration and appeals procedures.
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. 
In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19500), we did not 
propose any changes to the ECE policy.

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

[[Page 42510]]

(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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19500 through 
19510), we proposed several new policies for the PCHQR Program. As we 
noted in that proposed rule, 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). We stated that the proposals reflected our efforts to ensure 
that the PCHQR Program measure set continues to promote improved health 
outcomes for our beneficiaries. We further stated that the proposals 
also reflect our efforts to improve the usefulness of the data that we 
publicly report in the PCHQR Program.
2. 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 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 that 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19500 through 
19502), we proposed to adopt a substantive change to the HCAHPS Survey 
by removing the three Pain Management questions beginning with October 
1, 2019 discharges.
    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.\672\ Pain management is therefore an 
important safeguard against the unintended consequences of appropriate 
clinical care in these patients.\673\
---------------------------------------------------------------------------

    \672\ American Cancer Society. ``Cancer Pain.'' Available at: 
https://www.cancer.org/treatment/treatments-and-side-effects/physical-side-effects/pain.html.
    \673\ Mayo Clinic. ``Cancer Pain: Relief is Possible.'' 
Available at: https://www.mayoclinic.org/diseases-conditions/cancer/in-depth/cancer-pain/art-20045118.
---------------------------------------------------------------------------

    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\[square] Yes
    \2\[square] No [rarr] If No, Go to Question 15
    13. During this hospital stay, how often was your pain well 
controlled?
    \1\[square] Never
    \2\[square] Sometimes
    \3\[square] Usually
    \4\[square] Always
    14. During this hospital stay, how often did the hospital staff do 
everything they could to help you with your pain?
    \1\[square] Never
    \2\[square] Sometimes
    \3\[square] Usually
    \4\[square] 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

[[Page 42511]]

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. Removal of the Existing Pain Management Questions From the HCAHPS 
Survey
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19501 through 
19502), we proposed 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 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 regarding 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 also stated in the proposed rule that we were 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 that we believed 
removing the pain management questions would eliminate any such 
potential misuse. We noted that the HCAHPS Quality Assurance 
Guidelines,\674\ 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.
---------------------------------------------------------------------------

    \674\ HCAHPS Quality Assurance Guidelines (v.13.0), available 
at: http://www.hcahpsonline.org/en/quality-assurance/.
---------------------------------------------------------------------------

    While we recognized the importance of being able to provide 
performance results within the context of pain management for cancer 
patients, we also stated in the proposed rule that pain items in 
generic patient experience surveys (for example, HCAHPS) have 
limitations when implemented. As previously noted, 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 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.\675\ We believe that all of 
these issues support the removal of the pain management questions in 
the HCAHPS survey used by PCHs.
---------------------------------------------------------------------------

    \675\ 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.
---------------------------------------------------------------------------

    We also stated our belief that the removal of the questions will 
promote programmatic alignment with both the Hospital IQR Program and 
the Hospital VBP Program. Accordingly, we proposed 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 
noted 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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19501 through 
19502), we also proposed 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. We stated that while the data would not 
be publicly reported, we would 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.
    Comment: Several commenters supported the proposed refinement of 
the HCAHPS survey to remove the existing ``pain management'' questions. 
Commenters agreed that considering the current opioid epidemic, 
unintended consequences may result from these questions remaining in 
the survey. Commenters noted that the removal of these questions is 
prudent until we can better understand the relationship between these 
questions and opioid prescribing, and that the best course of action is 
for CMS to remove them from the HCAHPS survey. Further, commenters 
indicated that removal of the questions is a positive step toward 
improving patient safety and changing staff, patient and family 
perception about appropriate pain management and patient outcomes. 
Commenters also stated that the removal of the ``pain management'' 
questions allows for alignment with the other CMS programs (Hospital 
IQR and Hospital VBP) and agreed that in order to not create confusion 
for consumers, CMS should not publicly report performance data on pain 
assessment.
    Commenters acknowledged that pain assessment and management are 
critical components of cancer care and that under-treatment of pain is 
still a real concern. Commenters encouraged CMS to explore a range of 
approaches to assess how well hospitals are addressing pain management 
in the hospital setting. Commenters also encouraged CMS to continue to 
work with stakeholders to identify measures that encourage the adoption 
of appropriate pain assessment and management practices. Lastly, 
commenters recommended that CMS seek alternative ways to evaluate how 
cancer patients view their pain management and consult with specialty 
societies involved in the treatment of cancer patients.
    Response: We thank the commenters for their support. We acknowledge 
the importance of working with stakeholders to identify measures that 
encourage the adoption of appropriate

[[Page 42512]]

pain assessment and management practices, and alternative approaches to 
assess cancer patient pain management. We intend to conduct further 
education and outreach with stakeholders based on the discussion of 
these alternative approaches and potential future measures. We also 
note that in section IX.B.6.b. of the preamble of this final rule, we 
discuss the responses we received on our request for comments on 
measures and measurement concepts that would assess pain management in 
the cancer patient population, as well as measures that would assess 
post-treatment addiction prevention.
    Comment: Some commenters did not support the proposal to remove the 
``pain management'' questions from the HCAHPS survey. The commenters 
indicated that no evidence is provided that the pain management 
questions promote opioid overuse and expressed concern that CMS' 
rationale is therefore anecdotal. Further, rather than removing these 
questions, commenters recommended that CMS should pursue measures that 
adequately capture a hospital's performance on pain management and 
determine whether any such questions do indeed encourage opioid 
overuse. Until such evidence is confirmed, however, the commenters 
stated that the current questions should remain. Commenters encouraged 
CMS to ensure a balanced approach to pain management that reduces the 
potential for misuse and abuse. Commenters urged CMS to ensure that 
removing these questions does not inappropriately impact patient 
quality of care. Additionally, commenters urged CMS to consider 
alternate questions that seek to ensure adequate patient awareness of 
the range of treatment options available to manage pain--including non-
opioid analgesics and other non-pharmacological modalities of care.
    Response: Our belief that the retention of the pain management 
questions in the HCAHPS survey could lead to unintended consequences is 
based on known examples of current misuse of the HCAHPS survey (such as 
using it for outpatient emergency room care instead of inpatient care 
or using it for determining physician performance). We have also heard 
from stakeholders that the misuse of the HCAHPS Survey may contribute 
to the perception of a link between the pain management questions and 
opioid prescribing practices. We believe that retaining these questions 
would inadvertently continue to contribute to that perception and we 
want to avoid any potential for an adverse impact by virtue of 
retaining those questions in the survey.
    We acknowledge the commenters' concern regarding the importance of 
implementing measures that adequately capture a hospital's performance 
on pain management. We also appreciate their recommendation to consider 
alternate questions that seek to ensure adequate patient awareness of 
the range of treatment options available to manage pain--including non-
opioid analgesics and other non-pharmacological modalities of care. In 
the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19507 through 19508), we 
sought public comment on existing and/or newly developed cancer 
patient, pain-related measures. We refer readers to section IX.B.6.b. 
of the preamble of this final rule for a more detailed discussion of 
the comments that we received on this issue.
    After consideration of the public comments we received, we are 
finalizing our proposal to refine the HCAHPS Survey used in the PCHQR 
Program by removing the three Pain Management questions beginning with 
October 1, 2019 discharges. With respect to our proposal to discontinue 
publicly reporting the data collected on these questions beginning with 
October 1 discharges, due to planned website improvements we are 
currently targeting January 2020 for removal of those data from 
Hospital Compare. We note that we are working to provide performance 
results to PCHs in confidential preview reports that reflect four 
quarters of CY 2018 data, and we do not intend to make those data 
public on Hospital Compare.
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.
     Measure supports efforts to move PCHs towards reporting 
electronic measures.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19502), we did 
not propose any changes to these measure retention factors.
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.\676\ 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 as follows:
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    \676\ 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.
---------------------------------------------------------------------------

     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 <= 0.10.
     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.
     Factor 8. The costs associated with a measure outweigh the 
benefit of its continued use in the program.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19502), we did 
not propose any changes to these measure removal factors.

[[Page 42513]]

4. 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19502 through 
19503), we proposed to remove the External Beam Radiotherapy (EBRT) for 
Bone Metastases (formerly NQF #1822) \677\ 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.
---------------------------------------------------------------------------

    \677\ 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.
---------------------------------------------------------------------------

a. Background
    We adopted the EBRT measure beginning with the FY 2017 program year 
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.\678\ We note that the timing of this 
update was at the end of a quarter of the established reporting period 
for this measure; we finalized in the FY 2015 IPPS/LTCH PPS final rule 
that PCHs would report this measure on a quarterly basis, beginning 
with January 1, 2015 discharges for the FY 2017 program year (79 FR 
50282). We refer readers to a summary table in the FY 2015 IPPS/LTCH 
PPS final rule for a summary of the measure reporting periods for CY 
2016 (79 FR 50283).
---------------------------------------------------------------------------

    \678\ 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 stated in the proposed 
rule that we believed 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, we noted that 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 it has confounded the task of determining which sites 
should be included or excluded from the measure denominator. In 
addition, hospitals have had difficulty determining if sample size 
requirements for the measure are being met. As a result, we stated in 
the proposed rule that we believed the complexity of reporting this 
measure places substantial administrative burden on hospitals.
    We also noted in the proposed rule 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 
stated that we no longer believed we could ensure that the measure is 
in line with clinical guidelines and standards, which further 
diminishes the value of the measure.
c. Summary
    We stated in the proposed rule that we believed the burden 
associated with the measure outweighs the value of its inclusion in the 
PCHQR Program. Accordingly, we proposed, under removal Factor 8, to 
remove the EBRT measure from the PCHQR Program beginning with the FY 
2022 program year.
    Comment: Several commenters supported the proposed removal of the 
External Beam Radiotherapy (EBRT) for Bone Metastases (formerly NQF 
#1822) measure. The commenters stated that while this measure addresses 
a key treatment modality in cancer (radiation therapy), the burden 
associated with data abstraction and the challenges associated with 
maintaining updated specifications in the absence of a measure steward 
warrant removal of the measure from the PCHQR Program. Commenters 
commended CMS for recognizing the concerns that the radiation treatment 
delivery CPT codes used for the measure, which were part of a re-
specification after the measure was finalized, now require additional 
exclusions, and that implementation of these additional exclusions has 
proved burdensome for PCHs. Lastly, commenters indicated that the 
difficulty in identifying accurate and reliable specifications that 
would allow for reporting of the measure via claims is another factor 
that adequately qualifies this measure for removal from the program due 
to a poor cost/benefit ratio.
    Response: We thank the commenters for their support.
    After consideration of the public comments we received, we are 
finalizing our proposal to remove the External Beam Radiotherapy (EBRT) 
for Bone Metastases (formerly NQF #1822) measure from the PCHQR measure 
set beginning with the FY 2022 program year.
5. 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 
relationship 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

[[Page 42514]]

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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19503 
through 19507), we proposed to adopt one new measure beginning with the 
FY 2022 program year, as described below.
b. New Quality Measure Beginning With the FY 2022 Program Year: 
Surgical Treatment Complications for Localized Prostate Cancer
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19503 through 
19507), we proposed 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.\679\ Approximately 80 percent of patients are diagnosed with 
localized disease and therefore may be eligible for prostate directed 
therapy.\680\ 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.681 682 Patients consistently report that these 
adverse effects, which are patient-centered outcomes, can have a 
significant detrimental impact on their quality of 
life.683 684
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    \679\ Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. 
CA: a cancer journal for clinicians. 2016; 66(1):7-30.
    \680\ Ibid.
    \681\ 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.
    \682\ 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.
    \683\ 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.
    \684\ 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.
---------------------------------------------------------------------------

    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.685 686 687 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.\688\
---------------------------------------------------------------------------

    \685\ Schmid M, Meyer CP, Reznor G, et al. Racial Differences in 
the Surgical Care of Medicare Beneficiaries With Localized Prostate 
Cancer. JAMA oncology. 2016; 2(1):85-93.
    \686\ 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.
    \687\ 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.
    \688\ 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.
---------------------------------------------------------------------------

    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).\689\ 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 stated in the proposed rule that we believe the Surgical 
Treatment Complications for Localized Prostate Cancer measure would add 
value to the PCHQR Program measure set.
---------------------------------------------------------------------------

    \689\ Localized Prostate Cancer Standard Set, available at: 
http://www.ichom.org/medical-conditions/localized-prostate-cancer/.
---------------------------------------------------------------------------

(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.690 691 692 693 694 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

[[Page 42515]]

and hopefully mitigate unwarranted variation in prostatectomy 
procedures.
---------------------------------------------------------------------------

    \690\ 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.
    \691\ 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.
    \692\ 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.
    \693\ 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.
    \694\ 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.
---------------------------------------------------------------------------

    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 
would identify a specified timeframe for public reporting of this 
measure in future rulemaking. In addition, we noted that there are 
currently no measures assessing complications of prostate surgery in 
the PCHQR Program measure set.
(3) Data Sources
    We proposed that we would calculate this measure on a yearly basis 
using Medicare administrative claims data. Specifically, we proposed 
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 noted that the TEP endorsed the ICHOM's recommendation to measure 
prostate-directed surgical treatment complications. Because the measure 
methodology assesses complications pre-surgery and post-surgery 
directed to the prostate, this necessitated 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 \695\ 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 measure could successfully identify patients with prostate cancer, 
thereby substantiating the use of Medicare claims as the data source 
for this measure.
---------------------------------------------------------------------------

    \695\ SEER-Medicare Dataset. Available at: https://healthcaredelivery.cancer.gov/seermedicare/overview/.
---------------------------------------------------------------------------

(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 1 year before through 1 year after prostate directed therapy. The 
measure code lists include all codes required for the numerator and 
denominator calculation.\696\
---------------------------------------------------------------------------

    \696\ 2018-2019 Measure Applications Partnership Workgroup Final 
Recommendations Excel spreadsheet. Available at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
---------------------------------------------------------------------------

    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 noted in the proposed 
rule 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, we stated that the measure would be calculated as the 
numerator divided by the denominator (in accordance with the 
denominator exclusions as previously described). 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 (as previously discussed) 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

[[Page 42516]]

dictionary,\697\ 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.
---------------------------------------------------------------------------

    \697\ International Consortium for Health Outcomes Measurement 
(ICHOM) in the Localized Prostate Cancer Standard Set. https://www.ichom.org/medical-conditions/localized-prostate-cancer/.
---------------------------------------------------------------------------

(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,'' \698\ 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.\699\ 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.\700\ 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.\701\
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    \698\ Measures Application Partnership ``2018 measures Under 
Consideration Spreadsheet.'' Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=88813.
    \699\ 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.
    \700\ Ibid.
    \701\ Ibid.
---------------------------------------------------------------------------

    In response to the concern raised by the MAP regarding the grouping 
of surgical procedures, we noted that the measure is intended to 
calculate one overall facility rate for accountability purposes. 
However, given the guidance from the MAP, the steward has recommended 
to CMS that each hospital's publicly displayed performance on the 
Hospital Compare website would be stratified by prostatectomy procedure 
type (open versus not open) to add meaning for consumers and hospital 
quality improvement. Further, in response to the MAP's question of 
risk-adjustment, we noted that risk-adjustment is limited for cancer 
patients when using claims data (for example, cancer stage not captured 
in claims data). Despite this, we reiterated 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.
    In the proposed rule, we stated that we currently 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 
noted that we have not been able to identify a feasible and practical 
endorsed measure that addresses surgical procedures for localized 
prostate cancer. We also stated that 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 noted this measure aligns with recent initiatives to 
increase the number of outcome measures in quality reporting programs. 
Lastly, we stated that this measure aligns with the ``Make Care Safer 
by Reducing Harm Caused in the Delivery of Care'' domain of our 
Meaningful Measures Initiative,\702\ and would fill an existing gap 
area of patient-focused episode of care in the PCHQR Program.
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    \702\ 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) Adoption of the Surgical Treatment Complications for Localized 
Prostate Cancer Measure
    We stated in the proposed rule that 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.\703\
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    \703\ 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 previously outlined, we proposed to adopt the 
Surgical Treatment Complications for Localized Prostate Cancer measure 
for the FY 2022 program year and subsequent years.
    Comment: Many commenters supported the proposed adoption of the 
Surgical Treatment Complications for Localized Prostate Cancer measure, 
however, these same commenters recommended that CMS consider conducting 
confidential national reporting prior to public display of this 
measure's data. The commenters stated

[[Page 42517]]

that prostate cancer is a highly prevalent cancer diagnosis, making it 
particularly important to capture and report on differences in patient 
outcomes and variations between facilities. Further, analysis of claims 
data to report rates of urinary incontinence and erectile dysfunction 
among patients undergoing localized prostate cancer surgery will enable 
this evaluation and create an important opportunity for quality 
improvement activities. Commenters indicated that a confidential dry-
run on the measure is necessary to ensure the claims codes have been 
thoroughly vetted and that the measure's specifications are returning 
valid results. Commenters also noted that the measure was designed and 
tested for accountability purposes as an overall facility rate. 
Commenters also noted it would not be feasible or statistically valid 
to report this stratified data publicly. As such, the commenters 
recommended that CMS provide stratified results to hospitals in their 
confidential facility-specific reports for internal hospital quality 
improvement purposes only. Lastly, commenters expressed that since the 
measure calculates the risk adjusted rate of the occurrence of urinary 
and erectile dysfunction following surgical treatment for prostate 
cancer using Medicare claims data, outcomes data in this area would be 
useful.
    Response: We thank the commenters for their support and their 
recommendations regarding confidential national reporting of this 
measure prior to publicly reporting the data. We agree that 
confidential national reporting would be essential to ensure the 
reliability and validity of the measure's performance results and we 
commit to conducting confidential national reporting for this measure 
prior to publicly reporting the data. We believe that the best course 
of action is to conduct confidential reporting to ensure the 
feasibility of providing statistically robust, and valid stratified 
measure results.
    Additionally, we noted in the proposed rule that this measure will 
be stratified by prostatectomy procedure type (open versus not open) 
(84 FR 19606). We wish to clarify that the measure is not currently 
stratified by procedure type, and that we did not propose that the 
measure would be publicly reported on the Hospital Compare website as 
stratified by prostatectomy procedure type. CMS will consider this 
recommendation for future rulemaking on the public reporting of this 
measure. Further, we wish to clarify that our consideration of 
stratified measure results does not require a change to the measure's 
calculation and only has implications for how we would publicly report 
this measure's data in the future.
    Comment: A few commenters did not support the proposed adoption of 
the Surgical Treatment Complications for Localized Prostate Cancer 
measure. The commenters expressed concern that adopting such a measure 
would create financial incentives for hospitals to encourage patients 
to defer treatment or use other forms of prostate cancer treatments 
over localized surgical treatments, without regard to the patient's and 
physician's judgment of the best options for that patient. Further, the 
commenters indicated that this measure should not be included in the 
PCHQR Program until it has been refined and adequately tested. The 
commenters recommended adopting an additional exclusion for patients 
who have been diagnosed or treated for erectile dysfunction and/or 
urinary incontinence prior to undergoing surgery for prostate cancer to 
ensure accurate measurement.
    Response: We do not believe that the adoption of this measure into 
the PCHQR Program would incentivize hospitals to encourage patients to 
defer treatment or elect alternative treatments over localized surgical 
treatments. We reiterate that by identifying facilities where adverse 
outcomes associated with prostatectomy are more common, this measure 
will help address and hopefully mitigate unwarranted variation in 
prostatectomy procedures. Further, this measure is not intended nor 
designed to address whether a patient should undergo a prostatectomy; 
instead, it provides information on hospital/facility-level variation 
in adverse outcomes for patients presumably identified as appropriate 
candidates for this procedure. In this way, the measure may help 
hospitals/facilities identify potential opportunities for improvement 
based on their patient outcomes. As such, we believe that the inclusion 
of this measure in the PCHQR Program will set a precedent for the 
efficiency of localized treatments, and via positive performance 
results, help patients better understand that localized surgical 
treatments are viable care options for urinary incontinence and 
erectile dysfunction.
    Regarding the concerns about the measure's testing, we note that 
given the limitations of the prostatectomy codes available during the 
development and testing of this measure, as well as the number of cases 
required to assess reliability and validity of the stratified data, it 
was not feasible to provide statistically robust stratified results. 
The measure was designed and tested for accountability purposes as an 
overall facility rate; therefore, it would not be feasible or 
statistically valid to report this stratified data publicly, however, 
in recognition of the importance of confidential reporting prior to 
publicly reporting data, we intend to provide stratified results to 
hospitals in their confidential facility-specific reports for internal 
hospital quality improvement purposes only. To address the commenters' 
suggestion about additional exclusions, we note that this measure is 
calculated by subtracting the number of days with claims for ED and/or 
UI in the year before the prostatectomy from the number of days with 
claims in the year after surgery; therefore, patients serve as their 
own control given that any history of ED and/or UI prior to the 
surgical intervention is accounted for. Excluding those patients with a 
prior history of ED and/or UI is not necessary, and in fact, may reduce 
the number of appropriately eligible patients in the denominator.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Surgical Treatment Complications 
for Localized Prostate Cancer measure for the FY 2022 program year and 
subsequent years. We note that to be responsive to stakeholder 
feedback, we will include confidential national reporting for this 
measure prior to publicly reporting its performance data. Lastly, we 
note that we will address the timing of publicly reporting this 
measure's data in future rulemaking.
c. Summary of Previously Finalized and Newly Finalized PCHQR Program 
Measures for the FY 2022 Program Year and Subsequent Years
    This table summarizes the PCHQR Program measure set for the FY 2022 
program year.

[[Page 42518]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.187

[GRAPHIC] [TIFF OMITTED] TR16AU19.188

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 FR4979), 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19507 through 
19508), we again sought public comment on the topics we should consider 
for quality measurement in the PCHQR Program. In the proposed rule, we 
stated that we were 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 sought 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 finalizing our proposal 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

[[Page 42519]]

that providers may be incentivized to overprescribe opioids to cancer 
patients. In the proposed rule, we also discussed how the opioid 
epidemic is a national crisis, and that 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.\704\ 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.705 706 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.\707\ 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.
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    \704\ 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.
    \705\ 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.
    \706\ 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.
    \707\ 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.\708\ Further, postsurgical complications related 
to inadequate pain management negatively affect patient welfare and 
hospital performance because of extended lengths of stay and 
readmissions, both of which increase the cost of care.\709\ 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).\710\ In addition, patients who have not been treated 
adequately for pain management may be reluctant to seek medical care 
for other health problems.\711\
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    \708\ Optimal Pain Management for Patients with Cancer in the 
Modern Era. Available at: https://onlinelibrary.wiley.com/doi/full/10.3322/caac.21453.
    \709\ Patient Safety and Quality: An Evidence-Based Handbook for 
Nurses. Available at: https://www.ncbi.nlm.nih.gov/books/NBK2658/.
    \710\ Ibid.
    \711\ Ibid.
---------------------------------------------------------------------------

    On August 7, 2018, the Alliance of Dedicated Cancer Centers,\712\ 
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,\713\ 
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.
---------------------------------------------------------------------------

    \712\ Alliance of Dedicate Cancer Centers website: http://www.adcc.org/.
    \713\ 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, after consideration of public comments, we are 
removing from the survey. 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.714 715
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    \714\ 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.
    \715\ Denis, F et al. Patient-Reported Outcomes, Mobile 
Technology, and Response Burden. 2018 ASCO Annual Meeting. Abstract 
No: 6500.
---------------------------------------------------------------------------

    Accordingly, in the proposed rule we sought 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 also invited public comment on the potential future 
adoption of measures that assess post-treatment addiction prevention 
for cancer patients. Lastly, we invited public comment on existing 
measures or measurement concepts that evaluate pain management for 
cancer patients, and do not involve opioid use.
    Comment: Commenters supported CMS' focus on developing additional 
pain management PRO measures. The commenters indicated that these newly 
developed measures should be designed to avoid inadvertently 
incentivizing the over-prescribing of opioid medication, while also 
recognizing that opioid medications are an important tool for 
controlling cancer-related pain. Further,

[[Page 42520]]

in the years ahead, the tools available to treat acute and chronic pain 
will continue to expand and patient engagement on these treatment 
options will remain of critical importance. Commenters encouraged CMS 
to continue to facilitate research and development of patient-reported 
outcome performance measures (PROPMs) for health-related quality of 
life and pain in breast, colon, and non-small lung cancer patients 
receiving chemotherapy with curative intent, as well as pain and 
communication measures for patients receiving palliative care. 
Commenters also noted that while PRO measures are relatively complex to 
develop and time-consuming to implement, there is compelling data to 
suggest that collection of PRO data can make a significant difference 
in patient outcomes when results are actively monitored and paired with 
timely intervention. Lastly, commenters advised CMS to consider the 
standards of undue burden to cancer centers and physician practices in 
its' evaluation of appropriate PRO-PM measures for the PCHQR Program, 
especially as it relates to Electronic Medical Record (EMR) 
interoperability and patient survey fatigue.
    Response: We appreciate the commenters' feedback regarding PRO-PM 
measures in the context of cancer patient pain management. We will 
further explore the options and suggestions provided as we continue 
look to identify appropriate PRO-PM measures for the PCHQR measure set.
    Comment: A few commenters were supportive of CMS' efforts to 
identify existing measures or measurement concepts that evaluate pain 
management for cancer patients, and do not involve opioid use. 
Commenters noted that as CMS considers new measures to curb opioid 
misuse, it is critical that these measures contain appropriate 
exclusions to ensure that people living with serious illness have 
access to necessary medications. At a minimum, exclusions should 
specify patients who have elected or are discharged to hospice, as well 
as those who are receiving palliative care. Additionally, other 
patients with serious illness, such as patients with cancer, AIDS, end-
stage chronic lung disease, end stage renal disease, heart failure, 
hemophilia, or sickle cell disease, should be excluded. Commenters 
advised CMS to consider the following topical areas when looking to 
expand the pain management domain of the PCHQR measure set: causes of 
pain (for example, recurrent disease, second malignancy or late onset 
treatment effects); pain effect on sleep; pain interference with 
therapy activities; and pain interference with day-to-day activities.
    Lastly, one commenter indicated that there are existing 
stakeholders that manufacture a range of technologies that can markedly 
reduce the need to prescribe opioids to patients experiencing chronic 
and acute pain. Several of these devices may be suitable for use in 
addressing the acute and chronic pain needs of cancer patients. As 
such, the commenter recommended that CMS work with these stakeholders 
to structure those measures in a way that accommodates the evaluation 
and use of device-based alternatives as an option to prescribe systemic 
opioids.
    Response: We thank the commenters for their opinions and 
recommendations, and will take them into consideration as we continue 
to consider possible new quality measure topics for future years.
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, in the FY 2020 IPPS/LTCH PPS proposed 
rule (84 FR 19508 through 19510), we made two proposals regarding the 
timetable for the public display of data for specific PCHQR Program 
measures.
b. Public Display of the Admissions and Emergency Department (ED) 
Visits for Patients Receiving Outpatient Chemotherapy Measure Beginning 
With CY 2020
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19508 through 
19509), we proposed 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 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

[[Page 42521]]

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 proposed to begin publicly reporting performance data on 
the Admissions and Emergency Department (ED) Visits for Patients 
Receiving Outpatient Chemotherapy measure in CY 2020. We stated our 
belief 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.
    Comment: Several commenters supported the proposal to begin public 
reporting of the Admissions and Emergency Department (ED) Visits for 
Patients Receiving Outpatient Chemotherapy measure in CY 2020. A few 
commenters noted support for public display of the measure but 
recommended that CMS delay reporting for at least 1 year to allow for 
the provision of additional dry-run data and to ensure that measure 
data is returning valid results.
    Response: In response to recommendations that we delay public 
reporting by 1 year, we note that we have completed the confidential 
national reporting for this measure and have assessed the preliminary 
results to ensure data accuracy and completeness; and therefore, have 
confirmed that the measure data is returning valid results. As such, we 
believe it is appropriate to publicly report the Admissions and 
Emergency Department (ED) Visits for Patients Receiving Outpatient 
Chemotherapy measure in CY 2020.
    Comment: A few commenters noted that they are looking forward to 
CMS' announcement of the data period that will be included when the 
measure is publicly displayed in CY 2020.
    Response: We thank commenters for their input. We are not able to 
specify the data reporting period that will be included in the publicly 
displayed data for this measure at this time. We will announce 
additional information on the public display to affected providers as 
soon as is practicable.
    Despite our belief that public reporting of this measures is both 
important and appropriate, we note that planned website improvements 
may result in a delay in our ability to begin public reporting of this 
measure. Accordingly, after consideration of the public comments we 
received, we are finalizing our proposal with a modification to clarify 
that we will publicly report data for the Admissions and Emergency 
Department (ED) Visits for Patients Receiving Outpatient Chemotherapy 
measure as soon as is practicable, rather than beginning in CY 2020, as 
proposed.
c. Public Display of Centers for Disease Control and Prevention (CDC) 
National Healthcare Safety Network (NHSN) Measures
(1) 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.\716\ Currently, these rebaselining efforts--specifically, 
generation and implementation of new predictive models used to 
calculate SIRs--are complete. As such, in the FY 2020 IPPS/LTCH PPS 
proposed rule (84 FR 19509), we proposed to publicly report data for 
the Colon and Abdominal Hysterectomy SSI, MRSA, CDI, and HCP measures 
beginning with the October 2019 Hospital Compare release.
---------------------------------------------------------------------------

    \716\ Centers for Disease Control and Prevention. ``Paving Path 
Forward: 2015 Rebase line.'' Available at: https://www.cdc.gov/nhsn/2015rebaseline/index.html.
---------------------------------------------------------------------------

    Comment: Several commenters supported the proposal to publicly 
display the CDC National Health Safety Network (NHSN) measures 
beginning with the October 2019 release of Hospital Compare. A few 
specifically supported the proposed public display of the HCP measure, 
noting that cancer patients are at higher risk for influenza related 
complications.
    Response: We thank the commenters for their support.
    Comment: A few commenters opposed the proposal to publicly display 
the MRSA, CDI, and SSI measures beginning with the October 2019 release 
of Hospital Compare due to concerns that the cancer patient population 
is at increased risk for HAIs because treatment leaves patients 
immunocompromised. Commenters noted that comparing PCHs to other 
hospitals could lead to unfair performance comparisons and recommended 
that CMS work with NHSN to identify an appropriate strategy for 
displaying data for these measures. A few commenters specifically 
expressed concern that testing for CDI occurs at a higher frequency in 
the cancer population and is not accurate enough to distinguish between 
CDI infection and CDI colonization. Commenters expressed concern that 
displaying CDI measure data would not provide useful information to the 
public.
    Response: We noted 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 and that we would publicly report 
it on the Hospital Compare website via the next available Hospital 
Compare release. We recognize commenters' concerns that HAIs, and CDI 
in particular, may occur at a higher frequency than the general patient 
population due to clinical and treatment variations and believe that it 
is especially important to track and share this information on Hospital 
Compare so that this vulnerable patient population can make informed 
decisions. We do not believe that

[[Page 42522]]

increased rates of HAIs warrant limiting patient access to measure 
information. The predictive models used to calculate these summarized 
measures take into account the hospital's status as a cancer hospital, 
thereby accounting for the increased risk of HAI in this patient 
population.
    With respect to concerns that unfair performance comparisons will 
be made between PCHs and other hospitals, we note that PCH measure data 
are calculated taking cancer hospital status into account, specifically 
the increased HAI risk among their patients, and the measure data 
displayed for the 11 participating PPS-Exempt Cancer Hospitals as a 
separate and discrete group on Hospital Compare. Further, we note that 
cancer patients are recognized as a unique cohort, thus comparisons of 
measure data between participating PCHs takes precedence over data 
comparisons across other hospitals with broader patient populations. 
Moreover, we believe publicly displaying HAI measure data will provide 
meaningful data to participating PCHs, cancer patients, and their 
families when choosing care options.
    Despite our belief that public reporting of the Colon and Abdominal 
Hysterectomy SSI, MRSA, CDI, and HCP measures is both important and 
appropriate, we note that planned website improvements may result in a 
delay in our ability to begin public reporting of these measures. 
Accordingly, after consideration of the public comments we received, we 
are finalizing our proposal with a modification to clarify that we will 
publicly report data for the Colon and Abdominal Hysterectomy SSI, 
MRSA, CDI, and HCP measures as soon as is practicable, rather than 
beginning with the October 2019 Hospital Compare release, as proposed. 
We are currently targeting a January 2020 Hospital Compare initial 
public reporting release date for these measures.
(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.
    Comment: A few commenters supported the delay of public display of 
the CLABSI and CAUTI measures, noting that the definitions and organism 
lists have been changing and comparisons across hospitals may be 
difficult to make.
    Response: We thank commenters for their support. We will continue 
to defer public reporting of the CAUTI and CLABSI measures.
d. Summary of Finalized Public Display Requirements for the PCHQR 
Program
    Our finalized public display requirements for the PCHQR Program are 
shown in the following table.

[[Page 42523]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.189

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. Confidential National Reporting for Certain Existing PCHQR Measures
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19510), we 
proposed 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).
     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) Confidential National Reporting for Data Collection
    To prepare PCHs for public reporting, in the proposed rule, we 
proposed 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, we stated that 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 also stated that we believe 
these confidential national reporting activities will enable hospitals 
to gain data collection and reporting experience familiarity with these 
refined measures

[[Page 42524]]

for their efforts to improve quality and better understand the measure 
specifications and associated data. We stated that 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 proposed 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 proposed to conduct 
confidential national reporting using Medicare claims data collected 
from October 1, 2019 through September 30, 2020. We stated that 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.
    Comment: Several commenters supported the proposal to conduct 
confidential national reporting of the four end-of-life measures using 
Medicare claims data collected from July 1, 2019 through June 30, 2020. 
A commenter noted its agreement that these confidential reports will 
allow the PCHs to review results, understand the technical 
specifications, and review any potential concerns regarding attribution 
and risk adjustment.
    Response: We thank the commenters for their support.
    Comment: Several commenters supported the proposal to conduct 
confidential national reporting for the 30-Day Unplanned Readmissions 
for Cancer Patients measure using Medicare claims data collected from 
October 1, 2019 through September 30, 2020. A few commenters noted that 
these reports are especially important for claims-based measures to 
ensure that the technical measure specifications capture the measures 
accurately.
    Response: We thank the commenters for their support.
    After consideration of public comments, we are finalizing our 
proposals to: (1) Conduct confidential national reporting of the four 
end-of-life measures using Medicare claims data collected from July 1, 
2019 through June 30, 2020; and (2) conduct confidential national 
reporting for the 30-Day Unplanned Readmissions for Cancer Patients 
measure using Medicare claims data collected from October 1, 2019 
through September 30, 2020 as proposed.
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 the 
FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19510), we did not propose 
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 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).
    While we did not solicit comments on previously finalized LTCH QRP 
policies, we received some comments, which are summarized in this final 
rule.
    Comment: A few commenters supported the proposed changes to the 
LTCH QRP, recognizing that these changes are part of a multiyear 
process to reform patient assessment and quality reporting across 
multiple levels of care. A commenter supported CMS' effort to align 
areas of best practices with other quality reporting programs, 
specifically when accounting for social risk factors, applying the 
Meaningful Measures Framework in support of the Patients Over Paperwork 
Initiative, and removing, adopting, and retaining quality measures 
according to standardized decision criteria.
    Response: We appreciate the commenters' support and feedback.
    Comment: A commenter supported CMS' effort to show the implications 
and potential methods for addressing health disparities regarding 
social risk factors in quality measurement and supported the concept of 
using measures already included in quality reporting programs as tools 
for hospitals to identify gaps in their respective patients' outcomes. 
The commenter also requested that attribution details for each measure 
be addressed in technical specifications.
    Response: We appreciate the commenter's support and feedback and 
will take these comments into consideration.
    Comment: A few commenters requested that CMS lower the LTCH QRP 
compliance threshold of 80 percent for assessment-based items given the 
number of data elements that have been added to the LTCH CARE Data Set.
    Response: We appreciate the commenters' feedback. We did not 
propose any changes to the compliance threshold, which has been 
codified in the LTCH QRP regulations at Sec.  412.560(f).
2. General Considerations Used for the Selection of Measures for the 
LTCH QRP
    For a detailed discussion of the considerations we use 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:

[[Page 42525]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.190

    While we did not solicit comments on previously adopted measures 
(with the exception of the Discharge to Community-PAC LTCH QRP measure 
discussed in VIII.C.4.c. and the policies regarding public display of 
the Drug Regimen Review Conducted With Follow-Up for Identified Issues-
PAC LTCH QRP measure discussed in section VIII.C.10. of this rule), we 
received a comment.
    Comment: A commenter supported maintaining the Influenza 
Vaccination Coverage Among Healthcare Personnel (NQF #0431) quality 
measure in the LTCH QRP, citing the importance of publicly reporting 
measure data as an important tool for patients and families seeking to 
evaluate an LTCH setting and an essential component in the 
identification and management of influenza outbreaks.
    Response: We appreciate the commenter's support. We would like to 
clarify that we did not propose any changes to the previously finalized 
Influenza Vaccination Coverage Among Healthcare Personnel (NQF #0431) 
measure.
4. LTCH QRP Quality Measure Proposals Beginning With the FY 2022 LTCH 
QRP
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19511 through 
19517), we proposed 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 proposed to adopt are: (1) Transfer of Health 
Information to the Provider--Post-Acute

[[Page 42526]]

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, in the proposed rule (84 
FR 19517), we proposed 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. 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.
(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.\717\ 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.\718\ 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).\719\
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    \717\ 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.
    \718\ Ibid.
    \719\ 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.720 721 722 723 724 725 Poor communication and 
coordination across health care settings contributes to patient 
complications, hospital readmissions, emergency department visits, and 
medication errors.726 727 728 729 730 731 732 733 734 735 
Communication has been cited as the third most frequent root cause in 
sentinel events, which The Joint Commission defines \736\ 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.\737\ 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.738 739 740 741 742
---------------------------------------------------------------------------

    \720\ 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.
    \721\ 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.
    \722\ 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.
    \723\ 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.
    \724\ 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.
    \725\ Boling, P. A., ``Care transitions and home health care,'' 
Clinical Geriatric Medicine, 2009, Vol. 25(1), pp. 135-48.
    \726\ 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.
    \727\ 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.
    \728\ 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.
    \729\ 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.
    \730\ 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.
    \731\ 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.
    \732\ 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.
    \733\ 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.
    \734\ 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.
    \735\ King, B. J., Gilmore[hyphen]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.
    \736\ The Joint Commission, ``Sentinel Event Policy'' available 
at: https://www.jointcommission.org/sentinel_event_policy_and_procedures/.
    \737\ 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.
    \738\ 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.
    \739\ 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.
    \740\ 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.
    \741\ 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.
    \742\ Balaban RB, Weissman JS, Samuel PA, & 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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[[Page 42527]]

    Care transitions across health care settings have been 
characterized as complex, costly, and potentially hazardous, and may 
increase the risk for multiple adverse outcomes.743 744 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 billion in wasteful spending in 
2011.\745\ The communication of health information and patient care 
preferences is critical to ensuring safe and effective transitions from 
one health care setting to another.746 747
---------------------------------------------------------------------------

    \743\ 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.
    \744\ 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/.
    \745\ Berwick, D. M. & Hackbarth, A. D. ``Eliminating Waste in 
US Health Care,'' JAMA, 2012, Vol. 307(14), pp. 1513-1516.
    \746\ 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/.
    \747\ 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.748 749 750 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.751 752 
Preventable adverse drug events (ADEs) may occur after hospital 
discharge in a variety of settings including PAC.\753\ 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.\754\ 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.755 756
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    \748\ 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.
    \749\ 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.
    \750\ 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.
    \751\ 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.
    \752\ 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.
    \753\ 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.
    \754\ 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.
    \755\ 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.
    \756\ 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.\757\ Medication discrepancies are common,\758\ and 
found to occur in 86 percent of all transitions, increasing the 
likelihood of ADEs.759 760 761 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.762 763
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    \757\ 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.
    \758\ 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.
    \759\ 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.
    \760\ 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.
    \761\ 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.
    \762\ 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.
    \763\ 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,764 765 766 especially when medications are

[[Page 42528]]

reviewed by a pharmacist using electronic medical records.\767\
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    \764\ 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.
    \765\ 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.
    \766\ 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.
    \767\ 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,\768\ January 27, 2017,\769\ and August 3, 2017 
\770\ 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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    \768\ 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.
    \769\ 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.
    \770\ Ibid.
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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

[[Page 42529]]

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 previously discussed, 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 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, ``Final 
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 
proposed for this measure, we refer readers to the discussion in 
section VIII.C.8.d. of the preamble of this final rule.
    Commenters submitted the following comments related to the proposed 
rule's discussion of the LTCH QRP quality measure proposals beginning 
with the FY 2022 LTCH QRP. A discussion of these comments, along with 
our responses, appears below. We also address comments on the proposed 
Transfer of Health Information to the Patient--Post-Acute Care measure 
(discussed further in a subsequent section of this final rule) in this 
section because commenters frequently addressed both proposed Transfer 
of Health Information measures together.
    Comment: Several commenters supported the Transfer of Health 
Information measures, stating that they will help improve care 
coordination, patient safety, and care transitions.
    Response: We thank the commenters for their support of the Transfer 
of Health Information measures.
    Comment: A few commenters did not support finalizing the Transfer 
of Health Information measures. A few commenters suggested that instead 
of the proposed measures, which focus on whether medication information 
was transferred, CMS consider measures and approaches to collect 
information on the accuracy, timeliness, and clarity of critical 
medication information received by downstream providers, patients, and 
their families. A commenter described challenges in obtaining important 
information from acute care hospitals such as a current medication list 
and dosages, just prior to transition and stated that the downstream 
PAC provider has no control over the information received. The 
commenter added that the completeness and clarity of critical 
information transmitted from the LTCH or any other PAC provider to a 
patient and/or next care setting upon discharge is important.
    Response: We appreciate the suggestions that CMS develop and adopt 
measures that assess for the accuracy, timeliness, and clarity of 
critical medication information received by downstream providers, 
patients, and their families. We agree that measure concepts of this 
type are important and would complement these measures that focus on 
whether information was transferred. We would like to note that the 
measures address the timeliness of the transfer of a medication list by 
requiring that the information is shared with the subsequent provider 
and/or the patient as close to the time of discharge as this is 
actionable. With support from a TEP, public comment, the MAP, and other 
stakeholders, we have determined that these measures will provide 
important data and greater understanding of how information is 
transferred, reinforcing and supporting efforts toward health 
information exchange. Finally, we agree with the comments that critical 
information transmitted from the LTCH or any other PAC provider to a 
patient and/or next care setting upon discharge is important. We will 
explore the feasibility of expanding this measure set and will use the 
Transfer of Health Information measures to inform future efforts.
    Comment: Several commenters raised concerns about the Transfer of 
Health Information measures not being endorsed by NQF. Some of the 
commenters that raised these concerns stated that they generally 
supported or were not opposed to the Transfer of Health Information 
measures. Other commenters encouraged CMS to pursue the NQF endorsement 
process and a few commenters requested that we consider delaying 
rollout of these two new measures until endorsed by NQF. Commenters 
also recommended that we only adopt or implement measures that have NQF 
approval. A commenter elaborated on this recommendation, noting that 
the MAP was clear that it only ``conditionally supported both measures 
pending NQF endorsement'' and believes that CMS should not adopt the 
measures, or any other LTCH QRP measures, until NQF and MAP 
unconditionally endorse the new measures. Another commenter was opposed 
to the measures because they have not been endorsed by NQF.
    Response: This measure is not currently NQF-endorsed, and we 
recognize that the NQF endorsement process is an important part of 
measure development. As discussed in the FY 2020 IPPS/LTCH PPS proposed 
rule (84

[[Page 42530]]

FR 19512 through 19517), we believe that the measures better address 
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, than any currently endorsed measures. While 
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, 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. We plan to submit the measure to for NQF 
for endorsement consideration as soon as feasible.
    Comment: A commenter suggested that other providers, such as 
outpatient physical therapists, should be included in the definition of 
a subsequent provider for the Transfer of Health Information to the 
Provider--Post-Acute Care measure.
    Response: We appreciate the suggestion to expand the Transfer of 
Health Information to the Provider--Post-Acute Care measure outcome to 
assess the transfer of health information to other providers such as 
outpatient physical therapists. We recognize that sharing medication 
information with outpatient providers is important, and will take into 
consideration additional providers in future measure modifications. 
Through our measure development and pilot testing we learned that 
outpatient providers cannot always be readily identified by the PAC 
provider, including LTCHs. For this process measure, which serves as a 
building block for improving the transfer of medication information, we 
specified providers who will be involved in the care of the patient and 
medication management after discharge and can be readily identified 
through the discharge location item on the LCDS. The clear delineation 
of the recipient of the medication list in the measure specifications 
will improve measure reliability and validity.
    Comment: A few commenters expressed concern over burden. A 
commenter believed that the measures have no value and so the burden 
for data collection is not worth the benefit. Another commenter stated 
that while there will be additional burden on LTCHs to collect and 
report data for these new measures, the benefit to patients and the CMS 
program outweighs the additional burden on providers.
    Response: We agree that the benefit to patients outweighs any 
additional burden on providers. We are also very mindful of burden that 
may occur from the collection and reporting of our measures, as 
supported by the Meaningful Measures and Patients over Paperwork 
initiatives. We would like to emphasize that both measures are 
comprised of one item, and further, the activities associated with the 
measures align with existing requirements related to transferring 
information at the time of discharge in order to safeguard patients. 
Additionally, TEP feedback and pilot testing found that burden of 
reporting will not be significant. CMS believes that these measures 
will drive improvements in the transfer of medication information 
between providers and with patients, families, and caregivers.
    Comment: A commenter stated that because providing medication 
information as part of discharge planning is a Condition of 
Participation (CoP) requirement for Medicaid and Medicare and the 
medication list can be generated from the electronic medical record, 
there should be no added burden to LTCHs.
    Response: We believe that these measures will not substantially 
increase burden because we understand that many hospitals already 
generate medication lists as a best practice, in accordance with our 
interpretive guidance regarding our discharge planning CoP at Sec.  
482.43(c). While we recognize that not all LTCHs have electronic 
medical records, providing a medication list to the subsequent provider 
is standard practice and, therefore, this measure should not 
substantially increase burden.
    Comment: A commenter provided additional data to provide context 
around data from an OIG report in our background section. The commenter 
stated that when adjusted for variations in lengths of stay, per 1,000 
patient stays, LTCH patients experienced 38 adverse and temporary harm 
events as compared to 29, 24, and 69 adverse and temporary harm events 
in IRFs, SNFs, and STACHs, respectively. The commenter stated that OIG 
also reported that over half of these events (54 percent) were clearly 
or likely preventable; however, this was not out of the ordinary in 
comparison to the rate of preventable harm reported in SNFs (59 
percent).
    Response: We thank the commenter for providing this additional data 
and note that these data support our contention that there is room for 
improvement across PAC settings when it comes to adverse and temporary 
harm events.
    Comment: A few commenters expressed concerns that the Transfer of 
Health Information to the Provider and Transfer of Health Information 
to the Patient measures are not indicative of provider quality and 
questioned the ability of the measures to improve patient outcomes or 
reduce adverse events.
    Response: The Transfer of Health Information to the Provider--Post-
Acute Care and Transfer of Health Information to the Patient--Post-
Acute Care measures are process measures designed to address and 
improve an important aspect of care quality. Lack of timely transfer of 
medication information at transitions has been demonstrated to lead to 
increased risk of adverse events, medication errors and 
hospitalizations. In addition, public commenters and our TEP members 
identified many problems and gaps in the timely transfer of medication 
information at transitions. Process measures, such as these, are 
building blocks toward improved coordinated care and discharge 
planning, providing information that will improve shared decision 
making and coordination. Further, process measures provide value as 
they delineate negative and/or positive aspects of the health care 
process. These measures will capture the quality of the process of 
medication information transfer and, we believe, help to improve those 
processes.
    Comment: A commenter recommended that the Transfer of Health 
Information to the Provider--Post-Acute Care measure be expanded to 
include information that would help prevent infections and facilitate 
appropriate infection prevention and control interventions during care 
transitions in addition to the medication information in the finalized 
measure.
    Response: The Transfer of Health Information to the Provider--Post-
Acute Care measure focuses on the transfer of a reconciled medication 
list. The measure was designed after input from TEPs, public comment, 
and other stakeholders that suggested the quality measures focus on the 
transfer of the most critical pieces of information to support patient 
safety and care coordination. However, we acknowledge that the transfer 
of many other forms of health information is important, and while the 
focus of this measure is on a reconciled medication

[[Page 42531]]

list, we hope to expand our measures in the future.
    Comment: Some commenters recommended ways in which the Transfer of 
Health Information measures specifications could be updated or changed. 
A commenter suggested that the ``not applicable'' (N/A) answer choice 
available in the home health version of the measure be made available 
in all settings, including LTCHs. A few commenters also requested 
clarification about why patients discharged home under the care of an 
organized home health service or hospice would be captured in the 
denominators of both Transfer of Health information measures.
    Response: We are appreciative of the measure modification 
suggestions and would like to clarify why the response option of N/A 
was considered only for the Home Health version of this measure. The 
coding response, ``N/A'' or ``not applicable'' is used when the home 
health agency (HHA) was not made aware of the transfer in a timely 
manner, and therefore, the HHA is not able to provide the medication 
list at the time of transfer to the subsequent provider. For example, a 
HHA may not be immediately aware when a patient is taken to the 
emergency room. For facility settings such as the LTCH setting, where 
24-hour care is being provided, the facility should always be aware and 
actively involved in the discharge of the patient, and therefore, able 
to provide the current reconciled medication list at the time of 
discharge. Therefore, we believe that the coding option of ``N/A'' 
would not be useful in the facility-based measure as the facility is 
aware and involved in the discharge. We wish to note that while the 
``N/A'' option is considered for the HHA version of the measure, the 
measure specifications indicate that these patients are not removed 
from the denominator. In addition, discharge to home under the care of 
an organized HHA or hospice is captured in the denominator of both the 
Transfer of Health Information to Provider and Transfer of Health 
Information to Patient measures because this type of discharge 
represents two opportunities to transfer the medication list. These 
measures aim to assure that each of these transfers is taking place. We 
refer readers to the measure specifications, 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.
    Comment: A commenter urged CMS to enhance its efforts to develop 
standards and measures for data exchange and sharing across all care 
settings, including PAC, and that existing clinical and 
interoperability standards should be considered in the development of 
these and future measures. The commenter believes that ensuring 
interoperability across EHR systems and settings of care can unlock 
barriers to data sharing and care coordination between health systems, 
physicians and physician group practices, and PAC settings. The 
commenter further suggested that CMS leverage ongoing efforts to adopt 
data standards and implementation guides for certified EHRs, such as 
the USCDI and to build on efforts to base measures and calculations on 
data within certified EHRs. The commenter also suggested that CMS needs 
to consider ways to incentivize PAC providers to more readily adopt 
health IT.
    Response: We agree with the comments on the importance of 
interoperability solutions to support health information transfer. 
First, we would like to clarify that data collection for the Transfer 
of Health Information measures does not require adoption of certified 
EHRs, nor are they calculated from EHRs. CMS and ONC are focused on 
improving interoperability and the timely sharing of information 
between providers, patients, families and caregivers. We believe that 
PAC provider health information exchange supports the goals of high 
quality, personalized, efficient healthcare, care coordination, person-
centered care, and supports real-time, data driven, clinical decision 
making.
    To further support interoperability, we recently released the Data 
Element Library (DEL), a new public resource aimed at advancing 
interoperable health information exchange by enabling users to view 
assessment questions and response options about demographics, medical 
problems, and other types of health evaluations and their associated 
health IT standards. The DEL includes a multitude of data elements, 
including all data elements adopted for use in the quality reporting 
programs, and not limited to data collected under the IMPACT Act. In 
the initial version of the DEL (https://del.cms.gov/), assessment 
questions and response options are mapped to LOINC and SNOMED codes 
where feasible. We also recognize the importance of leveraging existing 
standards, obtaining input from standards setting organizations, and 
alignment across federal interoperability efforts.
    We acknowledge that meaningful use incentives have not been 
extended to LTCHs and other PAC providers. We will share these comments 
with the appropriate CMS staff and other governmental agencies to 
ensure they are taken into account as we continue to encourage adoption 
of health information technology. The Transfer of Health Information 
measures may encourage the electronic transfer of medication 
information at transitions. These measures and related efforts may help 
accelerate interoperability solutions.
    Comment: A commenter suggested that future measures could focus on 
the accuracy of the medication list and the result of medication 
reconciliation on patient care.
    Response: As supported by the CMS Meaningful Measures and Patients 
over Paperwork initiatives, we will take recommendations for future 
measures into consideration. We plan to use the data from the Transfer 
of Health Information measures to inform future efforts.
    Comment: In comments related to both the Transfer of Health 
Information to the Provider and Transfer of Health Information to the 
Patient measures, a commenter requested the definition of a reconciled 
medication list and made reference to an older version of measure 
specifications where a medication profile had been defined.
    Response: Reference to a medication profile in this comment appears 
to have come from measure specifications for a previous version of 
these measures that were posted for Blueprint public comment in March 
2018. We sought input on the types of information included in a 
medication list from our TEP and other stakeholders. Defining the 
completeness of that medication list is left to the discretion of the 
providers and patients who are coordinating this care.
    Comment: A commenter encouraged CMS to finalize revisions to 
``Requirements for Discharge Planning for Hospitals, Critical Access 
Hospitals, and Home Health Agencies'' (CMS-3317-P), which would require 
hospitals to transfer patient information, including diagnosis and 
other clinical information, to the patient's next setting in a timely 
manner and stated that this timely information can improve continuity 
of care.
    Response: We agree that PAC providers' receipt of timely medication 
information from hospitals at discharge would improve the accuracy and 
completeness of medication information in the patient's medical record 
and improve continuity of care. The Revisions to Requirements for 
Discharge Planning for Hospitals, Critical Access Hospitals, and Home 
Health Agencies

[[Page 42532]]

proposed rule (CMS-3317-P) has not been finalized. CMS has issued an 
extension notice for the publication of the final rule, which extends 
the timeline for publication of the final rule until November 3, 2019 
(please see https://www.federalregister.gov/documents/2018/11/02/2018-23922/medicare-and-medicaid-programs-revisions-to-requirements-for-discharge-planning-for-hospitals).
    Comment: A commenter expressed concerns related to the validity and 
accuracy of the Transfer of Health Information measures and suggested 
that CMS should ensure accuracy of these measures.
    Response: We appreciate the comments about measure accuracy and 
validity. Elements of validity and reliability were analyzed during 
pilot testing of these measures, with results showing an inter rater 
reliability of at least 87 percent for all tested items. As we monitor 
the outcomes of this measure, we will ensure that the reliability and 
validity of the measure will meet acceptable standards.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Transfer of Health Information to 
the Provider--Post-Acute Care (PAC) measure, pursuant to section 
1899B(c)(1)(E) of the Act, beginning with October 1, 2020 discharges.
b. Transfer of Health Information to the Patient--Post-Acute Care (PAC) 
Measure
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19515 through 
19517), beginning with the FY 2022 LTCH QRP, we proposed 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.\771\ 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.\772\
---------------------------------------------------------------------------

    \771\ 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.
    \772\ 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.773 774 775 776 777 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.778 779 Upon discharge to home, individuals in PAC 
settings may be faced with numerous medication changes, new medication 
regimes, and follow-up details.780 781 782 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.783 784
---------------------------------------------------------------------------

    \773\ 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.
    \774\ 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.
    \775\ 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.
    \776\ 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.
    \777\ 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.
    \778\ 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.
    \779\ 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.
    \780\ 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.
    \781\ 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.
    \782\ 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.
    \783\ 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.
    \784\ 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.
---------------------------------------------------------------------------

    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.785 786 Most PAC EHR systems 
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.\787\
---------------------------------------------------------------------------

    \785\ 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.
    \786\ 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.
    \787\ 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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[[Page 42533]]

(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,\788\ January 27, 2017,\789\ and August 3, 2017 
\790\ 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.
---------------------------------------------------------------------------

    \788\ 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.
    \789\ 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.
    \790\ Ibid.
---------------------------------------------------------------------------

    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 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

[[Page 42534]]

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 ``Final 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 
proposed for this measure, we refer readers to the discussion in 
section VIII.C.8.d. of the preamble of this final rule.
    Commenters submitted the following comments related to the proposed 
rule's discussion of the LTCH QRP quality measure proposals beginning 
with the FY 2022 LTCH QRP. A discussion of these comments, along with 
our responses, appears below. We received many comments that addressed 
both of the Transfer of Health Information measures. Comments that 
applied to both measures are discussed above in section VIII.C.4.a. of 
this rule.
    Comment: A few commenters urged CMS to use the field's experience 
with transferring information to patients and reporting on this measure 
to disseminate best practices about how to best convey the medication 
list. A commenter suggested this include formats and informational 
elements helpful to patients and families.
    Response: We have interpreted ``the field'' to mean PAC providers. 
Facilities and clinicians should use clinical judgement to guide their 
practices around transferring information to patients and how to best 
convey the medication list, including identifying the best formats and 
informational elements. This may be determined by the patient's 
individualized needs in response to their medical condition. We do not 
determine clinical best practices standards and facilities are advised 
to refer to other sources, such as professional guidelines.
    Comment: A commenter suggested that the Transfer of Health 
Information to the Patient measure should assess if the medication list 
was provided to both the patient and family member, when appropriate.
    Response: We agree there are times when it is appropriate for the 
LTCH to provide the medication list to the patient and family and this 
decision should be based on clinical judgement. However, because it is 
not always necessary or appropriate to provide the medication list to 
both the patient and family, we are not requiring this for the measure.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Transfer of Health Information to 
the Patient--Post-Acute Care (PAC) measure, pursuant to section 
1899B(c)(1)(E) of the Act, beginning with October 1, 2020 discharges.
c. Update to the Discharge to Community--Post Acute Care (PAC) Long-
Term Care Hospital (LTCH) Quality Reporting Program (QRP) Measure
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19517), we 
proposed 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 
proposed 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 ``Final 
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 invited public comment on this proposal and received several 
comments. A discussion of these comments, along with our responses, 
appears in this final rule.
    Comment: All commenters, except MedPAC, supported the proposed 
exclusion of baseline NF residents from the Discharge to Community--PAC 
LTCH QRP measure. Supportive commenters referred to their 
recommendation of this exclusion in prior years and appreciated CMS' 
willingness to consider and implement stakeholder feedback. A commenter 
suggested that CMS instead consider other quality measures for NF 
residents, such as functional status measures, to determine whether 
residents receive the

[[Page 42535]]

appropriate standard of care they need in a long-term NF stay. Two 
commenters requested that claims data be modified to indicate whether a 
patient is a NF resident so that the measure can be replicated with 
existing CMS claims data.
    Response: We thank the commenters for their support of the proposed 
exclusion of baseline NF residents from this measure and for their 
recommendations for future consideration.
    Comment: MedPAC did not support the proposed exclusion of baseline 
NF residents from the Discharge to Community--PAC LTCH QRP measure. 
They suggested that CMS instead expand their definition of ``return to 
the community'' to include baseline nursing home residents returning to 
the nursing home where they live, as this represents their home or 
community. MedPAC also stated that providers should be held accountable 
for the quality of care they provide for as much of their Medicare 
patient population as feasible.
    Response: We agree that providers should be accountable for quality 
of care for as much of their Medicare population as feasible; we 
endeavor to do this as much as possible, only specifying exclusions we 
believe are necessary for measure validity. We also believe that 
monitoring quality of care and outcomes is important for all PAC 
patients, including baseline NF residents who return to a NF after 
their PAC stay. We publicly report several long-stay resident quality 
measures on Nursing Home Compare including measures of hospitalization 
and emergency department visits.
    Community is traditionally understood as representing non-
institutional settings by policy makers, providers, and other 
stakeholders. Including long-term care NF in the definition of 
community would confuse this long-standing concept of community and 
would misalign with CMS' definition of community in patient assessment 
instruments. CMS conceptualized this measure using the traditional 
definition of ``community'' and specified the measure as a discharge to 
community measure, rather than a discharge to baseline residence 
measure.
    Baseline NF residents represent an inherently different patient 
population with not only a significantly lower likelihood of discharge 
to community settings, but also a higher likelihood of post-discharge 
readmissions and death compared with PAC patients who did not live in a 
NF at baseline. The inherent differences in patient characteristics and 
PAC processes and goals of care for baseline NF residents and non-NF 
residents are significant enough that we do not believe risk adjustment 
using a NF flag would provide adequate control. While we acknowledge 
that a return to nursing home for baseline NF residents represents a 
return to their home, this outcome does not align with our measure 
concept. Thus, we have chosen to exclude baseline NF residents from the 
measure.
    Comment: A commenter requested that CMS provide the definition of 
``long-term'' NF stay in the proposed measure exclusion.
    Response: We have further clarified the definition of long-term NF 
stay in the final measure specifications, ``Final 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. A 
long-term NF stay is identified by the presence of a non-SNF PPS MDS 
assessment in the 180 days preceding the qualifying prior acute care 
admission and index SNF stay.
    After consideration of the public comments we received, we are 
finalizing our proposal to exclude baseline NF residents from the 
Discharge to Community--PAC LTCH QRP measure.
5. LTCH QRP Quality Measures, Measure Concepts, and Standardized 
Patient Assessment Data Elements Under Consideration for Future Years: 
Request for Information
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19517 through 
19518), we sought 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 this table for future years in the LTCH QRP.

 Future Measures, Measure Concepts, and Standardized Patient Assessment
       Data Elements (SPADEs) Under Consideration for the LTCH QRP
------------------------------------------------------------------------
 
-------------------------------------------------------------------------
                  Quality Measures and Measure Concepts
------------------------------------------------------------------------
Functional mobility outcomes.
Sepsis.
Opioid use and frequency.
Exchange of electronic health information and interoperability.
Nutritional status.
------------------------------------------------------------------------
          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.
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.
------------------------------------------------------------------------

    In the proposed rule (84 FR 19518) we noted that, while we will not 
be responding to specific comments submitted in response to this 
Request for Information in this FY 2020 IPPS/LTCH PPS final rule, we 
intend to use this input to inform our future measure and SPADE 
development efforts.
    We received several comments on this Request for Information, which 
are summarized below. We appreciate the input provided by commenters.
    Comment: Several commenters supported the measures under 
consideration for future years in the LTCH QRP. A commenter supported 
the functional mobility outcomes future measure, as it could help to 
further align

[[Page 42536]]

quality measurement across post-acute care. Another commenter supported 
a future sepsis measure. Regarding the proposed opioid use measure 
concept, a few commenters were concerned with how to best balance the 
growing risks and consequences of Opioid Use Disorder with the need for 
ready access to appropriate pain medication. The commenters stated that 
these measure concepts should not result in unintended consequences 
that leave patients without access to critical treatments for pain 
management. For the exchange of electronic health information and 
interoperability future measure, a few commenters acknowledged the need 
to share patient information with other health care providers, however, 
they were concerned that challenges may impede this strategy to reduce 
burden, such as cost, uneven and slow development, limitations, varying 
technological proficiency, and difference in standards for meeting 
interoperability. Several commenters supported the inclusion of a 
nutritional status measure in the LTCH QRP and recommended that 
existing inpatient hospital malnutrition focused measures be used in 
the LTCH setting to identify poor nutritional status and subsequent 
treatment to improve outcomes for patients. A commenter also requested 
the addition of a standardized patient experience survey to the LTCH 
QRP. In addition, a commenter recommended the inclusion of quality 
measures to ensure high quality care for those with mental and/or 
substance use disorders.
    Regarding the SPADEs under consideration for future years in the 
LTCH QRP, a commenter supported cognitive complexity, dementia, health 
disparities and risk factors and suggested these are also relevant data 
elements for ambulatory and acute care settings. Some commenters 
requested more information on the future SPADEs. A commenter supported 
the dementia SPADE, as cognitive impairment can affect a beneficiary's 
ability to participate in his or her care in PAC settings, in addition 
to managing co-occurring chronic conditions and medications after 
discharge. A commenter supported the collection of the bowel and 
bladder incontinence SPADE and another commenter agreed with the future 
inclusion of the care preference SPADE, because advance directives and 
caregivers are important in effective discharge planning and 
facilitates transfers between levels of care. However, a few commenters 
believed that given their severity and conditions, many LTCH patients 
are unable to plan their future care with health professionals and must 
rely on a surrogate decision maker. A commenter supported the caregiver 
status SPADE because these individuals are more likely to communicate 
with health professionals, coordinate care, and help manage emotional 
and behavioral health issues. A commenter described a future desired 
list of social risk variables in response to the health disparities and 
risk factors SPADE, including literacy, marital status, live-in home 
support, family support structure, and home health resources.
6. 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, 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 admission and discharge 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 in 
this final rule, and believe this testing supports the use of the 
SPADEs in our PAC assessment instruments. Therefore, in the FY 2020 
IPPS/LTCH PPS proposed rule (84 FR 19518 through 19552), we proposed to 
adopt many of the same SPADEs that we previously proposed to adopt, 
along with other SPADEs.
    In that proposed rule, we proposed 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.

[[Page 42537]]

Beginning with the FY 2023 LTCH QRP, we proposed 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 also proposed that LTCHs that submit the Hearing, Vision, Race, 
and Ethnicity SPADEs with respect to admission 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 SPADEs in this final rule, 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 SPADEs. In selecting the SPADEs in this final rule, 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 in this final rule, 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 PAC facilities (26 LTCHs, 60 SNFs, 22 IRFs, and 35 
HHAs) from November 2017 to August 2018 to evaluate the feasibility, 
reliability, and validity of the candidate data elements across PAC 
settings. The 3,121 patients and residents with an admission assessment 
included 507 in LTCHs, 1,167 in SNFs, 794 in IRFs, and 653 in HHAs. 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 previously described. 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.
    Comment: Some commenters supported the goals of standardization as 
well as the SPADEs proposed in this rule. A commenter recognized that 
data standardization will help facilitate appropriate payment reforms 
and appropriate quality measures.
    Response: We thank the commenters for their support of the goals of 
standardization and of the proposed SPADEs. We selected the proposed 
SPADEs in part because of the attributes that the commenters noted.
    Comment: A commenter noted strong support for the goals of the 
IMPACT Act and for CMS' goals of ensuring that patient assessment 
practices support effective care plans and transitions, but expressed 
concern about the scope and timing of proposed changes, including the 
SPADEs.
    Response: We thank the commenter for the support for the goals of 
the IMPACT Act and appreciate the concern about the proposed changes. 
Since we issued the FY 2018 IPPS/LTCH PPS final rule (82 FR 37990 
through 38589), LTCHs have had an opportunity to familiarize themselves 
with other new reporting requirements that we have adopted under the 
IMPACT Act and prepare for additional changes. We have provided regular 
updates to stakeholders and gathered feedback through Special Open Door 
Forums and other events as described in our proposal. We intend to 
monitor and evaluate SPADEs as they are submitted, and to continue to 
engage stakeholders around ways the SPADEs could be best used in the 
PAC quality programs. We will continue to communicate and collaborate 
with stakeholders by soliciting input on use of the SPADEs in the LTCH 
QRP through future rulemaking.
    Comment: Some commenters stated support but noted reservations. A 
commenter described the SPADEs as an appropriate start, but noted that 
the SPADEs cannot stand alone, and must be built upon to be useful for 
risk adjustment and quality measurement. Similarly, another commenter 
suggested CMS continue working with clinicians and researchers to 
ensure that the SPADEs are collecting valid, reliable, and useful data, 
and to continue to refine and explore new data elements for 
standardization.
    Response: We agree with the commenter's statement that the SPADEs 
are an appropriate start for standardization, but we disagree that they 
cannot stand alone. While we intend to evaluate the SPADEs as they are 
submitted and explore additional opportunities for standardization, we 
also believe that the SPADEs as proposed represent an important core 
set of information about clinical status and patient characteristics 
and they will be useful for quality measurement. We welcome continued 
input, recommendations, and feedback from stakeholders about ways to 
improve assessment and quality measurement for PAC providers including 
ways that the SPADEs could be used in the LTCH QRP. Input can be shared 
with CMS through our PAC Quality Initiatives email address: 
[email protected].
    Comment: A commenter suggested CMS consider ways to incentivize PAC 
providers to adopt health information technology to support these 
efforts to standardize patient data. This commenter noted that the 
transfer of data to and from PAC settings often occurs via cumbersome, 
resource-intensive manual processes and that common data reporting 
processes alone will not achieve interoperability goals.
    Response: We appreciate the commenter's recommendation. It is our 
intention to use the SPADE data to inform the common standards and 
definitions to facilitate interoperable exchange of data. We believe 
that a core, standardized set of data elements that could be shared 
across PAC and other provider types is an important first step to 
foster this interoperability between providers. We are hopeful that by 
requiring the collection of standardized data, the SPADEs may spur 
providers to adopt health information technology that eases the burden 
associated with data collection and data exchange. Further, we believe 
that the collection of these SPADEs reflect common clinical practice 
and will improve discharge planning and errors that occur during 
transition from one setting to the next. While the collection of the 
SPADEs is one of many tasks to supporting interoperability, and will 
take into consideration how best to decrease

[[Page 42538]]

burden from data collection including our manual processes. CMS will 
take into consideration ways to help incentivize providers to adopt 
health information technology.
    Comment: A commenter questioned which clinical specialties (for 
example, RN, PT, OT, Psychologist) would be responsible for collecting 
the proposed SPADEs, and recommended that CMS clarify the member of the 
healthcare team they anticipate collecting the information, if CMS has 
specific expectations.
    Response: We do not require that a certain type of clinician 
complete assessments; the SPADEs have been developed so that any 
clinician who is trained in the administration of the assessment will 
be able to administer it correctly.
    Comment: A commenter expressed concerns about the level of evidence 
to support the SPADEs shared by CMS from the National Beta Test. These 
include the lack of representativeness of LTCHs included in the sample, 
the reported exclusion of patients with communication and cognitive 
impairments, as well as the exclusion of non-English speaking patients. 
The commenter described how these concerns compromise their confidence 
in the findings of the National Beta Test.
    Response: In a supplementary document to the proposed rule (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 described key findings from 
the National Beta Test related to the proposed SPADEs. We also referred 
readers to an initial volume of the National Beta Test report that 
details the methodology of the field test (``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). Additional volumes of the 
National Beta Test report will be available in late 2019. These volumes 
contain supplementary analyses of the SPADEs that may be of interest to 
stakeholders.
    To address the commenter's specific concerns about the lack of 
representativeness of LTCHs included in the National Beta Test, we note 
that the National Beta Test was designed to generate valid and robust 
national SPADE performance estimates for each of the four PAC provider 
types. This required acceptable geographic diversity, sufficient sample 
size, and reasonable coverage of the range of clinical characteristics. 
To meet these requirements, the National Beta Test was carefully 
designed so that data could be collected from a wide range of 
environments (such as geographic regions, and PAC providers of 
different types, sizes, and ownership), allowing for thorough 
evaluation of candidate SPADE performance in all PAC settings. The 
approach included a stratified random sample, to maximize 
generalizability, and subsequent analyses included extensive checks on 
the sampling design. We contend that performance of the SPADEs in LTCHs 
in the National Beta Test is generalizable, given the study design and 
range of LTCHs that were included. LTCH assessments in the National 
Beta Test were collected from 25 LTCHs in the 14 geographic markets in 
which the field test was conducted, and included for profit and non-
profit facilities in metropolitan and micropolitan areas, ranging in 
size from 31 to 675 beds.
    The National Beta Test did not exclude non-communicative patients/
residents; rather, it had two distinct samples, one of which focused on 
patients/residents who were able to communicate, and one of which 
focused on patient/residents who were not able to communicate. The 
assessment of non-communicative patients/residents differed primarily 
in that observational assessments were substituted for some interview 
assessments. Non-English-speaking patients were excluded from the 
National Beta Test due to feasibility constraints during the field 
test. Including limited English proficiency patients/residents in the 
sample would have required the Beta test facilities to engage or 
involve translators during the test assessments. We anticipated that 
this would have added undue complexity to what facilities/agencies were 
being asked to do, and would have undermined the ability of facility/
agency staff to complete the requested number of assessments during the 
study period. Moreover, there is strong existing evidence for the 
feasibility of all clinical patient/resident interview SPADEs included 
in this proposed rule (BIMS [section VIII.C.7.b in this final rule], 
Pain Interference [section VIII.C.7.d in this final rule], PHQ [section 
VIII.C.7.b in this final rule]) when administered in other languages, 
either through standard PAC workflow as tested and currently collected 
in the MDS 3.0 or through rigorous translation and testing such as the 
PHQ. For all these reasons, we determined that the performance of 
translated versions of these patient/resident interview SPADEs did not 
need to be further evaluated. In addition, because their exclusion did 
not threaten our ability to achieve acceptable geographic diversity, 
sufficient sample size, and reasonable coverage of the range of PAC 
patient/resident clinical characteristics, the exclusion of limited 
English proficiency patients/residents was not considered a limitation 
to interpretation of the National Beta Test results.
    Comment: A commenter also remarked on the lack of information about 
clinical characteristics that has been shared with stakeholders, 
limiting their ability to draw conclusions about the data, and 
requested that CMS release the data from the National Beta Test to be 
analyzed by third parties.
    Response: We shared both quantitative and qualitative findings from 
the National Beta Test with stakeholders at a public meeting on 
November 27, 2018. For each SPADE proposed in this rule within the 
clinical categories in the IMPACT Act, we provided information in the 
supplementary documents to the proposed rule (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) on the feasibility and 
reliability based on findings from the National Beta Test.
    We are in the process of writing the final report for the National 
Beta Test, which includes the clinical SPADEs in this rule as well as 
additional data elements. Volume 2 of that report (``Development and 
Evaluation of Candidate Standardized Patient Assessment Data Elements. 
Findings from the National Beta Test (Volume 2)'') was posted on CMS' 
website in March 2019 (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 other volumes will be available in late 2019. In 
addition, we are committed to making data available for researchers and 
the public to analyze in a way that protects the privacy of patients 
and providers who participated

[[Page 42539]]

in the National Beta Test. We are in the process of creating research 
identifiable files that we anticipate will be available through a data 
use agreement sometime in 2019.
    Comment: Several commenters expressed concerns with respect to the 
scope of the standardized patient assessment data proposals. These 
commenters were concerned that the proposed standardized patient 
assessment data reporting requirements will impose significant burden 
on providers, given the volume of new standardized patient assessment 
data elements that were proposed to be simultaneously added to the LCDS 
within a short timeframe. Commenters calculated the addition of the 
proposed SPADEs to increase the time spent completing the LCDS by 37 
percent and called on CMS to offset the expansion of the LCDS with 
removal of other data elements or requirements. A commenter remarked on 
the significant additional staff time that collecting and reporting the 
SPADEs would entail, and noted that even with electronic medical 
records in place, significant time and resources are spent on 
developing linkages and reporting systems between the EMR and CMS' 
systems.
    Response: We acknowledge the additional burden that the SPADEs will 
impose on providers and patients. Our development and selection process 
for the SPADEs prioritized data elements essential to comprehensive 
patient care. We maintain that there will be significant benefit 
associated with each of the SPADEs to providers and patients, in that 
they are clinically useful (for example, for care planning), they 
support patient-centered care, and they will promote interoperability 
and data exchange between providers. During the SPADE development 
process, we were cognizant of the changes that providers will need to 
make to implement these additions to the LCDS. In FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38451 through 38452), we provided information about 
goals, scope, and timeline for implementing SPADEs, as well as updated 
LTCHs about ongoing development and testing of data elements through 
other public forums. We believe that LTCHs have had an opportunity to 
familiarize themselves with other new reporting requirements that we 
have adopted under the IMPACT Act and prepare for additional changes.
    Comment: Several commenters expressed concern that this additional 
burden was not justified because, in their view, there was limited or 
no evidence for the SPADEs to improve patient care. A commenter noted 
that there is no minimum number of data elements that must be collected 
to satisfy the IMPACT Act, and expressed concerns about the relevance 
of cross-setting assessments and measures, given the differences in the 
patient populations that they serve (for example, highest-complexity 
patients in LTCHs). Other commenters stated that proposal of the SPADEs 
was inconsistent with the Meaningful Measures initiative and the 
principle to consider whether the costs of a measure outweigh its 
benefit.
    Response: The clinical SPADEs proposed in this rule are the result 
of an extensive consensus vetting process in which experts and 
stakeholders were engaged through TEPs, Special Open Door Forums, and 
posting of interim reports and other documents on the CMS website. 
Results of these activities provide evidence that experts and providers 
believe the proposed SPADEs have the potential for measuring quality, 
describing case mix, and improving care. We refer the commenter to the 
most recent TEP report: A summary of the most recent TEP meeting 
(September 17, 2018) titled ``SPADE Technical Expert Panel Summary 
(Third Convening)'', which 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. Therefore, we have provided evidence that the SPADEs have 
the potential for improving quality and utility for describing case 
mix.
    With regard to the consistency of our proposal with the larger 
Meaningful Measures framework, the proposed SPADEs correspond to 
several Meaningful Measures Areas. Specifically, the SPADEs will enable 
transfer of health information and interoperability; support 
prevention, treatment, and management of mental health; collect data 
that will support measurement of patient reported functional outcomes; 
as well as contribute to other Meaningful Measures Areas. We also note 
Meaningful Measures' priority of focusing health care quality efforts 
on what matters most to patients, including quality of care, care 
preferences, and overall experience. Developing appropriate and useful 
measures of quality of care that empower patients to make choices about 
their healthcare are only possible with a robust and valid set of data 
elements, such as the SPADEs.
    Comment: Some commenters noted that many of the proposed SPADEs 
occur too infrequently among LTCH patients to be useful, and that many 
of the proposed SPADEs will not be applicable or not able to be 
completed for LTCH patients.
    Response: We appreciate the commenters' concern that clinical 
treatments or response categories documented by some SPADEs are 
uncommon overall, and/or unlikely in the LTCH setting. We understand 
that not all SPADEs will be equally relevant to all patients and/or PAC 
providers. However, we assert that even relatively rare treatments or 
clinical situations, such as patient undergoing chemotherapy while 
receiving PAC services, or a having a feeding tube, are important to 
document, both for care planning within the setting and for transfer of 
information to the next setting of care. We note that the assessment of 
many of the less frequently occurring treatments and conditions is 
formatted as a ``check all that apply'' list, which minimizes burden. 
When treatments do not apply the assessor need only check one row for 
``None of the Above.'' Additionally, skip patterns in the assessment 
tool exempt patients who are unable to communicate from patient 
interview items (for example, BIMS, PHQ-2 to 9).
    Comment: Some commenters stated that the time burden (as in, 
``time-to-complete'') associated with the clinical SPADEs was 
underestimated. A commenter stated that because testing conditions 
focused on cognitively intact, English-speaking patients with no speech 
or language deficits, the estimates of impact to providers' time and 
resources is inadequate. Another commenter noted that based on 
experience of their own LTCHs who participated in the National Beta 
Test, it took approximately 30 minutes to complete the assessment for 
patients who were alert and oriented but took over an hour to complete 
for others who required constant re-directing. Other commenters believe 
that CMS overlooked the additional staff time necessary for reviewing, 
auditing, and transmitting the SPADEs to CMS; training clinical staff; 
or working with EHR vendors, and therefore, underestimated burden. This 
commenter suggested CMS revise the estimated burden for the proposed 
SPADEs.
    Response: We wish to clarify that time-to-complete estimates from 
the National Beta Test included the time spent both to collect data, 
including the review of the medical record, if needed, and to enter the 
data elements into a tablet. We note that time-to-complete estimates 
were calculated using the data from Facility/Agency Staff only, and not 
Research Nurses, who completed more

[[Page 42540]]

training and conducted more assessments overall than the Facility/
Agency staff.
    We also wish to clarify that National Beta Test did exclude 
patients/residents who were not able to communicate in English, but did 
not categorically exclude patients with cognitive impairment or 
patients with speech or language deficits. Therefore, we believe that 
our estimates of time-to-complete capture the general population of 
LTCH patients, including those with communication impairments.
    Comment: To reduce administrative burden, several commenters 
recommended changes to when and how SPADEs would be collected. These 
recommendations included collecting data only at admission when answers 
are unlikely to change between admission and discharge, reducing the 
speed and scope of SPADE implementation, adopting a staged 
implementation or only a subset of the proposed data elements that 
demonstrate high utility and reliability in the LTCH setting, and that 
CMS explore options for obtaining these data via claims or voluntary 
reporting only.
    Response: We appreciate the commenters' recommendations. To support 
data exchange between settings, and to support quality measurement, 
section 1899B(b)(1)(A) of the Act requires that the SPADEs be collected 
with respect to both admission and discharge. In the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19518), we proposed that LTCHs that submit 
four SPADEs with respect to admission will be deemed to have submitted 
those SPADEs with respect to both admission and discharge because we 
asserted that it is unlikely that the assessment of those SPADEs at 
admission would differ from the assessment of the same SPADEs at 
discharge. We note that a patient's ability to hear or ability to see 
is more likely to change between admission and discharge than, for 
example, a patient's self-report of his or her race, ethnicity, 
preferred language, or need for interpreter services. The Hearing and 
Vision SPADEs are also different from the other SPADEs (that is, Race, 
Ethnicity, Preferred Language, and Interpreter Services) because 
evaluation of sensory status is a fundamental part of the ongoing 
nursing assessment conducted for LTCH patients. Therefore, clinically 
significant changes that occur in a patient's hearing or vision status 
during the LTCH stay would be captured as part of the clinical record 
and communicated to the next setting of care, as well as taken into 
account during discharge planning as a part of standard best practice. 
As discussed in section VIII.C.7.e., section VIII.C.7.f.(2)(a) and 
section VIII.C.7.f.(2)(b), we are finalizing our policy to deem LTCHs 
that submit the Hearing, Vision, Race, Ethnicity, Preferred Language, 
and Interpreter Services SPADEs with respect to admission to have 
submitted with respect to both admission and discharge.
    Regarding the speed and scope of SPADE implementation, and the 
commenter's recommendation to adopt a staged approach to 
implementation, we note that since we issued the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38451 through 38452), LTCHs have had an opportunity 
to familiarize themselves with other new reporting requirements that we 
have adopted under the IMPACT Act and prepare for additional changes. 
We have provided regular updates to stakeholders and gathered feedback 
through Special Open Door Forums and other events as described in our 
proposal. We note that these items span many substantive clinical areas 
and patient characteristics, and are comprised of a mix of patient 
interview and non-interview assessments. We contend that we have been 
highly selective when identifying SPADEs, and that our selections 
reflect a balanced approach to assessor and patient burden versus the 
need for assessment data to support care planning, foster 
interoperability, and inform future quality measures.
    Regarding the commenter's recommendation to adopt only a subset of 
the proposed data elements that demonstrate high utility and 
reliability in the LTCH setting, we note that part of our process in 
evaluating candidate SPADEs was clinical relevance to all PAC provider 
types. We recognize that not all SPADEs will be equally salient to all 
PAC providers, but we selected clinical topics and a level of detail 
for the SPADEs that is important to patient care regardless of their 
care setting. We will take into consideration the recommendation to 
obtain patient data from claims data in future work.
    Comment: Some commenters encouraged CMS to create and make 
transparent a data use strategy and analysis plan for the SPADEs so PAC 
providers, including LTCHs, better understand how the agency will 
further assess the adequacy and usability of the SPADEs to support 
changes to payment and quality programs. A commenter stated that 
additional evaluation of SPADEs and their intended uses is needed prior 
to nationwide implementation and adoption. Another commenter noted 
appreciation for CMS' efforts to provide opportunities for stakeholder 
communication and input, but also recommended CMS develop additional 
lines of communication with stakeholders, such as a multi-disciplinary 
stakeholder workgroup representing all PAC settings to advise on 
strategic and operational implications of implementation and a data 
analytics advisory group to assist CMS in establishing a framework for 
SPADE analysis and ongoing assessment.
    Response: We appreciate the commenter's recommendations. It is our 
intention, as delineated by the IMPACT Act, to use the SPADE data to 
inform care planning, the common standards and definitions to 
facilitate interoperability, and to allow for comparing assessment data 
for standardized measures. In order to maintain open lines of 
communication with our stakeholders, we have used the public comment 
periods, TEPs, Subject Matter Expert working groups, stakeholder 
meetings, data forums, Medicare Learning Network (MLN) events, open 
door forums, help desks, in-person trainings, webinars with 
communication with the public, ``We Want to Hear From You'' sessions, 
and have had stakeholders serve as consultants on our measure work. If 
there are any other opportunities for communication and comment, we 
will publish those opportunities. We will continue to communicate with 
stakeholders about how the SPADEs will be used in quality programs, as 
those plans are established, by soliciting input during the development 
process and establishing use of the SPADEs in quality programs through 
future rulemaking.
    Comment: A commenter noted complexity and coding nuance related to 
the proposed SPADEs, stating that the SPADEs introduce a variety of 
different look-back periods (that is, 2 days, 3 days, 5 days, 7 days, 
and 2 weeks). The commenter implied that this could harm the quality of 
the data. The commenter went on to emphasize the importance of valid 
and reliable data collection, which they stated relies on CMS 
developing and making available all the necessary education and 
training for providers.
    Response: We agree that correct and consistent data collection 
practices are essential to accurate data. We wish to clarify that 
although multiple time frames were associated with individual data 
elements in the National Beta Test, this was for testing purposes only; 
a component of the National Beta Test was designed to investigate the 
stability of patients' responses and patterns of initiation and 
discontinuation of treatments at admission and discharge,

[[Page 42541]]

respectively. Each proposed SPADE for the LCDS had only one time frame 
associated with it, although we acknowledge that several SPADEs have 
different reference time periods. For example, the PHQ-2 to 9 asks 
about depressive symptoms in the last 2 weeks, because that time frame 
is consistent with the diagnostic criteria for depression. The pain 
interference interview asks about the last 5 days. The 5-day reference 
period was chosen to conform with similar data elements currently in 
use in the MDS 3.0 for SNFs, and because, when compared to a 3-day 
reference period in the National Beta Test, we found minimal 
differences. With regard to educational materials for assessors, we 
intend to provide comprehensive training materials for providers and 
ongoing support through our in-person and web-based trainings, guidance 
manuals, and website.
7. Standardized Patient Assessment Data by Category
a. Functional Status Data
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19519), we 
proposed 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 proposed 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 
proposed 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 previously listed 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 ``Final 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 to adopt the functional mobility data elements as 
SPADEs for use in the LTCH QRP.
    Comment: A commenter supported the adoption of the six proposed 
functional mobility data elements to the LTCH CARE Data Set as SPADEs 
for use in the LTCH QRP.
    Response: We appreciate the commenter's support.
    Comment: Several commenters were concerned about the addition of 
the six functional mobility data elements. The commenters stated that 
LTCHs admit high-acuity patients, and that these data elements are 
relevant for only a small proportion of LTCH patients. They also stated 
that CMS has not demonstrated the value of adding these data elements. 
Therefore, they do not believe the addition of these six data elements 
will provide useful information and the addition of these data elements 
would be burdensome.
    Response: We appreciate commenters' concerns about the burden 
associated with the six mobility data elements being added to the LTCH 
CARE Data Set. We recognize that any new data collection is associated 
with burden and take such concerns under consideration when selecting 
new data elements. To reduce the burden associated with collecting the 
functional mobility data, we have included skip patterns in Section GG 
to reduce the number of data elements that may need to be completed for 
any one LTCH patient. For example, if a patient cannot perform the 
activity of going up one step (or a curb) there is a skip pattern that 
allows the clinician to skip the 4 steps and 12 steps data elements. 
The inclusion of skip patterns means that only a subset of mobility 
data are needed for most LTCH patients. We also recognize that LTCH 
patients are critically ill and understand that ``activity not 
attempted'' codes may be used for higher-ability mobility data elements 
on admission for many patients. We note that for patients discharged to 
home (26 percent of LTCH patients in calendar year 2018) these mobility 
activities are relevant and useful for discharge planning.
    After consideration of the public comments we received, we are 
finalizing the six functional mobility data elements as SPADEs for use 
in the LTCH QRP as proposed.
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.\791\ 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,\792\ and because these 
assessments provide opportunity for improving quality of care.
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    \791\ 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.
    \792\ 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,793 794 795 and promising 
treatments for severe traumatic brain injury are currently

[[Page 42542]]

being tested.\796\ For older patients and residents diagnosed with 
depression, treatment options to reduce symptoms and improve quality of 
life include antidepressant medication and 
psychotherapy,797 798 799 800 and targeted services, such as 
therapeutic recreation, exercise, and restorative nursing, to increase 
opportunities for psychosocial interaction.\801\
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    \793\ Casey D.A., Antimisiaris D., O'Brien J. (2010). Drugs for 
Alzheimer's Disease: Are They Effective? Pharmacology & 
Therapeutics, 35, 208-11.
    \794\ 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.
    \795\ 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.
    \796\ 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.
    \797\ 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.
    \798\ Arean P.A., Cook B.L. (2002). Psychotherapy and combined 
psychotherapy/pharmacotherapy for late life depression. Biological 
Psychiatry, 52(3), 293-303.
    \799\ 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.
    \800\ 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.
    \801\ 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 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 in this final rule.
    Comment: A few commenters were supportive of the proposal to adopt 
the BIMS, CAM, and PHQ-2 to 9 as SPADEs on the topic of cognitive 
function and mental status. A commenter agreed that standardizing 
cognitive assessments will allow providers to identify changes in 
status, support clinical decision-making, and improve care continuity 
and interventions.
    Response: We thank the commenters for the support and feedback. We 
selected the Cognitive Function and Mental Status data elements for 
proposal as standardized data in part because of the attributes that 
the commenters noted.
    Comment: A few commenters noted limitations of these SPADEs to 
fully assess all areas of cognition and mental status, particularly 
mild to moderate cognitive impairment, and performance deficits that 
may be related to cognitive impairment. A few commenters recommended 
CMS continue exploring assessment tools on the topic of cognition and 
to include a more comprehensive assessment of cognitive function for 
use in PAC settings, noting that highly vulnerable patients with a mild 
cognitive impairment cannot be readily identified through the current 
SPADEs.
    Response: We have strived to balance the scope and level of detail 
of the data elements against the potential burden placed on patients 
and providers. In our past work, we evaluated the potential of several 
different cognition assessments for use as standardized data elements 
in PAC settings. We ultimately decided on the BIMS, CAM, and PHQ-2 to 9 
data elements as a starting point. We would welcome continued input, 
recommendations, and feedback from stakeholders about additional data 
elements for standardization. Input can be shared with CMS through our 
PAC Quality Initiatives email address: 
[email protected].
    Comment: Regarding future use of these data elements, a commenter 
recommended that CMS monitor the use of the cognition and mental status 
SPADEs as risk adjustors and make appropriate adjustments to 
methodology as needed.
    Response: We appreciate the commenter's recommendations. It is our 
intention, as delineated by the IMPACT Act, to use the cognition and 
mental status SPADEs to inform care planning, the common standards and 
definitions to facilitate interoperability, and to allow for comparing 
assessment data for standardized measures. We will continue to 
communicate with stakeholders about how the SPADEs will be used in 
quality programs, as those plans are established, by soliciting input 
during the development process and establishing use of the SPADEs 
through future rulemaking.
    Comment: A commenter recommended that CMS be cautious in their 
interpretation of SPADEs related to cognitive function and mood, out of 
consideration of the recent past experience of critically ill patients 
(for example, ICU stay, sedation, mechanical ventilation). The 
commenter described how cognitive impairment is nearly universal in 
LTCH patients who have been discharged from the ICU, and that 
depression screening may function differently in this population, given 
the level of somatic complaints related to patients' physical illness.
    Response: We appreciate the commenter's recommendation. We intend 
to monitor and conduct further analyses on the data submitted via the 
SPADEs to better understand the performance of the data elements among 
different populations and to determine the suitability of the data 
elements for other uses (for example, risk adjustment, payment). 
Notwithstanding the differences in how some patient types may respond 
to individual data elements, we believe that the SPADEs have immediate 
value for providers as they inform care planning and care transitions.
 Brief Interview for Mental Status (BIMS)
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19520 through 
19521), we proposed 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.\802\ This makes 
assessment of

[[Page 42543]]

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.\803\
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    \802\ 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.
    \803\ 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 ``Final 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 ``Final 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 
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 patient assessment data elements. However, taking 
together the importance of assessing for cognitive status, stakeholder 
input, and strong test results, we proposed 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.
    Comment: Several commenters support the use of the BIMS to assess 
cognitive function and mental status. A commenter was specifically 
supportive of the collection of BIMS at both admission and discharge 
and believes it will result in more complete data and better care. 
Another commenter appreciated that the BIMS results in a

[[Page 42544]]

score, which improves the usability of the assessment.
    Response: We thank the commenters for their support of the BIMS 
data element.
    Comment: Several commenters stated that the BIMS fails to detect 
mild cognitive impairment or functional cognition, differentiate 
cognitive impairment from a language impairment, link impairment to 
functional limitation, or identify issues with problem solving and 
executive function. A commenter recommended use of the Development of 
Outpatient Therapy Payment Alternatives (DOTPA) items for PAC as well 
as a screener targeting functional cognition.
    Response: We recognize that the BIMS assesses components of 
cognition and does not, alone, provide a comprehensive assessment of 
potential cognitive impairment. We would like to clarify that any SPADE 
or set of data elements is intended as a minimum assessment and would 
not limit the ability of providers to conduct a more comprehensive 
assessment of cognition to identify the complexities or potential 
impacts of cognitive impairment that the commenter describes.
    We evaluated the suitability of the DOTPA, as well as other 
screening tools that targeted functional cognition, by engaging our 
TEP, through ``alpha'' feasibility testing, and through soliciting 
input from stakeholders. At the second TEP meeting in March 2017, 
members questioned the use of data elements that rely on assessor 
observation and judgment, such as DOTPA CARE tool items, and favored 
other assessments of cognition that required patient interview or 
patient actions. The TEP also discussed performance-based assessment of 
functional cognition. These are assessments that require patients to 
respond by completing a simulated task, such as ordering from a menu, 
or reading medication instructions and simulating the taking of 
medications, as required by the Performance Assessment of Self-Care 
Skills (PASS) items.
    In Alpha 2 feasibility testing, which was conducted between April 
and July 2017, we included a subset of items from the DOTPA as well as 
the PASS. Findings of that test identified several limitations of the 
DOTPA items for use as SPADEs, such as relatively long to administer (5 
to 7 minutes), especially in the LTCH setting. Assessors also indicated 
that these items had low relevance for SNF and LTCH patients. In 
addition, interrater reliability was highly variable among the DOTPA 
items, both overall and across settings, with some items showing very 
low agreement (as low as 0.34) and others showing excellent agreement 
(as high as 0.81). Similarly, findings of the Alpha 2 feasibility test 
identified several limitations of the PASS for use as SPADEs. The PASS 
was relatively time-intensive to administer (also 5 to 7 minutes), many 
patients in HHAs and IRFs needed assistance completing the PASS tasks, 
and missing data were prevalent. Unlike the DOTPA items, interrater 
reliability was consistently high overall for PASS (ranging from 0.78 
to 0.92), but the high reliability was not deemed to outweigh 
fundamental feasibility concerns related to administration challenges. 
A summary report for the Alpha 2 feasibility testing titled 
``Development and Maintenance of Standardized Cross Setting Patient 
Assessment Data for Post-Acute Care: Summary Report of Findings from 
Alpha 2 Pilot Testing'' is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/Alpha-2-SPADE-Pilot-Summary-Document.pdf.
    Feedback was obtained on the DOTPA and other assessments of 
functional cognition through a call for input that was open from April 
26, 2017 to June 26, 2017. While we received support for the DOTPA, 
PASS, and other assessments of functional cognition, commenters also 
raised concerns about the reliability of the DOTPA, given that it is 
based on staff evaluation, and the feasibility of the PASS, given that 
the simulated medication task requires props, such as a medication 
bottle with printed label and pill box, which may not be accessible in 
all settings. A summary report for the April 26 to June 26, 2017 public 
comment period titled ``Public Comment Summary Report 2'' is available 
at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/Public-Comment-Summary-Report_Standardized-Patient-Assessment-Data-Element-Work_PC2_Jan-2018.pdf.
    Based on the input from our TEP, results of alpha feasibility 
testing, and input from stakeholders, we decided to propose the BIMS 
for standardization at this time due to the body of research literature 
supporting its feasibility and validity, its relative brevity, and its 
existing use in the MDS and IRF-PAI.
    Comment: Some commenters noted that the BIMS would likely not be 
completed for many LTCH patients upon admission, as many patients may 
be on a ventilator and/or may be unresponsive or unable to make him or 
herself understood. A commenter stated that they do not believe that 
CMS has adequately demonstrated the value of adding the BIMS data 
elements to the LCDS, and both commenters requested that the BIMS not 
be required for LTCHs.
    Response: We appreciate the commenters' concern. There are coding 
responses available in the BIMS to denote patients who are unable to 
complete the assessment (for example, patients who are rarely or never 
understood, patients who give nonsensical responses to the interview 
questions). The BIMS will be considered to have been completed for the 
purposes of the SPADE if an assessor uses these coding responses. 
Although a substantial share of LTCH patients may not be able to 
complete the BIMS at admission, we contend that the BIMS assessment 
should be attempted for all patients who are able to communicate by any 
means. We believe it will be feasible for many patients and that the 
care provided to these patients will benefit from having a standardized 
assessment of cognition that can be exchanged across settings. After 
consideration of the public comments we received, we are finalizing our 
proposal to adopt the BIMS as standardized patient assessment data 
beginning with the FY 2022 LTCH QRP as proposed.
 Confusion Assessment Method (CAM)
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19521 through 
19522), we proposed 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.\804\ Assessing these signs and symptoms of 
delirium is clinically relevant for care planning by PAC providers.
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    \804\ 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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[[Page 42545]]

    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 proposed 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 ``Final 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 ``Final 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/IMPACT-Act-Downloads-and-Videos.html.
    Taking together the importance of assessing for delirium, 
stakeholder input, and strong test results, we proposed 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.
    Comment: Several commenters support the use of the CAM to assess 
cognitive function and mental status, but noted that it lacks 
sensitivity to fully capture cognitive deficits. These commenters 
support CMS continuing to evaluate ways to assess cognitive function.
    Response: We thank the commenters for their support of the CAM data 
element and also recognize that the CAM assesses components of 
cognition and does not, alone, provide a comprehensive assessment of 
potential cognitive impairment.
    Comment: Some commenters had concerns with the use of the CAM in 
the LTCH setting. A commenter stated that the CAM is not sensitive 
enough to detect improvements in cognitive function within LTCH 
patients. This commenter did not support adoption of the CAM and 
recommended that CMS instead study alternative methods that would 
accurately assess cognitive function in the LTCH setting. Another 
commenter noted that the CAM is specifically designed to identify 
delirium only and may be too narrow in scope to prove useful.
    Response: We appreciate the commenters' concerns. We recognize that 
the CAM assesses components of cognition and does not, alone, provide a 
comprehensive assessment of potential cognitive impairment. As with any 
brief screening tool, we believe that the CAM has value as a universal 
assessment to identify patients in need of further clinical evaluation. 
We note that delirium occurs in up to half of patients/residents 
receiving PAC services,\805\ and signs and symptoms of delirium are 
associated with poor functional recovery,\806\ re-

[[Page 42546]]

hospitalization, and mortality.\807\ Hyperactive delirium--the type of 
delirium that manifests with agitation--makes up only a quarter of 
delirium cases.808 809 Delirium more commonly manifests as 
hypoactive, or ``quiet'' delirium,\810\ suggesting that brief, 
universal screening is appropriate. Moreover, because there are 
treatments for delirium that can be developed based on medication 
review, physical examination, laboratory tests, and evaluation of 
environmental factors,\811\ we believe that screening for delirium 
would support care planning and care transitions for these patients.
---------------------------------------------------------------------------

    \805\ Dan K. Kiely et al., ``Characteristics Associated with 
Delirium Persistence Among Newly Admitted Post-Acute Facility 
Patients,'' Journals of Gerontology: Series A (Biological Sciences 
and Medical Sciences), Vol. 59, No. 4, April 2004; Edward R. 
Marcantonio et al., ``Delirium Symptoms in Post-Acute Care: 
Prevalent, Persistent, and Associated with Poor Functional 
Recovery,'' Journal of the American Geriatrics Society, Vol. 51, No. 
1, January 2003.
    \806\ Marcantonio, Edward R., Samuel E. Simon, Margaret A. 
Bergmann, Richard N. Jones, Katharine M. Murphy, and John N. Morris, 
``Delirium Symptoms in Post-Acute Care: Prevalent, Persistent, and 
Associated with Poor Functional Recovery,'' Journal of the American 
Geriatrics Society, Vol. 51, No. 1, January 2003, pp. 4-9.
    \807\ Edward R. Marcantonio et al., Outcomes of Older People 
Admitted to Postacute Facilities with Delirium,'' Journal of the 
American Geratrics Society, Vol. 53, No. 6, June 2005.
    \808\ Inouye SK, Westendorp RG, Saczynski JS. Delirium in 
elderly people. Lancet 2014;383:911-922.
    \809\ Marcantonio ER. In the clinic: delirium. Ann Intern Med 
2011;154:ITC6-1-ITC6-1.
    \810\ Yang FM, Marcantonio ER, Inouye SK, et al. 
Phenomenological subtypes of delirium in older persons: patterns, 
prevalence, and prognosis. Psychosomatics2009;50:248-254
    \811\ Marcantonio ER. Delirium in Hospitalized Older Adults. N 
Engl J Med. 2017 Oct 12;377(15):1456-1466.
---------------------------------------------------------------------------

    Comment: A commenter encouraged CMS to make a CAM ``score'' part of 
the CAM SPADE. The commenter believes that LTCHs could make better and 
more immediate use of the results of the CAM assessment if it resulted 
in an easily interpretable score.
    Response: The LCDS guidance manual does not currently include 
instructions for scoring the CAM. When the CAM is implemented across 
the four PAC provider types as SPADE, we will standardize the guidance 
to be consistent with the current guidance for the CAM in the MDS 3.0 
for SNFs, which includes instructions for calculating a score. The 
calculation of the score and how the score is used is at the discretion 
of the provider. We chose not to include the score for the CAM as part 
of the SPADE to ensure that a diagnosis of delirium is ultimately 
conferred by a physician or other qualified provider. In its role as a 
SPADE, we do not intend the CAM to confer a diagnosis of delirium, only 
to indicate that delirium is likely present and that the patient 
requires further evaluation. However, we appreciate the commenter's 
recommendation and will take it into consideration as we evaluate and 
refine the SPADEs.
    Comment: A commenter believes the CAM would be difficult to 
administer and raised concerns about the training that staff would 
receive to ensure that administration is consistent and valid.
    Response: We appreciate the commenter's recommendation to provide 
clear training for administering the CAM and will take it into 
consideration as we revise the current training for the LTCHs. We 
intend to reinforce assessment tips and item rationale through 
training, open door forums, and future rulemaking efforts.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the CAM as standardized patient 
assessment data beginning with the FY 2022 LTCH QRP as proposed.
 Patient Health Questionnaire-2 to 9 (PHQ-2 to 9)
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19522 through 
19523), we proposed 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 in this final rule.
    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.\812 
813\ 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.
---------------------------------------------------------------------------

    \812\ Li, C., Friedman, B., Conwell, Y., & Fiscella, K. (2007). 
``Validity of the Patient Health Questionnaire 2 (PHQ-2) in 
identifying major depression in older people.'' J of the A 
Geriatrics Society, 55(4): 596-602.
    \813\ 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.
---------------------------------------------------------------------------

    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 
``Final 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

[[Page 42547]]

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,\814\ 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.
---------------------------------------------------------------------------

    \814\ 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.
---------------------------------------------------------------------------

    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 
included in recent, comprehensive field testing. In response to these 
comments, we carried out additional testing, and we provide our 
findings in this final rule.
    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 ``Final 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 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 the proposed rule, we 
proposed 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.
    Comment: A commenter supported the use of the PHQ-2 to 9 to assess 
cognitive function and mental status.
    Response: We thank the commenter for the support of the PHQ-2 to 9.
    Comment: A commenter noted confusion about how depression relates 
to cognitive function and the subsequent need for additional evaluation 
and treatment.
    Response: Section 1899(b)(1)(B)(ii) of the Act specifies the 
category of ``cognitive function, such as ability to express ideas and 
to understand, and mental status, such as depression and dementia.'' 
This category includes both cognitive function and mental status. The 
PHQ-2 to 9 data elements do not pertain to cognitive function, but do 
pertain to mental status.
    Comment: Several commenters expressed concern about the PHQ-2 to 9. 
Some commenters did not support adoption either because it was 
burdensome for staff and patients or because many LTCH patients do not 
have the cognitive function to comprehend the interview questions. Some 
commenters stated that asking a patient to consider a prior timeframe 
of 2 weeks was problematic because the typical LTCH patients are 
admitted after several days in the ICU, making them both unlikely to be 
able to respond accurately and likely to endorse depressive symptoms, 
given what they have recently experienced. A commenter shared results 
of the past internal study at their facility that identified 65 percent 
of admitted patients as clinically depressed. The commenter went on to 
inquire about what CMS hopes that additional PHQ-2 to 9 data will tell 
LTCHs.
    Response: We recognize the challenges faced by patients receiving 
care from LTCH providers. Patients in LTCH settings may not be able to 
communicate and many patients are admitted subsequent to acute care and 
intensive care. This item contains a response option that allows coding 
for when a patient is unable to communicate or otherwise unable to 
complete the interview. For example, patients who cannot recall the 
last 2 weeks would not be required to complete the interview. However, 
if a patient is able to comprehend the instructions and respond to the 
questions, those responses should never be considered inaccurate. This 
is a patient interview that asks a patient about his or her symptoms; 
the self-report of those symptoms is the gold standard and should not 
be questioned because of a patient's recent experiences.

[[Page 42548]]

    Regarding the commenter's concern that patients would be more 
likely to endorse depressive symptoms based on the prior acute care 
experiences, we acknowledge that may be the case, however, we believe 
these patients are perhaps some of the most likely to be experiencing 
the symptoms of depression and should be identified for further 
evaluation and treatment. In the National Beta Test, 38 percent of LTCH 
patients who were assessed with the PHQ-2 to 9 passed the threshold 
number of symptoms on the first two questions and went on to complete 
the additional seven questions, as compared to 28 percent of patients 
across all PAC provider types. This is evidence that LTCH patients in 
fact report higher rates of depressive symptoms than patients in other 
PAC settings. We believe the PHQ-2 to 9 is the most accurate and 
appropriate depression screening for the PAC population, including 
patients in LTCHs, and that assessing for depression is necessary for 
high-quality clinical care. We note that screening positive for 
depressive symptoms on the PHQ-2 to 9 does not confer a diagnosis of 
depression. Rather, it indicates that the patient requires further 
assessment by a clinician.
    Regardless of the length of stay of patients, the timeframe over 
which they may have been experiencing signs and symptoms of depression, 
and the types of circumstances that have led to their LTCH stay, it is 
the responsibility of the LTCH to deliver high quality care for all the 
symptoms or conditions a patient may have. Our proposal of the PHQ-2 to 
9 as SPADE is intended to improve patient care in LTCHs and across PAC 
provider types by ensuring that depression is assessed in every patient 
at admission and discharge. We believe the high prevalence of clinical 
depression in patients, as noted by a commenter, only highlights the 
need for universal screening.
    Comment: Some commenters questioned the validity of the PHQ-2 to 9 
because it is a based on a patient interview, rather than on a clinical 
assessment by a psychiatrist or psychologist.
    Response: The PHQ-2 to 9 is 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. Both the PHQ-9 \815\ and PHQ-2 
\816\ are reliable and valid measures of depression. Screening positive 
for depression with the PHQ-2 or PHQ-9 does not convey a diagnosis of 
depression, which requires a clinician's evaluation to consider the 
contribution of physical illness, situational conditions (for example, 
bereavement), the presence of additional symptoms (for example, mania) 
that may suggest other mental illness, and other factors to conclude 
that the patient has depression. Rather, positive screening for the 
signs and symptoms of depression with the PHQ-2 to 9 SPADE would 
identify patients who are in need of further evaluation and treatment.
---------------------------------------------------------------------------

    \815\ Kroenke K, Spitzer RL, Williams JWB. The PHQ-9: Validity 
of a Brief Depression Severity Measure. J Gen Intern Med. 2001 Sep; 
16(9): 606-613.
    \816\ Kroenke K, Spitzer RL, Williams JWB. The Patient Health 
Questionnaire-2: Validity of a Two-Item Depression Screener. Med 
Care. Vol. 41, No. 11 (Nov., 2003), pp. 1284-1292.
---------------------------------------------------------------------------

    Comment: Some commenters did not support the PHQ-2 to 9 because 
they stated it is unclear how it will be used to meaningfully improve 
care.
    Response: As we described in the supporting document to the 
proposed rule,\817\ depression is common in patients/residents 
receiving PAC services and associated with poor outcomes. A universal 
depression screening is therefore expected to improve patient outcomes 
by increasing the likelihood that depression will be identified and 
treated in LTCH patients. Regardless of the complexity of patients' 
medical condition, it is the responsibility of the PAC setting to 
deliver high quality care for all the symptoms or conditions a patient 
may have, including depression.
---------------------------------------------------------------------------

    \817\ ``Final 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.
---------------------------------------------------------------------------

    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the PHQ-2 to 9 data elements as 
standardized patient assessment data beginning with the FY 2022 LTCH 
QRP as proposed.
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-

[[Page 42549]]

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 in this final rule. 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.
    Comment: A commenter was supportive of collecting these data 
elements, noting that collection will help to better inform CMS and 
LTCH providers on the severity and needs of patients in this setting.
    Response: We thank the commenter for their support.
    Comment: Some commenters expressed concern about the relevance of 
the Special Services, Treatments, and Interventions data elements to 
patients in LTCHs, given the low prevalence of some of these treatments 
in the National Beta Test. These and another commenter also noted 
concern around burden of completion related to these data elements.
    Response: We assert that tracking important clinical information is 
important to care planning and transfer of information across settings 
of care, even if events are rare. We believe that assessment of various 
special services, treatments, and interventions received by patients in 
the LTCH setting would provide important information for care planning 
and resource use in LTCHs. We appreciate the commenter's concern for 
burden related to completion of these data elements. We note that the 
assessment of many of the less frequently occurring treatments and 
conditions is formatted as a ``check all that apply'' list. We believe 
this approach minimizes burden because a data element only needs to be 
checked if a patient is receiving that treatment. If a patient is 
receiving no treatments in the list, the assessor need only check the 
``none of the above'' option. The assessment of the special services, 
treatments and interventions with multiple responses are formatted as a 
``check all that apply'' format. Therefore, when treatments do not 
apply the assessor need only check one row for ``None of the Above.''
    Comment: Some commenters were concerned about the reliability of 
some Special Services, Treatments, and Interventions data elements, 
noting that the results of the National Beta Test indicated that some 
data elements demonstrated fair or even poor reliability.
    Response: In the category of Special Services, Treatments, and 
Interventions, for SPADEs where kappas could be calculated, 1 data 
element and 2 sub-elements demonstrated overall reliabilities in the 
moderate range (0.41-0.60) and only 1 sub-element demonstrated an 
overall reliability in the slight/poor range (0.00-0.20). These overall 
reliabilities were as follows: 0.60 for the Therapeutic Diet data 
element, 0.55 for the ``Continuous'' sub-element of Oxygen Therapy, 
0.46 for the ``Other'' sub-element of IV Medications, and 0.13 for the 
``Anticoagulant'' sub-element of IV Medications. However, the overall 
reliabilities for all other Special Services, Treatments, and 
Interventions data elements and sub-elements where kappas could be 
calculated were substantial/good or excellent/almost perfect. When 
looking at percent agreement--an alternative measure of interrater 
agreement--values of overall percent agreement for all Special 
Services, Treatments, and Interventions SPADEs and sub-elements ranged 
from 80 to 100 percent.
    Comment: A commenter expressed concern that the Special Services, 
Treatments, and Interventions data elements assess the presence or 
absence of the service, treatment, or intervention rather than the 
clinical rationale or patient outcomes. This commenter stressed the 
importance of bringing this assessment to ``the next level'' to 
determine impact on outcomes.
    Response: We appreciate the commenter's concern that recording the 
presence or absence of certain treatments is only a first step in 
characterizing the complexity that is often the cause of a patient's 
receipt of special services, treatments, and interventions. We would 
like to clarify that any SPADE or set of data elements we proposed is 
intended as a minimum assessment and does not limit the ability of 
providers to conduct a more comprehensive evaluation of a patient's 
situation to identify the potential impacts on outcomes that the 
commenter describes.
    Comment: A commenter requested clarification of the phrase, ``. . . 
that apply at discharge.'' This phrase would be used in the collection 
of the SPADEs in the category of Special Services, Treatments, and 
Interventions.
    Response: The commenter is referring to an instruction in the mock-
up of the SPADEs that was posted to CMS' website at the same time as 
the proposed rule. The mock-up 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 instruction appears at the top of a column within the 
group of items in O0110, Special Treatments, Procedures, and Programs. 
SPADEs on the topics of cancer treatments, respiratory therapies, and 
other treatments are included in this list. At discharge, the assessor 
is instructed to, ``Check all of the following treatments, procedures, 
and programs that apply at discharge.''
    This column is intended to capture the patient's status when he or 
she is discharged. Similar to other assessment data elements in current 
use, guidance related to these data elements will state that they 
should be assessed as close to the time of discharge as possible.
    Final decisions on the SPADEs are given below, following more 
detailed comments on each SPADE proposal.
 Cancer Treatment: Chemotherapy (IV, Oral, Other)
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19523 through 
19524), we proposed 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,

[[Page 42550]]

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 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 ``Final 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 ``Final 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 proposed 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

[[Page 42551]]

standardized patient assessment data for use in the LTCH QRP.
    Comment: A commenter stated it was important to know if a patient 
is receiving chemotherapy for cancer and the method of administration 
but also expressed concern about the lack of an association with a 
patient outcome. This commenter noted that implications of chemotherapy 
for patients needing speech-language pathology services include 
chemotherapy-related cognitive impairment, dysphagia, and speech and 
voice-related deficits.
    Response: We thank the commenter for the support and appreciate the 
concern. We agree with the commenter that chemotherapy can create 
related treatment needs for patients, such as the examples noted by the 
commenter. However, we believe that it is not feasible for SPADEs to 
capture all of a patient's needs related to any given treatment, and we 
maintain that the Special Services, Treatments, and Interventions 
SPADEs provide a common foundation of clinical assessment, which can be 
built on by the individual provider or a patient's care team.
    Comment: Several commenters noted concern about the low frequency 
of Chemotherapy in all PAC patients, which would limit the utility of 
the data collected.
    Response: We appreciate the commenters' concern and we agree that 
the frequency of chemotherapy in the LTCH setting is very low. However, 
tracking important clinical information is important to care planning 
and transfer of information across settings of care, even if events are 
rare. We note that the assessment of many of the less frequently 
occurring treatments and conditions, including Chemotherapy, is 
formatted as a ``check all that apply'' list. We believe this approach 
minimizes burden because a data element only needs to be checked if a 
patient is receiving that treatment. If a patient is receiving no 
treatments in the list, the assessor need only check the ``none of the 
above'' option.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Chemotherapy (IV, Oral, Other) 
data element as standardized patient assessment data beginning with the 
FY 2022 LTCH QRP as proposed.
 Cancer Treatment: Radiation
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19524 through 
19525), we proposed 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.
    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 ``Final 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 ``Final 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

[[Page 42552]]

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 proposed 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.
    Comment: A commenter expressed concern that the Radiation data 
element assesses whether a patient is receiving radiation for cancer 
treatment, but does not identify the rationale for and outcomes 
associated with radiation. The commenter noted that implications of 
radiation for patients needing speech-language pathology services 
include reduced head and neck range of motion due to radiation or 
severe fibrosis, scar bands, and reconstructive surgery complications 
and that these can impact both communication and swallowing abilities.
    Response: We appreciate the commenter's concern. We agree with the 
commenter that radiation can create related treatment needs for 
patients, such as the examples noted by the commenter. However, we 
believe that it is not feasible for SPADEs to capture all of a 
patient's needs related to any given treatment, and we maintain that 
the Special Services, Treatments, and Interventions SPADEs provide a 
common foundation of clinical assessment, which can be built on by the 
individual provider or a patient's care team.
    Comment: Several commenters noted concern about the low frequency 
of Radiation in all PAC patients, which would limit the utility of the 
data collected.
    Response: We appreciate the commenters' concern and we agree that 
the frequency of radiation in the LTCH setting is very low. However, we 
assert that tracking important clinical information is important to 
care planning and transfer of information across settings of care, even 
if events are rare. We note that the assessment of many of the less 
frequently occurring treatments and conditions, including Radiation, is 
formatted as a ``check all that apply'' list. We believe this approach 
minimizes burden because a data element only needs to be checked if a 
patient is receiving that treatment. If a patient is receiving no 
treatments in the list, the assessor need only check the ``none of the 
above'' option.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Radiation data element as 
standardized patient assessment data beginning with the FY 2022 LTCH 
QRP as proposed.
 Respiratory Treatment: Oxygen Therapy (Intermittent, 
Continuous, High-Concentration Oxygen Delivery System)
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19525 through 
19526), we proposed 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 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 ``Final 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-

[[Page 42553]]

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 
previously summarized. 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 in this final rule.
    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 ``Final 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 proposed 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.
    Comment: A commenter noted concern that CMS is proposing to adopt 
new SPADEs despite the fact that they believe that the reliability of 
these SPADEs was not confirmed during the National Beta Test. As an 
example, they stated that the Continuous sub-element within the Oxygen 
Therapy SPADE had only a ``fair'' reliability score for the LTCH 
setting. However, the description by CMS in the proposed rule only 
stated that the National Beta Test found that these SPADEs to be 
feasible and reliable.
    Response: We appreciate the commenter's concerns. We note that we 
have been transparent as to the results of the National Beta Test by 
sharing early findings with stakeholders at a public meeting on 
November 27, 2018, and including results from the National Beta Test in 
supplementary materials to the proposed rule.
    The kappa for the overarching Oxygen Therapy data element was good 
(0.82) when looking at all settings together, and in fact slightly 
higher in the LTCH setting (0.86). The commenter highlighted that the 
kappa for the Continuous Therapy sub-element was 0.55 overall and 0.35 
in the LTCH setting. Another measure of reliability, percent agreement 
between assessors, was excellent/almost perfect for the three Oxygen 
Therapy sub-elements: Percent agreement ranged from 94 to 99 percent 
across settings, and 92 to 97 percent in the LTCH setting.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Oxygen Therapy (Intermittent, 
Continuous, High-Concentration Oxygen Delivery System) data element as 
standardized patient assessment data beginning with the FY 2022 LTCH 
QRP as proposed.
 Respiratory Treatment: Suctioning (Scheduled, As needed)
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19526 through 
19528), we proposed that the Suctioning (Scheduled, As needed) 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 
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

[[Page 42554]]

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 ``Final 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 ``Final 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-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 proposed 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.
    Comment: A commenter requested that this data element also assess 
the frequency of suctioning, as it can impact resource utilization and 
potential medication changes in the plan of care.
    Response: We appreciate the commenter's concern that the response 
options for this data element may not fully capture impacts to resource 
utilization and care plans. The Suctioning data element includes sub-
elements to identify if suctioning is performed on a ``Scheduled'' or 
``As

[[Page 42555]]

Needed'' basis, but it does not directly assess the frequency of 
suctioning by, for example, asking an assessor to specify how often 
suctioning is scheduled. As finalized, this data element differentiates 
between patients who only occasionally need suctioning, and patients 
for whom assessment of suctioning needs is a frequent and routine part 
of the care they receive, and one that is monitored on a schedule 
according to physician instructions. In our work to identify 
standardized data elements, we have strived to balance the scope and 
level of detail of the data elements against the potential burden 
placed on patients and providers. However, we would like to clarify 
that any standardized patient assessment data element is intended as a 
minimum assessment and does not limit the ability of providers to 
conduct a more comprehensive evaluation of a patient's situation to 
identify the potential impacts on outcomes that the commenter 
describes.
    Comment: Several commenters noted concern about the low frequency 
of Suctioning in all PAC patients, which would limit the utility of the 
data collected.
    Response: We appreciate the commenters' concern and we agree that 
the frequency of suctioning in the LTCH setting is very low. However, 
we assert that tracking important clinical information is important to 
care planning and transfer of information across settings of care, even 
if events are rare. We note that the assessment of many of the less 
frequently occurring treatments and conditions, including the 
Suctioning data element, is formatted as a ``check all that apply'' 
list. We believe this approach minimizes burden because a data element 
only needs to be checked if a patient is receiving that treatment. If a 
patient is receiving no treatments in the list, the assessor need only 
check the ``none of the above'' option.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Suctioning (Scheduled, As needed) 
data element as standardized patient assessment data beginning with the 
FY 2022 LTCH QRP as proposed.
 Respiratory Treatment: Tracheostomy Care
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19528), we 
proposed 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 
``Final 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 ``Final 
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

[[Page 42556]]

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 proposed 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.
    Comment: A commenter noted the importance of determining whether a 
patient is receiving tracheostomy care, as it helps with risk 
adjustment and identifying increased resource utilization, and 
recommended that the SPADE be expanded to ask about the size of the 
tracheostomy and whether the tracheostomy has a cuff or is fenestrated.
    Response: Risk adjustment determinations is an issue that we 
continue to evaluate in all of our QRP programs. We will note this 
issue for further analysis in our future work to determine how the 
SPADEs will be used. With regard to the commenter's request to expand 
the Tracheostomy Care SPADE to include more detail about the type of 
tracheostomy, we do not believe that this level of clinical detail is 
necessary to fulfill the purposes of the SPADEs, which are to support 
care coordination, care planning, and future quality measures. We 
believe the broad indication that a patient is receiving Tracheostomy 
Care will be sufficient for the purposes of standardization and quality 
measurement.
    Comment: Several commenters noted concern about the low frequency 
of Tracheostomy Care in all PAC patients, which would limit the utility 
of the data collected.
    Response: We appreciate the commenters' concern and we agree that 
the frequency of tracheostomy care in the LTCH setting is very low. 
However, we assert that tracking important clinical information is 
important to care planning and transfer of information across settings 
of care, even if events are rare. We note that the assessment of many 
of the less frequently occurring treatments and conditions, including 
Tracheostomy Care, is formatted as a ``check all that apply'' list. We 
believe this approach minimizes burden because a data element only 
needs to be checked if a patient is receiving that treatment. If a 
patient is receiving no treatments in the list, the assessor need only 
check the ``none of the above'' option.
    Comment: A commenter stated a concern that emphasizing tracheostomy 
care may lead to unnecessary testing for bacteria (``cultures'') and 
thus unnecessary antibiotics.
    Response: We appreciate the commenter's concern. We would like to 
clarify that the Tracheostomy Care SPADE assesses whether or not a 
patient is receiving care for a tracheostomy, and does not speak to the 
clinical care that patients with tracheostomies may require. We intend 
to monitor data and outcomes related to implementation of the SPADEs, 
especially any adverse events (such as infections) as a result of 
tracheostomy care.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Tracheostomy Care data element as 
standardized patient assessment data beginning with the FY 2022 LTCH 
QRP as proposed.
 Respiratory Treatment: Non-invasive Mechanical Ventilator 
(BiPAP, CPAP)
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19529 through 
19530), we proposed 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 proposed 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 ``Final 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

[[Page 42557]]

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 ``Final 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 
proposed 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 assessment data for use in the LTCH QRP.
    Comment: Several commenters noted concern about the low frequency 
of Non-Invasive Mechanical Ventilators in all PAC patients, which would 
limit the utility of the data collected.
    Response: We appreciate the commenters' concern and we agree that 
the frequency of non-invasive mechanical ventilators in the LTCH 
setting is very low. However, we assert that tracking important 
clinical information is important to care planning and transfer of 
information across settings of care, even if events are rare. We note 
that the assessment of many less frequently occurring treatments and 
conditions, including Non-invasive Mechanical Ventilator, is formatted 
as a ``check all that apply'' list. We believe this approach minimizes 
burden because a data element only needs to be checked if a patient is 
receiving that treatment. If a patient is receiving no treatments in 
the list, the assessor need only check the ``none of the above'' 
option.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Non-invasive Mechanical Ventilator 
(BiPAP, CPAP) data element as standardized patient assessment data 
beginning with the FY 2022 LTCH QRP as proposed.
 Respiratory Treatment: Invasive Mechanical Ventilator
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19530 through 
19531), we proposed 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.\818\
---------------------------------------------------------------------------

    \818\ 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 proposed that this data element will be collected at 
admission from the ``Invasive Mechanical Ventilation Support upon

[[Page 42558]]

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 ``Final 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 a 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 ``Final 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 proposed 
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 
standardized patient assessment data for use in the LTCH QRP.
    Comment: A commenter was disappointed to see that this data element 
only assesses whether or not a patient is on a mechanical ventilator. 
The commenter suggested CMS consider collecting data to track 
functional outcomes related to progress towards independence in 
communication and swallowing.
    Response: In our evaluation of the suitability of data elements for 
SPADEs, we examined the clinical usefulness of candidate SPADEs across 
the full range of PAC providers. We intend to use the SPADEs to inform 
care planning and comparing of assessment data for standardized 
measures. We believe that assessing the use of an invasive mechanical 
ventilator is a useful point of information to inform care planning and 
further assessment, such as related to functional outcomes. We will 
take into consideration functional outcomes, overall, that are related 
to progress towards independence in communication and swallowing in 
future measure modifications.
    Comment: Several commenters noted concern about the low frequency 
of Invasive Mechanical Ventilators in all PAC patients, which would 
limit the utility of the data collected.
    Response: We appreciate the commenters' concern and we agree that 
the frequency of invasive mechanical ventilators in the LTCH setting is 
very low. However, we assert that tracking important clinical 
information is important to care planning and transfer of information 
across settings of care, even if events are rare. We note that the 
assessment of many of the less frequently occurring treatments and 
conditions, including Invasive Mechanical Ventilator, is formatted as a 
``check all that apply'' list. We believe this approach minimizes 
burden because a data element only needs to be checked if a patient is 
receiving that treatment. If a patient is receiving no treatments in 
the list, the assessor need

[[Page 42559]]

only check the ``none of the above'' option.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Invasive Mechanical Ventilator 
data element as standardized patient assessment data beginning with the 
FY 2022 LTCH QRP as proposed.
 Intravenous (IV) Medications (Antibiotics, Anticoagulants, 
Vasoactive Medications, Other)
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19531 through 
19532), we proposed 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 proposed 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 proposed 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 ``Final 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 ``Final 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

[[Page 42560]]

``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 IV medications, 
stakeholder input, and strong test results, we proposed 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.
    Comment: A commenter was supportive of the IV Medications data 
element, noting that the data could be leveraged to encourage providers 
to transition away from the use of IV antibiotics to oral antibiotics, 
which would support best practices in antimicrobial stewardship.
    Response: We thank the commenter for the support.
    Comment: Several commenters stated concern about the low 
reliability of the sub-elements of the Intravenous Medications data 
element in the National Beta Test.
    Response: For the IV Medications data element in the LTCH setting, 
when looking at the kappa statistic as a measures of reliability, 1 
sub-element demonstrated reliability in the moderate range (0.41--0.60) 
and 1 sub-element demonstrated an overall reliability in the slight/
poor range (0.00--0.20). These reliabilities were as follows: 0.46 for 
the ``Other'' sub-element of IV Medications, and 0.13 for the 
``Anticoagulation'' sub-element of IV Medications. However, the 
reliability for the IV Medications data element was substantial/good 
(0.68) and for the ``Antibiotics'' sub-element was excellent/almost 
perfect (0.84). Consultation with assessors suggested that the low 
kappa for the IV Anticoagulants sub-element was likely due to 
inconsistent interpretation of the coding instructions. Having 
identified the likely source of the relatively lower interrater 
reliability, we are confident that with proper training of LTCHs on how 
to report the data elements, the reliability of these sub-elements will 
be improved. We additionally note that, when looking at percent 
agreement--an alternative measure of interrater agreement--values of 
overall percent agreement for the IV Medications data element and sub-
elements were all strong, ranging from 79 to 93 percent, which provides 
additional support for the reliability of the IV Medications SPADE.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the IV Medications (Antibiotics, 
Anticoagulants, Vasoactive Medications, Other) data element as 
standardized patient assessment data beginning with the FY 2022 LTCH 
QRP as proposed.
 Transfusions
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19532), we 
proposed 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 ``Final 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 ``Final 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/

[[Page 42561]]

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 proposed 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 Transfusions 
data element as standardized patient assessment data for use in the 
LTCH QRP.
    Comment: A commenter applauded CMS for including the Transfusions 
data element, noting that it will provide information on care planning, 
clinical decision making, patient safety, care transitions, and 
resource use in LTCHs and will contribute to higher quality and 
coordinated care for patients who rely on these life-saving treatments.
    Response: We thank the commenter for the support. We selected the 
Transfusions data element for proposal as standardized data in part 
because of the attributes that the commenter noted.
    Comment: A commenter was concerned that LTCHs will not have the 
resources needed to provide patients with access to blood transfusions 
and requested that CMS consider whether payments to LTCHs are adequate 
to cover the cost of this resource intensive, specialized service.
    Response: We wish to clarify that the Transfusions SPADE collects 
information on the complexity of the patient and resources the patient 
requires. At this time, this item will not be used for any payment 
purposes, and thus we are not able to comment on the cost of this 
service. This SPADE is not intended to measure the ability of an LTCH 
to provide in-house transfusions, only to capture the services a given 
patient may be receiving. Further, for patients who require services 
related to blood transfusions, information collected by this data 
element is a part of common clinical workflow, and thus, we believe 
that burden on resource intensity would not be affected by the 
standardization of this data element.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Transfusions data element as 
standardized patient assessment data beginning with the FY 2022 LTCH 
QRP as proposed.
 Dialysis (Hemodialysis, Peritoneal dialysis)
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19533 through 
19534), we proposed 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 proposed 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 in this final rule, in 
the proposed rule, we proposed 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 ``Final 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,

[[Page 42562]]

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 proposed 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 ``Final 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 dialysis, 
stakeholder input, and strong test results, we proposed 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.
    Comment: A commenter was supportive of collecting information on 
dialysis for LTCH patients and stated it will be an important variable 
in the analysis of admissions to the hospital for infections.
    Response: We thank the commenter for the support of the Dialysis 
data element.
    Comment: Several commenters noted concern about the low frequency 
of dialysis in all PAC patients, which would limit the utility of the 
data collected.
    Response: We appreciate the commenters' concern and we agree that 
the frequency of dialysis in the LTCH setting is very low. However, we 
assert that tracking important clinical information is important to 
care planning and transfer of information across settings of care, even 
if events are rare. We note that the assessment of many of the less 
frequently occurring treatments and conditions, including Dialysis, is 
formatted as a ``check all that apply'' list. We believe this approach 
minimizes burden because a data element only needs to be checked if a 
patient is receiving that treatment. If a patient is receiving no 
treatments in the list, the assessor need only check the ``none of the 
above'' option.
    Comment: A commenter raised a concern about the possible use of the 
Dialysis SPADE in a future unified PAC payment system, noting that 
facilities like theirs provide dialysis services to patients without 
additional reimbursement while many SNFs, for example, send dialysis 
patients to a dialysis center, and therefore do not incur this cost for 
the patients under their care. The commenter recommended that future 
use of the Dialysis SPADE should require additional information on the 
site of services to properly attribute those services to a provider.
    Response: We appreciate the commenter's concern and will take this 
recommendation into consideration as we consider uses of the Dialysis 
SPADE in the future.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Dialysis (Hemodialysis, Peritoneal 
dialysis) data element as standardized patient assessment data 
beginning with the FY 2022 LTCH QRP as proposed.
 Intravenous (IV) Access (Peripheral IV, Midline, Central line)
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19534 through 
19535), we proposed 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

[[Page 42563]]

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 ``Final 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 ``Final 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 proposed 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, and to adopt the IV access (Peripheral IV, Midline, Central line) 
data element as standardized patient assessment data for use in the 
LTCH QRP.
    Comment: A commenter was supportive of collecting information on IV 
Access that includes peripheral IV, midline, and peripherally inserted 
central catheters (PICCs)--a type of central line--for LTCH patients 
and stated knowing about the presence of these devices will be helpful 
when tracking admissions for infections.
    Response: We thank the commenter for the support of the IV Access 
data element.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the IV Access (Peripheral IV, Midline, 
Central line) data element as standardized patient assessment data 
beginning with the FY 2022 LTCH QRP as proposed.
 Nutritional Approach: Parenteral/IV Feeding
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19535), we 
proposed that the Parenteral/IV Feeding

[[Page 42564]]

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 proposed 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 ``Final 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, a 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 ``Final 
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 proposed 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.
    Comment: Several commenters were supportive of collection of the 
Parenteral/IV Feeding data element. A commenter stated it is critical 
to document information on Parenteral/IV Feeding to ensure the 
appropriate nutritional management of at-risk patients. Another 
commenter described how the SPADEs ensure that nutritional status and 
diet orders are included in discharge planning and transfer of health 
information documents, which will in turn alert the receiving providers 
to incorporate this information in the patient's treatment plan. 
Another commenter was supportive, but noted that the Parenteral/IV 
Feeding SPADE should not be a substitute for capturing information 
related to swallowing

[[Page 42565]]

which reflects additional patient complexity and resource use.
    Response: We thank the commenters for their support of the 
Parenteral/IV Feeding data element. We agree that documenting 
Parenteral/IV Feeding via this SPADE supports nutritional management 
and will help ensure that this information is transferred to the next 
provider at discharge.
    We also appreciate the concern raised related to swallow 
assessment. We agree that the Parenteral/IV Feeding SPADE should not be 
used as a substitute for an assessment of a patient's swallowing. The 
SPADEs are not intended to replace comprehensive clinical evaluation 
and in no way preclude providers from conducting further patient 
evaluation or assessments in their settings as they believe are 
necessary and useful. We agree that information related to swallowing 
can capture patient complexity. However, we also note that Parenteral/
IV Feeding data element captures a different construct than an 
evaluation of swallowing. That is, the Parenteral/IV Feeding data 
element captures a patient's need to receive calories and nutrients 
intravenously, while an assessment of swallowing would capture a 
patient's functional ability to safely consume food orally for 
digestion in their gastrointestinal tract.
    Comment: Several commenters noted concern about the low frequency 
of Parenteral/IV Feeding in all PAC patients, which would limit the 
utility of the data collected.
    Response: We appreciate the commenters' concern and we agree that 
the frequency of parenteral/IV feeding in the LTCH setting is very low. 
However, we assert that tracking important clinical information is 
important to care planning and transfer of information across settings 
of care, even if events are rare. We note that the assessment of many 
of the less frequently occurring treatments and conditions, including 
Parenteral/IV Feeding, is formatted as a ``check all that apply'' list. 
We believe this approach minimizes burden because a data element only 
needs to be checked if a patient is receiving that treatment. If a 
patient is receiving no treatments in the list, the assessor need only 
check the ``none of the above'' option.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Parenteral/IV Feeding data element 
as standardized patient assessment data beginning with the FY 2022 LTCH 
QRP as proposed.
 Nutritional Approach: Feeding Tube
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19535 through 
19536), we proposed 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.
    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.\819\ 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).
---------------------------------------------------------------------------

    \819\ 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 ``Final 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 proposed in the 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 ``Final 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

[[Page 42566]]

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 proposed 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.
    Comment: Several commenters were supportive of collection of the 
Feeding Tube data element, with one stating it is critical to document 
information on Feeding Tube to ensure the appropriate nutritional 
management of at-risk patients. A commenter described how the SPADEs 
ensure that nutritional status and diet orders are included in 
discharge planning and transfer of health information documents, which 
will in turn alert the receiving providers to incorporate this 
information in the patient's treatment plan.
    Response: We thank the commenters for their support of the Feeding 
Tube data element.
    Comment: A commenter noted that in addition to identifying if the 
patient is on a feeding tube, it would be important to assess the 
patient's progression towards oral feeding within this data element, as 
this impacts the tube feeding regimen.
    Response: We agree that progression to oral feeding is important 
for care planning and transfer. At this time, we are finalizing a 
singular Feeding Tube SPADE, which assesses the nutritional approach 
only and does not capture the patient's prognosis with regard to oral 
feeding. We wish to clarify that the SPADEs are not intended to replace 
comprehensive clinical evaluation and in no way preclude providers from 
conducting further patient evaluation or assessments in their settings 
as they believe are necessary and useful. We will take this 
recommendation into consideration in future work on standardized data 
elements.
    Comment: Several commenters noted concern about the low frequency 
of a Feeding Tube in all PAC patients, which would limit the utility of 
the data collected.
    Response: We appreciate the commenters' concern and we agree that 
the frequency of a feeding tube in the LTCH setting is very low. 
However, we assert that tracking important clinical information is 
important to care planning and transfer of information across settings 
of care, even if events are rare. We note that the assessment of many 
of the less frequently occurring treatments and conditions, including 
Feeding Tube, is formatted as a ``check all that apply'' list. We 
believe this approach minimizes burden because a data element only 
needs to be checked if a patient is receiving that treatment. If a 
patient is receiving no treatments in the list, the assessor need only 
check the ``none of the above'' option.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Feeding Tube data element as 
standardized patient assessment data beginning with the FY 2022 LTCH 
QRP as proposed.
 Nutritional Approach: Mechanically Altered Diet
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19536 through 
19537), we proposed 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.\820\
---------------------------------------------------------------------------

    \820\ 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.
---------------------------------------------------------------------------

    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 ``Final 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.

[[Page 42567]]

    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, a 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 
``Final 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 proposed 
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.
    Comment: Several commenters were supportive of collection of the 
Mechanically Altered Diet data element, with a commenter stating that 
it is critical to document information on Mechanically Altered Diet to 
ensure the appropriate nutritional management of at-risk patients. 
Another commenter described how the SPADEs ensure that nutritional 
status and diet orders are included in discharge planning and transfer 
of health information documents, which will in turn alert the receiving 
providers to incorporate this information in the patient's treatment 
plan.
    Response: We thank the commenters for their support of the 
Mechanically Altered Diet data element.
    Comment: A commenter was concerned that the Mechanically Altered 
Diet data element does not capture clinical complexity and does not 
provide any insight into resource allocation because it only measures 
whether the patient needs a mechanically altered diet and not, for 
example, the extent of help a patient needs in consuming a meal.
    Response: We believe that assessing patients' needs for 
mechanically altered diets captures one piece of information about 
clinical complexity and resource allocation. A patient with this 
special nutritional requirement may require additional nutritional 
planning services, special meals, and staff to ensure that meals are 
prepared and served in the way the patient needs. Additional factors 
that would affect resource allocation, such as those noted by the 
commenter, are not captured by this data element. We have decided not 
to alter the SPADE as proposed in order to balance the scope and level 
of detail of the data elements against the potential burden placed on 
providers who must complete the assessment. We will take this 
suggestion into consideration in future refinement of the clinical 
SPADEs.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Mechanically Altered Diet data 
element as standardized patient assessment data beginning with the FY 
2022 LTCH QRP as proposed.
 Nutritional Approach: Therapeutic Diet
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19537 through 
19538), we proposed 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

[[Page 42568]]

Therapeutic Diet data element, we refer readers to the document titled 
``Final 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 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, a 
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. A 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 ``Final 
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 proposed 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.
    Comment: A few commenters were supportive of collection of the 
Therapeutic Diet data element, with one stating that it is critical to 
document information on Therapeutic Diet to ensure the appropriate 
nutritional management of at-risk patients. Another commenter described 
how the SPADEs ensure that nutritional status and diet orders are 
included in discharge planning and transfer of health information 
documents, which will in turn alert the receiving providers to 
incorporate this information in the patient's treatment plan.
    Response: We thank the commenters for their support of the 
Therapeutic Diet data element.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Therapeutic Diet data element as 
standardized patient assessment data beginning with the FY 2022 LTCH 
QRP as proposed.
 High-Risk Drug Classes: Use and Indication
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19538 through 
19540), we proposed 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.\821\ 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.\822\
---------------------------------------------------------------------------

    \821\ 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.
    \822\ 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,\823\ while the 
rate of ADEs in the long-term care setting is approximately 9.80 ADEs 
per 100 resident-months.\824\ In the hospital setting, the incidence 
has

[[Page 42569]]

been estimated at 15 ADEs per 100 admissions.\825\ 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.826 827 828 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.\829\
---------------------------------------------------------------------------

    \823\ 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.
    \824\ 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.
    \825\ 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].
    \826\ Barnsteiner JH. Medication reconciliation: transfer of 
medication information across settings--keeping it free from error. 
J Infus Nurs. 2005;28(2 Suppl):31-36.
    \827\ Rozich J, Roger, R. Medication safety: one organization's 
approach to the challenge. Journal of Clinical Outcomes Management. 
2001(8):27-34.
    \828\ 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.
    \829\ 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 
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.\830\ We proposed one High-Risk Drug Class data element with six 
medication classes as sub-elements. The six medication classes we 
proposed 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; 831 832 
fluid retention, heart failure, and lactic acidosis are associated with 
hypoglycemics; \833\ misuse is associated with opioids; \834\ fractures 
and strokes are associated with antipsychotics; 835 836 and 
various adverse events such as central nervous systems effects and 
gastrointestinal intolerance are associated with antimicrobials,\837\ 
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.\838\ 
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.\839\
---------------------------------------------------------------------------

    \830\ Ibid.
    \831\ 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.
    \832\ 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.
    \833\ Hamnvik OP, McMahon GT. Balancing Risk and Benefit with 
Oral Hypoglycemic Drugs. The Mount Sinai journal of medicine, New 
York. 2009; 76:234-243.
    \834\ Naples JG, Gellad WF, Hanlon JT. The Role of Opioid 
Analgesics in Geriatric Pain Management. Clin Geriatr Med. 
2016;32(4):725-735.
    \835\ 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].
    \836\ 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.
    \837\ Faulkner CM, Cox HL, Williamson JC. Unique aspects of 
antimicrobial use in older adults. Clin Infect Dis. 2005;40(7):997-
1004.
    \838\ 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.
    \839\ 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 
``Final 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.\840\ 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-

[[Page 42570]]

Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-
of-2014/IMPACT-Act-Downloads-and-Videos.html.
---------------------------------------------------------------------------

    \840\ 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 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 ``Final 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. A 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, a 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 proposed 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.
    Comment: A commenter supported the High-Risk Drug Class data 
element and the efforts of CMS to ensure LTCH patients are protected 
from unintended consequences that may occur with the use of high-risk 
medications. The commenter stated that including a documented 
indication for use may be helpful in assessing quality of care. The 
commenter also supported the six drug classes but encouraged CMS to 
consider the addition of the classes of high-risk medications captured 
in measures currently used in the Medicare Advantage program and the 
Merit-based Incentive Payment System (MIPS), which are also based on 
the Beers criteria, and to continue to refine the measures to ensure 
that providers are conducting high quality medication reconciliation 
for all patients.
    Response: We thank the commenter for the support of the High-Risk 
Drug Class data element and the six drug classes. We believe the 
commenter was referring to the Use of High-Risk Medications in the 
Elderly (NQF #0022) quality measure which is used by MIPS and is not in 
the LTCH QRP at this time. We will consider their recommendation to 
expand and further align the drug classes in the SPADE with the drug 
classes used in the Use of High-Risk Medications in the Elderly quality 
measure, as well as the recommendation to include a documented 
indication for use.
    Comment: Some commenters stated that the High-Risk Drugs: Use and 
Indication data element is not appropriate for use in patient 
assessments and has limited utility, because ADEs are not limited to 
high-risk drugs and finding the indications for drugs in a class is 
highly burdensome.
    Response: We understand that not all ADEs are associated with 
``high-risk'' drugs, and we also note that medications in the named 
drug classes are mostly used in a safe manner. Prescribed high-risk 
medications are defined as a ``proximate factor'' to preventable ADEs 
by the Joint Commission. However, the Joint Commission's conceptual 
model of preventable ADEs also includes provider, patient, health care 
system, organization, and technical factors, all of which present many 
opportunities for disrupting preventable ADEs. We have decided to focus 
on a selection of drug classes that are commonly used by older

[[Page 42571]]

adults and are related to ADEs which are clinically significant, 
preventable, and measurable. Anticoagulants, antibiotics, and diabetic 
agents have been implicated in an estimated 46.9 percent (95 percent 
CI, 44.2 percent-49.7 percent) of emergency department visits for 
adverse drug events.\841\ Among older adults (aged >=65 years), three 
drug classes (anticoagulants, diabetic agents, and opioid analgesics) 
have been implicated in an estimated 59.9 percent (95 percent CI, 56.8 
percent-62.9 percent) of emergency department visits for adverse drug 
events.\842\ Further, antipsychotic medications have been identified as 
a drug class for which there is a need for increased outreach and 
educational efforts to reduce use among older adults.
---------------------------------------------------------------------------

    \841\ Shehab N, Lovegrove MC, Geller AI, Rose KO, Weidle NJ, 
Budnitz DS. US emergency department visits for outpatient adverse 
drug events, 2013-2014. JAMA 2016;316(2):2115-2125.
    \842\ Shehab N, Lovegrove MC, Geller AI, Rose KO, Weidle NJ, 
Budnitz DS. US emergency department visits for outpatient adverse 
drug events, 2013-2014. JAMA 2016;316(2):2115-2125.
---------------------------------------------------------------------------

    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the High-Risk Drug Classes: Use and 
Indication data element as standardized patient assessment data 
beginning with the FY 2022 LTCH QRP as proposed.
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.
    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.\843\ 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.844 845 846
---------------------------------------------------------------------------

    \843\ 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.
    \844\ 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.
    \845\ 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.
    \846\ 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.
---------------------------------------------------------------------------

    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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19540 through 
19542), we invited 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 sought 
comment on whether or not we should add these pain items in light of 
those concerns. Commenters were asked to address to what extent the 
collection of the SPADES described in this final rule through patient 
queries might encourage providers to prescribe opioids.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19541 through 
19542), we proposed 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.\847\ 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.\848\ 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.\849\
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    \847\ 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/.
    \848\ 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.
    \849\ 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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[[Page 42572]]

    Pain is a common 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.\850\ 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.
---------------------------------------------------------------------------

    \850\ 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.
---------------------------------------------------------------------------

    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 the proposed rule we also proposed a SPADE that assesses for 
the use of, as well as importantly the indication for the 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 SPADEs 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,851 852 853 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.854 855 856
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    \851\ 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.
    \852\ Fine, P.G. (2009). Chronic Pain Management in Older 
Adults: Special Considerations. Journal of Pain and Symptom 
Management, 38(2): S4-S14.
    \853\ 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.
    \854\ 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.
    \855\ 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.
    \856\ 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.
---------------------------------------------------------------------------

    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,\857\ and consistent with HHS' 5-Point Strategy To Combat 
the Opioid Crisis \858\ which includes ``Better Pain Management.''
---------------------------------------------------------------------------

    \857\ 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.
    \858\ https://www.hhs.gov/opioids/about-the-epidemic/hhs-response/index.html.
---------------------------------------------------------------------------

    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 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 ``Final 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

[[Page 42573]]

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 ``Final 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, a 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 proposed 
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.
    Comment: Several commenters noted support for the Pain Interference 
SPADEs, noting that these SPADEs will provide a useful and more 
accurate assessment of a patient's ability to function, and that 
understanding the impact of pain on therapy and other activities, 
including sleep, can improve the quality of care, which in turn will 
support providers in their ability to provide effective pain management 
services.
    Response: We thank the commenters for their support of the Pain 
Interference SPADEs.
    Comment: A commenter noted that the proposed Pain Interference 
SPADEs document pain frequency but stated that it is important to 
identify both pain frequency and pain intensity.
    Response: We wish to clarify that the Pain Interference SPADEs are 
interview data elements that ask the patient the frequency with which 
pain interferes with sleep, therapy, or non-therapy activities. These 
data elements therefore combine the concepts of frequency and 
intensity, with the measure of intensity being interference with the 
named activities. Self-reported measures of pain intensity are often 
criticized for being infeasible to standardize. In these data elements, 
interference with activities is an alternative to asking about 
intensity.
    Comment: A commenter expressed concern about the suitability of the 
Pain Interference SPADEs for use in patients with cognitive and 
communication deficits and suggested CMS consider the use of non-verbal 
means to allow patients to respond to SPADEs related to pain.
    Response: We appreciate the commenter's concern surrounding pain 
assessment with patients with cognitive and communication deficits. The 
Pain Interference SPADEs require that a patient be able to communicate, 
whether verbally, in writing, or using another method. Assessors may 
use non-verbal means to administer the questions (for example, 
providing the questions and response in writing for a patient with 
severe hearing impairment). Patients who are unable to communicate by 
any means would not be required to complete the Pain Interference 
SPADEs. However, evidence suggests that pain presence can be reliably 
assessed through structural observational protocols. To that end, we 
tested observational pain presence elements in the National Beta Test, 
but have chosen not to propose those data elements as SPADEs at this 
time, out of consideration of the scale of additions and changes that 
would be required of PAC providers. We will take the commenters' 
concern into consideration as the SPADEs are monitored and refined in 
the future.
    Comment: A commenter expressed concerns about how CMS might use 
these data elements, noting particular concern that collection of these 
SPADEs may inappropriately translate into an assessment of quality, and 
that data collection on this topic could create incentives that 
directly or indirectly interfere with treatment decisions.
    Response: We appreciate the commenter's concern related to wanting 
to understand how we will use the SPADEs. It is our intention, as 
delineated by the IMPACT Act, to use the SPADE data to inform care 
planning, the common standards and definitions to facilitate 
interoperability, and to allow for comparing assessment data for 
standardized measures. We will continue to communicate and collaborate 
with stakeholders about how the SPADEs will be used in the LTCH QRP, as 
those plans are established, by soliciting input during the development 
process and establishing use of the SPADEs in quality programs through 
future rulemaking.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Pain Interference data elements 
(Pain Effect on Sleep, Pain Interference with Therapy Activities, and 
Pain Interference with Day-to-Day Activities)

[[Page 42574]]

as standardized patient assessment data beginning with the FY 2022 LTCH 
QRP as proposed.
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 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
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19543 through 
19544), we proposed 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.859 860 Treatment and accommodation of 
hearing impairment led to improved health outcomes, including but not 
limited to quality of life.\861\ For example, hearing loss in elderly 
individuals has been associated with depression and cognitive 
impairment,862 863 864 higher rates of incident cognitive 
impairment and cognitive decline,\865\ and less time in occupational 
therapy.\866\ Accurate assessment of hearing impairment is important in 
the PAC setting for care planning and defining resource use.
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    \859\ 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.
    \860\ 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.
    \861\ 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.
    \862\ 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.
    \863\ 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.
    \864\ 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.
    \865\ 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.
    \866\ 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 ``Final 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

[[Page 42575]]

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 ``Final 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 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 proposed 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.
    Comment: Several commenters supported the collection of information 
on hearing impairment, with some noting that LTCHs are already 
collecting similar information. One of these commenters also suggested 
that CMS consider how hearing impairment impacts a patient's ability to 
respond to the assessment tool in general. Another of these commenters 
noted that collecting this data at admission only is a logical approach 
since a patient's hearing impairment status is unlikely to change 
during an LTCH admission.
    Response: We thank the commenters for their support of the Hearing 
data element and support for the collection of hearing at admission. 
Concerning how hearing impairment affects a patient's ability to 
respond to the assessment overall, we offer guidance and 
recommendations through our CMS LTCH QRP Manual. Coding tips and steps 
for assessment direct assessors to take appropriate steps to 
accommodate sensory and communication impairments when conducting the 
assessment, so as to minimize the impact of a patient's impairment on 
their responses or ability to participate in the full assessment. For 
example, in the coding tips for BB0700, Expression of Ideas and Wants, 
the CMS LTCH QRP Manual states: ``Assess using the patient's preferred 
language.'' And ``Interact with the patient. Be sure he or she can hear 
you or has access to his or her preferred method for communication, 
such as an electronic device or paper and pencil. If appropriate, be 
sure he or she has access to his or her hearing aid or hearing 
appliance and glasses or other visual appliances. If appropriate, offer 
alternative means of communication such as an electronic device (smart 
phone, tablet, laptop, etc.), writing, pointing, nodding, or using cue 
cards.''
    Comment: A commenter stated that the rate of hearing impairment as 
measured by the Hearing SPADE occurs too infrequently to provide 
information that would benefit LTCH patients.
    Response: Based on findings from the National Beta Test, although 
the level of PAC patients/residents who were assessed as ``Highly 
Impaired'' was 1 percent, an additional 8 percent were assessed to have 
``Moderate difficulty'' and 17 percent were assessed to have ``Minimal 
difficulty'' with Hearing. These results are provided in the document 
titled ``Final 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 SPADE consists of one 
data element completed by the assessor based primarily on interacting 
with the patient and reviewing the medical record. Given the low burden 
of reporting the Hearing data element, and despite severe hearing 
impairment occurring in a small proportion of LTCH patients, we believe 
it is important to systematically assess for hearing impairment to 
improve clinical care and care transitions.
    Comment: A commenter recommended adding ``unable to assess'' as a 
response option, which the commenter believes would be the appropriate 
choice if the patient is comatose or is unable to effectively answer 
questions related to an assessment of their hearing.
    Response: We appreciate the commenter's recommendation. The 
assessment of hearing is completed based on observing the patient 
during assessment, patient interactions with others, reviewing medical 
record documentation, and consulting with patient's family and other 
staff, in addition to interviewing the patient. Therefore, the 
assessment can be completed when the patient is unable to effectively 
answer questions related to an assessment of their hearing.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Hearing data element as 
standardized patient assessment data beginning with the FY 2022 LTCH 
QRP as proposed.
 Vision
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19544 through 
19545), we proposed 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

[[Page 42576]]

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.867 868 869 870 871 872 873 
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.
---------------------------------------------------------------------------

    \867\ 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.
    \868\ 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.
    \869\ Keepnews D, Capitman JA, Rosati RJ. Measuring patient-
level clinical outcomes of home health care. J Nurs Scholarsh. 
2004;36(1):79-85.
    \870\ 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.
    \871\ 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.
    \872\ Rovner BW, Ganguli M. Depression and disability associated 
with impaired vision: the MoVies Project. J Am Geriatr Soc. 
1998;46(5):617-619.
    \873\ 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 
proposed 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 ``Final 
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. A 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 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 ``Final 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

[[Page 42577]]

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 proposed 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.
    Comment: Several commenters supported the collection of information 
on vision impairment. Some commenters noted that LTCHs are already 
collecting similar information.
    Response: We thank the commenters for their support of the Vision 
data element. To the extent that LTCHs are already collecting similar 
information, we hope that it will be possible to integrate the Vision 
SPADE into the existing workflow.
    Comment: A commenter recommended that a doctor of optometry should 
play a lead role in conducting vision assessments, and that vision 
assessments done by other clinicians should also obtain the patient's 
own assessment of his or her vision, such as used by the Centers for 
Disease Control and Prevention (CDC) Behavioral Risk Factors 
Surveillance System survey, which asks patients ``Do you have serious 
difficulty seeing, even when wearing glasses?'' This commenter 
expressed concerns about the proposed SPADE being subjective and risks 
of mis-categorizing patients.
    Response: We appreciate the commenter's recommendation about how to 
assess for vision impairment. We do not require that a certain type of 
clinician complete assessments; the SPADEs have been developed so that 
any clinician who is trained in the administration of the assessment 
will be able to administer it correctly. This data element relies on 
the assessor's evaluation of the patient's vision, which has the 
advantage of reducing burden placed on the patient. We will take the 
recommendation to use patient-reported vision impairment assessment 
into consideration in the development of future assessments.
    Comment: A commenter also recommended that CMS require vision 
assessment at discharge, noting that vision impairment could be related 
to challenges in medication management and compliance with written 
follow-up instructions for care.
    Response: We appreciate the commenter's recommendation. We agree 
that adequate vision--or the accommodations and assistive technology 
needed to compensate for vision impairment--is important to patient 
safety in the community, in part for the reasons the commenter 
mentions. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19544 
through 19545), we proposed that LTCHs that submitted the Vision SPADE 
with respect to admission will be deemed to have submitted with respect 
to both admission and discharge, as there is a low likelihood that the 
assessment of this SPADE at admission would differ from the assessment 
at discharge. Vision assessment, collected via the Vision SPADE, will 
provide information that will support the patient's care while in the 
LTCH. We also contend that significant clinical changes to a patient's 
vision will be documented in the medical record as part of routine 
clinical practice. We note that during the discharge planning process, 
it is incumbent on LTCH providers to make reasonable assurances that 
the patient's needs will be met in the next care setting, including in 
the home.
    Comment: A commenter recommended adding ``unable to assess'' as a 
response option, which the commenter believes would be the appropriate 
choice if a patient is comatose or is unable to effectively answer 
questions related to an assessment of their vision.
    Response: We appreciate the commenter's recommendation. However, 
the assessment of vision is completed based on consulting with 
patient's family and other staff, observing the patient including 
asking the patient to read text or examine pictures or numbers in 
addition to interviewing the patient about their vision abilities. 
These other sources/methods can be used to complete the assessment of 
vision when the patient is unable to effectively answer questions 
related to an assessment of their vision.
    Comment: A commenter stated that the rate of vision impairment as 
measured by the Vision SPADE occurs too infrequently to provide 
information that would benefit LTCH patients.
    Response: Based on findings from the National Beta Test. Although 
the level of PAC patients/residents who were assessed as ``Severely 
Impaired'' and ``Highly Impaired'' was 1 percent, respectively, an 
additional four percent were assessed to ``Moderately impaired'' and 16 
percent were assessed to be ``Impaired''. These results are provided in 
the document titled ``Final 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 SPADE consists 
of one data element completed by the assessor based primarily on 
interacting with the patient and reviewing the medical record. Given 
the low burden of the Vision data element, and despite severe vision 
impairment occurring in a small proportion of LTCH patients, we believe 
it is important to systematically assess for vision impairment to 
improve clinical care and care transitions.
    Comment: A commenter noted that assessment through the vision data 
element is just an initial step towards a care coordination system that 
recognizes the impact that eye health has on overall health outcomes. 
This commenter noted that a critical next step would be to ensure that 
patients get to the physician who can address their eye health needs.
    Response: We appreciate the commenter's recommendation and we agree 
that screening for vision impairment is an initial step towards 
ensuring patients receive the care they need. We expect LTCH providers 
to provide a standard of care to patients, and we defer to the clinical 
judgement of the patient's care team to determine when further 
assessment of vision or eye-related issues is warranted.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Vision data element as 
standardized patient assessment data beginning with the FY 2022 LTCH 
QRP as proposed.
f. New Category: Social Determinants of Health
(1) 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

[[Page 42578]]

under Medicare, based on those measures, after taking into account 
studies conducted by ASPE on social risk factors (described in this 
final rule) 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 previously 
described in such subparagraph (A) and for periodic analyses in such 
subparagraph (C)). Accordingly, we proposed 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 the 
proposed rule, we proposed 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 in this final rule. 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. In the FY 2020 
IPPS/LTCH PPS proposed rule (84 FR 19545 through 19552), we proposed to 
collect information on seven proposed SDOH SPADEs 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 final rule.
    We also proposed 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 final 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 in this final rule, 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. We also intend to review SDOH data elements 
across our programs and the industry to harmonize and align in 
instances where it is appropriate.
    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 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.'' \874\ 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.
---------------------------------------------------------------------------

    \874\ 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.
---------------------------------------------------------------------------

    Each of the data elements we proposed to collect and access under 
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.\875\
---------------------------------------------------------------------------

    \875\ Social Determinants of Health. Healthy People 2020. 
https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-of-health. (February 2019).
---------------------------------------------------------------------------

    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.\876\ 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-

[[Page 42579]]

medicares-value-based-purchasing-programs-reports.
---------------------------------------------------------------------------

    \876\ 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.
---------------------------------------------------------------------------

    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 
previously discussed, ASPE's study, and 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 proposed 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 final rule, under section 
2(d)(2) of the IMPACT Act, would be independent of our proposal 
discussed in this final rule (in section VIII.C.7.f.(2) of the preamble 
of this final 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 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 previously discussed, in the proposed rule we 
proposed under section 2(d)(2) of the IMPACT Act, to collect the data 
on the following SDOH: (1) Race, as discussed in section 
VIII.C.7.f.(2)(a) of the preamble of this final rule; (2) Ethnicity, as 
discussed in section VIII.C.7.f.(2)(a) of the preamble of this final 
rule; (3) Preferred Language, as discussed in section VIII.C.7.f.(2)(b) 
of the preamble of this final rule; (4) Interpreter Services as 
discussed in section VIII.C.7.f.(2)(b) of the preamble of this final 
rule; (5) Health Literacy, as discussed in section VIII.C.7.f.(2)(c) of 
the preamble of this final rule; (6) Transportation, as discussed in 
section VIII.C.7.f.(2)(d) of the preamble of this final rule; and (7) 
Social Isolation, as discussed in section VIII.C.7.f.(2)(e) of the 
preamble of this final rule. These data elements are discussed in more 
detail in this section VIII.C.7.f.(2) of the preamble of this final 
rule. A discussion of the comments we received, along with our 
responses, is included in each section.
(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. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19547 
through 19552), we proposed 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 previously outlined under 
section 2(d)(2)(B) of the IMPACT Act, in the proposed rule we also 
proposed 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 proposed 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

[[Page 42580]]

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 proposed 
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 proposed 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.
    We proposed 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,\877\ 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.
---------------------------------------------------------------------------

    \877\ Health Leads. Available at: https://healthleadsusa.org/.
---------------------------------------------------------------------------

    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.
    We solicited comment on these proposals.
    Commenters submitted the following comments related to the proposed 
rule's discussion of SDOH SPADEs. A discussion of these comments, along 
with our responses, appears below.
    Comment: A commenter supported the incorporation of SDOH in the 
LTCH QRP, in the interest of promoting access and assure high-quality 
care for all beneficiaries. The commenter also encouraged CMS to be 
mindful of meaningful data collection and the potential impact for data 
overload. Since SDOH have impacts far beyond the post-acute care 
setting, the commenter cautioned the collection of data that cannot be 
readily gathered, shared or replicated beyond the PAC setting.
    The commenter also encouraged CMS to consider leveraging data 
points collected during primary care visits by using social risk factor 
data captured during those encounters. They pointed out that the 
ability to have a hospital's or physician's EHR also collect, capture, 
and exchange segments of this information is powerful. The commenter 
recommended CMS to take a holistic view of SDOH across the care 
continuum so that all care settings may gather, collect or leverage 
this data efficiently and in a way that maximizes its impact.
    Response: We thank the commenter for the comment, and we agree that 
collecting SDOH data elements can be useful in identifying and address 
health disparities. We also agree that we should be mindful that data 
elements selected are useful. The proposed SDOH SPADEs are aligned with 
the SDOH identified in the 2016 NASEM report, which was commissioned by 
Office of the Assistant Secretary for Planning and Evaluation (ASPE). 
Regarding the commenter's suggestion that we consider how it can align 
existing and future SDOH data collection to minimize burden on 
providers, we agree that it is important to minimize duplication of 
effort and will take this under advisement for future policy 
development.
    Comment: Many commenters support the inclusion of the seven 
proposed SDOH data elements on the LTCH CARE Data Set, as they serve 
populations affected by social determinants. However, they also 
recommend including additional factors within the SDOH SPADE category 
to ensure that the full spectrum of social needs is examined. These 
factors included: Disability status, dual eligibility of beneficiaries, 
health insurance status, food insecurity, housing insecurity, 
independent living status, and ability to return to work. Another 
commenter suggested BMI, smoking status, age, sex, back pain, pain in 
non-operative lower extremity joint, health risk status, depression/
mental health status, chronic narcotic or pre-operative narcotic use, 
and socioeconomic status as they stated they are relevant to 
musculoskeletal care. A commenter also suggested that CMS explore 
family caregiver assessment as a future social risk factor because the 
health and capability of the family caregiver can have an impact on 
their health and medical interventions.
    The commenters noted that the inclusion of the additional SDOH 
would provide greater breadth and depth of data and would offer 
additional support to the Agency when developing policies to address 
social factors related to health. A commenter noted that disability 
status is already included in some Medicare risk adjustment. 
Furthermore, disability is included in risk adjustment across many 
aspects of the Medicare program. The commenters stated that the ASPE's 
report to Congress on Social Risk Factors and Medicare's Value-Based 
Purchasing Programs reported that disability is an independent 
predictor of poor mental and physical health outcomes, and that 
individuals with disabilities may receive lower-quality preventive 
care.
    Response: We thank the commenters for the comments and we will take 
the comments under advisement as we continue to improve and refine the 
SPADEs. We agree that it is important to understand the needs of 
patients with disabilities. However, we also want to note that 
disability status does not need to be added as a SDOH SPADE since 
disability/functionality is comprehensively assessed as part of the 
existing patient assessments in order to establish care plans and set 
health goals to allow the patient to return to the setting in which 
they are most comfortable. However, as we continue to evaluate SDOH 
SPADEs, we will keep commenters' feedback in mind and may consider 
these suggestions in future rulemaking.

[[Page 42581]]

    Comment: A few commenters recognize the importance of collecting 
SDOH information, as it is important to ensure that quality of care is 
assessed fairly for providers. However, they do not support using the 
information to penalize PAC settings for patient issues. They stated 
that it is unclear how CMS will utilize the information collected. The 
commenters request that CMS provide detailed information about how the 
collected information will be used in assessing PAC settings.
    Response: We appreciate the commenters for recognizing that 
collecting SDOH data elements can be useful in identifying and address 
health disparities. It is our intention, as delineated by the IMPACT 
Act, to use the SPADE data to inform care planning, the common 
standards and definitions to facilitate interoperability, and to allow 
for comparing assessment data for standardized measures. We will 
continue to work with stakeholders to promote transparency and support 
providers who serve vulnerable populations, promote high quality care, 
and refine and further implement SDOH SPADE. We appreciate the comment 
on collecting stakeholder feedback before implementing any adjustments 
to measures based on the SDOH SPADE. Collection of this data will help 
us in identifying potential disparities, conducting analyses, and 
assessing whether any adjustments are needed. Any future use of this 
data would be done transparently, through solicitation of stakeholder 
feedback, and through future proposals. With regard to the commenter's 
concerns about penalizing PAC settings for patient issues, we interpret 
the commenter to be referring to the 2 percent reduction in their 
annual payment update (APU) for failure to meet the minimum data 
completion threshold for the LTCH QRP. We do not penalize providers for 
patient issues. LTCHs must meet the APU minimum data completion 
threshold of no less than 80 percent of the LCDS assessments having 100 
percent completion of the required data elements. Successful completion 
means that the assessment does not contain non-informative responses, 
that is, a ``dash'' for required data elements. Failure to meet the 
minimum threshold may result in a 2 percent reduction in the LTCH's 
APU.
    Comment: A commenter was encouraged to see CMS propose a new 
category of SDOH. However, they noted that the proposal is a first step 
because collection of the information is reliant on paper 
questionnaires and ICD-10 codes. They encouraged CMS to move to 
electronic capture of this information to allow for more robust and 
granular data and recommended CMS move towards harmonization of 
assessment tools across settings (including LCDS PAC), and define 
explicit linkages between data capture/representation and terminology 
standards to allow data aggregation and analysis across populations and 
systems. They also suggested that CMS consider piloting of SDOH 
programs through the CMS Innovation Center. They cautioned that CMS 
must ensure data derived from assessment surveys, and the algorithms 
used to analyze those data, should be free of bias that exacerbate 
health disparities. The commenter welcomes the opportunity to work with 
CMS on piloting innovative solutions for capturing SDOH data and 
explain our ongoing efforts on improving SDOH data.
    Response: We appreciate the comment about electronic capture of 
data and note that at we offer free software to our providers (LASER 
for LTCHs) that allows LTCHs to record and transmit required assessment 
data; this data is submitted to CMS electronically. However, at this 
time we do not require that providers use EMRs to populate assessment 
data but note our support of this platform to facilitate 
interoperability. We further note that through the intent of the IMPACT 
Act, we have been working to align the assessment instruments. In order 
to align data capture and terminology standards, we have built the CMS 
DEL as a public resource aimed at advancing interoperable health 
information exchange by enabling users to view assessment questions and 
response options about demographics, medical problems, and other types 
of health evaluations and their associated health IT standards. The DEL 
includes a multitude of data elements, including all data elements 
adopted for use in the quality reporting programs, and not limited to 
data collected under the IMPACT Act. In the initial version of the DEL 
(https://del.cms.gov/), assessment questions and response options are 
mapped to LOINC and SNOMED codes, where feasible. We also recognize the 
importance of leveraging existing standards, obtaining input from 
standards setting organizations, and alignment across federal 
interoperability efforts. We appreciate the comments and we will take 
them under advisement for future consideration.
(a) Race and Ethnicity
    The persistence of racial and ethnic disparities in health and 
health care is widely documented, including in PAC 
settings.878 879 880 881 882 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.\883\ 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 rates of having a usual source of care and receiving 
immunizations such as the flu vaccine.\884\ Studies have also shown 
that African Americans are significantly more likely than white 
Americans to die prematurely from heart disease and stroke.\885\ 
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.\886\
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    \878\ 2017 National Healthcare Quality and Disparities Report. 
Rockville, MD: Agency for Healthcare Research and Quality; September 
2018. AHRQ Pub. No. 18-0033-EF.
    \879\ 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.
    \880\ 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.
    \881\ 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.
    \882\ 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.
    \883\ 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.
    \884\ National Center for Health Statistics. Health, United 
States, 2017: With special feature on mortality. Hyattsville, 
Maryland. 2018.
    \885\ HHS. Heart disease and African Americans. 2016b. (October 
24, 2016). http://minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=19.
    \886\ 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

[[Page 42582]]

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.\887\ 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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    \887\ ``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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    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19547 through 
19549), we proposed 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 proposed 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?'' In the 
proposed rule, we proposed 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?'' In the proposed rule, we proposed 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 are including the addition of 
``of'' to the Ethnicity data element to read, ``Are you of Hispanic, 
Latino/a, 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.888 889 890 891 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.\892\ Standardizing self-reported data 
collection for race and ethnicity allows for the equal comparison of 
data across multiple healthcare entities.\893\ 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 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 ``Final 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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    \888\ 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.
    \889\ 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.
    \890\ IOM (Institute of Medicine). 2009. Race, Ethnicity, and 
Language Data: Standardization for Health Care Quality Improvement. 
Washington, DC: The National Academies Press.
    \891\ ``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.
    \892\ 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/.
    \893\ 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 proposed to adopt the Race and Ethnicity data elements 
previously described as SPADEs with respect to the

[[Page 42583]]

proposed Social Determinants of Health category.
    Specifically, we proposed to replace the current Race/Ethnicity 
data element with the proposed Race and Ethnicity data elements on the 
LCDS. We also proposed 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.
    Comment: Some commenters noted that the response options for race 
do not align with those used in other government data, such as the U.S. 
Census or the Office of Management and Budget (OMB). The commenters 
also stated these responses are not consistent with the recommendations 
made in the 2009 Institute of Medicine report. The commenters pointed 
out that Institute of Medicine (IOM) report recommended using broader 
OMB race categories and granular ethnicities chosen from a national 
standard set that can be ``rolled up'' into the broader categories. The 
commenters stated that it is unclear how CMS chose the 14 response 
options under the race data element and the five options under the 
ethnicity element and worried that these response options would add to 
the confusion that already may exist for patients about what terms like 
``race'' and ``ethnicity'' mean for the purposes of health care data 
collection. A few commenters questioned why race response categories 
include additional granularity for Asian and Pacific Islander, but not 
for other races. They noted concern that the proposed question may 
interfere with successful efforts to collect data in culturally 
appropriate and standardized ways. They encouraged CMS to seek 
stakeholder feedback and consensus on the response categories for race 
and ethnicity data. Another commenter provided that the proposed list 
of response options for Race may not include all races that should be 
reflected, for example, Native African, Middle Eastern. In addition, 
the item should include ``check all that apply'' to ensure accurate and 
complete data collection. The commenter encouraged CMS to refine the 
list of response options for Race and provide a rational for the final 
list of response options. The commenters also noted that CMS should 
confer directly with experts on the issue to ensure patient assessments 
are collecting the right data in the right way before these SDOH SPADEs 
are finalized.
    Response: The proposed race and ethnicity categories align with and 
are rolled up into the 1997 OMB minimum data standards and conforming 
with the 2011 HHS Data Standards as described in the implementation 
guidance titled ``U.S. Department of Health and Human Services 
Implementation Guidance on Data Collection Standards for Race, 
Ethnicity, Sex, Primary Language, and Disability Status'' at https://aspe.hhs.gov/basic-report/hhs-implementation-guidance-data-collection-standards-race-ethnicity-sex-primary-language-and-disability-status. 
For example, the 1997 OMB minimum data standard for Hispanic is the 
roll up category for the following response options on the 2011 HHS 
Data Standards: Mexican, Mexican American, Chicano/a; Puerto Rican; 
Cuban; another Hispanic, Latino, or Spanish origin. The race and 
ethnicity data element that we proposed also includes ``check all that 
apply'' language. As stated in the proposed rule (84 FR 19548), the 14 
race categories and the 5 ethnicity categories conform with the 2011 
HHS Data Standards for person-level data collection, which were 
developed in fulfillment of section 4302 of the Affordable Care Act 
that required the Secretary of HHS to establish data collection 
standards for race, ethnicity, sex, primary language, and disability 
status. Through the HHS Data Council, which is the principal, senior 
internal Departmental forum and advisory body to the Secretary on 
health and human services data policy and coordinates HHS data 
collection and analysis activities, the Section 4302 Standards 
Workgroup was formed. The Workgroup included representatives from HHS, 
the OMB, and the Census Bureau. The Workgroup examined current federal 
data collection standards, adequacy of prior testing, and quality of 
the data produced in prior surveys; consulted with statistical agencies 
and programs; reviewed OMB data collection standards and the IOM Report 
Race, Ethnicity, and Language Data Collection: Standardization for 
Health Care Quality Improvement; sought input from national experts; 
and built on its members' experience with collecting and analyzing 
demographic data. As a result of this Workgroup, a set of data 
collection standards were developed, and then published for public 
comment. This set of data collection standards is referred to as the 
2011 HHS Data Standards.\894\ As described in the implementation 
guidance provided above, the categories of race and ethnicity under the 
2011 HHS Data Standards allow for more detailed information to be 
collected and the additional categories under the 2011 HHS Data 
Standards can be aggregated into the OMB minimum standards set of 
categories.
---------------------------------------------------------------------------

    \894\ HHS Data Standards. Available at https://aspe.hhs.gov/basic-report/hhs-implementation-guidance-data-collection-standards-race-ethnicity-sex-primary-language-and-disability-status.
---------------------------------------------------------------------------

    As noted in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19547 
through 19549), we conferred with experts by conducting a listening 
session regarding the proposed SDOH data elements regarding 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 Data Standards to better reflect state and 
local diversity. We thank the commenter for the comment on including 
Middle Eastern and North African (MENA), and Native African. The 2011 
HHS Data Standards does not include MENA or Native African but we will 
be aligning with the 2011 HHS Data Standards to ensure data is 
consistently being collected and will take it under consideration.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the Race and Ethnicity data elements 
as SPADEs beginning with the FY 2022 LTCH QRP.
(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).\895\ Individuals with LEP have been shown to 
receive worse care and have poorer health outcomes, including higher 
readmission rates.896 897 898 Communication with

[[Page 42584]]

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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    \895\ U.S. Census Bureau, 2013-2017 American Community Survey 5-
Year Estimates.
    \896\ 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.
    \897\ 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.
    \898\ 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.\899\
---------------------------------------------------------------------------

    \899\ IOM (Institute of Medicine). 2009. Race, Ethnicity, and 
Language Data: Standardization for Health Care Quality Improvement. 
Washington, DC: The National Academies Press.
---------------------------------------------------------------------------

    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.\900\ 
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, in the FY 2020 IPPS/LTCH PPS proposed 
rule (84 FR 19549 through 19550), we proposed to retain the Preferred 
Language and Interpreter Services data elements currently in use on the 
LCDS.
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    \900\ 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 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 did not include 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 ``Final 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 
proposed to adopt the Preferred Language and Interpreter Services data 
elements currently used on the LCDS, and previously described, as 
SPADEs with respect to the Social Determinants of Health category.
    Comment: A commenter noted that, if finalized, LTCHs should only 
need to submit data on the Race and Ethnicity SPADEs with respect to 
admission and would not need to collect and report again at discharge, 
as it is unlikely that patient status for these elements will change. 
They believe that a patient's preferred language and need for an 
interpreter also are unlikely to change between admission and 
discharge; thus, the commenter recommended CMS to require collection of 
these SDOH SPADEs with respect to admission only.

[[Page 42585]]

    Response: With regard to the submission of the Preferred Language 
and Interpreter Services SPADEs, we agree with the commenters that it 
is unlikely that the assessment of Preferred Language and Interpreter 
Services at admission would differ from assessment at discharge. As 
discussed in the previous response for Hearing and Vision, we believe 
that the submission of preferred language and the need for an 
interpreter is similar to the submission of the Race, Ethnicity, 
Hearing, and Vision SPADEs.
    We account for this change to the Collection of Information 
Requirements for the LTCH QRP in section X.B.6. of the preamble of this 
final rule.
    Based on the comments received, and for the reasons discussed, we 
are finalizing that the Preferred Language and Interpreter Services 
SPADEs be collected as proposed with the modification that we will deem 
LTCHs that submit these two SPADEs with respect to admission to have 
submitted with respect to both admission and discharge.
(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.'' \901\ 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.\902\
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    \901\ 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.
    \902\ 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.\903\ 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.\904\ 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.
---------------------------------------------------------------------------

    \903\ Social Determinants of Health. Healthy People 2020. 
https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-of-health. (February 2019).
    \904\ 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.
---------------------------------------------------------------------------

    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.905 906 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.\907\ Furthermore, the S-TOFHLA instrument is 
proprietary and subject to purchase for individual entities or 
users.\908\ 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, in the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19550 through 19551), we proposed 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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    \905\ 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.
    \906\ 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.
    \907\ 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.
    \908\ 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.\909\ Given 
the dearth of Medicare data on health literacy and gaps in addressing 
health literacy in practice, we recommend the addition of a health 
literacy data element.
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    \909\ 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.\910\ For more information on the proposed Health Literacy 
data element, we refer readers to the document titled ``Final 
Specifications for LTCH QRP Measures and Standardized Patient 
Assessment Data Elements,'' available on the website at: https://
www.cms.gov/Medicare/Quality-

[[Page 42586]]

Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-
Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
---------------------------------------------------------------------------

    \910\ 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 
proposed to adopt the SILS question, previously described for the 
Health Literacy data element, as SPADE under the Social Determinants of 
Health category. We proposed to add the Health Literacy data element to 
the LCDS.
    Comment: A commenter noted that, if finalized, LTCHs should only 
need to submit data on the Race and Ethnicity SPADEs with respect to 
admission and would not need to collect and report again at discharge, 
as it is unlikely that patient status for these elements will change. 
They believe that a patient's health literacy also is unlikely to 
change between admission and discharge; thus, the commenter recommended 
CMS to require collection of this SDOH SPADE with respect to admission 
only.
    Response: We disagree with the commenter who stated that health 
literacy responses will always be the same from admission to discharge. 
Unlike Vision, Hearing, Race, Ethnicity, Preferred Language, and 
Interpreter Services, we believe that the response to this question 
will change from admission to discharge; therefore, the SPADE is 
required to be collected at both admission and discharge. For example, 
some patients may develop health issues, such as cognitive decline 
during their stay that could impact their response to health literacy 
thus changing their status at discharged. While not directly evaluating 
health literacy, clinical conditions that impact a patient's health 
literacy status would be captured in the clinical record, even if they 
are not assessed by a SPADE. Therefore, we proposed to collect this 
SPADE with respect to both admission and discharge.
    Comment: A commenter stated that the health literacy question could 
be improved to capture whether the patient can read, understand, and 
implement/respond to the information. In addition, the commenter stated 
that the proposed question does not take into account whether a 
patient's need for help is due to limited vision, which is different 
from the purpose of the separate Vision data element. Another possible 
question the commenter suggested was ``How often do you have 
difficulty?''. The commenter suggested that a single construct may not 
be sufficient for this area, depending on the aspect of health literacy 
that CMS intends to identify. Another commenter requested that CMS 
provide more clarity regarding the timeframe of reference for this 
question.
    Response: We thank the commenter for the comment on the Health 
Literacy data element. We agree that knowing whether a patient has a 
reading or comprehension challenge, or limited vision would be helpful. 
However, we specifically proposed data elements that have been tested. 
We were also mindful to try and limit the potential burden of asking 
additional questions related to health literacy. The SILS Health 
Literacy data element that we proposed performed well when tested, and 
it minimizes concerns related to burden by requiring one instead of 
multiple questions on health literacy. If commenters have examples of 
SDOH questions that have been cognitively tested, we would welcome that 
feedback as we seek to refine SDOH SPADEs in future rulemaking.
(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.\911\ 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. In the FY 2020 IPPS/LTCH PPS 
proposed rule (84 FR 19551), we therefore proposed 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.
---------------------------------------------------------------------------

    \911\ 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 proposed 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.\912\
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    \912\ 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.\913\ 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.\914\ 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 proposed to adopt the Transportation data element from PRAPARE. More 
information about

[[Page 42587]]

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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    \913\ 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.
    \914\ Northwestern University. (2017). PROMIS Item Bank v. 1.0--
Emotional Distress--Anger--Short Form 1.
---------------------------------------------------------------------------

    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 ``Final 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 
proposed to adopt the Transportation data element previously described 
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.
    Comment: A commenter supported the collection of data to capture 
the reason(s) transportation affects a patient's access to health care. 
The commenter appreciated the inclusion of these items on the LCDS and 
encouraged exploration of quality measures in this area as 
transportation is an extremely important instrumental activity of daily 
living to effectively transition to the community.
    Response: We thank the commenter for the comment and we will 
consider this feedback as we continue to improve and refine the SPADEs.
    Comment: A commenter noted that, if finalized, LTCHs should only 
need to submit data on the Race and Ethnicity SPADEs with respect to 
admission and would not need to collect and report again at discharge, 
as it is unlikely that patient status for these elements will change. 
They believe that a patient's response to the Transportation SPADE also 
is unlikely to change between admission and discharge; thus, the 
commenter recommended CMS to require collection of this SDOH SPADE with 
respect to admission only.
    Response: We disagree with the commenter who stated that 
Transportation responses will always be the same from admission to 
discharge. Unlike Vision, Hearing, Race, Ethnicity, Preferred Language, 
and Interpreter Services, we believe that the response to this question 
will change from admission to discharge; therefore, the SPADE is 
required to be collected at both admission and discharge. For example, 
losing a family member or caregiver between admission and discharge 
could change how the patient responds to the Transportation SPADE. 
Therefore, we are finalizing to collect this SPADE with respect to both 
admission and discharge as proposed.
    After consideration of the public comments we received, and for the 
reasons discussed, we are finalizing our proposal with regard to 
Transportation as proposed.
(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 area.915 916 Social isolation tends to 
increase with age, is a risk factor for physical and mental illness, 
and a predictor of mortality.917 918 919 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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    \915\ 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.
    \916\ 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.
    \917\ 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.
    \918\ 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.
    \919\ 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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    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19551 through 
19552), we proposed 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.\920\ 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.
---------------------------------------------------------------------------

    \920\ Northwestern University. (2017). PROMIS Item Bank v. 1.0--
Emotional Distress--Anger--Short Form 1.
---------------------------------------------------------------------------

    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 ``Final 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.

[[Page 42588]]

    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 
proposed to adopt the Social Isolation data element previously 
described as SPADE with respect to the proposed Social Determinants of 
Health category. We proposed to add the Social Isolation data element 
to the LCDS.
    Comment: A commenter noted that, if finalized, LTCHs should only 
need to submit data on the Race and Ethnicity SPADEs with respect to 
admission and would not need to collect and report again at discharge, 
as it is unlikely that patient status for these elements will change. 
They believe that a patient's response to the Social Isolation SPADE 
also is unlikely to change between admission and discharge; thus, the 
commenter recommended CMS to require collection of this SDOH SPADE with 
respect to admission only.
    Response: We disagree with the commenter who stated that social 
isolation responses will always be the same from admission to 
discharge. Unlike Vision, Hearing, Race, Ethnicity, Preferred Language, 
and Interpreter Services, we believe that the response to this question 
will change from admission to discharge; therefore, the SPADE is 
required to be collected at both admission and discharge. For example, 
losing a family member or caregiver between admission and discharge 
could change how the patient responds to the Social Isolation SPADE. 
Therefore, we proposed to collect this SPADE with respect to both 
admission and discharge.
    Comment: A commenter stated that the proposed question on social 
isolation may have a very different answer based on the time horizon 
considered by the beneficiary as beneficiaries who are newly admitted 
to an LTCH may have experienced differing levels of social isolation 
over the preceding week due to interactions with health care providers, 
emergency providers, and friends or family visiting due to 
hospitalization. The commenter believes this question could be improved 
by adding timeframe to the question. For example, ``How often have you 
felt lonely or isolated from those around you in the past 6 months?''
    Response: We thank the commenter for this comment. The Social 
Isolation data element is assessing if a patient has experienced social 
isolation in the past six months to a year. The proposed Social 
Isolation data element is currently part of the Accountable Health 
Communities (AHC) Screening Tool. The AHC item was selected from the 
Patient-Reported Outcomes Measurement Information System 
(PROMIS[supreg]) Item Bank on Emotional Distress. The Social Isolation 
SPADE is asking about the last 6 months to 1 year.
    After consideration of the public comments we received, and for the 
reasons discussed, we are finalizing our proposal with regard to the 
Social Isolation SPADE as proposed.
    After consideration of the public comments, we are finalizing our 
proposals to collect SDOH data for the purposes under section 
2(d)(2)(B) of the IMPACT Act and section 1899B(b)(1)(B)(vi) of the Act 
as follows. We are finalizing our proposals for Race, Ethnicity, Health 
Literacy, Transportation, and Social Isolation as proposed. In response 
to stakeholder comments, we are revising our proposed policies and 
finalizing that LTCHs that submit the Preferred Language and 
Interpreter Services SPADEs with respect to admission will be deemed to 
have submitted with respect to both admission and discharge.
8. 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.
    We received some comments regarding the LTCH CARE Data Set, which 
we summarize and respond to in this final rule.
    Comment: A commenter was appreciative that CMS provided extensive 
supporting materials describing the proposed new and modified LTCH CARE 
Data Set items along with a change table as it helps foresee necessary 
software updates and system changes from a very early date. However, 
the commenter stated that it would be extremely useful to have early 
drafts of the new and modified data elements within the context of the 
entire assessment instrument.
    Response: We appreciate the commenters' support and suggestions and 
will take them into consideration for future proposed new and modified 
LTCH CARE Data Set data elements.
    Comment: A commenter provided feedback on the proposed set of LTCH 
CARE Data Set changes and the effect, if finalized, it would have on 
existing software user interfaces. The proposed changes to ethnicity, 
race, admitted from, and discharge location were cited as items which 
would require many LTCHs to reopen existing and long-running 
interfaces; this would likely result in many LTCHs no longer being able 
to take race and ethnicity information electronically. The commenter 
also cited that these data set changes would require reworking of 
existing interoperability as both sides of the interface (sending 
hospitals and receiving systems) would need to rewrite whole sections 
of that functionality to accommodate the modifications to CAM and 
Spontaneous Breathing Trial (SBT) items and that the cost of making 
these changes will act as a deterrent to hospitals to invest the time 
and money in building out interoperability. The commenter further 
specified that very small item set changes would require 
disproportionate amounts of work that impact all activities associated 
with data collection, submission, and reporting.
    Response: We acknowledge the complexities and level of effort 
required to modify an existing software user interface to collect the 
revised ethnicity, race, admitted from, discharge location, CAM, and 
SBT data elements. As mentioned previously, the Race and Ethnicity data 
elements were modified to standardize the submission of race and 
ethnicity data among IRFs, HHAs, SNFs and LTCHs. In addition, we agree 
on the importance of improving response options for these items as a 
component of improving health care assessments and for monitoring 
disparities and as a first step in improving quality of care and health 
outcomes. The Admission From and Discharge Location data elements were 
also modified to standardize among IRFs, HHAs, SNFs, and LTCHs for the 
Transfer of Health Information quality measures. Modifications to the 
CAM and SBT items were made to support alignment with the SNF and IRF 
settings and for clarity, respectively.
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, in the FY 2020 IPPS/LTCH PPS proposed 
rule (84 FR 19552), we proposed to designate that system as the data 
submission system for the LTCH QRP beginning October 1, 2019. We also 
proposed to revise our regulations at Sec.  412.560(d)(1) by replacing 
the reference to ``Quality Improvement and Evaluation System

[[Page 42589]]

(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 proposed to notify the public of any 
future changes to the CMS designated system using subregulatory 
mechanisms such as website postings, listserv messaging, and webinars.
    We did not receive any comments on this proposal. Therefore, we are 
finalizing our proposal to revise our regulations at Sec.  
412.560(d)(1), (d)(3), and (f)(1) as proposed. We are also finalizing 
our proposal 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. 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 the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19552 through 19553), we proposed 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 also proposed 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 in this section 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) measure data, which is submitted annually.
[GRAPHIC] [TIFF OMITTED] TR16AU19.191

    Comment: Commenters supported moving the implementation date of the 
LTCH CARE Data Set from April to October. A commenter appreciated that 
this change will provide LTCHs with an additional 6 months to prepare 
for any changes made to the LTCH CARE Data Set and will provide more 
time to adequately train staff on any changes to the LTCH CARE Data 
Set. The commenter also supported CMS' related proposal that for the 
first program year in which a new measure or SPADE is adopted, LTCHs 
would only need to report data on patients admitted or discharged in 
the last calendar quarter of the year (October 1 to December 31).
    Response: We appreciate the commenters' support. We would like to 
clarify that for the first program year in which a new measure or SPADE 
is adopted, LTCHs would only need to report data on patients admitted 
or

[[Page 42590]]

discharged in the last calendar quarter of the year (October 1 to 
December 31). 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.
    After consideration of the public comments we received, we are 
finalizing our proposal to move the implementation date of any new 
version of the LCDS from April to October, beginning October 1, 2020. 
We are also finalizing our proposal that, for the first program year in 
which measures or standardized patient assessment data are adopted, 
LTCHs will 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 will be required to report data on patients who 
are admitted and discharged during the 12-month calendar year that 
applies to the program year.
d. 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 final 
rule, we are adopting 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. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19553), we also proposed 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 final rule for an illustration of the initial and 
calendar year reporting cycles.
    We did not receive any comments on this proposal.
    We are finalizing our proposal that LTCHs report the data on 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 using the LTCH CARE Data Set as proposed. LTCHs will 
be required to collect data on both measures for all patients beginning 
with October 1, 2020 discharges.
e. 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 final 
rule, we are adopting SPADEs beginning with the FY 2022 LTCH QRP. In 
the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19553), we proposed 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 final rule for an illustration of the initial and calendar year 
reporting cycles.
    We did not receive any comments on this proposal.
    We are finalizing our proposal that LTCHs must submit the SPADEs 
for all patients beginning October 1, 2020 with respect to admissions 
and discharges using the LTCH CARE Data Set. LTCHs that submit data 
with respect to admission for the Hearing, Vision, Preferred Language, 
Interpreter Services, Race, and Ethnicity SPADEs will be considered to 
have submitted data with respect to discharges.
9. 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 the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19553), we proposed that we will no longer 
publish a list of compliant LTCHs on the LTCH QRP website effective 
beginning with the FY 2020 payment determination.
    We did not receive any comments on this proposal.
    We are finalizing our proposal that we will no longer publish a 
list of compliant LTCHs on the LTCH QRP website beginning with the FY 
2020 payment determination.
10. 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19553 through 
19554), we proposed 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 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 proposed 
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 proposed 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.''
    Comment: Several commenters supported the proposal to begin 
publicly displaying data for the Drug

[[Page 42591]]

Regimen Review Conducted With Follow-Up for Identified Issues--Post 
Acute Care (PAC) Long Term Care Hospital (LTCH) Quality Reporting 
Program (QRP) measure in CY 2020 or as soon as technically feasible, 
including the exception for LTCHs with fewer than 20 eligible cases.
    Response: We appreciate the commenters support.
    After consideration of the public comments we received, we are 
finalizing our proposal to begin publicly displaying data for the Drug 
Regimen Review Conducted With Follow-Up for Identified Issues--PAC LTCH 
QRP measure beginning CY 2020 or as soon as technically feasible.

D. 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 EHR 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.
2. EHR Reporting Period
a. 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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19554 through 
19555), we proposed 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 final 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 will provide such eligible hospitals all of 
CY 2019 to complete their respective minimum 90-day EHR reporting 
period for the FY 2020 payment adjustment year. We also proposed to 
revise the definition of ``EHR reporting period for a payment 
adjustment year'' at 42 CFR 495.4 to reflect this proposal.
    Comment: Many commenters supported the modification of the Query of 
PDMP measure to a ``yes/no'' attestation. Those same commenters were 
strongly in favor of CMS eliminating the October 1, 2019 deadline for 
an eligible hospital that has not successfully demonstrated it is a 
meaningful EHR user in a prior year and for CMS allowing flexibility to 
attest on data from any continuous 90-day period from January 1, 2019 
through December 31, 2019. Commenters stated that this continuation 
will allow hospitals to focus on improving interoperability and patient 
access to health information.
    Response: We appreciate the commenters' support, and we believe 
that both of these changes will help to reduce burden for eligible 
hospitals.
    As described in this section of the final rule, we are finalizing 
the conversion of the Query of PDMP measure to a yes/no attestation. 
Because we are finalizing this change, and after consideration of the 
public comments, we are, also, finalizing our proposal to 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. 
Those eligible hospitals that have not demonstrated themselves as being 
meaningful EHR users in a prior year will have all of CY 2019 to 
complete their respective minimum 90-day EHR reporting period for the 
FY 2020 payment adjustment year. We are, also, finalizing the revised 
definition of ``EHR reporting period for a payment adjustment year'' at 
42 CFR 495.4 as proposed.
b. 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 Sec.  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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19554 through 
19555), for CY 2021, we proposed 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 also proposed 
corresponding changes to the definitions of ``EHR reporting period'' 
and ``EHR reporting period for a payment adjustment year'' at Sec.  
495.4.
    In the July 28, 2010 final rule titled ``Medicare and Medicaid 
Programs; Electronic Health Record Incentive Program'' (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 Sec.  495.310(f)). Therefore, December 31, 2021 is the 
last date that States could make Medicaid Promoting

[[Page 42592]]

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 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 did not propose to do so 
in the FY 2020 IPPS/LTCH PPS 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 a comment agreeing with 
us, but we also stated that we will solicit additional comments on this 
issue in a proposed rule that is more specifically related to hospital 
payment (83 FR 59705 through 59706). Accordingly, in the proposed rule 
we again invited comments on whether we are correct in believing that 
there are no hospitals that would be able to receive Medicaid Promoting 
Interoperability Program payments in 2021. If this is not true, we 
sought comment on how we should adjust 2021 EHR reporting periods for 
Medicaid eligible hospitals in a manner that limits the burden on 
hospitals and States.
    Comment: Many commenters strongly supported the minimum of a 
continuous 90-day EHR reporting period. Commenters stated that the 
proposed EHR reporting period allows eligible hospitals and CAHs to 
adequately plan for any system updates and that it reduces 
administrative and regulatory burden. Several commenters, also, 
expressed their appreciation toward CMS for its efforts, including the 
proposed 90-day EHR reporting period, to help stabilize the Promoting 
Interoperability Programs.
    Response: We appreciate the support for our EHR reporting period 
proposal. We agree that keeping the EHR reporting period to a minimum 
of 90 days affords eligible hospitals and CAHs the flexibility they may 
need to develop and update their evolving EHRs.
    Comment: A commenter suggested that CMS should make the minimum 90-
day EHR reporting period permanent, as opposed to what CMS has done 
over the past several years, which is propose the minimum 90-day EHR 
reporting period each year.
    Response: We thank the commenter for the suggestion, and we will 
take this into consideration for future rulemaking.
    Comment: A commenter agreed with the 90-day EHR reporting period, 
but suggested that CMS not put an end date on the EHR reporting period.
    Response: We understand the concern over the limitations an end 
date could have, but the EHR reporting period is not required to end on 
the 90th day. The minimum EHR reporting period is a continuous 90 days, 
but an eligible hospital or CAH may choose to extend the period to be 
as long as the full calendar year, as long as the EHR reporting period 
ends no later than December 31.
    Comment: A commenter responded to CMS' invitation of comments on 
its understanding that there are no hospitals that will be able to 
receive Medicaid Promoting Interoperability Program payments in 2021, 
and the commenter was in agreement with CMS.
    Response: We thank the commenter for his or her input. In addition, 
we did not receive any comments indicating that there are hospitals 
that would be able to receive Medicaid Promoting Interoperability 
Program payments in 2021.
    After consideration of the public comments received, we are 
finalizing our proposal of 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 are, also, finalizing the 
corresponding changes to the definitions of ``EHR reporting period'' 
and ``EHR reporting period for a payment adjustment year'' at 42 CFR 
495.4 as proposed.
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 \921\) applicable to the Medicare and Medicaid 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 timeframe 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 will 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 will 
increment over a longer period of time. Therefore, in the FY 2020 IPPS/
LTCH PPS proposed rule (84 FR 19555 through 19556), we proposed 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

[[Page 42593]]

measures in the Medicare Promoting Interoperability Program will only 
increment based on actions that have occurred during the EHR reporting 
period that was selected by the eligible hospital or CAH. We also 
proposed to codify this proposed policy at Sec.  495.24(e)(1)(ii).
---------------------------------------------------------------------------

    \921\ https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Downloads/FAQs.pdf.
---------------------------------------------------------------------------

    We noted that 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 proposed to 
revise Sec.  495.24(e)(4)(iii) to reflect this existing policy for the 
Security Risk Analysis measure.
    In addition, we stated that these proposals will not apply to the 
Medicaid Promoting Interoperability Program.
    Comment: Several commenters supported CMS' proposal that the 
numerators and denominators of measures in the Medicare Promoting 
Interoperability Program will only increment based on actions that have 
occurred during the EHR reporting period that was selected by the 
eligible hospital or CAH.
    Response: We believe that incrementing the numerator and 
denominator should be limited to actions that have occurred in the EHR 
reporting period chosen by the eligible hospital or CAH, as opposed to 
requiring some measures to be incremented outside of the EHR reporting 
period as this will help to eliminate the confusion surrounding when 
measures may be incremented.
    Comment: Several commenters recommended that CMS maintain its 
current policy, with the belief that changes to EHR systems and 
reporting processes will be challenging. Additionally, commenters 
expressed confusion about the length of time the numerators of measures 
could accrue, as long as the action occurred within the calendar year, 
versus actions only being counted that have occurred during the 
selected EHR reporting period.
    Response: We disagree that any changes to EHR systems and reporting 
processes will be challenging, and we believe that this policy change 
will help to eliminate the confusion for both, vendors and eligible 
hospitals/CAHs, surrounding when the numerators and denominators of 
measures will increment. The EHR reporting period is not limited to the 
minimum 90 consecutive days. Eligible hospitals and CAHs have the 
flexibility to choose an EHR reporting period that is as long as the 
entire calendar year, so that the numerators and denominators will 
increment over a longer period of time. Doing this will allow for all 
actions that occurred in the calendar year to be counted in the 
numerators and denominators. However, if an eligible hospital or CAH 
elects to have their EHR reporting period be, for example, 200 
consecutive days, then only the actions that occurred over the course 
of those 200 consecutive days will be counted in the numerators and 
denominators.
    Comment: A commenter sought clarification on whether an eligible 
hospital or CAH may achieve ``active engagement'' for purposes of the 
Public Health and Clinical Data Exchange objective by engaging in one 
of the three types of active engagement outside its selected EHR 
reporting period.
    Response: Our proposal that the numerators and denominators of 
measures will only increment based on actions that have occurred during 
the EHR reporting period that was selected by the eligible hospital or 
CAH was limited to measures with numerators and denominators. Our 
proposal did not include measures that require a ``yes/no'' response, 
such as the measures associated with the Public Health and Clinical 
Data Exchange objective.
    After consideration of the public comments we received, we are 
finalizing our proposal so that, beginning with the EHR reporting 
period in CY 2020, eligible hospitals and CAHs that submit an 
attestation to CMS under the Medicare Promoting Interoperability 
Program will have the numerators and denominators of measures increment 
based on actions that have occurred during the EHR reporting period 
that was selected by the eligible hospital or CAH. We are, also, 
codifying this policy at Sec.  495.24(e)(1)(ii) as proposed. As 
previously noted, the actions included in the Security Risk Analysis 
measure may still occur any time during the calendar year in which the 
EHR reporting period occurs, and we are finalizing our proposal to 
revise Sec.  495.24(e)(4)(iii) to reflect this existing policy for the 
Security Risk Analysis measure.
3. 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 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.
    As explained in further detail in this final rule and in the FY 
2020 IPPS/LTCH PPS proposed rule (84 FR 19556 through 19559), we 
proposed 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 
the proposed rule (84 FR 19560 through 19561), we proposed to adopt two 
opioid-related clinical quality measures beginning with the EHR 
reporting period in CY 2021.
c. 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 will 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). We 
believe incorporating a requirement for integration, in the context of 
future changes to the measure, between PDMPs and CEHRT utilized by 
eligible hospitals and CAHs, will advance the access to and usability 
of PDMP data by health care providers, and it will 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 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 for 
only one 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 will require more robust 
certification specifications and standards. Stakeholders stated that 
health IT developers may face significant cost burdens under the 
current flexibility allowed for health care providers if they fully 
develop numerator and denominator calculations for all the potential 
use cases, and are required to change the specification at a later 
date. Developers expressed their view that the costs of

[[Page 42594]]

additional development will likely be passed on to health care 
providers without additional benefit as they believe this development 
will be solely for the purpose of calculating the measure rather than 
furthering the clinical end goal of the measure.
    For the reasons discussed in the FY 2020 IPPS/LTCH PPS proposed 
rule (84 FR 19557 through 19558), we proposed to make the Query of PDMP 
measure optional in CY 2020 and eligible for 5 bonus points, and we 
proposed corresponding changes to the regulations at Sec. Sec.  
495.24(e)(5)(ii)(B) and 495.24(e)(5)(iii)(B). We stated that making the 
measure optional in CY 2020 will allow time for further integration of 
PDMPs and EHRs to minimize the burden on eligible hospitals and CAHs 
when reporting on this measure. We proposed that, in the event we 
finalize the proposed changes to the Query of PDMP measure, the e-
Prescribing measure will be worth up to 10 points in CY 2020 and 
subsequent years, and we proposed corresponding changes to the 
regulations at Sec.  495.24(e)(5)(iii)(A).
    In addition, beginning with the EHR reporting period in CY 2019, we 
proposed 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 will remain the same, but instead 
of submitting numerator and denominator information for the measure, 
eligible hospitals and CAHs will 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 also proposed to remove the exclusions associated with the Query 
of PDMP measure beginning in CY 2020, and we proposed 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 will 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 proposed 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. We proposed 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 as previously discussed, in CY 
2020 as well. We stated that in the event we finalize those proposed 
changes, if an eligible hospital or CAH submits a ``yes'' for this 
measure, it will earn 5 bonus points in CY 2019 and 2020.
    Comment: A few commenters agreed with changing the maximum points 
for e-Prescribing measure from 5 points to 10 points.
    Response: We thank commenters for their support.
    Comment: A majority of commenters are supportive of the proposed 
changes to the Query of PDMP measure. Many commenters agree with 
retaining the measure as optional in CY 2020, further recommending that 
in order to make it mandatory, the Office of the National Coordinator 
for Health Information Technology (ONC) should consider adopting new 
certification criteria requiring EHRs to integrate with PDMPs. These 
commenters also agree with changing the measure to a yes/no attestation 
response rather than the current performance-based numerator-
denominator calculation. Commenters agree that these changes will 
reduce unnecessary burden, as developing custom reports are often time-
consuming and inaccurate.
    Response: We appreciate commenters' support of our proposal to make 
the Query of PDMP measure optional in CY 2020, and to require a yes/no 
measure instead of a numerator-denominator calculation. We believe this 
proposal will reduce overall provider burden by requiring a yes/no 
measure instead of a numerator and denominator calculations that have 
various potential use cases calculations varying by states which will 
require changes to the specifications at a later date and eliminate 
providers performing manual calculations of the numerator and 
denominator outside of certified EHR functionality.
    We also wish to note that ONC has proposed in the 21st Century 
Cures Act: Interoperability, Information Blocking, and the ONC Health 
IT Certification Program Notice of Proposed Rulemaking (84 FR 7444) to 
update the electronic prescribing (e-Rx) SCRIPT standard used for 
``electronic prescribing'' in the 2015 Edition to NCPDP SCRIPT 2017071, 
which will result in a new e-Rx standard becoming the baseline for 
certification . As summarized in the FY 2019 IPPS/LTCH PPS final rule 
(83 FR 41650), stakeholders have stated that they believe adoption of 
the NCPDP SCRIPT 2017071 standard for EHRs can more effectively support 
medication history transactions for PDMP queries and responses.
    Comment: A commenter suggested removing the e-prescribing component 
of the measure altogether due to time and cost burdens associated with 
its implementation.
    Response: We appreciate the concern surrounding provider and data 
collection burden, and we continue to make burden reduction a priority 
in the decision making process. The electronic prescribing component of 
the Query of PDMP measure is a central aspect in interoperability and 
alignment between the Query of PDMP measures with the e-Prescribing 
measure. This may reduce burden for eligible hospitals and CAHs that 
may have prescribed differently without those standards in place.
    Comment: A commenter expressed doubt in the ability of a ``yes/no'' 
measure to capture any clinically useful information, and suggested 
that CMS not use ``yes/no'' measures moving forward. Other commenters 
shared similar concerns that a yes/no measure would not capture enough 
clinically useful information, and that changing the scoring system in 
the middle of CY 2019 might be challenging for reporting.
    Response: We understand the concern and appreciate the feedback. 
However, regarding the Query of PDMP measure specifically, we believe 
that it is premature for this measure to be a numerator/denominator 
measure at this time and the numerator and denominator measure would 
not capture any clinically useful information.
    We also disagree that changing the scoring in the middle of CY 2019 
would be challenging for reporting as this would reduce provider burden 
when manually calculated numerator/denominators. Currently, there is 
limited use of consistent standards-based approaches to support 
integration between CEHRT and PDMPs, which contributes to eligible 
hospitals and CAHs having to manually track each PDMP query. 
Considering the added burden that doing this creates, we

[[Page 42595]]

believe a ``yes/no'' measure is more appropriate.
    Comment: Some commenters expressed concerns with the PDMP measure, 
primarily due to the lack of uniformity in the implementation and 
functionality of PDMPs across state lines. Because there are no 
standard criteria for PDMP functionality, commenters told CMS that, in 
their view, the measure is not ready for mandatory inclusion in the 
performance-based scoring methodology. Several commenters stated that 
eligible hospitals and CAHs will have wasted effort if the measure were 
removed completely.
    Response: We understand that PDMP systems comprise various 
processes and components that vary significantly across state lines, 
and that in any given state the PDMP system may include varying state-
developed and vendor-based solutions along with the core PDMP database. 
State laws and policies also differ on data storage and use, access 
roles and disclosures, and key definitions. The degree of PDMP and 
health IT (EHR, HIE, PDS) access integration (how the provider can 
access the PMDP) varies significantly across states, but also within 
states by product and/or health system. Today, most PDMP systems allow 
a provider ``view only'' access to PDMP data rather than allowing for 
the integration of discrete data from the PDMP system into the 
patient's record.
    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) includes new 
requirements and federal funding for PDMP enhancement, integration, and 
interoperability, and establishes mandatory use of PDMPs by certain 
Medicaid providers. CMS is continuously working with various 
stakeholders and the ONC to evaluate the implementation of the SUPPORT 
for Patients and Communities Act and progress around PDMP-EHR 
integration.
    We proposed to change the measure to optional in CY 2020 in order 
to account for readiness concerns such as those raised by stakeholders. 
CMS is dedicated to alleviating the concerns of the commenters as we 
work to further develop the measure.
    Comment: Several commenters requested clarification on whether CMS' 
intention is that the query activity must be facilitated by the use of 
CEHRT or if it can be performed outside of CEHRT and still be counted 
toward the numerator of the measure. Others stated that it is also 
unclear whether providers are to count queries of the PDMP for 
inpatients only.
    Response: As stated in the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41653), the measure description is as follows: for at least one 
Schedule II 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. In regards to commenters' assertion that it is 
unclear whether providers are to count queries of the PDMP for 
inpatients only, we have not addressed this issue in previous 
rulemaking and will consider doing so in future rulemaking.
    After consideration of the public comments we received, we are 
finalizing that the Query of PDMP measure is optional and eligible for 
5 bonus points in CY 2020 and finalizing corresponding changes to the 
regulations at Sec. Sec.  495.24(e)(5)(ii)(B) and 495.24(e)(5)(iii)(B) 
as proposed. We are also finalizing that the e-Prescribing measure will 
be worth up to 10 points beginning in CY 2020 and finalizing 
corresponding changes to the regulations at Sec.  495.24(e)(5)(iii)(A) 
as proposed.
    In addition, beginning with the EHR reporting period in CY 2019, we 
are finalizing our proposal 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. The measure description at Sec.  
495.24(e)(5)(iii)(B) and 83 FR 41653 will 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 indicates 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 also 
finalizing the proposal to remove the exclusions associated with the 
Query of PDMP measure beginning in CY 2020, and finalizing the 
corresponding changes to the regulations at Sec. Sec.  495.24(e)(5)(iv) 
and 495.24(e)(5)(v)(B) through (D) as proposed.
    Finally, we are finalizing our proposal to revise Sec.  
495.24(e)(5)(iii)(B) as proposed 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 CY 2020.
d. 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 promote interoperability. 
Stakeholders cited the lack of definition around a treatment agreement, 
the lack of certification standards and criteria, confusion with how to 
calculate the 30 cumulative day look-back period, and the burden caused 
by the lack of definition and standards. For the reasons discussed in 
the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19558 through 19559), we 
proposed to remove the Verify Opioid Treatment Agreement measure from 
the Promoting Interoperability Program beginning with the EHR reporting 
period in CY 2020, and we proposed corresponding changes to the 
regulations at Sec. Sec.  495.24(e)(5)(ii)(B) and 495.24(e)(5)(iii)(C).
    We also proposed 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 previously 
discussed Query of PDMP measure, in section VIII.D.3.b. of the preamble 
of this final rule, 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 proposed in (84 FR 19559) 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, 
it will be worth a full 5 bonus points in CY 2020, as well.
    Comment: A vast majority of commenters were in general agreement 
with removing the Verify Opioid Treatment Agreement measure. Several 
commenters stated that if the measure were to remain, it would result 
in increased provider burden and

[[Page 42596]]

decreased interoperability. A few commenters supported removing the 
measure until treatment agreement standards themselves are addressed, 
defined, and further clarified. A number of commenters were strongly 
supportive, further stating their belief that this measure is not 
appropriate for inpatient hospitals, and lacks standards defining the 
specific data points and structure to be included in such an agreement. 
Commenters expressed that this measure is therefore burdensome, vague 
and insurmountable, presenting significant implementation challenges as 
it is subject to misinterpretation until and unless such certification 
requirements are made clear.
    Response: We thank all commenters for their overwhelming support 
for removing the Verify Opioid Treatment Agreement measure beginning 
with CY 2020. We agree that while addressing OUD prevention and 
treatment is vital, the Verify Opioid Treatment Agreement measure 
presents significant implementation challenges, leads to an increase in 
burden, and as-is, does not promote interoperability. We thank all 
commenters for their suggestions on how to enhance and improve such a 
measure as we continue to combat the opioid crisis.
    Comment: A few commenters suggested that instead of removing the 
measure entirely, CMS should change it to a yes/no measure starting 
from CY 2019 rather than CY 2020. One commenter requested making the 
measure an optional, yes/no measure for three EHR reporting periods 
before retiring the measure entirely in CY 2022. The commenter further 
stated that based on the FY 2019 IPPS/LTCH PPS final rule, this measure 
would be required in 2021, and as some hospitals have already put 
significant work toward implementing functionality to meet the measure, 
retaining the optional bonus points for an additional two years would 
respect the good faith effort that has already been made. A commenter 
suggested removing the measure in CY 2019, or, changing it to a yes/no 
measure as both options would significantly reduce reporting burden 
until a more appropriate measure set could be developed. Many 
commenters agreed that an opioid specific measure is important in 
addressing the opioid epidemic, but requested that the Verify Opioid 
Treatment Agreement measure be removed while encouraging innovation 
around future collaborative measure development.
    Response: We understand and appreciate the concerns and suggestions 
addressed by the commenters who do not agree with the removal of the 
Verify Opioid Treatment Agreement measure starting in CY 2020. We 
considered the suggestions to change the measure to a yes/no measure or 
to delay its retirement until 2022. However, we agree with the vast 
majority of commenters who cited the lack of definition around the 
treatment agreements, and the lack of certification criteria and 
standards as reasons for the removal of the measure at this time. In 
addition, many stakeholders have stated that this measure presents 
significant implementation challenges that leads to an increase in 
burden, and does not promote interoperability which we do not believe 
would be beneficial by requested keeping the measure as an optional, 
yes/no measure for three EHR reporting periods before retiring the 
measure entirely in CY 2022. While several commenters requested 
changing the measure to a yes/no attestation for CY 2019, we have 
decided that the measure will remain an optional, numerator/
denominator-based measure in CY 2019 only.
    Comment: A few commenters have requested additional clarification 
on the CY 2019 EHR reporting period, specifically, on how the measure 
will be scored. A commenter further suggested conducting pilot testing 
to assess the feasibility of exchanging information before 
reintroducing the measure in the future.
    Response: We thank commenters for the suggestions. For the CY 2019 
EHR reporting period, the Verify Opioid Treatment Agreement measure 
will remain an optional, numerator/denominator-based measure. 
Additionally, the measure will be worth a full 5 bonus points. We would 
like to thank the commenter for their suggestion of conducting pilot/
feasibility testing for future measures, and if we decide to pursue 
this measure in the future, we will consider how to best operationalize 
the requirements while minimizing the burden on providers.
    After consideration of the public comments we received, we are 
finalizing the proposal to remove the Verify Opioid Treatment Agreement 
measure from the Promoting Interoperability Program beginning with the 
EHR reporting period in CY 2020 and the corresponding changes to the 
regulations at Sec. Sec.  495.24(e)(5)(ii)(B) and 495.24(e)(5)(iii)(C) 
as proposed. In addition, we are finalizing the proposal to revise 
Sec.  495.24(e)(5)(iii)(C) as proposed 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.
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, in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19559), we 
proposed to revise the regulations for the Support Electronic Referral 
Loops by Receiving and Incorporate Health Information measure. We 
proposed 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.
    Comment: Commenters supported our proposal and appreciated the 
effort CMS puts forth to keep language clear and expectations precise. 
They shared that the proposal reflects how eligible hospitals and CAHs 
have interpreted and implemented the measure requirements.
    Response: We thank commenters for their support.
    Comment: Several commenters raised issues not related to the 
proposal for this measure, including separating the two elements of the 
measure and creating two separate measures, requesting that the measure 
be a yes/no measure, and removing the requirements to reconcile 
medication, medication allergy, and current problem list.
    Response: We appreciate this input and may take it under 
consideration in future rulemaking.
    Comment: A commenter requested clarification as to whether the 
requirement that clinical information reconciliation must be conducted 
using CEHRT under the Support Electronic Referral Loops by Receiving 
and Incorporating Health Information measure is applicable only to the 
HIE objective within the Medicare Promoting Interoperability Program.
    Response: Our proposal was only applicable to the Support 
Electronic

[[Page 42597]]

Referral Loops by Receiving and Incorporating Health Information 
measure under Sec.  495.24(e)(6)(ii)(B) for the Medicare Promoting 
Interoperability Program.
    After consideration of the public comments we received, we are 
finalizing the proposed revisions to Sec.  495.24(e)(6)(ii)(B) as 
proposed.
5. 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 final rule, we are finalizing our proposals 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) make the 
maximum points available for the e-Prescribing measure 10 points.
    This table reflects the policies that we are finalizing for the 
objectives, measures, and maximum points available for the EHR 
reporting period in CY 2020. The maximum points available per measure 
do not include points that would be redistributed in the event that an 
exclusion is claimed.
[GRAPHIC] [TIFF OMITTED] TR16AU19.192

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.
    This table 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).
[GRAPHIC] [TIFF OMITTED] TR16AU19.193


[[Page 42598]]


b. 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, in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19560 
through 19561), we proposed to adopt two new opioid-related clinical 
quality measures and sought 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 the proposed rule, we proposed 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. We also proposed 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 final rule.
    In the proposed rule, we acknowledged that some stakeholders have 
expressed concern that some providers could withhold the use of 
naloxone for patients who are in respiratory depression, believing it 
may help providers to avoid poor performance on the proposed Hospital 
Harm--Opioid-Related Adverse Events CQM (84 FR 19479 through 19480). 
Therefore, we solicited public comment on the potential of this measure 
to disincentivize the appropriate use of naloxone in the hospital 
setting, or, for the withholding of opioids where they are clinically 
necessary, such as with patients requiring palliative care or those who 
are considered end of life, out of an overabundance of caution.
    Comment: Several commenters applauded the proposed alignment 
between the Hospital IQR Program and the Promoting Interoperability 
Program on the two opioid-related CQM policies; (1) Safe Use of 
Opioids--Concurrent Prescribing and (2) Hospital Harm--Opioid-Related 
Adverse Events eCQM.
    Response: We appreciate commenters' support for the proposed 
alignment between the Hospital IQR Program and the Promoting 
Interoperability Program on the two opioid-related CQM policies. 
Together, we want to ensure that we continue to minimize burden while 
maintaining a set of meaningful CQMs that will ultimately improve the 
quality of care provided to patients.
    Comment: Many commenters are supportive of the proposal to include 
the two new opioid CQMs. Of the reasons given, several state that these 
CQMs will aid in reducing opioid related adverse events, it will 
provide a richer picture into clinical care, and they will aid in 
assessing the high priority opioid epidemic.
    Response: We thank commenters for their overwhelming support as we 
continue to align the Hospital IQR Program and the Promoting 
Interoperability Program on the opioid related policies CQM policies. 
We agree with commenters that the Safe Use of Opioids--Concurrent 
Prescribing CQM will aid in reducing opioid related adverse events, it 
will provide a richer picture into clinical care, and they will aid in 
assessing the high priority opioid epidemic. Together, we want to 
ensure that we continue to minimize burden for the Hospital IQR Program 
and the Promoting Interoperability Program while maintaining a set of 
meaningful CQMs that will ultimately improve the quality of care 
provided to patients.
    Comment: A commenter suggested that CMS define and implement a 
long-term plan for PDMP and EHR integration before adding new CQMs.
    Response: We thank the commenter for their feedback. PDMP systems 
comprise various processes and components that vary significantly 
across state lines, and in any given state, the PDMP system may include 
varying levels of state-developed and/or vendor-based solutions along 
with the core PDMP database. State laws and policies also differ on 
data storage and usage, access roles and disclosures, and key 
definitions. The degree of PDMP and health IT (EHR, HIE, PDS) access 
integration (how the provider can access the PMDP) varies significantly 
both across and within state lines, by product and/or health system. 
CMS is continuously working with various stakeholders and the ONC to 
evaluate the implementation of the Support for Patients and Communities 
Act and the readiness of a standardized, integrated PDMP into EHRs.
    Additionally, The Safe Use of Opioids--Concurrent Prescribing CQM 
does not require the use of PDMP and EHR integration. The goal of The 
Safe Use of Opioids--Concurrent Prescribing CQM is to is intended to 
facilitate safer patient care not only by promoting adherence to 
recommended clinical guidelines on concurrent prescribing practices, 
but also in incentivizing hospitals to develop strategies to identify 
and monitor patients on concurrent opioid and opioid-benzodiazepine 
prescriptions, who might be at higher risk of adverse drug events. We 
do not believe that adding The Safe Use of Opioids--Concurrent 
Prescribing CQM should wait until PDMPs and EHRs are universally 
integrated, as this measure seeks to promote safer prescribing 
practices and incentivize providers to recognize and identify high-risk 
patients with concurrent regimens; these strategies may help combat the 
negative effects of the opioid crisis.
    Comment: Several commenters requested that CMS extend timeframes 
for mandating the proposed CQMs until each is fully endorsed by the 
NQF, to avoid any unforeseen consequences from implementation. Further, 
the general consensus is that until measure specifications have been 
clearly defined, the CQMs should not be made mandatory.
    Response: We refer readers to section XIII.A.5.a.(1). of the 
preamble of this final rule where we discuss the adoption of the Safe 
Use of Opioids--Concurrent Prescribing CQM and how this measure was 
tested for feasibility, reliability, and validity and received NQF 
endorsement. We believe adding the Safe Use of Opioids--Concurrent 
Prescribing CQM to the CQM measure set beginning in CY 2021 for 
reporting and requiring eligible hospitals and CAHs to report on the 
Safe Use of Opioids--Concurrent Prescribing CQM beginning with the CY 
2022 reporting period is an appropriate timeframe because it will 
afford hospitals and vendors sufficient time to work through 
implementation, testing, and reporting challenges.
    With regard to the Hospital Harm--Opioid-Related Adverse Events 
CQM, the NQF Patient Safety Standing Committee was concerned about 
using naloxone as a proxy for harm in the numerator and including all 
patients admitted to the hospital in the denominator, rather than 
limiting the denominator to only patients that have been administered 
opioids by the hospital. With respect to commenters' concerns, and with 
the NQF Patient Safety Standing Committee voting to not endorse this 
measure, we are not finalizing our proposal to adopt the Hospital 
Harm--Opioid-Related Adverse Events CQM for the Promoting 
Interoperability Program. For a complete discussion of the reasons why 
we are not adopting the Hospital Harm--

[[Page 42599]]

Opioid-Related Adverse Events CQM, we refer readers to section 
XIII.A.5.a.(1). of the preamble of this final rule.
    Comment: Several commenters requested clarification on the Safe Use 
of Opioids--Concurrent Prescribing CQM's definition.
    Response: In the proposed rule, we provided readers with a link to 
NQF's Patient Safety, Fall 2017 Cycle: CDP Report (84 FR 19477), where 
the measure specifications for the Safe Use of Opioids--Concurrent 
Prescribing CQM can be found. We further note that measure 
specifications can be found on the eCQI Resource Center,\2\ which 
provides a centralized location for news, information, tools, and 
standards related to CQMs. For a more complete discussion of this 
measure, we refer readers to section XIII.A.5.a. (1). of the preamble 
of this final rule.
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    \2\ https://protect2.fireeye.com/url?k=6e2af5a1-327ffcb2-
6e2ac49e-0cc47adb5650-387d438bf4672a83&u=https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
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    Comment: One commenter expressed concerns with including the 
Emergency department setting in the Safe Use of Opioids--Concurrent 
Prescribing CQM. Specifically, it was mentioned that in Emergency 
medicine, the goal is to provide short-term, life-saving care to 
patients, with the intention of those patients following-up with 
primary care. Given this unique environment, the commenter stated that 
there are instances where concurrent prescription of multiple opioids, 
or an opioid and benzodiazepine, would be clinically appropriate. 
Further, the commenter expressed a larger concern that providers may 
withhold clinically appropriate treatment based on misinterpretations 
of the measure.
    Response: Because this measure was proposed and is being finalized 
under the Hospital IQR Program, we believe it is appropriate to focus 
on inpatient stays. Specifically, there may be occasions in which 
patients admitted to the emergency department or for observation stays 
are not ultimately admitted as inpatients. We agree that those patients 
should be excluded from the measure and this was our intent in the 
proposed rule; however, the technical specifications referenced in the 
proposed rule were overbroad and not clearly consistent with the 
proposal. The Safe Use of Opioids--Concurrent Prescribing CQM was 
developed with broader specifications with flexibility in mind. 
Specifically, the measure, as initially developed, captured both 
encounters from the hospital outpatient and inpatient settings so that 
it could be implemented in either setting, with program implementation 
in either the Hospital Outpatient Quality Reporting (OQR) Program and/
or the Hospital IQR Program/Promoting Interoperability Program to be 
determined at a later date.
    We have made this minor refinement to the technical specifications 
to address confusion about which emergency department or observation 
stay encounters are included in the measure for implementation in the 
Promoting Interoperability Program and Hospital IQR Program, which are 
available here at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms. For a more detailed discussion of the Safe Use of Opioids--
Concurrent Prescribing CQM clarification to emergency department or 
observation stay encounters, we refer readers to section XIII.A.5.a. 
(1). of the preamble of this final rule.
    After consideration of the public comments, we are finalizing our 
proposal to add the Safe Use of Opioids--Concurrent Prescribing CQM to 
the Promoting Interoperability Program measure set, beginning with the 
reporting period in CY 2021. We are not finalizing the proposed 
addition of the Hospital Harm--Opioid-Related Adverse Events CQM.
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
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19561), we made a 
Request for Information regarding whether we should consider proposing 
to adopt the Hybrid Hospital-Wide Readmission (HWR) measure with claims 
and EHR data (also known as the Hybrid HWR measure) in future 
rulemaking for the Promoting Interoperability Program starting with the 
reporting period in CY 2023. While we are not summarizing and 
responding to the comments we received in this final rule, we thank the 
commenters for their responses and we will take them it account as we 
develop future policies for the Promoting Interoperability Program.
d. CQM Reporting Periods and Criteria for the Medicare and Medicaid 
Promoting Interoperability Programs in CY 2020, 2021, and 2022
(1) CQM Reporting Periods and Criteria in CY 2020 and 2021
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19561 through 
19562), for CY 2020 and 2021, we proposed 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 proposed 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 
proposed 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 proposed 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 (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 provided 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 stated that 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 
stated 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.
    Comment: Many commenters expressed overwhelming support for the 
proposals including reporting one self-selected calendar quarter of 
data for four self-selected CQMs; aligning with the requirements of the 
Hospital IQR Program; and submitting data during the 2 months following 
the close of the calendar year. We note that several commenters 
appreciated and supported

[[Page 42600]]

the consistency of the proposed CQM reporting and submission 
requirements. A commenter was appreciative of CMS extending the 
requirement of 4 self-selected CQMs for 1 calendar quarter through 
CY2021, as it has been challenging for EMR vendors and hospitals to 
respond in an efficient manner due to ongoing CMS maintenance and 
updates. Another commenter was grateful for CMS' sensitivity to 
provider burden, by focusing on measures and efforts that support CQMs. 
Commenters have expressed sincere gratitude that CMS has provided 
advanced notification and program consistency. Lastly, a commenter 
supported the continuation of these reporting requirements, as this 
will aid hospitals in the data extraction processes while providing 
flexibility and supporting the ultimate goal of creating a more 
efficient and seamless electronic collection and submission process for 
quality measures.
    Response: We thank all the commenters for their overwhelming 
support of our proposals. As we align with the Hospital IQR Program 
CQMs, we want to continue to offer eligible hospitals and CAHs 
reporting flexibility and decreased data collection burden.
    After consideration of public comments, we are finalizing all of 
the proposals for the CQM reporting periods, reporting criteria, and 
submission periods for CY 2020 and 2021 as proposed.
(2) CQM Reporting Periods and Criteria in CY 2022
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19562), for CY 
2022, we proposed 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: (1) Three self-selected CQMs from the set of 
available CQMs; and (2) 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 proposed 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 proposed 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 final 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.
    Comment: A few commenters have expressed support for the proposal 
that the submission period would be the 2 months following the close of 
the calendar year 2022, ending February 28, 2023.
    Response: Thank you to all commenters for the valuable input. In an 
effort to decrease data collection and hospital burden, and so that we 
continue to align with the Hospital IQR Program, we are pleased to have 
such support from the public.
    Comment: Many commenters, while fully supportive of the intent and 
introduction of the Safe Use of Opioids--Concurrent Prescribing CQM, 
have expressed concern with making this a required measure in CY 2022. 
Of the concerns, a few commenters have stated that as a new measure, 
adequate time is necessary to allow for vendors and eligible hospitals 
and CAHs to prepare and test its use, as well as make any necessary 
adjustments, and two years is not enough time for this to be done. One 
commenter had a concern that CMS needs to ensure that hospitals and 
CAHs are allowed an adequate amount of time in order to develop and 
execute validity testing. A couple commenters shared concern that 
additional time would be needed to develop the technology necessary to 
support reporting on such a measure, as implementation challenges often 
arise with new measures and the lag between data collection and 
reporting.
    Alongside these concerns, the overarching suggestion is to include 
the Safe Use of Opioids--Concurrent Prescribing CQM in the measure set, 
but not require it until CY 2023. This would allow for one additional 
year to ensure that the technology has been fully developed, and 
successful validation testing has been completed. Lastly, a commenter 
suggested that as an alternative to requiring all hospitals to report 
on the new CQM in CY 2022, CMS should instead consider incentivizing 
organizations to report the measure by offering bonus points.
    Response: We thank all commenters for sharing and expressing their 
concerns, and offering suggestions. We further note that the measure 
specifications for the measure can also be found on the eCQI Resource 
Center,\922\ which provides a centralized location for news, 
information, tools, and standards related to CQMs.\923\ We believe 
requiring the reporting of the Safe Use of Opioids--Concurrent 
Prescribing CQM beginning with the reporting period in CY 2022 will 
provide sufficient time to work through implementation, testing, and 
reporting challenges. We refer readers to section XIII.A.5.a.(1). of 
the preamble of this final rule for a discussion of how this measure 
was tested for feasibility, reliability, and validity and received NQF 
endorsement. We understand that many hospitals work with vendors to 
implement measure specifications in their EHRs, and we believe that the 
proposed timeline for required reporting of the Safe Use of Opioids--
Concurrent Prescribing CQM--the CY 2022 reporting period--will allow 
hospitals and vendors time to work through implementation, testing, and 
reporting challenges before reporting on the measure to CMS is 
required.
---------------------------------------------------------------------------

    \922\ Measure specifications for the Safe Use of Opioids--
Concurrent Prescribing eCQM are available at: https://ecqi.healthit.gov/ecqm/measures/cms506v1.
    \923\ https://ecqi.healthit.gov/content/about-ecqi.
---------------------------------------------------------------------------

    After consideration of public comments, we are finalizing all of 
the proposals for the CQM reporting periods, reporting criteria, and 
submission periods for CY 2022 as proposed.
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
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19562), we 
proposed 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.

[[Page 42601]]

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.
    Comment: Several commenters supported our proposal to require that 
EHR technology used for CQM reporting be certified to all CQMs. A 
number of those commenters expressed appreciation for this policy and 
shared that it helps preserve hospitals' ability to choose CQMs which 
reflect their patient populations and quality improvement goals.
    Response: We thank the commenters for their support of our proposal 
and believe that it gives eligible hospitals and CAHs flexibility to 
report on any of the CQMs available instead of being limited to those 
that their vendor chooses to have certified.
    After consideration of public comments, we are finalizing our 
proposal to continue requiring that EHRs be certified to all available 
CQMs adopted for the Medicare Promoting Interoperability Program for CY 
2020 and subsequent years.
(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 the 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.
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19562 through 
19563), for the reporting period in CY 2020, we proposed 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 proposed 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, we stated that 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/. For the CY 2020 electronic 
reporting of CQMs, we have published an updated version and requiring 
eligible hospitals and CAHs to use the 2019 CQM specifications update 
(published in May 2019 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 2015 Edition CEHRT for the Medicare 
and Medicaid Promoting Interoperability Programs, beginning with the 
EHR reporting period in CY 2019. We reiterated 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).
    Comment: A commenter appreciated the ability to report CQMs once 
and have the submission fulfill both the Hospital IQR requirement and 
the Promoting Interoperability Program requirements.
    Response: We thank the commenter for their support and believe that 
the alignment between the Hospital IQR requirement and the Promoting 
Interoperability Program alleviates burden for eligible hospitals and 
CAHs.
    Comment: A commenter shared support for the proposal that requires 
the use of the most recent version of the CQM electronic specification 
for each CQM to which the EHR is certified and appreciated that we were 
specifying in rulemaking.
    Response: We appreciate commenter support for using the most recent 
version of the CQM electronic specifications and believe that not 
requiring recertification of CEHRT every time that the specifications 
are updated with alleviate burden for eligible hospitals and CAHs.
    Comment: A commenter appreciated CMS' recognition and response to 
the challenges regarding feasibility of electronically submitted 
measures. They believe that maintaining the reduced reporting burden 
through CY 2021 would provide consistency and predictability while 
allowing hospitals additional time and bandwidth needed to address 
present challenges.
    Response: We thank the commenters for their support of our proposal 
and agree that establishing the requirements for through 2021 gives 
eligible hospitals and CAHs the ability to plan for the future.
    After consideration of the public comments we received, we are 
finalizing the following for CQM submission under the Medicare 
Promoting Interoperability Program for the reporting period in CY 2020:
     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.
    Additionally, we are finalizing the proposal to continue our policy 
for CY 2020 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.
(3) 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). In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19563), beginning with the CQM reporting period in CY 2023, we proposed 
to eliminate attestation as a method for reporting CQMs for the 
Medicare Promoting Interoperability Program and instead require all 
eligible hospitals and

[[Page 42602]]

CAHs to submit their CQM data electronically through the reporting 
methods available for the Hospital IQR Program. We stated that 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. We stated that 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 stated that we are allowing an adequate 
transition period for eligible hospitals and CAHs to migrate to 
electronic submission.
    Comment: A commenter supported the proposed modification to 
reporting methods for CQMs beginning with the reporting period in CY 
2023.
    Response: We thank the commenter for their supportive feedback and 
believe that by CY 2023 all eligible hospitals and CAHs should be able 
to submit their data electronically.
    Comment: A commenter agrees that while most hospitals and CAHs have 
the capacity for electronic reporting of CQMs, they believe CMS should 
retain a hardship exception process for unanticipated situations where 
they are unable to submit or report CQMs electronically.
    Response: For the Medicare Promoting Interoperability Program we do 
offer hardship exceptions for extreme and uncontrollable circumstances.
    After consideration of the public comments we received, we are 
finalizing our proposal 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 beginning with the CQM reporting period in CY 
2023.
7. Future Direction of the Promoting Interoperability Program
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19563 through 
19569), we made Requests for Information regarding several issues 
involving the Promoting Interoperability Program. While we are not 
summarizing and responding to the comments we received in this final 
rule, we thank the commenters for their responses and we will take them 
it account as we develop future policies for 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 
policies set forth in this final rule. MedPAC recommendations for the 
IPPS for FY 2020 are addressed in Appendix B to this final 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. 
We listed the data files available in the FY 2020 IPPS/LTCH PPS 
proposed rule (84 FR 19570 through 19571).
    Commenters interested in discussing any data files used in 
construction of this final rule should contact Michael Treitel at (410) 
786-4552.

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 the FY 2020 IPPS/LTCH PPS proposed rule, we solicited public 
comment on each of these issues for the following sections of this 
document that contain information collection requirements (ICRs).
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 the proposed rule and this final 
rule are not subject to the Paperwork Reduction Act, as stated in 
section 5506 of the Affordable Care Act, included at section 
1886(h)(4)(H)(vi)(V) of the 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. In this final rule, we describe the burden changes with 
regard to collection of information under OMB Control Number 0938-1022 
(expiration date February 28, 2022) for IPPS hospitals due to the 
policies in the proposed rule and this final rule.
    In section VIII.A.5.b. of the preamble of this final rule, we are 
adopting the Hybrid Hospital-Wide Readmission Measure with Claims and 
Electronic Health Record Data (Hybrid HWR measure) (NQF #2879) as we 
proposed, in a stepwise approach, beginning with 2 years of voluntary 
reporting which will 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 will run from July 1, 2023 
through June 30, 2024, impacting the FY 2026 payment determination and 
subsequent years. We are also adopting reporting and submission 
requirements for the Hybrid HWR measure. We expect these policies will 
affect our collection of information burden estimates. Details on these 
policies, as well as the

[[Page 42603]]

expected burden changes, are discussed further in this final rule.
    In section VIII.A. of the preamble of this final rule, we are: (1) 
Adopting the Safe Use of Opioids--Concurrent Prescribing eCQM beginning 
with the CY 2021 reporting period/FY 2023 payment determination with a 
clarification and update; (2) removing the claims-only version of the 
Hospital-Wide All-Cause Readmission measure beginning with the FY 2026 
payment determination; (3) extending 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) changing the eCQM reporting and submission 
requirements for the CY 2022 reporting period/FY 2024 payment 
determination, such that hospitals will be required to report one, 
self-selected calendar quarter of data for: (a) Three self-selected 
eCQMs, and (b) the finalized Safe Use of Opioids--Concurrent 
Prescribing eCQM, for a total of four eCQMs; and (5) continuing 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. We are not finalizing our proposal 
to adopt the Hospital Harm--Opioid-Related Adverse Events eCQM. As 
discussed further in this final rule, 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 final 
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.\924\ 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 in this final rule for the Hospital 
IQR Program.
---------------------------------------------------------------------------

    \924\ 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 Adoption of One eCQM 
Beginning With the CY 2021 Reporting Period/FY 2023 Payment 
Determination
    In section VIII.A.5.a. of the preamble of this final rule, we are 
adopting the Safe Use of Opioids--Concurrent Prescribing eCQM beginning 
with the CY 2021 reporting period/FY 2023 payment determination with a 
clarification and update. We are not finalizing our proposal to adopt 
the Hospital Harm--Opioid-Related Adverse Events eCQM.
    We do not believe that adding one new eCQM 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 final rule, we are 
extending, 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. The Safe Use of Opioids--
Concurrent Prescribing eCQM will 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.\925\ In other words, while this 
new measure will be added to the eCQM measure set, hospitals will not 
be required to report more than a total of four eCQMs as currently 
required. Therefore, we do not expect the adoption of this measure to 
impact our collection of information estimates. However, we refer 
readers to section I.K. of Appendix A of this final rule for a 
discussion of the potential costs associated with the implementation of 
a new eCQM that are not strictly related to information collection 
burden.
---------------------------------------------------------------------------

    \925\ We note that in section VIII.A.9.d.(4). of the preamble of 
this final rule we are finalizing that, beginning with the CY 2022 
reporting period, hospitals must report data on the Safe Use of 
Opioids--Concurrent Prescribing eCQM as one of the four required 
eCQMs.
---------------------------------------------------------------------------

c. Information Collection Burden Estimate for the Voluntary Reporting 
Periods and Subsequent Required Submission 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 final rule, as we 
proposed, we are establishing two additional voluntary reporting 
periods for the Hybrid Hospital-Wide Readmission Measure with Claims 
and Electronic Health Record Data (NQF #2879) (Hybrid HWR measure). The 
first voluntary reporting period will run from July 1, 2021 through 
June 30, 2022, and the second will run from July 1, 2022 through June 
30, 2023. We also are requiring 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 will 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 final rule, we are providing that hospitals will use the same 
submission process required for eCQM reporting; specifically, these 
data will 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 the 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 this 
policy 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

[[Page 42604]]

estimate as previously described, 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 policy is voluntary, but we 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 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 final rule, as we 
proposed, we are removing 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 will 
decrease our previously finalized burden estimates.
e. Information Collection Burden Estimates for Policies Related to eCQM 
Reporting and Submission Requirements
(1) Information Collection Burden Estimates for 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 final rule, 
we are extending the current requirements for 2 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 policies 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 will 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 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 final rule, for 
the CY 2022 reporting period/FY 2024 payment determination, as we 
proposed, we are finalizing changing the eCQM reporting and submission 
requirements, such that hospitals will be required to report one, self-
selected calendar quarter of data for: (1) Three self-selected eCQMs, 
and (2) the finalized Safe Use of Opioids--Concurrent Prescribing eCQM, 
for a total of four eCQMs. We note that the number of calendar quarters 
of data and total number of eCQMs required will remain the same. We 
believe there will be no change to the burden estimate because 
hospitals will 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 Requirement That EHRs Be 
Certified to All Available eCQMs
    In section VIII.A.10.d.(5)(B) of the preamble of this final rule, 
as we proposed, we are continuing to require 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 
information collection burden associated with this policy 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 final 
rule for a discussion of the potential costs associated with this 
policy 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 policy 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 rate as previously discussed), 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.

[[Page 42605]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.194

4. ICRs for PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) 
Program
a. Background
    As discussed in sections VIII.B. of the preamble of the proposed 
rule and this final 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. 
In this final rule, we discuss only changes in burden that will result 
from the policies that we are finalizing in this final 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.\926\
---------------------------------------------------------------------------

    \926\ 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 \927\ 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 in this final rule.
---------------------------------------------------------------------------

    \927\ Occupational Employment and Wages. Available at: https://www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.htm.
---------------------------------------------------------------------------

b. Estimated Burden of New PCHQR Program Policies Beginning With the FY 
2022 Program Year
(1) Removal of One Web-Based Structural Measure
    As discussed in section VIII.B.4. of the preamble of this final 
rule, we are finalizing the removal of 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 removal of this 
measure.
(2) New Quality Measure Beginning With the FY 2022 Program Year
    In section VIII.B.5. of the preamble of this final rule, we are 
finalizing the adoption of 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 adoption of 
this measure, as it does not require facilities to submit any 
additional data.
c. Summary of Burden Estimates Related to the PCHQR Program for the FY 
2022 Program Year
    In summary, for our finalized policies 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 measure, we estimate an overall burden 
decrease of approximately 3 hours across all 11 PCHs. Coupled with our 
estimated salary costs, we estimate that these changes will 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 consists of 15 measures 
for the FY 2022 program year. The burden associated

[[Page 42606]]

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 final rule, we discuss our 
proposed and finalized requirements for the Hospital VBP Program. 
Specifically, in this final rule, with respect to quality measures, we 
are calculating 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 
will 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.
    Comment: A few commenters noted a general belief that using the 
same administrative requirements that are used in the HAC Reduction 
Program will help reduce administrative burden associated with the 
programs.
    Response: We thank commenters for their feedback.
6. ICRs for the Long-Term Care Hospital Quality Reporting Program (LTCH 
QRP)
    In section VIII.C. of the preamble of this final rule, we are 
adopting 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 Transfer of Health 
Information quality measures will take 1.5 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 2,562 hours in burden for all 
LTCHs (0.025 hours x 102,468 discharges). Given 0.8 minutes of 
registered nurse time at $72.60 per hour and 0.7 minutes of licensed 
vocational nurse time at $45.24 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 $367.08 per LTCH 
annually, or $152,337 for all LTCHs annually. This increase in burden 
will be accounted for in the information collection under OMB control 
number 0938-1163 (Expiration Date: December 31, 2021).
    We estimate the SPADEs will take 11.3 minutes of clinical staff 
time to report data on admission and 10.4 minutes of clinical staff 
time to report data on discharge, for a total of 21.7 minutes. We note 
that this is a decrease from the proposed 10.5 minutes on discharge 
because of the final decision in section VIII.C.7.f.(2)(b) of the 
preamble of this final rule. 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 37,093 hours in burden for all 
LTCHs (0.362 hours x 102,468 discharges). Given 11.4 minutes of 
registered nurse time at $72.60 per hour and 10.2 minutes of licensed 
vocational nurse time at $45.24 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 $5,308.21 per LTCH 
annually, or $2,202,906 for all LTCHs annually. This increase in burden 
will be accounted for in the information collection under OMB control 
number 0938-1163 (Expiration Date: December 31, 2021).
    Overall, the changes added 11.3 minutes of clinical staff time to 
report data on admission and 11.9 minutes of clinical staff time to 
report data on discharge, for a total of 23.2 minutes. As a result, the 
cost associated with the changes to the LTCH QRP is estimated at 
$5,675.29 per LTCH annually or $2,355,243 for all LTCHs annually.
7. ICRs Relating to the Hospital-Acquired Condition (HAC) Reduction 
Program
    In section IV.I. of the preamble of this final rule, we discuss 
proposed and finalized requirements for the HAC Reduction Program. In 
this final rule, we are not removing any measures or adopting 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 (expiration November 30, 2021), 
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 
(expiration date January 31, 2021), 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.\928\ We note that, since then, more recent wage data 
have become available, and we are finalizing our proposal to update the 
wage rate used in these calculation. The most recent data from the 
Bureau of Labor Statistics reflects a median hourly wage of $18.83 
\929\ 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

[[Page 42607]]

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.
---------------------------------------------------------------------------

    \928\ 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.
    \929\ 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 \930\) as a result of our policy to validate NHSN HAI 
data under the HAC Reduction Program. A nonsubstantive information 
collection request will be submitted to OMB under control number 0938-
1352 to account for the updated costs.
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    \930\ Occupational Employment and Wages. Available at: https://www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.htm.
---------------------------------------------------------------------------

    We received a comment on our proposal to update the wage rate used 
in our calculation.
    Comment: A commenter supported updating the BLS wage rate used in 
the burden calculation.
    Response: We thank the commenter for the support.
8. ICRs Relating to the Hospital Readmissions Reduction Program
    In section IV.G. of the preamble of this final rule, we discuss 
proposed and finalized requirements for the Hospital Readmissions 
Reduction Program. In this final rule, we are not removing or adopting 
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.
    We did not receive any comments regarding the ICRs for the Hospital 
Readmissions Reduction Program.
9. ICRs for the Promoting Interoperability Programs
a. Background
    In section VIII.D. of the preamble of this final rule, we discuss 
proposed and finalized requirements for the Promoting Interoperability 
Programs. OMB has currently approved 623,562 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 
in this final rule focuses 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 Policies 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 final rule, as we 
proposed, we are changing 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 policy to affect our 
collection of information burden estimates for CY 2019 and CY 2020.
    This final rule also includes the following finalized 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) 
Elimination of 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) establishment of 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) requirement 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) revision of the Query of PDMP measure to make it an 
optional measure worth five bonus points in CY 2020, removal of the 
exclusions associated with this measure in CY 2020, and a clear 
statement of our intended policy that the measure is worth a full 5 
bonus points in CY 2019 and CY 2020; (5) change of the maximum points 
available for the e-Prescribing measure to 10 points beginning in CY 
2020, because we are finalizing the proposed changes to the Query of 
PDMP measure; (6) removal of the Verify Opioid Treatment Agreement 
measure beginning in CY 2020 and a clear statement of our intended 
policy that the measure is worth a full 5 bonus points in CY 2019; and 
(7) revision of 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 amending 
our regulations to incorporate several of these policies.
    Although we are removing 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 will not change burden since 
eligible hospitals and

[[Page 42608]]

CAHs will 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 policy 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 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 will 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 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 will 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 final rule, as we 
proposed, we are making a number of changes with respect to the 
reporting of CQM data, including the addition of one opioid-related 
measure beginning with the reporting period in CY 2021 and 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 policies are continuations of 
current policies and therefore we do not believe that there will be a 
change in burden for CY 2020.
c. Information Collection Burden Estimates for the Update to the Query 
of PDMP Measure
    In section VIII.D.3.b. of the preamble of this final rule, as we 
proposed, we are changing 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 will 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 will be a total of 40 minutes 
respectively for CY 2019 and CY 2020. By reducing the Query of PDMP 
measure reporting requirement from a numerator and denominator to a 
``yes/no'' response, manual calculation will not be required by 
eligible hospitals and CAHs. We estimate that the change in reporting 
requirement for the Query of PDMP measure will result in a reduction of 
collection of information burden of 2,200 hours (40 minutes * 3300 
respondents = 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.
[GRAPHIC] [TIFF OMITTED] TR16AU19.195

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 will 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 will take approximately one minute to complete. We estimated 
that the Security Risk Analysis measure will 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 collection of information burden estimates for this 
final rule.
    Given the finalized proposals in this final 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 burden hours 
(0.66 hours x 3,300 respondents) for the Medicare Promoting 
Interoperability Program.

[[Page 42609]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.196

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 updating this rate to $68.22 per hour for CY 
2020.\931\
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    \931\ https://www.bls.gov/oes/2017/may/oes231011.htm.
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    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 
$1,445,471.50 for CY 2019 and $1,466,320.68 for CY 2020. Due to a 
manual computation error in the proposed rule (84 FR 19578), the total 
costs for CY 2019 and CY 2020 are slightly different in this final 
rule. However, as seen in the below tables, and explained in greater 
detail in the next paragraph, the end result is a cost reduction for CY 
2019 and for CY 2020.
[GRAPHIC] [TIFF OMITTED] TR16AU19.197


[[Page 42610]]


[GRAPHIC] [TIFF OMITTED] TR16AU19.198

    This estimate takes into account the reduction of 2,200 total 
reporting burden hours per CY and the finalized hourly labor cost for 
CY 2019 and the updated hourly labor cost for CY 2020. This estimate 
represents a cost reduction of $147,950 ($1,593,421.50-$1,445,471.50) 
for CY 2019 and $127,100.82 ($1,593,421.50-$1,466,320.68) for 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 final 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 the proposed rule and this final 
rule discusses the alternative inpatient new technology add-on payment 
pathway for certain transformative new devices and for certain 
antimicrobial products. The burden associated with the finalized 
changes that will be needed for the new technology add-on payment 
application process will be discussed in a forthcoming revision of the 
information collection request (ICR) currently approved under OMB 
control number 0938-1347. The revised ICR is currently under 
development. However, upon completion of the revised ICR, we will 
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 Final Rule
    Below is a chart reflecting the total burden and associated costs 
for the provisions included in this final rule.
[GRAPHIC] [TIFF OMITTED] TR16AU19.199

XI. Provider Reimbursement Review Board Appeals

    As we discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 
19579), 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

[[Page 42611]]

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 the 
proposed rule, we requested public comments on PRRB appeals related to 
a hospital's Medicaid fraction in the DSH payment adjustment 
calculation. We refer readers to that section for a discussion of the 
public comments we received and our response.

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 amending 42 CFR chapter IV as set forth below:

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. Adding paragraphs (b)(1)(i) through (v);
0
b. Redesignating paragraph (c) as paragraph (e);
0
c. Adding a new paragraph (c) and paragraph (d); and
0
d. Revising newly redesignated paragraph (e).
    The additions and revision read as follows:


Sec.  412.87   Additional payment for new medical services and 
technologies: General provisions.

* * * * *
    (b) * * *
    (1) * * *
    (i) The totality of the circumstances is considered when making a 
determination that a new medical service or technology represents an 
advance that substantially improves, relative to services or 
technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries.
    (ii) A determination that a new medical service or technology 
represents an advance that substantially improves, relative to services 
or technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries means one of the following:
    (A) The new medical service or technology offers a treatment option 
for a patient population unresponsive to, or ineligible for, currently 
available treatments.
    (B) The new medical service or 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 and there must also be evidence that use of 
the new medical service or technology to make a diagnosis affects the 
management of the patient.
    (C) The use of the new medical service or technology significantly 
improves clinical outcomes relative to services or technologies 
previously available as demonstrated by one or more of the outcomes 
described in paragraphs (b)(1)(ii)(C(1) through (7) of this section.
    (1) A reduction in at least one clinically significant adverse 
event, including a reduction in mortality or a clinically significant 
complication.
    (2) A decreased rate of at least one subsequent diagnostic or 
therapeutic intervention.
    (3) A decreased number of future hospitalizations or physician 
visits.
    (4) A more rapid beneficial resolution of the disease process 
treatment including, but not limited to, a reduced length of stay or 
recovery time
    (5) An improvement in one or more activities of daily living
    (6) An improved quality of life
    (7) A demonstrated greater medication adherence or compliance.
    (D) The totality of the information otherwise demonstrates that the 
new medical service or technology substantially improves, relative to 
technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries.

[[Page 42612]]

    (iii) Evidence from published or unpublished information sources 
from within the United States or elsewhere may be sufficient to 
establish that a new medical service or technology represents an 
advance that substantially improves, relative to services or 
technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries. Information source may include the following:
    (A) Clinical trials;
    (B) Peer reviewed journal articles;
    (C) Study results;
    (D) Meta-analyses;
    (E) Consensus statements;
    (F) White papers;
    (G) Patient surveys;
    (H) Case studies;
    (I) Reports;
    (J) Systematic literature reviews;
    (K) Letters from major healthcare associations;
    (L) Editorials and letters to the editor; and,
    (M) Public comments.
    (N) Other appropriate information sources may be considered.
    (iv) The medical condition diagnosed or treated by the new medical 
service or technology may have a low prevalence among Medicare 
beneficiaries.
    (v) The new medical service or technology may represent an advance 
that substantially improves, relative to services or technologies 
previously available, the diagnosis or treatment of a subpopulation of 
patients with the medical condition diagnosed or treated by the new 
medical service or technology.
* * * * *
    (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) Eligibility criteria for alternative pathway for Qualified 
Infectious Disease Products. 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 products, if the following conditions are met:
    (1) A new medical product has received Food and Drug Administration 
(FDA) marketing authorization and is designated as a Qualified 
Infectious Disease Product by the FDA.
    (2) A medical product that meets the condition in paragraph (d)(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 product meets the conditions described in 
paragraph (b)(3) of this section.
    (e) Announcement of determinations and deadline for consideration 
of new medical service or technology applications. (1) CMS will 
consider whether a new medical service or technology meets the 
eligibility criteria specified in paragraph (b), (c), or (d) 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), (c), or (d) of this section.
    (2) 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. (A) 
Except as provided under paragraph (a)(2)(ii)(2) of this section, 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--
    (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.
    (B) For a medical product designated by the Food and Drug 
Administration (FDA) as a Qualified Infectious Disease Product, 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--
    (1) 75 percent of the costs of the new medical service or 
technology; or
    (2) 75 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, or the DRG payment plus 75 percent for a medical product 
designated by the FDA as a Qualified Infectious Disease Product, of the 
estimated costs of the new medical service or technology.

[[Page 42613]]


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.
    (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

[[Page 42614]]

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) this amount also 
does not include the difference between the hospital-specific payment 
rate and the Federal payment rate determined under subpart D of this 
part. With respect to a Medicare-dependent, small rural hospital that 
receives payments under Sec.  412.108(c), this amount 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 new paragraph (e)(4) and paragraph (e)(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.
* * * * *

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 equivalent to the hospital inpatient prospective 
payment system amount as determined under Sec.  412.529(d)(4)(i)(A) and 
(d)(4)(ii) and (iii); 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 calculated to be at least 50 percent, any 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 application of the payment adjustment delayed for that period if, 
for the period of at least 5 consecutive months of the 6 months 
immediately preceding the cost reporting period, the discharge payment 
percentage is calculated to be at least 50 percent.
    (ii) For any cost reporting period to which the payment adjustment 
under paragraph (d)(4) of this section would have applied but for a 
delay under paragraph (d)(6)(i) of this section, the payment adjustment 
under paragraph (d)(4) of this section will be applied to all 
discharges in the cost reporting period if the discharge payment 
percentage for the cost reporting period is not calculated to be 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

[[Page 42615]]

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 2.5 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.


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.
* * * * *

[[Page 42616]]


0
20. Section 495.24 is amended by revising paragraphs (e)(1), 
(e)(4)(iii), (e)(5)(ii)(B), (e)(5)(iii), (iv), and (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 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: July 26, 2019.
Seema Verma,
Administrator, Centers for Medicare and Medicaid Services.
    Dated: July 26, 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 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 figures for the standardized amounts, 
offsets, and budget neutrality factors. Therefore, in this final 
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 LTCH PPS standard Federal payment 
rate that will 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 
final 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.

[[Page 42617]]

    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 final 
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, as we proposed, we 
are making changes in the determination of the prospective payment 
rates for Medicare inpatient operating costs for acute care 
hospitals for FY 2020. In section III. of this Addendum, we discuss 
our 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 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 final rule 
are listed in section VI. of this Addendum and are available via the 
internet on the CMS website.

II. 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 used for determining the prospective payment rates for FY 2020.
    In summary, the 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 final rule for a complete discussion on the FY 2020 
inpatient hospital update. Below is a table with these four 
scenarios:

[[Page 42618]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.200

    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 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 to implement 
in a budget neutral manner the increase in the wage index values for 
hospitals with a wage index value below the 25th percentile wage 
index value across all hospitals (as described in section III.N. of 
the preamble of this final rule).
     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 transition 
(described in section III.N.2.d. of the preamble of this final rule) 
for hospitals negatively impacted due to changes to the wage index. 
We refer readers to section III.N. of the preamble of this final 
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, as we proposed, we 
applied the rural floor budget neutrality adjustment to hospital 
wage indexes. 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, as we proposed, we applied 
a uniform, national budget neutrality adjustment to the FY 2020 wage 
index for the rural floor.

A. Calculation of the 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

[[Page 42619]]

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, as we proposed, we are continuing 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 final rule, as we proposed, we are continuing 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, as we 
proposed, we applied 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 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 final 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, as we proposed, we calculated 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 final rule, as we 
proposed, we used the 2014-based IPPS operating and capital market 
baskets for FY 2020. As discussed in section IV.B. of the preamble 
of this final rule, in accordance with section 1886(b)(3)(B) of the 
Act, as amended by section 3401(a) of the Affordable Care Act, as we 
proposed, we reduced the FY 2020 applicable percentage increase 
(which for this final rule is based on IGI's second quarter 2019 
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 
0.4 percentage point, which for this final rule is also calculated 
based on IGI's second quarter 2019 forecast.
    Based on IGI's 2019 second quarter forecast of the hospital 
market basket increase (as discussed in Appendix B of this final 
rule), the forecast of the hospital market basket increase for FY 
2020 for this final rule is 3.0 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 final 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 will be 
applied to update the national standardized amount. The 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 Register for 
public comment. Our recommendation on the update factors is set 
forth in Appendix B of this final rule.

4. Methodology for Calculation of the Average Standardized Amount

    The methodology we used to calculate the 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 final 
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 adjusted 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 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.

[[Page 42620]]

     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), as we proposed, we are including 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, as we also proposed, we included 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, as we proposed, we 
are continuing to apply a proxy based on the prior fiscal year 
hospital readmissions payment adjustment (for FY 2020, this will be 
FY 2019 final adjustment factors) and a proxy based on the prior 
fiscal year hospital VBP payment adjustment (for FY 2020, this will 
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 applied 
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 proxy FY 2020 readmissions 
payment adjustment factors, for both the proposed rule and this 
final rule, as discussed in section IV.H. of the preamble of this 
final rule, we used 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 the proposed rule and 
this final rule, hospitals will not yet have 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 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 final rule.)
    In addition, for FY 2020, for the purpose of modeling aggregate 
payments when determining all budget neutrality factors, as we 
proposed, we used 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), 
as we proposed, we included 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 considered 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 final rule and below, we 
are continuing 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 included estimated 
uncompensated care payments in this comparison.
    Similarly, for MDHs, as discussed in section IV.F. of the 
preamble of this final 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, as we proposed, we continued to take 
into consideration uncompensated care payments in the computation of 
payments under the Federal rate and the hospital-specific rate for 
MDHs.
     As we proposed, we 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 applicable standardized 
amount in Tables 1A and 1B for discharges occurring in FY 2020.

[[Page 42621]]

     In our determination of all budget neutrality factors 
described in section II.A.4. of this Addendum, we used 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 final rule.

a. 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 final 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 
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 making 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 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 FY 2020 relative weights, and the FY 2019 
pre-reclassified wage data, and applied the FY 2020 hospital 
readmissions payment adjustments and estimated FY 2020 hospital VBP 
payment adjustments applied above. (We note that these FY 2020 
relative weights reflect our temporary measure for FY 2020, as 
discussed in section II.G. of the preamble of this final rule, to 
set the FY 2020 relative weight for the MS-DRG equal to the FY 2019 
relative weight, which was in turn set equal to the FY 2018 relative 
weight). Based on this comparison, we computed a budget neutrality 
adjustment factor equal to 0.997649 and applied this factor to the 
standardized amount. As discussed in section IV. of this Addendum, 
as we also proposed, we also applied the MS-DRG reclassification and 
recalibration budget neutrality factor of 0.997649 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, as we 
proposed, we are adjusting 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 final rule.
    To compute a 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 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 FY 2020 hospital readmissions payment adjustment and the 
estimated FY 2020 hospital VBP payment adjustment; and
     Aggregate payments using the FY 2020 relative weights 
and the FY 2020 pre-reclassified wage indexes, applied the 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 FY 2020 hospital readmissions payment 
adjustments and estimated FY 2020 hospital VBP payment adjustments 
applied above.
    In addition, we applied the MS-DRG reclassification and 
recalibration budget neutrality adjustment factor (derived in the 
first step) to the 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 budget neutrality 
adjustment factor of 1.001573 for changes to the wage index.

c. Reclassified Hospitals--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 budget neutrality adjustment factor, we applied the 
provisions of our policy proposal discussed in section III.N. of the 
preamble of this final 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 budget 
neutrality adjustment factor for FY 2020, we used FY 2018 discharge 
data to simulate payments and compared the following:
     Aggregate payments using the FY 2020 labor-related 
share percentages, the FY 2020 relative weights, and the 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 FY 
2020 hospital readmissions payment adjustments and the estimated FY 
2020 hospital VBP payment adjustments; and
     Aggregate payments using the FY 2020 labor-related 
share percentages, the FY 2020 relative weights, and the FY 2020 
wage data after such reclassifications, and applied the same 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 final rule, which is available via the internet on the CMS 
website. This table reflects reclassification crosswalks for FY 
2020, and applies the policies explained in section III. of the 
preamble of this final rule. Based on these simulations, we 
calculated a budget neutrality adjustment factor of 0.985425 to 
ensure that the effects of these provisions are budget neutral, 
consistent with the statute.

[[Page 42622]]

    The FY 2020 budget neutrality adjustment factor was applied to 
the standardized amount after removing the effects of the FY 2019 
budget neutrality adjustment factor. We note that the 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 final 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) are 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 final 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 final rule, we are calculating 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, as we proposed, we 
are calculating a national rural Puerto Rico wage index. Because 
there are no rural Puerto Rico hospitals with established wage data, 
our calculation of the 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 used 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 FY 2020 rural Puerto 
Rico wage index is calculated based on the average of the 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 national rural floor budget neutrality 
adjustment factor, we used FY 2018 discharge data to simulate 
payments and the post-reclassified national wage indexes and 
compared the following:
     National simulated payments without the national rural 
floor; and
     National simulated payments with the national rural 
floor.
    Based on this comparison, we determined a national rural floor 
budget neutrality adjustment factor of 0.997081. The national 
adjustment was applied to the national wage indexes to produce a 
national rural floor budget neutral wage index.

e. Rural Community Hospital Demonstration Program Adjustment

    In section IV.K. of the preamble of this final 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 final 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 Pub. L. 108-173. For FY 2020, 
based on the latest data for this final rule, the total amount that 
we are applying to make an adjustment to the standardized amounts to 
ensure the effects of the Rural Community Hospital Demonstration 
program are budget neutral is $25,742,822. Accordingly, using the 
most recent data available to account for the estimated costs of the 
demonstration program, for FY 2020, we computed a factor of 0.999771 
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 
final rule for complete details regarding the calculation of the 
amount we are applying to make an adjustment to the standardized 
amount.

f. Budget Neutrality Adjustment for Lowest Quartile Wage Index Hospital 
Policy

    As discussed in section III.N. of the preamble of this final 
rule, to address wage index disparities, we are establishing a 
policy 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 finalized policy, in order to 
offset the estimated increase in IPPS payments to hospitals with 
wage index values below the 25th percentile, we are adjusting the 
standardized amount. We refer readers to section III.N. of the 
preamble of this final rule for a complete discussion regarding this 
finalized policy.
    To calculate this budget neutrality adjustment factor for FY 
2020, we used FY 2018 discharge data to simulate payments and 
compared the following:
     Aggregate payments using the FY 2020 labor-related 
share percentages, the FY 2020 relative weights, and the FY 2020 
wage index for each hospital before adjusting the wage indexes under 
the finalized policy for the lowest quartile wage index hospitals 
but without the 5 percent cap, and applied the FY 2020 hospital 
readmissions payment adjustments and the estimated FY 2020 hospital 
VBP payment adjustments, and the operating outlier reconciliation 
adjusted outlier percentage discussed below; and
     Aggregate payments using the FY 2020 labor-related 
share percentages, the FY 2020 relative weights, and the FY 2020 
wage index for each hospital after adjusting the wage indexes under 
the finalized policy for the lowest quartile wage index hospitals 
but without the 5 percent cap, and applied the same FY 2020 hospital 
readmissions payment adjustments and the estimated FY 2020 hospital 
VBP payment adjustments applied above, and the operating outlier 
reconciliation adjusted outlier percentage discussed below. This FY 
2020 budget neutrality adjustment factor was applied to the 
standardized amount. Based on this comparison, we determined the 
lowest quartile wage index budget neutrality adjustment factor of 
0.997987.

g. Transition Budget Neutrality Adjustment Reflecting the FY 2020 Wage 
Index Changes

    In section III.N. of the preamble of this final rule, we state 
that we recognize that, absent further adjustments, the combined 
effect of the 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, as 
we proposed, we established 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 placing 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 establishing a policy that a hospital's final wage 
index for FY 2020 will not be less than 95 percent of its final wage 
index for FY 2019. For FY 2020, we are using 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 transition for hospitals negatively impacted (described in 
section III.N.2.d. of the preamble of this final rule) is 
implemented in a budget neutral manner. We refer readers to section 
III.N. of the preamble of this final rule for a complete discussion 
regarding this finalized policy.
    To calculate a transition budget neutrality adjustment factor 
for FY 2020, we used FY 2018 discharge data to simulate payments and 
compared the following:
     Aggregate payments without the 5-percent cap using the 
FY 2020 labor-related share percentages, the FY 2020 relative 
weights, the FY 2020 wage index for each hospital after adjusting 
the wage indexes under the finalized policy for the lowest quartile 
wage index hospitals with the associated budget neutrality 
adjustment to the standardized amount, and applied the FY 2020 
hospital readmissions payment adjustments and the estimated FY 2020 
hospital VBP payment adjustments, and the operating outlier 
reconciliation adjusted outlier percentage discussed below; and
     Aggregate payments with the 5-percent cap using the FY 
2020 labor-related share percentages, the FY 2020 relative weights, 
the FY 2020 wage index for each hospital after adjusting the wage 
indexes under the

[[Page 42623]]

finalized policy for the lowest quartile wage index hospitals with 
the associated budget neutrality adjustment to the standardized 
amount, and applied the FY 2020 hospital readmissions payment 
adjustments and the estimated FY 2020 hospital VBP payment 
adjustments, and the operating outlier reconciliation adjusted 
outlier percentage discussed below.
    This FY 2020 budget neutrality adjustment factor was applied to 
the standardized amount. Based on this comparison, we determined a 
transition budget neutrality adjustment factor of 0.998838. We note 
that Table 2 associated with this final rule (which is available via 
the internet on the CMS website) contains the wage index by provider 
before adjusting the wage indexes under the finalized policy for 
lowest quartile wage index hospitals and the 5-percent cap and the 
wage index by provider after the application of these policies.

h. 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, as we proposed, we are implementing the required +0.5 percent 
adjustment to the standardized amount. This is a permanent 
adjustment to the payment rates.

i. 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, as we proposed, we incorporated 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 payments may be found on the CMS 
website at: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/outlier.htm.

(1) 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 process is 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 2020 IPPS/LTCH PPS proposed rule, we noted that 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, the FY 
2020 proposed rule) as we continued 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

[[Page 42624]]

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 stated in the proposed rule that 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 stated that we 
believe this methodology would address concerns on the impact of 
outlier reconciliation on the modeling of the outlier threshold.
    We stated that 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 proposed 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 
proposed, and after consideration of public comments, are 
finalizing, to incorporate these dollars into the model.
    Currently, outlier reconciliation is among the last steps before 
the cost 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, in the proposed rule we proposed 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 we stated in the 
proposed rule were currently the most recent and complete set of 
outlier reconciliation data, which were finalized and/or approved by 
the MAC as of the time of development of the FY 2020 proposed rule. 
In the proposed rule we noted that approximately 90 percent of the 
FY 2014 cost reports were final settled, as compared to 
approximately 60 percent of the FY 2015 cost reports that were 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 stated that we believed 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 also stated that 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 stated that we believed 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 
proposed 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 the FY 2020 proposed rule, we used the 
December 2018 HCRIS extract to calculate the proposed percentage 
adjustment for outlier reconciliation. In the proposed rule we 
stated that for the FY 2020 final rule, we would use the 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 
stated that 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 the proposed rule and, therefore, 
would have outlier reconciliation estimates available for use in the 
FY 2020 final rule.

(a) Incorporating a Projection of Outlier Payment Reconciliations for 
the FY 2020 Outlier Threshold Calculation

    We proposed 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 SCHs that were paid under their 
hospital-specific rate (that is, if Worksheet E, Part A, Line 48 is 
greater than Line 47 in the applicable columns). In the proposed 
rule, we stated that we used the December 2018 HCRIS extract for the 
proposed rule and that we expected 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 
proposed 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 noted 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 adjusted 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.) We stated in

[[Page 42625]]

the proposed rule that 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 the FY 2020 proposed rule, the estimated percentage of FY 
2020 capital outlier payments otherwise determined using the shared 
outlier threshold was 5.39 percent (estimated capital outlier 
payments of $433,416,367 divided by (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. We stated that 
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 stated that 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 the 
Addendum to the proposed rule and this final rule, we proposed 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 invited public comment on 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.
    Comment: Commenters provided similar feedback regarding the 
proposed methodology for projecting the estimate of capital outlier 
reconciliation as they did with respect to the proposed methodology 
for projecting the estimate of operating outlier reconciliation, as 
previously summarized. Commenters requested the same clarifications 
as with respect to the operating outlier methodology, and noted the 
same concern regarding completeness of FY 2014 reports compared to 
other earlier reporting years (FY 2012 or FY 2013).
    Response: We refer readers to the response in the previous 
section regarding the methodology for projecting the estimate of 
operating outlier reconciliation and why we believe the FY 2014 cost 
reports are the best available data for use in calculating the 
estimated operating outlier reconciliation adjustments for FY 2020, 
as we believe these same reasons support the use of this FY 2014 
data for calculating the estimated capital outlier reconciliation 
adjustments for FY 2020. In addition, with respect to comments 
regarding the proposed methodology for projecting the estimate of 
capital outlier reconciliation (for example, when there are multiple 
columns relevant to IPPS payments), we refer readers to our 
discussion in the previous section in response to similar comments 
on the estimated operating outlier reconciliation adjustment 
methodology. We note we use the same general methodology to project 
the estimate of outlier reconciliation for both operating payments 
and capital payments (aside from the different cost report 
worksheets from which the data is collected). We also note, similar 
to the estimated operating outlier reconciliation adjustment 
methodology, the proposed rule capital outlier reconciliation 
adjustment methodology calculation inadvertently did not incorporate 
the multiple columns, however these multiple columns have been used 
in projecting the estimated outlier reconciliation for this final 
rule.
    Additionally, for projecting the estimate of capital outlier 
reconciliation, similar to our projection of the estimate of 
operating outlier reconciliation, we are using cost report data of 
17 hospitals from the March 2019 HCRIS supplemented for two 
hospitals for a total of 19 hospitals. As noted above, for this 
final rule, 22 cost reports were used for projecting the estimate of 
operating outlier reconciliation; however 19 cost reports were used 
for projecting the estimate of capital outlier reconciliation. This 
difference in the number of cost reports for the operating and 
capital outlier reconciliation projections may be due to new 
hospitals defined in the regulations at 42 CFR 412.300(b) that may 
receive capital cost-based payments (in lieu of Federal rate 
payments), and therefore would not receive capital outlier payments. 
As a result, capital outlier reconciliation is not applicable to 
such hospitals since there is no capital outlier payment.
    The following table shows the March 2019 HCRIS with the addition 
of the two hospitals' outlier reconciliation reports for this final 
rule:
[GRAPHIC] [TIFF OMITTED] TR16AU19.201

    After consideration of the comments received and for the reasons 
discussed in the proposed rule and this final rule, we are 
finalizing the methodology for projecting an estimate of capital 
outlier reconciliation. Therefore, for this final rule we used the 
same steps as described in the proposed rule and this final rule 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.
    Specifically, for this FY 2020 final rule, as stated above, we 
used the March HCRIS extract of FY 2014 cost reports supplemented by 
the data for two additional providers. The estimated percentage of 
FY 2020 capital outlier payments otherwise determined using the 
shared outlier threshold is 5.47 percent (estimated capital outlier 
payments of $441,745,478 divided by (estimated capital outlier 
payments of $441,745,478 plus the estimated total capital Federal 
payment of $8,077,508,094)). Based on the March 2019 HCRIS 
supplemented by the data for two additional providers, 19 hospitals 
had an outlier reconciliation amount recorded on Worksheet E, Part 
A, Line 93 for total capital outlier reconciliation dollars of 
negative $6,196,382 (Step 2). The total Federal capital payments 
based on the March 2019 HCRIS is $7,570,974,974 (Step 3). The ratio 
(Step 4) is a negative 0.081844 percent, which, when rounded to the 
second digit, is negative 0.08 percent (Step 4). Therefore, for FY 
2020, taking into account projected capital outlier reconciliation 
payments under our methodology would decrease the estimated 
percentage of FY 2020 aggregate capital outlier payments by 0.08 
percent.

[[Page 42626]]

(2) 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 FY 2020 outlier 
threshold, we simulated payments by applying 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 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 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 the FY 2020 IPPS/LTCH PPS 
proposed rule, we were continuing to consider using data that 
commenters can access earlier.
    For the FY 2020 IPPS/LTCH PPS proposed rule, after further 
consideration, we stated that 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 proposed 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 stated that 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. We stated that for example, under our current 
methodology, the most recent data available for purposes of the 
proposed rule was the December 2018 MedPAR release, with the final 
month of charge data being December 2018, and for this 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,

[[Page 42627]]

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 stated that 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 proposed to use the publicly available MedPAR 
files for the two most recent Federal fiscal year time periods to 
calculate the charge inflation factor beginning in FY 2020. 
Specifically, for the 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 the FY 2020 IPPS/LTCH PPS proposed rule) to compute 
the proposed charge inflation factor. In addition, we proposed 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 proposed 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 in the proposed rule we provided a table for 
comparison purposes and refer the reader to the FY 2020 IPPS/LTCH 
proposed rule to view the table (84 FR 19597.) We invited public 
comments on this proposed change to our methodology to use in the 
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, in the proposed rule, 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.
    Comment: Some commenters were concerned with what they stated 
was a lack of transparency with respect to the charge inflation 
component of the fixed-loss threshold calculation. One commenter 
stated that they were unable to match the figures in the table from 
the proposed rule with publicly available data sources and CMS did 
not disclose the source of the data. The commenter's estimate was 
5.38%, in comparison to the proposed rule's estimate of 5.45%. The 
commenter further 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 and charges 
per case used to measure charge inflation. Consequently, the 
commenter stated that the table 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.
    Commenters supported the decision to move to publically 
available data for the proposed rule, however they believed that the 
final rule should use more current data and that CMS should disclose 
all aspects of its edits to the most current data. Commenters also 
requested that CMS should commit to disclose the charge inflation 
data files used in the final rule, including edits and calculations, 
when it publishes the final rule.
    Response: We appreciate the commenter's input on the proposed 
methodology. As discussed in the FY 2020 proposed rule, under our 
proposed methodology, for this FY 2020 final rule, we proposed to 
use the MedPAR files from March 2019 for the FY 2018 charge data. 
These data are publically available, including for use by commenters 
that wish to reproduce charge inflation results. As discussed in the 
proposed rule, we provided the table of quarterly charges in the 
proposed rule for comparison with the methodology we used for FYs 
2014 through FY 2019, but for FY 2020, under our proposed 
methodology, we calculated the 1-year average annual rate-of-change 
in charges per case using the publicly available MedPAR data. The 
edits and calculation were described in the proposed rule (84 FR 
19595) and are also discussed in this final rule. Since the MedPAR 
files are publically available, we do not believe it is necessary to 
publish a separate PUF of the monthly charge data, which was done in 
the proposed rule and previous rules under our prior methodology for 
calculating charge inflation. In response to the commenter who 
believes more current data should be used in the final rule, we note 
that the FY 2018 claims used in this final rule are updated through 
March 2019, which we consider more current data than the proposed 
rule. In addition, as discussed in the proposed rule and in this 
final rule, since the MedPAR files are publically available, we 
believe this provides additional transparency.
    After consideration of the comments received and for the reasons 
discussed in the proposed rule and this final rule, we are 
finalizing as proposed the methodology to calculate charge inflation 
using the publically available FY 2017 and FY 2018 claims data. 
Below we provide the charge inflation information based on the 
finalized methodology.
    As we have done in the past, in the FY 2020 IPPS/LTCH PPS 
proposed rule, we proposed to establish the 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 the proposed rule. We proposed 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 proposed to 
continue to apply an adjustment factor to the CCRs to account for 
cost and charge inflation (as explained below). We also proposed 
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 proposed 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, in the proposed 
rule, 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 the 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

[[Page 42628]]

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 based on the proposed FY 2020 wage index 
that hospitals would be paid. This included 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 
incorporated 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. We stated that 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 
reflected the estimate of outlier reconciliation as calculated for 
the proposed rule).
    As described in sections IV.G. and IV.H. of the Addendum, 
respectively, of the preamble of this final 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 proposed to 
exclude the 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 proposed 
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 proposed to include estimated FY 2020 uncompensated 
care payments in the computation of the proposed outlier fixed-loss 
cost threshold. Specifically, we proposed 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 the Addendum to the proposed and final rules 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 proposed 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 reflected 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 noted 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 proposed 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.
    Comment: Commenters expressed concerns with the increase of the 
outlier threshold from $25,769 in FY 2019 to $ 26,994 in the FY 2020 
proposed rule. They asserted that the increase will reduce the 
number of Medicare inpatient cases that qualify for an outlier 
payment. The commenters recommended that CMS maintain the current 
threshold of $ 25,769. Another commenter recommended that CMS 
develop a reconciliation process model that indicates at its 
conclusion, should it be determined the outlier threshold was set 
too high resulting in fewer outlier payments, a funding mechanism to 
allow hospitals access to additional outlier payments.
    Response: As noted above, section 1886(d)(5)(A)(iv) of the Act 
states that outlier payments may not be not less than 5 percent nor 
more than 6 percent of the total payments projected or estimated to 
be made based on DRG prospective payment rates for discharges in 
that year. We believe that maintaining the FY 2019 outlier fixed-
loss cost threshold for FY 2020 would be inconsistent with the 
statute because we would be setting a threshold based on the prior 
fiscal year. Also, when we calculate the threshold, we use the 
updated data that is available at the time of the development of the 
proposed and final rule. As the outlier threshold is set based on a 
prospective estimate of future payments, we do not believe adjusting 
payments after the fact, whether because of reconciled amounts or 
otherwise, is appropriate.
    Comment: Some commenters requested that CMS consider whether it 
is appropriate to include extreme cases when calculating the 
threshold. One commenter explained that high charge cases have a 
significant impact on the threshold. The commenter observed that the 
amount of cases with over $1.5 million in covered charges has 
increased significantly from FY 2011 (926 cases) to FY 2018 (2,606 
cases). The commenter believed that the impact of these cases will 
cause the threshold to rise and recommended that CMS carefully 
consider what is causing the trend, whether the inclusion of these 
cases in the calculation of the threshold is appropriate, and 
whether a separate outlier mechanism should apply to these cases 
that more closely hews outlier payments to marginal costs.

[[Page 42629]]

    Response: As we explained when responding to a similar comment 
in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38526), the 
methodology used to calculate the outlier threshold includes all 
claims in order to account for all different types of cases, 
including high charge cases, to ensure that CMS meets the 5.1 
percent target. As the commenter pointed out, the volume of these 
cases continues to rise, making their impact on the threshold 
significant. We believe excluding these cases would artificially 
lower the threshold. We believe it is important to include all cases 
in the calculation of the threshold no matter how high or low the 
charges. Including these cases with high charges lends more accuracy 
to the threshold, as these cases have an impact on the threshold and 
continue to rise in volume. Therefore, we believe the inclusion of 
the high-cost outlier cases in the calculation of the outlier 
threshold is appropriate.
    Comment: One commenter stated that it could not confirm from the 
data CMS provided for the proposed outlier threshold whether CMS 
modeled and included the new technology payments that would apply in 
FY 2019 and in FY 2020, when it included claims for the MS-DRG that 
would include CAR-T payments. The commenter stated that if the 
claims used in the calculation predated FY 2019, and they do in fact 
relate to FY 2018, they would not have included such payments and 
that would otherwise significantly reduce or eliminate outlier 
payments for these cases. The commenter concluded that as a general 
matter, new technology add-on payments should be modeled and 
included in the outlier threshold calculation for claims that pre-
date the first fiscal year in which the payments are available. 
Another commenter requested that CMS examine the reasons for the 
continuing rise in the outlier threshold and whether there are any 
interventions it can take to ensure that outlier payments remain 
equitable and continue to protect hospitals from high cost cases 
where Medicare's IPPS payments are insufficient to adequately 
compensate the hospital.
    Response: We appreciate the input from the commenters. We did 
not include new technology add-on payments in the calculation of the 
FY 2020 outlier threshold. We welcome comments from the public how 
to incorporate new technology add-on payments into the outlier 
calculation. Because the commenters did not provide specifics how to 
incorporate these payments into the threshold, we will consider 
these comments for future rulemaking. Additionally, we believe the 
comment with regard to protecting hospitals from high cost cases is 
referring to new technology add on payments and cases such as CAR T-
cell therapy. We refer the reader to section II.F.2.c. of the 
preamble of this final rule for comments regarding CAR T-cell 
therapy. With regard to including new technology add-on payments in 
the calculation of the outlier threshold, as stated above, we will 
consider this for future rulemaking.
    Comment: A commenter noted that, for a given year, typically the 
final outlier threshold established by CMS in the final rule is 
lower than the threshold set forth in the proposed rule. The 
commenter emphasized that CMS should use the most recent data 
available when the Agency calculates the outlier threshold.
    Response: We responded to similar comments in the FY 2015 IPPS/
LTCH PPS final rule (79 FR 50378 through 50379) and refer readers to 
that rule for our response.
    After consideration of the public comments we received, we are 
using the same methodology we proposed to calculate the final 
outlier threshold. As discussed above, we are adopting for this 
final rule to calculate charge inflation using the publically 
available FY 2017 and FY 2018 claims data and to incorporate a 
projection of outlier payment reconciliations for the FY 2020 
outlier threshold calculation.
    For the FY 2020 final outlier threshold, we used the used the 
March 2018 MedPAR file of FY 2017 (October 1, 2016 through September 
30, 2017) charge data (released in conjunction with the FY 2019 
IPPS/LTCH PPS final rule) and the March 2019 MedPAR file of FY 2018 
(October 1, 2017 through September 30, 2018) charge data (released 
in conjunction with this FY 2020 IPPS/LTCH PPS final rule) to 
determine the charge inflation factor. To compute the 1-year average 
annual rate-of-change in charges per case, we compared the average 
covered charge per case of $58,422.22 ($565,500,080,304/9,679,538 
cases) from October 1, 2016 through September 31, 2017, to the 
average covered charge per case of $61,579.19 ($586,179,656,482/
9,519,120 cases) from October 1, 2017 through September 31, 2018. 
This rate-of-change was 5.4 percent (1.05404) or 11.1 percent 
(1.11100) over 2 years. The billed charges are obtained from the 
claims from the MedPAR file and inflated by the inflation factor 
specified above.
    As we have done in the past, we are establishing the FY 2020 
outlier threshold using hospital CCRs from the March 2019 update to 
the Provider-Specific File (PSF)-- the most recent available data at 
the time of the development of the final rule. We applied 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 replaced these CCRs with the statewide average 
CCR for the upcoming fiscal year. We also assigned 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 
did not apply the adjustment factors described below to hospitals 
assigned the statewide average CCR. For FY 2020, we also are 
continuing to apply an adjustment factor to the CCRs to account for 
cost and charge inflation (as explained below).
    For this final rule, as we have done since FY 2014, we are 
adjusting the CCRs from the March 2019 update of the PSF by 
comparing the percentage change in the national average case-
weighted operating CCR and capital CCR from the March 2018 update of 
the PSF to the national average case-weighted operating CCR and 
capital CCR from the March 2019 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 methodology above, for this final rule, we calculated 
a March 2018 operating national average case-weighted CCR of 
0.260798 and a March 2019 operating national average case-weighted 
CCR of 0.254578. We then calculated the percentage change between 
the two national operating case-weighted CCRs by subtracting the 
March 2018 operating national average case-weighted CCR from the 
March 2019 operating national average case-weighted CCR and then 
dividing the result by the March 2018 national operating average 
case-weighted CCR. This resulted in a national operating CCR 
adjustment factor of 0.976150.
    We used the same methodology above to adjust the capital CCRs. 
Specifically, for this final rule, we calculated a March 2018 
capital national average case-weighted CCR of 0.021618 and a March 
2019 capital national average case-weighted CCR of 0.020794. We then 
calculated the percentage change between the two national capital 
case weighted CCRs by subtracting the March 2018 capital national 
average case-weighted CCR from the March 2019 capital national 
average case-weighted CCR and then dividing the result by the March 
2018 capital national average case-weighted CCR. This resulted in a 
national capital CCR adjustment factor of 0.961884.
    As discussed previously, similar to the proposed rule, for FY 
2020, we applied the following policies (as discussed in more detail 
earlier):
     We used a wage index based on the FY 2020 wage index 
that hospitals would be paid. This included our final policy 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 final FY 2020 wage index policies 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 (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. 
(We note that, as discussed in section III.N. of the preamble of 
this final rule, we are not finalizing our proposal to decrease the 
wage index for hospitals with wage index values above the 75th 
percentile wage index value). As stated above, if we did not take 
the above into account, our estimate of total FY 2020

[[Page 42630]]

payments would be too low, and, as a result, our outlier threshold 
would be too high, such that estimated outlier payments would be 
less than our projected 5.14 percent of total payments (which 
reflects the estimate of outlier reconciliation calculated for this 
final rule).
     We excluded the hospital VBP payment adjustments and 
the hospital readmissions payment adjustments from the calculation 
of the outlier fixed-loss cost threshold.
     We used the estimated per-discharge uncompensated care 
payments to hospitals eligible for the uncompensated care payment 
for all cases in the calculation of the 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 finalizing 
to incorporate an estimate of FY 2020 outlier reconciliation in the 
methodology for determining the outlier threshold. Under this 
approach, we determined a threshold of $26,473 and calculated total 
operating Federal payments of $ 91,413,886,336 and total outlier 
payments of $4,943,282,951. We then divided total outlier payments 
by total operating Federal payments plus total outlier payments and 
determined that this threshold matched with the 5.14 percent target, 
which reflects our finalized methodology 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 
finalized methodology for incorporating an estimate of outlier 
reconciliation in the determination of the outlier threshold, the 
threshold would have been $26,662. We are finalizing 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 $26,473.

(2) Other 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 
$26,473 (which reflects our methodology to incorporate an estimate 
of outlier reconciliations) will result in outlier payments that 
will equal 5.1 percent of operating DRG payments and 5.42 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 reduced the FY 2020 standardized amount by 5.1 
percent to account for the projected proportion of payments paid as 
outliers.
    The outlier adjustment factors applied to the operating 
standardized amount and capital Federal rate based on the FY 2020 
outlier threshold are as follows:
[GRAPHIC] [TIFF OMITTED] TR16AU19.202

    We are applying the outlier adjustment factors to the 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 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 1.155 or capital CCRs greater than 0.144, 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 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 are effective for 
discharges occurring on or after October 1, 2019 and 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 statewide average capital 
CCRs. As previously stated, the CCRs in Tables 8A and 8B will 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 
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 4.98 
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

[[Page 42631]]

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 final rule. We will provide an 
estimate of actual FY 2019 outlier payments in the FY 2021 IPPS/LTCH 
PPS proposed rule.
    Comment: A commenter noted that, in the proposed rule, CMS 
stated that actual outlier payments for FY 2018 were approximately 
4.94 percent of total MS-DRG payments. The commenter performed its 
own analysis and concluded that outlier payments for FY 2018 are 
approximately 4.89 percent of total MS-DRG payments. The commenter 
was concerned that CMS' estimate was overstated.
    Response: We reviewed our data to ensure the estimate provided 
is accurate. Therefore, we believe we have provided a reliable 
estimate of the outlier percentage for FY 2018. In addition, the 
commenter did not provide specifics as to why CMS's estimate 
differed from the commenter's estimate. We welcome additional 
suggestions from the public, including the commenter, to improve the 
accuracy of our estimate of actual outlier payments.

5. 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 applying to all hospitals, except hospitals located in Puerto 
Rico, for FY 2020. The 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 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 
applying 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 standardized amounts 
reflecting the applicable percentage increases for FY 2020.
    The 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 Pub. L. 108-173, provides that the labor-
related share for hospitals located in Puerto Rico be 62 percent, 
unless the 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 FY 2020 national standardized 
amounts. The second through fifth columns display the changes from 
the FY 2019 standardized amounts for each applicable 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 budget neutrality factor for the finalized policy for lowest 
quartile wage index hospitals and transition, described above.
BILLING CODE 4120-01-P

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[GRAPHIC] [TIFF OMITTED] TR16AU19.204


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[GRAPHIC] [TIFF OMITTED] TR16AU19.205

BILLING CODE 4120-01-C

B. 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 labor-related and nonlabor-related shares that we used 
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 prospective 
payment rates as described in this Addendum.

1. 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 final rule, as we proposed, we are applying 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, as we proposed, we are 
applying 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 final rule, 
we discuss the data and methodology for the FY 2020 wage index.

2. 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, as we proposed, we are continuing 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

[[Page 42635]]

hospitals located in Alaska and Hawaii. Below is a table listing the 
COLA factors for FY 2020.
[GRAPHIC] [TIFF OMITTED] TR16AU19.206

    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 Prospective Payment Rates

1. 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 final 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.

2. 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 (l + 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

[[Page 42636]]

uncompensated care payment to the 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 previously, 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 2020

    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 
applicable percentage increases to the hospital-specific rates 
applicable to SCHs and MDHs are the following:
[GRAPHIC] [TIFF OMITTED] TR16AU19.207

    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 final 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 hospital-specific rate for an SCH or an MDH is 
adjusted by the MS-DRG reclassification and recalibration budget 
neutrality factor of 0.997649, 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 final rule, for FY 
2020, we are not making a documentation and coding adjustment to the 
hospital-specific rate. We refer readers to section II.D. of the 
preamble of this final rule for a complete discussion regarding our 
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. 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 used 
to determine the capital Federal rate for FY 2020, which are 
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),

[[Page 42637]]

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 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 Federal Hospital Inpatient Capital-Related 
Prospective Payment Rate Update for FY 2020

    In the discussion that follows, we explain the factors that we 
used to determine the capital Federal rate for FY 2020. In 
particular, we explain why the FY 2020 capital Federal rate 
increased approximately 0.70 percent, compared to the FY 2019 
capital Federal rate. As discussed in the impact analysis in 
Appendix A to this FY 2020 IPPS/LTCH PPS final rule, we estimate 
that capital payments per discharge will increase approximately 1.4 
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 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 0.0 percentage point adjustment for intensity, a 
0.0 percentage point adjustment for case-mix, a 0.0 percentage point 
adjustment for the DRG reclassification and recalibration, and a 
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 policy adjustments that we applied 
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 the following 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'').
     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 project a 0.5 percent total increase in the 
case-mix index. We estimate that the real case-mix increase will 
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, as 
we proposed, the 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 will 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, as we proposed, we are making 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, as we proposed, 
we are not making 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 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 final rule, as we proposed, we are continuing 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 used 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

[[Page 42638]]

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, as we 
proposed, we made 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 1.5 percent capital update factor under the capital 
update framework for FY 2020, as shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR16AU19.208

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, as we 
proposed, we are incorporating the estimated outlier reconciliation 
payment amounts into the outlier threshold model. (For more details 
on our incorporation of the 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. In FY 
2020, 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 5.47 percent for inpatient 
capital-related payments based on the capital Federal rate. However, 
as we proposed, using the methodology outlined in section II.A.4.h. 
of this Addendum, we estimate that taking into account projected 
capital outlier reconciliation payments will decrease FY 2020 
aggregate estimated capital outlier payments by 0.08 percent. 
Therefore, accounting for estimated capital outlier reconciliation, 
estimated outlier payments for capital-related PPS payments equal 
5.39 percent (5.47 percent -0.08 percent) of inpatient capital-
related payments based on the capital Federal rate in FY 2020. 
Accordingly, we applied an outlier adjustment factor of 0.9461 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 will 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 FY 2020 outlier adjustment 
of 0.9461 is a -0.35 percent change from the FY 2019 outlier 
adjustment of 0.9494. Therefore, the net change in the outlier 
adjustment to the capital Federal rate for FY 2020 is 0.9965 
(0.9461/0.9494; calculation performed on unrounded numbers) so that 
the outlier adjustment will decrease the FY 2020 capital Federal 
rate by approximately -0.35 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 final rule, we discuss 
our finalized policies to address wage index disparities between 
high and low wage index value hospitals. Specifically, we are: (1) 
Increasing 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 will 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) calculating 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) and removing 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 (3) placing 
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 
finalized policies 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 changes will affect the GAFs, as we 
proposed, we augmented our historical methodology for computing the 
budget neutrality factor for 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 changes to the wage index, which directly 
affect the GAF, as we proposed, we computed a budget neutrality 
factor for changes in the GAFs in two steps. Under our 2-step 
methodology, as we

[[Page 42639]]

proposed, we first calculate a factor to ensure budget neutrality 
for changes to the FY 2020 GAFs due to the update to the wage data, 
wage index reclassifications and redesignations, including our 
removal of 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 
calculation of 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, as we proposed, we calculate a 
factor to ensure budget neutrality for the changes to the FY 2020 
GAFs due to our increase in the wage index for hospitals with a wage 
index value below the 25th percentile wage index and placement of 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 two policies as the lowest quartile hospital wage index 
adjustment and the 5-percent cap on wage index decreases. We discuss 
our 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 the lowest quartile hospital wage index adjustment, and 
the 5-percent cap on wage index decreases. To achieve budget 
neutrality for these changes in the GAFs, we calculated an 
incremental GAF budget neutrality adjustment factor of 1.0005 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 lowest quartile hospital wage index 
adjustment and the 5-percent cap on wage index decreases. For this 
calculation, estimated aggregate capital Federal rate payments were 
calculated using the FY 2020 MS-DRG classifications and relative 
weights, and the FY 2020 GAFs (both with and without incorporating 
the effects on the GAF of the lowest quartile hospital wage index 
adjustment and the 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 lowest quartile hospital wage index adjustment and 
the 5-percent cap on wage index decreases on the FY 2020 GAFs, we 
calculated an incremental GAF budget neutrality adjustment factor of 
0.9964. Therefore, to achieve budget neutrality for the changes in 
the GAFs, based on the calculations described above, we applied an 
incremental budget neutrality adjustment factor of 0.9968 (1.0005 x 
0.9964; calculation performed on unrounded numbers) 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 FY 2020 GAFs to estimated aggregate capital Federal 
rate payments based on the cumulative effects of the FY 2020 MS-DRG 
classifications and relative weights and the FY 2020 GAFs without 
the effects of the lowest quartile hospital wage index adjustment 
and the 5-percent cap on wage index decreases. The incremental 
adjustment factor for DRG classifications and changes in relative 
weights is 0.9987. The incremental adjustment factor for MS-DRG 
classifications and changes in relative weights (0.9987) and for 
changes in the GAFs through FY 2020 (0.9968) is 0.9956 (0.9987 x 
0.9968). 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 lowest 
quartile hospital wage index adjustment and the 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 lowest quartile hospital wage 
index adjustment and the 5-percent cap on wage index decreases 
described above have on the other payment parameters, such as the 
payments for DSH or IME.
    The incremental GAF/DRG adjustment factor of 0.9956 (the product 
of the incremental GAF budget neutrality adjustment factor of 0.9968 
and the incremental DRG budget neutrality adjustment factor of 
0.9987) accounts for the MS-DRG reclassifications and recalibration 
and for changes in the GAFs. As noted previously, 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 lowest quartile hospital wage index adjustment and 
the 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. 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 establishing an 
update of 1.5 percent in determining the FY 2020 capital Federal 
rate for all hospitals. As a result of the update and the budget 
neutrality factors discussed earlier, we are establishing a national 
capital Federal rate of $462.61 for FY 2020, which results in a net 
change of 0.70 percent. The national capital Federal rate for FY 
2020 was calculated as follows:
     The FY 2020 update factor is 1.015; that is, the update 
is 1.5 percent.
     The 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 
0.9956.
     The FY 2020 outlier adjustment factor is 0.9461.
    We are providing the following chart that shows how each of the 
factors and adjustments for FY 2020 affects the computation of the 
FY 2020 national capital Federal rate in comparison to the FY 2019 
national capital Federal rate. The 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 GAF/DRG budget 
neutrality adjustment factor has the effect of decreasing the 
capital Federal rate by 0.44 percent. The FY 2020 outlier adjustment 
factor has the effect of decreasing the capital Federal rate by 0.35 
percent compared to the FY 2019 capital Federal rate. The combined 
effect of all the changes will increase the national capital Federal 
rate by approximately 0.70 percent, compared to the FY 2019 national 
capital Federal rate.

[[Page 42640]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.209

B. Calculation of the 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 threshold established for each fiscal year. 
Section 412.312(c) provides for a shared threshold to identify 
outlier cases for both inpatient operating and inpatient capital-
related payments. The outlier threshold 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 fixed-loss amount 
of $26,473.
    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 
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 final rule, we used 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 second quarter 2019 forecast, for 
this FY 2020 IPPS/LTCH/PPS final rule, we forecast the 2014-based 
CIPI to increase 1.5 percent in FY 2020. This reflects a projected 
1.8 percent increase in vintage-weighted depreciation prices 
(building and fixed equipment, and movable equipment), and a 
projected 3.3 percent increase in other capital expense prices in FY 
2020, partially offset by a projected 1.1 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. 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. In the FY 
2020 IPPS/LTCH PPS proposed rule (84 FR 19609), based on IGI's 2018 
fourth quarter forecast, we estimated that the 2014-based IPPS 
operating market basket update for FY 2020 was 3.2 percent (that is, 
the estimate of the market basket rate-of-increase). However, we 
proposed that if more recent data became available for the final 
rule, we would use them to calculate the IPPS operating market 
basket update for FY 2020. For this final rule, based on IGI's 2019 
second quarter forecast, (which is the most recent available data), 
we estimate that

[[Page 42641]]

the 2014-based IPPS operating market basket update for FY 2020 is 
3.0 percent (that is, the estimate of the market basket rate-of-
increase). 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 
will be applied to the FY 2019 target amounts, in order to determine 
the FY 2020 target amounts is 3.0 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 final rule 
and section V. of the Addendum to this final rule for the 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. Changes to the Payment Rates for the LTCH PPS for FY 2020

A. LTCH PPS Standard Federal Payment Rate for FY 2020

1. Overview

    In section VII. of the preamble of this final rule, we discuss 
our 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) of the Act 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 final 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 final 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 FY 2020 LTCH PPS Standard Federal Payment Rate

    Consistent with our historical practice, for FY 2020, as we 
proposed, we are applying the annual update to the LTCH PPS standard 
Federal payment rate from the previous year. Furthermore, in 
determining the LTCH PPS standard Federal payment rate for FY 2020, 
we also are making certain regulatory adjustments, consistent with 
past practices. Specifically, in determining the FY 2020 LTCH PPS 
standard Federal payment rate, as we proposed, we are applying a 
budget neutrality adjustment factor for the changes related to the 
area wage level adjustment (that is, changes 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 final rule).
    In this FY 2020 IPPS/LTCH PPS final rule, we are establishing an 
annual update to the LTCH PPS standard Federal payment rate of 2.5 
percent. Accordingly, as reflected in Sec.  412.523(c)(3)(xvi), we 
are applying a factor of 1.025 to the FY 2019 LTCH PPS standard 
Federal payment rate of $42,558.68 to determine the FY 2020 LTCH PPS 
standard Federal payment rate. Also, as reflected in Sec.  
412.523(c)(3)(xvi), applied in conjunction with the provisions of 
Sec.  412.523(c)(4), we are establishing an annual update to the 
LTCH PPS standard Federal payment rate of 0.5 percent (that is, an 
update factor of 1.005) 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 applying a temporary budget 
neutrality adjustment factor of 0.990737 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 0.990878 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 0.999858 as discussed in VII.D. of the 
preamble of this final rule). Consistent with Sec.  412.523(d)(4), 
we also are applying an area wage level budget neutrality factor to 
the FY 2020 LTCH PPS standard Federal payment rate of 1.0020203, 
based on the best available data at this time, to ensure that any 
changes to the area wage level adjustment (that is, the 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 payment rate payments. Accordingly, we are 
establishing an LTCH PPS standard Federal payment rate of $42,677.63 
(calculated as $41,558.68 x 0.999858 x 1.025 x 1.0020203) 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 establishing an LTCH PPS standard Federal payment 
rate of $41,844.89 (calculated as $41,558.68 x 0.999858 x 1.005 x 
1.0020203) (calculations performed on rounded numbers) for FY 2020.
    Comment: Some commenters objected to our application of the 
budget neutrality adjustment stemming from elimination of the 25-
percent threshold policy on the grounds that doing so penalizes 
LTCHs that have historically maintained compliance with this policy.
    Response: We addressed similar comments when we finalized the FY 
2020 budget neutrality adjustment stemming from elimination of the 
25-percent threshold policy in the FY 2019 IPPS/LTCH Final Rule (83 
FR 41532 through 41537). As a result of that rulemaking, this budget 
neutrality adjustment is required by regulations at Sec.  
412.523(d)(6).
    After review of public comments on our proposed development of 
the FY 2020 LTCH PPS standard Federal payment rate, we are 
finalizing our proposals as previously described, without 
modification.

B. 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. 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

[[Page 42642]]

(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, as we proposed, we 
are continuing 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 FY 2020 LTCH PPS wage index values in Tables 12A and 12B listed 
in section VI. of the Addendum to this final rule (which are 
available via the internet on the CMS website) reflect the CBSA-
based labor market area delineations as previously described. We 
note that, as discussed in section III.A.2. of the preamble of this 
final rule, these CBSA-based delineations also are being used under 
the IPPS.
    We did not receive any public comments in response to our 
proposals. Therefore, we are finalizing our proposals, without 
modification.

3. 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 final rule, as we proposed, we are establishing 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, in the proposed rule, we proposed 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 proposed to establish a labor-related 
share under the LTCH PPS for FY 2020 of 66.0 percent. (We noted that 
a proposed labor-related share of 66.0 percent was 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 remained at 66.0 percent when 
aggregating these components and rounding to one decimal.) This 
proposed labor-related share was determined using the same 
methodology as employed in calculating all previous LTCH PPS labor-
related shares. Consistent with our historical practice, we also 
proposed 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. We did not receive any public 
comments in response to our proposals. Therefore, we are finalizing 
our proposals, without modification.
    In this final rule, we are establishing 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 second quarter 
2019 forecast of the 2013-based LTCH market basket, consistent with 
our proposal to use more recent data, if appropriate, we are 
establishing a labor-related share under the LTCH PPS for FY 2020 of 
66.3 percent.
    The labor-related share for FY 2020 is the sum of the FY 2020 
relative importance of each labor-related cost category, and 
reflects 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 62.2 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, as we proposed, we are taking 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 62.2 percent for the operating cost amount to determine the 
total labor-related share for FY 2020. Therefore, as we proposed, we 
are establishing that the labor-related share under the LTCH PPS for 
FY 2020 is 66.3 percent.

4. 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),

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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 the 
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 proposed 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 using to compute the FY 2020 acute care hospital inpatient 
wage index, as discussed in section III. of the preamble of this 
final rule. We proposed to compute the 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 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 proposed 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 proposed 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.
    While our existing methodology remains unchanged, we identified 
an error in the proposed rule wage index values after the FY 2020 
IPPS/LTCH PPS proposed rule was published. A programming error 
caused the data for all providers in a single county to be included 
twice, which affected the national average hourly rate, and 
therefore affected all wage index values. In this final rule, we 
have changed the programming logic so this error cannot occur again. 
In addition, in this final rule, we corrected the classification of 
one county in North Carolina to rural status, as this county was 
erroneously identified as being in an urban CBSA. Finally, we 
standardized our procedures for rounding, to ensure consistency.
    Comment: A commenter objected to the underlying IPPS average 
hourly wage data, as released in the public use file, used to 
determine the FY 2020 LTCH PPS proposed wage index values, calling 
the exclusion of certain IPPS hospitals' wage index data, as 
discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19375 
through 19376), from the calculation untenable and asserting that 
the exclusion must be reversed. This commenter is referring to the 
exclusion of seven hospitals' wage data discussed in section III.C. 
of the preamble of this final rule.
    Response: Consistent with historical our practice (see, for 
example, the RY 2008 LTCH PPS final rule (72 FR 26891)), the 
proposed FY 2020 LTCH PPS wage index values were calculated using 
the same data we use to compute the FY 2020 acute care hospital 
inpatient wage index. While the commenter did not clarify how the 
exclusion of those seven hospitals' wage data made the LTCH PPS wage 
index calculation ``untenable'', or why we should deviate from our 
historical methodology of using IPPS hospital data to compute the FY 
2020 LTCH PPS wage index values, we note as discussed in more detail 
in section III.C. of this rule, the IPPS hospital wage data used to 
determine both the FY 2020 IPPS wage index and, by extension, the FY 
2020 LTCH PPS wage index includes data from those seven IPPS 
hospitals originally excluded in the proposed FY 2020 wage index 
values, therefore rendering the commenter's objections moot. For 
more information on the IPPS hospital wage data, including the data 
of those seven IPPS hospitals, we refer readers to III.C. of this 
rule).
    After consideration of public comments (and correction of the 
inadvertent programming errors discussed above), we are finalizing 
our proposals related to the FY 2020 LTCH PPS wage index values.
    Based on the FY 2016 IPPS wage data that we used to determine 
the FY 2020 LTCH PPS standard Federal payment rate area wage index 
values in this final rule, there are no IPPS wage data for the urban 
area of Hinesville, GA (CBSA 25980). Consistent with the methodology 
as previously discussed, we calculated the 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 final rule and 
available via the internet on the CMS website. (We note that 
although we had no IPPS wage data for the urban area of Carson City, 
NV (CBSA 16810) in the proposed rule, based on the updated data used 
for this final rule, there is now IPPS wage data for the urban area 
of Carson City, NV (CBSA 16810) for this final rule.)
    Based on the FY 2016 IPPS wage data that we used to determine 
the FY 2020 LTCH PPS standard Federal payment rate area wage index 
values in this final rule, there are no rural areas without IPPS 
hospital wage data. Therefore, it is not necessary to use our 
established methodology to calculate a LTCH PPS standard Federal 
payment rate wage index value for 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 FY 2020 LTCH PPS standard Federal payment 
rate wage index values that will 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 final 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 the proposed 
rule, we solicited 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. We appreciate the responses from 
commenters and shall consider their suggestions in future 
rulemaking.

5. 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

[[Page 42644]]

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 the 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 proposed 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 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). We did not 
receive any public comments in response to our proposals. Therefore, 
we are finalizing our proposals, without modification.
    Specifically, as we proposed, we determined 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 FY 2020 wage index values 
(as shown in Tables 12A and 12B listed in the Addendum to this final 
rule and available via the internet on the CMS website) and the FY 
2020 labor-related share of 66.3 percent (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 FY 2020 area wage level adjustments (calculated in Step 2) 
to determine the area wage level adjustment budget neutrality factor 
for FY 2020 LTCH PPS standard Federal payment rate payments.
    Step 4--We then applied the FY 2020 area wage level adjustment 
budget neutrality factor from Step 3 to determine the FY 2020 LTCH 
PPS standard Federal payment rate after the application of the 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 FY 2020 LTCH PPS standard Federal payment rate area 
wage level adjustment budget neutrality factor as previously 
described. Moreover, we note that the estimated LTCH PPS standard 
Federal payment rate used in the calculations in Steps 1 through 4, 
as previously discussed, 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 final rule.
    For this final rule, using the steps in the methodology 
previously described, we determined a FY 2020 LTCH PPS standard 
Federal payment rate area wage level adjustment budget neutrality 
factor of 1.0020203. Accordingly, in section V.A. of the Addendum to 
this final rule, to determine the FY 2020 LTCH PPS standard Federal 
payment rate, as we proposed, we are applying an area wage level 
adjustment budget neutrality factor of 1.0020203, in accordance with 
Sec.  412.523(d)(4).

C. 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 as previously 
described 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 the 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 proposed 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).)
    We did not receive any public comments on our proposal. 
Therefore, we are adopting our proposal, without modification. 
Consistent with our historical practice, we are establishing that 
the COLA factors shown in the following table will be used to adjust 
the nonlabor-related portion of the LTCH PPS standard Federal 
payment rate for LTCHs located in Alaska and Hawaii under Sec.  
412.525(b).

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D. 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 Pub. L. 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, as we proposed, we used 
the most recent data available to determine the LTCH total CCR 
ceiling for FY 2020 in this final rule. Specifically, in this final 
rule, using our established methodology for determining the LTCH 
total CCR ceiling based on IPPS total CCR data from the March 2019 
update of the Provider Specific File (PSF), which is the most recent 
data available, we are establishing an LTCH total CCR ceiling of 
1.253 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).)
    We did not receive any public comments on our proposals. 
Therefore, we are finalizing our proposals as described above, 
without modification.

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

[[Page 42646]]

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 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 final rule, using our established 
methodology for determining the LTCH statewide average CCRs, based 
on the most recent complete IPPS ``total CCR'' data from the March 
2019 update of the PSF, as we proposed, we are establishing 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 final rule (and available via the internet on the 
CMS website). Consistent with our historical practice, as we also 
proposed, we used more recent data to determine the LTCH PPS 
statewide average total CCRs for FY 2020 in this 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 March 2019. Therefore, consistent with our 
existing methodology, as we proposed, we used 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, as we proposed, we are 
continuing 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)).
    We did not receive any public comments on our proposals. 
Therefore, we are finalizing our proposals as described above, 
without modification.

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. 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. 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19615 through 
19616), we proposed 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 the proposed rule).
    Specifically, based on the most recent complete LTCH data 
available at that 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 determined 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 
be equal to 7.975 percent of estimated FY 2020 payments for such 
cases. Under this proposal, we proposed to 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).
    Consistent with our historical practice of using the best data 
available, as we proposed, when determining the fixed-loss amount 
for LTCH PPS standard Federal payment rate cases for FY 2020 in this 
final rule, we used the most recent available LTCH claims data and 
CCR data. In this FY 2020 IPPS/LTCH PPS final rule, we are 
continuing to use our

[[Page 42647]]

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 will 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 final rule). 
Specifically, based on the most recent complete LTCH data available 
at this time (that is, LTCH claims data from the March 2019 update 
of the FY 2018 MedPAR file and CCRs from the March 2019 update of 
the PSF), we determined a fixed-loss amount for LTCH PPS standard 
Federal payment rate cases for FY 2020 of $26,778 that will result 
in estimated outlier payments projected to be equal to 7.975 percent 
of estimated FY 2020 payments for such cases. Under the broad 
authority of section 123(a)(1) of the BBRA and section 307(b)(1) of 
the BIPA, we are establishing a fixed-loss amount of $26,778 for 
LTCH PPS standard Federal payment rate cases for FY 2020. Under this 
policy, 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 adjusted LTCH PPS standard Federal payment 
rate and the fixed-loss amount for LTCH PPS standard Federal payment 
rate cases of $26,778).
    We note, the fixed-loss amount for FY 2020 for LTCH PPS standard 
Federal payment rate cases we are establishing in this final rule 
based on the most recent LTCH claims data from the MedPAR file and 
the latest CCRs from the PSF, result in a fixed-loss amount for such 
cases that is lower than the proposed fixed-loss amount. This change 
is largely attributable to updates to CCRs from the December 2018 
update of the PSF to the March 2019 update of the PSF.

4. 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 final 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. 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. That is, our actuaries 
continue to 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 LTCH claims data 
used in the development of this FY 2020 IPPS/LTCH PPS final 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 fixed-loss amount for site neutral payment rate cases 
for FY 2020 is the IPPS fixed-loss amount for FY 2020. Therefore, 
consistent with past practice, in the FY 2020 IPPS/LTCH PPS proposed 
rule (84 FR 19617), we proposed 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 IPPS fixed-loss amount. That is, 
we proposed 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 the 
proposed rule. Accordingly, for FY 2020, we proposed 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).
    Comment: Some commenters requested CMS develop an HCO fixed-loss 
amount and HCO target based on data from site neutral discharges 
rather than adopting these figures from the IPPS. These commenters 
allege that the resource use of site neutral payment rate cases are 
not similar to IPPS cases based on their comparison of factors such 
as length of stay and average cost. However these commenters did not 
indicate what the HCO fixed-loss amount and HCO target should be 
based on data from site neutral discharges. Other commenters 
generally indicated that their analysis of LTCH claims data since 
the implementation of the site neutral payment rate shows that site 
neutral payment rate cases do not mirror similar IPPS cases, but did 
not specifically comment on the an HCO

[[Page 42648]]

fixed-loss amount and HCO target for site neutral payment rate 
cases.
    Response: FY 2018 LTCH claims data are currently the best 
available data, and as noted above, LTCH site neutral payment rate 
cases discharged during FY 2018 were paid the blended payment rate 
under the statutory extension of the transitional period. As we 
explained in the proposed rule (84 FR 19616), since not all of the 
FY 2018 LTCH claims data 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. 
That is, the expectation that the costs and resource use for FY 2020 
cases paid at the site neutral payment rate will likely mirror the 
costs and resource use for IPPS cases assigned to the same MS-DRG. 
Moreover, we note that evidence provided by commenters is not 
inconsistent with our assumptions. Leaving aside the fact that the 
LTCH site neutral payment rate cases discharged during FY 2018 were 
paid the blended payment rate under the statutory extension of the 
transitional period, our actuarial assumptions rests on comparing 
cases assigned to the same MS-DRG, and the commenters' analysis 
ignores this distinction by comparing all LTCH site neutral payment 
rate cases with the subset of IPPS cases having less than 3 days in 
an ICU.
    In addition, the statutory extension of the transitional blended 
payment rate for site neutral payment rate cases inherently reduces 
any financial incentives for LTCHs to respond as compared to the 
full site neutral payment rate. As LTCHs continue to transition to 
the full site neutral payment rate, it is reasonable to expect 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 prior to the implementation of the site 
neutral payment, and would continue to more closely resemble the 
costs and resource use for IPPS cases assigned to the same MS-DRG. 
Because of the on-going transition, it is not straightforward to 
project the costs and resource use for cases paid at the site 
neutral payment rate based on historical data as we near the end of 
the transitional period. For these reasons, we continue to believe 
the most appropriate fixed-loss amount for site neutral payment rate 
cases would be the IPPS fixed-loss amount.
    As we stated when adopted this approach in the FY 2016 IPPS/LTCH 
PPS final rule (80 FR 49619), to the extent experience under the 
revised LTCH PPS indicates site neutral payment rate cases differ 
sufficiently from these expectations, we agree it would be 
appropriate to revisit in future rulemaking the most appropriate 
fixed-loss amount used to determine HCO payments for site neutral 
payment rate cases. We intend to continue to review the most recent 
available LTCH PPS site neutral claims data. As we approach the end 
of the statutory transitional period, we will take stakeholders' 
feedback into consideration and continue to explore in future 
rulemaking the development of a HCO fixed-loss amount and HCO target 
for the site neutral payment rate rather than continuing to adopt 
the IPPS figures, and intend to explore for future rulemaking, 
perhaps as early as for next year's rule.
    After consideration of the public comments received on our 
proposals to use the FY 2020 IPPS fixed-loss amount and 5.1 percent 
HCO target for LTCH discharges paid at the site neutral payment rate 
in FY 2020, we are finalizing these proposals without modification.
    Therefore, for FY 2020, as we proposed, we are establishing 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 IPPS 
fixed loss amount. That is, we are establishing a fixed-loss amount 
for site neutral payment rate cases of $26,473, which is the same FY 
2020 IPPS fixed-loss amount discussed in section II.A.4.g.(1). of 
the Addendum to this final rule. Accordingly, under this policy, for 
FY 2020, we will calculate a HCO payment for site neutral payment 
rate cases with costs that exceed the HCO threshold amount, which is 
equal to 80 percent of the difference between the estimated cost of 
the case and the outlier threshold (the sum of site neutral payment 
rate payment and the fixed loss amount for site neutral payment rate 
cases of $26,473).
    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 proposed to continue this policy.
    As discussed earlier, consistent with the IPPS HCO payment 
threshold, we estimate our fixed-loss threshold of $26,473 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 proposed 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).
    Comment: Some commenters, as they have done since the inception 
of the site neutral payment rate, objected to the proposed site 
neutral payment rate HCO budget neutrality adjustment, claiming that 
it would result in savings to the Medicare program instead of being 
budget neutral. The commenters' primary objection continued to be 
based on their belief that, because the IPPS base rates used in the 
IPPS comparable per diem amount calculation of the site neutral 
payment rate include a budget neutrality adjustment for IPPS HCO 
payments (for example, a 5.1 percent adjustment on the operating 
IPPS standardized amount), an ``additional'' budget neutrality 
factor is not necessary and is, in fact, duplicative. Based on their 
belief that the proposed site neutral payment rate HCO budget 
neutrality adjustment is duplicative, some commenters recommended 
that if CMS continues with the application of that budget neutrality 
adjustment, the calculation of the IPPS comparable per diem amount 
should be revised to use the IPPS operating standardized amount 
prior to the application of the IPPS HCO budget neutrality 
adjustment.
    Some commenters indicated that their analysis of LTCH claims 
data since the implementation of the site neutral payment rate shows 
that site neutral payment rate cases continue to be 
``inappropriately underpaid''. These commenters believe the site 
neutral payment rate HCO budget neutrality adjustment exacerbates 
the ``underpayment'', as well as impacts access to care for Medicare 
patients that are LTCH site neutral payment rate cases.
    Response: We continue to disagree with the commenters that a 
budget neutrality adjustment for site neutral payment rate HCO 
payments is unnecessary or duplicative. We have stated such 
disagreement during each previous rulemaking cycle. We refer readers 
to 83 FR 41737 through 41738, 82 FR 38545 through 38546, 81 FR 57308 
through 57309, and 80 FR 49621 through 49622 for more information on 
our responses to these comments. As we stated in the FY 2016 IPPS/
LTCH PPS final rule (80 FR 49621 through 49622), while the 
commenters are correct that the IPPS base rates that are used in 
site neutral payment rate calculation include a budget neutrality 
adjustment for IPPS HCO payments, that adjustment is merely a part 
of the calculation of one of the inputs (that is, the IPPS base 
rates) that are used in the LTCH PPS computation of site neutral 
payment rate. The purpose of the HCO budget neutrality factor that 
is applied in determining the IPPS base rates is to ensure that 
estimated HCO payments made under

[[Page 42649]]

the IPPS do not increase aggregate IPPS payments in a given year. As 
such, the HCO budget neutrality factor that is applied to the IPPS 
base rates does not account for the additional HCO payments under 
the LTCH PPS that will be made to LTCH site neutral payment rate 
cases. Without a budget neutrality adjustment when determining 
payment for a case under the LTCH PPS, any HCO payments to site 
neutral payment rate cases would increase aggregate LTCH PPS 
payments above the level of expenditure if there were no HCO 
payments for site neutral payment rate cases.
    The fact that the budget neutrality factor for site neutral 
payment rate HCO payments and the outlier budget neutrality 
adjustment factor on the operating IPPS standardized amount are both 
set at the same outlier target percentage, that is, 5.1 percent, 
does not demonstrate the commenters' repeated assertions that the 
budget neutrality factor for site neutral payment rate HCO payments 
is duplicative. As we have explained since the implementation of the 
site neutral payment rate and above, we adopted the same percentage 
as is used under the IPPS due to our projection that costs and 
resource use of site neutral payment rate cases would likely mirror 
similar IPPS cases. (We discuss this projection in greater detail 
earlier in this section.) We also stated that, in the future, we 
will continue to explore in subsequent rulemaking the most 
appropriate fixed-loss amount, and thereby the outlier target 
percentage, used to determine LTCH PPS HCO payments for site neutral 
payment rate cases. The fact that the two outlier target percentages 
and the corresponding HCO budget neutrality factors (that is, the 
one under the operating IPPS and the one under the LTCH PPS for site 
neutral payment rate cases) do not necessarily have to match 
underscores that they serve to maintain budget neutrality in two 
distinct payment systems.
    The methodology for calculating the ``IPPS comparable per diem 
amount'' under Sec.  412.529(d)(4) had been already established by 
CMS at the time section 1886(m)(6)(B)(ii) of the Act, which defines 
the site neutral payment rate, was enacted, as that regulation has 
been used under the LTCH PPS since 2006 as a component in the 
calculation of short-stay outlier payments. The regulation at Sec.  
412.529(d)(4)(A) specifies that the ``IPPS comparable per diem 
amount'' is calculated by summing the applicable operating IPPS 
standardized amount and the capital IPPS Federal rate in effect at 
the time of the LTCH discharge. Both the IPPS standardized amount 
and the capital IPPS Federal rate are calculated by applying, among 
other adjustments, a budget neutrality factor to adjust for 
estimated outlier payments under the operating IPPS and capital 
IPPS, respectively. In other words, the statute requires the 
calculation of site neutral payment rate payments using defined 
amounts that already incorporate an IPPS outlier budget neutrality 
adjustment. Furthermore, since the implementation of the LTCH PPS, 
CMS has made a budget neutrality adjustment for estimated high cost 
outlier payments under the LTCH PPS (applied to the standard Federal 
rate) every year, by applying a reduction factor based on the 
estimated proportion of outlier payments under the LTCH PPS which 
are paid that rate. Given CMS's longstanding practice of budget 
neutralizing outlier payments throughout the various Medicare 
payment systems, including within the LTCH PPS, it is reasonable to 
expect when the site neutral payment rate was implemented, high cost 
outlier payments to cases paid at the site neutral payment rate 
would also be made in a budget neutral manner in the absence of any 
directive to the contrary.
    For these reasons, we continue to disagree with the commenters 
that a budget neutrality adjustment for site neutral payment rate 
HCO payments is unnecessary or duplicative, and we are, again, not 
adopting the commenters' recommendation to change the calculation of 
the IPPS comparable amount by adjusting the IPPS operating 
standardized amount used in that calculation to account for the 
application of the IPPS HCO budget neutrality adjustment.
    While commenters' analysis of LTCH claims data since the 
implementation of the site neutral payment rate may show that site 
neutral payment rate cases are typically paid less than the 
estimated cost, we disagree with the characterization that this 
results in an ``underpayment''. The statute requires that LTCH cases 
that do not meet the statutory patient criteria be paid the site 
neutral payment rate, and as discussed previously, the statute 
specifies the calculation of that site neutral payment rate. CMS's 
implementation of the site neutral payment rate is consistent with 
the statutory requirements at section 1886(m)(6) of the Act, and 
therefore, Medicare's payment for those cases is not inappropriate.
    While we understand and share commenters' concerns about access 
to and quality of care for Medicare beneficiaries, including those 
that are site neutral payment rate cases, as we have stated in the 
past, we believe the site neutral payment rate will not negatively 
impact 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 in areas where there is one or 
more LTCH present (82 FR 38754 through 38575). We further note, 
LTCHs must meet Medicare conditions of participation as general 
acute care hospitals.
    After consideration of public comments, for the reasons 
discussed above, we disagree with commenters that the site neutral 
payment rate case HCO budget neutrality factor is not necessary and 
duplicative or inappropriately reduces payments or Medicare 
patients' access to care, and we are, adopting our proposed site 
neutral payment rate HCO budget neutrality adjustment as final 
without modification.
    In order to achieve this, for FY 2020, as we proposed, we are 
applying 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, as proposed, this HCO budget 
neutrality adjustment will not apply to the HCO portion of the site 
neutral payment rate amount.

E. 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 site neutral payment rate at Sec.  
412.522. 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

[[Page 42650]]

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 the FY 2020 IPPS/
LTCH PPS proposed rule and in section IV.F.3. of the preamble of 
this final rule, based on the most recent data available, our 
estimate of 75 percent of the amount that would 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 is adjusted to 50.36 
percent (the product of 75 percent and 67.14 percent) and the 
resulting amount is used to calculate the uncompensated care 
payments to eligible hospitals. As a result, for FY 2020, we 
projected 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, in the FY 2020 IPPS/LTCH PPS proposed 
rule, we proposed 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 proposed that, if more recent data 
became available, we would use that data to determine this factor in 
this final rule.
    We did not receive any public comments in response to our 
proposal. In addition, there are no more recent data available to 
use that would affect the calculations determined in the proposed 
rule. Therefore, we are finalizing our proposal that, for FY 2020, 
the calculation of the ``IPPS comparable amount'' under Sec.  
412.529 includes 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.

F. Computing the 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 FY 2020 values are shown in 
Tables 12A through 12B listed in section VI. of the Addendum to this 
final 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 FY 2020 factors are shown in the 
chart in section V.C. of this Addendum) in accordance with Sec.  
412.525(b). In this final rule, we are establishing an LTCH PPS 
standard Federal payment rate for FY 2020 of $42,677.64, as 
discussed in section V.A. of the Addendum to this final rule. We 
illustrate the methodology to adjust the 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 FY 2020 LTCH PPS wage index 
value for CBSA 16974 is 1.0405 (obtained from Table 12A listed in 
section VI. of the Addendum to this final 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 relative weight for FY 2020 of 0.9616 
(obtained from Table 11 listed in section VI. of the Addendum to 
this final 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 Federal prospective payment amount by multiplying the 
unadjusted FY 2020 LTCH PPS standard Federal payment rate 
($42,677.64) by the labor-related share (66.3 percent) and the wage 
index value (1.0405). This wage-adjusted amount was then added to 
the nonlabor-related portion of the unadjusted LTCH PPS standard 
Federal payment rate (33.7 percent; adjusted for cost of living, if 
applicable) to determine the adjusted LTCH PPS standard Federal 
payment rate, which is then multiplied by the MS-LTC-DRG relative 
weight (0.9616) to calculate the total adjusted LTCH PPS standard 
Federal prospective payment for FY 2020 ($42,140.77). The table 
below illustrates the components of the calculations in this 
example.
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VI. Tables Referenced in This Final Rule Generally Available Through 
the Internet on the CMS Website

    This section lists the tables referred to throughout the 
preamble of this FY 2020 IPPS/LTCH PPS final 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 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

[[Page 42651]]

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 final 
rule, the 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 final 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 Final Rule Home Page'' or ``Acute 
Inpatient--Files for Download.''

Table 2.--Case-Mix Index and Wage Index Table by CCN--FY 2020
Table 3.--Wage Index Table by CBSA--FY 2020
Table 4.--List of Counties Eligible for the Out-Migration Adjustment 
under Section 1886(d)(13) of the Act--FY 2020
Table 5.--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.--Secondary Diagnosis Order Additions to the CC 
Exclusions List--FY 2020
Table 6G.2.--Principal Diagnosis Order Additions to the CC 
Exclusions List--FY 2020
Table 6H.1.--Secondary Diagnosis Order Deletions to the CC 
Exclusions List--FY 2020
Table 6H.2.--Principal Diagnosis Order Deletions to the CC 
Exclusions List--FY 2020
Table 6I.--Complete MCC List--FY 2020
Table 6I.1.--Additions to the MCC List--FY 2020
Table 6I.2.--Deletions to the MCC List--FY 2020
Table 6J.--Complete CC List--FY 2020
Table 6J.1.--Additions to the CC List--FY 2020
Table 6J.2.--Deletions to the CC List--FY 2020
Table 6K.--Complete List of CC Exclusions --FY 2020
Table 6P.-- ICD-10-PCS Codes for MS-DRG Changes--FY 2020 (Table 6P 
contains tables, 6P.1a. and 6P.1b., that include the ICD-10-PCS code 
lists relating to specific MS-DRG changes. These tables are referred 
to throughout section II.F. of the preamble of this final rule.)
Table 7A.--Medicare Prospective Payment System Selected Percentile 
Lengths of Stay: FY 2018 MedPAR Update--March 2019 GROUPER Version 
36 MS-DRGs
Table 7B.--Medicare Prospective Payment System Selected Percentile 
Lengths of Stay: FY 2018 MedPAR Update--March 2019 GROUPER Version 
37 MS-DRGs
Table 8A.--FY 2020 Statewide Average Operating Cost-to-Charge Ratios 
(CCRs) for Acute Care Hospitals (Urban and Rural)
Table 8B.--FY 2020 Statewide Average Capital Cost-to-Charge Ratios 
(CCRs) for Acute Care Hospitals
Table 16A.--Updated Proxy Hospital Value-Based Purchasing (VBP) 
Program Adjustment Factors for FY 2020
Table 18.--FY 2020 Medicare DSH Uncompensated Care Payment Factor 3

    The following LTCH PPS tables for this FY 2020 final 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-F:

Table 8C.--FY 2020 Statewide Average Total Cost-to-Charge Ratios 
(CCRs) for LTCHs (Urban and Rural)
Table 11.--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.--LTCH PPS Wage Index for Urban Areas for Discharges 
Occurring from October 1, 2019 through September 30, 2020
Table 12B.--LTCH PPS Wage Index for Rural Areas for Discharges 
Occurring from October 1, 2019 through September 30, 2020
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BILLING CODE 4120-01-C

Appendix A: Economic Analyses

I. Regulatory Impact Analysis

A. Statement of Need

    This final 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 final 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 changes in this final rule, such as the 
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 changes will 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 final 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 final rule is a major rule as 
defined in 5 U.S.C. 804(2). We estimate that the changes for FY 2020 
acute care hospital operating and capital payments will redistribute 
amounts in excess of $100 million to acute care hospitals. The 
applicable percentage increase to the IPPS rates required by the 
statute, in conjunction with other payment changes in this final 
rule, will result in an estimated $3.9 billion increase in FY 2020 
payments, primarily driven by a combined $3.5 billion increase in FY 
2020 operating payments and uncompensated care payments, and a net 
increase of $0.4 billion primarily resulting from estimated changes 
in FY 2020 capital payments and new technology add-on payments. 
These 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 $43 million in FY 2020 relative to FY 2019.
    Our operating impact estimate includes the 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 final rule. In addition, our operating payment 
impact estimate includes the 2.6 percent hospital update to the 
standardized amount (which includes the estimated 3.0 percent market 
basket update less the 0.4 percentage point for the multifactor 
productivity (MFP) adjustment). 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 final 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 final rule will 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 
final 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 changes in this final rule will 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 changes will ensure 
that the outcomes of the prospective payment systems are reasonable 
and equitable, while avoiding or minimizing unintended adverse 
consequences.
    Because this final rule contains a range of policies, we refer 
readers to the section of the final rule where each policy is 
discussed. These sections include the rationale for our decisions, 
including the need for the policy.

D. Limitations of Our Analysis

    The following quantitative analysis presents the projected 
effects of our policy changes, as well as statutory changes 
effective for FY 2020, on various hospital groups. We estimate the 
effects of individual 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 policies in the discussion 
of those 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 July 2019, there were 3,239 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 1,406 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

[[Page 42654]]

rulemaking. Payment impacts of changes to the prospective payment 
systems for these IPPS-excluded hospitals and units are not included 
in this final rule. The impact of the 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 July 2019, there were 97 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, 289 rehabilitation hospitals and 833 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 1,038 psychiatric units are paid 
the Federal per diem amount under the IPF PPS. As stated previously, 
IRFs and IPFs are not affected by the rate updates discussed in this 
final rule. The impacts of the 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 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 second quarter 2019 forecast of the 2014-based 
IPPS market basket increase, we are estimating the FY 2020 update to 
be 3.0 percent (that is, the estimate of the market basket rate-of-
increase). We used the most recent data available for this final 
rule to calculate the IPPS operating market basket update for FY 
2020. However, the Affordable Care Act requires a reduction for the 
multifactor productivity adjustment (0.4 percentage point for FY 
2020), resulting in a 2.6 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 final 
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 update is the percentage increase in 
the 2014-based IPPS operating market basket for FY 2020, estimated 
at 3.0 percent.
    The impact of the 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 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 Policy Changes Under the IPPS for 
Operating Costs

1. Basis and Methodology of Estimates

    In this final rule, we are announcing policy changes and payment 
rate updates for the IPPS for FY 2020 for operating costs of acute 
care hospitals. The FY 2020 updates to the capital payments to acute 
care hospitals are discussed in section I.I. of this Appendix.
    Based on the overall percentage change in payments per case 
estimated using our payment simulation model, we estimate that total 
FY 2020 operating payments will increase by 2.9 percent, compared to 
FY 2019. In addition to the applicable percentage increase, this 
amount reflects the +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 will also affect overall payment 
changes.
    We have prepared separate impact analyses of the changes to each 
system. This section deals with the 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 changes in this final rule. However, there are other changes 
for which we do not have data available that would allow us to 
estimate the payment impacts using this model. For those 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 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 
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 
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 payments under the capital IPPS, and the impact of the 
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 changes:
     The effects of the application of the applicable 
percentage increase of 2.6 percent (that is, a 3.0 percent market 
basket update with a reduction of 0.4 percentage point for the 
multifactor productivity adjustment), and a 0.5 percentage point 
adjustment required under section 414 of the MACRA to the IPPS 
standardized amount, and the applicable percentage increase 
(including the market basket update and the multifactor productivity 
adjustment) to the hospital-specific rates.
     The effects of the changes to the relative weights and 
MS-DRG GROUPER.
     The effects of the 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 FY 2020 wage index.
     The effects of the geographic reclassifications by the 
MGCRB (as of publication of this final rule) that will be effective 
for FY 2020.
     The effects of the rural floor with the application of 
the national budget neutrality factor to the wage index and the 
policy 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 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 policies to increase the wage index 
for hospitals with wage index

[[Page 42655]]

values below the 25th percentile wage index value (that is, the 
lowest quartile wage index adjustment), the transition policy in FY 
2020 pursuant to which a 5-percent cap will be placed on any 
decrease in a hospital's wage index compared to its final FY 2019 
wage index value (that is, the 5-percent cap), and the associated 
budget neutrality adjustments.
     The total estimated change in payments based on the FY 
2020 policies relative to payments based on FY 2019 policies, 
including estimated changes in outlier payments.
    To illustrate the impact of the 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, 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 will 
receive an applicable percentage increase of 1.85 percent. At the 
time this impact was prepared, 41 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 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, 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 will receive an applicable percentage 
increase of 0.35 percent. At the time this impact analysis was 
prepared, 167 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 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 will receive an 
applicable percentage increase of -0.4 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, 30 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 policy change, statutory or otherwise, is then added 
incrementally to this baseline, finally arriving at an FY 2020 model 
incorporating all of the changes. This simulation allows us to 
isolate the effects of each change.
    Our comparison illustrates the 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 update to the 
standardized amount. In accordance with section 1886(b)(3)(B)(i) of 
the Act, we are updating the standardized amounts for FY 2020 using 
an applicable percentage increase of 2.6 percent. This includes our 
forecasted IPPS operating hospital market basket increase of 3.0 
percent with a 0.4 percentage point reduction for the multifactor 
productivity adjustment. Hospitals that fail to comply with the 
quality data submission requirements and are meaningful EHR users 
will receive an update of 1.85 percent. This 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 will 
receive an update of 0.35 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 will receive an update of -0.4 
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 2.6 percent, if the hospital 
submits quality data and is a meaningful EHR user.
    A second significant factor that affects the 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 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 3,239 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 1,259 hospitals located in large urban areas 
(populations over 1 million), and 1,217 hospitals in other urban 
areas (populations of 1 million or fewer). In addition, there are 
763 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 2,183; 
1,281; 902; and 1,056, respectively.
    The next three groupings examine the impacts of the 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 2,116 nonteaching hospitals in our analysis, 873 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 changes on rural 
hospitals by special payment groups (SCHs, MDHs and RRCs). There 
were 383 RRCs, 306 SCHs, 150 MDHs, 144 hospitals that are both SCHs 
and RRCs, and 19 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

[[Page 42656]]

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) of the Act.
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a. Effects of the Hospital Update and Other Adjustments (Column 1)

    As discussed in section IV.B. of the preamble of this final 
rule, this column includes the hospital update, including the 3.0 
percent market basket update and the reduction of 0.4 percentage 
point for the multifactor productivity adjustment. In addition, as 
discussed in section II.D. of the preamble of this final rule, this 
column includes the FY 2020 +0.5 percentage point adjustment 
required under section 414 of the MACRA. As a result, we are making 
a 3.1 percent update to the national standardized amount. This 
column also includes the update to the hospital-specific rates which

[[Page 42661]]

includes the 3.0 percent market basket update and the reduction of 
0.4 percentage point for the multifactor productivity adjustment. As 
a result, we are making a 2.6 percent update to the hospital-
specific rates.
    Overall, hospitals will experience a 3.0 percent increase in 
payments primarily due to the combined effects of the hospital 
update to the national standardized amount and the hospital update 
to the hospital-specific rate. Hospitals that are paid under the 
hospital-specific rate will experience a 2.6 percent increase in 
payments; therefore, hospital categories containing hospitals paid 
under the hospital-specific rate will experience a lower than 
average increase in payments.

b. Effects of the Changes to the MS-DRG Reclassifications and Relative 
Cost-Based Weights With Recalibration Budget Neutrality (Column 2)

    Column 2 shows the effects of the changes to the MS-DRGs and 
relative weights with the application of the 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 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 final 
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 Version 37 
(FY 2020) MS-DRGs. The methodology to calculate the relative weights 
and the reclassification changes to the GROUPER are described in 
more detail in section II.G. of the preamble of this final rule.
    The ``All Hospitals'' line in Column 2 indicates that changes 
due to the MS-DRGs and relative weights will result in a 0.0 percent 
change in payments with the application of the recalibration budget 
neutrality factor of 0.997649 to the standardized amount. Hospital 
categories that generally treat cases in higher severity MS-DRGs, 
such as large urban hospitals, will experience a slight increase in 
their payments, while hospitals that generally treat fewer of these 
cases will experience a decrease in their payments under the 
relative weights. For example, rural hospitals will experience a 0.2 
percent decrease in payments in part because rural hospitals tend to 
treat fewer cases in higher severity MS-DRGs. Conversely, teaching 
hospitals with more than 100 residents will experience a slight 
increase in payments of 0.2 percent as those hospitals typically 
treat more cases in higher severity MS-DRGs.

c. Effects of the Wage Index Changes (Column 3)

    Column 3 shows the impact of the updated wage data using FY 2016 
cost report data, with the application of the 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 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 payment parameters constant in this 
simulation. That is, Column 3 shows the 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 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 Version 37 MS-
DRG GROUPER constant. The 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 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 calculated the 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 FY 2020 wage budget neutrality factor is 
1.001573 and the overall 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 wage budget neutrality adjustment, will 
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 1.03 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 1.03 percent increase in the 
national average hourly wage. Of the 3,220 hospitals with wage data 
for both FYs 2019 and 2020, 1490 or 46.3 percent would experience an 
average hourly wage increase of 1.03 percent or more.
    The following chart compares the shifts in wage index values for 
hospitals due to changes in the average hourly wage data for FY 2020 
relative to FY 2019. Among urban hospitals, none would experience a 
decrease of 10 percent or more, and 1 urban hospitals would 
experience an increase of 10 percent or more. Sixty six 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, 747 rural 
hospitals would experience increases or decreases of less than 5 
percent, while 2,398 urban hospitals would experience increases or 
decreases of less than 5 percent. Four urban hospitals and 2 rural 
hospitals would experience no change to their wage index. These 
figures reflect 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 final 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 final rule, which 
are available via the internet on the CMS website) is used 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 pre-reclassified wage index figures in the following chart may 
illustrate a somewhat larger or smaller change than would occur in a 
hospital's payment wage index and total payment.

[[Page 42662]]

    The following chart shows the projected impact of changes in the 
area wage index values for urban and rural hospitals.
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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 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 final 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 applied an adjustment of 
0.985425 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 final rule). We note 
that, with regard to the requirement under section 
1886(d)(8)(C)(iii) of the Act, in our calculation of the budget 
neutrality adjustment of 0.985425, we applied the provisions of our 
policy discussed in section III.N. of the preamble of this final 
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 final rule). Geographic reclassification generally benefits 
hospitals in rural areas. We estimate that the geographic 
reclassification will increase payments to rural hospitals by an 
average of 1.1 percent. By region, all the rural hospital categories 
will experience increases in payments due to MGCRB 
reclassifications.
    Table 2 listed in section VI. of the Addendum to this final rule 
and available via the internet on the CMS website reflects the 
reclassifications for FY 2020.

e. Effects of the 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 final 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 
applied a uniform budget neutrality adjustment to the wage index. 
Column 5 shows the effects of the 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 FY 2020 rural floor budget neutrality factor that was 
applied to the wage index of 0.997081, which will reduce wage 
indexes by 0.29 percent.
    Column 5 shows the projected impact of the 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) will 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 final rule, we 
calculated 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 change to the rural floor 
calculation methodology.
    We estimate that 164 hospitals will receive the rural floor in 
FY 2020. We note that there are approximately 99 fewer hospitals 
receiving the rural floor in FY 2020 than in FY 2019. This is due, 
in part, to our calculation of 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 
policy will 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 
will have their wage index reduced by the rural floor budget 
neutrality adjustment of 0.997081. We project that, in aggregate, 
rural hospitals will experience a 0.1 percent decrease in payments 
as a result of the application of the 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 will 
experience no change in payments because increases in payments to 
hospitals benefitting from the rural floor offset decreases in 
payments to non-rural floor urban hospitals whose wage index is 
downwardly adjusted by the rural floor budget neutrality factor. 
Urban hospitals in the New England region will experience a 0.4 
percent increase in payments primarily due to the application of the 
rural floor in Massachusetts. Eleven urban providers in 
Massachusetts are expected to receive the rural floor wage index 
value, including the rural floor budget neutrality adjustment, which 
will increase payments overall to hospitals in Massachusetts by an 
estimated $25 million. We estimate that Massachusetts hospitals

[[Page 42663]]

will receive approximately a 0.6 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 0.3 
percent increase in payments as a result of the application of the 
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 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 
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 calculating 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 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 will 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 will 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 will gain or lose due to the application of 
the 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 policy to increase the wage index for hospitals 
with a wage index value below the 25th percentile wage index, the 5-
percent cap, and the associated budget neutrality factors.
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f. Effects of the Application of the Frontier State Wage Index and 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 will increase 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 44 hospitals located in those 
States will 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 $64 million. Urban hospitals 
located in the West North Central region will 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 
176 providers that will receive the out-migration wage adjustment in 
FY 2020. Rural hospitals generally will 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 will 
each experience a 0.1 and 0.2 percent increase in payments, 
respectively. This out-migration wage adjustment also is not budget 
neutral, and we estimate the impact of these providers receiving the 
out-migration increase will be approximately $44 million.

g. Effects of the Lowest Quartile Wage Index Adjustment and 5-Percent 
Transition Policy With Application of Budget Neutrality

    Column 7 shows the effects of the wage index adjustment for 
hospitals with a wage index value below the 25th percentile wage 
index value, the 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, and the associated budget neutrality policy. As 
discussed in section III.N. of the preamble to this final rule, 
hospitals with a wage index value below the 25th percentile wage 
index value will 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 are also 
applying a budget neutrality factor to the standardized rate in 
order to ensure that our 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 applying a 5-percent cap on any 
decrease in a hospital's wage index from the hospital's final wage 
index in FY 2019 (which will include any decrease resulting from our 
policy to not include urban to rural reclassifications in the rural 
floor calculation).
    The overall effect of the application of the wage index 
adjustment for hospitals with a wage index value below the 25th 
percentile will be budget neutral. In order to ensure that the 
overall effect of the application of the wage index adjustment for 
hospitals with a wage index value below the 25th percentile is 
budget neutral, we are applying a budget neutrality factor of 
0.997987 to the FY 2020 standardized amount (as described in section 
III.N.2.b. of this final rule). In addition, we are implementing the 
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 
applying a budget neutrality adjustment factor of 0.998838 to the FY 
2020 standardized amount to implement the 5-percent cap in a budget 
neutral manner.
    To show the effects of the lowest quartile wage index 
adjustments, the 5-percent cap, and the associated budget neutrality 
factors, column 7 compares payments calculated with the FY 2020 wage 
index prior to the application of: (a) The adjustment for hospitals 
with a wage index value below the 25th percentile; (b) the 5-percent 
cap on any decrease in a hospital's wage index; and (c) the budget 
neutrality factors to the standardized rate associated with (1) the 
adjustment for hospitals with a wage index value below the 25th 
percentile and (2) the 5-percent cap to payments calculated using 
the FY 2020 wage index with the above mentioned adjustments applied 
(that is, the lowest quartile wage index adjustment, the 5-percent 
cap, and the associated budget neutrality factors). The net effect 
of these three policies generally benefits hospitals in rural areas. 
For example, we estimate that the adjustments for hospitals with a 
wage index value below the 25th percentile wage index, the 5-percent 
cap on any decrease in a hospital's wage index, and the application 
of the associated budget neutrality factors, will increase payments 
to rural hospitals by an average of 0.3 percent. By region, rural 
South Atlantic and West South Central hospital categories will 
experience increases in payments by 0.5 and 0.7 percent, 
respectively. Puerto Rico providers will experience a 12.5 percent 
increase in payments due to the application of the lowest quartile 
wage index adjustment because they generally have the lowest wage 
index values.

h. Effects of All FY 2020 Changes (Column 8)

    Column 8 shows our estimate of the changes in payments per 
discharge from FY 2019 and FY 2020, resulting from all changes 
reflected in this final rule for FY 2020. It includes combined 
effects of the year-to-year change of the previous columns in the 
table.
    The average increase in payments under the IPPS for all 
hospitals is approximately 2.9 percent for FY 2020 relative to FY 
2019 and for this row is primarily driven by the changes reflected 
in Column 1. Column 8 includes the annual hospital update of 2.6 
percent to the national standardized amount. This annual hospital 
update includes the 3.0 percent market basket update and the 0.4 
percentage point reduction for the multifactor productivity 
adjustment. As discussed in section II.D. of the preamble of this 
final 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 will receive a 2.6 percent hospital 
update. As described in Column 1, the annual hospital update with 
the +0.5 percent adjustment for hospitals paid under the national 
standardized amount, combined with the annual hospital update for 
hospitals paid under the hospital-specific rates, will result in a 
2.9 percent increase in payments in FY 2020 relative to FY 2019. 
This estimated increase also reflects an estimated decrease in 
outlier payments of 0.13 percent (from our current estimate of FY 
2019 outlier payments of approximately 5.23 percent to 5.1 percent 
projected for FY 2020 based on the FY 2018 MedPAR data used for this 
final 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 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 
applicable percentage increase and changes to policies related to 
MS-DRGs, geographic adjustments, and outliers are estimated to 
increase by 2.9 percent for FY 2020. Hospitals in urban areas will 
experience a 2.9 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 2.8 percent in FY 2020.

3. Impact Analysis of Table II

    Table II below presents the projected impact of the 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 
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 
changes presented in Table I. The estimated percentage changes shown 
in the last column of Table II equal

[[Page 42668]]

the estimated percentage changes in average payments per discharge 
from Column 8 of Table I.
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H. Effects of Other Policy Changes

    In addition to those policy changes discussed previously that we 
are able to model using our IPPS payment simulation model, we are 
making various other changes in this final 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 changes in this final rule. 
Generally, we have limited or no specific data available with which 
to estimate the impacts of these changes using that payment 
simulation model. For those 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 changes are discussed in this section.

1. Effects of Policies Relating to New Medical Service and Technology 
Add-On Payments

a. Technologies Approved for FY 2020 New Technology Add-On Payments

    In section II.H. of the preamble to this final rule, we discuss 
13 technologies for which we received applications for add-on 
payments for new medical services and technologies for FY 2020. We 
note that three applicants withdrew their applications prior to the 
issuance of this final rule, and one applicant did not receive FDA 
approval for its technology by the July 1 deadline. We also

[[Page 42670]]

discuss the status of the new technologies that were approved to 
receive new technology add-on payments in FY 2019. As explained in 
the preamble to this final 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 final 
rule, we are approving the following 9 applications for new 
technology add-on payments for FY 2020: AZEDRA[supreg] 
(Ultratrace[supreg] iobenguane Iodine-131) Solution; CABLIVI[supreg] 
(caplacizumab-yhdp); ELZONRISTM (tagraxofusp, SL-401); 
BalversaTM (Erdafitinib); ERLEADATM 
(Apalutamide); SPRAVATO (Esketamine); XOSPATA[supreg] 
(gilteritinib); JAKAFITM (Ruxolitinib) and T2 Bacteria 
Test Panel.
    In addition, as we proposed, as discussed in section II.H.4. of 
the preamble of this final rule, we are continuing 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 are still considered new for purposes of new 
technology add-on payments. (We note, as proposed, we are 
discontinuing 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.)
    Under our change to the calculation of the new technology add-on 
payments, in general the new technology add-on payment for each case 
will 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. For 
antimicrobials designated as a Qualified Infectious Disease Product 
(QIDP), the new technology add-on payment for each case will be 
limited to the lesser of (1) 75 percent of the costs of the new 
technology; or (2) 75 percent of the amount by which the costs of 
the case exceed the standard MS-DRG payment for the case.
    The following are estimates for FY 2020 for the nine 
technologies for which we are continuing 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 will 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) will 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 technology add-on payments for 
GIAPREZATM will 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] 
will 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 will 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 will 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 will increase overall FY 2020 payments by 
$22,020,768 (maximum add-on payment of $8,316 * 2,648 patients).
     Based on the applicant's estimate for FY 2019, we 
currently estimate that new technology add-on payments for 
VYXEOSTM will 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 will increase overall FY 2020 payments by 
$10,209,375 (maximum add-on payment of $4,083.75 * 2,500 patients).
    The following are estimates for FY 2020 for the nine 
technologies that we are approving for new technology add-on 
payments beginning in FY 2020.
     Based on the applicant's estimate for FY 2020, we 
currently estimate that new technology add-on payments for 
AZEDRA[supreg] (Ultratrace[supreg] iobenguane Iodine-131) Solution 
will increase overall FY 2020 payments by $39,260,000 (maximum add-
on payment of $98,150 * 400 patients).
     Based on the applicant's estimate for FY 2020, we 
currently estimate that new technology add-on payments for 
CABLIVI[supreg] (caplacizumab-yhdp) will increase overall FY 2020 
payments by $4,351,165 (maximum add-on payment of $33,215 * 131 
patients).
     Based on the applicant's estimate for FY 2020, we 
currently estimate that new technology add-on payments for 
ELZONRISTM (tagraxofusp, SL-401) will increase overall FY 
2020 payments by $30,985,668 (maximum add-on payment of $125,448.05 
* 247 patients).
     Based on the applicant's estimate for FY 2020, we 
currently estimate that new technology add-on payments for 
BalversaTM (Erdafitinib) will increase overall FY 2020 
payments by $178,162 (maximum add-on payment of $3,563.23 * 50 
patients).
     Based on the applicant's estimate for FY 2020, we 
currently estimate that new technology add-on payments for 
ERLEADATM (Apalutamide) will increase overall FY 2020 
payments by $286,171 (maximum add-on payment of $1,858.25 * 154 
patients).
     Based on the applicant's estimate for FY 2020, we 
currently estimate that new technology add-on payments for SPRAVATO 
(Esketamine) will increase overall FY 2020 payments by $6,494,656 
(maximum add-on payment of $1,014.79 * 6,400 patients).
     Based on the applicant's estimate for FY 2020, we 
currently estimate that new technology add-on payments for 
XOSPATA[supreg] (gilteritinib) will increase overall FY 2020 
payments by $13,710,938 (maximum add-on payment of $7,312.50 * 1,875 
patients).
     Based on the applicant's estimate for FY 2020, we 
currently estimate that new technology add-on payments for 
JAKAFITM (Ruxolitinib) will increase overall FY 2020 
payments by $556,788 (maximum add-on payment of $3,977.06 * 140 
patients).
     Based on the applicant's estimate for FY 2020, we 
currently estimate that new technology add-on payments for T2 
Bacteria Test Panel will increase overall FY 2020 payments by 
$3,669,803 (maximum add-on payment of $97.50 * 37,639 patients).

b. Alternative Inpatient New Technology Add-On Payment Pathway for 
Transformative New Devices and Certain Antimicrobial Resistant Products

    In section II.H.8. of the preamble of this final rule, we 
discuss the alternative inpatient new technology add-on payment 
pathway for certain new devices and certain antimicrobial resistant 
products we are establishing for applications received for IPPS new 
technology add-on payments for FY 2021 and subsequent fiscal years. 
Specifically, we are providing that, if a medical device is part of 
the FDA's Breakthrough Devices Program or if medical product is 
designated by the FDA as a Qualified Infectious Disease Product 
(QIDP), and received FDA market authorization, such a device or 
product will 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 providing that such a medical device or 
product will 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 or QIDPs 
that apply for new technology add-on payments would be approved 
under the existing criteria, this policy has no impact. To the 
extent that there are future medical devices or QIDPs 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 policy is a cost, but that 
cost is not estimable.
    The FDA has granted a total of 147 QIDP designations (74 of 
which were novel). However, designations may be granted at any point 
in the drug development process (e.g., Phase 1), and the majority of 
QIDP-designated drugs are not expected to get

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market authorization. Of all antibiotics to date, the FDA has only 
approved 12 QIDP drugs. Therefore, we believe there is minimal to no 
impact on Medicare program expenditures due to the alternative 
inpatient new technology add-on payment pathway for QIDPs. We also 
note that as this finalized policy will be effective beginning with 
new technology add-on payment applications for FY 2021, there is no 
impact of this policy in FY 2020.

c. Changes to the Calculation of the Inpatient New Technology Add-On 
Payment

    In section II.H.9. of the preamble of this final rule, we 
discuss our policy to modify the current new technology add-on 
payment mechanism to increase the amount of the maximum add-on 
payment amount to 65 percent (and 75 percent for Qualified 
Infectious Disease Products (QIDPs)). Specifically, for technologies 
other than QIDPs, 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 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) 75 percent of the amount by which the costs of 
the case exceed the standard DRG payment. For technologies 
designated as QIDPs, 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 will make an add-on payment equal to the lesser 
of: (1) 75 percent of the costs of the new medical service or 
technology; or (2) 75 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 
will be limited to the full MS-DRG payment plus 65 percent (or 75 
percent for QIDPs) of the estimated costs of the new technology or 
medical service.
    We estimate that for the nine technologies for which we are 
continuing to make new technology add-on payments in FY 2020 and for 
the nine FY 2020 new technology add-on payment applications that we 
are approving for new technology add-on payments for FY 2020, these 
changes to the calculation of the inpatient new technology add-on 
payment will increase IPPS spending by approximately $94 million in 
FY 2020, of which approximately $4 million is due to the 
differential new technology add-on payment percentage (that is, 75 
percent versus 65 percent).

2. Effects of 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 final rule, we discuss 
our 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 final 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 new or revised MS-DRGs will qualify for the 
postacute care transfer and MS-DRG special payment policies. As a 
result of our finalized policies to revise the MS-DRG 
classifications for FY 2020, which are discussed in section II.F. of 
the preamble of this final rule, we are removing two MS-DRGs from 
the list of MS-DRGs that will 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 changes to the 
MS-DRGs and the relative payment weights and the application of the 
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 
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 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 final 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 will decrease Medicare payments by $7 million in FY 2020 as 
compared to FY 2019. More specifically, in FY 2020, we estimate that 
594 providers will receive approximately $442 million compared to 
our estimate of 600 providers receiving approximately $449 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 subsection 
(d) hospital and have less than 3,800 total discharges).

4. Effects of the Changes to Medicare DSH and Uncompensated Care 
Payments for FY 2020

    As discussed in section IV.F. of the preamble of this final 
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 (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 final rule, we are establishing the amount to be 
distributed as uncompensated care payments to DSH eligible 
hospitals, which for FY 2020 is $8,350,599,096.04. 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 used hospitals' FY 
2015 cost reports from the HCRIS database, as updated through June 
30, 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 Medicaid days for FY 2013 and SSI days for FY 2017. 
For a complete discussion of the methodology for calculating Factor 
3, we refer readers to section IV.F.4. of the preamble of this final 
rule.
    To estimate the impact of the combined effect of 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 
final 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

[[Page 42672]]

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 Factor 2 of 67.14 percent and multiplied by a 
Factor 3 calculated using the methodology described previously.
    Our analysis included 2,432 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 June 
18, 2019, Maryland hospitals, new hospitals, MDHs, and SCHs that are 
expected to be paid based on their hospital-specific rates. The 28 
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 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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    Changes in projected FY 2020 uncompensated care payments from 
payments in FY 2019 are driven by an increase in Factor 1 and a 
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. Factor 1 has increased from $12.254 billion to 
$12.438 billion, and the 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 changes in these two factors, 
the impact analysis found that, across all projected DSH eligible 
hospitals, FY 2020 uncompensated care payments are estimated at 
approximately $8.351 billion, or an increase of approximately 0.94 
percent from FY 2019 uncompensated care payments (approximately 
$8.273 billion). While these changes will 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 
changes in Factor 3. As seen in the above table, percent increases 
smaller than 0.94 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 0.94 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. In general, rural hospitals, benefit under 
the FY 2020 final rule's methodology to use one year of Worksheet S-
10 data compared to FY 2019 final rule's methodology, which used a 
three-year average approach with low-income insured days proxy and 
two-years of uncompensated care cost Worksheet S-10 data. Overall, 
rural hospitals are projected to receive a 15.44 percent increase in 
uncompensated care payments, while urban hospitals are projected to 
receive a 0.07 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 23.00 percent payment increase, rural 
hospitals with 100-249 beds are projected to receive a 7.15 percent 
increase, and larger rural hospitals with 250+ beds are projected to 
receive a 10.96 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 14.42 percent, and urban hospitals 
with 100-249 beds projected to receive an increase of 2.14 percent, 
both of which are greater than the overall average. Larger urban 
hospitals with 250+ beds are projected to receive a 1.24 percent 
decrease in uncompensated care payments.
    By region, rural hospitals are expected to receive a larger than 
average increase in uncompensated care payments in all Regions, 
except for rural hospitals in the Middle Atlantic Region, which are 
projected to receive a decrease in uncompensated care payments. 
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 a decrease in uncompensated care payments. A 
smaller than average increase in uncompensated care payments is 
projected in the Middle Atlantic Region, while urban hospitals in 
the South Atlantic, East South Central, West South Central Regions 
and in Puerto Rico are projected to receive a larger than average 
increase in uncompensated care payments.
    By payment classification, although urban hospitals overall are 
expected to receive a 2.32 percent increase in uncompensated care

[[Page 42675]]

payments, hospitals in large urban areas are expected to see an 
increase in uncompensated care payments of 4.99 percent, while 
hospitals in other urban areas are expected to receive a decrease in 
uncompensated care payments of 3.01 percent. Hospitals in rural 
areas are also projected to receive a decrease of 4.17 percent.
    Nonteaching hospitals are projected to receive a larger than 
average payment increase of 3.82 percent. Teaching hospitals with 
fewer than 100 residents are projected to receive a payment decrease 
of 1.92 percent, while those teaching hospitals with 100+ residents 
have a projected payment increase of 1.27 percent, slightly higher 
than the overall average. Government hospitals are projected to 
receive a larger than average increase of 21.32 percent, while 
proprietary and voluntary hospitals are projected to receive 
decreases of 1.97 and 7.06 percent respectively. 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 decrease in uncompensated care payments.

5. Effects of Reductions Under the Hospital Readmissions Reduction 
Program for FY 2020

    In section IV.G. of the preamble of this final 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 and procedures. The table and 
analysis in this final rule illustrate the estimated financial 
impact the Hospital Readmissions Reduction Program payment 
adjustment methodology by hospital characteristic. As outlined in 
section IV.G. of the preamble of this final 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, 2015 and June 30, 2018 (that is, the FY 2020 
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 
2020 Hospital IPPS Proposed Rule Impact File.
    These analyses include 3,027 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, 2015 and June 
30, 2018. 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, 82.80 percent of eligible 
hospitals characterized as non-teaching hospitals are expected to be 
penalized. Among teaching hospitals, 88.41 percent of eligible 
hospitals with fewer than 100 residents and 95.22 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 characteristic. 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, 2017 and September 30, 2018 (FY 2018). For example, the penalty 
as a share of payments for urban hospitals is 0.69 percent. This 
means that total penalties for all urban hospitals are 0.69 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 Changes Under the FY 2020 Hospital Value-Based Purchasing 
(VBP) Program

    In section IV.H. of the preamble of this final 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 final 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, will 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 March 2019 update 
to the FY 2018 MedPAR file.
    The estimated impacts of the FY 2020 program year by hospital 
characteristic, found in the table in this section, 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 March 2019 update to the FY 2018 MedPAR 
file. The proxy adjustment factors can be found in Table 16A 
associated with this final 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 are expected to receive an increase in 
their base operating DRG payment amount is higher than the number of 
hospitals that are expected to receive a decrease. On average, among 
urban hospitals, hospitals in the West North Central region are 
expected to have the largest positive percent change in base 
operating DRG, and among rural hospitals, hospitals in the Mountain 
region are expected to have the largest positive percent change in 
base operating DRG. Urban Middle Atlantic, Urban East South Central, 
and Urban West South Central regions are expected to experience, on 
average, a decrease in base operating DRG. All other regions, both 
urban and rural, are expected to experience, on average, an increase 
in base operating DRG.
    As DSH patient percentage increases, the average percent change 
in base operating DRG is expected 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 is expected to increase. On average, teaching 
hospitals are expected to have a decrease in base operating DRG 
while non-teaching hospitals are expected to 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 this 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 were used for the updated impact analysis in this final rule.

7. Effects of Requirements Under the HAC Reduction Program for FY 2020

    In section IV.I. of the preamble of this final rule, we discuss 
the requirements for the HAC Reduction Program for FY 2020. In this 
final rule, we are not removing measures or adopting 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 (expiration date November 30, 2021), 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 final 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 updating 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 Hospital-
Acquired Condition (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 in this section 
presents the estimated proportion of hospitals in the worst-
performing quartile of Total HAC Scores by hospital characteristic.
    Hospitals' CMS Patient Safety Indicator (PSI) 90 measure results 
are based on Medicare fee-for-service (FFS) discharges from July 1, 
2016 through June 30, 2018 and version 9.0 of the PSI software. 
Hospitals' measure results for Centers for Disease Control and 
Prevention (CDC) Central Line-Associated Bloodstream Infection 
(CLABSI), Catheter-Associated Urinary Tract Infection (CAUTI), Colon 
and Abdominal Hysterectomy Surgical Site Infection (SSI), 
Methicillin-resistant Staphylococcus aureus (MRSA) bacteremia, and 
Clostridium difficile Infection (CDI) are derived from standardized 
infection ratios (SIRs) calculated with hospital surveillance data 
reported to the National Healthcare Safety Network (NHSN) for 
infections occurring between January 1, 2017 and December 31, 2018.
    To analyze the results by hospital characteristic, we used the 
FY 2020 Proposed Rule Impact File. This table includes 3,169

[[Page 42680]]

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 3,169 hospitals, 3,154 hospitals had information 
for geographic location with bed size, Safety-net status, 
Disproportionate Share Hospital (DSH) percent, and teaching status; 
3,168 had information on region, 3,126 had information for 
ownership; and 3,132 had information for Medicare Cost Report (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, 2,058 hospitals are characterized as non-teaching hospitals, 
845 are characterized as teaching hospitals with fewer than 100 
residents, and 251 are characterized as teaching hospitals with at 
least 100 residents. This only represents a total of 3,154 hospitals 
because the other 15 hospitals are missing from the FY 2020 Proposed 
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, 449 hospitals out of 2,058 
hospitals characterized as non-teaching hospitals would be subject 
to a payment reduction. Among teaching hospitals, 211 out of 845 
hospitals with fewer than 100 residents and 121 out of 251 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 2,058 hospitals characterized as non-teaching 
hospitals, 25.0 percent of the 845 teaching hospitals with fewer 
than 100 residents, and 48.2 percent of the 251 teaching hospitals 
with 100 or more residents would be subject to a payment reduction.
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8. Effects of Changes Related to Critical Access Hospitals (CAHs) as 
Nonproviders for Direct GME and IME Payment Purposes

    In section IV.J.2. of the preamble of this final rule, we 
discuss our finalized policy 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 setting requirements currently included at 42 CFR 
413.78(g) (and the corresponding IME regulation at 42 CFR 
412.105(f)(1)(ii)(E)). We note that we are not changing 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 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 can 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 will not mean the 
hospitals will be able to claim additional FTE residents above their 
FTE caps. Thus, because no additional funded slots will be created 
for IPPS hospitals by this policy, and because CAHs will 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 final 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 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 IPPS/LTCH PPS final 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 the 
Affordable Care Act elected to continue in the second 5-year 
extension period, while 13 additional hospitals were selected to 
participate. One of the hospitals selected in 2017 withdrew from the 
demonstration prior to beginning participation on July 1, 2018, and, 
in addition, one among the previously participating hospitals closed 
effective January 2019. Each of the remaining newly participating 
hospitals began its 5-year period of participation effective the 
start of the first cost reporting period on or after October 1, 
2017. Thus, 28 hospitals 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 final rule, the resulting amount applicable to FY 2020 
is $60,972,359, which we are including 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 
currently finalized update factors for cost and payment.
    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. Finalized cost reports are now 
available for the 22 and 21 hospitals that completed a cost 
reporting period according to the demonstration cost-based payment 
methodology beginning in FYs 2014 and 2015, respectively. The actual 
costs of the demonstration for FY 2014 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; 
the actual costs of the demonstration for FY 2015 determined from 
finalized cost reports fell short of the estimated amount finalized 
in the FY 2015 IPPS/LTCH PPS final rule by $20,297,477.
    We note that, for this final rule, the amounts identified for 
the actual costs of the demonstration for each of FYs 2014 and 2015 
(determined from finalized cost reports) is less than the amount 
that was identified in the final rule for the corresponding 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, respective to each of FYs 2014 and 
2015, 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 applying to 
the national IPPS rates is $25,742,822.

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10. Effects of Change Related to CAH Payment for Ambulance Services

    In section VI.C.2. of the preamble of this final rule, we 
discuss our decision to finalize the proposed revisions to the 
regulations at Sec.  413.70(b)(5) 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 are also finalizing the proposed conforming 
change to Sec.  413.70(b)(5)(i)(C), which will make that provision 
effective only for cost reporting periods starting on or before 
September 30, 2019.
    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 addressed by our revised 
policy under Sec.  413.70(b)(5)(i)(D), we estimate Medicare payments 
will increase by approximately $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 final 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 FY 2021. Therefore, this 
policy has no impact for any national payment system for FY 2020.

I. Effects of Changes in the Capital IPPS

1. General Considerations

    For the impact analysis presented below, we used data from the 
March 2019 update of the FY 2018 MedPAR file and the March 2019 
update of the Provider-Specific File (PSF) that was used for payment 
purposes. Although the analyses of the changes to the capital 
prospective payment system do not incorporate cost data, we used the 
March 2019 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 
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 March 2019 update of the FY 2018 MedPAR 
file, we simulated payments under the capital IPPS for FY 2019 and 
the 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 
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. Then we 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 will 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 final rule, the update to the 
capital Federal rate is 1.5 percent for FY 2020.
     In addition to the FY 2020 update factor, the FY 2020 
capital Federal rate was calculated based on a GAF/DRG budget

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neutrality adjustment factor of 0.9956 and a outlier adjustment 
factor of 0.9461.

2. Results

    We used the actuarial model previously described in section I.I. 
of Appendix A of this final rule to estimate the potential impact of 
the changes for FY 2020 on total capital payments per case, using a 
universe of 3,239 hospitals. As previously described, the individual 
hospital payment parameters are taken from updated data, including 
the March 2019 update of the FY 2018 MedPAR file, the March 2019 
update to the PSF, and the cost report data from the March 2019 
update of HCRIS. In Table III, we present a comparison of estimated 
total payments per case for FY 2019 and estimated total payments per 
case for FY 2020 based on the FY 2020 payment policies. Column 2 
shows estimates of payments per case under our model for FY 2019. 
Column 3 shows estimates of payments per case under our model for FY 
2020. Column 4 shows the total percentage change in payments from FY 
2019 to FY 2020. The change represented in Column 4 includes the 1.5 
percent update to the capital Federal rate and other 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 1.5 percent update to the capital Federal rate 
for FY 2020. In general, regional variations in estimated capital 
payments per case in FY 2020 as compared to capital payments per 
case in FY 2019 are primarily due to changes in the GAFs, and are 
generally consistent with the projected changes in payments due to 
changes in the wage index (and policies affecting the wage index), 
as shown in Table I in section I.G. of this Appendix A.
    The net impact of these changes is an estimated 1.4 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 will experience an increase in 
capital IPPS payments per case in FY 2020 as compared to FY 2019. 
Capital IPPS payments per case will increase by an estimated 1.4 
percent for hospitals in large urban areas and by 1.2 percent for 
hospitals in other urban areas, while payments to hospitals in rural 
areas will increase by 2.0 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 1.3 percent decrease for the New England region to a 
2.5 percent increase for the East South Central region. Similarly, 
for rural regions, the East South Central rural region is projected 
to experience an increase in capital IPPS payments per case of 3.1 
percent, while the New England rural region is projected to decrease 
0.6 percent. These regional differences are primarily due to the 
changes in the GAFs resulting from the changes we are adopting to 
the wage index to address wage index disparities. (As explained in 
section III.A.3. of the Addendum to this final rule, these finalized 
policies directly affect the GAF because the GAFs are calculated 
based on the hospital wage index value that is applicable to the 
hospital under 42 CFR part 412, subpart D which governs the 
methodology for determining the operating IPPS payments.) As 
discussed in section III.N of the preamble of this final rule, 
hospitals with a wage index value below the 25th percentile wage 
index value will 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; urban to rural 
reclassifications are no longer included in the rural floor 
calculation; and any decrease in a hospital's wage index from the 
hospital's final wage index in FY 2019 is capped at 5-percent. We 
note that application of the lowest quartile wage index adjustment 
results in regions with hospitals that have the lowest wage index 
values generally projected to experience the largest increases in 
payment. 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 1.3 percent compared with an 
increase of 1.5 percent for proprietary hospitals. Government 
hospitals are expected to experience an increase in capital IPPS 
payments of 1.6 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 final rule for FY 2020, we show the average 
capital payments per case for reclassified hospitals for FY 2020. 
Urban reclassified hospitals are expected to experience an increase 
in capital payments of 1.2 percent; urban nonreclassified hospitals 
are expected to experience an increase in capital payments of 1.5 
percent. The estimated percentage increase for rural reclassified 
hospitals is 1.7 percent, and for rural nonreclassified hospitals, 
the estimated percentage increase in capital payments is 2.7 
percent. This variation is largely due to the effect of changes in 
the GAF on capital payments for these hospitals.
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J. Effects of Payment Rate Changes and Policy Changes Under the 
LTCH PPS

1. Introduction and General Considerations

    In section VII. of the preamble of this final rule and section 
V. of the Addendum to this final rule, we set forth the annual 
update to the payment rates for the LTCH PPS for FY 2020. In the 
preamble of this final rule, we specify the statutory authority for 
the provisions that are presented, identify the policies for FY 
2020, and present rationales for our decisions as well as 
alternatives that were considered. In this section of Appendix A to 
this final rule, we discuss the impact of the changes to the payment 
rate, factors, and other payment rate policies related to the LTCH 
PPS that are presented in the preamble of this final 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 392 LTCHs, for 
purposes of this impact analysis, we excluded the data of all-
inclusive rate providers consistent with the development of the FY 
2020 MS-LTC-DRG relative weights (discussed in section VII.B.3.c. of 
the preamble of this final rule. Moreover, in the claims data used 
for this final 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 payment rate, factors, and policies 
presented in this final rule, the 2.5 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 final rule, the update to the MS-LTC-
DRG classifications and relative weights, the update to the wage 
index values and labor-related share, and the best available claims 
and CCR data to estimate the change in payments for FY 2020.

[[Page 42687]]

    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 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 2020, 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 determined under Sec.  
412.522(c)(3), 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 final 
rule, we estimate that overall LTCH PPS payments in FY 2020 will 
increase by approximately 1.0 percent (or approximately $43 million) 
based on the rates and factors presented in section VII. of the 
preamble and section V. of the Addendum to this final 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 total FY 2020 
LTCH PPS payments for site neutral payment rate cases, as we 
proposed, 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 will begin during FY 2020. For example, LTCHs with 
cost reporting periods that begin during October through December 
2019 are grouped to site neutral payment rate cases whose discharges 
will 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 
will 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 7.0 percent of all FY 2020 site neutral 
payment rate cases and, therefore, we estimate that group of LTCHs 
will discharge 7.0 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 March 
2019 update of the PSF and the LTCH claims from the March 2019 
update of the FY 2018 MedPAR files for the 384 LTCHs in our database 
used for this final rule, we found the following: 7.0 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; 9.2 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:
     First Quarter FY 2020: 7.0 percent of site neutral 
payment rate cases (that is, the percentage of discharges from LTCHs 
whose FY 2020 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 93.0 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 final 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

[[Page 42688]]

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 5.9 percent (or 
approximately $49 million).
    Comment: Some commenters expressed concern that the payment-to-
cost differential for site neutral payment rate cases, which they 
estimate to have decreased from 78 percent in FY 2017 to 46 percent 
in FY 2020, represents an ``inappropriate underpayment of site-
neutral cases''. These commenters stated that CMS should address the 
``chronic and substantial underpayment of site-neutral cases and its 
impact on patients seeking medically necessary LTCH services at the 
site-neutral level.'' Moreover, as discussed in section V.D.4. of 
the Addendum of this final rule, these commenters expressed their 
belief that this payment-to-cost differential, among other reasons, 
invalidates our assumptions that site neutral payment rate 
discharges are expected to mirror comparable IPPS discharges.
    Response: With respect to commenters' claims that the site 
neutral payment rate represents a ``chronic and substantial 
underpayment'', we remind readers that the site neutral payment rate 
is statutory. In explicitly defining the site neutral payment rate, 
the statute does so without regard to payment-to-cost ratios. For 
these reasons and as we discuss in greater detail section V.D.4. of 
the Addendum of this final rule, we believe Medicare's payment for 
those cases is appropriate. As we also discuss in section V.D.4. of 
the Addendum of this final rule, we continue to believe the site 
neutral payment rate will not negatively impact access to or quality 
of care for Medicare beneficiaries given that general acute care 
hospitals are effectively providing treatment for the same types of 
patients. We respond to the comments regarding our assumptions that 
site neutral discharges will mirror comparable IPPS discharges in 
our discussion of the establishment of the HCO threshold for site 
neutral cases while the blended payment rate remains in effect, and 
we refer readers to section V.D.4. of the Addendum of this final 
rule for that full discussion.
    For this final rule, we expect approximately 71 percent of LTCH 
cases 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 2.7 
percent (or approximately $91 million). This estimated increase in 
LTCH PPS payments for LTCH PPS standard Federal payment rate cases 
in FY 2020 is primarily due to the 2.5 percent annual update to the 
LTCH PPS standard Federal payment rate for FY 2020 and the projected 
0.2 percent increase in high cost outlier payments discussed in 
section V.D.3.b.(3). of the Addendum to this final rule.
    Based on the 384 LTCHs that were represented in the FY 2018 LTCH 
cases that were used for the analyses in this final rule presented 
in this Appendix, we estimate that aggregate FY 2019 LTCH PPS 
payments will be approximately $4.271 billion, as compared to 
estimated aggregate FY 2020 LTCH PPS payments of approximately 
$4.314 billion, resulting in an estimated overall increase in LTCH 
PPS payments of approximately $43 million. We note that the 
estimated $43 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 policies in this 
final rule.
    The LTCH PPS standard Federal payment rate for FY 2019 is 
$41,558.68. For FY 2020, we are establishing an LTCH PPS standard 
Federal payment rate of $42,677.64 which reflects the 2.5 percent 
annual update to the LTCH PPS standard Federal payment rate, the 
incremental change in the one-time budget neutrality adjustment 
factor of 0.999858 for eliminating the 25-percent threshold policy 
in FY 2020 as discussed in section VII.D. of the preamble of this 
final rule, and the area wage budget neutrality factor of 1.0020203 
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 establishing an LTCH PPS standard 
Federal payment rate of $41,844.90. This LTCH PPS standard Federal 
payment rate reflects the 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 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 annual update of 2.5 percent to the LTCH PPS standard Federal 
payment rate is projected to result in an increase of 2.4 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 annual update to the LTCH PPS standard Federal 
payment rate for FY 2020, the estimated increase of 2.4 percent 
shown in Column 6 of Table IV also includes estimated payments for 
short-stay outlier (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 LTCH PPS standard Federal payment rate to LTCH PPS standard 
Federal payment rate cases is somewhat less than the 2.5 percent 
annual update for FY 2020.
    For FY 2020, we are updating the wage index values based on the 
most recent available data (data from cost reporting periods 
beginning during FY 2016 which is the same data used for the FY 2020 
acute care hospital IPPS), and we are continuing to use labor market 
areas based on the CBSA delineations (as discussed in section V.B. 
of the Addendum to this final rule). In addition, the labor-related 
share will be 66.3 percent under the LTCH PPS for FY 2020, based on 
the most recent available data (IGI's second quarter 2019 forecast) 
on the relative importance of the labor-related share of operating 
and capital costs of the 2013-based LTCH market basket. We also are 
applying an area wage level budget neutrality factor of 1.0020203 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 will increase from FY 2019 
to FY 2020. Based on the FY 2018 LTCH cases that were used for the 
analyses in this final 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) will result in estimated high 
cost outlier payments for LTCH PPS standard Federal payment rate 
cases in FY 2019 that are projected to fall slightly below the 7.975 
percent target. Specifically, we currently estimate that high cost 
outlier payments for LTCH PPS standard Federal payment rate cases 
will be approximately 7.74 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 will be 7.975 percent of 
estimated total LTCH PPS standard Federal payment rate payments in 
FY 2020, this will result in an estimated increase in high cost 
outlier payments of approximately 0.2 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 5.5 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 payment rate and 
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 final rule, based on the 
most recent available data, we believe that the provisions of this 
final 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 payment amounts will result in appropriate 
Medicare payments that are consistent with the statute.

[[Page 42689]]

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 2.7 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 Payment Adjustment for LTCH Discharges That Do Not Meet 
the Applicable Discharge Payment Percentage

    In section VII.C. of the preamble of this final rule, we discuss 
our implementation of 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 continuing 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 providing that an LTCH will 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 providing that the payment adjustment for an LTCH will 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 
establishing a probationary-cure period that will 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 this probationary-cure 
period, an LTCH will 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 previously, under our finalized policy, an LTCH will be 
first subject to a potential payment adjustment based on the 
hospital's discharge payment percentage for its FY 2020 cost 
reporting period. Hospitals will 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 final rule, we estimate that, for FY 2022, 
our finalized policy will reduce Medicare spending under the LTCH 
PPS by approximately $50 million. While we expect that there will be 
less than the maximum estimated savings due to the 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 2018 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 will result 
in a payment decrease of approximately $19,700 for LTCH PPS standard 
Federal payment rate discharges and an estimated payment increase of 
approximately $1,600 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 2018 
claims data. We expect that an LTCH whose discharge payment 
percentage is at least 40 percent based on FY 2018 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 will be 2,903 
LTCH PPS standard Federal payment rate discharges and 7,275 site 
neutral payment rate discharges. The FY 2018 estimate is inflated to 
FY 2022, resulting in estimated savings of $50 million (comprised of 
approximately $60 million in savings from LTCH PPS standard Federal 
payment rate discharges and approximately $10 million in costs from 
site neutral payment rate discharges).

4. Anticipated Effects of 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 
$43 million. This estimated increase in payments reflects the 
projected increase in payments to LTCH PPS standard Federal payment 
rate cases of approximately $91 million and the projected decrease 
in payments to site neutral payment rate cases of approximately $49 
million under the dual rate LTCH PPS payment rate structure required 
by the statute beginning in FY 2016. (We note that these 
calculations are based on unrounded numbers and thus may not sum as 
expected.)
    As discussed in section V.D. of the Addendum to this final 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 final 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 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 changes to LTCH PPS payments 
for LTCH PPS standard Federal payment rate cases. Therefore, Table 
IV only reflects 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 LTCH PPS payments for LTCH PPS standard Federal 
payment rate cases. In the following section, we present our 
provider impact analysis for the 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 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

[[Page 42690]]

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 changes to the LTCH PPS payments 
for LTCH PPS standard Federal payment rate cases presented in this 
final 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 rates, factors, and the policies in this FY 2020 IPPS/LTCH 
PPS final rule (as discussed in section VII. of the preamble of this 
final rule and section V. of the Addendum to this final rule). As 
discussed elsewhere in this final 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 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 policies on payments for LTCH PPS 
standard Federal payment rate cases, we simulated FY 2019 and final 
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 FY 2020 LTCH PPS 
standard Federal payment rate, we used the FY 2020 standard Federal 
payment rate of $42,677.64 (or $41,844.90 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 FY 2020 LTCH PPS 
payments, we used the FY 2020 LTCH PPS labor-related share (66.3 
percent), the FY 2020 wage index values from Tables 12A and 12B 
listed in section VI. of the Addendum to this final rule (which are 
available via the internet on the CMS website), the FY 2020 fixed-
loss amount for LTCH PPS standard Federal payment rate cases of 
$26,778 (as discussed in section V.D.3. of the Addendum to this 
final rule), and the FY 2020 COLA factors (shown in the table in 
section V.C. of the Addendum to this final rule) to adjust the FY 
2020 nonlabor-related share (33.7 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 2.6 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 5.5 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 payment rates and policy changes applicable to 
LTCH PPS standard Federal payment rate cases presented in this final 
rule. Table IV illustrates the estimated aggregate impact of the 
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 annual update to the standard Federal rate (as 
discussed in section V.A.2. of the Addendum to this final 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 changes to the area 
wage level adjustment (that is, the wage indexes and the labor-
related share), including the application of the area wage level 
budget neutrality factor (as discussed in section V.B. of the 
Addendum to this final 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 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 final rule, we have prepared the following 
summary of the impact (as shown in Table IV) of the LTCH PPS payment 
rate and proposed policy changes for LTCH PPS standard Federal 
payment rate cases presented in this final 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 2.7 
percent, on average,

[[Page 42693]]

for all LTCHs from FY 2019 to FY 2020 as a result of the payment 
rate and policy changes applicable to LTCH PPS standard Federal 
payment rate cases presented in this final rule. This estimated 2.7 
percent increase in LTCH PPS payments per discharge was determined 
by comparing estimated FY 2020 LTCH PPS payments (using the payment 
rates and factors discussed in this final rule) to estimated FY 2019 
LTCH PPS payments for LTCH discharges which will 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 updating the LTCH PPS standard 
Federal payment rate for FY 2020 by 2.5 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 applying the incremental 
change in the one-time budget neutrality adjustment factor of 
0.999858 for the cost of eliminating the 25-percent threshold policy 
in FY 2020 as discussed in section VII.D. of the preamble of this 
final rule. Consistent with Sec.  412.523(d)(4), we also are 
applying an area wage level budget neutrality factor to the FY 2020 
LTCH PPS standard Federal payment rate of 1.0020203, based on the 
best available data at this time, to ensure that any changes to the 
area wage level adjustment (that is, the 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 2.5 percent annual 
update to the LTCH PPS standard Federal payment rate is projected to 
result in approximately a 2.4 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 changes in payments due to the 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 2.5 percent due to the 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 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 2.7 percent. This 2.7 percent increase is constant 
across all rural and urban LTCHs (both large urban and other urban), 
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 46 percent) are 
in LTCHs that began participating in the Medicare program between 
October 1993 and September 2002, and they are projected to 
experience a 2.7 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 3 percent of LTCHs began participating in the 
Medicare program before October 1983, and these LTCHs are projected 
to experience an average percent increase of 2.9 percent in 
estimated payments per discharge for LTCH PPS standard Federal 
payment rate cases from FY 2019 to FY 2020. Approximately 11 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 2.6 
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 2.8 percent increase in payments to LTCH PPS standard Federal 
payment rate cases, while proprietary LTCHs are expected to 
experience an average increase of 2.6 percent in payments to LTCH 
PPS standard Federal payment rate cases. Government owned and 
operated LTCHs, meanwhile, are expected to experience a 3.2 percent 
increase in payments to LTCH PPS standard Federal payment rate cases 
from FY 2019 to FY 2020. These LTCHs are projected to experience a 
somewhat higher percent increase in payments in LTCH PPS standard 
Federal payment rate payments from FY 2019 to FY 2020 due to a 
higher than average increase in payments due to changes in the MS-
LTC-DRGs and wage index.

(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 East South Central and the 
Pacific region are projected to experience the largest increase at 
3.1 percent. The remaining regions are projected to experience an 
increase in the range of 2.5 to 2.7 percent. These regional 
variations are largely due to 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 3.1 percent, and LTCHs with 75-124 beds are 
projected to experience the next largest increase of 2.9 percent. 
This somewhat higher percent increase in payments for these LTCHs is 
due mostly to a higher than average increase in payments due to 
changes in the wage index. LTCHs with 25-49 beds and 50-74 beds are 
both projected to experience an increase of 2.6 percent, while LTCHs 
with 125 or more beds are projected to experience an increase in 
payments of 2.5 percent.

5. Effect on the Medicare Program

    As stated previously, we project that the provisions of this 
final rule will 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 $91 million (or 
approximately 2.7 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 final rule will 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 $49 million 
(or approximately -5.9 percent) for the 384 LTCHs in our database. 
Therefore, we project that the provisions of this final rule will 
result in an increase in estimated aggregate LTCH PPS payments for 
all LTCH cases in FY 2020 relative to FY 2019 of approximately $43 
million (or approximately 1.0 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 final 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 42694]]

K. Effects of Requirements for the Hospital Inpatient Quality 
Reporting (IQR) Program

    In section VIII.A. of the preamble of this final rule, we 
discuss our current and proposed requirements that are being 
finalized 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 final rule, we are: (1) Adopting the Safe Use of 
Opioids--Concurrent Prescribing eCQM beginning with the CY 2021 
reporting period/FY 2023 payment determination with a clarification 
and update; (2) adopting the Hybrid Hospital-Wide Readmission 
Measure with Claims and Electronic Health Record Data (Hybrid HWR 
measure) (NQF #2879) in a stepwise manner, beginning with 2 years of 
voluntary reporting periods which will 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 
will run from July 1, 2023 through June 30, 2024, impacting the FY 
2026 payment determination and subsequent years; (3) removing the 
Claims-Based Hospital-Wide All-Cause Unplanned Readmission Measure 
(NQF #1789) (HWR claims-only measure) beginning with the FY 2026 
payment determination; \932\ (4) extending 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) changing the eCQM reporting and 
submission requirements for the CY 2022 reporting period/FY 2024 
payment determination, such that hospitals will be required to 
report one, self-selected calendar quarter of data for: (a) Three 
self-selected eCQMs; and (b) the Safe Use of Opioids--Concurrent 
Prescribing eCQM, for a total of four eCQMs; (6) continuing to 
require 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) establishing 
reporting and submission requirements for the Hybrid HWR measure. We 
are not finalizing our proposal to adopt the Hospital Harm--Opioid-
Related Adverse Events eCQM.
---------------------------------------------------------------------------

    \932\ As discussed in section X.B.3.d. of the preamble of this 
final rule, 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 the HWR claims-only 
measure will decrease our previously finalized burden estimates. We 
believe there are no other changes in costs for hospitals associated 
with removal of this measure.
---------------------------------------------------------------------------

    Regarding the newly finalized Hybrid HWR measure, we estimate a 
total information collection burden increase of 2,211 hours and a 
total cost increase related to information collection of 
approximately $83,266 (due to this finalized 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 final rule (information collection requirements) 
for a detailed discussion of the calculations estimating the changes 
to the information collection burden for submitting data to the 
Hospital IQR Program. We acknowledge that there may be costs beyond 
information collection burden associated with EHR based quality 
measures. Due to differences in the build of EHRs deployed in 
hospitals, the cost involved is not quantifiable as it will vary 
across hospitals.
    With regard to our finalized policy to add a new eCQM 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 final rule because we are 
also adopting as final our proposed eCQM reporting requirements such 
that the total number of eCQMs that will be reported and the total 
quarters of data will remain unchanged from previously finalized 
requirements, we expect some investment in EHR system updates. Due 
to differences in the build of EHRs deployed in hospitals, the cost 
involved is not quantifiable as it will vary across hospitals.
    We are also requiring 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 final 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. 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, 
however, an estimated cost impact of the policy is not quantifiable 
as it will vary by CEHRT and hospital. For certifying the new eCQM 
in the eCQM measure set specifically, we expect some costs for 
hospitals and EHR vendors in certifying the new eCQM so that 
hospitals have the option to report it.
    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 Requirements for the PPS-Exempt Cancer Hospital 
Quality Reporting (PCHQR) Program

    In section VIII.B. of the preamble of this final rule, we 
discuss our finalized 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 final rule, we 
are finalizing the removal of 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 final rule, we are 
finalizing the adoption of 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 final 
rule, we anticipate that the 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 removal of this measure.
    We do not anticipate any change in burden on the PCHs associated 
with our 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 will be any associated 
change in burden resulting from this policy.

M. Effects of 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 fails to 
comply 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 final 
rule (information collection requirements) for a detailed discussion 
of the burden associated with the new requirements for the LTCH QRP.

N. Effects of Requirements Regarding the Promoting Interoperability 
Program

    In section VIII.D. of the preamble of this final rule, we 
discuss our current and finalized proposed requirements for eligible 
hospitals and CAHs participating in the Medicare and Medicaid 
Promoting Interoperability Programs.
    In this final rule, as we proposed, we are making the following 
changes to the Medicare Promoting Interoperability Program: (1) 
Eliminating the requirement

[[Page 42695]]

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) 
establishing 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) requiring 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) revising 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, making it an optional measure worth five 
bonus points in CY 2020, removing the exclusions associated with 
this measure in CY 2020, and clearly stating our intended policy 
that the measure is worth a full 5 bonus points in CY 2019 and CY 
2020; (5) changing the maximum points available for the e-
Prescribing measure to 10 points beginning in CY 2020, to coincide 
with our finalization of the proposed changes to the Query of PDMP 
measure; (6) removing 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) revising 
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 amending 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 final rule, we are making a number of policy changes with 
respect to the reporting of CQM data, including adding one opioid-
related measures beginning with the reporting period in CY 2021 and 
establishing 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 finalized 
proposals are continuations of current policies and therefore we do 
not believe that there will be a change in burden for CY 2020.
    As explained in section X.B.9. of the preamble of this final 
rule, we estimate for CY 2020 a total information collection burden 
decrease of 2,200 hours, associated with our revision of 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 
Interoperability Program, and a total cost decrease of $130,102.50 
related to information collection burden cost estimates due to this 
finalized proposal and our updated hourly wage plus benefits 
estimate.

O. Alternatives Considered

    This final rule contains a range of policies. It also provides 
descriptions of the statutory provisions that are addressed, 
identifies the finalized 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 finalized policies 
discussed in section III.N.2.b of the preamble of this final rule to 
address the budget neutrality for the increase in the wage index for 
hospitals with wage index values below the 25th percentile wage 
index value (that is, low wage index hospitals).
    As described more fully in section III.N.2.b. of the preamble of 
this final rule, rather than reducing the wage index of hospitals 
with wage index values above the 75th percentile wage index value 
(that is, high wage index hospitals) as we proposed in the FY 2020 
IPPS/LTCH PPS proposed rule (summarized in section III.N.2.b of this 
final rule), we are maintaining budget neutrality for the increase 
in the wage index for low wage index hospitals by reducing the FY 
2020 standardized amount, which is one of the alternatives we 
considered in the proposed rule. We also considered the suggestion 
by many commenters that the policy should not be implemented in a 
budget neutral manner at all. However, as discussed in section 
III.N.2.b of the preamble of this final rule, given that budget 
neutrality is required under section 1886(d)(3)(E) of the Act, given 
that even if it were not required we think it would be inappropriate 
to use the wage index to increase or decrease overall IPPS spending, 
and given that we wish to consider further the policy arguments 
raised against our proposed budget neutrality on high wage 
hospitals, we are finalizing a budget neutrality adjustment for the 
increase in the wage index values for low wage hospitals that will 
be applied to the national standardized amount.
    As discussed in section III.N.2.f of the preamble of this final 
rule, we received very few public comments supporting the other two 
alternatives to our wage index disparities proposals discussed in 
the proposed rule, namely mirroring our approach of raising the wage 
index for low wage index hospitals by reducing the wage index values 
for high wage index hospitals (that is, reducing the wage index for 
high wage index hospitals by half the difference between the 
otherwise applicable final wage index value for these hospitals and 
the 75th percentile wage index value), or creating a national rural 
wage index area. Refer to section III.N.2.f of the preamble of this 
final rule for further discussion of the alternatives considered for 
our wage index disparities proposals.

2. New Technology Add-On Payments

    As discussed in section II.H.8. of the preamble of this final 
rule, in situations where a new medical device is part of the 
Breakthrough Devices Program and has received FDA marketing 
authorization, we proposed an alternative inpatient new technology 
add-on payment pathway to facilitate access to this technology for 
Medicare beneficiaries. We also considered in the proposed rule 
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, as discussed in the proposed rule, 
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. We 
stated that making this policy applicable to drugs would further 
incentivize 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 
(available at https://www.hhs.gov/sites/default/files/AmericanPatientsFirst.pdf), 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. We 
stated that while we continue to work on these initiatives for drug 
affordability, we continue to believe that it is appropriate to 
distinguish between drugs and devices in our consideration of a 
proposed policy change for transformative new technologies.
    In this final rule, are finalizing an alternative inpatient new 
technology add-on payment pathway for new medical devices that are 
part of the Breakthrough Devices Program and have received FDA 
marketing authorization, beginning with FY 2021 new technology 
applications. As also discussed in section II.H.8. of the preamble 
of this final rule, after consideration of specific concerns and 
consistent with the Administration's commitment to address issues 
related to antimicrobial resistance, we extended the proposed 
alternative new technology add-on payment pathway to a product that 
is designated by the FDA as a QIDP in order to secure access to 
antibiotics, and improve health outcomes for Medicare beneficiaries 
in a manner that is as expeditious as possible. We further state 
that we continue to believe that it is appropriate to distinguish 
between drugs and devices in our consideration of a policy change 
for transformative new technologies while we continue to work on 
these initiatives for drug affordability for the reasons stated in 
the proposed rule.

3. Uncompensated Care Payments

    Another policy area where an alternative was considered in the 
proposed rule 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 final rule. We 
proposed to use Worksheet S-10 data from the FY 2015 cost reports in 
the calculation of Factor 3 for FY 2020. Although we proposed to use 
Worksheet S-10 data from the FY 2015 cost reports, we discussed an 
alternative in the proposed rule under which we would use a single 
year of uncompensated care data from the FY 2017 cost reports, 
instead of the FY 2015 cost reports, to calculate Factor 3 for FY 
2020. We sought comment on whether, due to the changes in the cost 
reporting instructions, we

[[Page 42696]]

should use uncompensated care data from the FY 2017 cost reports 
instead of the FY 2015 data. As discussed in section IV.F.4.c. of 
this final rule, after considering the comments received, we agree 
with the commenters who indicated that our proposed approach of 
using the FY 2015 data is more appropriate. The FY 2015 data has 
been through an auditing process, while the FY 2017 data has not.

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 final rule. We proposed to 
implement a special probationary reinstatement process. Although we 
proposed to use a special probationary reinstatement process, we 
believe a reinstatement process that would not use a probationary 
period (as discussed in more detail in section VII.C. of the 
preamble of the proposed rule and this final rule) would satisfy the 
statutory requirement without further modification. But, as 
discussed in more detail in section VII.C. of the preamble of this 
final rule, in developing our proposals for the a special 
probationary reinstatement process, we were 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 solicited public 
comments as to whether we should have a special reinstatement 
process and, if so, whether it should be probationary. A summary of 
those comments and our responses, along with our final policy, are 
discussed in section VII.C. of the preamble of this final rule.

5. eCQM

    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19497), 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, we proposed that 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 as their 
fourth eCQM. We also considered in the proposed rule an alternative 
whereby hospitals would have the option to select one of the two 
proposed opioid-related eCQMs, the Safe Use of Opioids eCQM or 
Opioid-Related Adverse Events eCQM, as their fourth required eCQM. 
We stated, however, that 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 the proposed rule and this 
final 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 stated that 
we did not expect these alternatives to affect the reporting burden 
on hospitals. We considered this alternative and sought public 
comment on it.
    As discussed in sections VIII.A.5.a.(1) and (2) of the preamble 
of this final rule, while we are finalizing our proposal to adopt 
the Safe Use of Opioids--Concurrent Prescribing eCQM beginning with 
the CY 2021 reporting period/FY 2023 payment determination with a 
clarification and update, we are not finalizing our proposal to 
adopt the Hospital Harm--Opioid-Related Adverse Events eCQM. As 
discussed above in section I.K. of Appendix A of this final rule, we 
do not expect the adoption of the Safe Use of Opioids--Concurrent 
Prescribing eCQM or any of the alternatives considered to affect the 
reporting burden on hospitals.

6. MS-DRG Severity Level Designations

    As discussed in section II.F.14.c. of the preamble of this final 
rule, while we are continuing to examine the implementation of 
broader comprehensive changes to the CC/MCC designations, we believe 
it is appropriate to finalize the change in the severity level 
designations from non-CC to CC for the ICD-10-CM diagnosis codes 
specifying antimicrobial drug resistance. Commenters expressed 
significant concerns related to the public health crisis represented 
by antimicrobial resistance and urged CMS to also apply the change 
in the severity level designation from non-CC to CC to the other ICD 
10-CM diagnosis codes specifying antimicrobial drug resistance, in 
addition the codes included in our proposal. Addressing the concerns 
related to the public health crisis that antimicrobial resistance 
represents is consistent with the Administration's key priorities, 
and for the reasons discussed in section II.F.14.c. of the preamble 
of this final rule, we are finalizing a change to the severity level 
designation for all of the codes in category Z16- (Resistance to 
antimicrobial drugs) from a non-CC to a CC designation.
    In expressing their concerns regarding antimicrobial resistance, 
we also received several comments urging CMS to consider a separate 
payment mechanism that removes certain antimicrobials from the MS-
DRG, where those antimicrobial resistant drugs would be ``carved 
out'' from the MS-DRG and paid separately at 100 percent. Commenters 
also suggested that CMS develop a ``drug resistant modifier'' for 
infection-related MS-DRGs in certain circumstances related to 
antimicrobial resistance. We believe further information is required 
before engaging in broader changes to the severity levels of the MS-
DRGs. As stated in section II.F.14.c. of the preamble of this final 
rule, we will be gathering additional public input on these issues 
more broadly, and welcome feedback specifically on policy reforms 
aimed at recalibrating severity levels for antimicrobial resistance 
within the MS-DRGs.

P. Reducing Regulation and Controlling Regulatory Costs

    Executive Order 13771, titled Reducing Regulation and 
Controlling Regulatory Costs, was issued on January 30, 2017. This 
final rule 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 FY 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 final rule, and 
estimate that the impact of these 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 final rule, 
and estimate that the impact of these 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 final rule, and estimate that the 
impact of these changes is an increase in costs of approximately 
$5,675.29 per LTCH annually or approximately $2,355,243 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 
finalized policies in this final rule.
    Also, as noted in section I.R. of this Appendix, the regulatory 
review cost for this final rule is $1,905,475.
[GRAPHIC] [TIFF OMITTED] TR16AU19.240


[[Page 42697]]



Q. Overall Conclusion

1. Acute Care Hospitals

    Acute care hospitals are estimated to experience an increase of 
approximately $3.8 billion in FY 2020, taking into account 
operating, capital, new technology, and low volume hospital payments 
as modeled for this final rule. Approximately $3.5 billion of this 
estimated increase is due to the changes in operating payments, 
including $0.1 billion in uncompensated care payments (discussed in 
sections I.G. and I.H. of this Appendix), approximately $0.1 billion 
is due to the change in capital payments (discussed in section I.I. 
of this Appendix), approximately $0.2 billion is due to the change 
in new technology add-on payments (discussed in section I.H. of this 
Appendix), and approximately $-7 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 MS-DRG and wage index changes, and for the wage 
index reclassifications under the MGCRB.
    We estimate that hospitals will experience a 1.4 percent 
increase in capital payments per case, as shown in Table III. of 
section I.I. of this Appendix. We project that there will be a $0.1 
billion 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 final 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 rates, factors, and policies presented in this 
final 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 $43 million relative to FY 2019 as a 
result of the payment rates and factors presented in this final 
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 review. In the FY 2020 
IPPS/LTCH PPS proposed rule, 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 will be the number of 
reviewers of this 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 rule. We welcomed any public 
comments on the approach in estimating the number of entities that 
will review this final rule. We did not receive any public comments 
specific to our solicitation.
    We also recognize that different types of entities are in many 
cases affected by mutually exclusive sections of the 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 rule. 
In the proposed rule, we welcomed public comments on this 
assumption. We did not receive any public comments specific to our 
solicitation.
    We have used the number of timely pieces of correspondence on 
the FY 2020 proposed rule as our estimate for the number of 
reviewers of the 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 
final 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 
21.40 hours for the staff to review half of this final rule. For 
each IPPS hospital or LTCH that reviews this final rule, the 
estimated cost is $2,297 (21.40 hours x $107.38). Therefore, we 
estimate that the total cost of reviewing this final rule is 
$8,972,082 ($2,297 x 3,906 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 final 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 changes to the 
IPPS presented in this final 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 policies in this final rule are 
estimated at $3.8 billion.
[GRAPHIC] [TIFF OMITTED] TR16AU19.241

B. LTCHs

    As discussed in section I.J. of this Appendix, the impact 
analysis of the payment rates and factors presented in this final 
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 $43 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 final 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 payment rates and 
factors and other provisions presented in this final 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., the net cost to the Federal Government 
associated with the final policies for LTCHs in this final rule are 
estimated at $43 million.

[[Page 42698]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.242

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 final 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 final rule are impacts on small 
entities. For example, we refer readers to ``Table I--Impact 
Analysis of 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 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 final rule constitutes our 
regulatory flexibility analysis. This final rule contains a range of 
policies. It provides descriptions of the statutory provisions that 
are addressed, identifies the 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 final rule will result in an 
estimated $3.9 billion increase in FY 2020 payments to IPPS 
hospitals, primarily driven by the applicable percentage increase to 
the IPPS rates in conjunction with other payment changes including 
uncompensated care payments, capital payments, and new technology 
add-on payments, as discussed in section I.B. of this Appendix. As 
discussed in section I.J. of this Appendix, the impact analysis of 
the payment rates and factors presented in this final 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 $43 million. We solicited 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 are 
presented throughout this final rule.

IV. Impact on Small Rural Hospitals

    Section 1102(b) of the 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 3.4 
percent and 2.8 percent, respectively. We refer readers to Table I. 
in section I.G. of this Appendix for additional information on the 
quantitative effects of the 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 2019, that threshold level is approximately $154 
million. This final rule will 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 final rule will not mandate any requirement for Indian 
tribal governments, and it will 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 final 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

[[Page 42699]]

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. FY 2020 Inpatient Hospital Update

    As discussed in section IV.B. of the preamble to this final 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 the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19401), in 
accordance with section 1886(b)(3)(B) of the Act, we proposed to base 
the proposed FY 2020 market basket update used to determine the 
applicable percentage 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 was 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 the FY 2020 IPPS/LTCH PPS proposed rule, based on 
IGI's fourth quarter 2018 forecast, we proposed an MFP adjustment of 
0.5 percent for FY 2020. We also proposed that if more recent data 
subsequently became available, we would use such data, if appropriate, 
to determine the FY 2020 market basket update and MFP adjustment for 
the final rule. Based on the most recent data available for this FY 
2020 IPPS/LTCH PPS final rule, in accordance with section 1886(b)(3)(B) 
of the Act, we are establishing the FY 2020 market basket update used 
to determine the applicable percentage increase for the IPPS based on 
IGI's second quarter 2019 forecast of the 2014-based IPPS market basket 
rate-of-increase with historical data through first quarter 2019, which 
is estimated to be 3.0 percent. Based on the most recent data available 
for this final rule, we are establishing an MFP adjustment of 0.4 
percent.
    In the FY 2020 IPPS/LTCH PPS proposed rule, 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 
presented four possible applicable percentage increases that could be 
applied to the standardized amount.
    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 final rule, we are establishing the applicable 
percentages increase for the FY 2020 updates based on IGI's second 
quarter 2019 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 and is a meaningful EHR user under section 1886(b)(3)(B)(ix) of 
the Act, as shown in the table in this section.

[[Page 42700]]

[GRAPHIC] [TIFF OMITTED] TR16AU19.243

B. 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 establishing the same four possible 
applicable percentage increases in the previous table for the hospital-
specific rate applicable to SCHs and MDHs.

C. 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 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 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 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 final rule. Accordingly, for FY 2020, 
we are establishing an applicable percentage increase of 2.6 percent to 
the standardized amount for hospitals located in Puerto Rico.

D. 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 final 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 final rule, the update to the target 
amount for extended neoplastic disease care hospitals for FY 2020 is 
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,

[[Page 42701]]

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 is the FY 2020 
percentage increase in the 2014-based IPPS operating market basket. For 
this final rule, the current estimate of the IPPS operating market 
basket percentage increase for FY 2020 is 3.0 percent.

E. 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 final rule, we 
are establishing an update to the LTCH PPS standard Federal payment 
rate for FY 2020 of 2.5 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 reducing 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 
establishing an update factor of 1.025 in determining the LTCH PPS 
standard Federal rate for FY 2020. For LTCHs that fail to submit 
quality data for FY 2020, we are establishing an annual update to the 
LTCH PPS standard Federal rate of 0.5 percent (that is, the annual 
update for FY 2020 of 2.5 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 an update factor of 
1.005 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 
final rule, the update to the LTCH PPS standard Federal payment rate of 
2.5 percent for FY 2020 does not reflect any 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 in this section. As 
previously mentioned, 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 3.0 
percent.
    For FY 2020, consistent with policy set forth in section VII. of 
the preamble of this final rule, for LTCHs that submit quality data, we 
are recommending an update of 2.5 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 0.5 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 2.6 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 establishing an applicable percentage increase for FY 2020 of 
2.6 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 update to the capital rate is 
discussed in section III. of the Addendum to this final rule.

[FR Doc. 2019-16762 Filed 8-2-19; 4:15 pm]
 BILLING CODE 4120-01-P