Medicare and Medicaid Programs; CY 2016 Home Health Prospective Payment System Rate Update; Home Health Value-Based Purchasing Model; and Home Health Quality Reporting Requirements, 68623-68719 [2015-27931]
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Vol. 80
Thursday,
No. 214
November 5, 2015
Part II
Department of Health and Human Services
tkelley on DSK3SPTVN1PROD with RULES2
Centers for Medicare & Medicaid Services
42 CFR Part 409, 424, and 484
Medicare and Medicaid Programs; CY 2016 Home Health Prospective
Payment System Rate Update; Home Health Value-Based Purchasing
Model; and Home Health Quality Reporting Requirements; Final Rule
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Federal Register / Vol. 80, No. 214 / Thursday, November 5, 2015 / Rules and Regulations
information about the HH quality
reporting program. Lori Teichman, (410)
786–6684, for information about
HHCAHPS. Robert Flemming, (844)
280–5628, or send your inquiry via
email to HHVBPquestions@cms.hhs.gov
for information about the HHVBP
Model.
SUPPLEMENTARY INFORMATION:
DEPARTMENT OF HEALTH AND
HUMAN SERVICES
Centers for Medicare & Medicaid
Services
42 CFR Parts 409, 424, and 484
[CMS–1625–F]
RIN 0938–AS46
Medicare and Medicaid Programs; CY
2016 Home Health Prospective
Payment System Rate Update; Home
Health Value-Based Purchasing Model;
and Home Health Quality Reporting
Requirements
Centers for Medicare &
Medicaid Services (CMS), HHS.
ACTION: Final rule.
AGENCY:
This final rule will update
Home Health Prospective Payment
System (HH PPS) rates, including the
national, standardized 60-day episode
payment rates, the national per-visit
rates, and the non-routine medical
supply (NRS) conversion factor under
the Medicare prospective payment
system for home health agencies
(HHAs), effective for episodes ending on
or after January 1, 2016. As required by
the Affordable Care Act, this rule
implements the 3rd year of the 4-year
phase-in of the rebasing adjustments to
the HH PPS payment rates. This rule
updates the HH PPS case-mix weights
using the most current, complete data
available at the time of rulemaking and
provides a clarification regarding the
use of the ‘‘initial encounter’’ seventh
character applicable to certain ICD–10–
CM code categories. This final rule will
also finalize 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 (nominal
case-mix growth) between CY 2012 and
CY 2014. In addition, this rule
implements a HH value-based
purchasing (HHVBP) model, beginning
January 1, 2016, in which all Medicarecertified HHAs in selected states will be
required to participate. Finally, this rule
finalizes minor changes to the home
health quality reporting program and
minor technical regulations text
changes.
DATES: Effective Date: These regulations
are effective on January 1, 2016.
FOR FURTHER INFORMATION CONTACT: For
general information about the HH PPS
please send your inquiry via email to:
HomehealthPolicy@cms.hhs.gov.
Michelle Brazil, (410) 786–1648 or
Theresa White, (410) 786–2394 for
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SUMMARY:
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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. System for Payment of Home Health
Services
C. Updates to the Home Health Prospective
Payment System
D. Advancing Health Information Exchange
III. Provisions of the Proposed Rule and
Response to Comments
A. Monitoring for Potential Impacts—
Affordable Care Act Rebasing
Adjustments
B. CY 2016 HH PPS Case-Mix Weights and
Reduction to the National, Standardized
60-day Episode Payment Rate to Account
for Nominal Case-Mix Growth
1. CY 2016 HH PPS Case-Mix Weights
2. Reduction to the National, Standardized
60-day Episode Payment Rate to Account
for Nominal Case-Mix Growth
3. Clarification Regarding the Use of the
‘‘Initial Encounter’’ Seventh Character,
Applicable to Certain ICD–10–CM Code
Categories, under the HH PPS
C. CY 2016 Home Health Rate Update
1. CY 2016 Home Health Market Basket
Update
2. CY 2016 Home Health Wage Index
3. CY 2016 Annual Payment Update
D. Payments for High-Cost Outliers Under
the HH PPS
E. Report to the Congress on the Home
Health Study Required by Section
3131(d) of the Affordable Care Act and
an Update on Subsequent Research and
Analysis
F. Technical Regulations Text Changes
IV. Provisions of the Home Health ValueBased Purchasing (HHVBP) Model and
Response to Comments
A. Background
B. Overview
C. Selection Methodology
1. Identifying a Geographic Demarcation
Area Overview of the Randomized
Selection Methodology for States
D. Performance Assessment and Payment
Periods
1. Performance Reports
2. Payment Adjustment Timeline
E. Quality Measures
1. Objectives
2. Methodology for Selection of Quality
Measures
3. Selected Measures
4. Additional Information on HHCAHPS
5. New Measures
6. HHVBP Model’s Four Classifications
7. Weighting
F. Performance Scoring Methodology
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1. Performance Calculation Parameters
2. Considerations for Calculating the Total
Performance Score
3. Additional Considerations for the
HHVBP Total Performance Scores
4. Setting Performance Benchmarks and
Thresholds
5. Calculating Achievement and
Improvement Points
6. Scoring Methodology for New Measures
7. Minimum Number of Cases for Outcome
and Clinical Quality Measures
G. The Payment Adjustment Methodology
H. Preview and Period To Request
Recalculation
I. Evaluation
V. Provisions of the Home Health Care
Quality Reporting Program (HH QRP)
and Response to Comments
A. Background and Statutory Authority
B. General Considerations Used for the
Selection of Quality Measures for the HH
QRP
C. HH QRP Quality Measures and
Measures Under Consideration for
Future Years
D. Form, Manner, and Timing of OASIS
Data Submission and OASIS Data for
Annual Payment Update
1. Statutory Authority
2. Home Health Quality Reporting Program
Requirements for CY 2016 Payment and
Subsequent Years
3. Previously Established Pay-for-Reporting
Performance Requirement for
Submission of OASIS Quality Data
E. Home Health Care CAHPS Survey
(HHCAHPS)
1. Background and Description of
HHCAHPS
2. HHCAHPS Oversight Activities
3. HHCAHPS Requirements for the CY
2016 APU
4. HHCAHPS Requirements for the CY
2017 APU
5. HHCAHPS Requirements for the CY
2018 APU
6. HHCAHPS Reconsideration and Appeals
Process
7. Summary
F. Public Display of Home Health Quality
Data for the HH QRP
VI. Collection of Information Requirements
VII. Regulatory Impact Analysis
VIII. Federalism Analysis
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
APU Annual Payment Update
BBA Balanced Budget Act of 1997, Pub. L.
105–33
BBRA Medicare, Medicaid, and SCHIP
Balanced Budget Refinement Act of 1999,
Pub. L. 106–113
CAD Coronary Artery Disease
CAH Critical Access Hospital
CBSA Core-Based Statistical Area
CASPER Certification and Survey Provider
Enhanced Reports
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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, Pub. L.
109–171, enacted February 8, 2006
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
HHCAHPS Home Health Care Consumer
Assessment of Healthcare Providers and
Systems Survey
HH PPS Home Health Prospective Payment
System
HHRG Home Health Resource Group
HHVBP Home Health Value-Based
Purchasing
HIPPS Health Insurance Prospective
Payment System
HVBP Hospital Value-Based Purchasing
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)
IRF Inpatient Rehabilitation Facility
LEF Linear Exchange Function
LTCH Long-Term Care Hospital
LUPA Low-Utilization Payment Adjustment
MEPS Medical Expenditures Panel Survey
MMA Medicare Prescription Drug,
Improvement, and Modernization Act of
2003, Pub. L. 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, Pub. L. 100–203, enacted
December 22, 1987
OCESAA Omnibus Consolidated and
Emergency Supplemental Appropriations
Act, Pub. L. 105–277, enacted October 21,
1998
OES Occupational Employment Statistics
OIG Office of Inspector General
OT Occupational Therapy
OMB Office of Management and Budget
MFP Multifactor productivity
PAMA Protecting Access to Medicare Act of
2014
PAC–PRD Post-Acute Care Payment Reform
Demonstration
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PEP Partial Episode Payment Adjustment
PT Physical Therapy
PY Performance Year
PRRB Provider Reimbursement Review
Board
QAP Quality Assurance Plan
RAP Request for Anticipated Payment
RF Renal Failure
RFA Regulatory Flexibility Act, Pub. L. 96–
354
RHHIs Regional Home Health
Intermediaries
RIA Regulatory Impact Analysis
SAF Standard Analytic File
SLP Speech-Language Pathology
SN Skilled Nursing
SNF Skilled Nursing Facility
TPS Total Performance Score
UMRA Unfunded Mandates Reform Act of
1995.
VBP Value-Based Purchasing
I. Executive Summary
A. Purpose
This final rule will update the
payment rates for HHAs for calendar
year (CY) 2016, as required under
section 1895(b) of the Social Security
Act (the Act). This reflects the 3rd year
of the 4-year phase-in of the rebasing
adjustments to the national,
standardized 60-day episode payment
rate, the national per-visit rates, and the
NRS conversion factor finalized in the
CY 2014 HH PPS final rule (78 FR
72256), as required under section
3131(a) of the Patient Protection and
Affordable Care Act of 2010 (Pub. L.
111–148), as amended by the Health
Care and Education Reconciliation Act
of 2010 (Pub. L. 111–152) (collectively
referred to as the ‘‘Affordable Care
Act’’).
This rule will update the case-mix
weights under section 1895(b)(4)(A)(i)
and (b)(4)(B) of the Act and provides a
clarification regarding the use of the
‘‘initial encounter’’ seventh character
applicable to certain ICD–10–CM code
categories. This final rule will finalize
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 casemix growth unrelated to increases in
patient acuity (nominal case-mix
growth) between CY 2012 and CY 2014
under the authority of section
1895(b)(3)(B)(iv) of the Act. In addition,
this rule finalizes our proposal to
implement an HH Value-Based
Purchasing (VBP) model, in which
certain Medicare-certified HHAs are
required to participate, beginning
January 1, 2016 under the authority of
section 1115A of the Act. Finally, this
rule will finalize changes to the home
health quality reporting program
requirements under section
1895(b)(3)(B)(v)(II) of the Act and will
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finalize minor technical regulations text
changes in 42 CFR parts 409, 424, and
484 to better align the payment
requirements with recent statutory and
regulatory changes for home health
services.
B. Summary of the Major Provisions
As required by section 3131(a) of the
Affordable Care Act, and finalized in the
CY 2014 HH final rule, ‘‘Medicare and
Medicaid Programs; Home Health
Prospective Payment System Rate
Update for 2014, Home Health Quality
Reporting Requirements, and Cost
Allocation of Home Health Survey
Expenses’’ (78 FR 77256, December 2,
2013), we are implementing the 3rd 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 in section
III.C.3. The rebasing adjustments for CY
2016 will reduce the national,
standardized 60-day episode payment
amount by $80.95, increase the national
per-visit payment amounts by 3.5
percent of the national per-visit
payment amounts in CY 2010 with the
increases ranging from $1.79 for home
health aide services to $6.34 for medical
social services, and reduce the NRS
conversion factor by 2.82 percent.
In the CY 2015 HH PPS final rule (79
FR 66072), we finalized our proposal to
recalibrate the case-mix weights every
year with more current data. In section
III.B.1 of this rule, we are recalibrating
the HH PPS case-mix weights, using the
most current cost and utilization data
available, in a budget neutral manner. In
addition, in section III.B.2 of this rule,
we are finalizing 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
(nominal case-mix growth) between CY
2012 and CY 2014. In section III.B.3 of
this rule we are providing a clarification
regarding the use of the ‘‘initial
encounter’’ seventh character,
applicable to certain ICD–10–CM code
categories, under the HH PPS. In section
III.C.1 of this rule, we are updating the
payment rates under the HH PPS by the
home health payment update percentage
of 1.9 percent (using the 2010-based
Home Health Agency (HHA) market
basket update of 2.3 percent, minus 0.4
percentage point for productivity as
required by section 1895(b)(3)(B)(vi)(I)
of the Act. In the CY 2015 final rule (79
FR 66083 through 66087), we
incorporated new geographic area
designations, set out in a February 28,
2013 Office of Management and Budget
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(OMB) bulletin, into the home health
wage index. For CY 2015, we
implemented a wage index transition
policy consisting of a 50/50 blend of the
old geographic area delineations and the
new geographic area delineations. In
section III.C.2 of this rule, we will
update the CY 2016 home health wage
index using solely the new geographic
area designations. In section III.D of this
final rule, we discuss payments for high
cost outliers. In section III.E, we are
finalizing several technical corrections
in 42 CFR parts 409, 424, and 484, to
better align the payment requirements
with recent statutory and regulatory
changes for home health services. The
sections include §§ 409.43(e), 424.22(a),
484.205(d), 484.205(e), 484.220,
484.225, 484.230, 484.240(b),
484.240(e), 484.240(f), 484.245.
In section IV of this rule, we are
finalizing our proposal to implement a
HHVBP model that will begin on
January 1, 2016. Medicare-certified
HHAs selected for inclusion in the
HHVBP model will be required to
compete for payment adjustments to
their current PPS reimbursements based
on quality performance. A competing
HHA is defined as an agency that has a
current Medicare certification and that
is being paid by CMS for home health
care delivered within any of the states
selected in accordance with the HHVBP
Model’s selection methodology.
Finally, section V of this rule includes
changes to the home health quality
reporting program, including one new
quality measure, the establishment of a
minimum threshold for submission of
Outcome and Assessment Information
Set (OASIS) assessments for purposes of
quality reporting compliance, and
submission dates for Home Health Care
Consumer Assessment of Healthcare
Providers and Systems Survey
(HHCAHPS) Survey through CY 2018.
C. Summary of Costs and Transfers
TABLE 1—SUMMARY OF COSTS AND TRANSFERS
Provision description
Costs
CY 2016 HH PPS Payment Rate Update
...........................
CY 2016 HHVBP Model .........................
...........................
II. Background
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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 HH
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 HH services provided
under a plan of care (POC) that were
paid on a reasonable cost basis by
adding section 1895 of the Social
Security Act (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 HH services paid
under Medicare.
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.
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Transfers
The overall economic impact of the HH PPS payment rate update is an estimated ¥$260 million (¥1.4 percent) in payments to HHAs.
The overall economic impact of the HHVBP model provision for CY 2018
through 2022 is an estimated $380 million in total savings from a reduction in
unnecessary hospitalizations and SNF usage as a result of greater quality
improvements in the HH industry. As for payments to HHAs, there are no aggregate increases or decreases to the HHAs competing in the model.
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 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 HH 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 Patient
Protection and Affordable Care Act of
2010 (the Affordable Care Act) (Pub. L.
111–148, enacted March 23, 2010)
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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 HH services as required
by section 4603 of the BBA, as
subsequently amended by section 5101
of the Omnibus Consolidated and
Emergency Supplemental
Appropriations Act (OCESAA) for Fiscal
Year 1999, (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 (BBRA) of 1999, (Pub. L. 106–113,
enacted November 29, 1999). The
requirements include the
implementation of a HH PPS for HH
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 HH
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).
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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 HH 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 pay-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
Medicare Access and CHIP
Reauthorization Act of 2015 (MACRA)
(Public Law 114–10) amended section
421(a) of the MMA to extend the rural
add-on for two 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 HH 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.
B. System for Payment of Home Health
Services
Generally, Medicare 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 HH
disciplines (skilled nursing, HH aide,
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physical therapy, speech-language
pathology, occupational therapy, and
medical social services). Payment for
non-routine supplies (NRS) is no longer
part of the national standardized 60-day
episode rate and is computed by
multiplying the relative weight for a
particular NRS severity level by the NRS
conversion factor (See section II.D.4.e).
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 case-mix 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.
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 HH 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 HH patients. We
examined data on demographics, family
severity, and non-HH Part A Medicare
expenditures to predict the average
case-mix weight for 2005. We identified
8.03 percent of the total case-mix
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68627
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 a 1.32
percent reduction to the payment rates
for CY 2013 to account for nominal
case-mix growth from 2000 through
2010. When taking into account the total
measure of case-mix 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
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Federal Register / Vol. 80, No. 214 / Thursday, November 5, 2015 / Rules and Regulations
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
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 as reflected in
Table 2, 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 speech-language
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 2nd 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.
TABLE 2—MAXIMUM ADJUSTMENTS TO THE NATIONAL PER-VISIT PAYMENT RATES
[Not to exceed 3.5 percent of the amount(s) in CY 2010]
2010 National per-visit
payment rates
Maximum adjustments
per year
(CY 2014 through CY
2017)
$113.01
51.18
123.57
124.40
134.27
181.16
$3.96
1.79
4.32
4.35
4.70
6.34
Skilled Nursing .................................................................................................................................
Home Health Aide ...........................................................................................................................
Physical Therapy .............................................................................................................................
Occupational Therapy ......................................................................................................................
Speech-Language Pathology ..........................................................................................................
Medical Social Services ...................................................................................................................
tkelley on DSK3SPTVN1PROD with RULES2
D. Advancing Health Information
Exchange
HHS has a number of initiatives
designed to encourage and support the
adoption of health information
technology and to promote nationwide
health information exchange to improve
health care. As discussed in the August
2013 Statement ‘‘Principles and
Strategies for Accelerating Health
Information Exchange’’ (available at
https://www.healthit.gov/sites/default/
files/acceleratinghieprinciples_
strategy.pdf), HHS believes that all
individuals, their families, their
healthcare and social service providers,
and payers should have consistent and
timely access to health information in a
standardized format that can be securely
exchanged between the patient,
providers, and others involved in the
individual’s care. Health IT that
facilitates the secure, efficient, and
effective sharing and use of healthrelated information when and where it
is needed is an important tool for
settings across the continuum of care,
including home health. While home
health providers are not eligible for the
Medicare and Medicaid EHR Incentive
Programs, effective adoption and use of
health information exchange and health
IT tools will be essential as these
settings seek to improve quality and
lower costs through initiatives such as
value-based purchasing.
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The Office of the National
Coordinator for Health Information
Technology (ONC) has released a
document entitled ‘‘Connecting Health
and Care for the Nation: A Shared
Nationwide Interoperability Roadmap’’
(available at https://www.healthit.gov/
sites/default/files/hie-interoperability/
nationwide-interoperability-roadmapfinal-version-1.0.pdf). In the near term,
the Roadmap focuses on actions that
will enable individuals and providers
across the care continuum to send,
receive, find, and use a common set of
electronic clinical information at the
nationwide level by the end of 2017.
The Roadmap’s goals also align with the
Improving Medicare Post-Acute Care
Transformation Act of 2014 (Pub. L.
113–185) (IMPACT Act), which requires
assessment data to be standardized and
interoperable to allow for exchange of
the data. Moreover, the vision described
in the draft Roadmap significantly
expands the types of electronic health
information, information sources, and
information users well beyond clinical
information derived from electronic
health records (EHRs). The Roadmap
identifies four critical pathways that
health IT stakeholders should focus on
now in order to create a foundation for
long-term success: (1) Improve technical
standards and implementation guidance
for priority data domains and associated
elements; (2) rapidly shift and align
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federal, state, and commercial payment
policies from fee-for-service to valuebased models to stimulate the demand
for interoperability; (3) clarify and align
federal and state privacy and security
requirements that enable
interoperability; and (4) align and
promote the use of consistent policies
and business practices that support
interoperability, in coordination with
stakeholders. In addition, ONC has
released the draft version of the 2016
Interoperability Standards Advisory
(available at https://www.healthit.gov/
standards-advisory/2016), which
provides a list of the best available
standards and implementation
specifications to enable priority health
information exchange functions.
Providers, payers, and vendors are
encouraged to take these ‘‘best available
standards’’ into account as they
implement interoperable health
information exchange across the
continuum of care, including care
settings such as behavioral health, longterm and post-acute care, and home and
community-based service providers.
We encourage stakeholders to utilize
health information exchange and
certified health IT to effectively and
efficiently help providers improve
internal care delivery practices, engage
patients in their care, support
management of care across the
continuum, enable the reporting of
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Federal Register / Vol. 80, No. 214 / Thursday, November 5, 2015 / Rules and Regulations
electronically specified clinical quality
measures (eCQMs), and improve
efficiencies and reduce unnecessary
costs. As adoption of certified health IT
increases and interoperability standards
continue to mature, HHS will seek to
reinforce standards through relevant
policies and programs.
III. Provisions of the Proposed Rule and
Responses to Comments
We received 118 timely comments
from the public. The following sections,
arranged by subject area, include a
summary of the public comments
received, and our responses.
A. Monitoring for Potential Impacts—
Affordable Care Act Rebasing
Adjustments
tkelley on DSK3SPTVN1PROD with RULES2
In the CY 2016 HH PPS proposed rule
(80 FR 39840), we provided a summary
of analysis conducted on FY 2013 HHA
cost report data and how such data, if
used, would impact our estimate of the
percentage difference between Medicare
payments and HHA costs. In addition,
we also provided a summary of
MedPAC’s Report to the Congress on
home health payment rebasing and
presented information on Medicare
home health utilization using CY 2014
HHA claims data (the 1st year of the 4
year phase-in of the rebasing
adjustments mandated by section
3131(a) the Affordable Care Act). We
will continue to monitor the impact of
future payment and policy changes and
will provide the industry with periodic
updates on our analysis in future
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18:04 Nov 04, 2015
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rulemaking and/or announcements on
the HHA Center Web page at: https://
www.cms.gov/Center/Provider-Type/
Home-Health-Agency-HHA-Center.html.
B. CY 2016 HH PPS Case-Mix Weights
and Reduction to the National,
Standardized 60-day Episode Payment
Rate to Account for Nominal Case-Mix
Growth
1. CY 2016 HH PPS Case-Mix Weights
For CY 2014, as part of the rebasing
effort mandated by the Affordable Care
Act, we reset the HH PPS case-mix
weights, lowering the average case-mix
weight to 1.0000. To lower the HH PPS
case-mix weights to 1.0000, each HH
PPS case-mix weight was decreased by
the same factor (1.3464), thereby
maintaining the same relative values
between the weights. This ‘‘resetting’’ of
the HH PPS case-mix weights was done
in a budget neutral manner by inflating
the national, standardized 60-day
episode rate by the same factor (1.3464)
that was used to decrease the weights.
For CY 2015, 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 2016, we propose to 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
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68629
accurately as possible, current home
health resource use and changes in
utilization patterns.
To generate the proposed CY 2016 HH
PPS case-mix weights, we used CY 2014
home health claims data (as of
December 31, 2014) with linked OASIS
data. For this CY 2016 HH PPS final
rule, we used CY 2014 home health
claims data (as of June 30, 2015) with
linked OASIS data to generate the final
CY 2016 HH PPS case-mix weights.
These data are the most current and
complete data available at this time. The
tables below have been revised to reflect
the results using the updated data. The
process we used to calculate the HH
PPS case-mix weights are outlined
below.
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 Bureau of Labor
Statistics national hourly wage
(covering May 2014) plus fringe rates
(covering December 2014) 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 2014
data, are shown in Table 3. The points
for the clinical variables are added
together to determine an episode’s
clinical score. The points for the
functional variables are added together
to determine an episode’s functional
score.
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Federal Register / Vol. 80, No. 214 / Thursday, November 5, 2015 / Rules and Regulations
TABLE 3: Case-Mix Adjustment Variables and Scores
Case-Mix Ad"ustment Variables and Scores
Therapy visits
1
2
3
4
5
6
7
8
9
10
11
12
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13
VerDate Sep<11>2014
EQUATION:
CLINICAL DIMENSION
Primary or Other Diagnosis = Blindness/Low Vision
Primary or Other Diagnosis = Blood disorders
Primary or Other Diagnosis= Cancer, selected benign
neoplasms
Primary Diagnosis = Diabetes
Other Diagnosis = Diabetes
Primary or Other Diagnosis = Dysphagia
AND
Primary or Other Diagnosis= Neuro 3- Stroke
Primary or Other Diagnosis = Dysphagia
AND
M1030 (Therapy at home)= 3 (Enteral)
Primary or Other Diagnosis = Gastrointestinal
disorders
Primary or Other Diagnosis = Gastrointestinal
disorders
AND
M1630 (ostomy)= 1 or 2
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
Primary or Other Diagnosis = Heart Disease OR
Hypertension
Primary Diagnosis = N euro 1 - Brain disorders and
paralysis
Primary or Other Diagnosis= Neuro 1 -Brain
disorders and paralysis
AND
M1840 (Toilet transfer)= 2 or more
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E:\FR\FM\05NOR2.SGM
1 or
2
013
1
1 or
2
14+
2
3+
013
3
3+
14+
4
6
2
7
7
7
4
1
3
16
1
9
1
10
1
10
6
6
1
1
3
11
2
05NOR2
6
11
2
ER05NO15.000</GPH>
Episode number within sequence of adjacent episodes
68631
Federal Register / Vol. 80, No. 214 / Thursday, November 5, 2015 / Rules and Regulations
Case-Mix Adjustment Variables and Scores
Therapy visits
EQUATION:
14
15
16
17
18
19
20
tkelley on DSK3SPTVN1PROD with RULES2
21
22
23
VerDate Sep<11>2014
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
Primary or Other Diagnosis= Neuro 3- Stroke
Primary or Other Diagnosis= Neuro 3- Stroke AND
M1810 or M1820 (Dressing upper or lower body)= 1,
2, or 3
Primary or Other Diagnosis= Neuro 3- Stroke
AND
M1860 (Ambulation) = 4 or more
Primary or Other Diagnosis= Neuro 4- Multiple
Sclerosis AND AT LEAST ONE OF THE
FOLLOWING:
Ml830 (Bathing)= 2 or more
OR
Ml840 (Toilet transfer)= 2 or more
OR
Ml850 (Transferring)= 2 or more
OR
Ml860 (Ambulation) = 4 or more
Primary or Other Diagnosis = Ortho 1 - Leg Disorders
or Gait Disorders
AND
M1324 (most problematic pressure ulcer stage)= 1, 2,
3 or 4
Primary or Other Diagnosis = Ortho 1 - Leg OR Ortho
2 - Other orthopedic disorders
AND
M1030 (Therapy at home)= 1 (IV/Infusion) or 2
(Parenteral)
Primary or Other Diagnosis = Psych 1 -Affective and
other psychoses, depression
Primary or Other Diagnosis = Psych 2 - Degenerative
and other organic psychiatric disorders
Primary or Other Diagnosis = Pulmonary disorders
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E:\FR\FM\05NOR2.SGM
1 or
2
013
1 or
2
1
2
013
3
2
7
1
6
3
9
2
7
14+
3+
3+
14+
4
5
3
10
7
10
8
1
8
1
3
05NOR2
3
ER05NO15.001</GPH>
Episode number within sequence of adjacent episodes
68632
Federal Register / Vol. 80, No. 214 / Thursday, November 5, 2015 / Rules and Regulations
Case-Mix Adjustment Variables and Scores
tkelley on DSK3SPTVN1PROD with RULES2
Therapy visits
EQUATION:
Primary or Other Diagnosis = Pulmonary disorders
24
AND
M1860 (Ambulation) = 1 or more
Primary Diagnosis = Skin 1 -Traumatic wounds,
25
burns, and post-operative complications
Other Diagnosis = Skin 1 - Traumatic wounds, burns,
26
post-operative complications
Primary or Other Diagnosis = Skin 1 -Traumatic
wounds, burns, and post-operative complications OR
Skin 2 - Ulcers and other skin conditions
27
AND
M1030 (Therapy at home) = 1 (IV/Infusion) or 2
(Parenteral)
Primary or Other Diagnosis = Skin 2 - Ulcers and
28
other skin conditions
Primary or Other Diagnosis = Tracheostomy
29
Primary or Other Diagnosis= Urostomy/Cystostomy
30
M1030 (Therapy at home)= 1 (IV/Infusion) or 2
31
(Parenteral)
M1030 (Therapy at home)= 3 (Enteral)
32
M1200 (Vision)= 1 or more
33
34
M1242 (Pain)= 3 or 4
M1308 =Two or more pressure ulcers at stage 3 or 4
35
M1324 (Most problematic pressure ulcer stage)= 1 or
36
2
M1324 (Most problematic pressure ulcer stage)= 3 or
37
4
M1334 (Stasis ulcer status)= 2
38
M1334 (Stasis ulcer status)= 3
39
40
M1342 (Surgical wound status)= 2
41
M1342 (Surgical wound status)= 3
42
M1400 (Dyspnea) = 2, 3, or 4
43
M1620 (Bowel Incontinence)= 2 to 5
44
M1630 (Ostomy)= 1 or 2
M2030 (Injectable Drug Use)= 0, 1, 2, or 3
45
FUNCTIONAL DIMENSION
M1810 or M1820 (Dressing upper or lower body)= 1,
46
2, or 3
47
M1830 (Bathing)= 2 or more
M1840 (Toilet transferring)= 2 or more
48
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lor
2
013
1
1 or
2
3+
3+
14+
013
14+
2
3
4
3
19
8
19
6
16
8
13
2
17
9
17
3
17
19
3
17
12
17
6
17
4
15
2
5
5
5
1
5
14
4
19
7
17
8
33
11
27
4
7
2
1
13
17
8
7
1
4
12
8
10
5
5
13
17
13
8
1
4
7
4
2
6
1
05NOR2
2
1
2
4
5
1
1
ER05NO15.002</GPH>
Episode number within sequence of adjacent episodes
Federal Register / Vol. 80, No. 214 / Thursday, November 5, 2015 / Rules and Regulations
68633
steps. The categorizations for the steps
are as follows:
In updating the four-equation model
for CY 2016 using 2014 data (the last
update to the four-equation model for
CY 2015 used 2013 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 2013 and 2014. The CY 2016
four-equation model resulted in 124
point-giving variables being used in the
model (as compared to the 120 pointgiving variables for the 2015
recalibration). There were eight
variables that were added to the model
and four variables that were dropped
from the model due to the absence of
additional resources associated with the
variable. The points for 24 variables
increased in the CY 2016 four-equation
model and the points for 38 variables
decreased in the CY 2016 4-equation
model. There were 54 variables with the
same point values.
Step 2: Re-define the clinical and
functional thresholds so they are
reflective of the new points associated
with the CY 2016 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.
We then 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.1 Also, we looked at
the average resource use associated with
each clinical and functional score and
used that to guide where we placed our
thresholds. We tried to group 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 of the CY 2016
four-equation model points are shown
in Table 4.
1 For Step 1, 54% of episodes were in the medium
functional level (All with score 15). For Step 2.1,
77.2% of episodes were in the low functional level
(Most with score 2 and 4). For Step 2.2, 67.1% of
episodes were in the low functional level (All with
score 0). For Step 3, 60.9% of episodes were in the
medium functional level (Most with score 10). For
Step 4, 49.8% of episodes were in the low
functional level (Most with score 2).
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ER05NO15.003</GPH>
tkelley on DSK3SPTVN1PROD with RULES2
In updating the four-equation model
for CY 2016 using 2014 data (the last
update to the four-equation model for
CY 2015 used 2013 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 2013 and 2014. The CY 2016
four-equation model resulted in 124
point-giving variables being used in the
model (as compared to the 120 pointgiving variables for the 2015
recalibration). There were eight
variables that were added to the model
and four variables that were dropped
from the model due to the absence of
additional resources associated with the
variable. The points for 24 variables
increased in the CY 2016 four-equation
model and the points for 38 variables
decreased in the CY 2016 4-equation
model. There were 54 variables with the
same point values.
Step 2: Re-define the clinical and
functional thresholds so they are
reflective of the new points associated
with the CY 2016 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
68634
Federal Register / Vol. 80, No. 214 / Thursday, November 5, 2015 / Rules and Regulations
TABLE 4—CY 2016 CLINICAL AND FUNCTIONAL THRESHOLDS
1st and 2nd Episodes
0 to 13
therapy visits
Grouping Step:
Equation(s) used to calculate points: (see Table 3) ............
Dimension ...........................
Clinical ................................
Functional ...........................
Severity Level.
C1 .......................................
C2 .......................................
C3 .......................................
F1 ........................................
F2 ........................................
F3 ........................................
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
3rd+ Episodes
14 to 19
therapy visits
0 to 13
therapy visits
All episodes
14 to 19
therapy visits
20+ therapy
visits
1
1
2.1
2
3
3
2.2
4
4
(2&4)
0 to 1
2 to 3
4+
0 to 14
15
16+
0 to 1
2 to 7
8+
0 to 6
7 to 13
14+
0
1
2+
0 to 6
7 to 10
11+
0 to 3
4 to 12
13+
0
1 to 7
8+
0 to 3
4 to 16
17+
0 to 2
3 to 6
7+
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 5 shows
the regression coefficients for the
variables in the payment regression
model updated with CY 2014 data. The
R-squared value for the payment
regression model is 0.4822 (an increase
from 0.4680 for the CY 2015
recalibration).
TABLE 5—PAYMENT REGRESSION MODEL
New payment
regression
coefficients
Variable description
Step 1, Clinical Score Medium ............................................................................................................................................................
Step 1, Clinical Score High .................................................................................................................................................................
Step 1, Functional Score Medium .......................................................................................................................................................
Step 1, Functional Score High ............................................................................................................................................................
Step 2.1, Clinical Score Medium .........................................................................................................................................................
Step 2.1, Clinical Score High ..............................................................................................................................................................
Step 2.1, Functional Score Medium ....................................................................................................................................................
Step 2.1, Functional Score High .........................................................................................................................................................
Step 2.2, Clinical Score Medium .........................................................................................................................................................
Step 2.2, Clinical Score High ..............................................................................................................................................................
Step 2.2, Functional Score Medium ....................................................................................................................................................
Step 2.2, Functional Score High .........................................................................................................................................................
Step 3, Clinical Score Medium ............................................................................................................................................................
Step 3, Clinical Score High .................................................................................................................................................................
Step 3, Functional Score Medium .......................................................................................................................................................
Step 3, Functional Score High ............................................................................................................................................................
Step 4, Clinical Score Medium ............................................................................................................................................................
Step 4, Clinical Score High .................................................................................................................................................................
Step 4, Functional Score Medium .......................................................................................................................................................
Step 4, Functional Score High ............................................................................................................................................................
Step 2.1, 1st and 2nd Episodes, 14 to 19 Therapy Visits ..................................................................................................................
Step 2.2, 3rd+ Episodes, 14 to 19 Therapy Visits ..............................................................................................................................
Step 3, 3rd+ Episodes, 0–13 Therapy Visits ......................................................................................................................................
Step 4, All Episodes, 20+ Therapy Visits ............................................................................................................................................
Intercept ...............................................................................................................................................................................................
$24.69
$59.72
$76.46
$114.89
$68.55
$156.28
$34.15
$87.13
$61.06
$211.40
$10.90
$70.39
$10.27
$91.72
$56.53
$87.94
$72.66
$238.69
$15.65
$65.68
$479.21
$505.35
¥$76.20
$930.06
$391.33
tkelley on DSK3SPTVN1PROD with RULES2
Source: CY 2014 Medicare claims data for episodes ending on or before December 31, 2014 (as of June 30, 2015) 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
VerDate Sep<11>2014
19:46 Nov 04, 2015
Jkt 238001
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.
PO 00000
Frm 00012
Fmt 4701
Sfmt 4700
Step 5: The weights associated with 0
to 5 therapy visits are then increased by
3.75 percent, the weights associated
with 14–15 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
E:\FR\FM\05NOR2.SGM
05NOR2
Federal Register / Vol. 80, No. 214 / Thursday, November 5, 2015 / Rules and Regulations
to address MedPAC’s concerns that the
HH PPS overvalues therapy episodes
and undervalues non-therapy episodes
and to better aligned the case-mix
weights with episode costs estimated
from cost report data.2
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 0–5 to
14–15 therapy visits, and from 14–15 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 0–5 therapy visits and
68635
6 therapy visits and the increase
between 6 therapy visits and 7–9
therapy visits) are constant. This
interpolation is the 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 1.0000.3
This last step creates the CY 2016 casemix weights shown in Table 6.
TABLE 6: FINAL CY 2016 CASE-MIX PAYMENT WEIGHTS
tkelley on DSK3SPTVN1PROD with RULES2
Payment group
10111
10112
10113
10114
10115
10121
10122
10123
10124
10125
10131
10132
10133
10134
10135
10211
10212
10213
10214
10215
10221
10222
10223
10224
10225
10231
10232
10233
10234
10235
10311
10312
10313
10314
10315
10321
10322
10323
10324
10325
10331
10332
10333
10334
10335
21111
21112
21113
21121
21122
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
1st
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
and
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
2nd
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
Episodes,
2 Medicare Payment Advisory Commission
(MedPAC), Report to the Congress: Medicare
Payment Policy. March 2011, P. 176.
VerDate Sep<11>2014
Clinical and functional
levels
(1 = Low; 2 = Medium; 3= High)
Step (episode and/or therapy visit ranges)
18:04 Nov 04, 2015
Jkt 238001
0 to 5 Therapy Visits ..............................................................
6 Therapy Visits ......................................................................
7 to 9 Therapy Visits ..............................................................
10 Therapy Visits ....................................................................
11 to 13 Therapy Visits ..........................................................
0 to 5 Therapy Visits ..............................................................
6 Therapy Visits ......................................................................
7 to 9 Therapy Visits ..............................................................
10 Therapy Visits ....................................................................
11 to 13 Therapy Visits ..........................................................
0 to 5 Therapy Visits ..............................................................
6 Therapy Visits ......................................................................
7 to 9 Therapy Visits ..............................................................
10 Therapy Visits ....................................................................
11 to 13 Therapy Visits ..........................................................
0 to 5 Therapy Visits ..............................................................
6 Therapy Visits ......................................................................
7 to 9 Therapy Visits ..............................................................
10 Therapy Visits ....................................................................
11 to 13 Therapy Visits ..........................................................
0 to 5 Therapy Visits ..............................................................
6 Therapy Visits ......................................................................
7 to 9 Therapy Visits ..............................................................
10 Therapy Visits ....................................................................
11 to 13 Therapy Visits ..........................................................
0 to 5 Therapy Visits ..............................................................
6 Therapy Visits ......................................................................
7 to 9 Therapy Visits ..............................................................
10 Therapy Visits ....................................................................
11 to 13 Therapy Visits ..........................................................
0 to 5 Therapy Visits ..............................................................
6 Therapy Visits ......................................................................
7 to 9 Therapy Visits ..............................................................
10 Therapy Visits ....................................................................
11 to 13 Therapy Visits ..........................................................
0 to 5 Therapy Visits ..............................................................
6 Therapy Visits ......................................................................
7 to 9 Therapy Visits ..............................................................
10 Therapy Visits ....................................................................
11 to 13 Therapy Visits ..........................................................
0 to 5 Therapy Visits ..............................................................
6 Therapy Visits ......................................................................
7 to 9 Therapy Visits ..............................................................
10 Therapy Visits ....................................................................
11 to 13 Therapy Visits ..........................................................
14 to 15 Therapy Visits ..........................................................
16 to 17 Therapy Visits ..........................................................
18 to 19 Therapy Visits ..........................................................
14 to 15 Therapy Visits ..........................................................
16 to 17 Therapy Visits ..........................................................
3 When computing the average, we compute a
weighted average, assigning a value of one to each
PO 00000
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C1F1S1
C1F1S2
C1F1S3
C1F1S4
C1F1S5
C1F2S1
C1F2S2
C1F2S3
C1F2S4
C1F2S5
C1F3S1
C1F3S2
C1F3S3
C1F3S4
C1F3S5
C2F1S1
C2F1S2
C2F1S3
C2F1S4
C2F1S5
C2F2S1
C2F2S2
C2F2S3
C2F2S4
C2F2S5
C2F3S1
C2F3S2
C2F3S3
C2F3S4
C2F3S5
C3F1S1
C3F1S2
C3F1S3
C3F1S4
C3F1S5
C3F2S1
C3F2S2
C3F2S3
C3F2S4
C3F2S5
C3F3S1
C3F3S2
C3F3S3
C3F3S4
C3F3S5
C1F1S1
C1F1S2
C1F1S3
C1F2S1
C1F2S2
Final CY 2016
case-mix
weights
0.5908
0.7197
0.8485
0.9774
1.1063
0.7062
0.8217
0.9372
1.0527
1.1681
0.7643
0.8832
1.0021
1.1210
1.2399
0.6281
0.7690
0.9098
1.0507
1.1915
0.7435
0.8710
0.9985
1.1259
1.2534
0.8016
0.9325
1.0633
1.1942
1.3251
0.6810
0.8362
0.9913
1.1465
1.3017
0.7964
0.9382
1.0800
1.2218
1.3635
0.8544
0.9996
1.1449
1.2901
1.4353
1.2351
1.4323
1.6296
1.2836
1.4719
normal episode and a value equal to the episode
length divided by 60 for PEPs.
E:\FR\FM\05NOR2.SGM
05NOR2
68636
Federal Register / Vol. 80, No. 214 / Thursday, November 5, 2015 / Rules and Regulations
TABLE 6: FINAL CY 2016 CASE-MIX PAYMENT WEIGHTS—Continued
tkelley on DSK3SPTVN1PROD with RULES2
Payment group
21123
21131
21132
21133
21211
21212
21213
21221
21222
21223
21231
21232
21233
21311
21312
21313
21321
21322
21323
21331
21332
21333
22111
22112
22113
22121
22122
22123
22131
22132
22133
22211
22212
22213
22221
22222
22223
22231
22232
22233
22311
22312
22313
22321
22322
22323
22331
22332
22333
30111
30112
30113
30114
30115
30121
30122
30123
30124
30125
30131
30132
30133
30134
30135
30211
30212
30213
30214
30215
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
VerDate Sep<11>2014
Clinical and functional
levels
(1 = Low; 2 = Medium; 3= High)
Step (episode and/or therapy visit ranges)
1st and 2nd Episodes, 18 to 19 Therapy Visits ..........................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits ..........................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits ..........................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits ..........................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits ..........................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits ..........................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits ..........................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits ..........................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits ..........................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits ..........................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits ..........................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits ..........................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits ..........................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits ..........................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits ..........................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits ..........................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits ..........................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits ..........................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits ..........................................................
1st and 2nd Episodes, 14 to 15 Therapy Visits ..........................................................
1st and 2nd Episodes, 16 to 17 Therapy Visits ..........................................................
1st and 2nd Episodes, 18 to 19 Therapy Visits ..........................................................
3rd+ Episodes, 14 to 15 Therapy Visits ......................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ......................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ......................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ......................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ......................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ......................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ......................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ......................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ......................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ......................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ......................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ......................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ......................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ......................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ......................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ......................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ......................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ......................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ......................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ......................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ......................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ......................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ......................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ......................................................................
3rd+ Episodes, 14 to 15 Therapy Visits ......................................................................
3rd+ Episodes, 16 to 17 Therapy Visits ......................................................................
3rd+ Episodes, 18 to 19 Therapy Visits ......................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ..........................................................................
3rd+ Episodes, 6 Therapy Visits ..................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ..........................................................................
3rd+ Episodes, 10 Therapy Visits ................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ......................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ..........................................................................
3rd+ Episodes, 6 Therapy Visits ..................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ..........................................................................
3rd+ Episodes, 10 Therapy Visits ................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ......................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ..........................................................................
3rd+ Episodes, 6 Therapy Visits ..................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ..........................................................................
3rd+ Episodes, 10 Therapy Visits ................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ......................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ..........................................................................
3rd+ Episodes, 6 Therapy Visits ..................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ..........................................................................
3rd+ Episodes, 10 Therapy Visits ................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ......................................................................
18:04 Nov 04, 2015
Jkt 238001
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E:\FR\FM\05NOR2.SGM
C1F2S3
C1F3S1
C1F3S2
C1F3S3
C2F1S1
C2F1S2
C2F1S3
C2F2S1
C2F2S2
C2F2S3
C2F3S1
C2F3S2
C2F3S3
C3F1S1
C3F1S2
C3F1S3
C3F2S1
C3F2S2
C3F2S3
C3F3S1
C3F3S2
C3F3S3
C1F1S1
C1F1S2
C1F1S3
C1F2S1
C1F2S2
C1F2S3
C1F3S1
C1F3S2
C1F3S3
C2F1S1
C2F1S2
C2F1S3
C2F2S1
C2F2S2
C2F2S3
C2F3S1
C2F3S2
C2F3S3
C3F1S1
C3F1S2
C3F1S3
C3F2S1
C3F2S2
C3F2S3
C3F3S1
C3F3S2
C3F3S3
C1F1S1
C1F1S2
C1F1S3
C1F1S4
C1F1S5
C1F2S1
C1F2S2
C1F2S3
C1F2S4
C1F2S5
C1F3S1
C1F3S2
C1F3S3
C1F3S4
C1F3S5
C2F1S1
C2F1S2
C2F1S3
C2F1S4
C2F1S5
05NOR2
Final CY 2016
case-mix
weights
1.6601
1.3588
1.5450
1.7313
1.3324
1.5307
1.7289
1.3809
1.5702
1.7595
1.4560
1.6434
1.8307
1.4569
1.6902
1.9234
1.5053
1.7297
1.9540
1.5805
1.8028
2.0252
1.2722
1.4571
1.6419
1.2877
1.4746
1.6615
1.3721
1.5539
1.7357
1.3589
1.5483
1.7378
1.3743
1.5658
1.7573
1.4587
1.6452
1.8316
1.5722
1.7670
1.9619
1.5876
1.7845
1.9815
1.6721
1.8639
2.0557
0.4758
0.6351
0.7944
0.9536
1.1129
0.5611
0.7064
0.8518
0.9971
1.1424
0.6085
0.7613
0.9140
1.0667
1.2194
0.4913
0.6648
0.8383
1.0118
1.1854
Federal Register / Vol. 80, No. 214 / Thursday, November 5, 2015 / Rules and Regulations
68637
TABLE 6: FINAL CY 2016 CASE-MIX PAYMENT WEIGHTS—Continued
Payment group
tkelley on DSK3SPTVN1PROD with RULES2
30221
30222
30223
30224
30225
30231
30232
30233
30234
30235
30311
30312
30313
30314
30315
30321
30322
30323
30324
30325
30331
30332
30333
30334
30335
40111
40121
40131
40211
40221
40231
40311
40321
40331
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
................
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................
................
................
................
................
................
................
................
................
................
................
3rd+ Episodes, 0 to 5 Therapy Visits ..........................................................................
3rd+ Episodes, 6 Therapy Visits ..................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ..........................................................................
3rd+ Episodes, 10 Therapy Visits ................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ......................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ..........................................................................
3rd+ Episodes, 6 Therapy Visits ..................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ..........................................................................
3rd+ Episodes, 10 Therapy Visits ................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ......................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ..........................................................................
3rd+ Episodes, 6 Therapy Visits ..................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ..........................................................................
3rd+ Episodes, 10 Therapy Visits ................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ......................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ..........................................................................
3rd+ Episodes, 6 Therapy Visits ..................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ..........................................................................
3rd+ Episodes, 10 Therapy Visits ................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ......................................................................
3rd+ Episodes, 0 to 5 Therapy Visits ..........................................................................
3rd+ Episodes, 6 Therapy Visits ..................................................................................
3rd+ Episodes, 7 to 9 Therapy Visits ..........................................................................
3rd+ Episodes, 10 Therapy Visits ................................................................................
3rd+ Episodes, 11 to 13 Therapy Visits ......................................................................
All Episodes, 20+ Therapy Visits .................................................................................
All Episodes, 20+ Therapy Visits .................................................................................
All Episodes, 20+ Therapy Visits .................................................................................
All Episodes, 20+ Therapy Visits .................................................................................
All Episodes, 20+ Therapy Visits .................................................................................
All Episodes, 20+ Therapy Visits .................................................................................
All Episodes, 20+ Therapy Visits .................................................................................
All Episodes, 20+ Therapy Visits .................................................................................
All Episodes, 20+ Therapy Visits .................................................................................
To ensure the changes to the HH PPS
case-mix weights are implemented in a
budget neutral manner, we apply a casemix budget neutrality factor to the CY
2016 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
2016 HH PPS grouper and case-mix
weights (developed using CY 2014
claims data) are applied to CY 2014
utilization (claims) data to total
payments when the CY 2015 HH PPS
grouper and case-mix weights
(developed using CY 2013 claims data)
are applied to CY 2014 utilization data.
Using CY 2014 claims data as of
December 31, 2014, we calculated the
case-mix budget neutrality factor for CY
2016 to be 1.0141. Updating our
analysis with 2014 claims data as of
June 30, 2015, we calculated a final
case-mix budget neutrality factor for CY
2016 of 1.0187.
The following is a summary of the
comments and our responses to
comments on the CY 2016 case-mix
weights.
VerDate Sep<11>2014
Clinical and functional
levels
(1 = Low; 2 = Medium; 3= High)
Step (episode and/or therapy visit ranges)
18:04 Nov 04, 2015
Jkt 238001
Comment: One commenter noted that
the case-mix weights were increased
3.75 percent for 0–5 therapy visits,
decreased by 2.5 percent for 14–15
therapy visits, and decreased 5 percent
for 20+ therapy visits to address
MedPAC’s concerns that the therapy
episodes are over-valued and nontherapy episodes are undervalued, but
stated that a therapist’s salary and
benefits costs are higher than those
same costs for nursing, due to the
overall market for therapists and the
greater difficulty in retaining them in
the home health environment versus
other health care settings. Additionally,
the commenter noted that patients
requiring 20+ therapy visits typically
have functional deficits in multiple
domains, requiring the expertise of
multiple therapy disciplines (PT/OT/
ST) to address, justifying the higher case
mix.
Response: As we noted in the CY
2015 HH PPS final rule, these
adjustments to the case-mix weights are
the same adjustments finalized in the
CY 2012 HH PPS final rule (76 FR
68557). As the commenter correctly
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C2F2S2
C2F2S3
C2F2S4
C2F2S5
C2F3S1
C2F3S2
C2F3S3
C2F3S4
C2F3S5
C3F1S1
C3F1S2
C3F1S3
C3F1S4
C3F1S5
C3F2S1
C3F2S2
C3F2S3
C3F2S4
C3F2S5
C3F3S1
C3F3S2
C3F3S3
C3F3S4
C3F3S5
C1F1S1
C1F2S1
C1F3S1
C2F1S1
C2F2S1
C2F3S1
C3F1S1
C3F2S1
C3F3S1
Final CY 2016
case-mix
weights
0.5766
0.7362
0.8957
1.0553
1.2148
0.6241
0.7910
0.9579
1.1249
1.2918
0.6143
0.8058
0.9974
1.1890
1.3806
0.6996
0.8772
1.0548
1.2324
1.4100
0.7470
0.9320
1.1170
1.3020
1.4870
1.8268
1.8484
1.9176
1.9272
1.9488
2.0180
2.1567
2.1784
2.2475
noted, these adjustments were made, in
part, to address MedPAC’s concerns that
the HH PPS overvalues therapy episodes
and undervalues non-therapy episodes
(March 2011 MedPAC Report to the
Congress: Medicare Payment Policy,
p.176). However, we further note that
these adjustments also better aligned the
case-mix weights with episode costs
estimated from cost report data (79 FR
66061).
Comment: One commenter stated that
they are pleased that CMS used updated
claims and cost data to recalibrate all of
the case-mix weights. However, the
commenter went on to state that they
were somewhat confused that hightherapy episodes tend to get increased
case-mix weights, even though CMS has
stated its intention that therapy visit
volume should have less impact on the
weights. One commenter noted that
CMS did not provide sufficient
transparency of the details and methods
used to recalibrate the HH PPS case-mix
weights in its discussion in the
proposed rule. In addition, CMS
provided little justification for
recalibrating the case-mix weights just 1
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year following the recalibration of casemix weights in CY 2015 and a mere 3
years since the recalibration for the CY
2012 HH PPS final rule. The commenter
noted that this proposed recalibration
reduces the case weights for 117 HHRGs
or 76 percent of the 153 HHRGs.
Another commenter stated that analysis
of the case mix weight changes from
2014 through 2016 indicates an average
decrease of 1.52 percent in each HIPPS
code weight. The commenter stated that
they believe that these changes alone
have produced an overall decrease in
the case mix scoring of episodes since
2013. Specifically, applying the 2016
case mix weights to the HHA’s 2014
episodes would produce a decrease in
overall case mix weight of 4.7 percent
and from 2014–2016, the overall casemix weight was reduced by 7.2 percent
for certain HIPPS codes.
Response: As stated in the CY 2015
HH PPS final rule, 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). We
encourage commenters to refer to the CY
2012 HH PPS proposed and final rules
(76 FR 40988 and 76 FR 68526) and the
CY 2012 technical 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.
As we noted in the CY 2015 HH PPS
final rule (79 FR 66067), decreases in
the case-mix weights for the low therapy
case-mix groups and increases in the
case-mix weights for the high therapy
case-mix groups is generally attributable
to shifts away from the use of home
health aides and a shift to either more
nursing or more therapy care across all
therapy groups. While some of the low
therapy groups did add more skilled
nursing visits, most of the high therapy
groups added more occupational
therapy (OT) and speech-language
pathology (SLP), which have
substantially higher Bureau of Labor
Statistics (BLS) average hourly wage
values compared to skilled nursing. In
addition, while the average number of
total visits per episode has decreased
overall, it decreased disproportionately
more for the no/low therapy case-mix
groups. These utilization changes result
in changes to the weights observed by
the commenter, specifically, the
decreases in the case-mix weights for
the low or no therapy groups and
increases in the case-mix weights for the
high therapy groups.
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Comparing the final CY 2016 HH PPS
case-mix weights (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 4 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 60day 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 decreases in total
payments under the HH PPS, as result
of the case-mix recalibration, by
applying a budget neutrality factor to
the national, standardized 60-day
episode payment rate. For CY 2016, the
case-mix budget neutrality factor will be
1.87 percent as described above. For CY
2015, the case-mix budget neutrality
factor was 3.66 percent (79 FR 66088).
In addition, when the CY 2014 case-mix
weights were reset to 1.0000 by
decreasing the case-mix weights by
1.3464, we correspondingly increased
the national, standardized 60-day
episode payment rate by the same factor
(1.3464) as part of the rebasing of the
HH PPS payment rates required by the
Affordable Care Act (78 FR 72273). 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.
Final Decision: We will finalize the
recalibration of the HH PPS case-mix
weights as proposed. The CY 2016
scores for the case-mix variables, the
clinical and functional thresholds, and
the case-mix weights were developed
using complete CY 2014 claims data as
of June 30, 2015. 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 2016 HH PPS
proposed rule.
2. Reduction to the National,
Standardized 60-day Episode Payment
Rate to Account for Nominal Case-Mix
Growth
Section 1895(b)(3)(B)(iv) of the Act
gives the Secretary the authority to
implement payment reductions for
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nominal case-mix growth (that is, casemix growth unrelated to changes in
patient acuity). Previously, we
accounted for nominal case-mix growth
through case-mix reductions
implemented from 2008 through 2013
(76 FR 68528–68543). As stated in the
2013 final rule, the goal of the
reductions for nominal case-mix growth
is to better align payments with real
changes in patient severity (77 FR
67077). Our analysis of data from CY
2000 through CY 2010 found that only
15.97 percent of the total case-mix
change was real and 84.03 percent of
total case-mix change was nominal (77
FR 41553). In the CY 2015 HH PPS final
rule (79 FR 66032), we estimated that
total case-mix increased by 2.76 percent
between CY 2012 and CY 2013 and in
applying the 15.97 percent estimate of
real case-mix growth to the estimate of
total case-mix growth, we estimated
nominal case-mix growth to be 2.32
percent (2.76 ¥ (2.76 × 0.1597)).
However, for 2015, we did not
implement a reduction to the 2015
national, standardized 60-day episode
payment amount to account for nominal
case-mix growth, but stated that we
would continue to monitor case-mix
growth and may consider proposing
nominal case-mix reductions in the
future. Since the publication of 2015 HH
PPS final rule (79 FR 66032), MedPAC
reported on their assessment of the
impact of the mandated rebasing
adjustments on quality of and
beneficiary access to home health care
as required by section 3131(a) of the
Affordable Care Act. As noted in section
III.A.2 of the proposed rule, MedPAC
concluded that quality of care and
beneficiary access to care are unlikely to
be negatively affected by the rebasing
adjustments. For the proposed rule, we
further estimated that case-mix
increased by 1.41 percent between CY
2013 and CY 2014 using preliminary CY
2014 home health claims data (as of
December 31, 2014) with linked OASIS
data. In applying the 15.97 percent
estimate of real case-mix growth to the
total estimated case-mix growth from
CY 2013 to CY 2014 (1.41 percent), we
estimated that nominal case-mix growth
to be 1.18 percent (1.41 ¥ (1.41 ×
0.1597)). Given the observed nominal
case-mix growth of 2.32 percent in 2013
and 1.18 percent in 2014, we estimated
that the reduction to offset the nominal
case-mix growth for these 2 years would
be 3.41 percent (1 ¥ 1/(1.0232 × 1.0118)
= 0.0341).
We proposed to implement this 3.41
percent reduction in equal increments
over 2 years. Specifically, we proposed
to apply a 1.72 percent (1 ¥ 1/(1.0232
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× 1.0118) 1/2 = 1.72 percent) reduction to
the national, standardized 60-day
episode payment rate each year for 2
years, CY 2016 and CY 2017, under the
ongoing authority of section
1895(b)(3)(B)(iv) of the Act. In the
proposed rule, we noted that proposed
reductions to the national, standardized
60-day episode payment rate in CY 2016
and in CY 2017 to account for nominal
case-mix growth are separate from the
rebasing adjustments finalized in CY
2014 under section 1895(b)(3)(A)(iii) of
the Act, which were calculated using
CY 2012 claims and CY 2011 HHA cost
report data (which was the most current,
complete data at the time of the CY 2014
HH PPS proposed and final rules).
In updating our analysis for the final
rule and in reassessing our methodology
in response to comments, as discussed
further below in this section, we used a
more familiar methodology (one used in
the past) to measure case-mix growth.
We first calculated the average case-mix
index for 2012, 2013, and 2014 before
comparing the average case-mix index
for CY 2012 to CY 2013 and the average
case-mix index for CY 2013 to CY 2014
to calculate the total case-mix growth
between the years. To make the
comparison between the 2013 average
case-mix index and the 2014 average
case-mix index, we had to inflate the
2014 average case-mix index (multiply
it by 1.3464) before doing the
comparison. We inflated the 2014
average case-mix index by 1.3464 to
offset the decrease by that same factor
when the CY 2014 case-mix weights
were reset to 1.0000 in the CY 2014 HH
PPS final rule (78 FR 72256). By first
calculating the average case-mix index
for 2012, 2013, and 2014 before
comparing the average case-mix index
for CY 2012 to CY 2013 and then
comparing the average case-mix index
for CY 2013 to CY 2014 to calculate the
total case-mix growth between the years,
we used a more familiar methodology
than what was done for the CY 2015 HH
PPS final rule and the CY 2016 HH PPS
proposed rule. In those rules, we instead
simulated total payments using casemix weights from 2 consecutive years
(used to calculate the case-mix budget
neutrality factor when recalibrating the
case-mix weights) and isolated the
portion of the budget neutrality factor
that was due to changes in case-mix.
Calculating the average case-mix index
in a given year, and comparing indices
across years, better aligns with how
CMS historically measured case-mix
growth in previous years and is a
methodology that was thoroughly vetted
in previous rulemaking. In addition, we
believe that this more familiar
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methodology results in a more
straightforward measure of case-mix
growth between 2012 and 2014, given
that annual recalibration of the case-mix
weights did not begin until CY 2015.
Using this methodology, we estimate
that the average case-mix for 2012 was
1.3610 and that the average case-mix for
2013 was 1.3900.4 Dividing the average
case-mix for 2013 by the average casemix for 2012, we obtain a total case-mix
growth estimate from 2012 to 2013 of
2.13 percent (1.3900/1.3610 = 1.0213),
compared to 2.76 percent in the
proposed rule. We estimate that the
average case-mix for 2014 was 1.0465.
We note that in 2014, we decreased all
of the case-mix weights uniformly by
1.3464. Therefore, in order to make a
comparison between the 2014 average
case-mix weight and the 2013 average
case-mix weight, we multiplied the
1.0465 estimate by 1.3464 (1.0465 ×
1.3464 = 1.4090). We then divided the
average case-mix for 2014 by the average
case-mix for 2013 to obtain a total casemix growth estimate from 2013 to 2014
of 1.37 percent (1.4090/1.3900 =
1.0137), compared to 1.41 percent in the
proposed rule.
Using the 2.13 percent estimate of
total case-mix growth between CY 2012
and CY 2013, we estimate nominal casemix growth to be 1.79 percent (2.13 ¥
(2.13 × 0.1597) = 1.79). Similarly, using
the 1.37 percent estimate of total casemix growth between CY 2013 and CY
2014, we estimate nominal case-mix
growth to be 1.15 percent (1.37 ¥ (1.37
× 0.1597) = 1.15). Using the updated
estimates of case-mix growth between
2012 and 2013 and between 2013 and
2014, we estimate that the reduction to
the national, standardized 60-day
episode payment rate needed to offset
the nominal case-mix growth from 2012
through 2014 would be 2.88 percent (1
¥ 1/(1.0179 × 1.0115) = 0.0288). If we
finalized the 2 year phase-in described
in the proposed rule, we would need to
implement a reduction of 1.45 percent
to the national, standardized 60-day
episode payment rate each year for 2
years, CY 2016 and CY 2017, to account
for nominal case-mix growth from 2012
through 2014 (1 ¥ 1/(1.0179 ×
1.0115) 1/2 = 0.0145).
In the CY 2016 HH PPS proposed
rule, we solicited comments on the
proposed reduction to the national,
standardized 60-day episode payment
amount in CY 2016 and in CY 2017 to
account for nominal case-mix growth
from CY 2012 through CY 2014 and the
4 We include outlier episodes in the calculation
along with normal episodes and PEPs. We note that
the case-mix for PEP episodes are downward
weighted based on the length of the home health
episode.
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68639
associated changes in the regulations
text at § 484.220 in section VII. The
following is a summary of the comments
and our responses.
Comment: MedPAC supported the
proposed case-mix reductions and
stated that the Commission has long
held that it is necessary for CMS to
make adjustments to account for
nominal case-mix growth to prevent
overpayments.
Response: We thank MedPAC for their
support.
Comment: Several commenters
expressed concern with the
methodology used to determine casemix growth from CY 2012 to CY 2014
and the portion of such growth that is
nominal versus real. Specifically,
commenters stated that the percent
change in real case-mix used to
calculate the proposed nominal casemix reductions is not reflective of the
real case-mix growth between 2012 and
2014. Commenters stated that patients
are entering into home health at a much
higher acuity level than in previous
years and cited a number of statistics to
support their statements. Commenters
also disagreed with the use of the
percent change in real case-mix used in
the case-mix reduction calculations as it
was based on data from 2000–2010 and
applied to the total case mix growth
from 2012 to 2014. They stated that no
adjustments should be considered until
CMS conducts a thorough analysis of
real and nominal changes in case mix
through evaluation of changes that
occurred during the actual years of
concern (2012–2014) with respect to the
proposed adjustment and any
adjustments that might be considered in
future years. They further stated that
CMS should have the data and tools to
perform an updated analysis of the
percentage of real versus nominal casemix growth between 2012 and 2014 and
they noted that the historical analyses
conducted by CMS demonstrate that the
level of ‘‘nominal’’ case mix weight
change is not consistent from year to
year. While some commenters urged
CMS to update its analysis to determine
the percentage of real versus nominal
case-mix growth for CY 2012 through
CY 2014, other commenters stated that
out of the 921 variables used in such
analyses, there are only four drivers of
real case-mix growth and implied that
CMS’ analysis was not reliable or
comprehensive enough. Some
commenters stated that the adjustments
to payments should be based on current
data informed by clinical evaluation.
Finally, one commenter stated that CMS
should not implement the proposed
case-mix reductions and not propose
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any additional case-mix reductions in
the future.
Response: We believe the percent
change in real case-mix used in the
case-mix reduction calculations, which
is based on analysis of 2000 through
2010 data, is a stable proxy for the real
case-mix growth between 2012 and
2014. Our analysis of data has not
indicated that real case-mix change
between 2012 through 2014 is greater
than the change in real case-mix
between 2000 and 2010. In fact, our
analysis of claims data has shown a
decrease in the number of total visits
per episode between 2012 and 2014.
Furthermore, our analysis of 2012 and
2013 cost report data showed that the
cost per episode has decreased each
year.
In addition, we note that there is prior
precedent for applying historical
estimates of real case-mix growth on
more current data to set payment rates.
In the rate year (RY) 2008 and the RY
2009 LTCH final rules, an estimate of
the percentage of real case-mix growth
from a prior time period was applied to
the total case-mix growth from FY 2004
to FY 2005 and from FY2005 to FY 2006
in determining the RY 2008 and RY
2009 federal rate updates (72 FR 26889
and 73 FR 26805).
With regard to the recommendation
that the estimates should be informed
by clinical evaluation, we note that
CMS’ case-mix change model,
developed by Abt Associates, only
includes a few variables that are derived
from OASIS assessments (measures of
patient living arrangement) because the
OASIS items can be affected by changes
in coding practices. It is not practical to
consider other types of home health
clinical data (for example, from medical
charts) in the model given the resources
available.
We note that as a result of the
comments we received expressing
concerns about our methodology and
questioning the case-mix growth
estimates we presented in the proposed
rule, we did re-evaluate the
methodology to determine total casemix growth and are moving forward
with a more familiar, and slightly more
accurate, methodology (one used in the
past) to measure case-mix growth (as
described above). The methodology
results in the calculation of a 1.45
percent reduction each year in CY 2016
and CY 2017 to account for nominal
case-mix growth from 2012 to 2014
(instead of the 1.72 percent reduction
described in the CY 2016 proposed
rule).
Comment: A commenter stated that
their analyses suggest that all of the
historical increases have been driven by
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increased therapy utilization that is, in
turn, based on real needs of the patients.
A commenter stated that the technical
analyses used to conclude that case-mix
increases are generally ‘‘not real’’ have
been based on the non-case-mix
variables and that those non-case-mix
variables were found to have a lower
explanatory value. The commenter
expressed concerns with CMS’
exclusion of the therapy variables in the
model to assess real case-mix, stating
that those have the highest explanatory
power. The commenter asked that CMS
address this question in the final rule to
better inform their understanding of its
conclusions as to how ‘‘real’’ versus
‘‘nominal’’ determinations are made.
Response: The models to assess real
and nominal case-mix growth were
intended to analyze changes in case-mix
over time and do not distinguish
whether these changes are due to
increases in therapy use or other factors.
We do not believe that it would be
appropriate to include utilizationrelated variables, such as the number of
therapy visits, as predictors in the
model, as such variables are providerdetermined. In addition, the goal of
these analyses was to examine changes
in measures of patient acuity that are
not affected by any changes in provider
coding practices. For example, the
models do incorporate information
about change in the types of patients
more likely to use therapy, such as postacute joint replacement patients. We
encourage commenters to review the
Analysis of 2000–2009 Home Health
Case-Mix Change Report, available on
the HHA center page at: https://
www.cms.gov/Center/Provider-Type/
Home-Health-Agency-HHA-Center.html,
in order to better understand the models
used to assess real and nominal casemix growth.
Comment: A number of commenters
encouraged CMS to seek payment
system reforms that are value-based
rather than implementing payment
reductions.
Response: The Home Health ValueBased Purchasing (HHVBP) model will
be implemented January 1, 2016, as
described in section IV of this final rule.
However, the reductions to account for
nominal case-mix growth are necessary
to prevent overpayments due to coding
practices that led to increases in
payment that are not related to real
increases in patient acuity.
Comment: Commenters referenced
section 1895(b)(3)(B)(iv) of the Act,
stating that there has not been an
increase in aggregate payments that
would justify the proposed reductions,
and that CMS should withdraw its
proposal. Commenters stated that there
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was a decrease in spending from 2010
through 2013 and questioned how
nominal case-mix growth could have
increased during the time period.
Another commenter stated that
Medicare data for 2012 to 2014 appear
to indicate that the per episode payment
during this period actually fell below
the level that would have occurred as a
result of any up-coding even though
CMS’ estimates case mix up-coding
occurred. Commenters stated that no
payment reductions should be
implemented unless CMS could
demonstrate that Medicare spending on
home health services exceeded the
Congressional Budget Office’s (CBO)
forecasted spending.
Response: We have no statutory
authority to consider the relationship of
CBO projections to home health outlays
when setting the HH PPS payment rates.
The Secretary’s authority to respond to
nominal coding change is set out at
section 1895(b)(3)(B)(iv) of the Act. In
addition, the reference to ‘‘a change in
aggregate payments’’ in that provision
does not mean that overall expenditures
under the HH PPS need to increase in
order to implement reductions for
nominal case-mix growth. We would
also like to note that a decrease in
expenditures does not mean that there
has been no case-mix growth. The casemix growth during this time period may
have offset the decrease in expenditures
that might have otherwise occurred.
Comment: Commenters stated that the
recent recalibrations have eliminated
the nominal case-mix growth observed
from 2012 through 2014. Furthermore,
commenters stated that the removal of
certain ICD–9–CM codes included in the
HH PPS Grouper for CY 2014 addressed,
in part, nominal case-mix growth from
2012 through 2014. Commenters stated
that CMS should fully evaluate the
impact of the recalibration on case-mix
growth and publicly disclose the
information.
Response: While the recent
recalibrations (starting in CY 2015) may
help to reduce future nominal case-mix
growth, the proposed reductions are
addressing the nominal case-mix growth
from 2012 through 2014, prior to recent
efforts to annually recalibrate the HH
PPS case-mix weights. The reductions to
account for nominal case-mix growth
ensure that payments are not inflated by
case-mix changes unrelated to patient
severity that occurred from 2012
through 2014. This remains important
even in years when we are annually
recalibrating the case-mix weights.
When CMS recalibrates the case-mix
weights, a budget neutrality factor is
applied to the national, standardized 60day episode payment rate to ensure that
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the recalibration of the case-mix weights
result in the same aggregate
expenditures as the aggregate
expenditures using the current payment
weights. For the recalibration of the
weights in this rule, the budget
neutrality factor is applied to the CY
2016 national, standardized 60-day
episode payment rate to ensure that the
recalibration of the case-mix weights
results in the same aggregate
expenditures using the current CY 2015
payment weights (simulating payments
using CY 2014 utilization data, the most
current and complete data available at
this time). If there is nominal case-mix
growth in the data used to recalibrate
the case-mix weights, the nominal casemix growth is built into the national,
standardized 60-day episode rate
through the budget neutrality factor.
Thus nominal case-mix in a given year
could result in increases to the national,
standardized 60-day payment rate that
would otherwise not have occurred, and
future adjustments may be needed to
better align payment with patient
severity.
In measuring case-mix growth, we are
factoring in the removal of the ICD–9–
CM codes from the CY 2014 HH PPS
Grouper into our assessment of case-mix
growth from 2013 to 2014. We used the
2013 grouper and 2013 case-mix
weights to calculate the average casemix index for 2013. Then we used the
2014 grouper, which excluded ICD–9–
CM codes found to be rarely used and/
or not associated with resource use
increases, and 2014 case-mix weights, to
calculate the average case-mix index for
2014. Comparing the 2013 average casemix index to the 2014 average case-mix
index (multiplied by 1.3464 in order to
make the comparison), we obtained an
estimate of case-mix growth which
factors in the removal of the ICD–9
codes. We estimated 1.37 percent
growth in total case-mix even after
taking out the ICD–9–CM codes in 2014.
We will continue to monitor case-mix
growth and may examine the effects of
the annual recalibrations on future casemix growth.
Comment: Some commenters
questioned why the 2012 recalibration
did not have a budget neutrality
adjustment.
Response: The 2012 recalibration was
implemented in a budget neutral
manner. While a budget neutrality factor
was not applied to the national,
standardized 60-day episode payment
rate, we did apply a budget neutrality
factor to the weights to ensure that the
recalibration was implemented in a
budget neutral manner (76 FR 68555).
Comment: A few commenters stated
that CMS did not take into
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consideration any probable coding effect
in the transition from ICD–9–CM to
ICD–10–CM. The commenters stated
that it is highly likely that a decrease in
productivity will occur due to the
implementation of ICD–10–CM.
Commenters also stated that it is also
highly likely that ICD–10–CM will
result in coding inaccuracies, which in
turn, will lower average case mix. The
commenters encouraged CMS to
reconsider this large negative
adjustment and at least postpone it until
additional information and study results
are available. A commenter stated that,
in addition to ICD–10–CM
implementation, HHAs are
simultaneously facing increased costs
due to the implementation of the new
Department of Labor (DOL) rule on
minimum wage and overtime for
companionship providers.
Response: We note that providers
have been aware of the transition from
ICD–9–CM to ICD–10–CM for some
time. The original implementation date
for ICD–10–CM was October 1, 2013 (74
FR 3328). Therefore, the increase in
costs due to the ICD–10–CM transition
should be reflected in the latest cost
report data we examined for the
rebasing monitoring analyses in the
proposed rule (that is, CY 2013 cost
report data). In that analysis we found
that an even greater reduction to HHA
payments would need to occur to better
align payments with costs than is
currently allowed under section
1895(b)(3)(A)(iii) of the Act (80 FR
39845). We will continue to analyze
HHA Medicare cost report data and
monitor case-mix growth in future
rulemaking and may consider revising
payments accordingly.
Comment: Many commenters stated
that their individual home health
agencies have consistently had case-mix
that was below the national average and;
therefore, would be disproportionally
impacted. Commenters suggested that
CMS develop program integrity
measures to address provider-specific
up-coding rather than implementing the
across-the-board reductions. A
commenter suggested the program
integrity efforts could be performed
through the Recovery Audit Contractors
(RACs). Another commenter suggested
that CMS re-introduce the Medicare
review procedures of the past in both
the clinical and financial operations of
home health with monetary penalties
and/or recoupments based on those
reviews. A third commenter stated that
CMS should continue utilizing the
existing fraud and abuse prevention
processes to identify and target specific
agencies that have excessive profit
margins rather than impose the across
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the board reductions for all agencies and
that CMS should use its enforcement
authority to conduct targeted claims
reviews and deny payment for claims
where the case mix weight is not
supported by the plan of care rather
than cut the national standardized
episode rate for all agencies.
One commenter stated that the
Medicare Administrative Contractors
(MACs) are tasked with finding
instances of inappropriate coding and
that the industry should not be
penalized for inappropriate coding that
the MACs were unable to find. The
commenter also stated that the proposed
reductions are a ‘‘double whammy’’
because the claims that were identified
as erroneously billed have already been
adjusted and any identified
overpayments have been recovered and
that CMS is attempting to recover even
more than what was in error through the
proposed reductions. In addition, the
commenter questioned why there have
not been more denials if there has been
widespread up-coding, as suggested by
CMS’ analysis.
Response: For a variety of reasons, as
we have noted in previous regulations,
we have not proposed targeted
reductions for nominal case-mix change.
The foremost reason is that we believe
changes and improvements in coding
have been widespread, so that such
targeting would likely not separate
agencies clearly into high and low
coding-change groups. When
performing an independent review of
our case-mix measurement
methodology, Dr. David Grabowski,
Ph.D., a professor of health care policy
at Harvard Medical School, and his
team agreed with our reasons for not
proposing targeted reductions, stating
their concerns about the small sample
size of many agencies and their findings
of significant nominal case-mix across
different classes of agencies (please see
the ‘‘Home Health Study Report—
Independent Review of the Models to
Assess Nominal Case-Mix Growth’’,
dated June 21, 2011, located at:
https://www.cms.gov/Center/ProviderType/Home-Health-Agency-HHACenter.html).
While certain commenters seem to
assume that CMS can precisely identify
those agencies practicing abusive
coding, we do not agree that agencyspecific case-mix levels can precisely
distinguish the agencies that engage in
abusive coding from all others. System
wide, case-mix levels have risen over
time throughout the country, while
patient characteristics data indicate
little real change in patient severity over
time. That is, the main problem is not
the level of case-mix billed by any
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specific HHA over a period of time, but
the amount of change in the billed casemix weights not attributable to
underlying changes in actual patient
severity. We note that we have taken
various measures to reduce payment
vulnerabilities and the federal
government has launched actions to
directly identify fraudulent and abusive
activities. Commenters should be aware
of tip lines available that can help
support investigative efforts of the
federal government. The Office of the
Inspector General, Department of Health
and Human Services Web site at:
https://oig.hhs.gov/fraud/report-fraud/
index.asp, provides information about
how to report fraud. Another Web site,
https://www.stopmedicarefraud.gov/
index.html, is oriented to Medicare
patients and their families and provides
information about recognizing fraud.
In terms of recoupments that
correspond to claims denied after they
were reviewed, such would typically be
reflected in the claims data we used in
our case-mix analysis. In the case where
a paid-claim dispute is still active,
because the volume is so low, this data
would likely have little to no effect on
our determination of nominal case-mix
growth. In addition, while we
appreciate the commenters’ suggestion,
targeted claim review on a scale that
would be required to counteract the
broad-based uptrend in case-mix
weights would be resource-intensive
and not feasible.
Comment: Some commenters stated
that the additional payment reductions
for nominal case-mix growth are based
on a subset of the same factors used to
determine the rebasing adjustment, such
as the ‘‘intensity of services’’ factor. The
commenters stated that the use of an
earlier legislative authority to justify an
additional type of reduction above the
legislative cap on rebasing adjustments
is contrary to congressional intent. The
commenters urged CMS to adhere to the
limits on home health rate rebasing
established by Congress and
recommended that CMS evaluate the
impact of the rebasing adjustments and
consult with Congress before
considering additional reductions.
Other commenters stated that CMS
should provide a comprehensive
explanation as to why it has not
determined that the 2014 rate rebasing
effectively eliminated the impact of any
alleged nominal case mix weight change
that may have occurred in 2013 and
2014. Commenters recommended that
CMS should hold off on imposing the
adjustments until the completion of the
rebasing in 2017. Alternatively, the
commenters recommended phasing-in
the proposed reductions over more
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years. A commenter stated that this
approach would be more consistent
with approaches used by the agency to
implement similar rate reductions in the
IPPS and would soften the impact for
those agencies whose case-mix growth
was due to changes in patient acuity.
Another commenter stated that CMS
should do further analysis including
validation that no element of the
proposed coding cut would duplicate
reductions already accounted for in the
rebasing adjustments. Another
commenter requested that CMS provide
a discussion of the interaction of the
rebasing adjustments and the
recalibration of case weights on the
purported nominal case mix growth,
stating that they believed that the
rebasing and recalibration of case
weights addressed any nominal case
mix growth at that time.
Response: The rebasing adjustments
proposed and finalized for CY 2014
through CY 2017 were based on 2011
cost report data and 2012 claims data.
We compared payment and costs using
2011 cost data and 2012 claims data and
therefore, we did not account for any
nominal case-mix growth from 2012 to
2014 in the methodology. Specifically,
using the 2011 cost data, we estimated
a 2013 60-day episode cost by
increasing the 2011 60-day episode cost
by the change in the visit data between
2011 and 2012 and the full 2012 and
2013 market baskets. We calculated
payments by taking the 2012 national,
standardized 60-day payment amount
and updating it by the average case-mix
weight for 2012 as well as updating the
estimate based on the payment policies
implemented in CY 2013 to estimate
average payments in 2013. In the
rebasing methodology, we did not factor
in future projections of nominal casemix growth from 2012 to 2014 in our
analysis. As stated previously, the
nominal case-mix reductions would
allow us to account for nominal casemix growth from 2012 through 2014 and
mitigate structural overpayments.
While resetting the weights to 1.0000
and doing annual recalibrations may
potentially reduce future nominal casemix growth, it does not offset the
nominal case-mix growth previously
unaccounted for, particularly for those
last few years before annual
recalibrations began. We note that there
is a two year lag between the data used
to recalibrate the case-mix weights and
the year that the weights will be
implemented and we use the same
claims data when comparing payments
and developing the budget neutrality
factor. If that utilization in the claims
data is too high, it is built into the
payments for both the future year’s case
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mix weights and the previous year’s
case mix weights on which the
recalibration is based, and so that
increased utilization ends up being
carried forward. In other words, the
recalibration is adjusting for the next
year’s case mix change as compared to
the previous one, but, barring additional
action, will not (even in future years)
adjust for unaccounted nominal case
mix growth already built in to the
system.
With regard to the commenters’
concerns about congressional intent, we
do not believe that application of the
case-mix adjustment is contrary to
congressional intent. We have received
input from stakeholders and appreciate
their comments but believe our final
policy is within the authority under the
statute and is consistent with
congressional intent. Moreover, this
policy reflects our goal to better align
Medicare reimbursement with real
changes in patient severity. With regard
to the comment about phasing-in the
reductions over more years, we note that
in response to comments, we are
phasing-in the case-mix reductions over
3 years (CY 2016, CY 2017, and CY
2018) rather than the 2 years (CY 2016
and CY 2017) described in the proposed
rule. Specifically, we will be finalizing
a 0.97 percent reduction each year in CY
2016, CY 2017, and CY 2018 to account
for nominal case-mix growth from CY
2012 through CY 2014 (1 ¥ 1/(1.0179 ×
1.0115) 1/3 = 0.0097). Iteratively
implementing the case-mix reduction
over three years gives home health
agencies more time to adjust to the
intended reduction of 2.88 percent than
would be the case were we to account
for the nominal case-mix growth in two
years.
Comment: Commenters stated that the
proposed case-mix reductions would
disproportionately affect hospital-based
agencies and that hospital-based HHA’s
Medicare margins have been negative
for the past few years. A commenter
stated that hospital-based HHAs treat
more severe patients than freestanding
HHAs. Another commenter
recommended that CMS consider the
differences in case-mix across the types
of HHAs and regions.
Response: Hospital-based HHAs
comprise less than 10 percent of all
home health agencies in our impact
analysis (see section VII of this final
rule). As stated in their March 2011
Report to Congress, MedPAC focuses on
freestanding agencies because they are
the majority of providers and because
their costs do not reflect the sort of
allocation of overhead costs seen in
facility-based providers’ Medicare cost
reports, such as hospital-based HHA’s
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Medicare cost reports. MedPAC
explains that in the case of hospitals,
which often provide services that are
paid for by multiple Medicare payment
systems, measures of payments and
costs for an individual sector could
become distorted because of the
allocation of overhead costs or
complementarities of services. In
addition, MedPAC has reported negative
Medicare margins for hospital-based
HHAs since at least 2005,5 even though
freestanding HHA Medicare margins
have been around or over 15 percent.
We question how hospital-based HHAs
can still be operating after several years
with negative Medicare margins and
whether those HHAs have incentives to
report negative Medicare margins (such
as cost shifting/allocation by hospitals
amongst their various units).
In their March 2009 Report to the
Congress, MedPAC stated that hospitalbased providers have a lower case-mix
index, which suggests that they serve
less costly patients.6 Similarly, we also
examined the average case-mix index
for freestanding versus facility-based
HHAs in CY 2014 and found that
hospital-based HHAs had an average
case-mix index that was approximately
6 percent lower than freestanding
HHAs. However, the report on the
independent review of the model used
to assess real case-mix growth,
performed by Dr. David Grabowski from
Harvard University, stated ‘‘. . . when
we re-ran the Abt model by ownership
type (non-profit, government, for-profit),
agency type (facility-based,
freestanding), region of the country
(north, south, Midwest, west), agency
size (large vs. small; based on number
of initial episodes) and agency focus
(post-acute versus communitydwelling), the results suggest that—
although there is some variation—a
consistent percentage of the growth in
case-mix is nominal growth. As such,
these results do not provide much
support for adjusting payments by
classes of agencies.’’ The ‘‘Home Health
Study Report—Independent Review of
the Models to Assess Nominal Case-Mix
Growth’’, dated June 21, 2011, is located
on our homepage at: https://
www.cms.gov/Center/Provider-Type/
Home-Health-Agency-HHA-Center.html.
Comment: Commenters expressed
concerns with the impact of the
proposed reductions on HHA margins
and the financial viability of HHAs.
Commenters stated that CMS estimated
5 Medicare Payment Advisory Commission
(MedPAC), Report to the Congress: Medicare
Payment Policy. March 2007, P. 194.
6 Medicare Payment Advisory Commission
(MedPAC), Report to the Congress: Medicare
Payment Policy. March 2009, P. 196.
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that 43 percent of all HHAs would face
negative margins by 2017 with the
impact of rebasing and the annual
productivity adjustment and provided
other information on margins.
Commenters stated that a recent
analysis by NAHC indicates that the
percentage of impacted HHAs is now
forecasted at 53.71 percent by 2017 and
that, with the addition of the case mix
weight adjustment proposed by CMS,
some states will be impacted to a much
higher degree. Some other commenters
stated that analysis conducted by
Avalere Health determined that 45.3
percent of all HHAs nationwide will
operate at a loss by the end of 2017. A
commenter stated the MedPAC
Medicare Margin estimate is not
intended to serve as a measure of home
health agencies’ profit/loss, but is often
interpreted as such, and an HHA’s
overall margin (rather than just the
Medicare margin) is a standard measure
of a home health company’s bottom
line/profit (or loss, as applicable). A few
commenters stated that policymakers
may want to consider providers’ overall
margins, as well as the MedPAC
Medicare margin, when contemplating
changes to home health reimbursement.
A commenter stated that CMS should
accurately account for the current costs
of providing HH services to Medicare
beneficiaries and to offer HH agencies a
fair opportunity to generate a margin
needed to make the ongoing
investments that are necessary to
maintain and improve patient care.
Response: In the CY 2014 final rule,
we estimated that approximately 40
percent of providers would have
negative margins in CY 2017 and that of
the 40 percent of providers predicted to
have negative margins, 83 percent of
these providers already reported
negative margins in 2011. In their March
2015 Report to the Congress, MedPAC
estimates that the Medicare margins for
freestanding agencies averaged 12.7
percent in 2013 and averaged 17 percent
between 2001 and 2013. The
Commission estimates that the Medicare
margin for 2015 will be 10.3 percent. In
addition, as mandated in section 3131(a)
of the Affordable Care Act, MedPAC
conducted a study on the rebasing
implementation, which included an
impact analysis on access to care, and
submitted a Report to Congress on their
findings. MedPAC’s Report to Congress
noted that the rebasing adjustments are
partially offset by the payment update
each year and across all four years of the
phase-in of the rebasing adjustments the
cumulative net reduction would equal
about 2 percent. MedPAC concluded
that, as a result of the payment update
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68643
offsets to the rebasing adjustments, HHA
margins are likely to remain high under
the current rebasing policy and quality
of care and beneficiary access to care are
unlikely to be negatively affected.
Furthermore, in their 2013 Report to
Congress, MedPAC stated ‘‘low cost
growth or no cost growth has been
typical for home health care, and in
some years we have observed a decline
in cost per episode. The ability of HHAs
to keep costs low has contributed to the
high margins under the Medicare PPS.’’
Our analysis of 2012 and 2013 cost
report data supports MedPAC’s
statement about low or no cost growth
and suggests that the cost of 60 day
home health episodes has decreased
since 2011. In the CY 2014 final rule, we
estimated the cost of a 60-day episode
in 2011 to be $2,453.71 using CY 2011
Medicare claims data and 2011
Medicare cost report data (78 FR 72277).
In the CY 2015 proposed rule, we
estimated the cost of a 60-day episode
in 2012 to be $2,413.82 using CY 2012
Medicare claims data and FY 2012
Medicare cost report data (79 FR 38371).
In the CY 2016 proposed rule, we
estimated the cost of a 60-day episode
in 2013 to be $2,402.11 using CY 2013
Medicare claims data and FY 2013
Medicare cost report data (80 FR 39846).
In addition, we note that in their 2013
Report to Congress, MedPAC stated that
during the interim payment system
(1997–2000), when payments dropped
by about 50 percent in two years, many
agencies exited the program. However,
new agencies entered the program
(about 200 new agencies a year) and
existing agencies expanded their service
areas to enter markets left by exiting
agencies. This is due in part to the low
capital requirements for home health
care services that allow the industry to
react rapidly when the supply of
agencies changes or contracts. Reviews
of access found that access to care
remained adequate during this period
despite a substantial decline in the
number of agencies (Liu et al. 2003). In
summary, MedPAC’s past reviews of
access to home health care found that
access generally remained adequate
during periods of substantial decline in
the number of agencies. MedPAC stated
that this is due in part to the low capital
requirements for home health care
services that allow the industry to react
rapidly when the supply of agencies
changes or contracts. As described in
section III.A.3 of the CY 2016 proposed
rule, the number of HHAs billing
Medicare for home health services in CY
2013 was 11,889, or over 80 percent
higher than the 6,511 HHAs billing
Medicare for home health services in
2001. Even if some HHAs were to exit
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the program due to possible
reimbursement concerns, we would
expect the home health market to
remain robust (80 FR 39846).
With regard to the comments about
the overall margin, we note that as
stated in the CY 2014 final rule,
Medicare has never set payments so as
to cross-subsidize other payers. Indeed,
section 1861(v)(1)(A) of the Act states
‘‘under the methods of determining
costs, the necessary costs of efficiently
delivering covered services to
individuals covered by the insurance
programs established by this title will
not be borne by individuals not so
covered, and the costs with respect to
individuals not so covered will not be
borne by such insurance programs.’’ As
MedPAC stated in its March 2011
Report to Congress, cross-subsidization
is not advisable for two significant
reasons: ‘‘Raising Medicare rates to
supplement low Medicaid payments
would result in poorly targeted
subsidies. Facilities with high shares of
Medicare payments—presumably the
facilities that need revenues the least—
would receive the most in subsidies
from the higher Medicare payments,
while facilities with low Medicare
shares—presumably the facilities with
the greatest need—would receive the
smallest subsidies. Finally, increased
Medicare payment rates could
encourage states to further reduce their
Medicaid payments and, in turn, create
pressure to raise Medicare rates’’ (78 FR
72284).
Comment: A commenter stated that
the proposed payment rate reductions
will create job losses, particularly for
people in education and quality
positions. Commenters expressed
concerns that the proposed rate
reductions may create instability within
the industry and impact access to care,
particularly in underserved
communities or for patients with higher
cost or more complex care needs.
Commenters also stated that the
proposed rate reductions will have a
significant impact on those home health
agencies that serve as the safety-net
providers for their communities and
another commenter stated that the
proposed cuts will threaten access to
care in rural areas stating that patients
in rural areas tend to be sicker, older,
poorer, and require more complex care
than their urban counterparts. A
commenter urge CMS to eliminate the
proposed case mix cut pending a
detailed analysis utilizing current data
and incorporating an assessment of the
impact of such an additional cut on
Medicare beneficiaries as well as the
rural, small, and other HHAs who serve
them.
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Response: We do not expect the
payment reductions for nominal casemix growth to have a significant impact,
particularly given MedPAC’s projected
margins for 2015; however, we will
continue to monitor for unintended
consequences. As noted above, we are
phasing-in the reductions over three
years, rather than two years as described
in the proposed rule. Iteratively
implementing the case-mix reduction
over three years gives home health
agencies more time to adjust to the
intended reduction of 2.88 percent than
would be the case were we to account
for the nominal case-mix growth in two
years.
In addition, as described in the CY
2016 proposed rule, CMS has awarded
a follow-on contract to Abt Associates to
further explore margin differences
across patient characteristics and
possible payment methodology changes
suggested by the results of the home
health study. We presented several
model options under development in
the CY 2016 proposed rule and may
consider implementing payment reform
to address the margin differences across
patient characteristics in future
rulemaking (80 FR 39865). With regard
to the comment about patients in rural
areas, we note that episodes provided in
rural areas will continue to receive a
three percent add-on payment in CY
2016.
Comment: A commenter stated that
the proposed reductions will limit
services to the homebound population
and will lead to increased rehospitalization and costs. Another
commenter stated that the proposed
reductions would threaten the efficiency
of the health care system and will likely
increase the likelihood of unnecessary
institutional care episodes and that this
improper utilization may lead to higher
costs. The commenter urged CMS to
consider the role and value of home
health care in the overall health care
system as it makes changes to the home
health prospective payment system. The
commenter asked CMS to consider the
most vulnerable populations and the
demographics of home health users
when implementing payment
adjustments. The commenter urged
CMS to consider the potential impact of
payment adjustments on a generally,
older, sicker, poorer, and more
vulnerable population, and mitigate
these risks where possible. Commenters
also expressed concerns that the
proposed cuts may impact quality of
care.
Response: We note that we believe the
commenter is referring to both the
rebasing reductions as well as the
proposed reductions to account for
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nominal case-mix growth. As described
in the CY 2016 proposed rule, section
3131(a) of the Affordable Care Act
required the Medicare Payment
Advisory Commission (MedPAC) to
assess, by January 1, 2015, the impact of
the mandated rebasing adjustments on
quality of and beneficiary access to
home health care. As part of this
assessment, the statute required
MedPAC to consider the impact on care
delivered by rural, urban, nonprofit, and
for-profit home health agencies.
MedPAC’s Report to Congress noted that
the rebasing adjustments are partially
offset by the payment update each year
and across all four years of the phasein of the rebasing adjustments the
cumulative net reduction would equal
about 2 percent. MedPAC concluded
that, as a result of the payment update
offsets to the rebasing adjustments, HHA
margins are likely to remain high under
the current rebasing policy and quality
of care and beneficiary access to care are
unlikely to be negatively affected 7 (80
FR 39846). In addition, the overall
impact of this rule as discussed in
section VII of this final rule is smaller
than the overall impact of previous rules
in which reductions for nominal casemix growth have been implemented. For
instance, we estimated that the overall
impact of the CY 2011 HH PPS final rule
would be -4.89 percent and the overall
impact of the CY 2012 HH PPS final rule
would be -2.31 percent.
Commenters did not provide specific
information about why they believe
payment reductions would reduce the
quality of care. MedPAC estimates that
the Medicare margin for 2015 will be
10.3 percent, which should support
current levels of quality. We also believe
that policymaking in the quality
improvement area should help to ensure
quality advances. The HHVBP described
in this final rule will be implemented
on January 1, 2016, further enhancing
quality-related incentives. While we do
not anticipate significant negative
impacts of this rule, we will continue to
closely monitor the effects of the
payments adjustments on HHAs, as well
as on beneficiaries’ access and quality of
care.
Comment: Commenters stated that the
proposed reductions will limit home
health providers’ ability to continue
participating in broader payment and
7 Medicare Payment Advisory Commission
(MedPAC), ‘‘Report to the Congress: Impact of
Home Health Payment Rebasing on Beneficiary
Access to and Quality of Care’’. December 2014.
Washington, DC. Accessed on 5/05/15 at: https://
www.medpac.gov/documents/reports/december2014-report-to-the-congress-impact-of-home-healthpayment-rebasing-on-beneficiary-access-to-andquality-of-care.pdf?sfvrsn=0.
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delivery system reform efforts and in the
HHVBP program. Commenters stated
that the proposal fails to account for
significant new cost burdens placed on
agencies since 2010 and fails to take
into account the current and future
healthcare environment, such as the
reform initiatives underway. Another
commenter stated that the payment cuts
should be delayed until their impact on
HHAs can be more fully understood in
light of the dynamics that the Bundled
Payment for Care Improvement
Initiative (BPCI), the proposed
Comprehensive Care for Joint
Replacement (CCJR) model,
Accountable Care Organizations (ACOs)
and various other healthcare delivery
and payment reform initiatives are
creating for the home health sector,
including shifting more medically
complex functional impaired patients
into HHAs.
Response: While there may be
increased costs associated with
implementing the broader payment and
delivery system reform initiatives, we
expect that providers will be rewarded
for efficient care or higher quality of
care and will receive a return on their
investment for investing in the payment
reform efforts. The initiatives cited by
the commenters offer financial rewards
for high quality of care and/or efficient
care.
Comment: A commenter stated that
the proposed reductions will threaten
the ability of home health agencies to
reduce re-hospitalization rates and
requested that CMS re-consider the
reductions, given the current reductions
due to sequestration and rebasing.
Another commenter stated that they
disagree with the rationale used to
justify the proposed case-mix
reductions. The commenter stated that
the logic is ill-conceived and implies
that Medicare home health services
have increased due to overutilization.
Another commenter stated that the
proposed reductions assume that
providers ‘‘gamed the system.’’ A
commenter stated that the proposed
reductions are based on the fact that
CMS believes that the industry has
profit margins that are too high and has
inflated the case-mix of the patients
served.
Response: The goal of the reductions
for nominal case-mix growth is to better
align payment with real changes in
patient severity. The reductions would
adjust the national, standardized 60-day
episode payment rate to account for
nominal case-mix growth between CY
2012 and CY 2014 and mitigate
overpayments. As we have stated in
previous regulations, we believe
nominal coding change results mostly
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from changed coding practices,
including improved understanding of
the ICD–9 coding system, more
comprehensive coding, changes in the
interpretation of various items on the
OASIS and in formal OASIS definitions,
and other evolving measurement issues.
Our view of the causes of nominal
coding change does not emphasize the
idea that HHAs or clinicians in general
‘‘gamed the system’’ or over-provided
services or the idea that HHAs have
high profit margins. However, since our
goal is to pay only for increased costs
associated with real changes in patient
severity, and because nominal coding
change does not demonstrate that
underlying changes in patient severity
occurred, we believe it is necessary to
exclude nominal case-mix effects that
are unrelated to changes in patient
severity. We note that we will continue
to monitor for any unintended
consequences of the payment
reductions.
Comment: One commenter stated that
the starting point in the real and
nominal case-mix growth analysis
should have been 2002 or 2003, not
2000. Another commenter stated that
the original baseline of a case-mix
weight of 1.000 in 2000 was incorrect
and that the analysis is flawed because
the foundation or baseline is incorrect.
Commenters cited multiple examples to
support their statements that 2000
should not have been used as a baseline.
For instance, they stated that in the first
couple of years of the HH PPS, many
industry participants were struggling
with the transition to the new payment
system and the submission of OASIS
data. They also stated that the OASIS
document has changed over time and
that staff in 2000 had inadequate
training on the OASIS. A commenter
stated that the OASIS does not
adequately capture the level of illness of
the population being served.
Response: We followed the
Administrative Procedure Act (APA) in
implementing the HH PPS under the
mandate in the Balanced Budget Act of
1997. Under the APA, we solicited
public comments in 1999 on the then
proposed system. OASIS itself was
developed with industry participation
for the purpose of measuring home
health outcomes (see GAO–01–205,
January 2001, Appendix II). A version of
OASIS was used in the original casemix research that led to the design of
the HH PPS case-mix system. The
research results indicated that adequate
case-mix adjustment of payments could
be achieved using OASIS variables. We
have noted in previous regulations that
the average case-mix weight nationally,
as estimated from OASIS assessments in
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the 12 months leading up to October 1,
2000, was about 13 percent higher than
the average in the sample of agencies
whose data were used for the case-mix
research. We used the estimate from the
12 months leading up to October 1, 2000
as our baseline for measuring case-mix
change because it represented a very
large, broad-based set of episodes. It did
not reflect the earliest days of OASIS
use. Given that coding practices
continually evolved subsequent to the
last 12 months ending October 1, 2000,
and that agencies were not subject to the
HH PPS incentives during the 12
months ending October 1, 2000, the
selected baseline period is the most
appropriate one to use to begin
measuring coding change that occurred
in relation to the introduction of the HH
PPS. Any other period subsequent to
our baseline builds in impacts on
coding of the HH PPS and is
questionable to use from the point of
view of responsible fiscal stewardship.
We note that comments referencing
coding improvements, such as
increasing accuracy, do not recognize
that such improvements are an
inappropriate basis for increased
payment. We believe that measurable
changes in patient severity and patient
need are appropriate bases for changes
in payment. Our analysis found only
small changes in patient severity and
need.
With regard to the comments about
the baseline, we note that in our May
2007 proposed rule and our August
2007 final rule, we described the IPS
samples and PPS samples that were
used to calculate case-mix change. We
remind the commenters that 313,447
observations is an extremely large
sample by statistical standards, and that
agencies began collecting OASIS data in
1999, following issuance of a series of
regulations beginning on January 25,
1999 (64 FR 3764). Most of the data we
used for the baseline period come from
the first 3 quarters of the year 2000—
months after collection was mandated to
begin in August 1999. By 2000 the vast
majority of agencies were complying
with the reporting requirements.
Indirect evidence that the data from the
early years of the HH PPS were
sufficiently reliable comes from model
validation analysis we conducted
during that period. Validation of the 80group model on a large 19-month claims
sample ending June 2002 (N = 469,010
claims linked to OASIS) showed that
the goodness-of-fit of the model was
comparable to the fit statistic from the
original Abt Associates case-mix sample
(0.33 vs. 0.34), notwithstanding that
average total resources per episode
declined by 20 percent. That analysis
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also showed that all but three variables
in the scoring system remained
statistically significant.
Comment: A commenter questioned
CMS’ ability to be able to statistically
infer the difference between increases in
real changes in case-mix vs. nominal
case-mix growth to the degree that the
estimate was used in developing the
proposed reductions, i.e., a hundredth
of a percentage point. Some commenters
stated that the home health payment
system itself is flawed and cited the
Report to Congress on the home health
study on access to care for vulnerable
populations. The commenter implied
that since the payment system is flawed,
the analysis to assess real and nominal
case-mix is also flawed. Commenters
stated that the proposed rule relies
heavily on a case-mix methodology that
CMS itself found requires ‘‘additional
analysis’’ and ‘‘potential modifications’’.
A commenter stated that the proposed
case-mix creep adjustments should be
suspended pending the development of
a new case-mix model.
Response: As described in the CY
2012 final rule and discussed above, we
procured an independent review of our
methodology by a team at Harvard
University led by Dr. David Grabowski
(‘‘Home Health Study Report—
Independent Review of the Models to
Assess Nominal Case-Mix Growth’’,
dated June 21, 2011). When reviewing
the model, the Harvard team found that
overall, our models were robust. As
stated previously, we would like to
account for nominal case-mix growth
from 2012 through 2014 and mitigate
overpayments. We note that, as
described in the CY 2016 proposed rule,
we have several model options under
development and may implement
payment reform in the future. However,
while we are currently in the process of
developing payment reform options to
the case-mix methodology, we think it
is appropriate to account for the
nominal case-mix growth from 2012 to
2014.
Final Decision: After considering the
comments received in response to the
CY 2016 HH PPS proposed rule (80 FR
39840) and for the reasons discussed
above, we are finalizing a 0.97 percent
reduction to the national, standardized
60-day episode payment rate each year
in CY 2016, CY 2017, and CY 2018 to
account for nominal case-mix growth
from 2012 to 2014.
3. Clarification Regarding the Use of
the ‘‘Initial Encounter’’ Seventh
Character, Applicable to Certain ICD–
10–CM Code Categories, under the HH
PPS
The ICD–10–CM coding guidelines
regarding the seventh character
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assignment for diagnosis codes under
Chapter 19, Injury, poisoning, and
certain other consequences of external
causes (S00–T88), were revised in the
Draft 2015 ICD–10–CM, The Completed
Official Draft Code Set. Based upon the
2015 revised coding guidance above,
certain initial encounters are
appropriate when the patient is
receiving active treatment during a
home health episode.
Comment: A commenter requested
clarification on the use of the seventh
character for ‘‘initial encounters’’ in the
home health setting. The commenter
agrees that it seems reasonable that
traumatic injury codes with the initial
encounter extension may not be
appropriate. However, the commenter
contends that certain initial encounter
extensions may be appropriate if the
patient is still receiving active
treatment. The commenter provided an
example of active treatment whereby the
patient is receiving active treatment
with the continuation of antibiotics for
treatment of a postoperative infection.
Based upon this example of active
treatment, the commenter recommends
that CMS revise the home health
grouper to allow the reporting of the
initial encounter seventh character for
the ICD–10–CM codes for those
conditions that could reasonably
continue to receive active treatment in
the home health setting. A couple of
other commenters noted similar
concerns regarding initial encounters.
Response: While this comment is
outside the scope of this rule, we
recognize that in the CY 2014 HH PPS
final rule (78 FR 72271), we discussed
the decision to eliminate codes with
initial encounter extensions, listed in
the GEMs translation for ICD–10–CM
codes, that began with S and T that are
used for reporting traumatic injuries
(e.g., fractures and burns) as part of our
ICD–10 grouper conversion effort. Codes
beginning with S and T have a seventh
character that indicates whether the
treatment is for an initial encounter,
subsequent encounter or a sequela (a
residual effect (condition produced)
after the acute phase of an illness or
injury has terminated).
The decision to eliminate the seventh
character initial encounter for the S and
T ICD–10–CM codes from the HH PPS
ICD–10–CM translation list was based,
not only on the most current coding
conventions and guidelines that were
available at that time, but also in
collaboration with the cooperating
parties of the ICD–10 Coding Committee
(the American Health Information
Management Association, the American
Hospital Association, the Centers for
Disease Control and Prevention’s
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National Center for Health Statistics,
and CMS) who confirmed that initial
encounter extensions were not
appropriate for care in the home health
setting. Code extensions D, E, F, G, H,
J, K, M, N, P, Q and R indicate the
patient is being treated for a subsequent
encounter (care for the injury during the
healing or recovery phase) and were
included in the translation list in place
of the initial encounter extensions. CMS
provided the draft translation list to the
public on the CMS Web site at
https://www.cms.gov/Center/ProviderType/Home-Health-Agency-HHACenter.html?redirect=/center/hha.asp.
We did not receive any comments on
the ICD–10–CM draft translation list and
the elimination of initial encounter
seventh character extension.
Since the publication of the CY 2014
HH PPS final rule, the ICD–10–CM
coding guidelines regarding the use of
the seventh character assignment for
diagnosis codes under Chapter 19,
Injury, poisoning, and certain other
consequences of external causes (S00–
T88), were revised in the Draft 2015
ICD–10–CM, The Completed Official
Draft Code Set. Specifically, in March of
2015, the coding guidelines were
revised to clarify that the designation of
an initial encounter is based on whether
a patient is receiving active treatment
for the condition for which the code
describes. Initial encounters are not
based on chronology of care or whether
the patient is seeing the same or a new
provider for the same condition.
Examples of active treatment are:
Surgical treatment, emergency
department encounter, and evaluation
and continuing treatment by the same or
a different physician. Based on these
revisions, it is possible for a home
health agency to use a diagnosis code
with a seventh character ‘‘A’’ (an initial
encounter) for certain conditions. A
clinical example of this could include a
patient who was in the acute care
hospital for IV antibiotics for a postsurgical wound infection and who is
discharged to home health on IV
antibiotics for ongoing treatment of the
surgical wound infection. This would be
considered active treatment as the
surgical wound infection requires
continued IV antibiotics.
The coding guidelines state to assign
the seventh character ‘‘D’’, indicating a
subsequent encounter, for encounters
after the patient has received active
treatment of the condition and is
receiving routine care for the condition
during the healing or recovery phase.
Examples of subsequent care include:
cast change or removal, an x-ray to
check healing status of fracture, removal
of external or internal fixation device,
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medication adjustment, other aftercare
and follow up visits following treatment
of the injury or condition. Therefore, it
is also possible for home health
encounters to be designated as
subsequent encounters based on
services that are provided during
healing and recovery, after treatment of
the condition described by the code is
completed. A clinical example of this
could include a patient who was in the
acute care hospital for a traumatic hip
fracture that was surgically repaired and
the patient is discharged to home health
for rehabilitation services. This would
be considered a subsequent encounter
as the hip fracture has been repaired
and the patient is now in the healing
and recovery phase.
We recognize that this revision may
have caused some confusion among
home health providers and that there
may be subtle clinical differences
between what is considered active
treatment of a condition versus routine
care during the healing and recovery
phase of a condition in the home health
setting. The assignment of the seventh
character should be based on clinical
information from the physician and
depends on whether the individual is
receiving active treatment for the
condition in which the code describes,
or if the individual is receiving ongoing
care for that condition during the
healing and recovery stage. In
determining which diagnosis codes
would be appropriate for an HHA to
indicate that the care is for an initial
encounter, CMS developed and shared a
draft list of codes with the cooperating
parties. Agreement was reached
between CMS and the cooperating
parties and a revised translation list
effective January 1, 2016 will be posted
on the CMS Web site. Also effective,
January 1, 2016, the Home Health
Prospective Payment System Grouper
logic will be revised to award points for
certain initial encounter codes based
upon the revised ICD–10–CM coding
guidelines for M0090 dates on or after
October 1, 2015.
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C. CY 2016 Home Health Rate Update
1. CY 2016 Home Health Market Basket
Update
Section 1895(b)(3)(B) of the Act
requires that the standard prospective
payment amounts for CY 2015 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 HH
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
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rule (77 FR 67080- 67090). The HH
market basket percentage increase for
CY 2016 is based on IHS Global Insight
Inc.’s (IGI) third quarter forecast with
historical data through the second
quarter of 2015. The HH market basket
percentage increase for CY 2016 is 2.3
percent.
Section 3401(e) of the Affordable Care
Act, adding new section
1895(b)(3)(B)(vi) to the Act, requires that
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 for CY 2015
and each subsequent calendar year. The
statute defines the productivity
adjustment, described in section
1886(b)(3)(B)(xi)(II) of the Act, 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 https://www.bls.gov/mfp
to obtain the BLS historical published
MFP data.
Multifactor productivity is derived by
subtracting the contribution of labor and
capital input growth from output
growth. The projections of the
components of MFP are currently
produced by IGI, a nationally
recognized economic forecasting firm
with which CMS contracts to forecast
the components of the market basket
and MFP. As described in the CY 2015
HH PPS proposed rule (79 FR 38384
through 38386), in order to generate a
forecast of MFP, IGI replicated the MFP
measure calculated by the BLS using a
series of proxy variables derived from
IGI’s U.S. macroeconomic models. In
the CY 2015 HH PPS proposed rule, we
identified each of the major MFP
component series employed by the BLS
to measure MFP as well as provided the
corresponding concepts determined to
be the best available proxies for the BLS
series.
Beginning with the CY 2016
rulemaking cycle, the MFP adjustment
is calculated using a revised series
developed by IGI to proxy the aggregate
capital inputs. Specifically, IGI has
replaced the Real Effective Capital Stock
used for Full Employment GDP with a
forecast of BLS aggregate capital inputs
recently developed by IGI using a
regression model. This series provides a
better fit to the BLS capital inputs as
measured by the differences between
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68647
the actual BLS capital input growth
rates and the estimated model growth
rates over the historical time period.
Therefore, we are using IGI’s most
recent forecast of the BLS capital inputs
series in the MFP calculations beginning
with the CY 2016 rulemaking cycle. A
complete description of the MFP
projection methodology is available on
our Web site at https://www.cms.gov/
Research-Statistics-Data-and-Systems/
Statistics-Trends-and-Reports/
MedicareProgramRatesStats/
MarketBasketResearch.html. In the
future, when IGI makes changes to the
MFP methodology, we will announce
them on our Web site rather than in the
annual rulemaking.
Using IGI’s third quarter 2015
forecast, the MFP adjustment for CY
2016 (the 10-year moving average of
MFP for the period ending CY 2016) is
0.4 percent. The CY 2016 HH market
basket percentage of 2.3 percent will be
reduced by the MFP adjustment of 0.4
percent. The resulting HH payment
update percentage is equal to 1.9
percent, or 2.3 percent less 0.4
percentage point.
Section 1895(b)(3)(B) of the Act
requires that the HH 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 2016, the HH
payment update will be -0.1 percent (1.9
percent minus 2 percentage points).
2. CY 2016 Home Health Wage Index
a. Background
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 will 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).
We will 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, and
thus, no hospital wage data on which to
base the calculation of the CY 2015 HH
PPS wage index. For rural areas that do
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tkelley on DSK3SPTVN1PROD with RULES2
not have inpatient hospitals, we will use
the average wage index from all
contiguous CBSAs as a reasonable
proxy. For FY 2016, there are no rural
geographic areas without hospitals for
which we would apply this policy. For
rural Puerto Rico, we will 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 will 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 2016, the
only urban area without inpatient
hospital wage data is Hinesville, GA
(CBSA 25980).
b. Update
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. This bulletin
is available online at https://
www.whitehouse.gov/sites/default/files/
omb/bulletins/2013/b-13-01.pdf. This
bulletin states that it ‘‘provides the
delineations of all Metropolitan
Statistical Areas, Metropolitan
Divisions, Micropolitan Statistical
Areas, Combined Statistical Areas, and
New England City and Town Areas in
the United States and Puerto Rico based
on the standards published on June 28,
2010, in the Federal Register (75 FR
37246–37252) and Census Bureau data.’’
In the CY 2015 HH PPS final rule (79
FR 66085 through 66087), we finalized
changes to the HH PPS wage index
based on the newest OMB delineations,
as described in OMB Bulletin No. 13–
01, including a 1-year transition with a
blended wage index for CY 2015.
Because the 1-year transition period
expires at the end of CY 2015, the final
HH PPS wage index for CY 2016 will be
fully based on the revised OMB
delineations adopted in CY 2015. The
final CY 2016 wage index is available on
the CMS Web site at https://
www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/HomeHealthPPS/
Home-Health-Prospective-PaymentSystem-Regulations-and-Notices.html
3. CY 2016 Annual Payment Update
a. Background
The Medicare HH PPS has been in
effect since October 1, 2000. As set forth
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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 42 CFR 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 is 78.535
percent and the non-labor-related share
is 21.465 percent as set out in the CY
2013 HH PPS final rule (77 FR 67068).
The CY 2016 HH PPS rates will 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.C.
of this 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, this document
constitutes 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 two
percentage points. Any reduction of the
percentage change will apply only to the
calendar year involved and would 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
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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 would 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 2016 National, Standardized 60Day Episode Payment Rate
Section 1895(3)(A)(i) of the Act
required 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 2016
national, standardized 60-day episode
payment rate, we will apply a wage
index standardization factor, a case-mix
budget neutrality factor described in
section III.B.1, a nominal case-mix
growth adjustment described in section
III.B.2, the rebasing adjustment
described in section II.C, and the HH
payment update as discussed in section
III.C.1 of this final rule.
To calculate the wage index
standardization factor, henceforth
referred to as the wage index budget
neutrality factor, we simulated total
payments for non-LUPA episodes using
the 2016 wage index and compared it to
our simulation of total payments for
non-LUPA episodes using the 2015
wage index. By dividing the total
payments for non-LUPA episodes using
the 2016 wage index by the total
payments for non-LUPA episodes using
the 2015 wage index, we obtain a wage
index budget neutrality factor of 1.0011.
We will apply the wage index budget
neutrality factor of 1.0011 to the CY
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2016 national, standardized 60-day
episode rate.
As discussed in section III.B.1 of this
final rule, to ensure the changes to the
case-mix weights are implemented in a
budget neutral manner, we will apply a
case-mix weight budget neutrality factor
to the CY 2016 national, standardized
60-day episode payment rate. The casemix weight budget neutrality factor is
calculated as the ratio of total payments
when CY 2016 case-mix weights are
applied to CY 2014 utilization (claims)
data to total payments when CY 2015
case-mix weights are applied to CY 2014
utilization data. The case-mix budget
neutrality factor for CY 2016 will be
1.0187 as described in section III.B.1 of
this final rule.
Next, as discussed in section III.B.2 of
this final rule, we will apply a reduction
of 0.97 percent to the national,
standardized 60-day episode payment
rate in CY 2016 to account for nominal
case-mix growth between CY 2012 and
CY 2014. Then, we will apply the
68649
-$80.95 rebasing adjustment finalized in
the CY 2014 HH PPS final rule (78 FR
72256) and discussed in section II.C.
Lastly, we will update the payment rates
by the CY 2016 HH payment update of
1.9 percent (MFP-adjusted home health
market basket update) as described in
section III.C.1 of this final rule. The CY
2016 national, standardized 60-day
episode payment rate is calculated in
Table 7.
TABLE 7—CY 2016 NATIONAL, STANDARDIZED 60-DAY EPISODE PAYMENT AMOUNT
CY 2015 National,
standardized 60-day
episode payment
Wage index
budget
neutrality
factor
Case-mix
weights
budget
neutrality
factor
Nominal
case-mix
growth
adjustment
(1¥.0097)
CY 2016
Rebasing
adjustment
CY 2016 HH
payment
update
percentage
CY 2016
National,
standardized
60-day
episode
payment
$2,961.38 .................................................
× 1.0011
× 1.0187
× 0.9903
¥$80.95
× 1.019
$2,965.12
quality data is updated by the CY 2016
HH payment update (1.9 percent) minus
The CY 2016 national, standardized
60-day episode payment rate for an
HHA that does not submit the required
2 percentage points and is shown in
Table 8.
TABLE 8—FOR HHAS THAT DO NOT SUBMIT THE QUALITY DATA—CY 2016 NATIONAL, STANDARDIZED 60-DAY EPISODE
PAYMENT AMOUNT
CY 2015 National,
standardized 60-day
episode payment
Wage index
budget
neutrality
factor
Case-mix
weights
budget
neutrality
factor
Nominal
case-mix
growth
adjustment
(1¥.0097)
$2,961.38 .................................................
×1.0011
×1.0187
×0.9903
tkelley on DSK3SPTVN1PROD with RULES2
c. CY 2016 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); and
• Speech-language pathology (SLP).
To calculate the CY 2016 national pervisit rates, we start with the CY 2015
national per-visit rates. We then apply
a wage index budget neutrality factor to
ensure budget neutrality for LUPA pervisit payments and increase each of the
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six per-visit rates by the maximum
rebasing adjustments described in
section II.C. of this rule. We calculate
the wage index budget neutrality factor
by simulating total payments for LUPA
episodes using the 2016 wage index and
comparing it to simulated total
payments for LUPA episodes using the
2015 wage index. By dividing the total
payments for LUPA episodes using the
2016 wage index by the total payments
for LUPA episodes using the 2015 wage
index, we obtain a wage index budget
neutrality factor of 1.0010. We will
apply the wage index budget neutrality
factor of 1.0010 to the CY 2016 national
per-visit rates.
The LUPA per-visit rates are not
calculated using case-mix weights.
Therefore, there is no case-mix weight
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CY 2016
Rebasing
adjustment
CY 2016 HH
payment
update
percentage
minus 2
percentage
points
CY 2016
National,
standardized
60-day
episode
payment
¥$80.95
×0.999
$2,906.92
budget neutrality factor needed to
ensure budget neutrality for LUPA
payments. Then, we apply the rebasing
adjustments finalized in the CY 2014
HH PPS final rule (78 FR 72280) to the
per-visit rates for each discipline.
Finally, the per-visit rates are updated
by the CY 2016 HH payment update of
1.9 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 add-on
payment amount, which is paid for
episodes that occur as the only episode
or initial episode in a sequence of
adjacent episodes. The CY 2016 national
per-visit rates are shown in Tables 9 and
10.
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TABLE 9—CY 2016 NATIONAL PER-VISIT PAYMENT AMOUNTS FOR HHAS THAT DO SUBMIT THE REQUIRED QUALITY
DATA
HH discipline type
Home health aide .................................................................
Medical Social Services .......................................................
Occupational Therapy ..........................................................
Physical Therapy .................................................................
Skilled Nursing .....................................................................
Speech-Language Pathology ...............................................
Wage index
budget
neutrality
factor
CY 2015
Per-visit
payment
$57.89
204.91
140.70
139.75
127.83
151.88
The CY 2016 per-visit payment rates
for HHAs that do not submit the
required quality data are updated by the
×
×
×
×
×
×
1.0010
1.0010
1.0010
1.0010
1.0010
1.0010
CY 2016 HH payment update of 1.9
percent minus 2 percentage points
CY 2016
Rebasing
adjustment
+$1.79
+ $6.34
+ $4.35
+ $4.32
+ $3.96
+ 4.70
CY 2016 HH
payment
update
percentage
×
×
×
×
×
×
1.019
1.019
1.019
1.019
1.019
1.019
CY 2016
Per-visit
payment
$60.87
215.47
147.95
146.95
134.42
159.71
(which is equal to ¥0.1 percent) and is
shown in Table 10.
TABLE 10—CY 2016 NATIONAL PER-VISIT PAYMENT AMOUNTS FOR HHAS THAT DO NOT SUBMIT THE REQUIRED
QUALITY DATA
HH discipline type
CY 2015
Per-visit rates
Home Health Aide ................................................................
Medical Social Services .......................................................
Occupational Therapy ..........................................................
Physical Therapy .................................................................
Skilled Nursing .....................................................................
Speech-Language Pathology ...............................................
$57.89
204.91
140.70
139.75
127.83
151.88
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, 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 (78 FR 72306). We
multiply the per-visit payment amount
for the first SN, PT, or SLP visit in
Wage index
budget
neutrality
factor
×
×
×
×
×
×
1.0010
1.0010
1.0010
1.0010
1.0010
1.0010
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, 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 would be $248.02 (1.8451
multiplied by $134.42), subject to area
wage adjustment.
e. CY 2016 Non-routine Medical Supply
(NRS) Payment Rates
Payments for NRS are computed by
multiplying the relative weight for a
CY 2016
Rebasing
adjustment
+ $1.79
+ $6.34
+ $4.35
+ $4.32
+ $3.96
+ 4.70
CY 2016 HH
payment
update
percentage
minus 2
percentage
points
×
×
×
×
×
×
0.999
0.999
0.999
0.999
0.999
0.999
CY 2016
Per-visit rates
$59.68
211.24
145.05
144.07
131.79
156.58
particular severity level by the NRS
conversion factor. To determine the CY
2016 NRS conversion factor, we start
with the 2015 NRS conversion factor
($53.23) and apply the ¥2.82 percent
rebasing adjustment described in
section II.C. of this rule (1 ¥ 0.0282 =
0.9718). We then update the conversion
factor by the CY 2016 HH payment
update of 1.9 percent. We do 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 2016 is shown
in Table 11.
TABLE 11—CY 2016 NRS CONVERSION FACTOR FOR HHAS THAT DO SUBMIT THE REQUIRED QUALITY DATA
CY 2016
Rebasing
adjustment
CY 2016 HH
payment
update
percentage
CY 2016 NRS
conversion
factor
$53.23 ..........................................................................................................................................
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CY 2015 NRS conversion factor
× 0.9718
× 1.019
$52.71
Using the CY 2016 NRS conversion
factor, the payment amounts for the six
severity levels are shown in Table 12.
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68651
TABLE 12—CY 2016 NRS PAYMENT AMOUNTS FOR HHAS THAT DO SUBMIT THE REQUIRED QUALITY DATA
Points
(scoring)
Severity level
1
2
3
4
5
6
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
...................................................................................................................................................
For HHAs that do not submit the
required quality data, we again begin
with the CY 2015 NRS conversion factor
($53.23) and apply the ¥2.82 percent
rebasing adjustment as discussed in
section II.C of this final rule (1 ¥ 0.0282
= 0.9718). We then update the NRS
conversion factor by the CY 2016 HH
payment update of 1.9 percent minus 2
percentage points. The CY 2016 NRS
Relative
weight
CY 2016 NRS
payment
amounts
0
1 to 14
15 to 27
28 to 48
49 to 98
99+
0.2698
0.9742
2.6712
3.9686
6.1198
10.5254
$14.22
51.35
140.80
209.18
322.57
554.79
conversion factor for HHAs that do not
submit quality data is shown in Table
13.
TABLE 13—CY 2016 NRS CONVERSION FACTOR FOR HHAS THAT DO NOT SUBMIT THE REQUIRED QUALITY DATA
CY 2015 NRS
conversion
factor
CY 2016
rebasing
adjustment
CY 2016 HH
payment
update
percentage
minus 2
percentage
points
$53.23 ..........................................................................................................................................
× 0.9718
× 0.999
The payment amounts for the various
severity levels based on the updated
conversion factor for HHAs that do not
CY 2016 NRS
conversion
factor
$51.68
submit quality data are calculated in
Table 14.
TABLE 14—CY 2016 NRS PAYMENT AMOUNTS FOR HHAS THAT DO NOT SUBMIT THE REQUIRED QUALITY DATA
Points (scoring)
Relative
weight
CY 2016 NRS
payment
amounts
0 ....................................................................................
1 to 14 ..........................................................................
15 to 27 ........................................................................
28 to 48 ........................................................................
49 to 98 ........................................................................
99+ ................................................................................
0.2698
0.9742
2.6712
3.9686
6.1198
10.5254
$13.94
50.35
138.05
205.10
316.27
543.95
Severity level
1
2
3
4
5
6
....................................................................................
....................................................................................
....................................................................................
....................................................................................
....................................................................................
....................................................................................
f. Rural Add-On
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Section 421(a) of the MMA requires,
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, 2010, and before
January 1, 2018, that the Secretary
increase the payment amount that
otherwise would have been made under
section 1895 of the Act for the services
by 3 percent. Section 421 of the MMA
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waives budget neutrality related to this
provision, as the statute specifically
states that the Secretary shall not reduce
the standard prospective payment
amount (or amounts) under section 1895
of the Act applicable to HH services
furnished during a period to offset the
increase in payments resulting in the
application of this section of the statute.
For CY 2016, home health payment
rates for services provided to
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beneficiaries in areas that are defined as
rural under the OMB delineations will
be increased by 3 percent as mandated
by section 421(a) of the MMA. The 3
percent rural add-on is applied to the
national, standardized 60-day episode
payment rate, national per visit rates,
and NRS conversion factor when HH
services are provided in rural (nonCBSA) areas. Refer to Tables 15 through
18 for these payment rates.
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TABLE 15—CY 2016 PAYMENT AMOUNTS FOR 60-DAY EPISODES FOR SERVICES PROVIDED IN A RURAL AREA
For HHAs that DO submit quality data
For HHAs that DO NOT submit quality data
CY 2016 national, standardized 60day episode payment rate
Multiply by the
3 percent rural
add-on
CY 2016 rural
national,
standardized
60-day episode payment
rate
$2,965.12 ..........................................
× 1.03
$3,054.07
CY 2016 national, standardized 60day episode payment rate
Multiply by the
3 percent rural
add-on
CY 2016 rural
national,
standardized
60-day episode payment
rate
$2,906.92 .........................................
× 1.03
$2,994.13
TABLE 16—CY 2016 PER-VISIT AMOUNTS FOR SERVICES PROVIDED IN A RURAL AREA
For HHAs that DO submit quality data
HH Discipline type
CY 2016 pervisit rate
HH Aide ....................................................
MSS .........................................................
OT ............................................................
PT .............................................................
SN ............................................................
SLP ..........................................................
Multiply by the
3 percent rural
add-on
$60.87
215.47
147.95
146.95
134.42
159.71
×
×
×
×
×
×
For HHAs that DO NOT submit quality data
CY 2016 pervisit rate
$62.70
221.93
152.39
151.36
138.45
164.50
1.03
1.03
1.03
1.03
1.03
1.03
CY 2016 rural
per-visit rates
Multiply by the
3 percent rural
add-on
$59.68
211.24
145.05
144.07
131.79
156.58
×
×
×
×
×
×
CY 2016 rural
per-visit rates
1.03
1.03
1.03
1.03
1.03
1.03
$61.47
217.58
149.40
148.39
135.74
161.28
TABLE 17—CY 2016 NRS CONVERSION FACTOR FOR SERVICES PROVIDED IN RURAL AREAS
For HHAs that DO submit quality data
For HHAs that DO NOT submit quality data
CY 2016 conversion factor
Multiply by the
3 percent rural
add-on
CY 2016 rural
NRS conversion factor
CY 2016 conversion factor
Multiply by the
3 percent rural
add-on
CY 2016 rural
NRS conversion factor
$52.71 ...............................................
× 1.03
$54.29
$51.68 ..............................................
× 1.03
$53.23
TABLE 18—CY 2016 NRS PAYMENT AMOUNTS FOR SERVICES PROVIDED IN RURAL AREAS
For HHAs that DO submit quality data (CY 2016 NRS conversion factor = $54.29
Severity level
Points (scoring)
For HHAs that DO NOT submit
quality data (CY 2016 NRS
conversion factor = $53.23)
Relative
weight
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1
2
3
4
5
6
........................................................
........................................................
........................................................
........................................................
........................................................
........................................................
0 .......................................................
1 to 14 ..............................................
15 to 27 ............................................
28 to 48 ............................................
49 to 98 ............................................
99+ ...................................................
The following is a summary of
comments we received regarding the CY
2016 home health rate update.
Comment: A commenter objected to
the proposed 0.6 percent productivity
adjustment.
Response: The productivity
adjustment was mandated by Section
3401(e) of the Affordable Care Act by
adding section 1895(b)(3)(B)(vi) to the
Act and requiring that the market basket
percentage under the HH PPS be
annually adjusted by changes in
economy-wide productivity in CY 2015
(and in subsequent calendar years).
Since publication of the proposed rule,
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CY 2016 NRS
payment
amounts for
rural areas
Relative
weight
CY 2016 NRS
payment
amounts for
rural areas
0.2698
0.9742
2.6712
3.9686
6.1198
10.5254
$14.65
52.89
145.02
215.46
332.24
571.42
0.2698
0.9742
2.6712
3.9686
6.1198
10.5254
$14.36
51.86
142.19
211.25
325.76
560.27
our forecast for the productivity
adjustment has been revised to 0.4
percent based on an updated forecast
with historical data through 2014.
Comment: A commenter stated that
because CAHs are located in rural areas,
the absence of CAH wage data further
compromises the accuracy of the
hospital wage index to determine labor
costs of HHAs providing services in
rural areas. In addition, pending
development of an industry specific
wage index, CMS should add a
population density adjustment to the
labor portion of the payment to account
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for increased costs of providing services
in less densely populated areas.
Response: Although the pre-floor, prereclassified hospital wage index does
not include data from CAHs, we believe
it reflects the relative level of wages and
wage-related costs applicable to
providing home health services. As we
stated in the IPPS Final Rule published
on August 1, 2003 (68 FR 45397),
‘‘CAHs represent a substantial number
of hospitals with significantly different
labor costs in many labor market areas
where they exist.’’ We further noted
that, ‘‘. . . in 89 percent of all labor
market areas with hospitals that
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converted to CAH status sometime after
FY 2000, the average hourly wage for
CAHs is lower than the average hourly
wage for other short-term hospitals in
the area. In 79 percent of the labor
market areas with CAHs, the average
hourly wage for CAHs is lower than the
average hourly wage for other short-term
hospitals by 5 percent or greater. These
results suggest that the wage data for
CAHs, in general, are significantly
different from other short-term
hospitals.
At this time, we do not have evidence
that a population density adjustment is
appropriate. While rural HHAs cite the
added cost of long distance travel to
provide care for their patients, urban
HHAs cite added costs associated with
needed security measures and traffic
congestion.
Comment: A commenter urges CMS to
review the wage index calculation for
rural Massachusetts and to include
Nantucket Cottage Hospital’s data in the
calculation. The commenter states that
Nantucket Cottage Hospital had given
up its critical access hospital (CAH)
designation in 2014 yet CMS has
apparently not used wage data from
Nantucket Cottage Hospital in
calculating the 2016 wage index for
rural Massachusetts. The commenter
urges CMS to include wage data from
CAHs in calculating the wage index for
HHAs and other non-hospital provider
types. The commenter believes that
including wage data from CAHS would
make the wage index more reflective of
actual local wage practices.
Response: Data from Nantucket
Cottage Hospital is included in the
calculation of the 2016 wage index for
rural Massachusetts. In fact, data from
this hospital has been included in the
calculation of the HH wage index for
rural Massachusetts since CY 2012. It
has been our longstanding practice to
not include data from CAHs in the
calculation of the HH wage index. We
only include hospital data from acute
IPPS hospitals in the calculation of the
HH wage index.
Comment: A commenter questions the
validity of the wage index assigned to
CBSA 22520, Florence-Muscle Shoals,
AL. The commenter requests that the
underlying data to determine this index
be investigated to determine its validity.
In addition, the commenter states that
the wage index as assigned places this
urban area below the rural wage index
for the state, which cannot be correct.
Response: The HH wage index values
in urban areas are not necessarily higher
than the HH wage index values in rural
areas. The wage index values are based
on data submitted on the inpatient
hospital cost reports. We utilize efficient
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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, pre-reclassified 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, our
intermediaries 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 Inpatient Prospective
Payment System (IPPS) rule each year,
with the most recent discussion
provided in the FY 2016 IPPS final rule
(80 FR 49488 through 49508). Any
provider type may submit comments on
the hospital wage index during the
annual IPPS rulemaking cycle.
Comment: Several commenters took
issue with the fact that the HH wage
index is based on pre-floor, prereclassified hospital wage data, but
hospitals in the same geographic
locations have the ability to apply for reclassification to another CBSA and may
be eligible for the rural floor wage
index. The commenters state that this
inequity has created a competitive
advantage for hospitals in recruiting and
retaining scarce labor. Several
commenters believe that the statute does
give CMS authority to address and
correct some of these inequities. One
commenter believes that a correction to
the manner in which the wage index is
calculated is needed in order to recruit
and retain staff necessary to provide
home health care. The commenter
continues to state that otherwise it may
be difficult for HHAs to meet the
increased demand for services, which
may jeopardize the success of CMS’ VBP
initiatives. Another commenter
recommends that CMS reform the HH
wage index by instituting a proxy that
allows HHAs to receive the same
reclassification as hospitals if they
provide series in the same service area.
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
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68653
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 found in section
1886(d)(10) of the Act. Section
1886(d)(10)(C)(i) of the Act states, ‘‘The
Board shall consider the application of
any subsection (d) hospital requesting
that the Secretary change the hospital’s
geographic classification . . .’’ This
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
it may or may not apply to a given HHA
in a given instance. With regard to
implementing a rural floor, we do not
believe it would be prudent at this time
to adopt such a policy. MedPAC has
recommended eliminating the rural
floor policy from the calculation of the
IPPS wage index (see Chapter 3 of
MedPAC’s March 2013 Report to
Congress on Medicare Payment Policy,
available at https://medpac.gov/
documents/reports/mar13_
entirereport.pdf, which notes on page 65
that in 2007, MedPAC had ‘‘. . .
recommended eliminating these special
wage index adjustments and adopting a
new wage index system to avoid
geographic inequities that can occur due
to current wage index policies.’’
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: A commenter requests that
CMS explore wholesale revision and
reform of the HH wage index. The
commenter believes that existing law
permits CMS flexibility in establishing
area wage adjustment factors. Another
commenter notes that CMS indicated
that the entire wage index system was
under review, and that a move to a
Commuting-Based Wage Index (CBWI)
was being considered. The commenter
urges CMS to expedite that review and
implement a system that not only
recognizes variations between localities,
but also treats all provider types within
a local market equitably. Until such a
system is in place, the commenter urges
CMS to adjust the 2016 HHA wage
index to reflect a policy to limit the
wage index disparity between provider
types within a given CBSA to no more
than 10 percent.
Response: CMS’ ‘‘Report to Congress:
Plan to Reform the Medicare Wage
Index’’ was submitted by the Secretary
on April 11, 2012 and is available on
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our Wage Index Reform Web page at
https://www.cms.gov/Medicare/
Medicare-Fee-for-Service-Payment/
AcuteInpatientPPS/Wage-IndexReform.html. This report states that
other steps are necessary before we
would be able to adopt a CBWI. In the
meantime, we do not believe that
limiting wage index differences between
provider types within a given CBSA
would be feasible. Regardless of
whether or not it would be appropriate
to do so, it would not be feasible to limit
the differences in wage index values
among provider types within a given
CBSA to no more than 10 percent, due
to timing issues. Some provider types
are reimbursed on a calendar year basis
and some are reimbursed on a fiscal
year basis.
Comment: A commenter opposes
CMS’ use of the hospital wage index to
establish the HH wage index. The
commenter states that differences in the
occupational personnel pool and costs
between hospitals and HHAs make the
use of the hospital wage index
inappropriate in the HH setting. The
commenter further states that hospitals
benefit from institutional efficiencies
that and rural hospitals have a
reclassification mechanism to avoid
exposure to the drastic rural index rate
in most states. The commenter believes
that Congress has granted CMS
discretion in establishing the HH wage
index and that CMS should establish a
HH specific wage index. Another
commenter believes that basing the
wage index on hospital data is not
reliable for home health. The
commenter continues to state that home
health workers pay is typically much
more than that of a hospital employee
due to the demanding nature of the job.
The commenter suggests that CMS
complete a detailed study of this issue.
Response: Our previous attempts at
either proposing or developing a home
health specific wage index were not
well received by the home health
industry. In a Federal Register Notice
(53 FR 38476) published on September
30, 1988, the Health Care Financing
Administration (HCFA), as we were
then known, implemented an HHAspecific wage index based on data
received from HHAs. Subsequently,
HCFA and the Congress received
numerous complaints from providers
concerning the burden that the reporting
requirements posed and the accuracy of
the data. As a result, the Congress
retroactively repealed its mandate in the
Medicare Catastrophic Coverage Act of
1988 for use of an HHA wage index and
referenced use of the hospital wage
index (see section 1895(b)(4)(C) of the
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Act). This caused great confusion among
both providers and fiscal intermediaries.
Developing a wage index that utilizes
data specific to HHAs would require us
to engage resources in an audit process.
In order to establish a home health
specific wage index, we would need to
collect data that is specific to home
health services. Because of the volatility
of the home health wage data and the
significant amount of resources that
would be required to improve the
quality of those data, we do not expect
to propose a home health specific wage
index until we can demonstrate that a
home health specific wage index would
be more reflective of the wages and
salaries paid in a specific area, be based
upon stable data sources, significantly
improve our ability to determine
payment for HHAs, and that we can
justify the resources required to collect
the data, as well as the increased burden
on providers. We believe that in the
absence of home health specific wage
data, using the pre-floor, pre-reclassified
hospital wage data is appropriate and
reasonable for the HH PPS.
Comment: A commenter states that
the wage index needs to reflect the
growing difficulties of providing care in
rural areas. The commenter states that
paying lower wages for rural health care
professionals that put as much time,
skill and intensity into their work as
their urban counterparts, exacerbates
the workforces shortages. The
commenter continues to state that
further reducing the wage index for
rural providers will make recruiting and
retaining medical professionals more
difficult for rural America. The
commenter states that using the wage
index for the local area ignores
important market forces and that many
health professionals are recruited from a
distance, making the local wage
insufficient financial incentive for
practicing in rural America. Another
commenter states that rural HHAs often
function as the primary caregivers for
elderly homebound patients, who have
high resource needs, which also
increases the cost of rural home health
services.
Response: The HH wage index values
in rural areas are not necessarily lower
than the HH wage index values in urban
areas. The HH wage index reflects the
wages that inpatient hospitals pay in
their local geographic areas. In addition,
HHAs receive rural add-on payments for
services provided to beneficiaries in
rural areas. Section 421(a) of the MMA,
as amended by section 210 of the
Medicare Access and CHIP
Reauthorization Act of 2015 (MACRA)
(Pub. L. 114–10), provides for a payment
increase of 3 percent for HH services
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provided in rural areas for episodes or
visits ending on or after April 1, 2010,
and before January 1, 2018.
Final Decision: After considering the
comments received in response to the
CY 2016 HH PPS proposed rule (80 FR
39840) and for the reasons discussed
above, we are finalizing our proposal to
use the pre-floor, pre-reclassified
hospital inpatient wage index as the
wage adjustment to the labor portion of
the HH PPS rates. For CY 2016, the
updated wage data are for hospital cost
reporting periods beginning on or after
October 1, 2011 and before October 1,
2012 (FY 2012 cost report data).
D. Payments for High-Cost Outliers
Under the HH PPS
1. Background
In the July 10, 2015 Medicare and
Medicaid Programs; CY 2016 Home
Health Prospective Payment System
Rate Update; Home Health Value-Based
Purchasing Model; and Home Health
Quality Reporting Requirements;
Proposed Rules (80 FR 39863 through
39864), we described the background
and current method for determining
outlier payments under the HH PPS. In
that rule, we did not propose any
changes to the current home health
outlier payment policy for CY 2016.
For this final rule, simulating
payments using CY 2014 claims data (as
of June 30, 2015) and the CY 2016
payment rates, without the rebasing and
nominal case-mix growth adjustments
as described in section III.C.3 of this
rule, we estimate that outlier payments
in CY 2016 would comprise 2.13
percent of total payments. Based on
simulations using CY 2014 claims data
and the CY 2016 payments rates,
including the rebasing and nominal
case-mix growth adjustments as
described in section III.C.3 of this rule,
we estimate that outlier payments
would comprise approximately 2.30
percent of total HH PPS payments, a
percent change of almost 8 percent. This
increase is attributable to the increase in
the national per-visit amounts through
the rebasing adjustments and the
decrease in the national, standardized
60-day episode payment amount as a
result of the rebasing and nominal casemix growth adjustments. Given the
same rebasing adjustments and case-mix
growth reduction would also occur for
2017, and hence a similar anticipated
increase in the outlier payments, we
estimate that for CY 2017 outlier
payments as a percent of total HH PPS
payments would be approximately 2.5
percent.
We did not propose a change to the
FDL ratio or loss-sharing ratio for CY
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2016 as we believe that maintaining an
FDL of 0.45 and a loss-sharing ratio of
0.80 are appropriate given the
percentage of outlier payments is
estimated to increase as a result of the
increase in the national per-visit
amounts through the rebasing
adjustments and the decrease in the
national, standardized 60-day episode
payment amount as a result of the
rebasing adjustment and nominal casemix growth reduction. We will continue
to monitor the percent of total HH PPS
payments paid as outlier payments to
determine if future adjustments to either
the FDL ratio or loss-sharing ratio are
warranted.
The following is a summary of
comments we received regarding
payments for high-cost outliers.
Comment: One commenter expressed
support of the continuation of the high
cost outlier parameters as currently
structured.
Response: We appreciate the
commenter’s support of the current HH
PPS outlier policy. We strive to
maintain an approach that accounts for
episodes that incur unusually high costs
due to patient care needs.
Comment: Several commenters
recommended changes to the existing
outlier policy, including the elimination
of the outlier payment policy altogether
as well as modifications to the FDL
Ratio and/or Loss-Sharing Ratio in order
to generate outlier payment levels
approximating 2.5 percent.
Response: We believe that section
1895(b)(5)(A) of the Act affords the
Secretary the discretion as to whether or
not to have an outlier policy under the
HH PPS. We plan to continue
investigating 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 without
qualifying episodes of care that do not
meet said criteria or are potentially
fraudulent. We recently awarded a
contract to Abt Associates to address
any findings from the home health
study required by section 3131(d) of the
Affordable Care Act, monitor the
potential impact of the rebasing
adjustments and other recent payment
changes, and develop payment options
to ensure ongoing access to care for
vulnerable populations. The work under
this contract may include potential
revisions to the outlier payment
methodology to better reflect costs of
treating Medicare beneficiaries with
high levels of severity of illness.
Comment: One commenter suggested
that CMS’s outlier policy and ten
percent threshold cap are not
appropriate fraud-fighting initiatives
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and suggested other mechanisms for
oversight and monitoring, including a
provider-specific floor (minimum) on
the number or percent of episodes that
result in LUPAs.
Response: As we have noted in the
past (74 FR 58085), we are committed to
addressing potentially fraudulent
activities, especially those in areas
where we see suspicious outlier
payments. As we noted above, we plan
to examine potential revisions to the
outlier payment methodology through
ongoing studies and analysis of home
health claims and other utilization data.
Monitoring of potentially fraudulent
activity will be captured in this
analysis, and we will make policy and
other adjustments as necessary in light
of the new data and outcomes as
appropriate.
Final Decision: We are finalizing no
change to the FDL ratio or loss sharing
ratio for CY 2016. 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 due to
patient care needs without qualifying
episodes of care that do not meet that
criteria.
E. Report to the Congress on the Home
Health Study Required by Section
3131(d) of the Affordable Care Act and
an Update on Subsequent Research and
Analysis
In the CY 2016 HH PPS proposed rule
(80 FR 39840), we included an
informational summary of the Report to
Congress on the home health study
required by section 3131(d) of the
Affordable Care Act and we provided an
update on subsequent research and
analysis completed to date. We will
continue to provide the home health
industry with periodic updates on the
progress of our subsequent research,
aimed at addressing the findings from
the section 3131(d) of the Affordable
Care Act home health study, in future
rulemaking and/or announcements on
the HHA Center Web page at: https://
www.cms.gov/Center/Provider-Type/
Home-Health-Agency-HHA-Center.html.
F. Technical Regulations Text Changes
We proposed to make several
technical corrections in part 484 to
better align the payment requirements
with recent statutory and regulatory
changes for home health services. We
proposed to make changes to § 484.
205(e) to state that estimated total
outlier payments for a given calendar
year are limited to no more than 2.5
percent of total outlays under the HHA
PPS, as required by section
1895(b)(5)(A) of the Act as amended by
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68655
section 3131(b)(2)(B) of the Affordable
Care Act, rather than 5 percent of total
outlays. Similarly, we also proposed to
specify in § 484.240(e) that the fixed
dollar loss and the loss sharing amounts
are chosen so that the estimated total
outlier payment is no more than 2.5
percent of total payments under the HH
PPS. We also proposed to describe in
§ 484.240(f) that the estimated total
amount of outlier payments to an HHA
in a given year may not exceed 10
percent of the estimated total payments
to the specific agency under the HH PPS
in a given year. This update aligns the
regulations text at § 484.240(f) with the
statutory requirement. Finally, we
proposed a minor editorial change in
§ 484.240(b) to specify that the outlier
threshold for each case-mix group is the
episode payment amount for that group,
or the PEP adjustment amount for the
episode, plus a fixed dollar loss amount
that is the same for all case-mix groups.
In addition to the proposed changes to
the regulations text pertaining to outlier
payments under the HH PPS, we also
proposed to amend § 409.43(e)(iii) and
to add language to § 484.205(d) to clarify
the frequency of review of the plan of
care and the provision of Partial Episode
Payments (PEP) under the HH PPS as a
result of a regulations text change in
§ 424.22(b) that was finalized in the CY
2015 HH PPS final rule (79 FR 66032).
Specifically, we proposed to change the
definition of an intervening event to
include transfers and instances where a
patient is discharged and return to home
health during a 60-day episode, rather
than a discharge and return to the same
HHA during a 60-day episode. In
§ 484.220, we proposed to update the
regulations text to reflect the downward
adjustments to the 60-day episode
payment rate due to changes in the
coding or classification of different units
of service that do not reflect real
changes in case-mix (nominal case-mix
growth) applied to calendar years 2012
and 2013, which were finalized in the
CY 2012 HH PPS final rule (76 FR
68532) as well as updating the CY 2011
adjustment to 3.79 percent as finalized
in the CY 2011 HH PPS final rule (75
FR 70461). In § 484.225 we proposed to
eliminate references to outdated market
basket index factors by removing
paragraphs (b), (c), (d), (e), (f), and (g).
In § 484.230 we proposed to delete the
last sentence as a result of a change from
a separate LUPA add-on amount to a
LUPA add-on factor finalized in the CY
2014 HH PPS final rule (78 FR 72256).
Finally, we proposed deleting and
reserving § 484.245 as we believe that
this language is no longer applicable
under the HH PPS, as it was meant to
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facilitate the transition to the original
PPS established in CY 2000.
Lastly, we proposed to make one
technical correction in § 424.22 to redesignate paragraph (a)(1)(v)(B)(1) as
(a)(2).
We invited comments on these
technical corrections and associated
changes in the regulations in parts 409,
424, and 484. However, we did not
receive any comments regarding the
technical regulations text changes.
Final Decision: We are finalizing the
technical regulations text changes at
§ 409, § 424, and § 484 as proposed.
IV. Provisions of the Home Health
Value-Based Purchasing (HHVBP)
Model and Response to Comments
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A. Background
In the CY 2015 Home Health
Prospective Payment System (HH PPS)
final rule titled ‘‘Medicare and Medicaid
Programs; CY 2015 Home Health
Prospective Payment System Rate
Update; Home Health Quality Reporting
Requirements; and Survey and
Enforcement Requirements for Home
Health Agencies (79 FR 66032–66118),
we indicated that we were considering
the development of a home health
value-based purchasing (HHVBP)
model. We sought comments on a future
HHVBP model, including elements of
the model; size of the payment
incentives and percentage of payments
that would need to be placed at risk in
order to spur home health agencies
(HHAs) to make the necessary
investments to improve the quality of
care for Medicare beneficiaries; the
timing of the payment adjustments; and,
how performance payments should be
distributed. We also sought comments
on the best approach for selecting states
for participation in this model. We
noted that if the decision was made to
move forward with the implementation
of a HHVBP model in CY 2016, we
would solicit additional comments on a
more detailed model proposal to be
included in future rulemaking.
In the CY 2015 HH PPS final rule,8 we
indicated that we received a number of
comments related to the magnitude of
the percentage payment adjustments;
evaluation criteria; payment features; a
beneficiary risk adjustment strategy;
state selection methodology; and the
approach to selecting Medicare-certified
HHAs. A number of commenters
supported the development of a value8 Medicare and Medicaid Programs; CY 2015
Home Health Prospective Payment System Rate
Update; Home Health Quality Reporting
Requirements; and Survey and Enforcement
Requirements for Home Health Agencies, 79 FR
66105–66106 (November 6, 2014).
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based purchasing model in the home
health industry in whole or in part with
consideration of the design parameters
provided. No commenters provided
strong counterpoints or alternative
design options which dissuaded CMS
from moving forward with general
design and framework of the HHVBP
model as discussed in the CY 2015 HH
PPS proposed rule. All comments were
considered in our decision to develop
an HHVBP model for implementation
beginning January 1, 2016. Therefore, in
the CY 2016 HH PPS proposed rule, we
proposed to implement a HHVBP
model, which included a randomized
state selection methodology; a reporting
framework; a payment adjustment
methodology; a payment adjustment
schedule by performance year and
payment adjustment percentage; a
quality measures selection
methodology, classifications and
weighting, measures for performance
year one, including the reporting of New
Measures, and a framework for
proposing to adopt measures for
subsequent performance years; a
performance scoring methodology,
which includes performance based on
achievement and improvement; a
review and recalculation period; and an
evaluation framework. As we discuss in
more detail below, we are finalizing our
proposal to implement the HHVBP
Model beginning January 1, 2016. We
respond to comments received on the
proposed components of the model, and
discuss our final policies with respect to
each of these components, in the
relevant sections below.
The basis for developing the proposed
value-based purchasing (VBP) model, as
described in the proposed regulations at
§ 484.300 et seq., stems from several
important areas of consideration. First,
we expect that tying quality to payment
through a system of value-based
purchasing will improve the
beneficiaries’ experience and outcomes.
In turn, we expect payment adjustments
that both reward improved quality and
penalize poor performance will
incentivize quality improvement and
encourage efficiency, leading to a more
sustainable payment system.
Second, section 3006(b) of the
Affordable Care Act directed the
Secretary of the Department of Health
and Human Services (the Secretary) to
develop a plan to implement a VBP
program for payments under the
Medicare Program for HHAs and the
Secretary issued an associated Report to
Congress in March of 2012 (2012
Report).9 The 2012 Report included a
9 CMS, ‘‘Report to Congress: Plan to Implement a
Medicare Home Health Agency Value-Based
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roadmap for implementation of an
HHVBP model and outlined the need to
develop an HHVBP program that aligns
with other Medicare programs and
coordinates incentives to improve
quality. The 2012 Report also indicated
that a HHVBP program should build on
and refine existing quality measurement
tools and processes. In addition, the
2012 Report indicated that one of the
ways that such a program could link
payment to quality would be to tie
payments to overall quality
performance.
Third, section 402(a)(1)(A) of the
Social Security Amendments of 1967 (as
amended) (42 U.S.C. 1395b–1(a)(1)(A)),
provided authority for us to conduct the
Home Health Pay-for-Performance
(HHPFP) Demonstration that ran from
2008 to 2010. The results of that
demonstration found modest quality
improvement in certain measures after
comparing the quality of care furnished
by demonstration participants to the
quality of care furnished by the control
group. One important lesson learned
from the HHPFP Demonstration was the
need to link the HHA’s quality
improvement efforts and the incentives.
HHAs in three of the four regions
generated enough savings to have
incentive payments in the first year of
the demonstration, but the size of
payments were unknown until after the
conclusion of the demonstration. Also,
the time lag between quality
performance and payment incentives
was too long to provide a sufficient
motivation for HHAs to take necessary
steps to improve quality. The results of
the demonstration, published in a
comprehensive evaluation report 10
suggest that future models could benefit
from ensuring that incentives are
reliable enough, of sufficient magnitude,
and paid in a timely fashion to
encourage HHAs to be fully engaged in
the quality of care initiative.
Furthermore, the President’s FY 2015
and 2016 Budgets proposed that VBP
should be extended to additional
providers including skilled nursing
facilities, home health agencies,
ambulatory surgical centers, and
hospital outpatient departments. The FY
2015 Budget called for at least 2-percent
of payments to be tied to quality and
efficiency of care on a budget neutral
Purchasing Program’’ (March 15, 2012) available at
https://www.cms.gov/Medicare/Medicare-Fee-forService-Payment/HomeHealthPPS/downloads/
stage-2-NPRM.PDF.
10 ‘‘CMS Report on Home Health Agency ValueBased Purchasing Program’’ (February of 2012)
available at https://www.cms.gov/ResearchStatistics-Data-and-Systems/Statistics-Trends-andReports/Reports/Downloads/HHP4P_Demo_Eval_
Final_Vol1.pdf.
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basis. The FY 2016 Budget outlines a
program which would tie at least 2percent of Medicare payments to the
quality and efficiency of care in the first
2 years of implementation beginning in
2017, and at least 5-percent beginning in
2019 without any impact to the budget.
We proposed and are finalizing an
HHVBP model that follows a graduated
payment adjustment strategy within
certain selected states beginning January
1, 2016.
The Secretary has also set two overall
delivery system reform goals for CMS.
First, we seek to tie 30-percent of
traditional, or fee-for-service, Medicare
payments to quality or value-based
payments through alternative payment
models by the end of 2016, and to tie
50-percent of payments to these models
by the end of 2018. Second, we seek to
tie 85-percent of all traditional Medicare
payments to quality or value by 2016
and 90-percent by 2018.11 To support
these efforts the Health Care Payment
Learning and Action Network was
recently launched to help advance the
work being done across sectors to
increase the adoption of value-based
payments and alternative payment
models. We believe that testing the
HHVBP Model would support these
goals.
Finally, we have already successfully
implemented the Hospital Value-Based
Purchasing (HVBP) program, under
which value-based incentive payments
are made in a fiscal year to hospitals
that meet performance standards
established for a performance period
with respect to measures for that fiscal
year. The percentage of a participating
hospital’s base-operating DRG payment
amount for FY 2016 discharges that is
at risk, based on the hospital’s
performance under the program for that
fiscal year, is 1.75 percent. That
percentage will increase to 2.0 by FY
2017. We proposed and are finalizing in
this rule an HHVBP Model that builds
on the lessons learned and guidance
from the HVBP program and other
applicable demonstrations as discussed
above, as well as from the evaluation
report discussed earlier.
As we stated in the CY 2016 HH PPS
proposed rule, the HHVBP Model
presents an opportunity to improve the
quality of care furnished to Medicare
beneficiaries and study what incentives
are sufficiently significant to encourage
HHAs to provide high quality care. The
HHVBP Model will offer both a greater
potential reward for high performing
HHAs as well as a greater potential
11 Content of this announcement can be found at
https://www.hhs.gov/news/press/2015pres/01/
20150126a.html.
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downside risk for low performing
HHAs. We proposed, and are finalizing
in this rule, that the model will begin on
January 1, 2016, and include an array of
measures that would capture the
multiple dimensions of care that HHAs
furnish.
The HHVBP Model, as finalized, will
be tested by CMS’s Center for Medicare
and Medicaid Innovation (CMMI) under
section 1115A of the Act. Under section
1115A(d)(1) of the Act, the Secretary
may waive such requirements of Titles
XI and XVIII and of sections 1902(a)(1),
1902(a)(13), and 1903(m)(2)(A)(iii) as
may be necessary solely for purposes of
carrying out section 1115A with respect
to testing models described in section
1115A(b). The Secretary is not issuing
any waivers of the fraud and abuse
provisions in sections 1128A, 1128B,
and 1877 of the SSA or any other
Medicare or Medicaid fraud and abuse
laws for this model. Thus,
notwithstanding any other provisions of
this rule, all providers participating in
the HHVBP Model must comply with all
applicable fraud and abuse laws and
regulations. Therefore, to clarify the
scope of the Secretary’s authority we
have finalized § 484.300 confirming
authority to establish Part F under
sections 1102, 1115A, and 1871 of the
Act (42 U.S.C. 1315a), which authorizes
the Secretary to issue regulations to
operate the Medicare program and test
innovative payment and service
delivery models to improve
coordination, quality, and efficiency of
health care services furnished under
Title XVIII.
As we proposed, we are using section
1115A(d)(1) waiver authority to apply a
reduction or increase of up to 8-percent
to current Medicare payments to
competing HHAs delivering care to
beneficiaries in selected states,
depending on the HHA’s performance
on specified quality measures relative to
its peers. Specifically, the HHVBP
Model will utilize the waiver authority
to adjust Medicare payment rates under
section 1895(b) of the Act.12 In
accordance with the authority granted to
the Secretary in section 1115A(d)(1) of
the Act, we are waiving section
1895(b)(4) of the Act only to the extent
necessary to adjust payment amounts to
reflect the value-based payment
adjustments under this model for
Medicare-certified HHAs in specified
states selected in accordance with
CMS’s selection methodology. We are
not implementing this model under the
authority granted by the Affordable Care
12 42
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68657
Act under section 3131 (‘‘Payment
Adjustments for Home Health Care’’).
We are finalizing in this rule, as we
proposed, that the defined population
includes all Medicare beneficiaries
provided care by any Medicare-certified
HHA delivering care within the selected
states. Medicare-certified HHAs that are
delivering care within selected states are
considered ‘Competing Home Health
Agencies’ within the scope of this
HHVBP Model. If care is delivered
outside of selected states, or within a
non-selected state that does not have a
reciprocal agreement with a selected
state, payments for those beneficiaries
are not considered within the scope of
the model because we are basing
participation in the model on statespecific CMS Certification Numbers
(CCNs). Payment adjustments for each
year of the model will be calculated
based on a comparison of how well each
competing HHA performed during the
performance period for that year
(proposed, and finalized below, to be
one year in length, starting in CY 2016)
with its performance on the same
measures in 2015 (proposed, and
finalized below, to be the baseline data
year).
As we proposed, and are finalizing in
this rule, the first performance year will
be CY 2016, the second will be CY 2017,
the third will be CY 2018, the fourth
will be 2019, and the fifth will be CY
2020. Greater details on performance
periods are outlined in Section D—
Performance Assessment and Payment
Periods. This model will test whether
being subject to significant payment
adjustments to the Medicare payment
amounts that would otherwise be made
to competing Medicare-certified HHAs
would result in statistically-significant
improvements in the quality of care
being delivered to this specific
population of Medicare beneficiaries.
We proposed, and are finalizing in
this rule, to identify Medicare-certified
HHAs to compete in this model using
state borders as boundaries. We do so
under the authority granted in section
1115A(a)(5) of the Act to elect to limit
testing of a model to certain geographic
areas. This decision is influenced by the
2012 Report to Congress mandated
under section 3006(b) of the Affordable
Care Act. This Report stated that HHAs
which participated in previous valuebased purchasing demonstrations
‘‘uniformly believed that all Medicarecertified HHAs should be required to
participate in future VBP programs so
all agencies experience the potential
burdens and benefits of the program’’
and some HHAs expressed concern that
absent mandatory participation, ‘‘lowperforming agencies in areas with
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limited competition may not choose to
pursue quality improvement.’’ 13
Section 1115A(b)(2)(A) of the Act
requires that the Secretary select models
to be tested where the Secretary
determines that there is evidence that
the model addresses a defined
population for which there are deficits
in care leading to poor clinical
outcomes or potentially avoidable
expenditures. The HHVBP Model was
developed to improve care for Medicare
patients receiving care from HHAs
based on evidence in the March 2014
MedPAC Report to Congress citing
quality and cost concerns in the home
health sector. According to MedPAC,
‘‘about 29-percent of post-hospital home
health stays result in readmission, and
there is tremendous variation in
performance among providers within
and across geographic regions.’’ 14 The
same report cited limited improvement
in quality based on existing measures,
and noted that the data on quality ‘‘are
collected only for beneficiaries who do
not have their home health care stays
terminated by a hospitalization,’’
skewing the results in favor of a
healthier segment of the Medicare
population.15 This model will test the
use of adjustments to Medicare HH PPS
rates by tying payment to quality
performance with the goal of achieving
the highest possible quality and
efficiency.
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B. Overview
We proposed to include in § 484.305
definitions for ‘‘applicable percent’’,
‘‘applicable measure’’, ‘‘benchmark’’,
‘‘home health prospective payment
system’’, ‘‘larger-volume cohort’’,
‘‘linear exchange function’’, ‘‘Medicarecertified home health agency’’, ‘‘New
Measures’’, ‘‘payment adjustment’’,
‘‘performance period’’, ‘‘smaller-volume
cohort’’, ‘‘selected states’’, ‘‘starter set’’,
‘‘Total Performance Score’’, and ‘‘valuebased purchasing’’ as they pertain to
this subpart. Where we received
comments on the proposed definitions
or the substantive provisions of the
model connected to the proposed
definitions, we respond to comments in
the relevant sections below. We are
finalizing all the definitions as proposed
in § 484.305 except for two: We are
revising ‘‘applicable percent’’ so the
final definition reflects the revised
13 See the Recommendations section of the U.S.
Department of Health and Human Services. Report
to Congress: Plan to Implement a Medicare Home
Health Agency Value-Based Purchasing Program.’’
(March 2012) p. 28.
14 See full citation at note 11. MedPAC Report to
Congress (March 2014) p. 215.
15 MedPAC Report to Congress (March 2014) p.
226.
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percentages as 3-percent for CY 2018, 5percent for CY 2019, 6-percent for 2020;
7-percent for CY 2021 and 8-percent for
CY 2022, as discussed in section G and
we are revising ‘‘Medicare-certified
home health agency’’ as ‘‘Competing
home health agency’’ for clarity, since
all HHAs with CCNs are, by definition,
Medicare-certified, and only those
HHAs in selected states are competing
in the model. As we proposed and are
finalizing in this rule, the HHVBP
Model will encompass 5 performance
years and be implemented beginning
January 1, 2016 and conclude on
December 31, 2022.
Payment and service delivery models
are developed by CMMI in accordance
with the requirements of section 1115A
of the Act. During the development of
new models, CMMI builds on the ideas
received from internal and external
stakeholders and consults with clinical
and analytical experts.
We are finalizing our proposal to
implement a HHVBP Model that has an
overall purpose of improving the quality
and efficient delivery of home health
care services to the Medicare
population. The specific goals of the
model are to:
1. Incentivize HHAs to provide better
quality care with greater efficiency;
2. Study new potential quality and
efficiency measures for appropriateness
in the home health setting; and,
3. Enhance current public reporting
processes.
We proposed that the HHVBP Model
would adjust Medicare HHA payments
over the course of the model by up to
8-percent depending on the applicable
performance year and the degree of
quality performance demonstrated by
each competing HHA. As discussed in
greater detail in section G, we are
finalizing this proposal with
modification. Under our final policy,
the model will reduce the HH PPS final
claim payment amount to an HHA for
each episode in a calendar year by an
amount up to the applicable percentage
revised and defined in § 484.305. The
timeline of payment adjustments as they
apply to each performance year is
described in greater detail in the section
D2 entitled ‘‘Payment Adjustment
Timeline.’’
As we proposed, and are finalizing in
this rule, the model will apply to all
Medicare-certified HHAs in each of the
selected states, which means that all
HHAs in the selected states will be
required to compete. We codify this
policy at 42 CFR 484.310. Furthermore,
a competing HHA will only be
measured on performance for care
delivered to Medicare beneficiaries
within selected states (with rare
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exceptions given for care delivered
when a reciprocal agreement exists
between states). The distribution of
payment adjustments will be based on
quality performance, as measured by
both achievement and improvement,
across a set of quality measures
rigorously constructed to minimize
burden as much as possible and
improve care. Competing HHAs that
demonstrate they can deliver higher
quality of care in comparison to their
peers (as defined by the volume of
services delivered within the selected
state), or their own past performance,
could have their payment for each
episode of care adjusted higher than the
amount that otherwise would be paid
under section 1895 of the Act.
Competing HHAs that do not perform as
well as other competing HHAs of the
same size in the same state might have
their payments reduced and those
competing HHAs that perform similarly
to others of similar size in the same state
might have no payment adjustment
made. This operational concept is
similar in practice to what is used in the
HVBP program.
We expect that the risk of having
payments adjusted in this manner will
provide an incentive among all
competing HHAs delivering care within
the boundaries of selected states to
provide significantly better quality
through improved planning,
coordination, and management of care.
The degree of the payment adjustment
will be dependent on the level of quality
achieved or improved from the baseline
year, with the highest upward
performance adjustments going to
competing HHAs with the highest
overall level of performance based on
either achievement or improvement in
quality. The size of a competing HHA’s
payment adjustment for each year under
the model will be dependent upon that
HHA’s performance with respect to that
calendar year relative to other
competing HHAs of similar size in the
same state and relative to its own
performance during the baseline year.
We proposed that states would be
selected randomly from nine regional
groupings for model participation. As
discussed further in section IV.C. of this
rule, we are finalizing this proposal. A
competing HHA is only measured on
performance for care delivered to
Medicare beneficiaries within
boundaries of selected states and only
payments for HHA services provided to
Medicare beneficiaries within
boundaries of selected states will be
subject to adjustment under this model
unless a reciprocal agreement is in
place. Requiring all Medicare-certified
HHAs within the boundaries of selected
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states to compete in the model ensures
that: (1) There is no self-selection bias,
(2) competing HHAs are representative
of HHAs nationally, and (3) there is
sufficient participation to generate
meaningful results. We believe it is
necessary to require all HHAs delivering
care within boundaries of selected states
to be included in the model because, in
our experience, Medicare-providers are
generally reluctant to participate
voluntarily in models in which their
Medicare payments could be subject to
possible reduction. This reluctance to
participate in voluntary models has
been shown to cause self-selection bias
in statistical assessments and thus, may
present challenges to our ability to
evaluate the model. In addition, state
boundaries represent a natural
demarcation in how quality is currently
being assessed through Outcome
Assessment Information Set (OASIS)
measures on Home Health Compare
(HHC). Secondly, it is our intent to
generate an appropriate selection of
competitor types in this model as a
means of yielding the most optimal
level of generalizability and
representativeness of HHAs in the
nation. Finally, having an appropriate
number of competitors within the model
should generate an appropriate
statistical power to detect key effects we
are testing in this model.
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C. Selection Methodology
1. Identifying a Geographic Demarcation
Area
We proposed to adopt a methodology
that uses state borders as boundaries for
demarcating which Medicare-certified
HHAs will be required to compete in the
model and proposed to select nine states
from nine geographically-defined
groupings of five or six states.
Groupings were also defined so that the
successful implementation of the model
would produce robust and generalizable
results, as discussed later in this
section. We are finalizing this approach
here.
We took into account five key factors
when deciding to propose selection at
the state-level for this model. First, if we
required some, but not all, Medicarecertified HHAs that deliver care within
the boundaries of a selected state to
participate in the model, we believe the
HHA market for the state could be
disrupted because HHAs in the model
would be competing against HHAs that
are not included in the model (herein
referenced ‘non-competing HHAs’).
Second, we wanted to ensure that the
distribution of payment adjustments
based on performance under the model
could be extrapolated to the entire
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country. Statistically, the larger the
sample to which payment adjustments
are applied, the smaller the variance of
the sampling distribution and the
greater the likelihood that the
distribution accurately predicts what
would transpire if the methodology
were applied to the full population of
HHAs. Third, we considered the need to
align with other HHA quality program
initiatives including HHC. The HHC
Web site presently provides the public
and HHAs a state- and national-level
comparison of quality. We expect that
aligning performance with the HHVBP
benchmark and the achievement score
will support how measures are currently
being reported on HHC. Fourth, there is
a need to align with CMS regulations
which require that each HHA have a
unique CMS Certification Number
(CCN) for each state in which the HHA
provides service. Fifth, we wanted to
ensure sufficient sample size and the
ability to meet the rigorous evaluation
requirements for CMMI models. These
five factors are important for the
successful implementation and
evaluation of this model.
We expect that when there is a risk for
a downward payment adjustment based
on quality performance measures, the
use of a self-contained, mandatory
cohort of HHA participants will create
a stronger incentive to deliver greater
quality among competing HHAs.
Specifically, it is possible the market
would become distorted if non-model
HHAs are delivering care within the
same market as competing HHAs
because competition, on the whole,
becomes unfair when payment is
predicated on quality for one group and
volume for the other group. In addition,
we expect that evaluation efforts might
be negatively impacted because some
HHAs would be competing on quality
and others on volume, within the same
market.
We proposed the use of state
boundaries after careful consideration of
several alternative selection approaches,
including randomly selecting HHAs
from all HHAs across the country, and
requiring participation from smaller
geographic regions including the
county; the Combined Statistical Area
(CSA); the Core-Based Statistical Area
(CBSA); Metropolitan Statistical Area
(MSA) rural provider level; and the
Hospital Referral Region (HRR) level.
A methodology using a national
sample of HHAs that are randomly
selected from all HHAs across the
country could be designed to include
enough HHAs to ensure robust payment
adjustment distribution and a sufficient
sample size for the evaluation; however,
this approach may present significant
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limitations when compared with the
state boundaries selection methodology
we proposed in this model. Of primary
concern with randomly selecting at the
provider-level across the nation is the
issue with market distortions created by
having competing HHAs operating in
the same market as non-model HHAs.
Using smaller geographic areas than
states, such as counties, CSAs, CBSAs,
rural, and HRRs, could also present
challenges for this model. These smaller
geographic areas were considered as
alternate selection options; however,
their use could result in too small of a
sample size of potential competing
HHAs. As a result, we expect the
distribution of payment adjustments
could become highly divergent among
fewer HHA competitors. In addition, the
ability to evaluate the model could
become more complex and may be less
generalizable to the full population of
Medicare-certified HHAs and the
beneficiaries they serve across the
nation. Further, the use of smaller
geographic areas than states could
increase the proportion of Medicarecertified HHAs that could fall into
groupings with too few agencies to
generate a stable distribution of
payment adjustments. Thus, if we were
to define geographic areas based on
CSAs, CBSAs, counties, or HRRs, we
would need to develop an approach for
consolidating smaller regions into larger
regions.
Home health care is a unique type of
health care service when compared to
other Medicare provider types. In
general, the HHA’s care delivery setting
is in the beneficiaries’ homes as
opposed to other provider types that
traditionally deliver care at a brick and
mortar institution within beneficiaries’
respective communities. As a result, the
HHVBP Model needs to be designed to
account for the unique way that HHA
care is provided in order for results to
be generalizable to the population.
HHAs are limited to providing care to
beneficiaries in the state that they have
a CCN however; HHAs are not restricted
from providing service in a county,
CSA, CBSA or HRR that they are not
located in (as long as the other county/
CBSA/HRR is in the same state in which
the HHA is certified). As a result, using
smaller geographic areas (than state
boundaries) could result in similar
market distortion and evaluation
confounders as selecting providers from
a randomized national sampling. The
reason is that HHAs in adjacent
counties/CSAs/CBSAs/HRRs may not be
in the model but, would be directly
competing for services in the same
markets or geographic regions.
Competing HHAs delivering care in the
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same market area as non-competing
HHAs could generate a spillover effect
where non-model HHAs would be vying
for the same beneficiaries as competing
HHAs. This spillover effect presents
several issues for evaluation as the
dependent variable (quality) becomes
confounded by external influences
created by these non-competing HHAs.
These unintentional external influences
on competing HHAs may be made
apparent if non-competing HHAs
become incentivized to generate greater
volume at the expense of quality
delivered to the beneficiaries they serve
and at the expense of competing HHAs
that are paid on quality instead of
volume. Further, the ability to
extrapolate these results to the full
population of HHAs and the
beneficiaries they serve becomes
confounded by an artifact of the model
and inferences would be limited from
an inability to duplicate these results.
While these concerns would decrease in
some order of magnitude as larger
regions are considered, the only way to
eliminate these concerns entirely is to
define inclusion among Medicarecertified HHAs at the state level.
In addition, home health quality data
currently displayed on HHC allows
users to compare HHA services
furnished within a single state.
Selecting HHAs using other geographic
regions that are smaller and/or cross
state lines could require the model to
deviate from the established process for
reporting quality. For these reasons, we
stated in the proposed rule that we
believe a selection methodology based
on the use of Medicare-certified HHAs
delivering care within state boundaries
is the most appropriate for the
successful implementation and
evaluation of this model. In the
proposed rule, we requested comments
on this proposed state selection
methodology as well as potential
alternatives. We summarize and
respond to comments received at the
end of this section (section IV.C.). As we
discuss below, we are finalizing the
state selection model as proposed.
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2. Overview of the Randomized
Selection Methodology for States
We proposed the state selections
listed in proposed § 484.310 based on
the described proposed randomized
selection methodology. We proposed to
group states by each state’s geographic
proximity to one another accounting for
key evaluation characteristics (that is,
proportionality of service utilization,
proportionality of organizations with
similar tax-exempt status and HHA size,
and proportionality of beneficiaries that
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are dually-eligible for Medicare and
Medicaid).
Based on an analysis of OASIS quality
data and Medicare claims data, we
stated in the proposed rule that we
believe the use of nine geographic
groupings would account for the
diversity of beneficiary demographics,
rural and urban status, cost and quality
variations, among other criteria. To
provide for comparable and equitable
selection probabilities, these separate
geographic groupings each include a
comparable number of states. Under our
proposed methodology, groupings were
based on states’ geographic proximity to
one another, having a comparable
number of states if randomized for an
equal opportunity of selection, and
similarities in key characteristics that
will be considered in the evaluation
study because the attributes represent
different types of HHAs, regulatory
oversight, and types of beneficiaries
served. This is necessary for the
evaluation study to remain objective
and unbiased and so that the results of
this study best represent the entire
population of Medicare-certified HHAs
across the nation.
Several of the key characteristics we
used for grouping state boundaries into
clusters for selection into the model are
also used in the impact analysis of our
annual HHA payment updates, a fact
that reinforces their relevance for
evaluation. The additional proposed
standards for grouping (level of
utilization and socioeconomic status of
patients) are also important to consider
when evaluating the program, because
of their current policy relevance. Large
variations in the level of utilization of
the home health benefit has received
attention from policymakers concerned
with achieving high-value health care
and curbing fraud and abuse.16
Policymakers’ concerns about the role of
beneficiary-level characteristics as
determinants of resource use and health
care quality were highlighted in the
Affordable Care Act, which mandated a
study 17 of access to home health care
for vulnerable populations 18 and, more
recently, the Improving Medicare Post16 See MedPAC Report to Congress: Medicare
Payment Policy (March 2014, Chapter 9) available
at https://medpac.gov/documents/reports/
mar14_entirereport.pdf. See also the Institute of
Medicine Interim Report of the Committee on
Geographic Variation in Health Care Spending and
Promotion of High-Value Health Care: Preliminary
Committee Observations (March 2013) available at
https://iom.edu/Reports/2013/Geographic-Variationin-Health-Care-Spending-and-Promotion-of-HighCare-Value-Interim-Report.aspx.
17 This study can be accessed at https://
www.cms.gov/Center/Provider-Type/Home-HealthAgency-HHA-Center.html.
18 Section 3131(d) of the Affordable Care Act.
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acute Care Transformation (IMPACT)
Act of 2014 required the Secretary to
study the relationship between
individuals’ socioeconomic status and
resource use or quality.19 The
parameters used to define each
geographic grouping are further
described in the next three sections.
a. Geographic Proximity
We explained in the proposed rule
that under this methodology, in order to
ensure that the Medicare-certified HHAs
that would be required to participate in
the model are not all in one region of
the country, the states in each grouping
are adjacent to each other whenever
possible while creating logical
groupings of states based on common
characteristics as described above.
Specifically, analysis based on quality
data and claims data found that HHAs
in these neighboring states tend to hold
certain characteristics in common.
These include having similar patterns of
utilization, proportionality of non-profit
agencies, and types of beneficiaries
served (for example, severity and
number, type of co-morbidities, and
socio-economic status). Therefore, the
proposed groupings of states were
delineated according to states’
geographic proximity to one another
and common characteristics as a means
of permitting greater comparability. In
addition, each of the groupings retains
similar types of characteristics when
compared to any other type of grouping
of states.
b. Comparable Number of States in Each
Grouping
Under the proposed randomized
selection methodology, each geographic
region, or grouping, has a similar
number of states. As a result, all states
had a 16.7-percent to 20-percent chance
of being selected under our proposed
methodology, and Medicare-certified
HHAs had a similar likelihood of being
required to compete in the model by
using this sampling design. We asserted
in the proposed rule that this sampling
design would ensure that no single
entity is singled out for selection, since
all states and Medicare-certified HHAs
would have approximately the same
chance of being selected. In addition,
this sampling approach would mitigate
the opportunity for HHAs to self-select
into the model and thereby bias any
results of the test.
19 Improving Medicare Post-acute Care
Transformation (IMPACT) Act of 2014 (Public Law
113–185).
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c. Characteristics of State Groupings
Without sacrificing an equal
opportunity for selection, we explained
in the proposed rule that the proposed
state groupings are intended to ensure
that important characteristics of
Medicare-certified HHAs that deliver
care within state boundaries can be used
to evaluate the primary intervention
with greater generalizability and
representativeness of the entire
population of Medicare-certified HHAs
in the nation. Data analysis of these
characteristics employed the full data
set of Medicare claims and OASIS
quality data. Although some
characteristics, such as beneficiary age
and case-mix, yielded some variations
from one state to another, other
important characteristics do vary
substantially and could influence how
HHAs respond to the incentives of the
model. Specifically, home health
services utilization rates, tax-exemption
status of the provider, the
socioeconomic status of beneficiaries (as
measured by the proportion of duallyeligible beneficiaries), and agency size
(as measured by average number of
episodes of care per HHA), are
important characteristics that could
influence outcomes of the model.
Subsequently, we intend to study the
impacts of these characteristics for
purposes of designing future valuebased purchasing models and programs.
These characteristics and expected
variations must be considered in the
evaluation study to enable us to avoid
erroneous inferences about how
different types of HHAs will respond to
HHVBP incentives.
Under our proposed state selection
methodology, state groupings reflect
regional variations that enhance the
generalizability of the model. In line
with this methodology, each grouping
includes states that are similar in at
least one important aforementioned
characteristic while being
geographically located in close
proximity to one another. Using the
criteria described above, the following
geographic groupings were identified
using Medicare claims-based data from
calendar years 2013–2014. Each of the
50 states was assigned to one of the
following geographic groups:
• Group #1: (VT, MA, ME, CT, RI,
NH)
States in this group tend to have
larger HHAs and have average
utilization relative to other states.
• Group #2: (DE, NJ, MD, PA, NY)
States in this group tend to have
larger HHAs, have lower utilization, and
provide care to an average number of
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dually-eligible beneficiaries relative to
other states.
• Group #3: (AL, GA, SC, NC, VA)
States in this group tend to have
larger HHAs, have average utilization
rates, and provide care to a high
proportion of minorities relative to other
states.
• Group #4: (TX, FL, OK, LA, MS)
States in this group have HHAs that
tend to be for-profit, have very high
utilization rates, and have a higher
proportion of dually-eligible
beneficiaries relative to other states.
• Group #5: (WA, OR, AK, HI, WY,
ID)
States in this group tend to have
smaller HHAs, have average utilization
rates, and are more rural relative to
other states.
• Group #6: (NM, CA, NV, UT, CO,
AZ)
States in this group tend to have
smaller HHAs, have average utilization
rates, and provide care to a high
proportion of minorities relative to other
states.
• Group #7: (ND, SD, MT, WI, MN,
IA)
States in this group tend to have
smaller HHAs, have very low utilization
rates, and are more rural relative to
other states.
• Group #8: (OH, WV, IN, MO, NE.,
KS)
States in this group tend to have
HHAs that are of average size, have
average utilization rates, and provide
care to a higher proportion of duallyeligible beneficiaries relative to other
states.
• Group #9: (IL, KY, AR, MI, TN)
States in this group tend to have
HHAs with higher utilization rates
relative to other states.
d. Randomized Selection of States
We stated in the proposed rule that
upon the careful consideration of the
alternative selection methodologies
discussed in that rule, including
selecting states on a non-random basis,
we proposed to use a selection
methodology based on a randomized
sampling of states within each of the
nine regional groupings described
above. We examined data on the
evaluation elements listed in this
section of the proposed rule and this
final rule to determine if specific states
could be identified in order to fulfill the
needs of the evaluation. After careful
review, we determined that each
evaluation element could be measured
by more than one state. As a result, we
determined that it was necessary to
apply a fair method of selection where
each state would have a comparable
opportunity of being selected and which
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68661
would fulfill the need for a robust
evaluation. The proposed nine
groupings of states, as described in this
section of the proposed rule and this
final rule, permit the model to capture
the essential elements of the evaluation
including demographic, geographic, and
market factors.
We explained in the proposed rule
that the randomized sampling of states
is without bias to any characteristics of
any single state within any specific
regional grouping, where no states are
excluded, and no state appears more
than once across any of the groupings.
The randomized selection of states was
completed using a scientificallyaccepted computer algorithm designed
for randomized sampling. The
randomized selection of states was run
on each of the previously described
regional groupings using exactly the
same process and, therefore, reflects a
commonly accepted method of
randomized sampling. This computer
algorithm employs the aforementioned
sampling parameters necessary to define
randomized sampling and omits any
human interaction once it runs.
Based on this sampling methodology,
SAS Enterprise Guide (SAS EG) 5.1
software was used to run a computer
algorithm designed to randomly select
states from each grouping. SAS EG 5.1
and the computer algorithm were
employed to conduct the randomized
selection of states. SAS EG 5.1
represents an industry-standard for
generating advanced analytics and
provided a rigorous, standardized tool
by which to satisfy the requirements of
randomized selection. The key SAS
commands employed include a ‘‘PROC
SURVEYSELECT’’ statement coupled
with the ‘‘METHOD=SRS’’ option used
to specify simple random sampling as
the sample selection method. A random
number seed was generated by using the
time of day from the computer’s clock.
The random number seed was used to
produce random number generation.
Note that no stratification was used
within any of the nine geographicallydiverse groupings to ensure there is an
equal probability of selection within
each grouping. For more information on
this procedure and the underlying
statistical methodology, please reference
SAS support documentation at: https://
support.sas.com/documentation/cdl/en/
statug/63033/HTML/default/
viewer.htm#statug_surveyselect_
sect003.htm/.
Based on consideration of the
comments received and for the reasons
discussed, we believe this state
selection methodology provides the
strongest evidence of producing
meaningful results representative of the
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national population of competing
Medicare-certified HHAs and, in turn,
meets the evaluation requirements of
section 1115A(b)(4) of the Act.
In § 484.310, we proposed to codify
the names of the states selected utilizing
this proposed methodology, where one
state from each of the nine groupings
was selected. For each of these
groupings, we proposed to use state
borders to demarcate which Medicarecertified HHAs would be required to
compete in this model: Massachusetts
was randomly selected from Group 1,
Maryland was randomly selected from
Group 2, North Carolina was randomly
selected from Group 3, Florida was
randomly selected from Group 4,
Washington was randomly selected
from Group 5, Arizona was randomly
selected from Group 6, Iowa was
randomly selected from Group 7,
Nebraska was randomly selected from
Group 8, and Tennessee was randomly
selected from Group 9. Thus, we
explained in the proposed rule that if
our methodology is finalized as
proposed, all Medicare-certified HHAs
that provide services in Massachusetts,
Maryland, North Carolina, Florida,
Washington, Arizona, Iowa, Nebraska,
and Tennessee will be required to
compete in this model. We invited
comments on this proposed randomized
selection methodology.
We summarize and respond to these
comments at the end of this section. As
discussed we are finalizing the state
selection methodology as proposed
without modification, as well as
finalizing the states that were selected
utilizing this methodology as codified in
§ 484.310.
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e. Use of CMS Certification Numbers
(CCNs)
We proposed that Total Performance
Scores (TPS) and payment adjustments
would be calculated based on an HHA’s
CCN 20 and, therefore, based only on
services provided in the selected states.
The exception to this methodology is
where an HHA provides service in a
state that also has a reciprocal
agreement with another state. Services
being provided by the HHA to
beneficiaries who reside in another state
would be included in the TPS and
subject to payment adjustments.21 The
20 HHAs are required to report OASIS data and
any other quality measures by its own unique CMS
Certification Number (CCN) as defined under title
42, chapter IV, subchapter G, part 484, § 484.20
Available at URL https://www.ecfr.gov/cgi-bin/textidx?tpl=/ecfrbrowse/Title42/42cfr484_main_02.tpl.
21 See Chapter 2 of the State Operations Manual
(SOM), Section 2184—Operation of HHAs Cross
State Lines, stating ‘‘When an HHA provides
services across State lines, it must be certified by
the State in which its CCN is based, and its
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reciprocal agreement between states
allows for an HHA to provide services
to a beneficiary across state lines using
its original CCN number. Reciprocal
agreements are rare and, as identified
using the most recent Medicare claims
data from 2014, there was found to be
less than 0.1 percent of beneficiaries
that provided services that were being
served by CCNs with reciprocal
agreements across state lines. Due to the
very low number of beneficiaries served
across state borders as a result of these
agreements, we stated in the proposed
rule that we expect there to be an
inconsequential impact by including
these beneficiaries in the model.
We received the following comments
on the proposed selection methodology.
As discussed, we are finalizing the
selection methodology as proposed.
Comment: A few commenters
expressed concern that participating
HHAs will receive payment adjustment
incentives based on quality of care,
while non-participating HHAs in the
same geographic area might be
incentivized to generate greater volume
at the expense of quality. Some
commenters recommended expanding
the model to allow more states to
participate in each succeeding year of
the model to prevent non-participating
states from falling behind, and some
commenters also recommended CMS
shorten the duration of the model to
three (3) years to expedite the
implementation of VBP nationally.
Response: Competing HHAs within
the selected states will not be compared
with non-competing HHAs within the
same geographic area. HHAs will not
compete across state borders, other than
those HHAs that may provide services
in a state that has a reciprocal agreement
with another state. Specifically, the
model is designed to have HHAs
compete only within their state and
within their size cohort, as discussed
further in section F. Competing HHAs
will not compete for payment
adjustment incentives outside of their
state or size cohort. The decision to
utilize states to select HHAs for
inclusion in the model was based on a
range of factors related to
implementation and evaluation and
weighed against other selection
alternatives. Specifically, we considered
how the competing HHA’s CCN is
operationalized at the state-level and
how evaluation will determine whether
the payment adjustment incentive has
personnel must be qualified in all States in which
they provide services. The appropriate SA
completes the certification activities. The involved
States must have a written reciprocal agreement
permitting the HHA to provide services in this
manner.’’
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an effect on quality within each
competing HHA’s state and size-cohort.
In response to comments suggesting that
non-competing HHAs in non-selected
states might ‘fall behind,’ we again
reference the design of the payment
methodology which precludes noncompetitors from competing outside of
selected states and size-cohorts. The
purpose of this model is to test the effect
of high incentives on quality.
Performance measurement is based on a
linear exchange function which only
includes competing-HHAs. If the model
yields early positive results within these
states and competing cohorts, expansion
may be considered if the requirements
of the statute are met. Section 1115A(c)
of the Act authorizes the Secretary to
expand the scope and duration of a
model being tested through rulemaking,
including implementation on a
nationwide basis. In addition, we do not
expect that HHAs in non-selected states
would fall significantly behind in
improving quality because of their
interest in attracting beneficiaries, and
improving performance on quality
metrics in other programs, such as the
HHQRP. Further, we believe testing the
model over 5 years will provide more
data with which to evaluate the effects
of high incentives with greater certainty.
Comment: Several commenters
expressed concern regarding how HHAs
are selected to participate in the HHVBP
Model. Commenters expressed concerns
centered on leaving behind innovative
HHAs in non-participating states. Many
commenters recommended including
voluntary participation by interested
innovative HHAs in non-participating
states and carefully documenting
characteristics of selected agencies.
Commenters also stated that mandatory
participation may potentially put
agencies with fewer resources in
selected states at risk for closure.
Response: We appreciate the
comments and input on the state
selection methodology. The selection
methodology was based on lessons
learned, industry stakeholder
perspectives, and an analysis of
Medicare data. For the reasons
discussed above, we believe that
application of this methodology will
result in participation by HHAs that
represent an accurate reflection of the
entire population of Medicare-certified
HHAs, both in terms of size and in
terms of quality. In general, providers
do not voluntarily participate in
alternate payment models when
payments are at risk of being lowered.
This reluctance to participate in
voluntary models has been shown to
cause self-selection bias in statistical
assessments and thus, we believe that
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allowing voluntary participation by
interested HHAs in non-participating
states could present challenges to our
ability to evaluate the model. In
reference to concerns that some HHAs
with fewer resources may be at greater
risk for closure, CMS will continue to
monitor for direct associations between
HHAs that exhibit poor performance
and the effect of the payment
adjustment incentive.
Comment: Commenters questioned
the fairness of being required to
participate in both the proposed HHVBP
Model and the proposed Comprehensive
Care Joint Replacement Model (CJR).
Response: HHAs located in the MSAs
included in the proposed CJR Model
will not be excluded from the HHVBP
Model. HHAs are not participants in the
proposed CJR Model. As proposed,
Hospitals are the participants. Home
health payments for beneficiaries
participating in the proposed CJR are
not subject to alteration under that
model. As proposed, only the hospital
payments are at risk. HHAs will
continue to be paid for the services they
provide to and bill for Medicare
beneficiaries that are participating in the
proposed CJR.
Comment: Some commenters
expressed concern that state selection
will not sufficiently represent the
Medicare population at large and
impacts a disproportionate portion of
the Medicare population. Another
commenter recommended CMS
consider a hardship exemption for
HHAs with a high percentage of
Medicaid services or that serve a high
percentage of dual-eligible patients.
Commenters also expressed concern on
various topics around state selection,
including lack of complex urban areas
and corresponding utilization patterns;
peer cohorts based simply on size and
state; consideration of profit or nonprofit status, hospital-based or freestanding HHAs, and rural and urban
status, all related to either underrepresentation or potential bias in the
selected competing HHAs, or overrepresentation of certain subpopulations of Medicare beneficiaries
included in the model One commenter
also recommended excluding states
with populations under a certain
threshold, such as 2.5 million, to ensure
a large population and making the
model more robust.
Response: We have taken into
consideration the level of utilization
and socioeconomic status of patients in
grouping states for random selection,
and will evaluate the model sensitive to
these differences. The alternative
methodologies proposed by
stakeholders did not fulfill the
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requirements to be generalizable and
representative of the entire population
of Medicare-certified HHAs in the
nation. Our mechanisms, including
tracking quality improvement through
performance measures and conducting
comparative analysis based on
variations on HHA size, geographic
location, organizational structure, and
other HHA demographic information
will be utilized for evaluating the
model. We have conducted extensive
analysis on the population of HHAs
included in the model and are confident
we will be able to effectively extrapolate
model results to the general population.
In part, this analysis is referenced in
Table 24 and finds an association
between the higher proportion of
dually-eligible beneficiaries serviced
and better performance. The
performance and subsequent payment
distributions are consistent with respect
to the four described categories (that is
dually-eligible, level of acuity, percent
rural, and organization type). In
addition, CMS conducted a statistical
analysis of the sample size of HHAs
provided by the nine selected states and
determined it was sufficient to
effectively detect the model’s impact.
Comment: One commenter stated that
Maryland should not be included in the
selected states for HHVBP because
Maryland is already participating in the
Maryland All Payer Model. Another
commenter suggested that Florida not be
included in both HHVBP and ACO
bundling models because it is difficult
for HHAs to track compliance with all
relevant policy and regulatory
requirements.
Response: We understand the
variances in state demographics, state
regulatory structures, and the interplay
with other federal initiatives, and intend
to evaluate how the HHVBP Model
performs in the selected states,
including interactions with existing
policies, models and programs operating
in the specific states selected. For
example, the Maryland All-Payer Model
does not directly intersect with HHVBP
because it is a hospital-based model, so
we do not believe this is a compelling
reason to exclude this state. In addition,
concerns that Florida Medicare-certified
HHAs would also be included in ACO
models is not a compelling reason to
exclude this state because other states
have HHAs participating within ACO
models. We do, however, recognize the
need to evaluate the impact of the
model in the context of the various
policies and programs operating in
those states where participating HHAs
serve patients. As discussed, after
consideration of the public comments
received, we are finalizing our proposal
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to include the nine selected states as
stated in Section 2. In comparison to
other alternatives for selection, we
believe the proposed randomized stateselection method provides an equitable
process of selection and a comparable
number of HHAs to account for the
power to detect statistical variations
between the payment adjustment
incentive as well as non-financial
incentives and their effect on quality.
The nine selected states finalized here
will participate for the full duration of
the model.
Comment: One commenter suggested
that selected states be more homogenous
in having no prior experience in VBP
and to exclude any states that
participated in 2008–2010 HH Pay for
Performance demonstration.
Response: We understand concerns
about previous program and model
participation in that some competitors
may be more prepared for VBP in
comparison to others. While we are not
convinced that we can attribute the
level of preparedness for VBP to the
HHA’s experience with the HHP4P
Demonstration or any other VBP
initiative, we intentionally developed a
methodology for randomized selection
of states to prevent bias to any
characteristics of any single state within
any specific grouping. As a result of this
randomness of selection, the design
permits an equitable opportunity for
selection and provides a greater capacity
to generalize results to the entire
population of Medicare-certified HHAs
in the U.S.
Final Decision: For the reasons stated
and in consideration of the comments
received, we are finalizing the state
selection methodology as proposed,
including the nine states selected under
this methodology as codified at
§ 484.310. All Medicare-certified HHAs
that provide services in Massachusetts,
Maryland, North Carolina, Florida,
Washington, Arizona, Iowa, Nebraska,
and Tennessee will be required to
compete in the HHVBP Model.
D. Performance Assessment and
Payment Periods
1. Performance Reports
We proposed to use quarterly
performance reports, annual payment
adjustment reports, and annual
publicly-available performance reports
as a means of developing greater
transparency of Medicare data on
quality and aligning the competitive
forces within the market to deliver care
based on value over volume, and are
finalizing this reporting structure here.
The publicly-reported reports will
inform home health industry
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stakeholders (consumers, physicians,
hospitals) as well as all competing
HHAs delivering care to Medicare
beneficiaries within selected state
boundaries on their level of quality
relative to both their peers and their
own past performance.
We proposed that competing HHAs
would be scored for the quality of care
delivered under the model based on
their performance on measures
compared to both the performance of
their peers, defined by the same size
cohort (either smaller- or larger-volume
cohorts as defined in § 484.305), and
their own past performance on the
measures. We also proposed in
§ 484.305 to define larger-volume cohort
to mean the group of competing HHAs
within the boundaries of a selected state
that are participating in Home Health
Care Consumer Assessment of
Healthcare Providers and Systems
(HHCAHPS) in accordance with
§ 484.250 and to define smaller-volume
cohort to mean the group of HHAs
within the boundaries of a selected state
that are exempt from participation in
HHCAHPS in accordance with
§ 484.250. We also proposed where
there are too few HHAs in the smallervolume cohort in each state to compete
in a fair manner (that is, when there is
only one or two HHAs competing
within a small cohort in a given state),
these HHAs would be included in the
larger-volume cohort for purposes of
calculating the total performance score
and payment adjustment without being
measured on HHCAHPS. We requested
comments on this proposed
methodology.
Comment: A few commenters
mentioned the cohort methodology in
their submissions. One commenter
offered support to CMS’s decision to
measure each HHA against a
comparable cohort by size of agency and
agreed that large HHAs with multiple
locations have a scale that smaller
agencies do not, rendering outcomes
difficult to measure by comparison.
Conversely, other commenters did not
support CMS’s proposal to base
performance payments on relative
performance within HHA peer cohorts,
with one commenter recommending
payments should be based solely on
comparisons to prior year performance
and another suggesting using national
data for all HHAs, taking into account
socio-demographic factors.
Response: Analysis of existing HHA
data (see 80 FR 39910, Table 26—HHA
Cohort Payment Adjustment
Distributions by State) indicates
dividing HHAs into large and small
cohorts results in a higher likelihood of
fair and accurate performance
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comparisons and the subsequent
payment adjustments. We intend to
closely evaluate model outcomes across
a range of demographic factors within
the small and large cohorts, and may
modify the model if warranted in
subsequent years.
Final Decision: After considering the
comments received, we are finalizing
the large and small cohort structure as
proposed.
We proposed that quality performance
scores and relative peer rankings would
be determined through the use of a
baseline year (calendar year 2015) and
subsequent performance periods for
each competing HHA. Further, these
reports will provide competing HHAs
with an opportunity to track their
quality performance relative to their
peers and their own past performance.
Using these reports provides a
convenient and timely means for
competing HHAs to assess and track
their own respective performance as
capacity is developed to improve or
sustain quality over time.
Beginning with the data collected
during the first quarter of CY 2016 (that
is, data for the period January 1, 2016
to March 31, 2016), and for every
quarter of the model thereafter, we
proposed to provide each Medicarecertified HHA with a quarterly report
that contains information on their
performance during the quarter. We
stated that we expect to make the first
quarterly report available in July 2016,
and make performance reports for
subsequent quarters available in
October, January and April. The final
quarterly report would be made
available in April 2021. We proposed
that the quarterly reports would include
a competing HHA’s model-specific
performance results with a comparison
to other competing HHAs within its
cohort (larger- or smaller-volume)
within the state boundary. These modelspecific performance results will
complement all quality data sources
already being provided through the
QIES system and any other quality
tracking system possibly being
employed by HHAs. We note that all
performance measures that competing
HHAs will report through the QIES
system are also already made available
in the CASPER Reporting application.
The primary difference between the two
reports (CASPER reports and the modelspecific performance report) is that the
model-specific performance report we
proposed consolidates the applicable
performance measures used in the
HHVBP Model and provides a peerranking to other competing HHAs
within the same state and size-cohort. In
addition, CASPER reports will provide
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quality data earlier than model-specific
performance reports because CASPER
reports are not limited by a quarterly
run-out of data and a calculation of
competing peer-rankings. For more
information on the accessibility and
functionality of the CASPER system,
please reference the CASPER Provider
Reporting Guide.22
We proposed that the model-specific
quarterly performance report will be
made available to each HHA through a
dedicated CMMI model-specific
platform for data dissemination and
include each HHA’s relative ranking
amongst its peers along with
measurement scores and overall
performance rankings.
We also proposed that a separate
payment adjustment report would be
provided once a year to each of the
competing HHAs. This annual report
will focus primarily on the payment
adjustment percentage and include an
explanation of when the adjustment will
be applied and how this adjustment was
determined relative to performance
scores. Each competing HHA will
receive its own annual payment
adjustment report viewable only to that
HHA.
We also proposed a separate, annual,
publicly available quality report that
would provide home health industry
stakeholders, including providers and
suppliers that refer their patients to
HHAs, with an opportunity to confirm
that the beneficiaries they are referring
for home health services are being
provided the best possible quality of
care available.
We invited comments on the
proposed reporting framework.
Comment: Some commenters
expressed support for the proposed
HHVBP reporting framework of
quarterly/annual reports and public
reporting. Specifically, one commenter
supported CMS in its efforts to provide
agencies with performance reports and
notices of payment change prior to the
imposition of any payment penalty. One
commenter suggested that CMS employ
a continuous improvement cycle with
industry stakeholders to maximize the
value of the annual publicly available
quality reports so that information does
not mislead beneficiaries. Another
commenter supported the proposed
timeliness with which quarterly reports
would be made available to HHAs after
agency data submission, but expressed
doubts about CMS’s ability to comply
with its own proposed timeline for
22 The Casper Reporting Guide is available at
https://www.cms.gov/Medicare/Quality-InitiativesPatient-Assessment-Instruments/
HomeHealthQualityInits/downloads/
HHQICASPER.pdf).
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releasing quarterly reports. Conversely,
a few commenters suggested that
challenges related to providing updated
quarterly reports on performance should
be considered more fully before
implementation. Some commenters also
suggested that CMS should include in
future rulemaking how quarterly
reconciliation will be implemented.
Another commenter posited that current
reporting timeframes, even if complied
with, do not give small and rural HHAs
enough lead time to improve quality.
Response: We thank the commenters
for their overall support for the
inclusion of performance reports for all
competing HHAs and industry
stakeholders. In reference to concerns
with the timelines for delivery of
reports, we intend to meet all
performance report timeline
expectations. However, in this final
rule, we are revising the timelines for
notification and preview of the annual
payment adjustment to remove the
references to specific days of the month
set forth in the proposed rule. This will
allow for greater flexibility for the
industry and CMS to meet these
expectations and to account for the
possibility of a specific day falling on a
weekend or holiday. Through technical
assistance efforts, we will continuously
work with all competing-HHAs and
stakeholders in how these reports are
interpreted and reconciled and how
they may be used to support
transformational efforts to deliver care
within the HHVBP system of incentives.
Comment: Some comments offered
their general support of the HHVBP
public reporting of performance data
because it will inform industry
stakeholders of quality improvements,
and noted several areas of value in
performance data. Specifically,
commenters suggested public reports
would permit providers to steer patients
to high-performing HHAs based on
quality reports. Commenters offered that
to the extent possible, accurate
comparable data will provide HHAs the
ability to improve care delivery and
patient outcomes, while better
predicting and managing quality
performance and payment updates.
These same commenters urged CMS to
consider the HHA information
technology infrastructure needed to
support complex performance tracking
connected with a VBP program. Overall,
commenters generally encouraged the
transparency of data pertaining to the
HHVBP Model.
Response: As part of the HHVBP
Model, we will provide technical
assistance and other tools for HHAs in
selected states to encourage best
practices when making changes to
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improve quality. We anticipate that the
HHVBP learning network will be an
integral part of data monitoring and
performance related discussion and
feedback. As indicated in the proposed
rule (see 80 FR 39873) we also intend
to make public competing HHAs’ Total
Performance Scores with the intention
of encouraging providers and other
stakeholders to utilize quality ranking
when selecting an HHA.
Final Decision: For the reasons
discussed and in consideration of the
comments received, we are finalizing
the reporting framework for the HHVBP
Model as proposed without
modification.
2. Payment Adjustment Timeline
We proposed to codify in § 484.325
that competing HHAs will be subject to
upward or downward payment
adjustments based on the agency’s Total
Performance Score. We proposed that
the model would consist of 5
performance years, where each
performance year would link
performance to the opportunity and risk
for payment adjustment up to an
applicable percent as defined in
proposed § 484.305. The 1st
performance year would transpire from
January 1, 2016 through December 31,
2016, and subsequently, all other
performance years would be assessed on
an annual basis through 2020 unless
modified through rulemaking. We
proposed that the first payment
adjustment would begin January 1, 2018
applied to that calendar year based on
2016 performance data. Subsequently,
all other payment adjustments would be
made on an annual basis through the
conclusion of the model. We proposed
that payment adjustments would be
increased incrementally over the course
of the model with a maximum payment
adjustment of 5-percent (upward or
downward) in 2018 and 2019, a
maximum payment adjustment of 6percent (upward or downward) in 2020,
and a maximum payment adjustment of
8-percent (upward or downward) in
2021 and 2022. We proposed to
implement this model over a total of
seven (7) years beginning on January 1,
2016, and ending on December 31, 2022.
After consideration of comments
received, we are modifying the final
payment adjustment percentages as
discussed in Section G and finalized in
§ 484.305.
We proposed that the baseline year
would run from January 1, 2015 through
December 31, 2015 and provide a basis
from which each respective HHA’s
performance will be measured in each
of the performance years. Data related to
performance on quality measures will
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continue to be provided from the
baseline year through the model’s
tenure using a dedicated HHVBP webbased platform specifically designed to
disseminate data in this model (this
‘‘portal’’ will present and archive the
previously described quarterly and
annual quality reports). Further, HHAs
will provide performance data on the
three new quality measures discussed in
section E5 through this platform as well.
Any additional measures added through
the model’s tenure and proposed
through future rulemaking, will use data
from the previous calendar year as the
baseline.
We proposed that new market entries
(specifically, new competing HHAs
delivering care in the boundaries of
selected states) would also be measured
from their first full calendar year of
services in the state, which would be
treated as baseline data for subsequent
performance years under this model.
The delivery of services would be
measured by the number of episodes of
care for Medicare beneficiaries and used
to determine whether an HHA falls into
the smaller- or larger-volume cohort.
Furthermore, these new market entries
would be competing under the HHVBP
Model in the first full calendar year
following the full calendar year baseline
period.
We proposed that HHAs would be
notified in advance of their first
performance level and payment
adjustment being finalized, based on the
2016 performance period (January 1,
2016 to December 31, 2016), with their
first payment adjustment to be applied
January 1, 2018 through December 31,
2018. We proposed that each competing
HHA would be notified of this first
pending payment adjustment on August
1, 2017 and a preview period would run
for 10 days through August 11, 2017.
This preview period would provide
each competing HHA an opportunity to
reconcile any performance assessment
issues relating to the calculation of
scores prior to the payment adjustment
taking effect, in accordance with the
process in Section H—Preview and
Period to Request Recalculation. Once
the preview period ends, any changes
would be reconciled and a report
finalized no later than November 1,
2017 (or 60 days prior to the payment
adjustment taking affect). As discussed
further in section H, we are finalizing
this proposal with modification, to
allow for a longer preview period of
quarterly performance reports and
annual payment adjustment reports for
all competing HHAs. Specifically, we
are extending the preview period such
that each HHA will be notified of the
first pending payment adjustment in
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August 2017 and followed by a 30-day
preview period.
We proposed that subsequent
payment adjustments would be
calculated based on the applicable full
calendar year of performance data from
the quarterly reports, with competing
HHAs notified and payments adjusted,
respectively, every year thereafter. As a
sequential example, the second payment
adjustment will occur January 1, 2019
based on a full 12 months of the CY
2017 performance period. Notification
of the second adjustment will occur in
August of 2018, followed by a 30-day
preview period (under our
modifications to the proposed
notification and preview timeline, as
discussed previously) and followed by
reconciliation prior to November 1,
2018. Subsequent payment adjustments
will continue to follow a similar
timeline and process.
Beginning in CY 2019, we may
consider revising this payment
adjustment schedule and updating the
payment adjustment more frequently
than once each year if it is determined
that a more timely application of the
adjustment as it relates to performance
improvement efforts that have
transpired over the course of a calendar
year would generate increased
improvement in quality measures.
Specifically, we would expect that
having payment adjustments transpire
closer together through more frequent
performance periods would accelerate
improvement in quality measures
because HHAs would be able to justify
earlier investments in quality efforts and
be incentivized for improvements. In
effect, this concept may be
operationalized to create a smoothing
effect where payment adjustments are
based on overlapping 12-month
performance periods that occur every 6
months rather than annually. As an
example, the normal 12-month
performance period occurring from
January 1, 2020 to December 31, 2020
might have an overlapping 12-month
performance period occurring from July
1, 2020 to June 30, 2021. Following the
regularly scheduled January 1, 2022
payment adjustments, the next
adjustments could be applied to
payments beginning on July 1, 2022
through December 31, 2022. Depending
on if and when more frequent payment
adjustments would be applied,
performance would be calculated based
on the applicable 12-months of
performance data, HHAs notified, and
payments adjusted, respectively, every
six months thereafter, until the
conclusion of the model. As a result,
separate performance periods would
have a 6-month overlap through the
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conclusion of the model. HHAs would
be notified through rulemaking and be
given the opportunity to comment on
any proposed changes to the frequency
of payment adjustments.
We received the following comments
on this proposed payment adjustment
schedule.
Comment: Many commenters
recommended a delay in the payment
adjustment schedule. One commenter
recommended that CMS collect and
report quality data for 2016 as an
educational exercise only, and use 2017
data as the basis to adjust payment rates
beginning in October 2018. This same
commenter also recommended CMS
delay the first year of rate adjustments
by nine months to October 1, 2018.
Another commenter supported the
importance of HHAs in the VBP
program not experiencing payment
adjustments until two years after the
performance year in an effort to
minimize the programmatic impact and
allow agencies the ability to plan ahead.
Several commenters suggested a one
year delay in implementing the model,
citing the timeline as too aggressive. A
few commenters posited that it is
difficult for HHAs in the HHVBP Model
to begin preparing for the model now
without a final rule to guide them, and
noted concern that the final rule will
publish so close to the beginning of the
model. Some commenters specifically
supported payment adjustment on an
annual basis, positing adjustments made
more frequently than once each year
may jeopardize the financial viability of
smaller volume providers, causing
further disruption, as multiple
adjustments throughout a fiscal year
would be difficult to manage. Further,
due to the delay in data collection and
reporting used in these programs,
significant change in performance in
shorter increments would be unlikely,
as quality improvement initiatives take
time to fully implement and for results
to be realized. Another commenter
offered that any move to increase the
payment adjustment to every 6 months
would not offer HHAs sufficient time to
improve clinician practice patterns and
evaluate the effectiveness of the changes
made.
Response: We are finalizing the
proposed payment adjustment timeline
for model implementation on an annual
basis. Any changes to the frequency of
payment adjustments under the model
would be implemented through future
rulemaking. In response to concerns
with having the first performance year
tied to an annual payment adjustment in
2018, we expect that competing HHAs
will begin transforming delivery
patterns as soon as this model is
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implemented. Delaying the payment
adjustment, which is the primary
intervention in this model, limits the
ability to understand the intervention’s
associated effect on quality. We expect
that model-specific technical assistance
which will be made available to all
competing-HHAs will provide the
appropriate information and tools
needed to transform how care is
delivered within the HHVBP Model.
Comment: Several commenters
expressed concern about the time lag
between the performance year and the
year in which payment adjustments
would be applied and strongly
recommended less time lapse between
performance measurement and payment
adjustment. One commenter
recommended CMS revise the HHVBP
Model so that rewards and penalties are
imposed within 6 months of the end of
the measurement period, rather than a
full year later, and consider imposing
the rewards and penalties for 6 months
at a time, allowing the rates to return to
normal for the first 6 months of the
subsequent year. Another commenter
offered that this expedited timeframe
would allow agencies working towards
improvement to have the resources
available to do so more immediately.
Response: We agree that there may be
merit in closing the gap between
performance measurement and payment
adjustments in order to more effectively
connect improvements in quality care
with financial incentives. We will
closely evaluate the efficacy of the
model, and may consider whether
shorter performance assessment cycles
(and by extension, shorter payment
adjustment cycles) are warranted. Any
such changes will be implemented
through future rulemaking.
Final Decision: For the reasons
discussed, we are finalizing the
payment adjustment timeline as
proposed with modification.
Specifically, we are finalizing that
payment adjustments will be increased
incrementally over the course of the
model with a maximum payment
adjustment of 3-percent (upward or
downward) in 2018, a maximum
payment adjustment of 5-percent
(upward or downward) in 2019, a
maximum payment adjustment of 6percent (upward or downward) in 2020,
a maximum payment adjustment of 7percent (upward or downward) in 2021,
and a maximum payment adjustment of
8-percent (upward or downward) in
2022. We are also modifying the
timeline for notification and preview of
the pending payment adjustment to
allow for greater flexibility and to
account for the possibility of a specific
day falling on a weekend or holiday,
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and also to provide a longer preview
period for HHAs. Specifically, we are
extending the preview period such that
each HHA will be notified of each
pending payment adjustment in August
of the year prior to the payment
adjustment being applied and the
preview period will run for 30 days of
that year. We also removed specific days
of the month previously referenced in
the proposed rule to allow for greater
flexibility.
E. Quality Measures
1. Objectives
We proposed that initially, the
measures for the HHVBP Model would
be predominantly drawn from the
current OASIS,23 which is familiar to
the home health industry and readily
available for utilization by the model. In
addition, the HHVBP Model provides us
with an opportunity to examine a broad
array of quality measures that address
critical gaps in care. A recent
comprehensive review of the VBP
experience over the past decade,
sponsored by the Office of the Assistant
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23 For detailed information on OASIS see the
official CMS OASIS Web resource available at
https://www.cms.gov/Medicare/Quality-InitiativesPatient-Assessment-Instruments/OASIS/
index.html?redirect=/oasis. See also industry
resource available at https://www.oasisanswers.com/
index.htm, specifically updated OASIS component
information available at www.oasisanswers.com/
LiteratureRetrieve.aspx?ID=215074).
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Secretary for Planning and Evaluation
(ASPE), identified several near- and
long-term objectives for HHVBP
measures.24 The recommended
objectives emphasize measuring patient
outcomes and functional status;
appropriateness of care; and incentives
for providers to build infrastructure to
facilitate measurement within the
quality framework.25 The following
seven objectives derived from this study
served as guiding principles for the
selection of the proposed measures for
the HHVBP Model:
1. Use a broad measure set that
captures the complexity of the HHA
service provided;
2. Incorporate the flexibility to
include Improving Medicare Post-Acute
Care Transformation (IMPACT) Act of
2014 measures that are cross-cutting
amongst post-acute care settings;
3. Develop second-generation
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;
24 U.S. Department of Health and Human
Services. Office of the Assistant Secretary for
Planning and Evaluation (ASPE) (2014) Measuring
Success in Health Care Value-Based Purchasing
Programs. Cheryl L. Damberg et al. on behalf of
RAND Health.
25 Id.
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6. Add measures for appropriateness
or overuse; and,
7. Promote infrastructure investments.
2. Methodology for Selection of Quality
Measures
a. Direct Alignment With National
Quality Strategy Priorities
A central driver of the proposed
measure selection process was
incorporating innovative thinking from
the field while simultaneously drawing
on the most current evidence-based
literature and documented best
practices. Broadly, we proposed
measures that have a high impact on
care delivery and support the combined
priorities of HHS and CMS to improve
health outcomes, quality, safety,
efficiency, and experience of care for
patients. To frame the selection process,
we utilized the domains described in
the CMS Quality Strategy that maps to
the six National Quality Strategy (NQS)
priority areas (see Figure 3 for CMS
domains).26
26 The CMS Quality Strategy is discussed in broad
terms at URL https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-Assessment-Instruments/
QualityInitiativesGenInfo/CMS-QualityStrategy.html. CMS Domains appear presentations
by CMS and ONC (available at https://www.cms.gov/
eHealth/downloads/Webinar_eHealth_March25_
eCQM101.pdf) and a CMS discussion of the NQS
Domains can be found at URL https://www.cms.gov/
Regulations-and-Guidance/Legislation/
EHRIncentivePrograms/2014_
ClinicalQualityMeasures.html.
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b. Referenced Quality Measure
Authorities
We proposed at § 484.315 that
Medicare-certified HHAs will be
evaluated using a starter set of quality
measures (‘‘starter set’’ refers to the
quality measures for the first year of this
model) designed to encompass multiple
NQS domains, and provide future
flexibility to incorporate and study
newly developed measures over time.
New and evolving measures will be
considered for inclusion in subsequent
years of this model and proposed
through future rulemaking.
To create the proposed starter set we
began researching the current set of
OASIS measures that are being used
within the health home environment.27
Following that, we searched for
endorsed quality measures using the
National Quality Forum (NQF) Quality
Positioning System (QPS),28 selecting
measures that address all possible NQS
domains. We further examined
measures on the CMS-generated
Measures Under Consideration (MUC)
list,29 and reviewed other relevant
27 All data for the starter set measures, not
including New Measures, is currently collected
from HHAs under §§ 484.20 and 484.210.
28 The NQF Quality Positioning System is
available at https://www.qualityforum.org/QPS.
29 To review the MUC List see https://
www.qualityforum.org/Setting_Priorities/
Partnership/Measures_Under_Consideration_List_
2014.aspx.
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measures used within the health care
industry, but not currently used in the
home health setting, as well as measures
required by the IMPACT Act of 2014.
Finally, we searched the National
Quality Measures Clearinghouse
(NQMS) to identify evidence-based
measures and measure sets.
c. Key Policy Considerations and Data
Sources
So that measures for the HHVBP
Model take a more holistic view of the
patient beyond a particular disease state
or care setting, we proposed, and are
finalizing in this rule, measures, which
include outcome measures as well as
process measures, that have the
potential to follow patients across
multiple settings, reflect a multi-faceted
approach, and foster the intersection of
health care delivery and population
health. A key consideration behind this
approach is to use in performance year
one (PY1) of the model proven measures
that are readily available and meet a
high impact need, and in subsequent
model years augment this starter set
with innovative measures that have the
potential to be impactful and fill critical
measure gap areas. All substantive
changes or additions to the starter set or
new measures would be proposed in
future rulemaking. This approach to
quality measure selection aims to
balance the burden of collecting data
with the inclusion of new and important
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measures. We carefully considered the
potential burden on HHAs to report the
measure data when developing the
starter set, and prioritized measures that
will draw both from claims data and
data already collected in OASIS.
The majority of the measures
proposed, as well as the majority of
measures being finalized, in this model
will use OASIS data currently being
reported to CMS and linked to statespecific CCNs for selected states in
order to promote consistency and to
reduce the data collection burden for
providers. Utilizing primarily OASIS
data will allow the model to leverage
reporting structures already in place to
evaluate performance and identify
weaknesses in care delivery. This model
will also afford the opportunity to study
measures developed in other care
settings and new to the home health
industry (hereinafter referred to as
‘‘New Measures’’). Many of the New
Measures have been used in other
health care settings and are readily
applicable to the home health
environment (for example, influenza
vaccination coverage for health care
personnel). The final New Measures for
PY1 are described in detail below. We
proposed, and are finalizing with
modification, in PY1 to collect data on
these New Measures which have already
been tested for validity, reliability,
usability/feasibility, and sensitivity in
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other health care settings but have not
yet been validated within the home
health setting. As discussed in further
detail under ‘‘E5.New Measures,’’ we
are finalizing three of the four proposed
New Measures for reporting under this
model. HHVBP will study if their use in
the home health setting meets validity,
reliability, usability/feasibility, and
sensitivity to statistical variations
criteria. For PY1, we proposed that
HHAs could earn points to be included
in the Total Performance Score (TPS)
simply for reporting data on New
Measures (see Section—Performance
Scoring Methodology). To the extent we
determine that one or more of the New
Measures is valid and reliable for the
home health setting, we will consider in
future rulemaking to score Medicarecertified HHAs on their actual
performance on the measure.
3. Selected Measures
The initial set of measures proposed
for PY1 of the model utilizes data
collected via OASIS, Medicare claims,
HHCAHPS survey data, and data
reported directly from the HHAs to
CMS. We proposed, in total, 10 process
measures and 15 outcome measures (see
Figure 4a of the proposed rule) plus four
New Measures (see Figure 4b of the
proposed rule). As discussed below, we
are finalizing the proposed starter set of
measures with modification;
specifically, under our final policy,
there are in total six process measures
and 15 outcome measures (see Figure 4a
of this final rule) and three New
Measures (see Figure 4b of this final
rule). Process measures evaluate the rate
of HHA use of specific evidence-based
processes of care based on the evidence
available. Outcomes measures illustrate
the end result of care delivered to HHA
patients. When available, NQF endorsed
measures will be used. This set of
measures will be subject to change or
retirement during subsequent model
years and revised through the
rulemaking process. For example, we
may propose in future rulemaking to
remove one or more of these measures
if, based on the evidence; we conclude
that it is no longer appropriate for the
model due to its performance being
topped-out. We will also consider
proposing to update the measure set if
new measures that address gaps within
the NQS domains became available. We
will also consider proposing
adjustments to the measure set based on
lessons learned during the course of the
model. For instance, in light of the
passage of the IMPACT Act of 2014,
which mandates the collection and use
of standardized post-acute care
assessment data, we will consider
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proposing in future rulemaking to adopt
measures that meet the requirements of
the IMPACT Act as soon as they became
available. Provisions of the IMPACT
ACT applicable to HHAs will take effect
beginning CY 2017. Currently, IMPACT
measures for home health are in the
development stage and not available for
inclusion in the starter set of measures.
We requested public comment on the
methodology for constructing the
proposed starter set of quality measures
and on the proposed selected measures.
Comment: Many commenters
expressed concern at the number of
measures proposed for use in the model,
with the primary concern related to the
burden placed on HHAs to focus on so
many different areas at once, as well as
the effort required to track and report
New Measures at the same time. Many
commenters suggested decreasing the
number of measures, particularly
process measures, in the starter set and
expressed the opinion less measures
would allow for greater targeting of
quality improvement.
Response: We have considered the
commenters’ suggestions and agree that
more narrowly focusing the starter set of
measures being tested in the HHVBP
Model may increase the likelihood of
HHA success in their quality
improvement and transformation efforts.
In addition, we were encouraged by
commenters to re-evaluate the proposed
starter set of measures and specifically
include fewer process measures in the
final starter set. After consideration of
these comments we are reducing the
number of measures in the final starter
set. We proposed that the starter set
would include 25 measures that are
currently reported through existing
systems (in addition to the proposed
New Measures). Twenty of these
proposed measures were process/
outcomes measures collected on the
OASIS or through claims data and five
are HHCAHPs. We agree with
commenters that placing an emphasis
on outcome measures over process
measures determines performance in a
way most meaningful to patients. For
each process measure in the proposed
starter set we analyzed what specific
metrics were being assessed in relation
to the entire starter set and how close
the measure was to being ‘topped-out’
based on the most recent available data.
Based on these comments and for the
reasons stated we are reducing the
number of process measures by four
resulting in a final starter set with six
process measures, 10 outcome measures
and five HHCAHPS. In addition, we
have decreased the New Measures from
four to three (as discussed later in this
section). We are not including the
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following proposed measures in the
final starter set: Timely Initiation of
Care (NQF0526), Pressure Ulcer
Prevention and Care (NQF0538),
Multifactor Fall Risk Assessment
Conducted for All Patients who can
Ambulate (NQF0537), Depression
assessment conducted (NQF0518), and
Adverse Event for Improper Medication
Administration and/or Side Effects
(New Measures).
Comment: We received some public
comments expressing concern that all
measures in the starter set are not
endorsed by NQF.
Response: We agree that wherever
possible NQF-endorsed measures
should be utilized. When creating the
proposed starter set it was our policy to
utilize an NQF-endorsed measure
whenever one was available to address
a known quality improvement issue in
home health. For other measures
included in the finalized starter set, we
are utilizing long-standing OASIS data
components to track quality. As an
innovation model, it is our intention to
closely monitor the quality measures
and to address any needed adjustments
through future rulemaking. In addition,
the information we learn during this
model may, where appropriate, be
utilized to assist in effective measures
gaining endorsement within the HH
service line.
Comment: We received a number of
public comments citing the settlement
agreement in Jimmo v. Sebelius and
expressing concern with the inclusion
of five measures related to improvement
and articulating the importance of
including measures related to patient
stabilization and maintenance.
Response: We appreciate the feedback
on the measures methodology and
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
Jimmo settlement. The Jimmo settlement
agreement, however, pertains only to
the clarification of CMS’s manual
guidance on coverage standards, not
payment measures, and expressly does
not pertain to or prevent the
implementation of new regulations,
including new regulations pertaining to
the HHVBP Model. While we
considered using some of the
stabilization measures for this model,
we found that in contrast to the average
HHA improvement measure scores
which ranged from 56- to 65-percent,
the average HHA stabilization measure
scores ranged from 94- to 96-percent.
Using measures where the average rates
are nearly 100-percent would not allow
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for meaningful comparisons between
competing-HHAs on the quality of care
delivered. In addition, we performed
analyses on whether the proportion of
an individual HHA’s episodes of care
relating to ‘‘low therapy’’ episodes
(episodes with 0–5 therapy visits) and
the proportion of an individual HHA’s
total therapy visits relating to
maintenance therapy would have an
impact on the measures related to
improvement used in the model. HHAs
that have a higher proportion of patients
that require maintenance therapy or
patients that receive little to no therapy
at all would not be expected to perform
well on the measures related to
improvement. Although the functional
measures related to improvement are
expected to be sensitive to the provision
of therapy, our analysis did not
determine that HHAs’ performance on
the measures related to improvement
were negatively impacted by whether
they had a higher proportion of
maintenance therapy patients or a
higher proportion of patients that had
little to no therapy.
Based on these two analyses, CMS
expects that, at this time, HHAs that
provide care to more beneficiaries that
are maintenance-oriented will not be at
a disadvantage in the model. We also do
not expect any access issues for
beneficiaries that have more
maintenance needs because HHAs
would not know whether the
beneficiary has restorative or
maintenance needs until the HHA
initiates the episode of care and
conducts the necessary assessments.
Once the initial OASIS assessment is
complete, the beneficiary will be
included in measure calculation.
We are finalizing the measures related
to improvement as proposed in the
proposed rule, however, we are
sensitive to this issue and will closely
monitor whether HHVBP Model-specific
measures have the potential to impact
beneficiaries that require skilled care to
maintain the patient’s current condition,
or to prevent or slow further
deterioration of the patient’s condition.
If necessary, we will use future
rulemaking if we determine that this
issue has a meaningful detrimental
effect on payments of those HHAs that
provide more maintenance care. In
addition, we are currently working on
the development of valid and reliable
stabilization measures that may be
incorporated into the HHVBP Model in
the future. One stabilization measure is
referenced in Table 20 ‘Future Settingspecific Measure Constructs under
Consideration’. The HHVBP Model is
30 Cite
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.
Comment: Although CMS received
general support for the use of OASIS
data, some commenters expressed
concern with OASIS issues related to
data validation or with the use of certain
OASIS data elements as the basis for
measuring quality.
Response: We appreciate the
comments on this issue and are
committed to balancing concerns related
to provider burden with concerns
related to data validation and accurate
reporting of information to CMS via
OASIS. In designing the HHVBP Model,
we intentionally crafted a starter set of
measures to minimize burden.
Specifically, the majority of measures
rely on OASIS data already reported by
HHAs. In response to a 2012 report
issued by the Office of the Inspector
General,30 CMS affirmed a series of
monitoring activities related to OASIS
education, training and also updated the
HHA surveyor worksheet related to
HHA OASIS compliance. As part of the
monitoring and evaluation of this model
CMMI will utilize CMS best practices
for determining the validity of OASIS
data and detecting fraud related to data
submission. Should validation concerns
arise, CMMI may consider
implementing data validation processes.
The model will closely monitor reported
measures for indications of fraud and
CMS will propose any changes to the
model as needed in future rulemaking.
Comment: A few commenters
expressed specific concern that
measures in the starter set will be
duplicative of, or will not take into
account the future measures
implemented under the IMPACT Act,
and suggested consciously aligning the
HHVBP starter set with the IMPACT Act
as it is implemented.
Response: We agree the HHVBP
measure set should be in alignment with
the IMPACT Act. As stated in the
HHVBP proposed rule and finalized
here, as soon as new IMPACT measures
are finalized and approved, we will
consider how best to incorporate and
align IMPACT Act measures with the
HHVBP measure in future rulemaking.
As an example, once baseline data is
available for NQF #0678 ‘pressure
ulcers’ which will be implemented in
CY 2016, we will consider using this
measure in future years through
rulemaking.
Comment: One commenter
recommended eliminating all vaccinerelated measures, as vaccines are not the
primary focus of home health care. The
commenter stated that the use of
vaccine-related measures creates
misalignment between patient centered
principles and HHA financial
incentives.
Response: We have included two
immunization measures in the starter
set that are NQF-endorsed as preventive
services measures and already collected
by home health agencies. These
measures are the pneumococcal vaccine
and the influenza vaccines for HHA
beneficiaries. The immunization
measures that are New Measures, the
shingles vaccine and influenza vaccines
for HHA staff, under the final HHVBP
Model serve important public health
functions. The New Measure for
influenza vaccination for HHA staff is a
well-established scientific principle as
being a sound mechanism for protecting
vulnerable patient populations from
avoidable disease transmission. In
addition, this New Measure is utilized
in every care setting except home
health, and is intended to close the gap
in protection. The Shingles vaccination
is the other New Measure utilizing
immunizations, and its efficacy in either
preventing shingles entirely or reducing
the pain symptoms associated with
shingles is directly related to
improvement of patient quality of life.
The measurements related to
vaccination are not connected to
whether a patient does or does not
receive the vaccinations. Patients are
free to decline vaccinations and
competing HHAs are not financially
penalized for the patient’s choice.
Final Decision: For the reasons
discussed and in consideration of the
comments received we are not finalizing
the following proposed measures:
• Timely Initiation of Care (NQF0526)
• Pressure Ulcer Prevention and Care
(NQF0538)
• Multifactor Fall Risk Assessment
Conducted for All Patients Who Can
Ambulate (NQF0537)
• Depression assessment conducted
(NQF0518)
• Adverse Event for Improper
Medication Administration and/or Side
Effects (New Measure)
We are finalizing the remaining
quality measures as proposed. The final
starter set includes 6 process measures,
10 outcome measures and 5 HHCAHPS,
and three New Measures.
The final PY1 measures are presented
in the following figures.
for OIG report here.
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68671
FIGURE 4a: FINAL PY1 MEASURES 31
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 ending with a
discharge during the reporting period, other than those
covered by generic or measure-specific exclusions.
Clinical Quality of
Care.
Improvement in Bed
Transferring.
Outcome .......
NQF0175
OASIS (M1850) ......
Clinical Quality of
Care.
Improvement in
Bathing.
Outcome .......
NQF0174
OASIS (M1830) ......
Clinical Quality of
Care.
Improvement in
Dyspnea.
Outcome .......
NA ..........
OASIS (M1400) ......
Communication &
Care Coordination.
Discharged to Community.
Outcome .......
NA ..........
OASIS (M2420) ......
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 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 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 where the discharge assessment indicates
less dyspnea at discharge
than at start (or resumption)
of care.
Number of home health episodes where the assessment completed at the discharge indicates the patient
remained in the community
after discharge.
Communication &
Care Coordination.
Care Management:
Types and
Sources of Assistance.
Acute Care Hospitalization: Unplanned Hospitalization during
first 60 days of
Home Health.
Process .........
NA ..........
OASIS (M2102) ......
Multiple data elements ............
Outcome .......
NQF0171
CCW (Claims) .........
Number of home health stays
for patients who have a
Medicare claim for an admission to an acute care
hospital in the 60 days following the start of the home
health stay.
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.
Patient Safety .............
Improvement in Pain
Interfering with
Activity.
Outcome .......
NQF0177
OASIS (M1242) ......
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 frequent pain at discharge than at the start (or
resumption) of care.
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.
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Efficiency & Cost Reduction.
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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.
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.
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.
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.
Multiple data elements.
Number of home health stays
that begin during the 12month 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.
Number of home health stays
that begin during the 12month 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.
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.
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.
68672
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FIGURE 4a: FINAL PY1 MEASURES 31—Continued
Measure title
Measure type
Identifier
Data source
Numerator
Denominator
Patient Safety .............
NQS Domains
Prior Functioning
ADL/IADL.
Outcome .......
NQF0430
OASIS (M1900) ......
The number (or proportion) of
a clinician’s patients in a
particular risk adjusted diagnostic category who meet a
target threshold of improvement in Daily Activity (that
is, ADL and IADL) functioning.
Population/Community
Health.
Influenza Vaccine
Data Collection
Period: Does this
episode of care
include any dates
on or between
October 1 and
March 31?
Influenza Immunization Received for
Current Flu Season.
Process .........
NA ..........
OASIS (M1041) ......
NA ............................................
All patients in a risk adjusted
diagnostic category with a
Daily Activity goal for an episode of care. Cases to be
included in the denominator
could be identified based on
ICD–9 codes or alternatively,
based on CPT codes relevant to treatment goals focused on Daily Activity function.
NA.
Process .........
NQF0522
OASIS (M1046) ......
Population/Community
Health.
Pneumococcal Polysaccharide Vaccine Ever Received.
Process .........
NQF0525
OASIS (M1051) ......
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 during which patients
were determined to have
ever received Pneumococcal
Polysaccharide
Vaccine
(PPV).
Population/Community
Health.
Reason Pneumococcal vaccine not
received.
Drug Education on
All Medications
Provided to Patient/Caregiver
during all Episodes of Care.
Process .........
NA ..........
OASIS (M1056) ......
NA ............................................
Process .........
NA ..........
OASIS (M2015) ......
Number of home health episodes of care during which
patient/caregiver was instructed on how to monitor
the effectiveness of drug
therapy, how to recognize
potential adverse effects,
and how and when to report
problems (since the previous
OASIS assessment).
Population/Community
Health.
Clinical Quality of
Care.
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.
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.
NA.
Number of home health episodes of care ending with a
discharge or transfer to inpatient facility during the reporting period, other than
those covered by generic or
measure-specific exclusions.
Home Health CAHPS: Satisfaction Survey Measures
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Patient & CaregiverCentered Experience.
Patient & CaregiverCentered Experience.
Patient & CaregiverCentered Experience.
Patient & CaregiverCentered Experience.
Patient & CaregiverCentered Experience.
Care of Patients ......
Outcome .......
................
CAHPS ....................
NA ............................................
NA.
Communications between Providers
and Patients.
Specific Care Issues
Outcome .......
................
CAHPS ....................
NA ............................................
NA.
Outcome .......
................
CAHPS ....................
NA ............................................
NA.
Outcome .......
................
CAHPS ....................
NA ............................................
NA.
Outcome .......
................
CAHPS ....................
NA ............................................
NA.
Overall rating of
home health care
and.
Willingness to recommend the
agency.
31 For more detailed information on the proposed
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
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endorsed measures see The NQF Quality
Positioning System available at https://
www.qualityforum.org/QPS. For non-NQF measures
using OASIS see links for data tables related to
OASIS measures at https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-Assessment-Instruments/
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HomeHealthQualityInits/
HHQIQualityMeasures.html. For information on
HHCAHPS measures see https://
homehealthcahps.org/SurveyandProtocols/
SurveyMaterials.aspx.
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68673
FIGURE 4b—FINAL PY1 NEW MEASURES
NQS domains
Measure title
Measure type
Population/Community Health.
Influenza Vaccination Coverage for
Home Health
Care Personnel.
Process ........
NQF0431
Reported by HHAs
(Used in
through Web Porother care
tal.
settings, not
Home Health).
Population/Community Health.
Herpes zoster
(Shingles) vaccination: Has the
patient ever received the shingles vaccination?
Advance Care Plan
Process ........
NA ...................
Reported by HHAs
through Web Portal.
Process ........
NQF0326 .........
Reported by HHAs
through Web Portal.
Communication &
Care Coordination.
4. Additional Information on HHCAHPS
Figure 5 provides details on the
elements of the Home Health Care
Consumer Assessment of Healthcare
Providers and Systems Survey
Identifier
Data source
Numerator
Denominator
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 Guillain-Barre 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.
Total number of Medicare
beneficiaries aged 60 years
and over who report having
ever received zoster vaccine (shingles vaccine).
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.
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.
(HHCAHPS) we proposed, and are
finalizing, to include in the PY1 starter
set. The HHVBP Model will not alter the
HHCAHPS current scoring methodology
or the participation requirements in any
way. Details on participation
Total number of Medicare
beneficiaries aged 60 years
and over receiving services
from the HHA.
requirements for HHCAHPS can be
found at 42 CFR 484.250 32 and details
on HHCAHPS scoring methodology are
available at; https://homehealth
cahps.org/SurveyandProtocols/
SurveyMaterials.aspx.33
FIGURE 5—HOME HEALTH CARE CONSUMER ASSESSMENT OF HEALTHCARE PROVIDERS AND SYSTEMS SURVEY
(HHCAHPS) COMPOSITES
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Care of Patients
Response Categories
Q9. In the last 2 months of care, how often did home health providers from this agency seem informed and
up-to-date about all the care or treatment you got at home?
Q16. In the last 2 months of care, how often did home health providers from this agency treat you as gently as possible?
Q19. In the last 2 months of care, how often did home health providers from this agency treat you with
courtesy and respect?
Q24. In the last 2 months of care, did you have any problems with the care you got through this agency?
32 76 FR 68606, Nov. 4, 2011, as amended at 77
FR 67164, Nov. 8, 2012; 79 FR 66118, Nov. 6, 2014.
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33 Detailed scoring information is contained in the
Protocols and Guidelines manual posted on the
HHCAHPS Web site and available at https://
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Never, Sometimes,
ways.
Never, Sometimes,
ways.
Never, Sometimes,
ways.
Yes, No.
Usually,
Al-
Usually,
Al-
Usually,
Al-
homehealthcahps.org/Portals/0/PandGManual_
NOAPPS.pdf.
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68674
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FIGURE 5—HOME HEALTH CARE CONSUMER ASSESSMENT OF HEALTHCARE PROVIDERS AND SYSTEMS SURVEY
(HHCAHPS) COMPOSITES—Continued
Communications Between Providers & Patients
Response Categories
Q2. When you first started getting home health care from this agency, did someone from the agency tell
you what care and services you would get?
Q15. In the past 2 months of care, how often did home health providers from this agency keep you informed about when they would arrive at your home?
Q17. In the past 2 months of care, how often did home health providers from this agency explain things in
a way that was easy to understand?
Q18. In the past 2 months of care, how often did home health providers from this agency listen carefully to
you?
Q22. In the past 2 months of care, when you contacted this agency’s office did you get the help or advice
you needed?
Q23. When you contacted this agency’s office, how long did it take for you to get the help or advice you
needed?
Yes, No.
Never, Sometimes,
ways.
Never, Sometimes,
ways.
Never, Sometimes,
ways.
Yes, No.
Q25. Would you recommend this agency to your family or friends if they needed home health care?
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adjustment, New Measures scores
included in the final TPS for PY1 are
only based on whether the HHA has
submitted data to the HHVBP web-based
platform or not. We proposed the
following New Measures for competing
HHAs:
• Advance Care Planning;
• Adverse Event for Improper
Medication Administration and/or Side
Effects;
• Influenza Vaccination Coverage for
Home Health Care Personnel; and,
• Herpes Zoster (Shingles)
Vaccination received by HHA patients.
For the reasons explained below and
in consideration of the comments
received, we are not including the
proposed ‘‘Adverse Event for Improper
Medication Administration and/or Side
Effects’’ as one of the final New
Measures. We are finalizing the other
three proposed New Measures without
modification.
a. Advance Care Planning
Advance Care Planning is an NQFendorsed process measure in the NQS
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Usually,
Al-
Yes, No.
Yes, No.
Yes, No.
Yes, No.
Yes, No.
Yes, No.
Response Categories
Q20. What number would you use to rate your care from this agency’s home health providers?
19:46 Nov 04, 2015
Al-
Yes, No.
Global type Measures
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Usually,
Response Categories
Q3. When you first started getting home health care from this agency, did someone from the agency talk
with you about how to set up your home so you can move around safely?
Q4. When you started getting home health care from this agency, did someone from the agency talk with
you about all the prescription medicines you are taking?
Q5. When you started getting home health care from this agency, did someone from the agency ask to
see all the prescription medicines you were taking?
Q10. In the past 2 months of care, did you and a home health provider from this agency talk about pain?
Q12. In the past 2 months of care, did home health providers from this agency talk with you about the purpose for taking your new or changed prescription medicines?
Q13. In the last 2 months of care, did home health providers from this agency talk with you about when to
take these medicines?
Q14. In the last 2 months of care, did home health providers from this agency talk with you about the important side effects of these medicines?
As discussed in the proposed rule and
the previous section of this final rule,
the New Measures we proposed are not
currently reported by Medicare-certified
HHAs to CMS, but we believe fill gaps
in the NQS Domains not completely
covered by existing measures in the
home health setting. We proposed that
all competing HHAs in selected states,
regardless of cohort size or number of
episodes, will be required to submit
data on the New Measures for all
Medicare beneficiaries to whom they
provide home health services within the
state (unless an exception applies). We
proposed at § 484.315(b) that competing
HHAs would be required to report data
on these New Measures. Competing
HHAs will submit New Measure data
through a dedicated HHVBP web-based
platform. This web-based platform will
function as a means to collect and
distribute information from and to
competing HHAs. Also, for those HHAs
with a sufficient number of episodes of
care to be subject to a payment
Al-
Same day; 1 to 5 days; 6 to 14
days; More than 14 days.
Specific Care Issues
5. New Measures
Usually,
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Use a rating scale (0–10) (0 is
worst, 10 is best).
Definitely no; Probably no; Probably yes; Definitely yes.
domain of Person- and Caregivercentered experience and outcomes (see
Figure 3). This measure is currently
endorsed at the group practice/
individual clinician level of analysis.
We believe its adoption under the
HHVBP Model represents an
opportunity to study this measure in the
home health setting. This is an
especially pertinent measure for home
health care to confirm that the wishes of
the patient regarding their medical,
emotional, or social needs are met
across care settings. The Advance Care
Planning measure will focus on
Medicare beneficiaries, including
dually-eligible beneficiaries.
We proposed that the measure would
be numerically expressed by a ratio
whose numerator and denominator are
as follows:
Numerator: The measure would
calculate the percentage of patients age
65 years and older served by the HHA
that have an advance care plan or
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surrogate decision maker 34 documented
in the clinical record or documentation
in the clinical record that an advance
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.
Denominator: All patients aged 65
years and older admitted to the HHA.
Advance care planning provides that
the health care plan is consistent with
the patient’s wishes and preferences.
Therefore, studying this measure within
the HHA environment allows for further
analysis of planning for the ‘‘what ifs’’
that may occur during the patient’s
lifetime. In addition, the use of this
measure is expected to result in an
increase in the number of patients with
advance care plans. Increased advance
care planning among the elderly is
expected to result in enhanced patient
autonomy and reduced hospitalizations
and in-hospital deaths.35
We invited comments on this
proposed measure.
Comment: Some commenters
expressed support for the inclusion of
the advance care directive quality
measure in the HHVBP Model as an
important step towards advancing the
needs and wishes of Medicare
beneficiaries and improving care near
the end of life. One commenter
suggested CMS should collect data
separately for advance care plans and
for surrogate decision makers, since
they should not be considered to be
alternatives to each other and suggested
breaking this one measure into two new
separate measures. Another commenter
recommended that information
collected for Advanced Care Planning
be compliant with the standard at
§ 484.10(c)(ii), in which the HHA must
inform and distribute written
information to the patient, in advance,
concerning its policies on advance
directives, including a description of
applicable state law.
Response: HHAs are already required
to comply with Conditions of
Participation as codified in
§ 484.10(c)(1)(ii) regarding patient rights
and participation in this model in no
way alters those regulatory obligations
for participating HHAs. We will analyze
the data collected for this New Measure
and based on this analysis determine if
34 A surrogate decision maker, also known as a
health care proxy or agent, advocates for patients
who are unable to make decisions or speak for
themselves about personal health care such that
someone else must provide direction in decisionmaking, as the surrogate decision-maker.
35 Lauren Hersch Nicholas, Ph.D., MPP et al.
Regional Variation in the Association Between
Advance Directives and End-of-Life Medicare
Expenditures. JAMA. 2011;306(13):1447–1453.
doi:10.1001/jama.2011.1410.
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we need to modify the measure in future
rulemaking. We also note that standard
practices for developing advance care
plans integrate selection of surrogate
decision making into the plan, so if and
when a surrogate is needed they are
readily made aware of the patient’s
wishes as articulated in the care plan.
Comment: One commenter did not
support adoption of an Advance Care
Planning measure and stated that an
HHA should not be given an incentive
to make the patient acquire an advanced
directive. The commenter also asserted
that Advance Care Planning is better
suited for long-term care relationships
and that advance directive compliance
is already assessed at the HHA level.
The commenter expressed concern that
the Advance Care Planning measure
shows a preference for living wills
instead of working through a process to
create an advance care plan.
Response: Advance Care Plans are
fundamentally different than advanced
directives (also referred to as living
wills.) The basis for an Advance Care
Plan is ongoing communication with
health providers, family members, and
potential surrogate decision makers;
they are not focused exclusively on end
of life or life threatening conditions.
Advance Care Plans ensure patient
centered care by providing an
opportunity for health care providers
and patients to identify how a patient
would like to be cared for when a
medical crisis makes it difficult or
impossible to make their own healthcare
decisions.
Comment: Commenters suggested that
this metric, and the reporting on all
New Measures be delayed until CY2017
and that it be included within OASIS
for data collection due to the complexity
of the question and its multiple parts.
Response: Based on the comments we
received from HHAs to delay the
reporting requirement for New
Measures, including Advance Care
Planning, we are modifying our
proposal to require HHAs to submit the
first round of data on this and the other
New Measures no later than October 7,
2016 for the period July 2016 through
September 2016. In response to the
recommendation that we incorporate
this measure into OASIS before
including it in the Model, part of the
purpose of testing this measure in the
HH setting is to make informed
decisions based on newly available data
analysis prior to recommending that this
measure be incorporated into measures
that all HHAs are required to report.
Comment: Some commenters
expressed concern that the Advance
Care Planning Measure does not clearly
state that the patient does not have to
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68675
complete the advance care plan. In
addition, some commenters wrote that
the measure creates an incentive to
pressure patients to do so. A few
commenters requested CMS make
regulations and policy guidance on the
Advance Care Planning measure to more
strongly clarify that the well-being and
autonomy of the individual patient is
the primary concern, not cost savings
for the government.
Response: Beneficiaries are free to
make their own decisions related to
their participation in their care, and this
measure ascertains that providers
provide information and opportunity to
the patient so they can engage in
planning their own care. The intent of
the measure is to provide education and
guidance to the beneficiaries, not to
pressure them regarding this measure.
We will provide robust technical
assistance for HHAs related to this new
measure, including necessary tools and
information for ensuring autonomous
decision making on the part of the
patient.
Final Decision: For the reasons
discussed and in consideration of the
comments received, we are finalizing
this New Measure as proposed, with the
modification that HHAs will be required
to begin reporting data no later than
October 7, 2016 for the period July 2016
through September 2016 and quarterly
thereafter. As a result, the first quarterly
performance report in July 2016 will not
account for any of the New Measures.
b. Adverse Event for Improper
Medication Administration and/or Side
Effects
We proposed an Adverse Event for
Improper Medication Administration
and/or Side Effects measure that aligns
with the NQS domain of Safety
(specifically ‘‘medication safety’’—see
Figure 3) with the goal of making care
safer by reducing harm caused in the
delivery of care. The National Quality
Forum included ADEs as a Serious
Reportable Event (SRE) in the category
of Care Management, defining said
event as a ‘‘patient death or serious
injury associated with a medication
error (for example, errors involving the
wrong drug, wrong dose, wrong patient,
wrong time, wrong rate, wrong
preparation, or wrong route of
administration),’’ noting that ‘‘. . . the
high rate of medication errors resulting
in injury and death makes this event
important to endorse again.’’ 36 We refer
36 National Quality Forum, Serious Reportable
Events in Healthcare-2011, at 9. (2011), available at:
https://www.qualityforum.org/Publications/2011/12/
Serious_Reportable_Events_in_Healthcare_
2011.aspx.
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readers to the CY 2016 HH PPS
proposed rule for more detail on this
proposed measure (80 FR 39883 through
39884).
We invited comments on the Adverse
Drug Events measure.
Comment: Many commenters noted
the duplication between this proposed
New Measure and an existing OASIS
adverse event outcome measure,
‘‘Emergent Care for Improper
Medication Administration, Medication
Side Effects’’. A commenter
recommended substituting the proposed
New Measure titled Adverse Event for
Improper Medication Administration
and/or Side Effects with the current
measure called ‘‘Potentially Avoidable
Event Outcome titled Emergent Care for
Improper Medication Administration,
Medication Side Effects’’ generated
using OASIS data. In addition,
commenters generally did not support
inclusion of the ADE metric as part of
HHVBP because: HHA staff are not
typically trained to positively identify
ADEs, which are often complex; ADEs
often only become apparent after further
care; the complexity of ADEs means
they are often not identified on
discharge paperwork, meaning that
more effort would be required to
identify ADEs and less vigilant HHAs
would be rewarded for not inputting
information; and drug education metrics
are already part of home health compare
and in OASIS data. One commenter
expressed concern that ADE measure
could create a disincentive for HHAs to
accept patients with complex
medication regimes.
Response: We agree with the
comments suggesting Adverse Drug
Event data would be duplicative and are
not finalizing this measure for PY1 of
the model. We will evaluate if there is
a more narrowly tailored approach for
measuring quality performance related
to medication management. We will
continue to analyze ways to address the
issue of adverse drug events in the home
health setting and seek input from
stakeholders on including an alternative
measure in future model years.
Final Decision: In consideration of
comments received we are not finalizing
this measure.
c. Influenza Vaccination Coverage for
Home Health Care Personnel
Staff Immunizations (Influenza
Vaccination Coverage among Health
Care Personnel) (NQF #0431) is an NQFendorsed measure that addresses the
NQS domain of Population Health (see
Figure 3). The measure is currently
endorsed in Ambulatory Care;
Ambulatory Surgery Center (ASC),
Ambulatory Care; Clinician Office/
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Clinic, Dialysis Facility, Hospital/Acute
Care Facility, Post-Acute/Long Term
Care Facility; Inpatient Rehabilitation
Facility, Post-Acute/Long Term Care
Facility; Long Term Acute Care
Hospital, and Post-Acute/Long Term
Care Facility: Nursing Home/Skilled
Nursing Facility. Home health care is
among the only remaining settings for
which the measure has not been
endorsed. We stated in the proposed
rule that we believe the HHVBP Model
presents an opportunity to study this
measure in the home health setting.
This measure is currently reported in
multiple CMS quality reporting
programs, including Ambulatory
Surgical Center Quality Reporting,
Hospital Inpatient Quality Reporting,
and Long-Term Care Hospital Quality
Reporting; we believe its adoption
under the HHVBP Model presents an
opportunity for alignment in our quality
reporting programs. The documentation
of staff immunizations is also a standard
required by many HHA accrediting
organizations. We believe that this
measure would be appropriate for
HHVBP because it addresses total
population health across settings of care
by reducing the exposure of individuals
to a potentially avoidable virus.
We proposed that the measure would
be numerically expressed by a ratio
whose numerator and denominator are
as follows:
Numerator: The measure would
calculate the percentage of home health
care personnel who receive the
influenza vaccine, and document those
who do not receive the vaccine in the
articulated categories below:
(1) Received an influenza vaccination
administered at the health care agency,
or reported in writing (paper or
electronic) or provided documentation
that influenza vaccination was received
elsewhere; or
(2) Were determined to have a
medical contraindication/condition of
severe allergic reaction to eggs or to
other component(s) of the vaccine, or
´
history of Guillain-Barre Syndrome
within 6 weeks after a previous
influenza vaccination; or
(3) Declined influenza vaccination; or
(4) Persons with unknown
vaccination status or who do not
otherwise meet any of the definitions of
the above-mentioned numerator
categories.
We proposed that each of the above
groups would be divided by the number
of health care personnel who are
working in the HHA for at least one
working day between October 1 and
March 31 of the following year,
regardless of clinical responsibility or
patient contact.
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Denominator: This measure collects
the number of home health care
personnel who work in the HHA during
the flu season: 37 Denominators are to be
calculated separately for the following
three (3) groups:
1. Employees: all persons who receive
a direct paycheck from the reporting
HHA (that is, on the agency’s payroll);
2. Licensed independent
practitioners: include physicians (MD,
DO), advanced practice nurses, and
physician assistants only who are
affiliated with the reporting agency who
do not receive a direct paycheck from
the reporting HHA; and
3. Adult students/trainees and
volunteers: include all adult students/
trainees and volunteers who do not
receive a direct paycheck from the
reporting HHA.
We stated in the proposed rule that
this measure for the HHVBP Model is
expected to result in increased influenza
vaccination among home health
professionals. Reporting health care
personnel influenza vaccination status
would allow HHAs to better identify
and target unvaccinated personnel.
Increased influenza vaccination
coverage among HHA personnel would
be expected to result in reduced
morbidity and mortality related to
influenza virus infection among
patients, especially elderly and
vulnerable populations.38
We proposed, and are finalizing in
this rule, that information on the above
numerator and denominator will be
reported by HHAs through the HHVBP
Web-based platform, in addition to
other information related to this
measure as the Secretary deems
appropriate.
We invited comments on the
proposed Staff Influenza Vaccination
measure.
Comment: A few commenters asserted
that HHVBP is not the correct avenue
for improving population health and
that extending the measure to all allied
staff is too broad of a reach for the
program, especially considering that the
HHA has no mandate that allows it to
force allied staff to comply. Commenters
recommended modifying proposed
influenza measures to include in the
numerator HHA staff who decline the
vaccination yet wear protective masks
37 Flu season is generally October 1 (or when the
vaccine became available) through March 31 of the
following year. See URL https://www.cdc.gov/flu/
about/season/flu-season.htm for detailed
information.
38 Carman WF, Elder AG, Wallace LA, et al.
Effects of influenza vaccination of health-care
workers on mortality of elderly people in long-term
care: a randomized controlled trial. Lancet 2000;
355:93–97.
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or be limited to HHA staff who have
contact with the patient. Commenters
also noted that staff data is already
collected through licensure and
certification requirements, and
recommended that CMS promote staff
influenza immunization through the
upcoming Conditions of Participation in
Medicare and Medicaid for Home
Health Agencies rule.
Response: Home health care is among
the only remaining settings for which
the measure has not been endorsed.
Mandatory health worker vaccinations
are widely endorsed by national
professional associations 39 because
public health data has conclusively
demonstrated that immunizing health
staff to prevent influenza improves
population health.40 We also note that
state certification and documentation
requirements for licensure are not
consistent from state to state and the
requirement for staff vaccination is not
part of the CoPs.
Comment: Some commenters
suggested CMS develop state-specific or
regional time frames for when this
measure applies, noting the proposed
October-March timeframe may not be
sufficiently protective for states in the
Northeast.
Response: We are following flu season
guidelines from the Centers for Disease
Control (CDC), which indicates peak flu
season is from October through March.
We defer to CDC expertise and will not
be amending the flu time frame for the
purposes of the HHVBP model at this
time.
Comment: One commenter did not
support the inclusion of the metric for
Influenza Vaccination Coverage for
Home Health Care Personnel because, as
proposed, the metric does not include
consideration of the overall availability
of the flu vaccine at the local/state level.
The commenter asserted that regardless
of known national declared shortages,
regional availability limits should be
reflected within the measure so as not
to unduly penalize home health
agencies.
Response: In PY1, HHAs will not be
scored on immunization rates for health
personnel and will receive credit for
reporting data related to immunizing
healthcare staff.
Comment: Some commenters
expressed concern that the resources
39 For a complete list of professional
organizations that endorse mandatory flu
vaccinations for health workers see URL https://
www.immunize.org/honor-roll/influenza-mandates.
40 Carman WF, Elder AG, Wallace LA, et al.
Effects of influenza vaccination of health-care
workers on mortality of elderly people in long-term
care: a randomized controlled trial. Lancet 2000;
355:93–97.
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and time commitment required to be
able to reliably report on this metric
would create undue hardship for
January 1, 2016 implementation and
suggested delayed implementation.
Response: We acknowledge the
concerns expressed related to the
timeline for reporting data on New
Measures and agree with commenters
that additional time for HHAs to prepare
for data reporting is merited. We are
finalizing that competing HHAs will be
required to report data on this measure,
as well as the other New Measures, no
later than October 7, 2016.
Final Decision: For the reasons
discussed and in consideration of the
comments received, we are finalizing
this New Measure as proposed, with the
modification that HHAs will be required
to begin reporting data no later than
October 7, 2016 for the period July 2016
through September 2016 and quarterly
thereafter. As a result, the first quarterly
performance report in July 2016 will not
account for any of the New Measures.
c. Herpes Zoster Vaccine (Shingles
Vaccine) for Patients
We proposed to adopt this measure
for the HHVBP Model because it aligns
with the NQS Quality Strategy Goal to
Promote Effective Prevention &
Treatment of Chronic Disease. Currently
this measure is not endorsed by NQF or
collected in OASIS. However, due to the
severe physical consequences of
symptoms associated with shingles,41
we view its adoption under the HHVBP
Model as an opportunity to perform
further study on this measure. The
results of this analysis could provide the
necessary data to meet NQF
endorsement criteria. We proposed that
the measure would calculate the
percentage of home health patients who
receive the Shingles vaccine, and collect
the number of patients who did not
receive the vaccine.
Numerator: Equals the total number of
Medicare beneficiaries aged 60 years
and over who report having ever
received herpes zoster vaccine (shingles
vaccine) during the home health
episode of care.
Denominator: Equals the total number
of Medicare beneficiaries aged 60 years
and over receiving services from the
HHA.
The Food and Drug Administration
(FDA) has approved the use of herpes
zoster vaccine in adults age 50 and
older. In addition, the Advisory
Committee on Immunization Practices
41 For detailed information on Shingles
incidences and known complications associated
with this condition see CDC information available
at https://www.cdc.gov/shingles/about/
overview.html.
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(ACIP) currently recommends that
herpes zoster vaccine be routinely
administered to adults, age 60 years and
older.42 In 2013, 24.2 percent of adults
60 years and older reported receiving
herpes zoster vaccine to prevent
shingles, an increase from the 20.1
percent in 2012,43 yet below the targets
recommended in the HHS Healthy
People 2020 initiative.44
The incidence of herpes zoster
outbreak increases as people age, with a
significant increase after age 50. Older
people are more likely to experience the
severe nerve pain known as postherpetic neuralgia (PHN),45 the primary
acute symptom of shingles infection, as
well as non-pain complications,
hospitalizations,46 and interference with
activities of daily living.47 Studies have
shown for adults aged 60 years or older
the vaccine’s efficacy rate for the
prevention of herpes zoster is 51.3
percent and 66.5 percent for the
prevention of PHN for up to 4.9 years
after vaccination.48 The Short-Term
Persistence Sub study (STPS) followed
patients 4 to 7 years after vaccination
and found a vaccine efficacy of 39.6
percent for the prevention of herpes
zoster and 60.1 percent for the
prevention of PHN.49 The majority of
patients reporting PHN are over age 70;
vaccination of this older population
would prevent most cases, followed by
vaccination at age 60 and then age 50.
We stated in the proposed rule that
studying this measure in the home
42 CDC. Morbidity and Mortality Weekly Report
2011; 60(44):1528.
43 CDC. Morbidity and Mortality Weekly Report
2015; 64(04):95–102.
44 Healthy People 2020: Objectives and targets for
immunization and infectious diseases. Available at
https://www.healthypeople.gov/2020/topicsobjectives/topic/immunization-and-infectiousdiseases/objectives.
45 Yawn BP, Saddier P, Wollen PC, St Sauvier JL,
Kurland MJ, Sy LS. A population-based study of the
incidence and complication rate of herpes zoster
before zoster vaccine introduction. Mayo Clinic
Proc 2007; 82:1341–9.
46 Lin F, Hadler JL. Epidemiology of primary
varicella and herpes zoster hospitalizations: the prevaricella vaccine era. J Infect Dis 2000; 181:1897–
905.
47 Schmader KE, Johnson GR, Saddier P, et al.
Effect of a zoster vaccine on herpes zoster-related
interference with functional status and healthrelated quality-of-life measures in older adults. J
Am Geriatr Soc 2010; 58:1634–41.
48 Schmader KE, Johnson GR, Saddier P, et al.
Effect of a zoster vaccine on herpes zoster0-related
interference with functional status and healthrelated quality-of-life measures in older adults. J
Am Geriatr Soc 2010; 58:1634–41.
49 Schmader, KE, Oxman, MN, Levin, MJ,
Johnson,G, Zhang, JH, Betts, R, Morrison, VA, Gelb,
L, Guatelli, JC, Harbecke, R, Pachucki, C, Keay, S,
Menzies, B, Griffin, MR, Kauffman, C, Marques, A,
Toney, J, Keller, PM, LI, X, Chan, LSF, Annumziato,
P. Persistence of the Efficacy of Zoster Vaccine in
the Shingles Prevention Study and the Short Term
Persistence Substudy. Clinical Infectious Disease
2012; 55:1320–8
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health setting presents an ideal
opportunity to address a population at
risk which will benefit greatly from this
vaccination strategy. For example,
receiving the vaccine will often reduce
the course and severity of the disease
and reduce the risk of post herpetic
neuralgia.
We proposed, and are finalizing in
this rule, that information on the above
numerator and denominator will be
reported by HHAs through the HHVBP
web-based platform, in addition to other
information related to this measure as
the Secretary deems appropriate.
We invited public comment on the
proposed Herpes Zosters Vaccine
measure.
Comment: A number of commenters
expressed concern that patients refuse
Shingles vaccination since the vaccine
is costly and is paid for only through
Medicare Part D. A few commenters also
expressed concerns that patients in
home health may not have ready
knowledge of their vaccination status,
and tracking this information down
could be burdensome for HHAs. Some
commenters also raised the concern that
a desire to comply with the measure
presents the potential for unnecessary
repeat vaccinations.
Response: We appreciate public
comment on this issue. CMS recognizes
there are payment and access issues
related to the Shingles vaccination. As
a New Measure, competing HHAs will
have the opportunity to report on
implementation challenges related to
patients accessing the Shingles
vaccination and we will be evaluating
feedback from HHAs provided through
data reporting on the measure. However,
we believe inclusion of this New
Measure is connected to quality care for
patients because the Shingles
vaccination has been demonstrated to
either reduce the incidence of Shingles
or significantly mitigate the pain and
discomfort associated with Shingles.
Including the measure in intended to
increase patient awareness and access to
the vaccine if they so choose.
Comment: One commenter
recommended development of
additional vaccine measures to align
with ACIP policies.
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Response: We thank the commenter
and note that we intend to evaluate the
measures in the HHVBP Model on an
annual basis and implement any
changes to the measure set in future
rulemaking. In PY1 we have included
the ACIP recommendation to utilize the
Shingles vaccination, and we will refer
to ACIP recommendations when
analyzing additional measures in
subsequent years of the model.
Comment: Commenters expressed
concern about collecting Herpes Zoster
vaccination data because they asserted
that modifications to EMR will have to
occur. Commenters also asserted that
the resources and time commitment
required to be able to reliably report on
this metric would create undue
hardship for January 1, 2016
implementation. Commenters
recommended moving the timeline out
6–12 months for collecting this data.
Response: We appreciate commenters’
concerns regarding the timeline for data
collection and agree that in some
instances additional preparation time
may be needed by competing HHAs
including allowing for those HHAs who
may have to modify their clinical record
system. We are finalizing that
competing HHAs will be required to
report data on this measure, as well as
the other New Measures, no later than
October 7, 2016 for the period July 2016
through September 2016.
Final Decision: For the reasons
discussed and in consideration of the
comments received, we are finalizing
this New Measure as proposed, with the
modification that HHAs will be required
to begin reporting data no later than
October 7, 2016 for the period July 2016
through September 2016 and quarterly
thereafter. As a result, the first quarterly
performance report in July 2016 will not
account for any of the New Measures.
6. HHVBP Model’s Four Classifications
As previously stated, the quality
measures that we proposed to use in the
performance years, as well as the quality
measures that we are finalizing in this
final rule, are aligned with the six NQS
domains: Patient and CaregiverCentered Experience and Outcomes;
Clinical Quality of Care; Care
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Coordination; Population Health;
Efficiency and Cost Reduction; and,
Safety (see Figure 6).
We proposed to filter these NQS
domains and the HHVBP quality
measures into four classifications to
align directly with the measure
weighting utilized in calculating
payment adjustments. The four HHVBP
classifications we proposed are: Clinical
Quality of Care, Outcome and
Efficiency, Person- and CaregiverCentered Experience, and New
Measures reported by the HHAs.
We did not receive any public
comments on our proposed measure
classifications for the HHVBP Model
and are finalizing these classifications
with one modification. Specifically, we
are revising Classification II from
‘‘Outcome and Efficiency’’ to ‘‘Care
Coordination and Efficiency.’’ The
definition of this classification is
unchanged from the proposed rule. We
are making this change to be more
inclusive about this classification
designation, which includes measures/
NQS domains relating to care
coordination.
These final four classifications
capture the multi-dimensional nature of
health care provided by the HHA. These
classifications are further defined as:
• Classification I—Clinical Quality of
Care: Measures the quality of health care
services provided by eligible
professionals and paraprofessionals
within the home health environment.
• Classification II—Care Coordination
and Efficiency: Outcomes measure the
end result of care including
coordination of care provided to the
beneficiary. Efficiencies measure
maximizing quality and minimizing use
of resources.
• Classification III—Person- and
Caregiver-Centered Experience:
Measures the beneficiary and their
caregivers’ experience of care.
• Classification IV—New Measures:
Measures not currently reported by
Medicare-certified HHAs to CMS, but
that may fill gaps in the NQS Domains
not completely covered by existing
measures in the home health setting.
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We proposed that measures within
each classification would be weighted
the same for the purposes of payment
adjustment. We are weighting at the
individual measure level and not the
classification level. Classifications are
for organizational purposes only. We
proposed this approach because we did
not want any one measure within a
classification to be more important than
another measure. Under this approach,
a measure’s weight will remain the same
even if some of the measures within a
classification group have no available
data. We stated in the proposed rule that
weighting will be re-examined in
subsequent years of the model and be
subject to the rulemaking process. We
invited comments on the proposed
weighting methodology for the HHVBP
Model.
Comment: We received a few
comments on the weighting of measures
in the starter set. Some commenters
recommended that certain measures
should be weighted more than others;
with one comment specifying the rehospitalization measure should have
greater weight, and some other
commenters suggesting that measures
not based on self-reported data should
have greater weight. One commenter
expressed concern that by weighting
measures equally, HHAs will have little
opportunity to make significant
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improvements because each measure
will only represent a small fraction of
the agency’s score; therefore, agencies
would need to make large
improvements in many measures to see
a meaningful difference in their overall
score. All comments related to
weighting indicated a preference for
moving away from each measure
receiving equal weight.
Response: The quality measures that
were selected for the HHVBP Model
capture the multiple dimensions of care
that HHA provide to their beneficiaries.
We are finalizing this proposed policy
because equally weighted measures will
encourage HHAs to approach quality
improvement initiatives more broadly in
an effort to capture the
multidimensional aspects of care that
HHAs provide. In addition, weighting
the measures equally addresses
concerns where HHAs may be providing
services to beneficiaries with different
needs. If particular measures are
weighted more than others, HHAs may
only make the investment to improve
their quality in those areas where
measures have a higher weight,
potentially allowing other aspects of
care to be subject to potential neglect.
We will monitor the impact of the
equally weighting the individual
measures and may consider changes to
the weighting methodology after
analysis and through rulemaking.
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Final Decision: For the reasons
discussed, we are finalizing the
weighting methodology as proposed
without modification.
F. Performance Scoring Methodology
1. Performance Calculation Parameters
The methodology we proposed, and
are finalizing in this final rule for the
reasons discussed herein, for assessing
each HHA’s total annual performance is
based on a score calculated using the
starter set of quality measures that apply
to the HHA (based on a minimum
number of cases, as discussed herein).
The methodology will provide an
assessment on a quarterly basis for each
HHA and will result in an annual
distribution of value-based payment
adjustments among HHAs so that HHAs
achieving the highest performance
scores will receive the largest upward
payment adjustment. The methodology
includes three primary features:
• The HHA’s Total Performance Score
(TPS) will be determined using the
higher of an HHA’s achievement or
improvement score for each measure;
• All measures within the Clinical
Quality of Care, Care Coordination and
Efficiency, and Person and CaregiverCentered Experience classifications will
have equal weight and will account for
90-percent of the TPS (see Section 2
below) regardless of the number of
measures in the three classifications.
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Points for New Measures are awarded
for submission of data on the New
Measures via the HHVBP web-based
platform, and withheld if data is not
submitted. Data reporting for each New
Measure will have equal weight and
will account for 10-percent of the TPS
for the first performance year; and,
• The HHA performance score would
reflect all of the measures that apply to
the HHA based on a minimum number
of cases defined below.
For the reasons discussed in more
detail later in this section, we are
finalizing our proposed performance
scoring methodology with one
modification related to the rounding up
or down of achievement and
improvement scoring used in the
calculation of the Total Performance
Score.
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2. Considerations for Calculating the
Total Performance Score
We proposed, and are finalizing in
this final rule, in § 484.320 to calculate
the TPS by adding together points
awarded to Medicare-certified HHAs on
the starter set of measures, including the
New Measures. As explained in the
proposed rule, we considered several
factors when developing the
performance scoring methodology for
the HHVBP Model. First, it is important
that the performance scoring
methodology be straightforward and
transparent to HHAs, patients, and other
stakeholders. HHAs must be able to
clearly understand performance scoring
methods and performance expectations
to maximize quality improvement
efforts. The public must understand
performance score methods to utilize
publicly-reported information when
choosing HHAs.
Second, we believe the performance
scoring methodology for the HHVBP
Model should be aligned appropriately
with the quality measurements adopted
for other Medicare value-based
purchasing programs including those
introduced in the hospital and skilled
nursing home settings. This alignment
will facilitate the public’s
understanding of quality measurement
information disseminated in these
programs and foster more informed
consumer decision-making about their
health care choices.
Third, we believe that differences in
performance scores must reflect true
differences in quality performance. To
make sure that this point is addressed
in the performance scoring methodology
for the HHVBP Model, we assessed
quantitative characteristics of the
measures, including the current state of
measure development, number of
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measures, and the number and grouping
of measure classifications.
Fourth, we believe that both quality
achievement and improvement must be
measured appropriately in the
performance scoring methodology for
the HHVBP Model. The methodology
specifies that performance scores under
the HHVBP Model are calculated
utilizing the higher of achievement or
improvement scores for each measure.
The impact of performance scores
utilizing achievement and improvement
on HHAs’ behavior and the resulting
payment implications was also
considered. Using the higher of
achievement or improvement scores
allows the model to recognize HHAs
that have made great improvements,
though their measured performance
score may still be relatively lower in
comparison to other HHAs.
Fifth, through careful measure
selection we intend to eliminate, or at
least control for, unintended
consequences such as undermining
better outcomes to patients or rewarding
inappropriate care. As discussed above,
when available, NQF endorsed
measures will be used. In addition we
are adopting measures that we believe
are closely associated with better
outcomes in the HHA setting in order to
incentivize genuine improvements and
sustain positive achievement while
retaining the integrity of the model.
Sixth, we intend that the model will
utilize the most currently available data
to assess HHA performance. We
recognize that these data would not be
available instantaneously due to the
time required to process quality
measurement information accurately;
however, we intend to make every effort
to process data in the timeliest fashion.
Using more current data will result in a
more accurate performance score while
recognizing that HHAs need time to
report measure data.
3. Additional Considerations for the
HHVBP Total Performance Scores
Many of the key elements of the
HHVBP Model performance scoring
methodology that we proposed, and are
finalizing in this final rule for the
reasons described herein, are aligned
with the scoring methodology of the
Hospital Value-Based Purchasing
Program (HVBP) in order to leverage the
rigorous analysis and review
underpinning that Program’s approach
to value-based purchasing in the
hospital sector. The HVBP Program
includes as one of its core elements the
scoring methodology included in the
2007 Report to Congress ‘‘Plan to
Implement a Medicare Hospital ValueBased Purchasing Program’’ (hereinafter
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referred to as ‘‘The 2007 HVBP
Report’’).50 The 2007 HVBP Report
describes a Performance Assessment
Model with core elements that can
easily be replicated for other valuebased purchasing programs or models,
including the HHVBP Model.
In the HVBP Program, the
Performance Assessment Model
aggregates points on the individual
quality measures across different quality
measurement domains to calculate a
hospital’s TPS. Similarly, the proposed
HHVBP Model would aggregate points
on individual measures across four
measure classifications derived from the
6 CMS/NQS domains as described
above (see Figure 3) to calculate the
HHA’s TPS. In addition, the proposed
HHVBP payment methodology is also
aligned with the HVBP Program with
respect to evaluating an HHA’s
performance on each quality measure
based on the higher of an achievement
or improvement score in the
performance period. The model is not
only designed to provide incentives for
HHAs to provide the highest level of
quality, but also to provide incentives
for HHAs to improve the care they
provide to Medicare beneficiaries. By
rewarding HHAs that provide high
quality and/or high improvement, we
believe the HHVBP Model will ensure
that all HHAs will be incentivized to
commit the resources necessary to make
the organizational changes that will
result in better quality.
We proposed, and are finalizing for
the reasons described herein, that under
the model, an HHA will be awarded
points only for ‘‘applicable measures.’’
An ‘‘applicable measure’’ is one for
which the HHA has provided 20 home
health episodes of care per year. Points
awarded for each applicable measure
will be aggregated to generate a TPS. As
described in the benchmark section
below, HHAs will have the opportunity
to receive 0 to 10 points for each
measure in the Clinical Quality of Care,
Care Coordination and Efficiency, and
Person and Caregiver-Centered
Experience classifications. Each
measure will have equal weight
regardless of the total number of
measures in each of the first three
classifications. In contrast, we proposed,
and are finalizing in this rule, to score
the New Measures in a different way.
For each New Measure, HHAs will
receive 10 points if they report the New
Measure or 0 points if they do not report
the measure during the performance
50 The 2007 HVBP Report is available at the CMS
Web site at https://www.cms.gov/Medicare/
Medicare-Fee-for-Service-Payment/
AcuteInpatientPPS/downloads/
HospitalVBPPlanRTCFINALSUBMITTED2007.pdf.
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baseline period in order to evaluate the
degree of change that may occur over
the multiple years of the model. In
determining improvement points for
each measure, we proposed, and are
finalizing in this rule, that HHAs will
receive points along an improvement
range, which is a scale indicating
change between an HHA’s performance
during the performance period and the
baseline period. In addition, as in the
achievement calculation, the benchmark
and threshold will be calculated
separately for each state and for HHA
cohort size so that HHAs will only be
competing with those HHAs in their
state and their size cohort.
4. Setting Performance Benchmarks and
Thresholds
For scoring HHAs’ performance on
measures in the Clinical Quality of Care,
Care Coordination and Efficiency, and
Person and Caregiver-Centered
Experience classifications, we proposed,
and are finalizing in this rule, to adopt
an approach using several key elements
from the scoring methodology set forth
in the 2007 HVBP Report and the
successfully implemented HVBP
Program 51 including allocating points
based on achievement or improvement,
and calculating those points based on
industry benchmarks and thresholds.
In determining the achievement
points for each measure, HHAs will
receive points along an achievement
range, which is a scale between the
achievement threshold and a
benchmark. We proposed, and are
finalizing in this rule, that the
achievement threshold will be
calculated as the median of all HHAs’
performance on the specified quality
measure during the baseline period and
to calculate the benchmark as the mean
of the top decile of all HHAs’
performance on the specified quality
measure during the baseline period.
Unlike the HVBP Program that uses a
national sample, this model will
calculate both the achievement
threshold and the benchmark separately
for each selected state and for HHA
cohort size. Under this methodology, we
will have benchmarks and achievement
thresholds for both the larger-volume
cohort and for the smaller-volume
cohort of HHAs (defined in each state
based on a baseline period that runs
from January 1, 2015 through December
31, 2015). Another way HHVBP differs
from the Hospital VBP is this model
only uses 2015 as the baseline year for
the measures included in the starter set.
For the starter set used in the model,
2015 will consistently be used as the
We proposed that all achievement
points would be rounded up or down to
the nearest point (for example, an
achievement score of 4.55 would be
rounded to 5). After considering the
potential skewing of HHA ranking that
would occur with rounding up to the
nearest point, we are finalizing that all
achievement points will be rounded up
or down to the third decimal point (for
example, an achievement score of
4.5555 would be rounded to 4.556). The
will ensure greater precision in scoring
and ranking HHAs within their cohorts.
HHAs could receive an achievement
score as follows:
• An HHA with performance equal to
or higher than the benchmark could
receive the maximum of 10 points for
achievement.
• An HHA with performance equal to
or greater than the achievement
threshold (but below the benchmark)
could receive 1–9 points for
achievement, by applying the formula
above.
• An HHA with performance less
than the achievement threshold could
receive 0 points for achievement.
We invited comments on the
proposed methodology for scoring
HHAs on achievement.
Comment: Some commenters
expressed concern that HHAs will not
know what benchmark is needed to
avoid penalty until the end of the 2015
performance year, and several
commenters recommended that CMS
establish benchmarks based on
historical performance so it is clear to
HHAs the level of achievement
necessary to avoid penalties.
Commenters voiced concern that
agencies may not invest in quality
improvement activities if the potential
financial return is difficult to determine.
Commenters also recommended that
CMS set benchmarks at a level such that
most providers have a reasonable
expectation of achieving them. A few
commenters suggested keeping 2015 as
the base year, and suggested providing
HHAs with mid-course snapshots of
their performance against the
benchmarks.
Response: The HHVBP Model is using
the 2015 quality data as the baseline for
the model because it is the most recent
data available. As indicated in the
payment methodology, the achievement
threshold for each measure used in the
5. Calculating Achievement and
Improvement Points
a. Achievement Scoring
We proposed the achievement scoring
under the HHVBP Model be based on
the Performance Assessment Model set
forth in the 2007 HVBP Report and as
implemented under the HVBP Program.
An HHA could earn 0–10 points for
achievement for each measure in the
Clinical Quality of Care, Care
Coordination and Efficiency, and Person
and Caregiver-Centered Experience
classifications based on where its
performance during the performance
period falls relative to the achievement
threshold and the benchmark, according
to the following formula:
51 For detailed information on HVBP scoring see
https://www.medicare.gov/hospitalcompare/data/
hospital-vbp.html.
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year. In total, the New Measures will
account for 10-percent of the TPS
regardless of the number of measures
applied to an HHA in the other three
classifications.
We proposed, and are finalizing in
this rule, to calculate the TPS for the
HHVBP methodology similarly to the
TPS calculation that has been finalized
under the HVBP program. The
performance scoring methodology for
the HHVBP Model will include
determining performance standards
(benchmarks and thresholds) using the
2015 baseline period performance year’s
quality measure data, scoring HHAs
based on their achievement and/or
improvement with respect to those
performance standards, and weighting
each of the classifications by the
number of measures employed, as
presented in further detail in Section G
below.
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respective HHA’s quarterly report. The
2015 base year achievement threshold
and the benchmarks for each cohort will
be provided to the HHAs in April 2016.
We believe that this will provide
sufficient notice to HHAs of the level of
performance necessary to receive points
for each given measure. In addition,
baseline values will be included in all
quarterly reports for all measures.
Final Decision: For the reasons
discussed and in consideration of the
comments received, we are finalizing
the proposed methodology for scoring
HHAs on achievement under the
HHVBP Model, with one modification.
Specifically, as noted above, under our
final policy all achievement points will
be rounded up or down to the third
decimal point (for example, an
achievement score of 4.5555 would be
rounded to 4.556).
b. Improvement Scoring
We proposed that all improvement
points will be rounded to the nearest
point and are now finalizing that
improvement points will be rounded up
or down to the third decimal point (see
example above). If an HHA’s
performance on the measure during the
performance period was:
• Equal to or higher than the
benchmark score, the HHA could
receive an improvement score of 10
points;
• Greater than its baseline period
score but below the benchmark (within
the improvement range), the HHA could
receive an improvement score of 0–10,
based on the formula above; or
• Equal to or lower than its baseline
period score on the measure, the HHA
could receive 0 points for improvement.
We invited comments on the
proposed methodology for scoring
HHAs on improvement.
Comment: There were many
comments directed at the proposed
methodology for improvement scoring
under the HHVBP Model. Some
commenters opposed awarding credit
for improvement, and noted their
concern that by using the greater of
either an HHA’s achievement or
improvement score, the methodology
could reward a HHA with a low
performance but high improvement
score because that HHA could receive
higher payments than a high performing
agency. These commenters encouraged
CMS to focus on rewarding the
achievement of specified quality scores,
and reduce its emphasis on
improvement scores after the initial
three years of the HHVBP Model, given
that what matters most to beneficiaries
is an agency’s actual performance.
Additionally, commenters
recommended that HHA achievement
scores be weighted more heavily than
improvement scores, noting that some
HHAs may have little or no room for
improvement in their current quality
performance scores. Some commenters
suggested measuring performance
primarily on the basis of achievement of
specified quality scores, with a
declining emphasis over time on
improvement versus achievement.
Response: We appreciate the
commenters raising these concerns. The
model is designed to improve and to
ensure the highest quality of care for all
Medicare beneficiaries. If the model
only focused on rewarding those HHAs
that already provide the highest quality
of care, only the beneficiaries that
receive care from those HHAs would
benefit from the model. Therefore, we
believe that providing the opportunity
to earn points for both achievement and
improvement provides the greatest
opportunity for the quality of care to
rise for all beneficiaries who receive
services from competing HHAs. We
will, however, monitor and evaluate the
impact of awarding an equal amount of
points for both achievement and
improvement and may consider changes
to the weight of the improvement score
relative to the achievement score in
future years through rulemaking.
Final Decision: For the reasons
discussed, we are finalizing the
improvement scoring methodology as
proposed.
Comment: Several commenters
expressed concern that the proposed
HHVBP structure requires that HHAs be
penalized each year, regardless of their
performance or improvement, noting
that each year, some HHAs will end up
in the bottom decile, even if the
difference between the highest and
lowest scoring is only a few points.
These commenters were concerned that
if the lowest scoring HHAs do not have
the resources to rise from the bottom
they are at risk for going out of business
by the end of the model. If low scoring
HHAs leave the market, then higher
scoring HHAs will move into the bottom
decile the next year of the model. These
HHAs could experience a downward
payment adjustment even though their
performance, in actuality, is not
significantly different than HHAs
ranked higher. These commenters are
concerned this limits value based
performance improvement.
Response: We understand
commenters concerns but the purpose of
the model is to improve quality across
the HH sector. As is the case currently,
the market will not remain static, and
HHAs of all calibers will leave and enter
the market. In many instances, if a small
number of low performing HHAs do
drop out of the market, the next group
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In keeping with the approach used by
the HVBP Program, we proposed that an
HHA could earn 0–10 points based on
how much its performance during the
performance period improved from its
performance on each measure in the
Clinical Quality of Care, Care
Coordination and Efficiency, and Person
and Caregiver-Centered Experience
classifications during the baseline
period. A unique improvement range for
each measure will be established for
each HHA that defines the difference
between the HHA’s baseline period
score and the same state and size level
benchmark for the measure used in the
achievement scoring calculation
described previously, according to the
following formula:
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model will be based on the median of
Medicare-certified HHA performance on
the specified quality measure during the
baseline period (2015). The benchmark
refers to the mean of the top decile of
Medicare-certified HHA performance on
the specified quality measure during the
baseline period (2015). Benchmarks and
achievement thresholds are calculated
separately for the larger-volume and
smaller-volume cohorts within each
state. HHAs will receive points if they
achieve performance equal to or above
the achievement threshold (the median
of 2015). We believe that awarding
points to HHAs that provide better
quality than the median is an achievable
level and will incentivize HHAs to make
the investments necessary to improve
their quality. Benchmarks and
achievement thresholds for each
measure will be available on each
Federal Register / Vol. 80, No. 214 / Thursday, November 5, 2015 / Rules and Regulations
of low scoring HHAs will include HHAs
whose performance equals or exceeds
the average baseline performance, and
will likely have received bonus
payments in previous years. We have
done financial modeling based on recent
HHA performance (see chart I2 for
further explanation) and results support
our understanding of how scoring will
work. In addition, we have analyzed
available data and lessons learned from
the Hospital VBP program and the
previous home health demonstration to
support our findings. As indicated in
the proposed rule,52 HHAs may end up
in the bottom decile in relationship to
other HHAs in their cohort in later years
of the model even after they improve
their quality if all the HHAs in the
model improve at the same rate.
However, in the HHVBP model their
downward payment adjustment, if any,
could be substantially reduced because
all performance scoring is anchored to
the 2015 benchmark.
Final Decision: For the reasons
discussed and in consideration of the
comments received, we are finalizing
the proposed methodology for scoring
HHAs under the HHVBP Model, with
one modification to decimal scoring,
where we are finalizing that all
achievement and improvement points
will be rounded up or down to the third
decimal point (for example, an
achievement score of 4.5555 would be
rounded to 4.556).
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52 80
FR 39910 (July 10, 2015). See Table 25.
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c. Examples of Calculating Achievement
and Improvement Scores
For illustrative purposes we present
the following examples of how the
performance scoring methodology will
be applied in the context of the
measures in the Clinical Quality of Care,
Care Coordination and Efficiency, and
Person and Caregiver-Centered
Experience classifications. These HHA
examples were selected from an
empirical database created from 2013/
2014 data from the Home Health
Compare archived data, claims data and
enrollment data to support the
development of the HHVBP permutation
of the Performance Assessment Model,
and all performance scores are
calculated for the pneumonia measure,
with respect to the number of
individuals assessed and administered
the pneumococcal vaccine. We note that
the figures and examples below are the
same figures and examples set forth in
the proposed rule, updated to reflect our
final policy on rounding of these scores,
as discussed previously.
Figure 7 shows the scoring for HHA
‘A’, as an example. The benchmark
calculated for the pneumonia measure
in this case was 0.875 (the mean value
of the top decile in 2013), and the
achievement threshold was 0.474 (the
performance of the median or the 50th
percentile among HHAs in 2013). HHA
A’s 2014 performance rate of 0.910
during the performance period for this
measure exceeds the benchmark, so
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HHA A would earn 10 (the maximum)
points for its achievement score. The
HHA’s performance rate on a measure is
expressed as a decimal. In the
illustration, HHA A’s performance rate
of 0.910 means that 91-percent of the
applicable patients that were assessed
were given the pneumococcal vaccine.
In this case, HHA A has earned the
maximum number of 10 possible
achievement points for this measure and
thus, its improvement score is irrelevant
in the calculation.
Figure 7 also shows the scoring for
HHA ‘B’. As referenced below, HHA B’s
performance on this measure went from
0.212 (which was below the
achievement threshold) in the baseline
period to 0.703 (which is above the
achievement threshold) in the
performance period. Applying the
achievement scale, HHA B would earn
5.640 points for achievement, calculated
as follows: [9 * ((0.703 ¥ 0.474)/(0.875
¥ 0.474))] + 0.5 = 5.640.
Checking HHA B’s improvement score
yields the following result: Based on
HHA B’s period-to-period improvement,
from 0.212 in the baseline year to 0.703
in the performance year, HHA B would
earn 6.906 points, calculated as follows:
[10 * ((0.703 ¥ 0.212)/(0.875 ¥ 0.212))]
¥ 0.5 = 6.906. Because the higher of the
achievement and improvement scores is
used, HHA B would receive 6.906
points for this measure.
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In Figure 8, HHA ‘C’ yielded a decline
in performance on the pneumonia
measure, falling from 0.571 to 0.462 (a
decline of 0.11 points). HHA C’s
performance during the performance
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period is lower than the achievement
threshold of 0.472 and, as a result,
receives 0 points based on achievement.
It also receives 0 points for
improvement, because its performance
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during the performance period is lower
than its performance during the baseline
period.
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6. Scoring Methodology for New
Measures
The HHVBP Model provides us with
the opportunity to study new quality
measures. We proposed that the New
Measures for PY1 would be reported
directly by the HHA and would account
for 10-percent of the TPS regardless of
the number of measures in the other
three classifications (we refer the reader
to 80 FR 39890 for further discussion of
our proposed scoring methodology for
New Measures). For the reasons set forth
in the proposed rule and in response to
comments below, we are finalizing our
proposed scoring methodology for New
Measures, revised only to reflect that the
final starter set will include three, rather
than four, New Measures, as discussed
in section E5. Under our final
methodology, the final three New
Measures that we are adopting for PY1
will be reported directly by the HHA
and will account for 10-percent of the
TPS regardless of the number of
measures in the other three
classifications. HHAs that report on
these measures will receive 10 points
out of a maximum of 10 points for each
of the 3 measures in the New Measure
classification. Hence, a HHA that
reports on all 3 measures will receive 30
points out of a maximum of 30. An HHA
will receive 0 points for each measure
that it fails to report on. If an HHA
reports on all 3 measures, it will receive
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30 points for the classification and 10
points (30/30 * 10 points) will be added
to its TPS because the New Measure
classification has a maximum weight of
10 percent. If an HHA reports on 2 of
3 measures, it will receive 20 points of
30 points available for the classification
and 6.667 points (20/30 * 10 points)
added to its TPS. If an HHA reports on
1 of 3 measures, they will receive 10
points of 30 points available for the
classification and 3.333 points (10/30 *
10 points) added to their TPS. If an
HHA reports on 0 of 3 measures, they
will receive 0 points and have no points
added to their TPS. We intend to update
these measures through future
rulemaking to allow us to study newer,
leading-edge measures as well as retire
measures that no longer require such
analysis.
We invited comments on the
proposed scoring methodology for New
Measures.
Comment: Several commenters
expressed support for CMS limiting the
burden on HHAs by allowing them to
gain full credit toward their TPS on the
New Measures just for reporting data to
CMS.
Response: We appreciate the
commenters’ support for our proposal.
In order to reduce the burden of
introducing innovative measures not
previously endorsed for home health,
and to allow HHAs to acclimate to
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68685
reporting the New Measures, we are
finalizing our proposed scoring
methodology that awards HHAs full
credit for data reporting on New
Measures.
Final Decision: For the reasons
discussed and in consideration of the
comments received, we are finalizing
our proposed scoring methodology for
New Measures, modified to reflect the
removal of one New Measure resulting
in a total of three New Measures for
PY1.
7. Minimum Number of Cases for
Outcome and Clinical Quality Measures
We proposed that while no HHA in a
selected state would be exempt from the
HHVBP Model, there may be periods
when an HHA does not receive a
payment adjustment because there are
not an adequate number of episodes of
care to generate sufficient quality
measure data. We proposed, and are
finalizing in this rule, that the minimum
threshold for an HHA to receive a score
on a given measure will be 20 home
health episodes of care per year for
HHAs that have been certified for at
least 6-months. If a competing HHA
does not meet this threshold to generate
scores on five or more of the Clinical
Quality of Care, Care Coordination and
Efficiency, and Person and CaregiverCentered Experience measures, no
payment adjustment will be made, and
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the HHA will be paid for HHA services
in an amount equivalent to the amount
it would have been paid under section
1895 of the Act.53
We explained in the proposed rule
that HHAs with very low case volumes
will either increase their volume in later
performance years, and be subject to
future payment adjustment, or the
HHAs’ volume will remain very low and
the HHAs would continue to not have
their payment adjusted in future years.
Based on the most recent data available
at this time, a very small number of
HHAs are reporting on less than five of
the total number of measures included
in the Clinical Quality of Care, Care
Coordination and Efficiency, and Person
and Caregiver-Centered Experience
classifications and account for less than
0.5 percent of the claims made over
1,900 HHAs delivering care within the
nine selected states. We stated that we
expect very little impact of very low
service volume HHAs on the model due
to the low number of low-volume HHAs
and because it is unlikely that a HHA
will reduce the amount of service to
such a low level to avoid a payment
adjustment. Although these HHAs will
not be subject to payment adjustments,
they will remain in the model and have
access to the same technical assistance
as all other HHAs in the model, and will
receive quality reports on any measures
for which they do have 20 episodes of
care, and a future opportunity to
compete for payment adjustments.
We invited comments on the
proposed minimum number of cases to
receive a score on outcome and clinical
quality measures.
Comment: One commenter expressed
concern that some HHAs would
artificially suppress the number of cases
open in OASIS to below 20 in order to
be excluded from a particular measure,
or be excluded from a sufficient number
of measures to be excluded from
payment adjustments entirely.
Response: All Medicare-certified
HHAs in selected states are included in
the HHVBP Model, even when a
particular HHA does not meet the
minimum number of cases to generate
scores on a sufficient number of quality
measures. During a period when an
HHA does not receive a payment
adjustment the HHA remains in the
model, performance is still monitored,
and the agency is eligible for technical
assistance. HHAs with small patient
loads are expected to access technical
assistance and engage in quality
53 HHVBP would follow the Home Health
Compare Web site policy not to report measures on
HHAs that have less than 20 observations for
statistical reasons concerning the power to detect
reliable differences in the quality of care.
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improvement activities in anticipation
of earning scores on all quality measures
in the future. HHAs with small patient
populations are also expected to enter
data on the New Measures via the CMS
portal. In addition, HHAs must submit
OASIS data in order to receive payment
for their services. We do not anticipate
HHAs suppressing the number of
patients they serve in order to avoid
payment adjustments because there are
very few HHAs that provide care to such
a small number of beneficiaries and the
financial losses associated with
restricting the volume of care provided
would far outweigh the losses
associated with the downward payment
adjustment.
Final Decision: For these reasons and
in consideration of the comments
received, we are finalizing our proposal
on the minimum number of cases for
outcome and clinical quality measures
without modification.
We provide below an example of the
payment methodology. We note that this
is the same example provided in the
proposed rule (see 80 FR 39891),
modified only to reflect our final policy
to include 21 (rather than 25) measures
in the Clinical Quality of Care, Care
Coordination and Efficiency, and Person
and Caregiver-Centered Experience
classifications and three (rather than
four) New Measures in the final starter
set for PY1.
HHA ‘‘A’’ has at least 20 episodes of
care in a 12-month period for only nine
(9) quality measures out of a possible 21
measures from three of the four
classifications (except the New
Measures). Under the final scoring
methodology outlined above, HHA A
would be awarded 0, 0, 3, 4, 5, 7, 7, 9,
and 10 points, respectively, for these
measures. HHA A’s total earned points
for the three classifications would be
calculated by adding together all the
points awarded to HHA A, resulting in
a total of 45 points. HHA A’s total
possible points would be calculated by
multiplying the total number of
measures for which the HHA reported
on least 20 episodes (nine) by the
maximum number of points for those
measures (10), yielding a total of 90
possible points. HHA A’s score for the
three classifications would be the total
earned points (45) divided by the total
possible points (90) multiplied by 90
because as mentioned in section E7, the
Clinical Quality of Care, Care
Coordination and Efficiency, and Person
and Caregiver-Centered Experience
classifications account for 90-percent of
the TPS and the New Measures
classification accounts for 10-percent of
the TPS, which yields a result of 45. In
this example, HHAs also reported all 3
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measures and would receive the full 10
points for the New Measures. As a
result, the TPS for HHA A would be 55
(45 plus 10). In addition, as specified in
Section E:7—Weighting, all measures
have equal weights regardless of their
classification (except for New Measures)
and the total earned points for the three
classifications can be calculated by
adding the points awarded for each such
measure together.
G. The Payment Adjustment
Methodology
We proposed to codify at 42 CFR
484.330 a methodology for applying
value-based payment adjustments to
home health services under the HHVBP
Model. We proposed that payment
adjustments would be made to the HH
PPS final claim payment amount as
calculated in accordance with § 484.205
using a linear exchange function (LEF)
similar to the methodology utilized by
the HVBP Program. The LEF is used to
translate an HHA’s TPS into a
percentage of the value-based payment
adjustment earned by each HHA under
the HHVBP Model. The LEF was
identified by the HVBP Program as the
simplest and most straightforward
option to provide the same marginal
incentives to all hospitals, and we
believe the same to be true for HHAs.
We proposed the function’s intercept at
zero percent, meaning those HHAs that
have a TPS that is average in
relationship to other HHAs in their
cohort (a zero percent), would not
receive any payment adjustment.
Payment adjustments for each HHA
with a score above zero percent would
be determined by the slope of the LEF.
In addition we proposed to set the slope
of the LEF for the first performance year,
CY 2016, so that the estimated aggregate
value-based payment adjustments for
CY 2016 are equal to 5-percent of the
estimated aggregate base operating
episode payment amount for CY 2018.
The estimated aggregate base operating
episode payment amount is the total
amount of episode payments made to all
the HHAs by Medicare in each
individual state in the larger- and
smaller-volume cohorts respectively.
We provided in Figure 9 of the
proposed rule an example of how the
LEF is calculated and how it would be
applied to calculate the percentage
payment adjustment to a HHA’s TPS
(we refer the reader to 80 FR 39891
through 39892 for further discussion of
our proposal). For this example, we
applied the 8-percent payment
adjustment level that was proposed to
be used in the final 2 years of the
HHVBP Model, and noted that the rate
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for the payment adjustments for other
years would be proportionally less.
We invited comments on this
proposed payment adjustment
methodology.
Comment: While offering support for
the concept of value-based purchasing,
the majority of commenters expressed
concern with the magnitude of an 8percent maximum payment risk such
that it might reduce access to care for
vulnerable patients. Commenters offered
that payment adjustments could be
made in later years of the model to
provide HHAs with adequate time to
ensure readiness to comply with model
requirements and to allow CMS more
time to study the initial model results.
Many commenters also remarked on the
differences between the Hospital ValueBased Purchasing (HVBP) Program and
HHVBP Model maximum risk corridors
and suggested lowering the HHVBP
payment adjustments to align with the
2-percent maximum established in the
HVBP Program.
Response: We thank commenters for
their input. As discussed in the
proposed rule, based on lessons learned
from Hospital VBP, the 2008 Home
Health pay for performance
demonstration, and the MedPAC report,
we believe that testing high financial
incentives is necessary to motivate
improvements in quality and patient
satisfaction. However, we agree with
commenters that providing some
additional leeway for HHAs to ensure
compliance with the model is
important, and would also address
concerns associated with moving
competing HHAs from FFS incentives to
VBP financial incentives tied to quality
measures. Accordingly, under our final
policy, we are reducing the payment
adjustment percentage in CY 2018 from
5-percent to 3-percent. Further, by
responding to these practical concerns,
the conceptual model remains intact
with the capacity to test the effect of
higher incentives on quality.
We believe this will provide HHAs
more time to become familiar with the
operation of the model before applying
the higher percentage payment
adjustments in later years. Additionally,
under our final policy, we are reducing
the payment adjustment for CY 2021
from 8-percent to 7-percent to establish
a more gradual payment adjustment
incentive schedule of 3-percent (in
2018), 5-percent (in 2019), 6-percent (in
2020), 7-percent (in 2021) and, 8percent (in 2022).
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Comment: Several commenters raised
concerns with the magnitude of an 8percent maximum payment risk such
that it might reduce access to care for
vulnerable patients and threaten the
financial viability of HHAs, including
their ability to reinvest in infrastructure,
care coordination, and financial
preparations to participate in the
HHVBP Model.
Response: We have conducted
financial modeling based on the
proposed model and posit the finalized
maximum upward and downward
payment adjustments (ranging from 3- to
8-percent) are sufficiently significant to
improve quality of care and will not
have a negative impact on beneficiary
access. The model does not reduce the
overall payments to HHAs and, as a
result, the aggregate average margins of
all competing HHAs will be unaffected
by the model. 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.
Final Decision: For the reasons
discussed and in consideration of the
comments received, we are finalizing
the proposed payment adjustment
methodology with modification. As
noted, we are finalizing the following
maximum payment adjustment
percentage for each payment year: in CY
2018, 3-percent; in CY 2019, 5-percent;
in CY 2020, 6-percent; in CY 2021, 7percent; and in CY 2022, 8-percent.
Consistent with this final policy, under
our final payment adjustment
methodology, we set the slope of the
LEF for the first performance year, CY
2016, so that the estimated aggregate
value-based payment adjustments for
CY 2016 are equal to 3-percent of the
estimated aggregate base operating
episode payment amount for CY 2018,
rather than 5-percent as proposed.
Figure 9 provides an example of how
the LEF is calculated and how it is
applied to calculate the percentage
payment adjustment to a HHA’s TPS
under our final policy. For this example,
we applied the 8-percent payment
adjustment level that will be used in the
final year of the HHVBP Model (CY
2022) under our final policy. The rate
for the payment adjustments for other
years would be proportionally less.
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68687
Step #1 involves the calculation of the
‘Prior Year Aggregate HHA Payment
Amount’ (See C2 in Figure 9) that each
HHA was paid in the prior year. From
claims data, all payments are summed
together for each HHA for CY 2015, the
year prior to the HHVBP Model.
Step #2 involves the calculation of the
‘8-percent Payment Reduction Amount’
(C3 of Figure 9) for each HHA. The
‘Prior Year Aggregate HHA Payment
Amount’ is multiplied by the ‘8-percent
Payment Reduction Rate’. The aggregate
of the ‘8-percent Payment Reduction
Amount’ is the numerator of the LEF.
Step #3 involves the calculation of the
‘Final TPS Adjusted Reduction Amount’
(C4 of Figure 9) by multiplying the ‘8percent Payment Reduction Amount’
from Step #2 by the TPS (C1) divided
by 100. The aggregate of the ‘TPS
Adjusted Reduction Amount’ is the
denominator of the LEF.
Step #4 involves calculating the LEF
(C5 of Figure 9) by dividing the
aggregate ‘8-percent Payment Reduction
Amount’ by the aggregate ‘TPS Adjusted
Reduction Amount’.
Step #5 involves the calculation of the
‘Final TPS Adjusted Payment Amount’
(C6 of Figure 9) by multiplying the ‘TPS
Adjusted Reduction Amount’ (C4) by
the LEF (C5). This is an intermediary
value used to calculate ‘Quality
Adjusted Payment Rate’.
Step #6 involves the calculation of the
‘Quality Adjusted Payment Rate’ (C7 of
Figure 9) that the HHA will receive
instead of the 8-percent reduction in
payment. This is an intermediary step to
determining the payment adjustment
rate. For CY 2022, the payment
adjustment in this column will range
from 0-percent to 16-percent depending
on the quality of care provided.
Step #7 involves the calculation of the
‘Final Percent Payment Adjustment’ (C8
of Figure 9) that will be applied to the
HHA payments after the performance
period. It simply involves the CY
payment adjustment percent (as
finalized, in 2018, 3-percent; in 2019, 5percent; in 2020, 6-percent; in 2021, 7percent; and in 2022, 8-percent). In this
example, we use the maximum eightpercent (8-percent) subtraction to the
‘Quality Adjusted Payment Rate’. Note
that the payment adjustment percentage
is capped at no more than plus or minus
8-percent for each respective
performance period and the payment
adjustment will occur on the final claim
payment amount.
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FIGURE 9—8-PERCENT REDUCTION SAMPLE
Step 1
Step 3
Step 4
Step 5
Step 6
Step 7
TPS
Prior year
aggregate
HHA
payment *
8-Percent
payment
reduction
amount
(C2*8%)
TPS adjusted
reduction
amount
(C1/100)*C3
Linear
exchange
function
(LEF)
(Sum of C3/
Sum of C4)
Final TPS
adjusted
payment
amount
(C4*C5)
Quality
adjusted
payment rate
(C6/C2)
*100
Final percent
payment
adjustment
+/¥
(C7–8%)
(C1)
HHA
Step 2
(C2)
(C3)
(C4)
(C5)
(C6)
(C7)
(C8)
......................
......................
......................
......................
......................
......................
......................
......................
38
55
22
85
50
63
74
25
$100,000
145,000
800,000
653,222
190,000
340,000
660,000
564,000
$8,000
11,600
64,000
52,258
15,200
27,200
52,800
45,120
$3,040
6,380
14,080
44,419
7,600
17,136
39,072
11,280
1.93
1.93
1.93
1.93
1.93
1.93
1.93
1.93
$5,867
12,313
27,174
85,729
14,668
33,072
75,409
21,770
5.9 %
8.5
3.4
13.1
7.7
9.7
11.4
3.9
¥2.1%
0.5
¥4.6
5.1%
¥0.3%
1.7
3.4
¥4.1
Sum .................
................
......................
276,178
143,007
......................
276,002
......................
......................
HHA1
HHA2
HHA3
HHA4
HHA5
HHA6
HHA7
HHA8
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* Example cases.
H. Preview and Period to Request
Recalculation
We proposed that Medicare-certified
HHAs be provided two separate
opportunities to review scoring
information under the HHVBP Model.
First, HHAs will have the opportunity to
review their quarterly quality reports
following each quarterly posting;
second, competing HHAs will have the
opportunity to review their TPS and
payment adjustment calculations, and
request a recalculation if a discrepancy
is identified due to a CMS error as
described in this section. These
processes would help educate and
inform each competing Medicarecertified HHA on the direct relation
between the payment adjustment and
performance measure scores.
We proposed to inform HHAs
quarterly of their performance on each
of the individual quality measures used
to calculate the TPS. We proposed that
an HHA would have ten days after the
quarterly reports are provided to request
a recalculation of measure scores if it
believes there is evidence of a
discrepancy. We stated that we will
adjust the score if it is determined that
the discrepancy in the calculated
measure scores was the result of our
failure to follow measurement
calculation protocols.
In addition, we proposed to inform
each competing HHA of the TPS and
payment adjustment amount in an
annual report. We proposed that these
annual reports would be provided to
competing HHAs each August 1st prior
to the calendar year for which the
payment adjustment would be applied.
Similar to quarterly reports, we
proposed that HHAs will have ten days
to request a recalculation of their TPS
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and payment adjustment amount from
the date information is made available.
For both the quarterly reports and the
annual report containing the TPS and
payment adjustments, competing HHAs
will only be permitted to request scoring
recalculations, and must include a
specific basis for the requested
recalculation. We will not be
responsible for providing HHAs with
the underlying source data utilized to
generate performance measure scores.
Each HHA has access to this data via the
QIES system. The final TPS and
payment adjustment will then be
provided to competing Medicarecertified HHAs in a final report no later
than 60 days in advance of the payment
adjustment taking effect.
The TPS from the annual performance
report will be calculated based on the
calculation of performance measures
contained in the quarterly reports that
have already been provided and
reviewed by the HHAs. As a result, we
stated in the proposed rule that we
believe that quarterly reviews will
provide substantial opportunity to
identify and correct errors and resolve
discrepancies, thereby minimizing the
challenges to the annual performance
scores linked to payment adjustment.
As described above, a quarterly
performance report will be provided to
all competing HHAs within the selected
states beginning with the first quarter of
CY 2016 being reported in July 2016.
We proposed that HHAs would submit
recalculation requests for both quarterly
quality performance measure reports
and for the TPS and payment
adjustment reports via an email link
provided on the model-specific Web
page. We proposed that the request form
would be entered by a person who has
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authority to sign on behalf of the HHA
and be submitted within 10 days of
receiving the quarterly data report or the
annual TPS and payment adjustment
report.
We proposed that requests for both
quarterly report measure score
recalculations or TPS and payment
adjustment recalculations would
contain the following information:
• The provider’s name, address
associated with the services delivered,
and CMS Certification Number (CCN);
• The basis for requesting
recalculation to include the specific
quality measure data that the HHA
believes is inaccurate or the calculation
the HHA believes is incorrect;
• Contact information for a person at
the HHA with whom CMS or its agent
can communicate about this request,
including name, email address,
telephone number, and mailing address
(must include physical address, not just
a post office box); and,
• A copy of any supporting
documentation the HHA wishes to
submit in electronic form via the modelspecific Web page.
Following receipt of a request for
quarterly report measure score
recalculations or a request for TPS and
payment adjustment recalculation, we
proposed that CMS or its agent would:
• Provide an email acknowledgement,
using the contact information provided
in the recalculation request, to the HHA
contact notifying the HHA that the
request has been received;
• Review the request to determine
validity, and determine whether the
requested recalculation results in a
score change altering performance
measure scores or the HHA’s TPS;
• If recalculation results in a
performance measure score or TPS
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change, conduct a review of quality data
and if an error is found, recalculate the
TPS using the corrected performance
data; and,
• Provide a formal response to the
HHA contact, using the contact
information provided in the
recalculation request, notifying the HHA
of the outcome of the review and
recalculation process.
We proposed that recalculation and
subsequent communication of the
results of these determinations would
occur as soon as administratively
feasible following the submission of
requests. Additionally, we stated that
we will develop and adopt an appeals
mechanism under the model through
future rulemaking in advance of the
application of any payment
adjustments.
The following is a summary of
comments we received on the proposed
quarterly quality measure reports and
annual TPS preview periods.
Comment: Several commenters
suggested that the HHVBP Model
provide 30 days, instead of 10 days,
after quarterly and annual reports are
provided to request a recalculation of
the measure scores if the HHA believes
there is evidence of discrepancy. In
addition to allowing more time to
challenge report contents, one
commenter recommended another level
of appeal be added with an independent
entity to perform the calculation to
determine if the discrepancy is valid.
Response: We agree the review period
for performance scores should be greater
than 10 days to allow a more complete
opportunity for HHAs to review, and are
extending the time period for HHAs to
preview their quarterly performance
reports and annual payment adjustment
reports (with requests for recalculations)
from 10 days to 30 days. As noted in the
proposed rule, CMS intends to propose
an appeals mechanism in future
rulemaking prior to the application of
the first payment adjustments scheduled
for 2018.
Final Decision: For the reasons stated
and in consideration of the comments
received, we are finalizing the processes
described above with modification.
Specifically, under our final policy, the
recalculation request form must be
submitted within 30 days, rather than
10 days, of posting the quarterly data
report or the annual TPS and payment
adjustment reports on the modelspecific Web site. We are not making
any other changes to the proposed
policies as described in this section.
I. Evaluation
We proposed, and are finalizing in
this rule, to codify at § 484.315(c) that
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competing HHAs in selected states will
be required to collect and report
information to CMS necessary for the
purposes of monitoring and evaluating
this model as required by statute.54 An
evaluation of the HHVBP Model will be
conducted in accordance with section
1115A(b)(4) of the Act, which requires
the Secretary to evaluate each model
tested by CMMI. We consider an
independent evaluation of the model to
be necessary to understand its impacts
on care quality in the home health
setting. The evaluation will be focused
primarily on understanding how
successful the model is in achieving
quality improvement as evidenced by
HHAs’ performance on clinical care
process measures, clinical outcome
measures (for example, functional
status), utilization/outcome measures
(for example, hospital readmission rates,
emergency room visits), access to care,
and patient’s experience of care, and
Medicare costs. We also intend to
examine the likelihood of unintended
consequences. We intend to select an
independent evaluation contractor to
perform this evaluation. The
procurement for the selection of the
evaluation contractor is in progress,
thus we cannot provide a detailed
description of the evaluation
methodology here.
We intend to use a multilevel
approach to evaluation. Here, we intend
to conduct analyses at the state, HHA,
and patient levels. Based on the state
groupings discussed in the section on
selection of competing HHAs, we
believe there are several ways in which
we can draw comparison groups and
remain open to scientifically-sound,
rigorous methods for evaluating the
effect of the model intervention.
The evaluation effort may require of
HHAs participating in the model
additional data specifically for
evaluation purposes. Such requirements
for additional data to carry out model
evaluation will be in compliance with
42 CFR 403.1105 which, as of January
1, 2015, requires entities participating in
the testing of a model under section
1115A to collect and report such
information, including protected health
information (as defined at 45 CFR
160.103), as the Secretary determines is
necessary to monitor and evaluate the
model. We will consider all Medicarecertified HHAs providing services
within a state selected for the model to
be participating in the testing of this
model because the competing HHAs
54 See section 1115A(b)(4) of the Act (42 U.S.C.
1315a).
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68689
will be receiving payment from CMS
under the model.55
We invited comments on the
proposed evaluation plan.
Comment: Several commenters
highlighted the importance of closely
monitoring and evaluating Medicare
beneficiary access to home healthcare to
ensure the model does not inadvertently
negatively impact beneficiary access to
necessary and appropriate care. In
addition, some commenters suggested
the model may cause some HHAs in
selected states to leave the market,
thereby creating insufficient HHA
supply. Other commenters specifically
raised the concern that some HHAs may
attempt to avoid treating beneficiaries
they fear will have a negative impact on
performance scores. These commenters
suggest that CMS monitor whether
Medicare beneficiaries experience
problems with access to care, and if they
do, immediately address issues to
ensure beneficiaries receive needed
services. One commenter specifically
suggests surveying Medicare
beneficiaries to help measure access and
ensure proactive monitoring.
Response: Beneficiary access to care is
of paramount concern to us, and as
indicated in the proposed rule, we will
observe the progress of the model to
guard against unintended consequences.
Our monitoring and evaluation designs
will be able to detect the types of
concerns mentioned above. Adjustments
to the monitoring and evaluation plans
will be made as needed. As part of the
development of this model, we have
identified counties with low HHA
market penetration, high dually-eligible
populations, proportions of
beneficiaries with high levels of acuity
(as measured by hierarchical condition
categories or HCCs), and organizational
types. Future monitoring activities will
include a continuous review of
beneficiary-level claims data, Medicare
cost reports, and beneficiary enrollment
data to understand whether any
unintended consequences arise across
all competing HHAs in the Model.
Comment: Several commenters
suggested that CMS employ a process to
continuously monitor quality
improvement and evaluate other aspects
of the model in conjunction with all
stakeholders, including home health
agencies. Commenters also
recommended sharing lessons learned
from the model to inform, educate and
engage beneficiaries and the general
public of lessons learned. Several
commenters specifically recommended
that CMS establish a HHVBP learning
55 79
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network to foster smoother post-pilot
implementation of VBP in home health.
Response: We agree that wherever
possible, competing HHAs should have
every opportunity to share lessons
learned from the model. We appreciate
all suggestions related to learning from
the HHVBP Model, both for competing
HHAs and the public. The model
contains multiple mechanisms for
sharing information, including the use
of a model-specific Web site, a
collaboration Web site, and modelspecific technical assistance efforts.
Comment: Several commenters
specifically requested subsequent
revisions to the HHVBP Model
following initial evaluation in order to
ensure that payment reflects a broad
range of patients and does not
incentivize under or over provision of
services. These commenters
recommended independent evaluation
that includes state specific data on
changes in home health quality
outcomes, changes in home health
utilization and access to home health for
patients with specific diagnosis and
functional status, with breakdowns by
geographic location of patients (for
example, rural, urban).
Response: We appreciate the
recommendations provided. An
independent evaluation is planned. As
discussed in the proposed rule, we
intend to use a multilevel approach to
evaluation. We intend to conduct
analyses at the state, HHA, and patient
levels. The evaluation will be conducted
in accordance with section 1115A(b)(4)
of the Act and will include analysis of
quality improvement as evidenced by
HHAs’ performance on clinical care
process measures, clinical outcome
measures (for example, functional
status), utilization/outcome measures
(for example, hospital readmission rates,
emergency room visits), access to care,
and patient’s experience of care, and
changes in Medicare costs. We also
intend to examine the likelihood of
unintended consequences. The
evaluation will use a scientifically
rigorous approach for evaluating the
model intervention and making
necessary alterations to the model as
needed.
Final Decision: For these reasons and
in consideration of the comments
received, we are finalizing the
evaluation plan as proposed.
V. Provisions of the Home Health Care
Quality Reporting Program (HHQRP)
and Response to Comments
A. Background and Statutory Authority
Section 1895(b)(3)(B)(v)(II) of the Act
requires that for 2007 and subsequent
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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 for a particular year, the 2
percentage point reduction under
section 1895(b)(3)(B)(v)(I) of the Act
may result in this percentage increase,
after application of the productivity
adjustment under section
1895(b)(3)(B)(vi)(I) of the Act, 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.
Section 2(a) of the Improving
Medicare Post-Acute Care
Transformation Act of 2014 (the
IMPACT Act) (Pub. L. 113–185, enacted
on Oct. 6, 2014) amended Title XVIII of
the Act, in part, by adding a new section
1899B, which imposes new data
reporting requirements for certain postacute care (PAC) providers, including
HHAs. New section 1899B of the Act is
titled, ‘‘Standardized Post-Acute Care
(PAC) Assessment Data for Quality,
Payment, and Discharge Planning’’.
Under section 1899B(a)(1) of the Act,
certain post-acute care (PAC) providers
(defined in section 1899B(a)(2)(A) of the
Act to include HHAs, SNFs, IRFs, and
LTCHs) must submit standardized
patient assessment data in accordance
with section 1899B(b) of the Act, data
on quality measures required under
section 1899B(c)(1) of the Act, and data
on resource use, and other measures
required under section 1899B(d)(1) of
the Act. The Act also sets out specified
application dates for each of the
measures. The Secretary must specify
the quality, resource use, and other
measures no later than the applicable
specified application date defined in
section 1899B(a)(2)(E) of the Act.
Section 1899B(b) of the Act describes
the standardized patient assessment
data that PAC providers are required to
submit in accordance with section
1899B(b)(1) of the Act; requires the
Secretary, to the extent practicable, to
match claims data with standardized
patient assessment data in accordance
with section 1899B(b)(2) of the Act; and
requires the Secretary, as soon as
practicable, to revise or replace existing
patient assessment data to the extent
that such data duplicate or overlap with
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standardized patient assessment data, in
accordance with section 1899B(b)(3) of
the Act.
Sections 1899B(c)(1) and (d)(1) of the
Act direct the Secretary to specify
measures that relate to at least five
stated quality domains and three stated
resource use and other measure
domains. Section 1899B(c)(1) of the Act
provides that the quality measures on
which PAC providers, including HHAs,
are required to submit standardized
patient assessment data and other
necessary data specified by the
Secretary must be in accordance with, at
least, the following domains:
• Functional status, cognitive
function, and changes in function and
cognitive function;
• Skin integrity and changes in skin
integrity;
• Medication reconciliation;
• Incidence of major falls; and
• Accurately communicating the
existence of and providing for the
transfer of health information and care
preferences of an individual to the
individual, family caregiver of the
individual, and providers of services
furnishing items and services to the
individual when the individual
transitions (1) from a hospital or Critical
Access Hospital (CAH) to another
applicable setting, including a PAC
provider or the home of the individual,
or (2) from a PAC provider to another
applicable setting, including a different
PAC provider, hospital, CAH, or the
home of the individual.
Section 1899B(c)(2)(A) provides that,
to the extent possible, the Secretary
must require such reporting through the
use of a PAC assessment instrument and
modify the instrument as necessary to
enable such use.
Section 1899B(d)(1) of the Act
provides that the resource use and other
measures on which PAC providers,
including HHAs, are required to submit
any necessary data specified by the
Secretary, which may include
standardized assessment data in
addition to claims data, must be in
accordance with, at least, the following
domains:
• Resource use measures, including
total estimated Medicare spending per
beneficiary;
• Discharge to community; and
• Measures to reflect all-condition
risk-adjusted potentially preventable
hospital readmission rates.
Sections 1899B(c) and (d) of the Act
indicate that data satisfying the eight
measure domains in the IMPACT Act is
the minimum data reporting
requirement. The Secretary may specify
additional measures and additional
domains.
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Section 1899B(e)(1) of the Act
requires that the Secretary implement
the quality, resource use, and other
measures required under sections
1899B(c)(1) and (d)(1) of the Act in
phases consisting of measure
specification, data collection, and data
analysis; the provision of feedback
reports to PAC providers in accordance
with section 1899B(f) of the Act; and
public reporting of PAC providers’
performance on such measures in
accordance with section 1899B(g) of the
Act. Section 1899B(e)(2) of the Act
generally requires that each measure
specified by the Secretary under section
1899B of the Act be National Quality
Forum (NQF)-endorsed, but authorizes
an exception under which the Secretary
may select non-NQF-endorsed quality
measures in the case of specified areas
or medical topics determined
appropriate by the Secretary for which
a feasible or practical measure has not
been endorsed by the NQF, as long as
due consideration is given to measures
that have been endorsed or adopted by
a consensus organization identified by
the Secretary. Section 1899B(e)(3) of the
Act provides that the pre-rulemaking
process required by section 1890A of
the Act applies to quality, resource use,
and other measures specified under
sections 1899B(c)(1) and (d)(1) of the
Act, but authorizes exceptions under
which the Secretary may (1) use
expedited procedures, such as ad hoc
reviews, as necessary in the case of a
measure required for data submissions
during the 1-year period before the
applicable specified application date, or
(2) alternatively, waive section 1890A of
the Act in the case of such a measure
if applying section 1890A of the Act
(including through the use of expedited
procedures) would result in the inability
of the Secretary to satisfy any deadline
specified under section 1899B of the Act
for the measure.
Section 1899B(f)(1) of the Act requires
the Secretary to provide confidential
feedback reports to PAC providers on
the performance of such PAC providers
for quality, resource use, and other
measures required under sections
1899B(c)(1) and (d)(1) of the Act
beginning 1 year after the applicable
specified application date.
Section 1899B(g) of the Act requires
the Secretary to establish procedures for
making available to the public
information regarding the performance
of individual PAC providers for quality,
resource use, and other measures
required under sections 1899B(c)(1) and
(d)(1) beginning not later than 2 years
after the applicable specified
application date. The procedures must
ensure, including through a process
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consistent with the process applied
under section 1886(b)(3)(B)(viii)(VII) for
similar purposes, that each PAC
provider has the opportunity to review
and submit corrections to the data and
information that are to be made public
for the PAC provider prior to such data
being made public.
Section 1899B(h) of the Act sets out
requirements for removing, suspending,
or adding quality, resource use, and
other measures required under sections
1899B(c)(1) and (d)(1) of the Act. In
addition, section 1899B(j) of the Act
requires the Secretary to allow for
stakeholder input, such as through town
halls, open door forums, and mailbox
submissions, before the initial
rulemaking process to implement
section 1899B of the Act.
Section 2(c)(1) of the IMPACT Act
amended section 1895 of the Act to
address the payment consequences for
HHAs for the additional data which
HHAs are required to submit under
section 1899B of the Act. These changes
include the addition of a new section
1895(b)(3)(B)(v)(IV), which requires
HHAs to submit the following
additional data: (1) For the year
beginning on the specified application
date and each subsequent year, data on
the quality, resource use, and other
measures required under sections
1899B(c)(1) and (d)(1) of the Act; and (2)
for 2019 and subsequent years, the
standardized patient assessment data
required under section 1899B(b)(1) of
the Act. Such data must be submitted in
the form and manner, and at the time,
specified by the Secretary.
As noted, the IMPACT Act adds a
new section 1899B of the Act that
imposes new data reporting
requirements for certain post-acute care
(PAC) providers, including HHAs.
Sections 1899B(c)(1) and 1899B(d)(1) of
the Act collectively require that the
Secretary specify quality measures and
resource use and other measures with
respect to certain domains not later than
the specified application date that
applies to each measure domain and
PAC provider setting. Section
1899B(a)(2)(E) of the Act delineates the
specified application dates for each
measure domain and PAC provider. The
IMPACT Act also amends other sections
of the Act, including section
1895(b)(3)(B)(v), to require the Secretary
to reduce the otherwise applicable PPS
payment to a PAC provider that does
not report the new data in a form and
manner, and at a time, specified by the
Secretary. For HHAs, amended section
1895(b)(3)(B)(v) of the Act will require
the Secretary to reduce the payment
update for any HHA that does not
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satisfactorily submit the newly required
data.
Under the current HH QRP, the
general timeline and sequencing of
measure implementation occurs as
follows: Specification of measures;
proposal and finalization of measures
through notice-and-comment
rulemaking; HHA submission of data on
the adopted measures; analysis and
processing of the submitted data;
notification to HHAs regarding their
quality reporting compliance for a
particular year; consideration of any
reconsideration requests; and
imposition of a payment reduction in a
particular year for failure to
satisfactorily submit data for that year.
Any payment reductions that are taken
for a year begin approximately 1 year
after the end of the data submission
period for that year and approximately
2 years after we first adopt the measure.
To the extent that the IMPACT Act
could be interpreted to shorten this
timeline, so as to require us to reduce
HH PPS payment for failure to
satisfactorily submit data on a measure
specified under section 1899B(c)(1) or
(d)(1) of the IMPACT Act beginning
with the same year as the specified
application date for that measure, such
a timeline would not be feasible. The
current timeline discussed above
reflects operational and other practical
constraints, including the time needed
to specify and adopt valid and reliable
measures, collect the data, and
determine whether a HHA has complied
with our quality reporting requirements.
It also takes into consideration our
desire to give HHAs enough notice of
new data reporting obligations so that
they are prepared to timely start
reporting data. Therefore, we intend to
follow the same timing and sequence of
events for measures specified under
sections 1899B(c)(1) and (d)(1) of the
Act that we currently follow for other
measures specified under the HH QRP.
We intend to specify each of these
measures no later than the specified
application dates set forth in section
1899B(a)(2)(E) of the Act and will adopt
them consistent with the requirements
in the Act and Administrative
Procedure Act. To the extent that we
finalize a proposal to adopt a measure
for the HH QRP that satisfies an
IMPACT Act measure domain, we
intend to require HHAs to report data on
the measure for the year that begins 2
years after the specified application date
for that measure. Likewise, we intend to
require HHAs to begin reporting any
other data specifically required under
the IMPACT Act for the year that begins
2 years after we adopt requirements that
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would govern the submission of that
data.
Lastly, on April 1, 2014, the Congress
passed the Protecting Access to
Medicare Act of 2014 (PAMA) (Pub. L.
113–93), which stated the Secretary may
not adopt ICD–10 prior to October 1,
2015. On August 4, 2014, HHS
published a final rule titled
‘‘Administrative Simplification: Change
to the Compliance Date for the
International Classification of Diseases,
10th Revision (ICD–10–CM and ICD–
10–PCS Medical Data Code Sets’’ (79 FR
45128), which announced October 1,
2015 as the new compliance date. The
OASIS–C1 data item set had been
previously approved by the Office of
Management and Budget (OMB) on
February 6, 2014 and scheduled for
implementation on October 1, 2014. We
intended to use the OASIS–C1 to
coincide with the original
implementation date of the ICD–10. The
approved OASIS–C1 included changes
to accommodate coding of diagnoses
using the ICD–10–CM coding set and
other important stakeholder concerns
such as updating clinical concepts, and
revised item wording and response
categories to improve item clarity. This
version included five (5) data items that
required the use of ICD–10 codes.
Since OASIS–C1 was revised to
incorporate ICD–10 coding, it was not
feasible to implement the OASIS–C1/
ICD–10 version prior to October 1, 2015,
when ICD–10 was scheduled to be
implemented. Due to this delay, we had
to ensure the collection and submission
of OASIS data continued, until ICD–10
was implemented. Therefore, we made
interim changes to the OASIS–C1 data
item set to allow use with ICD–9 until
ICD–10 was adopted. The OASIS–C1/
ICD–9 version was submitted to OMB
for approval until the OASIS–C1/ICD–
10 version could be implemented. A 6month emergency approval was granted
on October 7, 2014 and CMS
subsequently applied for an extension.
The extension of the OASIS–C1/ICD–9
version was reapproved under OMB
control number 0938–0760 with a
current expiration date of March 31,
2018. It is important to note, that this
version of the OASIS will be
discontinued once the OASIS–C1/ICD–
10 version is approved and
implemented. In addition, to facilitate
the reporting of OASIS data as it relates
to the implementation of ICD–10 on
October 1, 2015, we submitted a new
request for approval to OMB for the
OASIS–C1/ICD–10 version under the
Paperwork Reduction Act (PRA)
process. We requested a new OMB
control number for the proposed revised
OASIS item as announced in the 30-day
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Federal Register notice (80 FR 15796).
The new information collection request
for OASIS–C1/ICD–10 version was
approved under OMB control number
0938–1279 with a current expiration
date of May 31, 2018. Information
regarding the OASIS–C1 can be located
on the OASIS C–1 Data Sets Web page
at: https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
OASIS-C1.html. Additional information
regarding the adoption of ICD–10 can be
located on the ICD–10 Web page at:
https://www.cms.gov/Medicare/Coding/
ICD10/?redirect=/icd10.
We received multiple public
comments pertaining to the general
timeline and plan for implementation of
the IMPACT Act, sequencing of measure
implementation, and standardization of
PAC assessment tools. The following is
a summary of the comments we
received on this topic and our
responses.
Comment: We received several
comments requesting the development
of a comprehensive implementation
plan for all settings covered by the
IMPACT Act. Commenters stated that a
comprehensive implementation plan
would give home health providers an
opportunity to plan for the potential
impact on their operations, and enable
all stakeholders to understand CMS’s
approach to implementing the IMPACT
Act across care settings. Some
commenters requested that CMS plans
be communicated as soon as possible
and that CMS develop setting-specific
communications to facilitate
understanding of the IMPACT Act
requirements. Another commenter
urged CMS to provide clear and
transparent explanations of each
measure’s specifications, providing as
much information as possible to the
public about the measures proposed.
This commenter added that the detailed
information submitted for NQF
consensus development process would
be helpful to stakeholders, and offered
to work with CMS on measure
development and specifications. One
commenter specifically expressed the
importance of a transparent process in
relation to measure development, noting
that the Act calls for informing the
public of the measure’s numerator,
denominator, exclusions, and any other
aspects the Secretary determines
necessary. Another commenter
requested that CMS abide by certain
principles such as: Provide
implementation timelines for data
collection and reporting requirements in
a timely manner; implement measures
that are reliable, feasible and setting
appropriate that are endorsed as well as
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included in the pre-rulemaking Measure
Applications Partnership (MAP)
process; minimize unnecessary provider
burden; and finally that CMS ensure the
standardization of measures and data
collection across post-acute care settings
as feasible.
Response: We appreciate and agree
with the commenters’ requests for a
comprehensive and transparent plan for
implementation of the IMPACT Act, as
well as the need for timely stakeholder
input, the development of reliable,
accurate measures that are endorsed and
have undergone the pre-rulemaking
MAP process, clarity on the level of
standardization of items and measures,
the importance of feasibility and
standardization, and the avoidance of
unnecessary burden on PAC providers.
Our intent has been to comply with
these principles in the implementation
and rollout of QRPs in the various care
settings, and we will continue to adhere
to these principles as the agency moves
forward with implementing IMPACT
Act requirements.
In addition to implementing the
IMPACT Act requirements, we will
follow the strategy for identifying crosscutting measures, timelines for data
collection, and timelines for reporting as
outlined in the IMPACT Act. As
described more fully above, the
IMPACT Act requires CMS to specify
measures that relate to at least five
stated quality domains and three stated
resource use and other measure
domains. The IMPACT Act also outlines
timelines for data collection and
timelines for reporting. We intend to
adopt measures that comply with the
IMPACT Act in a manner that is
consistent with the sequence we follow
in other quality reporting programs. We
intend to follow all processes in place
for adoption of measures including the
MAP review and the notice and
comment rulemaking process. In the
selection and specification of measures,
we employ a transparent process in
which we seek input from stakeholders
and national experts and engage in a
process that allows for pre-rulemaking
input on each measure, as required by
section 1890A of the Act. This process
is based on a private-public partnership,
and it occurs via the MAP. The MAP is
composed of multi-stakeholder groups
convened by the NQF, our current
contractor under section 1890 of the
Act, to provide input on the selection of
quality and efficiency measures
described in section 1890(b)(7)(B). The
NQF must convene these stakeholders
and provide us with the stakeholders’
input on the selection of such measures.
We, in turn, must take this input into
consideration in selecting such
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measures. In addition, the Secretary
must make available to the public by
December 1 of each year a list of such
measures that the Secretary is
considering under Title XVIII of the Act.
Additionally, proposed measures and
specifications are to be announced
through the Notice of Proposed
Rulemaking (NPRM) process in which
proposed rules are published in the
Federal Register and are available for
public view and comment.
We further note that we are
committed to the principles
surrounding public input as part of its
measure development that occurs prior
to rule making. As part of this measure
development process, we seek input
from the public on the measure
specifications under development by
CMS and our measure contractors. We
have a designated Web page where we
solicit public comment on measure
constructs during measure
development. This is a key component
to how we develop and maintain quality
measures, as outlined in the CMS
Blueprint for Measures Management
System. You can find more information
about the CMS Blueprint for Measures
Management System on the CMS
Measure Management System Web page
at: https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/MMS/. The CMS
Quality Measures Public Comment page
is located at: https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/MMS/
CallforPublicComment.html.
Comment: Several commenters
requested that CMS continue in its
public engagement with stakeholders.
They stated their appreciation for the
opportunity to work with CMS during
the implementation phases of the
IMPACT Act. These commenters noted
a need for more opportunities for
stakeholder input into various aspects of
the measure and assessment instrument
development process. Commenters
requested opportunities to provide
ongoing input into measure and
assessment instrument development
and modifications.
Response: We appreciate the
commenters’ feedback and the
continued involvement of stakeholders
in all phases of measure development
and implementation, as we see the value
in strong public-private partnerships.
We also believe that ongoing
stakeholder input is important to the
success of the IMPACT Act and look
forward to continued and regular input
from the provider communities as we
continue to implement the IMPACT Act.
It is our intent to move forward with
IMPACT Act implementation in a
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manner in which the measure and
assessment instrument development
process continues to be transparent, and
includes input and collaboration from
experts, the PAC provider community,
and the public. It is of the utmost
importance to CMS to continue to
engage stakeholders, including patients
and their families, throughout the
measure and assessment instrument
development lifecycle through our
measure development public comment
periods, the pre-rulemaking activities,
participation in the Technical Expert
Panels (TEPs) convened by our measure
development contractors, as well as
open door forums, and other
opportunities. We have already
provided multiple opportunities for
stakeholder input, including the
following activities: Our measure
development contractor(s) convened
TEPs for many of the measures in
development under the IMPACT Act
such as the functional assessment TEP,
Discharge to Community TEP,
Potentially Preventable Readmissions
TEP, and the Drug Regimen Review
TEP. We intend to continue this form of
stakeholder engagement with future
TEPs that will assess data
standardization and Medicare Spending
per Beneficiary measure concepts,
among other topics. We also convened
two separate listening sessions on
February 10, 2015 and March 24, 2015
in order to receive stakeholder input on
IMPACT Act implementation. In
addition, we heard stakeholder input
during the February 9, 2015 ad hoc
MAP meeting provided for the sole
purpose of reviewing the measures
proposed in response to the IMPACT
Act. We also implemented a public mail
box for the submission of comments in
January 2015, PACQualityInitiative@
cms.hhs.gov, which is listed on our
IMPACT Act of 2014 & Cross-Setting
Measures Web site at: https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014-andCross-Setting-Measures.html, and we
held a Special Open Door Forum to seek
input on the measures on February 25,
2015. The slides from the Special Open
Door Forum are available https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014-andCross-Setting-Measures.html.
Comment: We received several
comments requesting that CMS ensure
that the data used to satisfy the IMPACT
Act measure domains be aligned across
PAC settings to maximize the reliability
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and validity of such data and to enable
data comparability. Commenters noted
the importance of standardized patient
assessment data for cross-setting
comparisons of patient outcomes.
Another commenter expressed concern
about the level of standardization of
data collection instruments across PAC
settings, specifically the importance of
assessment item alignment for items
selected for use in the various PAC
settings, and urged CMS to consider
such data alignment issues. One
commenter recommended CMS move as
quickly as possible to collect
interoperable and standardized data,
and one commenter recommended that
CMS conduct testing to evaluate
comparability across settings. One
commenter expressed concern related to
the inconsistencies in the measures
proposed, suggesting that there was
significant variance in relation to their
numerator, denominator and exclusions.
We received a few comments
requesting details pertaining to the
timing of the development and
implementation of the standardized
patient assessment data, measures, data
collection, and reporting. Commenters
requested a detailed timeline and
schedule that specifies planned changes
to standardize assessment data,
including dates and sequencing of
changes. Specifically, one commenter
stated that although the sequencing for
the quality measures and specified
application dates were provided in the
proposed rule, the detail related to the
timing of the standardized data
appeared to have been left out. The
commenter requested that this final rule
provide such timeline and sequencing.
Response: We agree that
standardization is important for data
comparability and outcome analysis. We
will work to ensure that items
pertaining to measures required under
the IMPACT Act that are included in
assessment instruments are
standardized and aligned across the
assessment instruments. In addition, we
will ensure that the data used to satisfy
the IMPACT Act measure domains will
be aligned across PAC settings to
maximize the reliability and validity of
such data and to enable data
comparability. We recognize the need
for transparency as we move forward to
implement the IMPACT Act and we
intend to continue to engage
stakeholders and ensure that our
approach to implementation and timing
is communicated in an open and
informative manner. We will continue
this communication through various
means, such as open door forums,
national provider calls, email blasts, and
announcements. We intend to provide
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ongoing information pertaining to the
implementation and development of
standardized patient assessment data,
measures, data collection, and reporting
to the public. We will also continue to
provide information about development
and implementation of the IMPACT Act
on the IMPACT Act of 2014 & CrossSetting Measures Web page at: https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014-andCross-Setting-Measures.html. In
addition to the Web site updates and
provider calls, we intend to provide
information about development and
implementation through pre-rulemaking
activities surrounding the development
of quality measures, which includes
public input as part of our process. We
intend to engage stakeholders and
experts in developing the assessment
instrument modifications necessary to
meet data standardization requirements
of the IMPACT Act. We also will use the
rulemaking process to communicate
timelines for implementation, including
timelines for the replacement of items in
PAC assessment tools, timelines for
implementation of new or revised
quality measures, and timelines for
public reporting.
Regarding the timeline and
sequencing surrounding the
standardized patient assessment data,
we interpret the commenters’ concern to
refer to the standardized data
assessment domains listed within the
Act under section 2(b) ‘‘Standardized
patient assessment data’’. As stated in
the preamble to the CY 2016 HH PPS
proposed rule, we intend to require
HHAs to begin reporting data on the
quality measures required under the
IMPACT Act for the year that begins 2
years after we adopt requirements that
govern the submission of that data.
Comment: We received a few
comments supporting and encouraging
the use of NQF-endorsed measures and
recommending that measures be NQFendorsed prior to implementation.
Specifically, commenters urged CMS to
seek and receive NQF endorsement for
measures in each PAC setting, noting
that quality measure endorsement in
one setting, such as a skilled nursing
facility, may not mean a measure is
appropriate, reliable, or valid for use in
the home health setting.
Response: We will propose
appropriate measures that meet the
requirements of the IMPACT Act
measure domains and that have been
endorsed or adopted by a consensus
organization whenever possible.
However, when this is not feasible
because there is no NQF-endorsed
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measure that meets all the requirements
for a specified IMPACT Act measure
domain, we intend to rely on the
exception authority given to the
Secretary in section 1899B(e)(2)(B) of
the Act. This statutory exception allows
the Secretary to specify a measure for
the HH QRP setting that is not NQFendorsed where, as here, we have not
been able to identify other measures on
the topic that are endorsed or adopted
by a consensus organization. For all
quality measures for the HH QRP, we
seek MAP review, as well as expert
opinion on the validity and reliability of
those measures in the HH setting. For
the proposed quality measure, the
Percent of Residents/Patients/Persons
with Pressure Ulcers That Are New or
Worsened, the MAP PAC LTC Off-Cycle
Workgroup conditionally supported the
quality measure for HH QRP. We wish
to note that we intend to seek consensus
endorsement for the IMPACT Act
measures in each PAC setting.
Comment: We received several
comments about the burden on PAC
providers of meeting new requirements
imposed as a result of the
implementation of the IMPACT Act.
Specifically, commenters requested that
CMS consider minimizing the burden
for PAC providers when possible and
avoiding duplication in data collection.
Response: We appreciate the
importance of avoiding undue burden
and will continue to evaluate and
consider any burden the IMPACT Act
and the HH QRP places on home health
providers. In implementing the IMPACT
Act thus far, we have taken into
consideration any new burden that our
requirements might place on PAC
providers. In this respect, we note that
many assessment items used to
calculate the measure proposed for use
in the HH QRP, the Percent of Residents
or Patients with Pressure Ulcers That
Are New or Worsened are currently
being collected in the OASIS
instrument.
Comment: We received one comment
requesting that, in the future, crosssetting measures and assessment data
changes related to the IMPACT Act be
addressed in one stand-alone notice and
rule that applies to all four post-acute
care settings.
Response: We will take this request
under consideration.
Comment: We received one comment
expressing interest in learning about any
proposed changes to the OASIS
assessment instrument in the next
version of the item set and when these
changes might occur.
Response: We are committed to
transparent communication about
updates to the PAC assessment
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instruments required to support the
IMPACT Act measures, as well as any
new measures for the HH QRP. We wish
to clarify that the draft revisions to the
integumentary portion of the OASIS
were posted along with the proposed
rule on the Home Health Quality
Measures Web page at: https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html. We intend
to make publically available the final
item set with its revisions as well as the
submission specifications in a manner
consistent with our previous postings of
such information in the coming months.
Comment: We received one comment
expressing concern that data used in
reformulating the payment model and
assessing quality in PAC settings be
gathered by qualified clinicians.
Specifically, the commenter emphasized
the unique contributions of
occupational therapists to support the
intent of the IMPACT Act.
Response: We appreciate the feedback
and concur on the important role played
by qualified clinicians in collecting the
data needed to support the requirements
of the IMPACT Act.
Comment: One commenter
recommended that CMS invest in
training clinicians for any new data
collection requirements that address the
quality measures, the assessment items,
and how the measures and the items are
developed to meet the mandate of the
IMPACT Act objectives. This
commenter additionally noted that the
training should address different
settings of care and how patient
populations differ across PAC settings,
to support consistency in data
collection.
Response: We agree that training is
critical to assure both provider accuracy
and understanding of the assessment
and data collection requirements. We
intend to provide training on updates to
the OASIS assessment instrument as
suggested, and intend to ensure that
such training includes the information
necessary to ensure consistent data
collection.
Comment: One commenter
underscored cognitive function as an
important aspect of the IMPACT Act,
because of its significant relationship to
Medicare resource use, length of stay,
and patients’ long term outcomes. The
commenter recommended that
assessment of functional cognition be
incorporated as part of CMS’s efforts to
meet the requirements of the IMPACT
Act and added that providers need more
training around appropriate functional
activities for patients with cognitive
impairments. This commenter also
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offered to provide research studies and
related materials to support CMS in this
area.
Response: We concur on the
importance of cognitive function and its
relationship to quality outcomes for
PAC patients. We are working toward
developing quality measures that assess
areas of cognition, recognizing that this
quality topic is intrinsically linked to
the function domain. We appreciate the
commenter’s offer of assistance and
encourage the submission of comments
and measure specification details to our
comment email PACQualityInitiative@
cms.hhs.gov.
Comment: One commenter supported
the inclusion of new standardized selfcare and mobility functional items in
PAC assessment tools that utilize the
data source of the CARE Tool. The
commenter anticipated that functional
measures based on CARE items that are
being implemented in other PAC
settings will be eventually added to the
HH QRP. This commenter noted that
use of these new items would facilitate
accurate representation of patient
function across the spectrum of PAC
settings.
Response: We appreciate the
commenter’s feedback and support of
the self-care and functional items that
utilize data elements derived from the
CARE Tool item set source. We believe
that standardization of assessment items
and measures, such as measures of
functional status, across post-acute care
settings is an important goal.
Comment: One commenter expressed
concern regarding harmonization of
measures across settings and outcomes
measurement when multiple
populations are included. This
commenter urged that proposed
IMPACT Act measures be limited to
Medicare FFS beneficiaries, noting that
to include other populations (Medicaid,
Medicare Advantage, and MCO
Medicaid) will complicate the
interpretation of outcome results. The
commenter expressed support of the
construct of the Total Cost per
Beneficiary. The commenter also
suggested that a measure such as the
Percent of Patients Discharged to a
Higher Level of Care versus Community,
which the commenter suggested could
be used across all patients receiving
home care, be included in future
measure development. In addition, the
commenter expressed support for
measures related to falls and nutritional
assessment, and hospitalizations, but
requested clarification about the
population that would be measured and
recommended that all of these measures
be limited to Medicare FFS patients
only. The commenter additionally
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recommended that the uniqueness of
home health care be considered when
developing a standardized falls
measure, noting that home health staff
are not present 24 hours a day, seven
days a week and are reliant on patients
and caregivers in reporting and
preventing falls.
Response: We appreciate the
commenter’s feedback about
comparison of outcomes across different
payer populations and appreciate the
commenter’s support for quality
measure standardization as mandated
by the IMPACT Act. The cross-setting
measures: (1) Payment Standardized
Medicare Spending Per Beneficiary
(MSPB), (2) Percentage residents/
patients at discharge assessment, who
discharged to a higher level of care
versus to the community, (Application
of NQF #2510), (3) Skilled Nursing
Facility 30-Day All-Cause Readmission
Measure (SNFRM), and (4) Application
of the LTCH/IRF All-Cause Unplanned
Readmission Measure for 30 Days Post
Discharge from LTCHs/IRFs are
currently under development for all four
PAC settings. These quality measures
are being developed using Medicare
claims data, thus the denominators for
these measure constructs are limited to
the Medicare FFS population. We
intend to standardize denominator and
numerator definitions across PAC
settings in order to standardize quality
measures as required by the IMPACT
Act.
We acknowledge the unique
constraints home health agencies face in
monitoring patient falls. We are in the
process of standardizing a quality
measure that assesses one or more falls
with a major injury, rather than just a
measure assessing if a fall occurred. In
the FY 2016 IPPS/LTCH PPS final rule,
FY 2016 IRF PPS final rule and FY 2016
SNF PPS final rule, we finalized an
application of the quality measure, the
Percent of Residents Experiencing One
or More Falls with Major Injury (Long
Stay) measure (NQF #0674). This
application of the quality measure
assesses falls resulting in major injuries
only, satisfying the domain in the
IMPACT Act, the Incidence of Major
Falls. A TEP convened by our measure
development contractor provided input
on the technical specifications of the
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, including home
health care. The TEP was supportive of
the implementation of this measure
across PAC settings and was also
supportive of our efforts to standardize
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this measure for cross-setting
development. We have taken steps to
standardize the numerator,
denominator, and other facets of the
quality measure across all PAC settings.
As part of best clinical practice, the
HHA should take steps to mitigate falls
with major injury, especially since such
falls are considered to be ‘‘never events’’
as they relate to healthcare acquired
conditions.
Finally, we appreciate the
commenter’s concern that home health
staff are not present 24 hours, 7 days a
week and may not be able to track falls
as they occur.
B. General Considerations Used for the
Selection of Quality Measures for the
HH QRP
We strive to promote high quality and
efficiency in the delivery of health care
to the beneficiaries we serve.
Performance improvement leading to
the highest quality health care requires
continuous evaluation to identify and
address performance gaps and reduce
the unintended consequences that may
arise in treating a large, vulnerable, and
aging population. Quality reporting
programs, coupled with public reporting
of quality information, are critical to the
advancement of health care quality
improvement efforts.
We seek to adopt measures for the HH
QRP that promote better, safer, and
more efficient care. Valid, reliable,
relevant quality measures are
fundamental to the effectiveness of our
quality reporting programs. Therefore,
selection of quality measures is a
priority for CMS in all of its quality
reporting programs.
The measures selected will address
the measure domains as specified in the
IMPACT Act and align with the CMS
Quality Strategy, which is framed using
the three broad aims of the National
Quality Strategy:
• Better Care: Improve the overall
quality of care by making healthcare
more patient-centered, reliable,
accessible, and safe.
• Healthy People, Healthy
Communities: Improve the health of the
U.S. population by supporting proven
interventions to address behavioral,
social, and environmental determinants
of health in addition to delivering
higher-quality care.
• Affordable Care: Reduce the cost of
quality healthcare for individuals,
families, employers, and government.
In addition, our measure selection
activities for the HH QRP take into
consideration input we receive from the
MAP. Input from the MAP is located on
the MAP PAC LTC Programmatic
Deliverable—Final Report Web page at:
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https://www.qualityforum.org/
Publications/2015/02/MAP_PAC-LTC_
Programmatic_Deliverable_-_Final_
Report.aspx. We also take into account
national priorities, such as those
established by the National Priorities
Partnership at https://
www.qualityforum.org/npp/, and the
HHS Strategic Plan at: https://
www.hhs.gov/secretary/about/priorities/
priorities.html.
We initiated an Ad Hoc MAP process
for the review of the measures under
consideration for implementation in
preparation of the measures for
adoption into the HH QRP that we
proposed through this fiscal year’s rule,
in order to begin implementing such
measures by 2017. We included under
the List of Measures under
Consideration (MUC List) measures that
the Secretary must make available to the
public, as part of the pre-rulemaking
process, as described in section
1890A(a)(2) of the Act. The MAP OffCycle Measures under Consideration for
PAC–LTC Settings can be accessed on
the National Quality Forum Web site at:
https://www.qualityforum.org/
Publications/2015/03/MAP_Off-Cycle_
Deliberations_2015_-_Final_
Report.aspx. The NQF MAP met in
February 2015 and provided input to us
as required under section 1890A(a)(3) of
the Act. The MAP issued a prerulemaking report on March 6, 2015
entitled MAP Off-Cycle Deliberations
2015: Measures under Consideration to
Implement Provisions of the IMPACT
Act—Final Report, which is available
for download at: https://
www.qualityforum.org/Publications/
2015/03/MAP_Off-Cycle_Deliberations_
2015_-_Final_Report.aspx. The MAP’s
input for the proposed measure is
discussed in this section.
To meet the first specified application
date applicable to HHAs under section
1899B(a)(2)(E) of the Act, which is
January 1, 2017, we focused on
measures that:
• Correspond to a measure domain in
sections 1899B(c)(1) or (d)(1) of the Act
and are setting-agnostic: For example
falls with major injury and the
incidence of pressure ulcers;
• Are currently adopted for 1 or more
of our PAC quality reporting programs,
are already either NQF-endorsed and in
use or finalized for use, or already
previewed by the Measure Applications
Partnership (MAP) with support;
• Minimize added burden on HHAs;
• Minimize or avoid, to the extent
feasible, revisions to the existing items
in assessment tools currently in use (for
example, the OASIS); and
• Where possible, avoid duplication
of existing assessment items.
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As discussed in section V.A. of this
final rule, section 1899B(j) of the Act
requires that we allow for stakeholder
input, such as through town halls, open
door forums, and mailbox submissions,
before the initial rulemaking process to
implement section 1899B. To meet this
requirement, we provided the following
opportunities for stakeholder input: (1)
We convened a Technical Expert Panel
(TEP) that included stakeholder experts
and patient representatives on February
3, 2015; (2) we provided two separate
listening sessions on February 10 and
March 24, 2015; (3) we sought public
input during the February 2015 ad hoc
MAP process regarding the measures
under consideration for IMPACT Act
domains; (4) we sought public comment
as part of our measure maintenance
work; and (5) we implemented a public
mail box for the submission of
comments in January 2015 located at
PACQualityInitiative@cms.hhs.gov. The
CMS public mailbox can be accessed on
our IMPACT Act of 2014 & Cross-Setting
Measures Web page at: https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Post-Acute-Care-QualityInitiatives/IMPACT-Act-of-2014-andCross-Setting-Measures.html. Lastly, we
held a National Stakeholder Special
Open Door Forum to seek input on the
measures on February 25, 2015.
In the absence of NQF endorsement
on measures for the home health (HH)
setting, or measures that are not fully
supported by the MAP for the HH QRP,
we intend to propose for adoption
measures that most closely align with
the national priorities discussed above
and for which the MAP supports the
measure concept. Further discussion as
to the importance and high-priority
status of these measures in the HH
setting is included under each quality
measure in this final rule. In addition,
for measures not endorsed by the NQF,
we have sought, to the extent
practicable, to adopt measures that have
been endorsed or adopted by a national
consensus organization, recommended
by multi-stakeholder organizations, and/
or developed with the input of
providers, purchasers/payers, and other
stakeholders.
C. HH QRP Quality Measures and
Measures Under Consideration for
Future Years
In the CY 2014 HH PPS final rule, (78
FR 72256–72320), we finalized a
proposal to add two claims-based
measures to the HH QRP, and stated that
we would begin reporting the data from
these measures to HHAs beginning in
CY 2014. These claims based measures
are: (1) Rehospitalization during the first
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30 days of HH; and (2) Emergency
Department Use without Hospital
Readmission during the first 30 days of
HH. In an effort to align with other
updates to Home Health Compare,
including the transition to quarterly
provider preview reports, we made the
decision to delay the reporting of data
from these measures until July 2015
(https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQISpotlight.html). Also in that rule,
we finalized our proposal to reduce the
number of process measures reported on
the Certification and Survey Provider
Enhanced Reporting (CASPER) reports
by eliminating the stratification by
episode length for nine (9) process
measures. The removal of these
measures from the CASPER folders
occurred in October 2014. The CMS
Home Health Quality Initiative Web site
identifies the current HH QRP measures
located on the Quality Measures Web
page at: https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html. In
addition, as stated in the CY 2012 and
CY 2013 HH PPS final rules (76 FR
68575 and 77 FR 67093, respectively),
we finalized that we will also use
measures derived from Medicare claims
data to measure home health quality.
This effort ensures that providers do not
have an additional burden of reporting
quality of care measures through a
separate mechanism, and that the costs
associated with the development and
testing of a new reporting mechanism
are avoided.
(a) We proposed one standardized
cross-setting new measure for CY 2016
to meet the requirements of the IMPACT
Act. The proposed quality measure
addressing the domain of skin integrity
and changes in skin integrity is the
National Quality Forum (NQF)-endorsed
measure: Percent of Residents or
Patients with Pressure Ulcers That Are
New or Worsened (Short Stay) (NQF
#0678) (https://www.qualityforum.org/
QPS/0678).
The IMPACT Act requires the
specification of a quality measure to
address skin integrity and changes in
skin integrity in the home health setting
by January 1, 2017. We proposed the
implementation of quality measure NQF
#0678, Percent of Residents or Patients
with Pressure Ulcers that are New or
Worsened (Short Stay) in the HH QRP
as a cross-setting quality measure to
meet the requirements of the IMPACT
Act for the CY 2018 payment
determination and subsequent years.
This measure reports the percent of
patients with Stage 2 through 4 pressure
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ulcers that are new or worsened since
the beginning of the episode of care.
Pressure ulcers are high-volume in
post-acute care settings and high-cost
adverse events. According to the 2014
Prevention and Treatment Guidelines
published by the National Pressure
Ulcer Advisory Panel, European
Pressure Ulcer Advisory Panel, and Pan
Pacific Pressure Injury Alliance,
pressure ulcer care is estimated to cost
approximately $11 billion annually, and
between $500 and $70,000 per
individual pressure ulcer.56 Pressure
ulcers are a serious medical condition
that result in pain, decreased quality of
life, and increased mortality in aging
populations.57 58 59 60 Pressure ulcers
typically are the result of prolonged
periods of uninterrupted pressure on the
skin, soft tissue, muscle, and bone.61 62 63
Elderly individuals are prone to a wide
range of medical conditions that
increase their risk of developing
pressure ulcers. These include impaired
mobility or sensation, malnutrition or
undernutrition, obesity, stroke, diabetes,
dementia, cognitive impairments,
circulatory diseases, dehydration, bowel
or bladder incontinence, the use of
wheelchairs, the use of medical devices,
polypharmacy, and a history of pressure
ulcers or a pressure ulcer at
admission.64 65 66 67 68 69 70 71 72 73 74
56 National Pressure Ulcer Advisory Panel,
European Pressure Ulcer Advisory Panel and Pan
Pacific Pressure Injury Alliance. Prevention and
Treatment of Pressure Ulcers: Clinical Practice
Guideline. Emily Haesler (Ed.) Cambridge Media;
Osborne Park, Western Australia; 2014.
57 Casey, G. (2013). ‘‘Pressure ulcers reflect
quality of nursing care.’’ Nurs N Z 19(10): 20–24.
58 Gorzoni, M. L., and S. L. Pires (2011). ‘‘Deaths
in nursing homes.’’ Rev Assoc Med Bras 57(3): 327–
331.
59 Thomas, 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.
60 White-Chu, E. F., et al. (2011). ‘‘Pressure ulcers
in long-term care.’’ Clin Geriatr Med 27(2): 241–258.
61 Bates-Jensen BM. Quality indicators for
prevention and management of pressure ulcers in
vulnerable elders. Ann Int Med. 2001;135 (8 Part 2),
744–51.
62 Institute for Healthcare Improvement (IHI).
Relieve the pressure and reduce harm. May 21,
2007. Available from https://www.ihi.org/IHI/
Topics/PatientSafety/SafetyGeneral/
ImprovementStories/
FSRelievethePressureandReduceHarm.htm.
63 Russo CA, Steiner C, Spector W.
Hospitalizations related to pressure ulcers among
adults 18 years and older, 2006 (Healthcare Cost
and Utilization Project Statistical Brief No. 64).
December 2008. Available from https://
www.hcupus.ahrq.gov/reports/statbriefs/sb64.pdf.
64 Agency for Healthcare Research and Quality
(AHRQ). Agency news and notes: pressure ulcers
are increasing among hospital patients. January
2009. Available from https://www.ahrq.gov/
research/jan09/0109RA22.htm.=
65 Bates-Jensen BM. Quality indicators for
prevention and management of pressure ulcers in
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The IMPACT Act requires the
specification of quality measures that
are harmonized across PAC settings.
This requirement is consistent with the
NQF Steering Committee report, which
stated that to understand the impact of
pressure ulcers across settings, quality
measures addressing prevention,
incidence, and prevalence of pressure
ulcers must be harmonized and
aligned.75 NQF #0678, Percent of
Residents or Patients with Pressure
Ulcers That Are New or Worsened
(Short Stay) is NQF-endorsed and has
been successfully implemented using a
harmonized set of data elements in IRF,
LTCH, and SNF settings. A new item,
M1309 was previously added to the
OASIS–C1/ICD–9 version to collect data
on new and worsened pressure ulcers in
home health patients to support
harmonization with NQF #0678 and
data collection for this item began
January 1, 2015. A new measure, based
on this item, was included in the 2014
MUC list and received conditional
endorsement from the National Quality
Forum. That measure was harmonized
with NQF #0678, but differed in the
consideration of unstageable pressure
ulcers. In this rule, we proposed a HH
vulnerable elders. Ann Int Med. 2001;135 (8 Part 2),
744–51.
66 Cai, S., et al. (2013). ‘‘Obesity and pressure
ulcers among nursing home residents.’’ Med Care
51(6): 478–486.
67 Casey, G. (2013). ‘‘Pressure ulcers reflect
quality of nursing care.’’ Nurs N Z 19(10): 20–24.
68 Hurd D, Moore T, Radley D, Williams C.
Pressure ulcer prevalence and incidence across
post-acute care settings. Home Health Quality
Measures & Data Analysis Project, Report of
Findings, prepared for CMS/OCSQ, Baltimore, MD,
under Contract No. 500–2005–000181 TO 0002.
2010.
69 MacLean DS. Preventing & managing pressure
sores. Caring for the Ages. March 2003;4(3):34–7.
Available from https://www.amda.com/publications/
caring/march2003/policies.cfm.
70 Michel, J. M., et al. (2012). ‘‘As of 2012, what
are the key predictive risk factors for pressure
ulcers? Developing French guidelines for clinical
practice.’’ Ann Phys Rehabil Med 55(7): 454–465
71 National Pressure Ulcer Advisory Panel
(NPUAP) Board of Directors; Cuddigan J, Berlowitz
DR, Ayello EA (Eds). Pressure ulcers in America:
prevalence, incidence, and implications for the
future. An executive summary of the National
Pressure Ulcer Advisory Panel Monograph. Adv
Skin Wound Care. 2001;14(4):208–15
72 Park-Lee E, Caffrey C. Pressure ulcers among
nursing home residents: United States, 2004 (NCHS
Data Brief No. 14). Hyattsville, MD: National Center
for Health Statistics, 2009. Available from https://
www.cdc.gov/nchs/data/databriefs/db14.htm.
73 Reddy, M. (2011). ‘‘Pressure ulcers.’’ Clin Evid
(Online) 2011.
74 Teno, J. M., et al. (2012). ‘‘Feeding tubes and
the prevention or healing of pressure ulcers.’’ Arch
Intern Med 172(9): 697–701.
75 National Quality Forum. National voluntary
consensus standards for developing a framework for
measuring quality for prevention and management
of pressure ulcers. April 2008. Available from
https://www.qualityforum.org/Projects/Pressure_
Ulcers.aspx.
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measure that is fully-standardized with
NQF #0678.
A TEP convened by our measure
development contractor provided input
on the technical specifications of this
quality measure, including the
feasibility of implementing the measure
across PAC settings. The TEP was
supportive of the implementation of this
measure across PAC settings and
supported CMS’s efforts to standardize
this measure for cross-setting
development. Additionally, the NQF
MAP met on February 9, 2015 and
February 27, 2015 and provided input to
CMS. The MAP supported the use of
NQF #0678, Percent of Residents or
Patients with Pressure Ulcers that are
New or Worsened (Short Stay) in the
HH QRP as a cross-setting quality
measure implemented under the
IMPACT Act. More information about
the MAPs recommendations for this
measure on the National Quality Forum
Web site at: https://
www.qualityforum.org/Publications/
2015/02/MAP_PAC-LTC_Programmatic_
Deliverable_-_Final_Report.aspx.
We proposed that data for the
standardized quality measure would be
collected using the OASIS–C1 with
submission through the Quality
Improvement and Evaluation System
(QIES) Assessment Submission and
Processing (ASAP) system. HHAs began
submitting data for the OASIS items
used to calculate NQF #0678, the
Percent of Residents or Patients with
Pressure Ulcers That Are New or
Worsened (Short Stay), as part of the
Home Health Quality Initiative to assess
the number of new or worsened
pressure ulcers in January 2015. By
building on the existing reporting and
submission infrastructure for HHAs, we
intend to minimize the administrative
burden related to data collection and
submission for this measure under the
HH QRP. For more information on HH
reporting using the QIES ASAP system,
refer to OASIS User Manual Web page
at: https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIOASISUserManual.html and
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/OASIS/
index.html?redirect=/oasis/.
Data collected through the OASIS–C1
would be used to calculate this quality
measure. Data items in the OASIS–C1
include M1308 (Current Number of
Unhealed Pressure Ulcers at Each Stage
or Unstageable) and M1309 (Worsening
in Pressure Ulcer Status Since SOC/
ROC). Data collected through the
OASIS–C1 would be used for risk
adjustment of this measure. We
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anticipate risk adjustment items will
include, but not be limited to M1850
(Activities of Daily Living Assistance,
Transferring), and M1620 (Bowel
Incontinence Frequency). OASIS C1
items M1016 (Diagnoses Requiring
Medical or Treatment Change Within
past 14 Days), M1020 (Primary
Diagnoses) and M1022 (Other
Diagnoses) would be used to identify
patients with a diagnosis of peripheral
vascular disease, diabetes, or
malnutrition. More information about
the OASIS items is available in the
downloads section of the Home Health
Quality Measures Web page at: https://
www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
The specifications and data items for
NQF #0678, the Percent of Residents or
Patients with Pressure Ulcers that are
New or Worsened (Short Stay), are
available in the downloads section of
the Home Health Quality Measures Web
page at: https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
As part of our ongoing measure
development efforts, we considered a
future update to the numerator of the
quality measure NQF #0678, Percent of
Residents or Patients with Pressure
Ulcers that are New or Worsened (Short
Stay). This update would hold providers
accountable for the development of
unstageable pressure ulcers and
suspected deep tissue injuries (sDTIs).
Under this proposed change the
numerator of the quality measure would
be updated to include unstageable
pressure ulcers, including sDTIs that are
new/developed while the patient is
receiving home health care, as well as
Stage 1 or 2 pressure ulcers that become
unstageable due to slough or eschar
(indicating progression to a full
thickness [that is, stage 3 or 4] pressure
ulcer) after admission. This would be
consistent with the specifications of the
‘‘New and Worsened Pressure Ulcer’’
measure for HH patients presented to
the MAP on the 2014 MUC list. We did
not propose the implementation of this
change (that is, including sDTIs and
unstageable pressure ulcers in the
numerator) in the HH QRP, but solicited
public feedback on this potential area of
measure development.
Our measure development contractor
convened a cross-setting pressure ulcer
TEP that strongly recommended that
CMS hold providers accountable for the
development of new unstageable
pressure ulcers and sDTIs by including
these pressure ulcers in the numerator
of the quality measure. Although the
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TEP acknowledged that unstageable
pressure ulcers and sDTIs cannot and
should not be assigned a numeric stage,
panel members recommended that these
be included in the numerator of NQF
#0678, the Percent of Residents, or
Patients with Pressure Ulcers That Are
New or Worsened (Short Stay), as a new
pressure ulcer if developed during a
home health episode. The TEP also
recommended that a Stage 1 or 2
pressure ulcer that becomes unstageable
due to slough or eschar should be
considered worsened because the
presence of slough or eschar indicates a
full thickness (equivalent to Stage 3 or
4) wound.76 77 These recommendations
were supported by technical and
clinical advisors and the National
Pressure Ulcer Advisory Panel.78
Additionally, exploratory data analysis
conducted by our measure development
contractor suggested that the addition of
unstageable pressure ulcers, including
sDTIs, would increase the observed
incidence of new or worsened pressure
ulcers at the agency level and may
improve the ability of the quality
measure to discriminate between poorand high-performing facilities.
In addition, we also considered
whether body mass index (BMI) should
be used as a covariate for risk-adjusting
NQF #0678 in the home health setting,
as is done in other post-acute care
settings. We invited public feedback to
inform our direction to include
unstageable pressure ulcers and sDTIs
in the numerator of the quality measure
NQF #0678 Percent of Residents or
76 Schwartz, 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.
77 Schwartz, 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.
78 Schwartz, 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.
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Patients with Pressure Ulcers that are
New or Worsened (Short Stay), as well
as on the possible collection of height
and weight data for risk-adjustment, as
part of our future measure development
efforts.
We invited public comment on our
proposal to adopt NQF #0678 Percent of
Residents or Patients with Pressure
Ulcers that are New or Worsened (Short
Stay) for the HH QRP to fulfill the
requirements of the IMPACT Act for CY
2018 HH payment determination and
subsequent years. The following is a
summary of the comments received and
our responses.
Comment: The majority of
commenters supported the addition of
the proposed quality measure, the
Percent of Residents or Patients with
Pressure Ulcers That Are New or
Worsened (NQF #0678) to the Home
Health Quality Reporting Program.
Commenters appreciated that CMS
chose a measure that uses data home
health agencies already collect.
Response: We appreciate the
commenters’ support for implementing
the proposed quality measure, the
Percent of Residents or Patients with
Pressure Ulcers That Are New or
Worsened (NQF #0678).
Comment: A few commenters raised
concerns about the fairness of using
NQF #0678 to compare performance
within home health and across PAC
providers. One commenter noted that
pressure ulcer improvement is
challenging to measure in limited
timeframes and disadvantages providers
serving frailer populations and
requested CMS consider risk adjustment
based on sociodemographic, diagnostic,
and care coordination factors.
Commenters also recommended that
CMS take into account the discrepancy
in the control providers have over
patient care in home health, relative to
institutional settings. Another
commenter additionally raised concerns
about the reliability of the
implementation of the Wound, Ostomy,
and Continence Nurses (WOCN) Society
guidelines used in staging pressure
ulcers, and the lack of information about
the status of the wound beyond staging
while the patient is in the care of the
provider. In addition, one commenter
recommended that CMS conduct
ongoing evaluation of the risk
adjustment methodology for this
proposed quality measure.
Response: We appreciate the
commenters’ concerns about ensuring
fair comparisons within and across PAC
settings. We also appreciate that such
comparisons take into account the
discrepancy in the control providers
have over patient care in home health,
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relative to institutional settings. We are
committed to developing risk models
that take into account differences in
patient characteristics, including
chronic conditions and frailty. We
believe that as with provider services
within institutional settings, home
health agencies aim to provide high
quality care and therefore assess for and
put into place care planning and
services that mitigate poor quality
outcomes. However, we will also take
into account potential variation that
may exist in relation to home based
services as opposed to institutional
services. Therefore, as part of measure
maintenance, we intend to continue to
evaluate for risk factors associated with
pressure ulcers including those unique
to the individuals receiving home health
services. We intend to provide specific
guidance through the OASIS manual
and provider trainings to support
clinicians in appropriately coding the
stages of the pressure ulcers. In
addition, we plan to conduct field
testing on all the new and revised
OASIS items that support the IMPACT
Act measures, to assess inter-rater
reliability and to further refine guidance
and training.
This proposed quality measure
underwent recent review as part of its
measure maintenance by CMS’s
measure development contractor. Under
Technical Expert Panel review, which
included national experts and members
of a various professional wound
organizations such as the National
Pressure Ulcer Advisory Panel
(NPUAP), the current staging was not
adjusted. We confirm our commitment
to ongoing monitoring and re-evaluation
of the risk models for all applicable
outcome measures.
While we appreciate these comments
and the importance of the role that
sociodemographic status plays in the
care of patients, we continue to have
concerns about holding providers to
different standards for the outcomes of
their patients of low sociodemographic
status because we do not want to mask
potential disparities or minimize
incentives to improve the outcomes of
disadvantaged populations. We
routinely monitor the impact of
sociodemographic status on facilities’
results on our measures.
NQF is currently undertaking a 2-year
trial period in which new measures and
measures undergoing maintenance
review will be assessed to determine if
risk-adjusting for sociodemographic
factors is appropriate for each measure.
For 2 years, NQF will conduct a trial of
a temporary policy change that will
allow inclusion of sociodemographic
factors in the risk-adjustment approach
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for some performance measures. At the
conclusion of the trial, NQF will
determine whether to make this policy
change permanent. Measure developers
must submit information such as
analyses and interpretations as well as
performance scores with and without
sociodemographic factors in the risk
adjustment model.
Furthermore, the Office of the
Assistant Secretary for Planning and
Evaluation (ASPE) is conducting
research to examine the impact of
socioeconomic status on quality
measures, resource use, and other
measures under the Medicare program
as directed by the IMPACT Act. We will
closely examine the findings of these
reports and related Secretarial
recommendations and consider how
they apply to our quality programs at
such time as they are available.
Comment: A commenter expressed
concern that the proposed
implementation of NQF #0678 did not
include risk adjustment, just exclusion
of patients who die.
Response: The Percent of Residents or
Patients with Pressure Ulcers That Are
New or Worsened (NQF #0678) is riskadjusted based on an evaluation of
covariates that predict the outcome,
including low body mass, diabetes,
arterial and peripheral vascular disease,
med mobility and bowel incompetence.
As stated in the CY 2016 HH PPS
proposed rule, a discussion pertaining
to risk adjustment for this measure can
be found in the downloads section on
the Home Health Quality Measures Web
page at: https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIQualityMeasures.html.
Comment: One commenter
appreciated the revision in the
organization of the pressure ulcer items
in section M1308 that makes the section
easier to understand and suggested
similar revisions to other items. The
commenter also questioned why data on
the number and stage of pressure ulcers
was collected on both M1309 and
M1308, noting that this might confuse
clinicians. This commenter suggested
deleting M1309 and making additional
revisions to M1308 to capture the
number of new or worsened pressure
ulcers since the most recent SOC/ROC,
and further suggested adding M1308 at
recertification. Another commenter
noted that OASIS Item M1309 is
complex and recommended CMS
develop an algorithm to assist HHAs
with completing this item, adding that
this complexity may lead to a wide
variation of responses from HHAs and
affect data reliability. This commenter
further noted that home health agencies
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might be reliant on caregivers and
patients to follow instructions related to
pressure ulcer prevention in order to
achieve quality outcomes for pressure
ulcers.
Response: We appreciate the
commenters’ positive feedback on items
M1308, and suggestions related to
M1309 in the current OASIS C1 item
set, which we will take into
consideration. We wish to clarify that
M1308 would be collected at
recertification. We also wish to clarify
that the revised version of M1309 builds
upon the current version of this item in
the OASIS instrument and has been
adjusted to be standardized to ensure
comparable data capture of these items
across the PAC settings. We appreciate
the potential for confusion between the
item sections M1308 and M1309. The
items used in the skin assessment that
inform this measure were tested during
the development of the Minimum Data
Set version 3.0. The inter-rater
reliability and validity of these items
was very strong suggesting that there
was little confusion in the coding of
these items by clinicians. We believe
that training is important in assuring
accurate assessments and OASIS
coding. Therefore, we plan to issue new
guidance on these items, as part of the
update to the OASIS manual, well in
advance of their implementation, and to
provide further support through training
and other education materials. We
appreciate the unique role of patients
and caregivers in achieving quality
health outcomes in the home setting,
where skilled care is intermittent in
nature. We believe that as part of home
health services, the provider ensures
that adequate person and family
centered education is provided to help
in the avoidance and mitigation of
pressure ulcers, or other events. Thus,
CMS currently has implemented several
process measures in the HH QRP, which
assess whether care plans and other best
practices have been implemented to
help patients achieve the best possible
outcomes.
Comment: A commenter noted strong
support for assessing and considering
other wounds in addition to pressure
ulcers when determining the clinical
and functional status of the patient. This
commenter additionally recommended
that CMS expand the list of active
diagnoses that are typically barriers to
good outcomes and clarify whether
these are diagnoses or symptomology.
Response: We appreciate the
comment supporting assessment and
monitoring all wounds, as well as the
recommendation to expand the list of
active diagnoses. We believe that as part
of providing quality care, home health
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agencies assess, care for, document, and
ensure surveillance of all wound types.
We will consider this feedback in future
refinements of this proposed quality
measure. In addition, we will consider
expanding the items referencing active
diagnoses and better clarifying whether
items are referencing new diagnoses or
symptomology of a disease.
Comment: Several commenters
commented on the collection of a
patient’s height and weight in the
OASIS, in order to calculate body mass
index (BMI) as a risk adjustor for this
proposed quality measure. CMS
received several comments in support of
the proposal of this quality measure.
One commenter supported the efforts to
standardize data to improve data
accuracy and to help facilitate best
practices for the prevention of pressure
ulcers, while assuring appropriate care
for pressure ulcers is given in all
settings. The commenter expressed that
there is relevance of low BMI and the
incidence of pressure ulcers and
recommended that CMS consider
evaluating high BMI as a risk factor for
developing new or worsened pressure
ulcers. One commenter believed that
CMS should not use BMI obtained in
the home health setting, suggesting that
physician offices and care centers obtain
such information. One commenter did
not support the use of BMI as a
covariate for the New or Worsened
Pressure Ulcer proposed quality
measure without additional evidence of
its relevance in the home care setting.
Several commenters expressed
concerns about the situations in which
providers are unable to collect accurate
height and weight data in the home care
setting safely, including situations such
as, but not limited to, bedbound patients
who are unable to stand on scales or
whose self-reported height may be
invalid due to memory deficits.
Commenters additionally cited the lack
of appropriate equipment to obtain this
information in the home, including
scales and Hoyer lifts for patients who
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cannot transfer. An additional
commenter recommended that CMS add
an option box to the new OASIS items
to allow coding for those patients who
cannot be weighed. Finally, one
commenter requested clarification of
‘‘base weight’’ and the expectation for
recording a weight that is measured
during the visit versus a weight which
could be reported by the patient when
they are weighed in their home or based
a recent healthcare provider
appointment or hospitalization.
Response: We appreciate the
comments received pertaining to the
relevance of low BMI as a risk factor for
developing pressure ulcers, the
inclusion of low BMI in the measure
and the suggestion that we evaluate the
inclusion of high BMI as a risk factor for
pressure ulcers. We further appreciate
the comments regarding the challenge of
obtaining height and weight data in the
home for home health patients. This
information is collected in order to
standardize risk adjustment for
measuring the incidence of new and
worsened pressure ulcers to facilitate
the comparison of quality data within
and across post-acute care settings for
this outcome measure.
Low body mass index, which is
derived from a patient’s height and
weight, is a known correlate of
developing pressure ulcers. We
recognize that there will be instances in
which obtaining height and weight
cannot occur, and coding response
options will be available in order to
indicate when such data cannot be
obtained. We intend to issue specific
guidance through the OASIS manual on
obtaining these data, including a
definition of ‘‘base weight’’. We will
also offer support through training,
Open Door Forums, and other
communication mechanisms.
In response to the commenter who
suggested that physician offices and
wound care centers obtain information
related to height and weight, we will
take this feedback into consideration in
our ongoing maintenance of this
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proposed quality measure. In the crosssetting Technical Expert Panel held by
our measure contractor, it was advised
that we continue to use BMI, as
collected, to indicate low body mass.
We appreciate those comments that
suggest enhancements to the measure’s
risk adjustment and we will take into
consideration revisions to the measure
and risk adjustment model in our
ongoing maintenance of the measure.
Comment: One commenter expressed
support for the integration of
unstageable pressure ulcers and sDTIs
into the measure, and stressed the
importance of education on the
additional options prior to
implementing this change, citing the
challenges to correct staging and the
importance of inter-rater reliability
across PAC settings.
Response: We appreciate the feedback
on future integration of unstageable
pressure ulcers and sDTIs into this
measure, and will consider it when
undertaking any revisions. We also
appreciate the commenter’s emphasis
on the important of education and
training as the OASIS is revised and the
quality measures are developed. We
historically have and will continue to
provide comprehensive training each
time the assessment items change. In
addition to the manual and training
sessions, we will provide training
materials through the CMS webinars,
open door forums, and help desk
support. As provided previously, item
testing revealed very strong inter-rater
reliability. Additionally, with the
measure development and maintenance
process, we will continue to test this
proposed measure’s reliability and
validity across settings.
Final Action: After consideration of
the comments received, we are
finalizing as proposed the adoption of
NQF #0678 Percent of Residents or
Patients with Pressure Ulcers that are
New or Worsened (Short Stay) for use in
the HH QRP for CY 2018 HH payment
determination and subsequent years.
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TABLE 19—FUTURE CROSS-SETTING MEASURE CONSTRUCTS UNDER CONSIDERATION TO MEET IMPACT ACT
REQUIREMENTS
[Home Health Timeline for Implementation—January 1, 2017]
IMPACT Act Domain .......................
Measures ........................................
IMPACT Act Domain: ......................
Measure ..........................................
IMPACT Act Domain .......................
Measure ..........................................
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IMPACT Act Domain .......................
Measure ..........................................
Measures to reflect all-condition risk-adjusted potentially preventable hospital readmission rates.
Application of (NQF #2510): Skilled Nursing Facility 30-Day All-Cause Readmission Measure (SNFRM).
CMS is the steward.
Application of the LTCH/IRF All-Cause Unplanned Readmission Measure for 30 Days Post Discharge from
LTCHs/IRFs.
Resource Use, including total estimated Medicare spending per beneficiary.
Payment Standardized Medicare Spending Per Beneficiary (MSPB).
Discharge to community.
Percentage residents/patients at discharge assessment, who discharged to a higher level of care versus to
the community.
Medication Reconciliation.
Percent of patients for whom any needed medication review actions were completed.
We also identified four future, crosssetting measure constructs to potentially
meet requirements of the IMPACT Act
domains of: (1) All-condition riskadjusted potentially preventable
hospital readmission rates; (2) resource
use, including total estimated Medicare
spending per beneficiary; (3) discharge
to community; and (4) medication
reconciliation. These are shown in
Table 19; we solicited public feedback
to inform future measure development
of these constructs as it relates to
meeting the IMPACT Act requirements
in these areas. These measures will be
proposed in future rulemaking. The
comments we received on this topic,
with our responses, are summarized
below.
Comment: One commenter
encouraged CMS to include clinical
experts in the development of measures
for cognition, expressive and receptive
language, and swallowing stressing that
without clinical expertise, substandard
data, barriers to data collection, and
risks in improving patient outcomes
could occur. The commenter asked that
these suggested measures be considered
as items of function and not exclusively
as risk adjustors. This commenter
supported the risk adjustment of all
outcome measures based on key casemix variables due to the variability of
patients treated in PAC settings.
Response: We intend to incorporate
clinical expertise in our ongoing
measure refinement activities to better
inform the development of these quality
measures. One way we incorporate this
form of clinical input is through the
inclusion of Technical Expert Panels
supported by the quality measurement
development contractor. We also
encourage public input on our measure
development, and comments may be
submitted to our quality reporting
program email
HomeHealthQualityQuestions@
cms.hhs.gov
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We are working toward developing
quality measures that assess areas of
cognition and expression, recognizing
that these quality topic domains are
intrinsically linked or associated to the
domain of function and cognitive
function. In this measure development,
we will take into consideration the
variability of the PAC population and
the appropriate risk-adjustment based
on case-mix. In addition, we will take
into consideration the suggestion that
these measures operate as items of
function and not exclusively as risk
adjustors.
Comment: One commenter requested
that CMS consider the CARE–C and
CARE–F items based on the National
Outcomes Measurement System
(NOMS) to capture communication,
cognition, and swallowing as additional
measures to be adopted in post-acute
care settings for future measures.
Response: We appreciate the
suggestion that we consider refinements
to functional items such as
communication, cognition, and
swallowing, which may provide a more
meaningful picture of patients with
impairments in these areas. We will
consider these recommendations in our
item, measure, and testing efforts for
both measure development as well as
standardized assessment domain
development.
Comment: One commenter expressed
concern regarding the cross-setting allcause potentially preventable hospital
readmissions measure. The commenter
suggested that additional research on
the effectiveness of this measure be
pursued. The commenter proposed that
the measure include rewards for
sustained achievement as well as for
improvement; and that actions outside
of the agency’s control (for example,
timely physician signatures on orders)
be taken into consideration in the
application of the all-cause readmission
measure. In addition, the commenter
recommends that CMS consider risk
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adjustment to address family-requested
hospitalizations and increased risk of
hospitalization due to select diagnoses
and comorbidities.
One commenter noted difficulty in
providing meaningful comment on
specific measures and measure
constructs without further information.
Regarding the measure ‘‘Percent of
patients for whom any needed
medication review actions were
completed’’, the commenter stated it is
unclear from the table how one would
determine whether a medication review
action is needed for purposes of the
measure. One commenter stated they
need additional time to review more
thoroughly, and plans to provide further
feedback in the future.
Finally, one commenter
recommended the inclusion of nurse
practitioners in both the development
and implementation of care plans based
on quality indicators.
Response: We appreciate the
commenters’ feedback and suggestions
regarding the cross-setting all-cause
potentially preventable hospital
readmissions measure, and will
consider them in future revisions. We
intend to risk adjust this outcome
measure, based on evaluation of
statistically significant covariates,
including diagnoses and co-morbidities.
We appreciate the comments
pertaining to the quality measure, the
percent of patients for whom any
needed medication review actions were
completed. As we continue to develop
and test this measure construct, we will
make information about the
measurement specifications available
through posting specifications on our
Web site and public comment periods.
We recognize the need for transparency
as we move forward to implement the
IMPACT Act and will continue to
engage stakeholders to ensure that our
approach to measure development and
implementation is communicated in an
open and informative manner. We
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would like to note that anyone can
submit feedback on the measures by
means of our mailbox
PACQualityInitiative@cms.hhs.gov.
Finally, we appreciate the important
role played by nurse practitioners in
patient health and home care outcomes,
and encourage their participation
through the variety of modes of
stakeholder engagement noted above.
We will take all comments into
consideration when developing and
modifying assessment items and quality
measures.
TABLE 20—FUTURE SETTING-SPECIFIC MEASURE CONSTRUCTS UNDER CONSIDERATION
National Quality Strategy Domain
Measure Construct
Safety ..............................................
Falls risk composite process measure: Percentage of home health patients who were assessed for falls
risk and whose care plan reflects the assessment, and which was implemented appropriately.
Nutrition assessment composite measure: Percentage of home health patients who were assessed for nutrition risk with a validated tool and whose care plan reflects the assessment, and which was implemented appropriately.
Improvement in Dyspnea in Patients with a Primary Diagnosis of Congestive Heart Failure (CHF), Chronic
Obstructive Pulmonary Disease (COPD), and/or Asthma: Percentage of home health episodes of care
during which a patient with a primary diagnosis of CHF, asthma and/or COPD became less short of
breath or dyspneic.
Improvement in Patient-Reported Interference due to Pain: Percent of home health patients whose self-reported level of pain interference on the Patient-Reported Objective Measurement Information System
(PROMIS) tool improved.
Improvement in Patient-Reported Pain Intensity: Percent of home health patients whose self-reported level
of pain severity on the PROMIS tool improved.
Improvement in Patient-Reported Fatigue: Percent of home health patients whose self-reported level of fatigue on the PROMIS tool improved.
Stabilization in 3 or more Activities of Daily Living (ADLs): Percent of home health patients whose functional scores remain the same between admission and discharge for at least 3 ADLs.
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Effective Prevention and Treatment
(b) We worked with our measure
development and maintenance
contractor to identify setting-specific
measure concepts for future
implementation in the HH QRP that
align with or complement current
measures and new measures to meet
domains specified in the IMPACT Act.
In identifying priority areas for future
measure enhancement and
development, we took into
consideration results of environmental
scans and resulting gap analysis for
relevant home health quality measure
constructs, along with input from
numerous stakeholders, including the
Measures Application Partnership
(MAP), the Medicare Payment Advisory
Commission (MedPAC), Technical
Expert Panels, and national priorities,
such as those established by the
National Priorities Partnership, the HHS
Strategic Plan, the National Strategy for
Quality Improvement in Healthcare, and
the CMS Quality Strategy. Based on
input from stakeholders, CMS identified
several high priority concept areas for
future measure development in Table
20.
These measure concepts are under
development, and details regarding
measure definitions, data sources, data
collection approaches, and timeline for
implementation will be communicated
in future rulemaking. We invited
feedback about these seven high priority
concept areas for future measure
development. Public comments and our
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responses to comments are summarized
below.
Comment: Multiple commenters
expressed support for the potential
constructs for future development, and
especially cited stabilization in
function. One commenter expressed
appreciation that the basic timeline for
implementation of future measures is
consistent with the IMPACT Act’s
requirements.
One commenter recommended four
new quality measure constructs related
to family caregivers. These included:
Home health agency documentation of
whether the beneficiary has a family
caregiver; whether the care or discharge
plan relies on the family caregiver to
provide assistance; whether the family
caregiver was provided supports they
need as part of the plan after
determining the need for such supports;
and family caregiver experience of care.
A few commenters recommended that
CMS ensure new measures provide
meaningful information and minimize
burden.
One commenter urged CMS to
provide clear and transparent
explanations of measure specifications,
and to provide as much information as
possible about the measures proposed.
One commenter recommended CMS
only use measures after they have been
tested in the home health setting and
proved to have meaningful risk
adjustment, as well as to be personcentered and realistic for patients’
disease state. Two commenters
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recommended that CMS consider
consolidating or removing measures
prior to expanding the current set of
measures to minimize administrative
burden. One additionally noted that
some existing measures could prove to
be redundant or unnecessary when the
IMPACT Act measures are
implemented. A few commenters
encouraged CMS to employ a
transparent process for measure
development that allows for multiple
avenues for stakeholder input. One
commenter welcomed the opportunity
to work with CMS in the development
of these measures and their
specifications.
In response to the specific constructs
listed in the Notice for Proposed Rule
Making, one commenter said that a
nutrition assessment conducted in the
home setting, to support a nutritional
assessment process measure, must
comprise data elements that would not
be included in a facility assessment,
such as access to, and resources for food
shopping. This commenter additionally
recommended that new measures take
into account patient-centered decisions
and goals, including refusal of care, and
balance these against provider
accountability.
MedPAC expressed concern about the
number of quality measures in the
Medicare Program, specifically the
number currently used in the HH QRP.
MedPAC suggested that prior to
expanding the current set of measures in
the HH QRP, CMS should consider
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whether any of the current measures can
be consolidated or removed, recognizing
that some measures are proposed in
response to legislation. MedPAC further
suggested that CMS consider whether
any of its measures are unnecessary or
redundant for the HH QRP, once the
IMPACT Act measures are
implemented.
Response: We appreciate the feedback
on potential constructs for future
measure development and concur with
the importance of valid and reliable
stabilization measures for home health
patients. Additionally, we agree that
caregiver constructs are high priority
areas to consider for future measure
development.
With all new measure development,
we are committed to assessing the
burden and utility of proposed
measures, through Technical Expert
Panels, public comment periods and
other opportunities for stakeholder
input. In addition, we are planning to
conduct field testing of new and
existing OASIS items to assess their
reliability, validity and relevance in the
home health setting. This field testing
will inform new measure development.
We agree with MedPAC, as well as
other commenters, regarding the
importance of a modest set of measures
for the HH QRP and are re-evaluating
the entire set to determine which
measures are candidates for revision or
retirement. CMS’s measure contractor
has convened a Technical Expert Panel
of providers, caregiver representatives,
and other clinical experts to aid in the
re-evaluation process. This process has
included: (1) Analysis of historical
measure trends, as well as reliability,
validity and variability; (2) a review of
the scientific basis for the measure
construct in the literature and
guidelines; and (3) feedback on the
value of the measures to providers and
patients for assessing and improving
quality. Ongoing evaluation of measures
used in HH QRP will continue as
measures intended to satisfy the
IMPACT Act’s specified domains are
made operational.
In the current HH QRP outcome
measures are risk-adjusted for a wide
array of covariates and these risk models
undergo periodic review and updating.
We would extend this practice to new
outcome measures as appropriate.
We recognize the unique
circumstances of home health patients,
who have greater control and potentially
greater barriers for maintaining good
nutritional status. Additionally, we
recognize that home health patients may
make decisions that align with their
personal choice but may be at odds with
high quality outcomes.
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Comment: One commenter
recommended that the OASIS capture
information on cerebral palsy, traumatic
brain injury, and cognitive impairment
for long-term home health patients.
Response: We appreciate the
commenter’s recommendation to
capture information on the OASIS for
all individuals with cerebral palsy,
traumatic brain injury, and cognitive
impairment and will take these
comments into consideration when
developing and modifying assessment
items and quality measures.
D. Form, Manner, and Timing of OASIS
Data Submission and OASIS Data for
Annual Payment Update
1. Regulatory Authority
The HH conditions of participation
(CoPs) at § 484.55(d) require that the
comprehensive assessment must be
updated and revised (including the
administration of the OASIS) no less
frequently than: (1) The last 5 days of
every 60 days beginning with the start
of care date, unless there is a
beneficiary-elected transfer, significant
change in condition, or discharge and
return to the same HHA during the 60day episode; (2) within 48 hours of the
patient’s return to the home from a
hospital admission of 24-hours or more
for any reason other than diagnostic
tests; and (3) at discharge.
It is important to note that to calculate
quality measures from OASIS data,
there must be a complete quality
episode, which requires both a Start of
Care (initial assessment) or Resumption
of Care OASIS assessment and a
Transfer or Discharge OASIS
assessment. Failure to submit sufficient
OASIS assessments to allow calculation
of quality measures, including transfer
and discharge assessments, is a failure
to comply with the CoPs.
HHAs do not need to submit OASIS
data for those patients who are excluded
from the OASIS submission
requirements. As described in the
December 23, 2005 Medicare and
Medicaid Programs: Reporting Outcome
and Assessment Information Set Data as
Part of the Conditions of Participation
for Home Health Agencies final rule (70
FR 76202), we defined the exclusion as
those patients:
• Receiving only non-skilled services;
• For whom neither Medicare nor
Medicaid is paying for HH care (patient
receiving care under a Medicare or
Medicaid Managed Care Plan are not
excluded from the OASIS reporting
requirement);
• Receiving pre- or post-partum
services; or
• Under the age of 18 years.
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As set forth in the CY 2008 HH PPS
final rule (72 FR 49863), HHAs that
become Medicare certified on or after
May 31 of the preceding year are not
subject to the OASIS quality reporting
requirement nor any payment penalty
for quality reporting purposes for the
following year. For example, HHAs
certified on or after May 31, 2014 are
not subject to the 2 percentage point
reduction to their market basket update
for CY 2015. These exclusions only
affect quality reporting requirements
and do not affect the HHA’s reporting
responsibilities as announced in the
December 23, 2005 final rule.
2. Home Health Quality Reporting
Program Requirements for CY 2016
Payment and Subsequent Years
In the CY 2014 HH PPS Final rule (78
FR 72297), we finalized a proposal to
consider OASIS assessments submitted
by HHAs to CMS in compliance with
HH CoPs and Conditions for Payment
for episodes beginning on or after July
1, 2012, and before July 1, 2013 as
fulfilling one portion of the quality
reporting requirement for CY 2014.
In addition, we finalized a proposal to
continue this pattern for each
subsequent year beyond CY 2014.
OASIS assessments submitted for
episodes beginning on July 1 of the
calendar year 2 years prior to the
calendar year of the Annual Payment
Update (APU) effective date and ending
June 30 of the calendar year one year
prior to the calendar year of the APU
effective date, fulfill the OASIS portion
of the HH QRP requirement.
3. Previously Established Pay-forReporting Performance Requirement for
Submission of OASIS Quality Data
Section 1895(b)(3)(B)(v)(I) of the Act
states that for 2007 and each subsequent
year, the home health market basket
percentage increase applicable under
such clause for such year shall be
reduced by 2 percentage points if a
home health agency does not submit
data to the Secretary in accordance with
subclause (II) for such a year. This payfor-reporting requirement was
implemented on January 1, 2007. In the
CY 2015 HH PPS Final rule (79 FR
38387), we finalized a proposal to
define the quantity of OASIS
assessments each HHA must submit to
meet the pay-for-reporting requirement.
We believe that defining a more
explicit performance requirement for
the submission of OASIS data by HHAs
would better meet the intent of the
statutory requirement.
In the CY 2015 HH PPS Final rule (79
FR 38387), we reported information on
a study performed by the Department of
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were expanded to an earlier reporting
period or into the next reporting period.
Seven types of assessments submitted
by an HHA fit this definition of a quality
assessment. These are:
1. A Start of Care (SOC; M0100 = ‘01’)
or Resumption of Care (ROC; M0100 =
‘03’) assessment that can be matched to
an End of Care (EOC; M0100 = ‘06’, ‘07’,
‘08’, or ‘09’) assessment. These SOC/
ROC assessments are the first
assessment in the pair of assessments
that create a standard quality of care
episode describe in the previous
paragraph.
2. An End of Care (EOC) assessment
that can be matched to a Start of Care
(SOC) or Resumption of Care (ROC)
assessment. These EOC assessments are
the second assessment in the pair of
assessments that create a standard
quality of care episode describe in the
previous paragraph.
3. A SOC/ROC assessment that could
begin an episode of care, but the
assessment occurs in the last 60 days of
the performance period. This is labeled
as a Late SOC/ROC quality assessment.
The assumption is that the EOC
assessment will occur in the next
reporting period.
4. An EOC assessment that could end
an episode of care that began in the
previous reporting period, (that is, an
EOC that occurs in the first 60 days of
the performance period). This is labeled
as an Early EOC quality assessment. The
assumption is that the matching SOC/
ROC assessment occurred in the
previous reporting period.
5. A SOC/ROC assessment that is
followed by one or more follow-up
assessments, the last of which occurs in
the last 60 days of the performance
period. This is labeled as an SOC/ROC
Pseudo Episode quality assessment.
6. An EOC assessment is preceded by
one or more follow-up assessments, the
first of which occurs in the first 60 days
of the performance period. This is
labeled an EOC Pseudo Episode quality
assessment.
7. A SOC/ROC assessment that is part
of a known one-visit episode. This is
labeled as a One-Visit episode quality
assessment. This determination is made
by consulting HH claims data.
SOC, ROC, and EOC assessments that
do not meet any of these definitions are
labeled as Non-Quality assessments.
Follow-up assessments (that is, where
the M0100 Reason for Assessment = ‘04’
or ‘05’) are considered Neutral
assessments and do not count toward or
against the pay-for-reporting
performance requirement.
Compliance with this performance
requirement can be measured through
the use of an uncomplicated
mathematical formula. This pay-forreporting performance requirement
metric has been titled as the ‘‘Quality
Assessments Only’’ (QAO) formula
because only those OASIS assessments
that contribute, or could contribute, to
creating a quality episode of care are
included in the computation.
The formula based on this definition
is as follows:
Our ultimate goal is to require all
HHAs to achieve a pay-for-reporting
performance requirement compliance
rate of 90 percent or more, as calculated
using the QAO metric illustrated above.
In the CY 2015 HH PPS final rule (79
FR 66074), we proposed implementing
a pay-for-reporting performance
requirement over a 3-year period. After
consideration of the public comments
received, we adopted as final our
proposal to establish a pay-for-reporting
performance requirement for
assessments submitted on or after July 1,
2015 and before June 30, 2016 with
appropriate start of care dates, HHAs
must score at least 70 percent on the
QAO metric of pay-for-reporting
performance requirement or be subject
to a 2 percentage point reduction to
their market basket update for CY 2017.
HHAs have been statutorily required
to report OASIS for a number of years
and therefore should have many years of
experience with the collection of OASIS
data and transmission of this data to
CMS. Given the length of time that
HHAs have been mandated to report
OASIS data and based on preliminary
analyses that indicate that the majority
of HHAs are already achieving the target
goal of 90 percent on the QAO metric,
we believe that HHAs would adapt
quickly to the implementation of the
pay-for-reporting performance
requirement, if phased in over a 3-year
period.
In the CY 2015 rule, we did not
finalize a proposal to increase the
reporting requirement in 10 percent
increments over a 2-year period
beginning July 1, 2016 until the
maximum rate of 90 percent is reached.
Instead, we proposed to analyze
historical data to set the reporting
requirements. To set the threshold for
the 2nd year, we analyzed the most
recently available data, from 2013 and
2014, to make a determination about
what the pay-for-reporting performance
requirement should be. Specifically, we
reviewed OASIS data from this time
period simulating the pay-for-reporting
performance 70 percent submission
requirement to determine the
hypothetical performance of each HHA
as if the pay-for-reporting performance
requirement were in effect during the
reporting period preceding its
implementation. This analysis indicated
a nominal increase of 10 percent each
year would provide the greatest
opportunity for successful
implementation versus an increase of 20
percent from year 1 to year 2.
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Health & Human Services, Office of the
Inspector General (OIG) in February
2012 to: (1) Determine the extent to
which HHAs met federal reporting
requirements for the OASIS data; (2) to
determine the extent to which states met
federal reporting requirements for
OASIS data; and (3) to determine the
extent to which CMS was overseeing the
accuracy and completeness of OASIS
data submitted by HHAs. Based on the
OIG report we proposed a performance
requirement for submission of OASIS
quality data, which would be responsive
to the recommendations of the OIG.
In response to these requirements and
the OIG report, we designed a pay-forreporting performance system model
that could accurately measure the level
of an HHA’s submission of OASIS data.
The performance system is 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 Start of Care
(SOC) or Resumption of Care (ROC)
assessment and a matching End of Care
(EOC) assessment. However, it was
determined that there are several
scenarios that could meet this matching
assessment requirement of the new payfor-reporting performance requirement.
These scenarios or quality assessments
are defined as assessments that create a
quality episode of care during the
reporting period or could create a
quality episode if the reporting period
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Based on this analysis, we proposed
to set the performance threshold at 80
percent for the reporting period from
July 1, 2016 through June 30, 2017. For
the reporting period from July 1, 2017
through June 30, 2018 and thereafter, we
proposed the performance threshold
would be 90 percent.
We provided a report to each HHA of
their hypothetical performance under
the pay-for-reporting performance
requirement during the 2014–2015 preimplementation reporting period in June
2015. On January 1, 2015, the data
submission process for OASIS
converted from the current state-based
OASIS submission system to a new
national OASIS submission system
known as the Assessment Submission
and Processing (ASAP) System. On July
1, 2015, when the pay-for-reporting
performance requirement of 70 percent
went into effect, providers were
required to submit their OASIS
assessment data into the ASAP system.
Successful submission of an OASIS
assessment consist of the submission of
the data into the ASAP system with a
receipt of no ‘‘fatal error’’ messages.
Error messages received during
submission can be an indication of a
problem that occurred during the
submission process and could also be an
indication that the OASIS assessment
was rejected. Successful submission can
be verified by ascertaining that the
submitted assessment data resides in the
national database after the assessment
has met all of the quality standards for
completeness and accuracy during the
submission process. Should one or more
OASIS assessments submitted by a HHA
be rejected due to an IT/server issue
caused by CMS, we may at our
discretion, excuse the non-submission
of OASIS data. We anticipate that such
a scenario would rarely, if ever, occur.
In the event that a HHA believes that
they were unable to submit OASIS
assessments due to an IT/server issue on
the part of CMS, the HHA should be
prepared to provide any documentation
or proof available, which could
demonstrate that no fault on their part
contributed to the failure of the OASIS
records to transmit to CMS.
The initial performance period for the
pay-for-reporting performance
requirement is July 1, 2015 through June
30, 2016. Prior to and during this
performance period, we have scheduled
Open Door Forums and webinars to
educate HHA personnel as needed about
the pay-for-reporting performance
requirement program and the pay-forreporting performance QAO metric, and
distributed individual provider preview
reports. Additionally, OASIS Education
Coordinators (OECs) have been trained
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to provide state-level instruction on this
program and metric. We have posted a
report, which provides a detailed
explanation of the methodology for this
pay-for-reporting QAO methodology. To
view this report, go to the downloads
section at: https://www.cms.gov/
Medicare/Quality-Initiatives-PatientAssessment-Instruments/
HomeHealthQualityInits/Home-HealthQuality-Reporting-Requirements.html.
Training announcements and additional
educational information related to the
pay-for-reporting performance
requirement have been provided on the
HH Quality Initiatives Web page.
We invited public comment on our
proposal to implement an 80 percent
Pay-for-Reporting Performance
Requirement for Submission of OASIS
Quality Data for Year 2 reporting period
July 1, 2016 to June 30, 2017 as
described previously, for the HH QRP.
Public comments and our responses to
comments are summarized below.
Comment: Several commenters
supported CMS’ proposed phased-in
approach for the ‘‘Quality Assessments
Only’’ (QAO) reporting requirements
and the submission of OASIS data; one
additionally noted appreciation for the
added clarity about the QAO
benchmarks for the next two assessment
periods. A few commenters noted that
the proposed increase to 80 percent for
the 2016–2017 was acceptable, but
encouraged CMS to defer subsequent
increases, pending evaluation. One of
these commenters additionally
requested that CMS provide continuing
status updates on the progress toward
these goals so that HHAs could make
changes to their processes in order to be
compliant.
Response: We appreciate the feedback
and support for the QAO reporting
thresholds and intend to conduct
ongoing monitoring of the effect of
increasing the QAO threshold on the
percent of agencies that are compliant
with this pay-for-reporting requirement.
We do not intend to defer the increase
to 90 percent beyond the schedule
included in the rule; this threshold was
chosen based on analysis indicating
compliance was already at this level for
the vast majority of agencies. We
designed the pay-for-reporting
performance system model in response
to federal reporting requirements for the
OASIS data and the recommendation in
the OIG report entitled, ‘‘Limited
Oversight of Home Health Agency
OASIS Data,’’ that we ‘‘identify all
HHAs that failed to submit OASIS data
and apply the 2 percent payment
reduction to them’’. As the OASIS
reporting requirements have been in
existence for 16 years, HHAs should
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already possess knowledge of these
requirements and know what they need
to do to bring their agency into
compliance. We provided a report to
each HHA of their hypothetical
performance under the pay-for-reporting
performance requirement during the
2014–2015 pre-implementation
reporting period in June 2015;
additionally we are considering options
for ongoing communication with
agencies about their compliance levels.
Comment: One commenter requested
CMS provide additional clarification
about the definition of ‘‘OASIS
submission’’ and whether it required
acceptance of the submission by the
state agency, as well as whether the
QAO calculation included Medicare
Advantage and Medicaid patients, in
addition to traditional Medicare. This
commenter recommended the standard
be applied only to assessments
completed for traditional Medicare
patients and requested CMS provide
comprehensive education on the new
standard at least six months before it is
effective.
Response: On January 1, 2015, the
data submission process for OASIS
converted from the former state-based
OASIS submission system to a new
national OASIS submission system
known as the Assessment Submission
and Processing (ASAP) System.
Therefore, the commenter’s question
about whether successful submission
requires both submission and
acceptance of OASIS data by the state
agency is not applicable because the
state-based OASIS submission system is
no longer in existence.
Providers are required to submit their
OASIS assessment data into the ASAP
system. Successful submission of an
OASIS assessment consists of the
submission of the data into the ASAP
system with a receipt of no fatal error
messages. Error messages received
during submission can be an indication
of a problem that occurred during the
submission process and could also be an
indication that the OASIS assessment
was rejected. Successful submission can
be verified by ascertaining that the
submitted assessment data resides in the
national database after the assessment
has met all of the quality standards for
completeness and accuracy during the
submission process.
As noted previously, should one or
more OASIS assessments submitted by
a HHA be rejected due to an IT/server
issue caused by CMS, we may at our
discretion, excuse the non-submission
of OASIS data. We anticipate that such
a scenario would rarely, if ever, occur.
In the event that a HHA believes they
were unable to submit OASIS
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assessments due to an IT/server issue on
the part of CMS, the HHA should be
prepared to provide any documentation
or proof available which demonstrates
no fault on their part contributed to the
failure of the OASIS transmission to
CMS.
Patients receiving care under a
Medicare or Medicaid managed care
plan are not excluded from the OASIS
reporting requirements, and HHAs are
required to submit OASIS assessments
for these patients. OASIS reporting is
mandated for all Medicare beneficiaries
(under 42 CFR 484.250(a), 484.225(i),
and 484.55). The HH CoPs require that
the HH Registered Nurse (RN) or
qualified therapist perform an initial
assessment within 48 hours of referral,
within 48 hours of the patient’s return
home, or on the physician-ordered start
of care date. The HH RN or qualified
therapist must also complete a
comprehensive assessment within 5
days from the start of care. During these
assessments, the HH RN or qualified
therapist must determine the patient’s
eligibility for the Medicare HH benefit,
including homebound status (42 CFR
484.55(a)(1) and (b)). In addition, the
requirement for OASIS reporting on
Medicare and Medicaid Managed Care
patients was established in a final rule
titled ‘‘Medicare and Medicaid
Programs: Reporting Outcome and
Assessment Information Set Data as Part
of the Conditions of Participation for
Home Health Agencies Final Rule’’
dated December 23, 2005 (70 FR 76200),
which stated the following:
‘‘In the January 25, 1999, interim final
rule with comment period (64 FR 3749),
we generally mandated that all HHAs
participating in Medicare and Medicaid
(including managed care organizations
providing home health services to
Medicare and Medicaid beneficiaries)
report their OASIS data to the database
we established within each State via
electronic transmission.’’
We do not believe that there is more
burden associated with the collection of
OASIS assessment data for a Medicare
Managed Care patient than there is for
a HH patient that receives traditional
Medicare fee-for-service (FFS) benefits.
The requirements for the HH RN or
qualified therapist to perform an initial
and comprehensive assessment and
complete all required OASIS
assessments is the same for all Medicare
patients regardless of the type of
Medicare or Medicaid benefits they
receive. The completion of these
activities is a condition of payment of
both Medicare FFS and managed care
claims.
We are committed to stakeholder
education and as such conducted a
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Special Open Door forum on the QAO
methodology and compliance rates on
June 2, 2015; materials from this Special
Open Door Forum, along with
additional educational information, are
available in the downloads section at:
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
Home-Health-Quality-ReportingRequirements.html. CMS anticipates
communicating ongoing educational
opportunities through the regular HH
QRP communication channels,
including Open Door Forums, webinars,
listening sessions, memos, email
notification, and web postings.
Final Action: After consideration of
the comments received, we are adopting
as final our proposal to implement an 80
percent Pay-for-Reporting Performance
Requirement for Submission of OASIS
Quality Data for Year 2 reporting period
July 1, 2016 to June 30, 2017, and a 90
percent Pay-for-Reporting Performance
Requirement for Submission of OASIS
Quality Data for the reporting period
July 1, 2017 to June 30, 2018 and
thereafter.
e. Home Health Care CAHPS® Survey
(HHCAHPS)
In the CY 2015 HH PPS final rule (79
FR 66031), we stated that the home
health quality measures reporting
requirements for Medicare-certified
agencies includes the Home Health Care
CAHPS® (HHCAHPS) Survey for the CY
2015 Annual Payment Update (APU).
We are continuing to maintain the
stated HHCAHPS data requirements for
CY 2016 that were stated in CY 2015
and in previous rules, for the
continuous monthly data collection and
quarterly data submission of HHCAHPS
data.
1. Background and Description of
HHCAHPS
As part of the HHS Transparency
Initiative, we implemented a process to
measure and publicly report patient
experiences with home health care,
using a survey developed by the Agency
for Healthcare Research and Quality’s
(AHRQ’s) Consumer Assessment of
Healthcare Providers and Systems
(CAHPS®) program and endorsed by the
NQF in March 2009 (NQF Number
0517) and recently NQF re-endorsed in
2015. The HHCAHPS Survey is
approved under OMB Control Number
0938–1066 through May 31, 2017. The
HHCAHPS survey is part of a family of
CAHPS® surveys that asks patients to
report on and rate their experiences
with health care. The Home Health Care
CAHPS® (HHCAHPS) survey presents
home health patients with a set of
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standardized questions about their
home health care providers and about
the quality of their home health care.
Prior to this survey, there was no
national standard for collecting
information about patient experiences
that enabled valid comparisons across
all HHAs. The history and development
process for HHCAHPS has been
described in previous rules and is also
available on the official HHCAHPS Web
site at: https://homehealthcahps.org and
in the annually-updated HHCAHPS
Protocols and Guidelines Manual,
which is downloadable from https://
homehealthcahps.org.
Since April 2012, for public reporting
purposes, we report five measures from
the HHCAHPS Survey—three composite
measures and two global ratings of care
that are derived from the questions on
the HHCAHPS survey. The publicly
reported data are adjusted for
differences in patient mix across HHAs.
We update the HHCAHPS data on Home
Health Compare on www.medicare.gov
quarterly. Each HHCAHPS composite
measure consists of four or more
individual survey items regarding one of
the following related topics:
• Patient care (Q9, Q16, Q19, and
Q24);
• Communications between providers
and patients (Q2, Q15, Q17, Q18, Q22,
and Q23); and
• Specific care issues on medications,
home safety, and pain (Q3, Q4, Q5, Q10,
Q12, Q13, and Q14).
The two global ratings are the overall
rating of care given by the HHA’s care
providers (Q20), and the patient’s
willingness to recommend the HHA to
family and friends (Q25).
The HHCAHPS survey is currently
available in English, Spanish, Chinese,
Russian, and Vietnamese. The OMB
number on these surveys is the same
(0938–1066). All of these surveys are on
the Home Health Care CAHPS® Web
site, https://homehealthcahps.org. We
continue to consider additional
language translations of the HHCAHPS
in response to the needs of the home
health patient population.
All of the requirements about home
health patient eligibility for the
HHCAHPS survey and conversely,
which home health patients are
ineligible for the HHCAHPS survey are
delineated and detailed in the
HHCAHPS Protocols and Guidelines
Manual, which is downloadable at
https://homehealthcahps.org. Home
health patients are eligible for
HHCAHPS if they received at least two
skilled home health visits in the past 2
months, which are paid for by Medicare
or Medicaid.
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Home health patients are ineligible for
inclusion in HHCAHPS surveys if one of
these conditions pertains to them:
• Are under the age of 18;
• Are deceased prior to the date the
sample is pulled;
• Receive hospice care;
• Receive routine maternity care only;
•Are not considered survey eligible
because the state in which the patient
lives restricts release of patient
information for a specific condition or
illness that the patient has; or
• No Publicity patients, defined as
patients who on their own initiative at
their first encounter with the HHAs
make it very clear that no one outside
of the agencies can be advised of their
patient status, and no one outside of the
HHAs can contact them for any reason.
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 also must provide on a
monthly basis a list of their patients
served to their respective HHCAHPS
survey vendors. Agencies are not
allowed to influence at all how their
patients respond to the HHCAHPS
survey.
As previously required, HHCAHPS
survey vendors are required to attend
introductory and all update trainings
conducted by CMS and the HHCAHPS
Survey Coordination Team, as well as to
pass a post-training certification test.
We have approximately 30 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. As
stated in previous HH PPS final rules,
all HHCAHPS approved survey vendors
must develop a Quality Assurance Plan
(QAP) for survey administration in
accordance with the HHCAHPS
Protocols and Guidelines Manual. An
HHCAHPS survey vendor’s first QAP
must be submitted within 6 weeks of the
data submission deadline date after the
vendor’s first quarterly data submission.
The QAP must be updated and
submitted annually thereafter and at any
time that changes occur in staff or
vendor capabilities or systems. A model
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QAP is included in the HHCAHPS
Protocols and Guidelines Manual. The
QAP must include the following:
• Organizational Background and
Staff Experience;
• Work Plan;
• Sampling Plan;
• Survey Implementation Plan;
• Data Security, Confidentiality and
Privacy Plan; and
• Questionnaire Attachments
As part of the oversight activities, the
HHCAHPS Survey Coordination Team
conducts on-site visits to all approved
HHCAHPS survey vendors. The purpose
of the site visits is to allow the
HHCAHPS Survey Coordination Team
to observe the entire HHCAHPS Survey
implementation process, from the
sampling stage through file preparation
and submission, as well as to assess data
security and storage. The HHCAHPS
Survey Coordination Team reviews the
HHCAHPS survey vendor’s survey
systems, and assesses administration
protocols based on the HHCAHPS
Protocols and Guidelines Manual posted
at: https://homehealthcahps.org. The
systems and program site visit review
includes, but is not limited to the
following:
• Survey management and data
systems;
• Printing and mailing materials and
facilities;
• Telephone call center facilities;
• Data receipt, entry and storage
facilities; and
• Written documentation of survey
processes.
After the site visits, HHCAHPS survey
vendors are given a defined time period
in which to correct any identified issues
and provide follow-up documentation
of corrections for review. HHCAHPS
survey vendors are subject to follow-up
site visits on an as-needed basis.
In the CY 2013 HH PPS final rule (77
FR 67094, 67164), we codified the
current guideline that all approved
HHCAHPS survey vendors fully comply
with all HHCAHPS oversight activities.
We included this survey requirement at
§ 484.250(c)(3).
3. HHCAHPS Requirements for the CY
2016 APU
In the CY 2015 HH PPS final rule (79
FR 66031), we stated that for the CY
2016 APU, we would require continued
monthly HHCAHPS data collection and
reporting for four quarters. The data
collection period for the CY 2016 APU
includes the second quarter 2014
through the first quarter 2015 (the
months of April 2014 through March
2015). Although these dates are past, we
wished to state them in this rule so that
HHAs are again reminded of what
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months constituted the requirements for
the CY 2016 APU.
For the 2016 APU, we required that
all HHAs that had fewer than 60
HHCAHPS-eligible unduplicated or
unique patients in the period of April 1,
2013 through March 31, 2014 are
exempted from the HHCAHPS data
collection and submission requirements
for the CY 2016 APU, upon completion
of the CY 2016 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,
2013, through March 31, 2014, were
required to submit their patient counts
on the HHCAHPS Participation
Exemption Request form for the CY
2016 APU posted on https://
homehealthcahps.org from April 1,
2014, to 11:59 p.m., EST on March 31,
2015. This deadline for the exemption
form is firm, as are all of the quarterly
data submission deadlines for the HHAs
that participate in HHCAHPS.
We automatically exempt HHAs
receiving Medicare certification after the
period in which HHAs do their patient
counts. HHAs receiving Medicare
certification on or after April 1, 2014
were exempt from the HHCAHPS
reporting requirement for the CY 2016
APU. These newly-certified HHAs did
not need to complete the HHCAHPS
Participation Exemption Form for the
CY 2016 APU.
4. HHCAHPS Requirements for the CY
2017 APU
For the CY 2017 APU, we require
continued monthly HHCAHPS data
collection and reporting for four
quarters. The data collection period for
the CY 2017 APU includes the second
quarter 2015 through the first quarter
2016 (the months of April 2015 through
March 2016). HHAs are required to
submit their HHCAHPS data files to the
HHCAHPS Data Center for the second
quarter 2015 by 11:59 p.m., EST on
October 15, 2015; for the third quarter
2015 by 11:59 p.m., EST on January 21,
2016; for the fourth quarter 2015 by
11:59 p.m., EST on April 21, 2016; and
for the first quarter 2016 by 11:59 p.m.,
EST on July 21, 2016. These deadlines
are firm; no exceptions are permitted.
For the CY 2017 APU, we require that
all HHAs with fewer than 60
HHCAHPS-eligible unduplicated or
unique patients in the period of April 1,
2014, through March 31, 2015 are
exempt from the HHCAHPS data
collection and submission requirements
for the CY 2017 APU, upon completion
of the CY 2017 HHCAHPS Participation
Exemption Request form, and upon
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CMS verification of the HHA patient
counts. Agencies with fewer than 60
HHCAHPS-eligible, unduplicated or
unique patients in the period of April 1,
2014, through March 31, 2015, are
required to submit their patient counts
on the CY 2017 HHCAHPS Participation
Exemption Request form posted on
https://homehealthcahps.org from April
1, 2015, to 11:59 p.m., EST to March 31,
2016. This deadline is firm, as are all of
the quarterly data submission deadlines
for the HHAs that participate in
HHCAHPS.
We automatically exempt HHAs
receiving Medicare certification after the
period in which HHAs do their patient
count. HHAs receiving Medicarecertification on or after April 1, 2015 are
exempt from the HHCAHPS reporting
requirement for the CY 2017 APU.
These newly-certified HHAs do not
need to complete the HHCAHPS
Participation Exemption Request Form
for the CY 2017 APU.
5. HHCAHPS Requirements for the CY
2018 APU
For the CY 2018 APU, we require
continued monthly HHCAHPS data
collection and reporting for four
quarters. The data collection period for
the CY 2018 APU includes the second
quarter 2016 through the first quarter
2017 (the months of April 2016 through
March 2017). HHAs will be required to
submit their HHCAHPS data files to the
HHCAHPS Data Center for the second
quarter 2016 by 11:59 p.m., EST on
October 20, 2016; for the third quarter
2016 by 11:59 p.m., EST on January 19,
2017; for the fourth quarter 2016 by
11:59 p.m., EST on April 20, 2017; and
for the first quarter 2017 by 11:59 p.m.,
EST on July 20, 2017. These deadlines
are firm; no exceptions will be
permitted.
For the CY 2018 APU, we require that
all HHAs with fewer than 60
HHCAHPS-eligible unduplicated or
unique patients in the period of April 1,
2015 through March 31, 2016 are
exempt from the HHCAHPS data
collection and submission requirements
for the CY 2018 APU, upon completion
of the CY 2018 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,
2015 through March 31, 2016 are
required to submit their patient counts
on the CY 2018 HHCAHPS Participation
Exemption Request form posted on
https://homehealthcahps.org from April
1, 2016 to 11:59 p.m., EST to March 31,
2017. This deadline is firm, as are all of
the quarterly data submission deadlines
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for the HHAs that participate in
HHCAHPS.
We automatically exempt HHAs
receiving Medicare certification after the
period in which HHAs do their patient
count. HHAs receiving Medicarecertification on or after April 1, 2016 are
exempt from the HHCAHPS reporting
requirement for the CY 2018 APU.
These newly-certified HHAs do not
need to complete the HHCAHPS
Participation Exemption Request Form
for the CY 2018 APU.
6. HHCAHPS Reconsiderations and
Appeals Process
HHAs should 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 continue HHCAHPS oversight
activities as finalized in the previous
rules. In the CY 2013 HH PPS final rule
(77 FR 6704, 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).
We continue the OASIS and
HHCAHPS reconsiderations and appeals
process that we have finalized and that
we have used for prior all periods cited
in the previous rules, and utilized in the
CY 2012 to CY 2016 APU
determinations. We have described the
HHCAHPS reconsiderations and appeals
process requirements in the APU
Notification Letter that we send to the
affected HHAs annually in September.
HHAs have 30 days from their receipt of
the letter informing them that they did
not meet the HHCAHPS requirements to
reply to CMS with documentation that
supports their requests for
reconsideration of the annual payment
update to CMS. It is important that the
affected HHAs send in comprehensive
information in their reconsideration
letter/package because CMS will not
contact the affected HHAs to request
additional information or to clarify
incomplete or inconclusive information.
If clear evidence to support a finding of
compliance is not present, then the 2
percent reduction in the annual
payment update will be upheld. If clear
evidence of compliance is present, then
the 2 percent reduction for the APU will
be reversed. CMS notifies affected HHAs
by December 31 of the decisions that
affects payments in the annual year
beginning on January 1. If CMS
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determines to uphold the 2 percent
reduction for the annual payment
update, the affected HHA may further
appeal the 2 percent reduction via the
Provider Reimbursement Review Board
(PRRB) appeals process, which is
described in the December letter.
The following is a summary of the
comments that we received regarding
HHCAHPS:
Comment: We received one comment
that HHCAHPS is an unfunded
administrative mandate that entails
financial and resource burdens to
HHAs.
Response: The collection of the
patient’s perspectives of care data for
similar CAHPS surveys, such as
Hospital CAHPS (HCAHPS), follow the
same model where providers pay the
approved survey vendors for the data
collection and implementation of the
survey, and CMS pays for the
HHCAHPS survey administration and
technical assistance processes, the
vendor approval, the vendor training,
and vendor oversight activities,
technical support to the home health
agencies and for the vendors, and the
data compilation, data analysis, and
public reporting of the data’s findings
on www.Medicare.gov. HHAs are
strongly encouraged to report their
HHCAHPS costs on their respective
annual cost reports, but HHAs should
note that HHCAHPS costs are not
reimbursable under the HH PPS. We
post the list of the approved HHCAHPS
vendors on https://
homehealthcahps.org, and we
encourage HHAs to contact the vendors
for cost and service information
pertaining to HHCAHPS since the HHAs
may find differences among the vendors
and will very likely find a vendor that
is very suitable to their particular cost
and administrative needs for
HHCAHPS.
Comment: We received a comment of
concern regarding the fact that in the CY
2013 HH PPS final rule 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).
Response: We appreciate this
commenter’s continuing concern about
the policy set forth in the regulation
several years ago. The implementation
of the policy in the past 3 years has
worked out very well and it is working
as intended.
Comment: We received a comment
that the HHCAHPS Star Rating
methodology does not include Q25,
‘‘Would you recommend this agency to
your family or friends if they needed
home health care?’’ with the answer
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choices of ‘‘Definitely no, Probably no,
Probably yes, and Definitely yes’’. The
commenter recommends that we
include a Star Rating that is the average
of two questions on the HHCAHPS
survey, Q25 (the question above,
‘‘Would you recommend this agency to
your family or friends’’) and Q20
(‘‘Using a number from 0 to 10, where
0 is the worst home health care possible
and 10 is the best home health care
possible, what number would you use to
rate your care from this agency’s home
health providers?’’) or remove Q25 from
the composite measure.
Response: We thank the commenter
for the comments, but will continue to
retain Q20 and Q25 because they are
standalone questions and they are not
part of an HHCAHPS composite (which
is a measure combining several survey
questions).
Comment: We received one comment
that CMS should establish a minimum
number of completed HHCAHPS
surveys (at 50 surveys) per agency if the
data are going to be used in HHVBP or
any other quality assessment program.
Response: We are going to start
publicly reporting Star Ratings in
January 2016. We introduced the
methodology in several CMS Open Door
Forums in spring 2015 and
announcements on our Web sites. After
extensive data testing, our statisticians
established that at least 40 surveys are
needed in order to report Star Ratings
for a home health agency. The
commenter was correct; a minimum
number of surveys are needed to have
Star Ratings. In testing, it was found that
there is no statistically significant
difference between 40 surveys and 50
surveys as a minimum number for the
HHCAHPS data.
Comment: We received one comment
in support of the continuation of the
Home Health CAHPS® requirements
that are in line with previous years’
requirements.
Response: We thank this commenter
for their support.
Final Decision: We are not
recommending any changes to the
HHCAHPS requirements as a result of
comments received.
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
updated the information to reflect the
dates in the future APU years. We again
strongly encourage HHAs to keep up-todate about the HHCAHPS by regularly
viewing the official Web site for the
HHCAHPS at https://
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homehealthcahps.org. HHAs can also
send an email to the HHCAHPS Survey
Coordination Team at HHCAHPS@
rti.org, or telephone toll-free (1–866–
354–0985) for more information about
HHCAHPS.
F. Public Display of Home Health
Quality Data for the HH QRP
Section 1895(b)(3)(B)(v)(III) of the Act
and section 1899B(f) of the IMPACT Act
states the Secretary shall establish
procedures for making data submitted
under subclause (II) available to the
public. Such procedures shall ensure
that a home health agency has the
opportunity to review the data that is 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 be
meaningful and that comparing
performance across home health
agencies requires that measures be
constructed from data collected in a
standardized and uniform manner. We
also recognize the need to ensure that
each home health agency has the
opportunity to review the data before
publication. Medicare home health
regulations, as codified at § 484.250(a),
requires 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.
In addition, beginning April 1, 2015
HHAs began to receive Provider Preview
Reports (for all Process Measures and
Outcome Measures) on a quarterly,
rather than annual, basis. The
opportunity for providers to review
their data and to submit corrections
prior to public reporting aligns with the
other quality reporting programs and the
requirement for provider review under
the IMPACT Act. We provide quality
measure data to HHAs via the
Certification and Survey Provider
Enhanced Reports (CASPER reports),
which are available through the CMS
Health Care Quality Improvement and
Evaluation System (QIES).
As part of our ongoing efforts to make
healthcare more transparent, affordable,
and accountable, the HH QRP has
developed a CMS Compare Web site for
home health agencies, which identifies
home health providers based on the
areas they serve. Consumers can search
for all Medicare-certified home health
providers that serve their city or ZIP
code and then find the agencies offering
the types of services they need. A subset
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68709
of the HH quality measures has been
publicly reported on the Home Health
Compare (HH Compare) Web site since
2003. The selected measures that are
made available to the public can be
viewed on the HH Compare Web site
located at https://www.medicare.gov/
HHCompare/Home.asp
The Affordable Care Act calls for
transparent, easily understood
information on provider quality to be
publicly reported and made widely
available. To provide home health care
consumers with a summary of existing
quality measures in an accessible
format, we published a star rating based
on the quality of care measures for home
health agencies on Home Health
Compare starting in July 2015. This is
part of our plan to adopt star ratings
across all Medicare.gov Compare Web
sites. Star ratings are currently publicly
displayed on Nursing Home Compare,
Physician Compare, Hospital Compare,
Dialysis Facility Compare, and the
Medicare Advantage Plan Finder.
The Quality of Patient Care star rating
methodology assigns each home health
agency a rating between one (1) and five
(5) stars, using half stars for adjustment
and reporting. All Medicare-certified
home health agencies are eligible to
receive a Quality of Patient Care star
rating providing that they have quality
data reported on at least 5 out of the 9
quality measures that are included in
the calculation.
Home health agencies will continue to
have prepublication access to their
agency’s quality data, which enables
each agency to know how it is
performing before public posting of the
data on the Compare Web site. Starting
in April 2015, HHAs are receiving
quarterly preview reports showing their
Quality of Patient Care star rating and
how it was derived well before public
posting. HHAs have several weeks to
review and provide feedback.
The Quality of Patient Care star
ratings methodology was developed
through a transparent process the
included multiple opportunities for
stakeholder input, which was
subsequently the basis for refinements
to the methodology. An initial proposed
methodology for calculating the Quality
of Patient Care star ratings was posted
on the CMS.gov Web site in December
2014. CMS then held two Special Open
Door Forums (SODFs) on December 17,
2014 and February 5, 2015 to present
the proposed methodology and solicit
input. At each SODF, stakeholders
provided immediate input, and were
invited to submit additional comments
via the Quality of Patient Care star
ratings Help Desk mailbox HHC_Star_
Ratings_Helpdesk@cms.hhs.gov. CMS
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refined the methodology, based on
comments received and additional
analysis. The final methodology report
is posted on the new star ratings Web
page https://www.cms.gov/Medicare/
Quality-Initiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIHomeHealthStarRatings.html. A
Frequently-Asked-Questions (FAQ)
document is also posted on the same
Web page, addressing the issues raised
in the comments that were received. We
tested the Web site language used to
present the Quality of Patient Care star
ratings with Medicare beneficiaries to
assure that it allowed them to accurately
understand the significance of the
various star ratings.
Additional information regarding the
Quality of Patient Care star rating is
posted on the star ratings Web page at:
https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/HomeHealthQualityInits/
HHQIHomeHealthStarRatings.html.
Additional communications regarding
the Quality of Patient Care star ratings
will be announced via regular HH QRP
communication channels.
Summaries of public comments and
our responses to comments regarding
the Public Display of Home Health
Quality Data for the HH QRP are
provided below:
Comment: A commenter
recommended that CMS include
stabilization measures in the Quality of
Patient Care star ratings algorithm.
Response: We appreciate the feedback
on the Quality of Patient Care star
ratings methodology, and agree that
stabilization is an important goal for
some home health patients. CMS is
committed to ongoing evaluation and
improvement of the algorithm to
calculate the star rating, including
potential inclusion of new measures
that meet the inclusion criteria for
variability, reportability, and clinical
relevance.
VI. Collection of Information
Requirements
While this rule contains information
collection requirements, this rule does
not add new, nor revise any of the
existing information collection
requirements, or burden estimate. The
information collection requirements
discussed in this rule for the OASIS–C1
data item set had been previously
approved by the Office of Management
and Budget (OMB) on February 6, 2014
and scheduled for implementation on
October 1, 2014. The extension of
OASIS–C1/ICD–9 version was
reapproved under OMB control number
0938–0760 with a current expiration
date of March 31, 2018. This version of
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the OASIS will be discontinued once
the OASIS–C1/ICD–10 version is
approved and implemented. In addition,
to facilitate the reporting of OASIS data
as it relates to the implementation of
ICD–10 on October 1, 2015, CMS
submitted a new request for approval to
OMB for the OASIS–C1/ICD–10 version
under the Paperwork Reduction Act
(PRA) process. The proposed revised
OASIS item was announced in the 30day Federal Register notice (80 FR
15797) and received OMB approval and
assigned OMB control number 0938–
1279.
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 HH services paid under
Medicare. In addition, section
1895(b)(3)(A) of the Act requires (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 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 HH 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
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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.
Section 421(a) of the MMA requires
that HH services furnished in a rural
area, for episodes and visits ending on
or after April 1, 2010, and before
January 1, 2016, receive an increase of
3 percent of the payment amount
otherwise made under section 1895 of
the Act. Section 210 of the MACRA
amended section 421(a) of the MMA to
extend the 3 percent increase to the
payment amounts for serviced furnished
in rural areas for episodes and visits
ending before January 1, 2018.
Section 3131(a) of the Affordable Care
Act mandates that starting in CY 2014,
the Secretary must apply an adjustment
to the national, standardized 60-day
episode payment rate and other
amounts applicable under section
1895(b)(3)(A)(i)(III) of the Act to 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. In
addition, section 3131(a) of the
Affordable Care Act mandates that
rebasing must be phased-in over a 4year period in equal increments, not to
exceed 3.5 percent of the amount (or
amounts) as of the date of enactment
(2010) under section 1895(b)(3)(A)(i)(III)
of the Act, and be fully implemented in
CY 2017.
The HHVBP Model will apply a
payment adjustment based on an HHA’s
performance on quality measures to test
the effects on quality and costs of care.
This HHVBP Model was developed
based on the experiences we gained
from the implementation of the Home
Health Pay-for-Performance (HHPP)
demonstration as well as the successful
implementation of the HVBP program.
The model design was also developed
from the public comments received on
the discussion of a HHVBP model being
considered in the CY 2015 HH PPS
proposed and final rules. Value-based
purchasing programs have also been
included in the President’s budget for
most provider types, including Home
Health.
B. Overall Impact
We have examined the impacts of this
rule as required by Executive Order
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12866 on Regulatory Planning and
Review (September 30, 1993), Executive
Order 13563 on Improving Regulation
and Regulatory Review (January 18,
2011), the Regulatory Flexibility Act
(RFA) (September 19, 1980, Pub. L. 96–
354), section 1102(b) of the Act, section
202 of the Unfunded Mandates Reform
Act of 1995 (UMRA, March 22, 1995;
Pub. L. 104–4), Executive Order 13132
on Federalism (August 4, 1999), and the
Congressional Review Act (5 U.S.C.
804(2)).
Executive Orders 12866 and 13563
direct agencies to assess all costs and
benefits of available regulatory
alternatives and, if regulation is
necessary, to select regulatory
approaches that maximize net benefits
(including potential economic,
environmental, public health and safety
effects, distributive impacts, and
equity). Executive Order 13563
emphasizes the importance of
quantifying both costs and benefits, of
reducing costs, of harmonizing rules,
and of promoting flexibility. The net
transfer impacts related to the changes
in payments under the HH PPS for CY
2016 are estimated to be ¥$260 million.
The savings impacts related to the
HHVBP model are estimated at a total
projected 5-year gross savings of $380
million assuming a very conservative
savings estimate of a 6 percent annual
reduction in hospitalizations and a 1.0
percent annual reduction in SNF
admissions. In accordance with the
provisions of Executive Order 12866,
this regulation was reviewed by the
Office of Management and Budget.
1. HH PPS
The update set forth in this rule
applies to Medicare payments under HH
PPS in CY 2016. Accordingly, the
following analysis describes the impact
in CY 2016 only. We estimate that the
net impact of the policies in this rule is
approximately $260 million in
decreased payments to HHAs in CY
2016. 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 2016 wage index and the
recalibration of the case-mix weights for
2016 is zero. The ¥$260 million impact
reflects the distributional effects of the
1.9 percent HH payment update
percentage ($345 million increase), the
effects of the third year of the four-year
phase-in of the rebasing adjustments to
the national, standardized 60-day
episode payment amount, the national
per-visit payment rates, and the NRS
conversion factor for an impact of ¥2.4
percent ($440 million decrease), and the
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effects of the ¥0.97 percent adjustment
to the national, standardized 60-day
episode payment rate to account for
nominal case-mix growth ($165 million
decrease). The $260 million in
decreased payments is reflected in the
last column of the first row in Table 21
as a 1.4 percent decrease in
expenditures when comparing CY 2015
payments to estimated CY 2016
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 finalized in
this 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 final rule will have a significant
economic impact on a substantial
number of small entities. Further detail
is presented in Table 24, by HHA type
and location.
With regards to options for regulatory
relief, we note that in the CY 2014 HH
PPS final rule we finalized rebasing
adjustments to the national,
standardized 60-day episode rate, nonroutine supplies (NRS) conversion
factor, and the national per-visit
payment rates for each year, 2014
through 2017 as described in section
II.C and III.C.3 of this final rule. Since
the rebasing adjustments are mandated
by section 3131(a) of the Affordable
Care Act, we cannot offer HHAs relief
from the rebasing adjustments for CY
2016. For the 1.4 percent reduction to
the national, standardized 60-day
episode payment amount for CY 2016
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described in section III.B.2 of this final
rule, we believe it is appropriate to
reduce the national, standardized 60day episode payment amount 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. In the alternatives
considered section for the CY 2016 HH
PPS proposed rule (80 FR 39839), we
note that we considered reducing the
60-day episode rate in CY 2016 only to
account for nominal case-mix growth
between CY 2012 and CY 2014.
However, we instead proposed to
reduce the 60-day episode rate over a
two-year period (CY 2016 and CY 2017)
to account for estimated nominal casemix growth between CY 2012 and CY
2014 in order to lessen the impact on
HHAs in a given year. As discussed in
III.B.2 of this final rule, we are
implementing a reduction of 0.97
percent to the 60-day episode rate in
each of the next three calendar years
(CY 2016 through CY 2018.
Executive Order 13563 specifies, to
the extent practicable, agencies should
assess the costs of cumulative
regulations. However, given potential
utilization pattern changes, wage index
changes, changes to the market basket
forecasts, and unknowns regarding
future policy changes, we believe it is
neither practicable nor appropriate to
forecast the cumulative impact of the
rebasing adjustments on Medicare
payments to HHAs for future years at
this time. 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 will make it difficult to
predict accurately the full scope of the
impact upon HHAs for future years
beyond CY 2016. We note that the
rebasing adjustments to the national,
standardized 60-day episode payment
rate and the national per-visit rates are
capped at the statutory limit of 3.5
percent of the CY 2010 amounts (as
described in the preamble in section
II.C. of this final rule) for each year,
2014 through 2017. The NRS rebasing
adjustment will be ¥2.82 percent in
each year, 2014 through 2017.
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)
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tkelley on DSK3SPTVN1PROD with RULES2
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 final
rule is applicable exclusively to HHAs.
Therefore, the Secretary has determined
this rule will not have a significant
economic impact on the operations of
small rural hospitals.
2. HHVBP Model
To test the impact of upside and
downside value-based payment
adjustments, beginning in calendar year
2018 and in each succeeding calendar
year through calendar year 2022, the
HHVBP Model will adjust the final
claim payment amount for a home
health agency for each episode in a
calendar year by an amount equal to the
applicable percent. For purposes of this
final rule, we have limited our analysis
of the economic impacts to the valuebased incentive payment adjustments.
Under the model design, the incentive
payment adjustments will be limited to
the total payment reductions to home
health agencies included in the model
and would be no less than the total
amount available for value-based
incentive payment adjustment. Overall,
the distributive impact of this rule is
estimated at $380 million for CY 2018–
2022. Therefore, this rule is
economically significant and thus a
major rule under the Congressional
Review Act. The model will test the
effect on quality and costs of care by
applying payment adjustments based on
HHAs’ performance on quality
measures. This rule was developed
based on extensive research and
experience with value-based purchasing
models.
Guidance issued by the Department of
Health and Human Services interpreting
the Regulatory Flexibility Act considers
the effects economically ‘significant’
only if greater than 5-percent of
providers reach a threshold of 3- to 5percent or more of total revenue or total
costs. Among the over 1900 HHAs in the
selected states that would be expected
to be included in the HHVBP Model, we
estimate that the maximum percent
payment adjustment resulting from this
rule will only be greater than minus 3
percent for 10 percent of the HHAs
included in the model (using the 8
percent maximum payment adjustment
threshold to be applied in CY2022). As
a result, only 2-percent of all HHA
providers nationally would be
significantly impacted, falling well
below the RFA threshold. In addition,
only HHAs that are impacted with lower
payments are those providers that
provide the poorest quality which is the
main tenet of the model. This falls well
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below the threshold for economic
significance established by HHS for
requiring a more detailed impact
assessment under the RFA. Thus, we are
not preparing an analysis under the RFA
because the Secretary has determined
that this final rule would not have a
significant economic impact on a
substantial number of small entities.
In addition, section 1102(b) of the Act
requires us to prepare a regulatory
impact analysis if a rule may have a
significant impact on the operations of
a substantial number of small rural
HHAs. This analysis must conform to
the provisions of section 604 of the
RFA. For purposes of section 1102(b) of
the Act, we have identified less than 5
percent of HHAs included in the
selected states that primarily serve
beneficiaries that reside in rural areas
(greater than 50 percent of beneficiaries
served). We are not preparing an
analysis under section 1102(b) of the
Act because the Secretary has
determined that the HHVBP Model
would not have a significant impact on
the operations of a substantial number
of small rural HHAs.
Section 202 of the Unfunded
Mandates Reform Act of 1995 also
requires that agencies assess anticipated
costs and benefits before issuing any
rule whose mandates require spending
in any 1 year of $100 million in 1995
dollars, updated annually for inflation.
In 2015, that threshold is approximately
$144 million. This rule will have no
consequential effect on state, local, or
tribal governments or on the private
sector.
Executive Order 13132 establishes
certain requirements that an agency
must meet when it promulgates a
proposed rule (and subsequent final
rule) that imposes substantial direct
requirement costs on State and local
governments, preempts state law, or
otherwise has Federalism implications.
Since this regulation does not impose
any costs on state or local governments,
the requirements of Executive Order
13132 are not applicable.
In accordance with the provisions of
Executive Order 12866, this regulation
was reviewed by the Office of
Management and Budget.
C. Detailed Economic Analysis
1. HH PPS
This final rule sets forth updates for
CY 2016 to the HH PPS rates contained
in the CY 2015 HH PPS final rule (79
FR 66032 through 66118). The impact
analysis of this final rule presents the
estimated expenditure effects of policy
changes finalized in this rule. We use
the latest data and best analysis
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available, but we do not make
adjustments for future changes in such
variables as number of visits or casemix.
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 2014. 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.
Table 24 represents how HHA
revenues are likely to be affected by the
policy changes finalized in this rule. For
this analysis, we used an analytic file
with linked CY 2014 OASIS
assessments and HH claims data for
dates of service that ended on or before
December 31, 2014 (as of June 30, 2015).
The first column of Table 24 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 2016 wage
index. The fourth column shows the
payment effects of the CY 2016 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 effects of the rebasing
adjustments to the national,
standardized 60-day episode payment
rate, the national per-visit payment
rates, and NRS conversion factor. For
CY 2016, the average impact for all
HHAs due to the effects of rebasing is
an estimated 2.4 percent decrease in
payments. The seventh column shows
the effects of the CY 2016 home health
payment update percentage (i.e., the
home health market basket update
adjusted for multifactor productivity as
discussed in section III.C.1. of this final
rule).
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The last column shows the combined
effects of all the policies finalized in
this rule. Overall, it is projected that
aggregate payments in CY 2016 will
decrease by 1.4 percent. As illustrated
in Table 24, 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 2016
wage index, the extent to which HHAs
had episodes in case-mix groups where
68713
the case-mix weight decreased for CY
2016 relative to CY 2015, 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.
TABLE 21—ESTIMATED HOME HEALTH AGENCY IMPACTS BY FACILITY TYPE AND AREA OF THE COUNTRY, CY 2016
tkelley on DSK3SPTVN1PROD with RULES2
Number of
agencies
All Agencies .........................................
Facility Type and Control:
Free-Standing/Other Vol/NP ................
Free-Standing/Other Proprietary ..........
Free-Standing/Other Government .......
Facility-Based Vol/NP ..........................
Facility-Based Proprietary ....................
Facility-Based Government ..................
Subtotal: Freestanding ..................
Subtotal: Facility-based ................
Subtotal: Vol/NP ...........................
Subtotal: Proprietary .....................
Subtotal: Government ...................
Facility Type and Control: Rural:
Free-Standing/Other Vol/NP ................
Free-Standing/Other Proprietary ..........
Free-Standing/Other Government .......
Facility-Based Vol/NP ..........................
Facility-Based Proprietary ....................
Facility-Based Government ..................
Facility Type and Control: Urban:
Free-Standing/Other Vol/NP ................
Free-Standing/Other Proprietary ..........
Free-Standing/Other Government .......
Facility-Based Vol/NP ..........................
Facility-Based Proprietary ....................
Facility-Based Government ..................
Facility Location: Urban or Rural:
Rural .....................................................
Urban ...................................................
Facility Location: Region of the Country:
Northeast ..............................................
Midwest ................................................
South ....................................................
West .....................................................
Other ....................................................
Facility Location: Region of the Country (Census Region):
New England ........................................
Mid Atlantic ..........................................
East North Central ...............................
West North Central ..............................
South Atlantic .......................................
East South Central ...............................
West South Central ..............................
Mountain ..............................................
Pacific ...................................................
Facility Size (Number of 1st Episodes):
<100 episodes .....................................
100 to 249 ............................................
250 to 499 ............................................
500 to 999 ............................................
1,000 or More ......................................
CY 2016
wage
index 1
60-day
episode rate
nominal casemix reduction 3
CY 2016
case-mix
weights 2
Rebasing 4
HH payment
update
percentage 5
Total
11,609
0.0%
0.0%
¥0.9%
¥2.4%
1.9%
¥1.4%
1,094
9,076
382
718
117
222
10,552
1,057
1,812
9,193
604
0.0%
0.0%
¥0.1%
0.1%
¥0.3%
¥0.3%
0.0%
0.0%
0.1%
0.0%
¥0.2%
0.0%
¥0.1%
0.2%
0.2%
0.1%
0.3%
0.0%
0.2%
0.1%
¥0.1%
0.3%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥2.3%
¥2.4%
¥2.3%
¥2.3%
¥2.3%
¥2.3%
¥2.4%
¥2.3%
¥2.3%
¥2.4%
¥2.3%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
¥1.3%
¥1.5%
¥1.2%
¥1.0%
¥1.5%
¥1.3%
¥1.4%
¥1.1%
¥1.1%
¥1.5%
-1.2%
191
149
448
218
27
131
¥0.9%
¥0.4%
¥0.6%
¥0.7%
¥0.1%
¥0.5%
0.3%
0.1%
0.0%
0.3%
0.1%
0.5%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥2.3%
¥2.3%
¥2.3%
¥2.4%
¥2.3%
¥2.3%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
¥1.9%
¥1.6%
¥1.9%
¥1.8%
¥1.3%
¥1.3%
942
8,760
154
500
90
91
0.1%
0.0%
¥0.3%
0.2%
¥0.4%
¥0.2%
0.0%
¥0.1%
0.1%
0.2%
0.1%
0.2%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥2.3%
¥2.4%
¥2.4%
¥2.3%
¥2.2%
¥2.4%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
¥1.2%
¥1.5%
¥1.6%
¥0.9%
¥1.5%
¥1.4%
1,072
10,537
¥0.6%
0.0%
0.1%
0.0%
¥0.9%
¥0.9%
¥2.3%
¥2.4%
1.9%
1.9%
¥1.8%
¥1.4%
837
3,078
5,713
1885
96
0.0%
0.0%
¥0.2%
0.5%
¥0.2%
0.0%
0.1%
¥0.1%
0.0%
0.0%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥2.2%
¥2.4%
¥2.4%
¥2.3%
¥2.4%
1.9%
1.9%
1.9%
1.9%
1.9%
¥1.2%
¥1.3%
¥1.7%
¥0.8%
¥1.6%
294
543
2,447
631
1,883
432
3,398
621
1,264
¥0.2%
0.1%
0.0%
¥0.2%
0.0%
¥0.3%
¥0.3%
0.0%
0.7%
0.0%
0.0%
0.0%
0.2%
0.0%
¥0.1%
¥0.2%
0.1%
0.0%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥2.1%
¥2.3%
¥2.4%
¥2.4%
¥2.4%
¥2.5%
¥2.4%
¥2.3%
¥2.4%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
1.9%
¥1.3%
¥1.2%
¥1.4%
¥1.4%
¥1.4%
¥1.9%
¥1.9%
¥1.2%
¥0.7%
2,911
2,726
2,522
1,857
1,593
0.1%
0.1%
0.1%
0.1%
¥0.1%
0.1%
0.1%
0.0%
0.0%
¥0.1%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥0.9%
¥2.4%
¥2.4%
¥2.4%
¥2.4%
¥2.4%
1.9%
1.9%
1.9%
1.9%
1.9%
¥1.2%
¥1.2%
¥1.3%
¥1.3%
¥1.6%
Source: CY 2014 Medicare claims data for episodes ending on or before December 31, 2014 (as of June 30, 2015) for which we had a linked
OASIS assessment.
1 The impact of the CY 2016 home health wage index is offset by the wage index budget neutrality factor described in section III.C.3 of this
final rule.
2 The impact of the CY 2016 home health case-mix weights reflects the recalibration of the case-mix weights as outlined in section III.B.1 of
this final rule offset by the case-mix weights budget neutrality factor described in section III.C.3 of this final rule.
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3 The 0.97 percent reduction to the national, standardized 60-day episode payment amount in CY 2016 is estimated to have a 0.9 percent impact on overall HH PPS expenditures.
4 The impact of rebasing includes the rebasing adjustments to the national, standardized 60-day episode payment rate (¥2.74 percent after
the CY 2016 payment rate was adjusted for the wage index and case-mix weight budget neutrality factors and the nominal case-mix reduction),
the national per-visit rates (+2.9 percent), and the NRS conversion factor (¥2.82 percent). The estimated impact of the NRS conversion factor
rebasing adjustment is an overall ¥0.01 percent decrease in estimated payments to HHAs.
5 The CY 2016 home health payment update percentage reflects the home health market basket update of 2.3 percent, reduced by a 0.4 percentage point multifactor productivity (MFP) adjustment as required under section 1895(b)(3)(B)(vi)(I) of the Act, 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.
tkelley on DSK3SPTVN1PROD with RULES2
2. HHVBP Model
Table 22 displays our analysis of the
distribution of possible payment
adjustments at the 3-percent, 5-percent,
6-percent, 7-percent, and 8-percent rates
that are being used in the model based
on 2013–2014 data, providing
information on the estimated impact of
this rule. We note that this impact
analysis is based on the aggregate value
of all 9 states identified in section
IV.C.2. of this final rule by applying the
state selection methodology.
Table 23 displays our analysis of the
distribution of possible payment
adjustments based on 2013–2014 data,
providing information on the estimated
impact of this final rule. We note that
this impact analysis is based on the
aggregate value of all nine (9) states
(identified in section IV.C.2. of this rule)
by applying the state selection
methodology.
All Medicare-certified HHAs that
provide services in Massachusetts,
Maryland, North Carolina, Florida,
Washington, Arizona, Iowa, Nebraska,
and Tennessee will be required to
compete in this model.
Value-based incentive payment
adjustments for the estimated 1,900 plus
HHAs in the selected states that will
compete in the HHVBP Model are
stratified by the size as defined in
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section F. For example, Arizona has 31
HHAs that do not provide services to
enough beneficiaries to be required to
complete HHCAHPS surveys and
therefore are considered to be in the
state’s smaller-volume cohort under the
model. Using 2013–2014 data and the
highest payment adjustment of 5percent (as applied in CY 2019), based
on ten (10) process and outcome
measures currently available on Home
Health Compare, the smaller-volume
HHAs in Arizona would have a mean
payment adjustment of positive 0.64
percent. Only 10-percent of home health
agencies would be subject to downward
payment adjustments of more than
minus 3.3 percent (¥3.3 percent).
The next columns provide the
distribution of scores by percentile; we
see that the value-based incentive
percentage payments for home health
agencies in Arizona range from ¥3.3
percent at the 10th percentile to +5.0
percent at the 90th percentile, while the
value-based incentive payment at the
50th percentile is 0.56 percent.
The smaller-volume HHA cohorts
table identifies that some consideration
will have to be made for MD, WA, and
TN where there are too few HHAs in the
smaller-volume cohort and will be
included in the larger-volume cohort
without being measured on HHCAHPS.
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Table 24 provides the payment
adjustment distribution based on
proportion of dual-eligible beneficiaries,
average case mix (using HCC scores),
proportion that reside in rural areas, as
well as HHA organizational status.
Besides the observation that higher
proportion of dually-eligible
beneficiaries serviced is related to better
performance, the payment adjustment
distribution is consistent with respect to
these four categories.
The TPS score and the payment
methodology at the state and size level
were calculated so that each home
health agency’s payment adjustment
was calculated as it will be in the
model. Hence, the values of each
separate analysis in the tables are
representative of what they would be if
the baseline year was 2013 and the
performance year was 2014.
There were 1,931 HHAs in the nine
selected states out of 1,991 HHAs that
were found in the HHA data sources
that yielded a sufficient number of
measures to receive a payment
adjustment in the model. It is expected
that a certain number of HHAs will not
be subject to the payment adjustment
because they may be servicing too small
of a population to report on an adequate
number of measures to calculate a TPS.
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TABLE 23—HHA COHORT PAYMENT ADJUSTMENT DISTRIBUTIONS BY STATE
[Based on a 5 percent payment adjustment]
Average
payment
adjustment
%
# of
HHAs
State
10%
20%
30%
40%
50%
60%
70%
80%
90%
0.56
0.21
¥0.97
0.39
¥0.47
¥0.68
¥1.13
2.48
0.00
1.31
0.94
0.31
0.79
1.78
0.34
¥0.44
5.00
0.00
3.36
1.84
2.74
1.33
1.78
3.67
0.40
5.00
0.00
4.75
3.04
3.25
2.46
1.78
5.00
0.42
5.00
0.00
5.00
4.38
5.00
4.68
1.78
5.00
1.46
5.00
0.00
0.56
0.19
¥0.56
0.63
0.00
0.38
¥0.19
¥0.06
¥0.19
1.31
0.94
0.13
1.25
0.81
0.94
0.50
0.81
0.69
3.38
1.81
0.56
2.06
2.38
1.88
1.31
1.44
1.94
4.75
3.06
1.19
3.81
2.94
3.06
2.31
2.50
3.31
5.00
4.38
3.50
4.88
4.13
4.88
5.00
4.69
4.06
Smaller-volume HHA Cohort by State
AZ .................................................
FL .................................................
IA ..................................................
MA ................................................
MD ................................................
NC ................................................
NE ................................................
TN .................................................
WA ................................................
31
353
23
29
2
9
16
2
1
0.64
0.44
0.17
0.39
¥0.47
0.72
¥0.51
2.48
0.00
¥3.33
¥3.01
¥3.14
¥3.68
¥2.71
¥2.38
¥2.26
¥0.05
0.00
¥2.72
¥1.76
¥2.53
¥1.75
¥2.71
¥1.84
¥1.80
¥0.05
0.00
¥2.17
¥1.00
¥2.01
¥0.70
¥2.71
¥1.41
¥1.64
¥0.05
0.00
¥0.82
¥0.39
¥1.41
¥0.10
¥2.71
¥1.23
¥1.43
¥0.05
0.00
Larger-volume HHA Cohort by State
AZ .................................................
FL .................................................
IA ..................................................
MA ................................................
MD ................................................
NC ................................................
NE ................................................
TN .................................................
WA ................................................
82
672
129
101
50
163
48
134
55
0.39
0.41
¥0.31
0.64
0.41
0.65
0.37
0.39
0.39
¥3.31
¥3.00
¥3.13
¥2.88
¥2.75
¥2.75
¥2.63
¥2.56
¥2.75
¥2.75
¥1.75
¥2.31
¥2.19
¥2.06
¥1.56
¥2.19
¥1.81
¥1.63
¥2.19
¥1.60
¥2.70
¥1.50
¥2.30
¥1.30
¥1.40
¥2.00
¥2.00
¥0.81
¥0.38
¥1.13
¥0.38
¥0.88
¥0.06
¥0.56
¥0.63
¥0.94
TABLE 24—PAYMENT ADJUSTMENT DISTRIBUTIONS BY CHARACTERISTICS
[Based on a 5 percent payment adjustment]
Low % Dually-eligible
Medium % Dually-eligible ......................
High % Dually-eligible .........................
Acuity (HCC):
Low Acuity ................
Middle acuity ............
High Acuity ...............
% Rural Beneficiaries:
All non-rural ..............
VerDate Sep<11>2014
# of
HHAs
10%
20%
30%
40%
50%
498
¥3.21
¥2.57
¥1.86
¥1.29
¥0.60
0.12
0.78
2.13
3.97
995
¥2.91
¥2.10
¥1.33
¥0.63
0.01
0.67
1.39
2.47
4.12
498
¥2.46
¥1.04
¥0.24
0.59
1.29
2.34
3.38
4.53
5.00
499
993
499
¥2.83
¥3.05
¥3.04
¥1.76
¥2.08
¥2.04
¥0.94
¥1.24
¥1.29
¥0.23
¥0.50
¥0.51
0.46
0.19
0.26
1.16
0.90
1.06
2.03
1.71
2.00
3.40
2.81
3.16
5.00
4.51
4.91
800
¥2.81
¥1.51
¥0.66
0.08
0.78
1.54
2.64
3.94
5.00
19:46 Nov 04, 2015
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60%
E:\FR\FM\05NOR2.SGM
70%
05NOR2
80%
90%
ER05NO15.011</GPH>
tkelley on DSK3SPTVN1PROD with RULES2
Percentage
dually-eligible
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TABLE 24—PAYMENT ADJUSTMENT DISTRIBUTIONS BY CHARACTERISTICS—Continued
[Based on a 5 percent payment adjustment]
Percentage
dually-eligible
Up to 35% rural ........
over 35% rural ..........
Organizational Type:
Church ......................
Private Not-For-Profit
Other ........................
Private For-Profit ......
Federal .....................
State .........................
Local .........................
# of
HHAs
10%
20%
30%
40%
50%
60%
70%
80%
90%
925
250
¥3.12
¥2.91
¥2.37
¥2.01
¥1.71
¥1.17
¥1.01
¥0.62
¥0.42
¥0.11
0.32
0.56
1.18
1.32
2.24
2.86
3.97
4.58
62
194
93
1538
83
5
61
¥2.92
¥2.78
¥2.62
¥3.09
¥2.44
¥3.03
¥2.30
¥2.04
¥1.74
¥1.68
¥2.08
¥1.61
¥1.11
¥1.28
¥1.33
¥0.97
¥0.95
¥1.27
¥0.67
¥0.37
¥0.48
¥0.46
¥0.42
¥0.38
¥0.53
0.01
¥0.01
0.16
0.12
0.27
0.36
0.24
0.53
0.24
0.98
0.64
0.85
1.08
1.02
1.13
0.42
1.91
1.30
1.77
1.86
1.88
1.80
1.66
2.88
2.58
2.89
3.09
3.02
3.09
2.96
4.11
4.22
4.55
4.63
4.83
4.58
3.24
5.00
D. Accounting Statement and Table
As required by OMB Circular A–4
(available at https://
www.whitehouse.gov/omb/circulars_
a004_a-4), in Table 25, 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 25 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.
hospitalization relative rate of decline of
22-percent to 26-percent over the 3-year
and 4-year demonstration periods (the
1st year of each being the base year) for
the national and New York trials. CMMI
assumed a conservative savings estimate
of up to a 6-percent ultimate annual
reduction in hospitalizations and up to
a 1.0-percent ultimate annual reduction
in SNF admissions and took into
account costs incurred from the
beneficiary remaining in the HHA if the
hospitalization did not occur; resulting
in total projected five performance year
gross savings of $380 million. Based on
the JAGS study, which observed
hospitalization reductions of over 20percent, the 6-percent ultimate annual
hospitalization reduction assumptions
are considered reasonable.
2. HHVBP Model
In conclusion, we estimate there will
Annualized Monetized ¥$260 million.
be no net impact (to include either a net
Transfers.
increase or reduction in payments) in
From Whom to
Federal Government
this final rule in Medicare payments to
Whom?
to HHAs.
HHAs competing in the HHVBP Model
* The estimates reflect 2016 dollars.
for CY 2016. However, the overall
Table 26 provides our best estimate of economic impact of the HHVBP Model
provision is an estimated $380 million
the decrease in Medicare payments
in total savings from a reduction in
under the proposed HHVBP Model.
unnecessary hospitalizations and SNF
TABLE 26—ACCOUNTING STATEMENT: usage as a result of greater quality
HHVBP MODEL CLASSIFICATION OF improvements in the home health
ESTIMATED TRANSFERS AND COSTS industry over the life of the HHVBP
Model. The financial estimates were
FOR CY 2018–2022
based on the analysis of hospital, home
health and skilled nursing facility
Category
Transfers
claims data from nine states using the
5-Year Gross Trans¥$380 million.
most recent 2014 Medicare claims data.
fers.
A study published in 2002 by the
From Whom to
Federal Government
Journal of the American Geriatric
Whom?
to Hospitals and
Society (JAGS), ‘‘Improving patient
SNFs.
outcomes of home health care: Findings
from two demonstration trials of
E. Conclusion
outcome-based quality improvement,’’
formed the basis for CMMI’s
1. HH PPS
projections.79 That study observed a
In conclusion, we estimate that the
net impact of the HH PPS policies in
79 Shaughnessy, et al. ‘‘Improving patient
this rule is a decrease of 1.4 percent, or
outcomes of home health care: Findings from two
$260 million, in Medicare payments to
demonstration trials of outcome-based quality
VIII. Federalism Analysis
HHAs for CY 2016. The $260 million
decrease in estimated payments to
HHAs for CY 2016 reflects the effects of
the 1.9 percent CY 2016 HH payment
update percentage ($345 million
increase), 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 2016
to account for nominal case-mix growth
from 2012 through 2014 ($165 million
decrease), and a 2.4 percent decrease in
payments due to the third year of the 4year phase-in of the rebasing
adjustments required by section 3131(a)
TABLE 25—ACCOUNTING STATEMENT: of the Affordable Care Act ($440 million
decrease). This analysis, together with
HH PPS CLASSIFICATION OF ESTI- the remainder of this preamble,
MATED TRANSFERS AND COSTS, provides the final Regulatory Flexibility
FROM THE CYS 2015 TO 2016 *
Analysis.
tkelley on DSK3SPTVN1PROD with RULES2
Category
VerDate Sep<11>2014
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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.
List of Subjects
42 CFR Part 409
Health facilities, Medicare.
42 CFR Part 424
Emergency medical services, Health
facilities, Health professions, Medicare,
Reporting and recordkeeping
requirements.
improvement,’’ available at https://
www.ncbi.nlm.nih.gov/pubmed/12164991.
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Federal Register / Vol. 80, No. 214 / Thursday, November 5, 2015 / Rules and Regulations
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
chapter IV as set forth below:
PART 409—HOSPITAL INSURANCE
BENEFITS
1. The authority citation for part 409
continues to read as follows:
■
Authority: Secs. 1102 and 1871 of the
Social Security Act (42 U.S.C. 1302 and
1395hh).
2. Section 409.43 is amended by
revising paragraph (e)(1)(iii) to read as
follows:
■
§ 409.43
Plan of care requirements.
*
*
*
*
*
(e) * * *
(1) * * *
(iii) Discharge with goals met and/or
no expectation of a return to home
health care and the patient returns to
home health care during the 60-day
episode.
*
*
*
*
*
PART 424—CONDITIONS FOR
MEDICARE PAYMENT
3. The authority citation for part 424
continues to read as follows:
■
Authority: Secs. 1102 and 1871 of the
Social Security Act (42 U.S.C. 1302 and
1395hh).
§ 424.22
[Amended]
4. Section 424.22 is amended by
redesignating paragraph (a)(1)(v)(B)(1)
as paragraph (a)(2) and removing
reserved paragraph (a)(1)(v)(B)(2).
■
PART 484—HOME HEALTH SERVICES
5. The authority citation for part 484
continues to read as follows:
■
Authority: Secs 1102 and 1871 of the
Social Security Act (42 U.S.C. 1302 and
1395(hh)) unless otherwise indicated.
6. Section 484.205 is amended by
revising paragraphs (d) and (e) to read
as follows:
■
§ 484.205
Basis of payment.
tkelley on DSK3SPTVN1PROD with RULES2
*
*
*
*
*
(d) Partial episode payment
adjustment. (1) An HHA receives a
national 60-day episode payment of a
predetermined rate for home health
services unless CMS determines an
intervening event, defined as a
beneficiary elected transfer or discharge
with goals met or no expectation of
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18:04 Nov 04, 2015
Jkt 238001
return to home health and the
beneficiary returned to home health
during the 60-day episode, warrants a
new 60-day episode for purposes of
payment. A start of care OASIS
assessment and physician certification
of the new plan of care are required.
(2) The PEP adjustment will not apply
in situations of transfers among HHAs of
common ownership. Those situations
will be considered services provided
under arrangement on behalf of the
originating HHA by the receiving HHA
with the common ownership interest for
the balance of the 60-day episode. The
common ownership exception to the
transfer PEP adjustment does not apply
if the beneficiary moves to a different
MSA or Non-MSA during the 60-day
episode before the transfer to the
receiving HHA. The transferring HHA in
situations of common ownership not
only serves as a billing agent, but must
also exercise professional responsibility
over the arranged-for services in order
for services provided under
arrangements to be paid.
(3) If the intervening event warrants a
new 60-day episode payment and a new
physician certification and a new plan
of care, the initial HHA receives a
partial episode payment adjustment
reflecting the length of time the patient
remained under its care. A partial
episode payment adjustment is
determined in accordance with
§ 484.235.
(e) Outlier payment. An HHA receives
a national 60-day episode payment of a
predetermined rate for a home health
service, unless the imputed cost of the
60-day episode exceeds a threshold
amount. The outlier payment is defined
to be a proportion of the imputed costs
beyond the threshold. An outlier
payment is a payment in addition to the
national 60-day episode payment. The
total of all outlier payments is limited
to no more than 2.5 percent of total
outlays under the HHA PPS. An outlier
payment is determined in accordance
with § 484.240.
■ 7. Section 484.220 is amended by
revising paragraph (a)(3) and adding
paragraphs (a)(4), (5), and (6) to read as
follows:
§ 484.220 Calculation of the adjusted
national prospective 60-day episode
payment rate for case-mix and area wage
levels.
*
*
*
*
*
(a) * * *
(3) For CY 2011, the adjustment is
3.79 percent.
(4) For CY 2012, the adjustment is
3.79 percent.
(5) For CY 2013, the adjustment is
1.32 percent.
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68717
(6) For CY 2016, CY 2017, and CY
2018, the adjustment is 0.97 percent in
each year.
*
*
*
*
*
■ 8. Section 484.225 is revised to read
as follows:
§ 484.225 Annual update of the unadjusted
national prospective 60-day episode
payment rate.
(a) CMS updates the unadjusted
national 60-day episode payment rate
on a fiscal year basis (as defined in
section 1895(b)(1)(B) of the Act).
(b) For 2007 and subsequent calendar
years, in accordance with section
1895(b)(3)(B)(v) of the Act, in the case
of a home health agency that submits
home health 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 home health market basket
index amount.
(c) For 2007 and subsequent calendar
years, in accordance with section
1895(b)(3)(B)(v) of the Act, in the case
of a home health agency that does not
submit home health 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 home health 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 taken into
account in computing the prospective
payment amount for a subsequent
calendar year.
§ 484.230
[Amended]
9. Section 484.230 is amended by
removing the last sentence.
■ 10. Section 484.240 is amended by
revising paragraphs (b) and (e) and
adding paragraph (f) to read as follows:
■
§ 484.240 Methodology used for the
calculation of the outlier payment.
*
*
*
*
*
(b) The outlier threshold for each
case-mix group is the episode payment
amount for that group, or the PEP
adjustment amount for the episode, plus
a fixed dollar loss amount that is the
same for all case-mix groups.
*
*
*
*
*
(e) The fixed dollar loss amount and
the loss sharing proportion are chosen
so that the estimated total outlier
payment is no more than 2.5 percent of
total payment under home health PPS.
(f) The total amount of outlier
payments to a specific home health
agency for a year may not exceed an
amount equal to 10 percent of the total
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payments to the specific agency under
home health PPS for the year.
§ 484.245
[Removed and Reserved]
11. Section 484.245 is removed and
reserved.
■
§ 484.250
[Amended]
12. Section 484.250(a)(2) is amended
by removing the reference ‘‘§ 484.225(i)
of this subpart’’ and adding in its place
the reference ‘‘§ 484.225(c)’’.
■ 13. Subpart F is added to read as
follows:
■
Subpart F—Home Health Value-Based
Purchasing (HHVBP) Model Components
for Competing Home Health Agencies
within State Boundaries
Sec.
484.300 Basis and scope of subpart.
484.305 Definitions.
484.310 Applicability of the Home Health
Value-Based Purchasing (HHVBP)
model.
484.315 Data reporting for measures and
evaluation under the Home Health
Value-Based Purchasing (HHVBP)
Model.
484.320 Calculation of the Total
Performance Score.
484.325 Payments for home health services
under Home Health Value-Based
Purchasing (HHVBP) Model.
484.330 Process for determining and
applying the value-based payment
adjustment under the Home Health
Value-Based Purchasing (HHVBP)
Model.
Subpart F—Home Health Value-Based
Purchasing (HHVBP) Model
Components for Competing Home
Health Agencies Within State
Boundaries
§ 484.300
Basis and scope of subpart.
This subpart is established under
sections 1102, 1115A, and 1871 of the
Act (42 U.S.C. 1315a), which authorizes
the Secretary to issue regulations to
operate the Medicare program and test
innovative payment and service
delivery models to improve
coordination, quality, and efficiency of
health care services furnished under
Title XVIII.
tkelley on DSK3SPTVN1PROD with RULES2
§ 484.305
Definitions.
As used in this subpart—
Applicable measure means a measure
for which the competing HHA has
provided 20 home health episodes of
care per year.
Applicable percent means a
maximum upward or downward
adjustment for a given performance
year, not to exceed the following:
(1) For CY 2018, 3-percent.
(2) For CY 2019, 5-percent.
(3) For CY 2020, 6-percent.
(4) For CY 2021, 7-percent.
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18:04 Nov 04, 2015
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(5) For CY 2022, 8-percent.
Benchmark refers to the mean of the
top decile of Medicare-certified HHA
performance on the specified quality
measure during the baseline period,
calculated separately for the largervolume and smaller-volume cohorts
within each state.
Competing home health agency or
agencies means an agency or agencies:
(1) That has or have a current
Medicare certification; and,
(2) Is or are being paid by CMS for
home health care delivered within any
of the states specified in § 484.310.
Home health prospective payment
system (HH PPS) refers to the basis of
payment for home health agencies as set
forth in §§ 484.200 through 484.245.
Larger-volume cohort means the
group of competing home health
agencies within the boundaries of
selected states that are participating in
HHCAHPs in accordance with
§ 484.250.
Linear exchange function is the means
to translate a competing HHA’s Total
Performance Score into a value-based
payment adjustment percentage.
New measures means those measures
to be reported by competing HHAs
under the HHVBP Model that are not
otherwise reported by Medicarecertified HHAs to CMS and were
identified to fill gaps to cover National
Quality Strategy Domains not
completely covered by existing
measures in the home health setting.
Payment adjustment means the
amount by which a competing HHA’s
final claim payment amount under the
HH PPS is changed in accordance with
the methodology described in § 484.325.
Performance period means the time
period during which data are collected
for the purpose of calculating a
competing HHA’s performance on
measures.
Selected state(s) means those nine
states that were randomly selected to
compete/participate in the HHVBP
Model via a computer algorithm
designed for random selection and
identified at § 484.310(b).
Smaller-volume cohort means the
group of competing home health
agencies within the boundaries of
selected states that are exempt from
participation in HHCAHPs in
accordance with § 484.250.
Starter set means the quality measures
selected for the first year of this model.
Total Performance Score means the
numeric score ranging from 0 to 100
awarded to each competing HHA based
on its performance under the HHVBP
Model.
Value-based purchasing means
measuring, reporting, and rewarding
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excellence in health care delivery that
takes into consideration quality,
efficiency, and alignment of incentives.
Effective health care services and high
performing health care providers may be
rewarded with improved reputations
through public reporting, enhanced
payments through differential
reimbursements, and increased market
share through purchaser, payer, and/or
consumer selection.
§ 484.310 Applicability of the Home Health
Value-Based Purchasing (HHVBP) Model.
(a) General rule. The HHVBP Model
applies to all Medicare-certified home
health agencies (HHAs) in selected
states.
(b) Selected states. Nine states have
been selected in accordance with CMS’s
selection methodology. All Medicarecertified HHAs that provide services in
Massachusetts, Maryland, North
Carolina, Florida, Washington, Arizona,
Iowa, Nebraska, and Tennessee will be
required to compete in this model.
§ 484.315 Data reporting for measures and
evaluation under the Home Health ValueBased Purchasing (HHVBP) Model.
(a) Competing home health agencies
will be evaluated using a starter set of
quality measures.
(b) Competing home health agencies
in selected states will be required to
report information on New Measures, as
determined appropriate by the
Secretary, to CMS in the form, manner,
and at a time specified by the Secretary.
(c) Competing home health agencies
in selected states will be required to
collect and report such information as
the Secretary determines is necessary
for purposes of monitoring and
evaluating the HHVBP Model under
section 1115A(b)(4) of the Act (42 U.S.C.
1315a).
§ 484.320 Calculation of the Total
Performance Score.
A competing home health agency’s
Total Performance Score for a model
year is calculated as follows:
(a) CMS will award points to the
competing home health agency for
performance on each of the applicable
measures in the starter set, excluding
the New Measures.
(b) CMS will award points to the
competing home health agency for
reporting on each of the New Measures
in the starter set, worth up to ten
percent of the Total Performance Score.
(c) CMS will sum all points awarded
for each applicable measure excluding
the New Measures in the starter set,
weighted equally at the individual
measure level, to calculate a value
worth 90-percent of the Total
Performance Score.
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(d) The sum of the points awarded to
a competing HHA for each applicable
measure in the starter set and the points
awarded to a competing HHA for
reporting data on each New Measure is
the competing HHA’s Total Performance
Score for the calendar year.
§ 484.325 Payments for home health
services under Home Health Value-Based
Purchasing (HHVBP) Model.
tkelley on DSK3SPTVN1PROD with RULES2
CMS will determine a payment
adjustment up to the maximum
applicable percentage, upward or
downward, under the HHVBP Model for
each competing home health agency
based on the agency’s Total Performance
Score using a linear exchange function.
Payment adjustments made under the
HHVBP Model will be calculated as a
percentage of otherwise-applicable
payments for home health services
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18:04 Nov 04, 2015
Jkt 238001
provided under section 1895 of the Act
(42 U.S.C. 1395fff).
§ 484.330 Process for determining and
applying the value-based payment
adjustment under the Home Health ValueBased Purchasing (HHVBP) Model.
(a) General. Competing home health
agencies will be ranked within the
larger-volume and smaller-volume
cohorts in selected states based on the
performance standards that apply to the
HHVBP Model for the baseline year, and
CMS will make value-based payment
adjustments to the competing HHAs as
specified in this section.
(b) Calculation of the value-based
payment adjustment amount. The
value-based payment adjustment
amount is calculated by multiplying the
Home Health Prospective Payment final
claim payment amount as calculated in
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68719
accordance with § 484.205 by the
payment adjustment percentage.
(c) Calculation of the payment
adjustment percentage. The payment
adjustment percentage is calculated as
the product of: The applicable percent
as defined in § 484.320, the competing
HHA’s Total Performance Score divided
by 100, and the linear exchange
function slope.
Dated: October 27, 2015.
Andrew M. Slavitt,
Acting Administrator, Centers for Medicare
& Medicaid Services.
Dated: October 28, 2015.
Sylvia M. Burwell,
Secretary, Department of Health and Human
Services.
[FR Doc. 2015–27931 Filed 10–29–15; 4:15 pm]
BILLING CODE 4120–01–P
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]]>Agencies
[Federal Register Volume 80, Number 214 (Thursday, November 5, 2015)]
[Rules and Regulations]
[Pages 68623-68719]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2015-27931]
[[Page 68623]]
Vol. 80
Thursday,
No. 214
November 5, 2015
Part II
Department of Health and Human Services
-----------------------------------------------------------------------
Centers for Medicare & Medicaid Services
-----------------------------------------------------------------------
42 CFR Part 409, 424, and 484
Medicare and Medicaid Programs; CY 2016 Home Health Prospective Payment
System Rate Update; Home Health Value-Based Purchasing Model; and Home
Health Quality Reporting Requirements; Final Rule
Federal Register / Vol. 80 , No. 214 / Thursday, November 5, 2015 /
Rules and Regulations
[[Page 68624]]
-----------------------------------------------------------------------
DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Medicare & Medicaid Services
42 CFR Parts 409, 424, and 484
[CMS-1625-F]
RIN 0938-AS46
Medicare and Medicaid Programs; CY 2016 Home Health Prospective
Payment System Rate Update; 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 will update Home Health Prospective Payment
System (HH PPS) rates, including the national, standardized 60-day
episode payment rates, the national per-visit rates, and the non-
routine medical supply (NRS) conversion factor under the Medicare
prospective payment system for home health agencies (HHAs), effective
for episodes ending on or after January 1, 2016. As required by the
Affordable Care Act, this rule implements the 3rd year of the 4-year
phase-in of the rebasing adjustments to the HH PPS payment rates. This
rule updates the HH PPS case-mix weights using the most current,
complete data available at the time of rulemaking and provides a
clarification regarding the use of the ``initial encounter'' seventh
character applicable to certain ICD-10-CM code categories. This final
rule will also finalize 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 (nominal case-mix growth) between CY 2012
and CY 2014. In addition, this rule implements a HH value-based
purchasing (HHVBP) model, beginning January 1, 2016, in which all
Medicare-certified HHAs in selected states will be required to
participate. Finally, this rule finalizes minor changes to the home
health quality reporting program and minor technical regulations text
changes.
DATES: Effective Date: These regulations are effective on January 1,
2016.
FOR FURTHER INFORMATION CONTACT: For general information about the HH
PPS please send your inquiry via email to:
HomehealthPolicy@cms.hhs.gov. Michelle Brazil, (410) 786-1648 or
Theresa White, (410) 786-2394 for information about the HH quality
reporting program. Lori Teichman, (410) 786-6684, for information about
HHCAHPS. Robert Flemming, (844) 280-5628, or send your inquiry via
email to HHVBPquestions@cms.hhs.gov for information about the HHVBP
Model.
SUPPLEMENTARY INFORMATION:
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. System for Payment of Home Health Services
C. Updates to the Home Health Prospective Payment System
D. Advancing Health Information Exchange
III. Provisions of the Proposed Rule and Response to Comments
A. Monitoring for Potential Impacts--Affordable Care Act
Rebasing Adjustments
B. CY 2016 HH PPS Case-Mix Weights and Reduction to the
National, Standardized 60-day Episode Payment Rate to Account for
Nominal Case-Mix Growth
1. CY 2016 HH PPS Case-Mix Weights
2. Reduction to the National, Standardized 60-day Episode
Payment Rate to Account for Nominal Case-Mix Growth
3. Clarification Regarding the Use of the ``Initial Encounter''
Seventh Character, Applicable to Certain ICD-10-CM Code Categories,
under the HH PPS
C. CY 2016 Home Health Rate Update
1. CY 2016 Home Health Market Basket Update
2. CY 2016 Home Health Wage Index
3. CY 2016 Annual Payment Update
D. Payments for High-Cost Outliers Under the HH PPS
E. Report to the Congress on the Home Health Study Required by
Section 3131(d) of the Affordable Care Act and an Update on
Subsequent Research and Analysis
F. Technical Regulations Text Changes
IV. Provisions of the Home Health Value-Based Purchasing (HHVBP)
Model and Response to Comments
A. Background
B. Overview
C. Selection Methodology
1. Identifying a Geographic Demarcation Area Overview of the
Randomized Selection Methodology for States
D. Performance Assessment and Payment Periods
1. Performance Reports
2. Payment Adjustment Timeline
E. Quality Measures
1. Objectives
2. Methodology for Selection of Quality Measures
3. Selected Measures
4. Additional Information on HHCAHPS
5. New Measures
6. HHVBP Model's Four Classifications
7. Weighting
F. Performance Scoring Methodology
1. Performance Calculation Parameters
2. Considerations for Calculating the Total Performance Score
3. Additional Considerations for the HHVBP Total Performance
Scores
4. Setting Performance Benchmarks and Thresholds
5. Calculating Achievement and Improvement Points
6. Scoring Methodology for New Measures
7. Minimum Number of Cases for Outcome and Clinical Quality
Measures
G. The Payment Adjustment Methodology
H. Preview and Period To Request Recalculation
I. Evaluation
V. Provisions of the Home Health Care Quality Reporting Program (HH
QRP) and Response to Comments
A. Background and Statutory Authority
B. General Considerations Used for the Selection of Quality
Measures for the HH QRP
C. HH QRP Quality Measures and Measures Under Consideration for
Future Years
D. Form, Manner, and Timing of OASIS Data Submission and OASIS
Data for Annual Payment Update
1. Statutory Authority
2. Home Health Quality Reporting Program Requirements for CY
2016 Payment and Subsequent Years
3. Previously Established Pay-for-Reporting Performance
Requirement for Submission of OASIS Quality Data
E. Home Health Care CAHPS Survey (HHCAHPS)
1. Background and Description of HHCAHPS
2. HHCAHPS Oversight Activities
3. HHCAHPS Requirements for the CY 2016 APU
4. HHCAHPS Requirements for the CY 2017 APU
5. HHCAHPS Requirements for the CY 2018 APU
6. HHCAHPS Reconsideration and Appeals Process
7. Summary
F. Public Display of Home Health Quality Data for the HH QRP
VI. Collection of Information Requirements
VII. Regulatory Impact Analysis
VIII. Federalism Analysis
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
APU Annual Payment Update
BBA Balanced Budget Act of 1997, Pub. L. 105-33
BBRA Medicare, Medicaid, and SCHIP Balanced Budget Refinement Act of
1999, Pub. L. 106-113
CAD Coronary Artery Disease
CAH Critical Access Hospital
CBSA Core-Based Statistical Area
CASPER Certification and Survey Provider Enhanced Reports
[[Page 68625]]
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, Pub. L. 109-171, enacted February
8, 2006
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
HHCAHPS Home Health Care Consumer Assessment of Healthcare Providers
and Systems Survey
HH PPS Home Health Prospective Payment System
HHRG Home Health Resource Group
HHVBP Home Health Value-Based Purchasing
HIPPS Health Insurance Prospective Payment System
HVBP Hospital Value-Based Purchasing
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 Post-Acute Care Transformation Act of
2014 (Pub. L. 113-185)
IRF Inpatient Rehabilitation Facility
LEF Linear Exchange Function
LTCH Long-Term Care Hospital
LUPA Low-Utilization Payment Adjustment
MEPS Medical Expenditures Panel Survey
MMA Medicare Prescription Drug, Improvement, and Modernization Act
of 2003, Pub. L. 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, Pub. L. 100-203,
enacted December 22, 1987
OCESAA Omnibus Consolidated and Emergency Supplemental
Appropriations Act, Pub. L. 105-277, enacted October 21, 1998
OES Occupational Employment Statistics
OIG Office of Inspector General
OT Occupational Therapy
OMB Office of Management and Budget
MFP Multifactor productivity
PAMA Protecting Access to Medicare Act of 2014
PAC-PRD Post-Acute Care Payment Reform Demonstration
PEP Partial Episode Payment Adjustment
PT Physical Therapy
PY Performance Year
PRRB Provider Reimbursement Review Board
QAP Quality Assurance Plan
RAP Request for Anticipated Payment
RF Renal Failure
RFA Regulatory Flexibility Act, Pub. L. 96-354
RHHIs Regional Home Health Intermediaries
RIA Regulatory Impact Analysis
SAF Standard Analytic File
SLP Speech-Language Pathology
SN Skilled Nursing
SNF Skilled Nursing Facility
TPS Total Performance Score
UMRA Unfunded Mandates Reform Act of 1995.
VBP Value-Based Purchasing
I. Executive Summary
A. Purpose
This final rule will update the payment rates for HHAs for calendar
year (CY) 2016, as required under section 1895(b) of the Social
Security Act (the Act). This reflects the 3rd year of the 4-year phase-
in of the rebasing adjustments to the national, standardized 60-day
episode payment rate, the national per-visit rates, and the NRS
conversion factor finalized in the CY 2014 HH PPS final rule (78 FR
72256), as required under section 3131(a) of the Patient Protection and
Affordable Care Act of 2010 (Pub. L. 111-148), as amended by the Health
Care and Education Reconciliation Act of 2010 (Pub. L. 111-152)
(collectively referred to as the ``Affordable Care Act'').
This rule will update the case-mix weights under section
1895(b)(4)(A)(i) and (b)(4)(B) of the Act and provides a clarification
regarding the use of the ``initial encounter'' seventh character
applicable to certain ICD-10-CM code categories. This final rule will
finalize 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 case-mix growth unrelated to increases in patient
acuity (nominal case-mix growth) between CY 2012 and CY 2014 under the
authority of section 1895(b)(3)(B)(iv) of the Act. In addition, this
rule finalizes our proposal to implement an HH Value-Based Purchasing
(VBP) model, in which certain Medicare-certified HHAs are required to
participate, beginning January 1, 2016 under the authority of section
1115A of the Act. Finally, this rule will finalize changes to the home
health quality reporting program requirements under section
1895(b)(3)(B)(v)(II) of the Act and will finalize minor technical
regulations text changes in 42 CFR parts 409, 424, and 484 to better
align the payment requirements with recent statutory and regulatory
changes for home health services.
B. Summary of the Major Provisions
As required by section 3131(a) of the Affordable Care Act, and
finalized in the CY 2014 HH final rule, ``Medicare and Medicaid
Programs; Home Health Prospective Payment System Rate Update for 2014,
Home Health Quality Reporting Requirements, and Cost Allocation of Home
Health Survey Expenses'' (78 FR 77256, December 2, 2013), we are
implementing the 3rd 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 in
section III.C.3. The rebasing adjustments for CY 2016 will reduce the
national, standardized 60-day episode payment amount by $80.95,
increase the national per-visit payment amounts by 3.5 percent of the
national per-visit payment amounts in CY 2010 with the increases
ranging from $1.79 for home health aide services to $6.34 for medical
social services, and reduce the NRS conversion factor by 2.82 percent.
In the CY 2015 HH PPS final rule (79 FR 66072), we finalized our
proposal to recalibrate the case-mix weights every year with more
current data. In section III.B.1 of this rule, we are recalibrating the
HH PPS case-mix weights, using the most current cost and utilization
data available, in a budget neutral manner. In addition, in section
III.B.2 of this rule, we are finalizing 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 (nominal case-mix
growth) between CY 2012 and CY 2014. In section III.B.3 of this rule we
are providing a clarification regarding the use of the ``initial
encounter'' seventh character, applicable to certain ICD-10-CM code
categories, under the HH PPS. In section III.C.1 of this rule, we are
updating the payment rates under the HH PPS by the home health payment
update percentage of 1.9 percent (using the 2010-based Home Health
Agency (HHA) market basket update of 2.3 percent, minus 0.4 percentage
point for productivity as required by section 1895(b)(3)(B)(vi)(I) of
the Act. In the CY 2015 final rule (79 FR 66083 through 66087), we
incorporated new geographic area designations, set out in a February
28, 2013 Office of Management and Budget
[[Page 68626]]
(OMB) bulletin, into the home health wage index. For CY 2015, we
implemented a wage index transition policy consisting of a 50/50 blend
of the old geographic area delineations and the new geographic area
delineations. In section III.C.2 of this rule, we will update the CY
2016 home health wage index using solely the new geographic area
designations. In section III.D of this final rule, we discuss payments
for high cost outliers. In section III.E, we are finalizing several
technical corrections in 42 CFR parts 409, 424, and 484, to better
align the payment requirements with recent statutory and regulatory
changes for home health services. The sections include Sec. Sec.
409.43(e), 424.22(a), 484.205(d), 484.205(e), 484.220, 484.225,
484.230, 484.240(b), 484.240(e), 484.240(f), 484.245.
In section IV of this rule, we are finalizing our proposal to
implement a HHVBP model that will begin on January 1, 2016. Medicare-
certified HHAs selected for inclusion in the HHVBP model will be
required to compete for payment adjustments to their current PPS
reimbursements based on quality performance. A competing HHA is defined
as an agency that has a current Medicare certification and that is
being paid by CMS for home health care delivered within any of the
states selected in accordance with the HHVBP Model's selection
methodology.
Finally, section V of this rule includes changes to the home health
quality reporting program, including one new quality measure, the
establishment of a minimum threshold for submission of Outcome and
Assessment Information Set (OASIS) assessments for purposes of quality
reporting compliance, and submission dates for Home Health Care
Consumer Assessment of Healthcare Providers and Systems Survey
(HHCAHPS) Survey through CY 2018.
C. Summary of Costs and Transfers
Table 1--Summary of Costs and Transfers
------------------------------------------------------------------------
Provision description Costs Transfers
------------------------------------------------------------------------
CY 2016 HH PPS Payment Rate ................. The overall economic
Update. impact of the HH PPS
payment rate update
is an estimated -
$260 million (-1.4
percent) in payments
to HHAs.
CY 2016 HHVBP Model........... ................. The overall economic
impact of the HHVBP
model provision for
CY 2018 through 2022
is an estimated $380
million in total
savings from a
reduction in
unnecessary
hospitalizations and
SNF usage as a
result of greater
quality improvements
in the HH industry.
As for payments to
HHAs, there are no
aggregate increases
or decreases to the
HHAs competing in
the model.
------------------------------------------------------------------------
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 HH 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 HH services provided under a plan of care (POC)
that were paid on a reasonable cost basis by adding section 1895 of the
Social Security Act (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 HH services paid under Medicare.
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 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 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 HH services
furnished in a geographic area compared to the applicable national
average level. Under section 1895(b)(4)(C) of the Act, the wage-
adjustment 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 Patient Protection
and Affordable Care Act of 2010 (the Affordable Care Act) (Pub. L. 111-
148, enacted March 23, 2010) 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 HH services as required by section
4603 of the BBA, as subsequently amended by section 5101 of the Omnibus
Consolidated and Emergency Supplemental Appropriations Act (OCESAA) for
Fiscal Year 1999, (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 (BBRA) of 1999, (Pub. L. 106-113,
enacted November 29, 1999). The requirements include the implementation
of a HH PPS for HH 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 HH 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).
[[Page 68627]]
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 HH 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
Sec. 484.225(h) and (i) in accordance with the statute. The pay-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 Medicare
Access and CHIP Reauthorization Act of 2015 (MACRA) (Public Law 114-10)
amended section 421(a) of the MMA to extend the rural add-on for two
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 HH 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.
B. System for Payment of Home Health Services
Generally, Medicare 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 HH disciplines (skilled nursing,
HH aide, physical therapy, speech-language pathology, occupational
therapy, and medical social services). Payment for non-routine supplies
(NRS) is no longer part of the national standardized 60-day episode
rate and is computed by multiplying the relative weight for a
particular NRS severity level by the NRS conversion factor (See section
II.D.4.e). 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 case-mix 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.
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 low-utilization 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 HH 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 HH patients. We examined data on demographics,
family severity, and non-HH Part A Medicare expenditures to predict the
average case-mix weight for 2005. 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 case-mix 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 case-mix. 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 a
1.32 percent reduction to the payment rates for CY 2013 to account for
nominal case-mix growth from 2000 through 2010. When taking into
account the total measure of case-mix 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
[[Page 68628]]
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 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 as reflected in Table 2, 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
speech-language 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 2nd 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.
Table 2--Maximum Adjustments to the National Per-Visit Payment Rates
[Not to exceed 3.5 percent of the amount(s) in CY 2010]
------------------------------------------------------------------------
Maximum adjustments
2010 National per- per year (CY 2014
visit payment rates through CY 2017)
------------------------------------------------------------------------
Skilled Nursing............. $113.01 $3.96
Home Health Aide............ 51.18 1.79
Physical Therapy............ 123.57 4.32
Occupational Therapy........ 124.40 4.35
Speech-Language Pathology... 134.27 4.70
Medical Social Services..... 181.16 6.34
------------------------------------------------------------------------
D. Advancing Health Information Exchange
HHS has a number of initiatives designed to encourage and support
the adoption of health information technology and to promote nationwide
health information exchange to improve health care. As discussed in the
August 2013 Statement ``Principles and Strategies for Accelerating
Health Information Exchange'' (available at https://www.healthit.gov/sites/default/files/acceleratinghieprinciples_strategy.pdf), HHS
believes that all individuals, their families, their healthcare and
social service providers, and payers should have consistent and timely
access to health information in a standardized format that can be
securely exchanged between the patient, providers, and others involved
in the individual's care. Health IT that facilitates the secure,
efficient, and effective sharing and use of health-related information
when and where it is needed is an important tool for settings across
the continuum of care, including home health. While home health
providers are not eligible for the Medicare and Medicaid EHR Incentive
Programs, effective adoption and use of health information exchange and
health IT tools will be essential as these settings seek to improve
quality and lower costs through initiatives such as value-based
purchasing.
The Office of the National Coordinator for Health Information
Technology (ONC) has released a document entitled ``Connecting Health
and Care for the Nation: A Shared Nationwide Interoperability Roadmap''
(available at https://www.healthit.gov/sites/default/files/hie-interoperability/nationwide-interoperability-roadmap-final-version-1.0.pdf). In the near term, the Roadmap focuses on actions that will
enable individuals and providers across the care continuum to send,
receive, find, and use a common set of electronic clinical information
at the nationwide level by the end of 2017. The Roadmap's goals also
align with the Improving Medicare Post-Acute Care Transformation Act of
2014 (Pub. L. 113-185) (IMPACT Act), which requires assessment data to
be standardized and interoperable to allow for exchange of the data.
Moreover, the vision described in the draft Roadmap significantly
expands the types of electronic health information, information
sources, and information users well beyond clinical information derived
from electronic health records (EHRs). The Roadmap identifies four
critical pathways that health IT stakeholders should focus on now in
order to create a foundation for long-term success: (1) Improve
technical standards and implementation guidance for priority data
domains and associated elements; (2) rapidly shift and align federal,
state, and commercial payment policies from fee-for-service to value-
based models to stimulate the demand for interoperability; (3) clarify
and align federal and state privacy and security requirements that
enable interoperability; and (4) align and promote the use of
consistent policies and business practices that support
interoperability, in coordination with stakeholders. In addition, ONC
has released the draft version of the 2016 Interoperability Standards
Advisory (available at https://www.healthit.gov/standards-advisory/2016), which provides a list of the best available standards and
implementation specifications to enable priority health information
exchange functions. Providers, payers, and vendors are encouraged to
take these ``best available standards'' into account as they implement
interoperable health information exchange across the continuum of care,
including care settings such as behavioral health, long-term and post-
acute care, and home and community-based service providers.
We encourage stakeholders to utilize health information exchange
and certified health IT to effectively and efficiently help providers
improve internal care delivery practices, engage patients in their
care, support management of care across the continuum, enable the
reporting of
[[Page 68629]]
electronically specified clinical quality measures (eCQMs), and improve
efficiencies and reduce unnecessary costs. As adoption of certified
health IT increases and interoperability standards continue to mature,
HHS will seek to reinforce standards through relevant policies and
programs.
III. Provisions of the Proposed Rule and Responses to Comments
We received 118 timely comments from the public. The following
sections, arranged by subject area, include a summary of the public
comments received, and our responses.
A. Monitoring for Potential Impacts--Affordable Care Act Rebasing
Adjustments
In the CY 2016 HH PPS proposed rule (80 FR 39840), we provided a
summary of analysis conducted on FY 2013 HHA cost report data and how
such data, if used, would impact our estimate of the percentage
difference between Medicare payments and HHA costs. In addition, we
also provided a summary of MedPAC's Report to the Congress on home
health payment rebasing and presented information on Medicare home
health utilization using CY 2014 HHA claims data (the 1st year of the 4
year phase-in of the rebasing adjustments mandated by section 3131(a)
the Affordable Care Act). We will continue to monitor the impact of
future payment and policy changes and will provide the industry with
periodic updates on our analysis in future rulemaking and/or
announcements on the HHA Center Web page at: https://www.cms.gov/Center/Provider-Type/Home-Health-Agency-HHA-Center.html.
B. CY 2016 HH PPS Case-Mix Weights and Reduction to the National,
Standardized 60-day Episode Payment Rate to Account for Nominal Case-
Mix Growth
1. CY 2016 HH PPS Case-Mix Weights
For CY 2014, as part of the rebasing effort mandated by the
Affordable Care Act, we reset the HH PPS case-mix weights, lowering the
average case-mix weight to 1.0000. To lower the HH PPS case-mix weights
to 1.0000, each HH PPS case-mix weight was decreased by the same factor
(1.3464), thereby maintaining the same relative values between the
weights. This ``resetting'' of the HH PPS case-mix weights was done in
a budget neutral manner by inflating the national, standardized 60-day
episode rate by the same factor (1.3464) that was used to decrease the
weights. For CY 2015, we finalized a policy to annually recalibrate the
HH PPS case-mix 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 2016, we propose to 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 proposed CY 2016 HH PPS case-mix weights, we used
CY 2014 home health claims data (as of December 31, 2014) with linked
OASIS data. For this CY 2016 HH PPS final rule, we used CY 2014 home
health claims data (as of June 30, 2015) with linked OASIS data to
generate the final CY 2016 HH PPS case-mix weights. These data are the
most current and complete data available at this time. The tables below
have been revised to reflect the results using the updated data. The
process we used to calculate the HH PPS case-mix weights are outlined
below.
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 Bureau of Labor
Statistics national hourly wage (covering May 2014) plus fringe rates
(covering December 2014) 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 2014 data, are shown in
Table 3. The points for the clinical variables are added together to
determine an episode's clinical score. The points for the functional
variables are added together to determine an episode's functional
score.
[[Page 68630]]
[GRAPHIC] [TIFF OMITTED] TR05NO15.000
[[Page 68631]]
[GRAPHIC] [TIFF OMITTED] TR05NO15.001
[[Page 68632]]
[GRAPHIC] [TIFF OMITTED] TR05NO15.002
[[Page 68633]]
[GRAPHIC] [TIFF OMITTED] TR05NO15.003
In updating the four-equation model for CY 2016 using 2014 data
(the last update to the four-equation model for CY 2015 used 2013
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 2013 and 2014. The CY 2016 four-equation model resulted in
124 point-giving variables being used in the model (as compared to the
120 point-giving variables for the 2015 recalibration). There were
eight variables that were added to the model and four variables that
were dropped from the model due to the absence of additional resources
associated with the variable. The points for 24 variables increased in
the CY 2016 four-equation model and the points for 38 variables
decreased in the CY 2016 4-equation model. There were 54 variables with
the same point values.
Step 2: Re-define the clinical and functional thresholds so they
are reflective of the new points associated with the CY 2016 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:
In updating the four-equation model for CY 2016 using 2014 data
(the last update to the four-equation model for CY 2015 used 2013
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 2013 and 2014. The CY 2016 four-equation model resulted in
124 point-giving variables being used in the model (as compared to the
120 point-giving variables for the 2015 recalibration). There were
eight variables that were added to the model and four variables that
were dropped from the model due to the absence of additional resources
associated with the variable. The points for 24 variables increased in
the CY 2016 four-equation model and the points for 38 variables
decreased in the CY 2016 4-equation model. There were 54 variables with
the same point values.
Step 2: Re-define the clinical and functional thresholds so they
are reflective of the new points associated with the CY 2016 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.
We then 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.\1\ Also, we looked at the average resource use associated with
each clinical and functional score and used that to guide where we
placed our thresholds. We tried to group 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 of the CY 2016 four-equation model points are
shown in Table 4.
---------------------------------------------------------------------------
\1\ For Step 1, 54% of episodes were in the medium functional
level (All with score 15). For Step 2.1, 77.2% of episodes were in
the low functional level (Most with score 2 and 4). For Step 2.2,
67.1% of episodes were in the low functional level (All with score
0). For Step 3, 60.9% of episodes were in the medium functional
level (Most with score 10). For Step 4, 49.8% of episodes were in
the low functional level (Most with score 2).
[[Page 68634]]
Table 4--CY 2016 Clinical and Functional Thresholds
--------------------------------------------------------------------------------------------------------------------------------------------------------
1st and 2nd Episodes 3rd+ Episodes All episodes
-------------------------------------------------------------------------------
0 to 13 14 to 19 0 to 13 14 to 19 20+ therapy
therapy visits therapy visits therapy visits therapy visits visits
--------------------------------------------------------------------------------------------------------------------------------------------------------
Grouping Step: 1 2.1 3 2.2 4
Equation(s) used to calculate points: (see Table 3)..................... 1 2 3 4 (2&4)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Dimension................................. Severity Level..............
Clinical.................................. C1.......................... 0 to 1 0 to 1 0 0 to 3 0 to 3
C2.......................... 2 to 3 2 to 7 1 4 to 12 4 to 16
C3.......................... 4+ 8+ 2+ 13+ 17+
Functional................................ F1.......................... 0 to 14 0 to 6 0 to 6 0 0 to 2
F2.......................... 15 7 to 13 7 to 10 1 to 7 3 to 6
F3.......................... 16+ 14+ 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 5 shows the regression coefficients for the variables in the
payment regression model updated with CY 2014 data. The R-squared value
for the payment regression model is 0.4822 (an increase from 0.4680 for
the CY 2015 recalibration).
Table 5--Payment Regression Model
------------------------------------------------------------------------
New payment
Variable description regression
coefficients
------------------------------------------------------------------------
Step 1, Clinical Score Medium........................... $24.69
Step 1, Clinical Score High............................. $59.72
Step 1, Functional Score Medium......................... $76.46
Step 1, Functional Score High........................... $114.89
Step 2.1, Clinical Score Medium......................... $68.55
Step 2.1, Clinical Score High........................... $156.28
Step 2.1, Functional Score Medium....................... $34.15
Step 2.1, Functional Score High......................... $87.13
Step 2.2, Clinical Score Medium......................... $61.06
Step 2.2, Clinical Score High........................... $211.40
Step 2.2, Functional Score Medium....................... $10.90
Step 2.2, Functional Score High......................... $70.39
Step 3, Clinical Score Medium........................... $10.27
Step 3, Clinical Score High............................. $91.72
Step 3, Functional Score Medium......................... $56.53
Step 3, Functional Score High........................... $87.94
Step 4, Clinical Score Medium........................... $72.66
Step 4, Clinical Score High............................. $238.69
Step 4, Functional Score Medium......................... $15.65
Step 4, Functional Score High........................... $65.68
Step 2.1, 1st and 2nd Episodes, 14 to 19 Therapy Visits. $479.21
Step 2.2, 3rd+ Episodes, 14 to 19 Therapy Visits........ $505.35
Step 3, 3rd+ Episodes, 0-13 Therapy Visits.............. -$76.20
Step 4, All Episodes, 20+ Therapy Visits................ $930.06
Intercept............................................... $391.33
------------------------------------------------------------------------
Source: CY 2014 Medicare claims data for episodes ending on or before
December 31, 2014 (as of June 30, 2015) 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 wage-
weighted 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 weights associated with 0 to 5 therapy visits are then
increased by 3.75 percent, the weights associated with 14-15 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
[[Page 68635]]
to address MedPAC's concerns that the HH PPS overvalues therapy
episodes and undervalues non-therapy episodes and to better aligned the
case-mix weights with episode costs estimated from cost report data.\2\
---------------------------------------------------------------------------
\2\ Medicare Payment Advisory Commission (MedPAC), Report to the
Congress: Medicare Payment Policy. March 2011, P. 176.
---------------------------------------------------------------------------
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 0-5 to 14-15 therapy visits, and
from 14-15 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 0-5 therapy visits and 6
therapy visits and the increase between 6 therapy visits and 7-9
therapy visits) are constant. This interpolation is the 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 case-mix for the weights is equal to 1.0000.\3\ This last step
creates the CY 2016 case-mix weights shown in Table 6.
---------------------------------------------------------------------------
\3\ When 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.
Table 6: Final CY 2016 Case-Mix Payment Weights
----------------------------------------------------------------------------------------------------------------
Final CY 2016
Payment group Step (episode and/or therapy Clinical and functional levels (1 case-mix
visit ranges) = Low; 2 = Medium; 3= High) weights
----------------------------------------------------------------------------------------------------------------
10111........................ 1st and 2nd Episodes, 0 to 5 C1F1S1 0.5908
Therapy Visits.
10112........................ 1st and 2nd Episodes, 6 C1F1S2 0.7197
Therapy Visits.
10113........................ 1st and 2nd Episodes, 7 to 9 C1F1S3 0.8485
Therapy Visits.
10114........................ 1st and 2nd Episodes, 10 C1F1S4 0.9774
Therapy Visits.
10115........................ 1st and 2nd Episodes, 11 to C1F1S5 1.1063
13 Therapy Visits.
10121........................ 1st and 2nd Episodes, 0 to 5 C1F2S1 0.7062
Therapy Visits.
10122........................ 1st and 2nd Episodes, 6 C1F2S2 0.8217
Therapy Visits.
10123........................ 1st and 2nd Episodes, 7 to 9 C1F2S3 0.9372
Therapy Visits.
10124........................ 1st and 2nd Episodes, 10 C1F2S4 1.0527
Therapy Visits.
10125........................ 1st and 2nd Episodes, 11 to C1F2S5 1.1681
13 Therapy Visits.
10131........................ 1st and 2nd Episodes, 0 to 5 C1F3S1 0.7643
Therapy Visits.
10132........................ 1st and 2nd Episodes, 6 C1F3S2 0.8832
Therapy Visits.
10133........................ 1st and 2nd Episodes, 7 to 9 C1F3S3 1.0021
Therapy Visits.
10134........................ 1st and 2nd Episodes, 10 C1F3S4 1.1210
Therapy Visits.
10135........................ 1st and 2nd Episodes, 11 to C1F3S5 1.2399
13 Therapy Visits.
10211........................ 1st and 2nd Episodes, 0 to 5 C2F1S1 0.6281
Therapy Visits.
10212........................ 1st and 2nd Episodes, 6 C2F1S2 0.7690
Therapy Visits.
10213........................ 1st and 2nd Episodes, 7 to 9 C2F1S3 0.9098
Therapy Visits.
10214........................ 1st and 2nd Episodes, 10 C2F1S4 1.0507
Therapy Visits.
10215........................ 1st and 2nd Episodes, 11 to C2F1S5 1.1915
13 Therapy Visits.
10221........................ 1st and 2nd Episodes, 0 to 5 C2F2S1 0.7435
Therapy Visits.
10222........................ 1st and 2nd Episodes, 6 C2F2S2 0.8710
Therapy Visits.
10223........................ 1st and 2nd Episodes, 7 to 9 C2F2S3 0.9985
Therapy Visits.
10224........................ 1st and 2nd Episodes, 10 C2F2S4 1.1259
Therapy Visits.
10225........................ 1st and 2nd Episodes, 11 to C2F2S5 1.2534
13 Therapy Visits.
10231........................ 1st and 2nd Episodes, 0 to 5 C2F3S1 0.8016
Therapy Visits.
10232........................ 1st and 2nd Episodes, 6 C2F3S2 0.9325
Therapy Visits.
10233........................ 1st and 2nd Episodes, 7 to 9 C2F3S3 1.0633
Therapy Visits.
10234........................ 1st and 2nd Episodes, 10 C2F3S4 1.1942
Therapy Visits.
10235........................ 1st and 2nd Episodes, 11 to C2F3S5 1.3251
13 Therapy Visits.
10311........................ 1st and 2nd Episodes, 0 to 5 C3F1S1 0.6810
Therapy Visits.
10312........................ 1st and 2nd Episodes, 6 C3F1S2 0.8362
Therapy Visits.
10313........................ 1st and 2nd Episodes, 7 to 9 C3F1S3 0.9913
Therapy Visits.
10314........................ 1st and 2nd Episodes, 10 C3F1S4 1.1465
Therapy Visits.
10315........................ 1st and 2nd Episodes, 11 to C3F1S5 1.3017
13 Therapy Visits.
10321........................ 1st and 2nd Episodes, 0 to 5 C3F2S1 0.7964
Therapy Visits.
10322........................ 1st and 2nd Episodes, 6 C3F2S2 0.9382
Therapy Visits.
10323........................ 1st and 2nd Episodes, 7 to 9 C3F2S3 1.0800
Therapy Visits.
10324........................ 1st and 2nd Episodes, 10 C3F2S4 1.2218
Therapy Visits.
10325........................ 1st and 2nd Episodes, 11 to C3F2S5 1.3635
13 Therapy Visits.
10331........................ 1st and 2nd Episodes, 0 to 5 C3F3S1 0.8544
Therapy Visits.
10332........................ 1st and 2nd Episodes, 6 C3F3S2 0.9996
Therapy Visits.
10333........................ 1st and 2nd Episodes, 7 to 9 C3F3S3 1.1449
Therapy Visits.
10334........................ 1st and 2nd Episodes, 10 C3F3S4 1.2901
Therapy Visits.
10335........................ 1st and 2nd Episodes, 11 to C3F3S5 1.4353
13 Therapy Visits.
21111........................ 1st and 2nd Episodes, 14 to C1F1S1 1.2351
15 Therapy Visits.
21112........................ 1st and 2nd Episodes, 16 to C1F1S2 1.4323
17 Therapy Visits.
21113........................ 1st and 2nd Episodes, 18 to C1F1S3 1.6296
19 Therapy Visits.
21121........................ 1st and 2nd Episodes, 14 to C1F2S1 1.2836
15 Therapy Visits.
21122........................ 1st and 2nd Episodes, 16 to C1F2S2 1.4719
17 Therapy Visits.
[[Page 68636]]
21123........................ 1st and 2nd Episodes, 18 to C1F2S3 1.6601
19 Therapy Visits.
21131........................ 1st and 2nd Episodes, 14 to C1F3S1 1.3588
15 Therapy Visits.
21132........................ 1st and 2nd Episodes, 16 to C1F3S2 1.5450
17 Therapy Visits.
21133........................ 1st and 2nd Episodes, 18 to C1F3S3 1.7313
19 Therapy Visits.
21211........................ 1st and 2nd Episodes, 14 to C2F1S1 1.3324
15 Therapy Visits.
21212........................ 1st and 2nd Episodes, 16 to C2F1S2 1.5307
17 Therapy Visits.
21213........................ 1st and 2nd Episodes, 18 to C2F1S3 1.7289
19 Therapy Visits.
21221........................ 1st and 2nd Episodes, 14 to C2F2S1 1.3809
15 Therapy Visits.
21222........................ 1st and 2nd Episodes, 16 to C2F2S2 1.5702
17 Therapy Visits.
21223........................ 1st and 2nd Episodes, 18 to C2F2S3 1.7595
19 Therapy Visits.
21231........................ 1st and 2nd Episodes, 14 to C2F3S1 1.4560
15 Therapy Visits.
21232........................ 1st and 2nd Episodes, 16 to C2F3S2 1.6434
17 Therapy Visits.
21233........................ 1st and 2nd Episodes, 18 to C2F3S3 1.8307
19 Therapy Visits.
21311........................ 1st and 2nd Episodes, 14 to C3F1S1 1.4569
15 Therapy Visits.
21312........................ 1st and 2nd Episodes, 16 to C3F1S2 1.6902
17 Therapy Visits.
21313........................ 1st and 2nd Episodes, 18 to C3F1S3 1.9234
19 Therapy Visits.
21321........................ 1st and 2nd Episodes, 14 to C3F2S1 1.5053
15 Therapy Visits.
21322........................ 1st and 2nd Episodes, 16 to C3F2S2 1.7297
17 Therapy Visits.
21323........................ 1st and 2nd Episodes, 18 to C3F2S3 1.9540
19 Therapy Visits.
21331........................ 1st and 2nd Episodes, 14 to C3F3S1 1.5805
15 Therapy Visits.
21332........................ 1st and 2nd Episodes, 16 to C3F3S2 1.8028
17 Therapy Visits.
21333........................ 1st and 2nd Episodes, 18 to C3F3S3 2.0252
19 Therapy Visits.
22111........................ 3rd+ Episodes, 14 to 15 C1F1S1 1.2722
Therapy Visits.
22112........................ 3rd+ Episodes, 16 to 17 C1F1S2 1.4571
Therapy Visits.
22113........................ 3rd+ Episodes, 18 to 19 C1F1S3 1.6419
Therapy Visits.
22121........................ 3rd+ Episodes, 14 to 15 C1F2S1 1.2877
Therapy Visits.
22122........................ 3rd+ Episodes, 16 to 17 C1F2S2 1.4746
Therapy Visits.
22123........................ 3rd+ Episodes, 18 to 19 C1F2S3 1.6615
Therapy Visits.
22131........................ 3rd+ Episodes, 14 to 15 C1F3S1 1.3721
Therapy Visits.
22132........................ 3rd+ Episodes, 16 to 17 C1F3S2 1.5539
Therapy Visits.
22133........................ 3rd+ Episodes, 18 to 19 C1F3S3 1.7357
Therapy Visits.
22211........................ 3rd+ Episodes, 14 to 15 C2F1S1 1.3589
Therapy Visits.
22212........................ 3rd+ Episodes, 16 to 17 C2F1S2 1.5483
Therapy Visits.
22213........................ 3rd+ Episodes, 18 to 19 C2F1S3 1.7378
Therapy Visits.
22221........................ 3rd+ Episodes, 14 to 15 C2F2S1 1.3743
Therapy Visits.
22222........................ 3rd+ Episodes, 16 to 17 C2F2S2 1.5658
Therapy Visits.
22223........................ 3rd+ Episodes, 18 to 19 C2F2S3 1.7573
Therapy Visits.
22231........................ 3rd+ Episodes, 14 to 15 C2F3S1 1.4587
Therapy Visits.
22232........................ 3rd+ Episodes, 16 to 17 C2F3S2 1.6452
Therapy Visits.
22233........................ 3rd+ Episodes, 18 to 19 C2F3S3 1.8316
Therapy Visits.
22311........................ 3rd+ Episodes, 14 to 15 C3F1S1 1.5722
Therapy Visits.
22312........................ 3rd+ Episodes, 16 to 17 C3F1S2 1.7670
Therapy Visits.
22313........................ 3rd+ Episodes, 18 to 19 C3F1S3 1.9619
Therapy Visits.
22321........................ 3rd+ Episodes, 14 to 15 C3F2S1 1.5876
Therapy Visits.
22322........................ 3rd+ Episodes, 16 to 17 C3F2S2 1.7845
Therapy Visits.
22323........................ 3rd+ Episodes, 18 to 19 C3F2S3 1.9815
Therapy Visits.
22331........................ 3rd+ Episodes, 14 to 15 C3F3S1 1.6721
Therapy Visits.
22332........................ 3rd+ Episodes, 16 to 17 C3F3S2 1.8639
Therapy Visits.
22333........................ 3rd+ Episodes, 18 to 19 C3F3S3 2.0557
Therapy Visits.
30111........................ 3rd+ Episodes, 0 to 5 Therapy C1F1S1 0.4758
Visits.
30112........................ 3rd+ Episodes, 6 Therapy C1F1S2 0.6351
Visits.
30113........................ 3rd+ Episodes, 7 to 9 Therapy C1F1S3 0.7944
Visits.
30114........................ 3rd+ Episodes, 10 Therapy C1F1S4 0.9536
Visits.
30115........................ 3rd+ Episodes, 11 to 13 C1F1S5 1.1129
Therapy Visits.
30121........................ 3rd+ Episodes, 0 to 5 Therapy C1F2S1 0.5611
Visits.
30122........................ 3rd+ Episodes, 6 Therapy C1F2S2 0.7064
Visits.
30123........................ 3rd+ Episodes, 7 to 9 Therapy C1F2S3 0.8518
Visits.
30124........................ 3rd+ Episodes, 10 Therapy C1F2S4 0.9971
Visits.
30125........................ 3rd+ Episodes, 11 to 13 C1F2S5 1.1424
Therapy Visits.
30131........................ 3rd+ Episodes, 0 to 5 Therapy C1F3S1 0.6085
Visits.
30132........................ 3rd+ Episodes, 6 Therapy C1F3S2 0.7613
Visits.
30133........................ 3rd+ Episodes, 7 to 9 Therapy C1F3S3 0.9140
Visits.
30134........................ 3rd+ Episodes, 10 Therapy C1F3S4 1.0667
Visits.
30135........................ 3rd+ Episodes, 11 to 13 C1F3S5 1.2194
Therapy Visits.
30211........................ 3rd+ Episodes, 0 to 5 Therapy C2F1S1 0.4913
Visits.
30212........................ 3rd+ Episodes, 6 Therapy C2F1S2 0.6648
Visits.
30213........................ 3rd+ Episodes, 7 to 9 Therapy C2F1S3 0.8383
Visits.
30214........................ 3rd+ Episodes, 10 Therapy C2F1S4 1.0118
Visits.
30215........................ 3rd+ Episodes, 11 to 13 C2F1S5 1.1854
Therapy Visits.
[[Page 68637]]
30221........................ 3rd+ Episodes, 0 to 5 Therapy C2F2S1 0.5766
Visits.
30222........................ 3rd+ Episodes, 6 Therapy C2F2S2 0.7362
Visits.
30223........................ 3rd+ Episodes, 7 to 9 Therapy C2F2S3 0.8957
Visits.
30224........................ 3rd+ Episodes, 10 Therapy C2F2S4 1.0553
Visits.
30225........................ 3rd+ Episodes, 11 to 13 C2F2S5 1.2148
Therapy Visits.
30231........................ 3rd+ Episodes, 0 to 5 Therapy C2F3S1 0.6241
Visits.
30232........................ 3rd+ Episodes, 6 Therapy C2F3S2 0.7910
Visits.
30233........................ 3rd+ Episodes, 7 to 9 Therapy C2F3S3 0.9579
Visits.
30234........................ 3rd+ Episodes, 10 Therapy C2F3S4 1.1249
Visits.
30235........................ 3rd+ Episodes, 11 to 13 C2F3S5 1.2918
Therapy Visits.
30311........................ 3rd+ Episodes, 0 to 5 Therapy C3F1S1 0.6143
Visits.
30312........................ 3rd+ Episodes, 6 Therapy C3F1S2 0.8058
Visits.
30313........................ 3rd+ Episodes, 7 to 9 Therapy C3F1S3 0.9974
Visits.
30314........................ 3rd+ Episodes, 10 Therapy C3F1S4 1.1890
Visits.
30315........................ 3rd+ Episodes, 11 to 13 C3F1S5 1.3806
Therapy Visits.
30321........................ 3rd+ Episodes, 0 to 5 Therapy C3F2S1 0.6996
Visits.
30322........................ 3rd+ Episodes, 6 Therapy C3F2S2 0.8772
Visits.
30323........................ 3rd+ Episodes, 7 to 9 Therapy C3F2S3 1.0548
Visits.
30324........................ 3rd+ Episodes, 10 Therapy C3F2S4 1.2324
Visits.
30325........................ 3rd+ Episodes, 11 to 13 C3F2S5 1.4100
Therapy Visits.
30331........................ 3rd+ Episodes, 0 to 5 Therapy C3F3S1 0.7470
Visits.
30332........................ 3rd+ Episodes, 6 Therapy C3F3S2 0.9320
Visits.
30333........................ 3rd+ Episodes, 7 to 9 Therapy C3F3S3 1.1170
Visits.
30334........................ 3rd+ Episodes, 10 Therapy C3F3S4 1.3020
Visits.
30335........................ 3rd+ Episodes, 11 to 13 C3F3S5 1.4870
Therapy Visits.
40111........................ All Episodes, 20+ Therapy C1F1S1 1.8268
Visits.
40121........................ All Episodes, 20+ Therapy C1F2S1 1.8484
Visits.
40131........................ All Episodes, 20+ Therapy C1F3S1 1.9176
Visits.
40211........................ All Episodes, 20+ Therapy C2F1S1 1.9272
Visits.
40221........................ All Episodes, 20+ Therapy C2F2S1 1.9488
Visits.
40231........................ All Episodes, 20+ Therapy C2F3S1 2.0180
Visits.
40311........................ All Episodes, 20+ Therapy C3F1S1 2.1567
Visits.
40321........................ All Episodes, 20+ Therapy C3F2S1 2.1784
Visits.
40331........................ All Episodes, 20+ Therapy C3F3S1 2.2475
Visits.
----------------------------------------------------------------------------------------------------------------
To ensure the changes to the HH PPS case-mix weights are
implemented in a budget neutral manner, we apply a case-mix budget
neutrality factor to the CY 2016 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 2016 HH PPS grouper and case-mix weights (developed using
CY 2014 claims data) are applied to CY 2014 utilization (claims) data
to total payments when the CY 2015 HH PPS grouper and case-mix weights
(developed using CY 2013 claims data) are applied to CY 2014
utilization data. Using CY 2014 claims data as of December 31, 2014, we
calculated the case-mix budget neutrality factor for CY 2016 to be
1.0141. Updating our analysis with 2014 claims data as of June 30,
2015, we calculated a final case-mix budget neutrality factor for CY
2016 of 1.0187.
The following is a summary of the comments and our responses to
comments on the CY 2016 case-mix weights.
Comment: One commenter noted that the case-mix weights were
increased 3.75 percent for 0-5 therapy visits, decreased by 2.5 percent
for 14-15 therapy visits, and decreased 5 percent for 20+ therapy
visits to address MedPAC's concerns that the therapy episodes are over-
valued and non-therapy episodes are undervalued, but stated that a
therapist's salary and benefits costs are higher than those same costs
for nursing, due to the overall market for therapists and the greater
difficulty in retaining them in the home health environment versus
other health care settings. Additionally, the commenter noted that
patients requiring 20+ therapy visits typically have functional
deficits in multiple domains, requiring the expertise of multiple
therapy disciplines (PT/OT/ST) to address, justifying the higher case
mix.
Response: As we noted in the CY 2015 HH PPS final rule, these
adjustments to the case-mix weights are the same adjustments finalized
in the CY 2012 HH PPS final rule (76 FR 68557). As the commenter
correctly noted, these adjustments were made, in part, to address
MedPAC's concerns that the HH PPS overvalues therapy episodes and
undervalues non-therapy episodes (March 2011 MedPAC Report to the
Congress: Medicare Payment Policy, p.176). However, we further note
that these adjustments also better aligned the case-mix weights with
episode costs estimated from cost report data (79 FR 66061).
Comment: One commenter stated that they are pleased that CMS used
updated claims and cost data to recalibrate all of the case-mix
weights. However, the commenter went on to state that they were
somewhat confused that high-therapy episodes tend to get increased
case-mix weights, even though CMS has stated its intention that therapy
visit volume should have less impact on the weights. One commenter
noted that CMS did not provide sufficient transparency of the details
and methods used to recalibrate the HH PPS case-mix weights in its
discussion in the proposed rule. In addition, CMS provided little
justification for recalibrating the case-mix weights just 1
[[Page 68638]]
year following the recalibration of case-mix weights in CY 2015 and a
mere 3 years since the recalibration for the CY 2012 HH PPS final rule.
The commenter noted that this proposed recalibration reduces the case
weights for 117 HHRGs or 76 percent of the 153 HHRGs. Another commenter
stated that analysis of the case mix weight changes from 2014 through
2016 indicates an average decrease of 1.52 percent in each HIPPS code
weight. The commenter stated that they believe that these changes alone
have produced an overall decrease in the case mix scoring of episodes
since 2013. Specifically, applying the 2016 case mix weights to the
HHA's 2014 episodes would produce a decrease in overall case mix weight
of 4.7 percent and from 2014-2016, the overall case-mix weight was
reduced by 7.2 percent for certain HIPPS codes.
Response: As stated in the CY 2015 HH PPS final rule, 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). We encourage commenters to refer to the CY
2012 HH PPS proposed and final rules (76 FR 40988 and 76 FR 68526) and
the CY 2012 technical report on our home page at: https://www.cms.gov/Center/Provider-Type/Home-Health-Agency-HHA-Center.html for additional
information about the recalibration methodology.
As we noted in the CY 2015 HH PPS final rule (79 FR 66067),
decreases in the case-mix weights for the low therapy case-mix groups
and increases in the case-mix weights for the high therapy case-mix
groups is generally attributable to shifts away from the use of home
health aides and a shift to either more nursing or more therapy care
across all therapy groups. While some of the low therapy groups did add
more skilled nursing visits, most of the high therapy groups added more
occupational therapy (OT) and speech-language pathology (SLP), which
have substantially higher Bureau of Labor Statistics (BLS) average
hourly wage values compared to skilled nursing. In addition, while the
average number of total visits per episode has decreased overall, it
decreased disproportionately more for the no/low therapy case-mix
groups. These utilization changes result in changes to the weights
observed by the commenter, specifically, the decreases in the case-mix
weights for the low or no therapy groups and increases in the case-mix
weights for the high therapy groups.
Comparing the final CY 2016 HH PPS case-mix weights (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 4 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 decreases in total payments
under the HH PPS, as result of the case-mix recalibration, by applying
a budget neutrality factor to the national, standardized 60-day episode
payment rate. For CY 2016, the case-mix budget neutrality factor will
be 1.87 percent as described above. For CY 2015, the case-mix budget
neutrality factor was 3.66 percent (79 FR 66088). In addition, when the
CY 2014 case-mix weights were reset to 1.0000 by decreasing the case-
mix weights by 1.3464, we correspondingly increased the national,
standardized 60-day episode payment rate by the same factor (1.3464) as
part of the rebasing of the HH PPS payment rates required by the
Affordable Care Act (78 FR 72273). 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.
Final Decision: We will finalize the recalibration of the HH PPS
case-mix weights as proposed. The CY 2016 scores for the case-mix
variables, the clinical and functional thresholds, and the case-mix
weights were developed using complete CY 2014 claims data as of June
30, 2015. 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 2016 HH PPS
proposed rule.
2. Reduction to the National, Standardized 60-day Episode Payment Rate
to Account for Nominal Case-Mix Growth
Section 1895(b)(3)(B)(iv) of the Act gives the Secretary the
authority to implement payment reductions for nominal case-mix growth
(that is, case-mix growth unrelated to changes in patient acuity).
Previously, we accounted for nominal case-mix growth through case-mix
reductions implemented from 2008 through 2013 (76 FR 68528-68543). As
stated in the 2013 final rule, the goal of the reductions for nominal
case-mix growth is to better align payments with real changes in
patient severity (77 FR 67077). Our analysis of data from CY 2000
through CY 2010 found that only 15.97 percent of the total case-mix
change was real and 84.03 percent of total case-mix change was nominal
(77 FR 41553). In the CY 2015 HH PPS final rule (79 FR 66032), we
estimated that total case-mix increased by 2.76 percent between CY 2012
and CY 2013 and in applying the 15.97 percent estimate of real case-mix
growth to the estimate of total case-mix growth, we estimated nominal
case-mix growth to be 2.32 percent (2.76 - (2.76 x 0.1597)). However,
for 2015, we did not implement a reduction to the 2015 national,
standardized 60-day episode payment amount to account for nominal case-
mix growth, but stated that we would continue to monitor case-mix
growth and may consider proposing nominal case-mix reductions in the
future. Since the publication of 2015 HH PPS final rule (79 FR 66032),
MedPAC reported on their assessment of the impact of the mandated
rebasing adjustments on quality of and beneficiary access to home
health care as required by section 3131(a) of the Affordable Care Act.
As noted in section III.A.2 of the proposed rule, MedPAC concluded that
quality of care and beneficiary access to care are unlikely to be
negatively affected by the rebasing adjustments. For the proposed rule,
we further estimated that case-mix increased by 1.41 percent between CY
2013 and CY 2014 using preliminary CY 2014 home health claims data (as
of December 31, 2014) with linked OASIS data. In applying the 15.97
percent estimate of real case-mix growth to the total estimated case-
mix growth from CY 2013 to CY 2014 (1.41 percent), we estimated that
nominal case-mix growth to be 1.18 percent (1.41 - (1.41 x 0.1597)).
Given the observed nominal case-mix growth of 2.32 percent in 2013 and
1.18 percent in 2014, we estimated that the reduction to offset the
nominal case-mix growth for these 2 years would be 3.41 percent (1 - 1/
(1.0232 x 1.0118) = 0.0341).
We proposed to implement this 3.41 percent reduction in equal
increments over 2 years. Specifically, we proposed to apply a 1.72
percent (1 - 1/(1.0232
[[Page 68639]]
x 1.0118) 1/2 = 1.72 percent) reduction to the national,
standardized 60-day episode payment rate each year for 2 years, CY 2016
and CY 2017, under the ongoing authority of section 1895(b)(3)(B)(iv)
of the Act. In the proposed rule, we noted that proposed reductions to
the national, standardized 60-day episode payment rate in CY 2016 and
in CY 2017 to account for nominal case-mix growth are separate from the
rebasing adjustments finalized in CY 2014 under section
1895(b)(3)(A)(iii) of the Act, which were calculated using CY 2012
claims and CY 2011 HHA cost report data (which was the most current,
complete data at the time of the CY 2014 HH PPS proposed and final
rules).
In updating our analysis for the final rule and in reassessing our
methodology in response to comments, as discussed further below in this
section, we used a more familiar methodology (one used in the past) to
measure case-mix growth. We first calculated the average case-mix index
for 2012, 2013, and 2014 before comparing the average case-mix index
for CY 2012 to CY 2013 and the average case-mix index for CY 2013 to CY
2014 to calculate the total case-mix growth between the years. To make
the comparison between the 2013 average case-mix index and the 2014
average case-mix index, we had to inflate the 2014 average case-mix
index (multiply it by 1.3464) before doing the comparison. We inflated
the 2014 average case-mix index by 1.3464 to offset the decrease by
that same factor when the CY 2014 case-mix weights were reset to 1.0000
in the CY 2014 HH PPS final rule (78 FR 72256). By first calculating
the average case-mix index for 2012, 2013, and 2014 before comparing
the average case-mix index for CY 2012 to CY 2013 and then comparing
the average case-mix index for CY 2013 to CY 2014 to calculate the
total case-mix growth between the years, we used a more familiar
methodology than what was done for the CY 2015 HH PPS final rule and
the CY 2016 HH PPS proposed rule. In those rules, we instead simulated
total payments using case-mix weights from 2 consecutive years (used to
calculate the case-mix budget neutrality factor when recalibrating the
case-mix weights) and isolated the portion of the budget neutrality
factor that was due to changes in case-mix. Calculating the average
case-mix index in a given year, and comparing indices across years,
better aligns with how CMS historically measured case-mix growth in
previous years and is a methodology that was thoroughly vetted in
previous rulemaking. In addition, we believe that this more familiar
methodology results in a more straightforward measure of case-mix
growth between 2012 and 2014, given that annual recalibration of the
case-mix weights did not begin until CY 2015.
Using this methodology, we estimate that the average case-mix for
2012 was 1.3610 and that the average case-mix for 2013 was 1.3900.\4\
Dividing the average case-mix for 2013 by the average case-mix for
2012, we obtain a total case-mix growth estimate from 2012 to 2013 of
2.13 percent (1.3900/1.3610 = 1.0213), compared to 2.76 percent in the
proposed rule. We estimate that the average case-mix for 2014 was
1.0465. We note that in 2014, we decreased all of the case-mix weights
uniformly by 1.3464. Therefore, in order to make a comparison between
the 2014 average case-mix weight and the 2013 average case-mix weight,
we multiplied the 1.0465 estimate by 1.3464 (1.0465 x 1.3464 = 1.4090).
We then divided the average case-mix for 2014 by the average case-mix
for 2013 to obtain a total case-mix growth estimate from 2013 to 2014
of 1.37 percent (1.4090/1.3900 = 1.0137), compared to 1.41 percent in
the proposed rule.
---------------------------------------------------------------------------
\4\ We include outlier episodes in the calculation along with
normal episodes and PEPs. We note that the case-mix for PEP episodes
are downward weighted based on the length of the home health
episode.
---------------------------------------------------------------------------
Using the 2.13 percent estimate of total case-mix growth between CY
2012 and CY 2013, we estimate nominal case-mix growth to be 1.79
percent (2.13 - (2.13 x 0.1597) = 1.79). Similarly, using the 1.37
percent estimate of total case-mix growth between CY 2013 and CY 2014,
we estimate nominal case-mix growth to be 1.15 percent (1.37 - (1.37 x
0.1597) = 1.15). Using the updated estimates of case-mix growth between
2012 and 2013 and between 2013 and 2014, we estimate that the reduction
to the national, standardized 60-day episode payment rate needed to
offset the nominal case-mix growth from 2012 through 2014 would be 2.88
percent (1 - 1/(1.0179 x 1.0115) = 0.0288). If we finalized the 2 year
phase-in described in the proposed rule, we would need to implement a
reduction of 1.45 percent to the national, standardized 60-day episode
payment rate each year for 2 years, CY 2016 and CY 2017, to account for
nominal case-mix growth from 2012 through 2014 (1 - 1/(1.0179 x 1.0115)
1/2 = 0.0145).
In the CY 2016 HH PPS proposed rule, we solicited comments on the
proposed reduction to the national, standardized 60-day episode payment
amount in CY 2016 and in CY 2017 to account for nominal case-mix growth
from CY 2012 through CY 2014 and the associated changes in the
regulations text at Sec. 484.220 in section VII. The following is a
summary of the comments and our responses.
Comment: MedPAC supported the proposed case-mix reductions and
stated that the Commission has long held that it is necessary for CMS
to make adjustments to account for nominal case-mix growth to prevent
overpayments.
Response: We thank MedPAC for their support.
Comment: Several commenters expressed concern with the methodology
used to determine case-mix growth from CY 2012 to CY 2014 and the
portion of such growth that is nominal versus real. Specifically,
commenters stated that the percent change in real case-mix used to
calculate the proposed nominal case-mix reductions is not reflective of
the real case-mix growth between 2012 and 2014. Commenters stated that
patients are entering into home health at a much higher acuity level
than in previous years and cited a number of statistics to support
their statements. Commenters also disagreed with the use of the percent
change in real case-mix used in the case-mix reduction calculations as
it was based on data from 2000-2010 and applied to the total case mix
growth from 2012 to 2014. They stated that no adjustments should be
considered until CMS conducts a thorough analysis of real and nominal
changes in case mix through evaluation of changes that occurred during
the actual years of concern (2012-2014) with respect to the proposed
adjustment and any adjustments that might be considered in future
years. They further stated that CMS should have the data and tools to
perform an updated analysis of the percentage of real versus nominal
case-mix growth between 2012 and 2014 and they noted that the
historical analyses conducted by CMS demonstrate that the level of
``nominal'' case mix weight change is not consistent from year to year.
While some commenters urged CMS to update its analysis to determine the
percentage of real versus nominal case-mix growth for CY 2012 through
CY 2014, other commenters stated that out of the 921 variables used in
such analyses, there are only four drivers of real case-mix growth and
implied that CMS' analysis was not reliable or comprehensive enough.
Some commenters stated that the adjustments to payments should be based
on current data informed by clinical evaluation. Finally, one commenter
stated that CMS should not implement the proposed case-mix reductions
and not propose
[[Page 68640]]
any additional case-mix reductions in the future.
Response: We believe the percent change in real case-mix used in
the case-mix reduction calculations, which is based on analysis of 2000
through 2010 data, is a stable proxy for the real case-mix growth
between 2012 and 2014. Our analysis of data has not indicated that real
case-mix change between 2012 through 2014 is greater than the change in
real case-mix between 2000 and 2010. In fact, our analysis of claims
data has shown a decrease in the number of total visits per episode
between 2012 and 2014. Furthermore, our analysis of 2012 and 2013 cost
report data showed that the cost per episode has decreased each year.
In addition, we note that there is prior precedent for applying
historical estimates of real case-mix growth on more current data to
set payment rates. In the rate year (RY) 2008 and the RY 2009 LTCH
final rules, an estimate of the percentage of real case-mix growth from
a prior time period was applied to the total case-mix growth from FY
2004 to FY 2005 and from FY2005 to FY 2006 in determining the RY 2008
and RY 2009 federal rate updates (72 FR 26889 and 73 FR 26805).
With regard to the recommendation that the estimates should be
informed by clinical evaluation, we note that CMS' case-mix change
model, developed by Abt Associates, only includes a few variables that
are derived from OASIS assessments (measures of patient living
arrangement) because the OASIS items can be affected by changes in
coding practices. It is not practical to consider other types of home
health clinical data (for example, from medical charts) in the model
given the resources available.
We note that as a result of the comments we received expressing
concerns about our methodology and questioning the case-mix growth
estimates we presented in the proposed rule, we did re-evaluate the
methodology to determine total case-mix growth and are moving forward
with a more familiar, and slightly more accurate, methodology (one used
in the past) to measure case-mix growth (as described above). The
methodology results in the calculation of a 1.45 percent reduction each
year in CY 2016 and CY 2017 to account for nominal case-mix growth from
2012 to 2014 (instead of the 1.72 percent reduction described in the CY
2016 proposed rule).
Comment: A commenter stated that their analyses suggest that all of
the historical increases have been driven by increased therapy
utilization that is, in turn, based on real needs of the patients. A
commenter stated that the technical analyses used to conclude that
case-mix increases are generally ``not real'' have been based on the
non-case-mix variables and that those non-case-mix variables were found
to have a lower explanatory value. The commenter expressed concerns
with CMS' exclusion of the therapy variables in the model to assess
real case-mix, stating that those have the highest explanatory power.
The commenter asked that CMS address this question in the final rule to
better inform their understanding of its conclusions as to how ``real''
versus ``nominal'' determinations are made.
Response: The models to assess real and nominal case-mix growth
were intended to analyze changes in case-mix over time and do not
distinguish whether these changes are due to increases in therapy use
or other factors. We do not believe that it would be appropriate to
include utilization-related variables, such as the number of therapy
visits, as predictors in the model, as such variables are provider-
determined. In addition, the goal of these analyses was to examine
changes in measures of patient acuity that are not affected by any
changes in provider coding practices. For example, the models do
incorporate information about change in the types of patients more
likely to use therapy, such as post-acute joint replacement patients.
We encourage commenters to review the Analysis of 2000-2009 Home Health
Case-Mix Change Report, available on the HHA center page at: https://www.cms.gov/Center/Provider-Type/Home-Health-Agency-HHA-Center.html, in
order to better understand the models used to assess real and nominal
case-mix growth.
Comment: A number of commenters encouraged CMS to seek payment
system reforms that are value-based rather than implementing payment
reductions.
Response: The Home Health Value-Based Purchasing (HHVBP) model will
be implemented January 1, 2016, as described in section IV of this
final rule. However, the reductions to account for nominal case-mix
growth are necessary to prevent overpayments due to coding practices
that led to increases in payment that are not related to real increases
in patient acuity.
Comment: Commenters referenced section 1895(b)(3)(B)(iv) of the
Act, stating that there has not been an increase in aggregate payments
that would justify the proposed reductions, and that CMS should
withdraw its proposal. Commenters stated that there was a decrease in
spending from 2010 through 2013 and questioned how nominal case-mix
growth could have increased during the time period. Another commenter
stated that Medicare data for 2012 to 2014 appear to indicate that the
per episode payment during this period actually fell below the level
that would have occurred as a result of any up-coding even though CMS'
estimates case mix up-coding occurred. Commenters stated that no
payment reductions should be implemented unless CMS could demonstrate
that Medicare spending on home health services exceeded the
Congressional Budget Office's (CBO) forecasted spending.
Response: We have no statutory authority to consider the
relationship of CBO projections to home health outlays when setting the
HH PPS payment rates. The Secretary's authority to respond to nominal
coding change is set out at section 1895(b)(3)(B)(iv) of the Act. In
addition, the reference to ``a change in aggregate payments'' in that
provision does not mean that overall expenditures under the HH PPS need
to increase in order to implement reductions for nominal case-mix
growth. We would also like to note that a decrease in expenditures does
not mean that there has been no case-mix growth. The case-mix growth
during this time period may have offset the decrease in expenditures
that might have otherwise occurred.
Comment: Commenters stated that the recent recalibrations have
eliminated the nominal case-mix growth observed from 2012 through 2014.
Furthermore, commenters stated that the removal of certain ICD-9-CM
codes included in the HH PPS Grouper for CY 2014 addressed, in part,
nominal case-mix growth from 2012 through 2014. Commenters stated that
CMS should fully evaluate the impact of the recalibration on case-mix
growth and publicly disclose the information.
Response: While the recent recalibrations (starting in CY 2015) may
help to reduce future nominal case-mix growth, the proposed reductions
are addressing the nominal case-mix growth from 2012 through 2014,
prior to recent efforts to annually recalibrate the HH PPS case-mix
weights. The reductions to account for nominal case-mix growth ensure
that payments are not inflated by case-mix changes unrelated to patient
severity that occurred from 2012 through 2014. This remains important
even in years when we are annually recalibrating the case-mix weights.
When CMS recalibrates the case-mix weights, a budget neutrality factor
is applied to the national, standardized 60-day episode payment rate to
ensure that
[[Page 68641]]
the recalibration of the case-mix weights result in the same aggregate
expenditures as the aggregate expenditures using the current payment
weights. For the recalibration of the weights in this rule, the budget
neutrality factor is applied to the CY 2016 national, standardized 60-
day episode payment rate to ensure that the recalibration of the case-
mix weights results in the same aggregate expenditures using the
current CY 2015 payment weights (simulating payments using CY 2014
utilization data, the most current and complete data available at this
time). If there is nominal case-mix growth in the data used to
recalibrate the case-mix weights, the nominal case-mix growth is built
into the national, standardized 60-day episode rate through the budget
neutrality factor. Thus nominal case-mix in a given year could result
in increases to the national, standardized 60-day payment rate that
would otherwise not have occurred, and future adjustments may be needed
to better align payment with patient severity.
In measuring case-mix growth, we are factoring in the removal of
the ICD-9-CM codes from the CY 2014 HH PPS Grouper into our assessment
of case-mix growth from 2013 to 2014. We used the 2013 grouper and 2013
case-mix weights to calculate the average case-mix index for 2013. Then
we used the 2014 grouper, which excluded ICD-9-CM codes found to be
rarely used and/or not associated with resource use increases, and 2014
case-mix weights, to calculate the average case-mix index for 2014.
Comparing the 2013 average case-mix index to the 2014 average case-mix
index (multiplied by 1.3464 in order to make the comparison), we
obtained an estimate of case-mix growth which factors in the removal of
the ICD-9 codes. We estimated 1.37 percent growth in total case-mix
even after taking out the ICD-9-CM codes in 2014. We will continue to
monitor case-mix growth and may examine the effects of the annual
recalibrations on future case-mix growth.
Comment: Some commenters questioned why the 2012 recalibration did
not have a budget neutrality adjustment.
Response: The 2012 recalibration was implemented in a budget
neutral manner. While a budget neutrality factor was not applied to the
national, standardized 60-day episode payment rate, we did apply a
budget neutrality factor to the weights to ensure that the
recalibration was implemented in a budget neutral manner (76 FR 68555).
Comment: A few commenters stated that CMS did not take into
consideration any probable coding effect in the transition from ICD-9-
CM to ICD-10-CM. The commenters stated that it is highly likely that a
decrease in productivity will occur due to the implementation of ICD-
10-CM. Commenters also stated that it is also highly likely that ICD-
10-CM will result in coding inaccuracies, which in turn, will lower
average case mix. The commenters encouraged CMS to reconsider this
large negative adjustment and at least postpone it until additional
information and study results are available. A commenter stated that,
in addition to ICD-10-CM implementation, HHAs are simultaneously facing
increased costs due to the implementation of the new Department of
Labor (DOL) rule on minimum wage and overtime for companionship
providers.
Response: We note that providers have been aware of the transition
from ICD-9-CM to ICD-10-CM for some time. The original implementation
date for ICD-10-CM was October 1, 2013 (74 FR 3328). Therefore, the
increase in costs due to the ICD-10-CM transition should be reflected
in the latest cost report data we examined for the rebasing monitoring
analyses in the proposed rule (that is, CY 2013 cost report data). In
that analysis we found that an even greater reduction to HHA payments
would need to occur to better align payments with costs than is
currently allowed under section 1895(b)(3)(A)(iii) of the Act (80 FR
39845). We will continue to analyze HHA Medicare cost report data and
monitor case-mix growth in future rulemaking and may consider revising
payments accordingly.
Comment: Many commenters stated that their individual home health
agencies have consistently had case-mix that was below the national
average and; therefore, would be disproportionally impacted. Commenters
suggested that CMS develop program integrity measures to address
provider-specific up-coding rather than implementing the across-the-
board reductions. A commenter suggested the program integrity efforts
could be performed through the Recovery Audit Contractors (RACs).
Another commenter suggested that CMS re[hyphen]introduce the Medicare
review procedures of the past in both the clinical and financial
operations of home health with monetary penalties and/or recoupments
based on those reviews. A third commenter stated that CMS should
continue utilizing the existing fraud and abuse prevention processes to
identify and target specific agencies that have excessive profit
margins rather than impose the across the board reductions for all
agencies and that CMS should use its enforcement authority to conduct
targeted claims reviews and deny payment for claims where the case mix
weight is not supported by the plan of care rather than cut the
national standardized episode rate for all agencies.
One commenter stated that the Medicare Administrative Contractors
(MACs) are tasked with finding instances of inappropriate coding and
that the industry should not be penalized for inappropriate coding that
the MACs were unable to find. The commenter also stated that the
proposed reductions are a ``double whammy'' because the claims that
were identified as erroneously billed have already been adjusted and
any identified overpayments have been recovered and that CMS is
attempting to recover even more than what was in error through the
proposed reductions. In addition, the commenter questioned why there
have not been more denials if there has been widespread up-coding, as
suggested by CMS' analysis.
Response: For a variety of reasons, as we have noted in previous
regulations, we have not proposed targeted reductions for nominal case-
mix change. The foremost reason is that we believe changes and
improvements in coding have been widespread, so that such targeting
would likely not separate agencies clearly into high and low coding-
change groups. When performing an independent review of our case-mix
measurement methodology, Dr. David Grabowski, Ph.D., a professor of
health care policy at Harvard Medical School, and his team agreed with
our reasons for not proposing targeted reductions, stating their
concerns about the small sample size of many agencies and their
findings of significant nominal case-mix across different classes of
agencies (please see the ``Home Health Study Report--Independent Review
of the Models to Assess Nominal Case-Mix Growth'', dated June 21, 2011,
located at: https://www.cms.gov/Center/Provider-Type/Home-Health-Agency-HHA-Center.html).
While certain commenters seem to assume that CMS can precisely
identify those agencies practicing abusive coding, we do not agree that
agency-specific case-mix levels can precisely distinguish the agencies
that engage in abusive coding from all others. System wide, case-mix
levels have risen over time throughout the country, while patient
characteristics data indicate little real change in patient severity
over time. That is, the main problem is not the level of case-mix
billed by any
[[Page 68642]]
specific HHA over a period of time, but the amount of change in the
billed case-mix weights not attributable to underlying changes in
actual patient severity. We note that we have taken various measures to
reduce payment vulnerabilities and the federal government has launched
actions to directly identify fraudulent and abusive activities.
Commenters should be aware of tip lines available that can help support
investigative efforts of the federal government. The Office of the
Inspector General, Department of Health and Human Services Web site at:
https://oig.hhs.gov/fraud/report-fraud/index.asp, provides information
about how to report fraud. Another Web site, https://www.stopmedicarefraud.gov/, is oriented to Medicare patients
and their families and provides information about recognizing fraud.
In terms of recoupments that correspond to claims denied after they
were reviewed, such would typically be reflected in the claims data we
used in our case-mix analysis. In the case where a paid-claim dispute
is still active, because the volume is so low, this data would likely
have little to no effect on our determination of nominal case-mix
growth. In addition, while we appreciate the commenters' suggestion,
targeted claim review on a scale that would be required to counteract
the broad-based uptrend in case-mix weights would be resource-intensive
and not feasible.
Comment: Some commenters stated that the additional payment
reductions for nominal case-mix growth are based on a subset of the
same factors used to determine the rebasing adjustment, such as the
``intensity of services'' factor. The commenters stated that the use of
an earlier legislative authority to justify an additional type of
reduction above the legislative cap on rebasing adjustments is contrary
to congressional intent. The commenters urged CMS to adhere to the
limits on home health rate rebasing established by Congress and
recommended that CMS evaluate the impact of the rebasing adjustments
and consult with Congress before considering additional reductions.
Other commenters stated that CMS should provide a comprehensive
explanation as to why it has not determined that the 2014 rate rebasing
effectively eliminated the impact of any alleged nominal case mix
weight change that may have occurred in 2013 and 2014. Commenters
recommended that CMS should hold off on imposing the adjustments until
the completion of the rebasing in 2017. Alternatively, the commenters
recommended phasing-in the proposed reductions over more years. A
commenter stated that this approach would be more consistent with
approaches used by the agency to implement similar rate reductions in
the IPPS and would soften the impact for those agencies whose case-mix
growth was due to changes in patient acuity. Another commenter stated
that CMS should do further analysis including validation that no
element of the proposed coding cut would duplicate reductions already
accounted for in the rebasing adjustments. Another commenter requested
that CMS provide a discussion of the interaction of the rebasing
adjustments and the recalibration of case weights on the purported
nominal case mix growth, stating that they believed that the rebasing
and recalibration of case weights addressed any nominal case mix growth
at that time.
Response: The rebasing adjustments proposed and finalized for CY
2014 through CY 2017 were based on 2011 cost report data and 2012
claims data. We compared payment and costs using 2011 cost data and
2012 claims data and therefore, we did not account for any nominal
case-mix growth from 2012 to 2014 in the methodology. Specifically,
using the 2011 cost data, we estimated a 2013 60-day episode cost by
increasing the 2011 60-day episode cost by the change in the visit data
between 2011 and 2012 and the full 2012 and 2013 market baskets. We
calculated payments by taking the 2012 national, standardized 60-day
payment amount and updating it by the average case-mix weight for 2012
as well as updating the estimate based on the payment policies
implemented in CY 2013 to estimate average payments in 2013. In the
rebasing methodology, we did not factor in future projections of
nominal case-mix growth from 2012 to 2014 in our analysis. As stated
previously, the nominal case-mix reductions would allow us to account
for nominal case-mix growth from 2012 through 2014 and mitigate
structural overpayments.
While resetting the weights to 1.0000 and doing annual
recalibrations may potentially reduce future nominal case-mix growth,
it does not offset the nominal case-mix growth previously unaccounted
for, particularly for those last few years before annual recalibrations
began. We note that there is a two year lag between the data used to
recalibrate the case-mix weights and the year that the weights will be
implemented and we use the same claims data when comparing payments and
developing the budget neutrality factor. If that utilization in the
claims data is too high, it is built into the payments for both the
future year's case mix weights and the previous year's case mix weights
on which the recalibration is based, and so that increased utilization
ends up being carried forward. In other words, the recalibration is
adjusting for the next year's case mix change as compared to the
previous one, but, barring additional action, will not (even in future
years) adjust for unaccounted nominal case mix growth already built in
to the system.
With regard to the commenters' concerns about congressional intent,
we do not believe that application of the case-mix adjustment is
contrary to congressional intent. We have received input from
stakeholders and appreciate their comments but believe our final policy
is within the authority under the statute and is consistent with
congressional intent. Moreover, this policy reflects our goal to better
align Medicare reimbursement with real changes in patient severity.
With regard to the comment about phasing-in the reductions over more
years, we note that in response to comments, we are phasing-in the
case-mix reductions over 3 years (CY 2016, CY 2017, and CY 2018) rather
than the 2 years (CY 2016 and CY 2017) described in the proposed rule.
Specifically, we will be finalizing a 0.97 percent reduction each year
in CY 2016, CY 2017, and CY 2018 to account for nominal case-mix growth
from CY 2012 through CY 2014 (1 - 1/(1.0179 x 1.0115) 1/3 =
0.0097). Iteratively implementing the case-mix reduction over three
years gives home health agencies more time to adjust to the intended
reduction of 2.88 percent than would be the case were we to account for
the nominal case-mix growth in two years.
Comment: Commenters stated that the proposed case-mix reductions
would disproportionately affect hospital-based agencies and that
hospital-based HHA's Medicare margins have been negative for the past
few years. A commenter stated that hospital-based HHAs treat more
severe patients than freestanding HHAs. Another commenter recommended
that CMS consider the differences in case-mix across the types of HHAs
and regions.
Response: Hospital-based HHAs comprise less than 10 percent of all
home health agencies in our impact analysis (see section VII of this
final rule). As stated in their March 2011 Report to Congress, MedPAC
focuses on freestanding agencies because they are the majority of
providers and because their costs do not reflect the sort of allocation
of overhead costs seen in facility-based providers' Medicare cost
reports, such as hospital-based HHA's
[[Page 68643]]
Medicare cost reports. MedPAC explains that in the case of hospitals,
which often provide services that are paid for by multiple Medicare
payment systems, measures of payments and costs for an individual
sector could become distorted because of the allocation of overhead
costs or complementarities of services. In addition, MedPAC has
reported negative Medicare margins for hospital-based HHAs since at
least 2005,\5\ even though freestanding HHA Medicare margins have been
around or over 15 percent. We question how hospital-based HHAs can
still be operating after several years with negative Medicare margins
and whether those HHAs have incentives to report negative Medicare
margins (such as cost shifting/allocation by hospitals amongst their
various units).
---------------------------------------------------------------------------
\5\ Medicare Payment Advisory Commission (MedPAC), Report to the
Congress: Medicare Payment Policy. March 2007, P. 194.
---------------------------------------------------------------------------
In their March 2009 Report to the Congress, MedPAC stated that
hospital-based providers have a lower case-mix index, which suggests
that they serve less costly patients.\6\ Similarly, we also examined
the average case-mix index for freestanding versus facility-based HHAs
in CY 2014 and found that hospital-based HHAs had an average case-mix
index that was approximately 6 percent lower than freestanding HHAs.
However, the report on the independent review of the model used to
assess real case-mix growth, performed by Dr. David Grabowski from
Harvard University, stated ``. . . when we re-ran the Abt model by
ownership type (non-profit, government, for-profit), agency type
(facility-based, freestanding), region of the country (north, south,
Midwest, west), agency size (large vs. small; based on number of
initial episodes) and agency focus (post-acute versus community-
dwelling), the results suggest that--although there is some variation--
a consistent percentage of the growth in case-mix is nominal growth. As
such, these results do not provide much support for adjusting payments
by classes of agencies.'' The ``Home Health Study Report--Independent
Review of the Models to Assess Nominal Case-Mix Growth'', dated June
21, 2011, is located on our homepage at: https://www.cms.gov/Center/Provider-Type/Home-Health-Agency-HHA-Center.html.
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\6\ Medicare Payment Advisory Commission (MedPAC), Report to the
Congress: Medicare Payment Policy. March 2009, P. 196.
---------------------------------------------------------------------------
Comment: Commenters expressed concerns with the impact of the
proposed reductions on HHA margins and the financial viability of HHAs.
Commenters stated that CMS estimated that 43 percent of all HHAs would
face negative margins by 2017 with the impact of rebasing and the
annual productivity adjustment and provided other information on
margins. Commenters stated that a recent analysis by NAHC indicates
that the percentage of impacted HHAs is now forecasted at 53.71 percent
by 2017 and that, with the addition of the case mix weight adjustment
proposed by CMS, some states will be impacted to a much higher degree.
Some other commenters stated that analysis conducted by Avalere Health
determined that 45.3 percent of all HHAs nationwide will operate at a
loss by the end of 2017. A commenter stated the MedPAC Medicare Margin
estimate is not intended to serve as a measure of home health agencies'
profit/loss, but is often interpreted as such, and an HHA's overall
margin (rather than just the Medicare margin) is a standard measure of
a home health company's bottom line/profit (or loss, as applicable). A
few commenters stated that policymakers may want to consider providers'
overall margins, as well as the MedPAC Medicare margin, when
contemplating changes to home health reimbursement. A commenter stated
that CMS should accurately account for the current costs of providing
HH services to Medicare beneficiaries and to offer HH agencies a fair
opportunity to generate a margin needed to make the ongoing investments
that are necessary to maintain and improve patient care.
Response: In the CY 2014 final rule, we estimated that
approximately 40 percent of providers would have negative margins in CY
2017 and that of the 40 percent of providers predicted to have negative
margins, 83 percent of these providers already reported negative
margins in 2011. In their March 2015 Report to the Congress, MedPAC
estimates that the Medicare margins for freestanding agencies averaged
12.7 percent in 2013 and averaged 17 percent between 2001 and 2013. The
Commission estimates that the Medicare margin for 2015 will be 10.3
percent. In addition, as mandated in section 3131(a) of the Affordable
Care Act, MedPAC conducted a study on the rebasing implementation,
which included an impact analysis on access to care, and submitted a
Report to Congress on their findings. MedPAC's Report to Congress noted
that the rebasing adjustments are partially offset by the payment
update each year and across all four years of the phase-in of the
rebasing adjustments the cumulative net reduction would equal about 2
percent. MedPAC concluded that, as a result of the payment update
offsets to the rebasing adjustments, HHA margins are likely to remain
high under the current rebasing policy and quality of care and
beneficiary access to care are unlikely to be negatively affected.
Furthermore, in their 2013 Report to Congress, MedPAC stated ``low
cost growth or no cost growth has been typical for home health care,
and in some years we have observed a decline in cost per episode. The
ability of HHAs to keep costs low has contributed to the high margins
under the Medicare PPS.'' Our analysis of 2012 and 2013 cost report
data supports MedPAC's statement about low or no cost growth and
suggests that the cost of 60 day home health episodes has decreased
since 2011. In the CY 2014 final rule, we estimated the cost of a 60-
day episode in 2011 to be $2,453.71 using CY 2011 Medicare claims data
and 2011 Medicare cost report data (78 FR 72277). In the CY 2015
proposed rule, we estimated the cost of a 60-day episode in 2012 to be
$2,413.82 using CY 2012 Medicare claims data and FY 2012 Medicare cost
report data (79 FR 38371). In the CY 2016 proposed rule, we estimated
the cost of a 60-day episode in 2013 to be $2,402.11 using CY 2013
Medicare claims data and FY 2013 Medicare cost report data (80 FR
39846).
In addition, we note that in their 2013 Report to Congress, MedPAC
stated that during the interim payment system (1997-2000), when
payments dropped by about 50 percent in two years, many agencies exited
the program. However, new agencies entered the program (about 200 new
agencies a year) and existing agencies expanded their service areas to
enter markets left by exiting agencies. This is due in part to the low
capital requirements for home health care services that allow the
industry to react rapidly when the supply of agencies changes or
contracts. Reviews of access found that access to care remained
adequate during this period despite a substantial decline in the number
of agencies (Liu et al. 2003). In summary, MedPAC's past reviews of
access to home health care found that access generally remained
adequate during periods of substantial decline in the number of
agencies. MedPAC stated that this is due in part to the low capital
requirements for home health care services that allow the industry to
react rapidly when the supply of agencies changes or contracts. As
described in section III.A.3 of the CY 2016 proposed rule, the number
of HHAs billing Medicare for home health services in CY 2013 was
11,889, or over 80 percent higher than the 6,511 HHAs billing Medicare
for home health services in 2001. Even if some HHAs were to exit
[[Page 68644]]
the program due to possible reimbursement concerns, we would expect the
home health market to remain robust (80 FR 39846).
With regard to the comments about the overall margin, we note that
as stated in the CY 2014 final rule, Medicare has never set payments so
as to cross-subsidize other payers. Indeed, section 1861(v)(1)(A) of
the Act states ``under the methods of determining costs, the necessary
costs of efficiently delivering covered services to individuals covered
by the insurance programs established by this title will not be borne
by individuals not so covered, and the costs with respect to
individuals not so covered will not be borne by such insurance
programs.'' As MedPAC stated in its March 2011 Report to Congress,
cross-subsidization is not advisable for two significant reasons:
``Raising Medicare rates to supplement low Medicaid payments would
result in poorly targeted subsidies. Facilities with high shares of
Medicare payments--presumably the facilities that need revenues the
least--would receive the most in subsidies from the higher Medicare
payments, while facilities with low Medicare shares--presumably the
facilities with the greatest need--would receive the smallest
subsidies. Finally, increased Medicare payment rates could encourage
states to further reduce their Medicaid payments and, in turn, create
pressure to raise Medicare rates'' (78 FR 72284).
Comment: A commenter stated that the proposed payment rate
reductions will create job losses, particularly for people in education
and quality positions. Commenters expressed concerns that the proposed
rate reductions may create instability within the industry and impact
access to care, particularly in underserved communities or for patients
with higher cost or more complex care needs. Commenters also stated
that the proposed rate reductions will have a significant impact on
those home health agencies that serve as the safety-net providers for
their communities and another commenter stated that the proposed cuts
will threaten access to care in rural areas stating that patients in
rural areas tend to be sicker, older, poorer, and require more complex
care than their urban counterparts. A commenter urge CMS to eliminate
the proposed case mix cut pending a detailed analysis utilizing current
data and incorporating an assessment of the impact of such an
additional cut on Medicare beneficiaries as well as the rural, small,
and other HHAs who serve them.
Response: We do not expect the payment reductions for nominal case-
mix growth to have a significant impact, particularly given MedPAC's
projected margins for 2015; however, we will continue to monitor for
unintended consequences. As noted above, we are phasing-in the
reductions over three years, rather than two years as described in the
proposed rule. Iteratively implementing the case-mix reduction over
three years gives home health agencies more time to adjust to the
intended reduction of 2.88 percent than would be the case were we to
account for the nominal case-mix growth in two years.
In addition, as described in the CY 2016 proposed rule, CMS has
awarded a follow-on contract to Abt Associates to further explore
margin differences across patient characteristics and possible payment
methodology changes suggested by the results of the home health study.
We presented several model options under development in the CY 2016
proposed rule and may consider implementing payment reform to address
the margin differences across patient characteristics in future
rulemaking (80 FR 39865). With regard to the comment about patients in
rural areas, we note that episodes provided in rural areas will
continue to receive a three percent add-on payment in CY 2016.
Comment: A commenter stated that the proposed reductions will limit
services to the homebound population and will lead to increased re-
hospitalization and costs. Another commenter stated that the proposed
reductions would threaten the efficiency of the health care system and
will likely increase the likelihood of unnecessary institutional care
episodes and that this improper utilization may lead to higher costs.
The commenter urged CMS to consider the role and value of home health
care in the overall health care system as it makes changes to the home
health prospective payment system. The commenter asked CMS to consider
the most vulnerable populations and the demographics of home health
users when implementing payment adjustments. The commenter urged CMS to
consider the potential impact of payment adjustments on a generally,
older, sicker, poorer, and more vulnerable population, and mitigate
these risks where possible. Commenters also expressed concerns that the
proposed cuts may impact quality of care.
Response: We note that we believe the commenter is referring to
both the rebasing reductions as well as the proposed reductions to
account for nominal case-mix growth. As described in the CY 2016
proposed rule, section 3131(a) of the Affordable Care Act required the
Medicare Payment Advisory Commission (MedPAC) to assess, by January 1,
2015, the impact of the mandated rebasing adjustments on quality of and
beneficiary access to home health care. As part of this assessment, the
statute required MedPAC to consider the impact on care delivered by
rural, urban, nonprofit, and for-profit home health agencies. MedPAC's
Report to Congress noted that the rebasing adjustments are partially
offset by the payment update each year and across all four years of the
phase-in of the rebasing adjustments the cumulative net reduction would
equal about 2 percent. MedPAC concluded that, as a result of the
payment update offsets to the rebasing adjustments, HHA margins are
likely to remain high under the current rebasing policy and quality of
care and beneficiary access to care are unlikely to be negatively
affected \7\ (80 FR 39846). In addition, the overall impact of this
rule as discussed in section VII of this final rule is smaller than the
overall impact of previous rules in which reductions for nominal case-
mix growth have been implemented. For instance, we estimated that the
overall impact of the CY 2011 HH PPS final rule would be -4.89 percent
and the overall impact of the CY 2012 HH PPS final rule would be -2.31
percent.
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\7\ Medicare Payment Advisory Commission (MedPAC), ``Report to
the Congress: Impact of Home Health Payment Rebasing on Beneficiary
Access to and Quality of Care''. December 2014. Washington, DC.
Accessed on 5/05/15 at: https://www.medpac.gov/documents/reports/december-2014-report-to-the-congress-impact-of-home-health-payment-rebasing-on-beneficiary-access-to-and-quality-of-care.pdf?sfvrsn=0.
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Commenters did not provide specific information about why they
believe payment reductions would reduce the quality of care. MedPAC
estimates that the Medicare margin for 2015 will be 10.3 percent, which
should support current levels of quality. We also believe that
policymaking in the quality improvement area should help to ensure
quality advances. The HHVBP described in this final rule will be
implemented on January 1, 2016, further enhancing quality-related
incentives. While we do not anticipate significant negative impacts of
this rule, we will continue to closely monitor the effects of the
payments adjustments on HHAs, as well as on beneficiaries' access and
quality of care.
Comment: Commenters stated that the proposed reductions will limit
home health providers' ability to continue participating in broader
payment and
[[Page 68645]]
delivery system reform efforts and in the HHVBP program. Commenters
stated that the proposal fails to account for significant new cost
burdens placed on agencies since 2010 and fails to take into account
the current and future healthcare environment, such as the reform
initiatives underway. Another commenter stated that the payment cuts
should be delayed until their impact on HHAs can be more fully
understood in light of the dynamics that the Bundled Payment for Care
Improvement Initiative (BPCI), the proposed Comprehensive Care for
Joint Replacement (CCJR) model, Accountable Care Organizations (ACOs)
and various other healthcare delivery and payment reform initiatives
are creating for the home health sector, including shifting more
medically complex functional impaired patients into HHAs.
Response: While there may be increased costs associated with
implementing the broader payment and delivery system reform
initiatives, we expect that providers will be rewarded for efficient
care or higher quality of care and will receive a return on their
investment for investing in the payment reform efforts. The initiatives
cited by the commenters offer financial rewards for high quality of
care and/or efficient care.
Comment: A commenter stated that the proposed reductions will
threaten the ability of home health agencies to reduce re-
hospitalization rates and requested that CMS re-consider the
reductions, given the current reductions due to sequestration and
rebasing. Another commenter stated that they disagree with the
rationale used to justify the proposed case-mix reductions. The
commenter stated that the logic is ill-conceived and implies that
Medicare home health services have increased due to overutilization.
Another commenter stated that the proposed reductions assume that
providers ``gamed the system.'' A commenter stated that the proposed
reductions are based on the fact that CMS believes that the industry
has profit margins that are too high and has inflated the case-mix of
the patients served.
Response: The goal of the reductions for nominal case-mix growth is
to better align payment with real changes in patient severity. The
reductions would adjust the national, standardized 60-day episode
payment rate to account for nominal case-mix growth between CY 2012 and
CY 2014 and mitigate overpayments. As we have stated in previous
regulations, we believe nominal coding change results mostly from
changed coding practices, including improved understanding of the ICD-9
coding system, more comprehensive coding, changes in the interpretation
of various items on the OASIS and in formal OASIS definitions, and
other evolving measurement issues. Our view of the causes of nominal
coding change does not emphasize the idea that HHAs or clinicians in
general ``gamed the system'' or over-provided services or the idea that
HHAs have high profit margins. However, since our goal is to pay only
for increased costs associated with real changes in patient severity,
and because nominal coding change does not demonstrate that underlying
changes in patient severity occurred, we believe it is necessary to
exclude nominal case-mix effects that are unrelated to changes in
patient severity. We note that we will continue to monitor for any
unintended consequences of the payment reductions.
Comment: One commenter stated that the starting point in the real
and nominal case-mix growth analysis should have been 2002 or 2003, not
2000. Another commenter stated that the original baseline of a case-mix
weight of 1.000 in 2000 was incorrect and that the analysis is flawed
because the foundation or baseline is incorrect. Commenters cited
multiple examples to support their statements that 2000 should not have
been used as a baseline. For instance, they stated that in the first
couple of years of the HH PPS, many industry participants were
struggling with the transition to the new payment system and the
submission of OASIS data. They also stated that the OASIS document has
changed over time and that staff in 2000 had inadequate training on the
OASIS. A commenter stated that the OASIS does not adequately capture
the level of illness of the population being served.
Response: We followed the Administrative Procedure Act (APA) in
implementing the HH PPS under the mandate in the Balanced Budget Act of
1997. Under the APA, we solicited public comments in 1999 on the then
proposed system. OASIS itself was developed with industry participation
for the purpose of measuring home health outcomes (see GAO-01-205,
January 2001, Appendix II). A version of OASIS was used in the original
case-mix research that led to the design of the HH PPS case-mix system.
The research results indicated that adequate case-mix adjustment of
payments could be achieved using OASIS variables. We have noted in
previous regulations that the average case-mix weight nationally, as
estimated from OASIS assessments in the 12 months leading up to October
1, 2000, was about 13 percent higher than the average in the sample of
agencies whose data were used for the case-mix research. We used the
estimate from the 12 months leading up to October 1, 2000 as our
baseline for measuring case-mix change because it represented a very
large, broad-based set of episodes. It did not reflect the earliest
days of OASIS use. Given that coding practices continually evolved
subsequent to the last 12 months ending October 1, 2000, and that
agencies were not subject to the HH PPS incentives during the 12 months
ending October 1, 2000, the selected baseline period is the most
appropriate one to use to begin measuring coding change that occurred
in relation to the introduction of the HH PPS. Any other period
subsequent to our baseline builds in impacts on coding of the HH PPS
and is questionable to use from the point of view of responsible fiscal
stewardship.
We note that comments referencing coding improvements, such as
increasing accuracy, do not recognize that such improvements are an
inappropriate basis for increased payment. We believe that measurable
changes in patient severity and patient need are appropriate bases for
changes in payment. Our analysis found only small changes in patient
severity and need.
With regard to the comments about the baseline, we note that in our
May 2007 proposed rule and our August 2007 final rule, we described the
IPS samples and PPS samples that were used to calculate case-mix
change. We remind the commenters that 313,447 observations is an
extremely large sample by statistical standards, and that agencies
began collecting OASIS data in 1999, following issuance of a series of
regulations beginning on January 25, 1999 (64 FR 3764). Most of the
data we used for the baseline period come from the first 3 quarters of
the year 2000--months after collection was mandated to begin in August
1999. By 2000 the vast majority of agencies were complying with the
reporting requirements. Indirect evidence that the data from the early
years of the HH PPS were sufficiently reliable comes from model
validation analysis we conducted during that period. Validation of the
80-group model on a large 19-month claims sample ending June 2002 (N =
469,010 claims linked to OASIS) showed that the goodness-of-fit of the
model was comparable to the fit statistic from the original Abt
Associates case-mix sample (0.33 vs. 0.34), notwithstanding that
average total resources per episode declined by 20 percent. That
analysis
[[Page 68646]]
also showed that all but three variables in the scoring system remained
statistically significant.
Comment: A commenter questioned CMS' ability to be able to
statistically infer the difference between increases in real changes in
case-mix vs. nominal case-mix growth to the degree that the estimate
was used in developing the proposed reductions, i.e., a hundredth of a
percentage point. Some commenters stated that the home health payment
system itself is flawed and cited the Report to Congress on the home
health study on access to care for vulnerable populations. The
commenter implied that since the payment system is flawed, the analysis
to assess real and nominal case-mix is also flawed. Commenters stated
that the proposed rule relies heavily on a case-mix methodology that
CMS itself found requires ``additional analysis'' and ``potential
modifications''. A commenter stated that the proposed case-mix creep
adjustments should be suspended pending the development of a new case-
mix model.
Response: As described in the CY 2012 final rule and discussed
above, we procured an independent review of our methodology by a team
at Harvard University led by Dr. David Grabowski (``Home Health Study
Report--Independent Review of the Models to Assess Nominal Case-Mix
Growth'', dated June 21, 2011). When reviewing the model, the Harvard
team found that overall, our models were robust. As stated previously,
we would like to account for nominal case-mix growth from 2012 through
2014 and mitigate overpayments. We note that, as described in the CY
2016 proposed rule, we have several model options under development and
may implement payment reform in the future. However, while we are
currently in the process of developing payment reform options to the
case-mix methodology, we think it is appropriate to account for the
nominal case-mix growth from 2012 to 2014.
Final Decision: After considering the comments received in response
to the CY 2016 HH PPS proposed rule (80 FR 39840) and for the reasons
discussed above, we are finalizing a 0.97 percent reduction to the
national, standardized 60-day episode payment rate each year in CY
2016, CY 2017, and CY 2018 to account for nominal case-mix growth from
2012 to 2014.
3. Clarification Regarding the Use of the ``Initial Encounter''
Seventh Character, Applicable to Certain ICD-10-CM Code Categories,
under the HH PPS
The ICD-10-CM coding guidelines regarding the seventh character
assignment for diagnosis codes under Chapter 19, Injury, poisoning, and
certain other consequences of external causes (S00-T88), were revised
in the Draft 2015 ICD-10-CM, The Completed Official Draft Code Set.
Based upon the 2015 revised coding guidance above, certain initial
encounters are appropriate when the patient is receiving active
treatment during a home health episode.
Comment: A commenter requested clarification on the use of the
seventh character for ``initial encounters'' in the home health
setting. The commenter agrees that it seems reasonable that traumatic
injury codes with the initial encounter extension may not be
appropriate. However, the commenter contends that certain initial
encounter extensions may be appropriate if the patient is still
receiving active treatment. The commenter provided an example of active
treatment whereby the patient is receiving active treatment with the
continuation of antibiotics for treatment of a postoperative infection.
Based upon this example of active treatment, the commenter recommends
that CMS revise the home health grouper to allow the reporting of the
initial encounter seventh character for the ICD-10-CM codes for those
conditions that could reasonably continue to receive active treatment
in the home health setting. A couple of other commenters noted similar
concerns regarding initial encounters.
Response: While this comment is outside the scope of this rule, we
recognize that in the CY 2014 HH PPS final rule (78 FR 72271), we
discussed the decision to eliminate codes with initial encounter
extensions, listed in the GEMs translation for ICD-10-CM codes, that
began with S and T that are used for reporting traumatic injuries
(e.g., fractures and burns) as part of our ICD-10 grouper conversion
effort. Codes beginning with S and T have a seventh character that
indicates whether the treatment is for an initial encounter, subsequent
encounter or a sequela (a residual effect (condition produced) after
the acute phase of an illness or injury has terminated).
The decision to eliminate the seventh character initial encounter
for the S and T ICD-10-CM codes from the HH PPS ICD-10-CM translation
list was based, not only on the most current coding conventions and
guidelines that were available at that time, but also in collaboration
with the cooperating parties of the ICD-10 Coding Committee (the
American Health Information Management Association, the American
Hospital Association, the Centers for Disease Control and Prevention's
National Center for Health Statistics, and CMS) who confirmed that
initial encounter extensions were not appropriate for care in the home
health setting. Code extensions D, E, F, G, H, J, K, M, N, P, Q and R
indicate the patient is being treated for a subsequent encounter (care
for the injury during the healing or recovery phase) and were included
in the translation list in place of the initial encounter extensions.
CMS provided the draft translation list to the public on the CMS Web
site at https://www.cms.gov/Center/Provider-Type/Home-Health-Agency-HHA-Center.html?redirect=/center/hha.asp. We did not receive any
comments on the ICD-10-CM draft translation list and the elimination of
initial encounter seventh character extension.
Since the publication of the CY 2014 HH PPS final rule, the ICD-10-
CM coding guidelines regarding the use of the seventh character
assignment for diagnosis codes under Chapter 19, Injury, poisoning, and
certain other consequences of external causes (S00-T88), were revised
in the Draft 2015 ICD-10-CM, The Completed Official Draft Code Set.
Specifically, in March of 2015, the coding guidelines were revised to
clarify that the designation of an initial encounter is based on
whether a patient is receiving active treatment for the condition for
which the code describes. Initial encounters are not based on
chronology of care or whether the patient is seeing the same or a new
provider for the same condition. Examples of active treatment are:
Surgical treatment, emergency department encounter, and evaluation and
continuing treatment by the same or a different physician. Based on
these revisions, it is possible for a home health agency to use a
diagnosis code with a seventh character ``A'' (an initial encounter)
for certain conditions. A clinical example of this could include a
patient who was in the acute care hospital for IV antibiotics for a
post-surgical wound infection and who is discharged to home health on
IV antibiotics for ongoing treatment of the surgical wound infection.
This would be considered active treatment as the surgical wound
infection requires continued IV antibiotics.
The coding guidelines state to assign the seventh character ``D'',
indicating a subsequent encounter, for encounters after the patient has
received active treatment of the condition and is receiving routine
care for the condition during the healing or recovery phase. Examples
of subsequent care include: cast change or removal, an x-ray to check
healing status of fracture, removal of external or internal fixation
device,
[[Page 68647]]
medication adjustment, other aftercare and follow up visits following
treatment of the injury or condition. Therefore, it is also possible
for home health encounters to be designated as subsequent encounters
based on services that are provided during healing and recovery, after
treatment of the condition described by the code is completed. A
clinical example of this could include a patient who was in the acute
care hospital for a traumatic hip fracture that was surgically repaired
and the patient is discharged to home health for rehabilitation
services. This would be considered a subsequent encounter as the hip
fracture has been repaired and the patient is now in the healing and
recovery phase.
We recognize that this revision may have caused some confusion
among home health providers and that there may be subtle clinical
differences between what is considered active treatment of a condition
versus routine care during the healing and recovery phase of a
condition in the home health setting. The assignment of the seventh
character should be based on clinical information from the physician
and depends on whether the individual is receiving active treatment for
the condition in which the code describes, or if the individual is
receiving ongoing care for that condition during the healing and
recovery stage. In determining which diagnosis codes would be
appropriate for an HHA to indicate that the care is for an initial
encounter, CMS developed and shared a draft list of codes with the
cooperating parties. Agreement was reached between CMS and the
cooperating parties and a revised translation list effective January 1,
2016 will be posted on the CMS Web site. Also effective, January 1,
2016, the Home Health Prospective Payment System Grouper logic will be
revised to award points for certain initial encounter codes based upon
the revised ICD-10-CM coding guidelines for M0090 dates on or after
October 1, 2015.
C. CY 2016 Home Health Rate Update
1. CY 2016 Home Health Market Basket Update
Section 1895(b)(3)(B) of the Act requires that the standard
prospective payment amounts for CY 2015 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 HH 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- 67090). The HH market basket percentage increase for CY 2016
is based on IHS Global Insight Inc.'s (IGI) third quarter forecast with
historical data through the second quarter of 2015. The HH market
basket percentage increase for CY 2016 is 2.3 percent.
Section 3401(e) of the Affordable Care Act, adding new section
1895(b)(3)(B)(vi) to the Act, requires that 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 for CY 2015 and each subsequent calendar
year. The statute defines the productivity adjustment, described in
section 1886(b)(3)(B)(xi)(II) of the Act, 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 https://www.bls.gov/mfp to obtain the BLS historical published MFP
data.
Multifactor productivity is derived by subtracting the contribution
of labor and capital input growth from output growth. The projections
of the components of MFP are currently produced by IGI, a nationally
recognized economic forecasting firm with which CMS contracts to
forecast the components of the market basket and MFP. As described in
the CY 2015 HH PPS proposed rule (79 FR 38384 through 38386), in order
to generate a forecast of MFP, IGI replicated the MFP measure
calculated by the BLS using a series of proxy variables derived from
IGI's U.S. macroeconomic models. In the CY 2015 HH PPS proposed rule,
we identified each of the major MFP component series employed by the
BLS to measure MFP as well as provided the corresponding concepts
determined to be the best available proxies for the BLS series.
Beginning with the CY 2016 rulemaking cycle, the MFP adjustment is
calculated using a revised series developed by IGI to proxy the
aggregate capital inputs. Specifically, IGI has replaced the Real
Effective Capital Stock used for Full Employment GDP with a forecast of
BLS aggregate capital inputs recently developed by IGI using a
regression model. This series provides a better fit to the BLS capital
inputs as measured by the differences between the actual BLS capital
input growth rates and the estimated model growth rates over the
historical time period. Therefore, we are using IGI's most recent
forecast of the BLS capital inputs series in the MFP calculations
beginning with the CY 2016 rulemaking cycle. A complete description of
the MFP projection methodology is available on our Web site at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch.html. In the
future, when IGI makes changes to the MFP methodology, we will announce
them on our Web site rather than in the annual rulemaking.
Using IGI's third quarter 2015 forecast, the MFP adjustment for CY
2016 (the 10-year moving average of MFP for the period ending CY 2016)
is 0.4 percent. The CY 2016 HH market basket percentage of 2.3 percent
will be reduced by the MFP adjustment of 0.4 percent. The resulting HH
payment update percentage is equal to 1.9 percent, or 2.3 percent less
0.4 percentage point.
Section 1895(b)(3)(B) of the Act requires that the HH 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 2016, the HH payment update will be -
0.1 percent (1.9 percent minus 2 percentage points).
2. CY 2016 Home Health Wage Index
a. Background
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 will 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).
We will 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, and thus, no hospital wage
data on which to base the calculation of the CY 2015 HH PPS wage index.
For rural areas that do
[[Page 68648]]
not have inpatient hospitals, we will use the average wage index from
all contiguous CBSAs as a reasonable proxy. For FY 2016, there are no
rural geographic areas without hospitals for which we would apply this
policy. For rural Puerto Rico, we will 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 will 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 2016, the only urban area without inpatient hospital wage
data is Hinesville, GA (CBSA 25980).
b. Update
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. This
bulletin is available online at https://www.whitehouse.gov/sites/default/files/omb/bulletins/2013/b-13-01.pdf. This bulletin states that
it ``provides the delineations of all Metropolitan Statistical Areas,
Metropolitan Divisions, Micropolitan Statistical Areas, Combined
Statistical Areas, and New England City and Town Areas in the United
States and Puerto Rico based on the standards published on June 28,
2010, in the Federal Register (75 FR 37246-37252) and Census Bureau
data.''
In the CY 2015 HH PPS final rule (79 FR 66085 through 66087), we
finalized changes to the HH PPS wage index based on the newest OMB
delineations, as described in OMB Bulletin No. 13-01, including a 1-
year transition with a blended wage index for CY 2015. Because the 1-
year transition period expires at the end of CY 2015, the final HH PPS
wage index for CY 2016 will be fully based on the revised OMB
delineations adopted in CY 2015. The final CY 2016 wage index is
available on the CMS Web site at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/Home-Health-Prospective-Payment-System-Regulations-and-Notices.html
3. CY 2016 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 42 CFR 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 is 78.535 percent and the non-labor-related share is 21.465
percent as set out in the CY 2013 HH PPS final rule (77 FR 67068). The
CY 2016 HH PPS rates will 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.C. of this
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 case-mix and wage adjusted 60-day episode rate, subject to any
additional applicable adjustments.
In accordance with section 1895(b)(3)(B) of the Act, this document
constitutes the annual update of the HH PPS rates. Section 484.225 sets
forth the specific annual percentage update methodology. In accordance
with Sec. 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 two
percentage points. Any reduction of the percentage change will apply
only to the calendar year involved and would not be considered in
computing the prospective payment amount for a subsequent calendar
year.
Medicare pays the national, standardized 60-day case-mix and wage-
adjusted 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 Sec.
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 Sec. 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 would use to pay the claim.
We may also adjust the 60-day case-mix 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 per-visit basis as set forth in Sec. 484.205(c) and Sec. 484.230.
A partial episode payment (PEP) adjustment as set forth in
Sec. 484.205(d) and Sec. 484.235.
An outlier payment as set forth in Sec. 484.205(e) and
Sec. 484.240.
b. CY 2016 National, Standardized 60-Day Episode Payment Rate
Section 1895(3)(A)(i) of the Act required 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 2016 national, standardized 60-day episode
payment rate, we will apply a wage index standardization factor, a
case-mix budget neutrality factor described in section III.B.1, a
nominal case-mix growth adjustment described in section III.B.2, the
rebasing adjustment described in section II.C, and the HH payment
update as discussed in section III.C.1 of this final rule.
To calculate the wage index standardization factor, henceforth
referred to as the wage index budget neutrality factor, we simulated
total payments for non-LUPA episodes using the 2016 wage index and
compared it to our simulation of total payments for non-LUPA episodes
using the 2015 wage index. By dividing the total payments for non-LUPA
episodes using the 2016 wage index by the total payments for non-LUPA
episodes using the 2015 wage index, we obtain a wage index budget
neutrality factor of 1.0011. We will apply the wage index budget
neutrality factor of 1.0011 to the CY
[[Page 68649]]
2016 national, standardized 60-day episode rate.
As discussed in section III.B.1 of this final rule, to ensure the
changes to the case-mix weights are implemented in a budget neutral
manner, we will apply a case-mix weight budget neutrality factor to the
CY 2016 national, standardized 60-day episode payment rate. The case-
mix weight budget neutrality factor is calculated as the ratio of total
payments when CY 2016 case-mix weights are applied to CY 2014
utilization (claims) data to total payments when CY 2015 case-mix
weights are applied to CY 2014 utilization data. The case-mix budget
neutrality factor for CY 2016 will be 1.0187 as described in section
III.B.1 of this final rule.
Next, as discussed in section III.B.2 of this final rule, we will
apply a reduction of 0.97 percent to the national, standardized 60-day
episode payment rate in CY 2016 to account for nominal case-mix growth
between CY 2012 and CY 2014. Then, we will apply the -$80.95 rebasing
adjustment finalized in the CY 2014 HH PPS final rule (78 FR 72256) and
discussed in section II.C. Lastly, we will update the payment rates by
the CY 2016 HH payment update of 1.9 percent (MFP-adjusted home health
market basket update) as described in section III.C.1 of this final
rule. The CY 2016 national, standardized 60-day episode payment rate is
calculated in Table 7.
Table 7--CY 2016 National, Standardized 60-Day Episode Payment Amount
--------------------------------------------------------------------------------------------------------------------------------------------------------
CY 2016
Wage index Case-mix Nominal case- CY 2016 CY 2016 HH National,
CY 2015 National, standardized 60-day episode budget weights budget mix growth Rebasing payment update standardized
payment neutrality neutrality adjustment (1- adjustment percentage 60-day episode
factor factor .0097) payment
--------------------------------------------------------------------------------------------------------------------------------------------------------
$2,961.38......................................... x 1.0011 x 1.0187 x 0.9903 -$80.95 x 1.019 $2,965.12
--------------------------------------------------------------------------------------------------------------------------------------------------------
The CY 2016 national, standardized 60-day episode payment rate for
an HHA that does not submit the required quality data is updated by the
CY 2016 HH payment update (1.9 percent) minus 2 percentage points and
is shown in Table 8.
Table 8--For HHAs That Do Not Submit the Quality Data--CY 2016 National, Standardized 60-Day Episode Payment Amount
--------------------------------------------------------------------------------------------------------------------------------------------------------
CY 2016 HH
Wage index Case-mix Nominal case- payment update CY 2016
CY 2015 National, standardized 60-day episode budget weights budget mix growth CY 2016 percentage National,
payment neutrality neutrality adjustment (1- Rebasing minus 2 standardized
factor factor .0097) adjustment percentage 60-day episode
points payment
--------------------------------------------------------------------------------------------------------------------------------------------------------
$2,961.38......................................... x1.0011 x1.0187 x0.9903 -$80.95 x0.999 $2,906.92
--------------------------------------------------------------------------------------------------------------------------------------------------------
c. CY 2016 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); and
Speech-language pathology (SLP).
To calculate the CY 2016 national per-visit rates, we start with
the CY 2015 national per-visit rates. We then apply a wage index budget
neutrality factor to ensure budget neutrality for LUPA per-visit
payments and increase each of the six per-visit rates by the maximum
rebasing adjustments described in section II.C. of this rule. We
calculate the wage index budget neutrality factor by simulating total
payments for LUPA episodes using the 2016 wage index and comparing it
to simulated total payments for LUPA episodes using the 2015 wage
index. By dividing the total payments for LUPA episodes using the 2016
wage index by the total payments for LUPA episodes using the 2015 wage
index, we obtain a wage index budget neutrality factor of 1.0010. We
will apply the wage index budget neutrality factor of 1.0010 to the CY
2016 national per-visit rates.
The LUPA per-visit rates are not calculated using case-mix weights.
Therefore, there is no case-mix weight budget neutrality factor needed
to ensure budget neutrality for LUPA payments. Then, we apply the
rebasing adjustments finalized in the CY 2014 HH PPS final rule (78 FR
72280) to the per-visit rates for each discipline. Finally, the per-
visit rates are updated by the CY 2016 HH payment update of 1.9
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 add-on payment amount, which is
paid for episodes that occur as the only episode or initial episode in
a sequence of adjacent episodes. The CY 2016 national per-visit rates
are shown in Tables 9 and 10.
[[Page 68650]]
Table 9--CY 2016 National Per-Visit Payment Amounts for HHAs That DO Submit the Required Quality Data
--------------------------------------------------------------------------------------------------------------------------------------------------------
Wage index
CY 2015 Per- budget CY 2016 CY 2016 HH CY 2016 Per-
HH discipline type visit payment neutrality Rebasing payment update visit payment
factor adjustment percentage
--------------------------------------------------------------------------------------------------------------------------------------------------------
Home health aide................................................... $57.89 x 1.0010 +$1.79 x 1.019 $60.87
Medical Social Services............................................ 204.91 x 1.0010 + $6.34 x 1.019 215.47
Occupational Therapy............................................... 140.70 x 1.0010 + $4.35 x 1.019 147.95
Physical Therapy................................................... 139.75 x 1.0010 + $4.32 x 1.019 146.95
Skilled Nursing.................................................... 127.83 x 1.0010 + $3.96 x 1.019 134.42
Speech-Language Pathology.......................................... 151.88 x 1.0010 + 4.70 x 1.019 159.71
--------------------------------------------------------------------------------------------------------------------------------------------------------
The CY 2016 per-visit payment rates for HHAs that do not submit the
required quality data are updated by the CY 2016 HH payment update of
1.9 percent minus 2 percentage points (which is equal to -0.1 percent)
and is shown in Table 10.
Table 10--CY 2016 National Per-Visit Payment Amounts for HHAs That DO NOT Submit the Required Quality Data
--------------------------------------------------------------------------------------------------------------------------------------------------------
CY 2016 HH
Wage index payment update
CY 2015 Per- budget CY 2016 percentage CY 2016 Per-
HH discipline type visit rates neutrality Rebasing minus 2 visit rates
factor adjustment percentage
points
--------------------------------------------------------------------------------------------------------------------------------------------------------
Home Health Aide................................................... $57.89 x 1.0010 + $1.79 x 0.999 $59.68
Medical Social Services............................................ 204.91 x 1.0010 + $6.34 x 0.999 211.24
Occupational Therapy............................................... 140.70 x 1.0010 + $4.35 x 0.999 145.05
Physical Therapy................................................... 139.75 x 1.0010 + $4.32 x 0.999 144.07
Skilled Nursing.................................................... 127.83 x 1.0010 + $3.96 x 0.999 131.79
Speech-Language Pathology.......................................... 151.88 x 1.0010 + 4.70 x 0.999 156.58
--------------------------------------------------------------------------------------------------------------------------------------------------------
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, 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 (78 FR 72306). 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, 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 would be $248.02
(1.8451 multiplied by $134.42), subject to area wage adjustment.
e. CY 2016 Non-routine Medical Supply (NRS) Payment Rates
Payments for NRS are computed by multiplying the relative weight
for a particular severity level by the NRS conversion factor. To
determine the CY 2016 NRS conversion factor, we start with the 2015 NRS
conversion factor ($53.23) and apply the -2.82 percent rebasing
adjustment described in section II.C. of this rule (1 - 0.0282 =
0.9718). We then update the conversion factor by the CY 2016 HH payment
update of 1.9 percent. We do not apply a standardization factor as the
NRS payment amount calculated from the conversion factor is not wage or
case-mix adjusted when the final claim payment amount is computed. The
NRS conversion factor for CY 2016 is shown in Table 11.
Table 11--CY 2016 NRS Conversion Factor for HHAs That DO Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
CY 2016 CY 2016 HH CY 2016 NRS
CY 2015 NRS conversion factor Rebasing payment update conversion
adjustment percentage factor
----------------------------------------------------------------------------------------------------------------
$53.23....................................................... x 0.9718 x 1.019 $52.71
----------------------------------------------------------------------------------------------------------------
Using the CY 2016 NRS conversion factor, the payment amounts for
the six severity levels are shown in Table 12.
[[Page 68651]]
Table 12--CY 2016 NRS Payment Amounts for HHAs That DO Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
Points CY 2016 NRS
Severity level (scoring) Relative weight payment amounts
----------------------------------------------------------------------------------------------------------------
1............................................................ 0 0.2698 $14.22
2............................................................ 1 to 14 0.9742 51.35
3............................................................ 15 to 27 2.6712 140.80
4............................................................ 28 to 48 3.9686 209.18
5............................................................ 49 to 98 6.1198 322.57
6............................................................ 99+ 10.5254 554.79
----------------------------------------------------------------------------------------------------------------
For HHAs that do not submit the required quality data, we again
begin with the CY 2015 NRS conversion factor ($53.23) and apply the -
2.82 percent rebasing adjustment as discussed in section II.C of this
final rule (1 - 0.0282 = 0.9718). We then update the NRS conversion
factor by the CY 2016 HH payment update of 1.9 percent minus 2
percentage points. The CY 2016 NRS conversion factor for HHAs that do
not submit quality data is shown in Table 13.
Table 13--CY 2016 NRS Conversion Factor for HHAs That DO NOT Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
CY 2016 HH
payment update
CY 2016 percentage CY 2016 NRS
CY 2015 NRS conversion factor rebasing minus 2 conversion
adjustment percentage factor
points
----------------------------------------------------------------------------------------------------------------
$53.23....................................................... x 0.9718 x 0.999 $51.68
----------------------------------------------------------------------------------------------------------------
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 14.
Table 14--CY 2016 NRS Payment Amounts For HHAs That DO NOT Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
CY 2016 NRS
Severity level Points (scoring) Relative weight payment amounts
----------------------------------------------------------------------------------------------------------------
1......................................... 0................................. 0.2698 $13.94
2......................................... 1 to 14........................... 0.9742 50.35
3......................................... 15 to 27.......................... 2.6712 138.05
4......................................... 28 to 48.......................... 3.9686 205.10
5......................................... 49 to 98.......................... 6.1198 316.27
6......................................... 99+............................... 10.5254 543.95
----------------------------------------------------------------------------------------------------------------
f. Rural Add-On
Section 421(a) of the MMA requires, 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, 2010, and before January
1, 2018, that the Secretary increase the payment amount that otherwise
would have been made under section 1895 of the Act for the services by
3 percent. Section 421 of the MMA waives budget neutrality related to
this provision, as the statute specifically states that the Secretary
shall not reduce the standard prospective payment amount (or amounts)
under section 1895 of the Act applicable to HH services furnished
during a period to offset the increase in payments resulting in the
application of this section of the statute.
For CY 2016, home health payment rates for services provided to
beneficiaries in areas that are defined as rural under the OMB
delineations will be increased by 3 percent as mandated by section
421(a) of the MMA. The 3 percent rural add-on is applied to the
national, standardized 60-day episode payment rate, national per visit
rates, and NRS conversion factor when HH services are provided in rural
(non-CBSA) areas. Refer to Tables 15 through 18 for these payment
rates.
[[Page 68652]]
Table 15--CY 2016 Payment Amounts for 60-Day Episodes for Services Provided in a Rural Area
--------------------------------------------------------------------------------------------------------------------------------------------------------
For HHAs that DO submit quality data For HHAs that DO NOT submit quality data
--------------------------------------------------------------------------------------------------------------------------------------------------------
CY 2016 rural CY 2016 rural
Multiply by the national, Multiply by the national,
CY 2016 national, standardized 60-day episode 3 percent rural standardized 60- CY 2016 national, standardized 60- 3 percent rural standardized 60-
payment rate add-on day episode day episode payment rate add-on day episode
payment rate payment rate
--------------------------------------------------------------------------------------------------------------------------------------------------------
$2,965.12....................................... x 1.03 $3,054.07 $2,906.92......................... x 1.03 $2,994.13
--------------------------------------------------------------------------------------------------------------------------------------------------------
Table 16--CY 2016 Per-Visit Amounts for Services Provided in a Rural Area
--------------------------------------------------------------------------------------------------------------------------------------------------------
For HHAs that DO submit quality data For HHAs that DO NOT submit quality data
-----------------------------------------------------------------------------------------------------
HH Discipline type Multiply by the Multiply by the
CY 2016 per- 3 percent rural CY 2016 rural CY 2016 per- 3 percent rural CY 2016 rural
visit rate add-on per-visit rates visit rate add-on per-visit rates
--------------------------------------------------------------------------------------------------------------------------------------------------------
HH Aide........................................... $60.87 x 1.03 $62.70 $59.68 x 1.03 $61.47
MSS............................................... 215.47 x 1.03 221.93 211.24 x 1.03 217.58
OT................................................ 147.95 x 1.03 152.39 145.05 x 1.03 149.40
PT................................................ 146.95 x 1.03 151.36 144.07 x 1.03 148.39
SN................................................ 134.42 x 1.03 138.45 131.79 x 1.03 135.74
SLP............................................... 159.71 x 1.03 164.50 156.58 x 1.03 161.28
--------------------------------------------------------------------------------------------------------------------------------------------------------
Table 17--CY 2016 NRS Conversion Factor for Services Provided in Rural Areas
--------------------------------------------------------------------------------------------------------------------------------------------------------
For HHAs that DO submit quality data For HHAs that DO NOT submit quality data
--------------------------------------------------------------------------------------------------------------------------------------------------------
Multiply by the CY 2016 rural Multiply by the CY 2016 rural
CY 2016 conversion factor 3 percent rural NRS conversion CY 2016 conversion factor 3 percent rural NRS conversion
add-on factor add-on factor
--------------------------------------------------------------------------------------------------------------------------------------------------------
$52.71.......................................... x 1.03 $54.29 $51.68............................ x 1.03 $53.23
--------------------------------------------------------------------------------------------------------------------------------------------------------
Table 18--CY 2016 NRS Payment Amounts for Services Provided in Rural Areas
--------------------------------------------------------------------------------------------------------------------------------------------------------
For HHAs that DO submit quality For HHAs that DO NOT submit
data (CY 2016 NRS conversion quality data (CY 2016 NRS
factor = $54.29 conversion factor = $53.23)
Severity level Points (scoring) -------------------------------------------------------------------
CY 2016 NRS CY 2016 NRS
Relative weight payment amounts Relative weight payment amounts
for rural areas for rural areas
--------------------------------------------------------------------------------------------------------------------------------------------------------
1............................................... 0................................. 0.2698 $14.65 0.2698 $14.36
2............................................... 1 to 14........................... 0.9742 52.89 0.9742 51.86
3............................................... 15 to 27.......................... 2.6712 145.02 2.6712 142.19
4............................................... 28 to 48.......................... 3.9686 215.46 3.9686 211.25
5............................................... 49 to 98.......................... 6.1198 332.24 6.1198 325.76
6............................................... 99+............................... 10.5254 571.42 10.5254 560.27
--------------------------------------------------------------------------------------------------------------------------------------------------------
The following is a summary of comments we received regarding the CY
2016 home health rate update.
Comment: A commenter objected to the proposed 0.6 percent
productivity adjustment.
Response: The productivity adjustment was mandated by Section
3401(e) of the Affordable Care Act by adding section 1895(b)(3)(B)(vi)
to the Act and requiring that the market basket percentage under the HH
PPS be annually adjusted by changes in economy-wide productivity in CY
2015 (and in subsequent calendar years). Since publication of the
proposed rule, our forecast for the productivity adjustment has been
revised to 0.4 percent based on an updated forecast with historical
data through 2014.
Comment: A commenter stated that because CAHs are located in rural
areas, the absence of CAH wage data further compromises the accuracy of
the hospital wage index to determine labor costs of HHAs providing
services in rural areas. In addition, pending development of an
industry specific wage index, CMS should add a population density
adjustment to the labor portion of the payment to account for increased
costs of providing services in less densely populated areas.
Response: Although the pre-floor, pre-reclassified hospital wage
index does not include data from CAHs, we believe it reflects the
relative level of wages and wage-related costs applicable to providing
home health services. As we stated in the IPPS Final Rule published on
August 1, 2003 (68 FR 45397), ``CAHs represent a substantial number of
hospitals with significantly different labor costs in many labor market
areas where they exist.'' We further noted that, ``. . . in 89 percent
of all labor market areas with hospitals that
[[Page 68653]]
converted to CAH status sometime after FY 2000, the average hourly wage
for CAHs is lower than the average hourly wage for other short-term
hospitals in the area. In 79 percent of the labor market areas with
CAHs, the average hourly wage for CAHs is lower than the average hourly
wage for other short-term hospitals by 5 percent or greater. These
results suggest that the wage data for CAHs, in general, are
significantly different from other short-term hospitals.
At this time, we do not have evidence that a population density
adjustment is appropriate. While rural HHAs cite the added cost of long
distance travel to provide care for their patients, urban HHAs cite
added costs associated with needed security measures and traffic
congestion.
Comment: A commenter urges CMS to review the wage index calculation
for rural Massachusetts and to include Nantucket Cottage Hospital's
data in the calculation. The commenter states that Nantucket Cottage
Hospital had given up its critical access hospital (CAH) designation in
2014 yet CMS has apparently not used wage data from Nantucket Cottage
Hospital in calculating the 2016 wage index for rural Massachusetts.
The commenter urges CMS to include wage data from CAHs in calculating
the wage index for HHAs and other non-hospital provider types. The
commenter believes that including wage data from CAHS would make the
wage index more reflective of actual local wage practices.
Response: Data from Nantucket Cottage Hospital is included in the
calculation of the 2016 wage index for rural Massachusetts. In fact,
data from this hospital has been included in the calculation of the HH
wage index for rural Massachusetts since CY 2012. It has been our
longstanding practice to not include data from CAHs in the calculation
of the HH wage index. We only include hospital data from acute IPPS
hospitals in the calculation of the HH wage index.
Comment: A commenter questions the validity of the wage index
assigned to CBSA 22520, Florence-Muscle Shoals, AL. The commenter
requests that the underlying data to determine this index be
investigated to determine its validity. In addition, the commenter
states that the wage index as assigned places this urban area below the
rural wage index for the state, which cannot be correct.
Response: The HH wage index values in urban areas are not
necessarily higher than the HH wage index values in rural 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, pre-reclassified
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, our intermediaries 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 Inpatient Prospective Payment System (IPPS) rule each
year, with the most recent discussion provided in the FY 2016 IPPS
final rule (80 FR 49488 through 49508). Any provider type may submit
comments on the hospital wage index during the annual IPPS rulemaking
cycle.
Comment: Several commenters took issue with the fact that the HH
wage index is based on pre-floor, pre-reclassified hospital wage data,
but hospitals in the same geographic locations have the ability to
apply for re-classification to another CBSA and may be eligible for the
rural floor wage index. The commenters state that this inequity has
created a competitive advantage for hospitals in recruiting and
retaining scarce labor. Several commenters believe that the statute
does give CMS authority to address and correct some of these
inequities. One commenter believes that a correction to the manner in
which the wage index is calculated is needed in order to recruit and
retain staff necessary to provide home health care. The commenter
continues to state that otherwise it may be difficult for HHAs to meet
the increased demand for services, which may jeopardize the success of
CMS' VBP initiatives. Another commenter recommends that CMS reform the
HH wage index by instituting a proxy that allows HHAs to receive the
same reclassification as hospitals if they provide series in the same
service area.
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
re-classification provision found in section 1886(d)(10) of the Act.
Section 1886(d)(10)(C)(i) of the Act states, ``The Board shall consider
the application of any subsection (d) hospital requesting that the
Secretary change the hospital's geographic classification . . .'' This
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 it may or may not apply to a given HHA in a given
instance. With regard to implementing a rural floor, we do not believe
it would be prudent at this time to adopt such a policy. MedPAC has
recommended eliminating the rural floor policy from the calculation of
the IPPS wage index (see Chapter 3 of MedPAC's March 2013 Report to
Congress on Medicare Payment Policy, available at https://medpac.gov/documents/reports/mar13_entirereport.pdf, which notes on page 65 that
in 2007, MedPAC had ``. . . recommended eliminating these special wage
index adjustments and adopting a new wage index system to avoid
geographic inequities that can occur due to current wage index
policies.''
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: A commenter requests that CMS explore wholesale revision
and reform of the HH wage index. The commenter believes that existing
law permits CMS flexibility in establishing area wage adjustment
factors. Another commenter notes that CMS indicated that the entire
wage index system was under review, and that a move to a Commuting-
Based Wage Index (CBWI) was being considered. The commenter urges CMS
to expedite that review and implement a system that not only recognizes
variations between localities, but also treats all provider types
within a local market equitably. Until such a system is in place, the
commenter urges CMS to adjust the 2016 HHA wage index to reflect a
policy to limit the wage index disparity between provider types within
a given CBSA to no more than 10 percent.
Response: CMS' ``Report to Congress: Plan to Reform the Medicare
Wage Index'' was submitted by the Secretary on April 11, 2012 and is
available on
[[Page 68654]]
our Wage Index Reform Web page at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Wage-Index-Reform.html. This report states that other steps are necessary before
we would be able to adopt a CBWI. In the meantime, we do not believe
that limiting wage index differences between provider types within a
given CBSA would be feasible. Regardless of whether or not it would be
appropriate to do so, it would not be feasible to limit the differences
in wage index values among provider types within a given CBSA to no
more than 10 percent, due to timing issues. Some provider types are
reimbursed on a calendar year basis and some are reimbursed on a fiscal
year basis.
Comment: A commenter opposes CMS' use of the hospital wage index to
establish the HH wage index. The commenter states that differences in
the occupational personnel pool and costs between hospitals and HHAs
make the use of the hospital wage index inappropriate in the HH
setting. The commenter further states that hospitals benefit from
institutional efficiencies that and rural hospitals have a
reclassification mechanism to avoid exposure to the drastic rural index
rate in most states. The commenter believes that Congress has granted
CMS discretion in establishing the HH wage index and that CMS should
establish a HH specific wage index. Another commenter believes that
basing the wage index on hospital data is not reliable for home health.
The commenter continues to state that home health workers pay is
typically much more than that of a hospital employee due to the
demanding nature of the job. The commenter suggests that CMS complete a
detailed study of this issue.
Response: Our previous attempts at either proposing or developing a
home health specific wage index were not well received by the home
health industry. In a Federal Register Notice (53 FR 38476) published
on September 30, 1988, the Health Care Financing Administration (HCFA),
as we were then known, implemented an HHA-specific wage index based on
data received from HHAs. Subsequently, HCFA and the Congress received
numerous complaints from providers concerning the burden that the
reporting requirements posed and the accuracy of the data. As a result,
the Congress retroactively repealed its mandate in the Medicare
Catastrophic Coverage Act of 1988 for use of an HHA wage index and
referenced use of the hospital wage index (see section 1895(b)(4)(C) of
the Act). This caused great confusion among both providers and fiscal
intermediaries.
Developing a wage index that utilizes data specific to HHAs would
require us to engage resources in an audit process. In order to
establish a home health specific wage index, we would need to collect
data that is specific to home health services. Because of the
volatility of the home health wage data and the significant amount of
resources that would be required to improve the quality of those data,
we do not expect to propose a home health specific wage index until we
can demonstrate that a home health specific wage index would be more
reflective of the wages and salaries paid in a specific area, be based
upon stable data sources, significantly improve our ability to
determine payment for HHAs, and that we can justify the resources
required to collect the data, as well as the increased burden on
providers. We believe that in the absence of home health specific wage
data, using the pre-floor, pre-reclassified hospital wage data is
appropriate and reasonable for the HH PPS.
Comment: A commenter states that the wage index needs to reflect
the growing difficulties of providing care in rural areas. The
commenter states that paying lower wages for rural health care
professionals that put as much time, skill and intensity into their
work as their urban counterparts, exacerbates the workforces shortages.
The commenter continues to state that further reducing the wage index
for rural providers will make recruiting and retaining medical
professionals more difficult for rural America. The commenter states
that using the wage index for the local area ignores important market
forces and that many health professionals are recruited from a
distance, making the local wage insufficient financial incentive for
practicing in rural America. Another commenter states that rural HHAs
often function as the primary caregivers for elderly homebound
patients, who have high resource needs, which also increases the cost
of rural home health services.
Response: The HH wage index values in rural areas are not
necessarily lower than the HH wage index values in urban areas. The HH
wage index reflects the wages that inpatient hospitals pay in their
local geographic areas. In addition, HHAs receive rural add-on payments
for services provided to beneficiaries in rural areas. Section 421(a)
of the MMA, as amended by section 210 of the Medicare Access and CHIP
Reauthorization Act of 2015 (MACRA) (Pub. L. 114-10), provides for a
payment increase of 3 percent for HH services provided in rural areas
for episodes or visits ending on or after April 1, 2010, and before
January 1, 2018.
Final Decision: After considering the comments received in response
to the CY 2016 HH PPS proposed rule (80 FR 39840) and for the reasons
discussed above, we are finalizing our proposal to use the pre-floor,
pre-reclassified hospital inpatient wage index as the wage adjustment
to the labor portion of the HH PPS rates. For CY 2016, the updated wage
data are for hospital cost reporting periods beginning on or after
October 1, 2011 and before October 1, 2012 (FY 2012 cost report data).
D. Payments for High-Cost Outliers Under the HH PPS
1. Background
In the July 10, 2015 Medicare and Medicaid Programs; CY 2016 Home
Health Prospective Payment System Rate Update; Home Health Value-Based
Purchasing Model; and Home Health Quality Reporting Requirements;
Proposed Rules (80 FR 39863 through 39864), we described the background
and current method for determining outlier payments under the HH PPS.
In that rule, we did not propose any changes to the current home health
outlier payment policy for CY 2016.
For this final rule, simulating payments using CY 2014 claims data
(as of June 30, 2015) and the CY 2016 payment rates, without the
rebasing and nominal case-mix growth adjustments as described in
section III.C.3 of this rule, we estimate that outlier payments in CY
2016 would comprise 2.13 percent of total payments. Based on
simulations using CY 2014 claims data and the CY 2016 payments rates,
including the rebasing and nominal case-mix growth adjustments as
described in section III.C.3 of this rule, we estimate that outlier
payments would comprise approximately 2.30 percent of total HH PPS
payments, a percent change of almost 8 percent. This increase is
attributable to the increase in the national per-visit amounts through
the rebasing adjustments and the decrease in the national, standardized
60-day episode payment amount as a result of the rebasing and nominal
case-mix growth adjustments. Given the same rebasing adjustments and
case-mix growth reduction would also occur for 2017, and hence a
similar anticipated increase in the outlier payments, we estimate that
for CY 2017 outlier payments as a percent of total HH PPS payments
would be approximately 2.5 percent.
We did not propose a change to the FDL ratio or loss-sharing ratio
for CY
[[Page 68655]]
2016 as we believe that maintaining an FDL of 0.45 and a loss-sharing
ratio of 0.80 are appropriate given the percentage of outlier payments
is estimated to increase as a result of the increase in the national
per-visit amounts through the rebasing adjustments and the decrease in
the national, standardized 60-day episode payment amount as a result of
the rebasing adjustment and nominal case-mix growth reduction. We will
continue to monitor the percent of total HH PPS payments paid as
outlier payments to determine if future adjustments to either the FDL
ratio or loss-sharing ratio are warranted.
The following is a summary of comments we received regarding
payments for high-cost outliers.
Comment: One commenter expressed support of the continuation of the
high cost outlier parameters as currently structured.
Response: We appreciate the commenter's support of the current HH
PPS outlier policy. We strive to maintain an approach that accounts for
episodes that incur unusually high costs due to patient care needs.
Comment: Several commenters recommended changes to the existing
outlier policy, including the elimination of the outlier payment policy
altogether as well as modifications to the FDL Ratio and/or Loss-
Sharing Ratio in order to generate outlier payment levels approximating
2.5 percent.
Response: We believe that section 1895(b)(5)(A) of the Act affords
the Secretary the discretion as to whether or not to have an outlier
policy under the HH PPS. We plan to continue investigating 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 without qualifying episodes of care that do not meet
said criteria or are potentially fraudulent. We recently awarded a
contract to Abt Associates to address any findings from the home health
study required by section 3131(d) of the Affordable Care Act, monitor
the potential impact of the rebasing adjustments and other recent
payment changes, and develop payment options to ensure ongoing access
to care for vulnerable populations. The work under this contract may
include potential revisions to the outlier payment methodology to
better reflect costs of treating Medicare beneficiaries with high
levels of severity of illness.
Comment: One commenter suggested that CMS's outlier policy and ten
percent threshold cap are not appropriate fraud-fighting initiatives
and suggested other mechanisms for oversight and monitoring, including
a provider-specific floor (minimum) on the number or percent of
episodes that result in LUPAs.
Response: As we have noted in the past (74 FR 58085), we are
committed to addressing potentially fraudulent activities, especially
those in areas where we see suspicious outlier payments. As we noted
above, we plan to examine potential revisions to the outlier payment
methodology through ongoing studies and analysis of home health claims
and other utilization data. Monitoring of potentially fraudulent
activity will be captured in this analysis, and we will make policy and
other adjustments as necessary in light of the new data and outcomes as
appropriate.
Final Decision: We are finalizing no change to the FDL ratio or
loss sharing ratio for CY 2016. 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 due to patient care
needs without qualifying episodes of care that do not meet that
criteria.
E. Report to the Congress on the Home Health Study Required by Section
3131(d) of the Affordable Care Act and an Update on Subsequent Research
and Analysis
In the CY 2016 HH PPS proposed rule (80 FR 39840), we included an
informational summary of the Report to Congress on the home health
study required by section 3131(d) of the Affordable Care Act and we
provided an update on subsequent research and analysis completed to
date. We will continue to provide the home health industry with
periodic updates on the progress of our subsequent research, aimed at
addressing the findings from the section 3131(d) of the Affordable Care
Act home health study, in future rulemaking and/or announcements on the
HHA Center Web page at: https://www.cms.gov/Center/Provider-Type/Home-Health-Agency-HHA-Center.html.
F. Technical Regulations Text Changes
We proposed to make several technical corrections in part 484 to
better align the payment requirements with recent statutory and
regulatory changes for home health services. We proposed to make
changes to Sec. 484. 205(e) to state that estimated total outlier
payments for a given calendar year are limited to no more than 2.5
percent of total outlays under the HHA PPS, as required by section
1895(b)(5)(A) of the Act as amended by section 3131(b)(2)(B) of the
Affordable Care Act, rather than 5 percent of total outlays. Similarly,
we also proposed to specify in Sec. 484.240(e) that the fixed dollar
loss and the loss sharing amounts are chosen so that the estimated
total outlier payment is no more than 2.5 percent of total payments
under the HH PPS. We also proposed to describe in Sec. 484.240(f) that
the estimated total amount of outlier payments to an HHA in a given
year may not exceed 10 percent of the estimated total payments to the
specific agency under the HH PPS in a given year. This update aligns
the regulations text at Sec. 484.240(f) with the statutory
requirement. Finally, we proposed a minor editorial change in Sec.
484.240(b) to specify that the outlier threshold for each case-mix
group is the episode payment amount for that group, or the PEP
adjustment amount for the episode, plus a fixed dollar loss amount that
is the same for all case-mix groups.
In addition to the proposed changes to the regulations text
pertaining to outlier payments under the HH PPS, we also proposed to
amend Sec. 409.43(e)(iii) and to add language to Sec. 484.205(d) to
clarify the frequency of review of the plan of care and the provision
of Partial Episode Payments (PEP) under the HH PPS as a result of a
regulations text change in Sec. 424.22(b) that was finalized in the CY
2015 HH PPS final rule (79 FR 66032). Specifically, we proposed to
change the definition of an intervening event to include transfers and
instances where a patient is discharged and return to home health
during a 60-day episode, rather than a discharge and return to the same
HHA during a 60-day episode. In Sec. 484.220, we proposed to update
the regulations text to reflect the downward adjustments to the 60-day
episode payment rate due to changes in the coding or classification of
different units of service that do not reflect real changes in case-mix
(nominal case-mix growth) applied to calendar years 2012 and 2013,
which were finalized in the CY 2012 HH PPS final rule (76 FR 68532) as
well as updating the CY 2011 adjustment to 3.79 percent as finalized in
the CY 2011 HH PPS final rule (75 FR 70461). In Sec. 484.225 we
proposed to eliminate references to outdated market basket index
factors by removing paragraphs (b), (c), (d), (e), (f), and (g). In
Sec. 484.230 we proposed to delete the last sentence as a result of a
change from a separate LUPA add-on amount to a LUPA add-on factor
finalized in the CY 2014 HH PPS final rule (78 FR 72256). Finally, we
proposed deleting and reserving Sec. 484.245 as we believe that this
language is no longer applicable under the HH PPS, as it was meant to
[[Page 68656]]
facilitate the transition to the original PPS established in CY 2000.
Lastly, we proposed to make one technical correction in Sec.
424.22 to re-designate paragraph (a)(1)(v)(B)(1) as (a)(2).
We invited comments on these technical corrections and associated
changes in the regulations in parts 409, 424, and 484. However, we did
not receive any comments regarding the technical regulations text
changes.
Final Decision: We are finalizing the technical regulations text
changes at Sec. 409, Sec. 424, and Sec. 484 as proposed.
IV. Provisions of the Home Health Value-Based Purchasing (HHVBP) Model
and Response to Comments
A. Background
In the CY 2015 Home Health Prospective Payment System (HH PPS)
final rule titled ``Medicare and Medicaid Programs; CY 2015 Home Health
Prospective Payment System Rate Update; Home Health Quality Reporting
Requirements; and Survey and Enforcement Requirements for Home Health
Agencies (79 FR 66032-66118), we indicated that we were considering the
development of a home health value-based purchasing (HHVBP) model. We
sought comments on a future HHVBP model, including elements of the
model; size of the payment incentives and percentage of payments that
would need to be placed at risk in order to spur home health agencies
(HHAs) to make the necessary investments to improve the quality of care
for Medicare beneficiaries; the timing of the payment adjustments; and,
how performance payments should be distributed. We also sought comments
on the best approach for selecting states for participation in this
model. We noted that if the decision was made to move forward with the
implementation of a HHVBP model in CY 2016, we would solicit additional
comments on a more detailed model proposal to be included in future
rulemaking.
In the CY 2015 HH PPS final rule,\8\ we indicated that we received
a number of comments related to the magnitude of the percentage payment
adjustments; evaluation criteria; payment features; a beneficiary risk
adjustment strategy; state selection methodology; and the approach to
selecting Medicare-certified HHAs. A number of commenters supported the
development of a value-based purchasing model in the home health
industry in whole or in part with consideration of the design
parameters provided. No commenters provided strong counterpoints or
alternative design options which dissuaded CMS from moving forward with
general design and framework of the HHVBP model as discussed in the CY
2015 HH PPS proposed rule. All comments were considered in our decision
to develop an HHVBP model for implementation beginning January 1, 2016.
Therefore, in the CY 2016 HH PPS proposed rule, we proposed to
implement a HHVBP model, which included a randomized state selection
methodology; a reporting framework; a payment adjustment methodology; a
payment adjustment schedule by performance year and payment adjustment
percentage; a quality measures selection methodology, classifications
and weighting, measures for performance year one, including the
reporting of New Measures, and a framework for proposing to adopt
measures for subsequent performance years; a performance scoring
methodology, which includes performance based on achievement and
improvement; a review and recalculation period; and an evaluation
framework. As we discuss in more detail below, we are finalizing our
proposal to implement the HHVBP Model beginning January 1, 2016. We
respond to comments received on the proposed components of the model,
and discuss our final policies with respect to each of these
components, in the relevant sections below.
---------------------------------------------------------------------------
\8\ Medicare and Medicaid Programs; CY 2015 Home Health
Prospective Payment System Rate Update; Home Health Quality
Reporting Requirements; and Survey and Enforcement Requirements for
Home Health Agencies, 79 FR 66105-66106 (November 6, 2014).
---------------------------------------------------------------------------
The basis for developing the proposed value-based purchasing (VBP)
model, as described in the proposed regulations at Sec. 484.300 et
seq., stems from several important areas of consideration. First, we
expect that tying quality to payment through a system of value-based
purchasing will improve the beneficiaries' experience and outcomes. In
turn, we expect payment adjustments that both reward improved quality
and penalize poor performance will incentivize quality improvement and
encourage efficiency, leading to a more sustainable payment system.
Second, section 3006(b) of the Affordable Care Act directed the
Secretary of the Department of Health and Human Services (the
Secretary) to develop a plan to implement a VBP program for payments
under the Medicare Program for HHAs and the Secretary issued an
associated Report to Congress in March of 2012 (2012 Report).\9\ The
2012 Report included a roadmap for implementation of an HHVBP model and
outlined the need to develop an HHVBP program that aligns with other
Medicare programs and coordinates incentives to improve quality. The
2012 Report also indicated that a HHVBP program should build on and
refine existing quality measurement tools and processes. In addition,
the 2012 Report indicated that one of the ways that such a program
could link payment to quality would be to tie payments to overall
quality performance.
---------------------------------------------------------------------------
\9\ CMS, ``Report to Congress: Plan to Implement a Medicare Home
Health Agency Value-Based Purchasing Program'' (March 15, 2012)
available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/downloads/stage-2-NPRM.PDF.
---------------------------------------------------------------------------
Third, section 402(a)(1)(A) of the Social Security Amendments of
1967 (as amended) (42 U.S.C. 1395b-1(a)(1)(A)), provided authority for
us to conduct the Home Health Pay-for-Performance (HHPFP) Demonstration
that ran from 2008 to 2010. The results of that demonstration found
modest quality improvement in certain measures after comparing the
quality of care furnished by demonstration participants to the quality
of care furnished by the control group. One important lesson learned
from the HHPFP Demonstration was the need to link the HHA's quality
improvement efforts and the incentives. HHAs in three of the four
regions generated enough savings to have incentive payments in the
first year of the demonstration, but the size of payments were unknown
until after the conclusion of the demonstration. Also, the time lag
between quality performance and payment incentives was too long to
provide a sufficient motivation for HHAs to take necessary steps to
improve quality. The results of the demonstration, published in a
comprehensive evaluation report \10\ suggest that future models could
benefit from ensuring that incentives are reliable enough, of
sufficient magnitude, and paid in a timely fashion to encourage HHAs to
be fully engaged in the quality of care initiative.
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\10\ ``CMS Report on Home Health Agency Value-Based Purchasing
Program'' (February of 2012) available at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Reports/Downloads/HHP4P_Demo_Eval_Final_Vol1.pdf.
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Furthermore, the President's FY 2015 and 2016 Budgets proposed that
VBP should be extended to additional providers including skilled
nursing facilities, home health agencies, ambulatory surgical centers,
and hospital outpatient departments. The FY 2015 Budget called for at
least 2-percent of payments to be tied to quality and efficiency of
care on a budget neutral
[[Page 68657]]
basis. The FY 2016 Budget outlines a program which would tie at least
2-percent of Medicare payments to the quality and efficiency of care in
the first 2 years of implementation beginning in 2017, and at least 5-
percent beginning in 2019 without any impact to the budget. We proposed
and are finalizing an HHVBP model that follows a graduated payment
adjustment strategy within certain selected states beginning January 1,
2016.
The Secretary has also set two overall delivery system reform goals
for CMS. First, we seek to tie 30-percent of traditional, or fee-for-
service, Medicare payments to quality or value-based payments through
alternative payment models by the end of 2016, and to tie 50-percent of
payments to these models by the end of 2018. Second, we seek to tie 85-
percent of all traditional Medicare payments to quality or value by
2016 and 90-percent by 2018.\11\ To support these efforts the Health
Care Payment Learning and Action Network was recently launched to help
advance the work being done across sectors to increase the adoption of
value-based payments and alternative payment models. We believe that
testing the HHVBP Model would support these goals.
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\11\ Content of this announcement can be found at https://www.hhs.gov/news/press/2015pres/01/20150126a.html.
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Finally, we have already successfully implemented the Hospital
Value-Based Purchasing (HVBP) program, under which value-based
incentive payments are made in a fiscal year to hospitals that meet
performance standards established for a performance period with respect
to measures for that fiscal year. The percentage of a participating
hospital's base-operating DRG payment amount for FY 2016 discharges
that is at risk, based on the hospital's performance under the program
for that fiscal year, is 1.75 percent. That percentage will increase to
2.0 by FY 2017. We proposed and are finalizing in this rule an HHVBP
Model that builds on the lessons learned and guidance from the HVBP
program and other applicable demonstrations as discussed above, as well
as from the evaluation report discussed earlier.
As we stated in the CY 2016 HH PPS proposed rule, the HHVBP Model
presents an opportunity to improve the quality of care furnished to
Medicare beneficiaries and study what incentives are sufficiently
significant to encourage HHAs to provide high quality care. The HHVBP
Model will offer both a greater potential reward for high performing
HHAs as well as a greater potential downside risk for low performing
HHAs. We proposed, and are finalizing in this rule, that the model will
begin on January 1, 2016, and include an array of measures that would
capture the multiple dimensions of care that HHAs furnish.
The HHVBP Model, as finalized, will be tested by CMS's Center for
Medicare and Medicaid Innovation (CMMI) under section 1115A of the Act.
Under section 1115A(d)(1) of the Act, the Secretary may waive such
requirements of Titles XI and XVIII and of sections 1902(a)(1),
1902(a)(13), and 1903(m)(2)(A)(iii) as may be necessary solely for
purposes of carrying out section 1115A with respect to testing models
described in section 1115A(b). The Secretary is not issuing any waivers
of the fraud and abuse provisions in sections 1128A, 1128B, and 1877 of
the SSA or any other Medicare or Medicaid fraud and abuse laws for this
model. Thus, notwithstanding any other provisions of this rule, all
providers participating in the HHVBP Model must comply with all
applicable fraud and abuse laws and regulations. Therefore, to clarify
the scope of the Secretary's authority we have finalized Sec. 484.300
confirming authority to establish Part F under sections 1102, 1115A,
and 1871 of the Act (42 U.S.C. 1315a), which authorizes the Secretary
to issue regulations to operate the Medicare program and test
innovative payment and service delivery models to improve coordination,
quality, and efficiency of health care services furnished under Title
XVIII.
As we proposed, we are using section 1115A(d)(1) waiver authority
to apply a reduction or increase of up to 8-percent to current Medicare
payments to competing HHAs delivering care to beneficiaries in selected
states, depending on the HHA's performance on specified quality
measures relative to its peers. Specifically, the HHVBP Model will
utilize the waiver authority to adjust Medicare payment rates under
section 1895(b) of the Act.\12\ In accordance with the authority
granted to the Secretary in section 1115A(d)(1) of the Act, we are
waiving section 1895(b)(4) of the Act only to the extent necessary to
adjust payment amounts to reflect the value-based payment adjustments
under this model for Medicare-certified HHAs in specified states
selected in accordance with CMS's selection methodology. We are not
implementing this model under the authority granted by the Affordable
Care Act under section 3131 (``Payment Adjustments for Home Health
Care'').
---------------------------------------------------------------------------
\12\ 42 U.S.C. 1395fff.
---------------------------------------------------------------------------
We are finalizing in this rule, as we proposed, that the defined
population includes all Medicare beneficiaries provided care by any
Medicare-certified HHA delivering care within the selected states.
Medicare-certified HHAs that are delivering care within selected states
are considered `Competing Home Health Agencies' within the scope of
this HHVBP Model. If care is delivered outside of selected states, or
within a non-selected state that does not have a reciprocal agreement
with a selected state, payments for those beneficiaries are not
considered within the scope of the model because we are basing
participation in the model on state-specific CMS Certification Numbers
(CCNs). Payment adjustments for each year of the model will be
calculated based on a comparison of how well each competing HHA
performed during the performance period for that year (proposed, and
finalized below, to be one year in length, starting in CY 2016) with
its performance on the same measures in 2015 (proposed, and finalized
below, to be the baseline data year).
As we proposed, and are finalizing in this rule, the first
performance year will be CY 2016, the second will be CY 2017, the third
will be CY 2018, the fourth will be 2019, and the fifth will be CY
2020. Greater details on performance periods are outlined in Section
D--Performance Assessment and Payment Periods. This model will test
whether being subject to significant payment adjustments to the
Medicare payment amounts that would otherwise be made to competing
Medicare-certified HHAs would result in statistically-significant
improvements in the quality of care being delivered to this specific
population of Medicare beneficiaries.
We proposed, and are finalizing in this rule, to identify Medicare-
certified HHAs to compete in this model using state borders as
boundaries. We do so under the authority granted in section 1115A(a)(5)
of the Act to elect to limit testing of a model to certain geographic
areas. This decision is influenced by the 2012 Report to Congress
mandated under section 3006(b) of the Affordable Care Act. This Report
stated that HHAs which participated in previous value-based purchasing
demonstrations ``uniformly believed that all Medicare-certified HHAs
should be required to participate in future VBP programs so all
agencies experience the potential burdens and benefits of the program''
and some HHAs expressed concern that absent mandatory participation,
``low-performing agencies in areas with
[[Page 68658]]
limited competition may not choose to pursue quality improvement.''
\13\
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\13\ See the Recommendations section of the U.S. Department of
Health and Human Services. Report to Congress: Plan to Implement a
Medicare Home Health Agency Value-Based Purchasing Program.'' (March
2012) p. 28.
---------------------------------------------------------------------------
Section 1115A(b)(2)(A) of the Act requires that the Secretary
select models to be tested where the Secretary determines that there is
evidence that the model addresses a defined population for which there
are deficits in care leading to poor clinical outcomes or potentially
avoidable expenditures. The HHVBP Model was developed to improve care
for Medicare patients receiving care from HHAs based on evidence in the
March 2014 MedPAC Report to Congress citing quality and cost concerns
in the home health sector. According to MedPAC, ``about 29-percent of
post-hospital home health stays result in readmission, and there is
tremendous variation in performance among providers within and across
geographic regions.'' \14\ The same report cited limited improvement in
quality based on existing measures, and noted that the data on quality
``are collected only for beneficiaries who do not have their home
health care stays terminated by a hospitalization,'' skewing the
results in favor of a healthier segment of the Medicare population.\15\
This model will test the use of adjustments to Medicare HH PPS rates by
tying payment to quality performance with the goal of achieving the
highest possible quality and efficiency.
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\14\ See full citation at note 11. MedPAC Report to Congress
(March 2014) p. 215.
\15\ MedPAC Report to Congress (March 2014) p. 226.
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B. Overview
We proposed to include in Sec. 484.305 definitions for
``applicable percent'', ``applicable measure'', ``benchmark'', ``home
health prospective payment system'', ``larger-volume cohort'', ``linear
exchange function'', ``Medicare-certified home health agency'', ``New
Measures'', ``payment adjustment'', ``performance period'', ``smaller-
volume cohort'', ``selected states'', ``starter set'', ``Total
Performance Score'', and ``value-based purchasing'' as they pertain to
this subpart. Where we received comments on the proposed definitions or
the substantive provisions of the model connected to the proposed
definitions, we respond to comments in the relevant sections below. We
are finalizing all the definitions as proposed in Sec. 484.305 except
for two: We are revising ``applicable percent'' so the final definition
reflects the revised percentages as 3-percent for CY 2018, 5-percent
for CY 2019, 6-percent for 2020; 7-percent for CY 2021 and 8-percent
for CY 2022, as discussed in section G and we are revising ``Medicare-
certified home health agency'' as ``Competing home health agency'' for
clarity, since all HHAs with CCNs are, by definition, Medicare-
certified, and only those HHAs in selected states are competing in the
model. As we proposed and are finalizing in this rule, the HHVBP Model
will encompass 5 performance years and be implemented beginning January
1, 2016 and conclude on December 31, 2022.
Payment and service delivery models are developed by CMMI in
accordance with the requirements of section 1115A of the Act. During
the development of new models, CMMI builds on the ideas received from
internal and external stakeholders and consults with clinical and
analytical experts.
We are finalizing our proposal to implement a HHVBP Model that has
an overall purpose of improving the quality and efficient delivery of
home health care services to the Medicare population. The specific
goals of the model are to:
1. Incentivize HHAs to provide better quality care with greater
efficiency;
2. Study new potential quality and efficiency measures for
appropriateness in the home health setting; and,
3. Enhance current public reporting processes.
We proposed that the HHVBP Model would adjust Medicare HHA payments
over the course of the model by up to 8-percent depending on the
applicable performance year and the degree of quality performance
demonstrated by each competing HHA. As discussed in greater detail in
section G, we are finalizing this proposal with modification. Under our
final policy, the model will reduce the HH PPS final claim payment
amount to an HHA for each episode in a calendar year by an amount up to
the applicable percentage revised and defined in Sec. 484.305. The
timeline of payment adjustments as they apply to each performance year
is described in greater detail in the section D2 entitled ``Payment
Adjustment Timeline.''
As we proposed, and are finalizing in this rule, the model will
apply to all Medicare-certified HHAs in each of the selected states,
which means that all HHAs in the selected states will be required to
compete. We codify this policy at 42 CFR 484.310. Furthermore, a
competing HHA will only be measured on performance for care delivered
to Medicare beneficiaries within selected states (with rare exceptions
given for care delivered when a reciprocal agreement exists between
states). The distribution of payment adjustments will be based on
quality performance, as measured by both achievement and improvement,
across a set of quality measures rigorously constructed to minimize
burden as much as possible and improve care. Competing HHAs that
demonstrate they can deliver higher quality of care in comparison to
their peers (as defined by the volume of services delivered within the
selected state), or their own past performance, could have their
payment for each episode of care adjusted higher than the amount that
otherwise would be paid under section 1895 of the Act. Competing HHAs
that do not perform as well as other competing HHAs of the same size in
the same state might have their payments reduced and those competing
HHAs that perform similarly to others of similar size in the same state
might have no payment adjustment made. This operational concept is
similar in practice to what is used in the HVBP program.
We expect that the risk of having payments adjusted in this manner
will provide an incentive among all competing HHAs delivering care
within the boundaries of selected states to provide significantly
better quality through improved planning, coordination, and management
of care. The degree of the payment adjustment will be dependent on the
level of quality achieved or improved from the baseline year, with the
highest upward performance adjustments going to competing HHAs with the
highest overall level of performance based on either achievement or
improvement in quality. The size of a competing HHA's payment
adjustment for each year under the model will be dependent upon that
HHA's performance with respect to that calendar year relative to other
competing HHAs of similar size in the same state and relative to its
own performance during the baseline year.
We proposed that states would be selected randomly from nine
regional groupings for model participation. As discussed further in
section IV.C. of this rule, we are finalizing this proposal. A
competing HHA is only measured on performance for care delivered to
Medicare beneficiaries within boundaries of selected states and only
payments for HHA services provided to Medicare beneficiaries within
boundaries of selected states will be subject to adjustment under this
model unless a reciprocal agreement is in place. Requiring all
Medicare-certified HHAs within the boundaries of selected
[[Page 68659]]
states to compete in the model ensures that: (1) There is no self-
selection bias, (2) competing HHAs are representative of HHAs
nationally, and (3) there is sufficient participation to generate
meaningful results. We believe it is necessary to require all HHAs
delivering care within boundaries of selected states to be included in
the model because, in our experience, Medicare-providers are generally
reluctant to participate voluntarily in models in which their Medicare
payments could be subject to possible reduction. This reluctance to
participate in voluntary models has been shown to cause self-selection
bias in statistical assessments and thus, may present challenges to our
ability to evaluate the model. In addition, state boundaries represent
a natural demarcation in how quality is currently being assessed
through Outcome Assessment Information Set (OASIS) measures on Home
Health Compare (HHC). Secondly, it is our intent to generate an
appropriate selection of competitor types in this model as a means of
yielding the most optimal level of generalizability and
representativeness of HHAs in the nation. Finally, having an
appropriate number of competitors within the model should generate an
appropriate statistical power to detect key effects we are testing in
this model.
C. Selection Methodology
1. Identifying a Geographic Demarcation Area
We proposed to adopt a methodology that uses state borders as
boundaries for demarcating which Medicare-certified HHAs will be
required to compete in the model and proposed to select nine states
from nine geographically-defined groupings of five or six states.
Groupings were also defined so that the successful implementation of
the model would produce robust and generalizable results, as discussed
later in this section. We are finalizing this approach here.
We took into account five key factors when deciding to propose
selection at the state-level for this model. First, if we required
some, but not all, Medicare-certified HHAs that deliver care within the
boundaries of a selected state to participate in the model, we believe
the HHA market for the state could be disrupted because HHAs in the
model would be competing against HHAs that are not included in the
model (herein referenced `non-competing HHAs'). Second, we wanted to
ensure that the distribution of payment adjustments based on
performance under the model could be extrapolated to the entire
country. Statistically, the larger the sample to which payment
adjustments are applied, the smaller the variance of the sampling
distribution and the greater the likelihood that the distribution
accurately predicts what would transpire if the methodology were
applied to the full population of HHAs. Third, we considered the need
to align with other HHA quality program initiatives including HHC. The
HHC Web site presently provides the public and HHAs a state- and
national-level comparison of quality. We expect that aligning
performance with the HHVBP benchmark and the achievement score will
support how measures are currently being reported on HHC. Fourth, there
is a need to align with CMS regulations which require that each HHA
have a unique CMS Certification Number (CCN) for each state in which
the HHA provides service. Fifth, we wanted to ensure sufficient sample
size and the ability to meet the rigorous evaluation requirements for
CMMI models. These five factors are important for the successful
implementation and evaluation of this model.
We expect that when there is a risk for a downward payment
adjustment based on quality performance measures, the use of a self-
contained, mandatory cohort of HHA participants will create a stronger
incentive to deliver greater quality among competing HHAs.
Specifically, it is possible the market would become distorted if non-
model HHAs are delivering care within the same market as competing HHAs
because competition, on the whole, becomes unfair when payment is
predicated on quality for one group and volume for the other group. In
addition, we expect that evaluation efforts might be negatively
impacted because some HHAs would be competing on quality and others on
volume, within the same market.
We proposed the use of state boundaries after careful consideration
of several alternative selection approaches, including randomly
selecting HHAs from all HHAs across the country, and requiring
participation from smaller geographic regions including the county; the
Combined Statistical Area (CSA); the Core-Based Statistical Area
(CBSA); Metropolitan Statistical Area (MSA) rural provider level; and
the Hospital Referral Region (HRR) level.
A methodology using a national sample of HHAs that are randomly
selected from all HHAs across the country could be designed to include
enough HHAs to ensure robust payment adjustment distribution and a
sufficient sample size for the evaluation; however, this approach may
present significant limitations when compared with the state boundaries
selection methodology we proposed in this model. Of primary concern
with randomly selecting at the provider-level across the nation is the
issue with market distortions created by having competing HHAs
operating in the same market as non-model HHAs.
Using smaller geographic areas than states, such as counties, CSAs,
CBSAs, rural, and HRRs, could also present challenges for this model.
These smaller geographic areas were considered as alternate selection
options; however, their use could result in too small of a sample size
of potential competing HHAs. As a result, we expect the distribution of
payment adjustments could become highly divergent among fewer HHA
competitors. In addition, the ability to evaluate the model could
become more complex and may be less generalizable to the full
population of Medicare-certified HHAs and the beneficiaries they serve
across the nation. Further, the use of smaller geographic areas than
states could increase the proportion of Medicare-certified HHAs that
could fall into groupings with too few agencies to generate a stable
distribution of payment adjustments. Thus, if we were to define
geographic areas based on CSAs, CBSAs, counties, or HRRs, we would need
to develop an approach for consolidating smaller regions into larger
regions.
Home health care is a unique type of health care service when
compared to other Medicare provider types. In general, the HHA's care
delivery setting is in the beneficiaries' homes as opposed to other
provider types that traditionally deliver care at a brick and mortar
institution within beneficiaries' respective communities. As a result,
the HHVBP Model needs to be designed to account for the unique way that
HHA care is provided in order for results to be generalizable to the
population. HHAs are limited to providing care to beneficiaries in the
state that they have a CCN however; HHAs are not restricted from
providing service in a county, CSA, CBSA or HRR that they are not
located in (as long as the other county/CBSA/HRR is in the same state
in which the HHA is certified). As a result, using smaller geographic
areas (than state boundaries) could result in similar market distortion
and evaluation confounders as selecting providers from a randomized
national sampling. The reason is that HHAs in adjacent counties/CSAs/
CBSAs/HRRs may not be in the model but, would be directly competing for
services in the same markets or geographic regions. Competing HHAs
delivering care in the
[[Page 68660]]
same market area as non-competing HHAs could generate a spillover
effect where non-model HHAs would be vying for the same beneficiaries
as competing HHAs. This spillover effect presents several issues for
evaluation as the dependent variable (quality) becomes confounded by
external influences created by these non-competing HHAs. These
unintentional external influences on competing HHAs may be made
apparent if non-competing HHAs become incentivized to generate greater
volume at the expense of quality delivered to the beneficiaries they
serve and at the expense of competing HHAs that are paid on quality
instead of volume. Further, the ability to extrapolate these results to
the full population of HHAs and the beneficiaries they serve becomes
confounded by an artifact of the model and inferences would be limited
from an inability to duplicate these results. While these concerns
would decrease in some order of magnitude as larger regions are
considered, the only way to eliminate these concerns entirely is to
define inclusion among Medicare-certified HHAs at the state level.
In addition, home health quality data currently displayed on HHC
allows users to compare HHA services furnished within a single state.
Selecting HHAs using other geographic regions that are smaller and/or
cross state lines could require the model to deviate from the
established process for reporting quality. For these reasons, we stated
in the proposed rule that we believe a selection methodology based on
the use of Medicare-certified HHAs delivering care within state
boundaries is the most appropriate for the successful implementation
and evaluation of this model. In the proposed rule, we requested
comments on this proposed state selection methodology as well as
potential alternatives. We summarize and respond to comments received
at the end of this section (section IV.C.). As we discuss below, we are
finalizing the state selection model as proposed.
2. Overview of the Randomized Selection Methodology for States
We proposed the state selections listed in proposed Sec. 484.310
based on the described proposed randomized selection methodology. We
proposed to group states by each state's geographic proximity to one
another accounting for key evaluation characteristics (that is,
proportionality of service utilization, proportionality of
organizations with similar tax-exempt status and HHA size, and
proportionality of beneficiaries that are dually-eligible for Medicare
and Medicaid).
Based on an analysis of OASIS quality data and Medicare claims
data, we stated in the proposed rule that we believe the use of nine
geographic groupings would account for the diversity of beneficiary
demographics, rural and urban status, cost and quality variations,
among other criteria. To provide for comparable and equitable selection
probabilities, these separate geographic groupings each include a
comparable number of states. Under our proposed methodology, groupings
were based on states' geographic proximity to one another, having a
comparable number of states if randomized for an equal opportunity of
selection, and similarities in key characteristics that will be
considered in the evaluation study because the attributes represent
different types of HHAs, regulatory oversight, and types of
beneficiaries served. This is necessary for the evaluation study to
remain objective and unbiased and so that the results of this study
best represent the entire population of Medicare-certified HHAs across
the nation.
Several of the key characteristics we used for grouping state
boundaries into clusters for selection into the model are also used in
the impact analysis of our annual HHA payment updates, a fact that
reinforces their relevance for evaluation. The additional proposed
standards for grouping (level of utilization and socioeconomic status
of patients) are also important to consider when evaluating the
program, because of their current policy relevance. Large variations in
the level of utilization of the home health benefit has received
attention from policymakers concerned with achieving high-value health
care and curbing fraud and abuse.\16\ Policymakers' concerns about the
role of beneficiary-level characteristics as determinants of resource
use and health care quality were highlighted in the Affordable Care
Act, which mandated a study \17\ of access to home health care for
vulnerable populations \18\ and, more recently, the Improving Medicare
Post-acute Care Transformation (IMPACT) Act of 2014 required the
Secretary to study the relationship between individuals' socioeconomic
status and resource use or quality.\19\ The parameters used to define
each geographic grouping are further described in the next three
sections.
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\16\ See MedPAC Report to Congress: Medicare Payment Policy
(March 2014, Chapter 9) available at https://medpac.gov/documents/reports/mar14_entirereport.pdf. See also the Institute of Medicine
Interim Report of the Committee on Geographic Variation in Health
Care Spending and Promotion of High-Value Health Care: Preliminary
Committee Observations (March 2013) available at https://iom.edu/Reports/2013/Geographic-Variation-in-Health-Care-Spending-and-Promotion-of-High-Care-Value-Interim-Report.aspx.
\17\ This study can be accessed at https://www.cms.gov/Center/Provider-Type/Home-Health-Agency-HHA-Center.html.
\18\ Section 3131(d) of the Affordable Care Act.
\19\ Improving Medicare Post-acute Care Transformation (IMPACT)
Act of 2014 (Public Law 113-185).
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a. Geographic Proximity
We explained in the proposed rule that under this methodology, in
order to ensure that the Medicare-certified HHAs that would be required
to participate in the model are not all in one region of the country,
the states in each grouping are adjacent to each other whenever
possible while creating logical groupings of states based on common
characteristics as described above. Specifically, analysis based on
quality data and claims data found that HHAs in these neighboring
states tend to hold certain characteristics in common. These include
having similar patterns of utilization, proportionality of non-profit
agencies, and types of beneficiaries served (for example, severity and
number, type of co-morbidities, and socio-economic status). Therefore,
the proposed groupings of states were delineated according to states'
geographic proximity to one another and common characteristics as a
means of permitting greater comparability. In addition, each of the
groupings retains similar types of characteristics when compared to any
other type of grouping of states.
b. Comparable Number of States in Each Grouping
Under the proposed randomized selection methodology, each
geographic region, or grouping, has a similar number of states. As a
result, all states had a 16.7-percent to 20-percent chance of being
selected under our proposed methodology, and Medicare-certified HHAs
had a similar likelihood of being required to compete in the model by
using this sampling design. We asserted in the proposed rule that this
sampling design would ensure that no single entity is singled out for
selection, since all states and Medicare-certified HHAs would have
approximately the same chance of being selected. In addition, this
sampling approach would mitigate the opportunity for HHAs to self-
select into the model and thereby bias any results of the test.
[[Page 68661]]
c. Characteristics of State Groupings
Without sacrificing an equal opportunity for selection, we
explained in the proposed rule that the proposed state groupings are
intended to ensure that important characteristics of Medicare-certified
HHAs that deliver care within state boundaries can be used to evaluate
the primary intervention with greater generalizability and
representativeness of the entire population of Medicare-certified HHAs
in the nation. Data analysis of these characteristics employed the full
data set of Medicare claims and OASIS quality data. Although some
characteristics, such as beneficiary age and case-mix, yielded some
variations from one state to another, other important characteristics
do vary substantially and could influence how HHAs respond to the
incentives of the model. Specifically, home health services utilization
rates, tax-exemption status of the provider, the socioeconomic status
of beneficiaries (as measured by the proportion of dually-eligible
beneficiaries), and agency size (as measured by average number of
episodes of care per HHA), are important characteristics that could
influence outcomes of the model. Subsequently, we intend to study the
impacts of these characteristics for purposes of designing future
value-based purchasing models and programs. These characteristics and
expected variations must be considered in the evaluation study to
enable us to avoid erroneous inferences about how different types of
HHAs will respond to HHVBP incentives.
Under our proposed state selection methodology, state groupings
reflect regional variations that enhance the generalizability of the
model. In line with this methodology, each grouping includes states
that are similar in at least one important aforementioned
characteristic while being geographically located in close proximity to
one another. Using the criteria described above, the following
geographic groupings were identified using Medicare claims-based data
from calendar years 2013-2014. Each of the 50 states was assigned to
one of the following geographic groups:
Group #1: (VT, MA, ME, CT, RI, NH)
States in this group tend to have larger HHAs and have average
utilization relative to other states.
Group #2: (DE, NJ, MD, PA, NY)
States in this group tend to have larger HHAs, have lower
utilization, and provide care to an average number of dually-eligible
beneficiaries relative to other states.
Group #3: (AL, GA, SC, NC, VA)
States in this group tend to have larger HHAs, have average
utilization rates, and provide care to a high proportion of minorities
relative to other states.
Group #4: (TX, FL, OK, LA, MS)
States in this group have HHAs that tend to be for-profit, have
very high utilization rates, and have a higher proportion of dually-
eligible beneficiaries relative to other states.
Group #5: (WA, OR, AK, HI, WY, ID)
States in this group tend to have smaller HHAs, have average
utilization rates, and are more rural relative to other states.
Group #6: (NM, CA, NV, UT, CO, AZ)
States in this group tend to have smaller HHAs, have average
utilization rates, and provide care to a high proportion of minorities
relative to other states.
Group #7: (ND, SD, MT, WI, MN, IA)
States in this group tend to have smaller HHAs, have very low
utilization rates, and are more rural relative to other states.
Group #8: (OH, WV, IN, MO, NE., KS)
States in this group tend to have HHAs that are of average size,
have average utilization rates, and provide care to a higher proportion
of dually-eligible beneficiaries relative to other states.
Group #9: (IL, KY, AR, MI, TN)
States in this group tend to have HHAs with higher utilization
rates relative to other states.
d. Randomized Selection of States
We stated in the proposed rule that upon the careful consideration
of the alternative selection methodologies discussed in that rule,
including selecting states on a non-random basis, we proposed to use a
selection methodology based on a randomized sampling of states within
each of the nine regional groupings described above. We examined data
on the evaluation elements listed in this section of the proposed rule
and this final rule to determine if specific states could be identified
in order to fulfill the needs of the evaluation. After careful review,
we determined that each evaluation element could be measured by more
than one state. As a result, we determined that it was necessary to
apply a fair method of selection where each state would have a
comparable opportunity of being selected and which would fulfill the
need for a robust evaluation. The proposed nine groupings of states, as
described in this section of the proposed rule and this final rule,
permit the model to capture the essential elements of the evaluation
including demographic, geographic, and market factors.
We explained in the proposed rule that the randomized sampling of
states is without bias to any characteristics of any single state
within any specific regional grouping, where no states are excluded,
and no state appears more than once across any of the groupings. The
randomized selection of states was completed using a scientifically-
accepted computer algorithm designed for randomized sampling. The
randomized selection of states was run on each of the previously
described regional groupings using exactly the same process and,
therefore, reflects a commonly accepted method of randomized sampling.
This computer algorithm employs the aforementioned sampling parameters
necessary to define randomized sampling and omits any human interaction
once it runs.
Based on this sampling methodology, SAS Enterprise Guide (SAS EG)
5.1 software was used to run a computer algorithm designed to randomly
select states from each grouping. SAS EG 5.1 and the computer algorithm
were employed to conduct the randomized selection of states. SAS EG 5.1
represents an industry-standard for generating advanced analytics and
provided a rigorous, standardized tool by which to satisfy the
requirements of randomized selection. The key SAS commands employed
include a ``PROC SURVEYSELECT'' statement coupled with the
``METHOD=SRS'' option used to specify simple random sampling as the
sample selection method. A random number seed was generated by using
the time of day from the computer's clock. The random number seed was
used to produce random number generation. Note that no stratification
was used within any of the nine geographically-diverse groupings to
ensure there is an equal probability of selection within each grouping.
For more information on this procedure and the underlying statistical
methodology, please reference SAS support documentation at: https://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#statug_surveyselect_sect003.htm/.
Based on consideration of the comments received and for the reasons
discussed, we believe this state selection methodology provides the
strongest evidence of producing meaningful results representative of
the
[[Page 68662]]
national population of competing Medicare-certified HHAs and, in turn,
meets the evaluation requirements of section 1115A(b)(4) of the Act.
In Sec. 484.310, we proposed to codify the names of the states
selected utilizing this proposed methodology, where one state from each
of the nine groupings was selected. For each of these groupings, we
proposed to use state borders to demarcate which Medicare-certified
HHAs would be required to compete in this model: Massachusetts was
randomly selected from Group 1, Maryland was randomly selected from
Group 2, North Carolina was randomly selected from Group 3, Florida was
randomly selected from Group 4, Washington was randomly selected from
Group 5, Arizona was randomly selected from Group 6, Iowa was randomly
selected from Group 7, Nebraska was randomly selected from Group 8, and
Tennessee was randomly selected from Group 9. Thus, we explained in the
proposed rule that if our methodology is finalized as proposed, all
Medicare-certified HHAs that provide services in Massachusetts,
Maryland, North Carolina, Florida, Washington, Arizona, Iowa, Nebraska,
and Tennessee will be required to compete in this model. We invited
comments on this proposed randomized selection methodology.
We summarize and respond to these comments at the end of this
section. As discussed we are finalizing the state selection methodology
as proposed without modification, as well as finalizing the states that
were selected utilizing this methodology as codified in Sec. 484.310.
e. Use of CMS Certification Numbers (CCNs)
We proposed that Total Performance Scores (TPS) and payment
adjustments would be calculated based on an HHA's CCN \20\ and,
therefore, based only on services provided in the selected states. The
exception to this methodology is where an HHA provides service in a
state that also has a reciprocal agreement with another state. Services
being provided by the HHA to beneficiaries who reside in another state
would be included in the TPS and subject to payment adjustments.\21\
The reciprocal agreement between states allows for an HHA to provide
services to a beneficiary across state lines using its original CCN
number. Reciprocal agreements are rare and, as identified using the
most recent Medicare claims data from 2014, there was found to be less
than 0.1 percent of beneficiaries that provided services that were
being served by CCNs with reciprocal agreements across state lines. Due
to the very low number of beneficiaries served across state borders as
a result of these agreements, we stated in the proposed rule that we
expect there to be an inconsequential impact by including these
beneficiaries in the model.
---------------------------------------------------------------------------
\20\ HHAs are required to report OASIS data and any other
quality measures by its own unique CMS Certification Number (CCN) as
defined under title 42, chapter IV, subchapter G, part 484, Sec.
484.20 Available at URL https://www.ecfr.gov/cgi-bin/text-idx?tpl=/ecfrbrowse/Title42/42cfr484_main_02.tpl.
\21\ See Chapter 2 of the State Operations Manual (SOM), Section
2184--Operation of HHAs Cross State Lines, stating ``When an HHA
provides services across State lines, it must be certified by the
State in which its CCN is based, and its personnel must be qualified
in all States in which they provide services. The appropriate SA
completes the certification activities. The involved States must
have a written reciprocal agreement permitting the HHA to provide
services in this manner.''
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We received the following comments on the proposed selection
methodology. As discussed, we are finalizing the selection methodology
as proposed.
Comment: A few commenters expressed concern that participating HHAs
will receive payment adjustment incentives based on quality of care,
while non-participating HHAs in the same geographic area might be
incentivized to generate greater volume at the expense of quality. Some
commenters recommended expanding the model to allow more states to
participate in each succeeding year of the model to prevent non-
participating states from falling behind, and some commenters also
recommended CMS shorten the duration of the model to three (3) years to
expedite the implementation of VBP nationally.
Response: Competing HHAs within the selected states will not be
compared with non-competing HHAs within the same geographic area. HHAs
will not compete across state borders, other than those HHAs that may
provide services in a state that has a reciprocal agreement with
another state. Specifically, the model is designed to have HHAs compete
only within their state and within their size cohort, as discussed
further in section F. Competing HHAs will not compete for payment
adjustment incentives outside of their state or size cohort. The
decision to utilize states to select HHAs for inclusion in the model
was based on a range of factors related to implementation and
evaluation and weighed against other selection alternatives.
Specifically, we considered how the competing HHA's CCN is
operationalized at the state-level and how evaluation will determine
whether the payment adjustment incentive has an effect on quality
within each competing HHA's state and size-cohort. In response to
comments suggesting that non-competing HHAs in non-selected states
might `fall behind,' we again reference the design of the payment
methodology which precludes non-competitors from competing outside of
selected states and size-cohorts. The purpose of this model is to test
the effect of high incentives on quality. Performance measurement is
based on a linear exchange function which only includes competing-HHAs.
If the model yields early positive results within these states and
competing cohorts, expansion may be considered if the requirements of
the statute are met. Section 1115A(c) of the Act authorizes the
Secretary to expand the scope and duration of a model being tested
through rulemaking, including implementation on a nationwide basis. In
addition, we do not expect that HHAs in non-selected states would fall
significantly behind in improving quality because of their interest in
attracting beneficiaries, and improving performance on quality metrics
in other programs, such as the HHQRP. Further, we believe testing the
model over 5 years will provide more data with which to evaluate the
effects of high incentives with greater certainty.
Comment: Several commenters expressed concern regarding how HHAs
are selected to participate in the HHVBP Model. Commenters expressed
concerns centered on leaving behind innovative HHAs in non-
participating states. Many commenters recommended including voluntary
participation by interested innovative HHAs in non-participating states
and carefully documenting characteristics of selected agencies.
Commenters also stated that mandatory participation may potentially put
agencies with fewer resources in selected states at risk for closure.
Response: We appreciate the comments and input on the state
selection methodology. The selection methodology was based on lessons
learned, industry stakeholder perspectives, and an analysis of Medicare
data. For the reasons discussed above, we believe that application of
this methodology will result in participation by HHAs that represent an
accurate reflection of the entire population of Medicare-certified
HHAs, both in terms of size and in terms of quality. In general,
providers do not voluntarily participate in alternate payment models
when payments are at risk of being lowered. This reluctance to
participate in voluntary models has been shown to cause self-selection
bias in statistical assessments and thus, we believe that
[[Page 68663]]
allowing voluntary participation by interested HHAs in non-
participating states could present challenges to our ability to
evaluate the model. In reference to concerns that some HHAs with fewer
resources may be at greater risk for closure, CMS will continue to
monitor for direct associations between HHAs that exhibit poor
performance and the effect of the payment adjustment incentive.
Comment: Commenters questioned the fairness of being required to
participate in both the proposed HHVBP Model and the proposed
Comprehensive Care Joint Replacement Model (CJR).
Response: HHAs located in the MSAs included in the proposed CJR
Model will not be excluded from the HHVBP Model. HHAs are not
participants in the proposed CJR Model. As proposed, Hospitals are the
participants. Home health payments for beneficiaries participating in
the proposed CJR are not subject to alteration under that model. As
proposed, only the hospital payments are at risk. HHAs will continue to
be paid for the services they provide to and bill for Medicare
beneficiaries that are participating in the proposed CJR.
Comment: Some commenters expressed concern that state selection
will not sufficiently represent the Medicare population at large and
impacts a disproportionate portion of the Medicare population. Another
commenter recommended CMS consider a hardship exemption for HHAs with a
high percentage of Medicaid services or that serve a high percentage of
dual-eligible patients. Commenters also expressed concern on various
topics around state selection, including lack of complex urban areas
and corresponding utilization patterns; peer cohorts based simply on
size and state; consideration of profit or non-profit status, hospital-
based or free-standing HHAs, and rural and urban status, all related to
either under-representation or potential bias in the selected competing
HHAs, or over-representation of certain sub-populations of Medicare
beneficiaries included in the model One commenter also recommended
excluding states with populations under a certain threshold, such as
2.5 million, to ensure a large population and making the model more
robust.
Response: We have taken into consideration the level of utilization
and socioeconomic status of patients in grouping states for random
selection, and will evaluate the model sensitive to these differences.
The alternative methodologies proposed by stakeholders did not fulfill
the requirements to be generalizable and representative of the entire
population of Medicare-certified HHAs in the nation. Our mechanisms,
including tracking quality improvement through performance measures and
conducting comparative analysis based on variations on HHA size,
geographic location, organizational structure, and other HHA
demographic information will be utilized for evaluating the model. We
have conducted extensive analysis on the population of HHAs included in
the model and are confident we will be able to effectively extrapolate
model results to the general population. In part, this analysis is
referenced in Table 24 and finds an association between the higher
proportion of dually-eligible beneficiaries serviced and better
performance. The performance and subsequent payment distributions are
consistent with respect to the four described categories (that is
dually-eligible, level of acuity, percent rural, and organization
type). In addition, CMS conducted a statistical analysis of the sample
size of HHAs provided by the nine selected states and determined it was
sufficient to effectively detect the model's impact.
Comment: One commenter stated that Maryland should not be included
in the selected states for HHVBP because Maryland is already
participating in the Maryland All Payer Model. Another commenter
suggested that Florida not be included in both HHVBP and ACO bundling
models because it is difficult for HHAs to track compliance with all
relevant policy and regulatory requirements.
Response: We understand the variances in state demographics, state
regulatory structures, and the interplay with other federal
initiatives, and intend to evaluate how the HHVBP Model performs in the
selected states, including interactions with existing policies, models
and programs operating in the specific states selected. For example,
the Maryland All-Payer Model does not directly intersect with HHVBP
because it is a hospital-based model, so we do not believe this is a
compelling reason to exclude this state. In addition, concerns that
Florida Medicare-certified HHAs would also be included in ACO models is
not a compelling reason to exclude this state because other states have
HHAs participating within ACO models. We do, however, recognize the
need to evaluate the impact of the model in the context of the various
policies and programs operating in those states where participating
HHAs serve patients. As discussed, after consideration of the public
comments received, we are finalizing our proposal to include the nine
selected states as stated in Section 2. In comparison to other
alternatives for selection, we believe the proposed randomized state-
selection method provides an equitable process of selection and a
comparable number of HHAs to account for the power to detect
statistical variations between the payment adjustment incentive as well
as non-financial incentives and their effect on quality. The nine
selected states finalized here will participate for the full duration
of the model.
Comment: One commenter suggested that selected states be more
homogenous in having no prior experience in VBP and to exclude any
states that participated in 2008-2010 HH Pay for Performance
demonstration.
Response: We understand concerns about previous program and model
participation in that some competitors may be more prepared for VBP in
comparison to others. While we are not convinced that we can attribute
the level of preparedness for VBP to the HHA's experience with the
HHP4P Demonstration or any other VBP initiative, we intentionally
developed a methodology for randomized selection of states to prevent
bias to any characteristics of any single state within any specific
grouping. As a result of this randomness of selection, the design
permits an equitable opportunity for selection and provides a greater
capacity to generalize results to the entire population of Medicare-
certified HHAs in the U.S.
Final Decision: For the reasons stated and in consideration of the
comments received, we are finalizing the state selection methodology as
proposed, including the nine states selected under this methodology as
codified at Sec. 484.310. All Medicare-certified HHAs that provide
services in Massachusetts, Maryland, North Carolina, Florida,
Washington, Arizona, Iowa, Nebraska, and Tennessee will be required to
compete in the HHVBP Model.
D. Performance Assessment and Payment Periods
1. Performance Reports
We proposed to use quarterly performance reports, annual payment
adjustment reports, and annual publicly-available performance reports
as a means of developing greater transparency of Medicare data on
quality and aligning the competitive forces within the market to
deliver care based on value over volume, and are finalizing this
reporting structure here. The publicly-reported reports will inform
home health industry
[[Page 68664]]
stakeholders (consumers, physicians, hospitals) as well as all
competing HHAs delivering care to Medicare beneficiaries within
selected state boundaries on their level of quality relative to both
their peers and their own past performance.
We proposed that competing HHAs would be scored for the quality of
care delivered under the model based on their performance on measures
compared to both the performance of their peers, defined by the same
size cohort (either smaller- or larger-volume cohorts as defined in
Sec. 484.305), and their own past performance on the measures. We also
proposed in Sec. 484.305 to define larger-volume cohort to mean the
group of competing HHAs within the boundaries of a selected state that
are participating in Home Health Care Consumer Assessment of Healthcare
Providers and Systems (HHCAHPS) in accordance with Sec. 484.250 and to
define smaller-volume cohort to mean the group of HHAs within the
boundaries of a selected state that are exempt from participation in
HHCAHPS in accordance with Sec. 484.250. We also proposed where there
are too few HHAs in the smaller-volume cohort in each state to compete
in a fair manner (that is, when there is only one or two HHAs competing
within a small cohort in a given state), these HHAs would be included
in the larger-volume cohort for purposes of calculating the total
performance score and payment adjustment without being measured on
HHCAHPS. We requested comments on this proposed methodology.
Comment: A few commenters mentioned the cohort methodology in their
submissions. One commenter offered support to CMS's decision to measure
each HHA against a comparable cohort by size of agency and agreed that
large HHAs with multiple locations have a scale that smaller agencies
do not, rendering outcomes difficult to measure by comparison.
Conversely, other commenters did not support CMS's proposal to base
performance payments on relative performance within HHA peer cohorts,
with one commenter recommending payments should be based solely on
comparisons to prior year performance and another suggesting using
national data for all HHAs, taking into account socio-demographic
factors.
Response: Analysis of existing HHA data (see 80 FR 39910, Table
26--HHA Cohort Payment Adjustment Distributions by State) indicates
dividing HHAs into large and small cohorts results in a higher
likelihood of fair and accurate performance comparisons and the
subsequent payment adjustments. We intend to closely evaluate model
outcomes across a range of demographic factors within the small and
large cohorts, and may modify the model if warranted in subsequent
years.
Final Decision: After considering the comments received, we are
finalizing the large and small cohort structure as proposed.
We proposed that quality performance scores and relative peer
rankings would be determined through the use of a baseline year
(calendar year 2015) and subsequent performance periods for each
competing HHA. Further, these reports will provide competing HHAs with
an opportunity to track their quality performance relative to their
peers and their own past performance. Using these reports provides a
convenient and timely means for competing HHAs to assess and track
their own respective performance as capacity is developed to improve or
sustain quality over time.
Beginning with the data collected during the first quarter of CY
2016 (that is, data for the period January 1, 2016 to March 31, 2016),
and for every quarter of the model thereafter, we proposed to provide
each Medicare-certified HHA with a quarterly report that contains
information on their performance during the quarter. We stated that we
expect to make the first quarterly report available in July 2016, and
make performance reports for subsequent quarters available in October,
January and April. The final quarterly report would be made available
in April 2021. We proposed that the quarterly reports would include a
competing HHA's model-specific performance results with a comparison to
other competing HHAs within its cohort (larger- or smaller-volume)
within the state boundary. These model-specific performance results
will complement all quality data sources already being provided through
the QIES system and any other quality tracking system possibly being
employed by HHAs. We note that all performance measures that competing
HHAs will report through the QIES system are also already made
available in the CASPER Reporting application. The primary difference
between the two reports (CASPER reports and the model-specific
performance report) is that the model-specific performance report we
proposed consolidates the applicable performance measures used in the
HHVBP Model and provides a peer-ranking to other competing HHAs within
the same state and size-cohort. In addition, CASPER reports will
provide quality data earlier than model-specific performance reports
because CASPER reports are not limited by a quarterly run-out of data
and a calculation of competing peer-rankings. For more information on
the accessibility and functionality of the CASPER system, please
reference the CASPER Provider Reporting Guide.\22\
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\22\ The Casper Reporting Guide is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/downloads/HHQICASPER.pdf).
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We proposed that the model-specific quarterly performance report
will be made available to each HHA through a dedicated CMMI model-
specific platform for data dissemination and include each HHA's
relative ranking amongst its peers along with measurement scores and
overall performance rankings.
We also proposed that a separate payment adjustment report would be
provided once a year to each of the competing HHAs. This annual report
will focus primarily on the payment adjustment percentage and include
an explanation of when the adjustment will be applied and how this
adjustment was determined relative to performance scores. Each
competing HHA will receive its own annual payment adjustment report
viewable only to that HHA.
We also proposed a separate, annual, publicly available quality
report that would provide home health industry stakeholders, including
providers and suppliers that refer their patients to HHAs, with an
opportunity to confirm that the beneficiaries they are referring for
home health services are being provided the best possible quality of
care available.
We invited comments on the proposed reporting framework.
Comment: Some commenters expressed support for the proposed HHVBP
reporting framework of quarterly/annual reports and public reporting.
Specifically, one commenter supported CMS in its efforts to provide
agencies with performance reports and notices of payment change prior
to the imposition of any payment penalty. One commenter suggested that
CMS employ a continuous improvement cycle with industry stakeholders to
maximize the value of the annual publicly available quality reports so
that information does not mislead beneficiaries. Another commenter
supported the proposed timeliness with which quarterly reports would be
made available to HHAs after agency data submission, but expressed
doubts about CMS's ability to comply with its own proposed timeline for
[[Page 68665]]
releasing quarterly reports. Conversely, a few commenters suggested
that challenges related to providing updated quarterly reports on
performance should be considered more fully before implementation. Some
commenters also suggested that CMS should include in future rulemaking
how quarterly reconciliation will be implemented. Another commenter
posited that current reporting timeframes, even if complied with, do
not give small and rural HHAs enough lead time to improve quality.
Response: We thank the commenters for their overall support for the
inclusion of performance reports for all competing HHAs and industry
stakeholders. In reference to concerns with the timelines for delivery
of reports, we intend to meet all performance report timeline
expectations. However, in this final rule, we are revising the
timelines for notification and preview of the annual payment adjustment
to remove the references to specific days of the month set forth in the
proposed rule. This will allow for greater flexibility for the industry
and CMS to meet these expectations and to account for the possibility
of a specific day falling on a weekend or holiday. Through technical
assistance efforts, we will continuously work with all competing-HHAs
and stakeholders in how these reports are interpreted and reconciled
and how they may be used to support transformational efforts to deliver
care within the HHVBP system of incentives.
Comment: Some comments offered their general support of the HHVBP
public reporting of performance data because it will inform industry
stakeholders of quality improvements, and noted several areas of value
in performance data. Specifically, commenters suggested public reports
would permit providers to steer patients to high-performing HHAs based
on quality reports. Commenters offered that to the extent possible,
accurate comparable data will provide HHAs the ability to improve care
delivery and patient outcomes, while better predicting and managing
quality performance and payment updates. These same commenters urged
CMS to consider the HHA information technology infrastructure needed to
support complex performance tracking connected with a VBP program.
Overall, commenters generally encouraged the transparency of data
pertaining to the HHVBP Model.
Response: As part of the HHVBP Model, we will provide technical
assistance and other tools for HHAs in selected states to encourage
best practices when making changes to improve quality. We anticipate
that the HHVBP learning network will be an integral part of data
monitoring and performance related discussion and feedback. As
indicated in the proposed rule (see 80 FR 39873) we also intend to make
public competing HHAs' Total Performance Scores with the intention of
encouraging providers and other stakeholders to utilize quality ranking
when selecting an HHA.
Final Decision: For the reasons discussed and in consideration of
the comments received, we are finalizing the reporting framework for
the HHVBP Model as proposed without modification.
2. Payment Adjustment Timeline
We proposed to codify in Sec. 484.325 that competing HHAs will be
subject to upward or downward payment adjustments based on the agency's
Total Performance Score. We proposed that the model would consist of 5
performance years, where each performance year would link performance
to the opportunity and risk for payment adjustment up to an applicable
percent as defined in proposed Sec. 484.305. The 1st performance year
would transpire from January 1, 2016 through December 31, 2016, and
subsequently, all other performance years would be assessed on an
annual basis through 2020 unless modified through rulemaking. We
proposed that the first payment adjustment would begin January 1, 2018
applied to that calendar year based on 2016 performance data.
Subsequently, all other payment adjustments would be made on an annual
basis through the conclusion of the model. We proposed that payment
adjustments would be increased incrementally over the course of the
model with a maximum payment adjustment of 5-percent (upward or
downward) in 2018 and 2019, a maximum payment adjustment of 6-percent
(upward or downward) in 2020, and a maximum payment adjustment of 8-
percent (upward or downward) in 2021 and 2022. We proposed to implement
this model over a total of seven (7) years beginning on January 1,
2016, and ending on December 31, 2022.
After consideration of comments received, we are modifying the
final payment adjustment percentages as discussed in Section G and
finalized in Sec. 484.305.
We proposed that the baseline year would run from January 1, 2015
through December 31, 2015 and provide a basis from which each
respective HHA's performance will be measured in each of the
performance years. Data related to performance on quality measures will
continue to be provided from the baseline year through the model's
tenure using a dedicated HHVBP web-based platform specifically designed
to disseminate data in this model (this ``portal'' will present and
archive the previously described quarterly and annual quality reports).
Further, HHAs will provide performance data on the three new quality
measures discussed in section E5 through this platform as well. Any
additional measures added through the model's tenure and proposed
through future rulemaking, will use data from the previous calendar
year as the baseline.
We proposed that new market entries (specifically, new competing
HHAs delivering care in the boundaries of selected states) would also
be measured from their first full calendar year of services in the
state, which would be treated as baseline data for subsequent
performance years under this model. The delivery of services would be
measured by the number of episodes of care for Medicare beneficiaries
and used to determine whether an HHA falls into the smaller- or larger-
volume cohort. Furthermore, these new market entries would be competing
under the HHVBP Model in the first full calendar year following the
full calendar year baseline period.
We proposed that HHAs would be notified in advance of their first
performance level and payment adjustment being finalized, based on the
2016 performance period (January 1, 2016 to December 31, 2016), with
their first payment adjustment to be applied January 1, 2018 through
December 31, 2018. We proposed that each competing HHA would be
notified of this first pending payment adjustment on August 1, 2017 and
a preview period would run for 10 days through August 11, 2017. This
preview period would provide each competing HHA an opportunity to
reconcile any performance assessment issues relating to the calculation
of scores prior to the payment adjustment taking effect, in accordance
with the process in Section H--Preview and Period to Request
Recalculation. Once the preview period ends, any changes would be
reconciled and a report finalized no later than November 1, 2017 (or 60
days prior to the payment adjustment taking affect). As discussed
further in section H, we are finalizing this proposal with
modification, to allow for a longer preview period of quarterly
performance reports and annual payment adjustment reports for all
competing HHAs. Specifically, we are extending the preview period such
that each HHA will be notified of the first pending payment adjustment
in
[[Page 68666]]
August 2017 and followed by a 30-day preview period.
We proposed that subsequent payment adjustments would be calculated
based on the applicable full calendar year of performance data from the
quarterly reports, with competing HHAs notified and payments adjusted,
respectively, every year thereafter. As a sequential example, the
second payment adjustment will occur January 1, 2019 based on a full 12
months of the CY 2017 performance period. Notification of the second
adjustment will occur in August of 2018, followed by a 30-day preview
period (under our modifications to the proposed notification and
preview timeline, as discussed previously) and followed by
reconciliation prior to November 1, 2018. Subsequent payment
adjustments will continue to follow a similar timeline and process.
Beginning in CY 2019, we may consider revising this payment
adjustment schedule and updating the payment adjustment more frequently
than once each year if it is determined that a more timely application
of the adjustment as it relates to performance improvement efforts that
have transpired over the course of a calendar year would generate
increased improvement in quality measures. Specifically, we would
expect that having payment adjustments transpire closer together
through more frequent performance periods would accelerate improvement
in quality measures because HHAs would be able to justify earlier
investments in quality efforts and be incentivized for improvements. In
effect, this concept may be operationalized to create a smoothing
effect where payment adjustments are based on overlapping 12-month
performance periods that occur every 6 months rather than annually. As
an example, the normal 12-month performance period occurring from
January 1, 2020 to December 31, 2020 might have an overlapping 12-month
performance period occurring from July 1, 2020 to June 30, 2021.
Following the regularly scheduled January 1, 2022 payment adjustments,
the next adjustments could be applied to payments beginning on July 1,
2022 through December 31, 2022. Depending on if and when more frequent
payment adjustments would be applied, performance would be calculated
based on the applicable 12-months of performance data, HHAs notified,
and payments adjusted, respectively, every six months thereafter, until
the conclusion of the model. As a result, separate performance periods
would have a 6-month overlap through the conclusion of the model. HHAs
would be notified through rulemaking and be given the opportunity to
comment on any proposed changes to the frequency of payment
adjustments.
We received the following comments on this proposed payment
adjustment schedule.
Comment: Many commenters recommended a delay in the payment
adjustment schedule. One commenter recommended that CMS collect and
report quality data for 2016 as an educational exercise only, and use
2017 data as the basis to adjust payment rates beginning in October
2018. This same commenter also recommended CMS delay the first year of
rate adjustments by nine months to October 1, 2018. Another commenter
supported the importance of HHAs in the VBP program not experiencing
payment adjustments until two years after the performance year in an
effort to minimize the programmatic impact and allow agencies the
ability to plan ahead. Several commenters suggested a one year delay in
implementing the model, citing the timeline as too aggressive. A few
commenters posited that it is difficult for HHAs in the HHVBP Model to
begin preparing for the model now without a final rule to guide them,
and noted concern that the final rule will publish so close to the
beginning of the model. Some commenters specifically supported payment
adjustment on an annual basis, positing adjustments made more
frequently than once each year may jeopardize the financial viability
of smaller volume providers, causing further disruption, as multiple
adjustments throughout a fiscal year would be difficult to manage.
Further, due to the delay in data collection and reporting used in
these programs, significant change in performance in shorter increments
would be unlikely, as quality improvement initiatives take time to
fully implement and for results to be realized. Another commenter
offered that any move to increase the payment adjustment to every 6
months would not offer HHAs sufficient time to improve clinician
practice patterns and evaluate the effectiveness of the changes made.
Response: We are finalizing the proposed payment adjustment
timeline for model implementation on an annual basis. Any changes to
the frequency of payment adjustments under the model would be
implemented through future rulemaking. In response to concerns with
having the first performance year tied to an annual payment adjustment
in 2018, we expect that competing HHAs will begin transforming delivery
patterns as soon as this model is implemented. Delaying the payment
adjustment, which is the primary intervention in this model, limits the
ability to understand the intervention's associated effect on quality.
We expect that model-specific technical assistance which will be made
available to all competing-HHAs will provide the appropriate
information and tools needed to transform how care is delivered within
the HHVBP Model.
Comment: Several commenters expressed concern about the time lag
between the performance year and the year in which payment adjustments
would be applied and strongly recommended less time lapse between
performance measurement and payment adjustment. One commenter
recommended CMS revise the HHVBP Model so that rewards and penalties
are imposed within 6 months of the end of the measurement period,
rather than a full year later, and consider imposing the rewards and
penalties for 6 months at a time, allowing the rates to return to
normal for the first 6 months of the subsequent year. Another commenter
offered that this expedited timeframe would allow agencies working
towards improvement to have the resources available to do so more
immediately.
Response: We agree that there may be merit in closing the gap
between performance measurement and payment adjustments in order to
more effectively connect improvements in quality care with financial
incentives. We will closely evaluate the efficacy of the model, and may
consider whether shorter performance assessment cycles (and by
extension, shorter payment adjustment cycles) are warranted. Any such
changes will be implemented through future rulemaking.
Final Decision: For the reasons discussed, we are finalizing the
payment adjustment timeline as proposed with modification.
Specifically, we are finalizing that payment adjustments will be
increased incrementally over the course of the model with a maximum
payment adjustment of 3-percent (upward or downward) in 2018, a maximum
payment adjustment of 5-percent (upward or downward) in 2019, a maximum
payment adjustment of 6-percent (upward or downward) in 2020, a maximum
payment adjustment of 7-percent (upward or downward) in 2021, and a
maximum payment adjustment of 8-percent (upward or downward) in 2022.
We are also modifying the timeline for notification and preview of the
pending payment adjustment to allow for greater flexibility and to
account for the possibility of a specific day falling on a weekend or
holiday,
[[Page 68667]]
and also to provide a longer preview period for HHAs. Specifically, we
are extending the preview period such that each HHA will be notified of
each pending payment adjustment in August of the year prior to the
payment adjustment being applied and the preview period will run for 30
days of that year. We also removed specific days of the month
previously referenced in the proposed rule to allow for greater
flexibility.
E. Quality Measures
1. Objectives
We proposed that initially, the measures for the HHVBP Model would
be predominantly drawn from the current OASIS,\23\ which is familiar to
the home health industry and readily available for utilization by the
model. In addition, the HHVBP Model provides us with an opportunity to
examine a broad array of quality measures that address critical gaps in
care. A recent comprehensive review of the VBP experience over the past
decade, sponsored by the Office of the Assistant Secretary for Planning
and Evaluation (ASPE), identified several near- and long-term
objectives for HHVBP measures.\24\ The recommended objectives emphasize
measuring patient outcomes and functional status; appropriateness of
care; and incentives for providers to build infrastructure to
facilitate measurement within the quality framework.\25\ The following
seven objectives derived from this study served as guiding principles
for the selection of the proposed measures for the HHVBP Model:
---------------------------------------------------------------------------
\23\ For detailed information on OASIS see the official CMS
OASIS Web resource available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/OASIS/?redirect=/oasis. See also industry resource available at
https://www.oasisanswers.com/index.htm, specifically updated OASIS
component information available at www.oasisanswers.com/LiteratureRetrieve.aspx?ID=215074).
\24\ U.S. Department of Health and Human Services. Office of the
Assistant Secretary for Planning and Evaluation (ASPE) (2014)
Measuring Success in Health Care Value-Based Purchasing Programs.
Cheryl L. Damberg et al. on behalf of RAND Health.
\25\ Id.
---------------------------------------------------------------------------
1. Use a broad measure set that captures the complexity of the HHA
service provided;
2. Incorporate the flexibility to include Improving Medicare Post-
Acute Care Transformation (IMPACT) Act of 2014 measures that are cross-
cutting amongst post-acute care settings;
3. Develop second-generation 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.
2. Methodology for Selection of Quality Measures
a. Direct Alignment With National Quality Strategy Priorities
A central driver of the proposed measure selection process was
incorporating innovative thinking from the field while simultaneously
drawing on the most current evidence-based literature and documented
best practices. Broadly, we proposed measures that have a high impact
on care delivery and support the combined priorities of HHS and CMS to
improve health outcomes, quality, safety, efficiency, and experience of
care for patients. To frame the selection process, we utilized the
domains described in the CMS Quality Strategy that maps to the six
National Quality Strategy (NQS) priority areas (see Figure 3 for CMS
domains).\26\
---------------------------------------------------------------------------
\26\ The CMS Quality Strategy is discussed in broad terms at URL
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.html. CMS
Domains appear presentations by CMS and ONC (available at https://www.cms.gov/eHealth/downloads/Webinar_eHealth_March25_eCQM101.pdf)
and a CMS discussion of the NQS Domains can be found at URL https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/2014_ClinicalQualityMeasures.html.
---------------------------------------------------------------------------
[[Page 68668]]
[GRAPHIC] [TIFF OMITTED] TR05NO15.004
b. Referenced Quality Measure Authorities
We proposed at Sec. 484.315 that Medicare-certified HHAs will be
evaluated using a starter set of quality measures (``starter set''
refers to the quality measures for the first year of this model)
designed to encompass multiple NQS domains, and provide future
flexibility to incorporate and study newly developed measures over
time. New and evolving measures will be considered for inclusion in
subsequent years of this model and proposed through future rulemaking.
To create the proposed starter set we began researching the current
set of OASIS measures that are being used within the health home
environment.\27\ Following that, we searched for endorsed quality
measures using the National Quality Forum (NQF) Quality Positioning
System (QPS),\28\ selecting measures that address all possible NQS
domains. We further examined measures on the CMS-generated Measures
Under Consideration (MUC) list,\29\ and reviewed other relevant
measures used within the health care industry, but not currently used
in the home health setting, as well as measures required by the IMPACT
Act of 2014. Finally, we searched the National Quality Measures
Clearinghouse (NQMS) to identify evidence-based measures and measure
sets.
---------------------------------------------------------------------------
\27\ All data for the starter set measures, not including New
Measures, is currently collected from HHAs under Sec. Sec. 484.20
and 484.210.
\28\ The NQF Quality Positioning System is available at https://www.qualityforum.org/QPS.
\29\ To review the MUC List see https://www.qualityforum.org/Setting_Priorities/Partnership/Measures_Under_Consideration_List_2014.aspx.
---------------------------------------------------------------------------
c. Key Policy Considerations and Data Sources
So that measures for the HHVBP Model take a more holistic view of
the patient beyond a particular disease state or care setting, we
proposed, and are finalizing in this rule, measures, which include
outcome measures as well as process measures, that have the potential
to follow patients across multiple settings, reflect a multi-faceted
approach, and foster the intersection of health care delivery and
population health. A key consideration behind this approach is to use
in performance year one (PY1) of the model proven measures that are
readily available and meet a high impact need, and in subsequent model
years augment this starter set with innovative measures that have the
potential to be impactful and fill critical measure gap areas. All
substantive changes or additions to the starter set or new measures
would be proposed in future rulemaking. This approach to quality
measure selection aims to balance the burden of collecting data with
the inclusion of new and important measures. We carefully considered
the potential burden on HHAs to report the measure data when developing
the starter set, and prioritized measures that will draw both from
claims data and data already collected in OASIS.
The majority of the measures proposed, as well as the majority of
measures being finalized, in this model will use OASIS data currently
being reported to CMS and linked to state-specific CCNs for selected
states in order to promote consistency and to reduce the data
collection burden for providers. Utilizing primarily OASIS data will
allow the model to leverage reporting structures already in place to
evaluate performance and identify weaknesses in care delivery. This
model will also afford the opportunity to study measures developed in
other care settings and new to the home health industry (hereinafter
referred to as ``New Measures''). Many of the New Measures have been
used in other health care settings and are readily applicable to the
home health environment (for example, influenza vaccination coverage
for health care personnel). The final New Measures for PY1 are
described in detail below. We proposed, and are finalizing with
modification, in PY1 to collect data on these New Measures which have
already been tested for validity, reliability, usability/feasibility,
and sensitivity in
[[Page 68669]]
other health care settings but have not yet been validated within the
home health setting. As discussed in further detail under ``E5.New
Measures,'' we are finalizing three of the four proposed New Measures
for reporting under this model. HHVBP will study if their use in the
home health setting meets validity, reliability, usability/feasibility,
and sensitivity to statistical variations criteria. For PY1, we
proposed that HHAs could earn points to be included in the Total
Performance Score (TPS) simply for reporting data on New Measures (see
Section--Performance Scoring Methodology). To the extent we determine
that one or more of the New Measures is valid and reliable for the home
health setting, we will consider in future rulemaking to score
Medicare-certified HHAs on their actual performance on the measure.
3. Selected Measures
The initial set of measures proposed for PY1 of the model utilizes
data collected via OASIS, Medicare claims, HHCAHPS survey data, and
data reported directly from the HHAs to CMS. We proposed, in total, 10
process measures and 15 outcome measures (see Figure 4a of the proposed
rule) plus four New Measures (see Figure 4b of the proposed rule). As
discussed below, we are finalizing the proposed starter set of measures
with modification; specifically, under our final policy, there are in
total six process measures and 15 outcome measures (see Figure 4a of
this final rule) and three New Measures (see Figure 4b of this final
rule). Process measures evaluate the rate of HHA use of specific
evidence-based processes of care based on the evidence available.
Outcomes measures illustrate the end result of care delivered to HHA
patients. When available, NQF endorsed measures will be used. This set
of measures will be subject to change or retirement during subsequent
model years and revised through the rulemaking process. For example, we
may propose in future rulemaking to remove one or more of these
measures if, based on the evidence; we conclude that it is no longer
appropriate for the model due to its performance being topped-out. We
will also consider proposing to update the measure set if new measures
that address gaps within the NQS domains became available. We will also
consider proposing adjustments to the measure set based on lessons
learned during the course of the model. For instance, in light of the
passage of the IMPACT Act of 2014, which mandates the collection and
use of standardized post-acute care assessment data, we will consider
proposing in future rulemaking to adopt measures that meet the
requirements of the IMPACT Act as soon as they became available.
Provisions of the IMPACT ACT applicable to HHAs will take effect
beginning CY 2017. Currently, IMPACT measures for home health are in
the development stage and not available for inclusion in the starter
set of measures. We requested public comment on the methodology for
constructing the proposed starter set of quality measures and on the
proposed selected measures.
Comment: Many commenters expressed concern at the number of
measures proposed for use in the model, with the primary concern
related to the burden placed on HHAs to focus on so many different
areas at once, as well as the effort required to track and report New
Measures at the same time. Many commenters suggested decreasing the
number of measures, particularly process measures, in the starter set
and expressed the opinion less measures would allow for greater
targeting of quality improvement.
Response: We have considered the commenters' suggestions and agree
that more narrowly focusing the starter set of measures being tested in
the HHVBP Model may increase the likelihood of HHA success in their
quality improvement and transformation efforts. In addition, we were
encouraged by commenters to re-evaluate the proposed starter set of
measures and specifically include fewer process measures in the final
starter set. After consideration of these comments we are reducing the
number of measures in the final starter set. We proposed that the
starter set would include 25 measures that are currently reported
through existing systems (in addition to the proposed New Measures).
Twenty of these proposed measures were process/outcomes measures
collected on the OASIS or through claims data and five are HHCAHPs. We
agree with commenters that placing an emphasis on outcome measures over
process measures determines performance in a way most meaningful to
patients. For each process measure in the proposed starter set we
analyzed what specific metrics were being assessed in relation to the
entire starter set and how close the measure was to being `topped-out'
based on the most recent available data. Based on these comments and
for the reasons stated we are reducing the number of process measures
by four resulting in a final starter set with six process measures, 10
outcome measures and five HHCAHPS. In addition, we have decreased the
New Measures from four to three (as discussed later in this section).
We are not including the following proposed measures in the final
starter set: Timely Initiation of Care (NQF0526), Pressure Ulcer
Prevention and Care (NQF0538), Multifactor Fall Risk Assessment
Conducted for All Patients who can Ambulate (NQF0537), Depression
assessment conducted (NQF0518), and Adverse Event for Improper
Medication Administration and/or Side Effects (New Measures).
Comment: We received some public comments expressing concern that
all measures in the starter set are not endorsed by NQF.
Response: We agree that wherever possible NQF-endorsed measures
should be utilized. When creating the proposed starter set it was our
policy to utilize an NQF-endorsed measure whenever one was available to
address a known quality improvement issue in home health. For other
measures included in the finalized starter set, we are utilizing long-
standing OASIS data components to track quality. As an innovation
model, it is our intention to closely monitor the quality measures and
to address any needed adjustments through future rulemaking. In
addition, the information we learn during this model may, where
appropriate, be utilized to assist in effective measures gaining
endorsement within the HH service line.
Comment: We received a number of public comments citing the
settlement agreement in Jimmo v. Sebelius and expressing concern with
the inclusion of five measures related to improvement and articulating
the importance of including measures related to patient stabilization
and maintenance.
Response: We appreciate the feedback on the measures methodology
and 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 Jimmo settlement. The Jimmo
settlement agreement, however, pertains only to the clarification of
CMS's manual guidance on coverage standards, not payment measures, and
expressly does not pertain to or prevent the implementation of new
regulations, including new regulations pertaining to the HHVBP Model.
While we considered using some of the stabilization measures for this
model, we found that in contrast to the average HHA improvement measure
scores which ranged from 56- to 65-percent, the average HHA
stabilization measure scores ranged from 94- to 96-percent. Using
measures where the average rates are nearly 100-percent would not allow
[[Page 68670]]
for meaningful comparisons between competing-HHAs on the quality of
care delivered. In addition, we performed analyses on whether the
proportion of an individual HHA's episodes of care relating to ``low
therapy'' episodes (episodes with 0-5 therapy visits) and the
proportion of an individual HHA's total therapy visits relating to
maintenance therapy would have an impact on the measures related to
improvement used in the model. HHAs that have a higher proportion of
patients that require maintenance therapy or patients that receive
little to no therapy at all would not be expected to perform well on
the measures related to improvement. Although the functional measures
related to improvement are expected to be sensitive to the provision of
therapy, our analysis did not determine that HHAs' performance on the
measures related to improvement were negatively impacted by whether
they had a higher proportion of maintenance therapy patients or a
higher proportion of patients that had little to no therapy.
Based on these two analyses, CMS expects that, at this time, HHAs
that provide care to more beneficiaries that are maintenance-oriented
will not be at a disadvantage in the model. We also do not expect any
access issues for beneficiaries that have more maintenance needs
because HHAs would not know whether the beneficiary has restorative or
maintenance needs until the HHA initiates the episode of care and
conducts the necessary assessments. Once the initial OASIS assessment
is complete, the beneficiary will be included in measure calculation.
We are finalizing the measures related to improvement as proposed
in the proposed rule, however, we are sensitive to this issue and will
closely monitor whether HHVBP Model-specific measures have the
potential to impact beneficiaries that require skilled care to maintain
the patient's current condition, or to prevent or slow further
deterioration of the patient's condition. If necessary, we will use
future rulemaking if we determine that this issue has a meaningful
detrimental effect on payments of those HHAs that provide more
maintenance care. In addition, we are currently working on the
development of valid and reliable stabilization measures that may be
incorporated into the HHVBP Model in the future. One stabilization
measure is referenced in Table 20 `Future Setting-specific Measure
Constructs under Consideration'. 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.
Comment: Although CMS received general support for the use of OASIS
data, some commenters expressed concern with OASIS issues related to
data validation or with the use of certain OASIS data elements as the
basis for measuring quality.
Response: We appreciate the comments on this issue and are
committed to balancing concerns related to provider burden with
concerns related to data validation and accurate reporting of
information to CMS via OASIS. In designing the HHVBP Model, we
intentionally crafted a starter set of measures to minimize burden.
Specifically, the majority of measures rely on OASIS data already
reported by HHAs. In response to a 2012 report issued by the Office of
the Inspector General,\30\ CMS affirmed a series of monitoring
activities related to OASIS education, training and also updated the
HHA surveyor worksheet related to HHA OASIS compliance. As part of the
monitoring and evaluation of this model CMMI will utilize CMS best
practices for determining the validity of OASIS data and detecting
fraud related to data submission. Should validation concerns arise,
CMMI may consider implementing data validation processes. The model
will closely monitor reported measures for indications of fraud and CMS
will propose any changes to the model as needed in future rulemaking.
---------------------------------------------------------------------------
\30\ Cite for OIG report here.
---------------------------------------------------------------------------
Comment: A few commenters expressed specific concern that measures
in the starter set will be duplicative of, or will not take into
account the future measures implemented under the IMPACT Act, and
suggested consciously aligning the HHVBP starter set with the IMPACT
Act as it is implemented.
Response: We agree the HHVBP measure set should be in alignment
with the IMPACT Act. As stated in the HHVBP proposed rule and finalized
here, as soon as new IMPACT measures are finalized and approved, we
will consider how best to incorporate and align IMPACT Act measures
with the HHVBP measure in future rulemaking. As an example, once
baseline data is available for NQF #0678 `pressure ulcers' which will
be implemented in CY 2016, we will consider using this measure in
future years through rulemaking.
Comment: One commenter recommended eliminating all vaccine-related
measures, as vaccines are not the primary focus of home health care.
The commenter stated that the use of vaccine-related measures creates
misalignment between patient centered principles and HHA financial
incentives.
Response: We have included two immunization measures in the starter
set that are NQF-endorsed as preventive services measures and already
collected by home health agencies. These measures are the pneumococcal
vaccine and the influenza vaccines for HHA beneficiaries. The
immunization measures that are New Measures, the shingles vaccine and
influenza vaccines for HHA staff, under the final HHVBP Model serve
important public health functions. The New Measure for influenza
vaccination for HHA staff is a well-established scientific principle as
being a sound mechanism for protecting vulnerable patient populations
from avoidable disease transmission. In addition, this New Measure is
utilized in every care setting except home health, and is intended to
close the gap in protection. The Shingles vaccination is the other New
Measure utilizing immunizations, and its efficacy in either preventing
shingles entirely or reducing the pain symptoms associated with
shingles is directly related to improvement of patient quality of life.
The measurements related to vaccination are not connected to whether a
patient does or does not receive the vaccinations. Patients are free to
decline vaccinations and competing HHAs are not financially penalized
for the patient's choice.
Final Decision: For the reasons discussed and in consideration of
the comments received we are not finalizing the following proposed
measures:
Timely Initiation of Care (NQF0526)
Pressure Ulcer Prevention and Care (NQF0538)
Multifactor Fall Risk Assessment Conducted for All
Patients Who Can Ambulate (NQF0537)
Depression assessment conducted (NQF0518)
Adverse Event for Improper Medication Administration and/
or Side Effects (New Measure)
We are finalizing the remaining quality measures as proposed. The
final starter set includes 6 process measures, 10 outcome measures and
5 HHCAHPS, and three New Measures.
The final PY1 measures are presented in the following figures.
[[Page 68671]]
Figure 4a: Final PY1 Measures \31\
--------------------------------------------------------------------------------------------------------------------------------------------------------
NQS Domains Measure title Measure type Identifier Data source Numerator Denominator
--------------------------------------------------------------------------------------------------------------------------------------------------------
Clinical Quality of Care........ Improvement in Outcome........... NQF0167........... OASIS (M1860)..... Number of home Number of home
Ambulation- health episodes health episodes
Locomotion. of care where the of care ending
value recorded on with a discharge
the discharge during the
assessment reporting period,
indicates less other than those
impairment in covered by
ambulation/ generic or
locomotion at measure-specific
discharge than at exclusions.
the start (or
resumption) of
care.
Clinical Quality of Care........ Improvement in Bed Outcome........... NQF0175........... OASIS (M1850)..... Number of home Number of home
Transferring. health episodes health episodes
of care where the of care ending
value recorded on with a discharge
the discharge during the
assessment reporting period,
indicates less other than those
impairment in bed covered by
transferring at generic or
discharge than at measure-specific
the start (or exclusions.
resumption) of
care.
Clinical Quality of Care........ Improvement in Outcome........... NQF0174........... OASIS (M1830)..... Number of home Number of home
Bathing. health episodes health episodes
of care where the of care ending
value recorded on with a discharge
the discharge during the
assessment reporting period,
indicates less other than those
impairment in covered by
bathing at generic or
discharge than at measure-specific
the start (or exclusions.
resumption) of
care.
Clinical Quality of Care........ Improvement in Outcome........... NA................ OASIS (M1400)..... Number of home Number of home
Dyspnea. health episodes health episodes
of care where the of care ending
discharge with a discharge
assessment during the
indicates less reporting period,
dyspnea at other than those
discharge than at covered by
start (or generic or
resumption) of measure-specific
care. exclusions.
Communication & Care Discharged to Outcome........... NA................ OASIS (M2420)..... Number of home Number of home
Coordination. Community. health episodes health episodes
where the of care ending
assessment with discharge or
completed at the transfer to
discharge inpatient
indicates the facility during
patient remained the reporting
in the community period, other
after discharge. than those
covered by
generic or
measure-specific
exclusions.
Communication & Care Care Management: Process........... NA................ OASIS (M2102)..... Multiple data Multiple data
Coordination. Types and Sources elements. elements.
of Assistance.
Efficiency & Cost Reduction..... Acute Care Outcome........... NQF0171........... CCW (Claims)...... Number of home Number of home
Hospitalization: health stays for health stays that
Unplanned patients who have begin during the
Hospitalization a Medicare claim 12-month
during first 60 for an admission observation
days of Home to an acute care period. A home
Health. hospital in the health stay is a
60 days following sequence of home
the start of the health payment
home health stay. episodes
separated from
other home health
payment episodes
by at least 60
days.
Efficiency & Cost Reduction..... Emergency Outcome........... NQF0173........... CCW (Claims)...... Number of home Number of home
Department Use health stays for health stays that
without patients who have begin during the
Hospitalization. a Medicare claim 12-month
for outpatient observation
emergency period. A home
department use health stay is a
and no claims for sequence of home
acute care health payment
hospitalization episodes
in the 60 days separated from
following the other home health
start of the home payment episodes
health stay. by at least 60
days.
Patient Safety.................. Improvement in Outcome........... NQF0177........... OASIS (M1242)..... Number of home Number of home
Pain Interfering health episodes health episodes
with Activity. of care where the of care ending
value recorded on with a discharge
the discharge during the
assessment reporting period,
indicates less other than those
frequent pain at covered by
discharge than at generic or
the start (or measure-specific
resumption) of exclusions.
care.
Patient Safety.................. Improvement in Outcome........... NQF0176........... OASIS (M2020)..... Number of home Number of home
Management of health episodes health episodes
Oral Medications. of care where the of care ending
value recorded on with a discharge
the discharge during the
assessment reporting period,
indicates less other than those
impairment in covered by
taking oral generic or
medications measure-specific
correctly at exclusions.
discharge than at
start (or
resumption) of
care.
[[Page 68672]]
Patient Safety.................. Prior Functioning Outcome........... NQF0430........... OASIS (M1900)..... The number (or All patients in a
ADL/IADL. proportion) of a risk adjusted
clinician's diagnostic
patients in a category with a
particular risk Daily Activity
adjusted goal for an
diagnostic episode of care.
category who meet Cases to be
a target included in the
threshold of denominator could
improvement in be identified
Daily Activity based on ICD-9
(that is, ADL and codes or
IADL) functioning. alternatively,
based on CPT
codes relevant to
treatment goals
focused on Daily
Activity
function.
Population/Community Health..... Influenza Vaccine Process........... NA................ OASIS (M1041)..... NA................ NA.
Data Collection
Period: Does this
episode of care
include any dates
on or between
October 1 and
March 31?
Population/Community Health..... Influenza Process........... NQF0522........... OASIS (M1046)..... Number of home Number of home
Immunization health episodes health episodes
Received for during which of care ending
Current Flu patients (a) with discharge,
Season. Received or transfer to
vaccination from inpatient
the HHA or (b) facility during
had received the reporting
vaccination from period, other
HHA during than those
earlier episode covered by
of care, or (c) generic or
was determined to measure-specific
have received exclusions.
vaccination from
another provider.
Population/Community Health..... Pneumococcal Process........... NQF0525........... OASIS (M1051)..... Number of home Number of home
Polysaccharide health episodes health episodes
Vaccine Ever during which of care ending
Received. patients were with discharge or
determined to transfer to
have ever inpatient
received facility during
Pneumococcal the reporting
Polysaccharide period, other
Vaccine (PPV). than those
covered by
generic or
measure-specific
exclusions.
Population/Community Health..... Reason Process........... NA................ OASIS (M1056)..... NA................ NA.
Pneumococcal
vaccine not
received.
Clinical Quality of Care........ Drug Education on Process........... NA................ OASIS (M2015)..... Number of home Number of home
All Medications health episodes health episodes
Provided to of care during of care ending
Patient/Caregiver which patient/ with a discharge
during all caregiver was or transfer to
Episodes of Care. instructed on how inpatient
to monitor the facility during
effectiveness of the reporting
drug therapy, how period, other
to recognize than those
potential adverse covered by
effects, and how generic or
and when to measure-specific
report problems exclusions.
(since the
previous OASIS
assessment).
--------------------------------------------------------------------------------------------------------------------------------------------------------
Home Health CAHPS: Satisfaction Survey Measures
--------------------------------------------------------------------------------------------------------------------------------------------------------
Patient & Caregiver-Centered Care of Patients.. Outcome........... .................. CAHPS............. NA................ NA.
Experience.
Patient & Caregiver-Centered Communications Outcome........... .................. CAHPS............. NA................ NA.
Experience. between Providers
and Patients.
Patient & Caregiver-Centered Specific Care Outcome........... .................. CAHPS............. NA................ NA.
Experience. Issues.
Patient & Caregiver-Centered Overall rating of Outcome........... .................. CAHPS............. NA................ NA.
Experience. home health care
and.
Patient & Caregiver-Centered Willingness to Outcome........... .................. CAHPS............. NA................ NA.
Experience. recommend the
agency.
--------------------------------------------------------------------------------------------------------------------------------------------------------
---------------------------------------------------------------------------
\31\ For more detailed information on the proposed 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 https://www.qualityforum.org/QPS. For non-NQF measures using OASIS
see links for data tables related to OASIS measures at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html. For
information on HHCAHPS measures see https://homehealthcahps.org/SurveyandProtocols/SurveyMaterials.aspx.
[[Page 68673]]
Figure 4b--Final PY1 New Measures
--------------------------------------------------------------------------------------------------------------------------------------------------------
NQS domains Measure title Measure type Identifier Data source Numerator Denominator
--------------------------------------------------------------------------------------------------------------------------------------------------------
Population/Community Health..... Influenza Process........... NQF0431 (Used in Reported by HHAs Healthcare Number of
Vaccination other care through Web personnel in the healthcare
Coverage for Home settings, not Portal. denominator personnel who are
Health Care Home Health). population who working in the
Personnel. during the time healthcare
from October 1 facility for at
(or when the least 1 working
vaccine became day between
available) October 1 and
through March 31 March 31. of the
of the following following year,
year: (a) regardless of
received an clinical
influenza responsibility or
vaccination patient contact.
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
Guillain-Barre
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 above-
mentioned
numerator
categories.
Population/Community Health..... Herpes zoster Process........... NA................ Reported by HHAs Total number of Total number of
(Shingles) through Web Medicare Medicare
vaccination: Has Portal. beneficiaries beneficiaries
the patient ever aged 60 years and aged 60 years and
received the over who report over receiving
shingles having ever services from the
vaccination? received zoster HHA.
vaccine (shingles
vaccine).
Communication & Care Advance Care Plan. Process........... NQF0326........... Reported by HHAs Patients who have All patients aged
Coordination. through Web an advance care 65 years and
Portal. plan or surrogate older.
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.
--------------------------------------------------------------------------------------------------------------------------------------------------------
4. Additional Information on HHCAHPS
Figure 5 provides details on the elements of the Home Health Care
Consumer Assessment of Healthcare Providers and Systems Survey
(HHCAHPS) we proposed, and are finalizing, to include in the PY1
starter set. The HHVBP Model will not alter the HHCAHPS current scoring
methodology or the participation requirements in any way. Details on
participation requirements for HHCAHPS can be found at 42 CFR 484.250
\32\ and details on HHCAHPS scoring methodology are available at;
https://homehealthcahps.org/SurveyandProtocols/SurveyMaterials.aspx.\33\
---------------------------------------------------------------------------
\32\ 76 FR 68606, Nov. 4, 2011, as amended at 77 FR 67164, Nov.
8, 2012; 79 FR 66118, Nov. 6, 2014.
\33\ Detailed scoring information is contained in the Protocols
and Guidelines manual posted on the HHCAHPS Web site and available
at https://homehealthcahps.org/Portals/0/PandGManual_NOAPPS.pdf.
Figure 5--Home Health Care Consumer Assessment of Healthcare Providers
and Systems Survey (HHCAHPS) Composites
------------------------------------------------------------------------
------------------------------------------------------------------------
Care of Patients Response
Categories
------------------------------------------------------------------------
Q9. In the last 2 months of care, how often did home Never, Sometimes,
health providers from this agency seem informed and Usually, Always.
up-to-date about all the care or treatment you got
at home?
Q16. In the last 2 months of care, how often did home Never, Sometimes,
health providers from this agency treat you as Usually, Always.
gently as possible?
Q19. In the last 2 months of care, how often did home Never, Sometimes,
health providers from this agency treat you with Usually, Always.
courtesy and respect?
Q24. In the last 2 months of care, did you have any Yes, No.
problems with the care you got through this agency?
------------------------------------------------------------------------
[[Page 68674]]
Communications Between Providers & Patients Response
Categories
------------------------------------------------------------------------
Q2. When you first started getting home health care Yes, No.
from this agency, did someone from the agency tell
you what care and services you would get?
Q15. In the past 2 months of care, how often did home Never, Sometimes,
health providers from this agency keep you informed Usually, Always.
about when they would arrive at your home?
Q17. In the past 2 months of care, how often did home Never, Sometimes,
health providers from this agency explain things in Usually, Always.
a way that was easy to understand?
Q18. In the past 2 months of care, how often did home Never, Sometimes,
health providers from this agency listen carefully Usually, Always.
to you?
Q22. In the past 2 months of care, when you contacted Yes, No.
this agency's office did you get the help or advice
you needed?
Q23. When you contacted this agency's office, how Same day; 1 to 5
long did it take for you to get the help or advice days; 6 to 14
you needed? days; More than
14 days.
------------------------------------------------------------------------
Specific Care Issues Response
Categories
------------------------------------------------------------------------
Q3. When you first started getting home health care Yes, No.
from this agency, did someone from the agency talk
with you about how to set up your home so you can
move around safely?
Q4. When you started getting home health care from Yes, No.
this agency, did someone from the agency talk with
you about all the prescription medicines you are
taking?
Q5. When you started getting home health care from Yes, No.
this agency, did someone from the agency ask to see
all the prescription medicines you were taking?
Q10. In the past 2 months of care, did you and a home Yes, No.
health provider from this agency talk about pain?
Q12. In the past 2 months of care, did home health Yes, No.
providers from this agency talk with you about the
purpose for taking your new or changed prescription
medicines?
Q13. In the last 2 months of care, did home health Yes, No.
providers from this agency talk with you about when
to take these medicines?
Q14. In the last 2 months of care, did home health Yes, No.
providers from this agency talk with you about the
important side effects of these medicines?
------------------------------------------------------------------------
Global type Measures Response
Categories
------------------------------------------------------------------------
Q20. What number would you use to rate your care from Use a rating
this agency's home health providers? scale (0-10) (0
is worst, 10 is
best).
Q25. Would you recommend this agency to your family Definitely no;
or friends if they needed home health care? Probably no;
Probably yes;
Definitely yes.
------------------------------------------------------------------------
5. New Measures
As discussed in the proposed rule and the previous section of this
final rule, the New Measures we proposed are not currently reported by
Medicare-certified HHAs to CMS, but we believe fill gaps in the NQS
Domains not completely covered by existing measures in the home health
setting. We proposed that all competing HHAs in selected states,
regardless of cohort size or number of episodes, will be required to
submit data on the New Measures for all Medicare beneficiaries to whom
they provide home health services within the state (unless an exception
applies). We proposed at Sec. 484.315(b) that competing HHAs would be
required to report data on these New Measures. Competing HHAs will
submit New Measure data through a dedicated HHVBP web-based platform.
This web-based platform will function as a means to collect and
distribute information from and to competing HHAs. Also, for those HHAs
with a sufficient number of episodes of care to be subject to a payment
adjustment, New Measures scores included in the final TPS for PY1 are
only based on whether the HHA has submitted data to the HHVBP web-based
platform or not. We proposed the following New Measures for competing
HHAs:
Advance Care Planning;
Adverse Event for Improper Medication Administration and/
or Side Effects;
Influenza Vaccination Coverage for Home Health Care
Personnel; and,
Herpes Zoster (Shingles) Vaccination received by HHA
patients.
For the reasons explained below and in consideration of the
comments received, we are not including the proposed ``Adverse Event
for Improper Medication Administration and/or Side Effects'' as one of
the final New Measures. We are finalizing the other three proposed New
Measures without modification.
a. Advance Care Planning
Advance Care Planning is an NQF-endorsed process measure in the NQS
domain of Person- and Caregiver-centered experience and outcomes (see
Figure 3). This measure is currently endorsed at the group practice/
individual clinician level of analysis. We believe its adoption under
the HHVBP Model represents an opportunity to study this measure in the
home health setting. This is an especially pertinent measure for home
health care to confirm that the wishes of the patient regarding their
medical, emotional, or social needs are met across care settings. The
Advance Care Planning measure will focus on Medicare beneficiaries,
including dually-eligible beneficiaries.
We proposed that the measure would be numerically expressed by a
ratio whose numerator and denominator are as follows:
Numerator: The measure would calculate the percentage of patients
age 65 years and older served by the HHA that have an advance care plan
or
[[Page 68675]]
surrogate decision maker \34\ documented in the clinical record or
documentation in the clinical record that an advance 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.
---------------------------------------------------------------------------
\34\ A surrogate decision maker, also known as a health care
proxy or agent, advocates for patients who are unable to make
decisions or speak for themselves about personal health care such
that someone else must provide direction in decision-making, as the
surrogate decision-maker.
---------------------------------------------------------------------------
Denominator: All patients aged 65 years and older admitted to the
HHA.
Advance care planning provides that the health care plan is
consistent with the patient's wishes and preferences. Therefore,
studying this measure within the HHA environment allows for further
analysis of planning for the ``what ifs'' that may occur during the
patient's lifetime. In addition, the use of this measure is expected to
result in an increase in the number of patients with advance care
plans. Increased advance care planning among the elderly is expected to
result in enhanced patient autonomy and reduced hospitalizations and
in-hospital deaths.\35\
---------------------------------------------------------------------------
\35\ Lauren Hersch Nicholas, Ph.D., MPP et al. Regional
Variation in the Association Between Advance Directives and End-of-
Life Medicare Expenditures. JAMA. 2011;306(13):1447-1453.
doi:10.1001/jama.2011.1410.
---------------------------------------------------------------------------
We invited comments on this proposed measure.
Comment: Some commenters expressed support for the inclusion of the
advance care directive quality measure in the HHVBP Model as an
important step towards advancing the needs and wishes of Medicare
beneficiaries and improving care near the end of life. One commenter
suggested CMS should collect data separately for advance care plans and
for surrogate decision makers, since they should not be considered to
be alternatives to each other and suggested breaking this one measure
into two new separate measures. Another commenter recommended that
information collected for Advanced Care Planning be compliant with the
standard at Sec. 484.10(c)(ii), in which the HHA must inform and
distribute written information to the patient, in advance, concerning
its policies on advance directives, including a description of
applicable state law.
Response: HHAs are already required to comply with Conditions of
Participation as codified in Sec. 484.10(c)(1)(ii) regarding patient
rights and participation in this model in no way alters those
regulatory obligations for participating HHAs. We will analyze the data
collected for this New Measure and based on this analysis determine if
we need to modify the measure in future rulemaking. We also note that
standard practices for developing advance care plans integrate
selection of surrogate decision making into the plan, so if and when a
surrogate is needed they are readily made aware of the patient's wishes
as articulated in the care plan.
Comment: One commenter did not support adoption of an Advance Care
Planning measure and stated that an HHA should not be given an
incentive to make the patient acquire an advanced directive. The
commenter also asserted that Advance Care Planning is better suited for
long-term care relationships and that advance directive compliance is
already assessed at the HHA level. The commenter expressed concern that
the Advance Care Planning measure shows a preference for living wills
instead of working through a process to create an advance care plan.
Response: Advance Care Plans are fundamentally different than
advanced directives (also referred to as living wills.) The basis for
an Advance Care Plan is ongoing communication with health providers,
family members, and potential surrogate decision makers; they are not
focused exclusively on end of life or life threatening conditions.
Advance Care Plans ensure patient centered care by providing an
opportunity for health care providers and patients to identify how a
patient would like to be cared for when a medical crisis makes it
difficult or impossible to make their own healthcare decisions.
Comment: Commenters suggested that this metric, and the reporting
on all New Measures be delayed until CY2017 and that it be included
within OASIS for data collection due to the complexity of the question
and its multiple parts.
Response: Based on the comments we received from HHAs to delay the
reporting requirement for New Measures, including Advance Care
Planning, we are modifying our proposal to require HHAs to submit the
first round of data on this and the other New Measures no later than
October 7, 2016 for the period July 2016 through September 2016. In
response to the recommendation that we incorporate this measure into
OASIS before including it in the Model, part of the purpose of testing
this measure in the HH setting is to make informed decisions based on
newly available data analysis prior to recommending that this measure
be incorporated into measures that all HHAs are required to report.
Comment: Some commenters expressed concern that the Advance Care
Planning Measure does not clearly state that the patient does not have
to complete the advance care plan. In addition, some commenters wrote
that the measure creates an incentive to pressure patients to do so. A
few commenters requested CMS make regulations and policy guidance on
the Advance Care Planning measure to more strongly clarify that the
well-being and autonomy of the individual patient is the primary
concern, not cost savings for the government.
Response: Beneficiaries are free to make their own decisions
related to their participation in their care, and this measure
ascertains that providers provide information and opportunity to the
patient so they can engage in planning their own care. The intent of
the measure is to provide education and guidance to the beneficiaries,
not to pressure them regarding this measure. We will provide robust
technical assistance for HHAs related to this new measure, including
necessary tools and information for ensuring autonomous decision making
on the part of the patient.
Final Decision: For the reasons discussed and in consideration of
the comments received, we are finalizing this New Measure as proposed,
with the modification that HHAs will be required to begin reporting
data no later than October 7, 2016 for the period July 2016 through
September 2016 and quarterly thereafter. As a result, the first
quarterly performance report in July 2016 will not account for any of
the New Measures.
b. Adverse Event for Improper Medication Administration and/or Side
Effects
We proposed an Adverse Event for Improper Medication Administration
and/or Side Effects measure that aligns with the NQS domain of Safety
(specifically ``medication safety''--see Figure 3) with the goal of
making care safer by reducing harm caused in the delivery of care. The
National Quality Forum included ADEs as a Serious Reportable Event
(SRE) in the category of Care Management, defining said event as a
``patient death or serious injury associated with a medication error
(for example, errors involving the wrong drug, wrong dose, wrong
patient, wrong time, wrong rate, wrong preparation, or wrong route of
administration),'' noting that ``. . . the high rate of medication
errors resulting in injury and death makes this event important to
endorse again.'' \36\ We refer
[[Page 68676]]
readers to the CY 2016 HH PPS proposed rule for more detail on this
proposed measure (80 FR 39883 through 39884).
---------------------------------------------------------------------------
\36\ National Quality Forum, Serious Reportable Events in
Healthcare-2011, at 9. (2011), available at: https://www.qualityforum.org/Publications/2011/12/Serious_Reportable_Events_in_Healthcare_2011.aspx.
---------------------------------------------------------------------------
We invited comments on the Adverse Drug Events measure.
Comment: Many commenters noted the duplication between this
proposed New Measure and an existing OASIS adverse event outcome
measure, ``Emergent Care for Improper Medication Administration,
Medication Side Effects''. A commenter recommended substituting the
proposed New Measure titled Adverse Event for Improper Medication
Administration and/or Side Effects with the current measure called
``Potentially Avoidable Event Outcome titled Emergent Care for Improper
Medication Administration, Medication Side Effects'' generated using
OASIS data. In addition, commenters generally did not support inclusion
of the ADE metric as part of HHVBP because: HHA staff are not typically
trained to positively identify ADEs, which are often complex; ADEs
often only become apparent after further care; the complexity of ADEs
means they are often not identified on discharge paperwork, meaning
that more effort would be required to identify ADEs and less vigilant
HHAs would be rewarded for not inputting information; and drug
education metrics are already part of home health compare and in OASIS
data. One commenter expressed concern that ADE measure could create a
disincentive for HHAs to accept patients with complex medication
regimes.
Response: We agree with the comments suggesting Adverse Drug Event
data would be duplicative and are not finalizing this measure for PY1
of the model. We will evaluate if there is a more narrowly tailored
approach for measuring quality performance related to medication
management. We will continue to analyze ways to address the issue of
adverse drug events in the home health setting and seek input from
stakeholders on including an alternative measure in future model years.
Final Decision: In consideration of comments received we are not
finalizing this measure.
c. Influenza Vaccination Coverage for Home Health Care Personnel
Staff Immunizations (Influenza Vaccination Coverage among Health
Care Personnel) (NQF #0431) is an NQF-endorsed measure that addresses
the NQS domain of Population Health (see Figure 3). The measure is
currently endorsed in Ambulatory Care; Ambulatory Surgery Center (ASC),
Ambulatory Care; Clinician Office/Clinic, Dialysis Facility, Hospital/
Acute Care Facility, Post-Acute/Long Term Care Facility; Inpatient
Rehabilitation Facility, Post-Acute/Long Term Care Facility; Long Term
Acute Care Hospital, and Post-Acute/Long Term Care Facility: Nursing
Home/Skilled Nursing Facility. Home health care is among the only
remaining settings for which the measure has not been endorsed. We
stated in the proposed rule that we believe the HHVBP Model presents an
opportunity to study this measure in the home health setting. This
measure is currently reported in multiple CMS quality reporting
programs, including Ambulatory Surgical Center Quality Reporting,
Hospital Inpatient Quality Reporting, and Long-Term Care Hospital
Quality Reporting; we believe its adoption under the HHVBP Model
presents an opportunity for alignment in our quality reporting
programs. The documentation of staff immunizations is also a standard
required by many HHA accrediting organizations. We believe that this
measure would be appropriate for HHVBP because it addresses total
population health across settings of care by reducing the exposure of
individuals to a potentially avoidable virus.
We proposed that the measure would be numerically expressed by a
ratio whose numerator and denominator are as follows:
Numerator: The measure would calculate the percentage of home
health care personnel who receive the influenza vaccine, and document
those who do not receive the vaccine in the articulated categories
below:
(1) Received an influenza vaccination administered at the health
care agency, or reported in writing (paper or electronic) or provided
documentation that influenza vaccination was received elsewhere; or
(2) Were determined to have a medical contraindication/condition of
severe allergic reaction to eggs or to other component(s) of the
vaccine, or history of Guillain[hyphen]Barr[eacute] Syndrome within 6
weeks after a previous influenza vaccination; or
(3) Declined influenza vaccination; or
(4) Persons with unknown vaccination status or who do not otherwise
meet any of the definitions of the above[hyphen]mentioned numerator
categories.
We proposed that each of the above groups would be divided by the
number of health care personnel who are working in the HHA for at least
one working day between October 1 and March 31 of the following year,
regardless of clinical responsibility or patient contact.
Denominator: This measure collects the number of home health care
personnel who work in the HHA during the flu season: \37\ Denominators
are to be calculated separately for the following three (3) groups:
---------------------------------------------------------------------------
\37\ Flu season is generally October 1 (or when the vaccine
became available) through March 31 of the following year. See URL
https://www.cdc.gov/flu/about/season/flu-season.htm for detailed
information.
---------------------------------------------------------------------------
1. Employees: all persons who receive a direct paycheck from the
reporting HHA (that is, on the agency's payroll);
2. Licensed independent practitioners: include physicians (MD, DO),
advanced practice nurses, and physician assistants only who are
affiliated with the reporting agency who do not receive a direct
paycheck from the reporting HHA; and
3. Adult students/trainees and volunteers: include all adult
students/trainees and volunteers who do not receive a direct paycheck
from the reporting HHA.
We stated in the proposed rule that this measure for the HHVBP
Model is expected to result in increased influenza vaccination among
home health professionals. Reporting health care personnel influenza
vaccination status would allow HHAs to better identify and target
unvaccinated personnel. Increased influenza vaccination coverage among
HHA personnel would be expected to result in reduced morbidity and
mortality related to influenza virus infection among patients,
especially elderly and vulnerable populations.\38\
---------------------------------------------------------------------------
\38\ Carman WF, Elder AG, Wallace LA, et al. Effects of
influenza vaccination of health[hyphen]care workers on mortality of
elderly people in long[hyphen]term care: a randomized controlled
trial. Lancet 2000; 355:93-97.
---------------------------------------------------------------------------
We proposed, and are finalizing in this rule, that information on
the above numerator and denominator will be reported by HHAs through
the HHVBP Web-based platform, in addition to other information related
to this measure as the Secretary deems appropriate.
We invited comments on the proposed Staff Influenza Vaccination
measure.
Comment: A few commenters asserted that HHVBP is not the correct
avenue for improving population health and that extending the measure
to all allied staff is too broad of a reach for the program, especially
considering that the HHA has no mandate that allows it to force allied
staff to comply. Commenters recommended modifying proposed influenza
measures to include in the numerator HHA staff who decline the
vaccination yet wear protective masks
[[Page 68677]]
or be limited to HHA staff who have contact with the patient.
Commenters also noted that staff data is already collected through
licensure and certification requirements, and recommended that CMS
promote staff influenza immunization through the upcoming Conditions of
Participation in Medicare and Medicaid for Home Health Agencies rule.
Response: Home health care is among the only remaining settings for
which the measure has not been endorsed. Mandatory health worker
vaccinations are widely endorsed by national professional associations
\39\ because public health data has conclusively demonstrated that
immunizing health staff to prevent influenza improves population
health.\40\ We also note that state certification and documentation
requirements for licensure are not consistent from state to state and
the requirement for staff vaccination is not part of the CoPs.
---------------------------------------------------------------------------
\39\ For a complete list of professional organizations that
endorse mandatory flu vaccinations for health workers see URL https://www.immunize.org/honor-roll/influenza-mandates.
\40\ Carman WF, Elder AG, Wallace LA, et al. Effects of
influenza vaccination of health[hyphen]care workers on mortality of
elderly people in long[hyphen]term care: a randomized controlled
trial. Lancet 2000; 355:93-97.
---------------------------------------------------------------------------
Comment: Some commenters suggested CMS develop state-specific or
regional time frames for when this measure applies, noting the proposed
October-March timeframe may not be sufficiently protective for states
in the Northeast.
Response: We are following flu season guidelines from the Centers
for Disease Control (CDC), which indicates peak flu season is from
October through March. We defer to CDC expertise and will not be
amending the flu time frame for the purposes of the HHVBP model at this
time.
Comment: One commenter did not support the inclusion of the metric
for Influenza Vaccination Coverage for Home Health Care Personnel
because, as proposed, the metric does not include consideration of the
overall availability of the flu vaccine at the local/state level. The
commenter asserted that regardless of known national declared
shortages, regional availability limits should be reflected within the
measure so as not to unduly penalize home health agencies.
Response: In PY1, HHAs will not be scored on immunization rates for
health personnel and will receive credit for reporting data related to
immunizing healthcare staff.
Comment: Some commenters expressed concern that the resources and
time commitment required to be able to reliably report on this metric
would create undue hardship for January 1, 2016 implementation and
suggested delayed implementation.
Response: We acknowledge the concerns expressed related to the
timeline for reporting data on New Measures and agree with commenters
that additional time for HHAs to prepare for data reporting is merited.
We are finalizing that competing HHAs will be required to report data
on this measure, as well as the other New Measures, no later than
October 7, 2016.
Final Decision: For the reasons discussed and in consideration of
the comments received, we are finalizing this New Measure as proposed,
with the modification that HHAs will be required to begin reporting
data no later than October 7, 2016 for the period July 2016 through
September 2016 and quarterly thereafter. As a result, the first
quarterly performance report in July 2016 will not account for any of
the New Measures.
c. Herpes Zoster Vaccine (Shingles Vaccine) for Patients
We proposed to adopt this measure for the HHVBP Model because it
aligns with the NQS Quality Strategy Goal to Promote Effective
Prevention & Treatment of Chronic Disease. Currently this measure is
not endorsed by NQF or collected in OASIS. However, due to the severe
physical consequences of symptoms associated with shingles,\41\ we view
its adoption under the HHVBP Model as an opportunity to perform further
study on this measure. The results of this analysis could provide the
necessary data to meet NQF endorsement criteria. We proposed that the
measure would calculate the percentage of home health patients who
receive the Shingles vaccine, and collect the number of patients who
did not receive the vaccine.
---------------------------------------------------------------------------
\41\ For detailed information on Shingles incidences and known
complications associated with this condition see CDC information
available at https://www.cdc.gov/shingles/about/overview.html.
---------------------------------------------------------------------------
Numerator: Equals the total number of Medicare beneficiaries aged
60 years and over who report having ever received herpes zoster vaccine
(shingles vaccine) during the home health episode of care.
Denominator: Equals the total number of Medicare beneficiaries aged
60 years and over receiving services from the HHA.
The Food and Drug Administration (FDA) has approved the use of
herpes zoster vaccine in adults age 50 and older. In addition, the
Advisory Committee on Immunization Practices (ACIP) currently
recommends that herpes zoster vaccine be routinely administered to
adults, age 60 years and older.\42\ In 2013, 24.2 percent of adults 60
years and older reported receiving herpes zoster vaccine to prevent
shingles, an increase from the 20.1 percent in 2012,\43\ yet below the
targets recommended in the HHS Healthy People 2020 initiative.\44\
---------------------------------------------------------------------------
\42\ CDC. Morbidity and Mortality Weekly Report 2011;
60(44):1528.
\43\ CDC. Morbidity and Mortality Weekly Report 2015; 64(04):95-
102.
\44\ Healthy People 2020: Objectives and targets for
immunization and infectious diseases. Available at https://www.healthypeople.gov/2020/topics-objectives/topic/immunization-and-infectious-diseases/objectives.
---------------------------------------------------------------------------
The incidence of herpes zoster outbreak increases as people age,
with a significant increase after age 50. Older people are more likely
to experience the severe nerve pain known as post-herpetic neuralgia
(PHN),\45\ the primary acute symptom of shingles infection, as well as
non-pain complications, hospitalizations,\46\ and interference with
activities of daily living.\47\ Studies have shown for adults aged 60
years or older the vaccine's efficacy rate for the prevention of herpes
zoster is 51.3 percent and 66.5 percent for the prevention of PHN for
up to 4.9 years after vaccination.\48\ The Short-Term Persistence Sub
study (STPS) followed patients 4 to 7 years after vaccination and found
a vaccine efficacy of 39.6 percent for the prevention of herpes zoster
and 60.1 percent for the prevention of PHN.\49\ The majority of
patients reporting PHN are over age 70; vaccination of this older
population would prevent most cases, followed by vaccination at age 60
and then age 50.
---------------------------------------------------------------------------
\45\ Yawn BP, Saddier P, Wollen PC, St Sauvier JL, Kurland MJ,
Sy LS. A population-based study of the incidence and complication
rate of herpes zoster before zoster vaccine introduction. Mayo
Clinic Proc 2007; 82:1341-9.
\46\ Lin F, Hadler JL. Epidemiology of primary varicella and
herpes zoster hospitalizations: the pre-varicella vaccine era. J
Infect Dis 2000; 181:1897-905.
\47\ Schmader KE, Johnson GR, Saddier P, et al. Effect of a
zoster vaccine on herpes zoster-related interference with functional
status and health-related quality-of-life measures in older adults.
J Am Geriatr Soc 2010; 58:1634-41.
\48\ Schmader KE, Johnson GR, Saddier P, et al. Effect of a
zoster vaccine on herpes zoster0-related interference with
functional status and health-related quality-of-life measures in
older adults. J Am Geriatr Soc 2010; 58:1634-41.
\49\ Schmader, KE, Oxman, MN, Levin, MJ, Johnson,G, Zhang, JH,
Betts, R, Morrison, VA, Gelb, L, Guatelli, JC, Harbecke, R,
Pachucki, C, Keay, S, Menzies, B, Griffin, MR, Kauffman, C, Marques,
A, Toney, J, Keller, PM, LI, X, Chan, LSF, Annumziato, P.
Persistence of the Efficacy of Zoster Vaccine in the Shingles
Prevention Study and the Short Term Persistence Substudy. Clinical
Infectious Disease 2012; 55:1320-8
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We stated in the proposed rule that studying this measure in the
home
[[Page 68678]]
health setting presents an ideal opportunity to address a population at
risk which will benefit greatly from this vaccination strategy. For
example, receiving the vaccine will often reduce the course and
severity of the disease and reduce the risk of post herpetic neuralgia.
We proposed, and are finalizing in this rule, that information on
the above numerator and denominator will be reported by HHAs through
the HHVBP web-based platform, in addition to other information related
to this measure as the Secretary deems appropriate.
We invited public comment on the proposed Herpes Zosters Vaccine
measure.
Comment: A number of commenters expressed concern that patients
refuse Shingles vaccination since the vaccine is costly and is paid for
only through Medicare Part D. A few commenters also expressed concerns
that patients in home health may not have ready knowledge of their
vaccination status, and tracking this information down could be
burdensome for HHAs. Some commenters also raised the concern that a
desire to comply with the measure presents the potential for
unnecessary repeat vaccinations.
Response: We appreciate public comment on this issue. CMS
recognizes there are payment and access issues related to the Shingles
vaccination. As a New Measure, competing HHAs will have the opportunity
to report on implementation challenges related to patients accessing
the Shingles vaccination and we will be evaluating feedback from HHAs
provided through data reporting on the measure. However, we believe
inclusion of this New Measure is connected to quality care for patients
because the Shingles vaccination has been demonstrated to either reduce
the incidence of Shingles or significantly mitigate the pain and
discomfort associated with Shingles. Including the measure in intended
to increase patient awareness and access to the vaccine if they so
choose.
Comment: One commenter recommended development of additional
vaccine measures to align with ACIP policies.
Response: We thank the commenter and note that we intend to
evaluate the measures in the HHVBP Model on an annual basis and
implement any changes to the measure set in future rulemaking. In PY1
we have included the ACIP recommendation to utilize the Shingles
vaccination, and we will refer to ACIP recommendations when analyzing
additional measures in subsequent years of the model.
Comment: Commenters expressed concern about collecting Herpes
Zoster vaccination data because they asserted that modifications to EMR
will have to occur. Commenters also asserted that the resources and
time commitment required to be able to reliably report on this metric
would create undue hardship for January 1, 2016 implementation.
Commenters recommended moving the timeline out 6-12 months for
collecting this data.
Response: We appreciate commenters' concerns regarding the timeline
for data collection and agree that in some instances additional
preparation time may be needed by competing HHAs including allowing for
those HHAs who may have to modify their clinical record system. We are
finalizing that competing HHAs will be required to report data on this
measure, as well as the other New Measures, no later than October 7,
2016 for the period July 2016 through September 2016.
Final Decision: For the reasons discussed and in consideration of
the comments received, we are finalizing this New Measure as proposed,
with the modification that HHAs will be required to begin reporting
data no later than October 7, 2016 for the period July 2016 through
September 2016 and quarterly thereafter. As a result, the first
quarterly performance report in July 2016 will not account for any of
the New Measures.
6. HHVBP Model's Four Classifications
As previously stated, the quality measures that we proposed to use
in the performance years, as well as the quality measures that we are
finalizing in this final rule, are aligned with the six NQS domains:
Patient and Caregiver-Centered Experience and Outcomes; Clinical
Quality of Care; Care Coordination; Population Health; Efficiency and
Cost Reduction; and, Safety (see Figure 6).
We proposed to filter these NQS domains and the HHVBP quality
measures into four classifications to align directly with the measure
weighting utilized in calculating payment adjustments. The four HHVBP
classifications we proposed are: Clinical Quality of Care, Outcome and
Efficiency, Person- and Caregiver-Centered Experience, and New Measures
reported by the HHAs.
We did not receive any public comments on our proposed measure
classifications for the HHVBP Model and are finalizing these
classifications with one modification. Specifically, we are revising
Classification II from ``Outcome and Efficiency'' to ``Care
Coordination and Efficiency.'' The definition of this classification is
unchanged from the proposed rule. We are making this change to be more
inclusive about this classification designation, which includes
measures/NQS domains relating to care coordination.
These final four classifications capture the multi-dimensional
nature of health care provided by the HHA. These classifications are
further defined as:
Classification I--Clinical Quality of Care: Measures the
quality of health care services provided by eligible professionals and
paraprofessionals within the home health environment.
Classification II--Care Coordination and Efficiency:
Outcomes measure the end result of care including coordination of care
provided to the beneficiary. Efficiencies measure maximizing quality
and minimizing use of resources.
Classification III--Person- and Caregiver-Centered
Experience: Measures the beneficiary and their caregivers' experience
of care.
Classification IV--New Measures: Measures not currently
reported by Medicare-certified HHAs to CMS, but that may fill gaps in
the NQS Domains not completely covered by existing measures in the home
health setting.
[[Page 68679]]
[GRAPHIC] [TIFF OMITTED] TR05NO15.005
7. Weighting
We proposed that measures within each classification would be
weighted the same for the purposes of payment adjustment. We are
weighting at the individual measure level and not the classification
level. Classifications are for organizational purposes only. We
proposed this approach because we did not want any one measure within a
classification to be more important than another measure. Under this
approach, a measure's weight will remain the same even if some of the
measures within a classification group have no available data. We
stated in the proposed rule that weighting will be re-examined in
subsequent years of the model and be subject to the rulemaking process.
We invited comments on the proposed weighting methodology for the HHVBP
Model.
Comment: We received a few comments on the weighting of measures in
the starter set. Some commenters recommended that certain measures
should be weighted more than others; with one comment specifying the
re-hospitalization measure should have greater weight, and some other
commenters suggesting that measures not based on self-reported data
should have greater weight. One commenter expressed concern that by
weighting measures equally, HHAs will have little opportunity to make
significant improvements because each measure will only represent a
small fraction of the agency's score; therefore, agencies would need to
make large improvements in many measures to see a meaningful difference
in their overall score. All comments related to weighting indicated a
preference for moving away from each measure receiving equal weight.
Response: The quality measures that were selected for the HHVBP
Model capture the multiple dimensions of care that HHA provide to their
beneficiaries. We are finalizing this proposed policy because equally
weighted measures will encourage HHAs to approach quality improvement
initiatives more broadly in an effort to capture the multidimensional
aspects of care that HHAs provide. In addition, weighting the measures
equally addresses concerns where HHAs may be providing services to
beneficiaries with different needs. If particular measures are weighted
more than others, HHAs may only make the investment to improve their
quality in those areas where measures have a higher weight, potentially
allowing other aspects of care to be subject to potential neglect. We
will monitor the impact of the equally weighting the individual
measures and may consider changes to the weighting methodology after
analysis and through rulemaking.
Final Decision: For the reasons discussed, we are finalizing the
weighting methodology as proposed without modification.
F. Performance Scoring Methodology
1. Performance Calculation Parameters
The methodology we proposed, and are finalizing in this final rule
for the reasons discussed herein, for assessing each HHA's total annual
performance is based on a score calculated using the starter set of
quality measures that apply to the HHA (based on a minimum number of
cases, as discussed herein). The methodology will provide an assessment
on a quarterly basis for each HHA and will result in an annual
distribution of value-based payment adjustments among HHAs so that HHAs
achieving the highest performance scores will receive the largest
upward payment adjustment. The methodology includes three primary
features:
The HHA's Total Performance Score (TPS) will be determined
using the higher of an HHA's achievement or improvement score for each
measure;
All measures within the Clinical Quality of Care, Care
Coordination and Efficiency, and Person and Caregiver-Centered
Experience classifications will have equal weight and will account for
90-percent of the TPS (see Section 2 below) regardless of the number of
measures in the three classifications.
[[Page 68680]]
Points for New Measures are awarded for submission of data on the New
Measures via the HHVBP web-based platform, and withheld if data is not
submitted. Data reporting for each New Measure will have equal weight
and will account for 10-percent of the TPS for the first performance
year; and,
The HHA performance score would reflect all of the
measures that apply to the HHA based on a minimum number of cases
defined below.
For the reasons discussed in more detail later in this section, we
are finalizing our proposed performance scoring methodology with one
modification related to the rounding up or down of achievement and
improvement scoring used in the calculation of the Total Performance
Score.
2. Considerations for Calculating the Total Performance Score
We proposed, and are finalizing in this final rule, in Sec.
484.320 to calculate the TPS by adding together points awarded to
Medicare-certified HHAs on the starter set of measures, including the
New Measures. As explained in the proposed rule, we considered several
factors when developing the performance scoring methodology for the
HHVBP Model. First, it is important that the performance scoring
methodology be straightforward and transparent to HHAs, patients, and
other stakeholders. HHAs must be able to clearly understand performance
scoring methods and performance expectations to maximize quality
improvement efforts. The public must understand performance score
methods to utilize publicly-reported information when choosing HHAs.
Second, we believe the performance scoring methodology for the
HHVBP Model should be aligned appropriately with the quality
measurements adopted for other Medicare value-based purchasing programs
including those introduced in the hospital and skilled nursing home
settings. This alignment will facilitate the public's understanding of
quality measurement information disseminated in these programs and
foster more informed consumer decision-making about their health care
choices.
Third, we believe that differences in performance scores must
reflect true differences in quality performance. To make sure that this
point is addressed in the performance scoring methodology for the HHVBP
Model, we assessed quantitative characteristics of the measures,
including the current state of measure development, number of measures,
and the number and grouping of measure classifications.
Fourth, we believe that both quality achievement and improvement
must be measured appropriately in the performance scoring methodology
for the HHVBP Model. The methodology specifies that performance scores
under the HHVBP Model are calculated utilizing the higher of
achievement or improvement scores for each measure. The impact of
performance scores utilizing achievement and improvement on HHAs'
behavior and the resulting payment implications was also considered.
Using the higher of achievement or improvement scores allows the model
to recognize HHAs that have made great improvements, though their
measured performance score may still be relatively lower in comparison
to other HHAs.
Fifth, through careful measure selection we intend to eliminate, or
at least control for, unintended consequences such as undermining
better outcomes to patients or rewarding inappropriate care. As
discussed above, when available, NQF endorsed measures will be used. In
addition we are adopting measures that we believe are closely
associated with better outcomes in the HHA setting in order to
incentivize genuine improvements and sustain positive achievement while
retaining the integrity of the model.
Sixth, we intend that the model will utilize the most currently
available data to assess HHA performance. We recognize that these data
would not be available instantaneously due to the time required to
process quality measurement information accurately; however, we intend
to make every effort to process data in the timeliest fashion. Using
more current data will result in a more accurate performance score
while recognizing that HHAs need time to report measure data.
3. Additional Considerations for the HHVBP Total Performance Scores
Many of the key elements of the HHVBP Model performance scoring
methodology that we proposed, and are finalizing in this final rule for
the reasons described herein, are aligned with the scoring methodology
of the Hospital Value-Based Purchasing Program (HVBP) in order to
leverage the rigorous analysis and review underpinning that Program's
approach to value-based purchasing in the hospital sector. The HVBP
Program includes as one of its core elements the scoring methodology
included in the 2007 Report to Congress ``Plan to Implement a Medicare
Hospital Value-Based Purchasing Program'' (hereinafter referred to as
``The 2007 HVBP Report'').\50\ The 2007 HVBP Report describes a
Performance Assessment Model with core elements that can easily be
replicated for other value-based purchasing programs or models,
including the HHVBP Model.
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\50\ The 2007 HVBP Report is available at the CMS Web site at
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/downloads/HospitalVBPPlanRTCFINALSUBMITTED2007.pdf.
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In the HVBP Program, the Performance Assessment Model aggregates
points on the individual quality measures across different quality
measurement domains to calculate a hospital's TPS. Similarly, the
proposed HHVBP Model would aggregate points on individual measures
across four measure classifications derived from the 6 CMS/NQS domains
as described above (see Figure 3) to calculate the HHA's TPS. In
addition, the proposed HHVBP payment methodology is also aligned with
the HVBP Program with respect to evaluating an HHA's performance on
each quality measure based on the higher of an achievement or
improvement score in the performance period. The model is not only
designed to provide incentives for HHAs to provide the highest level of
quality, but also to provide incentives for HHAs to improve the care
they provide to Medicare beneficiaries. By rewarding HHAs that provide
high quality and/or high improvement, we believe the HHVBP Model will
ensure that all HHAs will be incentivized to commit the resources
necessary to make the organizational changes that will result in better
quality.
We proposed, and are finalizing for the reasons described herein,
that under the model, an HHA will be awarded points only for
``applicable measures.'' An ``applicable measure'' is one for which the
HHA has provided 20 home health episodes of care per year. Points
awarded for each applicable measure will be aggregated to generate a
TPS. As described in the benchmark section below, HHAs will have the
opportunity to receive 0 to 10 points for each measure in the Clinical
Quality of Care, Care Coordination and Efficiency, and Person and
Caregiver-Centered Experience classifications. Each measure will have
equal weight regardless of the total number of measures in each of the
first three classifications. In contrast, we proposed, and are
finalizing in this rule, to score the New Measures in a different way.
For each New Measure, HHAs will receive 10 points if they report the
New Measure or 0 points if they do not report the measure during the
performance
[[Page 68681]]
year. In total, the New Measures will account for 10-percent of the TPS
regardless of the number of measures applied to an HHA in the other
three classifications.
We proposed, and are finalizing in this rule, to calculate the TPS
for the HHVBP methodology similarly to the TPS calculation that has
been finalized under the HVBP program. The performance scoring
methodology for the HHVBP Model will include determining performance
standards (benchmarks and thresholds) using the 2015 baseline period
performance year's quality measure data, scoring HHAs based on their
achievement and/or improvement with respect to those performance
standards, and weighting each of the classifications by the number of
measures employed, as presented in further detail in Section G below.
4. Setting Performance Benchmarks and Thresholds
For scoring HHAs' performance on measures in the Clinical Quality
of Care, Care Coordination and Efficiency, and Person and Caregiver-
Centered Experience classifications, we proposed, and are finalizing in
this rule, to adopt an approach using several key elements from the
scoring methodology set forth in the 2007 HVBP Report and the
successfully implemented HVBP Program \51\ including allocating points
based on achievement or improvement, and calculating those points based
on industry benchmarks and thresholds.
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\51\ For detailed information on HVBP scoring see https://www.medicare.gov/hospitalcompare/data/hospital-vbp.html.
---------------------------------------------------------------------------
In determining the achievement points for each measure, HHAs will
receive points along an achievement range, which is a scale between the
achievement threshold and a benchmark. We proposed, and are finalizing
in this rule, that the achievement threshold will be calculated as the
median of all HHAs' performance on the specified quality measure during
the baseline period and to calculate the benchmark as the mean of the
top decile of all HHAs' performance on the specified quality measure
during the baseline period. Unlike the HVBP Program that uses a
national sample, this model will calculate both the achievement
threshold and the benchmark separately for each selected state and for
HHA cohort size. Under this methodology, we will have benchmarks and
achievement thresholds for both the larger-volume cohort and for the
smaller-volume cohort of HHAs (defined in each state based on a
baseline period that runs from January 1, 2015 through December 31,
2015). Another way HHVBP differs from the Hospital VBP is this model
only uses 2015 as the baseline year for the measures included in the
starter set. For the starter set used in the model, 2015 will
consistently be used as the baseline period in order to evaluate the
degree of change that may occur over the multiple years of the model.
In determining improvement points for each measure, we proposed, and
are finalizing in this rule, that HHAs will receive points along an
improvement range, which is a scale indicating change between an HHA's
performance during the performance period and the baseline period. In
addition, as in the achievement calculation, the benchmark and
threshold will be calculated separately for each state and for HHA
cohort size so that HHAs will only be competing with those HHAs in
their state and their size cohort.
5. Calculating Achievement and Improvement Points
a. Achievement Scoring
We proposed the achievement scoring under the HHVBP Model be based
on the Performance Assessment Model set forth in the 2007 HVBP Report
and as implemented under the HVBP Program. An HHA could earn 0-10
points for achievement for each measure in the Clinical Quality of
Care, Care Coordination and Efficiency, and Person and Caregiver-
Centered Experience classifications based on where its performance
during the performance period falls relative to the achievement
threshold and the benchmark, according to the following formula:
[GRAPHIC] [TIFF OMITTED] TR05NO15.006
We proposed that all achievement points would be rounded up or down
to the nearest point (for example, an achievement score of 4.55 would
be rounded to 5). After considering the potential skewing of HHA
ranking that would occur with rounding up to the nearest point, we are
finalizing that all achievement points will be rounded up or down to
the third decimal point (for example, an achievement score of 4.5555
would be rounded to 4.556). The will ensure greater precision in
scoring and ranking HHAs within their cohorts.
HHAs could receive an achievement score as follows:
An HHA with performance equal to or higher than the
benchmark could receive the maximum of 10 points for achievement.
An HHA with performance equal to or greater than the
achievement threshold (but below the benchmark) could receive 1-9
points for achievement, by applying the formula above.
An HHA with performance less than the achievement
threshold could receive 0 points for achievement.
We invited comments on the proposed methodology for scoring HHAs on
achievement.
Comment: Some commenters expressed concern that HHAs will not know
what benchmark is needed to avoid penalty until the end of the 2015
performance year, and several commenters recommended that CMS establish
benchmarks based on historical performance so it is clear to HHAs the
level of achievement necessary to avoid penalties. Commenters voiced
concern that agencies may not invest in quality improvement activities
if the potential financial return is difficult to determine. Commenters
also recommended that CMS set benchmarks at a level such that most
providers have a reasonable expectation of achieving them. A few
commenters suggested keeping 2015 as the base year, and suggested
providing HHAs with mid-course snapshots of their performance against
the benchmarks.
Response: The HHVBP Model is using the 2015 quality data as the
baseline for the model because it is the most recent data available. As
indicated in the payment methodology, the achievement threshold for
each measure used in the
[[Page 68682]]
model will be based on the median of Medicare-certified HHA performance
on the specified quality measure during the baseline period (2015). The
benchmark refers to the mean of the top decile of Medicare-certified
HHA performance on the specified quality measure during the baseline
period (2015). Benchmarks and achievement thresholds are calculated
separately for the larger-volume and smaller-volume cohorts within each
state. HHAs will receive points if they achieve performance equal to or
above the achievement threshold (the median of 2015). We believe that
awarding points to HHAs that provide better quality than the median is
an achievable level and will incentivize HHAs to make the investments
necessary to improve their quality. Benchmarks and achievement
thresholds for each measure will be available on each respective HHA's
quarterly report. The 2015 base year achievement threshold and the
benchmarks for each cohort will be provided to the HHAs in April 2016.
We believe that this will provide sufficient notice to HHAs of the
level of performance necessary to receive points for each given
measure. In addition, baseline values will be included in all quarterly
reports for all measures.
Final Decision: For the reasons discussed and in consideration of
the comments received, we are finalizing the proposed methodology for
scoring HHAs on achievement under the HHVBP Model, with one
modification. Specifically, as noted above, under our final policy all
achievement points will be rounded up or down to the third decimal
point (for example, an achievement score of 4.5555 would be rounded to
4.556).
b. Improvement Scoring
In keeping with the approach used by the HVBP Program, we proposed
that an HHA could earn 0-10 points based on how much its performance
during the performance period improved from its performance on each
measure in the Clinical Quality of Care, Care Coordination and
Efficiency, and Person and Caregiver-Centered Experience
classifications during the baseline period. A unique improvement range
for each measure will be established for each HHA that defines the
difference between the HHA's baseline period score and the same state
and size level benchmark for the measure used in the achievement
scoring calculation described previously, according to the following
formula:
[GRAPHIC] [TIFF OMITTED] TR05NO15.007
We proposed that all improvement points will be rounded to the
nearest point and are now finalizing that improvement points will be
rounded up or down to the third decimal point (see example above). If
an HHA's performance on the measure during the performance period was:
Equal to or higher than the benchmark score, the HHA could
receive an improvement score of 10 points;
Greater than its baseline period score but below the
benchmark (within the improvement range), the HHA could receive an
improvement score of 0-10, based on the formula above; or
Equal to or lower than its baseline period score on the
measure, the HHA could receive 0 points for improvement.
We invited comments on the proposed methodology for scoring HHAs on
improvement.
Comment: There were many comments directed at the proposed
methodology for improvement scoring under the HHVBP Model. Some
commenters opposed awarding credit for improvement, and noted their
concern that by using the greater of either an HHA's achievement or
improvement score, the methodology could reward a HHA with a low
performance but high improvement score because that HHA could receive
higher payments than a high performing agency. These commenters
encouraged CMS to focus on rewarding the achievement of specified
quality scores, and reduce its emphasis on improvement scores after the
initial three years of the HHVBP Model, given that what matters most to
beneficiaries is an agency's actual performance. Additionally,
commenters recommended that HHA achievement scores be weighted more
heavily than improvement scores, noting that some HHAs may have little
or no room for improvement in their current quality performance scores.
Some commenters suggested measuring performance primarily on the basis
of achievement of specified quality scores, with a declining emphasis
over time on improvement versus achievement.
Response: We appreciate the commenters raising these concerns. The
model is designed to improve and to ensure the highest quality of care
for all Medicare beneficiaries. If the model only focused on rewarding
those HHAs that already provide the highest quality of care, only the
beneficiaries that receive care from those HHAs would benefit from the
model. Therefore, we believe that providing the opportunity to earn
points for both achievement and improvement provides the greatest
opportunity for the quality of care to rise for all beneficiaries who
receive services from competing HHAs. We will, however, monitor and
evaluate the impact of awarding an equal amount of points for both
achievement and improvement and may consider changes to the weight of
the improvement score relative to the achievement score in future years
through rulemaking.
Final Decision: For the reasons discussed, we are finalizing the
improvement scoring methodology as proposed.
Comment: Several commenters expressed concern that the proposed
HHVBP structure requires that HHAs be penalized each year, regardless
of their performance or improvement, noting that each year, some HHAs
will end up in the bottom decile, even if the difference between the
highest and lowest scoring is only a few points. These commenters were
concerned that if the lowest scoring HHAs do not have the resources to
rise from the bottom they are at risk for going out of business by the
end of the model. If low scoring HHAs leave the market, then higher
scoring HHAs will move into the bottom decile the next year of the
model. These HHAs could experience a downward payment adjustment even
though their performance, in actuality, is not significantly different
than HHAs ranked higher. These commenters are concerned this limits
value based performance improvement.
Response: We understand commenters concerns but the purpose of the
model is to improve quality across the HH sector. As is the case
currently, the market will not remain static, and HHAs of all calibers
will leave and enter the market. In many instances, if a small number
of low performing HHAs do drop out of the market, the next group
[[Page 68683]]
of low scoring HHAs will include HHAs whose performance equals or
exceeds the average baseline performance, and will likely have received
bonus payments in previous years. We have done financial modeling based
on recent HHA performance (see chart I2 for further explanation) and
results support our understanding of how scoring will work. In
addition, we have analyzed available data and lessons learned from the
Hospital VBP program and the previous home health demonstration to
support our findings. As indicated in the proposed rule,\52\ HHAs may
end up in the bottom decile in relationship to other HHAs in their
cohort in later years of the model even after they improve their
quality if all the HHAs in the model improve at the same rate. However,
in the HHVBP model their downward payment adjustment, if any, could be
substantially reduced because all performance scoring is anchored to
the 2015 benchmark.
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\52\ 80 FR 39910 (July 10, 2015). See Table 25.
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Final Decision: For the reasons discussed and in consideration of
the comments received, we are finalizing the proposed methodology for
scoring HHAs under the HHVBP Model, with one modification to decimal
scoring, where we are finalizing that all achievement and improvement
points will be rounded up or down to the third decimal point (for
example, an achievement score of 4.5555 would be rounded to 4.556).
c. Examples of Calculating Achievement and Improvement Scores
For illustrative purposes we present the following examples of how
the performance scoring methodology will be applied in the context of
the measures in the Clinical Quality of Care, Care Coordination and
Efficiency, and Person and Caregiver-Centered Experience
classifications. These HHA examples were selected from an empirical
database created from 2013/2014 data from the Home Health Compare
archived data, claims data and enrollment data to support the
development of the HHVBP permutation of the Performance Assessment
Model, and all performance scores are calculated for the pneumonia
measure, with respect to the number of individuals assessed and
administered the pneumococcal vaccine. We note that the figures and
examples below are the same figures and examples set forth in the
proposed rule, updated to reflect our final policy on rounding of these
scores, as discussed previously.
Figure 7 shows the scoring for HHA `A', as an example. The
benchmark calculated for the pneumonia measure in this case was 0.875
(the mean value of the top decile in 2013), and the achievement
threshold was 0.474 (the performance of the median or the 50th
percentile among HHAs in 2013). HHA A's 2014 performance rate of 0.910
during the performance period for this measure exceeds the benchmark,
so HHA A would earn 10 (the maximum) points for its achievement score.
The HHA's performance rate on a measure is expressed as a decimal. In
the illustration, HHA A's performance rate of 0.910 means that 91-
percent of the applicable patients that were assessed were given the
pneumococcal vaccine. In this case, HHA A has earned the maximum number
of 10 possible achievement points for this measure and thus, its
improvement score is irrelevant in the calculation.
Figure 7 also shows the scoring for HHA `B'. As referenced below,
HHA B's performance on this measure went from 0.212 (which was below
the achievement threshold) in the baseline period to 0.703 (which is
above the achievement threshold) in the performance period. Applying
the achievement scale, HHA B would earn 5.640 points for achievement,
calculated as follows: [9 * ((0.703 - 0.474)/(0.875 - 0.474))] + 0.5 =
5.640.
Checking HHA B's improvement score yields the following result:
Based on HHA B's period-to-period improvement, from 0.212 in the
baseline year to 0.703 in the performance year, HHA B would earn 6.906
points, calculated as follows: [10 * ((0.703 - 0.212)/(0.875 - 0.212))]
- 0.5 = 6.906. Because the higher of the achievement and improvement
scores is used, HHA B would receive 6.906 points for this measure.
[[Page 68684]]
[GRAPHIC] [TIFF OMITTED] TR05NO15.008
In Figure 8, HHA `C' yielded a decline in performance on the
pneumonia measure, falling from 0.571 to 0.462 (a decline of 0.11
points). HHA C's performance during the performance period is lower
than the achievement threshold of 0.472 and, as a result, receives 0
points based on achievement. It also receives 0 points for improvement,
because its performance during the performance period is lower than its
performance during the baseline period.
[[Page 68685]]
[GRAPHIC] [TIFF OMITTED] TR05NO15.009
6. Scoring Methodology for New Measures
The HHVBP Model provides us with the opportunity to study new
quality measures. We proposed that the New Measures for PY1 would be
reported directly by the HHA and would account for 10-percent of the
TPS regardless of the number of measures in the other three
classifications (we refer the reader to 80 FR 39890 for further
discussion of our proposed scoring methodology for New Measures). For
the reasons set forth in the proposed rule and in response to comments
below, we are finalizing our proposed scoring methodology for New
Measures, revised only to reflect that the final starter set will
include three, rather than four, New Measures, as discussed in section
E5. Under our final methodology, the final three New Measures that we
are adopting for PY1 will be reported directly by the HHA and will
account for 10-percent of the TPS regardless of the number of measures
in the other three classifications. HHAs that report on these measures
will receive 10 points out of a maximum of 10 points for each of the 3
measures in the New Measure classification. Hence, a HHA that reports
on all 3 measures will receive 30 points out of a maximum of 30. An HHA
will receive 0 points for each measure that it fails to report on. If
an HHA reports on all 3 measures, it will receive 30 points for the
classification and 10 points (30/30 * 10 points) will be added to its
TPS because the New Measure classification has a maximum weight of 10
percent. If an HHA reports on 2 of 3 measures, it will receive 20
points of 30 points available for the classification and 6.667 points
(20/30 * 10 points) added to its TPS. If an HHA reports on 1 of 3
measures, they will receive 10 points of 30 points available for the
classification and 3.333 points (10/30 * 10 points) added to their TPS.
If an HHA reports on 0 of 3 measures, they will receive 0 points and
have no points added to their TPS. We intend to update these measures
through future rulemaking to allow us to study newer, leading-edge
measures as well as retire measures that no longer require such
analysis.
We invited comments on the proposed scoring methodology for New
Measures.
Comment: Several commenters expressed support for CMS limiting the
burden on HHAs by allowing them to gain full credit toward their TPS on
the New Measures just for reporting data to CMS.
Response: We appreciate the commenters' support for our proposal.
In order to reduce the burden of introducing innovative measures not
previously endorsed for home health, and to allow HHAs to acclimate to
reporting the New Measures, we are finalizing our proposed scoring
methodology that awards HHAs full credit for data reporting on New
Measures.
Final Decision: For the reasons discussed and in consideration of
the comments received, we are finalizing our proposed scoring
methodology for New Measures, modified to reflect the removal of one
New Measure resulting in a total of three New Measures for PY1.
7. Minimum Number of Cases for Outcome and Clinical Quality Measures
We proposed that while no HHA in a selected state would be exempt
from the HHVBP Model, there may be periods when an HHA does not receive
a payment adjustment because there are not an adequate number of
episodes of care to generate sufficient quality measure data. We
proposed, and are finalizing in this rule, that the minimum threshold
for an HHA to receive a score on a given measure will be 20 home health
episodes of care per year for HHAs that have been certified for at
least 6-months. If a competing HHA does not meet this threshold to
generate scores on five or more of the Clinical Quality of Care, Care
Coordination and Efficiency, and Person and Caregiver-Centered
Experience measures, no payment adjustment will be made, and
[[Page 68686]]
the HHA will be paid for HHA services in an amount equivalent to the
amount it would have been paid under section 1895 of the Act.\53\
---------------------------------------------------------------------------
\53\ HHVBP would follow the Home Health Compare Web site policy
not to report measures on HHAs that have less than 20 observations
for statistical reasons concerning the power to detect reliable
differences in the quality of care.
---------------------------------------------------------------------------
We explained in the proposed rule that HHAs with very low case
volumes will either increase their volume in later performance years,
and be subject to future payment adjustment, or the HHAs' volume will
remain very low and the HHAs would continue to not have their payment
adjusted in future years. Based on the most recent data available at
this time, a very small number of HHAs are reporting on less than five
of the total number of measures included in the Clinical Quality of
Care, Care Coordination and Efficiency, and Person and Caregiver-
Centered Experience classifications and account for less than 0.5
percent of the claims made over 1,900 HHAs delivering care within the
nine selected states. We stated that we expect very little impact of
very low service volume HHAs on the model due to the low number of low-
volume HHAs and because it is unlikely that a HHA will reduce the
amount of service to such a low level to avoid a payment adjustment.
Although these HHAs will not be subject to payment adjustments, they
will remain in the model and have access to the same technical
assistance as all other HHAs in the model, and will receive quality
reports on any measures for which they do have 20 episodes of care, and
a future opportunity to compete for payment adjustments.
We invited comments on the proposed minimum number of cases to
receive a score on outcome and clinical quality measures.
Comment: One commenter expressed concern that some HHAs would
artificially suppress the number of cases open in OASIS to below 20 in
order to be excluded from a particular measure, or be excluded from a
sufficient number of measures to be excluded from payment adjustments
entirely.
Response: All Medicare-certified HHAs in selected states are
included in the HHVBP Model, even when a particular HHA does not meet
the minimum number of cases to generate scores on a sufficient number
of quality measures. During a period when an HHA does not receive a
payment adjustment the HHA remains in the model, performance is still
monitored, and the agency is eligible for technical assistance. HHAs
with small patient loads are expected to access technical assistance
and engage in quality improvement activities in anticipation of earning
scores on all quality measures in the future. HHAs with small patient
populations are also expected to enter data on the New Measures via the
CMS portal. In addition, HHAs must submit OASIS data in order to
receive payment for their services. We do not anticipate HHAs
suppressing the number of patients they serve in order to avoid payment
adjustments because there are very few HHAs that provide care to such a
small number of beneficiaries and the financial losses associated with
restricting the volume of care provided would far outweigh the losses
associated with the downward payment adjustment.
Final Decision: For these reasons and in consideration of the
comments received, we are finalizing our proposal on the minimum number
of cases for outcome and clinical quality measures without
modification.
We provide below an example of the payment methodology. We note
that this is the same example provided in the proposed rule (see 80 FR
39891), modified only to reflect our final policy to include 21 (rather
than 25) measures in the Clinical Quality of Care, Care Coordination
and Efficiency, and Person and Caregiver-Centered Experience
classifications and three (rather than four) New Measures in the final
starter set for PY1.
HHA ``A'' has at least 20 episodes of care in a 12-month period for
only nine (9) quality measures out of a possible 21 measures from three
of the four classifications (except the New Measures). Under the final
scoring methodology outlined above, HHA A would be awarded 0, 0, 3, 4,
5, 7, 7, 9, and 10 points, respectively, for these measures. HHA A's
total earned points for the three classifications would be calculated
by adding together all the points awarded to HHA A, resulting in a
total of 45 points. HHA A's total possible points would be calculated
by multiplying the total number of measures for which the HHA reported
on least 20 episodes (nine) by the maximum number of points for those
measures (10), yielding a total of 90 possible points. HHA A's score
for the three classifications would be the total earned points (45)
divided by the total possible points (90) multiplied by 90 because as
mentioned in section E7, the Clinical Quality of Care, Care
Coordination and Efficiency, and Person and Caregiver-Centered
Experience classifications account for 90-percent of the TPS and the
New Measures classification accounts for 10-percent of the TPS, which
yields a result of 45. In this example, HHAs also reported all 3
measures and would receive the full 10 points for the New Measures. As
a result, the TPS for HHA A would be 55 (45 plus 10). In addition, as
specified in Section E:7--Weighting, all measures have equal weights
regardless of their classification (except for New Measures) and the
total earned points for the three classifications can be calculated by
adding the points awarded for each such measure together.
G. The Payment Adjustment Methodology
We proposed to codify at 42 CFR 484.330 a methodology for applying
value-based payment adjustments to home health services under the HHVBP
Model. We proposed that payment adjustments would be made to the HH PPS
final claim payment amount as calculated in accordance with Sec.
484.205 using a linear exchange function (LEF) similar to the
methodology utilized by the HVBP Program. The LEF is used to translate
an HHA's TPS into a percentage of the value-based payment adjustment
earned by each HHA under the HHVBP Model. The LEF was identified by the
HVBP Program as the simplest and most straightforward option to provide
the same marginal incentives to all hospitals, and we believe the same
to be true for HHAs. We proposed the function's intercept at zero
percent, meaning those HHAs that have a TPS that is average in
relationship to other HHAs in their cohort (a zero percent), would not
receive any payment adjustment. Payment adjustments for each HHA with a
score above zero percent would be determined by the slope of the LEF.
In addition we proposed to set the slope of the LEF for the first
performance year, CY 2016, so that the estimated aggregate value-based
payment adjustments for CY 2016 are equal to 5-percent of the estimated
aggregate base operating episode payment amount for CY 2018. The
estimated aggregate base operating episode payment amount is the total
amount of episode payments made to all the HHAs by Medicare in each
individual state in the larger- and smaller-volume cohorts
respectively.
We provided in Figure 9 of the proposed rule an example of how the
LEF is calculated and how it would be applied to calculate the
percentage payment adjustment to a HHA's TPS (we refer the reader to 80
FR 39891 through 39892 for further discussion of our proposal). For
this example, we applied the 8-percent payment adjustment level that
was proposed to be used in the final 2 years of the HHVBP Model, and
noted that the rate
[[Page 68687]]
for the payment adjustments for other years would be proportionally
less.
We invited comments on this proposed payment adjustment
methodology.
Comment: While offering support for the concept of value-based
purchasing, the majority of commenters expressed concern with the
magnitude of an 8-percent maximum payment risk such that it might
reduce access to care for vulnerable patients. Commenters offered that
payment adjustments could be made in later years of the model to
provide HHAs with adequate time to ensure readiness to comply with
model requirements and to allow CMS more time to study the initial
model results. Many commenters also remarked on the differences between
the Hospital Value- Based Purchasing (HVBP) Program and HHVBP Model
maximum risk corridors and suggested lowering the HHVBP payment
adjustments to align with the 2-percent maximum established in the HVBP
Program.
Response: We thank commenters for their input. As discussed in the
proposed rule, based on lessons learned from Hospital VBP, the 2008
Home Health pay for performance demonstration, and the MedPAC report,
we believe that testing high financial incentives is necessary to
motivate improvements in quality and patient satisfaction. However, we
agree with commenters that providing some additional leeway for HHAs to
ensure compliance with the model is important, and would also address
concerns associated with moving competing HHAs from FFS incentives to
VBP financial incentives tied to quality measures. Accordingly, under
our final policy, we are reducing the payment adjustment percentage in
CY 2018 from 5-percent to 3-percent. Further, by responding to these
practical concerns, the conceptual model remains intact with the
capacity to test the effect of higher incentives on quality.
We believe this will provide HHAs more time to become familiar with
the operation of the model before applying the higher percentage
payment adjustments in later years. Additionally, under our final
policy, we are reducing the payment adjustment for CY 2021 from 8-
percent to 7-percent to establish a more gradual payment adjustment
incentive schedule of 3-percent (in 2018), 5-percent (in 2019), 6-
percent (in 2020), 7-percent (in 2021) and, 8-percent (in 2022).
Comment: Several commenters raised concerns with the magnitude of
an 8-percent maximum payment risk such that it might reduce access to
care for vulnerable patients and threaten the financial viability of
HHAs, including their ability to reinvest in infrastructure, care
coordination, and financial preparations to participate in the HHVBP
Model.
Response: We have conducted financial modeling based on the
proposed model and posit the finalized maximum upward and downward
payment adjustments (ranging from 3- to 8-percent) are sufficiently
significant to improve quality of care and will not have a negative
impact on beneficiary access. The model does not reduce the overall
payments to HHAs and, as a result, the aggregate average margins of all
competing HHAs will be unaffected by the model. 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.
Final Decision: For the reasons discussed and in consideration of
the comments received, we are finalizing the proposed payment
adjustment methodology with modification. As noted, we are finalizing
the following maximum payment adjustment percentage for each payment
year: in CY 2018, 3-percent; in CY 2019, 5-percent; in CY 2020, 6-
percent; in CY 2021, 7-percent; and in CY 2022, 8-percent. Consistent
with this final policy, under our final payment adjustment methodology,
we set the slope of the LEF for the first performance year, CY 2016, so
that the estimated aggregate value-based payment adjustments for CY
2016 are equal to 3-percent of the estimated aggregate base operating
episode payment amount for CY 2018, rather than 5-percent as proposed.
Figure 9 provides an example of how the LEF is calculated and how
it is applied to calculate the percentage payment adjustment to a HHA's
TPS under our final policy. For this example, we applied the 8-percent
payment adjustment level that will be used in the final year of the
HHVBP Model (CY 2022) under our final policy. The rate for the payment
adjustments for other years would be proportionally less.
Step #1 involves the calculation of the `Prior Year Aggregate HHA
Payment Amount' (See C2 in Figure 9) that each HHA was paid in the
prior year. From claims data, all payments are summed together for each
HHA for CY 2015, the year prior to the HHVBP Model.
Step #2 involves the calculation of the `8-percent Payment
Reduction Amount' (C3 of Figure 9) for each HHA. The `Prior Year
Aggregate HHA Payment Amount' is multiplied by the `8-percent Payment
Reduction Rate'. The aggregate of the `8-percent Payment Reduction
Amount' is the numerator of the LEF.
Step #3 involves the calculation of the `Final TPS Adjusted
Reduction Amount' (C4 of Figure 9) by multiplying the `8-percent
Payment Reduction Amount' from Step #2 by the TPS (C1) divided by 100.
The aggregate of the `TPS Adjusted Reduction Amount' is the denominator
of the LEF.
Step #4 involves calculating the LEF (C5 of Figure 9) by dividing
the aggregate `8-percent Payment Reduction Amount' by the aggregate
`TPS Adjusted Reduction Amount'.
Step #5 involves the calculation of the `Final TPS Adjusted Payment
Amount' (C6 of Figure 9) by multiplying the `TPS Adjusted Reduction
Amount' (C4) by the LEF (C5). This is an intermediary value used to
calculate `Quality Adjusted Payment Rate'.
Step #6 involves the calculation of the `Quality Adjusted Payment
Rate' (C7 of Figure 9) that the HHA will receive instead of the 8-
percent reduction in payment. This is an intermediary step to
determining the payment adjustment rate. For CY 2022, the payment
adjustment in this column will range from 0-percent to 16-percent
depending on the quality of care provided.
Step #7 involves the calculation of the `Final Percent Payment
Adjustment' (C8 of Figure 9) that will be applied to the HHA payments
after the performance period. It simply involves the CY payment
adjustment percent (as finalized, in 2018, 3-percent; in 2019, 5-
percent; in 2020, 6-percent; in 2021, 7-percent; and in 2022, 8-
percent). In this example, we use the maximum eight-percent (8-percent)
subtraction to the `Quality Adjusted Payment Rate'. Note that the
payment adjustment percentage is capped at no more than plus or minus
8-percent for each respective performance period and the payment
adjustment will occur on the final claim payment amount.
[[Page 68688]]
Figure 9--8-Percent Reduction Sample
--------------------------------------------------------------------------------------------------------------------------------------------------------
Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7
-------------------------------------------------------------------------------------------------
Linear
Prior year 8-Percent TPS adjusted exchange Final TPS Quality Final
HHA TPS aggregate payment reduction function adjusted adjusted percent
HHA payment reduction amount (C1/ (LEF) (Sum payment payment rate payment
* amount 100)*C3 of C3/ Sum amount (C6/C2) *100 adjustment +/
(C2*8%) of C4) (C4*C5) - (C7-8%)
(C1) (C2) (C3) (C4) (C5) (C6) (C7) (C8)
--------------------------------------------------------------------------------------------------------------------------------------------------------
HHA1....................................... 38 $100,000 $8,000 $3,040 1.93 $5,867 5.9 % -2.1%
HHA2....................................... 55 145,000 11,600 6,380 1.93 12,313 8.5 0.5
HHA3....................................... 22 800,000 64,000 14,080 1.93 27,174 3.4 -4.6
HHA4....................................... 85 653,222 52,258 44,419 1.93 85,729 13.1 5.1%
HHA5....................................... 50 190,000 15,200 7,600 1.93 14,668 7.7 -0.3%
HHA6....................................... 63 340,000 27,200 17,136 1.93 33,072 9.7 1.7
HHA7....................................... 74 660,000 52,800 39,072 1.93 75,409 11.4 3.4
HHA8....................................... 25 564,000 45,120 11,280 1.93 21,770 3.9 -4.1
------------------------------------------------------------------------------------------------------------
Sum.................................... ......... ............ 276,178 143,007 ............ 276,002 ............ ............
--------------------------------------------------------------------------------------------------------------------------------------------------------
* Example cases.
H. Preview and Period to Request Recalculation
We proposed that Medicare-certified HHAs be provided two separate
opportunities to review scoring information under the HHVBP Model.
First, HHAs will have the opportunity to review their quarterly quality
reports following each quarterly posting; second, competing HHAs will
have the opportunity to review their TPS and payment adjustment
calculations, and request a recalculation if a discrepancy is
identified due to a CMS error as described in this section. These
processes would help educate and inform each competing Medicare-
certified HHA on the direct relation between the payment adjustment and
performance measure scores.
We proposed to inform HHAs quarterly of their performance on each
of the individual quality measures used to calculate the TPS. We
proposed that an HHA would have ten days after the quarterly reports
are provided to request a recalculation of measure scores if it
believes there is evidence of a discrepancy. We stated that we will
adjust the score if it is determined that the discrepancy in the
calculated measure scores was the result of our failure to follow
measurement calculation protocols.
In addition, we proposed to inform each competing HHA of the TPS
and payment adjustment amount in an annual report. We proposed that
these annual reports would be provided to competing HHAs each August
1st prior to the calendar year for which the payment adjustment would
be applied. Similar to quarterly reports, we proposed that HHAs will
have ten days to request a recalculation of their TPS and payment
adjustment amount from the date information is made available. For both
the quarterly reports and the annual report containing the TPS and
payment adjustments, competing HHAs will only be permitted to request
scoring recalculations, and must include a specific basis for the
requested recalculation. We will not be responsible for providing HHAs
with the underlying source data utilized to generate performance
measure scores. Each HHA has access to this data via the QIES system.
The final TPS and payment adjustment will then be provided to competing
Medicare-certified HHAs in a final report no later than 60 days in
advance of the payment adjustment taking effect.
The TPS from the annual performance report will be calculated based
on the calculation of performance measures contained in the quarterly
reports that have already been provided and reviewed by the HHAs. As a
result, we stated in the proposed rule that we believe that quarterly
reviews will provide substantial opportunity to identify and correct
errors and resolve discrepancies, thereby minimizing the challenges to
the annual performance scores linked to payment adjustment.
As described above, a quarterly performance report will be provided
to all competing HHAs within the selected states beginning with the
first quarter of CY 2016 being reported in July 2016. We proposed that
HHAs would submit recalculation requests for both quarterly quality
performance measure reports and for the TPS and payment adjustment
reports via an email link provided on the model-specific Web page. We
proposed that the request form would be entered by a person who has
authority to sign on behalf of the HHA and be submitted within 10 days
of receiving the quarterly data report or the annual TPS and payment
adjustment report.
We proposed that requests for both quarterly report measure score
recalculations or TPS and payment adjustment recalculations would
contain the following information:
The provider's name, address associated with the services
delivered, and CMS Certification Number (CCN);
The basis for requesting recalculation to include the
specific quality measure data that the HHA believes is inaccurate or
the calculation the HHA believes is incorrect;
Contact information for a person at the HHA with whom CMS
or its agent can communicate about this request, including name, email
address, telephone number, and mailing address (must include physical
address, not just a post office box); and,
A copy of any supporting documentation the HHA wishes to
submit in electronic form via the model-specific Web page.
Following receipt of a request for quarterly report measure score
recalculations or a request for TPS and payment adjustment
recalculation, we proposed that CMS or its agent would:
Provide an email acknowledgement, using the contact
information provided in the recalculation request, to the HHA contact
notifying the HHA that the request has been received;
Review the request to determine validity, and determine
whether the requested recalculation results in a score change altering
performance measure scores or the HHA's TPS;
If recalculation results in a performance measure score or
TPS
[[Page 68689]]
change, conduct a review of quality data and if an error is found,
recalculate the TPS using the corrected performance data; and,
Provide a formal response to the HHA contact, using the
contact information provided in the recalculation request, notifying
the HHA of the outcome of the review and recalculation process.
We proposed that recalculation and subsequent communication of the
results of these determinations would occur as soon as administratively
feasible following the submission of requests. Additionally, we stated
that we will develop and adopt an appeals mechanism under the model
through future rulemaking in advance of the application of any payment
adjustments.
The following is a summary of comments we received on the proposed
quarterly quality measure reports and annual TPS preview periods.
Comment: Several commenters suggested that the HHVBP Model provide
30 days, instead of 10 days, after quarterly and annual reports are
provided to request a recalculation of the measure scores if the HHA
believes there is evidence of discrepancy. In addition to allowing more
time to challenge report contents, one commenter recommended another
level of appeal be added with an independent entity to perform the
calculation to determine if the discrepancy is valid.
Response: We agree the review period for performance scores should
be greater than 10 days to allow a more complete opportunity for HHAs
to review, and are extending the time period for HHAs to preview their
quarterly performance reports and annual payment adjustment reports
(with requests for recalculations) from 10 days to 30 days. As noted in
the proposed rule, CMS intends to propose an appeals mechanism in
future rulemaking prior to the application of the first payment
adjustments scheduled for 2018.
Final Decision: For the reasons stated and in consideration of the
comments received, we are finalizing the processes described above with
modification. Specifically, under our final policy, the recalculation
request form must be submitted within 30 days, rather than 10 days, of
posting the quarterly data report or the annual TPS and payment
adjustment reports on the model-specific Web site. We are not making
any other changes to the proposed policies as described in this
section.
I. Evaluation
We proposed, and are finalizing in this rule, to codify at Sec.
484.315(c) that competing HHAs in selected states will be required to
collect and report information to CMS necessary for the purposes of
monitoring and evaluating this model as required by statute.\54\ An
evaluation of the HHVBP Model will be conducted in accordance with
section 1115A(b)(4) of the Act, which requires the Secretary to
evaluate each model tested by CMMI. We consider an independent
evaluation of the model to be necessary to understand its impacts on
care quality in the home health setting. The evaluation will be focused
primarily on understanding how successful the model is in achieving
quality improvement as evidenced by HHAs' performance on clinical care
process measures, clinical outcome measures (for example, functional
status), utilization/outcome measures (for example, hospital
readmission rates, emergency room visits), access to care, and
patient's experience of care, and Medicare costs. We also intend to
examine the likelihood of unintended consequences. We intend to select
an independent evaluation contractor to perform this evaluation. The
procurement for the selection of the evaluation contractor is in
progress, thus we cannot provide a detailed description of the
evaluation methodology here.
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\54\ See section 1115A(b)(4) of the Act (42 U.S.C. 1315a).
---------------------------------------------------------------------------
We intend to use a multilevel approach to evaluation. Here, we
intend to conduct analyses at the state, HHA, and patient levels. Based
on the state groupings discussed in the section on selection of
competing HHAs, we believe there are several ways in which we can draw
comparison groups and remain open to scientifically-sound, rigorous
methods for evaluating the effect of the model intervention.
The evaluation effort may require of HHAs participating in the
model additional data specifically for evaluation purposes. Such
requirements for additional data to carry out model evaluation will be
in compliance with 42 CFR 403.1105 which, as of January 1, 2015,
requires entities participating in the testing of a model under section
1115A to collect and report such information, including protected
health information (as defined at 45 CFR 160.103), as the Secretary
determines is necessary to monitor and evaluate the model. We will
consider all Medicare-certified HHAs providing services within a state
selected for the model to be participating in the testing of this model
because the competing HHAs will be receiving payment from CMS under the
model.\55\
---------------------------------------------------------------------------
\55\ 79 FR 67751 through 67755.
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We invited comments on the proposed evaluation plan.
Comment: Several commenters highlighted the importance of closely
monitoring and evaluating Medicare beneficiary access to home
healthcare to ensure the model does not inadvertently negatively impact
beneficiary access to necessary and appropriate care. In addition, some
commenters suggested the model may cause some HHAs in selected states
to leave the market, thereby creating insufficient HHA supply. Other
commenters specifically raised the concern that some HHAs may attempt
to avoid treating beneficiaries they fear will have a negative impact
on performance scores. These commenters suggest that CMS monitor
whether Medicare beneficiaries experience problems with access to care,
and if they do, immediately address issues to ensure beneficiaries
receive needed services. One commenter specifically suggests surveying
Medicare beneficiaries to help measure access and ensure proactive
monitoring.
Response: Beneficiary access to care is of paramount concern to us,
and as indicated in the proposed rule, we will observe the progress of
the model to guard against unintended consequences. Our monitoring and
evaluation designs will be able to detect the types of concerns
mentioned above. Adjustments to the monitoring and evaluation plans
will be made as needed. As part of the development of this model, we
have identified counties with low HHA market penetration, high dually-
eligible populations, proportions of beneficiaries with high levels of
acuity (as measured by hierarchical condition categories or HCCs), and
organizational types. Future monitoring activities will include a
continuous review of beneficiary-level claims data, Medicare cost
reports, and beneficiary enrollment data to understand whether any
unintended consequences arise across all competing HHAs in the Model.
Comment: Several commenters suggested that CMS employ a process to
continuously monitor quality improvement and evaluate other aspects of
the model in conjunction with all stakeholders, including home health
agencies. Commenters also recommended sharing lessons learned from the
model to inform, educate and engage beneficiaries and the general
public of lessons learned. Several commenters specifically recommended
that CMS establish a HHVBP learning
[[Page 68690]]
network to foster smoother post-pilot implementation of VBP in home
health.
Response: We agree that wherever possible, competing HHAs should
have every opportunity to share lessons learned from the model. We
appreciate all suggestions related to learning from the HHVBP Model,
both for competing HHAs and the public. The model contains multiple
mechanisms for sharing information, including the use of a model-
specific Web site, a collaboration Web site, and model-specific
technical assistance efforts.
Comment: Several commenters specifically requested subsequent
revisions to the HHVBP Model following initial evaluation in order to
ensure that payment reflects a broad range of patients and does not
incentivize under or over provision of services. These commenters
recommended independent evaluation that includes state specific data on
changes in home health quality outcomes, changes in home health
utilization and access to home health for patients with specific
diagnosis and functional status, with breakdowns by geographic location
of patients (for example, rural, urban).
Response: We appreciate the recommendations provided. An
independent evaluation is planned. As discussed in the proposed rule,
we intend to use a multilevel approach to evaluation. We intend to
conduct analyses at the state, HHA, and patient levels. The evaluation
will be conducted in accordance with section 1115A(b)(4) of the Act and
will include analysis of quality improvement as evidenced by HHAs'
performance on clinical care process measures, clinical outcome
measures (for example, functional status), utilization/outcome measures
(for example, hospital readmission rates, emergency room visits),
access to care, and patient's experience of care, and changes in
Medicare costs. We also intend to examine the likelihood of unintended
consequences. The evaluation will use a scientifically rigorous
approach for evaluating the model intervention and making necessary
alterations to the model as needed.
Final Decision: For these reasons and in consideration of the
comments received, we are finalizing the evaluation plan as proposed.
V. Provisions of the Home Health Care Quality Reporting Program (HHQRP)
and Response to Comments
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 for a particular year,
the 2 percentage point reduction under section 1895(b)(3)(B)(v)(I) of
the Act may result in this percentage increase, after application of
the productivity adjustment under section 1895(b)(3)(B)(vi)(I) of the
Act, 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.
Section 2(a) of the Improving Medicare Post-Acute Care
Transformation Act of 2014 (the IMPACT Act) (Pub. L. 113-185, enacted
on Oct. 6, 2014) amended Title XVIII of the Act, in part, by adding a
new section 1899B, which imposes new data reporting requirements for
certain post-acute care (PAC) providers, including HHAs. New section
1899B of the Act is titled, ``Standardized Post-Acute Care (PAC)
Assessment Data for Quality, Payment, and Discharge Planning''. Under
section 1899B(a)(1) of the Act, certain post-acute care (PAC) providers
(defined in section 1899B(a)(2)(A) of the Act to include HHAs, SNFs,
IRFs, and LTCHs) must submit standardized patient assessment data in
accordance with section 1899B(b) of the Act, data on quality measures
required under section 1899B(c)(1) of the Act, and data on resource
use, and other measures required under section 1899B(d)(1) of the Act.
The Act also sets out specified application dates for each of the
measures. The Secretary must specify the quality, resource use, and
other measures no later than the applicable specified application date
defined in section 1899B(a)(2)(E) of the Act.
Section 1899B(b) of the Act describes the standardized patient
assessment data that PAC providers are required to submit in accordance
with section 1899B(b)(1) of the Act; requires the Secretary, to the
extent practicable, to match claims data with standardized patient
assessment data in accordance with section 1899B(b)(2) of the Act; and
requires the Secretary, as soon as practicable, to revise or replace
existing patient assessment data to the extent that such data duplicate
or overlap with standardized patient assessment data, in accordance
with section 1899B(b)(3) of the Act.
Sections 1899B(c)(1) and (d)(1) of the Act direct the Secretary to
specify measures that relate to at least five stated quality domains
and three stated resource use and other measure domains. Section
1899B(c)(1) of the Act provides that the quality measures on which PAC
providers, including HHAs, are required to submit standardized patient
assessment data and other necessary data specified by the Secretary
must be in accordance with, at least, the following domains:
Functional status, cognitive function, and changes in
function and cognitive function;
Skin integrity and changes in skin integrity;
Medication reconciliation;
Incidence of major falls; and
Accurately communicating the existence of and providing
for the transfer of health information and care preferences of an
individual to the individual, family caregiver of the individual, and
providers of services furnishing items and services to the individual
when the individual transitions (1) from a hospital or Critical Access
Hospital (CAH) to another applicable setting, including a PAC provider
or the home of the individual, or (2) from a PAC provider to another
applicable setting, including a different PAC provider, hospital, CAH,
or the home of the individual.
Section 1899B(c)(2)(A) provides that, to the extent possible, the
Secretary must require such reporting through the use of a PAC
assessment instrument and modify the instrument as necessary to enable
such use.
Section 1899B(d)(1) of the Act provides that the resource use and
other measures on which PAC providers, including HHAs, are required to
submit any necessary data specified by the Secretary, which may include
standardized assessment data in addition to claims data, must be in
accordance with, at least, the following domains:
Resource use measures, including total estimated Medicare
spending per beneficiary;
Discharge to community; and
Measures to reflect all-condition risk-adjusted
potentially preventable hospital readmission rates.
Sections 1899B(c) and (d) of the Act indicate that data satisfying
the eight measure domains in the IMPACT Act is the minimum data
reporting requirement. The Secretary may specify additional measures
and additional domains.
[[Page 68691]]
Section 1899B(e)(1) of the Act requires that the Secretary
implement the quality, resource use, and other measures required under
sections 1899B(c)(1) and (d)(1) of the Act in phases consisting of
measure specification, data collection, and data analysis; the
provision of feedback reports to PAC providers in accordance with
section 1899B(f) of the Act; and public reporting of PAC providers'
performance on such measures in accordance with section 1899B(g) of the
Act. Section 1899B(e)(2) of the Act generally requires that each
measure specified by the Secretary under section 1899B of the Act be
National Quality Forum (NQF)-endorsed, but authorizes an exception
under which the Secretary may select non-NQF-endorsed quality measures
in the case of specified areas or medical topics determined appropriate
by the Secretary for which a feasible or practical measure has not been
endorsed by the NQF, as long as due consideration is given to measures
that have been endorsed or adopted by a consensus organization
identified by the Secretary. Section 1899B(e)(3) of the Act provides
that the pre-rulemaking process required by section 1890A of the Act
applies to quality, resource use, and other measures specified under
sections 1899B(c)(1) and (d)(1) of the Act, but authorizes exceptions
under which the Secretary may (1) use expedited procedures, such as ad
hoc reviews, as necessary in the case of a measure required for data
submissions during the 1-year period before the applicable specified
application date, or (2) alternatively, waive section 1890A of the Act
in the case of such a measure if applying section 1890A of the Act
(including through the use of expedited procedures) would result in the
inability of the Secretary to satisfy any deadline specified under
section 1899B of the Act for the measure.
Section 1899B(f)(1) of the Act requires the Secretary to provide
confidential feedback reports to PAC providers on the performance of
such PAC providers for quality, resource use, and other measures
required under sections 1899B(c)(1) and (d)(1) of the Act beginning 1
year after the applicable specified application date.
Section 1899B(g) of the Act requires the Secretary to establish
procedures for making available to the public information regarding the
performance of individual PAC providers for quality, resource use, and
other measures required under sections 1899B(c)(1) and (d)(1) beginning
not later than 2 years after the applicable specified application date.
The procedures must ensure, including through a process consistent with
the process applied under section 1886(b)(3)(B)(viii)(VII) for similar
purposes, that each PAC provider has the opportunity to review and
submit corrections to the data and information that are to be made
public for the PAC provider prior to such data being made public.
Section 1899B(h) of the Act sets out requirements for removing,
suspending, or adding quality, resource use, and other measures
required under sections 1899B(c)(1) and (d)(1) of the Act. In addition,
section 1899B(j) of the Act requires the Secretary to allow for
stakeholder input, such as through town halls, open door forums, and
mailbox submissions, before the initial rulemaking process to implement
section 1899B of the Act.
Section 2(c)(1) of the IMPACT Act amended section 1895 of the Act
to address the payment consequences for HHAs for the additional data
which HHAs are required to submit under section 1899B of the Act. These
changes include the addition of a new section 1895(b)(3)(B)(v)(IV),
which requires HHAs to submit the following additional data: (1) For
the year beginning on the specified application date and each
subsequent year, data on the quality, resource use, and other measures
required under sections 1899B(c)(1) and (d)(1) of the Act; and (2) for
2019 and subsequent years, the standardized patient assessment data
required under section 1899B(b)(1) of the Act. Such data must be
submitted in the form and manner, and at the time, specified by the
Secretary.
As noted, the IMPACT Act adds a new section 1899B of the Act that
imposes new data reporting requirements for certain post-acute care
(PAC) providers, including HHAs. Sections 1899B(c)(1) and 1899B(d)(1)
of the Act collectively require that the Secretary specify quality
measures and resource use and other measures with respect to certain
domains not later than the specified application date that applies to
each measure domain and PAC provider setting. Section 1899B(a)(2)(E) of
the Act delineates the specified application dates for each measure
domain and PAC provider. The IMPACT Act also amends other sections of
the Act, including section 1895(b)(3)(B)(v), to require the Secretary
to reduce the otherwise applicable PPS payment to a PAC provider that
does not report the new data in a form and manner, and at a time,
specified by the Secretary. For HHAs, amended section 1895(b)(3)(B)(v)
of the Act will require the Secretary to reduce the payment update for
any HHA that does not satisfactorily submit the newly required data.
Under the current HH QRP, the general timeline and sequencing of
measure implementation occurs as follows: Specification of measures;
proposal and finalization of measures through notice-and-comment
rulemaking; HHA submission of data on the adopted measures; analysis
and processing of the submitted data; notification to HHAs regarding
their quality reporting compliance for a particular year; consideration
of any reconsideration requests; and imposition of a payment reduction
in a particular year for failure to satisfactorily submit data for that
year. Any payment reductions that are taken for a year begin
approximately 1 year after the end of the data submission period for
that year and approximately 2 years after we first adopt the measure.
To the extent that the IMPACT Act could be interpreted to shorten
this timeline, so as to require us to reduce HH PPS payment for failure
to satisfactorily submit data on a measure specified under section
1899B(c)(1) or (d)(1) of the IMPACT Act beginning with the same year as
the specified application date for that measure, such a timeline would
not be feasible. The current timeline discussed above reflects
operational and other practical constraints, including the time needed
to specify and adopt valid and reliable measures, collect the data, and
determine whether a HHA has complied with our quality reporting
requirements. It also takes into consideration our desire to give HHAs
enough notice of new data reporting obligations so that they are
prepared to timely start reporting data. Therefore, we intend to follow
the same timing and sequence of events for measures specified under
sections 1899B(c)(1) and (d)(1) of the Act that we currently follow for
other measures specified under the HH QRP. We intend to specify each of
these measures no later than the specified application dates set forth
in section 1899B(a)(2)(E) of the Act and will adopt them consistent
with the requirements in the Act and Administrative Procedure Act. To
the extent that we finalize a proposal to adopt a measure for the HH
QRP that satisfies an IMPACT Act measure domain, we intend to require
HHAs to report data on the measure for the year that begins 2 years
after the specified application date for that measure. Likewise, we
intend to require HHAs to begin reporting any other data specifically
required under the IMPACT Act for the year that begins 2 years after we
adopt requirements that
[[Page 68692]]
would govern the submission of that data.
Lastly, on April 1, 2014, the Congress passed the Protecting Access
to Medicare Act of 2014 (PAMA) (Pub. L. 113-93), which stated the
Secretary may not adopt ICD-10 prior to October 1, 2015. On August 4,
2014, HHS published a final rule titled ``Administrative
Simplification: Change to the Compliance Date for the International
Classification of Diseases, 10th Revision (ICD-10-CM and ICD-10-PCS
Medical Data Code Sets'' (79 FR 45128), which announced October 1, 2015
as the new compliance date. The OASIS-C1 data item set had been
previously approved by the Office of Management and Budget (OMB) on
February 6, 2014 and scheduled for implementation on October 1, 2014.
We intended to use the OASIS-C1 to coincide with the original
implementation date of the ICD-10. The approved OASIS-C1 included
changes to accommodate coding of diagnoses using the ICD-10-CM coding
set and other important stakeholder concerns such as updating clinical
concepts, and revised item wording and response categories to improve
item clarity. This version included five (5) data items that required
the use of ICD-10 codes.
Since OASIS-C1 was revised to incorporate ICD-10 coding, it was not
feasible to implement the OASIS-C1/ICD-10 version prior to October 1,
2015, when ICD-10 was scheduled to be implemented. Due to this delay,
we had to ensure the collection and submission of OASIS data continued,
until ICD-10 was implemented. Therefore, we made interim changes to the
OASIS-C1 data item set to allow use with ICD-9 until ICD-10 was
adopted. The OASIS-C1/ICD-9 version was submitted to OMB for approval
until the OASIS-C1/ICD-10 version could be implemented. A 6-month
emergency approval was granted on October 7, 2014 and CMS subsequently
applied for an extension. The extension of the OASIS-C1/ICD-9 version
was reapproved under OMB control number 0938-0760 with a current
expiration date of March 31, 2018. It is important to note, that this
version of the OASIS will be discontinued once the OASIS-C1/ICD-10
version is approved and implemented. In addition, to facilitate the
reporting of OASIS data as it relates to the implementation of ICD-10
on October 1, 2015, we submitted a new request for approval to OMB for
the OASIS-C1/ICD-10 version under the Paperwork Reduction Act (PRA)
process. We requested a new OMB control number for the proposed revised
OASIS item as announced in the 30-day Federal Register notice (80 FR
15796). The new information collection request for OASIS-C1/ICD-10
version was approved under OMB control number 0938-1279 with a current
expiration date of May 31, 2018. Information regarding the OASIS-C1 can
be located on the OASIS C-1 Data Sets Web page at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/OASIS-C1.html. Additional information regarding
the adoption of ICD-10 can be located on the ICD-10 Web page at: https://www.cms.gov/Medicare/Coding/ICD10/?redirect=/icd10.
We received multiple public comments pertaining to the general
timeline and plan for implementation of the IMPACT Act, sequencing of
measure implementation, and standardization of PAC assessment tools.
The following is a summary of the comments we received on this topic
and our responses.
Comment: We received several comments requesting the development of
a comprehensive implementation plan for all settings covered by the
IMPACT Act. Commenters stated that a comprehensive implementation plan
would give home health providers an opportunity to plan for the
potential impact on their operations, and enable all stakeholders to
understand CMS's approach to implementing the IMPACT Act across care
settings. Some commenters requested that CMS plans be communicated as
soon as possible and that CMS develop setting-specific communications
to facilitate understanding of the IMPACT Act requirements. Another
commenter urged CMS to provide clear and transparent explanations of
each measure's specifications, providing as much information as
possible to the public about the measures proposed. This commenter
added that the detailed information submitted for NQF consensus
development process would be helpful to stakeholders, and offered to
work with CMS on measure development and specifications. One commenter
specifically expressed the importance of a transparent process in
relation to measure development, noting that the Act calls for
informing the public of the measure's numerator, denominator,
exclusions, and any other aspects the Secretary determines necessary.
Another commenter requested that CMS abide by certain principles such
as: Provide implementation timelines for data collection and reporting
requirements in a timely manner; implement measures that are reliable,
feasible and setting appropriate that are endorsed as well as included
in the pre-rulemaking Measure Applications Partnership (MAP) process;
minimize unnecessary provider burden; and finally that CMS ensure the
standardization of measures and data collection across post-acute care
settings as feasible.
Response: We appreciate and agree with the commenters' requests for
a comprehensive and transparent plan for implementation of the IMPACT
Act, as well as the need for timely stakeholder input, the development
of reliable, accurate measures that are endorsed and have undergone the
pre-rulemaking MAP process, clarity on the level of standardization of
items and measures, the importance of feasibility and standardization,
and the avoidance of unnecessary burden on PAC providers. Our intent
has been to comply with these principles in the implementation and
rollout of QRPs in the various care settings, and we will continue to
adhere to these principles as the agency moves forward with
implementing IMPACT Act requirements.
In addition to implementing the IMPACT Act requirements, we will
follow the strategy for identifying cross-cutting measures, timelines
for data collection, and timelines for reporting as outlined in the
IMPACT Act. As described more fully above, the IMPACT Act requires CMS
to specify measures that relate to at least five stated quality domains
and three stated resource use and other measure domains. The IMPACT Act
also outlines timelines for data collection and timelines for
reporting. We intend to adopt measures that comply with the IMPACT Act
in a manner that is consistent with the sequence we follow in other
quality reporting programs. We intend to follow all processes in place
for adoption of measures including the MAP review and the notice and
comment rulemaking process. In the selection and specification of
measures, we employ a transparent process in which we seek input from
stakeholders and national experts and engage in a process that allows
for pre-rulemaking input on each measure, as required by section 1890A
of the Act. This process is based on a private-public partnership, and
it occurs via the MAP. The MAP is composed of multi-stakeholder groups
convened by the NQF, our current contractor under section 1890 of the
Act, to provide input on the selection of quality and efficiency
measures described in section 1890(b)(7)(B). The NQF must convene these
stakeholders and provide us with the stakeholders' input on the
selection of such measures. We, in turn, must take this input into
consideration in selecting such
[[Page 68693]]
measures. In addition, the Secretary must make available to the public
by December 1 of each year a list of such measures that the Secretary
is considering under Title XVIII of the Act. Additionally, proposed
measures and specifications are to be announced through the Notice of
Proposed Rulemaking (NPRM) process in which proposed rules are
published in the Federal Register and are available for public view and
comment.
We further note that we are committed to the principles surrounding
public input as part of its measure development that occurs prior to
rule making. As part of this measure development process, we seek input
from the public on the measure specifications under development by CMS
and our measure contractors. We have a designated Web page where we
solicit public comment on measure constructs during measure
development. This is a key component to how we develop and maintain
quality measures, as outlined in the CMS Blueprint for Measures
Management System. You can find more information about the CMS
Blueprint for Measures Management System on the CMS Measure Management
System Web page at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/. The CMS Quality Measures
Public Comment page is located at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/CallforPublicComment.html.
Comment: Several commenters requested that CMS continue in its
public engagement with stakeholders. They stated their appreciation for
the opportunity to work with CMS during the implementation phases of
the IMPACT Act. These commenters noted a need for more opportunities
for stakeholder input into various aspects of the measure and
assessment instrument development process. Commenters requested
opportunities to provide ongoing input into measure and assessment
instrument development and modifications.
Response: We appreciate the commenters' feedback and the continued
involvement of stakeholders in all phases of measure development and
implementation, as we see the value in strong public-private
partnerships. We also believe that ongoing stakeholder input is
important to the success of the IMPACT Act and look forward to
continued and regular input from the provider communities as we
continue to implement the IMPACT Act. It is our intent to move forward
with IMPACT Act implementation in a manner in which the measure and
assessment instrument development process continues to be transparent,
and includes input and collaboration from experts, the PAC provider
community, and the public. It is of the utmost importance to CMS to
continue to engage stakeholders, including patients and their families,
throughout the measure and assessment instrument development lifecycle
through our measure development public comment periods, the pre-
rulemaking activities, participation in the Technical Expert Panels
(TEPs) convened by our measure development contractors, as well as open
door forums, and other opportunities. We have already provided multiple
opportunities for stakeholder input, including the following
activities: Our measure development contractor(s) convened TEPs for
many of the measures in development under the IMPACT Act such as the
functional assessment TEP, Discharge to Community TEP, Potentially
Preventable Readmissions TEP, and the Drug Regimen Review TEP. We
intend to continue this form of stakeholder engagement with future TEPs
that will assess data standardization and Medicare Spending per
Beneficiary measure concepts, among other topics. We also convened two
separate listening sessions on February 10, 2015 and March 24, 2015 in
order to receive stakeholder input on IMPACT Act implementation. In
addition, we heard stakeholder input during the February 9, 2015 ad hoc
MAP meeting provided for the sole purpose of reviewing the measures
proposed in response to the IMPACT Act. We also implemented a public
mail box for the submission of comments in January 2015,
PACQualityInitiative@cms.hhs.gov, which is listed on our IMPACT Act of
2014 & Cross-Setting Measures Web site at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014-and-Cross-Setting-Measures.html,
and we held a Special Open Door Forum to seek input on the measures on
February 25, 2015. The slides from the Special Open Door Forum are
available https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014-and-Cross-Setting-Measures.html.
Comment: We received several comments requesting that CMS ensure
that the data used to satisfy the IMPACT Act measure domains be aligned
across PAC settings to maximize the reliability and validity of such
data and to enable data comparability. Commenters noted the importance
of standardized patient assessment data for cross-setting comparisons
of patient outcomes. Another commenter expressed concern about the
level of standardization of data collection instruments across PAC
settings, specifically the importance of assessment item alignment for
items selected for use in the various PAC settings, and urged CMS to
consider such data alignment issues. One commenter recommended CMS move
as quickly as possible to collect interoperable and standardized data,
and one commenter recommended that CMS conduct testing to evaluate
comparability across settings. One commenter expressed concern related
to the inconsistencies in the measures proposed, suggesting that there
was significant variance in relation to their numerator, denominator
and exclusions.
We received a few comments requesting details pertaining to the
timing of the development and implementation of the standardized
patient assessment data, measures, data collection, and reporting.
Commenters requested a detailed timeline and schedule that specifies
planned changes to standardize assessment data, including dates and
sequencing of changes. Specifically, one commenter stated that although
the sequencing for the quality measures and specified application dates
were provided in the proposed rule, the detail related to the timing of
the standardized data appeared to have been left out. The commenter
requested that this final rule provide such timeline and sequencing.
Response: We agree that standardization is important for data
comparability and outcome analysis. We will work to ensure that items
pertaining to measures required under the IMPACT Act that are included
in assessment instruments are standardized and aligned across the
assessment instruments. In addition, we will ensure that the data used
to satisfy the IMPACT Act measure domains will be aligned across PAC
settings to maximize the reliability and validity of such data and to
enable data comparability. We recognize the need for transparency as we
move forward to implement the IMPACT Act and we intend to continue to
engage stakeholders and ensure that our approach to implementation and
timing is communicated in an open and informative manner. We will
continue this communication through various means, such as open door
forums, national provider calls, email blasts, and announcements. We
intend to provide
[[Page 68694]]
ongoing information pertaining to the implementation and development of
standardized patient assessment data, measures, data collection, and
reporting to the public. We will also continue to provide information
about development and implementation of the IMPACT Act on the IMPACT
Act of 2014 & Cross-Setting Measures Web page at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014-and-Cross-Setting-Measures.html. In addition to the Web site updates and provider calls,
we intend to provide information about development and implementation
through pre-rulemaking activities surrounding the development of
quality measures, which includes public input as part of our process.
We intend to engage stakeholders and experts in developing the
assessment instrument modifications necessary to meet data
standardization requirements of the IMPACT Act. We also will use the
rulemaking process to communicate timelines for implementation,
including timelines for the replacement of items in PAC assessment
tools, timelines for implementation of new or revised quality measures,
and timelines for public reporting.
Regarding the timeline and sequencing surrounding the standardized
patient assessment data, we interpret the commenters' concern to refer
to the standardized data assessment domains listed within the Act under
section 2(b) ``Standardized patient assessment data''. As stated in the
preamble to the CY 2016 HH PPS proposed rule, we intend to require HHAs
to begin reporting data on the quality measures required under the
IMPACT Act for the year that begins 2 years after we adopt requirements
that govern the submission of that data.
Comment: We received a few comments supporting and encouraging the
use of NQF-endorsed measures and recommending that measures be NQF-
endorsed prior to implementation. Specifically, commenters urged CMS to
seek and receive NQF endorsement for measures in each PAC setting,
noting that quality measure endorsement in one setting, such as a
skilled nursing facility, may not mean a measure is appropriate,
reliable, or valid for use in the home health setting.
Response: We will propose appropriate measures that meet the
requirements of the IMPACT Act measure domains and that have been
endorsed or adopted by a consensus organization whenever possible.
However, when this is not feasible because there is no NQF-endorsed
measure that meets all the requirements for a specified IMPACT Act
measure domain, we intend to rely on the exception authority given to
the Secretary in section 1899B(e)(2)(B) of the Act. This statutory
exception allows the Secretary to specify a measure for the HH QRP
setting that is not NQF-endorsed where, as here, we have not been able
to identify other measures on the topic that are endorsed or adopted by
a consensus organization. For all quality measures for the HH QRP, we
seek MAP review, as well as expert opinion on the validity and
reliability of those measures in the HH setting. For the proposed
quality measure, the Percent of Residents/Patients/Persons with
Pressure Ulcers That Are New or Worsened, the MAP PAC LTC Off-Cycle
Workgroup conditionally supported the quality measure for HH QRP. We
wish to note that we intend to seek consensus endorsement for the
IMPACT Act measures in each PAC setting.
Comment: We received several comments about the burden on PAC
providers of meeting new requirements imposed as a result of the
implementation of the IMPACT Act. Specifically, commenters requested
that CMS consider minimizing the burden for PAC providers when possible
and avoiding duplication in data collection.
Response: We appreciate the importance of avoiding undue burden and
will continue to evaluate and consider any burden the IMPACT Act and
the HH QRP places on home health providers. In implementing the IMPACT
Act thus far, we have taken into consideration any new burden that our
requirements might place on PAC providers. In this respect, we note
that many assessment items used to calculate the measure proposed for
use in the HH QRP, the Percent of Residents or Patients with Pressure
Ulcers That Are New or Worsened are currently being collected in the
OASIS instrument.
Comment: We received one comment requesting that, in the future,
cross-setting measures and assessment data changes related to the
IMPACT Act be addressed in one stand-alone notice and rule that applies
to all four post-acute care settings.
Response: We will take this request under consideration.
Comment: We received one comment expressing interest in learning
about any proposed changes to the OASIS assessment instrument in the
next version of the item set and when these changes might occur.
Response: We are committed to transparent communication about
updates to the PAC assessment instruments required to support the
IMPACT Act measures, as well as any new measures for the HH QRP. We
wish to clarify that the draft revisions to the integumentary portion
of the OASIS were posted along with the proposed rule on the Home
Health Quality Measures Web page at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html. We intend to make
publically available the final item set with its revisions as well as
the submission specifications in a manner consistent with our previous
postings of such information in the coming months.
Comment: We received one comment expressing concern that data used
in reformulating the payment model and assessing quality in PAC
settings be gathered by qualified clinicians. Specifically, the
commenter emphasized the unique contributions of occupational
therapists to support the intent of the IMPACT Act.
Response: We appreciate the feedback and concur on the important
role played by qualified clinicians in collecting the data needed to
support the requirements of the IMPACT Act.
Comment: One commenter recommended that CMS invest in training
clinicians for any new data collection requirements that address the
quality measures, the assessment items, and how the measures and the
items are developed to meet the mandate of the IMPACT Act objectives.
This commenter additionally noted that the training should address
different settings of care and how patient populations differ across
PAC settings, to support consistency in data collection.
Response: We agree that training is critical to assure both
provider accuracy and understanding of the assessment and data
collection requirements. We intend to provide training on updates to
the OASIS assessment instrument as suggested, and intend to ensure that
such training includes the information necessary to ensure consistent
data collection.
Comment: One commenter underscored cognitive function as an
important aspect of the IMPACT Act, because of its significant
relationship to Medicare resource use, length of stay, and patients'
long term outcomes. The commenter recommended that assessment of
functional cognition be incorporated as part of CMS's efforts to meet
the requirements of the IMPACT Act and added that providers need more
training around appropriate functional activities for patients with
cognitive impairments. This commenter also
[[Page 68695]]
offered to provide research studies and related materials to support
CMS in this area.
Response: We concur on the importance of cognitive function and its
relationship to quality outcomes for PAC patients. We are working
toward developing quality measures that assess areas of cognition,
recognizing that this quality topic is intrinsically linked to the
function domain. We appreciate the commenter's offer of assistance and
encourage the submission of comments and measure specification details
to our comment email PACQualityInitiative@cms.hhs.gov.
Comment: One commenter supported the inclusion of new standardized
self-care and mobility functional items in PAC assessment tools that
utilize the data source of the CARE Tool. The commenter anticipated
that functional measures based on CARE items that are being implemented
in other PAC settings will be eventually added to the HH QRP. This
commenter noted that use of these new items would facilitate accurate
representation of patient function across the spectrum of PAC settings.
Response: We appreciate the commenter's feedback and support of the
self-care and functional items that utilize data elements derived from
the CARE Tool item set source. We believe that standardization of
assessment items and measures, such as measures of functional status,
across post-acute care settings is an important goal.
Comment: One commenter expressed concern regarding harmonization of
measures across settings and outcomes measurement when multiple
populations are included. This commenter urged that proposed IMPACT Act
measures be limited to Medicare FFS beneficiaries, noting that to
include other populations (Medicaid, Medicare Advantage, and MCO
Medicaid) will complicate the interpretation of outcome results. The
commenter expressed support of the construct of the Total Cost per
Beneficiary. The commenter also suggested that a measure such as the
Percent of Patients Discharged to a Higher Level of Care versus
Community, which the commenter suggested could be used across all
patients receiving home care, be included in future measure
development. In addition, the commenter expressed support for measures
related to falls and nutritional assessment, and hospitalizations, but
requested clarification about the population that would be measured and
recommended that all of these measures be limited to Medicare FFS
patients only. The commenter additionally recommended that the
uniqueness of home health care be considered when developing a
standardized falls measure, noting that home health staff are not
present 24 hours a day, seven days a week and are reliant on patients
and caregivers in reporting and preventing falls.
Response: We appreciate the commenter's feedback about comparison
of outcomes across different payer populations and appreciate the
commenter's support for quality measure standardization as mandated by
the IMPACT Act. The cross-setting measures: (1) Payment Standardized
Medicare Spending Per Beneficiary (MSPB), (2) Percentage residents/
patients at discharge assessment, who discharged to a higher level of
care versus to the community, (Application of NQF #2510), (3) Skilled
Nursing Facility 30-Day All-Cause Readmission Measure (SNFRM), and (4)
Application of the LTCH/IRF All-Cause Unplanned Readmission Measure for
30 Days Post Discharge from LTCHs/IRFs are currently under development
for all four PAC settings. These quality measures are being developed
using Medicare claims data, thus the denominators for these measure
constructs are limited to the Medicare FFS population. We intend to
standardize denominator and numerator definitions across PAC settings
in order to standardize quality measures as required by the IMPACT Act.
We acknowledge the unique constraints home health agencies face in
monitoring patient falls. We are in the process of standardizing a
quality measure that assesses one or more falls with a major injury,
rather than just a measure assessing if a fall occurred. In the FY 2016
IPPS/LTCH PPS final rule, FY 2016 IRF PPS final rule and FY 2016 SNF
PPS final rule, we finalized an application of the quality measure, the
Percent of Residents Experiencing One or More Falls with Major Injury
(Long Stay) measure (NQF #0674). This application of the quality
measure assesses falls resulting in major injuries only, satisfying the
domain in the IMPACT Act, the Incidence of Major Falls. A TEP convened
by our measure development contractor provided input on the technical
specifications of the 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, including home health care. 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
cross-setting development. We have taken steps to standardize the
numerator, denominator, and other facets of the quality measure across
all PAC settings. As part of best clinical practice, the HHA should
take steps to mitigate falls with major injury, especially since such
falls are considered to be ``never events'' as they relate to
healthcare acquired conditions.
Finally, we appreciate the commenter's concern that home health
staff are not present 24 hours, 7 days a week and may not be able to
track falls as they occur.
B. General Considerations Used for the Selection of Quality Measures
for the HH QRP
We strive to promote high quality and efficiency in the delivery of
health care to the beneficiaries we serve. Performance improvement
leading to the highest quality health care requires continuous
evaluation to identify and address performance gaps and reduce the
unintended consequences that may arise in treating a large, vulnerable,
and aging population. Quality reporting programs, coupled with public
reporting of quality information, are critical to the advancement of
health care quality improvement efforts.
We seek to adopt measures for the HH QRP that promote better,
safer, and more efficient care. Valid, reliable, relevant quality
measures are fundamental to the effectiveness of our quality reporting
programs. Therefore, selection of quality measures is a priority for
CMS in all of its quality reporting programs.
The measures selected will address the measure domains as specified
in the IMPACT Act and align with the CMS Quality Strategy, which is
framed using the three broad aims of the National Quality Strategy:
Better Care: Improve the overall quality of care by making
healthcare more patient-centered, reliable, accessible, and safe.
Healthy People, Healthy Communities: Improve the health of
the U.S. population by supporting proven interventions to address
behavioral, social, and environmental determinants of health in
addition to delivering higher-quality care.
Affordable Care: Reduce the cost of quality healthcare for
individuals, families, employers, and government.
In addition, our measure selection activities for the HH QRP take
into consideration input we receive from the MAP. Input from the MAP is
located on the MAP PAC LTC Programmatic Deliverable--Final Report Web
page at:
[[Page 68696]]
https://www.qualityforum.org/Publications/2015/02/MAP_PAC-LTC_Programmatic_Deliverable_-_Final_Report.aspx. We also take into
account national priorities, such as those established by the National
Priorities Partnership at https://www.qualityforum.org/npp/, and the HHS
Strategic Plan at: https://www.hhs.gov/secretary/about/priorities/priorities.html.
We initiated an Ad Hoc MAP process for the review of the measures
under consideration for implementation in preparation of the measures
for adoption into the HH QRP that we proposed through this fiscal
year's rule, in order to begin implementing such measures by 2017. We
included under the List of Measures under Consideration (MUC List)
measures that the Secretary must make available to the public, as part
of the pre-rulemaking process, as described in section 1890A(a)(2) of
the Act. The MAP Off-Cycle Measures under Consideration for PAC-LTC
Settings can be accessed on the National Quality Forum Web site at:
https://www.qualityforum.org/Publications/2015/03/MAP_Off-Cycle_Deliberations_2015_-_Final_Report.aspx. The NQF MAP met in
February 2015 and provided input to us as required under section
1890A(a)(3) of the Act. The MAP issued a pre-rulemaking report on March
6, 2015 entitled MAP Off-Cycle Deliberations 2015: Measures under
Consideration to Implement Provisions of the IMPACT Act--Final Report,
which is available for download at: https://www.qualityforum.org/Publications/2015/03/MAP_Off-Cycle_Deliberations_2015_-_Final_Report.aspx. The MAP's input for the proposed measure is
discussed in this section.
To meet the first specified application date applicable to HHAs
under section 1899B(a)(2)(E) of the Act, which is January 1, 2017, we
focused on measures that:
Correspond to a measure domain in sections 1899B(c)(1) or
(d)(1) of the Act and are setting-agnostic: For example falls with
major injury and the incidence of pressure ulcers;
Are currently adopted for 1 or more of our PAC quality
reporting programs, are already either NQF-endorsed and in use or
finalized for use, or already previewed by the Measure Applications
Partnership (MAP) with support;
Minimize added burden on HHAs;
Minimize or avoid, to the extent feasible, revisions to
the existing items in assessment tools currently in use (for example,
the OASIS); and
Where possible, avoid duplication of existing assessment
items.
As discussed in section V.A. of this final rule, section 1899B(j)
of the Act requires that we allow for stakeholder input, such as
through town halls, open door forums, and mailbox submissions, before
the initial rulemaking process to implement section 1899B. To meet this
requirement, we provided the following opportunities for stakeholder
input: (1) We convened a Technical Expert Panel (TEP) that included
stakeholder experts and patient representatives on February 3, 2015;
(2) we provided two separate listening sessions on February 10 and
March 24, 2015; (3) we sought public input during the February 2015 ad
hoc MAP process regarding the measures under consideration for IMPACT
Act domains; (4) we sought public comment as part of our measure
maintenance work; and (5) we implemented a public mail box for the
submission of comments in January 2015 located at
PACQualityInitiative@cms.hhs.gov. The CMS public mailbox can be
accessed on our IMPACT Act of 2014 & Cross-Setting Measures Web page
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014-and-Cross-Setting-Measures.html. Lastly, we held a National Stakeholder
Special Open Door Forum to seek input on the measures on February 25,
2015.
In the absence of NQF endorsement on measures for the home health
(HH) setting, or measures that are not fully supported by the MAP for
the HH QRP, we intend to propose for adoption measures that most
closely align with the national priorities discussed above and for
which the MAP supports the measure concept. Further discussion as to
the importance and high-priority status of these measures in the HH
setting is included under each quality measure in this final rule. In
addition, for measures not endorsed by the NQF, we have sought, to the
extent practicable, to adopt measures that have been endorsed or
adopted by a national consensus organization, recommended by multi-
stakeholder organizations, and/or developed with the input of
providers, purchasers/payers, and other stakeholders.
C. HH QRP Quality Measures and Measures Under Consideration for Future
Years
In the CY 2014 HH PPS final rule, (78 FR 72256-72320), we finalized
a proposal to add two claims-based measures to the HH QRP, and stated
that we would begin reporting the data from these measures to HHAs
beginning in CY 2014. These claims based measures are: (1)
Rehospitalization during the first 30 days of HH; and (2) Emergency
Department Use without Hospital Readmission during the first 30 days of
HH. In an effort to align with other updates to Home Health Compare,
including the transition to quarterly provider preview reports, we made
the decision to delay the reporting of data from these measures until
July 2015 (https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQISpotlight.html). Also
in that rule, we finalized our proposal to reduce the number of process
measures reported on the Certification and Survey Provider Enhanced
Reporting (CASPER) reports by eliminating the stratification by episode
length for nine (9) process measures. The removal of these measures
from the CASPER folders occurred in October 2014. The CMS Home Health
Quality Initiative Web site identifies the current HH QRP measures
located on the Quality Measures Web page at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html. In addition, as stated
in the CY 2012 and CY 2013 HH PPS final rules (76 FR 68575 and 77 FR
67093, respectively), we finalized that we will also use measures
derived from Medicare claims data to measure home health quality. This
effort ensures that providers do not have an additional burden of
reporting quality of care measures through a separate mechanism, and
that the costs associated with the development and testing of a new
reporting mechanism are avoided.
(a) We proposed one standardized cross-setting new measure for CY
2016 to meet the requirements of the IMPACT Act. The proposed quality
measure addressing the domain of skin integrity and changes in skin
integrity is the National Quality Forum (NQF)-endorsed measure: Percent
of Residents or Patients with Pressure Ulcers That Are New or Worsened
(Short Stay) (NQF #0678) (https://www.qualityforum.org/QPS/0678).
The IMPACT Act requires the specification of a quality measure to
address skin integrity and changes in skin integrity in the home health
setting by January 1, 2017. We proposed the implementation of quality
measure NQF #0678, Percent of Residents or Patients with Pressure
Ulcers that are New or Worsened (Short Stay) in the HH QRP as a cross-
setting quality measure to meet the requirements of the IMPACT Act for
the CY 2018 payment determination and subsequent years. This measure
reports the percent of patients with Stage 2 through 4 pressure
[[Page 68697]]
ulcers that are new or worsened since the beginning of the episode of
care.
Pressure ulcers are high-volume in post-acute care settings and
high-cost adverse events. According to the 2014 Prevention and
Treatment Guidelines published by the National Pressure Ulcer Advisory
Panel, European Pressure Ulcer Advisory Panel, and Pan Pacific Pressure
Injury Alliance, pressure ulcer care is estimated to cost approximately
$11 billion annually, and between $500 and $70,000 per individual
pressure ulcer.\56\ Pressure ulcers are a serious medical condition
that result in pain, decreased quality of life, and increased mortality
in aging populations.57 58 59 60 Pressure ulcers typically
are the result of prolonged periods of uninterrupted pressure on the
skin, soft tissue, muscle, and bone.61 62 63 Elderly
individuals are prone to a wide range of medical conditions that
increase their risk of developing pressure ulcers. These include
impaired mobility or sensation, malnutrition or undernutrition,
obesity, stroke, diabetes, dementia, cognitive impairments, circulatory
diseases, dehydration, bowel or bladder incontinence, the use of
wheelchairs, the use of medical devices, polypharmacy, and a history of
pressure ulcers or a pressure ulcer at
admission.64 65 66 67 68 69 70 71 72 73 74
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\56\ National Pressure Ulcer Advisory Panel, European Pressure
Ulcer Advisory Panel and Pan Pacific Pressure Injury Alliance.
Prevention and Treatment of Pressure Ulcers: Clinical Practice
Guideline. Emily Haesler (Ed.) Cambridge Media; Osborne Park,
Western Australia; 2014.
\57\ Casey, G. (2013). ``Pressure ulcers reflect quality of
nursing care.'' Nurs N Z 19(10): 20-24.
\58\ Gorzoni, M. L., and S. L. Pires (2011). ``Deaths in nursing
homes.'' Rev Assoc Med Bras 57(3): 327-331.
\59\ Thomas, 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.
\60\ White-Chu, E. F., et al. (2011). ``Pressure ulcers in long-
term care.'' Clin Geriatr Med 27(2): 241-258.
\61\ Bates-Jensen BM. Quality indicators for prevention and
management of pressure ulcers in vulnerable elders. Ann Int Med.
2001;135 (8 Part 2), 744-51.
\62\ Institute for Healthcare Improvement (IHI). Relieve the
pressure and reduce harm. May 21, 2007. Available from https://www.ihi.org/IHI/Topics/PatientSafety/SafetyGeneral/ImprovementStories/FSRelievethePressureandReduceHarm.htm.
\63\ Russo CA, Steiner C, Spector W. Hospitalizations related to
pressure ulcers among adults 18 years and older, 2006 (Healthcare
Cost and Utilization Project Statistical Brief No. 64). December
2008. Available from https://www.hcupus.ahrq.gov/reports/statbriefs/sb64.pdf.
\64\ Agency for Healthcare Research and Quality (AHRQ). Agency
news and notes: pressure ulcers are increasing among hospital
patients. January 2009. Available from https://www.ahrq.gov/research/jan09/0109RA22.htm.=
\65\ Bates-Jensen BM. Quality indicators for prevention and
management of pressure ulcers in vulnerable elders. Ann Int Med.
2001;135 (8 Part 2), 744-51.
\66\ Cai, S., et al. (2013). ``Obesity and pressure ulcers among
nursing home residents.'' Med Care 51(6): 478-486.
\67\ Casey, G. (2013). ``Pressure ulcers reflect quality of
nursing care.'' Nurs N Z 19(10): 20-24.
\68\ Hurd D, Moore T, Radley D, Williams C. Pressure ulcer
prevalence and incidence across post-acute care settings. Home
Health Quality Measures & Data Analysis Project, Report of Findings,
prepared for CMS/OCSQ, Baltimore, MD, under Contract No. 500-2005-
000181 TO 0002. 2010.
\69\ MacLean DS. Preventing & managing pressure sores. Caring
for the Ages. March 2003;4(3):34-7. Available from https://www.amda.com/publications/caring/march2003/policies.cfm.
\70\ Michel, J. M., et al. (2012). ``As of 2012, what are the
key predictive risk factors for pressure ulcers? Developing French
guidelines for clinical practice.'' Ann Phys Rehabil Med 55(7): 454-
465
\71\ National Pressure Ulcer Advisory Panel (NPUAP) Board of
Directors; Cuddigan J, Berlowitz DR, Ayello EA (Eds). Pressure
ulcers in America: prevalence, incidence, and implications for the
future. An executive summary of the National Pressure Ulcer Advisory
Panel Monograph. Adv Skin Wound Care. 2001;14(4):208-15
\72\ Park-Lee E, Caffrey C. Pressure ulcers among nursing home
residents: United States, 2004 (NCHS Data Brief No. 14).
Hyattsville, MD: National Center for Health Statistics, 2009.
Available from https://www.cdc.gov/nchs/data/databriefs/db14.htm.
\73\ Reddy, M. (2011). ``Pressure ulcers.'' Clin Evid (Online)
2011.
\74\ Teno, J. M., et al. (2012). ``Feeding tubes and the
prevention or healing of pressure ulcers.'' Arch Intern Med 172(9):
697-701.
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The IMPACT Act requires the specification of quality measures that
are harmonized across PAC settings. This requirement is consistent with
the NQF Steering Committee report, which stated that to understand the
impact of pressure ulcers across settings, quality measures addressing
prevention, incidence, and prevalence of pressure ulcers must be
harmonized and aligned.\75\ NQF #0678, Percent of Residents or Patients
with Pressure Ulcers That Are New or Worsened (Short Stay) is NQF-
endorsed and has been successfully implemented using a harmonized set
of data elements in IRF, LTCH, and SNF settings. A new item, M1309 was
previously added to the OASIS-C1/ICD-9 version to collect data on new
and worsened pressure ulcers in home health patients to support
harmonization with NQF #0678 and data collection for this item began
January 1, 2015. A new measure, based on this item, was included in the
2014 MUC list and received conditional endorsement from the National
Quality Forum. That measure was harmonized with NQF #0678, but differed
in the consideration of unstageable pressure ulcers. In this rule, we
proposed a HH measure that is fully-standardized with NQF #0678.
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\75\ National Quality Forum. National voluntary consensus
standards for developing a framework for measuring quality for
prevention and management of pressure ulcers. April 2008. Available
from https://www.qualityforum.org/Projects/Pressure_Ulcers.aspx.
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A TEP convened by our measure development contractor provided input
on the technical specifications of this quality measure, including the
feasibility of implementing the measure across PAC settings. The TEP
was supportive of the implementation of this measure across PAC
settings and supported CMS's efforts to standardize this measure for
cross-setting development. Additionally, the NQF MAP met on February 9,
2015 and February 27, 2015 and provided input to CMS. The MAP supported
the use of NQF #0678, Percent of Residents or Patients with Pressure
Ulcers that are New or Worsened (Short Stay) in the HH QRP as a cross-
setting quality measure implemented under the IMPACT Act. More
information about the MAPs recommendations for this measure on the
National Quality Forum Web site at: https://www.qualityforum.org/Publications/2015/02/MAP_PAC-LTC_Programmatic_Deliverable_-_Final_Report.aspx.
We proposed that data for the standardized quality measure would be
collected using the OASIS-C1 with submission through the Quality
Improvement and Evaluation System (QIES) Assessment Submission and
Processing (ASAP) system. HHAs began submitting data for the OASIS
items used to calculate NQF #0678, the Percent of Residents or Patients
with Pressure Ulcers That Are New or Worsened (Short Stay), as part of
the Home Health Quality Initiative to assess the number of new or
worsened pressure ulcers in January 2015. By building on the existing
reporting and submission infrastructure for HHAs, we intend to minimize
the administrative burden related to data collection and submission for
this measure under the HH QRP. For more information on HH reporting
using the QIES ASAP system, refer to OASIS User Manual Web page at:
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIOASISUserManual.html and https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/OASIS/?redirect=/oasis/.
Data collected through the OASIS-C1 would be used to calculate this
quality measure. Data items in the OASIS-C1 include M1308 (Current
Number of Unhealed Pressure Ulcers at Each Stage or Unstageable) and
M1309 (Worsening in Pressure Ulcer Status Since SOC/ROC). Data
collected through the OASIS-C1 would be used for risk adjustment of
this measure. We
[[Page 68698]]
anticipate risk adjustment items will include, but not be limited to
M1850 (Activities of Daily Living Assistance, Transferring), and M1620
(Bowel Incontinence Frequency). OASIS C1 items M1016 (Diagnoses
Requiring Medical or Treatment Change Within past 14 Days), M1020
(Primary Diagnoses) and M1022 (Other Diagnoses) would be used to
identify patients with a diagnosis of peripheral vascular disease,
diabetes, or malnutrition. More information about the OASIS items is
available in the downloads section of the Home Health Quality Measures
Web page at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
The specifications and data items for NQF #0678, the Percent of
Residents or Patients with Pressure Ulcers that are New or Worsened
(Short Stay), are available in the downloads section of the Home Health
Quality Measures Web page at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
As part of our ongoing measure development efforts, we considered a
future update to the numerator of the quality measure NQF #0678,
Percent of Residents or Patients with Pressure Ulcers that are New or
Worsened (Short Stay). This update would hold providers accountable for
the development of unstageable pressure ulcers and suspected deep
tissue injuries (sDTIs). Under this proposed change the numerator of
the quality measure would be updated to include unstageable pressure
ulcers, including sDTIs that are new/developed while the patient is
receiving home health care, as well as Stage 1 or 2 pressure ulcers
that become unstageable due to slough or eschar (indicating progression
to a full thickness [that is, stage 3 or 4] pressure ulcer) after
admission. This would be consistent with the specifications of the
``New and Worsened Pressure Ulcer'' measure for HH patients presented
to the MAP on the 2014 MUC list. We did not propose the implementation
of this change (that is, including sDTIs and unstageable pressure
ulcers in the numerator) in the HH QRP, but solicited public feedback
on this potential area of measure development.
Our measure development contractor convened a cross-setting
pressure ulcer TEP that strongly recommended that CMS hold providers
accountable for the development of new unstageable pressure ulcers and
sDTIs by including these pressure ulcers in the numerator of the
quality measure. Although the TEP acknowledged that unstageable
pressure ulcers and sDTIs cannot and should not be assigned a numeric
stage, panel members recommended that these be included in the
numerator of NQF #0678, the Percent of Residents, or Patients with
Pressure Ulcers That Are New or Worsened (Short Stay), as a new
pressure ulcer if developed during a home health episode. The TEP also
recommended that a Stage 1 or 2 pressure ulcer that becomes unstageable
due to slough or eschar should be considered worsened because the
presence of slough or eschar indicates a full thickness (equivalent to
Stage 3 or 4) wound.76 77 These recommendations were
supported by technical and clinical advisors and the National Pressure
Ulcer Advisory Panel.\78\ Additionally, exploratory data analysis
conducted by our measure development contractor suggested that the
addition of unstageable pressure ulcers, including sDTIs, would
increase the observed incidence of new or worsened pressure ulcers at
the agency level and may improve the ability of the quality measure to
discriminate between poor- and high-performing facilities.
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\76\ Schwartz, 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-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/Development-of-a-Cross-Setting-Quality-Measure-for-Pressure-Ulcers-Information-Gathering-Final-Report.pdf.
\77\ Schwartz, 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/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/Development-of-a-Cross-Setting-Pressure-Ulcer-Quality-Measure-Summary-Report-on-November-15-2013-Technical-Expert-Pa.pdf.
\78\ Schwartz, 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-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/Development-of-a-Cross-Setting-Quality-Measure-for-Pressure-Ulcers-Information-Gathering-Final-Report.pdf.
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In addition, we also considered whether body mass index (BMI)
should be used as a covariate for risk-adjusting NQF #0678 in the home
health setting, as is done in other post-acute care settings. We
invited public feedback to inform our direction to include unstageable
pressure ulcers and sDTIs in the numerator of the quality measure NQF
#0678 Percent of Residents or Patients with Pressure Ulcers that are
New or Worsened (Short Stay), as well as on the possible collection of
height and weight data for risk-adjustment, as part of our future
measure development efforts.
We invited public comment on our proposal to adopt NQF #0678
Percent of Residents or Patients with Pressure Ulcers that are New or
Worsened (Short Stay) for the HH QRP to fulfill the requirements of the
IMPACT Act for CY 2018 HH payment determination and subsequent years.
The following is a summary of the comments received and our responses.
Comment: The majority of commenters supported the addition of the
proposed quality measure, the Percent of Residents or Patients with
Pressure Ulcers That Are New or Worsened (NQF #0678) to the Home Health
Quality Reporting Program. Commenters appreciated that CMS chose a
measure that uses data home health agencies already collect.
Response: We appreciate the commenters' support for implementing
the proposed quality measure, the Percent of Residents or Patients with
Pressure Ulcers That Are New or Worsened (NQF #0678).
Comment: A few commenters raised concerns about the fairness of
using NQF #0678 to compare performance within home health and across
PAC providers. One commenter noted that pressure ulcer improvement is
challenging to measure in limited timeframes and disadvantages
providers serving frailer populations and requested CMS consider risk
adjustment based on sociodemographic, diagnostic, and care coordination
factors. Commenters also recommended that CMS take into account the
discrepancy in the control providers have over patient care in home
health, relative to institutional settings. Another commenter
additionally raised concerns about the reliability of the
implementation of the Wound, Ostomy, and Continence Nurses (WOCN)
Society guidelines used in staging pressure ulcers, and the lack of
information about the status of the wound beyond staging while the
patient is in the care of the provider. In addition, one commenter
recommended that CMS conduct ongoing evaluation of the risk adjustment
methodology for this proposed quality measure.
Response: We appreciate the commenters' concerns about ensuring
fair comparisons within and across PAC settings. We also appreciate
that such comparisons take into account the discrepancy in the control
providers have over patient care in home health,
[[Page 68699]]
relative to institutional settings. We are committed to developing risk
models that take into account differences in patient characteristics,
including chronic conditions and frailty. We believe that as with
provider services within institutional settings, home health agencies
aim to provide high quality care and therefore assess for and put into
place care planning and services that mitigate poor quality outcomes.
However, we will also take into account potential variation that may
exist in relation to home based services as opposed to institutional
services. Therefore, as part of measure maintenance, we intend to
continue to evaluate for risk factors associated with pressure ulcers
including those unique to the individuals receiving home health
services. We intend to provide specific guidance through the OASIS
manual and provider trainings to support clinicians in appropriately
coding the stages of the pressure ulcers. In addition, we plan to
conduct field testing on all the new and revised OASIS items that
support the IMPACT Act measures, to assess inter-rater reliability and
to further refine guidance and training.
This proposed quality measure underwent recent review as part of
its measure maintenance by CMS's measure development contractor. Under
Technical Expert Panel review, which included national experts and
members of a various professional wound organizations such as the
National Pressure Ulcer Advisory Panel (NPUAP), the current staging was
not adjusted. We confirm our commitment to ongoing monitoring and re-
evaluation of the risk models for all applicable outcome measures.
While we appreciate these comments and the importance of the role
that sociodemographic status plays in the care of patients, we continue
to have concerns about holding providers to different standards for the
outcomes of their patients of low sociodemographic status because we do
not want to mask potential disparities or minimize incentives to
improve the outcomes of disadvantaged populations. We routinely monitor
the impact of sociodemographic status on facilities' results on our
measures.
NQF is currently undertaking a 2-year trial period in which new
measures and measures undergoing maintenance review will be assessed to
determine if risk-adjusting for sociodemographic factors is appropriate
for each measure. For 2 years, NQF will conduct a trial of a temporary
policy change that will allow inclusion of sociodemographic factors in
the risk-adjustment approach for some performance measures. At the
conclusion of the trial, NQF will determine whether to make this policy
change permanent. Measure developers must submit information such as
analyses and interpretations as well as performance scores with and
without sociodemographic factors in the risk adjustment model.
Furthermore, the Office of the Assistant Secretary for Planning and
Evaluation (ASPE) is conducting research to examine the impact of
socioeconomic status on quality measures, resource use, and other
measures under the Medicare program as directed by the IMPACT Act. We
will closely examine the findings of these reports and related
Secretarial recommendations and consider how they apply to our quality
programs at such time as they are available.
Comment: A commenter expressed concern that the proposed
implementation of NQF #0678 did not include risk adjustment, just
exclusion of patients who die.
Response: The Percent of Residents or Patients with Pressure Ulcers
That Are New or Worsened (NQF #0678) is risk-adjusted based on an
evaluation of covariates that predict the outcome, including low body
mass, diabetes, arterial and peripheral vascular disease, med mobility
and bowel incompetence. As stated in the CY 2016 HH PPS proposed rule,
a discussion pertaining to risk adjustment for this measure can be
found in the downloads section on the Home Health Quality Measures Web
page at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Comment: One commenter appreciated the revision in the organization
of the pressure ulcer items in section M1308 that makes the section
easier to understand and suggested similar revisions to other items.
The commenter also questioned why data on the number and stage of
pressure ulcers was collected on both M1309 and M1308, noting that this
might confuse clinicians. This commenter suggested deleting M1309 and
making additional revisions to M1308 to capture the number of new or
worsened pressure ulcers since the most recent SOC/ROC, and further
suggested adding M1308 at recertification. Another commenter noted that
OASIS Item M1309 is complex and recommended CMS develop an algorithm to
assist HHAs with completing this item, adding that this complexity may
lead to a wide variation of responses from HHAs and affect data
reliability. This commenter further noted that home health agencies
might be reliant on caregivers and patients to follow instructions
related to pressure ulcer prevention in order to achieve quality
outcomes for pressure ulcers.
Response: We appreciate the commenters' positive feedback on items
M1308, and suggestions related to M1309 in the current OASIS C1 item
set, which we will take into consideration. We wish to clarify that
M1308 would be collected at recertification. We also wish to clarify
that the revised version of M1309 builds upon the current version of
this item in the OASIS instrument and has been adjusted to be
standardized to ensure comparable data capture of these items across
the PAC settings. We appreciate the potential for confusion between the
item sections M1308 and M1309. The items used in the skin assessment
that inform this measure were tested during the development of the
Minimum Data Set version 3.0. The inter-rater reliability and validity
of these items was very strong suggesting that there was little
confusion in the coding of these items by clinicians. We believe that
training is important in assuring accurate assessments and OASIS
coding. Therefore, we plan to issue new guidance on these items, as
part of the update to the OASIS manual, well in advance of their
implementation, and to provide further support through training and
other education materials. We appreciate the unique role of patients
and caregivers in achieving quality health outcomes in the home
setting, where skilled care is intermittent in nature. We believe that
as part of home health services, the provider ensures that adequate
person and family centered education is provided to help in the
avoidance and mitigation of pressure ulcers, or other events. Thus, CMS
currently has implemented several process measures in the HH QRP, which
assess whether care plans and other best practices have been
implemented to help patients achieve the best possible outcomes.
Comment: A commenter noted strong support for assessing and
considering other wounds in addition to pressure ulcers when
determining the clinical and functional status of the patient. This
commenter additionally recommended that CMS expand the list of active
diagnoses that are typically barriers to good outcomes and clarify
whether these are diagnoses or symptomology.
Response: We appreciate the comment supporting assessment and
monitoring all wounds, as well as the recommendation to expand the list
of active diagnoses. We believe that as part of providing quality care,
home health
[[Page 68700]]
agencies assess, care for, document, and ensure surveillance of all
wound types. We will consider this feedback in future refinements of
this proposed quality measure. In addition, we will consider expanding
the items referencing active diagnoses and better clarifying whether
items are referencing new diagnoses or symptomology of a disease.
Comment: Several commenters commented on the collection of a
patient's height and weight in the OASIS, in order to calculate body
mass index (BMI) as a risk adjustor for this proposed quality measure.
CMS received several comments in support of the proposal of this
quality measure. One commenter supported the efforts to standardize
data to improve data accuracy and to help facilitate best practices for
the prevention of pressure ulcers, while assuring appropriate care for
pressure ulcers is given in all settings. The commenter expressed that
there is relevance of low BMI and the incidence of pressure ulcers and
recommended that CMS consider evaluating high BMI as a risk factor for
developing new or worsened pressure ulcers. One commenter believed that
CMS should not use BMI obtained in the home health setting, suggesting
that physician offices and care centers obtain such information. One
commenter did not support the use of BMI as a covariate for the New or
Worsened Pressure Ulcer proposed quality measure without additional
evidence of its relevance in the home care setting.
Several commenters expressed concerns about the situations in which
providers are unable to collect accurate height and weight data in the
home care setting safely, including situations such as, but not limited
to, bedbound patients who are unable to stand on scales or whose self-
reported height may be invalid due to memory deficits. Commenters
additionally cited the lack of appropriate equipment to obtain this
information in the home, including scales and Hoyer lifts for patients
who cannot transfer. An additional commenter recommended that CMS add
an option box to the new OASIS items to allow coding for those patients
who cannot be weighed. Finally, one commenter requested clarification
of ``base weight'' and the expectation for recording a weight that is
measured during the visit versus a weight which could be reported by
the patient when they are weighed in their home or based a recent
healthcare provider appointment or hospitalization.
Response: We appreciate the comments received pertaining to the
relevance of low BMI as a risk factor for developing pressure ulcers,
the inclusion of low BMI in the measure and the suggestion that we
evaluate the inclusion of high BMI as a risk factor for pressure
ulcers. We further appreciate the comments regarding the challenge of
obtaining height and weight data in the home for home health patients.
This information is collected in order to standardize risk adjustment
for measuring the incidence of new and worsened pressure ulcers to
facilitate the comparison of quality data within and across post-acute
care settings for this outcome measure.
Low body mass index, which is derived from a patient's height and
weight, is a known correlate of developing pressure ulcers. We
recognize that there will be instances in which obtaining height and
weight cannot occur, and coding response options will be available in
order to indicate when such data cannot be obtained. We intend to issue
specific guidance through the OASIS manual on obtaining these data,
including a definition of ``base weight''. We will also offer support
through training, Open Door Forums, and other communication mechanisms.
In response to the commenter who suggested that physician offices
and wound care centers obtain information related to height and weight,
we will take this feedback into consideration in our ongoing
maintenance of this proposed quality measure. In the cross-setting
Technical Expert Panel held by our measure contractor, it was advised
that we continue to use BMI, as collected, to indicate low body mass.
We appreciate those comments that suggest enhancements to the measure's
risk adjustment and we will take into consideration revisions to the
measure and risk adjustment model in our ongoing maintenance of the
measure.
Comment: One commenter expressed support for the integration of
unstageable pressure ulcers and sDTIs into the measure, and stressed
the importance of education on the additional options prior to
implementing this change, citing the challenges to correct staging and
the importance of inter-rater reliability across PAC settings.
Response: We appreciate the feedback on future integration of
unstageable pressure ulcers and sDTIs into this measure, and will
consider it when undertaking any revisions. We also appreciate the
commenter's emphasis on the important of education and training as the
OASIS is revised and the quality measures are developed. We
historically have and will continue to provide comprehensive training
each time the assessment items change. In addition to the manual and
training sessions, we will provide training materials through the CMS
webinars, open door forums, and help desk support. As provided
previously, item testing revealed very strong inter-rater reliability.
Additionally, with the measure development and maintenance process, we
will continue to test this proposed measure's reliability and validity
across settings.
Final Action: After consideration of the comments received, we are
finalizing as proposed the adoption of NQF #0678 Percent of Residents
or Patients with Pressure Ulcers that are New or Worsened (Short Stay)
for use in the HH QRP for CY 2018 HH payment determination and
subsequent years.
[[Page 68701]]
Table 19--Future Cross-Setting Measure Constructs Under Consideration To
Meet IMPACT Act Requirements
[Home Health Timeline for Implementation--January 1, 2017]
------------------------------------------------------------------------
------------------------------------------------------------------------
IMPACT Act Domain................. Measures to reflect all-condition
risk-adjusted potentially
preventable hospital readmission
rates.
Measures.......................... Application of (NQF #2510): Skilled
Nursing Facility 30-Day All-Cause
Readmission Measure (SNFRM). CMS is
the steward.
Application of the LTCH/IRF All-
Cause Unplanned Readmission Measure
for 30 Days Post Discharge from
LTCHs/IRFs.
IMPACT Act Domain:................ Resource Use, including total
estimated Medicare spending per
beneficiary.
Measure........................... Payment Standardized Medicare
Spending Per Beneficiary (MSPB).
IMPACT Act Domain................. Discharge to community.
Measure........................... Percentage residents/patients at
discharge assessment, who
discharged to a higher level of
care versus to the community.
IMPACT Act Domain................. Medication Reconciliation.
Measure........................... Percent of patients for whom any
needed medication review actions
were completed.
------------------------------------------------------------------------
We also identified four future, cross-setting measure constructs to
potentially meet requirements of the IMPACT Act domains of: (1) All-
condition risk-adjusted potentially preventable hospital readmission
rates; (2) resource use, including total estimated Medicare spending
per beneficiary; (3) discharge to community; and (4) medication
reconciliation. These are shown in Table 19; we solicited public
feedback to inform future measure development of these constructs as it
relates to meeting the IMPACT Act requirements in these areas. These
measures will be proposed in future rulemaking. The comments we
received on this topic, with our responses, are summarized below.
Comment: One commenter encouraged CMS to include clinical experts
in the development of measures for cognition, expressive and receptive
language, and swallowing stressing that without clinical expertise,
substandard data, barriers to data collection, and risks in improving
patient outcomes could occur. The commenter asked that these suggested
measures be considered as items of function and not exclusively as risk
adjustors. This commenter supported the risk adjustment of all outcome
measures based on key case-mix variables due to the variability of
patients treated in PAC settings.
Response: We intend to incorporate clinical expertise in our
ongoing measure refinement activities to better inform the development
of these quality measures. One way we incorporate this form of clinical
input is through the inclusion of Technical Expert Panels supported by
the quality measurement development contractor. We also encourage
public input on our measure development, and comments may be submitted
to our quality reporting program email
HomeHealthQualityQuestions@cms.hhs.gov
We are working toward developing quality measures that assess areas
of cognition and expression, recognizing that these quality topic
domains are intrinsically linked or associated to the domain of
function and cognitive function. In this measure development, we will
take into consideration the variability of the PAC population and the
appropriate risk-adjustment based on case-mix. In addition, we will
take into consideration the suggestion that these measures operate as
items of function and not exclusively as risk adjustors.
Comment: One commenter requested that CMS consider the CARE-C and
CARE-F items based on the National Outcomes Measurement System (NOMS)
to capture communication, cognition, and swallowing as additional
measures to be adopted in post-acute care settings for future measures.
Response: We appreciate the suggestion that we consider refinements
to functional items such as communication, cognition, and swallowing,
which may provide a more meaningful picture of patients with
impairments in these areas. We will consider these recommendations in
our item, measure, and testing efforts for both measure development as
well as standardized assessment domain development.
Comment: One commenter expressed concern regarding the cross-
setting all-cause potentially preventable hospital readmissions
measure. The commenter suggested that additional research on the
effectiveness of this measure be pursued. The commenter proposed that
the measure include rewards for sustained achievement as well as for
improvement; and that actions outside of the agency's control (for
example, timely physician signatures on orders) be taken into
consideration in the application of the all-cause readmission measure.
In addition, the commenter recommends that CMS consider risk adjustment
to address family-requested hospitalizations and increased risk of
hospitalization due to select diagnoses and comorbidities.
One commenter noted difficulty in providing meaningful comment on
specific measures and measure constructs without further information.
Regarding the measure ``Percent of patients for whom any needed
medication review actions were completed'', the commenter stated it is
unclear from the table how one would determine whether a medication
review action is needed for purposes of the measure. One commenter
stated they need additional time to review more thoroughly, and plans
to provide further feedback in the future.
Finally, one commenter recommended the inclusion of nurse
practitioners in both the development and implementation of care plans
based on quality indicators.
Response: We appreciate the commenters' feedback and suggestions
regarding the cross-setting all-cause potentially preventable hospital
readmissions measure, and will consider them in future revisions. We
intend to risk adjust this outcome measure, based on evaluation of
statistically significant covariates, including diagnoses and co-
morbidities.
We appreciate the comments pertaining to the quality measure, the
percent of patients for whom any needed medication review actions were
completed. As we continue to develop and test this measure construct,
we will make information about the measurement specifications available
through posting specifications on our Web site and public comment
periods. We recognize the need for transparency as we move forward to
implement the IMPACT Act and will continue to engage stakeholders to
ensure that our approach to measure development and implementation is
communicated in an open and informative manner. We
[[Page 68702]]
would like to note that anyone can submit feedback on the measures by
means of our mailbox PACQualityInitiative@cms.hhs.gov.
Finally, we appreciate the important role played by nurse
practitioners in patient health and home care outcomes, and encourage
their participation through the variety of modes of stakeholder
engagement noted above.
We will take all comments into consideration when developing and
modifying assessment items and quality measures.
Table 20--Future Setting-Specific Measure Constructs Under Consideration
------------------------------------------------------------------------
National Quality Strategy Domain Measure Construct
------------------------------------------------------------------------
Safety............................ Falls risk composite process
measure: Percentage of home health
patients who were assessed for
falls risk and whose care plan
reflects the assessment, and which
was implemented appropriately.
Nutrition assessment composite
measure: Percentage of home health
patients who were assessed for
nutrition risk with a validated
tool and whose care plan reflects
the assessment, and which was
implemented appropriately.
Effective Prevention and Treatment Improvement in Dyspnea in Patients
with a Primary Diagnosis of
Congestive Heart Failure (CHF),
Chronic Obstructive Pulmonary
Disease (COPD), and/or Asthma:
Percentage of home health episodes
of care during which a patient with
a primary diagnosis of CHF, asthma
and/or COPD became less short of
breath or dyspneic.
Improvement in Patient-Reported
Interference due to Pain: Percent
of home health patients whose self-
reported level of pain interference
on the Patient-Reported Objective
Measurement Information System
(PROMIS) tool improved.
Improvement in Patient-Reported Pain
Intensity: Percent of home health
patients whose self-reported level
of pain severity on the PROMIS tool
improved.
Improvement in Patient-Reported
Fatigue: Percent of home health
patients whose self-reported level
of fatigue on the PROMIS tool
improved.
Stabilization in 3 or more
Activities of Daily Living (ADLs):
Percent of home health patients
whose functional scores remain the
same between admission and
discharge for at least 3 ADLs.
------------------------------------------------------------------------
(b) We worked with our measure development and maintenance
contractor to identify setting-specific measure concepts for future
implementation in the HH QRP that align with or complement current
measures and new measures to meet domains specified in the IMPACT Act.
In identifying priority areas for future measure enhancement and
development, we took into consideration results of environmental scans
and resulting gap analysis for relevant home health quality measure
constructs, along with input from numerous stakeholders, including the
Measures Application Partnership (MAP), the Medicare Payment Advisory
Commission (MedPAC), Technical Expert Panels, and national priorities,
such as those established by the National Priorities Partnership, the
HHS Strategic Plan, the National Strategy for Quality Improvement in
Healthcare, and the CMS Quality Strategy. Based on input from
stakeholders, CMS identified several high priority concept areas for
future measure development in Table 20.
These measure concepts are under development, and details regarding
measure definitions, data sources, data collection approaches, and
timeline for implementation will be communicated in future rulemaking.
We invited feedback about these seven high priority concept areas for
future measure development. Public comments and our responses to
comments are summarized below.
Comment: Multiple commenters expressed support for the potential
constructs for future development, and especially cited stabilization
in function. One commenter expressed appreciation that the basic
timeline for implementation of future measures is consistent with the
IMPACT Act's requirements.
One commenter recommended four new quality measure constructs
related to family caregivers. These included: Home health agency
documentation of whether the beneficiary has a family caregiver;
whether the care or discharge plan relies on the family caregiver to
provide assistance; whether the family caregiver was provided supports
they need as part of the plan after determining the need for such
supports; and family caregiver experience of care. A few commenters
recommended that CMS ensure new measures provide meaningful information
and minimize burden.
One commenter urged CMS to provide clear and transparent
explanations of measure specifications, and to provide as much
information as possible about the measures proposed. One commenter
recommended CMS only use measures after they have been tested in the
home health setting and proved to have meaningful risk adjustment, as
well as to be person-centered and realistic for patients' disease
state. Two commenters recommended that CMS consider consolidating or
removing measures prior to expanding the current set of measures to
minimize administrative burden. One additionally noted that some
existing measures could prove to be redundant or unnecessary when the
IMPACT Act measures are implemented. A few commenters encouraged CMS to
employ a transparent process for measure development that allows for
multiple avenues for stakeholder input. One commenter welcomed the
opportunity to work with CMS in the development of these measures and
their specifications.
In response to the specific constructs listed in the Notice for
Proposed Rule Making, one commenter said that a nutrition assessment
conducted in the home setting, to support a nutritional assessment
process measure, must comprise data elements that would not be included
in a facility assessment, such as access to, and resources for food
shopping. This commenter additionally recommended that new measures
take into account patient-centered decisions and goals, including
refusal of care, and balance these against provider accountability.
MedPAC expressed concern about the number of quality measures in
the Medicare Program, specifically the number currently used in the HH
QRP. MedPAC suggested that prior to expanding the current set of
measures in the HH QRP, CMS should consider
[[Page 68703]]
whether any of the current measures can be consolidated or removed,
recognizing that some measures are proposed in response to legislation.
MedPAC further suggested that CMS consider whether any of its measures
are unnecessary or redundant for the HH QRP, once the IMPACT Act
measures are implemented.
Response: We appreciate the feedback on potential constructs for
future measure development and concur with the importance of valid and
reliable stabilization measures for home health patients. Additionally,
we agree that caregiver constructs are high priority areas to consider
for future measure development.
With all new measure development, we are committed to assessing the
burden and utility of proposed measures, through Technical Expert
Panels, public comment periods and other opportunities for stakeholder
input. In addition, we are planning to conduct field testing of new and
existing OASIS items to assess their reliability, validity and
relevance in the home health setting. This field testing will inform
new measure development.
We agree with MedPAC, as well as other commenters, regarding the
importance of a modest set of measures for the HH QRP and are re-
evaluating the entire set to determine which measures are candidates
for revision or retirement. CMS's measure contractor has convened a
Technical Expert Panel of providers, caregiver representatives, and
other clinical experts to aid in the re-evaluation process. This
process has included: (1) Analysis of historical measure trends, as
well as reliability, validity and variability; (2) a review of the
scientific basis for the measure construct in the literature and
guidelines; and (3) feedback on the value of the measures to providers
and patients for assessing and improving quality. Ongoing evaluation of
measures used in HH QRP will continue as measures intended to satisfy
the IMPACT Act's specified domains are made operational.
In the current HH QRP outcome measures are risk-adjusted for a wide
array of covariates and these risk models undergo periodic review and
updating. We would extend this practice to new outcome measures as
appropriate.
We recognize the unique circumstances of home health patients, who
have greater control and potentially greater barriers for maintaining
good nutritional status. Additionally, we recognize that home health
patients may make decisions that align with their personal choice but
may be at odds with high quality outcomes.
Comment: One commenter recommended that the OASIS capture
information on cerebral palsy, traumatic brain injury, and cognitive
impairment for long-term home health patients.
Response: We appreciate the commenter's recommendation to capture
information on the OASIS for all individuals with cerebral palsy,
traumatic brain injury, and cognitive impairment and will take these
comments into consideration when developing and modifying assessment
items and quality measures.
D. Form, Manner, and Timing of OASIS Data Submission and OASIS Data for
Annual Payment Update
1. Regulatory Authority
The HH conditions of participation (CoPs) at Sec. 484.55(d)
require that the comprehensive assessment must be updated and revised
(including the administration of the OASIS) no less frequently than:
(1) The last 5 days of every 60 days beginning with the start of care
date, unless there is a beneficiary-elected transfer, significant
change in condition, or discharge and return to the same HHA during the
60-day episode; (2) within 48 hours of the patient's return to the home
from a hospital admission of 24-hours or more for any reason other than
diagnostic tests; and (3) at discharge.
It is important to note that to calculate quality measures from
OASIS data, there must be a complete quality episode, which requires
both a Start of Care (initial assessment) or Resumption of Care OASIS
assessment and a Transfer or Discharge OASIS assessment. Failure to
submit sufficient OASIS assessments to allow calculation of quality
measures, including transfer and discharge assessments, is a failure to
comply with the CoPs.
HHAs do not need to submit OASIS data for those patients who are
excluded from the OASIS submission requirements. As described in the
December 23, 2005 Medicare and Medicaid Programs: Reporting Outcome and
Assessment Information Set Data as Part of the Conditions of
Participation for Home Health Agencies final rule (70 FR 76202), we
defined the exclusion as those patients:
Receiving only non-skilled services;
For whom neither Medicare nor Medicaid is paying for HH
care (patient receiving care under a Medicare or Medicaid Managed Care
Plan are not excluded from the OASIS reporting requirement);
Receiving pre- or post-partum services; or
Under the age of 18 years.
As set forth in the CY 2008 HH PPS final rule (72 FR 49863), HHAs
that become Medicare certified on or after May 31 of the preceding year
are not subject to the OASIS quality reporting requirement nor any
payment penalty for quality reporting purposes for the following year.
For example, HHAs certified on or after May 31, 2014 are not subject to
the 2 percentage point reduction to their market basket update for CY
2015. These exclusions only affect quality reporting requirements and
do not affect the HHA's reporting responsibilities as announced in the
December 23, 2005 final rule.
2. Home Health Quality Reporting Program Requirements for CY 2016
Payment and Subsequent Years
In the CY 2014 HH PPS Final rule (78 FR 72297), we finalized a
proposal to consider OASIS assessments submitted by HHAs to CMS in
compliance with HH CoPs and Conditions for Payment for episodes
beginning on or after July 1, 2012, and before July 1, 2013 as
fulfilling one portion of the quality reporting requirement for CY
2014.
In addition, we finalized a proposal to continue this pattern for
each subsequent year beyond CY 2014. OASIS assessments submitted for
episodes beginning on July 1 of the calendar year 2 years prior to the
calendar year of the Annual Payment Update (APU) effective date and
ending June 30 of the calendar year one year prior to the calendar year
of the APU effective date, fulfill the OASIS portion of the HH QRP
requirement.
3. Previously Established Pay-for-Reporting Performance Requirement for
Submission of OASIS Quality Data
Section 1895(b)(3)(B)(v)(I) of the Act states that for 2007 and
each subsequent year, the home health market basket percentage increase
applicable under such clause for such year shall be reduced by 2
percentage points if a home health agency does not submit data to the
Secretary in accordance with subclause (II) for such a year. This pay-
for-reporting requirement was implemented on January 1, 2007. In the CY
2015 HH PPS Final rule (79 FR 38387), we finalized a proposal to define
the quantity of OASIS assessments each HHA must submit to meet the pay-
for-reporting requirement.
We believe that defining a more explicit performance requirement
for the submission of OASIS data by HHAs would better meet the intent
of the statutory requirement.
In the CY 2015 HH PPS Final rule (79 FR 38387), we reported
information on a study performed by the Department of
[[Page 68704]]
Health & Human Services, Office of the Inspector General (OIG) in
February 2012 to: (1) Determine the extent to which HHAs met federal
reporting requirements for the OASIS data; (2) to determine the extent
to which states met federal reporting requirements for OASIS data; and
(3) to determine the extent to which CMS was overseeing the accuracy
and completeness of OASIS data submitted by HHAs. Based on the OIG
report we proposed a performance requirement for submission of OASIS
quality data, which would be responsive to the recommendations of the
OIG.
In response to these requirements and the OIG report, we designed a
pay-for-reporting performance system model that could accurately
measure the level of an HHA's submission of OASIS data. The performance
system is 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 Start of
Care (SOC) or Resumption of Care (ROC) assessment and a matching End of
Care (EOC) assessment. However, it was determined that there are
several scenarios that could meet this matching assessment requirement
of the new pay-for-reporting performance requirement. These scenarios
or quality assessments are defined as assessments that create a quality
episode of care during the reporting period or could create a quality
episode if the reporting period were expanded to an earlier reporting
period or into the next reporting period.
Seven types of assessments submitted by an HHA fit this definition
of a quality assessment. These are:
1. A Start of Care (SOC; M0100 = `01') or Resumption of Care (ROC;
M0100 = `03') assessment that can be matched to an End of Care (EOC;
M0100 = `06', `07', `08', or `09') assessment. These SOC/ROC
assessments are the first assessment in the pair of assessments that
create a standard quality of care episode describe in the previous
paragraph.
2. An End of Care (EOC) assessment that can be matched to a Start
of Care (SOC) or Resumption of Care (ROC) assessment. These EOC
assessments are the second assessment in the pair of assessments that
create a standard quality of care episode describe in the previous
paragraph.
3. A SOC/ROC assessment that could begin an episode of care, but
the assessment occurs in the last 60 days of the performance period.
This is labeled as a Late SOC/ROC quality assessment. The assumption is
that the EOC assessment will occur in the next reporting period.
4. An EOC assessment that could end an episode of care that began
in the previous reporting period, (that is, an EOC that occurs in the
first 60 days of the performance period). This is labeled as an Early
EOC quality assessment. The assumption is that the matching SOC/ROC
assessment occurred in the previous reporting period.
5. A SOC/ROC assessment that is followed by one or more follow-up
assessments, the last of which occurs in the last 60 days of the
performance period. This is labeled as an SOC/ROC Pseudo Episode
quality assessment.
6. An EOC assessment is preceded by one or more follow-up
assessments, the first of which occurs in the first 60 days of the
performance period. This is labeled an EOC Pseudo Episode quality
assessment.
7. A SOC/ROC assessment that is part of a known one-visit episode.
This is labeled as a One-Visit episode quality assessment. This
determination is made by consulting HH claims data.
SOC, ROC, and EOC assessments that do not meet any of these
definitions are labeled as Non-Quality assessments. Follow-up
assessments (that is, where the M0100 Reason for Assessment = `04' or
`05') are considered Neutral assessments and do not count toward or
against the pay-for-reporting performance requirement.
Compliance with this performance requirement can be measured
through the use of an uncomplicated mathematical formula. This pay-for-
reporting performance requirement metric has been titled as the
``Quality Assessments Only'' (QAO) formula because only those OASIS
assessments that contribute, or could contribute, to creating a quality
episode of care are included in the computation.
The formula based on this definition is as follows:
[GRAPHIC] [TIFF OMITTED] TR05NO15.010
Our ultimate goal is to require all HHAs to achieve a pay-for-
reporting performance requirement compliance rate of 90 percent or
more, as calculated using the QAO metric illustrated above. In the CY
2015 HH PPS final rule (79 FR 66074), we proposed implementing a pay-
for-reporting performance requirement over a 3-year period. After
consideration of the public comments received, we adopted as final our
proposal to establish a pay-for-reporting performance requirement for
assessments submitted on or after July 1, 2015 and before June 30, 2016
with appropriate start of care dates, HHAs must score at least 70
percent on the QAO metric of pay-for-reporting performance requirement
or be subject to a 2 percentage point reduction to their market basket
update for CY 2017.
HHAs have been statutorily required to report OASIS for a number of
years and therefore should have many years of experience with the
collection of OASIS data and transmission of this data to CMS. Given
the length of time that HHAs have been mandated to report OASIS data
and based on preliminary analyses that indicate that the majority of
HHAs are already achieving the target goal of 90 percent on the QAO
metric, we believe that HHAs would adapt quickly to the implementation
of the pay-for-reporting performance requirement, if phased in over a
3-year period.
In the CY 2015 rule, we did not finalize a proposal to increase the
reporting requirement in 10 percent increments over a 2-year period
beginning July 1, 2016 until the maximum rate of 90 percent is reached.
Instead, we proposed to analyze historical data to set the reporting
requirements. To set the threshold for the 2nd year, we analyzed the
most recently available data, from 2013 and 2014, to make a
determination about what the pay-for-reporting performance requirement
should be. Specifically, we reviewed OASIS data from this time period
simulating the pay-for-reporting performance 70 percent submission
requirement to determine the hypothetical performance of each HHA as if
the pay-for-reporting performance requirement were in effect during the
reporting period preceding its implementation. This analysis indicated
a nominal increase of 10 percent each year would provide the greatest
opportunity for successful implementation versus an increase of 20
percent from year 1 to year 2.
[[Page 68705]]
Based on this analysis, we proposed to set the performance
threshold at 80 percent for the reporting period from July 1, 2016
through June 30, 2017. For the reporting period from July 1, 2017
through June 30, 2018 and thereafter, we proposed the performance
threshold would be 90 percent.
We provided a report to each HHA of their hypothetical performance
under the pay-for-reporting performance requirement during the 2014-
2015 pre-implementation reporting period in June 2015. On January 1,
2015, the data submission process for OASIS converted from the current
state-based OASIS submission system to a new national OASIS submission
system known as the Assessment Submission and Processing (ASAP) System.
On July 1, 2015, when the pay-for-reporting performance requirement of
70 percent went into effect, providers were required to submit their
OASIS assessment data into the ASAP system. Successful submission of an
OASIS assessment consist of the submission of the data into the ASAP
system with a receipt of no ``fatal error'' messages. Error messages
received during submission can be an indication of a problem that
occurred during the submission process and could also be an indication
that the OASIS assessment was rejected. Successful submission can be
verified by ascertaining that the submitted assessment data resides in
the national database after the assessment has met all of the quality
standards for completeness and accuracy during the submission process.
Should one or more OASIS assessments submitted by a HHA be rejected due
to an IT/server issue caused by CMS, we may at our discretion, excuse
the non-submission of OASIS data. We anticipate that such a scenario
would rarely, if ever, occur. In the event that a HHA believes that
they were unable to submit OASIS assessments due to an IT/server issue
on the part of CMS, the HHA should be prepared to provide any
documentation or proof available, which could demonstrate that no fault
on their part contributed to the failure of the OASIS records to
transmit to CMS.
The initial performance period for the pay-for-reporting
performance requirement is July 1, 2015 through June 30, 2016. Prior to
and during this performance period, we have scheduled Open Door Forums
and webinars to educate HHA personnel as needed about the pay-for-
reporting performance requirement program and the pay-for- reporting
performance QAO metric, and distributed individual provider preview
reports. Additionally, OASIS Education Coordinators (OECs) have been
trained to provide state-level instruction on this program and metric.
We have posted a report, which provides a detailed explanation of the
methodology for this pay-for-reporting QAO methodology. To view this
report, go to the downloads section at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/Home-Health-Quality-Reporting-Requirements.html.
Training announcements and additional educational information related
to the pay-for-reporting performance requirement have been provided on
the HH Quality Initiatives Web page.
We invited public comment on our proposal to implement an 80
percent Pay-for-Reporting Performance Requirement for Submission of
OASIS Quality Data for Year 2 reporting period July 1, 2016 to June 30,
2017 as described previously, for the HH QRP. Public comments and our
responses to comments are summarized below.
Comment: Several commenters supported CMS' proposed phased-in
approach for the ``Quality Assessments Only'' (QAO) reporting
requirements and the submission of OASIS data; one additionally noted
appreciation for the added clarity about the QAO benchmarks for the
next two assessment periods. A few commenters noted that the proposed
increase to 80 percent for the 2016-2017 was acceptable, but encouraged
CMS to defer subsequent increases, pending evaluation. One of these
commenters additionally requested that CMS provide continuing status
updates on the progress toward these goals so that HHAs could make
changes to their processes in order to be compliant.
Response: We appreciate the feedback and support for the QAO
reporting thresholds and intend to conduct ongoing monitoring of the
effect of increasing the QAO threshold on the percent of agencies that
are compliant with this pay-for-reporting requirement. We do not intend
to defer the increase to 90 percent beyond the schedule included in the
rule; this threshold was chosen based on analysis indicating compliance
was already at this level for the vast majority of agencies. We
designed the pay-for-reporting performance system model in response to
federal reporting requirements for the OASIS data and the
recommendation in the OIG report entitled, ``Limited Oversight of Home
Health Agency OASIS Data,'' that we ``identify all HHAs that failed to
submit OASIS data and apply the 2 percent payment reduction to them''.
As the OASIS reporting requirements have been in existence for 16
years, HHAs should already possess knowledge of these requirements and
know what they need to do to bring their agency into compliance. We
provided a report to each HHA of their hypothetical performance under
the pay-for-reporting performance requirement during the 2014-2015 pre-
implementation reporting period in June 2015; additionally we are
considering options for ongoing communication with agencies about their
compliance levels.
Comment: One commenter requested CMS provide additional
clarification about the definition of ``OASIS submission'' and whether
it required acceptance of the submission by the state agency, as well
as whether the QAO calculation included Medicare Advantage and Medicaid
patients, in addition to traditional Medicare. This commenter
recommended the standard be applied only to assessments completed for
traditional Medicare patients and requested CMS provide comprehensive
education on the new standard at least six months before it is
effective.
Response: On January 1, 2015, the data submission process for OASIS
converted from the former state-based OASIS submission system to a new
national OASIS submission system known as the Assessment Submission and
Processing (ASAP) System. Therefore, the commenter's question about
whether successful submission requires both submission and acceptance
of OASIS data by the state agency is not applicable because the state-
based OASIS submission system is no longer in existence.
Providers are required to submit their OASIS assessment data into
the ASAP system. Successful submission of an OASIS assessment consists
of the submission of the data into the ASAP system with a receipt of no
fatal error messages. Error messages received during submission can be
an indication of a problem that occurred during the submission process
and could also be an indication that the OASIS assessment was rejected.
Successful submission can be verified by ascertaining that the
submitted assessment data resides in the national database after the
assessment has met all of the quality standards for completeness and
accuracy during the submission process.
As noted previously, should one or more OASIS assessments submitted
by a HHA be rejected due to an IT/server issue caused by CMS, we may at
our discretion, excuse the non-submission of OASIS data. We anticipate
that such a scenario would rarely, if ever, occur. In the event that a
HHA believes they were unable to submit OASIS
[[Page 68706]]
assessments due to an IT/server issue on the part of CMS, the HHA
should be prepared to provide any documentation or proof available
which demonstrates no fault on their part contributed to the failure of
the OASIS transmission to CMS.
Patients receiving care under a Medicare or Medicaid managed care
plan are not excluded from the OASIS reporting requirements, and HHAs
are required to submit OASIS assessments for these patients. OASIS
reporting is mandated for all Medicare beneficiaries (under 42 CFR
484.250(a), 484.225(i), and 484.55). The HH CoPs require that the HH
Registered Nurse (RN) or qualified therapist perform an initial
assessment within 48 hours of referral, within 48 hours of the
patient's return home, or on the physician-ordered start of care date.
The HH RN or qualified therapist must also complete a comprehensive
assessment within 5 days from the start of care. During these
assessments, the HH RN or qualified therapist must determine the
patient's eligibility for the Medicare HH benefit, including homebound
status (42 CFR 484.55(a)(1) and (b)). In addition, the requirement for
OASIS reporting on Medicare and Medicaid Managed Care patients was
established in a final rule titled ``Medicare and Medicaid Programs:
Reporting Outcome and Assessment Information Set Data as Part of the
Conditions of Participation for Home Health Agencies Final Rule'' dated
December 23, 2005 (70 FR 76200), which stated the following:
``In the January 25, 1999, interim final rule with comment period
(64 FR 3749), we generally mandated that all HHAs participating in
Medicare and Medicaid (including managed care organizations providing
home health services to Medicare and Medicaid beneficiaries) report
their OASIS data to the database we established within each State via
electronic transmission.''
We do not believe that there is more burden associated with the
collection of OASIS assessment data for a Medicare Managed Care patient
than there is for a HH patient that receives traditional Medicare fee-
for-service (FFS) benefits. The requirements for the HH RN or qualified
therapist to perform an initial and comprehensive assessment and
complete all required OASIS assessments is the same for all Medicare
patients regardless of the type of Medicare or Medicaid benefits they
receive. The completion of these activities is a condition of payment
of both Medicare FFS and managed care claims.
We are committed to stakeholder education and as such conducted a
Special Open Door forum on the QAO methodology and compliance rates on
June 2, 2015; materials from this Special Open Door Forum, along with
additional educational information, are available in the downloads
section at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/Home-Health-Quality-Reporting-Requirements.html. CMS anticipates communicating ongoing
educational opportunities through the regular HH QRP communication
channels, including Open Door Forums, webinars, listening sessions,
memos, email notification, and web postings.
Final Action: After consideration of the comments received, we are
adopting as final our proposal to implement an 80 percent Pay-for-
Reporting Performance Requirement for Submission of OASIS Quality Data
for Year 2 reporting period July 1, 2016 to June 30, 2017, and a 90
percent Pay-for-Reporting Performance Requirement for Submission of
OASIS Quality Data for the reporting period July 1, 2017 to June 30,
2018 and thereafter.
e. Home Health Care CAHPS[supreg] Survey (HHCAHPS)
In the CY 2015 HH PPS final rule (79 FR 66031), we stated that the
home health quality measures reporting requirements for Medicare-
certified agencies includes the Home Health Care CAHPS[supreg]
(HHCAHPS) Survey for the CY 2015 Annual Payment Update (APU). We are
continuing to maintain the stated HHCAHPS data requirements for CY 2016
that were stated in CY 2015 and in previous rules, for the continuous
monthly data collection and quarterly data submission of HHCAHPS data.
1. Background and Description of HHCAHPS
As part of the HHS Transparency Initiative, we implemented a
process to measure and publicly report patient experiences with home
health care, using a survey developed by the Agency for Healthcare
Research and Quality's (AHRQ's) Consumer Assessment of Healthcare
Providers and Systems (CAHPS[supreg]) program and endorsed by the NQF
in March 2009 (NQF Number 0517) and recently NQF re-endorsed in 2015.
The HHCAHPS Survey is approved under OMB Control Number 0938-1066
through May 31, 2017. The HHCAHPS survey is part of a family of
CAHPS[supreg] surveys that asks patients to report on and rate their
experiences with health care. The Home Health Care CAHPS[supreg]
(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.
Prior to this survey, there was no national standard for collecting
information about patient experiences that enabled valid comparisons
across all HHAs. The history and development process for HHCAHPS has
been described in previous rules and is also available on the official
HHCAHPS Web site at: https://homehealthcahps.org and in the annually-
updated HHCAHPS Protocols and Guidelines Manual, which is downloadable
from https://homehealthcahps.org.
Since April 2012, for public reporting purposes, we report five
measures from the HHCAHPS Survey--three composite measures and two
global ratings of care that are derived from the questions on the
HHCAHPS survey. The publicly reported data are adjusted for differences
in patient mix across HHAs. We update the HHCAHPS data on Home Health
Compare on www.medicare.gov quarterly. Each HHCAHPS composite measure
consists of four or more individual survey items regarding one of the
following related topics:
Patient care (Q9, Q16, Q19, and Q24);
Communications between providers and patients (Q2, Q15,
Q17, Q18, Q22, and Q23); and
Specific care issues on medications, home safety, and pain
(Q3, Q4, Q5, Q10, Q12, Q13, and Q14).
The two global ratings are the overall rating of care given by the
HHA's care providers (Q20), and the patient's willingness to recommend
the HHA to family and friends (Q25).
The HHCAHPS survey is currently available in English, Spanish,
Chinese, Russian, and Vietnamese. The OMB number on these surveys is
the same (0938-1066). All of these surveys are on the Home Health Care
CAHPS[supreg] Web site, https://homehealthcahps.org. We continue to
consider additional language translations of the HHCAHPS in response to
the needs of the home health patient population.
All of the requirements about home health patient eligibility for
the HHCAHPS survey and conversely, which home health patients are
ineligible for the HHCAHPS survey are delineated and detailed in the
HHCAHPS Protocols and Guidelines Manual, which is downloadable at
https://homehealthcahps.org. Home health patients are eligible for
HHCAHPS if they received at least two skilled home health visits in the
past 2 months, which are paid for by Medicare or Medicaid.
[[Page 68707]]
Home health patients are ineligible for inclusion in HHCAHPS
surveys if one of these conditions pertains to them:
Are under the age of 18;
Are deceased prior to the date the sample is pulled;
Receive hospice care;
Receive routine maternity care only;
Are not considered survey eligible because the state in
which the patient lives restricts release of patient information for a
specific condition or illness that the patient has; or
No Publicity patients, defined as patients who on their
own initiative at their first encounter with the HHAs make it very
clear that no one outside of the agencies can be advised of their
patient status, and no one outside of the HHAs can contact them for any
reason.
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 also must
provide on a monthly basis a list of their patients served to their
respective HHCAHPS survey vendors. Agencies are not allowed to
influence at all how their patients respond to the HHCAHPS survey.
As previously required, HHCAHPS survey vendors are required to
attend introductory and all update trainings conducted by CMS and the
HHCAHPS Survey Coordination Team, as well as to pass a post-training
certification test. We have approximately 30 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. As stated in previous HH PPS final rules, all
HHCAHPS approved survey vendors must develop a Quality Assurance Plan
(QAP) for survey administration in accordance with the HHCAHPS
Protocols and Guidelines Manual. An HHCAHPS survey vendor's first QAP
must be submitted within 6 weeks of the data submission deadline date
after the vendor's first quarterly data submission. The QAP must be
updated and submitted annually thereafter and at any time that changes
occur in staff or vendor capabilities or systems. A model QAP is
included in the HHCAHPS Protocols and Guidelines Manual. The QAP must
include the following:
Organizational Background and Staff Experience;
Work Plan;
Sampling Plan;
Survey Implementation Plan;
Data Security, Confidentiality and Privacy Plan; and
Questionnaire Attachments
As part of the oversight activities, the HHCAHPS Survey
Coordination Team conducts on-site visits to all approved HHCAHPS
survey vendors. The purpose of the site visits is to allow the HHCAHPS
Survey Coordination Team to observe the entire HHCAHPS Survey
implementation process, from the sampling stage through file
preparation and submission, as well as to assess data security and
storage. The HHCAHPS Survey Coordination Team reviews the HHCAHPS
survey vendor's survey systems, and assesses administration protocols
based on the HHCAHPS Protocols and Guidelines Manual posted at: https://homehealthcahps.org. The systems and program site visit review
includes, but is not limited to the following:
Survey management and data systems;
Printing and mailing materials and facilities;
Telephone call center facilities;
Data receipt, entry and storage facilities; and
Written documentation of survey processes.
After the site visits, HHCAHPS survey vendors are given a defined
time period in which to correct any identified issues and provide
follow-up documentation of corrections for review. HHCAHPS survey
vendors are subject to follow-up site visits on an as-needed basis.
In the CY 2013 HH PPS final rule (77 FR 67094, 67164), we codified
the current guideline that all approved HHCAHPS survey vendors fully
comply with all HHCAHPS oversight activities. We included this survey
requirement at Sec. 484.250(c)(3).
3. HHCAHPS Requirements for the CY 2016 APU
In the CY 2015 HH PPS final rule (79 FR 66031), we stated that for
the CY 2016 APU, we would require continued monthly HHCAHPS data
collection and reporting for four quarters. The data collection period
for the CY 2016 APU includes the second quarter 2014 through the first
quarter 2015 (the months of April 2014 through March 2015). Although
these dates are past, we wished to state them in this rule so that HHAs
are again reminded of what months constituted the requirements for the
CY 2016 APU.
For the 2016 APU, we required that all HHAs that had fewer than 60
HHCAHPS-eligible unduplicated or unique patients in the period of April
1, 2013 through March 31, 2014 are exempted from the HHCAHPS data
collection and submission requirements for the CY 2016 APU, upon
completion of the CY 2016 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, 2013, through March 31, 2014, were required to
submit their patient counts on the HHCAHPS Participation Exemption
Request form for the CY 2016 APU posted on https://homehealthcahps.org
from April 1, 2014, to 11:59 p.m., EST on March 31, 2015. This deadline
for the exemption form is firm, as are all of the quarterly data
submission deadlines for the HHAs that participate in HHCAHPS.
We automatically exempt HHAs receiving Medicare certification after
the period in which HHAs do their patient counts. HHAs receiving
Medicare certification on or after April 1, 2014 were exempt from the
HHCAHPS reporting requirement for the CY 2016 APU. These newly-
certified HHAs did not need to complete the HHCAHPS Participation
Exemption Form for the CY 2016 APU.
4. HHCAHPS Requirements for the CY 2017 APU
For the CY 2017 APU, we require continued monthly HHCAHPS data
collection and reporting for four quarters. The data collection period
for the CY 2017 APU includes the second quarter 2015 through the first
quarter 2016 (the months of April 2015 through March 2016). HHAs are
required to submit their HHCAHPS data files to the HHCAHPS Data Center
for the second quarter 2015 by 11:59 p.m., EST on October 15, 2015; for
the third quarter 2015 by 11:59 p.m., EST on January 21, 2016; for the
fourth quarter 2015 by 11:59 p.m., EST on April 21, 2016; and for the
first quarter 2016 by 11:59 p.m., EST on July 21, 2016. These deadlines
are firm; no exceptions are permitted.
For the CY 2017 APU, we require that all HHAs with fewer than 60
HHCAHPS-eligible unduplicated or unique patients in the period of April
1, 2014, through March 31, 2015 are exempt from the HHCAHPS data
collection and submission requirements for the CY 2017 APU, upon
completion of the CY 2017 HHCAHPS Participation Exemption Request form,
and upon
[[Page 68708]]
CMS verification of the HHA patient counts. Agencies with fewer than 60
HHCAHPS-eligible, unduplicated or unique patients in the period of
April 1, 2014, through March 31, 2015, are required to submit their
patient counts on the CY 2017 HHCAHPS Participation Exemption Request
form posted on https://homehealthcahps.org from April 1, 2015, to 11:59
p.m., EST to March 31, 2016. This deadline is firm, as are all of the
quarterly data submission deadlines for the HHAs that participate in
HHCAHPS.
We automatically exempt HHAs receiving Medicare certification after
the period in which HHAs do their patient count. HHAs receiving
Medicare-certification on or after April 1, 2015 are exempt from the
HHCAHPS reporting requirement for the CY 2017 APU. These newly-
certified HHAs do not need to complete the HHCAHPS Participation
Exemption Request Form for the CY 2017 APU.
5. HHCAHPS Requirements for the CY 2018 APU
For the CY 2018 APU, we require continued monthly HHCAHPS data
collection and reporting for four quarters. The data collection period
for the CY 2018 APU includes the second quarter 2016 through the first
quarter 2017 (the months of April 2016 through March 2017). HHAs will
be required to submit their HHCAHPS data files to the HHCAHPS Data
Center for the second quarter 2016 by 11:59 p.m., EST on October 20,
2016; for the third quarter 2016 by 11:59 p.m., EST on January 19,
2017; for the fourth quarter 2016 by 11:59 p.m., EST on April 20, 2017;
and for the first quarter 2017 by 11:59 p.m., EST on July 20, 2017.
These deadlines are firm; no exceptions will be permitted.
For the CY 2018 APU, we require that all HHAs with fewer than 60
HHCAHPS-eligible unduplicated or unique patients in the period of April
1, 2015 through March 31, 2016 are exempt from the HHCAHPS data
collection and submission requirements for the CY 2018 APU, upon
completion of the CY 2018 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, 2015 through March 31, 2016 are required to submit
their patient counts on the CY 2018 HHCAHPS Participation Exemption
Request form posted on https://homehealthcahps.org from April 1, 2016
to 11:59 p.m., EST to March 31, 2017. This deadline is firm, as are all
of the quarterly data submission deadlines for the HHAs that
participate in HHCAHPS.
We automatically exempt HHAs receiving Medicare certification after
the period in which HHAs do their patient count. HHAs receiving
Medicare-certification on or after April 1, 2016 are exempt from the
HHCAHPS reporting requirement for the CY 2018 APU. These newly-
certified HHAs do not need to complete the HHCAHPS Participation
Exemption Request Form for the CY 2018 APU.
6. HHCAHPS Reconsiderations and Appeals Process
HHAs should 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 continue HHCAHPS oversight activities as finalized in the
previous rules. In the CY 2013 HH PPS final rule (77 FR 6704, 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 Sec. 484.250(c)(3).
We continue the OASIS and HHCAHPS reconsiderations and appeals
process that we have finalized and that we have used for prior all
periods cited in the previous rules, and utilized in the CY 2012 to CY
2016 APU determinations. We have described the HHCAHPS reconsiderations
and appeals process requirements in the APU Notification Letter that we
send to the affected HHAs annually in September. HHAs have 30 days from
their receipt of the letter informing them that they did not meet the
HHCAHPS requirements to reply to CMS with documentation that supports
their requests for reconsideration of the annual payment update to CMS.
It is important that the affected HHAs send in comprehensive
information in their reconsideration letter/package because CMS will
not contact the affected HHAs to request additional information or to
clarify incomplete or inconclusive information. If clear evidence to
support a finding of compliance is not present, then the 2 percent
reduction in the annual payment update will be upheld. If clear
evidence of compliance is present, then the 2 percent reduction for the
APU will be reversed. CMS notifies affected HHAs by December 31 of the
decisions that affects payments in the annual year beginning on January
1. If CMS determines to uphold the 2 percent reduction for the annual
payment update, the affected HHA may further appeal the 2 percent
reduction via the Provider Reimbursement Review Board (PRRB) appeals
process, which is described in the December letter.
The following is a summary of the comments that we received
regarding HHCAHPS:
Comment: We received one comment that HHCAHPS is an unfunded
administrative mandate that entails financial and resource burdens to
HHAs.
Response: The collection of the patient's perspectives of care data
for similar CAHPS surveys, such as Hospital CAHPS (HCAHPS), follow the
same model where providers pay the approved survey vendors for the data
collection and implementation of the survey, and CMS pays for the
HHCAHPS survey administration and technical assistance processes, the
vendor approval, the vendor training, and vendor oversight activities,
technical support to the home health agencies and for the vendors, and
the data compilation, data analysis, and public reporting of the data's
findings on www.Medicare.gov. HHAs are strongly encouraged to report
their HHCAHPS costs on their respective annual cost reports, but HHAs
should note that HHCAHPS costs are not reimbursable under the HH PPS.
We post the list of the approved HHCAHPS vendors on https://homehealthcahps.org, and we encourage HHAs to contact the vendors for
cost and service information pertaining to HHCAHPS since the HHAs may
find differences among the vendors and will very likely find a vendor
that is very suitable to their particular cost and administrative needs
for HHCAHPS.
Comment: We received a comment of concern regarding the fact that
in the CY 2013 HH PPS final rule 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 Sec.
484.250(c)(3).
Response: We appreciate this commenter's continuing concern about
the policy set forth in the regulation several years ago. The
implementation of the policy in the past 3 years has worked out very
well and it is working as intended.
Comment: We received a comment that the HHCAHPS Star Rating
methodology does not include Q25, ``Would you recommend this agency to
your family or friends if they needed home health care?'' with the
answer
[[Page 68709]]
choices of ``Definitely no, Probably no, Probably yes, and Definitely
yes''. The commenter recommends that we include a Star Rating that is
the average of two questions on the HHCAHPS survey, Q25 (the question
above, ``Would you recommend this agency to your family or friends'')
and Q20 (``Using a number from 0 to 10, where 0 is the worst home
health care possible and 10 is the best home health care possible, what
number would you use to rate your care from this agency's home health
providers?'') or remove Q25 from the composite measure.
Response: We thank the commenter for the comments, but will
continue to retain Q20 and Q25 because they are standalone questions
and they are not part of an HHCAHPS composite (which is a measure
combining several survey questions).
Comment: We received one comment that CMS should establish a
minimum number of completed HHCAHPS surveys (at 50 surveys) per agency
if the data are going to be used in HHVBP or any other quality
assessment program.
Response: We are going to start publicly reporting Star Ratings in
January 2016. We introduced the methodology in several CMS Open Door
Forums in spring 2015 and announcements on our Web sites. After
extensive data testing, our statisticians established that at least 40
surveys are needed in order to report Star Ratings for a home health
agency. The commenter was correct; a minimum number of surveys are
needed to have Star Ratings. In testing, it was found that there is no
statistically significant difference between 40 surveys and 50 surveys
as a minimum number for the HHCAHPS data.
Comment: We received one comment in support of the continuation of
the Home Health CAHPS[supreg] requirements that are in line with
previous years' requirements.
Response: We thank this commenter for their support.
Final Decision: We are not recommending any changes to the HHCAHPS
requirements as a result of comments received.
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[supreg] Survey (HHCAHPS). We only updated the information
to reflect the dates in the future APU years. 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 telephone toll-free (1-866-
354-0985) for more information about HHCAHPS.
F. Public Display of Home Health Quality Data for the HH QRP
Section 1895(b)(3)(B)(v)(III) of the Act and section 1899B(f) of
the IMPACT Act states the Secretary shall establish procedures for
making data submitted under subclause (II) available to the public.
Such procedures shall ensure that a home health agency has the
opportunity to review the data that is 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 be meaningful and that comparing
performance across home health agencies requires that measures be
constructed from data collected in a standardized and uniform manner.
We also recognize the need to ensure that each home health agency has
the opportunity to review the data before publication. Medicare home
health regulations, as codified at Sec. 484.250(a), requires HHAs to
submit OASIS assessments and Home Health Care Consumer Assessment of
Healthcare Providers and Systems Survey[supreg] (HHCAHPS) data to meet
the quality reporting requirements of section 1895(b)(3)(B)(v) of the
Act.
In addition, beginning April 1, 2015 HHAs began to receive Provider
Preview Reports (for all Process Measures and Outcome Measures) on a
quarterly, rather than annual, basis. The opportunity for providers to
review their data and to submit corrections prior to public reporting
aligns with the other quality reporting programs and the requirement
for provider review under the IMPACT Act. We provide quality measure
data to HHAs via the Certification and Survey Provider Enhanced Reports
(CASPER reports), which are available through the CMS Health Care
Quality Improvement and Evaluation System (QIES).
As part of our ongoing efforts to make healthcare more transparent,
affordable, and accountable, the HH QRP has developed a CMS Compare Web
site for home health agencies, which identifies home health providers
based on the areas they serve. Consumers can search for all Medicare-
certified home health providers that serve their city or ZIP code and
then find the agencies offering the types of services they need. A
subset of the HH quality measures has been publicly reported on the
Home Health Compare (HH Compare) Web site since 2003. The selected
measures that are made available to the public can be viewed on the HH
Compare Web site located at https://www.medicare.gov/HHCompare/Home.asp
The Affordable Care Act calls for transparent, easily understood
information on provider quality to be publicly reported and made widely
available. To provide home health care consumers with a summary of
existing quality measures in an accessible format, we published a star
rating based on the quality of care measures for home health agencies
on Home Health Compare starting in July 2015. This is part of our plan
to adopt star ratings across all Medicare.gov Compare Web sites. Star
ratings are currently publicly displayed on Nursing Home Compare,
Physician Compare, Hospital Compare, Dialysis Facility Compare, and the
Medicare Advantage Plan Finder.
The Quality of Patient Care star rating methodology assigns each
home health agency a rating between one (1) and five (5) stars, using
half stars for adjustment and reporting. All Medicare-certified home
health agencies are eligible to receive a Quality of Patient Care star
rating providing that they have quality data reported on at least 5 out
of the 9 quality measures that are included in the calculation.
Home health agencies will continue to have prepublication access to
their agency's quality data, which enables each agency to know how it
is performing before public posting of the data on the Compare Web
site. Starting in April 2015, HHAs are receiving quarterly preview
reports showing their Quality of Patient Care star rating and how it
was derived well before public posting. HHAs have several weeks to
review and provide feedback.
The Quality of Patient Care star ratings methodology was developed
through a transparent process the included multiple opportunities for
stakeholder input, which was subsequently the basis for refinements to
the methodology. An initial proposed methodology for calculating the
Quality of Patient Care star ratings was posted on the CMS.gov Web site
in December 2014. CMS then held two Special Open Door Forums (SODFs) on
December 17, 2014 and February 5, 2015 to present the proposed
methodology and solicit input. At each SODF, stakeholders provided
immediate input, and were invited to submit additional comments via the
Quality of Patient Care star ratings Help Desk mailbox
HHC_Star_Ratings_Helpdesk@cms.hhs.gov. CMS
[[Page 68710]]
refined the methodology, based on comments received and additional
analysis. The final methodology report is posted on the new star
ratings Web page https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIHomeHealthStarRatings.html. A Frequently-Asked-Questions (FAQ)
document is also posted on the same Web page, addressing the issues
raised in the comments that were received. We tested the Web site
language used to present the Quality of Patient Care star ratings with
Medicare beneficiaries to assure that it allowed them to accurately
understand the significance of the various star ratings.
Additional information regarding the Quality of Patient Care star
rating is posted on the star ratings Web page at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIHomeHealthStarRatings.html. Additional
communications regarding the Quality of Patient Care star ratings will
be announced via regular HH QRP communication channels.
Summaries of public comments and our responses to comments
regarding the Public Display of Home Health Quality Data for the HH QRP
are provided below:
Comment: A commenter recommended that CMS include stabilization
measures in the Quality of Patient Care star ratings algorithm.
Response: We appreciate the feedback on the Quality of Patient Care
star ratings methodology, and agree that stabilization is an important
goal for some home health patients. CMS is committed to ongoing
evaluation and improvement of the algorithm to calculate the star
rating, including potential inclusion of new measures that meet the
inclusion criteria for variability, reportability, and clinical
relevance.
VI. Collection of Information Requirements
While this rule contains information collection requirements, this
rule does not add new, nor revise any of the existing information
collection requirements, or burden estimate. The information collection
requirements discussed in this rule for the OASIS-C1 data item set had
been previously approved by the Office of Management and Budget (OMB)
on February 6, 2014 and scheduled for implementation on October 1,
2014. The extension of OASIS-C1/ICD-9 version was reapproved under OMB
control number 0938-0760 with a current expiration date of March 31,
2018. This version of the OASIS will be discontinued once the OASIS-C1/
ICD-10 version is approved and implemented. In addition, to facilitate
the reporting of OASIS data as it relates to the implementation of ICD-
10 on October 1, 2015, CMS submitted a new request for approval to OMB
for the OASIS-C1/ICD-10 version under the Paperwork Reduction Act (PRA)
process. The proposed revised OASIS item was announced in the 30-day
Federal Register notice (80 FR 15797) and received OMB approval and
assigned OMB control number 0938-1279.
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 HH services paid under Medicare. In addition,
section 1895(b)(3)(A) of the Act requires (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 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
case-mix 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 HH
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.
Section 421(a) of the MMA requires that HH services furnished in a
rural area, for episodes and visits ending on or after April 1, 2010,
and before January 1, 2016, receive an increase of 3 percent of the
payment amount otherwise made under section 1895 of the Act. Section
210 of the MACRA amended section 421(a) of the MMA to extend the 3
percent increase to the payment amounts for serviced furnished in rural
areas for episodes and visits ending before January 1, 2018.
Section 3131(a) of the Affordable Care Act mandates that starting
in CY 2014, the Secretary must apply an adjustment to the national,
standardized 60-day episode payment rate and other amounts applicable
under section 1895(b)(3)(A)(i)(III) of the Act to 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.
In addition, section 3131(a) of the Affordable Care Act mandates that
rebasing must be phased-in over a 4-year period in equal increments,
not to exceed 3.5 percent of the amount (or amounts) as of the date of
enactment (2010) under section 1895(b)(3)(A)(i)(III) of the Act, and be
fully implemented in CY 2017.
The HHVBP Model will apply a payment adjustment based on an HHA's
performance on quality measures to test the effects on quality and
costs of care. This HHVBP Model was developed based on the experiences
we gained from the implementation of the Home Health Pay-for-
Performance (HHPP) demonstration as well as the successful
implementation of the HVBP program. The model design was also developed
from the public comments received on the discussion of a HHVBP model
being considered in the CY 2015 HH PPS proposed and final rules. Value-
based purchasing programs have also been included in the President's
budget for most provider types, including Home Health.
B. Overall Impact
We have examined the impacts of this rule as required by Executive
Order
[[Page 68711]]
12866 on Regulatory Planning and Review (September 30, 1993), Executive
Order 13563 on Improving Regulation and Regulatory Review (January 18,
2011), the Regulatory Flexibility Act (RFA) (September 19, 1980, Pub.
L. 96-354), section 1102(b) of the Act, section 202 of the Unfunded
Mandates Reform Act of 1995 (UMRA, March 22, 1995; Pub. L. 104-4),
Executive Order 13132 on Federalism (August 4, 1999), and the
Congressional Review Act (5 U.S.C. 804(2)).
Executive Orders 12866 and 13563 direct agencies to assess all
costs and benefits of available regulatory alternatives and, if
regulation is necessary, to select regulatory approaches that maximize
net benefits (including potential economic, environmental, public
health and safety effects, distributive impacts, and equity). Executive
Order 13563 emphasizes the importance of quantifying both costs and
benefits, of reducing costs, of harmonizing rules, and of promoting
flexibility. The net transfer impacts related to the changes in
payments under the HH PPS for CY 2016 are estimated to be -$260
million. The savings impacts related to the HHVBP model are estimated
at a total projected 5-year gross savings of $380 million assuming a
very conservative savings estimate of a 6 percent annual reduction in
hospitalizations and a 1.0 percent annual reduction in SNF admissions.
In accordance with the provisions of Executive Order 12866, this
regulation was reviewed by the Office of Management and Budget.
1. HH PPS
The update set forth in this rule applies to Medicare payments
under HH PPS in CY 2016. Accordingly, the following analysis describes
the impact in CY 2016 only. We estimate that the net impact of the
policies in this rule is approximately $260 million in decreased
payments to HHAs in CY 2016. 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 2016 wage index and the recalibration of the
case-mix weights for 2016 is zero. The -$260 million impact reflects
the distributional effects of the 1.9 percent HH payment update
percentage ($345 million increase), the effects of the third year of
the four-year phase-in of the rebasing adjustments to the national,
standardized 60-day episode payment amount, the national per-visit
payment rates, and the NRS conversion factor for an impact of -2.4
percent ($440 million decrease), and the effects of the -0.97 percent
adjustment to the national, standardized 60-day episode payment rate to
account for nominal case-mix growth ($165 million decrease). The $260
million in decreased payments is reflected in the last column of the
first row in Table 21 as a 1.4 percent decrease in expenditures when
comparing CY 2015 payments to estimated CY 2016 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 Medicare-paid visits and therefore the
majority of HHAs' revenue consists of Medicare payments. Based on our
analysis, we conclude that the policies finalized in this 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 final rule will have a
significant economic impact on a substantial number of small entities.
Further detail is presented in Table 24, by HHA type and location.
With regards to options for regulatory relief, we note that in the
CY 2014 HH PPS final rule we finalized rebasing adjustments to the
national, standardized 60-day episode rate, non-routine supplies (NRS)
conversion factor, and the national per-visit payment rates for each
year, 2014 through 2017 as described in section II.C and III.C.3 of
this final rule. Since the rebasing adjustments are mandated by section
3131(a) of the Affordable Care Act, we cannot offer HHAs relief from
the rebasing adjustments for CY 2016. For the 1.4 percent reduction to
the national, standardized 60-day episode payment amount for CY 2016
described in section III.B.2 of this final rule, we believe it is
appropriate to reduce the national, standardized 60-day episode payment
amount 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. In the alternatives considered section for the CY 2016
HH PPS proposed rule (80 FR 39839), we note that we considered reducing
the 60-day episode rate in CY 2016 only to account for nominal case-mix
growth between CY 2012 and CY 2014. However, we instead proposed to
reduce the 60-day episode rate over a two-year period (CY 2016 and CY
2017) to account for estimated nominal case-mix growth between CY 2012
and CY 2014 in order to lessen the impact on HHAs in a given year. As
discussed in III.B.2 of this final rule, we are implementing a
reduction of 0.97 percent to the 60-day episode rate in each of the
next three calendar years (CY 2016 through CY 2018.
Executive Order 13563 specifies, to the extent practicable,
agencies should assess the costs of cumulative regulations. However,
given potential utilization pattern changes, wage index changes,
changes to the market basket forecasts, and unknowns regarding future
policy changes, we believe it is neither practicable nor appropriate to
forecast the cumulative impact of the rebasing adjustments on Medicare
payments to HHAs for future years at this time. 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 will make it difficult to predict accurately the full scope of
the impact upon HHAs for future years beyond CY 2016. We note that the
rebasing adjustments to the national, standardized 60-day episode
payment rate and the national per-visit rates are capped at the
statutory limit of 3.5 percent of the CY 2010 amounts (as described in
the preamble in section II.C. of this final rule) for each year, 2014
through 2017. The NRS rebasing adjustment will be -2.82 percent in each
year, 2014 through 2017.
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)
[[Page 68712]]
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 final rule is applicable exclusively to HHAs. Therefore,
the Secretary has determined this rule will not have a significant
economic impact on the operations of small rural hospitals.
2. HHVBP Model
To test the impact of upside and downside value-based payment
adjustments, beginning in calendar year 2018 and in each succeeding
calendar year through calendar year 2022, the HHVBP Model will adjust
the final claim payment amount for a home health agency for each
episode in a calendar year by an amount equal to the applicable
percent. For purposes of this final rule, we have limited our analysis
of the economic impacts to the value-based incentive payment
adjustments. Under the model design, the incentive payment adjustments
will be limited to the total payment reductions to home health agencies
included in the model and would be no less than the total amount
available for value-based incentive payment adjustment. Overall, the
distributive impact of this rule is estimated at $380 million for CY
2018-2022. Therefore, this rule is economically significant and thus a
major rule under the Congressional Review Act. The model will test the
effect on quality and costs of care by applying payment adjustments
based on HHAs' performance on quality measures. This rule was developed
based on extensive research and experience with value-based purchasing
models.
Guidance issued by the Department of Health and Human Services
interpreting the Regulatory Flexibility Act considers the 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. Among the over 1900 HHAs in the selected states that would be
expected to be included in the HHVBP Model, we estimate that the
maximum percent payment adjustment resulting from this rule will only
be greater than minus 3 percent for 10 percent of the HHAs included in
the model (using the 8 percent maximum payment adjustment threshold to
be applied in CY2022). As a result, only 2-percent of all HHA providers
nationally would be significantly impacted, falling well below the RFA
threshold. In addition, only HHAs that are impacted with lower payments
are those providers that provide the poorest quality which is the main
tenet of the model. This falls well below the threshold for economic
significance established by HHS for requiring a more detailed impact
assessment under the RFA. Thus, we are not preparing an analysis under
the RFA because the Secretary has determined that this final rule would
not have a significant economic impact on a substantial number of small
entities.
In addition, section 1102(b) of the Act requires us to prepare a
regulatory impact analysis if a rule may have a significant impact on
the operations of a substantial number of small rural HHAs. This
analysis must conform to the provisions of section 604 of the RFA. For
purposes of section 1102(b) of the Act, we have identified less than 5
percent of HHAs included in the selected states that primarily serve
beneficiaries that reside in rural areas (greater than 50 percent of
beneficiaries served). We are not preparing an analysis under section
1102(b) of the Act because the Secretary has determined that the HHVBP
Model would not have a significant impact on the operations of a
substantial number of small rural HHAs.
Section 202 of the Unfunded Mandates Reform Act of 1995 also
requires that agencies assess anticipated costs and benefits before
issuing any rule whose mandates require spending in any 1 year of $100
million in 1995 dollars, updated annually for inflation. In 2015, that
threshold is approximately $144 million. This rule will have no
consequential effect on state, local, or tribal governments or on the
private sector.
Executive Order 13132 establishes certain requirements that an
agency must meet when it promulgates a proposed rule (and subsequent
final rule) that imposes substantial direct requirement costs on State
and local governments, preempts state law, or otherwise has Federalism
implications. Since this regulation does not impose any costs on state
or local governments, the requirements of Executive Order 13132 are not
applicable.
In accordance with the provisions of Executive Order 12866, this
regulation was reviewed by the Office of Management and Budget.
C. Detailed Economic Analysis
1. HH PPS
This final rule sets forth updates for CY 2016 to the HH PPS rates
contained in the CY 2015 HH PPS final rule (79 FR 66032 through 66118).
The impact analysis of this final rule presents the estimated
expenditure effects of policy changes finalized in this rule. 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 2014. 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.
Table 24 represents how HHA revenues are likely to be affected by
the policy changes finalized in this rule. For this analysis, we used
an analytic file with linked CY 2014 OASIS assessments and HH claims
data for dates of service that ended on or before December 31, 2014 (as
of June 30, 2015). The first column of Table 24 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 2016 wage index. The fourth column
shows the payment effects of the CY 2016 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 effects of the rebasing
adjustments to the national, standardized 60-day episode payment rate,
the national per-visit payment rates, and NRS conversion factor. For CY
2016, the average impact for all HHAs due to the effects of rebasing is
an estimated 2.4 percent decrease in payments. The seventh column shows
the effects of the CY 2016 home health payment update percentage (i.e.,
the home health market basket update adjusted for multifactor
productivity as discussed in section III.C.1. of this final rule).
[[Page 68713]]
The last column shows the combined effects of all the policies
finalized in this rule. Overall, it is projected that aggregate
payments in CY 2016 will decrease by 1.4 percent. As illustrated in
Table 24, 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 2016 wage index, the
extent to which HHAs had episodes in case-mix groups where the case-mix
weight decreased for CY 2016 relative to CY 2015, 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.
Table 21--Estimated Home Health Agency Impacts by Facility Type and Area of the Country, CY 2016
--------------------------------------------------------------------------------------------------------------------------------------------------------
60-day episode HH payment
Number of CY 2016 CY 2016 case- rate nominal Rebasing update
agencies wage index mix weights case-mix \4\ percentage Total
\1\ \2\ reduction \3\ \5\
--------------------------------------------------------------------------------------------------------------------------------------------------------
All Agencies............................................. 11,609 0.0% 0.0% -0.9% -2.4% 1.9% -1.4%
Facility Type and Control:
Free-Standing/Other Vol/NP............................... 1,094 0.0% 0.0% -0.9% -2.3% 1.9% -1.3%
Free-Standing/Other Proprietary.......................... 9,076 0.0% -0.1% -0.9% -2.4% 1.9% -1.5%
Free-Standing/Other Government........................... 382 -0.1% 0.2% -0.9% -2.3% 1.9% -1.2%
Facility-Based Vol/NP.................................... 718 0.1% 0.2% -0.9% -2.3% 1.9% -1.0%
Facility-Based Proprietary............................... 117 -0.3% 0.1% -0.9% -2.3% 1.9% -1.5%
Facility-Based Government................................ 222 -0.3% 0.3% -0.9% -2.3% 1.9% -1.3%
Subtotal: Freestanding............................... 10,552 0.0% 0.0% -0.9% -2.4% 1.9% -1.4%
Subtotal: Facility-based............................. 1,057 0.0% 0.2% -0.9% -2.3% 1.9% -1.1%
Subtotal: Vol/NP..................................... 1,812 0.1% 0.1% -0.9% -2.3% 1.9% -1.1%
Subtotal: Proprietary................................ 9,193 0.0% -0.1% -0.9% -2.4% 1.9% -1.5%
Subtotal: Government................................. 604 -0.2% 0.3% -0.9% -2.3% 1.9% -1.2%
Facility Type and Control: Rural:
Free-Standing/Other Vol/NP............................... 191 -0.9% 0.3% -0.9% -2.3% 1.9% -1.9%
Free-Standing/Other Proprietary.......................... 149 -0.4% 0.1% -0.9% -2.3% 1.9% -1.6%
Free-Standing/Other Government........................... 448 -0.6% 0.0% -0.9% -2.3% 1.9% -1.9%
Facility-Based Vol/NP.................................... 218 -0.7% 0.3% -0.9% -2.4% 1.9% -1.8%
Facility-Based Proprietary............................... 27 -0.1% 0.1% -0.9% -2.3% 1.9% -1.3%
Facility-Based Government................................ 131 -0.5% 0.5% -0.9% -2.3% 1.9% -1.3%
Facility Type and Control: Urban:
Free-Standing/Other Vol/NP............................... 942 0.1% 0.0% -0.9% -2.3% 1.9% -1.2%
Free-Standing/Other Proprietary.......................... 8,760 0.0% -0.1% -0.9% -2.4% 1.9% -1.5%
Free-Standing/Other Government........................... 154 -0.3% 0.1% -0.9% -2.4% 1.9% -1.6%
Facility-Based Vol/NP.................................... 500 0.2% 0.2% -0.9% -2.3% 1.9% -0.9%
Facility-Based Proprietary............................... 90 -0.4% 0.1% -0.9% -2.2% 1.9% -1.5%
Facility-Based Government................................ 91 -0.2% 0.2% -0.9% -2.4% 1.9% -1.4%
Facility Location: Urban or Rural:
Rural.................................................... 1,072 -0.6% 0.1% -0.9% -2.3% 1.9% -1.8%
Urban.................................................... 10,537 0.0% 0.0% -0.9% -2.4% 1.9% -1.4%
Facility Location: Region of the Country:
Northeast................................................ 837 0.0% 0.0% -0.9% -2.2% 1.9% -1.2%
Midwest.................................................. 3,078 0.0% 0.1% -0.9% -2.4% 1.9% -1.3%
South.................................................... 5,713 -0.2% -0.1% -0.9% -2.4% 1.9% -1.7%
West..................................................... 1885 0.5% 0.0% -0.9% -2.3% 1.9% -0.8%
Other.................................................... 96 -0.2% 0.0% -0.9% -2.4% 1.9% -1.6%
Facility Location: Region of the Country (Census Region):
New England.............................................. 294 -0.2% 0.0% -0.9% -2.1% 1.9% -1.3%
Mid Atlantic............................................. 543 0.1% 0.0% -0.9% -2.3% 1.9% -1.2%
East North Central....................................... 2,447 0.0% 0.0% -0.9% -2.4% 1.9% -1.4%
West North Central....................................... 631 -0.2% 0.2% -0.9% -2.4% 1.9% -1.4%
South Atlantic........................................... 1,883 0.0% 0.0% -0.9% -2.4% 1.9% -1.4%
East South Central....................................... 432 -0.3% -0.1% -0.9% -2.5% 1.9% -1.9%
West South Central....................................... 3,398 -0.3% -0.2% -0.9% -2.4% 1.9% -1.9%
Mountain................................................. 621 0.0% 0.1% -0.9% -2.3% 1.9% -1.2%
Pacific.................................................. 1,264 0.7% 0.0% -0.9% -2.4% 1.9% -0.7%
Facility Size (Number of 1st Episodes):
<100 episodes............................................ 2,911 0.1% 0.1% -0.9% -2.4% 1.9% -1.2%
100 to 249............................................... 2,726 0.1% 0.1% -0.9% -2.4% 1.9% -1.2%
250 to 499............................................... 2,522 0.1% 0.0% -0.9% -2.4% 1.9% -1.3%
500 to 999............................................... 1,857 0.1% 0.0% -0.9% -2.4% 1.9% -1.3%
1,000 or More............................................ 1,593 -0.1% -0.1% -0.9% -2.4% 1.9% -1.6%
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source: CY 2014 Medicare claims data for episodes ending on or before December 31, 2014 (as of June 30, 2015) for which we had a linked OASIS
assessment.
\1\ The impact of the CY 2016 home health wage index is offset by the wage index budget neutrality factor described in section III.C.3 of this final
rule.
\2\ The impact of the CY 2016 home health case-mix weights reflects the recalibration of the case-mix weights as outlined in section III.B.1 of this
final rule offset by the case-mix weights budget neutrality factor described in section III.C.3 of this final rule.
[[Page 68714]]
\3\ The 0.97 percent reduction to the national, standardized 60-day episode payment amount in CY 2016 is estimated to have a 0.9 percent impact on
overall HH PPS expenditures.
\4\ The impact of rebasing includes the rebasing adjustments to the national, standardized 60-day episode payment rate (-2.74 percent after the CY 2016
payment rate was adjusted for the wage index and case-mix weight budget neutrality factors and the nominal case-mix reduction), the national per-visit
rates (+2.9 percent), and the NRS conversion factor (-2.82 percent). The estimated impact of the NRS conversion factor rebasing adjustment is an
overall -0.01 percent decrease in estimated payments to HHAs.
\5\ The CY 2016 home health payment update percentage reflects the home health market basket update of 2.3 percent, reduced by a 0.4 percentage point
multifactor productivity (MFP) adjustment as required under section 1895(b)(3)(B)(vi)(I) of the Act, 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.
2. HHVBP Model
Table 22 displays our analysis of the distribution of possible
payment adjustments at the 3-percent, 5-percent, 6-percent, 7-percent,
and 8-percent rates that are being used in the model based on 2013-2014
data, providing information on the estimated impact of this rule. We
note that this impact analysis is based on the aggregate value of all 9
states identified in section IV.C.2. of this final rule by applying the
state selection methodology.
Table 23 displays our analysis of the distribution of possible
payment adjustments based on 2013-2014 data, providing information on
the estimated impact of this final rule. We note that this impact
analysis is based on the aggregate value of all nine (9) states
(identified in section IV.C.2. of this rule) by applying the state
selection methodology.
All Medicare-certified HHAs that provide services in Massachusetts,
Maryland, North Carolina, Florida, Washington, Arizona, Iowa, Nebraska,
and Tennessee will be required to compete in this model.
Value-based incentive payment adjustments for the estimated 1,900
plus HHAs in the selected states that will compete in the HHVBP Model
are stratified by the size as defined in section F. For example,
Arizona has 31 HHAs that do not provide services to enough
beneficiaries to be required to complete HHCAHPS surveys and therefore
are considered to be in the state's smaller-volume cohort under the
model. Using 2013-2014 data and the highest payment adjustment of 5-
percent (as applied in CY 2019), based on ten (10) process and outcome
measures currently available on Home Health Compare, the smaller-volume
HHAs in Arizona would have a mean payment adjustment of positive 0.64
percent. Only 10-percent of home health agencies would be subject to
downward payment adjustments of more than minus 3.3 percent (-3.3
percent).
The next columns provide the distribution of scores by percentile;
we see that the value-based incentive percentage payments for home
health agencies in Arizona range from -3.3 percent at the 10th
percentile to +5.0 percent at the 90th percentile, while the value-
based incentive payment at the 50th percentile is 0.56 percent.
The smaller-volume HHA cohorts table identifies that some
consideration will have to be made for MD, WA, and TN where there are
too few HHAs in the smaller-volume cohort and will be included in the
larger-volume cohort without being measured on HHCAHPS.
Table 24 provides the payment adjustment distribution based on
proportion of dual-eligible beneficiaries, average case mix (using HCC
scores), proportion that reside in rural areas, as well as HHA
organizational status. Besides the observation that higher proportion
of dually-eligible beneficiaries serviced is related to better
performance, the payment adjustment distribution is consistent with
respect to these four categories.
The TPS score and the payment methodology at the state and size
level were calculated so that each home health agency's payment
adjustment was calculated as it will be in the model. Hence, the values
of each separate analysis in the tables are representative of what they
would be if the baseline year was 2013 and the performance year was
2014.
There were 1,931 HHAs in the nine selected states out of 1,991 HHAs
that were found in the HHA data sources that yielded a sufficient
number of measures to receive a payment adjustment in the model. It is
expected that a certain number of HHAs will not be subject to the
payment adjustment because they may be servicing too small of a
population to report on an adequate number of measures to calculate a
TPS.
[[Page 68715]]
[GRAPHIC] [TIFF OMITTED] TR05NO15.011
Table 23--HHA Cohort Payment Adjustment Distributions by State
[Based on a 5 percent payment adjustment]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Average
# of payment
State HHAs adjustment 10% 20% 30% 40% 50% 60% 70% 80% 90%
%
--------------------------------------------------------------------------------------------------------------------------------------------------------
Smaller-volume HHA Cohort by State
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ................................................ 31 0.64 -3.33 -2.72 -2.17 -0.82 0.56 1.31 3.36 4.75 5.00
FL................................................ 353 0.44 -3.01 -1.76 -1.00 -0.39 0.21 0.94 1.84 3.04 4.38
IA................................................ 23 0.17 -3.14 -2.53 -2.01 -1.41 -0.97 0.31 2.74 3.25 5.00
MA................................................ 29 0.39 -3.68 -1.75 -0.70 -0.10 0.39 0.79 1.33 2.46 4.68
MD................................................ 2 -0.47 -2.71 -2.71 -2.71 -2.71 -0.47 1.78 1.78 1.78 1.78
NC................................................ 9 0.72 -2.38 -1.84 -1.41 -1.23 -0.68 0.34 3.67 5.00 5.00
NE................................................ 16 -0.51 -2.26 -1.80 -1.64 -1.43 -1.13 -0.44 0.40 0.42 1.46
TN................................................ 2 2.48 -0.05 -0.05 -0.05 -0.05 2.48 5.00 5.00 5.00 5.00
WA................................................ 1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
--------------------------------------------------------------------------------------------------------------------------------------------------------
Larger-volume HHA Cohort by State
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ................................................ 82 0.39 -3.31 -2.75 -2.19 -0.81 0.56 1.31 3.38 4.75 5.00
FL................................................ 672 0.41 -3.00 -1.75 -1.60 -0.38 0.19 0.94 1.81 3.06 4.38
IA................................................ 129 -0.31 -3.13 -2.31 -2.70 -1.13 -0.56 0.13 0.56 1.19 3.50
MA................................................ 101 0.64 -2.88 -2.19 -1.50 -0.38 0.63 1.25 2.06 3.81 4.88
MD................................................ 50 0.41 -2.75 -2.06 -2.30 -0.88 0.00 0.81 2.38 2.94 4.13
NC................................................ 163 0.65 -2.75 -1.56 -1.30 -0.06 0.38 0.94 1.88 3.06 4.88
NE................................................ 48 0.37 -2.63 -2.19 -1.40 -0.56 -0.19 0.50 1.31 2.31 5.00
TN................................................ 134 0.39 -2.56 -1.81 -2.00 -0.63 -0.06 0.81 1.44 2.50 4.69
WA................................................ 55 0.39 -2.75 -1.63 -2.00 -0.94 -0.19 0.69 1.94 3.31 4.06
--------------------------------------------------------------------------------------------------------------------------------------------------------
Table 24--Payment Adjustment Distributions by Characteristics
[Based on a 5 percent payment adjustment]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Percentage dually-eligible # of HHAs 10% 20% 30% 40% 50% 60% 70% 80% 90%
--------------------------------------------------------------------------------------------------------------------------------------------------------
Low % Dually-eligible..................... 498 -3.21 -2.57 -1.86 -1.29 -0.60 0.12 0.78 2.13 3.97
Medium % Dually-eligible.................. 995 -2.91 -2.10 -1.33 -0.63 0.01 0.67 1.39 2.47 4.12
High % Dually-eligible.................... 498 -2.46 -1.04 -0.24 0.59 1.29 2.34 3.38 4.53 5.00
Acuity (HCC):
Low Acuity................................ 499 -2.83 -1.76 -0.94 -0.23 0.46 1.16 2.03 3.40 5.00
Middle acuity............................. 993 -3.05 -2.08 -1.24 -0.50 0.19 0.90 1.71 2.81 4.51
High Acuity............................... 499 -3.04 -2.04 -1.29 -0.51 0.26 1.06 2.00 3.16 4.91
% Rural Beneficiaries:
All non-rural............................. 800 -2.81 -1.51 -0.66 0.08 0.78 1.54 2.64 3.94 5.00
[[Page 68716]]
Up to 35% rural........................... 925 -3.12 -2.37 -1.71 -1.01 -0.42 0.32 1.18 2.24 3.97
over 35% rural............................ 250 -2.91 -2.01 -1.17 -0.62 -0.11 0.56 1.32 2.86 4.58
Organizational Type:
Church.................................... 62 -2.92 -2.04 -1.33 -0.46 0.12 0.64 1.30 2.58 4.22
Private Not-For-Profit.................... 194 -2.78 -1.74 -0.97 -0.42 0.27 0.85 1.77 2.89 4.55
Other..................................... 93 -2.62 -1.68 -0.95 -0.38 0.36 1.08 1.86 3.09 4.63
Private For-Profit........................ 1538 -3.09 -2.08 -1.27 -0.53 0.24 1.02 1.88 3.02 4.83
Federal................................... 83 -2.44 -1.61 -0.67 0.01 0.53 1.13 1.80 3.09 4.58
State..................................... 5 -3.03 -1.11 -0.37 -0.01 0.24 0.42 1.66 2.96 3.24
Local..................................... 61 -2.30 -1.28 -0.48 0.16 0.98 1.91 2.88 4.11 5.00
--------------------------------------------------------------------------------------------------------------------------------------------------------
D. Accounting Statement and Table
As required by OMB Circular A-4 (available at https://www.whitehouse.gov/omb/circulars_a004_a-4), in Table 25, 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 25 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.
Table 25--Accounting Statement: HH PPS Classification of Estimated
Transfers and Costs, From the CYs 2015 to 2016 *
------------------------------------------------------------------------
Category Transfers
------------------------------------------------------------------------
Annualized Monetized Transfers............ -$260 million.
From Whom to Whom? Federal Government to HHAs.
------------------------------------------------------------------------
* The estimates reflect 2016 dollars.
Table 26 provides our best estimate of the decrease in Medicare
payments under the proposed HHVBP Model.
Table 26--Accounting Statement: HHVBP Model Classification of Estimated
Transfers and Costs for CY 2018-2022
------------------------------------------------------------------------
Category Transfers
------------------------------------------------------------------------
5-Year Gross Transfers.................... -$380 million.
From Whom to Whom? Federal Government to
Hospitals and SNFs.
------------------------------------------------------------------------
E. Conclusion
1. HH PPS
In conclusion, we estimate that the net impact of the HH PPS
policies in this rule is a decrease of 1.4 percent, or $260 million, in
Medicare payments to HHAs for CY 2016. The $260 million decrease in
estimated payments to HHAs for CY 2016 reflects the effects of the 1.9
percent CY 2016 HH payment update percentage ($345 million increase), 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 2016 to
account for nominal case-mix growth from 2012 through 2014 ($165
million decrease), and a 2.4 percent decrease in payments due to the
third year of the 4-year phase-in of the rebasing adjustments required
by section 3131(a) of the Affordable Care Act ($440 million decrease).
This analysis, together with the remainder of this preamble, provides
the final Regulatory Flexibility Analysis.
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 2016.
However, the overall economic impact of the HHVBP Model provision is an
estimated $380 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. The financial estimates were based on the analysis of hospital,
home health and skilled nursing facility claims data from nine states
using the most recent 2014 Medicare claims data. A study published in
2002 by the Journal of the American Geriatric Society (JAGS),
``Improving patient outcomes of home health care: Findings from two
demonstration trials of outcome-based quality improvement,'' formed the
basis for CMMI's projections.\79\ That study observed a hospitalization
relative rate of decline of 22-percent to 26-percent over the 3-year
and 4-year demonstration periods (the 1st year of each being the base
year) for the national and New York trials. CMMI assumed a conservative
savings estimate of up to a 6-percent ultimate annual reduction in
hospitalizations and up to a 1.0-percent ultimate annual reduction in
SNF admissions and took into account costs incurred from the
beneficiary remaining in the HHA if the hospitalization did not occur;
resulting in total projected five performance year gross savings of
$380 million. Based on the JAGS study, which observed hospitalization
reductions of over 20-percent, the 6-percent ultimate annual
hospitalization reduction assumptions are considered reasonable.
---------------------------------------------------------------------------
\79\ Shaughnessy, et al. ``Improving patient outcomes of home
health care: Findings from two demonstration trials of outcome-based
quality improvement,'' available at https://www.ncbi.nlm.nih.gov/pubmed/12164991.
---------------------------------------------------------------------------
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.
List of Subjects
42 CFR Part 409
Health facilities, Medicare.
42 CFR Part 424
Emergency medical services, Health facilities, Health professions,
Medicare, Reporting and recordkeeping requirements.
[[Page 68717]]
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 chapter IV as set forth below:
PART 409--HOSPITAL INSURANCE BENEFITS
0
1. The authority citation for part 409 continues to read as follows:
Authority: Secs. 1102 and 1871 of the Social Security Act (42
U.S.C. 1302 and 1395hh).
0
2. Section 409.43 is amended by revising paragraph (e)(1)(iii) to read
as follows:
Sec. 409.43 Plan of care requirements.
* * * * *
(e) * * *
(1) * * *
(iii) Discharge with goals met and/or no expectation of a return to
home health care and the patient returns to home health care during the
60-day episode.
* * * * *
PART 424--CONDITIONS FOR MEDICARE PAYMENT
0
3. The authority citation for part 424 continues to read as follows:
Authority: Secs. 1102 and 1871 of the Social Security Act (42
U.S.C. 1302 and 1395hh).
Sec. 424.22 [Amended]
0
4. Section 424.22 is amended by redesignating paragraph (a)(1)(v)(B)(1)
as paragraph (a)(2) and removing reserved paragraph (a)(1)(v)(B)(2).
PART 484--HOME HEALTH SERVICES
0
5. The authority citation for part 484 continues to read as follows:
Authority: Secs 1102 and 1871 of the Social Security Act (42
U.S.C. 1302 and 1395(hh)) unless otherwise indicated.
0
6. Section 484.205 is amended by revising paragraphs (d) and (e) to
read as follows:
Sec. 484.205 Basis of payment.
* * * * *
(d) Partial episode payment adjustment. (1) An HHA receives a
national 60-day episode payment of a predetermined rate for home health
services unless CMS determines an intervening event, defined as a
beneficiary elected transfer or discharge with goals met or no
expectation of return to home health and the beneficiary returned to
home health during the 60-day episode, warrants a new 60-day episode
for purposes of payment. A start of care OASIS assessment and physician
certification of the new plan of care are required.
(2) The PEP adjustment will not apply in situations of transfers
among HHAs of common ownership. Those situations will be considered
services provided under arrangement on behalf of the originating HHA by
the receiving HHA with the common ownership interest for the balance of
the 60-day episode. The common ownership exception to the transfer PEP
adjustment does not apply if the beneficiary moves to a different MSA
or Non-MSA during the 60-day episode before the transfer to the
receiving HHA. The transferring HHA in situations of common ownership
not only serves as a billing agent, but must also exercise professional
responsibility over the arranged-for services in order for services
provided under arrangements to be paid.
(3) If the intervening event warrants a new 60-day episode payment
and a new physician certification and a new plan of care, the initial
HHA receives a partial episode payment adjustment reflecting the length
of time the patient remained under its care. A partial episode payment
adjustment is determined in accordance with Sec. 484.235.
(e) Outlier payment. An HHA receives a national 60-day episode
payment of a predetermined rate for a home health service, unless the
imputed cost of the 60-day episode exceeds a threshold amount. The
outlier payment is defined to be a proportion of the imputed costs
beyond the threshold. An outlier payment is a payment in addition to
the national 60-day episode payment. The total of all outlier payments
is limited to no more than 2.5 percent of total outlays under the HHA
PPS. An outlier payment is determined in accordance with Sec. 484.240.
0
7. Section 484.220 is amended by revising paragraph (a)(3) and adding
paragraphs (a)(4), (5), and (6) to read as follows:
Sec. 484.220 Calculation of the adjusted national prospective 60-day
episode payment rate for case-mix and area wage levels.
* * * * *
(a) * * *
(3) For CY 2011, the adjustment is 3.79 percent.
(4) For CY 2012, the adjustment is 3.79 percent.
(5) For CY 2013, the adjustment is 1.32 percent.
(6) For CY 2016, CY 2017, and CY 2018, the adjustment is 0.97
percent in each year.
* * * * *
0
8. Section 484.225 is revised to read as follows:
Sec. 484.225 Annual update of the unadjusted national prospective 60-
day episode payment rate.
(a) CMS updates the unadjusted national 60-day episode payment rate
on a fiscal year basis (as defined in section 1895(b)(1)(B) of the
Act).
(b) For 2007 and subsequent calendar years, in accordance with
section 1895(b)(3)(B)(v) of the Act, in the case of a home health
agency that submits home health 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 home health market basket index amount.
(c) For 2007 and subsequent calendar years, in accordance with
section 1895(b)(3)(B)(v) of the Act, in the case of a home health
agency that does not submit home health 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 home health 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 taken into account in computing
the prospective payment amount for a subsequent calendar year.
Sec. 484.230 [Amended]
0
9. Section 484.230 is amended by removing the last sentence.
0
10. Section 484.240 is amended by revising paragraphs (b) and (e) and
adding paragraph (f) to read as follows:
Sec. 484.240 Methodology used for the calculation of the outlier
payment.
* * * * *
(b) The outlier threshold for each case-mix group is the episode
payment amount for that group, or the PEP adjustment amount for the
episode, plus a fixed dollar loss amount that is the same for all case-
mix groups.
* * * * *
(e) The fixed dollar loss amount and the loss sharing proportion
are chosen so that the estimated total outlier payment is no more than
2.5 percent of total payment under home health PPS.
(f) The total amount of outlier payments to a specific home health
agency for a year may not exceed an amount equal to 10 percent of the
total
[[Page 68718]]
payments to the specific agency under home health PPS for the year.
Sec. 484.245 [Removed and Reserved]
0
11. Section 484.245 is removed and reserved.
Sec. 484.250 [Amended]
0
12. Section 484.250(a)(2) is amended by removing the reference ``Sec.
484.225(i) of this subpart'' and adding in its place the reference
``Sec. 484.225(c)''.
0
13. Subpart F is added to read as follows:
Subpart F--Home Health Value-Based Purchasing (HHVBP) Model Components
for Competing Home Health Agencies within State Boundaries
Sec.
484.300 Basis and scope of subpart.
484.305 Definitions.
484.310 Applicability of the Home Health Value-Based Purchasing
(HHVBP) model.
484.315 Data reporting for measures and evaluation under the Home
Health Value-Based Purchasing (HHVBP) Model.
484.320 Calculation of the Total Performance Score.
484.325 Payments for home health services under Home Health Value-
Based Purchasing (HHVBP) Model.
484.330 Process for determining and applying the value-based payment
adjustment under the Home Health Value-Based Purchasing (HHVBP)
Model.
Subpart F--Home Health Value-Based Purchasing (HHVBP) Model
Components for Competing Home Health Agencies Within State
Boundaries
Sec. 484.300 Basis and scope of subpart.
This subpart is established under sections 1102, 1115A, and 1871 of
the Act (42 U.S.C. 1315a), which authorizes the Secretary to issue
regulations to operate the Medicare program and test innovative payment
and service delivery models to improve coordination, quality, and
efficiency of health care services furnished under Title XVIII.
Sec. 484.305 Definitions.
As used in this subpart--
Applicable measure means a measure for which the competing HHA has
provided 20 home health episodes of care per year.
Applicable percent means a maximum upward or downward adjustment
for a given performance year, not to exceed the following:
(1) For CY 2018, 3-percent.
(2) For CY 2019, 5-percent.
(3) For CY 2020, 6-percent.
(4) For CY 2021, 7-percent.
(5) For CY 2022, 8-percent.
Benchmark refers to the mean of the top decile of Medicare-
certified HHA performance on the specified quality measure during the
baseline period, calculated separately for the larger-volume and
smaller-volume cohorts within each state.
Competing home health agency or agencies means an agency or
agencies:
(1) That has or have a current Medicare certification; and,
(2) Is or are being paid by CMS for home health care delivered
within any of the states specified in Sec. 484.310.
Home health prospective payment system (HH PPS) refers to the basis
of payment for home health agencies as set forth in Sec. Sec. 484.200
through 484.245.
Larger-volume cohort means the group of competing home health
agencies within the boundaries of selected states that are
participating in HHCAHPs in accordance with Sec. 484.250.
Linear exchange function is the means to translate a competing
HHA's Total Performance Score into a value-based payment adjustment
percentage.
New measures means those measures to be reported by competing HHAs
under the HHVBP Model that are not otherwise reported by Medicare-
certified HHAs to CMS and were identified to fill gaps to cover
National Quality Strategy Domains not completely covered by existing
measures in the home health setting.
Payment adjustment means the amount by which a competing HHA's
final claim payment amount under the HH PPS is changed in accordance
with the methodology described in Sec. 484.325.
Performance period means the time period during which data are
collected for the purpose of calculating a competing HHA's performance
on measures.
Selected state(s) means those nine states that were randomly
selected to compete/participate in the HHVBP Model via a computer
algorithm designed for random selection and identified at Sec.
484.310(b).
Smaller-volume cohort means the group of competing home health
agencies within the boundaries of selected states that are exempt from
participation in HHCAHPs in accordance with Sec. 484.250.
Starter set means the quality measures selected for the first year
of this model.
Total Performance Score means the numeric score ranging from 0 to
100 awarded to each competing HHA based on its performance under the
HHVBP Model.
Value-based purchasing means measuring, reporting, and rewarding
excellence in health care delivery that takes into consideration
quality, efficiency, and alignment of incentives. Effective health care
services and high performing health care providers may be rewarded with
improved reputations through public reporting, enhanced payments
through differential reimbursements, and increased market share through
purchaser, payer, and/or consumer selection.
Sec. 484.310 Applicability of the Home Health Value-Based Purchasing
(HHVBP) Model.
(a) General rule. The HHVBP Model applies to all Medicare-certified
home health agencies (HHAs) in selected states.
(b) Selected states. Nine states have been selected in accordance
with CMS's selection methodology. All Medicare-certified HHAs that
provide services in Massachusetts, Maryland, North Carolina, Florida,
Washington, Arizona, Iowa, Nebraska, and Tennessee will be required to
compete in this model.
Sec. 484.315 Data reporting for measures and evaluation under the
Home Health Value-Based Purchasing (HHVBP) Model.
(a) Competing home health agencies will be evaluated using a
starter set of quality measures.
(b) Competing home health agencies in selected states will be
required to report information on New Measures, as determined
appropriate by the Secretary, to CMS in the form, manner, and at a time
specified by the Secretary.
(c) Competing home health agencies in selected states will be
required to collect and report such information as the Secretary
determines is necessary for purposes of monitoring and evaluating the
HHVBP Model under section 1115A(b)(4) of the Act (42 U.S.C. 1315a).
Sec. 484.320 Calculation of the Total Performance Score.
A competing home health agency's Total Performance Score for a
model year is calculated as follows:
(a) CMS will award points to the competing home health agency for
performance on each of the applicable measures in the starter set,
excluding the New Measures.
(b) CMS will award points to the competing home health agency for
reporting on each of the New Measures in the starter set, worth up to
ten percent of the Total Performance Score.
(c) CMS will sum all points awarded for each applicable measure
excluding the New Measures in the starter set, weighted equally at the
individual measure level, to calculate a value worth 90-percent of the
Total Performance Score.
[[Page 68719]]
(d) The sum of the points awarded to a competing HHA for each
applicable measure in the starter set and the points awarded to a
competing HHA for reporting data on each New Measure is the competing
HHA's Total Performance Score for the calendar year.
Sec. 484.325 Payments for home health services under Home Health
Value-Based Purchasing (HHVBP) Model.
CMS will determine a payment adjustment up to the maximum
applicable percentage, upward or downward, under the HHVBP Model for
each competing home health agency based on the agency's Total
Performance Score using a linear exchange function. Payment adjustments
made under the HHVBP Model will be calculated as a percentage of
otherwise-applicable payments for home health services provided under
section 1895 of the Act (42 U.S.C. 1395fff).
Sec. 484.330 Process for determining and applying the value-based
payment adjustment under the Home Health Value-Based Purchasing (HHVBP)
Model.
(a) General. Competing home health agencies will be ranked within
the larger-volume and smaller-volume cohorts in selected states based
on the performance standards that apply to the HHVBP Model for the
baseline year, and CMS will make value-based payment adjustments to the
competing HHAs as specified in this section.
(b) Calculation of the value-based payment adjustment amount. The
value-based payment adjustment amount is calculated by multiplying the
Home Health Prospective Payment final claim payment amount as
calculated in accordance with Sec. 484.205 by the payment adjustment
percentage.
(c) Calculation of the payment adjustment percentage. The payment
adjustment percentage is calculated as the product of: The applicable
percent as defined in Sec. 484.320, the competing HHA's Total
Performance Score divided by 100, and the linear exchange function
slope.
Dated: October 27, 2015.
Andrew M. Slavitt,
Acting Administrator, Centers for Medicare & Medicaid Services.
Dated: October 28, 2015.
Sylvia M. Burwell,
Secretary, Department of Health and Human Services.
[FR Doc. 2015-27931 Filed 10-29-15; 4:15 pm]
BILLING CODE 4120-01-P
