[Federal Register Volume 86, Number 147 (Wednesday, August 4, 2021)]
[Rules and Regulations]
[Pages 42608-42679]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2021-16336]
[[Page 42607]]
Vol. 86
Wednesday,
No. 147
August 4, 2021
Part VI
Department of Health and Human Services
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Centers for Medicare & Medicaid Services
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42 CFR Part 412
Medicare Program; FY 2022 Inpatient Psychiatric Facilities Prospective
Payment System and Quality Reporting Updates for Fiscal Year Beginning
October 1, 2021 (FY 2022); Final Rule
Federal Register / Vol. 86 , No. 147 / Wednesday, August 4, 2021 /
Rules and Regulations
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Medicare & Medicaid Services
42 CFR Part 412
[CMS-1750-F]
RIN 0938-AU40
Medicare Program; FY 2022 Inpatient Psychiatric Facilities
Prospective Payment System and Quality Reporting Updates for Fiscal
Year Beginning October 1, 2021 (FY 2022)
AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.
ACTION: Final rule.
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SUMMARY: This final rule updates the prospective payment rates, the
outlier threshold, and the wage index for Medicare inpatient hospital
services provided by Inpatient Psychiatric Facilities (IPF), which
include psychiatric hospitals and excluded psychiatric units of an
acute care hospital or critical access hospital. This rule also updates
and clarifies the IPF teaching policy with respect to IPF hospital
closures and displaced residents and finalizes a technical change to
one of the 2016-based IPF market basket price proxies. In addition,
this final rule finalizes proposals on quality measures and reporting
requirements under the Inpatient Psychiatric Facilities Quality
Reporting (IPFQR) Program. We note that this final rule does not
finalize two proposals to remove quality measures. The changes
finalized in this rule for the IPFQR Program are effective for IPF
discharges occurring during the Fiscal Year (FY) beginning October 1,
2021 through September 30, 2022 (FY 2022).
DATES: These regulations are effective on October 1, 2021.
FOR FURTHER INFORMATION CONTACT:
The IPF Payment Policy mailbox at [email protected] for
general information.
Mollie Knight (410) 786-7948 or Eric Laib (410) 786-9759, for
information regarding the market basket update or the labor related
share.
Nick Brock (410) 786-5148 or Theresa Bean (410) 786-2287, for
information regarding the regulatory impact analysis.
Lauren Lowenstein, (410) 786-4507, for information regarding the
inpatient psychiatric facilities quality reporting program.
SUPPLEMENTARY INFORMATION:
Availability of Certain Tables Exclusively Through the Internet on the
CMS Website
Addendum A to this final rule summarizes the FY 2022 IPF PPS
payment rates, outlier threshold, cost of living adjustment factors
(COLA) for Alaska and Hawaii, national and upper limit cost-to-charge
ratios, and adjustment factors. In addition, the B Addenda to this
final rule shows the complete listing of ICD-10 Clinical Modification
(CM) and Procedure Coding System (PCS) codes, the FY 2022 IPF PPS
comorbidity adjustment, and electroconvulsive therapy (ECT) procedure
codes. The A and B Addenda are available online at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
Tables setting forth the FY 2022 Wage Index for Urban Areas Based
on Core-Based Statistical Area (CBSA) Labor Market Areas and the FY
2022 Wage Index Based on CBSA Labor Market Areas for Rural Areas are
available exclusively through the internet, on the CMS website at
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/IPFPPS/WageIndex.html.
I. Executive Summary
A. Purpose
This final rule updates the prospective payment rates, the outlier
threshold, and the wage index for Medicare inpatient hospital services
provided by Inpatient Psychiatric Facilities (IPFs) for discharges
occurring during FY 2022 beginning October 1, 2021 through September
30, 2022. This rule also updates and clarifies the IPF teaching policy
with respect to IPF hospital closures and displaced residents and
finalizes a technical change to one of the 2016-based IPF market basket
price proxies. In addition, the final rule finalizes proposals to adopt
quality measures and reporting requirements under the Inpatient
Psychiatric Facilities Quality Reporting (IPFQR) Program.
B. Summary of the Major Provisions
1. Inpatient Psychiatric Facilities Prospective Payment System (IPF
PPS)
For the IPF PPS, we are finalizing our proposal to--
Update IPF PPS teaching policy with respect to IPF
hospital closures and displaced residents.
Replace one of the price proxies currently used for the
For-profit Interest cost category in the 2016-based IPF market basket
with a similar price proxy.
Adjust the 2016-based IPF market basket update (2.7
percent) for economy-wide productivity (0.7 percentage point) as
required by section 1886(s)(2)(A)(i) of the Social Security Act (the
Act), resulting in a final IPF payment rate update of 2.0 percent for
FY 2022.
Make technical rate setting changes: The IPF PPS payment
rates will be adjusted annually for inflation, as well as statutory and
other policy factors. This final rule updates:
++ The IPF PPS Federal per diem base rate from $815.22 to $832.94.
++ The IPF PPS Federal per diem base rate for providers who failed
to report quality data to $816.61.
++ The Electroconvulsive therapy (ECT) payment per treatment from
$350.97 to $358.60.
++ The ECT payment per treatment for providers who failed to report
quality data to $351.57.
++ The labor-related share from 77.3 percent to 77.2 percent.
++ The wage index budget-neutrality factor from 0.9989 to 1.0017.
++ The fixed dollar loss threshold amount from $14,630 to $14,470
to maintain estimated outlier payments at 2 percent of total estimated
aggregate IPF PPS payments.
2. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program
In this final rule, we are:
Adopting voluntary patient-level data reporting for chart-
abstracted measures for data submitted for the FY 2023 payment
determination and mandatory patient-level data reporting for chart-
abstracted measures for the FY 2024 payment determination and
subsequent years;
Revising our regulations at 42 CFR 412.434(b)(3) by
replacing the term ``QualityNet system administrator'' with
``QualityNet security official'';
Adopting the Coronavirus disease 2019 (COVID-19)
Vaccination Coverage Among Health Care Personnel (HCP) measure for the
FY 2023 payment determination and subsequent years;
Adopting the Follow-up After Psychiatric Hospitalization
(FAPH) measure for the FY 2024 payment determination and subsequent
years; and
Removing the following two measures for FY 2024 payment
determination and subsequent years:
++ Timely Transmission of Transition Record (Discharges from an
Inpatient Facility to Home/Self Care or Any Other Site of Care) measure
and
++ Follow-up After Hospitalization for Mental Illness (FUH)
measure.
Not finalizing our proposals to remove the following two
measures for
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FY 2024 payment determination and subsequent years:
++ Alcohol Use Brief Intervention Provided or Offered and Alcohol
Use Brief Intervention Provided (SUB-2/2a) measure; and
++ Tobacco Use Treatment Provided or Offered and Tobacco Use
Treatment (TOB-2/2a) measure.
C. Summary of Impacts
[GRAPHIC] [TIFF OMITTED] TR04AU21.169
II. Background
A. Overview of the Legislative Requirements of the IPF PPS
Section 124 of the Medicare, Medicaid, and State Children's Health
Insurance Program Balanced Budget Refinement Act of 1999 (BBRA) (Pub.
L. 106-113) required the establishment and implementation of an IPF
PPS. Specifically, section 124 of the BBRA mandated that the Secretary
of the Department of Health and Human Services (the Secretary) develop
a per diem Prospective Payment System (PPS) for inpatient hospital
services furnished in psychiatric hospitals and excluded psychiatric
units including an adequate patient classification system that reflects
the differences in patient resource use and costs among psychiatric
hospitals and excluded psychiatric units. ``Excluded psychiatric unit''
means a psychiatric unit of an acute care hospital or of a Critical
Access Hospital (CAH), which is excluded from payment under the
Inpatient Prospective Payment System (IPPS) or CAH payment system,
respectively. These excluded psychiatric units will be paid under the
IPF PPS.
Section 405(g)(2) of the Medicare Prescription Drug, Improvement,
and Modernization Act of 2003 (MMA) (Pub. L. 108-173) extended the IPF
PPS to psychiatric distinct part units of CAHs.
Sections 3401(f) and 10322 of the Patient Protection and Affordable
Care Act (Pub. L. 111-148) as amended by section 10319(e) of that Act
and by section 1105(d) of the Health Care and Education Reconciliation
Act of 2010 (Pub. L. 111-152) (hereafter referred to jointly as ``the
Affordable Care Act'') added subsection (s) to section 1886 of the Act.
Section 1886(s)(1) of the Act titled ``Reference to Establishment
and Implementation of System,'' refers to section 124 of the BBRA,
which relates to the establishment of the IPF PPS.
Section 1886(s)(2)(A)(i) of the Act requires the application of the
productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of
the Act to the IPF PPS for the rate year (RY) beginning in 2012 (that
is, a RY that coincides with a FY) and each subsequent RY.
Section 1886(s)(2)(A)(ii) of the Act required the application of an
``other adjustment'' that reduced any update to an IPF PPS base rate by
a percentage point amount specified in section 1886(s)(3) of the Act
for the RY beginning in 2010 through the RY beginning in 2019. As noted
in the FY 2020 IPF PPS final rule, for the RY beginning in 2019,
section 1886(s)(3)(E) of the Act required that the other adjustment
reduction be equal to 0.75 percentage point; this was the final year
the statute required the application of this adjustment. Because FY
2021, was a RY beginning in 2020, FY 2021 was the first-year section
1886(s)(2)(A)(ii) did not apply since its enactment.
Sections 1886(s)(4)(A) through (D) of the Act require that for RY
2014 and each subsequent RY, IPFs that fail to report required quality
data with respect to such a RY will have their annual update to a
standard Federal rate for discharges reduced by 2.0 percentage points.
This may result in an annual update being less than 0.0 for a RY, and
may result in payment rates for the upcoming RY being less than such
payment rates for the preceding RY. Any reduction for failure to report
required quality data will apply only to the RY involved, and the
Secretary will not take into account such reduction in computing the
payment amount for a subsequent RY. More information about the
specifics of the current Inpatient Psychiatric Facilities Quality
Reporting (IPFQR) Program is available in the FY 2020 IPF PPS and
Quality Reporting Updates for Fiscal Year Beginning October 1, 2019
final rule (84 FR 38459 through 38468).
To implement and periodically update these provisions, we have
published various proposed and final rules and notices in the Federal
Register. For more information regarding these documents, see the
Center for Medicare & Medicaid (CMS) website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/index.html?redirect=/InpatientPsychFacilPPS/.
B. Overview of the IPF PPS
The November 2004 IPF PPS final rule (69 FR 66922) established the
IPF PPS, as required by section 124 of the BBRA and codified at 42 CFR
part 412, subpart N. The November 2004 IPF PPS final rule set forth the
Federal per diem base rate for the implementation year (the 18-month
period from January 1, 2005 through June 30, 2006), and provided
payment for the inpatient operating and capital costs to IPFs for
covered psychiatric services they furnish (that is, routine, ancillary,
and capital costs, but not costs of approved educational activities,
bad debts, and
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other services or items that are outside the scope of the IPF PPS).
Covered psychiatric services include services for which benefits are
provided under the fee-for-service Part A (Hospital Insurance Program)
of the Medicare program.
The IPF PPS established the Federal per diem base rate for each
patient day in an IPF derived from the national average daily routine
operating, ancillary, and capital costs in IPFs in FY 2002. The average
per diem cost was updated to the midpoint of the first year under the
IPF PPS, standardized to account for the overall positive effects of
the IPF PPS payment adjustments, and adjusted for budget-neutrality.
The Federal per diem payment under the IPF PPS is comprised of the
Federal per diem base rate described previously and certain patient-
and facility-level payment adjustments for characteristics that were
found in the regression analysis to be associated with statistically
significant per diem cost differences with statistical significance
defined as p less than 0.05. A complete discussion of the regression
analysis that established the IPF PPS adjustment factors can be found
in the November 2004 IPF PPS final rule (69 FR 66933 through 66936).
The patient-level adjustments include age, Diagnosis-Related Group
(DRG) assignment, and comorbidities; additionally, there are
adjustments to reflect higher per diem costs at the beginning of a
patient's IPF stay and lower costs for later days of the stay.
Facility-level adjustments include adjustments for the IPF's wage
index, rural location, teaching status, a cost-of-living adjustment for
IPFs located in Alaska and Hawaii, and an adjustment for the presence
of a qualifying emergency department (ED).
The IPF PPS provides additional payment policies for outlier cases,
interrupted stays, and a per treatment payment for patients who undergo
electroconvulsive therapy (ECT). During the IPF PPS mandatory 3-year
transition period, stop-loss payments were also provided; however,
since the transition ended as of January 1, 2008, these payments are no
longer available.
C. Annual Requirements for Updating the IPF PPS
Section 124 of the BBRA did not specify an annual rate update
strategy for the IPF PPS and was broadly written to give the Secretary
discretion in establishing an update methodology. Therefore, in the
November 2004 IPF PPS final rule, we implemented the IPF PPS using the
following update strategy:
Calculate the final Federal per diem base rate to be
budget-neutral for the 18-month period of January 1, 2005 through June
30, 2006.
Use a July 1 through June 30 annual update cycle.
Allow the IPF PPS first update to be effective for
discharges on or after July 1, 2006 through June 30, 2007.
In November 2004, we implemented the IPF PPS in a final rule that
published on November 15, 2004 in the Federal Register (69 FR 66922).
In developing the IPF PPS, and to ensure that the IPF PPS can account
adequately for each IPF's case-mix, we performed an extensive
regression analysis of the relationship between the per diem costs and
certain patient and facility characteristics to determine those
characteristics associated with statistically significant cost
differences on a per diem basis. That regression analysis is described
in detail in our November 28, 2003 IPF proposed rule (68 FR 66923;
66928 through 66933) and our November 15, 2004 IPF final rule (69 FR
66933 through 66960). For characteristics with statistically
significant cost differences, we used the regression coefficients of
those variables to determine the size of the corresponding payment
adjustments.
In the November 15, 2004 final rule, we explained the reasons for
delaying an update to the adjustment factors, derived from the
regression analysis, including waiting until we have IPF PPS data that
yields as much information as possible regarding the patient-level
characteristics of the population that each IPF serves. We indicated
that we did not intend to update the regression analysis and the
patient-level and facility-level adjustments until we complete that
analysis. Until that analysis is complete, we stated our intention to
publish a notice in the Federal Register each spring to update the IPF
PPS (69 FR 66966).
On May 6, 2011, we published a final rule in the Federal Register
titled, ``Inpatient Psychiatric Facilities Prospective Payment System--
Update for Rate Year Beginning July 1, 2011 (RY 2012)'' (76 FR 26432),
which changed the payment rate update period to a RY that coincides
with a FY update. Therefore, final rules are now published in the
Federal Register in the summer to be effective on October 1. When
proposing changes in IPF payment policy, a proposed rule would be
issued in the spring, and the final rule in the summer to be effective
on October 1. For a detailed list of updates to the IPF PPS, we refer
readers to our regulations at 42 CFR 412.428.
The most recent IPF PPS annual update was published in a final rule
on August 4, 2020 in the Federal Register titled, ``Medicare Program;
FY 2021 Inpatient Psychiatric Facilities Prospective Payment System and
Special Requirements for Psychiatric Hospitals for Fiscal Year
Beginning October 1, 2020 (FY 2021)'' (85 FR 47042), which updated the
IPF PPS payment rates for FY 2021. That final rule updated the IPF PPS
Federal per diem base rates that were published in the FY 2020 IPF PPS
Rate Update final rule (84 FR 38424) in accordance with our established
policies.
III. Provisions of the FY 2022 IPF PPS Final Rule and Responses to
Comments
A. Final Update to the FY 2021 Market Basket for the IPF PPS
1. Background
Originally, the input price index that was used to develop the IPF
PPS was the ``Excluded Hospital with Capital'' market basket. This
market basket was based on 1997 Medicare cost reports for Medicare
participating inpatient rehabilitation facilities (IRFs), IPFs, long-
term care hospitals (LTCHs), cancer hospitals, and children's
hospitals. Although ``market basket'' technically describes the mix of
goods and services used in providing health care at a given point in
time, this term is also commonly used to denote the input price index
(that is, cost category weights and price proxies) derived from that
market basket. Accordingly, the term market basket as used in this
document, refers to an input price index.
Since the IPF PPS inception, the market basket used to update IPF
PPS payments has been rebased and revised to reflect more recent data
on IPF cost structures. We last rebased and revised the IPF market
basket in the FY 2020 IPF PPS rule, where we adopted a 2016-based IPF
market basket, using Medicare cost report data for both Medicare
participating freestanding psychiatric hospitals and psychiatric units.
We refer readers to the FY 2020 IPF PPS final rule for a detailed
discussion of the 2016-based IPF PPS market basket and its development
(84 FR 38426 through 38447). References to the historical market
baskets used to update IPF PPS payments are listed in the FY 2016 IPF
PPS final rule (80 FR 46656).
2. Final FY 2022 IPF Market Basket Update
For FY 2022 (that is, beginning October 1, 2021 and ending
September 30, 2022), we proposed to update the IPF PPS payments by a
market basket
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increase factor with a productivity adjustment as required by section
1886(s)(2)(A)(i) of the Act. In the FY 2022 IPF proposed rule (86 FR
19483), we proposed to use the same methodology described in the FY
2021 IPF PPS final rule (85 FR 47045 through 47046), with one proposed
modification to the 2016-based IPF market basket.
For the price proxy for the For-profit Interest cost category of
the 2016-based IPF market basket, we proposed to use the iBoxx AAA
Corporate Bond Yield index instead of the Moody's AAA Corporate Bond
Yield index. Effective for December 2020, the Moody's AAA Corporate
Bond series is no longer available for use under license to IHS Global
Inc. (IGI), the nationally recognized economic and financial
forecasting firm with which we contract to forecast the components of
the market baskets and multi-factor productivity (MFP). Since IGI is no
longer licensed to use and publish the Moody's series, IGI was required
to discontinue the publication of the associated historical data and
forecasts of this series. Therefore, IGI constructed a bond yield index
(iBoxx) that closely replicates the Moody's corporate bond yield
indices currently used in the market baskets.
In the FY 2022 IPF PPS proposed rule, we stated that because the
iBoxx AAA Corporate Bond Yield index captures the same technical
concept as the current corporate bond proxy and tracks similarly to the
current measure that is no longer available, we believed that the iBoxx
AAA Corporate Bond Yield index is technically appropriate to use in the
2016-based IPF market basket.
Based on IGI's fourth quarter 2020 forecast with historical data
through the third quarter of 2020, the proposed 2016-based IPF market
basket increase factor for FY 2022 was projected to be 2.3 percent. We
also proposed that if more recent data became available after the
publication of the proposed rule and before the publication of this
final rule (for example, a more recent estimate of the market basket
update or MFP), we would use such data, if appropriate, to determine
the FY 2022 market basket update in this final rule.
Section 1886(s)(2)(A)(i) of the Act requires that, after
establishing the increase factor for a FY, the Secretary shall reduce
such increase factor for FY 2012 and each subsequent FY, by the
productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of
the Act. Section 1886(b)(3)(B)(xi)(II) of the Act sets forth the
definition of this productivity adjustment. The statute defines the
productivity adjustment to be equal to the 10-year moving average of
changes in annual economy-wide, private nonfarm business MFP (as
projected by the Secretary for the 10-year period ending with the
applicable FY, year, cost reporting period, or other annual period)
(the ``productivity adjustment''). The U.S. Department of Labor's
Bureau of Labor Statistics (BLS) publishes the official measure of
private nonfarm business MFP. Please see http://www.bls.gov/mfp for the
BLS historical published MFP data. A complete description of the MFP
projection methodology is available on the CMS website at https://www.cms.gov/Research-Statistics-Dataand-Systems/Statistics-Trends-andReports/MedicareProgramRatesStats/MarketBasketResearch.html. We note
that effective with FY 2022 and forward, CMS is changing the name of
this adjustment to refer to it as the productivity adjustment rather
than the MFP adjustment. We note that the adjustment relies on the same
underlying data and methodology. This new terminology is more
consistent with the statutory language described in section
1886(s)(2)(A)(i) of the Act.
Using IGI's fourth quarter 2020 forecast, the productivity
adjustment for FY 2022 was projected to be 0.2 percent. We proposed to
then reduce the proposed 2.3 percent IPF market basket update by the
estimated productivity adjustment for FY 2022 of 0.2 percentage point.
Therefore, the proposed FY 2022 IPF update was equal to 2.1 percent
(2.3 percent market basket update reduced by the 0.2 percentage point
productivity adjustment). Furthermore, we proposed that if more recent
data became available after the publication of the proposed rule and
before the publication of this final rule (for example, a more recent
estimate of the market basket or MFP), we would use such data, if
appropriate, to determine the FY 2022 market basket update and
productivity adjustment in this final rule.
Based on the more recent data available for this FY 2022 IPF final
rule (that is, IGI's second quarter 2021 forecast of the 2016-based IPF
market basket with historical data through the first quarter of 2021),
we estimate that the IPF FY 2022 market basket update is 2.7 percent.
The current estimate of the productivity adjustment for FY 2022 is 0.7
percentage point. Therefore, the current estimate of the FY 2022 IPF
increase factor is equal to 2.0 percent (2.7 percent market basket
update reduced by 0.7 percentage point productivity adjustment).
We invited public comment on our proposals for the FY 2022 market
basket update and productivity adjustment. The following is a summary
of the public comments received on the proposed FY 2022 market basket
update and productivity adjustment and our responses:
Comment: One commenter supported the update to the IPF payment
rates of 2.1 percent.
Response: We thank the commenter for their support.
Comment: One commenter stated that given the growing behavioral
health and substance abuse crisis made worse by the COVID-19 Public
Health Emergency (PHE), that CMS should provide additional payment for
IPFs in the future.
Response: We understand the commenter's concern. We acknowledge
that the COVID-19 PHE has amplified the growing need for behavioral
health services in this country and remain committed to trying to find
ways to mitigate its impact on IPFs. Our goal is to ensure that the IPF
payment rates accurately reflect the best available data. For example,
as discussed in section VI.C.3 of this final rule, in comparing and
analyzing FY 2019 and FY 2020 claims, we determined that the COVID-19
PHE appears to have significantly impacted the FY 2020 IPF claims such
that the FY 2019 claims are the best available data to set the outlier
fixed dollar loss threshold for FY 2022. Therefore, we deviated from
our longstanding practice of using the most recent available year of
claims, that is, FY 2020 claims, for estimating IPF PPS payments in FY
2022. We will continue to analyze more recent available IPF claims data
to better understand both the short- and long-term effects of the
COVID-19 PHE on the IPF PPS.
Final Decision: After consideration of the comments we received, we
are finalizing a FY 2022 IPF update equal to 2.0 percent based on the
more recent data available.
3. Final FY 2022 IPF Labor-Related Share
Due to variations in geographic wage levels and other labor-related
costs, we believe that payment rates under the IPF PPS should continue
to be adjusted by a geographic wage index, which would apply to the
labor-related portion of the Federal per diem base rate (hereafter
referred to as the labor-related share). The labor-related share is
determined by identifying the national average proportion of total
costs that are related to, influenced by, or vary with the local labor
market. We proposed to continue to classify a cost category as labor-
related if the costs are labor-intensive and vary with the local labor
market.
[[Page 42612]]
Based on our definition of the labor-related share and the cost
categories in the 2016-based IPF market basket, we proposed to
calculate the labor-related share for FY 2022 as the sum of the FY 2022
relative importance of Wages and Salaries; Employee Benefits;
Professional Fees: Labor-related; Administrative and Facilities Support
Services; Installation, Maintenance, and Repair Services; All Other:
Labor-related Services; and a portion of the Capital-Related relative
importance from the 2016-based IPF market basket. For more details
regarding the methodology for determining specific cost categories for
inclusion in the 2016-based IPF labor-related share, see the FY 2020
IPF PPS final rule (84 FR 38445 through 38447).
The relative importance reflects the different rates of price
change for these cost categories between the base year (FY 2016) and FY
2022. Based on IGI's fourth quarter 2020 forecast of the 2016-based IPF
market basket, the sum of the FY 2022 relative importance for Wages and
Salaries; Employee Benefits; Professional Fees: Labor-related;
Administrative and Facilities Support Services; Installation
Maintenance & Repair Services; and All Other: Labor related Services
was 74.0 percent. We proposed that the portion of Capital-Related costs
that are influenced by the local labor market is 46 percent. Since the
relative importance for Capital- Related costs was 6.7 percent of the
2016-based IPF market basket for FY 2022, we proposed to take 46
percent of 6.7 percent to determine the labor-related share of Capital-
Related costs for FY 2022 of 3.1 percent. Therefore, we proposed a
total labor-related share for FY 2022 of 77.1 percent (the sum of 74.0
percent for the labor-related share of operating costs and 3.1 percent
for the labor-related share of Capital-Related costs). We also proposed
that if more recent data became available after publication of the
proposed rule and before the publication of this final rule (for
example, a more recent estimate of the labor-related share), we would
use such data, if appropriate, to determine the FY 2022 IPF labor-
related share in the final rule.
Based on IGI's second quarter 2021 forecast of the 2016-based IPF
market basket, the sum of the FY 2022 relative importance for Wages and
Salaries; Employee Benefits; Professional Fees: Labor-related;
Administrative and Facilities Support Services; Installation
Maintenance & Repair Services; and All Other: Labor-related Services is
74.1 percent. Since the relative importance for Capital-Related costs
is 6.7 percent of the 2016-based IPF market basket for FY 2022, we take
46 percent of 6.7 percent to determine the labor-related share of
Capital-Related costs for FY 2022 of 3.1 percent. Therefore, the
current estimate of the total labor-related share for FY 2022 is equal
to 77.2 percent (the sum of 74.1 percent for the labor-related share of
operating costs and 3.1 percent for the labor-related share of Capital-
Related costs). Table 1 shows the final FY 2022 labor-related share and
the final FY 2021 labor-related share using the 2016-based IPF market
basket relative importance.
[GRAPHIC] [TIFF OMITTED] TR04AU21.170
We invited public comments on the proposed labor-related share for
FY 2022.
Comment: Several commenters supported the decrease in the labor-
related share from 77.3 percent in FY 2021 to 77.1 percent in FY 2022
noting that it will help any facility that has a wage index less than
1.0. The commenters stated that, across this country there is a growing
disparity between high-wage and low-wage states. Recognizing this
disparity and slightly lowering the labor-related share provides some
aid to hospitals in many rural and underserved communities.
Response: We thank the commenter for their support. We agree with
the commenters that the labor-related share should reflect the
proportion of costs that are attributable to labor and vary
geographically to account for differences in labor-related costs across
geographic areas. More recent data became available; therefore, based
on IGI's second quarter 2021 forecast with historical data through the
first quarter 2021 the FY 2022 labor-related share for the final rule
is 77.2 percent as shown in Table 1.
After consideration of comments received, we are finalizing the use
of the sum of the FY 2022 relative importance
[[Page 42613]]
for the labor-related cost categories based on the most recent forecast
(IGI's second quarter 2021 forecast) of the 2016-based IPF market
basket labor-related share cost weights, as proposed.
B. Final Updates to the IPF PPS Rates for FY Beginning October 1, 2021
The IPF PPS is based on a standardized Federal per diem base rate
calculated from the IPF average per diem costs and adjusted for budget-
neutrality in the implementation year. The Federal per diem base rate
is used as the standard payment per day under the IPF PPS and is
adjusted by the patient-level and facility-level adjustments that are
applicable to the IPF stay. A detailed explanation of how we calculated
the average per diem cost appears in the November 2004 IPF PPS final
rule (69 FR 66926).
1. Determining the Standardized Budget-Neutral Federal per Diem Base
Rate
Section 124(a)(1) of the BBRA required that we implement the IPF
PPS in a budget-neutral manner. In other words, the amount of total
payments under the IPF PPS, including any payment adjustments, must be
projected to be equal to the amount of total payments that would have
been made if the IPF PPS were not implemented. Therefore, we calculated
the budget-neutrality factor by setting the total estimated IPF PPS
payments to be equal to the total estimated payments that would have
been made under the Tax Equity and Fiscal Responsibility Act of 1982
(TEFRA) (Pub. L. 97-248) methodology had the IPF PPS not been
implemented. A step-by-step description of the methodology used to
estimate payments under the TEFRA payment system appears in the
November 2004 IPF PPS final rule (69 FR 66926).
Under the IPF PPS methodology, we calculated the final Federal per
diem base rate to be budget-neutral during the IPF PPS implementation
period (that is, the 18-month period from January 1, 2005 through June
30, 2006) using a July 1 update cycle. We updated the average cost per
day to the midpoint of the IPF PPS implementation period (October 1,
2005), and this amount was used in the payment model to establish the
budget-neutrality adjustment.
Next, we standardized the IPF PPS Federal per diem base rate to
account for the overall positive effects of the IPF PPS payment
adjustment factors by dividing total estimated payments under the TEFRA
payment system by estimated payments under the IPF PPS. In addition,
information concerning this standardization can be found in the
November 2004 IPF PPS final rule (69 FR 66932) and the RY 2006 IPF PPS
final rule (71 FR 27045). We then reduced the standardized Federal per
diem base rate to account for the outlier policy, the stop loss
provision, and anticipated behavioral changes. A complete discussion of
how we calculated each component of the budget-neutrality adjustment
appears in the November 2004 IPF PPS final rule (69 FR 66932 through
66933) and in the RY 2007 IPF PPS final rule (71 FR 27044 through
27046). The final standardized budget-neutral Federal per diem base
rate established for cost reporting periods beginning on or after
January 1, 2005 was calculated to be $575.95.
The Federal per diem base rate has been updated in accordance with
applicable statutory requirements and Sec. 412.428 through publication
of annual notices or proposed and final rules. A detailed discussion on
the standardized budget-neutral Federal per diem base rate and the
electroconvulsive therapy (ECT) payment per treatment appears in the FY
2014 IPF PPS update notice (78 FR 46738 through 46740). These documents
are available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/index.html.
IPFs must include a valid procedure code for ECT services provided
to IPF beneficiaries in order to bill for ECT services, as described in
our Medicare Claims Processing Manual, Chapter 3, Section 190.7.3
(available at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c03.pdf.) There were no changes to the ECT
procedure codes used on IPF claims as a result of the final update to
the ICD-10-PCS code set for FY 2022. Addendum B to this final rule
shows the ECT procedure codes for FY 2022 and is available on our
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
2. Final Update of the Federal Per Diem Base Rate and Electroconvulsive
Therapy Payment per Treatment
The current (FY 2021) Federal per diem base rate is $815.22 and the
ECT payment per treatment is $350.97. For the final FY 2022 Federal per
diem base rate, we applied the payment rate update of 2.0 percent--that
is, the 2016-based IPF market basket increase for FY 2022 of 2.7
percent less the productivity adjustment of 0.7 percentage point--and
the wage index budget-neutrality factor of 1.0017 (as discussed in
section III.D.1 of this final rule) to the FY 2021 Federal per diem
base rate of $815.22, yielding a final Federal per diem base rate of
$832.94 for FY 2022. Similarly, we applied the 2.0 percent payment rate
update and the 1.0017 wage index budget-neutrality factor to the FY
2021 ECT payment per treatment of $350.97, yielding a final ECT payment
per treatment of $358.60 for FY 2022.
Section 1886(s)(4)(A)(i) of the Act requires that for RY 2014 and
each subsequent RY, in the case of an IPF that fails to report required
quality data with respect to such RY, the Secretary will reduce any
annual update to a standard Federal rate for discharges during the RY
by 2.0 percentage points. Therefore, we are applying a 2.0 percentage
point reduction to the Federal per diem base rate and the ECT payment
per treatment as follows:
For IPFs that fail requirements under the IPFQR Program,
we applied a 0.0 percent payment rate update--that is, the IPF market
basket increase for FY 2022 of 2.7 percent less the productivity
adjustment of 0.7 percentage point for an update of 2.0 percent, and
further reduced by 2 percentage points in accordance with section
1886(s)(4)(A)(i) of the Act--and the wage index budget-neutrality
factor of 1.0017 to the FY 2021 Federal per diem base rate of $815.22,
yielding a Federal per diem base rate of $816.61 for FY 2022.
For IPFs that fail to meet requirements under the IPFQR
Program, we applied the 0.0 percent annual payment rate update and the
1.0017 wage index budget-neutrality factor to the FY 2021 ECT payment
per treatment of $350.97, yielding an ECT payment per treatment of
$351.57 for FY 2022.
C. Final Updates to the IPF PPS Patient-Level Adjustment Factors
1. Overview of the IPF PPS Adjustment Factors
The IPF PPS payment adjustments were derived from a regression
analysis of 100 percent of the FY 2002 Medicare Provider and Analysis
Review (MedPAR) data file, which contained 483,038 cases. For a more
detailed description of the data file used for the regression analysis,
see the November 2004 IPF PPS final rule (69 FR 66935 through 66936).
We are finalizing our proposal to continue to use the existing
regression-derived adjustment factors established in 2005 for FY 2022.
However, we have used more recent claims data to simulate payments to
finalize the outlier fixed dollar loss threshold amount and to assess
the impact of the IPF PPS updates.
[[Page 42614]]
2. IPF PPS Patient-Level Adjustments
The IPF PPS includes payment adjustments for the following patient-
level characteristics: Medicare Severity Diagnosis Related Groups (MS-
DRGs) assignment of the patient's principal diagnosis, selected
comorbidities, patient age, and the variable per diem adjustments.
a. Final Update to MS-DRG Assignment
We believe it is important to maintain for IPFs the same diagnostic
coding and Diagnosis Related Group (DRG) classification used under the
IPPS for providing psychiatric care. For this reason, when the IPF PPS
was implemented for cost reporting periods beginning on or after
January 1, 2005, we adopted the same diagnostic code set (ICD-9-CM) and
DRG patient classification system (MS-DRGs) that were utilized at the
time under the IPPS. In the RY 2009 IPF PPS notice (73 FR 25709), we
discussed CMS' effort to better recognize resource use and the severity
of illness among patients. CMS adopted the new MS-DRGs for the IPPS in
the FY 2008 IPPS final rule with comment period (72 FR 47130). In the
RY 2009 IPF PPS notice (73 FR 25716), we provided a crosswalk to
reflect changes that were made under the IPF PPS to adopt the new MS-
DRGs. For a detailed description of the mapping changes from the
original DRG adjustment categories to the current MS-DRG adjustment
categories, we refer readers to the RY 2009 IPF PPS notice (73 FR
25714).
The IPF PPS includes payment adjustments for designated psychiatric
DRGs assigned to the claim based on the patient's principal diagnosis.
The DRG adjustment factors were expressed relative to the most
frequently reported psychiatric DRG in FY 2002, that is, DRG 430
(psychoses). The coefficient values and adjustment factors were derived
from the regression analysis discussed in detail in the November 28,
2003 IPF proposed rule (68 FR 66923; 66928 through 66933) and the
November 15, 2004 IPF final rule (69 FR 66933 through 66960). Mapping
the DRGs to the MS-DRGs resulted in the current 17 IPF MS-DRGs, instead
of the original 15 DRGs, for which the IPF PPS provides an adjustment.
For FY 2022, we did not propose any changes to the IPF MSDRG adjustment
factors. Therefore, we are finalizing our proposal to maintain the
existing IPF MS-DRG adjustment factors.
In the FY 2015 IPF PPS final rule published August 6, 2014 in the
Federal Register titled, ``Inpatient Psychiatric Facilities Prospective
Payment System--Update for FY Beginning October 1, 2014 (FY 2015)'' (79
FR 45945 through 45947), we finalized conversions of the ICD-9-CM-based
MS-DRGs to ICD-10-CM/PCS-based MS-DRGs, which were implemented on
October 1, 2015. Further information on the ICD-10-CM/PCS MS-DRG
conversion project can be found on the CMS ICD-10-CM website at https://www.cms.gov/Medicare/Coding/ICD10/ICD-10-MS-DRG-Conversion-Project.html.
For FY 2022, we are finalizing our proposal to continue to make the
existing payment adjustment for psychiatric diagnoses that group to one
of the existing 17 IPF MS-DRGs listed in Addendum A. Addendum A is
available on our website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html. Psychiatric
principal diagnoses that do not group to one of the 17 designated MS-
DRGs will still receive the Federal per diem base rate and all other
applicable adjustments, but the payment will not include an MS-DRG
adjustment.
The diagnoses for each IPF MS-DRG will be updated as of October 1,
2021, using the final IPPS FY 2022 ICD-10-CM/PCS code sets. The FY 2022
IPPS/LTCH PPS final rule includes tables of the changes to the ICD-10-
CM/PCS code sets, which underlie the FY 2022 IPF MS-DRGs. Both the FY
2022 IPPS final rule and the tables of final changes to the ICD-10-CM/
PCS code sets, which underlie the FY 2022 MS-DRGs, are available on the
CMS IPPS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.
Code First
As discussed in the ICD-10-CM Official Guidelines for Coding and
Reporting, certain conditions have both an underlying etiology and
multiple body system manifestations due to the underlying etiology. For
such conditions, the ICD-10-CM has a coding convention that requires
the underlying condition be sequenced first followed by the
manifestation. Wherever such a combination exists, there is a ``use
additional code'' note at the etiology code, and a ``code first'' note
at the manifestation code. These instructional notes indicate the
proper sequencing order of the codes (etiology followed by
manifestation). In accordance with the ICD-10-CM Official Guidelines
for Coding and Reporting, when a primary (psychiatric) diagnosis code
has a ``code first'' note, the provider will follow the instructions in
the ICD-10-CM Tabular List. The submitted claim goes through the CMS
processing system, which will identify the principal diagnosis code as
non-psychiatric and search the secondary codes for a psychiatric code
to assign a DRG code for adjustment. The system will continue to search
the secondary codes for those that are appropriate for comorbidity
adjustment.
For more information on the code first policy, we refer our readers
to the November 2004 IPF PPS final rule (69 FR 66945) and see sections
I.A.13 and I.B.7 of the FY 2020 ICD-10-CM Coding Guidelines, available
at https://www.cdc.gov/nchs/data/icd/10cmguidelines-FY2020_final.pdf.
In the FY 2015 IPF PPS final rule, we provided a code first table for
reference that highlights the same or similar manifestation codes where
the code first instructions apply in ICD-10-CM that were present in
ICD-9-CM (79 FR 46009). In FY 2018, FY 2019 and FY 2020, there were no
changes to the final ICD-10-CM codes in the IPF Code First table. For
FY 2021, there were 18 ICD-10-CM codes deleted from the final IPF Code
First table. For FY 2022 there are 18 codes finalized for deletion from
the ICD-10-CM codes in the IPF Code First table. The final FY 2022 Code
First table is shown in Addendum B on our website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
b. Final Payment for Comorbid Conditions
The intent of the comorbidity adjustments is to recognize the
increased costs associated with comorbid conditions by providing
additional payments for certain existing medical or psychiatric
conditions that are expensive to treat. In our RY 2012 IPF PPS final
rule (76 FR 26451 through 26452), we explained that the IPF PPS
includes 17 comorbidity categories and identified the new, revised, and
deleted ICD-9-CM diagnosis codes that generate a comorbid condition
payment adjustment under the IPF PPS for RY 2012 (76 FR 26451).
Comorbidities are specific patient conditions that are secondary to
the patient's principal diagnosis and that require treatment during the
stay. Diagnoses that relate to an earlier episode of care and have no
bearing on the current hospital stay are excluded and must not be
reported on IPF claims. Comorbid conditions must exist at the time of
admission or develop subsequently, and affect the treatment received,
length of stay (LOS), or both treatment and LOS.
[[Page 42615]]
For each claim, an IPF may receive only one comorbidity adjustment
within a comorbidity category, but it may receive an adjustment for
more than one comorbidity category. Current billing instructions for
discharge claims, on or after October 1, 2015, require IPFs to enter
the complete ICD-10-CM codes for up to 24 additional diagnoses if they
co-exist at the time of admission, or develop subsequently and impact
the treatment provided.
The comorbidity adjustments were determined based on the regression
analysis using the diagnoses reported by IPFs in FY 2002. The principal
diagnoses were used to establish the DRG adjustments and were not
accounted for in establishing the comorbidity category adjustments,
except where ICD-9-CM code first instructions applied. In a code first
situation, the submitted claim goes through the CMS processing system,
which will identify the principal diagnosis code as non-psychiatric and
search the secondary codes for a psychiatric code to assign an MS-DRG
code for adjustment. The system will continue to search the secondary
codes for those that are appropriate for comorbidity adjustment.
As noted previously, it is our policy to maintain the same
diagnostic coding set for IPFs that is used under the IPPS for
providing the same psychiatric care. The 17 comorbidity categories
formerly defined using ICD-9-CM codes were converted to ICD-10-CM/PCS
in our FY 2015 IPF PPS final rule (79 FR 45947 through 45955). The goal
for converting the comorbidity categories is referred to as
replication, meaning that the payment adjustment for a given patient
encounter is the same after ICD-10-CM implementation as it will be if
the same record had been coded in ICD-9-CM and submitted prior to ICD-
10-CM/PCS implementation on October 1, 2015. All conversion efforts
were made with the intent of achieving this goal. For FY 2022, we are
finalizing our proposal to continue to use the same comorbidity
adjustment factors in effect in FY 2021, which are found in Addendum A,
available on our website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
We have updated the ICD-10-CM/PCS codes, which are associated with
the existing IPF PPS comorbidity categories, based upon the final FY
2022 update to the ICD-10-CM/PCS code set. The final FY 2022 ICD-10-CM/
PCS updates include: 8 ICD-10-CM diagnosis codes added to the Poisoning
comorbidity category, 4 codes deleted, and 4 changes to Poisoning
comorbidity long descriptions; 2 ICD-10-CM diagnosis codes added to the
Developmental Disabilities comorbidity category and 1 code deleted; and
3 ICD-10-PCS codes added to the Oncology Procedures comorbidity
category. These updates are detailed in Addenda B of this final rule,
which are available on our website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
In accordance with the policy established in the FY 2015 IPF PPS
final rule (79 FR 45949 through 45952), we reviewed all new FY 2022
ICD-10-CM codes to remove codes that were site ``unspecified'' in terms
of laterality from the FY 2022 ICD-10-CM/PCS codes in instances where
more specific codes are available. As we stated in the FY 2015 IPF PPS
final rule, we believe that specific diagnosis codes that narrowly
identify anatomical sites where disease, injury, or a condition exists
should be used when coding patients' diagnoses whenever these codes are
available. We finalized in the FY 2015 IPF PPS rule, that we would
remove site ``unspecified'' codes from the IPF PPS ICD-10-CM/PCS codes
in instances when laterality codes (site specified codes) are
available, as the clinician should be able to identify a more specific
diagnosis based on clinical assessment at the medical encounter. None
of the finalized additions to the FY 2022 ICD-10-CM/PCS codes were site
``unspecified'' by laterality, therefore, we are not removing any of
the new codes.
Comment: A commenter requested that CMS add 13 ICD-10-CM codes for
infectious diseases to the list of codes that qualify for the IPF PPS
comorbidity adjustment.
Response: As noted previously, the intent of the comorbidity
adjustments is to recognize the increased costs associated with
comorbid conditions by providing additional payments for certain
existing medical or psychiatric conditions that are expensive to treat.
Also, the comorbidity adjustments were derived through a regression
analysis, which also includes other IPF PPS adjustments (for example,
the age adjustment). Our established policy is to annually update the
ICD-10-CM/PCS codes, which are associated with the existing IPF PPS
comorbidity categories. Adding or removing codes to the existing
comorbidity categories that are not part of the annual coding update
would occur as part of a larger IPF PPS refinement. We did not propose
to refine the IPF PPS in the FY 2022 IPF PPS proposed rule, and
therefore, are not changing the policy in this final rule. However, we
will consider the comment to potentially inform future refinements.
c. Final Patient Age Adjustments
As explained in the November 2004 IPF PPS final rule (69 FR 66922),
we analyzed the impact of age on per diem cost by examining the age
variable (range of ages) for payment adjustments. In general, we found
that the cost per day increases with age. The older age groups are
costlier than the under 45 age group, the differences in per diem cost
increase for each successive age group, and the differences are
statistically significant. For FY 2022, we are finalizing our proposal
to continue to use the patient age adjustments currently in effect in
FY 2021, as shown in Addendum A of this rule (see https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html).
d. Final Variable Per Diem Adjustments
We explained in the November 2004 IPF PPS final rule (69 FR 66946)
that the regression analysis indicated that per diem cost declines as
the length of stay (LOS) increases. The variable per diem adjustments
to the Federal per diem base rate account for ancillary and
administrative costs that occur disproportionately in the first days
after admission to an IPF. As discussed in the November 2004 IPF PPS
final rule, we used a regression analysis to estimate the average
differences in per diem cost among stays of different lengths (69 FR
66947 through 66950). As a result of this analysis, we established
variable per diem adjustments that begin on day 1 and decline gradually
until day 21 of a patient's stay. For day 22 and thereafter, the
variable per diem adjustment remains the same each day for the
remainder of the stay. However, the adjustment applied to day 1 depends
upon whether the IPF has a qualifying ED. If an IPF has a qualifying
ED, it receives a 1.31 adjustment factor for day 1 of each stay. If an
IPF does not have a qualifying ED, it receives a 1.19 adjustment factor
for day 1 of the stay. The ED adjustment is explained in more detail in
section III.D.4 of this rule.
For FY 2022, we are finalizing our proposal to continue to use the
variable per diem adjustment factors currently in effect, as shown in
Addendum A of this rule (available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html). A
complete discussion of the variable per diem adjustments appears in the
November 2004 IPF PPS final rule (69 FR 66946).
[[Page 42616]]
D. Final Updates to the IPF PPS Facility-Level Adjustments
The IPF PPS includes facility-level adjustments for the wage index,
IPFs located in rural areas, teaching IPFs, cost of living adjustments
for IPFs located in Alaska and Hawaii, and IPFs with a qualifying ED.
1. Wage Index Adjustment
a. Background
As discussed in the RY 2007 IPF PPS final rule (71 FR 27061), RY
2009 IPF PPS (73 FR 25719) and the RY 2010 IPF PPS notices (74 FR
20373), in order to provide an adjustment for geographic wage levels,
the labor-related portion of an IPF's payment is adjusted using an
appropriate wage index. Currently, an IPF's geographic wage index value
is determined based on the actual location of the IPF in an urban or
rural area, as defined in Sec. 412.64(b)(1)(ii)(A) and (C).
Due to the variation in costs and because of the differences in
geographic wage levels, in the November 15, 2004 IPF PPS final rule, we
required that payment rates under the IPF PPS be adjusted by a
geographic wage index. We proposed and finalized a policy to use the
unadjusted, pre-floor, pre-reclassified IPPS hospital wage index to
account for geographic differences in IPF labor costs. We implemented
use of the pre-floor, pre-reclassified IPPS hospital wage data to
compute the IPF wage index since there was not an IPF-specific wage
index available. We believe that IPFs generally compete in the same
labor market as IPPS hospitals so the pre-floor, pre-reclassified IPPS
hospital wage data should be reflective of labor costs of IPFs. We
believe this pre-floor, pre-reclassified IPPS hospital wage index to be
the best available data to use as proxy for an IPF specific wage index.
As discussed in the RY 2007 IPF PPS final rule (71 FR 27061 through
27067), under the IPF PPS, the wage index is calculated using the IPPS
wage index for the labor market area in which the IPF is located,
without considering geographic reclassifications, floors, and other
adjustments made to the wage index under the IPPS. For a complete
description of these IPPS wage index adjustments, we refer readers to
the FY 2019 IPPS/LTCH PPS final rule (83 FR 41362 through 41390). Our
wage index policy at Sec. 412.424(a)(2), requires us to use the best
Medicare data available to estimate costs per day, including an
appropriate wage index to adjust for wage differences.
When the IPF PPS was implemented in the November 15, 2004 IPF PPS
final rule, with an effective date of January 1, 2005, the pre-floor,
pre-reclassified IPPS hospital wage index that was available at the
time was the FY 2005 pre-floor, pre-reclassified IPPS hospital wage
index. Historically, the IPF wage index for a given RY has used the
pre-floor, pre-reclassified IPPS hospital wage index from the prior FY
as its basis. This has been due in part to the pre-floor, pre-
reclassified IPPS hospital wage index data that were available during
the IPF rulemaking cycle, where an annual IPF notice or IPF final rule
was usually published in early May. This publication timeframe was
relatively early compared to other Medicare payment rules because the
IPF PPS follows a RY, which was defined in the implementation of the
IPF PPS as the 12-month period from July 1 to June 30 (69 FR 66927).
Therefore, the best available data at the time the IPF PPS was
implemented was the pre-floor, pre-reclassified IPPS hospital wage
index from the prior FY (for example, the RY 2006 IPF wage index was
based on the FY 2005 pre-floor, pre-reclassified IPPS hospital wage
index).
In the RY 2012 IPF PPS final rule, we changed the reporting year
timeframe for IPFs from a RY to the FY, which begins October 1 and ends
September 30 (76 FR 26434 through 26435). In that FY 2012 IPF PPS final
rule, we continued our established policy of using the pre-floor, pre-
reclassified IPPS hospital wage index from the prior year (that is,
from FY 2011) as the basis for the FY 2012 IPF wage index. This policy
of basing a wage index on the prior year's pre-floor, pre-reclassified
IPPS hospital wage index has been followed by other Medicare payment
systems, such as hospice and inpatient rehabilitation facilities. By
continuing with our established policy, we remained consistent with
other Medicare payment systems.
In FY 2020, we finalized the IPF wage index methodology to align
the IPF PPS wage index with the same wage data timeframe used by the
IPPS for FY 2020 and subsequent years. Specifically, we finalized to
use the pre-floor, pre-reclassified IPPS hospital wage index from the
FY concurrent with the IPF FY as the basis for the IPF wage index. For
example, the FY 2020 IPF wage index was based on the FY 2020 pre-floor,
pre-reclassified IPPS hospital wage index rather than on the FY 2019
pre-floor, pre-reclassified IPPS hospital wage index.
We explained in the FY 2020 proposed rule (84 FR 16973), that using
the concurrent pre-floor, pre-reclassified IPPS hospital wage index
will result in the most up-to-date wage data being the basis for the
IPF wage index. It will also result in more consistency and parity in
the wage index methodology used by other Medicare payment systems. The
Medicare SNF PPS already used the concurrent IPPS hospital wage index
data as the basis for the SNF PPS wage index. Thus, the wage adjusted
Medicare payments of various provider types will be based upon wage
index data from the same timeframe. CMS proposed similar policies to
use the concurrent pre-floor, pre-reclassified IPPS hospital wage index
data in other Medicare payment systems, such as hospice and inpatient
rehabilitation facilities. For FY 2022, we proposed to continue to use
the concurrent pre-floor, pre-reclassified IPPS hospital wage index as
the basis for the IPF wage index.
Comment: Several commenters expressed concerns with our proposal to
continue using the concurrent pre-floor, pre-reclassified IPPS hospital
wage index as the basis for the IPF wage index. Three commenters
recommended CMS extend the transition for the reductions in payment for
certain IPFs resulting from the wage index changes adopted in the FY
2021 IPF PPS final rule. Another commenter also recommended that CMS
apply a non-budget neutral 5 percent cap on decreases to a hospital's
wage index value to help mitigate wide annual swings that are beyond a
hospital's ability to control.
Response: We did not propose to modify the transition policy that
was finalized in the FY 2021 IPF PPS final rule; therefore, we are not
changing the previously adopted policy in this final rule. As we
discussed in the FY 2021 IPF PPS final rule (85 FR 47058 through
47059), the transition policy caps the estimated reduction in an IPF's
wage index to 5 percent in FY 2021, with no cap applied in FY 2022. We
stated our belief that implementing updated wage index values along
with the revised OMB delineations will result in wage index values
being more representative of the actual costs of labor in a given area.
As evidenced by the detailed economic analysis (85 FR 47065 through
47068), we estimated that implementing these wage index changes would
have distributional effects, both positive and negative, among IPF
providers. We continue to believe that applying the 5-percent cap
transition policy in year one provided an adequate safeguard against
any significant payment reductions, has allowed for sufficient time to
make operational changes for future FYs, and provided a reasonable
balance between mitigating some short-term instability in IPF payments
and improving the accuracy of the payment adjustment for differences in
area wage levels.
[[Page 42617]]
We note that certain changes to wage index policy may significantly
affect Medicare payments. These changes may arise from revisions to the
OMB delineations of statistical areas resulting from the decennial
census data, periodic updates to the OMB delineations in the years
between the decennial censuses, or other wage index policy changes.
While we consider how best to address these potential scenarios in a
consistent and thoughtful manner, we reiterate that our policy
principles with regard to the wage index include generally using the
most current data and information available and providing that data and
information, as well as any approaches to addressing any significant
effects on Medicare payments resulting from these potential scenarios,
in notice and comment rulemaking.
Comment: Two commenters recommended that CMS incorporate a frontier
state floor into the IPF wage index. Another commenter requested that
CMS implement policies to address the disparity in payments between
rural and urban IPFs, similar to policies that have been adopted for
IPPS hospitals.
Response: We appreciate commenters' suggestions regarding
opportunities to improve the accuracy of the IPF wage index. We did not
propose the specific policies that commenters have suggested, but we
will take them into consideration to potentially inform future
rulemaking.
Final Decision: For FY 2022, we are finalizing the proposal to
continue to use the concurrent pre-floor, pre-reclassified IPPS
hospital wage index as the basis for the IPF wage index. Since we did
not propose any changes to the 2-year transition that was finalized in
the FY 2021 IPF PPS final rule, there will be no cap applied to the
reduction in the wage index for the second year (that is, FY 2022).
We will apply the IPF wage index adjustment to the labor-related
share of the national base rate and ECT payment per treatment. The
labor-related share of the national rate and ECT payment per treatment
will change from 77.3 percent in FY 2021 to 77.2 percent in FY 2022.
This percentage reflects the labor-related share of the 2016-based IPF
market basket for FY 2022 (see section III.A.4 of this rule).
b. Office of Management and Budget (OMB) Bulletins
(i.) Background
The wage index used for the IPF PPS is calculated using the
unadjusted, pre-reclassified and pre-floor IPPS wage index data and is
assigned to the IPF on the basis of the labor market area in which the
IPF is geographically located. IPF labor market areas are delineated
based on the Core-Based Statistical Area (CBSAs) established by the
OMB.
Generally, OMB issues major revisions to statistical areas every 10
years, based on the results of the decennial census. However, OMB
occasionally issues minor updates and revisions to statistical areas in
the years between the decennial censuses through OMB Bulletins. These
bulletins contain information regarding CBSA changes, including changes
to CBSA numbers and titles. OMB bulletins may be accessed online at
https://www.whitehouse.gov/omb/information-for-agencies/bulletins/. In
accordance with our established methodology, the IPF PPS has
historically adopted any CBSA changes that are published in the OMB
bulletin that corresponds with the IPPS hospital wage index used to
determine the IPF wage index and, when necessary and appropriate, has
proposed and finalized transition policies for these changes.
In the RY 2007 IPF PPS final rule (71 FR 27061 through 27067), we
adopted the changes discussed in the 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 OMB CBSA geographic designations in RY 2007, we did not
provide a separate transition for the CBSA-based wage index since the
IPF PPS was already in a transition period from TEFRA payments to PPS
payments.
In the RY 2009 IPF PPS notice, we incorporated the CBSA
nomenclature changes published in the most recent OMB bulletin that
applied to the IPPS hospital wage index used to determine the current
IPF wage index and stated that we expected to continue to do the same
for all the OMB CBSA nomenclature changes in future IPF PPS rules and
notices, as necessary (73 FR 25721).
Subsequently, CMS adopted the changes that were published in past
OMB bulletins in the FY 2016 IPF PPS final rule (80 FR 46682 through
46689), the FY 2018 IPF PPS rate update (82 FR 36778 through 36779),
the FY 2020 IPF PPS final rule (84 FR 38453 through 38454), and the FY
2021 IPF PPS final rule (85 FR 47051 through 47059). We direct readers
to each of these rules for more information about the changes that were
adopted and any associated transition policies.
In part due to the scope of changes involved in adopting the CBSA
delineations for FY 2021, we finalized a 2-year transition policy
consistent with our past practice of using transition policies to help
mitigate negative impacts on hospitals of certain wage index policy
changes. We applied a 5-percent cap on wage index decreases to all IPF
providers that had any decrease in their wage indexes, regardless of
the circumstance causing the decline, so that an IPF's final wage index
for FY 2021 will not be less than 95 percent of its final wage index
for FY 2020, regardless of whether the IPF was part of an updated CBSA.
We refer readers to the FY 2021 IPF PPS final rule (85 FR 47058 through
47059) for a more detailed discussion about the wage index transition
policy for FY 2021.
On March 6, 2020 OMB issued OMB Bulletin 20-01 (available on the
web at https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf). In considering whether to adopt this bulletin, we analyzed
whether the changes in this bulletin would have a material impact on
the IPF PPS wage index. This bulletin creates only one Micropolitan
statistical area. As discussed in further detail in section
III.D.1.b.ii, since Micropolitan areas are considered rural for the IPF
PPS wage index, this bulletin has no material impact on the IPF PPS
wage index. That is, the constituent county of the new Micropolitan
area was considered rural effective as of FY 2021 and would continue to
be considered rural if we adopted OMB Bulletin 20-01. Therefore, we did
not propose to adopt OMB Bulletin 20-01 in the FY 2022 IPF PPS proposed
rule.
(ii.) Micropolitan Statistical Areas
OMB defines a ``Micropolitan Statistical Area'' as a CBSA
associated with at least one urban cluster that has a population of at
least 10,000, but less than 50,000 (75 FR 37252). We refer to these as
Micropolitan Areas. After extensive impact analysis, consistent with
the treatment of these areas under the IPPS as discussed in the FY 2005
IPPS final rule (69 FR 49029 through 49032), we determined the best
course of action would be to treat Micropolitan Areas as ``rural'' and
include them in the calculation of each state's IPF PPS rural wage
index. We refer the reader to the FY 2007 IPF PPS final rule (71 FR
27064 through 27065) for a complete discussion regarding treating
Micropolitan Areas as rural.
c. Final Adjustment for Rural Location
In the November 2004 IPF PPS final rule, (69 FR 66954) we provided
a 17 percent payment adjustment for IPFs located in a rural area. This
adjustment was based on the regression analysis, which indicated that
the per diem cost
[[Page 42618]]
of rural facilities was 17 percent higher than that of urban facilities
after accounting for the influence of the other variables included in
the regression. This 17 percent adjustment has been part of the IPF PPS
each year since the inception of the IPF PPS. For FY 2022, we proposed
to continue to apply a 17 percent payment adjustment for IPFs located
in a rural area as defined at Sec. 412.64(b)(1)(ii)(C) (see 69 FR
66954 for a complete discussion of the adjustment for rural locations).
Comment: We received one comment in favor of the proposed extension
of the 17 percent payment adjustment for rural IPFs. The commenter
acknowledged CMS' efforts to avoid disparities in payments to
facilities in rural and underserved communities.
Response: We appreciate this comment of support. Since the
inception of the IPF PPS, we have applied a 17 percent adjustment for
IPFs located in rural areas. As stated in the previous paragraph, this
adjustment was derived from the results of our regression analysis and
was incorporated into the payment system in order to ensure the
accuracy of payments to rural IPFs. CMS continues to look for ways to
ensure accuracy of payments to rural IPFs.
Final Decision: For FY 2022, we are finalizing our proposal to
continue to apply a 17 percent payment adjustment for IPFs located in a
rural area as defined at Sec. 412.64(b)(1)(ii)(C).
d. Final Budget Neutrality Adjustment
Changes to the wage index are made in a budget-neutral manner so
that updates do not increase expenditures. Therefore, for FY 2022, we
are finalizing our proposal to continue to apply a budget-neutrality
adjustment in accordance with our existing budget-neutrality policy.
This policy requires us to update the wage index in such a way that
total estimated payments to IPFs for FY 2022 are the same with or
without the changes (that is, in a budget-neutral manner) by applying a
budget neutrality factor to the IPF PPS rates. We use the following
steps to ensure that the rates reflect the FY 2022 update to the wage
indexes (based on the FY 2018 hospital cost report data) and the labor-
related share in a budget-neutral manner:
Step 1: Simulate estimated IPF PPS payments, using the FY 2021 IPF
wage index values (available on the CMS website) and labor-related
share (as published in the FY 2021 IPF PPS final rule (85 FR 47043)).
Step 2: Simulate estimated IPF PPS payments using the final FY 2022
IPF wage index values (available on the CMS website) and final FY 2022
labor-related share (based on the latest available data as discussed
previously).
Step 3: Divide the amount calculated in step 1 by the amount
calculated in step 2. The resulting quotient is the FY 2022 budget-
neutral wage adjustment factor of 1.0017.
Step 4: Apply the FY 2022 budget-neutral wage adjustment factor
from step 3 to the FY 2021 IPF PPS Federal per diem base rate after the
application of the market basket update described in section III.A of
this rule, to determine the FY 2022 IPF PPS Federal per diem base rate.
2. Final Teaching Adjustment
a. Background
In the November 2004 IPF PPS final rule, we implemented regulations
at sect; 412.424(d)(1)(iii) to establish a facility-level adjustment
for IPFs that are, or are part of, teaching hospitals. The teaching
adjustment accounts for the higher indirect operating costs experienced
by hospitals that participate in graduate medical education (GME)
programs. The payment adjustments are made based on the ratio of the
number of full-time equivalent (FTE) interns and residents training in
the IPF and the IPF's average daily census (ADC).
Medicare makes direct GME payments (for direct costs such as
resident and teaching physician salaries, and other direct teaching
costs) to all teaching hospitals including those paid under a PPS, and
those paid under the TEFRA rate-of-increase limits. These direct GME
payments are made separately from payments for hospital operating costs
and are not part of the IPF PPS. The direct GME payments do not address
the estimated higher indirect operating costs teaching hospitals may
face.
The results of the regression analysis of FY 2002 IPF data
established the basis for the payment adjustments included in the
November 2004 IPF PPS final rule. The results showed that the indirect
teaching cost variable is significant in explaining the higher costs of
IPFs that have teaching programs. We calculated the teaching adjustment
based on the IPF's ``teaching variable,'' which is (1 + (the number of
FTE residents training in the IPF/the IPF's ADC)). The teaching
variable is then raised to the 0.5150 power to result in the teaching
adjustment. This formula is subject to the limitations on the number of
FTE residents, which are described in this section of this rule.
We established the teaching adjustment in a manner that limited the
incentives for IPFs to add FTE residents for the purpose of increasing
their teaching adjustment. We imposed a cap on the number of FTE
residents that may be counted for purposes of calculating the teaching
adjustment. The cap limits the number of FTE residents that teaching
IPFs may count for the purpose of calculating the IPF PPS teaching
adjustment, not the number of residents teaching institutions can hire
or train. We calculated the number of FTE residents that trained in the
IPF during a ``base year'' and used that FTE resident number as the
cap. An IPF's FTE resident cap is ultimately determined based on the
final settlement of the IPF's most recent cost report filed before
November 15, 2004 (publication date of the IPF PPS final rule). A
complete discussion of the temporary adjustment to the FTE cap to
reflect residents due to hospital closure or residency program closure
appears in the RY 2012 IPF PPS proposed rule (76 FR 5018 through 5020)
and the RY 2012 IPF PPS final rule (76 FR 26453 through 26456). In
section III.D.2.b of this final rule, we discuss finalized updates to
the IPF policy on temporary adjustment to the FTE cap.
In the regression analysis, the logarithm of the teaching variable
had a coefficient value of 0.5150. We converted this cost effect to a
teaching payment adjustment by treating the regression coefficient as
an exponent and raising the teaching variable to a power equal to the
coefficient value. We note that the coefficient value of 0.5150 was
based on the regression analysis holding all other components of the
payment system constant. A complete discussion of how the teaching
adjustment was calculated appears in the November 2004 IPF PPS final
rule (69 FR 66954 through 66957) and the RY 2009 IPF PPS notice (73 FR
25721). As with other adjustment factors derived through the regression
analysis, we do not plan to rerun the teaching adjustment factors in
the regression analysis until we more fully analyze IPF PPS data.
Therefore, in this FY 2022 final rule, we are finalizing our proposal
to continue to retain the coefficient value of 0.5150 for the teaching
adjustment to the Federal per diem base rate.
b. Final Update to IPF Teaching Policy on IPF Program Closures and
Displaced Residents
For FY 2022, we proposed to change the IPF policy regarding
displaced residents from IPF closures and closures of IPF teaching
programs. Specifically, we proposed to adopt conforming changes to the
IPF PPS teaching policy
[[Page 42619]]
to align with the policy changes that the IPPS finalized in the FY 2021
IPPS final rule (85 FR 58865 through 58870). We believe that the IPF
IME policy relating to hospital closure and displaced students is
susceptible to the same vulnerabilities as IPPS GME policy. Hence, if
an IPF with a large number of residents training in its residency
program announces that it is closing, these residents will become
displaced and will need to find alternative positions at other IPF
hospitals or risk being unable to become Board-certified. Although we
proposed to adopt a policy under the IPF PPS that is consistent with an
applicable policy under the IPPS, the actual caps under the two payment
systems may not be commingled. In other words, the resident cap
applicable under the IPPS is separate from the resident cap applicable
under the IPF PPS; moreover, a provider cannot add its IPF resident cap
to its IPPS resident cap in order to increase the number of residents
it receives payment for under either payment system.
As stated in the November 2004 IPF PPS final rule (69 FR 66922), we
implemented regulations at Sec. 412.424(d)(1)(iii) to establish a
facility-level adjustment for IPFs that are, or are part of, teaching
hospitals. The facility-level adjustment we are providing for teaching
hospitals under IPF PPS parallels the IME payments paid under the IPPS.
Both payments are add on adjustments to the amount per case and both
are based in part on the number of full-time equivalent (FTE) residents
training at the facility.
The regulation at 42 CFR 412.424(d)(1)(iii)(F) permits an IPF to
temporarily adjust its FTE cap to reflect residents added because of
another hospital or program's closure. We first implemented regulations
regarding residents displaced by teaching hospital and program closures
in the May 6, 2011 IPF PPS final rule (76 FR 26431). In that final
rule, we adopted the IPPS definition of ``closure of a hospital'' at 42
CFR 413.79(h)(1)(i) to apply to IPF closures as well, and to mean that
the IPF terminates its Medicare provider agreement as specified in 42
CFR 489.52. In the proposed rule, we proposed to codify this
definition, as well as, the definition of an IPF program closure, at
Sec. 412.402.
Although not explicitly stated in regulatory text, our current
policy is that a displaced resident is one that is physically present
at the hospital training on the day prior to or the day of hospital or
program closure. This longstanding policy derived from the fact that in
the regulations text, there are requirements that the receiving
hospital identifies the residents ``who have come from the closed IPF''
(Sec. 412.424(d)(1)(iii)(F)(1)(ii)) or identifies the residents ``who
have come from another IPF's closed program'' (Sec.
412.424(d)(1)(iii)(F)(2)(i)), and that the IPF that closed its program
identifies ``the residents who were in training at the time of the
program's closure'' (Sec. 412.424(d)(1)(iii)(F)(2)(ii)). We considered
the residents who were physically present at the IPF to be those
residents who were ``training at the time of the program's closure,''
thereby granting them the status of ``displaced residents.'' Although
we did not want to limit the ``displaced residents'' to only those
physically present at the time of closure, it becomes much more
administratively challenging for the following groups of residents at
closing IPFs/programs to continue their training: (1) Residents who
leave the program after the closure is publicly announced to continue
training at another IPF, but before the actual closure; (2) residents
assigned to and training at planned rotations at other IPFs who will be
unable to return to their rotations at the closing IPF or program; and
(3) individuals (such as medical students or would-be fellows) who
matched into resident programs at the closing IPF or program but have
not yet started training at the closing IPF or program. Other groups of
residents who, under current policy, are already considered ``displaced
residents'' include--(1) residents who are physically training in the
IPF on the day prior to or day of program or IPF closure; and (2)
residents who would have been at the closing IPF or IPF program on the
day prior to or of closure but were on approved leave at that time, and
are unable to return to their training at the closing IPF or IPF
program.
We proposed to amend the IPF policy with regard to closing teaching
IPFs and closing residency programs to address the needs of residents
attempting to find alternative IPFs in which to complete their
training. Additionally, this proposal addresses the incentives of
originating and receiving IPFs with regard to ensuring we appropriately
account for their indirect teaching costs by way of an appropriate IPF
teaching adjustment based on each program's resident FTEs. We proposed
to change two aspects of the current IPF policy, which are discussed in
the following section.
First, rather than link the status of displaced residents, for the
purpose of the receiving IPF's request to increase their FTE cap, to
the resident's presence at the closing IPF or program on the day prior
to or the day of program or IPF closure, we proposed that the ideal day
will be the day that the closure was publicly announced, (for example,
via a press release or a formal notice to the Accreditation Council on
Graduate Medical Education (ACGME)). This will provide greater
flexibility for the residents to transfer while the IPF operations or
residency programs were winding down, rather than waiting until the
last day of IPF or program operation. This will address the needs of
the first group of residents as previously described: Residents who
leave the IPF program after the closure was publicly announced to
continue training at another IPF, but before the day of actual closure.
Second, by removing the link between the status of displaced
residents and their presence at the closing IPF or program on the day
prior to or the day of program or IPF closure, we proposed to also
allow the second and third group of residents who are not physically at
the closing IPF/closing program, but had intended to train at (or
return to training at, in the case of residents on rotation) to be
considered displaced residents. Thus, we proposed to revise our
teaching policy with regard to which residents can be considered
``displaced'' for the purpose of the receiving IPF's request to
increase their FTE cap in the situation where an IPF announces publicly
that it is closing or that it is closing an IPF residency program(s).
Specifically, we are adopting the definitions of ``closure of a
hospital'', ``closure of a hospital residency training program'', and
``displaced resident'' as defined at 42 CFR 413.79(h) but with respect
to IPFs and for the purposes of accounting for indirect teaching costs.
In addition, we proposed to change another detail of the IPF
teaching policy specific to the requirements for the receiving IPF. To
apply for the temporary increase in the FTE resident cap, the receiving
IPF will have to submit a letter to its Medicare Administrative
Contractor (MAC) within 60 days of beginning the training of the
displaced residents. As established under existing regulation at Sec.
412.424(d)(1)(iii)(F)(1)(ii) and Sec. 412.424(d)(1)(iii)(F)(2)(i),
this letter must identify the residents who have come from the closed
IPF or program that have caused the receiving IPF to exceed its cap,
and the receiving IPF must specify the length of time the adjustment is
needed. Moreover, we want to propose clarifications on how the
information will be delivered in this letter. Consistent with IPPS
teaching policy, we proposed that the letter from the receiving IPF
will have to include:
[[Page 42620]]
(1) The name of each displaced resident; (2) the last four digits of
each displaced resident's social security number; (3) the IPF and
program in which each resident was training previously; and (4) the
amount of the cap increase needed for each resident (based on how much
the receiving IPF is in excess of its cap and the length of time for
which the adjustments are needed). We proposed to require the receiving
hospital to only supply the last four digits of each displaced
resident's social security number to reduce the amount of personally
identifiable information (PII) included in these agreements.
We also clarified, as previously discussed in the May 6, 2011 IPF
PPS final rule (76 FR 26455), the maximum number of FTE resident cap
slots that could be transferred to all receiving IPFs is the number of
FTE resident cap slots belonging to the IPF that has the closed program
or that is closing. Therefore, if the originating IPF is training
residents in excess of its cap, then being a displaced resident does
not guarantee that a cap slot will be transferred along with that
resident. Therefore, if there are more IPF displaced residents than
available cap slots, the slots may be apportioned according to the
closing IPF's discretion. The decision to transfer a cap slot if one is
available will be voluntary and made at the sole discretion of the
originating IPF. However, if the originating IPF decides to do so, then
it will be the originating IPF's responsibility to determine how much
of an available cap slot will go with a particular resident (if any).
We also note, as we previously discussed in the May 6, 2011 IPF PPS
final rule (76 FR 25455), only to the extent a receiving IPF would
exceed its FTE cap by training displaced residents would it be eligible
for a temporary adjustment to its resident FTE cap. Displaced residents
are factored into the receiving IPF's ratio of resident FTEs to the
facility's average daily census.
Comment: We received 3 comments on our proposed updates to IPF
teaching policy. All commenters appreciate the alignment of IPF
teaching policy with IPPS. They believe it is important to protect
medical education. Therefore, decreasing confusion and streamlining the
process gives residents and program directors more time to find a new
program or rotation site, which can only help the transfer process.
Response: We thank these commenters for their support.
Final Decision: For FY 2022, we are finalizing the closure policy
as proposed. Section 124 of the BBRA gives the Secretary broad
discretion to determine the appropriate adjustment factors for the IPF
PPS. We are finalizing our proposal to implement the policy regarding
IPF resident caps and closures to remain consistent with the way that
the IPPS teaching policy calculates FTE resident caps in the case of a
receiving hospital that obtains a temporary IME and direct GME cap
adjustment for assuming the training of displaced residents due to
another hospital or residency program's closure. We are also finalizing
our proposal that in the future, we will deviate from IPPS teaching
policy as it pertains to counting displaced residents for the purposes
of the IPF teaching adjustment only when it is necessary and
appropriate for the IPF PPS.
In addition, we are finalizing our proposal to amend the IPF policy
with regard to closing teaching IPFs and closing residency programs to
address the needs of residents attempting to find alternative IPFs in
which to complete their training. This proposal addresses the
incentives of originating and receiving IPFs with regard to ensuring we
appropriately account for their indirect teaching costs by way of an
appropriate IPF teaching adjustment based on each program's resident
FTEs. We are also finalizing our proposal to change two aspects of the
current IPF policy, which are discussed in the following section.
First, rather than link the status of displaced residents for the
purpose of the receiving IPF's request to increase their FTE cap to the
resident's presence at the closing IPF or program on the day prior to
or the day of program or IPF closure, we are finalizing our proposal
that the ideal day will be the day that the closure was publicly
announced, (for example, via a press release or a formal notice to the
Accreditation Council on Graduate Medical Education (ACGME)). This will
provide greater flexibility for the residents to transfer while the IPF
operations or residency programs were winding down, rather than waiting
until the last day of IPF or program operation. This will address the
needs of the first group of residents as previously described:
Residents who leave the IPF program after the closure was publicly
announced to continue training at another IPF, but before the day of
actual closure.
Second, by removing the link between the status of displaced
residents and their presence at the closing IPF or program on the day
prior to or the day of program or IPF closure, we are finalizing to
also allow the second and third group of residents who are not
physically at the closing IPF/closing program, but had intended to
train at (or return to training at, in the case of residents on
rotation) to be considered a displaced resident. Thus, we are
finalizing our proposal to revise our teaching policy with regard to
which residents can be considered ``displaced'' for the purpose of the
receiving IPF's request to increase their FTE cap in the situation
where an IPF announces publicly that it is closing or that it is
closing an IPF residency program(s). Specifically, we are adopting the
definitions of ``closure of a hospital'', ``closure of a hospital
residency training program'', and ``displaced resident'' as defined at
42 CFR 413.79(h) but with respect to IPFs and for the purposes of
accounting for indirect teaching costs.
In addition, we are finalizing our proposal to change another
detail of the IPF teaching policy specific to the requirements for the
receiving IPF. To apply for the temporary increase in the FTE resident
cap, the receiving IPF will have to submit a letter to its Medicare
Administrative Contractor (MAC) within 60 days of beginning the
training of the displaced residents. As established under existing
regulation at Sec. 412.424(d)(1)(iii)(F)(1)(ii) and Sec.
412.424(d)(1)(iii)(F)(2)(i), this letter must identify the residents
who have come from the closed IPF or program that have caused the
receiving IPF to exceed its cap, and the receiving IPF must specify the
length of time the adjustment is needed. Moreover, we are finalizing
the clarifications on how the information will be delivered in this
letter. Consistent with IPPS teaching policy, the letter from the
receiving IPF will have to include: (1) The name of each displaced
resident; (2) the last four digits of each displaced resident's social
security number; (3) the IPF and program in which each resident was
training previously; and (4) the amount of the cap increase needed for
each resident (based on how much the receiving IPF is in excess of its
cap and the length of time for which the adjustments are needed). We
are also finalizing our proposal to require the receiving hospital to
only supply the last four digits of each displaced resident's social
security number to reduce the amount of personally identifiable
information (PII) included in these agreements.
We are also finalizing the clarification that the maximum number of
FTE resident cap slots that could be transferred to all receiving IPFs
is the number of FTE resident cap slots belonging to the IPF that has
the closed program or that is closing. Therefore, if the originating
IPF is training residents in excess of its cap, then being a displaced
resident does not guarantee that a cap slot will be transferred along
[[Page 42621]]
with that resident. Therefore, if there are more IPF displaced
residents than available cap slots, the slots may be apportioned
according to the closing IPF's discretion. The decision to transfer a
cap slot if one is available will be voluntary and made at the sole
discretion of the originating IPF. However, if the originating IPF
decides to do so, then it will be the originating IPF's responsibility
to determine how much of an available cap slot will go with a
particular resident (if any). We also note that, as we previously
discussed in the May 6, 2011 IPF PPS final rule (76 FR 25455), only to
the extent a receiving IPF would exceed its FTE cap by training
displaced residents would it be eligible for a temporary adjustment to
its resident FTE cap. Displaced residents are factored into the
receiving IPF's ratio of resident FTEs to the facility's average daily
census.
3. Final Cost of Living Adjustment for IPFs Located in Alaska and
Hawaii
The IPF PPS includes a payment adjustment for IPFs located in
Alaska and Hawaii based upon the area in which the IPF is located. As
we explained in the November 2004 IPF PPS final rule, the FY 2002 data
demonstrated that IPFs in Alaska and Hawaii had per diem costs that
were disproportionately higher than other IPFs. Other Medicare
prospective payment systems (for example, the IPPS and LTCH PPS)
adopted a COLA to account for the cost differential of care furnished
in Alaska and Hawaii.
We analyzed the effect of applying a COLA to payments for IPFs
located in Alaska and Hawaii. The results of our analysis demonstrated
that a COLA for IPFs located in Alaska and Hawaii will improve payment
equity for these facilities. As a result of this analysis, we provided
a COLA in the November 2004 IPF PPS final rule.
A COLA for IPFs located in Alaska and Hawaii is made by multiplying
the non-labor-related portion of the Federal per diem base rate by the
applicable COLA factor based on the COLA area in which the IPF is
located.
The COLA factors through 2009 were published by the Office of
Personnel Management (OPM), and the OPM memo showing the 2009 COLA
factors is available at https://www.chcoc.gov/content/nonforeign-area-retirement-equity-assurance-act.
We note that the COLA areas for Alaska are not defined by county as
are the COLA areas for Hawaii. In 5 CFR 591.207, the OPM established
the following COLA areas:
City of Anchorage, and 80-kilometer (50-mile) radius by
road, as measured from the Federal courthouse.
City of Fairbanks, and 80-kilometer (50-mile) radius by
road, as measured from the Federal courthouse.
City of Juneau, and 80-kilometer (50-mile) radius by road,
as measured from the Federal courthouse.
Rest of the state of Alaska.
As stated in the November 2004 IPF PPS final rule, we update the
COLA factors according to updates established by the OPM. However,
sections 1911 through 1919 of the Non-foreign Area Retirement Equity
Assurance Act, as contained in subtitle B of title XIX of the National
Defense Authorization Act (NDAA) for FY 2010 (Pub. L. 111-84, October
28, 2009), transitions the Alaska and Hawaii COLAs to locality pay.
Under section 1914 of NDAA, locality pay was phased in over a 3-year
period beginning in January 2010, with COLA rates frozen as of the date
of enactment, October 28, 2009, and then proportionately reduced to
reflect the phase-in of locality pay.
When we published the proposed COLA factors in the RY 2012 IPF PPS
proposed rule (76 FR 4998), we inadvertently selected the FY 2010 COLA
rates, which had been reduced to account for the phase-in of locality
pay. We did not intend to propose the reduced COLA rates because that
would have understated the adjustment. Since the 2009 COLA rates did
not reflect the phase-in of locality pay, we finalized the FY 2009 COLA
rates for RY 2010 through RY 2014.
In the FY 2013 IPPS/LTCH final rule (77 FR 53700 through 53701), we
established a new methodology to update the COLA factors for Alaska and
Hawaii, and adopted this methodology for the IPF PPS in the FY 2015 IPF
final rule (79 FR 45958 through 45960). We adopted this new COLA
methodology for the IPF PPS because IPFs are hospitals with a similar
mix of commodities and services. We think it is appropriate to have a
consistent policy approach with that of other hospitals in Alaska and
Hawaii. Therefore, the IPF COLAs for FY 2015 through FY 2017 were the
same as those applied under the IPPS in those years. As finalized in
the FY 2013 IPPS/LTCH PPS final rule (77 FR 53700 and 53701), the COLA
updates are determined every 4 years, when the IPPS market basket
labor-related share is updated. Because the labor-related share of the
IPPS market basket was updated for FY 2018, the COLA factors were
updated in FY 2018 IPPS/LTCH rulemaking (82 FR 38529). As such, we also
updated the IPF PPS COLA factors for FY 2018 (82 FR 36780 through
36782) to reflect the updated COLA factors finalized in the FY 2018
IPPS/LTCH rulemaking.
For FY 2022, we are finalizing our proposal to update the COLA
factors published by OPM for 2009 (as these are the last COLA factors
OPM published prior to transitioning from COLAs to locality pay) using
the methodology that we finalized in the FY 2013 IPPS/LTCH PPS final
rule and adopted for the IPF PPS in the FY 2015 IPF final rule.
Specifically, we are finalizing our proposal to update the 2009 OPM
COLA factors by a comparison of the growth in the Consumer Price
Indices (CPIs) for the areas of Urban Alaska and Urban Hawaii, relative
to the growth in the CPI for the average U.S. city as published by the
Bureau of Labor Statistics (BLS). We note that for the prior update to
the COLA factors, we used the growth in the CPI for Anchorage and the
CPI for Honolulu. Beginning in 2018, these indexes were renamed to the
CPI for Urban Alaska and the CPI for Urban Hawaii due to the BLS
updating its sample to reflect the data from the 2010 Decennial Census
on the distribution of the urban population (https://www.bls.gov/regions/west/factsheet/2018cpirevisionwest.pdf, accessed January 22,
2021). The CPI for Urban Alaska area covers Anchorage and Matanuska-
Susitna Borough in the State of Alaska and the CPI for Urban Hawaii
covers Honolulu in the State of Hawaii. BLS notes that the indexes are
considered continuous over time, regardless of name or composition
changes.
Because BLS publishes CPI data for only Urban Alaska and Urban
Hawaii, using the methodology we finalized in the FY 2013 IPPS/LTCH PPS
final rule and adopted for the IPF PPS in the FY 2015 IPF final rule,
we are finalizing our proposal to use the comparison of the growth in
the overall CPI relative to the growth in the CPI for those areas to
update the COLA factors for all areas in Alaska and Hawaii,
respectively. We believe that the relative price differences between
these urban areas and the U.S. (as measured by the CPIs) are
appropriate proxies for the relative price differences between the
``other areas'' of Alaska and Hawaii and the U.S.
BLS publishes the CPI for All Items for Urban Alaska, Urban Hawaii,
and for the average U.S. city. However, consistent with our methodology
finalized in the FY 2013 IPPS/LTCH PPS final rule and adopted for the
IPF PPS in the FY 2015 IPF final rule, we are finalizing our proposal
to create reweighted CPIs for each of the respective areas to reflect
the underlying
[[Page 42622]]
composition of the IPPS market basket nonlabor-related share. The
current composition of the CPI for All Items for all of the respective
areas is approximately 40 percent commodities and 60 percent services.
However, the IPPS nonlabor-related share is comprised of a different
mix of commodities and services. Therefore, we are finalizing our
proposal to create reweighted indexes for Urban Alaska, Urban Hawaii,
and the average U.S. city using the respective CPI commodities index
and CPI services index and proposed shares of 57 percent commodities/43
percent. We created reweighted indexes using BLS data for 2009 through
2020--the most recent data available at the time of this final
rulemaking. In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38530), we
created reweighted indexes based on the 2014-based IPPS market basket
(which was adopted for the FY 2018 IPPS update) and BLS data for 2009
through 2016 (the most recent BLS data at the time of the FY 2018 IPPS/
LTCH PPS rulemaking), and we updated the IPF PPS COLA factors
accordingly for FY 2018.
We continue to believe this methodology is appropriate because we
continue to make a COLA for hospitals located in Alaska and Hawaii by
multiplying the nonlabor-related portion of the standardized amount by
a COLA factor. We note that OPM's COLA factors were calculated with a
statutorily mandated cap of 25 percent. As stated in the FY 2018 IPPS/
LTCH PPS final rule (82 FR 38530), under the COLA update methodology we
finalized in the FY 2013 IPPS/LTCH PPS final rule, we exercised our
discretionary authority to adjust payments to hospitals in Alaska and
Hawaii by incorporating this cap. In applying this finalized
methodology for updating the COLA factors, for FY 2022, we are
finalizing our proposal to continue to use such a cap, as our policy is
based on OPM's COLA factors (updated by the methodology described
above).
Applying this methodology, the COLA factors that we are finalizing
our proposal to establish for FY 2022 to adjust the nonlabor-related
portion of the standardized amount for IPFs located in Alaska and
Hawaii are shown in Table 2. For comparison purposes, we also are
showing the COLA factors effective for FY 2018 through FY 2021.
[GRAPHIC] [TIFF OMITTED] TR04AU21.171
The final IPF PPS COLA factors for FY 2022 are also shown in
Addendum A to this final rule, and is available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
4. Final Adjustment for IPFs with a Qualifying Emergency Department
(ED)
The IPF PPS includes a facility-level adjustment for IPFs with
qualifying EDs. We provide an adjustment to the Federal per diem base
rate to account for the costs associated with maintaining a full-
service ED. The adjustment is intended to account for ED costs incurred
by a psychiatric hospital with a qualifying ED or an excluded
psychiatric unit of an IPPS hospital or a CAH, for preadmission
services otherwise payable under the Medicare Hospital Outpatient
Prospective Payment System (OPPS), furnished to a beneficiary on the
date of the beneficiary's admission to the hospital and during the day
immediately preceding the date of admission to the IPF (see Sec.
413.40(c)(2)), and the overhead cost of maintaining the ED. This
payment is a facility-level adjustment that applies to all IPF
admissions (with one exception which we described), regardless of
whether a particular patient receives preadmission services in the
hospital's ED.
The ED adjustment is incorporated into the variable per diem
adjustment for the first day of each stay for IPFs with a qualifying
ED. Those IPFs with a qualifying ED receive an adjustment factor of
1.31 as the variable per diem adjustment for day 1 of each patient
stay. If an IPF does not have a qualifying ED, it receives an
adjustment factor of 1.19 as the variable per diem adjustment for day 1
of each patient stay.
The ED adjustment is made on every qualifying claim except as
described in this section of the proposed rule. As specified in Sec.
412.424(d)(1)(v)(B), the ED adjustment is not made when a patient is
discharged from an IPPS hospital or CAH and admitted to the same IPPS
hospital's or CAH's excluded psychiatric unit. We clarified in the
November 2004 IPF PPS final rule (69 FR 66960) that an ED adjustment is
not made in this case because the costs associated with ED services are
reflected in the DRG payment to the IPPS hospital or through the
reasonable cost payment made to the CAH.
Therefore, when patients are discharged from an IPPS hospital or
CAH and admitted to the same hospital's or CAH's excluded
[[Page 42623]]
psychiatric unit, the IPF receives the 1.19 adjustment factor as the
variable per diem adjustment for the first day of the patient's stay in
the IPF. For FY 2022, we are finalizing our proposal to continue to
retain the 1.31 adjustment factor for IPFs with qualifying EDs. A
complete discussion of the steps involved in the calculation of the ED
adjustment factors are in the November 2004 IPF PPS final rule (69 FR
66959 through 66960) and the RY 2007 IPF PPS final rule (71 FR 27070
through 27072).
F. Other Final Payment Adjustments and Policies
1. Outlier Payment Overview
The IPF PPS includes an outlier adjustment to promote access to IPF
care for those patients who require expensive care and to limit the
financial risk of IPFs treating unusually costly patients. In the
November 2004 IPF PPS final rule, we implemented regulations at Sec.
412.424(d)(3)(i) to provide a per-case payment for IPF stays that are
extraordinarily costly. Providing additional payments to IPFs for
extremely costly cases strongly improves the accuracy of the IPF PPS in
determining resource costs at the patient and facility level. These
additional payments reduce the financial losses that would otherwise be
incurred in treating patients who require costlier care, and therefore,
reduce the incentives for IPFs to under-serve these patients. We make
outlier payments for discharges in which an IPF's estimated total cost
for a case exceeds a fixed dollar loss threshold amount (multiplied by
the IPF's facility-level adjustments) plus the Federal per diem payment
amount for the case.
In instances when the case qualifies for an outlier payment, we pay
80 percent of the difference between the estimated cost for the case
and the adjusted threshold amount for days 1 through 9 of the stay
(consistent with the median LOS for IPFs in FY 2002), and 60 percent of
the difference for day 10 and thereafter. The adjusted threshold amount
is equal to the outlier threshold amount adjusted for wage area,
teaching status, rural area, and the COLA adjustment (if applicable),
plus the amount of the Medicare IPF payment for the case. We
established the 80 percent and 60 percent loss sharing ratios because
we were concerned that a single ratio established at 80 percent (like
other Medicare PPSs) might provide an incentive under the IPF per diem
payment system to increase LOS in order to receive additional payments.
After establishing the loss sharing ratios, we determined the
current fixed dollar loss threshold amount through payment simulations
designed to compute a dollar loss beyond which payments are estimated
to meet the 2 percent outlier spending target. Each year when we update
the IPF PPS, we simulate payments using the latest available data to
compute the fixed dollar loss threshold so that outlier payments
represent 2 percent of total estimated IPF PPS payments.
2. Final Update to the Outlier Fixed Dollar Loss Threshold Amount
In accordance with the update methodology described in Sec.
412.428(d), we are finalizing our proposal to update the fixed dollar
loss threshold amount used under the IPF PPS outlier policy. Based on
the regression analysis and payment simulations used to develop the IPF
PPS, we established a 2 percent outlier policy, which strikes an
appropriate balance between protecting IPFs from extraordinarily costly
cases while ensuring the adequacy of the Federal per diem base rate for
all other cases that are not outlier cases.
Our longstanding methodology for updating the outlier fixed dollar
loss threshold involves using the best available data, which is
typically the most recent available data. For this final rulemaking,
the most recent available data are the FY 2020 claims. However, during
FY 2020, the U.S. healthcare system undertook an unprecedented response
to the PHE declared by the Health and Human Services Secretary on
January 31, 2020 in response to the outbreak of respiratory disease
caused by a novel (new) coronavirus that has been named ``SARS CoV 2''
and the disease it causes, which has been named ``coronavirus disease
2019'' (abbreviated ``COVID-19''). Therefore, as discussed in section
VI.C.3 of the FY 2022 IPF PPS proposed rule (86 FR 19524 through
195266), we considered whether the most recent available year of
claims, FY 2020, or the prior year, FY 2019, would be the best for
estimating IPF PPS payments in FY 2021 and FY 2022. We compared the two
years' claims distributions as well as the impact results, and based on
that analysis determined that the FY 2019 claims appeared to be the
best available data at this time. We refer the reader to section VI.C.3
of the FY 2022 IPF PPS proposed rule (86 FR 19524 through 195266 FR)
for a detailed discussion of that analysis.
Comment: We received 2 comments on our analysis of the FY 2019 and
FY 2020 claims in determining the best available data for estimating
IPF PPS payments in FY 2021 and FY 2022. Both comments were supportive
of our proposal to use the FY 2019 claims for this purpose. One of
these commenters expressed appreciation for the proposed reduction in
the outlier fixed dollar loss threshold. Another commenter agreed with
our assessment that FY 2020 claims were heavily impacted by the
intensity of the COVID-19 pandemic.
Response: We appreciate these commenters' support. Based on the
revised impact analysis discussed in section VI.C.3 of this final rule,
we continue to believe that the FY 2019 claims are the best available
data for estimating FY 2021 and FY 2022 payments.
Final Decision: We are finalizing as proposed to use the June 2020
update of the FY 2019 IPF claims for updating the outlier fixed dollar
loss threshold.
Based on an analysis of the June 2020 update of FY 2019 IPF claims
and the FY 2021 rate increases, we believe it is necessary to update
the fixed dollar loss threshold amount to maintain an outlier
percentage that equals 2 percent of total estimated IPF PPS payments.
We are finalizing our proposal to update the IPF outlier threshold
amount for FY 2022 using FY 2019 claims data and the same methodology
that we used to set the initial outlier threshold amount in the RY 2007
IPF PPS final rule (71 FR 27072 and 27073), which is also the same
methodology that we used to update the outlier threshold amounts for
years 2008 through 2021. Based on an analysis of these updated data, we
estimate that IPF outlier payments as a percentage of total estimated
payments are approximately 1.9 percent in FY 2021. Therefore, we are
finalizing our proposal to update the outlier threshold amount to
$14,470 to maintain estimated outlier payments at 2 percent of total
estimated aggregate IPF payments for FY 2022. This final update is a
decrease from the FY 2021 threshold of $14,630. In contrast, using the
FY 2020 claims to estimate payments, the final outlier fixed dollar
loss threshold for FY 2022 would be $22,720, which would have been an
increase from the FY 2021 threshold of $14,630. We refer the reader to
section VI.C.3 of this final rule for a detailed discussion of the
estimated impacts of the final update to the outlier fixed dollar loss
threshold.
We note that our use of the FY 2019 claims to set the final outlier
fixed dollar loss threshold for FY 2022 deviates from what has been our
longstanding practice of using the most recent available year of
claims, which is FY 2020 data. However, we are finalizing this policy
in a way that remains otherwise consistent with the
[[Page 42624]]
established outlier update methodology. As discussed in this section
and in section VI.C.3 of this final rule, we are finalizing our
proposal to update the outlier fixed dollar loss threshold based on FY
2019 IPF claims in order to maintain the appropriate outlier percentage
in FY 2022. We are finalizing our proposal to deviate from our
longstanding practice of using the most recent available year of claims
only because, and to the extent that, the COVID-19 PHE appears to have
significantly impacted the FY 2020 IPF claims. As discussed in section
VI.C.3 of this final rule, we have analyzed more recent available IPF
claims data and continue to believe that using FY 2019 IPF claims is
appropriate for the FY 2022 update. We intend to continue to analyze
further data in order to better understand both the short-term and
long-term effects of the COVID-19 PHE on IPFs.
3. Final Update to IPF Cost-to-Charge Ratio Ceilings
Under the IPF PPS, an outlier payment is made if an IPF's cost for
a stay exceeds a fixed dollar loss threshold amount plus the IPF PPS
amount. In order to establish an IPF's cost for a particular case, we
multiply the IPF's reported charges on the discharge bill by its
overall cost-to-charge ratio (CCR). This approach to determining an
IPF's cost is consistent with the approach used under the IPPS and
other PPSs. In the FY 2004 IPPS final rule (68 FR 34494), we
implemented changes to the IPPS policy used to determine CCRs for IPPS
hospitals, because we became aware that payment vulnerabilities
resulted in inappropriate outlier payments. Under the IPPS, we
established a statistical measure of accuracy for CCRs to ensure that
aberrant CCR data did not result in inappropriate outlier payments.
As we indicated in the November 2004 IPF PPS final rule (69 FR
66961), we believe that the IPF outlier policy is susceptible to the
same payment vulnerabilities as the IPPS; therefore, we adopted a
method to ensure the statistical accuracy of CCRs under the IPF PPS.
Specifically, we adopted the following procedure in the November 2004
IPF PPS final rule:
Calculated two national ceilings, one for IPFs located in
rural areas and one for IPFs located in urban areas.
Computed the ceilings by first calculating the national
average and the standard deviation of the CCR for both urban and rural
IPFs using the most recent CCRs entered in the most recent Provider
Specific File (PSF) available.
For FY 2022, we are finalizing our proposal to continue to follow
this methodology.
To determine the rural and urban ceilings, we multiplied each of
the standard deviations by 3 and added the result to the appropriate
national CCR average (either rural or urban). The upper threshold CCR
for IPFs in FY 2022 is 2.0261 for rural IPFs, and 1.6879 for urban
IPFs, based on CBSA-based geographic designations. If an IPF's CCR is
above the applicable ceiling, the ratio is considered statistically
inaccurate, and we assign the appropriate national (either rural or
urban) median CCR to the IPF.
We apply the national median CCRs to the following situations:
New IPFs that have not yet submitted their first Medicare
cost report. We continue to use these national median CCRs until the
facility's actual CCR can be computed using the first tentatively or
final settled cost report.
IPFs whose overall CCR is in excess of three standard
deviations above the corresponding national geometric mean (that is,
above the ceiling).
Other IPFs for which the MAC obtains inaccurate or
incomplete data with which to calculate a CCR.
We are finalizing our proposal to continue to update the FY 2022
national median and ceiling CCRs for urban and rural IPFs based on the
CCRs entered in the latest available IPF PPS PSF. Specifically, for FY
2022, to be used in each of the three situations listed previously,
using the most recent CCRs entered in the CY 2021 PSF, we provide an
estimated national median CCR of 0.5720 for rural IPFs and a national
median CCR of 0.4200 for urban IPFs. These calculations are based on
the IPF's location (either urban or rural) using the CBSA-based
geographic designations. A complete discussion regarding the national
median CCRs appears in the November 2004 IPF PPS final rule (69 FR
66961 through 66964).
IV. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program
A. Background and Statutory Authority
We refer readers to the FY 2019 IPF PPS final rule (83 FR 38589)
for a discussion of the background and statutory authority \1\ of the
IPFQR Program.
---------------------------------------------------------------------------
\1\ We note that the statute uses the term ``rate year'' (RY).
However, beginning with the annual update of the inpatient
psychiatric facility prospective payment system (IPF PPS) that took
effect on July 1, 2011 (RY 2012), we aligned the IPF PPS update with
the annual update of the ICD codes, effective on October 1 of each
year. This change allowed for annual payment updates and the ICD
coding update to occur on the same schedule and appear in the same
Federal Register document, promoting administrative efficiency. To
reflect the change to the annual payment rate update cycle, we
revised the regulations at 42 CFR 412.402 to specify that, beginning
October 1, 2012, the IPF PPS RY means the 12-month period from
October 1 through September 30, which we refer to as a ``fiscal
year'' (FY) (76 FR 26435). Therefore, with respect to the IPFQR
Program, the terms ``rate year,'' as used in the statute, and
``fiscal year'' as used in the regulation, both refer to the period
from October 1 through September 30. For more information regarding
this terminology change, we refer readers to section III. of the RY
2012 IPF PPS final rule (76 FR 26434 through 26435).
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B. Covered Entities
In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645), we
established that the IPFQR Program's quality reporting requirements
cover those psychiatric hospitals and psychiatric units paid under
Medicare's IPF PPS (Sec. 412.404(b)). Generally, psychiatric hospitals
and psychiatric units within acute care and critical access hospitals
that treat Medicare patients are paid under the IPF PPS. Consistent
with previous regulations, we continue to use the terms ``facility'' or
IPF to refer to both inpatient psychiatric hospitals and psychiatric
units. This usage follows the terminology in our IPF PPS regulations at
Sec. 412.402. For more information on covered entities, we refer
readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645).
C. Previously Finalized Measures and Administrative Procedures
The current IPFQR Program includes 14 measures. For more
information on these measures, we refer readers to Table 5 of this
final rule and the following final rules:
The FY 2013 IPPS/LTCH PPS final rule (77 FR 53646 through
53652);
The FY 2014 IPPS/LTCH PPS final rule (78 FR 50889 through
50897);
The FY 2015 IPF PPS final rule (79 FR 45963 through
45975);
The FY 2016 IPF PPS final rule (80 FR 46695 through
46714);
The FY 2017 IPPS/LTCH PPS final rule (81 FR 57238 through
57247);
The FY 2019 IPF PPS final rule (83 FR 38590 through
38606); and
The FY 2020 IPF PPS final rule (84 FR 38459 through
38467).
For more information on previously adopted procedural requirements,
we refer readers to the following rules:
The FY 2013 IPPS/LTCH PPS final rule (77 FR 53653 through
53660);
The FY 2014 IPPS/LTCH PPS final rule (78 FR 50897 through
50903);
The FY 2015 IPF PPS final rule (79 FR 45975 through
45978);
The FY 2016 IPF PPS final rule (80 FR 46715 through
46719);
[[Page 42625]]
The FY 2017 IPPS/LTCH PPS final rule (81 FR 57248 through
57249);
The FY 2018 IPPS/LTCH PPS final rule (82 FR 38471 through
38474);
The FY 2019 IPF PPS final rule (83 FR 38606 through
38608); and
The FY 2020 IPF PPS final rule (84 FR 38467 through
38468).
D. Closing the Health Equity Gap in CMS Quality Programs--Request for
Information (RFI)
Persistent inequities in health care outcomes exist in the U.S.,
including among Medicare patients. In recognition of persistent health
disparities and the importance of closing the health equity gap, we
requested 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 facilities,
providers, and patients. The RFI that was included in the proposed rule
is part of an ongoing effort across CMS to evaluate appropriate
initiatives to reduce health disparities. Feedback will be used to
inform the creation of a future, comprehensive, RFI focused on closing
the health equity gap in CMS programs and policies.
The RFI contained four parts:
Background: This section provided information describing
our commitment to health equity, and existing initiatives with an
emphasis on reducing health disparities.
Current CMS Disparity Methods: This section described the
methods, measures, and indicators of social risk currently used with
the CMS Disparity Methods.
Future potential stratification of quality measure
results: This section described four potential future expansions of the
CMS Disparity Methods, including (1) Stratification of Quality Measure
Results--Dual Eligibility; (2) Stratification of Quality Measure
Results--Race and Ethnicity; (3) Improving Demographic Data Collection;
and (4) Potential Creation of a Facility Equity Score to Synthesize
Results Across Multiple Social Risk Factors.
Solicitation of public comment: This section specified 12
requests for feedback on these topics. We reviewed feedback on these
topics and note our intention for an additional RFI or rulemaking on
this topic in the future.
1. Background
Significant and persistent inequities in health care outcomes exist
in the U.S. 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; living in a rural area; or
being near or below the poverty level, is often associated with worse
health outcomes.2 3 4 5 6 7 8 9 Such disparities in health
outcomes are the result of 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.10 11 12 13 14 15 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.16 17 18 19 20 Studies have also shown that
African Americans are significantly more likely than white Americans to
die prematurely from heart disease, and stroke.\21\ 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.22 23 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.'' \24\ One
important strategy for addressing these important inequities is
improving data collection to allow for better measurement and reporting
on equity across our programs and policies.
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\2\ 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.
\3\ 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.
\4\ 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.
\5\ 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.
\6\ Rural Health Research Gateway. Rural Communities: Age,
Income, and Health Status. Rural Health Research Recap. November
2018.
\7\ https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf.
\8\ www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm.
\9\ 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.
\10\ 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.
\11\ 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.
\12\ 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.
\13\ 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.
\14\ 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.
\15\ 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.
\16\ 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.
\17\ Centers for Medicare and Medicaid Services. Medicare
Hospital Quality Chartbook: Performance Report on Outcome Measures;
2014.
\18\ 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.
\19\ 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.
\20\ 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.
\21\ HHS. Heart disease and African Americans. (March 29, 2021).
https://www.minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=19.
\22\ https://www.cms.gov/files/document/medicare-covid-19-data-snapshot-fact-sheet.pdf.
\23\ 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/.
\24\ https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/race-ethnicity.html.
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We are 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.\25\ For the purposes of this final rule, we are using
a definition of equity established in
[[Page 42626]]
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.'' \26\ 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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\25\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
\26\ 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 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) in their efforts to engage with
and assist providers that care for vulnerable populations; Federal,
state, local, and tribal organizations; providers; researchers;
policymakers; beneficiaries and their families; and other stakeholders
in activities to achieve health equity.\27\ The CMS Equity Plan for
Improving Quality in Medicare focuses on three core priority areas
which inform our policies and programs: (1) Increasing understanding
and awareness of health disparities; (2) developing and disseminating
solutions to achieve health equity; and (3) implementing sustainable
actions to achieve health equity.\28\ The CMS Quality Strategy \29\ and
Meaningful Measures Framework \30\ include elimination of racial and
ethnic disparities as a central principle. Our efforts aimed at closing
the health equity gap to date have included providing transparency
about health disparities, supporting providers with evidence-informed
solutions to achieve health equity, and reporting to providers on gaps
in quality through the following reports and programs:
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\27\ Centers for Medicare and Medicaid Services Office of
Minority Health. The CMS Equity Plan for Improving Quality in
Medicare. 2015. https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH_Dwnld-CMS_EquityPlanforMedicare_090615.pdf.
\28\ Centers for Medicare and Medicaid Services Office of
Minority Health. The CMS Equity Plan for Improving Quality in
Medicare. 2015. https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH_Dwnld-CMS_EquityPlanforMedicare_090615.pdf.
\29\ Centers for Medicare Services. CMS Quality Strategy. 2016.
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
\30\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
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The CMS Mapping Medicare Disparities Tool, which is an
interactive map that identifies areas of disparities and a starting
point to understand and investigate geographical, racial and ethnic
differences in health outcomes for Medicare patients.\31\
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\31\ https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH-Mapping-Medicare-Disparities.
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The Racial, Ethnic, and Gender Disparities in Health Care
in Medicare Advantage Stratified Report, which highlights racial and
ethnic differences in health care experiences and clinical care,
compares quality of care for women and men, and looks at racial and
ethnic differences in quality of care among women and men separately
for Medicare Advantage plans.\32\
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\32\ https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
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The Rural-Urban Disparities in Health Care in Medicare
Report, which details rural-urban differences in health care
experiences and clinical care.\33\
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\33\ Centers for Medicare and Medicaid Services. Rural-Urban
Disparities in Health Care in Medicare. 2019. https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Rural-Urban-Disparities-in-Health-Care-in-Medicare-Report.pdf.
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The Standardized Patient Assessment Data Elements for
certain post-acute care Quality Reporting Programs, which now includes
data reporting for race and ethnicity and preferred language, in
addition to screening questions for social needs (84 FR 42536 through
42588).
The CMS Innovation Center's Accountable Health Communities
Model, which include standardized data collection of health-related
social needs data.
The Guide to Reducing Disparities which provides an
overview of key issues related to disparities in readmissions and
reviews sets of activities that can help hospital leaders reduce
readmissions in diverse populations.\34\
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\34\ 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.
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The CMS Disparity Methods, which provide hospital-level
confidential results stratified by dual eligibility for condition-
specific readmission measures currently included in the Hospital
Readmission Reduction Program (84 FR 42496 through 42500).
These programs are informed by reports by the National Academies of
Science, Engineering and Medicine (NASEM) \35\ and the Office of the
Assistant Secretary for Planning and Evaluation (ASPE) \36\ which have
examined the influence of social risk factors on several of our quality
programs. In this RFI, we addressed only the seventh initiative listed,
the CMS Disparity Methods, which we have implemented for measures in
the Hospital Readmissions Reduction Program and are considering in
other programs, including the IPFQR Program. We discussed the
implementation of these methods to date and present considerations for
continuing to improve and expand these methods to provide providers and
ultimately consumers with actionable information on disparities in
health care quality to support efforts at closing the equity gap.
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\35\ National Academies of Sciences, Engineering, and Medicine.
2016. Accounting for Social Risk Factors in Medicare Payment:
Identifying Social Risk Factors. Washington, DC: The National
Academies Press. https://doi.org/10.17226/21858.
\36\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
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2. Current CMS Disparity Methods
We first sought public comment on potential confidential and public
reporting of IPFQR program measure data stratified by social risk
factors in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20121). We
initially focused on stratification by dual eligibility, which is
consistent with recommendations from ASPE's First Report to Congress
which was required by the Improving Medicare Post-Acute Care
Transformation (IMPACT) Act of 2014 (Pub. L. 113-185).\37\ This report
found that in the context of value-based purchasing (VBP) programs,
dual eligibility was among the most powerful predictors of poor health
outcomes
[[Page 42627]]
among those social risk factors that ASPE examined and tested.
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\37\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
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In the FY 2018 IPPS/LTCH PPS final rule we also solicited feedback
on two potential methods for illuminating differences in outcomes rates
among patient groups within a provider's patient population that would
also allow for a comparison of those differences, or disparities,
across providers for the Hospital IQR Program (82 FR 38403 through
38409). The first method (the Within-Hospital disparity method)
promotes quality improvement by calculating differences in outcome
rates among patient groups within a hospital while accounting for their
clinical risk factors. This method also allows for a comparison of the
magnitude of disparity across hospitals, permitting hospitals to assess
how well they are closing disparity gaps compared to other hospitals.
The second methodological approach (the Across-Hospital method) is
complementary and assesses hospitals' outcome rates for dual-eligible
patients only, across hospitals, allowing for a comparison among
hospitals on their performance caring for their patients with social
risk factors. In the FY 2018 IPPS/LTCH PPS proposed rule under the
IPFQR Program (82 FR 20121), we also specifically solicited feedback on
which social risk factors provide the most valuable information to
stakeholders. Overall, comments supported the use of dual eligibility
as a proxy for social risk, although commenters also suggested
investigation of additional social risk factors, and we continue to
consider which risk factors provide the most valuable information to
stakeholders.
Concurrent with our comment solicitation on stratification in the
IPFQR Program, we have considered methods for stratifying measure
results for other quality reporting programs. For example, in the FY
2019 IPPS/LTCH PPS final rule (82 FR 41597 through 41601), we finalized
plans to provide confidential hospital-specific reports (HSRs)
containing stratified results of the Pneumonia Readmission (NQF #0506)
and Pneumonia Mortality (NQF #0468) measures including both the Across-
Hospital Disparity Method and the Within-Hospital Disparity Method
(disparity methods), stratified by dual eligibility. In the FY 2019
IPPS/LTCH PPS final rule (83 FR 41554 through 41556), we also removed
six condition/procedure specific readmissions measures, including the
Pneumonia Readmission measure (NQF #0506) and five mortality measures,
including the Pneumonia Mortality measure (NQF #0468) (83 FR 41556
through 41558) from the Hospital IQR Program. However, the Pneumonia
Readmission (NQF #0506) and the other condition/procedure readmissions
measures remained in the Hospital Readmissions Reduction Program. In
2019, we provided hospitals with results of the Pneumonia Readmission
measure (NQF#0506) stratified using dual eligibility. We provided this
information in annual confidential HSRs for claims-based measures.
We then, in the FY 2020 IPPS/LTCH PPS Final Rule (84 FR 42388
through 42390), finalized the proposal to provide confidential hospital
specific reports (HSRs) containing data stratified by dual-eligible
status for all six readmission measures included in the Hospital
Readmission Reduction Program.
3. Potential Expansion of the CMS Disparity Methods
We are committed to advancing health equity by improving data
collection to better measure and analyze disparities across programs
and policies.\38\ As we previously noted, we have been considering,
among other things, expanding our efforts to provide stratified data
for additional social risk factors and measures, optimizing the ease-
of-use of the results, enhancing public transparency of equity results,
and building towards provider accountability for health equity. We
sought public comment on the potential stratification of quality
measures in the IPFQR Program across two social risk factors: Dual
eligibility and race/ethnicity.
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\38\ Centers for Medicare Services. CMS Quality Strategy. 2016.
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
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a. Stratification of Quality Measure Results--Dual Eligibility
As described previously in this section, landmark reports by the
National Academies of Science, Engineering and Medicine (NASEM) \39\
and the Office of the Assistant Secretary for Planning and Evaluation
(ASPE),\40\ which have examined the influence of social risk factors on
several of our quality programs, have shown that in the context of
value-based purchasing (VBP) programs, dual eligibility, as an
indicator of social risk, is a powerful predictor of poor health
outcomes. We noted that the patient population of IPFs has a higher
percentage of dually eligible patients than the general Medicare
population. Specifically, over half (56 percent) of Medicare patients
in IPFs are dually eligible \41\ while approximately 20 percent of all
Medicare patients are dually eligible.\42\ We are considering
stratification of quality measure results in the IPFQR Program and are
considering which measures would be most appropriate for stratification
and if dual eligibility would be a meaningful social risk factor for
stratification.
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\39\ National Academies of Sciences, Engineering, and Medicine.
2016. Accounting for Social Risk Factors in Medicare Payment:
Identifying Social Risk Factors. Washington, DC: The National
Academies Press. https://doi.org/10.17226/21858.
\40\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
\41\ https://aspe.hhs.gov/basic-report/transitions-care-and-service-use-among-medicare-beneficiaries-inpatient-psychiatric-facilities-issue-brief.
\42\ https://www.cms.gov/Medicare-Medicaid-Coordination/Medicare-and-Medicaid-Coordination/Medicare-Medicaid-Coordination-Office/DataStatisticalResources/Downloads/MedicareMedicaidDualEnrollmentEverEnrolledTrendsDataBrief2006-2018.pdf.
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For the IPFQR Program, we would consider disparity reporting using
two disparity methods derived from the Within-Hospital and Across-
Hospital methods, described in section IV.D.2 of this final rule. The
first method (based on the Within-Facility disparity method) would aim
to promote quality improvement by calculating differences in outcome
rates between dual and non-dual eligible patient groups within a
facility while accounting for their clinical risk factors. This method
would allow for a comparison of those differences, or disparities,
across facilities, so facilities could assess how well they are closing
disparity gaps compared to other facilities. The second approach (based
on the Across-Facility method) would be complementary and assesses
facilities' outcome rates for subgroups of patients, such as dual
eligible patients, across facilities, allowing for a comparison among
facilities on their performance caring for their patients with social
risk factors.
b. Stratification of Quality Measure Results--Race and Ethnicity
The Administration's Executive Order on Advancing Racial Equity and
Support for Underserved Communities Through the Federal Government
directs agencies to assess potential barriers that underserved
communities and individuals may face to enrollment in and access to
benefits and services in Federal Programs. As summarized in section
IV.D of this final rule, studies have shown that among Medicare
beneficiaries, racial and ethnic minority persons often experience
worse health outcomes, including more frequent hospital readmissions
and operative
[[Page 42628]]
complications. An important part of identifying and addressing
inequities in health care is improving data collection to allow us to
better measure and report on equity across our programs and policies.
We are considering stratification of quality measure results in the
IPFQR Program by race and ethnicity and are considering which measures
would be most appropriate for stratification.
As outlined in the 1997 Office of Management and Budget (OMB)
Revisions to the Standards for the Collection of Federal Data on Race
and Ethnicity, the racial and ethnic categories, which may be used for
reporting the disparity methods are considered to be social and
cultural, not biological or genetic.\43\ The 1997 OMB Standard lists
five minimum categories of race: (1) American Indian or Alaska Native;
(2) Asian; (3) Black or African American; (4) Native Hawaiian or Other
Pacific Islander; (5) and White. In the OMB standards, Hispanic or
Latino is the only ethnicity category included, and since race and
ethnicity are two separate and distinct concepts, persons who report
themselves as Hispanic or Latino can be of any race.\44\ Another
example, the ``Race & Ethnicity--CDC'' code system in Public Health
Information Network (PHIN) Vocabulary Access and Distribution System
(VADS) \45\ permits a much more granular structured recording of a
patient's race and ethnicity with its inclusion of over 900 concepts
for race and ethnicity. The recording and exchange of patient race and
ethnicity at such a granular level can facilitate the accurate
identification and analysis of health disparities based on race and
ethnicity. Further, the ``Race & Ethnicity--CDC'' code system has a
hierarchy that rolls up to the OMB minimum categories for race and
ethnicity and, thus, supports aggregation and reporting using the OMB
standard. ONC includes both the CDC and OMB standards in its criterion
for certified health IT products.\46\ For race and ethnicity, a
certified health IT product must be able to express both detailed races
and ethnicities using any of the 900 plus concepts in the ``Race &
Ethnicity--CDC'' code system in the PHIN VADS, as well as aggregate
each one of a patient's races and ethnicities to the categories in the
OMB standard for race and ethnicity. This approach can reduce burden on
providers recording demographics using certified products.
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\43\ Executive Office of the President Office of Management and
Budget, Office of Information and Regulatory Affairs. Revisions to
the standards for the classification of Federal data on race and
ethnicity. Vol 62. Federal Register. 1997:58782-58790
\44\ https://www.census.gov/topics/population/hispanic-origin/about.html.
\45\ https://phinvads.cdc.gov/vads/ViewValueSet.action?id=67D34BBC-617F-DD11-B38D-00188B398520.
\46\ ONC criteria for certified health IT products: https://www.healthit.gov/isa/representing-patient-race-and-ethnicity.
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Self-reported race and ethnicity data remain the gold standard for
classifying an individual according to race or ethnicity. However, CMS
does not consistently collect self-reported race and ethnicity for the
Medicare program, but instead gets the data from the Social Security
Administration (SSA) and the data accuracy and comprehensiveness have
proven challenging despite capabilities in the marketplace via
certified health IT products. Historical inaccuracies in Federal data
systems and limited collection classifications have contributed to the
limited quality of race and ethnicity information in Medicare's
administrative data systems.\47\ In recent decades, to address these
data quality issues, we have undertaken numerous initiatives, including
updating data taxonomies and conducting direct mailings to some
beneficiaries to enable more comprehensive race and ethnic
identification.48 49 Despite those efforts, studies reveal
varying data accuracy in identification of racial and ethnic groups in
Medicare administrative data, with higher sensitivity for correctly
identifying White and Black individuals, and lower sensitivity for
correctly identifying individuals of Hispanic ethnicity or of Asian/
Pacific Islander and American Indian/Alaskan Native race.\50\
Incorrectly classified race or ethnicity may result in overestimation
or underestimation in the quality of care received by certain groups of
beneficiaries.
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\47\ Eicheldinger, C., & Bonito, A. (2008). More accurate racial
and ethnic codes for Medicare administrative data. Health Care
Financing Review, 29(3), 27-42.
\48\ Filice CE, Joynt KE. Examining Race and Ethnicity
Information in Medicare Administrative Data. Med Care.
2017;55(12):e170-e176. doi:10.1097/MLR.0000000000000608.
\49\ Eicheldinger, C., & Bonito, A. (2008). More accurate racial
and ethnic codes for Medicare administrative data. Health Care
Financing Review, 29(3), 27-42.
\50\ 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.
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We continue to work with Federal and private partners to better
collect and 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
\51\ and supported collection of specialized International
Classification of Disease, 10th Revision, Clinical Modification (ICD-
10-CM) codes for describing the socioeconomic, cultural, and
environmental determinants of health, and sponsored several initiatives
to statistically estimate race and ethnicity information when it is
absent.\52\ The Office of the National Coordinator for Health
Information Technology (ONC) included social, psychological, and
behavioral standards in the 2015 Edition health information technology
(IT) certification criteria (2015 Edition), providing interoperability
standards (LOINC (Logical Observation Identifiers Names and Codes) and
SNOMED CT (Systematized Nomenclature of Medicine--Clinical Terms)) for
financial strain, education, social connection and isolation, and
others. Additional stakeholder efforts underway to expand capabilities
to capture additional social determinants of health data elements
include the Gravity Project to identify and harmonize social risk
factor data for interoperable electronic health information exchange
for EHR fields, as well as proposals to expand the ICD-10
(International Classification of Diseases, Tenth Revision) Z codes, the
alphanumeric codes used worldwide to represent diagnoses.\53\
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\51\ 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.
\52\ https://pubmed.ncbi.nlm.nih.gov/18567241/, https://pubmed.ncbi.nlm.nih.gov/30506674/, Eicheldinger C, Bonito A. More
accurate racial and ethnic codes for Medicare administrative data.
Health Care Finance Rev. 2008;29(3):27-42. Haas A, Elliott MN,
Dembosky JW, et al. Imputation of race/ethnicity to enable
measurement of HEDIS performance by race/ethnicity. Health Serv Res.
2019;54(1):13-23. doi:10.1111/1475-6773.13099.
\53\ https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress.
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While development of sustainable and consistent programs to collect
data on social determinants of health can be considerable undertakings,
we recognize that another method to identify better race and ethnicity
data is needed in the short term to address the need for reporting on
health equity. In working with our contractors, two algorithms have
been developed to indirectly estimate the race and ethnicity of
Medicare beneficiaries (as described further in the following
paragraphs). We feel that using indirect estimation can
[[Page 42629]]
help to overcome the current limitations of demographic information and
enable timelier reporting of equity results until longer term
collaborations to improve demographic data quality across the health
care sector materialize. The use of indirectly estimated race and
ethnicity for conducting stratified reporting does not place any
additional collection or reporting burdens on facilities as these data
are derived using existing administrative and census-linked data.
Indirect estimation relies on a statistical imputation method for
inferring a missing variable or improving an imperfect administrative
variable using a related set of information that is more readily
available.\54\ Indirectly estimated data are most commonly used at the
population level (such as the facility or health plan-level), where
aggregated results form a more accurate description of the population
than existing, imperfect data sets. These methods often estimate race
and ethnicity using a combination of other data sources which are
predictive of self-identified race and ethnicity, such as language
preference, information about race and ethnicity in our administrative
records, first and last names matched to validated lists of names
correlated to specific national origin groups, and the racial and
ethnic composition of the surrounding neighborhood. Indirect estimation
has been used in other settings to support population-based equity
measurement when self-identified data are not available.\55\
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\54\ IOM. 2009. Race, Ethnicity, and Language Data:
Standardization for Health Care Quality Improvement. Washington, DC:
The National Academies Press.
\55\ IOM. 2009. Race, Ethnicity, and Language Data:
Standardization for Health Care Quality Improvement. Washington, DC:
The National Academies Press.
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As described in section IV.D.2, we have previously supported the
development of two such methods of indirect estimation of race and
ethnicity of Medicare beneficiaries. One indirect estimation approach,
developed by our contractor, uses Medicare administrative data, first
name and surname matching, derived from the U.S. Census and other
sources, with beneficiary language preference, state of residence, and
the source of the race and ethnicity code in Medicare administrative
data to reclassify some beneficiaries as Hispanic or Asian/Pacific
Islander (API).\56\ In recent years, we have also worked with another
contractor to develop a new approach, the Medicare Bayesian Improved
Surname Geocoding (MBISG), which combines Medicare administrative data,
first and surname matching, geocoded residential address linked to the
2010 U.S. Census, and uses both Bayesian updating and multinomial
logistic regression to estimate the probability of belonging to each of
six racial/ethnic groups.\57\
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\56\ Bonito AJ, Bann C, Eicheldinger C, Carpenter L. Creation of
New Race-Ethnicity Codes and Socioeconomic Status (SES) Indicators
for Medicare Beneficiaries. Final Report, Sub-Task 2. (Prepared by
RTI International for the Centers for Medicare and Medicaid Services
through an interagency agreement with the Agency for Healthcare
Research and Policy, under Contract No. 500-00-0024, Task No. 21)
AHRQ Publication No. 08-0029-EF. Rockville, MD, Agency for
Healthcare Research and Quality. January 2008.
\57\ Haas, A., Elliott, M. et al (2018). Imputation of race/
ethnicity to enable measurement of HEDIS performance by race/
ethnicity. Health Services Research, 54:13-23.
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The MBISG model is currently used to conduct the national,
contract-level, stratified reporting of Medicare Part C & D performance
data for Medicare Advantage Plans by race and ethnicity.\58\ Validation
testing reveals concordances with self-reported race and ethnicity of
0.96 through 0.99 for API, Black, Hispanic, and White beneficiaries for
MBISG version 2.1.\59\ The algorithms under consideration are
considerably less accurate for individuals who self-identify as
American Indian/Alaskan Native or multiracial.\60\ Indirect estimation
can be a statistically reliable approach for calculating population-
level equity results for groups of individuals (such as the facility-
level) and is not intended, nor being considered, as an approach for
inferring the race and ethnicity of an individual.
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\58\ The Office of Minority Health (2020). Racial, Ethnic, and
Gender Disparities in Health Care in Medicare Advantage, The Centers
for Medicare and Medicaid Services, (pg vii). https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
\59\ MBISG 2.1 validation results performed under contract #GS-
10F-0012Y/HHSM-500-2016-00097G). Pending public release of the 2021
Part C and D Performance Data Stratified by Race, Ethnicity, and
Gender Report, available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
\60\ Haas, A., Elliott, M. et al (2018). Imputation of race/
ethnicity to enable measurement of HEDIS performance by race/
ethnicity. Health Services Research, 54:13-23 and Bonito AJ, Bann C,
Eicheldinger C, Carpenter L. Creation of New Race-Ethnicity Codes
and Socioeconomic Status (SES) Indicators for Medicare
Beneficiaries. Final Report, Sub-Task 2. (Prepared by RTI
International for the Centers for Medicare and Medicaid Services
through an interagency agreement with the Agency for Healthcare
Research and Policy, under Contract No. 500-00-0024, Task No. 21)
AHRQ Publication No. 08-0029-EF. Rockville, MD, Agency for
Healthcare Research and Quality. January 2008.
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However, despite the high degree of statistical accuracy of the
indirect estimation algorithms under consideration there remains the
small risk of unintentionally introducing bias. For example, if the
indirect estimation is not as accurate in correctly estimating race and
ethnicity in certain geographies or populations it could lead to some
bias in the method results. Such bias might result in slight
overestimation or underestimation of the quality of care received by a
given group. We feel this amount of bias is considerably less than
would be expected if stratified reporting was conducted using the race
and ethnicity currently contained in our administrative data. Indirect
estimation of race and ethnicity is envisioned as an intermediate step,
filling the pressing need for more accurate demographic information for
the purposes of exploring inequities in service delivery, while
allowing newer approaches, as described in the next section, for
improving demographic data collection to progress. We expressed
interest in learning more about, and solicited comments about, the
potential benefits and challenges associated with measuring facility
equity using an imputation algorithm to enhance existing administrative
data quality for race and ethnicity until self-reported information is
sufficiently available.
c. Improving Demographic Data Collection
Stratified facility-level reporting using dual eligibility and
indirectly estimated race and ethnicity would represent an important
advance in our ability to provide equity reports to facilities.
However, self-reported race and ethnicity data remain the gold standard
for classifying an individual according to race or ethnicity. The CMS
Quality Strategy outlines our commitment to strengthening
infrastructure and data systems by ensuring that standardized
demographic information is collected to identify disparities in health
care delivery outcomes.\61\ Collection and sharing of a standardized
set of social, psychological, and behavioral data by facilities,
including race and ethnicity, using electronic data definitions which
permit nationwide, interoperable health information exchange, can
significantly enhance the accuracy and robustness of our equity
reporting.\62\ This could potentially include expansion to
[[Page 42630]]
additional social risk factors, such as disability status, where
accuracy of administrative data is currently limited. We are mindful
that additional resources, including data collection and staff training
may be necessary to ensure that conditions are created whereby all
patients are comfortable answering all demographic questions, and that
individual preferences for non-response are maintained.
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\61\ The Centers for Medicare & Medicaid Services. CMS Quality
Strategy. 2016. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
\62\ The Office of the National Coordinator for Health
Information Technology. United State Core Data for Interoperability
Draft Version 2. 2021. https://www.healthit.gov/isa/sites/isa/files/2021-01/Draft-USCDI-Version-2-January-2021-Final.pdf.
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We are also interested in learning about and solicited comments on
current data collection practices by facilities to capture demographic
data elements (such as race, ethnicity, sex, sexual orientation and
gender identity (SOGI), primary language, and disability status).
Further, we are interested in potential challenges facing facility
collection, at the time of admission, of a minimum set of demographic
data elements in alignment with national data collection standards
(such as the standards finalized by the Affordable Care Act) \63\ and
standards for interoperable exchange (such as the U.S. Core Data for
Interoperability incorporated into certified health IT products as part
of the 2015 Edition of health IT certification criteria).\64\ Advancing
data interoperability through collection of a minimum set of
demographic data collection, and incorporation of this demographic
information into quality measure specifications, has the potential for
improving the robustness of the disparity method results, potentially
permitting reporting using more accurate, self-reported information,
such as race and ethnicity, and expanding reporting to additional
dimensions of equity, including stratified reporting by disability
status.
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\63\ https://minorityhealth.hhs.gov/assets/pdf/checked/1/Fact_Sheet_Section_4302.pdf.
\64\ https://www.healthit.gov/sites/default/files/2020-08/2015EdCures_Update_CCG_USCDI.pdf.
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d. Potential Creation of a Facility Equity Score To Synthesize Results
Across Multiple Social Risk Factors
As we describe in section IV.D.3.a of this final rule, we are
considering expanding the disparity methods to IPFs and to include two
social risk factors (dual eligibility and race/ethnicity). This
approach would improve the comprehensiveness of health equity
information provided to facilities. Aggregated results from multiple
measures and multiple social risk factors, from the CMS Disparity
Methods, in the format of a summary score, can improve the usefulness
of the equity results. In working with our contractors, we recently
developed an equity summary score for Medicare Advantage contract/
plans, the Health Equity Summary Score (HESS), with application to
stratified reporting using two social risk factors: Dual eligibility
and race and as described in Incentivizing Excellent Care to At-Risk
Groups with a Health Equity Summary Score.\65\
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\65\ Agniel D, Martino SC, Burkhart Q, et al. Incentivizing
Excellent Care to At-Risk Groups with a Health Equity Summary Score.
J Gen Intern Med. Published online November 11, 2019 Nov 11. doi:
10.1007/s11606-019-05473-x.
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The HESS calculates standardized and combined performance scores
blended across the two social risk factors. The HESS also combines
results of the within-plan (similar to the Within-Facility method) and
across-plan method (similar to the Across-Facility method) across
multiple performance measures.
We are considering building a ``Facility Equity Score,'' not yet
developed, which would be modeled off the HESS but adapted to the
context of risk-adjusted facility outcome measures and potentially
other IPF quality measures. We envision that the Facility Equity Score
would synthesize results for a range of measures and using multiple
social risk factors, using measures and social risk factors, which
would be reported to facilities as part of the CMS Disparity Methods.
We believe that creation of the Facility Equity Score has the potential
to supplement the overall measure data already reported on the Care
Compare or successor website, by providing easy to interpret
information regarding disparities measured within individual facilities
and across facilities nationally. A summary score would decrease burden
by minimizing the number of measure results provided and providing an
overall indicator of equity.
The Facility Equity Score under consideration would potentially:
Summarize facility performance across multiple social
determinants of health (initially dual eligibility and indirectly
estimated race and ethnicity); and
Summarize facility performance across the two disparity
methods (that is, the Within-Facility Disparity Method and the Across-
Facility Disparity Method) and potentially for multiple measures.
Prior to any future public reporting, if we determine that a
Facility Equity Score can be feasibly and accurately calculated, we
would provide results of the Facility Equity Score, in confidential
facility specific reports, which facilities and their QIN-QIOs would be
able to download. Any potential future proposal to display the Facility
Equity Score on the Care Compare or successor website would be made
through future RFI or rulemaking.
c. Solicitation of Public Comment
We solicited public comments on the possibility of stratifying
IPFQR Program measures by dual eligibility and race and ethnicity. We
also solicited public comments on mechanisms of incorporating co-
occurring disability status into such stratification as well. We sought
public comments on the application of the within-facility or across-
facility disparities methods IPFQR Program measures if we were to
stratify IPFQR Program measures. We also solicited comment on the
possibility of facility collection of standardized demographic
information for the purposes of potential future quality reporting and
measure stratification. In addition, we solicited public comments on
the potential design of a facility equity score for calculating results
across multiple social risk factors and measures, including race and
disability. Any data pertaining to these areas that are recommended for
collection for measure reporting for a CMS program and any potential
public disclosure on Care Compare or successor website would be
addressed through a separate and future notice- and-comment rulemaking.
We plan to continue working with ASPE, facilities, the public, and
other key stakeholders on this important issue to identify policy
solutions that achieve the goals of attaining health equity for all
patients and minimizing unintended consequences. We also noted our
intention for additional RFIs or rulemaking on this topic in the
future.
Specifically, we solicited public comment on the following:
Future Potential Stratification of Quality Measure Results
The possible stratification of facility-specific reports
for IPFQR program measure data by dual-eligibility status given that
over half of the patient population in IPFs are dually eligible,
including, which measures would be most appropriate for stratification;
The potential future application of indirect estimation of
race and ethnicity to permit stratification of measure data for
reporting facility-level disparity results until more accurate forms of
self-identified demographic information are available;
Appropriate privacy safeguards with respect to data
produced from the indirect estimation of race and ethnicity to ensure
that such data are properly
[[Page 42631]]
identified if/when they are shared with providers;
Ways to address the challenges of defining and collecting
accurate and standardized self-identified demographic information,
including information on race and ethnicity and disability, for the
purposes of reporting, measure stratification and other data collection
efforts relating to quality.
Recommendations for other types of readily available data
elements for measuring disadvantage and discrimination for the purposes
of reporting, measure stratification and other data collection efforts
relating to quality, in addition, or in combination with race and
ethnicity.
Recommendations for types of quality measures or
measurement domains to prioritize for stratified reporting by dual
eligibility, race and ethnicity, and disability.
Examples of approaches, methods, research, and
considerations or any combination of these for use of data-driven
technologies that do not facilitate exacerbation of health inequities,
recognizing that biases may occur in methodology or be encoded in
datasets.
We received comments on these topics.
Comments: Many commenters expressed support for the collection of
data to support stratifying or otherwise measuring disparities in care
related to dual-eligibility, race and ethnicity, and disability. Some
commenters specifically supported the confidential reporting of
stratified results to facilities. Several commenters urged CMS to
expand data collection and measure stratification to include factors
such as language preference, veteran status, health literacy, gender
identity, and sexual orientation to provide a more comprehensive
assessment of health equity. One commenter urged CMS to collect data on
race and ethnicity specifically for patients suffering from psychiatric
disorders, while another noted that for the IPF patient population risk
factors, such as substance abuse, may be of more importance. One
commenter also provided examples of how their health system has
successfully collected and begun to analyze patient-level demographic
data. Another commenter referred to an existing effort by the National
Committee for Quality Assurance to improve the collection of race and
ethnicity data as a possible model for improving data collection. This
commenter also supported the use of indirect estimation of race and
ethnicity for Medicare beneficiaries, noting some concern about the
lack of granularity, especially with respect to Native American and
Asian populations. One commenter urged CMS to explore how to best
identify social determinants of health using current claims data.
While many commenters expressed support for stratification of
claims-based measures, many commenters expressed concern that the
existing chart-abstracted measures would face limitations when
stratified and thus felt the burden of collecting stratification data
for these measures significantly outweighed any potential benefit of
doing so. Specifically, commenters noted that stratifying the IPF
patient population is more vulnerable to statistical concerns during
the stratification process than other patient populations (for example,
numbers of patients in one or more strata may be insufficient for
reliable sampling and calculations) due to low patient volume in some
facilities. One commenter suggested that for this and other reasons CMS
should develop disparities reporting specifically for the IPF program
rather than adopt an approach developed for a different program. A few
commenters also questioned the value of stratification of these
measures given the current high levels of performance by many IPFs.
One commenter noted that stratified claims-based measures would
exclude all privately insured care and thus be less useful. Several
commenters stated that interoperability issues such as a lack of EHRs,
particularly for IPFs that are smaller or not part of a large hospital
or health system, further add to the burden of stratifying chart-
abstracted measures and may contribute to bias in the data.
Several commenters also noted that stratification may be
challenging due to differences in the patient population served by IPFs
compared to other Medicare programs such as acute and long-term care
hospitals, for example, age, proportion and reason for dual-eligibility
(income versus disability), and substance abuse disorder prevalence.
However, several commenters noted many of these same characteristics,
as well as the mental and behavioral health needs of patients cared for
by IPFs, are evidence of the need to improve data collection and
measurement in IPFs. A commenter also recommended further analysis on
the predictive power of social risk factors on mental and behavioral
health patient outcomes compared to that of the diagnosis requiring
treatment. Several commenters recommended CMS further address issues
related to the potential stratification of data such as: Patient
privacy and the collection and sharing of social risk factors from
patient records or through indirect estimation, differing requirements
for collection of race and ethnicity data, transparency regarding
indirect estimation methods, and differing Medicaid eligibility
requirements by state. One commenter related these concerns to public
reporting, suggesting support for confidential reporting until these
issues are addressed.
We appreciate all of the comments and interest in this topic. We
believe that this input is very valuable in the continuing development
of the CMS health equity quality measurement efforts. We will continue
to take all concerns, comments, and suggestions into account for future
development and expansion of our health equity quality measurement
efforts.
Improving Demographic Data Collection
Experiences of users of certified health IT regarding
local adoption of practices for collection of social, psychological,
and behavioral data elements, the perceived value of using these data
for improving decision-making and care delivery, and the potential
challenges and benefits of collecting more granular, structured
demographic information, such as the ``Race & Ethnicity--CDC'' code
system.
The possible collection of a minimum set of social,
psychological, and behavioral data elements by hospitals at the time of
admission using structured, interoperable data standards, for the
purposes of reporting, measure stratification and other data collection
efforts relating to quality.
We received comments on these topics.
Comments: We received mixed feedback regarding demographic data
collection. Many commenters supported the need for and use of such
data, noting that structured, interoperable electronic health data are
the gold standard. They also noted that many barriers exist to adopting
electronic health information technology systems necessary for capture
of these data, particularly in freestanding psychiatric facilities. A
commenter stated that the commenter's organization cannot support
demographic data collection due to the workload burden it would place
on both the IPF and patients and their families. This commenter also
noted that the likelihood of patients and families comfortably
answering multiple sensitive demographic questions is low, especially
upon admission. Another commenter expressed concerns with the current
capabilities of the industry to collect these data, specifying a lack
of standardization in screening and data collection and need for staff
training.
[[Page 42632]]
Multiple commenters expressed concern about the patient and family's
perception of the organization if given a data collection questionnaire
upon admission, noting that they may think the organization is more
focused on data collection rather than care.
Other commenters noted the importance of closing the health equity
gap through measurement of demographic characteristics. A commenter
suggested that agencies leverage the role of nurses in identifying
sociodemographic factors and barriers to health equity. Another
commenter supported this method, noting that although this may add
another step to data collection processes, it would be valuable in
addressing health equity gaps. To reduce possible workload burden on
organizations that are new to this process, a commenter recommended a
staggered approach to data collection, suggesting CMS require providers
and facilities to collect data on age and sex by the end of 2022, race
and ethnicity by the end of 2023, etc., with the goal of at least 80
percent data completeness with 80 percent accuracy. In addition,
commenters suggested reducing burden by adopting standardized screening
tools to collect this information, such as ICD-Z-codes, which in
practice would allow patients to be referred to resources and
initiatives when appropriate. Several commenters encouraged collection
of comprehensive social determinants of health and demographic
information in addition to race and ethnicity, such as disability,
sexual orientation, and primary language. Several commenters provided
feedback on the potential use of an indirect estimation algorithm when
race and ethnicity are missing/incorrect, and emphasized the
sensitivity of demographic information and recommended that CMS use
caution when using estimates from the algorithm, including assessing
for potential bias, reporting the results of indirect estimation
alongside direct self-report at the organizational level for
comparison, and establishing a timeline to transition to entirely
directly collected data. Commenters also advised that CMS be
transparent with beneficiaries and explain why data are being collected
and the plans to use these data. A commenter noted that information
technology infrastructure should be established in advance to ensure
that this information is being used and exchanged appropriately.
We appreciate all of the comments and interest in this topic. We
believe that this input is very valuable in the continuing development
of the CMS health equity quality measurement efforts. We will continue
to take all concerns, comments, and suggestions into account for future
development and expansion of our health equity quality measurement
efforts.
Potential Creation of a Facility Equity Score To Synthesize Results
Across Multiple Social Risk Factors
The possible creation and confidential reporting of a
Facility Equity Score to synthesize results across multiple social risk
factors and disparity measures.
Interventions facilities could institute to improve a low
facility equity score and how improved demographic data could assist
with these efforts.
We received comments on these topics.
Comments: Commenters generally supported ongoing thoughtful
investigation into best practices for measuring health equity.
Many commenters expressed concerns about the potential Facility
Equity Score. Commenters argued that the current approach used to
generate the composite score may not lead to aggregate results, which
would not be actionable for many facilities. Commenters also raised
concerns about risk adjustment, limitations in stratification
variables, and the appropriateness of the current measure set. A
commenter noted that although they support thoughtful efforts to
categorize performance, the HESS has been established only as a ``proof
of concept'' and will require considerable time and resources to
produce a valid and actionable measure. The same commenter also noted
that HESS scoring was only feasible for less than one-half of Medicare
Advantage (MA) plans and as such, may not be practical for many smaller
facilities, or facilities whose enrolled populations differ in social
risk factor distribution patterns compared to typical MA plans.
Commenters generally did not support use of the Facility Equity
Score in public reporting or payment incentive programs, suggesting
that it is imperative to first understand any unintended consequences
prior to implementation. More specifically, several commenters gave the
example of facilities failing to raise the quality of care for at-risk
patients while appearing to achieve greater equity due to lower quality
of care for patients that are not at risk. A commenter stated the
belief that CMS should begin their initiative to improve health equity
by using structural health equity measures. Commenters also raised
concerns about use of dual-eligibility as a social risk factor due to
variations in state-level eligibility for Medicaid, making national
comparisons, or benchmarking of facility scores unreliable.
Additionally, commenters who expressed data reliability concerns
recommended that CMS focus its resources on improving standardized data
collection and reporting procedures for sociodemographic data before
moving forward with a Facility Equity Score.
We appreciate all of the comments and interest in this topic. We
believe that this input is very valuable in the continuing development
of the CMS health equity quality measurement efforts. We will continue
to take all concerns, comments, and suggestions into account for future
development and expansion of our health equity quality measurement
efforts.
We also received comments on the general topic of health equity in
the IPFQR Program.
Comments: Many commenters expressed overall support of CMS' goals
to advance health equity. There were some comments regarding the need
to further extend and specify the definition of equity provided in the
proposed rule. Commenters also noted that equity initiatives should be
based on existing disparities and population health goals, be mindful
of the needs of the communities served, and work to bridge hospitals
with post-acute and community-based providers. Several commenters
encouraged CMS to be mindful about whether collection of additional
quality measures and standardized patient assessment elements might
increase provider burden. Several commenters noted support for
consideration of a measure of organizational commitment to health
equity, outlining how infrastructure supports delivery of equitable
care. A commenter noted the importance of focusing programming on
inequities in vaccine-preventable illness. Another commenter noted that
CMS may expand their view of equity beyond quality reporting to payment
and coverage policies.
We appreciate all of the comments and interest in this topic. We
believe that this input is very valuable in the continuing development
of the CMS health equity quality measurement efforts. We will continue
to take all concerns, comments, and suggestions into account for future
development and expansion of our health equity quality measurement
efforts.
E. Measure Adoption
We strive to put consumers and caregivers first, ensuring they are
empowered to make decisions about their own healthcare along with their
[[Page 42633]]
clinicians using information from data-driven insights that are
increasingly aligned with meaningful quality measures. We support
technology that reduces burden and allows clinicians to focus on
providing high-quality healthcare for their patients. We also support
innovative approaches to improve quality, accessibility, and
affordability of care while paying particular attention to improving
clinicians' and beneficiaries' experiences when interacting with our
programs. In combination with other efforts across the Department of
Health and Human Services (HHS), we believe the IPFQR Program helps to
incentivize facilities to improve healthcare quality and value while
giving patients and providers the tools and information needed to make
the best decisions for them. Consistent with these goals, our objective
in selecting quality measures is to balance the need for information on
the full spectrum of care delivery and the need to minimize the burden
of data collection and reporting. We have primarily focused on measures
that evaluate critical processes of care that have significant impact
on patient outcomes and support CMS and HHS priorities for improved
quality and efficiency of care provided by IPFs. When possible, we also
propose to incorporate measures that directly evaluate patient outcomes
and experience. We refer readers to section VIII.F.4.a. of the FY 2013
IPPS/LTCH PPS final rule (77 FR 53645 through 53646) for a detailed
discussion of the considerations taken into account in selecting
quality measures.
1. Measure Selection Process
Before being proposed for inclusion in the IPFQR Program, measures
are placed on a list of measures under consideration (MUC), which is
published annually on behalf of CMS by the National Quality Forum
(NQF). Following publication on the MUC list, the Measure Applications
Partnership (MAP), a multi-stakeholder group convened by the NQF,
reviews the measures under consideration for the IPFQR Program, among
other Federal programs, and provides input on those measures to the
Secretary. We consider the input and recommendations provided by the
MAP in selecting all measures for the IPFQR Program. In our evaluation
of the IPFQR Program measure set, we identified two measures that we
believe are appropriate for the IPFQR Program.
2. COVID-19 Vaccination Coverage Among Health Care Personnel (HCP)
66 Measure for the FY 2023 Payment Determination and
Subsequent Years
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\66\ This measure was previously titled, ``SARS-CoV-2
Vaccination Coverage among Healthcare Personnel.''
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a. Background
On January 31, 2020, the Secretary declared a PHE for the U.S. in
response to the global outbreak of SARS-CoV-2, a novel (new)
coronavirus that causes a disease named ``coronavirus disease 2019''
(COVID-19).\67\ COVID-19 is a contagious respiratory illness \68\ that
can cause serious illness and death. Older individuals and those with
underlying medical conditions are considered to be at higher risk for
more serious complications from COVID-19.\69\
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\67\ 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.
\68\ 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.
\69\ 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.
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As of April 2, 2021, the U.S. had reported over 30 million cases of
COVID-19 and over 550,000 COVID-19 deaths.\70\ Hospitals and health
systems saw significant surges of COVID-19 patients as community
infection levels increased.\71\ From December 2, 2020 through January
30, 2021, more than 100,000 Americans were in the hospital with COVID-
19 at the same time.\72\
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\70\ Centers for Disease Control and Prevention. (2020). CDC
COVID Data Tracker. Accessed on April 3, 2021 at: https://covid.cdc.gov/covid-data-tracker/#cases_casesper100klast7days.
\71\ 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.
\72\ U.S. Currently Hospitalized [verbar] The COVID Tracking
Project https://covidtracking.com/data/charts/us-currently-hospitalized.
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Evidence indicates that COVID-19 primarily spreads when individuals
are in close contact with one another.\73\ 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.\74\ Thus, the CDC advises that infections mainly
occur through exposure to respiratory droplets when a person is in
close contact with someone who has COVID-19.\75\ Experts believe that
COVID-19 spreads less commonly through contact with a contaminated
surface (although that is not thought to be a common way that COVID-19
spreads),\76\ and that in certain circumstances, infection can occur
through airborne transmission.\77\
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\73\ Centers for Disease Control and Prevention. (2021). How
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
\74\ Centers for Disease Control and Prevention. (2021). How
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
\75\ Centers for Disease Control and Prevention. (2021). How
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
\76\ Centers for Disease Control and Prevention. (2021). How
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
\77\ Centers for Disease Control and Prevention. (2021). How
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
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Subsequent to the publication of the proposed rule, the CDC
confirmed that the three main ways that COVID-19 is spread are: (1)
Breathing in air when close to an infected person who is exhaling small
droplets and particles that contain the virus; (2) Having these small
droplets and particles that contain virus land on the eyes, nose, or
mouth, especially through splashes and sprays like a cough or sneeze;
and (3) Touching eyes, nose, or mouth with hands that have the virus on
them.\78\ 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.\79\ 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
health care personnel (HCP) and patients, or from patient to patient
given the close contact that may occur during the provision of
care.\80\ The CDC has emphasized that health care settings, including
long-term care
[[Page 42634]]
settings, can be high-risk places for COVID-19 exposure and
transmission.\81\
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\78\ Centers for Disease Control and Prevention. (2021). How
COVID-19 Spreads. Accessed on July 15, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
\79\ Centers for Disease Control and Prevention. (2021). When to
Quarantine. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/if-you-are-sick/quarantine.html.
\80\ 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 April 2, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/hcp/faq.html#Transmission.
\81\ 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.\82\ On December 11, 2020, FDA issued the first
Emergency Use Authorization (EUA) for a COVID-19 vaccine in the
U.S.\83\ Subsequently, FDA issued EUAs for additional COVID-19
vaccines.\84\
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\82\ Centers for Disease Control and Prevention. (2020). COVID-
19 Vaccination Program Interim Playbook for Jurisdiction Operations.
Accessed on April 3, 2021 at: https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
\83\ 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. (as reissued on May 10, 2021).
\84\ U.S. Food and Drug Administration. (2020). Moderna COVID-19
Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/144636/download (as reissued on July 7, 2021);
U.S. Food and Drug Administration. (2021). Janssen COVID-19 Vaccine
EUA Letter of Authorization. Available at https://www.fda.gov/media/146303/download (as reissued on June 10, 2021).
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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.\85\
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\85\ 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 (as reissued on May 10, 2021) and
U.S. Food and Drug Administration. (2020). Moderna COVID-19 Vaccine
EUA Letter of Authorization. Available at https://www.fda.gov/media/144636/download (as reissued on July 7, 2021); U.S. Food and Drug
Administration. (2021). Janssen COVID-19 Vaccine EUA Letter of
Authorization. Available at https://www.fda.gov/media/146303/download (as reissued on June 10, 2021).
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As part of its national strategy to address COVID-19, the Biden
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.\86\ 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 HCP providing direct care to patients with
COVID-19, and individuals at highest risk for developing severe illness
from COVID-19.\87\ 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.\88\
Research suggests most states followed this recommendation,\89\ and HCP
began receiving the vaccine in mid-December of 2020.\90\
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\86\ 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/.
\87\ 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.
\88\ 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.
\89\ 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/.
\90\ 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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There are approximately 18 million healthcare workers in the
U.S.\91\ As of April 3, 2021 the CDC reported that over 162 million
doses of COVID-19 vaccine had been administered, and approximately 60
million people had received a complete vaccination course as described
in IV.E.b.i of this final rule.\92\ By July 15, 2021 the CDC reported
that over 336,000,000 doses had been administered, and approximately
160,000,000 people had received a complete vaccination course.\93\
President Biden indicated on March 2, 2021 that the U.S. is on track to
have sufficient vaccine supply for every adult by the end of May
2021.\94\ Subsequent to the publication of the IPF PPS proposed rule,
on June 3, 2021, the White House confirmed that there was sufficient
vaccine supply for all Americans.\95\
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\91\ https://www.cdc.gov/niosh/topics/healthcare/
default.html#:~:text=HEALTHCARE%20WORKERS,-
Related%20Pages&text=Healthcare%20is%20the%20fastest%2Dgrowing,of%20t
he%20healthcare%20work%20force.
\92\ CDC. COVID Data Tracker. COVID-19 Vaccinations in the
United States. Accessed on 4/4/21 at: https://covid.cdc.gov/covid-data-tracker/#vaccinations.
\93\ CDC. COVID Data Tracker. COVID-19 Vaccinations in the
United States. Accessed on 7/6/2021 at: https://covid.cdc.gov/covid-data-tracker/#vaccinations.
\94\ The White House. Remarks by President Biden on the
Administration's COVID-19 Vaccination Efforts. Accessed March 18,
2021 at: https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/03/02/remarks-by-president-biden-on-the-administrations-covid-19-vaccination-efforts/.
\95\ Press Briefing by White House COVID-19 Response Team and
Public Health Officials [verbar] The White House.
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We believe it is important to require that IPFs report HCP
vaccination in their facilities in order to assess whether they are
taking steps to protect health care workers and to help sustain the
ability of IPFs to continue serving their communities throughout the
PHE and beyond. Therefore, we proposed a new measure, COVID-19
Vaccination Coverage Among HCP, beginning with the FY 2023 program
year. For that program year, IPFs would be required to report data on
the measure for the fourth quarter of 2021 (October 1, 2021 through
December 31, 2021). For more information about the reporting period,
see section V.E.2.c of this final rule. The measure would assess the
proportion of an IPF's health care workforce that has been vaccinated
against COVID-19.
Although at the time of the proposed rule, data to show the
effectiveness of COVID-19 vaccines to prevent asymptomatic infection or
transmission of SARS-CoV-2 were limited, we stated our belief that IPFs
should report the level of vaccination among their HCP as part of their
efforts to assess and reduce the risk of transmission of COVID-19
within their facilities. HCP vaccination can potentially reduce illness
that leads to work absence and limit disruptions to care.\96\ Data from
influenza vaccination demonstrates that provider uptake of the vaccine
is associated with that provider recommending vaccination to
patients,\97\ and we believe HCP COVID-19 vaccination in IPFs could
similarly increase uptake among that patient population. We also
believe that publishing the HCP vaccination rates would be helpful to
many patients, including those who are at high-risk for
[[Page 42635]]
developing serious complications from COVID-19, as they choose
facilities from which to seek treatment. Under CMS' Meaningful Measures
Framework, the COVID-19 measure addresses the quality priority of
``Promote Effective Prevention and Treatment of Chronic Disease''
through the Meaningful Measure Area of ``Preventive Care.''
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\96\ Centers for Disease Control and Prevention. Overview of
Influenza Vaccination among Health Care Personnel. October 2020.
(2020) Accessed March 16, 2021 at: https://www.cdc.gov/flu/toolkit/long-term-care/why.htm.
\97\ Measure Application Committee Coordinating Committee
Meeting Presentation. March 15, 2021. (2021) Accessed March 16, 2021
at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
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b. Overview of Measure
The COVID-19 Vaccination Coverage Among HCP measure (``COVID-19 HCP
vaccination measure'') is a process measure developed by the CDC to
track COVID-19 vaccination coverage among HCP in facilities such as
IPFs.
(1). Measure Specifications
The denominator is the number of HCP eligible to work in the IPF
for at least 1 day during the reporting period, excluding persons with
contraindications to COVID-19 vaccination that are described by the
CDC.\98\
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\98\ Centers for Disease Control and Prevention.
Contraindications and precautions. https://www.cdc.gov/vaccines/covid-19/info-by-product/clinical-considerations.html#Contraindications.
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The numerator is the cumulative number of HCP eligible to work in
the IPF for at least 1 day during the reporting period and who received
a completed vaccination course against COVID-19 since the vaccine was
first available or on a repeated interval if revaccination on a regular
basis is needed.\99\ Vaccination coverage for the purposes of this
measure is defined as the estimated percentage of HCP eligible to work
at the IPF for at least 1 day who received a completed vaccination
course. A completed vaccination course may require one or more doses
depending on the EUA for the specific vaccine used.
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\99\ Measure Application Partnership Coordinating Committee
Meeting Presentation. March 15, 2021. (2021) Accessed March 16, 2021
at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
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The finalized specifications for this measure are available at
https://www.cdc.gov/nhsn/nqf/index.html.
(2). Review by the Measure Applications Partnership
The COVID-19 HCP vaccination measure was included on the publicly
available ``List of Measures under Consideration for December 21,
2020,'' \100\ a list of measures under consideration for use in various
Medicare programs. When the Measure Applications Partnership (MAP)
Hospital Workgroup convened on January 11, 2021, it reviewed the MUC
List and the COVID-19 HCP vaccination 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 IPFQR Program measure set by providing transparency about
an important COVID-19 intervention to help prevent infections in HCP
and patients.\101\ The MAP also stated that collecting information on
COVID-19 vaccination coverage among HCP and providing feedback to
facilities would allow facilities to benchmark coverage rates and
improve coverage in their IPF, and that reducing rates of COVID-19 in
HCP may reduce transmission among patients and reduce instances of
staff shortages due to illness.\102\
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\100\ https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94212.
\101\ Measure Applications Partnership. MAP Preliminary
Recommendations 2020-2021. Accessed on January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
\102\ Measure Applications Partnership. MAP Preliminary
Recommendations 2020-2021. Accessed on January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
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In its preliminary recommendations, the MAP Hospital Workgroup did
not support this measure for rulemaking, subject to potential for
mitigation.\103\ To mitigate its concerns, the MAP believed that the
measure needed well-documented evidence, finalized specifications,
testing, and NQF endorsement prior to implementation.\104\
Subsequently, the MAP Coordinating Committee met on January 25, 2021,
and reviewed the COVID-19 Vaccination Coverage Among HCP measure. In
the 2020-2021 MAP Final Recommendations, the MAP offered conditional
support for rulemaking contingent on CMS bringing the measures back to
MAP once the specifications are further refined.\105\ The MAP
specifically stated, ``the incomplete specifications require immediate
mitigation and further development should continue.'' \106\ The
spreadsheet of final recommendations no longer cited concerns regarding
evidence, testing, or NQF endorsement.\107\ In response to the MAP
final recommendation request that CMS bring the measure back to the MAP
once the specifications were further refined, CMS and the CDC met with
MAP Coordinating committee on March 15th. Additional information was
provided to address vaccine availability, alignment of the COVID-19
Vaccination Coverage Among HCP measure as closely as possible with the
data collection for the Influenza HCP vaccination measure (NQF 0431),
and clarification related to how HCP are defined. At this meeting, CMS
and the CDC presented preliminary findings from the testing of the
numerator of COVID-19 Vaccination Coverage Among HCP, which was in
process at that time. These preliminary findings showed numerator data
should be feasible and reliable. Testing of the numerator of the number
of healthcare personnel vaccinated involves a comparison of the data
collected through NHSN and independently reported through the Federal
pharmacy partnership program for delivering vaccination to LTC
facilities. These are two completely independent data collection
systems. In initial analyses of the first month of vaccination, the
number of healthcare workers vaccinated in approximately 1,200
facilities, which had data from both systems, the number of healthcare
personnel vaccinated was highly correlated between these 2 systems with
a correlation coefficient of nearly 90 percent in the second two weeks
of reporting.\108\ The MAP further noted that the measure would add
value to the program measure set by providing visibility into an
important intervention to limit COVID-19 infections in healthcare
personnel and the patients for whom they provide care.\109\
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\103\ Measure Applications Partnership. MAP Preliminary
Recommendations 2020-2021. Accessed on January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
\104\ Measure Applications Partnership. MAP Preliminary
Recommendations 2020-2021. Accessed on January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
\105\ Measure Applications Partnership. 2020-2021 MAP Final
Recommendations. Accessed on February 3, 2021 at: http://www.qualityforum.org/Setting_Priorities/Partnership/Measure_Applications_Partnership.aspx.
\106\ Measure Applications Partnership. 2020-2021 MAP Final
Recommendations. Accessed on February 23, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
\107\ Ibid.
\108\ For more information on testing results and other measure
updates, please see the Meeting Materials (including Agenda,
Recording, Presentation Slides, Summary, and Transcript) of the
March 15, 2021 meeting available at https://www.qualityforum.org/ProjectMaterials.aspx?projectID=75367.
\109\ Measure Applications Partnership. 2020-2021 MAP Final
Recommendations. Accessed on February 23, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
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We value the recommendations of the MAP and considered these
recommendations carefully. Section 1890A(a)(4) of the Act requires the
Secretary to take into consideration input from multi-stakeholder
groups in selecting certain quality and efficiency measures. While we
value input from the MAP, we believe it is important to propose the
measure as quickly as
[[Page 42636]]
possible to address the urgency of the COVID-19 PHE and its impact on
vulnerable populations, including IPFs. We continue to engage with the
MAP to mitigate concerns and appreciate the MAP's conditional support
for the measure.
(3). NQF Endorsement
Under section 1886(s)(4)(D)(i) of the Act, unless the exception of
clause (ii) applies, measures selected for the quality reporting
program must have been endorsed by the entity with a contract under
section 1890(a) of the Act. The NQF currently holds this contract.
Section 1886(s)(4)(D)(ii) of the Act provides an exception to the
requirement for NQF endorsement of measures: In the case of a specified
area or medical topic determined appropriate by the Secretary for which
a feasible and practical measure has not been endorsed by the entity
with a contract under section 1890(a) of the Act, the Secretary may
specify a measure that is not so endorsed as long as due consideration
is given to measures that have been endorsed or adopted by a consensus
organization identified by the Secretary.
This measure is not NQF endorsed and has not been submitted to NQF
for endorsement consideration. The CDC, in collaboration with CMS, are
planning to submit the measure for consideration in the NQF Fall 2021
measure cycle.
Because this measure is not NQF-endorsed, we considered other
available measures. We found no other feasible and practical measures
on the topic of COVID-19 vaccination among HCP, therefore, we believe
the exception in Section 1186(s)(4)(D)(ii) of the Act applies.
c. Data Collection, Submission and Reporting
Given the time-sensitive nature of this measure considering the
PHE, in the FY 2022 IPF PPS proposed rule, we proposed that IPFs would
be required to begin reporting data on the proposed COVID-19
Vaccination Coverage Among HCP measure beginning October 1, 2021 for
the FY 2023 IPFQR Program year (86 FR 19504). Thereafter, we proposed
quarterly \110\ reporting periods.
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\110\ We note that the proposed rule incorrectly read ``annual
reporting periods'' however the section of the proposed rule on data
submission (IV.J.2.a) correctly described the data submission
process and timelines.
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To report this measure, facilities would report COVID-19
vaccination data to the NHSN for at least one week each month,
beginning in October 2021 for the October 1, 2021 through December 31,
2021 reporting period affecting FY 2023 payment determination and
continuing for each quarter in subsequent years. For more details on
data submission, we refer readers to section V.J.2.a of this final
rule.
We proposed that IPFs would report the measure through the CDC
National Healthcare Safety Network (NHSN) web-based surveillance
system.\111\ While the IPFQR Program does not currently require use of
the NHSN web-based surveillance system, we have previously required use
of this system. We refer readers to the FY 2015 IPF PPS final rule in
which we adopted the Influenza Vaccination Coverage Among Healthcare
Personnel (NQF #0431) measure for additional information on reporting
through the NHSN web-based surveillance system (79 FR 45968 through
45970).
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\111\ 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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IPFs would report COVID-19 vaccination data in the NHSN Healthcare
Personnel Safety (HPS) Component by reporting the number of HCP
eligible to have worked at the IPF that week (denominator) and the
number of those HCP who have received a completed vaccination course of
a COVID-19 vaccination (numerator). For additional information about
the data reporting requirements, see IV.J.4. of this final rule.
We invited public comment on our proposal to add a new measure,
COVID-19 Vaccination Coverage Among HCP, to the IPFQR Program for the
FY 2023 payment determination and subsequent years.
Comment: Some commenters supported the proposed COVID-19
Vaccination Coverage Among Healthcare Personnel measure. One commenter
observed that data on vaccination coverage are important for patients
and for individuals seeking employment at IPFs. Several commenters
noted the importance of vaccines to reduce transmission, and one
commenter specifically observed that vaccination is particularly
important in settings such as IPFs because non-pharmaceutical
interventions are challenging in such institutional settings. Another
commenter expressed the belief that the measure is methodologically
sound.
Response: We thank these commenters for their support.
Comment: Many commenters expressed concern that using NHSN for
reporting is too burdensome and disproportionately affects smaller and
freestanding IPFs. Some of these commenters further expressed that
requiring reporting through NHSN is inconsistent with the removal of
Influenza Vaccine Coverage among HCP measure because the rationale for
removing the Influenza Vaccine Coverage among HCP measure was the high
reporting burden associated with NHSN reporting.
Response: We believe that there are many significant benefits to
collecting and reporting data on COVID-19 vaccination coverage among
HCP that outweigh its burden. As discussed in our proposal to adopt
this measure, HCP vaccination can potentially reduce illness that leads
to work absence and limit disruptions to care (86 FR 19502). The CDC
has emphasized that health care settings can be high-risk places for
COVID-19 exposure and transmission.\112\ In these settings, COVID-19
can spread between health care personnel (HCP) and patients, or from
patient to patient given the close contact that may occur during the
provision of care.\113\
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\112\ 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.
\113\ 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 April 2, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/hcp/faq.html#Transmission.
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Subsequent to the publication of the IPF PPS proposed rule, the CDC
updated its Science Brief on COVID-19 Vaccines and Vaccination and
observed that the growing body of evidence indicates that people who
are fully vaccinated with an mRNA vaccine are less likely to have
asymptomatic infection or to transmit SARS-CoV-2 to others. The CDC
further noted that the studies are continuing on the benefits of the
Johnson & Johnson/Janssen vaccine.\114\ Therefore we believe that
vaccination coverage among HCP will reduce the risk of contracting
COVID-19 for patients in IPFs, and that IPFs reporting this information
can help patients identify IPFs where they may have lower risk of
COVID-19 exposure. Publishing the HCP vaccination rates will be helpful
to many patients, including those who are at high-risk for developing
serious complications from COVID-19, as they choose IPFs from which to
seek treatment.
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\114\ https://www.cdc.gov/coronavirus/2019-ncov/science/science-briefs/fully-vaccinated-people.html.
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While we agree with the commenters that there is some burden
associated with reporting this measure (see Section (V)(A)(2)(c) of
this final rule), we believe the benefits of data collection and
[[Page 42637]]
reporting on COVID-19 vaccination coverage among HCP are sufficient to
outweigh this burden. In addition, commenters are correct in noting
that when we removed the Influenza Vaccination Coverage Among
Healthcare Personnel (NQF #0431) measure from the IPFQR Program in the
FY 2019 IPF PPS final rule, we observed that reporting measure data
through the NHSN is relatively more burdensome for IPFs than for acute
care hospitals and that this may be especially true for independent or
freestanding IPFs (83 FR 38593 through 38595). However, in our analysis
of facilities that did not receive full payment updates for FY 2018 and
FY 2019 and the reasons these facilities did not receive full payment
updates we observed that 98.24 percent and 99.05 percent of IPFs
respectively, including small, independent, and freestanding IPFs,
successfully reported data for the Influenza Vaccination Coverage Among
Health Care Personnel (NQF #0431) measure prior to its removal from the
IPFQR Program. For the reasons outlined above, the COVID-19 pandemic
and associated PHE has had a much more significant effect on most
aspects of society, including the ability of the healthcare system to
operate smoothly, than influenza, making the benefits of the COVID-19
Vaccination Among HCP measure greater than those of the Influenza
Vaccination Coverage Among Health Care Personnel (NQF #0431) measure.
Comment: Other commenters expressed concern that facilities face
duplicative reporting requirements given that other agencies are
requiring reporting through systems other than NHSN, such as the HHS
TeleTracking site. A few of these commenters recommended that CMS use
the TeleTracking site for data reporting and consumer information as
opposed to adopting a quality measure. Other commenters recommended
that CMS sunset TeleTracking and use NHSN for reporting COVID-19
vaccination coverage data. One commenter recommended that CMS
collaborate with CDC to ensure minimal reporting burden.
Response: We recognize that this measure may lead to duplicative
reporting requirements if facilities voluntarily report COVID-19 HCP
vaccination information to data reporting systems other than NHSN, and
we are collaborating with other HHS agencies, including the CDC, to
ensure minimal reporting burden and to eliminate duplicative
requirements to the extent feasible.
Comment: Some commenters expressed concern about the measure
specifications leading to increased reporting burden. Several of these
commenters expressed that the proposed quarterly reporting of three
weeks of data (one week per month) is excessively burdensome. Other
commenters expressed concern that the measure specifications are not
aligned with the Influenza Vaccination Coverage Among Healthcare
Personnel measure (NQF #0431), specifically noting that the COVID
Vaccination Coverage Among HCP measure requires data elements (such as
contraindications) that are not required for Influenza Vaccination
Coverage Among Healthcare Personnel measure (NQF #0431). One commenter
observed that including all staff (not just clinical staff or staff
directly employed by the IPF) makes the measure unduly burdensome.
Another commenter observed that tracking location is challenging in
large organizations with staff that work across locations.
Response: We recognize commenters' concern regarding reporting
burden associated with the specifications of this measure. We believe
that, given the public health importance of vaccination in addressing
the COVID-19 PHE, the benefits of requiring reporting outweigh the
burden. We believe that reporting these data on a frequent interval
would increase their value by allowing the CDC to better track these
important public health data while also being a valuable quality
measure that supports consumer choice and IPF improvement initiatives.
Because the CDC requests data reported on a monthly basis for one week
per month, we believe this is an appropriate reporting frequency for
our quality measure to ensure that IPFs do not have duplicative
reporting requirements to meet the CDC's need for public health data
and CMS' quality measure reporting requirements. We further note that
while we have sought to align this measure with the Influenza
Vaccination Coverage Among HCP measure (NQF #0431), each measure
addresses different public health initiatives and therefore complete
alignment may not be possible. For example, because influenza
vaccinations are provided during the influenza season (that is, October
1 through March 31) these measures have different reporting periods.
Further, we note that while the Influenza Vaccination Coverage
Among HCP measure (NQF #0431) does not have a denominator exclusion for
HCP with contraindications to the influenza vaccine, there is a
numerator category for these HCP. Specifically, the numerator
description is as follows: ``HCP in the denominator population who
during the time from October 1 (or when the vaccine became available)
through March 31 of the following year: . . . (b) were determined to
have a medical contraindication/condition of severe allergic reaction
to eggs or to other component(s) of the vaccine, or a history of
Guillain-Barre Syndrome within 6 weeks after a previous influenza
vaccination . . .'' \115\ We believe that this numerator element
requires the IPF to track HCP's contraindications to the influenza
vaccination. Therefore, we disagree with the commenter's statement that
the COVID-19 Vaccination Coverage Among HCP measure is more burdensome
than the Influenza Vaccination Coverage Among HCP measure due to
requiring IPFs to track HCP's contraindications to the vaccine.
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\115\ http://www.qualityforum.org/Projects/n-r/Population_Health_Prevention/0431_InfluenzaImmunizationHCPersonnelForm_CDC.aspx.
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Finally, we note that CDC's guidance for entering data requires
submission of HCP count at the IPF level \116\ and the measure requires
reporting consistent with that guidance. We proposed the reporting
schedule of monthly reporting of data from only one week a month to
provide COVID-19 vaccination coverage data on a more timely basis than
annual influenza vaccination coverage (NQF #0431) while also reducing
burden on facilities of weekly reporting which has been the reporting
cycle for many COVID-19-related metrics during the pandemic. As
described in response to previous commenters, we believe that the
public health benefits to having these data available are high, and
that they therefore outweigh the burden of reporting for systems with
multiple facilities or locations. In summary, we recognize that there
may be some elements of the measure specifications that increase burden
for some IPFs, however given the impact that the COVID-19 PHE has had
on society and the healthcare system, we believe that the benefits
outweigh this reporting burden.
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\116\ COVID-19 Vaccination Non-LTC Healthcare Personnel TOI
(cdc.gov).
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Comment: Some commenters expressed concern that having some
vaccinations require two doses creates undue reporting burden for IPFs.
One commenter recommended modelling this measure on the measure under
consideration for patient vaccination coverage within the Merit-Based
Incentive Payment System (MIPS) program which would require reporting
based on receipt of one dose, as opposed to requiring reporting on
receipt of a full course of the vaccine. Some commenters
[[Page 42638]]
expressed concern that because it can take up to 28 days for an
individual to be fully vaccinated, requiring reporting for HCP who have
worked only one day of the reporting period is burdensome or that this
disparately affects facilities without access to the one-dose vaccine.
Response: We believe that it is appropriate to require data on HCP
who have received complete COVID-19 vaccination courses, because an IPF
has more long-term and regular contact with the HCP who work there than
an ambulatory care provider, such as those being evaluated under the
MIPS Program, has with their patient population. This gives the IPF
more ability to track and encourage HCP to receive their complete
vaccination course.
We recognize that since a complete vaccination course could take up
to 28 days, some IPFs may initially appear to have lower performance
than others (based on having access to two dose vaccinations as opposed
to one dose vaccination). However, we believe that with the reporting
frequency these providers should show rapid improvement as their staff
become fully vaccinated. We note that given the highly infectious
nature of the COVID-19 virus, we believe it is important to encourage
all personnel within the IPF, regardless of patient contact, role, or
employment type, to receive the COVID-19 vaccination to prevent
outbreaks within the IPF which may affect resource availability and
have a negative impact on patient access to care.
Comment: Some commenters recommended deferring measurement of
vaccine coverage among HCP until there is at least one vaccine that has
received full FDA approval (as opposed to an EUA). A few commenters
expressed concern that the long-term effects of the vaccines are
unknown and that some HCP concerned about the risk of serious adverse
events; one commenter further expressed concerns regarding the rapid
development and EUA timelines. A few commenters expressed concerns
regarding HCP being unwilling to receive a vaccine which has not
received full FDA approval.
Response: We support widespread vaccination coverage, and note that
in issuing the EUAs for these vaccines FDA has established that the
known and potential benefits of these vaccines outweigh the known and
potential risks.\117\ Furthermore, as July 15, 2021, more than
336,000,000 doses have been administered in the United States.\118\
Although COVID-19 vaccines are authorized for emergency use prevent
COVID-19 and serious health outcomes associated with COVID-19,
including hospitalization and death,\119\ we understand that some HCP
may be concerned about receiving the COVID-19 vaccine prior to the
vaccine receiving full FDA approval. We also understand that some HCP
may be concerned about long-term effects. We note that the COVID-19
Vaccination Coverage Among HCP measure does not require HCP to receive
the vaccination, nor does this measure reward or penalize IPFs for the
rate of HCP who have received a COVID-19 vaccine. The COVID-19
Vaccination Coverage Among HCP measure requires IPFs to collect and
report COVID-19 vaccination data that would support public health
tracking and provide beneficiaries and their caregivers information to
support informed decision making. Therefore, we believe that it is
appropriate to collect and report these data as soon as possible.
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\117\ https://www.fda.gov/vaccines-blood-biologics/vaccines/emergency-use-authorization-vaccines-explained.
\118\ CDC COVID Data Tracker.
\119\ https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/pfizer-biontech-covid-19-vaccine,
https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/moderna-covid-19-vaccine, https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/janssen-covid-19-vaccine.
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Comment: One commenter observed that there are interventions
through which an IPF can promote vaccination coverage, such as by
removing barriers to access (through means such as extended vaccine
clinic hours). This commenter recommended encouraging these
interventions as opposed to promoting vaccination coverage among HCP by
adopting the COVID-19 Vaccination Coverage Among HCP measure.
Response: We agree with the commenter that there are interventions
through which an IPF can increase vaccination coverage by reducing
barriers to access. However, we believe that it is appropriate to
propose this measure for the IPFQR Program to encourage such
interventions by collecting data on vaccination coverage among HCP. We
believe that vaccination is an important health intervention that can
protect the health of vulnerable patients and the availability of the
healthcare system (that is, limiting the number of HCP absent from work
due to illness to ensure that patients have access to care).
Comment: Some commenters expressed the belief that it is
inappropriate to use IPF payment policies to drive vaccination coverage
among HCP. Some commenters expressed concern that this measure could
lead facilities to mandate vaccines for staff, with potential
unintended consequences (specifically, staff quitting or legal risk for
facilities for staff experiencing adverse events). One commenter
expressed the belief that the tie to public reporting and potentially
IPF payment is an indirect vaccine mandate.
Several commenters recommended CMS not consider this measure for
pay-for-reporting because state laws regarding mandates vary and
therefore could lead to inconsistent performance through no fault of
facilities. One commenter expressed the belief that this measure was
developed for public health tracking and is not appropriate for quality
assessment.
Response: We note that this measure does not require vaccination
coverage among HCP at IPFs; it requires IPFs to report of COVID-19
vaccination rates. Therefore, we believe it is incorrect to
characterize this measure as a ``vaccine mandate.'' Furthermore, we
note that the historical national average of providers who had received
the influenza vaccination, as reported on the then Hospital Compare
website was 85 percent, 80 percent, and 82 percent respectively for the
FY 2017, FY 2018, and FY 2019 payment determinations prior to removal
of the Influenza Vaccination Coverage among Healthcare Personnel
measure from the IPFQR Program. We do not believe that this represents
performance that would be consistent with a widespread ``vaccine
mandate'' and therefore we do not believe that a vaccination coverage
among HCP measure, including the COVID-19 Vaccination Coverage among
HCP measure, inherently leads to ``vaccine mandates.'' However, we
believe that data regarding COVID-19 vaccination coverage among HCP are
important to empower patients to make health care decisions that are
best for them.
Comment: Some commenters expressed concern that the measure does
not fully account for potential reasons that HCP may not receive COVID-
19 vaccinations. One commenter recommended expanding the exclusions to
the measure's calculation, specifically citing religious objections as
an exclusion category. Another commenter observed that there is
uncertainty about how effective vaccines are for certain populations,
such as those with underlying conditions.
[[Page 42639]]
Response: We recognize that there are many reasons, including
religious objections or concerns regarding an individual provider's
specific health status, which may lead individual HCP to decline
vaccination. The CDC's NHSN tool allows facilities to report on the
number of HCP who were offered a vaccination but declined for reasons
including religious or philosophical objections.\120\ We agree that
there is uncertainty about effectiveness among certain patient
populations, including those with underlying conditions. The CDC has
found that there is evidence of reduced antibody response to or reduced
immunogenicity of COVID-19 mRNA vaccine among some immunosuppressed
people.\121\ However, we note that COVID-19 vaccines may be
administered to most people with underlying medical conditions.\122\
Therefore, we believe that individual HCP who may have underlying
conditions that could affect vaccine efficacy should make the decision
of whether to receive the COVID-19 vaccination in discussion with their
individual care provider. We believe that vaccination coverage rates
are meaningful data for beneficiaries to use in choosing an IPF which
can also be used for public health tracking.
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\120\ https://www.cdc.gov/nhsn/forms/instr/57.220-toi-508.pdf.
\121\ https://www.cdc.gov/coronavirus/2019-ncov/science/science-briefs/fully-vaccinated-people.htmla.
\122\ https://www.cdc.gov/coronavirus/2019-ncov/vaccines/recommendations/underlying-conditions.html.
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Comment: One commenter expressed the concern that this may have an
adverse impact on HCP as it is unclear whether in the future individual
HCP will be required to pay for the vaccination themselves.
Response: We understand the commenter's concerns that individual
HCP may potentially have to pay for the COVID-19 vaccine in the future.
In alignment with our pledge to put patients first in all our programs,
we believe that it is important to empower patients to work with their
doctors and make health care decisions that are best for them.\123\
This includes the belief that HCP should be empowered to work with
their own healthcare providers to make the health care decisions that
are best for them, based on the totality of their circumstances,
including potential costs to receive the vaccine and their increased
risks of contracting COVID-19 based on occupational exposure.
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\123\ Home--Centers for Medicare & Medicaid Services [verbar]
CMS.
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Comment: Many commenters expressed concern that this measure should
not be adopted until there is clarity around the impact of future
boosters. These commenters also noted that booster availability could
have an impact on vaccination coverage among HCP. One commenter
specifically expressed concern regarding past supply chain disruptions
and observed that similar issues may affect booster availability in the
future.
Response: The COVID-19 Vaccination Coverage among HCP measure is a
measure of a completed vaccination course (as defined in section
IV.E.2.b.(1) of the FY 2022 IPF PPS proposed rule (86 FR 19502 through
19503) and does not address booster shots. Currently, the need for
COVID-19 booster doses has not been established, and no additional
doses are currently recommended for HCP. However, we believe that the
numerator is sufficiently broad to include potential future boosters as
part of a ``complete vaccination course'' and therefore the measure is
sufficiently specified to address boosters. We acknowledge the
potential for supply chain disruptions or other factors that affect
vaccine availability, but we believe that the urgency of adopting the
measure to address the current COVID-19 PHE outweighs these potential
concerns.
Comment: Some commenters expressed that collecting the data to
report this measure is challenging. These commenters observed that
because, unlike influenza vaccinations, HCP have received COVID
vaccinations from settings outside their places of employment,
employers may still be attaining vaccination records from employees.
One commenter observed that the data for HCP is housed in separate
systems from those typically used for quality reporting.
Response: We recognize that some IPFs may still be obtaining
vaccination records from their employees and other personnel that work
within their facilities. However, most healthcare settings, including
IPFs, have been reporting COVID-19 data to Federal or state agencies
for some time and therefore have established the appropriate workflows
or other means to obtain these records from employees or other
personnel that work within the IPF. Therefore, we believe that IPFs
must have the means to obtain the data, either directly from HCP or
from other systems in which these data are housed, and that it is
appropriate to require IPFs to report these data.
Comment: Another commenter expressed concern that the shortened
performance period for the first year may lead to incomplete data. One
commenter recommended allowing voluntary reporting without publicly
reporting data for the first performance year to account for potential
data gaps.
Response: Given that results would be calculated quarterly for this
measure, facilities should show rapid progress as they obtain more
complete data on vaccination coverage for their HCP. While we
understand the desire for a year of voluntary reporting to account for
potential data gaps, we believe that the importance of providing
patients and their caregivers with data on COVID-19 Vaccination
Coverage among HCP at individual IPFs in a timely manner outweighs this
concern and should be accomplished as soon as practical.
Comment: A few commenters expressed concern that due to the delay
between data collection (which takes place during a quarter) and public
reporting (which follows the reporting of the data collected during the
quarter, the deadline for which is 4.5 months after the end of the
quarter) the data would not be useful by the time they are publicly
reported either because they are too old or because the trajectory of
the pandemic has changed. One commenter opposed public reporting until
data has been reported for several years.
Response: We believe that it is important to make these data
available as soon as possible. We agree with commenters that observe
that there is a delay between data collection and public reporting for
this measure, and note that such a delay exists for all measures in the
IPFQR Program. However, we believe that the data will provide
meaningful information to consumers in making healthcare decisions
because the data will be able to reflect differences between IPFs in
COVID-19 vaccination coverage among HCP even if the data do not reflect
the current vaccination rates and we believe it will benefit consumers
to have these data available as early as possible. We proposed the
shortened reporting period for the first performance period to make the
COVID-19 Vaccination among HCP measure data available as quickly as
possible.
Comment: One commenter observed that the data would not provide
consumers a complete picture of infection control procedures because
vaccines are only one tactic to prevent and control infections. Another
commenter observed that public reporting may lead to comparisons
between facilities. An additional commenter recommended a validation
process to ensure that consumers can rely on the data.
[[Page 42640]]
Response: While we recognize that the data may not fully represent
all activities to prevent and control infections, we believe that the
data would be useful to consumers in choosing IPFs, including making
comparisons between facilities. We note that we do not currently have a
validation process for any measures in the IPFQR Program and refer
readers to section IV.J.3 of this final rule where we discuss
considerations for a validation program for the IPFQR Program.
Comment: Some commenters recommended deferring the measure until it
has been fully tested and NQF endorsed. One commenter observed that the
MAP reviewed the measure concept, not the full measure, and therefore
it is premature to include it in the IPFQR Program without further
review. Another commenter observed that such rapid measure adoption may
set a precedent for future rapid measure adoption.
Response: We believe that given the current COVID-19 PHE, it is
important to adopt this measure as quickly as possible to allow
tracking and reporting of COVID-19 Vaccination Coverage Among HCP in
IPFs. This tracking would provide consumers with important information.
We refer readers to FY 2022 IPF PPS proposed rule where we discuss our
consideration of NQF endorsed measures on the topic of COVID-19
vaccination coverage among healthcare personnel for additional
information (86 FR 19503 through 19504). We note that the MAP had the
opportunity to review and provide feedback on the full measure in the
March 15th meeting. The CDC, in collaboration with CMS, is planning to
submit the measure for consideration in the NQF Fall 2021 measure
cycle. Finally, we evaluate all measures on a case-by-case basis and
therefore the pace at which we propose to adopt one measure is
dependent on the measure and the purpose for adopting it.
Comment: One commenter requested clarification for the reporting
frequency.
Response: We recognize that the proposed required frequency for
reporting, may have been unclear because we referred to ``annual
reporting'' periods two times in the proposed rule. Specifically, we
referenced annual reporting periods in the first paragraph of section
IV.E.2.c (86 FR 19504) and in our burden estimate for the measure (86
FR 19519). Our description of data submission under IV.J.2.a in which
we stated that facilities would be required to report the vaccination
data to the NHSN for at least one week each month and that if they
reported more than one week, the most recent week's data would be used
(86 FR 19513) is correct. In that section, we further noted that the
CDC would calculate a single quarterly result for summarizing the data
reported monthly. In summary, the measure would require monthly
reporting of at least one week's data per month. This would be
calculated into quarterly results. We note that IPFs are required to
report to NHSN sufficient data (that is, vaccination data for at least
one week in each month per quarter) to calculate four quarterly results
per year, except for the first performance period which depends on only
one quarter of data (the vaccination data for at least one week in each
month in Q1 of FY 2022). While IPFs can report data to the NHSN at any
time, they must report by 4.5 months following the preceding quarter
for the purposes of measure calculation. For the first performance
period for this measure (that is Q1 of FY 2022), 4.5 months following
the end of the quarter is May 15, 2022.
Comment: One commenter requested clarification on which provider
types are considered healthcare personnel.
Response: The provider types that are considered healthcare
personnel, along with the specifications for this measure, are
available at https://www.cdc.gov/nhsn/nqf/index.html. The categories of
HCP included in this measure are ancillary services employees; nurse
employees; aide, assistant, and technician employees; therapist
employees; physician and licensed independent practitioner employees;
and other HCP. For more detail about each of these categories we refer
readers to the Table of Instructions for Completion of the Weekly
Healthcare Personnel COVID-19 Cumulative Vaccination Summary Form for
Non-Long-Term Care Facilities available at https://www.cdc.gov/nhsn/forms/instr/57.220-toi-508.pdf.
Comment: One commenter observed that the definition of ``location''
for measure calculation is unclear.
Response: CDC's guidance for entering data requires submission of
HCP count at the IPF level, not at the location level within the
IPF.\124\
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\124\ COVID-19 Vaccination Non-LTC Healthcare Personnel TOI
(cdc.gov).
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After consideration of the public comments, we are finalizing the
COVD-19 Vaccination Coverage Among Healthcare Personnel measure as
proposed for the FY 2023 payment determination and subsequent years.
3. Follow-Up After Psychiatric Hospitalization (FAPH) Measure for the
FY 2024 Payment Determination and Subsequent Years
a. Background
We proposed one new measure, Follow-Up After Psychiatric
Hospitalization (FAPH), for the FY 2024 payment determination and
subsequent years. The FAPH measure would use Medicare fee-for-service
(FFS) claims to determine the percentage of inpatient discharges from
an inpatient psychiatric facility (IPF) stay with a principal diagnosis
of select mental illness or substance use disorders (SUDs) for which
the patient received a follow-up visit for treatment of mental illness
or SUD. Two rates would be calculated for this measure: (1) The
percentage of discharges for which the patient received follow-up
within 7 days of discharge; and (2) the percentage of discharges for
which the patient received follow-up within 30 days of discharge.
The FAPH measure is an expanded and enhanced version of the Follow-
Up After Hospitalization for Mental Illness (FUH, NQF #0576) measure
currently in the IPFQR Program. We proposed to adopt the FAPH measure
and replace the FUH measure and refer readers to section IV.F.2.d of
the FY 2022 IPF PPS proposed rule for our proposal to remove the FUH
measure contingent on adoption of the FAPH measure (86 FR 19510). The
FUH (NQF #0576) measure uses Medicare FFS claims to determine the
percentage of inpatient discharges from an IPF stay with a principal
diagnosis of select mental illness diagnoses for which the patient
received a follow-up visit for treatment of mental illness, and it
excludes patients with primary substance use diagnoses. During the 2017
comprehensive review of NQF #0576, the NQF Behavioral Health Standing
Committee (BHSC) recommended expanding the measure population to
include patients hospitalized for drug and alcohol disorders, because
these patients also require follow-up care after they are discharged.
In 2018, CMS began development of a measure to expand the IPFQR FUH
population to include patients with principal SUD diagnoses to address
the NQF BHSC recommendation and the CMS Meaningful Measures priority to
promote treatment of SUDs. The FAPH measure would expand the number of
discharges in the denominator by about 35 percent over the current FUH
measure by adding patients with SUD or dementia as principal diagnoses
(including patients with any
[[Page 42641]]
combination of SUD, dementia, or behavioral health disorders),
populations that also benefit from timely follow-up care.
Furthermore, compared to the criteria for provider type in the
current FUH measure, the FAPH measure does not limit the provider type
for the follow-up visit if it is billed with a diagnosis of mental
illness or SUD. During the measure's testing, the most frequent
provider types for the FAPH measure were family or general practice
physicians, internal medicine physicians, nurse practitioners, and
physician assistants. The technical expert panel (TEP) convened by our
contractor agreed that these provider types should be credited by the
measure for treating mental illness and SUD and confirmed that this is
aligned with integrated care models that aim to treat the whole
patient. The TEP further noted that in areas where there are shortages
of mental health or SUD clinicians, other types of providers are often
the only choice for follow-up treatment. Allowing visits to these types
of providers to count towards the numerator allows the measure to
capture the rates of appropriate follow-up care more accurately in
areas with provider shortages.
Performance on the FAPH measure indicates that follow-up rates for
patients hospitalized with mental illness or SUD are less than optimal
and that room for improvement is ample. The clinical benefits of timely
follow-up care after hospitalization, including reduced risk of
readmission and improved adherence to medication, are well-documented
in the published literature.125 126 127 128 129 130 131
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\125\ Tong, L., Arnold, T., Yang, J., Tian, X., Erdmann, C., &
Esposito, T. (2018). The association between outpatient follow-up
visits and all-cause non-elective 30-day readmissions: A
retrospective observational cohort study. PloS one, 13(7), e0200691.
https://doi.org/10.1371/journal.pone.0200691.
\126\ Terman, S. W., Reeves, M. J., Skolarus, L. E., & Burke, J.
F. (2018). Association Between Early Outpatient Visits and
Readmissions After Ischemic Stroke. Circulation. Cardiovascular
quality and outcomes, 11(4), e004024. https://doi.org/10.1161/CIRCOUTCOMES.117.004024.
\127\ First Outpatient Follow-Up After Psychiatric
Hospitalization: Does One Size Fit All? (2014). Psychiatric
Services, 66(6), 364-372. https://doi.org/10.1176/appi.ps.201400081.
\128\ Terman, S. W., Reeves, M. J., Skolarus, L. E., & Burke, J.
F. (2018). Association Between Early Outpatient Visits and
Readmissions After Ischemic Stroke. Circulation. Cardiovascular
quality and outcomes, 11(4), e004024. https://doi.org/10.1161/CIRCOUTCOMES.117.004024.
\129\ Jackson, C., Shahsahebi, M., Wedlake, T., & DuBard, C. A.
(2015). Timeliness of outpatient follow-up: An evidence-based
approach for planning after hospital discharge. Annals of family
medicine, 13(2), 115-122. https://doi.org/10.1370/afm.1753.
\130\ Hernandez, A. F., Greiner, M. A., Fonarow, G. C., Hammill,
B. G., Heidenreich, P. A., Yancy, C. W., Peterson, E. D., & Curtis,
L. H. (2010). Relationship between early physician follow-up and 30-
day readmission among Medicare beneficiaries hospitalized for heart
failure. JAMA, 303(17), 1716-1722. https://doi.org/10.1001/jama.2010.533.
\131\ Nadereh Pourat, Xiao Chen, Shang-Hua Wu and Anna C. Davis.
Timely Outpatient Follow-up Is Associated with Fewer Hospital
Readmissions among Patients with Behavioral Health Conditions. The
Journal of the American Board of Family Medicine. May 2019, 32 (3)
353-361; DOI: https://doi.org/10.3122/jabfm.2019.03.180244.
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Behavioral health patients in particular have a number of risk
factors that underscore the need for timely follow-up and continuity of
care: Behavioral health patients have higher baseline hospitalization
rates, higher hospital readmission rates, and higher health care costs
as compared with the general population of patients.132 133
Among patients with serious mental illness, 90 percent have comorbid
clinical conditions such as hypertension, cardiovascular disease,
hyperlipidemia, or diabetes.\134\ Among patients hospitalized for
general medical conditions, those who also have a mental illness are 28
percent more likely to be readmitted within 30 days than their
counterparts without a psychiatric comorbidity.\135\ The high
prevalence of clinical comorbidities among behavioral health patients,
combined with the compounding effect of mental illness on patients with
general medical conditions, suggests that behavioral health patients
are uniquely vulnerable and supports the intent of the measure to
increase follow-up after hospitalization.
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\132\ Germack, H.D., et al. (2019, January). Association of
comorbid serious mental illness diagnosis with 30-day medical and
surgical readmissions. JAMA Psychiatry.
\133\ First Outpatient Follow-Up After Psychiatric
Hospitalization: Does One Size Fit All? (2014). Psychiatric
Services, 66(6), 364-372. https://doi.org/10.1176/appi.ps.201400081.
\134\ First Outpatient Follow-Up After Psychiatric
Hospitalization: Does One Size Fit All? (2014). Psychiatric
Services, 66(6), 364-372. https://doi.org/10.1176/appi.ps.201400081.
\135\ Benjenk, I., & Chen, J. (2018). Effective mental health
interventions to reduce hospital readmission rates: A systematic
review. Journal of hospital management and health policy, 2, 45.
https://doi.org/10.21037/jhmhp.2018.08.05.
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In addition, clinical practice guidelines stress the importance of
continuity of care between settings for patients with mental illness
and SUD. For the treatment of SUD patients, the 2010 guidelines of the
American Psychiatric Association (APA) state: ``It is important to
intensify the monitoring for substance use during periods when the
patient is at a high risk of relapsing, including during the early
stages of treatment, times of transition to less intensive levels of
care, and the first year after active treatment has ceased.'' \136\
This statement is accompanied by a grade of [I], which indicates the
highest level of APA endorsement: ``recommended with substantial
clinical evidence.''
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\136\ American Psychiatric Association. Practice guideline for
the treatment of patients with substance use disorders. 2010. http://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/substanceuse.pdf.
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Evidence supports that outpatient follow-up care and interventions
after hospital discharges are associated with a decreased risk of
readmissions for patients with mental illness.137 138 IPFs
can influence rates of follow-up care for patients hospitalized for
mental illness or SUD. Three studies reported that with certain
interventions--such as pre-discharge transition interviews, appointment
reminder letters or reminder phone calls, meetings with outpatient
clinicians before discharge, and meetings with inpatient staff familiar
to patients at the first post-discharge appointment--facilities
achieved 30-day follow-up rates of 88 percent or
more.139 140 141 This is substantially higher than the
national rate of about 52 percent observed in the current FUH measure
for Medicare FFS discharges between July 1, 2016, and June 30,
2017.\142\ Medicare FFS data from July 1, 2016, to June 30, 2017, show
the national 7-day follow-up rate to be 35.5 percent and the 30-day
rate to be 61.0 percent. These data reveal wide variation in follow-up
rates across facilities, with a 16.9 percent absolute difference
between the 25th and 75th
[[Page 42642]]
percentiles for the 7-day rate and a 17.4 percent absolute difference
for the 30-day rate. If all facilities achieved the benchmark follow-up
rates for their Medicare FFS patients (as calculated using the AHRQ
Achievable Benchmarks of Care method,) \143\ 53,841 additional
discharges would have a 7-day follow-up visit, and 47,552 would have a
30-day follow-up visit.\144\
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\137\ Kurdyak P, Vigod SN, Newman A, Giannakeas V, Mulsant BH,
Stukel T. Impact of Physician Follow-Up Care on Psychiatric
Readmission Rates in a Population-Based Sample of Patients With
Schizophrenia. Psychiatr Serv. 2018;69(1):61-68. doi: 10.1176/
appi.ps.201600507.
\138\ Marcus SC, Chuang CC, Ng-Mak DS, Olfson M. Outpatient
follow-up care and risk of hospital readmission in schizophrenia and
bipolar disorder. Psychiatr Serv. 2017;68(12):1239-1246. doi:
10.1176/appi.ps.201600498.
\139\ Batscha C, McDevitt J, Weiden P, Dancy B. The effect of an
inpatient transition intervention on attendance at the first
appointment post discharge from a psychiatric hospitalization. J Am
Psychiatr Nurses Assoc. 2011;17(5):330-338. doi: 10.1177/
1078390311417307.
\140\ Agarin T, Okorafor E, Kailasam V, et al. Comparing kept
appointment rates when calls are made by physicians versus behavior
health technicians in inner city hospital: literature review and
cost considerations. Community Ment Health J. 2015;51(3):300-304.
doi: 10.1007/s10597-014-9812-x.
\141\ Olfson M, Mechanic D, Boyer CA, Hansell S. Linking
inpatients with schizophrenia to outpatient care. Psychiatr Serv.
1998;49(7):911-917. doi: 10.1176/ps.49.7.911. Quality AFHRA. 2017
National Healthcare Quality and Disparities Report. Rockville, MD:
Services USDoHaH; 2018.
\142\ https://data.cms.gov/provider-data/archived-data/hospitals.
\143\ https://nhqrnet.ahrq.gov/inhqrdr/resources/methods#Benchmarks.
\144\ Quality AfHRa. 2017 National Healthcare Quality and
Disparities Report. Rockville, MD: Services USDoHaH; 2018.
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During the development process, we used the CMS Quality Measures
Public Comment Page to ask for public comments on the measure.\145\ We
accepted public comments from January 25, 2019, to February 13, 2019.
During this period, we received comments from 29 organizations or
individuals. Many commenters acknowledged the importance of developing
a measure that assesses acute care providers for follow-up post-
hospitalization. Some commenters expressed skepticism about the
measure's appropriateness as a tool for evaluating the performance of
discharging IPFs due to factors beyond the IPFs' control that can
affect whether a patient receives timely post-discharge follow-up care.
Ten stakeholders expressed support for the measure based on the
expanded list of qualifying diagnoses in the denominator and the
inclusion of more patients who could benefit from post-discharge
follow-up visits.\146\
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\145\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/IPF_-Follow-Up-After-Psychiatric-Hospitalization_Public-Comment-Summary.pdf.
\146\ Mathematica. FAPH public comment summary. April 2019.
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We reviewed the comments we received with the TEP, whose members
shared similar feedback regarding the importance of follow-up for
patients with both mental health diagnoses and substance use disorders,
as well as concerns about the ability of IPFs to influence follow-up
care. We agree with commenters that some factors that influence follow-
up are outside of an IPF's control. However, as described previously in
this section, we believe that there are interventions (such as pre-
discharge transition interviews, appointment reminder letters or
reminder phone calls, meetings with outpatient clinicians before
discharge, and meetings with inpatient staff familiar to patients at
the first post-discharge appointment) that allow facilities to improve
their follow-up adherence. We remain committed to monitoring follow-up
to improve health outcomes and view this measure as an expansion of our
ability to measure appropriate follow-up care established by FUH.
b. Overview of Measure
(1). Measure Calculation
The FAPH measure would be calculated by dividing the number of
discharges that meet the numerator criteria by the number that meet the
denominator criteria. Two rates are reported for this measure: the 7-
day rate and the 30-day rate.
(a) Numerator
The first rate that would be reported for this measure includes
discharges from an IPF that are followed by an outpatient visit for
treatment of mental illness or SUD within 7 days. The second rate
reported for this measure would include discharges from an IPF that are
followed by an outpatient visit for treatment of mental illness or SUD
within 30 days. Outpatient visits are defined as outpatient visits,
intensive outpatient encounters, or partial hospitalization and are
defined by the Current Procedural Terminology (CPT), Healthcare Common
Procedure Coding System (HCPCS), and Uniform Billing (UB) Revenue
codes. Claims with codes for emergency room visits do not count toward
the numerator.
(b) Denominator
The denominator includes discharges paid under the IPF prospective
payment system during the performance period for Medicare FFS patients
with a principal diagnosis of mental illness or SUD. Specifically, the
measure includes IPF discharges for which the patient was:
Discharged with a principal diagnosis of mental illness or
SUD that would necessitate outpatient follow-up care,
Alive at the time of discharge,
Enrolled in Medicare Parts A and B during the month of the
discharge date and at least one month after the discharge date to
ensure that data are available to capture the index admission and
follow-up visits, and
Age 6 or older on the date of discharge, because follow-up
treatment for mental illness or SUD might not always be recommended for
younger children.
The denominator excludes IPF discharges for patients who:
Were admitted or transferred to acute and non-acute
inpatient facilities within the 30-day follow-up period, because
admission or transfer to other institutions could prevent an outpatient
follow-up visit from taking place,
Were discharged against medical advice, because the IPF
could have limited opportunity to complete treatment and prepare for
discharge,
Died during the 30-day follow-up period, or
Use hospice services or elect to use a hospice benefit at
any time during the measurement year regardless of when the services
began, because hospice patients could require different follow-up
services.
The FAPH measure differs from FUH mostly in the expansion of the
measure population to include SUD and other mental health diagnoses in
the measure's denominator, but it includes some additional differences:
The FAPH measure simplifies the exclusion of admission or
transfer to acute or non-acute inpatient facilities within 30 days
after discharge by aligning with the HEDIS[supreg] Inpatient Stay Value
Set used in both the HEDIS[supreg] FUH and the HEDIS[supreg] Follow-Up
After Emergency Department Visit for Alcohol and Other Drug Abuse or
Dependence (FUA) measures to identify acute and non-acute inpatient
stays. A discharge is excluded from the FAPH measure if it is followed
by an admission or a transfer with one of the codes in the value set.
The FAPH measure uses Medicare UB Revenue codes (rather
than inpatient discharge status code, which the FUH measure uses) to
identify discharge or transfer to other health care institutions. This
is to align better with the intent of the HEDIS[supreg] FUH and
HEDIS[supreg] FUA measures.
The FAPH measure allows mental illness or SUD diagnoses in
any position on the follow-up visit claim to count toward the numerator
and does not require that it be in the primary position as the FUH
measure does.
(2) Measure Reliability and Validity
In 2019, CMS used the final measure specifications to complete
reliability and validity testing, which revealed that the FAPH measure
provides reliable and valid IPF-level rates of follow-up after
psychiatric hospitalization. We evaluated measure reliability based on
a signal-to-noise analysis,\147\ in which a score of 0.0 implies that
all variation is attributed to measurement error (noise), and a score
of 1.0 implies that all measure score variation is caused by a real
difference in performance across IPFs. Using that approach, we
established a minimum denominator size of 40 discharges to attain an
overall
[[Page 42643]]
reliability score of 0.7 for both the 7-day and the 30-day rate. These
analyses revealed that the measure can reliably distinguish differences
in performance between IPFs with adequate denominator size.
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\147\ For additional information on reliability tests see http://www.qualityforum.org/Measuring_Performance/Improving_NQF_Process/Measure_Testing_Task_Force_Final_Report.aspx.
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We evaluated the validity of the measure based on its correlation
to two conceptually related measures in the IPFQR Program: The 30-Day
All-Cause Unplanned Readmission After Psychiatric Discharge from an IPF
(IPF Readmission) measure, and the Medication Continuation Following
Inpatient Psychiatric Discharge (Medication Continuation) measure. We
observed a weak negative correlation between FAPH and the IPF
Readmission measure for both 7-day (--0.11) and 30-day (--0.18) measure
rates. This negative correlation is expected because a higher score is
indicative of better quality of care for the FAPH, while a lower score
is indicative of better quality of care for the IPF readmission measure
(that is, a lower rate of unplanned readmissions). High rates of
follow-up after visits after discharge and low rates of unplanned
readmissions both indicate good care coordination during the discharge
process. We observed a weak positive correlation between the 7-day FAPH
measure rate and the Medication Continuation measure (0.32), and
between the 30-day FAPH measure rate and the Medication Continuation
measure (0.42). This result is expected because for both the FAPH and
the Medication Continuation measures higher scores are indicative of
better-quality care. Follow-up visits after discharge and continuation
of medication after discharge both indicate good care coordination
during the discharge process. After reviewing these results and the
proposed measure specifications, all 13 TEP members who were present
agreed that the measure had face validity.\148\
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\148\ Face validity is defined as a subjective determination by
experts that the measure appears to reflect quality of care, done
through a systematic and transparent process, that explicitly
addresses whether performance scores resulting from the measure as
specified can be used to distinguish good from poor quality, with
degree of consensus and any areas of disagreement provided/
discussed: https://www.qualityforum.org/Measuring_Performance/Scientific_Methods_Panel/Docs/Evaluation_Guidance.aspx.
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(3) Review by the Measure Applications Partnership and NQF
Under section 1890A(a)(2) of the Act, this measure was included in
a publicly available document: ``List of Measures Under Consideration
for December 1, 2019,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityMeasures/Downloads/Measures-under-Consideration-List-for-2018.pdf.
On January 15, 2020, the MAP Coordinating Committee rated the
measure as ``Conditional Support for Rulemaking'' contingent upon NQF
endorsement. We submitted the measure to the NQF for endorsement in the
spring 2020 cycle. However, some members of the NQF Behavioral Health
and Substance Use Standing Committee were concerned about the measure's
exclusions for patients who died during the 30-day follow-up period or
who were transferred. In addition, some members objected to combining
persons with a diagnosis of SUD and those with a diagnosis for a mental
health disorder into a single measure of follow-up care. Therefore, the
NQF declined to endorse this measure. We noted that the exclusions for
patients who died or who were admitted or transferred to an acute or
non-acute inpatient facility during the 30-day follow up period align
with the FUH measure currently in the IPFQR Program.
Section 1886(s)(4)(D)(ii) of the Act authorizes the Secretary to
specify a measure for the IPFQR Program that is not endorsed by NQF.
The exception to the requirement to specify an endorsed measure states
that in the case of a specified area or medical topic determined
appropriate by the Secretary for which a feasible and practical measure
has not been endorsed by the entity with a contract under section
1890(a) of the Act, the Secretary may specify a measure that is not so
endorsed as long as due consideration is given to measures that have
been endorsed or adopted by a consensus organization.
The FAPH measure is not NQF endorsed. We have reviewed NQF-endorsed
and other consensus-endorsed measures related to follow-up care and
identified the FUH measure (NQF #0576) currently in the IPFQR Program
and Continuity of Care after Inpatient or [verbar] Residential
Treatment for SUD (NQF #3453), we believe that the FAPH measure is an
improvement over the current FUH measure and over the Continuity of
Care after Inpatient or Residential Treatment of Substance Use Disorder
because we believe that it is important to ensure appropriate access to
follow-up treatment for the largest patient population possible and the
FAPH measure applies to a larger patient population than either of the
measures we considered. Therefore, we proposed to adopt the FAPH
measure described in this section for the FY 2024 payment determination
and subsequent years.
c. Data Collection, Submission and Reporting
FAPH uses Medicare FFS Part A and Part B claims that are received
by Medicare for payment purposes. The measure links Medicare FFS claims
submitted by IPFs and subsequent outpatient providers for Medicare FFS
IPF discharges. Therefore, no additional data collection would be
required from IPFs. For additional information on data submission for
this measure, see section IV.J.2.b of this final rule. The performance
period used to identify cases in the denominator is 12 months. Data
from this period and 30 days afterward are used to identify follow-up
visits in the numerator. Consistent with other claims-based measures in
the IPFQR Program, the performance period for this measure is July 1
through June 30. For example, for the FY 2024 payment determination,
the performance period would include discharges between July 1, 2021
and June 30, 2022.\149\
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\149\ If data availability or operational issues prevent use of
this performance period, we would announce the updated performance
period through subregulatory communications including announcement
on a CMS website and/or on our applicable listservs.
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We invited public comment on our proposal to add a new measure,
Follow-Up After Psychiatric Hospitalization, to the IPFQR Program,
beginning with the FY 2024 payment determination and subsequent years.
We received the following comments on our proposal.
Comment: Many commenters supported the adoption of the FAPH
measure. Some commenters expressed that the expanded cohort would
improve the measure's value. Some commenters expressed that expanding
the eligible provider types for the follow-up visit would improve care
because of the shortage of psychiatrists. A few commenters observed
that care transitions are important, and that outpatient follow-up
serves to improve the value of the inpatient services provided. One
commenter expressed that adoption of this measure is timely due to the
increased behavioral health needs associated with the COVID-19
pandemic. One commenter recommended using this measure at the health
system level to better identify care coordination, access, and referral
network adequacy.
Response: We thank these commenters for their support. We agree
that the expanded definitions would improve the measure's applicability
and capture more follow-up visits. Regarding the commenter's
[[Page 42644]]
recommendation on using this measure at the health system level, we
believe the commenter is recommending adopting this measure to evaluate
performance of regional or local health systems (such as those
affiliated with large hospital networks). We note that the IPFQR
Program applies to Medicare participating freestanding psychiatric
hospitals and psychiatric units and we believe that health systems that
have IPFs that participate in the IPFQR Program would find this measure
useful as they assess access and referral network adequacy within their
systems.
Comment: Some commenters observed that some follow-ups, especially
for substance use disorders, may not be identifiable in claims. A few
commenters specifically noted that some providers who often provide
follow-ups are not covered by Medicare (for example, therapists) or
that some follow-ups may be covered by other insurers. These commenters
observed that this may lead the measure to undercount follow-ups
provided. A few of these commenters did not support measure adoption
because of this undercount. However, one commenter that expressed this
concern supported measure adoption because the commenter believes that
burden reduction associated with claims reporting outweighs the
potential undercounting.
Response: We acknowledge that, like the Follow-Up After
Hospitalization for Mental Illness (FUH, NQF #0576) measure that we
proposed to replace with the FAPH measure, the FAPH measure would not
be able to capture follow-up visits provided by professionals outside
of Medicare, or if the patient uses another payer or self-pay to cover
the patient's follow-up care, which could lead to an undercount.
However, we believe that the data captured by the measure would be
sufficient to inform consumers and to provide data for quality
improvement initiatives. Further, we agree with the commenter that the
burden reduction associated with using claims-based measures outweighs
the potential undercounting.
Comment: Some commenters expressed concern that this measure may be
difficult for some IPFs to perform well on due to factors outside of
the IPF's control. One commenter observed that many rural hospitals
lack community resources and therefore cannot refer patients to
outpatient psychiatrists. Another commenter observed that some patients
may be unwilling to see an outpatient psychiatrist. Other commenters
observed that this measure captures patient behavior, not provider
actions. Some of these commenters observed that lack of transportation,
access barriers, homelessness or other patient characteristics outside
of the IPF's control may affect performance. Some of these commenters
expressed preference for a process measure that tracks whether IPFs
performed interventions to improve follow-up rates before or during
discharge.
Response: We recognize that there is regional variation in access
to outpatient resources and that patients have varying comfort levels
with different provider types. However, we believe that this updated
measure helps to address some of the commenters' concerns.
Specifically, we note that this measure expands the definition of
follow-up to include a wider range of outpatient providers, including
family or general practice physicians, internal medicine physicians,
nurse practitioners, and physician assistants. We agree with commenters
that there are factors that influence follow-up that are outside of an
IPF's control (including patient behavior, lack of transportation,
access barriers, homelessness, among others).
As described in the FY 2022 IPF PPS proposed rule (86 FR 19504
through 19505), there are interventions that allow facilities to
improve their follow-up adherence. We believe it is incumbent upon
facilities to identify potential barriers to follow-up adherence and
apply appropriate interventions to improve adherence. We believe that
this measure is preferable to a process measure because it provides
insight into the success of interventions by identifying follow-up
rates. As discussed in the FY 2014 IPPS/LTCH PPS final rule (78 FR
50894 through 50895) and the FY 2022 IPF PPS proposed rule in our
proposal to adopt the FAPH measure (86 FR 19504 through 19507) we do
not expect 100 percent of patients discharged from IPFs to receive
follow-up care within 7 or 30 days of discharge because of factors both
within and outside of the control of facilities such as availability of
providers in the referral network.
Comment: Some commenters opposed the FAPH measure because it is not
NQF endorsed and because it was not fully supported by the MAP. A few
commenters observed that the measure may undergo changes to achieve NQF
endorsement which would create burden if the measure were in the
program when these changes occurred. Some commenters recommended
delaying implementation until NQF's concerns are fully addressed. One
commenter observed that the similar NQF-endorsed FUH measure is
available and therefore CMS has not properly considered available
consensus endorsed measures.
Response: We appreciate the commenters' concerns about the FAPH
measure's lack of NQF endorsement. As we stated in the proposed rule,
after having given due consideration to similar measures, FUH measure
(NQF #0576) and Continuity of Care after Inpatient or Residential
Treatment for SUD (NQF #3453), we believe that the FAPH measure is an
improvement over the FUH measure currently in the IPFQR Program (86 FR
19507). The FAPH measure expands the number of discharges in the
denominator by adding patients with SUD or dementia, populations that
also benefit from timely follow-up care. We propose updates to the
IPFQR program measure set on an annual basis through the rulemaking
process. During the measure evaluation process, we carefully consider
the potential burden to clinicians, health systems, and patients of any
updates that are under consideration.
The primary concerns of some NQF Behavioral Health and Substance
Use Standing Committee members with the FAPH measure were exclusions
for patients who died during the 30-day follow-up period or who were
transferred. While we respect the NQF's concerns, we note that these
same exclusions align with the exclusions in the Follow-Up After
Hospitalization for Mental Illness (FUH, NQF #0576) measure which is
already NQF endorsed, and which we adopted under the IPFQR Program in
the FY 2014 IPPS/LTCH PPS final rule. This measure has a very similar
denominator (78 FR 50893 through 50895). The clinical expert work group
and technical expert panel convened by our contractor supported these
exclusions as being appropriate for both measures.
After having given due consideration to similar measures, FUH
measure (NQF #0576) and Continuity of Care after Inpatient or
Residential Treatment for SUD (NQF #3453), we believe that the FAPH
measure is an improvement over the FUH measure which is currently in
the IPFQR Program, because it includes patients with SUD or dementia,
populations that also benefit from timely follow-up care (86 FR 19504
through 19506).
Comment: Some commenters recommended further research or testing.
Some commenters recommended that CMS continue to consider evidence
supporting the expanded patient cohort.
Response: We thank commenters for these recommendations and will
[[Page 42645]]
continue to evaluate them as part of our measure monitoring and
evaluation process. We believe that the evidence cited in our proposal,
including the evidence supporting the APA grade of [I] applied to the
2010 guidelines for the treatment of SUD patients that state ``It is
important to intensify the monitoring for substance use during periods
when the patient is at a high risk of relapsing, including during the
early stages of treatment, times of transition to less intensive levels
of care, and the first year after active treatment has ceased'' \150\
is sufficient evidence to support measuring follow up after
hospitalization for SUD. We note that because discharge from an IPF is
a time of transition to less intensive levels of care these guidelines
apply to discharge from an IPF and support the expanded patient cohort.
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\150\ American Psychiatric Association. Practice guideline for
the treatment of patients with substance use disorders. 2010. http://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/substanceuse.pdf.
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Comment: One commenter requested CMS specifically consider the
impact of the physician self-referral law (commonly referred to as
``the Stark Law'') on an IPF's ability to ensure necessary SUD follow-
up care. Some commenters recommended that CMS evaluate additional risk
adjustment for social risk factors. One commenter further expressed
that this measure may not be a successful strategy for reducing
readmissions. Another commenter recommended that CMS investigate
whether FAPH is an appropriate replacement for the Alcohol & Other Drug
Use Disorder Treatment Provided or Offered at Discharge and Alcohol &
Other Drug Use Disorder Treatment at Discharge (SUB-3/3a) measure.
Response: Section 1877 of the Act, also known as the physician
self-referral law: (1) Prohibits a physician from making referrals for
certain designated health services payable by Medicare to an entity
with which he or she (or an immediate family member) has a financial
relationship, unless an exception applies; and (2) prohibits the entity
from filing claims with Medicare (or billing another individual,
entity, or third party payer) for those referred services. A financial
relationship is an ownership or investment interest in the entity or a
compensation arrangement with the entity.\151\ We believe that the
comment regarding the physician self-referral law relates to
compensation arrangements between IPFs (which qualify as hospitals, and
``entities'', for purposes of the physician self-referral law) and
physicians who provide post-discharge SUD follow-up care that may
implicate the physician self-referral law. To the extent an IPF enters
into a compensation arrangement with a physician who provides SUD
follow-up care to patients discharged from the hospital, we note that
there are exceptions to the physician self-referral law applicable to
such compensation arrangements, including recently finalized exceptions
for value-based arrangements.
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\151\ https://www.cms.gov/medicare/fraud-and-abuse/physicianselfreferral.
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We will consider this measure for potential risk adjustment or
stratification as we seek to close the equity gap as described in
section IV.D of this final rule. We note that a reduction in
readmissions is this measure's objective, though improved follow-up
adherence may serve to reduce readmissions because of improved
continuity of care. Finally, we will evaluate whether the FAPH measure
is an appropriate replacement for Alcohol & Other Drug Use Disorder
Treatment Provided or Offered at Discharge and Alcohol & Other Drug Use
Disorder Treatment at Discharge (SUB-3/3a).
Comment: Some commenters requested clarification regarding visits
that would be considered post-discharge follow-up. Some commenters
requested clarification regarding whether telehealth visits,
specifically audio-only telehealth visits, would be considered follow-
up for purposes of the measure. A few commenters requested
clarification regarding whether visits implemented through
collaborative agreements with mental health providers would be
considered follow-ups. These commenters further observed that including
these visits would incentivize community partnerships. One commenter
requested clarification regarding whether a visit to any HCP (including
physicians, clinics, etc.) would be considered follow-up for purposes
of the measure. This commenter further requested clarification
regarding whether specific diagnosis codes would be required to be
present on the follow-up claim.
Response: Regarding the request for clarification about the
eligibility of telehealth visits for FAPH measure, both in-person and
telehealth outpatient visits are acceptable, including audio-only
visits. The FAPH numerator defines qualifying outpatient visits as
outpatient visits, intensive outpatient encounters or partial
hospitalizations that occur within 7 or 30 days of discharge and are
defined by the Current Procedural Terminology (CPT), Healthcare Common
Procedure Coding System (HCPCS), and Uniform Billing (UB) Revenue
codes, with or without the GT telehealth modifier. The CPT codes 99441,
99442, and 99443, which represent telephone E/M visits, are included in
the list of codes to identify eligible outpatient visits. With respect
to the request for clarification regarding collaborative agreements,
the measure is agnostic to relationships between mental health
providers, other providers, and health systems. The codes used to
identify outpatient visits for the FAPH measure are not limited to
mental health providers. The outpatient visit may be any outpatient
visit, intensive outpatient encounter or partial hospitalization that
occurs within 7 or 30 days of discharge as defined in section
IV.E.3.b.(1). This visit must be paired with a qualifying ICD-10-CM
diagnosis of mental illness or substance use disorder used to define
the denominator.
Comment: One commenter observed that historical trending would no
longer be available due to the transition from FUH to FAPH.
Response: We agree with the commenter that replacing FUH with FAPH
would mean that historical trending would no longer be available.
However, we believe that the benefits associated with the expanded
patient population and the expanded provider types for follow-up
appointments outweigh the loss of trend data.
After consideration of the public comments, we are finalizing the
FAPH measure as proposed for the FY 2024 payment determination and
subsequent years.
F. Removal or Retention of IPFQR Program Measures
1. Background
In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38463 through
38465), we adopted considerations for removing or retaining measures
within the IPFQR Program and criteria for determining when a measure is
``topped out.'' In the FY 2019 IPF PPS final rule (83 FR 38591 through
38593), we adopted one additional measure removal factor. We did not
propose any changes to these removal factors, topped-out criteria, or
retention factors and refer readers to the FY 2018 IPPS/LTCH PPS final
rule (82 FR 38463 through 38465) and the FY 2019 IPF PPS final rule (83
FR 38591 through 38593) for more information. We will continue to
retain measures from each previous year's IPFQR Program measure set for
subsequent years' measure sets, except when we specifically propose to
remove or replace a measure. We will continue to use the notice-and-
comment rulemaking
[[Page 42646]]
process to propose measures for removal or replacement, as we described
upon adopting these factors in the FY 2018 IPPS/LTCH PPS final rule (82
FR 38464 through 38465).
In the FY 2022 IPF PPS proposed rule we described that in our
continual evaluation of the IPFQR Program measure set under our
Meaningful Measures Framework and according to our measure removal and
retention factors, we identified four measures that we believed were
appropriate to propose removing from the IPFQR Program for the FY 2024
payment determination and subsequent years (86 FR 19507). Our
discussion of these measures follows.
2. Measures Proposed for Removal in the FY 2022 IPF PPS Proposed Rule
a. Retention of the Alcohol Use Brief Intervention Provided or Offered
and Alcohol Use Brief Intervention (SUB- 2/2a) Measure Beginning With
FY 2024 Payment Determination
We proposed to remove the Alcohol Use Brief Intervention Provided
or Offered (SUB-2) and subset measure Alcohol Use Brief Intervention
(SUB2a) collectively referred to as the SUB-2/2a measure from the IPFQR
Program beginning with the FY 2024 payment determination under our
measure removal Factor 8, ``The costs associated with a measure
outweigh the benefit of its continued use in the program.'' We adopted
the Alcohol Use Brief Intervention Provided or Offered and Alcohol Use
Brief Intervention (SUB- 2/2a) measure in the FY 2016 IPF PPS final
rule (80 FR 46699 through 46701) because we believe it is important to
address the common comorbidity of alcohol use among IPF patients. This
measure requires facilities to chart-abstract measure data on a sample
of IPF patient records, in accordance with established sampling
policies (80 FR 46717 through 46719).
We have previously stated our intent to move away from chart-
abstracted measures to reduce information collection burden in this and
other CMS quality programs (78 FR 50808; 79 FR 50242; 80 FR 49693).
When we adopted the SUB-2/2a measure to the IPFQR Program, the benefits
of this measure were high because IPF performance was not consistent.
Therefore, the measure provided a means of distinguishing IPF
performance and incentivized facilities to improve rates of treatment
for this common comorbidity. Between the FY 2018 payment determination
(the first year that SUB-2/2a was included in the IPFQR Program measure
set) and the FY 2019 payment determination, we saw substantial
performance improvement on the SUB-2 measure (which is the portion of
the SUB-2/2a measure that assesses whether the IPF provided or offered
a brief intervention for alcohol use). However, for the FY 2019 and FY
2020 payment determinations, the rate of improvement has leveled off to
consistently high performance, as indicated in Table 3. These data
further show that at this time there is little room for improvement in
the SUB 2 measure, and that the quality improvement benefits from the
measure have greatly diminished.
As stated in the proposed rule, we continue to believe that alcohol
use is an important comorbidity to address in the IPF setting, and that
brief interventions are a key component of addressing this comorbidity.
However, based on these data, we believe that most IPFs routinely offer
alcohol use brief interventions, and that IPFs will continue to offer
these interventions to patients, regardless of whether the SUB-2/2a
measure is in the IPFQR Program measure set, because it has become an
embedded part of their clinical workflows.
[GRAPHIC] [TIFF OMITTED] TR04AU21.172
In the proposed rule, we noted that while the measure does not meet
our criteria for ``topped-out'' status because of the TCV higher than
0.1, we believe that this measure no longer meaningfully supports the
program objectives of informing beneficiary choice and driving
improvement in IPF interventions for alcohol use because it is no
longer showing significant improvement in IPF performance (that is, in
providing or offering alcohol use brief interventions). Furthermore, as
we stated in the FY 2019 IPF PPS final rule, costs are multi-faceted
and include not only the burden associated with reporting, but also the
costs associated with implementing and maintaining the program (83 FR
38592). For example, it may be costly for health care providers to
maintain general administrative knowledge to report this measure.
Additionally, CMS must expend resources in maintaining information
collection systems, analyzing reported data, and providing public
reporting of the collected information.
Here, IPF information collection burden and related costs
associated with reporting the SUB 2/2a measure to CMS are high because
it is a chart-abstracted measure. Furthermore, CMS incurs costs
associated with the program oversight of the measure for public
display. As a result, we believe that the costs and burdens associated
with this chart-abstracted measure outweigh the benefit of its
continued use in the program.
Therefore, we proposed to remove the Alcohol Use Brief Intervention
Provided or Offered and Alcohol Use Brief Intervention (SUB-2/2a)
measure from the IPFQR Program beginning with the FY 2024 payment
determination. We welcomed public comments on our proposal to remove
the SUB-2/2a measure from the IPFQR Program.
We received the following comments on our proposal.
Comment: Many commenters supported our proposal to remove the
Alcohol Use Brief Intervention Provided or Offered and Alcohol Use
Brief Intervention (SUB-2/2a) measure. Some commenters agreed with our
rationale that the costs of this measure outweigh the benefit of its
continued use in the IPFQR Program. A few commenters recommended that
CMS remove the measure immediately, rather than beginning with FY 2024
payment determination as proposed, to further reduce burden. One
commenter agreed
[[Page 42647]]
that providers will continue these interventions after the measure has
been removed. Another commenter also supported removal because the
measure is no longer NQF endorsed and was not specified for this
setting.
Response: We thank the commenters for their support. While we
continue to believe that the performance on the SUB-2/2a measure in
recent years indicates that IPFs routinely offer alcohol use brief
interventions, we recognize that we will not be able to monitor whether
IPFs continue these interventions if we remove this measure. We
considered proposing to remove the measure sooner, but because data are
currently being collected to report during CY 2022 to inform the FY
2023 payment determination, we proposed removing the measure following
that payment determination, that is, for the FY 2024 payment
determination.
The commenter is correct that the measure is no longer NQF endorsed
and is not specified for the IPF setting. However, we continue to
believe that this measure is appropriate for the IPF setting. We
reiterate that we proposed to remove this measure because of the belief
that the costs of the measure outweigh its continued benefits in the
IPFQR Program, not because it is no longer NQF endorsed nor because it
was not specified for this setting.
Comment: One commenter supported removal of the SUB-2/2a measure,
but recommended development of more meaningful measures than SUB-2/2a
and the Alcohol & Other Drug Use Disorder Treatment Provided or Offered
at Discharge and Alcohol & Other Drug Use Treatment at Discharge (SUB-
3/3a) measure to address screening and intervention for substance use.
Another commenter recommended that CMS consult with consumers to
ascertain the benefits of measures in the IPFQR Program prior to
proposing to remove any such measures, this commenter specifically
recommended that CMS not finalize removal of the SUB-2/2a measure until
fully considering input from consumers.
Response: We appreciate this commenter's input and are continually
seeking to improve our measure set by developing more meaningful and
less burdensome measures. As we evaluate areas appropriate for measure
development, we will consider additional measures or measure concepts
that more meaningfully address alcohol use disorder treatment for the
IPF patient population.
In response to the request that we consult with consumers to
ascertain the benefits of the measure, we note that we evaluate input
from all stakeholders, including consumers, patients, caregivers, and
patient advocacy groups that we receive in response to our proposals to
adopt or remove measures from the IPFQR Program. As part of this
process, we have reviewed input from consumers regarding the benefits
of the measure and considered this input in our analysis.
Comment: Some commenters expressed concern about removing the
measure. A few of these commenters stated that not all facilities
perform well on the measure and, therefore, there is still room for
improvement. One commenter stated that the COVID-19 pandemic has led to
increased alcohol use and expressed the belief that removing the
measure now is poorly timed.
Response: We note that we proposed to remove the measure because of
the belief that the benefits of retaining it have lessened to the point
that its costs outweigh those benefits, not because the measure is
topped out. We agree with commenters that not all facilities perform
uniformly well on the Alcohol Use Disorder Brief Intervention Provided
or Offered and Alcohol Use Disorder Brief Intervention Provided (SUB-2/
2a) measure.
We also agree that alcohol use has increased during the COVID-19
pandemic.152 153 154 In our literature review regarding this
comment, we also identified evidence that individuals with mental
health and substance use conditions may be at an increased risk of
COVID-19 complications and appropriate substance use disorder treatment
may help mitigate these complications.155 156 To ensure that
providers would continue to address alcohol use disorders among this
patient population, we have maintained the Alcohol & Other Drug Use
Disorder Treatment Provided or Offered at Discharge and Alcohol & Other
Drug Use Treatment at Discharge (SUB-3/3a) measure. However, we note
that a prominent model to ensure those with alcohol use disorder are
identified and referred to treatment include both brief interventions
and referrals.\157\ Given the increased need for alcohol use brief
interventions due to the pandemic, the current performance levels \158\
(for FY 2018 payment determination, the mean performance nationally was
approximately 80 percent of patients who screened positive for alcohol
use disorder were offered or provided a brief intervention), and the
importance of providing alcohol use brief interventions to improve the
efficacy of alcohol use treatment at discharge, we believe that the
benefits of retaining the Alcohol Use Brief Intervention Provided or
Offered and Alcohol Use Brief Intervention (SUB-2/2a) measure are
greater than we initially estimated in our proposal to remove this
measure and that the measure should not be removed from the program at
this time.
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\152\ Pollard et. al., Changes in Adult Alcohol Use and
Consequences During the COVID-19 Pandemic in the US, JAMA Network
Open, 2020;3(9):e2022942. doi:10.1001/jamanetworkopen.2020.22942.
\153\ Alcohol Consumption Rises Sharply During Pandemic
Shutdown; Heavy Drinking by Women Rises 41%, RAND, https://www.rand.org/news/press/2020/09/29.html.
\154\ Nemani et al., Association of Psychiatric Disorders With
Mortality Among Patients With COVID-19, JAMA Psychiatry.
2021;78(4):380-386. doi:10.1001/jamapsychiatry.2020.4442; COVID-19
and people at increased risk, CDC, https://www.cdc.gov/drugoverdose/resources/covid-drugs-QA.html; U. Saengow et. al.
\155\ Wang et. al., COVID-19 risk and outcomes in patients with
substance use disorders: Analyses from electronic health records in
the United States, Molecular Psychiatry volume 26, pages 30-39
(2021), https://www.nature.com/articles/s41380-020-00880-7.
\156\ Vai et. al., Mental disorders and risk of COVID-19-related
mortality, hospitalisation, and intensive care unit admission: A
systematic review and meta-analysis, Lancet Psychiatry, https://www.thelancet.com/pdfs/journals/lanpsy/PIIS2215-0366(21)00232-7.pdf.
\157\ https://www.samhsa.gov/sbirt; https://www.samhsa.gov/sbirt/coding-reimbursement.
\158\ For FY 2018 payment determination, the mean performance
nationally was approximately 80 percent of patients who screened
positive for alcohol use disorder were offered or provided a brief
intervention.
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Comment: One commenter observed that this measure may be useful for
future stratification based on race and ethnicity.
Response: We agree with the commenter that this measure may be
useful for future stratification based on race and ethnicity. While we
do not believe it would be appropriate to retain this measure
specifically for the purpose of potential future stratification, we
agree that this potential is another benefit of the measure that we had
not considered in our previous analysis of the benefits versus the
costs of retaining the measure.
Comment: One commenter observed that there are benefits to
retaining this measure because IPFs and health systems use performance
data on this measure as part of quality improvement initiatives to
reduce alcohol use and that removal may affect these programs.
Response: We thank the commenter for this input. We note that IPFs
are responsible for abstracting the data for this measure, so we
believe that IPFs who use these data for their own quality improvement
initiatives have access to these data regardless of whether the measure
is in the IPFQR Program.
[[Page 42648]]
However, we recognize that such IPFs and health systems would not have
access to publicly reported data regarding other IPFs and that these
data may be useful for baselining. Therefore, we agree that such IPF
level and systemic programs to reduce alcohol use is a benefit to
retaining the measure that we had not evaluated in our proposal to
remove this measure.
Comment: One commenter observed that this measure is less
burdensome than the newly proposed COVID-19 vaccination measure and
therefore the commenter believes that removing this measure because the
costs, especially the information collection burden, outweigh benefits
is inconsistent.
Response: We evaluate measures on a case-by-case basis looking at
the overall benefits of the measure versus the overall costs of the
measure. Therefore, measures are not evaluated based on whether they
are more or less burdensome than other measures. However, we now
believe that the benefits of retaining this measure are greater than we
had considered in our proposal to remove the measure from the IPFQR
Program measure set.
After consideration of the public comments, we now believe that the
benefits of retaining this measure, which include the potential for
IPFs to continue improving performance on this measure, the importance
of substance use interventions due to increased substance use during
the COVID-19 pandemic, and this measure's potential influence on other
quality improvement activities related to substance use are greater
than we had considered in our proposal to remove the measure from the
IPFQR Program measure set. Accordingly, we are not finalizing our
proposal to remove the Alcohol Use Brief Intervention Provided or
Offered and Alcohol Use Brief Intervention (SUB-2/2a) measure beginning
with the FY 2024 payment determination. That is, we are retaining the
Alcohol Use Disorder Brief Intervention Provided or Offered and Alcohol
Use Disorder Brief Intervention Provided (SUB-2/2a) measure in the
IPFQR Program measure set.
After consideration of the public comments, we are not finalizing
our proposal to remove the Alcohol Use Brief Intervention Provided or
Offered and Alcohol Use Brief Intervention (SUB-2/2a) measure beginning
with the FY 2024 payment determination. That is, we are retaining the
Alcohol Use Disorder Brief Intervention Provided or Offered and Alcohol
Use Disorder Brief Intervention Provided (SUB-2/2a) measure in the
IPFQR Program measure set.
b. Retention of the Tobacco Use Treatment Provided or Offered and
Tobacco Treatment (TOB-2/2a) Measure Beginning With FY 2024 Payment
Determination \159\
---------------------------------------------------------------------------
\159\ We note that the proposed rule incorrectly referred to
this measure as the Tobacco Use Brief Intervention Provided or
Offered and Tobacco Use Brief Intervention (TOB-2/2a) measure, we
have corrected it here and throughout this final rule.
---------------------------------------------------------------------------
We proposed to remove the Tobacco Use Treatment Provided or Offered
(TOB-2) and Treatment (TOB-2a), collectively referred to as the TOB-2/
2a measure from the IPFQR Program beginning with the FY 2024 payment
determination under our measure removal Factor 8, ``The costs
associated with a measure outweigh the benefit of its continued use in
the program.'' We adopted the Tobacco Use Treatment Provided or Offered
and Tobacco Use Treatment (TOB-2/2a) measure in the FY 2015 IPF PPS
final rule (79 FR 45971 through 45972) because we believe it is
important to address the common comorbidity of tobacco use among IPF
patients. Like SUB-2/2a described in the previous subsection, this
measure requires facilities to chart-abstract measure data on a sample
of IPF patient records, in accordance with established sampling
policies (80 FR 46717 through 46719).
When we introduced the TOB-2/2a measure to the IPFQR Program, the
benefits of this measure were high, because IPF performance was not
consistent and therefore the measure provided a means of distinguishing
IPF performance and incentivized facilities to improve rates of
treatment for this common comorbidity. Between the FY 2017 payment
determination (the first year that TOB-2/2a was included in the IPFQR
Program's measure set) and the FY 2019 payment determination we saw
substantial performance improvement on TOB-2. However, between the FY
2019 and FY 2020 payment determinations, that improvement has leveled
off to consistently high performance, as indicated in Table 4. These
data further show that currently there is little room for improvement
in the TOB-2 measure, and that the quality improvement benefits from
the measure have greatly diminished. We continue to believe that
tobacco use is an important comorbidity to address in the IPF setting,
and that brief interventions are a key component of addressing this
comorbidity. However, based on these data, we stated in the proposed
rule that we believe that most IPFs routinely offer tobacco use brief
interventions, and that IPFs will continue to offer these interventions
to patients, regardless of whether the TOB-2/2a measure is in the IPFQR
Program measure set, because it has become an embedded part of their
clinical workflows.
[GRAPHIC] [TIFF OMITTED] TR04AU21.173
While the measure does not meet our criteria for ``topped-out''
status because of the TCV higher than 0.1, we believe that this measure
no longer meaningfully supports the program objectives of informing
beneficiary choice and driving improvement in IPF interventions for
tobacco use because it is no longer showing significant improvement in
IPF performance (that is, in providing or offering tobacco use brief
interventions). Furthermore, as we
[[Page 42649]]
stated in the FY 2019 IPF PPS final rule, costs are multi-faceted and
include not only the burden associated with reporting, but also the
costs associated with implementing and maintaining the program (83 FR
38592). For example, it may be costly for health care providers to
maintain general administrative knowledge to report this measure.
Additionally, CMS must expend resources in maintaining information
collection systems, analyzing reported data, and providing public
reporting of the collected information. Here, IPF information
collection burden and related costs associated with reporting this
measure to CMS are high because the measure is a chart-abstracted
measure. Furthermore, CMS incurs costs associated with the program
oversight of the measure for public display. As a result, we believe
that the costs and burdens associated with this chart-abstracted
measure outweigh the benefit of its continued use in the program.
Therefore, we proposed to remove the Tobacco Use Treatment Provided
or Offered and Tobacco Use Treatment (TOB-2/2a) measure from the IPFQR
Program beginning with the FY 2024 payment determination. We welcomed
public comments on our proposal to remove the TOB-2/2a measure from the
IPFQR Program.
We received the following comments on our proposal.
Comment: Many commenters supported our proposal to remove the
Tobacco Use Treatment Provided or Offered and Tobacco Use Treatment
(TOB-2/2a) measure. Some of these commenters agreed with our rationale
that the costs of this measure outweigh the benefits of its continued
use in the IPFQR Program. Several commenters recommended removing the
measure immediately, rather than beginning with FY 2024 payment
determination as proposed, to further reduce burden. One commenter
agreed that providers will continue offering this intervention even if
it is not being measured. Another commenter further expressed that
removal is appropriate because the measure is no longer NQF endorsed
and is not specified for this setting.
Response: We thank the commenters for their support. We considered
proposing to remove the measure sooner, but because data are currently
being collected to report during CY 2022 to inform the FY 2023 payment
determination, we proposed to remove the measure following that payment
determination, that is, for the FY 2024 payment determination. While we
continue to believe that the performance on the TOB-2/2a measure in
recent years indicates that IPFs routinely offer tobacco use cessation
interventions during the inpatient stay, we recognize that we will not
be able to monitor whether IPFs continue these interventions if we
remove this measure. The commenter is correct that the measure is no
longer NQF endorsed and is not specified for the IPF setting. We
reiterate that we proposed to remove this measure because of the belief
that the costs of the measure outweigh its continued benefits in the
IPFQR Program not because it is no longer NQF endorsed nor because it
was not specified for this setting and we continue to believe that this
measure is appropriate for the IPF setting.
Comment: One commenter expressed the belief that progress in
electronic reporting systems leads to lower burden for reporting this
measure. This commenter expressed the belief that this reduced burden
should factor into the consideration of whether costs outweigh benefits
and recommended that CMS retain this measure.
Response: We thank the commenter for this feedback. However, we
note that because this is a chart-abstracted measure, we do not believe
access to electronic reporting systems will significantly impact the
burden of collecting and reporting this measure for most IPFs.
Comment: One commenter supported removal of the Tobacco Use
Treatment Provided or Offered and Tobacco Use Treatment Provided (TOB-
2/2a) measure, but recommended development of more meaningful measures
than TOB-2/2a and Tobacco Use Treatment Provided or Offered at
Discharge and Tobacco Use Treatment Provided at Discharge (TOB-3/3a) to
address screening and intervention for tobacco use. One commenter
recommended that CMS seek consumer input on the benefit of measures
before proposing to remove them.
Response: We appreciate this commenter's input and are continually
seeking to improve our measure set by developing more meaningful and
less burdensome measures. As we evaluate areas appropriate for measure
development, we will consider additional measures or measure concepts
that more meaningfully address tobacco use treatment for the IPF
patient population.
In response to the request that we consult with consumers to
ascertain the benefits of the measure, we note that we evaluate input
from all stakeholders, including consumers, patients, caregivers, and
patient advocacy groups that we receive in response to our proposals to
adopt or remove measures from the IPFQR Program. As part of this
process, we have reviewed input from consumers regarding the benefits
of the measure and considered this input in our analysis.
Comment: Some commenters expressed concern about removing the TOB-
2/2a measure from the IPFQR Program measure set. Some of these
commenters expressed that there continues to be significant room for
improvement in providing interventions. One commenter specifically
observed that the measure is not topped out. A few commenters observed
that the proposed removal is poorly timed due to the increase in
tobacco use during the COVID-19 pandemic. Another commenter cited
evidence supporting the benefit of brief interventions as part of a
comprehensive program to address topped out.
We agree with commenters that not all facilities perform uniformly
well on the Tobacco Use Treatment Provided or Offered and Tobacco Use
Treatment Provided (TOB-2/2a) measure. We also agree with the
commenter's observation that tobacco use has increased during the
COVID-19 pandemic.\160\ In our literature review, we also identified
evidence that individuals who use tobacco may be at an increased risk
of COVID-19 complications and tobacco use treatment may help mitigate
these complications.\161\ To ensure that providers would continue to
address tobacco use among this patient population, we maintained the
Tobacco Use Treatment Provided or Offered at Discharge and Tobacco Use
Treatment Provided at Discharge (TOB-3/3a). However, we agree with the
commenter who expressed that these interventions are most effective as
part of a comprehensive tobacco treatment program. Given the increased
need for tobacco use interventions due to the COVID-19 pandemic, that
this measure is not topped out and there is room for improvement across
facilities,\162\ and the importance of providing tobacco use treatment
during the inpatient stay to improve the efficacy of tobacco use
treatment at discharge, we believe that the benefits of retaining the
Tobacco Use Treatment Provided or Offered and Tobacco Use Treatment
Provided (TOB-2/2a) measure are greater than we
[[Page 42650]]
estimated in our proposal to remove this measure and that the measure
should not be removed from the program at this time.
---------------------------------------------------------------------------
\160\ Giovenco et. al., Multi-level drivers of tobacco use and
purchasing behaviors during COVID-19 ``lockdown'': A qualitative
study in the United States, International Journal of Drug Policy,
Volume 94, August 2021, 103175.
\161\ https://www.who.int/news/item/11-05-2020-who-statement-tobacco-use-and-covid-19.
\162\ For the FY 2018 payment determination, the mean
performance nationally was approximately 79 percent of patients who
screened positive for tobacco use were provided or offered treatment
while inpatients.
---------------------------------------------------------------------------
Comment: Many commenters opposed removal of the measure because of
the clinical importance of treating tobacco use in the IPF patient
population. Many of these commenters observed that tobacco use is
undertreated. Some of these commenters referenced CDC data stating that
only 48.9 percent of mental health treatment facilities reported
screening patients for tobacco use. Some commenters pointed to this
statistic and expressed concern that without measures related to
tobacco use treatment this care may no longer be provided in IPFs.
These commenters observed that tobacco use is nearly three times more
prevalent in people with serious psychological distress than in those
without. Some of these commenters observed that this discrepancy
contributes to a shorter life expectancy for patients with mental
illness who smoke. These commenters expressed the belief that the
potential to increase patient life expectancy and quality of life
outweighs the costs of reporting the measure. A few of these commenters
observed there are high costs associated with treating tobacco
associated illness and that these costs could be significantly reduced
by increased screening, intervention, and treatment.
Some commenters stated that the 2020 Surgeon General's report
specifically stated that tobacco dependence treatment is applicable to
the behavioral health setting. One commenter observed that brief
interventions are part of the ``Treating Tobacco Use and Dependence
Clinical Practice Guidelines.'' One commenter stated that behavioral
health patients often have limited interaction with the healthcare
system and therefore the commenter believes that it is important to use
these interactions to drive health behaviors.
Response: We agree with commenters that providing or offering
tobacco use brief intervention within the IPF setting is a valuable
intervention because of the prevalence of this comorbidity within this
patient population and because of the ability of this intervention to
facilitate quitting tobacco use. We further agree that brief
interventions are part of clinical guidelines and are appropriate to
provide to patients receiving care for behavioral health conditions. We
note that the tobacco screening statistics cited by commenters refer to
all behavioral health and substance use treatment facilities, whereas
the IPFQR Program only requires reporting on treatment provided by IPFs
that receive Medicare payment under the IPF PPS, therefore the
statistics cited by commenters do not directly reflect care provided by
IPFs.\163\ However, we acknowledge that the low performance on tobacco
use screening in the behavioral health setting does indicate that
tobacco screening and treatment performance may lapse in the IPF
setting without measures to address this topic, and that the inpatient
setting may be a uniquely opportune setting for providing tobacco
cessation interventions to some patients due to limited access to or
utilization of the healthcare system. We also agree with commenters
that providing tobacco use brief interventions has the potential to
increase patient life expectancy and quality of life while reducing
healthcare costs associated with treating tobacco associated illness.
Given the importance of tobacco use interventions in extending life
expectancy and improving quality of life, the concern regarding
potential reduction in performance if measures are removed (as
demonstrated by CDC data that show that the provision of brief
intervention for tobacco use cessation is not the current standard of
care across behavioral health settings as only 48.9 percent of mental
health treatment facilities report screening patients for tobacco use),
and the room for improvement in the current performance levels, we
believe that the benefits of retaining the Tobacco Use Treatment
Provided or Offered and Tobacco Use Treatment Provided (TOB-2/2a)
measure are greater than we estimated in our proposal to remove this
measure and that the measure should not be removed from the program at
this time.
---------------------------------------------------------------------------
\163\ https://www.cdc.gov/mmwr/volumes/67/wr/mm6718a3.htm.
---------------------------------------------------------------------------
Comment: One commenter observed that there are health equity
concerns regarding tobacco use and recommended that CMS retain this
measure for future stratification based on race and ethnicity.
Response: We agree with the commenter that this measure may be
useful for future stratification based on race and ethnicity. While we
do not believe it would be appropriate to retain this measure
specifically for the purpose of potential future stratification, we
agree that this potential is another benefit of the measure that we had
not considered in our previous analysis of the benefits versus the
costs of retaining the measure.
Comment: One commenter observed that there are benefits to
retaining this measure because IPFs and health systems use performance
data on this measure as part of quality improvement initiatives to
reduce tobacco use and that measure removal may affect those programs.
Response: We thank the commenter for this feedback. We note that
IPFs are responsible for abstracting the data for this measure, so we
believe that IPFs who use these data for their own quality improvement
initiatives have access to these data regardless of whether the measure
is in the IPFQR Program. However, we recognize that such IPFs and
health systems would not have access to publicly reported data
regarding other IPFs and that these data may be useful for baselining.
Therefore, we agree that such IPF level and systemic programs to reduce
tobacco use is a benefit to retaining the measure that we had not
evaluated in our proposal to remove this measure.
Comment: Many commenters expressed the belief that without this
measure IPFs would not continue to provide tobacco use brief
interventions. Some commenters expressed concern that removing this
measure would reduce providers' incentive to offer brief interventions.
These commenters further observed that it would be difficult to
determine whether IPFs continue to offer this intervention as the
ability to track that depends on the continued collection of this
measure. Some commenters further expressed concern that CMS policies
drive the behavior of other payers and without this measure the
healthcare system may lose focus on tobacco treatment for patients with
behavioral health disorders.
Response: We understand commenters' concern regarding the potential
for IPFs and other payers to no longer focus on tobacco treatment
without the Tobacco Use Treatment Provided or Offered and Tobacco Use
Treatment (TOB-2/2a) quality measure in the IPFQR Program and we agree
that ensuring continuing focus on tobacco use treatment in this setting
is a benefit of retaining this measure in the IPFQR program.
Additionally, we agree that tracking whether IPFs continue to offer
this intervention is a benefit of retaining the measure in the IPFQR
program measure set.
Comment: One commenter observed that the Tobacco Use Treatment
Provided or Offered and Tobacco Use Treatment (TOB-2/2a) measure is not
as burdensome as the newly proposed COVID-19 vaccination measure and
therefore the commenter believes that removing this measure because the
costs, especially the information
[[Page 42651]]
collection burden, outweigh benefits is inconsistent.
Response: We evaluate measures on a case-by-case basis looking at
the overall benefits of the measure versus the overall costs of the
measure. Therefore, measures are not evaluated based on whether they
are more or less burdensome than other measures. However, we now
believe that the benefits of retaining this measure are greater than we
had considered in our proposal to remove the measure from the IPFQR
Program measure set.
After consideration of the public comments, we now believe that the
benefits of retaining this measure, which include the potential for
IPFs to continue improving performance on this measure, the importance
of tobacco use interventions due to increased tobacco use during the
COVID-19 pandemic, and this measure's potential influence on other
quality improvement activities related to tobacco use, are greater than
we had considered in our proposal to remove the measure from the IPFQR
Program measure set. Accordingly, we are not finalizing our proposal to
remove the Tobacco Use Treatment Provided or Offered and Tobacco Use
Treatment (TOB-2/2a) measure beginning with the FY 2024 payment
determination. That is, we are retaining the Tobacco Use Treatment
Provided or Offered and Tobacco Use Treatment (TOB-2/2a) measure in the
IPFQR Program measure set.
c. Removal of the Timely Transmission of Transition Record (Discharges
From an Inpatient Facility to Home/Self Care or Any Other Site of Care)
Measure Beginning With FY 2024 Payment Determination
We proposed to remove the Timely Transmission of Transition Record
(Discharges from an Inpatient Facility to Home/Self Care or Any Other
Site of Care) measure from the IPFQR Program beginning with the FY 2024
payment determination under our measure removal Factor 8, ``The costs
associated with a measure outweigh the benefit of its continued use in
the program.''
We adopted the Timely Transmission of Transition Record (Discharges
from an Inpatient Facility to Home/Self Care or Any Other Site of Care)
measure in the FY 2016 IPF PPS final rule (80 FR 46706 through 46709)
because more timely communication of vital information regarding the
inpatient hospitalization results in better care, reduction of systemic
medical errors, and improved patient outcomes. The Timely Transmission
of Transition Record (Discharges from an Inpatient Facility to Home/
Self Care or Any Other Site of Care) measure builds on the Transition
Record with Specified Elements Received by Discharged Patients
(Discharges from an Inpatient Facility to Home/Self Care or Any Other
Site of Care) measure, which requires facilities to provide a discharge
record with 11 specified elements to patients at discharge.
We continue to believe that the 11 elements required by the
Transition Record with Specified Elements measure provide meaningful
information about the quality of care provided by IPFs, and we
therefore did not propose to remove that measure from the IPFQR
Program. However, we believe that the benefits of requiring facilities
to transmit the discharge record with 11 specified elements to the next
level care provided within 24 hours, as required by the Timely
Transmission of Transition Record (Discharges from an Inpatient
Facility to Home/Self Care or Any Other Site of Care) measure, have
been reduced. Reporting this measure requires facilities to chart-
abstract measure data on a sample of IPF patient records, in accordance
with established sampling policies (80 FR 46717 through 46719). On May
1, 2020, we updated the Conditions of Participation (CoPs) for IPFs
participating in the Medicare program in the Medicare and Medicaid
Programs; Patient Protection and Affordable Care Act; Interoperability
and Patient Access for Medicare Advantage Organization and Medicaid
Managed Care Plans, State Medicaid Agencies, CHIP Agencies and CHIP
Managed Care Entities, Issuers of Qualified Health Plans on the
Federally Facilitated Exchanges, and Health Care Providers final rule
(85 FR 25588).
In the May 1, 2020 update to the CoPs, we adopted a requirement for
psychiatric hospitals that possess EHR or other administrative systems
with the technical capacity to generate information for electronic
patient event notifications to send electronic patient event
notifications of a patient's admission, discharge, transfer to another
health care facility or to another community provider, or combination
of patient events at the time of a patient's discharge or transfer.
Because these updated CoP requirements overlap with, but are not the
same as, the requirements for the Timely Transmission of Transition
Record (Discharges from an Inpatient Facility to Home/Self Care or Any
Other Site of Care) measure (which requires transmission of a discharge
record with 11 specified elements to the next level care provider
within 24 hours of the patient's discharge rather that requiring
notification regarding the patient's inpatient stay to be transmitted
at discharge), we believe that the adoption of these updated CoPs
increases the costs of the Timely Transmission of Transition Record
(Discharges from an Inpatient Facility to Home/Self Care or Any Other
Site of Care) measure while decreasing its benefit. Specifically, we
believe that the costs of this measure are increased because facilities
to which the new CoPs apply (that is, facilities that possess EHR or
other administrative systems with the technical capacity to generate
information for electronic patient event notifications as defined in
the CoP) could bear increased cost if they separately implement the
patient event notifications meeting both the criteria for the updated
CoPs and the capacity to share a transition record that meets the
requirements of our measure. We noted that the updated CoPs do not
include the level of detail regarding data to be transferred at
discharge that our Timely Transmission of Transition Record (Discharges
from an Inpatient Facility to Home/Self Care or Any Other Site of Care)
measure requires. While the set of information in the CoP notification
policy is a minimal set of information, we believe that it would
continue to be appropriate for providers to transmit the transition
record that they will continue to be providing to patients under our
Transition Record Received by Discharged Patients (Discharges from an
Inpatient Facility to Home/Self Care or Any Other Site of Care)
measure, we further note that the CoPs referenced in the proposed rule
are not an exhaustive list of data transfer requirements.
We believe the different requirements regarding both timeliness of
notification and contents of notification could lead some providers to
send two separate discharge notifications to meet the separate
requirements. Further, we believe that the benefits of the measure are
reduced because all facilities to which the new CoPs apply will be
sending patient discharge information to the next level of care
provider as required by the CoPs. Therefore, the benefits of this
measure are reduced because it is less likely to ensure that these
facilities provide patient discharge information to the next level care
provider, and it is less likely to provide information to help
consumers differentiate quality between facilities. While these updated
CoPs do not directly address transmission of patient event
notifications for facilities that do not possess EHR systems with the
capacity to generate information for electronic patient event
notifications,
[[Page 42652]]
such facilities should continue to transmit data using their existing
infrastructure and timelines.
Because we believe that the costs are now increased and the
benefits are now reduced, we believe that the costs and burdens
associated with this chart-abstracted measure outweigh the benefit of
its continued use in the IPFQR Program.
Therefore, we proposed to remove the Timely Transmission of
Transition Record (Discharges from an Inpatient Facility to Home/Self
Care or Any Other Site of Care) measure from the IPFQR Program
beginning with the FY 2024 payment determination. We welcomed public
comments on our proposal to remove the Timely Transmission of
Transition Record (Discharges from an Inpatient Facility to Home/Self
Care or Any Other Site of Care) measure from the IPFQR Program.
We received the following comments on our proposal.
Comment: Many commenters supported the removal of the Timely
Transmission of Transition Record (Discharges from an Inpatient
Facility to Home/Self Care or Any Other Site of Care) measure. One
commenter recommended immediate removal to further reduce burden.
Another commenter expressed that this measure was not developed for
IPFs and has been difficult to report because the specifications are
not appropriate for the setting. Another commenter further noted that
the measure is no longer NQF endorsed.
Response: We thank the commenters for their support. We considered
removing the measure sooner, but because data are currently being
collected to report during CY 2022 to inform the FY 2023 payment
determination, we decided to propose removing the measure following
that payment determination, therefore we proposed removal for the FY
2024 payment determination. The commenter is correct that the measure
is no longer NQF endorsed and is not specified for the IPF setting;
however we continue to believe that this measure is appropriate for the
setting. We reiterate that removal of the measure is because we believe
that the costs of the measure outweigh its continued benefits in the
IPFQR Program.
Comment: Some commenters observed that the updated CoPs will not
apply to many IPFs, especially freestanding IPFs that are not part of
larger healthcare facilities, because IPFs were excluded from
Meaningful Use incentives and therefore often do not have electronic
data systems capable of meeting the standards in the updated CoPs.
Response: We acknowledge that there are a large number of IPFs that
do not possess EHR systems with the technical capacity to generate
information for electronic patient event notifications of a patient's
admission, discharge, or transfer to another health care facility or to
another community provider, or combination of patient events at the
time of a patient's discharge or transfer. However, for those IPFs that
can meet these requirements, we believe that retaining the Timely
Transmission of Transition Record (Discharges from an Inpatient
Facility to Home/Self Care or Any Other Site of Care) measure could be
burdensome depending on how facilities implement new requirements.
Therefore, while for some IPFs the benefits may outweigh the costs,
overall, for the IPFQR Program we believe the costs now outweigh the
benefits. We reiterate that for IPFs that do not possess EHR systems
with the capacity to generate information for patient event
notifications as defined in the CoP regulations set forth at 42 CFR
482.24(d), such facilities should continue to transmit data using their
existing infrastructure and timelines.
Comment: A few commenters recommended that CMS retain the Timely
Transmission of Transition Record (Discharges from an Inpatient
Facility to Home/Self Care or Any Other Site of Care) measure. Some of
these commenters believe that the measure's benefits are more
significant than the burden. One commenter recommended that CMS seek
consumer input on benefits prior to proposing measures for removal.
Response: We reiterate that we do not believe that the benefits of
transmitting the transition record within 24 hours of discharge are
reduced, or are lower than the costs of reporting; we believe that
given the updates to the CoPs which overlap with this measure the
benefits of retaining the Timely Transmission of Transition Record
(Discharges from an Inpatient Facility to Home/Self Care or Any Other
Site of Care) measure are no longer sufficient to justify retention. We
used the notice and comment rulemaking process to solicit input on
measure benefits from all stakeholders, including consumers.
After consideration of the public comments, we are finalizing our
proposal to remove the Timely Transmission of Transition Record
(Discharges from an Inpatient Facility to Home/Self Care or Any Other
Site of Care) measure beginning with the FY 2024 payment determination.
d. Removal of the Follow-Up After Hospitalization for Mental Illness
(FUH, NQF #0576) Beginning With FY 2024 Payment Determination
In the FY 2022 IPF PPS proposed rule we stated that if we finalize
adoption of the Follow-Up After Psychiatric Hospitalization measure
described in section IV.E.3, we believed that our current measure
removal Factor 3 would apply to the existing Follow-Up After
Hospitalization for Mental Illness (FUH, NQF #0576) measure (86 FR
19510). Measure removal Factor 3 applies when a ``measure can be
replaced by a more broadly applicable measure (across settings or
populations) or a measure that is more proximal in time to desired
patient outcomes for the particular topics.'' We adopted removal factor
3 in the FY 2017 IPPS/LTCH PPS final rule (82 FR 38463 through 38465).
The FAPH measure expands the patient population from patients with
mental illness to also include patients with primary SUD diagnoses
while addressing the same important aspect of care transitions. Because
this FAPH measure uses the same methodology to address the same element
of care for a broader patient population than the FUH measure, we
believe that it is more broadly applicable across populations.
Therefore, we proposed to remove the FUH measure under measure
removal Factor 3 only if we finalized our proposal to adopt of the FAPH
measure. We noted that if we did not adopt the FAPH measure, we would
retain the FUH measure because we believe this measure addresses an
important clinical topic. We welcomed public comments on our proposal
to remove FUH if we were to adopt FAPH.
We received the following comments on our proposal.
Comment: Many commenters supported removal of this measure. Some
commenters specifically noted that FAPH is more broadly applicable and
therefore preferable.
Response: We thank these commenters for their support.
Comment: One commenter does not support either the FUH measure or
the FAPH measure due to the belief that measures of follow-up after
hospitalization are not appropriate for the IPFQR Program and
recommended removing the FUH measure but not adopting the FAPH measure.
Response: For the reasons set forth in the FY 2014 IPPS/LTCH PPS
final rule (78 FR 50894 through 50895) and the FY 2022 IPF PPS proposed
rule in our proposal to adopt the FAPH measure (86 FR 19504 through
19507), we believe that a measure of follow-after
[[Page 42653]]
hospitalization is an important concept for the inpatient psychiatric
setting. Therefore, we do not believe it would be appropriate to remove
the FUH measure without adopting the FAPH measure.
Comment: One commenter observed that the FUH measure is an NQF-
endorsed measure, while the NQF declined to endorse the FAPH measure.
This commenter recommended retaining the FUH measure because it is
endorsed.
Response: The commenter is correct that the FUH measure is NQF
endorsed and that the NQF declined to endorse the FAPH measure.
However, as discussed in the FY 2022 IPF PPS proposed rule, the FUH
measure does not apply to as broad a patient population, nor does it
allow for follow-up care to be provided by as many provider types (86
FR 19507). Further, for the reasons we discussed in the FY 2022 IPF PPS
proposed rule, we believe the exception under section 1886(s)(4)(D)(ii)
of the Act applies (86 FR 19507). Because the FAPH measure is a more
broadly applicable measure we believe it is appropriate for adoption
into the IPFQR Program.
After consideration of the public comments, we are finalizing our
proposal to remove Follow-Up After Hospitalization for Mental Illness
(FUH, NQF #0576) measure beginning with the FY 2024 payment
determination.
G. Summary of IPFQR Program Measures
1. IPFQR Program Measures for the FY 2023 Payment Determination and
Subsequent Years
There are 14 previously finalized measures for the FY 2023 payment
determination and subsequent years. In this final rule, we are adopting
one measure for the FY 2023 payment determination and subsequent years.
The 15 measures which will be in the program are shown in Table 5.
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2. IPFQR Program Measures for the FY 2024 Payment Determination and
Subsequent Years
There are 14 previously finalized measures for the FY 2024 payment
determination and subsequent years. In this final rule, we are adopting
one measure for the FY 2023 payment determination and subsequent years.
Additionally, we are finalizing our proposal to remove one measure and
replace one measure for the FY 2024 payment determination and
subsequent years. We are not finalizing our proposals to remove two
measures for the FY 2024 payment determination and subsequent years.
The 14 measures which will be in the program for FY 2024 payment
determination and subsequent years are shown in Table 6.
[[Page 42654]]
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H. Considerations for Future Measure Topics
As we have previously indicated, we seek to develop a comprehensive
set of quality measures to be available for widespread use for informed
decision-making and quality improvement in the IPF setting (79 FR 45974
through 45975). Therefore, through future rulemaking, we intend to
propose new measures for development or adoption that will help further
our goals of achieving better healthcare and improved health for
individuals who obtain inpatient psychiatric services through the
widespread dissemination and use of quality information. In 2017, we
introduced the Meaningful Measures Framework as a tool to foster
operational efficiencies and reduce costs including collection and
reporting burden while producing quality measurement that is more
focused on meaningful outcomes (83 FR 38591). As we continue to evolve
the Meaningful Measures Framework, we have stated that we intend to
better address health care priorities and gaps, emphasize digital
quality measurement, and promote patient perspectives.\164\ As we work
to align the IPFQR Program's measure set with these priorities, we have
identified the following areas that we believe are important to
stakeholders, but which are not covered in the current IPFQR Program
measure set: Patient Experience of Care, Functional Outcomes
Measurement, and digital measures. As described in the following
subsections, we sought public comment on each of these topics and other
future measure considerations which stakeholders believe are important.
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\164\ https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
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We received the following public comment on measure considerations
which stakeholders believe are important.
Comments: Many commenters suggested measure areas that they believe
are important for IPFs. These areas were: (1) Suicide evaluation and
reduction; (2) patient experience; (3) patient improvement; (4)
clinical processes that impact significant numbers of patients in
important clinical domains; (5) patient and workforce safety; (6)
caregiver engagement; (7) safety culture; (8) workforce engagement, (9)
immunization status; (10) measures that more rigorously capture data on
tobacco and substance use interventions; and (11) discharge planning
measures. Some commenters recommended developing improved discharge
planning measures. One commenter recommended that CMS ensure that the
role of nurse practitioners is included in measures. One commenter
recommend that CMS engage with patients and their caregivers to
identify topics they find important. Another commenter recommended that
CMS seek industry input on measure considerations.
Response: We thank these commenters for this input. We will
consider these recommendations as we seek to develop a more
comprehensive measure set for the IPFQR Program.
1. Patient Experience of Care Data Collection Instrument
When we finalized removal of the Assessment of Patient Experience
of
[[Page 42655]]
Care attestation measure in the FY 2019 IPF PPS final rule (83 FR
38596) we stated that we believed we had collected sufficient
information to inform development of a patient experience of care
measure that would capture data on the results of such a survey. In the
FY 2020 IPF PPS proposed rule (84 FR 16986 through 16987), we solicited
input on how providers had implemented the Hospital Consumer Assessment
of Healthcare Providers and Systems (HCAHPS) survey in their
facilities. We also sought public comment on other potential surveys
that commenters believed would be appropriate to adopt for the IPFQR
Program. We received many comments on this subject, and many of these
comments expressed that there is not one survey used predominantly
across IPFs (84 FR 38467). Additional commenters expressed concerns
that the HCAHPS survey may not be appropriate for the IPF setting
because it does not include some of the unique aspects of inpatient
psychiatric care including, group therapy, non-physician providers, and
involuntary admissions. While we did not solicit public comment on this
issue in the FY 2021 IPF PPS proposed rule, we received many comments
addressing this issue (85 FR 47043). We continue to seek to identify a
minimally burdensome patient experience of care instrument that would
be appropriate for the IPF setting. Therefore, in the FY 2022 IPF PPS
proposed rule (86 FR 19511 through 19512) we sought public comment on
instruments currently in use in the IPF setting, input on whether the
HCAHPS survey may be appropriate for this setting, and information on
how facilities that currently use the HCAHPS survey have addressed
challenges with using this survey within this setting (that is,
concerns regarding unique aspects of inpatient psychiatric care).
We received the following comments in response to our request.
Comment: Many commenters expressed support for development of a
uniform patient experience of care measure because this is a gap in the
IPFQR measure set. Many commenters expressed that there is currently no
patient experience of care measure in the IPFQR Program and expressed
the belief that such a survey could improve provider accountability,
show respect for patients, and drive quality improvement. Some
commenters observed that patients should be given the opportunity to
share their experiences regardless of diagnosis. One commenter observed
that evaluations of patient experience of care can be a driver of
health equity.
Many commenters shared personal or family experiences in IPFs and
indicated that being able to share such experiences in a formal survey
would allow patients and caregivers to have a voice, provide valuable
feedback, feel respected, provide information for quality improvements,
and inform other potential patients. One commenter observed that
allowing proxies would be valuable. Some commenters observed that not
collecting patient experience of care data leads to the perception that
patients' opinions are not valid and expressed the concern that this
message may further objectify and traumatize a vulnerable patient
population in a stressful and potentially stigmatizing situation (that
is, psychiatric hospitalization). Other commenters expressed that not
collecting such data normalizes poor treatment of psychiatric patients.
Some commenters observed that patients with psychiatric illness are not
less likely to be competent to express their experience of care than
patients with other acute care needs.
Many commenters recommended that CMS identify a minimum set of
items to include in surveys, as opposed to requiring a specific survey.
These commenters observed that the net promoter score (NPS) used by the
National Health Service in the UK may be a good model to consider. Some
commenters observed that many facilities have designed their own
surveys tailored to their patient populations (for example, pediatric
patients, involuntarily admitted, etc.) and that it would be preferable
for these facilities to add questions to meet a minimum set rather than
to replace their surveys.
Many commenters expressed that they do not support HCAHPS for the
IPF setting. These commenters expressed that (1) the HCAHPS was
developed for patients with non-psych primary diagnoses and not for
behavioral health diagnoses therefore the questions on HCAHPS do not
address patients' top concerns regarding IPF care; (2) the survey
protocols which allow for administration of the survey up to 6 weeks
post-discharge may negatively impact completion rates due to the
transient nature of the patient population; (3) the protocols do not
have a web-interface for survey administration nor email or text survey
invites; and (4) HCAHPS does not account for involuntary admissions.
Some commenters also expressed concern that HCAHPS is not validated,
nor has it been through psychometric testing in this setting. Some
commenters observed the HCAHPS survey is due for a redesign and
observed that CMS could potentially address concerns with the HCAHPS
survey as part of the intended redesign. Other commenters recommended
that CMS develop a survey unique to this setting that addresses aspects
of care specific to the setting (such as group therapy, treatment by
therapists, involuntary admission, medication treatment, consistency of
treatment). One commenter recommended that CMS collaborate with AHRQ in
survey design and development. Some commenters recommended that CMS
ensure proper risk adjustment because patient characteristic can affect
patient experience.
Some commenters observed that the questions on HCAHPS apply to IPF
patients and recommended that CMS test HCAHPS for this setting. A few
of these commenters observed that using the same measure across
settings would improve behavioral health parity, facility comparison,
and reduce burden for facilities that are distinct part units in acute
care hospitals that use HCAHPS. A few commenters expressed concern that
excluding psychiatric patients from HCAHPS is discrimination based on a
disability which, because of the benefits derived from patient
experience surveys, denies patients with psychiatric diagnoses equal
treatment. Other commenters observed that minimizing burden is not a
factor in establishing patient experience of care measures in other
settings and that therefore it should not be a consideration in this
setting. Some commenters observed that CMS has requested and received
input on this subject for several years and requested a specific plan
of action.
A few commenters recommended that CMS collaborate with IPFs to
determine how to assess patients' experience of care, several
commenters recommended that CMS establish a technical expert panel
(TEP) with IPF members.
One commenter recommended that CMS reintroduce the attestation
measure until a solution for assessing patient experience of care is
identified.
Response: We thank these commenters for their input. We agree that
Patient Experience of Care is a gap in the current IPFQR Program
measure set and we agree with commenters that adoption of such a
measure would be a meaningful step towards ensuring that patients have
a voice regarding the care they receive. We appreciate the input from
patients and their caregivers explaining how meaningful such a measure
would be for these stakeholders. We intend to use the feedback provided
here and in past requests to identify the most appropriate
[[Page 42656]]
path forward towards adopting such a measure as soon as possible.
2. Functional Outcomes Instrument for Use in a Patient Reported
Outcomes Measure
When we introduced the Meaningful Measures Framework, we stated
that we wanted to focus on meaningful outcomes (83 FR 38591). As we
have assessed the IPFQR Program measure set against the Meaningful
Measures Framework, we have identified functional outcomes as a
potential gap area in the IPFQR Program's measure set. Therefore, we
are evaluating whether a patient reported outcomes measure that
assesses functional outcomes, such as global functioning, interpersonal
problems, psychotic symptoms, alcohol or drug use, emotional lability,
and self-harm, would be an appropriate measure to include in the IPFQR
program measure set. If we were to develop such a measure, we would
develop a measure that compares a patient's responses to a standardized
functional outcomes assessment instrument at admission with the
patient's results on the same assessment instrument at discharge. We
sought public comment on the value of such a measure in the IPFQR
program measure set, what would be an appropriate functional outcome
assessment instrument to use in the potential development of such a
measure, and any additional topics or concepts stakeholders believe
would be appropriate for patient reported outcomes measures.
We received the following comments in response to our request.
Comment: Many commenters supported the concept of a functional
outcomes measure and recommended preceding development of such a
measure with an attestation measure which asks IPFs whether they use an
assessment, and if so which one.
Some commenters expressed concern regarding outcome measures in
this setting. One commenter specifically observed that short lengths of
stay often lead to minimal progress on outcomes. One commenter
mentioned the lack of endorsed, public domain outcome measures for this
setting.
A few commenters recommended that CMS convene a technical expert
panel (TEP) on patient reported outcomes for this setting.
One commenter uses PHQ-9 to assess outcomes. Another commenter uses
BASIS-32 or CABA-Y depending on the patient population.
Response: We thank the commenters for their input and will consider
this feedback as we continue to evaluate a functional outcomes measure
for this setting.
3. Measures for Electronic Data Reporting
As we seek to improve digital measurement across our quality
reporting and value-based payment programs, we are considering measures
both within and appropriate to adopt for the IPFQR Program measure set
that would be appropriate for digital data collection. In our
assessment of the current measure set, we identified the Transition
Record with Specified Elements Received by Discharged Patients
(Discharges from an Inpatient Facility to Home/Self Care or Any Other
Site of Care) measure as a potential option for digital data
collection. We sought stakeholder input on the current data collection
burden associated with this measure, concerns regarding potential
electronic specification and data collection for this measure, and
other measures that may be appropriate for electronic data collection,
either those currently in the IPFQR Program measure set, or those that
we could adopt in the future.
We received the following comments in response to our request.
Comment: Several commenters supported transitioning the IPFQR
Program to electronic reporting.
Many commenters observed that IPFs have not received Federal
incentives to support EHR adoption and expressed the belief that
electronic data reporting without such funding is premature.
Some commenters observed that the Transition Record measure is a
complicated measure for e-specification. Some of these commenters noted
that this measure requires a large number of data elements, some of
which are not available in structured fields. One commenter recommended
considering Metabolic Screening or Influenza Immunization for
electronic specification as these measures have fewer data elements and
those elements are available in structured fields. Another commenter
observed that e-specification of existing chart measures often does not
provide comparable results.
Response: We thank commenters for this input. We acknowledge that
IPFs were not eligible to receive prior Federal incentives to support
EHR adoption and will consider this and other input as we seek to
transition the IPFQR Program to electronic data reporting.
I. Public Display and Review Requirements
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53653 through 53654), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50897
through 50898), and the FY 2017 IPPS/LTCH PPS final rule (81 FR 57248
through 57249) for discussion of our previously finalized public
display and review requirements. We did not propose any changes to
these requirements.
J. Form, Manner, and Timing of Quality Data Submission for the FY 2022
Payment Determination and Subsequent Years
1. Procedural Requirements for the FY 2023 Payment Determination and
Subsequent Years
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53654 through 53655), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50898
through 50899), and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38471
through 38472) for our previously finalized procedural requirements. In
this final rule, we are finalizing our proposal to use the term
``QualityNet security official'' instead of ``QualityNet system
administrator,'' finalizing our proposal to revise Sec. 412.434(b)(3)
by replacing the term ``QualityNet system administrator'' with the term
``QualityNet security official,'' and clarifying our policy under the
previously finalized requirement that hospitals ``[i]dentify a
QualityNet Administrator who follows the registration process located
on the QualityNet website'' (77 FR 53654).
a. Updated References to QualityNet System Administrator and to No
Longer Require Active Account To Qualify for Payment
The previously finalized QualityNet security administrator
requirements, including those for setting up a QualityNet account and
the associated timelines, are described in the FY 2013 IPPS/LTCH final
rule (77 FR 53654).
In the FY 2022 IPF PPS proposed rule, we proposed to use the term
``QualityNet security official'' instead of ``QualityNet system
administrator'' to denote the exercise of authority invested in the
role and align with the Hospital Outpatient Quality Reporting Program
and other programs (86 FR 19512). The term ``security official'' would
refer to ``the individual(s)'' who have responsibilities for security
and account management requirements for a IPF's QualityNet account. To
clarify, this update in terminology will not change the individual's
responsibilities or add burden.
We invited public comment on our proposal to replace the term
``QualityNet system administrator'' with ``QualityNet security
official.''
[[Page 42657]]
We did not receive any public comments on this proposal.
We are finalizing our proposal to replace the term ``Quality Net
system administrator'' with ``QualityNet security official'' as
proposed.
Additionally, we proposed to no longer require IPFs to maintain an
active QualityNet security official account to qualify for payment. As
we reviewed the requirements for the security official role and the
basic user \165\ role to identify the most appropriate language to
describe the distinguishing authority invested in the security official
role, we recognized that the QualityNet security official is not
required for submitting data--a basic user can serve in this role--but
remains necessary to set up QualityNet basic user accounts and for
security purposes. Therefore, consistent with adopting the security
official term to differentiate the unique security authority and
responsibilities of the role from the data submission responsibilities
of the basic user role, we would continue to require a QualityNet basic
user account to meet IPFQR Program requirements, including data
submission and administrative requirements, while recommending, but not
requiring, that hospitals maintain an active QualityNet security
official account.
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\165\ We also noted that a basic user is a QualityNet user who
(1) does not have the registration access described for security
officials, (2) has the appropriate data entry roles and permissions
for program participation, (3) can submit and review measures and
non-measure data, (4) signs and submits the Data Accuracy
Completeness Acknowledgement (DACA) form, and (5) refreshes their
QualityNet account password every 180 days to ensure that the
facility's IPFQR Program Notice of Participation status is
``Participating.''
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We welcomed public comments on our proposal to no longer require
facilities to maintain an active QualityNet security official account
to qualify for payment.
We received the following comments in response to our proposal.
Comment: Many commenters supported removal of the requirement to
have an active QualityNet Security Official for the complete year to
meet IPFQR Program requirements and therefore be eligible to receive a
full payment update.
Response: We thank these commenters for their support. We note that
IPFs that do not meet all IPFQR Program requirements must receive a 2
percent reduction to their annual payment update.
After review of the public comments received, we are finalizing our
proposal to no longer require facilities to maintain an active
QualityNet security official account to qualify for payment as
proposed.
b. Updated Reference to QualityNet Administrator in Code of Federal
Regulations
We proposed to revise our regulation at Sec. 412.434(b)(3) by
replacing ``QualityNet system administrator'' with ``QualityNet
security official.'' The term ``QualityNet security official'' refers
to the individual(s) who have responsibilities for security and account
management requirements for a hospital's QualityNet account. To
clarify, this update in terminology would not change the individual's
responsibilities or add burden. The revised paragraph (b)(3) reads:
``Contact information for the inpatient psychiatric facility's chief
executive officer and QualityNet security official, including each
individual's name, email address, telephone number, and physical
mailing address.''
We invited public comment on our proposal to replace the term
``QualityNet system administrator'' with ``QualityNet security
official'' at Sec. 412.434(b)(3).
We did not receive any public comments in response to our proposal.
We are finalizing our proposal to no longer require facilities to
replace the term ``QualityNet system administrator'' with ``QualityNet
security official'' at Sec. 412.434(b)(3) as proposed.
2. Data Submission Requirements
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53655 through 53657), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50899
through 50900), and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38472
through 38473) for our previously finalized data submission
requirements. In this final rule, we are finalizing our proposal to
adopt one measure for the FY 2023 payment determination and subsequent
years and one measure for the FY 2024 payment determination and
subsequent years. Data submission requirements for each of these
measures are described in the following subsections. Additionally, we
are finalizing our proposal to adopt patient level data submission for
certain chart abstracted measures beginning with data submitted for the
FY 2023 payment determination and subsequent years; details of this
proposal are in subsection c. of this section.
a. Data Submission Requirements for FY 2023 Payment Determination and
Subsequent Years
The measure we are finalizing for FY 2023 payment determination and
subsequent years (the COVID-19 Vaccination Coverage Among HCP measure)
requires facilities to report data on the number of HCP who have
received completed vaccination course of a COVID-19 vaccine through the
CDC's National Healthcare Safety Network (NHSN). Specific details on
data submission for this measure can be found in the CDC's Overview of
the Healthcare Safety Component, available at https://www.cdc.gov/nhsn/PDFs/slides/NHSN-Overview-HPS_Aug2012.pdf. For each CMS Certification
Number (CCN), a percentage of the HCP who received a completed vaccine
course of the COVID-19 vaccination would be calculated and publicly
reported, so that the public would know what percentage of the HCP have
been vaccinated in each IPF.
For the COVID-19 HCP Vaccination measure, we proposed that
facilities would report the numerator and denominator for the COVID-19
HCP vaccination measure to the NHSN for at least one week each month,
beginning in October 2021 for the October 1, 2021 through December 31,
2021 reporting period affecting the FY 2023 payment determination. If
facilities report more than one week of data in a month, the most
recent week's data would be used to calculate the measure. Each
quarter, the CDC would calculate a single quarterly result of COVID-19
vaccination coverage which would summarize the data submitted by IPFs
for each of the three weeks of data submitted over the three-month
period. CMS will publicly report the CDC's quarterly summary of COVID-
19 vaccination coverage for IPFs.
We invited public comment on our proposal to require facilities to
report the COVID-19 HCP vaccination measure.
We did not receive any comments in response to our proposal.
We are finalizing our proposal to require facilities to report the
COVID-19 HCP vaccination measure as proposed.
b. Data Submission Requirements for FY 2024 Payment Determination and
Subsequent Years
Because the Follow-Up After Psychiatric Hospitalization (FAPH)
measure would be calculated by CMS using Medicare Fee-for-Service
claims, there will be no additional data submission requirements for
the FY 2024 payment determination and subsequent years. Therefore, we
did not propose any changes to our data submission policies associated
with the proposal to adopt this measure.
[[Page 42658]]
c. Patient-Level Reporting for Certain Chart-Abstracted Measures
Beginning With FY 2024 Payment Determination and Subsequent Years
In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53655 through
53657), we finalized that IPFs participating in the IPFQR Program must
submit data to the Web-Based Measures Tool found in the Inpatient
Psychiatric Facility section of the QualityNet website's secure portal
between July 1 and August 15 of each year. We noted that the data input
forms within the Quality Net secure portal require submission of
aggregate data for each separate quarter. In the FY 2014 IPPS/LTCH PPS
final rule, we clarified our intent to require that IPFs submit
aggregate data on measures on an annual basis via the Web-Based
Measures Tool found in the IPF section of the Quality Net website's
secure portal and that the forms available require aggregate data for
each separate quarter (78 FR 50899 through 50900). In the FY 2016 IPF
PPS final rule (80 FR 46716), we updated our data submission
requirements to require facilities to report data for chart-abstracted
measures to the Web-Based Measures Tool on an aggregate basis by year,
rather than by quarter. Additionally, we discontinued the requirement
for reporting by age group. We updated these policies in the FY 2018
IPPS/LTCH PPS final rule (82 FR 38472 through 38473) to change the
specification of the submission deadline from exact dates to a 45-day
submission period beginning at least 30 days following the end of the
data collection period.
In the FY 2019 IPF PPS final rule (83 FR 38607), we observed that
reporting aggregate measure data increases the possibility of human
error, such as making typographical errors while entering data, which
cannot be detected by CMS or by data submission systems. We noted that
unlike patient-level data reporting, aggregate measure data reporting
does not allow for data accuracy validation, thereby lowering the
ability to detect error. We stated that we were considering requiring
patient-level data reporting (data regarding each patient included in a
measure and whether the patient was included in each numerator and
denominator of the measure) of IPFQR measure data in the future. We
sought public comment on including patient-level data collection in the
IPFQR program. Several commenters expressed support for patient-level
data collection, observing that it provides greater confidence in the
data's validity and reliability. Other commenters recommended that CMS
use a system that has already been tested and used for IPF data
reporting or work with IPFs in selecting a system so that any selected
system would avoid additional burden.
We believe that patient-level data reporting would improve the
accuracy of the submitted and publicly reported data without increasing
burden. As we considered the current IPFQR measure set, we determined
that patient-level reporting of the Hours of Physical Restraint Use
(HBIPS-2, NQF #0640) measure and Hours of Seclusion Use (HBIPS-3,\166\
NQF #0641) measure would be appropriate for the numerators of these
measures only, because these measures are calculated with a denominator
of 1,000 hours rather than a denominator of patients who meet specific
criteria for inclusion in the measure. Therefore, we proposed to
require reporting patient-level information for the numerators of these
measures only. For the remainder of the chart-abstracted measures in
the IPFQR Program we proposed to require patient-level reporting of the
both the numerator and the denominator. Table 7 lists the proposed FY
2023 IPFQR measure set categorized by whether we would require patient-
level data submission through the QualityNet secure portal.
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\166\ We note that in the FY 2022 IPF PPS proposed rule this
incorrectly read HBIPS-2 (86 FR 19514). We have corrected it to
HBIPS-3 here.
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Submission of aggregate data requires facilities to abstract
patient-level data, then calculate measure performance prior to
submitting data through the QualityNet website's secure portal. For
measures for which we would require patient-level data submission, we
would allow facilities to submit data using a tool such as the CMS
Abstraction & Reporting Tool (CART). This is the tool we use in our
other quality reporting and value-based purchasing programs, and
therefore, we believe that many facilities may already have familiarity
with using this tool to abstract and report data. Additionally, the
tool has been specifically designed to facilitate data reporting and
minimize provider burden.
We note that under aggregate data reporting, facilities submit
aggregate numerators and aggregate denominators for all measures to CMS
in the Hospital Quality Reporting (HQR) system. These aggregate
numerators and denominators are generally calculated by manually
abstracting the medical record of each included patient using the
algorithm, a paper tool, or a vendor abstraction tool. After each
required medical record has been abstracted, the numerator and
denominator results are added up and submitted as aggregate values in
the HQR system. Under our patient level data reporting proposal,
facilities would still manually abstract the medical record using
either a vendor abstraction tool or an abstraction tool provided by
CMS. The vendor abstraction tool or the CMS tool would then produce an
individual XML file for each of the cases abstracted. Instead of
submitting the aggregate data, the IPF would log into HQR and upload
batches of XML files that contain patient level data for each measure
with data from all patients whose records were abstracted, and CMS
would calculate the aggregate numerators, aggregate denominators, and
measure rates from those XML file submissions. Because facilities must
abstract patient-level data as one step in calculating measure results,
we do not believe that requiring patient-level data submission would
increase provider costs or burden associated with measure submission.
[[Page 42660]]
Because we believe that patient-level data would improve the data
accuracy without increasing provider burden, we proposed to adopt
patient-level data reporting for numerators only for the Hours of
Physical Restraint Use (HBIPS-2, NQF #0640) and the Hours of Seclusion
Use (HBIPS-3, NQF #0631) for numerators and denominators for the
following 9 chart-abstracted IPFQR Program measures as detailed in
Table 7: Patients Discharged on Multiple Antipsychotic Medications with
Appropriate Justification (NQF #0560); Alcohol Use Brief Intervention
Provided or Offered and SUB-2a Alcohol Use Brief Intervention; Alcohol
and Other Drug Use Disorder Treatment Provided or Offered at Discharge
and SUB-3a Alcohol and Other Drug Use Disorder Treatment at Discharge;
Tobacco Use Treatment Provided or Offered and TOB-2a Tobacco Use
Treatment; Tobacco Use Treatment Provided or Offered at Discharge and
TOB-3a Tobacco Use Treatment at Discharge; Influenza Immunization (NQF
#1659); Transition Record with Specified Elements Received by
Discharged Patients (discharges from an Inpatient Facility to Home/Self
Care or Any Other Site of Care); Timely Transmission of Transition
Record (Discharges from an Inpatient Facility to Home/Self Care or any
Other Site of Care); and Screening for Metabolic Disorders.
We believe that it is appropriate to transition to patient-level
reporting incrementally. This would allow facilities to become familiar
with the data submission systems and to provide feedback on any
challenges they face in reporting data to us. Therefore, we proposed to
allow voluntary patient-level data submission for the FY 2023 payment
determination (that is, data submitted during CY 2022). We note that
because participation in patient-level reporting for these chart-
abstracted measures would be voluntary for this one-year period,
facilities would be able to choose whether to submit measure data in
aggregate or at the patient level, and would not face a payment
reduction as long as they submit all measure data either at the patient
level or in aggregate for each measure for which reporting is required,
and as long as they met all other IPFQR Program requirements.
Therefore, we are proposed to allow voluntary patient-level reporting
prior to requiring such data submission for one year prior to the FY
2024 payment determination. We will ensure that facilities have
guidance available through our standard communications channels (that
is, listserv announcements, educational webinars, and training material
on the QualityNet website).
We also proposed to require patient-level data submission for these
chart-abstracted measures for the FY 2024 payment determination (that
is, data submitted during CY 2023) and subsequent years.
We welcomed comment on our proposals to allow voluntary patient-
level data reporting for these chart-abstracted measures for the FY
2023 payment determination and then to require patient-level data
reporting for the FY 2024 payment determination and subsequent years.
We received the following comments in response to our proposal.
Comment: Many commenters supported the adoption of patient-level
reporting. Many of these commenters supported initiating the process
with one year of voluntary participation. One commenter observed that
having patient level data would help accurately identify trends and
improve outcomes and with demographic data could help identify health
disparities. One commenter specifically supported the numerator only
patient-level reporting for HBIPS-2 and HBIPS-3. One commenter observed
that HBIPS-2 was listed twice in the proposed rule (86 FR 19514).
Response: We thank these commenters for their support.
Comment: Some commenters recommended that CMS use a more gradual
transition to patient-level reporting. One commenter specifically
recommended two cycles of voluntary reporting to ensure that the data
submission system works properly. Others recommended that CMS provide
additional guidance and education, including XML specifications or
other reporting templates prior to the voluntary reporting period. One
commenter recommended aligning guidance across programs. One commenter
observed that the start date for collecting data for the mandatory
reporting period is before the data submission timeframe for the
voluntary reporting period.
Response: We recognize that IPFs will need additional guidance and
education in preparation for patient-level reporting. We will provide
templates, guidance, and education and outreach sessions prior to
beginning patient level reporting. We note that, to the extent
feasible, we will align guidance across programs. We do not believe
that it is necessary to have a longer voluntary reporting period
because many IPFs also have experience with these tools already and we
have extensive experience with patient-level reporting, both using
electronic data reporting systems, and using tools such as the CMS
Abstraction & Reporting Tool (CART) in our other quality reporting
programs and intend to provide templates, guidance and education and
outreach to IPFs.
Comment: Some commenters recommended that CMS not require patient
level reporting for measures proposed for removal.
Response: We note that the measure being removed from the IPFQR
Program (Timely Transmission of Transition Record (Discharges from an
Inpatient Facility to Home/Self Care or any Other Site of Care)) is
being removed for FY 2024 payment determination and subsequent years.
The first year of mandatory patient-level reporting is FY 2024 payment
determination. Therefore, this measure will no longer be in the program
when patient-level reporting is required. We further note that we are
not finalizing our proposals to remove Alcohol Use Brief Intervention
Provided or Offered and Alcohol Use Brief Intervention (SUB-2/2a) and
Tobacco Use Treatment Provided or Offered and Tobacco Use Treatment
(TOB-2/2a); and therefore these patient-level data reporting will be
required for these measures beginning with the FY 2024 payment
determination.
Comment: Some commenters oppose patient level reporting because of
a lack of technology. Some commenters observed that CMS should assist
with development of EHRs in the same way they did for acute care
hospitals. One commenter observed that patient-level reporting would be
burdensome without EHR technology.
Response: We disagree with commenters that EHR technology is
necessary for patient level reporting and note that acute care
hospitals reported patient-level data for the Hospital IQR Program
prior to the introduction of the HITECH act and associated meaningful
use incentives. We further note that because IPFs must abstract the
same data from patient records regardless of whether they are reporting
at the patient-level or in aggregate, we do not believe that submitting
patient-level data is more burdensome than aggregate data reporting for
providers whether or not they have EHR technology.
Comment: One commenter requested clarification on the start date
for voluntary patient-level data submission for FY 2023. This commenter
specifically requested clarification on whether that would be for
discharges beginning for FY 2023 or CY 2023.
Response: The voluntary patient-level data submission period is for
FY 2023 payment determination. This applies to the data submitted
during CY 2022
[[Page 42661]]
(which affects FY 2023 payment determination). Data submitted during CY
2022 covers discharges that occur during CY 2021.
After review of the public comments we received, we are finalizing
our proposal to allow voluntary patient-level data reporting for these
chart-abstracted measures for the FY 2023 payment determination and
then to require patient-level data reporting for the FY 2024 payment
determination and subsequent years as proposed.
3. Considerations for Data Validation Pilot
As discussed in section IV.J.4 and in the FY 2019 IPF PPS final
rule, we are concerned about the limitations of aggregate data
submission (83 FR 28607). One such concern was that the ability to
detect error is lower for aggregate measure data reporting than for
patient-level data reporting (that is, data regarding each patient
included in a measure and whether the patient was included in the
numerator and denominator of the measure). In the FY 2022 IPF PPS
proposed rule, we noted that if we finalize our proposal to adopt
patient-level data requirements, we would be able to adopt a data
validation policy for the IPFQR Program in the future (86 FR 19515). We
believe that it would be appropriate to develop such a policy
incrementally through adoption of a data validation pilot prior to
national implementation of data validation within the IPFQR Program. We
sought public input on elements of a potential data validation pilot,
for example, the number of measures to validate, number of
participating facilities, whether the pilot should be mandatory or
voluntary, potential thresholds for determining measure accuracy, or
any other policies that commenters believe would be appropriate to
include in a data validation pilot or eventual data validation policy.
We received the following comments in response to our request.
Comment: Many commenters supported the concept of data validation
but recommended that CMS ensure a stable and successful patient-level
reporting process prior to developing a data validation plan.
One commenter recommended using two measures and 200 hospitals to
pilot data validation.
Some commenters did not support eventual adoption of validation for
the IPFQR program because of the belief that data validation would be
burdensome. One commenter observed data validation is only necessary in
pay-for-performance programs.
Response: We thank these commenters for this input and will take it
into consideration if we develop a data validation program for the
IPFQR Program.
4. Reporting Requirements for the FY 2022 Payment Determination and
Subsequent Years
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53656 through 53657), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50900
through 50901), and the FY 2015 IPF PPS final rule (79 FR 45976 through
45977) for our previously finalized reporting requirements. We did not
propose any changes to these policies.
5. Quality Measure Sampling Requirements
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53657 through 53658), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50901
through 50902), the FY 2016 IPF PPS final rule (80 FR 46717 through
46719), and the FY 2019 IPF PPS final rule (83 FR 38607 through 38608)
for discussions of our previously finalized sampling policies. In the
FY 2022 IPF PPS proposed rule, we noted that neither the measure we
proposed to remove (FUH--NQF #0576) nor the measure we proposed to
adopt (FAPH) if we remove the FUH-NQF #0576 are affected by our
sampling policies because these are both calculated by CMS using
Medicare Fee-for-Service claims and, therefore, apply to all Medicare
patients in the denominator (86 FR 19515). Furthermore, the denominator
of the COVID-19 Healthcare Personnel Vaccination measure we are
adopting in this final rule is all healthcare personnel, and therefore,
this measure is not eligible for sampling. We did not propose any
changes to these policies.
6. Non-Measure Data Collection
We refer readers to the FY 2015 IPF PPS final rule (79 FR 45973),
the FY 2016 IPF PPS final rule (80 FR 46717), and the FY 2019 IPF PPS
final rule (83 FR 38608) for our previously finalized non-measure data
collection policies. We did not propose any changes to these policies.
7. Data Accuracy and Completeness Acknowledgement (DACA) Requirements
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53658) for our previously finalized DACA requirements. We did not
propose any changes to these policies.
K. Reconsideration and Appeals Procedures
We refer readers to 42 CFR 412.434 for the IPFQR Program's
reconsideration and appeals procedures. We did not propose any changes
to these policies.
L. Extraordinary Circumstances Exceptions (ECE) Policy
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR
53659 through 53660), the FY 2014 IPPS/LTCH PPS final rule (78 FR
50903), the FY 2015 IPF PPS final rule (79 FR 45978), and the FY 2018
IPPS/LTCH PPS final rule (82 FR 38473 through 38474) for our previously
finalized ECE policies. We did not propose any changes to these
policies.
V. Collection of Information Requirements
Under the Paperwork Reduction Act of 1995 (PRA) (44 U.S.C. 3501 et
seq.), we are required to provide 60-day notice in the Federal Register
and solicit public comment before a ``collection of information'' (as
defined under 5 CFR 1320.3(c) of the PRA's implementing regulations)
requirement is submitted to the Office of Management and Budget (OMB)
for review and approval. In order to fairly evaluate whether an
information collection should be approved by OMB, section 3506(c)(2)(A)
of the PRA requires that we solicit comment on the following issues:
The need for the information collection and its usefulness
in carrying out the proper functions of our agency.
The accuracy of our estimate of the information collection
burden.
The quality, utility, and clarity of the information to be
collected.
Recommendations to minimize the information collection
burden on the affected public, including automated collection
techniques.
In the FY 2022 IPF PPS proposed rule (86 FR 19480) we solicited
public comment on each of the section 3506(c)(2)(A)-required issues for
the following information collection requirements (ICRs). As indicated
in section V.2.c.(1) of this final rule, we received some comments that
generally discuss the burden of reporting through NHSN, but not
comments specific to our information collection estimates. We have not
made any changes from what was proposed.
A. Final ICRs for the (IPFQR) Program
The following final requirement and burden changes will be
submitted to OMB for approval under control number 0938-1171 (CMS-
10432).
[[Page 42662]]
1. Wage Estimates
In the FY 2020 IPF PPS final rule (84 FR 38468), which was the most
recent rule in which we adopted updates to the IPFQR Program, we
estimated that reporting measures for the IPFQR Program could be
accomplished by a Medical Records and Health Information Technician
(BLS Occupation Code: 29-2071) with a median hourly wage of $18.83/hr
(May 2017). In May 2019, the U.S. Bureau of Labor Statistics (BLS)
revised their $18.83/hr wage figure to $20.50/hr (May 2019).\167\ In
response, we proposed to adjust our cost estimates using the updated
median wage rate figure of $20.50/hr., an increase of $1.67/hr. We are
finalizing our proposal to use the $20.50/hr wage in this FY 2022 final
rule.
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\167\ https://www.bls.gov/oes/current/oes292098.htm (Accessed on
June 28, 2021).
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Under OMB Circular A-76, in calculating direct labor, agencies
should not only include salaries and wages, but also ``other
entitlements'' such as fringe benefits and overhead.\168\ Consistent
with our past approach, we continue to calculate the cost of fringe
benefits and overhead at 100 percent of the median hourly wage (81 FR
57266). This is necessarily a rough adjustment, both because fringe
benefits and overhead costs vary significantly from employer to
employer, and methods of estimating these costs vary widely from study
to study. Therefore, using these assumptions, we estimate an hourly
labor cost increase from $37.66/hr ($18.83/hr base salary + $18.83/hr
fringe benefits and overhead) to $41.00/hr ($20.50/hr base salary +
$20.50/hr fringe benefits and overhead). Table 8 presents these
assumptions.
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\168\ http://www.whitehouse.gov/omb/circulars_a076_a76_incl_tech_correction.
[GRAPHIC] [TIFF OMITTED] TR04AU21.177
2. ICRs Regarding the Inpatient Psychiatric Facility Quality Reporting
(IPFQR) Program
In subsection 2.a., we restate our currently approved burden
estimates. In subsection 2.b., we estimate the adjustments in burden
associated with the updated BLS wage rate, our facility estimates, and
our case estimates. In subsection 2.c., we estimate the changes in
burden associated with the finalized policies in this rule. Finally, in
subsection 2.d., we provide an overview of the total estimated burden.
a. Currently Approved Burden
For a detailed discussion of the burden for the IPFQR Program
requirements that we have previously adopted, we refer readers to the
following rules:
The FY 2013 IPPS/LTCH PPS final rule (77 FR 53673);
The FY 2014 IPPS/LTCH PPS final rule (78 FR 50964);
The FY 2015 IPF PPS final rule (79 FR 45978 through
45980);
The FY 2016 IPF PPS final rule (80 FR 46720 through
46721);
The FY 2017 IPPS/LTCH PPS final rule (81 FR 57265 through
57266);
The FY 2018 IPPS/LTCH PPS final rule (82 FR 38507 through
38508);
The FY 2019 IPF PPS final rule (83 FR 38609 through
38612); and
The FY 2020 IPF PPS final rule (84 FR 38468 through
38476).
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\169\ https://www.reginfo.gov/public/do/PRAViewDocument?ref_nbr=201908-0938-011.
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Tables 9, 10, and 11 provide an overview of our currently approved
burden. These tables use our previous estimate of $37.66/hr ($18.83/hr
base salary plus $18.83/hr fringe benefits and overhead) hourly labor
cost. For more information on our currently approved burden estimates,
please see Supporting Statement A on the Office of Information and
Regulatory Affairs (OIRA) website.\169\
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b. Final Adjustments in Burden due to Updated Wage, Facility Count, and
Case Count Estimates
In the FY 2020 IPF PPS final rule (84 FR 38468), which is the most
recent rule, that updated the IPFQR Program policies, we estimated that
there were 1,679 participating IPFs and that (for measures that require
reporting on the entire patient population) these facilities will
report on an average of 1,283 cases per facility. In this FY 2022 rule,
we are finalizing our proposal to update our facility count and case
estimates by using the most recent data available. Specifically, we
estimate that there are now approximately 1,634 facilities (a decrease
of 45 facilities) and an average of 1,346 cases per facility (an
increase of 63 cases per facility). Tables 12, 13, and 14, depict the
effects of these updates, as well as the wage rate update to $41.00/hr
described in section V.A.1 of the preamble of this final rule, on our
previously estimated burden.
[[Page 42666]]
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[[Page 42667]]
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BILLING CODE 4120-01-C
c. Changes in Burden due to This Final Rule
(1) Updates Due to Final Measure Adoptions
In section IV.E of this preamble, we are adopting the following two
measures:
COVID-19 Vaccination Among HCP for FY 2023 Payment
Determination and Subsequent Years; and
Follow-Up After Psychiatric Hospitalization (FAPH) for FY
2024 Payment Determination and Subsequent Years.
We are adopting the COVID-19 Vaccination among HCP measure
beginning with an initial reporting period from October 1 to December
31, 2021 affecting the FY 2023 payment determination followed by
quarterly reporting beginning with the FY 2024 payment determination
and subsequent years. IPFs will submit data through the CDC's NHSN. The
NHSN is a secure, internet-based system that is maintained by the CDC
and provided free. The CDC does not estimate burden for COVID-19
vaccination reporting since the department has been granted a waiver
under Section 321 of the National Childhood Vaccine Injury Act of 1986
(NCVIA).\170\
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\170\ Section 321 of the National Childhood Vaccine Injury Act
(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.
---------------------------------------------------------------------------
Although the burden associated with the COVID-19 HCP Vaccination
measure is not accounted for due to the NCVIA waiver, the burden is set
forth here and will be accounted for by the CDC under OMB control
number 0920-1317.
Consistent with the CDC's experience of collecting data using the
NHSN, we estimate that it will take each IPF on average approximately 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. This burden is comprised of
administrative time and wages. We believe it would take an
Administrative Assistant \171\ between 45 minutes (0.75 hr) and 1 hour
and 15 minutes (1.25 hr) to enter the data into NHSN. For the CY 2021
reporting period (consisting of October 1, 2021 through December 31,
2021) 3 months are required. For the CY 2021 reporting period/FY 2023
payment determination, IPFs would incur an additional burden between
2.25 hours (0.75 hours * 3 responses at 1 response per month) and 3.75
hours (1.25 hours * 3 responses at 1 response per month) per IPF. For
all 1,634 IPFs, the total time would range from 3,676.5 hours (2.25
hours * 1,634 IPFs) and 6,127.5 hours (3.75 hours * 1,634 IPFs).
---------------------------------------------------------------------------
\171\ https://www.bls.gov/oes/current/oes436013.htm (accessed on
March 30, 2021). The hourly rate of $36.62 includes an adjustment of
100 percent of the median hourly wage to account for the cost of
overhead, including fringe benefits.
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Each IPF would incur an estimated cost of between $27.47 (0.75 hour
* $36.62/hr) and $45.78 (1.25 hours * $36.62/hr) monthly and between
$82.40 (2.25 hours * $36.62/hr) and $137.33 (3.75 hours * $36.62/hr) in
total over the CY 2021 reporting period to complete this task.
Thereafter, 12 months of data are required annually. Therefore, IPFs
would incur an additional annual burden between 9 hours (0.75 hours/
month * 12 months) and 15 hours (1.25 hours/month * 12 months) per IPF
and between 14,706 hours (9 hours/IPF * 1,634 IPFs) and 24,510 hours
(15 hours/IPF * 1,634 IPFs) for all IPFs. Each IPF would incur an
estimated cost of between $329.58 (9 hours x $36.62/hr) and $549.30
annually (15 hours x $36.62/hr). The estimated cost across all 1,634
IPFs would be between $134,641.60 ($82.40/IPF * 1,634 IPFs) and
$224,397.22 ($137.33/IPF * 1,634 IPFs) for the CY 2021 reporting
period. The estimated cost across all 1,634 IPFs would be between
$538,533.72 ($329.58/IPF * 1,634 IPFs) and $897,556.20 ($549.30/IPF *
1,634 IPFs) annually thereafter. Since the burden falls under the
authority of the CDC, we have not added such burden to Table 16.
We recognize that many healthcare facilities are also reporting
other COVID-19 data to HHS. We believe the benefits of requiring IPFs
to report data on the COVID-19 HCP Vaccination measure to assess
whether they are taking steps to limit the spread of
[[Page 42669]]
COVID-19 among their healthcare workers and to help sustain the ability
of IPFs to continue serving their communities throughout the PHE and
beyond outweigh the costs of reporting. In our proposed rule, we
welcomed comments on the time to collect data and enter it into the
NHSN. While we did receive some comments addressing the burden of NHSN
reporting, which we address in section IV.E.2 of this rule, we did not
receive any public comments on the estimated time to collect and submit
such data.
We further note that as described in section IV.E.3 of this
preamble, we will calculate the FAPH measure using Medicare Part A and
Part B claims that IPFs and other providers (specifically outpatient
providers who provide the follow-up care) submit for payment. Since
this is a claims-based measure, there is no additional burden outside
of submitting the claim. The claim submission is approved by OMB under
control number 0938-0050 (CMS-2552-10). This rule does not warrant any
changes under that control number.
(2) Updates Due to Final Measure Removals
In section IV.F. of this preamble, we are finalizing our proposals
to remove the following two measures for the FY 2024 payment
determination and subsequent years:
Timely Transmission of Transition Record (Discharges from
an Inpatient Facility to Home/Self Care or Any Other Site of Care); and
FUH--Follow-Up After Hospitalization for Mental Illness
(NQF #0576).
We note that we are not finalizing our proposals to remove the
following two measures:
SUB-2--Alcohol Use Brief Intervention Provided or Offered
and the subset measure SUB-2a Alcohol Use Brief Intervention Provided;
and
TOB-2--Tobacco Use Treatment Provided or Offered and the
subset measure TOB-2a Tobacco Use Treatment.
For the FY 2024 payment determination, data on CY 2022 performance
would be reported during the summer of 2023. Therefore, we are applying
the burden reduction that would occur to the FY 2023 burden
calculation. One of the measures we are removing (the Timely
Transmission of Transition Record (Discharges from an Inpatient
Facility to Home/Self Care or Any Other Site of Care) measure) falls
under our previously finalized ``global sample'' (80 FR 46717 through
46718) and, therefore, would require abstraction of 609 records. We
estimate that removing this measure would result in a decrease in
burden of 152.25 hours per facility (609 cases per facility * 0.25
hours per case), or 248,776.5 hours (152.25 hours/facility x 1,634
facilities) across all IPFs. Therefore, the decrease in costs for each
measure is approximately $6,242.25 per IPF ($41.00/hr * 152.25 hours),
or $10,199,836.50 across all IPFs ($6,242.25/facility * 1,634
facilities).
We have previously estimated that the FUH (NQF #0576) measure does
not have any reporting burden because it is calculated from Medicare
FFS claims. Therefore, we do not anticipate a reduction in facility
burden associated with the removal of this measure. Table 15 describes
our estimated reduction in burden associated with removing these two
measures.
[GRAPHIC] [TIFF OMITTED] TR04AU21.186
[[Page 42670]]
(3) Updates Due to Final Administrative Policies
(a) Updates Associated With Final Updated Reference to QualityNet
System Administrator
In section IV.J.1.a of this preamble, we are finalizing our
proposal to use the term ``QualityNet security official'' instead of
``QualityNet system administrator.'' Because this final update will not
change the individual's responsibilities, we do not believe there would
be any changes to the information collection burden as a result of this
update. We also do not believe that removing the requirement for
facilities to have an active QualityNet security official account to
qualify for payment updates will affect burden because we continue to
recommend that facilities maintain an active QualityNet security
official account.
(b) Updates Associated With Adoption of Patient-Level Reporting for
Certain Chart Abstracted Measures
In section IV.J.2.c of this preamble, we are adopting patient-level
data submission for the 11 chart-abstracted measures currently in the
IPFQR Program measure set (for more details on these measures we refer
readers to Table 7). Because submission of aggregate data requires
facilities to abstract patient-level data, then calculate measure
performance prior to submitting data through the QualityNet website's
secure portal, facilities must already abstract patient-level data.
Therefore, we do not believe that submitting data that facilities must
already calculate through a tool that facilities already have
experience using will change provider burden.
d. Overall Burden Summary
Table 16 summarizes the estimated burden associated with the IPFQR
Program.
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[[Page 42672]]
The total change in burden associated with this final rule
(including all updates to wage rate, case counts, facility numbers, and
the measures and administrative policies) is a reduction of 287,924
hours and $512,065 from our currently approved burden of 3,381,086
hours and $127,331,707. We refer readers to Table 17 for details.
[GRAPHIC] [TIFF OMITTED] TR04AU21.188
BILLING CODE 4120-01-C
VI. Regulatory Impact Analysis
A. Statement of Need
This rule finalizes updates to the prospective payment rates for
Medicare inpatient hospital services provided by IPFs for discharges
occurring during FY 2022 (October 1, 2021 through September 30, 2022).
We are finalizing our proposal to apply the 2016-based IPF market
basket increase of 2.7 percent, less the productivity adjustment of 0.7
percentage point as required by 1886(s)(2)(A)(i) of the Act for a final
total FY 2022 payment rate update of 2.0 percent. In this final rule,
we are finalizing our proposal to update the IPF labor-related share
and update the IPF wage index to reflect the FY 2022 hospital inpatient
wage index.
B. Overall Impact
We have examined the impacts of this final rule as required by
Executive Order 12866 on Regulatory Planning and Review (September 30,
1993), Executive Order 13563 on Improving Regulation and Regulatory
Review (January 18, 2011), the Regulatory Flexibility Act (RFA)
(September 19, 1980, Pub. L. 96 354), section 1102(b) of the Social
Security Act (the Act), section 202 of the Unfunded Mandates Reform Act
of 1995 (March 22, 1995; Pub. L. 104-4), Executive Order 13132 on
Federalism (August 4, 1999), 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). Section
3(f) of Executive Order 12866 defines a ``significant regulatory
action'' as an action that is likely to result in a rule: (1) Having an
annual effect on the economy of $100 million or more in any 1 year, or
adversely and materially affecting a sector of the economy,
productivity, competition, jobs, the environment, public health or
safety, or state, local or tribal governments or communities (also
referred to as ``economically significant''); (2) creating a serious
inconsistency or otherwise interfering with an action taken or planned
by another agency; (3) materially altering the budgetary impacts of
entitlement grants, user fees, or loan programs or the rights and
obligations of recipients thereof; or (4) raising novel legal or policy
issues arising out of legal mandates, the President's priorities, or
the principles set forth in the Executive Order.
A regulatory impact analysis (RIA) must be prepared for major rules
with significant regulatory action/s or with economically significant
effects ($100 million or more in any 1 year).
We estimate that the total impact of these changes for FY 2022
payments compared to FY 2021 payments will be a net increase of
approximately $80 million. This reflects an $75 million increase from
the update to the payment rates (+$100 million from the 2nd quarter
2021 IGI forecast of the 2016-based IPF market basket of 2.7 percent,
and -$25 million for the productivity adjustment of 0.7 percentage
point), as well as a $5 million increase as a result of the update to
the outlier threshold amount. Outlier payments are estimated to change
from 1.9 percent in FY 2021 to 2.0 percent of total estimated IPF
payments in FY 2022.
Based on our estimates, OMB's Office of Information and Regulatory
Affairs has determined that this rulemaking is ``economically
significant,'' and hence also a major rule under Subtitle E of the
Small Business Regulatory Enforcement Fairness Act of 1996 (also known
as the Congressional Review Act).
C. Detailed Economic Analysis
In this section, we discuss the historical background of the IPF
PPS and the impact of this final rule on the Federal Medicare budget
and on IPFs.
1. Budgetary Impact
As discussed in the November 2004 and RY 2007 IPF PPS final rules,
we applied a budget neutrality factor to the Federal per diem base rate
and ECT payment per treatment to ensure that total estimated payments
under the IPF PPS in the implementation period would equal the amount
that would have been paid if the IPF PPS had not been implemented. The
budget neutrality factor includes the following components: Outlier
adjustment, stop-loss adjustment, and the behavioral offset. As
discussed in the RY 2009 IPF PPS notice (73 FR 25711), the stop-loss
adjustment is no longer applicable under the IPF PPS.
As discussed in section III.D.1 of this final rule, we are updating
the wage index and labor-related share in a budget neutral manner by
applying a wage index budget neutrality factor to the Federal per diem
base rate and ECT payment per treatment. Therefore, the budgetary
impact to the Medicare program of this final rule will be due to the
market basket update for FY 2022 of 2.7 percent (see section III.A.4 of
this final rule) less the productivity adjustment of 0.7 percentage
point required by section 1886(s)(2)(A)(i) of the Act and the update to
the outlier fixed dollar loss threshold amount.
We estimate that the FY 2022 impact will be a net increase of $80
million in payments to IPF providers. This reflects an estimated $75
million increase from the update to the payment rates and a $5 million
increase due to the update to the outlier threshold amount to set total
[[Page 42673]]
estimated outlier payments at 2.0 percent of total estimated payments
in FY 2022. This estimate does not include the implementation of the
required 2.0 percentage point reduction of the market basket update
factor for any IPF that fails to meet the IPF quality reporting
requirements (as discussed in section V.A. of this final rule).
2. Impact on Providers
To show the impact on providers of the changes to the IPF PPS
discussed in this final rule, we compare estimated payments under the
IPF PPS rates and factors for FY 2022 versus those under FY 2021. We
determined the percent change in the estimated FY 2022 IPF PPS payments
compared to the estimated FY 2021 IPF PPS payments for each category of
IPFs. In addition, for each category of IPFs, we have included the
estimated percent change in payments resulting from the update to the
outlier fixed dollar loss threshold amount; the updated wage index data
including the updated labor-related share; and the market basket update
for FY 2022, as reduced by the productivity adjustment according to
section 1886(s)(2)(A)(i) of the Act.
Our longstanding methodology uses the best available data as the
basis for our estimates of payments. Typically, this is the most recent
update of the latest available fiscal year of IPF PPS claims, and for
this final rulemaking, that would be the FY 2020 claims. However, as
discussed in section III.F.2 of this final rule, the U.S. healthcare
system undertook an unprecedented response to the COVID-19 PHE during
FY 2020. Therefore, we considered whether the most recent available
year of claims, FY 2020, or the prior year, FY 2019, would be the best
for estimating IPF PPS payments in FY 2021 and FY 2022.
As discussed in the FY 2022 IPF PPS proposed rule (86 FR 19524
through 19526), we examined the differences between the FY 2019 and FY
2020 claims distributions to better understand the disparity in the
estimate of outlier payments as a percentage of total PPS payments
between the two years, which was driving the divergent results in our
proposed rule impacts between FY 2019 claims and FY 2020 claims. Based
on our analysis, we stated that we believe it is likely that the
response to the COVID-19 PHE in FY 2020 has contributed to increases in
estimated outlier payments and to decreases in estimated total PPS
payments in the FY 2020 claims. Therefore, we proposed, in contrast to
our usual methodology, to use the FY 2019 claims to calculate the
outlier fixed dollar loss threshold and wage index budget neutrality
factor.
We requested comments from stakeholders about likely explanations
for the declines in total PPS payments, covered IPF days, and covered
IPF stays in FY 2020. Additionally, we requested comments from
stakeholders about likely explanations for the observed fluctuations
and overall increases in covered lab charges per claim and per day,
which we identified through our analysis. Lastly, we requested comments
regarding likely explanations for the increases in estimated cost per
stay relative to estimated IPF Federal per diem payment amounts per
stay.
Comment: We received 1 comment regarding our analysis of FY 2020
claims and 3 comments in support of our proposal to use FY 2019 claims
for calculating the outlier fixed dollar loss threshold and wage index
budget neutrality factor for FY 2022. One commenter appreciated CMS'
recognition of the impact of the COVID-19 PHE on providers. Another
commenter agreed with our analysis about the effect of the COVID-19 PHE
on the FY 2020 claims, stating their belief that FY 2020 cases were
heavily impacted by the intensity of the COVID-19 pandemic, which
continues to subside.
Response: We appreciate the support from these commenters. As we
discuss later in this section of this final rule, based on the results
of our final impact analysis, we continue to believe that the FY 2019
claims are the best available data for estimating payments in this FY
2022 final rulemaking, due to the likely impact of the COVID-19 PHE on
IPF utilization in FY 2020. We will continue to analyze data in order
to understand its short-term and long-term effects on IPF utilization.
Final Decision: In light of the comments received and after
analyzing more recently updated FY 2020 claims, we are finalizing our
proposal to use the FY 2019 claims to calculate the outlier fixed
dollar loss threshold and wage index budget neutrality factor.
To illustrate the impacts of the FY 2022 changes in this final
rule, our analysis presents a side-by-side comparison of payments
estimated using FY 2019 claims versus payments estimated using FY 2020
claims. We begin with FY 2019 IPF PPS claims (based on the 2019 MedPAR
claims, June 2020 update) and FY 2020 IPF PPS claims (based on the 2020
MedPAR claims, March 2021 update). We estimate FY 2021 IPF PPS payments
using these 2019 and 2020 claims, the finalized FY 2021 IPF PPS Federal
per diem base rates, and the finalized FY 2021 IPF PPS patient and
facility level adjustment factors (as published in the FY 2021 IPF PPS
final rule (85 FR 47042 through 47070)). We then estimate the FY 2021
outlier payments based on these simulated FY 2021 IPF PPS payments
using the same methodology as finalized in the FY 2021 IPF PPS final
rule (85 FR 47061 through 47062) where total outlier payments are
maintained at 2 percent of total estimated FY 2021 IPF PPS payments.
Each of the following changes is added incrementally to this
baseline model in order for us to isolate the effects of each change:
The final update to the outlier fixed dollar loss
threshold amount.
The final FY 2022 IPF wage index, the final FY 2022 labor-
related share, and the final updated COLA factors.
The final market basket update for FY 2022 of 2.7 percent
less the productivity adjustment of 0.7 percentage point in accordance
with section 1886(s)(2)(A)(i) of the Act for a payment rate update of
2.0 percent.
Our final column comparison in Table 18 illustrates the percent
change in payments from FY 2021 (that is, October 1, 2020, to September
30, 2021) to FY 2022 (that is, October 1, 2021, to September 30, 2022)
including all the payment policy changes in this final rule. For each
column, Table 18 presents a side-by-side comparison of the results
using FY 2019 and FY 2020 IPF PPS claims.
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3. Impact Results
Table 18 displays the results of our analysis. The table groups
IPFs into the categories listed here based on characteristics provided
in the Provider of Services file, the IPF PSF, and cost report data
from the Healthcare Cost Report Information System:
Facility Type.
Location.
Teaching Status Adjustment.
Census Region.
Size.
The top row of the table shows the overall impact on the 1,519 IPFs
included in the analysis for FY 2019 claims or the 1,534 IPFs included
in the analysis for FY 2020 claims. In column 2, we present the number
of facilities of each type that had information available in the PSF
and also had claims in the MedPAR dataset for FY 2019 or FY 2020. The
number of providers in each category therefore differs slightly between
the two years.
In column 3, we present the effects of the update to the outlier
fixed dollar loss threshold amount. Based on the FY 2019 claims, we
would estimate that IPF outlier payments as a percentage of total IPF
payments are 1.9 percent in FY 2021. Alternatively, based on the FY
2020 claims, we would estimate that IPF outlier payments as a
percentage of total IPF payments are 3.1 percent in FY 2021.
Thus, we are finalizing our proposal to adjust the outlier
threshold amount in this final rule to set total estimated outlier
payments equal to 2.0 percent of total payments in FY 2022. Based on
the FY 2019 claims, the estimated change in total IPF payments for FY
2022 would include an approximate 0.1 percent increase in payments
because we would expect the outlier portion of total payments to
increase from approximately 1.9 percent to 2.0 percent. Alternatively,
based on the FY 2020 claims, the estimated change in total IPF payments
for FY 2022 would include an approximate 1.1 percent decrease in
payments because we would expect the outlier portion of total payments
to decrease from approximately 3.1 percent to 2.0 percent.
The overall impact of the estimated increase or decrease to
payments due to updating the outlier fixed dollar loss threshold (as
shown in column 3 of Table 18), across all hospital groups, is 0.1
percent based on the FY 2019 claims, or -1.1 percent based on the FY
2020 claims. Based on the FY 2019 claims, the largest increase in
payments due to this change is estimated to be 0.4 percent for teaching
IPFs with more than 30 percent interns and residents to beds. Among
teaching IPFs, this same provider facility type would experience the
largest estimated decrease in payments if we were to instead increase
the outlier fixed dollar loss threshold based on the FY 2020 claims
distribution.
In column 4, we present the effects of the budget-neutral update to
the IPF wage index, the Labor-Related Share (LRS), and the final
updated COLA factors discussed in section III.D.3. This represents the
effect of using the concurrent hospital wage data as discussed in
section III.D.1.a of this final rule. That is, the impact represented
in this column reflects the final updated COLA factors and the update
from the FY 2021 IPF wage index to the final FY 2022 IPF wage index,
which includes basing the FY 2022 IPF wage index on the FY 2022 pre-
floor, pre-reclassified IPPS hospital wage index data and updating the
LRS from 77.3 percent in FY 2021 to 77.2 percent in FY 2022. We note
that there is no projected change in aggregate payments to IPFs, as
indicated in the first row of column 4; however, there will be
distributional effects among different categories of IPFs. We also note
that when comparing the results using
[[Page 42676]]
FY 2019 and FY 2020 claims, the distributional effects are very
similar. For example, we estimate the largest increase in payments to
be 0.6 percent for IPFs in the South Atlantic region, and the largest
decrease in payments to be -0.5 percent for IPFs in the East South
Central region, based on either the FY 2019 or FY 2020 claims.
Finally, column 5 compares the total final changes reflected in
this final rule for FY 2022 to the estimates for FY 2021 (without these
changes). The average estimated increase for all IPFs is approximately
2.1 percent based on the FY 2019 claims, or 0.9 percent based on the FY
2020 claims. These estimated net increases include the effects of the
2016-based market basket update of 2.7 percent reduced by the
productivity adjustment of 0.7 percentage point, as required by section
1886(s)(2)(A)(i) of the Act. They also include the overall estimated
0.1 percent increase in estimated IPF outlier payments as a percent of
total payments from updating the outlier fixed dollar loss threshold
amount. In addition, column 5 includes the distributional effects of
the final updates to the IPF wage index, the labor-related share, and
the final updated COLA factors, whose impacts are displayed in column
4. Based on the FY 2020 claims distribution, the increase to estimated
payments due to the market basket update factor are offset in large
part for some provider types by the increase to the outlier fixed
dollar loss threshold.
In summary, comparing the impact results for the FY 2019 and FY
2020 claims, the largest difference in the results continues to be due
to the update to the outlier fixed dollar loss threshold, which is the
same result we observed in the FY 2022 IPF PPS proposed rule (86 FR
19524). Estimated outlier payments increased and estimated total PPS
payments decreased, when comparing FY 2020 to FY 2019. As a result, we
continue to believe that FY 2019 claims, rather than FY 2020 claims,
are the best available data for setting the FY 2022 final outlier fixed
dollar loss threshold. Furthermore, the distributional effects of the
updates presented in column 4 of Table 18 (the budget-neutral update to
the IPF wage index, the LRS, and the final updated COLA factors) are
very similar when using the FY 2019 or FY 2020 claims data. Therefore,
we believe the FY 2019 claims are the best available data for
estimating payments in this FY 2022 final rulemaking, and we are
finalizing our proposal to use the FY 2019 claims to calculate the
outlier fixed dollar loss threshold and wage index budget neutrality
factor.
IPF payments are therefore estimated to increase by 2.1 percent in
urban areas and 2.2 percent in rural areas based on this finalized
policy. Overall, IPFs are estimated to experience a net increase in
payments as a result of the updates in this final rule. The largest
payment increase is estimated at 2.7 percent for IPFs in the South
Atlantic region.
4. Effect on Beneficiaries
Under the FY 2022 IPF PPS, IPFs will continue to receive payment
based on the average resources consumed by patients for each day. Our
longstanding payment methodology reflects the differences in patient
resource use and costs among IPFs, as required under section 124 of the
BBRA. We expect that updating IPF PPS rates as finalized in this rule
will improve or maintain beneficiary access to high quality care by
ensuring that payment rates reflect the best available data on the
resources involved in inpatient psychiatric care and the costs of these
resources. We continue to expect that paying prospectively for IPF
services under the FY 2022 IPF PPS will enhance the efficiency of the
Medicare program.
As discussed in sections IV.E.2, IV.E.3, and V.A.2.d of this final
rule, we expect that additional program measures will improve follow-up
for patients with both mental health and substance use disorders and
ensure health-care personnel COVID-19 vaccinations. We also estimate an
annualized estimate of $512,065 reduction in information collection
burden as a result our measure removals. Therefore, we expect that the
final updates to the IPFQR program will improve quality for
beneficiaries.
5. Effects of Updates to the IPFQR Program
As discussed in section V. of this final rule and in accordance
with section 1886(s)(4)(A)(i) of the Act, we will apply a 2 percentage
point reduction to the FY 2022 market basket update for IPFs that have
failed to comply with the IPFQR Program requirements for FY 2022,
including reporting on the required measures. In section V. of this
final rule, we discuss how the 2 percentage point reduction will be
applied. For FY 2021, of the 1,634 IPFs eligible for the IPFQR Program,
43 IPFs (2.6 percent) did not receive the full market basket update
because of the IPFQR Program; 31 of these IPFs chose not to participate
and 12 did not meet the requirements of the program. We anticipate that
even fewer IPFs would receive the reduction for FY 2022 as IPFs become
more familiar with the requirements. Thus, we estimate that the IPFQR
Program will have a negligible impact on overall IPF payments for FY
2022.
Based on the IPFQR Program policies finalized in this final rule,
we estimate a total decrease in burden of 287,924 hours across all
IPFs, resulting in a total decrease in information collection burden of
$512,065 across all IPFs. As discussed in section VI. of this final
rule, we will attribute the cost savings associated with the proposals
to the year in which these savings begin; for the purposes of all the
policies in this final rule, that year is FY 2023. Further information
on these estimates can be found in section VI. of this final rule.
We intend to closely monitor the effects of the IPFQR Program on
IPFs and help facilitate successful reporting outcomes through ongoing
stakeholder education, national trainings, and a technical help desk.
6. Regulatory Review Costs
If regulations impose administrative costs on private entities,
such as the time needed to read and interpret this final rule, we
should estimate the cost associated with regulatory review. Due to the
uncertainty involved with accurately quantifying the number of entities
that will be directly impacted and will review this final rule, we
assume that the total number of unique commenters on the most recent
IPF proposed rule will be the number of reviewers of this final rule.
For this FY 2022 IPF PPS final rule, the most recent IPF proposed rule
was the FY 2022 IPF PPS proposed rule, and we received 898 unique
comments on this proposed rule. We acknowledge that this assumption may
understate or overstate the costs of reviewing this final rule. It is
possible that not all commenters reviewed the FY 2021 IPF proposed rule
in detail, and it is also possible that some reviewers chose not to
comment on that proposed rule. For these reasons, we thought that the
number of commenters would be a fair estimate of the number of
reviewers who are directly impacted by this final rule. We solicited
comments on this assumption.
We also recognize that different types of entities are in many
cases affected by mutually exclusive sections of this final rule;
therefore, for the purposes of our estimate, we assume that each
reviewer reads approximately 50 percent of this final rule.
Using the May, 2020 mean (average) wage information from the BLS
for medical and health service managers (Code 11-9111), we estimate
that the cost of reviewing this final rule is $114.24 per hour,
including overhead and fringe benefits (https://www.bls.gov/oes/current/oes119111.htm). Assuming
[[Page 42677]]
an average reading speed of 250 words per minute, we estimate that it
would take approximately 128 minutes (2.13 hours) for the staff to
review half of this final rule, which is approximately 32,000 words.
For each IPF that reviews the final rule, the estimated cost is (2.13 x
$114.24) or $243.33. Therefore, we estimate that the total cost of
reviewing this final rule is $ 218,510.34 ($243.33 x 898 reviewers).
D. Alternatives Considered
The statute does not specify an update strategy for the IPF PPS and
is broadly written to give the Secretary discretion in establishing an
update methodology. We continue to believe it is appropriate to
routinely update the IPF PPS so that it reflects the best available
data about differences in patient resource use and costs among IPFs as
required by the statute. Therefore, we are finalizing our proposal to
update the IPF PPS using the methodology published in the November 2004
IPF PPS final rule; applying the 2016-based IPF PPS market basket
update for FY 2022 of 2.7 percent, reduced by the statutorily required
productivity adjustment of 0.7 percentage point along with the wage
index budget neutrality adjustment to update the payment rates; and
finalizing a FY 2022 IPF wage index which uses the FY 2022 pre-floor,
pre-reclassified IPPS hospital wage index as its basis.
As discussed in section VI.C.3 of this final rule, we also
considered using FY 2020 claims data to determine the final FY 2022
outlier fixed dollar loss threshold, wage index budget neutrality
factor, per diem base rate, and ECT rate. For the reasons discussed in
that section, we are finalizing our proposal to use FY 2019 claims
data.
E. Accounting Statement
As required by OMB Circular A-4 (available at www.whitehouse.gov/sites/whitehouse.gov/files/omb/circulars/A4/a-4.pdf), in Table 19, we
have prepared an accounting statement showing the classification of the
expenditures associated with the updates to the IPF wage index and
payment rates in this final rule. Table 19 provides our best estimate
of the increase in Medicare payments under the IPF PPS as a result of
the changes presented in this final rule and based on the data for
1,519 IPFs with data available in the PSF and with claims in our FY
2019 MedPAR claims dataset. Table 19 also includes our best estimate of
the cost savings for the 1,634 IPFs eligible for the IPFQR Program.
Lastly, Table 19 also includes our best estimate of the costs of
reviewing and understanding this final rule.
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F. Regulatory Flexibility Act
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, nonprofit organizations, and small
governmental jurisdictions. Most IPFs and most other providers and
suppliers are small entities, either by nonprofit status or having
revenues of $8 million to $41.5 million or less in any 1 year.
Individuals and states are not included in the definition of a small
entity.
Because we lack data on individual hospital receipts, we cannot
determine the number of small proprietary IPFs or the proportion of
IPFs' revenue derived from Medicare payments. Therefore, we assume that
all IPFs are considered small entities.
The Department of Health and Human Services generally uses a
revenue impact of 3 to 5 percent as a significance threshold under the
RFA. As shown in Table 18, we estimate that the overall revenue impact
of this final rule on all IPFs is to increase estimated Medicare
payments by approximately 2.1 percent. As a result, since the estimated
impact of this final rule is a net increase in revenue across almost
all categories of IPFs, the Secretary has determined that this final
rule will have a positive revenue impact on a substantial number of
small entities.
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 604 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 a metropolitan
statistical area and has fewer than 100 beds. As discussed in section
V.C.1 of this final rule, the rates and policies set forth in this
final rule will not have an adverse impact on the rural hospitals based
on the data of the 239 rural excluded psychiatric units and 60 rural
psychiatric hospitals in our database of 1,519 IPFs for which data were
available. Therefore, the Secretary has certified that this final rule
will not have a significant impact on the operations of a substantial
number of small rural hospitals.
G. Unfunded Mandate Reform Act (UMRA)
Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) also
requires that agencies assess anticipated costs and benefits before
issuing any rule whose mandates require spending in any 1 year of $100
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million in 1995 dollars, updated annually for inflation. In 2021, that
threshold is approximately $158 million. This final rule does not
mandate any requirements for state, local, or tribal governments, or
for the private sector. This final rule would not impose a mandate that
will result in the expenditure by state, local, and Tribal Governments,
in the aggregate, or by the private sector, of more than $158 million
in any one year.
H. Federalism
Executive Order 13132 establishes certain requirements that an
agency must meet when it promulgates a proposed rule that imposes
substantial direct requirement costs on state and local governments,
preempts state law, or otherwise has Federalism implications. This
final rule does not impose substantial direct costs on state or local
governments or preempt state law.
I, Chiquita Brooks-LaSure, Administrator of the Centers for
Medicare & Medicaid Services, approved this document on July 23, 2021.
List of Subjects in 42 CFR Part 412
Administrative practice and procedure, Health facilities, Medicare,
Puerto Rico, Reporting and recordkeeping requirements.
For the reasons set forth in the preamble, the Centers for Medicare
& Medicaid Services is amending 42 CFR chapter IV as set forth below:
PART 412--PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL
SERVICES
0
1. The authority citation for part 412 continues to read as follows:
Authority: 42 U.S.C. 1302 and 1395hh.
0
2. Section 412.402 is amended by adding definitions for ``Closure of an
IPF'', ``Closure of an IPF's residency training program'', and
``Displaced resident'' in alphabetical order to read as follows:
Sec. 412.402 Definitions.
* * * * *
Closure of an IPF means closure of a hospital as defined in Sec.
413.79(h)(1)(i) by an IPF meeting the requirements of Sec. 412.404(b)
for the purposes of accounting for indirect teaching costs.
Closure of an IPF's residency training program means closure of a
hospital residency training program as defined in Sec.
413.79(h)(1)(ii) by an IPF meeting the requirements of Sec. 412.404(b)
for the purposes of accounting for indirect teaching costs.
* * * * *
Displaced resident means a displaced resident as defined in Sec.
413.79(h)(1)(iii) for the purposes of accounting for indirect teaching
costs.
* * * * *
0
3. Section 412.424 is amended by revising paragraph (d)(1)(iii)(F) to
read as follows:
Sec. 412.424 Methodology for calculating the Federal per diem payment
system.
* * * * *
(d) * * *
(1) * * *
(iii) * * *
(F) Closure of an IPF or IPF residency training program--(1)
Closure of an IPF. For cost reporting periods beginning on or after
July 1, 2011, an IPF may receive a temporary adjustment to its FTE cap
to reflect displaced residents added because of another IPF's closure
if the IPF meets the following criteria:
(i) The IPF is training additional displaced residents from an IPF
that closed on or after July 1, 2011.
(ii) No later than 60 days after the IPF begins to train the
displaced residents, the IPF submits a request to its Medicare
contractor for a temporary adjustment to its cap, documents that the
IPF is eligible for this temporary adjustment by identifying the
displaced residents who have come from the closed IPF and have caused
the IPF to exceed its cap, and specifies the length of time the
adjustment is needed.
(2) Closure of an IPF's residency training program. If an IPF that
closes its residency training program on or after July 1, 2011, agrees
to temporarily reduce its FTE cap according to the criteria specified
in paragraph (d)(1)(iii)(F)(2)(ii) of this section, another IPF(s) may
receive a temporary adjustment to its FTE cap to reflect displaced
residents added because of the closure of the residency training
program if the criteria specified in paragraph (d)(1)(iii)(F)(2)(i) of
this section are met.
(i) Receiving IPF(s). For cost reporting periods beginning on or
after July 1, 2011, an IPF may receive a temporary adjustment to its
FTE cap to reflect displaced residents added because of the closure of
another IPF's residency training program if the IPF is training
additional displaced residents from the residency training program of
an IPF that closed a program; and if no later than 60 days after the
IPF begins to train the displaced residents, the IPF submits to its
Medicare Contractor a request for a temporary adjustment to its FTE
cap, documents that it is eligible for this temporary adjustment by
identifying the displaced residents who have come from another IPF's
closed program and have caused the IPF to exceed its cap, specifies the
length of time the adjustment is needed, and submits to its Medicare
contractor a copy of the FTE reduction statement by the hospital that
closed its program, as specified in paragraph (d)(1)(iii)(F)(2)(ii) of
this section.
(ii) IPF that closed its program. An IPF that agrees to train
displaced residents who have been displaced by the closure of another
IPF's program may receive a temporary FTE cap adjustment only if the
hospital with the closed program temporarily reduces its FTE cap based
on the FTE of displaced residents in each program year training in the
program at the time of the program's closure. This yearly reduction in
the FTE cap will be determined based on the number of those displaced
residents who would have been training in the program during that year
had the program not closed. No later than 60 days after the displaced
residents who were in the closed program begin training at another
hospital, the hospital with the closed program must submit to its
Medicare contractor a statement signed and dated by its representative
that specifies that it agrees to the temporary reduction in its FTE cap
to allow the IPF training the displaced residents to obtain a temporary
adjustment to its cap; identifies the displaced residents who were in
training at the time of the program's closure; identifies the IPFs to
which the displaced residents are transferring once the program closes;
and specifies the reduction for the applicable program years.
* * * * *
0
4. Section 412.434 is amended by revising paragraph (b)(3) to read as
follows:
Sec. 412.434 Reconsideration and appeals procedures of Inpatient
Psychiatric Facilities Quality Reporting (IPFQR) Program decisions
* * * * *
(b) * * *
(3) Contact information for the inpatient psychiatric facility's
chief executive officer and QualityNet security official, including
each individual's name, email address, telephone number, and physical
mailing address;
* * * * *
[[Page 42679]]
Dated: July 27, 2021.
Xavier Becerra,
Secretary, Department of Health and Human Services.
[FR Doc. 2021-16336 Filed 7-29-21; 4:15 pm]
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