51676 Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 

DEPARTMENT OF HEALTH AND 

HUMAN SERVICES 

Centers for Medicare & Medicaid 

Services 

42 CFR Part 484 

[CMS–1672–F] 

RIN 0938–AT01 

Medicare and Medicaid Programs; CY 

2018 Home Health Prospective 

Payment System Rate Update and CY 

2019 Case-Mix Adjustment 

Methodology Refinements; Home 

Health Value-Based Purchasing Model; 

and Home Health Quality Reporting 

Requirements 

AGENCY: Centers for Medicare & 

Medicaid Services (CMS), HHS. 

ACTION: Final rule. 

SUMMARY: This final rule updates the 

home health prospective payment 

system (HH PPS) payment rates, 

including the national, standardized 60- 

day episode payment rates, the national 

per-visit rates, and the non-routine 

medical supply (NRS) conversion factor, 

effective for home health episodes of 

care ending on or after January 1, 2018. 

This rule also: Updates the HH PPS 

case-mix weights using the most 

current, complete data available at the 

time of rulemaking; implements the 

third year of a 3-year phase-in of a 

reduction to the national, standardized 

60-day episode payment to account for 

estimated case-mix growth unrelated to 

increases in patient acuity (that is, 

nominal case-mix growth) between 

calendar year (CY) 2012 and CY 2014; 

and discusses our efforts to monitor the 

potential impacts of the rebasing 

adjustments that were implemented in 

CY 2014 through CY 2017. In addition, 

this rule finalizes changes to the Home 

Health Value-Based Purchasing 

(HHVBP) Model and to the Home Health 

Quality Reporting Program (HH QRP). 

We are not finalizing the 

implementation of the Home Health 

Groupings Model (HHGM) in this final 

rule. 

DATES: These regulations are effective 

on January 1, 2018. 

FOR FURTHER INFORMATION CONTACT: 

For general information about the 

Home Health Prospective Payment 

System (HH PPS), please send your 

inquiry via email to: 

HomehealthPolicy@cms.hhs.gov. 

For information about the Home 

Health Value-Based Purchasing 

(HHVBP) Model, please send your 

inquiry via email to: HHVBPquestions@

cms.hhs.gov. 

Contact Joan Proctor, (410) 786–0949 

for information about the Home Health 

Quality Reporting Program (HH QRP). 

SUPPLEMENTARY INFORMATION: Wage 

index addenda will be available only 

through the internet on the CMS Web 

site at: https://www.cms.gov/Medicare/ 

Medicare-Fee-for-Service-Payment/ 

HomeHealthPPS/coding_billing.html. 

Table of Contents 

I. Executive Summary 

A. Purpose 

B. Summary of the Major Provisions 

C. Summary of Costs and Benefits 

II. Background 

A. Statutory Background 

B. Current System for Payment of Home 

Health Services 

C. Updates to the Home Health Prospective 

Payment System 

D. Report to Congress: Home Health Study 

on Access to Care for Vulnerable Patient 

Populations and Subsequent Research 

and Analyses 

III. Provisions of the Proposed Rule: Payment 

Under the Home Health Prospective 

Payment System (HH PPS) and 

Responses to Comments 

A. Monitoring for Potential Impacts— 

Affordable Care Act Rebasing 

Adjustments 

B. CY 2018 HH PPS Case-Mix Weights 

C. CY 2018 Home Health Payment Rate 

Update 

D. Payments for High-Cost Outliers Under 

the HH PPS 

E. Proposed Implementation of the Home 

Health Groupings Model (HHGM) for CY 

2019 

IV. Provisions of the Home Health ValueBased Purchasing (HHVBP) Model and 

Responses to Comments 

A. Background 

B. Quality Measures 

C. Quality Measures for Future 

Consideration 

V. Updates to the Home Health Care Quality 

Reporting Program (HH QRP) 

A. Background and Statutory Authority 

B. General Considerations Used for the 

Selection of Quality Measures for the HH 

QRP 

C. Accounting for Social Risk Factors in 

the HH QRP 

D. Removal From OASIS 

E. Collection of Standardized Patient 

Assessment Data Under the HH QRP 

F. HH QRP Quality Measures Beginning 

With the CY 2020 HH QRP 

G. HH QRP Quality Measures and Measure 

Concepts Under Consideration for Future 

Years 

H. Standardized Patient Assessment Data 

I. Form, Manner, and Timing of Data 

Submission Under the HH QRP 

J. Other Provisions for the CY 2019 HH 

QRP and Subsequent Years 

K. Policies Regarding Public Display of 

Quality Measure Data for the HH QRP 

L. Mechanism for Providing Confidential 

Feedback Reports to HHAs 

M. Home Health Care CAHPS® Survey 

(HHCAHPS) 

VI. Collection of Information Requirements 

A. Statutory Requirement for Solicitation 

of Comments 

B. Collection of Information Requirements 

for the HH QRP 

C. Submission of PRA-Related Comments 

VII. Regulatory Impact Analysis 

A. Statement of Need 

B. Overall Impact 

C. Detailed Economic Analysis 

D. Accounting Statement and Table 

E. Reducing Regulation and Controlling 

Regulatory Costs 

F. Conclusion 

VIII. Federalism Analysis 

Regulation Text 

Acronyms 

In addition, because of the many 

terms to which we refer by abbreviation 

in this final rule, we are listing these 

abbreviations and their corresponding 

terms in alphabetical order below: 

ACH LOS Acute Care Hospital Length of 

Stay 

ADL Activities of Daily Living 

AM–PAC Activity Measure for Post-Acute 

Care 

APR DRG All-Patient Refined DiagnosisRelated Group 

APU Annual Payment Update 

ASPE Assistant Secretary for Planning and 

Evaluation 

BBA Balanced Budget Act of 1997, Public 

Law 105–33 

BBRA Medicare, Medicaid, and SCHIP 

Balanced Budget Refinement Act of 1999, 

(Pub. L. 106–113) 

BIMS Brief Interview for Mental Status 

BLS Bureau of Labor Statistics 

CAD Coronary Artery Disease 

CAH Critical Access Hospital 

CAM Confusion Assessment Method 

CARE Continuity Assessment Record and 

Evaluation 

CASPER Certification and Survey Provider 

Enhanced Reports 

CBSA Core-Based Statistical Area 

CCN CMS Certification Number 

CHF Congestive Heart Failure 

CMI Case-Mix Index 

CMP Civil Money Penalty 

CMS Centers for Medicare & Medicaid 

Services 

CoPs Conditions of Participation 

COPD Chronic Obstructive Pulmonary 

Disease 

CVD Cardiovascular Disease 

CY Calendar Year 

DM Diabetes Mellitus 

DRA Deficit Reduction Act of 2005, Public 

Law 109–171, enacted February 8, 2006 

DRG Diagnosis-Related Group 

DTI Deep Tissue Injury 

EOC End of Care 

FDL Fixed Dollar Loss 

FI Fiscal Intermediaries 

FR Federal Register 

FY Fiscal Year 

HAVEN Home Assessment Validation and 

Entry System 

HCC Hierarchical Condition Categories 

HCIS Health Care Information System 

HH Home Health 

HHA Home Health Agency 


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HHCAHPS Home Health Care Consumer 

Assessment of Healthcare Providers and 

Systems Survey 

HH PPS Home Health Prospective Payment 

System 

HHGM Home Health Groupings Model 

HHQRP Home Health Quality Reporting 

Program 

HHRG Home Health Resource Group 

HHVBP Home Health Value-Based 

Purchasing 

HIPPS Health Insurance Prospective 

Payment System 

HVBP Hospital Value-Based Purchasing 

IADL Instrumental Activities of Daily 

Living 

ICD–9–CM International Classification of 

Diseases, Ninth Revision, Clinical 

Modification 

ICD–10–CM International Classification of 

Diseases, Tenth Revision, Clinical 

Modification 

IH Inpatient Hospitalization 

IMPACT Act Improving Medicare PostAcute Care Transformation Act of 2014 

(Pub. L. 113–185) 

IPPS [Acute Care Hospital] Inpatient 

Prospective Payment System 

IPR Interim Performance Report 

IRF Inpatient Rehabilitation Facility 

IRF–PAI IRF Patient Assessment Instrument 

IV Intravenous 

LCDS LTCH CARE Data Set 

LEF Linear Exchange Function 

LTCH Long-Term Care Hospital 

LUPA Low-Utilization Payment Adjustment 

MACRA Medicare Access and CHIP 

Reauthorization Act of 2015 

MAP Measure Applications Partnership 

MDS Minimum Data Set 

MFP Multifactor productivity 

MMA Medicare Prescription Drug, 

Improvement, and Modernization Act of 

2003, Public Law 108–173, enacted 

December 8, 2003 

MSA Metropolitan Statistical Area 

MSS Medical Social Services 

NQF National Quality Forum 

NQS National Quality Strategy 

NRS Non-Routine Supplies 

OASIS Outcome and Assessment 

Information Set 

OBRA Omnibus Budget Reconciliation Act 

of 1987, Public Law 100–2–3, enacted 

December 22, 1987 

OCESAA Omnibus Consolidated and 

Emergency Supplemental Appropriations 

Act, Public Law 105–277, enacted October 

21, 1998 

OES Occupational Employment Statistics 

OIG Office of Inspector General 

OLS Ordinary Least Squares 

OT Occupational Therapy 

OMB Office of Management and Budget 

PAC Post-Acute Care 

PAC–PRD Post-Acute Care Payment Reform 

Demonstration 

PAMA Protecting Access to Medicare Act of 

2014 

PEP Partial Episode Payment Adjustment 

PHQ–2 Patient Health Questionnaire-2 

PPOC Primary Point of Contact 

PPS Prospective Payment System 

PRA Paperwork Reduction Act 

PRRB Provider Reimbursement Review 

Board 

PT Physical Therapy 

PY Performance Year 

QAP Quality Assurance Plan 

QIES Quality Improvement Evaluation 

System 

QRP Quality Reporting Program 

RAP Request for Anticipated Payment 

RF Renal Failure 

RFA Regulatory Flexibility Act, Public Law 

96—354 

RHHIs Regional Home Health 

Intermediaries 

RIA Regulatory Impact Analysis 

ROC Resumption of Care 

SAF Standard Analytic File 

SLP Speech-Language Pathology 

SN Skilled Nursing 

SNF Skilled Nursing Facility 

SOC Start of Care 

SSI Surgical Site Infection 

TEP Technical Expert Panel 

TPS Total Performance Score 

UMRA Unfunded Mandates Reform Act of 

1995 

VAD Vascular Access Device 

VBP Value-Based Purchasing 

I. Executive Summary 

A. Purpose 

This final rule updates the payment 

rates for home health agencies (HHAs) 

for calendar year (CY) 2018, as required 

under section 1895(b) of the Social 

Security Act (the Act). This final rule 

also updates the case-mix weights under 

section 1895(b)(4)(A)(i) and (b)(4)(B) of 

the Act for CY 2018 and implements a 

0.97 percent reduction to the national, 

standardized 60-day episode payment 

amount to account for case-mix growth 

unrelated to increases in patient acuity 

(that is, nominal case-mix growth) 

between CY 2012 and CY 2014, under 

the authority of section 1895(b)(3)(B)(iv) 

of the Act. Additionally, this rule 

finalizes changes to the Home Health 

Value Based Purchasing (HHVBP) 

Model under the authority of section 

1115A of the Act, and Home Health 

Quality Reporting Program (HH QRP) 

requirements under the authority of 

section 1895(b)(3)(B)(v) of the Act. We 

are not finalizing the implementation of 

the Home Health Groupings Model 

(HHGM) in this final rule. We received 

a number of comments from the public 

that we would like to take into further 

consideration. 

B. Summary of the Major Provisions 

In the CY 2015 HH PPS final rule (79 

FR 66072), we finalized our proposal to 

recalibrate the case-mix weights every 

year with the most current and complete 

data available at the time of rulemaking. 

In section III.B. of this final rule, we are 

recalibrating the HH PPS case-mix 

weights, using the most current cost and 

utilization data available, in a budgetneutral manner. Also in section III.B. of 

this final rule, as finalized in the CY 

2016 HH PPS final rule (80 FR 68624), 

we are implementing a reduction to the 

national, standardized 60-day episode 

payment rate for CY 2018 of 0.97 

percent to account for estimated casemix growth unrelated to increases in 

patient acuity (that is, nominal case-mix 

growth) between CY 2012 and CY 2014. 

In section III.C. of this final rule, we 

update the payment rates under the HH 

PPS by 1 percent for CY 2018 in 

accordance with section 411(d) of the 

Medicare Access and CHIP 

Reauthorization Act of 2015 (MACRA) 

(Pub. L. 114–10, enacted April 16, 2015) 

which amended section 1895(b)(3)(B) of 

the Act. Additionally, section III.C. of 

this final rule, updates the CY 2018 

home health wage index using FY 2014 

hospital cost report data. In section 

III.D. of this final rule, we note that the 

fixed-dollar loss ratio remains 0.55 for 

CY 2018 to pay up to, but no more than, 

2.5 percent of total payments as outlier 

payments, as required by section 

1895(b)(5)(A) of the Act. 

In section IV of this final rule, we are 

finalizing changes to the Home Health 

Value-Based Purchasing (HHVBP) 

Model implemented January 1, 2016. 

We are amending the definition of 

‘‘applicable measure’’ to mean a 

measure for which a competing HHA 

has provided a minimum of 40 

completed surveys for Home Health 

Care Consumer Assessment of 

Healthcare Providers and Systems 

(HHCAHPS) measures, beginning with 

Performance Year (PY) 1, for purposes 

of receiving a performance score for any 

of the HHCAHPS measures, and for PY 

3 and subsequent years, we are 

finalizing the removal of the Outcome 

and Assessment Information Set 

(OASIS)-based measure, Drug Education 

on All Medications Provided to Patient/ 

Caregiver during All Episodes of Care, 

from the set of applicable measures. 

In section V. of this final rule, we are 

finalizing updates to the Home Health 

Quality Reporting Program, including: 

The replacement of one quality measure 

and the adoption of two new quality 

measures, data submission 

requirements, exception and extension 

requirements, and reconsideration and 

appeals procedures. We have also 

finalized the removal of 235 data 

elements from 33 current OASIS items, 

effective with all HHA assessments on 

or after January 1, 2019. We are not 

finalizing the standardized patient 

assessment data elements that we 

proposed to adopt for three of the five 

categories under section 1899B(b)(1)(B) 

of the Act: Cognitive Function and 

Mental Status; Special Services, 

Treatments, and Interventions; and 

Impairments. 


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C. Summary of Costs and Benefits 

TABLE 1—SUMMARY OF COSTS AND TRANSFERS

Provision description Costs Transfers 

CY 2018 HH PPS Payment Rate 

Update.

........................................................ The overall economic impact of the HH PPS payment rate update is 

an estimated ¥$80 million (¥0.4 percent) in payments to HHAs. 

CY 2018 HHVBP Model .................. ........................................................ The overall economic impact of the HHVBP Model provision for CY 

2018 through 2022 is an estimated $378 million in total savings 

from a reduction in unnecessary hospitalizations and SNF usage 

as a result of greater quality improvements in the HH industry 

(none of which is attributable to the changes finalized in this final 

rule). As for payments to HHAs, there are no aggregate increases 

or decreases expected to be applied to the HHAs competing in the 

model. 

CY 2019 HH QRP ........................... The overall economic impact of 

the HH QRP changes is a savings to HHAs of an estimated 

$146.0 million, beginning January 1, 2019.

II. Background 

A. Statutory Background 

The Balanced Budget Act of 1997 

(BBA) (Pub. L. 105–33, enacted August 

5, 1997), significantly changed the way 

Medicare pays for Medicare home 

health services. Section 4603 of the BBA 

mandated the development of the HH 

PPS. Until the implementation of the 

HH PPS on October 1, 2000, HHAs 

received payment under a retrospective 

reimbursement system. 

Section 4603(a) of the BBA mandated 

the development of a HH PPS for all 

Medicare-covered home health services 

provided under a plan of care (POC) that 

were paid on a reasonable cost basis by 

adding section 1895 of the Act, entitled 

‘‘Prospective Payment For Home Health 

Services.’’ Section 1895(b)(1) of the Act 

requires the Secretary to establish a HH 

PPS for all costs of home health services 

paid under Medicare. Section 1895(b)(2) 

of the Act requires that, in defining a 

prospective payment amount, the 

Secretary shall consider an appropriate 

unit of service and the number, type, 

and duration of visits provided within 

that unit, potential changes in the mix 

of services provided within that unit 

and their cost, and a general system 

design that provides for continued 

access to quality services. 

Section 1895(b)(3)(A) of the Act 

requires the following: (1) The 

computation of a standard prospective 

payment amount include all costs for 

HH services covered and paid for on a 

reasonable cost basis and that such 

amounts be initially based on the most 

recent audited cost report data available 

to the Secretary; and (2) the 

standardized prospective payment 

amount be adjusted to account for the 

effects of case-mix and wage levels 

among HHAs. 

Section 1895(b)(3)(B) of the Act 

addresses the annual update to the 

standard prospective payment amounts 

by the home health applicable 

percentage increase. Section 1895(b)(4) 

of the Act governs the payment 

computation. Sections 1895(b)(4)(A)(i) 

and (b)(4)(A)(ii) of the Act require the 

standard prospective payment amount 

to be adjusted for case-mix and 

geographic differences in wage levels. 

Section 1895(b)(4)(B) of the Act requires 

the establishment of an appropriate 

case-mix change adjustment factor for 

significant variation in costs among 

different units of services. 

Similarly, section 1895(b)(4)(C) of the 

Act requires the establishment of wage 

adjustment factors that reflect the 

relative level of wages, and wage-related 

costs applicable to home health services 

furnished in a geographic area 

compared to the applicable national 

average level. Under section 

1895(b)(4)(C) of the Act, the wageadjustment factors used by the Secretary 

may be the factors used under section 

1886(d)(3)(E) of the Act. 

Section 1895(b)(5) of the Act gives the 

Secretary the option to make additions 

or adjustments to the payment amount 

otherwise paid in the case of outliers 

due to unusual variations in the type or 

amount of medically necessary care. 

Section 3131(b)(2) of the Affordable 

Care Act revised section 1895(b)(5) of 

the Act so that total outlier payments in 

a given year would not exceed 2.5 

percent of total payments projected or 

estimated. The provision also made 

permanent a 10 percent agency-level 

outlier payment cap. 

In accordance with the statute, as 

amended by the BBA, we published a 

final rule in the July 3, 2000 Federal 

Register (65 FR 41128) to implement the 

HH PPS legislation. The July 2000 final 

rule established requirements for the 

new HH PPS for home health services 

as required by section 4603 of the BBA, 

as subsequently amended by section 

5101 of the Omnibus Consolidated and 

Emergency Supplemental 

Appropriations Act for Fiscal Year 1999 

(OCESAA), (Pub. L. 105–277, enacted 

October 21, 1998); and by sections 302, 

305, and 306 of the Medicare, Medicaid, 

and SCHIP Balanced Budget Refinement 

Act of 1999, (BBRA) (Pub. L. 106–113, 

enacted November 29, 1999). The 

requirements include the 

implementation of a HH PPS for home 

health services, consolidated billing 

requirements, and a number of other 

related changes. The HH PPS described 

in that rule replaced the retrospective 

reasonable cost-based system that was 

used by Medicare for the payment of 

home health services under Part A and 

Part B. For a complete and full 

description of the HH PPS as required 

by the BBA, see the July 2000 HH PPS 

final rule (65 FR 41128 through 41214). 

Section 5201(c) of the Deficit 

Reduction Act of 2005 (DRA) (Pub. L. 

109–171, enacted February 8, 2006) 

added new section 1895(b)(3)(B)(v) to 

the Act, requiring HHAs to submit data 

for purposes of measuring health care 

quality, and links the quality data 

submission to the annual applicable 

percentage increase. This data 

submission requirement is applicable 

for CY 2007 and each subsequent year. 

If an HHA does not submit quality data, 

the home health market basket 

percentage increase is reduced by 2 

percentage points. In the November 9, 

2006 Federal Register (71 FR 65884, 

65935), we published a final rule to 

implement the pay-for-reporting 

requirement of the DRA, which was 

codified at § 484.225(h) and (i) in 

accordance with the statute. The payVerDate Sep<11>2014 20:38 Nov 06, 2017 Jkt 244001 PO 00000 Frm 00004 Fmt 4701 Sfmt 4700 E:\FR\FM\07NOR2.SGM 07NOR2

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Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 51679 

for-reporting requirement was 

implemented on January 1, 2007. 

The Affordable Care Act made 

additional changes to the HH PPS. One 

of the changes in section 3131 of the 

Affordable Care Act is the amendment 

to section 421(a) of the Medicare 

Prescription Drug, Improvement, and 

Modernization Act of 2003 (MMA) (Pub. 

L. 108–173, enacted on December 8, 

2003) as amended by section 5201(b) of 

the DRA. Section 421(a) of the MMA, as 

amended by section 3131 of the 

Affordable Care Act, requires that the 

Secretary increase, by 3 percent, the 

payment amount otherwise made under 

section 1895 of the Act, for HH services 

furnished in a rural area (as defined in 

section 1886(d)(2)(D) of the Act) with 

respect to episodes and visits ending on 

or after April 1, 2010, and before 

January 1, 2016. 

Section 210 of the MACRA amended 

section 421(a) of the MMA to extend the 

rural add-on for 2 more years. Section 

421(a) of the MMA, as amended by 

section 210 of the MACRA, requires that 

the Secretary increase, by 3 percent, the 

payment amount otherwise made under 

section 1895 of the Act, for home health 

services provided in a rural area (as 

defined in section 1886(d)(2)(D) of the 

Act) with respect to episodes and visits 

ending on or after April 1, 2010, and 

before January 1, 2018. Section 411(d) of 

MACRA amended section 1895(b)(3)(B) 

of the Act such that for home health 

payments for CY 2018, the market 

basket percentage increase shall be 1 

percent. 

B. Current System for Payment of Home 

Health Services 

Generally, Medicare currently makes 

payment under the HH PPS on the basis 

of a national, standardized 60-day 

episode payment rate that is adjusted for 

the applicable case-mix and wage index. 

The national, standardized 60-day 

episode rate includes the six home 

health disciplines (skilled nursing, 

home health aide, physical therapy, 

speech-language pathology, 

occupational therapy, and medical 

social services). Payment for nonroutine supplies (NRS) is not part of the 

national, standardized 60-day episode 

rate, but is computed by multiplying the 

relative weight for a particular NRS 

severity level by the NRS conversion 

factor. Payment for durable medical 

equipment covered under the HH 

benefit is made outside the HH PPS 

payment system. To adjust for case-mix, 

the HH PPS uses a 153-category casemix classification system to assign 

patients to a home health resource 

group (HHRG). The clinical severity 

level, functional severity level, and 

service utilization are computed from 

responses to selected data elements in 

the OASIS assessment instrument and 

are used to place the patient in a 

particular HHRG. Each HHRG has an 

associated case-mix weight which is 

used in calculating the payment for an 

episode. Therapy service use is 

measured by the number of therapy 

visits provided during the episode and 

can be categorized into nine visit level 

categories (or thresholds): 0 to 5; 6; 7 to 

9; 10; 11 to 13; 14 to 15; 16 to 17; 18 

to 19; and 20 or more visits. 

For episodes with four or fewer visits, 

Medicare pays national per-visit rates 

based on the discipline(s) providing the 

services. An episode consisting of four 

or fewer visits within a 60-day period 

receives what is referred to as a lowutilization payment adjustment (LUPA). 

Medicare also adjusts the national 

standardized 60-day episode payment 

rate for certain intervening events that 

are subject to a partial episode payment 

adjustment (PEP adjustment). For 

certain cases that exceed a specific cost 

threshold, an outlier adjustment may 

also be available. 

C. Updates to the Home Health 

Prospective Payment System 

As required by section 1895(b)(3)(B) 

of the Act, we have historically updated 

the HH PPS rates annually in the 

Federal Register. The August 29, 2007 

final rule with comment period set forth 

an update to the 60-day national 

episode rates and the national per-visit 

rates under the HH PPS for CY 2008. 

The CY 2008 HH PPS final rule 

included an analysis performed on CY 

2005 home health claims data, which 

indicated a 12.78 percent increase in the 

observed case-mix since 2000. Case-mix 

represents the variations in conditions 

of the patient population served by the 

HHAs. Subsequently, a more detailed 

analysis was performed on the 2005 

case-mix data to evaluate if any portion 

of the 12.78 percent increase was 

associated with a change in the actual 

clinical condition of home health 

patients. We identified 8.03 percent of 

the total case-mix change as real, and 

therefore, decreased the 12.78 percent of 

total case-mix change by 8.03 percent to 

get a final nominal case-mix increase 

measure of 11.75 percent (0.1278 * 

(1¥0.0803) = 0.1175). 

To account for the changes in casemix that were not related to an 

underlying change in patient health 

status, we implemented a reduction, 

over 4 years, to the national, 

standardized 60-day episode payment 

rates. That reduction was to be 2.75 

percent per year for 3 years beginning in 

CY 2008 and 2.71 percent for the fourth 

year in CY 2011. In the CY 2011 HH PPS 

final rule (76 FR 68532), we updated our 

analyses of case-mix change and 

finalized a reduction of 3.79 percent, 

instead of 2.71 percent, for CY 2011 and 

deferred finalizing a payment reduction 

for CY 2012 until further study of the 

case-mix change data and methodology 

was completed. 

In the CY 2012 HH PPS final rule (76 

FR 68526), we updated the 60-day 

national episode rates and the national 

per-visit rates. In addition, as discussed 

in the CY 2012 HH PPS final rule (76 

FR 68528), our analysis indicated that 

there was a 22.59 percent increase in 

overall case-mix from 2000 to 2009 and 

that only 15.76 percent of that overall 

observed case-mix percentage increase 

was due to real case-mix change. As a 

result of our analysis, we identified a 

19.03 percent nominal increase in casemix. At that time, to fully account for 

the 19.03 percent nominal case-mix 

growth identified from 2000 to 2009, we 

finalized a 3.79 percent payment 

reduction in CY 2012 and a 1.32 percent 

payment reduction for CY 2013. 

In the CY 2013 HH PPS final rule (77 

FR 67078), we implemented the 1.32 

percent reduction to the payment rates 

for CY 2013 finalized the previous year, 

to account for nominal case-mix growth 

from 2000 through 2010. When taking 

into account the total measure of casemix change (23.90 percent) and the 

15.97 percent of total case-mix change 

estimated as real from 2000 to 2010, we 

obtained a final nominal case-mix 

change measure of 20.08 percent from 

2000 to 2010 (0.2390 * (1¥0.1597) = 

0.2008). To fully account for the 

remainder of the 20.08 percent increase 

in nominal case-mix beyond that which 

was accounted for in previous payment 

reductions, we estimated that the 

percentage reduction to the national, 

standardized 60-day episode rates for 

nominal case-mix change would be 2.18 

percent. Although we considered 

proposing a 2.18 percent reduction to 

account for the remaining increase in 

measured nominal case-mix, we 

finalized the 1.32 percent payment 

reduction to the national, standardized 

60-day episode rates in the CY 2012 HH 

PPS final rule (76 FR 68532). 

Section 3131(a) of the Affordable Care 

Act requires that, beginning in CY 2014, 

we apply an adjustment to the national, 

standardized 60-day episode rate and 

other amounts that reflect factors such 

as changes in the number of visits in an 

episode, the mix of services in an 

episode, the level of intensity of services 

in an episode, the average cost of 

providing care per episode, and other 

relevant factors. Additionally, we must 

phase in any adjustment over a 4-year 


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1The Report to Congress can be found in its 

entirety at https://www.cms.gov/Medicare/

Medicare-Fee-for-ServicePayment/HomeHealthPPS/

Downloads/HH-Report-to-Congress.pdf. 

2For the purposes of the surveys, ‘‘vulnerable 

patient populations’’ were defined as beneficiaries 

who were either eligible for the Part D low-income 

subsidy (LIS) 27 or residing in a health professional 

shortage area (HPSA). 

period in equal increments, not to 

exceed 3.5 percent of the amount (or 

amounts) as of the date of enactment of 

the Affordable Care Act, and fully 

implement the rebasing adjustments by 

CY 2017. The statute specifies that the 

maximum rebasing adjustment is to be 

no more than 3.5 percent per year of the 

CY 2010 rates. Therefore, in the CY 

2014 HH PPS final rule (78 FR 72256) 

for each year, CY 2014 through CY 2017, 

we finalized a fixed-dollar reduction to 

the national, standardized 60-day 

episode payment rate of $80.95 per year, 

increases to the national per-visit 

payment rates per year, and a decrease 

to the NRS conversion factor of 2.82 

percent per year. We also finalized three 

separate LUPA add-on factors for skilled 

nursing, physical therapy, and speechlanguage pathology and removed 170 

diagnosis codes from assignment to 

diagnosis groups in the HH PPS 

Grouper. In the CY 2015 HH PPS final 

rule (79 FR 66032), we implemented the 

second year of the 4-year phase-in of the 

rebasing adjustments to the HH PPS 

payment rates and made changes to the 

HH PPS case-mix weights. In addition, 

we simplified the face-to-face encounter 

regulatory requirements and the therapy 

reassessment timeframes. 

In the CY 2016 HH PPS final rule (80 

FR 68624), we implemented the third 

year of the 4-year phase-in of the 

rebasing adjustments to the national, 

standardized 60-day episode payment 

amount, the national per-visit rates and 

the NRS conversion factor (as outlined 

previously). In the CY 2016 HH PPS 

final rule, we also recalibrated the HH 

PPS case-mix weights, using the most 

current cost and utilization data 

available, in a budget-neutral manner 

and finalized reductions to the national, 

standardized 60-day episode payment 

rate in CY 2016, CY 2017, and CY 2018 

of 0.97 percent in each year to account 

for estimated case-mix growth unrelated 

to increases in patient acuity (that is, 

nominal case-mix growth) between CY 

2012 and CY 2014. Finally, section 

421(a) of the MMA, as amended by 

section 210 of the MACRA, extended 

the payment increase of 3 percent for 

HH services provided in rural areas (as 

defined in section 1886(d)(2)(D) of the 

Act) to episodes or visits ending before 

January 1, 2018. 

In the CY 2017 HH PPS final rule (81 

FR 76702), we implemented the last 

year of the 4-year phase-in of the 

rebasing adjustments to the national, 

standardized 60-day episode payment 

amount, the national per-visit rates and 

the NRS conversion factor (as outlined 

previously). We also finalized changes 

to the methodology used to calculate 

outlier payments under the authority of 

section 1895(b)(5) of the Act. Lastly, in 

accordance with section 1834(s) of the 

Act, as added by section 504(a) of the 

Consolidated Appropriations Act, 2016 

(Pub. L. 114–113, enacted December 18, 

2015), we implemented changes in 

payment for furnishing Negative 

Pressure Wound Therapy (NPWT) using 

a disposable device for patients under a 

home health plan of care for which 

payment would otherwise be made 

under section 1895(b) of the Act. 

D. Report to Congress: Home Health 

Study on Access to Care for Vulnerable 

Patient Populations and Subsequent 

Research and Analyses 

Section 3131(d) of the Affordable Care 

Act required CMS to conduct a study on 

home health agency costs involved with 

providing ongoing access to care to lowincome Medicare beneficiaries or 

beneficiaries in medically underserved 

areas, and in treating beneficiaries with 

varying levels of severity of illness and 

submit a report to Congress. As 

discussed in the CY 2016 HH PPS 

proposed rule (80 FR 39840) and the CY 

2017 HH PPS proposed rule (81 FR 

43744), the findings from the Report to 

Congress on the ‘‘Medicare Home 

Health Study: An Investigation on 

Access to Care and Payment for 

Vulnerable Patient Populations,’’ found 

that payment accuracy could be 

improved under the current payment 

system, particularly for patients with 

certain clinical characteristics requiring 

more nursing care than therapy.1

The research for the Report to 

Congress, released in December 2014, 

consisted of extensive analysis of both 

survey and administrative data. The 

CMS-developed surveys were given to 

physicians who referred vulnerable 

patient populations to Medicare home 

health and to Medicare-certified HHAs.2

The response rates were 72 percent and 

59 percent for the HHA and physician 

surveys, respectively. The results of the 

survey revealed that over 80 percent of 

respondent HHAs and over 90 percent 

of respondent physicians reported that 

access to home health care for Medicare 

fee-for-service beneficiaries in their 

local area was excellent or good. When 

survey respondents reported access 

issues, specifically their inability to 

place or admit Medicare fee-for-service 

patients into home health, the most 

common reason reported (64 percent of 

respondent HHAs surveyed) was that 

the patients did not qualify for the 

Medicare home health benefit. HHAs 

and physicians also cited family or 

caregiver issues as an important 

contributing factor in the inability to 

admit or place patients. Only 17.2 

percent of HHAs and 16.7 percent of 

physicians reported insufficient 

payment as an important contributing 

factor in the inability to admit or place 

patients. The results of the CMSconducted surveys suggested that CMS’ 

ability to improve access for certain 

vulnerable patient populations through 

payment policy may be limited. 

However, we are able to revise the casemix system to minimize differences in 

payment that could potentially be 

serving as a barrier to receiving care. In 

the near future, we intend to better align 

payment with resource use so that it 

reduces HHAs’ financial incentives to 

select certain patients over others. 

We also performed an analysis of 

Medicare administrative data (CY 2010 

Medicare claims and cost report data) 

and calculated margins for episodes of 

care. This was done because margin 

differences associated with patient 

clinical and social characteristics can 

indicate whether financial incentives 

exist in the current HH PPS to provide 

home health care for certain types of 

patients over others. Lower margins, if 

systematically associated with care for 

vulnerable patient populations, may 

indicate financial disincentives for 

HHAs to admit these patients, 

potentially creating access to care 

issues. The findings from the data 

analysis found that certain patient 

characteristics appear to be strongly 

associated with margin levels, and thus 

may create financial incentives to select 

certain patients over others. Margins 

were estimated to be lower for patients 

who required parenteral nutrition, who 

had traumatic wounds or ulcers, or 

required substantial assistance in 

bathing. For example, in CY 2010, 

episodes for patients with parenteral 

nutrition were, on average, associated 

with a $178.53 lower margin than 

episodes for patients without parenteral 

nutrition. Given that these variables are 

already included in the HH PPS casemix system, the results indicated that 

modifications to the way the current 

case-mix system accounts for resource 

use differences may be needed to 

mitigate any financial incentives to 

select certain patients over others. 

Margins were also lower for 

beneficiaries who were admitted after 

acute or post-acute stays or who had 

certain poorly-controlled clinical 


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3Fout B, Plotzke M, Christian T. (2016). Using 

Predicted Therapy Visits in the Medicare Home 

Health Prospective Payment System. Home Health 

Care Management & Practice, 29(2), 81–90. http:// 

journals.sagepub.com/doi/abs/10.1177/

1084822316678384. 

4Medicare Payment Advisory Commission 

(MedPAC). ‘‘Home Health Care Services.’’ Report to 

Congress: Medicare Payment Policy. Washington, 

DC, March 2015. P. 223. Accessed on March 28, 

2017 at: http://www.medpac.gov/docs/defaultsource/reports/mar2015_entirereport_revised

.pdf?sfvrsn=0. 

conditions, such as poorly controlled 

pulmonary disorders, indicating that 

accounting for additional patient 

characteristic variables in the HH PPS 

case-mix system may also reduce 

financial incentives to select certain 

types of patients over others. More 

information on the results from the 

home health study required by section 

3131(d) of the Affordable Care Act can 

be found in the Report to Congress on 

the ‘‘Medicare Home Health Study: An 

Investigation on Access to Care and 

Payment for Vulnerable Patient 

Populations’’ available at https://

www.cms.gov/center/provider-Type/

home-Health-Agency-HHA-Center.html. 

Section 3131(d)(5) of the Affordable 

Care Act authorized the Secretary to 

determine whether it would be 

appropriate to conduct a Medicare 

demonstration project based on the 

result of the home health study. If the 

Secretary determined it was appropriate 

to conduct the demonstration project 

under this subsection, the Secretary was 

to conduct the project for a 4-year 

period beginning not later than January 

1, 2015. We did not determine that it 

was appropriate to conduct a 

demonstration project based on the 

findings from the home health study. 

Rather, the findings from the home 

health study suggested that follow-on 

work should be conducted to better 

align payments with costs under the 

authority of section 1895 of the Act. 

In addition to the findings from the 

Report to Congress on the ‘‘Medicare 

Home Health Study: An Investigation on 

Access to Care and Payment for 

Vulnerable Patient Populations,’’ 

concerns have also been raised about 

the use of therapy thresholds in the 

current payment system. Under the 

current payment system, HHAs receive 

higher payments for providing more 

therapy visits once certain thresholds 

are reached. As a result, the average 

number of therapy visits per 60-day 

episode of care have increased since the 

implementation of the HH PPS, while 

the number of skilled nursing and home 

health aide visits have decreased over 

the same time period (82 FR 35280 

(Figure 3)). A study examining an 

option of using predicted, rather than 

actual, therapy visits in the home health 

found that in 2013, 58 percent of home 

health episodes included some therapy 

services, and these episodes accounted 

for 72 percent of all Medicare home 

health payments.3 Figure 1, from that 

study, demonstrates that the percentage 

of episodes, and the average episode 

payment by the number of therapy visits 

for episodes with at least one therapy 

visit in 2013 increased sharply in 

therapy provision just over payment 

thresholds at 6, 7, and 16. According to 

the study, the presence of sharp 

increases in the percentage of episodes 

just above payment thresholds suggests 

a response to financial incentives in the 

home health payment system. Similarly, 

between 2008 and 2013, MedPAC 

reported a 26 percent increase in the 

number of episodes with at least 6 

therapy visits, compared with a 1 

percent increase in the number of 

episodes with 5 or fewer therapy visits.4

CMS analysis demonstrates that the 

average share of therapy visits across all 

60-day episodes of care increased from 

9 percent of all visits in 1997, prior to 

the implementation of the HH PPS (see 

64 FR 58151), to 39 percent of all visits 

in 2015 (82 FR 35277 through 35278 

(Table 2)). 


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5Committee on Finance, United States Senate. 

Staff Report on Home Health and the Medicare 

Therapy Threshold. Washington, DC, 2011. 

Accessed on March 28, 2017 at https://

www.finance.senate.gov/imo/media/doc/Home_

Health_Report_Final4.pdf. 

6Medicare Payment Advisory Commission 

(MedPAC). ‘‘Home Health Services.’’ Report to 

Congress: Medicare Payment Policy. Washington, 

DC, March 2011. P. 182–183. Accessed on March 

28, 2017 at http://www.medpac.gov/docs/defaultsource/reports/Mar11_Ch08.pdf?sfvrsn=0. 

7Medicare Payment Advisory Commission 

(MedPAC). ‘‘Home Health Care Services.’’ Report to 

Congress: Medicare Payment Policy. Washington, 

DC, March 2017. P. 243–244. Accessed on March 

28, 2017 at http://www.medpac.gov/docs/defaultsource/reports/mar17_medpac_ch9.pdf?sfvrsn=0. 

Figure 1 suggests that HHAs may be 

responding to financial incentives in the 

home health payment system when 

making care plan decisions. 

Additionally, an investigation into the 

therapy practices of the four largest 

publically-traded home health 

companies, conducted by the Senate 

Committee on Finance in 2010, found 

that three out of the four companies 

investigated ‘‘encouraged therapists to 

target the most profitable number of 

therapy visits, even when patient need 

alone may not have justified such 

patterns’’.5 The Senate Committee on 

Finance investigation also highlighted 

the abrupt and dramatic responses the 

home health industry has taken to 

maximize reimbursement under the 

therapy threshold models (both the 

original 10-visit threshold model and 

under the revised thresholds 

implemented in the CY 2008 HH PPS 

final rule (72 FR 49762)). The report 

noted that, under the HH PPS, HHAs 

have broad discretion over the number 

of therapy visits to provide patients, and 

therefore, have control of the singlelargest variable in determining 

reimbursement and overall margins. The 

report recommended that CMS closely 

examine a future payment approach that 

focuses on patient well-being and health 

characteristics, rather than the 

numerical utilization measures. 

MedPAC also continues to 

recommend the removal of the therapy 

thresholds used for determining 

payment from the HH PPS, as it believes 

that such thresholds run counter to the 

goals of a prospective payment system, 

create financial incentives that detract 

from a focus on patient characteristics 

and care needs when agencies are 

setting plans of care for their patients, 

and incentivize unnecessary therapy 

utilization. For the average HHA, 

according to MedPAC, the increase in 

payment for therapy visits rises faster 

than costs, resulting in financial 

incentives for HHAs to overprovide 

therapy services.6 HHAs that provide 

more therapy episodes tend to be more 

profitable and this higher profitability 

and rapid growth in the number of 

therapy episodes suggest that financial 

incentives are causing agencies to favor 

therapy services when possible.7

Eliminating therapy as a payment factor 

will base home health payment solely 

on patient characteristics, which is a 

more patient-focused approach to 

payment, as recommended by both 

MedPAC and previously by the Senate 

Committee on Finance. 

After considering the findings from 

the Report to Congress and 

recommendations from MedPAC and 

the Senate Committee on Finance, CMS, 

along with our contractor, conducted 

additional research on ways to improve 

the payment accuracy under the current 

payment system. Exploring all options 

and different models ultimately led us 

to further develop the Home Health 

Groupings Model (HHGM). As 

discussed in the CY 2018 HH PPS 

proposed rule (82 FR 35294), we shared 


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the analysis and development of the 

HHGM with both internal and external 

stakeholders via technical expert panels, 

clinical workgroups, special open door 

forums, in the CY 2016 HH PPS 

proposed rule (80 FR 39840) and the CY 

2017 HH PPS proposed rule (81 FR 

43744), in a detailed technical report 

posted on the CMS Web site in 

December 2016 (followed by additional 

technical and clinical expert panels) 

and a National Provider Call in January 

2017. The HHGM uses 30-day periods, 

rather than 60-day episodes, and relies 

more heavily on clinical characteristics 

and other patient information (for 

example, principal diagnosis, functional 

level, comorbid conditions, admission 

source, and timing) to place patients 

into meaningful payment categories, 

rather than the current therapy-driven 

system, which are the major differences 

between the current system and the 

HHGM. 

III. Provisions of the Proposed Rule: 

Payment Under the Home Health 

Prospective Payment System (HH PPS) 

and Responses to Comments 

In the July 28, 2017 Federal Register 

(82 FR 35270 through 35393), we 

published the proposed rule titled 

‘‘Medicare and Medicaid Programs; CY 

2018 Home Health Prospective Payment 

System Rate Update and Proposed CY 

2019 Case-Mix Adjustment 

Methodology Refinements; Home Health 

Value-Based Purchasing Model; and 

Home Health Quality Reporting 

Requirements’’. We received 

approximately 1,346 timely comments 

from the public, including comments 

from home health agencies, national and 

state provider associations, patient and 

other advocacy organizations, nurses, 

and physical therapists. In the following 

sections, we summarize the proposed 

provisions and the public comments, 

and provide the responses to comments. 

A. Monitoring for Potential Impacts— 

Affordable Care Act Rebasing 

Adjustments 

In the CY 2018 HH PPS proposed rule 

(82 FR 35277), we provided a summary 

of analysis on fiscal year (FY) 2015 HHA 

cost report data and how such data, if 

used, would impact our estimate of the 

percentage difference between Medicare 

payments and HHA costs used to 

calculate the Affordable Care Act 

rebasing adjustments. In addition, we 

presented information on Medicare 

home health utilization statistics and 

trends that included HHA claims data 

through CY 2016. We will continue 

monitoring the impacts due to the 

rebasing adjustments and other policy 

changes and will provide the industry 

with periodic updates on our analysis in 

rulemaking and announcements on the 

HHA Center Web page at https://

www.cms.gov/Center/Provider-Type/

Home-Health-Agency-HHA-Center.html. 

The following is a summary of the 

comments received on the analysis of 

HHA cost report and utilization data 

and our responses. 

Comment: A commenter noted that it 

may come as no surprise that payments 

exceed costs by 21 percent, given that 

Medicare payment for home health is 

statutorily required to be based on a 

prospective payment system and the 

industry is now 90 percent for-profit, 

with incentives to admit only the most 

profitable cases. The commenter went 

on to state that home health payments 

from Medicare Advantage (MA) plans 

are inadequate and that HHAs subsidize 

low payments from MA plans with 

payments for fee-for-service patients. 

The commenter further noted that the 

number of patients coming into home 

health care from the community (rather 

than following an acute or post-acute 

care stay) has risen in response to 

deliberate Medicare and public health 

effort to keep patients out of the 

hospital. Similar comments from 

MedPAC stated that CMS’s review of 

utilization is consistent with the 

Commission’s findings on access to 

care, and the analysis of the cost and 

utilization data in the proposed rule 

underscores the Commission’s longstanding concern that the Patient 

Protection and Affordable Care Act 

(PPACA) rebasing provision would not 

adequately reduce payments. 

Response: We thank the commenters 

for their feedback on the HHA cost and 

utilization data presented in the 

proposed rule. We will continue 

monitoring the impacts due to the 

rebasing adjustments and other policy 

changes and will provide the industry 

with periodic updates on our analysis in 

rulemaking or announcements on the 

HHA Center Web page at: https://

www.cms.gov/Center/Provider-Type/

Home-Health-Agency-HHA-Center.html. 

Comment: A commenter questioned 

whether CMS did any trimming to the 

cost report data used to populate Table 

2 in the CY 2018 HH PPS proposed rule 

and whether NRS costs were excluded 

from this calculation. 

Response: As we noted in the CY 

2018 HH PPS proposed rule (82 FR 

35277), to determine the 2015 average 

cost per visit per discipline, we applied 

the same trimming methodology 

outlined in the CY 2014 HH PPS 

proposed rule (78 FR 40284) and 

weighted the costs per visit from the 

2015 cost reports by size, facility type, 

and urban/rural location so the costs per 

visit were nationally representative 

according to 2015 claims data. The 2015 

average number of visits was taken from 

2015 claims data (82 FR 35277). Because 

CMS currently pays for NRS using a 

separate conversion factor, NRS costs 

were not included in Table 2 as the 

national, standardized 60-day episode 

payment amount only reflects the cost 

of care related to skilled nursing, 

physical therapy, occupational therapy, 

speech-language pathology, home health 

aide, and medical social services. The 

payment for NRS is calculated through 

the NRS conversion factor, multiplied 

by the weights for the six severity levels. 

B. CY 2018 HH PPS Case-Mix Weights 

In the CY 2015 HH PPS final rule (79 

FR 66072), we finalized a policy to 

annually recalibrate the HH PPS casemix weights—adjusting the weights 

relative to one another—using the most 

current, complete data available. To 

recalibrate the HH PPS case-mix weights 

for CY 2018, we will use the same 

methodology finalized in the CY 2008 

HH PPS final rule (72 FR 49762), the CY 

2012 HH PPS final rule (76 FR 68526), 

and the CY 2015 HH PPS final rule (79 

FR 66032). Annual recalibration of the 

HH PPS case-mix weights ensures that 

the case-mix weights reflect, as 

accurately as possible, current home 

health resource use and changes in 

utilization patterns. 

To generate the CY 2018 HH PPS 

case-mix weights, we used CY 2016 

home health claims data (as of August 

17, 2017) with linked OASIS data. 

These data are the most current and 

complete data available at this time. We 

noted in the proposed rule that we 

would use CY 2016 home health claims 

data (as of June 30, 2017 or later) with 

linked OASIS data to generate the CY 

2018 HH PPS case-mix weights for this 

final rule. The process we used to 

calculate the HH PPS case-mix weights 

is outlined in this section. 

Step 1: Re-estimate the four-equation 

model to determine the clinical and 

functional points for an episode using 

wage-weighted minutes of care as our 

dependent variable for resource use. 

The wage-weighted minutes of care are 

determined using the CY 2015 Bureau of 

Labor Statistics national hourly wage 

plus fringe rates for the six home health 

disciplines and the minutes per visit 

from the claim. The points for each of 

the variables for each leg of the model, 

updated with CY 2016 home health 

claims data, are shown in Table 2. The 

points for the clinical variables are 

added together to determine an 

episode’s clinical score. The points for 

the functional variables are added 


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together to determine an episode’s 

functional score. 

TABLE 2—CASE-MIX ADJUSTMENT VARIABLES AND SCORES

Episode number within sequence of adjacent episodes .................................... 1 or 2 1 or 2 3+ 3+ 

Therapy visits ...................................................................................................... 0–13 14+ 0–13 14+ 

EQUATION: ........................................................................................................ 1 2 3 4 

CLINICAL DIMENSION 

1 ....................... Primary or Other Diagnosis = Blindness/Low Vision ......................................... ........................ ........................ ........................ ........................

2 ....................... Primary or Other Diagnosis = Blood disorders .................................................. ........................ 1 ........................ ........................

3 ....................... Primary or Other Diagnosis = Cancer, selected benign neoplasms .................. ........................ 4 ........................ 4 

4 ....................... Primary Diagnosis = Diabetes ............................................................................ ........................ 3 ........................ ........................

5 ....................... Other Diagnosis = Diabetes ............................................................................... 1 ........................ ........................ ........................

6 ....................... Primary or Other Diagnosis = Dysphagia AND Primary or Other Diagnosis = 

Neuro 3—Stroke.

2 16 1 10 

7 ....................... Primary or Other Diagnosis = Dysphagia AND M1030 (Therapy at home) = 3 

(Enteral).

1 5 ........................ 9 

8 ....................... Primary or Other Diagnosis = Gastrointestinal disorders ................................... ........................ ........................ ........................ 2 

9 ....................... Primary or Other Diagnosis = Gastrointestinal disorders AND M1630 

(ostomy)= 1 or 2.

........................ 7 ........................ ........................

10 ..................... Primary or Other Diagnosis = Gastrointestinal disorders AND Primary or 

Other Diagnosis = Neuro 1—Brain disorders and paralysis, OR Neuro 2— 

Peripheral neurological disorders, OR Neuro 3—Stroke, OR Neuro 4—Multiple Sclerosis.

........................ ........................ ........................ ........................

11 ..................... Primary or Other Diagnosis = Heart Disease OR Hypertension ........................ 1 3 ........................ 2 

12 ..................... Primary Diagnosis = Neuro 1—Brain disorders and paralysis ........................... 3 9 6 9 

13 ..................... Primary or Other Diagnosis = Neuro 1—Brain disorders and paralysis AND 

M1840 (Toilet transfer) = 2 or more.

........................ 4 ........................ 4 

14 ..................... Primary or Other Diagnosis = Neuro 1—Brain disorders and paralysis OR 

Neuro 2—Peripheral neurological disorders AND M1810 or M1820 (Dressing upper or lower body) = 1, 2, or 3.

2 4 2 4 

15 ..................... Primary or Other Diagnosis = Neuro 3—Stroke ................................................. 3 9 2 4 

16 ..................... Primary or Other Diagnosis = Neuro 3—Stroke AND M1810 or M1820 

(Dressing upper or lower body) = 1, 2, or 3.

........................ 2 ........................ ........................

17 ..................... Primary or Other Diagnosis = Neuro 3—Stroke AND M1860 (Ambulation) = 4 

or more.

........................ ........................ ........................ ........................

18 ..................... Primary or Other Diagnosis = Neuro 4—Multiple Sclerosis AND AT LEAST 

ONE OF THE FOLLOWING: M1830 (Bathing) = 2 or more OR M1840 (Toilet transfer) = 2 or more OR M1850 (Transferring) = 2 or more OR M1860 

(Ambulation) = 4 or more.

3 7 5 11 

19 ..................... Primary or Other Diagnosis = Ortho 1—Leg Disorders or Gait Disorders AND 

M1324 (most problematic pressure ulcer stage) = 1, 2, 3 or 4.

7 1 7 ........................

20 ..................... Primary or Other Diagnosis = Ortho 1—Leg OR Ortho 2—Other orthopedic 

disorders AND M1030 (Therapy at home) = 1 (IV/Infusion) or 2 (Parenteral).

3 ........................ 3 7 

21 ..................... Primary or Other Diagnosis = Psych 1—Affective and other psychoses, depression......................... ........................ ........................ ........................

22 ..................... Primary or Other Diagnosis = Psych 2—Degenerative and other organic psychiatric disorders......................... ........................ ........................ ........................

23 ..................... Primary or Other Diagnosis = Pulmonary disorders .......................................... ........................ 2 ........................ 1 

24 ..................... Primary or Other Diagnosis = Pulmonary disorders AND M1860 (Ambulation) 

= 1 or more.

........................ ........................ ........................ ........................

25 ..................... Primary Diagnosis = Skin 1—Traumatic wounds, burns, and post-operative 

complications.

3 17 6 17 

26 ..................... Other Diagnosis = Skin 1—Traumatic wounds, burns, post-operative complications.6 14 7 14 

27 ..................... Primary or Other Diagnosis = Skin 1—Traumatic wounds, burns, and post-operative complications OR Skin 2—Ulcers and other skin conditions AND 

M1030 (Therapy at home) = 1 (IV/Infusion) or 2 (Parenteral).

2 ........................ ........................ ........................

28 ..................... Primary or Other Diagnosis = Skin 2—Ulcers and other skin conditions .......... 2 16 8 18 

29 ..................... Primary or Other Diagnosis = Tracheostomy ..................................................... 2 17 ........................ 17 

30 ..................... Primary or Other Diagnosis = Urostomy/Cystostomy ........................................ ........................ 17 ........................ 12 

31 ..................... M1030 (Therapy at home) = 1 (IV/Infusion) or 2 (Parenteral) ........................... ........................ 15 5 15 

32 ..................... M1030 (Therapy at home) = 3 (Enteral) ............................................................ ........................ 16 ........................ 6 

33 ..................... M1200 (Vision) = 1 or more ............................................................................... ........................ ........................ ........................ ........................

34 ..................... M1242 (Pain)= 3 or 4 ......................................................................................... 3 ........................ 2 ........................

35 ..................... M1311 = Two or more pressure ulcers at stage 3 or 4 ..................................... 4 6 4 6 

36 ..................... M1324 (Most problematic pressure ulcer stage) = 1 or 2 .................................. 4 19 7 17 

37 ..................... M1324 (Most problematic pressure ulcer stage)= 3 or 4 ................................... 9 31 10 25 

38 ..................... M1334 (Stasis ulcer status) = 2 ......................................................................... 4 13 8 13 

39 ..................... M1334 (Stasis ulcer status) = 3 ......................................................................... 7 17 9 17 

40 ..................... M1342 (Surgical wound status) = 2 ................................................................... 2 7 6 13 

41 ..................... M1342 (Surgical wound status) = 3 ................................................................... ........................ 6 5 10 

42 ..................... M1400 (Dyspnea) = 2, 3, or 4 ............................................................................ 1 1 ........................ ........................

43 ..................... M1620 (Bowel Incontinence) = 2 to 5 ................................................................ ........................ 3 ........................ 2 

44 ..................... M1630 (Ostomy) = 1 or 2 ................................................................................... 4 11 2 8 

45 ..................... M2030 (Injectable Drug Use) = 0, 1, 2, or 3 ...................................................... ........................ ........................ ........................ ........................

FUNCTIONAL DIMENSION 

46 ..................... M1810 or M1820 (Dressing upper or lower body) = 1, 2, or 3 .......................... 1 ........................ ........................ ........................

47 ..................... M1830 (Bathing) = 2 or more ............................................................................. 6 5 6 2 

48 ..................... M1840 (Toilet transferring) = 2 or more ............................................................. ........................ 1 ........................ ........................


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8For Step 1, 45.3 percent of episodes were in the 

medium functional level (All with score 14). 

For Step 2.1, 87.3 percent of episodes were in the 

low functional level (Most with scores 5 to 7). 

For Step 2.2, 81.9 percent of episodes were in the 

low functional level (Most with score 2). 

For Step 3, 46.3 percent of episodes were in the 

medium functional level (Most with score 10). 

For Step 4, 48.7 percent of episodes were in the 

medium functional level (Most with score 5 or 6). 

TABLE 2—CASE-MIX ADJUSTMENT VARIABLES AND SCORES—Continued 

49 ..................... M1850 (Transferring) = 2 or more ...................................................................... 3 1 2 . 

50 ..................... M1860 (Ambulation) = 1, 2 or 3 ......................................................................... 7 ........................ 4 ........................

51 ..................... M1860 (Ambulation) = 4 or more ....................................................................... 8 9 7 7 

Source: CY 2016 Medicare claims data for episodes ending on or before December 31, 2016 (as of August 17, 2017) for which we had a linked 

OASIS assessment. LUPA episodes, outlier episodes, and episodes with PEP adjustments were excluded. 

Note(s): Points are additive; however, points may not be given for the same line item in the table more than once. Please see Medicare Home 

Health Diagnosis Coding guidance at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/coding_billing.html for 

definitions of primary and secondary diagnoses. 

In updating the four-equation model 

for CY 2018, using 2016 home health 

claims data (the last update to the fourequation model for CY 2017 used CY 

2015 home health claims data), there 

were few changes to the point values for 

the variables in the four-equation 

model. These relatively minor changes 

reflect the change in the relationship 

between the grouper variables and 

resource use between CY 2015 and CY 

2016. The CY 2018 four-equation model 

resulted in 120 point-giving variables 

being used in the model (as compared 

to the 124 variables for the CY 2017 

recalibration). There were 8 variables 

that were added to the model and 12 

variables that were dropped from the 

model due to the absence of additional 

resources associated with the variable. 

Of the variables that were in both the 

four-equation model for CY 2017 and 

the four-equation model for CY 2018, 

the points for 14 variables increased in 

the CY 2018 four-equation model and 

the points for 48 variables decreased in 

the CY 2018 4-equation model. There 

were 50 variables with the same point 

values. 

Step 2: Redefining the clinical and 

functional thresholds so they are 

reflective of the new points associated 

with the CY 2018 four-equation model. 

After estimating the points for each of 

the variables and summing the clinical 

and functional points for each episode, 

we look at the distribution of the 

clinical score and functional score, 

breaking the episodes into different 

steps. The categorizations for the steps 

are as follows: 

• Step 1: First and second episodes, 

0–13 therapy visits. 

• Step 2.1: First and second episodes, 

14–19 therapy visits. 

• Step 2.2: Third episodes and 

beyond, 14–19 therapy visits. 

• Step 3: Third episodes and beyond, 

0–13 therapy visits. 

• Step 4: Episodes with 20+ therapy 

visits 

Then, we divide the distribution of 

the clinical score for episodes within a 

step such that a third of episodes are 

classified as low clinical score, a third 

of episodes are classified as medium 

clinical score, and a third of episodes 

are classified as high clinical score. The 

same approach is then done looking at 

the functional score. It was not always 

possible to evenly divide the episodes 

within each step into thirds due to 

many episodes being clustered around 

one particular score.8 Also, we looked at 

the average resource use associated with 

each clinical and functional score and 

used that as a guide for setting our 

thresholds. We grouped scores with 

similar average resource use within the 

same level (even if it meant that more 

or less than a third of episodes were 

placed within a level). The new 

thresholds, based off the CY 2018 fourequation model points are shown in 

Table 3. 

TABLE 3—CY 2018 CLINICAL AND FUNCTIONAL THRESHOLDS

1st and 2nd episodes 3rd+ episodes All episodes 

0 to 13 

therapy visits 

14 to 19 

therapy visits 

0 to 13 

therapy visits 

14 to 19 

therapy visits 

20+ therapy 

visits 

Grouping Step 1 2 ....................... 3 ....................... 4 ....................... 5 

Equations used to calculate points (see Table 1) 1 2 ....................... 3 ....................... 4 ....................... (2&4) 

Dimension Severity 

Level 

Clinical ............................................. C1 ............ 0 to 1 ................ 0 to 1 ................ 0 to 1 ................ 0 to 1 ................ 0 to 3 

C2 ............ 2 to 3 ................ 2 to 7 ................ 2 ....................... 2 to 9 ................ 4 to 16 

C3 ............ 4+ ..................... 8+ ..................... 3+ ..................... 10+ ................... 17+ 

Functional ........................................ F1 ............ 0 to 13 .............. 0 to 7 ................ 0 to 6 ................ 0 to 2 ................ 0 to 2 

F2 ............ 14 ..................... 8 to 15 .............. 7 to 10 .............. 3 to 7 ................ 3 to 6 

F3 ............ 15+ ................... 16+ ................... 11+ ................... 8+ ..................... 7+ 

Step 3: Once the clinical and 

functional thresholds are determined 

and each episode is assigned a clinical 

and functional level, the payment 

regression is estimated with an 

episode’s wage-weighted minutes of 

care as the dependent variable. 

Independent variables in the model are 

indicators for the step of the episode as 

well as the clinical and functional levels 

within each step of the episode. Like the 

four-equation model, the payment 

regression model is also estimated with 

robust standard errors that are clustered 

at the beneficiary level. Table 4 shows 

the regression coefficients for the 

variables in the payment regression 

model updated with CY 2016 home 

health claims data. The R-squared value 

for the payment regression model is 


asabaliauskas on DSKBBXCHB2PROD with RULES
51686 Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 

9Medicare Payment Advisory Commission 

(MedPAC), Report to the Congress: Medicare 

Payment Policy. March 2011, p. 176. 

10When computing the average, we compute a 

weighted average, assigning a value of one to each 

normal episode and a value equal to the episode 

length divided by 60 for PEPs. 

0.5095 (an increase from 0.4919 for the 

CY 2017 recalibration). 

TABLE 4—PAYMENT REGRESSION MODEL

Payment regression 

from 4-equation 

model for CY 2018 

Step 1, Clinical Score Medium .................................................................................................................................................... $24.58 

Step 1, Clinical Score High ......................................................................................................................................................... 54.24 

Step 1, Functional Score Medium ............................................................................................................................................... 72.76 

Step 1, Functional Score High .................................................................................................................................................... 107.48 

Step 2.1, Clinical Score Medium ................................................................................................................................................. 48.81 

Step 2.1, Clinical Score High ...................................................................................................................................................... 135.99 

Step 2.1, Functional Score Medium ............................................................................................................................................ 31.51 

Step 2.1, Functional Score High ................................................................................................................................................. 57.73 

Step 2.2, Clinical Score Medium ................................................................................................................................................. 39.37 

Step 2.2, Clinical Score High ...................................................................................................................................................... 194.18 

Step 2.2, Functional Score Medium ............................................................................................................................................ 21.53 

Step 2.2, Functional Score High ................................................................................................................................................. 56.25 

Step 3, Clinical Score Medium .................................................................................................................................................... 17.07 

Step 3, Clinical Score High ......................................................................................................................................................... 95.93 

Step 3, Functional Score Medium ............................................................................................................................................... 59.15 

Step 3, Functional Score High .................................................................................................................................................... 90.40 

Step 4, Clinical Score Medium .................................................................................................................................................... 80.09 

Step 4, Clinical Score High ......................................................................................................................................................... 263.75 

Step 4, Functional Score Medium ............................................................................................................................................... 27.97 

Step 4, Functional Score High .................................................................................................................................................... 62.20 

Step 2.1, 1st and 2nd Episodes, 14 to 19 Therapy Visits .......................................................................................................... 512.27 

Step 2.2, 3rd+ Episodes, 14 to 19 Therapy Visits ...................................................................................................................... 523.60 

Step 3, 3rd+ Episodes, 0–13 Therapy Visits .............................................................................................................................. ¥72.22 

Step 4, All Episodes, 20+ Therapy Visits .................................................................................................................................... 907.99 

Intercept ....................................................................................................................................................................................... 389.35 

Source: CY 2016 Medicare claims data for episodes ending on or before December 31, 2016 (as of August 17, 2017) for which we had a 

linked OASIS assessment. 

Step 4: We use the coefficients from 

the payment regression model to predict 

each episode’s wage-weighted minutes 

of care (resource use). We then divide 

these predicted values by the mean of 

the dependent variable (that is, the 

average wage-weighted minutes of care 

across all episodes used in the payment 

regression). This division constructs the 

weight for each episode, which is 

simply the ratio of the episode’s 

predicted wage-weighted minutes of 

care divided by the average wageweighted minutes of care in the sample. 

Each episode is then aggregated into one 

of the 153 home health resource groups 

(HHRGs) and the ‘‘raw’’ weight for each 

HHRG was calculated as the average of 

the episode weights within the HHRG. 

Step 5: The raw weights associated 

with 0 to 5 therapy visits are then 

increased by 3.75 percent, the weights 

associated with 14 to 15 therapy visits 

are decreased by 2.5 percent, and the 

weights associated with 20+ therapy 

visits are decreased by 5 percent. These 

adjustments to the case-mix weights 

were finalized in the CY 2012 HH PPS 

final rule (76 FR 68557) and were done 

to address MedPAC’s concerns that the 

HH PPS overvalues therapy episodes 

and undervalues non-therapy episodes 

and to better align the case-mix weights 

with episode costs estimated from cost 

report data.9

Step 6: After the adjustments in Step 

5 are applied to the raw weights, the 

weights are further adjusted to create an 

increase in the payment weights for the 

therapy visit steps between the therapy 

thresholds. Weights with the same 

clinical severity level, functional 

severity level, and early/later episode 

status were grouped together. Then 

within those groups, the weights for 

each therapy step between thresholds 

are gradually increased. We do this by 

interpolating between the main 

thresholds on the model (from 0 to 5 to 

14 to 15 therapy visits, and from 14 to 

15 to 20+ therapy visits). We use a 

linear model to implement the 

interpolation so the payment weight 

increase for each step between the 

thresholds (such as the increase 

between 0 and 5 therapy visits and 6 

therapy visits and the increase between 

6 therapy visits and 7 to 9 therapy 

visits) are constant. This interpolation is 

identical to the process finalized in the 

CY 2012 HH PPS final rule (76 FR 

68555). 

Step 7: The interpolated weights are 

then adjusted so that the average casemix for the weights is equal to 1.0000.10

This last step creates the final CY 2018 

case-mix weights shown in Table 5. 


asabaliauskas on DSKBBXCHB2PROD with RULES
Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 51687 

TABLE 5—CY 2018 CASE-MIX PAYMENT WEIGHTS

Pay group Description 

Clinical and 

functional 

levels 

(1 = Low; 

2 = Medium; 

3 = High) 

CY 2018 

weight 

10111 ................ 1st and 2nd Episodes, 0 to 5 Therapy Visits ........................................................................... C1F1S1 0.5595 

10112 ................ 1st and 2nd Episodes, 6 Therapy Visits .................................................................................. C1F1S2 0.6911 

10113 ................ 1st and 2nd Episodes, 7 to 9 Therapy Visits ........................................................................... C1F1S3 0.8227 

10114 ................ 1st and 2nd Episodes, 10 Therapy Visits ................................................................................ C1F1S4 0.9543 

10115 ................ 1st and 2nd Episodes, 11 to 13 Therapy Visits ....................................................................... C1F1S5 1.0859 

10121 ................ 1st and 2nd Episodes, 0 to 5 Therapy Visits ........................................................................... C1F2S1 0.6640 

10122 ................ 1st and 2nd Episodes, 6 Therapy Visits .................................................................................. C1F2S2 0.7832 

10123 ................ 1st and 2nd Episodes, 7 to 9 Therapy Visits ........................................................................... C1F2S3 0.9025 

10124 ................ 1st and 2nd Episodes, 10 Therapy Visits ................................................................................ C1F2S4 1.0217 

10125 ................ 1st and 2nd Episodes, 11 to 13 Therapy Visits ....................................................................... C1F2S5 1.1409 

10131 ................ 1st and 2nd Episodes, 0 to 5 Therapy Visits ........................................................................... C1F3S1 0.7139 

10132 ................ 1st and 2nd Episodes, 6 Therapy Visits .................................................................................. C1F3S2 0.8302 

10133 ................ 1st and 2nd Episodes, 7 to 9 Therapy Visits ........................................................................... C1F3S3 0.9466 

10134 ................ 1st and 2nd Episodes, 10 Therapy Visits ................................................................................ C1F3S4 1.0629 

10135 ................ 1st and 2nd Episodes, 11 to 13 Therapy Visits ....................................................................... C1F3S5 1.1792 

10211 ................ 1st and 2nd Episodes, 0 to 5 Therapy Visits ........................................................................... C2F1S1 0.5948 

10212 ................ 1st and 2nd Episodes, 6 Therapy Visits .................................................................................. C2F1S2 0.7325 

10213 ................ 1st and 2nd Episodes, 7 to 9 Therapy Visits ........................................................................... C2F1S3 0.8703 

10214 ................ 1st and 2nd Episodes, 10 Therapy Visits ................................................................................ C2F1S4 1.0080 

10215 ................ 1st and 2nd Episodes, 11 to 13 Therapy Visits ....................................................................... C2F1S5 1.1457 

10221 ................ 1st and 2nd Episodes, 0 to 5 Therapy Visits ........................................................................... C2F2S1 0.6994 

10222 ................ 1st and 2nd Episodes, 6 Therapy Visits .................................................................................. C2F2S2 0.8247 

10223 ................ 1st and 2nd Episodes, 7 to 9 Therapy Visits ........................................................................... C2F2S3 0.9500 

10224 ................ 1st and 2nd Episodes, 10 Therapy Visits ................................................................................ C2F2S4 1.0753 

10225 ................ 1st and 2nd Episodes, 11 to 13 Therapy Visits ....................................................................... C2F2S5 1.2007 

10231 ................ 1st and 2nd Episodes, 0 to 5 Therapy Visits ........................................................................... C2F3S1 0.7493 

10232 ................ 1st and 2nd Episodes, 6 Therapy Visits .................................................................................. C2F3S2 0.8717 

10233 ................ 1st and 2nd Episodes, 7 to 9 Therapy Visits ........................................................................... C2F3S3 0.9941 

10234 ................ 1st and 2nd Episodes, 10 Therapy Visits ................................................................................ C2F3S4 1.1166 

10235 ................ 1st and 2nd Episodes, 11 to 13 Therapy Visits ....................................................................... C2F3S5 1.2390 

10311 ................ 1st and 2nd Episodes, 0 to 5 Therapy Visits ........................................................................... C3F1S1 0.6374 

10312 ................ 1st and 2nd Episodes, 6 Therapy Visits .................................................................................. C3F1S2 0.7902 

10313 ................ 1st and 2nd Episodes, 7 to 9 Therapy Visits ........................................................................... C3F1S3 0.9429 

10314 ................ 1st and 2nd Episodes, 10 Therapy Visits ................................................................................ C3F1S4 1.0957 

10315 ................ 1st and 2nd Episodes, 11 to 13 Therapy Visits ....................................................................... C3F1S5 1.2484 

10321 ................ 1st and 2nd Episodes, 0 to 5 Therapy Visits ........................................................................... C3F2S1 0.7420 

10322 ................ 1st and 2nd Episodes, 6 Therapy Visits .................................................................................. C3F2S2 0.8823 

10323 ................ 1st and 2nd Episodes, 7 to 9 Therapy Visits ........................................................................... C3F2S3 1.0227 

10324 ................ 1st and 2nd Episodes, 10 Therapy Visits ................................................................................ C3F2S4 1.1630 

10325 ................ 1st and 2nd Episodes, 11 to 13 Therapy Visits ....................................................................... C3F2S5 1.3034 

10331 ................ 1st and 2nd Episodes, 0 to 5 Therapy Visits ........................................................................... C3F3S1 0.7919 

10332 ................ 1st and 2nd Episodes, 6 Therapy Visits .................................................................................. C3F3S2 0.9293 

10333 ................ 1st and 2nd Episodes, 7 to 9 Therapy Visits ........................................................................... C3F3S3 1.0668 

10334 ................ 1st and 2nd Episodes, 10 Therapy Visits ................................................................................ C3F3S4 1.2042 

10335 ................ 1st and 2nd Episodes, 11 to 13 Therapy Visits ....................................................................... C3F3S5 1.3417 

21111 ................ 1st and 2nd Episodes, 14 to 15 Therapy Visits ....................................................................... C1F1S1 1.2176 

21112 ................ 1st and 2nd Episodes, 16 to 17 Therapy Visits ....................................................................... C1F1S2 1.3807 

21113 ................ 1st and 2nd Episodes, 18 to 19 Therapy Visits ....................................................................... C1F1S3 1.5439 

21121 ................ 1st and 2nd Episodes, 14 to 15 Therapy Visits ....................................................................... C1F2S1 1.2601 

21122 ................ 1st and 2nd Episodes, 16 to 17 Therapy Visits ....................................................................... C1F2S2 1.4213 

21123 ................ 1st and 2nd Episodes, 18 to 19 Therapy Visits ....................................................................... C1F2S3 1.5826 

21131 ................ 1st and 2nd Episodes, 14 to 15 Therapy Visits ....................................................................... C1F3S1 1.2955 

21132 ................ 1st and 2nd Episodes, 16 to 17 Therapy Visits ....................................................................... C1F3S2 1.4600 

21133 ................ 1st and 2nd Episodes, 18 to 19 Therapy Visits ....................................................................... C1F3S3 1.6244 

21211 ................ 1st and 2nd Episodes, 14 to 15 Therapy Visits ....................................................................... C2F1S1 1.2835 

21212 ................ 1st and 2nd Episodes, 16 to 17 Therapy Visits ....................................................................... C2F1S2 1.4598 

21213 ................ 1st and 2nd Episodes, 18 to 19 Therapy Visits ....................................................................... C2F1S3 1.6361 

21221 ................ 1st and 2nd Episodes, 14 to 15 Therapy Visits ....................................................................... C2F2S1 1.3260 

21222 ................ 1st and 2nd Episodes, 16 to 17 Therapy Visits ....................................................................... C2F2S2 1.5004 

21223 ................ 1st and 2nd Episodes, 18 to 19 Therapy Visits ....................................................................... C2F2S3 1.6748 

21231 ................ 1st and 2nd Episodes, 14 to 15 Therapy Visits ....................................................................... C2F3S1 1.3614 

21232 ................ 1st and 2nd Episodes, 16 to 17 Therapy Visits ....................................................................... C2F3S2 1.5390 

21233 ................ 1st and 2nd Episodes, 18 to 19 Therapy Visits ....................................................................... C2F3S3 1.7166 

21311 ................ 1st and 2nd Episodes, 14 to 15 Therapy Visits ....................................................................... C3F1S1 1.4012 

21312 ................ 1st and 2nd Episodes, 16 to 17 Therapy Visits ....................................................................... C3F1S2 1.6188 

21313 ................ 1st and 2nd Episodes, 18 to 19 Therapy Visits ....................................................................... C3F1S3 1.8364 

21321 ................ 1st and 2nd Episodes, 14 to 15 Therapy Visits ....................................................................... C3F2S1 1.4437 

21322 ................ 1st and 2nd Episodes, 16 to 17 Therapy Visits ....................................................................... C3F2S2 1.6594 


asabaliauskas on DSKBBXCHB2PROD with RULES
51688 Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 

TABLE 5—CY 2018 CASE-MIX PAYMENT WEIGHTS—Continued 

Pay group Description 

Clinical and 

functional 

levels 

(1 = Low; 

2 = Medium; 

3 = High) 

CY 2018 

weight 

21323 ................ 1st and 2nd Episodes, 18 to 19 Therapy Visits ....................................................................... C3F2S3 1.8751 

21331 ................ 1st and 2nd Episodes, 14 to 15 Therapy Visits ....................................................................... C3F3S1 1.4791 

21332 ................ 1st and 2nd Episodes, 16 to 17 Therapy Visits ....................................................................... C3F3S2 1.6981 

21333 ................ 1st and 2nd Episodes, 18 to 19 Therapy Visits ....................................................................... C3F3S3 1.9170 

22111 ................ 3rd+ Episodes, 14 to 15 Therapy Visits .................................................................................. C1F1S1 1.2328 

22112 ................ 3rd+ Episodes, 16 to 17 Therapy Visits .................................................................................. C1F1S2 1.3909 

22113 ................ 3rd+ Episodes, 18 to 19 Therapy Visits .................................................................................. C1F1S3 1.5489 

22121 ................ 3rd+ Episodes, 14 to 15 Therapy Visits .................................................................................. C1F2S1 1.2619 

22122 ................ 3rd+ Episodes, 16 to 17 Therapy Visits .................................................................................. C1F2S2 1.4225 

22123 ................ 3rd+ Episodes, 18 to 19 Therapy Visits .................................................................................. C1F2S3 1.5832 

22131 ................ 3rd+ Episodes, 14 to 15 Therapy Visits .................................................................................. C1F3S1 1.3088 

22132 ................ 3rd+ Episodes, 16 to 17 Therapy Visits .................................................................................. C1F3S2 1.4688 

22133 ................ 3rd+ Episodes, 18 to 19 Therapy Visits .................................................................................. C1F3S3 1.6288 

22211 ................ 3rd++ Episodes, 14 to 15 Therapy Visits ................................................................................ C2F1S1 1.2860 

22212 ................ 3rd+ Episodes, 16 to 17 Therapy Visits .................................................................................. C2F1S2 1.4615 

22213 ................ 3rd+ Episodes, 18 to 19 Therapy Visits .................................................................................. C2F1S3 1.6369 

22221 ................ 3rd+ Episodes, 14 to 15 Therapy Visits .................................................................................. C2F2S1 1.3151 

22222 ................ 3rd+ Episodes, 16 to 17 Therapy Visits .................................................................................. C2F2S2 1.4931 

22223 ................ 3rd+ Episodes, 18 to 19 Therapy Visits .................................................................................. C2F2S3 1.6712 

22231 ................ 3rd+ Episodes, 14 to 15 Therapy Visits .................................................................................. C2F3S1 1.3620 

22232 ................ 3rd+ Episodes, 16 to 17 Therapy Visits .................................................................................. C2F3S2 1.5394 

22233 ................ 3rd+ Episodes, 18 to 19 Therapy Visits .................................................................................. C2F3S3 1.7168 

22311 ................ 3rd+ Episodes, 14 to 15 Therapy Visits .................................................................................. C3F1S1 1.4951 

22312 ................ 3rd+ Episodes, 16 to 17 Therapy Visits .................................................................................. C3F1S2 1.6814 

22313 ................ 3rd+ Episodes, 18 to 19 Therapy Visits .................................................................................. C3F1S3 1.8677 

22321 ................ 3rd+ Episodes, 14 to 15 Therapy Visits .................................................................................. C3F2S1 1.5241 

22322 ................ 3rd+ Episodes, 16 to 17 Therapy Visits .................................................................................. C3F2S2 1.7130 

22323 ................ 3rd+ Episodes, 18 to 19 Therapy Visits .................................................................................. C3F2S3 1.9019 

22331 ................ 3rd+ Episodes, 14 to 15 Therapy Visits .................................................................................. C3F3S1 1.5710 

22332 ................ 3rd+ Episodes, 16 to 17 Therapy Visits .................................................................................. C3F3S2 1.7593 

22333 ................ 3rd+ Episodes, 18 to 19 Therapy Visits .................................................................................. C3F3S3 1.9476 

30111 ................ 3rd+ Episodes, 0 to 5 Therapy Visits ...................................................................................... C1F1S1 0.4557 

30112 ................ 3rd+ Episodes, 6 Therapy Visits .............................................................................................. C1F1S2 0.6111 

30113 ................ 3rd+ Episodes, 7 to 9 Therapy Visits ...................................................................................... C1F1S3 0.7666 

30114 ................ 3rd+ Episodes, 10 Therapy Visits ............................................................................................ C1F1S4 0.9220 

30115 ................ 3rd+ Episodes, 11 to 13 Therapy Visits .................................................................................. C1F1S5 1.0774 

30121 ................ 3rd+ Episodes, 0 to 5 Therapy Visits ...................................................................................... C1F2S1 0.5407 

30122 ................ 3rd+ Episodes, 6 Therapy Visits .............................................................................................. C1F2S2 0.6850 

30123 ................ 3rd+ Episodes, 7 to 9 Therapy Visits ...................................................................................... C1F2S3 0.8292 

30124 ................ 3rd+ Episodes, 10 Therapy Visits ............................................................................................ C1F2S4 0.9734 

30125 ................ 3rd+ Episodes, 11 to 13 Therapy Visits .................................................................................. C1F2S5 1.1177 

30131 ................ 3rd+ Episodes, 0 to 5 Therapy Visits ...................................................................................... C1F3S1 0.5856 

30132 ................ 3rd+ Episodes, 6 Therapy Visits .............................................................................................. C1F3S2 0.7303 

30133 ................ 3rd+ Episodes, 7 to 9 Therapy Visits ...................................................................................... C1F3S3 0.8749 

30134 ................ 3rd+ Episodes, 10 Therapy Visits ............................................................................................ C1F3S4 1.0195 

30135 ................ 3rd+ Episodes, 11 to 13 Therapy Visits .................................................................................. C1F3S5 1.1642 

30211 ................ 3rd+ Episodes, 0 to 5 Therapy Visits ...................................................................................... C2F1S1 0.4802 

30212 ................ 3rd+ Episodes, 6 Therapy Visits .............................................................................................. C2F1S2 0.6414 

30213 ................ 3rd+ Episodes, 7 to 9 Therapy Visits ...................................................................................... C2F1S3 0.8025 

30214 ................ 3rd+ Episodes, 10 Therapy Visits ............................................................................................ C2F1S4 0.9637 

30215 ................ 3rd+ Episodes, 11 to 13 Therapy Visits .................................................................................. C2F1S5 1.1249 

30221 ................ 3rd+ Episodes, 0 to 5 Therapy Visits ...................................................................................... C2F2S1 0.5652 

30222 ................ 3rd+ Episodes, 6 Therapy Visits .............................................................................................. C2F2S2 0.7152 

30223 ................ 3rd+ Episodes, 7 to 9 Therapy Visits ...................................................................................... C2F2S3 0.8652 

30224 ................ 3rd+ Episodes, 10 Therapy Visits ............................................................................................ C2F2S4 1.0151 

30225 ................ 3rd+ Episodes, 11 to 13 Therapy Visits .................................................................................. C2F2S5 1.1651 

30231 ................ 3rd+ Episodes, 0 to 5 Therapy Visits ...................................................................................... C2F3S1 0.6101 

30232 ................ 3rd+ Episodes, 6 Therapy Visits .............................................................................................. C2F3S2 0.7605 

30233 ................ 3rd+ Episodes, 7 to 9 Therapy Visits ...................................................................................... C2F3S3 0.9109 

30234 ................ 3rd+ Episodes, 10 Therapy Visits ............................................................................................ C2F3S4 1.0612 

30235 ................ 3rd+ Episodes, 11 to 13 Therapy Visits .................................................................................. C2F3S5 1.2116 

30311 ................ 3rd+ Episodes, 0 to 5 Therapy Visits ...................................................................................... C3F1S1 0.5936 

30312 ................ 3rd+ Episodes, 6 Therapy Visits .............................................................................................. C3F1S2 0.7739 

30313 ................ 3rd+ Episodes, 7 to 9 Therapy Visits ...................................................................................... C3F1S3 0.9542 

30314 ................ 3rd+ Episodes, 10 Therapy Visits ............................................................................................ C3F1S4 1.1345 

30315 ................ 3rd+ Episodes, 11 to 13 Therapy Visits .................................................................................. C3F1S5 1.3148 

30321 ................ 3rd+ Episodes, 0 to 5 Therapy Visits ...................................................................................... C3F2S1 0.6786 

30322 ................ 3rd+ Episodes, 6 Therapy Visits .............................................................................................. C3F2S2 0.8477 


asabaliauskas on DSKBBXCHB2PROD with RULES
Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 51689 

TABLE 5—CY 2018 CASE-MIX PAYMENT WEIGHTS—Continued 

Pay group Description 

Clinical and 

functional 

levels 

(1 = Low; 

2 = Medium; 

3 = High) 

CY 2018 

weight 

30323 ................ 3rd+ Episodes, 7 to 9 Therapy Visits ...................................................................................... C3F2S3 1.0168 

30324 ................ 3rd+ Episodes, 10 Therapy Visits ............................................................................................ C3F2S4 1.1859 

30325 ................ 3rd+ Episodes, 11 to 13 Therapy Visits .................................................................................. C3F2S5 1.3550 

30331 ................ 3rd+ Episodes, 0 to 5 Therapy Visits ...................................................................................... C3F3S1 0.7235 

30332 ................ 3rd+ Episodes, 6 Therapy Visits .............................................................................................. C3F3S2 0.8930 

30333 ................ 3rd+ Episodes, 7 to 9 Therapy Visits ...................................................................................... C3F3S3 1.0625 

30334 ................ 3rd+ Episodes, 10 Therapy Visits ............................................................................................ C3F3S4 1.2320 

30335 ................ 3rd+ Episodes, 11 to 13 Therapy Visits .................................................................................. C3F3S5 1.4015 

40111 ................ All Episodes, 20+ Therapy Visits ............................................................................................. C1F1S1 1.7070 

40121 ................ All Episodes, 20+ Therapy Visits ............................................................................................. C1F2S1 1.7438 

40131 ................ All Episodes, 20+ Therapy Visits ............................................................................................. C1F3S1 1.7888 

40211 ................ All Episodes, 20+ Therapy Visits ............................................................................................. C2F1S1 1.8124 

40221 ................ All Episodes, 20+ Therapy Visits ............................................................................................. C2F2S1 1.8492 

40231 ................ All Episodes, 20+ Therapy Visits ............................................................................................. C2F3S1 1.8942 

40311 ................ All Episodes, 20+ Therapy Visits ............................................................................................. C3F1S1 2.0540 

40321 ................ All Episodes, 20+ Therapy Visits ............................................................................................. C3F2S1 2.0908 

40331 ................ All Episodes, 20+ Therapy Visits ............................................................................................. C3F3S1 2.1359 

To ensure the changes to the HH PPS 

case-mix weights are implemented in a 

budget neutral manner, we then apply a 

case-mix budget neutrality factor to the 

CY 2018 national, standardized 60-day 

episode payment rate (see section 

III.C.3. of this final rule). The case-mix 

budget neutrality factor is calculated as 

the ratio of total payments when the CY 

2018 HH PPS case-mix weights 

(developed using CY 2016 home health 

claims data) are applied to CY 2016 

utilization (claims) data to total 

payments when CY 2017 HH PPS casemix weights (developed using CY 2015 

home health claims data) are applied to 

CY 2016 utilization data. This produces 

a case-mix budget neutrality factor for 

CY 2018 of 1.0160. 

The following is a summary of the 

comments and our responses to 

comments on the CY 2018 case-mix 

weights: 

Comment: A few commenters stated 

that CMS did not provide sufficient 

transparency of the details and methods 

used to recalibrate the HH PPS case-mix 

weights in the proposed rule. In 

addition, commenters stated that CMS 

provided little justification for 

recalibrating the case-mix weights just 1 

year following the recalibration of casemix weights in CY 2017, 2 years since 

the recalibration in 2016, and 5 years 

since the recalibration for the CY 2012 

HH PPS final rule. The commenters 

noted that they opposed the 

recalibration of the case weights for CY 

2018, but supported the budget 

neutrality adjustment to account for the 

recalibrated case-mix weights if CMS 

finalizes the recalibration. 

Response: As stated in the CY 2018 

HH PPS proposed rule (82 FR 35282), 

the methodology used to recalibrate the 

weights is identical to the methodology 

used in the CY 2012 recalibration except 

for the minor exceptions as noted in the 

CY 2015 HH PPS proposed and final 

rules (79 FR 38366 and 79 FR 66032, 

respectively). In the CY 2015 HH PPS 

final rule, we finalized annual 

recalibration and the methodology to be 

used for each year’s recalibration (79 FR 

66072). For more detail, we also 

encourage commenters to refer to the CY 

2012 HH PPS proposed and final rules 

(76 FR 40988 and 76 FR 68526, 

respectively) and the November 1, 2011 

‘‘Revision of the Case-Mix Weights for 

the HH PPS Report’’ on our home page 

at: https://www.cms.gov/center/

provider-Type/home-Health-AgencyHHA-Center.html for additional 

information about the recalibration 

methodology. 

We note that in comparing the final 

CY 2018 HH PPS case-mix weights (see 

Table 5) to the final CY 2015 HH PPS 

case-mix weights (79 FR 66062), the 

case-mix weights change very little, 

with most case-mix weights either 

increasing or decreasing by 1 to 2 

percent with no case-mix weights 

increasing by more than 3 percent or 

decreasing by more than 3 percent. The 

aggregate decreases in the case-mix 

weights are offset by the case-mix 

budget neutrality factor, which is 

applied to the national, standardized 60- 

day episode payment rate. In other 

words, although the case-mix weights 

themselves may increase or decrease 

from year-to-year, we correspondingly 

offset any estimated increases or 

decreases in total payments under the 

HH PPS, as a result of the case-mix 

recalibration, by applying a budget 

neutrality factor to the national, 

standardized 60-day episode payment 

rate. For CY 2018, the case-mix budget 

neutrality factor will be 1.0160 as 

described previously. The recalibration 

of the case-mix weights is not intended 

to increase or decrease overall HH PPS 

payments, but rather is used to update 

the relative differences in resource use 

amongst the 153 groups in the HH PPS 

case-mix system and maintain the level 

of aggregate payments before 

application of any other adjustments. 

We will continue to monitor the 

performance of any finalized case-mix 

model, and will make changes to it as 

necessary. 

Final Decision: We are finalizing the 

recalibrated scores for the case-mix 

adjustment variables, clinical and 

functional thresholds, payment 

regression model, and case-mix weights 

in Tables 2 through 5. For this final rule, 

the CY 2018 scores for the case-mix 

variables, the clinical and functional 

thresholds, and the case-mix weights 

were developed using complete CY 

2016 claims data as of August 17, 2017. 

We note that we finalized the 

recalibration methodology and the 

proposal to annually recalibrate the HH 

PPS case-mix weights in the CY 2015 

HH PPS final rule (79 FR 66072). No 

additional proposals were made with 

regard to the recalibration methodology 

in the CY 2018 HH PPS proposed rule. 


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51690 Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 

C. CY 2018 Home Health Payment Rate 

Update 

1. CY 2018 Home Health Market Basket 

Update 

Section 1895(b)(3)(B) of the Act 

requires that the standard prospective 

payment amounts for CY 2018 be 

increased by a factor equal to the 

applicable HH market basket update for 

those HHAs that submit quality data as 

required by the Secretary. The home 

health market basket was rebased and 

revised in CY 2013. A detailed 

description of how we derive the HHA 

market basket is available in the CY 

2013 HH PPS final rule (77 FR 67080 

through 67090). 

Section 1895(b)(3)(B)(vi) of the Act, 

requires that, in CY 2015 (and in 

subsequent calendar years, except CY 

2018 (under section 411(c) of the 

Medicare Access and CHIP 

Reauthorization Act of 2015 (MACRA) 

(Pub. L. 114–10, enacted April 16, 

2015)), the market basket percentage 

under the HHA prospective payment 

system as described in section 

1895(b)(3)(B) of the Act be annually 

adjusted by changes in economy-wide 

productivity. Section 

1886(b)(3)(B)(xi)(II) of the Act defines 

the productivity adjustment to be equal 

to the 10-year moving average of change 

in annual economy-wide private 

nonfarm business multifactor 

productivity (MFP) (as projected by the 

Secretary for the 10-year period ending 

with the applicable fiscal year, calendar 

year, cost reporting period, or other 

annual period) (the ‘‘MFP adjustment’’). 

The Bureau of Labor Statistics (BLS) is 

the agency that publishes the official 

measure of private nonfarm business 

MFP. Please see http://www.bls.gov/mfp 

to obtain the BLS historical published 

MFP data. 

Prior to the enactment of the MACRA, 

which amended section 1895(b)(3)(B) of 

the Act, the home health update 

percentage for CY 2018 would have 

been based on the estimated home 

health market basket update of 2.5 

percent (based on IHS Global Inc.’s 

third-quarter 2017 forecast with 

historical data through second-quarter 

2017). Due to the requirements specified 

at section 1895(b)(3)(B)(vi) of the Act 

prior to the enactment of MACRA, the 

estimated CY 2018 home health market 

basket update of 2.5 percent would have 

been reduced by a MFP adjustment as 

mandated by the Affordable Care Act 

(currently estimated to be 0.6 percentage 

point for CY 2018). In effect, the home 

health payment update percentage for 

CY 2018 would have been 1.9 percent. 

However, section 411(c) of the MACRA 

amended section 1895(b)(3)(B) of the 

Act, such that, for home health 

payments for CY 2018, the market 

basket percentage increase is required to 

be 1 percent. 

Section 1895(b)(3)(B) of the Act 

requires that the home health update be 

decreased by 2 percentage points for 

those HHAs that do not submit quality 

data as required by the Secretary. For 

HHAs that do not submit the required 

quality data for CY 2018, the home 

health payment update will be ¥1 

percent (1 percent minus 2 percentage 

points). 

2. CY 2018 Home Health Wage Index 

Sections 1895(b)(4)(A)(ii) and (b)(4)(C) 

of the Act require the Secretary to 

provide appropriate adjustments to the 

proportion of the payment amount 

under the HH PPS that account for area 

wage differences, using adjustment 

factors that reflect the relative level of 

wages and wage-related costs applicable 

to the furnishing of HH services. Since 

the inception of the HH PPS, we have 

used inpatient hospital wage data in 

developing a wage index to be applied 

to HH payments. We proposed to 

continue this practice for CY 2018, as 

we continue to believe that, in the 

absence of HH-specific wage data, using 

inpatient hospital wage data is 

appropriate and reasonable for the HH 

PPS. Specifically, we proposed to 

continue to use the pre-floor, prereclassified hospital wage index as the 

wage adjustment to the labor portion of 

the HH PPS rates. For CY 2018, the 

updated wage data are for hospital cost 

reporting periods beginning on or after 

October 1, 2013, and before October 1, 

2014 (FY 2014 cost report data). We 

apply the appropriate wage index value 

to the labor portion of the HH PPS rates 

based on the site of service for the 

beneficiary (defined by section 1861(m) 

of the Act as the beneficiary’s place of 

residence). 

To address those geographic areas in 

which there are no inpatient hospitals, 

and thus, no hospital wage data on 

which to base the calculation of the CY 

2018 HH PPS wage index, we proposed 

to continue to use the same 

methodology discussed in the CY 2007 

HH PPS final rule (71 FR 65884) to 

address those geographic areas in which 

there are no inpatient hospitals. For 

rural areas that do not have inpatient 

hospitals, we proposed to use the 

average wage index from all contiguous 

Core Based Statistical Areas (CBSAs) as 

a reasonable proxy. Currently, the only 

rural area without a hospital from which 

hospital wage data could be derived is 

Puerto Rico. However, for rural Puerto 

Rico, we do not apply this methodology 

due to the distinct economic 

circumstances that exist there (for 

example, due to the close proximity to 

one another of almost all of Puerto 

Rico’s various urban and non-urban 

areas, this methodology would produce 

a wage index for rural Puerto Rico that 

is higher than that in half of its urban 

areas). Instead, we proposed to continue 

to use the most recent wage index 

previously available for that area. For 

urban areas without inpatient hospitals, 

we use the average wage index of all 

urban areas within the state as a 

reasonable proxy for the wage index for 

that CBSA. For CY 2018, the only urban 

area without inpatient hospital wage 

data is Hinesville, GA (CBSA 25980). 

On February 28, 2013, OMB issued 

Bulletin No. 13–01, announcing 

revisions to the delineations of MSAs, 

Micropolitan Statistical Areas, and 

CBSAs, and guidance on uses of the 

delineation of these areas. In the CY 

2015 HH PPS final rule (79 FR 66085 

through 66087), we adopted the OMB’s 

new area delineations using a 1-year 

transition. The most recent bulletin (No. 

15–01) concerning the revised 

delineations was published by the OMB 

on July 15, 2015. 

The CY 2018 wage index is available 

on the CMS Web site at http://

www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/HomeHealthPPS/

Home-Health-Prospective-PaymentSystem-Regulations-and-Notices.html. 

3. CY 2018 Annual Payment Update 

a. Background 

The Medicare HH PPS has been in 

effect since October 1, 2000. As set forth 

in the July 3, 2000 final rule (65 FR 

41128), the base unit of payment under 

the Medicare HH PPS is a national, 

standardized 60-day episode payment 

rate. As set forth in § 484.220, we adjust 

the national, standardized 60-day 

episode payment rate by a case-mix 

relative weight and a wage index value 

based on the site of service for the 

beneficiary. 

To provide appropriate adjustments to 

the proportion of the payment amount 

under the HH PPS to account for area 

wage differences, we apply the 

appropriate wage index value to the 

labor portion of the HH PPS rates. The 

labor-related share of the case-mix 

adjusted 60-day episode rate will 

continue to be 78.535 percent and the 

non-labor-related share will continue to 

be 21.465 percent as set out in the CY 

2013 HH PPS final rule (77 FR 67068). 

The CY 2018 HH PPS rates use the same 

case-mix methodology as set forth in the 

CY 2008 HH PPS final rule with 

comment period (72 FR 49762) and will 

be adjusted as described in section III.B. 


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Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 51691 

of this final rule. The following are the 

steps we take to compute the case-mix 

and wage-adjusted 60-day episode rate: 

(1) Multiply the national 60-day 

episode rate by the patient’s applicable 

case-mix weight. 

(2) Divide the case-mix adjusted 

amount into a labor (78.535 percent) 

and a non-labor portion (21.465 

percent). 

(3) Multiply the labor portion by the 

applicable wage index based on the site 

of service of the beneficiary. 

(4) Add the wage-adjusted portion to 

the non-labor portion, yielding the casemix and wage adjusted 60-day episode 

rate, subject to any additional applicable 

adjustments. 

In accordance with section 

1895(b)(3)(B) of the Act, we proposed 

the annual update of the HH PPS rates. 

Section 484.225 sets forth the specific 

annual percentage update methodology. 

In accordance with § 484.225(i), for a 

HHA that does not submit HH quality 

data, as specified by the Secretary, the 

unadjusted national prospective 60-day 

episode rate is equal to the rate for the 

previous calendar year increased by the 

applicable HH market basket index 

amount minus 2 percentage points. Any 

reduction of the percentage change will 

apply only to the calendar year involved 

and will not be considered in 

computing the prospective payment 

amount for a subsequent calendar year. 

Medicare pays the national, 

standardized 60-day case-mix and wageadjusted episode payment on a split 

percentage payment approach. The split 

percentage payment approach includes 

an initial percentage payment and a 

final percentage payment as set forth in 

§ 484.205(b)(1) and (b)(2). We may base 

the initial percentage payment on the 

submission of a request for anticipated 

payment (RAP) and the final percentage 

payment on the submission of the claim 

for the episode, as discussed in § 409.43. 

The claim for the episode that the HHA 

submits for the final percentage 

payment determines the total payment 

amount for the episode and whether we 

make an applicable adjustment to the 

60-day case-mix and wage-adjusted 

episode payment. The end date of the 

60-day episode as reported on the claim 

determines which calendar year rates 

Medicare will use to pay the claim. 

We may also adjust the 60-day casemix and wage-adjusted episode 

payment based on the information 

submitted on the claim to reflect the 

following: 

• A low-utilization payment 

adjustment (LUPA) is provided on a pervisit basis as set forth in §§ 484.205(c) 

and 484.230. 

• A partial episode payment (PEP) 

adjustment as set forth in §§ 484.205(d) 

and 484.235. 

• An outlier payment as set forth in 

§§ 484.205(e) and 484.240. 

b. CY 2018 National, Standardized 60- 

Day Episode Payment Rate 

Section 1895(b)(3)(A)(i) of the Act 

requires that the 60-day episode base 

rate and other applicable amounts be 

standardized in a manner that 

eliminates the effects of variations in 

relative case-mix and area wage 

adjustments among different home 

health agencies in a budget neutral 

manner. To determine the CY 2018 

national, standardized 60-day episode 

payment rate, we apply a wage index 

budget neutrality factor; a case-mix 

budget neutrality factor described in 

section III.B. of this final rule; a 

reduction of 0.97 percent to account for 

nominal case-mix growth from 2012 to 

2014, as finalized in the CY 2016 HH 

PPS final rule (80 FR 68646); and the 

home health payment update percentage 

discussed in section III.C.1 of this final 

rule. 

To calculate the wage index budget 

neutrality factor, we simulated total 

payments for non-LUPA episodes using 

the CY 2018 wage index and compared 

it to our simulation of total payments for 

non-LUPA episodes using the CY 2017 

wage index. By dividing the total 

payments for non-LUPA episodes using 

the CY 2018 wage index by the total 

payments for non-LUPA episodes using 

the CY 2017 wage index, we obtain a 

wage index budget neutrality factor of 

1.0004. We will apply the wage index 

budget neutrality factor of 1.0004 to the 

calculation of the CY 2018 national, 

standardized 60-day episode rate. 

As discussed in section III.B. of the 

proposed rule, to ensure the changes to 

the case-mix weights are implemented 

in a budget neutral manner, we 

proposed to apply a case-mix weight 

budget neutrality factor to the CY 2018 

national, standardized 60-day episode 

payment rate. The case-mix weight 

budget neutrality factor is calculated as 

the ratio of total payments when CY 

2018 case-mix weights are applied to CY 

2016 utilization (claims) data to total 

payments when CY 2017 case-mix 

weights are applied to CY 2016 

utilization data. The case-mix budget 

neutrality factor for CY 2018 is 1.0160 

as described in section III.B of this final 

rule. 

Next, we apply a reduction of 0.97 

percent to the national, standardized 60- 

day payment rate for CY 2018 to 

account for nominal case-mix growth 

between CY 2012 and CY 2014. Lastly, 

we will update the payment rates by the 

CY 2018 home health payment update 

percentage of 1 percent as mandated by 

section 1895(b)(3)(B)(iii) of the Act. The 

CY 2018 national, standardized 60-day 

episode payment rate is calculated in 

Table 6. 

TABLE 6—CY 2018 60-DAY NATIONAL, STANDARDIZED 60-DAY EPISODE PAYMENT AMOUNT

CY 2017 national, standardized 60-day episode payment 

Wage index 

budget 

neutrality 

factor 

Case-mix 

weights 

budget 

neutrality 

factor 

Nominal 

case-mix 

growth 

adjustment 

(1–0.0097) 

CY 2018 HH 

payment 

update 

CY 2018 

national, 

standardized 

60-day 

episode 

payment 

$2,989.97 ............................................................................. × 1.0004 × 1.0160 × 0.9903 × 1.01 $3,039.64 

The CY 2018 national, standardized 

60-day episode payment rate for an 

HHA that does not submit the required 

quality data is updated by the CY 2018 

home health payment update of 1 

percent minus 2 percentage points and 

is shown in Table 7. 


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51692 Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 

TABLE 7—CY 2017 NATIONAL, STANDARDIZED 60-DAY EPISODE PAYMENT AMOUNT FOR HHAS THAT DO NOT SUBMIT

THE QUALITY DATA

CY 2017 national, standardized 60-day episode payment 

Wage index 

budget neutrality 

factor 

Case-mix 

weights 

budget 

neutrality 

factor 

Nominal 

case-mix 

growth 

adjustment 

(1–0.0097) 

CY 2018 HH 

payment 

update 

CY 2018 

national, 

standardized 

60-day 

episode 

payment 

$2,989.97 ............................................................................. × 1.0004 × 1.0160 × 0.9903 × 0.99 $2,979.45 

c. CY 2018 National Per-Visit Rates 

The national per-visit rates are used to 

pay LUPAs (episodes with four or fewer 

visits) and are also used to compute 

imputed costs in outlier calculations. 

The per-visit rates are paid by type of 

visit or HH discipline. The six HH 

disciplines are as follows: 

• Home health aide (HH aide). 

• Medical Social Services (MSS). 

• Occupational therapy (OT). 

• Physical therapy (PT). 

• Skilled nursing (SN). 

• Speech-language pathology (SLP). 

To calculate the CY 2018 national pervisit rates, we started with the CY 2017 

national per-visit rates. Then we applied 

a wage index budget neutrality factor to 

ensure budget neutrality for LUPA pervisit payments. We calculated the wage 

index budget neutrality factor by 

simulating total payments for LUPA 

episodes using the CY 2018 wage index 

and comparing it to simulated total 

payments for LUPA episodes using the 

CY 2017 wage index. By dividing the 

total payments for LUPA episodes using 

the CY 2018 wage index by the total 

payments for LUPA episodes using the 

CY 2017 wage index, we obtained a 

wage index budget neutrality factor of 

1.0010. We apply the wage index budget 

neutrality factor of 1.0010 in order to 

calculate the CY 2018 national per-visit 

rates. 

The LUPA per-visit rates are not 

calculated using case-mix weights. 

Therefore, there is no case-mix weights 

budget neutrality factor needed to 

ensure budget neutrality for LUPA 

payments. Lastly, the per-visit rates for 

each discipline are updated by the CY 

2018 home health payment update 

percentage of 1 percent. The national 

per-visit rates are adjusted by the wage 

index based on the site of service of the 

beneficiary. The per-visit payments for 

LUPAs are separate from the LUPA addon payment amount, which is paid for 

episodes that occur as the only episode 

or initial episode in a sequence of 

adjacent episodes. The CY 2018 national 

per-visit rates are shown in Tables 8 and 

9. 

TABLE 8—CY 2018 NATIONAL PER-VISIT PAYMENT AMOUNTS FOR HHAS THAT DO SUBMIT THE REQUIRED QUALITY

DATA

HH Discipline 

CY 2017 

per-visit 

payment 

Wage index 

budget 

neutrality 

factor 

CY 2018 

HH 

payment 

update 

CY 2018 

per-visit 

payment 

Home Health Aide ........................................................................................... $64.23 × 1.0010 × 1.01 $64.94 

Medical Social Services ................................................................................... 227.36 × 1.0010 × 1.01 229.86 

Occupational Therapy ...................................................................................... 156.11 × 1.0010 × 1.01 157.83 

Physical Therapy ............................................................................................. 155.05 × 1.0010 × 1.01 156.76 

Skilled Nursing ................................................................................................. 141.84 × 1.0010 × 1.01 143.40 

Speech-Language Pathology .......................................................................... 168.52 × 1.0010 × 1.01 170.38 

The CY 2018 per-visit payment rates 

for HHAs that do not submit the 

required quality data are updated by the 

CY 2018 HH payment update percentage 

of 1 percent minus 2 percentage points 

and are shown in Table 9. 

TABLE 9—CY 2018 NATIONAL PER-VISIT PAYMENT AMOUNTS FOR HHAS THAT DO NOT SUBMIT THE REQUIRED QUALITY

DATA

HH Discipline 

CY 2017 

per-visit 

rates 

Wage index 

budget 

neutrality 

factor 

CY 2018 

HH payment 

update minus 

2 percentage 

points 

CY 2018 

per-visit 

rates 

Home Health Aide ........................................................................................... $64.23 × 1.0010 × 0.99 $63.65 

Medical Social Services ................................................................................... 227.36 × 1.0010 × 0.99 225.31 

Occupational Therapy ...................................................................................... 156.11 × 1.0010 × 0.99 154.70 

Physical Therapy ............................................................................................. 155.05 × 1.0010 × 0.99 153.65 

Skilled Nursing ................................................................................................. 141.84 × 1.0010 × 0.99 140.56 

Speech-Language Pathology .......................................................................... 168.52 × 1.0010 × 0.99 167.00 


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Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 51693 

d. Low-Utilization Payment Adjustment 

(LUPA) Add-On Factors 

LUPA episodes that occur as the only 

episode or as an initial episode in a 

sequence of adjacent episodes are 

adjusted by applying an additional 

amount to the LUPA payment before 

adjusting for area wage differences. In 

the CY 2014 HH PPS final rule (78 FR 

72305), we changed the methodology for 

calculating the LUPA add-on amount by 

finalizing the use of three LUPA add-on 

factors: 1.8451 for SN; 1.6700 for PT; 

and 1.6266 for SLP. We multiply the 

per-visit payment amount for the first 

SN, PT, or SLP visit in LUPA episodes 

that occur as the only episode or an 

initial episode in a sequence of adjacent 

episodes by the appropriate factor to 

determine the LUPA add-on payment 

amount. For example, in the case of 

HHAs that do submit the required 

quality data, for LUPA episodes that 

occur as the only episode or an initial 

episode in a sequence of adjacent 

episodes, if the first skilled visit is SN, 

the payment for that visit will be 

$264.59 (1.8451 multiplied by $143.40), 

subject to area wage adjustment. 

e. CY 2018 Non-Routine Medical 

Supply (NRS) Payment Rates 

All medical supplies (routine and 

nonroutine) must be provided by the 

HHA while the patient is under a home 

health plan of care. Examples of 

supplies that can be considered nonroutine include dressings for wound 

care, I.V. supplies, ostomy supplies, 

catheters, and catheter supplies. 

Payments for NRS are computed by 

multiplying the relative weight for a 

particular severity level by the NRS 

conversion factor. To determine the CY 

2018 NRS conversion factor, we 

updated the CY 2017 NRS conversion 

factor ($52.50) by the CY 2018 home 

health payment update percentage of 1 

percent. We did not apply a 

standardization factor as the NRS 

payment amount calculated from the 

conversion factor is not wage or casemix adjusted when the final claim 

payment amount is computed. The NRS 

conversion factor for CY 2018 is shown 

in Table 10. 

TABLE 10—CY 2018 NRS CONVERSION FACTOR FOR HHAS THAT DO

SUBMIT THE REQUIRED QUALITY

DATA

CY 2017 

NRS 

conversion 

factor 

CY 2018 HH 

payment 

update 

CY 2018 NRS 

conversion 

factor 

$52.50 ....... × 1.01 $53.03 

Using the CY 2018 NRS conversion 

factor, the payment amounts for the six 

severity levels are shown in Table 11. 

TABLE 11—CY 2018 NRS PAYMENT AMOUNTS FOR HHAS THAT DO SUBMIT THE REQUIRED QUALITY DATA

Severity level Points 

(scoring) 

Relative 

weight 

CY 2018 NRS 

payment 

amounts 

1 ................................................................................................................................................... 0 ..................... 0.2698 $14.31 

2 ................................................................................................................................................... 1 to 14 ........... 0.9742 51.66 

3 ................................................................................................................................................... 15 to 27 ......... 2.6712 141.65 

4 ................................................................................................................................................... 28 to 48 ......... 3.9686 210.45 

5 ................................................................................................................................................... 49 to 98 ......... 6.1198 324.53 

6 ................................................................................................................................................... 99+ ................. 10.5254 558.16 

For HHAs that do not submit the 

required quality data, we updated the 

CY 2017 NRS conversion factor ($52.50) 

by the CY 2018 home health payment 

update percentage of 1 percent minus 2 

percentage points. The CY 2018 NRS 

conversion factor for HHAs that do not 

submit quality data is shown in Table 

12. 

TABLE 12—CY 2018 NRS CONVERSION FACTOR FOR HHAS THAT DO

NOT SUBMIT THE REQUIRED QUALITY DATA

CY 2017 

NRS 

conversion 

factor 

CY 2018 HH 

payment 

update 

percentage 

minus 2 

percentage 

points 

CY 2018 NRS 

conversion 

factor 

$52.50 ....... × 0.99 $51.98 

The payment amounts for the various 

severity levels based on the updated 

conversion factor for HHAs that do not 

submit quality data are calculated in 

Table 13. 

TABLE 13—CY 2018 NRS PAYMENT AMOUNTS FOR HHAS THAT DO NOT SUBMIT THE REQUIRED QUALITY DATA

Severity level Points 

(scoring) 

Relative 

weight 

CY 2018 NRS 

payment 

amounts 

1 ................................................................................................................................................... 0 ..................... 0.2698 $14.02 

2 ................................................................................................................................................... 1 to 14 ........... 0.9742 50.64 

3 ................................................................................................................................................... 15 to 27 ......... 2.6712 138.85 

4 ................................................................................................................................................... 28 to 48 ......... 3.9686 206.29 

5 ................................................................................................................................................... 49 to 98 ......... 6.1198 318.11 

6 ................................................................................................................................................... 99+ ................. 10.5254 547.11 


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51694 Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 

11See U.S. CONST. art. I, § 9 (‘‘No money shall 

be drawn from the Treasury, but in Consequence of 

Appropriations made by Law’’). 

f. Rural Add-On 

Section 421(a) of the MMA required, 

for HH services furnished in a rural area 

(as defined in section 1886(d)(2)(D) of 

the Act), for episodes or visits ending on 

or after April 1, 2004, and before April 

1, 2005, that the Secretary increase the 

payment amount that otherwise would 

have been made under section 1895 of 

the Act for the services by 5 percent. 

Section 5201 of the DRA amended 

section 421(a) of the MMA. The 

amended section 421(a) of the MMA 

required, for HH services furnished in a 

rural area (as defined in section 

1886(d)(2)(D) of the Act), on or after 

January 1, 2006, and before January 1, 

2007, that the Secretary increase the 

payment amount otherwise made under 

section 1895 of the Act for those 

services by 5 percent. 

Section 3131(c) of the Affordable Care 

Act amended section 421(a) of the MMA 

to provide an increase of 3 percent of 

the payment amount otherwise made 

under section 1895 of the Act for HH 

services furnished in a rural area (as 

defined in section 1886(d)(2)(D) of the 

Act), for episodes and visits ending on 

or after April 1, 2010, and before 

January 1, 2016. 

Section 210 of the MACRA amended 

section 421(a) of the MMA to extend the 

rural add-on by providing an increase of 

3 percent of the payment amount 

otherwise made under section 1895 of 

the Act for HH services provided in a 

rural area (as defined in section 

1886(d)(2)(D) of the Act), for episodes 

and visits ending before January 1, 2018. 

Therefore, for episodes and visits that 

end on or after January 1, 2018, a rural 

add-on payment will not apply. 

The following is a summary of the 

public comments received on the ‘‘CY 

2018 Home Health Payment Rate 

Update’’ proposals and our responses: 

Comment: Several commenters stated 

that they wanted CMS to rescind the 

nominal case-mix reduction for CY 

2018. Some commenters stated that 

implementation of the nominal case-mix 

reductions in 2016, 2017, and 2018 

violated the limits on payment 

reductions set out by the Congress, and 

urged CMS to adhere to the statutory 

limits on home health rate cuts. 

Commenters expressed concerns with 

the data and methodology used to 

develop the proposed case-mix cuts and 

stated that the annual recalibration may 

have eliminated any practice of 

assigning an inaccurate code to increase 

reimbursement and questioned the 

interaction between the rebasing 

adjustments, nominal case-mix growth 

reductions, and case-mix recalibration. 

A few commenters stated that the 

baseline used in calculating the amount 

of case-mix growth was inappropriate. 

Some commenters noted that actual 

program spending on home health was 

consistently less than Congressional 

Budget Office (CBO) estimates, and 

questioned CMS’ authority to 

implement case mix weight adjustments 

when home health spending was less 

than these estimates. Commenters stated 

that there was no increase in aggregate 

expenditures that warranted the 

application of this statutory authority, 

and CMS should withdraw its proposal. 

Some commenters stated that CMS 

should implement program integrity 

measures to control aberrant coding by 

some providers instead of imposing 

across-the-board case mix creep 

adjustments on all providers. 

Response: We finalized the nominal 

case-mix reduction for CY 2018 in the 

CY 2016 HH PPS final rule. We did not 

propose changes to the finalized 

reduction for CY 2018, nor did we 

propose any changes in the 

methodology used to calculate nominal 

case-mix growth in the CY 2018 HH PPS 

proposed rule. The majority of the 

comments received regarding the 

payment reductions for nominal casemix growth were very similar to the 

comments submitted during the 

comment period for the CY 2016 HH 

PPS proposed rule. Therefore, we 

encourage commenters to review our 

responses to the comments we received 

on the payment reductions for nominal 

case-mix growth in the CY 2016 HH PPS 

final rule (80 FR 68639 through 68646), 

which include responses on the 

interaction between the rebasing and 

recalibration of the case-mix weights on 

the measurement of nominal case-mix 

growth between 2012 and 2014, our 

rationale for the methodology used to 

determine ‘‘real’’ versus ‘‘nominal’’ 

case-mix growth in CYs 2012–2014, the 

role of CBO estimates in our 

determination of nominal case-mix 

reductions, and our ability to target 

nominal case-mix reductions to certain 

providers rather the industry as a whole. 

We will continue to monitor real and 

nominal case-mix growth and may 

propose additional reductions for 

nominal case-mix growth, as needed, in 

the future. 

Comment: MedPAC stated that they 

have long believed that it was necessary 

for CMS to make adjustments to account 

for nominal case-mix change to prevent 

additional overpayments. MedPAC 

stated that the CMS’ reduction to 

account for nominal case-mix growth is 

consistent with the agency’s past 

findings on trends in case-mix change in 

the payment system and thus is 

warranted to ensure the accuracy of 

payments under the home health PPS. 

MedPAC stated that a reduction of 0.97 

percent should not significantly affect 

access to care. 

Response: We thank MedPAC for their 

comments. 

Comment: Several commenters stated 

their belief that the CY 2018 payment 

update of 1 percent is inadequate. 

Response: We appreciate the 

commenters’ concerns. However, the 1 

percent payment update for CY 2018 is 

mandated by section 1895(b)(3)(B)(iii) of 

the Act, as amended by section 411(c) 

of the MACRA. 

Comment: Several commenters urged 

CMS to continue providing rural add-on 

payments in order that beneficiaries in 

rural communities continue to have 

access to home health services. 

Response: The sunset of rural add-on 

payments for CY 2018 is statutory and 

we do not have the authority to reauthorize rural add-on payments for 

episodes and visits ending on or after 

January 1, 2018.11 However, we plan to 

continue to monitor the costs associated 

with providing home health care in 

rural versus urban areas. We note that 

in Chapter 9 of its 2013 Report to 

Congress (available at http:// 

medpac.gov/docs/default-source/ 

reports/mar13_ch09.pdf?sfvrsn=0), 

MedPAC stated that the use of the 

‘‘broadly targeted add-on, providing the 

same payment for all rural areas 

regardless of access, results in rural 

areas with the highest utilization 

drawing a disproportionate share of the 

add-on payments.’’ MedPAC stated that 

‘‘70 percent of the episodes that 

received the add-on payments in 2011 

were in rural counties with utilization 

significantly higher than the national 

average’’ and recommended that 

Medicare target payment adjustments 

for rural areas to those areas that have 

access challenges. 

Comment: A commenter 

recommended that CMS explore 

policies that provide Medicare coverage 

for services from therapy providers who 

furnish telehealth services to their 

patients as proper application of 

telehealth rehabilitation therapy 

services, particularly in underserved 

areas, can potentially have a dramatic 

impact on improving care, diminishing 

negative consequences, and reducing 

costs. 

Response: The definition of a visit for 

purposes of Medicare home health 

services as set forth in § 409.48(c) 

specifies that a visit is an episode of 

personal contact with the beneficiary by 


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staff of the HHA or others under 

arrangements with the HHA for the 

purpose of providing a covered service. 

A telephone contact or telehealth visit 

does not meet the definition of a visit 

and therefore does not count as a visit. 

While there is nothing to preclude an 

HHA from furnishing services via 

telehealth or other technologies that 

they believe promote efficiencies, those 

technologies are not specifically 

recognized and paid by Medicare under 

the home health benefit. 

Comment: Several commenters 

expressed concerns with the wage index 

for rural areas in Maine, citing it as one 

of the lowest in New England. Another 

commenter questioned the validity of 

the wage index data, especially in the 

case of the CBSA for AlbanySchenectady-Troy, noting that in the 

past 5 years, this CBSA has seen its 

wage index reduced 5.41 percent, going 

from 0.8647 in 2013 to a proposed CY 

2018 wage index of 0.8179. 

Response: As discussed in the CY 

2017 HH PPS final rule (81 FR 76721), 

we believe that the wage index values 

are reflective of the labor costs in each 

geographic area as they reflect the costs 

included on the cost reports of hospitals 

in those specific labor market areas. The 

wage index values are based on data 

submitted on the inpatient hospital cost 

reports. We utilize efficient means to 

ensure and review the accuracy of the 

hospital cost report data and resulting 

wage index. The home health wage 

index is derived from the pre-floor, prereclassified wage index, which is 

calculated based on cost report data 

from hospitals paid under the Hospital 

Inpatient Prospective Payment System 

(IPPS). All IPPS hospitals must 

complete the wage index survey 

(Worksheet S–3, Parts II and III) as part 

of their Medicare cost reports. Cost 

reports will be rejected if Worksheet S– 

3 is not completed. In addition, 

Medicare contractors perform desk 

reviews on all hospitals’ Worksheet S– 

3 wage data, and we run edits on the 

wage data to further ensure the accuracy 

and validity of the wage data. We 

believe that our review processes result 

in an accurate reflection of the 

applicable wages for the areas given. 

The processes and procedures 

describing how the inpatient hospital 

wage index is developed are discussed 

in the IPPS rule each year, with the 

most recent discussion provided in the 

FY 2018 IPPS final rule (82 FR 38130 

through 38136 and 82 FR 38152 through 

38156). Any provider type may submit 

comments on the hospital wage index 

during the annual IPPS rulemaking 

cycle. 

Comment: A commenter stated that 

CMS’s decision to switch from MSAs to 

the CBSAs for the wage index 

calculation has had serious financial 

ramifications for New York HHAs. The 

commenter stated that CMS’s shift to the 

CBSA wage index designation has 

resulted in below trend reimbursement 

for New York City agencies. 

Response: The MSA delineations as 

well as the CBSA delineations are 

determined by the OMB. The OMB 

reviews its Metropolitan Area 

definitions preceding each decennial 

census to reflect recent population 

changes. We believe that the OMB’s 

CBSA designations reflect the most 

recent available geographic 

classifications and are a reasonable and 

appropriate way to define geographic 

areas for purposes of wage index values. 

Comment: Several commenters 

opposed the fact that hospitals are given 

the opportunity to appeal their annual 

wage index and apply for geographic 

reclassification while HHAs in the same 

geographic location are not given that 

same privilege. The commenters believe 

that this lack of parity between different 

health care sectors further exemplifies 

the inadequacy of CMS’s decision to 

continue to use the pre-floor, prereclassified hospital wage index to 

adjust home health services payment 

rates. Another commenter suggests that 

CMS include wage data from 

reclassified hospitals in calculating 

rural wage index values. 

Response: We continue to believe that 

the regulations and statutes that govern 

the HH PPS do not provide a 

mechanism for allowing HHAs to seek 

geographic reclassification or to utilize 

the rural floor provisions that exist for 

IPPS hospitals. Section 4410(a) of the 

BBA provides that the area wage index 

applicable to any hospital that is located 

in an urban area of a State may not be 

less than the area wage index applicable 

to hospitals located in rural areas in that 

state. This is the rural floor provision 

and it is specific to hospitals. The 

reclassification provision at section 

1886(d)(10)(C)(i) of the Act states that 

the Board shall consider the application 

of any subsection (d) hospital requesting 

the Secretary change the hospital’s 

geographic classification. This 

reclassification provision is only 

applicable to hospitals as defined in 

section 1886(d) of the Act. In addition, 

we do not believe that using hospital 

reclassification data would be 

appropriate as these data are specific to 

the requesting hospitals and may or may 

not apply to a given HHA. 

We continue to believe that using the 

pre-floor, pre-reclassified hospital wage 

index as the wage adjustment to the 

labor portion of the HH PPS rates is 

appropriate and reasonable. 

Comment: Several commenters 

requested that CMS explore wholesale 

revision and reform of the home health 

wage index, including the development 

of a home health-specific wage index. 

Commenters noted that reform of the 

home health wage index should address 

the commenters’ following concerns and 

opinions: (1) The impact on care access 

and financial stability of HHAs at the 

local level; (2) the unpredictable year-toyear swings in wage index values that 

are often based on inaccurate or 

incomplete hospital cost reports which 

have negatively impacted HHAs 

throughout the years and jeopardized 

access to care; (3) the inadequacy and 

inaccuracy of the pre-floor, prereclassified hospital wage index for 

adjusting home health costs; and (4) the 

labor market distortions created by 

reclassification of hospitals in areas in 

which home health labor costs are not 

reclassified. 

Response: We appreciate the 

commenter’s recommendation to 

continue exploring potential approaches 

for wage index reform, including 

collecting home health-specific wage 

data in order to establish a home healthspecific wage index. We note that our 

previous attempts at either proposing or 

developing a home health-specific wage 

index were not well-received by the 

home health industry. In September 30, 

1988 Federal Register notice (53 FR 

38476), the Health Care Financing 

Administration (HCFA), as CMS was 

then known, implemented an HHAspecific wage index based on data 

received from HHAs. Subsequently, 

providers gave significant feedback 

concerning the burden that the reporting 

requirements posed and the accuracy of 

the data. As a result, the Medicare 

Catastrophic Coverage Act of 1988 

retroactively repealed the use of an 

HHA-specific wage index and 

referenced use of the hospital wage 

index (see section 1895(b)(4)(C) of the 

Act). While this occurred many years 

ago, we believe that HHAs would voice 

similar concerns regarding the burden 

such reporting requirements would 

place on HHAs. 

Consistent with our previous 

responses to these recurring comments 

(most recently published in the CY 2016 

HH PPS final rule (80 FR 68654)), we 

also note that developing such a wage 

index would require a resourceintensive audit process similar to that 

used for IPPS hospital data, to improve 

the quality of the HHA cost report data 

in order for it to be used as part of this 

analysis. This audit process is quite 

extensive in the case of approximately 


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3,300 hospitals, it would be 

significantly more so in the case of 

approximately 11,000 HHAs. We believe 

auditing all HHA cost reports, similar to 

the process used to audit inpatient 

hospital cost reports for purposes of the 

IPPS wage index, would also place a 

burden on providers in terms of 

recordkeeping and completion of the 

cost report worksheet. 

We also believe that adopting such an 

approach would require a significant 

commitment of resources by CMS and 

the Medicare Administrative 

Contractors, potentially far in excess of 

those required under the IPPS given that 

there are more than three times as many 

HHAs as there are hospitals. Therefore, 

we continue to believe that, in the 

absence of the appropriate home healthspecific wage data, using the pre-floor, 

pre-reclassified inpatient hospital wage 

data is appropriate and reasonable for 

the HH PPS. 

Finally, CMS has conducted research 

on a possible alternative to the hospital 

wage index. CMS issued its ‘‘Report to 

Congress: Plan to Reform the Medicare 

Wage Index’’ concerning the hospital 

wage index, on April 11, 2012 and is 

available on our Wage Index Reform 

Web page https://www.cms.gov/

Medicare/Medicare-Fee-for-ServicePayment/AcuteInpatientPPS/WageIndex-Reform.html. This report 

describes the concept of a commutingbased wage index (CBWI). However, 

implementation of a CBWI may require 

both statutory and regulatory changes. 

In addition, we believe other 

intermediate steps for implementation, 

including the collection of commuting 

data, may be necessary. In considering 

alternative methodologies for area wage 

adjustment, CMS would have to 

consider whether the benefits of such 

methodologies outweigh the reporting, 

record keeping and audit burden that 

would be placed on HHAs and/or other 

providers. 

Comment: Several commenters stated 

that the pre-floor, pre-reclassified 

hospital wage index is inadequate for 

adjusting home health costs, 

particularly in states like New York, 

which has among the nation’s highest 

labor costs, exacerbated, in the 

commenters’ opinions, by their state’s 

implementation of a phased-in $15 perhour minimum wage hike, which they 

argue would be unfunded by Medicare. 

The commenters estimated that the 

minimum wage mandate, when fully 

phased-in, would add $2 billion in costs 

for that state’s HHAs across all payers 

(Medicaid, Medicare, managed care, 

commercial insurance and private-pay), 

and would not be captured by the prefloor, pre-reclassified hospital wage 

index. One commenter recommended 

that providers meeting higher minimum 

wage standards, such as HHAs, obtain 

additional supplemental funding to 

better align payments with cost trends 

impacting providers. 

Response: Regarding minimum wage 

standards, we note that such increases 

will be reflected in future data used to 

create the hospital wage index to the 

extent that these changes to state 

minimum wage standards are reflected 

in increased wages to hospital staff. 

Comment: Commenters raised issues 

with CMS’s decision to maintain the 

current policy of using the pre-floor, 

pre-reclassified hospital wage index to 

adjust home health services payment 

rates because this resulted in volatility 

in the home health wage index from one 

year to the next. These commenters 

believe that what they view as 

unpredictable year-to-year swings in 

wage index values were based on 

inaccurate or incomplete hospital cost 

reports. 

Response: We appreciate the 

commenters’ concerns regarding the 

accuracy of the home health wage 

index. We utilize efficient means to 

ensure and review the accuracy of the 

hospital cost report data and resulting 

wage index. The home health wage 

index is derived from the pre-floor, prereclassified wage index, which is 

calculated based on cost report data 

from hospitals paid under the IPPS. All 

IPPS hospitals must complete the wage 

index survey (Worksheet S–3, Parts II 

and III) as part of their Medicare cost 

reports. Cost reports will be rejected if 

Worksheet S–3 is not completed. In 

addition, Medicare contractors perform 

desk reviews on all hospitals’ 

Worksheet S–3 wage data, and we run 

edits on the wage data to further ensure 

the accuracy and validity of the wage 

data. We believe that our review 

processes result in an accurate reflection 

of the applicable wages for the areas 

given. The processes and procedures 

describing how the inpatient hospital 

wage index is developed, including a 

wage data verification and correction 

process, are discussed in the IPPS rule 

each year, with the most recent 

discussion provided in the FY 2018 

IPPS final rule (82 FR 38130 through 

38136, and 82 FR 38152 through 38156). 

Any provider type may submit 

comments on the hospital wage index 

during the annual IPPS rulemaking 

cycle. 

Comment: A commenter 

recommended that CMS research the 

impact of instituting a population 

density adjustment to the labor portion 

of the HH PPS payments. 

Response: As discussed in the CY 

2017 HH PPS final rule (81 FR 76721), 

we do not believe that a population 

density adjustment is appropriate at this 

time. Rural HHAs continually cite the 

added cost of traveling from one patient 

to the next patient. However, urban 

HHAs cite the added costs associated 

with needed security measures and 

traffic congestion. The home health 

wage index values in rural areas are not 

necessarily lower than the home health 

wage index values in urban areas. The 

home health wage index reflects the 

wages that inpatient hospitals pay in 

their local geographic areas. 

Final Decision: After considering the 

comments received in response to the 

CY 2018 HH PPS proposed rule, we are 

finalizing our proposal to use the prefloor, pre-reclassified hospital inpatient 

wage index as the wage adjustment to 

the labor portion of the HH PPS rates. 

For CY 2018, the updated wage data are 

for the hospital cost reporting periods 

beginning on or after October 1, 2013 

and before October 1, 2014 (FY 2014 

cost report data). In addition, we are 

implementing the third and final year of 

a 0.97 percent payment reduction to 

account for nominal case-mix growth 

from CY 2012 through CY 2014 when 

finalizing the CY 2018 HH PPS payment 

rates. We note that the payment 

reductions to account for nominal casemix growth from 2012 to 2014 were 

finalized in the CY 2016 HH PPS final 

rule. No additional adjustments or 

reductions were proposed in the CY 

2018 proposed rule. 

D. Payments for High-Cost Outliers 

Under the HH PPS 

1. Background 

Section 1895(b)(5) of the Act allows 

for the provision of an addition or 

adjustment to the home health payment 

amount in the case of outliers because 

of unusual variations in the type or 

amount of medically necessary care. 

Outlier payments serve as a type of 

‘‘reinsurance’’ whereby, under the HH 

PPS, Medicare reimburses HHAs 80 

percent of their costs for outlier cases 

once the case exceeds an outlier 

threshold amount. Prior to the 

enactment of the Affordable Care Act, 

section 1895(b)(5) of the Act stipulated 

that projected total outlier payments 

could not exceed 5 percent of total 

projected or estimated HH payments in 

a given year. In the July 3, 2000 

Medicare Program; Prospective Payment 

System for Home Health Agencies final 

rule (65 FR 41188 through 41190), we 

described the method for determining 

outlier payments. Under this system, 

outlier payments are made for episodes 


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whose estimated costs exceed a 

threshold amount for each Home Health 

Resource Group (HHRG). The episode’s 

estimated cost was established as the 

sum of the national wage-adjusted pervisit payment amounts delivered during 

the episode. The outlier threshold for 

each case-mix group or Partial Episode 

Payment (PEP) adjustment is defined as 

the 60-day episode payment or PEP 

adjustment for that group plus a fixeddollar loss (FDL) amount. The outlier 

payment is defined to be a proportion of 

the wage-adjusted estimated cost 

beyond the wage-adjusted threshold. 

The threshold amount is the sum of the 

wage and case-mix adjusted PPS 

episode amount and wage-adjusted FDL 

amount. The proportion of additional 

costs over the outlier threshold amount 

paid as outlier payments is referred to 

as the loss-sharing ratio. 

In the CY 2010 HH PPS proposed rule 

(74 FR 40948, 40957), we stated that 

outlier payments increased as a 

percentage of total payments from 4.1 

percent in CY 2005, to 5.0 percent in CY 

2006, to 6.4 percent in CY 2007 and that 

this excessive growth in outlier 

payments was primarily the result of 

unusually high outlier payments in a 

few areas of the country. In that 

discussion, we noted that despite 

program integrity efforts associated with 

excessive outlier payments in targeted 

areas of the country, we discovered that 

outlier expenditures still exceeded the 5 

percent target in CY 2007 and, in the 

absence of corrective measures, would 

continue do to so. Consequently, we 

assessed the appropriateness of taking 

action to curb outlier abuse. As 

described in the CY 2010 HH PPS final 

rule (74 FR 58080 through 58087), to 

mitigate possible billing vulnerabilities 

associated with excessive outlier 

payments and adhere to our statutory 

limit on outlier payments, we finalized 

an outlier policy that included a 10 

percent agency-level cap on outlier 

payments. This cap was implemented in 

concert with a reduced FDL ratio of 

0.67. These policies resulted in a 

projected target outlier pool of 

approximately 2.5 percent. (The 

previous outlier pool was 5 percent of 

total home health expenditures). For CY 

2010, we first returned the 5 percent 

held for the previous target outlier pool 

to the national, standardized 60-day 

episode rates, the national per-visit 

rates, the LUPA add-on payment 

amount, and the NRS conversion factor. 

Then, we reduced the CY 2010 rates by 

2.5 percent to account for the new 

outlier pool of 2.5 percent. This outlier 

policy was adopted for CY 2010 only. 

As we noted in the CY 2011 HH PPS 

final rule (75 FR 70397 through 70399), 

section 3131(b)(1) of the Affordable Care 

Act amended section 1895(b)(3)(C) of 

the Act, and required the Secretary to 

reduce the HH PPS payment rates such 

that aggregate HH PPS payments were 

reduced by 5 percent. In addition, 

section 3131(b)(2) of the Affordable Care 

Act amended section 1895(b)(5) of the 

Act by redesignating the existing 

language as section 1895(b)(5)(A) of the 

Act, and revising the language to state 

that the total amount of the additional 

payments or payment adjustments for 

outlier episodes may not exceed 2.5 

percent of the estimated total HH PPS 

payments for that year. Section 

3131(b)(2)(C) of the Affordable Care Act 

also added section 1895(b)(5)(B) of the 

Act which capped outlier payments as 

a percent of total payments for each 

HHA at 10 percent. 

As such, beginning in CY 2011, our 

HH PPS outlier policy is that we reduce 

payment rates by 5 percent and target 

up to 2.5 percent of total estimated HH 

PPS payments to be paid as outliers. To 

do so, we returned the 2.5 percent held 

for the target CY 2010 outlier pool to the 

national, standardized 60-day episode 

rates, the national per visit rates, the 

LUPA add-on payment amount, and the 

NRS conversion factor for CY 2010. 

Then we reduced the rates by 5 percent 

as required by section 1895(b)(3)(C) of 

the Act, as amended by section 

3131(b)(1) of the Affordable Care Act. 

For CY 2011 and subsequent calendar 

years we target up to 2.5 percent of 

estimated total payments to be paid as 

outlier payments, and apply a 10 

percent agency-level outlier cap. 

In the CY 2017 HH PPS proposed and 

final rules (81 FR 43737 through 43742 

and 81 FR 76724), we described our 

concerns regarding patterns observed in 

home health outlier episodes. 

Specifically, we noted that the 

methodology for calculating home 

health outlier payments may have 

created a financial incentive for 

providers to increase the number of 

visits during an episode of care to 

surpass the outlier threshold and 

simultaneously created a disincentive 

for providers to treat medically complex 

beneficiaries who require fewer but 

longer visits. Given these concerns, in 

the CY 2017 HH PPS final rule (81 FR 

76724), we finalized changes to the 

methodology used to calculate outlier 

payments, using a cost-per-unit 

approach rather than a cost-per-visit 

approach. This change in methodology 

allows for more accurate payment for 

outlier episodes, accounting for both the 

number of visits during an episode of 

care and also the length of the visits 

provided. Using this approach, we now 

convert the national per-visit rates into 

per 15-minute unit rates. These per 15- 

minute unit rates are used to calculate 

the estimated cost of an episode to 

determine whether the claim will 

receive an outlier payment and the 

amount of payment for an episode of 

care. In conjunction with our finalized 

policy to change to a cost-per-unit 

approach to estimate episode costs and 

determine whether an outlier episode 

should receive outlier payments, in the 

CY 2017 HH PPS final rule (81 FR 

76725) we also finalized the 

implementation of a cap on the amount 

of time per day that would be counted 

toward the estimation of an episode’s 

costs for outlier calculation purposes. 

Specifically, we limit the amount of 

time per day (summed across the six 

disciplines of care) to 8 hours (32 units) 

per day when estimating the cost of an 

episode for outlier calculation purposes. 

2. Fixed Dollar Loss (FDL) Ratio 

For a given level of outlier payments, 

there is a trade-off between the values 

selected for the FDL ratio and the losssharing ratio. A high FDL ratio reduces 

the number of episodes that can receive 

outlier payments, but makes it possible 

to select a higher loss-sharing ratio, and 

therefore, increase outlier payments for 

qualifying outlier episodes. 

Alternatively, a lower FDL ratio means 

that more episodes can qualify for 

outlier payments, but outlier payments 

per episode must then be lower. 

The FDL ratio and the loss-sharing 

ratio must be selected so that the 

estimated total outlier payments do not 

exceed the 2.5 percent aggregate level 

(as required by section 1895(b)(5)(A) of 

the Act). Historically, we have used a 

value of 0.80 for the loss-sharing ratio 

which, we believe, preserves incentives 

for agencies to attempt to provide care 

efficiently for outlier cases. With a losssharing ratio of 0.80, Medicare pays 80 

percent of the additional estimated costs 

above the outlier threshold amount. 

Simulations based on CY 2015 claims 

data (as of June 30, 2016) completed for 

the CY 2017 HH PPS final rule showed 

that outlier payments were estimated to 

represent approximately 2.84 percent of 

total HH PPS payments in CY 2017, and 

as such, we finalized a change to the 

FDL ratio from 0.45 to 0.55. We stated 

that raising the FDL ratio to 0.55, while 

maintaining a loss-sharing ratio of 0.80, 

struck an effective balance of 

compensating for high-cost episodes 

while still meeting the statutory 

requirement to target up to, but no more 

than, 2.5 percent of total payments as 

outlier payments (81 FR 76726). The 

national, standardized 60-day episode 

payment amount is multiplied by the 

FDL ratio. That amount is wage-adjusted 


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to derive the wage-adjusted FDL 

amount, which is added to the case-mix 

and wage-adjusted 60-day episode 

payment amount to determine the 

outlier threshold amount that costs have 

to exceed before Medicare would pay 80 

percent of the additional estimated 

costs. 

Using preliminary CY 2016 claims 

data (as of March 17, 2017) and the 

proposed CY 2018 payment rates 

presented in section III.C. of the CY 

2018 HH PPS proposed rule (82 FR 

35293), we estimated that outlier 

payments would constitute 

approximately 2.47 percent of total HH 

PPS payments in CY 2018 under the 

current outlier methodology. Given the 

statutory requirement to target up to, but 

no more than, 2.5 percent of total 

payments as outlier payments, we did 

not propose a change to the FDL ratio 

for CY 2018 as we believed that 

maintaining an FDL ratio of 0.55 with a 

loss-sharing ratio of 0.80 was still 

appropriate given the percentage of 

outlier payments projected for CY 2018. 

Likewise, we did not propose a change 

to the loss-sharing ratio (0.80) for the 

HH PPS to remain consistent with 

payment for high-cost outliers in other 

Medicare payment systems (for 

example, Inpatient Rehabilitation 

Facility (IRF) PPS, IPPS, etc.). While we 

did not propose to change the FDL ratio 

of 0.55 for CY 2018, we noted that we 

would update our estimate of outlier 

payments as a percent of total HH PPS 

payments using the most current and 

complete year of HH PPS data (CY 2016 

claims data as of June 30, 2017 or later) 

in this final rule. 

Using updated CY 2016 claims data 

(as of August 18, 2017) and the final CY 

2018 payment rates presented in section 

III.C of this final rule, we estimate that 

outlier payments would continue to 

constitute approximately 2.47 percent of 

total HH PPS payments in CY 2018 

under the current outlier methodology. 

Given the statutory requirement to target 

up to, but no more than, 2.5 percent of 

total payments as outlier payments, we 

continue to believe that maintaining an 

FDL ratio of 0.55 with a loss-sharing 

ratio of 0.80 is still appropriate given 

the percentage of outlier payments 

projected for CY 2018. 

The following is a summary of the 

comments received and our responses. 

Comment: A commenter questioned if 

we would provide the CY 2018 cost-perunit values to be used for the outlier 

calculation. 

Response: The cost-per-unit amounts 

for CY 2018 are in Table 14 of this final 

rule. We note that in the CY 2017 HH 

PPS final rule (81 FR 76724), we stated 

that we did not plan to re-estimate the 

average minutes per visit by discipline 

every year. Additionally, we noted that 

the per-unit rates used to estimate an 

episode’s cost will be updated by the 

home health update percentage each 

year, meaning we would start with the 

national per-visit amounts for the same 

calendar year when calculating the costper-unit used to determine the cost of an 

episode of care (81 FR 76727). 

TABLE 14—CY 2018 COST-PER-UNIT PAYMENT RATES FOR THE CALCULATION OF OUTLIER PAYMENTS * 

Visit type 

CY 2018 

National 

per-visit 

payment rates 

Average 

minutesper-visit 

Cost-per-unit 

(1 unit = 15 

minutes) 

Home health aide ........................................................................................................................ $64.94 63.0 $15.46 

Medical social services ................................................................................................................ 229.86 56.5 61.02 

Occupational therapy ................................................................................................................... 157.83 47.1 50.26 

Physical therapy .......................................................................................................................... 156.76 46.6 50.46 

Skilled nursing ............................................................................................................................. 143.40 44.8 48.01 

Speech-language pathology ........................................................................................................ 170.38 48.1 53.13 

* These values reflect the national per visit rates for each discipline for providers who have submitted quality data; for rates applicable to those 

providers who did not submit quality data submitted, please see our forthcoming CY 2018 Rate Update Change Request, which will be available 

here: https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/2017-Transmittals.html. 

We note that we will continue to 

monitor the visit length by discipline as 

more recent data become available, and 

we may propose to update the rates as 

needed in the future. 

Comment: Several commenters stated 

that the changes to the outlier 

methodology made in the CY 2017 final 

rule, particularly the increase in the 

FDL ratio from 0.45 to 0.55, were 

significant and may have led to a 

reduction in the number of home health 

episodes that would qualify for outlier 

payment. The commenters 

recommended that CMS release data on 

the impact of this policy change on the 

dually eligible beneficiary population 

and in particular those patients with 

clinically complex conditions. 

Response: We appreciate the 

commenters’ concerns regarding the 

potential impact of the changes to the 

outlier policy finalized in the CY 2017 

HH PPS final rule (81 FR 76727). Data 

reflecting the changes to the outlier 

policy made for CY 2017 are not yet 

available for analysis and assessment. 

However, as these updated data become 

available, we will evaluate for changes, 

analyze patterns in home health outlier 

payments, and monitor for any impacts, 

particularly for those beneficiaries with 

clinically complex conditions, and may 

include the results of such efforts in 

future rulemaking. 

Additionally, as discussed in the CY 

2017 HH PPS final rule (81 FR 76728), 

the goal of this policy change is to more 

accurately pay for outlier episodes. We 

noted in the CY 2017 HH PPS proposed 

rule that analysis indicates that a larger 

percentage of episodes of care for 

patients with a fragile overall health 

status will qualify for outlier payments 

(81 FR 43713). The outlier system is 

meant to help address extra costs 

associated with extra, and potentially 

unpredictable, medically necessary care. 

In section II.D. of the CY 2018 HH PPS 

proposed rule (82 FR 35275), we 

discussed Report to Congress: Home 

Health Study on Access to Care for 

Vulnerable Patient Populations and 

Subsequent Research and Analyses. We 

believe that this change in the outlier 

payment policy may ultimately serve to 

address some of the findings from the 

home health study, where margins were 

lower for patients with medically 

complex needs that typically require 

longer visits, thus potentially creating 

an incentive to treat only or primarily 

patients with less complex needs. 

Moreover, the 2.5 percent target of 

outlier payments to total home health 

payments is a statutory requirement, as 

established in section 1895(b)(5) of the 

Act. Therefore, we modified the FDL in 

order to align the estimated outlier 

payments with the 2.5 percent target 

required by law. 


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Comment: A few commenters 

expressed disagreement with CMS’s 

decision to maintain the existing 10- 

percent cap on outlier payments to 

HHAs as a purported fraud-fighting 

effort, suggesting that a potentially more 

appropriate and targeted fraud-fighting 

initiative will include a possible 

minimum provider-specific number or 

percent of episodes that result in 

LUPAs, suggesting that reporting 

periods with zero LUPAs could be an 

indicator of inappropriate provider 

behavior. 

Response: Regarding the 

appropriateness of the 10 percent peragency cap, we note that the 2.5 percent 

target of outlier payments to total home 

health payments and the 10 percent cap 

on outlier payments at the home health 

agency level are statutory requirements, 

as established in section 1895(b)(5) of 

the Act. Therefore, we do not have the 

authority to adjust or eliminate the 10- 

percent cap or increase the 2.5 percent 

target amount. Additionally, we 

appreciate the commenter’s suggestion 

regarding alternative approaches for 

targeting fraud within the Medicare 

home health benefit. The Program for 

Evaluating Payment Patterns Electronic 

Report (PEPPER) is a comparative data 

report that summarizes a single 

provider’s Medicare claims data 

statistics for services vulnerable to 

improper payments. PEPPER can 

support a hospital or facility’s 

compliance efforts by identifying where 

its billing patterns are different from the 

majority of other providers in the 

nation. This data can help identify both 

potential overpayments and potential 

underpayments, and can provide 

guidance on areas in which a provider 

may want to focus auditing and 

monitoring efforts with the goal of 

preventing improper Medicare 

payments. In the HHA PEPPER, we 

include a metric for non-LUPA 

payment, which represents the count of 

episodes paid to the HHA that did not 

have a LUPA payment during the report 

period as a proportion of total episodes 

paid to the HHA during the report 

period (available at: https://

www.pepperresources.org/Portals/0/

Documents/PEPPER/HHA/HHA_

PEPPERUsersGuide_Edition2.pdf). This 

measure is provided to the HHA 

community for review and may also be 

used by our Center for Program Integrity 

as a guide for audits and other 

investigative efforts. 

We also note that, as described in the 

CY 2017 HH PPS final rule (82 FR 

76727), in 2015, only about 1 percent of 

HHAs received 10 percent of their total 

HH PPS payments as outlier payments, 

while almost 71 percent of HHAs 

received less than 1 percent of their 

total HH PPS payments as outliers. 

Therefore, the 10 percent agency-level 

cap does not seem to significantly 

impact a large portion of HHAs. 

Comment: Several commenters 

recommended that CMS conduct a more 

detailed analysis to determine whether 

the total cap of 2.5 percent of total 

payments as outlier payments is 

adequate or whether it needs to be 

increased for future years, particularly 

given the expected change in Medicare 

beneficiary demographics anticipated in 

the coming years. 

Response: As established in section 

1895(b)(5) of the Act, both the 2.5 

percent target of outlier payments to 

total home health payments and the 10- 

percent cap on outlier payments at the 

home health agency level are statutory 

requirements. Therefore, we do not have 

the authority to adjust or eliminate the 

10-percent cap or increase the 2.5- 

percent target amount. However, we 

will continue to evaluate for the 

appropriateness of those elements of the 

outlier policy that may be modified, 

including the FDL and the loss-sharing 

ratio. We note that other Medicare 

payment systems with outlier payments, 

such as the IRF PPS and IPPS, annually 

reassess the fixed-loss cost outlier 

threshold amount. Adjusting the outlier 

threshold amount in order to target the 

statutorily required percentage of total 

payments as outlier payments is 

standard practice. 

Comment: A commenter 

recommended that CMS eliminate 

outlier payments in their entirety. 

Response: We believe that section 

1895(b)(5)(A) of the Act allows the 

Secretary the discretion as to whether or 

not to have an outlier policy under the 

HH PPS. However, we also believe that 

outlier payments are beneficial in that 

they help mitigate the incentive for 

HHAs to avoid patients that may have 

episodes of care that result in unusual 

variations in the type or amount of 

medically necessary care. The outlier 

system is meant to help address extra 

costs associated with extra, and 

potentially unpredictable, medically 

necessary care. We note that we plan to 

continue evaluating whether or not an 

outlier policy remains appropriate as 

well as ways to maintain an outlier 

policy for episodes that incur unusually 

high costs due to patient care needs. 

Final Decision: We are finalizing no 

change to the FDL ratio or loss sharing 

ratio for CY 2018. We are maintaining 

an FDL ratio of 0.55 with a loss-sharing 

ratio of 0.80 for CY 2018. However, we 

will continue to monitor outlier 

payments and continue to explore ways 

to maintain an outlier policy for 

episodes that incur unusually high 

costs. 

E. Proposed Implementation of the 

Home Health Groupings Model (HHGM) 

for CY 2019 

We proposed case-mix methodology 

refinements through the implementation 

of the Home Health Groupings Model 

(HHGM). We proposed to implement the 

HHGM for home health periods of care 

beginning on or after January 1, 2019. 

The HHGM uses 30-day periods rather 

than the 60-day episode used in the 

current payment system, eliminates the 

use of the number of therapy visits 

provided to determine payment, and 

relies more heavily on clinical 

characteristics and other patient 

information (for example, diagnosis, 

functional level, comorbid conditions, 

admission source) to place patients into 

clinically meaningful payment 

categories. 

We are not finalizing the 

implementation of the HHGM in this 

final rule. We received many comments 

from the public that we would like to 

take into further consideration. While 

commenters were generally supportive 

of the concept of revising the HH PPS 

case-mix methodology to better align 

payments with the costs of providing 

care, commenters included technical 

comments on various aspects of the 

proposed case-mix adjustment 

methodology under the HHGM and 

were most concerned about the 

proposed change in the unit of payment 

from 60 days to 30 days and such 

change being proposed for 

implementation in a non-budget neutral 

manner. Commenters also stated their 

desire for greater involvement in the 

development of the HHGM and the need 

for access to the necessary data in order 

to replicate and model the effects on 

their businesses. 

We note that information continues to 

be available to stakeholders around this 

important initiative. The analyses and 

the ultimate development of HHGM was 

previously shared with both internal 

and external stakeholders via technical 

expert panels, clinical workgroups, and 

special open door forums. We provided 

high-level summaries on our case-mix 

methodology refinement work in the HH 

PPS proposed rules for CYs 2016 and 

2017 (80 FR 39839, and 81 FR 76702). 

Additionally, a detailed technical report 

was posted on the CMS Web site in 

December 2016 and remains available, 

additional technical expert panel and 

clinical workgroup webinars were held 

after the posting of the technical report, 

and a National Provider call occurred in 

January 2017 to further solicit feedback 

from stakeholders and the general 


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12https://www.cms.gov/Outreach-and-Education/ 

Outreach/NPC/National-Provider-Calls-and-EventsItems/2017-01-18-Home-Health.html. 

13https://www.resdac.org/cms-data/request/cmsdata-request-center. 

public.12 As many did, any provider or 

organization wishing to receive the 

necessary data to replicate and model 

the effects of the HHGM or study the 

Medicare home health benefit can 

submit a request through the CMS Data 

Request Center.13 We note that the 

Home Health Agency Limited Data Set 

files and Research Identifiable Files are 

available on a quarterly and annual 

basis. The fourth quarter data for CY 

2016 were available in mid-May of 

2017. The fourth quarter files include all 

final action fee-for-service claims 

received by December 31, 2016. We also 

posted a HHGM Groupings Tool along 

with the CY 2018 HH PPS proposed rule 

on the HHA Center Web page, which 

providers can continue to use in order 

to replicate the HHGM methodology 

using their own internal data. 

We also note that, in the CY 2018 HH 

PPS proposed rule, we assumed that 

behavioral responses would occur upon 

implementation of the HHGM. If no 

behavioral assumptions were made and 

we implemented the HHGM for CY 

2018, we estimate that the 30-day 

payment amount needed to achieve 

budget neutrality would have been 

$1,722.29. However, because we have a 

continued fiduciary duty as stewards of 

the Medicare program to mitigate 

potential overpayments, if possible, we 

assumed behavioral responses would 

occur in the estimation of the 30-day 

payment amount. We determined that, if 

the HHGM were implemented for CY 

2018 with assumed behavioral 

responses, the 30-day payment amount 

needed to achieve budget neutrality 

would have been $1,622.61. For the CY 

2018 HH PPS proposed rule, we 

included two behavioral assumptions in 

our impact estimates related to the 

proposed implementation of the HHGM 

for CY 2019: (1) For LUPAs one visit 

under the proposed HHGM case-mix 

group thresholds, HHAs would provide 

an additional visit so the 30-day period 

of care becomes a non-LUPA; and (2) 

the highest-paying diagnosis code 

would be listed as primary for clinical 

grouping assignment. While we do not 

support or condone coding practices or 

the provision of services solely to 

maximize payment, we often take into 

account expected behavioral effects of 

policy changes related to rate setting. 

We included a LUPA behavioral 

assumption in our estimated impact of 

the HHGM based on past behavioral 

assumptions made under the HH PPS. 

As noted in the FY 2001 HH PPS final 

rule, the episode file showed that 

approximately 16 percent of episodes 

would have received a LUPA (65 FR 

41162). However, currently, about 7 

percent of all 60-day episodes receive a 

LUPA. For the HHGM, approximately 7 

percent of 30-day periods would receive 

a LUPA. However, because 4.9 percent 

of 30-day periods of care are just one 

visit below the LUPA thresholds under 

the HHGM, we assume that for these 30- 

day periods, HHAs will provide an 

additional visit to avoid receiving a 

LUPA, especially in the absence of 

therapy thresholds and the change from 

a 60-day to 30-day unit of payment. 

With regards to our assumption that 

HHAs would code the highest-paying 

diagnosis code as primary for the 

clinical grouping assignment, this 

assumption was based on decades of 

past experience under the HH PPS and 

other case-mix systems, such as the 

implementation of the diagnosis-related 

groups (DRGs) and the Medicare 

Severity (MS)-DRGs under the inpatient 

prospective payment system. In the FY 

2008 IPPS final rule (72 FR 47176), we 

noted that case-mix refinements can 

lead to substantial unwarranted increase 

in payments. To address this issue when 

CMS transitioned from DRGs to MS– 

DRGs, MedPAC recommended that the 

Secretary project the likely effect of 

reporting improvements on total 

payments and make an offsetting 

adjustment to the national average base 

payment amounts (72 FR 47176). In the 

FY 2008 IPPS final rule (72 FR 47181), 

we summarized instances where casemix increases resulted from 

documentation and coding-induced 

changes for the first year of the IRF PPS 

and in Maryland hospitals’ transition to 

APR DRGs (estimated at around 5 

percent in both instances). Therefore, 

we estimated that an adjustment of 4.8 

percent would be necessary to maintain 

budget neutrality for the transition to 

the MS–DRGs (72 FR 47178). With 

regards to experience under the HH 

PPS, as outlined in the CY 2018 HH PPS 

proposed rule (82 FR 35274), between 

CY 2000 and 2010, total case-mix 

change was 23.90 percent, with 20.08 

considered nominal case-mix growth, an 

average of approximately 2 percent 

nominal case-mix growth per year. 

IV. Provisions of the Home Health 

Value-Based Purchasing (HHVBP) 

Model 

A. Background 

As authorized by section 1115A of the 

Act and finalized in the CY 2016 HH 

PPS final rule (80 FR 68624), we began 

testing the HHVBP Model on January 1, 

2016. The HHVBP Model has an overall 

purpose of improving the quality and 

delivery of home health care services to 

Medicare beneficiaries. The specific 

goals of the Model are to: (1) Provide 

incentives for better quality care with 

greater efficiency; (2) study new 

potential quality and efficiency 

measures for appropriateness in the 

home health setting; and (3) enhance the 

current public reporting process. 

Using the randomized selection 

methodology finalized in the CY 2016 

HH PPS final rule, nine states were 

selected for inclusion in the HHVBP 

Model, representing each geographic 

area across the nation. All Medicarecertified HHAs providing services in 

Arizona, Florida, Iowa, Maryland, 

Massachusetts, Nebraska, North 

Carolina, Tennessee, and Washington 

(competing HHAs) are required to 

compete in the Model. Requiring all 

Medicare-certified HHAs providing 

services in the selected states to 

participate in the Model ensures that: 

(1) There is no selection bias; (2) 

participating HHAs are representative of 

HHAs nationally; and, (3) there is 

sufficient participation to generate 

meaningful results. 

As finalized in the CY 2016 HH PPS 

final rule, the HHVBP Model will utilize 

the waiver authority under section 

1115A(d)(1) of the Act to adjust 

Medicare payment rates under section 

1895(b) of the Act beginning in CY 2018 

based on performance on applicable 

measures. Payment adjustments will be 

increased incrementally over the course 

of the HHVBP Model in the following 

manner: (1) A maximum payment 

adjustment of 3 percent (upward or 

downward) in CY 2018; (2) a maximum 

payment adjustment of 5 percent 

(upward or downward) in CY 2019; (3) 

a maximum payment adjustment of 6 

percent (upward or downward) in CY 

2020; (4) a maximum payment 

adjustment of 7 percent (upward or 

downward) in CY 2021; and (5) a 

maximum payment adjustment of 8 

percent (upward or downward) in CY 

2022. Payment adjustments will be 

based on each HHA’s Total Performance 

Score (TPS) in a given performance year 

(PY) on: (1) A set of measures already 

reported via OASIS and HHCAHPS for 

all patients serviced by the HHA and 

select claims data elements; and (2) 

three new measures where points are 

achieved for reporting data. 

In the CY 2017 HH PPS final rule (81 

FR 76741 through 76752), in addition to 

providing an update on the progress 

towards developing public reporting of 

performance under the HHVBP Model, 

we finalized the following changes 

related to the HHVBP Model: 


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14Patient Survey Star Ratings https://

www.medicare.gov/HomeHealthCompare/Data/

Patient-Survey-Star-Ratings.html. 

• Calculating benchmarks and 

achievement thresholds at the state level 

rather than the level of the size-cohort 

and revising the definition for 

benchmark to state that benchmark 

refers to the mean of the top decile of 

Medicare-certified HHA performance on 

the specified quality measure during the 

baseline period, calculated for each 

state. 

• Requiring a minimum of eight 

HHAs in a size-cohort. 

• Increasing the timeframe for 

submitting new measure data from 

seven calendar days to 15 calendar days 

following the end of each reporting 

period to account for weekends and 

holidays. 

• Removing four measures (Care 

Management: Types and Sources of 

Assistance, Prior Functioning Activities 

of Daily Living (ADL)/Instrumental ADL 

(IADL), Influenza Vaccine Data 

Collection Period, and Reason 

Pneumococcal Vaccine Not Received) 

from the set of applicable measures. 

• Adjusting the reporting period and 

submission date for the Influenza 

Vaccination Coverage for Home Health 

Personnel measure from a quarterly 

submission to an annual submission. 

• Allowing for an appeals process 

that includes the recalculation process 

finalized in the CY 2016 HH PPS final 

rule (80 FR 68688 through 68689), as 

modified, and adds a reconsideration 

process. 

B. Quality Measures 

1. Adjustment to the Minimum Number 

of Completed Home Health Care 

Consumer Assessment of Healthcare 

Providers and System (HHCAHPS) 

Surveys 

The HHCAHPS survey presents home 

health patients with a set of 

standardized questions about their 

home health care providers and about 

the quality of their home health care. 

The survey is designed to measure the 

experiences of people receiving home 

health care from Medicare-certified 

home health care agencies and meet the 

following three broad goals to: (1) 

Produce comparable data on the 

patient’s perspective that allows 

objective and meaningful comparisons 

between HHAs on domains that are 

important to consumers; (2) create 

incentives through public reporting of 

survey results for agencies to improve 

their quality of care; and (3) enhance 

public accountability in health care by 

increasing the transparency of the 

quality of care provided in return for 

public investment through public 

reporting. 

As finalized in the CY 2016 HH PPS 

final rule (80 FR 68685 through 68686), 

if a HHA does not have a minimum of 

20 episodes of care during a 

performance year (PY) to generate a 

performance score on at least five 

measures, that HHA would not be 

included in the Linear Exchange 

Function (LEF) and would not have a 

payment adjustment percentage 

calculated. The LEF is used to translate 

an HHA’s Total Performance Score 

(TPS) into a percentage of the valuebased payment adjustment earned by 

each HHA under the HHVBP Model. For 

the HHCAHPS measures, a minimum of 

20 HHCAHPS completed surveys would 

be necessary in order for scores to be 

generated for the HHCAHPS quality 

measures that can be included in the 

calculation of the TPS. 

However, as we stated in the CY 2018 

HH PPS proposed rule (82 FR 35333), 

we believe that using a minimum of 40 

completed HHCAHPS surveys, rather 

than a minimum of 20 completed 

HHCAHPS surveys, will better align the 

Model with HHCAHPS policy for the 

Patient Survey Star Ratings on Home 

Health Compare.14 The decision to use 

a minimum of 40 completed surveys for 

these star ratings was a result of 

balancing two competing goals. One 

goal was to provide star ratings that 

were meaningful and minimized 

random variations. This goal was best 

served by calculating star ratings for 

large numbers of cases by having a 

larger minimum of completed 

HHCAHPS surveys (for example, 50 or 

100 completed HHCAHPS surveys). At 

the same time, we also wanted to be 

able to provide star ratings for as many 

HHAs as possible. This goal was best 

served by using a lower minimum of 

completed HHCAHPS surveys (for 

example, 20 completed HHCAHPS 

surveys). We chose to balance these 

opposing and necessary goals by using 

40 completed HHCAHPS surveys for the 

Patient Survey Star Ratings. Because we 

believe that aligning the Patient Survey 

Star Ratings system and the HHVBP 

Model provides uniformity, consistency, 

and standard transformability for 

different healthcare platforms, we 

proposed using a minimum of 40 

instead of 20 completed HHCAHPS 

surveys under the HHVBP Model (82 FR 

35333). 

In the CY 2018 HH PPS proposed rule 

(82 FR 35333), we noted that we 

received a comment in response to the 

CY 2016 HH PPS proposed rule in 

support of using a higher minimum 

threshold for HHCAHPS completed 

surveys for the Patient Survey Star 

Ratings if the data are going to be used 

in HHVBP or any other quality 

assessment program. We also noted that 

we received public comment in 

response to the CY 2017 HH PPS 

proposed rule in support of using a 

higher minimum threshold for 

HHCAHPS completed surveys in the 

HHVBP Model, including a 

recommendation to use a minimum of 

100 HHCAHPS rather than a sample size 

of 20 surveys (82 FR 35333). We stated 

in the CY 2018 HH PPS proposed rule 

(82 FR 35333) that we believe that 

proposing a minimum of 40 completed 

HHCAHPS surveys for the Model would 

be more appropriate than the higher 

minimums previously recommended by 

some commenters because it represents 

a balance between providing meaningful 

data and having sufficient numbers of 

HHAs with performance scores for at 

least 5 measures in the cohorts. 

Moreover, using a minimum of 40 

completed HHCAHPS surveys aligns 

with the Patient Survey Star Ratings on 

Home Health Compare (82 FR 35333). 

To understand the possible impact of 

our proposal to use a minimum of 40 

HHCAHPS completed surveys, we noted 

in the CY 2018 HH PPS proposed rule 

(82 FR 35333) that HHAs may refer to 

the Interim Performance Reports (IPRs) 

issued in October 2016, January 2017 

and April 2017, which analyzed 40 or 

more completed HHCAHPS surveys to 

determine each HHA’s HHCAHPS 

quality measure scores. As a point of 

comparison to the minimum of 40 

HHCAHPS completed surveys, these 

IPRs were reissued using a minimum of 

20 or more completed HHCAHPS 

surveys and included quality measure 

scores, for these same time periods, 

calculated with HHAs that qualify for 

the LEF by having sufficient data for at 

least five measures. HHAs had the 

opportunity to submit a request for 

recalculation of the revised interim 

performance scores. 

HHAs had an opportunity to evaluate 

these IPRs in light of the proposal to 

change to a minimum of 40 HHCAHPS 

completed surveys, as well as seek 

clarification on the difference in their 

reports. The participating HHAs 

received concurrent IPRs in July 2017 

and concurrent Annual Total 

Performance Score and Payment 

Adjustment Reports, which we made 

available in August 2017. The 

concurrent reports showed one report 

with HHCAHPS quality measure scores 

calculated based on a minimum of 40 

completed surveys and one report with 

HHCAHPS quality measure scores 

calculated based on a minimum of 20 


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completed surveys. Because the CY 

2018 HH PPS proposed rule would not 

be finalized before the timeline for 

submission of recalculation and 

reconsideration requests, we noted 

HHAs would have the opportunity to 

submit recalculation requests for the 

interim performance scores based on 

both a minimum of 40 and 20 

completed surveys, and recalculation 

and reconsideration requests, as 

applicable, for the annual total 

performance scores included in these 

reports for these thresholds in 

accordance with the appeals process set 

forth at § 484.335, which was finalized 

in the CY 2017 HH PPS final rule (82 

FR 35333). 

As discussed in the CY 2018 HH PPS 

proposed rule (82 FR 35333 through 

35334), we analyzed the effects on 

participating HHAs of using the 

proposed 40 or more completed 

HHCAHPS surveys as compared to 

using 20 or more completed HHCAHPS 

surveys by examining OASIS measures 

submitted from January 1, 2015 through 

December 31, 2016, claims measures 

submitted from September 1, 2015 

through September 30, 2016, and 12 

months ending June 30, 2016 for 

HHCAHPS-based measures. We found 

that achievement thresholds, which are 

calculated as the median of all HHAs’ 

performance on the specified quality 

measures during the 2015 baseline year 

for each state, would not change by 

more than ±1.1 percent, with the largest 

changes occurring in the statewide 

achievement thresholds for the 

HHCAHPS Willingness to Recommend 

the Agency measure in Arizona (+1.1 

percent) and Nebraska (¥1.1 percent). 

Benchmarks (the mean of the top decile 

of Medicare-certified HHA performance 

on the specified quality measures 

during the 2015 baseline year, 

calculated for each state) had greater 

potential for change, ranging down to 

¥3.2 percent. For instance, we found 

that when calculated using a minimum 

of 40 surveys rather than a minimum of 

20 surveys, there was a ¥2.0 percent 

change in the benchmark for the 

HHCAHPS Willingness to Recommend 

the Agency measure for Arizona and a 

¥1.7 percent change in the benchmark 

for Nebraska. We also found that when 

calculated using a minimum of 40 

surveys rather than a minimum of 20 

surveys, there was a ¥1.7 percent 

change in the benchmark for the 

HHCAHPS Communications between 

Providers and Patients measure for 

Arizona, a ¥1.7 percent change in the 

benchmark for Florida, and a ¥3.2 

percent change in the benchmark for 

Nebraska. Overall, the proposed change 

in the HHCAHPS minimum of 40 

completed surveys was estimated to 

result in a limited percent change in the 

average statewide TPS for larger-volume 

HHAs, ranging from ¥0.4 through +2.2 

percent. We provided estimates of the 

expected payment adjustment 

distribution based on the proposed 

minimum of 40 completed HHCAHPS 

surveys in the impact analysis of the CY 

2018 HH PPS proposed rule (82 FR 

35387).’’ 

We invited public comment on our 

proposal to use 40 or more completed 

HHCAHPS surveys as the minimum to 

generate a quality measure score on the 

HHCAHPS measures, as is currently 

used in Home Health Compare and the 

Patient Survey Star Ratings. Therefore, 

we proposed to revise the definition of 

‘‘applicable measure’’ at § 484.305 from 

a measure for which the competing 

HHA has provided 20 home health 

episodes of care per year to a measure 

for which a competing HHA has 

provided a minimum of 20 home health 

episodes of care per year for the OASISbased measures, 20 home health 

episodes of care per year for the claimsbased measures, or 40 completed 

surveys for the HHCAHPS measures. We 

proposed that if finalized, this policy 

would apply to the calculation of the 

benchmark and achievement thresholds 

and the calculation of performance 

scores for all Model years, beginning 

with PY 1. 

The following is a summary of the 

public comments received on this 

proposal and our responses: 

Comment: Most commenters 

supported CMS’ proposal to adjust the 

minimum number of completed Home 

Health Care Consumer Assessment of 

Healthcare Providers and System 

(HHCAHPS) Surveys. Several of these 

commenters expressed that it will result 

in more reliable and valid data results, 

as well as better align with the Patient 

Survey Star Ratings policy. A few 

commenters expressed concern about 

the proposed change and that using a 

minimum of 40 completed HHCAHPS 

surveys will greatly reduce the number 

of agencies with data sufficient for 

Model participation. A commenter 

specifically requested that CMS provide 

a clear and separate announcement 

regarding the change in survey 

minimum, how to interpret changes in 

total performance scores, and how to 

engage in the appeals process. Finally, 

a few commenters were concerned that 

smaller volume agencies will be 

negatively impacted, or forced to close, 

given the shift from 20 to 40 completed 

HHCAHPS surveys. 

Response: We appreciate commenters’ 

support for our proposal to use a 

minimum of 40 completed HHCAHPS 

surveys, rather than a minimum of 20 

completed HHCAHPS surveys. We 

continue to believe that a minimum of 

40 completed HHCAHPS surveys, rather 

than a minimum of 20 completed 

HHCAHPS surveys, better aligns the 

Model with HHCAHPS policy for the 

Patient Survey Star Ratings on Home 

Health Compare. As discussed in the 

proposed rule, we believe that aligning 

the Patient Survey Star Ratings and the 

HHVBP Model will provide uniformity, 

consistency, and standard 

transformability for different healthcare 

platforms. While we recognize that this 

change could result in fewer agencies 

receiving a measure score on the 

HHCAHPS measures, we believe, as 

indicated in the proposed rule, that 

using a minimum of 40 completed 

HHCAHPS surveys represents an 

appropriate balance between providing 

meaningful data and having sufficient 

numbers of HHAs with performance 

scores on five other measures (for 

example OASIS based and claims based) 

to be included in the LEF. As we 

discuss later in this section, however, 

our updated analysis using full CY 2016 

data found that no HHA fell below the 

minimum of having five measures to 

generate a TPS as a result of using a 

minimum of 40 rather than 20 

completed HHCAHPs surveys. 

For purposes of this final rule, we 

analyzed the effects on participating 

HHAs of using the proposed 40 or more 

completed HHCAHPS surveys as 

compared to using 20 or more 

completed HHCAHPS surveys by 

examining OASIS, claims and 

HHCAHPS measures from January 1, 

2016 to December 31, 2016. We found 

that achievement thresholds will not 

change by more than ±1.1 percent, with 

the largest changes occurring in the 

statewide achievement thresholds for 

the HHCAHPS Willingness to 

Recommend the Agency measure in 

Arizona (+1.1 percent) and Nebraska 

(¥1.1 percent). Benchmarks continued 

to have greater potential for change, 

ranging down to ¥3.1 percent. For 

instance, we found that when calculated 

using a minimum of 40 surveys rather 

than a minimum of 20 surveys, there 

was a ¥2.0 percent change in the 

benchmark for the HHCAHPS 

Willingness to Recommend the Agency 

measure for Arizona and a ¥1.7 percent 

change in the benchmark for Nebraska. 

We also found that when calculated 

using a minimum of 40 surveys rather 

than a minimum of 20 surveys, there 

was a ¥1.6 percent change in the 

benchmark for the HHCAHPS 

Communications between Providers and 


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15 2015 Annual Report to Congress, http://

www.ahrq.gov/workingforquality/reports/annualreports/nqs2015annlrpt.htm. 

Patients measure for Arizona, a ¥1.7 

percent change in the benchmark for 

Florida, and a ¥3.1 percent change in 

the benchmark for Nebraska. 

Overall, based on this updated 

analysis using full CY 2016 data, the 

proposed change in the HHCAHPS 

minimum of 40 completed surveys was 

estimated to result in a limited percent 

change in the average statewide TPS for 

larger-volume HHAs, ranging from ¥0.3 

percent through +1.8 percent and the 

majority of the states were close to zero. 

Additionally, the updated analysis 

using full CY 2016 data found that there 

were no Medicare-certified HHAs in the 

selected states that fell below the 

minimum of having five measures to 

generate a TPS for CY 2018 as a result 

of using a minimum of 40 rather than 

20 completed HHCAHPs surveys. 

To provide HHAs with information on 

the effects of using a minimum of 40 

completed HHCAHPS surveys, rather 

than a minimum of 20 completed 

HHCAHPS surveys, we reissued the 

October 2016, January 2017 and April 

2017 IPRs, which analyzed 40 or more 

completed HHCAHPS surveys, so that 

they could be recalculated with HHAs 

that have 20 or more completed 

HHCAHPS surveys. Moreover, CMS 

provided HHAs with concurrent IPRs in 

July 2017 and concurrent Annual Total 

Performance Score and Payment 

Adjustment Reports in August 2017 to 

show one report with HHCAHPS quality 

measure scores calculated based on a 

minimum of 40 completed surveys and 

one report with HHCAHPS quality 

measure scores calculated based on a 

minimum of 20 completed surveys. 

HHAs also had the opportunity to 

submit recalculation requests for the 

interim performance scores and 

recalculation and reconsideration 

requests, as applicable, for the annual 

total performance scores, in accordance 

with the process set forth at § 484.335. 

Additionally, we provided a number of 

webinars and other information on the 

interpretation of the quality measure 

scores and the Total Performance Scores 

and on the appeals process. More 

specifically, we provided all HHAs with 

a questions and answers document on 

the use of HHCAHPS measures in 

HHVBP Model performance reports 

when the reissued and concurrent IPRs 

were made available. These reports and 

communications provided points of 

comparison, clarification and 

information on the potential impact of 

using a minimum of 40 completed 

HHCAHPS surveys, rather than a 

minimum of 20 completed HHCAHPS 

surveys, to generate a quality measure 

score on the HHCAHPS measures. CMS 

notes that no recalculation requests on 

the reissued and concurrent IPRs were 

received and no recalculation or 

reconsideration requests on the 

concurrent Annual Reports were 

received that related to our proposal to 

change to the minimum of 40 completed 

HHCAHPS surveys. 

The change from a minimum of 20 

completed HHCAHPS surveys to a 

minimum of 40 completed HHCAHPS 

surveys was not intended to negatively 

impact smaller agencies. We do not 

believe smaller HHAs will be 

disadvantaged by this change to a 

minimum of 40, because given their 

exemption from HHCAHPS reporting 

requirements, it is unlikely they would 

be measured on HHCAHPS under the 

Model and they can still compete on 

other measures. 

We will continue to monitor the 

impacts of using a minimum of 40 

completed HHCAHPS surveys, rather 

than a minimum of 20 completed 

HHCAHPS surveys, for purposes of 

receiving a performance score for any of 

the HHCAHPS measures. 

Comment: A commenter suggested 

that because one negative survey might 

affect a score based on a minimum of 20 

completed HHCAHPS surveys, 

removing the lowest and highest 

HHCAHPS for HHAs may be an 

effective method to align with the 

average customer response. 

Response: We believe this comment is 

outside of the scope of the proposed 

methodology change in the CY 2018 HH 

PPS proposed rule to use a minimum of 

40 completed HHCAHPS surveys rather 

than a minimum of 20 completed 

HHCAHPS surveys. However, we note 

that we believe each HHCAHPS survey 

may be an important avenue for public 

quality reporting and continued 

improvement within the HHA 

environment. 

Final Decision: For the reasons stated 

previously and in consideration of the 

comments received, we are finalizing 

our proposal to amend the definition of 

‘‘applicable measure’’ to mean a 

measure for which a competing HHA 

has provided a minimum of 40 

completed surveys for HHCAHPS 

measures, for purposes of receiving a 

performance score for any of the 

HHCAHPS measures, beginning with 

PY1. In addition, we are finalizing a few 

minor technical edits to the regulation 

at § 484.305 to replace the colon and 

spell out ‘‘twenty’’ and ‘‘forty’’ (rather 

than ‘‘20’’ and ‘‘40’’). 

2. Removal of One OASIS-Based 

Measure Beginning With Performance 

Year 3 

In the CY 2016 HH PPS final rule, we 

finalized a set of quality measures in 

Figure 4a: Final PY1 Measures and 

Figure 4b: Final PY1 new measures (80 

FR 68671 through 68673) for the 

HHVBP Model to be used in PY 1, 

referred to as the starter set. 

The measures were selected for the 

Model using the following guiding 

principles: (1) Use a broad measure set 

that captures the complexity of the 

services HHAs provide; (2) Incorporate 

the flexibility for future inclusion of the 

Improving Medicare Post-Acute Care 

Transformation Act of 2014 (IMPACT) 

measures that cut across post-acute care 

settings; (3) Develop ‘second generation’ 

(of the HHVBP Model) measures of 

patient outcomes, health and functional 

status, shared decision making, and 

patient activation; (4) Include a balance 

of process, outcome and patient 

experience measures; (5) Advance the 

ability to measure cost and value; (6) 

Add measures for appropriateness or 

overuse; and (7) Promote infrastructure 

investments. This set of quality 

measures encompasses the multiple 

National Quality Strategy (NQS) 

domains 15 (80 FR 68668). The NQS 

domains include six priority areas 

identified in the CY 2016 HH PPS final 

rule (80 FR 68668) as the CMS 

Framework for Quality Measurement 

Mapping. These areas are: (1) Clinical 

quality of care; (2) care coordination; (3) 

population & community health; (4) 

person- and caregiver-centered 

experience and outcomes; (5) safety; and 

(6) efficiency and cost reduction. 

Figures 4a and 4b of the CY 2016 HH 

PPS final rule (80 FR 68671 through 

68673) identified 15 outcome measures 

(five from the HHCAHPS, eight from 

Outcome and Assessment Information 

Set (OASIS), and two from the Chronic 

Care Warehouse (claims)), and nine 

process measures (six from OASIS, and 

three new measures, which were not 

previously reported in the home health 

setting). 

In the CY 2017 HH PPS final rule (81 

FR 76743 through 76747), we removed 

the following four measures from the 

measure set for PY 1 and subsequent 

performance years: (1) Care 

Management: Types and Sources of 

Assistance; (2) Prior Functioning ADL/ 

IADL; (3) Influenza Vaccine Data 

Collection Period: Does this episode of 

care include any dates on or between 

October 1 and March 31?; and (4) 

Reason Pneumococcal Vaccine Not 

Received, for the reasons discussed in 

that final rule. 

For PY 3, we proposed to remove one 

OASIS-based measure, Drug Education 


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16 Jimmo v. Sebelius Settlement Agreement Fact 

Sheet: https://www.cms.gov/Medicare/MedicareFee-for-Service-Payment/SNFPPS/Downloads/Jimmo-FactSheet.pdf. 

on All Medications Provided to Patient/ 

Caregiver during All Episodes of Care, 

from the set of applicable measures (82 

FR 35334). We stated in the CY 2018 HH 

PPS proposed rule that, as part of our 

ongoing monitoring efforts, we found 

that based on the standard metrics of 

measure performance, many providers 

have achieved full performance on the 

Drug Education measure. For example, 

for the January 2017 IPRs (which 

covered the 12-month period of October 

1, 2015 through September 30, 2016), 

the average value for this measure 

across all participating HHAs was 95.69 

percent from October 2015 through 

September 2016. When looking at 

September 2016, the mean value on this 

measure across all participating HHAs 

had increased to 97.8 percent. In 

addition, we noted that there are few 

HHAs with poor performance on the 

measure. Based on the January 2017 

IPRs, across all participating HHAs, the 

10th percentile was 89 percent and the 

5th percentile was 81.8 percent, but 

only 1.8 percent of HHAs had a value 

below 70 percent on the measure. We 

stated in the CY 2018 HH PPS proposed 

rule (82 FR 35334) that we believe that 

removing this measure would be 

consistent with our policy, as noted in 

the CY 2017 HH PPS final rule (81 FR 

76746), that when a measure has 

achieved full performance, we may 

propose the removal of the measure in 

future rulemaking. In addition, our 

contractor’s Technical Expert Panel 

(TEP), which consists of 11 panelists 

with expertise in home health care and 

quality measures, expressed concern 

that the Drug Education measure does 

not capture whether the education 

provided by the HHA was meaningful. 

We presented the revised set of 

applicable measures, reflecting our 

proposal to remove the OASIS-based 

measure, Drug Education on All 

Medications Provided to Patient/

Caregiver during All Episodes of Care, 

in Table 43 of the CY 2018 HH PPS 

proposed rule. We stated that this 

measure set would be applicable to PY3 

and each subsequent performance year 

until such time that another set of 

applicable measures, or changes to this 

measure set, are proposed and finalized 

in future rulemaking (82 FR 35334 

through 35336). 

We invited public comment on the 

proposal to remove one OASIS-based 

measure, Drug Education on All 

Medications Provided to Patient/

Caregiver during All Episodes of Care, 

from the set of applicable measures for 

PY3 and subsequent performance years 

and Table 43 of the CY 2018 HH PPS 

proposed rule. The following is a 

summary of the public comments 

received on this proposal and our 

responses: 

Comment: Several commenters 

expressed support for removing the 

OASIS-based quality measure, Drug 

Education on All Medications Provided 

to Patient/Caregiver during All Episodes 

of Care, from the set of applicable 

measures as it has ‘‘topped out.’’ 

Response: We appreciate the support 

regarding the proposed removal of the 

‘‘Drug Education’’ measure from the 

HHVBP Model’s set of applicable 

measures because it has ‘‘topped out’’. 

We are finalizing the removal of the 

‘‘Drug Education’’ measure as most 

providers have achieved full 

performance on the measure. 

Comment: Several commenters 

provided feedback regarding the 

measure set more generally and some 

were outside of the scope of the 

proposed change. A commenter 

recommended that CMS consider 

assigning 50 percent of the ‘‘Star 

Rating’’ and HHVBP performance to 

claims-based measures and Patient 

Satisfaction, as the commenter believed 

that these measures are difficult or 

impossible to manipulate, and then 

assign the other 50 percent to OASISbased self-reported measures. A 

commenter expressed concern that the 

measure set for the HHVBP Model 

mainly requires improvement in patient 

functioning and that this conflicts 

directly with the Jimmo v. Sebelius 

settlement.16 Another commenter 

recommended replacing the 

Pneumococcal Polysaccharide Vaccine 

Ever Received (NQF#0525) because the 

measure no longer reflects current 

recommendations of the Advisory 

Committee for Immunization Practice 

(ACIP). 

Response: We appreciate the 

comments on the measures 

methodology and, as discussed in the 

CY 2016 HH PPS final rule (80 FR 

68669) and CY 2017 HH PPS final rule 

(81 FR 76747), acknowledge that skilled 

care may be necessary to improve a 

patient’s current condition, to maintain 

the patient’s current condition, or to 

prevent or slow further deterioration of 

the patient’s condition, as was clarified 

through the provisions revised as part of 

Jimmo v. Sebelius settlement. As stated 

in those rules, this settlement agreement 

pertains only to the clarification of 

CMS’s manual guidance on coverage 

standards, not payment measures like 

those at issue here, and expressly does 

not pertain to or prevent the 

implementation of new regulations, 

including new regulations pertaining to 

the HHVBP Model. We refer readers to 

the CY 2016 HH PPS final rule (80 FR 

68669 through 68670) for additional 

discussion of our analyses of measure 

selection, including our analyses of 

existing measures relating to 

improvement and stabilization. As 

discussed in that rule, the HHVBP 

Model is designed such that any 

measures determined to be good 

indicators of quality will be considered 

for use in the HHVBP Model in future 

years and may be added through the 

rulemaking process. As discussed in 

prior years, we will continue to seek 

and consider input we have received on 

the measure set for the HHVBP Model. 

Final Decision: We are finalizing our 

proposal to remove the OASIS-based 

measure, Drug Education on All 

Medications Provided to Patient/

Caregiver during All Episodes of Care, 

from the set of applicable measures for 

PY3 and subsequent years, as reflected 

in Table 15. Table 15 identifies the 

applicable measures set for PY3 and 

each subsequent performance year until 

such time that another set of applicable 

measures, or changes to this measure 

set, are proposed and finalized in future 

rulemaking. 

TABLE 15—MEASURE SET FOR THE HHVBP MODEL* BEGINNING PY 3 

NQS domains Measure title Measure type Identifier Data source Numerator Denominator 

Clinical Quality of 

Care.

Improvement in 

Ambulation-Locomotion.

Outcome ....... NQF0167 ...... OASIS 

(M1860).

Number of home health episodes 

of care where the value recorded 

on the discharge assessment indicates less impairment in ambulation/locomotion at discharge 

than at the start (or resumption) 

of care.

Number of home health episodes 

of care ending with a discharge 

during the reporting period, other 

than those covered by generic or 

measure-specific exclusions. 


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TABLE 15—MEASURE SET FOR THE HHVBP MODEL* BEGINNING PY 3—Continued 

NQS domains Measure title Measure type Identifier Data source Numerator Denominator 

Clinical Quality of 

Care.

Improvement in 

Bed Transferring.

Outcome ....... NQF0175 ...... OASIS 

(M1850).

Number of home health episodes 

of care where the value recorded 

on the discharge assessment indicates less impairment in bed 

transferring at discharge than at 

the start (or resumption) of care.

Number of home health episodes 

of care ending with a discharge 

during the reporting period, other 

than those covered by generic or 

measure-specific exclusions. 

Clinical Quality of 

Care.

Improvement in 

Bathing.

Outcome ....... NQF0174 ...... OASIS 

(M1830).

Number of home health episodes 

of care where the value recorded 

on the discharge assessment indicates less impairment in bathing at discharge than at the start 

(or resumption) of care.

Number of home health episodes 

of care ending with a discharge 

during the reporting period, other 

than those covered by generic or 

measure-specific exclusions. 

Clinical Quality of 

Care.

Improvement in 

Dyspnea.

Outcome ....... NA ................. OASIS 

(M1400).

Number of home health episodes 

of care where the discharge assessment indicates less dyspnea 

at discharge than at start (or resumption) of care.

Number of home health episodes 

of care ending with a discharge 

during the reporting period, other 

than those covered by generic or 

measure-specific exclusions. 

Communication & 

Care Coordination.

Discharged to 

Community.

Outcome ....... NA ................. OASIS 

(M2420).

Number of home health episodes 

where the assessment completed 

at the discharge indicates the patient remained in the community 

after discharge.

Number of home health episodes 

of care ending with discharge or 

transfer to inpatient facility during 

the reporting period, other than 

those covered by generic or 

measure-specific exclusions. 

Efficiency & Cost 

Reduction.

Acute Care Hospitalization: Unplanned Hospitalization during first 60 

days of Home 

Health.

Outcome ....... NQF0171 ...... CCW (Claims) Number of home health stays for 

patients who have a Medicare 

claim for an unplanned admission to an acute care hospital in 

the 60 days following the start of 

the home health stay.

Number of home health stays that 

begin during the 12-month observation period. A home health 

stay is a sequence of home 

health payment episodes separated from other home health 

payment episodes by at least 60 

days. 

Efficiency & Cost 

Reduction.

Emergency Department Use 

without Hospitalization.

Outcome ....... NQF0173 ...... CCW (Claims) Number of home health stays for 

patients who have a Medicare 

claim for outpatient emergency 

department use and no claims 

for acute care hospitalization in 

the 60 days following the start of 

the home health stay.

Number of home health stays that 

begin during the 12-month observation period. A home health 

stay is a sequence of home 

health payment episodes separated from other home health 

payment episodes by at least 60 

days. 

Patient Safety ....... Improvement in 

Pain Interfering 

with Activity.

Outcome ....... NQF0177 ...... OASIS 

(M1242).

Number of home health episodes 

of care where the value recorded 

on the discharge assessment indicates less frequent pain at discharge than at the start (or resumption) of care.

Number of home health episodes 

of care ending with a discharge 

during the reporting period, other 

than those covered by generic or 

measure-specific exclusions. 

Patient Safety ....... Improvement in 

Management of 

Oral Medications.

Outcome ....... NQF0176 ...... OASIS 

(M2020).

Number of home health episodes 

of care where the value recorded 

on the discharge assessment indicates less impairment in taking 

oral medications correctly at discharge than at start (or resumption) of care.

Number of home health episodes 

of care ending with a discharge 

during the reporting period, other 

than those covered by generic or 

measure-specific exclusions. 

Population/Community Health.Influenza Immunization Received for Current Flu Season.

Process ......... NQF0522 ...... OASIS 

(M1046).

Number of home health episodes 

during which patients (a) received vaccination from the HHA 

or (b) had received vaccination 

from HHA during earlier episode 

of care, or (c) was determined to 

have received vaccination from 

another provider.

Number of home health episodes 

of care ending with discharge, or 

transfer to inpatient facility during 

the reporting period, other than 

those covered by generic or 

measure-specific exclusions. 

Population/Community Health.Pneumococcal 

Polysaccharide 

Vaccine Ever 

Received.

Process ......... NQF0525 ...... OASIS 

(M1051).

Number of home health episodes 

during which patients were determined to have ever received 

Pneumococcal Polysaccharide 

Vaccine (PPV).

Number of home health episodes 

of care ending with discharge or 

transfer to inpatient facility during 

the reporting period, other than 

those covered by generic or 

measure-specific exclusions. 

Patient & Caregiver-Centered 

Experience.

Care of Patients Outcome ....... ....................... CAHPS ......... NA ................................................... NA. 

Patient & Caregiver-Centered 

Experience.

Communications 

between Providers and Patients.

Outcome ....... ....................... CAHPS ......... NA ................................................... NA. 

Patient & Caregiver-Centered 

Experience.

Specific Care 

Issues.

Outcome ....... ....................... CAHPS ......... NA ................................................... NA. 

Patient & Caregiver-Centered 

Experience.

Overall rating of 

home health 

care.

Outcome ....... ....................... CAHPS ......... NA ................................................... NA. 


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TABLE 15—MEASURE SET FOR THE HHVBP MODEL* BEGINNING PY 3—Continued 

NQS domains Measure title Measure type Identifier Data source Numerator Denominator 

Patient & Caregiver-Centered 

Experience.

Willingness to 

recommend the 

agency.

Outcome ....... ....................... CAHPS ......... NA ................................................... NA. 

Population/Community Health.Influenza Vaccination Coverage for Home 

Health Care 

Personnel.

Process ......... NQF0431 

(Used in 

other care 

settings, not 

Home 

Health).

Reported by 

HHAs 

through 

Web Portal.

Healthcare personnel in the denominator population who during 

the time from October 1 (or when 

the vaccine became available) 

through March 31 of the following 

year: a) received an influenza 

vaccination administered at the 

healthcare facility, or reported in 

writing or provided documentation that influenza vaccination 

was received elsewhere: or b) 

were determined to have a medical contraindication/condition of 

severe allergic reaction to eggs 

or to other components of the 

vaccine or history of GuillainBarre Syndrome within 6 weeks 

after a previous influenza vaccination; or c) declined influenza 

vaccination; or d) persons with 

unknown vaccination status or 

who do not otherwise meet any 

of the definitions of the abovementioned numerator categories.

Number of healthcare personnel 

who are working in the 

healthcare facility for at least 1 

working day between October 1 

and March 31 of the following 

year, regardless of clinical responsibility or patient contact. 

Population/Community Health.Herpes zoster 

(Shingles) vaccination: Has 

the patient ever 

received the 

shingles vaccination? 

Process ......... NA ................. Reported by 

HHAs 

through 

Web Portal.

Total number of Medicare beneficiaries aged 60 years and over 

who report having ever received 

zoster vaccine (shingles vaccine).

Total number of Medicare beneficiaries aged 60 years and over 

receiving services from the HHA. 

Communication & 

Care Coordination.

Advance Care 

Plan.

Process ......... NQF0326 ...... Reported by 

HHAs 

through 

Web Portal.

Patients who have an advance 

care plan or surrogate decision 

maker documented in the medical record or documentation in 

the medical record that an advanced care plan was discussed 

but the patient did not wish or 

was not able to name a surrogate decision maker or provide 

an advance care plan.

All patients aged 65 years and 

older. 

* Notes: For more detailed information on the measures utilizing OASIS refer to the OASIS–C1/ICD–9, Changed Items & Data Collection Resources dated September 3, 2014 available at www.oasisanswers.com/LiteratureRetrieve.aspx?ID=215074. For NQF endorsed measures see The NQF Quality Positioning System 

available at http://www.qualityforum.org/QPS. For non-NQF measures using OASIS see links for data tables related to OASIS measures at http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html. For information on HHCAHPS measures see https://

homehealthcahps.org/SurveyandProtocols/SurveyMaterials.aspx. 

C. Quality Measures for Future 

Consideration 

The CY 2016 HH PPS final rule 

discusses the HHVBP Model design, the 

guiding principles to select measures, 

and the six priority areas of the National 

Quality Strategy (NQS) we considered 

for the Model (80 FR 68656 through 

68678). Under the HHVBP Model, any 

measures we determine to be good 

indicators of quality will be considered 

for use in the HHVBP Model in future 

years, and may be added or removed 

through the rulemaking process. To 

further our commitment to objectively 

assess HHVBP quality measures, we are 

utilizing an implementation contractor 

that invited a group of measure experts 

to provide advice on the adjustment of 

the current measure set for 

consideration. The contractor convened 

a technical expert panel (TEP) 

consisting of 11 panelists with expertise 

in home health care and quality 

measures that met on September 7, 

2016, in Baltimore, Maryland and via 

conference call on December 2, 2016. 

The TEP discussed developing a 

composite total change in ADL/IADL 

measure; a composite functional decline 

measure; a measure to capture when an 

HHA correctly identifies the patient’s 

need for mental and behavioral health 

supervision; and a measure to identify 

if a caregiver is able to provide the 

patient’s mental or behavioral health 

supervision, to align with 

§ 409.45(b)(3)(iii) and the Medicare 

Benefit Policy Manual (Pub. 100–02), 

Chapter 7, Section 20.2. We discussed 

each of these potential measures in 

further detail in the CY 2018 HH PPS 

proposed rule (82 FR 35336 through 

35340), and also discuss in this section 

of this final rule. While any new 

measures would be proposed for use in 

future rulemaking, we solicited 

comment on these potential measures 

now to inform measure development 

and selection. 

As noted in the CY 2017 HH PPS final 

rule (81 FR 76747), we received several 

comments expressing concern that the 

measures under the Model do not reflect 

the patient population served under the 

Medicare Home Health benefit as the 

outcome measures focus on a patient’s 

clinical improvement and do not 

address patients with chronic illnesses; 

deteriorating neurological, pulmonary, 

cardiac, and other conditions; and some 

with terminal illness. The commenters 

opined that the value of including 

stabilization measures in the HHVBP 

Model is readily apparent as it aligns 

the Model with the Medicare Home 

Health benefit. Commenters also 

expressed concerns that improvement is 

not always the goal for each patient and 


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Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 51707 

17Fox, John (1997). Applied Regression Analysis, 

Linear Models, and Related\Methods/Edition 1, 

1997, SAGE. 

18 Greene, William H. (2017). Econometric 

analysis (8th ed.). New Jersey: Pearson. ISBN 978– 

0134461366. 

that stabilization is a reasonable clinical 

goal for some patients. Commenters 

suggested the addition of stabilization or 

maintenance measures be considered for 

the HHVBP Model. Many commenters 

objected to the use of improvement 

measures in the HHVBP Model. We did 

not receive any specific measures for 

future consideration as part of those 

comments. In the CY 2018 HH PPS 

proposed rule (82 FR 35336 through 

35340), we identified measures that we 

are considering for possible inclusion 

under the Model in future rulemaking 

and sought input from the public on the 

measures described, as well as any 

input about the development or 

construction of the measures and their 

features or methodologies. We are also 

including the description of these 

possible measures in this final rule in 

the subsections that follow. 

1. Total Change in ADL/IADL 

Performance by HHA Patients 

The measure set finalized in the CY 

2016 HH PPS final rule included 

Change in Daily Activity Function as 

Measured by the Activity Measure for 

Post-Acute Care (AM–PAC) (NQF 

#0430). However, the measure was 

removed in the CY 2017 HH PPS final 

rule and never used in the HHVBP 

Model because the measure required use 

of a proprietary data collection 

instrument in the home health 

environment. We stated in the CY 2018 

HH PPS proposed rule that we were 

considering replacing Change in Daily 

Activity Function as Measured by AM– 

PAC (NQF #0430) with a composite 

total ADL/IADL change performance 

measure. During the September 2016 

TEP meeting, an alternative to the 

Change in Daily Activity Function 

measure was presented. The TEP 

requested that a composite Total ADL/ 

IADL Change measure be investigated 

empirically. This measure was 

discussed as part of the follow-up 

conference call, and the TEP supported 

continued development of the measure 

in the HHVBP Model as a way of 

including a measure that captures all 

three potential outcomes for home 

health patients: stabilization; decline; 

and improvement. They provided input 

on the technical specifications of the 

potential composite measure, including 

the feasibility of implementing the 

measure and the overall measure 

reliability and validity. We noted in the 

CY 2018 HH PPS proposed rule that we 

reviewed this suggested alternative and 

believe this measure would provide 

actionable and transparent information 

that would support HHA efforts to 

improve care and prevent functional 

decline for all patients across a broad 

range of patient functional outcomes. 

The measure would also improve 

accountability during an episode of care 

when the patient is directly under the 

HHA’s care. 

We noted in the CY 2018 HH PPS 

proposed rule that the name of this 

potential composite measure could be 

Total Change in ADL/IADL Performance 

by HHA Patients. The measure would 

report the average, normalized, total 

improved functioning across the 11 

ADL/IADL items on the current OASIS– 

C2 instrument. The measure is 

calculated by comparing scores from the 

start-of-care/resumption of care to 

scores at discharge. For each item the 

patient’s discharge assessed 

performance score is subtracted from 

the patient’s start of care/resumption of 

care assessed performance score, and 

then divided by the maximum 

improvement value based on the 

number of response options for that 

item. These values are summed into a 

total normalized change score that can 

range from ¥11 (that is, for an episode 

where there is maximum decline on all 

11 items used in the measure) to +11 

(that is, for an episode where there is 

the maximum improvement on all 11 

items). An HHA’s score on the measure 

is based on its average across all eligible 

episodes. Patients who are independent 

on all 11 ADL/IADL items at Start of 

Care (SOC)/Resumption of Care (ROC) 

would also be included in the measure. 

The HHA’s observed score on the 

measure is the average of the 

normalized total scores for all eligible 

episodes for its patients during the 

reporting period. 

The following 11 ADLs/IADL-related 

items from OASIS–C2 items were 

included in developing a composite 

measure: 

ADL OASIS–C2 items related to SelfCare: 

• M1800 (Grooming). 

• M1810 (Upper body dressing). 

• M1820 (Lower body dressing). 

• M1845 (Toileting hygiene). 

• M1870 (Eating). 

ADL OASIS–C2 items related to 

Mobility: 

• M1840 (Toilet transferring). 

• M1840 (Bed transferring). 

• M1860 (Ambulation). 

Other IADLs OASIS items: 

• M1880 (Light meal preparation). 

• M1890 (Telephone use). 

• M2020 (Oral medication 

management). 

Based on these identified measures, 

we would risk-adjust using OASIS–C2 

items to account for case-mix variation 

and other factors that affect functional 

decline but are outside the influence of 

the HHA. The risk-adjustment model 

uses an ordinary least squares (OLS) 17 18

regression framework because the 

outcome measure (normalized change in 

ADL/IADL performance) is a continuous 

variable. 

The prediction model for this 

outcome measure was derived using the 

predicted values from the 11 individual 

outcomes that are currently used to risk 

adjust these 11 individual quality 

measures. Of the 11 values tested, the 8 

identified in the proposed rule were 

found to be statistically related to the 

Total Change in ADL/IADL Performance 

by HHA Patients measure at p < 0.0001 

level and would be used in the 

prediction model that we are 

considering proposing to use to risk 

adjust the HHA’s observed value for this 

potential future measure. The prediction 

model for this outcome measure uses 

predicted values from the following 

individual outcomes (NOTE: The primary 

source OASIS item is listed in 

parenthesis after the name of the quality 

measure): 

• Improvement in Upper Body 

Dressing (M1810). 

• Improvement in Management of 

Oral Medications (M2020). 

• Improvement in Bed Transferring 

(M1850). 

• Improvement in Ambulation/

Locomotion (M1860). 

• Improvement in Grooming (M1800). 

• Improvement in Toileting Hygiene 

(M1845). 

• Discharged to the Community 

(M2420). 

• Improvement in Toileting Transfer 

(M1840). 

Two predictive models, one based on 

predicted values from CY 2014 and one 

from CY 2015, were computed. The 

correlations at the episode level 

between observed and predicted values 

for the target outcome measure Total 

Change in ADL/IADL Performance by 

HHA Patients are shown in Table 16. 


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51708 Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 

19 ‘‘Long-stay Nursing Home Care: Percent of 

Residents Whose Need for help with Activities of 

Daily Living has Increased.’’ https://

www.qualitymeasures.ahrq.gov/summaries/

summary/50060. 

TABLE 16—CORRELATIONS AT THE EPISODE LEVEL BETWEEN OBSERVED AND PREDICTED VALUES FOR THE TARGET

OUTCOME MEASURE TOTAL CHANGE IN ADL/IADL PERFORMANCE BY HHA PATIENTS

Data group Correlation Significance 

(p < ) 

r2 (Coeff. 

Determination) 

% 

CY2014, National ......................................................................................................................... 0.5022 0.0001 25.22 

CY2014, HHVBP states ............................................................................................................... 0.5094 0.0001 25.95 

CY2015, National ......................................................................................................................... 0.5011 0.0001 25.11 

CY2015, HHVBP states ............................................................................................................... 0.5076 0.0001 25.76 

The results in Table 16 suggest that 

either model would account for 25 

percent or more of the variability in the 

outcome measure. These models could 

be considered very strong predictive 

models for the target outcome measure. 

Although the analysis supports 

developing a composite measure, the 

analysis assumes that the OASIS–C2 

items identified to be used in the 

composite measure do not change. 

However, we recognize that OASIS–C2 

items could be removed or added in any 

given year. We expect to conduct an 

additional analysis, in advance of any 

future proposal, to assess whether 

changes to OASIS–C2 items that are 

removed or added could significantly 

impact a HHA’s ability to address 

several measures to improve its overall 

score in the composite measure. We 

solicited public comments on whether 

or not to include a composite total ADL/ 

IADL change performance measure in 

the set of applicable measures, the name 

of any such measure, the risk 

adjustment method, and whether we 

should conduct an analysis of the 

impact of removal/addition of OASIS– 

C2 items. 

2. Composite Functional Decline 

Measure 

The second measure we are 

considering for possible inclusion under 

the Model in future rulemaking is a 

Composite Functional Decline Measure 

that could be the percentage of episodes 

where there was decline on one or more 

of the eight ADL items used in the 

measure. As noted in the CY 2018 HH 

PPS proposed rule and this final rule, 

we received comments on the CY 2017 

HH PPS proposed rule suggesting that 

we consider the addition of stabilization 

or maintenance measures. We stated in 

the CY 2018 HH PPS proposed rule that 

to address this suggestion, we are 

considering a composite functional 

decline measure because the existing 

functional stabilization measures, taken 

individually, are topped out, with HHA 

level means of 95 percent or higher. 

This type of composite functional 

decline measure is similar to the 

composite ADL decline measure that is 

used in the Skilled Nursing Facility 

(SNF) Quality Reporting program 

(QRP).19 The SNF QRP measure is 

constructed from four ADL items: Bed 

mobility; transfer; eating; and toileting. 

An HHVBP composite functional 

decline measure could provide 

actionable and transparent information 

that could support HHA efforts to 

improve care and prevent functional 

decline for all patients, including those 

for whom improvement in functional 

status is not a realistic care goal. We 

noted in the CY 2018 HH PPS proposed 

rule that this concept was discussed 

during the TEP meeting on September 7, 

2016, with a follow-up conference call 

held on December 2, 2016. The TEP 

supported the inclusion of measures of 

stabilization and decline in the HHVBP 

Model, as well as further development 

of the composite functional decline 

measure. They provided input on the 

technical specifications of the potential 

composite measure, including the 

feasibility of implementing the measure 

and the overall measure reliability and 

validity. 

When calculating the composite 

functional decline measure, we noted 

that we could use the following 8 

existing OASIS–C2 items: 

• Ambulation/Locomotion (M1860). 

• Bed Transferring (M1840). 

• Toilet Transferring (M1840). 

• Bathing (M1830). 

• Toilet Hygiene (M1845). 

• Lower Body Dressing (M1820). 

• Upper Body Dressing (M1810). 

• Grooming (M1800). 

We noted that the measure could be 

defined as 1 if there is decline reported 

in one or more of these items between 

the Start of Care and the Discharge 

assessments and zero if no decline is 

reported on any of these items. As with 

other OASIS-based measures, a 

performance score for the measure 

would only be calculated for HHAs that 

have 20 or more episodes of care during 

a performance year. 

The measure could be risk-adjusted 

using OASIS–C2 items to account for 

case-mix variation and other factors that 

affect functional decline but are outside 

of the influence of the HHA. The riskadjustment model uses a logistic 

regression framework. The model 

includes a large number of patient 

clinical conditions and other 

characteristics measured at start of care. 

A logistic regression model is estimated 

to predict whether the patient will have 

a length of stay of greater than 60 days. 

The predicted probability of a length of 

stay of greater than 60 days is used, 

along with other patient characteristics, 

to construct a logistic regression model 

to predict the probability of decline in 

any of eight ADLs. This model is used 

to estimate the predicted percent of ADL 

decline at the HHA level. To calculate 

case-mix adjusted values, the observed 

value of the measure is adjusted by the 

difference between the HHA predicted 

percent and the national predicted 

percent. The risk-adjustment model 

reduces the adjusted difference between 

HHAs that serve a disproportionate 

number of longer-stay patients and 

those that serve patients with more 

typical lengths of stay of one episode. 

Across all participating HHAs in the 

HHVBP Model, for HHAs that had less 

than 20 percent of episodes lasting more 

than 60 days, the average on the 

functional decline measure was 8.08 

percent. This increased to 11.08 percent 

for HHAs with 20 percent to 40 percent 

of episodes lasting more than 60 days, 

14.23 percent for HHAs with 40 percent 

to 60 percent of episodes lasting more 

than 60 days, and 20.59 percent for 

HHAs with more than 60 percent of 

episodes lasting more than 60 days. This 

finding suggests that, in addition to 

focusing on prevention of functional 

decline, we should also attempt to better 

predict a patient’s functional trajectory 

and potentially stratify the population 

to exclude those on a likely downward 

trajectory. However, in spite of this 

finding, the inclusion of a measure that 

rewards providers for avoiding 

functional decline has the advantage of 

diversifying the set of measures for the 

HHVBP model. We solicited public 


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comments on whether or not to include 

a composite functional decline measure 

in the set of applicable measures, the 

name of any such measure, the risk 

adjustment method, and whether we 

should conduct an analysis of the 

impact of removal/addition of OASIS– 

C2 items. 

3. Behavioral Health Measures 

Although we did not receive 

comments or suggestions through the 

rulemaking process for the HHVBP 

Model regarding behavioral or mental 

health measures, we noted in the CY 

2018 HH PPS proposed rule that we 

recognize that the Model does not 

include such measures. The OASIS–C2 

collects several items related to 

behavioral and mental health (M1700 

Cognitive Functioning; M1710 

Confusion Frequency; M1720 Anxiety; 

M1730 Depression Screening; M1740 

Cognitive, Behavioral, and Psychiatric 

Symptoms; M1745 Frequency of 

Disruptive Behavior Symptoms; and 

M1750 Psychiatric Nursing Services). 

These items are used to compute both 

Improvement and Process measures as 

well as Potentially Avoidable Events. 

The inclusion of behavioral health 

measures is important for care 

transformation and improvement 

activities as many persons served by the 

Home Health program may have 

behavioral health needs. 

The TEP made several suggestions 

during the December 2016 conference 

call as to whether the focus of a 

behavioral or mental health measure 

could be identifying whether a patient 

needed mental or behavioral health 

assistance compared to the supervision 

of the patient or advocacy assistance. 

The TEP supported the supervision type 

measure due to its opportunity for 

potential improvement. In further 

analyses, we identified two underlying 

components to outcomes for providing 

assistance. We developed a method, 

described in the following section, to 

identify patients who have or do not 

have needs for mental or behavioral 

health supervision. We noted that we 

are considering further refining this 

method by identifying the involvement 

of the caregiver in addressing the 

patient’s mental or behavioral health 

supervision needs as an important 

outcome measure, and we solicited 

comment on whether this is an 

appropriate factor or feature that we 

should consider in developing such a 

measure in future rulemaking. 

a. HHA Correctly Identifies Patient’s 

Need for Mental or Behavioral Health 

Supervision 

We stated in the CY 2018 HH PPS 

proposed rule that we are considering 

adding a HHA Correctly Identifies 

Patient’s Need for Mental or Behavioral 

Health Supervision measure to the 

HHVBP Model in the future to capture 

a patient’s need for mental or behavioral 

health supervision based on an 

identifier. This identifier is based on 

information from existing Neuro/

Emotional/Behavioral Status OASIS 

items, along with other indicators of 

mental/behavioral health problems to 

identify a patient in need of supervisory 

assistance. The outcome measure 

assesses whether the HHA correctly 

identifies whether or not the patient 

needs mental or behavioral health 

supervision based on the OASIS SOC/

ROC assessment item M2102f, Types 

and Sources of Assistance: Supervision 

and Safety. 

A composite Mental/Behavioral 

Health measure could be a dichotomous 

measure that reports the percentage of 

episodes of care where the HHA 

correctly identifies: (a) Patients who 

need mental or behavioral health 

supervision; and (b) patients who do not 

need mental or behavioral health 

supervision. The numerator could be a 

combination of two values: (1) The 

number of episodes of care where the 

HHA correctly identifies patients who 

need mental or behavioral health 

supervision; plus (2) the number of 

episodes of care where the HHA 

correctly identifies patients who do not 

need mental or behavioral health 

supervision. The denominator is all 

episodes of care. 

The composite measure requires that 

a patient’s need for mental or behavioral 

health supervision be identified. The 

following algorithm was designed to 

identify if a patient was in need of 

mental or behavioral health supervision. 

If the patient met any of the following 

conditions, the patient was identified by 

the algorithm as in need of mental or 

behavioral health supervision: 

• Was discharged from a psychiatric 

hospital prior to entering home health 

care (M1000 = 6). 

• Is diagnosed as having chronic 

mental behavioral problems (M1021 and 

M1023). 

• Is diagnosed with a mental illness 

(M1021 and M1023). 

• Is cognitively impaired (M1700 ≥ 2). 

• Is confused (M1710 ≥ 2). 

• Is identified as having a memory 

deficit (M1740 = 1). 

• Is identified as having impaired 

decision-making (M1740 = 2). 

• Is identified as being verbally 

disruptive (M1740 = 3). 

• Is identified as being physically 

aggressive (M1740 = 4). 

• Is identified as exhibiting 

disruptive, infantile, or inappropriate 

behaviors (M1740 = 5). 

• Is identified as being delusional 

(M1740 = 6). 

• Has a frequency of disruptive 

symptoms (M1745 ≥ 2). 

The measure also requires that the 

HHA identify if the patient is in need of 

mental or behavioral health supervision. 

This requirement is based on the SOC/ 

ROC code for M2102f, Types and 

Sources of Assistance: Supervision and 

Safety. If the HHA codes a value of zero, 

then the HHA has identified this patient 

as not needing mental or behavioral 

health supervision. If the HHA codes 

another value for M2102f, Types and 

Sources of Assistance: Supervision and 

Safety, then the HHA has identified this 

patient as needing mental or behavioral 

health supervision. The outcome 

measure is defined as the agreement 

between the algorithm’s identification of 

a patient’s need for mental or behavioral 

health supervision and the HHA’s 

coding of this need. That is, if— 

• The algorithm identifies the patient 

as not in need of mental or behavioral 

health supervision and the HHA 

identifies the patient as not in need of 

mental or behavioral health supervision; 

or 

• The algorithm identifies the patient 

as in need of mental or behavioral 

health supervision and the HHA 

identifies the patient as in need of 

mental or behavioral health supervision; 

then 

• The outcome is coded as 1, 

successful. 

As with other OASIS-based measures, 

a performance score for the measure 

would only be calculated for HHAs that 

have 20 or more episodes of care during 

a performance year. 

The measure is risk-adjusted using 

OASIS–C2 items to account for case-mix 

variation and other factors that affect 

functional decline but are outside the 

influence of the HHA. The riskadjustment model uses a logistic 

regression framework. The model 

includes a large number of patient 

clinical conditions and other 

characteristics measured at the start of 

care. To calculate case-mix adjusted 

values, the observed value of the 

measure is adjusted by the difference 

between the HHA predicted percent and 

the national predicted percent. 


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51710 Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 

20 ‘‘Home Health Quality Initiative: Quality 

Measures’’ https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/

HomeHealthQualityInits/

HHQIQualityMeasures.html 

21Somers’ D is a statistic that is based on the 

concept of concordant vs. discordant pairs for two 

related values. In this case, if both the observed and 

predicted values are higher than the average or if 

both values are less than the average, then the pair 

of numbers is considered concordant. However, if 

one value is higher than average and the other is 

lower than average—or vice versa, then the pair of 

values is considered discordant. The Somer’s D is 

(# of concordant pairs—# of discordant pairs)/total 

# of pairs. The higher the ratio, the stronger the 

concordance between the two set of values. 

22The Kendall Tau-a assumes that if there is a 

correlation between two variables, then sorting the 

variables based on one of the values will result in 

ordering the second variable. It uses the same 

concept of concordant pairs in Somers’ D but a 

different formula: t = [(4P)/[(n) (n–1)]—1 where 

p = # of concordant pairs and n = # of pairs. This 

correlation method reduces the effect of outlier 

values as the values are essentially ranked. 

23The C-statistic (sometimes called the 

‘‘concordance’’ statistic or C-index) is a measure of 

goodness of fit for binary outcomes in a logistic 

regression model. In clinical studies, the C-statistic 

gives the probability a randomly selected patient 

who experienced an event (for example, a disease 

or condition) had a higher risk score than a patient 

who had not experienced the event. It is equal to 

the area under the Receiver Operating Characteristic 

(ROC) curve and ranges from 0.5 to 1. 

• A value below 0.5 indicates a very poor model. 

• A value of 0.5 means that the model is no better 

than predicting an outcome than random chance. 

• Values over 0.7 indicate a good model. 

• Values over 0.8 indicate a strong model. 

The prediction model for this 

outcome measure uses 39 risk factors 20

with each risk factor statistically 

significant at p<0.0001. The correlation 

for the model between observed and 

predicted values as estimated by 

Somers’ D 21 is 0.427, that yields an 

estimated coefficient of determination 

(r2) value based on the Tau-a 22 of 0.201. 

This suggests that the variability in the 

model accounts for (predicts) 

approximately 20 percent of the 

variability in the outcome measure. The 

best statistic for evaluating the power of 

a prediction model that is derived using 

logistic regression is the c-statistic.23

This statistic identifies the overall 

accuracy of prediction by comparing 

observed and predicted value pairs to 

the proportion of the time that both 

predict the outcome in the same 

direction with 0.500 being a coin-flip. 

The discussed prediction model has a cstatistic equal to 0.713, which is 

considered to be good. Using data from 

CY 2015, the episode-level mean for the 

HHA Correctly Identifies Patient’s Need 

for Mental or Behavioral Health 

Supervision measure is 61.98 percent, 

nationally, and 62.98 percent for the 

HHVBP states. 

b. Caregiver Can/Does Provide for 

Patient’s Mental or Behavioral Health 

Supervision Need 

We stated in the CY 2018 HH PPS 

proposed rule that we are considering 

including under the Model in future 

rulemaking a Caregiver Can/Does 

Provide for Patient’s Mental or 

Behavioral Health Supervision Need 

measure that would encourage HHAs to 

ensure that patients who need mental or 

behavioral health supervision are 

receiving such care from the patient’s 

caregivers, and would be a realistic care 

goal. 

When considering how to develop a 

measure to determine whether or not 

the caregiver can/does provide the 

patient’s mental or behavioral health 

supervision, we would create an 

identifier of a patient’s need for mental 

or behavioral health supervision. This 

identifier is based on the same 

algorithm described in the previous 

section from existing Neuro/Emotional/ 

Behavioral Status OASIS items along 

with other indicators of mental/

behavioral health problems to identify a 

patient in need of supervisory 

assistance. The outcome measure is 

whether the HHA correctly identifies 

this patient as having the need for 

mental or behavioral health supervision 

based on the OASIS SOC/ROC 

assessment item M2102f, Types and 

Sources of Assistance: Supervision and 

Safety. 

The measure could be a dichotomous 

measure that reports the percentage of 

episodes where patients with identified 

mental or behavioral health supervision 

needs have their needs met or could 

have their needs met by the patient’s 

caregiver with additional training (if 

needed) and support by the HHA. The 

numerator is the intersection of the 

number of episodes of care where: (1) 

The patient needs mental or behavioral 

health supervision; and (2) these 

patients have their needs met or could 

have their needs met by the patient’s 

caregiver with additional training (if 

needed) and support by the HHA. By 

intersection, we mean that, for the 

numerator to equal one, a patient has to 

need mental or behavioral health 

supervision and has to have these needs 

met by his or her caregiver, or could 

have their needs met by the caregiver 

with additional training and/or support 

by the HHA. The denominator is all 

episodes of care. The algorithm 

discussed previously for HHA Correctly 

Identifies Patient’s Need for Mental or 

Behavioral Health Supervision could 

also be used to first identify if a patient 

was in need of mental or behavioral 

health supervision. 

To identify whether caregivers are 

able to provide supervisory care or, with 

training, could be able to provide 

supervisory care for these patients, we 

could use the SOC/ROC code for 

M2102f, Types and Sources of 

Assistance: Supervision and Safety. If 

the HHA codes a value of 1 (Non-agency 

caregiver(s) currently provide 

assistance) or 2 (Non-agency caregiver(s) 

need training/supportive services to 

provide assistance), then the measure 

identifies that a caregiver does or could 

provide supervision to a patient who 

has been identified as needing mental or 

behavioral health supervision. 

The outcome measure is defined as 

the agreement between the algorithm’s 

identification of a patient’s need for 

mental or behavioral health supervision 

and the availability of supervision from 

the patient’s caregiver(s). That is, if— 

• The algorithm identifies the patient 

as in need of mental or behavioral 

health supervision and there is 

documentation that the patient’s 

caregiver(s) do or could provide this 

supervision; then 

• The outcome is coded as 1, 

successful. 

As with other OASIS-based measures, 

a performance score for the measure 

would only be calculated for HHAs that 

have 20 or more episodes during a 

performance year. We would use the 

same methodology to risk-adjust by 

using OASIS–C2 items and the 

prediction model described previously. 

The prediction model for this outcome 

measure uses 55 risk factors with each 

risk factor significant at p <0.0001. The 

correlation for the model between 

observed and predicted values as 

estimated by Somers’ D is 0.672, that 

yields an estimated coefficient of 

determination (r2) value based on the 

Tau-a of 0.205. This suggests that the 

variability in the model accounts for 

(predicts) approximately 20 percent of 

the variability in the outcome measure. 

The best statistic for evaluating the 

power of a prediction model that is 

derived using logistic regression is the 

c-statistic. This statistic identifies the 

overall accuracy of prediction by 

comparing observed and predicted 

value pairs to the proportion of the time 

that both predict the outcome in the 

same direction with 0.500 being a coinflip. The prediction model has a cstatistic equal to 0.836, which is 

considered to be extremely strong. 

We noted in the CY 2018 HH PPS 

proposed rule that we are considering 

whether the HHA Correctly Identifies 

Patient’s Need for Mental or Behavioral 

Health Supervision measure or the 

Caregiver Can/Does Provide for Patient’s 

Mental or Behavioral Health 


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Supervision Need measure would be 

most meaningful to include in the 

Model. We also noted that we were 

considering the interactions between the 

Home Health Grouping Model (HHGM) 

proposal on quality measures discussed 

in section III. of the proposed rule and 

the HHVBP Model for the quality 

measures discussed in section IV.B of 

the proposed rule. We solicited public 

comments on the methodologies, 

analyses used to test the quality 

measure, and issues described in this 

section for future measure 

considerations. We noted that we will 

continue to share analyses as they 

become available with participating 

HHAs during future webinars. 

The following is a summary of the 

public comments received on the 

‘‘Quality Measures for Future 

Consideration’’ and our responses: 

Comment: We received several 

comments from stakeholders offering 

their input on the quality measures 

discussed. Many were receptive to the 

development of new measures. Some 

commenters supported the development 

of composite measures, but believed 

improvement should not be the sole 

focus of any measure as they indicated 

that many patients benefit greatly from 

skilled home health services but are not 

likely to improve on these measures. 

While many commenters were in 

support of the inclusion of measures 

that capture an agency’s ability to 

identify mental or behavioral health 

needs and identify whether a caregiver 

is available to provide behavioral 

supervision, they cautioned CMS that 

home health providers should not be 

made responsible for determining 

behavioral health diagnoses outside of a 

simple recognition of need. MedPAC 

was one of a few commenters that did 

not support developing new process 

measures, such as the described 

measure concepts of correctly 

identifying the patient’s need for mental 

and behavioral health supervision, and 

identifying if a caregiver is able to 

provide the patient’s mental or 

behavioral health supervision. MedPAC 

indicated that while it believes that 

improving a patient’s functional ability 

is a goal of home health care, it has 

some degree of concern that the 

‘composite total change in ADL/IADL 

measure’ and the ‘composite functional 

decline measure’ represent reporting 

elements completely within the control 

of the home health agency. MedPAC 

recommended that if CMS includes 

these measures, it may also want to 

consider and propose ways that such 

data could be independently audited or 

otherwise verified. Another commenter 

opposed the addition of a composite 

functional decline measure as they 

believe it rewards agencies that have 

selective admission practices of refusing 

patients that are likely to decline toward 

end of life, and also opposed the 

inclusion of behavioral health measures 

as they believe that they may discourage 

agencies from accepting patients when 

there are behavioral health issues or few 

local resources. 

Response: We appreciate the 

comments on the discussion of the 

measures that we are considering for 

possible inclusion in the Model and will 

take the recommendations into 

consideration as we determine whether 

or not to include new measures in 

future rulemaking. 

Comment: In response to our 

solicitation of public comment, we also 

received a few comments that were 

outside the scope of discussion of the 

specific future quality measures that we 

are considering, as discussed in the 

proposed rule. A commenter 

recommended that CMS develop and 

implement HHVBP policies in 

alignment with Congressional activity 

supporting one national approach to 

VBP for home care services. Another 

commenter recommended that CMS 

factor quality metrics into HHVBP that 

not only relate to health outcomes, but 

also that are within the control of the 

home health care provider, adequately 

measuring the quality of care provided. 

Another commenter recommended that 

CMS ensure that value-based home 

health purchasing models incorporate a 

shared definition of value that 

incorporates the patient and caregiver 

voice. A few commenters questioned the 

level of payment at risk under the 

Model, and believed that placing up to 

eight percent of HHA payment at risk 

for performance is too much. A few 

commenters questioned the geographic 

participation criteria for the Model and 

recommended including voluntary 

participation by interested HHAs in 

non-participating states. 

Response: We appreciate the 

comment to align home health VBP 

policies with Congressional activity 

supporting a national approach to VBP 

home care services. We also appreciate 

the comments that recommend 

adequately measuring the quality of care 

provided and for CMS to ensure that 

value-based home health purchasing 

models incorporate a shared definition 

of value that incorporates the patient 

and caregiver voice. As an Innovation 

Center model, we are closely monitoring 

the quality measures and will address 

any needed adjustments through future 

rulemaking. With respect to the 

comments regarding the level of 

payment at risk under the Model, as 

discussed in the CY 2016 HH PPS final 

rule (80 FR 68687), competing HHAs 

that provide the highest quality of care 

and that receive the maximum upward 

adjustment will improve their financial 

viability that could ensure that the 

vulnerable population that they serve 

has access to high quality care. Only 

HHAs that provide very poor quality of 

care, relative to the cohort they compete 

within, would be subject to the highest 

downward payment adjustments. We 

appreciate the desire for interested 

HHAs in non-participating states to 

participate in the Model, but do not 

plan to re-open the Model to additional 

participants at this time. 

We appreciate the comments on 

potential new quality measures and 

intend to continue to provide 

opportunities for stakeholder input as 

we consider additional measures for 

possible inclusion in the HHVBP 

Model’s applicable measure set. We will 

continue to collect and analyze data as 

we consider whether to propose any 

additional measures in future 

rulemaking. 

V. Updates to the Home Health Care 

Quality Reporting Program (HH QRP) 

A. Background and Statutory Authority 

Section 1895(b)(3)(B)(v)(II) of the Act 

requires that for 2007 and subsequent 

years, each HHA submit to the Secretary 

in a form and manner, and at a time, 

specified by the Secretary, such data 

that the Secretary determines are 

appropriate for the measurement of 

health care quality. To the extent that an 

HHA does not submit data in 

accordance with this clause, the 

Secretary is directed to reduce the home 

health market basket percentage 

increase applicable to the HHA for such 

year by 2 percentage points. As 

provided at section 1895(b)(3)(B)(vi) of 

the Act, depending on the market basket 

percentage increase applicable for a 

particular year, the reduction of that 

increase by 2 percentage points for 

failure to comply with the requirements 

of the HH QRP and (except in 2018) 

further reduction of the increase by the 

productivity adjustment described in 

section 1886(b)(3)(B)(xi)(II) of the Act 

may result in the home health market 

basket percentage increase being less 

than 0.0 percent for a year, and may 

result in payment rates under the Home 

Health PPS for a year being less than 

payment rates for the preceding year. 

We use the terminology ‘‘CY [year] 

HH QRP’’ to refer to the calendar year 

for which the HH QRP requirements 

applicable to that calendar year must be 

met in order for an HHA to avoid a 2 

percentage point reduction to its market 


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24http://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/ 

QualityInitiativesGenInfo/CMS-QualityStrategy.html. 

25http://www.ahrq.gov/workingforquality/nqs/ 

nqs2011annlrpt.htm. 

basket percentage increase under 

section 1895(b)(3)(B)(v)(I) of the Act 

when calculating the payment rates 

applicable to it for that calendar year. 

The Improving Medicare Post-Acute 

Care Transformation Act of 2014 (Pub. 

L. 113–185, enacted on October 6, 2014) 

(IMPACT Act) amended Title XVIII of 

the Act, in part, by adding new section 

1899B of the Act, entitled 

‘‘Standardized Post-Acute Care 

Assessment Data for Quality, Payment, 

and Discharge Planning,’’ and by 

enacting new data reporting 

requirements for certain post-acute care 

(PAC) providers, including Home 

Health Agencies (HHAs). Specifically, 

new sections 1899B(a)(1)(A)(ii) and (iii) 

of the Act require HHAs, Inpatient 

Rehabilitation Facilities (IRFs), Long 

Term Care Hospitals (LTCHs) and 

Skilled Nursing Facilities (SNFs), under 

each of their respective quality reporting 

program (which, for HHAs, is found at 

section 1895(b)(3)(B)(v) of the Act), to 

report data on quality measures 

specified under section 1899B(c)(1) of 

the Act for at least five domains, and 

data on resource use and other measures 

specified under section 1899B(d)(1) of 

the Act for at least three domains. 

Section 1899B(a)(1)(A)(i) of the Act 

further requires each of these PAC 

providers to report under its respective 

quality reporting program standardized 

patient assessment data in accordance 

with subsection (b) for at least the 

quality measures specified under 

subsection (c)(1) and that is with respect 

to five specific categories: Functional 

status; cognitive function and mental 

status; special services, treatments, and 

interventions; medical conditions and 

co-morbidities; and impairments. All of 

the data that must be reported in 

accordance with section 1899B(a)(1)(A) 

of the Act must be standardized and 

interoperable, so as to allow for the 

exchange of the information among PAC 

providers and other providers, as well 

as for the use of such data to enable 

access to longitudinal information and 

to facilitate coordinated care. We refer 

readers to the CY 2016 HH PPS final 

rule (80 FR 68690 through 68692) for 

additional information on the IMPACT 

Act and its applicability to HHAs. 

B. General Considerations Used for the 

Selection of Quality Measures for the 

HH QRP 

We refer readers to the CY 2016 HH 

PPS final rule (80 FR 68695 through 

68698) for a detailed discussion of the 

considerations we apply in measure 

selection for the HH QRP, such as 

alignment with the CMS Quality 

Strategy,24 which incorporates the three 

broad aims of the National Quality 

Strategy.25 As part of our consideration 

for measures for use in the HH QRP, we 

review and evaluate measures that have 

been implemented in other programs 

and take into account measures that 

have been endorsed by NQF for 

provider settings other than the home 

health setting. We have previously 

adopted measures with the term 

‘‘Application of’’ in the names of those 

measures. We have received questions 

pertaining to the term ‘‘application’’ and 

clarified in the proposed rule that when 

we refer to a measure as an 

‘‘Application of’’ the measure, we mean 

that the measure would be used in a 

setting other than the setting for which 

it was endorsed by the NQF. For 

example, in the FY 2016 SNF PPS Rule 

(80 FR 46440 through 46444) we 

adopted An Application of the Measure 

Percent of Residents with Experiencing 

Falls with Major Injury (Long Stay) 

(NQF #0674), which is endorsed for the 

Nursing Home setting but not the SNF 

setting. For such measures, we stated 

that we intend to seek NQF 

endorsement for the home health 

setting, and if the NQF endorses one or 

more of them, we would update the title 

of the measure to remove the reference 

to ‘‘Application of.’’ 

We received comments on the 

considerations we apply in our measure 

selection and on other topics related to 

measures used in the HH QRP. 

Comment: Some commenters 

supported the standardization of 

measures and data across HHAs, LTCHs, 

IRFs, and SNFs so that CMS can make 

comparisons between them, but 

cautioned that such standardization 

could compromise the validity of the 

data. These commenters stated that the 

home is different than institutional 

settings because the patient has a greater 

role in determining how, when, and if 

certain interventions are provided, and 

that individual skill, cognitive and 

functional ability, and financial 

resources affect the ability of home 

health patients to safely manage their 

health care needs, interventions, and 

medication regimens. Other commenters 

expressed concerns about the reliability 

and validity of cross-setting measures 

due to the unique characteristics of the 

home health setting and emphasized 

caution in interpreting measure rates. 

Response: We appreciate the support 

for standardization to enable 

comparisons across post-acute care 

providers. We also recognize the 

uniqueness of the home setting, 

including patients’ capacity to directly 

and independently manage their 

environment and health care needs, 

such as medications and treatments. 

However, we disagree that patients are 

limited in their freedom to help set their 

goals and preferences when receiving 

care services within LTCHs, IRFs or 

SNFs. In our measure development and 

alignment work, we continuously assess 

and account for the unique 

characteristics of home health patients 

including the use of risk-adjustment 

models that account for differences in 

cognitive and functional ability. 

Further, we are mindful that regardless 

of where services are rendered, risk 

adjustment is generally applied to 

characteristics of the individual rather 

than the provider setting. 

All of the measures we proposed to 

adopt for the HH QRP were tested for 

reliability and/or validity, and we 

believe that the results of that testing 

support our conclusion that the 

measures are sufficiently reliable and 

valid to warrant their adoption in the 

HH QRP. The results of our reliability 

and validity testing for these measures 

may be found in the Measure 

Specifications for Measures Proposed in 

CY 2018 HH QRP Final Rule, posted on 

the CMS HH QRP Web page at https:// 

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

HHQIQualityMeasures.html. We will 

continue to test, monitor and validate 

these measures as part of measure 

maintenance. 

Comment: One commenter suggested 

that the claims-based measures be 

weighted more than OASIS measures in 

order to control for inflated outcomes. 

Another commenter was concerned that 

OASIS measure data can be 

manipulated and suggested the HH QRP 

should only use claims-based measures 

because they are more objective. 

Response: We wish to clarify that we 

do not weight home health measures in 

the home health quality reporting 

program. However, we believe that the 

commenter is concerned about the 

gaming on behalf of home health 

agencies. We believe that the collection 

of both claims-based and OASIS based 

measures is appropriate for the program. 

Claims-based data can be limited 

because they are associated with billing 

and do not always provide a complete 

picture of the patient’s health 

assessment status. OASIS fills in those 

gaps by giving us additional information 

about care processes and outcomes that 

are furnished to HHA patients. 


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26https://aspe.hhs.gov/pdf-report/reportcongress-social-risk-factors-and-performanceunder-medicares-value-based-purchasingprograms. 

27https://aspe.hhs.gov/pdf-report/reportcongress-social-risk-factors-and-performanceunder-medicares-value-based-purchasingprograms. 28National Academies of Sciences, Engineering, 

and Medicine. 2017. Accounting for social risk 

factors in Medicare payment. Washington, DC: The 

National Academies Press. 

Although we recognize that OASIS 

assessments are, by their nature, more 

subjective than claims, we require 

HHAs to attest to the accuracy of the 

data submitted on each OASIS 

assessment. 

C. Accounting for Social Risk Factors in 

the HH QRP 

In the CY 2018 HH PPS proposed rule 

(82 FR 35341 through 35342), we 

discussed accounting for social risk 

factors in the HH QRP. We understand 

that social risk factors such as income, 

education, race and ethnicity, 

employment, disability, community 

resources, and social support (certain 

factors of which are also sometimes 

referred to as socioeconomic status 

(SES) factors or socio-demographic 

status (SDS) factors) play a major role in 

health. One of our core objectives is to 

improve beneficiary outcomes including 

reducing health disparities, and we 

want to ensure that all beneficiaries, 

including those with social risk factors, 

receive high quality care. In addition, 

we seek to ensure that the quality of 

care furnished by providers and 

suppliers is assessed as fairly as 

possible under our programs while 

ensuring that beneficiaries have 

adequate access to excellent care. 

We have been reviewing reports 

prepared by the Office of the Assistant 

Secretary for Planning and Evaluation 

(ASPE 26) and the National Academies 

of Sciences, Engineering, and Medicine 

on the issue of measuring and 

accounting for social risk factors in 

CMS’ quality measurement and 

payment programs, and considering 

options on how to address the issue in 

these programs. On December 21, 2016, 

ASPE submitted a Report to Congress on 

a study it was required to conduct under 

section 2(d) of the Improving Medicare 

Post-Acute Care Transformation 

(IMPACT) Act of 2014. The study 

analyzed the effects of certain social risk 

factors of Medicare beneficiaries on 

quality measures and measures of 

resource use used in one or more of nine 

Medicare value-based purchasing 

programs.27 The report also included 

considerations for strategies to account 

for social risk factors in these programs. 

In a January 10, 2017 report released by 

The National Academies of Sciences, 

Engineering, and Medicine, that body 

provided various potential methods for 

measuring and accounting for social risk 

factors, including stratified public 

reporting.28

In addition, the NQF undertook a 2- 

year trial period in which new 

measures, measures undergoing 

maintenance review, and measures 

endorsed with the condition that they 

enter the trial period were assessed to 

determine whether risk adjustment for 

selected social risk factors was 

appropriate for these measures. 

Measures from the HH QRP, 

Rehospitalization During the First 30 

Days of Home Health (NQF# 2380), and 

Emergency Department Use without 

Hospital Readmission During the First 

30 Days of Home Health (NQF# 2505) 

were included in this trial. This trial 

entailed temporarily allowing inclusion 

of social risk factors in the riskadjustment approach for these 

measures. Since the publication of the 

CY 2018 HH PPS proposed rule, the 

National Quality Forum (NQF) has 

concluded their initial trial on risk 

adjustment for quality measures. Based 

on the findings from the initial trial, 

NQF will continue its work to evaluate 

the impact of social risk factor 

adjustment on intermediate outcome 

and outcome measures for an additional 

3 years. The extension of this work will 

allow NQF to determine further how to 

effectively account for social risk factors 

through risk adjustment and other 

strategies in quality measurement. 

As we continue to consider the 

analyses and recommendations from 

these reports, we are continuing to work 

with stakeholders in this process. As we 

have previously communicated, we are 

concerned about holding providers to 

different standards for the outcomes of 

their patients with social risk factors 

because we do not want to mask 

potential disparities or minimize 

incentives to improve the outcomes for 

disadvantaged populations. Keeping 

this concern in mind, while we sought 

input on this topic previously, we 

continue to seek public comment on 

whether we should account for social 

risk factors in measures in the HH QRP, 

and if so, what method or combination 

of methods would be most appropriate 

for accounting for social risk factors. 

Examples of methods include: 

confidential reporting to providers of 

measure rates stratified by social risk 

factors, public reporting of stratified 

measure rates, and potential risk 

adjustment of a particular measure as 

appropriate based on data and evidence. 

In addition, in the CY 2018 HH PPS 

proposed rule (82 FR 35341 through 

35342), we sought public comment on 

which social risk factors might be most 

appropriate for reporting stratified 

measure scores and potential risk 

adjustment of a particular measure. 

Examples of social risk factors include, 

but are not limited to, dual eligibility/ 

low-income subsidy, race and ethnicity, 

and geographic area of residence. We 

also sought comments on which of these 

factors, including current data sources 

where this information would be 

available, could be used alone or in 

combination, and whether other data 

should be collected to better capture the 

effects of social risk. We will take 

commenters’ input into consideration as 

we continue to assess the 

appropriateness and feasibility of 

accounting for social risk factors in the 

HH QRP. We note that to the extent we 

consider making any changes we would 

propose them through future notice and 

comment rulemaking. 

We look forward to working with 

stakeholders as we consider the issue of 

accounting for social risk factors and 

reducing health disparities in CMS 

programs. Of note, implementing any of 

the methods previously stated will be 

taken into consideration in the context 

of how this and other CMS programs 

operate (for example, data submission 

methods, availability of data, statistical 

considerations relating to reliability of 

data calculations, among others), so we 

also sought comment on operational 

considerations. We are committed to 

ensuring that beneficiaries have access 

to and receive excellent care, and that 

the quality of care furnished by 

providers and suppliers is assessed 

fairly in CMS programs. This section of 

this final rule includes a discussion of 

the comments we received on this topic, 

along with our responses. 

Comment: Commenters were 

generally supportive of accounting for 

social risk factors in the HH QRP quality 

measures. Many commenters stated that 

there was evidence demonstrating that 

these factors can have substantial 

influence on patient health outcomes. 

Some commenters who supported 

accounting for social risk factors noted 

that these factors are outside the control 

of the provider and were concerned that 

without risk adjustment, differences in 

quality scores may reflect differences in 

patient populations rather than 

differences in quality. 

A few other commenters, while 

acknowledging the influence of social 

risk factors on health outcomes, 

cautioned against adjusting for them in 

quality measurement due to the 

potential for unintended consequences. 


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These commenters expressed concern 

over the possibility that risk- adjusted 

measures may remove incentives for 

quality improvement among facilities 

that serve higher levels of underserved 

populations. 

Regarding risk adjustment 

methodology, some commenters made 

specific recommendations regarding the 

type of risk adjustment that must be 

used. Commenters stated that any risk 

stratification must be considered on a 

measure-by-measure basis, and that 

measures that are broadly within the 

control of the provider and reflective of 

direct care, such as pressure ulcers, 

must not be stratified. The commenters 

stated that social risk factor adjustment 

be used only on outcome measures, not 

process measures. One commenter 

alternately suggested using 

socioeconomic factors to stratify, rather 

than adjust, measure results. Multiple 

commenters recommended that we 

conduct further research and testing of 

risk-adjustment methods. A commenter 

suggested that CMS use Social Risk 

Factors, Social Determinants of Health 

or Distressed Communities Index scores 

within the HH QRP. Some commenters 

suggested the formation of a TEP to 

further refine the use of such data. 

In addition to supporting race and 

ethnicity, dual eligibility status, and 

geographical location, commenters 

suggested additional risk factors, 

including: Patient-level factors such as 

lack of personal resources, education 

level, and employment. Some 

commenters also suggested community 

resources and other factors such as 

access to adequate food, medications, 

living conditions (including living 

alone), and lack of an adequate support 

system or caregiver availability. Several 

encouraged the development of 

measures that reflect person-centered 

domains to improve the focus on 

outcomes for disadvantaged 

populations. 

A few commenters provided feedback 

on confidential and public reporting of 

data adjusted for social risk factors. A 

commenter suggested that CMS start 

with confidential reporting and, once 

there has been opportunity for HHAs to 

review and understand their results, 

CMS could transition to public 

reporting. 

Response: We thank commenters for 

their suggestions. As we have 

previously stated, we are concerned 

about holding providers to different 

standards for the outcomes of their 

patients with social risk factors because 

we do not want to mask potential 

disparities. We believe that the path 

forward must incentivize improvements 

in health outcomes for disadvantaged 

populations while ensuring that 

beneficiaries have adequate access to 

excellent care. Also, based on the 

findings from the initial trial, NQF will 

continue its work to evaluate the impact 

of social risk factor adjustment on 

intermediate outcome and outcome 

measures for an additional three years. 

The extension of this work will allow 

NQF to determine further how to 

effectively account for social risk factors 

through risk adjustment and other 

strategies in quality measurement. We 

await recommendations of the NQF trial 

to further inform our efforts. 

We will consider all suggestions as we 

continue to assess each measure and the 

overall HH QRP. We intend to explore 

options including but not limited to 

measure stratification by social risk 

factors in a consistent manner across 

several quality reporting programs, 

informed by considerations of 

stratification methods described in 

IX.A.13 of the preamble of the FY 2018 

IPPS/LTCH PPS final rule. We thank 

commenters for this important feedback 

and will continue to consider options to 

account for social risk factors that will 

allow us to address disparities and 

potentially incentivize improvement in 

care for patients and beneficiaries. We 

will also consider providing feedback to 

providers on outcomes for individuals 

with social risk factors in confidential 

reports. 

D. Removal of OASIS Items 

In the CY 2018 HH PPS proposed rule 

(82 FR 35342) we proposed to remove 

247 data elements from 35 OASIS items 

collected at specific time points during 

a home health episode. These data 

elements are not used in the calculation 

of quality measures already adopted in 

the HH QRP, nor are they being used for 

previously established purposes 

unrelated to the HH QRP, including 

payment, survey, the HH VBP Model or 

care planning. We included list of the 

35 OASIS items we proposed to remove, 

in part or in their entirety, in Table 45 

of the proposed rule (82 FR 35342 and 

35343) and also made them available at 

https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

OASIS-Data-Sets.html. Subsequent to 

issuing the proposed rule, we 

discovered that we had inadvertently 

included three OASIS items in Table 45 

that are used either for payment or for 

the HH QRP. Those items are M1200 

Vision (used for payment), M2030 

Management of Injectable Medications 

(used for payment), and M1730 

Depression Screening (used in the HH 

QRP). Accordingly, we will not be 

removing these items from the OASIS. 

Comment: Many commenters 

supported our proposal to remove items 

from OASIS. Most of these commenters 

agreed that items not used for the 

purposes of determining patient 

outcomes or the quality of care should 

be removed. 

Response: We appreciate the support 

for our proposal to remove items from 

OASIS. 

Comment: One commenter noted that 

OASIS Item M2250 (Plan of Care 

Synopsis) is proposed for removal and 

questioned whether OASIS Item M2401 

(Intervention Synopsis) will continue to 

be collected. 

Response: We proposed to remove 

OASIS Item M2250 because it is not 

used for the HH QRP or for any other 

purpose. OASIS Item M2401 is used in 

the calculation of the quality measure 

Diabetic Foot Care and Patient 

Education Implemented (NQF #0519), 

which we adopted in the CY 2010 HH 

PPS final rule (74 FR 58096), and will 

therefore continue to be collected at the 

time point of Transfer to an Inpatient 

Facility and Discharge from Agency. 

Comment: One commenter questioned 

if there is another OASIS version that 

will be implemented so that a 

beneficiary’s Medicare Beneficiary 

Identifier (MBI) can be provided in the 

OASIS. 

Response: Effective January 1, 2018 

the OASIS–C2 will be able to 

accommodate the MBI which is an 

alternative Medicare Beneficiary 

Identifier that we are adopting to 

replace the Social Security number 

(SSN)-based Health Insurance Claim 

Number (HICN) in an effort to prevent 

identity theft in the Medicare 

population. Instructions for reporting 

OASIS Item M0063 (Medicare 

Beneficiary Number) can be found in 

the OASIS–C2 Guidance Manual: 

Effective January 1, 2018 at https:// 

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/ 

Downloads/OASIS-C2-GuidanceManual-Effective_1_1_18.pdf. 

Comment: A few commenters raised 

concerns about the overall burden 

associated with CMS’ proposals, noting 

that if all proposed new assessment 

items are finalized, the new assessment 

items could be more burdensome to 

collect than the one being removed. 

Response: We appreciate the 

comments and as more fully discussed 

in section V.H. of this final rule, we 

have decided not to finalize the 

standardized patient assessment data 

elements proposed for three of the five 

categories under § 1899B(b)(1)(B) of the 

Act: Cognitive Function and Mental 


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Status; Special Services, Treatments, 

and Interventions; and Impairments. 

Final Decision: After consideration of 

the comments received, we are 

finalizing the removal of 235 data 

elements from 33 OASIS items collected 

at specific time points during a home 

health episode, effective with all HHA 

assessments on or after January 1, 2019. 

As previously explained, we will 

continue to collect OASIS items M1200, 

M2030 and M1730. Table 17 lists the 

OASIS items and data elements to be 

removed and they can also be found at 

https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

OASIS-Data-Sets.html. 

TABLE 17—ITEMS TO BE REMOVED FROM OASIS EFFECTIVE JANUARY 1, 2019 

OASIS item 

Specific time point 

Start of care Resumption of 

care Follow-up 

Transfer to 

an inpatient 

facility 

Death at 

home 

Discharge 

from agency 

M0903 ...................................................... ........................ ........................ ........................ 1 1 1 

M1011 ...................................................... 6 6 6 ........................ ........................ ........................

M1017 ...................................................... 6 6 ........................ ........................ ........................ ........................

M1018 ...................................................... 6 6 ........................ ........................ ........................ ........................

M1025 ...................................................... 12 12 12 ........................ ........................ ........................

M1034 ...................................................... 1 1 ........................ ........................ ........................ ........................

M1036 ...................................................... 4 4 ........................ ........................ ........................ ........................

M1210 ...................................................... 1 1 ........................ ........................ ........................ ........................

M1220 ...................................................... 1 1 ........................ ........................ ........................ ........................

M1230 ...................................................... 1 1 ........................ ........................ ........................ 1 

M1240 ...................................................... 1 1 ........................ ........................ ........................ ........................

M1300 ...................................................... 1 1 ........................ ........................ ........................ ........................

M1302 ...................................................... 1 1 ........................ ........................ ........................ ........................

M1320 ...................................................... 1 1 ........................ ........................ ........................ 1 

M1322 ...................................................... ........................ ........................ ........................ ........................ ........................ 1 

M1332 ...................................................... ........................ ........................ ........................ ........................ ........................ 1 

M1350 ...................................................... 1 1 ........................ ........................ ........................ ........................

M1410 ...................................................... 3 3 ........................ ........................ ........................ ........................

M1501 ...................................................... ........................ ........................ ........................ 1 ........................ 1 

M1511 ...................................................... ........................ ........................ ........................ 5 ........................ 5 

M1610 ...................................................... ........................ ........................ ........................ ........................ ........................ 1 

M1615 ...................................................... 1 1 ........................ ........................ ........................ 1 

M1750 ...................................................... 1 1 ........................ ........................ ........................ ........................

M1880 ...................................................... 1 1 ........................ ........................ ........................ 1 

M1890 ...................................................... 1 1 ........................ ........................ ........................ 1 

M1900 ...................................................... 4 4 ........................ ........................ ........................ ........................

M2030 ...................................................... ........................ ........................ ........................ ........................ ........................ 1 

M2040 ...................................................... 2 2 ........................ ........................ ........................ ........................

M2102 * .................................................... 6 6 ........................ ........................ ........................ ** 3 

M2110 ...................................................... 1 1 ........................ ........................ ........................ ........................

M2250 ...................................................... 7 7 ........................ ........................ ........................ ........................

M2310 ...................................................... ........................ ........................ ........................ *** 15 ........................ *** 15 

M2430 ...................................................... ........................ ........................ ........................ 20 ........................ ........................

Total .................................................. 70 70 18 42 1 34 

* M2102 row f to remain collected at Start of Care, Resumption of Care and Discharge from Agency as part of the HH VBP program. 

** M2102 rows a, c, d to remain collected at Discharge from Agency for survey purposes. 

*** M2310 responses 1, 10, OTH, UK to remain collected at Transfer to an Inpatient Facility and Discharge from Agency for survey purposes. 

E. Collection of Standardized Patient 

Assessment Data Under the HH QRP 

1. Definition of Standardized Patient 

Assessment Data 

Section 1895(b)(3)(B)(v)(IV)(bb) of the 

Act requires that beginning with the CY 

2019 HH QRP, HHAs report 

standardized patient assessment data 

required under section 1899B(b)(1) of 

the Act. For purposes of meeting this 

requirement, section 

1895(b)(3)(B)(v)(IV)(cc) of the Act 

requires that a HHA submit the 

standardized patient assessment data 

required under section 1899B(b)(1) of 

the Act in the form and manner, and at 

the time, as specified by the Secretary. 

Section 1899B(b)(1)(B) of the Act 

describes standardized patient 

assessment data as data required for at 

least the quality measures described in 

sections 1899B(c)(1) of the Act and that 

is with respect to the following 

categories: 

• Functional status, such as mobility 

and self-care at admission to a PAC 

provider and before discharge from a 

PAC provider. 

• Cognitive function, such as ability 

to express and understand ideas, and 

mental status, such as depression and 

dementia. 

• Special services, treatments and 

interventions such as the need for 

ventilator use, dialysis, chemotherapy, 

central line placement, and total 

parenteral nutrition. 

• Medical conditions and 

comorbidities such as diabetes, 

congestive heart failure and pressure 

ulcers. 

• Impairments, such as incontinence 

and an impaired ability to hear, see or 

swallow. 

• Other categories deemed necessary 

and appropriate by the Secretary. 

As required under section 

1899B(b)(1)(A) of the Act, the 

standardized patient assessment data 

must be reported at least for the 

beginning of the home health episode 

(for example, HH start of care/

resumption of care) and end of episode 


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(discharge), but the Secretary may 

require the data to be reported more 

frequently. 

In the CY 2018 HH PPS proposed rule 

(82 FR 35343), we proposed to define 

the standardized patient assessment 

data that HHAs must report under the 

HH QRP, as well as the requirements for 

the reporting of these data. The 

collection of standardized patient 

assessment data is critical to our efforts 

to drive improvement in healthcare 

quality across the four post-acute care 

(PAC) settings to which the IMPACT 

Act applies. We noted that we intend to 

use these data for a number of purposes, 

including facilitating their exchange and 

longitudinal use among healthcare 

providers to enable high quality care 

and outcomes through care 

coordination, as well as for quality 

measure calculation, and identifying 

comorbidities that might increase the 

medical complexity of a particular 

admission. 

HHAs are currently required to report 

patient assessment data through the 

Outcome and Assessment Information 

Set (OASIS) by responding to an 

identical set of assessment questions 

using an identical set of response 

options (we refer to a solitary question/ 

response option as a data element and 

we refer to a group of questions/

responses as data elements), both of 

which incorporate an identical set of 

definitions and standards. The primary 

purpose of the identical questions and 

response options is to ensure that we 

collect a set of standardized data 

elements across HHAs, which we can 

then use for a number of purposes, 

including HH payment and measure 

calculation for the HH QRP. 

LTCHs, IRFs, and SNFs are also 

required to report patient assessment 

data through their applicable PAC 

assessment instruments, and they do so 

by responding to identical assessment 

questions developed for their respective 

settings using an identical set of 

response options (which incorporate an 

identical set of definitions and 

standards). Like the OASIS, the 

questions and response options for each 

of these other PAC assessment 

instruments are standardized across the 

PAC provider type to which the PAC 

assessment instrument applies. 

However, the assessment questions and 

response options in the four PAC 

assessment instruments are not 

currently standardized with each other. 

As a result, questions and response 

options that appear on the OASIS 

cannot be readily compared with 

questions and response options that 

appear, for example, on the Inpatient 

Rehabilitation Facility-Patient 

Assessment Instrument (IRF–PAI), 

which is the PAC assessment 

instrument used by IRFs. This is true 

even when the questions and response 

options are similar. This lack of 

standardization across the four PAC 

provider types has limited our ability to 

compare one PAC provider type with 

another for purposes such as care 

coordination and quality improvement. 

To achieve a level of standardization 

across HHAs, LTCHs, IRFs, and SNFs 

that enables us to make comparisons 

between them, we proposed to define 

‘‘standardized patient assessment data’’ 

as patient or resident assessment 

questions and response options that are 

identical in all four PAC assessment 

instruments, and to which identical 

standards and definitions apply. 

We stated in the proposed rule that 

standardizing the questions and 

response options across the four PAC 

assessment instruments is an essential 

step in making that data interoperable, 

allowing it to be shared electronically, 

or otherwise, between PAC provider 

types. It will enable the data to be 

comparable for various purposes, 

including the development of crosssetting quality measures and to inform 

payment models that take into account 

patient characteristics rather than 

setting, as described in the IMPACT Act. 

We did not receive any specific 

comments on the proposed definition. 

Final Decision: We are finalizing as 

proposed our definition of standardized 

patient assessment data. 

2. General Considerations Used for the 

Selection of Standardized Patient 

Assessment Data 

As part of our effort to identify 

appropriate standardized patient 

assessment data for purposes of 

collecting under the HH QRP, we sought 

input from the general public, 

stakeholder community, and subject 

matter experts on items that would 

enable person-centered, high quality 

health care, as well as access to 

longitudinal information to facilitate 

coordinated care and improved 

beneficiary outcomes. 

To identify optimal data elements for 

standardization, our data element 

contractor organized teams of 

researchers for each category, with each 

team working with a group of advisors 

made up of clinicians and academic 

researchers with expertise in PAC. 

Information-gathering activities were 

used to identify data elements, as well 

as key themes related to the categories 

described in section 1899B(b)(1)(B) of 

the Act. In January and February 2016, 

our data element contractor also 

conducted provider focus groups for 

each of the four PAC provider types, 

and a focus group for consumers that 

included current or former PAC patients 

and residents, caregivers, ombudsmen, 

and patient advocacy group 

representatives. The Development and 

Maintenance of Post-Acute Care CrossSetting Standardized Patient 

Assessment Data Focus Group Summary 

Report is available at https://

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/

IMPACT-Act-Downloads-andVideos.html. 

Our data element contractor also 

assembled a 16-member TEP that met on 

April 7 and 8, 2016, and January 5 and 

6, 2017, in Baltimore, Maryland, to 

provide expert input on data elements 

that are currently in each PAC 

assessment instrument, as well as data 

elements that could be standardized. 

The Development and Maintenance of 

Post-Acute Care Cross-Setting 

Standardized Patient Assessment Data 

TEP Summary Reports are available at 

https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/

IMPACT-Act-Downloads-andVideos.html. 

As part of the environmental scan, 

data elements currently in the four 

existing PAC assessment instruments 

were examined to see if any could be 

considered for proposal as standardized 

patient assessment data. Specifically, 

this evaluation included consideration 

of data elements in OASIS–C2 (effective 

January 2017); IRF–PAI, v1.4 (effective 

October 2016); LCDS, v3.00 (effective 

April 2016); and MDS 3.0, v1.14 

(effective October 2016). Data elements 

in the standardized assessment 

instrument that we tested in the PostAcute Care Payment Reform 

Demonstration (PAC PRD)—the 

Continuity Assessment Record and 

public reporting Evaluation (CARE)— 

were also considered. A literature 

search was also conducted to determine 

whether we could propose to adopt 

additional data elements as 

standardized patient assessment data. 

Additionally, we held four Special 

Open Door Forums (SODFs) on October 

27, 2015; May 12, 2016; September 15, 

2016; and December 8, 2016, to present 

data elements we were considering and 

to solicit input. At each SODF, some 

stakeholders provided immediate input, 

and all were invited to submit 

additional comments via the CMS 

IMPACT Mailbox: 

PACQualityInitiative@cms.hhs.gov. 


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We also convened a meeting with 

federal agency subject matter experts 

(SMEs) on May 13, 2016. In addition, a 

public comment period was open from 

August 12 to September 12, 2016 to 

solicit comments on detailed candidate 

data element descriptions, data 

collection methods, and coding 

methods. The IMPACT Act Public 

Comment Summary Report containing 

the public comments (summarized and 

verbatim) and our responses is available 

at https://www.cms.gov/Medicare/

Quality-Initiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/

IMPACT-Act-Downloads-andVideos.html. 

We specifically sought to identify 

standardized patient assessment data 

that we could feasibly incorporate into 

the LTCH, IRF, SNF, and HHA 

assessment instruments and that have 

the following attributes: (1) Being 

supported by current science; (2) testing 

well in terms of their reliability and 

validity, consistent with findings from 

the Post-Acute Care Payment Reform 

Demonstration (PAC PRD); (3) the 

potential to be shared (for example, 

through interoperable means) among 

PAC and other provider types to 

facilitate efficient care coordination and 

improved beneficiary outcomes; (4) the 

potential to inform the development of 

quality, resource use and other 

measures, as well as future payment 

methodologies that could more directly 

take into account individual beneficiary 

health characteristics; and (5) the ability 

to be used by practitioners to inform 

their clinical decision and care planning 

activities. We also applied the same 

considerations that we apply to quality 

measures, including the CMS Quality 

Strategy which is framed using the three 

broad aims of the National Quality 

Strategy. 

3. Policy for Retaining HH QRP 

Measures and Standardized Patient 

Assessment Data 

In the CY 2017 HH PPS final rule (81 

FR 76755 through 76756), we adopted a 

policy that will allow for any quality 

measure adopted for use in the HH QRP 

to remain in effect until the measure is 

removed, suspended, or replaced. For 

further information on how measures 

are considered for removal, suspension 

or replacement, we refer readers to the 

CY 2017 HH PPS final rule (81 FR 76755 

through 76756). We proposed to apply 

this same policy to the standardized 

patient assessment data that we adopt 

for the HH QRP. 

Comment: Several commenters 

supported this proposal. 

Response: We appreciate the 

commenters’ support. 

Final Decision: We are finalizing that 

our policy for retaining HH QRP 

measures will apply to the standardized 

patient assessment data that we adopt 

for the HH QRP. 

4. Policy for Adopting Changes to HH 

QRP Measures and Application of That 

Policy to Standardized Patient 

Assessment Data 

In the CY 2017 HH PPS final rule (81 

FR 76756), we adopted a subregulatory 

process to incorporate updates to HH 

quality measure specifications that do 

not substantively change the nature of 

the measure. We noted that 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, we refer 

readers to the CY 2017 HH PPS final 

rule (81 FR 76756). We proposed to 

apply this policy to the standardized 

patient assessment data that we adopt 

for the HH QRP. We invited public 

comment on this proposal. 

Comment: One commenter requested 

that we propose to adopt all substantive 

changes to measures only after soliciting 

input from a technical expert panel of 

home health clinical leaders, holding a 

Special Open Door Forum to explain the 

changes under consideration, and 

allowing stakeholders to submit 

meaningful comments on those 

potential changes. 

Response: We agree that input from 

both technical experts and the public is 

critical to the measure development 

process, and we generally solicit both 

types of input when we consider 

whether to propose substantive updates 

to measures. We also solicit input in 

other ways, such as through open door 

forums and solicitations for public 

comment, and often engage in these 

activities prior to proposing substantive 

updates through the rulemaking 

process. Finally, the rulemaking process 

itself gives the public an additional 

opportunity to comment on the 

substantive updates to measures under 

consideration. 

Final Decision: After consideration of 

the public comments, we are finalizing 

that we will apply our policy for 

adopting changes to HH QRP measures 

to the standardized patient assessment 

data that we adopt for the HH QRP. 

5. Quality Measures Previously 

Finalized for the HH QRP 

The HH QRP currently has 23 

measures, as outlined in Table 18. 

TABLE 18—MEASURES CURRENTLY ADOPTED FOR THE HH QRP 

Short name Measure name & data source 

OASIS-based 

Pressure Ulcers ........................................... Percent of Patients or Residents with Pressure Ulcers that are New or Worsened (NQF # 0678).* ∂

DRR ............................................................. Drug Regimen Review Conducted with Follow-Up for Identified Issues-Post Acute Care (PAC) Home Health Quality Reporting Program.∂

Ambulation ................................................... Improvement in Ambulation/Locomotion (NQF #0167). 

Bathing ......................................................... Improvement in Bathing (NQF #0174). 

Dyspnea ....................................................... Improvement in Dyspnea. 

Oral Medications .......................................... Improvement in Management of Oral Medication (NQF #0176). 

Pain .............................................................. Improvement in Pain Interfering with Activity (NQF #0177). 

Surgical Wounds .......................................... Improvement in Status of Surgical Wounds (NQF #0178). 

Bed Transferring .......................................... Improvement in Bed Transferring (NQF # 0175). 

Timely Care .................................................. Timely Initiation Of Care (NQF # 0526). 

Depression Assessment .............................. Depression Assessment Conducted. 

Influenza ....................................................... Influenza Immunization Received for Current Flu Season (NQF #0522). 

PPV .............................................................. Pneumococcal Polysaccharide Vaccine Ever Received (NQF #0525).

Falls Risk ..................................................... Multifactor Fall Risk Assessment Conducted For All Patients Who Can Ambulate (NQF #0537). 

Diabetic Foot Care ....................................... Diabetic Foot Care and Patient/Caregiver Education Implemented during All Episodes of Care (NQF #0519). 

Drug Education ............................................ Drug Education on All Medications Provided to Patient/Caregiver during All Episodes of Care. 

Claims-based 

MSPB ........................................................... Total Estimated Medicare Spending Per Beneficiary (MSPB)—Post Acute Care (PAC) Home Health (HH) Quality Reporting Program (QRP). ∂


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51718 Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 

29Casey, G. (2013). ‘‘Pressure ulcers reflect 

quality of nursing care.’’ Nurs N Z 19(10): 20–24. 

30 Gorzoni, M.L. and S.L. Pires (2011). ‘‘Deaths in 

nursing homes.’’ Rev Assoc Med Bras 57(3): 327– 

331. 

31Thomas, J.M., et al. (2013). ‘‘Systematic review: 

health-related characteristics of elderly hospitalized 

adults and nursing home residents associated with 

short-term mortality.’’ J Am Geriatr Soc 61(6): 902– 

911. 

32White-Chu, E.F., et al. (2011). ‘‘Pressure ulcers 

in long-term care.’’ Clin Geriatr Med 27(2): 241–258. 

33Bates-Jensen BM. Quality indicators for 

prevention and management of pressure ulcers in 

vulnerable elders. Ann Int Med. 2001;135 (8 Part 2), 

744–51. 

34Bennet, G, Dealy, C Posnett, J (2004). The cost 

of pressure ulcers in the UK, Age and Aging, 

33(3):230–235. 

35Black, Joyce M., et al. ‘‘Pressure ulcers: 

avoidable or unavoidable? Results of the national 

pressure ulcer advisory panel consensus 

conference.’’ Ostomy-Wound Management 57.2 

(2011): 24. 

36Sullivan, R. (2013). A Two-year Retrospective 

Review of Suspected Deep Tissue Injury Evolution 

in Adult Acute Care Patients. Ostomy Wound 

Management 59(9) http://www.o-wm.com/article/

two-year-retrospective-review-suspected-deeptissue-injury-evolution-adult-acute-care-patien. 

37Posthauer, ME, Zulkowski, K. (2005). Special to 

OWM: The NPUAP Dual Mission Conference: 

Reaching Consensus on Staging and Deep Tissue 

Injury. Ostomy Wound Management 51(4) http://

www.o-wm.com/content/the-npuap-dual-missionconference-reaching-consensus-staging-and-deeptissue-injury. 

TABLE 18—MEASURES CURRENTLY ADOPTED FOR THE HH QRP—Continued 

Short name Measure name & data source 

DTC .............................................................. Discharge to Community-Post Acute Care (PAC) Home Health (HH) Quality Reporting Program (QRP). ∂

PPR .............................................................. Potentially Preventable 30-Day Post-Discharge Readmission Measure for Home Health Quality Reporting Program. ∂

ACH .............................................................. Acute Care Hospitalization During the First 60 Days of Home Health (NQF #0171). 

ED Use ......................................................... Emergency Department Use without Hospitalization During the First 60 Days of Home Health (NQF #0173). 

Rehospitalization .......................................... Rehospitalization During the First 30 Days of Home Health (NQF #2380). 

ED Use without Readmission ...................... Emergency Department Use without Hospital Readmission During the First 30 Days of Home Health (NQF #2505). 

HHCAHPs-based 

Professional Care ........................................ How often the home health team gave care in a professional way. 

Communication ............................................ How well did the home health team communicate with patients. 

Team Discussion ......................................... Did the home health team discuss medicines, pain, and home safety with patients. 

Overall Rating .............................................. How do patients rate the overall care from the home health agency. 

Willing to Recommend ................................. Will patients recommend the home health agency to friends and family. 

* Not currently NQF-endorsed for the home health setting. 

The data collection period will begin with CY 2017 Q1&2 reporting for CY 2018 APU determination, followed by the previously established HH QRP use of 12 

months (July 1, 2017–June 30, 2018) of CY 2017 reporting for CY 2019 APU determination. Subsequent years will be based on the HH July 1–June 30 timeframe for 

APU purposes. For claims data, the performance period will use rolling CY claims for subsequent reporting purposes. 

F. New HH QRP Quality Measures 

Beginning With the CY 2020 HH QRP 

In the CY 2018 HH PPS proposed rule 

(82 FR 35345) we proposed that 

beginning with the CY 2020 HH QRP, in 

addition to the quality measures we are 

retaining under our policy described in 

section V.B. of this final rule, we would 

replace the current pressure ulcer 

measure entitled Percent of Residents or 

Patients with Pressure Ulcers That Are 

New or Worsened (Short Stay) (NQF 

#0678) with a modified version of the 

measure and adopt one measure on 

patient falls and one measure on 

assessment of patient functional status. 

We also proposed to characterize the 

data elements described in this section 

as standardized patient assessment data 

under section 1899B(b)(1)(B) of the Act 

that must be reported by HHAs under 

the HH QRP through the OASIS. The 

new measures that we proposed to 

adopt are as follows: 

• Changes in Skin Integrity PostAcute Care: Pressure Ulcer/Injury. 

• Application of Percent of Residents 

Experiencing One or More Falls with 

Major Injury (NQF #0674). 

• Application of Percent of LongTerm Care Hospital Patients with an 

Admission and Discharge Functional 

Assessment and a Care Plan That 

Addresses Function (NQF #2631). 

The measures are described in more 

detail as follows: 

1. Replacing the Current Pressure Ulcer 

Quality Measure, Entitled Percent of 

Residents or Patients With Pressure 

Ulcers That Are New or Worsened 

(Short Stay) (NQF #0678), With a 

Modified Pressure Ulcer Measure, 

Entitled Changes in Skin Integrity PostAcute Care: Pressure Ulcer/Injury 

a. Measure Background 

We proposed to remove the current 

pressure ulcer measure, Percent of 

Residents or Patients with Pressure 

Ulcers That Are New or Worsened 

(Short Stay) (NQF #0678), from the HH 

QRP measure set and to replace it with 

a modified version of that measure, 

Changes in Skin Integrity Post-Acute 

Care: Pressure Ulcer/Injury, beginning 

with the CY 2020 HH QRP. The change 

in the measure name is to reduce 

confusion about the new modified 

measure. The modified version differs 

from the current version of the measure 

because it includes new or worsened 

unstageable pressure ulcers, including 

deep tissue injuries (DTIs), in the 

measure numerator. The proposed 

modified version of the measure also 

contained updated specifications 

intended to eliminate redundancies in 

the assessment items needed for its 

calculation and to reduce the potential 

for underestimating the frequency of 

pressure ulcers. The modified version of 

the measure would satisfy the IMPACT 

Act domain of ‘‘Skin integrity and 

changes in skin integrity.’’ 

b. Measure Importance 

As described in the CY 2016 HH PPS 

final rule (80 FR 68697), pressure ulcers 

are high-cost adverse events and are an 

important measure of quality. For 

information on the history and rationale 

for the relevance, importance, and 

applicability of having a pressure ulcer 

measure in the HH QRP, we referred 

readers to the CY 2016 HH PPS final 

rule (80 FR 68697 to 68700. 

We proposed to adopt a modified 

version of the current pressure ulcer 

measure because unstageable pressure 

ulcers, including DTIs, are similar to 

Stage 2, Stage 3, and Stage 4 pressure 

ulcers in that they represent poor 

outcomes, are a serious medical 

condition that can result in death and 

disability, are debilitating and painful 

and are often an avoidable outcome of 

medical care.29 30 31 32 33 34 Studies show 

that most pressure ulcers can be avoided 

and can also be healed in acute, postacute, and long term care settings with 

appropriate medical care. 35

Furthermore, some studies indicate that 

DTIs, if managed using appropriate care, 

can be resolved without deteriorating 

into a worsened pressure ulcer.36 37

While there are few studies that 

provide information regarding the 

incidence of unstageable pressure ulcers 

in PAC settings, an analysis conducted 

by our measure development contractor 

indicated that adding unstageable 

pressure ulcers to the quality measure 

numerator would result in a higher 


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38Schwartz, M., Nguyen, K.H., Swinson Evans, 

T.M., Ignaczak, M.K., Thaker, S., and Bernard, S.L.: 

Development of a Cross-Setting Quality Measure for 

Pressure Ulcers: OY2 Information Gathering, Final 

Report. Centers for Medicare & Medicaid Services, 

November 2013. Available: https://www.cms.gov/

Medicare/Quality-Initiatives-Patient-AssessmentInstruments/Post-Acute-Care-Quality-Initiatives/

Downloads/Development-of-a-Cross-SettingQuality-Measure-for-Pressure-Ulcers-InformationGathering-Final-Report.pdf. 

39Schwartz, M., Ignaczak, M.K., Swinson Evans, 

T.M., Thaker, S., and Smith, L.: The Development 

of a Cross-Setting Pressure Ulcer Quality Measure: 

Summary Report on November 15, 2013, Technical 

Expert Panel Follow-Up Webinar. Centers for 

Medicare & Medicaid Services, January 2014. 

Available: https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/PostAcute-Care-Quality-Initiatives/Downloads/

Development-of-a-Cross-Setting-Pressure-UlcerQuality-Measure-Summary-Report-on-November15-2013-Technical-Expert-Pa.pdf. 

percentage of patients with new or 

worsened pressure ulcers in HHA 

settings and increase the variability of 

measure scores. A higher percentage 

indicates lower quality. This increased 

variability serves to improve the 

measure by improving the ability of the 

measure to distinguish between high 

and low quality home health agencies. 

We have found in the testing of this 

measure that given the low prevalence 

of pressure ulcers in the home health 

setting, the addition of unstageable 

ulcers to this measure could enhance 

variability. Analysis of 2015 OASIS data 

found that in approximately 1.2 percent, 

or more than 70,000 episodes, of 

patients had an unstageable ulcer upon 

admission. Patients in more than 13,000 

episodes were discharged with an 

unstageable ulcer. In addition, 

unstageable ulcers due to slough/eschar 

worsened between admission and 

discharge in approximately 5,000 

episodes of care. In conclusion, the 

inclusion of unstageable pressure ulcers, 

including DTIs, in the numerator of this 

measure is expected to increase measure 

scores and variability in measure scores, 

thereby improving the ability to 

discriminate among poor- and highperforming HHAs. 

Testing shows similar results in other 

PAC settings. For example, in SNFs, 

using data from Quarter 4 2015 through 

Quarter 3 2016, the mean score on the 

currently implemented pressure ulcer 

measure is 1.75 percent, compared with 

2.58 percent in the proposed measure. 

In the proposed measure, the SNF mean 

score is 2.58 percent; the 25th and 75th 

percentiles are 0.65 percent and 3.70 

percent, respectively; and 20.32 percent 

of facilities have perfect scores. In 

LTCHs, using data from Quarter 1 

through Quarter 4 2015, the mean score 

on the currently implemented pressure 

ulcer measure is 1.95 percent, compared 

with 3.73 percent in the proposed 

measure. In the proposed measure, the 

LTCH mean score is 3.73 percent; the 

25th and 75th percentiles are 1.53 

percent and 4.89 percent, respectively; 

and 5.46 percent of facilities have 

perfect scores. In IRFs, using data from 

Quarter 4 2016, the mean score on the 

currently implemented pressure ulcer 

measure is 0.64 percent, compared with 

1.46 percent in the proposed measure. 

In the proposed measure, the IRF mean 

score is 1.46 percent and the 25th and 

75th percentiles are 0 percent and 2.27 

percent, respectively. The inclusion of 

unstageable pressure ulcers, including 

DTIs, in the numerator of this measure 

is expected to increase measure scores 

and variability in measure scores, 

thereby improving the ability to 

distinguish between poor and high 

performing HHAs. 

This increased variability of scores 

across quarters and deciles may improve 

the ability of the measure to distinguish 

between high and low performing 

providers across PAC settings. 

c. Stakeholder Feedback 

Our measure development contractor 

sought input from subject matter 

experts, including Technical Expert 

Panels (TEPs), over the course of several 

years on various skin integrity topics 

and specifically those associated with 

the inclusion of unstageable pressure 

ulcers including DTIs. Most recently, on 

July 18, 2016, a TEP convened by our 

measure development contractor 

provided input on the technical 

specifications of this proposed quality 

measure, including the feasibility of 

implementing the proposed measure’s 

updates across PAC settings. The TEP 

supported the use of the proposed 

measure across PAC settings, including 

the use of different data elements for 

measure calculation. The TEP supported 

the updates to the measure across PAC 

settings, including the inclusion in the 

numerator of unstageable pressure 

ulcers due to slough and/or eschar that 

are new or worsened, new unstageable 

pressure ulcers due to a non-removable 

dressing or device, and new DTIs. The 

TEP recommended supplying additional 

guidance to providers regarding each 

type of unstageable pressure ulcer. This 

support was in agreement with earlier 

TEP meetings, held on June 13, and 

November 15, 2013, which had 

recommended that CMS update the 

specifications for the pressure ulcer 

measure to include unstageable pressure 

ulcers in the numerator.38 39 Exploratory 

data analysis conducted by our measure 

development contractor suggests that 

the addition of unstageable pressure 

ulcers, including DTIs, will increase the 

observed incidence of new or worsened 

pressure ulcers at the facility level and 

may improve the ability of the proposed 

quality measure to discriminate between 

poor- and high-performing agencies. 

We solicited stakeholder feedback on 

this proposed measure by means of a 

public comment period held from 

October 17 through November 17, 2016. 

In general, we received considerable 

support for the proposed measure. A 

few commenters supported all of the 

changes to the current pressure ulcer 

measure that resulted in the proposed 

measure, with one commenter noting 

the significance of the work to align the 

pressure ulcer quality measure 

specifications across the PAC settings. 

Many commenters supported the 

inclusion of unstageable pressure ulcers 

due to slough/eschar, due to nonremovable dressing/device, and DTIs in 

the proposed quality measure. Other 

commenters did not support the 

inclusion of DTIs in the proposed 

quality measure because they stated that 

there is no universally accepted 

definition for this type of skin injury. 

Some commenters provided feedback 

on the data elements used to calculate 

the proposed quality measure. We 

believe that these data elements will 

promote facilitation of cross-setting 

quality comparison as required under 

the IMPACT Act, alignment between 

quality measures and payment, 

reduction in redundancies in 

assessment items, and prevention of 

inappropriate underestimation of 

pressure ulcers. The currently 

implemented pressure ulcer measure is 

calculated using retrospective data 

elements that assess the number of new 

or worsened pressure ulcers at each 

stage, while the proposed measure is 

calculated using data elements that 

assess the current number of unhealed 

pressure ulcers at each stage, and the 

number of these that were present upon 

admission, which are subtracted from 

the current number at that stage. Some 

commenters did not support the data 

elements that will be used to calculate 

the proposed measure, and requested 

further testing of these data elements. 

Other commenters supported the use of 

these data elements stating that these 

data elements simplified the measure 

calculation process. 

The public comment summary report 

for the proposed measure is available on 

the CMS Web site at https://

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/

IMPACT-Act-Downloads-andVideos.html. 


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51720 Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 

The NQF-convened Measures 

Application Partnership (MAP) PostAcute Care/Long-Term Care (PAC/LTC) 

Workgroup met on December 14 and 15, 

2016, and provided us input about this 

proposed measure. The NQF-convened 

MAP PAC/LTC workgroup provided a 

recommendation of ‘‘support for 

rulemaking’’ for use of the proposed 

measure in the HH QRP. The MAP 

Coordinating Committee met on January 

24 and 25, 2017, and provided a 

recommendation of ‘‘conditional 

support for rulemaking’’ for use of the 

proposed measure in the HH QRP. The 

MAP’s conditions of support include 

that, as a part of measure 

implementation, we provide guidance 

on the correct collection and calculation 

of the measure result, as well as 

guidance on public reporting Web sites 

explaining the impact of the 

specification changes on the measure 

result. The MAP’s conditions also 

specify that CMS continue analyzing the 

proposed measure to investigate 

unexpected results reported in public 

comment. We stated in the proposed 

rule that we intend to fulfill these 

conditions by offering additional 

training opportunities and educational 

materials in advance of public reporting, 

and by continuing to monitor and 

analyze the proposed measure. We 

currently provide private provider 

feedback reports as well as a Quarterly 

Quality Measure report that allows 

HHAs to track their measure outcomes 

for quality improvement purposes. 

Aside from those reports, we conduct 

internal monitoring and evaluation of 

our measures to ensure that the 

measures are performing as they were 

intended to perform during the 

development of the measure. More 

information about the MAP’s 

recommendations for this measure is 

available at http://www.qualityforum.

org/WorkArea/linkit.aspx?Link

Identifier=id&ItemID=84452. 

We reviewed the NQF’s consensus 

endorsed measures and were unable to 

identify any home health measures that 

address changes in skin integrity related 

to pressure ulcers. Therefore, based on 

the evidence previously discussed, we 

proposed to adopt the quality measure 

entitled, Changes in Skin Integrity PostAcute Care: Pressure Ulcer/Injury, for 

the HH QRP beginning with the CY 

2020 HH QRP. We noted that we plan 

to submit the proposed measure to the 

NQF for endorsement consideration as 

soon as feasible. 

d. Data Collection 

The data for this quality measure will 

be collected using the OASIS data set, 

which is currently submitted by HHAs 

through the Quality Improvement and 

Evaluation System (QIES) Assessment 

Submission and Processing (ASAP) 

System. While the inclusion of 

unstageable wounds in the proposed 

measure results in a measure calculation 

methodology that is different from the 

methodology used to calculate the 

current pressure ulcer measure, the data 

elements needed to calculate the 

proposed measure are already included 

on the OASIS data set. In addition, our 

proposal to eliminate duplicative data 

elements that were used in calculation 

of the current pressure ulcer measure 

will result in an overall reduced 

reporting burden for HHAs for the 

proposed measure. For more 

information on OASIS data set 

submission using the QIES ASAP 

System, we refer readers to https://

www.qtso.com/. 

For technical information about this 

proposed measure, including 

information about the measure 

calculation and the standardized patient 

assessment data elements used to 

calculate this measure, we refer readers 

to the document titled Finalized 

Specifications for HH QRP Quality 

Measures and Standardized Patient 

Assessment Data Elements, available at 

https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

HHQIQualityMeasures.html. 

We proposed that HHAs will begin 

reporting the proposed pressure ulcer 

measure, Changes in Skin Integrity PostAcute Care: Pressure Ulcer/Injury, 

which will replace the current pressure 

ulcer measure, with data collection 

beginning with respect to admissions 

and discharges occurring on or after 

January 1, 2019. 

We solicited public comment on our 

proposal to remove the current pressure 

ulcer measure, Percent of Residents or 

Patients with Pressure Ulcers That Are 

New or Worsened (Short Stay) (NQF 

#0678), and replace it with a modified 

version of that measure, entitled, 

Changes in Skin Integrity Post-Acute 

Care: Pressure Ulcer/Injury, beginning 

with the CY 2020 HH QRP. 

Comment: Several commenters 

supported the proposed replacement of 

the current pressure ulcer measure, 

Percent of Residents or Patients with 

Pressure Ulcers That Are New or 

Worsened (Short Stay) (NQF #0678), 

with a modified version of that measure 

entitled, Changes in Skin Integrity PostAcute Care: Pressure Ulcer/Injury. One 

of these commenters noted that this 

measure will increase the number of 

identified pressure ulcers. 

One commenter supported the 

proposed measure calculation approach 

because it does not include pressure 

ulcers that were present at the time of 

admission, and noted that a pressure 

ulcer that is present on admission is 

only included in the measure if it 

subsequently worsens during the home 

health episode of care. 

Response: We appreciate the 

commenters’ support. 

Comment: A few commenters 

suggested that we make additional 

refinements to the proposed measure 

before we adopt it for the HH QRP; 

however, these commenters did not 

specifically describe any proposed 

refinements. One commenter stated 

generally that the measure was not fully 

developed. Another commenter 

expressed concerns about the 

differences between the specifications 

for this measure in the SNF setting 

related to other PAC settings, including 

the home health setting. A few 

commenters additionally commented on 

the reliability and validity of the 

proposed measure, Changes in Skin 

Integrity Post-Acute Care: Pressure 

Ulcer/Injury. Some commenters 

requested that additional testing 

analyses be conducted prior to the 

implementation of this measure, and 

others recommended that we conduct 

additional testing to determine the 

applicability of this measure for its use 

in the home health setting. One 

commenter encouraged CMS to 

continue to test the measure to ensure 

it collects accurate data. 

Response: We believe that the 

Changes in Skin Integrity Post-Acute 

Care: Pressure Ulcer/Injury measure is a 

fully developed measure that is 

standardized across the PAC settings, 

including in the SNF setting. Testing 

results for this measure indicated 

increased observed pressure ulcer scores 

in the LTCH, IRF, SNF and HH patient 

populations when the unstageable 

ulcers were included, compared with 

the previously implemented pressure 

ulcer measure. Specifically, an analysis 

conducted by the measure development 

contractor, using data from October 

through December 2016, showed mean 

scores increasing by 2.03 percentage 

points in home health, with the addition 

of unstageable pressure ulcers in the 

measure. The changes in the proposed 

measure also increased the variability of 

measures scores. 

Further, the reliability and validity of 

the M0300/M1311 data elements used to 

calculate this quality measure have been 

tested in several ways. The MDS 3.0 

pilot test showed good reliability in the 

SNF setting, and we believe that the 

results are applicable to other post-acute 

care providers, including HHAs, 

because the data elements are 


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40Landis, R., & Koch, G. (1977, March). The 

measurement of observer agreement for categorical 

data. Biometrics 33(1), 159–174. Landis, R., & Koch, 

G. (1977, March). The measurement of observer 

agreement for categorical data. Biometrics 33(1), 

159–174. 

standardized across the LTCH, IRF, 

SNF, and HH settings. Testing 

conducted to evaluate our ability to 

derive the measure’s numerator from the 

M0300 data elements revealed that 

accuracy improved. The M0300 data 

elements are standardized with the 

M1311 data elements used in OASIS, 

and we are able to determine that we 

can also reliably use M1311 data 

elements to calculate the measure. 

Additionally, with regard to the 

reliability of the pressure ulcer data 

elements, the average gold-standard to 

gold-standard kappa statistic was 0.905. 

The average gold-standard to facilitynurse kappa statistic was 0.937. These 

kappa scores indicate ‘‘almost perfect’’ 

agreement using the Landis and Koch 

standard for strength of agreement.40

A main difference between the 

current and proposed pressure ulcer 

measures is that the proposed measure 

includes unstageable pressure ulcers, 

including DTIs, in the numerator of the 

quality measure, resulting in increased 

scores in all settings. By including 

pressure ulcers that were not included 

in the numerator of the current pressure 

ulcer measure, the scores on the 

proposed measure are higher and the 

risk of the measure being ‘‘topped-out’’ 

is lower. 

To assess the construct validity of this 

measure, or the degree to which the 

measure assesses what it claims or 

purports to be assessing, our measure 

contractor sought input from TEPs over 

the course of several years. Most 

recently, on July 18, 2016, a TEP 

supported the inclusion in the 

numerator of unstageable pressure 

ulcers due to slough and/or eschar that 

are new or worsened, new unstageable 

pressure ulcers/injuries due to a nonremovable dressing or device, and new 

DTIs. The measure testing activities 

were presented to TEP members for 

their input on the reliability, validity, 

and feasibility of the proposed measure 

and the changes. The TEP members 

supported the measure construct. 

We intend to continue to perform 

reliability and validity testing to ensure 

that that the measure demonstrates 

scientific acceptability (including 

reliability and validity) and meets the 

goals of the HH QRP. Further, while we 

intend to validate the data collected to 

ensure data accuracy, we note that 

providers are expected to submit 

accurate data. Finally, as with all 

measure development and 

implementation, we will provide 

training and guidance prior to 

implementation of the measure to 

promote consistency in the 

interpretation of the measure. 

Comment: A few commenters 

suggested that we monitor the measure 

for unintended consequences such as 

surveillance bias, suggesting that this 

could affect measure performance. 

Response: We appreciate the 

comments pertaining to unintended 

consequences, including potential bias 

in reporting the number and stage of 

pressure ulcers, which could affect 

measure performance. We intend to 

monitor measure results and item-level 

responses on an ongoing basis to 

identify potential biases or other issues. 

Comment: Some commenters 

expressed concerns pertaining to the 

importance of appropriate 

documentation of unstageable pressure 

ulcers, including deep tissue injuries 

(DTIs). One commenter commented that 

the definition of pressure ulcers 

included in the measure may be too 

subjective to collect reliable, accurate 

measure data across post-acute care 

providers, citing DTIs specifically. This 

commenter added that, as a result, the 

measure could provide misleading 

portrayals of HH performance. 

Response: We appreciate the 

comments pertaining to the concerns 

related to appropriate documentation 

and definition of unstageable pressure 

ulcers. We interpret the commenters’ 

comment regarding appropriate 

documentation of unstageable pressure 

ulcers in the medical record to mean 

that as a result of this measure, 

providers should ensure such 

documentation is incorporated into the 

medical record. We note that accurate 

assessment and documentation of all 

patient assessment findings is 

customary for ensuring quality care. 

We agree that unstageable pressure 

ulcers should be appropriately 

documented, but disagree that the 

definition of pressure ulcers used in the 

measure may be too subjective to allow 

for accurate and reliable data capture in 

post-acute care settings. The definitions 

of the pressure-related ulcers and 

injuries used in this measure are 

standardized and, while all healthcare 

assessment information can invoke 

clinical subjectivity, we believe that the 

definitions provided in our guidance 

manuals, which align with nationally 

recognized definitions, enables the 

collection of data in a reliable manner. 

We are also confident, based on the 

reliability testing results previously 

explained, that the measure can 

accurately assess HHA performance. 

Further, we intend to provide training to 

HHAs to ensure that they understand 

how to properly report it. 

Comment: Some commenters 

requested training, help desk support, 

and guidance in completing the items 

that will be used to calculate the 

proposed measure. One commenter also 

recommended that CMS conduct 

training on steps HHAs can take to 

improve quality. 

Response: We are currently engaged 

in efforts to provide educational 

activities related to the HH QRP, 

including training events and responses 

to questions submitted to the Help Desk, 

which will include information to help 

HHAs understand how to complete and 

code the pressure ulcer. Such 

educational and training information is 

part of our ongoing strategy to ensure 

successful implementation of the HH 

QRP, and ultimately quality 

improvement. Recordings of previous 

trainings are available on the CMS 

YouTube Web site at https://

www.youtube.com/user/CMSHHSgov/

featured, and we will continue to make 

recordings of trainings available there. 

We invite HHAs to submit specific 

inquiries related to the coding of the 

OASIS through our help desk, 

HHQualityQuestions@cms.hhs.gov. 

Additionally, a Frequently Asked 

Questions document is provided 

quarterly for the HH QRP, in the 

Downloads section of the HH Quality 

Reporting FAQs Web site at https://

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HH-Quality-Reporting/HHQuality-Reporting-FAQs-.html. These 

FAQ documents are updated to reflect 

current guidance related to the HH QRP, 

including data submission deadlines 

and training materials. 

Comment: One commenter noted the 

proposed measure requires HHAs to 

count the number of unhealed pressure 

ulcers at each stage and subtract the 

number present upon admission. While 

the commenter agreed that excluding 

pressure ulcers that are present on 

admission is an appropriate 

improvement to the measure, the 

commenter cautioned that it adds 

complexity to the coding process. Other 

commenters stated that this information 

may be difficult for providers to capture 

because of the new data elements used 

to calculate the new measure. 

Response: We disagree that the 

proposed measure will require HHAs to 

make adjustments to their coding 

processes because HHAs already submit 

the data to calculate the modified 

measure. Additionally, the assessment 

does not require HHAs to tally or count 

the number of unhealed pressure ulcers. 

We perform that calculation for 


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51722 Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 

41National Pressure Ulcer Advisory Panel 

(NPUAP) announces a change in terminology from 

pressure ulcer to pressure injury and updates the 

stages of pressure injury √ The National Pressure 

Ulcer Advisory Panel—NPUAP. (2016, April 13), 

from http://www.npuap.org/national-pressureulcer-advisory-panel-npuap-announces-a-changein-terminology-from-pressure-ulcer-to-pressureinjury-and-updates-the-stages-of-pressure-injury/. 

42Subcommittee on Health National Committee 

on Vital and Health Statistics, ‘‘Classifying and 

Reporting Functional Status’’ (2001). 43Reistetter TA, Graham JE, Granger CV, Deutsch 

A, Ottenbacher KJ. Utility of Functional Status for 

Classifying Community Versus Institutional 

Discharges after Inpatient Rehabilitation for Stroke. 

Archives of Physical Medicine and Rehabilitation, 

2010; 91:345–350. 44Miller EA, Weissert WG. Predicting Elderly 

People’s Risk for Nursing Home Placement, 

Hospitalization, Functional Impairment, and 

Mortality: A Synthesis. Medical Care Research and 

Review, 57; 3: 259–297. 45 Kortebein, P., Ferrando, A., Lombebeida, J., 

Wolfe, R., & Evans, W.J. (2007). Effect of 10 days 

of bed rest on skeletal muscle in health adults. 

JAMA; 297(16):1772–4. 47Riggs, J.S. & Madigan, E.A. (2012). Describing 

variation in home health care episodes for patients 

with heart failure. Home Health Care Management 

and Practice, 24(3): 146–152. 

48Ellenbecker, C.H., Samia, L., Cushman, M.J., & 

Alster, K (2008). Patient safety and quality: an 

evidence-based handbook for nurses. Rockville 

(MD): agency for healthcare research and quality 

(US); 2008 Apr. Chapter 13. 

purposes of calculating the measure 

rates. 

Comment: Several commenters 

recommended that CMS attain NQF 

endorsement of the Changes in Skin 

Integrity Post-Acute Care: Pressure 

Ulcer/Injury measure prior to 

implementation. 

Response: While this measure is not 

currently -endorsed by a consensusbased entity, which is currently the 

National Quality Forum (NQF), we 

believe that this measure possess the 

attributes necessary for such 

endorsement, including the measure’s 

applicability, face validity and 

feasibility, and its reliability and 

validity as derived from the national 

testing. Therefore, we believe that this 

measure is appropriate for adoption into 

the HH QRP. However, we intend to 

submit this measure to NQF for 

consideration for its consideration for 

endorsement as soon as feasible. 

Comment: A few commenters 

provided feedback on the use of the 

term ‘‘pressure injury’’. Commenters 

encouraged CMS to use the terminology 

recommended by NPUAP and to align 

with their staging definitions, which 

will assist providers to be more 

standardized. 

Response: We have integrated the 

current language of NPUAP terminology 

for coding the patient and resident 

assessment instruments, especially in 

light of the recent updates made by the 

NPUAP to their Pressure Ulcer Staging 

System. The NPUAP announced a 

change in terminology to use the term 

‘‘pressure injury’’ in April 2016.41 A 

TEP held by our measure development 

contractor on July 15, 2016, was 

supportive of using the term ‘‘pressure 

injury.’’ Some members of the TEP 

stated that the term ‘‘injury’’ is not 

associated with blame or harm by an 

entity, that ‘‘injury’’ may be a more 

inclusive term than ‘‘ulcer’’, and that 

the term ‘‘pressure injury’’ may be more 

easily and positively understood by 

patients, residents, and family members 

than ‘‘pressure ulcer.’’ The TEP 

recommended training for providers and 

consumers regarding any change in 

terminology. This change will be 

accompanied by additional training and 

guidance for providers, patients, or 

residents to clarify any confusion. 

Comment: One commenter suggested 

that the burden of replacing the current 

measure with the modified pressure 

ulcer measure will be greater than the 

burden associated with reporting the 

current pressure ulcer measure. The 

commenter encouraged CMS to 

streamline reporting and reduce 

duplicative efforts. The commenter 

further commented that CMS should 

review the total number of data points, 

including the OASIS measure set, to 

eliminate HHA documentation and 

administrative burden. 

Response: We appreciate the 

commenter’s feedback. We do not 

believe that the reporting of the 

proposed measure will impose a new 

burden on HHAs because the measure is 

calculated using data elements that are 

currently included in OASIS that HHAs 

already submit. As we continue to refine 

and modify the OASIS, we will 

continue to evaluate and avoid any 

unnecessary burden associated with the 

implementation of the HH QRP. 

Final Decision: After consideration of 

the comments received, we are 

finalizing our proposal to replace the 

current pressure ulcer measure, Percent 

of Residents or Patients with Pressure 

Ulcers That Are New or Worsened 

(Short Stay) (NQF #0678), with a 

modified version of that measure 

entitled, Changes in Skin Integrity PostAcute Care: Pressure Ulcer/Injury, 

effective with the CY 2020 HH QRP. 

2. Addressing the IMPACT Act Domain 

of Functional Status, Cognitive 

Function, and Changes in Function and 

Cognitive Function: 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) 

a. Measure Background 

Sections 1899B(c)(1)(A) of the Act 

requires that no later than the specified 

application date (which under section 

1899B(a)(1)(E)(ii) is January 1, 2019 for 

HHAs, and October 1, 2016 for SNFs, 

IRFs and LTCHs), the Secretary specify 

a quality measure to address the domain 

of ‘‘Functional status, cognitive 

function, and changes in function and 

cognitive function.’’ We proposed to 

adopt the measure, Application of 

Percent of Long-Term Care Hospital 

Patients with an Admission and 

Discharge Functional Assessment and a 

Care Plan That Addresses Function 

(NQF #2631) for the HH QRP, beginning 

with the CY 2020 program year. This is 

a process measure that reports the 

percentage of patients with an 

admission and discharge functional 

assessment and treatment goal that 

addresses function. The treatment goal 

provides evidence that a care plan with 

a goal has been established for the HH 

patient. 

The National Committee on Vital and 

Health Statistics’ Subcommittee on 

Health,42 noted that ‘‘information on 

functional status is becoming 

increasingly essential for fostering 

healthy people and a healthy 

population. Achieving optimal health 

and well-being for Americans requires 

an understanding across the life span of 

the effects of people’s health conditions 

on their ability to do basic activities and 

participate in life situations in other 

words, their functional status.’’ This is 

supported by research showing that 

patient and resident functioning is 

associated with important outcomes 

such as discharge destination and length 

of stay in inpatient settings,43 as well as 

the risk of nursing home placement and 

hospitalization of older adults living in 

the community.44 For example, many 

patients who utilize HH services may be 

at risk for a decline in function due to 

limited mobility and ambulation.45

Thus, impairment in function activities 

such as self-care and mobility is highly 

prevalent in HH patients. For example, 

in 98 percent of the over six million HH 

episodes in 2015, the patient had at 

least one limitation or was not 

completely independent in self-care 

activities such as grooming, upper and 

lower body dressing, bathing, toilet 

hygiene, and/or feeding/eating.46

The primary goal of home health care 

is to provide restorative care when 

improvement is expected, maintain 

function and health status if 

improvement is not expected, slow the 

rate of functional decline to avoid 

institutionalization in an acute or postacute setting, and/or facilitate transition 

to end-of-life care as appropriate.47 48


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& Dalton, J. (2012). The influence of social 

environmental factors on rehospitalization among 

patients receiving home health care services. ANS. 

Advances in Nursing Science, 35(4), 346–358. 

https://doi.org/10.1097/ANS.0b013e318271d2ad. 

65Hayes, S.L., Salzberg, C.A., McCarthy, D., 

Radley, DC, Abrams, M.K., Shah, T., and Anderson, 

G.F. (2016). High-Need, High-Cost Patients: Who are 

they and how do they use health care—A 

population-based comparison of demographics, 

health care use, and expenditures. The 

Commonwealth Fund. 

66 Kortebein P, Ferrando A, Lombebeida J, Wolfe 

R, Evans WJ. Effect of 10 days of bed rest on skeletal 

muscle in health adults. JAMA; 297(16):1772–4. 

67Ellenbecker CH, Samia L, Cushman MJ, Alster 

K. Patient safety and quality in home health care. 

Patient Safety and Quality: An Evidence-Based 

Handbook for Nurses. Vol 1. 

68 Kresevic DM. Assessment of physical function. 

In: Boltz M, Capezuti E, Fulmer T, Zwicker D, 

editor(s). Evidence-based geriatric nursing protocols 

for best practice. 4th ed. New York (NY): Springer 

Publishing Company; 2012. p. 89–103. 

Home health care can positively impact 

functional outcomes. In stroke patients, 

home-based rehabilitation programs 

administered by home health clinicians 

significantly improved ADL function 

and gait performance.49 Home health 

services, delivered by a registered nurse, 

positively impacted patient Quality of 

Life (QOL) and clinical outcomes, 

including significant improvement in 

dressing lower body, bathing meal 

preparation, shopping, and 

housekeeping. For some home health 

patients, achieving independence 

within the living environment and 

improved community mobility might be 

the goal of care. For others, the goal of 

care might be to slow the rate of 

functional decline to avoid 

institutionalization.50

Patients’ functional status is 

associated with important patient 

outcomes, so measuring and monitoring 

the patients’ extent of engaging in selfcare and mobility is valuable. 

Functional decline among the elderly; 51

and chronic illness comorbidities, such 

as chronic pain among the older adult 

population 52 53 are associated with 

decreases in self-sufficiency and patient 

activation (defined as the patient’s 

knowledge and confidence in selfmanaging their health). Impaired 

mobility, frailty, and low physical 

activity are associated with 

institutionalization,54 higher risk of falls 

and falls-related hip fracture and 

death,55 56 greater risk of under 

nutrition,57 higher rates of inpatient 

admission from the emergency 

department,58 and higher prevalence of 

hypertension and diabetes.59

In addition, the assessment of 

functional ability and provision of 

treatment plans directed toward 

improving or maintaining functional 

ability could impact health care costs. 

Providing comprehensive home health 

care, which includes improving or 

maintaining functional ability for frail 

elderly adults, can reduce the likelihood 

of hospital readmissions or emergency 

department visits, leading to reduced 

health care service expenditures. 60 61 62

Reducing preventable 

rehospitalizations, which made up 

approximately 17 percent of Medicare’s 

$102.6 billion in 2004 hospital 

payments, creates the potential for large 

health care cost savings.63 64

Further, improving and maintaining 

functional ability in individuals with 

high needs, defined as those with three 

or more chronic conditions, may also 

account for an increase in healthcare 

savings. Adults with three or more 

chronic conditions have nearly four 

times the average annual per-person 

spending for health care services and 

prescription medications than the 

average for all U.S. adults, and high 

needs adults with limitations in their 

ability to perform ADLs, have even 

higher average annual health care 

expenditures.65 High needs individuals 

with functional limitations spend, on 

average, $21,021 on annual health care 

services, whereas the average annual 

health care expenditures for all U.S. 

adults are approximately $4,845.45. 

b. Measure Importance 

The majority of individuals who 

receive PAC services, including care 

provided by HHAs, SNFs, IRFs, and 

LTCHs, have functional limitations, and 

many of these individuals are at risk for 

further decline in function due to 

limited mobility and ambulation.66 The 

patient populations treated by HHAs, 

SNFs, IRFs, and LTCHs vary in terms of 

their functional abilities. For example, 

for home health patients, achieving 

independence within the home 

environment and promoting community 

mobility may be the goal of care. For 

other home health patients, the goal of 

care may be to slow the rate of 

functional decline in order to allow the 

person to remain at home and avoid 

institutionalization.67 The clinical 

practice guideline Assessment of 

Physical Function 68 recommends that 

clinicians document functional status at 

baseline and over time to validate 

capacity, decline, or progress. Therefore, 

assessment of functional status at 

admission and discharge, as well as 

establishing a functional goal for 

discharge as part of the care plan is an 


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51724 Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 

69Barbara Gage et al., ‘‘The Development and 

Testing of the Continuity Assessment Record and 

Evaluation (CARE) Item Set: Final Report on the 

Development of the CARE Item Set’’ (RTI 

International, 2012). 

70 Ibid. 

71 Ibid. 

important aspect of patient or resident 

care across PAC settings. 

Currently, functional assessment data 

are collected by all four PAC providers, 

yet data collection has employed 

different assessment instruments, scales, 

and item definitions. The data cover 

similar topics, but are not standardized 

across PAC settings. The different sets of 

functional assessment items coupled 

with different rating scales makes 

communication about patient and 

resident functioning challenging when 

patients and residents transition from 

one type of setting to another. Collection 

of standardized functional assessment 

data across HHAs, SNFs, IRFs, and 

LTCHs using common data items will 

establish a common language for patient 

and resident functioning, which may 

facilitate communication and care 

coordination as patients and residents 

transition from one type of provider to 

another. The collection of standardized 

functional status data may also help 

improve patient functioning during an 

episode of care by ensuring that basic 

daily activities are assessed for all PAC 

residents at the start and end of care, 

and that at least one functional goal is 

established. 

The functional assessment items 

included in the proposed functional 

status quality measure were originally 

developed and tested as part of the PostAcute Care Payment Reform 

Demonstration version of the Continuity 

Assessment Record and Evaluation 

(CARE) Item Set, which was designed to 

standardize the assessment of a person’s 

status, including functional status, 

across acute and post-acute settings 

(HHAs, SNFs, IRFs, and LTCHs). The 

functional status items in the CARE 

Item Set are daily activities that 

clinicians typically assess at the time of 

admission and/or discharge to 

determine patient or resident needs, 

evaluate patient or resident progress, 

and prepare patients, residents, and 

their families for a transition to home or 

to another setting. 

The development of the CARE Item 

Set and a description and rationale for 

each item is described in a report 

entitled ‘‘The Development and Testing 

of the Continuity Assessment Record 

and Evaluation (CARE) Item Set: Final 

Report on the Development of the CARE 

Item Set: Volume 1 of 3.’’ 69 Reliability 

and validity testing were conducted as 

part of CMS’s Post-Acute Care Payment 

Reform Demonstration (PAC–PRD), and 

we concluded that the functional status 

items have acceptable reliability and 

validity. Testing for the functional 

assessment items concluded that the 

items were able to evaluate all patients 

on basic self-care and mobility 

activities, regardless of functional level 

or PAC setting. A description of the 

testing methodology and results are 

available in several reports, including 

the report entitled ‘‘The Development 

and Testing of the Continuity 

Assessment Record And Evaluation 

(CARE) Item Set: Final Report On 

Reliability Testing: Volume 2 of 3’’ 70

and the report entitled ‘‘The 

Development and Testing of The 

Continuity Assessment Record And 

Evaluation (CARE) Item Set: Final 

Report on Care Item Set and Current 

Assessment Comparisons: Volume 3 of 

3.’’ 71 These reports are available on our 

Post-Acute Care Quality Initiatives Web 

page at http://www.cms.gov/Medicare/

Quality-Initiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/CARE-Item-Set-and-BCARE.html. 

Additional testing of these functional 

assessment items was conducted in a 

small field test occurring in 2016–2017, 

capturing data from 12 HHAs. 

Preliminary data results yielded 

moderate to substantial reliability for 

the self-care and mobility data items. 

More information about testing design 

and results can be found at https://

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

OASIS-Data-Sets.html. 

The functional status quality measure 

we proposed to adopt beginning with 

the CY 2020 HH QRP is a process 

quality measure that is an application of 

the NQF-endorsed quality measure, the 

Percent of Long-Term Care Hospital 

Patients with an Admission and 

Discharge Functional Assessment and a 

Care Plan that Addresses Function (NQF 

#2631). This quality measure reports the 

percent of patients with both an 

admission and a discharge functional 

assessment and a functional treatment 

goal. 

This process measure requires the 

collection of admission and discharge 

functional status data by clinicians 

using standardized patient assessment 

data elements, which assess specific 

functional activities, such as self-care 

and mobility activities. The self-care 

and mobility function activities are 

coded using a 6-level rating scale that 

indicates the patient’s level of 

independence with the activity at both 

admission and discharge. A higher score 

indicates more independence. These 

functional assessment data elements 

will be collected at Start or Resumption 

of Care (SOC/ROC) and discharge. 

For this quality measure, there must 

be documentation at the time of 

admission (SOC) that at least one 

activity performance (function) goal is 

recorded for at least one of the 

standardized self-care or mobility 

function items using the 6-level rating 

scale. This indicates that an activity 

goal(s) has been established. Following 

this initial assessment, the clinical best 

practice will be to ensure that the 

patient’s care plan reflected and 

included a plan to achieve such activity 

goal(s). At the time of discharge, goal 

setting and establishment of a care plan 

to achieve the goal, is reassessed using 

the same 6-level rating scale, allowing 

for the ability to evaluate success in 

achieving the patient’s activity 

performance goals. 

To the extent that a patient has an 

unplanned discharge, for example, 

transfer to an acute care facility, the 

collection of discharge functional status 

data may not be feasible. Therefore, for 

patients with unplanned discharges, 

admission functional status data and at 

least one treatment goal must be 

reported, but discharge functional status 

data are not required to be reported. 

c. Stakeholder Feedback 

Our measures contractor convened a 

TEP on October 17 and October 18, 

2016. The TEP was composed of a 

diverse group of stakeholders with HH, 

PAC, and functional assessment 

expertise. 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 of 

reliability and validity. The TEP 

additionally provided feedback on the 

clinical assessment items used to 

calculate the measure. The TEP 

reviewed the measure ‘‘Percent of LongTerm Care Patients with an Admission 

and Discharge Functional Assessment 

and a Care Plan That Addresses 

Function (NQF 2631)’’ for potential 

application to the home health setting. 

Overall they were supportive of a 

functional process measure, noting it 

could have the positive effect of 

focusing clinician attention on 

functional status and goals. A summary 

of the TEP proceedings is available on 

the PAC Quality Initiatives Downloads 

and Videos Web page at https://

www.cms.gov/medicare/qualityinitiatives-patient-assessmentinstruments/post-acute-care-qualityinitiatives/impact-act-of-2014/impactact-downloads-and-videos.html. 


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We also solicited stakeholder 

feedback on the development of this 

measure through a public comment 

period held from November 4, 2016 

through December 5, 2016. Several 

stakeholders and organizations 

supported this measure for 

implementation and for measure 

standardization. Some commenters also 

provided feedback on the standardized 

patient assessment data elements used 

to calculate the proposed quality 

measure. Commenters offered 

suggestions, including providing 

education regarding the difference in 

measure scales for the standardized 

items relative to current OASIS 

functional items, and guidance on the 

type of clinical staff input needed to 

appropriately complete new functional 

assessment items. Commenters also 

addressed the feasibility of collecting 

data for the individual standardized 

self-care and mobility items in the home 

health setting. Finally, commenters 

noted the importance of appropriate 

goal setting when functional 

improvement for a patient may not be 

feasible. The public comment summary 

report for the proposed measure is 

available on the CMS Web site at 

https://www.cms.gov/medicare/qualityinitiatives-patient-assessmentinstruments/post-acute-care-qualityinitiatives/impact-act-of-2014/impactact-downloads-and-videos.html. 

The NQF-convened MAP met on 

December 14 and 15, 2016, and 

provided input on the use of this 

proposed measure in the HH QRP. The 

MAP recommended ‘‘conditional 

support for rulemaking’’ for this 

measure. MAP members noted the 

measure will drive care coordination 

and improve transitions by encouraging 

the use of standardized functional 

assessment items across PAC settings, 

but recommended submission to the 

NQF for endorsement to include the 

home health setting. More information 

about the MAP’s recommendations for 

this measure is available at http://

www.qualityforum.org/Publications/

2017/02/MAP_2017_Considerations_

for_Implementing_Measures_in_

Federal_Programs_-_PAC-LTC.aspx. 

We reviewed the NQF’s consensus 

endorsed measures and were unable to 

identify any home health measures that 

address functional assessment and 

treatment goals that that address 

function. However, we were able to 

identify five functional measures in 

home health that assess functional 

activities only, without a treatment goal. 

These measures are: (1) Improvement in 

Ambulation/Locomotion (NQF #0167); 

(2) Improvement in Bathing (NQF 

#0174); (3) Improvement in Bed 

Transfer (NQF #0175); (4) Improvement 

in Management of Oral Medications 

(NQF # 0176); and (5) Improvement in 

Pain Interfering with Activity (NQF 

#0177). Our review determined that 

these setting-specific measures are not 

appropriate to meet the specified 

IMPACT Act domain as they do not 

include standardized items or are not 

included for various other PAC 

populations. Specifically— 

• The items used to collect data for 

the current home health measures are 

less specific, leading to broader measure 

results, whereas the standardized 

patient assessment data items used for 

the proposed measure assess core 

activities such as rolling in bed, walking 

a specified distance, or wheelchair 

capability. 

• The item coding responses are more 

detailed when compared to the nonstandardized OASIS item responses, 

allowing for more granular data for the 

measure. 

• The proposed functional measure 

will capture a patient’s discharge goal at 

admission into home health; this detail 

is not captured in the existing endorsed 

HH function measures. 

Therefore, based on the evidence 

discussed previously, we proposed to 

adopt the quality measure entitled, 

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), for 

the HH QRP beginning with the CY 

2020 HH QRP. We noted that we plan 

to submit the proposed measure to the 

NQF for endorsement consideration as 

soon as is feasible. 

For technical information about the 

proposed measure, including 

information about the measure 

calculation and the standardized patient 

assessment data elements used to 

calculate this measure, we referred 

readers to the document titled, Final 

Specifications for HH QRP Quality 

Measures and Standardized Patient 

Assessment Data, available at https://

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

HHQIQualityMeasures.html. 

d. Data Collection 

For purposes of assessment data 

collection, we proposed to add new 

functional status items to the OASIS, to 

be collected at SOC/ROC and discharge. 

These items will assess specific self-care 

and mobility activities, and will be 

based on functional items included in 

the PAC–PRD version of the CARE Item 

Set. More information pertaining to item 

testing is available on our Post-Acute 

Care Quality Initiatives Web page at 

http://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/CARE-Item-Set-and-BCARE.html. 

To allow HHAs to fulfill the 

requirements of the Home Health 

Agency Conditions of Participation 

(HHA CoPs) (82 FR 4509), we proposed 

to add a subset of the functional 

assessment items to the OASIS, with 

collection of these items at Follow-Up 

(FU). The collection of these assessment 

items at FU by HHAs will allow them 

to fulfill the requirements outlined in 

the HHA CoPs that suggest that the 

collection of a patient’s current health, 

including functional status, be collected 

on the comprehensive assessment. 

This new subset of functional status 

items are standardized across PAC 

settings and support the proposed 

standardized measure. They are 

organized into two functional domains: 

Self-Care and Mobility. Each domain 

includes dimensions of these functional 

constructs that are relevant for home 

health patients. The proposed function 

items that we proposed to add to the 

OASIS for purposes of the calculation of 

this proposed quality measure would 

not duplicate existing items currently 

collected in that assessment instrument 

for other purposes. The current OASIS 

function items evaluate current ability, 

whereas the proposed functional items 

would evaluate an individual’s usual 

performance at the time of admission 

and at the time of discharge for goal 

setting purposes. Additionally, we 

noted that there are several key 

differences between the existing and 

new proposed function items that may 

result in variation in the patient 

assessment results including: (1) The 

data collection and associated data 

collection instructions; (2) the rating 

scales used to score a resident’s level of 

independence; and (3) the item 

definitions. A description of these 

differences is provided with the 

measure specifications available at 

https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

HHQIQualityMeasures.html. 

Because of the differences between 

the current function assessment items 

(OASIS C–2) and the proposed function 

assessment items that we would collect 

for purposes of calculating the proposed 

measure, we would require that HHAs 

submit data on both sets of items. Data 

collection for the new proposed 

function items do not substitute for the 

data collection under the current OASIS 

ADL and IADL items, and as discussed 

previously, we do not believe that the 


asabaliauskas on DSKBBXCHB2PROD with RULES
51726 Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 

72Barbara Gage et al., ‘‘The Development and 

Testing of the Continuity Assessment Record and 

Evaluation (CARE) Item Set: Final Report on the 

Development of the CARE Item Set’’ (RTI 

International, 2012). 

items are duplicative. However, we 

solicited comment on opportunities to 

streamline reporting to avoid 

duplication and minimize burden. 

We proposed that data for the 

proposed quality measure would be 

collected through the OASIS, which 

HHAs currently submit through the 

QIES ASAP system. We referred readers 

to section V.F.2 of the proposed rule (82 

FR 35345 through 35353) for more 

information on the proposed data 

collection and submission timeline for 

this proposed quality measure. We 

noted that if this measure is finalized, 

we intended to provide initial 

confidential feedback to home health 

agencies, prior to the public reporting of 

this measure. 

We solicited public comment on our 

proposal to adopt the measure, 

Application of Percent of Long-Term 

Care Hospital Patients with an 

Admission and Discharge Functional 

Assessment and a Care Plan That 

Addresses Function (NQF #2631). 

Comment: A number of commenters 

supported the proposed measure, 

Application of Percent of Long-Term 

Care Hospital Patients with an 

Admission and Discharge Functional 

Assessment and a Care Plan That 

Addresses Function (NQF #2631). 

MedPAC acknowledged the value of a 

functional status quality measure that 

would be standardized with other 

functional status quality measures 

across the four PAC settings. 

Response: We appreciate the 

commenters’ support of the measure. 

Comment: Some commenters 

suggested that CMS refine the measure 

and conduct additional testing for home 

health setting applicability before 

adopting it Other commenters 

recommended that we provide training 

and give HHAs time to adjust their 

workflow to both accommodate the new 

measure and the removal of duplicative 

data elements in the OASIS. Further, a 

few commenters expressed concern over 

the addition of the items used to 

calculate the proposed process quality 

measure, claiming that the items will be 

duplicative and that the legacy items 

must be removed from the OASIS–C2 

assessment instrument to limit provider 

burden. Commenters also requested that 

CMS consider the additional resources 

providers will need to accommodate 

item set changes and encouraged 

ongoing education efforts for new data 

elements. 

Response: The items for this measure 

were rigorously tested in the Post-Acute 

Care Payment Reform Demonstration 

(PAC PRD). Based on testing from the 

PAC PRD, the inter-rater reliability of 

the items needed to calculate this 

measure was favorable, with items’ 

kappa scores between 0.59 and 0.80. 

This is important for measuring progress 

in some of the most complex cases 

treated in post-acute care settings. The 

data elements developed to calculate 

this proposed process measure were 

also tested in a comprehensive field test 

of existing and potential OASIS data 

elements and found to be feasible with 

acceptable levels of inter-rater 

reliability, as described at https://

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

OASIS-Data-Sets.html. 

Although HHAs will need to 

incorporate the data on this measure 

into their workflow, we do not believe 

that these data elements are duplicative 

of other data already collected. The 

items needed to calculate the proposed 

measure different assessment scales, 

coding options for those with medical 

complexities, and have different 

definitions for items and activities, and 

the proposed measure’s data elements 

evaluate usual performance in various 

manners. Further, to reduce potential 

burden associated with collecting the 

proposed measure, we have included 

several mechanisms to reduce the 

number of items that apply to any one 

patient. For example, there are gateway 

questions pertaining to walking and 

wheelchair mobility that allow the 

clinician to skip items that ask if the 

patient does not walk or does not use a 

wheelchair, respectively. 

Comment: Commenters provided 

feedback on the reliability and validity 

of the items necessary to calculate the 

function process measure. Some of these 

commenters expressed concern that the 

proposed function measure has not 

undergone testing and validation in the 

home health setting or may not be 

applicable for home health setting as in 

the facility-based post-acute care 

settings. One of these commenter 

expressed concern that the scales used 

to assess the items for the proposed 

process quality measure and the current 

OASIS functional assessment items are 

different, which could affect the items’ 

reliability and validity. Another 

commenter raised concern with the 

difference in timeframe allowed for data 

collection when compared to other 

OASIS items. 

Response: In the PAC PRD, the 

functional activity items (self-care and 

mobility) were tested sufficiently in 

HHAs and with sufficient patients to 

support reliability. The functional 

assessment items were compared to 

other functional assessment instrument 

data (including OASIS functional 

assessment items), as part of the PAC– 

PRD analyses with positive results. The 

inter-rater reliability of the functional 

activity items has been tested and the 

results have been favorable with items’ 

kappa scores between .59 and .80. We 

also conducted analyses of the internal 

consistency of the function data 

analyses which indicate moderate to 

substantial agreement suggesting 

sufficient reliability for the items used 

to calculate the proposed process 

quality measure. 

We acknowledge that the scale for the 

items used to calculate the proposed 

quality measure vary from the scales 

that are used in current OASIS–C2 

items. The scale used to assess the items 

for the proposed process quality 

measure assesses independence in 

functional activities (a higher score 

indicates greater independence). We 

believe that the 6-level scale will allow 

us to better distinguish change at the 

highest and lowest levels of patient 

functioning by documenting minimal 

change from no change at the low end 

of the scale.72 The PAC PRD supported 

the use of the scale in HHAs with both 

the alpha testing and beta testing 

reinforcing the clinical logic and 

consistency of language for the 

functional assessment items. The items 

in section GG were developed with 

input from clinicians and stakeholders 

to better measure the change in 

function, regardless of the severity of 

the individual’s impairment. 

The items used to calculate the 

proposed process quality measure are 

standardized across the four PAC 

settings, based on the need for data to 

reflect the patient’s status at the time of 

SOC/ROC and EOC. We are currently 

conducting testing across the four PAC 

settings to align the most appropriate 

time frame of data collection at 

admission/SOC and at discharge/EOC. 

A full description of the analyses and 

the results are provided in the report, 

The Development and Testing of the 

Continuity Assessment Record and 

Evaluation (CARE) Item Set: Final 

Report on the Development of the CARE 

Item Set and Current Assessment 

Comparisons Volume 3 of 3, and the 

report is available at http://

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/CARE-Item-Set-and-BCARE.html. Additional testing of the 

Section GG items with the OASIS 

functional items was recently completed 


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87Patil, R., Uusi-Rasi, K., Tokola, K., Karinkanta, 

S., Kannus, P., & Sievanen, H. (2015). Effects of a 

Multimodal Exercise Program on Physical Function, 

Falls, and Injuries in Older Women: A 2-Year 

Community-Based, Randomized Controlled Trial. 

Journal of the American Geriatrics Society, 63(7), 

1306–1313. 

88Centers for Disease Control and Prevention, 

National Center for Injury Prevention and Control. 

Web–based Injury Statistics Query and Reporting 

System (WISQARS) [online]. Accessed August 5, 

2016. 

89Burns ER, Stevens JA, Lee R. The direct costs 

of fatal and non-fatal falls among older adults— 

United States. J Safety Res 2016;58:99–103. 

and will to continue to help inform 

guidance for HH providers. 

Comment: One commenter suggested 

that the OASIS should include an 

assessment of Instrumental Activities of 

Daily Living (IADL) as a part of 

functional assessment. 

Response: We appreciate the 

commenter’s recommendation and will 

take it into consideration in future 

measure refinement work. 

Comment: Commenters expressed 

concern about different clinical staff 

assessing functional status and setting 

functional goals across PAC settings, 

noting that in some settings, such as 

SNFs, licensed physical therapists 

typically assess function and set 

functional goals, whereas in HHAs, 

nurses typically perform that 

assessment. Commenters noted that 

setting a goal will pose a challenge for 

nurses in the home health setting. 

Response: We are unclear why the 

commenters believe that goal setting 

will be more difficult in the home 

health setting than in other settings. The 

goals being assessed through the 

measure are intended to be set by 

patients, not clinicians. In addition, the 

original testing of the assessment items 

used for the proposed measure included 

a wide variety of clinicians to assess 

item collection, coding and reliability. 

For more information on testing results, 

we refer readers to the PAC PRD final 

report located at: https://www.cms.gov/ 

Medicare/Quality-Initiatives-PatientAssessment-Instruments/Post-AcuteCare-Quality-Initiatives/Downloads/

The-Development-and-Testing-of-theContinuity-Assessment-Record-andEvaluation-CARE-Item-Set-Final-Reporton-the-Development-of-the-CARE-ItemSet-Volume-1-of-3.pdf. 

Final Decision: After consideration of 

the comments received, we are 

finalizing, as proposed, the adoption of 

the measure entitled the 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) for the HH QRP beginning 

with the CY 2020 program year. 

3. Addressing the IMPACT Act Domain 

of ‘‘Incidence of Major Falls’’ Measure: 

Percent of Residents Experiencing One 

or More Falls With Major Injury 

a. Measure Background 

Section 1899B(c)(1)(D) of the Act 

requires that no later than the specified 

application date (which under section 

1899B(a)(1)(E)(i)(IV) of the Act is 

January 1, 2019 for HHAs, and October 

1, 2016 for SNFs, IRFs and LTCHs), the 

Secretary specify a measure to address 

the domain of incidence of major falls, 

including falls with major injury. We 

proposed to adopt the measure, 

Application of Percent of Residents 

Experiencing One or More Falls with 

Major Injury (NQF #0674), for which we 

would begin to collect data on January 

1, 2019 for the CY 2020 HH QRP to meet 

this requirement. This proposed 

outcome measure reports the percentage 

of patients who have experienced falls 

with major injury during episodes 

ending in a 3-month period. 

b. Measure Importance 

Falls affect an estimated 6 to 12 

million older adults each year and are 

the leading cause of both fatal injury 

and nonfatal hospital admissions.73 74

Within the home health population, the 

risk of falling is significant as 

approximately one third of individuals 

over the age of 65 experienced at least 

one fall annually.75 Major fall-related 

injuries among older communitydwelling adults are a growing health 

concern within the United States 76 77

because they can have high medical and 

cost implications for the Medicare 

community.78 In 2013, the direct 

medical cost for falls in older adults was 

$34 billion 79 and is projected to 

increase to over $101 billion by 2030 

due to the aging population.80

Evidence from various studies 

indicates that implementing effective 

fall prevention interventions and 

minimizing the impact of falls that do 

occur reduces overall costs, emergency 

department visits, hospital 

readmissions, and overall Medicare 

resource utilization.81 82 83 84 In the 2006 

Home Assessments and Modification 

study, a home visit by an occupational 

therapist or home care worker to 

identify and mitigate potential home 

hazards and risky behavior, resulted in 

a 46 percent reduction in fall rates for 

those receiving the intervention 

compared to controls.85 Overall, 

patients participating in interventions 

experienced improved quality of life 

due to reduced morbidity, improved 

functional ability and mobility, reduced 

number of falls and injurious falls, and 

a decrease in the fear of falling.86 87

Falls also represent a significant cost 

burden to Medicare. Each year, 2.8 

million older people are treated in 

Emergency Departments for fall related 

injuries and over 800,000 require 

hospitalization.88 Adjusted to 2015 

dollars, nationally, direct medical costs 

for nonfatal fall related injuries in older 

adults were over $31.3 billion.89

Additional health care costs (in 2010 

dollars) can range from $3,500 for a fall 

without serious injury to $27,000 for a 


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90Wu S, Keeler EB, Rubenstein LZ, Maglione MA, 

Shekelle PG. A cost-effectiveness analysis of a 

proposed national falls prevention program. Clin 

Geriatr Med. 2010;26(4): 751–66. 

91Orces, C.H. & Alamgir, H. (2014). Trends in fallrelated injuries among older adults treated in 

emergency departments in the USA. Injury 

Prevention, 20: 421–423. 

92Towne, S.D., Ory, M.G., & Smith, M.L. (2014). 

Cost of fall-related hospitalizations among older 

adults: Environmental comparisons from the 2011 

Texas hospital inpatient discharge data. Population 

Health Management, 17(6), 351–356. 

93American Nurses Association (2014, April 9). 

Falls with injury. Retrieved from http://

www.qualityforum.org/QPS/0202. 

fall with a serious injury.90 Between 

1988 and 2005, fractures accounted for 

84 percent of hospitalizations for fallrelated injuries among older adults.91

Researchers evaluated the cost of fallrelated hospitalizations among older 

adults using the 2011 Texas Hospital 

Inpatient Discharge Data and 

determined that the average cost for fallrelated hip fractures was $61,715 for 

individuals 50 and older living in 

metropolitan areas and $55,366 for 

those living nonmetropolitan areas.92

To meet the IMPACT Act provision 

requiring the development of a 

standardized quality measure for the 

domain of Incidence of Major Falls 

(sections 1899B(c)(1)(D) of the Act), we 

proposed the standardized measure, The 

Percent of Residents Experiencing One 

or More Falls with Major Injury (Long 

Stay) (NQF #0674). We noted that this 

quality measure is NQF-endorsed and 

has been successfully implemented in 

the Nursing Home Quality Initiative for 

nursing facility long-stay residents since 

2011, demonstrating the measure is 

feasible, appropriate for assessing PAC 

quality of care, and could be used as a 

platform for standardized quality 

measure development. This quality 

measure is standardized across PAC 

settings and contains items that are 

collected uniformly in each setting’s 

assessment instruments (that is, MDS, 

IRF–PAI, and LCDS). Further, an 

application of the quality measure was 

adopted for use in the LTCH QRP in the 

FY 2014 IPPS/LTCH PPS final rule (78 

FR 50874 through 50877), revised in the 

FY 2015 IPPS/LTCH PPS final rule (79 

FR 50290 through 50291), and adopted 

to fulfill IMPACT Act requirements in 

the FY 2016 IPPS/LTCH PPS final rule 

(80 FR 49736 through 49739). Data 

collection began in April 1, 2016 for 

LTCHs, and October 1, 2016 for SNFs 

and IRFs. 

More information on the NQFendorsed quality measure, the Percent 

of Residents Experiencing One or More 

Falls with Major Injury (Long Stay) 

(NQF #0674) is available at http://

www.qualityforum.org/QPS/0674. 

c. Stakeholder Feedback 

A TEP convened by our measure 

development contractor provided input 

on the technical specifications of an 

application of the quality measure, the 

Percent of Residents Experiencing One 

or More Falls with Major Injury (Long 

Stay) (NQF #0674), including the 

feasibility of implementing the measure 

across PAC settings. The TEP was 

supportive of the implementation of this 

measure across PAC settings and was 

also supportive of our efforts to 

standardize this measure for crosssetting development. More information 

about this TEP can be found at https:// 

www.cms.gov/medicare/qualityinitiatives-patient-assessmentinstruments/post-acute-care-qualityinitiatives/impact-act-of-2014/impactact-downloads-and-videos.html. 

In addition, we solicited public 

comment on this measure from 

September 19, 2016, through October 

14, 2016. Overall, commenters were 

generally supportive of the measure, but 

raised concerns about the attribution 

given that home health clinicians are 

not present in the home at all times and 

recommended risk-adjusting the 

measure. The summary of this public 

comment period can be found at https:// 

www.cms.gov/medicare/qualityinitiatives-patient-assessmentinstruments/post-acute-care-qualityinitiatives/impact-act-of-2014/impactact-downloads-and-videos.html. 

Finally, we presented this measure to 

the NQF-convened MAP on December 

14, 2016. The MAP conditionally 

supported the use of an application of 

the quality measure, the Percent of 

Residents Experiencing One or More 

Falls with Major Injury (Long Stay) 

(NQF #0674) in the HH QRP as a crosssetting quality measure. The MAP 

highlighted the clinical significance of 

falls with major injury, while noting 

potential difficulties in collecting falls 

data and more limited action ability in 

the home health setting. The MAP 

suggested that CMS explore 

stratification of measure rates by referral 

origin when public reporting. More 

information about the MAP’s 

recommendations for this measure is 

available at http://

www.qualityforum.org/Publications/

2017/02/MAP_2017_Considerations_

for_Implementing_Measures_in_

Federal_Programs_-_PAC-LTC.aspx. We 

solicited public comment on the 

stratification of the proposed measure, 

specifically on the measure rates for 

public reporting. The quality measure, 

the Percent of Residents Experiencing 

One or More Falls with Major Injury 

(Long Stay) (NQF #0674) is not 

currently endorsed for the home health 

setting. We reviewed the NQF’s 

consensus endorsed measures and were 

unable to identify any NQF-endorsed 

cross-setting quality measures for that 

setting that are focused on falls with 

major injury. We found one falls-related 

measure in home health titled, 

Multifactor Fall Risk Assessment 

Conducted for All Patients Who Can 

Ambulate (NQF #0537). 

We noted that we are also aware of 

one NQF-endorsed measure, Falls with 

Injury (NQF #0202), which is a measure 

designed for adult acute inpatient and 

rehabilitation patients capturing ‘‘all 

documented patient falls with an injury 

level of minor or greater on eligible unit 

types in a calendar quarter, reported as 

injury falls per 100 days.’’ 93 After 

careful review, we determined that 

these measures are not appropriate to 

meet the IMPACT Act domain of 

incidence of major falls. Specifically— 

• NQF #0202 includes minor injuries 

in the numerator definition. Including 

all falls in an outcome measure could 

result in providers limiting activity for 

individuals at higher risk for falls. 

• NQF #0537 is a process-based 

measure of HHAs’ efforts to assess the 

risk for any fall, but not actual falls. 

• Neither measure is standardized 

across PAC settings. 

We are unaware of any other crosssetting quality measures for falls with 

major injury that have been endorsed or 

adopted by another consensus 

organization for the Home health 

setting. Therefore, based on the 

evidence discussed previously, we 

proposed to adopt the quality measure 

entitled, An Application of the Measure 

Percent of Residents Experiencing One 

or More Falls with Major Injury (Long 

Stay) (NQF #0674), for the HH QRP 

beginning with the CY 2020 HH QRP. 

We noted in the proposed rule that we 

plan to submit the proposed measure to 

the NQF for endorsement consideration 

as soon as it is feasible. 

d. Data Collection 

For purposes of assessment data 

collection, we proposed to add two new 

falls-related items to the OASIS. The 

proposed falls with major injury item 

used to calculate the proposed quality 

measure does not duplicate existing 

items currently collected in the OASIS. 

We proposed to add two standardized 

items to the OASIS for collection at 

EOC, which comprises the Discharge 

from Agency, Death at Home, and 

Transfer to an Inpatient Facility time 


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points: J1800 and J1900. The first item 

(J1800) is a gateway item that asks 

whether the patient has experienced any 

falls since admission/resumption of care 

(prior assessment). If the answer to 

J1800 is yes, the next item (J1900) asks 

for the number of falls with: (a) No 

injury, (b) injury (except major), and (c) 

major injury. The measure is calculated 

using data reported for J1900C (number 

of falls with major injury). This measure 

would be calculated at the time of 

discharge (see 82 FR 35351). For 

technical information about this 

proposed measure, including 

information pertaining to measure 

calculation and the standardized patient 

assessment data element used to 

calculate this measure, we referred 

readers to the document titled, Final 

Specifications for HH QRP Quality 

Measures and Standardized Patient 

Assessment Data, available at https://

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

HHQIQualityMeasures.html. 

We proposed that data for the 

proposed quality measure would be 

collected through the OASIS, which 

HHAs currently submit through the 

QIES ASAP system. We referred readers 

to section V.I.4 of the proposed rule for 

more information on the proposed data 

collection and submission timeline for 

this proposed quality measure. 

We solicited public comments on our 

proposal to adopt an application of the 

quality measure, the Percent of 

Residents Experiencing One or More 

Falls with Major Injury (Long Stay) 

(NQF #0674) beginning with the CY 

2020 HH QRP. 

Comment: A few commenters 

supported the proposed measure, 

Application of Percent of Residents 

Experiencing One or More Falls With 

Major Injury (Long Stay) (NQF #0674), 

noting that it aligned with measures in 

other post-acute care settings. 

Response: We appreciate the 

commenters’ support of the proposed 

measures. 

Comment: Several commenters 

suggested that CMS further refine and 

test Application of Percent of Residents 

Experiencing One or More Falls With 

Major Injury (Long Stay) (NQF #0674), 

to determine HHA setting applicability 

before adopting it for the HH QRP. 

Other commenters recommended that 

we provide training and time for HHAs 

to accommodate the new measures into 

their workflow. One commenter 

recommended that we review the 

impact of new measures on high needs 

beneficiaries. 

Response: This measure is fully 

developed and testing of this measure is 

based on a comprehensive field test of 

the items used to calculate this measure. 

Further, feedback from clinicians 

suggested that the items used to 

calculate this measure are feasible to 

collect in a Home health setting, 

reinforcing the measure testing by CMS 

and their measure contractor. Therefore, 

by way of testing results and consensus 

vetting, we believe that this measure is 

applicable to a home health setting. 

With respect to training, we intend to 

engage in multiple activities including 

updating our manual and conducting 

training sessions, to ensure that HHAs 

understand how to properly report the 

measure. 

Comment: A few commenters 

addressed the administrative burden of 

the measure, specifically focusing on 

the addition of items used in its 

calculation to the OASIS. Specifically, 

one of these commenters encouraged 

CMS to review the overall number of 

OASIS data elements and measures. The 

same commenter noted that HHAs 

already are evaluated on a falls measure, 

‘‘Multifactor Fall Risk Assessment 

Conducted for All Patients Who Can 

Ambulate’’. 

Response: This proposed measure is 

an outcome measure that we are 

adopting to satisfy the measure domain, 

Incidence of Major Falls, required by the 

IMPACT Act. The process measure, 

‘‘Multifactor Fall Risk Assessment 

Conducted for All Patients Who Can 

Ambulate’’, is a measure that assesses 

falls risk rather than the outcome of a 

major fall. That measure is not aligned 

across post-acute care settings and 

therefore does not meet the 

requirements of the IMPACT Act. 

Pertaining to the administrative 

burden, the proposed measure, ‘‘Falls 

with Major Injury,’’ requires a total of 

two items to be added to the OASIS, 

which were considered feasible for 

collection in post-acute care settings. 

We believe these items add minimally 

to the quality reporting burden. 

Comment: Several commenters noted 

that the home health setting is unique 

from facility-based care, making it 

difficult to assess or prevent patient 

falls. Commenters noted that home 

health staff are not with their patients 

around the clock, unlike facility-based 

care, and that patients may refuse or 

decline to follow staff recommendations 

on falls prevention. 

Response: Assessing the incidence of 

major falls, which is associated with 

morbidity, mortality, and high costs, is 

required under the IMPACT Act and is 

also one of our major priorities for 

improving the quality of patient care. In 

order to ensure that this measure is 

appropriate for a home health setting, 

we examined fall risk and prevalence 

among the cohort of home health 

patients by means of an analysis using 

2015 OASIS data. In nearly 32 percent 

of the 5.3 million episodes with relevant 

data, the patient had a history of falls, 

defined as two or more falls, or any fall 

with an injury, in the previous 12 

months. For the more than 6.1 million 

episodes where the patient received a 

multi-factor falls risk assessment using 

a standardized, validated assessment 

tool, the patient was found to have falls 

risk 93 percent of the time. 

Additionally, there were nearly 100,000 

instances documented where a patient 

required emergency care for an injury 

due to a fall. Our environmental scan 

identified evidence-based strategies that 

can and have been applied in the home 

health setting to reduce falls risk. 

Therefore, we believe that a measure of 

this type is important for both providers 

and individuals, to support personcentered care to properly assess for the 

risk of falling accompanied by a major 

injury to support proper care planning. 

In addition to meeting the requirements 

of the IMPACT Act, this measure will 

address the current gap in the HH QRP 

measure set for this type of injurious 

fall. 

Comment: Several commenters 

recommended that this measure be riskadjusted for the purpose of publicreporting, and that unadjusted rates be 

shared with providers via confidential 

feedback only. Commenters additionally 

suggested that there may be unintended 

consequences without risk adjustment 

such that HHAs may be hesitant to 

accept higher falls’ risk patients for fear 

of the financial impact. The commenters 

stated that this may potentially limit the 

value of comparison amongst HHAs. 

According to one of these commenters, 

without risk adjustment, the measure 

could present a distorted correlation 

between the rate of major injuries 

related to falls and the quality of care 

provided by the agency. This will limit 

comparisons among home health 

agencies. Another commenter noted that 

stratifying results for public reporting 

may not be feasible given sample sizes 

and will not be a substitute for riskadjustment. 

Response: While we acknowledge that 

various patient characteristics can 

elevate the risk for falls, falls with major 

injury are considered to be ‘never 

events. A never event is a serious 

reportable event. For that reason, we do 

not believe we should risk adjust the 

proposed measure. Risk adjusting for 

falls with major injury could 

unintentionally lead to insufficient risk 

prevention by the provider. The need 

for risk assessment, based on varying 


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risk factors among residents, does not 

remove the obligation of providers to 

minimize that risk. 

Comment: Many commenters noted 

that the falls measure is not endorsed by 

NQF for the home health setting and 

encouraged CMS to pursue NQF 

endorsement. 

Response: While this measure is not 

currently NQF-endorsed, we recognize 

that the NQF endorsement process is an 

important part of measure development 

and we plan to submit this measure for 

NQF endorsement consideration as soon 

as feasible. 

Final Decision: After consideration of 

the comments received, we are 

finalizing as proposed the measure 

Percent of Residents Experiencing One 

or More Falls with Major Injury for 

adoption in the HH QRP beginning with 

the CY 2020 program year. 

G. HH QRP Quality Measures and 

Measure Concepts Under Consideration 

for Future Years 

We solicited public comment on the 

importance, relevance, appropriateness, 

and applicability of each of the quality 

measures listed in Table 19 for use in 

future years in the HH QRP. 

TABLE 19—HH QRP QUALITY MEASURES UNDER CONSIDERATION FOR FUTURE YEARS

IMPACT Act domain Functional status, cognitive function, and changes in function and cognitive function 

Measures ............................................................ A. Application of NQF #2633—Change in Self-Care Score for Medical Rehabilitation Patients. 

B. Application of NQF #2634—Change in Mobility Score for Medical Rehabilitation Patients. 

C. Application of NQF #2635—Discharge Self-Care Score for Medical Rehabilitation Patients. 

D. Application of NQF #2636—Discharge Mobility Score for Medical Rehabilitation Patients. 

We noted that we are considering four 

measures that will assess a change in 

functional outcomes such as self-care 

and mobility across a HH episode. 

These measures would be standardized 

to measures finalized in other PAC 

quality reporting programs, such as the 

IRF QRP. We solicited feedback on the 

importance, relevance, appropriateness, 

and applicability of these measure 

constructs. 

Based on input from stakeholders, we 

have identified additional concept areas 

for potential future measure 

development for the HH QRP. These 

include claims-based within stay 

potentially preventable hospitalization 

measures. The potentially preventable 

within-stay hospitalization measures 

will look at the percentage of HH 

episodes in which patients were 

admitted to an acute care hospital or 

seen in an emergency department for a 

potentially preventable condition 

during an HH episode. We solicited 

feedback on the importance, relevance, 

appropriateness, and applicability of 

these measure constructs. 

In alignment with the requirements of 

the IMPACT Act to develop quality 

measures and standardize data for 

comparative purposes, we believe that 

evaluating outcomes across the postacute settings using standardized data is 

an important priority. Therefore, in 

addition to proposing a process-based 

measure for the domain of ‘‘Functional 

status, cognitive function, and changes 

in function and cognitive function’’, 

included in the proposed rule, we noted 

that we also intended to develop 

outcomes-based quality measures, 

including functional status and other 

quality outcome measures to further 

satisfy this domain. 

Comment: Three commenters 

expressed general support for the 

measures under consideration for future 

years. These commenters stated that 

measures should be tested in the home 

health setting prior to being finalized, 

highlighting that the home setting is 

different than other standardized 

institutional care settings and presents 

unique challenges to caregivers and 

beneficiaries. One of the commenters 

stated that the measurement domains 

are critically important in the home 

health setting and highly relevant, 

especially for patients whose goal is 

improvement, adding that the relevance, 

appropriateness, and applicability can 

only be discussed after validity and 

reliability testing is completed in the 

home health setting. Another 

commenter suggested leveraging 

changes in quality measures as an effort 

to safeguard the delivery of therapy 

services and ensure accountability on 

the part of the provider. 

Response: We appreciate the 

recommendations and comments. We 

agree that all future measures should be 

adequately tested and found reliable for 

the home health setting. 

Comment: Commenters supported the 

development of functional status 

measures. MedPAC also supported 

measures that cut-across sectors, as long 

as they are standardized, and noted they 

would support the self-care and 

mobility measure concepts for HHAs 

based on the IRF measure specifications, 

as long as CMS ensured that the 

measures are aligned across PAC 

settings. A few commenters 

recommended that functional measures 

may assess for beneficiaries who do not 

have the goal of improvement. Other 

commenters noted that stabilization 

measures are appropriate for quality 

improvement initiatives as they closely 

align with the goal of HH services to 

help patients maintain their current 

level of function or when possible to 

improve it. Another commenter 

suggested closely monitoring functional 

status measures to determine the impact 

of other reforms, such as changes to the 

payment approaches, to determine the 

impact of these changes on patient 

outcomes. 

Response: We appreciate the 

comments from MedPAC and others. 

We agree that the maintenance of 

function and avoidance or reduction in 

functional decline are appropriate goals 

for HH patients. We appreciate all 

recommendations and will take these 

comments into consideration as we 

consider measures for future 

rulemaking. 

Comment: Three commenters 

specifically supported the potentially 

preventable within-stay hospitalization 

measure. MedPAC supported the 

development of a claims-based, 

potentially preventable hospitalization 

measure, adding that measuring 

potentially preventable hospitalizations 

holds providers accountable only for 

conditions that generally could have 

been managed by the HHA. 

Response: We appreciate the 

comments from MedPAC and others 

pertaining to the potentially preventable 

within-stay hospitalization measure 

under consideration for future 

implementation in the HH QRP. We 

note that appropriately assessing 

hospital readmissions as an outcome is 

important, acknowledge the importance 

of avoiding unintended consequences 

that may arise from such assessments, 

and will take into consideration the 

commenters’ recommendations. 

Comment: Commenters had 

suggestions for other measures that 

could be added to the HH QRP. 

Response: We appreciate the 

commenters’ recommendations and will 


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94Casey, G. (2013). ‘‘Pressure ulcers reflect 

quality of nursing care.’’ Nurs N Z 19(10): 20–24. 

95 Gorzoni, M.L. and S.L. Pires (2011). ‘‘Deaths in 

nursing homes.’’ Rev Assoc Med Bras 57(3): 327– 

331. 

96Thomas, J.M., et al. (2013). ‘‘Systematic review: 

Health-related characteristics of elderly 

hospitalized adults and nursing home residents 

associated with short-term mortality.’’ J Am Geriatr 

Soc 61(6): 902–911. 

97White-Chu, E.F., et al. (2011). ‘‘Pressure ulcers 

in long-term care.’’ Clin Geriatr Med 27(2): 241–258. 

98Bates-Jensen BM. Quality indicators for 

prevention and management of pressure ulcers in 

vulnerable elders. Ann Int Med. 2001;135 (8 Part 2), 

744–51. 

99Bennet, G, Dealy, C Posnett, J (2004). The cost 

of pressure ulcers in the UK, Age and Aging, 

33(3):230–235. 

100Saliba, D., & Buchanan, J. (2008, April). 

Development and validation of a revised nursing 

home assessment tool: MDS 3.0. Contract No. 500– 

00–0027/Task Order #2. Santa Monica, CA: Rand 

Corporation. Retrieved from http://

www.cms.hhs.gov/NursingHomeQualityInits/

Downloads/MDS30FinalReport.pdf. 

101Landis, R., & Koch, G. (1977, March). The 

measurement of observer agreement for categorical 

data. Biometrics 33(1), 159–174. 

take them into account in our future 

measure development work. 

1. IMPACT Act Implementation Update 

As a result of the input and 

suggestions provided by technical 

experts at the TEPs held by our measure 

developer, we noted in the proposed 

rule that we are engaging in additional 

development work for two measures 

that will satisfy section 1899B(c)(1)(E) of 

the Act, including performing 

additional testing. We noted that we 

intended to specify these measures 

under section 1899B(c)(1)(E) of the Act 

no later than January 1, 2019 and we 

intend to propose to adopt them for the 

CY 2021 HH QRP, with data collection 

beginning on or about January 1, 2020. 

We did not receive any comments on 

this update. 

H. Standardized Patient Assessment 

Data 

1. Standardized Patient Assessment 

Data Reporting for the CY 2019 HH QRP 

Section 1895(b)(3)(B)(v)(IV)(bb) of the 

Act requires that for calendar years 

beginning on or after January 1, 2019, 

HHAs submit to the Secretary 

standardized patient assessment data 

required under section 1899B(b)(1) of 

the Act. 

In the CY 2018 HH PPS proposed rule 

(82 FR 35351) we proposed that the 

current pressure ulcer measure, 

Application of Percent of Residents or 

Patients with Pressure Ulcers That Are 

New or Worsened (Short Stay) (NQF 

#0678), be replaced with the proposed 

pressure ulcer measure, Changes in Skin 

Integrity Post-Acute Care: Pressure 

Ulcer/Injury, beginning with the CY 

2020 HH QRP. The current pressure 

ulcer measure will remain in the HH 

QRP until that time. Accordingly, for 

the requirement that HHAs report 

standardized patient assessment data for 

the CY 2019 HH QRP, we proposed that 

the data elements used to calculate that 

measure meet the definition of 

standardized patient assessment data for 

medical conditions and co-morbidities 

under section 1899B(b)(1)(B)(iv) of the 

Act, and that the successful reporting of 

that data under section 

1895(b)(3)(b)(v)(IV)(aa) of the Act for the 

beginning of the HH episode (for 

example, HH start of care/resumption of 

care), as well as the end of the HH 

episode (discharges) occurring during 

the first two quarters of CY 2018 will 

also satisfy the requirement to report 

standardized patient assessment data 

beginning with the CY 2019 HH QRP. 

The collection of assessment data 

pertaining to skin integrity, specifically 

pressure related wounds, is important 

for multiple reasons. Clinical decision 

making, care planning, and quality 

improvement all depend on reliable 

assessment data collection. Pressure 

related wounds represent poor 

outcomes, are a serious medical 

condition that can result in death and 

disability, are debilitating and painful, 

and are often avoidable.94 95 96 97 98 99

Pressure related wounds are considered 

healthcare acquired conditions. 

As we noted, the data elements 

needed to calculate the current pressure 

ulcer measure are already included on 

the OASIS data set and reported by 

HHAs, and exhibit validity and 

reliability for use across PAC providers. 

Item reliability for these data elements 

was also tested for the nursing home 

setting during implementation of MDS 

3.0. Testing results are from the RAND 

Development and Validation of MDS 3.0 

project.100 The RAND pilot test of the 

MDS 3.0 data elements showed good 

reliability and are applicable to the 

OASIS because the data elements tested 

are the same as those used in the OASIS 

Data Set. Across the pressure ulcer data 

elements, the average gold-standard 

nurse to gold-standard nurse kappa 

statistic was 0.905. The average goldstandard nurse to facility-nurse kappa 

statistic was 0.937. Data elements used 

to risk adjust this quality measure were 

also tested under this same pilot test, 

and the gold-standard to gold-standard 

kappa statistic, or percent agreement 

(where kappa statistic not available), 

ranged from 0.91 to 0.99 for these data 

elements. These kappa scores indicate 

‘‘almost perfect’’ agreement using the 

Landis and Koch standard for strength 

of agreement.101

The data elements used to calculate 

the current pressure ulcer measure 

received public comment on several 

occasions, including when that measure 

was proposed in the CY 2016 HH PPS 

(80 FR 68623). Further, they were 

discussed in the past by TEPs held by 

our measure development contractor on 

June 13 and November 15, 2013, and 

recently by a TEP on July 18, 2016. TEP 

members supported the measure and its 

cross-setting use in PAC. The report, 

Technical Expert Panel Summary 

Report: Refinement of the Percent of 

Patients or Residents with Pressure 

Ulcers that are New or Worsened (ShortStay) (NQF #0678) Quality Measure for 

Skilled Nursing Facilities (SNFs), 

Inpatient Rehabilitation Facilities 

(HHAs), Long-Term Care Hospitals 

(LTCHs), and Home Health Agencies 

(HHAs), is available at and https://

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014/

IMPACT-Act-Downloads-andVideos.html. 

Comment: Some commenters 

supported reporting the data elements 

already implemented in the HH QRP to 

fulfill the requirement to report 

standardized patient assessment data for 

the CY 2019 HH QRP. Specifically, the 

commenters supported the use of data 

elements used in calculation of the 

Percent of Residents or Patients with 

Pressure Ulcers That Are New or 

Worsened (Short Stay) (NQF #0678) to 

fulfill this requirement. However, one 

commenter recommended that CMS 

implement such measures after public 

deliberation and discussion. A 

commenter suggested that CMS adopt 

the same policies in this CY 2018 HH 

PPS final rule as it adopted for IRFs, 

SNFs and LTCHs in the other final rules 

issued this year. 

Response: We appreciate the support 

and where possible we have aligned 

with the other settings. We affirm that 

as we continue to implement measures, 

such as the pressure ulcer quality 

measure, we will continue to engage the 

public both during the measure 

development phase and through the 

rulemaking process. 

Final Decision: After consideration of 

the public comments received, we are 

finalizing as proposed that the data 

elements currently reported by HHAs to 

calculate the current measure, Percent 

of Residents or Patients with Pressure 

Ulcers That Are New or Worsened 

(Short Stay) (NQF #0678),to meet the 

definition of standardized patient 

assessment data with respect to medical 

conditions and co-morbidities under 

section 1899B(b)(1)(B)(iv) of the Act, 


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and that the successful reporting of that 

data under section 

1895(b)(3)(B)(v)(IV)(aa) of the Act will 

also satisfy the requirement to report 

standardized patient assessment data 

under section 1895(b)(3)(B)(v)(IV)(bb) of 

the Act beginning with the CY 2019 HH 

QRP. 

2. Standardized Patient Assessment 

Data Reporting Beginning With the CY 

2020 HH QRP 

In the CY 2018 HH PPS proposed rule 

(82 FR 35355 through 35371), we 

described our proposals for the 

reporting of standardized patient 

assessment data by HHAs beginning 

with the CY 2020 HH QRP. LTCHs, 

IRFs, and SNFs are also required to 

report standardized patient assessment 

data through their applicable PAC 

assessment instruments, and they do so 

by responding to identical assessment 

questions developed for their respective 

settings using an identical set of 

response options (which incorporate an 

identical set of definitions and 

standards). We proposed that HHAs will 

be required to report these data at 

admission (SOC/ROC) and discharge 

beginning on January 1, 2019, with the 

exception of three data elements (Brief 

Interview of Mental Status (BIMS), 

Hearing, and Vision) that will be 

required at SOC/ROC only. Following 

the initial reporting year (which will be 

based on 6 months of data) for the CY 

2020 HH QRP, subsequent years for the 

HH QRP would be based on a full 

calendar year of such data reporting. 

In selecting the data elements, we 

carefully weighed the balance of burden 

in assessment-based data collection and 

aimed to minimize additional burden 

through the utilization of existing data 

in the assessment instruments. We also 

noted that the patient and resident 

assessment instruments are considered 

part of the medical record and sought 

the inclusion of data elements relevant 

to patient care. 

We also took into consideration the 

following factors for each data element: 

overall clinical relevance; ability to 

support clinical decisions, care 

planning, and interoperable exchange to 

facilitate care coordination during 

transitions in care; and the ability to 

capture medical complexity and risk 

factors that can inform both payment 

and quality. In addition, the data 

elements had to have strong scientific 

reliability and validity; be meaningful 

enough to inform longitudinal analysis 

by providers; had to have received 

general consensus agreement for its 

usability; and had to have the ability to 

collect such data once but support 

multiple uses. Further, to inform the 

final set of data elements for proposal, 

we took into account technical and 

clinical subject matter expert review, 

public comment, and consensus input 

in which such principles were applied. 

We received several comments related 

to the reporting of the standardized 

patient assessment data. 

Comment: Many commenters 

expressed significant concerns with 

respect to our standardized patient 

assessment data proposals. Several 

commenters stated that the new 

standardized patient assessment data 

reporting requirements will impose 

significant burden on providers, given 

the volume of new standardized patient 

assessment data elements that we 

proposed to add to the OASIS. Several 

commenters noted that the addition of 

the proposed standardized patient 

assessment data elements will require 

hiring more staff, retraining staff on 

revised questions or coding guidance, 

and reconfiguring internal databases 

and EHRs. Other commenters expressed 

concerns about the gradual but 

significant past and future expansion of 

the OASIS through the addition of 

standardized patient assessment data 

elements and quality measures, noting 

the challenge of coping with ongoing 

additions and changes. 

Several commenters expressed 

concern related to the implementation 

timeline in the proposed rule. Several 

commenters noted that CMS had not yet 

provided sufficient specifications or 

educational materials to support 

implementation of the new patient 

assessments in the proposed timeline. A 

few commenters urged CMS to delay the 

reporting of new standardized patient 

assessment data elements and to 

carefully assess whether all of the 

proposed standardized patient 

assessment data elements are necessary 

under the IMPACT Act. 

Response: We understand the 

concerns raised by commenters that 

finalizing our standardized patient 

assessment data proposals will require 

HHAs to spend a significant amount of 

resources preparing to report the data, 

including updating relevant protocols 

and systems and training appropriate 

staff. We also recognize that we can 

meet our obligation to require the 

reporting of standardized patient 

assessment data for the categories 

described in section 1899B(b)(1)(B) of 

the Act while simultaneously being 

responsive to these concerns. Therefore, 

after consideration of the public 

comments we received on these issues, 

we have decided that at this time, we 

will not finalize the standardized 

patient assessment data elements we 

proposed for three of the five categories 

under section 1899B(b)(1)(B) of the Act: 

Cognitive Function and Mental Status; 

Special Services, Treatments, and 

Interventions; and Impairments. 

Although we believe that the 

proposed standardized patient 

assessment data elements would 

promote transparency around quality of 

care and price as we continue to explore 

reforms to the PAC payment system, the 

data elements that we proposed for each 

of these categories would have imposed 

a new reporting burden on HHAs. We 

agree that it would be useful to evaluate 

further how to best identify the 

standardized patient assessment data 

that would satisfy each of these 

categories; would be most appropriate 

for our intended purposes including 

payment and measure standardization; 

and can be reported by HHAs in the 

least burdensome manner. As part of 

this effort, we intend to conduct a 

national field test that allows for 

stakeholder feedback and to consider 

how to maximize the time HHAs have 

to prepare for the reporting of 

standardized patient assessment data in 

these categories. We intend to make new 

proposals for the categories described in 

sections 1899B(b)(1)(B)(ii), (iii) and (v) 

of the Act no later than in the CY 2020 

HH PPS proposed rule. 

In this final rule, we are finalizing the 

standardized patient assessment data 

elements that we proposed to adopt for 

the IMPACT Act categories of 

Functional Status and Medical 

Conditions and Co-Morbidities. Unlike 

the standardized patient assessment 

data that we are not finalizing, the 

standardized patient assessment data 

that we proposed for Medical 

Conditions Co-Morbidities category is 

already required to calculate the Percent 

of Residents or Patients with Pressure 

Ulcers That Are New or Worsened (NQF 

#0678) quality measure, and the 

Changes in Skin Integrity Post-Acute 

Care: Pressure Ulcer/Injury quality 

measure. We are finalizing the quality 

measure, Application of Percent of 

Long-Term Care Hospital Patients with 

an Admission and Discharge Functional 

Assessment and a Care Plan That 

Addresses Function (NQF #2631), and 

the additional standardized patient 

assessment data elements in Section GG 

to satisfy the category of Functional 

Status. 

Comment: Some commenters 

expressed support for the adoption of 

standardized patient assessment data 

elements. Several of these commenters 

expressed support for standardizing the 

definitions as well as the 

implementation of the data collection 

effort. A few commenters also supported 

CMS’ goal of standardizing the 


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questions and responses across all PAC 

settings. Another commenter approved 

of the efforts CMS is making to engage 

the PAC community on the 

implementation of the IMPACT Act, 

including holding Special Open Door 

Forums and Medicare Learning Network 

(MLN) Calls to communicate with 

providers about expectations/timelines 

over five years. MedPAC recognized the 

value of and need for a unified patient 

assessment system for PAC as part of a 

potential unified payment system for 

PAC. 

Response: We appreciate the support. 

Comment: A few commenters stated 

that there is insufficient evidence 

demonstrating the reliability and 

validity of the proposed standardized 

patient assessment data elements. 

Several commenters stated that the 

expanded standardized patient 

assessment data reporting requirements 

have not yet been adequately tested to 

ensure they collect accurate and useful 

data in the HHA setting. 

Response: Our standardized patient 

assessment data elements were selected 

based on a rigorous multistage process 

described in the CY 2018 HH PPS 

proposed rule (82 FR 35344). In 

addition, we believe that the PAC PRD 

testing of many of these data elements 

provides good evidence from a large, 

national sample of patients and 

residents in PAC settings to support the 

use of these standardized patient 

assessment data elements in and across 

PAC settings. However, as previously 

explained, we have decided at this time 

not to finalize the proposals for three of 

the five categories under section 

1899B(b)(1)(B) of the Act: Cognitive 

Function and Mental Status; Special 

Services, Treatments, and Interventions; 

and Impairments. Prior to making new 

proposals for these categories, we intend 

to conduct additional testing to ensure 

that the standardized patient assessment 

data elements we select are reliable, 

valid and appropriate for their intended 

use. 

Comment: MedPAC suggested that 

CMS should be mindful that some data 

elements, when used for risk 

adjustment, may be susceptible to 

provider manipulation. MedPAC is 

concerned about the proposed elements 

such as oxygen therapy, intravenous 

medications, and nutritional approaches 

that may incentivize increased use of 

services. MedPAC supported the 

inclusion of these care items when they 

are tied to medical necessity, such as in 

previous MedPAC work, where patients 

were counted as using oxygen services 

only if they have diagnoses that 

typically require the use of oxygen. 

MedPAC encouraged CMS to take a 

similar approach in measuring use of 

services that are especially 

discretionary. For some data elements, 

MedPAC suggested that CMS consider 

requiring a physician to attest that the 

reported service was reasonable and 

necessary and include a statement 

adjacent to the signature line warning 

that filing a false claim is subject to 

treble damages under the False Claims 

Act. 

Response: We thank MedPAC for their 

support of the standardized patient 

assessment data elements that are 

associated with medical necessity. We 

appreciate their suggestions to mitigate 

the potential for false data submission 

and the unintended consequence of use 

of services that are not medically 

indicated. 

Comment: While supporting the 

overall concept of standardization 

across PAC settings, several commenters 

strongly believed that the home health 

setting is different than institutional 

settings and urged CMS to consider this. 

One of these commenters encouraged 

CMS to perform testing specifically in 

the home health setting. Another 

commenter was concerned about the use 

of some data elements because they 

were not designed for the home health 

setting and require specialized training 

to accurately administer. Several 

commenters emphasized the importance 

of risk adjustment, with some stating 

that effective risk adjustment will be an 

essential policy feature for home health 

agencies to distinguish how patients 

and data collection in non-standardized 

settings such as the beneficiary’s home 

differ from institutional settings. 

Response: We acknowledge that the 

four PAC provider types each have 

unique challenges and provide unique 

services and appreciate the commenters’ 

concerns specific to the home health 

setting and the potential variation in 

services and populations. Because of 

this, we conducted a thorough process 

of phased testing and stakeholder 

consensus to ensure we considered 

items that are aligned across PAC 

settings and are relevant to and feasible 

in each setting. However, for the reasons 

previously explained, we have decided 

at this time not to finalize the 

standardized patient assessment data 

elements we proposed for three of the 

five categories under section 

1899B(b)(1)(B) of the Act. 

A full discussion of the standardized 

patient assessment data elements that 

we proposed to adopt for the categories 

described in sections 1899B(b)(1)(B)(ii), 

(iii) and (v) of the Act can be found in 

the CY 2018 HH PPS proposed rule (82 

FR 35355 through 35371). In light of our 

decision not to finalize our proposals 

with respect to these categories, we are 

not going to address in this final rule the 

specific technical comments that we 

received on these proposed 

standardized patient assessment data 

elements. However, we appreciate the 

many technical comments we did 

receive specific to each of these data 

elements, and we will take them into 

consideration as we develop new 

proposals for these categories. In this 

section, we discuss the comments we 

received specific to the standardized 

patient assessment data we proposed to 

adopt and are finalizing in this final 

rule, for the categories of Functional 

Status and Medical Conditions and CoMorbidities. 

3. Standardized Patient Assessment 

Data by Category 

a. Functional Status Data 

We proposed that the data elements 

that will be reported by HHAs to 

calculate the measure, Application of 

Percent of Long-Term Care Hospital 

Patients with an Admission and 

Discharge Functional Assessment and a 

Care Plan That Addresses Function 

(NQF #2631), as described in section 

V.F.2 of the proposed rule will also 

meet the definition of standardized 

patient assessment data for functional 

status under section 1899B(b)(1)(B)(i) of 

the Act, and that the successful 

reporting of that data under section 

1895(b)(3)(B)(v)(IV)(aa) of the Act will 

also satisfy the requirement to report 

standardized patient assessment data 

under section 1895(b)(3)(B)(v)(IV)(bb) of 

the Act. Details on the data used to 

calculate this measure is discussed in 

section V.F.2. of this final rule. 

To further satisfy the requirements 

under section 1899B(b)(1)(B)(i) of the 

Act and specifically our efforts to 

achieve standardized patient assessment 

data pertaining to functional status, 

such as mobility and self-care at 

admission to a PAC provider and before 

discharge from a PAC provider, we also 

proposed to adopt the functional status 

data elements that specifically address 

mobility and self-care as provided in the 

Act. We noted that these data elements 

were also used to calculate the function 

outcome measures implemented and/or 

proposed for implementation in three 

other post-acute quality reporting 

programs to which the IMPACT Act 

applies (Application of NQF #2633— 

Change in Self-Care Score for Medical 

Rehabilitation Patients; Application of 

NQF #2634—Change in Mobility Score 

for Medical Rehabilitation Patients; 

Application of NQF #2635—Discharge 

Self-Care Score for Medical 

Rehabilitation Patients; and Application 


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of NQF #2636—Discharge Mobility 

Score for Medical Rehabilitation 

Patients). 

To achieve standardization, we noted 

that we have implemented such data 

elements, or sub-sets of the items, into 

the other post-acute care patient/

resident assessment instruments and we 

proposed that they also meet the 

definition of standardized patient 

assessment data for functional status 

under section 1899B(b)(1)(B)(i) of the 

Act, and that the successful reporting of 

such data under section 

1895(b)(3)(B)(v)(IV)(aa) of the Act will 

also satisfy the requirement to report 

standardized patient assessment data 

under section 1895(b)(3)(B)(v)(IV)(bb) of 

the Act. These data elements currently 

are collected in the Section GG: 

Functional Abilities and Goals located 

in current versions of the MDS and the 

IRF–PAI assessment instruments. 

As previously described, the patient 

assessment data that assess for 

functional status are from the CARE 

Item Set. They were specifically 

developed for cross-setting application 

and are the result of consensus building 

and public input. Further, we received 

public comment and input on these 

patient assessment data. Their reliability 

and validity testing were conducted as 

part of CMS’ Post-Acute Care Payment 

Reform Demonstration, and we 

concluded that the functional status 

items have acceptable reliability and 

validity. We referred the reader to 

section V.F.2 of the proposed rule for a 

full description of the CARE Item Set 

and description of the testing 

methodology and results that are 

available in several reports. For more 

information about this quality measure 

and the data elements used to calculate 

it, we referred readers to the FY 2016 

IPPS/LTCH PPS final rule (80 FR 49739 

through 49747), the FY 2016 IRF PPS 

final rule (80 FR 47100 through 47111), 

and the FY 2016 SNF PPS final rule (80 

FR 46444 through 46453). 

Therefore, we proposed to adopt the 

functional status data elements for the 

CY 2020 HH QRP, requiring HHAs to 

report these data starting on January 1, 

2019. We noted that this proposal 

would align with the required reporting 

timeframe for the CY 2020 HH QRP. 

Following the initial 2 quarters of 

reporting for the CY 2020 HH QRP, we 

proposed that for subsequent years for 

the HH QRP, the reporting of 

standardized patient assessment data 

would be based on 12 months of data 

reporting beginning with July 1, 2019, 

through June 30, 2020 for the CY 2021 

HH QRP. 

Comment: Several commenters, 

including MedPAC, supported the 

collection of standardized patient 

assessment data across PAC settings. 

Some commenters specifically 

addressed support for CMS’ proposal 

that data elements submitted to CMS to 

calculate the measure, Application of 

Percent of Long-Term Care Hospital 

Patients with an Admission and 

Discharge Functional Assessment and a 

Care Plan that Addresses Function (NQF 

#2631), would also satisfy the 

requirement to report standardized 

patient assessment data elements under 

section 1899B(b)(1)(B)(i) of the Act 

addressing functional status, such as 

mobility and self-care at admission to a 

PAC provider and before discharge from 

a PAC provider. 

Response: We appreciate the 

commenters’ support. 

Comment: A commenter suggested 

that CMS use the functional assessment 

item, GG0170C: Lying to sitting on the 

side of bed for purposes of 

standardization. 

Response: We do not believe that 

collecting only GG170C would be 

sufficient for purposes of collecting 

standardized function data. We need a 

larger subset of Section GG items to 

calculate one of the measures that we 

are finalizing in this final rule, 

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), 

which is already finalized for SNFs, 

LTCHs and IRFs. Section GG in its 

entirety also meets the definition of 

standardized patient assessment data 

with respect to function because it is 

standardized across the four PAC 

settings. If we did not collect Section 

GG in its entirety from HHAs, we would 

be collecting a different set of function 

items from HHAs than we collect from 

other PAC provider types. 

Final Decision: After consideration of 

the public comments received, we are 

finalizing that the data elements in 

Section GG: Functional Abilities and 

Goals meet the definition of 

standardized patient assessment data 

elements for functional status under 

section 1899B(b)(1)(B)(i) of the Act, 

specifically those Section GG 

standardized patient assessment data 

elements that are used in the quality 

measure, ‘‘Percent of Long-Term Care 

Hospital Patients with an Admission 

and Discharge Functional Assessment 

and a Care Plan that Addresses Function 

(NQF #2631)’’, and the additional 

standardized functional status data 

elements in Section GG. We note that 

Section GG includes item GG170Q, 

which we inadvertently omitted in the 

specifications that accompanied the CY 

2018 HH PPS proposed rule. The 

Section GG data elements can be found 

in the Finalized Specifications for HH 

QRP Quality Measures and 

Standardized Patient Assessment Data 

Elements document available at: https:// 

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

HHQIQualityMeasures.html. We are 

also finalizing that the data elements 

needed to calculate the measure, 

Application of Percent of Long-Term 

Care Hospital Patients with an 

Admission and Discharge Functional 

Assessment and a Care Plan That 

Addresses Function (NQF #2631), meet 

the definition of standardized patient 

assessment data elements for functional 

status under section 1899B(b)(1)(B)(i) of 

the Act, and that the successful 

reporting of that data under section 

1895(b)(3)(B)(v)(IV)(aa) of the Act will 

also satisfy the requirement to report 

standardized patient assessment data 

elements under section 

1895(b)(3)(B)(v)(IV)(bb) of the Act. 

b. Medical Condition and Comorbidity 

Data 

We proposed that the data elements 

needed to calculate the current measure, 

Percent of Residents or Patients with 

Pressure Ulcers That Are New or 

Worsened (Short Stay) (NQF #0678), 

and that the proposed measure, Changes 

in Skin Integrity Post-Acute Care: 

Pressure Ulcer/Injury, meet the 

definition of standardized patient 

assessment data element with respect to 

medical conditions and co-morbidities 

under section 1899B(b)(1)(B)(iv) of the 

Act, and that the successful reporting of 

that data under section 

1895(b)(3)(B)(v)(IV)(aa) of the Act will 

also satisfy the requirement to report 

standardized patient assessment data 

under section 1895(b)(3)(B)(v)(IV)(bb) of 

the Act. 

‘‘Medical conditions and comorbidities’’ and the conditions 

addressed in the standardized 

assessment patient data elements used 

in the calculation and risk adjustment of 

these measures, that is, the presence of 

pressure ulcers, diabetes, incontinence, 

peripheral vascular disease or 

peripheral arterial disease, mobility, as 

well as low body mass index (BMI), are 

all health-related conditions that 

indicate medical complexity that can be 

indicative of underlying disease severity 

and other comorbidities. 

Specifically, the data elements used 

in the measure are important for care 

planning and provide information 

pertaining to medical complexity. 

Pressure ulcers are serious wounds 

representing poor outcomes, and can 


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result in sepsis and death. Assessing 

skin condition, care planning for 

pressure ulcer prevention and healing, 

and informing providers about their 

presence in patient transitions of care 

are a customary and best practice. 

Venous and arterial disease and diabetes 

are associated with insufficient low 

blood flow, which may increase the risk 

of tissue damage. These diseases 

commonly are indicators of factors that 

may place individuals at risk for 

pressure ulcer development and are 

therefore important for care planning. 

Low BMI, which may be an indicator of 

underlying disease severity, may be 

associated with loss of fat and muscle, 

resulting in potential risk for pressure 

ulcers due to shearing. Bowel 

incontinence, and the possible 

maceration to the skin associated, can 

lead to higher risk for pressure ulcers. 

In addition, the bacteria associated with 

bowel incontinence can complicate 

current wounds and cause local 

infection. Mobility is an indicator of 

impairment or reduction in mobility 

and movement which is a major risk 

factor for the development of pressure 

ulcers. These data elements are 

important for care planning, transitions 

in services and identifying medical 

complexities. 

Comment: Commenters supported our 

proposal to use data elements already 

implemented in the HH QRP to satisfy 

the requirement to report standardized 

patient assessment data. 

Response: We appreciate the support. 

Final decision: After consideration of 

the public comments received, we are 

finalizing as proposed that the data 

elements currently reported by HHAs to 

calculate the current measure, Percent 

of Residents or Patients with Pressure 

Ulcers That Are New or Worsened 

(Short Stay) (NQF #0678), and the 

finalized measure, Changes in Skin 

Integrity Post-Acute Care: Pressure 

Ulcer/Injury, meet the definition of 

standardized patient assessment data for 

medical conditions and co-morbidities 

under section 1899B(b)(1)(B)(iv) of the 

Act, and that the successful reporting of 

that data under section 

1895(b)(3)(B)(v)(IV)(aa) of the Act will 

also satisfy the requirement to report 

standardized patient assessment data 

under section 1895(b)(3)(B)(v)(IV)(bb) of 

the Act. 

We note that for purposes of meeting 

the requirements of the CY 2020 HH 

QRP, HHAs will be required to report 

the data elements needed to calculate 

the current pressure ulcer measure for 

the last two quarters of CY 2018 (July– 

December) and the data elements 

needed to calculate the updated 

pressure ulcer measure for the first two 

quarters of CY 2019 (January–June). 

I. Form, Manner, and Timing of Data 

Submission Under the HH QRP 

1. Start Date for Reporting Standardized 

Patient Assessment Data by New HHAs 

In the CY 2016 HH PPS final rule (80 

FR 68703 through 68706), we adopted 

timing for new HHAs to begin reporting 

data on quality measures under the HH 

QRP. In the CY 2018 HH PPS proposed 

rule (82 FR 35371), we proposed that 

new HHAs would be required to begin 

reporting standardized patient 

assessment data on the same schedule. 

Comment: One commenter supported 

our proposed policy to require that new 

HHAs begin reporting standardized 

patient assessment data on the same 

schedule that they are required to begin 

reporting data on quality measures. 

Response: We thank the commenter 

for the support. 

Final Decision: After consideration of 

the comments we received, we are 

finalizing our proposal that new HHAs 

will be required to begin reporting 

standardized patient assessment data on 

the same schedule that they are 

currently required to begin reporting 

other quality data under the HH QRP. 

2. Mechanism for Reporting 

Standardized Patient Assessment Data 

Beginning With the CY 2019 HH QRP 

Under our current policy, HHAs 

report data by completing applicable 

sections of the OASIS, and submitting 

the OASIS to CMS through the QIES, 

ASAP system. For more information on 

HH QRP reporting through the QIES 

ASAP system, we referred readers to 

https://www.qtso.com/index.php. In 

addition to the data currently submitted 

on quality measures as previously 

finalized and described in Table 18 of 

this rule, in the CY 2018 HH PPS 

proposed rule (82 FR 35372), we 

proposed that HHAs would be required 

to begin submitting the proposed 

standardized patient assessment data for 

HHA Medicare and Medicaid quality 

episodes that begin or end on or after 

January 1, 2019 using the OASIS. 

Further, we proposed that all 

standardized patient assessment data 

elements would be collected at SOC/

ROC using the OASIS item set, and all 

except the Brief Interview for Mental 

Status (BIMS), Hearing, and Vision data 

elements are or would be collected at 

discharge using the OASIS item set. 

Details on the modifications and 

assessment collection for the OASIS for 

the proposed standardized data are 

available at https://www.cms.gov/

Medicare/Quality-Initiatives-PatientAssessment-Instruments/

HomeHealthQualityInits/

HHQIQualityMeasures.html. 

We invited public comment on these 

proposals. 

Comment: We received a comment in 

support of the proposed mechanisms for 

reporting standardized patient 

assessment in the same manner as the 

quality measure data for assessment 

based data beginning with the CY 2019 

HH QRP. 

Response: We thank the commenter 

for its support. 

Final Decision: After consideration of 

the public comment received, we are 

finalizing our policy as proposed to use 

the same data reporting mechanism for 

the submission of the standardized 

patient assessment data elements that is 

already used for reporting quality 

measure data used in the HH QRP 

beginning with the CY 2019 HH QRP. 

3. Schedule for Reporting Standardized 

Patient Assessment Data Beginning 

With the CY 2019 HH QRP 

In the CY 2018 HH PPS proposed rule 

(82 FR 35372) we proposed to apply our 

current schedule for the reporting of 

measure data to the reporting of 

standardized patient assessment data, 

beginning with the CY 2019 HH QRP. 

Under that policy, except for the first 

program year for which a measure is 

adopted, HHAs must report data on 

measures for HHA Medicare and 

Medicaid quality episodes that occur 

during the 12-month period (between 

July 1 and June 30) that applies to the 

program year. For the first program year 

for which a measure is adopted, HHAs 

are only required to report data on HHA 

Medicare and Medicaid quality episodes 

that begin on or after January 1 and end 

up to and including June 30 of the 

calendar year that applies to that 

program year. For example, for the CY 

2019 HH QRP, data on measures 

adopted for earlier program years must 

be reported for all HHA Medicare and 

Medicaid quality episodes that begin on 

or after July 1, 2017, and end on or 

before June 30, 2018. However, data on 

new measures adopted for the first time 

for the CY 2019 HH QRP program year 

must only be reported for HHA 

Medicare and Medicaid quality episodes 

that begin or end during the first two 

quarters of CY 2018. Tables 20 and 21 

illustrate this policy and its proposed 

application to the reporting of 

standardized patient assessment data, 

using CY 2019 and CY 2020 as 

examples. 


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TABLE 20—SUMMARY ILLUSTRATION OF INITIAL REPORTING FOR NEWLY ADOPTED MEASURES AND PROPOSED

STANDARDIZED PATIENT ASSESSMENT DATA REPORTING USING CY Q1 AND Q2 DATA FOR THE HH QRP * 

Proposed data collection/submission reporting period * Proposed data submission deadlines beginning with CY 2019 HH 

QRP * 

January 1, 2018–June 30, 2018. ............................................................. July 31, 2018. 

* We note that submission of the OASIS must also adhere to the HH PPS deadlines. 

¥The term ‘‘CY 2019 HH QRP’’ means the calendar year for which the HH QRP requirements applicable to that calendar year must be met in 

order for a HHA to avoid a two percentage point reduction to its market basket percentage when calculating the payment rates applicable to it for 

that calendar year. 

TABLE 21—SUMMARY ILLUSTRATION OF OASIS 12 MONTH DATA REPORTING FOR MEASURES AND PROPOSED

STANDARDIZED PATIENT ASSESSMENT DATA REPORTING FOR THE HH QRP * 

Proposed data collection/submission reporting period * Proposed data submission deadlines beginning with CY 2020 HH 

QRP * ∧

July 1, 2018–June 30, 2019. .................................................................... July 31, 2019. 

* We note that submission of the OASIS must also adhere to the HH PPS deadlines. 

∧The term ‘‘CY 2020 HH QRP’’ means the calendar year for which the HH QRP requirements applicable to that calendar year must be met in 

order for a HHA to avoid a two percentage point reduction to its market basket percentage when calculating the payment rates applicable to it for 

that calendar year. 

We invited comment on our proposal 

to extend our current policy governing 

the schedule for reporting the quality 

measure data to the reporting of 

standardized patient assessment data for 

the HH QRP beginning with the CY 

2019 HH QRP. 

We did not receive any comments 

regarding this proposal. 

Final Decision: We are finalizing our 

proposal as proposed to extend our 

current policy governing the schedule 

for reporting the quality measure data to 

the reporting of standardized patient 

assessment data for the HH QRP 

beginning with the CY 2019 HH QRP. 

4. Schedule for Reporting Quality 

Measures Beginning With the CY 2020 

HH QRP 

As discussed in section V.I. of this 

final rule, we are finalizing the adoption 

of three quality measures beginning 

with the CY 2020 HH QRP: Changes in 

Skin Integrity Post-Acute Care: Pressure 

Ulcer/Injury; Application of The Percent 

of Residents Experiencing One or More 

Falls with Major Injury (NQF #0674); 

and Application of Percent of LongTerm Care Hospital Patients with an 

Admission and Discharge Functional 

Assessment and a Care Plan That 

Addresses Function (NQF #2631). In the 

CY 2018 HH PPS proposed rule (82 FR 

35372), we proposed that HHAs would 

report data on these measures using 

OASIS reporting that is submitted 

through the QIES ASAP system. More 

information on OASIS reporting using 

the QIES ASAP system is located at 

https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/OASIS/

DataSpecifications.html. 

For the CY 2020 HH QRP, under our 

current policy HHAs will be required to 

report these data for HHA Medicare and 

Medicaid quality episodes that begin or 

end during the period from January 1, 

2019, to June 30, 2019. Beginning with 

the CY 2021 HH QRP, we proposed that 

HHAs would will be required to submit 

data for the entire 12-month period from 

July 1 to June 30. Further, for the 

purposes of measure calculation, our 

policy was established in the CY 2017 

HH PPS final rule (81 FR76784) that 

data are utilized using calendar year 

timeframes with review and correction 

periods. 

Comment: A commenter supported 

the proposed schedule for reporting the 

three new quality measures beginning 

with the CY 2020 QRP. However, the 

commenter also suggested that there is 

a disparity in how home health 

providers are reimbursed, which creates 

challenges for their submission of the 

required data. 

Response: We interpret the comment 

to be suggesting that Medicare 

reimbursement rates for HH services, 

compared to Medicare rates for postacute care services furnished by 

different provider-types, may affect the 

ability of HHAs to comply with the data 

reporting requirements under the HH 

QRP. We are cognizant of the challenges 

of data collection and we consider this 

when developing and adopting our 

measures. 

Final Decision: After consideration of 

the public comment received, we are 

finalizing our policy as proposed for the 

Schedule for Reporting the Quality 

Measures beginning with the CY 2020 

HH QRP. 

5. Input Sought for Data Reporting 

Related to Assessment Based Measures 

We have received input suggesting 

that we expand the population for 

quality measurement to include all 

patients regardless of payer. 

Approximately 75 percent of home 

health expenditures in 2014 were made 

by either Medicare or Medicaid and 

currently both Medicare and Medicaid 

collect and report data for OASIS. We 

believe that expanding the patient 

population for which OASIS collects 

data will allow us to ensure data that is 

representative of quality provided to all 

patients in the HHA setting, and 

therefore, allow us to better determine 

whether HH Medicare beneficiaries 

receive the same quality of care that 

other patients receive. We also 

appreciate that collecting quality data 

on all patients regardless of payer 

source may create additional burden. 

However, we have also received input 

that the effort to separate out Medicare 

and Medicaid beneficiaries, who are 

currently reported through OASIS, from 

other patients, creates clinical and work 

flow implications with an associated 

burden too, and noted that we further 

appreciate that it is common practice for 

HHAs to collect OASIS data on all 

patients, regardless of payer source. 

Thus, we sought input on whether we 

should require quality data reporting on 

all HH patients, regardless of payer, 

where feasible—noting that because 

Medicare Part A claims data are 

submitted only with respect to Medicare 

beneficiaries, claims-based measures 

would continue to be calculated only for 

Medicare beneficiaries. We would like 

to clarify that CMS sought comment on 

this all payor topic and therefore there 


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is no proposed policy to finalize. We 

appreciate the comments received and 

will take all recommendations into 

consideration. 

Comment: Several commenters 

supported data collection on all patients 

regardless of payor. One commenter 

requested that CMS provide additional 

explanation of what the benefit would 

be to collecting OASIS data on all 

patients regardless of payor. Several 

commenters stated that the addition of 

OASIS reporting for all patients 

regardless of payor will impose 

significant burden on HHAs. Some 

commenters noted that they used 

separate assessment documents for 

patients who are insured by private 

payors and that they used these 

assessments, in part, to avoid the 

burden of OASIS. A few commenters 

suggested that the collection of OASIS 

data on all patients regardless of payor 

could result in healthcare professionals 

spending more time with 

documentation and less time providing 

patient care. Some commenters 

suggested that if CMS requires HHAs to 

submit OASIS assessments on all 

patients, they might need to increase 

their staff hours, hire additional staff 

and incur additional expenses. 

Response: We continue to believe that 

the reporting of all-payor data under the 

HH QRP would add value to the 

program and provide a more accurate 

representation of the quality provided 

by HHAs. Although we acknowledge the 

concerns raised by commenters 

regarding the potential burden of 

reporting all-payer data and on the 

potential impact of such a requirement 

for the HH QRP, we wish to clarify that 

under the HH Conditions of 

Participation (42 CFR 484.55), each 

patient must receive, and an HHA must 

provide, a patient-specific, 

comprehensive assessment that 

accurately reflects the patient’s current 

health status and includes information 

that may be used to demonstrate the 

patient’s progress toward achievement 

of desired outcomes. The 

comprehensive assessment must also 

incorporate the use of the current 

version of the OASIS items, using the 

language and groupings of the OASIS 

items, as specified by the Secretary. 

Comment: We received several 

comments pertaining to the submission 

requirements of the OASIS instrument. 

Some commenters suggested that OASIS 

data was required for submission on 

only Medicare fee-for-service 

beneficiaries, while other commenters 

stated that HHAs must complete the 

OASIS for all Medicare and Medicaid 

patients. Another commenter noted that 

the HH Conditions of Participation 

already apply to all patients in a 

Medicare-certified HHA. Other 

commenters stated that they did not 

know what patient populations must be 

given an OASIS assessment. 

Response: As previously discussed, 

for the purposes HH QRP, data reporting 

on the OASIS includes all Medicare and 

Medicaid beneficiaries. However, the 

comprehensive assessment must also 

incorporate the collection of the current 

version of the OASIS items, using the 

language and groupings of the OASIS 

items. 

Comment: Several commenters stated 

concerns about the potential impact of 

all-payor information on the HH QRP 

public reporting and on the HHVBP 

model because private payors differ 

from CMS with regard to care pathways, 

approval, and authorization processes. 

Some commenters stated that private 

payors had proprietary information and 

that CMS would exceed its authority if 

it required all-payor reporting. 

Commenters also stated that some 

private insurers had different 

requirements than CMS pertaining to 

the number of visits paid for by such 

insurers, which would inhibit the 

agency in comparing performance 

across HHAs. 

Response: We acknowledge concerns 

raised for the HHVBP model and the 

potential downstream impacts. With 

regard to the commenter suggesting that 

private payors’ patients would generate 

proprietary information, we want to 

clarify that the OASIS is not a 

proprietary instrument and therefore we 

do not believe that a requirement that 

HHAs use the OASIS in compliance 

with our CoPs raises proprietary issues. 

J. Other Provisions for the CY 2019 HH 

QRP and Subsequent Years 

1. Application of the HH QRP Data 

Completion Thresholds to the 

Submission of Standardized Patient 

Assessment Data Beginning With the CY 

2019 HH QRP 

In the CY 2016 HH PPS final rule (80 

FR 68703 through 68704), we defined 

the pay-for-reporting performance 

system model that could accurately 

measure the level of an HHA’s 

submission of OASIS data based on the 

principle that each HHA is expected to 

submit a minimum set of two matching 

assessments for each patient admitted to 

their agency. These matching 

assessments together create what is 

considered a quality episode of care, 

consisting ideally of a SOC or ROC 

assessment and a matching End of Care 

EOC assessment. EOC assessments 

comprise the Discharge from Agency, 

Death at Home and Transfer to an 

Inpatient Facility time points. For 

further information on successful 

submission of OASIS assessments, types 

of assessments submitted by an HHA 

that fit the definition of a quality 

assessment, defining the ‘‘Quality 

Assessments Only’’ (QAO) formula, and 

implementing a pay-for-reporting 

performance requirement over a 3-year 

period, please see the CY 2016 HH PPS 

final rule (80 FR 68704 to 68705). 

Additionally, we finalized the payfor-reporting threshold requirements in 

the CY 2016 HH PPS final rule. We 

finalized a policy through which HHAs 

must score at least 70 percent on the 

QAO metric of pay-for-reporting 

performance requirement for CY 2017 

(reporting period July 1, 2015, to June 

30, 2016), 80 percent for CY 2018 

(reporting period July 1, 2016, to June 

30, 2017) and 90 percent for CY 2019 

(reporting period July 1, 2017, to June 

30, 2018). An HHA that does not meet 

this requirement for a calendar year will 

be subject to a two percentage point 

reduction to the market basket 

percentage increase that will otherwise 

apply for that calendar year. In the CY 

2018 HH PPS proposed rule (82 FR 

35373), we proposed to apply the 

threshold requirements established in 

the CY 2016 HH PPS rule to the 

submission of standardized patient 

assessment data beginning with the CY 

2019 HH QRP. 

Comment: Commenter provided 

feedback on the QAO standard which 

requires that at least 90 percent of 

OASIS assessments be usable for 

calculating quality measures or be 

subject to a 2-percentage point 

reduction to the market basket update 

for CY 2019. One commenter agreed 

with our proposal to apply the HH QRP 

data completion thresholds to the 

submission of standardized patient 

assessment data beginning in the CY 

2019 HH QRP. A commenter suggested 

that the proposed 90 percent threshold 

is very high and may be difficult for 

small or rural providers meet, and 

suggested changing this to 80 percent or 

higher. 

Response: We disagree that the 90 

percent threshold for CY 2019 is too 

high or difficult for HHAs to meet. 

The home health CoPs as codified (42 

CFR 484.55) mandate use of the OASIS 

data set. OASIS reporting was first 

implemented on July 19, 1999 and in 

2007, we adopted mandatory OASIS 

reporting for quality reporting purposes 

under section 1895(b)(3)(B)(v)(I) of the 

Act. Furthermore, HHAs have been 

required to submit OASIS data as a 

condition of payment of their Medicare 

claims since 2010. Since, HHAs have 

been required to report OASIS data for 


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the last 18 years as a CoP in the 

Medicare program and as a condition of 

payment of their Medicare claims for 

the past 7 years, our establishment of a 

90 percent threshold for OASIS 

reporting should not place any new or 

additional burden on HHAs. 

Final Decision: After consideration of 

the comments received, we are 

finalizing our proposal as proposed to 

extend our current HH QRP data 

completion requirements to the 

submission of standardized patient 

assessment data. 

2. HH QRP Submission Exception and 

Extension Requirements 

Our experience with other QRPs has 

shown that there are times when 

providers are unable to submit quality 

data due to extraordinary circumstances 

outside their control (for example, 

natural, or man-made disasters). Other 

extenuating circumstances are reviewed 

on a case-by-case basis. In the CY 2018 

HH QRP proposed rule (82 FR 35373), 

we proposed to define a ‘‘disaster’’ as 

any natural or man-made catastrophe 

which causes damages of sufficient 

severity and magnitude to partially or 

completely destroy or delay access to 

medical records and associated 

documentation. Natural disasters could 

include events such as hurricanes, 

tornadoes, earthquakes, volcanic 

eruptions, fires, mudslides, snowstorms, 

and tsunamis. Man-made disasters 

could include such events as terrorist 

attacks, bombings, floods caused by 

man-made actions, civil disorders, and 

explosions. A disaster may be 

widespread and impact multiple 

structures or be isolated and impact a 

single site only. 

In certain instances of either natural 

or man-made disasters, an HHA may 

have the ability to conduct a full patient 

assessment and record and save the 

associated data either during or before 

the occurrence of the extraordinary 

event. In this case, the extraordinary 

event has not caused the agency’s data 

files to be destroyed, but it could hinder 

the HHA’s ability to meet the QRP’s data 

submission deadlines. In this scenario, 

the HHA will potentially have the 

ability to report the data at a later date, 

after the emergency has passed. In such 

cases, a temporary extension of the 

deadlines for reporting might be 

appropriate. 

In other circumstances of natural or 

man-made disaster, an HHA may not 

have had the ability to conduct a full 

patient assessment, or to record and 

save the associated data before the 

occurrence of the extraordinary event. 

In such a scenario, the agency may not 

have complete data to submit to CMS. 

We believe that it may be appropriate, 

in these situations, to grant a full 

exception to the reporting requirements 

for a specific period of time. 

We do not wish to penalize HHAs in 

these circumstances or to unduly 

increase their burden during these 

times. Therefore, we proposed a process 

for HHAs to request and for us to grant 

exceptions and extensions for the 

reporting requirements of the HH QRP 

for one or more quarters, beginning with 

the CY 2019 HH QRP, when there are 

certain extraordinary circumstances 

outside the control of the HHA. When 

an exception or extension is granted, we 

would not reduce the HHA’s PPS 

payment for failure to comply with the 

requirements of the HH QRP. 

We proposed that if an HHA seeks to 

request an exception or extension for 

the HH QRP, the HHA must request an 

exception or extension within 90 days 

of the date that the extraordinary 

circumstances occurred. The HHA may 

request an exception or extension for 

one or more quarters by submitting a 

written request to CMS that contains the 

information noted below, via email to 

the HHA Exception and Extension 

mailbox at HHAPureConsiderations@

cms.hhs.gov. Requests sent to CMS 

through any other channel would not be 

considered as valid requests for an 

exception or extension from the HH 

QRP’s reporting requirements for any 

payment determination. 

The subject of the email must read 

‘‘HH QRP Exception or Extension 

Request’’ and the email must contain 

the all following information: 

• HHA CCN. 

• HHA name. 

• CEO or CEO-designated personnel 

contact information including name, 

telephone number, email address, and 

mailing address (the address must be a 

physical address, not a post office box). 

• HHA’s reason for requesting an 

exception or extension. 

• Evidence of the impact of 

extraordinary circumstances, including 

but not limited to photographs, 

newspaper and other media articles. 

• A date when the HHA believes it 

will be able to again submit HH QRP 

data and a justification for the proposed 

date. 

We proposed that exception and 

extension requests would need to be 

signed by the HHA’s CEO or CEOdesignated personnel, and that if the 

CEO designates an individual to sign the 

request, the CEO-designated individual 

would be able to submit such a request 

on behalf of the HHA. Following receipt 

of the email, we would provide a: (1) 

Written acknowledgement, using the 

contact information provided in the 

email, to the CEO or CEO-designated 

contact notifying them that the request 

has been received; and (2) a formal 

response to the CEO or any CEOdesignated HHA personnel, using the 

contact information provided in the 

email, indicating our decision. 

We stated that this proposal would 

not preclude us from granting 

exceptions or extensions to HHAs that 

have not requested them when we 

determine that an extraordinary 

circumstance, such as an act of nature, 

affects an entire region or locale. If we 

were to make the determination to grant 

an exception or extension to all HHAs 

in a region or locale, we proposed to 

communicate this decision through 

routine communication channels to 

HHAs and vendors, including, but not 

limited to, issuing memos, emails, and 

notices on our HH QRP Web site once 

it is available at https://www.cms.gov/

Medicare/Quality-Initiatives-PatientAssessment-Instruments/

HomeHealthQualityInits/

HomeHealthQualityReportingReconsideration-and-Exception-andExtension.html. 

We also proposed that we may grant 

an exception or extension to HHAs if we 

determine that a systemic problem with 

one of our data collection systems 

directly affected the ability of the HHA 

to submit data. Because we do not 

anticipate that these types of systemic 

errors will happen often, we do not 

anticipate granting an exception or 

extension on this basis frequently. 

If an HHA is granted an exception, we 

would not require that the HHA submit 

any measure data for the period of time 

specified in the exception request 

decision. If we grant an extension to the 

original submission deadline, the HHA 

would still remain responsible for 

submitting quality data collected during 

the timeframe in question, although we 

would specify a revised deadline by 

which the HHA must submit this 

quality data. 

We also proposed that any exception 

or extension requests submitted for 

purposes of the HH QRP would apply to 

that program only, and not to any other 

program we administer for HHAs such 

as survey and certification. OASIS 

requirements, including electronic 

submission, during Declared Public 

Health Emergencies can be found at 

FAQs I–5, I–6, I–7, I–8 at http://

www.cms.gov/Medicare/ProviderEnrollment-and-Certification/

SurveyCertEmergPrep/downloads/

AllHazardsFAQs.pdf. 

We intend to provide additional 

information pertaining to exceptions 

and extensions for the HH QRP, 

including any additional guidance, on 


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the HH QRP Web site at https://

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

HomeHealthQualityReportingReconsideration-and-Exception-andExtension.html. 

In the CY 2018 HH PPS proposed rule 

(82 FR 35374), we proposed to codify 

the HH QRP Submission Exception and 

Extension Requirements at § 484.250(d) 

of our regulations. 

Comment: One commenter expressed 

support for the creation of an exception 

and extension request process for HHAs 

that experience disasters or other 

extraordinary circumstances. 

Response: We thank the commenter 

for the comment and support. 

Final Decision: After consideration of 

comments received, we are finalizing 

the adoption of the policy as proposed 

for HH QRP Submission Exception and 

Extension Requirements beginning with 

the CY 2019 HH QRP and our decision 

to codify the HH QRP Submission 

Exception and Extension Requirements 

at § 484.250(d) of our regulations. 

3. HH QRP Submission Reconsideration 

and Appeals Procedures 

The HH QRP reconsiderations and 

appeals process was finalized in the CY 

2013 HH PPS final rule (77 FR 67096). 

At the conclusion of the required 

quality data reporting and submission 

period, we review the data received 

from each HHA during that reporting 

period to determine if the HHA met the 

HH QRP reporting requirements. HHAs 

that are found to be noncompliant with 

the HH QRP reporting requirements for 

the applicable calendar year will receive 

a 2 percentage point reduction to its 

market basket percentage update for that 

calendar year. 

Similar to our other quality reporting 

programs, such as the SNF QRP, the 

LTCH QRP, and the IRF QRP, we 

include an opportunity for the providers 

to request a reconsideration of our 

initial noncompliance determination. 

To be consistent with other established 

quality reporting programs and to 

provide an opportunity for HHAs to 

seek reconsideration of our initial 

noncompliance decision, in the CY 2018 

HH PPS proposed rule (82 FR 35374 

through 35375) we proposed a process 

that enables an HHA to request 

reconsideration of our initial noncompliance decision in the event that it 

believes that it was incorrectly 

identified as being non-compliant with 

the HH QRP reporting requirements for 

a particular calendar year. 

For the CY 2019 HH QRP, and 

subsequent years, we proposed a HHA 

would receive a notification of 

noncompliance if we determine that the 

HHA did not submit data in accordance 

with the HH QRP reporting 

requirements for the applicable CY. The 

purpose of this notification is to put the 

HHA on notice that the HHA: (1) Has 

been identified as being non-compliant 

with the HH QRP’s reporting 

requirements for the applicable calendar 

year; (2) will be scheduled to receive a 

reduction in the amount of two 

percentage points to its market basket 

percentage update for the applicable 

calendar year; (3) may file a request for 

reconsideration if it believes that the 

finding of noncompliance is erroneous, 

has submitted a request for an extension 

or exception that has not yet been 

decided, or has been granted an 

extension or exception; and (4) must 

follow a defined process on how to file 

a request for reconsideration, which will 

be described in the notification. 

We stated that we would only 

consider requests for reconsideration 

after an HHA has been found to be 

noncompliant. 

Notifications of noncompliance and 

any subsequent notifications from CMS 

would be sent via a traceable delivery 

method, such as certified U.S. mail or 

registered U.S. mail, or through other 

practicable notification processes, such 

as a report from CMS to the provider as 

a Certification and Survey Provider 

Enhanced Reports (CASPER) report, that 

will provide information pertaining to 

their compliance with the reporting 

requirements for the given reporting 

cycle or from the Medicare 

Administrative Contractors assigned to 

process the provider’s claims. To obtain 

the compliance reports, we stated that 

HHAs must access the CASPER 

Reporting Application. HHAs can access 

the CASPER Reporting application via 

their CMS OASIS System Welcome page 

by selecting the CASPER Reporting link. 

The ‘‘CASPER Reports’’ link will 

connect an HHA to the QIES National 

System Login page for CASPER 

Reporting. 

We proposed to disseminate 

communications regarding the 

availability of compliance reports 

through routine channels to HHAs and 

vendors, including, but not limited to 

issuing memos, emails, Medicare 

Learning Network (MLN) 

announcements, and notices on our HH 

QRP Web site once it is available at 

https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

HomeHealthQualityReportingReconsideration-and-Exception-andExtension.html. 

We proposed that an HHA would 

have 30 days from the date of the letter 

of noncompliance to submit to us a 

request for reconsideration. This 

proposed time frame would allow us to 

balance our desire to ensure that HHA 

s have the opportunity to request 

reconsideration with our need to 

complete the process and provide HHAs 

with our reconsideration decision in a 

timely manner. We proposed that an 

HHA may withdraw its request at any 

time and may file an updated request 

within the proposed 30-day deadline. 

We also proposed that, in very limited 

circumstances, we may grant a request 

by an HHA to extend the proposed 

deadline for reconsideration requests. 

We stated that it would be the 

responsibility of an HHA to request an 

extension and demonstrate that 

extenuating circumstances existed that 

prevented the filing of the 

reconsideration request by the proposed 

deadline. 

We also proposed that as part of the 

HHA’s request for reconsideration, the 

HHA would be required to submit all 

supporting documentation and evidence 

demonstrating full compliance with all 

HH QRP reporting requirements for the 

applicable calendar year, that the HHA 

has requested an extension or exception 

for which a decision has not yet been 

made, that the HHA has been granted an 

extension or exception, or has 

experienced an extenuating 

circumstance as defined in section V.I.2. 

of this final rule, but failed to file a 

timely request of exception. We 

proposed that we would not review any 

reconsideration request that fails to 

provide the necessary documentation 

and evidence along with the request. 

We proposed that the documentation 

and evidence may include copies of any 

communications that demonstrate the 

HHA’s compliance with the HH QRP, as 

well as any other records that support 

the HHA’s rationale for seeking 

reconsideration, but must not include 

any protected health information (PHI). 

We stated that we intended to provide 

a sample list of acceptable supporting 

documentation and evidence, as well as 

instructions for HHAs on how to 

retrieve copies of the data submitted to 

CMS for the appropriate program year in 

the future on our HH QRP Web site at 

https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

HomeHealthQualityReportingReconsideration-and-Exception-andExtension.html. 

We proposed that an HHA wishing to 

request a reconsideration of our initial 

noncompliance determination would be 

required to do so by submitting an email 

to the following email address: 

HHAPureConsiderations@cms.hhs.gov. 


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Any request for reconsideration 

submitted to us by an HHA would be 

required to follow the guidelines 

outlined on our HH QRP Web site once 

it is available once it is available at 

https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

HomeHealthQualityReportingReconsideration-and-Exception-andExtension.html. 

All emails must contain a subject line 

that reads ‘‘HH QRP Reconsideration 

Request.’’ Electronic email submission 

is the only form of reconsideration 

request submission that will be accepted 

by us. We proposed that any 

reconsideration requests communicated 

through another channel including, but 

not limited to, U.S. Postal Service or 

phone, would not be considered as a 

valid reconsideration request. 

We proposed that a reconsideration 

request include the all of the following 

information: 

• HHA CMS Certification Number 

(CCN). 

• HHA Business Name. 

• HHA Business Address. 

• The CEO contact information 

including name, email address, 

telephone number, and physical mailing 

address; or the CEO-designated 

representative contact information 

including name, title, email address, 

telephone number and physical mailing 

address. 

• CMS identified reason(s) for 

noncompliance from the noncompliance notification. 

• The reason(s) for requesting 

reconsideration. 

We proposed that the request for 

reconsideration must be accompanied 

by supporting documentation 

demonstrating compliance. Following 

receipt of a request for reconsideration, 

we would provide an email 

acknowledgment, using the contact 

information provided in the 

reconsideration request, to the CEO or 

CEO-designated representative that the 

request has been received. Once we 

have reached a decision regarding the 

reconsideration request, an email would 

be sent to the HHA CEO or CEO 

designated representative, using the 

contact information provided in the 

reconsideration request, notifying the 

HHA of our decision. 

We also proposed that the 

notifications of our decision regarding 

reconsideration requests may be made 

available through a traceable delivery 

method, such as certified U.S. mail or 

registered U.S. mail or through the use 

of CASPER reports. If the HHA is 

dissatisfied with the decision rendered 

at the reconsideration level, the HHA 

may appeal the decision to the PRRB 

under 42 CFR 405.1835. We believe the 

proposed process is more efficient and 

less costly for CMS and for HHAs 

because it decreases the number of 

PRRB appeals by resolving issues earlier 

in the process. Additional information 

about the reconsideration process 

including details for submitting a 

reconsideration request will be posted 

in the future to our HH QRP Web site 

at https://www.cms.gov/Medicare/

Quality-Initiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

HomeHealthQualityReportingReconsideration-and-Exception-andExtension.html. 

In the CY 2018 HH PPS proposed rule 

(82 FR 35375), we proposed to add the 

HH QRP Submission Reconsideration 

and Appeals Procedures at §§ 484.250(e) 

and (f) of our regulations. 

Comment: One commenter expressed 

support for the submission 

reconsideration and appeals procedures 

for HHAs. 

Response: We thank the commenter 

for the comment and support. 

Final Decision: After consideration of 

the public comments received, we are 

finalizing as proposed the adoption of 

the policy for HH QRP Submission 

Reconsideration and Appeals 

Procedures for the CY 2019 HH QRP 

and subsequent years, which will be 

codified at § 484.250(e) and (f) of our 

regulations. 

K. Policies Regarding Public Display of 

Quality Measure Data for the HH QRP 

Our home health regulations, at 

§ 484.250(a), require HHAs to submit 

OASIS assessments and Home Health 

Care Consumer Assessment of 

Healthcare Providers and Systems 

Survey® (HHCAHPS) data to meet the 

quality reporting requirements of 

section 1895(b)(3)(B)(v) of the Act. 

Section 1899B(g) of the Act requires that 

data and information of provider 

performance on quality measures and 

resource use and other measures be 

made publicly available beginning not 

later than 2 years after the applicable 

specified ‘‘application date’’. In 

addition, section 1895(b)(3)(B)(v)(III) of 

the Act requires the Secretary to 

establish procedures for making data 

submitted under section 

1895(b)(3)(B)(v)(II) of the Act available 

to the public, and section 1899B(g)(1) of 

the Act requires the Secretary to do the 

same with respect to HHA performance 

on measures specified under sections 

1899B(c)(1) and (d)(1) of the Act. 

Section 1895(b)(3)(B)(v)(III) of the Act 

requires that the public reporting 

procedures for data submitted under 

subclause (II) ensure that a HHA has the 

opportunity to review the data that is to 

be made public with respect to it prior 

to such data being made public. Under 

section 1899B(g)(2) of the Act, the 

public reporting procedures for 

performance on measures under 

sections 1899B(c)(1) and (d)(1) of the 

Act 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 

Inpatient Quality Reporting (Hospital 

IQR) Program), that a HHA has the 

opportunity to review and submit 

corrections to its data and information 

that are to be made public for the agency 

prior to such data being made public. 

We recognize that public reporting of 

quality data is a vital component of a 

robust quality reporting program and are 

fully committed to ensuring that the 

data made available to the public are 

meaningful. Further, we agree that 

measures for comparing performance 

across home health agencies must be 

constructed from data collected in a 

standardized and uniform manner. 

In the CY 2017 HH PPS final rule (81 

FR 76785 through 76786), we finalized 

procedures that allow individual HHAs 

to review and correct their data and 

information on IMPACT Act measures 

that are to be made public before those 

measure data are made public. 

Information on how to review and 

correct data on IMPACT Act measures 

that are to be made public before those 

measure data are made public can be 

found on the HH QRP Web site at 

https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/

Home-Health-Quality-ReportingRequirements.html. We did not propose 

any changes to these policies in the CY 

2018 HH PPS proposed rule. 

However, in the CY 2018 HH PPS 

proposed rule (82 FR 35375 and 35376), 

pending the availability of data, we 

proposed to publicly report data 

beginning in CY 2019 for the following 

two assessment-based measures: (1) 

Percent of Patients or Residents with 

Pressure Ulcers that are New or 

Worsened (NQF #0678); and (2) Drug 

Regimen Review Conducted with 

Follow-Up for Identified Issues—PAC 

HH QRP. Data collection for these two 

assessment-based measures began on 

OASIS on January 1, 2017. We proposed 

to publicly report data beginning in CY 

2019 for these assessment-based 

measures based on four rolling quarters 

of data, beginning with data collected 

for discharges in 2017. 

We proposed to publicly report data 

beginning in CY 2019 for the following 


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102This language is currently available as 

Footnote #4 on Home Health Compare (https://

www.medicare.gov/HomeHealthCompare/Data/

Footnotes.html). 

3 claims-based measures: (1) Medicare 

Spending Per Beneficiary—PAC HH 

QRP; (2) Discharge to Community-PAC 

HH QRP; and (3) Potentially Preventable 

30-Day Post-Discharge Readmission 

Measure for HH QRP. As adopted in the 

CY 2017 HH PPS final rule (81 FR 

43773), for the MSPB–PAC HH QRP 

measure, we will use 1 year of claims 

data beginning with CY 2016 claims 

data to inform confidential feedback 

reports for HHAs, and CY 2017 claims 

data for public reporting for the HH 

QRP. For the Discharge to Community— 

PAC HH QRP measure we will use 2 

years of claims data, beginning with CYs 

2015 and 2016 claims data to inform 

confidential feedback and CYs 2016 and 

2017 claims data for public reporting. 

For the Potentially Preventable 30-Day 

Post-Discharge Readmission Measure for 

HH QRP, we will use 3 years of claims 

data, beginning with CY 2014, 2015 and 

2016 claims data to inform confidential 

feedback reports for HHAs, and CY 

2015, 2016 and 2017 claims data for 

public reporting. 

Finally, we proposed to assign HHAs 

with fewer than 20 eligible cases during 

a performance period to a separate 

category: ‘‘The number of patient 

episodes for this measure is too small to 

report,’’ 102 to ensure the statistical 

reliability of the measures. If a HHA had 

fewer than 20 eligible cases, the HHA’s 

performance would not be publicly 

reported for the measure for that 

performance period. 

TABLE 22—NEW HH QRP MEASURES PROPOSED FOR CY 2019 PUBLIC DISPLAY

Proposed measures: 

Percent of Residents or Patients with Pressure Ulcers that Are New or Worsened (Short Stay) (NQF #0678). 

Drug Regimen Review Conducted with Follow-Up for Identified Issues—PAC HH QRP. 

Potentially Preventable 30-Day Post-Discharge Readmission Measure for HH QRP. 

Discharge to Community—(PAC) HH QRP. 

Medicare Spending Per Beneficiary (PAC) HH QRP. 

We invited public comments on these 

proposals for the public display of 

quality data. 

Comment: Commenters provide 

feedback regarding the public display of 

quality measures beginning CY 2019 for 

data collected beginning CY 2017. One 

commenter questioned if the Medicare 

Spending Per Beneficiary—PAC HH 

QRP measure includes spending data 

that is specific to HH services or the 

total amount of Medicare spending for 

beneficiaries specific to a defined 

timeframe. One commenter did not 

support public reporting for the 

Discharge to Community—PAC HH QRP 

measure based on the potential for 

providers to have incentives against the 

appropriate use of hospice services in a 

patient-centered continuum of care. 

Another commenter did not support 

publicly reporting the Drug Regimen 

Review Conducted with Follow-Up for 

Identified Issues—PAC HH QRP 

measure, stating that this measure is 

dependent on physician response and is 

not a measure of HHA quality or 

performance. Finally, a commenter 

suggested a dashboard of measures 

aligned across home health quality 

initiatives, including star ratings, Home 

Health Compare and the HH VBP 

demonstration. 

Response: We appreciate the 

commenters’ suggestions regarding the 

public display of quality measures. As 

finalized in the CY 2017 rule, the 

MSPB–PAC HH QRP measure episode is 

comprised of a treatment period and an 

associated services period. The 

treatment period includes those services 

that are provided directly by the HHA. 

The associated services period is the 

time during which Medicare Part A and 

Part B services that are not treatment 

services are counted towards the 

episode, subject to certain exclusions, 

such as planned admissions and organ 

transplants. More detailed specifications 

for the MSPB–PAC measures, including 

the MSPB–PAC HH QRP measure, are 

available at https://www.cms.gov/

Medicare/Quality-Initiatives-PatientAssessment-Instruments/

HomeHealthQualityInits/

HHQIQualityMeasures.html. 

The Discharge to Community measure 

excludes patients discharged to home or 

facility-based hospice care. Thus, 

discharges to hospice are not considered 

discharges to community, but rather are 

excluded from the measure calculation. 

We wish to also note that including 31- 

day post-discharge mortality outcomes 

is intended to identify successful 

discharges to community, and to avoid 

the potential unintended consequence 

of inappropriate community discharges 

that bypass hospice care. With respect 

to the public reporting of Drug Regimen 

Review Conducted with Follow-Up for 

Identified Issues, the intent of the 

measure is to capture timely follow up 

for all potential clinically significant 

issues. We believe the timely review 

and follow up of potentially clinically 

significant medication issues at every 

assessment time period and across the 

patient’s episode of care is essential for 

providing the best quality care for 

patients, and that this measure helps to 

ensure that high quality care services 

are furnished and that patient harm is 

avoided. 

With regard to the commenter’s 

suggestion that we provide a dashboard 

that communicates alignment across the 

measures, we will take the commenter’s 

suggestion under consideration. 

Comment: We received several 

comments about the Quality of Patient 

Care star ratings. One commenter noted 

increased administrative and clinical 

costs HHAs incur to maintain or 

improve the number of stars instead of 

focusing on improving the scores on 

individual quality measures. Another 

commenter stated that poor performing 

home health agencies could rate higher 

than their actual performance while 

good or excellent agencies could rate 

lower than their actual performance due 

to the way the data is calculated. 

Response: We thank the commenters, 

but note that these comments relate to 

issues for which we made no proposals 

in the CY 2018 HH proposed rule. 

Therefore, we believe these comments 

to be outside the scope of the proposed 

rule and will not address them here. 

Final Decision: After considering the 

comments received, we are finalizing 

our proposals regarding public display 

of quality measure data in the HH QRP. 

L. Mechanism for Providing Confidential 

Feedback Reports to HHAs 

Section 1899B(f) of the Act requires 

the Secretary to provide confidential 

feedback reports to post-acute care 

(PAC) providers on their performance 

on the measures specified under 

subsections (c)(1) and (d)(1) of section 

1899B of the Act, beginning one year 

after the specified application date that 

applies to such measures and PAC 


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providers. In the CY 2017 HH PPS final 

rule (81 FR 76702), we finalized 

processes to allow HH providers the 

opportunity to review their data and 

information using confidential feedback 

reports that will enable HHAs to review 

their performance on the measures 

required under the HH QRP. 

Information on how to obtain these and 

other reports available to the HH QRP 

can be found at https://www.cms.gov/

Medicare/Quality-Initiatives-PatientAssessment-Instruments/

HomeHealthQualityInits/Home-HealthQuality-Reporting-Requirements.html. 

We did not propose any changes to this 

policy. 

M. Home Health Care CAHPS® Survey 

(HHCAHPS) 

In the CY 2017 HH PPS final rule (81 

FR 76787), we stated that the home 

health quality measures reporting 

requirements for Medicare-certified 

agencies includes the Home Health Care 

CAHPS® (HHCAHPS) Survey for the 

Home Health Quality Reporting Program 

and along with OASIS measures, 

HHCAHPS participation is required for 

the Annual Payment Update (APU). In 

the CY 2017 HH PPS final rule, we 

finalized the reporting requirements and 

the data submission dates for the CY 

2017–CY 2020 APU periods. We 

proposed to continue the HHCAHPS 

requirements in future years for the 

continuous monthly data collection and 

quarterly data submission of HHCAHPS 

data. 

1. Background and Description of 

HHCAHPS 

The HHCAHPS survey is part of a 

family of CAHPS® surveys that asks 

patients to report on and rate their 

experiences with health care. For more 

details about the HHCAHPS Survey 

please see 81 FR 76787 through 76788. 

We stated in previous rules that 

Medicare-certified HHAs are required to 

contract with an approved HHCAHPS 

survey vendor. This requirement 

continues, and Medicare-certified 

agencies are required to provide a 

monthly list of their HHCAHPS-eligible 

patients to their respective HHCAHPS 

survey vendors. Home health agencies 

are not allowed to influence their 

patients about how the HHCAHPS 

survey. 

As previously required, new 

HHCAHPS survey vendors are required 

to attend Introduction training, and 

current HHCAHPS vendors are required 

to attend Update training conducted by 

CMS and the HHCAHPS Survey 

Coordination Team. New HHCAHPS 

vendors need to pass a post-training 

certification test. We have 

approximately 25 approved HHCAHPS 

survey vendors. The list of approved 

HHCAHPS survey vendors is available 

at https://homehealthcahps.org. 

2. HHCAHPS Oversight Activities 

We stated in prior final rules that all 

approved HHCAHPS survey vendors are 

required to participate in HHCAHPS 

oversight activities to ensure 

compliance with HHCAHPS protocols, 

guidelines, and survey requirements. 

The purpose of the oversight activities 

is to ensure that approved HHCAHPS 

survey vendors follow the HHCAHPS 

Protocols and Guidelines Manual. 

In the CY 2013 HH PPS final rule (77 

FR 67095 through 67097, 67164), we 

codified at § 484.250(c)(3) that all 

approved HHCAHPS survey vendors are 

required to fully comply with all 

HHCAHPS oversight activities. 

In the CY 2018 HH PPS proposed rule 

(82 FR 35377), we restated the 

HHCAHPS requirements for CY 2019, 

because participation occurs in the 

period of the publication of the 

proposed and final rules for CY 2018. 

We additionally presented the 

HHCAHPS requirements for CY 2020 for 

the sake of continuity. We proposed the 

HHCAHPS requirements for the CY 

2021 Annual Payment Update. 

3. HHCAHPS Requirements for the CY 

2019 HH QRP 

In the CY 2017 HH PPS final rule (81 

FR 76789), we finalized the 

requirements for the CY 2019 HH QRP. 

For the CY 2019 HH QRP, we require 

continuous monthly HHCAHPS data 

collection and reporting for four 

quarters. The data collection period for 

the CY 2018 HH QRP includes the 

second quarter 2017 through the first 

quarter 2018 (the months of April 2017 

through March 2018). HHAs will be 

required to submit their HHCAHPS data 

files to the HHCAHPS Data Center for 

the second quarter 2017 by 11:59 p.m., 

eastern daylight time (e.d.t.) on October 

19, 2017; for the third quarter 2017 by 

11:59 p.m., eastern standard time (e.s.t.) 

on January 18, 2018; for the fourth 

quarter 2017 by 11:59 p.m., e.d.t. on 

April 19, 2018; and for the first quarter 

2018 by 11:59 p.m., e.d.t. on July 19, 

2018. These deadlines are firm; no 

exceptions will be permitted. 

For more details on the CY 2019 HH 

QRP, we refer readers to 81 FR 76789. 

4. HHCAHPS Requirements for the CY 

2020 HH QRP 

In the CY 2017 HH PPS final rule (81 

FR 76789), we finalized the 

requirements for the CY 2020 HH QRP. 

For the CY 2020 HH QRP, we require 

continued monthly HHCAHPS data 

collection and reporting for four 

quarters. The data collection period for 

the CY 2020 HH QRP includes the 

second quarter 2018 through the first 

quarter 2019 (the months of April 2018 

through March 2019). HHAs will be 

required to submit their HHCAHPS data 

files to the HHCAHPS Data Center for 

the second quarter 2018 by 11:59 p.m., 

e.d.t. on October 18, 2018; for the third 

quarter 2018 by 11:59 p.m., e.s.t. on 

January 17, 2019; for the fourth quarter 

2018 by 11:59 p.m., e.d.t. on April 18, 

2019; and for the first quarter 2019 by 

11:59 p.m., e.d.t. on July 18, 2019. These 

deadlines are firm; no exceptions will 

be permitted. 

For more details about the CY 2020 

HH QRP, we refer readers to 81 FR 

76789. 

5. HHCAHPS Requirements for the CY 

2021 HH QRP 

For the CY 2021 HH QRP, we 

proposed to require the continued 

monthly HHCAHPS data collection and 

reporting for four quarters. The data 

collection period for the CY 2021 HH 

QRP includes the second quarter 2019 

through the first quarter 2020 (the 

months of April 2019 through March 

2020). HHAs will be required to submit 

their HHCAHPS data files to the 

HHCAHPS Data Center for the second 

quarter 2019 by 11:59 p.m., e.d.t. on 

October 17, 2019; for the third quarter 

2019 by 11:59 p.m., e.s.t. on January 16, 

2020; for the fourth quarter 2019 by 

11:59 p.m., e.d.t. on April 16, 2020; and 

for the first quarter 2020 by 11:59 p.m., 

e.d.t. on July 16, 2020. These deadlines 

are firm; no exceptions will be 

permitted. 

For the CY 2021 HH QRP, we 

proposed to require that all HHAs with 

fewer than 60 HHCAHPS-eligible 

unduplicated or unique patients in the 

period of April 1, 2018 through March 

31, 2019 are exempt from the HHCAHPS 

data collection and submission 

requirements for the CY 2021 HH QRP, 

upon completion of the CY 2021 

HHCAHPS Participation Exemption 

Request form, and upon CMS 

verification of the HHA patient counts. 

Agencies with fewer than 60 

HHCAHPS-eligible, unduplicated or 

unique patients in the period of April 1, 

2018 through March 31, 2019 were 

proposed to be required to submit their 

patient counts on the CY 2021 

HHCAHPS Participation Exemption 

Request form posted on https://

homehealthcahps.org from April 1, 

2019 to 11:59 p.m., e.d.t. to March 31, 

2020. This deadline is firm, as are all of 

the quarterly data submission deadlines 

for the HHAs that participate in 

HHCAHPS. 


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We proposed to automatically exempt 

HHAs receiving Medicare certification 

on or after the start of the period in 

which HHAs do their patient count for 

a particular year’s HHCAHPS data 

submission from the HHCAHPS 

reporting requirement for the year. We 

proposed that HHAs receiving 

Medicare-certification on or after April 

1, 2019 would be exempt from the 

HHCAHPS reporting requirement for the 

CY 2021 HH QRP. As we have finalized 

in previous years, we proposed that 

these newly-certified HHAs do not need 

to complete the HHCAHPS Participation 

Exemption Request Form for the CY 

2021 HH QRP. 

6. HHCAHPS Reconsiderations and 

Appeals Process 

As finalized in previous rules, we 

proposed that HHAs must monitor their 

respective HHCAHPS survey vendors to 

ensure that vendors submit their 

HHCAHPS data on time, by accessing 

their HHCAHPS Data Submission 

Reports on https://

homehealthcahps.org. This helps HHAs 

ensure that their data are submitted in 

the proper format for data processing to 

the HHCAHPS Data Center. 

We proposed to continue HHCAHPS 

oversight activities as finalized in the 

previous rules. In the CY 2013 HH PPS 

final rule (77 FR 67068, 67164), we 

codified the current guideline that all 

approved HHCAHPS survey vendors 

must fully comply with all HHCAHPS 

oversight activities. We included this 

survey requirement at § 484.250(c)(3). 

For further information on the HH 

QRP reconsiderations and appeals 

process, please see section V.J.3. of this 

final rule. 

7. Summary 

We did not propose any changes to 

the participation requirements, or to the 

requirements pertaining to the 

implementation of the Home Health 

CAHPS® Survey (HHCAHPS). We only 

proposed updates to the information to 

reflect the dates for future HH QRP 

years. We encouraged HHAs to keep upto-date about the HHCAHPS by 

regularly viewing the official Web site 

for the HHCAHPS at https://

homehealthcahps.org. We noted that 

HHAs can also send an email to the 

HHCAHPS Survey Coordination Team 

at hhcahps@rti.org or to CMS at 

homehealthcahps@cms.hhs.gov, or 

telephone toll-free 

(1–866–354–0985) for more information 

about the HHCAHPS Survey. 

Final Decision: We did not receive 

any comments on our proposals. 

Accordingly, we are finalizing the 

proposals. We again strongly encourage 

HHAs to keep up-to-date about the 

HHCAHPS by regularly viewing the 

official Web site for the HHCAHPS at 

https://homehealthcahps.org. HHAs can 

also send an email to the HHCAHPS 

Survey Coordination Team at hhcahps@

rti.org or to CMS at homehealthcahps@

cms.hhs.gov, or telephone toll-free (1– 

866–354–0985) for more information 

about the HHCAHPS Survey. 

VI. Collection of Information 

Requirements 

A. Statutory Requirement for 

Solicitation of Comments 

Under the Paperwork Reduction Act 

of 1995 (PRA), we are required to 

provide 60-day notice in the Federal 

Register and solicit public comment 

before a collection of information 

requirement is submitted to the OMB for 

review and approval. We note that we 

will submit a revised information 

collection request (OMB control number 

0938–1279) to OMB for review. This 

will also extend the information 

collection request which expires 

December 30, 2019. To fairly evaluate 

whether an information collection 

should be approved by OMB, section 

3506(c)(2)(A) of the PRA requires that 

we solicit comment on the following 

issues: 

• The need for the information 

collection and its usefulness in carrying 

out the proper functions of our agency. 

• The accuracy of our estimate of the 

information collection burden. 

• The quality, utility, and clarity of 

the information to be collected. 

• Recommendations to minimize the 

information collection burden on the 

affected public, including automated 

collection techniques. 

This final rule makes reference to 

associated information collections that 

are not discussed in the regulation text 

contained in this document. 

B. Collection of Information 

Requirements for the HH QRP 

We believe that the burden associated 

with the HH QRP is the time and effort 

associated with data collection and 

reporting. As of April 1, 2017, there are 

approximately 12,149 HHAs reporting 

quality data to CMS. For the purposes 

of calculating the costs associated with 

the collection of information 

requirements, we obtained mean hourly 

wages for these staff from the U.S. 

Bureau of Labor Statistics’ May 2016 

National Occupational Employment and 

Wage Estimates (http://www.bls.gov/

oes/current/oes_nat.htm). To account 

for overhead and fringe benefits (100 

percent), we have doubled the hourly 

wage. These amounts are detailed in 

Table 23. 

TABLE 23—U.S. BUREAU OF LABOR STATISTICS’ MAY 2016 NATIONAL OCCUPATIONAL EMPLOYMENT AND WAGE

ESTIMATES

Occupation title Occupation 

code 

Mean hourly 

wage 

($/hr) 

Fringe 

benefit 

(100%) 

($/hr) 

Adjusted 

hourly 

wage 

($/hr) 

Registered Nurse (RN) .................................................................................... 29–1141 $34.70 $34.70 $69.40 

Physical therapists HHAs ................................................................................ 29–1123 46.42 46.42 92.84 

Speech-Language Pathologists (SLP) ............................................................ 29–1127 37.60 37.60 75.20 

Occupational Therapists (OT) ......................................................................... 29–1122 40.25 40.25 80.50 

The OASIS changes that we are 

finalizing in section V.D of this final 

rule will result in the removal of 70 data 

elements from the OASIS at the time 

point of Start of Care (SOC), 70 data 

elements at the time point of 

Resumption of Care (ROC), 18 data 

elements at the time point of Follow-up 

(FU), 42 data elements at the time point 

of Transfer to an Inpatient Facility 

(TOC), 1 data element at the time point 

of Death at Home (Death), and 34 data 

elements at the time point of Discharge 

from Agency (Discharge). These data 

items will not be used in the calculation 

of quality measures adopted in the HH 

QRP, or for other purposes that are not 

related to the HH QRP. 

Section V.F.1. of this final rule adopts 

a new pressure ulcer measure to replace 

the current pressure ulcer measure that 


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we previously specified under section 

1899B(c)(1)(B) of the Act, beginning 

with the CY 2020 HH QRP. The 

replacement measure is entitled, 

‘‘Changes in Skin Integrity Post-Acute 

Care: Pressure Ulcer/Injury.’’ The new 

measure will be calculated using data 

elements that are currently collected 

and reported using the OASIS–C2 

(version effective January 1, 2017). 

Adoption of the Changes in Skin 

Integrity Post-Acute Care: Pressure 

Ulcer/Injury measure will result in the 

removal of item M1313, which has 6 

data elements that cover the same issues 

that are addressed in the pressure ulcer 

assessment that will be required under 

the new pressure ulcer measure, making 

it duplicative and no longer necessary to 

separately collect. 

In sections V.F.2. of this final rule, we 

are adopting a new quality measure 

under section 1899B(c)(1)(A) of the Act 

beginning with the CY 2020 HH QRP 

entitled ‘‘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).’’ In 

the CY 2018 HH PPS proposed rule (82 

FR 35379), we stated that if we finalized 

the adoption of this measure, we would 

add 13 standardized patient assessment 

data elements at SOC, 13 data elements 

at ROC, 15 standardized patient 

assessment data elements at FU, and 13 

standardized patient assessment data 

elements at Discharge. We inadvertently 

did not include in our original burden 

estimate two OASIS items (GG0170Q 

and GG0170RR) that are needed to 

calculate this measure.103 We have 

updated our burden estimate to include 

these items, and note that as a result of 

finalizing this measure, we will be 

adding 15 standardized patient 

assessment data elements at SOC, 15 

standardized patient assessment data 

elements at ROC, 16 standardized 

patient assessment data elements at FU, 

and 15 standardized patient assessment 

data elements at Discharge. 

In sections V.F.3. of this final rule, we 

are adopting a new quality measure 

under section 1899B(c)(1)(D) of the Act 

beginning with the CY 2020 HH QRP 

entitled ‘‘Application of Percent of 

Residents Experiencing One or More 

Falls with Major Injury (NQF# 0674).’’ 

The new measure will be calculated 

using new standardized data elements 

added to the OASIS. Specifically, we are 

adding 4 data elements at TOC, 4 data 

elements at Death, and 4 data elements 

at Discharge. 

In sections V.H.2 and V.H.3 of this 

final rule, we are finalizing our proposal 

to collect standardized patient 

assessment data with respect to the 

Medical Condition and Comorbidity 

category beginning with the CY 2019 

HH QRP and Functional Status 

beginning with the CY 2020 HH QRP. 

As a result, we are adding to the OASIS 

the standardized patient assessment 

data elements associated with these 

categories, which include 17 

standardized patient assessment data 

elements at SOC, 17 standardized 

patient assessment data elements at 

ROC, and 12 standardized patient 

assessment data elements at Discharge. 

We are not finalizing our proposals to 

require HHAs to report standardized 

patient assessment data elements for 

three of the five categories under section 

1899B(b)(1)(B) of the Act: Cognitive 

Function and Mental Status; Special 

Services, Treatments, and Interventions; 

and Impairments. As a result, we will 

not be adding to the OASIS the data 

elements associated with these 

proposals, which included 36 data 

elements at SOC, 36 data elements at 

ROC, or 24 data elements at discharge. 

The OASIS instrument is used for 

both the HH QRP and the HH PPS. In 

sections III.E. of this final rule, after 

receiving detailed comments from the 

public we are not finalizing the 

implementation of the HHGM. 

Therefore, we are not finalizing the 

proposal to add two current OASIS–C2 

items, M1033 and M1800, at the FU 

time point or to remove collection of 

eight current OASIS–C2 integumentary 

status items at the FU time point. 

In summary, as a net result of the 

policies we are finalizing in this final 

rule, we will be removing 38 data 

elements at SOC, 38 data elements at 

ROC, 2 data elements at FU, 38 data 

elements at TOC and 9 data elements at 

Discharge. We will be adding 3 data 

elements at Death. 

Under section 1899B(m) of the Act, 

the Paperwork Reduction Act does not 

apply to section 1899B, or to the 

sections of the OASIS that require 

modification to achieve the 

standardization of patient assessment 

data. We are, however, setting out the 

burden as a courtesy to advise interested 

parties of the actions’ time and costs 

and for reference in the regulatory 

impact analysis (RIA) section VII. of this 

final rule. The requirement and burden 

will be submitted to OMB for review 

and approval when the modifications to 

the OASIS have achieved 

standardization and are no longer 

exempt from the requirements under 

section 1899B(m) of the Act. 

We assume that each data element 

requires 0.3 minutes of clinician time to 

complete. Therefore, there is a reduction 

in clinician burden per OASIS 

assessment of 11.4 minutes at SOC, 11.4 

minutes at ROC, 0.6 minutes at FU, 11.4 

minutes at TOC 2.7 minutes at 

Discharge. There is an increase in 

clinician burden per assessment of 0.9 

minutes at Death. 

The OASIS is completed by RNs or 

PTs, or very occasionally by 

occupational therapists (OT) or speech 

language pathologists (SLP/ST). Data 

from 2016 show that the SOC/ROC 

OASIS is completed by RNs 

(approximately 87 percent of the time), 

PTs (approximately 12.7 percent of the 

time), and other therapists, including 

OTs and SLP/STs (approximately 0.3 

percent of the time). Based on this 

analysis, we estimated a weighted 

clinician average hourly wage of $72.40, 

inclusive of fringe benefits, using the 

hourly wage data in Table 23. 

Individual providers determine the 

staffing resources necessary. 

Table 24 shows the total number of 

assessments submitted in CY 2016 and 

estimated burden at each time point. 

TABLE 24—CY 2016 OASIS SUBMISSIONS AND ESTIMATED BURDEN, BY TIME POINT

Time point 

CY 2016 

assessments 

completed 

Estimated 

burden 

($) 

Start of Care ................................................................................................................................................ 6,261,934 ¥$86,139,164.10 

Resumption of Care ..................................................................................................................................... 1,049,247 ¥14,443,441.73 

Follow-up ..................................................................................................................................................... 3,797,410 ¥2,749,324.84 

Transfer to an inpatient facility .................................................................................................................... 1,892,099 ¥26,027,713.84 

Death at Home ............................................................................................................................................ 41,128 44,665.01 

Discharge from agency ................................................................................................................................ 5,120,124 ¥16,681,363.99 


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TABLE 24—CY 2016 OASIS SUBMISSIONS AND ESTIMATED BURDEN, BY TIME POINT—Continued 

Time point 

CY 2016 

assessments 

completed 

Estimated 

burden 

($) 

Total ...................................................................................................................................................... 18,161,942 ¥145,986,343.50 

* Estimated Burden ($) at each Time-Point = (# CY 2016 Assessments Completed) x (clinician burden [min]/60) x ($72.40 [weighted clinician 

average hourly wage]). 

Based on the data in Table 24, for the 

12,149 active Medicare-certified HHAs 

in April 2017, we estimate the total 

average decrease in cost associated with 

changes to the HH QRP at $12,016.33 

per HHA annually, or $145,986,343.50 

for all HHAs annually. This corresponds 

to an estimated reduction in clinician 

burden associated with changes to the 

HH QRP of 166 hours per HHA 

annually, or 2,016,386 hours for all 

HHAs annually. This decrease in 

burden will be accounted for in the 

information collection under OMB 

control number 0938–1279. 

C. Submission of PRA-Related 

Comments 

We have submitted a copy of this final 

rule to OMB for its review of the rule’s 

information collection and 

recordkeeping requirements. The 

requirements are not effective until they 

have been approved by OMB. 

To obtain copies of a supporting 

statement and any related forms for the 

proposed collection(s) summarized in 

this notice, you may make your request 

using one of following: 

1. Access CMS’ Web site address at 

https://www.cms.gov/Regulations-andGuidance/Legislation/

PaperworkReductionActof1995/PRAListing.html. 

2. Email your request, including your 

address, phone number, OMB number, 

and CMS document identifier, to 

Paperwork@cms.hhs.gov. 

3. Call the Reports Clearance Office at 

(410) 786–1326. 

See this final rule’s DATES and 

ADDRESSES sections for the comment 

due date and for additional instructions. 

VII. Regulatory Impact Analysis 

A. Statement of Need 

Section 1895(b)(1) of the Act requires 

the Secretary to establish a HH PPS for 

all costs of home health services paid 

under Medicare. In addition, section 

1895(b) of the Act requires: (1) The 

computation of a standard prospective 

payment amount include all costs for 

home health services covered and paid 

for on a reasonable cost basis and that 

such amounts be initially based on the 

most recent audited cost report data 

available to the Secretary; (2) the 

prospective payment amount under the 

HH PPS to be an appropriate unit of 

service based on the number, type, and 

duration of visits provided within that 

unit; and (3) the standardized 

prospective payment amount be 

adjusted to account for the effects of 

case-mix and wage levels among HHAs. 

Section 1895(b)(3)(B) of the Act 

addresses the annual update to the 

standard prospective payment amounts 

by the HH applicable percentage 

increase. Section 1895(b)(4) of the Act 

governs the payment computation. 

Sections 1895(b)(4)(A)(i) and 

(b)(4)(A)(ii) of the Act require the 

standard prospective payment amount 

to be adjusted for case-mix and 

geographic differences in wage levels. 

Section 1895(b)(4)(B) of the Act requires 

the establishment of appropriate casemix adjustment factors for significant 

variation in costs among different units 

of services. Lastly, section 1895(b)(4)(C) 

of the Act requires the establishment of 

wage adjustment factors that reflect the 

relative level of wages, and wage-related 

costs applicable to home health services 

furnished in a geographic area 

compared to the applicable national 

average level. 

Section 1895(b)(3)(B)(iv) of the Act 

provides the Secretary with the 

authority to implement adjustments to 

the standard prospective payment 

amount (or amounts) for subsequent 

years to eliminate the effect of changes 

in aggregate payments during a previous 

year or years that was the result of 

changes in the coding or classification 

of different units of services that do not 

reflect real changes in case-mix. Section 

1895(b)(5) of the Act provides the 

Secretary with the option to make 

changes to the payment amount 

otherwise paid in the case of outliers 

because of unusual variations in the 

type or amount of medically necessary 

care. Section 1895(b)(3)(B)(v) of the Act 

requires HHAs to submit data for 

purposes of measuring health care 

quality, and links the quality data 

submission to the annual applicable 

percentage increase. 

The HHVBP Model will apply a 

payment adjustment based on an HHA’s 

performance on quality measures to test 

the effects on quality and expenditures. 

B. Overall Impact 

We have examined the impacts of this 

final rule as required by Executive 

Order 12866 on Regulatory Planning 

and Review (September 30, 1993), 

Executive Order 13563 on Improving 

Regulation and Regulatory Review 

(January 18, 2011), the Regulatory 

Flexibility Act (RFA) (September 19, 

1980, Pub. L. 96–354), section 1102(b) of 

the Act, section 202 of the Unfunded 

Mandates Reform Act of 1995 (UMRA, 

March 22, 1995; Pub. L. 104–4), 

Executive Order 13132 on Federalism 

(August 4, 1999), the Congressional 

Review Act (5 U.S.C. 804(2) and 

Executive Order 13771 on Reducing 

Regulation and Controlling Regulatory 

Costs (January 30, 2017). 

Executive Orders 12866 and 13563 

direct agencies to assess all costs and 

benefits of available regulatory 

alternatives and, if regulation is 

necessary, to select regulatory 

approaches that maximize net benefits 

(including potential economic, 

environmental, public health and safety 

effects, distributive impacts, and 

equity). We included a detailed 

alternatives considered section in the 

CY 2018 HH PPS proposed rule, which 

outlined alternatives considered for the 

CY 2018 HH PPS payment update, the 

proposed HHGM, and HH VBP model 

(82 FR 35388 and 35389). 

Section 3(f) of Executive Order 12866 

defines a ‘‘significant regulatory action’’ 

as an action that is likely to result in a 

rule: (1) (Having an annual effect on the 

economy of $100 million or more in any 

1 year, or adversely and materially 

affecting a sector of the economy, 

productivity, competition, jobs, the 

environment, public health or safety, or 

state, local or tribal governments or 

communities (also referred to as 

‘‘economically significant’’); (2) creating 

a serious inconsistency or otherwise 

interfering with an action taken or 

planned by another agency; (3) 

materially altering the budgetary 

impacts of entitlement grants, user fees, 

or loan programs or the rights and 

obligations of recipients thereof; or (4) 

raising novel legal or policy issues 

arising out of legal mandates, the 

President’s priorities, or the principles 

set forth in the Executive Order. 


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A regulatory impact analysis (RIA) 

must be prepared for major rules with 

economically significant effects ($100 

million or more in any 1 year). The 

savings impacts related to the HHVBP 

Model as a whole are estimated at a total 

projected 5-year gross savings of $378 

million assuming a savings estimate of 

a 6 percent annual reduction in 

hospitalizations and a 1.0 percent 

annual reduction in SNF admissions; 

the portion attributable to this final rule 

is negligible. In section VII. of this final 

rule, we identified a reduction in our 

regulatory reporting burden of $ 

145,986,343.50. We estimate that this 

rulemaking is ‘‘economically 

significant’’ as measured by the $100 

million threshold, and hence also a 

major rule under the Congressional 

Review Act. Accordingly, we have 

prepared a Regulatory Impact Analysis 

that, to the best of our ability, presents 

the costs and benefits of the rulemaking. 

In addition, section 1102(b) of the Act 

requires us to prepare a RIA 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 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. This rule 

is applicable exclusively to HHAs. 

Therefore, the Secretary has determined 

this final rule will not have a significant 

economic impact on the operations of 

small rural hospitals. 

Section 202 of the Unfunded 

Mandates Reform Act of 1995 (UMRA) 

also requires that agencies assess 

anticipated costs and benefits before 

issuing any rule whose mandates 

require spending in any 1 year of $100 

million in 1995 dollars, updated 

annually for inflation. In 2017, that 

threshold is approximately $148 

million. This final rule is not 

anticipated to have an effect on State, 

local, or tribal governments, in the 

aggregate, or on the private sector of 

$148 million or more. 

If regulations impose administrative 

costs on private entities, such as the 

time needed to read and interpret this 

final rule, we must estimate the cost 

associated with regulatory review. Due 

to the uncertainty involved with 

accurately quantifying the number of 

entities that will review the rule, we 

assume that the total number of unique 

commenters on this year’s proposed rule 

will be the number of reviewers of this 

final rule. We acknowledge that this 

assumption may understate or overstate 

the costs of reviewing this final rule. It 

is possible that not all commenters 

reviewed this year’s rule in detail, and 

it is also possible that some reviewers 

chose not to comment on the proposed 

rule. For these reasons we believe that 

the number of commenters will be a fair 

estimate of the number of reviewers of 

this final rule. 

We also recognize that different types 

of entities are in many cases affected by 

mutually exclusive sections of this 

proposed rule, and therefore for the 

purposes of our estimate we assume that 

each reviewer reads approximately 50 

percent of the rule. 

Using the wage information from the 

BLS for medical and health service 

managers (Code 11–9111), we estimate 

that the cost of reviewing this final rule 

is $105.16 per hour, including overhead 

and fringe benefits (https://www.bls.gov/ 

oes/2016/may/naics4_621100.htm). 

Assuming an average reading speed, we 

estimate that it will take approximately 

2.6 hours for the staff to review half of 

this final rule. For each HHA that 

reviews the rule, the estimated cost is 

$273.42 (2.6 hours x $105.16). 

Therefore, we estimate that the total cost 

of reviewing this regulation is 

$368,023.32 ($273.42 x 1,346 

reviewers). 

1. HH PPS for CY 2018 

The update set forth in this final rule 

applies to Medicare payments under HH 

PPS in CY 2018. Accordingly, the 

following analysis describes the impact 

in CY 2018 only. We estimate that the 

net impact of the policies in this final 

rule is approximately $80 million in 

decreased payments to HHAs in CY 

2018. We applied a wage index budget 

neutrality factor and a case-mix weights 

budget neutrality factor to the rates as 

discussed in section III.C.3. of this final 

rule. Therefore, the estimated impact of 

the 2018 wage index and the 

recalibration of the case-mix weights for 

2018 is zero. The ¥$80 million impact 

reflects the distributional effects of a 0.5 

percent reduction in payments due to 

the sunset of the rural add-on provision 

($100 million decrease), a 1 percent 

home health payment update percentage 

($190 million increase), and a ¥0.97 

percent adjustment to the national, 

standardized 60-day episode payment 

rate to account for nominal case-mix 

growth for an impact of ¥0.9 percent 

($170 million decrease). The $80 

million in decreased payments is 

reflected in the last column of the first 

row in Table 25 as a 0.4 percent 

decrease in expenditures when 

comparing CY 2017 payments to 

estimated CY 2018 payments. 

The RFA requires agencies to analyze 

options for regulatory relief of small 

entities, if a rule has a significant impact 

on a substantial number of small 

entities. For purposes of the RFA, small 

entities include small businesses, 

nonprofit organizations, and small 

governmental jurisdictions. Most 

hospitals and most other providers and 

suppliers are small entities, either by 

nonprofit status or by having revenues 

of less than $7.5 million to $38.5 

million in any one year. For the 

purposes of the RFA, we estimate that 

almost all HHAs are small entities as 

that term is used in the RFA. 

Individuals and states are not included 

in the definition of a small entity. The 

economic impact assessment is based on 

estimated Medicare payments 

(revenues) and HHS’s practice in 

interpreting the RFA is to consider 

effects economically ‘‘significant’’ only 

if greater than 5 percent of providers 

reach a threshold of 3 to 5 percent or 

more of total revenue or total costs. The 

majority of HHAs’ visits are Medicarepaid visits, and therefore, the majority 

of HHAs’ revenue consists of Medicare 

payments. Based on our analysis, we 

conclude that the policies in this final 

rule will result in an estimated total 

impact of 3 to 5 percent or more on 

Medicare revenue for greater than 5 

percent of HHAs. Therefore, the 

Secretary has determined that this HH 

PPS rule will have a significant 

economic impact on a substantial 

number of small entities. Further detail 

is presented in Table 25, by HHA type 

and location. 

With regards to options for regulatory 

relief, the sunset of rural add-on 

payments for CY 2018 is statutory and 

we do not have the authority to 

authorize rural add-on payments past 

December 31, 2017. We believe it is 

appropriate to reduce the national, 

standardized 60-day episode payment 

amount by 0.97 percent in CY 2018 to 

account for the estimated increase in 

nominal case-mix in order to move 

towards more accurate payment for the 

delivery of home health services where 

payments better align with the costs of 

providing such services. 

2. HHVBP Model 

Under the HHVBP Model, the first 

payment adjustment will apply in CY 

2018 based on PY1 (2016) data and the 

final payment adjustment will apply in 

CY 2022 based on PY5 (2020) data. In 

the CY 2016 HH PPS final rule, we 

estimated that the overall impact of the 

HHVBP Model from CY 2018 through 

CY 2022 was a reduction of 

approximately $380 million (80 FR 

68716). In the CY 2017 HH PPS final 

rule, we estimated that the overall 

impact of the HHVBP Model from CY 

2018 through CY 2022 was a reduction 


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Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 51747 

of approximately $378 million (81 FR 

76795). We do not believe the changes 

finalized in this final rule will affect the 

prior estimates. 

C. Detailed Economic Analysis 

This final rule updates for CY 2018 

the HH PPS rates contained in the CY 

2017 HH PPS final rule (81 FR 76702 

through 76797). The impact analysis of 

this final rule presents the estimated 

expenditure effects of policy changes 

that are be finalized. We use the latest 

data and best analysis available, but we 

do not make adjustments for future 

changes in such variables as number of 

visits or case-mix. 

This analysis incorporates the latest 

estimates of growth in service use and 

payments under the Medicare HH 

benefit, based primarily on Medicare 

claims data from 2016. 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 

errors resulting from other changes in 

the impact time period assessed. Some 

examples of such possible events are 

newly-legislated general Medicare 

program funding changes made by the 

Congress, or changes specifically related 

to HHAs. In addition, changes to the 

Medicare program may continue to be 

made as a result of the Affordable Care 

Act, or new statutory provisions. 

Although these changes may not be 

specific to the HH 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 HHAs. 

1. HH PPS for CY 2018 

Table 25 represents how HHA 

revenues are likely to be affected by the 

policy changes in this final rule for CY 

2018. For this analysis, we used an 

analytic file with linked CY 2016 OASIS 

assessments and HH claims data for 

dates of service that ended on or before 

December 31, 2016. The first column of 

Table 25 classifies HHAs according to a 

number of characteristics including 

provider type, geographic region, and 

urban and rural locations. The second 

column shows the number of facilities 

in the impact analysis. The third 

column shows the payment effects of 

the CY 2018 wage index. The fourth 

column shows the payment effects of 

the CY 2018 case-mix weights. The fifth 

column shows the effects the 0.97 

percent reduction to the national, 

standardized 60-day episode payment 

amount to account for nominal case-mix 

growth. The sixth column shows the 

payment effects from the sunset of the 

rural add-on payment provision in 

statute. The seventh column shows the 

effects of the CY 2018 home health 

payment update percentage. 

The last column shows the combined 

effects of all the policies in this final 

rule. Overall, it is projected that 

aggregate payments in CY 2018 will 

decrease by 0.4 percent. As illustrated 

in Table 25, the combined effects of all 

of the changes vary by specific types of 

providers and by location. We note that 

some individual HHAs within the same 

group may experience different impacts 

on payments than others due to the 

distributional impact of the CY 2018 

wage index, the extent to which HHAs 

had episodes in case-mix groups where 

the case-mix weight decreased for CY 

2018 relative to CY 2017, the percentage 

of total HH PPS payments that were 

subject to the low-utilization payment 

adjustment (LUPA) or paid as outlier 

payments, and the degree of Medicare 

utilization. In addition, we clarify that 

there are negative estimated impacts 

attributed to the sunset of the rural addon provision for HHAs located in urban 

areas as well as rural areas. This is due 

to the fact that HHAs located in urban 

areas provide services to patients 

located in rural areas and payments are 

based on the location of the beneficiary. 

TABLE 25—ESTIMATED HHA IMPACTS BY FACILITY TYPE AND AREA OF THE COUNTRY, CY 2018 

Number of 

agencies 

CY 2018 

wage 

index 1

% 

CY 2018 

case-mix 

weights 2

% 

60-Day 

episode 

rate nominal 

case-mix 

reduction 3

% 

Sunset of 

rural add-on 

HH payment 

update 

percentage 4

% 

Total 

% 

All Agencies .............................................................................. 11,056 0.0 0.0 ¥0.9 ¥0.5 1.0 ¥0.4 

Facility Type and Control 

Free-Standing/Other Vol/NP ..................................................... 1,110 0.0 0.1 ¥0.8 ¥0.4 1.0 ¥0.1 

Free-Standing/Other Proprietary ............................................... 8,724 0.0 0.0 ¥0.9 ¥0.4 1.0 ¥0.3 

Free-Standing/Other Government ............................................. 318 ¥0.3 0.1 ¥0.9 ¥1.3 1.0 ¥1.4 

Facility-Based Vol/NP ............................................................... 634 0.0 0.2 ¥0.8 ¥0.7 1.0 ¥0.3 

Facility-Based Proprietary ......................................................... 81 ¥0.3 0.2 ¥0.9 ¥1.3 1.0 ¥1.3 

Facility-Based Government ....................................................... 189 0.0 0.2 ¥0.9 ¥1.5 1.0 ¥1.2 

Subtotal: Freestanding .............................................................. 10,152 0.0 0.0 ¥0.9 ¥0.4 1.0 ¥0.3 

Subtotal: Facility-based ............................................................. 904 0.0 0.2 ¥0.8 ¥0.8 1.0 ¥0.4 

Subtotal: Vol/NP ........................................................................ 1,744 0.0 0.1 ¥0.8 ¥0.5 1.0 ¥0.2 

Subtotal: Proprietary ................................................................. 8,805 0.0 0.0 ¥0.9 ¥0.5 1.0 ¥0.4 

Subtotal: Government ............................................................... 507 ¥0.2 0.2 ¥0.9 ¥1.4 1.0 ¥1.3 

Facility Type and Control: Rural 

Free-Standing/Other Vol/NP ..................................................... 265 0.2 0.1 ¥0.9 ¥2.5 1.0 ¥2.1 

Free-Standing/Other Proprietary ............................................... 832 ¥0.1 ¥0.2 ¥0.9 ¥2.3 1.0 ¥2.5 

Free-Standing/Other Government ............................................. 224 ¥0.4 0.0 ¥0.9 ¥2.6 1.0 ¥2.9 

Facility-Based Vol/NP ............................................................... 285 ¥0.4 0.1 ¥0.8 ¥2.7 1.0 ¥2.8 

Facility-Based Proprietary ......................................................... 42 ¥0.1 0.1 ¥0.9 ¥2.7 1.0 ¥2.6 

Facility-Based Government ....................................................... 142 ¥0.2 0.1 ¥0.8 ¥2.6 1.0 ¥2.5 

Facility Type and Control: Urban 

Free-Standing/Other Vol/NP ..................................................... 845 ¥0.9 0.1 ¥0.8 ¥0.1 1.0 ¥0.7 

Free-Standing/Other Proprietary ............................................... 7,892 0.0 0.0 ¥0.9 ¥0.2 1.0 ¥0.1 

Free-Standing/Other Government ............................................. 94 ¥0.3 0.2 ¥0.9 ¥0.1 1.0 ¥0.1 

Facility-Based Vol/NP ............................................................... 349 0.1 0.2 ¥0.8 ¥0.1 1.0 0.4 

Facility-Based Proprietary ......................................................... 39 ¥0.5 0.2 ¥0.9 ¥0.2 1.0 ¥0.4 


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51748 Federal Register / Vol. 82, No. 214 / Tuesday, November 7, 2017 / Rules and Regulations 

TABLE 25—ESTIMATED HHA IMPACTS BY FACILITY TYPE AND AREA OF THE COUNTRY, CY 2018—Continued 

Number of 

agencies 

CY 2018 

wage 

index 1

% 

CY 2018 

case-mix 

weights 2

% 

60-Day 

episode 

rate nominal 

case-mix 

reduction 3

% 

Sunset of 

rural add-on 

HH payment 

update 

percentage 4

% 

Total 

% 

Facility-Based Government ....................................................... 47 0.3 0.2 ¥0.9 ¥0.3 1.0 0.3 

Facility Location: Urban or Rural 

Rural .......................................................................................... 1,790 ¥0.1 ¥0.1 ¥0.9 ¥2.4 1.0 ¥2.5 

Urban ......................................................................................... 9,266 0.0 0.0 ¥0.9 ¥0.2 1.0 ¥0.1 

Facility Location: Region of the Country (Census Region) 

New England ............................................................................. 359 0.0 0.1 ¥0.8 ¥0.3 1.0 0.0 

Mid Atlantic ................................................................................ 495 0.0 ¥0.1 ¥0.8 ¥0.2 1.0 ¥0.1 

East North Central .................................................................... 2,235 0.0 0.2 ¥0.9 ¥0.4 1.0 ¥0.1 

West North Central ................................................................... 711 0.2 0.1 ¥0.9 ¥0.8 1.0 ¥0.4 

South Atlantic ............................................................................ 1,736 ¥0.2 ¥0.1 ¥0.9 ¥0.3 1.0 ¥0.5 

East South Central .................................................................... 426 ¥0.2 ¥0.2 ¥0.9 ¥1.3 1.0 ¥1.6 

West South Central ................................................................... 2,987 0.2 ¥0.3 ¥0.9 ¥0.7 1.0 ¥0.7 

Mountain .................................................................................... 683 ¥0.2 0.1 ¥0.9 ¥0.4 1.0 ¥0.4 

Pacific ........................................................................................ 1,377 0.1 0.5 ¥0.9 ¥0.1 1.0 0.6 

Other ......................................................................................... 47 0.1 ¥1.0 ¥0.8 ¥0.6 1.0 ¥1.3 

Facility Size (Number of 1st Episodes) 

<100 episodes ........................................................................... 3,092 0.0 0.1 ¥0.9 ¥0.4 1.0 ¥0.2 

100 to 249 ................................................................................. 2,467 0.1 0.2 ¥0.9 ¥0.5 1.0 ¥0.1 

250 to 499 ................................................................................. 2,225 0.1 0.2 ¥0.9 ¥0.5 1.0 ¥0.1 

500 to 999 ................................................................................. 1,710 0.0 0.0 ¥0.9 ¥0.5 1.0 ¥0.4 

1,000 or More ............................................................................ 1,562 ¥0.1 ¥0.1 ¥0.9 ¥0.5 1.0 ¥0.6 

Source: CY 2016 Medicare claims data for episodes ending on or before December 31, 2016 for which we had a linked OASIS assessment. 1The impact of the CY 2018 home health wage index is offset by the wage index budget neutrality factor described in section III.C.3 of this final rule. 

2The impact of the CY 2018 home health case-mix weights reflects the recalibration of the case-mix weights offset by the case-mix weights budget neutrality factor 

described in section III.B of this final rule. 3The 0.97 percent reduction to the national, standardized 60-day episode payment amount in CY 2018 is estimated to have a 0.9 percent impact on overall HH 

PPS expenditures. 4The CY 2018 home health payment update percentage reflects the home health payment update of 1 percent as described in section III.C.1 of this final rule. 

REGION KEY: 

New England = Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont. 

Middle Atlantic = Pennsylvania, New Jersey, New York. 

South Atlantic = Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia. 

East North Central = Illinois, Indiana, Michigan, Ohio, Wisconsin. 

East South Central = Alabama, Kentucky, Mississippi, Tennessee. 

West North Central = Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota. 

West South Central = Arkansas, Louisiana, Oklahoma, Texas. 

Mountain = Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, Wyoming. 

Pacific = Alaska, California, Hawaii, Oregon, Washington. 

Other = Guam, Puerto Rico, Virgin Islands. 

The following is a summary of the 

public comments received on the 

‘‘Regulatory Impact Analysis’’ and our 

responses: 

Comment: A commenter requested 

that CMS provide the impact analyses of 

the case-mix weight changes that are 

annually proposed. 

Response: The analyses of the annual 

case-mix weight changes are included in 

Table 25 in the fourth column titled, 

‘‘CY 2018 Case-Mix Weights’’. 

Comment: A commenter stated that 

when isolating the case mix changes 

from CY2017 to the CY2018 proposed 

rule, they are seeing an average impact 

of ¥0.58% which differs from the CMS 

projected 0.0 percent in Table 54 of the 

proposed rule. This analysis is for the 

case-mix components only (weights and 

budget neutrality factor), and excludes 

all other components such as wage 

index, nominal CM reduction, sunset of 

rural add-on, and the payment update 

percentage. The commenter requested 

an explanation of the apparent 

discrepancy. 

Response: We estimate that all HHAs 

nationwide will see a decrease in 

average case-mix between CY 2017 and 

CY 2018 of 1.6 percent due to 

recalibration of the case-mix weights 

(hence the BN factor of 1.6 percent). In 

increasing the base rate by 1.6 percent 

to offset the decrease in average casemix, those HHAs that have a decrease in 

average case-mix of less than 1.6 percent 

between CY 2017 and CY 2018 will see 

a small increase in payment for CY 2018 

due to the case-mix weights budget 

neutrality factor. Those HHAs that have 

a decrease in average case-mix of more 

than 1.6 percent due to the case-mix 

weight recalibration between CY 2017 

and CY 2018 will see a small decrease 

in payment for CY 2018 (generally 

proportional to the decrease in average 

case-mix above and beyond ¥1.6 

percent). The adjustment for case-mix 

normalization is budget neutral in the 

aggregate but not so for individual 

HHAs. 

2. HHVBP Model 

Table 26 displays our analysis of the 

distribution for possible payment 

adjustments at the 3-percent, 5-percent, 

6-percent, 7-percent, and 8-percent rates 

that are being used in the Model using 

CY 2015 baseline data and CY 2016 PY 

1 data for OASIS-based measures, 

claims-based hospitalization and 

Emergency Department (ED) measures, 

and HHCAHPS data. The estimated 

impacts account for the minimum 40 

HHCAHPS completed surveys policy, 

beginning with PY 1, as finalized in this 

rule. For PY 1 and 2, we show the 

impacts based on ten OASIS quality 

measures (9 OASIS quality measures 

were used for PY 3 through 5 to 

represent the removal of the Drug 

Education measure), two claims-based 

measures in QIES, five HHCAHPS 

measures, and the three new measures 


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(using the October 2016 and January 

2017 submission data), using the QIES 

Roll Up File data in the same manner as 

they will be in the Model. HHAs were 

classified as being in the smaller or 

larger volume cohort using the 2015 

Quality Episode File, as updated for this 

final rule, which is created using OASIS 

assessments. The basis of the payment 

adjustment was derived from complete 

2015 claims data. We note that this 

impact analysis is based on the 

aggregate value of all nine states. 

Table 27 displays our analysis of the 

distribution of possible payment 

adjustments based on the same CY 2015 

baseline data and 2016 PY 1 data used 

to calculate Table 26, providing 

information on the estimated impact of 

the finalized policies in this final rule. 

Note that all Medicare-certified HHAs 

that provide services in Massachusetts, 

Maryland, North Carolina, Florida, 

Washington, Arizona, Iowa, Nebraska, 

and Tennessee are required to compete 

in this Model. This analysis reflects that 

only HHAs that have data for at least 

five measures that meet the 

requirements of § 484.305, as amended 

by this final rule, will be included in the 

LEF and will have a payment 

adjustment calculated. Value-based 

incentive payment adjustments for the 

estimated 1,600 plus HHAs in the 

selected states that will compete in the 

HHVBP Model are stratified by size as 

described in section IV.B. of the CY 

2017 HH PPS final rule. As finalized in 

section IV.B. of the CY 2017 HH PPS 

final rule, there must be a minimum of 

eight HHAs in any cohort. 

Those HHAs that are in states that do 

not have at least eight smaller-volume 

HHAs do not have a separate smallervolume cohort and thus there will only 

be one cohort that will include all the 

HHAs in that state. As indicated in 

Table 27, Arizona, Maryland, North 

Carolina, Tennessee and Washington 

will only have one cohort while Florida, 

Iowa, Massachusetts, and Nebraska will 

have both a smaller-volume cohort and 

a larger-volume cohort. For example, 

Iowa has 26 HHAs exempt from the 

requirement that their beneficiaries 

complete HHCAHPS surveys because 

they provided HHA services to fewer 

than 60 beneficiaries in CY 2015. 

Therefore, 26 HHAs competed in Iowa’s 

smaller-volume cohort for the 2016 

performance year under the Model. 

Using CY 2015 baseline year data and 

CY 2016 PY 1 data and the maximum 

payment adjustment for PY 1 of 3- 

percent (as applied in CY 2018), based 

on the ten OASIS quality measures, two 

claims-based measures in QIES, the five 

HHCAHPS measures, and the three new 

measures, the smaller-volume HHAs in 

Iowa have a mean payment adjustment 

of ¥0.1 percent (Table 27). Ten percent 

of HHAs in the smaller-volume cohort 

will be subject to payment adjustments 

of more than minus 1.1 percent (¥1.1 

percent), the lowest 10th percentile. The 

next columns provide the distribution of 

scores by percentile; we see that the 

cohort payment adjustment distribution 

for HHAs in Iowa in the smaller-volume 

cohort ranges from ¥1.1 percent at the 

10th percentile to +1.5 percent at the 

90th percentile, while the cohort 

payment adjustment distribution 

median is ¥0.3 percent. 

Table 28 provides the payment 

adjustment distribution based on agency 

size, proportion of dually-eligible 

beneficiaries, average case mix (using 

the average case-mix for non-LUPA 

episodes), the proportion of the HHA’s 

beneficiaries that reside in rural areas 

and HHA organizational status. HHAs 

with a higher proportion of duallyeligible beneficiaries and HHAs whose 

beneficiaries have higher acuity tend to 

have better performance. 

The payment adjustment percentages 

are calculated at the state and size 

cohort level. Hence, the values of each 

separate analysis in the tables reflect the 

baseline year of 2015 and the 

performance year of 2016. There are 

1,622 Medicare-certified HHAs in the 

nine selected states that have a 

sufficient number of measures to receive 

a payment adjustment in the Model. We 

note in Table 28, that at the time of our 

analysis, seven of the 1,622 Medicarecertified HHAs were missing 

information needed for the 

stratifications in the table. Not all 

Medicare-certified HHAs in the nine 

states have a payment adjustment 

because some HHAs are servicing too 

small of a population to report an 

adequate number of measures to 

calculate a TPS. However, as noted 

previously, our updated analysis found 

that the number of such HHAs was not 

affected by the proposed minimum 40 

HHCAHPS survey policy, which we are 

finalizing. 

Additional analysis (see Table 29) was 

conducted to illustrate the effect of the 

finalized policy to require 40 or more 

completed HHCAHPS surveys versus 20 

or more completed HHCAHPS surveys. 

We include information on average 

statewide TPS by size of the HHA. The 

percentage difference in the average TPS 

across all larger-volume HHAs for each 

state ranges from ¥0.3 percent through 

1.8 percent and the majority of states are 

close to zero. 

TABLE 26—ADJUSTMENT DISTRIBUTION BY PERCENTILE LEVEL OF QUALITY TOTAL PERFORMANCE SCORE AT DIFFERENT

MODEL PAYMENT ADJUSTMENT RATES

[Percentage]* 

Payment adjustment distribution Range 

(%) 10% 20% 30% 40% Median 60% 70% 80% 90% 

3% Payment Adjustment For Performance Year 1 of the Model ..... 2.8 ¥1.3 ¥0.9 ¥0.6 ¥0.4 ¥0.1 0.2 0.5 0.8 1.4 

5% Payment Adjustment For Performance Year 2 of the Model ..... 4.6 ¥2.2 ¥1.6 ¥1.0 ¥0.6 ¥0.1 0.3 0.8 1.4 2.4 

6% Payment Adjustment For Performance Year 3 of the Model** .. 5.8 ¥2.8 ¥1.9 ¥1.3 ¥0.7 ¥0.2 0.4 1.0 1.7 3.0 

7% Payment Adjustment For Performance Year 4 of the Model** .. 6.7 ¥3.2 ¥2.2 ¥1.5 ¥0.9 ¥0.2 0.5 1.2 1.9 3.5 

8% Payment Adjustment For Performance Year 5 of the Model** .. 7.7 ¥3.7 ¥2.5 ¥1.7 ¥1.0 ¥0.2 0.5 1.4 2.2 4.0 

* Based on measure performance data from Performance Year 1 (January 1, 2016 to December 31, 2016), the baseline year (January 1, 2015 to December 31, 

2015), and home health Medicare claims data from 2015. 

** For Performance Years 3, 4, and 5, the payment adjustment rate simulation incorporated the removal of the Drug Education measure. 

TABLE 27—HHA COHORT PAYMENT ADJUSTMENT DISTRIBUTIONS BY STATE/COHORT

[Based on a 3-percent payment adjustment] 

State Number 

of HHAs 

Average 

payment 

adj. % 

10% 20% 30% 40% 50% 60% 70% 80% 90% 

HHA Cohort in States with no small cohorts (percent) 

AZ .................................................................... 114 ¥0.1 ¥1.3 ¥0.9 ¥0.7 ¥0.4 ¥0.2 0.1 0.5 0.7 1.1 

MD ................................................................... 51 0.1 ¥0.8 ¥0.8 ¥0.6 ¥0.4 0.1 0.4 0.5 0.8 1.0 


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TABLE 27—HHA COHORT PAYMENT ADJUSTMENT DISTRIBUTIONS BY STATE/COHORT—Continued 

[Based on a 3-percent payment adjustment] 

State Number 

of HHAs 

Average 

payment 

adj. % 

10% 20% 30% 40% 50% 60% 70% 80% 90% 

NC ................................................................... 163 ¥0.1 ¥1.3 ¥0.9 ¥0.5 ¥0.2 0.0 0.2 0.4 0.7 0.9 

TN .................................................................... 123 ¥0.1 ¥1.3 ¥1.0 ¥0.7 ¥0.4 ¥0.1 0.2 0.3 0.6 1.0 

WA ................................................................... 57 ¥0.1 ¥1.0 ¥0.8 ¥0.6 ¥0.2 ¥0.2 0.0 0.3 0.3 0.8 

Smaller-volume HHA Cohort in states with small cohort (percent) 

FL .................................................................... 82 0.1 ¥1.6 ¥1.3 ¥1.0 ¥0.6 ¥0.2 0.6 0.9 1.5 2.2 

IA ..................................................................... 26 ¥0.1 ¥1.1 ¥1.0 ¥0.9 ¥0.6 ¥0.3 0.0 0.4 0.8 1.5 

MA ................................................................... 16 ¥0.4 ¥1.7 ¥1.5 ¥1.5 ¥1.1 ¥0.8 ¥0.4 0.3 0.8 2.3 

NE ................................................................... 16 0.2 ¥1.6 ¥1.5 ¥1.0 ¥0.1 0.2 0.6 1.1 1.2 2.7 

Large-volume HHA Cohort in states with small cohort (percent) 

FL .................................................................... 706 0.1 ¥1.2 ¥0.8 ¥0.5 ¥0.3 0.0 0.2 0.6 1.0 1.7 

IA ..................................................................... 99 ¥0.2 ¥1.4 ¥1.1 ¥0.8 ¥0.5 ¥0.3 0.0 0.3 0.7 1.2 

MA ................................................................... 124 ¥0.2 ¥1.5 ¥1.1 ¥0.8 ¥0.6 ¥0.3 0.0 0.3 0.6 1.1 

NE ................................................................... 45 0.0 ¥1.4 ¥0.7 ¥0.6 ¥0.2 0.1 0.3 0.7 0.9 1.2 

Notes: Based on measure performance data from Performance Year 1 (January 1, 2016 to December 31, 2016), the baseline year (January 1, 2015 to December 

31, 2015), and home health Medicare claims data from 2015. 

TABLE 28—PAYMENT ADJUSTMENT DISTRIBUTIONS BY CHARACTERISTICS

[Based on a 3-percent payment adjustment]1

Cohort Number of 

HHAs 

Average payment adj. % 10% 20% 30% 40% 50% 60% 70% 80% 90% 

Small HHA (<60 patients in CY 2015) ............ 150 0.0 ¥1.6 ¥1.4 ¥1.0 ¥0.6 ¥0.3 0.2 0.7 1.2 2.2 

Large HHA (≥60 patients in CY 2015) ............ 1,465 0.0 ¥1.2 ¥0.9 ¥0.6 ¥0.3 ¥0.1 0.2 0.5 0.8 1.4 

Low % Dually-Eligible ..................................... 403 0.1 ¥1.1 ¥0.8 ¥0.5 ¥0.2 0.1 0.3 0.6 0.9 1.4 

Medium % Dually-Eligible ............................... 809 ¥0.1 ¥1.3 ¥0.9 ¥0.6 ¥0.4 ¥0.1 0.1 0.4 0.6 1.0 

High % Dually-Eligible ..................................... 403 0.1 ¥1.5 ¥1.1 ¥0.8 ¥0.5 ¥0.1 0.3 0.7 1.3 2.1 

Low Acuity ....................................................... 403 ¥0.3 ¥1.6 ¥1.2 ¥1.0 ¥0.7 ¥0.4 ¥0.1 0.2 0.6 1.1 

Mid Acuity ........................................................ 809 0.0 ¥1.2 ¥0.9 ¥0.6 ¥0.4 ¥0.1 0.1 0.4 0.7 1.2 

High Acuity ...................................................... 403 0.4 ¥1.1 ¥0.6 ¥0.3 0.0 0.3 0.6 0.9 1.4 2.1 

All non-rural beneficiaries ............................... 956 0.1 ¥1.3 ¥0.9 ¥0.6 ¥0.3 0.0 0.3 0.6 1.0 1.7 

Up to 35% rural beneficiaries ......................... 384 ¥0.1 ¥1.3 ¥0.9 ¥0.6 ¥0.3 ¥0.1 0.1 0.4 0.7 1.0 

Over 35% rural beneficiaries .......................... 275 ¥0.1 ¥1.3 ¥1.0 ¥0.7 ¥0.4 ¥0.2 0.0 0.2 0.7 1.2 

Non-Profit HHAs .............................................. 295 0.1 ¥1.1 ¥0.8 ¥0.5 ¥0.2 0.0 0.3 0.6 0.9 1.3 

For-Profit HHAs ............................................... 1,211 0.0 ¥1.4 ¥1.0 ¥0.6 ¥0.4 ¥0.1 0.2 0.5 0.8 1.5 

Government HHAs .......................................... 109 ¥0.2 ¥1.1 ¥0.9 ¥0.8 ¥0.5 ¥0.3 0.0 0.1 0.4 1.0 

Freestanding ................................................... 1,460 0.0 ¥1.3 ¥0.9 ¥0.6 ¥0.4 ¥0.1 0.2 0.5 0.8 1.5 

Facility-based .................................................. 155 ¥0.1 ¥1.3 ¥0.9 ¥0.6 ¥0.3 ¥0.1 0.1 0.3 0.7 1.0 

Notes: 

1 Rural beneficiaries identified based on the CBSA code reported on the claim. Acuity is based on the average case-mix weight for non-LUPA episodes. Low acuity 

is defined as the bottom 25 percent (among HHVBP Model participants); mid-acuity is the middle 50 percent and high acuity is the highest 25 percent. Note that at 

the time of the analysis, seven HHAs were missing information needed for the stratifications in this table. 

TABLE 29—IMPACT OF CHANGING MINIMUM REQUIRED SAMPLE SIZE FOR HHCAHPS PERFORMANCE MEASURES ON

AVERAGE TPS AND PAYMENT ADJUSTMENT RANGE* 

State HHA 

count 

Average TPS Minimum payment 

adjustment 

Maximum payment 

adjustment 

20 

Minimum 

40 

Minimum Difference 

% 

Difference 

20 

Minimum 

(%) 

40 

Minimum 

(%) 

20 

Minimum 

(%) 

40 

Minimum 

(%) 

Larger-volume HHAS 

AZ .............................................................. 107 42.160 42.924 0.765 1.8 ¥2.3 ¥2.3 2.8 2.7 

FL .............................................................. 706 39.110 39.731 0.621 1.6 ¥2.5 ¥2.5 3.0 3.0 

IA ............................................................... 99 43.191 43.186 ¥0.005 0.0 ¥2.1 ¥2.1 2.0 2.4 

MA ............................................................. 124 41.380 41.256 ¥0.125 ¥0.3 ¥2.6 ¥2.5 2.4 2.5 

MD ............................................................. 50 49.179 49.549 0.370 0.7 ¥1.3 ¥1.3 2.0 2.0 

NC ............................................................. 163 45.798 46.187 0.390 0.8 ¥2.1 ¥2.1 2.9 2.9 

NE ............................................................. 45 42.252 43.028 0.776 1.8 ¥2.1 ¥2.1 2.6 2.4 

TN .............................................................. 119 47.462 47.540 0.078 0.2 ¥2.5 ¥2.3 1.6 2.1 

WA ............................................................. 57 51.840 51.712 ¥0.128 ¥0.2 ¥1.5 ¥1.6 1.1 1.1 

Total ................................................... 1,470 .................... .................... .................... ................ ................ ................ .................... ....................

Smaller-volume HHAS 

AZ .............................................................. 7 36.706 36.706 0.000 0.0 ¥1.8 ¥1.9 1.0 1.0 

FL .............................................................. 82 42.810 42.810 0.000 0.0 ¥2.3 ¥2.3 2.9 2.9 

IA ............................................................... 26 38.663 38.663 0.000 0.0 ¥1.8 ¥1.8 2.2 2.2 

MA ............................................................. 16 25.004 25.004 0.000 0.0 ¥1.7 ¥1.7 2.3 2.3 


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TABLE 29—IMPACT OF CHANGING MINIMUM REQUIRED SAMPLE SIZE FOR HHCAHPS PERFORMANCE MEASURES ON

AVERAGE TPS AND PAYMENT ADJUSTMENT RANGE*—Continued 

State HHA 

count 

Average TPS Minimum payment 

adjustment 

Maximum payment 

adjustment 

20 

Minimum 

40 

Minimum Difference 

% 

Difference 

20 

Minimum 

(%) 

40 

Minimum 

(%) 

20 

Minimum 

(%) 

40 

Minimum 

(%) 

MD ............................................................. 1 61.135 61.135 0.000 0.0 0.8 0.8 0.8 0.8 

NE ............................................................. 16 37.485 37.485 0.000 0.0 ¥2.6 ¥2.6 3.0 3.0 

TN .............................................................. 4 39.983 39.983 0.000 0.0 ¥1.8 ¥1.8 1.9 1.9 

Total ................................................... 152 .................... .................... .................... ................ ................ ................ .................... ....................

Total ................................................... 1,622 .................... .................... .................... ................ ................ ................ .................... ....................

* OASIS, claims and HHCAHPS measures run from January 1, 2016 to December 31, 2016 for Performance Year 1. The baseline year is January 1, 2015 to December 31, 2015. Payment based on 2015 Medicare home health claims data. North Carolina and Washington did not have any smaller-volume HHAs. 

3. HH QRP 

Failure to submit data required under 

section 1895(b)(3)(B)(v) 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 HHA 

that does not comply with the 

requirements established by the 

Secretary. At the time that this analysis 

was prepared, 1,206, or approximately 

9.9 percent, of the 12,149 active 

Medicare-certified HHAs, did not 

receive the full annual percentage 

increase for CY 2017 because they did 

not meet the requirements of the HH 

QRP. Information is not available to 

determine the precise number of HHAs 

that will not meet the requirements to 

receive the full annual percentage 

increase for the CY 2018 payment 

determination. 

As noted in section VII.B. of this final 

rule, the net effect of our provisions is 

an estimated decrease in cost associated 

with changes to the HH QRP on average 

of $12,016.33 per HHA annually, or 

$145,986,343.50 for all HHAs annually. 

Comment: A commenter stated that 

CMS had underestimated the cost of 

changes to the OASIS, adding that CMS 

had not considered training and 

opportunity costs related to data set 

changes. 

Response: Our burden estimates 

reflect the burden on data submission. 

We intend to provide educational 

resources on the OASIS changes, 

including training and guidance, to 

providers at no cost. 

D. Accounting Statements and Tables 

As required by OMB Circular A–4 

(available at http://

www.whitehouse.gov/omb/circulars_

a004_a-4), in Table 30, we have 

prepared an accounting statement 

showing the classification of the 

transfers and costs associated with the 

HH PPS provisions of this final rule. 

Table 30 provides our best estimate of 

the decrease in Medicare payments 

under the HH PPS as a result of the 

changes presented in this final rule for 

the HH PPS provisions in CY 2018. 

Table 31 provides our best estimates of 

the changes associated with the HH QRP 

provisions. 

TABLE 30—ACCOUNTING STATEMENT: 

HH PPS CLASSIFICATION OF ESTIMATED TRANSFERS, FROM CY 2017 

TO 2018 

Category Transfers 

Annualized Monetized 

Transfers.

¥$80 million. 

From Whom to 

Whom? 

Federal Government 

to HHAs. 

TABLE 31—ACCOUNTING STATEMENT: HH QRP CLASSIFICATION OF ESTIMATED COSTS, FROM CY 2018 TO 2019 

Category Costs 

Annualized Monetized Net Burden for HHAs Submission of the OASIS ¥$146.0 million. 

E. Reducing Regulation and Controlling 

Regulatory Costs 

Executive Order 13771, entitled 

Reducing Regulation and Controlling 

Regulatory Costs (82 FR 9339), was 

issued on January 30, 2017. This final 

rule is considered an E.O. 13771 

deregulatory action. Details on the 

estimated cost savings of this proposed 

rule can be found in the rule’s PRA and 

economic analysis. 

F. Conclusion 

1. HH PPS 

In conclusion, we estimate that the 

net impact of the HH PPS policies in 

this final rule is a decrease of 0.4 

percent, or $80 million, in Medicare 

payments to HHAs for CY 2018. The 

¥$80 million impact reflects the effects 

of a 0.5 percent reduction in payments 

due to the sunset of the rural add-on 

provision ($100 million decrease), a 1 

percent CY 2018 HH payment update 

percentage ($190 million increase), and 

a 0.9 percent decrease in payments due 

to the 0.97 percent reduction to the 

national, standardized 60-day episode 

payment rate in CY 2017 to account for 

nominal case-mix growth ($170 million 

decrease). 

2. HHVBP Model 

In conclusion, we estimate there will 

be no net impact (to include either a net 

increase or reduction in payments) in 

this final rule in Medicare payments to 

HHAs competing in the HHVBP Model 

for CY 2018. However, the overall 

economic impact of the HHVBP Model 

is an estimated $378 million in total 

savings from a reduction in unnecessary 

hospitalizations and SNF usage as a 

result of greater quality improvements 

in the home health industry over the life 

of the HHVBP Model. 

3. HH QRP 

In conclusion, for CY 2019 we 

estimate that there will be a total 

decrease in costs of $145,986,343.50 

associated with the changes to the HH 

QRP. 

This analysis, together with the 

remainder of this preamble, provides 

afinal Regulatory Flexibility Analysis. 


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VIII. Federalism Analysis 

Executive Order 13132 on Federalism 

(August 4, 1999) 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. We have 

reviewed this final rule under the 

threshold criteria of Executive Order 

13132, Federalism, and have 

determined that it will not have 

substantial direct effects on the rights, 

roles, and responsibilities of states, local 

or tribal governments. 

In accordance with the provisions of 

Executive Order 12866, this final rule 

was reviewed by the Office of 

Management and Budget. 

List of Subjects for 42 CFR Part 484 

Health facilities, Health professions, 

Medicare, Reporting and recordkeeping 

requirements. 

For the reasons set forth in the 

preamble, the Centers for Medicare & 

Medicaid Services amends 42 CFR part 

484 as set forth below: 

PART 484—HOME HEALTH SERVICES 

■ 1. The authority citation for part 484 

continues to read as follows: 

Authority: Secs 1102 and 1871 of the Act 

(42 U.S.C. 1302 and 1395(hh)) unless 

otherwise indicated. 

■ 2. Section 484.250 is amended by 

revising paragraph (a)(1) and adding 

paragraphs (d) through (f) to read as 

follows: 

§ 484.250 Patient assessment data. 

(a) * * * 

(1) The OASIS data described at 

§ 484.55(b) and (d) for CMS to 

administer the payment rate 

methodologies described in §§ 484.215, 

484.220, 484. 230, 484.235, and 484.240; 

and to meet the quality reporting 

requirements of section 1895(b)(3)(B)(v) 

of the Act. 

* * * * * 

(d) Exceptions and extension 

requirements. (1) A HHA may request 

and CMS may grant exceptions or 

extensions to the reporting requirements 

under section 1895(b)(3)(B)(v) of the Act 

for one or more quarters, when there are 

certain extraordinary circumstances 

beyond the control of the HHA. 

(2) A HHA may request an exception 

or extension within 90 days of the date 

that the extraordinary circumstances 

occurred by sending an email to CMS 

HHAPU reconsiderations at 

HHAPUReconsiderations@cms.hhs.gov 

that contains all of the following 

information: 

(i) HHA CMS Certification Number 

(CCN). 

(ii) HHA Business Name. 

(iii) HHA Business Address. 

(iv) CEO or CEO-designated personnel 

contact information including name, 

telephone number, title, email address, 

and mailing address (the address must 

be a physical address, not a post office 

box). 

(v) HHA’s reason for requesting the 

exception or extension. 

(vi) Evidence of the impact of 

extraordinary circumstances, including, 

but not limited to, photographs, 

newspaper, and other media articles. 

(vii) Date when the HHA believes it 

will be able to again submit data under 

section 1895(b)(3)(B)(v) of the Act and a 

justification for the proposed date. 

(3) Except as provided in paragraph 

(d)(4) of this section, CMS will not 

consider an exception or extension 

request unless the HHA requesting such 

exception or extension has complied 

fully with the requirements in this 

paragraph (d). 

(4) CMS may grant exceptions or 

extensions to HHAs without a request if 

it determines that one or more of the 

following has occurred: 

(i) An extraordinary circumstance 

affects an entire region or locale. 

(ii) A systemic problem with one of 

CMS’s data collection systems directly 

affected the ability of a HHA to submit 

data under section 1895(b)(3)(B)(v) of 

the Act. 

(e) Reconsideration. (1) HHAs that do 

not meet the quality reporting 

requirements under section 

1895(b)(3)(B)(v) of the Act for a program 

year will receive a letter of noncompliance via the United States Postal 

Service and notification in CASPER. An 

HHA may request reconsideration no 

later than 30 calendar days after the date 

identified on the letter of noncompliance. 

(2) Reconsideration requests may be 

submitted to CMS by sending an email 

to CMS HHAPU reconsiderations at 

HHAPureConsiderations@cms.hhs.gov 

containing all of the following 

information: 

(i) HHA CCN. 

(ii) HHA Business Name. 

(iii) HHA Business Address. 

(iv) CEO or CEO-designated personnel 

contact information including name, 

telephone number, title, email address, 

and mailing address (the address must 

be a physical address, not a post office 

box). 

(v) CMS identified reason(s) for noncompliance from the non-compliance 

letter. 

(vi) Reason(s) for requesting 

reconsideration, including all 

supporting documentation. 

(3) CMS will not consider an 

exception or extension request unless 

the HHA has complied fully with the 

requirements in paragraph (e)(2) of this 

section. 

(4) CMS will make a decision on the 

request for reconsideration and provide 

notice of the decision to the HHA 

through CASPER and via letter sent via 

the United States Postal Service. 

(f) Appeals. (1) A HHA that is 

dissatisfied with CMS’ decision on a 

request for reconsideration submitted 

under paragraph (e) of this section may 

file an appeal with the Provider 

Reimbursement Review Board (PRRB) 

under 42 CFR part 405, subpart R. 

(2) [Reserved] 

■ 3. Section 484.305 is amended by 

revising the definition of ‘‘Applicable 

measure’’ to read as follows: 

§ 484.305 Definitions. 

* * * * * 

Applicable measure means a measure 

for which a competing HHA has 

provided a minimum of— 

(1) Twenty home health episodes of 

care per year for the OASIS-based 

measures; 

(2) Twenty home health episodes of 

care per year for the claims-based 

measures; or 

(3) Forty completed surveys for the 

HHCAHPS measures. 

* * * * * 

Dated: October 23, 2017. 

Seema Verma, 

Administrator, Centers for Medicare & 

Medicaid Services. 

Dated: October 24, 2017. 

Eric D. Hargan, 

Acting Secretary, Department of Health and 

Human Services. 

[FR Doc. 2017–23935 Filed 11–1–17; 4:15 pm] 

BILLING CODE 4120–01–P 


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