A Collaboration with the University of Pittsburgh

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

Issued by Health and Human Services Department
on Monday 25 April 2016
 

Table of Contents Back to Top

Tables Back to Top

DATES: Back to Top

To be assured consideration, comments must be received at one of the addresses provided below, not later than 5 p.m. on June 20, 2016.

ADDRESSES: Back to Top

In commenting, please refer to file code CMS-1647-P. Because of staff and resource limitations, we cannot accept comments by facsimile (FAX) transmission.

You may submit comments in one of four ways (please choose only one of the ways listed):

1. Electronically. You may submit electronic comments on this regulation to http://www.regulations.gov. Follow the “Submit a comment” instructions.

2. By regular mail. You may mail written comments to the following address ONLY: Centers for Medicare & Medicaid Services, Department of Health and Human Services, Attention: CMS-1647-P, P.O. Box 8016, Baltimore, MD 21244-8016.

Please allow sufficient time for mailed comments to be received before the close of the comment period.

3. By express or overnight mail. You may send written comments to the following address ONLY: Centers for Medicare & Medicaid Services, Department of Health and Human Services, Attention: CMS-1647-P, Mail Stop C4-26-05, 7500 Security Boulevard, Baltimore, MD 21244-1850.

4. By hand or courier. Alternatively, you may deliver (by hand or courier) your written comments ONLY to the following addresses prior to the close of the comment period:

a. For delivery in Washington, DC—Centers for Medicare & Medicaid Services, Department of Health and Human Services, Room 445-G, Hubert H. Humphrey Building, 200 Independence Avenue SW., Washington, DC 20201

(Because access to the interior of the Hubert H. Humphrey Building is not readily available to persons without Federal government identification, commenters are encouraged to leave their comments in the CMS drop slots located in the main lobby of the building. A stamp-in clock is available for persons wishing to retain a proof of filing by stamping in and retaining an extra copy of the comments being filed.)

b. For delivery in Baltimore, MD—Centers for Medicare & Medicaid Services, Department of Health and Human Services, 7500 Security Boulevard, Baltimore, MD 21244-1850

If you intend to deliver your comments to the Baltimore address, please call telephone number (410) 786-7195 in advance to schedule your arrival with one of our staff members.

Comments erroneously mailed to the addresses indicated as appropriate for hand or courier delivery may be delayed and received after the comment period.

For information on viewing public comments, see the beginning of the SUPPLEMENTARY INFORMATION section.

FOR FURTHER INFORMATION CONTACT: Back to Top

Gwendolyn Johnson, (410) 786-6954, for general information.

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: Back to Top

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

Inspection of Public Comments: All comments received before the close of the comment period are available for viewing by the public, including any personally identifiable or confidential business information that is included in a comment. We post all comments received before the close of the comment period on the following Web site as soon as possible after they have been received: http://www.regulations.gov. Follow the search instructions on that Web site to view public comments.

Comments received timely will also be available for public inspection as they are received, generally beginning approximately 3 weeks after publication of a document, at the headquarters of the Centers for Medicare & Medicaid Services, 7500 Security Boulevard, Baltimore, Maryland 21244, Monday through Friday of each week from 8:30 a.m. to 4 p.m. To schedule an appointment to view public comments, phone 1-800-743-3951.

Executive Summary Back to Top

A. Purpose

This proposed rule would update 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 proposed rule also proposes revisions and updates to the quality measures and reporting requirements under the IRF QRP.

B. Summary of Major Provisions

In this proposed rule, we use the methods described in the FY 2016 IRF PPS final rule (80 FR 47036) to propose updates to 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 proposing to revise and update quality measures and reporting requirements under the IRF QRP.

C. Summary of Impacts

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Provision description Transfers
FY 2017 IRF PPS payment rate update The overall economic impact of this proposed rule is an estimated $125 million in increased payments from the Federal government to IRFs during FY 2017.
Provision description Costs
New quality reporting program requirements The total costs in FY 2017 for IRFs as a result of the proposed 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 Back to Top

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

IV. Facility-Level Adjustment Factors

V. Proposed FY 2017 IRF PPS Payment Update

A. Background

B. Proposed FY 2017 Market Basket Update and Productivity Adjustment

C. Proposed Labor-Related Share for FY 2017

D. Proposed Wage Adjustment

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

F. Example of the Methodology for Adjusting the Proposed Federal Prospective Payment Rates

VI. Proposed Update to Payments for High-Cost Outliers under the IRF PPS

A. Proposed Update to the Outlier Threshold Amount for FY 2017

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

VII. Proposed 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 Proposed for the FY 2018 Payment Determination and Subsequent Years

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

H. IRF QRP Quality Measures and Measure Concepts under Consideration for Future Years

I. Proposed 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

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

VIII. Collection of Information Requirements

A. Statutory Requirement for Solicitation of Comments

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

IX. Response to Public Comments

X. 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 Back to Top

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

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

eCQMs Electronically Specified Clinical Quality Measures

ESRD End-Stage Renal Disease

FFS Fee-for-Service

FR Federal Register

FY Federal Fiscal Year

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)

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 Back to Top

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 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 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 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 V.B. of this proposed rule. Section 3401(d) of the Affordable Care Act requires an additional 0.75 percentage point adjustment to the IRF increase factor for FY 2017, as discussed in section V.B. of this proposed 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 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://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) (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.

II. Summary of Provisions of the Proposed Rule Back to Top

In this proposed rule, we propose 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 are 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 this proposed rule.
  • Describe the continued use of FY 2014 facility-level adjustment factors as discussed in section IV of this proposed rule.
  • 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 this proposed rule.
  • 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 this proposed rule.
  • Describe the calculation of the IRF standard payment conversion factor for FY 2017, as discussed in section V of this proposed rule.
  • Update the outlier threshold amount for FY 2017, as discussed in section VI of this proposed rule.
  • Update the cost-to-charge ratio (CCR) ceiling and urban/rural average CCRs for FY 2017, as discussed in section VI of this proposed rule.
  • 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 this proposed rule.

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

As specified in § 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 this proposed rule, we propose 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 propose 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. Currently, only a small portion of the FY 2015 IRF cost report data are available for analysis, but the majority of the FY 2015 IRF claims data are available for analysis.

In this proposed rule, we propose 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 proposed 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 propose 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 proposed changes to the CMG relative weights (as discussed in this proposed rule).

Step 3. Divide the amount calculated in step 1 by the amount calculated in step 2 to determine the budget neutrality factor (0.9990) that would maintain the same total estimated aggregate payments in FY 2017 with and without the proposed changes to the CMG relative weights.

Step 4. Apply the budget neutrality factor (0.9990) to the FY 2016 IRF PPS standard payment amount after the application of the budget-neutral wage adjustment factor.

In section V.E. of this proposed rule, we discuss the proposed use of the existing methodology to calculate the proposed standard payment conversion factor for FY 2017.

In Table 1, “Proposed 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.

Table 1—Proposed Relative Weights and Average Length of Stay Values for Case-Mix Groups Back to Top
CMG CMG Description (M=motor, C=cognitive, A=age) Relative weight Average length of stay
Tier 1 Tier 2 Tier 3 None Tier 1 Tier 2 Tier 3 None
0101 Stroke M>51.05 0.8007 0.7158 0.6527 0.6228 8 9 9 8
0102 Stroke M>44.45 and M<51.05 and C>18.5 1.0117 0.9044 0.8247 0.7869 11 12 10 10
0103 Stroke M>44.45 and M<51.05 and C<18.5 1.1804 1.0552 0.9622 0.9181 11 13 12 12
0104 Stroke M>38.85 and M<44.45 1.2603 1.1266 1.0274 0.9803 12 12 12 12
0105 Stroke M>34.25 and M<38.85 1.4562 1.3018 1.1871 1.1327 14 15 14 14
0106 Stroke M>30.05 and M<34.25 1.6306 1.4576 1.3293 1.2683 16 16 15 15
0107 Stroke M>26.15 and M<30.05 1.8168 1.6241 1.4811 1.4132 17 19 17 17
0108 Stroke M<26.15 and A>84.5 2.2856 2.0432 1.8632 1.7779 21 22 21 20
0109 Stroke M>22.35 and M<26.15 and A<84.5 2.0579 1.8396 1.6776 1.6007 19 20 18 19
0110 Stroke M<22.35 and A<84.5 2.7293 2.4398 2.2249 2.1230 29 27 24 24
0201 Traumatic brain injury M>53.35 and C>23.5 0.7826 0.6402 0.5775 0.5385 8 8 8 7
0202 Traumatic brain injury M>44.25 and M<53.35 and C>23.5 1.0939 0.8948 0.8072 0.7527 12 10 9 10
0203 Traumatic brain injury M>44.25 and C<23.5 1.2187 0.9969 0.8993 0.8385 11 12 11 11
0204 Traumatic brain injury M>40.65 and M<44.25 1.3419 1.0977 0.9902 0.9233 16 13 12 11
0205 Traumatic brain injury M>28.75 and M<40.65 1.6233 1.3279 1.1979 1.1170 14 15 14 13
0206 Traumatic brain injury M>22.05 and M<28.75 1.9247 1.5744 1.4202 1.3243 19 18 16 15
0207 Traumatic brain injury M<22.05 2.5314 2.0708 1.8680 1.7418 31 23 20 19
0301 Non-traumatic brain injury M>41.05 1.1417 0.9423 0.8561 0.8003 10 11 10 10
0302 Non-traumatic brain injury M>35.05 and M<41.05 1.4064 1.1608 1.0546 0.9858 13 13 12 12
0303 Non-traumatic brain injury M>26.15 and M<35.05 1.6478 1.3600 1.2356 1.1550 15 15 14 14
0304 Non-traumatic brain injury M<26.15 2.1328 1.7604 1.5993 1.4949 21 20 17 16
0401 Traumatic spinal cord injury M>48.45 0.9816 0.8589 0.7927 0.7201 11 11 10 9
0402 Traumatic spinal cord injury M>30.35 and M<48.45 1.4090 1.2330 1.1379 1.0337 14 14 14 13
0403 Traumatic spinal cord injury M>16.05 and M<30.35 2.2221 1.9445 1.7946 1.6303 21 21 20 19
0404 Traumatic spinal cord injury M<16.05 and A>63.5 3.8903 3.4042 3.1418 2.8541 47 37 34 32
0405 Traumatic spinal cord injury M<16.05 and A<63.5 3.4259 2.9979 2.7668 2.5134 47 33 28 28
0501 Non-traumatic spinal cord injury M>51.35 0.8605 0.6793 0.6459 0.5815 9 8 7 8
0502 Non-traumatic spinal cord injury M>40.15 and M<51.35 1.1607 0.9162 0.8712 0.7843 11 11 10 10
0503 Non-traumatic spinal cord injury M>31.25 and M<40.15 1.4538 1.1476 1.0912 0.9824 14 13 13 12
0504 Non-traumatic spinal cord injury M>29.25 and M<31.25 1.7071 1.3475 1.2813 1.1535 19 16 14 14
0505 Non-traumatic spinal cord injury M>23.75 and M<29.25 1.9596 1.5468 1.4708 1.3242 20 17 17 16
0506 Non-traumatic spinal cord injury M<23.75 2.7126 2.1412 2.0360 1.8330 28 24 22 21
0601 Neurological M>47.75 1.0371 0.8203 0.7581 0.6940 10 9 9 9
0602 Neurological M>37.35 and M<47.75 1.3356 1.0563 0.9762 0.8936 12 12 11 11
0603 Neurological M>25.85 and M<37.35 1.6450 1.3010 1.2023 1.1007 14 14 13 13
0604 Neurological M<25.85 2.1787 1.7232 1.5924 1.4578 20 18 16 16
0701 Fracture of lower extremity M>42.15 1.0013 0.8151 0.7777 0.7065 10 9 9 9
0702 Fracture of lower extremity M>34.15 and M<42.15 1.2773 1.0398 0.9921 0.9013 12 12 12 11
0703 Fracture of lower extremity M>28.15 and M<34.15 1.5395 1.2533 1.1958 1.0863 15 14 14 13
0704 Fracture of lower extremity M<28.15 1.9955 1.6245 1.5500 1.4081 18 18 17 16
0801 Replacement of lower extremity joint M>49.55 0.7944 0.6410 0.5920 0.5443 8 8 7 7
0802 Replacement of lower extremity joint M>37.05 and M<49.55 1.0351 0.8353 0.7714 0.7093 11 10 9 9
0803 Replacement of lower extremity joint M>28.65 and M<37.05 and A>83.5 1.3845 1.1173 1.0318 0.9488 13 13 12 12
0804 Replacement of lower extremity joint M>28.65 and M<37.05 and A<83.5 1.2461 1.0055 0.9286 0.8539 12 12 11 10
0805 Replacement of lower extremity joint M>22.05 and M<28.65 1.4829 1.1966 1.1051 1.0162 15 13 12 12
0806 Replacement of lower extremity joint M<22.05 1.7995 1.4521 1.3410 1.2331 16 16 15 14
0901 Other orthopedic M>44.75 0.9866 0.7948 0.7350 0.6689 11 10 9 8
0902 Other orthopedic M>34.35 and M<44.75 1.2620 1.0166 0.9402 0.8556 12 12 11 10
0903 Other orthopedic M>24.15 and M<34.35 1.5866 1.2780 1.1819 1.0757 15 15 13 13
0904 Other orthopedic M<24.15 2.0099 1.6190 1.4973 1.3627 18 18 16 16
1001 Amputation, lower extremity M>47.65 1.0742 0.9500 0.8207 0.7414 11 11 10 9
1002 Amputation, lower extremity M>36.25 and M<47.65 1.3925 1.2314 1.0639 0.9611 14 15 12 12
1003 Amputation, lower extremity M<36.25 1.9643 1.7371 1.5008 1.3558 18 19 17 16
1101 Amputation, non-lower extremity M>36.35 1.3216 1.1917 0.9756 0.8848 12 12 10 11
1102 Amputation, non-lower extremity M<36.35 1.8958 1.7094 1.3994 1.2692 17 16 16 14
1201 Osteoarthritis M>37.65 1.0418 1.0235 0.9300 0.8239 10 11 11 10
1202 Osteoarthritis M>30.75 and M<37.65 1.2108 1.1895 1.0808 0.9576 12 13 12 11
1203 Osteoarthritis M<30.75 1.5410 1.5140 1.3756 1.2187 14 17 15 14
1301 Rheumatoid, other arthritis M>36.35 1.1826 0.9291 0.8691 0.8014 13 10 10 10
1302 Rheumatoid, other arthritis M>26.15 and M<36.35 1.6264 1.2778 1.1954 1.1021 14 15 13 13
1303 Rheumatoid, other arthritis M<26.15 2.0043 1.5746 1.4731 1.3582 16 20 15 15
1401 Cardiac M>48.85 0.8643 0.7307 0.6621 0.6007 9 8 8 8
1402 Cardiac M>38.55 and M<48.85 1.1810 0.9985 0.9047 0.8208 11 11 10 10
1403 Cardiac M>31.15 and M<38.55 1.4079 1.1903 1.0785 0.9785 13 13 12 11
1404 Cardiac M<31.15 1.7799 1.5048 1.3635 1.2371 17 16 15 14
1501 Pulmonary M>49.25 1.0124 0.8580 0.7912 0.7466 10 9 9 8
1502 Pulmonary M>39.05 and M<49.25 1.2770 1.0823 0.9980 0.9418 11 11 11 10
1503 Pulmonary M>29.15 and M<39.05 1.5560 1.3187 1.2160 1.1475 15 14 12 12
1504 Pulmonary M<29.15 1.9351 1.6400 1.5123 1.4271 19 17 15 14
1601 Pain syndrome M>37.15 0.9845 0.8935 0.8304 0.7671 9 9 10 9
1602 Pain syndrome M>26.75 and M<37.15 1.2824 1.1639 1.0817 0.9993 12 13 12 12
1603 Pain syndrome M<26.75 1.6089 1.4602 1.3571 1.2537 13 17 15 14
1701 Major multiple trauma without brain or spinal cord injury M>39.25 1.1329 0.9223 0.8471 0.7644 16 10 10 10
1702 Major multiple trauma without brain or spinal cord injury M>31.05 and M<39.25 1.4266 1.1614 1.0667 0.9626 13 14 13 12
1703 Major multiple trauma without brain or spinal cord injury M>25.55 and M<31.05 1.7041 1.3873 1.2743 1.1498 16 16 14 14
1704 Major multiple trauma without brain or spinal cord injury M<25.55 2.1883 1.7815 1.6363 1.4766 22 19 18 17
1801 Major multiple trauma with brain or spinal cord injury M>40.85 1.3252 1.0733 0.9440 0.8290 15 13 12 10
1802 Major multiple trauma with brain or spinal cord injury M>23.05 and M<40.85 1.8549 1.5023 1.3214 1.1604 17 17 15 14
1803 Major multiple trauma with brain or spinal cord injury M<23.05 2.8949 2.3447 2.0623 1.8110 31 27 21 20
1901 Guillian Barre M>35.95 1.1743 1.0503 0.9267 0.9127 13 13 11 11
1902 Guillian Barre M>18.05 and M<35.95 2.1344 1.9090 1.6843 1.6589 19 22 19 19
1903 Guillian Barre M<18.05 3.4585 3.0934 2.7292 2.6881 50 31 32 28
2001 Miscellaneous M>49.15 0.9216 0.7549 0.6924 0.6268 9 9 8 8
2002 Miscellaneous M>38.75 and M<49.15 1.2117 0.9926 0.9103 0.8241 12 11 11 10
2003 Miscellaneous M>27.85 and M<38.75 1.5152 1.2412 1.1383 1.0305 14 14 13 12
2004 Miscellaneous M<27.85 1.9423 1.5911 1.4591 1.3210 19 17 16 15
2101 Burns M>0 1.6749 1.6749 1.4953 1.3672 24 18 16 17
5001 Short-stay cases, length of stay is 3 days or fewer 0.1586 2
5101 Expired, orthopedic, length of stay is 13 days or fewer 0.6791 7
5102 Expired, orthopedic, length of stay is 14 days or more 1.4216 17
5103 Expired, not orthopedic, length of stay is 15 days or fewer 0.8033 8
5104 Expired, not orthopedic, length of stay is 16 days or more 2.1360 21

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 proposed 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 propose 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 Proposed Changes to the CMG Relative Weights Back to Top
Percentage change Number of cases affected Percentage of cases affected
[FY 2016 Values compared with FY 2017 values]
Increased by 15% or more 0 0.0
Increased by between 5% and 15% 797 0.2
Changed by less than 5% 391,183 99.5
Decreased by between 5% and 15% 1,237 0.3
Decreased by 15% or more 14 0.0

As Table 2 shows, 99.5 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 proposed revisions for FY 2017. The largest estimated increase in the proposed CMG relative weight values that affects the largest number of IRF discharges would be a 0.1 percent increase in the CMG relative weight value for CMG 0704—Fracture of lower extremity, with a motor score less than 28.15-in the “no comorbidity” tier. In the FY 2015 claims data, 18,696 IRF discharges (4.8 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 13,587 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.

We invite public comment on our proposed updates to the CMG relative weights and average length of stay values for FY 2017.

IV. Facility-Level Adjustment Factors Back to Top

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 § 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.

V. Proposed FY 2017 IRF PPS Payment Update Back to Top

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 this proposed rule, we propose 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. Proposed FY 2017 Market Basket Update and Productivity Adjustment

For FY 2017, we are proposing 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 are proposing 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, the projected 2012-based IRF market basket increase factor for FY 2017 would be 2.7 percent. Therefore, consistent with our historical practice of estimating market basket increases based on the best available data, we are proposing a market basket increase factor of 2.7 percent for FY 2017. We are also proposing that if more recent data are 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.

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 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 MFP adjustment for FY 2017 (the 10-year moving average of MFP for the period ending FY 2017) is currently projected to be 0.5 percent. Thus, in accordance with section 1886(j)(3)(C) of the Act, we are proposing 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 are proposing to then reduce this percentage increase by the most up-to-date estimate of the MFP adjustment for FY 2017 of 0.5 percentage point (the 10-year moving average of MFP for the period ending FY 2017 based on IGI's first quarter 2016 forecast). Following application of the MFP, we are proposing 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 is 1.45 percent (2.7 percent market basket update, less 0.5 percentage point MFP adjustment, less 0.75 percentage point legislative adjustment). Furthermore, we propose that if more recent data are subsequently available (for example, a more recent estimate of the market basket update and MFP adjustment), we would use such data to determine the FY 2017 market basket update and MFP adjustment in the final rule.

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 is proposing 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.

C. Proposed 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 propose 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 proposed 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 is the sum of the FY 2017 relative importance of each labor-related cost category. The relative importance reflects the different rates of price change for these cost categories between the base year (FY 2012) and FY 2017.

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 67.1 percent, as shown in Table 3.

We propose that the portion of Capital that is influenced by the local labor market is estimated to be 46 percent. Since the relative importance for Capital-Related Costs is 8.4 percent of the 2012-based IRF market basket in FY 2017, we propose to take 46 percent of 8.4 percent to determine the labor-related share of Capital for FY 2017. The result would be 3.9 percent, which we propose to add to 67.1 percent for the operating cost amount to determine the total proposed labor-related share for FY 2017. Thus, the labor-related share that we are proposing to use for IRF PPS in FY 2017 would be 71.0 percent. By comparison, the FY 2016 labor-related share under the 2012-based IRF market basket was also 71.0 percent. Furthermore, we propose that if more recent data are subsequently available (for example, a more recent estimate of the labor-related share), we would use such data to determine the FY 2017 IRF labor-related share in the final rule.

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

D. Proposed 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 propose 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 propose 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 propose 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 on which to base the calculation for the FY 2017 IRF PPS wage index.

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. In FY 2016, all IRF providers received a blended wage index 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. We propose to maintain the policy established in FY 2016 IRF PPS final rule related to the blended one-year transition wage index (80 FR 47036, 47073 through 47074). This 1-year blended wage index became effective on October 1, 2015, and expires 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 FY 2015 rural IRFs that 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 proposed 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). We are not proposing any additional wage index transition adjustments for IRF providers due to the adoption of the new OMB delineations in FY 2016, but 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).

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). We are not proposing any changes to this policy in this proposed rule. For FY 2017, 19 IRFs that were designated as rural in FY 2015 and became designated as urban in FY 2016 will receive the proposed 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 proposed wage index applicable to FY 2017 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 proposed 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 (71.0 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 V.C of this proposed rule. We then multiply the labor-related portion by the applicable IRF wage index from the tables in the addendum to this proposed 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 propose to calculate a budget-neutral wage adjustment factor as established in the FY 2004 IRF PPS final rule (68 FR 45689), codified at § 412.624(e)(1), as described in the steps below. We propose to use the listed steps to ensure that the FY 2017 IRF standard payment conversion factor reflects the proposed 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 proposed FY 2017 standard payment conversion factor and the proposed 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 proposed FY 2017 budget-neutral wage adjustment factor of 0.9992.

Step 4. Apply the proposed 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 proposed FY 2017 standard payment conversion factor.

We discuss the calculation of the proposed standard payment conversion factor for FY 2017 in section V.E of this proposed rule.

We invite public comment on the proposed IRF wage adjustment for FY 2017.

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

To calculate the proposed standard payment conversion factor for FY 2017, as illustrated in Table 4, we begin by applying the proposed 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 proposed 1.45 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 $15,702. Then, we apply the proposed budget neutrality factor for the FY 2017 wage index and labor-related share of 0.9992, which results in a proposed standard payment amount of $15,690. We next apply the proposed budget neutrality factors for the revised CMG relative weights of 0.9990, which results in the proposed standard payment conversion factor of $15,674 for FY 2017.

Table 4—Calculations To Determine the Proposed FY 2017 Standard Payment Conversion Factor Back to Top
Explanation for adjustment Calculations
Standard Payment Conversion Factor for FY 2016 $15,478
Market Basket Increase Factor for FY 2017 (2.7 percent), reduced by 0.5 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 × 1.0145
Budget Neutrality Factor for the Wage Index and Labor-Related Share × 0.9992
Budget Neutrality Factor for the Revisions to the CMG Relative Weights × 0.9990
Proposed FY 2017 Standard Payment Conversion Factor = $15,674

We invite public comment on the proposed FY 2017 standard payment conversion factor.

After the application of the proposed CMG relative weights described in section III of this proposed rule to the proposed FY 2017 standard payment conversion factor ($15,674), the resulting proposed unadjusted IRF prospective payment rates for FY 2017 are shown in Table 5.

Table 5—Proposed FY 2017 Payment Rates Back to Top
CMG Payment rate tier 1 Payment rate tier 2 Payment rate tier 3 Payment rate no comorbidity
0101 $12,550.17 $11,219.45 $10,230.42 $9,761.77
0102 15,857.39 14,175.57 12,926.35 12,333.87
0103 18,501.59 16,539.20 15,081.52 14,390.30
0104 19,753.94 17,658.33 16,103.47 15,365.22
0105 22,824.48 20,404.41 18,606.61 17,753.94
0106 25,558.02 22,846.42 20,835.45 19,879.33
0107 28,476.52 25,456.14 23,214.76 22,150.50
0108 35,824.49 32,025.12 29,203.80 27,866.80
0109 32,255.52 28,833.89 26,294.70 25,089.37
0110 42,779.05 38,241.43 34,873.08 33,275.90
0201 12,266.47 10,034.49 9,051.74 8,440.45
0202 17,145.79 14,025.10 12,652.05 11,797.82
0203 19,101.90 15,625.41 14,095.63 13,142.65
0204 21,032.94 17,205.35 15,520.39 14,471.80
0205 25,443.60 20,813.50 18,775.88 17,507.86
0206 30,167.75 24,677.15 22,260.21 20,757.08
0207 39,677.16 32,457.72 29,279.03 27,300.97
0301 17,895.01 14,769.61 13,418.51 12,543.90
0302 22,043.91 18,194.38 16,529.80 15,451.43
0303 25,827.62 21,316.64 19,366.79 18,103.47
0304 33,429.51 27,592.51 25,067.43 23,431.06
0401 15,385.60 13,462.40 12,424.78 11,286.85
0402 22,084.67 19,326.04 17,835.44 16,202.21
0403 34,829.20 30,478.09 28,128.56 25,553.32
0404 60,976.56 53,357.43 49,244.57 44,735.16
0405 53,697.56 46,989.08 43,366.82 39,395.03
0501 13,487.48 10,647.35 10,123.84 9,114.43
0502 18,192.81 14,360.52 13,655.19 12,293.12
0503 22,786.86 17,987.48 17,103.47 15,398.14
0504 26,757.09 21,120.72 20,083.10 18,079.96
0505 30,714.77 24,244.54 23,053.32 20,755.51
0506 42,517.29 33,561.17 31,912.26 28,730.44
0601 16,255.51 12,857.38 11,882.46 10,877.76
0602 20,934.19 16,556.45 15,300.96 14,006.29
0603 25,783.73 20,391.87 18,844.85 17,252.37
0604 34,148.94 27,009.44 24,959.28 22,849.56
0701 15,694.38 12,775.88 12,189.67 11,073.68
0702 20,020.40 16,297.83 15,550.18 14,126.98
0703 24,130.12 19,644.22 18,742.97 17,026.67
0704 31,277.47 25,462.41 24,294.70 22,070.56
0801 12,451.43 10,047.03 9,279.01 8,531.36
0802 16,224.16 13,092.49 12,090.92 11,117.57
0803 21,700.65 17,512.56 16,172.43 14,871.49
0804 19,531.37 15,760.21 14,554.88 13,384.03
0805 23,242.97 18,755.51 17,321.34 15,927.92
0806 28,205.36 22,760.22 21,018.83 19,327.61
0901 15,463.97 12,457.70 11,520.39 10,484.34
0902 19,780.59 15,934.19 14,736.69 13,410.67
0903 24,868.37 20,031.37 18,525.10 16,860.52
0904 31,503.17 25,376.21 23,468.68 21,358.96
1001 16,837.01 14,890.30 12,863.65 11,620.70
1002 21,826.05 19,300.96 16,675.57 15,064.28
1003 30,788.44 27,227.31 23,523.54 21,250.81
1101 20,714.76 18,678.71 15,291.55 13,868.36
1102 29,714.77 26,793.14 21,934.20 19,893.44
1201 16,329.17 16,042.34 14,576.82 12,913.81
1202 18,978.08 18,644.22 16,940.46 15,009.42
1203 24,153.63 23,730.44 21,561.15 19,101.90
1301 18,536.07 14,562.71 13,622.27 12,561.14
1302 25,492.19 20,028.24 18,736.70 17,274.32
1303 31,415.40 24,680.28 23,089.37 21,288.43
1401 13,547.04 11,452.99 10,377.76 9,415.37
1402 18,510.99 15,650.49 14,180.27 12,865.22
1403 22,067.42 18,656.76 16,904.41 15,337.01
1404 27,898.15 23,586.24 21,371.50 19,390.31
1501 15,868.36 13,448.29 12,401.27 11,702.21
1502 20,015.70 16,963.97 15,642.65 14,761.77
1503 24,388.74 20,669.30 19,059.58 17,985.92
1504 30,330.76 25,705.36 23,703.79 22,368.37
1601 15,431.05 14,004.72 13,015.69 12,023.53
1602 20,100.34 18,242.97 16,954.57 15,663.03
1603 25,217.90 22,887.17 21,271.19 19,650.49
1701 17,757.07 14,456.13 13,277.45 11,981.21
1702 22,360.53 18,203.78 16,719.46 15,087.79
1703 26,710.06 21,744.54 19,973.38 18,021.97
1704 34,299.41 27,923.23 25,647.37 23,144.23
1801 20,771.18 16,822.90 14,796.26 12,993.75
1802 29,073.70 23,547.05 20,711.62 18,188.11
1803 45,374.66 36,750.83 32,324.49 28,385.61
1901 18,405.98 16,462.40 14,525.10 14,305.66
1902 33,454.59 29,921.67 26,399.72 26,001.60
1903 54,208.53 48,485.95 42,777.48 42,133.28
2001 14,445.16 11,832.30 10,852.68 9,824.46
2002 18,992.19 15,558.01 14,268.04 12,916.94
2003 23,749.24 19,454.57 17,841.71 16,152.06
2004 30,443.61 24,938.90 22,869.93 20,705.35
2101 26,252.38 26,252.38 23,437.33 21,429.49
5001 2,485.90
5101 10,644.21
5102 22,282.16
5103 12,590.92
5104 33,479.66

F. Example of the Methodology for Adjusting the Proposed Federal Prospective Payment Rates

Table 6 illustrates the methodology for adjusting the proposed federal prospective payments (as described in sections V.A. through V.F. of this proposed rule). The following examples are based on two hypothetical Medicare beneficiaries, both classified into CMG 0110 (without comorbidities). The proposed 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 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 (71.0 percent) described in section V.E. of this proposed rule by the proposed unadjusted federal prospective payment rate. To determine the non-labor portion of the proposed federal prospective payment rate, we subtract the labor portion of the proposed federal payment from the proposed unadjusted federal prospective payment.

To compute the proposed wage-adjusted federal prospective payment, we multiply the labor portion of the proposed federal payment by the appropriate proposed 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 proposed wage-adjusted federal payment by adding the wage-adjusted labor amount to the non-labor portion.

Adjusting the proposed 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.

TABLE 6—Example of Computing the IRF FY 2017 Federal Prospective Payment Back to Top
Steps Rural Facility A (Spencer Co., IN) Urban Facility B (Harrison Co., IN)
1. Unadjusted Federal Prospective Payment $33,275.90 $33,275.90
2. Labor Share × 0.710 × 0.710
3. Labor Portion of Federal Payment = $23,625.89 = $23,625.89
4. CBSA-Based Wage Index (shown in the Addendum, Tables A and B) × 0.8297 × 0.8756
5. Wage-Adjusted Amount = $19,602.40 = $20,686.83
6. Non-Labor Amount + $9,650.01 + $9,650.01
7. Wage-Adjusted Federal Payment = $29,252.41 = $30,336.84
8. Rural Adjustment × 1.149 × 1.000
9. Wage- and Rural-Adjusted Federal Payment = $33,611.02 = $30,336.84
10. LIP Adjustment × 1.0156 × 1.0454
11. FY 2017 Wage-, Rural- and LIP-Adjusted Federal Prospective Payment Rate = $34,135.35 = $31,714.13
12. FY 2017 Wage- and Rural-Adjusted Federal Prospective Payment $33,611.02 $30,336.84
13. Teaching Status Adjustment × 0 × 0.0784
14. Teaching Status Adjustment Amount = $0.00 = $2,378.41
15. FY 2017 Wage-, Rural-, and LIP-Adjusted Federal Prospective Payment Rate + $34,135.35 + $31,714.13
16. Total FY 2017 Adjusted Federal Prospective Payment = $34,135.35 = $34,092.54

Thus, the proposed adjusted payment for Facility A would be $34,135.35, and the proposed adjusted payment for Facility B would be $34,092.54.

VI. Proposed Update to Payments for High-Cost Outliers Under the IRF PPS Back to Top

A. Proposed 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 propose 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 propose 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 invite public comment 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.

B. Proposed 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 propose to apply a ceiling to IRFs' CCRs. Using the methodology described in that final rule, we propose 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 propose 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 propose 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 costs factor more heavily into the averages than the CCRs of IRFs with lower costs. For this proposed 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.

In accordance with past practice, we propose to set the national CCR ceiling at 3 standard deviations above the mean CCR. Using this method, the proposed national CCR ceiling would be 1.36 for FY 2017. This means that, if an individual IRF's CCR exceeds 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.

The proposed national average rural and urban CCRs and the proposed national CCR ceiling in this section will be updated in the final rule if more recent data becomes available to use in these analyses.

We invite public comment on the proposed update to the IRF CCR ceiling and the urban/rural averages for FY 2017.

VII. Proposed Revisions and Updates to the IRF Quality Reporting Program (QRP) Back to Top

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 would occur under the 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.

In this proposed rule, we propose 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 are proposing 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 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) Measures to reflect all-condition risk-adjusted potentially preventable hospital readmission rates: Potentially Preventable 30-Day Post-Discharge Readmission Measure for Inpatient Rehabilitation Facility Quality Reporting Program. Also, we are proposing an additional measure: (4) Potentially Preventable Within Stay Readmission Measure for Inpatient Rehabilitation Facilities.

In our selection and specification of measures, we employ 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 panel (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, PACQualityInitiative@cms.hhs.gov, 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-and-Cross-Setting-Measures.html.

Additionally, we sought public input from the MAP Post-Acute Care, Long-Term Care Workgroup during the annual in-person meeting held December 14 and 15, 2015. The MAP is composed of multi-stakeholder groups convened by the NQF, our current contractor under section 1890(a) of the Act, 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 are proposing 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 proposal in this proposed rule.

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 would allow 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 propose to 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 are not proposing 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 are not proposing 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 the Table 7.

Table 7—Quality Measures Previously Finalized for and Currently Used in the IRF Quality Reporting Program Back to Top
Measure title Final rule Data collection start date Annual payment determination: initial and subsequent APU years
* These measures were under review at NQF when they were finalized for use in the IRF QRP. These measures are now NQF-endorsed.
National Healthcare Safety Network (NHSN) Catheter-Associated Urinary Tract Infection (CAUTI) Outcome Measure (NQF #0138) Adopted an application of the measure in FY 2012 IRF PPS Final Rule (76 FR 47874 through 47886) October 1, 2012 FY 2014 and subsequent years.
Adopted the NQF-endorsed version and expanded measure (with standardized infection ratio) in CY 2013 OPPS/ASC Final Rule (77 FR 68504 through 68505) January 1, 2013 FY 2015 and subsequent years.
Percent of Residents or Patients with Pressure Ulcers That Are New or Worsened (Short Stay) (NQF #0678) Adopted application of measure in FY 2012 IRF PPS final rule (76 FR 47876 through 47878) October 1, 2012 FY 2014 and subsequent years.
Adopted a non-risk-adjusted application of the NQF-endorsed version in CY 2013 OPPS/ASC Final Rule (77 FR 68500 through 68507) January 1, 2013 FY 2015 and subsequent years.
Adopted the risk adjusted, NQF-endorsed version in FY 2014 IRF PPS Final Rule (78 FR 47911 through 47912) October 1, 2014 FY 2017 and subsequent years.
Adopted in the FY 2016 IRF PPS final rule (80 FR 47089 through 47096) to fulfill IMPACT Act requirements October 1, 2015 FY 2018 and subsequent years.
Percent of Residents or Patients Who Were Assessed and Appropriately Given the Seasonal Influenza Vaccine (Short Stay) (NQF #0680) Adopted in FY 2014 IRF PPS final rule (78 FR 47906 through 47911) October 1, 2014 FY 2017 and subsequent years.
Influenza Vaccination Coverage among Healthcare Personnel (NQF #0431) Adopted in FY 2014 IRF PPS final rule (78 FR 47905 through 47906) October 1, 2014 FY 2016 and subsequent years.
All-Cause Unplanned Readmission Measure for 30 Days Post Discharge from Inpatient Rehabilitation Facilities (NQF #2502) Adopted in FY 2014 IRF PPS final rule (78 FR 47906 through 47910) N/A FY 2017 and subsequent years.
Adopted the NQF-endorsed version in FY 2016 IRF PPS final rule (80 FR 47087 through 47089) N/A FY 2018 and subsequent years.
National Healthcare Safety Network (NHSN) Facility-Wide Inpatient Hospital-Onset Methicillin-Resistant Staphylococcus aureus (MRSA) Bacteremia Outcome Measure (NQF #1716) Adopted in the FY 2015 IRF PPS final rule (79 FR 45911 through 45913) January 1, 2015 FY 2017 and subsequent years.
National Healthcare Safety Network (NHSN) Facility-Wide Inpatient Hospital-Onset Clostridium difficile Infection (CDI) Outcome Measure (NQF #1717) Adopted in the FY 2015 IRF PPS final rule (79 FR 45913 through 45914) January 1, 2015 FY 2017 and subsequent years.
Application of Percent of Residents Experiencing One or More Falls with Major Injury (Long Stay) (NQF #0674) Adopted an application of the measure in FY 2016 IRF PPS Final Rule (80 FR 47096 through 47100) October 1, 2016 FY 2018 and subsequent years.
Application of Percent of Long-Term Care Hospital Patients with an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function (NQF #2631) Adopted an application of the measure in the FY 2016 IRF PPS final rule (80 FR 47100 through 47111) October 1, 2016 FY 2018 and subsequent years.
IRF Functional Outcome Measure: Change in Self-Care for Medical Rehabilitation Patients (NQF #2633)* Adopted in the FY 2016 IRF PPS final rule (80 FR 47111 through 47117) October 1, 2016 FY 2018 and subsequent years.
IRF Functional outcome Measure: Change in Mobility Score for Medical Rehabilitation (NQF #2634)* Adopted in the FY 2016 IRF PPS final rule (80 FR 47117 through 47118) October 1, 2016 FY 2018 and subsequent years.
IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients (NQF #2635) Adopted in the FY 2016 IRF PPS final rule (80 FR 47118 through 47119) October 1, 2016 FY 2018 and subsequent years.
IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients (NQF #2636) Adopted in the FY 2016 IRF PPS final rule (80 FR 47119 through 47120) October 1, 2016 FY 2018 and subsequent years.

F. IRF QRP Quality, Resource Use and Other Measures Proposed 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 VII.C. of this proposed rule, we are proposing four new measures. Three of these measures proposed 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 to be proposed 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 on 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 two 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, 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 are inviting public comment on how socioeconomic and demographic factors should be used in risk adjustment for the resource use measures.

1. Proposal To Address the IMPACT Act Domain of Resource Use and Other Measures: Total Estimated MSPB-PAC IRF QRP

We are proposing 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

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 are proposing this MSPB-PAC IRF measure under the Secretary's authority to specify non-NQF-endorsed measures under section 1899B(e)(2)(B). Given the current lack of resource use measures for PAC settings, our proposed MSPB-PAC IRF QRP measure has the potential to provide valuable information to IRF providers on their relative Medicare spending in delivering services to approximately 338,000 Medicare beneficiaries. [5]

The proposed MSPB-PAC IRF 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 QPR 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 and has the potential to improve post-treatment care planning and coordination. While some stakeholders throughout the measure development process supported the measures and believe 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 recognize providers that are involved in the provision of high quality care at lower cost.

We have undertaken development of MSPB-PAC measures for each of the four PAC settings. We are proposing an LTCH-specific MSPB-PAC measure in the FY 2017 IPPS/LTCH proposed rule published elsewhere in this issue of the Federal Register and a SNF-specific MSBP-PAC measure in the FY 2017 SNF PPS proposed rule published elsewhere in this issue of the Federal Register. We intend to propose a HHA-specific MSBP-PAC measure through future notice-and-comment rulemaking. 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, developing setting-specific measures allows 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 are proposing to 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 that was finalized in the FY 2012 IPPS/LTCH PPS Final Rule (76 FR 51618 through 51627). It was endorsed by the NQF on December 6, 2013, and has been used in the Hospital Value-Based Purchasing (VBP) Program (NQF #2158) since FY 2015. [6] The hospital MSPB measure was originally established under the authority of section 1886(o)(2)(B)(ii) of the Act. 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 below, is the time period which Medicare FFS Part A and Part B services are counted towards the MSPB-PAC IRF QRP episode). However, there are differences between the MSPB-PAC measures, as proposed, 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]

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 will 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 have 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 7 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/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html. The measures were also presented to the NQF-convened MAP Post-Acute Care/Long-Term Care (PAC/LTC) Workgroup on December 15, 2015. As the MSPB-PAC measures were under development, there were three voting options for members: (1) Encourage continued development, (2) do not encourage further consideration, and (3) 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

Since the MAP's review and recommendation of continued development, we have continued to refine risk adjustment models and conduct measure testing for the IMPACT Act measures in compliance with the MAP's recommendations. The proposed IMPACT Act measures are both 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 originally open from January 13 to 27, 2016 and twice extended to January 29 and February 5. A total of 45 comments on the MSPB-PAC measures were received during this 3.5 week period. Also, the comments received 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/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html and contains the public comments (summarized and verbatim), along with our responses including statistical analyses. If finalized, the MSPB-PAC IRF QRP measure, along with the other MSPB-PAC measures, as applicable, will be submitted for NQF endorsement.

To calculate the MSPB-PAC IRF QRP measure for each IRF provider, we first define 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 below. More detailed specifications for the proposed MSPB-PAC measures, including the MSPB-PAC IRF QRP measure in this proposed rule, are available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.

a. Episode Construction

An MSPB-PAC IRF QRP episode begins at the episode trigger, which is defined as the patient's admission to an IRF. This 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 will not be required to report any additional data to CMS for calculation of this measure. Thus, there will 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 have been determined by clinicians 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 a HHA within 30 days. The HHA claim would 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 provider of the second MSPB-PAC HHA 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 is 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 below, 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 proposed 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 propose to use the same payment standardization methodology as that 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. [16]

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 for MSPB-PAC IRF QRP episodes, we create 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 proposed MSPB-PAC IRF QRP model, 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 propose to include the Medicare spending for hospice services but risk adjust for them, such that MSPB-PAC IRF QRP episodes with hospice are compared to a benchmark reflecting other MSPB-PAC IRF QRP episodes with hospice. We believe that this provides 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 are proposing 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 believe 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 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 are seeking comment on whether the use of CMGs would still 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 routinely monitor the impact of sociodemographic status on providers' results on 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 two 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 are not proposing to adjust the MSPB-PAC IRF QRP measure for socioeconomic and demographic factors at this time. As this MSPB-PAC IRF QRP measure will be submitted for NQF endorsement, we prefer to await the results of this trial and study before deciding whether to risk adjust for socioeconomic and demographic factors. We will monitor the results of the trial, studies, and recommendations. We are inviting 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:

Where:

  • Y ij = attributed standardized spending for episode i and provider j
  • Y ij = expected standardized spending for episode i and provider j, as predicted from risk adjustment
  • n j = number of episodes for provider j
  • n = total number of episodes nationally
  • i ∈ {I j} = 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

If this proposed measure is finalized, 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 propose a minimum of 20 episodes for reporting and inclusion in the IRF QRP. For the reliability calculation, as described in the measure specifications identified and for which a link has been provided above, we used two 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 invite public comment on our proposal to adopt the MSPB-PAC IRF QRP measure for the IRF QRP.

2. Proposal To Address the IMPACT Act Domain of Resource Use and Other Measures: Discharge to Community-Post Acute Care (PAC) Inpatient Rehabilitation Facility Quality Reporting Program

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 are proposing 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 proposed 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 proposed 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/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.

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

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 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]

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]

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]

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 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.

A TEP convened by our measure development contractor was strongly supportive of the importance of measuring discharge to community outcomes, and implementing the proposed measure, Discharge to Community-PAC IRF QRP in the IRF QRP. The panel provided input on the technical specifications of this proposed 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 proposed 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 proposed Discharge to Community-PAC IRF QRP measure in the IRF QRP. The MAP encouraged continued development of the proposed measure to meet the mandate of the IMPACT Act. The MAP supported the alignment of this proposed 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 proposed measure is consistent with the information submitted to the MAP and is scientifically acceptable for current specification in the IRF QRP. 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 are proposing 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 are proposing to use data from the Medicare FFS claims and Medicare eligibility files to calculate this proposed measure. We are proposing 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 proposed 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 believe 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 are proposing to adopt the measure, Discharge to Community-PAC IRF QRP, for the IRF QRP for FY 2018 payment determination and subsequent years. This proposed measure is calculated using 2 years of data. We are proposing a minimum of 25 eligible stays in a given IRF for public reporting of the proposed 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 CMS for calculation of this measure. The proposed measure denominator is the risk-adjusted expected number of discharges to community. The proposed 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 this proposed measure, including information about the measure calculation, risk adjustment, and denominator exclusions, 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-Quality-Reporting-Program-Measures-Information-.html.

If this proposed measure is finalized, 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 plan to submit this proposed measure to the NQF for consideration for endorsement.

We are inviting public comment on our proposal to adopt the measure, Discharge to Community-PAC IRF QRP, for the IRF QRP.

3. Proposal 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 are proposing 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 proposed 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 proposed 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 two 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. 58 59 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.” [60] In addition, MedPAC calculated that annual Medicare spending on potentially preventable readmissions would be $12 billion for 30-day, $8 billion for 15-day, and $5 billion for 7-day readmissions. [61] 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. [62] 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. [63] Fewer studies have investigated potentially preventable readmission rates from the remaining post-acute care settings.

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). [64] 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.

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 3MTM algorithm for Potentially Preventable Readmissions. 65 66 67 Recent work led by Kramer et al. for MedPAC identified 13 conditions for which readmissions were deemed as potentially preventable among SNF and IRF populations. 68 69 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. 70 71 72

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 proposed 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 proposed 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 at http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html. In addition to the CMS Planned Readmission Algorithm, this proposed 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 proposed 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 proposed 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 proposed 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 are proposing a minimum of 25 eligible stays for public reporting of the proposed measure.

A TEP convened by our measure contractor provided recommendations on the technical specifications of this proposed 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/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.

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 are proposing 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 proposed measure to the NQF for consideration of endorsement. If this proposed measure is finalized, we intend to provide initial confidential feedback to providers, prior to public reporting of this proposed measure, based on 2 calendar years of data from discharges in CY 2015 and 2016. We intend to publicly report this proposed measure using data from CY 2016 and 2017.

We are inviting public comment on our proposal to adopt the measure, Potentially Preventable 30-Day Post-Discharge Readmission Measure for IRF QRP.

4. Potentially Preventable Within Stay Readmission Measure for Inpatient Rehabilitation Facilities

In addition to the measure proposed in section VII.F.3. of the proposed rule, Potentially Preventable 30-Day Post-Discharge Readmission Measure for IRF QRP, we are proposing 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 proposed 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 proposed PPR measures are intended to function in tandem, covering readmissions during the IRF stay and for 30 days following discharge from the IRF. Our proposal for two PPR measures for use in the IRF QRP will enable us to assess different aspects of care and care coordination. The proposed 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 proposed 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 VII.F.3. of this proposed 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 which can be found at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Reporting-Program-Measures-Information-.html.

Refer to section VII.F of this proposed rule for the relevant background and details that are also relevant for this measure. This proposed measure defines planned readmissions in the same manner as described in section VII.F.3 of this proposed 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 proposed measure, this proposed measure uses the same risk-adjustment and statistical approach as described in section VII.F.3 of this proposed 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 proposed 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/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 measure specifications, such as including standardized function data. A summary of our public comment period 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.

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 proposed measure to the NQF for consideration of endorsement. If this proposed measure is finalized, we intend to provide initial confidential feedback to providers, prior to public reporting of this proposed measure, based on 2 calendar years of claims data from discharges in 2015 and 2016. We propose a minimum of 25 eligible stays in a given IRF for public reporting of the proposed measure for that IRF. We intend to publicly report this proposed measure using claims data from calendar years 2016 and 2017.

We are inviting public comment on our proposal to adopt this measure, Potentially Preventable Within Stay Readmission Measure for IRFs.

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

In addition to the measures we are retaining as described in section VII.E. of this proposed rule under our policy described in section VII.C. of this proposed rule and the new quality measures proposed in section VII.F of this proposed rule for the FY 2018 payment determinations and subsequent years, we are proposing one new quality measure to meet the requirements of the IMPACT Act for the FY 2020 payment determination and subsequent years. The proposed 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 IRF QRP

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 are proposing 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 proposed measure assesses whether PAC providers were responsive to potential or actual clinically significant medication issue(s) when such issues were identified. Specifically, the proposed 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 proposed 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 proposed 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 proposed 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. [73] This measure is applied uniformly across the PAC settings.

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). [74] 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. [75] 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. [76] 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. [77] There is universal agreement that medication reconciliation directly addresses patient safety issues that can result from medication miscommunication and unavailable or incorrect information. 78 79 80

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 81 82 83 including subsequent emergency room visits and re-hospitalizations. [84] Annual health care costs in the United States are estimated at $3.5 billion, resulting in 7,000 deaths annually. 85 86

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. 87 88 89 90 91 92 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. [93]

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. [94] An estimated 50 percent of patients experienced a clinically important medication error after hospital discharge in an analysis of two tertiary care academic hospitals. [95]

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. 96 97 Hospital discharge has been identified as a particularly high risk time point, with evidence that medication reconciliation identifies high levels of discrepancy. 98 99 100 101 102 103 Also, there is evidence that medication reconciliation discrepancies occur throughout the patient stay. 104 105 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, [106] and medication reconciliation and patient knowledge (medication literacy) can be inadequate post-discharge. [107] The proposed quality measure, Drug Regimen Review Conducted with Follow-Up for Identified Issues—PAC IRF QRP, provides an important component of care coordination for PAC settings and would 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. [108]

A TEP convened by our measure development contractor provided input on the technical specifications of this proposed 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 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 proposed measure. The public comment summary report for the proposed 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 proposed measure, Drug Regimen Review Conducted with Follow-Up for Identified Issues—PAC IRF QRP. The MAP encouraged continued development of the proposed 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 proposed measure in compliance with the MAP's recommendations. The proposed measure is both consistent with the information submitted to the MAP and support its scientific acceptability for use in quality reporting programs. Therefore, we are proposing 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 proposed 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 have 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 proposed 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 proposed 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 proposed 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 proposed 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 proposed quality measure, Drug Regimen Review Conducted with Follow-Up for Identified Issues—PAC IRF QRP, would 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 are proposing 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 proposed quality measure would be 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 would be obtained at admission and discharge. For more information about the data submission required for this proposed measure, we refer readers to section VII.I.c of this proposed rule.

The standardized items used to calculate this proposed quality measure do not duplicate existing items currently used for data collection within the IRF-PAI. The proposed measure denominator is the number of patient stays with a discharge assessment during the reporting period. The proposed 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 proposed 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-Quality-Reporting-Program-Measures-Information-.html.

Data for the proposed quality measure, Drug Regimen Review Conducted with Follow-Up for Identified Issues—PAC IRF QRP, would be collected using the IRF-PAI with submission through the Quality Improvement Evaluation System (QIES) Assessment Submission and Processing (ASAP) system.

We invite 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.

H. IRF QRP Quality Measures and Measure Concepts Under Consideration for Future Years

We invite 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 are considering 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 through 72727). 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.

Table 8—IRF QRP Quality Measures Under Consideration for Future Years Back to Top
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. Proposed 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 9 through 17 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 17 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 would 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 9 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 9 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 span two consecutive years from July 1 through June 30th and we therefore separately illustrate those collection/submission quarterly reporting periods and review and correction periods and submission deadlines for FY 2019 and subsequent years in Table 15. We also separately distinguish the reporting periods and data submission timeframes for the finalized measure Influenza Vaccination Coverage among Healthcare Personnel which spans two consecutive years in Table 16.

Table 9—Annual QRP CY IRF-PAI & CDC/NHSN Data Collection/Submission Reporting Periods and Data Submission/Correction Deadlines ** Payment Determinations ^ Back to Top
* We refer readers to Table 16 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.
^ We refer readers to Table 15 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.
Proposed CY data collection quarter Data collection/submission quarterly reporting period QRP quarterly review and correction periods data submission deadlines for payment determination **
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.*
Table 10—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 Back to Top
Submission method Data collection/submission quarterly reporting period(s) Quarterly review and correction periods data submission deadlines for payment determination * * * APU determination affected
* We refer readers to the Table 9 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.
Finalized Measure:      
• NQF #0678 Percent of Residents or Patients with Pressure Ulcers That Are New or Worsened (Short Stay) (80 FR 47122)      
IRF-PAI/QIES ASAP System CY 15 Q4— 10/1/15-12/31/15 1/1/2016-5/15/16 deadline FY 2018.
CY 16 Q1—1/1/16-3/31/16 4/1/2016-8/15/16 deadline  
CY 16 Q2 —4/1/16-6/30/16 7/1/16-11/15/16 deadline  
CY 16 Q3 —7/1/16-9/30/16 10/1/16-2/15/17 deadline  
CY 16 Q4 —10/01/16-12/31/16 1/1/17-5/15/17 deadline  
Table 11—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 Back to Top
Submission method Data collection/submission quarterly reporting period(s) Quarterly review and correction periods data submission deadlines for payment determination * APU determination affected
* We note that the submission of IRF-PAI data must also adhere to the IRF PPS deadlines.
Finalized Measure:      
• NQF #0680 Percent of Residents or Patients Who Were Assessed and Appropriately Given the Seasonal Influenza Vaccine (80 FR 47122)      
IRF-PAI/QIES ASAP System CY 15 Q4 —10/1/15-12/31/15 1/1/2016-5/15/16 deadline FY 2018.
CY 16 Q1 —1/1/16-3/31/16 4/1/2016-8/15/16 deadline  
CY 16 Q2 —4/1/16-6/30/16 7/1/16-11/15/16 deadline  
Table 12—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 Back to Top
Submission method Data collection/submission quarterly reporting period(s) Quarterly review and correction periods data submission deadlines for payment determination * * * APU determination affected
* We refer readers to the Table 9 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.
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)      
IRF-PAI/QIES ASAP System CY 16 Q4 —10/1/16-12/31/16 1/1/2017-5/15/17 FY 2018.
Table 13—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 * Back to Top
Submission method Data collection/submission quarterly reporting period(s) Quarterly review and correction periods data submission deadlines for payment determination APU determination affected
* We refer readers to the Table 9 for an illustration of the data collection/submission quarterly reporting periods and correction and submission deadlines.
** As is illustrated in Table 9: 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.
Finalized Measure:      
• 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)      
CDC/NHSN CY 16 Q1—1/1/16-3/31/16 and Q1 of subsequent Calendar Years 4/1/2016-8/15/16 ** and 4/1-8/15 of subsequent years FY 2018 and subsequent years.**
CY 16 Q2—4/1/16-6/30/16 and Q2 of subsequent Calendar Years 7/1/16-11/15/16 **nand 7/1-11/15 of subsequent years  
CY 16 Q3—7/1/16-9/30/16 and Q3 of subsequent Calendar Years 10/1/16-2/15/17 ** and 10/1-2/15 of subsequent years  
CY 16 Q4—10/1/16-12/31/16 and Q4 of subsequent Calendar Years 1/1/17-5/15/17 ** and 1/1-5/15 of subsequent years  
Table 14—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 Back to Top
Submission method Data collection/submission quarterly reporting period(s) Quarterly review and correction periods data submission deadlines for payment determination * * * APU determination affected
* We refer readers to the Table 9 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 9: 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.
Finalized Measure:      
• 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)      
IRF-PAI/QIES ASAP System CY 17 Q1—1/1/17-3/31/17 and Q1 of subsequent Calendar Years 4/1/2017-8/15/17 *** and 4/1-8/15 of subsequent years FY 2019 and subsequent years.***
CY 17 Q2—4/1/17-6/30/17 and Q2 of subsequent Calendar Years 7/1/17-11/15/17 *** and 7/1-11/15 of subsequent years  
CY 17 Q3—7/1/17-9/30/17 and Q3 of subsequent Calendar Years 10/1/17-2/15/18 *** and 10/1-1/15 of subsequent years  
CY 17 Q4—10/1/17-12/31/17 and Q4 of subsequent Calendar Years 1/1/18-5/15/18 *** and 1/1-5/15 of subsequent years  

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 for a more detailed discussion of these timelines and deadlines.

We would like to clarify that this measure includes all patients in the IRF one or more days during the influenza vaccination season (IVS) (October 1 of 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 15 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 15 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 15—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 * Back to Top
Submission method Data collection/submission quarterly reporting period(s) Quarterly review and correction periods data submission deadlines for payment determination ** APU determination affected
* We note that the submission of IRF-PAI data must also adhere to the IRF PPS deadlines.
** As is illustrated in Table 9: 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.
Finalized Measure:      
• NQF #0680 Percent of Residents or Patients Who Were Assessed and Appropriately Given the Seasonal Influenza Vaccine (80 FR 47122)      
IRF-PAI/QIES ASAP System CY 16 Q3—7/1/16-9/30/16 and Q3 of subsequent Calendar Years 10/1/16-2/15/17 ** and 10/1-2/15 of subsequent years FY 2019 and subsequent years.**
CY 16 Q4—10/1/16-12/31/16 and Q4 of subsequent Calendar Years 1/1/17-5/15/17 ** and 1/1-5/15 of subsequent years  
CY 17 Q1—1/1/17-3/31/17 and Q1 of subsequent Calendar Years 4/1/17-8/15/17 ** and 4/1-8/15 of subsequent years  
CY 17 Q2—4/1/17-6/30/17 and Q2 of subsequent Calendar Years 7/1/17-11/15/17 ** and 7/1-11/15 of subsequent years  

We finalized in the FY 2014 IRF PPS final rule (78 FR 47905 through 47906) that for FY 2018 and subsequent years IRFs would submit data on the quality measure Influenza Vaccination Coverage among Healthcare Personnel (NQF #0431) beginning with data submission starting October 1, 2015. 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 vaccine 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 16—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 Back to Top
+ 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.
Influenza vaccination coverage among healthcare personnel data submission quarters+ Data submission period Review and correction periods data submission (CDC/NHSN) deadlines for payment determination++
CY QTR 4 through Subsequent CY QTR 1 10/1/15-3/31/16 and 10/1-3/31 of subsequent years 4/1/16-5/15/16 and 4/1-5/15 of subsequent years Deadline: May 15, 2016 and May 15 of subsequent years.
TABLE 17—Finalized IRF QRP Claims-Based Measure Affecting FY 2018 and Subsequent Years Back to Top
Quality measure Data submission method Performance period
NQF #2502 All-Cause Unplanned Readmission Measure for 30 Days Post-Discharge from Inpatient Rehabilitation Facilities (80 FR 47087 through 47089) Medicare FFS Claims CY 2013 and 2014 for public reporting in 2016. CY 2014 and 2015 for public reporting in 2017.

b. Proposed Timeline and Data Submission Mechanisms for the FY 2018 Payment Determination and Subsequent Years for the Proposed 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 have proposed in this proposed 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 VII.F of this proposed 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 invite public comments on this proposal.

c. Proposed Timeline and Data Submission Mechanisms for the IRF QRP Quality Measure for the FY 2020 Payment Determination and Subsequent Years

As discussed in section VII.F of this proposed rule, we propose that the data for the proposed 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 would be added to the IRF-PAI with submission through the QIES-ASAP system. Data collection would 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 propose to collect 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 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 proposed IRF QRP Quality Measure for the FY 2020 Payment Determination. We invite public comments on this proposal.

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

Following the close of the reporting quarter, October 1, 2018, through December 31, 2018, for the FY 2020 payment determination, IRFs would 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 would be May 15, 2019 for these measures. We further propose that for the FY 2021 payment determination and subsequent years, we will collect data using the calendar year reporting cycle as described in section VII.I.c of this proposed rule, and illustrated in Table 19. We invite public comments on this proposal.

TABLE 19—Proposed Data Collection Period and Data Correction Deadlines* Affecting the FY 2021 Payment Determination and Subsequent Years Back to Top
Quality measure Submission method Proposed CY data collection quarter Proposed data collection period Proposed quarterly review and data correction periods * deadlines for payment determination
* We note that the submission of IRF-PAI data must also adhere to the IRF PPS deadlines
Drug Regimen Review Conducted with Follow-Up for Identified Issues PAC IRF QRP IRF-PAI/QIES ASAP Quarter 1 January 1- March 31 April 1- August 15.
Quarter 2 April 1-June 30 July 1-November 15.
Quarter 3 July 1- September 30 October 1- February 15.
Quarter 4 October 1- December 31 January 1- May 15.

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 propose to codify the IRF QRP Data Completion Thresholds at § 412.634. We invite public comments on this proposal.

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 are not proposing a data validation policy at this time, 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 § 412.634 for requirements pertaining to submission exception and extension for the FY 2017 payment determination and subsequent years. At this time, we are proposing to revise § 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 are proposing 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 is also proposing to extend the deadline to 90 days in section VIII.A.15.a. of the FY 2017 IPPS/LTCH PPS proposed rule published elsewhere in this issue of the Federal Register. We believe that this increased time will assist providers experiencing 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 are not proposing any additional changes to the exception and extension policies for the IRF QRP at this time.

We invite public comments on the proposal to revise § 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 § 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 are not proposing 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 US Mail, and we may elect to utilize the MACs to administer such notifications.

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 the following section. 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 would 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 would 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 would be displayed based on 2 consecutive years of data. For IRFs with fewer than 25 eligible cases, we propose 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 are proposing 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 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) would be displayed based on 4 rolling quarters of data and would initially use MRSA bacteremia and CDI events that occurred from January 1, 2015 through December 31, 2015 (CY 2015), for calculations. We are proposing that the display of these ratios would be updated quarterly.

Rates for the Influenza Vaccination Coverage Among Healthcare Personnel (NQF #0431) would 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) would be displayed for patients in the IRF during the influenza vaccination season, from October 1, 2015, through March 31, 2016. We are proposing that the display of these rates would 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 propose 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 are inviting public comment on our proposal to begin publicly reporting in CY 2017 pending the availability of data on Facility-wide Inpatient Hospital-onset Methicillin-resistant Staphylococcus aureus (MRSA) Bacteremia Outcome Measure (NQF #1716); Facility-wide Inpatient Hospital-onset Clostridium difficile Infection (CDI) Outcome Measure (NQF #1716); 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 propose 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 would 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 invite 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 invite 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.

Additionally, we are requesting 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.

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 9 in section VII.I.a of this proposed 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 would 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.

In this proposed rule, we are restating and proposing additional details surrounding procedures that would 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 propose a process by which we would provide each IRF with a confidential feedback report that would 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 would be able to request correction of any errors in the assessment-based measure rate calculations.

We propose that these confidential feedback reports would be available to each IRF using the CASPER system. We refer to these reports as the IRF Quality Measure (QM) Reports. We propose to provide monthly updates to the data contained in these reports as data become available. We propose to provide the reports so that providers would 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 would make other reports available in the CASPER system, such as IRF-PAI assessment data submission reports and provider validation reports, which would 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 would 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 10 in section VII.I.c of this proposed rule, IRFs would 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 would 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 would 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 would like 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 propose 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 would not be permitted during this time; however, IRFs may ask for a correction to their measure calculations during the 30-day preview period. We are proposing that if it determines 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 would 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 invite 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., 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 propose 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 propose 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 would be for feedback purposes only and could not be corrected. This information would 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 would have 30 days from the date the preview report is made available in which to review this information. The 30-day preview period is the only time when IRFs would be able to see claims-based measures before they are publicly displayed. IRFs would not be able to make corrections to underlying claims data during this preview period, nor would 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 propose 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 would 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 propose 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 would 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 would 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 would consider IRF claims data to be complete for purposes of calculating the claims-based measures.

We propose 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 would 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 proposed procedure, during the 30-day preview period, IRFs would 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 would 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 proposed at least 90-day “run-out” period when we would 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 would not be able to deliver the calculations to IRFs sooner than 18 to 24 months after the last discharge. We believe this would create an unacceptably long delay both for IRFs and for us to deliver timely calculations to IRFs for quality improvement.

We invite public comment on these proposals.

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 would be confidential feedback reports that would enable IRFs to review their performance on the measures required under the IRF QRP. We propose that these confidential feedback reports would be available to each IRF using the CASPER system. Data contained within these CASPER reports would 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 propose 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 seek public comment on this proposal to satisfy the requirement to provide confidential feedback reports to IRFs.

P. Proposed 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 will apply a 2-percentage point reduction to the applicable FY 2017 market basket increase factor (1.45 percent) 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. Table 13 shows the calculation of the proposed 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).

Table 20—Calculations To Determine the Proposed Adjusted FY 2017 Standard Payment Conversion Factor for IRFs That Failed To Meet the Quality Reporting Requirement Back to Top
Explanation for adjustment Calculations
Standard Payment Conversion Factor for FY 2016 $15,478
Market Basket Increase Factor for FY 2017 (2.7 percent), reduced by 0.5 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 × 0.9945
Budget Neutrality Factor for the Wage Index and Labor-Related Share × 0.9992
Budget Neutrality Factor for the Revisions to the CMG Relative Weights × 0.9990
Proposed Adjusted FY 2017 Standard Payment Conversion Factor = $15,365

We invite 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.

VIII. Collection of Information Requirements Back to Top

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 proposed 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 2015 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 proposed rule, we are proposing 5 measures. For the FY 2018 payment determinations and subsequent years, we are proposing four new measures: (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 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 are proposing one measure: Drug Regimen Review Conducted with Follow-Up for Identified Issues—PAC IRF QRP. Additionally we propose 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 proposed 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 are proposing 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 would 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, section VII.M of this proposed rule proposes to 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 VII.N of this proposed rule, this rule proposes to 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.

If you comment on these information collection and recordkeeping requirements, please submit your comments electronically as specified in the ADDRESSES section of this proposed rule.

IX. Response to Public Comments Back to Top

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

X. Regulatory Impact Analysis Back to Top

A. Statement of Need

This proposed 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 proposed 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 proposed rule also adopts policy changes under the statutory discretion afforded to the Secretary under section 1886(j)(7) of the Act. Specifically, we propose to 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 proposed 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 proposed rule by comparing the estimated payments in FY 2017 with those in FY 2016. This analysis results in an estimated $125 million increase for FY 2017 IRF PPS payments. As a result, this proposed 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 21, we estimate that the net revenue impact of this proposed rule on all IRFs is to increase estimated payments by approximately 1.6 percent. The rates and policies set forth in this proposed 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 proposed 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 1,131 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 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 proposed 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 proposed 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 proposed rule proposes updates to the IRF PPS rates contained in the FY 2016 IRF PPS final rule (80 FR 47036). Specifically, this proposed rule would update the CMG relative weights and average length of stay values, the wage index, and the outlier threshold for high-cost cases. This proposed rule would apply 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 proposed rule contains proposed revisions to the IRF quality reporting requirements that are expected to result in some additional financial effects on IRFs. In addition, section VII of this proposed 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 proposed rule will be a net estimated increase of $125 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 X.C.7. of this proposed rule). The impact analysis in Table 21 of this proposed 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 proposing standard annual revisions described in this proposed 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 $125 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 $110 million. Furthermore, there is an additional estimated $15 million increase in aggregate payments to IRFs due to the proposed update to the outlier threshold amount. Outlier payments are estimated to increase from approximately 2.8 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 $125 million from FY 2016 to FY 2017.

The effects of the proposed updates that impact IRF PPS payment rates are shown in Table 21. The following proposed updates that affect the IRF PPS payment rates are discussed separately below:

  • The effects of the proposed update to the outlier threshold amount, from approximately 2.8 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 proposed 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 proposed budget-neutral labor-related share and wage index adjustment, as required under section 1886(j)(6) of the Act.
  • The effects of the proposed 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 proposed FY 2017 payment changes relative to the estimated FY 2016 payments.

2. Description of Table 21

Table 21 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 21 shows the overall impact on the 1,131 IRFs included in the analysis.

The next 12 rows of Table 21 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 980 IRFs located in urban areas included in our analysis. Among these, there are 729 IRF units of hospitals located in urban areas and 251 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 408 for-profit IRFs. Among these, there are 355 IRFs in urban areas and 53 IRFs in rural areas. There are 652 non-profit IRFs. Among these, there are 562 urban IRFs and 90 rural IRFs. There are 71 government-owned IRFs. Among these, there are 63 urban IRFs and 8 rural IRFs.

The remaining four parts of Table 21 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 proposed rule to the facility categories listed are shown in the columns of Table 21. 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 proposed adjustment to the outlier threshold amount.
  • Column (5) shows the estimated effect of the proposed update to the IRF labor-related share and wage index, in a budget-neutral manner.
  • Column (6) shows the estimated effect of the proposed 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 proposed policies reflected in this proposed rule for FY 2017 to our estimates of payments per discharge in FY 2016.

The average estimated increase for all IRFs is approximately 1.6 percent. This estimated net increase includes the effects of the proposed IRF market basket increase factor for FY 2017 of 2.7 percent, reduced by a productivity adjustment of 0.5 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 0.2 percent overall increase in estimated IRF outlier payments from the proposed update to the outlier threshold amount. Since we are making the proposed 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.

3. Impact of the Proposed Update to the Outlier Threshold Amount

The estimated effects of the proposed update to the outlier threshold adjustment are presented in column 4 of Table 21. In the FY 2016 IRF PPS final rule (80 FR 47036), we used FY 2014 IRF claims data (the best, most complete data available at that time) to set the outlier threshold amount for FY 2016 so that estimated outlier payments would equal 3 percent of total estimated payments for FY 2016.

For this proposed rule, we are using preliminary FY 2015 IRF claims data, and, based on that preliminary analysis, we estimate that IRF outlier payments as a percentage of total estimated IRF payments would be 2.8 percent in FY 2016. Thus, we propose to adjust 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 0.2 percent increase in payments because the estimated outlier portion of total payments is estimated to increase from approximately 2.8 percent to 3 percent.

The impact of this proposed outlier adjustment update (as shown in column 4 of Table 21) is to increase estimated overall payments to IRFs by about 0.2 percent. We estimate the largest increase in payments from the update to the outlier threshold amount to be 0.8 percent for rural IRFs in the Pacific region.

4. Impact of the Proposed CBSA Wage Index and Labor-Related Share

In column 5 of Table 21, we present the effects of the proposed budget-neutral update of the wage index and labor-related share. The proposed 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 proposed changes in the two have a combined effect on payments to providers. As discussed in section V.C. of this proposed rule, we are proposing to keep the labor-related share unchanged from FY 2016 to FY 2017 at 71.0 percent.

5. Impact of the Proposed Update to the CMG Relative Weights and Average Length of Stay Values.

In column 6 of Table 21, we present the effects of the proposed budget-neutral update of the CMG relative weights and average length of stay values. In the aggregate, we do not estimate that these proposed updates will affect overall estimated payments of IRFs. However, we do expect these updates to have small distributional effects.

6. Effects of Proposed 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 VII.P of this proposed 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 2015 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 VII.L of this proposed rule, we discuss our proposal to suspend the previously finalized data accuracy validation policy for IRFs. While we cannot estimate the increase 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 VII.F of this proposed rule, we are proposing 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 VII.G of this proposed rule, we are also proposing to adopt 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, we propose that 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 proposed 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.

D. Alternatives Considered

The following is a discussion of the alternatives considered for the IRF PPS updates contained in this proposed 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 increase factor for FY 2017. However, as noted previously in this proposed 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 propose to update the IRF federal prospective payments in this proposed rule by 1.45 percent (which equals the 2.7 percent estimated IRF market basket increase factor for FY 2017 reduced by a 0.5 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 propose 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 0.2 percent, unless we updated the outlier threshold amount. Consequently, we propose adjusting the outlier threshold amount in this proposed rule to reflect a 0.2 percent increase thereby setting the total outlier payments equal to 3 percent, instead of 2.8 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 22, we have prepared an accounting statement showing the classification of the expenditures associated with the provisions of this proposed rule. Table 22 provides our best estimate of the increase in Medicare payments under the IRF PPS as a result of the proposed updates presented in this proposed rule based on the data for 1,131 IRFs in our database. In addition, Table 22 presents the costs associated with the proposed new IRF quality reporting program for FY 2017.

Table 22—Accounting Statement: Classification of Estimated Expenditures Back to Top
Category Transfers
Change in Estimated Transfers from FY 2016 IRF PPS to FY 2017 IRF PPS:  
Annualized Monetized Transfers $125 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 Quality Reporting Program $5,231,398.17.

F. Conclusion

Overall, the estimated payments per discharge for IRFs in FY 2017 are projected to increase by 1.6 percent, compared with the estimated payments in FY 2016, as reflected in column 7 of Table 21.

IRF payments per discharge are estimated to increase by 1.7 percent in urban areas and 0.9 percent in rural areas, compared with estimated FY 2016 payments. Payments per discharge to rehabilitation units are estimated to increase 1.8 percent in urban areas and 1.1 percent in rural areas. Payments per discharge to freestanding rehabilitation hospitals are estimated to increase 1.5 percent in urban areas and decrease 0.1 percent in rural areas.

Overall, IRFs are estimated to experience a net increase in payments as a result of the proposed policies in this proposed rule. The largest payment increase is estimated to be a 2.4 percent increase for urban IRFs located in the Middle Atlantic region.

In accordance with the provisions of Executive Order 12866, this proposed rule was reviewed by the Office of Management and Budget.

List of Subjects in 42 CFR Part 412 Back to Top

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

begin regulatory text

PART 412—PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL SERVICES Back to Top

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.

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

§ 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 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.

end regulatory text

Dated: April 5, 2016.

Andrew M. Slavitt,

Acting Administrator, Centers for Medicare & Medicaid Services.

Dated: April 14, 2016.

Sylvia M. Burwell,

Secretary, Department of Health and Human Services.

[FR Doc. 2016-09397 Filed 4-21-16; 4:15 pm]

BILLING CODE 4120-01-P

Footnotes Back to Top

3.  MedPAC, “A Data Book: Health Care Spending and the Medicare Program,” (2015). 114

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4.  Institute of Medicine, “Variation in Health Care Spending: Target Decision Making, Not Geography,” (Washington, DC: National Academies 2013). 2.

5.  Figures for 2013. MedPAC, “Medicare Payment Policy,” Report to the Congress (2015). xvii-xviii.

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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&amp;cid=1228772053996.

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7.  QualityNet, “Measure Methodology Reports: Medicare Spending Per Beneficiary (MSPB) Measure,” (2015). http://www.qualitynet.org/dcs/ContentServer?pagename=QnetPublic%2FPage%2FQnetTier3&amp;cid=1228772053996.

8.  FY 2012 IPPS/LTCH PPS final rule (76 FR 51619).

9.  FY 2012 IPPS/LTCH PPS Final Rule (76 FR 51620).

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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&amp;ItemID=81693.

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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&amp;ItemID=81470.

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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&amp;ItemID=81637.

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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&amp;ItemID=81593.

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&amp;ItemID=81593.

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16.  QualityNet, “CMS Price (Payment) Standardization—Detailed Methods” (Revised May 2015) https://qualitynet.org/dcs/ContentServer?c=Page&amp;pagename=QnetPublic%2FPage%2FQnetTier4&amp;cid=1228772057350.

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17.  Further description of patient discharge status codes can be found, for example, at the following Web page: https://med.noridianmedicare.com/web/jea/topics/claim-submission/patient-status-codes.

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.

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.

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.

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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.

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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.

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

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27.  Ibid.

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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.

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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.

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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.

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49.  Ibid.

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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.

58.  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.

59.  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.

60.  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.

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61.  Ibid.

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62.  Ibid.

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63.  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.

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64.  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.

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65.  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/.

66.  National Quality Forum: Prevention Quality Indicators Overview. 2008.

67.  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.

68.  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.

69.  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.

70.  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.

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72.  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‐and community‐based services waiver programs. J. Am. Geriatr. Soc. 60(5):821-829, 2012. doi:10.1111/j.1532-5415.2012.03920.x.

73.  Institute of Medicine. Preventing Medication Errors. Washington DC: National Academies Press; 2006.

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74.  Ibid.

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75.  Leotsakos A., et al. Standardization in patient safety: The WHO High 5s project. Int J Qual Health Care. 2014:26(2):109-116.

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76.  The Joint Commission. 2016 Long Term Care: National Patient Safety Goals Medicare/Medicaid Certification-based Option. (NPSG.03.06.01).

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77.  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.

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78.  Leotsakos A., et al. Standardization in patient safety: The WHO High 5s project. Int J Qual Health Care. 2014:26(2):109-116.

79.  The Joint Commission. 2016 Long Term Care: National Patient Safety Goals Medicare/Medicaid Certification-based Option. (NPSG.03.06.01).

80.  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.

81.  Institute of Medicine. Preventing Medication Errors. Washington DC: National Academies Press; 2006.

82.  Jha A.K., Kuperman G.J., 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.

83.  Hohl C.M., Nosyk B., Kuramoto L., et al. Outcomes of emergency department patients presenting with adverse drug events. Ann Emerg Med. 2011;58:270-279.

84.  Kohn L.T., Corrigan J.M., Donaldson M.S. To Err Is Human: Building a Safer Health System Washington, DC: National Academies Press; 1999.

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85.  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.

86.  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.

87.  Institute of Medicine. To err is human: Building a safer health system. Washington, DC: National Academies Press; 2000.

88.  Lesar, T.S., Briceland, L., Stein, D.S. Factors related to errors in medication prescribing. JAMA. 1997:277(4): 312-317.

89.  Bond, C.A., Raehl, C.L., & Franke, T. Clinical pharmacy services, hospital pharmacy staffing, and medication errors in United States hospitals. Pharmacotherapy. 2002:22(2): 134-147.

90.  Bates, D.W., Cullen D.J., Laird, N., Petersen, L.A., Small, S.D., et al. Incidence of adverse drug events and potential adverse drug events. Implications for prevention. JAMA. 1995:274(1): 29-34.

91.  Barker, K.N., Flynn, E.A., Pepper, G.A., Bates, D.W., & Mikeal, R.L. Medication errors observed in 36 health care facilities. JAMA. 2002: 162(16):1897-1903.

92.  Bates, D.W., Boyle, D.L., Vander, Vliet M.B., Schneider, J., & Leape, L. Relationship between medication errors and adverse drug events. J Gen Intern Med. 1995:10(4): 199-205.

93.  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.

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94.  Wong, Jacqueline D., et al. “Medication reconciliation at hospital discharge: Evaluating discrepancies.” Annals of Pharmacotherapy 42.10 (2008): 1373-1379.

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95.  Kripalani, S., Roumie, C.L., Dalal, A.K., 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.

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96.  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.

97.  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.

98.  Coleman, E.A., Smith, J.D., Raha, D., Min, S.J. Post hospital medication discrepancies: Prevalence and contributing factors. Arch Intern Med. 2005 165(16):1842-1847.

99.  Wong, J.D., Bajcar, J.M., Wong, G.G., et al. Medication reconciliation at hospital discharge: Evaluating discrepancies. Ann Pharmacother. 2008 42(10):1373-1379.

100.  Hawes, E.M., Maxwell, W.D., White, S.F., Mangun, J., Lin, F.C. 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.

101.  Foust, J.B., Naylor, M.D., Bixby, M.B., Ratcliffe, S.J. Medication problems occurring at hospital discharge among older adults with heart failure. Research in Gerontological Nursing. 2012, 5(1): 25-33.

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103.  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.

104.  Bates, D.W., Cullen, D.J., Laird, N., Petersen, L.A., Small SD, et al. Incidence of adverse drug events and potential adverse drug events. Implications for prevention. JAMA. 1995:274(1): 29-34.

105.  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.

106.  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.

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107.  Kripalani, S., Roumie, C.L., Dalal, A.K., 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.

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108.  March 2015 Report to the Congress: Medicare Payment Policy. Medicare Payment Advisory Commission; 2015.

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Citation: 81 FR 24177
 

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