[Federal Register Volume 81, Number 151 (Friday, August 5, 2016)]
[Rules and Regulations]
[Pages 52056-52141]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2016-18196]



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Vol. 81

Friday,

No. 151

August 5, 2016

Part III





 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; Inpatient Rehabilitation Facility Prospective Payment 
System for Federal Fiscal Year 2017; Final Rule

  Federal Register / Vol. 81 , No. 151 / Friday, August 5, 2016 / Rules 
and Regulations  

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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Medicare & Medicaid Services

42 CFR Part 412

[CMS-1647-F]
RIN 0938-AS78


Medicare Program; Inpatient Rehabilitation Facility Prospective 
Payment System for Federal Fiscal Year 2017

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

ACTION: Final rule.

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SUMMARY: This final rule will update the prospective payment rates for 
inpatient rehabilitation facilities (IRFs) for federal fiscal year (FY) 
2017 as required by the statute. As required by section 1886(j)(5) of 
the Act, this rule includes the classification and weighting factors 
for the IRF prospective payment system's (IRF PPS's) case-mix groups 
and a description of the methodologies and data used in computing the 
prospective payment rates for FY 2017. This final rule also revises and 
updates quality measures and reporting requirements under the IRF 
quality reporting program (QRP).

DATES: 
    Effective Dates: These regulations are effective on October 1, 
2016.
    Applicability Dates: The updated IRF prospective payment rates are 
applicable for IRF discharges occurring on or after October 1, 2016, 
and on or before September 30, 2017 (FY 2017). The updated quality 
measures and reporting requirements under the IRF QRP are effective for 
IRF discharges occurring on or after October 1, 2016.

FOR FURTHER INFORMATION CONTACT: Gwendolyn Johnson, (410) 786-6954, for 
general information. Catie Kraemer, (410) 786-0179, for information 
about the wage index. Christine Grose, (410) 786-1362, for information 
about the quality reporting program. Kadie Derby, (410) 786-0468, or 
Susanne Seagrave, (410) 786-0044, for information about the payment 
policies and payment rates.

SUPPLEMENTARY INFORMATION: The IRF PPS Addenda along with other 
supporting documents and tables referenced in this final rule are 
available through the Internet on the CMS Web site at http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/.

Executive Summary

A. Purpose

    This final rule updates the prospective payment rates for IRFs for 
FY 2017 (that is, for discharges occurring on or after October 1, 2016, 
and on or before September 30, 2017) as required under section 
1886(j)(3)(C) of the Social Security Act (the Act). As required by 
section 1886(j)(5) of the Act, this rule includes the classification 
and weighting factors for the IRF PPS's case-mix groups and a 
description of the methodologies and data used in computing the 
prospective payment rates for FY 2017. This final rule also finalizes 
revisions and updates to the quality measures and reporting 
requirements under the IRF QRP.

B. Summary of Major Provisions

    In this final rule, we use the methods described in the FY 2016 IRF 
PPS final rule (80 FR 47036) to update the federal prospective payment 
rates for FY 2017 using updated FY 2015 IRF claims and the most recent 
available IRF cost report data, which is FY 2014 IRF cost report data. 
We are also finalizing revisions and updates to the quality measures 
and reporting requirements under the IRF QRP.

C. Summary of Impacts

------------------------------------------------------------------------
    Provision description                      Transfers
------------------------------------------------------------------------
FY 2017 IRF PPS payment rate   The overall economic impact of this final
 update.                        rule is an estimated $145 million in
                                increased payments from the Federal
                                government to IRFs during FY 2017.
------------------------------------------------------------------------
    Provision description                        Costs
------------------------------------------------------------------------
New quality reporting program  The total costs in FY 2017 for IRFs as a
 requirements.                  result of the new quality reporting
                                requirements are estimated to be
                                $5,231,398.17.
------------------------------------------------------------------------

    To assist readers in referencing sections contained in this 
document, we are providing the following Table of Contents.

Table of Contents

I. Background
    A. Historical Overview of the IRF PPS
    B. Provisions of the Affordable Care Act Affecting the IRF PPS 
in FY 2012 and Beyond
    C. Operational Overview of the Current IRF PPS
    D. Advancing Health Information Exchange
II. Summary of Provisions of the Proposed Rule
III. Analysis and Responses to Public Comments
IV. Update to the Case-Mix Group (CMG) Relative Weights and Average 
Length of Stay Values for FY 2017
V. Facility-Level Adjustment Factors
VI. FY 2017 IRF PPS Payment Update
    A. Background
    B. FY 2017 Market Basket Update and Productivity Adjustment
    C. Labor-Related Share for FY 2017
    D. Wage Adjustment
    E. Description of the IRF Standard Payment Conversion Factor and 
Payment Rates for FY 2017
    F. Example of the Methodology for Adjusting the Federal 
Prospective Payment Rates
VII. Update to Payments for High-Cost Outliers Under the IRF PPS
    A. Update to the Outlier Threshold Amount for FY 2017
    B. Update to the IRF Cost-to-Charge Ratio Ceiling and Urban/
Rural Averages
VIII. Revisions and Updates to the IRF Quality Reporting Program 
(QRP)
    A. Background and Statutory Authority
    B. General Considerations Used for Selection of Quality, 
Resource Use, and Other Measures for the IRF QRP
    C. Policy for Retention of IRF QRP Measures Adopted for Previous 
Payment Determinations
    D. Policy for Adopting Changes to IRF QRP Measures
    E. Quality Measures Previously Finalized for and Currently Used 
in the IRF QRP
    F. IRF QRP Quality, Resource Use and Other Measures Finalized 
for the FY 2018 Payment Determination and Subsequent Years
    G. IRF QRP Quality Measure Finalized for the FY 2020 Payment 
Determination and Subsequent Years
    H. IRF QRP Quality Measures and Measure Concepts Under 
Consideration for Future Years
    I. Form, Manner, and Timing of Quality Data Submission for the 
FY 2018 Payment Determination and Subsequent Years
    J. IRF QRP Data Completion Thresholds for the FY 2016 Payment 
Determination and Subsequent Years
    K. IRF QRP Data Validation Process for the FY 2016 Payment 
Determination and Subsequent Years

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    L. Previously Adopted and Codified IRF QRP Submission Exception 
and Extension Policies
    M. Previously Adopted and Finalized IRF QRP Reconsideration and 
Appeals Procedures
    N. Public Display of Measure Data for the IRF QRP & Procedures 
for the Opportunity to Review and Correct Data and Information
    O. Mechanism for Providing Feedback Reports to IRFs
    P. Method for Applying the Reduction to the FY 2017 IRF Increase 
Factor for IRFs That Fail To Meet the Quality Reporting Requirements
IX. Miscellaneous Comments
X. Provisions of the Final Regulations
XI. Collection of Information Requirements
    A. Statutory Requirement for Solicitation of Comments
    B. Collection of Information Requirements for Updates Related to 
the IRF QRP
XII. Regulatory Impact Analysis
    A. Statement of Need
    B. Overall Impacts
    C. Detailed Economic Analysis
    D. Alternatives Considered
    E. Accounting Statement
    F. Conclusion

Acronyms, Abbreviations, and Short Forms

    Because of the many terms to which we refer by acronym, 
abbreviation, or short form in this final rule, we are listing the 
acronyms, abbreviation, and short forms used and their corresponding 
terms in alphabetical order.

The Act The Social Security Act
ADC Average Daily Census
ADE Adverse Drug Events
The Affordable Care Act Patient Protection and Affordable Care Act 
(Pub. L. 111-148, enacted on March 23, 2010)
AHRQ Agency for Healthcare Research and Quality
APU Annual Payment Update
ASAP Assessment Submission and Processing
ASCA The Administrative Simplification Compliance Act of 2002 (Pub. 
L. 107-105, enacted on December 27, 2002)
ASPE Office of the Assistant Secretary for Planning and Evaluation
BLS U.S. Bureau of Labor Statistics
BMI Body Mass Index
CAH Critical Access Hospitals
CASPER Certification and Survey Provider Enhanced Reports
CAUTI Catheter-Associated Urinary Tract Infection
CBSA Core-Based Statistical Area
CCR Cost-to-Charge Ratio
CDC The Centers for Disease Control and Prevention
CDI Clostridium difficile Infection
CFR Code of Federal Regulations
CMG Case-Mix Group
CMS Centers for Medicare & Medicaid Services
COA Care for Older Adults
CY Calendar year
DSH Disproportionate Share Hospital
DSH PP Disproportionate Share Patient Percentage
DRG Diagnosis-Related Group
eCQMs Electronically Specified Clinical Quality Measures
ESRD End-Stage Renal Disease
FFS Fee-for-Service
FR Federal Register
FY Federal Fiscal Year
GEMS General Equivalence Mapping
GPCI Geographic Practice Cost Index
HAI Healthcare Associated Infection
HCC Hierarchical Condition Category
HHA Home Health Agencies
HCP Home Care Personnel
HHS U.S. Department of Health & Human Services
HIPAA Health Insurance Portability and Accountability Act of 1996 
(Pub. L. 104-191, enacted on August 21, 1996)
Hospital VBP Hospital Value-Based Purchasing Program (also HVBP)
ICD-9-CM International Classification of Diseases, 9th Revision, 
Clinical Modification
ICD-10-CM International Classification of Diseases, 10th Revision, 
Clinical Modification
IGC Impairment Group Code
IGI IHS Global Insight
IMPACT Act Improving Medicare Post-Acute Care Transformation Act of 
2014 (Pub. L. 113-185, enacted on October 6, 2014)
IME Indirect Medical Education
IPF Inpatient Psychiatric Facility
IPPS Inpatient prospective payment system
IQR Inpatient Quality Reporting Program
IRF Inpatient Rehabilitation Facility
IRF-PAI Inpatient Rehabilitation Facility-Patient Assessment 
Instrument
IRF PPS Inpatient Rehabilitation Facility Prospective Payment System
IRF QRP Inpatient Rehabilitation Facility Quality Reporting Program
IRVEN Inpatient Rehabilitation Validation and Entry
LIP Low-Income Percentage
IVS Influenza Vaccination Season
LTCH Long-Term Care Hospital
MA (Medicare Part C) Medicare Advantage
MAC Medicare Administrative Contractor
MAP Measures Application Partnership
MedPAC Medicare Payment Advisory Commission
MFP Multifactor Productivity
MMSEA Medicare, Medicaid, and SCHIP Extension Act of 2007 (Pub. L. 
110-173, enacted on December 29, 2007)
MRSA Methicillin-Resistant Staphylococcus aureus
MSPB Medicare Spending per Beneficiary
MUC Measures under Consideration
NHSN National Healthcare Safety Network
NQF National Quality Forum
OMB Office of Management and Budget
ONC Office of the National Coordinator for Health Information 
Technology
OPPS/ASC Outpatient Prospective Payment System/Ambulatory Surgical 
Center
PAC Post-Acute Care
PAC/LTC Post-Acute Care/Long-Term Care
PAI Patient Assessment Instrument
PPR Potentially Preventable Readmissions
PPS Prospective Payment System
PRA Paperwork Reduction Act of 1995 (Pub. L. 104-13, enacted on May 
22, 1995)
QIES Quality Improvement Evaluation System
QM Quality Measure
QRP Quality Reporting Program
RIA Regulatory Impact Analysis
RIC Rehabilitation Impairment Category
RFA Regulatory Flexibility Act (Pub. L. 96-354, enacted on September 
19, 1980)
RN Registered Nurse
RPL Rehabilitation, Psychiatric, and Long-Term Care market basket
RSRR Risk-standardized readmission rate
SIR Standardized Infection Ratio
SNF Skilled Nursing Facilities
SRR Standardized Risk Ratio
SSI Supplemental Security Income
TEP Technical Expert Panel

I. Background

A. Historical Overview of the IRF PPS

    Section 1886(j) of the Act provides for the implementation of a 
per-discharge prospective payment system (PPS) for inpatient 
rehabilitation hospitals and inpatient rehabilitation units of a 
hospital (collectively, hereinafter referred to as IRFs). Payments 
under the IRF PPS encompass inpatient operating and capital costs of 
furnishing covered rehabilitation services (that is, routine, 
ancillary, and capital costs), but not direct graduate medical 
education costs, costs of approved nursing and allied health education 
activities, bad debts, and other services or items outside the scope of 
the IRF PPS. Although a complete discussion of the IRF PPS provisions 
appears in the original FY 2002 IRF PPS final rule (66 FR 41316) and 
the FY 2006 IRF PPS final rule (70 FR 47880), we are providing below a 
general description of the IRF PPS for FYs 2002 through 2016.
    Under the IRF PPS from FY 2002 through FY 2005 the federal 
prospective payment rates were computed across 100 distinct case-mix 
groups (CMGs), as described in the FY 2002 IRF PPS final rule (66 FR 
41316). We constructed 95 CMGs using rehabilitation impairment 
categories (RICs), functional status (both motor and cognitive), and 
age (in some cases, cognitive status and age may not be a factor in 
defining a CMG). In addition, we constructed five special CMGs to 
account for very short stays and for patients who expire in the IRF.
    For each of the CMGs, we developed relative weighting factors to 
account for a patient's clinical characteristics and expected resource 
needs. Thus, the weighting factors accounted for the relative 
difference in resource use across all CMGs. Within each CMG, we created 
tiers based on the estimated effects that certain comorbidities would 
have on resource use.
    We established the federal PPS rates using a standardized payment 
conversion factor (formerly referred to

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as the budget-neutral conversion factor). For a detailed discussion of 
the budget-neutral conversion factor, please refer to our FY 2004 IRF 
PPS final rule (68 FR 45684 through 45685). In the FY 2006 IRF PPS 
final rule (70 FR 47880), we discussed in detail the methodology for 
determining the standard payment conversion factor.
    We applied the relative weighting factors to the standard payment 
conversion factor to compute the unadjusted federal prospective payment 
rates under the IRF PPS from FYs 2002 through 2005. Within the 
structure of the payment system, we then made adjustments to account 
for interrupted stays, transfers, short stays, and deaths. Finally, we 
applied the applicable adjustments to account for geographic variations 
in wages (wage index), the percentage of low-income patients, location 
in a rural area (if applicable), and outlier payments (if applicable) 
to the IRFs' unadjusted federal prospective payment rates.
    For cost reporting periods that began on or after January 1, 2002, 
and before October 1, 2002, we determined the final prospective payment 
amounts using the transition methodology prescribed in section 
1886(j)(1) of the Act. Under this provision, IRFs transitioning into 
the PPS were paid a blend of the federal IRF PPS rate and the payment 
that the IRFs would have received had the IRF PPS not been implemented. 
This provision also allowed IRFs to elect to bypass this blended 
payment and immediately be paid 100 percent of the federal IRF PPS 
rate. The transition methodology expired as of cost reporting periods 
beginning on or after October 1, 2002 (FY 2003), and payments for all 
IRFs now consist of 100 percent of the federal IRF PPS rate.
    We established a CMS Web site as a primary information resource for 
the IRF PPS which is available at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/index.html. The Web site 
may be accessed to download or view publications, software, data 
specifications, educational materials, and other information pertinent 
to the IRF PPS.
    Section 1886(j) of the Act confers broad statutory authority upon 
the Secretary to propose refinements to the IRF PPS. In the FY 2006 IRF 
PPS final rule (70 FR 47880) and in correcting amendments to the FY 
2006 IRF PPS final rule (70 FR 57166) that we published on September 
30, 2005, we finalized a number of refinements to the IRF PPS case-mix 
classification system (the CMGs and the corresponding relative weights) 
and the case-level and facility-level adjustments. These refinements 
included the adoption of the Office of Management and Budget's (OMB) 
Core-Based Statistical Area (CBSA) market definitions, modifications to 
the CMGs, tier comorbidities, and CMG relative weights, implementation 
of a new teaching status adjustment for IRFs, revision and rebasing of 
the market basket index used to update IRF payments, and updates to the 
rural, low-income percentage (LIP), and high-cost outlier adjustments. 
Beginning with the FY 2006 IRF PPS final rule (70 FR 47908 through 
47917), the market basket index used to update IRF payments was a 
market basket reflecting the operating and capital cost structures for 
freestanding IRFs, freestanding inpatient psychiatric facilities 
(IPFs), and long-term care hospitals (LTCHs) (hereinafter referred to 
as the rehabilitation, psychiatric, and long-term care (RPL) market 
basket). Any reference to the FY 2006 IRF PPS final rule in this final 
rule also includes the provisions effective in the correcting 
amendments. For a detailed discussion of the final key policy changes 
for FY 2006, please refer to the FY 2006 IRF PPS final rule (70 FR 
47880 and 70 FR 57166).
    In the FY 2007 IRF PPS final rule (71 FR 48354), we further refined 
the IRF PPS case-mix classification system (the CMG relative weights) 
and the case-level adjustments, to ensure that IRF PPS payments would 
continue to reflect as accurately as possible the costs of care. For a 
detailed discussion of the FY 2007 policy revisions, please refer to 
the FY 2007 IRF PPS final rule (71 FR 48354).
    In the FY 2008 IRF PPS final rule (72 FR 44284), we updated the 
federal prospective payment rates and the outlier threshold, revised 
the IRF wage index policy, and clarified how we determine high-cost 
outlier payments for transfer cases. For more information on the policy 
changes implemented for FY 2008, please refer to the FY 2008 IRF PPS 
final rule (72 FR 44284), in which we published the final FY 2008 IRF 
federal prospective payment rates. After publication of the FY 2008 IRF 
PPS final rule (72 FR 44284), section 115 of the Medicare, Medicaid, 
and SCHIP Extension Act of 2007 (Pub. L. 110-173, enacted on December 
29, 2007) (MMSEA), amended section 1886(j)(3)(C) of the Act to apply a 
zero percent increase factor for FYs 2008 and 2009, effective for IRF 
discharges occurring on or after April 1, 2008. Section 1886(j)(3)(C) 
of the Act required the Secretary to develop an increase factor to 
update the IRF federal prospective payment rates for each FY. Based on 
the legislative change to the increase factor, we revised the FY 2008 
federal prospective payment rates for IRF discharges occurring on or 
after April 1, 2008. Thus, the final FY 2008 IRF federal prospective 
payment rates that were published in the FY 2008 IRF PPS final rule (72 
FR 44284) were effective for discharges occurring on or after October 
1, 2007, and on or before March 31, 2008; and the revised FY 2008 IRF 
federal prospective payment rates were effective for discharges 
occurring on or after April 1, 2008, and on or before September 30, 
2008. The revised FY 2008 federal prospective payment rates are 
available on the CMS Web site at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/Data-Files.html.
    In the FY 2009 IRF PPS final rule (73 FR 46370), we updated the CMG 
relative weights, the average length of stay values, and the outlier 
threshold; clarified IRF wage index policies regarding the treatment of 
``New England deemed'' counties and multi-campus hospitals; and revised 
the regulation text in response to section 115 of the MMSEA to set the 
IRF compliance percentage at 60 percent (the ``60 percent rule'') and 
continue the practice of including comorbidities in the calculation of 
compliance percentages. We also applied a zero percent market basket 
increase factor for FY 2009 in accordance with section 115 of the 
MMSEA. For more information on the policy changes implemented for FY 
2009, please refer to the FY 2009 IRF PPS final rule (73 FR 46370), in 
which we published the final FY 2009 IRF federal prospective payment 
rates.
    In the FY 2010 IRF PPS final rule (74 FR 39762) and in correcting 
amendments to the FY 2010 IRF PPS final rule (74 FR 50712) that we 
published on October 1, 2009, we updated the federal prospective 
payment rates, the CMG relative weights, the average length of stay 
values, the rural, LIP, teaching status adjustment factors, and the 
outlier threshold; implemented new IRF coverage requirements for 
determining whether an IRF claim is reasonable and necessary; and 
revised the regulation text to require IRFs to submit patient 
assessments on Medicare Advantage (MA) (formerly called Medicare Part 
C) patients for use in the 60 percent rule calculations. Any reference 
to the FY 2010 IRF PPS final rule in this final rule also includes the 
provisions effective in the correcting amendments. For more information 
on the policy changes implemented for FY 2010, please refer

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to the FY 2010 IRF PPS final rule (74 FR 39762 and 74 FR 50712), in 
which we published the final FY 2010 IRF federal prospective payment 
rates.
    After publication of the FY 2010 IRF PPS final rule (74 FR 39762), 
section 3401(d) of the Patient Protection and Affordable Care Act (Pub. 
L. 111-148, enacted on March 23, 2010), as amended by section 10319 of 
the same Act and by section 1105 of the Health Care and Education 
Reconciliation Act of 2010 (Pub. L. 111-152, enacted on March 30, 2010) 
(collectively, hereinafter referred to as ``The Affordable Care Act''), 
amended section 1886(j)(3)(C) of the Act and added section 
1886(j)(3)(D) of the Act. Section 1886(j)(3)(C) of the Act requires the 
Secretary to estimate a multifactor productivity adjustment to the 
market basket increase factor, and to apply other adjustments as 
defined by the Act. The productivity adjustment applies to FYs from 
2012 forward. The other adjustments apply to FYs 2010 to 2019.
    Sections 1886(j)(3)(C)(ii)(II) and 1886(j)(3)(D)(i) of the Act 
defined the adjustments that were to be applied to the market basket 
increase factors in FYs 2010 and 2011. Under these provisions, the 
Secretary was required to reduce the market basket increase factor in 
FY 2010 by a 0.25 percentage point adjustment. Notwithstanding this 
provision, in accordance with section 3401(p) of the Affordable Care 
Act, the adjusted FY 2010 rate was only to be applied to discharges 
occurring on or after April 1, 2010. Based on the self-implementing 
legislative changes to section 1886(j)(3) of the Act, we adjusted the 
FY 2010 federal prospective payment rates as required, and applied 
these rates to IRF discharges occurring on or after April 1, 2010, and 
on or before September 30, 2010. Thus, the final FY 2010 IRF federal 
prospective payment rates that were published in the FY 2010 IRF PPS 
final rule (74 FR 39762) were used for discharges occurring on or after 
October 1, 2009, and on or before March 31, 2010, and the adjusted FY 
2010 IRF federal prospective payment rates applied to discharges 
occurring on or after April 1, 2010, and on or before September 30, 
2010. The adjusted FY 2010 federal prospective payment rates are 
available on the CMS Web site at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/Data-Files.html.
    In addition, sections 1886(j)(3)(C) and (D) of the Act also 
affected the FY 2010 IRF outlier threshold amount because they required 
an adjustment to the FY 2010 RPL market basket increase factor, which 
changed the standard payment conversion factor for FY 2010. 
Specifically, the original FY 2010 IRF outlier threshold amount was 
determined based on the original estimated FY 2010 RPL market basket 
increase factor of 2.5 percent and the standard payment conversion 
factor of $13,661. However, as adjusted, the IRF prospective payments 
are based on the adjusted RPL market basket increase factor of 2.25 
percent and the revised standard payment conversion factor of $13,627. 
To maintain estimated outlier payments for FY 2010 equal to the 
established standard of 3 percent of total estimated IRF PPS payments 
for FY 2010, we revised the IRF outlier threshold amount for FY 2010 
for discharges occurring on or after April 1, 2010, and on or before 
September 30, 2010. The revised IRF outlier threshold amount for FY 
2010 was $10,721.
    Sections 1886(j)(3)(C)(ii)(II) and 1886(j)(3)(D)(i) of the Act also 
required the Secretary to reduce the market basket increase factor in 
FY 2011 by a 0.25 percentage point adjustment. The FY 2011 IRF PPS 
notice (75 FR 42836) and the correcting amendments to the FY 2011 IRF 
PPS notice (75 FR 70013) described the required adjustments to the FY 
2011 and FY 2010 IRF PPS federal prospective payment rates and outlier 
threshold amount for IRF discharges occurring on or after April 1, 
2010, and on or before September 30, 2011. It also updated the FY 2011 
federal prospective payment rates, the CMG relative weights, and the 
average length of stay values. Any reference to the FY 2011 IRF PPS 
notice in this final rule also includes the provisions effective in the 
correcting amendments. For more information on the FY 2010 and FY 2011 
adjustments or the updates for FY 2011, please refer to the FY 2011 IRF 
PPS notice (75 FR 42836 and 75 FR 70013).
    In the FY 2012 IRF PPS final rule (76 FR 47836), we updated the IRF 
federal prospective payment rates, rebased and revised the RPL market 
basket, and established a new quality reporting program for IRFs in 
accordance with section 1886(j)(7) of the Act. We also revised 
regulation text for the purpose of updating and providing greater 
clarity. For more information on the policy changes implemented for FY 
2012, please refer to the FY 2012 IRF PPS final rule (76 FR 47836), in 
which we published the final FY 2012 IRF federal prospective payment 
rates.
    The FY 2013 IRF PPS notice (77 FR 44618) described the required 
adjustments to the FY 2013 federal prospective payment rates and 
outlier threshold amount for IRF discharges occurring on or after 
October 1, 2012, and on or before September 30, 2013. It also updated 
the FY 2013 federal prospective payment rates, the CMG relative 
weights, and the average length of stay values. For more information on 
the updates for FY 2013, please refer to the FY 2013 IRF PPS notice (77 
FR 44618).
    In the FY 2014 IRF PPS final rule (78 FR 47860), we updated the 
federal prospective payment rates, the CMG relative weights, and the 
outlier threshold amount. We also updated the facility-level adjustment 
factors using an enhanced estimation methodology, revised the list of 
diagnosis codes that count toward an IRF's 60 percent rule compliance 
calculation to determine ``presumptive compliance,'' revised sections 
of the Inpatient Rehabilitation Facility-Patient Assessment Instrument 
(IRF-PAI), revised requirements for acute care hospitals that have IRF 
units, clarified the IRF regulation text regarding limitation of 
review, updated references to previously changed sections in the 
regulations text, and revised and updated quality measures and 
reporting requirements under the IRF quality reporting program. For 
more information on the policy changes implemented for FY 2014, please 
refer to the FY 2014 IRF PPS final rule (78 FR 47860), in which we 
published the final FY 2014 IRF federal prospective payment rates.
    In the FY 2015 IRF PPS final rule (79 FR 45872), we updated the 
federal prospective payment rates, the CMG relative weights, and the 
outlier threshold amount. We also further revised the list of diagnosis 
codes that count toward an IRF's 60 percent rule compliance calculation 
to determine ``presumptive compliance,'' revised sections of the IRF-
PAI, and revised and updated quality measures and reporting 
requirements under the IRF quality reporting program. For more 
information on the policy changes implemented for FY 2015, please refer 
to the FY 2015 IRF PPS final rule (79 FR 45872) and the FY 2015 IRF PPS 
correction notice (79 FR 59121).
    In the FY 2016 IRF PPS final rule (80 FR 47036), we updated the 
federal prospective payment rates, the CMG relative weights, and the 
outlier threshold amount. We also adopted an IRF-specific market basket 
that reflects the cost structures of only IRF providers, a blended one-
year transition wage index based on the adoption of new OMB area 
delineations, a 3-year phase-out of the rural adjustment for certain 
IRFs due to the new OMB area delineations, and revisions and updates to 
the IRF QRP. For more information on the policy changes implemented for

[[Page 52060]]

FY 2016, please refer to the FY 2016 IRF PPS final rule (80 FR 47036).

B. Provisions of the Affordable Care Act Affecting the IRF PPS in FY 
2012 and Beyond

    The Affordable Care Act included several provisions that affect the 
IRF PPS in FYs 2012 and beyond. In addition to what was previously 
discussed, section 3401(d) of the Affordable Care Act also added 
section 1886(j)(3)(C)(ii)(I) (providing for a ``productivity 
adjustment'' for fiscal year 2012 and each subsequent fiscal year). The 
productivity adjustment for FY 2017 is discussed in section VI.B. of 
this final rule. Section 3401(d) of the Affordable Care Act requires an 
additional 0.75 percentage point adjustment to the IRF increase factor 
for each of FYs 2017, 2018, and 2019. The applicable adjustment for FY 
2017 is discussed in section VI.B. of this final rule. Section 
1886(j)(3)(C)(ii)(II) of the Act notes that the application of these 
adjustments to the market basket update may result in an update that is 
less than 0.0 for a fiscal year and in payment rates for a fiscal year 
being less than such payment rates for the preceding fiscal year. 
Section 3004(b) of the Affordable Care Act also addressed the IRF PPS 
program. It reassigned the previously designated section 1886(j)(7) of 
the Act to section 1886(j)(8) and inserted a new section 1886(j)(7), 
which contains requirements for the Secretary to establish a quality 
reporting program for IRFs. Under that program, data must be submitted 
in a form and manner and at a time specified by the Secretary. 
Beginning in FY 2014, section 1886(j)(7)(A)(i) of the Act requires the 
application of a 2 percentage point reduction of the applicable market 
basket increase factor for IRFs that fail to comply with the quality 
data submission requirements. Application of the 2 percentage point 
reduction may result in an update that is less than 0.0 for a fiscal 
year and in payment rates for a fiscal year being less than such 
payment rates for the preceding fiscal year. Reporting-based reductions 
to the market basket increase factor will not be cumulative; they will 
only apply for the FY involved.
    Under section 1886(j)(7)(D)(i) and (ii) of the Act, the Secretary 
is generally required to select quality measures for the IRF quality 
reporting program from those that have been endorsed by the consensus-
based entity which holds a performance measurement contract under 
section 1890(a) of the Act. This contract is currently held by the 
National Quality Forum (NQF). So long as due consideration is given to 
measures that have been endorsed or adopted by a consensus-based 
organization, section 1886(j)(7)(D)(ii) of the Act authorizes the 
Secretary to select non-endorsed measures for specified areas or 
medical topics when there are no feasible or practical endorsed 
measure(s).
    Section 1886(j)(7)(E) of the Act requires the Secretary to 
establish procedures for making the IRF PPS quality reporting data 
available to the public. In so doing, the Secretary must ensure that 
IRFs have the opportunity to review any such data prior to its release 
to the public.

C. Operational Overview of the Current IRF PPS

    As described in the FY 2002 IRF PPS final rule, upon the admission 
and discharge of a Medicare Part A Fee-for-Service (FFS) patient, the 
IRF is required to complete the appropriate sections of a patient 
assessment instrument (PAI), designated as the IRF-PAI. In addition, 
beginning with IRF discharges occurring on or after October 1, 2009, 
the IRF is also required to complete the appropriate sections of the 
IRF-PAI upon the admission and discharge of each Medicare Advantage 
(MA) (formerly called Medicare Part C) patient, as described in the FY 
2010 IRF PPS final rule. All required data must be electronically 
encoded into the IRF-PAI software product. Generally, the software 
product includes patient classification programming called the Grouper 
software. The Grouper software uses specific IRF-PAI data elements to 
classify (or group) patients into distinct CMGs and account for the 
existence of any relevant comorbidities.
    The Grouper software produces a 5-character CMG number. The first 
character is an alphabetic character that indicates the comorbidity 
tier. The last 4 characters are numeric characters that represent the 
distinct CMG number. Free downloads of the Inpatient Rehabilitation 
Validation and Entry (IRVEN) software product, including the Grouper 
software, are available on the CMS Web site at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/Software.html.
    Once a Medicare FFS Part A patient is discharged, the IRF submits a 
Medicare claim as a Health Insurance Portability and Accountability Act 
of 1996 (Pub. L. 104-191, enacted on August 21, 1996) (HIPAA) compliant 
electronic claim or, if the Administrative Simplification Compliance 
Act of 2002 (Pub. L. 107-105, enacted on December 27, 2002) (ASCA) 
permits, a paper claim (a UB-04 or a CMS-1450 as appropriate) using the 
five-character CMG number and sends it to the appropriate Medicare 
Administrative Contractor (MAC). In addition, once a Medicare Advantage 
patient is discharged, in accordance with the Medicare Claims 
Processing Manual, chapter 3, section 20.3 (Pub. 100-04), hospitals 
(including IRFs) must submit an informational-only bill (Type of Bill 
(TOB) 111), which includes Condition Code 04 to their MAC. This will 
ensure that the Medicare Advantage days are included in the hospital's 
Supplemental Security Income (SSI) ratio (used in calculating the IRF 
low-income percentage adjustment) for fiscal year 2007 and beyond. 
Claims submitted to Medicare must comply with both ASCA and HIPAA.
    Section 3 of the ASCA amends section 1862(a) of the Act by adding 
paragraph (22), which requires the Medicare program, subject to section 
1862(h) of the Act, to deny payment under Part A or Part B for any 
expenses for items or services ``for which a claim is submitted other 
than in an electronic form specified by the Secretary.'' Section 
1862(h) of the Act, in turn, provides that the Secretary shall waive 
such denial in situations in which there is no method available for the 
submission of claims in an electronic form or the entity submitting the 
claim is a small provider. In addition, the Secretary also has the 
authority to waive such denial ``in such unusual cases as the Secretary 
finds appropriate.'' For more information, see the ``Medicare Program; 
Electronic Submission of Medicare Claims'' final rule (70 FR 71008). 
Our instructions for the limited number of Medicare claims submitted on 
paper are available at http://www.cms.gov/manuals/downloads/clm104c25.pdf.
    Section 3 of the ASCA operates in the context of the administrative 
simplification provisions of HIPAA, which include, among others, the 
requirements for transaction standards and code sets codified in 45 
CFR, parts 160 and 162, subparts A and I through R (generally known as 
the Transactions Rule). The Transactions Rule requires covered 
entities, including covered health care providers, to conduct covered 
electronic transactions according to the applicable transaction 
standards. (See the CMS program claim memoranda at http://www.cms.gov/ElectronicBillingEDITrans/ and listed in the addenda to the Medicare 
Intermediary Manual, Part 3, section 3600).
    The MAC processes the claim through its software system. This 
software system includes pricing programming called the ``Pricer'' 
software. The Pricer

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software uses the CMG number, along with other specific claim data 
elements and provider-specific data, to adjust the IRF's prospective 
payment for interrupted stays, transfers, short stays, and deaths, and 
then applies the applicable adjustments to account for the IRF's wage 
index, percentage of low-income patients, rural location, and outlier 
payments. For discharges occurring on or after October 1, 2005, the IRF 
PPS payment also reflects the teaching status adjustment that became 
effective as of FY 2006, as discussed in the FY 2006 IRF PPS final rule 
(70 FR 47880).

D. Advancing Health Information Exchange

    The Department of Health & Human Services (HHS) has a number of 
initiatives designed to encourage and support the adoption of health 
information technology and to promote nationwide health information 
exchange to improve health care. As discussed in the August 2013 
Statement ``Principles and Strategies for Accelerating Health 
Information Exchange'' (available at http://www.healthit.gov/sites/default/files/acceleratinghieprinciples_strategy.pdf). HHS believes 
that all individuals, their families, their healthcare and social 
service providers, and payers should have consistent and timely access 
to health information in a standardized format that can be securely 
exchanged between the patient, providers, and others involved in the 
individual's care. Health IT that facilitates the secure, efficient, 
and effective sharing and use of health-related information when and 
where it is needed is an important tool for settings across the 
continuum of care, including inpatient rehabilitation facilities. The 
effective adoption and use of health information exchange and health IT 
tools will be essential as IRFs seek to improve quality and lower costs 
through value-based care.
    The Office of the National Coordinator for Health Information 
Technology (ONC) has released a document entitled ``Connecting Health 
and Care for the Nation: A Shared Nationwide Interoperability Roadmap'' 
(available at https://https://www.healthit.gov/sites/default/files/hie-interoperability/nationwide-interoperability-roadmap-final-version-1.0.pdf). In the near term, the Roadmap focuses on actions that will 
enable individuals and providers across the care continuum to send, 
receive, find, and use a common set of electronic clinical information 
at the nationwide level by the end of 2017. The Roadmap's goals also 
align with the Improving Medicare Post-Acute Care Transformation Act of 
2014 (Pub. L. 113-185, enacted on October 6, 2014) (IMPACT Act), which 
requires assessment data to be standardized and interoperable to allow 
for exchange of the data.
    The Roadmap identifies four critical pathways that health IT 
stakeholders should focus on now in order to create a foundation for 
long-term success: (1) Improve technical standards and implementation 
guidance for priority data domains and associated elements; (2) rapidly 
shift and align federal, state, and commercial payment policies from 
FFS to value-based models to stimulate the demand for interoperability; 
(3) clarify and align federal and state privacy and security 
requirements that enable interoperability; and (4) align and promote 
the use of consistent policies and business practices that support 
interoperability, in coordination with stakeholders. In addition, ONC 
has released the final version of the 2016 Interoperability Standards 
Advisory (available at https://www.healthit.gov/standards-advisory/2016), which provides a list of the best available standards and 
implementation specifications to enable priority health information 
exchange functions. Providers, payers, and vendors are encouraged to 
take these ``best available standards'' into account as they implement 
interoperable health information exchange across the continuum of care, 
including care settings such as inpatient rehabilitation facilities.
    We encourage stakeholders to utilize health information exchange 
and certified health IT to effectively and efficiently help providers 
improve internal care delivery practices, engage patients in their 
care, support management of care across the continuum, enable the 
reporting of electronically specified clinical quality measures 
(eCQMs), and improve efficiencies and reduce unnecessary costs. As 
adoption of certified health IT increases and interoperability 
standards continue to mature, HHS will seek to reinforce standards 
through relevant policies and programs. We received one comment on 
health information exchange, which is summarized below.
    Comment: A commenter stated that the rule focuses only on 
providers, vendors, and institutions, not individuals and that sharing 
information requires standardized data exchange. The commenter 
suggested that CMS add a system-wide measure to assess whether robust 
data standards, policies, and governance infrastructure exists to 
support widespread industry and individual participation.
    Response: We agree with the commenter that all individuals, 
families, and healthcare providers should have consistent and timely 
access to health information, in accordance with applicable law, in a 
standardized format that can be securely exchanged to support the 
health and wellness of individuals and shared decision-making. We agree 
nationwide interoperability across the care continuum will require 
stakeholders to agree to and follow a common set of standards, 
services, policies and practices that facilitates the exchange and use 
of interoperable health information. ONC recently requested comment on 
system-wide measures of interoperability required under the Medicare 
Access and CHIP Reauthorization Act of 2015 (81 FR 20651, https://federalregister.gov/a/2016-08134).

II. Summary of Provisions of the Proposed Rule

    In the FY 2017 IRF PPS proposed rule (81 FR 24178), we proposed to 
update the IRF federal prospective payment rates for FY 2017 and to 
revise and update quality measures and reporting requirements under the 
IRF QRP.
    The proposed updates to the IRF federal prospective payment rates 
for FY 2017 were as follows:
     Update the FY 2017 IRF PPS relative weights and average 
length of stay values using the most current and complete Medicare 
claims and cost report data in a budget-neutral manner, as discussed in 
section III of the FY 2017 IRF PPS proposed rule (81 FR 24178, 24184 
through 24187).
     Describe the continued use of FY 2014 facility-level 
adjustment factors as discussed in section IV of the FY 2017 IRF PPS 
proposed rule (81 FR 24178 at 24187).
     Update the FY 2017 IRF PPS payment rates by the proposed 
market basket increase factor, based upon the most current data 
available, with a 0.75 percentage point reduction as required by 
sections 1886(j)(3)(C)(ii)(II) and 1886(j)(3)(D)(v) of the Act and a 
proposed productivity adjustment required by section 
1886(j)(3)(C)(ii)(I) of the Act, as described in section V of the FY 
2017 IRF PPS proposed rule (81 FR 24178, 24187 through 24189).
     Update the FY 2017 IRF PPS payment rates by the FY 2017 
wage index and the labor-related share in a budget-neutral manner, as 
discussed in section V of the FY 2017 IRF PPS proposed rule (81 FR 
24178, 24189 through 24190).

[[Page 52062]]

     Describe the calculation of the IRF standard payment 
conversion factor for FY 2017, as discussed in section V of the FY 2017 
IRF PPS proposed rule (81 FR 24178, 24190 through 24192).
     Update the outlier threshold amount for FY 2017, as 
discussed in section VI of the FY 2017 IRF PPS proposed rule (81 FR 
24178, at 24193).
     Update the cost-to-charge ratio (CCR) ceiling and urban/
rural average CCRs for FY 2017, as discussed in section VI of the FY 
2017 IRF PPS proposed rule (81 FR 24178, 24193 through 24194).
     Describe proposed revisions and updates to quality 
measures and reporting requirements under the quality reporting program 
for IRFs in accordance with section 1886(j)(7) of the Act, as discussed 
in section VII of the FY 2017 IRF PPS proposed rule (81 FR 24194 
through 24220).

III. Analysis and Responses to Public Comments

    We received 61 timely responses from the public, many of which 
contained multiple comments on the FY 2017 IRF PPS proposed rule (81 FR 
24178). We received comments from various trade associations, inpatient 
rehabilitation facilities, individual physicians, therapists, 
clinicians, health care industry organizations, and health care 
consulting firms. The following sections, arranged by subject area, 
include a summary of the public comments that we received, and our 
responses.

IV. Update to the Case-Mix Group (CMG) Relative Weights and Average 
Length of Stay Values for FY 2017

    As specified in Sec.  412.620(b)(1), we calculate a relative weight 
for each CMG that is proportional to the resources needed by an average 
inpatient rehabilitation case in that CMG. For example, cases in a CMG 
with a relative weight of 2, on average, will cost twice as much as 
cases in a CMG with a relative weight of 1. Relative weights account 
for the variance in cost per discharge due to the variance in resource 
utilization among the payment groups, and their use helps to ensure 
that IRF PPS payments support beneficiary access to care, as well as 
provider efficiency.
    In the FY 2017 IRF PPS proposed rule (81 FR 24178, 24184 through 
24187), we proposed to update the CMG relative weights and average 
length of stay values for FY 2017. As required by statute, we always 
use the most recent available data to update the CMG relative weights 
and average lengths of stay. For FY 2017, we proposed to use the FY 
2015 IRF claims and FY 2014 IRF cost report data. These data are the 
most current and complete data available at this time.
    We note that, as we typically do, we updated our data between the 
FY 2017 IRF PPS proposed and final rules to ensure that we use the most 
recent available data in calculating IRF PPS payments. This updated 
data reflects a more complete set of claims for FY 2015 and additional 
cost report data for FY 2014.
    In the FY 2017 IRF PPS proposed rule, we proposed to apply these 
data using the same methodologies that we have used to update the CMG 
relative weights and average length of stay values each fiscal year 
since we implemented an update to the methodology to use the more 
detailed CCR data from the cost reports of IRF subprovider units of 
primary acute care hospitals, instead of CCR data from the associated 
primary care hospitals, to calculate IRFs' average costs per case, as 
discussed in the FY 2009 IRF PPS final rule (73 FR 46372). In 
calculating the CMG relative weights, we use a hospital-specific 
relative value method to estimate operating (routine and ancillary 
services) and capital costs of IRFs. The process used to calculate the 
CMG relative weights for this final rule is as follows:
    Step 1. We estimate the effects that comorbidities have on costs.
    Step 2. We adjust the cost of each Medicare discharge (case) to 
reflect the effects found in the first step.
    Step 3. We use the adjusted costs from the second step to calculate 
CMG relative weights, using the hospital-specific relative value 
method.
    Step 4. We normalize the FY 2017 CMG relative weights to the same 
average CMG relative weight from the CMG relative weights implemented 
in the FY 2016 IRF PPS final rule (80 FR 47036).
    Consistent with the methodology that we have used to update the IRF 
classification system in each instance in the past, we proposed to 
update the CMG relative weights for FY 2017 in such a way that total 
estimated aggregate payments to IRFs for FY 2017 are the same with or 
without the changes (that is, in a budget-neutral manner) by applying a 
budget neutrality factor to the standard payment amount. To calculate 
the appropriate budget neutrality factor for use in updating the FY 
2017 CMG relative weights, we use the following steps:
    Step 1. Calculate the estimated total amount of IRF PPS payments 
for FY 2017 (with no changes to the CMG relative weights).
    Step 2. Calculate the estimated total amount of IRF PPS payments 
for FY 2017 by applying the changes to the CMG relative weights (as 
discussed in this final rule).
    Step 3. Divide the amount calculated in step 1 by the amount 
calculated in step 2 to determine the budget neutrality factor (0.9992) 
that would maintain the same total estimated aggregate payments in FY 
2017 with and without the changes to the CMG relative weights.
    Step 4. Apply the budget neutrality factor (0.9992) to the FY 2016 
IRF PPS standard payment amount after the application of the budget-
neutral wage adjustment factor.
    In section VI.E. of this final rule, we discuss the proposed use of 
the existing methodology to calculate the standard payment conversion 
factor for FY 2017.
    In Table 1, ``Relative Weights and Average Length of Stay Values 
for Case-Mix Groups,'' we present the CMGs, the comorbidity tiers, the 
corresponding relative weights, and the average length of stay values 
for each CMG and tier for FY 2017. The average length of stay for each 
CMG is used to determine when an IRF discharge meets the definition of 
a short-stay transfer, which results in a per diem case level 
adjustment.

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    Generally, updates to the CMG relative weights result in some 
increases and some decreases to the CMG relative weight values. Table 2 
shows how we estimate that the application of the revisions for FY 2017 
would affect particular CMG relative weight values, which would affect 
the overall distribution of payments within CMGs and tiers. Note that, 
because we proposed to implement the CMG relative weight revisions in a 
budget-neutral manner (as previously described), total estimated 
aggregate payments to IRFs for FY 2017 would not be affected as a 
result of the proposed CMG relative weight revisions. However, the 
proposed revisions would affect the distribution of payments within 
CMGs and tiers.

   Table 2--Distributional Effects of the Changes to the CMG Relative
                                 Weights
              [FY 2016 values compared with FY 2017 values]
------------------------------------------------------------------------
                                                         Percentage of
         Percentage change           Number of cases     cases affected
                                         affected          (percent)
------------------------------------------------------------------------
Increased by 15% or more..........                  0                0.0
Increased by between 5% and 15%...                540                0.1
Changed by less than 5%...........            395,897               99.7
Decreased by between 5% and 15%...                761                0.2
Decreased by 15% or more..........                 41                0.0
------------------------------------------------------------------------

    As Table 2 shows, 99.7 percent of all IRF cases are in CMGs and 
tiers that would experience less than a 5 percent change (either 
increase or decrease) in the CMG relative weight value as a result of 
the revisions for FY 2017. The largest estimated increase in the CMG 
relative weight values that affects the largest number of IRF 
discharges would be a 0.7 percent change in the CMG relative weight 
value for CMG 0604--Neurological, with a motor score less than 25.85--
in the ``no comorbidity'' tier. In the FY 2015 claims data, 8,572 IRF 
discharges (2.2 percent of all IRF discharges) were classified into 
this CMG and tier.
    The largest decrease in a CMG relative weight value affecting the 
largest number of IRF cases would be a 1.4 percent decrease in the CMG 
relative weight for CMG 0110--Stroke, with a motor score less than 
22.35 and age less than 84.5--in the ``no comorbidity'' tier. In the FY 
2015 IRF claims data, this change would have affected 13,739 cases (3.5 
percent of all IRF cases).
    The proposed changes in the average length of stay values for FY 
2017, compared with the FY 2016 average length of stay values, are 
small and do not show any particular trends in IRF length of stay 
patterns.

[[Page 52071]]

    We received 3 comments on the proposed update to the CMG relative 
weights and average length of stay values for FY 2017, which are 
summarized below.
    Comment: Commenters, while supportive of the methodology used to 
calculate the weights, requested that we provide more detail about the 
use of the CCR data in the CMG relative weight calculations. 
Additionally, the commenters requested that we outline the methodology 
used to calculate the average length of stay values in the FY 2017 IRF 
PPS proposed rule.
    Response: As we discussed, most recently, in the FY 2016 IRF PPS 
final rule (80 FR 47036, 47045), a key variable used to calculate the 
CMG relative weights is a facility's average cost per case, which is 
obtained by averaging the estimated cost per case for every patient 
discharged from the facility in a given fiscal year. To obtain the 
estimated cost per case for a given IRF patient, we start by pulling 
the appropriate charges from the Medicare claim for that patient. Then, 
we calculate the appropriate CCRs from the Medicare cost report 
submitted by the facility. The CCRs are then multiplied by the charges 
from the Medicare claim to obtain the estimated IRF cost for the case. 
This variable is used as the dependent variable in the regression 
analysis to estimate the CMG relative weights.
    As we also discussed in the FY 2016 IRF PPS final rule (80 FR 
47036, 47045), the methodology for calculating the average length of 
stay values is available for download from the IRF PPS Web site at 
http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/Research.html.
    Final Decision: After careful consideration of the public comments, 
we are finalizing our proposal to update the CMG relative weight and 
average length of stay values for FY 2017, as shown in Table 1 of this 
final rule. These updates are effective October 1, 2016.

V. Facility-Level Adjustment Factors

    Section 1886(j)(3)(A)(v) of the Act confers broad authority upon 
the Secretary to adjust the per unit payment rate by such factors as 
the Secretary determines are necessary to properly reflect variations 
in necessary costs of treatment among rehabilitation facilities. Under 
this authority, we currently adjust the federal prospective payment 
amount associated with a CMG to account for facility-level 
characteristics such as an IRF's LIP, teaching status, and location in 
a rural area, if applicable, as described in Sec.  412.624(e).
    Based on the substantive changes to the facility-level adjustment 
factors that were adopted in the FY 2014 final rule (78 FR 47860, 47868 
through 47872), in the FY 2015 final rule (79 FR 45872, 45882 through 
45883), we froze the facility-level adjustment factors at the FY 2014 
levels for FY 2015 and all subsequent years (unless and until we 
propose to update them again through future notice-and-comment 
rulemaking). For FY 2017, we will continue to hold the adjustment 
factors at the FY 2014 levels as we continue to monitor the most 
current IRF claims data available and continue to evaluate and monitor 
the effects of the FY 2014 changes.

VI. FY 2017 IRF PPS Payment Update

A. Background

    Section 1886(j)(3)(C) of the Act requires the Secretary to 
establish an increase factor that reflects changes over time in the 
prices of an appropriate mix of goods and services included in the 
covered IRF services, which is referred to as a market basket index. 
According to section 1886(j)(3)(A)(i) of the Act, the increase factor 
shall be used to update the IRF federal prospective payment rates for 
each FY. Section 1886(j)(3)(C)(ii)(I) of the Act requires the 
application of a productivity adjustment, as described below. In 
addition, sections 1886(j)(3)(C)(ii)(II) and 1886(j)(3)(D)(v) of the 
Act require the application of a 0.75 percentage point reduction to the 
market basket increase factor for FY 2017. Thus, in the FY 2017 IRF PPS 
proposed rule (81 FR 24178, 24187 through 24188), we proposed to update 
the IRF PPS payments for FY 2017 by a market basket increase factor as 
required by section 1886(j)(3)(C) of the Act, with a productivity 
adjustment as required by section 1886(j)(3)(C)(ii)(I) of the Act, and 
a 0.75 percentage point reduction as required by sections 
1886(j)(3)(C)(ii)(II) and 1886(j)(3)(D)(v) of the Act.
    For FY 2015, IRF PPS payments were updated using the 2008-based RPL 
market basket. Beginning with the FY 2016 IRF PPS, we created and 
adopted a stand-alone IRF market basket, which was referred to as the 
2012-based IRF market basket, reflecting the operating and capital cost 
structures for freestanding IRFs and hospital-based IRFs. The general 
structure of the 2012-based IRF market basket is similar to the 2008-
based RPL market basket; however, we made several notable changes. In 
developing the 2012-based IRF market basket, we derived cost weights 
from Medicare cost report data for both freestanding and hospital-based 
IRFs (the 2008-based RPL market basket was based on freestanding data 
only), incorporated the 2007 Input-Output data from the Bureau of 
Economic Analysis (the 2008-based RPL market basket was based on the 
2002 Input-Output data); used new price proxy blends for two cost 
categories (Fuel, Oil, and Gasoline and Medical Instruments); added one 
additional cost category (Installation, Maintenance, and Repair), which 
was previously included in the residual All Other Services: Labor-
Related cost category of the 2008-based RPL market basket; and 
eliminated three cost categories (Apparel, Machinery & Equipment, and 
Postage). The FY 2016 IRF PPS final rule (80 FR 47046 through 47068) 
contains a complete discussion of the development of the 2012-based IRF 
market basket.

B. FY 2017 Market Basket Update and Productivity Adjustment

    For FY 2017, we proposed to use the same methodology described in 
the FY 2016 IRF PPS final rule (80 FR 47066) to compute the FY 2017 
market basket increase factor to update the IRF PPS base payment rate. 
Consistent with historical practice, we proposed to estimate the market 
basket update for the IRF PPS based on IHS Global Insight's forecast 
using the most recent available data. IHS Global Insight (IGI), Inc. is 
a nationally recognized economic and financial forecasting firm with 
which CMS contracts to forecast the components of the market baskets 
and multifactor productivity (MFP).
    Based on IGI's first quarter 2016 forecast with historical data 
through the fourth quarter of 2015, we proposed that the projected 
2012-based IRF market basket increase factor for FY 2017 would be 2.7 
percent. We also proposed that if more recent data were subsequently 
available (for example, a more recent estimate of the market basket 
update), we would use such data to determine the FY 2017 update in the 
final rule. Incorporating the most recent data available, based on 
IGI's second quarter 2016 forecast with historical data through the 
first quarter of 2016, the projected 2012-based IRF market basket 
increase factor for FY 2017 is 2.7 percent.
    According to section 1886(j)(3)(C)(i) of the Act, the Secretary 
shall establish an increase factor based on an appropriate percentage 
increase in a market basket of goods and services. Section 
1886(j)(3)(C)(ii) of the Act then 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

[[Page 52072]]

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 ``MFP adjustment''). The 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 Web site at http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch.html.
    Using IGI's first quarter 2016 forecast, the proposed MFP 
adjustment for FY 2017 (the 10-year moving average of MFP for the 
period ending FY 2017) was 0.5 percent. We proposed that if more recent 
data were subsequently available, we would use such data to determine 
the FY 2017 MFP adjustment in the final rule. Incorporating the most 
recent data available, based on IGI's second quarter 2016 forecast with 
historical data through the first quarter of 2016, the projected MFP 
adjustment for FY 2017 is 0.3 percent.
    Thus, in accordance with section 1886(j)(3)(C) of the Act, we 
proposed to base the FY 2017 market basket update, which is used to 
determine the applicable percentage increase for the IRF payments, on 
the most recent estimate of the 2012-based IRF market basket. We 
proposed to then reduce this percentage increase by the most up-to-date 
estimate of the MFP adjustment for FY 2017. Following application of 
the MFP, we proposed to further reduce the applicable percentage 
increase by 0.75 percentage point, as required by sections 
1886(j)(3)(C)(ii)(II) and 1886(j)(3)(D)(v) of the Act. Therefore, the 
estimate of the FY 2017 IRF update for the proposed rule was 1.45 
percent (2.7 percent market basket update, less 0.5 percentage point 
MFP adjustment, less 0.75 percentage point legislative adjustment). 
Incorporating the most recent data, the current estimate of the FY 2017 
IRF update is 1.65 percent (2.7 percent market basket update, less 0.3 
percentage point MFP adjustment, less 0.75 percentage point legislative 
adjustment).
    For FY 2017, the Medicare Payment Advisory Commission (MedPAC) 
recommends that a 0-percent update be applied to IRF PPS payment rates. 
As discussed, and in accordance with sections 1886(j)(3)(C) and 
1886(j)(3)(D) of the Act, the Secretary proposed to update the IRF PPS 
payment rates for FY 2017 by an adjusted market basket increase factor 
of 1.45 percent, as section 1886(j)(3)(C) of the Act does not provide 
the Secretary with the authority to apply a different update factor to 
IRF PPS payment rates for FY 2017. As noted above, incorporating the 
most recent data, the current estimate of the FY 2017 IRF update is 
1.65 percent.
    We received 10 comments on the proposed market basket increase 
update and productivity adjustment, which are summarized below.
    Comment: One commenter (MedPAC) stated that it understood that CMS 
is required to implement this statutory payment update; however, MedPAC 
noted that after reviewing many factors--including indicators of 
beneficiary access to rehabilitative services, the supply of providers, 
and Medicare margins--it determined that Medicare's current payment 
rates for IRFs appear to be adequate and therefore recommended no 
update to IRF payment rates for FY 2017. MedPAC appreciated that CMS 
cited its recommendation, even while noting that the Secretary does not 
have the authority to deviate from statutorily mandated updates.
    Response: As discussed, and in accordance with sections 
1886(j)(3)(C) and 1886(j)(3)(D) of the Act, the Secretary is updating 
IRF PPS payment rates for FY 2017 by an adjusted market basket increase 
factor of 1.65 percent, as section 1886(j)(3)(C) of the Act does not 
provide the Secretary with the authority to apply a different update 
factor to IRF PPS payment rates for FY 2017.
    Comment: Several commenters requested that, with respect to the 
productivity adjustment, CMS remain cognizant of the intensive labor, 
time and costs required by state and/or federal regulations to which 
IRFs are bound. These commenters stated that these requirements may be 
barriers to IRFs achieving further gains in productivity efficiencies. 
Further, some commenters stated that successful rehabilitation outcomes 
require an intense labor component, including the interaction of the 
full multidisciplinary treatment team, which includes physicians, 
nurses, physical and occupational therapists, speech language 
pathologists as well as social workers, psychologists and others. In 
addition, these commenters indicated that some states have regulations 
mandating increased professional staffing ratios between health care 
providers and patients. A few commenters claimed that, since CMS has 
stated its policy is that the majority of patient therapy should be 
one-on-one, which is highly labor-intensive, then CMS should not 
mandate further efficiencies such as productivity adjustments while 
simultaneously implementing new regulations or interpreting existing 
regulations in ways that preclude IRFs from adopting clinically 
appropriate innovations that would allow for greater efficiencies. 
These commenters requested that the 0.5 percentage point productivity 
adjustment be ``reversed.'' In addition, several commenters requested 
that CMS be mindful of the additional labor costs and quality 
improvement activities that IRFs will incur as a result of the 
additional items required in version 1.4 of the IRF PAI beginning on 
October 1, 2016 as well as the IRF PAI proposed changes relating to the 
drug regimen measure for which data would start to be collected on 
October 1, 2018.
    Response: Section 1886(j)(3)(C)(ii)(I) of the Act requires the 
application of a productivity adjustment that must be applied to the 
IRF PPS market basket update. The statute does not provide the 
Secretary with the authority to ``reverse'' the productivity adjustment 
or apply a different adjustment. We will continue to monitor the impact 
of the payment updates, including the effects of the productivity 
adjustment, on IRF provider margins as well as beneficiary access to 
care.
    Comment: One commenter recommended that CMS use the latest data 
available in estimating the market basket in the final rule.
    Response: We agree with the commenter's recommendation, and it is 
consistent with the proposed rule language stating that the final IRF 
PPS payment update will be based on the most recent forecast of the 
market basket update and productivity adjustment. As noted above, the 
most recent estimate of the 2012-based IRF market basket is based on 
IGI's second quarter 2016 forecast with historical data through the 
first quarter of 2016.
    Final Decision: Based on careful consideration of the comments, we 
are finalizing the FY 2017 market basket update for IRF payments of 
1.65 percent (2.7 percent market basket update, less 0.3 percentage 
point MFP adjustment, less 0.75 percentage point legislative 
adjustment), which is based on the most recent forecasts of the 2012-
based IRF market basket update and the MFP adjustment.

[[Page 52073]]

C. Labor-Related Share for FY 2017

    Section 1886(j)(6) of the Act specifies that the Secretary is to 
adjust the proportion (as estimated by the Secretary from time to time) 
of rehabilitation facilities' costs which are attributable to wages and 
wage-related costs of the prospective payment rates computed under 
section 1886(j)(3) for area differences in wage levels by a factor 
(established by the Secretary) reflecting the relative hospital wage 
level in the geographic area of the rehabilitation facility compared to 
the national average wage level for such facilities. 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 continue to classify a cost category as labor-related 
if the costs are labor-intensive and vary with the local labor market.
    Based on our definition of the labor-related share and the cost 
categories in the 2012-based IRF market basket, we proposed to include 
in the labor-related share for FY 2017 the sum of the FY 2017 relative 
importance of Wages and Salaries, Employee Benefits, Professional Fees: 
Labor-Related, Administrative and Facilities Support Services, 
Installation, Maintenance, and Repair, All Other: Labor-related 
Services, and a portion of the Capital-Related cost weight from the 
2012-based IRF market basket. For more details regarding the 
methodology for determining specific cost categories for inclusion in 
the 2012-based IRF labor-related share, see the FY 2016 IRF final rule 
(80 FR 47066 through 47068).
    Using this method and the IHS Global Insight, Inc. first quarter 
2016 forecast for the 2012-based IRF market basket, the proposed IRF 
labor-related share for FY 2017 was 71.0 percent. We proposed that if 
more recent data were subsequently available, we would use such data to 
determine the FY 2017 IRF labor-related share in the final rule.
    Incorporating the most recent estimate of the 2012-based IRF market 
basket based on IGI's second quarter 2016 forecast with historical data 
through the first quarter of 2016, the sum of the relative importance 
for FY 2017 operating costs (Wages and Salaries, Employee Benefits, 
Professional Fees: Labor-related, Administrative and Facilities Support 
Services, Installation Maintenance & Repair Services, and All Other: 
Labor-related Services) using the 2012-based IRF market basket is 67.0 
percent. We proposed that the portion of Capital-Related Costs that is 
influenced by the local labor market is estimated to be 46 percent. 
Incorporating the most recent estimate of the FY 2017 relative 
importance of Capital-Related costs from the 2012-based IRF market 
basket based on IGI's second quarter 2016 forecast with historical data 
through the first quarter of 2016, which is 8.4 percent, we take 46 
percent of 8.4 percent to determine the labor-related share of Capital 
for FY 2017. As we proposed, we then add this amount (3.9 percent) to 
the sum of the relative importance for FY 2017 operating costs (67.0 
percent) to determine the total labor-related share for FY 2017 of 70.9 
percent.

                    Table 3--IRF Labor-Related Share
------------------------------------------------------------------------
                                      FY 2017  Final     FY 2016  Final
                                      labor-related      labor-related
                                        share \1\          share \2\
------------------------------------------------------------------------
Wages and Salaries................               47.7               47.6
Employee Benefits.................               11.3               11.4
Professional Fees: Labor-related..                3.5                3.5
Administrative and Facilities                     0.8                0.8
 Support Services.................
Installation, Maintenance, and                    1.9                2.0
 Repair...........................
All Other: Labor-related Services.                1.8                1.8
Subtotal..........................               67.0               67.1
Labor-related portion of capital                  3.9                3.9
 (46%)............................
                                   -------------------------------------
    Total Labor-Related Share.....               70.9               71.0
------------------------------------------------------------------------
\1\ Based on the 2012-based IRF Market Basket, IHS Global Insight, Inc.
  2nd quarter 2016 forecast.
\2\ Federal Register 80 FR 47068.

    Final Decision: As we did not receive any comments on the proposed 
labor-related share for FY 2017, we are finalizing the FY 2017 labor-
related share of 70.9 percent.
D. Wage Adjustment
1. Background
    Section 1886(j)(6) of the Act requires the Secretary to adjust the 
proportion of rehabilitation facilities' costs attributable to wages 
and wage-related costs (as estimated by the Secretary from time to 
time) by a factor (established by the Secretary) reflecting the 
relative hospital wage level in the geographic area of the 
rehabilitation facility compared to the national average wage level for 
those facilities. The Secretary is required to update the IRF PPS wage 
index on the basis of information available to the Secretary on the 
wages and wage-related costs to furnish rehabilitation services. Any 
adjustment or updates made under section 1886(j)(6) of the Act for a FY 
are made in a budget-neutral manner.
    For FY 2017, we proposed to maintain the policies and methodologies 
described in the FY 2016 IRF PPS final rule (80 FR 47036, 47068 through 
47075) related to the labor market area definitions and the wage index 
methodology for areas with wage data. Thus, we proposed to use the CBSA 
labor market area definitions and the FY 2016 pre-reclassification and 
pre-floor hospital wage index data. The current statistical areas which 
were implemented in FY 2016 are based on OMB standards published on 
February 28, 2013, in OMB Bulletin No. 13-01. For FY 2017, we are 
continuing to use the new OMB delineations that we adopted beginning 
with FY 2016. In accordance with section 1886(d)(3)(E) of the Act, the 
FY 2016 pre-reclassification and pre-floor hospital wage index is based 
on data submitted for hospital cost reporting periods beginning on or 
after October 1, 2011, and before October 1, 2012 (that is, FY 2012 
cost report data).
    The labor market designations made by the OMB include some 
geographic areas where there are no hospitals and, thus, no hospital 
wage index data on which to base the calculation of the IRF PPS wage 
index. We proposed to continue to use the same methodology discussed in 
the FY 2008 IRF PPS final rule (72 FR 44299) to address those 
geographic areas where there are no

[[Page 52074]]

hospitals and, thus, no hospital wage index data on which to base the 
calculation for the FY 2017 IRF PPS wage index.
    We did not receive any comments on these proposals. Therefore, we 
are finalizing our proposal to use the CBSA labor market area 
definitions and the FY 2016 pre-reclassification and pre-floor hospital 
wage index data for areas with wage data. We are also finalizing our 
proposal to continue to use the same methodology discussed in the FY 
2008 IRF PPS final rule (72 FR 44299) to address those geographic areas 
where there are no hospitals and, thus, no hospital wage index data.
2. Update
    The wage index used for the IRF PPS is calculated using the pre-
reclassification and pre-floor acute care hospital wage index data and 
is assigned to the IRF on the basis of the labor market area in which 
the IRF is geographically located. IRF labor market areas are 
delineated based on the CBSAs established by the OMB. In the FY 2016 
IRF PPS final rule (80 FR 47036, 47068), we established an IRF wage 
index based on FY 2011 acute care hospital wage data to adjust the FY 
2016 IRF payment rates. We also adopted the revised CBSAs set forth by 
OMB. The current CBSA delineations (which were implemented for the IRF 
PPS beginning with FY 2016) are based on revised OMB delineations 
issued on February 28, 2013, in OMB Bulletin No. 13-01. OMB Bulletin 
No. 13-01 established revised delineations for Metropolitan Statistical 
Areas, Micropolitan Statistical Areas, and Combined Statistical Areas 
in the United States and Puerto Rico, and provided guidance on the use 
of the delineations of these statistical areas based on new standards 
published on June 28, 2010, in the Federal Register (75 FR 37246 
through 37252). A copy of this bulletin may be obtained at http://www.whitehouse.gov/sites/default/files/omb/bulletins/2013/b-13-01.pdf. 
For FY 2017, we are continuing to use the new OMB delineations that we 
adopted beginning with FY 2016 to calculate the area wage indexes and 
the transition periods, which we discuss below.
3. Transition Period
    In FY 2016, we applied a 1-year blended wage index for all IRF 
providers to mitigate the impact of the wage index change due to the 
implementation of the revised CBSA delineations. Under that policy, all 
IRF providers are receiving a blended wage index in FY 2016 using 50 
percent of their FY 2016 wage index based on the revised OMB CBSA 
delineations and 50 percent of their FY 2016 wage index based on the 
OMB delineations used in FY 2015. For FY 2017, we proposed to maintain 
the policy established in FY 2016 IRF PPS final rule related to the 
blended one-year transition wage index (see 80 FR 47036, 47073 through 
47074). Thus, the 1-year blended wage index that became effective on 
October 1, 2015, will expire on September 30, 2016.
    We did not receive any comments on the proposal to maintain the 
policy established in FY 2016 IRF PPS final rule related to the blended 
one-year transition wage index.
    Final decision: As we did not receive any comments on our proposal 
to maintain the 1-year blended wage index for all IRF providers, we are 
finalizing the expiration of this policy on September 30, 2016.
    For FY 2016, in addition to the blended wage index, we also adopted 
a 3-year budget neutral phase out of the rural adjustment for IRFs that 
were rural in FY 2015 and became urban in FY 2016 under the revised 
CBSA delineations. In FY 2016, IRFs that were designated as rural in FY 
2015 and became designated as urban in FY 2016 received two-thirds of 
the 2015 rural adjustment of 14.9 percent. FY 2017 represents the 
second year of the 3-year phase out of the rural adjustment, in which 
these same IRFs will receive one-third of the 2015 rural adjustment of 
14.9 percent, as finalized in the FY 2016 IRF PPS final rule (80 FR 
47036, 47073 through 47074).
    For FY 2017, the wage index will be based solely on the previously 
adopted revised CBSA delineations and their respective wage index 
(rather than on a blended wage index). Furthermore, we will continue 
the 3-year phase out of the rural adjustments for IRF providers that 
changed from rural to urban status that was finalized in the FY 2016 
IFR PPS final rule (80 FR 47036, 47073 through 47074).
    We received one comment on our proposal to continue the 3-year 
phase out of the rural adjustments for IRF providers that changed from 
rural to urban status and that was finalized in the FY 2016 IFR PPS 
final rule.
    Comment: One commenter suggested that we implement a 5-year phase-
out of the rural adjustment or allow IRFs that are losing the FY 2015 
rural adjustment due to the changes in the CBSA delineations to apply 
for reclassification back to rural status for a period of 5 years.
    Response: The intent of the 3-year phase-out of the rural 
adjustment is to mitigate potential negative payment effects on rural 
facilities that are redesignated as urban facilitates, effective FY 
2016. As described in more detail in the FY 2006 IRF PPS final rule (70 
FR 47880), our analysis determined that a 3-year budget-neutral 
transition policy would best accomplish the goals of mitigating the 
loss of the rural adjustment for existing IRFs that were rural in FY 
2005 and became urban in FY 2006 under the new CBSA designations. For a 
complete discussion of this policy, we refer readers to the FY 2006 IRF 
PPS final rule (70 FR 47880, 47921 through 47925). As discussed in the 
FY 2016 IRF PPS final rule (80 FR 47036, 47074), we continue to believe 
that a 3-year budget-neutral phase-out of the rural adjustment 
appropriately mitigates the adverse payment impacts for these IRFs 
while also ensuring that payment rates for all IRFs are set accurately 
and appropriately.
    Final Decision: After careful consideration, we are finalizing the 
continuation of the 3-year phase-out of the rural adjustment for IRFs 
that were designated as rural in FY 2015 but changed to urban in FY 
2016 under the new OMB market area delineations. For FY 2017, these 
IRFs will receive the full FY 2017 wage index and one-third of the FY 
2015 rural adjustment. For FY 2018, these IRFs will receive the full FY 
2018 wage index with no rural adjustment.
    For a full discussion of our implementation of the new OMB labor 
market area delineations for the FY 2016 wage index, please refer to 
the FY 2016 IRF PPS final rule (80 FR 47036, 47068 through 47076). 
While conducting analysis for the FY 2017 IRF PPS final rule, an 
additional IRF provider was identified as being eligible for the 3-year 
phase out of the rural adjustments for IRF providers that changed from 
rural to urban status. The original 19 providers were identified in FY 
2014 claims data for the FY 2016 IRF PPS proposed and final rules. This 
newly eligible provider was new in FY 2015 and thus had no claims data 
in FY 2014. An analysis of the FY 2015 claims determined that this 
provider should have received two-thirds of the rural adjustment in FY 
2016. This provider will be added to the group of providers receiving 
two-thirds of the rural adjustment in FY 2016 and one-third of the 
rural adjustment in FY 2017. For FY 2017, 20 IRFs that were designated 
as rural in FY 2015 and became designated as urban in FY 2016 will 
receive the FY 2017 wage index (based solely on the revised CBSA 
delineations) and one-third of the FY 2015 rural adjustment of 14.9 
percent (80 FR 47036, 47073 through 47076). The wage index applicable 
to FY 2017

[[Page 52075]]

is available on the CMS Web site at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/Data-Files.html. 
Table A is for urban areas, and Table B is for rural areas.
    To calculate the wage-adjusted facility payment for the payment 
rates set forth in this final rule, we multiply the unadjusted federal 
payment rate for IRFs by the FY 2017 labor-related share based on the 
2012-based IRF market basket (70.9 percent) to determine the labor-
related portion of the standard payment amount. A full discussion of 
the calculation of the labor-related share is located in section VI.C 
of this final rule. We then multiply the labor-related portion by the 
applicable IRF wage index from the tables in the addendum to this final 
rule. These tables are available through the Internet on the CMS Web 
site at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/Data-Files.html.
    Adjustments or updates to the IRF wage index made under section 
1886(j)(6) of the Act must be made in a budget-neutral manner. We 
proposed to calculate a budget-neutral wage adjustment factor as 
established in the FY 2004 IRF PPS final rule (68 FR 45689), codified 
at Sec.  412.624(e)(1), as described in the steps below. We proposed to 
use the listed steps to ensure that the FY 2017 IRF standard payment 
conversion factor reflects the update to the wage indexes (based on the 
FY 2012 hospital cost report data) and the labor-related share in a 
budget-neutral manner:
    Step 1. Determine the total amount of the estimated FY 2016 IRF PPS 
payments, using the FY 2016 standard payment conversion factor and the 
labor-related share and the wage indexes from FY 2016 (as published in 
the FY 2016 IRF PPS final rule (80 FR 47036)).
    Step 2. Calculate the total amount of estimated IRF PPS payments 
using the FY 2017 standard payment conversion factor and the FY 2017 
labor-related share and CBSA urban and rural wage indexes.
    Step 3. Divide the amount calculated in step 1 by the amount 
calculated in step 2. The resulting quotient is the FY 2017 budget-
neutral wage adjustment factor of 0.9992.
    Step 4. Apply the FY 2017 budget-neutral wage adjustment factor 
from step 3 to the FY 2016 IRF PPS standard payment conversion factor 
after the application of the adjusted market basket update to determine 
the FY 2017 standard payment conversion factor.
    We discuss the calculation of the standard payment conversion 
factor for FY 2017 in section VI.E of this final rule.
    We did not receive any specific comments on the proposal to 
calculate a budget-neutral wage adjustment factor.
    Final Decision: As we did not receive any comments on the proposal 
to calculate a budget-natural wage adjustment factor, we are finalizing 
our calculation of the budget-neutral wage adjustment factor of 0.9992 
for FY 2017.
    We received 11 public comments on the proposed IRF wage adjustment 
for FY 2017, which are summarized below.
    Comment: Commenters again recommended that we develop a new 
methodology for the area wage adjustment that eliminates hospital wage 
index reclassifications for all hospitals and reduces the problems 
associated with annual fluctuations in wage indices and across 
geographic boundaries. Until such time as the new methodology may be 
developed, commenters also recommended that we consider adopting 
certain wage index policies currently employed under the IPPS, because 
IRFs compete in a similar labor pool as acute care hospitals. Such 
comments included requests that CMS grant IRFs the ability to request 
reclassification and/or establish a rural floor policy. One commenter 
further recommended that, until a new wage index system is implemented, 
we institute a ``smoothing'' variable to the current process to reduce 
the fluctuations IRFs annually experience.
    Response: Consistent with our previous responses to these comments 
(most recently published in our FY 2016 IRF PPS final rule (80 FR 
47036, 47076)), we note that the IRF PPS does not account for 
geographic reclassification under sections 1886(d)(8) and (d)(10) of 
the Act, and does not apply the ``rural floor'' under section 4410 of 
the BBA. Furthermore, as we do not have an IRF-specific wage index, we 
are unable to determine at this time the degree, if any, to which a 
geographic reclassification adjustment or a rural floor policy under 
the IRF PPS would be appropriate. The rationale for our current wage 
index policies is fully described in the FY 2006 IRF PPS final rule (70 
FR 47880, 47926 through 47928).
    Additionally, while some commenters recommended that we adopt IPPS 
reclassification and/or floor policies, we note the MedPAC's June 2007 
report to the Congress, titled ``Report to Congress: Promoting Greater 
Efficiency in Medicare'' (available at http://www.medpac.gov/-documents-/reports), recommends that Congress ``repeal the existing 
hospital wage index statute, including reclassification and exceptions, 
and give the Secretary authority to establish new wage index systems.'' 
We continue to believe it would not be appropriate at this time to 
adopt the IPPS wage index policies, such as reclassification and/or 
floor policies. Therefore, we will continue to use the CBSA labor 
market area definitions and the pre-reclassification and pre-floor 
hospital wage index data based on 2012 cost report data as this is the 
most recent final data available.
    With regard to issues mentioned about ensuring that the wage index 
minimizes fluctuations, matches the costs of labor in the market, and 
provides for a single wage index policy, we note that section 3137(b) 
of the Affordable Care Act required us to submit a report to the 
Congress by December 31, 2011 that includes a plan to reform the 
hospital wage index system. This report describes the concept of a 
Commuting Based Wage Index as a potential replacement to the current 
Medicare wage index methodology. While this report addresses the goals 
of broad based Medicare wage index reform, no consensus has been 
achieved regarding how best to implement a replacement system. These 
concerns will be taken into consideration while CMS continues to 
explore potential wage index reforms.
    The report that we submitted is available online at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Wage-Index-Reform.html.
    Comment: Several commenters suggested that CMS use the most current 
wage data that is available and align the timeframe for the IRF wage 
index with other post-acute and acute care settings. These commenters 
indicated that this would position the IRF PPS to be more in line with 
alternative payment models that are currently being developed and 
tested.
    Response: As we did not propose any changes to the methodology for 
determining the wage index for IRF providers, these comments are 
outside the scope of the proposed rule. We appreciate the commenters' 
suggestions and agree that this issue needs to be considered within the 
broader context of Medicare post-acute care payment reform efforts. We 
will consider these suggestions for future analyses.
    Final Decision: After careful consideration of the comments, we are 
finalizing use of the FY 2016 pre-floor, pre-reclassified hospital wage 
index data to derive the applicable IRF PPS wage index for FY 2017. We 
are also continuing to implement the 3-year

[[Page 52076]]

phase-out of the rural adjustment for IRFs that were designated as 
rural in FY 2015 but changed to urban in FY 2016 under the new OMB 
market area delineations. For FY 2017, these IRFs will receive the full 
FY 2017 wage index and one-third of the FY 2015 rural adjustment. For 
FY 2018, these IRFs will receive the full FY 2018 wage index with no 
rural adjustment.

E. Description of the IRF Standard Payment Conversion Factor and 
Payment Rates for FY 2017

    To calculate the standard payment conversion factor for FY 2017, as 
illustrated in Table 4, we begin by applying the adjusted market basket 
increase factor for FY 2017 that was adjusted in accordance with 
sections 1886(j)(3)(C) and (D) of the Act, to the standard payment 
conversion factor for FY 2016 ($15,478). Applying the 1.65 percent 
adjusted market basket increase for FY 2017 to the standard payment 
conversion factor for FY 2016 of $15,478 yields a standard payment 
amount of $15,733. Then, we apply the budget neutrality factor for the 
FY 2017 wage index and labor-related share of 0.9992, which results in 
a standard payment amount of $15,721. We next apply the budget 
neutrality factor for the revised CMG relative weights of 0.9992, which 
results in the standard payment conversion factor of $15,708 for FY 
2017.

     Table 4--Calculations to Determine the FY 2017 Standard Payment
                            Conversion Factor
------------------------------------------------------------------------
             Explanation for adjustment                    Calculations
------------------------------------------------------------------------
Standard Payment Conversion Factor for FY 2016.....              $15,478
Market Basket Increase Factor for FY 2017 (2.7        x           1.0165
 percent), reduced by 0.3 percentage point for the
 productivity adjustment as required by section
 1886(j)(3)(C)(ii)(I) of the Act, and reduced by
 0.75 percentage point in accordance with
 paragraphs 1886(j)(3)(C) and (D) of the Act.......
Budget Neutrality Factor for the Wage Index and       x           0.9992
 Labor-Related Share...............................
Budget Neutrality Factor for the Revisions to the     x           0.9992
 CMG Relative Weights..............................
FY 2017 Standard Payment Conversion Factor.........   =           15,708
------------------------------------------------------------------------

    We did not receive comments specifically on the proposed FY 2017 
standard payment conversion factor. We received comments on how the FY 
2016 IRF QRP relates to the proposed FY 2017 standard payment 
conversion factor, which we have summarized in section IX. of this 
final rule.
    Final Decision: As we did not receive comments specifically on the 
proposed FY 2017 standard payment conversion factor, we are finalizing 
the IRF standard payment conversion factor of $15,708 for FY 2017.
    After the application of the proposed CMG relative weights 
described in section IV of this final rule to the FY 2017 standard 
payment conversion factor ($15,708), the resulting unadjusted IRF 
prospective payment rates for FY 2017 are shown in Table 5.

                                         Table 5--FY 2017 Payment Rates
----------------------------------------------------------------------------------------------------------------
                                                   Payment rate    Payment rate    Payment rate    Payment rate
                       CMG                            Tier 1          Tier 2          Tier 3      no comorbidity
----------------------------------------------------------------------------------------------------------------
0101............................................      $12,553.83      $11,179.38      $10,227.48       $9,762.52
0102............................................       15,912.20       14,168.62       12,962.24       12,373.19
0103............................................       18,591.99       16,556.23       15,145.65       14,457.64
0104............................................       19,788.94       17,621.23       16,121.12       15,387.56
0105............................................       22,889.70       20,382.70       18,646.97       17,798.73
0106............................................       25,597.76       22,793.88       20,852.37       19,903.61
0107............................................       28,568.14       25,439.11       23,271.40       22,214.25
0108............................................       35,960.32       32,022.33       29,293.85       27,961.81
0109............................................       32,333.35       28,791.19       26,339.17       25,140.65
0110............................................       42,914.26       38,212.85       34,958.15       33,368.50
0201............................................       12,178.41        9,960.44        8,977.12        8,392.78
0202............................................       17,192.41       14,060.23       12,671.64       11,846.97
0203............................................       19,121.35       15,637.31       14,094.79       13,175.87
0204............................................       21,135.11       17,283.51       15,579.19       14,564.46
0205............................................       25,484.66       20,842.95       18,785.20       17,563.11
0206............................................       30,220.62       24,714.97       22,277.09       20,825.67
0207............................................       39,716.11       32,481.00       29,275.00       27,369.62
0301............................................       17,944.82       14,815.79       13,463.33       12,569.54
0302............................................       22,090.16       18,236.99       16,573.51       15,472.38
0303............................................       25,902.49       21,384.87       19,433.94       18,142.74
0304............................................       33,514.59       27,668.07       25,143.80       23,474.04
0401............................................       15,392.27       13,534.01       12,483.15       11,330.18
0402............................................       22,072.88       19,410.38       17,900.84       16,248.36
0403............................................       34,816.78       30,618.03       28,236.70       25,629.17
0404............................................       60,793.10       53,459.04       49,302.70       44,750.52
0405............................................       54,027.67       47,510.42       43,815.90       39,771.09
0501............................................       13,389.50       10,547.92       10,045.27        9,033.67
0502............................................       18,221.28       14,355.54       13,670.67       12,294.65
0503............................................       22,866.14       18,015.51       17,154.71       15,428.40
0504............................................       26,840.26       21,146.11       20,136.09       18,109.75
0505............................................       30,798.68       24,264.15       23,104.90       20,780.11
0506............................................       42,648.79       33,600.98       31,995.63       28,777.06

[[Page 52077]]

 
0601............................................       16,260.92       12,888.41       11,901.95       10,899.78
0602............................................       20,926.20       16,587.65       15,316.87       14,027.24
0603............................................       25,778.40       20,432.97       18,868.45       17,280.37
0604............................................       34,168.04       27,082.16       25,010.28       22,903.83
0701............................................       15,693.86       12,780.03       12,200.40       11,077.28
0702............................................       20,041.84       16,320.61       15,580.77       14,146.62
0703............................................       24,163.62       19,677.41       18,783.63       17,055.75
0704............................................       31,326.46       25,509.79       24,352.11       22,110.58
0801............................................       12,539.70       10,120.66        9,358.83        8,601.70
0802............................................       16,231.08       13,100.47       12,115.58       11,135.40
0803............................................       21,713.17       17,523.84       16,205.94       14,894.33
0804............................................       19,548.61       15,777.12       14,591.16       13,409.92
0805............................................       23,257.26       18,769.49       17,358.91       15,954.62
0806............................................       28,253.98       22,803.30       21,087.99       19,382.10
0901............................................       15,455.10       12,472.15       11,554.80       10,513.36
0902............................................       19,765.38       15,951.47       14,778.09       13,446.05
0903............................................       24,834.35       20,043.41       18,568.43       16,893.95
0904............................................       31,437.99       25,373.13       23,507.02       21,386.44
1001............................................       16,831.12       14,840.92       12,878.99       11,623.92
1002............................................       21,843.54       19,259.58       16,714.88       15,085.96
1003............................................       30,848.94       27,201.54       23,607.55       21,306.33
1101............................................       20,769.12       18,826.04       15,298.02       13,889.01
1102............................................       29,771.37       26,987.91       21,929.94       19,911.46
1201............................................       16,303.33       16,086.56       14,617.86       12,929.25
1202............................................       18,945.42       18,692.52       16,985.06       15,023.13
1203............................................       24,143.20       23,821.18       21,645.62       19,144.91
1301............................................       18,753.78       14,754.52       13,650.25       12,577.40
1302............................................       25,756.41       20,263.32       18,747.50       17,274.09
1303............................................       31,753.72       24,982.00       23,114.32       21,296.91
1401............................................       13,612.55       11,504.54       10,428.54        9,464.07
1402............................................       18,551.15       15,678.15       14,211.03       12,897.84
1403............................................       22,115.29       18,690.95       16,941.08       15,374.99
1404............................................       27,968.09       23,637.40       21,425.71       19,444.93
1501............................................       15,847.80       13,419.34       12,390.47       11,680.47
1502............................................       20,021.42       16,953.64       15,654.59       14,756.10
1503............................................       24,414.94       20,674.87       19,089.93       17,995.08
1504............................................       30,426.40       25,764.26       23,789.77       22,424.74
1601............................................       15,533.64       14,031.96       13,070.63       12,059.03
1602............................................       20,264.89       18,306.10       17,051.03       15,731.56
1603............................................       25,376.27       22,921.11       21,350.31       19,697.83
1701............................................       17,820.73       14,542.47       13,383.22       12,049.61
1702............................................       22,388.61       18,269.97       16,813.84       15,137.80
1703............................................       26,683.18       21,774.43       20,040.27       18,042.21
1704............................................       34,276.43       27,969.66       25,740.70       23,174.01
1801............................................       20,313.59       16,642.63       14,456.07       12,965.38
1802............................................       28,641.97       23,466.18       20,382.70       18,282.54
1803............................................       45,069.39       36,924.80       32,074.17       28,767.63
1901............................................       19,269.00       16,518.53       14,561.32       14,347.69
1902............................................       35,009.99       30,011.70       26,456.98       26,067.43
1903............................................       57,623.23       49,396.95       43,545.72       42,906.40
2001............................................       14,490.63       11,878.39       10,904.49        9,872.48
2002............................................       19,001.97       15,576.05       14,300.56       12,944.96
2003............................................       23,756.78       19,473.21       17,877.27       16,183.95
2004............................................       30,492.37       24,994.57       22,946.25       20,772.26
2101............................................       26,544.95       26,544.95       23,657.82       21,697.46
5001............................................  ..............  ..............  ..............        2,489.72
5101............................................  ..............  ..............  ..............       10,657.88
5102............................................  ..............  ..............  ..............       26,084.70
5103............................................  ..............  ..............  ..............       12,569.54
5104............................................  ..............  ..............  ..............       33,300.96
----------------------------------------------------------------------------------------------------------------

F. Example of the Methodology for Adjusting the Federal Prospective 
Payment Rates
    Table 6 illustrates the methodology for adjusting the federal 
prospective payments (as described in sections VI.A. through VI.F. of 
this final rule). The following examples are based on two hypothetical 
Medicare beneficiaries, both classified into CMG 0110 (without 
comorbidities). The unadjusted federal prospective payment rate for CMG 
0110 (without comorbidities) appears in Table 5.
    Example: One beneficiary is in Facility A, an IRF located in rural 
Spencer County, Indiana, and another beneficiary is in Facility B, an 
IRF located in urban Harrison County, Indiana. Facility A, a rural non-
teaching hospital has a Disproportionate Share

[[Page 52078]]

Hospital (DSH) percentage of 5 percent (which would result in a LIP 
adjustment of 1.0156), a wage index of 0.8297, and a rural adjustment 
of 14.9 percent. Facility B, an urban teaching hospital, has a DSH 
percentage of 15 percent (which would result in a LIP adjustment of 
1.0454 percent), a wage index of 0.8756, and a teaching status 
adjustment of 0.0784.
    To calculate each IRF's labor and non-labor portion of the federal 
prospective payment, we begin by taking the unadjusted federal 
prospective payment rate for CMG 0110 (without comorbidities) from 
Table 5. Then, we multiply the labor-related share for FY 2017 (70.9 
percent) described in section VI.C. of this final rule by the 
unadjusted federal prospective payment rate. To determine the non-labor 
portion of the federal prospective payment rate, we subtract the labor 
portion of the federal payment from the unadjusted federal prospective 
payment.
    To compute the wage-adjusted federal prospective payment, we 
multiply the labor portion of the federal payment by the appropriate 
wage index located in tables A and B. These tables are available on CMS 
Web site at http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/. The resulting figure is the wage-
adjusted labor amount. Next, we compute the wage-adjusted federal 
payment by adding the wage-adjusted labor amount to the non-labor 
portion.
    Adjusting the wage-adjusted federal payment by the facility-level 
adjustments involves several steps. First, we take the wage-adjusted 
federal prospective payment and multiply it by the appropriate rural 
and LIP adjustments (if applicable). Second, to determine the 
appropriate amount of additional payment for the teaching status 
adjustment (if applicable), we multiply the teaching status adjustment 
(0.0784, in this example) by the wage-adjusted and rural-adjusted 
amount (if applicable). Finally, we add the additional teaching status 
payments (if applicable) to the wage, rural, and LIP-adjusted federal 
prospective payment rates. Table 6 illustrates the components of the 
adjusted payment calculation.
[GRAPHIC] [TIFF OMITTED] TR05AU16.008


[[Page 52079]]


    Thus, the adjusted payment for Facility A would be $34,236.98 and 
the adjusted payment for Facility B would be $34,192.08.

VII. Update to Payments for High-Cost Outliers Under the IRF PPS

A. Update to the Outlier Threshold Amount for FY 2017

    Section 1886(j)(4) of the Act provides the Secretary with the 
authority to make payments in addition to the basic IRF prospective 
payments for cases incurring extraordinarily high costs. A case 
qualifies for an outlier payment if the estimated cost of the case 
exceeds the adjusted outlier threshold. We calculate the adjusted 
outlier threshold by adding the IRF PPS payment for the case (that is, 
the CMG payment adjusted by all of the relevant facility-level 
adjustments) and the adjusted threshold amount (also adjusted by all of 
the relevant facility-level adjustments). Then, we calculate the 
estimated cost of a case by multiplying the IRF's overall CCR by the 
Medicare allowable covered charge. If the estimated cost of the case is 
higher than the adjusted outlier threshold, we make an outlier payment 
for the case equal to 80 percent of the difference between the 
estimated cost of the case and the outlier threshold.
    In the FY 2002 IRF PPS final rule (66 FR 41362 through 41363), we 
discussed our rationale for setting the outlier threshold amount for 
the IRF PPS so that estimated outlier payments would equal 3 percent of 
total estimated payments. For the 2002 IRF PPS final rule, we analyzed 
various outlier policies using 3, 4, and 5 percent of the total 
estimated payments, and we concluded that an outlier policy set at 3 
percent of total estimated payments would optimize the extent to which 
we could reduce the financial risk to IRFs of caring for high-cost 
patients, while still providing for adequate payments for all other 
(non-high cost outlier) cases.
    Subsequently, we updated the IRF outlier threshold amount in the 
FYs 2006 through 2016 IRF PPS final rules and the FY 2011 and FY 2013 
notices (70 FR 47880, 71 FR 48354, 72 FR 44284, 73 FR 46370, 74 FR 
39762, 75 FR 42836, 76 FR 47836, 76 FR 59256, and 77 FR 44618, 78 FR 
47860, 79 FR 45872, 80 FR 47036, respectively) to maintain estimated 
outlier payments at 3 percent of total estimated payments. We also 
stated in the FY 2009 final rule (73 FR 46370 at 46385) that we would 
continue to analyze the estimated outlier payments for subsequent years 
and adjust the outlier threshold amount as appropriate to maintain the 
3 percent target.
    To update the IRF outlier threshold amount for FY 2017, we proposed 
to use FY 2015 claims data and the same methodology that we used to set 
the initial outlier threshold amount in the FY 2002 IRF PPS final rule 
(66 FR 41316 and 41362 through 41363), which is also the same 
methodology that we used to update the outlier threshold amounts for 
FYs 2006 through 2016. Based on an analysis of the preliminary data 
used for the proposed rule, we estimated that IRF outlier payments as a 
percentage of total estimated payments would be approximately 2.8 
percent in FY 2016. Therefore, we proposed to update the outlier 
threshold amount from $8,658 for FY 2016 to $8,301 for FY 2017 to 
maintain estimated outlier payments at approximately 3 percent of total 
estimated aggregate IRF payments for FY 2017.
    We note that, as we typically do, we updated our data between the 
FY 2017 IRF PPS proposed and final rules to ensure that we use the most 
recent available data in calculating IRF PPS payments. This updated 
data includes a more complete set of claims for FY 2015. Based on our 
analysis using this updated data, we now estimate that IRF outlier 
payments as a percentage of total estimated payments are approximately 
2.7 percent in FY 2016. Therefore, we will update the outlier threshold 
amount from $8,658 for FY 2016 to $7,984 for FY 2017 to maintain 
estimated outlier payments at approximately 3 percent of total 
estimated aggregate IRF payments for FY 2017.
    We received 7 public comments on the proposed update to the FY 2017 
outlier threshold amount to maintain estimated outlier payments at 
approximately 3 percent of total estimated IRF payments, which are 
summarized below.
    Comment: Commenters, while supportive of maintaining estimated 
payments for outlier payments at approximately 3 percent, suggested 
that CMS review its methodology for setting the outlier threshold 
amount and modify as needed so that the full 3 percent is paid as 
outlier payments. Some commenters suggested implementing a forecast 
error correction if the full amount of the outlier pool is not paid 
out.
    Response: We will continue to monitor our IRF outlier policies to 
ensure that they continue to compensate IRFs appropriately for treating 
unusually high-cost patients and, thereby, promote access to care for 
patients who are likely to require unusually high-cost care. As we have 
indicated in previous IRF PPS final rules, we do not make adjustments 
to IRF PPS payment rates for the sole purpose of accounting for 
differences between projected and actual outlier payments. We use the 
best available data at the time to establish an outlier threshold for 
IRF PPS payments prior to the beginning of each fiscal year to help 
ensure that estimated outlier payments for that fiscal year will equal 
3 percent of total estimated IRF PPS payments. We analyze expenditures 
annually, and if there is a difference from our projection, that 
information is used to make a prospective adjustment to lower or raise 
the outlier threshold for the upcoming fiscal year. We believe a 
retrospective adjustment would not be appropriate, given that we do not 
recoup or make excess payments to hospitals.
    If outlier payments for a given year turn out to be greater than 
projected, we do not recoup money from hospitals; if outlier payments 
for a given year are lower than projected, we do not make an adjustment 
to account for the difference. Payments for a given discharge in a 
given fiscal year are generally intended to reflect or address the 
prospective average costs of that discharge in that year; that goal 
would be undermined if we adjusted IRF PPS payments to account for 
``underpayments'' or ``overpayments'' in IRF outliers in previous 
years.
    Comment: One commenter recommended that we expand the outlier pool 
from 3 percent to 5 percent in order to ensure that payments are more 
equitably distributed within the IRF payment system. However, this same 
commenter noted that such an expansion in the outlier pool could 
inappropriately reward facilities for inefficiencies. Several other 
commenters stated that expanding the outlier pool would be 
inappropriate for this same reason.
    Response: We refer readers to the 2002 IRF PPS final rule (66 FR 
41316, 41362 through 41363), for a discussion of the rationale for 
setting the outlier threshold amount for the IRF PPS so that estimated 
outlier payments would equal 3 percent of total estimated payments. For 
the 2002 IRF PPS final rule, we analyzed various outlier policies using 
3, 4, and 5 percent of the total estimated payments, and we concluded 
that an outlier policy set at 3 percent of total estimated payments 
would optimize the extent to which we could reduce the financial risk 
to IRFs of caring for high-cost patients, while still providing for 
adequate payments for all other (non-high cost outlier)

[[Page 52080]]

cases. We believe that the outlier policy of 3 percent of total 
estimated payments optimizes the extent to which we can encourage 
facilities to continue to take patients that are likely to have 
unusually high costs, while still providing adequate payment for all 
other cases. Increasing the outlier pool would leave less money 
available to cover the costs of non-outlier cases, due to the fact that 
we would implement such a change in a budget-neutral manner. We believe 
that our current outlier policy, to set outlier payments at 3 percent 
of total payments, is consistent with the statute and the goals of the 
prospective payment system.
    Comment: Several commenters recommended that CMS impose a cap on 
the amount of outlier payments an individual IRF can receive under the 
IRF PPS.
    Response: Comments regarding the amount of outlier payments an 
individual IRF can receive are outside the scope of this rule. However, 
any future consideration given to imposing a limit on outlier payments 
would have to be carefully analyzed and would need to take into account 
any effect on access to IRF care it would have for certain high-cost 
populations.
    Final Decision: Having carefully considered the public comments 
received and also taking into account the most recent available data, 
we are finalizing the outlier threshold amount of $7,984 to maintain 
estimated outlier payments at approximately 3 percent of total 
estimated aggregate IRF payments for FY 2017. This update is effective 
October 1, 2016.

B. Update to the IRF Cost-to-Charge Ratio Ceiling and Urban/Rural 
Averages

    In accordance with the methodology stated in the FY 2004 IRF PPS 
final rule (68 FR 45674, 45692 through 45694), we proposed to apply a 
ceiling to IRFs' CCRs. Using the methodology described in that final 
rule, we proposed to update the national urban and rural CCRs for IRFs, 
as well as the national CCR ceiling for FY 2017, based on analysis of 
the most recent data that is available. We apply the national urban and 
rural CCRs in the following situations:
     New IRFs that have not yet submitted their first Medicare 
cost report.
     IRFs whose overall CCR is in excess of the national CCR 
ceiling for FY 2017, as discussed below.
     Other IRFs for which accurate data to calculate an overall 
CCR are not available.
    Specifically, for FY 2017, we proposed to estimate a national 
average CCR of 0.562 for rural IRFs, which we calculated by taking an 
average of the CCRs for all rural IRFs using their most recently 
submitted cost report data. Similarly, we proposed to estimate a 
national average CCR of 0.435 for urban IRFs, which we calculated by 
taking an average of the CCRs for all urban IRFs using their most 
recently submitted cost report data. We apply weights to both of these 
averages using the IRFs' estimated costs, meaning that the CCRs of IRFs 
with higher total costs factor more heavily into the averages than the 
CCRs of IRFs with lower total costs. We used FY 2013 IRF cost report 
data for the proposed rule. (Please note that we erroneously stated in 
the proposed rule that we used FY 2014 cost report data.) For this 
final rule, we have used the most recent available cost report data (FY 
2014). This includes all IRFs whose cost reporting periods begin on or 
after October 1, 2013, and before October 1, 2014. If, for any IRF, the 
FY 2014 cost report was missing or had an ``as submitted'' status, we 
used data from a previous fiscal year's (that is, FY 2004 through FY 
2013) settled cost report for that IRF. We do not use cost report data 
from before FY 2004 for any IRF because changes in IRF utilization 
since FY 2004 resulting from the 60 percent rule and IRF medical review 
activities suggest that these older data do not adequately reflect the 
current cost of care. Using the updated FY 2014 cost report data for 
this final rule, we estimate a national average CCR of 0.522 for rural 
IRFs, and a national average CCR of 0.421 for urban IRFs.
    In accordance with past practice, we proposed to set the national 
CCR ceiling at 3 standard deviations above the mean CCR. Using this 
method, we proposed a national CCR ceiling of 1.36 for FY 2017. This 
means that, if an individual IRF's CCR were to exceed this proposed 
ceiling of 1.36 for FY 2017, we would replace the IRF's CCR with the 
appropriate proposed national average CCR (either rural or urban, 
depending on the geographic location of the IRF). We calculated the 
proposed national CCR ceiling by:
    Step 1. Taking the national average CCR (weighted by each IRF's 
total costs, as previously discussed) of all IRFs for which we have 
sufficient cost report data (both rural and urban IRFs combined).
    Step 2. Estimating the standard deviation of the national average 
CCR computed in step 1.
    Step 3. Multiplying the standard deviation of the national average 
CCR computed in step 2 by a factor of 3 to compute a statistically 
significant reliable ceiling.
    Step 4. Adding the result from step 3 to the national average CCR 
of all IRFs for which we have sufficient cost report data, from step 1.
    Using the updated FY 2014 cost report data for this final rule, we 
estimate a national average CCR ceiling of 1.29, using this same 
methodology.
    We did not receive any comments on the proposed update to the IRF 
CCR ceiling and the urban/rural averages for FY 2017.
    Final Decision: As we did not receive any comments on the proposed 
updates to the IRF CCR ceiling and the urban/rural averages for FY 
2017, we are finalizing the national average urban CCR at 0.421, the 
national average rural CCR at 0.522, and the national CCR ceiling at 
1.29 for FY 2017. These updates are effective October 1, 2016.

VIII. Revisions and Updates to the IRF Quality Reporting Program (QRP)

A. Background and Statutory Authority

    We seek to promote higher quality and more efficient health care 
for Medicare beneficiaries, and our efforts are furthered by QRPs 
coupled with public reporting of that information. Section 3004(b) of 
the Affordable Care Act amended section 1886(j)(7) of the Act, 
requiring the Secretary to establish the IRF QRP. This program applies 
to freestanding IRFs, as well as IRF units affiliated with either acute 
care facilities or critical access hospitals (CAHs). Beginning with the 
FY 2014 payment determination and subsequent years, the Secretary is 
required to reduce any annual update to the standard federal rate for 
discharges occurring during such fiscal year by 2 percentage points for 
any IRF that does not comply with the requirements established by the 
Secretary. Section 1886(j)(7) of the Act requires that for the FY 2014 
payment determination and subsequent years, each IRF submit data on 
quality measures specified by the Secretary in a form and manner, and 
at a time, specified by the Secretary. For more information on the 
statutory history of the IRF QRP, please refer to the FY 2015 IRF PPS 
final rule (79 FR 45908).
    The Improving Medicare Post-Acute Care Transformation Act of 2014 
(IMPACT Act) imposed new data reporting requirements for certain PAC 
providers, including IRFs. For information on the statutory background 
of the IMPACT Act, please refer to the FY 2016 IRF PPS final rule (80 
FR 47080 through 47083).
    In the FY 2016 IRF PPS final rule, we reviewed general activities 
and finalized the general timeline and sequencing of such activities 
that will occur under the

[[Page 52081]]

IRF QRP. For further information, please refer to the FY 2016 IRF PPS 
final rule (80 FR 40708 through 47128). In addition, we established our 
approach for identifying cross-cutting measures and process for the 
adoption of measures, including the application and purpose of the 
Measures Application Partnership (MAP) and the notice-and-comment 
rulemaking process (80 FR 47080 through 47084). For information on 
these topics, please refer to the FY 2016 IRF PPS final rule (80 FR 
47080).

B. General Considerations Used for Selection of Quality, Resource Use, 
and Other Measures for the IRF QRP

    For a detailed discussion of the considerations we use for the 
selection of IRF QRP quality measures, such as alignment with the CMS 
Quality Strategy,\1\ which incorporates the 3 broad aims of the 
National Quality Strategy,\2\ please refer to the FY 2015 IRF PPS final 
rule (79 FR 45911) and the FY 2016 IRF PPS final rule (80 FR 47083 
through 47084). Overall, we strive to promote high quality and 
efficiency in the delivery of health care to the beneficiaries we 
serve. Performance improvement leading to the highest-quality health 
care requires continuous evaluation to identify and address performance 
gaps and reduce the unintended consequences that may arise in treating 
a large, vulnerable, and aging population. QRPs, coupled with public 
reporting of quality information, are critical to the advancement of 
health care quality improvement efforts. Valid, reliable, relevant 
quality measures are fundamental to the effectiveness of our QRPs. 
Therefore, selection of quality measures is a priority for us in all of 
our QRPs.
---------------------------------------------------------------------------

    \1\ http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.html.
    \2\ http://www.ahrq.gov/workingforquality/nqs/nqs2011annlrpt.htm.
---------------------------------------------------------------------------

    In the IRF PPS FY 2017 proposed rule (81 FR 24178), we proposed to 
adopt for the IRF QRP one measure that we are specifying under section 
1899B(c)(1) of the Act to meet the Medication Reconciliation domain, 
that is, Drug Regimen Review Conducted with Follow-Up for Identified 
Issues-Post Acute Care Inpatient Rehabilitation Facility Quality 
Reporting Program. Further, we proposed to adopt for the IRF QRP three 
measures to meet the resource use and other measure domains identified 
in section 1899B(d)(1) of the Act. These measures include: (1) Total 
Estimated Medicare Spending per Beneficiary: Medicare Spending per 
Beneficiary-Post Acute Care Inpatient Rehabilitation Facility Quality 
Reporting Program; (2) Discharge to Community: Discharge to Community-
Post Acute Care Inpatient Rehabilitation Facility Quality Reporting 
Program, and (3) Potentially Preventable 30-Day Post-Discharge 
Readmission Measure for Inpatient Rehabilitation Facility Quality 
Reporting Program. We also proposed an additional measure, which is not 
required under the IMPACT Act: (4) Potentially Preventable Within Stay 
Readmission Measure for Inpatient Rehabilitation Facilities.
    In our development and specification of measures, we employed a 
transparent process in which we seek input from stakeholders and 
national experts and engage in a process that allows for pre-rulemaking 
input on each measure, as required by section 1890A of the Act. To meet 
this requirement, we provided the following opportunities for 
stakeholder input: Our measure development contractor convened 
technical expert panels (TEPs) that included stakeholder experts and 
patient representatives on July 29, 2015, for the Drug Regimen Review 
Conducted with Follow-Up for Identified Issues measures; on August 25, 
2015, September 25, 2015, and October 5, 2015, for the Discharge to 
Community measures; on August 12 and 13, 2015, and October 14, 2015, 
for the Potentially Preventable 30-Day Post-Discharge Readmission 
Measures and Potentially Preventable Within Stay Readmission Measure 
for IRFs; and on October 29 and 30, 2015, for the Medicare Spending per 
Beneficiary (MSPB) measures. In addition, we released draft quality 
measure specifications for public comment for the Drug Regimen Review 
Conducted with Follow-Up for Identified Issues measures from September 
18, 2015, to October 6, 2015; for the Discharge to Community measures 
from November 9, 2015, to December 8, 2015; for the Potentially 
Preventable 30-Day Post-Discharge Readmission Measure for IRFs and 
Potentially Preventable Within Stay Readmission Measure for IRFs from 
November 2, 2015 to December 1, 2015; and for the MSPB measures from 
January 13, 2016 to February 5, 2016. We implemented a public mailbox, 
[email protected], for the submission of public 
comments. This PAC mailbox is accessible on our post-acute care quality 
initiatives Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-of-2014-Data-Standardization-and-Cross-Setting-MeasuresMeasures.html.
    Additionally, we sought public input from the NQF-convened MAP 
Post-Acute Care, Long-Term Care Workgroup during the annual in-person 
meeting held December 14 and 15, 2015. The MAP, composed of multi-
stakeholder groups, is tasked to provide input on the selection of 
quality and efficiency measures described in section 1890(b)(7)(B) of 
the Act.
    The MAP reviewed each IMPACT Act-related measure, as well as other 
quality measures proposed in this rule for use in the IRF QRP. For more 
information on the MAP's recommendations, please refer to the MAP 2016 
Final Recommendations to HHS and CMS public report at http://www.qualityforum.org/Publications/2016/02/MAP_2016_Considerations_for_Implementing_Measures_in_Federal_Programs_-_PAC-LTC.aspx.
    For measures that do not have NQF endorsement, or which are not 
fully supported by the MAP for use in the IRF QRP, we proposed for the 
IRF QRP for the purposes of satisfying the measure domains required 
under the IMPACT Act, measures that closely align with the national 
priorities identified in the National Quality Strategy (http://www.ahrq.gov/workingforquality/) and for which the MAP supports the 
measure concept. Further discussion as to the importance and high-
priority status of these proposed measures in the IRF setting is 
included under each quality measure in this final rule.
    Although we did not solicit feedback on General Considerations Used 
for Selection of Quality, Resource Use, and Other Measures for the IRF 
QRP, we received a number of comments, which are summarized with our 
responses below.
    Comment: One commenter supported CMS's intention to select measures 
that are already incorporated in various quality reporting programs to 
minimize burden. One commenter commented that CMS should recognize 
burden of data collection and focus on measures that are the most 
clinically relevant and actionable to the facility and patients. 
Additionally, the commenter recommended that CMS use minimum standards 
in the development of new measures so that they are as clear and 
consistent across facilities as possible.
    Response: We appreciate the commenters' support of CMS's intention 
to select measures that are already incorporated in the various quality 
reporting programs to minimize burden. In addition, we note that we 
strive to strike a balance between minimizing burden and addressing 
gaps in quality

[[Page 52082]]

of care as we continue to expand the IRF QRP. We interpret the 
commenter's suggestion that CMS apply minimum standards in its measure 
development to suggest that we simplify our approach to quality measure 
development itself. We will take these recommendations into 
consideration in our future measure development.
    We also received several comments related to the proposed measures, 
the IMPACT Act, NQF endorsement, the NQF MAP review process, and the 
use of TEPs, which are addressed below.
    Comment: We received several comments supporting the goals of the 
IMPACT Act and the implementation of cross-setting measures across PAC 
settings as required by the IMPACT Act. One commenter appreciated the 
use of TEPs and input of stakeholders. These commenters noted the 
importance of functional status measures and recommended that CMS 
include additional functional status measures in future iterations. 
Also, one of the commenters indicated that achieving standardized and 
interoperable patient assessment data will allow for better cross-
setting comparisons of quality and will support the development of 
better quality measures with uniform risk standardization.
    Response: We believe that standardizing patient assessment data 
will allow for the exchange of data among PAC providers in order to 
facilitate care coordination and improve patient outcomes. We 
appreciate the importance of functional status measures and will 
consider inclusion of additional measures. As with our measure 
development process, we will continue to use TEPs, public comments, 
open door forums, and the pre-rulemaking process in order to gather 
stakeholder input on all measures under development.
    Comment: One commenter recommended that CMS seek an increased level 
of patient engagement in order to discern what quality measures are of 
greatest value to patients.
    Response: We value the patient perspective in the measure 
development process. We have employed a transparent process in which we 
seek input from stakeholders, as described earlier. We have also have 
taken several steps to engage stakeholders, including patients, in all 
TEPs, public comments, and special open door forums. In addition, a 
summary of the IMPACT Act measure TEP proceedings, public comments, and 
special open door forums is available on the PAC Quality Initiatives 
Downloads and Videos Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html 
Patient engagement is a priority for CMS, and we will continue to take 
steps to include the patient perspective, especially with regard to 
assembling TEP, which review and comment on our measure development 
activities.
    Comment: Several commenters recommended that CMS delay 
implementation of proposed measures until NQF has completed its review 
and has endorsed measures that are appropriate for the specific 
characteristics of the IRF patient population. A few commenters 
suggested that CMS seek NQF's formal consensus development process 
instead of a time-limited endorsement, as it was perceived that the 
time-limited endorsement was not sufficient.
    Response: We received several comments regarding the NQF 
endorsement status for the proposed measures, and acknowledge the 
commenters' recommendation to submit the measures to the NQF prior to 
implementation. We consider and propose appropriate measures that have 
been endorsed by the NQF whenever possible. However, when this is not 
feasible because there is no NQF-endorsed measure, we utilize our 
statutory authority that allows the Secretary to specify a measure for 
the IRF QRP that is not NQF-endorsed where, as in the case for the 
proposed measures, we have not been able to identify other measures 
that are endorsed or adopted by a consensus organization. While we 
appreciate the importance of consensus endorsement and intend to seek 
such endorsement, we must balance the need to address gaps in quality 
and adhere to statutorily required timelines as in the case of the 
quality and resource use measures that we proposed to address the 
IMPACT Act. In regard to the comments surrounding time-limited 
endorsement, NQF uses time-limited endorsement for measures that meet 
all of the NQF's endorsement criteria with the exception of field 
testing and are critical to advancing quality improvement. When 
measures are granted this two-year endorsement rather than the 
traditional three-year period, measure developers must test the measure 
and return results to NQF within the two-year window to maintain the 
endorsement. We wish to clarify that we have not yet sought endorsement 
of the proposed measures, time-limited or otherwise.
    Comment: Several commenters stated the NQF MAP committee did not 
endorse the proposed measures; instead, the commenters recommended that 
CMS delay measure implementation until the measures are fully developed 
and tested and brought back to the NQF for further consideration. One 
commenter further stated that TEP members and other stakeholders who 
provided feedback in the measure development process did not support 
measures moving forward without further testing.
    Response: We interpret this comment to address the activities of 
the Measures Application Partnership, a multi-stakeholder partnership 
convened by NQF that provides input to the U.S. Department of Health 
and Human Services (HHS) on its selection of measures for certain 
Medicare programs. We would like to clarify that the MAP ``encouraged 
continued development'' for the proposed measures. According to the 
MAP, the term ``encourage continued development'' is applied when a 
measure addresses a critical program objective or promotes alignment, 
but is in an earlier stage of development. In contrast, the MAP uses 
the phrase ``do not support'' when it does not support the measure at 
all.
    Since the MAP recommendation of ``encourage continued development'' 
for the proposed measures during the December 2015 NQF-convened PAC LTC 
MAP meeting, further refinement of measure specifications and testing 
of measure validity and reliability have been performed. These efforts 
have included: A pilot test in 12 post-acute care settings, including 
IRFs, to determine the feasibility of assessment items for use in 
calculation of the Drug Regimen Review Conducted with Follow-Up for 
Identified Issues measure, and further development of the risk-adjusted 
models for the Discharge to Community, Medicare Spending per 
Beneficiary, Potentially Preventable Readmissions, and Potentially 
Preventable Within Stay Readmissions Measure for Inpatient 
Rehabilitation Facilities measures. Additional information regarding 
testing is further described in the specific measure sections. 
Additional information regarding testing that was performed since the 
MAP Meeting, TEP meetings, and public comment periods is further 
described below in our responses to comments on individual proposed 
measures.
    For these reasons, we believe that the measures have been fully and 
robustly developed, and believe they are appropriate for implementation 
and should not be delayed.
    Comment: Several commenters, including MedPAC, expressed concern 
regarding the standardization and

[[Page 52083]]

interoperability of the proposed measures as they perceived the 
measures to have different inclusion/exclusion criteria, episode 
constructions and risk factors, and therefore do not meet the mandate 
of the IMPACT Act. The commenters expressed further concern about 
future implications of such variations and recommend delaying 
implementation until measures are standardized and interoperable across 
PAC settings. One commenter further indicated that the measure names 
were different for each setting, pointing out the words ``IRF QRP'' or 
``Inpatient Rehabilitation Facility'' were included in the measures' 
titles to designate a difference in the measure in each setting. One 
commenter stated implementing the quality measures in an unstandardized 
fashion would result in additional costs in the future for aligning 
measures between PAC providers.
    MedPAC suggested that the measures use uniform definitions, 
specifications, and risk-adjustment methods, conveying that findings 
from their work on a unified PAC payment system suggest overlap or 
similar care provided for Medicare beneficiaries with similar needs 
across PAC settings. As a result of this work, MedPAC recommended that 
the IMPACT Act measures be standardized to facilitate quality 
comparison across PAC settings to inform Medicare beneficiary choice 
and provide an opportunity for CMS to evaluate the value of PAC 
services, noting that differences in rates should reflect differences 
in quality of care rather than differences in the way rates are 
constructed.
    Response: We wish to clarify that the IMPACT Act requires that the 
patient assessment instruments be modified to enable the submission of 
standardized data, for purposes such as interoperability. However, 
measures themselves are not ``interoperable.''
    CMS, in collaboration with our measure contractors, developed the 
proposed measures with the intent to standardize the measure 
methodology so that we are able to detect variation among PAC providers 
in order to be able to assess differences in quality of care. For 
example, the proposed patient assessment-based quality measure, Drug 
Regimen Review Conducted with Follow-Up for Identified Issues-PAC IRF 
QRP, was developed across PAC settings with uniform definitions and 
specifications. This measure is not risk adjusted. The standardized 
development of this assessment-based measure follows the mandate of the 
IMPACT Act to develop standardized patient assessment-based measures 
for the four PAC settings (section 1899B(c)(1) of the Act). The 
resource use and other measures, Discharge to the Community-PAC IRF QRP 
and All-Condition Risk-Adjusted Potentially Preventable Hospital 
Readmissions Rates--PAC IRF QRP were developed to be uniform across the 
PAC settings in terms of their definitions, measure calculations, and 
risk-adjustment approach where applicable. However, there is variation 
in each measure primarily due to the data sources for each PAC setting. 
Further, the risk-adjustment approach for the resource use and other 
IMPACT Act measures is aligned, but is tailored to each measure based 
on measure testing results. Adjusting for relevant case-mix 
characteristics in each setting improves the validity and explanatory 
power of risk adjustment models, and helps ensure that any differences 
in measure performance reflect differences in the care provided rather 
than differences in patient case-mix. We employ this approach to 
measure development to enable appropriate cross-setting comparisons in 
PAC settings and to maximize measure reliability and validity. It 
should be noted that sections 1899B(c)(3)(B) and 1899B(d)(3)(B) of the 
Act require that quality measures and resource use and other measures 
be risk adjusted, as determined appropriate by the Secretary.
    Comment: Several commenters expressed concerns regarding the 
validity and reliability of IMPACT Act measures and encouraged CMS to 
conduct further analysis of data to ensure comparability across post-
acute care settings, prior to implementation and public reporting of 
data.
    Response: We have tested for validity and reliability all of the 
IMPACT Act measures, and the results of that testing is available at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.
    We intend to continue to monitor the reliability and validity of 
the IRF QRP measures, including whether the measures are reliable and 
valid for cross-setting purposes.
    Comment: A few commenters voiced concern regarding the burden of 
implementing the proposed measures in the IRF setting. One commenter 
requested that CMS proceed cautiously to ensure new measures are 
associated with minimal administrative and data collection burden. One 
commenter expressed concern that the new measures increase provider 
burden by increasing the time providers are ensuring data accuracy and 
move the focus away from patient-centered care towards a more metric-
based focus.
    Response: We appreciate the importance of avoiding undue burden on 
providers and will continue to evaluate and consider any unnecessary 
burden associated with the implementation of the IRF QRP. We wish to 
note that the three proposed resource measures are claims-based, and 
will require no additional data collection by providers and thus result 
in minimal increases in burden. The measure, Drug Regimen Review 
Conducted with Follow-Up for Identified Issues, is calculated using 
assessment data and requires the addition of three items to the IRF-
PAI, also requiring minimal additional burden. We address the issue of 
burden further under section XI.B. of this final rule.
    Comment: Several commenters recommended that CMS engage in several 
activities which would afford greater transparency with stakeholders 
regarding proposed measure development. These commenters also requested 
that measures undergo field testing with providers prior to 
implementation. Commenters also requested that more detailed measure 
specifications be posted in order to enable providers to evaluate 
measure design decisions. Commenters requested that IRF providers be 
provided with confidential preview reports as a part of a ``dry run'' 
process as this would enable providers to review data and provide CMS 
with feedback on potential technical issues with proposed measure. 
Finally, the commenters requested that measure data be provided to IRFs 
on a patient level on a quarterly basis, similar to other quality 
reporting programs, in order to make effective use of the data and 
improve performance.
    Response: With regard to the testing and analytic results provided 
for this measure, since the December 2015 MAP meeting, further 
refinement of measure specifications and testing of measure validity 
and reliability have been performed.
    We direct readers to the Measure Specifications for Measures 
Adopted in the FY 2017 IRF QRP final rule are available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html, which include detailed information 
regarding measure specifications, including results of the final risk 
adjustment models for the resource use measures. For resource use 
measures, our testing results are within range for similar outcome 
measures finalized in

[[Page 52084]]

public reporting and value-based purchasing programs, including the 
All-Cause Unplanned Readmission Measure for 30 Days Post Discharge from 
IRFs (NQF #2502), previously adopted into the IRF QRP.
    We appreciate the comment requesting that we provide performance 
data on IRF QRP measures on a more frequent, such as quarterly, basis 
in order to promote quality improvement. We wish to note that the 
proposed claims-based measures are based on 2 consecutive years of data 
in order to ensure a sufficient sample size to reliably assess IRFs' 
performance. However, we will investigate the feasibility and usability 
of providing IRFs with information more frequently, such as unadjusted 
counts of PPRs and discharge data. We also appreciate the commenters' 
suggestions related to the implementation of dry run activities, such 
as confidential reports, for the purposes of identifying any technical 
issues prior to public reporting, as was successfully provided in the 
fall of 2015 for the All Cause Unplanned Readmission Measure for 30 
Days Post Discharge from IRFs (NQF#2502). We wish to note that we 
intend to provide confidential feedback reports beginning in October, 
2017, as described in section VIII.O of this final rule, and we believe 
that the reports could serve as an opportunity for providers to extend 
to us any technical issues they may discover. We note that, as 
described in section VIII.P of this final rule, we are unable at this 
time to provide patient-level information for the claims-based measure, 
for example, the readmission measures, because such data comes from a 
separate entity. Finally, we wish to note that we intend to continue 
refining specifications, and we will consider pilot testing in addition 
to the performance testing that we currently conduct.

C. Policy for Retention of IRF QRP Measures Adopted for Previous 
Payment Determinations

    In the CY 2013 Hospital Outpatient Prospective Payment System/
Ambulatory Surgical Center (OPPS/ASC) Payment Systems and Quality 
Reporting Programs final rule (77 FR 68500 through 68507), we adopted a 
policy that allows any quality measure adopted for use in the IRF QRP 
to remain in effect until the measure was actively removed, suspended, 
or replaced, when we initially adopt a measure for the IRF QRP for a 
payment determination. For the purpose of streamlining the rulemaking 
process, when we initially adopt a measure for the IRF QRP for a 
payment determination, this measure will also be adopted for all 
subsequent years or until we remove, suspend, or replace the measure. 
For further information on how measures are considered for removal, 
suspension, or replacement, please refer to the CY 2013 OPPS/ASC final 
rule (77 FR 68500). We did not propose any changes to the policy for 
retaining IRF QRP measures adopted for previous payment determinations.

D. Policy for Adopting Changes to IRF QRP Measures

    In the CY 2013 OPPS/ASC final rule (77 FR 68500 through 68507), we 
adopted a subregulatory process to incorporate NQF updates to IRF 
quality measure specifications that do not substantively change the 
nature of the measure. Substantive changes will be proposed and 
finalized through rulemaking. For further information on what 
constitutes a substantive versus a nonsubstantive change and the 
subregulatory process for nonsubstantive changes, please refer to the 
CY 2013 OPPS/ASC final rule (77 FR 68500). We did not propose any 
changes to the policy for adopting changes to IRF QRP measures.

E. Quality Measures Previously Finalized for and Currently Used in the 
IRF QRP

    A history of the IRF QRP quality measures adopted for the FY 2014 
payment determinations and subsequent years is presented in Table 7. 
The year in which each quality measure was first adopted and 
implemented, and then subsequently re-proposed or revised, if 
applicable, is displayed. The initial and subsequent annual payment 
determination years are also shown in Table 7. For more information on 
a particular measure, please refer to the IRF PPS final rule and 
associated page numbers referenced in Table 7.
    Although we did not solicit feedback, we received a number of 
comments about previously finalized measures for and currently used in 
the IRF QRP. These comments are summarized and addressed below.
    Comment: One commenter was generally supportive of implementing 
additional quality measures in post-acute care, especially those that 
are cross-setting, but recommended that CMS take steps to validate data 
and assess provider experience during the first several months of 
reporting. One commenter supported the retention of the NHSN measures.
    With regard to the measure, Pressure Ulcers that are New or 
Worsened (Short-Stay) (NQF #0678), several commenters recommended that 
future updates to the measure include clinical guidance that is 
consistent with the most current evidence-based processes.
    We received several comments about the NHSN Facility-Wide Inpatient 
Hospital-Onset Clostridium difficile Infection (CDI) Outcome Measure 
(NQF #1717). Several commenters recommended that CMS revise the measure 
so that it is only reported at the first site of discovery, to avoid 
penalizing IRFs for the presence of the infection that started in a 
previous care setting.
    With regard to the measure, Application of Percent of Residents 
Experiencing One or More Falls with Major Injury (NQF #0674), one 
commenter had concerns that the nature of IRF treatment could lead to a 
frequency of falls higher than other settings. The commenter was 
concerned that including assisted falls in the definition of falls for 
this quality measure was inappropriate and confusing and recommended 
that CMS revisit the definition and include only falls with major 
injury.
    Response: With regard to the measure Pressure Ulcers that are New 
or Worsened (Short-Stay) (NQF #0678), we intend to continue our ongoing 
measure development and refinement activities to inform the ongoing 
evaluation of this measure, to ensure that the measure remains valid 
and reliable to inform quality improvement within and across each PAC 
setting, and to fulfill the public reporting goals of quality reporting 
programs, including the IRF QRP. Reviewing the most current evidence-
based clinical guidance is part of that process. With regard to the 
comments about the NHSN Facility-Wide Inpatient Hospital-Onset CDI 
Outcome Measure (NQF #1717), the scope of NQF#1717 extends to acute 
care hospitals, long-term care hospitals, inpatient rehabilitation 
facilities, and cancer hospitals. The same measure specifications are 
used by all these facility types to report Clostridium difficile 
Laboratory Identified events to NHSN, and these measure specifications 
differentiate between community-onset events, which include events that 
had their onset at another healthcare facility, from healthcare-
associated events, which are attributed to the facility reporting the 
event. CDC reports only incident healthcare-associated events on behalf 
of healthcare facilities to CMS. To limit Clostridium difficile 
Laboratory Identified event reporting to the first site of discovery 
offers opportunity for missed ``true'' healthcare-associated events 
(those recognized on or after hospital day 4) and would require

[[Page 52085]]

additional data collection and investigation burden to users.
    The measure specifications for NQF#1717, by design, align with the 
NHSN LabID Event protocol, which was developed to require minimal 
investigation on the part of facilities and to provide a proxy measure 
of infection. Dates of admission and specimen collection are required 
and can easily be collected via electronic methods and identified as 
healthcare-associated (HO) or community-onset (CO). To require a 
facility to determine if a CDI LabID Event had been identified in 
another facility would call for manual review of medical records and 
potential communication with transferring facilities. In accordance 
with protocol guidelines, IRF-based events are categorized as 
``incident'' (first non-duplicate event for the IRF) in addition to a 
CO/HO categorization. IRF facilities are analyzed independently of any 
other reporting facility, that is, are viewed as separate reporting 
facilities.
    With regard to the measure, An Application of Percent of Residents 
Experiencing One or More Falls with Major Injury (Long Stay) (NQF 
#0674), we would like to clarify that the quality measure adopted for 
the IRF QRP includes only falls with a major injury, satisfying the 
IMPACT Act domain, Incidence of Major Falls. Thus, falls with no 
injury, such as those that may be considered near-falls, are not 
included in the measure.
    Additionally, we received a number of comments specifically 
regarding quality measures that were finalized into the IRF QRP in the 
FY 2016 IRF PPS final rule.
    Comment: Many commenters indicated they had concerns about the use 
of CARE items or the use of the CARE Tool. Several commenters were 
concerned that the CARE items added to the IRF-PAI would be duplicative 
and confusing to clinicians because they are similar to the FIM[supreg] 
items. One commenter suggested the FIM[supreg] items be removed from 
the IRF-PAI. Other commenters supported continued use of the 
FIM[supreg] instrument, and recommended a delay in implementing the 
CARE items. The commenters also had concerns about the precision of the 
CARE items and the patient types with which it was tested, the 
timeframe and six-point scale, as well as NQF-endorsement of CARE items 
in all settings. Commenters noted that the FIM[supreg] instrument has 
demonstrated increased efficiency and decreased length of stay, and 
allows for comparison of functional gains across patients with similar 
debility levels. Commenters had concerns about lack of credentialing of 
staff for CARE items, as this is currently required for the FIM[supreg] 
instrument to ensure consistent scoring.
    Several commenters were concerned about the training, data 
submission specifications, and support CMS has provided for items being 
required on the IRF-PAI Version 1.4, effective October 1, 2016. Several 
commenters were concerned that the data were collected for research 
purposes. One commenter indicated there was a discrepancy between the 
IRF-PAI Training Manual and the data submission specifications. Many 
commenters had concerns about the need for further clarification about 
the patient's usual status, and another commenter requested 
clarification about the use of a dash to indicate that an item was not 
assessed.
    Response: As we did not propose any changes to the quality measures 
finalized in the FY 2016 IRF PPS final rule, these comments are outside 
the scope of the proposed rule. However, we would like to clarify that 
we are not implementing the CARE Tool for the IRF QRP to meet the 
mandate of the IMPACT Act. To meet the mandate, and to standardize 
quality measures and data items, we retained the use of the IRF-PAI as 
the collection instrument for all IRF settings. We incorporated items 
from the CARE Tool into new section GG: Functional Abilities and Goals 
of the IRF-PAI Version 1.4 in order to calculate the 5 function quality 
measures that were adopted into the IRF QRP in the IRF PPS FY 2016 
Final Rule (80 FR 47100 through 47120). The items were not added to the 
IRF-PAI for research purposes.
    We refer the readers to the FY 2016 final rule (80 FR 47100 through 
47120) for discussion about the testing, including the rating scale, 
reliability, validity and sensitivity of the function items that were 
added to the IRF-PAI, as well as plans for ongoing evaluation of these 
items, and concerns related to FIM[supreg] item duplication. With 
regard to training and provider support, we agree with the importance 
of thorough and comprehensive training. Information about and materials 
from each IRF QRP training are posted on the IRF-QRP Training Web site 
at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/Training.html. With regard to the 
comments related to the data specifications, we post data 
specifications and errata on the CMS Web site as soon as we are able so 
that vendors and providers are able to review and understand the valid 
data codes for all items and the associated requirements: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/Software.html.

   Table 7--Quality Measures Previously Finalized for and Currently Used in the IRF Quality Reporting Program
----------------------------------------------------------------------------------------------------------------
                                                    Data collection start  Annual payment determination: Initial
         Measure title              Final rule              date                  and subsequent APU years
----------------------------------------------------------------------------------------------------------------
National Healthcare Safety      Adopted an         October 1, 2012.......  FY 2014 and subsequent years.
 Network (NHSN) Catheter-        application of
 Associated Urinary Tract        the measure in
 Infection (CAUTI) Outcome       FY 2012 IRF PPS
 Measure (NQF #0138).            Final Rule (76
                                 FR 47874 through
                                 47886).
                                Adopted the NQF-   January 1, 2013.......  FY 2015 and subsequent years.
                                 endorsed version
                                 and expanded
                                 measure (with
                                 standardized
                                 infection ratio)
                                 in CY 2013 OPPS/
                                 ASC Final Rule
                                 (77 FR 68504
                                 through 68505).
Percent of Residents or         Adopted            October 1, 2012.......  FY 2014 and subsequent years.
 Patients with Pressure Ulcers   application of
 That Are New or Worsened        measure in FY
 (Short Stay) (NQF #0678).       2012 IRF PPS
                                 final rule (76
                                 FR 47876 through
                                 47878).
                                Adopted a non-     January 1, 2013.......  FY 2015 and subsequent years.
                                 risk-adjusted
                                 application of
                                 the NQF-endorsed
                                 version in CY
                                 2013 OPPS/ASC
                                 Final Rule (77
                                 FR 68500 through
                                 68507).

[[Page 52086]]

 
                                Adopted the risk   October 1, 2014.......  FY 2017 and subsequent years.
                                 adjusted, NQF-
                                 endorsed version
                                 in FY 2014 IRF
                                 PPS Final Rule
                                 (78 FR 47911
                                 through 47912).
                                Adopted in the FY  October 1, 2015.......  FY 2018 and subsequent years.
                                 2016 IRF PPS
                                 final rule (80
                                 FR 47089 through
                                 47096) to
                                 fulfill IMPACT
                                 Act requirements.
Percent of Residents or         Adopted in FY      October 1, 2014.......  FY 2017 and subsequent years.
 Patients Who Were Assessed      2014 IRF PPS
 and Appropriately Given the     final rule (78
 Seasonal Influenza Vaccine      FR 47906 through
 (Short Stay) (NQF #0680).       47911).
Influenza Vaccination Coverage  Adopted in FY      October 1, 2014.......  FY 2016 and subsequent years.
 among Healthcare Personnel      2014 IRF PPS
 (NQF #0431).                    final rule (78
                                 FR 47905 through
                                 47906).
All-Cause Unplanned             Adopted in FY      N/A...................  FY 2017 and subsequent years.
 Readmission Measure for 30      2014 IRF PPS
 Days Post Discharge from        final rule (78
 Inpatient Rehabilitation        FR 47906 through
 Facilities (NQF #2502).         47910).
                                Adopted the NQF-   N/A...................  FY 2018 and subsequent years.
                                 endorsed version
                                 in FY 2016 IRF
                                 PPS final rule
                                 (80 FR 47087
                                 through 47089).
National Healthcare Safety      Adopted in the FY  January 1, 2015.......  FY 2017 and subsequent years.
 Network (NHSN) Facility-Wide    2015 IRF PPS
 Inpatient Hospital-Onset        final rule (79
 Methicillin-Resistant           FR 45911 through
 Staphylococcus aureus (MRSA)    45913).
 Bacteremia Outcome Measure
 (NQF #1716).
National Healthcare Safety      Adopted in the FY  January 1, 2015.......  FY 2017 and subsequent years.
 Network (NHSN) Facility-Wide    2015 IRF PPS
 Inpatient Hospital-Onset        final rule (79
 Clostridium difficile           FR 45913 through
 Infection (CDI) Outcome         45914).
 Measure (NQF #1717).
Application of Percent of       Adopted an         October 1, 2016.......  FY 2018 and subsequent years.
 Residents Experiencing One or   application of
 More Falls with Major Injury    the measure in
 (Long Stay) (NQF #0674).        FY 2016 IRF PPS
                                 Final Rule (80
                                 FR 47096 through
                                 47100).
Application of Percent of Long- Adopted an         October 1, 2016.......  FY 2018 and subsequent years.
 Term Care Hospital Patients     application of
 with an Admission and           the measure in
 Discharge Functional            the FY 2016 IRF
 Assessment and a Care Plan      PPS final rule
 That Addresses Function (NQF    (80 FR 47100
 #2631).                         through 47111).
IRF Functional Outcome          Adopted in the FY  October 1, 2016.......  FY 2018 and subsequent years.
 Measure: Change in Self-Care    2016 IRF PPS
 for Medical Rehabilitation      final rule (80
 Patients (NQF #2633).*          FR 47111 through
                                 47117).
IRF Functional outcome          Adopted in the FY  October 1, 2016.......  FY 2018 and subsequent years.
 Measure: Change in Mobility     2016 IRF PPS
 Score for Medical               final rule (80
 Rehabilitation (NQF #2634).*    FR 47117 through
                                 47118).
IRF Functional Outcome          Adopted in the FY  October 1, 2016.......  FY 2018 and subsequent years.
 Measure: Discharge Self-Care    2016 IRF PPS
 Score for Medical               final rule (80
 Rehabilitation Patients (NQF    FR 47118 through
 #2635).                         47119).
IRF Functional Outcome          Adopted in the FY  October 1, 2016.......  FY 2018 and subsequent years.
 Measure: Discharge Mobility     2016 IRF PPS
 Score for Medical               final rule (80
 Rehabilitation Patients (NQF    FR 47119 through
 #2636).                         47120).
----------------------------------------------------------------------------------------------------------------
* These measures were under review at NQF when they were finalized for use in the IRF QRP. These measures are
  now NQF-endorsed.

F. IRF QRP Quality, Resource Use and Other Measures Finalized for the 
FY 2018 Payment Determination and Subsequent Years

    For the FY 2018 payment determinations and subsequent years, in 
addition to the quality measures we are retaining under our policy 
described in section VIII.C. of this final rule, we proposed four new 
measures. Three of these measures were developed to meet the 
requirements of IMPACT Act. They are:
    (1) MSPB-PAC IRF QRP,
    (2) Discharge to Community-PAC IRF QRP, and
    (3) Potentially Preventable 30-Day Post-Discharge Readmission 
Measure for IRF QRP.
    The fourth measure is: (4) Potentially Preventable Within Stay 
Readmission Measure for IRFs. The measures are described in more detail 
below.
    For the risk-adjustment of the resource use and other measures, we 
understand the important role that sociodemographic status plays in the 
care of patients. However, we continue to have concerns about holding 
providers to different standards for the outcomes of their patients of 
diverse sociodemographic status because we do not want to mask 
potential disparities or minimize incentives to improve the outcomes of 
disadvantaged populations. We routinely monitor the impact of 
sociodemographic status on providers' results for our measures.
    The NQF is currently undertaking a two-year trial period in which 
new measures and measures undergoing maintenance review will be 
assessed to determine if risk-adjusting for sociodemographic factors is 
appropriate. For 2 years, NQF will conduct a trial of temporarily 
allowing inclusion of sociodemographic factors in the risk-adjustment 
approach for some

[[Page 52087]]

performance measures. At the conclusion of the trial, NQF will issue 
recommendations on future permanent inclusion of sociodemographic 
factors. During the trial, measure developers are expected to submit 
information such as analyses and interpretations as well as performance 
scores with and without sociodemographic factors in the risk adjustment 
model.
    Furthermore, the Office of the Assistant Secretary for Planning and 
Evaluation (ASPE) is conducting research to examine the impact of 
sociodemographic status on quality measures, resource use, and other 
measures under the Medicare program as directed by the IMPACT Act. We 
will closely examine the findings of the ASPE reports and related 
Secretarial recommendations and consider how they apply to our quality 
programs at such time as they are available.
    We received several comments on the impact of sociodemographic 
status on quality measures, resource use, and other measures, which are 
summarized with our responses below.
    Comment: Several commenters indicated their support for the 
inclusion of sociodemographic status adjustment in quality measures, 
resource use, and other measures. Commenters suggested that failure to 
account for patient characteristics could penalize IRFs for providing 
care to a more medically-complex and socioeconomically disadvantaged 
patient population and affect provider performance. Some commenters 
expressed concerns about standardization and interoperability of the 
measures as it pertain to risk-adjusting, particularly for SDS 
characteristics. Many commenters recommended incorporating 
socioeconomic factors as risk-adjustors for the measures, and several 
commenters suggested conducting additional testing and NQF-endorsement 
prior to implementation of these measures. In addition, many commenters 
recommended including functionality as an additional risk-adjustment 
factor, and several commenters suggested risk-adjustment for cognitive 
impairment.
    A few commenters, including MedPAC, did not support risk-adjustment 
of measures by socioeconomic status (SES) or SDS status. One commenter 
did not support risk-adjustment, stating that it can hide disparities 
and create different standards of care for IRFs based on the 
demographics in the facility. MedPAC reiterated that risk adjustment 
can hide disparities in care and suggested that risk-adjustment reduces 
pressure on providers to improve quality of care for low-income 
Medicare beneficiaries. Instead, MedPAC supported peer provider group 
comparisons with providers of similar low-income beneficiary 
populations. Another commenter stated that SDS factors should not be 
included in measures that examine the patient during an IRF stay, but 
should only be considered for measures evaluating care after the IRF 
discharge.
    Response: We appreciate the considerations and suggestions conveyed 
in relation to the measures and the importance in balancing appropriate 
risk adjustment along with ensuring access to high-quality care. We 
note that in the measures that are risk adjusted, we do take into 
account characteristics associated with medical complexity, as well as 
factors such as age where appropriate to do so. For those cross-setting 
post-acute measures, such as those intended to satisfy the IMPACT Act 
domains that use the patient assessment-based data elements for risk 
adjustment, we have either made such items standardized, or intend to 
do so as feasible. With regard to the incorporation of additional 
factors, such as function, we have and will continue to take such 
factors into account, which would include further testing as part of 
our ongoing measure development monitoring activities. As discussed 
previously, we intend to seek NQF endorsement for our measures.
    We also received suggestions pertaining to the incorporation of 
socioeconomic factors as risk-adjustors for the measures, including in 
those measures that pertain to after the patient was discharged from 
the IRF, additional testing and/or NQF endorsement prior to 
implementation of these measures, and comments that pertain to 
potential consequences associated with such risk adjustors and 
alternative approaches to grouping comparative data. We wish to 
reiterate that as previously discussed, NQF is currently undertaking a 
2-year trial period in which new measures and measures undergoing 
maintenance review will be assessed to determine if risk-adjusting for 
sociodemographic factors is appropriate. This trial entails temporarily 
allowing inclusion of sociodemographic factors in the risk-adjustment 
approach for some performance measures. At the conclusion of the trial, 
NQF will issue recommendations on future permanent inclusion of 
sociodemographic factors. During the trial, measure developers are 
encouraged to submit information such as analyses and interpretations 
as well as performance scores with and without sociodemographic factors 
in the risk adjustment model. Several measures developed by CMS have 
been brought to NQF since the beginning of the trial. CMS, in 
compliance with NQF's guidance, has tested sociodemographic factors in 
the measures' risk models and made recommendations about whether or not 
to include these factors in the endorsed measure. We intend to continue 
engaging in the NQF process as we consider the appropriateness of 
adjusting for sociodemographic factors in our outcome measures.
    Furthermore, the Office of the ASPE is conducting research to 
examine the impact of sociodemographic status on quality measures, 
resource use, and other measures under the Medicare program as directed 
by the IMPACT Act. We will closely examine the findings of the ASPE 
reports and related Secretarial recommendations and consider how they 
apply to our quality programs at such time as they are available.
1. Measure to Address the IMPACT Act Domain of Resource Use and Other 
Measures: Total Estimated MSPB-PAC IRF QRP
    We proposed an MSPB-PAC IRF QRP measure for inclusion in the IRF 
QRP for the FY 2018 payment determination and subsequent years. Section 
1899B(d)(1)(A) of the Act requires the Secretary to specify resource 
use measures, including total estimated MSPB, on which PAC providers 
consisting of Skilled Nursing Facilities (SNFs), IRFs, Long-Term Care 
Hospitals (LTCHs), and Home Health Agencies (HHAs) are required to 
submit necessary data specified by the Secretary.
    Rising Medicare expenditures for post-acute care as well as wide 
variation in spending for these services underlines the importance of 
measuring resource use for providers rendering these services. Between 
2001 and 2013, Medicare PAC spending grew at an annual rate of 6.1 
percent and doubled to $59.4 billion, while payments to inpatient 
hospitals grew at an annual rate of 1.7 percent over this same 
period.\3\ A study commissioned by the Institute of Medicine discovered 
that variation in PAC spending explains 73 percent of variation in 
total Medicare spending across the United States.\4\
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    \3\ MedPAC, ``A Data Book: Health Care Spending and the Medicare 
Program,'' (2015). 114.
    \4\ Institute of Medicine, ``Variation in Health Care Spending: 
Target Decision Making, Not Geography,'' (Washington, DC: National 
Academies 2013). 2.
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    We reviewed the NQF's consensus-endorsed measures and were unable 
to identify any NQF-endorsed resource use measures for PAC settings. As 
such, we proposed this MSPB-PAC IRF QRP measure under the Secretary's 
authority

[[Page 52088]]

to specify non-NQF-endorsed measures under section 1899B(e)(2)(B) of 
the Act. Given the current lack of resource use measures for PAC 
settings, our MSPB-PAC IRF QRP measure will provide valuable 
information to IRF providers on their relative Medicare spending in 
delivering services to approximately 338,000 Medicare beneficiaries.\5\
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    \5\ Figures for 2013. MedPAC, ``Medicare Payment Policy,'' 
Report to the Congress (2015). xvii-xviii.
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    The MSPB-PAC IRF QRP episode-based measure will provide actionable 
and transparent information to support IRF providers' efforts to 
promote care coordination and deliver high quality care at a lower cost 
to Medicare. The MSPB-PAC IRF QRP measure holds IRF providers 
accountable for the Medicare payments within an ``episode of care'' 
(episode), which includes the period during which a patient is directly 
under the IRF's care, as well as a defined period after the end of the 
IRF treatment, which may be reflective of and influenced by the 
services furnished by the IRF. MSPB-PAC IRF QRP episodes, constructed 
according to the methodology described below, have high levels of 
Medicare spending with substantial variation. In FY 2013 and FY 2014, 
Medicare FFS beneficiaries experienced 613,089 MSPB-PAC IRF QRP 
episodes triggered by admission to an IRF. The mean payment-
standardized, risk-adjusted episode spending for these episodes is 
$30,370. There is substantial variation in the Medicare payments for 
these MSPB-PAC IRF QRP episodes--ranging from approximately $15,059 at 
the 5th percentile to approximately $55,912 at the 95th percentile. 
This variation is partially driven by variation in payments occurring 
following IRF treatment.
    Evaluating Medicare payments during an episode creates a continuum 
of accountability between providers that should improve post-treatment 
care planning and coordination. While some stakeholders throughout the 
measure development process supported the MSPB-PAC measures and 
believed that measuring Medicare spending was critical for improving 
efficiency, others believed that resource use measures did not reflect 
quality of care in that they do not take into account patient outcomes 
or experience beyond those observable in claims data. However, IRFs 
involved in the provision of high quality PAC care as well as 
appropriate discharge planning and post-discharge care coordination 
would be expected to perform well on this measure since beneficiaries 
would likely experience fewer costly adverse events (for example, 
avoidable hospitalizations, infections, and emergency room usage). 
Further, it is important that the cost of care be explicitly measured 
so that, in conjunction with other quality measures, we can publicly 
report which IRFs provide high quality care at lower cost.
    We developed an MSPB-PAC measure for each of the four PAC settings. 
We proposed an LTCH-specific MSPB-PAC measure in the FY 2017 IPPS/LTCH 
proposed rule (81 FR 25216 through 25220), an IRF-specific MSBP-PAC 
measure in the FY 2017 IRF PPS proposed rule (81 FR 24197 through 
24201), a SNF-specific MSPB-PAC measure in the FY 2017 SNF proposed 
rule (81 FR 24258 through 24262), and a HHA-specific MSBP-PAC measure 
in the CY 2017 HH proposed rule (81 FR 43760 through 43764). The four 
setting-specific MSPB-PAC measures are closely aligned in terms of 
episode construction and measure calculation. Each of the MSPB-PAC 
measures assess Medicare Part A and Part B spending during an episode, 
and the numerator and denominator are defined similarly for each of the 
MSPB-PAC measures. However, setting-specific measures allow us to 
account for differences between settings in payment policy, the types 
of data available, and the underlying health characteristics of 
beneficiaries. For example, we use the IRF setting-specific 
rehabilitation impairment categories (RICs) in the MSPB-PAC IRF QRP 
risk adjustment model, as detailed below.
    The MSPB-PAC measures mirror the general construction of the 
inpatient prospective payment system (IPPS) hospital MSPB measure, 
which was adopted for the Hospital IQR Program beginning with the FY 
2014 program, and was implemented in the Hospital VBP Program beginning 
with the FY 2015 program. The measure was endorsed by the NQF on 
December 6, 2013 (NQF #2158).\6\ The hospital MSPB measure evaluates 
hospitals' Medicare spending relative to the Medicare spending for the 
national median hospital during a hospital MSPB episode. It assesses 
Medicare Part A and Part B payments for services performed by hospitals 
and other healthcare providers during a hospital MSPB episode, which is 
comprised of the periods immediately prior to, during, and following a 
patient's hospital stay.7 8 Similarly, the MSPB-PAC measures 
assess all Medicare Part A and Part B payments for FFS claims with a 
start date during the episode window (which, as discussed in this 
section, is the time period during which Medicare FFS Part A and Part B 
services are counted towards the MSPB-PAC IRF QRP episode). There are 
differences between the MSPB-PAC measures and the hospital MSPB measure 
to reflect differences in payment policies and the nature of care 
provided in each PAC setting. For example, the MSPB-PAC measures 
exclude a limited set of services (for example, clinically unrelated 
services) provided to a beneficiary during the episode window, while 
the hospital MSPB measure does not exclude any services.\9\
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    \6\ QualityNet, ``Measure Methodology Reports: Medicare Spending 
per Beneficiary (MSPB) Measure,'' (2015). http://www.qualitynet.org/dcs/ContentServer?pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228772053996.
    \7\ QualityNet, ``Measure Methodology Reports: Medicare Spending 
per Beneficiary (MSPB) Measure,'' (2015). http://www.qualitynet.org/dcs/ContentServer?pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228772053996.
    \8\ FY 2012 IPPS/LTCH PPS final rule (76 FR 51619).
    \9\ National Quality Forum, Applications Partnership, ``Process 
and Approach for MAP Pre-Rulemaking Deliberations, 2015-2016'' 
(February 2016) http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&Ote,OD=81693.
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    MSPB-PAC episodes may begin within 30 days of discharge from an 
inpatient hospital as part of a patient's trajectory from an acute to a 
PAC setting. An IRF stay beginning within 30 days of discharge from an 
inpatient hospital would therefore be included once in the hospital's 
MSPB measure, and once in the IRF provider's MSPB-PAC measure. Aligning 
the hospital MSPB and MSPB-PAC measures in this way creates continuous 
accountability and aligns incentives to improve care planning and 
coordination across inpatient and PAC settings.
    We sought and considered the input of stakeholders throughout the 
measure development process for the MSPB-PAC measures. We convened a 
TEP consisting of 12 panelists with combined expertise in all of the 
PAC settings on October 29 and 30, 2015 in Baltimore, Maryland. A 
follow-up email survey was sent to TEP members on November 18, 2015 to 
which seven responses were received by December 8, 2015. The MSPB-PAC 
TEP Summary Report is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/Technical-Expert-Panel-on-Medicare-Spending-Per-Beneficiary.pdf. The measures were also presented to the 
MAP Post-Acute Care/Long-Term Care (PAC/LTC) Workgroup on December 15, 
2015. As the MSPB-PAC measures were under

[[Page 52089]]

development, there were three voting options for members: Encourage 
continued development, do not encourage further consideration, and 
insufficient information.\10\ The MAP PAC/LTC workgroup voted to 
``encourage continued development'' for each of the MSPB-PAC 
measures.\11\ The MAP PAC/LTC workgroup's vote of ``encourage continued 
development'' was affirmed by the MAP Coordinating Committee on January 
26, 2016.\12\ The MAP's concerns about the MSPB-PAC measures, as 
outlined in their final report ``MAP 2016 Considerations for 
Implementing Measures in Federal Programs: Post-Acute Care and Long-
Term Care'' and Spreadsheet of Final Recommendations, were taken into 
consideration during the measure development process and are discussed 
as part of our responses to public comments, described 
below.13 14
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    \10\ National Quality Forum, Measure Applications Partnership, 
``Process and Approach for MAP Pre-Rulemaking Deliberations, 2015-
2016'' (February 2016) http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=81693.
    \11\ National Quality Forum, Measure Applications Partnership 
Post-Acute Care/Long-Term Care Workgroup, ``Meeting Transcript--Day 
2 of 2'' (December 15, 2015) 104-106. http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=81470.
    \12\ National Quality Forum, Measure Applications Partnership, 
``Meeting Transcript--Day 1 of 2'' (January 26, 2016) 231-232 http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=81637.
    \13\ National Quality Forum, Measure Applications Partnership, 
``MAP 2016. Considerations for Implementing Measures in Federal 
Programs: Post-Acute Care and Long-Term Care'' Final Report, 
(February 2016) http://www.qualityforum.org/Publications/2016/02/MAP_2016_Considerations_for_Implementing_Measures_in_Federal_Programs_-_PAC-LTC.aspx.
    \14\ National Quality Forum, Measure Applications Partnership, 
``Spreadsheet of MAP 2016 Final Recommendations'' (February 1, 2016) 
http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=81593.
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    Since the MAP's review and recommendation of continued development, 
CMS continued to refine risk adjustment models and conduct measure 
testing for the IMPACT Act measures in compliance with the MAP's 
recommendations. The IMPACT Act measures are consistent with the 
information submitted to the MAP and support the scientific 
acceptability of these measures for use in quality reporting programs.
    In addition, a public comment period, accompanied by draft measures 
specifications, was open from January 13 to 27, 2016 and extended to 
February 5. A total of 45 comments on the MSPB-PAC measures were 
received during this 3.5 week period. The comments received also 
covered each of the MAP's concerns as outlined in their Final 
Recommendations.\15\ The MSPB-PAC Public Comment Summary Report is 
available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/2016_03_24_mspb_pac_public_comment_summary_report.pdf and the MSPB-PAC 
Public Comment Supplementary Materials are available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/2016_03_24_mspb_pac_public_comment_summary_report_supplementary_materials.pdf: These documents contain the public comments, along with our 
responses including statistical analyses. The MSPB-PAC IRF QRP measure, 
along with the other MSPB-PAC measures, as applicable, will be 
submitted for NQF endorsement when feasible.
---------------------------------------------------------------------------

    \15\ National Quality Forum, Measure Applications Partnership, 
``Spreadsheet of MAP 2016 Final Recommendations'' (February 1, 2016) 
http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=81593.
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    To calculate the MSPB-PAC IRF QRP measure for each IRF provider, we 
first defined the construction of the MSPB-PAC IRF QRP episode, 
including the length of the episode window as well as the services 
included in the episode. Next, we apply the methodology for the measure 
calculation. The specifications are discussed further in this section. 
More detailed specifications for the MSPB-PAC measures, including the 
MSPB-PAC IRF QRP measure, are available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.
a. Episode Construction
    An MSPB-PAC IRF QRP episode begins at the episode trigger, which is 
defined as the patient's admission to an IRF. The admitting facility is 
the attributed provider, for whom the MSPB-PAC IRF QRP measure is 
calculated. The episode window is the time period during which Medicare 
FFS Part A and Part B services are counted towards the MSPB-PAC IRF QRP 
episode. Because Medicare FFS claims are already reported to the 
Medicare program for payment purposes, IRF providers would not be 
required to report any additional data to CMS for calculation of this 
measure. Thus, there would be no additional data collection burden from 
the implementation of this measure.
    The episode window is comprised of a treatment period and an 
associated services period. The treatment period begins at the trigger 
(that is, on the day of admission to the IRF) and ends on the day of 
discharge from that IRF. Readmissions to the same facility occurring 
within 7 or fewer days do not trigger a new episode, and instead are 
included in the treatment period of the original episode. When two 
sequential stays at the same IRF occur within 7 or fewer days of one 
another, the treatment period ends on the day of discharge for the 
latest IRF stay. The treatment period includes those services that are 
provided directly or reasonably managed by the IRF provider that are 
directly related to the beneficiary's care plan. The associated 
services period is the time during which Medicare Part A and Part B 
services (with certain exclusions) are counted towards the episode. The 
associated services period begins at the episode trigger and ends 30 
days after the end of the treatment period. The distinction between the 
treatment period and the associated services period is important 
because clinical exclusions of services may differ for each period. 
Certain services are excluded from the MSPB-PAC IRF QRP episodes 
because they are clinically unrelated to IRF care, and/or because IRF 
providers may have limited influence over certain Medicare services 
delivered by other providers during the episode window. These limited 
service-level exclusions are not counted towards a given IRF provider's 
Medicare spending to ensure that beneficiaries with certain conditions 
and complex care needs receive the necessary care. Certain services 
that are determined to be outside of the control of an IRF provider 
include planned hospital admissions, management of certain preexisting 
chronic conditions (for example, dialysis for end-stage renal disease 
(ESRD), and enzyme treatments for genetic conditions), treatment for 
preexisting cancers, organ transplants, and preventive screenings (for 
example, colonoscopy and mammograms). Exclusion of such services from 
the MSPB-PAC IRF QRP episode ensures that facilities do not have 
disincentives to treat patients with certain conditions or complex care 
needs.
    An MSPB-PAC episode may begin during the associated services period 
of an MSPB-PAC IRF QRP episode in the 30 days post-treatment. One 
possible scenario occurs where an IRF provider discharges a beneficiary 
who is then admitted to an LTCH within 30 days. The LTCH claim will be 
included once as an associated service for the attributed provider of 
the first MSPB-PAC IRF QRP episode and once as a treatment service for 
the attributed

[[Page 52090]]

provider of the second MSPB-PAC LTCH QRP episode. As in the case of 
overlap between hospital and PAC episodes discussed earlier, this 
overlap is necessary to ensure continuous accountability between 
providers throughout a beneficiary's trajectory of care, as both 
providers share incentives to deliver high quality care at a lower cost 
to Medicare. Even within the IRF setting, one MSPB-PAC IRF QRP episode 
may begin in the associated services period of another MSPB-PAC IRF QRP 
episode in the 30 days post-treatment. The second IRF claim would be 
included once as an associated service for the attributed IRF provider 
of the first MSPB-PAC IRF QRP episode and once as a treatment service 
for the attributed IRF provider of the second MSPB-PAC IRF QRP episode. 
Again, this ensures that IRF providers have the same incentives 
throughout both MSPB-PAC IRF QRP episodes to deliver quality care and 
engage in patient-focused care planning and coordination. If the second 
MSPB-PAC IRF QRP episode were excluded from the second IRF provider's 
MSPB-PAC IRF QRP measure, that provider would not share the same 
incentives as the first IRF provider of the first MSPB-PAC IRF QRP 
episode. The MSPB-PAC IRF QRP measure was designed to benchmark the 
resource use of each attributed provider against what their spending is 
expected to be as predicted through risk adjustment. As discussed 
further in this section, the measure takes the ratio of observed 
spending to expected spending for each episode and then takes the 
average of those ratios across all of the attributed provider's 
episodes. The measure is not a simple sum of all costs across a 
provider's episodes, thus mitigating concerns about double counting.
b. Measure Calculation
    Medicare payments for Part A and Part B claims for services 
included in MSPB-PAC IRF QRP episodes, defined according to the 
methodology previously discussed, are used to calculate the MSPB-PAC 
IRF QRP measure. Measure calculation involves determination of the 
episode exclusions, the approach for standardizing payments for 
geographic payment differences, the methodology for risk adjustment of 
episode spending to account for differences in patient case mix, and 
the specifications for the measure numerator and denominator.
(1) Exclusion Criteria
    In addition to service-level exclusions that remove some payments 
from individual episodes, we exclude certain episodes in their entirety 
from the MSPB-PAC IRF QRP measure to ensure that the MSPB-PAC IRF QRP 
measure accurately reflects resource use and facilitates fair and 
meaningful comparisons between IRF providers. The episode-level 
exclusions are as follows:
     Any episode that is triggered by an IRF claim outside the 
50 states, DC, Puerto Rico, and U.S. Territories.
     Any episode where the claim(s) constituting the attributed 
IRF provider's treatment have a standard allowed amount of zero or 
where the standard allowed amount cannot be calculated.
     Any episode in which a beneficiary is not enrolled in 
Medicare FFS for the entirety of a 90-day lookback period (that is, a 
90-day period prior to the episode trigger) plus episode window 
(including where a beneficiary dies), or is enrolled in Part C for any 
part of the lookback period plus episode window.
     Any episode in which a beneficiary has a primary payer 
other than Medicare for any part of the 90-day lookback period plus 
episode window.
     Any episode where the claim(s) constituting the attributed 
IRF provider's treatment include at least one related condition code 
indicating that it is not a prospective payment system bill.
(2) Standardization and Risk Adjustment
    Section 1899B(d)(2)(C) of the Act requires that the MSPB-PAC 
measures are adjusted for the factors described under section 
1886(o)(2)(B)(ii) of the Act, which include adjustment for factors such 
as age, sex, race, severity of illness, and other factors that the 
Secretary determines appropriate. Medicare payments included in the 
MSPB-PAC IRF QRP measure are payment-standardized and risk-adjusted. 
Payment standardization removes sources of payment variation not 
directly related to clinical decisions and facilitates comparisons of 
resource use across geographic areas. We proposed to use the same 
payment standardization methodology that was used in the NQF-endorsed 
hospital MSPB measure. This methodology removes geographic payment 
differences, such as wage index and geographic practice cost index 
(GPCI), incentive payment adjustments, and other add-on payments that 
support broader Medicare program goals including indirect graduate 
medical education (IME) and hospitals serving a disproportionate share 
of uninsured patients (DSH).\16\
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    \16\ QualityNet, ``CMS Price (Payment) Standardization--Detailed 
Methods'' (Revised May 2015) https://qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier4&cid=1228772057350.
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    Risk adjustment uses patient claims history to account for case-mix 
variation and other factors that affect resource use but are beyond the 
influence of the attributed IRF provider. To assist with risk 
adjustment, we created mutually exclusive and exhaustive clinical case 
mix categories using the most recent institutional claim in the 60 days 
prior to the start of the MSPB-PAC IRF QRP episode. The beneficiaries 
in these clinical case mix categories have a greater degree of clinical 
similarity than the overall IRF patient population, and allow us to 
more accurately estimate Medicare spending. Our MSPB-PAC IRF QRP 
measure, adapted for the IRF setting from the NQF-endorsed hospital 
MSPB measure, uses a regression framework with a 90-day hierarchical 
condition category (HCC) lookback period and covariates including the 
clinical case mix categories, HCC indicators, age brackets, indicators 
for originally disabled, ESRD enrollment, and long-term care status, 
and selected interactions of these covariates where sample size and 
predictive ability make them appropriate. We sought and considered 
public comment regarding the treatment of hospice services occurring 
within the MSPB-PAC IRF QRP episode window. Given the comments 
received, we proposed to include the Medicare spending for hospice 
services but risk adjust for them, such that MSPB-PAC IRF QRP episodes 
with hospice services are compared to a benchmark reflecting other 
MSPB-PAC IRF QRP episodes with hospice services. We believe this 
strikes a balance between the measure's intent of evaluating Medicare 
spending and ensuring that providers do not have incentives against the 
appropriate use of hospice services in a patient-centered continuum of 
care.
    We proposed to use RICs in response to commenters' concerns about 
the risk adjustment approach for the MSPB-PAC IRF QRP measure. 
Commenters suggested the use of case mix groups (CMGs); however, we 
believed that the use of RICs may be more appropriate given that the 
other covariates incorporated in the model partially account for 
factors in CMGs (for example, age and certain HCC indicators). RICs do 
not account for functional status as CMGs do, as the functional status 
information in CMGs is based on the IRF-PAI. Given the

[[Page 52091]]

move toward standardized data that was mandated by the IMPACT Act, we 
have chosen to defer risk adjustment for functional status until 
standardized data become available. We sought comments on whether the 
use of CMGs would be appropriate to include in the MSPB-PAC IRF QRP 
risk adjustment model.
    We understand the important role that sociodemographic factors, 
beyond age, play in the care of patients. However, we continue to have 
concerns about holding providers to different standards for the 
outcomes of their patients of diverse sociodemographic status because 
we do not want to mask potential disparities or minimize incentives to 
improve the outcomes of disadvantaged populations. We will monitor the 
impact of sociodemographic status on providers' results on our 
measures.
    The NQF is currently undertaking a 2-year trial period in which new 
measures and measures undergoing maintenance review will be assessed to 
determine if risk-adjusting for sociodemographic factors is 
appropriate. For 2 years, NQF will conduct a trial of temporarily 
allowing inclusion of sociodemographic factors in the risk-adjustment 
approach for some performance measures. At the conclusion of the trial, 
NQF will issue recommendations on future permanent inclusion of 
sociodemographic factors. During the trial, measure developers are 
expected to submit information such as analyses and interpretations as 
well as performance scores with and without sociodemographic factors in 
the risk adjustment model.
    Furthermore, ASPE is conducting research to examine the impact of 
sociodemographic status on quality measures, resource use, and other 
measures under the Medicare program as required under the IMPACT Act. 
We will closely examine the findings of the ASPE reports and related 
Secretarial recommendations and consider how they apply to our quality 
programs at such time as they are available.
    While we conducted analyses on the impact of age by sex on the 
performance of the MSPB-PAC IRF QRP risk-adjustment model, we did not 
propose to adjust the MSPB-PAC IRF QRP measure for socioeconomic 
factors. As this MSPB-PAC IRF QRP measure would be submitted for NQF 
endorsement, we prefer to await the results of this trial and study 
before deciding whether to risk adjust for socioeconomic factors. We 
will monitor the results of the trial, studies, and recommendations. We 
invited public comment on how socioeconomic and demographic factors 
should be used in risk adjustment for the MSPB-PAC IRF QRP measure.
(3) Measure Numerator and Denominator
    The MPSB-PAC IRF QRP measure is a payment-standardized, risk-
adjusted ratio that compares a given IRF provider's Medicare spending 
against the Medicare spending of other IRF providers within a 
performance period. Similar to the hospital MSPB measure, the ratio 
allows for ease of comparison over time as it obviates the need to 
adjust for inflation or policy changes.
    The MSPB-PAC IRF QRP measure is calculated as the ratio of the 
MSPB-PAC Amount for each IRF provider divided by the episode-weighted 
median MSPB-PAC Amount across all IRF providers. To calculate the MSPB-
PAC Amount for each IRF provider, one calculates the average of the 
ratio of the standardized episode spending over the expected episode 
spending (as predicted in risk adjustment), and then multiplies this 
quantity by the average episode spending level across all IRF providers 
nationally. The denominator for an IRF provider's MSPB-PAC IRF QRP 
measure is the episode-weighted national median of the MSPB-PAC Amounts 
across all IRF providers. An MSPB-PAC IRF QRP measure of less than 1 
indicates that a given IRF provider's Medicare spending is less than 
that of the national median IRF provider during a performance period. 
Mathematically, this is represented in equation (A) below:
[GRAPHIC] [TIFF OMITTED] TR05AU16.009

where

 Yij = attributed standardized spending for episode i and 
provider j
 [Ycirc]ij = expected standardized spending for episode i 
and provider j, as predicted from risk adjustment
 nj = number of episodes for provider j
 n = total number of episodes nationally
 i [isin] {Ij{time}  = all episodes i in the set of episodes 
attributed to provider j.
c. Data Sources
    The MSPB-PAC IRF QRP resource use measure is an administrative 
claims-based measure. It uses Medicare Part A and Part B claims from 
FFS beneficiaries and Medicare eligibility files.
d. Cohort
    The measure cohort includes Medicare FFS beneficiaries with an IRF 
treatment period ending during the data collection period.
e. Reporting
    We intend to provide initial confidential feedback to providers, 
prior to public reporting of this measure, based on Medicare FFS claims 
data from discharges in CY 2015 and 2016. We intend to publicly report 
this measure using claims data from discharges in CY 2016 and 2017.
    We proposed to use a minimum of 20 episodes for reporting and 
inclusion in the IRF QRP. For the reliability calculation, as described 
in the measure specifications for which a link has been provided above, 
we used 2 years of data (FY 2013 and FY 2014) to increase the 
statistical reliability of this measure. The reliability results 
support the 20 episode case minimum, and 99.74 percent of IRF providers 
had moderate or high reliability (above 0.4).
    We invited public comment on our proposal to adopt the MSPB-PAC IRF 
QRP measure for the IRF QRP. The comments we received, with our 
responses, appear below.
    Comment: Several commenters expressed concern about the lack of NQF 
endorsement for proposed measures; some believed that the measure 
should not be finalized until NQF endorsement is obtained.

[[Page 52092]]

    Response: Regarding the lack of NQF endorsement, refer to section 
VIII.B. of this final rule where we also discuss this topic.
    Comment: Some commenters recommended the use of uniform single 
MSPB-PAC measure that could be used to compare providers' resource use 
across settings, but the commenters also recognized that we do not have 
a uniform PPS for all the PAC settings currently. In the absence of a 
single PAC PPS, the commenters recommended a single MSPB-PAC measure 
for each setting that could be used to compare providers within a 
setting. Under a single measure, the episode definitions, service 
inclusions/exclusions, and risk adjustment methods would be the same 
across all PAC settings.
    Response: The four separate MSPB-PAC measures reflect the unique 
characteristics of each PAC setting and the population it serves. The 
four setting-specific MSPB-PAC measures are defined as consistently as 
possible across settings given the differences in the payment systems 
for each setting, and types of patients served in each setting. We have 
taken into consideration these differences and aligned the 
specifications, such as episode definitions, service inclusions/
exclusions and risk adjustment methods for each setting, to the extent 
possible while ensuring the accuracy of the measures in each PAC 
setting.
    Each of the measures assess Medicare Part A and Part B spending 
during the episode window which begins upon admission to the provider's 
care and ends 30 days after the end of the treatment period. The 
service-level exclusions are harmonized across settings. The definition 
of the numerator and denominator is the same across settings. However, 
specifications differ between settings when necessary to ensure that 
the measures accurately reflect patient care and align with each 
setting's payment system. For example, Medicare pays LTCHs and IRFs a 
stay-level payment based on the assigned MS-LTC-DRG and CMG, 
respectively, while SNFs are paid a daily rate based on the RUG level, 
and HHA providers are reimbursed based on a fixed 60-day period for 
standard home health claims. While the definition of the episode window 
is consistent across settings and is based on the period of time that a 
beneficiary is under a given provider's care, the duration of the 
treatment period varies to reflect how providers are reimbursed under 
the PPS that applies to each setting. The length of the post-treatment 
period is consistent between settings. There are also differences in 
services covered under the PPS that applies to each setting: For 
example, durable medical equipment, prosthetics, orthotics, and 
supplies (DMEPOS) claims are covered LTCH, IRF, and SNF services but 
are not covered HHA services. This affects the way certain first-day 
service exclusions are defined for each measure.
    We recognize that beneficiaries may receive similar services as 
part of their overall treatment plan in different PAC settings, but 
believe that there are some important differences in beneficiaries' 
care profiles that are difficult to capture in a single measure that 
compares resource use across settings.
    Also, the risk adjustment models for the MSPB-PAC measures share 
the same covariates to the greatest extent possible to account for 
patient case mix. However, the measures also incorporate additional 
setting-specific information where available to increase the predictive 
power of the risk adjustment models. For example, the MSPB-PAC LTCH QRP 
risk adjustment model uses MS-LTC-DRGs and Major Diagnostic Categories 
(MDCs) and the MSPB-PAC IRF QRP model includes Rehabilitation 
Impairment Categories (RICs). The HH and SNF settings do not have 
analogous variables that directly reflect a patient's clinical profile.
    We will continue to work towards a more uniform measure across 
settings as we gain experience with these measures, and we plan to 
conduct further research and analyses about comparability of resource 
use measures across settings for clinically similar patients, different 
treatment periods and windows, risk adjustment, service exclusions, and 
other factors.
    Comment: A few commenters noted that the MSPB-PAC measures are 
resource use measures that are not a standalone indicator of quality.
    Response: We appreciate the comment regarding the proposed MSPB-PAC 
measures as resource use measures. The MSPB-PAC IRF QRP measure is one 
of five QRP measures that were proposed in the FY 2017 IRF PPS proposed 
rule for inclusion in the IRF QRP: In addition to the MSPB-PAC IRF QRP 
measure, these proposed measures were the Discharge to Community--PAC 
IRF QRP measure (81 FR 24201 through 24204), the Potentially 
Preventable 30-day Post-Discharge Readmission Measure for IRF QRP (81 
FR 24204 through 24206), the Potentially Preventable Within Stay 
Readmission Measure for IRFs (81 FR 242096 through 24207), and the Drug 
Regimen Review Conducted with Follow-Up for Identified Issues--PAC IRF 
QRP measure (81 FR 24207 through 24209). As part of the IRF QRP, the 
MSPB-PAC IRF QRP measure will be paired with quality measures; we 
direct readers to section VIII.E. of this final for a discussion of 
quality measures previously finalized for use in the IRF QRP. We 
believe it is important that the cost of care be explicitly measured so 
that, in conjunction with other quality measures, we can publicly 
report which IRF providers are involved in the provision of high 
quality care at lower cost.
    Comment: One commenter recommended that proposed quality measures 
obtain the support of a TEP including IRF representatives to ensure the 
applicability of the measures to the IRF setting.
    Response: We thank the commenter for their recommendation. As 
discussed in the proposed rule (81 FR 24198), we convened a TEP 
consisting of 12 panelists with combined expertise in PAC settings, 
including IRFs, on October 29 and 30, 2015, in Baltimore, Maryland. 
TEPs do not formally support or endorse measures. However, their 
feedback on risk adjustment, episode windows, exclusions, and other key 
elements of measure construction were incorporated into measure 
development. The MSPB-PAC TEP Summary Report Web site is listed above 
in this section.
    Comment: Several commenters recommended that the risk adjustment 
model for the MSPB-PAC IRF QRP measure include variables for SES/SDS 
factors. A commenter recommended that a ``fairer'' approach than using 
SES/SDS factors as risk adjustment variables would be to compare 
resource use levels that have not been adjusted for SES/SDS factors 
across peer providers (that is, providers with similar shares of 
beneficiaries with similar SES characteristics).
    Response: With regard to the suggestions that the model include 
sociodemographic factors and the suggestion pertaining to an approach 
with which to convey data comparisons, we refer readers to section 
VIII.F of this final rule where we also discuss these topics.
    Comment: Some commenters recommended that additional variables be 
included in risk adjustment to better capture clinical complexity. A 
few commenters suggested the inclusion of functional and cognitive 
status, other patient assessment data and patient-reported data. 
Commenters recommended that additional variables should include 
obesity, amputations, CVAs (hemiplegia/paresis), ventilator status, and 
discharged against medical advice.
    Response: We thank the commenters for their suggestions. HCC 
indicators

[[Page 52093]]

that are already included in the risk adjustment model account for 
amputations, hemiplegia, and paresis. We believe that the other risk 
adjustment variables adequately adjust for ventilator dependency and 
obesity by accounting for HCCs, clinical case mix categories, and prior 
inpatient and ICU length of stay. Excluding patients who are discharged 
against medical advice may create incentives for providers to use this 
discharge status code to remove high-cost patients from their MSPB-PAC 
measure calculation. Patient-reported data is not currently available 
on Medicare FFS claims. The addition of such data would likely be 
burdensome on IRF providers and the reliability of the data would need 
to be thoroughly tested before use in Medicare programs.
    We recognize the importance of accounting for beneficiaries' 
functional and cognitive status in the calculation of predicted episode 
spending. We considered the potential use of functional status 
information in the risk adjustment models for the MSPB-PAC measures. 
However, we decided not to include this information derived from 
current setting-specific assessment instruments given the move towards 
standardized data as mandated by the IMPACT Act. We will revisit the 
inclusion of functional status in these measures' risk adjustment 
models in the future when the standardized functional status data 
mandated by the IMPACT Act become available. Once they are available, 
we will take a gradual and systematic approach in evaluating how they 
might be incorporated. We intend to implement any changes if 
appropriate based on testing.
    Comment: A few commenters expressed concern that the measures will 
give incentive to IRFs to avoid admitting medically complex patients, 
which would result in unintended consequences.
    Response: To mitigate the risk of creating incentives for IRFs to 
avoid admitting medically complex patients, who may be at higher risk 
for poor outcomes and higher costs, we have included factors related to 
medical complexity in the risk adjustment methodology for the MSPB-PAC 
IRF QRP measure. We also intend to conduct ongoing monitoring to assess 
for potential unintended consequences associated with the 
implementation of these measures.
    Comment: Several commenters recommended that IRF interrupted stays 
be excluded as those patients would appear more expensive for receiving 
necessary care outside of the control of the IRF (that is, during the 
interruption).
    Response: We believe that IRFs are in a position to influence a 
patient's experience and outcomes after the initial discharge from the 
IRF, including the likelihood and intensity of IRF readmissions. As 
noted in the proposed rule (81 FR 24197), the proposed MSPB-PAC IRF QRP 
measure will support IRF providers' efforts to promote care 
coordination.
    Comment: Several commenters expressed concerns over the inclusion 
of spending that occurs within the thirty day post-discharge timeframe 
in the measure, believing that providers do not have sufficient control 
over the patient in the post-treatment period.
    Response: We believe that the post-treatment period may be 
reflective of and influenced by the services furnished by the PAC 
provider, therefore, including the 30-day post-treatment period in the 
MSPB-PAC IRF QRP measure creates a continuum of accountability between 
providers and may incentivize improvements in post-treatment care 
planning and coordination. The MSPB-PAC measures complement the NQF-
endorsed hospital MSPB measure: As they all include a period during 
which post-treatment spending is attributed to the provider, this 
accountability incentivizes acute and PAC providers to engage in 
appropriate discharge planning and post-treatment care coordination to 
minimize the likelihood of costly adverse events, such as avoidable 
hospitalizations.
    Comment: Several commenters recommended first day service 
exclusions for IRFs that are the same as other PAC settings, such as 
SNFs.
    Response: As discussed in the MSPB-PAC Measure Specifications, the 
Web site that is listed above in this section, treatment services 
occurring on the first day of MSPB-PAC episodes are subject to 
exclusions related to prior institutional care such as discharge care 
services. IRFs provide more intense hospital-level care and have 
physicians or midlevel practitioners evaluate patients upon admission, 
which enables the facility to influence many services delivered on the 
first day of the PAC stay. As such, only a limited number of discharge 
care services are excluded. Moreover, the NQF-endorsed hospital MSPB 
measure includes a period during which post-treatment spending is 
attributed to the provider; this accountability incentivizes acute and 
PAC providers to engage in appropriate discharge planning and post-
treatment care coordination.
    Comment: Several commenters recommended that short stays be 
excluded from the MSPB-PAC IRF QRP measure as these patients are 
identified as not being suitable for IRF care.
    Response: We believe that including short stay discharges in the 
measure promotes timely and accurate pre-admission screening, as well 
as discharge planning and post-discharge care coordination. Including 
IRF short stays maintains consistency across the MSPB-PAC measures to 
the greatest extent possible. Short stays constitute a very small share 
of IRF stays nationally; in FY 2014, approximately 1.8 percent of IRF 
stays were short stay discharges. Moreover, the MSPB-PAC IRF QRP 
measure's methodology excludes outlier episodes. Therefore, we do not 
believe that inclusion of short stays in the MSPB-PAC IRF QRP measure 
will unfairly disadvantage or advantage an IRF provider in their 
performance on the measure. Moreover, including short stay discharges 
incentivizes providers to maintain beneficiaries under their care for 
the appropriate length of time, and will not incentivize IRFs to 
prematurely discharge their beneficiaries. We are finalizing the MSPB-
PAC IRF QRP measure to include short stay discharges after careful 
consideration of the commenter's input.
    Comment: Several commenters recommended the use of CMGs for risk 
adjustment instead of RICs to more fully and accurately account for and 
explain variances in resource utilization and case mix in the IRF 
setting. Commenters noted that CMGs incorporate functional status and 
are weighted to account for patients' predicted resource requirements, 
while RICs only indicate patients' overall medical condition; as such 
there can be wide variation of reimbursement within a single RIC.
    Response: We have carefully considered the commenters feedback and 
are proceeding to finalize the measure as proposed. We believe the 
beneficiary's principal diagnosis or impairment as provided by the RIC 
currently supports the accurate estimation of Medicare spending while 
also reflecting clinical information that is accurately and 
consistently coded on IRF claims. The inclusion of RICs as variables in 
the MSPB-PAC IRF QRP risk adjustment model maintains consistency 
between MSPB-PAC resource use measures for each setting to the greatest 
extent possible, in that the other settings' MSPB-PAC measures do not 
incorporate variables reflecting the beneficiaries' functional status 
information. We may reconsider how to consistently incorporate 
functional status into the risk adjustment models for the MSPB-PAC 
measures once standardized data mandated by the IMPACT Act become 
available in the

[[Page 52094]]

future. Furthermore, the covariates incorporated in the MSPB-PAC IRF 
QRP risk adjustment model partially account for two factors in CMGs--
age and co-morbidities. For co-morbidities, the risk adjustment 
specifications use flags for Hierarchical Condition Categories (HCCs) 
defined by scanning inpatient, Part B physician/carrier, and outpatient 
claims during a 90-day lookback period. We appreciate commenters' 
thoughtful input and thank them for their engagement with this measure 
through the rulemaking process.
    Comment: A few commenters suggested that descriptive statistics on 
the measure score by provider-level characteristics (for example, 
urban/rural status and bed size) would be useful to evaluate measure 
design decisions.
    Response: Table 8 shows the MSPB-PAC IRF provider scores by 
provider characteristics, calculated using FY 2013 and FY 2014 data.

                                                Table 8--MSPB-PAC IRF Scores by Provider Characteristics
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                           Score percentile
               Provider characteristic                 Number of     Mean   ----------------------------------------------------------------------------
                                                       providers    score       1st        10th       25th       50th       75th       90th       99th
--------------------------------------------------------------------------------------------------------------------------------------------------------
All Providers........................................      1,169       0.99       0.78       0.88       0.93       0.98       1.04       1.09       1.24
Urban/Rural:
    Urban............................................        979       0.99       0.77       0.88       0.93       0.98       1.04       1.08       1.24
    Rural............................................        190       0.98       0.79       0.88       0.91       0.97       1.04       1.10       1.25
Ownership Type:
    For profit.......................................        345       1.01       0.82       0.91       0.97       1.01       1.06       1.10       1.24
    Non-profit.......................................        569       0.97       0.76       0.87       0.91       0.97       1.02       1.07       1.28
    Government.......................................        142       0.98       0.81       0.88       0.93       0.98       1.02       1.08       1.23
    Unknown..........................................        113       0.97       0.77       0.88       0.91       0.96       1.02       1.06       1.31
Census Division:
    New England......................................         36       1.03       0.86       0.92       0.97       1.03       1.08       1.12       1.16
    Middle Atlantic..................................        153       0.99       0.79       0.89       0.93       0.98       1.05       1.09       1.30
    East North Central...............................        210       0.96       0.79       0.87       0.91       0.97       1.01       1.04       1.10
    West North Central...............................        103       0.94       0.76       0.83       0.90       0.94       0.99       1.03       1.14
    South Atlantic...................................        162       1.00       0.80       0.90       0.95       1.00       1.05       1.09       1.24
    East South Central...............................         78       1.00       0.87       0.92       0.96       0.99       1.04       1.08       1.11
    West South Central...............................        226       1.01       0.85       0.91       0.95       1.02       1.05       1.12       1.24
    Mountain.........................................         91       1.00       0.79       0.88       0.93       0.98       1.05       1.12       1.99
    Pacific..........................................        106       0.96       0.74       0.83       0.89       0.95       1.02       1.08       1.32
    Other............................................          4       0.88       0.74       0.74       0.79       0.90       0.97       0.98       0.98
Bed Count:
    0-49.............................................        114       1.01       0.79       0.91       0.96       1.01       1.04       1.12       1.25
    50-99............................................        188       1.01       0.80       0.91       0.96       1.00       1.06       1.09       1.30
    100-199..........................................        231       0.98       0.79       0.87       0.92       0.98       1.04       1.10       1.24
    200-299..........................................        184       0.97       0.77       0.87       0.91       0.97       1.01       1.07       1.44
    300 +............................................        452       0.98       0.77       0.88       0.92       0.97       1.03       1.08       1.24
Number of Episodes:
    0-99.............................................        108       1.00       0.74       0.81       0.89       0.97       1.07       1.16       1.83
    100-249..........................................        344       0.97       0.76       0.86       0.90       0.96       1.03       1.08       1.31
    250-499..........................................        327       0.98       0.82       0.88       0.92       0.97       1.03       1.08       1.23
    500-1000.........................................        216       0.99       0.83       0.92       0.95       0.99       1.03       1.07       1.17
    1000 +...........................................        174       1.01       0.89       0.94       0.97       1.02       1.06       1.08       1.15
Teaching:
    Non-teaching.....................................      1,059       0.98       0.77       0.88       0.93       0.98       1.03       1.08       1.24
    Patient to ADC less than 10%.....................         63       0.99       0.83       0.90       0.93       0.98       1.04       1.08       1.30
    Patient to ADC 10%-20%...........................         36       1.02       0.83       0.89       0.95       1.00       1.06       1.11       1.83
    Patient to ADC greater than 20%..................         11       1.00       0.88       0.90       0.91       1.03       1.06       1.07       1.08
--------------------------------------------------------------------------------------------------------------------------------------------------------

    Comment: One commenter recommended that a geographic-specific (for 
example, state or regional) median should be used instead of the 
national median, citing differences in cost, patient population, and 
regulation.
    Response: As noted in the proposed rule (81 FR 24199), we proposed 
to use the same payment standardization methodology that used in the 
NQF-endorsed hospital MSPB measure to account for variation in Medicare 
spending. This methodology removes geographic payment differences, such 
as wage index and geographic practice cost index (GPCI), incentive 
payment adjustments, and other add-on payments that support broader 
Medicare program goals including indirect graduate medical education 
(IME) and hospitals serving a disproportionate share of uninsured 
patients (DSH). We believe that this approach accounts for the 
differences that the commenter raises while also maintaining 
consistency with the NQF-endorsed hospital MSPB measure's methodology 
for addressing regional variation through payment standardization.
    Comment: Some commenters recommended that the measure be tested for 
reliability and validity prior to finalization.
    Response: The MSPB-PAC IRF QRP measure has been tested for 
reliability using 2 years of data (FY 2013 and FY 2014). The 
reliability results support the 20 episode case minimum, and 99.74 
percent of IRF providers had moderate or high reliability (above 0.4). 
Further details on the reliability calculation are provided in the 
MSPB-PAC Measure Specifications Web site that is listed above in this 
section.
    Comment: Some commenters recommended an initial confidential

[[Page 52095]]

data preview period for providers, prior to public reporting.
    Response: Providers will receive a confidential preview report with 
30 days for review in advance of their data and information being 
publically displayed.
    Comment: A few commenters believed that the measure is a burden for 
providers.
    Response: We appreciate the importance of avoiding undue burden on 
providers. The MSPB-PAC IRF QRP measure relies on Medicare FFS claims, 
which are already reported to the Medicare program for payment 
purposes. PAC providers will not be required to report additional data 
to CMS for calculation of this measure
    Comment: One commenter requested that if the measures are finalized 
after a trial, that the same FIM Rating system be used to eliminate 
confusion and ensure that providers are submitting accurate 
information.
    Response: The MSPB-PAC IRF QRP Measure focuses on comparing 
resource use among providers within a given PAC setting and does not 
measure clinical outcomes such as severity of disability.
    In summary, after consideration of the public comments we received, 
we are finalizing the specifications of the MSPB-PAC IRF QRP resource 
use measure, as proposed. A Web site for the measure specifications has 
been provided above in this section.
    Specifically, we are finalizing the definition of an MSPB-PAC IRF 
QRP episode, beginning from episode trigger. An episode window 
comprises a treatment period beginning at the trigger and ended upon 
discharge, and associated services period beginning at the trigger and 
ending 30 days after the end of the treatment period. Readmissions to 
the same IRF within 7 or fewer days do not trigger a new episode and 
are instead included in the treatment period of the first episode.
    We exclude certain services that are clinically unrelated to IRF 
care and/or because IRF providers may have limited influence over 
certain Medicare services delivered by other providers during the 
episode window. We also exclude certain episodes in their entirety from 
the MSPB-PAC IRF QRP measure, such as where a beneficiary is not 
enrolled in Medicare FFS for the entirety of the lookback period plus 
episode window.
    We finalize the inclusion of Medicare payments for Part A and Part 
B claims for services included in the MSPB-PAC IRF QRP episodes to 
calculate the MSPB-PAC IRF QRP measure.
    We are finalizing our proposal to risk adjust using covariates 
including age brackets, HCC indicators, prior inpatient stay length, 
ICU stay length, clinical case mix categories, and indicators for 
originally disabled, ESRD enrollment, long-term care status, and 
hospice claim in episode window. The measure also adjusts for 
geographic payment differences such as wage index and GPCI, and adjust 
for Medicare payment differences resulting from IME and DSH.
    We calculate the individual providers' MSPB-PAC Amount which is 
inclusive of MSPB-PAC IRF QRP observed episode spending over the 
expected episode spending as predicted through risk adjustment. 
Individual IRF providers' scores are calculated as their individual 
MSPB-PAC Amount divided by the median MSPB-PAC amount across all IRFs.
2. Measure To Address the IMPACT Act Domain of Resource Use and Other 
Measures: Discharge to Community-Post Acute Care (PAC) Inpatient 
Rehabilitation Facility (IRF) Quality Reporting Program (QRP)
    Sections 1899B(d)(1)(B) and 1899B(a)(2)(E)(ii) of the Act require 
the Secretary to specify a measure to address the domain of discharge 
to community by SNFs, LTCHs, and IRFs by October 1, 2016, and HHAs by 
January 1, 2017. We proposed to adopt the measure, Discharge to 
Community-PAC IRF QRP, for the IRF QRP for the FY 2018 payment 
determination and subsequent years as a Medicare FFS claims-based 
measure to meet this requirement.
    This measure assesses successful discharge to the community from an 
IRF setting, with successful discharge to the community including no 
unplanned rehospitalizations and no death in the 31 days following 
discharge from the IRF. Specifically, this measure reports an IRF's 
risk-standardized rate of Medicare FFS patients who are discharged to 
the community following an IRF stay, and do not have an unplanned 
readmission to an acute care hospital or LTCH in the 31 days following 
discharge to community, and who remain alive during the 31 days 
following discharge to community. The term ``community'', for this 
measure, is defined as home or self care, with or without home health 
services, based on Patient Discharge Status Codes 01, 06, 81, and 86 on 
the Medicare FFS claim.17 18 This measure is conceptualized 
uniformly across the PAC settings, in terms of the definition of the 
discharge to community outcome, the approach to risk adjustment, and 
the measure calculation.
---------------------------------------------------------------------------

    \17\ National Uniform Billing Committee Official UB-04 Data 
Specifications Manual 2017, Version 11, July 2016, Copyright 2016, 
American Hospital Association.
    \18\ This definition is not intended to suggest that board and 
care homes, assisted living facilities, or other settings included 
in the definition of ``community'' for the purpose of this measure 
are the most integrated setting for any particular individual or 
group of individuals under the Americans with Disabilities Act (ADA) 
and Section 504.
---------------------------------------------------------------------------

    Discharge to a community setting is an important health care 
outcome for many patients for whom the overall goals of post-acute care 
include optimizing functional improvement, returning to a previous 
level of independence, and avoiding institutionalization. Returning to 
the community is also an important outcome for many patients who are 
not expected to make functional improvement during their IRF stay, and 
for patients who may be expected to decline functionally due to their 
medical condition. The discharge to community outcome offers a multi-
dimensional view of preparation for community life, including the 
cognitive, physical, and psychosocial elements involved in a discharge 
to the community.19 20
---------------------------------------------------------------------------

    \19\ El-Solh AA, Saltzman SK, Ramadan FH, Naughton BJ. Validity 
of an artificial neural network in predicting discharge destination 
from a postacute geriatric rehabilitation unit. Archives of physical 
medicine and rehabilitation. 2000;81(10):1388-1393.
    \20\ Tanwir S, Montgomery K, Chari V, Nesathurai S. Stroke 
rehabilitation: Availability of a family member as caregiver and 
discharge destination. European journal of physical and 
rehabilitation medicine. 2014;50(3):355-362.
---------------------------------------------------------------------------

    In addition to being an important outcome from a patient and family 
perspective, patients discharged to community settings, on average, 
incur lower costs over the recovery episode, compared with those 
discharged to institutional settings.21 22 Given the high 
costs of care in institutional settings, encouraging IRFs to prepare 
patients for discharge to community, when clinically appropriate, may 
have cost-saving implications for the Medicare program.\23\ Also, 
providers have discovered that successful discharge to community was a 
major driver of their ability to achieve savings, where capitated 
payments for post-acute care

[[Page 52096]]

were in place.\24\ For patients who require long-term care due to 
persistent disability, discharge to community could result in lower 
long-term care costs for Medicaid and for patients' out-of-pocket 
expenditures.\25\
---------------------------------------------------------------------------

    \21\ Dobrez D, Heinemann AW, Deutsch A, Manheim L, Mallinson T. 
Impact of Medicare's prospective payment system for inpatient 
rehabilitation facilities on stroke patient outcomes. American 
journal of physical medicine & rehabilitation/Association of 
Academic Physiatrists. 2010;89(3):198-204.
    \22\ Gage B, Morley M, Spain P, Ingber M. Examining Post Acute 
Care Relationships in an Integrated Hospital System. Final Report. 
RTI International;2009.
    \23\ Ibid.
    \24\ Doran JP, Zabinski SJ. Bundled payment initiatives for 
Medicare and non-Medicare total joint arthroplasty patients at a 
community hospital: Bundles in the real world. The journal of 
arthroplasty. 2015;30(3):353-355.
    \25\ Newcomer RJ, Ko M, Kang T, Harrington C, Hulett D, Bindman 
AB. Health Care Expenditures After Initiating Long-term Services and 
Supports in the Community Versus in a Nursing Facility. Medical 
Care. 2016;54(3):221-228.
---------------------------------------------------------------------------

    Analyses conducted for ASPE on PAC episodes, using a 5 percent 
sample of 2006 Medicare claims, revealed that relatively high average, 
unadjusted Medicare payments are associated with discharge to 
institutional settings from IRFs, SNFs, LTCHs or HHAs, as compared with 
payments associated with discharge to community settings.\26\ Average, 
unadjusted Medicare payments associated with discharge to community 
settings ranged from $0 to $4,017 for IRF discharges, $0 to $3,544 for 
SNF discharges, $0 to $4,706 for LTCH discharges, and $0 to $992 for 
HHA discharges. In contrast, payments associated with discharge to non-
community settings were considerably higher, ranging from $11,847 to 
$25,364 for IRF discharges, $9,305 to $29,118 for SNF discharges, 
$12,465 to $18,205 for LTCH discharges, and $7,981 to $35,192 for HHA 
discharges.\27\
---------------------------------------------------------------------------

    \26\ Gage B, Morley M, Spain P, Ingber M. Examining Post Acute 
Care Relationships in an Integrated Hospital System. Final Report. 
RTI International;2009.
    \27\ Ibid.
---------------------------------------------------------------------------

    Measuring and comparing facility-level discharge to community rates 
is expected to help differentiate among facilities with varying 
performance in this important domain, and to help avoid disparities in 
care across patient groups. Variation in discharge to community rates 
has been reported within and across post-acute settings; across a 
variety of facility-level characteristics, such as geographic location 
(for example, regional location, urban or rural location), ownership 
(for example, for-profit or nonprofit), and freestanding or hospital-
based units; and across patient-level characteristics, such as race and 
gender.28 29 30 31 32 33 Discharge to community rates in the 
IRF setting have been reported to range from about 60 to 80 
percent.34 35 36 37 38 39 Longer-term studies show that 
rates of discharge to community from IRFs have decreased over time as 
IRF length of stay has decreased.40 41 In the IRF Medicare 
FFS population, using CY 2013 national claims data, we discovered that 
approximately 69 percent of patients were discharged to the community. 
Greater variation in discharge to community rates is seen in the SNF 
setting, with rates ranging from 31 to 65 
percent.42 43 44 45 A multi-center study of 23 LTCHs 
demonstrated that 28.8 percent of 1,061 patients who were ventilator-
dependent on admission were discharged to home.\46\ A single-center 
study revealed that 31 percent of LTCH hemodialysis patients were 
discharged to home.\47\ One study noted that 64 percent of 
beneficiaries who were discharged from the home health episode did not 
use any other acute or post-acute services paid by Medicare in the 30 
days after discharge.\48\ However, significant numbers of patients were 
admitted to hospitals (29 percent) and lesser numbers to SNFs (7.6 
percent), IRFs (1.5 percent), home health (7.2 percent) or hospice (3.3 
percent).\49\
---------------------------------------------------------------------------

    \28\ Reistetter TA, Karmarkar AM, Graham JE, et al. Regional 
variation in stroke rehabilitation outcomes. Archives of physical 
medicine and rehabilitation. 2014;95(1):29-38.
    \29\ El-Solh AA, Saltzman SK, Ramadan FH, Naughton BJ. Validity 
of an artificial neural network in predicting discharge destination 
from a postacute geriatric rehabilitation unit. Archives of physical 
medicine and rehabilitation. 2000;81(10):1388-1393.
    \30\ March 2015 Report to the Congress: Medicare Payment Policy. 
Medicare Payment Advisory Commission; 2015.
    \31\ Bhandari VK, Kushel M, Price L, Schillinger D. Racial 
disparities in outcomes of inpatient stroke rehabilitation. Archives 
of physical medicine and rehabilitation. 2005;86(11):2081-2086.
    \32\ Chang PF, Ostir GV, Kuo YF, Granger CV, Ottenbacher KJ. 
Ethnic differences in discharge destination among older patients 
with traumatic brain injury. Archives of physical medicine and 
rehabilitation. 2008;89(2):231-236.
    \33\ Berges IM, Kuo YF, Ostir GV, Granger CV, Graham JE, 
Ottenbacher KJ. Gender and ethnic differences in rehabilitation 
outcomes after hip-replacement surgery. American journal of physical 
medicine & rehabilitation/Association of Academic Physiatrists. 
2008;87(7):567-572.
    \34\ Galloway RV, Granger CV, Karmarkar AM, et al. The Uniform 
Data System for Medical Rehabilitation: Report of patients with 
debility discharged from inpatient rehabilitation programs in 2000-
2010. American journal of physical medicine & rehabilitation/
Association of Academic Physiatrists. 2013;92(1):14-27.
    \35\ Morley MA, Coots LA, Forgues AL, Gage BJ. Inpatient 
rehabilitation utilization for Medicare beneficiaries with multiple 
sclerosis. Archives of physical medicine and rehabilitation. 
2012;93(8):1377-1383.
    \36\ Reistetter TA, Graham JE, Deutsch A, Granger CV, Markello 
S, Ottenbacher KJ. Utility of functional status for classifying 
community versus institutional discharges after inpatient 
rehabilitation for stroke. Archives of physical medicine and 
rehabilitation. 2010;91(3):345-350.
    \37\ Gagnon D, Nadeau S, Tam V. Clinical and administrative 
outcomes during publicly-funded inpatient stroke rehabilitation 
based on a case-mix group classification model. Journal of 
rehabilitation medicine. 2005;37(1):45-52.
    \38\ DaVanzo J, El-Gamil A, Li J, Shimer M, Manolov N, Dobson A. 
Assessment of patient outcomes of rehabilitative care provided in 
inpatient rehabilitation facilities (IRFs) and after discharge. 
Vienna, VA: Dobson DaVanzo & Associates, LLC;2014.
    \39\ Kushner DS, Peters KM, Johnson-Greene D. Evaluating Siebens 
Domain Management Model for Inpatient Rehabilitation to Increase 
Functional Independence and Discharge Rate to Home in Geriatric 
Patients. Archives of physical medicine and rehabilitation. 
2015;96(7):1310-1318.
    \40\ Galloway RV, Granger CV, Karmarkar AM, et al. The Uniform 
Data System for Medical Rehabilitation: Report of patients with 
debility discharged from inpatient rehabilitation programs in 2000-
2010. American journal of physical medicine & rehabilitation/
Association of Academic Physiatrists. 2013;92(1):14-27.
    \41\ Mallinson T, Deutsch A, Bateman J, et al. Comparison of 
discharge functional status after rehabilitation in skilled nursing, 
home health, and medical rehabilitation settings for patients after 
hip fracture repair. Archives of physical medicine and 
rehabilitation. 2014;95(2):209-217.
    \42\ El-Solh AA, Saltzman SK, Ramadan FH, Naughton BJ. Validity 
of an artificial neural network in predicting discharge destination 
from a postacute geriatric rehabilitation unit. Archives of physical 
medicine and rehabilitation. 2000;81(10):1388-1393.
    \43\ Hall RK, Toles M, Massing M, et al. Utilization of acute 
care among patients with ESRD discharged home from skilled nursing 
facilities. Clinical journal of the American Society of Nephrology: 
CJASN. 2015;10(3):428-434.
    \44\ Stearns SC, Dalton K, Holmes GM, Seagrave SM. Using 
propensity stratification to compare patient outcomes in hospital-
based versus freestanding skilled-nursing facilities. Medical care 
research and review: MCRR. 2006;63(5):599-622.
    \45\ Wodchis WP, Teare GF, Naglie G, et al. Skilled nursing 
facility rehabilitation and discharge to home after stroke. Archives 
of physical medicine and rehabilitation. 2005;86(3):442-448.
    \46\ Scheinhorn DJ, Hassenpflug MS, Votto JJ, et al. Post-ICU 
mechanical ventilation at 23 long-term care hospitals: A multicenter 
outcomes study. Chest. 2007;131(1):85-93.
    \47\ Thakar CV, Quate-Operacz M, Leonard AC, Eckman MH. Outcomes 
of hemodialysis patients in a long-term care hospital setting: A 
single-center study. American journal of kidney diseases: The 
official journal of the National Kidney Foundation. 2010;55(2):300-
306.
    \48\ Wolff JL, Meadow A, Weiss CO, Boyd CM, Leff B. Medicare 
home health patients' transitions through acute and post-acute care 
settings. Medical care. 2008;46(11):1188-1193.
    \49\ Ibid.
---------------------------------------------------------------------------

    Discharge to community is an actionable health care outcome, as 
targeted interventions have been shown to successfully increase 
discharge to community rates in a variety of post-acute 
settings.50 51 52 53 Many of these

[[Page 52097]]

interventions involve discharge planning or specific rehabilitation 
strategies, such as addressing discharge barriers and improving medical 
and functional status.54 55 56 57 The effectiveness of these 
interventions suggests that improvement in discharge to community rates 
among post-acute care patients is possible through modifying provider-
led processes and interventions.
---------------------------------------------------------------------------

    \50\ Kushner DS, Peters KM, Johnson-Greene D. Evaluating Siebens 
Domain Management Model for Inpatient Rehabilitation to Increase 
Functional Independence and Discharge Rate to Home in Geriatric 
Patients. Archives of physical medicine and rehabilitation. 
2015;96(7):1310-1318.
    \51\ Wodchis WP, Teare GF, Naglie G, et al. Skilled nursing 
facility rehabilitation and discharge to home after stroke. Archives 
of physical medicine and rehabilitation. 2005;86(3):442-448.
    \52\ Berkowitz RE, Jones RN, Rieder R, et al. Improving 
disposition outcomes for patients in a geriatric skilled nursing 
facility. Journal of the American Geriatrics Society. 
2011;59(6):1130-1136.
    \53\ Kushner DS, Peters KM, Johnson-Greene D. Evaluating use of 
the Siebens Domain Management Model during inpatient rehabilitation 
to increase functional independence and discharge rate to home in 
stroke patients. PM & R: The journal of injury, function, and 
rehabilitation. 2015;7(4):354-364.
    \54\ Kushner DS, Peters KM, Johnson-Greene D. Evaluating Siebens 
Domain Management Model for Inpatient Rehabilitation to Increase 
Functional Independence and Discharge Rate to Home in Geriatric 
Patients. Archives of physical medicine and rehabilitation. 
2015;96(7):1310-1318.
    \55\ Wodchis WP, Teare GF, Naglie G, et al. Skilled nursing 
facility rehabilitation and discharge to home after stroke. Archives 
of physical medicine and rehabilitation. 2005;86(3):442-448.
    \56\ Berkowitz RE, Jones RN, Rieder R, et al. Improving 
disposition outcomes for patients in a geriatric skilled nursing 
facility. Journal of the American Geriatrics Society. 
2011;59(6):1130-1136.
    \57\ Kushner DS, Peters KM, Johnson-Greene D. Evaluating use of 
the Siebens Domain Management Model during inpatient rehabilitation 
to increase functional independence and discharge rate to home in 
stroke patients. PM & R: The journal of injury, function, and 
rehabilitation. 2015;7(4):354-364.
---------------------------------------------------------------------------

    A TEP convened by our measure development contractor was strongly 
supportive of the importance of measuring discharge to community 
outcomes, and implementing the measure, Discharge to Community-PAC IRF 
QRP in the IRF QRP. The panel provided input on the technical 
specifications of this measure, including the feasibility of 
implementing the measure, as well as the overall measure reliability 
and validity. A summary of the TEP proceedings is available on the PAC 
Quality Initiatives Downloads and Videos Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
    We also solicited stakeholder feedback on the development of this 
measure through a public comment period held from November 9, 2015, 
through December 8, 2015. Several stakeholders and organizations, 
including the MedPAC, among others, supported this measure for 
implementation. The public comment summary report for the measure is 
available on our Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
    The NQF-convened MAP met on December 14 and 15, 2015, and provided 
input on the use of this Discharge to Community-PAC IRF QRP measure in 
the IRF QRP. The MAP encouraged continued development of the measure to 
meet the mandate of the IMPACT Act. The MAP supported the alignment of 
this measure across PAC settings, using standardized claims data. More 
information about the MAP's recommendations for this measure is 
available at http://www.qualityforum.org/Publications/2016/02/MAP_2016_Considerations_for_Implementing_Measures_in_Federal_Programs_-_PAC-LTC.aspx.
    Since the MAP's review and recommendation of continued development, 
we have continued to refine risk-adjustment models and conduct measure 
testing for this measure, as recommended by the MAP. This measure is 
consistent with the information submitted to the MAP, and the original 
MAP submission and our continued refinements support its scientific 
acceptability for use in quality reporting programs. As discussed with 
the MAP, we fully anticipate that additional analyses will continue as 
we submit this measure to the ongoing measure maintenance process.
    We reviewed the NQF's consensus-endorsed measures and were unable 
to identify any NQF-endorsed resource use or other measures for post-
acute care focused on discharge to community. In addition, we are 
unaware of any other post-acute care measures for discharge to 
community that have been endorsed or adopted by other consensus 
organizations. Therefore, we proposed the measure, Discharge to 
Community-PAC IRF QRP, under the Secretary's authority to specify non-
NQF-endorsed measures under section 1899B(e)(2)(B) of the Act.
    We proposed to use data from the Medicare FFS claims and Medicare 
eligibility files to calculate this measure. We proposed to use data 
from the ``Patient Discharge Status Code'' on Medicare FFS claims to 
determine whether a patient was discharged to a community setting for 
calculation of this measure. In all PAC settings, we tested the 
accuracy of determining discharge to a community setting using the 
``Patient Discharge Status Code'' on the PAC claim by examining whether 
discharge to community coding based on PAC claim data agreed with 
discharge to community coding based on PAC assessment data. We found 
excellent agreement between the two data sources in all PAC settings, 
ranging from 94.6 percent to 98.8 percent. Specifically, in the IRF 
setting, using 2013 data, we found 98.8 percent agreement in coding of 
community and non-community discharges when comparing discharge status 
codes on claims and the Discharge to Living Setting (item 44A) codes on 
the IRF-PAI. We further examined the accuracy of the ``Patient 
Discharge Status Code'' on the PAC claim by assessing how frequently 
discharges to an acute care hospital were confirmed by follow-up acute 
care claims. We discovered that 88 percent to 91 percent of IRF, LTCH, 
and SNF claims with acute care discharge status codes were followed by 
an acute care claim on the day of, or day after, PAC discharge. We 
believed these data support the use of the claims ``Patient Discharge 
Status Code'' for determining discharge to a community setting for this 
measure. In addition, this measure can feasibly be implemented in the 
IRF QRP because all data used for measure calculation are derived from 
Medicare FFS claims and eligibility files, which are already available 
to CMS.
    Based on the evidence discussed above, we proposed to adopt the 
measure, Discharge to Community-PAC IRF QRP, for the IRF QRP for FY 
2018 payment determination and subsequent years. This measure is 
calculated using 2 years of data. We proposed a minimum of 25 eligible 
stays in a given IRF for public reporting of the measure for that IRF. 
Since Medicare FFS claims data are already reported to the Medicare 
program for payment purposes, and Medicare eligibility files are also 
available, IRFs will not be required to report any additional data to 
us for calculation of this measure. The measure denominator is the 
risk-adjusted expected number of discharges to community. The measure 
numerator is the risk-adjusted estimate of the number of patients who 
are discharged to the community, do not have an unplanned readmission 
to an acute care hospital or LTCH in the 31-day post-discharge 
observation window, and who remain alive during the post-discharge 
observation window. The measure is risk-adjusted for variables such as 
age and sex, principal diagnosis, comorbidities, ESRD status, and 
dialysis, among other variables. For technical information about the 
proposed measure, including information about the measure calculation, 
risk adjustment, and denominator exclusions, we referred readers to the 
document titled, Proposed Measure Specifications for Measures Proposed 
in the FY 2017 IRF QRP proposed rule, available at https://

[[Page 52098]]

www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-
Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-
Measures-Information-.html.
    We stated in the proposed rule that we intend to provide initial 
confidential feedback to IRFs, prior to public reporting of this 
measure, based on Medicare FFS claims data from discharges in CY 2015 
and 2016. We intend to publicly report this measure using claims data 
from discharges in CY 2016 and 2017. We will submit this measure to the 
NQF for consideration for endorsement.
    In the CY 2013 OPPS/ASC final rule (77 FR 68500), we finalized our 
policy to use a subregulatory approach to incorporate non-substantive 
changes to measures adopted in the IRF QRP, including changes to 
exclusions. In that rule, we noted that we expect to make this 
determination on a measure-by-measure basis and that examples of non-
substantive changes to measures might include exclusions for a measure. 
For the proposed Discharge to Community-IRF QRP measure, we have added 
an exclusion of patients/residents with a hospice benefit in the post-
discharge observation window, in response to comments received during 
measure development and our ongoing analysis and testing. The rationale 
for the exclusion of patients/residents with a hospice benefit in the 
post-discharge observation window aligns with the rationale for 
exclusion of discharges to hospice. Based on testing, we found that 
patients/residents with a post-discharge hospice benefit have a much 
higher death rate in the post-discharge observation window compared 
with patients/residents without a hospice benefit. We determined that 
the addition of this hospice exclusion enhances the measure by 
excluding patients/residents with a high likelihood of post-discharge 
death and improves the national observed discharge to community rate 
for IRFs by approximately 0.8 percent. With the addition of this 
hospice exclusion, we do not believe burden is added, nor that the 
addition of this exclusion is a substantive change to the overall 
measure. Failure to include this hospice exclusion could lead to 
unintended consequences and access issues for terminally-ill patients/
residents in our PAC populations.
    We invited public comment on our proposal to adopt the measure, 
Discharge to Community-PAC IRF QRP, for the IRF QRP. The comments we 
received on this topic, with our responses, appear below.
    Comment: Multiple commenters, including MedPAC, supported the 
Discharge to Community-PAC IRF QRP measure, noting that it is a 
critical measure assessing the ability of PAC providers to avoid 
patient institutionalization. One commenter noted that measuring the 
rate that the various PAC settings discharge patients to the community, 
without an admission (or readmission) to an acute care hospital within 
30 days, is one of the most relevant patient-centered measures that 
exists in the post-acute care area. One commenter conveyed that 
successful transitions to the community are expected to decrease 
potentially preventable readmissions, while another was appreciative 
that the measure did not place additional data collection burden on 
facilities. One commenter stated that achieving a standardized and 
interoperable patient assessment data set and stable quality measures 
as quickly as possible will allow for better cross-setting comparisons 
and the evolution of better quality measures with uniform risk 
standardization.
    Response: We thank the commenters for their support of the 
Discharge to Community-PAC IRF QRP measure, and their recognition of 
the patient-centeredness of this measure, its potential to decrease 
post-discharge readmissions, and its lack of data collection burden. We 
also thank the commenter for their support of standardized and 
interoperable patient assessment data and quality measures. As mandated 
by the IMPACT Act, we are moving toward the goal of standardized 
patient assessment data and quality measures across PAC settings.
    Comment: One commenter interpreted our measure proposal language as 
suggesting that functional improvement is not a requirement, and 
encouraged that Medicare coverage for maintenance nursing and therapy 
be ensured and reflected by the measure.
    Response: Our intent in the measure proposal was to acknowledge 
that discharge to community can be an important goal even for patients 
who may not be able to make functional improvement. This measure does 
not impact Medicare coverage rules for maintenance nursing and therapy.
    Comment: Several commenters expressed concerns regarding the use of 
the Patient Discharge Status Code variable to define community 
discharges. Commenters emphasized that it was important to ensure that 
only home and community based settings were included in the definition 
of community, and were concerned that Code 01 (Discharge to home or 
self-care) included institutional settings such as jail or law 
enforcement. One commenter expressed that many settings included under 
Code 01 do not satisfy the home and community based settings rule, and 
may be inconsistent with the integration mandate of the Americans with 
Disabilities Act. Commenters strongly recommended that CMS either 
revise Patient Discharge Status Code 01 to exclude non community-based 
settings, or use alternative variables to capture discharge to 
community.
    Response: We agree with the commenters that the discharge to 
community measure should only capture discharges to home and community 
based settings. We believe that the comment referring to the ``home and 
community based settings rule'' refers to Medicaid regulations 
applicable to services authorized under sections 1915(c), 1915(i) and 
1915(k) of the Social Security Act (the Act), which are provided 
through waivers or state plans amendments approved by CMS. We would 
like to clarify that this measure only captures discharges to home and 
community based settings, not to institutional settings, and is 
consistent with both Medicaid regulations requiring home and community 
based settings to support integration, and also with the Americans with 
Disabilities Act (ADA), based on Patient Discharge Status Codes 01, 06, 
81, and 86 on the Medicare FFS PAC claim.\58\ Discharges to court or 
law enforcement are not included under Code 01 of the Patient Discharge 
Status Code; rather these are included under Code 21 (Discharged/
transferred to Court/Law Enforcement).
---------------------------------------------------------------------------

    \58\ National Uniform Billing Committee Official UB-04 Data 
Specifications Manual 2017, Version 11, July 2016, Copyright 2016, 
American Hospital Association.
---------------------------------------------------------------------------

    We also note that Title II of the ADA requires public entities to 
administer services, programs, and activities in the most integrated 
setting appropriate to the needs of qualified individuals with 
disabilities (28 CFR 35.130(d)). The preamble discussion of the 
``integration regulation'' explains that ``the most integrated 
setting'' is one that enables individuals with disabilities to interact 
with nondisabled persons to the fullest extent possible. Integrated 
settings are those that provide individuals with disabilities 
opportunities to live, work, and receive services in the greater 
community, like individuals without disabilities (28 CFR part 35, app. 
A (2010) (addressing Sec.  35.130)).
    Comment: Several commenters stated that PAC patients/residents 
discharged to a nursing facility as long-term care

[[Page 52099]]

residents should not be considered discharges to community, 
particularly if they were discharged to the nursing facility from the 
Medicare-certified skilled nursing part of the same nursing home, and 
even if they resided in a long-term nursing facility at baseline. 
Commenters emphasized that a nursing home does not represent an 
individual's own home in their own community. These commenters 
interpreted the measure specifications as allowing these discharges to 
nursing facility to be coded as ``group home'', ``foster care'', or 
``other residential care arrangement'' under discharge status code 01. 
Commenters expressed concern that coding discharges from the SNF to 
residential/long-term care facility within the same nursing home as 
discharges to community would unfairly advantage SNFs and artificially 
inflate their discharge to community rates, would disadvantage other 
PAC providers, and would miscommunicate a facility's actual discharge 
to community performance to the average Medicare beneficiary. One 
commenter suggested exclusion of patients discharged to a non-Medicare 
certified residence, such as a ``group home'' or ``foster care'' or 
other arrangement.
    Response: We agree with the commenters that discharges to long-term 
care nursing facilities, or any other institutional settings, should 
not be coded as discharges to community. We also recognize the 
differences in required discharge planning processes and resources for 
discharging a patient/resident to the community compared with 
discharging to a long-term nursing facility. The discharge to community 
measure only captures discharges to home and community based settings 
as discharges to community, based on Patient Discharge Status Codes 01, 
06, 81, and 86 on the Medicare FFS PAC claim.\59\ These codes do not 
include discharges to long-term care nursing facilities or any other 
institutional setting that may violate the integration mandate of Title 
II of the ADA. Instead, depending on the nature of the facility to 
which patients/residents are discharged, such discharges may be coded 
on the Medicare FFS claim as 04, 64, 84, 92, or another appropriate 
code for an institutional discharge.
---------------------------------------------------------------------------

    \59\ Ibid.
---------------------------------------------------------------------------

    In response to the commenters' concerns that SNFs may be unfairly 
advantaged by this measure as compared with other PAC providers, we 
would like to note that, in our measure development samples, the 
national discharge to community rate for SNFs was 47.26 percent, while 
this rate for IRFs was considerably higher (69.51 percent). Further, 
using an MDS-claims linked longitudinal file, we found that of the SNF 
stays that had a pre-hospitalization non-PPS MDS assessment suggesting 
prior nursing facility residence, two-thirds had a discharge status 
code of 30 (still patient), and approximately 18 percent had a 
discharge status code of 02 (acute hospital). Less than 5 percent of 
these patients had a Discharge Status Code of 01 (discharge to home or 
self care). Thus, the commenters' concerns that discharges from SNF to 
nursing facility are largely coded as Patient Discharge Status Code 01 
are not reflected in our data.
    Comment: Some commenters expressed concern that the discharge to 
community measure fails to distinguish patients/residents who lived in 
a long-term care nursing facility at baseline and returned to the 
nursing facility after their PAC stay. Commenters recommended that 
baseline long-stay nursing facility residents be excluded from the 
discharge to community measure, as they could not be reasonably 
expected to discharge back to the community. One commenter noted that 
these residents have a very different discharge process back to the 
nursing facility compared with patients discharged to the community. 
The commenter recommended that different measures be developed for the 
baseline nursing facility resident population, such as return to prior 
level of function, improvement in function, prevention of further 
functional decline, development of pressure ulcers, or accidental 
falls. The commenter also recognized CMS's current efforts in 
monitoring transitions of care and quality requirements in long-term 
care facilities. Commenters suggested that CMS could use longitudinal 
Minimum Data Set-linkage to identify and exclude baseline nursing 
facility residents.
    Response: We appreciate the commenters' concerns and their 
recommendation to exclude baseline nursing facility residents from the 
discharge to community measure, and to distinguish baseline custodial 
nursing facility residents who are discharged back to the nursing 
facility after their PAC stay. We recognize that patients/residents who 
permanently lived in a nursing facility at baseline may not be expected 
to discharge back to a home and community based setting after their PAC 
stay. We also recognize that, for baseline nursing facility residents, 
a discharge back to their nursing facility represents a discharge to 
their baseline residence. We agree with the commenter about the 
differences in discharge planning processes when discharging a patient/
resident to the community compared with discharging to a long-term 
nursing facility. However, using Medicare FFS claims alone, we are 
unable to accurately identify baseline nursing facility residents. 
Potential future modifications of the measure could include the 
assessment of the feasibility and impact of excluding baseline nursing 
facility residents from the measure through the addition of patient 
assessment-based data. However, we note that, currently, the IRF-PAI is 
the only PAC assessment that contains an item related to pre-hospital 
baseline living setting.
    Comment: A few commenters questioned the inclusion of only Medicare 
FFS patients/residents in the measure, and stated whether the measure 
would be expanded to include patients/residents with other payers or 
plan types. One commenter recommended that the patient populations be 
consistent across IRF measures, and not vary by payer or plan type, 
stating that consistency in measure populations across IRF measures was 
important for facilities to understand their quality metrics. Other 
commenters recommended that the discharge to community measure include 
other payer populations, and particularly emphasized the importance of 
including Medicare Advantage patients in the measure, highlighting that 
Medicare Advantage patients were included in the IRF Drug Regimen 
Review measure. The commenters noted that the Medicare Advantage 
population was a rapidly growing Medicare population, warranting their 
inclusion in quality measures.
    Response: We agree that is it important to monitor quality and 
resource use outcomes of all post-acute care patients/residents, not 
just Medicare FFS patients/residents. The discharge to community 
measure is limited to the Medicare FFS population through the use of a 
Medicare FFS claim, but we will consider the appropriateness and 
feasibility of including Managed Care patients/residents in future 
modifications of the measure. We would like to note that further 
expansion of the measure to include Medicare Managed Care or other 
payer populations would require standardized data collection across all 
settings and payer populations.
    Comment: MedPAC recommended that CMS confirm discharge to a 
community setting with the absence of a subsequent claim to a hospital, 
IRF, SNF, or LTCH, to ensure that discharge to community rates reflect 
actual facility performance. Other commenters also

[[Page 52100]]

recommended that CMS assess the reliability and validity of the Patient 
Discharge Status Code on PAC claims. Commenters cited MedPAC and other 
studies, noting that Patient Discharge Status Codes often have low 
reliability, and that this could impact accurate portrayal of measure 
performance.
    Response: We are committed to developing measures based on reliable 
and valid data. This measure does confirm the absence of hospital or 
LTCH claims following discharge to a community setting. Unplanned 
hospital and LTCH readmissions following the discharge to community, 
including those on the day of IRF discharge, are considered an 
unfavorable outcome. We will consider verifying the absence of IRF and 
SNF claims following discharge to a community setting, as we continue 
to refine this measure. Nonetheless, we would like to note that an ASPE 
report on post-acute care relationships found that, following discharge 
to community settings from IRFs, LTCHs, or SNFs in a 5 percent Medicare 
sample, IRFs or SNFs were very infrequently reported as the next site 
of post-acute care.\60\
---------------------------------------------------------------------------

    \60\ Gage B, Morley M, Spain P, Ingber M. Examining Post Acute 
Care Relationships in an Integrated Hospital System Final Report. 
RTI International; 2009.
---------------------------------------------------------------------------

    Because the discharge to community measure is a measure of 
discharge destination from the PAC setting, we have chosen to use the 
PAC-reported discharge destination (from the Medicare FFS claims) to 
determine whether a patient/resident was discharged to the community 
(based on discharge status codes 01, 06, 81, 86). We assessed the 
reliability of the claims discharge status code(s) by examining 
agreement between discharge status on claims and assessment instruments 
in all four PAC settings. We found between 94 and 99 percent agreement 
in coding of community discharges on matched claims and assessments in 
each of the PAC settings. We also assessed how frequently discharges to 
acute care, as indicated on the PAC claim, were confirmed by follow-up 
acute care claims, and found that 88 percent to 91 percent of IRF, 
LTCH, and SNF claims indicating acute care discharge were followed by 
an acute care claim on the day of, or day after, PAC discharge. We 
believe that these data support the use of the ``Patient Discharge 
Status Code'' from the PAC claim for determining discharge to a 
community setting for this measure.
    The use of the claims discharge status code to identify discharges 
to the community was discussed at length with the TEP convened by our 
measure development contractor. TEP members did not express significant 
concerns regarding the accuracy of the claims discharge status code in 
coding community discharges, nor about our use of the discharge status 
code for defining this quality measure. A summary of the TEP 
proceedings is available on the PAC Quality Initiatives Downloads and 
Videos Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
    Comment: A few commenters conveyed the importance of ensuring 
consistency in coding of discharge status codes across PAC settings, 
and requested a clear definition of community discharge for purposes of 
this measure.
    Response: This measure captures discharges to home and community 
based settings, with or without home health services. Community, for 
this measure, is defined as Patient Discharge Status codes 01, 06, 81, 
and 86 on the PAC claim. Code 01 refers to discharge to home or self 
care; Code 06 refers to discharge with home health services; Code 81 
refers to discharge to home or self care with a planned acute care 
readmission; and Code 86 refers to discharge with home health services 
with a planned acute care readmission. We refer readers to the National 
Uniform Billing Committee Data Specifications Manual for coding 
instructions.\61\ For further details on measure specifications, 
including the definition of community, we refer readers to the Measure 
Specifications for Measures Adopted in the FY 2017 IRF QRP final rule, 
posted on the CMS IRF QRP Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.
---------------------------------------------------------------------------

    \61\ National Uniform Billing Committee Official UB-04 Data 
Specifications Manual 2017, Version 11, July 2016, Copyright 2016, 
American Hospital Association.
---------------------------------------------------------------------------

    Comment: Some commenters were concerned about overlap between the 
discharge to community and readmissions measures, specifically 
expressing concern that a single post-discharge readmission would 
affect a facility's performance on two measures. One commenter 
expressed that the discharge to community measure essentially 
functioned as a readmission measure, and that different definitions of 
readmissions could be confusing for providers and patients, lead to 
unintended differences in the data CMS receives, and skew the data. One 
commenter indicated that the IMPACT Act measures overemphasized 
reducing readmissions and did not adequately address the domains they 
are meant to measure. This commenter suggested that quality measures 
should exclude aspects measured by other domains and/or quality 
measures, and instead should measure unique domains. This commenter 
further recommended that the Secretary suspend this measure until CMS 
can evaluate whether the inclusion of readmissions within each quality 
measure is necessary, and whether it produces duplicative results 
within the various quality reporting programs.
    Response: There are distinct differences between the discharge to 
community and readmission measures under the IRF QRP. Although there 
may be some overlap in the outcomes captured across the two measures 
(for example, patients who have a post-discharge readmission also have 
an unsuccessful discharge to community), the discharge to community and 
readmission measures each have a distinct purpose, outcome definition, 
and measure population. For example, the discharge to community measure 
assesses the rate of successful discharges to the community, defined as 
discharge to a community setting without post-discharge unplanned 
readmissions or death, while the readmission measures assess the rate 
of readmissions for patients discharged to lower levels of care from 
the IRF.
    Our goal is to develop measures that are meaningful to patients and 
consumers, and assist them in making informed choices when selecting 
post-acute providers. Since the goal of PAC for most patients and 
family members is to be discharged to the community and remain in the 
community, from a patient/consumer perspective, it is important to 
assess whether a patient remained in the community after discharge and 
to separately report discharge to community rates. In addition to 
assessing the success of community discharges, the inclusion of post-
discharge readmission and death outcomes in this measure is intended to 
avoid the potential unintended consequence of inappropriate discharges 
to the community.
    Comment: Several commenters expressed concern that the discharge to 
community measure holds IRFs accountable for post-discharge adverse 
outcomes, including unplanned readmissions and death. Commenters 
expressed that IRFs have little control

[[Page 52101]]

over patient behavior or adherence once the patient is discharged from 
the facility, and should not be penalized for post-discharge events. We 
received recommendations to exclude patients who have been discharged 
to the community and then expire within the post-discharge window; this 
recommendation was based on the explanation that the types of patients 
treated in IRFs greatly varied and that including post-discharge death 
in the measure could lead to an inaccurate reflection of the quality of 
care furnished by the IRF.
    Response: We monitor 31-day post-discharge unplanned readmissions 
and death in the measure to more accurately capture successful 
discharge to community outcomes, and to avoid the potential unintended 
consequence of inappropriate discharges to the community. We expect 
that improved care transitions and care coordination across providers 
will reduce these post-discharge adverse outcomes. Members of our TEP 
unanimously believed that the definition of discharge to community 
should be broader than discharge destination alone, and should 
incorporate indicators of post-discharge patient outcomes. TEP members 
agreed with the inclusion of both post-discharge readmissions and death 
in the discharge to community measure.
    We found, through our analyses in our measure development sample, 
that death in the 31 days following discharge to community is an 
infrequent event, with only 0.9 percent of IRF Medicare FFS 
beneficiaries dying during that period. By risk adjusting for prior 
service use (that is, number of hospitalizations in the past year), our 
intent is to adjust for patient characteristics, such as access, 
patient compliance, or sociodemographic and socioeconomic factors that 
may influence the likelihood of post-discharge readmissions. 
Additionally, by excluding patients discharged against medical advice 
from the measure, we are excluding patients who demonstrate non-
compliance or non-adherence during the PAC stay.
    We would like to note that we do not expect facilities to achieve a 
0 percent readmission or death rate in the measure's post-discharge 
observation window; the focus is to identify facilities with 
unexpectedly high rates of unplanned readmissions and death for quality 
monitoring purposes.
    Comment: Multiple commenters suggested that the measure include 
risk adjustment for sociodemographic factors such as home and community 
caregivers and supports, and socioeconomic factors of patients and 
communities.
    Response: We understand the importance of home and community 
supports, sociodemographic factors, and socioeconomic factors in 
ensuring a successful discharge to community outcome. The discharge to 
community measure is a claims-based measure in its first phase of 
development. Currently, there are no standardized data on variables 
such as living status or family and caregiver supports across the four 
PAC settings. As we refine the measure in the future, we will consider 
testing and adding additional relevant data sources and standardized 
items for risk adjustment of this measure. We refer readers to section 
VIII.F of this final rule for a more detailed discussion of the role of 
SES/SDS factors in risk adjustment of our measures.
    Comment: A few commenters emphasized the relationship between 
functional gains during the IRF stay and the ability to discharge to 
the community, stating that functional status measures are important 
indicators of recovery and achievement of rehabilitation goals and 
should be more intimately embedded in the proposed discharge to 
community measure. One commenter stated that return to one's previous 
home represents part of the goal of care. The commenter noted that, 
additionally, it is also important that the patient is able to function 
to the greatest possible extent in the home and community setting and 
achieve the highest quality of life possible. The commenter recommended 
that CMS delay adopting this measure until it incorporated metrics that 
assess whether patients achieved their functional and independence 
goals based on their plan of care and their specific condition.
    Multiple commenters suggested that the measure include risk 
adjustment for functional status in all settings, as it is closely 
associated with patients' discharge destination. One commenter noted 
that functional status is associated with increased risk of 30-day all-
cause hospital readmissions, and since readmissions and discharge to 
community are closely related, functional status risk adjustment is 
also important for this measure. One commenter suggested that the SNF 
and LTCH measures include risk adjustment that is similar to the risk 
adjustment for CMGs in the IRF setting and Activities of Daily Living 
in the HHA setting. One commenter interpreted the measure proposal as 
stating that CMS will not adjust the quality measures, including the 
discharge to community measure, to account for functional status of 
beneficiaries until such data are collected under the IMPACT Act.
    Response: We agree that it is important to assess various aspects 
of patient outcomes that are indicative of successful discharge from 
the IRF setting. We also agree that functional status may be related to 
discharge to community outcomes, and that it is important to test 
admission functional status risk adjustment when assessing discharge to 
community outcomes. The discharge to community measure does include 
functional status risk adjustment in the IRF setting using CMGs from 
claims, and in the home health setting using Activities of Daily Living 
from claims.
    As mandated by the IMPACT Act, we are moving toward the goal of 
collecting standardized patient assessment data for functional status 
across PAC settings. The IRF QRP includes five NQF-endorsed functional 
status quality measures, with a data collection start date of October 
1, 2016. Two measures are related to mobility functional outcomes, two 
are related to self-care functional outcomes, and one is a process 
measure. Once standardized functional status data become available 
across settings, it is our intent to use these data to assess patients' 
functional gains during their PAC stay, and to examine the relationship 
between functional status, discharge destination, and patients' ability 
to discharge to the community. As we examine these relationships 
between functional outcomes and discharge to community outcomes in the 
future, we will assess the feasibility of leveraging these standardized 
patient assessment data to incorporate functional outcomes into the 
discharge to community measure. Standardized cross-setting patient 
assessment data will also allow us to examine interrelationships 
between the quality and resource use measures in each PAC setting, and 
to understand how these measures are correlated.
    Comment: One commenter questioned the appropriateness of using HCCs 
for risk adjustment in the new quality measures proposed for the IRF 
QRP. The commenters noted that HCCs were initially developed for 
setting payment benchmarks for the Medicare Advantage program, and 
broad application of HCCs across quality measures may be beyond the 
scope of their appropriate use. The commenter cited reports suggesting 
that the HCC risk model was inaccurate at cost-estimation, and 
recommended that CMS reconsider the validity and reliability of the HCC 
risk-adjustment model. The commenter suggested that CMS instead develop 
a refined model that encompasses the diversity and complexity of PAC 
patients to a greater

[[Page 52102]]

extent, and is more sensitive to their levels of resource use.
    Response: We agree that comorbidities are important risk adjusters 
when examining quality and resource use measures. The HCCs were 
developed to separate clinically-related codes by Medicare utilization 
implications; they represent diagnosis-based, clinically meaningful 
clusters of ICD codes that have also been grouped by cost implications. 
When we apply HCCs for risk adjustment of quality or resources use 
measures, we do not use the HCC models applied to payment. In our 
measure development, we typically test individual HCCs that are 
relevant to the outcome of interest; we estimate the effects of the 
individual HCCs or clusters on the dependent variable in the particular 
model and retain those that are significant or meaningful predictors of 
outcomes. We believe that risk adjusting for individual HCCs or small 
clusters provides greater sensitivity than using a single comorbidity 
index, which is based on selected diagnoses. Our approach accounts for 
an average effect for each comorbidity or comorbidity group, rather 
than an overall burden of comorbidities.
    The HCCs are more comprehensive than the simpler diagnosis-based 
systems, such as the Elixhauser Comorbidity Index or Charlson 
Comorbidity Index, which were targeted for predicting specific outcomes 
(for example, hospital mortality). We believe that HCCs provide a good 
representation of health risk, and their use to examine outcomes other 
than costs is supported in the literature.62 63 A study 
comparing the ability of five comorbidity indices to predict discharge 
functional status of IRF patients found that HCCs slightly outperformed 
other comorbidity indices.\64\ The superior performance of HCCs was 
hypothesized to be related to the inclusion of more medical conditions, 
and the inclusion of more ICD codes per condition in HCCs, making them 
a slightly more sensitive index for predicting clinical outcomes 
compared with other comorbidity indices.\65\
---------------------------------------------------------------------------

    \62\ Li P, Kim MM, Doshi JA. Comparison of the performance of 
the CMS Hierarchical Condition Category (CMS-HCC) risk adjuster with 
the Charlson and Elixhauser comorbidity measures in predicting 
mortality. BMC Health Serv Res. 2010 Aug 20;10:245. doi: 10.1186/
1472-6963-10-245.
    \63\ Kumar A, Graham JE, Resnik L, Karmarkar AM, Tan A, Deutsch 
A, Ottenbacher KJ. Comparing Comorbidity Indices to Predict Post-
Acute Rehabilitation Outcomes in Older Adults. Am J Phys Med 
Rehabil. 2016 May 4. [Epub ahead of print]
    \64\ Ibid.
    \65\ Ibid.
---------------------------------------------------------------------------

    We have successfully used HCCs as risk adjusters in several other 
quality measures, such as the readmissions and functional status 
measures for post-acute care. We have found HCCs to be significant and 
important predictors of outcomes across these quality measures.
    Comment: One commenter stated that ventilator use is included as a 
risk adjuster in the LTCH setting only, but should be used across all 
settings. This commenter also requested information on the hierarchical 
logistic regression modeling and variables that will be used for risk 
adjustment.
    Response: We would like to clarify that risk adjustment for 
ventilator use is included in both LTCH and SNF settings. We 
investigated the need for risk adjustment for ventilator use in IRFs, 
but found that less than 0.01 percent of the IRF population (19 patient 
stays in 2012, and 9 patient stays in 2013) had ventilator use in the 
IRF. Given the low frequency of ventilator use in IRFs, any associated 
estimates would not be reliable, and therefore, ventilator use is not 
included as a risk adjuster in the IRF setting measure. However, we 
will continue to assess this risk adjuster for inclusion in the IRF 
model for this measure.
    For details on measure specifications, modeling, and calculations, 
we refer readers to the Measure Specifications for Measures Adopted in 
the FY 2017 IRF QRP final rule, posted on the CMS IRF QRP Web page at 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.
    Comment: Two commenters requested clarification on the dual status 
of IRFs as qualifying hospitals for the purposes of the SNF ``3-Day 
Stay'' rule, and PAC providers for purposes of the discharge to 
community measure. Specifically, the commenters questioned whether a 
discharge from a SNF back to an IRF would count as a readmission under 
this measure (and thus result in a ``failed'' community discharge for 
the SNF), or whether it would only count as a non-community discharge.
    Response: For the discharge to community measure, a PAC stay must 
be preceded by an acute care stay in the past 30 days to be included in 
the measure. IRF stays are not considered qualifying stays for the 
purposes of inclusion in the discharge to community measure. When 
examining discharge destination from PAC, a discharge to an IRF would 
be considered a non-community discharge. Additionally, in the current 
measure specification, if a patient is discharged from PAC to the 
community and has a subsequent IRF admission in the post-discharge 
observation window, this IRF admission does not translate into a failed 
community discharge. In future measure work, we will assess the impact 
of flagging IRF admissions in the post-discharge window as failed 
discharges to community.
    Comment: One commenter encouraged CMS to provide PAC settings with 
access to measure performance data as early as possible so providers 
have time to adequately review these data, and implement strategies to 
decrease readmissions where necessary.
    Response: We intend to provide initial confidential feedback to PAC 
providers, prior to public reporting of this measure, based on Medicare 
FFS claims data from discharges in CY 2015 and 2016.
    Comment: A few commenters were concerned about potential unintended 
consequences associated with perceived conflicting incentives of 
measures within the IRF QRP. One commenter noted that while the 
discharge to community measure may incentivize IRFs to discharge 
patients with home health services in order to continue their recovery 
and function in a safe, lower cost setting, the MSPB measure may create 
an opposite incentive for IRFs to avoid the use of home health to 
reduce post-discharge resource utilization. Another commenter conveyed 
that IRFs may not be incentivized to discharge patients to the 
community as there is a risk of post-discharge readmissions affecting 
their measure performance. The commenter expressed that decreased 
discharge to community rates may result in increased costs.
    Response: We expect that, on average, discharges to community 
settings rather than institutional settings, will result in lower 
healthcare costs. We choose measures for our quality reporting programs 
that reflect patient-centeredness, and assess healthcare outcomes and 
utilization that may be indicators of poor quality of care or 
inefficient resource use. As with all our measures, we will monitor for 
unintended consequences as part of measure monitoring and evaluation to 
ensure that measures do not reduce quality of care or access for 
patients.
    Comment: Several commenters expressed concern that the discharge to 
community measure had not been endorsed by the NQF, and had not been 
fully developed and tested when presented to the NQF MAP. Some 
commenters recommended that CMS delay measure implementation and seek

[[Page 52103]]

NQF endorsement before measure adoption, while others recommended that 
CMS submit the measures for NQF endorsement as soon as feasible after 
measure adoption. A few commenters suggested that CMS obtain the 
support of a TEP before deciding whether to implement new quality 
measures, and that the TEP include IRF setting representatives.
    Response: We would like to clarify that the discharge to community 
measure has been fully developed and tested. We plan to submit the 
Discharge to Community-PAC IRF QRP measure to the NQF for consideration 
for endorsement.
    As with all measure development, our measure development contractor 
held three TEP meetings to seek input to guide development of the 
Discharge to Community measure. The TEP represented members of IRF, 
LTCH, SNF and home health agency settings. A summary of the TEP 
proceedings is available on the PAC Quality Initiatives Downloads and 
Videos Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html. TEP members 
were very supportive of the discharge to community measure concept 
across all PAC settings. We incorporated various TEP member 
recommendations into the measure specifications.
    Final Decision: After careful consideration of the public comments, 
we are finalizing our proposal to adopt the measure, Discharge to 
Community-PAC IRF QRP as a Medicare FFS claims-based measure for the FY 
2018 payment determination and subsequent years, with the added 
exclusion of patients with a hospice benefit in the 31-day post-
discharge observation window.
    For measure specifications, we refer readers to the Measure 
Specifications for Measures Adopted in the FY 2017 IRF QRP final rule, 
posted on the CMS IRF QRP Web site at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.
3. Measure To Address the IMPACT Act Domain of Resource Use and Other 
Measures: Potentially Preventable 30-Day Post-Discharge Readmission 
Measure for Inpatient Rehabilitation Facility Quality Reporting Program
    Sections 1899B(a)(2)(E)(ii) and 1899B(d)(1)(C) of the Act require 
the Secretary to specify measures to address the domain of all-
condition risk-adjusted potentially preventable hospital readmission 
rates by SNFs, LTCHs, and IRFs by October 1, 2016, and HHAs by January 
1, 2017. We proposed the measure Potentially Preventable 30-Day Post-
Discharge Readmission Measure for IRF QRP as a Medicare FFS claims-
based measure to meet this requirement for the FY 2018 payment 
determination and subsequent years.
    The measure assesses the facility-level risk-standardized rate of 
unplanned, potentially preventable hospital readmissions for Medicare 
FFS beneficiaries in the 30 days post IRF discharge. The IRF admission 
must have occurred within up to 30 days of discharge from a prior 
proximal hospital stay which is defined as an inpatient admission to an 
acute care hospital (including IPPS, CAH, or a psychiatric hospital). 
Hospital readmissions include readmissions to a short-stay acute-care 
hospital or an LTCH, with a diagnosis considered to be unplanned and 
potentially preventable. This measure is claims-based, requiring no 
additional data collection or submission burden for IRFs. Because the 
measure denominator is based on IRF admissions, each Medicare 
beneficiary may be included in the measure multiple times within the 
measurement period. Readmissions counted in this measure are identified 
by examining Medicare FFS claims data for readmissions to either acute 
care hospitals (IPPS or CAH) or LTCHs that occur during a 30-day window 
beginning 2 days after IRF discharge. This measure is conceptualized 
uniformly across the PAC settings, in terms of the measure definition, 
the approach to risk adjustment, and the measure calculation. Our 
approach for defining potentially preventable hospital readmissions is 
described in more detail below.
    Hospital readmissions among the Medicare population, including 
beneficiaries that utilize PAC, are common, costly, and often 
preventable.66 67 MedPAC and a study by Jencks et al. 
estimated that 17 to 20 percent of Medicare beneficiaries discharged 
from the hospital were readmitted within 30 days. MedPAC found that 
more than 75 percent of 30-day and 15-day readmissions and 84 percent 
of 7-day readmissions were considered ``potentially preventable.'' \68\ 
In addition, MedPAC calculated that annual Medicare spending on 
potentially preventable readmissions were $12 billion for 30-day, $8 
billion for 15-day, and $5 billion for 7-day readmissions in 2005.\69\ 
For hospital readmissions from one post-acute care setting, SNFs, 
MedPAC deemed 76 percent of these readmissions as ``potentially 
avoidable''-associated with $12 billion in Medicare expenditures.\70\ 
Mor et al. analyzed 2006 Medicare claims and SNF assessment data 
(Minimum Data Set), and reported a 23.5 percent readmission rate from 
SNFs, associated with $4.3 billion in expenditures.\71\ Fewer studies 
have investigated potentially preventable readmission rates from the 
remaining post-acute care settings.
---------------------------------------------------------------------------

    \66\ Friedman, B., and Basu, J.: The rate and cost of hospital 
readmissions for preventable conditions. Med. Care Res. Rev. 
61(2):225-240, 2004. doi:10.1177/1077558704263799.
    \67\ Jencks, S.F., Williams, M.V., and Coleman, E.A.: 
Rehospitalizations among patients in the Medicare Fee-for-Service 
Program. N. Engl. J. Med. 360(14):1418-1428, 2009. doi:10.1016/
j.jvs.2009.05.045.
    \68\ MedPAC: Payment policy for inpatient readmissions, in 
Report to the Congress: Promoting Greater Efficiency in Medicare. 
Washington, DC, pp. 103-120, 2007. Available from http://www.medpac.gov/documents/reports/Jun07_EntireReport.pdf.
    \69\ ibid.
    \70\ ibid.
    \71\ Mor, V., Intrator, O., Feng, Z., et al.: The revolving door 
of rehospitalization from skilled nursing facilities. Health Aff. 
29(1):57-64, 2010. doi:10.1377/hlthaff.2009.0629.
---------------------------------------------------------------------------

    We have addressed the high rates of hospital readmissions in the 
acute care setting as well as in PAC. For example, we developed the 
following measure: All-Cause Unplanned Readmission Measure for 30 Days 
Post-Discharge from IRFs (NQF #2502), as well as similar measures for 
other PAC providers (NQF #2512 for LTCHs and NQF #2510 for SNFs).\72\ 
These measures are endorsed by the NQF, and the NQF-endorsed IRF 
measure (NQF #2502) was adopted into the IRF QRP in the FY 2016 IRF PPS 
final rule (80 FR 47087 through 47089). Note that these NQF-endorsed 
measures assess all-cause unplanned readmissions.
---------------------------------------------------------------------------

    \72\ National Quality Forum: All-Cause Admissions and 
Readmissions Measures. pp. 1-319, April 2015. Available from http://www.qualityforum.org/Publications/2015/04/All-Cause_Admissions_and_Readmissions_Measures_-_Final_Report.aspx.
---------------------------------------------------------------------------

    Several general methods and algorithms have been developed to 
assess potentially avoidable or preventable hospitalizations and 
readmissions for the Medicare population. These include the Agency for 
Healthcare Research and Quality's (AHRQ's) Prevention Quality 
Indicators, approaches developed by MedPAC, and proprietary approaches, 
such as the 3M\TM\ algorithm for Potentially Preventable 
Readmissions.73 74 75 Recent

[[Page 52104]]

work led by Kramer et al. for MedPAC identified 13 conditions for which 
readmissions were deemed as potentially preventable among SNF and IRF 
populations.76 77 Although much of the existing literature 
addresses hospital readmissions more broadly and potentially avoidable 
hospitalizations for specific settings like long-term care, these 
findings are relevant to the development of potentially preventable 
readmission measures for PAC.78 79 80
---------------------------------------------------------------------------

    \73\ Goldfield, N.I., McCullough, E.C., Hughes, J.S., et al.: 
Identifying potentially preventable readmissions. Health Care Finan. 
Rev. 30(1):75-91, 2008. Available from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4195042/.
    \74\ National Quality Forum: Prevention Quality Indicators 
Overview. 2008.
    \75\ MedPAC: Online Appendix C: Medicare Ambulatory Care 
Indicators for the Elderly. pp. 1-12, prepared for Chapter 4, 2011. 
Available from http://www.medpac.gov/documents/reports/Mar11_Ch04_APPENDIX.pdf?sfvrsn=0.
    \76\ Kramer, A., Lin, M., Fish, R., et al.: Development of 
Inpatient Rehabilitation Facility Quality Measures: Potentially 
Avoidable Readmissions, Community Discharge, and Functional 
Improvement. pp. 1-42, 2015. Available from http://www.medpac.gov/documents/contractor-reports/development-of-inpatient-rehabilitation-facility-quality-measures-potentially-avoidable-readmissions-community-discharge-and-functional-improvement.pdf?sfvrsn=0.
    \77\ Kramer, A., Lin, M., Fish, R., et al.: Development of 
Potentially Avoidable Readmission and Functional Outcome SNF Quality 
Measures. pp. 1-75, 2014. Available from http://www.medpac.gov/documents/contractor-reports/mar14_snfqualitymeasures_contractor.pdf?sfvrsn=0.
    \78\ Allaudeen, N., Vidyarthi, A., Maselli, J., et al.: 
Redefining readmission risk factors for general medicine patients. 
J. Hosp. Med. 6(2):54-60, 2011. doi:10.1002/jhm.805.
    \79\ \4\ Gao, J., Moran, E., Li, Y.-F., et al.: Predicting 
potentially avoidable hospitalizations. Med. Care 52(2):164-171, 
2014. doi:10.1097/MLR.0000000000000041.
    \80\ Walsh, E.G., Wiener, J.M., Haber, S., et al.: Potentially 
avoidable hospitalizations of dually eligible Medicare and Medicaid 
beneficiaries from nursing facility and home[hyphen]and 
community[hyphen]based services waiver programs. J. Am. Geriatr. 
Soc. 60(5):821-829, 2012. doi:10.1111/j.1532-5415.2012.03920.x.
---------------------------------------------------------------------------

    Potentially Preventable Readmission Measure Definition: We 
conducted a comprehensive environmental scan, analyzed claims data, and 
obtained input from a TEP to develop a definition and list of 
conditions for which hospital readmissions are potentially preventable. 
The Ambulatory Care Sensitive Conditions and Prevention Quality 
Indicators, developed by AHRQ, served as the starting point in this 
work. For patients in the 30-day post-PAC discharge period, a 
potentially preventable readmission refers to a readmission for which 
the probability of occurrence could be minimized with adequately 
planned, explained, and implemented post-discharge instructions, 
including the establishment of appropriate follow-up ambulatory care. 
Our list of PPR conditions is categorized by 3 clinical rationale 
groupings:
     Inadequate management of chronic conditions;
     Inadequate management of infections; and
     Inadequate management of other unplanned events.
    Additional details regarding the definition for potentially 
preventable readmissions are available in the document titled, Proposed 
Measure Specifications for Measures Proposed in the FY 2017 IRF QRP 
proposed rule, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.
    This measure focuses on readmissions that are potentially 
preventable and also unplanned. Similar to the All-Cause Unplanned 
Readmission Measure for 30 Days Post-Discharge from IRFs (NQF #2502), 
this measure uses the current version of the CMS Planned Readmission 
Algorithm as the main component for identifying planned readmissions. A 
complete description of the CMS Planned Readmission Algorithm, which 
includes lists of planned diagnoses and procedures, can be found on the 
CMS Web site http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html. 
In addition to the CMS Planned Readmission Algorithm, this measure 
incorporates procedures that are considered planned in post-acute care 
settings, as identified in consultation with TEPs. Full details on the 
planned readmissions criteria used, including the CMS Planned 
Readmission Algorithm and additional procedures considered planned for 
post-acute care, can be found in the document titled, Proposed Measure 
Specifications for Measures Proposed in the FY 2017 IRF QRP proposed 
rule, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.
    The measure, Potentially Preventable 30-Day Post-Discharge 
Readmission Measure for IRF QRP, assesses potentially preventable 
readmission rates while accounting for patient demographics, principal 
diagnosis in the prior hospital stay, comorbidities, and other patient 
factors. While estimating the predictive power of patient 
characteristics, the model also estimates a facility-specific effect, 
common to patients treated in each facility. This measure is calculated 
for each IRF based on the ratio of the predicted number of risk-
adjusted, unplanned, potentially preventable hospital readmissions that 
occur within 30 days after an IRF discharge, including the estimated 
facility effect, to the estimated predicted number of risk-adjusted, 
unplanned inpatient hospital readmissions for the same patients treated 
at the average IRF. A ratio above 1.0 indicates a higher than expected 
readmission rate (worse) while a ratio below 1.0 indicates a lower than 
expected readmission rate (better). This ratio is referred to as the 
standardized risk ratio (SRR). The SRR is then multiplied by the 
overall national raw rate of potentially preventable readmissions for 
all IRF stays. The resulting rate is the risk-standardized readmission 
rate (RSRR) of potentially preventable readmissions.
    An eligible IRF stay is followed until: (1) The 30-day post-
discharge period ends; or (2) the patient is readmitted to an acute 
care hospital (IPPS or CAH) or LTCH. If the readmission is unplanned 
and potentially preventable, it is counted as a readmission in the 
measure calculation. If the readmission is planned, the readmission is 
not counted in the measure rate. This measure is risk adjusted. The 
risk adjustment modeling estimates the effects of patient 
characteristics, comorbidities, and select health care variables on the 
probability of readmission. More specifically, the risk-adjustment 
model for IRFs accounts for demographic characteristics (age, sex, 
original reason for Medicare entitlement), principal diagnosis during 
the prior proximal hospital stay, body system specific surgical 
indicators, IRF case-mix groups which capture motor function, 
comorbidities, and number of acute care hospitalizations in the 
preceding 365 days.
    The measure is calculated using 2 consecutive calendar years of FFS 
claims data, to ensure the statistical reliability of this measure for 
facilities. In addition, we proposed a minimum of 25 eligible stays for 
public reporting of the measure.
    A TEP convened by our measure contractor provided recommendations 
on the technical specifications of this measure, including the 
development of an approach to define potentially preventable hospital 
readmission for PAC. Details from the TEP meetings, including TEP 
members' ratings of conditions proposed as being potentially 
preventable, are available in the TEP summary report available on the 
CMS Web site at https://www.cms.gov/Medicare/Quality-Initiatives-
Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/
IMPACT-Act-of-2014/

[[Page 52105]]

IMPACT-Act-Downloads-and-Videos.html. We also solicited stakeholder 
feedback on the development of this measure through a public comment 
period held from November 2 through December 1, 2015. Comments on the 
measure varied, with some commenters supportive of the measure, while 
others either were not in favor of the measure, or suggested potential 
modifications to the measure specifications, such as including 
standardized function data. A summary of the public comments is also 
available on our Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
    The MAP encouraged continued development of the proposed measure. 
Specifically, the MAP stressed the need to promote shared 
accountability and ensure effective care transitions. More information 
about the MAP's recommendations for this measure is available at http://www.qualityforum.org/Publications/2016/02/MAP_2016_Considerations_for_Implementing_Measures_in_Federal_Programs_-_PAC-LTC.aspx. At the time, the risk-adjustment model was still under 
development. Following completion of that development work, we were 
able to test for measure validity and reliability as identified in the 
measure specifications document provided above. Testing results are 
within range for similar outcome measures finalized in public reporting 
and value-based purchasing programs, including the All-Cause Unplanned 
Readmission Measure for 30 Days Post Discharge from IRFs (NQF #2502) 
adopted into the IRF QRP.
    We reviewed the NQF's consensus endorsed measures and were unable 
to identify any NQF-endorsed measures focused on potentially 
preventable hospital readmissions. We are unaware of any other measures 
for this IMPACT Act domain that have been endorsed or adopted by other 
consensus organizations. Therefore, we proposed the Potentially 
Preventable 30-Day Post-Discharge Readmission Measure for IRF QRP, 
under the Secretary's authority to specify non-NQF-endorsed measures 
under section 1899B(e)(2)(B) of the Act, for the IRF QRP for the FY 
2018 payment determination and subsequent years, given the evidence 
previously discussed above.
    We plan to submit the measure to the NQF for consideration of 
endorsement. We stated in the proposed rule that we intended to provide 
initial confidential feedback to providers, prior to public reporting 
of this measure, based on 2 calendar years of data from discharges in 
CY 2015 and 2016. We also stated that we intended to publicly report 
this measure using data from CY 2016 and 2017.
    We invited public comment on our proposal to adopt the measure, 
Potentially Preventable 30-Day Post-Discharge Readmission Measure for 
IRF QRP. We received several comments, which are summarized with our 
responses below.
    Comment: We received several comments in support of the proposed 
Potentially Preventable 30-Day Post-Discharge Readmission Measure for 
IRF QRP. In particular, MedPAC supported this measure and believes that 
IRFs should be held accountable for readmissions in the post-discharge 
readmission window. Some commenters preferred a potentially preventable 
readmission measure over an all-cause readmission measure.
    Response: We thank commenters for their support of this measure.
    Comment: One commenter specifically supported the inclusion of 
infectious conditions in the inadequate management of infections and 
inadequate management of other unplanned events categories in the 
measure's definition of potentially preventable hospital readmissions. 
Another commenter expressed concern over being ``penalized'' for 
readmissions that are clinically unrelated to a patient's original 
reason for IRF admission. One commenter recommended that CMS continue 
evaluating and testing the measure to ensure that the codes used for 
the PPR definition are clinically relevant. Another commenter expressed 
concern over using DRGs as the basis for defining the reasons for 
receiving inpatient rehabilitation or the reason for a subsequent 
hospital readmission given variation in coding practices in acute care 
hospitals.
    Response: As described in the proposed rule, the definition for 
potentially preventable readmissions for this measure was developed 
based on existing evidence and was vetted by a TEP, which included 
clinicians and post-acute care experts. We also conducted a 
comprehensive environmental scan to identify conditions for which 
readmissions may be considered potentially preventable. Results of this 
environmental scan and details of the TEP input received were made 
available in the PPR TEP summary report available on the CMS Web site 
at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html. We also solicited stakeholder 
feedback on the development of this measure through a public comment 
period held from November 2 through December 1, 2015. Comments on the 
measure varied, with some commenters supportive of the proposed 
measure, while others either were not in favor of the measure, or 
suggested potential modifications to the measure specifications, such 
as including standardized function data. A summary of the public 
comments is also available on the CMS Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
    Though readmissions may be considered potentially preventable even 
if they may not appear to be clinically related to the patient's 
original reason for IRF admission, there is substantial evidence that 
the conditions included in the definition may be preventable with 
adequately planned, explained, and implemented post-discharge 
instructions, including the establishment of appropriate follow-up 
ambulatory care. Furthermore, this measure is based on Medicare FFS 
claims data and it may not always be feasible to determine whether a 
subsequent readmission is or is not clinically related to the reason 
why the patient was receiving inpatient rehabilitation. We intend to 
conduct ongoing evaluation and monitoring of this measure, and will 
take these comments into consideration.
    With regard to the comment related to DRGs, we wish to clarify that 
this measure does not use hospital DRGs to define PPRs or in the risk 
adjustment. Potentially preventable hospital readmissions are defined 
by the principal diagnosis on the readmission claim. Our risk-
adjustment model uses diagnoses (not DRGs) from the prior hospital 
claim as risk adjusters. Though there may be variation in coding 
practices, claims data are the most reliable source to identify 
potentially preventable hospital readmissions post-IRF discharge. We 
would also like to clarify that the reason for receiving inpatient 
rehabilitation is captured as a risk adjuster by the use of the IRF PPS 
CMGs which also incorporate the RICs as well as function.
    Comment: Several commenters expressed support for the cross-setting 
standardization of the inclusion and exclusion criteria for the PPR 
measures. MedPAC and another commenter

[[Page 52106]]

commented that the measure definition and risk adjustment should be 
identical across PAC settings so that potentially preventable 
readmission rates can be compared across settings. One commenter 
expressed concern over the ``nonalignment'' specifically between the 
IRF and SNF versions of the measure, adding that this may lead to 
confusion. Another commenter suggested a single or harmonized measure 
to better inform patients, caregivers, and payers. One comment 
encouraged CMS to assess readmission measures across the agency's 
programs to ensure that they promote collaboration and support 
readmission reduction efforts.
    Response: The PPR definition (that is, list of conditions for which 
readmissions would be considered potentially preventable) is aligned 
for measures with the same readmission window, regardless of PAC 
setting. Specifically, the post-PAC discharge PPR measures that were 
developed for each of the PAC settings contain the same list of PPR 
conditions. Although there are some minor differences in the 
specifications across these potentially preventable readmissions 
measures (for example, years of data used to calculate the measures to 
ensure reliability and some of the measure exclusions necessary to 
attribute responsibility to the individual settings), the IMPACT Act 
PPR measures are standardized. As described for all IMPACT Act measures 
in section VIII.B in this final rule, the statistical approach for risk 
adjustment is also aligned across the measures; however, there is 
variation in the exact risk adjusters. The risk-adjustment models are 
empirically driven and differ between measures as a consequence of case 
mix differences, which is necessary to ensure that the estimates are 
valid. We appreciate the comment that the readmission measures across 
our programs be assessed to ensure they promote collaboration and 
support readmission reduction efforts. As we continually evaluate and 
monitor the PAC quality reporting and other CMS programs, we will take 
the commenter's suggestion into consideration.
    Comment: Several commenters expressed concern that this measure 
would capture outcomes that are outside of PAC providers' control, 
specifically with respect to chronically ill patients, instances of 
poor patient compliance, unhealthy choices, and various SDS factors, 
such as lack of resources or limited access to follow up or primary 
care. One commenter also expressed concern over the added risk of 
caring for a high volume of transplant patients that other IRFs may 
choose not to admit. Another commenter noted that even though the risk 
adjustment will account for some of these circumstances, it is 
difficult for providers to fully evaluate the risk-adjustment model 
because the testing and risk-adjustment coefficients have not been 
finalized. A few commenters recommend these measures be suspended until 
CMS explains how the measures will treat each of these scenarios.
    Response: As noted by one commenter, the measure's comprehensive 
risk-adjustment approach and exclusion criteria are intended to capture 
many of these factors. As described above, there is substantial 
evidence that the conditions included in the definition may be 
preventable with adequately planned, explained, and implemented post-
discharge instructions, including the establishment of appropriate 
follow-up ambulatory care. We would like to clarify that the focus of 
the PPR measure is to identify excess PPR rates for the purposes of 
quality improvement.
    We would also like to clarify that the finalized risk-adjustment 
models and coefficients are included in the measure specifications 
available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.
    Comment: Several commenters expressed concern over the overlap 
between the proposed PPR measure and other IRF QRP measures, including 
the existing all-cause readmission measure. Commenters expressed 
concern that public reporting of more than one hospital readmission 
measure for IRFs may result in confusion among the public; the 
commenters also noted providers could face confusion over two distinct 
but similar measures, which could potentially pose challenges for 
quality improvement efforts. One commenter noted that the proposed PPR 
measures and the existing all-cause measure are distinct yet 
overlapping, adding that the PPR measure is a subset of the all-cause 
readmission measure. Given this overlap, one commenter was concerned 
that providers who perform poorly on the all-cause readmission measure 
are likely to do so for the proposed PPR measure as well, and suggested 
CMS suspend the measure until it could evaluate the necessity of each 
measure. Some commenters requested that CMS clarify the overlap and 
intent of these measures, and provide more education to providers and 
the public on the multiple IRF QRP readmission measures. Another 
commenter suggested that CMS conduct dry runs of the readmission 
measures, similar to those conducted for the all-cause measure.
    One commenter supported the use of Medicare claims data to 
calculate these measures because it does not require the submission of 
additional data by IRFs. Another commenter noted that despite the lack 
of a data collection burden for providers, multiple readmission 
measures in the program will create burden on the part of providers to 
track and improve performance. Another commenter expressed concern that 
the measures are ``extensive'' and will place additional financial 
burden on providers.
    Response: The All-Cause Unplanned Hospital Readmission Measure for 
30 Days Post-IRF Discharge (NQF #2502) was adopted for the IRF QRP 
prior to the IMPACT Act. The measure of potentially preventable 
hospital readmissions was developed in response to the statutory 
mandate of the IMPACT Act. We would like to clarify that providers are 
not held financially accountable for their performance on these 
measures, but only whether they report the necessary data for the IRF 
QRP.
    With regard to overlap with the existing IRF QRP readmission 
measure, retaining the all-cause measure will allow us to monitor 
trends in both all-cause and PPR rates in order to assess the extent to 
which changes in facility performance for one measure are reflected in 
the other. We are committed to ensuring that measures in the IRF QRP 
are useful in assessing quality and will continue to evaluate all 
readmission measures over time.
    We thank commenters for their feedback related to provider burden 
on the measure. We would like to note that the PPR measure uses 
Medicare claims data and is not collected by means of an assessment 
instrument. Therefore, the measure does not increase data collection 
burden on the provider as this data is currently collected by 
providers. Despite the lack of data collection burden, we appreciate 
the comments that more education will be required for the public and 
providers to understand the differences between the readmission 
measures in the IRF QRP.
    Comment: Several commenters raised concerns over the risk-
adjustment approach for the PPR measure. One commenter expressed 
concern that the HCC risk-adjustment method is insufficient at 
predicting costs for certain patient populations. The commenter 
suggested CMS research and develop a refined risk-adjustment model that 
encompasses more of the diversity

[[Page 52107]]

and complexity of PAC patients and is more sensitive to their levels of 
resource use. Several commenters expressed concern that the proposed 
measure is not adjusted for socio-economic factors, and a couple 
commenters, including MedPAC, suggested the use of peer group 
comparisons of performance rates to address this issue.
    Another commenter supported the proposed risk-adjustment 
methodology commenting it will provide a valid assessment of quality of 
care in preventing unplanned, preventable hospital readmissions. One 
commenter also suggested that, in addition to the measure exclusion for 
non-surgical treatment of cancer, that other conditions with similar 
disease trajectories be excluded from the measure, citing end-stage 
Multiple Sclerosis (MS), motor neuron disease, and Alzheimer's disease.
    Response: We would like to note that the measure is fully developed 
and the finalized risk-adjustment model and coefficients are included 
in the measure specifications available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.
    The HCCs were developed to separate clinically-related codes by 
Medicare utilization implications; they represent diagnosis-based, 
clinically meaningful clusters of ICD codes that have also been grouped 
by cost implications. When we apply HCCs for risk adjustment of quality 
or resources use measures, we do not use the HCC models applied to 
payment. In our measure development, we typically test individual HCCs 
that are relevant to the outcome of interest; we estimate the effects 
of the individual HCCs or clusters on the dependent variable in the 
particular model and retain those that are significant or meaningful 
predictors of outcomes. We believe that risk adjusting for individual 
HCCs or small clusters provides greater sensitivity than using a single 
comorbidity index, which is based on selected diagnoses. Our approach 
accounts for an average effect for each comorbidity or comorbidity 
group, rather than an overall burden of comorbidities.
    The HCCs are more comprehensive than the simpler diagnosis-based 
systems, such as the Elixhauser Comorbidity Index or Charlson 
Comorbidity Index, which were targeted for predicting specific outcomes 
(for example, hospital mortality). We believe that HCCs provide a good 
representation of health risk, and their use to examine outcomes other 
than costs is supported in the literature.81 82 A study 
comparing the ability of five comorbidity indices to predict discharge 
functional status of IRF patients found that HCCs slightly outperformed 
other comorbidity indices.\83\ The superior performance of HCCs was 
hypothesized to be related to the inclusion of more medical conditions 
in HCCs, and the inclusion of more ICD codes per condition in HCCs, 
making them a slightly more sensitive index for predicting clinical 
outcomes compared with other comorbidity indices.\84\
---------------------------------------------------------------------------

    \81\ Kumar A, Graham JE, Resnik L, Karmarkar AM, Tan A, Deutsch 
A, Ottenbacher KJ. Comparing Comorbidity Indices to Predict Post-
Acute Rehabilitation Outcomes in Older Adults. Am J Phys Med 
Rehabil. 2016 May 4. [Epub ahead of print]
    \82\ Li P, Kim MM, Doshi JA. Comparison of the performance of 
the CMS Hierarchical Condition Category (CMS-HCC) risk adjuster with 
the Charlson and Elixhauser comorbidity measures in predicting 
mortality. BMC Health Serv Res. 2010 Aug 20;10:245. doi: 10.1186/
1472-6963-10-245.
    \83\ Kumar A, Graham JE, Resnik L, Karmarkar AM, Tan A, Deutsch 
A, Ottenbacher KJ. Comparing Comorbidity Indices to Predict Post-
Acute Rehabilitation Outcomes in Older Adults. Am J Phys Med 
Rehabil. 2016 May 4. [Epub ahead of print]
    \84\ Kumar A, Graham JE, Resnik L, Karmarkar AM, Tan A, Deutsch 
A, Ottenbacher KJ. Comparing Comorbidity Indices to Predict Post-
Acute Rehabilitation Outcomes in Older Adults. Am J Phys Med 
Rehabil. 2016 May 4. [Epub ahead of print]
---------------------------------------------------------------------------

    We wish to clarify that the model included in the specifications 
using HCCs as risk adjusters for comorbidities posted for the proposed 
rule demonstrated sufficient discrimination power. The model had a c-
statistic of 0.74 which is within range, if not higher than, similar 
readmission measures finalized in public reporting programs, including 
the All-Cause Unplanned Readmission Measure for 30 Days Post-Discharge 
from IRFs (NQF #2502) previously adopted for the IRF QRP.
    With regard to the suggestions that the model include 
sociodemographic factors and the suggestion pertaining to an approach 
with which to convey data comparisons, we refer the readers to section 
VIII.F of this final rule where we also discuss these topics. In 
response to the suggestion to include additional conditions from the 
measure, such as end-stage MS, motor neuron disease, and Alzheimer's 
disease, we wish to clarify that we risk adjust for these clinical 
characteristics in our risk-adjustment model. These are low prevalence 
conditions and the claims data are limited in their ability to identify 
disease progression. However, we will take this suggestion into 
consideration.
    Comment: Several commenters expressed concern that the measures are 
not NQF-endorsed, and some had additional concerns over measure testing 
and development. Some of these commenters recommended that CMS should 
adopt measures endorsed by the NQF in quality reporting programs or 
recommended that CMS submit the measures through the NQF endorsement 
process as soon as feasible.
    Response: With regard to NQF endorsement, as noted in the proposed 
rule, we intend to submit this measure to NQF for consideration of 
endorsement. In addition, we noted that we reviewed the NQF's consensus 
endorsed measures and were unable to identify any NQF endorsed measures 
focused on potentially preventable hospital readmissions. We are 
unaware of any other measures for this IMPACT Act domain that have been 
endorsed or adopted by other consensus organizations. Therefore, we 
proposed the Potentially Preventable 30-Day Post-Discharge Readmission 
Measure for IRF QRP, under the Secretary's authority to specify non-NQF 
endorsed measures under section 1899B(e)(2)(B) of the Act, for the IRF 
QRP.
    We would also like to clarify that the finalized risk-adjustment 
models and coefficients are included in the measure specifications 
available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html. We will make additional testing 
results available in the future.
    We would like to clarify that the MAP encouraged continued 
development of the proposed measure. More information about the MAP's 
recommendations for this measure is available at http://www.qualityforum.org/Publications/2016/02/MAP_2016_Considerations_for_Implementing_Measures_in_Federal_Programs_-_PAC-LTC.aspx.
    Comment: Some commenters raised concerns over unintended 
consequences of the measure. One commenter was concerned that the 
measure could create an incentive for IRFs to be selective about the 
types of patients they admit (that is, ``cherry pick'' their patients) 
in order to reduce the risk of PPRs. Another comment suggested that 
IRFs should not be held accountable for IRF patients with planned 
procedures that are not admitted and treated as observation stays and 
requested that CMS provide clarification on how these types of patients 
will be assessed by the measure.
    Response: We intend to conduct ongoing monitoring to assess for 
potential unintended consequences

[[Page 52108]]

associated with the implementation of this measure and will take these 
suggestions into account.
    In response to the concern regarding holding an IRF accountable for 
planned procedures that are treated as observation stays instead of 
planned hospital readmissions, we appreciate the commenter's concern 
and expect that this is a relatively infrequent occurrence given that 
most of the planned procedures are invasive surgical procedures. The 
measure is of hospital readmissions and does not count planned 
procedures that are treated as observation stays. We will take this 
issue into consideration for future measure development.
    Comment: One commenter expressed concern over using claims data for 
hospital readmissions, noting that these data may not be accurate.
    Response: We appreciate the commenter's concern over the accuracy 
of claims data. However, we wish to clarify that claims data have been 
validated for the purposes of assessing hospital readmissions and are 
used for several NQF-endorsed measures adopted for CMS programs, 
including the IRF QRP. Multiple studies have been conducted to examine 
the validity of using Medicare hospital claims to calculate several 
NQF-endorsed quality measures for public 
reporting.85 86 87Additionally, although assessment and 
other data sources may be valuable for risk adjustment, we are not 
aware of any other data source aside from Medicare claims data that 
could be used to reliably assess potentially preventable hospital 
readmissions for this measure.
---------------------------------------------------------------------------

    \85\ Bratzler DW, Normand SL, Wang Y, et al. An administrative 
claims model for profiling hospital 30-day mortality rates for 
pneumonia patients. PLoS One 2011;6(4):e17401.
    \86\ Keenan PS, Normand SL, Lin Z, et al. An administrative 
claims measure suitable for profiling hospital performance on the 
basis of 30-day all-cause readmission rates among patients with 
heart failure. Circulation 2008;1(1):29-37.
    \87\ Krumholz HM, Wang Y, Mattera JA, et al. An administrative 
claims model suitable for profiling hospital performance based on 
30-day mortality rates among patients with heart failure. 
Circulation 2006;113:1693-1701.
---------------------------------------------------------------------------

    Final Decision: After careful consideration of the public comments, 
we are finalizing our proposal to adopt the measure, Potentially 
Preventable 30-Day Post-Discharge Readmission Measure for IRF QRP. 
Measure Specifications for Measures Adopted in the FY 2017 IRF QRP 
final rule are available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.
4. Potentially Preventable Within Stay Readmission Measure for 
Inpatient Rehabilitation Facilities
    In addition to the measure finalized in section VIII.F.3. of this 
final rule, Potentially Preventable 30-Day Post-Discharge Readmission 
Measure for IRF QRP, we proposed the Potentially Preventable Within 
Stay Readmission Measure for IRFs for the FY 2018 payment determination 
and subsequent years. This measure is similar to the Potentially 
Preventable 30-Day Post-Discharge Readmission Measure for IRF QRP; 
however, the readmission window for this measure focuses on potentially 
preventable hospital readmissions that take place during the IRF stay 
as opposed to during the 30-day post-discharge period. The two PPR 
measures are intended to function in tandem, covering readmissions 
during the IRF stay and for 30 days following discharge from the IRF. 
Utilizing two PPR measures in the IRF QRP will enable us to assess 
different aspects of care and care coordination. The within stay 
measure focuses on the care transition into inpatient rehabilitation as 
well as the care provided during the IRF stay, whereas the 30-day post-
IRF discharge measure focuses on transitions from the IRF into less-
intensive levels of care or the community.
    Similar to the Potentially Preventable 30-Day Post-Discharge 
Readmission Measure for IRF QRP measure for IRFs, this measure assesses 
the facility-level risk-standardized rate of unplanned, potentially 
preventable hospital readmissions during the IRF stay. Hospital 
readmissions include readmissions to a short-stay acute-care hospital 
or an LTCH, with a diagnosis considered to be unplanned and potentially 
preventable. This Medicare FFS measure is claims-based, requiring no 
additional data collection or submission burden for IRFs. As described 
in section VIII.F.3. of this final rule, we developed the approach for 
defining PPR measure based on a comprehensive environmental scan, 
analysis of claims data, and TEP input. Also, we obtained public 
comment.
    The definition for PPRs differs by readmission window. For the 
within-IRF stay window, PPRs should be avoidable with sufficient 
medical monitoring and appropriate patient treatment. The list of PPR 
conditions for the Potentially Preventable Within Stay Readmission 
Measure for IRFs are categorized by 4 clinical rationale groupings:
     Inadequate management of chronic conditions;
     Inadequate management of infections;
     Inadequate management of other unplanned events; and
     Inadequate injury prevention.
    Additional details regarding the definition for PPRs are available 
in our document titled, Proposed Measure Specifications for Measures 
Proposed in the FY 2017 IRF QRP proposed rule available on our Web site 
at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.
    Section VIII.F of this final rule discusses the relevant background 
and details that are also relevant for this measure. This measure 
defines planned readmissions in the same manner as described in section 
VIII.F.3 of this final rule, for the Potentially Preventable 30-Day 
Post-Discharge Readmission Measure for IRF QRP. In addition, similar to 
the Potentially Preventable 30-Day Post-Discharge Readmission Measure 
for IRF QRP measure, this measure uses the same risk-adjustment and 
statistical approach as described in section VIII.F.3 of this final 
rule. Note the full methodology is detailed in the document titled, 
Proposed Measure Specifications for Measures Proposed in the FY 2017 
IRF QRP proposed rule, at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html. This measure is 
also based on 2 consecutive calendar years of Medicare FFS claims data.
    A TEP convened by our measure contractor provided recommendations 
on the technical specifications of this measure, including the 
development of an approach to define potentially preventable hospital 
readmission for PAC. Details from the TEP meetings, including TEP 
members' ratings of conditions proposed as being potentially 
preventable, are available in the TEP Summary Report available on our 
Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html. We also solicited 
stakeholder feedback on the development of this measure through a 
public comment period held from November 2 through December 1, 2015. 
Comments on this and other PAC measures of PPR measures varied, with 
some commenters supportive of the proposed measure, while others either 
were not in favor of the measure, or suggested potential modifications 
to the

[[Page 52109]]

measure specifications, such as including standardized function data. A 
summary of our public comment period is also available on our Web site 
at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
    The MAP encouraged continued development of the proposed measure. 
Specifically, the MAP stressed the need to promote shared 
accountability and ensure effective care transitions. More information 
about the MAP's recommendations for this measure is available at http://www.qualityforum.org/Publications/2016/02/MAP_2016_Considerations_for_Implementing_Measures_in_Federal_Programs_-_PAC-LTC.aspx. At the time, the risk-adjustment model was still under 
development. Following completion of that development work, we were 
able to test for measure validity and reliability as described in the 
measure specifications document provided above. Testing results are 
within range for similar outcome measures finalized in public reporting 
and value-based purchasing programs, including the All-Cause Unplanned 
Readmission Measure for 30 Days Post-Discharge from IRFs (NQF #2502) 
that we previously adopted into the IRF QRP.
    We plan to submit the measure to the NQF for consideration of 
endorsement. We stated in the proposed rule that we intended to provide 
initial confidential feedback to providers, prior to public reporting 
of this measure, based on 2 calendar years of claims data from 
discharges in 2015 and 2016. We proposed a minimum of 25 eligible stays 
in a given IRF for public reporting of the measure for that IRF. We 
also stated that we intended to publicly report this measure using 
claims data from calendar years 2016 and 2017.
    We invited public comment on our proposal to adopt this measure, 
Potentially Preventable Within Stay Readmission Measure for IRFs. We 
received several comments, which are summarized with our responses 
below.
    Comment: CMS received comments in support of this measure. In 
particular, MedPAC supported this measure, and further suggested that 
it should be applied identically across the four PAC settings so that 
post-discharge rates can be meaningfully compared.
    Response: We wish to clarify that this particular measure, 
developed and proposed for use in the IRF QRP, is unique in that it is 
a within stay readmission measure. Analogous measures applicable to 
other PAC settings may be considered in future rulemaking.
    Comment: Several commenters expressed concern over cross-setting 
alignment of measures, some urging CMS to delay implementation of this 
measure until there are equivalent within stay PPR measures for each 
PAC setting. Commenters noted this measure is not required by the 
IMPACT Act and that incongruences between measures in the different PAC 
settings present concerns for cross-setting comparisons and potential 
confusion for IRFs about their quality performance. One commenter was 
particularly concerned about the differences between the IRF within 
stay measure and the SNF PPR measure proposed for the SNF VBP Program 
that assess PPRs 30 days after discharge from the prior hospital.
    Response: We are clarifying that though this within-stay PPR 
measure is not required by the IMPACT Act, capturing potentially 
preventable readmission measures during an IRF stay assesses important 
aspects of inpatient post-acute care. The measure is a starting point 
for this work, which is being conducted in phases, and additional 
measures that calculate PPRs using different readmission windows in 
other PAC settings will be considered in the future. We will take this 
comment into consideration.
    Comment: Some commenters expressed that IRFs may not be able to 
control or prevent hospital readmissions that take place during an IRF 
stay, especially within the first few days of admission, if patients 
are admitted to IRFs prior to the availability of diagnostic testing 
results, or if they did not receive adequate acute care. One commenter 
cited the example of patients with leukemia, who are often readmitted 
to the hospital for treatment. Another commenter noted that even though 
the risk adjustment will account for some of these circumstances, it is 
difficult for providers to fully evaluate the risk-adjustment model 
because the testing and risk-adjustment coefficients have not been 
finalized. The commenter recommended these measures be suspended until 
CMS explains how the measures will treat each of these scenarios. 
Commenters suggested that the IRF within-stay PPR measure should 
account for the three-day, short-stay and transfer care policies that 
exist in the IRF PPS. One commenter expressed concern that the proposed 
measure's readmission window and IRF payment rules would cause a 
``double penalty'' for short-stay episodes that end in a readmission. 
Commenters noted that the home health measures account for short-stay 
payment policies and that the IRF measure should be designed in a 
similar manner.
    Response: We recognize the concerns raised related to potential 
delays in receiving diagnostic information and/or inadequate care 
provided in the prior acute setting for some patients. However, we wish 
to clarify that this measure is intended to address potentially 
preventable hospital readmissions and does not count all hospital 
readmissions that take place during the IRF stay. The goal of this 
measure is to improve care transitions and coordination of care, which 
is important for all patients. Furthermore, providers assume the 
responsibility for this outcome for all patients that they admit into 
their facility, including those with shorter lengths of stay.
    We would like to clarify that for the commenter's example regarding 
patients with leukemia, these patients would most likely be excluded 
from the measure because non-surgical treatment of cancer is a measure 
exclusion. Based on analysis of data from 2013, 0.5 percent of the IRF 
sample was excluded because the prior short-term acute-care stay was 
for nonsurgical treatment of cancer which includes leukemia. In 
addition, leukemia and other cancer patients that are not excluded from 
the measure are more likely being readmitted for planned procedures and 
treatments; however, this is a measure of potentially preventable 
hospital readmissions that are also unplanned.
    With regard to excluding readmissions during the first three days 
of an IRF stay, we would like to clarify that the policy cited is for 
IRF payment determination and is not related to measurement of quality 
of care. This measure focuses on care transitions and coordination 
which is relevant to all patients, including those with shorter lengths 
of stay. Furthermore, excluding readmissions during the first three 
days of an IRF stay may result in transferring patients back sooner in 
order to exclude patients from the measure.
    We would also like to clarify that the finalized risk-adjustment 
models and coefficients are included in the measure specifications 
available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.
    Comment: Some commenters expressed concern over the 
``multiplicity'' of the IRF QRP's readmission measures, adding that 
this may lead to confusion and make it difficult for IRFs to track and 
improve performance. There was also concern

[[Page 52110]]

that this IRF within stay PPR measure was not required by the IMPACT 
Act, nor did it align with a domain in CMS's National Quality Strategy. 
Several commenters expressed concern over the overlap between the PPR 
measure and the existing all-cause readmission measures adopted for the 
IRF QRP. A few commenters recommended CMS not to adopt this measure, or 
to postpone implementation, commenting that the purpose and 
implications of the measure were ambiguous and its introduction was 
premature. The commenters respectfully recommended CMS not to adopt 
this measure, and some commenters suggested postponing the 
implementation of this measure pending further development or use in a 
cross-setting and standardized manner.
    Response: We appreciate the comment related to the potential 
challenges that may be associated with proposing multiple readmission 
measures for the program. However, given that each measure focuses on a 
different aspect of care, we believe that each measure provides value 
in the program. We are committed to ensuring that measures in the IRF 
QRP are useful in assessing quality and will evaluate the readmission 
measures in the future.
    In addition, we wish to clarify that though this measure is not 
required by the IMPACT Act, capturing potentially preventable 
readmission measures during an IRF stay assesses important aspects of 
inpatient post-acute care, including care coordination. Like other 
hospital readmission measures for post-acute care, the measure fits 
within the National Quality Strategy communication and care 
coordination priority area. We also wish to clarify that this measure 
does not overlap readmission captured in other readmission measures 
proposed or adopted for the IRF QRP.
    We would also like to clarify that the full measure specifications 
including preliminary results were made available at the time of the 
proposed rule's display. The measure is fully developed and the final 
measure specifications, including the finalized risk-adjustment models 
and descriptive statistics on IRFs' risk-standardized within-stay PPR 
rates, are available are included in the measure specifications 
available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.
    Comment: One commenter specifically supported the inclusion of 
infectious conditions in the inadequate management of infections and 
inadequate management of other unplanned events categories in the 
measure's definition of potentially preventable hospital readmissions. 
Another commenter expressed support for the inclusion of chronic 
conditions and infections as conditions for which readmissions would be 
considered potentially preventable, citing infection prevention and 
other interventions that are effective in preventing such readmissions. 
Another commenter expressed appreciation for the focus on preventable 
readmissions, but recommended that CMS continue evaluating and testing 
the measure to ensure that the codes used for the PPR definition are 
clinically relevant. One commenter expressed concern over being 
``penalized'' for readmissions that are clinically unrelated to a 
patient's original reason for IRF admission.
    Response: As described in the proposed rule, the definition for 
potentially preventable readmissions for this measure was developed 
based on existing evidence and was vetted by a TEP, which included 
clinicians and post-acute care experts. We also conducted a 
comprehensive environmental scan to identify conditions for which 
readmissions may be considered potentially preventable. Results of this 
environmental scan and details of the TEP input received were made 
available in the PPR TEP summary report available on the CMS Web site 
at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
    Though readmissions may be considered potentially preventable even 
if they may not appear to be clinically related to the patient's 
original reason for IRF admission, there is substantial evidence that 
the conditions included in the definition may be preventable with 
sufficient medical monitoring and appropriate patient treatment. 
Furthermore, this measure is based on Medicare claims data and it may 
not always be feasible to determine whether a subsequent readmission is 
or is not clinically related to the reason why the patient was 
receiving inpatient rehabilitation. We intend to conduct ongoing 
evaluation and monitoring of this measure, and will take these comments 
into consideration.
    Comment: One commenter expressed concern that the measure could 
create an incentive for IRFs to be selective about the types of 
patients they admit in order to reduce the risk of PPRs (that is, 
``cherry pick'' less complex patients for IRF admission). Another 
commenter noted this measure could incentivize longer acute hospital 
stays and delay admission to IRFs, expressing concern over being 
penalized for brief readmissions for follow-up procedures.
    Response: We wish to clarify that this measure does not count 
planned procedures as these types of readmissions do not reflect 
quality of care or care transitions. We intend to conduct ongoing 
monitoring to assess for potential unintended consequences associated 
with the implementation of this measure, and will take these 
suggestions into account.
    Comment: One commenter raised concerns over the risk-adjustment 
approach for the within-stay PPR measure. The commenter expressed 
concern that the HCC risk-adjustment method is insufficient at 
predicting costs for certain patient populations. The commenters 
suggested CMS reconsider the validity and reliability of the HCC risk-
adjustment model, and research and develop a refined risk-adjustment 
model that encompasses more of the diversity and complexity of PAC 
patients and is more sensitive to their levels of resource use. The 
commenter also expressed concern that the proposed measure is not 
adjusted for socio-economic factors.
    Response: We appreciate the comment received regarding the risk-
adjustment model and will take this comment into consideration. We 
refer readers to our response on the use of HCCs as described in 
section VIII.F.3. of this final rule. We wish to clarify that the model 
included in the specifications using HCCs as risk adjusters for 
comorbidities posted for the proposed rule demonstrated more than 
adequate discrimination power. The model had a c-statistic of 0.74 
which is within range if not higher for similar readmission measures 
finalized in public reporting programs, including the All-Cause 
Unplanned Readmission Measure for 30 Days Post-Discharge from IRFs (NQF 
#2502) previously adopted for the IRF QRP. We would also like to 
clarify that the finalized risk-adjustment models and coefficients are 
included in the measure specifications available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.
    With regard to the suggestions that the model include 
sociodemographic factors and the suggestion pertaining to an approach 
with which to convey data comparisons, we refer the readers to section 
VIII.F of this final rule where we also discuss these topics.

[[Page 52111]]

    Comment: Some commenters expressed concern over provider burden and 
questioned CMS's intention of applying both all-cause and potentially 
preventable readmission measures. The commenters also noted that with 
the finalization of all required measures by the IMPACT Act, the 
industry would be subject to significant changes and an increased data 
reporting burden with regard to the quality reporting program. Some 
commenters noted that there would not be an additional reporting or 
data collection burden given the measure is claim-based; however, 
providers would take on additional burdens, including understanding the 
measure design, evaluating its implications, and reconciling the CASPER 
Quality Measure feedback data.
    Response: We would like to note that the within-stay PPR measures 
use a data source of claims data and are not collected by means of an 
assessment instrument. Therefore, the measure does not increase data 
collection burden on the provider as this data is currently collected 
by providers. Despite the lack of data collection burden, we appreciate 
the comments that more education will be required for the public and 
providers to understand the differences between the readmission 
measures in the IRF QRP. We also wish to clarify that the within-stay 
readmission measure does not overlap any existing readmission measures.
    Comment: Several commenters expressed concern that the measures are 
not NQF-endorsed, some with additional concerns over measure testing 
and development. Some of these commenters recommended that CMS should 
adopt measures endorsed by the NQF in quality reporting programs or 
recommended that CMS submit the measures through the NQF endorsement 
process as soon as feasible.
    Response: With regard to NQF endorsement, as noted in the proposed 
rule, we intend to submit this measure to NQF for consideration of 
endorsement. We are unaware of any other measures that assess 
potentially preventable readmissions during an IRF stay. We appreciate 
the comments related to the measure's testing. We would also like to 
clarify that the finalized risk-adjustment models and coefficients are 
included in the measure specifications available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html. We will make results of additional testing 
and evaluation of the measure beyond those provided in the final 
measure specifications available in the future.
    Final Decision: After careful consideration of the public comments, 
we are finalizing our proposal to adopt this measure, Potentially 
Preventable Within Stay Readmission Measure for IRFs. Measure 
Specifications for Measures Adopted in the FY 2017 IRF QRP Final Rule 
are available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.

G. IRF QRP Quality Measure Finalized for the FY 2020 Payment 
Determination and Subsequent Years

    We proposed to adopt one new quality measure to meet the 
requirements of the IMPACT Act beginning with the FY 2020 payment 
determination and subsequent years. The measure, Drug Regimen Review 
Conducted with Follow-Up for Identified Issues--PAC IRF QRP, addresses 
the IMPACT Act quality domain of Medication Reconciliation.
1. Quality Measure Addressing the IMPACT Act Domain of Medication 
Reconciliation: Drug Regimen Review Conducted With Follow-Up for 
Identified Issues--Post Acute Care Inpatient Rehabilitation Facility 
Quality Reporting Program
    Sections 1899B(a)(2)(E)(i)(III) and 1899B(c)(1)(C) of the Act, as 
added by the IMPACT Act, require the Secretary to specify a quality 
measure to address the quality domain of medication reconciliation by 
October 1, 2018 for IRFs, LTCHs and SNFs by January 1, 2017 for HHAs. 
We proposed to adopt the quality measure, Drug Regimen Review Conducted 
with Follow-Up for Identified Issues--PAC IRF QRP, for the IRF QRP as a 
patient-assessment based, cross-setting quality measure to meet the 
IMPACT Act requirements with data collection beginning October 1, 2018 
for the FY 2020 payment determinations and subsequent years.
    This measure assesses whether PAC providers were responsive to 
potential or actual clinically significant medication issue(s) when 
such issues were identified. Specifically, the quality measure reports 
the percentage of patient stays in which a drug regimen review was 
conducted at the time of admission and timely follow-up with a 
physician occurred each time potential clinically significant 
medication issues were identified throughout that stay.
    For this quality measure, drug regimen review is defined as the 
review of all medications or drugs the patient is taking to identify 
any potential clinically significant medication issues. The quality 
measure utilizes both the processes of medication reconciliation and a 
drug regimen review, in the event an actual or potential medication 
issue occurred. The measure informs whether the PAC facility identified 
and addressed each clinically significant medication issue and if the 
facility responded or addressed the medication issue in a timely 
manner. Of note, drug regimen review in PAC settings is generally 
considered to include medication reconciliation and review of the 
patient's drug regimen to identify potential clinically significant 
medication issues.\88\ This measure is applied uniformly across the PAC 
settings.
---------------------------------------------------------------------------

    \88\ Institute of Medicine. Preventing Medication Errors. 
Washington DC: National Academies Press; 2006.
---------------------------------------------------------------------------

    Medication reconciliation is a process of reviewing an individual's 
complete and current medication list. Medication reconciliation is a 
recognized process for reducing the occurrence of medication 
discrepancies that may lead to Adverse Drug Events (ADEs).\89\ 
Medication discrepancies occur when there is conflicting information 
documented in the medical records. The World Health Organization 
regards medication reconciliation as a standard operating protocol 
necessary to reduce the potential for ADEs that cause harm to patients. 
Medication reconciliation is an important patient safety process that 
addresses medication accuracy during transitions in patient care and in 
identifying preventable ADEs.\90\ The Joint Commission added medication 
reconciliation to its list of National Patient Safety Goals (2005), 
suggesting that medication reconciliation is an integral component of 
medication safety.\91\ The Society of Hospital Medicine published a 
statement in agreement of the Joint Commission's emphasis and value of 
medication reconciliation as a patient safety goal.\92\ There is 
universal agreement that medication reconciliation directly addresses 
patient safety issues that can result from medication

[[Page 52112]]

miscommunication and unavailable or incorrect 
information.93 94 95
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    \89\ Ibid.
    \90\ Leotsakos A., et al. Standardization in patient safety: The 
WHO High 5s project. Int J Qual Health Care. 2014:26(2):109-116.
    \91\ The Joint Commission. 2016 Long Term Care: National Patient 
Safety Goals Medicare/Medicaid Certification-based Option. 
(NPSG.03.06.01).
    \92\ Greenwald, J.L., Halasyamani, L., Greene, J., LaCivita, C., 
et al. (2010). Making inpatient medication reconciliation patient 
centered, clinically relevant and implementable: A consensus 
statement on key principles and necessary first steps. Journal of 
Hospital Medicine, 5(8), 477-485.
    \93\ Leotsakos A., et al. Standardization in patient safety: The 
WHO High 5s project. Int J Qual Health Care. 2014:26(2):109-116.
    \94\ The Joint Commission. 2016 Long Term Care: National Patient 
Safety Goals Medicare/Medicaid Certification-based Option. 
(NPSG.03.06.01).
    \95\ IHI. Medication Reconciliation to Prevent Adverse Drug 
Events [Internet]. Cambridge, MA: Institute for Healthcare 
Improvement; [cited 2016 Jan 11]. Available from: http://www.ihi.org/topics/adesmedicationreconciliation/Pages/default.aspx.
---------------------------------------------------------------------------

    The performance of timely medication reconciliation is valuable to 
the process of drug regimen review. Preventing and responding to ADEs 
is of critical importance as ADEs account for significant increases in 
health services utilization and costs 96 97 98 including 
subsequent emergency room visits and re-hospitalizations.\99\ Annual 
health care costs in the United States from ADEs are estimated at $3.5 
billion, resulting in 7,000 deaths annually.100 101
---------------------------------------------------------------------------

    \96\ Institute of Medicine. Preventing Medication Errors. 
Washington DC: National Academies Press; 2006.
    \97\ Jha AK, Kuperman GJ, Rittenberg E, et al. Identifying 
hospital admissions due to adverse drug events using a computer-
based monitor. Pharmacoepidemiol Drug Saf. 2001;10(2):113-119.
    \98\ Hohl CM, Nosyk B, Kuramoto L, et al. Outcomes of emergency 
department patients presenting with adverse drug events. Ann Emerg 
Med. 2011;58:270-279.
    \99\ Kohn LT, Corrigan JM, Donaldson MS. To Err Is Human: 
Building a Safer Health System Washington, DC: National Academies 
Press; 1999.
    \100\ Greenwald, J.L., Halasyamani, L., Greene, J., LaCivita, 
C., et al. (2010). Making inpatient medication reconciliation 
patient centered, clinically relevant and implementable: A consensus 
statement on key principles and necessary first steps. Journal of 
Hospital Medicine, 5(8), 477-485.
    \101\ Phillips, David P.; Christenfeld, Nicholas; and Glynn, 
Laura M. Increase in US Medication-Error Deaths between 1983 and 
1993. The Lancet. 351:643-644, 1998.
---------------------------------------------------------------------------

    Medication errors include the duplication of medications, delivery 
of an incorrect drug, inappropriate drug omissions, or errors in the 
dosage, route, frequency, and duration of medications. Medication 
errors are one of the most common types of medical error and can occur 
at any point in the process of ordering and delivering a medication. 
Medication errors have the potential to result in an 
ADE.102 103 104 105 106 107 Inappropriately prescribed 
medications are also considered a major healthcare concern in the 
United States for the elderly population, with costs of roughly $7.2 
billion annually.\108\
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    \102\ Institute of Medicine. To err is human: Building a safer 
health system. Washington, DC: National Academies Press; 2000.
    \103\ Lesar TS, Briceland L, Stein DS. Factors related to errors 
in medication prescribing. JAMA. 1997:277(4): 312-317.
    \104\ Bond CA, Raehl CL, & Franke T. Clinical pharmacy services, 
hospital pharmacy staffing, and medication errors in United States 
hospitals. Pharmacotherapy. 2002:22(2): 134-147.
    \105\ Bates DW, Cullen DJ, Laird N, Petersen LA, Small SD, et 
al. Incidence of adverse drug events and potential adverse drug 
events. Implications for prevention. JAMA. 1995:274(1): 29-34.
    \106\ Barker KN, Flynn EA, Pepper GA, Bates DW, & Mikeal RL. 
Medication errors observed in 36 health care facilities. JAMA. 2002: 
162(16):1897-1903.
    \107\ Bates DW, Boyle DL, Vander Vliet MB, Schneider J, & Leape 
L. Relationship between medication errors and adverse drug events. J 
Gen Intern Med. 1995:10(4): 199-205.
    \108\ Fu, Alex Z., et al. ``Potentially inappropriate medication 
use and healthcare expenditures in the US community-dwelling 
elderly.'' Medical care 45.5 (2007): 472-476.
---------------------------------------------------------------------------

    There is strong evidence that medication discrepancies occur during 
transfers from acute care facilities to post-acute care facilities. 
Discrepancies occur when there is conflicting information documented in 
the medial records. Almost one-third of medication discrepancies have 
the potential to cause patient harm.\109\ An estimated 50 percent of 
patients experienced a clinically important medication error after 
hospital discharge in an analysis of two tertiary care academic 
hospitals.\110\
---------------------------------------------------------------------------

    \109\ Wong, Jacqueline D., et al. ``Medication reconciliation at 
hospital discharge: Evaluating discrepancies.'' Annals of 
Pharmacotherapy 42.10 (2008): 1373-1379.
    \110\ Kripalani S, Roumie CL, Dalal AK, et al. Effect of a 
pharmacist intervention on clinically important medication errors 
after hospital discharge: A randomized controlled trial. Ann Intern 
Med. 2012:157(1):1-10.
---------------------------------------------------------------------------

    Medication reconciliation has been identified as an area for 
improvement during transfer from the acute care facility to the 
receiving post-acute care facility. PAC facilities report gaps in 
medication information between the acute care hospital and the 
receiving post-acute-care setting when performing medication 
reconciliation.111 112 Hospital discharge has been 
identified as a particularly high risk time point, with evidence that 
medication reconciliation identifies high levels of 
discrepancy.113 114 115 116 117 118 Also, there is evidence 
that medication reconciliation discrepancies occur throughout the 
patient stay.119 120 For older patients, who may have 
multiple comorbid conditions and thus multiple medications, transitions 
between acute and post-acute care settings can be further 
complicated,\121\ and medication reconciliation and patient knowledge 
(medication literacy) can be inadequate post-discharge.\122\ The 
quality measure, Drug Regimen Review Conducted with Follow-Up for 
Identified Issues-PAC IRF QRP, evaluates an important component of care 
coordination for PAC settings and will affect a large proportion of the 
Medicare population who transfer from hospitals into PAC services each 
year. For example, in 2013, 1.7 million Medicare FFS beneficiaries had 
SNF stays, 338,000 beneficiaries had IRF stays, and 122,000 
beneficiaries had LTCH stays.\123\
---------------------------------------------------------------------------

    \111\ Gandara, Esteban, et al. ``Communication and information 
deficits in patients discharged to rehabilitation facilities: An 
evaluation of five acute care hospitals.'' Journal of Hospital 
Medicine 4.8 (2009): E28-E33.
    \112\ Gandara, Esteban, et al. ``Deficits in discharge 
documentation in patients transferred to rehabilitation facilities 
on anticoagulation: Results of a system wide evaluation.'' Joint 
Commission Journal on Quality and Patient Safety 34.8 (2008): 460-
463.
    \113\ Coleman EA, Smith JD, Raha D, Min SJ. Post hospital 
medication discrepancies: Prevalence and contributing factors. Arch 
Intern Med. 2005 165(16):1842-1847.
    \114\ Wong JD, Bajcar JM, Wong GG, et al. Medication 
reconciliation at hospital discharge: Evaluating discrepancies. Ann 
Pharmacother. 2008 42(10):1373-1379.
    \115\ Hawes EM, Maxwell WD, White SF, Mangun J, Lin FC. Impact 
of an outpatient pharmacist intervention on medication discrepancies 
and health care resource utilization in post hospitalization care 
transitions. Journal of Primary Care & Community Health. 2014; 
5(1):14-18.
    \116\ Foust JB, Naylor MD, Bixby MB, Ratcliffe SJ. Medication 
problems occurring at hospital discharge among older adults with 
heart failure. Research in Gerontological Nursing. 2012, 5(1): 25-
33.
    \117\ Pherson EC, Shermock KM, Efird LE, et al. Development and 
implementation of a post discharge home-based medication management 
service. Am J Health Syst Pharm. 2014; 71(18): 1576-1583.
    \118\ Pronovosta P, Weasta B, Scwarza M, et al. Medication 
reconciliation: A practical tool to reduce the risk of medication 
errors. J Crit Care. 2003; 18(4): 201-205.
    \119\ Bates DW, Cullen DJ, Laird N, Petersen LA, Small SD, et 
al. Incidence of adverse drug events and potential adverse drug 
events. Implications for prevention. JAMA. 1995:274(1): 29-34.
    \120\ Himmel, W., M. Tabache, and M. M. Kochen. ``What happens 
to long-term medication when general practice patients are referred 
to hospital?.''European journal of clinical pharmacology 50.4 
(1996): 253-257.
    \121\ Chhabra, P.T., et al. (2012). ``Medication reconciliation 
during the transition to and from long-term care settings: A 
systematic review.'' Res Social Adm Pharm 8(1): 60-75.
    \122\ Kripalani S, Roumie CL, Dalal AK, et al. Effect of a 
pharmacist intervention on clinically important medication errors 
after hospital discharge: A randomized controlled trial. Ann Intern 
Med. 2012:157(1):1-10.
    \123\ March 2015 Report to the Congress: Medicare Payment 
Policy. Medicare Payment Advisory Commission; 2015.
---------------------------------------------------------------------------

    A TEP convened by our measure development contractor provided input 
on the technical specifications of this quality measure, Drug Regimen 
Review Conducted with Follow-Up for Identified Issues-PAC IRF QRP, 
including components of reliability, validity, and the feasibility of 
implementing the measure across PAC settings. The TEP supported the 
measure's implementation across PAC settings and was supportive of our 
plans to standardize this measure for cross-setting development. A 
summary of the TEP proceedings is available on the PAC Quality 
Initiatives Downloads and

[[Page 52113]]

Video Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
    We solicited stakeholder feedback on the development of this 
measure by means of a public comment period held from September 18 
through October 6, 2015. Through public comments submitted by several 
stakeholders and organizations, we received support for implementation 
of this measure. The public comment summary report for the measure is 
available on the CMS Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
    The NQF-convened MAP met on December 14 and 15, 2015, and provided 
input on the use of this measure, Drug Regimen Review Conducted with 
Follow-Up for Identified Issues-PAC IRF QRP. The MAP encouraged 
continued development of the quality measure to meet the mandate added 
by the IMPACT Act. The MAP agreed with the measure gaps identified by 
CMS, including medication reconciliation, and stressed that medication 
reconciliation be present as an ongoing process. More information about 
the MAPs recommendations for this measure is available at http://www.qualityforum.org/Publications/2016/02/MAP_2016_Considerations_for_Implementing_Measures_in_Federal_Programs_-_PAC-LTC.aspx.
    Since the MAP's review and recommendation of continued development, 
we have continued to refine this measure in compliance with the MAP's 
recommendations. The measure is consistent with the information 
submitted to the MAP and supports its scientific acceptability for use 
in quality reporting programs. Therefore, we proposed this measure for 
implementation in the IRF QRP as required by the IMPACT Act.
    We reviewed the NQF's endorsed measures and identified one NQF-
endorsed cross-setting and quality measure related to medication 
reconciliation, which applies to the SNF, LTCH, IRF, and HHA settings 
of care: Care for Older Adults (COA), (NQF #0553). The quality measure, 
Care for Older Adults (COA), (NQF #0553) assesses the percentage of 
adults 66 years and older who had a medication review. The Care for 
Older Adults (COA), (NQF #0553) measure requires at least one 
medication review conducted by a prescribing practitioner or clinical 
pharmacist during the measurement year and the presence of a medication 
list in the medical record. This is in contrast to the quality measure, 
Drug Regimen Review Conducted with Follow-Up for Identified Issues-PAC 
IRF QRP, which reports the percentage of patient stays in which a drug 
regimen review was conducted at the time of admission and that timely 
follow-up with a physician occurred each time one or more potential 
clinically significant medication issues were identified throughout 
that stay.
    After careful review of both quality measures, we decided to 
propose the quality measure, Drug Regimen Review Conducted with Follow-
Up for Identified Issues-PAC IRF QRP for the following reasons:
     The IMPACT Act requires the implementation of quality 
measures, using patient assessment data that are standardized and 
interoperable across PAC settings. The quality measure, Drug Regimen 
Review Conducted with Follow-Up for Identified Issues-PAC IRF QRP, 
employs three standardized patient-assessment data elements for each of 
the four PAC settings so that data are standardized, interoperable, and 
comparable; whereas, the Care for Older Adults (COA), (NQF #0553) 
quality measure does not contain data elements that are standardized 
across all four PAC settings.
     The quality measure, Drug Regimen Review Conducted with 
Follow-Up for Identified Issues-PAC IRF QRP, requires the 
identification of potential clinically significant medication issues at 
the beginning, during, and at the end of the patient's stay to capture 
data on each patient's complete PAC stay; whereas, the Care for Older 
Adults (COA), (NQF #0553) quality measure only requires annual 
documentation in the form of a medication list in the medical record of 
the target population.
     The quality measure, Drug Regimen Review Conducted with 
Follow-Up for Identified Issues-PAC IRF QRP, includes identification of 
the potential clinically significant medication issues and 
communication with the physician (or physician designee) as well as 
resolution of the issue(s) within a rapid timeframe (by midnight of the 
next calendar day); whereas, the Care for Older Adults (COA), (NQF 
#0553) quality measure does not include any follow-up or timeframe in 
which the follow-up would need to occur.
     The quality measure, Drug Regimen Review Conducted with 
Follow-Up for Identified Issues-PAC IRF QRP, does not have age 
exclusions; whereas, the Care for Older Adults (COA), (NQF #0553) 
quality measure limits the measure's population to patients aged 66 and 
older.
     The quality measure, Drug Regimen Review Conducted with 
Follow-Up for Identified Issues-PAC IRF QRP, will be reported to IRFs 
quarterly to facilitate internal quality monitoring and quality 
improvement in areas such as patient safety, care coordination, and 
patient satisfaction; whereas, the Care for Older Adults (COA), (NQF 
#0553) quality measure would not enable quarterly quality updates, and 
thus data comparisons within and across PAC providers would be 
difficult due to the limited data and scope of the data collected.
    Therefore, based on the evidence discussed above, we proposed to 
adopt the quality measure entitled, Drug Regimen Review Conducted with 
Follow-Up for Identified Issues-PAC IRF QRP, for the IRF QRP for FY 
2020 payment determination and subsequent years. We plan to submit the 
quality measure to the NQF for consideration for endorsement.
    The calculation of the quality measure is based on the data 
collection of three standardized items to be included in the IRF-PAI. 
The collection of data by means of the standardized items will be 
obtained at admission and discharge. For more information about the 
data submission required for this measure, we refer readers to section 
VIII.I.c of this final rule.
    The standardized items used to calculate this quality measure do 
not duplicate existing items currently used for data collection within 
the IRF-PAI. The measure denominator is the number of patient stays 
with a discharge assessment during the reporting period. The measure 
numerator is the number of stays in the denominator where the medical 
record contains documentation of a drug regimen review conducted at: 
(1) Admission and (2) discharge with a lookback through the entire 
patient stay with all potential clinically significant medication 
issues identified during the course of care and followed up with a 
physician or physician designee by midnight of the next calendar day. 
This measure is not risk adjusted. For technical information about this 
measure, including information about the measure calculation and 
discussion pertaining to the standardized items used to calculate this 
measure, we refer readers to the document titled, Proposed Measure 
Specifications for Measures Proposed in the FY 2017 IRF QRP proposed 
rule available at https://www.cms.gov/Medicare/Quality-Initiatives-
Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-

[[Page 52114]]

Quality-Reporting-Program-Measures-Information-.html.
    Data for the quality measure, Drug Regimen Review Conducted with 
Follow-Up for Identified Issues-PAC IRF QRP, will be collected using 
the IRF-PAI with submission through the Quality Improvement Evaluation 
System (QIES) Assessment Submission and Processing (ASAP) system.
    We invited public comment on our proposal to adopt the quality 
measure, Drug Regimen Review Conducted with Follow-Up for Identified 
Issues-PAC IRF QRP for the IRF QRP. We received several comments, which 
are summarized with our responses below.
    Comment: Several commenters, including MedPAC, expressed support 
for the quality measure. Commenters supported the medication 
reconciliation concept, and one commenter conveyed that preventing and 
responding to ADEs that account for increases in health services 
utilization and cost is critically important. MedPAC further noted that 
the medication reconciliation and follow-up process can help reduce 
medication errors that are especially common among patients who have 
multiple health care providers and multiple comorbidities.
    Response: We agree that medication reconciliation is an important 
patient safety process for addressing medication accuracy during 
transitions in patient care and identifying preventable ADEs, which may 
lead to reduced health services utilization and associated costs.
    Comment: Several commenters recommended that CMS add an additional 
response option, to indicate that the item N2003 Medication Follow-up 
(completed at admission) is not applicable if a patient does not take 
any medication. Alternatively, commenters suggested that CMS clarify 
whether this item would be mandatory in the event that a patient is not 
taking any medications.
    Response: We wish to point out that Measure item N2003 has a skip 
pattern that allows the user to skip over this item if the patient does 
not take medication. Additional guidance will be included in the IRF-
PAI training manual.
    Comment: We received several comments regarding concerns about 
whether the measure has been fully developed and tested. Many 
commenters noted that the NQF-convened MAP recommended continued 
development for the measure and requested testing of the measure to 
ensure that it is appropriate for the IRF setting. Several commenters 
expressed concern that the measure was not NQF-endorsed.
    Response: Since the time of the NQF-convened MAP, with our measure 
contractor, we tested this measure in a pilot test involving twelve 
post-acute care facilities (IRF, SNF, LTCH), representing variation 
across geographic location, size, profit status, and clinical records 
system. Two clinicians in each facility collected data on a sample of 
10 to 20 patients for a total of 298 records (147 qualifying pairs). 
Analysis of agreement between coders within each participating facility 
indicated a 71 percent agreement for item DRR-01 \124\ Drug Regimen 
Review (admission); 69 percent agreement for item DRR-02 \125\ 
Medication Follow-up (admission); and 61 percent agreement for DRR-03 
\126\ Medication Intervention (during stay and discharge). Overall, 
pilot testing enabled us to verify feasibility of the measure. 
Furthermore, measure development included convening a TEP to provide 
input on the technical specifications of this quality measure, 
including components of reliability, validity and the feasibility of 
implementing the measure across PAC settings. The TEP included 
stakeholders from the IRF setting and was supportive of our plans to 
standardize this measure for cross-setting development. A summary of 
the TEP proceedings is available on the PAC Quality Initiatives 
Downloads and Videos Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
---------------------------------------------------------------------------

    \124\ DRR pilot items DRR-01, DRR-02 and DRR-03 are equivalent 
to the proposed rule DRR PAC instrument items N. 2001, N. 2003 and 
N. 2005
    \125\ DRR pilot items DRR-01, DRR-02 and DRR-03 are equivalent 
to the proposed rule DRR PAC instrument items N. 2001, N. 2003 and 
N. 2005
    \126\ DRR pilot items DRR-01, DRR-02 and DRR-03 are equivalent 
to the proposed rule DRR PAC instrument items N. 2001, N. 2003 and 
N. 2005
---------------------------------------------------------------------------

    As noted above, we plan to conduct further testing on this measure 
once we have started collecting data from the PAC settings. Once we 
have completed this additional measure performance testing, we plan to 
submit the measure to NQF for endorsement.
    Comment: We received several comments about guidance and training. 
One commenter requested clear and consistent information for training 
staff and resources to meet the requirements of the measure. We 
received several comments requesting guidance regarding the definition 
of ``clinically significant medication issues.'' Several commenters 
were concerned that the phrase could be interpreted differently by the 
many providers involved in a patient's treatment and that this could 
result in a challenge to collect reliable and accurate data for this 
quality measure. One commenter further conveyed that there are likely 
to be variations in measure performance that are not based on 
differences in care, but rather on differences in data collection. In 
addition, one commenter requested a specific definition in the measure 
specifications for the word ``potential,'' and another commenter 
requested further guidance on what would be considered an ``adequate 
response'' to a clinically significant medication issue.
    Response: For this measure, potential clinically significant 
medication issues are defined as those issues that, in the clinician's 
professional judgment, warrant interventions, such as alerting the 
physician and/or others, and the timely completion of any recommended 
actions (by midnight of the next calendar day) so as to avoid and 
mitigate any untoward or adverse outcomes. The definition of 
``clinically significant'' in this measure was conceptualized during 
the measure development process. For purposes of the measure, the 
decision regarding whether or not a medication issue is ``clinically 
significant'' will need to be made on a case-by-case basis, but we also 
intend to provide additional guidance and training on this issue.
    Comment: We received several comments regarding the patient 
populations for the measure, specifically conveying concern that the 
populations are not standardized across PAC settings. For example, many 
commenters noted that IRF QRP measure includes data collection for 
Medicare Fee for Service and Medicare Advantage patients, while the SNF 
QRP measure only includes Medicare Part A patients, and the LTCH QRP 
includes all patients. Commenters were concerned that this could result 
in selective sampling of the patient population that would skew the 
collected data and distort or otherwise invalidate meaningful 
comparisons across measures and across settings, thereby falling short 
of the PAC standardization goals of the IMPACT Act. Several commenters 
suggested that CMS exclude Medicare Advantage patients, while others 
recommended that they be included for all measures across all PAC 
settings.
    Response: We are working to standardize all measures as mandated by 
the IMPACT Act to increase data comparability and interoperability. We 
will take the commenter's comments and concerns into consideration as 
we work to standardize the proposed measure.

[[Page 52115]]

    Comment: We received several comments regarding the time period for 
the proposed measure. One commenter disagreed with the measure's 
requirement that a facility must respond to urgent medication issues 
within one calendar day, noting that some medication issues may need to 
be resolved much more quickly for the patient's well-being. Another 
commenter was concerned that the measure tracks medication issues 
during any point of the patient's stay, citing that medication 
reconciliation occurs only during transitions of care such as 
admission, transfer and discharge. Therefore, this commenter had 
concerns that this drug regimen review process was fundamentally 
different than a medication reconciliation measure that focused only on 
care transitions.
    Response: We appreciate the challenges in coordinating patient care 
in IRF settings. However, we chose to set the intervention timeline as 
midnight of the next calendar day because we believe this timeline is 
consistent with current standard clinical practice where a clinically 
significant medication issue arises. The measure evaluates 
responsiveness to potential or actual clinically significant medication 
issues when such issues are identified. The measure evaluates 
responsiveness to potential or actual clinically significant medication 
issues when such issues are identified. We would like to note that the 
measure is simply assessing responsiveness to issues and does not 
prevent clinicians from acting more quickly when an issue is 
identified.
    We agree that medication discrepancies can occur during patient 
admissions, transfers, and discharges. We wish to clarify that the 
quality measure requires the identification of potential clinically 
significant medication issues for each patient's complete IRF stay, 
from admission to discharge. Medication reconciliation and drug regimen 
review are interrelated activities; while medication reconciliation is 
a process that identifies the most accurate and current list of 
medications, particularly during transitions of care, it also includes 
the evaluation of the name, dosage, frequency, and route. Drug regimen 
review is a process that necessitates and includes the review of all 
medications for additional purposes such as the identification of 
potential adverse effects. The process of drug regimen review includes 
medication reconciliation at the time of patient transitions and 
throughout the patient's stay.
    Comment: We received several comments pertaining to the scope of 
the measure. Several commenters commented that medication 
reconciliation and drug regimen review are distinct processes. Several 
commenters were concerned that the measure does not meet the medication 
reconciliation domain of the IMPACT Act. Commenters maintained that the 
services provided as part of drug regimen review are distinctly 
different from the services provided as part of medication 
reconciliation, and that they are completed by different members of the 
care team. These commenters believe that the measure goes beyond the 
statutory mandate of the medication reconciliation domain of the IMPACT 
Act. One commenter was also concerned that, according to the definition 
provided in the Home Health Conditions of Participation, drug regimen 
review includes taking into consideration a patient's noncompliance 
with drug therapy, significant side effects, and ineffective drug 
therapy, which are not feasible for a facility to assess during 
admission. The commenter conveyed that this was distinct from 
medication reconciliation. Many commenters were concerned that the 
measure only evaluates whether the patient's current medications are 
being reviewed and does not determine whether this review affects the 
patient's quality of care.
    Response: We disagree with the commenters' suggestion that the 
measure does not meet the requirements of the IMPACT Act. Medication 
reconciliation and drug regimen review are interrelated activities; 
while medication reconciliation is a process that identifies the most 
accurate and current list of medications, particularly during 
transitions in care, it also includes the evaluation of the name, 
dosage, frequency, and route. Drug regimen review is a process that 
necessitates, and includes the review of all medications for additional 
purposes, such as the identification of potential adverse effects. The 
process of drug regimen review includes medication reconciliation at 
the time of patient transitions and throughout the patient's stay. 
Therefore, we believe that medication reconciliation and drug regimen 
review are processes that are appropriate to combine into a single 
measure for purposes of the IRF QRP. We would also like to note that 
during the development of the measure, the definitions of medication 
reconciliation and drug regimen review, as detailed in the State 
Operations Manual (SOM), which includes the Conditions of 
Participation, were taken into consideration. We do not believe that 
the measure's use of the term ``clinically significant'' overrides or 
conflicts with the guidance as outlined in the SOM. Further, we wish to 
clarify that the specification of the measure does not preclude the 
activities of drug regimen reviews that are consistent with the SOM. 
The measure encompasses the IMPACT Act's medication reconciliation 
domain.
    Comment: Several commenters were concerned that the measure does 
not specify which healthcare provider is required to perform the drug 
regimen review, or the level of clinical training required to do so. 
The commenters were concerned that this lack of standardization could 
lead to differences across the PAC settings. Many commenters conveyed 
that in the IRF setting, medication reconciliation is complicated and 
time consuming, as IRF patients with multiple clinical needs often 
arrive from an acute hospital where many physicians, including 
specialists, have made changes to patients' prescriptions. One 
commenter noted that patient medications may be adjusted more 
frequently in an IRF due to the high level of physician supervision and 
was concerned that the measure would not count the extensive drug 
regimen review being done if a clinically significant medication issue 
was not identified during the stay. However, commenters note that other 
PAC settings may lack the clinical expertise required to perform such 
thorough medication reviews. Commenters were concerned that the 
assessment items proposed do not capture the intense involvement of a 
pharmacist, physician, and nurse that occurs in complex cases.
    Response: We wish to clarify that the measure does not override, 
supersede or conflict with current CMS guidance or regulations related 
to drug regimen review. The measure also does not specify what clinical 
professional is required to perform these activities. We do not 
prescribe guidance on which clinician may complete patient assessments. 
We also appreciate concerns about standardization across the PAC 
settings and acknowledge the complexity of drug regimen review in the 
IRF settings. While we agree that this measure does not capture every 
aspect of the drug regimen review process undertaken for each IRF 
patient, we emphasize that it is intended to assess whether PAC 
providers were responsive to potential or actual clinically significant 
medication issue(s) when such issues were identified. As noted in the 
measure specifications, the

[[Page 52116]]

measure's assessment items are standardized.
    Comment: Many commenters, including MedPAC, encouraged CMS to 
develop a measure to evaluate medication reconciliation throughout the 
care continuum. Commenters, including MedPAC, suggested CMS focus on 
discharge from the PAC setting and evaluate whether the PAC sends a 
medication list to the patient's primary care physician or to the next 
PAC provider. One commenter recommended that CMS not proceed with the 
measure and instead focus on medication reconciliation at discharge.
    Response: PAC facilities are expected to document information 
pertaining to the process of a drug regimen review, which includes 
medication reconciliation, in the patient's discharge medical record. 
Further, it is standard practice for patient discharge records to 
include a medication list to be transferred to the admitting PAC 
facility. We appreciate MedPAC and other commenters' recommendation for 
a quality measure that assesses post-discharge medication communication 
with primary care providers for patients discharged to home. We will 
take the recommendation into consideration for future measure 
development in accordance with the IMPACT Act, which emphasizes the 
transfer of interoperable patient information across the continuum of 
care.
    Comment: We received a number of comments related to unintended 
consequences of the measure. One commenter expressed concern that the 
measure would discourage PAC clinicians from reporting and correcting 
medication errors. Another commenter was concerned that the measure 
does not require an IRF to take steps to identify clinically 
significant medication issues, but instead measures whether steps were 
taken once an issue was identified, which could be abused by PAC 
providers who limit the identification of clinically significant 
medication issues in order to artificially increase their score.
    Response: Since it is a professional standard of practice for all 
providers to address potential clinically significant medication issues 
before they lead to avoidable harm to the patient, we do not believe 
that the measure will discourage a clinician from reporting a 
significant medication issue. We reiterate that the quality measure 
encourages PAC providers to conduct thorough drug regimen review to 
identify, address, and follow up for all clinically significant 
medication errors. The measure was informed by current evidence 
surrounding medication reconciliation and drug regimen review, as well 
as a review of best practice and professional standards of care.
    Comment: We received multiple comments related to burden and 
expenses related to this measure. One commenter expressed concern that 
the requirements required increased resources without clear benefit or 
increase in pay to providers for additional expenses. One commenter 
conveyed concern that providers' existing electronic medical record 
systems (EMRs) likely do not include data collection and reporting 
capabilities required by the measure. The commenter conveyed the 
challenge of collecting the data for this measure manually and had 
concerns about the cost of doing so, and resulting data inaccuracy.
    Response: We are very sensitive to the issue of burden associated 
with data collection and have proposed only the minimal number of items 
needed to calculate the quality measures. We emphasize that this 
measure follows standard clinical practice requirements of ongoing 
review, documentation, and timely reconciliation of all patient 
medications, with appropriate follow-up to address all clinically 
significant medication concerns. While we support the use of EMRs, we 
do not require that providers use EMRs to populate assessment data.
    Comment: One commenter suggested that CMS exclude patients from the 
measure who were unexpectedly discharged before the medication 
reconciliation process is completed.
    Response: We would like to clarify that this IRF measure includes 
all Medicare Part A and Medicare Advantage patient stays, including 
stays where a patient has an unexpected discharge. Data for coding 
N2005 Medicare Interventions can be obtained from the patient's medical 
records, so it is feasible to code the measure item when a patient has 
an unexpected discharge.
    Comment: One commenter conveyed concern that drug regimen review 
occurs differently across the care settings. The commenter specifically 
expressed that inpatient settings may handle clinically significant 
medication issues more immediately than home health agencies.
    Response: We believe that this comment is immaterial to the intent 
of the measure. It should be noted that we strive for consistency in 
the collection and application of the measure across all PAC settings.
    Comment: One commenter requested for clarification about whether 
the measure is intended to include instances where a drug was reviewed 
for potential adverse effects and drug reactions prior to being 
ordered. The commenter conveyed that the measure only included 
medications that have been ordered for the patient but not those that 
were prevented from being ordered by a drug regimen process.
    Response: We appreciate the commenter's concern regarding 
medications that were prevented from being ordered by the drug regimen 
review process. If finalized, we would provide guidance on these and 
other clinical examples as part of the training efforts.
    Final Decision: After careful consideration of the public comments, 
we are finalizing our proposal to adopt the quality measure, Drug 
Regimen Review Conducted with Follow-Up for Identified Issues-PAC IRF 
QRP measure for the IRF QRP for FY 2020 payment determination and 
subsequent years, as described in the Measure Specifications for 
Measures Adopted in the FY 2017 IRF QRP final rule, available at 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/Technical-Information.html.
H. IRF QRP Quality Measures and Measure Concepts under Consideration 
for Future Years
    We invited comment on the importance, relevance, appropriateness, 
and applicability of each of the quality measures listed in Table 8 for 
future years in the IRF QRP. We are developing a measure related to the 
IMPACT Act domain, ``Accurately communicating the existence of and 
providing for the transfer of health information and care preferences 
of an individual to the individual, family caregiver of the individual, 
and providers of services furnishing items and services to the 
individual, when the individual transitions.'' We considered the 
possibility of adding quality measures that rely on the patient's 
perspective; that is, measures that include patient-reported experience 
of care and health status data. We recently posted a ``Request for 
Information to Aid in the Design and Development of a Survey Regarding 
Patient and Family Member Experiences with Care Received in Inpatient 
Rehabilitation Facilities'' (80 FR 72725). Also, we are considering a 
measure focused on pain that relies on the collection of patient-
reported pain data. Finally, we are considering a measure related to 
patient safety, Venous Thromboembolism Prophylaxis.
    We received several comments about IRF QRP quality measures under

[[Page 52117]]

consideration for future years which are summarized with our responses 
below.
    Comment: Commenters had concerns about the current process for 
seeking stakeholder feedback, noting that seven- and fourteen-day 
public comment periods are unreasonable for stakeholders. Other 
commenters did not support the addition of process measures, citing 
administrative burden and expense, and recommended that CMS focus on 
outcome measures and postpone any measures outside the requirements of 
the IMPACT Act.
    Many commenters remarked on the limited number of items in the IRF-
PAI related to communication, cognition, and swallowing and noted that 
these domains are important in treating individuals with neurological 
disorders. One commenter encouraged CMS to adopt a specific screening 
instrument (Montreal Cognitive Assessment (MoCA)) or similar screening 
tools and assessment tools (such as the Continuity Assessment Record 
and Evaluation-Community, or CARE-C) to best meet the needs of Medicare 
beneficiaries and the intent of the IMPACT Act. Another commenter 
requested that CMS add a functional cognition assessment item to the 
IRF discharge assessment and that this information be provided to the 
next provider when a patient is transferred. The commenters offered to 
collaborate with CMS to develop future measures in the area of 
cognitive function.
    Response: We wish to note that several of the measures currently 
adopted in the IRF QRP are outcome measures, including: Percent of 
Residents or Patients with Pressure Ulcers that are New or Worsened 
(Short-Stay) (NQF #0678), NHSN CAUTI Outcome Measure (NQF #0138), All-
Cause Unplanned Readmission Measure for 30 Days Post Discharge from an 
IRF (NQF #2502), NHSN Facility-wide Inpatient Hospital-onset MRSA 
Bacteremia Outcome Measure (NQF #1716), and NHSN Facility-wide 
Inpatient Hospital-onset CDI Outcome Measure (NQF #1717). Measures that 
have been finalized for implementation October 1, 2016 also include 
outcome measures: Application of Percent of Residents Experiencing One 
or More Falls with Major Injury (NQF #0674), IRF Functional Outcome 
Measure: Change in Self-Care Score for Medical Rehabilitation Patients 
(NQF #2633), IRF Functional Outcome Measure: Change in Mobility Score 
for Medical Rehabilitation Patients (NQF #2634), Discharge Self-Care 
Score for Medical Rehabilitation Patients (NQF #2635), Discharge 
Mobility Score for Medical Rehabilitation Patients (NQF #2636) We agree 
that future development of outcome measures should include other areas 
of function, such as communication, cognition and swallowing, and are 
important components of functional assessment and improvement for 
patients who receive care in PAC settings, including IRFs. We 
appreciate comments related to the public comment periods during the 
measure development and stakeholder feedback process, and will continue 
to engage stakeholders as we develop and implement quality measures to 
meet the requirements of the IMPACT Act.
    Comment: Several commenters supported a Venous Thromboembolism 
(VTE) Prophylaxis measure but suggested that the measure take into 
account that not all VTEs can be prevented due to its complexity. Some 
commenters did not support a process measure, since VTE prophylaxis is 
already a standard of practice and the measure would add burden, but 
have no clinical significance. These commenters do support the 
development of a VTE outcome measure.
    Response: We thank the commenters for their comments on the VTE 
Prophylaxis measure under consideration for future implementation in 
the IRF QRP and will take into consideration the commenters' 
recommendations.
    Comment: Several commenters recommended that a pain measure take 
into consideration pain that might be experienced as the result of 
intense therapy. One commenter suggested that pain management was a 
more meaningful measure for IRF patients and requested guidance on the 
definitions of moderate and severe pain.
    Response: We will take these suggested quality measure concepts and 
recommendations regarding measure specifications into consideration in 
our ongoing measure development and testing efforts.
    Comment: We received several comments regarding the patient 
experience of care measure. Several commenters had concerns about 
survey fatigue across the continuum of care. Many commenters were 
concerned that for one episode of care, a patient could receive a 
survey from each setting which could result in confusion in responses 
and inaccurate results. Many commenters were concerned that since many 
IRFs are small units, their data may not be statistically 
representative or may show high variability. The commenters recommended 
that CMS take a systems-based approach with patient experience surveys 
to avoid these problems.
    Many commenters supported a patient experience of care measure, and 
supported accepting proxy response from family members and caregivers 
to support accurate and reliable results at the facility level. Other 
commenters supported a measure of patient experience, instead of only 
patient satisfaction, and recommended that it include several aspects 
unique to IRF care, including goal setting and discharge planning. 
Commenters recommended that CMS implement the survey as a voluntary 
tool prior to requiring it, which would allow IRFs to transition 
operationally and find a vendor, if needed. Commenters also recommended 
that the quality measure adjust for factors already in place for 
existing CAHPS[supreg] surveys, including adjusting for mode of survey 
administration, as well as IRF-specific patient-mix adjustment. The 
commenter also suggested converting responses to a 0 to 100 linear-
scaled score. Several commenters recommended that CMS seek stakeholder 
input on the development of a patient experience of care measure.
    Response: We will take these recommendations regarding measure 
specifications and survey fatigue across the care continuum into 
consideration in our ongoing measure development and testing efforts, 
and will continue to engage stakeholders in the development process.
    Comment: We received several comments regarding the transfer of 
health information and care preferences measure. Many commenters 
recommended that development efforts for this measure should recognize 
that there is a large amount of variation in the different health 
information systems used by different IRFs to record, store, retrieve, 
and share patient information. The commenter noted that hospitals are 
already required to transfer health information and care preferences as 
part of their Medicare Conditions of Participation, and posited that 
adding such a measure to the IRF QRP would rely on receiving accurate 
and complete discharge information from a prior level of care, which 
may be out of the IRF's control.
    Response: As we move through the development of this measure 
concept, we will consider the variation in health information systems 
used by different IRFs, as well as the concerns about receiving 
complete discharge information from a prior level of care for these 
measure concepts.

[[Page 52118]]



 Table 9--IRF QRP Quality Measures Under Consideration for Future Years
------------------------------------------------------------------------
 
------------------------------------------------------------------------
IMPACT Act Domain.................  Accurately communicating the
                                     existence of and providing for the
                                     transfer of health information and
                                     care preferences of an individual
                                     to the individual, family caregiver
                                     of the individual, and providers of
                                     services furnishing items and
                                     services to the individual, when
                                     the individual transitions.
    IMPACT Act Measure............      Transfer of health
                                        information and care preferences
                                        when an individual transitions.
NQS Priority......................  Patient- and Caregiver-Centered
                                     Care.
    Measures......................      Patient Experience of
                                        Care.
                                     Percent of Patients with
                                     Moderate to Severe Pain.
NQS Priority......................  Patient Safety.
    Measure.......................      Venous Thromboembolism
                                        Prophylaxis.
------------------------------------------------------------------------

I. Form, Manner, and Timing of Quality Data Submission for the FY 2018 
Payment Determination and Subsequent Years

1. Background
    Section 1886(j)(7)(C) of the Act requires that, for the FY 2014 
payment determination and subsequent years, each IRF submit to the 
Secretary data on quality measures specified by the Secretary. In 
addition, section 1886(j)(7)(F) of the Act requires that, for the 
fiscal year beginning on the specified application date, as defined in 
section 1899B(a)(2)(E) of the Act, and each subsequent year, each IRF 
submit to the Secretary data on measures specified by the Secretary 
under section 1899B of the Act. The data required under section 
1886(j)(7)(C) and (F) of the Act must be submitted in a form and 
manner, and at a time, specified by the Secretary. As required by 
section 1886(j)(7)(A)(i) of the Act, for any IRF that does not submit 
data in accordance with section 1886(j)(7)(C) and (F) of the Act for a 
given fiscal year, the annual increase factor for payments for 
discharges occurring during the fiscal year must be reduced by 2 
percentage points.
a. Timeline for Data Submission Under the IRF QRP for the FY 2018, FY 
2019 and Subsequent Year Payment Determinations
    Tables 10 through 18 represent our finalized data collection and 
data submission quarterly reporting periods, as well as the quarterly 
review and correction periods and submission deadlines for the quality 
measure data submitted via the IRF-PAI and the CDC/NHSN affecting the 
FY 2018 and subsequent year payment determinations. We also provide in 
Table 10 our previously finalized claims-based measures for FY 2018 and 
subsequent years, although we note that, for claims-based measures, 
there is no corresponding quarterly-based data collection or submission 
reporting periods with quarterly-based review and correction deadline 
periods.
    Further, in the FY 2016 IRF PPS final rule (80 FR 47122 through 
47123), we established that the IRF-PAI-based measures finalized for 
adoption into the IRF QRP will transition from reporting based on the 
fiscal year to an annual schedule consistent with the calendar year, 
with quarterly reporting periods followed by quarterly review and 
correction periods and submission deadlines, unless there is a clinical 
reason for an alternative data collection time frame. The pattern for 
annual, calendar year-based data reporting, in which we use 4 quarters 
of data, is illustrated in Table 10 and is in place for all Annual 
Payment Update (APU) years except for the measure in Table 10 for which 
the FY 2018 APU determination will be based on 5 calendar year quarters 
in order to transition this measure from FY to CY reporting. We also 
wish to clarify that payment determinations for the measures finalized 
for use in the IRF QRP that use the IRF-PAI or CDC NHSN data sources 
will subsequently use the quarterly data collection/submission and 
review, correction and submission deadlines described in Table 10 
unless otherwise specified, as is with the measure NQF #0680: Percent 
of Residents or Patients Who Were Assessed and Appropriately Given the 
Seasonal Influenza Vaccine. For this measure, we clarify in a 
subsequent discussion that the data collection and reporting periods, 
which are based on the Influenza Season, span 2 consecutive years from 
July 1 through June 30th and we therefore separately illustrate those 
collection/submission quarterly reporting periods, review and 
correction periods, and submission deadlines for FY 2019 and subsequent 
years in Table 10. We also separately distinguish the reporting periods 
and data submission timeframes for the finalized measure Influenza 
Vaccination Coverage among Healthcare Personnel which spans 2 
consecutive years, as this measure is based on the Influenza 
vaccination season, in Table 10.

  Table 10--Annual QRP CY IRF-PAI & CDC/NHSN Data Collection/submission Reporting Periods and Data Submission/
                            Correction Deadlines ** Payment Determinations [supcaret]
----------------------------------------------------------------------------------------------------------------
 
----------------------------------------------------------------------------------------------------------------
 Proposed CY data collection quarter       Data Collection/     QRP Quarterly review and correction periods data
                                         submission quarterly     submission deadlines for payment determination
                                           reporting period                             **
----------------------------------------------------------------------------------------------------------------
Quarter 1............................  January 1-March 31 *...  April 1-August 15 *....  Deadline: August 15.*
Quarter 2............................  April 1-June 30........  July 1-November 15.....  Deadline: November 15.
Quarter 3............................  July 1-September 30....  October 1-February 15..  Deadline: February 15.
Quarter 4............................  October 1-December 31 *  January 1-May 15 *.....  Deadline: May 15.*
----------------------------------------------------------------------------------------------------------------
* We refer readers to Table 10 for the annual data collection time frame for the measure, Influenza Vaccination
  Coverage among Healthcare Personnel
** We note that the submission of IRF-PAI data must also adhere to the IRF PPS deadlines
[supcaret] We refer readers to Table 10 for the 12 month (July-June) data collection/submission quarterly
  reporting periods, review and correction periods and submission deadlines for APU determinations for the
  measure NQF #0680: Percent of Residents or Patients Who Were Assessed and Appropriately Given the Seasonal
  Influenza Vaccine


[[Page 52119]]


 Table 11--Summary Details on Data Collection Period and Data Submission Timeline for Previously Adopted Quality
Measure Affecting the FY 2018 Payment Determination That Will Use 5 CY Quarters in Order To Transition From a FY
                                             to a CY Reporting Cycle
----------------------------------------------------------------------------------------------------------------
 
----------------------------------------------------------------------------------------------------------------
Finalized Measure:
 NQF # 0678 Percent of Residents or Patients with Pressure Ulcers That Are New or Worsened (Short Stay)
 (80 FR 47122)
----------------------------------------------------------------------------------------------------------------
          Submission method               Data collection/       Quarterly review and       APU Determination
                                        submission quarterly      correction periods             affected
                                         reporting period(s)        data submission
                                                                 deadlines for payment
                                                                  determination */**
----------------------------------------------------------------------------------------------------------------
IRF-PAI/QIES ASAP System............  CY 15 Q4, 10/1/15-12/31/ 1/1/2016-5/15/16         FY 2018.
                                       15.                      deadline.
                                      CY 16 Q1, 1/1/16-3/31/   4/1/2016-8/15/16
                                       16.                      deadline..
                                      CY 16 Q2, 4/1/16-6/30/   7/1/16-11/15/16
                                       16.                      deadline.
                                      CY 16 Q3, 7/1/16-9/30/   10/1/16-2/15/17
                                       16.                      deadline.
                                      CY 16 Q4, 10/01/16-12/   1/1/17-5/15/17 deadline
                                       31/16.
----------------------------------------------------------------------------------------------------------------
* We refer readers to the Table 11 for an illustration of the data collection/submission quarterly reporting
  periods and correction and submission deadlines
** We note that the submission of IRF-PAI data must also adhere to the IRF PPS deadlines


 Table 12--Summary Details on Data Collection Period and Data Submission Timeline for Previously Adopted IRF-PAI
    Quality Measure, NQF #0680 Percent of Residents or Patients Who Were Assessed and Appropriately Given the
                     Seasonal Influenza Vaccine, Affecting the FY 2018 Payment Determination
----------------------------------------------------------------------------------------------------------------
 
----------------------------------------------------------------------------------------------------------------
Finalized Measure:
 NQF #0680 Percent of Residents or Patients Who Were Assessed and Appropriately Given the Seasonal
 Influenza Vaccine (80 FR 47122)
----------------------------------------------------------------------------------------------------------------
          Submission method               Data collection/       Quarterly review and       APU Determination
                                        submission quarterly      correction periods             affected
                                         reporting period(s)        data submission
                                                                 deadlines for payment
                                                                    determination *
----------------------------------------------------------------------------------------------------------------
IRF-PAI/QIES ASAP System............  CY 15 Q4, 10/1/15-12/31/ 1/1/2016-5/15/16         FY 2018.
                                       15.                      deadline.
                                      CY 16 Q1, 1/1/16-3/31/   4/1/2016-8/15/16
                                       16.                      deadline.
                                      CY 16 Q2, 4/1/16-6/30/   7/1/16-11/15/16
                                       16.                      deadline.
----------------------------------------------------------------------------------------------------------------
* We note that the submission of IRF-PAI data must also adhere to the IRF PPS deadlines


 Table 13--Summary Details on Data Collection Period and Data Submission Timeline for Previously Adopted Quality
 Measures Affecting the FY 2018 Payment Determination That Will Use Only 1 CY Quarter of Data Initially for the
                                   Purpose of Determining Provider Compliance
----------------------------------------------------------------------------------------------------------------
 
----------------------------------------------------------------------------------------------------------------
Finalized Measure:
 NQF #0674 Application of Percent of Residents Experiencing One or More Falls with Major Injury (Long
 Stay) (80 FR 47122)
 NQF #2631 Application of Percent of Long-Term Care Hospital Patients with an Admission and Discharge
 Functional Assessment and a Care Plan That Addresses Function (80 FR 47122)
 NQF #2633 IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients
 (80 FR 47122)
 NQF #2634 IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients
 (80 FR 47122)
 NQF #2635 IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients
 (80 FR 47122)
 NQF #2636 IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients
 (80 FR 47122)
----------------------------------------------------------------------------------------------------------------
          Submission method               Data collection/       Quarterly review and       APU Determination
                                        submission quarterly      correction periods             affected
                                         reporting period(s)        data submission
                                                                 deadlines for payment
                                                                  determination */**
----------------------------------------------------------------------------------------------------------------
IRF-PAI/QIES ASAP System............  CY 16 Q4, 10/1/16-12/31/ 1/1/2017-5/15/17.......  FY 2018.
                                       16.
----------------------------------------------------------------------------------------------------------------
* We refer readers to the Table 12 for an illustration of the data collection/submission quarterly reporting
  periods and correction and submission deadlines, which will be followed for the above measures, for all
  payment determinations subsequent to that of FY 2018.
** We note that the submission of IRF-PAI data must also adhere to the IRF PPS deadlines.


Table 14--Summary Details on Data Collection Period and Data Submission Timeline for Previously Adopted CDC/NHSN
 Quality Measures Affecting the FY 2018 Payment Determination and Subsequent Years That Will Use 4 CY quarters *
----------------------------------------------------------------------------------------------------------------
 
----------------------------------------------------------------------------------------------------------------
Finalized Measures:
 NQF #0138 NHSN Catheter-Associated Urinary Tract Infection (CAUTI) Outcome Measure (80 FR 47122 through
 47123)
 NQF #1716 NHSN Facility-wide Inpatient Hospital-onset Methicillin-resistant Staphylococcus aureus
 (MRSA) Bacteremia Outcome Measure (80 FR 47122 through 47123)
 NQF #1717 NHSN Facility-wide Inpatient Hospital-onset Clostridium difficile Infection (CDI) Outcome
 Measure (79 FR 45917)
----------------------------------------------------------------------------------------------------------------

[[Page 52120]]

 
          Submission method                Data Collection/       Quarterly Review and      APU determination
                                         submission Quarterly      Correction Periods            affected
                                          Reporting Period(s)        Data Submission
                                                                  Deadlines for Payment
                                                                      Determination
----------------------------------------------------------------------------------------------------------------
CDC/NHSN.............................  CY 16 Q1, 1/1/16-3/31/   4/1/2016-8/15/16 ** and  FY 2018 and subsequent
                                        16 and Q1 of             4/1-8/15 of subsequent   years.**
                                        subsequent Calendar      years.
                                        Years.
                                       CY 16 Q2, 4/1/16-6/30/   7/1/16-11/15/16 **and 7/
                                        16 and Q2 of             1-11/15 of subsequent
                                        subsequent Calendar      years.
                                        Years.
                                       CY 16 Q3, 7/1/16-9/30/   10/1/16-2/15/17 ** and
                                        16 and Q3 of             10/1-2/15 of
                                        subsequent Calendar      subsequent years.
                                        Years.
                                       CY 16 Q4, 10/1/16-12/31/ 1/1/17-5/15/17 ** and 1/
                                        16 and Q4 of             1-5/15 of subsequent
                                        subsequent Calendar      years.
                                        Years.
----------------------------------------------------------------------------------------------------------------
* We refer readers to the Table 14 for an illustration of the data collection/submission quarterly reporting
  periods and correction and submission deadlines.
** As is illustrated in Table 14: Subsequent years follow the same CY Quarterly Data Collection/submission
  Quarterly Reporting Periods and Quarterly Review and Correction Periods Deadlines for Payment Determination in
  which every CY quarter is followed by approximately 135 days for IRFs to review and correct their data until
  midnight on the final submission deadline dates.


 Table 15--Summary Details on Data Collection Period and Data Submission Timeline for Previously Adopted IRF-PAI
  Quality Measures Affecting the FY 2019 Payment Determination and Subsequent Years That Will Use 4 CY Quarters
----------------------------------------------------------------------------------------------------------------
 
----------------------------------------------------------------------------------------------------------------
Finalized Measures:
 NQF #0678 Percent of Residents or Patients with Pressure Ulcers That Are New or Worsened (Short Stay)
 (80 FR 47122)
 NQF #0674 Application of Percent of Residents Experiencing One or More Falls with Major Injury (Long
 Stay) (80 FR 47122)
 NQF #2631 Application of Percent of Long-Term Care Hospital Patients with an Admission and Discharge
 Functional Assessment and a Care Plan That Addresses Function (80 FR 47122)
 NQF #2633 IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients
 (80 FR 47122)
 NQF #2634 IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients
 (80 FR 47122)
 NQF #2635 IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients
 (80 FR 47122)
 NQF #2636 IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients
 (80 FR 47122)
----------------------------------------------------------------------------------------------------------------
          Submission method                Data Collection/       Quarterly Review and      APU determination
                                         submission Quarterly      Correction Periods            affected
                                          Reporting Period(s)        Data Submission
                                                                  Deadlines for Payment
                                                                   Determination */**
----------------------------------------------------------------------------------------------------------------
IRF-PAI/QIES ASAP System.............  CY 17 Q1, 1/1/17-3/31/   4/1/2017-8/15/17 ***     FY 2019 and subsequent
                                        17 and Q1 of             and 4/1-8/15 of          years.***
                                        subsequent Calendar      subsequent years.
                                        Years.
                                       CY 17 Q2, 4/1/17-6/30/   7/1/17-11/15/17 *** and
                                        17 and Q2 of             7/1-11/15 of
                                        subsequent Calendar      subsequent years.
                                        Years.
                                       CY 17 Q3, 7/1/17-9/30/   10/1/17-2/15/18 *** and
                                        17 and Q3 of             10/1-1/15 of
                                        subsequent Calendar      subsequent years.
                                        Years.
                                       CY 17 Q4, 10/1/17-12/31/ 1/1/18-5/15/18 *** and
                                        17 and Q4 of             1/1-5/15 of subsequent
                                        subsequent Calendar      years.
                                        Years.
----------------------------------------------------------------------------------------------------------------
 We refer readers to the Table 15 for an illustration of the data collection/submission quarterly reporting
  periods and correction and submission deadlines.
** We note that the submission of IRF-PAI data must also adhere to the IRF PPS deadlines.
*** As is illustrated in Table 15: Subsequent years follow the same CY Quarterly Data Collection/submission
  Quarterly Reporting Periods and Quarterly Review and Correction Periods) and Data Submission Deadlines for
  Payment Determination in which every CY quarter is followed by approximately 135 days for IRFs to review and
  correct their data until midnight on the final submission deadline dates.

    In the FY 2014 IRF PPS final rule, we adopted the Percent of 
Residents or Patients Who Were Assessed and Appropriately Given the 
Seasonal Influenza Vaccine (Short Stay) (NQF #0680) measure for the FY 
2017 payment determination and subsequent years (78 FR 47910 through 
47911). In the FY 2014 IRF PPS final rule (78 FR 47917 through 47919), 
we finalized the data submission timelines and submission deadlines for 
the measures for FY 2017 payment determination. Refer to the FY 2014 
final rule (78 FR 47917 through 47919) for a more detailed discussion 
of these timelines and deadlines.
    We want to clarify that this measure includes all patients in the 
IRF one or more days during the influenza vaccination season (IVS) 
(October 1 of

[[Page 52121]]

any given CY through March 31 of the subsequent CY). This includes, for 
example, a patient is admitted September 15, 2015, and discharged April 
1, 2016 (thus, the patient was in the IRF during the 2015-2016 
influenza vaccination season). If a patient's stay did not include one 
or more days in the IRF during the IVS, IRFs must also complete the 
influenza items. For example, if a patient was admitted after April 1, 
2016, and discharged September 30, 2016, and the patient did not 
receive the influenza vaccine during the IVS, IRFs should code the 
reason the patient did not receive the influenza vaccination as 
``patient was not in the facility during this year's influenza 
vaccination season.''
    Further, we wish to clarify that the data submission timeline for 
this measure includes 4 calendar quarters and is based on the influenza 
season (July 1 through June 30 of the subsequent year), rather than on 
the calendar year. For the purposes of APU determination and for public 
reporting, data calculation and analysis uses data from an influenza 
vaccination season that is within the influenza season itself. While 
the influenza vaccination season is October 1 of a given year (or when 
the vaccine becomes available) through March 31 of the subsequent year, 
this timeframe rests within a greater time period of the influenza 
season which spans 12 months--that is July 1 of a given year through 
June 30 of the subsequent year. Thus for this measure, we utilize data 
from a timeframe of 12 months that mirrors the influenza season which 
is July 1 of a given year through June 30th of the subsequent year. 
Additionally, for the APU determination, we review data that has been 
submitted beginning on July 1 of the calendar year 2 years prior to the 
calendar year of the APU effective date and ending June 30 of the 
subsequent calendar year, one year prior to the calendar year of the 
APU effective date. For example, and as provided in Table 14 for the FY 
2019 (October 1, 2018) APU determination, we review data submission 
beginning July 1 of 2016 through June 30th of June 2017 for the 2016/
2017 influenza vaccination season, so as to capture all data that an 
IRF will have submitted with regard to the 2016/2017 Influenza season 
itself. We will use assessment data for that time period as well for 
public reporting. Further, because we enable the opportunity to review 
and correct data for all assessment based IRF-PAI measures within the 
IRF QRP, we continue to follow quarterly calendar data collection/
submission quarterly reporting period(s) and their subsequent quarterly 
review and correction periods with data submission deadlines for public 
reporting and payment determinations. However, rather than using CY 
timeframe, these quarterly data collection/submission periods and their 
subsequent quarterly review and correction periods and submission 
deadlines begin with CY quarter 3, July 1, of a given year and end June 
30th, CY quarter 2, of the following year. For further information on 
data collection for this measure, please refer to section 4 of the IRF-
PAI training manual, which is available on the CMS IRF QRP Measures 
Information Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html, under the 
downloads section. For further information on data submission of the 
IRF-PAI, please refer to the IRF-PAI Data Specifications Version 1.12.1 
(FINAL)--in effect on October 1, 2015, available for download at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/Software.html.
    Refer to Table 16 for details about the quarterly data collection/
submission and the review and correction deadlines for FY 2019 and 
subsequent years for NQF #0680 Percent of Residents or Patients Who 
Were Assessed and Appropriately Given the Seasonal Influenza Vaccine.

 Table 16--Summary Details on Data Collection Period and Data Submission Timeline for Previously Adopted IRF-PAI
    Quality Measure, NQF #0680 Percent of Residents or Patients Who Were Assessed and Appropriately Given the
         Seasonal Influenza Vaccine, Affecting the FY 2019 Payment Determination and Subsequent Years *
----------------------------------------------------------------------------------------------------------------
 
----------------------------------------------------------------------------------------------------------------
Finalized Measure:
 NQF #0680 Percent of Residents or Patients Who Were Assessed and Appropriately Given the Seasonal
 Influenza Vaccine (80 FR 47122)
----------------------------------------------------------------------------------------------------------------
          Submission method                Data collection/       Quarterly review and      APU determination
                                         submission Quarterly      correction periods            affected
                                          Reporting Period(s)        data submission
                                                                  deadlines for payment
                                                                    determination **
----------------------------------------------------------------------------------------------------------------
IRF-PAI/QIES ASAP System.............  CY 16 Q3, 7/1/16-9/30/   10/1/16-2/15/17 ** and   FY 2019 and subsequent
                                        16 and Q3 of             10/1-2/15 of             years.**
                                        subsequent Calendar      subsequent years.
                                        Years.
                                       CY 16 Q4, 10/1/16-12/31/ 1/1/17-5/15/17 ** and 1/
                                        16 and Q4 of             1-5/15 of subsequent
                                        subsequent Calendar      years.
                                        Years.
                                       CY 17 Q1, 1/1/17-3/31/   4/1/17-8/15/17 ** and 4/
                                        17 and Q1 of             1-8/15 of subsequent
                                        subsequent Calendar      years.
                                        Years.
                                       CY 17 Q2, 4/1/17-6/30/   7/1/17-11/15/17 ** and
                                        17 and Q2 of             7/1-11/15 of
                                        subsequent Calendar      subsequent years.
                                        Years.
----------------------------------------------------------------------------------------------------------------
* We note that the submission of IRF-PAI data must also adhere to the IRF PPS deadlines.
** As is illustrated in Table 16: Subsequent years follow the same CY Quarterly Data Collection/submission
  Quarterly Reporting Periods and Quarterly Review and Correction Periods (IRF-PAI) and Data Submission (CDC/
  NHSN) Deadlines for Payment Determination in which every CY quarter is followed by approximately 135 days for
  IRFs to review and correct their data until midnight on the final submission deadline dates.

    We finalized in the FY 2014 IRF PPS final rule (78 FR 47905 through 
47906) that for FY 2016 and subsequent years IRFs will submit data on 
the quality measure Influenza Vaccination Coverage among Healthcare 
Personnel (NQF

[[Page 52122]]

#0431) beginning with data submission starting October 1, 2014 (or when 
the influenza vaccine becomes available). To clarify that while the 
data collected by IRFs for this measure includes vaccination 
information for a flu vaccination season that begins October 1 (or when 
the vaccine becomes available) of a given year through March 31 of the 
subsequent year, the CDC/NHSN system only allows for the submission of 
the corresponding data any time between October 1 of a given year until 
March 31 of the subsequent year; however, corrections can be made to 
such data until May 15th of that year. Quality data for this measure 
are only required to be submitted once per IVS (Oct 1 through March 
31), but must be submitted prior to the May 15 deadline for the year in 
which the IVS ends; quarterly reporting is not required. For example, 
for FY 2018 payment determinations, while IRFs can begin immunizing 
their staff when the vaccine is available throughout the influenza 
vaccination season which ends on March 31, 2016, IRFs can only begin 
submitting the data for this measure via the CDC/NHSN system starting 
on October 1, 2015, and may do so up until May 15 of 2016.

  Table 17--Summary Details on the Data Submission Timeline and Correction Deadline Timeline for the Previously
    Adopted Influenza Vaccination Coverage Among Healthcare Personnel Affecting CY 2018 and Subsequent Years
----------------------------------------------------------------------------------------------------------------
 
----------------------------------------------------------------------------------------------------------------
 Influenza Vaccination Coverage Among   Data submission Period    Review and Correction Periods Data Submission
 Healthcare Personnel Data submission                             (CDC/NHSN) Deadlines for payment determination
              Quarters +                                                                ++
----------------------------------------------------------------------------------------------------------------
CY QTR 4 through Subsequent CY QTR 1.  10/1/15-3/31/16 and 10/  4/1/16-5/15/16 and 4/1-  Deadline: May 15, 2016
                                        1-3/31 of subsequent     5/15 of subsequent       and May 15 of
                                        years.                   years.                   subsequent years.
----------------------------------------------------------------------------------------------------------------
+ Data on this measure may be submitted via the CDC/NHSN system from October 1 of a given year through May 15 of
  the subsequent year.
++ A time period of April 1-May 15th is also allotted for the submission, review, and corrections.


 Table 18--Finalized IRF QRP Claims-Based Measure Affecting FY 2018 and
                            Subsequent Years
------------------------------------------------------------------------
                                    Data submission
         Quality measure                method        Performance period
------------------------------------------------------------------------
NQF #2502 All-Cause Unplanned     Medicare FFS        CY 2013 and 2014
 Readmission Measure for 30 Days   Claims.             for public
 Post-Discharge from Inpatient                         reporting in
 Rehabilitation Facilities (80                         2016.
 FR 47087 through 47089).                             CY 2014 and 2015
                                                       for public
                                                       reporting in
                                                       2017.
------------------------------------------------------------------------

    Although we did not solicit feedback, we received several comments 
about the previously finalized policy to adopt calendar year data 
collection time frames, unless there is a clinical reason for an 
alternative data collection time frame, which are summarized with our 
responses below.
    Comment: Several commenters supported these data collection 
timelines to simplify the data collection and reporting process, as 
summarized in the FY 2016 IRF PPS Final Rule (80 FR 47122 through 
47123).
    Response: We thank these commenters for their support.
    Comment: One commenter generally supported the change to calendar 
year, but was concerned that the IRF-PAI versions aligned with the 
fiscal year. Several others also commented that since updates are made 
to the IRF-PAI on a FY basis, this change would create a discrepancy 
within a single calendar year's data set. Many commenters were 
concerned that variations in FY 2018 APU data collection periods placed 
an increased burden on IRFs to maintain compliance and requested that 
CMS grant some leniency to an IRF the first time it is not compliant 
with quality reporting due to the new CY-based deadlines.
    Response: When we finalized this change in the FY 2016 IRF PPS 
final rule (80 FR 47122 through 47123), we posited this change would 
simplify the data collection and submission time frame under the IRF 
QRP for IRF providers. It would also eliminate the situation in which 
data collection during a quarter in the same calendar year can affect 2 
different years of annual payment update determination (that is, 
October 1 to December 31 is the first quarter of data collection for 
quality measures with a FY-based data collection time frame and the 
last quarter of data collection for quality measures with a CY-based 
data collection time frame). This change means that when additional 
quality measures that use IRF-PAI as the data collection mechanism, 
such as the measure Drug Regimen Review Conducted with Follow-Up for 
Identified Issues, are adopted for future use in the IRF QRP, the first 
data collection time frame for those newly-adopted measures will be 3 
months (October to December) and subsequent data collection time frames 
would follow a calendar year data collection time frame. This policy 
only affects IRFs insofar as for these newly adopted measures, 
compliance determinations for the applicable FY APU will only reflect 
data collection and submission for Q4 of the CY in which data 
collection begins. This does not create a discrepancy in the data set, 
as stated by the commenter, as we would use the following CY of data 
for APU analysis and public reporting purposes, should state measures 
be proposed and finalized for public display in the future.
    With regard to concerns about increased burden with the change in 
data collection periods and requests for leniency regarding submission 
deadlines, we disagree that leniency is warranted, given that there is 
no discrepancy in the data set and the policy only affects the first 
quarter of data collection for newly adopted measures. We have ongoing 
education regarding data submission deadlines, including quarterly 
email reminders of upcoming deadlines. We also remind the reader of the 
availability of the reconsideration process, in which IRFs may file for 
reconsideration if they believe the finding of non-compliance is in 
error, or they have evidence of the impact of extraordinary 
circumstances which prevented timely submission of data.

[[Page 52123]]

b. Timeline and Data Submission Mechanisms for the FY 2018 Payment 
Determination and Subsequent Years for the IRF QRP Resource Use and 
Other Measures Claims-Based Measures
    The MSPB PAC IRF QRP measure; Discharge to Community PAC IRF QRP 
measure; Potentially Preventable 30-Day Post-Discharge Readmission 
Measure for IRF QRP; and Potentially Preventable Within Stay 
Readmission Measure for IRFs, which we are finalizing in this final 
rule, are Medicare FFS claims-based measures. Because claims-based 
measures can be calculated based on data that are already reported to 
the Medicare program for payment purposes, no additional information 
collection will be required from IRFs. As discussed in section VIII.F 
of this final rule, these measures will use 2 years of claims-based 
data beginning with CY 2015 and CY 2016 claims to inform confidential 
feedback reports for IRFs, and CYs 2016 and 2017 claims data for public 
reporting.
    We invited public comments on this proposal. We did not receive 
comments related to data submission mechanisms for these measures. For 
comments related to the measures, please see section VIII.F of this 
final rule. For comments related to the future public display of these 
measures, please see section VIII.N of this final rule.
    We finalize the timeline and data submission mechanisms for FY 2018 
payment determination and subsequent years as proposed.
c. Timeline and Data Submission Mechanisms for the IRF QRP Quality 
Measure for the FY 2020 Payment Determination and Subsequent Years
    As discussed in section VIII.F of this final rule, we proposed that 
the data for the quality measure, Drug Regimen Review Conducted with 
Follow-Up for Identified Issues--PAC IRF QRP, affecting FY 2020 payment 
determination and subsequent years, be collected by completing data 
elements that will be added to the IRF-PAI with submission through the 
QIES-ASAP system. Data collection will begin on October 1, 2018. More 
information on IRF reporting using the QIES-ASAP system is located at 
the Web site at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/IRFPAI.html.
    For the FY 2020 payment determinations, we proposed to use CY 2018 
4th quarter data, that is, beginning with discharges on October 1, 
2018, through discharges on December 31, 2018, to remain consistent 
with the usual October release schedule for the IRF-PAI, to give IRFs 
sufficient time to update their systems so that they can comply with 
the new data reporting requirements, and to give us sufficient time to 
determine compliance for the FY 2020 program. The proposed use of 1 
quarter of data for the initial year of assessment data reporting in 
the IRF QRP, to make compliance determinations related to the 
applicable FY APU, is consistent with the approach we used previously 
for the SNF, LTCH, and Hospice QRPs.
    Table 18 presents the proposed data collection period and data 
submission timelines for the new IRF QRP quality measure, Drug Regimen 
Review Conducted with Follow-Up for Identified Issues--PAC IRF QRP, for 
the FY 2020 Payment Determination. We invited public comments on this 
proposal.

Table 19--Details on the Proposed Data Collection Period and Data Submission Timeline for Resource Use and Other
                              Measures Affecting the FY 2020 Payment Determination
----------------------------------------------------------------------------------------------------------------
                                                                                                       APU
       Quality measure              Submission method        Data collection   Data correction    determination
                                                                 period          deadlines *        affected
----------------------------------------------------------------------------------------------------------------
Drug Regimen Review Conducted  IRF-PAI/QIES ASAP            CY 2018 Q4, 10/1/ 5/15/19           FY 2020.
 with Follow-Up for                                          18-12/31/18;      Quarterly
 Identified Issues PAC IRF                                   Quarterly for     approximately
 QRP.                                                        each subsequent   135 days after
                                                             calendar year.    the end of each
                                                                               quarter for
                                                                               subsequent
                                                                               years..
----------------------------------------------------------------------------------------------------------------
* We note that the submission of IRF-PAI data must also adhere to the IRF PPS deadlines.

    Following the close of the reporting quarter, October 1, 2018, 
through December 31, 2018, for the FY 2020 payment determination, IRFs 
will have the already established additional 4.5 months to correct 
their quality data and that the final deadline for correcting data for 
the FY 2020 payment determination will be May 15, 2019 for these 
measures. We further proposed that for the FY 2021 payment 
determination and subsequent years, we will collect data using the 
calendar year reporting cycle as described in section VIII.I.c of this 
final rule, and illustrated in Table 20. We invited public comments on 
this proposal.
    We did not receive any comments on the proposed data collection 
periods and data submission timelines for the new proposed IRF QRP 
quality measure for the FY 2020 and FY 2021 payment determination and 
subsequent years.
    Final Decision: We finalize the timeline and data submission 
mechanisms for FY 2020 and FY2021 payment determinations and subsequent 
years as proposed, as described in Table 19. For comments related to 
the measure, Drug Regimen Review Conducted with Follow-Up for 
Identified Issues PAC IRF QRP, please see section VIII.G of final rule.

[[Page 52124]]



     Table 20--Proposed Data Collection Period and Data Correction Deadlines * Affecting the FY 2021 Payment
                                       Determination and Subsequent Years
----------------------------------------------------------------------------------------------------------------
                                                                                                     Proposed
                                                                                                    quarterly
                                                                                                 review and data
                                                             Proposed CY data    Proposed data      correction
       Quality measure              Submission method           collection        collection        periods *
                                                                 quarter            period        deadlines for
                                                                                                     payment
                                                                                                  determination
----------------------------------------------------------------------------------------------------------------
Drug Regimen Review Conducted  IRF-PAI/QIES ASAP            Quarter 1........  January 1-March   April 1- August
 with Follow-Up for                                         Quarter 2........   31.               15.
 Identified Issues PAC IRF                                  Quarter 3........  April 1-June 30.  July 1-November
 QRP.                                                       Quarter 4........  July 1-September   15.
                                                                                30.              October 1-
                                                                               October 1-         February 15.
                                                                                December 31.     January 1-May
                                                                                                  15.
----------------------------------------------------------------------------------------------------------------
* We note that the submission of IRF-PAI data must also adhere to the IRF PPS deadlines.

J. IRF QRP Data Completion Thresholds for the FY 2016 Payment 
Determination and Subsequent Years

    In the FY 2015 IRF PPS final rule (79 FR 45921 through 45923), we 
finalized IRF QRP thresholds for completeness of IRF data submissions. 
To ensure that IRFs are meeting an acceptable standard for completeness 
of submitted data, we finalized the policy that, beginning with the FY 
2016 payment determination and for each subsequent year, IRFs must meet 
or exceed two separate data completeness thresholds: One threshold set 
at 95 percent for completion of quality measures data collected using 
the IRF-PAI submitted through the QIES and a second threshold set at 
100 percent for quality measures data collected and submitted using the 
CDC NHSN.
    Additionally, we stated that we will apply the same thresholds to 
all measures adopted as the IRF QRP expands and IRFs begin reporting 
data on previously finalized measure sets. That is, as we finalize new 
measures through the regulatory process, IRFs will be held accountable 
for meeting the previously finalized data completion threshold 
requirements for each measure until such time that updated threshold 
requirements are proposed and finalized through a subsequent regulatory 
cycle.
    Further, we finalized the requirement that an IRF must meet or 
exceed both thresholds to avoid receiving a 2 percentage point 
reduction to their annual payment update for a given fiscal year, 
beginning with FY 2016 and for all subsequent payment updates. For a 
detailed discussion of the finalized IRF QRP data completion 
requirements, please refer to the FY 2015 IRF PPS final rule (79 FR 
45921 through 45923). We proposed to codify the IRF QRP Data Completion 
Thresholds at Sec.  412.634. We invited public comments on this 
proposal.
    We received several comments with concerns about the proposal to 
codify the IRF QRP Data Completion Thresholds at Sec.  412.634, which 
are summarized below.
    Comment: One commenter supported the 100 percent standard, but had 
concerns regarding technical errors with the NHSN that IRFs have 
experienced in the past year. Several commenters expressed concern 
about the threshold set at 100 percent for quality measures data 
collected and submitted using the CDC NHSN, citing significant burden 
on infection preventionists to review and complete reports in NHSN. One 
commenter expressed concern that the data completion threshold would be 
applied to data collected in FY 2014, having a retroactive impact on 
payment. One commenter recommended changes to the NHSN that could 
alleviate the reporting requirement, including minimize the reporting 
of elements outside of CMS regulatory requirements, as well as altering 
the system to remove monthly reporting plans or allowing them to be 
submitted electronically.
    Response: We wish to clarify that the IRF QRP thresholds for 
completeness of IRF data submissions were finalized in the FY 2015 IRF 
PPS final rule (79 FR 45921 through 45923), beginning with FY 2016, 
which considered quality data submitted during CY 2014. We have 
continually maintained that providers should be submitting complete and 
accurate data, and the adoption of the data completion thresholds in 
the FY 2015 IRF PPS final rule did not change this policy. We believe 
that both data completion thresholds are achievable, as evidenced by 
the 91 percent of IRFs that were able to achieve these thresholds for 
purposes of the FY 2016 payment determination. We have also taken 
strides to assist providers achieve compliance, including regular 
notification of upcoming deadlines, updated guidance documents, 
increased outreach to providers with incomplete data submissions, and 
the development of several reports which will help providers better 
determine where they stand with respect to compliance throughout the 
year. We appreciate the commenters' concerns related to burden and have 
taken this into consideration when issuing data completion thresholds.
    Final Decision: We are finalizing our proposal to codify the IRF 
QRP data completion thresholds at Sec.  412.634.

K. IRF QRP Data Validation Process for the FY 2016 Payment 
Determination and Subsequent Years

    Validation is intended to provide added assurance of the accuracy 
of the data that will be reported to the public as required by sections 
1886(j)(7)(E) and 1899B(g) of the Act. In the FY 2015 IRF PPS rule (79 
FR 45923), we finalized, for the FY 2016 adjustments to the IRF PPS 
annual increase factor and subsequent years, a process to validate the 
data submitted for quality purposes. However, in the FY 2016 IRF PPS 
final rule (80 FR 47124), we finalized our decision to temporarily 
suspend the implementation of this policy. We did not propose a data 
validation policy in the FY 2017 IRF PPS proposed rule, as we are 
developing a policy that could be applied to several PAC QRPs. We 
intend to propose a data validation policy through future rulemaking.

L. Previously Adopted and Codified IRF QRP Submission Exception and 
Extension Policies

    Refer to Sec.  412.634 for requirements pertaining to submission 
exception and extension for the FY 2017 payment determination and 
subsequent years. We proposed to revise Sec.  412.634 to change the 
timing for submission of these exception and extension requests from 30 
days to 90 days from the date of the qualifying event which is 
preventing an IRF from submitting their quality data for the IRF QRP. 
We proposed the increased time allotted for the submission of the 
requests from 30 to 90 days to be consistent with other quality 
reporting programs; for example, the Hospital Inpatient Quality 
Reporting (IQR) Program also proposed to extend the deadline to 90 days 
in the FY 2017 IPPS/LTCH PPS proposed rule (81 FR 25205). We believe 
that this increased time will assist providers experiencing

[[Page 52125]]

an event in having the time needed to submit such a request. We believe 
that allowing only 30 days was insufficient. With the exception of this 
one change, we did not propose any additional changes to the exception 
and extension policies for the IRF QRP at this time.
    We invited public comments on the proposal to revise Sec.  412.634 
to change the timing for submission of these exception and extension 
requests from 30 days to 90 days from the date of the qualifying event 
which is preventing an IRF from submitting their quality data for the 
IRF QRP. We received one comment on this proposal, which is summarized 
and addressed below in this section.
    Comment: One commenter supported changing the timing for submission 
of exception and extension requests from 30 days to 90 days from the 
date of the qualifying event preventing an IRF from submitting their 
IRF QRP data.
    Response: We thank the commenter for their support.
    Final Decision: After careful consideration of the public comments, 
we are finalizing our proposal to revise Sec.  412.634 to change the 
timing for submission of these exception and extension requests from 30 
days to 90 days from the date of the qualifying event which is 
preventing an IRF from submitting their quality data for the IRF QRP.

M. Previously Adopted and Finalized IRF QRP Reconsideration and Appeals 
Procedures

    Refer to Sec.  412.634 for a summary of our finalized 
reconsideration and appeals procedures for the IRF QRP for FY 2017 
payment determination and subsequent years. We did not propose any 
changes to this policy. However, we wish to clarify that in order to 
notify IRFs found to be non-compliant with the reporting requirements 
set forth for a given payment determination, we may include the QIES 
mechanism in addition to U.S. Mail, and we may elect to utilize the 
MACs to administer such notifications.
    We received several comments about the previously adopted and 
finalized IRF QRP reconsideration and appeals procedures, which are 
summarized below.
    Comment: One commenter requested that the notification also include 
the reason for non-compliance. Multiple commenters appreciated that CMS 
is using both U.S. Mail and the QIES system to notify IRFs found to be 
non-compliant. Another commenter recommended that CMS continue using 
the U.S. Mail method, noting that QIES may not be a reliable way to 
distribute time-sensitive information. Several commenters were 
concerned about the possibility of using MACs to administer 
notifications, citing their lack of expertise in quality reporting, and 
requested that CMS clarify the authority that MACs would have to 
consider IRF QRP compliance and levy corrective action.
    Response: We intend to retain this method of notification in 
addition to the use of QIES. We wish to clarify that the role of the 
MACs is for notification purposes only. They do not have a role in 
determining provider compliance in meeting the IRF QRP reporting 
requirements. We intend to include the reason for non-compliance in the 
notifications distributed via the CASPER folders; however, we wish to 
remind facilities that there are reports available in QIES (more 
information at: https://www.qtso.com/irfpai.html) and NHSN (more 
information at: http://www.cdc.gov/nhsn/cms/) that can be utilized to 
confirm quality measure data submissions. Additional information 
regarding non-compliance is also available on the IRF QRP 
Reconsiderations Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Reconsideration-and-Exception-and-Extension.html.

N. Public Display of Measure Data for the IRF QRP & Procedures for the 
Opportunity to Review and Correct Data and Information

1. Public Display of Measures
    Section 1886(j)(7)(E) of the Act requires the Secretary to 
establish procedures for making the IRF QRP data available to the 
public. In the FY 2016 IRF PPS final rule (80 FR 47126 through 47127), 
we finalized our proposals to display performance data for the IRF QRP 
quality measures by Fall 2016 on a CMS Web site, such as the Hospital 
Compare, after a 30-day preview period, and to give providers an 
opportunity to review and correct data submitted to the QIES-ASAP 
system or to the CDC NHSN. The procedures for the opportunity to review 
and correct data are provided in section VIII.N.2 of this final rule. 
In addition, we finalized the proposal to publish a list of IRFs that 
successfully meet the reporting requirements for the applicable payment 
determination on the IRF QRP Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/Spotlights-Announcements.html. In the FY 2016 IRF PPS final 
rule, we finalized that we will update the list after the 
reconsideration requests are processed on an annual basis.
    Also, in the FY 2016 IRF PPS final rule (80 FR 47126 through 
47127), we also finalized that the display of information for fall 2016 
contains performance data on three quality measures:
     Percent of Residents or Patients with Pressure Ulcers That 
Are New or Worsened (Short Stay) (NQF #0678);
     NHSN CAUTI Outcome Measure (NQF #0138); and
     All-Cause Unplanned Readmission Measure for 30 Days Post-
Discharge from IRFs (NQF #2502).
    The measures Percent of Residents or Patients with Pressure Ulcers 
That Are New or Worsened (Short Stay) (NQF #0678) and NHSN CAUTI 
Outcome Measure (NQF #0138) are based on data collected beginning with 
the first quarter of 2015 or discharges beginning on January 1, 2015. 
With the exception of the All-Cause Unplanned Readmission Measure for 
30 Days Post-Discharge from IRFs (NQF #2502), rates are displayed based 
on 4 rolling quarters of data and will initially use discharges from 
January 1, 2015, through December 31, 2015 (CY 2015) for Percent of 
Residents or Patients with Pressure Ulcers That Are New or Worsened 
(Short Stay) (NQF #0678) and data collected from January 1, 2015, 
through December 31, 2015 (CY 2015) for NHSN CAUTI Outcome Measure (NQF 
#0138). For the readmissions measure, data will be publicly report 
beginning with data collected for discharges beginning January 1, 2013, 
and rates will be displayed based on 2 consecutive years of data. For 
IRFs with fewer than 25 eligible cases, we proposed to assign the IRF 
to a separate category: ``The number of cases is too small (fewer than 
25) to reliably tell how well the IRF is performing.'' If an IRF has 
fewer than 25 eligible cases, the IRF's readmission rates and interval 
estimates will not be publicly reported for the measure.
    Calculations for all three measures are discussed in detail in the 
FY 2016 IRF PPS final rule (80 FR 47126 through 47127).
    Pending the availability of data, we proposed to publicly report 
data in CY 2017 on 4 additional measures beginning with data collected 
on these measures for the first quarter of 2015, or discharges 
beginning on January 1, 2015: (1) Facility-wide Inpatient Hospital-
onset Methicillin-resistant Staphylococcus aureus (MRSA) Bacteremia 
Outcome Measure (NQF #1716) ; (2) Facility-wide Inpatient Hospital-
onset Clostridium difficile Infection (CDI) Outcome Measure (NQF #1717) 
and, beginning with the 2015-16

[[Page 52126]]

influenza vaccination season, these two measures; (3) Influenza 
Vaccination Coverage Among Healthcare Personnel (NQF #0431); and (4) 
Percent of Residents or Patients Who Were Assessed and Appropriately 
Given the Seasonal Influenza Vaccine (NQF #0680).
    Standardized infection ratios (SIRs) for the Facility-wide 
Inpatient Hospital-onset Methicillin-resistant Staphylococcus aureus 
(MRSA) Bacteremia Outcome Measure (NQF #1716) and Facility-wide 
Inpatient Hospital-onset Clostridium difficile Infection (CDI) Outcome 
Measure (NQF #1717) will be displayed based on 4 rolling quarters of 
data and will initially use MRSA bacteremia and CDI events that 
occurred from January 1, 2015 through December 31, 2015 (CY 2015), for 
calculations. We proposed that the display of these ratios will be 
updated quarterly. Rates for the Influenza Vaccination Coverage Among 
Healthcare Personnel (NQF #0431) will initially be displayed for 
personnel working in the reporting facility October 1, 2015 through 
March 31, 2016. Rates for the Percent of Residents or Patients Who Were 
Assessed and Appropriately Given the Seasonal Influenza Vaccine (NQF 
#0680) will also initially be displayed for patients in the IRF during 
the influenza vaccination season, from October 1, 2015, through March 
31, 2016. We proposed that the display of these rates will be updated 
annually for subsequent influenza vaccination seasons.
    Calculations for the MRSA and CDI Healthcare Associated Infection 
(HAI) measures adjust for differences in the characteristics of 
hospitals and patients using a SIR. The SIR is a summary measure that 
takes into account differences in the types of patients that a hospital 
treats. For a more detailed discussion of the SIR, please refer to the 
FY 2016 IRF PPS final rule (80 FR 47126 through 47127). The MRSA and 
CDI SIRs may take into account the laboratory methods, bed size of the 
hospital, and other facility-level factors. It compares the actual 
number of HAIs in a facility or state to a national benchmark based on 
previous years of reported data and adjusts the data based on several 
factors. A confidence interval with a lower and upper limit is 
displayed around each SIR to indicate that there is a high degree of 
confidence that the true value of the SIR lies within that interval. A 
SIR with a lower limit that is greater than 1.0 means that there were 
more HAIs in a facility or state than were predicted, and the facility 
is classified as ``Worse than the U.S. National Benchmark.'' If the SIR 
has an upper limit that is less than 1, the facility had fewer HAIs 
than were predicted and is classified as ``Better than the U.S. 
National Benchmark.'' If the confidence interval includes the value of 
1, there is no statistical difference between the actual number of HAIs 
and the number predicted, and the facility is classified as ``No 
Different than U.S. National Benchmark.'' If the number of predicted 
infections is less than 1.0, the SIR and confidence interval are not 
calculated by CDC.
    Calculations for the Influenza Vaccination Coverage Among 
Healthcare Personnel (NQF #0431) are based on reported numbers of 
personnel who received an influenza vaccine at the reporting facility 
or who provided written documentation of influenza vaccination outside 
the reporting facility. The sum of these two numbers is divided by the 
total number of personnel working at the facility for at least 1 day 
from October 1 through March 31 of the following year, and the result 
is multiplied by 100 to produce a compliance percentage (vaccination 
coverage). No risk adjustment is applicable to these calculations. More 
information on these calculations and measure specifications is 
available at http://www.cdc.gov/nhsn/pdfs/hps-manual/vaccination/4-hcp-vaccination-module.pdf. We proposed that this data will be displayed on 
an annual basis and will include data submitted by IRFs for a specific, 
annual influenza vaccination season. A single compliance (vaccination 
coverage) percentage for all eligible healthcare personnel will be 
displayed for each facility.
    We invited public comment on our proposal to begin publicly 
reporting in CY 2017, pending the availability of data, on Facility-
wide Inpatient Hospital-onset MRSA Bacteremia Outcome Measure (NQF 
#1716); Facility-wide Inpatient Hospital-onset CDI Outcome Measure (NQF 
#1717); and Influenza Vaccination Coverage Among Healthcare Personnel 
(NQF #0431). These comments are summarized and addressed below.
    Comment: Several commenters, including MedPAC, supported public 
reporting of quality measures. MedPAC encouraged ongoing development 
and public reporting of cross-cutting measures for all provider 
settings.
    Response: We will continue to move forward with cross-setting 
measure development and public reporting of these measures to meet the 
mandate of the IMPACT Act.
    Comment: Several commenters stated CMS should risk-adjust IRFs' 
publicly displayed data for Percent of Residents or Patients with 
Pressure Ulcers That Are New or Worsened (Short Stay) (NQF #0678) for 
the number of patients that have pressure ulcers.
    Response: We refer commenters to the FY 2016 IRF PPS final rule (80 
FR 47126 through 47127) that finalized public display of the risk-
adjusted quality measure, the Percent of Residents or Patients with 
Pressure Ulcers That Are New or Worsened (Short Stay) (NQF #0678)
    Comment: One commenter expressed concerns that CMS will utilize 
data from the CARE Tool or IRF-PAI for public reporting of the quality 
measures and that such data is subjective and non-evidence based and 
there is a lack of ability to access the competency of staff completing 
the tool either within or across PAC settings. Therefore, the commenter 
is concerned that the publicly reported data will not represent the 
quality of care provided in IRFs and comparing across IRFs.
    Response: We appreciate the comment expressing concern regarding 
the CARE Tool and IRF-PAI data for public reporting. We would like to 
clarify that quality measures set for public display have already been 
finalized, and the Secretary has a statutory obligation under sections 
1886(j)(7)(E) and 1899B(g) of the Act to establish procedures to make 
the data publicly available.
    Comment: Several commenters expressed concern that the public 
display of quality measure information is based on measures that do not 
exemplify the IRF experience, target very small populations of cases, 
and are not a good indicator of the overall quality of IRFs. Many 
commenters conveyed that the goals of IRFs are to provide medically 
necessary rehabilitation therapies to bring about recovery and improved 
function and the measures fail to assess IRFs success at achieving 
these goals.
    Response: Section 3004 of the Affordable Care Act and the IMPACT 
Act require the Secretary of Health and Human Services to publish the 
data on the quality measures implemented in the IRF QRP through 
rulemaking. The public reporting of the three measures finalized for 
public reporting in the FY 2016 IRF PPS final rule and the four 
measures proposed for public reporting in the FY 2017 IRF PPS proposed 
rule supports the goals of the National Quality Strategy, the CMS 
Quality Strategy, the HHS HAI Action Plan, and the Hospital Acquired 
Condition Reduction Program. It is both a CMS and an HHS priority to 
ensure the delivery of high quality, patient-centered, and safe care 
across all care settings. While the main focus of care in

[[Page 52127]]

an IRF may be centered on restoration of a patient's functional status, 
we believe that this cannot be achieved without attention to the basic 
tenants of patient care, which speak to prevention and patient safety, 
and believe that our quality measures reflect these aspects of quality. 
The IMPACT Act requires us to address the domain of functional status 
and requires the public reporting of this data within 2 years of a 
finalized quality, resource use, and other measure's specified 
application date. We believe that the addition of these measures to the 
public display of IRF quality data will help to address any concerns 
relayed by the commenter.
    Comment: One commenter expressed concerns that the NHSN Facility-
Wide Inpatient Hospital-Onset MRSA Bacteremia Outcome Measure (NQF 
#1716) does not reflect care provided in an IRF, specifically, 
rehabilitation provided to promote functional recovery and achievement 
of goals. The commenter also noted that the incidence of MRSA is rare, 
and generally, if a patient in rehabilitation has MRSA, the infection 
is present upon admission to the rehabilitation facility following 
transfer from the acute care facility. Finally, the commenter noted 
that the inclusion of the NHSN Facility-Wide Inpatient Hospital-Onset 
MRSA Bacteremia Outcome Measure (NQF #1716) within the IRF QRP may 
cause rehabilitation facilities to inappropriately screen for this 
condition, resulting in unnecessary costs to the Medicare program.
    Response: Section 3004 of the Affordable Care Act and the IMPACT 
Act requires the Secretary of Health and Human Services to publish the 
data on the quality measures implemented in the IRF QRP through 
rulemaking. The public reporting of the NHSN Facility-Wide Inpatient 
Hospital-Onset MRSA Bacteremia Outcome Measure (NQF #1716) support the 
goals of the National Quality Strategy, the CMS Quality Strategy, the 
HHS HAI Action Plan, and the Hospital Acquired Condition Reduction 
Program. It is both a CMS and an HHS priority to ensure the delivery of 
high quality, patient-centered, and safe care across all care settings.
    According to the CDC, the steward of this quality measure, cases 
defined by NHSN as Community-onset MRSA Bacteremia are excluded from 
the data that is provided by NHSN to CMS. Only those cases that meet 
the NHSN definition of Incident and Healthcare Facility-onset are 
reported as a part of the CMS IRF QRP. For IRF units within a hospital 
that participate in the CMS IRF QRP will be given a single MRSA 
bacteremia LabID SIR for each type of CMS-certified IRF unit (adult and 
pediatric) mapped within the hospital according to CMS Certification 
Number (CCN). The MRSA Bacteremia LabID SIR is calculated as: Number of 
all incident blood source MRSA LabID events identified >3 days after 
admission to an IRF unit and where the patient had no positive MRSA 
bacteremia LabID events in the prior 14 days in any CMS-certified IRF 
unit of that type divided by the total number of predicted incident 
healthcare facility-onset blood source MRSA LabID events. Clinicians 
should base decisions about diagnostic testing on the needs and 
clinical picture of the patient. Patients with MRSA bacteremia would be 
expected to be symptomatic. Routine collection of blood cultures on 
patients not suspected of being bacteremic would be outside of the 
standards of medical care. For additional information on the 
specifications for this measure, please refer to the CDC reference: 
http://www.cdc.gov/nhsn/pdfs/cms/irfs/linelists_irfunits_indicators.pdf.
    Comment: Several commenters recommended that CMS revise the 
Facility-wide Inpatient Hospital-onset CDI Outcome Measure (NQF #1717) 
because there are multiple C. difficile quality measures for Medicare 
providers across the continuum of care (acute care hospitals, IRFs, 
etc.) and one incident of C. difficile onset may be reported by three 
providers and effectively, and unreasonably, be a ``triple hit'' for 
multiple providers so that it is only reported at the first site of 
discovery.
    Response: The Facility-wide Inpatient Hospital-onset CDI Outcome 
Measure (NQF #1717) was adopted in the IRF QRP and finalized in the FY 
2015 IRF PPS final rule (79 FR 45913 through 45914). The CDC, the 
steward of this measure, noted that the measure specifications for NQF 
#1717, by design, align with the NHSN LabID Event protocol, which was 
developed to require minimal investigation on the part of healthcare 
facilities and to provide a proxy measure of infection. Dates of 
admission and specimen collection are required and can easily be 
collected via electronic methods. These dates enable differentiation of 
healthcare-associated and community-onset events. To require a facility 
to determine if a CDI LabID Event had been identified in another 
facility would call for manual review of medical records and potential 
communication with transferring facilities. The design of LabID event 
reporting via NHSN is by single facility, which means that events are 
reported for the facility where they occur. Analysis is by single 
facility identifier (NHSN organizational ID) and does not cross 
admissions to a different NHSN facility (or a different type reporting 
facility such as nursing home to acute care facility) or transfer from 
facility A to facility B. Cases defined by NHSN as community-onset 
Clostridium difficile are excluded from the data that is provided by 
NHSN to CMS. Only those cases that meet the NHSN definitions of an 
Incident (non-duplicate) Healthcare Facility-onset are reported as a 
part of the CMS IRF QRP. Therefore, cases that are identified during 
the first 3 days of admission to a facility, and which may be related 
to a discharge from another hospital, will not be included in the 
Clostridium difficile LabID Event data reported for the admitting 
facility.
    Comment: The commenter was concerned that the public display of 
these measures will provide misleading interpretations of quality, as 
almost all the measures will be based on different time frames and will 
use different minimum patient thresholds and potentially varying 
patient populations. The commenter recommends that CMS suspend public 
display of IRF QRP data until (1) all IMPACT Act domains are 
implemented and (2) the patient populations for each measure are 
standardized.
    Response: The Secretary has a statutory obligation under section 
1899B(g) and 1886(j)(7)(E) of the Act to make the data available to the 
public. We are transitioning towards aligning the data collection 
periods to follow the calendar year. Once this is achieved, the only 
measure that will not be in alignment is the influenza measure since 
these measures require taking into account the influenza season and 
vaccination season for the data collection period.
    Minimum patient thresholds and populations are dependent on the 
specific measure. Each measure is specifically applied in public 
reporting so that there is enough volume of cases reported to protect 
anonymity and provide meaningful results with representative sample 
size. Public reporting must comply with applicable privacy laws and 
provide minimum sample sizes in order for facilities to compare their 
performance with other IRFs. If the sample size is too small, the 
results will not reflect their facility performance for comparison 
purposes.
    Final Decision: After careful consideration of the public comments, 
we are finalizing our proposal to begin publicly reporting in CY 2017, 
pending the availability of data, on Facility-wide Inpatient Hospital-
onset MRSA Bacteremia Outcome Measure (NQF

[[Page 52128]]

#1716); Facility-wide Inpatient Hospital-onset CDI Outcome Measure (NQF 
#1717); and Influenza Vaccination Coverage Among Healthcare Personnel 
(NQF #0431).
    For the Percent of Residents or Patients Who Were Assessed and 
Appropriately Given the Seasonal Influenza Vaccine (Short Stay) (NQF 
#0680), we proposed to display rates annually based on the influenza 
season to avoid reporting for more than one influenza vaccination 
within a CY. For example, in 2017 we will display rates for the patient 
vaccination measure based on discharges starting on July 1, 2015, to 
June 30, 2016. This is proposed because it includes the entire 
influenza vaccination season (October 1, 2015, to March 31, 2016).
    Calculations for Percent of Residents or Patients Who Were Assessed 
and Appropriately Given the Seasonal Influenza Vaccine (Short Stay) 
(NQF #0680) will be based on patients meeting any one of the following 
criteria: Patients who received the influenza vaccine during the 
influenza season, patients who were offered and declined the influenza 
vaccine, and patients who were ineligible for the influenza vaccine due 
to contraindication(s). The facility's summary observed score will be 
calculated by combining the observed counts of all the criteria. This 
is consistent with the publicly reported patient influenza vaccination 
measure for Nursing Home Compare. Additionally, for the patient 
influenza measure, we will exclude IRFs with fewer than 20 stays in the 
measure denominator. For additional information on the specifications 
for this measure, please refer to the IRF Quality Reporting Measures 
Information Web page at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.
    We invited public comments on our proposal to begin publicly 
reporting the Percent of Residents or Patients Who Were Assessed and 
Appropriately Given the Seasonal Influenza Vaccine (Short Stay) (NQF 
#0680) measure on discharges from July 1st of the previous calendar 
year to June 30th of the current calendar year. We invited comments on 
the public display of the measure Percent of Residents or Patients Who 
Were Assessed and Appropriately Given the Seasonal Influenza Vaccine 
(NQF #0680) in 2017 pending the availability of data.
    We received several comments, which are summarized below.
    Comment: Several commenters expressed concern that the Percent of 
Residents or Patients Who Were Assessed and Appropriately Given the 
Seasonal Influenza Vaccine (Short-Stay) (NQF #0680) is not a true 
indicator of the quality of care provided in IRFs, which focuses on 
functional recovery so that patients are able to function to their 
maximum potential in the least restrictive environment. Commenters 
expressed concern that the influenza vaccination rates do not 
adequately assess whether quality care was provided and that CMS has 
not provided any evidence in the IRF QRP that differences in influenza 
vaccination rates between facilities affect the quality of outcomes or 
the patient experience.
    Response: We appreciate the concerns by several commenters in 
regard to the Percent of Residents or Patients Who Were Assessed and 
Appropriately Given the Seasonal Influenza Vaccine (Short-Stay) (NQF 
#0680). However, this quality measure was adopted in the IRF QRP and 
finalized in the FY 2014 IRF PPS final rule (78 FR 47906 through 
47911).
    Final Decision: After careful consideration of the public comments, 
we are finalizing our proposal to begin publicly reporting the Percent 
of Residents or Patients Who Were Assessed and Appropriately Given the 
Seasonal Influenza Vaccine (Short Stay) (NQF #0680) measure, pending 
the availability of data, on discharges from July 1st of the previous 
calendar year to June 30th of the current calendar year.
    Additionally, we requested public comments on whether to include, 
in the future, public display comparison rates based on CMS regions or 
US census regions for Percent of Residents or Patients with Pressure 
Ulcers That Are New or Worsened (Short Stay) (NQF #0678); All-Cause 
Unplanned Readmission Measure for 30 Days Post-Discharge from IRFs (NQF 
#2502); and Percent of Residents or Patients Who Were Assessed and 
Appropriately Given the Seasonal Influenza Vaccine (Short Stay) (NQF 
#0680) for CY 2017 public display.
    We did not receive any comments about whether to include, in the 
future, public display comparison rates based on CMS regions or US 
census regions for CY 2017 public display.
2. Procedures for the Opportunity To Review and Correct Data and 
Information
    Section 1899B(g) of the Act requires the Secretary to establish 
procedures for public reporting of IRFs' performance, including the 
performance of individual IRFs, on quality measures specified under 
section 1899B(c)(1) of the Act and resource use and other measures 
specified under section 1899B(d)(1) of the Act (collectively, IMPACT 
Act measures) beginning not later than 2 years after the applicable 
specified application date under section 1899B(a)(2)(E) of the Act. 
Under section 1899B(g)(2) of the Act, the procedures must ensure, 
including through a process consistent with the process applied under 
section 1886(b)(3)(B)(viii)(VII) of the Act, which refers to public 
display and review requirements in the Hospital IQR Program, that each 
IRF has the opportunity to review and submit corrections to its data 
and information that are to be made public prior to the information 
being made public.
    In the FY 2016 IRF PPS final rule (80 FR 47126 through 47128), and 
as illustrated in Table 10 in section VIII.I.a of this final rule, we 
finalized that once the provider has an opportunity to review and 
correct quarterly data related to measures submitted via the QIES-ASAP 
system or CDC NHSN, we will consider the provider to have been given 
the opportunity to review and correct this data. We wish to clarify 
that although the correction of data (including claims) can occur after 
the submission deadline, if such corrections are made after a 
particular quarter's submission and correction deadline, such 
corrections will not be captured in the file that contains data for 
calculation of measures for public reporting purposes. To have publicly 
displayed performance data that is based on accurate underlying data, 
it will be necessary for IRFs to review and correct this data before 
the quarterly submission and correction deadline.
    We restated and proposed additional details surrounding procedures 
that will allow individual IRFs to review and correct their data and 
information on measures that are to be made public before those measure 
data are made public.
    For assessment-based measures, we proposed a process by which we 
will provide each IRF with a confidential feedback report that will 
allow the IRF to review its performance on such measures and, during a 
review and correction period, to review and correct the data the IRF 
submitted to CMS via the CMS QIES-ASAP system for each such measure. In 
addition, during the review and correction period, the IRF will be able 
to request correction of any errors in the assessment-based measure 
rate calculations.
    We proposed that these confidential feedback reports will be 
available to each IRF using the CASPER system. We

[[Page 52129]]

refer to these reports as the IRF Quality Measure (QM) Reports. We 
proposed to provide monthly updates to the data contained in these 
reports as data become available. We proposed to provide the reports so 
that providers will be able to view their data and information at both 
the facility and patient level for its quality measures. The CASPER 
facility level QM Reports may contain information such as the 
numerator, denominator, facility rate, and national rate. The CASPER 
patient-level QM Reports may contain individual patient information 
which will provide information related to which patients were included 
in the quality measures to identify any potential errors for those 
measures in which we receive patient-level data. Currently, we do not 
receive patient-level data on the CDC measure data received via the 
NHSN system. In addition, we will make other reports available in the 
CASPER system, such as IRF-PAI assessment data submission reports and 
provider validation reports, which will disclose the IRFs data 
submission status providing details on all items submitted for a 
selected assessment and the status of records submitted. We refer 
providers to the CDC/NHSN system Web site for information on obtaining 
reports specific to NHSN submitted data at http://www.cdc.gov/nhsn/inpatient-rehab/index.html. Additional information regarding the 
content and availability of these confidential feedback reports will be 
provided on an ongoing basis on our Web site(s) at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/index.html.
    As previously finalized in the FY 2016 IRF PPS final rule and 
illustrated in Table 18 in section VIII.I.c of this final rule, IRFs 
will have approximately 4.5 months after the reporting quarter to 
correct any errors of their assessment-based data (that appear on the 
CASPER generated QM reports) and NHSN data used to calculate the 
measures. During the time of data submission for a given quarterly 
reporting period and up until the quarterly submission deadline, IRFs 
could review and perform corrections to errors in the assessment data 
used to calculate the measures and could request correction of measure 
calculations. However, as already established, once the quarterly 
submission deadline occurs, the data is ``frozen'' and calculated for 
public reporting and providers can no longer submit any corrections. We 
will encourage IRFs to submit timely assessment data during a given 
quarterly reporting period and review their data and information early 
during the review and correction period so that they can identify 
errors and resubmit data before the data submission deadline.
    As noted above, the assessment data will be populated into the 
confidential feedback reports, and we intend to update the reports 
monthly with all data that have been submitted and are available. We 
believe that the data collection/submission quarterly reporting periods 
plus 4.5 months to review correct and review the data is sufficient 
time for IRFs to submit, review and, where necessary, correct their 
data and information. These time frames and deadlines for review and 
correction of such measures and data satisfy the statutory requirement 
that IRFs be provided the opportunity to review and correct their data 
and information and are consistent with the informal process hospitals 
follow in the Hospital IQR Program.
    In FY 2016 IRF PPS final rule (80 FR 47126 through 47128), we 
finalized the data submission/correction and review period. Also, we 
afford IRFs a 30-day preview period prior to public display during 
which IRFs may preview the performance information on their measures 
that will be made public. We want to clarify that we will provide the 
preview report using the CASPER system, with which IRFs are familiar. 
The CASPER preview reports inform providers of their performance on 
each measure which will be publicly reported. Please note that the 
CASPER preview reports for the reporting quarter will be available 
after the 4.5 month correction period and the applicable data 
submission/correction deadline have passed and are refreshed on a 
quarterly basis for those measures publicly reported quarterly, and 
annually for those measure publicly reported annually. We proposed to 
give IRFs 30 days to review the preview report beginning from the date 
on which they can access the report. As already finalized, corrections 
to the underlying data will not be permitted during this time; however, 
IRFs may ask for a correction to their measure calculations during the 
30-day preview period, should they believe the calculation is 
inaccurate. We proposed that if we agree that the measure, as it is 
displayed in the preview report, contains a calculation error, we could 
suppress the data on the public reporting Web site, recalculate the 
measure and publish it at the time of the next scheduled public display 
date. This process will be consistent with informal processes used in 
the Hospital IQR Program. If finalized, we intend to utilize a 
subregulatory mechanism, such as our IRF QRP Web site, to provide more 
information about the preview reports, such as when they will be made 
available and explain the process for how and when providers may ask 
for a correction to their measure calculations. We invited public 
comment on these proposals to provide preview reports using the CASPER 
system, giving IRFs 30 days review the preview report and ask for a 
correction, and to use a subregulatory mechanism to explain the process 
for how and when providers may ask for a correction.
    In addition to assessment-based measures and CDC measure data 
received via the NHSN system, we have also proposed claims-based 
measures for the IRF QRP. The claims-based measures include those 
proposed to meet the requirements of the IMPACT Act as well as the All-
Cause Unplanned Readmission Measure for 30 Days Post-Discharge from 
IRFs (NQF #2502) which was finalized for public display in the FY 2016 
IRF PPS final rule (80 FR 47126 through 47127). As noted in section 
VII.N.2. of this final rule, section 1899B(g)(2) of the Act requires 
prepublication provider review and correction procedures that are 
consistent with those followed in the Hospital IQR Program. Under the 
Hospital IQR Program's informal procedures, for claims-based measures, 
we provide hospitals 30 days to preview their claims-based measures and 
data in a preview report containing aggregate hospital-level data. We 
proposed to adopt a similar process for the IRF QRP.
    Prior to the public display of our claims-based measures, in 
alignment with the Hospital IQR, HAC and Hospital VBP Programs, we 
proposed to make available through the CASPER system, a confidential 
preview report that will contain information pertaining to claims-based 
measure rate calculations, for example, facility and national rates. 
The data and information will be for feedback purposes only and could 
not be corrected. This information will be accompanied by additional 
confidential information based on the most recent administrative data 
available at the time we extract the claims data for purposes of 
calculating the measures. Because the claims-based measures are 
recalculated on an annual basis, these confidential CASPER QM reports 
for claims-based measures will be refreshed annually. As previously 
finalized in the FY 2016 IRF PPS final rule (80 FR 47126 through 
47128), IRFs will have 30 days from the date the preview report is made 
available in which to review this information. The

[[Page 52130]]

30-day preview period is the only time when IRFs will be able to see 
claims-based measures before they are publicly displayed. IRFs will not 
be able to make corrections to underlying claims data during this 
preview period, nor will they be able to add new claims to the data 
extract. However, IRFs may request that we correct our measure 
calculation if the IRF believes it is incorrect during the 30 day 
preview period. We proposed that if we agree that the measure, as it is 
displayed in the preview report, contains a calculation error, we could 
suppress the data on the public reporting Web site, recalculate the 
measure, and publish it at the time of the next scheduled public 
display date. This process will be consistent with informal policies 
followed in the Hospital IQR Program. If finalized, we intend to 
utilize a subregulatory mechanism, such as our IRF QRP Web site, to 
explain the process for how and when providers may contest their 
measure calculations
    The proposed claims-based measures--The MSPB-PAC IRF QRP measure; 
Discharge to Community--PAC, Potentially Preventable 30-Day Post-
Discharge Readmission Measure for IRF QRP, and Potentially Preventable 
Within Stay Readmission Measure for IRFs--use Medicare administrative 
data from hospitalizations for Medicare FFS beneficiaries. Public 
reporting of data will be based on 2 consecutive calendar years of 
data, which is consistent with the specifications of the proposed 
measures. We proposed to create data extracts using claims data for the 
proposed claims-based measures-The MSPB-PAC IRF QRP measure; Discharge 
to Community--PAC, Potentially Preventable 30-Day Post-Discharge 
Readmission Measure for IRF QRP, and Potentially Preventable Within 
Stay Readmission Measure for IRFs--at least 90 days after the last 
discharge date in the applicable period, which we will use for the 
calculations. For example, if the last discharge date in the applicable 
period for a measure is December 31, 2017, for data collection January 
1, 2016, through December 31, 2017, we will create the data extract on 
approximately March 31, 2018, at the earliest, and use that data to 
calculate the claims-based measures for that applicable period. Since 
IRFs will not be able to submit corrections to the underlying claims 
snapshot nor add claims (for measures that use IRF claims) to this data 
set at the conclusion of the at least the 90-day period following the 
last date of discharge used in the applicable period, at that time we 
will consider IRF claims data to be complete for purposes of 
calculating the claims-based measures.
    We proposed that beginning with data that will be publicly 
displayed in 2018, claims-based measures will be calculated using 
claims data at least 90 days after the last discharge date in the 
applicable period, at which time we will create a data extract or 
snapshot of the available claims data to use for the measures 
calculation. This timeframe allows us to balance the need to provide 
timely program information to IRFs with the need to calculate the 
claims-based measures using as complete a data set as possible. As 
noted, under this procedure, during the 30-day preview period, IRFs 
will not be able to submit corrections to the underlying claims data or 
to add new claims to the data extract. This is for two reasons: First, 
for certain measures, the claims data used to calculate the measure is 
derived not from the IRF's claims, but from the claims of another 
provider. For example, the proposed measure Potentially Preventable 30-
Day Post-Discharge Readmission Measure for IRF QRP uses claims data 
submitted by the hospital to which the patient was readmitted. The 
claims are not those of the IRF and, therefore, the IRF could not make 
corrections to them. Second, even where the claims used to calculate 
the measures are those of the IRF, it will not be not possible to 
correct the data after it is extracted for the measures calculation. 
This is because it is necessary to take a static ``snapshot'' of the 
claims in order to perform the necessary measure calculations.
    We seek to have as complete a data set as possible. We recognize 
that the at least 90-day ``run-out'' period, when we will take the data 
extract to calculate the claims-based measures, is less than the 
Medicare program's current timely claims filing policy under which 
providers have up to 1 year from the date of discharge to submit 
claims. We considered a number of factors in determining that the 
proposed at least 90-day run-out period is appropriate to calculate the 
claims-based measures. After the data extract is created, it takes 
several months to incorporate other data needed for the calculations 
(particularly in the case of risk-adjusted or episode-based measures). 
We then need to generate and check the calculations. Because several 
months lead time is necessary after acquiring the data to generate the 
claims-based calculations, if we were to delay our data extraction 
point to 12 months after the last date of the last discharge in the 
applicable period, we will not be able to deliver the calculations to 
IRFs sooner than 18 to 24 months after the last discharge. We believe 
this will create an unacceptably long delay both for IRFs and for us to 
deliver timely calculations to IRFs for quality improvement.
    We invited public comment on these proposals. We received a number 
of comments, which are summarized below.
    Comment: Several commenters expressed concern that for claims-based 
measures, CMS proposes to calculate claims-based measures on an annual 
basis and the CASPER QM provider reports for these measures would only 
be available annually. Commenters also expressed concern that CMS does 
not propose to allow providers to correct their metrics on claims-based 
measures; reports would be for feedback purposes only. Several 
commenters requested CMS provide claims-based feedback reports at least 
twice a year as well as providing patient-level data.
    Response: We appreciate the commenters' concerns and suggestions to 
provide feedback reports at least twice a year as well as providing 
patient-level data for claims-based measures. As discussed previously, 
the All-Cause Unplanned Readmission Measure for 30 Days Post-Discharge 
from IRFs (NQF #2502) is based on 2 consecutive years of data in order 
to ensure a sufficient sample size to reliably assess IRFs' 
performance. The decision to update claims-based measures on an annual 
basis was to ensure that the amount of data received during the 
reporting period was sufficient to generate reliable measure rates. 
However, we will explore the feasibility of providing IRFs with 
information more frequently. We believe that we are limited in our 
ability to provide patient level information that stems from claims 
submitted by providers other than IRF, but we will explore the 
feasibility of providing patient-level data. With regard to the concern 
for the correction of claims-based measures and the IRF's ability to 
correct their metrics, and that the reports we provide will be for 
feedback purposes only, we interpret the commenter to be referring to 
both the preview reports and the QM reports we discussed. The 
limitation on claims-based data and corrections is that the measures 
are calculated after the claims file has been obtained. If the IRF 
determines there are errors in the claims data they submitted, then 
they can correct such data. The corrections to the claims data will be 
reflected in the subsequent measure calculation. We urge IRFs to submit 
timely and accurate claims-based data.
    Comment: One commenter expressed concern that 30 days is inadequate 
to

[[Page 52131]]

preview and assess the QM reports and recommends 60 days and that CMS 
should establish a process to discuss and reconcile issues or 
incongruities between CMS's and the provider's data.
    Response: We interpret the commenter to be referring to the preview 
reports we will provide prior to public reporting and appreciate their 
concern for the 30-day timeframe for which IRFs have to review and 
assess the preview reports. The 30-day preview period, previously 
finalized, is consistent with other public reporting programmatic 
procedures. As described, this timeframe is for providers to evaluate 
their data that will be published and alert us to any discrepancies 
they may find. In addition, as described, IRFs will have an opportunity 
to review their information and data using various reports, which are 
provided through the CASPER system and can be used to inform data 
correction needs on behalf of the IRF. For example, as discussed, we 
intend to provide IRF QM Reports that will provide monthly reporting on 
both facility-level and patient-level CMS assessment-based data. 
Further, we refer the commenter to the discussion we provide in which 
IRFs will have 4.5 months to review and correct data prior to the 
quarterly freeze dates and posting of the final preview reports in 
QIES.
    Final Decision: After careful consideration of the public comments, 
we are finalizing our proposals related to procedures for the 
opportunity to review and correct data and information. We are 
finalizing as proposed, our policies and procedures pertaining to 
public reporting and the opportunity to review and correct data and 
information. We are also finalizing as proposed, our policies and 
procedures for claims-based measures for public reporting.

O. Mechanism for Providing Feedback Reports to IRFs

    Section 1899B(f) of the Act requires the Secretary to provide 
confidential feedback reports to post-acute care providers on their 
performance to the measures specified under section 1899B(c)(1) and 
(d)(1) of the Act, beginning 1 year after the specified application 
date that applies to such measures and PAC providers. As discussed 
earlier, the reports we proposed to provide for use by IRFs to review 
their data and information will be confidential feedback reports that 
will enable IRFs to review their performance on the measures required 
under the IRF QRP. We proposed that these confidential feedback reports 
will be available to each IRF using the CASPER system. Data contained 
within these CASPER reports will be updated as previously described, on 
a monthly basis as the data become available except for our claims-
based measures, which are only updated on an annual basis.
    We intend to provide detailed procedures to IRFs on how to obtain 
their confidential feedback CASPER reports on the IRF QRP Web site at 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/index.html. We proposed to use the 
CMS QIES-ASAP system to provide quality measure reports in a manner 
consistent with how providers obtain various reports to date. The QIES-
ASAP system is a confidential and secure system with access granted to 
providers, or their designees.
    We sought public comment on this proposal to satisfy the 
requirement to provide confidential feedback reports to IRFs. We 
received several comments, which are summarized are below.
    Comment: Several commenters recommended CMS provide more frequent 
feedback, such as quarterly, for assessment-based measures and every 
six months reporting for claims-based measures.
    Response: We appreciate commenters' suggestion for CMS to provide 
more frequent feedback, such as quarterly, for assessment-based 
measures and every 6 months for claims-based measures.
    As previously discussed, IRFs will have an opportunity to review 
and utilize their data using confidential reports provided through the 
CASPER system. The decision to update claims-based measures on an 
annual basis was basis was explained previously in response to the 
comment concerning providing feedback reports at least twice a year.
    Comment: One commenter recommended CMS conduct a ``dry run'' in 
which providers receive confidential preview reports prior to publicly 
reporting measures so that providers can become familiar with the 
methodology, understand the measure results, know how well they are 
performing, and have an opportunity to give CMS feedback on potential 
technical issues with the measures.
    Response: We intend to offer providers information related to their 
measures so that they become familiar with the measure's methodology 
and can utilize their confidential preview reports which they will 
receive prior to the public reporting of new IRF QRP measures. IRFs 
will also receive other confidential reports such as the IRF facility 
and patient level QM Reports as well as an additional confidential 
facility-level report to incorporate the quarterly freeze dates, for 
example, the Review and Correct Report. We believe that these various 
reports will provide an indication on how well the IRF is performing as 
well as opportunities to provide CMS feedback on technical issues with 
the measures. Therefore, no additional dry run period is warranted.
    Final Decision: After careful consideration of the public comments, 
we are finalizing our proposal to provide confidential feedback reports 
to IRFs, as proposed.

P. Method for Applying the Reduction to the FY 2017 IRF Increase Factor 
for IRFs That Fail To Meet the Quality Reporting Requirements

    As previously noted, section 1886(j)(7)(A)(i) of the Act requires 
the application of a 2-percentage point reduction of the applicable 
market basket increase factor for IRFs that fail to comply with the 
quality data submission requirements. In compliance with section 
1886(j)(7)(A)(i) of the Act, we proposed to apply a 2-percentage point 
reduction to the applicable FY 2017 market basket increase factor in 
calculating a proposed adjusted FY 2017 standard payment conversion 
factor to apply to payments for only those IRFs that failed to comply 
with the data submission requirements. As previously noted, application 
of the 2-percentage point reduction may result in an update that is 
less than 0.0 for a fiscal year and in payment rates for a fiscal year 
being less than such payment rates for the preceding fiscal year. Also, 
reporting-based reductions to the market basket increase factor will 
not be cumulative; they will only apply for the FY involved.
    We invited public comment on the proposed method for applying the 
reduction to the FY 2017 IRF increase factor for IRFs that fail to meet 
the quality reporting requirements. We did not receive any comments on 
this proposal.
    Final Decision: We are finalizing our proposed method for applying 
the reduction to the FY 2017 IRF increase factor for IRFs that fail to 
meet the quality reporting requirements.
    Table 21 shows the calculation of the adjusted FY 2017 standard 
payment conversion factor that will be used to compute IRF PPS payment 
rates for any IRF that failed to meet the quality reporting 
requirements for the applicable reporting period(s).

[[Page 52132]]



    Table 21--Calculations To Determine the Adjusted FY 2017 Standard
   Payment Conversion Factor for IRFs That Failed To Meet the Quality
                          Reporting Requirement
------------------------------------------------------------------------
       Explanation for adjustment                  Calculations
------------------------------------------------------------------------
Standard Payment Conversion Factor for   $15,478.
 FY 2016.
Market Basket Increase Factor for FY     x 0.9965.
 2017 (2.7 percent), reduced by 0.3
 percentage point for the productivity
 adjustment as required by section
 1886(j)(3)(C)(ii)(I) of the Act,
 reduced by 0.75 percentage point in
 accordance with sections 1886(j)(3)(C)
 and (D) of the Act and further reduced
 by 2 percentage points for IRFs that
 failed to meet the quality reporting
 requirement.
Budget Neutrality Factor for the Wage    x 0.9992.
 Index and Labor-Related Share.
Budget Neutrality Factor for the         x 0.9992.
 Revisions to the CMG Relative Weights.
Adjusted FY 2017 Standard Payment        = 15,399.
 Conversion Factor.
------------------------------------------------------------------------

IX. Miscellaneous Comments

    Comment: Several commenters were supportive of our continued use of 
the FY 2014 facility-level adjustments and recommended that CMS 
continue monitoring the adjustments. Other commenters suggested that 
CMS be more transparent about the methodology and the factors it 
utilizes for calculating facility adjustment payments to IRFs. Several 
commenters suggested that CMS should establish a three-year minimum 
interval for any change in the IRF provider-level adjustment factors 
and recommended that if any factor varies by a minimum amount, the 
factor should be adjusted. Some commenters also recommended that CMS 
monitor the facility-level adjustment factors annually and adjust them 
if there is a change in excess of 5 to 10 percent.
    Response: As we did not propose any changes to the facility-level 
adjustments, these comments are outside the scope of the proposed rule. 
In the FY 2017 IRF PPS proposed rule (81 FR 24177), we noted that, in 
the FY 2015 IRF PPS final rule (79 FR 45872 at 45882), we froze the 
facility-level adjustments at FY 2014 levels for FY 2015 and all 
subsequent years (unless and until we propose to update them again 
through future notice-and-comment rulemaking). We will continue to 
monitor the facility-level adjustments and update them as necessary 
through rulemaking to ensure the continued accuracy of IRF PPS 
payments.
    Comment: Several commenters expressed concerns about the impact of 
the changes to the 60 percent rule compliance methodology that we 
finalized in the FY 2014 and FY 2015 IRF PPS final rules on beneficiary 
access to IRF services, and suggested that we revisit them. These 
commenters further stated that the translation of International 
Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-
CM) codes to International Classification of Diseases, 10th Revision, 
Clinical Modification (ICD-10-CM) codes using the General Equivalence 
Mapping (GEMS) tool may have unintentionally caused some diagnoses to 
now be excluded from counting under the presumptive compliance 
methodology. In particular, the commenters suggested that we review the 
codes excluded under the IGCs for traumatic brain injury, hip fracture, 
and major multiple trauma, and add these cases back in as presumptively 
compliant cases under the 60 percent rule. Some commenters suggested 
that we issue clarifications to MACs and CMS Regional Offices that 
these codes are considered presumptively compliant. Further, one 
commenter suggested that we revisit our decision on no longer 
considering presumptively compliant diagnoses codes for rheumatoid 
myopathy and polyneuropathy, unilateral amputations, and amputation 
status/aftercare.
    Response: As we did not propose any changes to the methodology for 
determining IRFs' compliance with the 60 percent rule in the FY 2017 
IRF PPS proposed rule, these comments are outside the scope of the 
proposed rule. We appreciate the commenter's suggestions, and will 
continue to monitor and assess the implications of the changes to the 
presumptive methodology that we finalized in the FY 2014 and FY 2015 
IRF PPS final rules to determine if any further refinements to the 
methodology are needed. We intend to take a comprehensive look at the 
ICD-10-CM codes to identify any diagnosis codes that may need to be 
added to the presumptive compliance methodology, as well as any codes 
that may need to be removed.
    Comment: Several commenters suggested that, as height and weight 
are now required information on the IRF-PAI (beginning October 1, 
2014), CMS should now use this information to identify patients with 
unilateral joint replacements and body mass indexes (BMI) greater than 
50 for presumptive compliance with the 60 percent rule requirements.
    Response: As we did not propose any changes to the methodology for 
determining IRFs' compliance with the 60 percent rule, these comments 
are outside the scope of the proposed rule. However, we will take these 
suggestions into consideration.
    Comment: One commenter stated that the translation to ICD-10-CM has 
created a problem with the grouping of rehabilitation diagnosis-related 
groups (DRGs) in rehabilitation units due to the loss of the ``V code'' 
under ICD-10-CM. The commenter expressed concern that rehabilitation 
patients may not be reimbursed appropriately and in many instances 
would be paid under the Hospital IPPS MS-DRGs.
    Response: As payment under the IRF PPS is not based on diagnosis-
related groups, this comment is outside the scope of the proposed rule. 
This final rule only applies to rehabilitation units that are paid 
under the IRF PPS, not to other types of rehabilitation units which may 
be present in an acute care hospital but that are paid under other 
Medicare payment systems.
    Comment: One commenter stated that CMS should review its policy 
regarding the use of ``D-subsequent encounter'' as an eligible 7th 
character for traumatic injury diagnosis codes as advised by the AHA 
Coding Clinic for ICD-10-CM and ICD-10-PCS Editorial Advisory Board 
(reference material for this can be found at http://www.ahacentraloffice.org/codes/Resources.shtml). The commenter stated 
that ``subsequent encounter'' is an appropriate option for 
rehabilitation services and that CMS should allow the ``D'' as an 
eligible 7th character for traumatic injury diagnosis codes.
    Response: IRFs are permitted to use ``D'' as an eligible 7th 
character for traumatic injury diagnosis codes on both the IRF claim 
and the IRF-PAI. However, for the reasons indicated in the FY 2015 IRF 
PPS final rule (79 FR 45872, 45907), effective with discharges 
occurring on or after October 1, 2015, ICD-10-CM codes with the seventh 
character extension of ``D'' are not included in the ICD-10-CM versions 
of the ``List of Comorbidities,'' ``ICD-10-CM Codes That Meet 
Presumptive Compliance Criteria,'' or ``Impairment

[[Page 52133]]

Group Codes That Meet Presumptive Compliance Criteria.'' Whereas the 
AHA Coding Clinic for ICD-10-CM and ICD-10 PCS (Vol. 2, No. 1) 
guidelines instruct providers to use the 7th character ``D'' for 
traumatic injury diagnosis codes used in an IRF setting, the guidelines 
specifically say that the AHA Coding Clinic guidelines only apply to 
the IRF claim and that providers should refer to the instructions 
provided in the IRF-PAI training manual, which is available for 
download from the IRF PPS Web site at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/IRFPAI.html, for 
instructions on how to code the IRF-PAI. Thus, ICD-10-CM diagnosis 
codes with the 7th character ``D,'' if used for traumatic injury 
diagnosis codes on the IRF-PAI, will not result in a tier payment or 
result in a case being presumptively compliant with the IRF 60 percent 
rule for the reasons stated in the FY 2015 IRF PPS final rule (79 FR 
45872, 45907).
    Comment: Several commenters stated that the FY 2017 update to the 
standard payment conversion factor does not include additional payment 
to IRFs for the time and resources needed to complete assessments for 
quality reporting. These commenters further stated that the additional 
quality reporting elements in the FY 2016 IRF PPS final rule will add 
time spent collecting information while decreasing the time available 
for direct patient care. Several commenters stated that the proposed 
increase does not cover the costs of medical inflation, or of the 
technical implementation, training, and data collection related to the 
quality reporting measures even though costs will be significant. 
Several commenters stated that the ``minimal increase'' does not 
adequately take into account the estimated costs of implementing the 
quality reporting measures and request that CMS add the estimated costs 
of these measures to the FY 2017 payment update.
    Response: We refer readers to the FY 2016 IRF PPS final rule (80 FR 
47129 through 47137) for details regarding the Collection of 
Information Requirements and Regulatory Impact Analysis for the 
finalized measures. We would also like to clarify that quality program 
reporting requirements are not included in the standard payment 
conversion factor. However, in accordance with section 1886(j)(7)(A) of 
the Act, the applicable annual increase factor for any IRF that does 
not submit the required data to CMS must be reduced by two percentage 
points.
    Comment: One commenter reiterated MedPAC's March 2016 
recommendation that we should analyze patterns of coding across IRFs 
and reassess the inter-rater reliability of the IRF-PAI.
    Response: This comment involves data monitoring activities that are 
not discussed in the proposed rule, and are therefore outside the scope 
of the rule. However, we will share this recommendation with the 
appropriate components within CMS for their consideration of these 
issues.

X. Provisions of the Final Regulations

    In this final rule, we are adopting the provisions set forth in the 
FY 2017 IRF PPS proposed rule (81 FR 24178). Specifically:
     We will update the FY 2017 IRF PPS relative weights and 
average length of stay values using the most current and complete 
Medicare claims and cost report data in a budget-neutral manner, as 
discussed in section IV of this final rule.
     As established in the FY 2015 IRF PPS final rule (79 FR 
45872 at 45882), the facility-level adjustments will remain frozen at 
FY 2014 levels for FY 2015 and all subsequent years (unless and until 
we propose to update them again through future notice-and-comment 
rulemaking), as discussed in section V of this final rule.
     We will update the FY 2017 IRF PPS payment rates by the 
market basket increase factor, based upon the most current data 
available, with a 0.75 percentage point reduction as required by 
sections 1886(j)(3)(C)(ii)(II) and 1886(j)(3)(D)(v) of the Act and the 
productivity adjustment required by section 1886(j)(3)(C)(ii)(I) of the 
Act, as described in section VI of this final rule.
     We will update the FY 2017 IRF PPS payment rates by the FY 
2017 wage index and the labor-related share in a budget-neutral manner 
and continue the phase-out of the rural adjustment as discussed in 
section VI of this final rule.
     We will calculate the final IRF standard payment 
conversion factor for FY 2017, as discussed in section VI of this final 
rule.
     We will update the outlier threshold amount for FY 2017, 
as discussed in section VII of this final rule.
     We will update the cost-to-charge ratio (CCR) ceiling and 
urban/rural average CCRs for FY 2017, as discussed in section VII of 
this final rule.
     We will adopt revisions and updates to quality measures 
and reporting requirements under the quality reporting program for IRFs 
in accordance with section 1886(j)(7) of the Act, as discussed in 
section VIII of this final rule.

XI. Collection of Information Requirements

A. Statutory Requirement for Solicitation of Comments

    Under the Paperwork Reduction Act of 1995 (PRA), we are required to 
provide 60-day notice in the Federal Register and solicit public 
comment before a collection of information requirement is submitted to 
the OMB for review and approval. 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.
    This final rule makes reference to associated information 
collections that are not discussed in the regulation text contained in 
this document.

B. Collection of Information Requirements for Updates Related to the 
IRF QRP

    Failure to submit data required under section 1886(j)(7)(C) and (F) 
of the Act will result in the reduction of the annual update to the 
standard federal rate for discharges occurring during such fiscal year 
by 2 percentage points for any IRF that does not comply with the 
requirements established by the Secretary. At the time that this 
analysis was prepared, 91, or approximately 8 percent, of the 1166 
active Medicare-certified IRFs did not receive the full annual 
percentage increase for the FY 2016 annual payment update 
determination. Information is not available to determine the precise 
number of IRFs that will not meet the requirements to receive the full 
annual percentage increase for the FY 2017 payment determination.
    We believe that the burden associated with the IRF QRP is the time 
and effort associated with data collection and reporting. As of 
February 1, 2016 there are approximately 1131 IRFs currently reporting 
quality data to CMS. In this final rule, we are adopting 5 measures. 
For the FY 2018 payment determinations and subsequent years, we 
proposed four new measures: (1)

[[Page 52134]]

MSPB-PAC IRF QRP; (2) Discharge to Community-PAC IRF QRP, and (3) 
Potentially Preventable 30-Day Post-Discharge Readmission Measure for 
IRF QRP; (4) Potentially Preventable 30-Day Within Stay Readmission 
Measure for IRF QRP. These four measures are Medicare claims-based 
measures. Because claims-based measures can be calculated based on data 
that are already reported to the Medicare program for payment purposes, 
we believe there will be no additional impact.
    For the FY 2020 payment determination and subsequent years, we 
proposed one measure: Drug Regimen Review Conducted with Follow-Up for 
Identified Issues-PAC IRF QRP. Additionally, we proposed that data for 
this new measure will be collected and reported using the IRF-PAI 
(version effective October 1, 2018).
    Our burden calculations take into account all ``new'' items 
required on the IRF-PAI (version effective October 1, 2018) to support 
data collection and reporting for this measure. The addition of the new 
items required to collect the newly proposed measure is for the purpose 
of achieving standardization of data elements.
    We estimate the additional elements for the newly proposed Drug 
Regimen Review Conducted with Follow-Up for Identified Issues-PAC IRF 
QRP measure will take 6 minutes of nursing/clinical staff time to 
report data on admission and 4 minutes of nursing/clinical staff time 
to report data on discharge, for a total of 10 minutes. We estimate 
that the additional IRF-PAI items we proposed will be completed by 
Registered Nurses (RN) for approximately 75 percent of the time 
required, and Pharmacists for approximately 25 percent of the time 
required. Individual providers determine the staffing resources 
necessary. In accordance with OMB control number 0938-0842, we estimate 
398,254 discharges from all IRFs annually, with an additional burden of 
10 minutes. This will equate to 66,375.67 total hours or 58.69 hours 
per IRF. We believe this work will be completed by RNs (75 percent) and 
Pharmacists (25 percent). We obtained mean hourly wages for these staff 
from the U.S. Bureau of Labor Statistics' May 2014 National 
Occupational Employment and Wage Estimates (http://www.bls.gov/oes/current/oes_nat.htm), and to account for overhead and fringe benefits, 
we have doubled the mean hourly wage. Per the U.S. Bureau of Labor and 
Statistics, the mean hourly wage for a RN is $33.55. However, to 
account for overhead and fringe benefits, we have doubled the mean 
hourly wage, making it $67.10 for an RN. Per the U.S. Bureau of Labor 
and Statistics, the mean hourly wage for a pharmacist is $56.98. 
However, to account for overhead and fringe benefits, we have doubled 
the mean hourly wage, making it $113.96 for a pharmacist. Given these 
wages and time estimates, the total cost related to the newly proposed 
measures is estimated at $4,625.46 per IRF annually, or $5,231,398.17 
for all IRFs annually.
    For the quality reporting during extraordinary circumstances, in 
section VIII.L of this final rule, we add a previously finalized 
process that IRFs may request an exception or extension from the FY 
2019 payment determination and that of subsequent payment 
determinations. The request must be submitted by email within 90 days 
from the date that the extraordinary circumstances occurred.
    While the preparation and submission of the request is an 
information collection, unlike the aforementioned temporary exemption 
of the data collection requirements for the new drug regimen review 
measure, the request is not expected to be submitted to OMB for formal 
review and approval since we estimate less than two requests (total) 
per year. Since we estimate fewer than 10 respondents annually, the 
information collection requirement and associated burden is not subject 
as stated in 5 CFR 1320.3(c) of the implementing regulations of the 
Paperwork Reduction Act of 1995.
    As discussed in section VIII.M of this final rule, we add a 
previously finalized process that will enable IRFs to request 
reconsiderations of our initial non-compliance decision in the event 
that it believes that it was incorrectly identified as being subject to 
the 2-percentage point reduction to its annual increase factor due to 
non-compliance with the IRF QRP reporting requirements. While there is 
burden associated with filing a reconsideration request, 5 CFR 1320.4 
of OMB's implementing regulations for PRA excludes activities during 
the conduct of administrative actions such as reconsiderations.
    We received comments about the collection of information 
requirements associated with measures being proposed for the IRF QRP, 
which are summarized and addressed below.
    Comment: One commenter appreciated that the claims-based measures 
being proposed do not place additional burden on the facilities and 
their staff. Other commenters had concerns about the claims-based 
measures, noting that while they had no data collection burden, they 
were associated with time and resources needed to compile and verify 
data for submission. One commenter expressed concerns that the burden 
estimate doubles the resources required to collect data but doesn't 
take into consideration limited resources smaller organizations have.
    Response: We recognize the commenter's concern pertaining to burden 
due to the requirements being added to the IRF Quality Reporting 
Program. We are very sensitive to the issue of burden associated with 
data collection and have proposed only the minimal number of additional 
items (3) needed to calculate the proposed quality measure. Though we 
recognize that new IRF-PAI items will require additional activities and 
efforts by providers, we would like to clarify that burden estimates 
are intended to reflect only the time needed to complete IRF-PAI items, 
independent of clinical time spent assessing the patient. Similarly, 
burden estimates are not indented to reflect costs of training and 
operational processes; these are considered part of the operating costs 
for an IRF. Time estimates for coding required items being added for 
the Drug Regimen Review measure were based on a Drug Regimen Review 
pilot testing conducted in November and December 2015. It should be 
noted that with each assessment release, we provide free software to 
our providers that allows for the completion and submission of any 
required assessment data. Free downloads of the Inpatient 
Rehabilitation Validation and Entry (IRVEN) software product are 
available on the CMS Web site at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/Software.html.
    We also wish to note that, as pointed out by one commenter, four of 
the five measures proposed are claims-based and have no additional data 
collection burden to providers. Since the data source for these 
measures is claims data, and is not collected by means of an assessment 
instrument, the measure does not increase data collection burden on the 
provider as this data is currently collected by providers. We also note 
that providers will be given a chance to review their claims-based 
measure data via feedback provided in the CASPER system. Despite the 
lack of data collection burden, we appreciate the comments that more 
education will be required for the public and providers to understand 
the claims-based measures and the feedback mechanism. We will be 
providing additional training for the reports that are, and will be, 
available for providers for reviewing their data.

[[Page 52135]]

    Although we did not solicit feedback on the burden associated with 
the measures finalized in the FY 2016 IRF PPS final rule (80 FR 47100 
through 47120), including functional status measures, which will be 
collected via the IRF-PAI Version 1.4 effective October 1, 2016, we 
received several comments, which are summarized below.
    Comment: Several commenters were concerned that the additional 41.5 
minutes required to collect new required data elements finalized in the 
FY 2016 IRF PPS final rule, including training staff and updating 
medical records, led to increased costs to IRFs that are not covered in 
the update to the standard payment conversion factor proposed for IRFs. 
One commenter also noted that delays in training led to additional 
expenses for preparing staff and electronic health records.
    Response: We refer the reader to our discussion of burden due to 
data set revisions, data collection, or training of staff due to the 
revisions in the IRF-PAI Version 1.4 in the FY 2016 IRF PPS final rule 
(80 FR 47086 through 47120). Feedback relating to provider burden will 
be taken into account as we consider future updates to the IRF QRP.
    With regards to comments about the updated SPCF, we refer readers 
to the IRF PPS FY 2016 final rule (80 FR 47129 through 47137) for 
details regarding the Collection of Information Requirements and 
Regulatory Impact Analysis for the measures finalized in FY 2016. We 
would also like to clarify that QRP requirements are not included in 
the SPCF, however, per statutory requirements, the applicable annual 
increase factor for any IRF that does not submit the required data to 
CMS is reduced by 2 percentage points. Additional responses to these 
comments are included in sections VI.E and IX. of this final rule.

XII. Regulatory Impact Analysis

A. Statement of Need

    This final rule updates the IRF prospective payment rates for FY 
2017 as required under section 1886(j)(3)(C) of the Act. It responds to 
section 1886(j)(5) of the Act, which requires the Secretary to publish 
in the Federal Register on or before the August 1 that precedes the 
start of each fiscal year, the classification and weighting factors for 
the IRF PPS's case-mix groups and a description of the methodology and 
data used in computing the prospective payment rates for that fiscal 
year.
    This final rule also implements sections 1886(j)(3)(C) and (D) of 
the Act. Section 1886(j)(3)(C)(ii)(I) of the Act requires the Secretary 
to apply a multi-factor productivity adjustment to the market basket 
increase factor, and to apply other adjustments as defined by the Act. 
The productivity adjustment applies to FYs from 2012 forward. The other 
adjustments apply to FYs 2010 through 2019.
    Furthermore, this final rule also adopts policy changes under the 
statutory discretion afforded to the Secretary under section 1886(j)(7) 
of the Act. Specifically, we will revise and update the quality 
measures and reporting requirements under the IRF quality reporting 
program.

B. Overall Impacts

    We have examined the impacts of this final rule as required by 
Executive Order 12866 (September 30, 1993, Regulatory Planning and 
Review), Executive Order 13563 on Improving Regulation and Regulatory 
Review (January 18, 2011), the Regulatory Flexibility Act (September 
19, 1980, Pub. L. 96-354) (RFA), section 1102(b) of the Act, section 
202 of the Unfunded Mandates Reform Act of 1995 (Pub. L. 104-4), 
Executive Order 13132 on Federalism (August 4, 1999), and the 
Congressional Review Act (5 U.S.C. 804(2)).
    Executive Orders 12866 and 13563 direct agencies to assess all 
costs and benefits of available regulatory alternatives and, if 
regulation is necessary, to select regulatory approaches that maximize 
net benefits (including potential economic, environmental, public 
health and safety effects, distributive impacts, and equity). Executive 
Order 13563 emphasizes the importance of quantifying both costs and 
benefits, of reducing costs, of harmonizing rules, and of promoting 
flexibility. A regulatory impact analysis (RIA) must be prepared for a 
major final rule with economically significant effects ($100 million or 
more in any 1 year). We estimate the total impact of the policy updates 
described in this final rule by comparing the estimated payments in FY 
2017 with those in FY 2016. This analysis results in an estimated $145 
million increase for FY 2017 IRF PPS payments. As a result, this final 
rule is designated as economically ``significant'' under section 
3(f)(1) of Executive Order 12866, and hence a major rule under the 
Congressional Review Act. Also, the rule has been reviewed by OMB.
    The Regulatory Flexibility Act (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 IRFs and most 
other providers and suppliers are small entities, either by having 
revenues of $7.5 million to $38.5 million or less in any 1 year 
depending on industry classification, or by being nonprofit 
organizations that are not dominant in their markets. (For details, see 
the Small Business Administration's final rule that set forth size 
standards for health care industries, at 65 FR 69432 at http://www.sba.gov/sites/default/files/files/Size_Standards_Table.pdf, 
effective March 26, 2012 and updated on February 26, 2016.) Because we 
lack data on individual hospital receipts, we cannot determine the 
number of small proprietary IRFs or the proportion of IRFs' revenue 
that is derived from Medicare payments. Therefore, we assume that all 
IRFs (an approximate total of 1,100 IRFs, of which approximately 60 
percent are nonprofit facilities) are considered small entities and 
that Medicare payment constitutes the majority of their revenues. The 
HHS generally uses a revenue impact of 3 to 5 percent as a significance 
threshold under the RFA. As shown in Table 22, we estimate that the net 
revenue impact of this final rule on all IRFs is to increase estimated 
payments by approximately 1.9 percent. The rates and policies set forth 
in this final rule will not have a significant impact (not greater than 
3 percent) on a substantial number of small entities. Medicare 
Administrative Contractors are not considered to be small entities. 
Individuals and states are not included in the definition of a small 
entity.
    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 detail 
below in this section, the rates and policies set forth in this final 
rule will not have a significant impact (not greater than 3 percent) on 
a substantial number of rural hospitals based on the data of the 140 
rural units and 11 rural hospitals in our database of 1,133 IRFs for 
which data were available.
    Section 202 of the Unfunded Mandates Reform Act of 1995 (Pub. L. 
104-04, enacted on March 22, 1995) also requires that agencies assess 
anticipated costs and benefits before

[[Page 52136]]

issuing any rule whose mandates require spending in any 1 year of $100 
million in 1995 dollars, updated annually for inflation. In 2016, that 
threshold level is approximately $146 million. This final rule will not 
mandate spending costs on state, local, or tribal governments, in the 
aggregate, or by the private sector, of greater than $146 million.
    Executive Order 13132 establishes certain requirements that an 
agency must meet when it promulgates a final rule that imposes 
substantial direct requirement costs on state and local governments, 
preempts state law, or otherwise has federalism implications. As 
stated, this final rule will not have a substantial effect on state and 
local governments, preempt state law, or otherwise have a federalism 
implication.

C. Detailed Economic Analysis

1. Basis and Methodology of Estimates
    This final rule updates to the IRF PPS rates contained in the FY 
2016 IRF PPS final rule (80 FR 47036). Specifically, this final rule 
updates the CMG relative weights and average length of stay values, the 
wage index, and the outlier threshold for high-cost cases. This final 
rule applies a MFP adjustment to the FY 2017 IRF market basket increase 
factor in accordance with section 1886(j)(3)(C)(ii)(I) of the Act, and 
a 0.75 percentage point reduction to the FY 2017 IRF market basket 
increase factor in accordance with sections 1886(j)(3)(C)(ii)(II) and 
(D)(v) of the Act. Further, this final rule contains revisions to the 
IRF quality reporting requirements that are expected to result in some 
additional financial effects on IRFs. In addition, section VIII of this 
final rule discusses the implementation of the required 2 percentage 
point reduction of the market basket increase factor for any IRF that 
fails to meet the IRF quality reporting requirements, in accordance 
with section 1886(j)(7) of the Act.
    We estimate that the impact of the changes and updates described in 
this final rule will be a net estimated increase of $145 million in 
payments to IRF providers. This estimate does not include the 
implementation of the required 2 percentage point reduction of the 
market basket increase factor for any IRF that fails to meet the IRF 
quality reporting requirements (as discussed in section XII.C.6. of 
this final rule). The impact analysis in Table 22 of this final rule 
represents the projected effects of the updates to IRF PPS payments for 
FY 2017 compared with the estimated IRF PPS payments in FY 2016. We 
determine the effects by estimating payments while holding all other 
payment variables constant. We use the best data available, but we do 
not attempt to predict behavioral responses to these changes, and we do 
not make adjustments for future changes in such variables as number of 
discharges or case-mix.
    We note that certain events may combine to limit the scope or 
accuracy of our impact analysis, because such an analysis is future-
oriented and, thus, susceptible to forecasting errors because of other 
changes in the forecasted impact time period. Some examples could be 
legislative changes made by the Congress to the Medicare program that 
would impact program funding, or changes specifically related to IRFs. 
Although some of these changes may not necessarily be specific to the 
IRF PPS, the nature of the Medicare program is such that the changes 
may interact, and the complexity of the interaction of these changes 
could make it difficult to predict accurately the full scope of the 
impact upon IRFs.
    In updating the rates for FY 2017, we are adopting standard annual 
revisions described in this final rule (for example, the update to the 
wage and market basket indexes used to adjust the federal rates). We 
are also implementing a productivity adjustment to the FY 2017 IRF 
market basket increase factor in accordance with section 
1886(j)(3)(C)(ii)(I) of the Act, and a 0.75 percentage point reduction 
to the FY 2017 IRF market basket increase factor in accordance with 
sections 1886(j)(3)(C)(ii)(II) and (D)(v) of the Act. We estimate the 
total increase in payments to IRFs in FY 2017, relative to FY 2016, 
will be approximately $145 million.
    This estimate is derived from the application of the FY 2017 IRF 
market basket increase factor, as reduced by a productivity adjustment 
in accordance with section 1886(j)(3)(C)(ii)(I) of the Act, and a 0.75 
percentage point reduction in accordance with sections 
1886(j)(3)(C)(ii)(II) and (D)(v) of the Act, which yields an estimated 
increase in aggregate payments to IRFs of $125 million. Furthermore, 
there is an additional estimated $20 million increase in aggregate 
payments to IRFs due to the update of the outlier threshold amount. 
Outlier payments are estimated to increase from approximately 2.7 
percent in FY 2016 to 3.0 percent in FY 2017. Therefore, summed 
together, we estimate that these updates will result in a net increase 
in estimated payments of $145 million from FY 2016 to FY 2017.
    The effects of the updates that impact IRF PPS payment rates are 
shown in Table 22. The following updates that affect the IRF PPS 
payment rates are discussed separately below:
     The effects of the update to the outlier threshold amount, 
from approximately 2.7 percent to 3.0 percent of total estimated 
payments for FY 2017, consistent with section 1886(j)(4) of the Act.
     The effects of the annual market basket update (using the 
IRF market basket) to IRF PPS payment rates, as required by section 
1886(j)(3)(A)(i) and sections 1886(j)(3)(C) and (D) of the Act, 
including a productivity adjustment in accordance with section 
1886(j)(3)(C)(i)(I) of the Act, and a 0.75 percentage point reduction 
in accordance with sections 1886(j)(3)(C)(ii)(II) and (D)(v) of the 
Act.
     The effects of applying the budget-neutral labor-related 
share and wage index adjustment, as required under section 1886(j)(6) 
of the Act.
     The effects of the budget-neutral changes to the CMG 
relative weights and average length of stay values, under the authority 
of section 1886(j)(2)(C)(i) of the Act.
     The total change in estimated payments based on the FY 
2017 payment changes relative to the estimated FY 2016 payments.
2. Description of Table 22
    Table 22 categorizes IRFs by geographic location, including urban 
or rural location, and location for CMS's 9 Census divisions (as 
defined on the cost report) of the country. In addition, the table 
divides IRFs into those that are separate rehabilitation hospitals 
(otherwise called freestanding hospitals in this section), those that 
are rehabilitation units of a hospital (otherwise called hospital units 
in this section), rural or urban facilities, ownership (otherwise 
called for-profit, non-profit, and government), by teaching status, and 
by disproportionate share patient percentage (DSH PP). The top row of 
Table 22 shows the overall impact on the 1,133 IRFs included in the 
analysis.
    The next 12 rows of Table 22 contain IRFs categorized according to 
their geographic location, designation as either a freestanding 
hospital or a unit of a hospital, and by type of ownership; all urban, 
which is further divided into urban units of a hospital, urban 
freestanding hospitals, and by type of ownership; and all rural, which 
is further divided into rural units of a hospital, rural freestanding 
hospitals, and by type of ownership. There are 982 IRFs located in 
urban areas included in

[[Page 52137]]

our analysis. Among these, there are 730 IRF units of hospitals located 
in urban areas and 252 freestanding IRF hospitals located in urban 
areas. There are 151 IRFs located in rural areas included in our 
analysis. Among these, there are 140 IRF units of hospitals located in 
rural areas and 11 freestanding IRF hospitals located in rural areas. 
There are 409 for-profit IRFs. Among these, there are 356 IRFs in urban 
areas and 53 IRFs in rural areas. There are 653 non-profit IRFs. Among 
these, there are 564 urban IRFs and 89 rural IRFs. There are 71 
government-owned IRFs. Among these, there are 62 urban IRFs and 9 rural 
IRFs.
    The remaining four parts of Table 22 show IRFs grouped by their 
geographic location within a region, by teaching status, and by DSH PP. 
First, IRFs located in urban areas are categorized for their location 
within a particular one of the nine Census geographic regions. Second, 
IRFs located in rural areas are categorized for their location within a 
particular one of the nine Census geographic regions. In some cases, 
especially for rural IRFs located in the New England, Mountain, and 
Pacific regions, the number of IRFs represented is small. IRFs are then 
grouped by teaching status, including non-teaching IRFs, IRFs with an 
intern and resident to average daily census (ADC) ratio less than 10 
percent, IRFs with an intern and resident to ADC ratio greater than or 
equal to 10 percent and less than or equal to 19 percent, and IRFs with 
an intern and resident to ADC ratio greater than 19 percent. Finally, 
IRFs are grouped by DSH PP, including IRFs with zero DSH PP, IRFs with 
a DSH PP less than 5 percent, IRFs with a DSH PP between 5 and less 
than 10 percent, IRFs with a DSH PP between 10 and 20 percent, and IRFs 
with a DSH PP greater than 20 percent.
    The estimated impacts of each policy described in this final rule 
to the facility categories listed are shown in the columns of Table 22. 
The description of each column is as follows:
     Column (1) shows the facility classification categories.
     Column (2) shows the number of IRFs in each category in 
our FY 2016 analysis file.
     Column (3) shows the number of cases in each category in 
our FY 2016 analysis file.
     Column (4) shows the estimated effect of the adjustment to 
the outlier threshold amount.
     Column (5) shows the estimated effect of the update to the 
IRF labor-related share and wage index, in a budget-neutral manner.
     Column (6) shows the estimated effect of the update to the 
CMG relative weights and average length of stay values, in a budget-
neutral manner.
     Column (7) compares our estimates of the payments per 
discharge, incorporating all of the policies reflected in this final 
rule for FY 2017 to our estimates of payments per discharge in FY 2016.
    The average estimated increase for all IRFs is approximately 1.9 
percent. This estimated net increase includes the effects of the IRF 
market basket increase factor for FY 2017 of 2.7 percent, reduced by a 
productivity adjustment of 0.3 percentage point in accordance with 
section 1886(j)(3)(C)(ii)(I) of the Act, and further reduced by 0.75 
percentage point in accordance with sections 1886(j)(3)(C)(ii)(II) and 
(D)(v) of the Act. It also includes the approximate 0.3 percent overall 
increase in estimated IRF outlier payments from the update to the 
outlier threshold amount. Since we are making the updates to the IRF 
wage index and the CMG relative weights in a budget-neutral manner, 
they will not be expected to affect total estimated IRF payments in the 
aggregate. However, as described in more detail in each section, they 
will be expected to affect the estimated distribution of payments among 
providers.

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3. Impact of the Update to the Outlier Threshold Amount
    The estimated effects of the update to the outlier threshold 
adjustment are presented in column 4 of Table 22.
    For the FY 2017 IRF PPS proposed rule, we used preliminary FY 2015 
IRF claims data, and, based on that preliminary analysis, we estimated 
that IRF outlier payments as a percentage of total estimated IRF 
payments would be 2.8 percent in FY 2016 (81 FR 24178, 24193). As we 
typically do between the proposed and final rules each year, we updated 
our FY 2015 IRF claims data to ensure that we are using the most recent 
available data in setting IRF payments. Therefore, based on updated 
analysis of the most recent IRF claims data for this final rule, we now 
estimate that IRF outlier payments as a percentage of total estimated 
IRF payments are 2.7 percent in FY 2016. Thus, we are adjusting the 
outlier threshold amount in this final rule to set total estimated 
outlier payments equal to 3 percent of total estimated payments in FY 
2017. The estimated change in total IRF payments for FY 2017, 
therefore, includes an approximate 0.3 percent increase in payments 
because the estimated outlier portion of total payments is estimated to 
increase from approximately 2.7 percent to 3 percent.
    The impact of this outlier adjustment update (as shown in column 4 
of Table 22) is to increase estimated overall payments to IRFs by about 
0.3 percent. We estimate the largest increase in payments from the 
update to the outlier threshold amount to be 1.4 percent for rural IRFs 
in the Pacific region.
4. Impact of the CBSA Wage Index and Labor-Related Share
    In column 5 of Table 22, we present the effects of the budget-
neutral update of the wage index and labor-related share. The changes 
to the wage index and the labor-related share are discussed together 
because the wage index is applied to the labor-related share portion of 
payments, so the changes in the two have a combined effect on payments 
to providers. As discussed in section VI.C. of this final rule, we will 
decrease the labor-related share from 71.0 percent in FY 2016 to 70.9 
percent in FY 2017.
5. Impact of the Update to the CMG Relative Weights and Average Length 
of Stay Values
    In column 6 of Table 22, we present the effects of the budget-
neutral update of the CMG relative weights and average length of stay 
values. In the aggregate, we do not estimate that these updates will 
affect overall estimated payments of IRFs. However, we do expect these 
updates to have small distributional effects. The largest estimated 
increase in payments is a 0.1 percent increase for rural IRFs in the 
Middle Atlantic region, and urban IRFs in the New England and East 
North Central regions. Rural IRFs in the Pacific region and urban IRFs 
in the East south Central regions are estimated to experience a 0.1 
percent decrease in payments due to the CMG relative weights change.
6. Effects of Requirements for the IRF QRP for FY 2018
    In accordance with section 1886(j)(7) of the Act, we will implement 
a 2 percentage point reduction in the FY 2018 increase factor for IRFs 
that have failed to report the required quality reporting data to us 
during the most recent IRF quality reporting period. In section VIII.P 
of this final rule, we discuss the proposed method for applying the 2 
percentage point reduction to IRFs that fail to meet the IRF QRP 
requirements. At the time that this analysis was prepared, 91, or 
approximately 8 percent, of the 1166 active Medicare-certified IRFs did 
not receive the full annual percentage increase for the FY 2016 annual 
payment update determination. Information is not available to determine 
the precise number of IRFs that will not meet the requirements to 
receive the full annual percentage increase for the FY 2017 payment 
determination.
    In section VIII.L of this final rule, we discuss our proposal to 
suspend the previously finalized data accuracy validation policy for 
IRFs. While we cannot estimate the change in the number of IRFs that 
will meet IRF QRP compliance standards at this time, we believe that 
this number will increase due to the temporary suspension of this 
policy. Thus, we estimate that the suspension of this policy will 
decrease impact on overall IRF payments, by increasing the rate of 
compliance, in addition to decreasing the cost of the IRF QRP to each 
IRF provider by approximately $47,320 per IRF, which was the estimated 
cost to each IRF provider to the implement the previously finalized 
policy.
    In section VIII.F of this final rule, we are finalizing four 
measures for the FY 2018 payment determinations and subsequent years: 
(1) MSPB-PAC IRF QRP; (2) Discharge to Community-PAC IRF QRP, and (3) 
Potentially Preventable 30-Day Post-Discharge Readmission Measure for 
IRF QRP; (4) Potentially Preventable Within Stay Readmission Measure 
IRFs. These four measures are Medicare claims-based measures; because 
claims-based measures can be calculated based on data that are already 
reported to the Medicare program for payment purposes, we believe there 
will be no additional impact.
    In section VIII.G of this final rule, we are also finalizing one 
measure for the FY 2020 payment determination and subsequent years: 
Drug Regimen Review Conducted with Follow-Up for Identified Issues-PAC 
IRF QRP. Additionally, data for this measure will be collected and 
reported using the IRF-PAI (version effective October 1, 2018). While 
the reporting of data on quality measures is an information collection, 
we believe that the burden associated with modifications to the IRF-PAI 
discussed in this final rule fall under the PRA exceptions provided in 
1899B(m) of the Act because they are required to achieve the 
standardization of patient assessment data. Section 1899B(m) of the Act 
provides that the PRA does not apply to section 1899B and the sections 
referenced in section 1899B(a)(2)(B) of the Act that require 
modification to achieve the standardization of patient assessment data. 
The requirement and burden will, however, be submitted to OMB for 
review and approval when the modifications to the IRF-PAI or other 
applicable PAC assessment instrument are not used to achieve the 
standardization of patient assessment data.
    The total cost related to the proposed measures is estimated at 
$4,625.46 per IRF annually, or $5,231,398.17 for all IRFs annually.
    We intend to continue to closely monitor the effects of this new 
quality reporting program on IRF providers and help perpetuate 
successful reporting outcomes through ongoing stakeholder education, 
national trainings, IRF provider announcements, Web site postings, CMS 
Open Door Forums, and general and technical help desks.
    We did not receive any comments related to the Effects of Proposed 
Requirements for the IRF QRP for FY 2018.

D. Alternatives Considered

    The following is a discussion of the alternatives considered for 
the IRF PPS updates contained in this final rule.
    Section 1886(j)(3)(C) of the Act requires the Secretary to update 
the IRF PPS payment rates by an increase factor that reflects changes 
over time in the prices of an appropriate mix of goods and services 
included in the covered IRF services Thus, we did not consider 
alternatives to updating payments using the estimated IRF market basket

[[Page 52140]]

increase factor for FY 2017. However, as noted previously in this final 
rule, section 1886(j)(3)(C)(ii)(I) of the Act requires the Secretary to 
apply a productivity adjustment to the market basket increase factor 
for FY 2017, and sections 1886(j)(3)(C)(ii)(II) and 1886(j)(3)(D)(v) of 
the Act require the Secretary to apply a 0.75 percentage point 
reduction to the market basket increase factor for FY 2017. Thus, in 
accordance with section 1886(j)(3)(C) of the Act, we update the IRF 
federal prospective payments in this final rule by 1.65 percent (which 
equals the 2.7 percent estimated IRF market basket increase factor for 
FY 2017 reduced by a 0.3 percentage point productivity adjustment as 
required by section 1886(j)(3)(C)(ii)(I) of the Act and further reduced 
by 0.75 percentage point). We considered maintaining the existing CMG 
relative weights and average length of stay values for FY 2017. 
However, in light of recently available data and our desire to ensure 
that the CMG relative weights and average length of stay values are as 
reflective as possible of recent changes in IRF utilization and case 
mix, we believe that it is appropriate to update the CMG relative 
weights and average length of stay values at this time to ensure that 
IRF PPS payments continue to reflect as accurately as possible the 
current costs of care in IRFs.
    We considered updating facility-level adjustment factors for FY 
2017. However, as discussed in more detail in the FY 2015 final rule 
(79 FR 45872), we believe that freezing the facility-level adjustments 
at FY 2014 levels for FY 2015 and all subsequent years (unless and 
until the data indicate that they need to be further updated) will 
allow us an opportunity to monitor the effects of the substantial 
changes to the adjustment factors for FY 2014, and will allow IRFs time 
to adjust to the previous changes.
    We considered maintaining the existing outlier threshold amount for 
FY 2017. However, analysis of updated FY 2015 data indicates that 
estimated outlier payments would be lower than 3 percent of total 
estimated payments for FY 2017, by approximately 0.3 percent, unless we 
updated the outlier threshold amount. Consequently, we are adjusting 
the outlier threshold amount in this final rule to reflect a 0.3 
percent increase thereby setting the total outlier payments equal to 3 
percent, instead of 2.7 percent, of aggregate estimated payments in FY 
2017.

E. Accounting Statement

    As required by OMB Circular A-4 (available at http://www.whitehouse.gov/sites/default/files/omb/assets/omb/circulars/a004/a-4.pdf), in Table 23, we have prepared an accounting statement showing 
the classification of the expenditures associated with the provisions 
of this final rule. Table 23 provides our best estimate of the increase 
in Medicare payments under the IRF PPS as a result of the updates 
presented in this final rule based on the data for 1,133 IRFs in our 
database. In addition, Table 23 presents the costs associated with the 
new IRF quality reporting program for FY 2017.

Table 23--Accounting Statement: Classification of Estimated Expenditures
------------------------------------------------------------------------
                Category                            Transfers
------------------------------------------------------------------------
  Change in Estimated Transfers from FY 2016 IRF PPS to FY 2017 IRF PPS
------------------------------------------------------------------------
Annualized Monetized Transfers.........  $145 million.
From Whom to Whom?.....................  Federal Government to IRF
                                          Medicare Providers.
------------------------------------------------------------------------
                Category                              Costs
------------------------------------------------------------------------
         FY 2017 Cost to Updating the Quality Reporting Program
------------------------------------------------------------------------
Cost for IRFs to Submit Data for the     $5,231,398.17.
 Quality Reporting Program.
------------------------------------------------------------------------

F. Conclusion

    Overall, the estimated payments per discharge for IRFs in FY 2017 
are projected to increase by 1.9 percent, compared with the estimated 
payments in FY 2016, as reflected in column 7 of Table 22.
    IRF payments per discharge are estimated to increase by 2.0 percent 
in urban areas and 1.2 percent in rural areas, compared with estimated 
FY 2016 payments. Payments per discharge to rehabilitation units are 
estimated to increase 2.2 percent in urban areas and 1.5 percent in 
rural areas. Payments per discharge to freestanding rehabilitation 
hospitals are estimated to increase 1.8 percent in urban areas and 0.0 
percent in rural areas.
    Overall, IRFs are estimated to experience a net increase in 
payments as a result of the proposed policies in this final rule. The 
largest payment increase is estimated to be a 3.1 percent increase for 
rural IRFs located in the Pacific region.
    In accordance with the provisions of Executive Order 12866, this 
final rule was reviewed by the Office of Management and Budget.

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 amends 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:  Secs. 1102 and 1871 of the Social Security Act (42 
U.S.C. 1302 and 1395hh), sec. 124 of Pub. L. 106-113 (113 Stat. 
1501A-332), sec. 1206 of Pub. L. 113-67, and sec. 112 of Pub. L. 
113-93.

0
2. Section 412.634 is amended by revising paragraph (c)(2) and adding 
paragraph (f) to read as follows:


Sec.  412.634  Requirements under the Inpatient Rehabilitation Facility 
(IRF) Quality Reporting Program (QRP).

* * * * *
    (c) * * *
    (2) An IRF must request an exception or extension within 90 days of 
the date that the extraordinary circumstances occurred.
* * * * *
    (f) Data Completion Thresholds. (1) IRFs must meet or exceed two 
separate data completeness thresholds: One threshold set at 95 percent 
for completion of quality measures data collected using the IRF-PAI 
submitted through the QIES and a second threshold set at 100 percent 
for quality

[[Page 52141]]

measures data collected and submitted using the CDC NHSN.
    (2) These thresholds will apply to all measures adopted into IRF 
QRP.
    (3) An IRF must meet or exceed both thresholds to avoid receiving a 
2 percentage point reduction to their annual payment update for a given 
fiscal year, beginning with FY 2016 and for all subsequent payment 
updates.

    Dated: July 18, 2016.
Andrew M. Slavitt,
Acting Administrator, Centers for Medicare & Medicaid Services.

    Dated: July 25, 2016.
Sylvia M. Burwell,
Secretary, Department of Health and Human Services.
[FR Doc. 2016-18196 Filed 7-29-16; 4:15 pm]
 BILLING CODE 4120-01-P