[Federal Register Volume 86, Number 71 (Thursday, April 15, 2021)]
[Proposed Rules]
[Pages 19954-20022]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2021-07556]



[[Page 19953]]

Vol. 86

Thursday,

No. 71

April 15, 2021

Part II





Department of Health and Human Services





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Centers for Medicare & Medicaid Services





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42 CFR Parts 411, 413 and 489





Medicare Program; Prospective Payment System and Consolidated Billing 
for Skilled Nursing Facilities; Updates to the Quality Reporting 
Program and Value-Based Purchasing Program for Federal Fiscal Year 
2022; Proposed Rule

  Federal Register / Vol. 86 , No. 71 / Thursday, April 15, 2021 / 
Proposed Rules  

[[Page 19954]]



DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Medicare & Medicaid Services

42 CFR Parts 411, 413, and 489

[CMS-1746-P]
RIN 0938-AU36


Medicare Program; Prospective Payment System and Consolidated 
Billing for Skilled Nursing Facilities; Updates to the Quality 
Reporting Program and Value-Based Purchasing Program for Federal Fiscal 
Year 2022

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

ACTION: Proposed rule.

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SUMMARY: This proposed rule would update the payment rates used under 
the prospective payment system (PPS) for skilled nursing facilities 
(SNFs) for fiscal year (FY) 2022. In addition, the proposed rule 
includes a proposed forecast error adjustment for FY 2022, proposes 
updates to the diagnosis code mappings used under the Patient Driven 
Payment Model (PDPM), proposes to rebase and revise the SNF market 
basket, proposes to implement a recently-enacted SNF consolidated 
billing exclusion along with the required proportional reduction in the 
SNF PPS base rates, and includes a discussion of a methodology to 
recalibrate the PDPM parity adjustment. In addition, the proposed rule 
includes proposals for the SNF Quality Reporting Program (QRP) and the 
SNF Value-Based Purchasing (VBP) Program, including a proposal to 
suppress the use of the SNF readmission measure for scoring and payment 
adjustment purposes in the FY 2022 SNF VBP program because we have 
determined that circumstances caused by the public health emergency for 
COVID-19 have significantly affected the validity and reliability of 
the measure and resulting performance scores.

DATES: To be assured consideration, comments must be received at one of 
the addresses provided below, no later than 5 p.m. on June 7, 2021.

ADDRESSES: In commenting, please refer to file code CMS-1746-P.
    Comments, including mass comment submissions, must be submitted in 
one of the following three ways (please choose only one of the ways 
listed):
    1. Electronically. You may submit electronic comments on this 
regulation to http://www.regulations.gov. Follow the ``Submit a 
comment'' instructions.
    2. By regular mail. You may mail written comments to the following 
address ONLY: Centers for Medicare & Medicaid Services, Department of 
Health and Human Services, Attention: CMS-1746-P, P.O. Box 8016, 
Baltimore, MD 21244-8016.
    Please allow sufficient time for mailed comments to be received 
before the close of the comment period.
    3. By express or overnight mail. You may send written comments to 
the following address ONLY: Centers for Medicare & Medicaid Services, 
Department of Health and Human Services, Attention: CMS-1746-P, Mail 
Stop C4-26-05, 7500 Security Boulevard, Baltimore, MD 21244-1850.
    For information on viewing public comments, see the beginning of 
the SUPPLEMENTARY INFORMATION section.

FOR FURTHER INFORMATION CONTACT: 
    Penny Gershman, (410) 786-6643, for information related to SNF PPS 
clinical issues.
    Anthony Hodge, (410) 786-6645, for information related to 
consolidated billing, and payment for SNF-level swing-bed services.
    John Kane, (410) 786-0557, for information related to the 
development of the payment rates and case-mix indexes, and general 
information.
    Kia Burwell, (410) 786-7816, for information related to the wage 
index.
    Heidi Magladry, (410) 786-6034, for information related to the 
skilled nursing facility quality reporting program.
    Lang Le, (410) 786-5693, for information related to the skilled 
nursing facility value-based purchasing program.

SUPPLEMENTARY INFORMATION:
    Inspection of Public Comments: All comments received before the 
close of the comment period are available for viewing by the public, 
including any personally identifiable or confidential business 
information that is included in a comment. We post all comments 
received before the close of the comment period on the following 
website as soon as possible after they have been received: http://www.regulations.gov. Follow the search instructions on that website to 
view public comments. CMS will not post on Regulations.gov public 
comments that make threats to individuals or institutions or suggest 
that the individual will take actions to harm the individual. CMS 
continues to encourage individuals not to submit duplicative comments. 
We will post acceptable comments from multiple unique commenters even 
if the content is identical or nearly identical to other comments.

Availability of Certain Tables Exclusively Through the Internet on the 
CMS Website

    As discussed in the FY 2014 SNF PPS final rule (78 FR 47936), 
tables setting forth the Wage Index for Urban Areas Based on CBSA Labor 
Market Areas and the Wage Index Based on CBSA Labor Market Areas for 
Rural Areas are no longer published in the Federal Register. Instead, 
these tables are available exclusively through the internet on the CMS 
website. The wage index tables for this proposed rule can be accessed 
on the SNF PPS Wage Index home page, at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html.
    Readers who experience any problems accessing any of these online 
SNF PPS wage index tables should contact Kia Burwell at (410) 786-7816.
    To assist readers in referencing sections contained in this 
document, we are providing the following Table of Contents.

Table of Contents

I. Executive Summary
    A. Purpose
    B. Summary of Major Provisions
    C. Summary of Cost and Benefits
    D. Advancing Health Information Exchange
II. Background on SNF PPS
    A. Statutory Basis and Scope
    B. Initial Transition for the SNF PPS
    C. Required Annual Rate Updates
III. Proposed SNF PPS Rate Setting Methodology and FY 2022 Update
    A. Federal Base Rates
    B. SNF Market Basket Update
    C. Case-Mix Adjustment
    D. Wage Index Adjustment
    E. SNF Value-Based Purchasing Program
    F. Adjusted Rate Computation Example
IV. Additional Aspects of the SNF PPS
    A. SNF Level of Care--Administrative Presumption
    B. Consolidated Billing
    C. Payment for SNF-Level Swing-Bed Services
    D. Revisions to the Regulation Text
V. Other SNF PPS Issues
    A. Proposed Changes to SNF PPS Wage Index
    B. Technical Updates to PDPM ICD-10 Mappings
    C. Recalibrating the PDPM Parity Adjustment
VI. Skilled Nursing Facility (SNF) Quality Reporting Program (QRP)
VII. Skilled Nursing Facility Value-Based Purchasing Program (SNF 
VBP)
VIII. Collection of Information Requirements
IX. Response to Comments
X. Economic Analyses
    A. Regulatory Impact Analysis
    B. Regulatory Flexibility Act Analysis
    C. Unfunded Mandates Reform Act Analysis
    D. Federalism Analysis
    E. Reducing Regulation and Controlling Regulatory Costs

[[Page 19955]]

    F. Congressional Review Act
    G. Regulatory Review Costs

I. Executive Summary

A. Purpose

    This proposed rule would update the SNF prospective payment rates 
for fiscal year (FY) 2022 as required under section 1888(e)(4)(E) of 
the Social Security Act (the Act). It also responds to section 
1888(e)(4)(H) of the Act, which requires the Secretary to provide for 
publication of certain specified information relating to the payment 
update (see section II.C. of this proposed rule) in the Federal 
Register, before the August 1 that precedes the start of each FY. As 
discussed in section V.A. of this proposed rule, it would also rebase 
and revise the SNF market basket index, including updating the base 
year from 2014 to 2018. As discussed in section IV.D. of this proposed 
rule, it would also make revisions in the regulation text to exclude 
from SNF consolidated billing certain blood clotting factors and items 
and services related to the furnishing of such factors effective for 
items and services furnished on or after October 1, 2021, as required 
by the Consolidated Appropriations Act, 2021 (Pub. L. 116-260, enacted 
December 27, 2020), as well as certain other conforming revisions. In 
addition, as required under section 1888(e)(4)(G)(iii) of the Act, as 
added by section 103(b) of the BBRA 1999, we propose to provide for a 
proportional reduction in the Part A SNF PPS base rates to account for 
this exclusion, as described in section III.B.6. of this proposed rule. 
We also propose to make changes to the code mappings used under the SNF 
PPS for classifying patients into case-mix groups. Additionally, this 
proposed rule includes a proposed forecast error adjustment for FY 
2022. This proposed rule also includes a discussion of a methodology to 
recalibrate the PDPM parity adjustment. Finally, this proposed rule 
would also update requirements for the Skilled Nursing Facility Quality 
Reporting Program (SNF QRP) and the Skilled Nursing Facility Value-
Based Purchasing Program (SNF VBP), including a proposal to suppress 
the use of the SNF readmission measure for scoring and payment 
adjustment purposes in the FY 2022 SNF VBP program because we have 
determined that circumstances caused by the public health emergency for 
COVID-19 have significantly affected the validity and reliability of 
the measure and resulting performance scores.

B. Summary of Major Provisions

    In accordance with sections 1888(e)(4)(E)(ii)(IV) and (e)(5) of the 
Act, the Federal rates in this proposed rule would reflect an update to 
the rates that we published in the SNF PPS final rule for FY 2021 (85 
FR47594, August 5, 2020). We also propose to rebase and revise the SNF 
market basket index, including updating the base year from 2014 to 
2018. This proposed rule proposes revisions to the regulation text to 
exclude from SNF consolidated billing certain blood clotting factors 
and items and services related to the furnishing of such factors 
effective for items and services furnished on or after October 1, 2021, 
as required by the Consolidated Appropriations Act, 2021, as well as 
certain conforming revisions. We also propose to make a required 
reduction in the SNF PPS base rates to account for this new exclusion. 
This proposed rule also proposes revisions to the International 
Classification of Diseases, Version 10 (ICD-10) code mappings used 
under PDPM to classify patients into case-mix groups. Additionally, 
this proposed rule includes a proposed forecast error adjustment for FY 
2022. This proposed rule also includes a discussion of a methodology to 
recalibrate the PDPM parity adjustment, used to implement PDPM in a 
budget neutral manner.
    This proposed rule proposes to update requirements for the SNF QRP, 
including the proposal of two new quality measures beginning with the 
FY 2023 SNF QRP: The SNF Healthcare Associated Infections (HAI) 
Requiring Hospitalization measure; and the COVID-19 Vaccination 
Coverage among Healthcare Personnel (HCP) measure. We are proposing 
that SNFs use the Centers for Disease Control and Prevention (CDC)/
National Healthcare Safety Network (NHSN) as the method of data 
submission for the proposed COVID-19 Vaccination Coverage among 
Healthcare Personnel (HCP) measure. We are also proposing to modify the 
denominator for the Transfer of Health Information to the Patient--Post 
Acute Care (PAC) Measure. We are proposing a revision to the number of 
quarters used for publicly reporting certain SNF QRP measures due to 
the public health emergency (PHE). Finally, we are seeking comment on 
the use of Health Level Seven International (HL7[supreg]) Fast 
Healthcare Interoperability Resources[supreg] (FHIR) in quality 
programs, specifically the SNF QRP, and on our continued efforts to 
close the health equity gap.
    Additionally, we are proposing several updates for the SNF VBP 
Program including a proposal to suppress the Skilled Nursing Facility 
30-Day All-Cause Readmission Measure (SNFRM) for the FY 2022 SNF VBP 
Program Year and other proposals for scoring and adjusting payments to 
SNFs for that program year if the SNFRM is suppressed. We are also 
proposing to update the Phase One Review and Corrections policy to 
implement a claims ``snapshot'' policy which would align the review and 
corrections policy for the SNF VBP Program with the review and 
corrections policy we use in other value-based purchasing programs and 
to codify the proposed policy at Sec.  413.338(e)(1) of our 
regulations. We are further proposing to make a technical update to the 
instructions for a SNF to request an extraordinary circumstance 
exception and to codify that update at Sec.  413.338(d)(4)(ii) of our 
regulations. Finally, we are seeking comments on measures and measure 
concepts we are considering for an expanded SNF VBP Program measure 
set.

C. Summary of Cost and Benefits

                       Table 1--Cost and Benefits
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    Provision  description               Total transfers/costs
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Proposed FY 2022 SNF PPS       The overall economic impact of this
 payment rate update.           proposed rule is an estimated increase
                                of $444 million in aggregate payments to
                                SNFs during FY 2022.
Proposed FY 2022 SNF QRP       The overall economic impact of this
 changes.                       proposed rule is an estimated increase
                                in cost to SNFs of $6.63 million.
Proposed FY 2022 SNF VBP       The overall economic impact of the SNF
 changes.                       VBP Program is an estimated reduction of
                                $191.64 million in aggregate payments to
                                SNFs during FY 2022.
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D. 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 and patient access 
to their health information.
    To further interoperability in post-acute care settings, CMS and 
the Office of the National Coordinator for Health Information 
Technology (ONC) participate in the Post-Acute Care Interoperability 
Workgroup (PACIO) (https://pacioproject.org/) to facilitate 
collaboration with industry stakeholders to develop FHIR standards. 
These standards could support the exchange and reuse of patient 
assessment data derived from the minimum data set (MDS), inpatient 
rehabilitation facility patient assessment instrument (IRF-PAI), long 
term care hospital continuity assessment record and evaluation (LCDS), 
outcome and assessment information set (OASIS), and other sources. The 
PACIO Project has focused on FHIR implementation guides for functional 
status, cognitive status and new use cases on advance directives and 
speech, and language pathology. We encourage post-acute care (PAC) 
provider and health information technology (IT) vendor participation as 
these efforts advance.
    The CMS Data Element Library (DEL) continues to be updated and 
serves as the authoritative resource for PAC assessment data elements 
and their associated mappings to health IT standards such as Logical 
Observation Identifiers Names and Codes (LOINC) and Systematized 
Nomenclature of Medicine Clinical Terms (SNOMED). The DEL furthers CMS' 
goal of data standardization and interoperability. When combined with 
digital information systems that capture and maintain these coded 
elements, their standardized clinical content can reduce provider 
burden by supporting and exchange of standardized healthcare data; 
supporting provider exchange of electronic health information for care 
coordination, person-centered care; and supporting real-time, data 
driven, clinical decision making. Standards in the Data Element Library 
(https://del.cms.gov/DELWeb/pubHome) can be referenced on the CMS 
website and in the ONC Interoperability Standards Advisory (ISA). The 
2021 ISA is available at https://www.healthit.gov/isa.
    The 21st Century Cures Act (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. The Cures Act 
includes a trusted exchange framework and common agreement (TEFCA) 
provision \1\ that will enable the nationwide exchange of electronic 
health information across health information networks and provide an 
important way to enable bi-directional health information exchange in 
the future. For more information on current developments related to 
TEFCA, we refer readers to https://www.healthit.gov/topic/interoperability/trusted-exchange-framework-and-common-agreement and 
https://rce.sequoiaproject.org/.
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    \1\ ONC, Draft 2 Trusted Exchange Framework and Common 
Agreement, https://www.healthit.gov/sites/default/files/page/2019-04/FINALTEFCAQTF41719508version.pdf.
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    The ONC final rule entitled ``21st Century Cures Act: 
Interoperability, Information Blocking, and the ONC Health IT 
Certification Program'' (85 FR 25642) published in the May 1, 2020 
Federal Register (hereinafter referred to as ``ONC Cures Act Final 
Rule'') established policies related to information blocking as 
authorized under section 4004 of the 21st Century Cures Act. 
Information blocking is generally defined as a practice by a health IT 
developer of certified health IT, health information network, health 
information exchange, or health care provider that, except as required 
by law or specified by the HHS Secretary as a reasonable and necessary 
activity, is likely to interfere with access, exchange, or use of 
electronic health information. The definition of information blocking 
includes a knowledge standard, which is different for health care 
providers than for health IT developers of certified health IT and 
health information networks or health information exchanges. A 
healthcare provider must know that the practice is unreasonable, as 
well as likely to interfere with access, exchange, or use of electronic 
health information. To deter information blocking, health IT developers 
of certified health IT, health information networks and health 
information exchanges whom the HHS Inspector General determines, 
following an investigation, have committed information blocking, are 
subject to civil monetary penalties of up to $1 million per violation. 
Appropriate disincentives for health care providers are expected to be 
established by the Secretary through future rulemaking. Stakeholders 
can learn more about information blocking at https://www.healthit.gov/curesrule/final-rule-policy/information-blocking. ONC has posted 
information resources including fact sheets (https://www.healthit.gov/curesrule/resources/fact-sheets), frequently asked questions (https://www.healthit.gov/curesrule/resources/information-blocking-faqs), and 
recorded webinars (https://www.healthit.gov/curesrule/resources/webinars).
    We invite providers to learn more about these important 
developments and how they are likely to affect SNFs.

II. Background on SNF PPS

A. Statutory Basis and Scope

    As amended by section 4432 of the Balanced Budget Act of 1997 (BBA 
1997) (Pub. L. 105-33, enacted August 5, 1997), section 1888(e) of the 
Act provides for the implementation of a PPS for SNFs. This methodology 
uses prospective, case-mix adjusted per diem payment rates applicable 
to all covered SNF services defined in section 1888(e)(2)(A) of the 
Act. The SNF PPS is effective for cost reporting periods beginning on 
or after July 1, 1998, and covers all costs of furnishing covered SNF 
services (routine, ancillary, and capital-related costs) other than 
costs associated with approved educational activities and bad debts. 
Under section 1888(e)(2)(A)(i) of the Act, covered SNF services include 
post-hospital extended care services for which benefits are provided 
under Part A, as well as those items and services (other than a small 
number of excluded services, such as physicians' services) for which 
payment may otherwise be made under Part B and which are furnished to 
Medicare beneficiaries who are residents in a SNF during a covered Part 
A stay. A comprehensive discussion of these provisions appears in the 
May 12, 1998 interim final rule (63 FR 26252). In addition, a detailed 
discussion of the legislative history of the SNF PPS is available 
online at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/Downloads/Legislative_History_2018-10-01.pdf.
    Section 215(a) of the Protecting Access to Medicare Act of 2014 
(PAMA) (Pub. L. 113-93, enacted April 1, 2014) added section 1888(g) to 
the Act requiring the Secretary to specify an all-cause all-condition 
hospital readmission measure and an all-condition risk-adjusted 
potentially preventable hospital readmission measure for the SNF 
setting. Additionally, section 215(b) of PAMA added section 1888(h)

[[Page 19957]]

to the Act requiring the Secretary to implement a VBP program for SNFs. 
Finally, section 2(c)(4) of the IMPACT Act amended section 1888(e)(6) 
of the Act, which requires the Secretary to implement a QRP for SNFs 
under which SNFs report data on measures and resident assessment data.

B. Initial Transition for the SNF PPS

    Under sections 1888(e)(1)(A) and (e)(11) of the Act, the SNF PPS 
included an initial, three-phase transition that blended a facility-
specific rate (reflecting the individual facility's historical cost 
experience) with the Federal case-mix adjusted rate. The transition 
extended through the facility's first 3 cost reporting periods under 
the PPS, up to and including the one that began in FY 2001. Thus, the 
SNF PPS is no longer operating under the transition, as all facilities 
have been paid at the full Federal rate effective with cost reporting 
periods beginning in FY 2002. As we now base payments for SNFs entirely 
on the adjusted Federal per diem rates, we no longer include adjustment 
factors under the transition related to facility-specific rates for the 
upcoming FY.

C. Required Annual Rate Updates

    Section 1888(e)(4)(E) of the Act requires the SNF PPS payment rates 
to be updated annually. The most recent annual update occurred in a 
final rule that set forth updates to the SNF PPS payment rates for FY 
2021 (85 FR 47594, August 5, 2020).
    Section 1888(e)(4)(H) of the Act specifies that we provide for 
publication annually in the Federal Register the following:
     The unadjusted Federal per diem rates to be applied to 
days of covered SNF services furnished during the upcoming FY.
     The case-mix classification system to be applied for these 
services during the upcoming FY.
     The factors to be applied in making the area wage 
adjustment for these services.
    Along with other revisions discussed later in this preamble, this 
proposed rule provides the required annual updates to the per diem 
payment rates for SNFs for FY 2022.

III. Proposed SNF PPS Rate Setting Methodology and FY 2022 Update

A. Federal Base Rates

    Under section 1888(e)(4) of the Act, the SNF PPS uses per diem 
Federal payment rates based on mean SNF costs in a base year (FY 1995) 
updated for inflation to the first effective period of the PPS. We 
developed the Federal payment rates using allowable costs from 
hospital-based and freestanding SNF cost reports for reporting periods 
beginning in FY 1995. The data used in developing the Federal rates 
also incorporated a Part B add-on, which is an estimate of the amounts 
that, prior to the SNF PPS, would be payable under Part B for covered 
SNF services furnished to individuals during the course of a covered 
Part A stay in a SNF.
    In developing the rates for the initial period, we updated costs to 
the first effective year of the PPS (the 15-month period beginning July 
1, 1998) using a SNF market basket index, and then standardized for 
geographic variations in wages and for the costs of facility 
differences in case mix. In compiling the database used to compute the 
Federal payment rates, we excluded those providers that received new 
provider exemptions from the routine cost limits, as well as costs 
related to payments for exceptions to the routine cost limits. Using 
the formula that the BBA 1997 prescribed, we set the Federal rates at a 
level equal to the weighted mean of freestanding costs plus 50 percent 
of the difference between the freestanding mean and weighted mean of 
all SNF costs (hospital-based and freestanding) combined. We computed 
and applied separately the payment rates for facilities located in 
urban and rural areas, and adjusted the portion of the Federal rate 
attributable to wage-related costs by a wage index to reflect 
geographic variations in wages.

B. SNF Market Basket Update

1. SNF Market Basket Index
    Section 1888(e)(5)(A) of the Act requires us to establish a SNF 
market basket index that reflects changes over time in the prices of an 
appropriate mix of goods and services included in covered SNF services. 
Accordingly, we have developed a SNF market basket index that 
encompasses the most commonly used cost categories for SNF routine 
services, ancillary services, and capital-related expenses. In the SNF 
PPS final rule for FY 2018 (82 FR 36548 through 36566), we rebased and 
revised the market basket index, which included updating the base year 
from FY 2010 to 2014. In this year's rule, we propose to rebase and 
revise the market basket index and update the base year from 2014 to 
2018. See section V.A. of this proposed rule for more information.
    The SNF market basket index is used to compute the market basket 
percentage change that is used to update the SNF Federal rates on an 
annual basis, as required by section 1888(e)(4)(E)(ii)(IV) of the Act. 
This market basket percentage update is adjusted by a forecast error 
correction, if applicable, and then further adjusted by the application 
of a productivity adjustment as required by section 1888(e)(5)(B)(ii) 
of the Act and described in section III.B.2.d. of this proposed rule. 
In the FY 2021 SNF PPS final rule (85 FR 47597), the SNF market basket 
percentage was estimated to be 2.2 percent for FY 2021 based on IHS 
Global Inc's (IGI's) second quarter 2020 forecast of the 2014-based SNF 
market basket with historical data through first quarter 2020.
    For this proposed rule, we propose a FY 2022 SNF market basket 
percentage of 2.3 percent based on IGI's fourth quarter 2020 forecast 
of the proposed 2018-based SNF market basket (before application of the 
forecast error adjustment and multifactor productivity (MFP) 
adjustment). We also propose that if more recent data subsequently 
become available (for example, a more recent estimate of the market 
basket and/or the MFP), we would use such data, if appropriate, to 
determine the FY 2022 SNF market basket percentage change, labor-
related share relative importance, forecast error adjustment, or MFP 
adjustment in the SNF PPS final rule.
    In section III.B.2.e. of this proposed rule, we discuss the 2 
percent reduction applied to the market basket update for those SNFs 
that fail to submit measures data as required by section 1888(e)(6)(A) 
of the Act.
2. Use of the SNF Market Basket Percentage
    Section 1888(e)(5)(B) of the Act defines the SNF market basket 
percentage as the percentage change in the SNF market basket index from 
the midpoint of the previous FY to the midpoint of the current FY. For 
the Federal rates set forth in this proposed rule, we use the 
percentage change in the SNF market basket index to compute the update 
factor for FY 2022. This factor is based on the FY 2022 percentage 
increase in the proposed 2018-based SNF market basket index reflecting 
routine, ancillary, and capital-related expenses. As stated previously, 
in this proposed rule, the SNF market basket percentage update is 
estimated to be 2.3 percent for FY 2022 based on IGI's fourth quarter 
2020 forecast.
3. Forecast Error Adjustment
    As discussed in the June 10, 2003 supplemental proposed rule (68 FR 
34768) and finalized in the August 4, 2003 final rule (68 FR 46057 
through 46059), Sec.  413.337(d)(2) provides for an

[[Page 19958]]

adjustment to account for market basket forecast error. The initial 
adjustment for market basket forecast error applied to the update of 
the FY 2003 rate for FY 2004, and took into account the cumulative 
forecast error for the period from FY 2000 through FY 2002, resulting 
in an increase of 3.26 percent to the FY 2004 update. Subsequent 
adjustments in succeeding FYs take into account the forecast error from 
the most recently available FY for which there is final data, and apply 
the difference between the forecasted and actual change in the market 
basket when the difference exceeds a specified threshold. We originally 
used a 0.25 percentage point threshold for this purpose; however, for 
the reasons specified in the FY 2008 SNF PPS final rule (72 FR 43425), 
we adopted a 0.5 percentage point threshold effective for FY 2008 and 
subsequent FYs. As we stated in the final rule for FY 2004 that first 
issued the market basket forecast error adjustment (68 FR 46058), the 
adjustment will reflect both upward and downward adjustments, as 
appropriate.
    For FY 2020 (the most recently available FY for which there is 
final data), the forecasted or estimated increase in the SNF market 
basket index was 2.8 percentage points, and the actual increase for FY 
2020 is 2.0 percentage points, resulting in the actual increase being 
0.8 percentage point lower than the estimated increase. Accordingly, as 
the difference between the estimated and actual amount of change in the 
market basket index exceeds the 0.5 percentage point threshold, under 
the policy previously described (comparing the forecasted and actual 
increase in the market basket), the FY 2022 market basket percentage 
change of 2.3 percent would be adjusted downward to account for the 
forecast error correction of 0.8 percentage point, resulting in a SNF 
market basket percentage change of 1.5 percent.
    We note that we may consider modifying this forecast error 
methodology in future rulemaking. We invite comments and feedback on 
this issue, in particular on the possibility of, in future rulemaking, 
either eliminating the forecast error adjustment, or raising the 
threshold for the forecast error from 0.5 percent to 1.0 percent.
    Table 2 shows the forecasted and actual market basket increases for 
FY 2020.

            Table 2--Difference Between the Actual and Forecasted Market Basket Increases for FY 2020
----------------------------------------------------------------------------------------------------------------
                                                      Forecasted FY 2020    Actual FY 2020          FY 2020
                        Index                              Increase*          Increase**          difference
----------------------------------------------------------------------------------------------------------------
SNF.................................................                2.8                 2.0                -0.8
----------------------------------------------------------------------------------------------------------------
* Published in Federal Register; based on second quarter 2019 IGI forecast (2014-based index).
** Based on the fourth quarter 2020 IGI forecast (2014-based index).

4. Multifactor Productivity Adjustment
    Section 1888(e)(5)(B)(ii) of the Act, as added by section 3401(b) 
of the Patient Protection and Affordable Care Act (Affordable Care Act) 
(Pub. L. 111-148, enacted March 23, 2010) requires that, in FY 2012 and 
in subsequent FYs, the market basket percentage under the SNF payment 
system (as described in section 1888(e)(5)(B)(i) of the Act) is to be 
reduced annually by the MFP adjustment described in section 
1886(b)(3)(B)(xi)(II) of the Act. Section 1886(b)(3)(B)(xi)(II) of the 
Act, in turn, defines the MFP adjustment to be equal to the 10-year 
moving average of changes in annual economy-wide private nonfarm 
business multi-factor productivity (as projected by the Secretary for 
the 10-year period ending with the applicable FY, year, cost-reporting 
period, or other annual period). The Bureau of Labor Statistics (BLS) 
is the agency that 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 
inputs 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. To generate a forecast of MFP, IGI 
replicates the MFP measure calculated by the BLS, using a series of 
proxy variables derived from IGI's U.S. macroeconomic models. For a 
discussion of the MFP projection methodology, we refer readers to the 
FY 2012 SNF PPS final rule (76 FR 48527 through 48529) and the FY 2016 
SNF PPS final rule (80 FR 46395). A complete description of the MFP 
projection methodology is available on our website at http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch.html.
a. Incorporating the MFP Into the Market Basket Update
    Per section 1888(e)(5)(A) of the Act, the Secretary shall establish 
a SNF market basket index that reflects changes over time in the prices 
of an appropriate mix of goods and services included in covered SNF 
services. Section 1888(e)(5)(B)(ii) of the Act, added by section 
3401(b) of the Affordable Care Act, requires that for FY 2012 and each 
subsequent FY, after determining the market basket percentage described 
in section 1888(e)(5)(B)(i) of the Act, the Secretary shall reduce such 
percentage by the productivity adjustment described in section 
1886(b)(3)(B)(xi)(II) of the Act (which we refer to as the MFP 
adjustment). Section 1888(e)(5)(B)(ii) of the Act further states that 
the reduction of the market basket percentage by the MFP adjustment may 
result in the market basket percentage being less than zero for a FY, 
and may result in payment rates under section 1888(e) of the Act being 
less than such payment rates for the preceding fiscal year. Thus, if 
the application of the MFP adjustment to the market basket percentage 
calculated under section 1888(e)(5)(B)(i) of the Act results in an MFP-
adjusted market basket percentage that is less than zero, then the 
annual update to the unadjusted Federal per diem rates under section 
1888(e)(4)(E)(ii) of the Act would be negative, and such rates would 
decrease relative to the prior FY.
    Based on the data available for this FY 2022 SNF PPS proposed rule, 
the current estimate of the 10-year moving average of changes in MFP 
for the period ending September 30, 2022 would be 0.2 percentage point.
    Consistent with section 1888(e)(5)(B)(i) of the Act and Sec.  
413.337(d)(2), as discussed previously, the market basket percentage 
for FY 2022 for the SNF PPS is based on IGI's fourth quarter 2020 
forecast of the SNF market basket percentage, which is estimated to be 
2.3 percent. As discussed above, we are applying a 0.2 percentage point 
MFP adjustment to the FY 2022 SNF market basket percentage.

[[Page 19959]]

The resulting MFP-adjusted FY 2022 SNF market basket update is, 
therefore, equal to 2.1 percent, or 2.3 percent less 0.2 percentage 
point.
5. Market Basket Update Factor for FY 2022
    Sections 1888(e)(4)(E)(ii)(IV) and (e)(5)(i) of the Act require 
that the update factor used to establish the FY 2022 unadjusted Federal 
rates be at a level equal to the market basket index percentage change. 
Accordingly, we determined the total growth from the average market 
basket level for the period of October 1, 2020 through September 30, 
2021 to the average market basket level for the period of October 1, 
2021 through September 30, 2022. This process yields a percentage 
change in the proposed 2018-based SNF market basket of 2.3 percent.
    As further explained in section III.B.2.c. of this proposed rule, 
as applicable, we adjust the market basket percentage change by the 
forecast error from the most recently available FY for which there is 
final data and apply this adjustment whenever the difference between 
the forecasted and actual percentage change in the market basket 
exceeds a 0.5 percentage point threshold. Since the forecasted FY 2020 
SNF market basket percentage change exceeded the actual FY 2020 SNF 
market basket percentage change (FY 2020 is the most recently available 
FY for which there is historical data) by more than the 0.5 percentage 
point threshold, we propose to adjust the FY 2022 market basket 
percentage change downward by the forecast error correction. Applying 
the -0.8 percent forecast error correction results in an adjusted FY 
2022 SNF market basket percentage change of 1.5 percent (2.3 percent 
market basket update less 0.8 percentage point forecast error 
adjustment).
    Section 1888(e)(5)(B)(ii) of the Act requires us to reduce the 
market basket percentage change by the MFP adjustment (10-year moving 
average of changes in MFP for the period ending September 30, 2022) 
which is estimated to be 0.2 percent, as described in section 
III.B.2.d. of this proposed rule. Thus, we propose to apply a net SNF 
market basket update factor of 1.3 percent in our determination of the 
FY 2022 SNF PPS unadjusted Federal per diem rates, which reflects a 
market basket increase factor of 2.3 percent, less the 0.8 percent 
forecast error correction and less the projected 0.2 percentage point 
MFP adjustment.
    We note that if more recent data become available (for example, a 
more recent estimate of the SNF market basket and/or MFP), we would use 
such data, if appropriate, to determine the FY 2022 SNF market basket 
percentage change, labor-related share relative importance, forecast 
error adjustment, or MFP adjustment in the FY 2022 SNF PPS final rule.
    We also note that section 1888(e)(6)(A)(i) of the Act provides 
that, beginning with FY 2018, SNFs that fail to submit data, as 
applicable, in accordance with sections 1888(e)(6)(B)(i)(II) and (III) 
of the Act for a fiscal year will receive a 2.0 percentage point 
reduction to their market basket update for the fiscal year involved, 
after application of section 1888(e)(5)(B)(ii) of the Act (the MFP 
adjustment) and section 1888(e)(5)(B)(iii) of the Act (the 1 percent 
market basket increase for FY 2018). In addition, section 
1888(e)(6)(A)(ii) of the Act states that application of the 2.0 
percentage point reduction (after application of section 
1888(e)(5)(B)(ii) and (iii) of the Act) may result in the market basket 
index percentage change being less than zero for a fiscal year, and may 
result in payment rates for a fiscal year being less than such payment 
rates for the preceding fiscal year. Section 1888(e)(6)(A)(iii) of the 
Act further specifies that the 2.0 percentage point reduction is 
applied in a noncumulative manner, so that any reduction made under 
section 1888(e)(6)(A)(i) of the Act applies only to the fiscal year 
involved, and that the reduction cannot be taken into account in 
computing the payment amount for a subsequent fiscal year.
6. Unadjusted Federal per Diem Rates for FY 2022
    As discussed in the FY 2019 SNF PPS final rule (83 FR 39162), in FY 
2020 we implemented a new case-mix classification system to classify 
SNF patients under the SNF PPS, the PDPM. As discussed in section V.B. 
of that final rule, under PDPM, the unadjusted Federal per diem rates 
are divided into six components, five of which are case-mix adjusted 
components (Physical Therapy (PT), Occupational Therapy (OT), Speech-
Language Pathology (SLP), Nursing, and Non-Therapy Ancillaries (NTA)), 
and one of which is a non-case-mix component, as existed under the 
previous RUG-IV model. We propose to use the SNF market basket, 
adjusted as described previously, to adjust each per diem component of 
the Federal rates forward to reflect the change in the average prices 
for FY 2022 from the average prices for FY 2021. We propose to further 
adjust the rates by a wage index budget neutrality factor, described 
later in this section. Further, in the past, we used the revised OMB 
delineations adopted in the FY 2015 SNF PPS final rule (79 FR 45632, 
45634), with updates as reflected in OMB Bulletin Nos. 15-01 and 17-01, 
to identify a facility's urban or rural status for the purpose of 
determining which set of rate tables would apply to the facility. As 
discussed in the FY 2021 SNF PPS proposed and final rules, we adopted 
the revised OMB delineations identified in OMB Bulletin No. 18-04 
(available at https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf) to identify a facility's urban or rural status 
effective beginning with FY 2021.
    For FY 2022, we note an additional adjustment to the unadjusted per 
diem base rates. Specifically, section 134 in Division CC of the 
Consolidated Appropriations Act, 2021 included a provision amending 
section 1888(e)(2)(A)(iii) of the Act so as to add ``blood clotting 
factors indicated for the treatment of patients with hemophilia and 
other bleeding disorders . . . and items and services related to the 
furnishing of such factors under section 1842(o)(5)(C)'' to the list of 
items and services excludable from the Part A SNF PPS per diem payment, 
effective for items and services furnished on or after October 1, 2021. 
We discuss this provision further in section IV.B. of this proposed 
rule.
    Section 1888(e)(4)(G)(iii) of the Act further requires that the 
Secretary ``provide for an appropriate proportional reduction in 
payments so that . . . the aggregate amount of such reductions is equal 
to the aggregate increase in payments attributable to the exclusion'' 
of the services from the Part A PPS per diem rates under section 
1888(e)(2)(A)(iii) of the Act.
    In the FY 2001 rulemaking cycle (65 FR 19202 and 46792), we 
established a methodology for computing such offsets in response to 
similar targeted consolidated billing exclusions added to section 
1888(e)(2)(A)(iii) Act by section 103 of BBRA 1999. This methodology 
resulted in a reduction of 5 cents ($0.05) in the unadjusted urban and 
rural rates, using the identical data as used to establish the Part B 
add-on for a sample of approximately 1,500 SNFs from the 1995 base 
period. However, because this methodology relied on data from 1995, we 
propose a new methodology based on updated data (as discussed below) to 
apply the offsets required for the exclusion of the blood clotting 
factors and items and services related to the furnishing of such 
factors under section 1842(o)(5)(C) of the Act (referred to 
collectively as the blood clotting factor exclusion), as specified 
under the

[[Page 19960]]

Consolidated Appropriations Act, 2021. We believe the use of the 
updated data will more accurately capture the actual cost of these 
factors, as using updated utilization data would reflect new types of 
blood clotting factors introduced in recent years and changes in 
utilization patterns of blood clotting factors since 1995.
    The proposed methodology for calculating the blood clotting factor 
exclusion offset consists of five steps. In the first step, we begin 
with the total number of SNF utilization days for beneficiaries who 
have any amount of blood clotting factor (BCF) use in FY 2020. While we 
recognize the potential effects of the PHE for COVID-19 on SNF 
utilization during 2020, we believe we should use FY 2020 data because 
it is the most recent data available, and thus would best reflect the 
latest types of blood clotting factors and the most recent changes in 
utilization patterns; also, the FY 2020 data is the only data available 
that reflects utilization under the PDPM model rather than the RUG-IV 
model. However, in light of the potential impact of the PHE for COVID-
19 on SNF utilization, particularly as it relates to those patients 
admitted with COVID-19 or whose stays utilized a PHE-related waiver 
(for example, the waiver which removes the requirement for a three-day 
prior inpatient hospital stay in order to receive SNF Part A coverage), 
we believe it would be appropriate to use a subset of the full FY 2020 
SNF population which excludes patients diagnosed with COVID-19 and 
those stays which utilized a PHE-related waiver. We discuss this 
concept in more detail in relation to the recalibration of the PDPM 
parity adjustment, discussed in section V.C. of this proposed rule. As 
further explained below, we would note that using this subset 
population has very little impact on the result of the methodology 
described below. Throughout the discussion below, the term ``SNF 
beneficiary'' refers to beneficiaries in the FY 2020 subset population 
described above.
    Since BCF use has historically been subject to SNF consolidated 
billing and its usage cannot be observed on billed SNF claims, this 
methodology resorts to claims from other settings to approximate BCF 
utilization in SNFs. Specifically, BCF use as well as items and 
services related to the furnishing of such factors under section 
1842(o)(5)(C) of the Act are identified by checking if any of the HCPCS 
codes listed in the Act, including J7170, J7175, J7177-J7183, J7185-
J7190, J7192-J7195, J7198-J7203, J7205, and J7207-J7211, are recorded 
on outpatient claims, which are claims submitted by institutional 
outpatient providers (such as a hospital outpatient department), or 
carrier claims, which are fee-for-service claims submitted by 
professional practitioners, such as physicians, physician assistants, 
clinical social workers, and nurse practitioners, and by some 
organizational providers, such as free-standing facilities. A SNF 
beneficiary with any BCF use is defined as a SNF beneficiary with at 
least one matched outpatient or carrier claim for blood clotting 
factors in FY 2020. To calculate the number of SNF utilization days for 
beneficiaries who have any amount of BCF use in FY 2020, we sum up the 
corresponding SNF utilization days of SNF beneficiaries with BCF use in 
FY 2020 (84 beneficiaries), which is 3,317 total utilization days.
    In the second step, we estimate the BCF payment per day per SNF 
beneficiary with any BCF use in FY 2020, which would include payment 
for the BCFs and items and services related to the furnishing of such 
factors under section 1842(o)(5)(C) of the Act. There is no direct 
payment data to track BCF use in SNFs since BCF use is bundled within 
the Part A per diem payment. Therefore, we rely on payment in 
outpatient and carrier claims as a proxy for this step. Instead of 
calculating BCF payment per day for SNF beneficiaries in a SNF stay, we 
estimate the BCF payment per day for SNF beneficiaries outside of their 
SNF and inpatient stays, under the assumption that BCF payment per day 
for SNF beneficiaries is similar during and outside of SNF stays. 
Outpatient or carrier claims for BCF use that overlap with a SNF stay 
or an inpatient stay of a SNF beneficiary are excluded to ensure that 
BCF-related payment is fully captured in Part B claims instead of 
partially paid through Part A. Overlapping claims are identified when 
the outpatient claim ``From'' date or the carrier claim expense date 
fall within a SNF or inpatient stay's admission and discharge date 
window. The total BCF payment for SNF beneficiaries' BCF use observed 
through Part B claims in FY 2020 was $4,843,551. Next, to determine the 
corresponding utilizations days for SNF beneficiaries' BCF use, we need 
to carve out their utilization days in a SNF or inpatient setting for 
these target beneficiaries. We first determine the total SNF and 
inpatient utilization days for these beneficiaries in FY 2020, which 
totals 5,408. Next, we determine the total days that the beneficiaries 
with BCF use were not in a SNF or inpatient stay, which is 365 (for 
days in the year) multiplied by the number of SNF beneficiaries with 
BCF use (84), less the total SNF and inpatient utilization days for 
these beneficiaries (5,408), which is 20,142. Finally, we estimated the 
BCF payment per day, which is the total BCF payment observed in 
outpatient and carrier claims ($4,843,551) divided by the total days 
the beneficiaries were not in a SNF or inpatient (20,142). Thus, we 
calculate the BCF payment per day per SNF beneficiary to be $240.
    In the third step, we calculate the percentage of SNF payment 
associated with BCF usage. We multiply the estimated BCF payment per 
day ($240 as determined in step 2) by the total SNF utilization days 
for SNF beneficiaries with BCF use in FY 2020 (3,317 as determined in 
step 1). This yields an estimated BCF payment for SNF beneficiaries in 
the study population of $797,640. Next, we divide this by the total SNF 
payment for the study population during FY 2020 ($22,636,345,868) to 
yield the percentage of SNF payment associated with BCF use, which we 
estimate to be 0.00352 percent.
    In the fourth step, we calculate the urban and rural base rate 
reductions, by multiplying the proposed FY 2022 urban/rural base rates 
by the percentage of SNF payment associated with clotting factor use 
determined in step 3 (0.00352 percent). In the case of the proposed 
urban base rate of $434.79, this yields an urban base rate deduction of 
$0.02, which we would apply as a $0.01 reduction to the proposed FY 
2022 NTA base rate and a $0.01 reduction to the proposed FY 2022 
nursing base rate. In the case of the proposed rural base rate of 
$444.79, this yields a rural base rate deduction of $0.02, which we 
would apply as a $0.01 reduction to the proposed FY 2022 NTA base rates 
and a $0.01 reduction to the proposed FY 2022 nursing base rate. We 
would apply the reduction to the NTA and nursing base rates because BCF 
is a type of NTA and nursing resources are required to furnish this 
medication.
    In step five, for purposes of impact analysis, we calculate the 
budget impact of the base rate reductions to be $782,785. We estimate 
the budget impact by multiplying the total FY2022 SNF baseline 
($34,211,000,000) by the percentage of SNF payment for clotting factor 
(0.00352 percent). This results in a total reduction in SNF spending of 
$1.2 million. To compare the result of this proposed methodology to 
that which would have resulted from using the full FY 2020 SNF 
population, we note that if we had used the full FY 2020 SNF 
population, the resultant impact would be a reduction in SNF spending 
of $1.5 million, which represents 0.004551 percent of total

[[Page 19961]]

payments made under the SNF PPS. Given that these figures are so close 
as to result in the same two cent reduction in the FY 2022 SNF PPS 
unadjusted per diem rates, and given the reasons for using the subset 
population discussed in section V.C. of this proposed rule, we believe 
it is appropriate to use this subset population as the basis for the 
calculations described throughout this section.
    We apply these rate reductions to the NTA and nursing components of 
the unadjusted Federal urban and rural per diem rate as shown in Tables 
4 and 5.
    Table 3 displays the methodology and figures used to calculate 
these rate reductions.

   Table 3--Estimation of Blood Clotting Factor on Base Rate Reduction
------------------------------------------------------------------------
 
------------------------------------------------------------------------
Step 1: SNF Utilization Days of Benes with Any BCF
 Use:
    FY2020 # SNF Benes with Any BCF Use..............                 84
    FY2020 Total SNF Util Days for Benes with Any BCF              3,317
     Use.............................................
Step 2: Clotting Factor Payment per Day per SNF Bene
 with Any BCF Use:
    FY2020 Total Part B Clotting Factor Payment for           $4,843,551
     Benes with Any BCF Use Outside of SNF or
     Inpatient Stay..................................
    FY2020 Total SNF and Inpatient Util Days for                   5,408
     Benes with Any BCF Use..........................
    FY2020 Total Days Not in SNF or Inpatient Stay                20,142
     for Benes with Any BCF Use......................
    FY2020 Clotting Factor Payment per Day...........               $240
Step 3: % of SNF Payment Associated with Clotting
 Factor Use:
    FY2020 Estimated Clotting Factor Payment in SNF..           $797,640
    FY2020 Total SNF Payment.........................    $22,636,345,868
    % of SNF Payment Associated with Clotting Factor            0.00352%
     Use.............................................
------------------------------------------------------------------------

    Tables 4 and 5 reflect the updated unadjusted Federal rates for FY 
2022, prior to adjustment for case-mix. The rates in Tables 4 and 5 
include the reductions calculated in Table 3 for blood clotting factor 
use.

                                                Table 4--FY 2022 Unadjusted Federal Rate Per Diem--Urban
--------------------------------------------------------------------------------------------------------------------------------------------------------
                  Rate component                           PT               OT              SLP            Nursing            NTA          Non-case-mix
--------------------------------------------------------------------------------------------------------------------------------------------------------
Per Diem Amount...................................          $62.84           $58.49           $23.46          $109.55           $82.64           $98.10
--------------------------------------------------------------------------------------------------------------------------------------------------------


                                                Table 5--FY 2022 Unadjusted Federal Rate Per Diem--Rural
--------------------------------------------------------------------------------------------------------------------------------------------------------
                  Rate component                           PT               OT              SLP            Nursing            NTA          Non-case-mix
--------------------------------------------------------------------------------------------------------------------------------------------------------
Per Diem Amount...................................          $71.63           $65.79           $29.56          $104.66           $78.96           $99.91
--------------------------------------------------------------------------------------------------------------------------------------------------------

C. Case-Mix Adjustment

    Under section 1888(e)(4)(G)(i) of the Act, the Federal rate also 
incorporates an adjustment to account for facility case-mix, using a 
classification system that accounts for the relative resource 
utilization of different patient types. The statute specifies that the 
adjustment is to reflect both a resident classification system that the 
Secretary establishes to account for the relative resource use of 
different patient types, as well as resident assessment data and other 
data that the Secretary considers appropriate. In the FY 2019 final 
rule (83 FR 39162, August 8, 2018), we finalized a new case-mix 
classification model, the PDPM, which took effect beginning October 1, 
2019. The previous RUG-IV model classified most patients into a therapy 
payment group and primarily used the volume of therapy services 
provided to the patient as the basis for payment classification, thus 
creating an incentive for SNFs to furnish therapy regardless of the 
individual patient's unique characteristics, goals, or needs. PDPM 
eliminates this incentive and improves the overall accuracy and 
appropriateness of SNF payments by classifying patients into payment 
groups based on specific, data-driven patient characteristics, while 
simultaneously reducing the administrative burden on SNFs.
    As we noted in the FY 2021 SNF PPS final rule (85 FR 47600), we 
continue to monitor the impact of PDPM implementation on patient 
outcomes and program outlays. We hope to release information in the 
future that relates to these issues, though we provide some of this 
information in section V.C. of this proposed rule. We also continue to 
monitor the impact of PDPM implementation as it relates to our 
intention to ensure that PDPM is implemented in a budget neutral 
manner, as discussed in the FY 2020 SNF PPS final rule (84 FR 38734). 
In section V.C. of this proposed rule, we discuss and solicit comments 
on a methodology to recalibrate the PDPM parity adjustment as 
appropriate to ensure budget neutrality, as we did after the 
implementation of RUG-IV in FY 2011.
    The PDPM uses clinical data from the MDS to assign case-mix 
classifiers to each patient that are then used to calculate a per diem 
payment under the SNF PPS, consistent with the provisions of section 
1888(e)(4)(G)(i) of the Act. As discussed in section IV.A. of this 
proposed rule, the clinical orientation of the case-mix classification 
system supports the SNF PPS's use of an administrative presumption that 
considers a beneficiary's initial case-mix classification to assist in 
making certain SNF level of care determinations. Further, because the 
MDS is used as a basis for payment, as well as a clinical assessment, 
we have provided extensive training on proper coding and the timeframes 
for MDS completion in our Resident Assessment Instrument (RAI) Manual. 
As we have stated in prior rules, for an MDS to be considered valid for 
use in determining payment, the MDS assessment should be completed in 
compliance with the instructions in the RAI Manual in effect at the 
time the assessment is completed. For payment and quality monitoring 
purposes, the RAI Manual consists of both the Manual

[[Page 19962]]

instructions and the interpretive guidance and policy clarifications 
posted on the appropriate MDS website at http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/MDS30RAIManual.html.
    Under section 1888(e)(4)(H) of the Act, each update of the payment 
rates must include the case-mix classification methodology applicable 
for the upcoming FY. The proposed FY 2022 payment rates set forth in 
this proposed rule reflect the use of the PDPM case-mix classification 
system from October 1, 2021, through September 30, 2022. We list the 
proposed case-mix adjusted PDPM payment rates for FY 2022 separately 
for urban and rural SNFs, in Tables 6 and 7 with corresponding case-mix 
values.
    Given the differences between the previous RUG-IV model and PDPM in 
terms of patient classification and billing, it was important that the 
format of Tables 6 and 7 reflect these differences. More specifically, 
under both RUG-IV and PDPM, providers use a Health Insurance 
Prospective Payment System (HIPPS) code on a claim to bill for covered 
SNF services. Under RUG-IV, the HIPPS code included the three-character 
RUG-IV group into which the patient classified as well as a two-
character assessment indicator code that represented the assessment 
used to generate this code. Under PDPM, while providers still use a 
HIPPS code, the characters in that code represent different things. For 
example, the first character represents the PT and OT group into which 
the patient classifies. If the patient is classified into the PT and OT 
group ``TA'', then the first character in the patient's HIPPS code 
would be an A. Similarly, if the patient is classified into the SLP 
group ``SB'', then the second character in the patient's HIPPS code 
would be a B. The third character represents the Nursing group into 
which the patient classifies. The fourth character represents the NTA 
group into which the patient classifies. Finally, the fifth character 
represents the assessment used to generate the HIPPS code.
    Tables 6 and 7 reflect the PDPM's structure. Accordingly, Column 1 
of Tables 6 and 7 represents the character in the HIPPS code associated 
with a given PDPM component. Columns 2 and 3 provide the case-mix index 
and associated case-mix adjusted component rate, respectively, for the 
relevant PT group. Columns 4 and 5 provide the case-mix index and 
associated case-mix adjusted component rate, respectively, for the 
relevant OT group. Columns 6 and 7 provide the case-mix index and 
associated case-mix adjusted component rate, respectively, for the 
relevant SLP group. Column 8 provides the nursing case-mix group (CMG) 
that is connected with a given PDPM HIPPS character. For example, if 
the patient qualified for the nursing group CBC1, then the third 
character in the patient's HIPPS code would be a ``P.'' Columns 9 and 
10 provide the case-mix index and associated case-mix adjusted 
component rate, respectively, for the relevant nursing group. Finally, 
columns 11 and 12 provide the case-mix index and associated case-mix 
adjusted component rate, respectively, for the relevant NTA group.
    Tables 6 and 7 do not reflect adjustments which may be made to the 
SNF PPS rates as a result of the SNF VBP program, discussed in section 
III.D. of this proposed rule, or other adjustments, such as the 
variable per diem adjustment. Further, in the past, we used the revised 
OMB delineations adopted in the FY 2015 SNF PPS final rule (79 FR 
45632, 45634), with updates as reflected in OMB Bulletin Nos, 15-01 and 
17-01, to identify a facility's urban or rural status for the purpose 
of determining which set of rate tables would apply to the facility. As 
discussed in the FY 2021 SNF PPS final rule (85 FR 47594), we adopted 
the revised OMB delineations identified in OMB Bulletin No. 18-04 
(available at https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf) to identify a facility's urban or rural status 
effective beginning with FY 2021.

                                       Table 6--PDPM Case-Mix Adjusted Federal Rates and Associated Indexes--URBAN
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                         SLP                       Nursing   Nursing               NTA
            PDPM group               PT  CMI  PT  rate   OT  CMI  OT  rate  SLP  CMI    rate      Nursing  CMG       CMI      rate    NTA  CMI    rate
--------------------------------------------------------------------------------------------------------------------------------------------------------
A.................................      1.53    $96.15      1.49    $87.15      0.68    $15.95  ES3.............      4.06   $444.77      3.24   $267.75
B.................................      1.70    106.83      1.63     95.34      1.82     42.70  ES2.............      3.07    336.32      2.53    209.08
C.................................      1.88    118.14      1.69     98.85      2.67     62.64  ES1.............      2.93    320.98      1.84    152.06
D.................................      1.92    120.65      1.53     89.49      1.46     34.25  HDE2............      2.40    262.92      1.33    109.91
E.................................      1.42     89.23      1.41     82.47      2.34     54.90  HDE1............      1.99    218.00      0.96     79.33
F.................................      1.61    101.17      1.60     93.58      2.98     69.91  HBC2............      2.24    245.39      0.72     59.50
G.................................      1.67    104.94      1.64     95.92      2.04     47.86  HBC1............      1.86    203.76  ........  ........
H.................................      1.16     72.89      1.15     67.26      2.86     67.10  LDE2............      2.08    227.86  ........  ........
I.................................      1.13     71.01      1.18     69.02      3.53     82.81  LDE1............      1.73    189.52  ........  ........
J.................................      1.42     89.23      1.45     84.81      2.99     70.15  LBC2............      1.72    188.43  ........  ........
K.................................      1.52     95.52      1.54     90.07       3.7     86.80  LBC1............      1.43    156.66  ........  ........
L.................................      1.09     68.50      1.11     64.92      4.21     98.77  CDE2............      1.87    204.86  ........  ........
M.................................      1.27     79.81      1.30     76.04  ........  ........  CDE1............      1.62    177.47  ........  ........
N.................................      1.48     93.00      1.50     87.74  ........  ........  CBC2............      1.55    169.80  ........  ........
O.................................      1.55     97.40      1.55     90.66  ........  ........  CA2.............      1.09    119.41  ........  ........
P.................................      1.08     67.87      1.09     63.75  ........  ........  CBC1............      1.34    146.80  ........  ........
Q.................................  ........  ........  ........  ........  ........  ........  CA1.............      0.94    102.98  ........  ........
R.................................  ........  ........  ........  ........  ........  ........  BAB2............      1.04    113.93  ........  ........
S.................................  ........  ........  ........  ........  ........  ........  BAB1............      0.99    108.45  ........  ........
T.................................  ........  ........  ........  ........  ........  ........  PDE2............      1.57    171.99  ........  ........
U.................................  ........  ........  ........  ........  ........  ........  PDE1............      1.47    161.04  ........  ........
V.................................  ........  ........  ........  ........  ........  ........  PBC2............      1.22    133.65  ........  ........
W.................................  ........  ........  ........  ........  ........  ........  PA2.............      0.71     77.78  ........  ........
X.................................  ........  ........  ........  ........  ........  ........  PBC1............      1.13    123.79  ........  ........
Y.................................  ........  ........  ........  ........  ........  ........  PA1.............      0.66     72.30  ........  ........
--------------------------------------------------------------------------------------------------------------------------------------------------------


[[Page 19963]]


                                       Table 7--PDPM Case-Mix Adjusted Federal Rates and Associated Indexes--RURAL
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                                   Nursing   Nursing
            PDPM Group               PT CMI    PT rate   OT CMI    OT rate   SLP CMI  SLP rate     Nursing CMG       CMI      rate     NTA CMI  NTA rate
--------------------------------------------------------------------------------------------------------------------------------------------------------
A.................................      1.53   $109.59      1.49    $98.03      0.68    $20.10  ES3.............      4.06   $424.92      3.24   $255.83
B.................................      1.70    121.77      1.63    107.24      1.82     53.80  ES2.............      3.07    321.31      2.53    199.77
C.................................      1.88    134.66      1.69    111.19      2.67     78.93  ES1.............      2.93    306.65      1.84    145.29
D.................................      1.92    137.53      1.53    100.66      1.46     43.16  HDE2............      2.40    251.18      1.33    105.02
E.................................      1.42    101.71      1.41     92.76      2.34     69.17  HDE1............      1.99    208.27      0.96     75.80
F.................................      1.61    115.32      1.60    105.26      2.98     88.09  HBC2............      2.24    234.44      0.72     56.85
G.................................      1.67    119.62      1.64    107.90      2.04     60.30  HBC1............      1.86    194.67  ........  ........
H.................................      1.16     83.09      1.15     75.66      2.86     84.54  LDE2............      2.08    217.69  ........  ........
I.................................      1.13     80.94      1.18     77.63      3.53    104.35  LDE1............      1.73    181.06  ........  ........
J.................................      1.42    101.71      1.45     95.40      2.99     88.38  LBC2............      1.72    180.02  ........  ........
K.................................      1.52    108.88      1.54    101.32       3.7    109.37  LBC1............      1.43    149.66  ........  ........
L.................................      1.09     78.08      1.11     73.03      4.21    124.45  CDE2............      1.87    195.71  ........  ........
M.................................      1.27     90.97      1.30     85.53  ........  ........  CDE1............      1.62    169.55  ........  ........
N.................................      1.48    106.01      1.50     98.69  ........  ........  CBC2............      1.55    162.22  ........  ........
O.................................      1.55    111.03      1.55    101.97  ........  ........  CA2.............      1.09    114.08  ........  ........
P.................................      1.08     77.36      1.09     71.71  ........  ........  CBC1............      1.34    140.24  ........  ........
Q.................................  ........  ........  ........  ........  ........  ........  CA1.............      0.94     98.38  ........  ........
R.................................  ........  ........  ........  ........  ........  ........  BAB2............      1.04    108.85  ........  ........
S.................................  ........  ........  ........  ........  ........  ........  BAB1............      0.99    103.61  ........  ........
T.................................  ........  ........  ........  ........  ........  ........  PDE2............      1.57    164.32  ........  ........
U.................................  ........  ........  ........  ........  ........  ........  PDE1............      1.47    153.85  ........  ........
V.................................  ........  ........  ........  ........  ........  ........  PBC2............      1.22    127.69  ........  ........
W.................................  ........  ........  ........  ........  ........  ........  PA2.............      0.71     74.31  ........  ........
X.................................  ........  ........  ........  ........  ........  ........  PBC1............      1.13    118.27  ........  ........
Y.................................  ........  ........  ........  ........  ........  ........  PA1.............      0.66     69.08  ........  ........
--------------------------------------------------------------------------------------------------------------------------------------------------------

D. Wage Index Adjustment

    Section 1888(e)(4)(G)(ii) of the Act requires that we adjust the 
Federal rates to account for differences in area wage levels, using a 
wage index that the Secretary determines appropriate. Since the 
inception of the SNF PPS, we have used hospital inpatient wage data in 
developing a wage index to be applied to SNFs. We propose to continue 
this practice for FY 2022, as we continue to believe that in the 
absence of SNF-specific wage data, using the hospital inpatient wage 
index data is appropriate and reasonable for the SNF PPS. As explained 
in the update notice for FY 2005 (69 FR 45786), the SNF PPS does not 
use the hospital area wage index's occupational mix adjustment, as this 
adjustment serves specifically to define the occupational categories 
more clearly in a hospital setting; moreover, the collection of the 
occupational wage data under the inpatient prospective payment system 
(IPPS) also excludes any wage data related to SNFs. Therefore, we 
believe that using the updated wage data exclusive of the occupational 
mix adjustment continues to be appropriate for SNF payments. As in 
previous years, we would continue to use the pre-reclassified IPPS 
hospital wage data, without applying the occupational mix, rural floor, 
or outmigration adjustment, as the basis for the SNF PPS wage index. 
For FY 2022, the updated wage data are for hospital cost reporting 
periods beginning on or after October 1, 2017 and before October 1, 
2018 (FY 2018 cost report data).
    We note that section 315 of the Medicare, Medicaid, and SCHIP 
Benefits Improvement and Protection Act of 2000 (BIPA) (Pub. L. 106-
554, enacted December 21, 2000) authorized us to establish a geographic 
reclassification procedure that is specific to SNFs, but only after 
collecting the data necessary to establish a SNF PPS wage index that is 
based on wage data from nursing homes. However, to date, this has 
proven to be unfeasible due to the volatility of existing SNF wage data 
and the significant amount of resources that would be required to 
improve the quality of the data. More specifically, auditing all SNF 
cost reports, similar to the process used to audit inpatient hospital 
cost reports for purposes of the IPPS wage index, would place a burden 
on providers in terms of recordkeeping and completion of the cost 
report worksheet. In addition, adopting such an approach would require 
a significant commitment of resources by CMS and the Medicare 
Administrative Contractors, potentially far in excess of those required 
under the IPPS given that there are nearly five times as many SNFs as 
there are inpatient hospitals. Therefore, while we continue to believe 
that the development of such an audit process could improve SNF cost 
reports in such a manner as to permit us to establish a SNF-specific 
wage index, we do not believe this undertaking is feasible at this 
time.
    In addition, we propose to continue to use the same methodology 
discussed in the SNF PPS final rule for FY 2008 (72 FR 43423) to 
address those geographic areas in which there are no hospitals, and 
thus, no hospital wage index data on which to base the calculation of 
the FY 2022 SNF PPS wage index. For rural geographic areas that do not 
have hospitals and, therefore, lack hospital wage data on which to base 
an area wage adjustment, we propose to continue to use the average wage 
index from all contiguous Core-Based Statistical Areas (CBSAs) as a 
reasonable proxy. For FY 2022, there are no rural geographic areas that 
do not have hospitals, and thus, this methodology will not be applied. 
For rural Puerto Rico, we propose not to apply this methodology due to 
the distinct economic circumstances that exist there (for example, due 
to the close proximity to one another of almost all of Puerto Rico's 
various urban and non-urban areas, this methodology would produce a 
wage index for rural Puerto Rico that is higher than that in half of 
its urban areas); instead, we propose that we would continue to use the 
most recent wage index previously available for that area. For urban 
areas without specific hospital wage index data, we propose that we 
would use the average wage indexes of all of the urban areas within the 
state to serve as a reasonable proxy for the wage index of that urban

[[Page 19964]]

CBSA. For FY 2022, the only urban area without wage index data 
available is CBSA 25980, Hinesville-Fort Stewart, GA.
    The wage index applicable to FY 2022 is set forth in Tables A and B 
available on the CMS website at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html.
    In the SNF PPS final rule for FY 2006 (70 FR 45026, August 4, 
2005), we adopted the changes discussed in OMB Bulletin No. 03-04 (June 
6, 2003), which announced revised definitions for MSAs and the creation 
of micropolitan statistical areas and combined statistical areas. In 
adopting the CBSA geographic designations, we provided for a 1-year 
transition in FY 2006 with a blended wage index for all providers. For 
FY 2006, the wage index for each provider consisted of a blend of 50 
percent of the FY 2006 MSA-based wage index and 50 percent of the FY 
2006 CBSA-based wage index (both using FY 2002 hospital data). We 
referred to the blended wage index as the FY 2006 SNF PPS transition 
wage index. As discussed in the SNF PPS final rule for FY 2006 (70 FR 
45041), after the expiration of this 1-year transition on September 30, 
2006, we used the full CBSA-based wage index values.
    In the FY 2015 SNF PPS final rule (79 FR 45644 through 45646), we 
finalized changes to the SNF PPS wage index based on the newest OMB 
delineations, as described in OMB Bulletin No. 13-01, beginning in FY 
2015, including a 1-year transition with a blended wage index for FY 
2015. 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). 
Subsequently, on July 15, 2015, OMB issued OMB Bulletin No. 15-01, 
which provided minor 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 and were 
adopted under the SNF PPS in the FY 2017 SNF PPS final rule (81 FR 
51983, August 5, 2016). In addition, on August 15, 2017, OMB issued 
Bulletin No. 17-01 which announced a new urban CBSA, Twin Falls, Idaho 
(CBSA 46300) which was adopted in the SNF PPS final rule for FY 2019 
(83 FR 39173, August 8, 2018).
    As discussed in the FY 2021 SNF PPS final rule (85 FR 47594), we 
adopted the revised OMB delineations identified in OMB Bulletin No. 18-
04 (available at https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf) beginning October 1, 2020, including a 1-year 
transition for FY 2021 under which we applied a 5 percent cap on any 
decrease in a hospital's wage index compared to its wage index for the 
prior fiscal year (FY 2020). The updated OMB delineations more 
accurately reflect the contemporary urban and rural nature of areas 
across the country, and the use of such delineations allows us to 
determine more accurately the appropriate wage index and rate tables to 
apply under the SNF PPS.
    As we previously stated in the FY 2008 SNF PPS proposed and final 
rules (72 FR 25538 through 25539, and 72 FR 43423), this and all 
subsequent SNF PPS rules and notices are considered to incorporate any 
updates and revisions set forth in the most recent OMB bulletin that 
applies to the hospital wage data used to determine the current SNF PPS 
wage index. We note that on March 6, 2020, OMB issued Bulletin No. 20-
01, which provided updates to and superseded OMB Bulletin No. 18-04 
that was issued on September 14, 2018. The attachments to OMB Bulletin 
No. 20-01 provided detailed information on the updates (available on 
the web at https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf). In the FY 2021 SNF PPS final rule (85 FR 47611), 
we stated that we intended to propose any updates from OMB Bulletin No. 
20-01 in the FY 2022 SNF PPS proposed rule. After reviewing OMB 
Bulletin No. 20-01, we have determined that the changes in OMB Bulletin 
20-01 encompassed delineation changes that do not impact the CBSA-based 
labor market area delineations adopted in FY 2021. Therefore, while we 
are proposing to adopt the updates set forth in OMB Bulletin No. 20-01 
consistent with our longstanding policy of adopting OMB delineation 
updates, we note that specific wage index updates would not be 
necessary for FY 2022 as a result of adopting these OMB updates.
    The proposed wage index applicable to FY 2022 is set forth in 
Tables A and B and is available on the CMS website at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html.
    Once calculated, we would apply the wage index adjustment to the 
labor-related portion of the Federal rate. Each year, we calculate a 
revised labor-related share, based on the relative importance of labor-
related cost categories (that is, those cost categories that are labor-
intensive and vary with the local labor market) in the input price 
index. In the SNF PPS final rule for FY 2018 (82 FR 36548 through 
36566), we finalized a proposal to revise the labor-related share to 
reflect the relative importance of the 2014-based SNF market basket 
cost weights for the following cost categories: 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 proportion of 
Capital-Related expenses. Effective beginning FY 2022, as discussed in 
section V.A.4. of this proposed rule, for FY 2022, we are proposing to 
rebase and revise the labor-related share to reflect the relative 
importance of the proposed 2018-based SNF market basket cost weights 
for the following cost categories: 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 proportion of 
Capital-Related expenses. The proposed methodology for calculating the 
labor-related portion for FY 2022 is discussed in section V.A. of this 
proposed rule.
    We calculate the labor-related relative importance from the SNF 
market basket, and it approximates the labor-related portion of the 
total costs after taking into account historical and projected price 
changes between the base year and FY 2022. The price proxies that move 
the different cost categories in the market basket do not necessarily 
change at the same rate, and the relative importance captures these 
changes. Accordingly, the relative importance figure more closely 
reflects the cost share weights for FY 2022 than the base year weights 
from the SNF market basket. We calculate the labor-related relative 
importance for FY 2022 in four steps. First, we compute the FY 2022 
price index level for the total market basket and each cost category of 
the market basket. Second, we calculate a ratio for each cost category 
by dividing the FY 2022 price index level for that cost category by the 
total market basket price index level. Third, we determine

[[Page 19965]]

the FY 2022 relative importance for each cost category by multiplying 
this ratio by the base year (2018) weight. Finally, we add the FY 2022 
relative importance for each of the labor-related cost categories 
(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 Capital-Related expenses) to produce the FY 2022 
labor-related relative importance. Table 8 summarizes the proposed 
labor-related share for FY 2022, based on IGI's fourth quarter 2020 
forecast of the proposed 2018-based SNF market basket with historical 
data through third quarter 2020, compared to the labor-related share 
that was used for the FY 2021 SNF PPS final rule.

     Table 8--Labor-Related Relative Importance, FY 2021 and FY 2022
------------------------------------------------------------------------
                                         Relative           Relative
                                    importance, labor- importance, labor-
                                    related share, FY  related share, FY
                                        2021 20:2          2022 20:4
                                       forecast \1\       forecast \2\
------------------------------------------------------------------------
Wages and salaries................               51.1               51.2
Employee benefits.................                9.9                9.5
Professional fees: Labor-related..                3.7                3.5
Administrative & facilities                       0.5                0.6
 support services.................
Installation, maintenance & repair                0.6                0.4
 services.........................
All other: Labor-related services.                2.6                1.9
Capital-related (.391)............                2.9                3.0
                                   -------------------------------------
    Total.........................               71.3               70.1
------------------------------------------------------------------------
\1\ Published in the Federal Register (85 FR 47605); based on the second
  quarter 2020 IHS Global Inc. forecast of the 2014-based SNF market
  basket, with historical data through first quarter 2020.
\2\ Based on the fourth quarter 2020 IHS Global Inc. forecast of the
  proposed 2018-based SNF market basket.

    To calculate the labor portion of the case-mix adjusted per diem 
rate, we would multiply the total case-mix adjusted per diem rate, 
which is the sum of all five case-mix adjusted components into which a 
patient classifies, and the non-case-mix component rate, by the FY 2022 
labor-related share percentage provided in Table 8. The remaining 
portion of the rate would be the non-labor portion. Under the previous 
RUG-IV model, we included tables which provided the case-mix adjusted 
RUG-IV rates, by RUG-IV group, broken out by total rate, labor portion 
and non-labor portion, such as Table 9 of the FY 2019 SNF PPS final 
rule (83 FR 39175). However, as we discussed in the FY 2020 final rule 
(84 FR 38738), under PDPM, as the total rate is calculated as a 
combination of six different component rates, five of which are case-
mix adjusted, and given the sheer volume of possible combinations of 
these five case-mix adjusted components, it is not feasible to provide 
tables similar to those that existed in the prior rulemaking.
    Therefore, to aid stakeholders in understanding the effect of the 
wage index on the calculation of the SNF per diem rate, we have 
included a hypothetical rate calculation in Table 9.
    Section 1888(e)(4)(G)(ii) of the Act also requires that we apply 
this wage index in a manner that does not result in aggregate payments 
under the SNF PPS that are greater or less than would otherwise be made 
if the wage adjustment had not been made. For FY 2022 (Federal rates 
effective October 1, 2021), we would apply an adjustment to fulfill the 
budget neutrality requirement. We would meet this requirement by 
multiplying each of the components of the unadjusted Federal rates by a 
budget neutrality factor, equal to the ratio of the weighted average 
wage adjustment factor for FY 2021 to the weighted average wage 
adjustment factor for FY 2022. For this calculation, we would use the 
same FY 2020 claims utilization data for both the numerator and 
denominator of this ratio. We define the wage adjustment factor used in 
this calculation as the labor portion of the rate component multiplied 
by the wage index plus the non-labor portion of the rate component. The 
proposed budget neutrality factor for FY 2022 would be 0.9999.
    We note that if more recent data become available (for example, 
revised wage data), we would use such data, as appropriate, to 
determine the wage index budget neutrality factor in the SNF PPS final 
rule.

E. SNF Value-Based Purchasing Program

    Beginning with payment for services furnished on October 1, 2018, 
section 1888(h) of the Act requires the Secretary to reduce the 
adjusted Federal per diem rate determined under section 1888(e)(4)(G) 
of the Act otherwise applicable to a SNF for services furnished during 
a fiscal year by 2 percent, and to adjust the resulting rate for a SNF 
by the value-based incentive payment amount earned by the SNF based on 
the SNF's performance score for that fiscal year under the SNF VBP 
Program. To implement these requirements, we finalized in the FY 2019 
SNF PPS final rule the addition of Sec.  413.337(f) to our regulations 
(83 FR 39178).
    Please see section VII. of this proposed rule for a further 
discussion of our policies for the SNF VBP Program.

F. Adjusted Rate Computation Example

    Tables 9, 10, and 11 provide examples generally illustrating 
payment calculations during FY 2022 under PDPM for a hypothetical 30-
day SNF stay, involving the hypothetical SNF XYZ, located in Frederick, 
MD (Urban CBSA 23244), for a hypothetical patient who is classified 
into such groups that the patient's HIPPS code is NHNC1. Table 9 shows 
the adjustments made to the Federal per diem rates (prior to 
application of any adjustments under the SNF VBP program as discussed 
previously) to compute the provider's case-mix adjusted per diem rate 
for FY 2022, based on the patient's PDPM classification, as well as how 
the variable per diem (VPD) adjustment factor affects calculation of 
the per diem rate for a given day of the stay. Table 10 shows the 
adjustments made to the case-mix adjusted per diem rate from Table 9 to 
account for the provider's wage index. The wage index used in this 
example is based on the FY 2022 SNF PPS wage index that appears in 
Table A available on the CMS website at http://

[[Page 19966]]

www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/
WageIndex.html. Finally, Table 11 provides the case-mix and wage index 
adjusted per-diem rate for this patient for each day of the 30-day 
stay, as well as the total payment for this stay. Table 11 also 
includes the VPD adjustment factors for each day of the patient's stay, 
to clarify why the patient's per diem rate changes for certain days of 
the stay. As illustrated in Table 9, SNF XYZ's total PPS payment for 
this particular patient's stay would equal $20,571.17.

                            Table 9--PDPM Case-Mix Adjusted Rate Computation Example
----------------------------------------------------------------------------------------------------------------
                                            Per Diem Rate Calculation
-----------------------------------------------------------------------------------------------------------------
                                                                                        VPD
                    Component                        Component    Component rate    adjustment    VPD  adj. rate
                                                       group                          factor
----------------------------------------------------------------------------------------------------------------
PT..............................................               N          $93.00            1.00          $93.00
OT..............................................               N           87.74            1.00           87.74
SLP.............................................               H           67.10            1.00           67.10
Nursing.........................................               N          169.80            1.00          169.80
NTA.............................................               C          152.06            3.00          456.18
Non-Case-Mix....................................  ..............           98.10  ..............           98.10
                                                                 -----------------------------------------------
    Total PDPM Case-Mix Adj. Per Diem...........  ..............  ..............  ..............         $971.92
----------------------------------------------------------------------------------------------------------------


                                                 Table 10--Wage Index Adjusted Rate Computation Example
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                         PDPM wage index adjustment calculation
---------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                     PDPM case-mix                                                        Total case mix
                            HIPPS code                               adjusted per      Labor       Wage       Wage index      Non-labor   and wage index
                                                                         diem         portion     index      adjusted rate     portion      adj. rate
--------------------------------------------------------------------------------------------------------------------------------------------------------
NHNC1............................................................          $971.92    $681.32     0.9776           $666.06     $290.60          $956.66
--------------------------------------------------------------------------------------------------------------------------------------------------------


                                   Table 11--Adjusted Rate Computation Example
----------------------------------------------------------------------------------------------------------------
                                                                                                   Case mix and
                                                                      NTA VPD        PT/OT VPD      wage index
                           Day of stay                              adjustment      adjustment     adjusted per
                                                                      factor          factor         diem rate
----------------------------------------------------------------------------------------------------------------
1...............................................................             3.0             1.0         $956.66
2...............................................................             3.0             1.0          956.66
3...............................................................             3.0             1.0          956.66
4...............................................................             1.0             1.0          657.31
5...............................................................             1.0             1.0          657.31
6...............................................................             1.0             1.0          657.31
7...............................................................             1.0             1.0          657.31
8...............................................................             1.0             1.0          657.31
9...............................................................             1.0             1.0          657.31
10..............................................................             1.0             1.0          657.31
11..............................................................             1.0             1.0          657.31
12..............................................................             1.0             1.0          657.31
13..............................................................             1.0             1.0          657.31
14..............................................................             1.0             1.0          657.31
15..............................................................             1.0             1.0          657.31
16..............................................................             1.0             1.0          657.31
17..............................................................             1.0             1.0          657.31
18..............................................................             1.0             1.0          657.31
19..............................................................             1.0             1.0          657.31
20..............................................................             1.0             1.0          657.31
21..............................................................             1.0            0.98          653.76
22..............................................................             1.0            0.98          653.76
23..............................................................             1.0            0.98          653.76
24..............................................................             1.0            0.98          653.76
25..............................................................             1.0            0.98          653.76
26..............................................................             1.0            0.98          653.76
27..............................................................             1.0            0.98          653.76
28..............................................................             1.0            0.96          650.20
29..............................................................             1.0            0.96          650.20
30..............................................................             1.0            0.96          650.20
                                                                 -----------------------------------------------
    Total Payment...............................................  ..............  ..............       20,571.17
----------------------------------------------------------------------------------------------------------------


[[Page 19967]]

IV. Additional Aspects of the SNF PPS

A. SNF Level of Care--Administrative Presumption

    The establishment of the SNF PPS did not change Medicare's 
fundamental requirements for SNF coverage. However, because the case-
mix classification is based, in part, on the beneficiary's need for 
skilled nursing care and therapy, we have attempted, where possible, to 
coordinate claims review procedures with the existing resident 
assessment process and case-mix classification system discussed in 
section III.B.3. of this proposed rule. This approach includes an 
administrative presumption that utilizes a beneficiary's correct 
assignment, at the outset of the SNF stay, of one of the case-mix 
classifiers designated for this purpose to assist in making certain SNF 
level of care determinations.
    In accordance with Sec.  413.345, we include in each update of the 
Federal payment rates in the Federal Register a discussion of the 
resident classification system that provides the basis for case-mix 
adjustment. We also designate those specific classifiers under the 
case-mix classification system that represent the required SNF level of 
care, as provided in 42 CFR 409.30. This designation reflects an 
administrative presumption that those beneficiaries who are correctly 
assigned one of the designated case-mix classifiers on the initial 
Medicare assessment are automatically classified as meeting the SNF 
level of care definition up to and including the assessment reference 
date (ARD) for that assessment.
    A beneficiary who does not qualify for the presumption is not 
automatically classified as either meeting or not meeting the level of 
care definition, but instead receives an individual determination on 
this point using the existing administrative criteria. This presumption 
recognizes the strong likelihood that those beneficiaries who are 
correctly assigned one of the designated case-mix classifiers during 
the immediate post-hospital period would require a covered level of 
care, which would be less likely for other beneficiaries.
    In the July 30, 1999 final rule (64 FR 41670), we indicated that we 
would announce any changes to the guidelines for Medicare level of care 
determinations related to modifications in the case-mix classification 
structure. The FY 2018 final rule (82 FR 36544) further specified that 
we would henceforth disseminate the standard description of the 
administrative presumption's designated groups via the SNF PPS website 
at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/index.html (where such designations appear in the paragraph 
entitled ``Case Mix Adjustment''), and would publish such designations 
in rulemaking only to the extent that we actually intend to propose 
changes in them. Under that approach, the set of case-mix classifiers 
designated for this purpose under PDPM was finalized in the FY 2019 SNF 
PPS final rule (83 FR 39253) and is posted on the SNF PPS website 
(https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/index.html), in the paragraph entitled ``Case Mix Adjustment.''
    However, we note that this administrative presumption policy does 
not supersede the SNF's responsibility to ensure that its decisions 
relating to level of care are appropriate and timely, including a 
review to confirm that any services prompting the assignment of one of 
the designated case-mix classifiers (which, in turn, serves to trigger 
the administrative presumption) are themselves medically necessary. As 
we explained in the FY 2000 SNF PPS final rule (64 FR 41667), the 
administrative presumption is itself rebuttable in those individual 
cases in which the services actually received by the resident do not 
meet the basic statutory criterion of being reasonable and necessary to 
diagnose or treat a beneficiary's condition (according to section 
1862(a)(1) of the Act). Accordingly, the presumption would not apply, 
for example, in those situations where the sole classifier that 
triggers the presumption is itself assigned through the receipt of 
services that are subsequently determined to be not reasonable and 
necessary. Moreover, we want to stress the importance of careful 
monitoring for changes in each patient's condition to determine the 
continuing need for Part A SNF benefits after the ARD of the initial 
Medicare assessment.

B. Consolidated Billing

    Sections 1842(b)(6)(E) and 1862(a)(18) of the Act (as added by 
section 4432(b) of the BBA 1997) require a SNF to submit consolidated 
Medicare bills to its Medicare Administrative Contractor (MAC) for 
almost all of the services that its residents receive during the course 
of a covered Part A stay. In addition, section 1862(a)(18) of the Act 
places the responsibility with the SNF for billing Medicare for 
physical therapy, occupational therapy, and speech-language pathology 
services that the resident receives during a noncovered stay. Section 
1888(e)(2)(A) of the Act excludes a small list of services from the 
consolidated billing provision (primarily those services furnished by 
physicians and certain other types of practitioners), which remain 
separately billable under Part B when furnished to a SNF's Part A 
resident. These excluded service categories are discussed in greater 
detail in section V.B.2. of the May 12, 1998 interim final rule (63 FR 
26295 through 26297).
    A detailed discussion of the legislative history of the 
consolidated billing provision is available on the SNF PPS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/Downloads/Legislative_History_2018-10-01.pdf. In particular, section 
103 of the BBRA 1999 amended section 1888(e)(2)(A)(iii) of the Act by 
further excluding a number of individual high-cost, low probability 
services, identified by Healthcare Common Procedure Coding System 
(HCPCS) codes, within several broader categories (chemotherapy items, 
chemotherapy administration services, radioisotope services, and 
customized prosthetic devices) that otherwise remained subject to the 
provision. We discuss this BBRA 1999 amendment in greater detail in the 
SNF PPS proposed and final rules for FY 2001 (65 FR 19231 through 
19232, April 10, 2000, and 65 FR 46790 through 46795, July 31, 2000), 
as well as in Program Memorandum AB-00-18 (Change Request #1070), 
issued March 2000, which is available online at www.cms.gov/transmittals/downloads/ab001860.pdf.
    As explained in the FY 2001 proposed rule (65 FR 19232), the 
amendments enacted in section 103 of the BBRA 1999 not only identified 
for exclusion from this provision a number of particular service codes 
within four specified categories (that is, chemotherapy items, 
chemotherapy administration services, radioisotope services, and 
customized prosthetic devices), but also gave the Secretary the 
authority to designate additional, individual services for exclusion 
within each of these four specified service categories. In the proposed 
rule for FY 2001, we also noted that the BBRA 1999 Conference report 
(H.R. Rep. No. 106-479 at 854 (1999) (Conf. Rep.)) characterizes the 
individual services that this legislation targets for exclusion as 
high-cost, low probability events that could have devastating financial 
impacts because their costs far exceed the payment SNFs receive under 
the PPS. According to the conferees, section 103(a) of the BBRA 1999 is 
an attempt to exclude from the PPS certain services and costly items 
that are provided infrequently in SNFs. By contrast, the amendments 
enacted in section 103 of

[[Page 19968]]

the BBRA 1999 do not designate for exclusion any of the remaining 
services within those four categories (thus, leaving all of those 
services subject to SNF consolidated billing), because they are 
relatively inexpensive and are furnished routinely in SNFs.
    As we further explained in the final rule for FY 2001 (65 FR 
46790), and as is consistent with our longstanding policy, any 
additional service codes that we might designate for exclusion under 
our discretionary authority must meet the same statutory criteria used 
in identifying the original codes excluded from consolidated billing 
under section 103(a) of the BBRA 1999: They must fall within one of the 
four service categories specified in the BBRA 1999; and they also must 
meet the same standards of high cost and low probability in the SNF 
setting, as discussed in the BBRA 1999 Conference report. Accordingly, 
we characterized this statutory authority to identify additional 
service codes for exclusion as essentially affording the flexibility to 
revise the list of excluded codes in response to changes of major 
significance that may occur over time (for example, the development of 
new medical technologies or other advances in the state of medical 
practice) (65 FR 46791).
    Effective with items and services furnished on or after October 1, 
2021, section 134 in Division CC of the Consolidated Appropriations 
Act, 2021 (Pub. L. 116-260) has established an additional category of 
excluded codes in section 1888(e)(2)(A)(iii)(VI) of the Act, for 
certain blood clotting factors for the treatment of patients with 
hemophilia and other bleeding disorders along with items and services 
related to the furnishing of such factors under section 1842(o)(5)(C) 
of the Act. The specific factors, and items and services related to the 
furnishing of such factors, excluded under this provision are those 
identified, as of July 1, 2020, by HCPCS codes J7170, J7175, J7177-
J7183, J7185-J7190, J7192-J7195, J7198-J7203, J7205, and J7207-J7211. 
Like the provisions enacted in the BBRA 1999, new section 
1888(e)(2)(A)(iii)(VI) of the Act gives the Secretary the authority to 
designate additional items and services for exclusion within the 
category of items and services described in that section. Section 
1888(e)(4)(G)(iii) of the Act further requires that for any services 
that are unbundled from consolidated billing under section 
1888(e)(2)(A)(iii) of the Act (and, thus, become qualified for separate 
payment under Part B), there must also be a corresponding proportional 
reduction made in aggregate SNF payments under Part A. Accordingly, 
using the methodology described in section III.B.6. of this proposed 
rule, we propose to make a proportional reduction of $0.02 in the 
unadjusted urban and rural rates to reflect these new exclusions, 
effective for items and services furnished on or after October 1, 2021.
    In this proposed rule, we specifically invite public comments 
identifying HCPCS codes in any of these five service categories 
(chemotherapy items, chemotherapy administration services, radioisotope 
services, customized prosthetic devices, and blood clotting factors) 
representing recent medical advances that might meet our criteria for 
exclusion from SNF consolidated billing. We may consider excluding a 
particular service if it meets our criteria for exclusion as specified 
previously. We request that commenters identify in their comments the 
specific HCPCS code that is associated with the service in question, as 
well as their rationale for requesting that the identified HCPCS 
code(s) be excluded.
    We note that the original BBRA amendment and the Consolidated 
Appropriations Act, 2021 identified a set of excluded items and 
services by means of specifying individual HCPCS codes within the 
designated categories that were in effect as of a particular date (in 
the case of the BBRA 1999, July 1, 1999, and in the case of the 
Consolidated Appropriations Act, 2021, July 1, 2020), as subsequently 
modified by the Secretary. In addition, as noted above, the statute 
(section 1888(e)(2)(A)(iii)(II)-(VI) of the Act) gives the Secretary 
authority to identify additional items and services for exclusion 
within the categories of items and services described in the statute, 
which are also designated by HCPCS code. Designating the excluded 
services in this manner makes it possible for us to utilize program 
issuances as the vehicle for accomplishing routine updates to the 
excluded codes to reflect any minor revisions that might subsequently 
occur in the coding system itself (such as the assignment of a 
different code number to a service already designated as excluded, or 
the creation of a new code for a type of service that falls within one 
of the established exclusion categories and meets our criteria for 
exclusion (for example, J7212, ``factor viia (antihemophilic factor, 
recombinant)-jncw (sevenfact), 1 microgram'', which became effective on 
January 1, 2021 and would fall in the blood clotting factor exclusion 
category).
    Accordingly, in the event that we identify through the current 
rulemaking cycle any new services that would actually represent a 
substantive change in the scope of the exclusions from SNF consolidated 
billing, we would identify these additional excluded services by means 
of the HCPCS codes that are in effect as of a specific date (in this 
case, October 1, 2021). By making any new exclusions in this manner, we 
could similarly accomplish routine future updates of these additional 
codes through the issuance of program instructions. The latest list of 
excluded codes can be found on the SNF Consolidated Billing website at 
https://www.cms.gov/Medicare/Billing/SNFConsolidatedBilling.

C. Payment for SNF-Level Swing-Bed Services

    Section 1883 of the Act permits certain small, rural hospitals to 
enter into a Medicare swing-bed agreement, under which the hospital can 
use its beds to provide either acute- or SNF-level care, as needed. For 
critical access hospitals (CAHs), Part A pays on a reasonable cost 
basis for SNF-level services furnished under a swing-bed agreement. 
However, in accordance with section 1888(e)(7) of the Act, SNF-level 
services furnished by non-CAH rural hospitals are paid under the SNF 
PPS, effective with cost reporting periods beginning on or after July 
1, 2002. As explained in the FY 2002 final rule (66 FR 39562), this 
effective date is consistent with the statutory provision to integrate 
swing-bed rural hospitals into the SNF PPS by the end of the transition 
period, June 30, 2002.
    Accordingly, all non-CAH swing-bed rural hospitals have now come 
under the SNF PPS. Therefore, all rates and wage indexes outlined in 
earlier sections of this proposed rule for the SNF PPS also apply to 
all non-CAH swing-bed rural hospitals. As finalized in the FY 2010 SNF 
PPS final rule (74 FR 40356 through 40357), effective October 1, 2010, 
non-CAH swing-bed rural hospitals are required to complete an MDS 3.0 
swing-bed assessment which is limited to the required demographic, 
payment, and quality items. As discussed in the FY 2019 SNF PPS final 
rule (83 FR 39235), revisions were made to the swing bed assessment to 
support implementation of PDPM, effective October 1, 2019. A discussion 
of the assessment schedule and the MDS effective beginning FY 2020 
appears in the FY 2019 SNF PPS final rule (83 FR 39229 through 39237). 
The latest changes in the MDS for swing-bed rural hospitals appear on 
the SNF PPS website at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/index.html.

[[Page 19969]]

D. Revisions to the Regulation Text

    We propose to make certain revisions in the regulation text itself. 
Specifically, we propose to redesignate current 42 CFR 
411.15(p)(2)(xvii) and 489.20(s)(17) to Sec.  411.15(p)(2)(xviii) and 
489.20(s)(18), and update the regulation text at Sec. Sec.  
411.15(p)(2)(xvii) and 489.20(s)(17) to reflect the recently-enacted 
exclusion from SNF consolidated billing at section 
1888(e)(2)(A)(iii)(VI) of the Act effective for items and services 
furnished on or after October 1, 2021. Specifically, proposed revised 
Sec. Sec.  411.15(p)(2)(xvii) and 489.20(s)(17) would reflect the 
exclusion of certain blood clotting factors for the treatment of 
patients with hemophilia and other bleeding disorders (identified by 
designated HCPCS codes in effect as of July 1, 2020, as subsequently 
modified by CMS), and items and services related to the furnishing of 
such factors, and would allow for the exclusion of any additional blood 
clotting factors identified by CMS and items and services related to 
the furnishing of such factors. In addition, we are proposing to make 
conforming changes to the regulation text at Sec. Sec.  
411.15(p)(2)(xiii) through (xvi) and 489.20(s)(13) through (16) to 
reflect the authority that has always existed for CMS to make updates 
to the list of excluded codes as provided in section 
1888(e)(2)(A)(iii)(II) through (V) of the Act, and as discussed in 
section IV. C. of this proposed rule.

V. Other SNF PPS Issues

A. Rebasing and Revising the SNF Market Basket

    Section 1888(e)(5)(A) of the Act requires the Secretary to 
establish a market basket index that reflects the changes over time in 
the prices of an appropriate mix of goods and services included in 
covered SNF services. Accordingly, we have developed a SNF market 
basket index that encompasses the most commonly used cost categories 
for SNF routine services, ancillary services, and capital-related 
expenses. We use the SNF market basket index, adjusted in the manner 
described in section III.B. of this proposed rule, to update the SNF 
PPS per diem rates and to determine the labor-related share on an 
annual basis.
    The SNF market basket is a fixed-weight, Laspeyres-type price 
index. A Laspeyres price index measures the change in price, over time, 
of the same mix of goods and services purchased in the base period. Any 
changes in the quantity or mix of goods and services (that is, 
intensity) purchased over time relative to a base period are not 
measured.
    The index itself is constructed in three steps. First, a base 
period is selected (the proposed base period is 2018) and total base 
period expenditures are estimated for a set of mutually exclusive and 
exhaustive spending categories and the proportion of total costs that 
each category represents is calculated. These proportions are called 
cost or expenditure weights. Second, each expenditure category is 
matched to an appropriate price or wage variable, referred to as a 
price proxy. In nearly every instance, these price proxies are derived 
from publicly available statistical series that are published on a 
consistent schedule (preferably at least on a quarterly basis). 
Finally, the expenditure weight for each cost category is multiplied by 
the level of its respective price proxy. The sum of these products 
(that is, the expenditure weights multiplied by their price levels) for 
all cost categories yields the composite index level of the market 
basket in a given period. Repeating this step for other periods 
produces a series of market basket levels over time. Dividing an index 
level for a given period by an index level for an earlier period 
produces a rate of growth in the input price index over that timeframe.
    Effective for cost reporting periods beginning on or after July 1, 
1998, we revised and rebased our 1977 routine costs input price index 
and adopted a total expenses SNF input price index using FY 1992 as the 
base year. In the FY 2002 SNF PPS final rule (66 FR 39582), we rebased 
and revised the market basket to a base year of FY 1997. In the FY 2008 
SNF PPS final rule (72 FR 43425), we rebased and revised the market 
basket to a base year of FY 2004. In the FY 2014 SNF PPS final rule (78 
FR 47939), we revised and rebased the SNF market basket, which included 
updating the base year from FY 2004 to FY 2010. Lastly, in the FY 2018 
SNF PPS final rule (82 FR 36548), we revised and rebased the SNF market 
basket, which included updating the base year from FY 2010 to FY 2014. 
For FY 2022 and subsequent fiscal years, we are proposing to rebase the 
market basket to reflect 2018 Medicare-allowable total cost data 
(routine, ancillary, and capital-related) from freestanding SNFs and to 
revise applicable cost categories and price proxies used to determine 
the market basket. Medicare-allowable costs are those costs that are 
eligible to be paid under the SNF PPS. For example, the SNF market 
basket excludes home health agency (HHA) costs as these costs would be 
paid under the HHA PPS and, therefore, these costs are not SNF PPS 
Medicare-allowable costs. We propose to maintain our policy of using 
data from freestanding SNFs, which represent 93 percent of the total 
SNFs shown in Table 12. We believe using freestanding Medicare cost 
report (MCR) data, as opposed to the hospital-based SNF MCR data, for 
the proposed cost weight calculation is most appropriate because of the 
complexity of hospital-based data and the representativeness of the 
freestanding data. Because hospital-based SNF expenses are embedded in 
the hospital cost report, any attempt to incorporate data from 
hospital-based facilities requires more complex calculations and 
assumptions regarding the ancillary costs related to the hospital-based 
SNF unit. We believe the use of freestanding SNF cost report data is 
technically appropriate for reflecting the cost structures of SNFs 
serving Medicare beneficiaries.
    We are proposing to use 2018 as the base year as we believe that 
the 2018 MCRs represent the most recent, complete set of MCR data 
available to develop cost weights for SNFs at the time of rulemaking. 
We believe it is important to regularly rebase and revise the SNF 
market to reflect more recent data. Historically, the cost weights 
change minimally from year to year as they represent percent of total 
costs rather than cost levels; however, given the PHE for COVID-19, we 
will continue to monitor the upcoming MCR data to see if a more 
frequent rebasing schedule is necessary than our recent historical 
precedent of about every 4 years. The 2018 Medicare cost reports are 
for cost reporting periods beginning on and after October 1, 2017 and 
before October 1, 2018. While these dates appear to reflect fiscal year 
data, we note that a Medicare cost report that begins in this timeframe 
is generally classified as a ``2018 cost report''. For example, we 
found that of the available 2018 Medicare cost reports for SNFs, 
approximately 7 percent had an October 1, 2017 begin date, 
approximately 70 percent of the reports had a January 1, 2018 begin 
date, and approximately 12 percent had a July 1, 2018 begin date. For 
this reason, we are defining the base year of the market basket as 
``2018-based'' instead of ``FY 2018-based''.
    Specifically, we are proposing to develop cost category weights for 
the 2018-based SNF market basket in two stages. First, we are proposing 
to derive eight major expenditures or cost weights from the 2018 MCR 
data (CMS Form 2540-10, OMB NO. 0938-0463) for freestanding SNFs: Wages 
and Salaries; Employee Benefits; Contract Labor; Pharmaceuticals; 
Professional Liability

[[Page 19970]]

Insurance; Home Office/Related Organization Contract Labor; Capital-
related; and a residual ``All Other''. These are the same cost 
categories calculated using the 2014 MCR data for the 2014-based SNF 
market basket. The residual ``All Other'' category would reflect all 
remaining costs that are not captured in the other seven cost 
categories. Second, we are proposing to divide the residual ``All 
Other'' cost category into more detailed subcategories, using U.S. 
Department of Commerce Bureau of Economic Analysis' (BEA) 2012 
Benchmark Input-Output (I-O) ``use table before redefinitions, 
purchaser's value'' for the Nursing and Community Care Facilities 
industry (NAICS 623A00) aged to 2018 using applicable price proxy 
growth for each category of costs. Furthermore, we are proposing to 
continue to use the same overall methodology as was used for the 2014-
based SNF market basket to develop the capital related cost weights of 
the proposed 2018-based SNF market basket.
1. Development of Cost Categories and Weights
a. Use of Medicare Cost Report Data To Develop Major Cost Weights
    In order to create a market basket that is representative of 
freestanding SNF providers serving Medicare patients and to help ensure 
accurate major cost weights (which is the percent of total Medicare-
allowable costs, as defined below), we propose to apply edits to remove 
reporting errors and outliers. Specifically, the SNF MCRs used to 
calculate the market basket cost weights exclude any providers that 
reported costs less than or equal to zero for the following categories: 
Total facility costs (Worksheet B, part 1, column 18, line 100); total 
operating costs (Worksheet B, part 1, column 18, line 100 less 
Worksheet B, part 2, column 18, line 100); Medicare general inpatient 
routine service costs (Worksheet D, part 1, column 1, line 1); and 
Medicare PPS payments (Worksheet E, part 3, column 1, line 1). We also 
limited our sample to providers that had a MCR reporting period that 
was between 10 and 14 months. The final sample used included roughly 
13,500 MCRs (about 90 percent of the universe of SNF MCRs for 2018). 
The sample of providers is representative of the national universe of 
providers by region, by ownership-type (proprietary, nonprofit, and 
government), and by urban/rural status.
    Additionally, for all of the major cost weights, except Home 
Office/Related Organization Contract Labor costs, the data are trimmed 
to remove outliers (a standard statistical process) by: (1) Requiring 
that major expenses (such as Wages and Salaries costs) and total 
Medicare-allowable costs are greater than zero; and (2) excluding the 
top and bottom five percent of the major cost weight (for example, 
Wages and Salaries costs as a percent of total Medicare-allowable 
costs). We note that missing values are assumed to be zero, consistent 
with the methodology for how missing values are treated in the 2014-
based market basket methodology.
    For the Home Office/Related Organization Contract Labor cost 
weight, we propose to first exclude providers whose Home Office/Related 
Organization Contract Labor costs are greater than Medicare-allowable 
total costs and then apply a trim that excludes those reporters with a 
Home Office/Related Organization Contract Labor cost weight above the 
99th percentile. This allows providers with no Home Office/Related 
Organization Contract Labor costs to be included in the Home Office/
Related Organization Contract Labor cost weight calculation . If we 
were to trim the top and bottom Home Office/Related Organization 
Contract Labor cost weight, we would exclude providers with a zero cost 
weight and the MCR data (Worksheet S-2 line 45) indicate that not all 
SNF providers have a home office. Providers without a home office would 
report administrative costs that might typically be associated with a 
home office in the Wages and Salaries and Employee Benefits cost 
weights, or in the residual ``All-Other'' cost weight if they purchased 
these types of services from external contractors. We believe the 
trimming methodology that excludes those who report Home Office costs 
above the 99th percentile is appropriate as it removes extreme outliers 
while also allowing providers with zero Home Office/Related 
Organization Contract Labor costs to be included in the Home Office/
Related Organization Contract Labor cost weight calculation.
    The trimming process is done individually for each cost category so 
that providers excluded from one cost weight calculation are not 
automatically excluded from another cost weight calculation. We note 
that these proposed trimming methods are the same types of edits 
performed for the 2014-based SNF market basket, as well as other PPS 
market baskets (including but not limited to the IPPS market basket and 
HHA market basket). We believe this trimming process improves the 
accuracy of the data used to compute the major cost weights by removing 
possible data misreporting.
    The final weights of the proposed 2018-based SNF market basket are 
based on weighted means. For example, the aggregate Wages and Salaries 
cost weight, after trimming, is equal to the sum of total Medicare-
allowable wages and salaries of all providers divided by the sum of 
total Medicare-allowable costs for all providers in the sample. This 
methodology is consistent with the methodology used to calculate the 
2014-based SNF market basket cost weights and other PPS market basket 
cost weights. We note that for each of the cost weights, we evaluated 
the distribution of providers and costs by region, by ownership-type, 
and by urban/rural status. For all of the cost weights, with the 
exception of the PLI (which is discussed in more detail later), the 
trimmed sample was nationally representative.
    For all of the cost weights, we use Medicare-allowable total costs 
as the denominator (for example, Wages and Salaries cost weight = Wages 
and Salaries costs divided by Medicare-allowable total costs). 
Medicare-allowable total costs were equal to total costs (after 
overhead allocation) from Worksheet B part I, column 18, for lines 30, 
40 through 49, 51, 52, and 71 plus estimated Medicaid drug costs, as 
defined below. We included estimated Medicaid drug costs in the 
pharmacy cost weight, as well as the denominator for total Medicare-
allowable costs. This is the same methodology used for the 2014-based 
SNF market basket. The inclusion of Medicaid drug costs was finalized 
in the FY 2008 SNF PPS final rule (72 FR 43425 through 43430), and for 
the same reasons set forth in that final rule, we are proposing to 
continue to use this methodology in the proposed 2018-based SNF market 
basket.
    We describe the detailed methodology for obtaining costs for each 
of the eight cost categories determined from the Medicare Cost Report 
below. The methodology used in the 2014-based SNF market basket can be 
found in the FY 2018 SNF PPS final rule (82 FR 36548 through 36555).
    (1) Wages and Salaries: To derive Wages and Salaries costs for the 
Medicare-allowable cost centers, we are proposing first to calculate 
total facility wages and salaries costs as reported on Worksheet S-3, 
part II, column 3, line 1. We are then proposing to remove the wages 
and salaries attributable to non-Medicare-allowable cost centers (that 
is, excluded areas), as well as a portion of overhead wages and 
salaries attributable to these excluded areas. Excluded area wages and 
salaries are equal to wages and salaries as reported on Worksheet S-3, 
part II, column 3, lines 3, 4, and 7

[[Page 19971]]

through 11 plus nursing facility and non-reimbursable salaries from 
Worksheet A, column 1, lines 31, 32, 50, and 60 through 63.
    Overhead wages and salaries are attributable to the entire SNF 
facility; therefore, we are proposing to include only the proportion 
attributable to the Medicare-allowable cost centers. We are proposing 
to estimate the proportion of overhead wages and salaries attributable 
to the non-Medicare-allowable costs centers in two steps. First, we 
propose to estimate the ratio of excluded area wages and salaries (as 
defined above) to non-overhead total facility wages and salaries (total 
facility wages and salaries (Worksheet S-3, part II, column 3, line 1) 
less total overhead wages and salaries (Worksheet S-3, Part III, column 
3, line 14)). Next, we propose to multiply total overhead wages and 
salaries by the ratio computed in step 1. We excluded providers whose 
excluded areas wages and salaries were greater than total facility 
wages and salaries and/or their excluded area overhead wages and 
salaries were greater than total facility wages and salaries (about 50 
providers). This is similar to the methodology used to derive Wages and 
Salaries costs in the 2014-based SNF market basket. For the 2014-based 
SNF market basket, we estimated the proportion of overhead wages and 
salaries that is attributable to the non-Medicare allowable costs 
centers (that is, excluded areas) by multiplying the ratio of excluded 
area wages and salaries (as defined above) to total wages and salaries 
as reported on Worksheet S-3, Part II, column 3, line 1 by total 
overhead wages and salaries as reported on Worksheet S-3, Part III, 
column 3, line 14.
    (2) Employee Benefits: Medicare-allowable employee benefits are 
equal to total facility benefits as reported on Worksheet S-3, part II, 
column 3, lines 17 through 19 minus non-Medicare-allowable (that is, 
excluded area) employee benefits and minus a portion of overhead 
benefits attributable to these excluded areas. Excluded area employee 
benefits are derived by multiplying total excluded area wages and 
salaries (as defined above in the `Wages and Salaries' section) times 
the ratio of total facility benefits to total facility wages and 
salaries. This ratio of benefits to wages and salaries is defined as 
total facility benefit costs to total facility wages and salary costs 
(as reported on Worksheet S-3, part II, column 3, line 1). Likewise, 
the portion of overhead benefits attributable to the excluded areas is 
derived by multiplying overhead wages and salaries attributable to the 
excluded areas (as defined in the `Wages and Salaries' section) times 
the ratio of total facility benefit costs to total facility wages and 
salary costs (as defined above). Similar to the Wages and Salaries cost 
weight, we excluded providers whose excluded areas benefits were 
greater than total facility benefits and/or their excluded area 
overhead benefits were greater than total facility benefits (zero 
providers were excluded because of this edit). This is similar to the 
methodology used to derive Employee Benefits costs in the 2014-based 
SNF market basket.
    (3) Contract Labor: We are proposing to derive Medicare-allowable 
contract labor costs from Worksheet S-3, part II, column 3, line 14, 
which reflects costs for contracted direct patient care services (that 
is, nursing, therapeutic, rehabilitative, or diagnostic services 
furnished under contract rather than by employees and management 
contract services). This is the same methodology used to derive the 
Contract Labor costs in the 2014-based SNF market basket.
    (4) Pharmaceuticals: We are proposing to calculate pharmaceuticals 
costs using the non-salary costs from the Pharmacy cost center 
(Worksheet B, part I, column 0, line 11 less Worksheet A, column 1, 
line 11) and the Drugs Charged to Patients' cost center (Worksheet B, 
part I, column 0, line 49 less Worksheet A, column 1, line 49). Since 
these drug costs were attributable to the entire SNF and not limited to 
Medicare-allowable services, we propose to adjust the drug costs by the 
ratio of Medicare-allowable pharmacy total costs (Worksheet B, part I, 
column 11, for lines 30, 40 through 49, 51, 52, and 71) to total 
pharmacy costs from Worksheet B, part I, column 11, line 11. Worksheet 
B, part I allocates the general service cost centers, which are often 
referred to as ``overhead costs'' (in which pharmacy costs are 
included) to the Medicare-allowable and non-Medicare-allowable cost 
centers. This adjustment was made for those providers who reported 
Pharmacy cost center expenses. Otherwise, we assumed the non-salary 
Drugs Charged to Patients costs were Medicare-allowable. Since drug 
costs for Medicare patients are included in the SNF PPS per diem rate, 
a provider with Medicare days should have also reported costs in the 
Drugs Charged to Patient cost center. We found a small number of 
providers (roughly 60) did not report Drugs Charged to Patients' costs 
despite reporting Medicare days (an average of about 2,600 Medicare 
days per provider) and, therefore, these providers were excluded from 
the Pharmaceuticals cost weight calculations. This is similar to the 
methodology used for the 2014-based SNF market basket.
    Second, as was done for the 2014-based SNF market basket, we 
propose to continue to adjust the drug expenses reported on the MCR to 
include an estimate of total Medicaid drug costs, which are not 
represented in the Medicare-allowable drug cost weight. As stated 
previously in this section, the proposed 2018-based SNF market basket 
reflects total Medicare-allowable costs (that is, total costs for all 
payers for those services reimbursable under the SNF PPS). For the FY 
2006-based SNF market basket (72 FR 43426), commenters noted that the 
total pharmaceutical costs reported on the MCR did not include 
pharmaceutical costs for dual-eligible Medicaid patients as these were 
directly reimbursed by Medicaid. Since all of the other cost category 
weights reflect expenses associated with treating Medicaid patients 
(including the compensation costs for dispensing these drugs), we made 
an adjustment to include these Medicaid drug expenses so the market 
basket cost weights would be calculated consistently.
    Similar to the 2014-based SNF market basket, we propose to estimate 
Medicaid drug costs based on data representing dual-eligible Medicaid 
beneficiaries. Medicaid drug costs are estimated by multiplying 
Medicaid dual-eligible drug costs per day times the number of Medicaid 
days as reported in the Medicare-allowable skilled nursing cost center 
(Worksheet S-3, part I, column 5, line 1) in the SNF MCR. Medicaid 
dual-eligible drug costs per day (where the day represents an 
unduplicated drug supply day) were estimated using 2018 Part D claims 
for those dual-eligible beneficiaries who had a Medicare SNF stay 
during the year. The total drug costs per unduplicated day for 2018 of 
$24.48 represented all drug costs (including the drug ingredient cost, 
the dispensing fee, vaccine administration fee and sales tax) incurred 
during the 2018 calendar year for those dual-eligible beneficiaries who 
had a SNF Medicare stay during that 2018 calendar year. Therefore, they 
include drug costs incurred during a Medicaid SNF stay occurring in the 
2018 calendar year. By comparison, the 2014-based SNF market basket 
also relied on data from the Part D claims, which yielded a dual-
eligible Medicaid drug cost per day of $19.62 for 2014.
    We continue to believe that Medicaid dual-eligible beneficiaries 
are a reasonable proxy for the estimated drug costs per day incurred by 
Medicaid patients staying in a skilled nursing unit under a Medicaid 
stay. The skilled nursing unit is the Medicare-allowable unit in a SNF, 
which encompasses more

[[Page 19972]]

skilled nursing and rehabilitative care compared to a nursing facility 
or long-term care unit. We believe that Medicaid patients receiving 
this skilled nursing care would on average have similar drug costs per 
day to dual-eligible Medicare beneficiaries who have received Medicare 
skilled nursing care in the skilled nursing care unit during the year. 
We note that our previous analysis of the Part D claims data showed 
that Medicare beneficiaries with a SNF stay during the year have higher 
drug costs than Medicare patients without a SNF stay during the year. 
Also, in 2018, dual-eligible beneficiaries with a SNF stay during the 
year had drug costs per day of $24.48, which were approximately two 
times higher than the drug costs per day of $13.19 for nondual-eligible 
beneficiaries with a SNF Part A stay during the year.
    The Pharmaceuticals cost weight using only 2018 MCR data (without 
the inclusion of the Medicaid dual-eligible drug costs) is 2.6 percent, 
compared to the proposed Pharmaceuticals cost weight (including the 
adjustment for Medicaid dual-eligible drug costs) of 7.5 percent. The 
2014-based SNF market basket had a Pharmaceuticals cost weight using 
only 2014 MCR data without the inclusion of the Medicaid dual-eligible 
drug costs of 2.9 percent and a total Pharmaceuticals cost weight of 
7.3 percent. Therefore, the 0.2 percentage point increase in the 
Pharmaceuticals cost weight is a result of a 0.5-percentage point 
increase in the Medicaid dual-eligible drug cost weight (reflecting the 
25 percent increase in the Medicaid dual-eligible drug costs per day 
between 2014 and 2018) and a 0.3-percentage point decrease in the MCR 
drug cost weight. The decrease in the MCR drug cost weight was 
consistent, in aggregate, across urban and rural status SNFs as well as 
across for-profit, government, and nonprofit ownership type SNFs.
    (5) Professional Liability Insurance: We are proposing to calculate 
the professional liability insurance costs from Worksheet S-2 of the 
MCRs as the sum of premiums; paid losses; and self-insurance (Worksheet 
S-2, Part I, columns 1 through 3, line 41). This was the same 
methodology used to derive the Professional Liability costs for the 
2014-based SNF market basket.
    About 60 percent of SNFs (about 8,000) reported professional 
liability costs. After trimming, about 7,200 (reflecting about 850,000 
Skilled Nursing unit beds) were included in the calculation of the 
Professional Liability Insurance (PLI) cost weight for the proposed 
2018-based SNF market basket. These providers treated roughly 870,000 
Medicare beneficiaries and had a Medicare length of stay (LOS) of 33 
days, a skilled nursing unit occupancy rate of 80 percent, and an 
average skilled nursing unit bed size of 125 beds, which are all 
consistent with the national averages. We also verified that this 
sample of providers are representative of the national distribution of 
providers by ownership-type and urban/rural status. We note that the 
sample of providers is less consistent with the national distribution 
of providers by region; however, we performed a sensitivity analysis 
where the PLI cost weight was reweighted based on the national regional 
distribution and the impacts were less than a 0.1 percentage point on 
the cost weight.
    We note that based on prior comments during the rebasing of the 
2014-based SNF market basket, we reviewed in detail the AON 2018 
Professional and General Liability Benchmark for Long Term Care 
Providers \2\ that examines professional liability and general 
liability claim costs for long term care providers (including SNF beds, 
as well as independent living, assisted living, home health care, and 
rehabilitation facilities, representing about 186,000 long term care 
beds). This study, although informative, was not appropriate for 
calculating a PLI cost weight as it represents more than just SNFs 
serving Medicare patients and captures claim losses as opposed to PLI 
costs (premiums, paid losses, and self-insurance) incurred during a 
cost reporting year. We note that only 13 percent of providers reported 
PLI paid losses or PLI self-insurance costs on the MCR while over 90 
percent of providers reported PLI premiums indicating that the majority 
of losses incurred by Medicare participating SNFs will be covered by 
insurance premiums paid over time. Our comparison of the MCR data to 
the AON study for those select states' data provided did show 
consistencies between the average state PLI costs per bed relative to 
the national average (as measured by the MCR) and AON's loss per 
occupied bed relative to national values indicating that states with 
higher losses per occupied bed have higher PLI costs per total bed.
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    \2\ https://www.aon.com/risk-services/thought-leadership/report-2018-long-term-care.jsp.
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    We believe the MCR data continues to be the most appropriate data 
source to calculate the PLI cost weight for the proposed 2018-based SNF 
market basket as it is representative of SNFs serving Medicare 
beneficiaries and reflects PLI costs (premiums, paid losses, and self-
insurance) incurred during the provider's cost reporting year.
    (6) Capital-Related: We are proposing to derive the Medicare-
allowable capital-related costs from Worksheet B, part II, column 18 
for lines 30, 40 through 49, 51, 52, and 71. This is the same 
methodology to derive capital-related costs used in the 2014-based SNF 
market basket.
    (7) Home Office/Related Organization Contract Labor Costs: We are 
proposing to calculate Medicare-allowable Home Office/Related 
Organization Contract Labor costs to be equal to data reported on 
Worksheet S-3, part II, column 3, line 16. We note that for the 2014-
based SNF market basket we also used Worksheet S-3, part II, column 3, 
line 16 (Home office salaries & wage related costs) to determine these 
expenses; however, we referred to this category as Home Office Contract 
Labor Costs. The instructions for this data state ``enter the salaries 
and wage related costs (as defined on lines 17 and 18 below) paid to 
personnel who are affiliated with a home office and/or related 
organization, who provide services to the SNF and/or NF, and whose 
salaries are not included on Worksheet A, column 1,'' and therefore, we 
are referring to this cost category as Home Office/Related Organization 
Contract Labor costs. Furthermore, for this rebasing we are no longer 
adjusting these expenses by the ratio of Medicare allowable operating 
costs to total facility operating costs as done for the 2014-based SNF 
market basket as the instructions indicate these expenses are for the 
SNF and NF units.
    About 7,000 providers (about 53 percent) in 2018 reported having a 
home office (as reported on Worksheet S-2, part I, line 45); a lower 
share of providers than those in the 2014-based SNF market basket. As 
discussed in section VI.A.1. of this proposed rule, providers without a 
home office can incur these expenses directly by having their own 
staff, for which the costs would be included in the Wages and Salaries 
and Employee Benefits cost weights. Alternatively, providers without a 
home office could also purchase related services from external 
contractors for which these expenses would be captured in the residual 
``All-Other'' cost weight. For this reason, unlike the other major cost 
weights described previously, we did not exclude providers that did not 
report Home Office/Related Organization Contract Labor costs. We note 
that this is similar to the methodology that was used for other PPS 
market baskets such as the 2017-based LTCH market basket (85 FR 58911).

[[Page 19973]]

    (8) All Other (residual): The ``All Other'' cost weight is a 
residual, calculated by subtracting the major cost weights (Wages and 
Salaries, Employee Benefits, Contract Labor, Pharmaceuticals, 
Professional Liability Insurance, Capital-Related, and Home Office/
Related Organization Contract Labor) from 100.
    Table 12 shows the proposed major cost categories and their 
respective cost weights as derived from the 2018 Medicare cost reports.

   Table 12--Major Cost Categories Derived From the SNF Medicare Cost
                                Reports *
------------------------------------------------------------------------
                                          Proposed 2018-
          Major cost categories                based        2014-based
------------------------------------------------------------------------
Wages and Salaries......................            44.1            44.3
Employee Benefits.......................             8.6             9.3
Contract Labor..........................             7.5             6.8
Pharmaceuticals.........................             7.5             7.3
Professional Liability Insurance........             1.1             1.1
Capital-related.........................             8.2             7.9
Home Office/Related Organization                     0.7             0.7
 Contract Labor.........................
All other (residual)....................            22.3            22.6
------------------------------------------------------------------------
* Total may not sum to 100 due to rounding.

    Compared to the 2014-based SNF market basket, the Wages and 
Salaries cost weight and the Employee Benefits cost weight as 
calculated directly from the Medicare cost reports decreased by 0.2 
percentage point and 0.7 percentage point, respectively. The Contract 
Labor cost weight increased 0.7 percentage point and so in aggregate, 
the Compensation cost weight decreased 0.2 percentage point.
    As we did for the 2014-based SNF market basket (82 FR 36555), we 
are proposing to allocate contract labor costs to the Wages and 
Salaries and Employee Benefits cost weights based on their relative 
proportions under the assumption that contract labor costs are 
comprised of both wages and salaries and employee benefits. The 
contract labor allocation proportion for wages and salaries is equal to 
the Wages and Salaries cost weight as a percent of the sum of the Wages 
and Salaries cost weight and the Employee Benefits cost weight. Using 
the 2018 Medicare cost report data, this percentage is 84 percent (1 
percentage point higher than the percent in the 2014-based SNF market 
basket); therefore, we are proposing to allocate approximately 84 
percent of the Contract Labor cost weight to the Wages and Salaries 
cost weight and 16 percent to the Employee Benefits cost weight.
    Table 13 shows the Wages and Salaries and Employee Benefits cost 
weights after contract labor allocation for the proposed 2018-based SNF 
market basket and the 2014-based SNF market basket.

  Table 13--Wages and Salaries and Employee Benefits Cost Weights After
                        Contract Labor Allocation
------------------------------------------------------------------------
                                          Proposed 2018-
          Major cost categories            based market     2014-based
                                              basket       market basket
------------------------------------------------------------------------
Wages and Salaries......................            50.4            50.0
Employee Benefits.......................             9.9            10.5
------------------------------------------------------------------------

b. Derivation of the Detailed Operating Cost Weights
    To further divide the ``All Other'' residual cost weight estimated 
from the 2018 Medicare cost report data into more detailed cost 
categories, we are proposing to use the 2012 Benchmark I-O ``Use 
Tables/Before Redefinitions/Purchaser Value'' for Nursing and Community 
Care Facilities industry (NAICS 623A00), published by the Census 
Bureau's, Bureau of Economic Analysis (BEA). These data are publicly 
available at the following website at http://www.bea.gov/industry/io_annual.htm. The BEA Benchmark I-O data are generally scheduled for 
publication every 5 years with 2012 being the most recent year for 
which data is available. The 2012 Benchmark I-O data are derived from 
the 2012 Economic Census and are the building blocks for BEA's economic 
accounts; therefore, they represent the most comprehensive and complete 
set of data on the economic processes or mechanisms by which output is 
produced and distributed.\3\ BEA also produces Annual I-O estimates. 
However, while based on a similar methodology, these estimates are less 
comprehensive and provide less detail than benchmark data. 
Additionally, the annual I-O data are subject to revision once 
benchmark data become available. For these reasons, we propose to 
inflate the 2012 Benchmark I-O data aged forward to 2018 by applying 
the annual price changes from the respective price proxies to the 
appropriate market basket cost categories that are obtained from the 
2012 Benchmark I-O data. Next, the relative shares of the cost shares 
that each cost category represents to the total residual I-O costs are 
calculated. These resulting 2018 cost shares of the I-O data are 
applied to the ``All Other'' residual cost weight to obtain detailed 
cost weights for the residual costs for the proposed 2018-based SNF 
market basket. For example, the cost for Food: Direct Purchases 
represents 11.3 percent of the sum of the ``All Other'' 2012 Benchmark 
I-O Expenditures inflated to 2018. Therefore, the Food: Direct 
Purchases cost weight is 2.5 percent of the proposed 2018-based SNF 
market basket (11.3 percent x 22.3 percent = 2.5 percent). For the 
2014-based SNF market basket (82 FR 36553), we used a similar 
methodology utilizing the 2007 Benchmark I-O data (aged to 2014).
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    \3\ http://www.bea.gov/papers/pdf/IOmanual_092906.pdf.
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    Using this methodology, we are proposing to derive 19 detailed SNF 
market basket cost category weights from the proposed 2018-based SNF 
market basket ``All Other'' residual cost

[[Page 19974]]

weight (22.3 percent). These categories are: (1) Fuel: Oil and Gas; (2) 
Electricity and Other Non-Fuel Utilities; (3) Food: Direct Purchases; 
(4) Food: Contract Services; (5) Chemicals; (6) Medical Instruments and 
Supplies; (7) Rubber and Plastics; (8) Paper and Printing Products; (9) 
Apparel; (10) Machinery and Equipment; (11) Miscellaneous Products; 
(12) Professional Fees: Labor-Related; (13) Administrative and 
Facilities Support Services; (14) Installation, Maintenance, and Repair 
Services; (15) All Other: Labor-Related Services; (16) Professional 
Fees: Nonlabor-Related; (17) Financial Services; (18) Telephone 
Services; and (19) All Other: Nonlabor-Related Services. The 2014-based 
SNF market basket had separate cost categories for Postage services and 
Water and Sewerage. Due to the small weights (less than 0.1 percentage 
point), we are proposing that Postage costs be included in the All 
Other: Non-labor-Related Services and Water and Sewerage costs be 
included in the Electricity and Other Non-Fuel Utilities category.
    We note that the machinery and equipment expenses are for equipment 
that is paid for in a given year and not depreciated over the asset's 
useful life. Depreciation expenses for moveable equipment are accounted 
for in the capital component of the proposed 2018-based SNF market 
basket (described in section IV.A.1.c. of this proposed rule).
c. Derivation of the Detailed Capital Cost Weights
    Similar to the 2014-based SNF market basket, we further divided the 
Capital-related cost weight into: Depreciation, Interest, Lease and 
Other Capital-related cost weights.
    We calculated the depreciation cost weight (that is, depreciation 
costs excluding leasing costs) using depreciation costs from Worksheet 
S-2, column 1, lines 20 and 21. Since the depreciation costs reflect 
the entire SNF facility (Medicare and non-Medicare-allowable units), we 
used total facility capital costs (Worksheet B, Part I, Column 18, line 
100) as the denominator. This methodology assumes that the depreciation 
of an asset is the same regardless of whether the asset was used for 
Medicare or non-Medicare patients. This methodology yielded 
depreciation costs as a percent of capital costs of 25.3 percent for 
2018. We then apply this percentage to the proposed 2018-based SNF 
market basket Medicare-allowable Capital-related cost weight of 8.2 
percent, yielding a Medicare-allowable depreciation cost weight 
(excluding leasing expenses, which is described in more detail below) 
of 2.1 percent. To further disaggregate the Medicare-allowable 
depreciation cost weight into fixed and moveable depreciation, we are 
proposing to use the 2018 SNF MCR data for end-of-the-year capital 
asset balances as reported on Worksheet A-7. The 2018 SNF MCR data 
showed a fixed/moveable split of 86/14. The 2014-based SNF market 
basket, which utilized the same data from the 2014 MCRs, had a fixed/
moveable split of 83/17.
    We also derived the interest expense share of capital-related 
expenses from 2018 SNF MCR data, specifically from Worksheet A, column 
2, line 81. Similar to the depreciation cost weight, we calculated the 
interest cost weight using total facility capital costs. This 
methodology yielded interest costs as a percent of capital costs of 
22.8 percent for 2018. We then apply this percentage to the proposed 
2018-based SNF market basket Medicare-allowable Capital-related cost 
weight of 8.2 percent, yielding a Medicare-allowable interest cost 
weight (excluding leasing expenses) of 1.9 percent. As done with the 
last rebasing (82 FR 36556), we are proposing to determine the split of 
interest expense between for-profit and not-for-profit facilities based 
on the distribution of long-term debt outstanding by type of SNF (for-
profit or not-for-profit/government) from the 2018 SNF MCR data. We 
estimated the split between for-profit and not-for-profit interest 
expense to be 25/75 percent compared to the 2014-based SNF market 
basket with 27/73 percent.
    Because the detailed data were not available in the MCRs, we used 
the most recent 2017 Census Bureau Service Annual Survey (SAS) data to 
derive the capital-related expenses attributable to leasing and other 
capital-related expenses. The 2014-based SNF market basket used the 
2014 SAS data. We note that we are proposing to use the 2017 SAS data 
because the Census Bureau no longer publishes these detailed capital-
related expenses effective for 2018.
    Based on the 2017 SAS data, we determined that leasing expenses are 
62 percent of total leasing and capital-related expenses costs. In the 
2014-based SNF market basket, leasing costs represent 63 percent of 
total leasing and capital-related expenses costs. We then apply this 
percentage to the proposed 2018-based SNF market basket residual 
Medicare-allowable capital costs of 4.2 percent derived from 
subtracting the Medicare-allowable depreciation cost weight and 
Medicare-allowable interest cost weight from the 2018-based SNF market 
basket of total Medicare-allowable capital cost weight (8.2 percent-2.1 
percent-1.9 percent = 4.2 percent). This produces the proposed 2018-
based SNF Medicare-allowable leasing cost weight of 2.6 percent and 
all-other capital-related cost weight of 1.6 percent.
    Lease expenses are not broken out as a separate cost category in 
the SNF market basket, but are distributed among the cost categories of 
depreciation, interest, and other capital-related expenses, reflecting 
the assumption that the underlying cost structure and price movement of 
leasing expenses is similar to capital costs in general. As was done 
with past SNF market baskets and other PPS market baskets, we assumed 
10 percent of lease expenses are overhead and assigned them to the 
other capital-related expenses cost category. This is based on the 
assumption that leasing expenses include not only depreciation, 
interest, and other capital-related costs but also additional costs 
paid to the lessor. We distributed the remaining lease expenses to the 
three cost categories based on the proportion of depreciation, 
interest, and other capital-related expenses to total capital costs, 
excluding lease expenses.
    Table 14 shows the capital-related expense distribution (including 
expenses from leases) in the proposed 2018-based SNF market basket and 
the 2014-based SNF market basket.

 Table 14--Comparison of the Capital-Related Expense Distribution of the
   Proposed 2018-Based SNF Market Basket and the 2014-Based SNF Market
                                 Basket
------------------------------------------------------------------------
                                          Proposed 2018-
              Cost category                  based SNF    2014-based SNF
                                           market basket   market basket
------------------------------------------------------------------------
Capital-related Expenses................             8.2             7.9
    Total Depreciation..................             3.0             2.9

[[Page 19975]]

 
    Total Interest......................             2.7             3.0
    Other Capital-related Expenses......             2.6             2.0
------------------------------------------------------------------------
Note: The cost weights are calculated using three decimal places. For
  presentational purposes, we are displaying one decimal and, therefore,
  the detail capital cost weights may not add to the total capital-
  related expenses cost weight due to rounding.

    Table 15 presents the proposed 2018-based SNF market basket and the 
2014-based SNF market basket.

   Table 15--Proposed 2018-Based SNF Market Basket and 2014-Based SNF
                              Market Basket
------------------------------------------------------------------------
                                          Proposed 2018-
              Cost category                  based SNF    2014-Based SNF
                                           market basket   market basket
------------------------------------------------------------------------
Total...................................           100.0           100.0
Compensation............................            60.2            60.4
    Wages and Salaries \1\..............            50.4            50.0
    Employee Benefits \1\...............             9.9            10.5
Utilities...............................             1.5             2.6
    Electricity and Other Non-Fuel                   1.0             1.4
     Utilities..........................
    Fuel: Oil and Gas...................             0.4             1.3
Professional Liability Insurance........             1.1             1.1
All Other...............................            29.0            27.9
    Other Products......................            17.6            14.3
        Pharmaceuticals.................             7.5             7.3
        Food: Direct Purchase...........             2.5             3.1
        Food: Contract Purchase.........             4.3             0.7
        Chemicals.......................             0.2             0.2
        Medical Instruments and Supplies             0.6             0.6
        Rubber and Plastics.............             0.7             0.8
        Paper and Printing Products.....             0.5             0.8
        Apparel.........................             0.5             0.3
        Machinery and Equipment.........             0.5             0.3
        Miscellaneous Products..........             0.3             0.3
All Other Services......................            11.5            13.6
    Labor-Related Services..............             6.4             7.4
        Professional Fees: Labor-related             3.5             3.8
        Installation, Maintenance, and               0.6             0.6
         Repair Services................
        Administrative and Facilities                0.4             0.5
         Support........................
        All Other: Labor-Related                     1.9             2.5
         Services.......................
    Non Labor-Related Services..........             5.1             6.2
        Professional Fees: Nonlabor-                 2.0             1.8
         Related........................
        Financial Services..............             1.3             2.0
        Telephone Services..............             0.3             0.5
        All Other: Nonlabor-Related                  1.5             2.0
         Services \3\...................
Capital-Related Expenses................             8.2             7.9
    Total Depreciation..................             3.0             2.9
        Building and Fixed Equipment....             2.5             2.5
        Movable Equipment...............             0.4             0.4
    Total Interest......................             2.7             3.0
        For-Profit SNFs.................             0.7             0.8
        Government and Nonprofit SNFs...             2.0             2.1
    Other Capital-Related Expenses......             2.6             2.0
------------------------------------------------------------------------
Note: The cost weights are calculated using three decimal places. For
  presentational purposes, we are displaying one decimal and, therefore,
  the detailed cost weights may not add to the aggregate cost weights or
  to 100.0 due to rounding.
\1\ Contract labor is distributed to wages and salaries and employee
  benefits based on the share of total compensation that each category
  represents.
\2\ Water and Sewerage costs are included in the Electricity and Other
  Non-Fuel Utilities cost category in the proposed 2018-based SNF market
  basket.
\3\ Postage costs are included in the All Other Non-labor-related cost
  category in the proposed 2018-based SNF market basket.


[[Page 19976]]

2. Price Proxies Used To Measure Operating Cost Category Growth
    After developing the 27 cost weights for the proposed 2018-based 
SNF market basket, we selected the most appropriate wage and price 
proxies currently available to represent the rate of change for each 
expenditure category. With four exceptions (three for the capital-
related expenses cost categories and one for Professional Liability 
Insurance (PLI)), we base the wage and price proxies on Bureau of Labor 
Statistics (BLS) data, and group them into one of the following BLS 
categories:
     Employment Cost Indexes. Employment Cost Indexes (ECIs) 
measure the rate of change in employment wage rates and employer costs 
for employee benefits per hour worked. These indexes are fixed-weight 
indexes and strictly measure the change in wage rates and employee 
benefits per hour. ECIs are superior to Average Hourly Earnings (AHE) 
as price proxies for input price indexes because they are not affected 
by shifts in occupation or industry mix, and because they measure pure 
price change and are available by both occupational group and by 
industry. The industry ECIs are based on the 2012 NAICS and the 
occupational ECIs are based on the 2000 and 2010 Standard Occupational 
Classification System (SOC).
     Producer Price Indexes. Producer Price Indexes (PPIs) 
measure the average change over time in the selling prices received by 
domestic producers for their output. The prices included in the PPI are 
from the first commercial transaction for many products and some 
services (https://www.bls.gov/ppi/).
     Consumer Price Indexes. Consumer Price Indexes (CPIs) 
measure the average change over time in the prices paid by urban 
consumers for a market basket of consumer goods and services (https://www.bls.gov/cpi/). CPIs are only used when the purchases are similar to 
those of retail consumers rather than purchases at the producer level, 
or if no appropriate PPIs are available.
    We evaluated the price proxies using the criteria of reliability, 
timeliness, availability, and relevance. Reliability indicates that the 
index is based on valid statistical methods and has low sampling 
variability. Widely accepted statistical methods ensure that the data 
were collected and aggregated in a way that can be replicated. Low 
sampling variability is desirable because it indicates that the sample 
reflects the typical members of the population. (Sampling variability 
is variation that occurs by chance because only a sample was surveyed 
rather than the entire population.) Timeliness implies that the proxy 
is published regularly, preferably at least once a quarter. The market 
baskets are updated quarterly, and therefore, it is important for the 
underlying price proxies to be up-to-date, reflecting the most recent 
data available. We believe that using proxies that are published 
regularly (at least quarterly, whenever possible) helps to ensure that 
we are using the most recent data available to update the market 
basket. We strive to use publications that are disseminated frequently, 
because we believe that this is an optimal way to stay abreast of the 
most current data available. Availability means that the proxy is 
publicly available. We prefer that our proxies are publicly available 
because this will help ensure that our market basket updates are as 
transparent to the public as possible. In addition, this enables the 
public to be able to obtain the price proxy data on a regular basis. 
Finally, relevance means that the proxy is applicable and 
representative of the cost category weight to which it is applied. The 
CPIs, PPIs, and ECIs that we have selected to propose in this 
regulation meet these criteria. Therefore, we believe that they 
continue to be the best measure of price changes for the cost 
categories to which they would be applied.
    Table 20 lists all price proxies for the proposed 2018-based SNF 
market basket. Below is a detailed explanation of the price proxies 
used for each operating cost category.
     Wages and Salaries: We are proposing to use the ECI for 
Wages and Salaries for Private Industry Workers in Nursing Care 
Facilities (NAICS 6231; BLS series code CIU2026231000000I) to measure 
price growth of this category. NAICS 623 includes facilities that 
provide a mix of health and social services, with many of the health 
services being largely some level of nursing services. Within NAICS 623 
is NAICS 6231, which includes nursing care facilities primarily engaged 
in providing inpatient nursing and rehabilitative services. These 
facilities, which are most comparable to Medicare-certified SNFs, 
provide skilled nursing and continuous personal care services for an 
extended period of time, and, therefore, have a permanent core staff of 
registered or licensed practical nurses. This is the same index used in 
the 2014-based SNF market basket.
     Employee Benefits: We are proposing to use the ECI for 
Benefits for Nursing Care Facilities (NAICS 6231) to measure price 
growth of this category. The ECI for Benefits for Nursing Care 
Facilities is calculated using BLS's total compensation (BLS series ID 
CIU2016231000000I) for nursing care facilities series and the relative 
importance of wages and salaries within total compensation. We believe 
this constructed ECI series is technically appropriate for the reason 
stated above in the Wages and Salaries price proxy section. This is the 
same index used in the 2014-based SNF market basket.
     Electricity and Other Non-Fuel Utilities: We are proposing 
to use the PPI Commodity for Commercial Electric Power (BLS series code 
WPU0542) to measure the price growth of this cost category as 
Electricity costs account for 93 percent of these expenses. This is the 
same index used for the Electricity cost category in the 2014-based SNF 
market basket. As previously noted, we are proposing to include Water 
and Sewerage costs within the Electricity and Other Non-Fuel Utilities 
cost category, and to no longer use the CPI All Urban for Water and 
Sewerage Maintenance as we did for the 2014-based SNF market basket, 
due to the small size of this estimated cost weight (less than 0.1 
percent).
     Fuel: Oil and Gas: We are proposing to change the proxy 
used for the Fuel: Oil and Gas cost category. Our analysis of the 
Bureau of Economic Analysis' 2012 Benchmark I-O data for Nursing and 
Community Care Facilities shows approximately 96 percent of SNF Fuel: 
Oil and Gas expenses are for Petroleum Refineries (NAICS 324110), 
Natural gas (NAICS 221200), and Other Petroleum and Coal Products 
Manufacturing (NAICS 324190). We are proposing to create a blended 
index based on those three NAICS chemical expenses listed above that 
account for 96 percent of SNF chemical expenses. We are proposing to 
create this blend based on each NAICS' expenses as a share of their 
sum. Therefore, we are proposing a blended proxy of 61 percent of the 
PPI Industry for Petroleum Refineries (BLS series code PCU32411-32411), 
7 percent of the PPI Commodity for Natural Gas (BLS series code 
WPU0531), and 32 percent of the PPI for Other Petroleum and Coal 
Products manufacturing (BLS series code PCU32419-32419).
    The 2014-based SNF market basket also used a blended chemical proxy 
that was based on 2007 Benchmark I-O data. We believe our proposed 
Fuel: Oil and Gas blended index for the 2018-based SNF market basket is 
technically appropriate as it reflects more recent data on SNFs 
purchasing patterns. Table 16 provides the weights for the proposed 
2018-based blended chemical index and the 2014-based blended chemical 
index.

[[Page 19977]]



       Table 16--Proposed Fuel: Oil and Gas Blended Index Weights
------------------------------------------------------------------------
                                          Proposed 2018-
       NAICS             Price proxy        based index     2014-based
                                                (%)          index (%)
------------------------------------------------------------------------
221200............  PPI Commodity for                  7              35
                     Natural Gas.
324110............  PPI Industry for                  61              65
                     Petroleum
                     Refineries.
324190............  PPI for Other                     32             n/a
                     Petroleum and Coal
                     Products
                     manufacturing.
                                         -------------------------------
    Total.........  ....................             100             100
------------------------------------------------------------------------

     Professional Liability Insurance: We are proposing to use 
the CMS Hospital Professional Liability Insurance Index to measure 
price growth of this category. We were unable to find a reliable data 
source that collects SNF-specific PLI data. Therefore, we are proposing 
to use the CMS Hospital Professional Liability Index, which tracks 
price changes for commercial insurance premiums for a fixed level of 
coverage, holding non-price factors constant (such as a change in the 
level of coverage). This is the same index used in the 2014-based SNF 
market basket. We believe this is an appropriate proxy to measure the 
price growth associated of SNF professional liability insurance as it 
captures the price inflation associated with other medical institutions 
that serve Medicare patients.
     Pharmaceuticals: We are proposing to use the PPI Commodity 
for Pharmaceuticals for Human Use, Prescription (BLS series code 
WPUSI07003) to measure the price growth of this cost category. This is 
the same index used in the 2014-based SNF market basket.
     Food: Wholesale Purchases: We are proposing to use the PPI 
Commodity for Processed Foods and Feeds (BLS series code WPU02) to 
measure the price growth of this cost category. This is the same index 
used in the 2014-based SNF market basket.
     Food: Retail Purchase: We are proposing to use the CPI All 
Urban for Food Away From Home (All Urban Consumers) (BLS series code 
CUUR0000SEFV) to measure the price growth of this cost category. This 
is the same index used in the 2014-based SNF market basket.
     Chemicals: For measuring price change in the Chemicals 
cost category, we are proposing to use a blended PPI composed of the 
Industry PPIs for Other Basic Organic Chemical Manufacturing (NAICS 
325190) (BLS series code PCU32519-32519), Soap and Cleaning Compound 
Manufacturing (NAICS 325610) (BLS series code PCU32561-32561), and 
Other Miscellaneous Chemical Product Manufacturing (NAICS 325998) (BLS 
series code PCU325998325998).
    Using the 2012 Benchmark I-O data, we found that these three NAICS 
industries accounted for approximately 96 percent of SNF chemical 
expenses. The remaining four percent of SNF chemical expenses are for 
three other incidental NAICS chemicals industries such as Paint and 
Coating Manufacturing. We are proposing to create a blended index based 
on those three NAICS chemical expenses listed above that account for 96 
percent of SNF chemical expenses. We are proposing to create this blend 
based on each NAICS' expenses as a share of their sum. These expenses 
as a share of their sum are listed in Table 17.
    The 2014-based SNF market basket also used a blended chemical proxy 
that was based on 2007 Benchmark I-O data. We believe our proposed 
chemical blended index for the 2018-based SNF market basket is 
technically appropriate as it reflects more recent data on SNFs 
purchasing patterns. Table 17 provides the weights for the proposed 
2018-based blended chemical index and the 2014-based blended chemical 
index.

            Table 17--Proposed Chemical Blended Index Weights
------------------------------------------------------------------------
                                          Proposed 2018-
       NAICS             Price proxy        based index     2014-based
                                                (%)          index (%)
------------------------------------------------------------------------
325190............  PPI for Other Basic               34              22
                     Organic Chemical
                     Manufacturing.
325610............  PPI for Soap and                  21              37
                     Cleaning Compound
                     Manufacturing.
325998............  PPI for Other                     45              41
                     Miscellaneous
                     Chemical Product
                     Manufacturing.
                                         -------------------------------
    Total.........  ....................             100             100
------------------------------------------------------------------------

     Medical Instruments and Supplies: We are proposing to 
change the proxy used for the Medical Instruments and Supplies cost 
weight. The 2012 Benchmark I-O data shows 46 percent of medical 
instruments and supply costs are for Surgical and medical instrument 
manufacturing costs (NAICS 339112) and 54 percent are for Surgical 
appliance and supplies manufacturing costs (NAICS 339113). To proxy the 
price changes associated with NAICS 339112, we propose using the PPI--
Commodity--Surgical and medical instruments (BLS series code WPU1562). 
This the same price proxy we used in the 2014-based SNF market basket. 
To proxy the price changes associated with NAICS 339113, we are 
proposing to use 50 percent for the PPI--Commodity--Medical and 
surgical appliances and supplies (BLS series code WPU1563) and 50 
percent for the PPI Commodity data for Miscellaneous products-Personal 
safety equipment and clothing (BLS series code WPU1571). The latter 
price proxy would reflect personal protective equipment including but 
not limited to face shields and protective clothing. The 2012 Benchmark 
I-O data does not provide specific expenses for personal protective 
equipment (which would be reflected in the NAICS 339113 expenses); 
however, we recognize that this category reflects costs faced by SNFs. 
In absence of any specific cost data on personal protective equipment, 
we are proposing to include the PPI Commodity data for

[[Page 19978]]

Miscellaneous products-Personal safety equipment and clothing (BLS 
series code WPU1571) in the blended proxy for Medical Instruments and 
Supplies cost category with a weight of 27 percent (that is, 50 percent 
of the NAICS 339113 expenses as a percent of the sum of NAICS 339113 
and NAICS 339112 expenses from the I-O).
    The 2014-based SNF market basket used a blend composed of 60 
percent of the PPI Commodity for Medical and Surgical Appliances and 
Supplies (BLS series code WPU1563) and 40 percent of the PPI Commodity 
for Surgical and Medical Instruments (BLS series code WPU1562). Table 
18 provides the proposed Medical Instruments and Supplies cost weight 
blended price proxy.

    Table 18--Proposed Medical Instruments and Supplies Blended Index
                                 Weights
------------------------------------------------------------------------
                                          Proposed 2018-
       NAICS             Price proxy        based index     2014-based
                                                (%)          index (%)
------------------------------------------------------------------------
339112............  PPI--Commodity--Surg              46              40
                     ical and medical
                     instruments
                     (WUI1562).
339113............  PPI--Commodity--Medi              27              60
                     cal and surgical
                     appliances and
                     supplies (WPU1563).
                    PPI Commodity data                27             n/a
                     for Miscellaneous
                     products--Personal
                     safety equipment
                     and clothing
                     (WPU1571).
                                         -------------------------------
    Total.........  ....................             100             100
------------------------------------------------------------------------

     Rubber and Plastics: We are proposing to use the PPI 
Commodity for Rubber and Plastic Products (BLS series code WPU07) to 
measure price growth of this cost category. This is the same index used 
in the 2014-based SNF market basket.
     Paper and Printing Products: We are proposing to use the 
PPI Commodity for Converted Paper and Paperboard Products (BLS series 
code WPU0915) to measure the price growth of this cost category. This 
is the same index used in the 2014-based SNF market basket.
     Apparel: We are proposing to use the PPI Commodity for 
Apparel (BLS series code WPU0381) to measure the price growth of this 
cost category. This is the same index used in the 2014-based SNF market 
basket.
     Machinery and Equipment: We are proposing to use the PPI 
Commodity for Machinery and Equipment (BLS series code WPU11) to 
measure the price growth of this cost category. This is the same index 
used in the 2014-based SNF market basket.
     Miscellaneous Products: For measuring price change in the 
Miscellaneous Products cost category, we are proposing to use the PPI 
Commodity for Finished Goods less Food and Energy (BLS series code 
WPUFD4131). Both food and energy are already adequately represented in 
separate cost categories and should not also be reflected in this cost 
category. This is the same index used in the 2014-based SNF market 
basket.
     Professional Fees: Labor-Related: We are proposing to use 
the ECI for Total Compensation for Private Industry Workers in 
Professional and Related (BLS series code CIU2010000120000I) to measure 
the price growth of this category. This is the same index used in the 
2014-based SNF market basket.
     Administrative and Facilities Support Services: We are 
proposing to use the ECI for Total Compensation for Private Industry 
Workers in Office and Administrative Support (BLS series code 
CIU2010000220000I) to measure the price growth of this category. This 
is the same index used in the 2014-based SNF market basket.
     Installation, Maintenance and Repair Services: We are 
proposing to use the ECI for Total Compensation for All Civilian 
Workers in Installation, Maintenance, and Repair (BLS series code 
CIU1010000430000I) to measure the price growth of this new cost 
category. This is the same index used in the 2014-based SNF market 
basket.
     All Other: Labor-Related Services: We are proposing to use 
the ECI for Total Compensation for Private Industry Workers in Service 
Occupations (BLS series code CIU2010000300000I) to measure the price 
growth of this cost category. This is the same index used in the 2014-
based SNF market basket.
     Professional Fees: NonLabor-Related: We are 
proposing to use the ECI for Total Compensation for Private Industry 
Workers in Professional and Related (BLS series code CIU2010000120000I) 
to measure the price growth of this category. This is the same index 
used in the 2014-based SNF market basket.
     Financial Services: We are proposing to use the 
ECI for Total Compensation for Private Industry Workers in Financial 
Activities (BLS series code CIU201520A000000I) to measure the price 
growth of this cost category. This is the same index used in the 2014-
based SNF market basket.
     Telephone Services: We are proposing to use the 
CPI All Urban for Telephone Services (BLS series code CUUR0000SEED) to 
measure the price growth of this cost category. This is the same index 
used in the 2014-based SNF market basket.
     All Other: NonLabor-Related Services: We are proposing to 
use the CPI All Urban for All Items Less Food and Energy (BLS series 
code CUUR0000SA0L1E) to measure the price growth of this cost category. 
This is the same index used in the 2014-based SNF market basket. As 
previously noted, we are proposing to include Postage costs within the 
All Other: NonLabor-Related Services cost category, and to no longer 
use the CPI All Urban for Postage as we did for the 2014-based SNF 
market basket, due to the small size of this estimated cost weight 
(less than 0.1 percent).
3. Price Proxies Used To Measure Capital Cost Category Growth
    We are proposing to apply the same capital price proxies as were 
used in the 2014-based SNF market basket, with the exception of the 
For-profit interest cost category, and below is a detailed explanation 
of the price proxies used for each capital cost category. We also are 
proposing to continue to vintage weight the capital price proxies for 
Depreciation and Interest to capture the long-term consumption of 
capital. This vintage weighting method is the same method that was used 
for the 2014-based SNF market basket and is described below.
     Depreciation--Building and Fixed Equipment: We are 
proposing to use the BEA Chained Price Index for Private Fixed 
Investment in Structures, Nonresidential, Hospitals and Special Care 
(BEA Table 5.4.4. Price Indexes for Private Fixed Investment in 
Structures by Type). This BEA index is intended to capture prices for 
construction of facilities such as hospitals, nursing

[[Page 19979]]

homes, hospices, and rehabilitation centers. This is the same index 
used in the 2014-based SNF market basket.
     Depreciation--Movable Equipment: We are proposing to use 
the PPI Commodity for Machinery and Equipment (BLS series code WPU11). 
This price index reflects price inflation associated with a variety of 
machinery and equipment that would be utilized by SNFs including but 
not limited to medical equipment, communication equipment, and 
computers. This is the same index used in the 2014-based SNF market 
basket.
     Nonprofit Interest: We are proposing to use the average 
yield on Municipal Bonds (Bond Buyer 20-bond index). This is the same 
index used in the 2014-based SNF market basket.
     For-Profit Interest: For the For-Profit Interest cost 
category, we are proposing to use the iBoxx AAA Corporate Bond Yield 
index instead of the Moody's AAA Corporate Bond Yield index that was 
used for the 2014-based SNF market basket. Effective for December 2020, 
the Moody's AAA Corporate Bond series is no longer available for use 
under license to IGI, the nationally-recognized economic and financial 
forecasting firm with whom we contract to forecast the components of 
the market baskets and MFP. Therefore, we are proposing to replace the 
price proxy for the For-Profit interest cost category. We compared the 
iBoxx AAA Corporate Bond Yield index with the Moody's AAA Corporate 
Bond Yield index and found that the average growth rates in the two 
series were similar. Over the historical time period of FY 2000 to FY 
2020, the 4-quarter percent change moving average growth in the iBoxx 
series was approximately 0.1 percentage point higher, on average, than 
the Moody's AAA corporate Bond Yield index.
     Other Capital: Since this category includes fees for 
insurances, taxes, and other capital-related costs, we are proposing to 
use the CPI for Rent of Primary Residence (BLS series code 
CUUS0000SEHA), which would reflect the price growth of these costs. 
This is the same index used in the 2014-based SNF market basket.
    We believe that these price proxies are the most appropriate 
proxies for SNF capital costs that meet our selection criteria of 
relevance, timeliness, availability, and reliability.
    As stated above, we are proposing to continue to vintage weight the 
capital price proxies for Depreciation and Interest to capture the 
long-term consumption of capital. To capture the long-term nature, the 
price proxies are vintage-weighted; and the vintage weights are 
calculated using a two-step process. First, we determine the expected 
useful life of capital and debt instruments held by SNFs. Second, we 
identify the proportion of expenditures within a cost category that is 
attributable to each individual year over the useful life of the 
relevant capital assets, or the vintage weights.
    We rely on Bureau of Economic Analysis (BEA) fixed asset data to 
derive the useful lives of both fixed and movable capital, which is the 
same data source used to derive the useful lives for the 2014-based SNF 
market basket. The specifics of the data sources used are explained 
below.
a. Calculating Useful Lives for Moveable and Fixed Assets
    Estimates of useful lives for movable and fixed assets for the 
proposed 2018-based SNF market basket are 9 and 26 years, respectively. 
These estimates are based on three data sources from the BEA: (1) 
Current-cost average age; (2) historical-cost average age; and (3) 
industry-specific current cost net stocks of assets.
    BEA current-cost and historical-cost average age data by asset type 
are not available by industry but are published at the aggregate level 
for all industries. The BEA does publish current-cost net capital 
stocks at the detailed asset level for specific industries. There are 
64 detailed movable assets (including intellectual property) and there 
are 32 detailed fixed assets in the BEA estimates. Since we seek 
aggregate useful life estimates applicable to SNFs, we developed a 
methodology to approximate movable and fixed asset ages for nursing and 
residential care services (NAICS 623) using the published BEA data. For 
the proposed 2018 SNF market basket, we use the current-cost average 
age for each asset type from the BEA fixed assets Table 2.9 for all 
assets and weight them using current-cost net stock levels for each of 
these asset types in the nursing and residential care services 
industry, NAICS 6230. (For example, nonelectro medical equipment 
current-cost net stock (accounting for about 35 percent of total 
moveable equipment current-cost net stock in 2018) is multiplied by an 
average age of 4.7 years. Current-cost net stock levels are available 
for download from the BEA website at https://apps.bea.gov/iTable/index_FA.cfm. We then aggregate the ``weighted'' current-cost net stock 
levels (average age multiplied by current-cost net stock) into moveable 
and fixed assets for NAICS 6230. We then adjust the average ages for 
moveable and fixed assets by the ratio of historical-cost average age 
(Table 2.10) to current-cost average age (Table 2.9).
    This produces historical cost average age data for movable 
(equipment and intellectual property) and fixed (structures) assets 
specific to NAICS 6230 of 4.7 and 13.1 years for 2018, respectively. 
The average age reflects the average age of an asset at a given point 
in time, whereas we want to estimate a useful life of the asset, which 
would reflect the average over all periods an asset is used. To do 
this, we multiply each of the average age estimates by two to convert 
to average useful lives with the assumption that the average age is 
normally distributed (about half of the assets are below the average at 
a given point in time, and half above the average at a given point in 
time). This produces estimates of likely useful lives of 9.49 and 26.19 
years for movable and fixed assets, which we round to 9 and 26 years, 
respectively. We are proposing an interest vintage weight time span of 
24 years, obtained by weighting the fixed and movable vintage weights 
(26 years and 9 years, respectively) by the fixed and movable split (86 
percent and 14 percent, respectively). This is the same methodology 
used for the 2014-based SNF market basket, which had useful lives of 23 
years and 10 years for fixed and moveable assets, respectively. We 
estimate that the impact of revising the useful lives had a minor 
impact on the average historical growth rate of the proposed 2018-based 
SNF market basket total aggregate capital cost price proxy. Over the FY 
2016 to FY 2020 time period, the percent change moving average in the 
total aggregate capital cost price proxy was about 0.06 percentage 
point higher, on average, based on the proposed 2018-based SNF market 
basket compared to the 2014-based SNF market basket.
b. Constructing Vintage Weights
    Given the expected useful life of capital (fixed and moveable 
assets) and debt instruments, we must determine the proportion of 
capital expenditures attributable to each year of the expected useful 
life for each of the three asset types: Building and fixed equipment, 
moveable equipment, and interest. These proportions represent the 
vintage weights. We were not able to find a historical time series of 
capital expenditures by SNFs. Therefore, we approximated the capital 
expenditure patterns of SNFs over time, using alternative SNF data 
sources. For building and fixed equipment, we used the stock of beds in 
nursing homes from the National Nursing Home Survey (NNHS) conducted by 
the National

[[Page 19980]]

Center for Health Statistics (NCHS) for 1962 through 1999. For 2000 
through 2010, we extrapolated the 1999 bed data forward using a 5-year 
moving average of growth in the number of beds from the SNF MCR data. 
For 2011 to 2014, we extrapolate the 2010 bed data forward using the 
average growth in the number of beds over the 2011 to 2014 time period. 
For 2015 to 2018, we propose to extrapolate the 2014 bed data forward 
using the average growth in the number of beds over the 2015 to 2018 
time period. We then used the change in the stock of beds each year to 
approximate building and fixed equipment purchases for that year. This 
procedure assumes that bed growth reflects the growth in capital-
related costs in SNFs for building and fixed equipment. We believe that 
this assumption is reasonable because the number of beds reflects the 
size of a SNF, and as a SNF adds beds, it also likely adds fixed 
capital.
    As was done for the 2014-based SNF market basket (as well as prior 
market baskets), we are proposing to estimate moveable equipment 
purchases based on the ratio of ancillary costs to routine costs. The 
time series of the ratio of ancillary costs to routine costs for SNFs 
measures changes in intensity in SNF services, which are assumed to be 
associated with movable equipment purchase patterns. The assumption 
here is that as ancillary costs increase compared to routine costs, the 
SNF caseload becomes more complex and would require more movable 
equipment. The lack of movable equipment purchase data for SNFs over 
time required us to use alternative SNF data sources. A more detailed 
discussion of this methodology was published in the FY 2008 SNF final 
rule (72 FR 43428). We believe the resulting two time series, 
determined from beds and the ratio of ancillary to routine costs, 
reflect real capital purchases of building and fixed equipment and 
movable equipment over time.
    To obtain nominal purchases, which are used to determine the 
vintage weights for interest, we converted the two real capital 
purchase series from 1963 through 2018 determined above to nominal 
capital purchase series using their respective price proxies (the BEA 
Chained Price Index for Nonresidential Construction for Hospitals & 
Special Care Facilities and the PPI for Machinery and Equipment). We 
then combined the two nominal series into one nominal capital purchase 
series for 1963 through 2018. Nominal capital purchases are needed for 
interest vintage weights to capture the value of debt instruments.
    Once we created these capital purchase time series for 1963 through 
2018, we averaged different periods to obtain an average capital 
purchase pattern over time: (1) For building and fixed equipment, we 
averaged 31, 26-year periods; (2) for movable equipment, we averaged 
48, 9-year periods; and (3) for interest, we averaged 33, 24-year 
periods. We calculate the vintage weight for a given year by dividing 
the capital purchase amount in any given year by the total amount of 
purchases during the expected useful life of the equipment or debt 
instrument. To provide greater transparency, we posted on the CMS 
market basket website at http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch.html, an illustrative spreadsheet that contains an 
example of how the vintage-weighted price indexes are calculated.
    The vintage weights for the proposed 2018-based SNF market basket 
and the 2014-based SNF market basket are presented in Table 19.

                                      Table 19--Proposed 2018-Based Vintage Weights and 2014-Based Vintage Weights
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                           Building and fixed equipment          Movable equipment                   Interest
                                                         -----------------------------------------------------------------------------------------------
                        Year \1\                          Proposed 2018-   2014-Based 23  Proposed 2018-   2014-Based 10  Proposed 2018-   2014-Based 21
                                                          based 26 years       years       based 9 years       years      based 24 years       years
--------------------------------------------------------------------------------------------------------------------------------------------------------
1.......................................................           0.049           0.056           0.135           0.085           0.027           0.032
2.......................................................           0.050           0.055           0.140           0.087           0.028           0.033
3.......................................................           0.049           0.054           0.128           0.091           0.029           0.034
4.......................................................           0.047           0.052           0.112           0.097           0.031           0.036
5.......................................................           0.045           0.049           0.119           0.099           0.032           0.037
6.......................................................           0.043           0.046           0.111           0.102           0.034           0.039
7.......................................................           0.041           0.044           0.084           0.108           0.036           0.041
8.......................................................           0.040           0.043           0.080           0.109           0.037           0.043
9.......................................................           0.037           0.040           0.091           0.110           0.038           0.044
10......................................................           0.035           0.038  ..............           0.112           0.040           0.045
11......................................................           0.036           0.038  ..............  ..............           0.043           0.048
12......................................................           0.036           0.039  ..............  ..............           0.047           0.052
13......................................................           0.036           0.039  ..............  ..............           0.049           0.056
14......................................................           0.036           0.039  ..............  ..............           0.051           0.058
15......................................................           0.035           0.039  ..............  ..............           0.050           0.060
16......................................................           0.036           0.039  ..............  ..............           0.048           0.059
17......................................................           0.036           0.040  ..............  ..............           0.048           0.057
18......................................................           0.038           0.041  ..............  ..............           0.048           0.057
19......................................................           0.037           0.043  ..............  ..............           0.048           0.056
20......................................................           0.036           0.042  ..............  ..............           0.048           0.056
21......................................................           0.035           0.042  ..............  ..............           0.047           0.057
22......................................................           0.035           0.042  ..............  ..............           0.047  ..............
23......................................................           0.035           0.042  ..............  ..............           0.047  ..............
24......................................................           0.033  ..............  ..............  ..............           0.049  ..............
25......................................................           0.032  ..............  ..............  ..............  ..............  ..............
26......................................................           0.032  ..............  ..............  ..............  ..............  ..............
                                                         -----------------------------------------------------------------------------------------------

[[Page 19981]]

 
    Total...............................................           1.000           1.000           1.000           1.000           1.000           1.000
--------------------------------------------------------------------------------------------------------------------------------------------------------
Note: The vintage weights are calculated using thirteen decimals. For presentation purposes, we are displaying three decimals and therefore, the detail
  vintage weights may not add to 1.000 due to rounding.
\1\ Year 1 represents the vintage weight applied to the farthest year while the vintage weight for year 26, for example, would apply to the most recent
  year.

    Table 20 shows all the price proxies for the proposed 2018-based 
SNF market basket.

 Table 20--Proposed Price Proxies for the Proposed 2018-Based SNF Market
                                 Basket
------------------------------------------------------------------------
         Cost category               Weight        Proposed price proxy
------------------------------------------------------------------------
Total..........................           100.0
Compensation...................            60.2
    Wages and Salaries \1\.....            50.4  ECI for Wages and
                                                  Salaries for Private
                                                  Industry Workers in
                                                  Nursing Care
                                                  Facilities.
    Employee Benefits \1\......             9.9  ECI for Total Benefits
                                                  for Private Industry
                                                  Workers in Nursing
                                                  Care Facilities.
Utilities......................             1.5
    Electricity and Other Non-              1.0  PPI Commodity for
     Fuel Utilities.                              Commercial Electric
                                                  Power.
    Fuel: Oil and Gas..........             0.4  Blend of Fuel PPIs.
Professional Liability                      1.1  CMS Professional
 Insurance.                                       Liability Insurance
                                                  Premium Index.
All Other......................            29.0
    Other Products.............            17.6
        Pharmaceuticals........             7.5  PPI Commodity for
                                                  Pharmaceuticals for
                                                  Human Use,
                                                  Prescription.
        Food: Direct Purchase..             2.5  PPI Commodity for
                                                  Processed Foods and
                                                  Feeds.
        Food: Contract Purchase             4.3  CPI for Food Away From
                                                  Home (All Urban
                                                  Consumers).
        Chemicals..............             0.2  Blend of Chemical PPIs.
        Medical Instruments and             0.6  Blend of Medical
         Supplies.                                Instruments and
                                                  Supplies PPIs.
        Rubber and Plastics....             0.7  PPI Commodity for
                                                  Rubber and Plastic
                                                  Products.
        Paper and Printing                  0.5  PPI Commodity for
         Products.                                Converted Paper and
                                                  Paperboard Products.
        Apparel................             0.5  PPI Commodity for
                                                  Apparel.
        Machinery and Equipment             0.5  PPI Commodity for
                                                  Machinery and
                                                  Equipment.
        Miscellaneous Products.             0.3  PPI Commodity for
                                                  Finished Goods Less
                                                 Food and Energy.
All Other Services.............            11.5
    Labor-Related Services.....             6.4
        Professional Fees:                  3.5  ECI for Total
         Labor-related.                           Compensation for
                                                  Private Industry
                                                  Workers in
                                                  Professional and
                                                  Related.
        Installation,                       0.6  ECI for Total
         Maintenance, and                         Compensation for All
         Repair Services.                         Civilian workers in
                                                  Installation,
                                                  Maintenance, and
                                                  Repair.
        Administrative and                  0.4  ECI for Total
         Facilities Support.                      Compensation for
                                                  Private Industry
                                                  Workers in Office and
                                                  Administrative
                                                  Support.
        All Other: Labor-                   1.9  ECI for Total
         Related Services.                        Compensation for
                                                  Private Industry
                                                  Workers in Service
                                                  Occupations.
    Non Labor-Related Services.             5.1
        Professional Fees:                  2.0  ECI for Total
         Nonlabor-Related.                        Compensation for
                                                  Private Industry
                                                  Workers in
                                                  Professional and
                                                  Related.
        Financial Services.....             1.3  ECI for Total
                                                  Compensation for
                                                  Private Industry
                                                  Workers in Financial
                                                  Activities.
        Telephone Services.....             0.3  CPI for Telephone
                                                  Services.
        All Other: Nonlabor-                1.5  CPI for All Items Less
         Related Services.                        Food and Energy.
    Capital-Related Expenses...             8.2
    Total Depreciation.........             3.0
        Building and Fixed                  2.5  BEA's Chained Price
         Equipment.                               Index for Private
                                                  Fixed Investment in
                                                  Structures,
                                                  Nonresidential,
                                                  Hospitals and Special
                                                  Care--vintage weighted
                                                  26 years.
        Movable Equipment......             0.4  PPI Commodity for
                                                  Machinery and
                                                  Equipment--vintage
                                                  weighted 9 years.
    Total Interest.............             2.7

[[Page 19982]]

 
        For-Profit SNFs........             0.7  iBoxx--Average yield on
                                                  Aaa bond--vintage
                                                  weighted 24 years.
        Government and                      2.0  Bond Buyer--Average
         Nonprofit SNFs.                          yield on Domestic
                                                  Municipal Bonds--
                                                  vintage weighted 24
                                                  years.
    Other Capital-Related                   2.6  CPI for Rent of Primary
     Expenses.                                    Residence.
------------------------------------------------------------------------
Note: The cost weights are calculated using three decimal places. For
  presentation purposes, we are displaying one decimal and, therefore,
  the detailed cost weights may not add to the aggregate cost weights or
  to 100.0 due to rounding.
\1\ Contract labor is distributed to wages and salaries and employee
  benefits based on the share of total compensation that each category
  represents.

4. Labor-Related Share
    We define the labor-related share (LRS) as those expenses that are 
labor-intensive and vary with, or are influenced by, the local labor 
market. Each year, we calculate a revised labor-related share based on 
the relative importance of labor-related cost categories in the input 
price index. Effective for FY 2022, we are proposing to revise and 
update the labor-related share to reflect the relative importance of 
the proposed 2018-based SNF market basket cost categories that we 
believe are labor-intensive and vary with, or are influenced by, the 
local labor market. For the proposed 2018-based SNF market basket these 
are: (1) Wages and Salaries (including allocated contract labor costs 
as described above); (2) Employee Benefits (including allocated 
contract labor costs as described above); (3) Professional fees: Labor-
related; (4) Administrative and Facilities Support Services; (5) 
Installation, Maintenance, and Repair Services; (6) All Other: Labor-
Related Services; and (7) a proportion of capital-related expenses. We 
propose to continue to include a proportion of capital-related expenses 
because a portion of these expenses are deemed to be labor-intensive 
and vary with, or are influenced by, the local labor market. For 
example, a proportion of construction costs for a medical building 
would be attributable to local construction workers' compensation 
expenses.
    Consistent with previous SNF market basket revisions and rebasings, 
the All Other: Labor-related services cost category is mostly comprised 
of building maintenance and security services (including, but not 
limited to, landscaping services, janitorial services, waste management 
services services) and dry cleaning and laundry services. Because these 
services tend to be labor-intensive and are mostly performed at the SNF 
facility or in the local area (and therefore, unlikely to be purchased 
in the national market), we believe that they meet our definition of 
labor-related services.
    These are the same cost categories we have included in the LRS for 
the 2014-based SNF market basket rebasing (82 FR 36563) as well as the 
same categories included in the LRS for the 2016-based IRF market 
basket (84 FR 39087), 2016-based IPF market basket (84 FR 38445), and 
2017-based LTCH market basket (85 FR 58910).
    As discussed in the FY 2018 SNF PPS proposed rule (82 FR 21040), in 
an effort to determine more accurately the share of nonmedical 
professional fees (included in the proposed 2018-based SNF market 
basket Professional Fees cost categories) that should be included in 
the labor-related share, we surveyed SNFs regarding the proportion of 
those fees that are attributable to local firms and the proportion that 
are purchased from national firms. Based on these weighted results, we 
determined that SNFs purchase, on average, the following portions of 
contracted professional services inside their local labor market:
     78 percent of legal services.
     86 percent of accounting and auditing services.
     89 percent of architectural, engineering services.
     87 percent of management consulting services.
    Together, these four categories represent 3.5 percentage points of 
the total costs for the proposed 2018-based SNF market basket. We 
applied the percentages from this special survey to their respective 
SNF market basket weights to separate them into labor-related and 
nonlabor-related costs. As a result, we are designating 2.9 of the 3.5 
percentage points total to the labor-related share, with the remaining 
0.6 percentage point categorized as nonlabor-related.
    In addition to the professional services as previously listed, for 
the 2018-based SNF market basket, we propose to allocate a proportion 
of the Home Office/Related Organization Contract Labor cost weight, 
calculated using the Medicare cost reports as previously stated, into 
the Professional Fees: Labor-related and Professional Fees: Nonlabor-
related cost categories. We propose to classify these expenses as 
labor-related and nonlabor-related as many facilities are not located 
in the same geographic area as their home office and, therefore, do not 
meet our definition for the labor-related share that requires the 
services to be purchased in the local labor market.
    Similar to the 2014-based SNF market basket, we propose for the 
2018-based SNF market basket to use the Medicare cost reports for SNFs 
to determine the home office labor-related percentages. The Medicare 
cost report requires a SNF to report information regarding their home 
office provider. Using information on the Medicare cost report, we 
compared the location of the SNF with the location of the SNF's home 
office. We propose to classify a SNF with a home office located in 
their respective labor market if the SNF and its home office are 
located in the same Metropolitan Statistical Area (MSA). Then we 
determine the proportion of the Home Office/Related Organization 
Contract Labor cost weight that should be allocated to the labor-
related share based on the percent of total Home Office/Related 
Organization Contract Labor costs for those SNFs that had home offices 
located in their respective local labor markets of total Home Office/
Related Organization Contract Labor costs for SNFs with a home office. 
We determined a SNF's and its home office's MSA using their zip code 
information from the Medicare cost report. Using this methodology, we 
determined that 21 percent of SNFs' Home Office/Related Organization 
Contract Labor costs were for home offices located in their respective 
local labor markets. Therefore, we propose to allocate 21 percent of 
the Home Office/Related Organization Contract Labor cost weight (0.14 
percentage point = 0.69 percent x 21 percent) to the Professional Fees: 
Labor-related cost weight and 79 percent of the Home Office/Related 
Organization Contract Labor cost weight to the Professional Fees: 
Nonlabor-related cost weight (0.55

[[Page 19983]]

percentage point = 0.69 percent x 79 percent). The 2014-based SNF 
market basket used a similar methodology for allocating the Home 
Office/Related Organization Contract Labor cost weight to the labor-
related share.
    In summary, based on the two allocations mentioned earlier, we 
propose to apportion 3.0 percentage points of the Professional Fees 
(2.9 percentage points) and Home Office/Related Organization Contract 
Labor (0.1 percentage point) cost weights into the Professional Fees: 
Labor-Related cost category. This amount was added to the portion of 
professional fees that we already identified as labor-related using the 
I-O data such as contracted advertising and marketing costs 
(approximately 0.45 percentage point of total costs) resulting in a 
Professional Fees: Labor-Related cost weight of 3.5 percent.
    Table 21 compares the FY 2022 labor-related share based on the 
proposed 2018-based SNF market basket relative importance and the FY 
2021 labor-related share based on the 2014-based SNF market basket 
relative importance as finalized in the FY 2021 SNF final rule (85 FR 
47605).

     Table 21--FY 2021 and Proposed FY 2022 SNF Labor-Related Share
------------------------------------------------------------------------
                                       Relative        Proposed relative
                                  importance, labor-  importance, labor-
                                   related share, FY   related share, FY
                                  2021 20:2 forecast  2022 20:4 forecast
                                          \1\                 \2\
------------------------------------------------------------------------
Wages and salaries \3\..........                51.1                51.2
Employee benefits\*\............                 9.9                 9.5
Professional fees: Labor-related                 3.7                 3.5
Administrative & facilities                      0.5                 0.6
 support services...............
Installation, maintenance &                      0.6                 0.4
 repair services................
All other: Labor-related                         2.6                 1.9
 services.......................
Capital-related (.391)..........                 2.9                 3.0
                                 ---------------------------------------
    Total.......................                71.3                70.1
------------------------------------------------------------------------
\1\ Published in the Federal Register (85 FR 47605); based on the second
  quarter 2020 IHS Global Inc. forecast of the 2014-based SNF market
  basket, with historical data through first quarter 2020.
\2\ Based on the fourth quarter 2020 IHS Global Inc. forecast of the
  proposed 2018-based SNF market basket.
\3\ The Wages and Salaries and Employee Benefits cost weight reflect
  contract labor costs as described above.

    The proposed FY 2022 SNF labor-related share is 1.2 percentage 
points lower than the FY 2021 SNF labor-related share (based on the 
2014-based SNF market basket). The major reason for the lower labor-
related share is due to the incorporation of the 2012 Benchmark I-O 
data, primarily stemming from a decrease in the All Other: Labor-
related services and Professional Fees: Labor-related services cost 
weights, and a decrease in the Compensation cost weight as a result of 
incorporating the 2018 MCR data.
5. Proposed Market Basket Estimate for the FY 2022 SNF PPS Update
    As discussed previously in this proposed rule, beginning with the 
FY 2022 SNF PPS update, we are proposing to adopt the 2018-based SNF 
market basket as the appropriate market basket of goods and services 
for the SNF PPS. Consistent with historical practice, we estimate the 
market basket update for the SNF PPS based on IHS Global Inc.'s (IGI) 
forecast. IGI is a nationally recognized economic and financial 
forecasting firm that contracts with CMS to forecast the components of 
the market baskets and multifactor productivity (MFP). Based on IGI's 
fourth quarter 2020 forecast with historical data through the third 
quarter of 2020, the most recent estimate of the proposed 2018-based 
SNF market basket update for FY 2022 is 2.3 percent-0.1 percentage 
point lower (after rounding) than the FY 2022 percent change of the 
2014-based SNF market basket. We are also proposing that if more recent 
data subsequently become available (for example, a more recent estimate 
of the market basket and/or the MFP), we would use such data, if 
appropriate, to determine the FY 2022 SNF market basket percentage 
change, labor-related share relative importance, forecast error 
adjustment, or MFP adjustment in the SNF PPS final rule.
    Table 22 compares the proposed 2018-based SNF market basket and the 
2014-based SNF market basket percent changes. For the historical period 
between FY 2017 and FY 2020, there is no difference in the average 
growth rates between the two market baskets. For the forecasted period 
between FY 2021 and FY 2023, the average difference between the two 
market baskets is -0.1 percentage point.

   Table 22--Proposed 2018-Based SNF Market Basket and 2014-Based SNF
                Market Basket, Percent Changes: 2017-2023
------------------------------------------------------------------------
                                    Proposed  2018-
        Fiscal year  (FY)          Based SNF  market    2014-Based SNF
                                        basket           market basket
------------------------------------------------------------------------
Historical data:
    FY 2017.....................                 2.5                 2.7
    FY 2018.....................                 2.6                 2.6
    FY 2019.....................                 2.4                 2.3
    FY 2020.....................                 2.1                 2.0
    Average FY 2017-2020........                 2.4                 2.4
Forecast:
    FY 2021.....................                 2.4                 2.4
    FY 2022.....................                 2.3                 2.4

[[Page 19984]]

 
    FY 2023.....................                 2.6                 2.7
    Average FY 2021-2023........                 2.4                 2.5
------------------------------------------------------------------------
Source: IHS Global, Inc. 4th quarter 2020 forecast with historical data
  through 3rd quarter 2020.

B. Technical Updates to PDPM ICD-10 Mappings

    In the FY 2019 SNF PPS final rule (83 FR 39162), we finalized the 
implementation of the Patient Driven Payment Model (PDPM), effective 
October 1, 2019. The PDPM utilizes International Classification of 
Diseases, Version 10 (ICD-10) codes in several ways, including to 
assign patients to clinical categories used for categorization under 
several PDPM components, specifically the PT, OT, SLP and NTA 
components. The ICD-10 code mappings and lists used under PDPM are 
available on the PDPM website at https://www.cms.gov/Medicare/MedicareFee-for-Service-Payment/SNFPPS/PDPM.
    Each year, the ICD-10 Coordination and Maintenance Committee, a 
Federal interdepartmental committee that is chaired by representatives 
from the National Center for Health Statistics (NCHS) and by 
representatives from CMS, meets biannually and publishes updates to the 
ICD-10 medical code data sets in June of each year. These changes 
become effective October 1 of the year in which these updates are 
issued by the committee. The ICD-10 Coordination and Maintenance 
Committee also has the ability to make changes to the ICD-10 medical 
code data sets effective on April 1.
    In the FY 2020 SNF PPS final rule (84 FR 38750), we outlined the 
process by which we maintain and update the ICD-10 code mappings and 
lists associated with the PDPM, as well as the SNF GROUPER software and 
other such products related to patient classification and billing, so 
as to ensure that they reflect the most up to date codes possible. 
Beginning with the updates for FY 2020, we apply nonsubstantive changes 
to the ICD-10 codes included on the PDPM code mappings and lists 
through a subregulatory process consisting of posting updated code 
mappings and lists on the PDPM website at https://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/SNFPPS/PDPM. Such nonsubstantive 
changes are limited to those specific changes that are necessary to 
maintain consistency with the most current ICD-10 medical code data 
set. On the other hand, substantive changes, or those that go beyond 
the intention of maintaining consistency with the most current ICD-10 
medical code data set, will be proposed through notice and comment 
rulemaking. For instance, changes to the assignment of a code to a 
comorbidity list or other changes that amount to changes in policy are 
considered substantive changes for which we would undergo notice and 
comment rulemaking.
    We are proposing several changes to the PDPM ICD-10 code mappings 
and lists. Our proposed changes are as follows:
    On October 1, 2020 two ICD-10 codes representing types of sickle-
cell disease; D57.42 ``Sickle-cell thalassemia beta zero without 
crisis'' and D57.44 ``Sickle-cell thalassemia beta plus without 
crisis'' took effect and were clinically mapped to the category of 
``Medical Management''. However, there are more specific codes to 
indicate why a patient with sickle-cell disease would require SNF care, 
and if the patient is not in crisis, this most likely indicates that 
SNF care is not required. For this reason, we propose to change the 
assignment of D57.42 and D57.44 to ``Return to Provider''.
    On October 1, 2020, three new ICD-10 codes representing types of 
esophageal conditions; K20.81 ``Other esophagitis with bleeding'', 
K20.91, ``Esophagitis, unspecified with bleeding, and K21.01 ``Gastro-
esophageal reflux disease with esophagitis, with bleeding'' took effect 
and were clinically mapped to ``Return to Provider''. Upon review of 
these codes, we recognize that these codes represent these esophageal 
conditions with more specificity than originally considered because of 
the bleeding that is part of the conditions and that they would more 
likely be found in SNF patients. Therefore, we propose to change the 
assignment of K20.81, K20.91, and K21.01 to ``Medical Management'' in 
order to promote more accurate clinical category assignment.
    In December 2020, the CDC announced several additions to the ICD-10 
Classification related to COVID-19 that became effective on January 1, 
2021. One such code, M35.81 ``Multisystem inflammatory syndrome'', was 
assigned to ``Non-Surgical Orthopedic/Musculoskeletal''. However, 
Multisystem inflammatory syndrome can involve more than the 
musculoskeletal system. It can also involve the gastrointestinal tract, 
heart, central nervous system, and kidneys. For this reason, we propose 
to change the assignment of M35.81 to ``Medical Management'' in order 
to promote more accurate clinical category assignment.
    On October 1, 2020, three new ICD-10 codes representing types of 
neonatal cerebral infarction were classified as ``Return to Provider.'' 
These codes were P91.821 ``Neonatal cerebral infarction, right side of 
brain,'' P91.822, ``Neonatal cerebral infarction, left side of brain,'' 
and P91.823, ``Neonatal cerebral infarction, bilateral.'' While a 
neonate is unlikely to be a Medicare beneficiary, this diagnosis could 
continue to be used later in life hence placing those with this 
condition in the acute neurologic category. Therefore, we propose to 
change the assignment of P91.821, P91.822, and P91.823 to ``Acute 
Neurologic'' in order to promote more accurate clinical category 
assignment.
    On April 1, 2020, U07.0, ``Vaping-related disorder,'' took effect 
and was classified as a ``Return to Provider'' code because at the 
time, ``Vaping-related disorder'' was not considered a code that would 
be a primary diagnosis during a SNF stay. However, upon further review, 
we believe that many patients who exhibit this diagnosis require 
steroids, empiric antibiotics and oxygen for care which could carry 
over to the post-acute setting. For this reason, we propose to change 
the assignment of U07.0 to ``Pulmonary'' classification in order to 
promote more accurate clinical category assignment.
    In the FY 2021 proposed rule (85 FR 20939), we sought comments on 
additional substantive and nonsubstantive changes that commenters 
believed were necessary. We received three comments suggesting several 
changes to the ICD-10 to clinical category mappings. One of those 
changes was substantive, requiring notice and comment rulemaking. The

[[Page 19985]]

commenter suggested that the FY 2020 ICD-10 to clinical category 
mapping of G93.1 ``Anoxic brain damage, not elsewhere classified'' be 
changed to ``Acute Neurologic'' from ``Return to Provider,'' which we 
would consider a substantive change. Codes that result in ``Return to 
Provider'' are codes that cannot be used in I0020B of the MDS because 
item I0020B is used to establish the primary medical condition that a 
patient presents with during a SNF stay. Although some codes are 
considered ``Return to Provider'' for payment purposes, they are still 
used to support the care and services used for secondary and co-
morbidity diagnoses. The ICD-10 code, G93.1 was initially clinically 
mapped to ``Return to provider'' because ``Anoxic brain damage, not 
elsewhere classified'' was non-specific and did not fully describe a 
patient's deficits and may not have been an acute condition. However, 
upon further review, our clinicians determined that although this may 
not be an acute condition, ``Anoxic brain damage, not elsewhere 
classified'' would still likely result in a need for SNF care and is 
similar to conditions such as ``Compression of the brain'', ``Cerebral 
edema'', and ``encephalopathy'', which are mapped into the ``Acute 
Neurologic'' category. Therefore, we propose to change the assignment 
of G93.1 ``Anoxic brain damage, not elsewhere classified'' to ``Acute 
Neurologic''.
    We invite comments on the proposed substantive changes to the ICD-
10 code mappings discussed previously, as well as comments on 
additional substantive and non-substantive changes that commenters 
believe are necessary.

C. Recalibrating the PDPM Parity Adjustment

1. Background
    On October 1, 2019, we implemented the Patient Driven Payment Model 
(PDPM) under the SNF PPS, a new case-mix classification model that 
replaced the prior case-mix classification model, the Resource 
Utilization Groups, Version IV (RUG-IV). As discussed in the FY 2019 
SNF PPS final rule (83 FR 39256), as with prior system transitions, we 
proposed and finalized to implement PDPM in a budget neutral manner. 
This means that the transition to PDPM, along with the related policies 
finalized in the FY 2019 SNF PPS final rule, were not intended to 
result in an increase or decrease in the aggregate amount of Medicare 
payment to SNFs. We believe ensuring parity is integral to the process 
of providing ``for an appropriate adjustment to account for case mix'' 
that is based on appropriate data in accordance with section 
1888(e)(4)(G)(i) of the Act. Section V.I. of the FY 2019 SNF PPS final 
rule (83 FR 39255 through 39256) discusses the methodology that we used 
to implement PDPM in a budget neutral manner. Specifically, we 
multiplied each of the PDPM case-mix indexes (CMI) by an adjustment 
factor that was calculated by comparing total payments under RUG-IV, 
using FY 2017 claims and assessment data (the most recent final claims 
data available at the time), and what we expected total payments would 
be under the then proposed PDPM based on that same FY 2017 claims and 
assessment data. In the FY 2020 SNF PPS final rule (84 FR 38734-38735), 
CMS finalized an updated standardization multiplier and parity 
adjustment based on FY 2018 claims and assessment data. Through this 
comparison, and as discussed in the FY 2020 SNF PPS final rule, this 
analysis resulted in an adjustment factor of 1.46, by which the PDPM 
CMIs were multiplied so that total estimated payments under PDPM would 
be equal to total actual payments under RUG-IV, assuming no changes in 
the population, provider behavior, and coding. By multiplying the CMIs 
by 1.46, the CMIs were inflated by 46 percent in order to achieve 
budget neutrality.
    A similar type of adjustment was used when we transitioned from 
RUG-III to RUG-IV in FY 2011. However, as discussed in the FY 2012 SNF 
PPS final rule (76 FR 48492 through 48500), we observed that, once 
actual RUG-IV utilization data became available, the actual RUG-IV 
utilization patterns differed significantly from those we had projected 
using the historical data that grounded the RUG-IV parity adjustment. 
As a result, in the FY 2012 SNF PPS final rule, we used actual FY 2011 
RUG-IV utilization data to recalibrate the RUG-IV parity adjustment. 
Based on the use of FY 2011 RUG-IV utilization data, we decreased the 
RUG-IV parity adjustment applied to the nursing CMIs for all RUG-IV 
therapy groups from an adjustment factor of 61 percent to an adjustment 
factor of 19.84 percent (while maintaining the original 61 percent 
total nursing CMI increase for all non-therapy RUG-IV groups). As a 
result of this recalibration, FY 2012 SNF PPS rates were reduced by 
12.5 percent, or $4.47 billion, in order to achieve budget neutrality 
under RUG-IV prospectively.
    Since PDPM implementation, we have closely monitored PDPM 
utilization data to ascertain, among other things, if the PDPM parity 
adjustment provided for a budget neutral transition to this new case-
mix classification model. Similar to what occurred in FY 2011 with RUG-
IV implementation, we have observed significant differences between 
expected SNF PPS payments and case-mix utilization, based on historical 
data, and the actual SNF PPS payments and case-mix utilization under 
the PDPM, based on FY 2020 data. As a result, it would appear that 
rather than simply achieving parity, the FY 2020 parity adjustment may 
have inadvertently triggered a significant increase in overall payment 
levels under the SNF PPS. We believe that, based on the data from this 
initial phase of PDPM, a recalibration of the PDPM parity adjustment is 
warranted to ensure that the adjustment serves its intended purpose to 
make the transition between RUG-IV and PDPM budget neutral.
    However, we also acknowledge that the pandemic-related PHE for 
COVID-19, which began during the first year of PDPM and has continued 
into at least part of FY 2021, has had a likely impact on SNF PPS 
utilization data. Further, following the methodology utilized in 
calculating the initial parity adjustment, we typically would use 
claims and assessment data for a given year to classify patients under 
both the current system and the prior system to compare aggregate 
payments between the prior system and new system and determine an 
appropriate adjustment factor to achieve parity. When we performed a 
similar recalibration of the RUG-IV parity adjustment, for example, we 
used data from FY 2011, the first year of RUG-IV implementation, as the 
basis for recalibrating the RUG-IV parity adjustment. However, in 
addition to the aforementioned potential issues with the FY 2020 SNF 
utilization data arising from the PHE for COVID-19, we are concerned 
that given the significant differences in both patient assessment 
requirements and payment incentives between RUG-IV and PDPM, using the 
same methodology we have used in the past to calculate a recalibrated 
PDPM parity adjustment could lead to a potentially inaccurate 
recalibration.
    Therefore, given these issues, and for the reasons below, we are 
taking this opportunity to present some of the results of our PDPM data 
monitoring efforts and a potential recalibration methodology intended 
to address the issues presented above. First, it is important to 
provide transparency on the observed impacts of PDPM implementation, as 
we do believe there have been significant changes observed in SNF 
utilization that are tied strictly to PDPM and not the PHE for COVID-
19. Second, we wish to make clear why we believe that the typical 
methodology for recalibrating the parity adjustment

[[Page 19986]]

may not provide an accurate recalibration under PDPM. Finally, we view 
this as an opportunity to seek comment on a path forward for 
recalibrating the PDPM parity adjustment to ensure that PDPM is 
implemented in a budget neutral manner, as intended.
2. FY 2020 Changes in SNF Case-Mix Utilization
    FY 2020 was a year of significant change under the SNF PPS. In 
addition to implementing PDPM, a national PHE for COVID-19 was 
declared. With the announcement of the PHE for COVID-19, we also 
announced a number of waivers which impacted SNF operations and the 
population of Medicare beneficiaries who were able to access the Part A 
SNF benefit. Most notably, under authority granted us by section 
1812(f) of the Act, we issued a waiver of section 1861(i) of the Act, 
specifically the requirement that in order for a SNF stay to be covered 
by Medicare, a beneficiary must have a prior inpatient hospital stay of 
not less than 3 consecutive days before being admitted to the Part A 
SNF stay. Additionally, this waiver also allowed certain beneficiaries 
renewed SNF coverage without first having to start a new benefit 
period. The section 1812(f) waiver, particularly the component which 
permits beneficiaries to access the Part A SNF benefit without a prior 
hospitalization, allowed beneficiaries who would not typically be able 
to access the Part A SNF benefit to receive a Part A covered SNF stay 
(for example, long term care nursing home patients without any prior 
hospitalization). A key aspect of our methodology for recalibrating the 
PDPM parity adjustment involves parsing out the impact of these waivers 
and the different population of beneficiaries that had access to the 
SNF benefit as result of these waivers from the population of 
beneficiaries that would have been admitted to SNFs subsequent to PDPM 
implementation without these waivers, as well as differences in the 
type of care these patients received. We would note that while the PHE 
for COVID-19 clearly had impacts on nursing home care protocols and 
many other aspects of SNF operations, the relevant issue for pursuing a 
recalibration of the PDPM parity adjustment is whether or not these 
changes caused the SNF case-mix distribution to be distinctly different 
from what it would have been were it not for the PHE for COVID-19. In 
other words, while different people were able to access the Part A SNF 
benefit than would typically be able to do so, the issue is whether or 
not the relative percentage of beneficiaries in each PDPM group is 
different than what those percentages would have been were it not for 
the PHE for COVID-19 and related waivers. We solicit comments on 
whether stakeholders believe that the PHE for COVID-19 impacted on the 
distribution of patient case-mix.
    To understand the potential impact of the PHE for COVID-19 on SNF 
utilization data, we can begin by understanding the overall utilization 
of the waivers and the overall frequency of COVID-19 diagnoses among 
the SNF population. In FY 2020, only approximately 9.8 percent of SNF 
stays included a COVID-19 ICD-10 diagnosis code (either as a primary or 
secondary diagnosis), while 15.6 percent of SNF stays utilized a 
section 1812(f) waiver (with the majority of these cases using the 
prior hospitalization waiver), as identified by the presence of a 
``DR'' condition code on the SNF claim. As compared to prior years, 
when approximately 98 percent of SNF beneficiaries had a qualifying 
prior hospital stay, approximately 87 percent of SNF beneficiaries had 
a qualifying prior hospitalization in FY 2020. These general statistics 
are important, as they highlight that while the PHE for COVID-19 
certainly impacted many aspects of nursing home operations, the 
overwhelming majority of SNF beneficiaries entered into Part A SNF 
stays in FY 2020 as they would have in any other year; that is, without 
using a PHE-related waiver, with a prior hospitalization, and without a 
COVID-19 diagnosis. In fact, as we discuss further below, even when 
removing those using a PHE-related waiver and those with a COVID-19 
diagnosis from our dataset, the observed inadvertent increase in SNF 
payments since PDPM was implemented is approximately the same. This 
would seem to imply that this ``new'' population of SNF beneficiaries 
(that is, COVID-19 patients and those using a section 1812(f) waiver) 
does not appear to be the cause of the increase in SNF payments after 
implementation of PDPM, since we would expect a much greater impact on 
the calculation of the necessary recalibration from removing this 
population from our analysis if that were the case.
    Moreover, we do believe that there is clear evidence that PDPM 
alone is impacting certain aspects of SNF patient classification and 
care provision. For example, through FY 2019, the average number of 
therapy minutes SNF patients received per day was approximately 91 
minutes. Beginning almost immediately with PDPM implementation (and 
well before the onset of the pandemic), the average number of therapy 
minutes SNF patients received per day dropped to approximately 62, a 
decrease of over 30 percent. Given both the immediacy and ubiquity of 
this change in the SNF data, without any concurrent change in the SNF 
population, it is clear that this overall decrease in the amount of 
therapy services provided to SNF patients is a result of PDPM 
implementation and not other factors. A number of media articles 
further corroborated this finding, which identified significant changes 
in therapy staffing and care directives at the outset of PDPM. 
Similarly, we also observed an increase in non-individualized modes of 
therapy provision beginning with PDPM implementation. Specifically, 
while the percentage of SNF stays which included concurrent or group 
therapy was approximately 1 percent for each of these therapy modes 
prior to FY 2020, these numbers rose to approximately 32 percent and 29 
percent, respectively, beginning in the first month of PDPM 
implementation. Coincidentally, these numbers then dropped to 8 percent 
and 4 percent, respectively, beginning in April 2020, close to when the 
PHE for COVID-19 was declared (highlighting at least one impact of the 
PHE for COVID-19 on SNF care provision and utilization). We also note 
that while these findings (increases in concurrent and group therapy 
utilization) were anticipated prior to PDPM implementation based on 
comments on the FY 2019 and FY 2020 SNF PPS proposed rules, we maintain 
the belief that the unique characteristics and goals of each SNF 
patient should drive patient care decisions. As we stated in the FY 
2020 SNF PPS final rule (84 FR 38748), we believe that financial 
motives should not override the clinical judgment of a therapist or 
therapy assistant or pressure a therapist or therapy assistant to 
provide less than appropriate therapy. We would also note that, despite 
these changes in therapy provision, we did not identify any significant 
changes in health outcomes for SNF patients. For example, we observed 
no changes in the percentage of stays with falls with major injury, the 
percentage of stays ending with Stage 2-4 or unstageable pressure 
ulcers or deep tissue injury, the percentage of stays readmitted to an 
inpatient hospital setting within 30 days of SNF discharge, or other 
similar metrics. We will continue to monitor these and other metrics to 
identify any adverse trends that may have been caused by changes in 
care patterns that

[[Page 19987]]

accompanied the implementation of PDPM.
    These changes in therapy provision highlight the reasons we believe 
that the typical methodology for recalibrating a parity adjustment 
would not be appropriate in the context of PDPM. As discussed 
previously in this proposed rule and in the FY 2012 SNF PPS final rule 
(76 FR 26371), we would typically utilize claims and assessment data 
from a given period under the new payment system, classify patients 
under both the current and prior payment model using this same set of 
data, compare aggregate payments under each payment model, and 
calculate an appropriate adjustment factor to achieve budget 
neutrality. However, given the significant changes in therapy provision 
since PDPM implementation, we found that using patient assessment data 
collected under PDPM (for example, FY 2020 data) would lead to a 
drastic underestimation of RUG-IV case mix for purposes of determining 
what aggregate payments would have been under RUG-IV for the same 
period. In other words, given the significant reduction in the overall 
amount of therapy provided to SNF patients since PDPM implementation, 
as well as changes in the way that the therapy is provided (for 
example, increases in group and concurrent therapy), classifying SNF 
patients into RUG-IV payment groups using data collected under PDPM 
would lead to a RUG-IV case-mix distribution that contrasts 
significantly with historical trends under RUG-IV. This finding is 
precisely why we do not believe that the typical methodology for 
recalibrating the PDPM parity adjustment would result in an accurate 
calculation of the revised parity adjustment factor and may lead to an 
overcorrection. We invite comments on the information presented above, 
as well as on the potential impact of using the reported FY 2020 
patient assessment data from the MDS to reclassify SNF beneficiaries 
under RUG-IV, consistent with the same type of recalibration 
methodology we have used after prior system transitions. Below, we 
discuss the methodology we are considering for recalibrating the PDPM 
parity adjustment, which we believe accounts for this change in therapy 
provision.
3. Methodology for Recalibrating the PDPM Parity Adjustment
    As discussed above, we have identified an inadvertent increase in 
SNF spending since implementing PDPM. As in the past, identifying the 
scope and magnitude of this type of inadvertent increase begins with 
looking at the type of case-mix distribution that was expected under 
the new case-mix system and the actual case-mix distribution that 
occurs under the new case-mix system. In the FY 2012 SNF PPS proposed 
rule (76 FR 26371), we were able to provide a table which listed each 
of the RUG-IV payment groups with the projected and actual percentage 
of SNF days of service associated with each group. Due to the number of 
possible payment groups under PDPM, this type of table is not possible. 
However, Table 23 provides the average PDPM case-mix index expected for 
each of the PDPM rate components based on data from FY 2019. This 
average is calculated for each component by summing the expected PDPM 
case-mix index for each day of service and then dividing this number by 
the total number of FY 2019 days of service. Table 23 also provides the 
actual average PDPM case-mix index for each of these components in two 
different ways. First, we used FY 2020 data for the full SNF population 
and, following the same methodology described above to determine the 
expected average PDPM case-mix index, we summed the case-mix index for 
each day of service in FY 2020 and then divided this by the total 
number of FY 2020 days of service. Second, we used FY 2020 data for the 
SNF population excluding those SNF stays where either the patient was 
diagnosed with COVID-19 or the stay utilized a PHE for COVID-19 related 
waiver (for example, the waiver issued under authority granted by 
section 1812(f) of the Act to allow Part A coverage of a SNF stay 
without a qualifying prior hospital stay), as identified by the 
presence of a ``DR'' condition code on the associated SNF claim. We 
evaluated the average CMI using this subset of the SNF population as we 
believe it would provide a way to identify the effect of the PHE for 
COVID-19 on FY 2020 case mix and the recalibration calculation if we 
were to use FY 2020 data collected during the PHE for COVID-19. The 
results of this analysis are provided in Table 23.

                       Table 23--Average Case-Mix Index, Expected and Actual, by Component
----------------------------------------------------------------------------------------------------------------
                                                                   Expected CMI     Actual CMI      Actual CMI
                                                                     (FY 2019        (FY 2020)       (FY 2020
                                                                     Estimate)   ---------------- without DR  or
                            Component                            ----------------                     COVID)
                                                                                    Average CMI  ---------------
                                                                    Average CMI                     Average CMI
----------------------------------------------------------------------------------------------------------------
PT..............................................................            1.53            1.50            1.52
OT..............................................................            1.52            1.51            1.52
SLP.............................................................            1.39            1.71            1.67
Nursing.........................................................            1.43            1.67            1.62
NTA.............................................................            1.14            1.20            1.21
----------------------------------------------------------------------------------------------------------------

    According to this analysis, while we observed slight decreases in 
the average CMI for the PT and OT rate components for both the full and 
subset FY 2020 populations as compared to what was expected, we 
observed significant increases in the average CMI for the SLP, Nursing, 
and NTA components for both the full and subset FY 2020 populations as 
compared to what was expected, with increases of 22.6 percent, 16.8 
percent, and 5.6 percent, respectively, for the full FY 2020 SNF 
population. We believe these significant increases in the average case-
mix for these components is primarily responsible for the inadvertent 
increase in spending under PDPM. Further, given that we observe similar 
increases in the average CMI for these components even when using the 
subset of the FY 2020 SNF population that excludes those patients 
diagnosed with COVID-19 or who used a PHE-related waiver, we believe 
that these increases in average case-mix for these components are the 
result of PDPM and not the PHE for COVID-19. We invite comments on this 
approach and the extent to which commenters believe that the PHE for 
COVID-19 may have impacted on the PDPM case-mix distribution in ways 
not captured in Table 23 or in the discussion provided here.
    Our basic methodology for recalibrating the parity adjustment has

[[Page 19988]]

been to compare total payments under the new case-mix model with what 
total payments would have been under the prior case-mix model, were the 
new model not implemented. In the context of the PDPM, this means 
comparing total FY 2020 payments under PDPM to what FY 2020 payments 
would have been under RUG-IV if PDPM were not implemented. In order to 
calculate the actual total payments under PDPM for this proposed rule, 
we used data reported on FY 2020 claims. Specifically, we used the 
Health Insurance Prospective Payment System (HIPPS) code on the SNF 
claim to identify the patient's case-mix assignment and associated 
CMIs, utilization days on the claim to calculate stay payments and to 
compute the variable per diem adjustment, the presence of an HIV 
diagnosis on the claim to account for the PDPM AIDS add-on, and 
finally, we accounted for the provider's urban or rural status. As with 
the analysis that led to Table 23, we calculated total payments both 
for the full SNF population in FY 2020, as well as the subset of that 
population removing those with a COVID-19 diagnosis and those using a 
PHE-related waiver.
    In order to calculate expected total payments under RUG-IV, in 
light of the discussion above (which describes why we believe it would 
not be appropriate simply to reclassify SNF patients under RUG-IV using 
the information reported in FY 2020), we used the percentage of stays 
in each RUG-IV group in FY 2019 and multiplied these percentages by the 
total number of FY 2020 days of service. We then multiplied the number 
of days for each RUG-IV group by the RUG-IV per diem rate, which we 
obtained by inflating the FY 2019 SNF PPS RUG-IV rates by the FY 2020 
market basket update factor, as we would have were it not for the 
implementation of PDPM. The total payments under RUG-IV also account 
for the difference in how the AIDS add-on is calculated under RUG-IV, 
as compared to PDPM, and similarly accounts for a provider's FY 2020 
urban or rural status.
    We believe that this methodology provides a more accurate 
representation of what RUG-IV payments would have been in FY 2020 were 
it not for the change in payment incentives and care provision 
precipitated by PDPM implementation, than using data reported under 
PDPM to reclassify these patients under RUG-IV. In particular, given 
the reduction in therapy utilization under PDPM, as compared to RUG-IV, 
using the therapy utilization data reported under PDPM to reclassify 
SNF patients back into RUG-IV groups would produce a case-mix 
distribution that would be significantly different from the RUG-IV 
case-mix distribution we would have expected were it not for PDPM 
implementation. Since the reduction in therapy would lead to a 
reduction in the RUG-IV case-mix assignments (for example, Ultra-High 
and Very-High Rehabilitation assignments are not nearly as prevalent 
using PDPM-reported data as they are using data that existed prior to 
PDPM), this would lead to an underestimation of what RUG-IV payments 
would have been in FY 2020. This, in turn, would lead to an 
overcorrection in recalibrating the parity adjustment due to the low 
estimated total RUG-IV payments. Additionally, given the significant 
changes in the patient assessment schedule, specifically the removal of 
the Change of Therapy Other Medicare Required Assessment, we cannot 
know if the patient would continue to remain classified in the RUG-IV 
group into which the patient classified on the 5-day assessment beyond 
that assessment window. In other words, without having an interim 
assessment between the 5-day assessment and the patient's discharge 
from the facility, we would be unable to determine if the RUG-IV group 
into which the patient classified on the 5-day assessment changed 
during the stay or if the patient continued to receive an amount of 
therapy services consistent with this initial RUG-IV classification. As 
a result, using reported data under PDPM could lead to a 
reclassification of patients under RUG-IV that is not consistent with 
how patients would have been classified under RUG-IV if PDPM had not 
been implemented. As such, we believe that using the FY 2019 RUG-IV 
case-mix distribution as a proxy for what the RUG-IV case-mix 
distribution would have been in FY 2020 were it not for PDPM 
implementation, provides a more accurate calculation of what total RUG-
IV payments would have been during FY 2020 absent PDPM implementation.
    The result of these analyses was that we identified a 5.3 percent 
increase in aggregate spending under PDPM as compared to expected total 
payments under RUG-IV for FY 2020 when considering the full SNF 
population, and a 5.0 percent increase in aggregate spending under PDPM 
for FY 2020 when considering the subset population. Although these 
results are similar, in light of the potential differences in the PDPM 
case-mix distribution which may have been precipitated by the admission 
of patients diagnosed with COVID-19 and patients whose stays utilized a 
PHE-related waiver, we believe it would be more appropriate to pursue a 
recalibration using the subset population. We invite comments on our 
methodology, particularly on the use of the FY 2019 RUG-IV case-mix 
distribution to calculate expected FY 2020 SNF payments if PDPM were 
not implemented and on using the subset FY 2020 SNF population which 
excludes patients diagnosed with COVID-19 and those using a PHE-related 
waiver in our recalibration calculation rather than the full FY 2020 
SNF population.
    Based on the above discussion and analysis, we have described above 
a potential path towards a recalibration of the PDPM parity adjustment 
using a subset of the full FY 2020 SNF data set. Since the initial 
increase applied to the PDPM CMIs to achieve budget neutrality applied 
equally across all case-mix adjusted components, we believe it would be 
appropriate, in the event an adjustment is made, to adjust the CMIs 
across all such components in equal measure. Using the methodology 
described above, the resultant PDPM parity adjustment factor would be 
lowered from 46 percent to 37 percent for each of the PDPM case-mix 
adjusted components. If this were applied for FY 2022, we estimate that 
this methodology would result in a reduction in SNF spending of 5.0 
percent, or approximately $1.7 billion.
    Tables 24 and 25 set forth what the FY 2022 PDPM CMIs and case-mix 
adjusted rates would be if we applied the recalibration methodology 
described above in FY 2022.

                                Table 24--Recalibrated PDPM Case-Mix Adjusted Federal Rates and Associated Indexes--URBAN
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                               Nursing    Nursing
          PDPM group             PT CMI    PT rate     OT CMI    OT rate    SLP CMI    SLP rate  Nursing CMG     CMI        rate     NTA CMI    NTA rate
--------------------------------------------------------------------------------------------------------------------------------------------------------
A............................       1.44     $90.49       1.40     $81.89       0.64     $15.01  ES3........       3.82    $418.48       3.05    $252.05
B............................       1.60     100.54       1.53      89.49       1.71      40.12  ES2........       2.89     316.60       2.38     196.68
C............................       1.77     111.23       1.59      93.00       2.51      58.88  ES1........       2.76     302.36       1.73     142.97
D............................       1.81     113.74       1.44      84.23       1.37      32.14  HDE2.......       2.26     247.58       1.25     103.30

[[Page 19989]]

 
E............................       1.34      84.21       1.33      77.79        2.2      51.61  HDE1.......       1.87     204.86        0.9      74.38
F............................       1.52      95.52       1.51      88.32       2.80      65.69  HBC2.......       2.11     231.15       0.68      56.20
G............................       1.57      98.66       1.54      90.07       1.92      45.04  HBC1.......       1.75     191.71  .........  .........
H............................       1.09      68.50       1.08      63.17       2.69      63.11  LDE2.......       1.96     214.72  .........  .........
I............................       1.06      66.61       1.11      64.92       3.32      77.89  LDE1.......       1.63     178.57  .........  .........
J............................       1.34      84.21       1.36      79.55       2.81      65.92  LBC2.......       1.62     177.47  .........  .........
K............................       1.43      89.86       1.45      84.81       3.48      81.64  LBC1.......       1.35     147.89  .........  .........
L............................       1.03      64.73       1.04      60.83       3.96      92.90  CDE2.......       1.76     192.81  .........  .........
M............................       1.20      75.41       1.22      71.36  .........  .........  CDE1.......       1.52     166.52  .........  .........
N............................       1.39      87.35       1.41      82.47  .........  .........  CBC2.......       1.46     159.94  .........  .........
O............................       1.46      91.75       1.46      85.40  .........  .........  CA2........       1.03     112.84  .........  .........
P............................       1.02      64.10       1.03      60.24  .........  .........  CBC1.......       1.26     138.03  .........  .........
Q............................  .........  .........  .........  .........  .........  .........  CA1........       0.88      96.40  .........  .........
R............................  .........  .........  .........  .........  .........  .........  BAB2.......       0.98     107.36  .........  .........
S............................  .........  .........  .........  .........  .........  .........  BAB1.......       0.93     101.88  .........  .........
T............................  .........  .........  .........  .........  .........  .........  PDE2.......       1.48     162.13  .........  .........
U............................  .........  .........  .........  .........  .........  .........  PDE1.......       1.38     151.18  .........  .........
V............................  .........  .........  .........  .........  .........  .........  PBC2.......       1.15     125.98  .........  .........
W............................  .........  .........  .........  .........  .........  .........  PA2........       0.67      73.40  .........  .........
X............................  .........  .........  .........  .........  .........  .........  PBC1.......       1.06     116.12  .........  .........
Y............................  .........  .........  .........  .........  .........  .........  PA1........       0.62      67.92  .........  .........
--------------------------------------------------------------------------------------------------------------------------------------------------------


                                Table 25: Recalibrated PDPM Case-Mix Adjusted Federal Rates and Associated Indexes--RURAL
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                               Nursing    Nursing
          PDPM group             PT CMI    PT rate     OT CMI    OT rate    SLP CMI    SLP rate  Nursing CMG     CMI        rate     NTA CMI    NTA rate
--------------------------------------------------------------------------------------------------------------------------------------------------------
A............................       1.44    $103.15       1.40     $92.11       0.64     $18.92  ES3........       3.82    $399.80       3.05    $240.83
B............................       1.60     114.61       1.53     100.66       1.71      50.55  ES2........       2.89     302.47       2.38     187.92
C............................       1.77     126.79       1.59     104.61       2.51      74.20  ES1........       2.76     288.86       1.73     136.60
D............................       1.81     129.65       1.44      94.74       1.37      40.50  HDE2.......       2.26     236.53       1.25      98.70
E............................       1.34      95.98       1.33      87.50        2.2      65.03  HDE1.......       1.87     195.71        0.9      71.06
F............................       1.52     108.88       1.51      99.34        2.8      82.77  HBC2.......       2.11     220.83       0.68      53.69
G............................       1.57     112.46       1.54     101.32       1.92      56.76  HBC1.......       1.75     183.16  .........  .........
H............................       1.09      78.08       1.08      71.05       2.69      79.52  LDE2.......       1.96     205.13  .........  .........
I............................       1.06      75.93       1.11      73.03       3.32      98.14  LDE1.......       1.63     170.60  .........  .........
J............................       1.34      95.98       1.36      89.47       2.81      83.06  LBC2.......       1.62     169.55  .........  .........
K............................       1.43     102.43       1.45      95.40       3.48     102.87  LBC1.......       1.35     141.29  .........  .........
L............................       1.03      73.78       1.04      68.42       3.96     117.06  CDE2.......       1.76     184.20  .........  .........
M............................       1.20      85.96       1.22      80.26  .........  .........  CDE1.......       1.52     159.08  .........  .........
N............................       1.39      99.57       1.41      92.76  .........  .........  CBC2.......       1.46     152.80  .........  .........
O............................       1.46     104.58       1.46      96.05  .........  .........  CA2........       1.03     107.80  .........  .........
P............................       1.02      73.06       1.03      67.76  .........  .........  CBC1.......       1.26     131.87  .........  .........
Q............................  .........  .........  .........  .........  .........  .........  CA1........       0.88      92.10  .........  .........
R............................  .........  .........  .........  .........  .........  .........  BAB2.......       0.98     102.57  .........  .........
S............................  .........  .........  .........  .........  .........  .........  BAB1.......       0.93      97.33  .........  .........
T............................  .........  .........  .........  .........  .........  .........  PDE2.......       1.48     154.90  .........  .........
U............................  .........  .........  .........  .........  .........  .........  PDE1.......       1.38     144.43  .........  .........
V............................  .........  .........  .........  .........  .........  .........  PBC2.......       1.15     120.36  .........  .........
W............................  .........  .........  .........  .........  .........  .........  PA2........       0.67      70.12  .........  .........
X............................  .........  .........  .........  .........  .........  .........  PBC1.......       1.06     110.94  .........  .........
Y............................  .........  .........  .........  .........  .........  .........  PA1........       0.62      64.89  .........  .........
--------------------------------------------------------------------------------------------------------------------------------------------------------

    We invite comments on the methodology described in this section of 
the proposed rule for recalibrating the PDPM parity adjustment, as well 
as the findings of our analysis described throughout this section. To 
assist commenters in providing comments on this issue, we have also 
posted a file on the CMS website, at https://www.cms.gov/snfpps, which 
provides the FY 2019 RUG-IV case-mix distribution and calculation of 
total payments under RUG-IV, as well as PDPM case-mix utilization data 
at the case-mix group and component level to demonstrate the 
calculation of total payments under PDPM. As we noted in the FY 2012 
SNF PPS final rule (76 FR 48493), we believe it is imperative that we 
act in a well-considered but expedient manner once excess payments are 
identified, as we did in FY 2012.
    However, in the event we confirm the finding that the current 
implementation of PDPM is not budget neutral and that a recalibration 
is appropriate, despite the importance of ensuring that PDPM is budget 
neutral going forward, we acknowledge the possibility that applying 
such a significant reduction in payments in a single year and without 
time to prepare for the reduction in revenue could create a financial 
burden for providers. In light of this possibility, we are also 
considering a number of potential mitigation strategies that would help 
to ease the transition to prospective budget neutrality in the event an 
adjustment is finalized. These strategies fall into two broad 
categories: Delayed implementation; and phased implementation.
    With regard to a delayed implementation strategy, this would mean 
that we would implement the reduction in payment, or some portion of 
the reduction in payment if combined with a phased implementation 
approach described below, in a later year than the year in which the 
reduction is finalized. For example, considering the 5 percent 
reduction discussed above, if this reduction was finalized in FY 2022 
with

[[Page 19990]]

a 1 year delayed implementation, this would mean that the full 5 
percent reduction would be prospectively applied to the PDPM CMIs in FY 
2023. If the reduction was finalized in FY 2022 with a 2 year delayed 
implementation, then the reduction in the PDPM CMIs would be applied 
prospectively beginning in FY 2024. This type of strategy, on its own, 
does not serve to mitigate the overall amount of the reduction in a 
single year, but rather serves to provide facilities with time to 
prepare for the impending reduction in payments. We solicit comments on 
whether stakeholders believe that, in the event we finalize the parity 
adjustment recalibration, we should finalize this recalibration with a 
delayed implementation. Additionally, to the extent that stakeholders 
believe that a delayed implementation would be warranted, we solicit 
comments on the appropriate length of the delay.
    With regard to a phased implementation strategy, this would mean 
that the amount of the reduction would be spread out over some number 
of years. Such an approach helps to mitigate the impact of the 
reduction in payments by applying only a portion of the reduction in a 
given year. For example, if we were to use a 2-year phased 
implementation approach to the 5 percent reduction discussed above, 
this would mean that the PDPM CMIs would be reduced by 2.5 percent in 
the first year of implementation and then reduced by the remaining 2.5 
percent in the second and final year of implementation. So, for 
example, if this adjustment was finalized for FY 2022, then the PDPM 
CMIs would be reduced by 2.5 percent in FY 2022 and then reduced by an 
additional 2.5 percent in FY 2023. We note that the number of years for 
a phased implementation approach could be as little as 2 years but as 
long as necessary to appropriately mitigate the yearly impact of the 
reduction. For example, we could implement a 5-year phased approach for 
this reduction, which would apply a one percent reduction to the PDPM 
CMIs each year for 5 years. We solicit comments on the need for a 
phased implementation approach to recalibrating the PDPM parity 
adjustment, as well as on the appropriate length of such an approach.
    We would, finally, note that these mitigation strategies may be 
used in combination with each other. For example, we could finalize a 2 
year phased approach with a 1 year delayed implementation. Using FY 
2022 as the hypothetical year in which such an approach could be 
finalized, this would mean that there would be no reduction to the PDPM 
CMIs in FY 2022, a 2.5 percent reduction to the PDPM CMIs in FY 2023 
and then a 2.5 percent reduction in the PDPM CMIs in FY 2024. We 
solicit comments on the possibility of combining these approaches and 
what stakeholders believe would be appropriate, using these approaches, 
to appropriately mitigate the impact of the reduction in SNF PPS 
payments.
    We note that in any of these options, the adjustment would be 
applied prospectively, and the case mix indexes would not be adjusted 
to account for deviations from budget neutrality in years before the 
payment adjustments were implemented.
    We are considering these approaches as they may be warranted to 
mitigate potential negative impacts on providers resulting from 
implementation of such a reduction in the SNF PPS rates entirely within 
a single year in the event we determine that recalibrating the parity 
adjustment is necessary to achieve budget neutrality. However, we 
believe that these alternatives would continue to reimburse in amounts 
that significantly exceed our intended policy in excess of the rates 
that would have been paid had we maintained the prior payment 
classification system rather than in a budget neutral manner as 
intended, and as we stated above, we believe it is imperative that we 
act in a well-considered but appropriately expedient manner once excess 
payments are identified. In addition, as we move forward with programs 
designed to enhance and restructure our post-acute care payment 
systems, we believe that payments under the SNF PPS should be 
established at their intended and most appropriate levels as quickly as 
possible. Moreover, stabilizing the baseline is a necessary first step 
toward properly implementing and maintaining the integrity of the PDPM 
classification methodology and the SNF PPS as a whole as discussed 
above. We invite comments on the mitigation strategies described above 
for mitigating the impact of recalibrating the PDPM parity adjustment 
in the event we finalize a recalibration.

VI. Skilled Nursing Facility (SNF) Quality Reporting Program (QRP)

A. Background and Statutory Authority

    The Skilled Nursing Facility Quality Reporting Program (SNF QRP) is 
authorized by section 1888(e)(6) of the Act, and it applies to 
freestanding SNFs, SNFs affiliated with acute care facilities, and all 
non-CAH swing-bed rural hospitals. Section 1888(e)(6)(A)(i) of the Act 
requires the Secretary to reduce by 2 percentage points the annual 
market basket percentage update described in section 1888(e)(5)(B)(i) 
of the Act applicable to a SNF for a fiscal year, after application of 
section 1888(e)(5)(B)(ii) of the Act (the multifactor productivity 
(MFP) adjustment) and section 1888(e)(5)(B)(iii) of the Act, in the 
case of a SNF that does not submit data in accordance with sections 
1888(e)(6)(B)(i)(II) and (III) of the Act for that fiscal year. For 
more information on the requirements we have adopted for the SNF QRP, 
we refer readers to the FY 2016 SNF PPS final rule (80 FR 46427 through 
46429), FY 2017 SNF PPS final rule (81 FR 52009 through 52010), FY 2018 
SNF PPS final rule (82 FR 36566 through 36605), FY 2019 SNF PPS final 
rule (83 FR 39162 through 39272), and FY 2020 SNF PPS final rule (84 FR 
38728 through 38820).

B. General Considerations Used for the Selection of Measures for the 
SNF QRP

    For a detailed discussion of the considerations we use for the 
selection of SNF QRP quality, resource use, or other measures, we refer 
readers to the FY 2016 SNF PPS final rule (80 FR 46429 through 46431).
1. Quality Measures Currently Adopted for the FY 2022 SNF QRP
    The SNF QRP currently has 13 measures for the FY 2022 SNF QRP, 
which are outlined in Table 26. For a discussion of the factors used to 
evaluate whether a measure should be removed from the SNF QRP, we refer 
readers to 42 CFR 413.360(b)(3).

  Table 26--Quality Measures Currently Adopted for the FY 2022 SNF QRP
------------------------------------------------------------------------
            Short name                   Measure name & data source
------------------------------------------------------------------------
   Resident Assessment Instrument Minimum Data Set (Assessment-Based)
------------------------------------------------------------------------
Pressure Ulcer/Injury.............  Changes in Skin Integrity Post-Acute
                                     Care: Pressure Ulcer/Injury.

[[Page 19991]]

 
Application of Falls..............  Application of Percent of Residents
                                     Experiencing One or More Falls with
                                     Major Injury (Long Stay) (NQF
                                     #0674).
Application of Functional           Application of Percent of Long-Term
 Assessment/Care Plan.               Care Hospital (LTCH) Patients with
                                     an Admission and Discharge
                                     Functional Assessment and a Care
                                     Plan That Addresses Function (NQF
                                     #2631).
Change in Mobility Score..........  Application of IRF Functional
                                     Outcome Measure: Change in Mobility
                                     Score for Medical Rehabilitation
                                     Patients (NQF #2634).
Discharge Mobility Score..........  Application of IRF Functional
                                     Outcome Measure: Discharge Mobility
                                     Score for Medical Rehabilitation
                                     Patients (NQF #2636).
Change in Self-Care Score.........  Application of the IRF Functional
                                     Outcome Measure: Change in Self-
                                     Care Score for Medical
                                     Rehabilitation Patients (NQF
                                     #2633).
Discharge Self-Care Score.........  Application of IRF Functional
                                     Outcome Measure: Discharge Self-
                                     Care Score for Medical
                                     Rehabilitation Patients (NQF
                                     #2635).
DRR...............................  Drug Regimen Review Conducted With
                                     Follow-Up for Identified Issues--
                                     Post Acute Care (PAC) Skilled
                                     Nursing Facility (SNF) Quality
                                     Reporting Program (QRP).
TOH-Provider *....................  Transfer of Health Information to
                                     the Provider Post-Acute Care (PAC).
TOH-Patient *.....................  Transfer of Health Information to
                                     the Patient Post-Acute Care (PAC).
------------------------------------------------------------------------
                              Claims-Based
------------------------------------------------------------------------
MSPB SNF..........................  Medicare Spending Per Beneficiary
                                     (MSPB)-Post Acute Care (PAC)
                                     Skilled Nursing Facility (SNF)
                                     Quality Reporting Program (QRP).
DTC...............................  Discharge to Community (DTC)-Post
                                     Acute Care (PAC) Skilled Nursing
                                     Facility (SNF) Quality Reporting
                                     Program (QRP) (NQF #3481).
PPR...............................  Potentially Preventable 30-Day Post-
                                     Discharge Readmission Measure for
                                     Skilled Nursing Facility (SNF)
                                     Quality Reporting Program (QRP).
------------------------------------------------------------------------
* In response to the public health emergency (PHE) for the Coronavirus
  Disease 2019 (COVID-19), CMS released an Interim Final Rule (85 FR
  27595 through 27597) which delayed the compliance date for collection
  and reporting of the Transfer of Health Information measures for at
  least two full fiscal years after the end of the PHE.

C. SNF QRP Quality Measure Proposals Beginning With the FY 2023 SNF QRP

    Section 1899B(h)(1) of the Act permits the Secretary to remove, 
suspend, or add quality measures or resource use or other measures 
described in sections 1899B(c)(1) and (d)(1) of the Act, respectively, 
so long as the Secretary publishes in the Federal Register (with a 
notice and comment period) a justification for such removal, suspension 
or addition. Section 1899B(a)(1)(B) of the Act requires that all of the 
data that must be reported in accordance with section 1899B(a)(1)(A) of 
the Act (including resource use or other measure data under section 
1899B(d)(1)) be standardized and interoperable to allow for the 
exchange of the information among post-acute care (PAC) providers and 
other providers and the use by such providers of such data to enable 
access to longitudinal information and to facilitate coordinated care.
    We propose to adopt two new measures for the SNF QRP beginning with 
the FY 2023 SNF QRP: The SNF Healthcare-Associated Infections Requiring 
Hospitalization measure (SNF HAI) and the COVID-19 Vaccination Coverage 
among Healthcare Personnel (HCP) \4\ measure as an ``other measure'' 
under section 1899B(d)(1) of the Act. The SNF HAI measure is an outcome 
measure. The data used to report the SNF HAI measure are standardized 
and interoperable and would allow providers to exchange this data and 
compare outcomes across the care continuum and PAC settings. Clinical 
data captured in every clinical setting informs a resident's current 
medical care plan, facilitates coordinated care, and improves Medicare 
beneficiary outcomes. We plan to develop HAI measures in other PAC 
settings, such as the Inpatient Rehabilitation Facility (IRF) Quality 
Reporting Program and the Long-Term Care Hospital (LTCH) Quality 
Reporting Program. The proposed measure supports the CMS Meaningful 
Measures Initiative through the Making Care Safer by Reducing Harm 
Caused in the Delivery of Care domain. We have previously solicited 
feedback on the SNF HAI measure as a future measure for the SNF QRP and 
received several comments of support as well as a few comments 
recommending suggestions (84 FR 38765). The measure is described in 
more detail below.
---------------------------------------------------------------------------

    \4\ The measure steward changed the name of the measure from 
SARS-CoV-2 Vaccination Coverage among Healthcare Personnel to COVID-
19 Vaccination Coverage among Healthcare Personnel. There were no 
changes to the measure itself, other than the name change.
---------------------------------------------------------------------------

    We are proposing the COVID-19 Vaccination Coverage among HCP 
measure as an ``other'' measure under section 1899B(d)(1) of the Act 
beginning with the FY 2023 SNF QRP. In accordance with section 
1899B(a)(1)(B) of the Act, the data used to calculate this measure are 
standardized and interoperable. The proposed measure supports the 
Meaningful Measures domain of Promote Effective Prevention and 
Treatment of Chronic Disease. We identified the measure concept as a 
priority in response to the current public health crisis. This process 
measure was developed with the Centers for Disease Control and 
Prevention (CDC) to track COVID-19 vaccination coverage among HCP in 
the SNF setting. This measure is described in more detail below.
    In addition, we propose to update the denominator for one measure, 
the Transfer of Health (TOH) Information to the Patient--Post-Acute 
Care (PAC) measure to exclude residents discharged home under the care 
of an organized home health service or hospice.
1. Proposed Skilled Nursing Facility (SNF) Healthcare-Associated 
Infections (HAI) Requiring Hospitalization Quality Measure Beginning 
With the FY 2023 SNF QRP
a. Background
    Monitoring the occurrence of HAIs among SNF residents can provide 
valuable information about a SNF's quality of care. Although HAIs are 
not considered ``never events'', or serious adverse errors in the 
provision of health care services that should never occur,

[[Page 19992]]

most are preventable as they are often the result of poor processes and 
structures of care.\5\ Evidence suggests there is a wide variation in 
HAI rates among SNF providers. An analysis of FY 2018 SNF claims 
indicates a performance gap in HAI rates across SNFs. Among the 14,347 
SNFs included in the sample for the analysis, risk-adjusted measure 
scores ranged from a minimum of 2.19 percent to a maximum of 19.83 
percent. Further, a 2014 report from the Office of the Inspector 
General (OIG) estimated that one in four adverse events among SNF 
residents are due to HAIs, and more than half of all HAIs are 
potentially preventable.\6\ Typically, HAIs result from inadequate 
patient management following a medical intervention, such as surgery or 
device implementation, or poor adherence to protocol and antibiotic 
stewardship guidelines.7 8 9 Several provider 
characteristics are also related to HAIs including staffing levels (for 
example, high turnover, low staff-to-resident ratios, etc.), facility 
structure characteristics (for example, national chain membership, high 
occupancy rates, etc.), and adoption or lack thereof of infection 
surveillance and prevention policies.10 11 12 13 14 15 
Inadequate prevention and treatment of HAIs is likely to result in poor 
health care outcomes for residents and wasteful resource use. For 
example, HAIs are associated with longer lengths of stay, use of 
higher-intensity care (for example, critical care services and hospital 
readmissions), increased mortality, and high health care 
costs.\16,17,18,19\ Monitoring SNF HAI rates would provide information 
about each facility's adeptness in infection prevention and management.
---------------------------------------------------------------------------

    \5\ CMS. (2006). Eliminating Serious Preventable, and Costly 
Medical Errors--Never Events. Retrieved from https://www.cms.gov/newsroom/fact-sheets/eliminating-serious-preventable-and-costly-medical-errors-never-events.
    \6\ Office of Inspector General. (2014). Adverse events in 
skilled nursing facilities: National incidence among Medicare 
beneficiaries. Retrieved from https://oig.hhs.gov/oei/reports/oei-06-11-00370.pdf.
    \7\ Beganovic, M., & Laplante, K. (2018). Communicating with 
Facility Leadership; Metrics for Successful Antimicrobial 
Stewardship Programs (Asp) in Acute Care and Long-Term Care 
Facilities. Rhode Island medical journal (2013), 101(5) (2018), 45-
49.
    \8\ Cooper, D., McFarland, M., Petrilli, F., & Shells, C. 
(2019). Reducing inappropriate antibiotics for urinary tract 
infections in long-term care: A replication study. Journal of 
Nursing Care Quality, 34(1), 16-21. http://dx.doi.org/10.1097/NCQ.0000000000000343.
    \9\ Feldstein, D., Sloane, P.D., & Feltner, C. (2018). 
Antibiotic stewardship programs in nursing homes: A systematic 
review. Journal of the American Medical Directors Association, 
19(2), 110-116. http://dx.doi.org/10.1016/j.jamda.2017.06.019.
    \10\ Castle, N., Engberg, J.B., Wagner, L.M., & Handler, S. 
(2017). Resident and facility factors associated with the incidence 
of urinary tract infections identified in the Nursing Home Minimum 
Data Set. Journal of Applied Gerontology, 36(2), 173-194. http://dx.doi.org/10.1177/0733464815584666.
    \11\ Crnich, C.J., Jump, R., Trautner, B., Sloane, P.D., & Mody, 
L. (2015). Optimizing antibiotic stewardship in nursing homes: A 
narrative review and recommendations for improvement. Drugs & Aging, 
32(9), 699-716. http://dx.doi.org/10.1007/s40266-015-0292-7.
    \12\ Dick, A.W., Bell, J.M., Stone, N.D., Chastain, A.M., 
Sorbero, M., & Stone, P.W. (2019). Nursing home adoption of the 
National Healthcare Safety Network Long-term Care Facility 
Component. American Journal of Infection Control, 47(1), 59-64. 
http://dx.doi.org/10.1016/j.ajic.2018.06.018.
    \13\ Cooper, D., McFarland, M., Petrilli, F., & Shells, C. 
(2019). Reducing inappropriate antibiotics for urinary tract 
infections in long-term care: A replication study. Journal of 
Nursing Care Quality, 34(1), 16-21. http://dx.doi.org/10.1097/NCQ.0000000000000343.
    \14\ Gucwa, A.L., Dolar, V., Ye, C., & Epstein, S. (2016). 
Correlations between quality ratings of skilled nursing facilities 
and multidrug-resistant urinary tract infections. American Journal 
of Infection Control, 44(11), 1256-1260. http://dx.doi.org/10.1016/j.ajic.2016.03.015.
    \15\ Travers, J.L., Stone, P.W., Bjarnadottir, R.I., 
Pogorzelska-Maziarz, M., Castle, N.G., & Herzig, C.T. (2016). 
Factors associated with resident influenza vaccination in a national 
sample of nursing homes. American Journal of Infection Control, 
44(9), 1055-1057. http://dx.doi.org/10.1016/j.ajic.2016.01.019.
    \16\ CMS. (2006). Eliminating Serious Preventable, and Costly 
Medical Errors--Never Events. Retrieved from https://www.cms.gov/newsroom/fact-sheets/eliminating-serious-preventable-and-costly-medical-errors-never-events.
    \17\ Centers for Disease Control and Prevention (2009). The 
Direct Medical Costs of Healthcare-Associated Infections in U.S. 
Hospitals and the Benefits of Prevention. Retrieved from https://www.cdc.gov/hai/pdfs/hai/scott_costpaper.pdf.
    \18\ Ouslander, J.G., Diaz, S., Hain, D., & Tappen, R. (2011). 
Frequency and diagnoses associated with 7- and 30-day readmission of 
skilled nursing facility patients to a nonteaching community 
hospital. Journal of the American Medical Directors Association, 
12(3), 195-203. http://dx.doi.org/10.1016/j.jamda.2010.02.015.
    \19\ Zimlichman, E., Henderson, D., Tamir, O., Franz, C., Song, 
P., Yamin, C.K., . . . Bates, D.W. (2013). Health care-associated 
infections: A meta-analysis of costs and financial impact on the US 
health care system. JAMA Internal Medicine, 173(22), 2039-2046. 
Retrieved from https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/1733452.
---------------------------------------------------------------------------

    Addressing HAIs in SNFs is particularly important as several 
factors place SNF residents at high risk for infection, including 
increased age, cognitive and functional decline, use of indwelling 
devices, frequent care transitions, and close contact with other 
resident and healthcare workers.20 21 Furthermore, in SNFs, 
COVID-19 has a disproportionate impact on racial and ethnic minorities 
as well as people living with disabilities.22 23 Emerging 
COVID-19 studies reveal higher patient spread due to poor infection 
control, staff rotations between multiple SNFs, and poor patient COVID-
19 screenings.24 25 An analysis comparing SNF HAI rates 
using FY 2019 data with the currently reported rates of COVID-19 in 
SNFs found that nursing homes with higher HAI rates in FY 2019 also 
have a higher number of COVID-19 cases.\26\ This analysis was presented 
to the PAC-LTC MAP Workgroup at the January 11th meeting (http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94559, slide 134). We believe this 
finding supports a relationship not only between this measure and 
overall HAI prevention and control in SNFs, but also in predicting 
those SNFs more likely to have higher rates of infection in future 
pandemics. Several interventions may reduce HAI rates among SNFs, thus 
improving quality of care. These interventions include the adoption of 
infection surveillance and prevention policies, safety procedures, 
antibiotic stewardship, and staff education and training

[[Page 19993]]

programs.27 28 29 30 31 32 33 Additionally, infection 
prevention and control programs with core components in education, 
monitoring, and feedback on infection rates from surveillance programs 
or feedback on infection control practices from audits have been found 
to be successful interventions for reducing HAIs.\34\ The effectiveness 
of these interventions suggests improvement of HAI rates among SNF 
residents is possible through modifying provider-led processes and 
interventions.
---------------------------------------------------------------------------

    \20\ Montoya, A., & Mody, L. (2011). Common infections in 
nursing homes: A review of current issues and challenges. Aging 
Health, 7(6), 889-899. http://dx.doi.org/10.2217/ahe.11.80.
    \21\ Office of Disease Prevention and Health Promotion. (2013). 
Long-term care facilities. In U.S. Department of Health and Human 
Services, National action plan to prevent health care-associated 
infections: Road map to elimination (pp. 194-239). Retrieved from 
https://health.gov/our-work/health-care-quality/health-care-associated-infections/national-hai-action-plan.
    \22\ Chidambaram, P., Neuman T., Garfield R. (2020). Racial and 
Ethnic Disparities in COVID-19 Cases and Deaths in Nursing Homes. 
Retrieved from https://www.kff.org/coronavirus-covid-19/issue-brief/racial-and-ethnic-disparities-in-covid-19-cases-and-deaths-in-nursing-homes/.
    \23\ Li Y., Cen X., Temkin-Greener R. (2020). Racial and Ethnic 
Disparities in COVID-19 Infections and Deaths Across U.S. Nursing 
Homes. Journal of the American Geriatrics Society, 68(11), 2454-
2461. https://pubmed.ncbi.nlm.nih.gov/32955105/.
    \24\ Kimball, A., Hatfield, K.M., Arons, M., James, A., Taylor, 
J., Spicer, K., Bardossy, A.C., Oakley, L.P., Tanwar, S., Chisty, 
Z., Bell, J.M., Methner, M., Harney, J., Jacobs, J.R., Carlson, 
C.M., McLaughlin, H.P., Stone, N., Clark, S., Brostrom-Smith, C., 
Page, L.C., . . . CDC COVID-19 Investigation Team (2020). 
Asymptomatic and Presymptomatic SARS-CoV-2 Infections in Residents 
of a Long-Term Care Skilled Nursing Facility--King County, 
Washington, March 2020. MMWR. Morbidity and mortality weekly report, 
69(13), 377-381. https://doi.org/10.15585/mmwr.mm6913e1.
    \25\ McMichael, T.M., Clark, S., Pogosjans, S., Kay, M., Lewis, 
J., Baer, A., Kawakami, V., Lukoff, M.D., Ferro, J., Brostrom-Smith, 
C., Riedo, F.X., Russell, D., Hiatt, B., Montgomery, P., Rao, A.K., 
Currie, D.W., Chow, E.J., Tobolowsky, F., Bardossy, A.C., Oakley, 
L.P., . . . Public Health--Seattle & King County, EvergreenHealth, 
and CDC COVID-19 Investigation Team (2020). COVID-19 in a Long-Term 
Care Facility--King County, Washington, February 27-March 9, 2020. 
MMWR. Morbidity and mortality weekly report, 69(12), 339-342. 
https://doi.org/10.15585/mmwr.mm6912e1.
    \26\ The CMS COVID-19 Nursing Home Dataset used in this analysis 
was not limited to just the SNF, but applied to the entire nursing 
home. The study population of the analysis includes Medicare-
certified nursing homes providing SNF care.
    \27\ Office of Inspector General. (2014). Adverse events in 
skilled nursing facilities: National incidence among Medicare 
beneficiaries. Retrieved from https://oig.hhs.gov/oei/reports/oei-06-11-00370.pdf.
    \28\ Beganovic, M., & Laplante, K. (2018). Communicating with 
Facility Leadership; Metrics for Successful Antimicrobial 
Stewardship Programs (Asp) in Acute Care and Long-Term Care 
Facilities. Rhode Island medical journal (2013), 101(5) (2018), 45-
49.
    \29\ Crnich, C.J., Jump, R., Trautner, B., Sloane, P.D., & Mody, 
L. (2015). Optimizing antibiotic stewardship in nursing homes: A 
narrative review and recommendations for improvement. Drugs & Aging, 
32(9), 699-716. http://dx.doi.org/10.1007/s40266-015-0292-7.
    \30\ Freeman-Jobson, J.H., Rogers, J.L., & Ward-Smith, P. 
(2016). Effect of an education presentation on the knowledge and 
awareness of urinary tract infection among non-licensed and licensed 
health care workers in long-term care facilities. Urologic Nursing, 
36(2), 67-71. http://dx.doi.org/10.7257/1053-816X.2016.36.2.67 
Crnich, C.J., Jump, R., Trautner, B., Sloane, P.D., & Mody, L. 
(2015). Optimizing antibiotic stewardship in nursing homes: A 
narrative review and recommendations for improvement. Drugs & Aging, 
32(9), 699-716. http://dx.doi.org/10.1007/s40266-015-0292-7.
    \31\ Hutton, D.W., Krein, S.L., Saint, S., Graves, N., Kolli, 
A., Lynem, R., & Mody, L. (2018). Economic evaluation of a catheter-
associated urinary tract infection prevention program in nursing 
homes. Journal of the American Geriatrics Society, 66(4), 742-747. 
http://dx.doi.org/10.1111/jgs.15316.
    \32\ Nguyen, H.Q., Tunney, M.M., & Hughes, C.M. (2019). 
Interventions to Improve Antimicrobial Stewardship for Older People 
in Care Homes: A Systematic Review. Drugs & aging, 36(4), 355-369. 
https://doi.org/10.1007/s40266-019-00637-0.
    \33\ Sloane, P.D., Zimmerman, S., Ward, K., Kistler, C.E., 
Paone, D., Weber, D.J., Wretman, C.J., & Preisser, J.S. (2020). A 2-
Year Pragmatic Trial of Antibiotic Stewardship in 27 Community 
Nursing Homes. Journal of the American Geriatrics Society, 68(1), 
46-54. https://doi.org/10.1111/jgs.16059.
    \34\ Lee, M.H., Lee GA, Lee SH, Park YH (2019). Effectiveness 
and core components of infection prevention and control programmes 
in long-term care facilities: A systematic review. Retrieved from 
https://pubmed.ncbi.nlm.nih.gov/30794854/.
---------------------------------------------------------------------------

    The proposed SNF HAI measure uses Medicare fee-for-service (FFS) 
claims data to estimate the risk-standardized rate of HAIs that are 
acquired during SNF care and result in hospitalization. Unlike other 
HAI measures that target specific infections, this measure would target 
all HAIs serious enough to require admission to an acute care hospital. 
Given the current COVID-19 public health emergency, we believe this 
measure would promote patient safety and increase the transparency of 
quality of care in the SNF setting. This measure also compares SNFs to 
their peers to statistically separate those that perform better than or 
worse than each other in infection prevention and management. We 
believe peer comparison would encourage SNFs to improve the quality of 
care they deliver.
b. Stakeholder and Technical Expert Panel (TEP) Input
    In our development and specification of this measure, we employed a 
transparent process in which we sought input from stakeholders and 
national experts and engaged in a process that allowed for pre-
rulemaking input, in accordance with section 1890A of the Act.
    To meet this requirement, we provided the following opportunities 
for stakeholder input. Our measure development contractor for the SNF 
HAI measure convened a Technical Expert Panel (TEP) on May 9, 2019 to 
obtain expert input on the development of an HAI measure for use in the 
SNF QRP. The TEP consisted of stakeholders with a diverse range of 
expertise, including SNF and PAC subject matter knowledge, clinical and 
infectious disease expertise, patient and family perspectives, and 
measure development experience. The TEP supported the proposed measure 
concept and provided substantive input regarding the measure's 
specifications. Recommendations provided by the TEP included refining 
the measure's operational definition, exclusion criteria, and HAI ICD-
10 diagnosis code list, among other considerations. All recommendations 
from the TEP were taken into consideration and applied appropriately 
where feasible. A summary of the TEP proceedings titled SNF HAI Final 
TEP Report is available on the SNF QRP Measures and Technical 
Information page at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Measures-and-Technical-Information.
    Following the TEP, our measure development contractor released 
draft quality measure specifications for public comment on the SNF HAI 
measure. Stakeholder feedback was solicited on the proposed measure by 
requesting comment on the CMS Measures Management System Blueprint 
site. The comment submission period was from September 14, 2020 to 
October 14, 2020. Comments on the measure varied. Many commenters 
supported the idea of adopting an HAI measure to improve prevention 
efforts; however, commenters also offered criticisms about the 
measure's specifications and implementation. The summary report of the 
September 14 to October 14, 2020 public comment period titled SNF HAI 
Public Comment Summary Report is available on the SNF QRP Measures and 
Technical Information page at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Measures-and-Technical-Information.
c. Measure Applications Partnership (MAP) Review
    Our pre-rulemaking process includes making publicly available a 
list of quality and efficiency measures, called the Measures under 
Consideration (MUC) List, that the Secretary is considering adopting 
through the Federal rulemaking process for use in Medicare programs. 
This allows multi-stakeholder groups to provide recommendations to the 
Secretary on the measures included on the list.
    We included the SNF HAI measure under the SNF QRP Program in the 
publicly available ``List of Measures under Consideration for December 
21, 2020'' (MUC List).\35\ The National Quality Forum (NQF)-convened 
Measure Applications Partnership (MAP) Post-Acute Care/Long-Term Care 
(PAC-LTC) workgroup met virtually on January 11, 2021 and provided 
input on the proposed measure. The MAP offered conditional support of 
the SNF HAI measure for rulemaking contingent upon NQF endorsement, 
noting that the measure adds value to the SNF QRP by presenting one 
overall measurement of all HAIs acquired during SNF care that result in 
hospitalizations, information that is not currently available. The MAP 
recognized that the proposed measure is intended to reflect global 
infection control for a facility, and may encourage SNFs to access 
processes and perform interventions to reduce adverse events among SNF 
residents that are due to HAIs. The MAP Rural Health

[[Page 19994]]

Workgroup also agreed that the SNF HAI measure is suitable for use with 
rural providers in the SNF QRP. The final MAP report is available at 
http://www.qualityforum.org/Publications/2021/03/MAP_2020-2021_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
---------------------------------------------------------------------------

    \35\ National Quality Forum. List of Measures Under 
Consideration for December 21, 2020. Accessed at https://www.cms.gov/files/document/measures-under-consideration-list-2020-report.pdf on January 12, 2021.
---------------------------------------------------------------------------

    Additionally, measure testing was conducted on the SNF HAI measure. 
Split-half testing revealed the proposed measure's moderate 
reliability. Validity testing of the measure showed good model 
discrimination as the HAI model can accurately predict HAI cases while 
controlling for differences in resident case-mix. The SNF HAI TEP also 
showed strong support for the face validity of the proposed measure. 
For measure testing details, refer to the document titled, Skilled 
Nursing Facility Healthcare-Associated Infections Requiring 
Hospitalization for the Skilled Nursing Facility Quality Reporting 
Program Technical Report available on the SNF QRP Measures and 
Technical Information page at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Measures-and-Technical-Information. This proposed 
measure is not currently NQF endorsed, but CMS plans to submit the 
measure for NQF endorsement in the future.
d. Competing and Related Measures
    Section 1899B(e)(2)(A) of the Act requires that, absent an 
exception under section 1899B(e)(2)(B) of the Act, measures specified 
under section 1899B of the Act be endorsed by the entity with a 
contract under section 1890(a), currently the National Quality Forum 
(NQF). 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, section 1899B(e)(2)(B) permits the Secretary to 
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.
    The proposed SNF HAI measure is not NQF endorsed, so we considered 
whether there are other available measures that assess HAIs in SNFs. 
After review of the NQF's consensus-endorsed measures, we were unable 
to identify any NQF endorsed measures for SNFs focused on capturing 
several types of severe infections attributable to the SNF setting in 
one composite score. For example, although the measures Percent of 
Residents with a Urinary Tract Infection (Long-Stay) (NQF #0684), 
National Healthcare Safety Network (NHSN) Catheter-Associated Urinary 
Tract Infections (NQF #0138), NHSN Central Line-Associated Bloodstream 
Infections (NQF #0139), and NHSN Facility-Wide Inpatient Hospital-onset 
Clostridium Difficile Infection (NQF #1717) are NQF endorsed and all 
report on specific types of infections, they do not provide an overall 
HAI rate and are not specific to the SNF setting. Additionally, 
although the Skilled Nursing Facility 30-Day All-Cause Readmission 
measure (NQF #2510), the Potentially Preventable 30-Day Post-Discharge 
Readmission measure for SNF QRP, and the Skilled Nursing Facility 30-
Day Potentially Preventable Readmission after Hospital Discharge 
measure (SNFPPR) are all specific to the SNF setting, they are not 
solely focused on infections. We intend to submit this proposed measure 
to the NQF for consideration of endorsement when feasible.
    Therefore, after consideration of other available measures, we find 
that the exception under section 1899B(e)(2)(B) of the Act applies and 
are proposing the measure, Skilled Nursing Facility (SNF) Healthcare-
Associated Infections (HAI) Requiring Hospitalization measure beginning 
with the FY 2023 SNF QRP.
e. Quality Measure Calculation
    The proposed measure estimates the risk-standardized rate of HAIs 
that are acquired during SNF care and result in hospitalization using 1 
year of Medicare FFS claims data.
    Both the proposed measure numerator and denominator are risk-
adjusted. The measure's adjusted numerator is the estimated number of 
SNF stays predicted to have an HAI that results in hospitalization. The 
estimate starts with the observed count of the measure outcome, which 
is then risk-adjusted for resident characteristics and a statistical 
estimate of the SNF effect beyond resident case mix. The term ``SNF 
effect'' represents provider-specific behaviors that result in 
facilities' HAI rates. These behaviors may include adherence to 
evidence-based infection control policies and procedures. The adjusted 
denominator is the expected number of SNF stays with the measure 
outcome. The adjusted denominator is calculated by risk-adjusting the 
total eligible SNF stays for resident characteristics excluding the SNF 
effect.
    The proposed measure is calculated using a standardized risk ratio 
(SRR) in which the predicted number of HAIs for SNF stays per provider 
is divided by the expected number of HAIs. For each SNF, a risk-
adjusted rate of HAIs that are acquired during SNF care and result in 
hospitalization is calculated by multiplying the SRR by the overall 
national observed rate of HAIs for all SNF stays. The measure is risk-
adjusted for age and gender characteristics, original reason for 
Medicare Entitlement, principal diagnosis during the prior proximal 
inpatient (IP) stay, types of surgery or procedure from the prior 
proximal IP stay, length of stay and ICU/CCU utilization from the prior 
proximal IP stay, dialysis treatment from the prior proximal IP stay, 
and HCC comorbidities and number of prior IP stays within 1 year 
preceding the SNF stay. For technical information about this proposed 
measure, including information about the measure calculation, risk 
adjustment, and exclusions, refer to the document titled, Skilled 
Nursing Facility Healthcare-Associated Infections Requiring 
Hospitalization for the Skilled Nursing Facility Quality Reporting 
Program Technical Report available on the SNF QRP Measures and 
Technical Information page at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Measures-and-Technical-Information. If this measure 
is finalized, we intend to publicly report this measure using four 
quarters of claims data. We refer readers to section VI.H.2. of this 
proposed rule for information regarding public reporting.
    We invite public comment on our proposal to adopt the quality 
measure, the Skilled Nursing Facility (SNF) Healthcare-Associated 
Infections (HAIs) Requiring Hospitalization, beginning with the FY 2023 
SNF QRP.
2. Proposed COVID-19 Vaccination Coverage Among Healthcare Personnel 
(HCP) Measure Beginning With the FY 2023 SNF QRP
a. Background
    On January 31, 2020, the Secretary of the U.S. Department of Health 
and Human Services (HHS) declared a public health emergency (PHE) for 
the United States in response to the global outbreak of SARS-CoV-2, a 
novel (new) coronavirus that causes a disease named ``coronavirus 
disease 2019'' (COVID-19).\36\ COVID-19 is a contagious

[[Page 19995]]

respiratory infection \37\ that can cause serious illness and death. 
Older individuals, racial and ethnic minorities, and those with 
underlying medical conditions are considered to be at higher risk for 
more serious complications from COVID-19.38 39 As of April 
4, 2021 the U.S. reported over 30 million cases of COVID-19 and over 
553,000 COVID-19 deaths.\40\ Hospitals and health systems saw 
significant surges of COVID-19 patients as community infection levels 
increased.\41\ In December 2020 and January 2021, media outlets 
reported that more than 100,000 Americans were in the hospital with 
COVID-19.\42\
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    \36\ U.S. Dept. of Health and Human Services, Office of the 
Assistant Secretary for Preparedness and Response. (2020). 
Determination that a Public Health Emergency Exists. Available at 
https://www.phe.gov/emergency/news/healthactions/phe/Pages/2019-nCoV.aspx.
    \37\ Centers for Disease Control and Prevention. (2020). Your 
Health: Symptoms of Coronavirus. Available at https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html.
    \38\ Centers for Disease Control and Prevention (2021). Health 
Equity Considerations and Racial and Ethnic Minority Groups. 
Available at https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/race-ethnicity.html.
    \39\ Centers for Disease Control and Prevention. (2020). Your 
Health: Symptoms of Coronavirus. Available at https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html.
    \40\ Centers for Disease Control and Prevention. (2020). CDC 
COVID Data Tracker. Available at https://covid.cdc.gov/covid-data-tracker/#cases_casesper100klast7days.
    \41\ Associated Press. Tired to the Bone. Hospitals Overwhelmed 
with Virus Cases. November 18, 2020. Accessed on December 16, 2020, 
at https://apnews.com/article/hospitals-overwhelmed-coronavirus-cases-74a1f0dc3634917a5dc13408455cd895. Also see: New York Times. 
Just how full are U.S. intensive care units? New data paints an 
alarming picture. November 18, 2020. Accessed on December 16, 2020, 
at https://www.nytimes.com/2020/12/09/world/just-how-full-are-us-intensive-care-units-new-data-paints-an-alarming-picture.html.
    \42\ NPR. U.S. Hits 100,000 COVID-19 Hospitalizations, Breaks 
Daily Death Record. Dec. 2, 2020. Accessed on December 17, 2020 at 
https://www.npr.org/sections/coronavirus-live-updates/2020/12/02/941902471/u-s-hits-100-000-covid-19-hospitalizations-breaks-daily-death-record; The Wall Street Journal. Coronavirus Live Updates: 
U.S. Hospitalizations, Newly Reported Cases, Deaths Edge Downward. 
Accessed on January 11 at https://www.wsj.com/livecoverage/covid-2021-01-11.
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    Evidence indicates that COVID-19 primarily spreads when individuals 
are in close contact with one another.\43\ The virus is typically 
transmitted through respiratory droplets or small particles created 
when someone who is infected with the virus coughs, sneezes, sings, 
talks or breathes.\44\ Experts believe that COVID-19 spreads less 
commonly through contact with a contaminated surface \45\ (although 
that is not thought to be a common way that COVID-19 spreads), and that 
in certain circumstances, infection can occur through airborne 
transmission.\46\ According to the CDC, those at greatest risk of 
infection are persons who have had prolonged, unprotected close contact 
(that is, within 6 feet for 15 minutes or longer) with an individual 
with confirmed SARS-CoV-2 infection, regardless of whether the 
individual has symptoms.\47\ Although personal protective equipment 
(PPE) and other infection-control precautions can reduce the likelihood 
of transmission in health care settings, COVID-19 can spread between 
healthcare personnel (HCP) and patients given the close contact that 
may occur during the provision of care.\48\ The CDC has emphasized that 
health care settings, including long-term care settings, can be high-
risk places for COVID-19 exposure and transmission.\49\
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    \43\ Centers for Disease Control and Prevention. (2021). COVID-
19. Your Health. Frequently Asked Questions. Accessed on January 11, 
2021 at https://www.cdc.gov/coronavirus/2019-ncov/faq.html.
    \44\ Centers for Disease Control and Prevention (2021). COVID-
19. Your Health. Frequently Asked Questions. Accessed on January 11, 
2021 at https://www.cdc.gov/coronavirus/2019-ncov/faq.html.
    \45\ Centers for Disease Control and Prevention (2021). COVID-
19. Your Health. Frequently Asked Questions. Accessed on January 11, 
2021 at https://www.cdc.gov/coronavirus/2019-ncov/faq.html.
    \46\ Centers for Disease Control and Prevention. (2020). Centers 
for Disease Control Scientific Brief: SARS-CoV-2 and Potential 
Airborne Transmission. Available at https://www.cdc.gov/coronavirus/2019-ncov/more/scientific-brief-sars-cov-2.html.
    \47\ Centers for Disease Control and Prevention. (2020). 
Clinical Questions about COVID-19: Questions and Answers. Accessed 
on December 2, 2020 at https://www.cdc.gov/coronavirus/2019-ncov/hcp/faq.html.
    \48\ Centers for Disease Control and Prevention. (2020). Interim 
U.S. Guidance for Risk Assessment and Work Restrictions for 
Healthcare Personnel with Potential Exposure to COVID-19. Accessed 
on December 2 at https://www.cdc.gov/coronavirus/2019-ncov/hcp/guidance-risk-assesment-hcp.html.
    \49\ Dooling, K, McClung, M, et al. ``The Advisory Committee on 
Immunization Practices' Interim Recommendations for Allocating 
Initial Supplies of COVID-19 Vaccine--United States, 2020.'' Morb 
Mortal Wkly Rep. 2020; 69(49): 1857-1859.
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    Vaccination is a critical part of the nation's strategy to 
effectively counter the spread of COVID-19 and ultimately help restore 
societal functioning.\50\
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    \50\ Centers for Disease Control and Prevention. (2020). COVID-
19 Vaccination Program Interim Playbook for Jurisdiction Operations. 
Accessed on December 18 at https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
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    On December 11, 2020, the Food and Drug Administration (FDA) issued 
the first Emergency Use Authorization (EUA) for a COVID-19 vaccine in 
the U.S.\51\ Subsequently, the FDA issued EUAs for additional COVID-19 
vaccines. In issuing these EUAs, the FDA determined that it was 
reasonable to conclude that the known and potential benefits of each 
vaccine, when used as authorized to prevent COVID-19, outweighed its 
known and potential risks.52 53 54
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    \51\ U.S. Food and Drug Administration. (2020). Pfizer-BioNTech 
COVID-19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/144412/download.
    \52\ Ibid.
    \53\ U.S. Food and Drug Administration. (2021). ModernaTX, Inc. 
COVID-19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/144636/download.
    \54\ U.S. Food and Drug Administration (2020). Janssen Biotech, 
Inc. COVID-19 Vaccine EUA Letter of Authorization. Available at 
https://www.fda.gov/media/146303/download.
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    As part of its national strategy to address COVID-19, the current 
administration stated that it would work with states and the private 
sector to execute an aggressive vaccination strategy and has outlined a 
goal of administering 200 million shots in 100 days.\55\ Although the 
goal of the U.S. government is to ensure that every American who wants 
to receive a COVID-19 vaccine can receive one, Federal agencies 
recommended that early vaccination efforts focus on those critical to 
the PHE response, including healthcare personnel (HCP), and individuals 
at highest risk for developing severe illness from COVID-19.\56\ For 
example, the CDC's Advisory Committee on Immunization Practices (ACIP) 
recommended that HCP should be among those individuals prioritized to 
receive the initial, limited supply of the COVID-19 vaccination, given 
the potential for transmission in health care settings and the need to 
preserve health care system capacity.\57\ Research suggests most states 
followed this recommendation,\58\ and HCP began

[[Page 19996]]

receiving the vaccine in mid-December of 2020.\59\
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    \55\ The White House. Remarks by President Biden on the COVID-19 
Response and the State of Vaccinations. March 29, 2021. Accessed at 
https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/03/29/remarks-by-president-biden-on-the-covid-19-response-and-the-state-of-vaccinations/.
    \56\ Health and Human Services, Department of Defense. (2020) 
From the Factory to the Frontlines: The Operation Warp Speed 
Strategy for Distributing a COVID-19 Vaccine. Accessed December 18 
at https://www.hhs.gov/sites/default/files/strategy-for-distributing-covid-19-vaccine.pdf; Centers for Disease Control 
(2020). COVID-19 Vaccination Program Interim Playbook for 
Jurisdiction Operations. Accessed December 18 at https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
    \57\ Dooling, K, McClung, M, et al. ``The Advisory Committee on 
Immunization Practices' Interim Recommendations for Allocating 
Initial Supplies of COVID-19 Vaccine--United States, 2020.'' Morb. 
Mortal Wkly Rep. 2020; 69(49): 1857-1859. ACIP also recommended that 
long-term care residents be prioritized to receive the vaccine, 
given their age, high levels of underlying medical conditions, and 
congregate living situations make them high risk for severe illness 
from COVID-19.
    \58\ Kates, J, Michaud, J, Tolbert, J. ``How Are States 
Prioritizing Who Will Get the COVID-19 Vaccine First?'' Kaiser 
Family Foundation. December 14, 2020. Accessed on December 16 at 
https://www.kff.org/policy-watch/how-are-states-prioritizing-who-will-get-the-covid-19-vaccine-first/.
    \59\ Associated Press. `Healing is Coming:' US Health Workers 
Start Getting Vaccine. December 15, 2020. Accessed on December 16 at 
https://apnews.com/article/us-health-workers-coronavirus-vaccine-56df745388a9fc12ae93c6f9a0d0e81f.
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    HCP are at risk of carrying COVID-19 infection to patients, 
experiencing illness or death as a result of COVID-19 themselves, and 
transmitting it to their families, friends, and the general public. We 
believe it is important to require that SNFs report HCP vaccination in 
order to assess whether they are taking steps to limit the spread of 
COVID-19 among their HCP, reduce the risk of transmission of COVID-19 
within their facilities, and to help sustain the ability of SNFs to 
continue serving their communities throughout the PHE and beyond. 
Currently, as required under the May 8, 2020 Interim final rule with 
comment period (85 FR 27601-27602), SNFs are required to submit COVID-
19 data through the CDC's NHSN Long-term Care Facility COVID-19 Module 
of the NHSN. Examples of data reported in the module include: suspected 
and confirmed COVID-19 infections among residents and staff, including 
residents previously treated for COVID-19; total deaths and COVID-19 
deaths among residents and staff; personal protective equipment and 
hand hygiene supplies in the facility; ventilator capacity and supplies 
available in the facility; resident beds and census; access to COVID-19 
testing while the resident is in the facility; and staffing shortages. 
Although HCP and resident COVID-19 vaccination data reporting modules 
are currently available through the NHSN, the reporting of this data is 
voluntary. \60\
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    \60\ Centers for Disease Control and Prevention. Weekly COVID-19 
Vaccination Data Reporting. Accessed at https://www.cdc.gov/nhsn/ltc/weekly-covid-vac/index.html.
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    We also believe that publishing facility-level COVID-19 HCP 
vaccination rates on Care Compare would be helpful to many patients, 
including those who are at high-risk for developing serious 
complications from COVID-19, as they choose facilities from which to 
seek treatment. Under CMS' Meaningful Measures Framework, the COVID-19 
Vaccination Coverage among Healthcare Personnel measure addresses the 
quality priority of ``Promote Effective Prevention & Treatment of 
Chronic Disease'' through the Meaningful Measures Area of ``Preventive 
Care.''
    Therefore, we are proposing a new measure, COVID-19 Vaccination 
Coverage among HCP to assess the proportion of a SNF's healthcare 
workforce that has been vaccinated against COVID-19.
b. Stakeholder Input
    In the development and specification of the measure, a transparent 
process was employed to seek input from stakeholders and national 
experts and engage in a process that allows for pre-rulemaking input on 
each measure, under section 1890A of the Act.\61\ To meet this 
requirement, the following opportunity was provided for stakeholder 
input.
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    \61\ Centers for Medicare & Medicaid Services. Pre-rulemaking. 
Accessed at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityMeasures/Pre-Rulemaking.
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    The pre-rulemaking process includes making publicly available a 
list of quality and efficiency measures, called the Measures Under 
Consideration (MUC) List that the Secretary is considering adopting, 
through Federal rulemaking process, for use in Medicare program(s). 
This allows multi-stakeholder groups to provide recommendations to the 
Secretary on the measures included on the list. The COVID-19 
Vaccination Coverage among Healthcare Personnel measure was included on 
the publicly available ``List of Measures under Consideration for 
December 21, 2020'' (MUC List).\62\ Five comments were received from 
industry stakeholders during the pre-rulemaking process on the COVID-19 
Vaccination Coverage among HCP measure, and support was mixed. 
Commenters generally supported the concept of the measure. However, 
there was concern about the availability of the vaccine and measure 
definition for HCP, and some commenters encouraged CMS to continue to 
update the measure as new evidence comes in.
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    \62\ National Quality Forum. List of Measures Under 
Consideration for December 21, 2020. Accessed at https://www.cms.gov/files/document/measures-under-consideration-list-2020-report.pdf on January 12, 2021.
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c. Measure Applications Partnership (MAP) Review
    When the Measure Applications Partnership (MAP) PAC-LTC Workgroup 
convened on January 11, 2021, it reviewed the MUC List and the COVID-19 
Vaccination Coverage among HCP measure. The MAP recognized that the 
proposed measure represents a promising effort to advance measurement 
for an evolving national pandemic and that it would bring value to the 
SNF QRP measure set by providing transparency about an important COVID-
19 intervention to help limit COVID-19 infections.\63\ The MAP also 
stated that collecting information on COVID-19 vaccination coverage 
among healthcare personnel and providing feedback to facilities would 
allow facilities to benchmark coverage rates and improve coverage in 
their facility, and that reducing rates of COVID-19 in healthcare 
personnel may reduce transmission among patients and reduce instances 
of staff shortages due to illness.\64\
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    \63\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on February 3, 2021 at https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94650.
    \64\ Ibid.
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    In its preliminary recommendations, the MAP PAC-LTC Workgroup did 
not support this measure for rulemaking, subject to potential for 
mitigation.\65\ To mitigate its concerns, the MAP believed that the 
measure needed well-documented evidence, finalized specifications, 
testing, and NQF endorsement prior to implementation.\66\ Subsequently, 
the MAP Coordinating Committee met on January 25, 2021, and reviewed 
the COVID-19 Vaccination Coverage among Healthcare Personnel measure. 
In the 2020-2021 MAP Final Recommendations, the MAP offered conditional 
support for rulemaking contingent on CMS bringing the measure back to 
the MAP once the specifications are further clarified. The final MAP 
report is available at http://www.qualityforum.org/Publications/2021/03/MAP_2020-2021_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
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    \65\ Ibid.
    \66\ Ibid.
---------------------------------------------------------------------------

    In response to the MAP request for CMS to bring the measure back 
once the specifications were further clarified, CMS met with the MAP 
Coordinating Committee on March 15, 2021. First, CMS and CDC clarified 
the alignment of the COVID-19 Vaccination Coverage among HCP with the 
Influenza Vaccination Coverage among HCP (NQF #0431), an NQF-endorsed 
measure since 2012. The COVID-19 Vaccination Coverage among HCP measure 
is calculated using the same approach as the Influenza Vaccination 
Coverage among HCP measure.\67\ The approach to identifying HCPs 
eligible for the COVID-19 vaccination is analogous to those used in the 
NQF endorsed flu measure which underwent rigorous review from technical 
experts about the validity of that approach and for which

[[Page 19997]]

ultimately received NQF endorsement. More recently, prospective cohorts 
of health care personnel, first responders, and other essential and 
frontline workers over 13 weeks in eight U.S. locations confirmed that 
authorized COVID-19 vaccines are highly effective in real-world 
conditions. Vaccine effectiveness of full immunization with two doses 
of vaccines was 90 percent.\68\
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    \67\ The Influenza Vaccination Coverage among Healthcare 
Personnel (NQF #0431) measure which is NQF endorsed and was adopted 
in the IRF QRP in the FY 2014 IRF PPS Final Rule (78 FR 47905 
through 47906), and in the LTCH QRP in the FY 2013 IPPS/LTCH PPS 
Final Rule (77 FR 53630 through 53631).
    \68\ Centers for Disease Control and Preventions. Morbidity and 
Mortality Weekly Report. March 29, 2021. Available at https://www.cdc.gov/mmwr/volumes/70/wr/mm7013e3.htm?s_cid=mm7013e3_w.
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    Additionally, to support the measure's data element validity, CDC 
conducted testing of the COVID-19 vaccination numerator using data 
collected through the NHSN and independently reported through the 
Federal Pharmacy Partnership for Long-term Care Program for delivering 
vaccines to long-term care facilities. These are two completely 
independent data collection systems. In initial analyses of the first 
month of vaccination, the number of HCP vaccinated in approximately 
1,200 facilities which had data from both systems, the number of HCP 
vaccinated was highly correlated between these two systems with a 
correlation coefficient of nearly 90 percent in the second two weeks of 
reporting. Of note, assessment of data element reliability may not be 
required by NQF if data element validity is demonstrated.\69\ To assess 
the validity of new performance measure score (in this case, percentage 
of COVID-19 vaccination coverage), NQF allows assessment by face 
validity (that is, subjective determination by experts that the measure 
appears to reflect quality of care, done through a systematic and 
transparent process),\70\ and the MAP concurred with the face validity 
of the COVID-19 Vaccination Coverage among HCP measure. Materials from 
the March 15, 2021 MAP Coordinating Committee meeting are on the NQF 
website at https://www.qualityforum.org/ProjectMaterials.aspx?projectID=75367.
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    \69\ National Quality Form. Key Points for Evaluating Scientific 
Acceptability. Revised January 3, 2020. https://
www.qualityforum.org/Measuring_Performance/Scientific_Methods_Panel/
Docs/
Evaluation_Guidance.aspx#:~:text=NQF%20is%20not%20prescriptive%20abou
t,reliability%20or%20validity%20testing%20results.&text=Reliability%2
0and%20validity%20must%20be,source%20and%20level%20of%20analysis).
    \70\ Ibid.
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    This measure is not NQF endorsed, but the CDC, in collaboration 
with CMS, plans to submit the measure for NQF endorsement in the 
future.
d. Competing and Related Measures
    Section 1899B(e)(2)(A) of the Act requires that absent an exception 
under section 1899B(e)(2)(B) of the Act, each measure specified by the 
Secretary be endorsed by the entity with a contract under section 
1890(a) of the Act, currently the National Quality Forum (NQF). 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, section 1899B(e)(2)(B) of the Act permits the Secretary to 
specify a measure that is not so 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. The proposed COVID-
19 Vaccination Coverage among HCP measure is not currently NQF endorsed 
and has not been submitted to the NQF for consideration, so we 
considered whether there are other available measures that assess 
COVID-19 vaccinations among HCP. After review of the NQF's consensus-
endorsed measures, we were unable to identify any NQF endorsed measures 
for SNFs focused on capturing COVID-19 vaccination coverage of HCP, and 
we found no other feasible and practical measure on the topic of COVID-
19 vaccination coverage among HCP. The only other vaccination coverage 
of HCP measure found was the Influenza Vaccination Coverage among 
Healthcare Personnel (NQF #0431) measure which is NQF endorsed and was 
adopted in the IRF QRP in the FY 2014 IRF PPS Final Rule (78 FR 47905 
through 47906), and in the LTCH QRP in the FY 2013 IPPS/LTCH PPS Final 
Rule (77 FR 53630 through 53631).
    Given the novel nature of the SARS-CoV-2 virus, and the significant 
and immediate risk it poses in SNFs, we believe it is necessary to 
propose the measure as soon as possible. Therefore, after consideration 
of other available measures that assess COVID-19 vaccination rates 
among HCP, we believe the exception under section 1899B(e)(2)(B) of the 
Act applies. This proposed measure has the potential to generate 
actionable data on vaccination rates that can be used to target quality 
improvement among SNF providers.
e. Quality Measure Calculation
    The COVID-19 Vaccination Coverage among Healthcare Personnel (HCP) 
measure is a process measure developed by the CDC to track COVID-19 
vaccination coverage among HCP in facilities such as SNFs. Since this 
proposed measure is a process measure, rather than an outcome measure, 
it does not require risk-adjustment.
    The denominator would be the number of HCP eligible to work in the 
facility for at least one day during the reporting period, excluding 
persons with contraindications to COVID-19 vaccination that are 
described by the CDC.\71\ While the SNF QRP applies to freestanding 
SNFs, SNFs affiliated with acute care facilities, and all non-CAH 
swing-bed rural hospitals, we believe it is necessary to include all 
HCP within the facility in the measure denominator because all HCP 
would have access to and may interact with SNF residents.
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    \71\ Centers for Disease Control and Prevention. Interim 
Clinical Considerations for Use of COVID-19 Vaccines Currently 
Authorized in the United Sates. Contraindications found in Appendix 
B: Triage of people presenting for the vaccination. Accessed at 
https://www.cdc.gov/vaccines/covid-19/info-by-product/clinical-considerations.html.
---------------------------------------------------------------------------

    The numerator would be the cumulative number of HCP eligible to 
work in the facility for at least one day during the reporting period 
and who received a complete vaccination course against SARS-CoV-2. A 
complete vaccination course may require one or more doses depending on 
the specific vaccine used. The finalized measure specifications are on 
the CDC website at https://www.cdc.gov/nhsn/nqf/index.html.
    We propose that SNFs would submit data for the measure through the 
CDC/NHSN data collection and submission framework.\72\ SNFs would use 
the COVID-19 vaccination data reporting module in the NHSN Healthcare 
Personnel Safety (HPS) Component to report the number of HCP eligible 
who have worked at the facility that week (denominator) and the number 
of those HCP who have received a completed COVID-19 vaccination course 
(numerator). SNFs would submit COVID-19 vaccination data for at least 1 
week each month. If SNFs submit more than 1 week of data in a month, 
the most recent week's data would be used for measure calculation 
purposes. Each quarter, the CDC would calculate a summary measure of 
COVID-19 vaccination coverage from the 3 monthly modules of data 
reported for the quarter. This quarterly rate would be publicly 
reported on the Care Compare website. Subsequent to the first refresh, 
one additional quarter of data would be added to the measure 
calculation during each advancing refresh, until the point four full 
quarters of data is reached. Thereafter, the measure would be reported 
using four rolling quarters of data on Care Compare.
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    \72\ Centers for Disease Control and Prevention. Surveillance 
for Weekly HCP COVID-19 Vaccination. Accessed at https://www.cdc.gov/nhsn/hps/weekly-covid-vac/index.html on February 10, 
2021.
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    For purposes of submitting data to CMS for the FY 2023 SNF QRP, 
SNFs

[[Page 19998]]

would be required to submit data for the period October 1, 2021 through 
December 31, 2021. Following the initial data submission quarter for 
the FY 2023 SNF QRP, subsequent compliance for the SNF QRP would be 
based on four quarters of such data submission. For more information on 
the measure's proposed public reporting period, we refer readers to 
section VI.H.3. of this proposed rule.
    We invite public comment on our proposal to add a new measure, 
COVID-19 Vaccination Coverage among Healthcare Personnel, to the SNF 
QRP beginning with the FY 2023 SNF QRP.
3. Proposed Update to the Transfer of Health (TOH) Information to the 
Patient--Post-Acute Care (PAC) Measure Beginning With the FY 2023 SNF 
QRP
    We are proposing to update the Transfer of Health Information to 
the Patient--Post-Acute Care (PAC) measure denominator to exclude 
residents discharged home under the care of an organized home health 
service or hospice. This measure assesses for and reports on the timely 
transfer of health information, specifically transfer of a medication 
list. We adopted this measure in the FY 2020 SNF PPS final rule (84 FR 
38761 through 38764) beginning with the FY 2022 SNF QRP. It is a 
process-based measure that evaluates for the transfer of information 
when a resident is discharged from his or her current PAC setting to a 
private home/apartment, board and care home, assisted living, group 
home, transitional living, or home under the care of an organized home 
health service organization or hospice.
    This measure, adopted under section 1899B(c)(1)(E) of the Act, was 
developed to be a standardized measure for the IRF QRP, LTCH QRP, SNF 
QRP, and Home Health (HH) QRP. The measure is calculated by one 
standardized data element that asks, ``At the time of discharge, did 
the facility provide the resident's current reconciled medication list 
to the resident, family, and/or caregiver?'' The discharge location is 
captured by items on the Minimum Data Set (MDS).
    Specifically, we are proposing to update the measure denominator. 
Currently, the measure denominators for both the TOH-Patient and the 
TOH-Provider measure assess the number of residents discharged home 
under the care of an organized home health service organization or 
hospice. In order to align the measure with the IRF QRP, LTCH QRP and 
HH QRP and avoid counting the resident in both TOH measures in the SNF 
QRP, we are proposing to remove this location from the definition of 
the denominator for the TOH-Patient measure. Therefore, we are 
proposing to update the denominator for the TOH-Patient measure to only 
discharges to a private home/apartment, board and care home, assisted 
living, group home, or transitional living. For additional technical 
information regarding the TOH-Patient measure, we refer readers to the 
document titled ``Final Specifications for SNF QRP Quality Measures and 
Standardized Patient Assessment Data Elements (SPADEs)'' available at 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Downloads/Final-Specifications-for-SNF-QRP-Quality-Measures-and-SPADEs.pdf.
    We invite public comment on our proposal to update the denominator 
of the Transfer of Health (TOH) Information to the Patient--Post-Acute 
Care (PAC) measure beginning with the FY 2023 SNF QRP.

D. SNF QRP Quality Measures Under Consideration for Future Years: 
Request for Information (RFI)

    We are seeking input on the importance, relevance, appropriateness, 
and applicability of each of the measures and concepts under 
consideration listed in Table 27 for future years in the SNF QRP.

 Table 27--Future Measures and Measure Concepts Under Consideration for
                               the SNF QRP
------------------------------------------------------------------------
         Assessment-based quality measures and measure concepts
-------------------------------------------------------------------------
Frailty.
Patient reported outcomes.
Shared decision making process.
Appropriate pain assessment and pain management processes.
Health equity.
------------------------------------------------------------------------

    While we will not be responding to specific comments submitted in 
response to this Request for Information (RFI) in the FY 2022 SNF PPS 
final rule, we intend to use this input to inform our future measure 
development efforts.

E. Fast Healthcare Interoperability Resources (FHIR) in Support of 
Digital Quality Measurement in Quality Programs--Request for 
Information (RFI)

1. Background
    The SNF QRP is authorized by section 1888(e)(6) of the Act and 
furthers our mission to improve the quality of health care for 
beneficiaries through measurement, transparency, and public reporting 
of data. The SNF QRP and CMS's other quality programs are foundational 
for contributing to improvements in health care, enhancing patient 
outcomes, and informing consumer choice. In October 2017, we launched 
the Meaningful Measures Framework. This framework captures our vision 
to address health care quality priorities and gaps, including 
emphasizing digital quality measurement (dQM), reducing measurement 
burden, and promoting patient perspectives, while also focusing on 
modernization and innovation. The scope of the Meaningful Measures 
Framework has evolved to accommodate the changes in the health care 
environment, initially focusing on measure and burden reduction to 
include the promotion of innovation and modernization of all aspects of 
quality.\73\ There is a need to streamline our approach to data 
collection, calculation, and reporting to fully leverage clinical and 
patient-centered information for measurement, improvement, and 
learning.
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    \73\ Meaningful Measures 2.0: Moving from Measure Reduction to 
Modernization. Available at https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
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    In alignment with Meaningful Measures 2.0, we are seeking feedback 
on our future plans to define digital quality measures (dQMs) for the 
SNF QRP. We also are seeking feedback on the potential use of Fast 
Healthcare Interoperable Resources (FHIR) for dQMs within the SNF QRP 
aligning where possible with other quality programs. FHIR is a free and 
open source standards framework (in both commercial and government 
settings) created by Health Level Seven International (HL7[supreg]) 
that establishes a common language and process for all health 
information technology.
2. Definition of Digital Quality Measures
    We are considering adopting a standardized definition of Digital 
Quality Measures (dQMs) in alignment across quality programs, including 
the SNF QRP. We are considering in the future to propose the adoption 
within the SNF QRP the following definition: Digital Quality Measures 
(dQMs) are quality measures that use one or more sources of health 
information that are captured and can be transmitted electronically via 
interoperable systems.\74\ A dQM includes a calculation that processes 
digital data to produce a measure score or measure scores. Data sources 
for dQMs may

[[Page 19999]]

include administrative systems, electronically submitted clinical 
assessment data, case management systems, EHRs, instruments (for 
example, medical devices and wearable devices), patient portals or 
applications (for example, for collection of patient-generated health 
data), health information exchanges (HIEs) or registries, and other 
sources. As an example, the quality measures calculated from patient 
assessment data submitted electronically to CMS would be considered 
digital quality measures.
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    \74\ Definition taken from the CMS Quality Conference 2021.
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3. Use of FHIR for Future dQMs in the SNF QRP
    One of the first areas CMS has identified relative to improving our 
digital strategy is through the use of Fast Healthcare Interoperability 
Resources (FHIR)-based standards to exchange clinical information 
through application programming interfaces (APIs), aligning with other 
programs where possible, to allow clinicians to digitally submit 
quality information one time that can then be used in many ways. We 
believe that in the future proposing such a standard within the SNF QRP 
could potentially enable collaboration and information sharing, which 
is essential for delivering high-quality care and better outcomes at a 
lower cost.
    We are currently evaluating the use of FHIR based APIs to access 
assessment data collected and maintained through the Quality 
Improvement and Evaluation System (QIES) and internet QIES (iQIES) 
health information systems and are working with healthcare standards 
organizations to assure that their evolving standards fully support our 
assessment instrument content. Further, as more SNFs are adopting EHRs, 
we are evaluating using the FHIR interfaces for accessing patient data 
(including standard assessments) directly from SNF EHRs. Accessing data 
in this manner could also enable the exchange of data for purposes 
beyond data reporting to CMS, such as care coordination further 
increasing the value of EHR investments across the healthcare 
continuum. Once providers map their EHR data to a FHIR API in standard 
FHIR formats it could be possible to send and receive the data needed 
for measures and other uses from their EHRs through FHIR APIs.
4. Future Alignment of Measures Across Reporting Programs, Federal and 
State Agencies, and the Private Sector
    We are committed to using policy levers and working with 
stakeholders to achieve interoperable data exchange and to transition 
to full digital quality measurement in our quality programs. We are 
considering the future potential development and staged implementation 
of a cohesive portfolio of dQMs across our quality programs (including 
the SNF QRP), agencies, and private payers. This cohesive portfolio 
would require, where possible, alignment of: (1) Measure concepts and 
specifications including narrative statements, measure logic, and value 
sets; and (2) the individual data elements used to build these measure 
specifications and calculate the measures. Further, the required data 
elements would be limited to standardized, interoperable elements to 
the fullest extent possible; hence, part of the alignment strategy will 
be the consideration and advancement of data standards and 
implementation guides for key data elements. We would coordinate 
closely with quality measure developers, Federal and state agencies, 
and private payers to develop and to maintain a cohesive dQM portfolio 
that meets our programmatic requirements and that fully aligns across 
Federal and state agencies and payers to the extent possible.
    We intend this coordination to be ongoing and allow for continuous 
refinement to ensure quality measures remain aligned with evolving 
healthcare practices and priorities (for example, patient reported 
outcomes (PROs), disparities, care coordination), and track with the 
transformation of data collection. This includes conformance with 
standards and health IT module updates, future adoption of technologies 
incorporated within the ONC Health IT Certification Program and may 
also include standards adopted by ONC (for example, to enable 
standards-based APIs). The coordination would build on the principles 
outlined in HHS' Nation Health Quality Roadmap.\75\ It would focus on 
the quality domains of safety, timeliness, efficiency, effectiveness, 
equitability, and patient-centeredness. It would leverage several 
existing Federal and public-private efforts including our Meaningful 
Measures 2.0 Framework; the Federal Electronic Health Record 
Modernization (DoD/VA); the Core Quality Measure Collaborative, which 
convenes stakeholders from America's Health Insurance Plans (AHIP), 
CMS, NQF, provider organizations, private payers, and consumers and 
develops consensus on quality measures for provider specialties; and 
the NQF-convened Measure Applications Partnership (MAP), which 
recommends measures for use in public payment and reporting programs. 
We would coordinate with HL7's ongoing work to advance FHIR resources 
in critical areas to support patient care and measurement such as 
social determinants of health. Through this coordination, we would 
identify which existing measures could be used or evolved to be used as 
dQMs, in recognition of current healthcare practice and priorities.
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    \75\ Department of Health and Human Services. National Health 
Quality Roadmap. May 15, 2020. Available at https://www.hhs.gov/sites/default/files/national-health-quality-roadmap.pdf.
---------------------------------------------------------------------------

    This multi-stakeholder, joint Federal, state, and industry effort, 
made possible and enabled by the pending advances towards true 
interoperability, would yield a significantly improved quality 
measurement enterprise. The success of the dQM portfolio would be 
enhanced by the degree to which the measures achieve our programmatic 
requirements as well as the requirements of other agencies and payers.
5. Solicitation of Comments
    We seek input on the following steps that would enable 
transformation of CMS' quality measurement enterprise to be fully 
digital:
     What EHR/IT systems do you use and do you participate in a 
health information exchange (HIE)?
     How do you currently share information with other 
providers?
     In what ways could we incentivize or reward innovative 
uses of health information technology (IT) that could reduce burden for 
post-acute care settings, including but not limited to SNFs?
     What additional resources or tools would post-acute care 
settings, including but not limited to SNFs, and health IT vendors find 
helpful to support the testing, implementation, collection, and 
reporting of all measures using FHIR standards via secure APIs to 
reinforce the sharing of patient health information between care 
settings?
     Would vendors, including those that service post-acute 
care settings, such as SNFs, be interested in or willing to participate 
in pilots or models of alternative approaches to quality measurement 
that would align standards for quality measure data collection across 
care settings to improve care coordination, such as sharing patient 
data via secure FHIR API as the basis for calculating and reporting 
digital measures?
    We plan to continue working with other agencies and stakeholders to 
coordinate and to inform our transformation to dQMs leveraging health 
IT standards. While we will not be responding to specific comments 
submitted in response to this RFI in the FY 2022 SNF PPS final rule, we 
will

[[Page 20000]]

actively consider all input as we develop future regulatory proposals 
or future subregulatory policy guidance. Any updates to specific 
program requirements related to quality measurement and reporting 
provisions would be addressed through separate and future notice-and-
comment rulemaking, as necessary.

F. Closing the Health Equity Gap in Post-Acute Care Quality Reporting 
Programs--Request for Information (RFI)

1. Background
    Significant and persistent inequities in health outcomes exist in 
the United States. In recognition of persistent health disparities and 
the importance of closing the health equity gap, we request information 
on revising several CMS programs to make reporting of health 
disparities based on social risk factors and race and ethnicity more 
comprehensive and actionable for providers and patients. Belonging to a 
racial or ethnic minority group; living with a disability; being a 
member of the lesbian, gay, bisexual, transgender, and queer (LGBTQ+) 
community; or being near or below the poverty level is often associated 
with worse health outcomes.76 77 78 79 80 81 82 83 Such 
disparities in health outcomes are the result of a number of factors, 
but importantly for CMS programs, although not the sole determinant, 
poor access and provision of lower quality health care contribute to 
health disparities. For instance, numerous studies have shown that 
among Medicare beneficiaries, racial and ethnic minority individuals 
often receive lower quality of care, report lower experiences of care, 
and experience more frequent hospital readmissions and operative 
complications.84 85 86 87 88 89
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    \76\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for 
Medicare Beneficiaries by Race and Site of Care. JAMA. 2011; 
305(7):675-681.
    \77\ Lindenauer PK, Lagu T, Rothberg MB, et al. Income 
Inequality and 30 Day Outcomes After Acute Myocardial Infarction, 
Heart Failure, and Pneumonia: Retrospective Cohort Study. British 
Medical Journal. 2013; 346.
    \78\ Trivedi AN, Nsa W, Hausmann LRM, et al. Quality and Equity 
of Care in U.S. Hospitals. New England Journal of Medicine. 2014; 
371(24):2298-2308.
    \79\ Polyakova, M., et al. Racial Disparities In Excess All-
Cause Mortality During The Early COVID-19 Pandemic Varied 
Substantially Across States. Health Affairs. 2021; 40(2): 307-316.
    \80\ Rural Health Research Gateway. Rural Communities: Age, 
Income, and Health Status. Rural Health Research Recap. November 
2018.
    \81\ https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf.
    \82\ www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm.
    \83\ Poteat TC, Reisner SL, Miller M, Wirtz AL. COVID-19 
Vulnerability of Transgender Women With and Without HIV Infection in 
the Eastern and Southern U.S. Preprint. medRxiv. 
2020;2020.07.21.20159327. Published 2020 Jul 24. doi:10.1101/
2020.07.21.20159327.
    \84\ Martino, SC, Elliott, MN, Dembosky, JW, Hambarsoomian, K, 
Burkhart, Q, Klein, DJ, Gildner, J, and Haviland, AM. Racial, 
Ethnic, and Gender Disparities in Health Care in Medicare Advantage. 
Baltimore, MD: CMS Office of Minority Health. 2020.
    \85\ Guide to Reducing Disparities in Readmissions. CMS Office 
of Minority Health. Revised August 2018. Available at https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
    \86\ Singh JA, Lu X, Rosenthal GE, Ibrahim S, Cram P. Racial 
disparities in knee and hip total joint arthroplasty: an 18-year 
analysis of national Medicare data. Ann Rheum Dis. 2014 
Dec;73(12):2107-15.
    \87\ Rivera-Hernandez M, Rahman M, Mor V, Trivedi AN. Racial 
Disparities in Readmission Rates among Patients Discharged to 
Skilled Nursing Facilities. J Am Geriatr Soc. 2019 Aug;67(8):1672-
1679.
    \88\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for 
Medicare Beneficiaries by Race and Site of Care. JAMA. 
2011;305(7):675-681.
    \89\ Tsai TC, Orav EJ, Joynt KE. Disparities in surgical 30-day 
readmission rates for Medicare beneficiaries by race and site of 
care. Ann Surg. Jun 2014;259(6):1086-1090.
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    Readmission rates for common conditions in the Hospital 
Readmissions Reduction Program are higher for black Medicare 
beneficiaries and higher for Hispanic Medicare beneficiaries with 
Congestive Heart Failure and Acute Myocardial 
Infarction.90 91 92 93 94 Studies have also shown that 
African Americans are significantly more likely than white Americans to 
die prematurely from heart disease and stroke.\95\ The COVID-19 
pandemic has further illustrated many of these longstanding health 
inequities with higher rates of infection, hospitalization, and 
mortality among black, Latino, and Indigenous and Native American 
persons relative to white persons.96 97 As noted by the 
Centers for Disease Control ``long-standing systemic health and social 
inequities have put many people from racial and ethnic minority groups 
at increased risk of getting sick and dying from COVID-19''.\98\ One 
important strategy for addressing these important inequities is by 
improving data collection to allow for better measurement and reporting 
on equity across post-acute care programs and policies.
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    \90\ Rodriguez F, Joynt KE, Lopez L, Saldana F, Jha AK. 
Readmission rates for Hispanic Medicare beneficiaries with heart 
failure and acute myocardial infarction. Am Heart J. Aug 
2011;162(2):254-261 e253.
    \91\ Centers for Medicare and Medicaid Services. Medicare 
Hospital Quality Chartbook: Performance Report on Outcome Measures; 
2014.
    \92\ Guide to Reducing Disparities in Readmissions. CMS Office 
of Minority Health. Revised August 2018. Available at https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
    \93\ Prieto-Centurion V, Gussin HA, Rolle AJ, Krishnan JA. 
Chronic obstructive pulmonary disease readmissions at minority-
serving institutions. Ann Am Thorac Soc. Dec 2013;10(6):680-684.
    \94\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for 
Medicare Beneficiaries by Race and Site of Care. JAMA. 
2011;305(7):675-681.
    \95\ HHS. Heart disease and African Americans. (March 29, 2021). 
https://www.minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=19.
    \96\ https://www.cms.gov/files/document/medicare-covid-19-data-snapshot-fact-sheet.pdf.
    \97\ Ochieng N, Cubanski J, Neuman T, Artiga S, and Damico A. 
Racial and Ethnic Health Inequities and Medicare. Kaiser Family 
Foundation. February 2021. Available at https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/.
    \98\ https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/race-ethnicity.html.
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    We are also committed to achieving equity in health care outcomes 
for our beneficiaries by supporting providers in quality improvement 
activities to reduce health inequities, enabling them to make more 
informed decisions, and promoting provider accountability for health 
care disparities.99 100 For the purposes of this rule, we 
are using a definition of equity established in Executive Order 13985, 
as ``the consistent and systematic fair, just, and impartial treatment 
of all individuals, including individuals who belong to underserved 
communities that have been denied such treatment, such as Black, 
Latino, and Indigenous and Native American persons, Asian Americans and 
Pacific Islanders and other persons of color; members of religious 
minorities; lesbian, gay, bisexual, transgender, and queer (LGBTQ+) 
persons; persons with disabilities; persons who live in rural areas; 
and persons otherwise adversely affected by persistent poverty or 
inequality.'' \101\ We note that this definition was recently 
established by the current administration, and provides a useful, 
common definition for equity across different areas of government, 
although numerous other definitions of equity exist.
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    \99\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
    \100\ Report to Congress: Improving Medicare Post-Acute Care 
Transformation (IMPACT) Act of 2014 Strategic Plan for Accessing 
Race and Ethnicity Data. January 5, 2017. Available at https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Research-Reports-2017-Report-to-Congress-IMPACT-ACT-of-2014.pdf.
    \101\ https://www.federalregister.gov/documents/2021/01/25/2021-01753/advancing-racial-equity-and-support-for-underserved-communities-through-the-Federal-government.
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    Our ongoing commitment to closing the equity gap in CMS quality 
programs is demonstrated by a portfolio of programs aimed at making 
information

[[Page 20001]]

on the quality of health care providers and services, including 
disparities, more transparent to consumers and providers. The CMS 
Equity Plan for Improving Quality in Medicare outlines a path to equity 
which aims to support Quality Improvement Networks and Quality 
Improvement Organizations (QIN-QIOs); Federal, state, local, and tribal 
organizations; providers; researchers; policymakers; beneficiaries and 
their families; and other stakeholders in activities to achieve health 
equity. The CMS Equity Plan includes three core elements: (1) 
Increasing understanding and awareness of disparities; (2) developing 
and disseminating solutions to achieve health equity; and (3) 
implementing sustainable actions to achieve health equity.\102\ The CMS 
Quality Strategy and Meaningful Measures Framework \103\ include 
elimination of racial and ethnic disparities as a central principle. 
Our ongoing commitment to closing the health equity gap in the SNF QRP 
is demonstrated by the adoption of standardized patient assessment data 
elements (SPADEs) which include several social determinants of health 
(SDOH) that were finalized in the FY 2020 SNF PPS final rule for the 
SNF QRP (84 FR 38805 through 38817).
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    \102\ Centers for Medicare & Medicaid Services Office of 
Minority Health. The CMS Equity Plan for Improving Quality in 
Medicare. https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH_Dwnld-CMS_EquityPlanforMedicare_090615.pdf.
    \103\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
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    We continue to work with Federal and private partners to better 
leverage data on social risk to improve our understanding of how these 
factors can be better measured in order to close the health equity gap. 
Among other things, we have developed an Inventory of Resources for 
Standardized Demographic and Language Data Collection \104\ and 
supported collection of specialized International Classification of 
Disease, 10th Edition, Clinical Modification (ICD-10-CM) codes for 
describing the socioeconomic, cultural, and environmental determinants 
of health. We continue to work to improve our understanding of this 
important issue and to identify policy solutions that achieve the goals 
of attaining health equity for all patients.
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    \104\ Centers for Medicare and Medicaid Services. Building an 
Organizational Response to Health Disparities Inventory of Resources 
for Standardized Demographic and Language Data Collection. 2020. 
https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Data-Collection-Resources.pdf.
---------------------------------------------------------------------------

2. Solicitation of Public Comment
    Under authority of the IMPACT Act and section 1888(e)(6) of the 
Act, we are seeking comment on the possibility of revising measure 
development, and the collection of other SPADEs that address gaps in 
health equity in the SNF QRP. Any potential health equity data 
collection or measure reporting within a CMS program that might result 
from public comments received in response to this solicitation would be 
addressed through a separate notice-and-comment rulemaking in the 
future.
    Specifically, we are inviting public comment on the following:
     Recommendations for quality measures, or measurement 
domains that address health equity, for use in the SNF QRP.
     As finalized in the FY 2020 SNF PPS final rule (84 FR 
38805 through 38817), SNFs must report certain standardized patient 
assessment data elements (SPADEs) on SDOH, including race, ethnicity, 
preferred language, interpreter services, health literacy, 
transportation and social isolation.\105\ CMS is seeking guidance on 
any additional items, including SPADEs that could be used to assess 
health equity in the care of SNF residents, for use in the SNF QRP.
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    \105\ In response to the COVID-19 PHE, CMS released an Interim 
Final Rule (85 FR 27595 through 27597) which delayed the compliance 
date for the collection and reporting of the SDOH for at least two 
full fiscal years after the end of the PHE.
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     Recommendations for how CMS can promote health equity in 
outcomes among SNF residents. For example, we are interested in 
feedback regarding whether including facility-level quality measure 
results stratified by social risk factors and social determinants of 
health (for example, dual eligibility for Medicare and Medicaid, race) 
in confidential feedback reports could allow facilities to identify 
gaps in the quality of care they provide. (For example, methods similar 
or analogous to the CMS Disparity Methods \106\ which provide hospital-
level confidential results stratified by dual eligibility for 
condition-specific readmission measures, which are currently included 
in the Hospital Readmission Reduction Program (see 84 FR 42496 through 
42500)).
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    \106\ https://qualitynet.cms.gov/inpatient/measures/disparity-methods/methodology.
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     Methods that commenters or their organizations use in 
employing data to reduce disparities and improve patient outcomes, 
including the source(s) of data used, as appropriate.
     Given the importance of structured data and health IT 
standards for the capture, use, and exchange of relevant health data 
for improving health equity, the existing challenges providers' 
encounter for effective capture, use, and exchange of health 
information, including data on race, ethnicity, and other social 
determinants of health, to support care delivery and decision making.
    While we will not be responding to specific comments submitted in 
response to this RFI in the FY 2022 SNF PPS final rule, we intend to 
use this input to inform future policy development. We look forward to 
receiving feedback on these topics, and note for readers that responses 
to the RFI should focus on how they could be applied to the quality 
reporting program requirements. Please note that any responses provided 
will not impact payment decisions.

G. Form, Manner, and Timing of Data Submission Under the SNF QRP

1. Background
    We refer readers to the regulatory text at 42 CFR 413.360(b) for 
information regarding the current policies for reporting SNF QRP data.
2. Proposed Schedule for Data Submission of the SNF HAI Measure 
Beginning With the FY 2023 QRP
    The SNF HAI measure, which we propose in section VI.C.1. of this 
proposed rule, is a Medicare FFS claims-based measure. Because claims-
based measures can be calculated based on data that have already been 
submitted to the Medicare program for payment purposes, no additional 
information collection would be required from SNFs. We are proposing to 
use 1 year of FY 2019 claims data (October 1, 2018 through September 
30, 2019) for the FY 2023 SNF QRP. We are proposing to use FY 2019 data 
to calculate this measure because it is the most recent fiscal year of 
data that has not been exempted due to the PHE. Beginning with the FY 
2024 SNF QRP, compliance with APU reporting requirements would use FY 
2021 claims data (October 1, 2020 through September 30, 2021) and 
advance by one FY with each annual refresh. Due to the fact that Q1 and 
Q2 2020 data were excepted by CMS related to the COVID-19 PHE, these 
quarters of data would not be used for purposes of the QRP. For 
information on public reporting of the SNF HAI measure, we refer you to 
Table 31 in section VI.H.4.c. of this proposed rule.
    We invite public comment on this proposal.

[[Page 20002]]

3. Proposed Method of Data Submission for COVID-19 Vaccination Coverage 
Among Healthcare Personnel Measure
    As discussed in section VI.C.2 of this proposed rule, we propose to 
require that SNFs submit data on the COVID-19 Vaccination Coverage 
among Healthcare Personnel Measure through the Centers for Disease 
Control and Prevention (CDC)/National Healthcare Safety Network (NHSN). 
The NHSN is a secure, internet-based surveillance system maintained by 
the CDC that can be utilized by all types of healthcare facilities in 
the United States, including acute care hospitals, long term acute care 
hospitals, psychiatric hospitals, rehabilitation hospitals, outpatient 
dialysis centers, ambulatory surgery centers, and SNFs. The NHSN 
enables healthcare facilities to collect and use vaccination data, and 
information on other adverse events. NHSN collects data via a Web-based 
tool hosted by the CDC (http://www.cdc.gov/). The NHSN is provided free 
of charge. We propose for SNFs to submit the data needed to calculate 
the COVID-19 Vaccination Coverage among Healthcare Personnel measure 
using the NHSN's standard data submission requirements. CDC/NHSN 
requirements include adherence to training requirements, use of CDC 
measure specifications, data element definitions, data submission 
requirements and instructions, data submission timeframes, as well as 
NHSN participation forms and indications to CDC allowing CMS to access 
data for this measure for the SNF quality reporting program purposes. 
Detailed requirements for NHSN participation, measure specifications, 
and data collection can be found at http://www.cdc.gov/nhsn/. We 
propose to require SNFs to use the specifications and data collection 
tools for the proposed COVID-19 Vaccination Coverage among Healthcare 
Personnel measure as required by CDC as of the time that the data are 
submitted.
    We invite public comment on this proposal.
4. Proposed Schedule for Data Submission of the COVID-19 Vaccination 
Coverage Among Healthcare Personnel Measure Beginning With the FY 2023 
SNF QRP
    As discussed in section VI.C.2. of this proposed rule, we are 
proposing to adopt the COVID-19 Vaccination Coverage among HCP quality 
measure beginning with the FY 2023 SNF QRP. Given the time-sensitive 
nature of this measure in light of the PHE, we propose an initial data 
submission period from October 1, 2021 through December 31, 2021. 
Starting in CY 2022, SNFs would be required to submit data for the 
entire calendar year beginning with the FY 2024 SNF QRP.
    SNFs would submit data for the measure through the CDC/NHSN web-
based surveillance system. SNFs would use the COVID-19 vaccination data 
collection module in the NHSN Long-term Care (LTC) Component to report 
the cumulative number of HCP eligible to work in the healthcare 
facility for at least 1 day during the reporting period, excluding 
persons with contraindications to COVID-19 vaccination (denominator) 
and the cumulative number of HCP eligible to work in the SNF for at 
least 1 day during the reporting period and who received a complete 
vaccination course against COVID-19 (numerator). SNFs would submit 
COVID-19 vaccination data through the NHSN for at least 1 week each 
month and the CDC would report to CMS quarterly.
    We invite public comment on this proposal.
5. Consolidated Appropriations Act and the SNF QRP
    On December 27, 2020, Congress enacted the Consolidated 
Appropriations Act, 2021 (CAA) (Pub. L. 116-260). Section 111(a)(3) of 
Division CC of the CAA amends section 1888 of the Act by adding a new 
paragraph (h)(12), which requires the Secretary to apply a process to 
validate the measures submitted under the SNF VBP and the measures and 
data submitted under the SNF QRP as appropriate, which may be similar 
to the process specified under the Hospital Inpatient Quality Reporting 
(IQR) Program for validating inpatient hospital measures. We plan to 
develop a process for validating the SNF QRP measures and data and 
implement this policy as soon as technically feasible. We will provide 
more details and seek public comment in future rulemaking. For more 
information on the SNF VBP please refer to section VII. of this rule.

H. Proposed Policies Regarding Public Display of Measure Data for the 
SNF QRP

1. Background
    Section 1899B(g) of the Act requires the Secretary to establish 
procedures for making the SNF QRP data available to the public, 
including the performance of individual SNFs, after ensuring that SNFs 
have the opportunity to review their data prior to public display. SNF 
QRP measure data are currently displayed on the Nursing homes including 
rehab services website within Care Compare and the Provider Data 
Catalog. Both Care Compare and the Provider Data Catalog replaced 
Nursing Home Compare and Data.Medicare.gov, which were retired in 
December 2020. For a more detailed discussion about our policies 
regarding public display of SNF QRP measure data and procedures for the 
opportunity to review and correct data and information, we refer 
readers to the FY 2017 SNF PPS final rule (81 FR 52045 through 52048).
2. Proposal to Publicly Report the Skilled Nursing Facility Healthcare-
Associated Infections Requiring Hospitalization Measure Beginning With 
the FY 2023 SNF QRP
    We propose public reporting for the SNF HAI measure beginning with 
the April 2022 Care Compare refresh or as soon as technically feasible 
using data collected from discharges in FY 2019 beginning October 1, 
2018 through September 30, 2019. Provider preview reports would be 
distributed in January 2022. A SNF's HAI rates would be displayed based 
on 1 fiscal year of data. Since we cannot publicly report data from Q1 
and Q2 of 2020 due to the PHE, we are proposing to use data collected 
from discharges in FY 2021 (October 1, 2020 through September 30, 2021) 
for public reporting of the SNF HAI measure in the October 2022 Care 
Compare refresh. Thereafter, the SNF HAI measure would be calculated 
using four quarters of FY data for the annual refresh on Care Compare. 
Claims-based measures are only refreshed on Care Compare annually. To 
ensure statistical reliability of the data, we propose assigning SNFs 
with fewer than 25 eligible stays during a performance period to a 
separate category: ``The number of resident stays is too small to 
report.'' Eligible stays meet the measure's denominator inclusion 
criteria, and we refer readers to the Skilled Nursing Facility 
Healthcare-Associated Infections Requiring Hospitalization for the 
Skilled Nursing Facility Quality Reporting Program Technical Report 
available at https://www.cms.gov/files/document/snf-hai-technical-report.pdf/ for more details. If a SNF had fewer than 25 eligible 
stays, the SNF's performance would not be publicly reported for the 
measure for that performance period. We refer readers to CMS's SNF QRP 
Public Reporting web page for more information available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Public-Reporting.

[[Page 20003]]

    We invite public comment on this proposal for the public display of 
the SNF HAI measure on Care Compare.
3. Proposal to Publicly Report the COVID-19 Vaccination Coverage Among 
Healthcare Personnel (HCP) Measure Beginning With the FY 2023 SNF QRP
    We propose to publicly report the COVID-19 Vaccination Coverage 
among Healthcare Personnel measure beginning with the October 2022 Care 
Compare refresh or as soon as technically feasible using data collected 
for Q4 2021 (October 1, 2021 through December 31, 2021). If finalized 
as proposed, a SNF's HCP COVID-19 vaccination coverage rate would be 
displayed based on one quarter of data. Provider preview reports would 
be distributed in July 2022. Thereafter, HCP COVID-19 vaccination 
coverage rates would be displayed based on one quarter of data updated 
quarterly. Subsequent to this, one additional quarter of data would be 
added to the measure calculation during each advancing refresh, until 
the point four full quarters of data is reached. Thereafter, the 
measure would be reported using four rolling quarters of data.
    We invite public comment on this proposal for the public display of 
the COVID-19 Vaccination Coverage among HCP measure on Care Compare.
4. Proposals for Public Reporting of Quality Measures in the SNF QRP 
With Fewer Quarters Due to COVID-19 Public Health Emergency (PHE) 
Exemptions
a. COVID-19 Public Health Emergency Temporary Exemptions
    Under the authority of section 319 of the Public Health Service 
Act, the Secretary of Health and Human Services declared a public 
health emergency (PHE) effective as of January 27, 2020. On March 13, 
2020, subsequent to a presidential declaration of national emergency 
under the Stafford Act, the Secretary invoked section 1135(b) of the 
Act (42 U.S.C. 1320b-5) to waive or modify the requirements of titles 
XVIII, XIX, and XXI of the Act and regulations related to the PHE for 
COVID-19, effective as of March 1, 2020.\107\ On March 27, 2020, we 
sent a guidance memorandum under the subject title, ``Exceptions and 
Extensions for Quality Reporting Requirements for Acute Care Hospitals, 
PPS-Exempt Cancer Hospitals, Inpatient Psychiatric Facilities, Skilled 
Nursing Facilities, Home Health Agencies, Hospices, Inpatient 
Rehabilitation Facilities, Long-Term Care Hospitals, Ambulatory 
Surgical Centers, Renal Dialysis Facilities, and MIPS Eligible 
Clinicians Affected by COVID-19'' to the Medicare Learning Network 
(MLN) Connects Newsletter and Other Program-Specific Listserv 
Recipients,\108\ hereafter referred to as the March 27, 2020 CMS 
Guidance Memo. In that memo we granted an exception to the SNF QRP 
reporting requirements from Q4 2019 (October 1, 2019-December 31, 
2019), Q1 2020 (January 1, 2020-March 31, 2020), and Q2 2020 (April 1, 
2020-June 30, 2020). We also stated that we would not publicly report 
any SNF QRP data that might be greatly impacted by the exceptions from 
Q1 and Q2 of 2020. This exception impacted the schedule for public 
reporting that would have included those two quarters of data.
---------------------------------------------------------------------------

    \107\ https://www.phe.gov/emergency/news/healthactions/section1135/Pages/covid19-13March20.aspx.
    \108\ https://www.cms.gov/files/document/guidance-memo-exceptions-and-extensions-quality-reporting-and-value-based-purchasing-programs.pdf.
---------------------------------------------------------------------------

    SNF quality measures are publicly reported on Care Compare. Care 
Compare uses four quarters of data for MDS assessment-based measures 
and eight quarters for claims-based measures. Table 28 displays the 
original schedule for public reporting of SNF QRP measures.\109\
---------------------------------------------------------------------------

    \109\ More information about the SNF QRP Public Reporting 
schedule can be found on the SNF QRP Public Reporting website at 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Public-Reporting.

    Table 28--SNF Quarters in Care Compare Original Schedule for Refreshes Affected by COVID-19 PEH Exemptions--Assessment and Claims Based Measures
--------------------------------------------------------------------------------------------------------------------------------------------------------
             Quarter refresh                                             SNF quarters in original schedule for care compare
--------------------------------------------------------------------------------------------------------------------------------------------------------
January 2021.............................  MDS: Q2 2019--Q1 2020 (4 quarters). Claims: Q4 2017--Q3 2019 (8 quarters).
April 2021...............................  MDS: Q3 2019--Q2 2020 (4 quarters). Claims: Q4 2017--Q3 2019 (8 quarters).
July 2021................................  MDS: Q4 2019--Q3 2020 (4 quarters). Claims: Q4 2017--Q3 2019 (8 quarters).
October 2021.............................  MDS: Q1 2020--Q4 2020 (4 quarters). Claims: Q4 2018--Q3 2020 (8 quarters).
January 2022.............................  MDS: Q2 2020--Q1 2021 (4 quarters). Claims: Q4 2018--Q3 2020 (8 quarters).
April 2022...............................  MDS: Q3 2020--Q2 2021 (4 quarters). Claims: Q4 2018--Q3 2020 (8 quarters).
July 2022................................  MDS: Q4 2020--Q3 2021 (4 quarters). Claims: Q4 2018--Q3 2020 (8 quarters).
October 2022.............................  MDS: Q1 2021--Q4 2021 (4 quarters). Claims: Q4 2019--Q3 2021 (8 quarters).
January 2023.............................  MDS: Q2 2021--Q1 2022 (4 quarters). Claims: Q4 2019--Q3 2021 (8 quarters).
Apri1 2023...............................  MDS: Q3 2021--Q2 2022 (4 quarters). Claims: Q4 2019--Q3 2021 (8 quarters).
July 2023................................  MDS: Q4 2021--Q3 2022 (4 quarters). Claims: Q4 2019--Q3 2021 (8 quarters).
--------------------------------------------------------------------------------------------------------------------------------------------------------

    During 2020, we conducted testing to inform decisions about 
publicly reporting data for those refreshes which include partially 
and/or fully exempt data (discussed below). The testing helped us 
develop a plan for posting data that are as up-to-date as possible and 
that also meet acceptable standards for public reporting. We believe 
that the plan allows us to provide consumers with helpful information 
on the quality of SNF care, while also making the necessary adjustments 
to accommodate the exemption provided SNFs. The following sections 
provide the results of our testing, and explain how we used the results 
to develop plans for accommodating exempt and partially-exempt data in 
public reporting.
b. Exempted Quarters
    In the March 27, 2020 Medicare Learning Network (MLN) Newsletter on 
Exceptions and Extensions for Quality Reporting Program (QRP) 
Requirements, we stated that we would not report any PAC quality data 
that might be greatly impacted by the exemptions granted for Quarter 1 
and Quarter 2 of 2020. Given the timing of the PHE onset, we determined 
that we would not use SNF MDS assessments or SNF claims from Quarter 1 
and Quarter 2 of 2020 for public reporting, but that we would

[[Page 20004]]

assess the COVID-19 PHE impact on data from Quarter 4 2019. Before 
proceeding with the October 2020 refresh, we conducted testing to 
ensure that, despite the voluntary nature of reporting for that 
quarter, public reporting would still meet our public reporting 
standards. We found the level of reporting, measured in the number of 
eligible stays and providers, and the reported outcomes, to be in line 
with levels and trends observed in FY 2018 and FY 2019. We note that 
Quarter 4 2019 ended before the onset of the COVID-19 pandemic in the 
United States. Thus, we proceeded with including these data in SNF QRP 
measure calculations for the October 2020 refresh.
c. Update on Data Freeze and Proposal for January 2022 Public Reporting 
Methodology for SNF Claims-Based and MDS Assessment-Based Measures
    In addition to the January 2021 refresh, there are several other 
forthcoming refreshes for which the original public reporting schedules 
included exempted quarters of SNF QRP data. The impacted refreshes for 
MDS assessment and claims based measures are outlined in (Table 28). We 
determined that freezing the data displayed on the website with the 
October 2020 refresh values--that is, hold data constant after the 
October 2020 refresh data on the website without subsequent update--
would be the most straightforward, efficient, and equitable approach 
for SNFs. Thus, we decided that, for as many refreshes as necessary, we 
would hold data constant on the website with the October 2020 data, and 
communicate this decision to the public.
    Because October 2020 refresh data will become increasingly out-of-
date and thus less useful for consumers, we analyzed whether it would 
be possible to use fewer quarters of data for one or more refreshes and 
thus reduce the number of refreshes that continue to display October 
2020 data. Using fewer quarters of more up-to-date data requires that 
(1) a sufficient percentage of SNFs would still likely have enough 
assessment data to report quality measures (reportability); and (2) 
fewer quarters would likely produce similar measure scores for 
providers, with similar reliability, and thus not unfairly represent 
the quality of care SNFs provide during the period reported in a given 
refresh (reliability).
    To assess these criteria, we conducted reportability and 
reliability analysis using 3 quarters of data in a refresh, instead of 
the standard 4 quarters of data for reporting assessment-based measures 
and using 6 quarters instead of 8 for claims-based measures. 
Specifically, we used historical data to calculate MDS assessment based 
and SNF claims based quality measures under two scenarios:
    1. Standard Public Reporting (SPR) Base Scenario: We used four 
quarters of CY 2019 data as a proxy alternative for the exempted 
quarters in CY 2020 in order to compare results. For assessment-based 
measures, the quarters used in this scenario are Q1 through Q4 2019. 
For claims-based measures, the quarters used in this scenario are Q1 
2018 through Q4 2019.
    2. COVID-19 Affected Reporting (CAR) Scenario: We calculated SNF 
QRP measures using 3 quarters (Q2 2019 through Q4 2019) of SNF QRP data 
for assessment-based measures, and 6 quarters (Q1 2018 through Q4 2018 
and Q3 2019 through Q4 2019) for claims-based measures. The CAR 
scenario uses the most recently available data to simulate the public 
health emergency reality where quarters 1 and 2 of a calendar year must 
be excluded from calculation. Quarterly trends in MDS assessment-based 
and claims based measures indicate that these measures do not exhibit 
substantial seasonal variation.
    To assess performance in these scenarios, we calculated the 
reportability as the percent of SNFs meeting the case minimum for 
public reporting (the public reporting threshold). To test the 
reliability of restricting the SNFs included in the SPR Base Scenario 
to those included in the CAR Scenario, we performed three tests on the 
set of SNFs included in both scenarios. First, we evaluated measure 
correlation using the Pearson and Spearman correlation coefficients, 
which assess the alignment of SNFs' provider scores. Second, for each 
scenario, we conducted a split-half reliability analysis and estimated 
intraclass correlation (ICC) scores, where higher scores imply better 
internal reliability. Modest differences in ICC scores between both 
scenarios would suggest that using fewer quarters of data does not 
impact the internal reliability of the results. Third, we estimated 
reliability scores where a higher value indicates that measure scores 
are relatively consistent for patients admitted to the same SNF and 
variation in the measure reflects true differences across providers. To 
calculate the reliability results, we restricted the SNFs included in 
the SPR scenario to those included in the CAR scenario.
    Our testing indicated that the expected impact of using fewer 
quarters of data on reportability and reliability of MDS assessment-
based and claims based measures is acceptable.
    We are proposing to use the CAR scenario as the approach for the 
following affected refreshes for MDS assessment-based measures, the 
affected refresh is the January 2022 refresh; for claims-based 
measures, the affected refreshes occur from January 2022 through July 
2023. For the earlier four affected refreshes (January, April, July, 
and October 2021), we decided to hold constant the Care Compare website 
with October 2020 data. We communicated this decision in a Public 
Reporting Tip Sheet, which is located at https://www.cms.gov/files/document/snfqrp-covid19prtipsheet-october2020.pdf.
    Our proposal of the CAR approach for the affected refreshes would 
allow us to begin displaying more recent data in January 2022, rather 
than continue displaying October 2020 data (Q1 2019 through Q4 2019 for 
assessment-based measures, Q4 2017 through Q3 2019 for claims-based 
measures). We believe that resuming public reporting starting in 
January 2022 with fewer quarters of data can assist consumers by 
providing more recent quality data as well as more actionable data for 
SNF providers. Our testing results indicate we can achieve these 
positive impacts with acceptable changes in reportability and 
reliability. Table 29 summarizes the revised schedule (that is, frozen 
data) and the proposed schedule (that is, using fewer quarters in the 
affected refreshes) for assessment-based measures. Tables 30 and 31 
summarize the revised schedule (that is, frozen data) and the proposed 
schedule (that is, using fewer quarters in the affected refreshes) for 
claims-based measures.
    We invite public comment on the proposal to use the CAR scenario to 
publicly report SNF measures for the January 2022-July 2023 refreshes.
BILLING CODE 4120-01-P

[[Page 20005]]

[GRAPHIC] [TIFF OMITTED] TP15AP21.005

BILLING CODE 4120-01-C

[[Page 20006]]

VII. Skilled Nursing Facility Value-Based Purchasing (SNF VBP) Program

A. Background

    Section 215(b) of the Protecting Access to Medicare Act of 2014 
(PAMA) (Pub. L. 113-93) authorized the SNF VBP Program (the 
``Program'') by adding section 1888(h) to the Act. As a prerequisite to 
implementing the SNF VBP Program, in the FY 2016 SNF PPS final rule (80 
FR 46409 through 46426), we adopted an all-cause, all-condition 
hospital readmission measure, as required by section 1888(g)(1) of the 
Act, and discussed other policies to implement the Program such as 
performance standards, the performance period and baseline period, and 
scoring. SNF VBP Program policies have been codified in our regulations 
at Sec.  413.338. For additional background information on the SNF VBP 
Program, including an overview of the SNF VBP Report to Congress and a 
summary of the Program's statutory requirements, we refer readers to 
the following prior final rules:
     In the FY 2017 SNF PPS final rule (81 FR 51986 through 
52009), we adopted an all-condition, risk-adjusted potentially 
preventable hospital readmission measure for SNFs, as required by 
section 1888(g)(2) of the Act, adopted policies on performance 
standards, performance scoring, and sought comment on an exchange 
function methodology to translate SNF performance scores into value-
based incentive payments, among other topics.
     In the FY 2018 SNF PPS final rule (82 FR 36608 through 
36623), we adopted additional policies for the Program, including an 
exchange function methodology for disbursing value-based incentive 
payments.
     In the FY 2019 SNF PPS final rule (83 FR 39272 through 
39282), we adopted more policies for the Program, including a scoring 
adjustment for low-volume facilities.
     In the FY 2020 SNF PPS final rule (84 FR 38820 through 
38825), we adopted additional policies for the Program, including a 
change to our public reporting policy and an update to the deadline for 
the Phase One Review and Correction process. We also adopted a data 
suppression policy for low-volume SNFs.
     In the FY 2021 SNF PPS final rule (85 FR 47624 through 
47627), we amended regulatory text definitions at Sec.  413.338(a)(9) 
and (11) to reflect the definition of Performance Standards and the 
updated Skilled Nursing Facility Potentially Preventable Readmissions 
after Hospital Discharge measure name, respectively. We also updated 
the Phase One Review and Correction deadline and codified that update 
at Sec.  413.338(e)(1). Additionally, we codified the data suppression 
policy for low-volume SNFs at Sec.  413.338(e)(3)(i), (ii), and (iii) 
and amended Sec.  413.338(e)(3) to reflect that SNF performance 
information will be publicly reported on the Nursing Home Compare 
website and/or successor website (84 FR 38823 through 38824) which 
since December 2020 is the Provider Data Catalogue website (https://data.cms.gov/provider-data/).
    The SNF VBP Program applies to freestanding SNFs, SNFs affiliated 
with acute care facilities, and all non-CAH swing-bed rural hospitals. 
Section 1888(h)(1)(B) of the Act requires that the SNF VBP Program 
apply to payments for services furnished on or after October 1, 2018. 
We believe the implementation of the SNF VBP Program is an important 
step towards transforming how payment is made for care, moving 
increasingly towards rewarding better value, outcomes, and innovations 
instead of merely rewarding volume.

B. Measures

    For background on the measures we have adopted for the SNF VBP 
Program, we refer readers to the FY 2016 SNF PPS final rule (80 FR 
46419), where we finalized the Skilled Nursing Facility 30-Day All-
Cause Readmission Measure (SNFRM) (NQF #2510) that we are currently 
using for the SNF VBP Program. We also refer readers to the FY 2017 SNF 
PPS final rule (81 FR 51987 through 51995), where we finalized the 
Skilled Nursing Facility 30-Day Potentially Preventable Readmission 
Measure (SNFPPR) that we will use for the SNF VBP Program instead of 
the SNFRM as soon as practicable, as required by statute. The SNFPPR 
measure's name is now ``Skilled Nursing Facility Potentially 
Preventable Readmissions after Hospital Discharge measure'' (Sec.  
413.338(a)(11)). We intend to submit the SNFPPR measure for NQF 
endorsement review during the Fall 2021 cycle, and to assess transition 
timing of the SNFPPR measure to the SNF VBP Program after NQF 
endorsement review is complete.
1. Proposed Flexibilities for the SNF VBP Program in Response to the 
Public Health Emergency Due to COVID-19
    In previous rules, we have identified the need for flexibility in 
our quality programs to account for the impact of changing conditions 
that are beyond participating facilities' or practitioners' control. We 
identified this need because we would like to ensure that participants 
in our programs are not affected negatively when their quality 
performance suffers not due to the care provided, but due to external 
factors.
    A significant example of the type of external factor that may 
affect quality measurement is the COVID-19 public health emergency 
(PHE), which has had, and continues to have, significant and ongoing 
effects on the provision of medical care in the country and around the 
world. The COVID-19 pandemic and associated PHE has impeded effective 
quality measurement in many ways. Changes to clinical practices to 
incorporate safety protocols for medical personnel and patients, as 
well as unpredicted changes in the number of stays and facility-level 
case mixes, have affected the data that SNFs report under the SNF VBP 
Program and the resulting measure calculations. CMS is currently 
considering whether the SNF readmission measure specifications should 
be updated to account for changes in SNF admission and/or hospital 
readmission patterns that we have observed during the PHE. 
Additionally, because COVID-19 prevalence is not identical across the 
country, facilities located in different areas have been affected 
differently at different times throughout the pandemic. Under those 
circumstances, we remain concerned that the SNF readmission measure 
scores are distorted, which would result in skewed payment incentives 
and inequitable payments, particularly for SNFs that have treated more 
COVID-19 patients than others.
    It is not our intention to penalize SNFs based on measure scores 
that we believe are distorted by the COVID-19 pandemic, and are thus 
not reflective of the quality of care that the measure in the SNF VBP 
Program was designed to assess. As discussed above, the COVID-19 
pandemic has had, and continues to have, significant and enduring 
effects on health care systems around the world, and affects care 
decisions, including readmissions to the hospital as measured by the 
SNF VBP Program. As a result of the PHE, SNFs could provide care to 
their patients that meets the underlying clinical standard but results 
in worse measured performance, and by extension, lower incentive 
payments in the SNF VBP Program. Additionally, because COVID-19 
prevalence has not been identical across the country, SNFs located in 
different regions have been affected differently during the PHE. As a 
result, we are concerned that regional differences in COVID-19 
prevalence during the revised performance period for the FY 2022 SNF 
VBP Program, which includes one quarter of data

[[Page 20007]]

during the pandemic (July 1, 2020 through September 30, 2020), have 
directly affected SNF readmission measure scores for the FY 2022 SNF 
VBP program year. Although these regional differences in COVID-19 
prevalence rates do not reflect differences in the quality of care 
furnished by SNFs, they directly affect the value-based incentive 
payments that these SNFs are eligible to receive and could result in an 
unfair and inequitable distribution of those incentives. These 
inequities could be especially pronounced for SNFs that have treated a 
large number of COVID-19 patients.
    Therefore, we are proposing to adopt a policy for the duration of 
the PHE for COVID-19 that would enable us to suppress the use of SNF 
readmission measure data for purposes of scoring and payment 
adjustments in the SNF VBP Program if we determine that circumstances 
caused by the PHE for COVID-19 have affected the measure and the 
resulting performance scores significantly. Under this proposed policy, 
if we determine that the suppression of the SNF readmission measure is 
warranted for a SNF VBP program year, we would propose to calculate the 
SNF readmission measure rates for that program year but then suppress 
the use of those rates to generate performance scores, rank SNFs, and 
generate value-based incentive payment percentages based on those 
performance scores. We would instead assign each eligible SNF's 
performance score of zero for the program year to mitigate the effect 
that the distorted measure results would otherwise have on SNF's 
performance scores and incentive payment multipliers. We would also 
reduce each eligible SNF's adjusted Federal per diem rate by the 
applicable percent (2 percent) and then further adjust the resulting 
amounts by a value-based incentive payment amount equal to 60 percent 
of the total reduction. Those SNFs subject to the Low-Volume Adjustment 
policy would receive 100 percent of their 2 percent withhold per the 
policy previously finalized in the FY 2020 SNF PPS final rule (84 FR 
38823 through 38824). We would also provide each SNF with its SNF 
readmission measure rate in confidential feedback reports so that the 
SNF is aware of the observed changes to its measure rates. We would 
also publicly report the FY 2022 SNF readmission measure rates with 
appropriate caveats noting the limitations of the data due to the PHE 
for COVID-19.
    In developing this proposed policy, we considered what 
circumstances caused by the PHE for COVID-19 would affect a quality 
measure significantly enough to warrant its suppression in a value-
based purchasing program. We believe that a significant deviation in 
measured performance that can be reasonably attributed to the PHE for 
COVID-19 is a significant indicator of changes in clinical conditions 
that affect quality measurement. Similarly, we believe that a measure 
may be focused on a clinical topic or subject that is proximal to the 
disease, pathogen, or other health impacts of the PHE. As has been the 
case during the COVID-19 PHE, we believe that rapid or unprecedented 
changes in clinical guidelines and care delivery, potentially including 
appropriate treatments, drugs, or other protocols, may affect quality 
measurement significantly and should not be attributed to the 
participating facility positively or negatively. We also note that 
scientific understanding of a particular disease or pathogen may evolve 
quickly during an emergency, especially in cases of new disease or 
conditions. Finally, we believe that, as evidenced during the COVID-19 
PHE, national or regional shortages or changes in health care 
personnel, medical supplies, equipment, diagnostic tools, and patient 
case volumes or facility-level case mix may result in significant 
distortions to quality measurement.
    Based on these considerations, we developed a number of Measure 
Suppression Factors that we believe should guide our determination of 
whether to propose to suppress the SNF readmission measure for one or 
more program years that overlap with the PHE for COVID-19. We are 
proposing to adopt these Measure Suppression Factors for use in the SNF 
VBP and, for consistency, the following other value-based purchasing 
programs: Hospital Value-Based Purchasing Program, Hospital 
Readmissions Reduction Program, HAC Reduction Program, and End-Stage 
Renal Disease Quality Incentive Program. We believe that these Measure 
Suppression Factors will help us evaluate the SNF readmission measure 
in the SNF VBP program and that their adoption in the other value-based 
purchasing programs noted above will help ensure consistency in our 
measure evaluations across programs. The proposed Measure Suppression 
Factors are:
    (1) Significant deviation in national performance on the measure 
during the PHE for COVID-19, which could be significantly better or 
significantly worse compared to historical performance during the 
immediately preceding program years.
    (2) Clinical proximity of the measure's focus to the relevant 
disease, pathogen, or health impacts of the PHE for COVID-19.
    (3) Rapid or unprecedented changes in:
     Clinical guidelines, care delivery or practice, 
treatments, drugs, or related protocols, or equipment or diagnostic 
tools or materials; or
     The generally accepted scientific understanding of the 
nature or biological pathway of the disease or pathogen, particularly 
for a novel disease or pathogen of unknown origin.
    (4) Significant national shortages or rapid or unprecedented 
changes in:
     Healthcare personnel;
     Medical supplies, equipment, or diagnostic tools or 
materials; or
     Patient case volumes or facility-level case mix.
    We also considered alternatives to this proposed policy that could 
also fulfill our objective to not hold facilities accountable for 
measure results that are distorted due to the PHE for COVID-19. As 
noted above, the country continues to grapple with the effects of the 
COVID-19 PHE, and in March 2020, we issued a nationwide, blanket 
Extraordinary Circumstances Exception (ECE) for all hospitals and other 
facilities participating in our quality reporting and value-based 
purchasing programs in response to the PHE for COVID-19. This blanket 
ECE excepted all data reporting requirements for Q1 and Q2 2020 data. 
For claims-based measures, we also stated that we would exclude all 
qualifying Q1 and Q2 2020 claims from our measure calculations. We 
considered extending the blanket ECE that we issued for Q1 and Q2 2020 
to also include Q3 2020 data. However, this option would result in less 
than 12 months of data being used to calculate the single readmissions 
measure in the Program for multiple Program years, which we do not 
believe would provide an accurate assessment of the quality of care 
provided in SNFs. This option would also leave no comprehensive data 
available for us to provide confidential performance feedback to 
providers nor for monitoring and to inform decision-making for 
potential future programmatic changes, particularly as the PHE is 
extended.
    We view this measure suppression proposal as a necessity to ensure 
that the SNF VBP program does not reward or penalize facilities based 
on factors that the SNF readmission measure was not designed to 
accommodate. We intend for this proposed policy to provide short-term 
relief to SNFs when we have determined that one or more of the Measure 
Suppression Factors

[[Page 20008]]

warrants the suppression of the SNF readmission measure.
    We invite public comments on this proposal for the adoption of a 
measure suppression policy for the SNF VBP Program for the duration of 
the PHE for COVID-19, and also on the proposed Measure Suppression 
Factors that we developed for purposes of this proposed policy.
    We are also inviting comment on whether we should consider adopting 
a measure suppression policy that would apply in a future national PHE, 
and if so, whether under such a policy, we should have the flexibility 
to suppress quality measures without specifically proposing to do so in 
rulemaking. We also request comment on whether we should in future 
years consider adopting any form of regional adjustment for the 
proposed measure suppression policy that could take into account any 
disparate effects of circumstances affecting hospitals around the 
country that would prompt us to suppress a measure. For example, COVID-
19 affected different regions of the country at different rates 
depending on factors like time of year, geographic density, state and 
local policies, and health care system capacity. In future years and 
for future PHEs, should they arise, we also request commenters' 
feedback on whether we should, rather than suppress a measure 
completely, consider a suppression policy with more granular effects 
based on our assessment of the geographic effects of the circumstances, 
and if so, how region-based measure suppression could be accounted for 
within the program's scoring methodology.
2. Proposal To Suppress the SNFRM for the FY 2022 SNF VBP Program Year
    In this proposed rule, we are proposing to suppress the SNFRM for 
the FY 2022 SNF VBP Program Year under proposed Measure Suppression 
Factor: (4) Significant national shortages or rapid or unprecedented 
changes in: (iii) Patient case volumes or facility-level case mix.
    In response to the PHE for COVID-19, we granted an extraordinary 
circumstance exemption (ECE) for SNFs participating in the SNF VBP 
Program. Under the ECE, SNF qualifying claims for the period January 1, 
2020-June 30, 2020 are excepted from the calculation of the SNFRM. 
Because this ECE excepted data for 6 months of the performance period 
that we had previously finalized for the FY 2022 SNF VBP program year 
(84 FR 38822), we updated the performance period for that program year 
in the ``Medicare and Medicaid Programs, Clinical Laboratory 
Improvement Amendments, and Patient Protection and Affordable Care Act: 
Additional Policy and Regulatory Revisions in Response to the COVID-19 
Public Health Emergency'' interim final rule with comment (``the 
September 2nd IFC'') (85 FR 54820). Specifically, we finalized that the 
new performance period for the FY 2022 SNF VBP Program year would be 
April 1, 2019-December 31, 2019 and July 1, 2020-September 30, 2020 
because we believed that this period, which combined 9 months of data 
prior to the start of the PHE for COVID-19 and 3 months of data after 
the end of the ECE, would provide sufficiently reliable data for 
evaluating SNFs for the FY 2022 SNF VBP Program. However, analyses 
conducted by our contractor since the publication of the September 2nd 
IFC have found that when July-September 2020 SNF data are compared with 
July-September 2019 SNF data, the July-September 2020 SNF data showed 
25 percent fewer SNF admissions and 26 percent fewer readmissions from 
a SNF to a hospital. These impacts have affected the reliability of the 
SNFRM. Generally speaking, the SNFRM's reliability decreases as the 
sample size and measured outcome (that is, readmissions) decrease. A 
drop of 25 percent in SNF admissions and 26 percent in readmissions to 
the hospital from July-September 2020 has significantly reduced the 
sample size needed to calculate both the measure cohort and outcome for 
the FY 2022 SNF VBP, thus jeopardizing the measure reliability. Our 
contractor's analysis using FY 2019 data showed that such changes may 
lead to a 15 percent decrease in the measure reliability, assessed by 
the intra[hyphen]class correlation coefficient (ICC). In addition, the 
current risk-adjustment model does not factor in COVID-19 or the fact 
that SNFs are treating different types of patients as a result of the 
COVID-19 PHE. Nearly 10 percent of SNF residents in July-September 2020 
had a current or prior diagnosis of COVID-19, with uneven regional 
impacts. The SNFRM does not adjust for COVID-19 in the risk adjustment 
methodology, as the measure was developed before the pandemic. As a 
result, risk-adjusted rates, which compare SNFs to each other 
nationally, are likely to reflect variation in COVID-19 prevalence 
rather than variation in quality of care. We do not believe that 
assessing SNFs on a quality measure affected significantly by the 
varied regional response to the COVID-19 PHE presents a clear picture 
of the quality of care provided by an individual SNF. The data also 
demonstrated other important changes in SNF patient case-mix during the 
PHE for COVID-19, including an 18 percent increase in dual-eligible 
residents and a 9 percent increase in African-American SNF residents at 
the facility level. They have been disproportionately impacted by 
COVID, both in terms of morbidity and mortality. We are currently 
conducting analyses to determine whether and how the SNFRM 
specifications may need to be updated to account for SNF residents with 
a primary or secondary diagnosis of COVID-19 for future program years. 
We also plan to conduct such analysis for the SNFPPR measure.
    We considered whether we could propose to remove the July 1, 2020-
September 30, 2020 data from the updated performance period for the FY 
2022 SNF VBP program year and calculate the SNFRM using a 9-month 
performance period (April 1, 2019-December 31, 2019). To determine 
whether the measure would be reliable using data during this period, 
which would be closer to 8 months once we remove all SNF stays whose 
30-day readmission risk-window extended to or after January 1, 2020, we 
performed reliability analyses using a formula that relates the 
reliability of a measure to its intraclass correlation (ICC), and found 
that an estimate of reliability using all 12 combinations of potential 
8-month data periods from FY 2019 (that is, October through May, 
November through June, and so on) \110\ produces an average reliability 
estimate of 0.367, which is lower than our generally accepted minimum 
reliability threshold of 0.40.
---------------------------------------------------------------------------

    \110\ We assessed multiple 8-month data periods and averaged the 
reliability results to obtain a complete understanding of 
reliability across FY 2019, the most recent full year of production 
data available for analysis, and avoid potential issues caused by 
seasonality.
---------------------------------------------------------------------------

    We also considered substituting the July 1, 2020-September 30, 2020 
period with an alternate data period; however, we are limited 
operationally in terms of which data may be used. Using data from 
further in the future would cause a delay in the calculation and 
dissemination of results for the FY 2022 Program. Such a delay could 
require us to make adjustments to the otherwise applicable Federal per 
diem rate paid to SNFs in FY 2022 on a delayed basis, which would be an 
extremely burdensome process for the MACs and a potentially confusing 
process for SNFs. While using older data is feasible, and we recognize 
that we adopted a performance period in the September 2nd IFC that 
duplicated the use of data from a previous performance period, our

[[Page 20009]]

preference is to use as much new data as possible to assess SNF 
performance each year and to avoid, where feasible, using the same data 
as a performance period in multiple program years. Further revising the 
FY 2022 Program performance period to include older data would create a 
substantial overlap with the FY 2021 Program's performance period. Such 
a significant overlap would result in SNFs receiving payments in FY 
2022 based largely on the same performance used to assess SNFs for the 
FY 2021 program year. Using over 80 percent of the same data twice as a 
performance period could result in some SNFs being penalized (or 
receiving a bonus) twice for nearly the same performance.
    Therefore, due to concerns about the validity of the measure when 
calculated as currently specified on data during the PHE given the 
significant changes in SNF patient case volume and facility-level case 
mix described above, and lacking any viable alternatives, we are 
proposing to suppress the use of SNF readmission measure data for 
purposes of scoring and payment adjustments in the FY 2022 program 
year, under the proposed Measure Suppression Factor (4) Significant 
national or regional shortages or rapid or unprecedented changes in: 
(iii) Patient case volumes or facility-level case mix.
    Under this proposed suppression policy, for all SNFs participating 
in the FY 2022 SNF VBP program, we will use the previously finalized 
performance period and baseline period to calculate each SNF's RSRR for 
the SNFRM. Then, we would suppress the use of SNF readmission measure 
data for purposes of scoring and payment adjustments. Specifically, we 
are proposing to change the scoring methodology to assign all SNFs a 
performance score of zero in the FY 2022 Program year. This would 
result in all participating SNFs receiving an identical performance 
score, as well as an identical incentive payment multiplier. We would 
then apply the Low-Volume Adjustment policy as previously finalized in 
the FY 2020 SNF PPS final rule (84 FR 38823 through 38824). That is, if 
a SNF has fewer than 25 eligible stays during the performance period 
for a program year we will assign that SNF a performance score 
resulting in a net-neutral payment incentive multiplier. SNFs will not 
be ranked for the FY 2022 SNF VBP program.
    Under this proposal we would reduce each participating SNF's 
adjusted Federal per diem rate for FY 2022 by 2 percentage points and 
award each participating SNF 60 percent of that 2 percent withhold, 
resulting in a 1.2 percent payback for the FY 2022 program year. We 
believe this continued application of the 2 percent withhold is 
required under section 1888(h)(5)(C)(ii)(III) of the Act and that a 
payback percentage that is spread evenly across all qualifying SNFs is 
the most equitable way to reduce the impact of the withhold in light of 
our proposal to award a performance score of zero to all SNFs. Those 
SNFs subject to the Low-Volume Adjustment policy would receive 100 
percent of their 2 percent withhold per the previously finalized policy 
increasing the overall payback percentage to an estimated 62.9 percent.
    Further, we propose to provide quarterly confidential feedback 
reports to SNFs and publicly report the SNFRM rates for the FY 2022 SNF 
VBP Program year. However, we will make clear in the public 
presentation of those data that the measure has been suppressed for 
purposes of scoring and payment adjustments because of the effects of 
the PHE for COVID-19 on the data used to calculate the measure. We 
propose to codify this policy at Sec.  413.338(g).
    We invite public comment on this proposal.
3. Proposed Revision to the SNFRM Risk Adjustment Look-Back Period for 
the FY 2023 SNF VBP Program
    In the FY 2021 SNF PPS final rule (85 FR 47624), we finalized the 
FY 2023 Program performance period as FY 2021 (October 1, 2020-
September 30, 2021). In the FY 2016 SNF PPS final rule (80 FR 46418), 
we finalized that the risk adjustment model would account for certain 
risk-factors within 365 days prior to the discharge from the hospital 
to the SNF (a 365-day lookback period). Under the COVID-19 ECE, SNF 
qualifying claims for the period January 1, 2020-June 30, 2020 are 
excepted from the calculation of the SNFRM; using FY 2021 data this 
results in at least 3 months of lookback being available for all SNF 
stays included in the measure without extending into or beyond June 30, 
2020. Here, we propose instead a 90-day lookback period for risk 
adjustment in the FY 2023 performance period (FY 2021) only. Using a 
90-day risk-adjustment period will allow us to use the most recent 
claims available for risk-adjustment, and an identical risk-adjustment 
lookback period for all stays included in the measure. It also allows 
us to avoid combining data from both prior to and during the COVID-19 
PHE in the risk-adjustment lookback period, which would be necessary if 
we attempted to maintain a 12-month look-back period due to the COVID-
19 ECE. Using a 90-day lookback period for risk adjustment will allow 
us to look back 90 days prior to the discharge from the hospital to the 
SNF for each SNF stay. Analyses conducted on FY 2019 performance data 
found that when compared to the 365-day lookback period traditionally 
used, a 90-day lookback period resulted in similar model performance 
(that is, the C-statistic was nearly identical). We are also 
considering similarly reducing the risk-adjustment lookback period for 
the applicable FY 2023 program baseline year which would align the 
risk-adjustment lookback period for the baseline and performance years 
in the FY 2023 program; we invite comments on this consideration.
    We invite public comment on the proposed updates to the risk 
adjustment look-back period for the FY 2023 Performance Period.
4. Request for Comments on Potential Future Measures for the SNF VBP 
Program
    On December 27, 2020, Congress enacted the Consolidated 
Appropriations Act, 2021 (CAA) (Pub. L. 116-260). Section 111(a)(1) of 
Division CC of the CAA amends section 1888(h)(1) of the Act to, with 
respect to payments for services furnished on or after October 1, 2022, 
preclude the SNF VBP from applying to a SNF for which there are not a 
minimum number (as determined by the Secretary) of cases for the 
measures that apply to the facility for the performance period for the 
applicable fiscal year, or measures that apply to the facility for the 
performance period for the applicable fiscal year. Section 111(a)(2) of 
the CAA amended section 1888(h)(2)(A) of the Act to, with respect to 
payments for services furnished on or after October 1, 2023, require 
the Secretary to apply the readmission measure specified under section 
1888(g)(1) of the Act, and allow the Secretary to apply up to 9 
additional measures determined appropriate, which may include measures 
of functional status, patient safety, care coordination, or patient 
experience. To the extent that the Secretary decides to apply 
additional measures, section 1888(h)(2)(A)(ii) of the Act, as amended 
by section 111(a)(2)(C) of the CAA, requires the Secretary to consider 
and apply, as appropriate, quality measures specified under section 
1899B(c)(1) of the Act. Finally, section 111(a)(3) of the CAA amended 
section 1888(h) of the Act by adding a new paragraph (12), which 
requires that the Secretary apply a process to validate the measures 
and data submitted under the SNF VBP and the SNF QRP, as appropriate, 
which may be similar to the process specified under the Hospital 
Inpatient Quality Reporting (IQR) Program for validating

[[Page 20010]]

inpatient hospital measures. In this proposed rule, we are seeking 
input from stakeholders regarding which measures we should consider 
adding to the SNF VBP Program. We intend to use future rulemaking to 
address these new statutory requirements.
    Currently, the SNF VBP Program includes only a single quality 
measure, the SNFRM, which we intend to transition to the SNFPPR measure 
as soon as practicable. Both the SNFRM and SNFPPR assess the risk-
adjusted rate of readmissions to hospitals, for SNF residents within 30 
days of discharge from a prior hospital stay. Consistent with amended 
section 1888(h)(2)(A)(ii) of the Act, in considering which measures 
might be appropriate to add to the SNF VBP Program, we are considering 
additional clinical topics such as measures of functional status, 
patient safety, care coordination, and patient experience, as well as 
measures on those topics that are utilized in the SNF Quality Reporting 
Program (QRP). For more information about the SNF QRP measures, please 
visit: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Measures-and-Technical-Information.
    We are also considering measures on clinical topics that are not 
included in the SNF QRP's measure set because we believe that other 
clinical topics would be helpful to our efforts to robustly assess the 
quality of care furnished by SNFs.
    In expanding the SNF VBP measure set, we are also considering 
measures that we already require for Long-Term Care Facilities (LTCFs), 
which include both SNFs and nursing facilities (NFs), to collect and 
report under other initiatives. Approximately 94 percent of LTCFs are 
dually certified as both a SNF and NF (Provider Data Catalog Nursing 
Homes and Rehab Services Provider Information File January 2021) 
(https://data.cms.gov/provider-data/dataset/4pq5-n9py). The vast 
majority of LTCF residents are also Medicare beneficiaries, regardless 
of whether they are in a Medicare Part A SNF stay, because they are 
enrolled in Medicare Part B and receive Medicare coverage of certain 
services provided by the LTCF even if they are a long-term care 
resident. Therefore, we believe that expanding the SNF VBP measure set 
to assess the quality of care that SNFs provide to all residents of the 
facility, regardless of payer, would best represent the quality of care 
provided to all Medicare beneficiaries in the facility. We are 
requesting public comment on whether the measures in an expanded SNF 
VBP measure set should require SNFs to collect data on all residents in 
the facility, regardless of payer.
    We have identified the measures listed in Table 31 as measures we 
could add to the SNF VBP Program measure set, and we seek comment on 
those measures, including which of those measures would be best suited 
for the program. We also seek public comment on any measures or measure 
concepts that are not listed in Table 31 that stakeholders believe we 
should consider for the SNF VBP Program. In considering an initial set 
of measures with which SNFs should largely be familiar (through the SNF 
QRP, 5-Star Rating Program and/or the Nursing Home Quality Initiative 
(NHQI)), we believe we can implement a measure set that would impose 
minimal additional burden on SNFs.

 Table 31--Quality Measures Under Consideration for an Expanded Skilled Nursing Facility Value-Based Purchasing
                                                     Program
----------------------------------------------------------------------------------------------------------------
       Meaningful measure area                     NQF                             Quality measure
----------------------------------------------------------------------------------------------------------------
                                                Minimum Data Set
----------------------------------------------------------------------------------------------------------------
Functional Outcomes..................  A2635......................  Application of IRF Functional Outcome
                                                                     Measure: Discharge Self-Care Score for
                                                                     Medical Rehabilitation Patients.*
Functional Outcomes..................  A2636......................  Application of IRF Functional Outcome
                                                                     Measure: Discharge Mobility Score for
                                                                     Medical Rehabilitation Patients.*
Preventable Healthcare Harm..........  0674.......................  Percent of Residents Experiencing One or
                                                                     More Falls with Major Injury (Long Stay).**
Preventable Healthcare Harm..........  0679.......................  Percent of High Risk Residents with Pressure
                                                                     Ulcers (Long Stay).**
Functional Outcomes..................  N/A........................  Percent of Residents Whose Ability to Move
                                                                     Independently Worsened (Long Stay).**
Functional Outcomes..................  N/A........................  Percent of Residents Whose Need for Help
                                                                     with Activities of Daily Living Has
                                                                     Increased (Long Stay).**
Transfer of Health Information and     N/A........................  Transfer of Health Information to the
 Interoperability.                                                   Provider-Post Acute Care.*
Medication Management................  N/A........................  Percentage of Long-Stay Residents who got an
                                                                     Antipsychotic Medication.**
----------------------------------------------------------------------------------------------------------------
                                 Medicare Fee-For-Service Claims Based Measures
----------------------------------------------------------------------------------------------------------------
Community Engagement.................  3481.......................  Discharge to Community Measure-Post Acute
                                                                     Care Skilled Nursing Facility Quality
                                                                     Reporting Program.*
Patient-focused Episode of Care......  N/A........................  Medicare Spending per Beneficiary (MSPB)-
                                                                     Post Acute Care Skilled Nursing Facility
                                                                     Quality Reporting Program.*
Healthcare-Associated Infections.....  N/A........................  Skilled Nursing Facility Healthcare-
                                                                     Associated Infections Requiring
                                                                     Hospitalization Measure.~
Admissions and Readmissions to         N/A........................  Number of hospitalizations per 1,000 long-
 Hospitals.                                                          stay resident days (Long Stay).**
----------------------------------------------------------------------------------------------------------------
                               Patient-Reported Outcome-Based Performance Measure
----------------------------------------------------------------------------------------------------------------
Functional Outcomes..................  N/A........................  Patient-Reported Outcomes Measurement
                                                                     Information System [PROMIS]- PROMIS Global
                                                                     Health, Physical.
----------------------------------------------------------------------------------------------------------------

[[Page 20011]]

 
        Survey Questionnaire (similar to Consumer Assessment of Healthcare Providers and Systems (CAHPS))
----------------------------------------------------------------------------------------------------------------
Patient's Experience of Care.........  2614.......................  CoreQ: Short Stay Discharge Measure.
----------------------------------------------------------------------------------------------------------------
                                              Payroll Based Journal
----------------------------------------------------------------------------------------------------------------
N/A..................................  N/A........................  Nurse staffing hours per resident day:
                                                                     Registered Nurse (RN) hours per resident
                                                                     per day; Total nurse staffing (including
                                                                     RN, licensed practical nurse (LPN), and
                                                                     nurse aide) hours per resident per day.**
----------------------------------------------------------------------------------------------------------------
* Measures adopted in the SNF Quality Reporting Program (QRP).
** ** These measures are reported on the Nursing Home Care Compare website (https://www.medicare.gov/care-compare/ compare/).
~ Measure proposed in section VII.C.1 of this proposed rule for adoption in the SNF QRP.

    In addition to the staffing measures listed in Table 31 that focus 
on nurse staffing hours per resident day and that are currently 
reported on the Nursing Home Care Compare website, we are also 
interested in measures that focus on staff turnover. We have been 
developing measures of staff turnover, as required by section 1128I(g) 
of the Act, with the goal of making the information publicly available. 
Through our implementation of the Payroll-Based Journal (PBJ) staffing 
data collection program, we have indicated that we will be reporting 
rates of turnover in the future (for more information on this program, 
see CMS memorandum QSO-18-17-NH \111\). As we plan to report staff 
turnover information in the near future, we are also seeking comment on 
inclusion of these measures in the SNF VBP Program.
---------------------------------------------------------------------------

    \111\ https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/SurveyCertificationGenInfo/Downloads/QSO18-17-NH.pdf.
---------------------------------------------------------------------------

    We are also considering two patient-reported measures, as listed in 
Table 31, to assess residents' views of their healthcare.
    The CoreQ: Short Stay Discharge Measure calculates the percentage 
of individuals discharged in a 6-month time period from a SNF, within 
100 days of admission, who are satisfied with their SNF stay. This 
patient reported outcome measure is based on the CoreQ: Short Stay 
Discharge questionnaire that utilizes four items: (1) In recommending 
this facility to your friends and family, how would you rate it 
overall; (2) Overall, how would you rate the staff; (3) How would you 
rate the care you receive; (4) How would you rate how well your 
discharge needs were met. For additional information about the CoreQ: 
Short Stay Discharge Measure, please visit https://cmit.cms.gov/CMIT_public/ViewMeasure?MeasureId=3436.
    We welcome public comment on future measures for the SNF VBP 
Program, and on whether the measures in an expanded SNF VBP measure set 
should require SNFs to collect data on all residents in the facility, 
regardless of payer.

C. SNF VBP Performance Period and Baseline Period

1. Background
    We refer readers to the FY 2016 SNF PPS final rule (80 FR 46422) 
for a discussion of our considerations for determining performance 
periods under the SNF VBP Program. In the FY 2019 SNF PPS final rule 
(83 FR 39277 through 39278), we adopted a policy whereby we will 
automatically adopt the performance period and baseline period for a 
SNF VBP program year by advancing the performance period and baseline 
period by 1 year from the previous program year.
2. Revised Performance Period for the FY 2022 SNF VBP Program
    In the September 2nd IFC, we updated the performance period for the 
FY 2022 SNF VBP Program to April 1, 2019 through December 31, 2019 and 
July 1, 2020 through September 30, 2020. We also noted that the 
baseline period of the FY 2022 Program had not been impacted by the PHE 
for COVID-19 and will remain as FY 2018 (October 1, 2017 through 
September 30, 2018), and the FY 2022 Program performance standards 
included in the FY 2020 final rule (84 FR 38822 through 38823) will 
remain as finalized.
    However, as noted in section VII.B.3. of this proposed rule, there 
are concerns about the validity of the measure when calculated as 
currently specified on data during the PHE (specifically, July 1, 2020 
through September 30, 2020) given the significant changes in SNF 
patient case volume and facility-level case mix described above. 
Therefore, we are proposing to suppress the SNFRM for the FY 2022 
program year. We will calculate each SNF's RSRR for the SNFRM. Then, we 
would change the scoring methodology to assign all SNFs a performance 
score of zero. This would result in all participating SNFs receiving an 
identical performance score, as well as an identical incentive payment 
multiplier. We would then apply the Low-Volume Adjustment policy as 
previously finalized in the FY 2020 SNF PPS final rule (84 FR 38823 
through 38824). That is, if a SNF has fewer than 25 eligible stays 
during the performance period for a program year we will assign that 
SNF a performance score resulting in a net-neutral payment incentive 
multiplier. We will continue to provide quarterly confidential feedback 
reports to facilities and publicly report based on the usable data from 
the previously finalized performance period (April 1, 2019 through 
December 31, 2019) and the previously finalized baseline period (FY 
2018).
3. Performance Period for the FY 2023 SNF VBP Program
    In the FY 2021 SNF PPS final rule (85 FR 47624), we finalized that 
the Performance Period for the FY 2023 program year would be October 1, 
2020-September 30, 2021 (FY 2021) and the baseline would be FY 2019 
(October 1, 2018-September 30, 2019). We are not proposing any updates 
to the performance period and baseline period previously finalized for 
FY 2023.
    We also considered alternatives to the previously finalized 
performance period for FY 2023. We considered modifying the performance 
period for the FY 2023 program year to Calendar Year 2021 (January 1, 
2021-December 31, 2021). However, CY 2021 data are available later than 
FY 2021 data, and would likely result in a delay calculating SNFRM 
scores for SNFs and a subsequent delay in the application of

[[Page 20012]]

payment incentives for the FY 2023 program year.
    We acknowledge that the COVID-19 PHE extends into both performance 
period options. We believe that following the completion of testing, 
SNF readmission measure specifications may account for changes in SNF 
admission and/or hospital readmission patterns that we have observed 
during the PHE as noted above.
    We invite public comment on this alternative to the previously 
finalized Performance Period for the FY 2023 SNF VBP program.
4. Performance Period and Baseline Period for the FY 2024 SNF VBP 
Program
    Under the policy finalized in the FY 2019 SNF PPS final rule (83 FR 
39277 through 39278), for the FY 2024 program year, the performance 
period would be FY 2022 and the baseline period would be FY 2020. 
However, under the ECE, SNF qualifying claims for a 6-month period in 
FY 2020 (January 1, 2020-June 30, 2020) are excepted from the 
calculation of the SNFRM, which means that we will not have a full year 
of data to calculate the SNFRM for the FY 2020 baseline period. 
Moreover, as described in more detail in section VII.B.3 above, we are 
proposing to suppress the SNFRM for the FY 2022 program year, in part 
because there are concerns about the validity of the measure when 
calculated as currently specified on data during the PHE (specifically, 
July 1, 2020 through September 30, 2020) given the significant changes 
in SNF patient case volume and facility-level case mix described above. 
As the SNF VBP Program uses only a single measure calculated on 1 year 
of data and uses each year of data first as a performance period and 
then later on as a baseline period in the Program, the removal of 9 
months of data in light of the COVID-19 PHE as described above will 
necessarily result in data being used more than once in the Program. 
Therefore, to ensure enough data are available to reliably calculate 
the SNFRM, we are proposing FY 2019 data be used for the baseline 
period for the FY 2024 program year. We also considered using FY 2021, 
which will be the baseline period for the FY 2025 program year under 
our current policy. However, it is operationally infeasible for us to 
calculate the baseline for the FY 2024 program year using FY 2021 data 
in time to establish the performance standards for that program year at 
least 60 days prior to the start of the performance period, as required 
under section 1888(h)(3)(C) of the Act.
    We invite public comment on this proposal.

D. Performance Standards

1. Background
    We refer readers to the FY 2017 SNF PPS final rule (81 FR 51995 
through 51998) for a summary of the statutory provisions governing 
performance standards under the SNF VBP Program and our finalized 
performance standards policy. We adopted the final numerical values for 
the FY 2022 performance standards in the FY 2020 SNF PPS final rule (84 
FR 38822), and adopted the final numerical values for the FY 2023 
performance standards in the FY 2021 SNF PPS final rule (85 FR 47625). 
We also adopted a policy allowing us to correct the numerical values of 
the performance standards in the FY 2019 SNF PPS final rule (83 FR 
39276 through 39277).
    We are not proposing any changes to these performance standard 
policies in this proposed rule.
2. SNF VBP Performance Standards Correction Policy
    In the FY 2019 SNF PPS final rule (83 FR 39276 through 39277), we 
finalized a policy to correct numerical values of performance standards 
for a program year in cases of errors. We also finalized that we will 
only update the numerical values for a program year one time, even if 
we identify a second error, because we believe that a one-time 
correction will allow us to incorporate new information into the 
calculations without subjecting SNFs to multiple updates. We stated 
that any update we make to the numerical values based on a calculation 
error will be announced via the CMS website, listservs, and other 
available channels to ensure that SNFs are made fully aware of the 
update. In the FY 2021 SNF PPS final rule (85 FR 47625), we amended the 
definition of ``Performance standards'' at Sec.  413.338(a)(9), 
consistent with these policies finalized in the FY 2019 SNF PPS final 
rule, to reflect our ability to update the numerical values of 
performance standards if we determine there is an error that affects 
the achievement threshold or benchmark. We are not proposing any 
changes to the performance standards correction policy in this proposed 
rule.
3. Performance Standards for the FY 2024 Program Year
    In section VII.C.1, we propose to use FY 2019 data for the baseline 
period for the FY 2024 program year. Based on this baseline period, we 
estimate that the performance standards would have the numerical values 
noted in Table 32. We note that these values represent estimates based 
on the most recently available data, and that we will update the 
numerical values in the FY 2022 SNF PPS final rule.

                        Table 32--Estimated FY 2024 SNF VBP Program Performance Standards
----------------------------------------------------------------------------------------------------------------
                                                                                  Achievement
              Measure ID                          Measure description              threshold        Benchmark
----------------------------------------------------------------------------------------------------------------
SNFRM.................................  SNF 30-Day All-Cause Readmission               0.79270          0.83028
                                         Measure (NQF #2510).
----------------------------------------------------------------------------------------------------------------

E. SNF VBP Performance Scoring

    We refer readers to the FY 2017 SNF PPS final rule (81 FR 52000 
through 52005) for a detailed discussion of the scoring methodology 
that we have finalized for the Program. We also refer readers to the FY 
2018 SNF PPS final rule (82 FR 36614 through 36616) for discussion of 
the rounding policy we adopted. We also refer readers to the FY 2019 
SNF PPS final rule (83 FR 39278 through 39281), where we adopted: (1) A 
scoring policy for SNFs without sufficient baseline period data, (2) a 
scoring adjustment for low-volume SNFs, and (3) an extraordinary 
circumstances exception policy.
    In section VII.B.3. of this proposed rule, we are proposing to 
suppress the SNFRM for the FY 2022 program year. If finalized, for all 
SNFs participating in the FY 2022 SNF VBP program, we will use the 
previously finalized performance period and baseline period to 
calculate each SNF's RSRR for the SNFRM. Then, we would assign all SNFs 
a performance score of zero. This would result in all participating 
SNFs receiving an identical performance score, as well as an identical 
incentive payment multiplier. We would then apply the Low-Volume 
Adjustment policy as previously finalized. That is, if a SNF has fewer 
than 25 eligible stays during the performance period for a

[[Page 20013]]

program year we will assign that SNF a performance score resulting in a 
net-neutral payment incentive multiplier. SNFs will not be ranked for 
the FY 2022 SNF VBP program.

F. SNF Value-Based Incentive Payments

    We refer readers to the FY 2018 SNF PPS final rule (82 FR 36616 
through 36621) for discussion of the exchange function methodology that 
we have adopted for the Program, as well as the specific form of the 
exchange function (logistic, or S-shaped curve) that we finalized, and 
the payback percentage of 60 percent. We adopted these policies for FY 
2019 and subsequent fiscal years.
    We also discussed the process that we undertake for reducing SNFs' 
adjusted Federal per diem rates under the Medicare SNF PPS and awarding 
value-based incentive payments in the FY 2019 SNF PPS final rule (83 FR 
39281 through 39282).
    In section VII.B.3. of this proposed rule, we are proposing to 
suppress the SNFRM for the FY 2022 program year. If finalized, for all 
SNFs participating in the FY 2022 SNF VBP program, we will use the 
previously finalized performance period and baseline period to 
calculate each SNF's RSRR for the SNFRM. Then, we would assign all SNFs 
a performance score of zero. This would result in all participating 
SNFs receiving an identical performance score, as well as an identical 
incentive payment multiplier. SNFs will not be ranked for the FY 2022 
SNF VBP program. We would then apply the Low-Volume Adjustment policy 
as previously finalized. That is, if a SNF has fewer than 25 eligible 
stays during the performance period for a program year we will assign 
that SNF a performance score resulting in a net-neutral payment 
incentive multiplier.
    We are also proposing to reduce each participating SNF's adjusted 
Federal per diem rate for FY 2022 by 2 percentage points and to award 
each participating SNF 60 percent of that 2 percent withhold, resulting 
in a 1.2 percent payback for the FY 2022 program year. We believe this 
continued application of the 2 percent withhold is required under 
section 1888(h)(5)(C)(ii)(III) of the Act and that a payback percentage 
that is spread evenly across all SNFs is the most equitable way to 
reduce the impact of the withhold in light of our proposal to award a 
performance score of zero to all SNFs. Those SNFs subject to the Low-
Volume Adjustment policy which would receive 100 percent of their 2 
percent withhold per the previously finalized policy, increasing the 
overall payback percentage to an estimated 62.9 percent. We propose to 
codify this policy at Sec.  413.338(g).
    We invite public comment on this proposed change to the SNF VBP 
payment policy for the FY 2022 program year.

G. Public Reporting on the Nursing Home Compare Website or a Successor 
Website

1. Background
    Section 1888(g)(6) of the Act requires the Secretary to establish 
procedures to make SNFs' performance information on SNF VBP Program 
measures available to the public on the Nursing Home Compare website or 
a successor website, and to provide SNFs an opportunity to review and 
submit corrections to that information prior to its publication. We 
began publishing SNFs' performance information on the SNFRM in 
accordance with this directive and the statutory deadline of October 1, 
2017. In December 2020, we retired the Nursing Home Compare website and 
are now using the Provider Data Catalogue website (https://data.cms.gov/provider-data/) to make quality data available to the 
public, including SNF VBP performance information.
    Additionally, section 1888(h)(9)(A) of the Act requires the 
Secretary to make available to the public certain information on SNFs' 
performance under the SNF VBP Program, including SNF performance scores 
and their ranking. Section 1888(h)(9)(B) of the Act requires the 
Secretary to post aggregate information on the Program, including the 
range of SNF performance scores and the number of SNFs receiving value-
based incentive payments, and the range and total amount of those 
payments.
    In the FY 2017 SNF PPS final rule (81 FR 52009), we discussed the 
statutory requirements governing public reporting of SNFs' performance 
information under the SNF VBP Program. In the FY 2018 SNF PPS final 
rule (82 FR 36622 through 36623), we finalized our policy to publish 
SNF VBP Program performance information on the Nursing Home Compare or 
successor website after SNFs have had an opportunity to review and 
submit corrections to that information under the two-phase Review and 
Correction process that we adopted in the FY 2017 SNF PPS final rule 
(81 FR 52007 through 52009) and for which we adopted additional 
requirements in the FY 2018 SNF PPS final rule. In the FY 2018 SNF PPS 
final rule, we also adopted requirements to rank SNFs and adopted data 
elements that we will include in the ranking to provide consumers and 
stakeholders with the necessary information to evaluate SNFs' 
performance under the Program (82 FR 36623).
    In section VII.B.3. of this proposed rule, we are proposing to 
suppress the SNFRM for the FY 2022 program year. Under this proposal, 
for all SNFs participating in the FY 2022 SNF VBP program, we will use 
the previously finalized performance period and baseline period to 
calculate each SNF's RSRR for the SNFRM. Then, we would assign all SNFs 
a performance score of zero. This would result in all participating 
SNFs receiving an identical performance score, as well as an identical 
incentive payment multiplier. We would then apply the Low-Volume 
Adjustment policy as previously finalized. That is, if a SNF has fewer 
than 25 eligible stays during the performance period for a program year 
we will assign that SNF a performance score resulting in a net-neutral 
payment incentive multiplier.
    While we will publicly report the SNFRM rates for the FY 2022 
program year, we will make clear in the public presentation of those 
data that we are suppressing the use of those data for purposes of 
scoring and payment adjustments in the FY 2022 SNF VBP given the 
significant changes in SNF patient case volume and facility-level case 
mix described above. SNFs will not be ranked for the FY 2022 SNF VBP 
program.
2. Data Suppression Policy for Low-Volume SNFs
    In the FY 2020 SNF PPS final rule (84 FR 38823 through 38824), we 
adopted a data suppression policy for low-volume SNF performance 
information. Specifically, we finalized that we will suppress the SNF 
performance information available to display as follows: (1) If a SNF 
has fewer than 25 eligible stays during the baseline period for a 
program year, we will not display the baseline risk-standardized 
readmission rate (RSRR) or improvement score, although we will still 
display the performance period RSRR, achievement score, and total 
performance score if the SNF had sufficient data during the performance 
period; (2) if a SNF has fewer than 25 eligible stays during the 
performance period for a program year and receives an assigned SNF 
performance score as a result, we will report the assigned SNF 
performance score and we will not display the performance period RSRR, 
the achievement score, or improvement score; and (3) if a SNF has zero 
eligible cases during the performance period for a program year, we 
will not display any information for that SNF. We codified

[[Page 20014]]

this policy in the FY 2021 SNF PPS final rule (85 FR 47626) at Sec.  
413.338(e)(3)(i), (ii), and (iii).
    In section VII.B.3. of this proposed rule, we are proposing to 
suppress the SNFRM for the FY 2022 program year. Under this proposal, 
for all SNFs participating in the FY 2022 SNF VBP program, we will use 
the previously finalized performance period and baseline period to 
calculate each SNF's RSRR for the SNFRM. Then, we would assign all SNFs 
a performance score of zero. This would result in all participating 
SNFs receiving an identical performance score, as well as an identical 
incentive payment multiplier. We would then apply the Low-Volume 
Adjustment policy as previously finalized. That is, if a SNF has fewer 
than 25 eligible stays during the performance period for a program year 
we will assign that SNF a performance score resulting in a net-neutral 
payment incentive multiplier. SNFs will not be ranked for the FY 2022 
SNF VBP program.
3. Public Reporting of SNF VBP Performance Information on Nursing Home 
Compare or a Successor Website
    Section 1888(h)(9)(A) of the Act requires that the Secretary make 
available to the public on the Nursing Home Compare website or a 
successor website information regarding the performance of individual 
SNFs for a fiscal year, including the performance score for each SNF 
for the fiscal year and each SNF's ranking, as determined under section 
1888(h)(4)(B) of the Act. Additionally, section 1888(h)(9)(B) of the 
Act requires that the Secretary periodically post aggregate information 
on the SNF VBP Program on the Nursing Home Compare website or a 
successor website, including the range of SNF performance scores, and 
the number of SNFs receiving value-based incentive payments and the 
range and total amount of those payments. In the FY 2018 SNF PPS final 
rule (82 FR 36622 through 36623), we finalized our policy to publish 
SNF measure performance information under the SNF VBP Program on 
Nursing Home Compare.
    In the FY 2021 SNF PPS final rule (85 FR 47626), we finalized an 
amendment to Sec.  413.338(e)(3) to reflect that we will publicly 
report SNF performance information on the Nursing Home Compare website 
or a successor website located at https://www.medicare.gov/care-compare/. We are not proposing any changes to the public reporting 
policies in this proposed rule.

H. Proposal To Update and Codify the Phase One Review and Correction 
Claims ``Snapshot'' Policy

    In the FY 2017 SNF PPS final rule (81 FR 52007 through 52009), we 
adopted a two-phase review and corrections process for SNFs' quality 
measure data that will be made public under section 1888(g)(6) of the 
Act and SNF performance information that will be made public under 
section 1888(h)(9) of the Act. We detailed the process for requesting 
Phase One corrections and finalized a policy whereby we would accept 
Phase One corrections to a quarterly report provided during a calendar 
year until the following March 31.
    In the FY 2020 SNF PPS final rule (84 FR 38824 through 38835), we 
updated this policy to reflect a 30-day Phase One Review and Correction 
deadline rather than through March 31st following receipt of the 
performance period quality measure quarterly report.
    In the FY 2021 SNF PPS final rule (85 FR 47626 through 47627), we 
updated the 30-day deadline for Phase One Review and Correction and 
codified the policy at Sec.  413.338(e)(1). Under the updated policy, 
beginning with the baseline period quality report issued on or after 
October 1, 2020 that contains the baseline period measure rate and 
underlying claim information used to calculate the measure rate for the 
applicable program year, SNFs have 30 days following the date that CMS 
provides those reports to review and submit corrections to the data 
contained in those reports. We also stated that if the issuance dates 
of these reports are significantly delayed or need to be shifted for 
any reason, we would notify SNFs through routine communication channels 
including, but not limited to memos, emails, and notices on the CMS SNF 
VBP website at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/SNF-VBP/SNF-VBP-Page.
    We are now proposing to include a Phase One Review and Correction 
claims ``snapshot'' policy beginning with the baseline period and 
performance period quality measure quarterly reports issued on or after 
October 1, 2021. This proposed policy would limit the Phase One Review 
and Correction to errors made by CMS or its contractors when 
calculating a SNF's readmission measure rate and will not allow 
corrections to the underlying administrative claims data used to 
calculate those rates. Under this proposed policy, the administrative 
claims data we use to calculate a SNF's readmission measure rate for 
purposes of a baseline period or performance period for a given SNF VBP 
program year would be held constant (that is, frozen in a ``snapshot'') 
from the time we extract it for that purpose. This proposal would align 
the review and correction policy for the SNF VBP Program with the 
review and correction policy we have adopted for other value-based 
purchasing programs, including the Hospital Readmissions Reduction 
Program (HRRP), Hospital-Acquired Condition (HAC) Reduction Program, 
and Hospital Value-Based Purchasing (VBP) Program.
    For purposes of this program, we propose to calculate the SNF 
readmission measure rates using a static ``snapshot'' of claims updated 
as of 3 months following the last index SNF admission in the applicable 
baseline period or performance period. The source of the administrative 
claims data we use to calculate the SNF readmission measure is the 
Medicare Provider Analysis and Review (MedPAR). For example, if the 
last index SNF admission date for the applicable baseline period or 
performance period is September 30th, 2019, we would extract the 
administrative claims data from the MedPAR file as that data exists on 
December 31st, 2019. SNFs would then receive their SNF readmission 
measure rate and accompanying stay-level information in their 
confidential quality measure quarterly reports, and they would have an 
opportunity to review and submit corrections to our calculations as 
part of the Phase One corrections process. SNFs, however, would not be 
able to correct any of the underlying administrative claims data (for 
example, a SNF discharge destination code) we use to generate the 
measure rate.
    The use of a data ``snapshot'' enables us to provide as timely 
quality data as possible, both to SNFs for the purpose of quality 
improvement and to the public for the purpose of transparency. After 
the claims ``snapshot'' is taken through our extraction of the data 
from MedPAR, it takes several months to incorporate other data needed 
for the SNF readmission measure calculations, generate and check the 
calculations, as well as program, populate, and deliver the 
confidential quarterly reports and accompanying data to SNFs. Because 
several months lead time is necessary after acquiring the input data to 
generate these calculations, if we were to delay our data extraction 
point beyond the date that is 3 months after the last SNF index 
admission attributable to a baseline period or performance period, we 
believe this would create an

[[Page 20015]]

unacceptably long delay both for SNFs to receive timely data for 
quality improvement and transparency, and, incentive payments for 
purposes of this program. Therefore, we believe that a 3-month claims 
``run-out'' period between the date of the last SNF index admission and 
the date of the data extraction is a reasonable period that allows SNFs 
time to correct their administrative claims or add any missing claims 
before those claims are used for measure calculation purposes while 
enabling us to timely calculate the measure. If unforeseen 
circumstances require the use of additional months of claims ``run-
out'', that is, more than 3 months, we would notify SNFs through 
routine communication channels including, but not limited to, memos, 
emails, quarterly reports and notices on the CMS SNF VBP website at 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/SNF-VBP/SNF-VBP-Page.
    We believe this proposed policy would address both fairness and 
operational concerns associated with calculating measure rates and 
would provide consistency across value-based purchasing programs.
    We are also proposing to codify this policy in our regulations by 
revising Sec.  413.338(e)(1) to remove the policies that would no 
longer be applicable beginning October 1, 2021 and state the newly 
proposed policy that would be effective, if finalized, on October 1, 
2021.
    We invite public comment on this proposal to update the Phase One 
Review and Correction policy.

I. Proposal To Update the Instructions for Requesting an ECE in Sec.  
413.338(d)(4)(ii) of the SNF VBP Regulations

    We are proposing to update the instructions for a SNF to request an 
extraordinary circumstances exception (ECE). Specifically, we are 
proposing to update the email address that a SNF must use to send the 
request, as well as the URL for our QualityNet website from 
QualityNet.org to QualityNet.cms.gov. We are also proposing to remove 
the separate reference to newspapers because newspapers are already 
included in the broader term ``media articles.'' We are proposing to 
update Sec.  413.338(d)(4)(ii) of our regulations to reflect these 
changes.
    We invite public comment on this proposal.

VIII. Collection of Information Requirements

    This proposed rule would not impose any new or revised ``collection 
of information'' requirements or burden as it pertains to CMS. For the 
purpose of this section of the preamble, collection of information is 
defined under 5 CFR 1320.3(c) of the Paperwork Reduction Act of 1995's 
(PRA) (44 U.S.C. 3501 et seq.) implementing regulations. Consequently, 
this rule is not subject to the requirements of the PRA.
    We propose in section VI.C.1. of this proposed rule, the SNF HAIs 
Requiring Hospitalization measure beginning with the FY 2023 SNF QRP. 
All claims-based measures are calculated using data that are already 
reported to the Medicare program for payment purposes. Since the data 
source for this quality measure is Medicare fee-for-service claims, 
there is no additional burden for providers.
    In section VI.C.2. of this proposed rule, we propose that SNFs 
submit data on the COVID-19 Vaccination Coverage among Healthcare 
Personnel (HCP) measure beginning with the FY 2023 SNF QRP. We note 
that the CDC would account for the burden associated with the COVID-19 
Vaccination Coverage among HCP measure collection under OMB control 
number 0920-1317 (expiration January 31, 2024). However, the CDC 
currently has a PRA waiver for the collection and reporting of 
vaccination data under section 321 of the National Childhood Vaccine 
Injury Act of 1986 (Pub. L. 99-660, enacted on November 14, 1986) 
(NCVIA).\112\ We refer readers to section X.A.5. of this proposed rule, 
where CMS has provided an estimate of the burden and cost to SNFs, and 
note that the CDC will include it in a revised information collection 
request for 0920-1317.
---------------------------------------------------------------------------

    \112\ Section 321 of the NCVIA provides the PRA waiver for 
activities that come under the NCVIA, including those in the NCVIA 
at section 2102 of the Public Health Service Act (42 U.S.C. 300aa-
2). Section 321 is not codified in the U.S. Code, but can be found 
in a note at 42 U.S.C. 300aa-1.
---------------------------------------------------------------------------

    In section VI.C.3. of this proposed rule, we are proposing to 
update the Transfer of Health (TOH) Information to the Patient--Post 
Acute Care (PAC) measure to exclude residents discharged home under the 
care of an organized home health service or hospice. This measure was 
adopted in the FY 2020 SNF PPS final rule (84 FR 38728) and the 
associated burden was accounted for in OMB 0938-1140 (expiration 
November 30, 2022). The proposed update would not affect the 
information collection burden already established.
    In section VI.G.3. of this proposed rule, we are proposing that 
SNFs submit data on the COVID-19 Vaccination among HCP measure through 
the CDC/National Healthcare Safety Network (NHSN). The NHSN is a 
secure, internet-based surveillance system maintained by the CDC and 
provided free of charge to healthcare facilities including SNFs.
    While the NHSN is currently not utilized by SNFs for purposes of 
meeting the SNF QRP requirements, nursing homes were enrolled in the 
NHSN in 2020 and are currently submitting mandatory COVID-19 data 
through the Long-term Care Facility COVID-19 module (https://www.cdc.gov/nhsn/ltc/covid19/index.html). As such, there is no 
additional information collection burden related to the onboarding and 
training of SNF providers to utilize this system. In section VII.B.3. 
of this proposed rule, we are proposing to suppress the Skilled Nursing 
Facility 30-Day All-Cause Readmission Measure (SNFRM) for the FY 2022 
SNF VBP Program Year. Because the data source for this quality measure 
is Medicare fee-for-service claims, there is no additional burden for 
SNFs. All claims-based measures can be calculated based on data that 
are already reported to the Medicare program for payment purposes.

IX. Response to Comments

    Because of the large number of public comments we normally receive 
on Federal Register documents, we are not able to acknowledge or 
respond to them individually. We will consider all comments we receive 
by the date and time specified in the DATES section of this preamble, 
and, when we proceed with a subsequent document, we will respond to the 
comments in the preamble to that document.

X. Economic Analyses

A. Regulatory Impact Analysis

1. Statement of Need
    This proposed rule updates the FY 2022 SNF prospective payment 
rates as required under section 1888(e)(4)(E) of the Act. It also 
responds to section 1888(e)(4)(H) of the Act, which requires the 
Secretary to provide for publication in the Federal Register before the 
August 1 that precedes the start of each FY, the unadjusted Federal per 
diem rates, the case-mix classification system, and the factors to be 
applied in making the area wage adjustment. As these statutory 
provisions prescribe a detailed methodology for calculating and 
disseminating payment rates under the SNF PPS, we do not have the 
discretion

[[Page 20016]]

to adopt an alternative approach on these issues.
2. Introduction
    We have examined the impacts of this proposed rule as required by 
Executive Order 12866 on Regulatory Planning and Review (September 30, 
1993), Executive Order 13563 on Improving Regulation and Regulatory 
Review (January 18, 2011), the Regulatory Flexibility Act (RFA, 
September 19, 1980, Pub. L. 96-354), section 1102(b) of the Act, 
section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA, March 
22, 1995; Pub. L. 104-4), Executive Order 13132 on Federalism (August 
4, 1999), and the Congressional Review Act (5 U.S.C. 804(2)).
    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). Executive 
Order 13563 emphasizes the importance of quantifying both costs and 
benefits, of reducing costs, of harmonizing rules, and of promoting 
flexibility. This rule has been designated an economically significant 
rule, under section 3(f)(1) of Executive Order 12866. Accordingly, we 
have prepared a regulatory impact analysis (RIA) as further discussed 
below. Also, the rule has been reviewed by OMB.
3. Overall Impacts
    This rule would update the SNF PPS rates contained in the SNF PPS 
final rule for FY 2021 (85 FR 47594). We estimate that the aggregate 
impact would be an increase of approximately $444 million in Part A 
payments to SNFs in FY 2022. This reflects a $445 million increase from 
the update to the payment rates and a $1.2 million decrease due to the 
proposed reduction to the SNF PPS rates to account for the recently 
excluded blood-clotting factors (and items and services related to the 
furnishing of such factors) in section 1888(e)(2)(A)(iii)(VI) of the 
Act. We note that these impact numbers do not incorporate the SNF VBP 
reductions that we estimate would total $191.64 million in FY 2022. We 
would note that events may occur to limit the scope or accuracy of our 
impact analysis, as this analysis is future-oriented, and thus, very 
susceptible to forecasting errors due to events that may occur within 
the assessed impact time period.
    In accordance with sections 1888(e)(4)(E) and (e)(5) of the Act and 
implementing regulations at Sec.  413.337(d), we would update the FY 
2021 payment rates by a factor equal to the market basket index 
percentage change reduced by the forecast error adjustment and the MFP 
adjustment to determine the payment rates for FY 2022. The impact to 
Medicare is included in the total column of Table 33. In proposing the 
SNF PPS rates for FY 2022, we are proposing a number of standard annual 
revisions and clarifications mentioned elsewhere in this proposed rule 
(for example, the proposed update to the wage and market basket indexes 
used for adjusting the Federal rates).
    The annual update proposed in this rule would apply to SNF PPS 
payments in FY 2022. Accordingly, the analysis of the impact of the 
annual update that follows only describes the impact of this single 
year. Furthermore, in accordance with the requirements of the Act, we 
will publish a rule or notice for each subsequent FY that will provide 
for an update to the payment rates and include an associated impact 
analysis.
4. Detailed Economic Analysis
    The FY 2022 SNF PPS payment impacts appear in Table 33. Using the 
most recently available data, in this case FY 2020, we apply the 
current FY 2021 CMIs, wage index and labor-related share value to the 
number of payment days to simulate FY 2021 payments. Then, using the 
same FY 2020 data, we apply the proposed FY 2022 CMIs, wage index and 
labor-related share value to simulate FY 2022 payments. We would note 
that, given that this same data is being used for both parts of this 
calculation, as compared to other analyses discussed in this proposed 
rule which compare data from FY 2020 to data from other fiscal years, 
any issues discussed throughout this proposed rule with regard to data 
collected in FY 2020 would not cause any difference in this economic 
analysis. We tabulate the resulting payments according to the 
classifications in Table 33 (for example, facility type, geographic 
region, facility ownership), and compare the simulated FY 2021 payments 
to the simulated FY 2022 payments to determine the overall impact. The 
breakdown of the various categories of data in Table 33 follows:
     The first column shows the breakdown of all SNFs by urban 
or rural status, hospital-based or freestanding status, census region, 
and ownership.
     The first row of figures describes the estimated effects 
of the various proposed changes on all facilities. The next six rows 
show the effects on facilities split by hospital-based, freestanding, 
urban, and rural categories. The next nineteen rows show the effects on 
facilities by urban versus rural status by census region. The last 
three rows show the effects on facilities by ownership (that is, 
government, profit, and non-profit status).
     The second column shows the number of facilities in the 
impact database.
     The third column shows the effect of the proposed annual 
update to the wage index. This represents the effect of using the most 
recent wage data available. The total impact of this change is 0.0 
percent; however, there are distributional effects of the proposed 
change.
     The fourth column shows the effect of all of the changes 
on the FY 2022 payments. The proposed update of 1.3 percent is constant 
for all providers and, though not shown individually, is included in 
the total column. It is projected that aggregate payments would 
increase by 1.3 percent, assuming facilities do not change their care 
delivery and billing practices in response.
    As illustrated in Table 33, the combined effects of all of the 
changes vary by specific types of providers and by location. For 
example, due to changes in this proposed rule, rural providers would 
experience a 1.8 percent increase in FY 2022 total payments. Finally, 
we note that we did not include in Table 33 the distributional impacts 
associated with the blood-clotting factor exclusion because the 
reduction is so minor that it does not have any visible effect on the 
distributional impacts included in the Table 33.

                                   Table 33--Impact to the SNF PPS for FY 2022
----------------------------------------------------------------------------------------------------------------
                                                                      Number        Update wage    Total change
                    Provider characteristics                         providers       data (%)           (%)
----------------------------------------------------------------------------------------------------------------
Group:
    Total.......................................................          15,440             0.0             1.3

[[Page 20017]]

 
    Urban.......................................................          10,887            -0.1             1.2
    Rural.......................................................           4,553             0.4             1.8
    Hospital-based urban........................................             385            -0.2             1.1
    Freestanding urban..........................................          10,502            -0.1             1.2
    Hospital-based rural........................................             451             0.3             1.6
    Freestanding rural..........................................           4,102             0.4             1.7
Urban by region:
    New England.................................................             742            -0.7             0.6
    Middle Atlantic.............................................           1,447            -0.5             0.8
    South Atlantic..............................................           1,820             0.4             1.7
    East North Central..........................................           2,145            -0.2             1.1
    East South Central..........................................             539            -0.4             0.9
    West North Central..........................................             919             0.4             1.7
    West South Central..........................................           1,342            -0.3             1.0
    Mountain....................................................             536             0.1             1.4
    Pacific.....................................................           1,391             0.2             1.5
    Outlying....................................................               6             0.4             1.7
Rural by region:
    New England.................................................             129            -0.9             0.4
    Middle Atlantic.............................................             245             0.5             1.8
    South Atlantic..............................................             597             1.2             2.5
    East North Central..........................................             909             0.5             1.8
    East South Central..........................................             526            -0.1             1.2
    West North Central..........................................           1,058            -0.3             1.0
    West South Central..........................................             756             0.4             1.7
    Mountain....................................................             222             0.5             1.8
    Pacific.....................................................             111             0.3             1.6
Ownership:
    For profit..................................................          10,809             0.0             1.3
    Non-profit..................................................           3,637             0.0             1.3
    Government..................................................             994             0.2             1.5
----------------------------------------------------------------------------------------------------------------
Note: The Total column includes the proposed FY 2022 1.3 percent market basket increase factor. Additionally, we
  found no SNFs in rural outlying areas.

5. Impacts for the SNF QRP for FY 2022
    Estimated impacts for the SNF QRP are based on analysis discussed 
in section VIII.B. of this proposed rule. The proposed SNF QRP 
requirements add no additional burden to the active collection under 
OMB control number #0938-1140 (CMS-10387; expiration November 30, 
2022).
    In accordance with section 1888(e)(6)(A)(i) of the Act, the 
Secretary must reduce by 2 percentage points the annual payment update 
applicable to a SNF for a fiscal year if the SNF does not comply with 
the requirements of the SNF QRP for that fiscal year. In section VI.A. 
of this proposed rule, we discuss the method for applying the 2 
percentage point reduction to SNFs that fail to meet the SNF QRP 
requirements. As discussed in section VI.C. of this proposed rule, we 
are proposing to add two new measures to the SNF QRP beginning with the 
FY 2023 SNF QRP: SNF Healthcare-Associated Infections Requiring 
Hospitalization Measure (SNF-HAI) and the COVID-19 Vaccination Coverage 
among Healthcare Personnel measure. The SNF-HAI measure is a claims-
based measure, and therefore, would impose no additional burden to the 
SNFs.
    We believe that the burden associated with the SNF QRP is the time 
and effort associated with complying with the non-claims-based measures 
requirements of the SNF QRP. Although the burden associated with the 
COVID-19 Vaccination Coverage among HCP measure is not accounted for 
under the CDC PRA package currently approved under OMB control number 
0920-1317 due to the NCVIA waiver the cost and burden is discussed here 
and will be included in a revised information collection request for 
0920-1317.
    Consistent with the CDC's experience of collecting data using the 
NHSN, we estimate that it would take each SNF an average of 1 hour per 
month to collect data for the COVID-19 Vaccination Coverage among HCP 
measure and enter it into NHSN. We have estimated the time to complete 
this entire activity, since it could vary based on provider systems and 
staff availability. We believe it would take an administrative 
assistant from 45 minutes up to 1 hour and 15 minutes to enter this 
data into NHSN. For the purposes of calculating the costs associated 
with the collection of information requirements, we obtained mean 
hourly wages from the U.S. Bureau of Labor Statistics' May 2019 
National Occupational Employment and Wage Estimates.\113\ To account 
for overhead and fringe benefits, we have doubled the hourly wage. 
These amounts are detailed in Table 34.
---------------------------------------------------------------------------

    \113\ https://www.bls.gov/oes/current/oes_nat.htm. Accessed on 
March 30, 2021.

[[Page 20018]]



   Table 34--U.S. Bureau of Labor and Statistics' May 2019 National Occupational Employment and Wage Estimates
----------------------------------------------------------------------------------------------------------------
                                                                                  Overhead and
              Occupation title                Occupation code    Mean hourly     fringe benefit  Adjusted hourly
                                                                 wage ($/hr)         ($/hr)        wage ($/hr)
----------------------------------------------------------------------------------------------------------------
Administrative Assistant....................         43-6013           $18.31           $18.31           $36.62
----------------------------------------------------------------------------------------------------------------

    Based on this time range, it would cost each SNF between $27.47 and 
$45.78 each month or an average cost of $36.62 each month, and between 
$329.64 and $549.36 each year, or an average cost of $439.44 each year. 
We believe the data submission for the COVID-19 Vaccination Coverage 
among HCP measure would cause SNFs to incur additional average burden 
of 12 hours per year for each SNF and a total annual burden of 180,936 
hours for all SNFs. The estimated annual cost across all 15,078 SNFs in 
the U.S. for the submission of the COVID-19 Vaccination Coverage among 
HCP measure would be between $4,970,312 and $8,283,250.08, and an 
average of $6,625,872.
    We recognize that many SNFs may also be reporting other COVID-19 
data to HHS. However, we believe the benefits of reporting data on the 
COVID-19 Vaccination Coverage among HCP measure to assess whether SNFs 
are taking steps to limit the spread of COVID-19 among their HCP, 
reduce the risk of transmission of COVID-19 within their facilities, 
and to help sustain the ability of SNFs to continue serving their 
communities throughout the PHE and beyond outweigh the costs of 
reporting. We welcome comments on the estimated time to collect data 
and enter it into NHSN.
6. Impacts for the SNF VBP Program
    The estimated impacts of the FY 2022 SNF VBP Program are based on 
historical data and appear in Table 35. We modeled SNF performance in 
the Program using SNFRM data from FY 2018 as the baseline period and an 
8-month period from February 1, 2019 through September 30, 2019 as the 
performance period. Additionally, we modeled a logistic exchange 
function with a payback percentage of 60 percent, as we finalized in 
the FY 2018 SNF PPS final rule (82 FR 36619 through 36621), though we 
note that the 60 percent payback percentage for FY 2022 will be 
adjusted to account for the low-volume scoring adjustment that we 
adopted in the FY 2019 SNF PPS final rule (83 FR 39278 through 39280). 
However, in section VII.B.3. of this proposed rule, we are proposing to 
suppress the SNFRM for the FY 2022 program year. If finalized, we will 
award each participating SNF 60 percent of their 2 percent withhold, 
except those SNFs subject to the low-volume scoring adjustment, which 
would receive 100 percent of their 2 percent withhold. We estimated 
that the low-volume scoring adjustment would increase the 60 percent 
payback percentage for FY 2022 by approximately 2.9 percentage points 
(or $16.4 million), resulting in a payback percentage for FY 2022 that 
is 62.9 percent of the estimated $516.2 million in withheld funds for 
that fiscal year. Based on the 60 percent payback percentage (as 
modified by the low-volume scoring adjustment), we estimated that we 
will redistribute approximately $324.5 million in value-based incentive 
payments to SNFs in FY 2022, which means that the SNF VBP Program is 
estimated to result in approximately $191.6 million in savings to the 
Medicare Program in FY 2022.
    Our detailed analysis of the estimated impacts of the FY 2022 SNF 
VBP Program follows in Table 35.

                             Table 35--SNF VBP Program Estimated Impacts for FY 2022
----------------------------------------------------------------------------------------------------------------
                                                    Mean Risk-
                                                   Standardized         Mean           Mean     Percent of total
        Characteristic             Number of       Readmission      performance     incentive     payment after
                                   facilities      Rate (SNFRM)        score        multiplier      applying
                                                       (%)                                         incentives
----------------------------------------------------------------------------------------------------------------
Group:
    Total.....................           15,026            19.90           1.4545      0.99426               100
    Urban.....................           10,845            19.94           1.1528      0.99379             85.29
    Rural.....................            4,181            19.81           2.2371      0.99547             14.71
    Hospital-based urban *....              284            19.68           1.1794      0.99383              1.79
    Freestanding urban *......           10,520            19.95           1.1423      0.99377             83.47
    Hospital-based rural *....              182            19.55           2.6050      0.99604              0.43
    Freestanding rural *......            3,803            19.81           2.1749      0.99538             14.12
Urban by region:
    New England...............              744            20.10           0.8104      0.99326              5.38
    Middle Atlantic...........            1,462            19.78           0.7155      0.99311             16.57
    South Atlantic............            1,874            20.00           0.6407      0.99299             17.01
    East North Central........            2,065            20.08           1.3950      0.99417             13.32
    East South Central........              555            20.08           0.9471      0.99347              3.53
    West North Central........              923            19.92           2.1104      0.99528              4.23
    West South Central........            1,312            20.11           1.6811      0.99461              7.48
    Mountain..................              523            19.56           1.4090      0.99419              3.72
    Pacific...................            1,381            19.67           0.9702      0.99351             14.05
    Outlying..................                6            20.96           2.5766       0.9960              0.00
Rural by region:
    New England...............              122            19.30           1.6896      0.99462              0.64
    Middle Atlantic...........              210            19.53           1.1779      0.99383              0.90
    South Atlantic............              473            19.91           1.5144      0.99435              2.11
    East North Central........              895            19.69           1.8310      0.99484              3.35

[[Page 20019]]

 
    East South Central........              495            20.06           1.1139      0.99373              2.26
    West North Central........            1,006            19.77           3.5653      0.99753              1.99
    West South Central........              689            20.13           2.5430      0.99595              2.18
    Mountain..................              199            19.43           2.5378      0.99594              0.66
    Pacific...................               91            19.22           1.5856      0.99446              0.60
    Outlying..................                1            19.37           5.1533       1.0000              0.00
Ownership:
    Government................              877            19.77           2.5149       0.9959              3.28
    Profit....................           10,583            19.95           1.3693       0.9941             74.38
    Non-Profit................            3,566            19.81           1.4466       0.9943             22.33
----------------------------------------------------------------------------------------------------------------
* The group category which includes hospital-based/freestanding by urban/rural excludes 237 swing-bed SNFs.

7. Alternatives Considered
    As described in this section, we estimated that the aggregate 
impact for FY 2022 under the SNF PPS would be an increase of 
approximately $444 million in Part A payments to SNFs. This reflects a 
$445 million increase from the update to the payment rates, and a $1.2 
million decrease due to the proposed reduction to the SNF PPS rates to 
account for the recently excluded blood-clotting factors (and items and 
services related to the furnishing of such factors) in section 
1888(e)(2)(A)(iii)(VI) of the Act.
    Section 1888(e) of the Act establishes the SNF PPS for the payment 
of Medicare SNF services for cost reporting periods beginning on or 
after July 1, 1998. This section of the statute prescribes a detailed 
formula for calculating base payment rates under the SNF PPS, and does 
not provide for the use of any alternative methodology. It specifies 
that the base year cost data to be used for computing the SNF PPS 
payment rates must be from FY 1995 (October 1, 1994, through September 
30, 1995). In accordance with the statute, we also incorporated a 
number of elements into the SNF PPS (for example, case-mix 
classification methodology, a market basket index, a wage index, and 
the urban and rural distinction used in the development or adjustment 
of the Federal rates). Further, section 1888(e)(4)(H) of the Act 
specifically requires us to disseminate the payment rates for each new 
FY through the Federal Register, and to do so before the August 1 that 
precedes the start of the new FY; accordingly, we are not pursuing 
alternatives for this process.
    With regard to the alternatives considered related to the other 
provisions contained in this proposed rule, such as the proposed 
methodology for calculating the proportional reduction to the rates to 
account for the exclusion of blood clotting factors from SNF 
consolidated billing, we discuss any alternatives considered within 
those sections.
    With regard to the proposed SNF VBP measure suppression policy, we 
discuss any alternatives considered within those sections.
8. Accounting Statement
    As required by OMB Circular A-4 (available online at https://obamawhitehouse.archives.gov/omb/circulars_a004_a-4/), in Tables 36, 37 
and 38, we have prepared an accounting statement showing the 
classification of the expenditures associated with the provisions of 
this proposed rule for FY 2022. Tables 33 and 36 provide our best 
estimate of the possible changes in Medicare payments under the SNF PPS 
as a result of the policies in this proposed rule, based on the data 
for 15,440 SNFs in our database. Tables 35 and 37 provide our best 
estimate of the possible changes in Medicare payments under the SNF VBP 
as a result of the policies we have proposed for this program. Tables 
34 and 38 provide our best estimate of the additional cost to SNFs to 
submit the data for the SNF QRP as a result of the policies in this 
proposed rule.

       Table 36--Accounting Statement: Classification of Estimated
   Expenditures, From the 2021 SNF PPS Fiscal Year to the 2022 SNF PPS
                               Fiscal Year
------------------------------------------------------------------------
                Category                            Transfers
------------------------------------------------------------------------
Annualized Monetized Transfers.........  $444 million.*
From Whom To Whom?.....................  Federal Government to SNF
                                          Medicare Providers.
------------------------------------------------------------------------
* The net increase of $444 million in transfer payments is a result of
  the $445 million increase due to the proposed market basket increase
  of 1.3 percent, reduced by $1.2 million due to the proposed
  proportional reduction associated with excluding blood clotting
  factors from SNF consolidated billing.


Table 37--Accounting Statement: Classification of Estimated Expenditures
                     for the FY 2022 SNF VBP Program
------------------------------------------------------------------------
                Category                            Transfers
------------------------------------------------------------------------
Annualized Monetized Transfers.........  $324.5 million.*
From Whom To Whom?.....................  Federal Government to SNF
                                          Medicare Providers.
------------------------------------------------------------------------
* This estimate does not include the two percent reduction to SNFs'
  Medicare payments (estimated to be $516.15 million) required by
  statute.


[[Page 20020]]


Table 38--Accounting Statement: Classification of Estimated Expenditures
                     for the FY 2022 SNF QRP Program
------------------------------------------------------------------------
                Category                         Transfers/Costs
------------------------------------------------------------------------
Costs for SNFs to Submit Data for QRP..  $6.6 million.*
------------------------------------------------------------------------
* Costs associated with the submission of data for the COVID-19
  Vaccination Coverage among HCP will occur in FY 2022 and is likely to
  continue in future years.

9. Conclusion
    This rule updates the SNF PPS rates contained in the SNF PPS final 
rule for FY 2021 (85 FR 47594). Based on the above, we estimate that 
the overall payments for SNFs under the SNF PPS in FY 2022 are 
projected to increase by approximately $444 million, or 1.3 percent, 
compared with those in FY 2021. We estimate that in FY 2022, SNFs in 
urban and rural areas would experience, on average, a 1.2 percent 
increase and 1.8 percent increase, respectively, in estimated payments 
compared with FY 2021. Providers in the rural South Atlantic region 
would experience the largest estimated increase in payments of 
approximately 2.5 percent. Providers in the rural New England region 
would experience the smallest estimated increase in payments of 0.4 
percent.

B. Regulatory Flexibility Act Analysis

    The RFA requires agencies to analyze options for regulatory relief 
of small entities, if a rule has a significant impact on a substantial 
number of small entities. For purposes of the RFA, small entities 
include small businesses, non-profit organizations, and small 
governmental jurisdictions. Most SNFs and most other providers and 
suppliers are small entities, either by reason of their non-profit 
status or by having revenues of $30 million or less in any 1 year. We 
utilized the revenues of individual SNF providers (from recent Medicare 
Cost Reports) to classify a small business, and not the revenue of a 
larger firm with which they may be affiliated. As a result, for the 
purposes of the RFA, we estimate that almost all SNFs are small 
entities as that term is used in the RFA, according to the Small 
Business Administration's latest size standards (NAICS 623110), with 
total revenues of $30 million or less in any 1 year. (For details, see 
the Small Business Administration's website at http://www.sba.gov/category/navigation-structure/contracting/contracting-officials/eligibility-size-standards). In addition, approximately 20 percent of 
SNFs classified as small entities are non-profit organizations. 
Finally, individuals and states are not included in the definition of a 
small entity.
    This rule would update the SNF PPS rates contained in the SNF PPS 
final rule for FY 2021 (85 FR 47594). Based on the above, we estimate 
that the aggregate impact for FY 2022 would be an increase of $444 
million in payments to SNFs, resulting from the SNF market basket 
update to the payment rates, reduced by the impact of excluding blood 
clotting factors (and items and services related to the furnishing of 
such factors) from SNF consolidated billing under section 
1888(e)(2)(A)(iii)(VI) and (e)(4)(G)(iii) of the Act. While it is 
projected in Table 33 that all providers would experience a net 
increase in payments, we note that some individual providers within the 
same region or group may experience different impacts on payments than 
others due to the distributional impact of the FY 2022 wage indexes and 
the degree of Medicare utilization.
    Guidance issued by the Department of Health and Human Services on 
the proper assessment of the impact on small entities in rulemakings, 
utilizes a cost or revenue impact of 3 to 5 percent as a significance 
threshold under the RFA. In their March 2021 Report to Congress 
(available at http://www.medpac.gov/docs/default-source/reports/mar21_medpac_ch7_sec.pdf), MedPAC states that Medicare covers 
approximately 9 percent of total patient days in freestanding 
facilities and 16 percent of facility revenue (March 2020 MedPAC Report 
to Congress, 224). As indicated in Table 33, the effect on facilities 
is projected to be an aggregate positive impact of 1.3 percent for FY 
2022. As the overall impact on the industry as a whole, and thus on 
small entities specifically, is less than the 3 to 5 percent threshold 
discussed previously, the Secretary has determined that this proposed 
rule would not have a significant impact on a substantial number of 
small entities for FY 2022.
    In addition, section 1102(b) of the Act requires us to prepare a 
regulatory impact analysis if a rule 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 603 of the RFA. For 
purposes of section 1102(b) of the Act, we define a small rural 
hospital as a hospital that is located outside of an MSA and has fewer 
than 100 beds. This proposed rule would affect small rural hospitals 
that: (1) Furnish SNF services under a swing-bed agreement or (2) have 
a hospital-based SNF. We anticipate that the impact on small rural 
hospitals would be a positive impact. Moreover, as noted in previous 
SNF PPS final rules (most recently, the one for FY 2021 (85 FR 47594)), 
the category of small rural hospitals is included within the analysis 
of the impact of this proposed rule on small entities in general. As 
indicated in Table 33, the effect on facilities for FY 2022 is 
projected to be an aggregate positive impact of 1.3 percent. As the 
overall impact on the industry as a whole is less than the 3 to 5 
percent threshold discussed above, the Secretary has determined that 
this proposed rule would not have a significant impact on a substantial 
number of small rural hospitals for FY 2022.

C. Unfunded Mandates Reform Act Analysis

    Section 202 of the Unfunded Mandates Reform Act of 1995 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 2021, that 
threshold is approximately $158 million. This proposed rule would 
impose no mandates on state, local, or tribal governments or on the 
private sector.

D. Federalism Analysis

    Executive Order 13132 establishes certain requirements that an 
agency must meet when it issues a proposed rule (and subsequent final 
rule) that imposes substantial direct requirement costs on state and 
local governments, preempts state law, or otherwise has federalism 
implications. This proposed rule would have no substantial direct 
effect on state and local governments, preempt state law, or otherwise 
have federalism implications.

[[Page 20021]]

E. Congressional Review Act

    This proposed regulation is subject to the Congressional Review Act 
provisions of the Small Business Regulatory Enforcement Fairness Act of 
1996 (5 U.S.C. 801 et seq.) and has been transmitted to the Congress 
and the Comptroller General for review.

F. Regulatory Review Costs

    If regulations impose administrative costs on private entities, 
such as the time needed to read and interpret this proposed rule, we 
should estimate the cost associated with regulatory review. Due to the 
uncertainty involved with accurately quantifying the number of entities 
that will review the rule, we assume that the total number of unique 
commenters on last year's proposed rule would be the number of 
reviewers of this year's proposed rule. We acknowledge that this 
assumption may understate or overstate the costs of reviewing this 
rule. It is possible that not all commenters reviewed last year's 
proposed rule in detail, and it is also possible that some reviewers 
chose not to comment on that proposed rule. For these reasons, we 
believe that the number of commenters on last year's proposed rule is a 
fair estimate of the number of reviewers of this proposed rule.
    We also recognize that different types of entities are in many 
cases affected by mutually exclusive sections of the proposed rule, and 
therefore, for the purposes of our estimate we assume that each 
reviewer reads approximately 50 percent of the rule.
    Using the national mean hourly wage data from the May 2019 BLS 
Occupational Employment Statistics (OES) for medical and health service 
managers (SOC 11-9111), we estimate that the cost of reviewing this 
rule is $110.74 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 4 hours for 
the staff to review half of the proposed rule. For each SNF that 
reviews the rule, the estimated cost is $442.96 (4 hours x $110.74). 
Therefore, we estimate that the total cost of reviewing this regulation 
is $20,819.12 ($442.96 x 47 reviewers).
    In accordance with the provisions of Executive Order 12866, this 
proposed rule was reviewed by the Office of Management and Budget.

List of Subjects

42 CFR Part 411

    Diseases, Medicare, Reporting and recordkeeping requirements.

42 CFR Part 413

    Principles of reasonable cost reimbursement; payment for end-stage 
renal disease services; optional prospectively determined payment rates 
for skilled nursing facilities; payment for acute kidney injury 
dialysis.

42 CFR Part 489

    Health facilities, Medicare, Reporting and recordkeeping 
requirements.

    For the reasons set forth in the preamble, the Centers for Medicare 
& Medicaid Services proposes to amend 42 CFR chapter IV as set forth 
below:

PART 411--EXCLUSIONS FROM MEDICARE AND LIMITATIONS ON MEDICARE 
PAYMENT

0
1. The authority citation for part 411 continues to read as follows:

    Authority: 42 U.S.C. 1302, 1395w-101 through 1395w-152, 1395hh, 
and 1395nn.

0
2. Amend Sec.  411.15 by--
0
a. Revising paragraphs (p)(2)(xiii) through (xvi);
0
b. Redesignating paragraph (p)(2)(xvii) as (p)(2)(xviii); and
0
c. Adding new paragraph (p)(2)(xvii).
    The revisions and addition read as follows:


Sec.  411.15  Particular services excluded from coverage.

* * * * *
    (p) * * *
    (2) * * *
    (xiii) Those chemotherapy items identified, as of July 1, 1999, by 
HCPCS codes J9000-J9020, J9040-J9151, J9170-J9185, J9200-J9201, J9206-
J9208, J9211, J9230-J9245, and J9265-J9600, and as of January 1, 2004, 
by HCPCS codes A9522, A9523, A9533, and A9534 (as subsequently modified 
by CMS), and any additional chemotherapy items identified by CMS.
    (xiv) Those chemotherapy administration services identified, as of 
July 1, 1999, by HCPCS codes 36260-36262, 36489, 36530-36535, 36640, 
36823, and 96405-96542 (as subsequently modified by CMS), and any 
additional chemotherapy administration services identified by CMS.
    (xv) Those radioisotope services identified, as of July 1, 1999, by 
HCPCS codes 79030-79440 (as subsequently modified by CMS), and any 
additional radioisotope services identified by CMS.
    (xvi) Those customized prosthetic devices (including artificial 
limbs and their components) identified, as of July 1, 1999, by HCPCS 
codes L5050-L5340, L5500-L5611, L5613-L5986, L5988, L6050-L6370, L6400-
6880, L6920-L7274, and L7362-L7366 (as subsequently modified by CMS) 
and any additional customized prosthetic devices identified by CMS, 
which are delivered for a resident's use during a stay in the SNF and 
intended to be used by the resident after discharge from the SNF.
    (xvii) Those blood clotting factors indicated for the treatment of 
patients with hemophilia and other bleeding disorders identified, as of 
July 1, 2020, by HCPCS codes J7170, J7175, J7177-J7183, J7185-J7190, 
J7192-J7195, J7198-J7203, J7205, and J7207-J7211 (as subsequently 
modified by CMS) and items and services related to the furnishing of 
such factors, and any additional blood clotting factors identified by 
CMS and items and services related to the furnishing of such factors.
* * * * *

PART 413--PRINCIPLES OF REASONABLE COST REIMBURSEMENT; PAYMENT FOR 
END-STAGE RENAL DISEASE SERVICES; PROSPECTIVELY DETERMINED PAYMENT 
RATES FOR SKILLED NURSING FACILITIES; PAYMENT FOR ACUTE KIDNEY 
INJURY DIALYSIS

0
3. The authority citation for part 413 continues 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
4. Amend Sec.  413.338 by revising paragraphs (d)(4)(ii) and (e)(1) and 
adding paragraph (g) to read as follows:


Sec.  413.338  Skilled nursing facility value-based purchasing program.

* * * * *
    (d) * * *
    (4) * * *
    (ii) A SNF may request an exception within 90 days of the date that 
the extraordinary circumstances occurred by sending an email to the 
designated email address for SNF VBP ECE requests, which is 
[email protected]. The email must include a completed Extraordinary 
Circumstances Request form (available on https://qualitynet.cms.gov/) 
and any available evidence of the impact of the extraordinary 
circumstances on the care that the SNF furnished to patients including, 
but not limited to, photographs and media articles.
* * * * *
    (e) * * *
    (1) CMS will provide quarterly confidential feedback reports to 
SNFs on their performance on the SNF

[[Page 20022]]

readmission measure. Beginning with the baseline period and performance 
period quality measure quarterly reports issued on or after October 1, 
2021, which contain the baseline period and performance period measure 
rates, respectively, SNFs will have 30 days following the date CMS 
provides each of these reports to review and submit corrections to the 
SNF readmission measure rates contained in that report. The 
administrative claims data used to calculate a SNF's readmission 
measure rates are not subject to review and correction under this 
paragraph (e)(1). All correction requests must be accompanied by 
appropriate evidence showing the basis for the correction to the SNF 
readmission measure rates.
* * * * *
    (g) Special rules for the FY 2022 SNF VBP Program. (1) CMS will 
calculate a SNF readmission measure rate for each SNF based on its 
performance on the SNF readmission measure during the performance 
period specified by CMS for fiscal year 2022, but CMS will not 
calculate a performance score for any SNF using the methodology 
described in paragraphs (d)(1) and (2) of this section. CMS will 
instead assign a performance score of zero to each SNF, with the 
exception of those SNFs qualifying for the low-volume scoring 
adjustment described in paragraph (d)(3) of this section.
    (2) CMS will calculate the value-based incentive payment adjustment 
factor for each SNF using a performance score of zero and will then 
calculate the value-based incentive payment amount for each SNF using 
the methodology described in paragraph (c)(2)(ii) of this section. CMS 
will then apply low-volume scoring adjustment described in paragraph 
(d)(3) of this section.
    (3) CMS will provide confidential feedback reports to SNFs on their 
performance on the SNF readmission measure in accordance with 
paragraphs (e)(1) and (2) of this section.
    (4) CMS will publicly report SNF performance on the SNF readmission 
measure in accordance with paragraph (e)(3) of this section.

PART 489--PROVIDER AGREEMENTS AND SUPPLIER APPROVAL

0
5. The authority citation for part 489 continues to read as follows:

    Authority: 42 U.S.C. 1302, 1395i-3, 1395x, 1395aa(m), 1395cc, 
1395ff, and 1395(hh).

0
6. Amend Sec.  489.20 by--
0
a. Revising paragraphs (s)(13) through (16);
0
b. Redesignating paragraph (s)(17) as paragraph (s)(18); and
0
c. Adding new paragraph (s)(17) to read as follows:


Sec.  489.20  Basis commitments.

* * * * *
    (s) * * *
    (13) Those chemotherapy items identified, as of July 1, 1999, by 
HCPCS codes J9000-J9020, J9040-J9151, J9170-J9185, J9200-J9201, J9206-
J9208, J9211, J9230-J9245, and J9265-J9600, and as of January 1, 2004, 
by HCPCS codes A9522, A9523, A9533, and A9534 (as subsequently modified 
by CMS), and any additional chemotherapy items identified by CMS.
    (14) Those chemotherapy administration services identified, as of 
July 1, 1999, by HCPCS codes 36260-36262, 36489, 36530-36535, 36640, 
36823, and 96405-96542 (as subsequently modified by CMS), and any 
additional chemotherapy administration services identified by CMS.
    (15) Those radioisotope services identified, as of July 1, 1999, by 
HCPCS codes 79030-79440 (as subsequently modified by CMS), and any 
additional radioisotope services identified by CMS.
    (16) Those customized prosthetic devices (including artificial 
limbs and their components) identified, as of July 1, 1999, by HCPCS 
codes L5050-L5340, L5500-L5611, L5613-L5986, L5988, L6050-L6370, L6400-
6880, L6920-L7274, and L7362-L7366 (as subsequently modified by CMS) 
and any additional customized prosthetic devices identified by CMS, 
which are delivered for a resident's use during a stay in the SNF and 
intended to be used by the resident after discharge from the SNF.
    (17) Those blood clotting factors indicated for the treatment of 
patients with hemophilia and other bleeding disorders identified, as of 
July 1, 2020, by HCPCS codes J7170, J7175, J7177-J7183, J7185-J7190, 
J7192-J7195, J7198-J7203, J7205, and J7207-J7211 (as subsequently 
modified by CMS) and items and services related to the furnishing of 
such factors, and any additional blood clotting factors identified by 
CMS and items and services related to the furnishing of such factors.
* * * * *

    Dated: March 29, 2021.
Elizabeth Richter,
Acting Administrator, Centers for Medicare & Medicaid Services.
    Dated: April 8, 2021.
Xavier Becerra,
Secretary, Department of Health and Human Services.
[FR Doc. 2021-07556 Filed 4-8-21; 4:15 pm]
BILLING CODE 4120-01-P